Search results for: signal classification

Authors: Yi-Hao Wong, Li-Li Chan, Chee-Onn Leong, Stephen Ambu, Joon-Wah Mak, Priyasashi Sahu

Abstract:

Background: Acanthamoeba is a genus of amoebae which lives as a free-living in nature or as a human pathogen that causes severe brain and eye infections. Virulence potential of Acanthamoeba is not constant and can change with growth conditions. DNA methylation, an epigenetic process which adds methyl groups to DNA, is used by eukaryotic cells, including several human parasites to control their gene expression. We used qPCR, siRNA gene silencing, and RNA sequencing (RNA-Seq) to study DNA-methyltransferase gene family (DNMT) in order to indicate the possibility of its involvement in programming Acanthamoeba virulence potential. Methods: A virulence-attenuated Acanthamoeba isolate (designation: ATCC; original isolate: ATCC 50492) was subjected to mouse passages to restore its pathogenicity; a virulence-reactivated isolate (designation: AC/5) was generated. Several established factors associated with Acanthamoeba virulence phenotype were examined to confirm the succession of reactivation process. Differential gene expression of DNMT between ATCC and AC/5 isolates was performed by qPCR. Silencing on DNMT gene expression in AC/5 isolate was achieved by siRNA duplex. Total RNAs extracted from ATCC, AC/5, and siRNA-treated (designation: si-146) were subjected to RNA-Seq for comparative transcriptomic analysis in order to identify the genome-wide effect of DNMT in regulating Acanthamoeba gene expression. qPCR was performed to validate the RNA-Seq results. Results: Physiological and cytophatic assays demonstrated an increased in virulence potential of AC/5 isolate after mouse passages. DNMT gene expression was significantly higher in AC/5 compared to ATCC isolate (p ≤ 0.01) by qPCR. si-146 duplex reduced DNMT gene expression in AC/5 isolate by 30%. Comparative transcriptome analysis identified the differentially expressed genes, with 3768 genes in AC/5 vs ATCC isolate; 2102 genes in si-146 vs AC/5 isolate and 3422 genes in si-146 vs ATCC isolate, respectively (fold-change of ≥ 2 or ≤ 0.5, p-value adjusted (padj) < 0.05). Of these, 840 and 1262 genes were upregulated and downregulated, respectively, in si-146 vs AC/5 isolate. Eukaryotic orthologous group (KOG) assignments revealed a higher percentage of downregulated gene expression in si-146 compared to AC/5 isolate, were related to posttranslational modification, signal transduction and energy production. Gene Ontology (GO) terms for those downregulated genes shown were associated with transport activity, oxidation-reduction process, and metabolic process. Among these downregulated genes were putative genes encoded for heat shock proteins, transporters, ubiquitin-related proteins, proteins for vesicular trafficking (small GTPases), and oxidoreductases. Functional analysis of similar predicted proteins had been described in other parasitic protozoa for their survival and pathogenicity. Decreased expression of these genes in si146-treated isolate may account in part for Acanthamoeba reduced pathogenicity. qPCR on 6 selected genes upregulated in AC/5 compared to ATCC isolate corroborated the RNA sequencing findings, indicating a good concordance between these two analyses. Conclusion: To the best of our knowledge, this study represents the first genome-wide analysis of DNA methylation and its effects on gene expression in Acanthamoeba spp. The present data indicate that DNA methylation has substantial effect on global gene expression, allowing further dissection of the genome-wide effects of DNA-methyltransferase gene in regulating Acanthamoeba pathogenicity.

Keywords: Acanthamoeba, DNA methylation, RNA sequencing, virulence

Procedia PDF Downloads 196

Authors: M. Doudi, M. H. Pazandeh, L. Rahimzadeh Torabi

Abstract:

Bedsores are pressure ulcers that occur on the skin or tissue due to being immobile and lying in bed for extended periods. Bedsores have the potential to progress into open ulcers, increasing the possibility of variety of bacterial infection. Acinetobacter baumannii, a pathogen of considerable clinical importance, exhibited a significant correlation with Bedsores (pressure ulcers) infections, thereby manifesting a wide spectrum of antibiotic resistance. The emergence of drug resistance has led researchers to focus on alternative methods, particularly phage therapy, for tackling bacterial infections. Phage therapy has emerged as a novel therapeutic approach to regulate the activity of these agents. The management of bacterial infections greatly benefits from the clinical utilization of bacteriophages as a valuable antimicrobial intervention. The primary objective of this investigation consisted of isolating and discerning potent bacteriophage capable of targeting multi drug-resistant (MDR) and extensively drug-resistant (XDR) bacteria obtained from pressure ulcers. In present study, analyzed and isolated A. baumannii strains obtained from a cohort of patients suffering from pressure ulcers at Taleghani Hospital in Ahvaz, Iran. An approach that included biochemical and molecular identification techniques was used to determine the taxonomic classification of bacterial isolates at the genus and species levels. The molecular identification process was facilitated by using the 16S rRNA gene in combination with universal primers 27 F, and 1492 R. Bacteriophage was obtained through the isolation process conducted on treatment plant sewage located in Isfahan, Iran. The main goal of this study was to evaluate different characteristics of phage, such as their appearance, range of hosts they can infect, how quickly they can enter a host, their stability at varying temperatures and pH levels, their effectiveness in killing bacteria, the growth pattern of a single phage stage, mapping of enzymatic digestion, and identification of proteomics patterns. The findings demonstrated that an examination was conducted on a sample of 50 specimens, wherein 15 instances of A. baumannii were identified. These microorganisms are the predominant Gram-negative agents known to cause wound infections in individuals suffering from bedsores. The study's findings indicated a high prevalence of antibiotic resistance in the strains isolated from pressure ulcers, excluding the clinical strains that exhibited responsiveness to colistin.According to the findings obtained from assessments of host range and morphological characteristics of bacteriophage VbɸAB-1, it can be concluded that this phage possesses specificity towards A. Baumannii BAH_Glau1001 was classified as a member of the Plasmaviridae family. The bacteriophage mentioned earlier showed the strongest antibacterial effect at a temperature of 18 °C and a pH of 6.5. Through the utilization of sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) analysis on protein fragments, it was established that the bacteriophage VbɸAB-1 exhibited a size range between 50 and 75 kilodaltons (KDa). The numerous research findings on the effectiveness of phages and the safety studies conducted suggest that the phages studied in this research can be considered as a practical solution and recommended approach for controlling and treating stubborn pathogens in burn wounds among hospitalized patients.

Keywords: acinetobacter baumannii, extremely drug- resistant, phage therapy, surgery wound

Procedia PDF Downloads 92

Authors: Jaco Oosthuizen, Nerina C. Van Der Merwe

Abstract:

The National Health Laboratory Services in Bloemfontien has been the diagnostic testing facility for 1830 patients for familial breast cancer since 1997. From the cohort, 540 were comprehensively screened using High-Resolution Melting Analysis or Next Generation Sequencing for the presence of point mutations and/or indels. Approximately 90% of these patients stil remain undiagnosed as they are BRCA1/2 negative. Multiplex ligation-dependent probe amplification was initially added to screen for copy number variation detection, but with the introduction of next generation sequencing in 2017, was substituted and is currently used as a confirmation assay. The aim was to investigate the viability of utilizing internationally designed copy number variation detection assays based on mostly European/Caucasian genomic data for use within a South African context. The multiplex ligation-dependent probe amplification technique is based on the hybridization and subsequent ligation of multiple probes to a targeted exon. The ligated probes are amplified using conventional polymerase chain reaction, followed by fragment analysis by means of capillary electrophoresis. The experimental design of the assay was performed according to the guidelines of MRC-Holland. For BRCA1 (P002-D1) and BRCA2 (P045-B3), both multiplex assays were validated, and results were confirmed using a secondary probe set for each gene. The next generation sequencing technique is based on target amplification via multiplex polymerase chain reaction, where after the amplicons are sequenced parallel on a semiconductor chip. Amplified read counts are visualized as relative copy numbers to determine the median of the absolute values of all pairwise differences. Various experimental parameters such as DNA quality, quantity, and signal intensity or read depth were verified using positive and negative patients previously tested internationally. DNA quality and quantity proved to be the critical factors during the verification of both assays. The quantity influenced the relative copy number frequency directly whereas the quality of the DNA and its salt concentration influenced denaturation consistency in both assays. Multiplex ligation-dependent probe amplification produced false positives due to ligation failure when ligation was inhibited due to a variant present within the ligation site. Next generation sequencing produced false positives due to read dropout when primer sequences did not meet optimal multiplex binding kinetics due to population variants in the primer binding site. The analytical sensitivity and specificity for the South African population have been proven. Verification resulted in repeatable reactions with regards to the detection of relative copy number differences. Both multiplex ligation-dependent probe amplification and next generation sequencing multiplex panels need to be optimized to accommodate South African polymorphisms present within the genetically diverse ethnic groups to reduce the false copy number variation positive rate and increase performance efficiency.

Keywords: familial breast cancer, multiplex ligation-dependent probe amplification, next generation sequencing, South Africa

Procedia PDF Downloads 231

Authors: Majdah Alnefaie

Abstract:

The ‘netnographic study’ and data mining have been used to monitor the public interaction on Social Media Sites (SMSs) to understand what the motivational factors influence the Saudi intentions regarding allowing women driving in Saudi Arabia in 2018. The netnographic study monitored the publics’ textual and visual communications in Twitter, Snapchat, and YouTube. SMSs users’ communications method is also known as electronic word of mouth (eWOM). Netnography methodology is still in its initial stages as it depends on manual extraction, reading and classification of SMSs users text. On the other hand, data mining is come from the computer and physical sciences background, therefore it is much harder to extract meaning from unstructured qualitative data. In addition, the new development in data mining software does not support the Arabic text, especially local slang in Saudi Arabia. Therefore, collaborations between social and computer scientists such as ‘netnographic study’ and data mining will enhance the efficiency of this study methodology leading to comprehensive research outcome. The eWOM communications between individuals on SMSs can promote a sense that sharing their preferences and experiences regarding politics and social government regulations is a part of their daily life, highlighting the importance of using SMSs as assistance in promoting participation in political and social. Therefore, public interactions on SMSs are important tools to comprehend people’s intentions regarding the new government regulations in the country. This study aims to answer this question, "What factors influence the Saudi Arabians' intentions of Saudi female's car-driving in 2018". The study utilized qualitative method known as netnographic study. The study used R studio to collect and analyses 27000 Saudi users’ comments from 25th May until 25th June 2018. The study has developed data collection model that support importing and analysing the Arabic text in the local slang. The data collection model in this study has been clustered based on different type of social networks, gender and the study main factors. The social network analysis was employed to collect comments from SMSs owned by governments’ originations, celebrities, vloggers, social activist and news SMSs accounts. The comments were collected from both males and females SMSs users. The sentiment analysis shows that the total number of positive comments Saudi females car driving was higher than negative comments. The data have provided the most important factors influenced the Saudi Arabians’ intention of Saudi females car driving including, culture and environment, freedom of choice, equal opportunities, security and safety. The most interesting finding indicted that women driving would play a role in increasing the individual freedom of choice. Saudi female will be able to drive cars to fulfill her daily life and family needs without being stressed due to the lack of transportation. The study outcome will help Saudi government to improve woman quality of life by increasing the ability to find more jobs and studies, increasing income through decreasing the spending on transport means such as taxi and having more freedom of choice in woman daily life needs. The study enhances the importance of using use marketing research to measure the public opinions on the new government regulations in the country. The study has explained the limitations and suggestions for future research.

Keywords: netnographic study, data mining, social media, Saudi Arabia, female driving

Procedia PDF Downloads 153

Authors: Irina Mizeva, Elena Potapova, Viktor Dremin, Mikhail Mezentsev, Valeri Shupletsov

Abstract:

The local tissue perfusion is regulated by the microvascular tone which is under the control of a number of physiological mechanisms. Laser Doppler flowmetry (LDF) together with wavelet analyses is the most commonly used technique to study the regulatory mechanisms of cutaneous microcirculation. External factors such as temperature, local pressure of the probe on the skin, etc. influence on the blood flow characteristics and are used as physiological tests to evaluate microvascular regulatory mechanisms. Local probe pressure influences on the microcirculation parameters measured by optical methods: diffuse reflectance spectroscopy, fluorescence spectroscopy, and LDF. Therefore, further study of probe pressure effects can be useful to improve the reliability of optical measurement. During pressure tests variation of the mean perfusion measured by means of LDF usually is estimated. An additional information concerning the physiological mechanisms of the vascular tone regulation system in response to local pressure can be obtained using spectral analyses of LDF samples. The aim of the present work was to develop protocol and algorithm of data processing appropriate for study physiological response to the local pressure test. Involving 6 subjects (20±2 years) and providing 5 measurements for every subject we estimated intersubject and-inter group variability of response of both averaged and oscillating parts of the LDF sample on external surface pressure. The final purpose of the work was to find special features which further can be used in wider clinic studies. The cutaneous perfusion measurements were carried out by LAKK-02 (SPE LAZMA Ltd., Russia), the skin loading was provided by the originally designed device which allows one to distribute the pressure around the LDF probe. The probe was installed on the dorsal part of the distal finger of the index figure. We collected measurements continuously for one hour and varied loading from 0 to 180mmHg stepwise with a step duration of 10 minutes. Further, we post-processed the samples using the wavelet transform and traced the energy of oscillations in five frequency bands over time. Weak loading leads to pressure-induced vasodilation, so one should take into account that the perfusion measured under pressure conditions will be overestimated. On the other hand, we revealed a decrease in endothelial associated fluctuations. Further loading (88 mmHg) induces amplification of pulsations in all frequency bands. We assume that such loading leads to a higher number of closed capillaries, higher input of arterioles in the LDF signal and as a consequence more vivid oscillations which mainly are formed in arterioles. External pressure higher than 144 mmHg leads to the decrease of oscillating components, after removing the loading very rapid restore of the tissue perfusion takes place. In this work, we have demonstrated that local skin loading influence on the microcirculation parameters measured by optic technique; this should be taken into account while developing portable electronic devices. The proposed protocol of local loading allows one to evaluate PIV as far as to trace dynamic of blood flow oscillations. This study was supported by the Russian Science Foundation under project N 18-15-00201.

Keywords: blood microcirculation, laser Doppler flowmetry, pressure-induced vasodilation, wavelet analyses blood

Procedia PDF Downloads 150

Authors: Philipp Wenger, Michael Beltle, Stefan Tenbohlen, Uwe Riechert

Abstract:

The integration of renewable energy introduces new challenges to the transmission grid, as the power generation is located far from load centers. The associated necessary long-range power transmission increases the demand for high voltage direct current (HVDC) transmission lines and DC distribution grids. HVDC gas-insulated switchgears (GIS) are considered being a key technology, due to the combination of the DC technology and the long operation experiences of AC-GIS. To ensure long-term reliability of such systems, insulation defects must be detected in an early stage. Operational experience with AC systems has proven evidence, that most failures, which can be attributed to breakdowns of the insulation system, can be detected and identified via partial discharge (PD) measurements beforehand. In AC systems the identification of defects relies on the phase resolved partial discharge pattern (PRPD). Since there is no phase information within DC systems this method cannot be transferred to DC PD diagnostic. Furthermore, the behaviour of e.g. free-moving particles differs significantly at DC: Under the influence of a constant direct electric field, charge carriers can accumulate on particles’ surfaces. As a result, a particle can lift-off, oscillate between the inner conductor and the enclosure or rapidly bounces at just one electrode, which is known as firefly motion. Depending on the motion and the relative position of the particle to the electrodes, broadband electromagnetic PD pulses are emitted, which can be recorded by ultra-high frequency (UHF) measuring methods. PDs are often accompanied by light emissions at the particle’s tip which enables optical detection. This contribution investigates PD characteristics of free moving metallic particles in a commercially available 300 kV SF6-insulated HVDC-GIS. The influences of various defect parameters on the particle motion and the PD characteristic are evaluated experimentally. Several particle geometries, such as cylinder, lamella, spiral and sphere with different length, diameter and weight are determined. The applied DC voltage is increased stepwise from inception voltage up to UDC = ± 400 kV. Different physical detection methods are used simultaneously in a time-synchronized setup. Firstly, the electromagnetic waves emitted by the particle are recorded by an UHF measuring system. Secondly, a photomultiplier tube (PMT) detects light emission with a wavelength in the range of λ = 185…870 nm. Thirdly, a high-speed camera (HSC) tracks the particle’s motion trajectory with high accuracy. Furthermore, an electrically insulated electrode is attached to the grounded enclosure and connected to a current shunt in order to detect low frequency ion currents: The shunt measuring system’s sensitivity is in the range of 10 nA at a measuring bandwidth of bw = DC…1 MHz. Currents of charge carriers, which are generated at the particle’s tip migrate through the gas gap to the electrode and can be recorded by the current shunt. All recorded PD signals are analyzed in order to identify characteristic properties of different particles. This includes e.g. repetition rates and amplitudes of successive pulses, characteristic frequency ranges and detected signal energy of single PD pulses. Concluding, an advanced understanding of underlying physical phenomena particle motion in direct electric field can be derived.

Keywords: current shunt, free moving particles, high-speed imaging, HVDC-GIS, UHF

Procedia PDF Downloads 160

Authors: Jawaad Saleem, Hannah Wright, Peter Sommerville, Adrian Hopper

Abstract:

Introduction: Inpatient falls are the most commonly reported patient safety incidents, and carry a significant burden on resources, morbidity, and mortality. Ensuring adequate post falls management of patients by staff is therefore paramount to maintaining patient safety especially in out of hours and resource stretched settings. Aims: This quality improvement project aims to improve the current practice of falls management at Guys St Thomas Hospital, London as compared to our 2016 Quality Improvement Project findings. Furthermore, it looks to increase current junior doctors confidence in managing falls and their use of new guidance protocols. Methods: Multifaceted Interventions implemented included: the development of new trust wide guidelines detailing management pathways for patients post falls, available for intranet access. Furthermore, the production of 2000 lanyard cards distributed amongst junior doctors and staff which summarised these guidelines. Additionally, a ‘safety signal’ email was sent from the Trust chief medical officer to all staff raising awareness of falls and the guidelines. Formal falls teaching was also implemented for new doctors at induction. Using an established incident database, 189 consecutive falls in 2017were retrospectively analysed electronically to assess and compared to the variables measured in 2016 post interventions. A separate serious incident database was used to analyse 50 falls from May 2015 to March 2018 to ascertain the statistical significance of the impact of our interventions on serious incidents. A similar questionnaire for the 2017 cohort of foundation year one (FY1) doctors was performed and compared to 2016 results. Results: Questionnaire data demonstrated improved awareness and utility of guidelines and increased confidence as well as an increase in training. 97% of FY1 trainees felt that the interventions had increased their awareness of the impact of falls on patients in the trust. Data from the incident database demonstrated the time to review patients post fall had decreased from an average of 130 to 86 minutes. Improvement was also demonstrated in the reduced time to order and schedule X-ray and CT imaging, 3 and 5 hours respectively. Data from the serious incident database show that ‘the time from fall until harm was detected’ was statistically significantly lower (P = 0.044) post intervention. We also showed the incidence of significant delays in detecting harm ( > 10 hours) reduced post intervention. Conclusions: Our interventions have helped to significantly reduce the average time to assess, order and schedule appropriate imaging post falls. Delays of over ten hours to detect serious injuries after falls were commonplace; since the intervention, their frequency has markedly reduced. We suggest this will lead to identifying patient harm sooner, reduced clinical incidents relating to falls and thus improve overall patient safety. Our interventions have also helped increase clinical staff confidence, management, and awareness of falls in the trust. Next steps include expanding teaching sessions, improving multidisciplinary team involvement to aid this improvement.

Keywords: patient safety, quality improvement, serious incidents, falls, clinical care

Procedia PDF Downloads 124

Authors: Damien Mouratille, Antonio R. Hidalgo-Muñoz, Nadine Matton, Yves Rouillard, Mickael Causse, Radouane El Yagoubi

Abstract:

Background: The monitoring of the physiological activity related to mental workload (MW) on pilots will be useful to improve aviation safety by anticipating human performance degradation. The electrocardiogram (ECG) can reveal MW fluctuations due to either cognitive workload or/and emotional state since this measure exhibits autonomic nervous system modulations. Arguably, heart rate (HR) is one of its most intuitive and reliable parameters. It would be particularly interesting to analyze the interaction between cognitive requirements and emotion in ecologic sets such as a flight simulator. This study aims to explore by means of HR the relation between cognitive demands and emotional activation. Presumably, the effects of cognition and emotion overloads are not necessarily cumulative. Methodology: Eight healthy volunteers in possession of the Private Pilot License were recruited (male; 20.8±3.2 years). ECG signal was recorded along the whole experiment by placing two electrodes on the clavicle and left pectoral of the participants. The HR was computed within 4 minutes segments. NASA-TLX and Big Five inventories were used to assess subjective workload and to consider the influence of individual personality differences. The experiment consisted in completing two dual-tasks of approximately 30 minutes of duration into a flight simulator AL50. Each dual-task required the simultaneous accomplishment of both a pre-established flight plan and an additional task based on target stimulus discrimination inserted between Air Traffic Control instructions. This secondary task allowed us to vary the cognitive workload from low (LC) to high (HC) levels, by combining auditory and visual numerical stimuli to respond to meeting specific criteria. Regarding emotional condition, the two dual-tasks were designed to assure analogous difficulty in terms of solicited cognitive demands. The former was realized by the pilot alone, i.e. Low Arousal (LA) condition. In contrast, the latter generates a high arousal (HA), since the pilot was supervised by two evaluators, filmed and involved into a mock competition with the rest of the participants. Results: Performance for the secondary task showed significant faster reaction times (RT) for HA compared to LA condition (p=.003). Moreover, faster RT was found for LC compared to HC (p < .001) condition. No interaction was found. Concerning HR measure, despite the lack of main effects an interaction between emotion and cognition is evidenced (p=.028). Post hoc analysis showed smaller HR for HA compared to LA condition only for LC (p=.049). Conclusion. The control of an aircraft is a very complex task including strong cognitive demands and depends on the emotional state of pilots. According to the behavioral data, the experimental set has permitted to generate satisfactorily different emotional and cognitive levels. As suggested by the interaction found in HR measure, these two factors do not seem to have a cumulative impact on the sympathetic nervous system. Apparently, low cognitive workload makes pilots more sensitive to emotional variations. These results hint the independency between data processing and emotional regulation. Further physiological data are necessary to confirm and disentangle this relation. This procedure may be useful for monitoring objectively pilot’s mental workload.

Keywords: cognitive demands, emotion, flight simulator, heart rate, mental workload

Procedia PDF Downloads 275

Authors: Laurence Weinberg, Dominic Walpole, Dong-Kyu Lee, Michael D’Silva, Jian W. Chan, Lachlan F. Miles, Bradley Carp, Adam Wells, Tuck S. Ngun, Siven Seevanayagam, George Matalanis, Ziauddin Ansari, Rinaldo Bellomo, Michael Yii

Abstract:

Background: There have been multiple recent advancements in the selection, optimization and management of cardiac surgical patients. However, there is limited data regarding the outcomes of nonagenarians undergoing cardiac surgery, despite this vulnerable cohort increasingly receiving these interventions. This study describes the patient characteristics, management and outcomes of a group of nonagenarians undergoing cardiac surgery in the context of contemporary peri-operative care. Methods: A retrospective observational study was conducted of patients 90 to 99 years of age (i.e., nonagenarians) who had undergone cardiac surgery requiring a classic median sternotomy (i.e., open-heart surgery). All operative indications were included. Patients who underwent minimally invasive surgery, transcatheter aortic valve implantation and thoracic aorta surgery were excluded. Data were collected from four hospitals in Victoria, Australia, over an 8-year period (January 2012 – December 2019). The primary objective was to assess six-month mortality in nonagenarians undergoing open-heart surgery and to evaluate the incidence and severity of postoperative complications using the Clavien-Dindo classification system. The secondary objective was to provide a detailed description of the characteristics and peri-operative management of this group. Results: A total of 12,358 adult patients underwent cardiac surgery at the study centers during the observation period, of whom 18 nonagenarians (0.15%) fulfilled the inclusion criteria. The median (IQR) [min-max] age was 91 years (90.0:91.8) [90-94] and 14 patients (78%) were men. Cardiovascular comorbidities, polypharmacy and frailty, were common. The median (IQR) predicted in-hospital mortality by EuroSCORE II was 6.1% (4.1-14.5). All patients were optimized preoperatively by a multidisciplinary team of surgeons, cardiologists, geriatricians and anesthetists. All index surgeries were performed on cardiopulmonary bypass. Isolated coronary artery bypass grafting (CABG) and CABG with aortic valve replacement were the most common surgeries being performed in four and five patients, respectively. Half the study group underwent surgery involving two or more major procedures (e.g. CABG and valve replacement). Surgery was undertaken emergently in 44% of patients. All patients except one experienced at least one postoperative complication. The most common complications were acute kidney injury (72%), new atrial fibrillation (44%) and delirium (39%). The highest Clavien-Dindo complication grade was IIIb occurring once each in three patients. Clavien-Dindo grade IIIa complications occurred in only one patient. The median (IQR) postoperative length of stay was 11.6 days (9.8:17.6). One patient was discharged home and all others to an inpatient rehabilitation facility. Three patients had an unplanned readmission within 30 days of discharge. All patients had follow-up to at least six months after surgery and mortality over this period was zero. The median (IQR) duration of follow-up was 11.3 months (6.0:26.4) and there were no cases of mortality observed within the available follow-up records. Conclusion: In this group of nonagenarians undergoing cardiac surgery, postoperative six-month mortality was zero. Complications were common but generally of low severity. These findings support carefully selected nonagenarian patients being offered cardiac surgery in the context of contemporary, multidisciplinary perioperative care. Further, studies are needed to assess longer-term mortality and functional and quality of life outcomes in this vulnerable surgical cohort.

Keywords: cardiac surgery, mortality, nonagenarians, postoperative complications

Procedia PDF Downloads 119

Authors: Shuo Li, Yannick Coffinier, Chann Lagadec, Fabrizio Cleri, Katsuhiko Nishiguchi, Akira Fujiwara, Soo Hyeon Kim, Nicolas Clément

Abstract:

The need for single cell detection and analysis techniques has increased in the past decades because of the heterogeneity of individual living cells, which increases the complexity of the pathogenesis of malignant tumors. In the search for early cancer detection, high-precision medicine and therapy, the technologies most used today for sensitive detection of target analytes and monitoring the variation of these species are mainly including two types. One is based on the identification of molecular differences at the single-cell level, such as flow cytometry, fluorescence-activated cell sorting, next generation proteomics, lipidomic studies, another is based on capturing or detecting single tumor cells from fresh or fixed primary tumors and metastatic tissues, and rare circulating tumors cells (CTCs) from blood or bone marrow, for example, dielectrophoresis technique, microfluidic based microposts chip, electrochemical (EC) approach. Compared to other methods, EC sensors have the merits of easy operation, high sensitivity, and portability. However, despite various demonstrations of low limits of detection (LOD), including aptamer sensors, arrayed EC sensors for detecting single-cell have not been demonstrated. In this work, a new technique based on 20-nm-thick nanopillars array to support cells and keep them at ideal recognition distance for redox-labeled aptamers grafted on the surface. The key advantages of this technology are not only to suppress the false positive signal arising from the pressure exerted by all (including non-target) cells pushing on the aptamers by downward force but also to stabilize the aptamer at the ideal hairpin configuration thanks to a confinement effect. With the first implementation of this technique, a LOD of 13 cells (with5.4 μL of cell suspension) was estimated. In further, the nanosupported cell technology using redox-labeled aptasensors has been pushed forward and fully integrated into a single-cell electrochemical aptasensor array. To reach this goal, the LOD has been reduced by more than one order of magnitude by suppressing parasitic capacitive electrochemical signals by minimizing the sensor area and localizing the cells. Statistical analysis at the single-cell level is demonstrated for the recognition of cancer cells. The future of this technology is discussed, and the potential for scaling over millions of electrodes, thus pushing further integration at sub-cellular level, is highlighted. Despite several demonstrations of electrochemical devices with LOD of 1 cell/mL, the implementation of single-cell bioelectrochemical sensor arrays has remained elusive due to their challenging implementation at a large scale. Here, the introduced nanopillar array technology combined with redox-labeled aptamers targeting epithelial cell adhesion molecule (EpCAM) is perfectly suited for such implementation. Combining nanopillar arrays with microwells determined for single cell trapping directly on the sensor surface, single target cells are successfully detected and analyzed. This first implementation of a single-cell electrochemical aptasensor array based on Brownian-fluctuating redox species opens new opportunities for large-scale implementation and statistical analysis of early cancer diagnosis and cancer therapy in clinical settings.

Keywords: bioelectrochemistry, aptasensors, single-cell, nanopillars

Procedia PDF Downloads 117

Authors: M. Doudi, M. H. Pazandeh, L. Rahimzadeh Torabi

Abstract:

Bedsores are pressure ulcers that occur on the skin or tissue due to being immobile and lying in bed for extended periods. Bedsores have the potential to progress into open ulcers, increasing the possibility of a variety of bacterial infections. Acinetobacter baumannii, a pathogen of considerable clinical importance, exhibited a significant correlation with Bedsores (pressure ulcers) infections, thereby manifesting a wide spectrum of antibiotic resistance. The emergence of drug resistance has led researchers to focus on alternative methods, particularly phage therapy, for tackling bacterial infections. Phage therapy has emerged as a novel therapeutic approach to regulate the activity of these agents. The management of bacterial infections greatly benefits from the clinical utilization of bacteriophages as a valuable antimicrobial intervention. The primary objective of this investigation consisted of isolating and discerning potent bacteriophage capable of targeting multi-drug-resistant (MDR) and extensively drug-resistant (XDR) bacteria obtained from pressure ulcers. The present study analyzed and isolated A. baumannii strains obtained from a cohort of patients suffering from pressure ulcers at Taleghani Hospital in Ahvaz, Iran. An approach that included biochemical and molecular identification techniques was used to determine the taxonomic classification of bacterial isolates at the genus and species levels. The molecular identification process was facilitated by using the 16S rRNA gene in combination with universal primers 27 F and 1492 R. Bacteriophage was obtained through the isolation process conducted on treatment plant sewage located in Isfahan, Iran. The main goal of this study was to evaluate different characteristics of phage, such as their appearance, the range of hosts they can infect, how quickly they can enter a host, their stability at varying temperatures and pH levels, their effectiveness in killing bacteria, the growth pattern of a single phage stage, mapping of enzymatic digestion, and identification of proteomics patterns. The findings demonstrated that an examination was conducted on a sample of 50 specimens, wherein 15 instances of A. baumannii were identified. These microorganisms are the predominant Gram-negative agents known to cause wound infections in individuals suffering from bedsores. The study's findings indicated a high prevalence of antibiotic resistance in the strains isolated from pressure ulcers, excluding the clinical strains that exhibited responsiveness to colistin. According to the findings obtained from assessments of host range and morphological characteristics of bacteriophage VbɸAB-1, it can be concluded that this phage possesses specificity towards A. Baumannii BAH_Glau1001 was classified as a member of the Podoviridae family. The bacteriophage mentioned earlier showed the strongest antibacterial effect at a temperature of 18 °C and a pH of 6.5. Through the utilization of sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) analysis on protein fragments, it was established that the bacteriophage VbɸAB-1 exhibited a size range between 50 and 75 kilodaltons (KDa). The numerous research findings on the effectiveness of phages and the safety studies conducted suggest that the phages studied in this research can be considered as a practical solution and recommended approach for controlling and treating stubborn pathogens in burn wounds among hospitalized patients. The findings of our research indicated that isolated phages could be an effective antimicrobial and an appreciate candidate for prophylaxis against pressure ulcers.

Keywords: acinetobacter baumannii, extremely drug-resistant, phage therapy, surgery wound

Procedia PDF Downloads 90

Authors: Dawid Jakimiuk, Krzysztof Mitura, Leszek Szpakowski, Sławomir Pilip, Daniel Celiński

Abstract:

The Emergency Medical Teams (EMS) of the Ambulance Service in Siedlce serve the population living in the Mazowieckie Voivodeship (the area of eastern Poland with approximately 550,000 inhabitants). They provide health services at the pre-hospital stage to all life-threatening patients. The analysis covered the interventions of emergency medical teams in cases of suicide attempts that occurred in the years 2015-2018. The study was retrospective. The data was obtained on the basis of digital medical records of completed call-outs. When defining the disease entity, the International Statistical Classification of Diseases and Health Problems ICD-10 prepared by WHO was used. The relationship between selected disease entities and the area of EMT intervention, the patient's sex and age, and the time of occurrence of the event were investigated. Non-urban area was defined as the area inhabited by a population below 10,000 residents. Statistical analysis was performed using Pearson's Chi ^ 2 test and presenting the percentage of cases in the study group. Of all the suicide attempts, drug abuse cases were the most frequent, including: X60 (Intentional self-poisoning by and exposure to nonopioid analgesics, antipyretics and antirheumatics); X61 (Intentional self-poisoning by and exposure to antiepileptic, sedative-hypnotic, antiparkinsonian and psychotropic drugs, not elsewhere classified); X62 (Intentional self-poisoning by and exposure to narcotics and psycholeptics [hallucinogens], not elsewhere classified); X63 (Intentional self-poisoning by and exposure to other drugs acting on the autonomic nervous system); X64 (Intentional self-poisoning by and exposure to other and unspecified drugs, medicaments and biological substance) oraz X70 (Intentional self-harm by hanging, strangulation and suffocation). In total, they accounted for 69.4% of all interventions to suicide attempts in the studied period. Statistical analysis shows significant differences (χ2 = 39.30239, p <0.0001, n = 561) between the area of EMT intervention and the type of suicide attempt. In non-urban areas, a higher percentage of X70 diagnoses was recorded (55.67%), while in urban areas, X60-X64 (72.53%). In non-urban areas, a higher proportion of patients attempting suicide was observed compared to patients living in urban areas. For X70 and X60 - X64 in total, the incidence rates in non-urban areas were 80.8% and 56%, respectively. Significant differences were found (χ2 = 119.3304, p <0.0001, n = 561) depending on the method of attempting suicide in relation to the patient's sex. The percentage of women diagnosed with X60-X64 versus X70 was 87.50%, which was the largest number of patients (n = 154) as compared to men. In the case of X70 in relation to X60-X64, the percentage of men was 62.08%, which was the largest number of patients (n = 239) as compared to women (n = 22). In the case of X70, the percentage of men compared to women was as high as 92%. Significant differences were observed (χ2 = 14.94848, p <0.01058) between the hour of EMT intervention and the type of suicide attempt. The highest percentage of X70 occurred between 04:01 - 08:00 (64.44%), while X60-X64 between 00:01 - 04:00 (70.45%). The largest number of cases of all tested suicide attempts was recorded between 16:01 - 20:00 for X70 (n = 62), X60 - X64 (n = 82), respectively. The highest percentage of patients undertaking all suicide attempts studied at work was observed in the age range of 18-30 (31.5%), while the lowest was in the age group over 60 years of age. (11%). There was no significant correlation between the day of the week or individual months of the year and the type of suicide attempt - respectively (χ2 = 6.281729, p <0.39238, n = 561) and (χ2 = 3.348913, p <0.9857, n = 561). There were also no significant differences in the incidence of suicide attempts for each year in the study period (χ2 = 3.348913, p <0.9857 n = 561). The obtained results suggest the necessity to undertake preventive measures in order to minimize the number of suicide attempts. Such activities should be directed especially at young patients living in non-urban areas.

Keywords: emergency med, emergency medical team, attempted suicide, pre-hospital

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Authors: Marco Frieslaar, Bing Chu, Eric Rogers

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Stroke is a devastating illness that is the second biggest cause of death in the world (after heart disease). Where it does not kill, it leaves survivors with debilitating sensory and physical impairments that not only seriously harm their quality of life, but also cause a high incidence of severe depression. It is widely accepted that early intervention is essential for recovery, but current rehabilitation techniques largely favor hospital-based therapies which have restricted access, expensive and specialist equipment and tend to side-step the emotional challenges. In addition, there is insufficient funding available to provide the long-term assistance that is required. As a consequence, recovery rates are poor. The relatively unexplored solution is to develop therapies that can be harnessed in the home and are formulated from technologies that already exist in everyday life. This would empower individuals to take control of their own improvement and provide choice in terms of when and where they feel best able to undertake their own healing. This research seeks to identify how effective post-stroke, rehabilitation therapy can be applied to upper limb mobility, within the physical context of a home rather than a hospital. This is being achieved through the design and construction of an automation scheme, based on iterative learning control and the Riener muscle model, that has the ability to adapt to the user and react to their level of fatigue and provide tangible physical recovery. It utilizes a SMART Phone and laptop to construct an iterative learning control (ILC) system, that monitors upper arm movement in three dimensions, as a series of exercises are undertaken. The equipment generates functional electrical stimulation to assist in muscle activation and thus improve directional accuracy. In addition, it monitors speed, accuracy, areas of motion weakness and similar parameters to create a performance index that can be compared over time and extrapolated to establish an independent and objective assessment scheme, plus an approximate estimation of predicted final outcome. To further extend its assessment capabilities, nerve conduction velocity readings are taken by the software, between the shoulder and hand muscles. This is utilized to measure the speed of response of neuron signal transfer along the arm and over time, an online indication of regeneration levels can be obtained. This will prove whether or not sufficient training intensity is being achieved even before perceivable movement dexterity is observed. The device also provides the option to connect to other users, via the internet, so that the patient can avoid feelings of isolation and can undertake movement exercises together with others in a similar position. This should create benefits not only for the encouragement of rehabilitation participation, but also an emotional support network potential. It is intended that this approach will extend the availability of stroke recovery options, enable ease of access at a low cost, reduce susceptibility to depression and through these endeavors, enhance the overall recovery success rate.

Keywords: home-based therapy, iterative learning control, Riener muscle model, SMART phone, stroke rehabilitation

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Authors: Anita Conti, Riccardo Ossanna, Lindsey A. Quintero, Giamaica Conti, Andrea Sbarbati

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Ischemia/reperfusion (IR) injury induces muscle fiber atrophy and skeletal muscle fiber death with subsequently functionality loss. The heterogeneous pool of cells, especially mesenchymal stem cells, contained in the stromal vascular fraction (SVF) of adipose tissue could promote muscle fiber regeneration. To prevent SVF dispersion, it has been proposed the use of injectable biopolymers that work as cells carrier. A significant element of the extracellular matrix is hyaluronic acid (HA), which has been widely used in regenerative medicine as a cell scaffold given its biocompatibility, degradability, and the possibility of chemical functionalization. Connective tissue micro-fragments enriched with SVF obtained from mechanical disaggregation of adipose tissue were evaluated for IR muscle injury regeneration using low molecular weight HA as a scaffold. IR induction. Hindlimb ischemia was induced in 9 athymic nude mice through the clamping of the right quadriceps using a plastic band. Reperfusion was induced by cutting the plastic band after 3 hours of ischemic period. Contralateral (left) muscular tissue was used as healthy control. Treatment. Twenty-four hours after the IR induction, animals (n=3) were intramuscularly injected with 100 µl of SVF mixed with HA (SVF-HA). Animals treated with 100 µl of HA (n=3) and 100 µl saline solution (n=3) were used as control. Treatment monitoring. All animals were in vivo monitored by magnetic resonance imaging (MRI) at 5, 7, 14 and 18 days post-injury (dpi). High-resolution morphological T2 weighed, quantitative T2 map and Dynamic Contrast-Enhanced (DCE) images were acquired in order to assess the regenerative potential of SVF-HA treatment. Ex vivo evaluation. After 18 days from IR induction, animals were sacrificed, and the muscles were harvested for histological examination. At 5 dpi T2 high-resolution MR images clearly reveal the presence of an extensive edematous area due to IR damage for all groups identifiable as an increase of signal intensity (SI) of muscular and surrounding tissue. At 7 dpi, animals of the SVF-HA group showed a reduction of SI, and the T2relaxation time of muscle tissue of the HA-SVF group was 29±0.5ms, comparable with the T2relaxation time of contralateral muscular tissue (30±0.7ms). These suggest a reduction of edematous overflow and swelling. The T2relaxation time at 7dpi of HA and saline groups were 84±2ms and 90±5ms, respectively, which remained elevated during the rest of the study. The evaluation of vascular regeneration showed similar results. Indeed, DCE-MRI analysis revealed a complete recovery of muscular tissue perfusion after 14 dpi for the SVF-HA group, while for the saline and HA group, controls remained in a damaged state. Finally, the histological examination of SVF-HA treated animals exhibited well-defined and organized fibers morphology with a lateralized nucleus, similar to contralateral healthy muscular tissue. On the contrary, HA and saline-treated animals presented inflammatory infiltrates, with HA slightly improving the diameter of the fibers and less degenerated tissue. Our findings show that connective tissue micro-fragments enriched with SVF induce higher muscle homeostasis and perfusion restoration in contrast to control groups.

Keywords: ischemia/reperfusion injury, regenerative medicine, resonance imaging, stromal vascular fraction

Procedia PDF Downloads 127

Authors: Mohamed Gazzeh, Bradley Null, Fethi Tlili, Hichem Besbes

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The burgeoning global ownership of personal vehicles has posed a significant strain on urban infrastructure, notably parking facilities, leading to traffic congestion and environmental concerns. Effective parking management systems (PMS) are indispensable for optimizing urban traffic flow and reducing emissions. The most commonly deployed systems nowadays rely on computer vision technology. This paper explores the integration of radar sensors and simulation in the context of smart parking management. We concentrate on radar sensors due to their versatility and utility in automotive applications, which extends to PMS. Additionally, radar sensors play a crucial role in driver assistance systems and autonomous vehicle development. However, the resource-intensive nature of radar data collection for algorithm development and testing necessitates innovative solutions. Simulation, particularly the monoDrive simulator, an internal development tool used by NI the Test and Measurement division of Emerson, offers a practical means to overcome this challenge. The primary objectives of this study encompass simulating radar sensors to generate a substantial dataset for algorithm development, testing, and, critically, assessing the transferability of models between simulated and real radar data. We focus on occupancy detection in parking as a practical use case, categorizing each parking space as vacant or occupied. The simulation approach using monoDrive enables algorithm validation and reliability assessment for virtual radar sensors. It meticulously designed various parking scenarios, involving manual measurements of parking spot coordinates, orientations, and the utilization of TI AWR1843 radar. To create a diverse dataset, we generated 4950 scenarios, comprising a total of 455,400 parking spots. This extensive dataset encompasses radar configuration details, ground truth occupancy information, radar detections, and associated object attributes such as range, azimuth, elevation, radar cross-section, and velocity data. The paper also addresses the intricacies and challenges of real-world radar data collection, highlighting the advantages of simulation in producing radar data for parking lot applications. We developed classification models based on Support Vector Machines (SVM) and Density-Based Spatial Clustering of Applications with Noise (DBSCAN), exclusively trained and evaluated on simulated data. Subsequently, we applied these models to real-world data, comparing their performance against the monoDrive dataset. The study demonstrates the feasibility of transferring models from a simulated environment to real-world applications, achieving an impressive accuracy score of 92% using only one radar sensor. This finding underscores the potential of radar sensors and simulation in the development of smart parking management systems, offering significant benefits for improving urban mobility and reducing environmental impact. The integration of radar sensors and simulation represents a promising avenue for enhancing smart parking management systems, addressing the challenges posed by the exponential growth in personal vehicle ownership. This research contributes valuable insights into the practicality of using simulated radar data in real-world applications and underscores the role of radar technology in advancing urban sustainability.

Keywords: autonomous vehicle simulator, FMCW radar sensors, occupancy detection, smart parking management, transferability of models

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Authors: Sam Weber, Deepak Mishra, Susan Wilde, Elizabeth Kramer

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The frequency and severity of cyanobacteria harmful blooms (CyanoHABs) have been increasing over time, with point and non-point source eutrophication and shifting climate paradigms being blamed as the primary culprits. Excessive nutrients, warm temperatures, quiescent water, and heavy and less regular rainfall create more conducive environments for CyanoHABs. CyanoHABs have the potential to produce a spectrum of toxins that cause gastrointestinal stress, organ failure, and even death in humans and animals. To promote enhanced, proactive CyanoHAB management, risk modeling using geospatial tools can act as predictive mechanisms to supplement current CyanoHAB monitoring, management and mitigation efforts. The risk maps would empower water managers to focus their efforts on high risk water bodies in an attempt to prevent CyanoHABs before they occur, and/or more diligently observe those waterbodies. For this research, exploratory spatial data analysis techniques were used to identify the strongest predicators for CyanoHAB blooms based on remote sensing-derived cyanobacteria cell density values for 771 waterbodies in the Georgia Piedmont and landscape characteristics of their watersheds. In-situ datasets for cyanobacteria cell density, nutrients, temperature, and rainfall patterns are not widely available, so free gridded geospatial datasets were used as proxy variables for assessing CyanoHAB risk. For example, the percent of a watershed that is agriculture was used as a proxy for nutrient loading, and the summer precipitation within a watershed was used as a proxy for water quiescence. Cyanobacteria cell density values were calculated using atmospherically corrected images from the European Space Agency’s Sentinel-2A satellite and multispectral instrument sensor at a 10-meter ground resolution. Seventeen explanatory variables were calculated for each watershed utilizing the multi-petabyte geospatial catalogs available within the Google Earth Engine cloud computing interface. The seventeen variables were then used in a multiple linear regression model, and the strongest predictors of cyanobacteria cell density were selected for the final regression model. The seventeen explanatory variables included land cover composition, winter and summer temperature and precipitation data, topographic derivatives, vegetation index anomalies, and soil characteristics. Watershed maximum summer temperature, percent agriculture, percent forest, percent impervious, and waterbody area emerged as the strongest predictors of cyanobacteria cell density with an adjusted R-squared value of 0.31 and a p-value ~ 0. The final regression equation was used to make a normalized cyanobacteria cell density index, and a Jenks Natural Break classification was used to assign waterbodies designations of low, medium, or high risk. Of the 771 waterbodies, 24.38% were low risk, 37.35% were medium risk, and 38.26% were high risk. This study showed that there are significant relationships between free geospatial datasets representing summer maximum temperatures, nutrient loading associated with land use and land cover, and the area of a waterbody with cyanobacteria cell density. This data analytics approach to CyanoHAB risk assessment corroborated the literature-established environmental triggers for CyanoHABs, and presents a novel approach for CyanoHAB risk mapping in waterbodies across the greater southeastern United States.

Keywords: cyanobacteria, land use/land cover, remote sensing, risk mapping

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Authors: Judy M. Obliosca, Olivia Vest, Sandra Poulos, Kelsi Smith, Tammy Ferguson, Abigail Powers Lott, Alicia K. Smith, Yang Xu, Christopher K. Tison

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Post-Traumatic Stress Disorder (PTSD) is a mental health problem that people may develop after experiencing traumatic events such as combat, natural disasters, and major emotional challenges. Tragically, the number of military personnel with PTSD correlates directly with the number of veterans who attempt suicide, with the highest rate in the Army. Research has shown epigenetic risks in those who are prone to several psychiatric dysfunctions, particularly PTSD. Once initiated in response to trauma, epigenetic alterations in particular, the DNA methylation in the form of 5-methylcytosine (5mC) alters chromatin structure and represses gene expression. Current methods to detect DNA methylation, such as bisulfite-based genomic sequencing techniques, are laborious and have massive analysis workflow while still having high error rates. A faster and simpler detection method of high sensitivity and precision would be useful in a clinical setting to confirm potential PTSD etiologies, prevent other psychiatric disorders, and improve military health. A nano-enhanced Surface Plasmon Resonance imaging (SPRi)-based assay that simultaneously detects site-specific 5mC base (termed as PTSD base) in methylated genes related to PTSD is being developed. The arrays on a sensing chip were first constructed for parallel detection of PTSD bases using synthetic and genomic DNA (gDNA) samples. For the gDNA sample extracted from the whole blood of a PTSD patient, the sample was first digested using specific restriction enzymes, and fragments were denatured to obtain single-stranded methylated target genes (ssDNA). The resulting mixture of ssDNA was then injected into the assay platform, where targets were captured by specific DNA aptamer probes previously immobilized on the surface of a sensing chip. The PTSD bases in targets were detected by anti-5-methylcytosine antibody (anti-5mC), and the resulting signals were then enhanced by the universal nanoenhancer. Preliminary results showed successful detection of a PTSD base in a gDNA sample. Brighter spot images and higher delta values (control-subtracted reflectivity signal) relative to those of the control were observed. We also implemented the in-house surface activation system for detection and developed SPRi disposable chips. Multiplexed PTSD base detection of target methylated genes in blood DNA from PTSD patients of severity conditions (asymptomatic and severe) was conducted. This diagnostic capability being developed is a platform technology, and upon successful implementation for PTSD, it could be reconfigured for the study of a wide variety of neurological disorders such as traumatic brain injury, Alzheimer’s disease, schizophrenia, and Huntington's disease and can be extended to the analyses of other sample matrices such as urine and saliva.

Keywords: epigenetic assay, DNA methylation, PTSD, whole blood, multiplexing

Procedia PDF Downloads 123

Authors: Federica Verna, Alessandra Pautasso, Maria Caramelli, Cristiana Maurella, Walter Mignone, Cristina Casalone

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Mosquito-Borne Diseases (MBDs) are dangerously increasing in prevalence, geographical distribution and severity, representing an emerging threat for both humans and animals. Interaction between multiple disciplines is needed for an effective early warning, surveillance and control of MBDs, according to the One Health concept. This work reports the integrated surveillance system enforced by IZSPLV in Piedmont, Liguria and Valle d’Aosta regions (Northwestern Italy) in order to control MDBs spread. Veterinary services and local human health authority are involved in an information network, to connect the surveillance of human clinical cases with entomological surveillance and veterinary monitoring in order to implement control measures in case of outbreak. A systematic entomological surveillance is carried out during the vector season using mosquitoes traps located in sites selected according to risk factors. Collected mosquitoes are counted, identified to species level by morphological standard classification keys and pooled by collection site, date and species with a maximum of 100 individuals. Pools are analyzed, after RNA extraction, by Real Time RT-PCR distinctive for West Nile Virus (WNV) Lineage 1 and Lineage 2, Real Time RT-PCR USUTU virus (USUV) and a traditional flavivirus End-point RT-PCR. Positive pools are sequenced and the related sequences employed to perform a basic local alignment search tool (BLAST) in the GenBank library. Positive samples are sent to the National Reference Centre for Animal Exotic Diseases (CESME, Teramo) for confirmation. With particular reference to WNV, after the confirmation, as provided by national legislation, control measures involving both local veterinary and human health services are activated: equine sera are randomly sampled within a 4 km radius from the positive collection sites and tested with ELISA kit and WNV NAT screening of blood donors is introduced. This surveillance network allowed to detect since 2011 USUV circulation in this area of Italy. WNV was detected in Piedmont and Liguria for the first time in 2014 in mosquitoes. During the 2015 vector season, we observed the expansion of its activity in Piedmont. The virus was detected in almost all Provinces both in mosquitoes (6 pools) and animals (19 equine sera, 4 birds). No blood bag tested resulted infected. The first neuroinvasive human case occurred too. Competent authorities should be aware of a potentially increased risk of MBDs activity during the 2016 vector season. This work shows that this surveillance network allowed to early detect the presence of MBDs in humans and animals, and provided useful information to public authorities, in order to apply control measures. Finally, an additional value of our diagnostic protocol is the ability to detect all viruses belonging to the Flaviviridae family, considering the emergence caused by other Flaviviruses in humans such as the recent Zika virus infection in South America. Italy has climatic and environmental features conducive to Zika virus transmission, the competent vector and many travellers from Brazil reported every year.

Keywords: integrated surveillance, mosquito borne disease, West Nile virus, Zika virus

Procedia PDF Downloads 361

Authors: Thanthrige Thiunuwan Priyathilaka, Don Anushka Sandaruwan Elvitigala, Bong-Soo Lim, Hyung-Bok Jeong, Jehee Lee

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Toll like receptors (TLRs) are a phylogeneticaly conserved family of pattern recognition receptors, which participates in the host immune responses against various pathogens and pathogen derived mitogen. TLR21, a non-mammalian type, is almost restricted to the fish species even though those can be identified rarely in avians and amphibians. Herein, this study was carried out to identify and characterize TLR21 from rock bream (Oplegnathus fasciatus) designated as RbTLR21, at transcriptional and genomic level. In this study, the full length cDNA and genomic sequence of RbTLR21 was identified using previously constructed cDNA sequence database and BAC library, respectively. Identified RbTLR21 sequence was characterized using several bioinformatics tools. The quantitative real time PCR (qPCR) experiment was conducted to determine tissue specific expressional distribution of RbTLR21. Further, transcriptional modulation of RbTLR21 upon the stimulation with Streptococcus iniae (S. iniae), rock bream iridovirus (RBIV) and Edwardsiella tarda (E. tarda) was analyzed in spleen tissues. The complete coding sequence of RbTLR21 was 2919 bp in length which can encode a protein consisting of 973 amino acid residues with molecular mass of 112 kDa and theoretical isoelectric point of 8.6. The anticipated protein sequence resembled a typical TLR domain architecture including C-terminal ectodomain with 16 leucine rich repeats, a transmembrane domain, cytoplasmic TIR domain and signal peptide with 23 amino acid residues. Moreover, protein folding pattern prediction of RbTLR21 exhibited well-structured and folded ectodomain, transmembrane domain and cytoplasmc TIR domain. According to the pair wise sequence analysis data, RbTLR21 showed closest homology with orange-spotted grouper (Epinephelus coioides) TLR21with 76.9% amino acid identity. Furthermore, our phylogenetic analysis revealed that RbTLR21 shows a close evolutionary relationship with its ortholog from Danio rerio. Genomic structure of RbTLR21 consisted of single exon similar to its ortholog of zebra fish. Sevaral putative transcription factor binding sites were also identified in 5ʹ flanking region of RbTLR21. The RBTLR 21 was ubiquitously expressed in all the tissues we tested. Relatively, high expression levels were found in spleen, liver and blood tissues. Upon induction with rock bream iridovirus, RbTLR21 expression was upregulated at the early phase of post induction period even though RbTLR21 expression level was fluctuated at the latter phase of post induction period. Post Edwardsiella tarda injection, RbTLR transcripts were upregulated throughout the experiment. Similarly, Streptococcus iniae induction exhibited significant upregulations of RbTLR21 mRNA expression in the spleen tissues. Collectively, our findings suggest that RbTLR21 is indeed a homolog of TLR21 family members and RbTLR21 may be involved in host immune responses against bacterial and DNA viral infections.

Keywords: rock bream, toll like receptor 21 (TLR21), pattern recognition receptor, genomic characterization

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Authors: Vishal Kumar, Soumitra Satapathi

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Föster Resonance Energy Transfer (FRET) is a powerful technique used to probe close-range molecular interactions. Physically, the FRET phenomenon manifests as a dipole–dipole interaction between closely juxtaposed fluorescent molecules (10–100 Å). Our effort is to employ this FRET technique to make a prototype device for highly sensitive detection of environment pollutant. Among the most common environmental pollutants, nitroaromatic compounds (NACs) are of particular interest because of their durability and toxicity. That’s why, sensitive and selective detection of small amounts of nitroaromatic explosives, in particular, 2,4,6-trinitrophenol (TNP), 2,4-dinitrotoluene (DNT) and 2,4,6-trinitrotoluene (TNT) has been a critical challenge due to the increasing threat of explosive-based terrorism and the need of environmental monitoring of drinking and waste water. In addition, the excessive utilization of TNP in several other areas such as burn ointment, pesticides, glass and the leather industry resulted in environmental accumulation, and is eventually contaminating the soil and aquatic systems. To the date, high number of elegant methods, including fluorimetry, gas chromatography, mass, ion-mobility and Raman spectrometry have been successfully applied for explosive detection. Among these efforts, fluorescence-quenching methods based on the mechanism of FRET show good assembly flexibility, high selectivity and sensitivity. Here, we report a FRET-based sensor system for the highly selective detection of NACs, such as TNP, DNT and TNT. The sensor system is composed of a copolymer Poly [(N,N-dimethylacrylamide)-co-(Boc-Trp-EMA)] (RP) bearing tryptophan derivative in the side chain as donor and dansyl tagged copolymer P(MMA-co-Dansyl-Ala-HEMA) (DCP) as an acceptor. Initially, the inherent fluorescence of RP copolymer is quenched by non-radiative energy transfer to DCP which only happens once the two molecules are within Förster critical distance (R0). The excellent spectral overlap (Jλ= 6.08×10¹⁴ nm⁴M⁻¹cm⁻¹) between donors’ (RP) emission profile and acceptors’ (DCP) absorption profile makes them an exciting and efficient FRET pair i.e. further confirmed by the high rate of energy transfer from RP to DCP i.e. 0.87 ns⁻¹ and lifetime measurement by time correlated single photon counting (TCSPC) to validate the 64% FRET efficiency. This FRET pair exhibited a specific fluorescence response to NACs such as DNT, TNT and TNP with 5.4, 2.3 and 0.4 µM LODs, respectively. The detection of NACs occurs with high sensitivity by photoluminescence quenching of FRET signal induced by photo-induced electron transfer (PET) from electron-rich FRET pair to electron-deficient NAC molecules. The estimated stern-volmer constant (KSV) values for DNT, TNT and TNP are 6.9 × 10³, 7.0 × 10³ and 1.6 × 104 M⁻¹, respectively. The mechanistic details of molecular interactions are established by time-resolved fluorescence, steady-state fluorescence and absorption spectroscopy confirmed that the sensing process is of mixed type, i.e. both dynamic and static quenching as lifetime of FRET system (0.73 ns) is reduced to 0.55, 0.57 and 0.61 ns DNT, TNT and TNP, respectively. In summary, the simplicity and sensitivity of this novel FRET sensor opens up the possibility of designing optical sensor of various NACs in one single platform for developing multimodal sensor for environmental monitoring and future field based study.

Keywords: FRET, nitroaromatic, stern-Volmer constant, tryptophan and dansyl tagged copolymer

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Authors: Pei Yi Lin

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Objective: The objective of this study is to use machine learning methods to build an early prediction classifier model for acute delirium to improve the quality of medical care for intensive care patients. Background: Delirium is a common acute and sudden disturbance of consciousness in critically ill patients. After the occurrence, it is easy to prolong the length of hospital stay and increase medical costs and mortality. In 2021, the incidence of delirium in the intensive care unit of internal medicine was as high as 59.78%, which indirectly prolonged the average length of hospital stay by 8.28 days, and the mortality rate is about 2.22% in the past three years. Therefore, it is expected to build a delirium prediction classifier through big data analysis and machine learning methods to detect delirium early. Method: This study is a retrospective study, using the artificial intelligence big data database to extract the characteristic factors related to delirium in intensive care unit patients and let the machine learn. The study included patients aged over 20 years old who were admitted to the intensive care unit between May 1, 2022, and December 31, 2022, excluding GCS assessment <4 points, admission to ICU for less than 24 hours, and CAM-ICU evaluation. The CAMICU delirium assessment results every 8 hours within 30 days of hospitalization are regarded as an event, and the cumulative data from ICU admission to the prediction time point are extracted to predict the possibility of delirium occurring in the next 8 hours, and collect a total of 63,754 research case data, extract 12 feature selections to train the model, including age, sex, average ICU stay hours, visual and auditory abnormalities, RASS assessment score, APACHE-II Score score, number of invasive catheters indwelling, restraint and sedative and hypnotic drugs. Through feature data cleaning, processing and KNN interpolation method supplementation, a total of 54595 research case events were extracted to provide machine learning model analysis, using the research events from May 01 to November 30, 2022, as the model training data, 80% of which is the training set for model training, and 20% for the internal verification of the verification set, and then from December 01 to December 2022 The CU research event on the 31st is an external verification set data, and finally the model inference and performance evaluation are performed, and then the model has trained again by adjusting the model parameters. Results: In this study, XG Boost, Random Forest, Logistic Regression, and Decision Tree were used to analyze and compare four machine learning models. The average accuracy rate of internal verification was highest in Random Forest (AUC=0.86), and the average accuracy rate of external verification was in Random Forest and XG Boost was the highest, AUC was 0.86, and the average accuracy of cross-validation was the highest in Random Forest (ACC=0.77). Conclusion: Clinically, medical staff usually conduct CAM-ICU assessments at the bedside of critically ill patients in clinical practice, but there is a lack of machine learning classification methods to assist ICU patients in real-time assessment, resulting in the inability to provide more objective and continuous monitoring data to assist Clinical staff can more accurately identify and predict the occurrence of delirium in patients. It is hoped that the development and construction of predictive models through machine learning can predict delirium early and immediately, make clinical decisions at the best time, and cooperate with PADIS delirium care measures to provide individualized non-drug interventional care measures to maintain patient safety, and then Improve the quality of care.

Keywords: critically ill patients, machine learning methods, delirium prediction, classifier model

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Authors: Kaleem Kashif, Tayyaba Anam, Yizhi Wu

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This paper introduces a methodology for advancing Italian speech vowels landmark detection within the distinctive feature-based speech recognition domain. Leveraging the legacy tool 'xkl' by integrating combined convolutional neural networks (CNNs) and recurrent neural networks (RNNs), the study presents a comprehensive enhancement to the 'xkl' legacy software. This integration incorporates re-assigned spectrogram methodologies, enabling meticulous acoustic analysis. Simultaneously, our proposed model, integrating combined CNNs and RNNs, demonstrates unprecedented precision and robustness in landmark detection. The augmentation of re-assigned spectrogram fusion within the 'xkl' software signifies a meticulous advancement, particularly enhancing precision related to vowel formant estimation. This augmentation catalyzes unparalleled accuracy in landmark detection, resulting in a substantial performance leap compared to conventional methods. The proposed model emerges as a state-of-the-art solution in the distinctive feature-based speech recognition systems domain. In the realm of deep learning, a synergistic integration of combined CNNs and RNNs is introduced, endowed with specialized temporal embeddings, harnessing self-attention mechanisms, and positional embeddings. The proposed model allows it to excel in capturing intricate dependencies within Italian speech vowels, rendering it highly adaptable and sophisticated in the distinctive feature domain. Furthermore, our advanced temporal modeling approach employs Bayesian temporal encoding, refining the measurement of inter-landmark intervals. Comparative analysis against state-of-the-art models reveals a substantial improvement in accuracy, highlighting the robustness and efficacy of the proposed methodology. Upon rigorous testing on a database (LaMIT) speech recorded in a silent room by four Italian native speakers, the landmark detector demonstrates exceptional performance, achieving a 95% true detection rate and a 10% false detection rate. A majority of missed landmarks were observed in proximity to reduced vowels. These promising results underscore the robust identifiability of landmarks within the speech waveform, establishing the feasibility of employing a landmark detector as a front end in a speech recognition system. The synergistic integration of re-assigned spectrogram fusion, CNNs, RNNs, and Bayesian temporal encoding not only signifies a significant advancement in Italian speech vowels landmark detection but also positions the proposed model as a leader in the field. The model offers distinct advantages, including unparalleled accuracy, adaptability, and sophistication, marking a milestone in the intersection of deep learning and distinctive feature-based speech recognition. This work contributes to the broader scientific community by presenting a methodologically rigorous framework for enhancing landmark detection accuracy in Italian speech vowels. The integration of cutting-edge techniques establishes a foundation for future advancements in speech signal processing, emphasizing the potential of the proposed model in practical applications across various domains requiring robust speech recognition systems.

Keywords: landmark detection, acoustic analysis, convolutional neural network, recurrent neural network

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Authors: Adriana Muñoz-Talavera, Ana Rosa Rincón-Sánchez, Abraham Escobedo-Moratilla, María Cristina Islas-Carbajal, Miguel Ángel Gómez-Lim

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The highest rates of diabetes incidence and prevalence worldwide will increase the number of diabetic patients requiring insulin or insulin analogues. Then, current production systems would not be sufficient to meet the future market demands. Therefore, developing efficient expression systems for insulin and insulin analogues are needed. In addition, insulin analogues with better pharmacokinetics and pharmacodynamics properties and without mitogenic potential will be required. SCI-57 (single chain insulin-57) is an insulin analogue having 10 times greater affinity to the insulin receptor, higher resistance to thermal degradation than insulin, native mitogenicity and biological effect. Plants as expression platforms have been used to produce recombinant proteins because of their advantages such as cost-effectiveness, posttranslational modifications, absence of human pathogens and high quality. Immunoglobulin production with a yield of 50% has been achieved by transient expression in Nicotiana benthamiana (Nb). The aim of this study is to produce SCI-57 by transient expression in Nb. Methodology: DNA sequence encoding SCI-57 was cloned in pICH31070. This construction was introduced into Agrobacterium tumefaciens by electroporation. The resulting strain was used to infiltrate leaves of Nb. In order to isolate SCI-57, leaves from transformed plants were incubated 3 hours with the extraction buffer therefore filtrated to remove solid material. The resultant protein solution was subjected to anion exchange chromatography on an FPLC system and ultrafiltration to purify SCI-57. Detection of SCI-57 was made by electrophoresis pattern (SDS-PAGE). Protein band was digested with trypsin and the peptides were analyzed by Liquid chromatography tandem-mass spectrometry (LC-MS/MS). A purified protein sample (20µM) was analyzed by ESI-Q-TOF-MS to obtain the ionization pattern and the exact molecular weight determination. Chromatography pattern and impurities detection were performed using RP-HPLC using recombinant insulin as standard. The identity of the SCI-57 was confirmed by anti-insulin ELISA. The total soluble protein concentration was quantified by Bradford assay. Results: The expression cassette was verified by restriction mapping (5393 bp fragment). The SDS-PAGE of crude leaf extract (CLE) of transformed plants, revealed a protein of about 6.4 kDa, non-present in CLE of untransformed plants. The LC-MS/MS results displayed one peptide with a high score that matches SCI-57 amino acid sequence in the sample, confirming the identity of SCI-57. From the purified SCI-57 sample (PSCI-57) the most intense charge state was 1069 m/z (+6) on the displayed ionization pattern corresponding to the molecular weight of SCI-57 (6412.6554 Da). The RP-HPLC of the PSCI-57 shows the presence of a peak with similar retention time (rt) and UV spectroscopic profile to the insulin standard (SCI-57 rt=12.96 and insulin rt=12.70 min). The collected SCI-57 peak had ELISA signal. The total protein amount in CLE from transformed plants was higher compared to untransformed plants. Conclusions: Our results suggest the feasibility to produce insulin analogue SCI-57 by transient expression in Nicotiana benthamiana. Further work is being undertaken to evaluate the biological activity by glucose uptake by insulin-sensitive and insulin-resistant murine and human cultured adipocytes.

Keywords: insulin analogue, mass spectrometry, Nicotiana benthamiana, transient expression

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Authors: Wonil Nam, Xiang Ren, Inyoung Kim, Masoud Agah, Wei Zhou

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Despite its ultrasensitive detection capability, surface-enhanced Raman spectroscopy (SERS) faces challenges as a quantitative biochemical analysis tool due to the significant dependence of local field intensity in hotspots on nanoscale geometric variations of plasmonic nanostructures. Therefore, despite enormous progress in plasmonic nanoengineering of high-performance SERS devices, it is still challenging to quantitatively correlate the measured SERS signals with the actual molecule concentrations at hotspots. A significant effort has been devoted to developing SERS calibration methods by introducing internal standards. It has been achieved by placing Raman tags at plasmonic hotspots. Raman tags undergo similar SERS enhancement at the same hotspots, and ratiometric SERS signals for analytes of interest can be generated with reduced dependence on geometrical variations. However, using Raman tags still faces challenges for real-world applications, including spatial competition between the analyte and tags in hotspots, spectral interference, laser-induced degradation/desorption due to plasmon-enhanced photochemical/photothermal effects. We show that electronic Raman scattering (ERS) signals from metallic nanostructures at hotspots can serve as the internal calibration standard to enable quantitative SERS analysis and improve biostatistical analysis. We perform SERS with Au-SiO₂ multilayered metal-insulator-metal nano laminated plasmonic nanostructures. Since the ERS signal is proportional to the volume density of electron-hole occupation in hotspots, the ERS signals exponentially increase when the wavenumber is approaching the zero value. By a long-pass filter, generally used in backscattered SERS configurations, to chop the ERS background continuum, we can observe an ERS pseudo-peak, IERS. Both ERS and SERS processes experience the |E|⁴ local enhancements during the excitation and inelastic scattering transitions. We calibrated IMRS of 10 μM Rhodamine 6G in solution by IERS. The results show that ERS calibration generates a new analytical value, ISERS/IERS, insensitive to variations from different hotspots and thus can quantitatively reflect the molecular concentration information. Given the calibration capability of ERS signals, we performed label-free SERS analysis of living biological systems using four different breast normal and cancer cell lines cultured on nano-laminated SERS devices. 2D Raman mapping over 100 μm × 100 μm, containing several cells, was conducted. The SERS spectra were subsequently analyzed by multivariate analysis using partial least square discriminant analysis. Remarkably, after ERS calibration, MCF-10A and MCF-7 cells are further separated while the two triple-negative breast cancer cells (MDA-MB-231 and HCC-1806) are more overlapped, in good agreement with the well-known cancer categorization regarding the degree of malignancy. To assess the strength of ERS calibration, we further carried out a drug efficacy study using MDA-MB-231 and different concentrations of anti-cancer drug paclitaxel (PTX). After ERS calibration, we can more clearly segregate the control/low-dosage groups (0 and 1.5 nM), the middle-dosage group (5 nM), and the group treated with half-maximal inhibitory concentration (IC50, 15 nM). Therefore, we envision that ERS calibrated SERS can find crucial opportunities in label-free molecular profiling of complicated biological systems.

Keywords: cancer cell drug efficacy, plasmonics, surface-enhanced Raman spectroscopy (SERS), SERS calibration

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Authors: Meena Agrawal, Chaitanya P. Agrawal

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The power systems are transforming and becoming smarter with innovations in technologies to enable embark simultaneously upon the sustainable energy needs, rising environmental concerns, economic benefits and quality requirements. The advantages provided by inter-connection of renewable energy resources are becoming more viable and dependable with the smart controlling technologies. The limitation of most renewable resources have their diversity and intermittency causing problems in power quality, grid stability, reliability, security etc. is being cured by these efforts. A necessitate of optimal energy management by intelligent Micro-Grids at the distribution end of the power system has been accredited to accommodate sustainable renewable Distributed Energy Resources on large scale across the power grid. All over the world Smart Grids are emerging now as foremost concern infrastructure upgrade programs. The hardware setup includes NI cRIO 9022, Compact Reconfigurable Input Output microcontroller board connected to the PC on a LAN router with three hardware modules. The Real-Time Embedded Controller is reconfigurable controller device consisting of an embedded real-time processor controller for communication and processing, a reconfigurable chassis housing the user-programmable FPGA, Eight hot-swappable I/O modules, and graphical LabVIEW system design software. It has been employed for signal analysis, controls and acquisition and logging of the renewable sources with the LabVIEW Real-Time applications. The employed cRIO chassis controls the timing for the module and handles communication with the PC over the USB, Ethernet, or 802.11 Wi-Fi buses. It combines modular I/O, real-time processing, and NI LabVIEW programmable. In the presented setup, the Analog Input Module NI 9205 five channels have been used for input analog voltage signals from renewable energy sources and NI 9227 four channels have been used for input analog current signals of the renewable sources. For switching actions based on the programming logic developed in software, a module having Electromechanical Relays (single-pole single throw) with 4-Channels, electrically isolated and LED indicating the state of that channel have been used for isolating the renewable Sources on fault occurrence, which is decided by the logic in the program. The module for Ethernet based Data Acquisition Interface ENET 9163 Ethernet Carrier, which is connected on the LAN Router for data acquisition from a remote source over Ethernet also has the module NI 9229 installed. The LabVIEW platform has been employed for efficient data acquisition, monitoring and control. Control logic utilized in program for operation of the hardware switching Related to Fault Relays has been portrayed as a flowchart. A communication system has been successfully developed amongst the sources and loads connected on different computers using Hypertext transfer protocol, HTTP or Ethernet Local Stacked area Network TCP/IP protocol. There are two main I/O interfacing clients controlling the operation of the switching control of the renewable energy sources over internet or intranet. The paper presents experimental results of the briefed setup for intelligent control of the micro-grid for renewable energy sources, besides the control of Micro-Grid with data acquisition and control hardware based on a microcontroller with visual program developed in LabVIEW.

Keywords: data acquisition and control, LabVIEW, microcontroller cRIO, Smart Micro-Grid

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Authors: Yung-Chih Kuo, Che-Yu Lin, Jay-Shake Li, Yung-I Lou

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Curcumin (CRM) and nerve growth factor (NGF) were entrapped in liposomes (LIP) with cardiolipin (CL) to downregulate the phosphorylation of mitogen-activated protein kinases for Alzheimer’s disease (AD) management. AD belongs to neurodegenerative disorder with a gradual loss of memory, yielding irreversible dementia. CL-conjugated LIP loaded with CRM (CRM-CL/LIP) and that with NGF (NGF-CL/LIP) were applied to AD models of SK-N-MC cells and Wistar rats with an insult of β-amyloid peptide (Aβ). Lipids comprising 1,2-dipalmitoyl-sn-glycero-3- phosphocholine (Avanti Polar Lipids, Alabaster, AL), 1',3'-bis[1,2- dimyristoyl-sn-glycero-3-phospho]-sn-glycerol (CL; Avanti Polar Lipids), 1,2-dipalmitoyl-sn-glycero-3-phosphoethanolamine-N- [methoxy(polyethylene glycol)-2000] (Avanti Polar Lipids), 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[carboxy(polyethylene glycol)-2000] (Avanti Polar Lipids) and CRM (Sigma–Aldrich, St. Louis, MO) were dissolved in chloroform (J. T. Baker, Phillipsburg, NJ) and condensed using a rotary evaporator (Panchum, Kaohsiung, Taiwan). Human β-NGF (Alomone Lab, Jerusalem, Israel) was added in the aqueous phase. Wheat germ agglutinin (WGA; Medicago AB, Uppsala, Sweden) was grafted on LIP loaded with CRM for (WGA-CRM-LIP) and CL-conjugated LIP loaded with CRM (WGA-CRM-CL/LIP) using 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide (Sigma–Aldrich) and N-hydroxysuccinimide (Alfa Aesar, Ward Hill, MA). The protein samples of SK-N-MC cells (American Type Tissue Collection, Rockville, MD) were used for sodium dodecyl sulfate (Sigma–Aldrich) polyacrylamide gel (Sigma–Aldrich) electrophoresis. In animal study, the LIP formulations were administered by intravenous injection via a tail vein of male Wistar rats (250–280 g, 8 weeks, BioLasco, Taipei, Taiwan), which were housed in the Animal Laboratory of National Chung Cheng University in accordance with the institutional guidelines and the guidelines of Animal Protection Committee under the Council of Agriculture of the Republic of China. We found that CRM-CL/LIP could inhibit the expressions of phosphorylated p38 (p-p38), p-Jun N-terminal kinase (p-JNK), and p-tau protein at serine 202 (p-Ser202) to retard the neuronal apoptosis. Free CRM and released CRM from CRM-LIP and CRM-CL/LIP were not in a straightforward manner to effectively inhibit the expression of p-p38 and p-JNK in the cytoplasm. In addition, NGF-CL/LIP enhanced the quantities of p-neurotrophic tyrosine kinase receptor type 1 (p-TrkA) and p-extracellular-signal-regulated kinase 5 (p-ERK5), preventing the Aβ-induced degeneration of neurons. The membrane fusion of NGF-LIP activated the ERK5 pathway and the targeting capacity of NGF-CL/LIP enhanced the possibility of released NGF to affect the TrkA level. Moreover, WGA-CRM-LIP improved the permeation of CRM across the blood–brain barrier (BBB) and significantly reduced the Aβ plaque deposition and malondialdehyde level and increased the percentage of normal neurons and cholinergic function in the hippocampus of AD rats. This was mainly because the encapsulated CRM was protected by LIP against a rapid degradation in the blood. Furthermore, WGA on LIP could target N-acetylglucosamine on endothelia and increased the quantity of CRM transported across the BBB. In addition, WGA-CRM-CL/LIP could be effective in suppressing the synthesis of acetylcholinesterase and reduced the decomposition of acetylcholine for better neurotransmission. Based on the in vitro and in vivo evidences, WGA-CRM-CL/LIP can rescue neurons from apoptosis in the brain and can be a promising drug delivery system for clinical AD therapy.

Keywords: Alzheimer’s disease, β-amyloid, liposome, mitogen-activated protein kinase

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Authors: Andreea Campu, Ilinica Muresan, Simona Cainap, Simion Astilean, Monica Focsan

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Acute myocardial infarction (AMI) is the most severe cardiovascular disease, which has threatened human lives for decades, thus a continuous interest is directed towards the detection of cardiac biomarkers such as cardiac troponin I (cTnI) in order to predict risk and, implicitly, fulfill the early diagnosis requirements in AMI settings. Microfluidics is a major technology involved in the development of efficient sensing devices with real-time fast responses and on-site applicability. Microfluidic devices have gathered a lot of attention recently due to their advantageous features such as high sensitivity and specificity, miniaturization and portability, ease-of-use, low-cost, facile fabrication, and reduced sample manipulation. The integration of gold nanoparticles into the structure of microfluidic sensors has led to the development of highly effective detection systems, considering the unique properties of the metallic nanostructures, specifically the Localized Surface Plasmon Resonance (LSPR), which makes them highly sensitive to their microenvironment. In this scientific context, herein, we propose the implementation of a novel detection device, which successfully combines the efficiency of gold bipyramids (AuBPs) as signal transducers and thermal generators with the sample-driven advantages of the microfluidic channels into a miniaturized, portable, low-cost, specific, and sensitive test for the dual LSPR-thermographic cTnI detection. Specifically, AuBPs with longitudinal LSPR response at 830 nm were chemically synthesized using the seed-mediated growth approach and characterized in terms of optical and morphological properties. Further, the colloidal AuBPs were deposited onto pre-treated silanized glass substrates thus, a uniform nanoparticle coverage of the substrate was obtained and confirmed by extinction measurements showing a 43 nm blue-shift of the LSPR response as a consequence of the refractive index change. The as-obtained plasmonic substrate was then integrated into a microfluidic “Y”-shaped polydimethylsiloxane (PDMS) channel, fabricated using a Laser Cutter system. Both plasmonic and microfluidic elements were plasma treated in order to achieve a permanent bond. The as-developed microfluidic plasmonic chip was further coupled to an automated syringe pump system. The proposed biosensing protocol implicates the successive injection inside the microfluidic channel as follows: p-aminothiophenol and glutaraldehyde, to achieve a covalent bond between the metallic surface and cTnI antibody, anti-cTnI, as a recognition element, and target cTnI biomarker. The successful functionalization and capture of cTnI was monitored by LSPR detection thus, after each step, a red-shift of the optical response was recorded. Furthermore, as an innovative detection technique, thermal determinations were made after each injection by exposing the microfluidic plasmonic chip to 785 nm laser excitation, considering that the AuBPs exhibit high light-to-heat conversion performances. By the analysis of the thermographic images, thermal curves were obtained, showing a decrease in the thermal efficiency after the anti-cTnI-cTnI reaction was realized. Thus, we developed a microfluidic plasmonic chip able to operate as both LSPR and thermal sensor for the detection of the cardiac troponin I biomarker, leading thus to the progress of diagnostic devices.

Keywords: gold nanobipyramids, microfluidic device, localized surface plasmon resonance detection, thermographic detection

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Authors: Claudia Cocozza, Niccolò Frassinelli, Enrico Marchi, Cristiano Foderi, Alessandro Bizzarri, Margherita Paladini, Maria Laura Traversi, Eleftherious Touloupakis, Alessio Giovannelli

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The development of tools to quickly identify the fate of injured trees after stress is highly relevant when biodiversity restoration of damaged sites is based on nature-based solutions. In this context, an approach to assess irreversible physiological damages within trees could help to support planning management decisions of perturbed sites to restore biodiversity, for the safety of the environment and understanding functionality adjustments of the ecosystems. Tree vitality can be estimated by a series of physiological proxies like cambium activity, starch, and soluble sugars amount in C-sinks whilst the accumulation of ethanol within the cambial cells and phloem is considered an alert of cell death. However, their determination requires time-consuming laboratory protocols, which makes the approach unfeasible as a practical option in the field. The project aims to develop biosensors to assess the concentration of soluble sugars and ethanol in stem tissues. Soluble sugars and ethanol concentrations will be used to define injured trees to discriminate compromised and recovering trees in the forest directly. To reach this goal, we select study sites subjected to prescribed fires or recent wildfires as experimental set-ups. Indeed, in Mediterranean countries, forest fire is a recurrent event that must be considered as a central component of regional and global strategies in forest management and biodiversity restoration programs. A biosensor will be developed through a multistep process related to target analytes characterization, bioreceptor selection, and, finally, calibration/testing of the sensor. To validate biosensor signals, soluble sugars and ethanol will be quantified by HPLC and GC using synthetic media (in lab) and phloem sap (in field) whilst cambium vitality will be assessed by anatomical observations. On burnt trees, the stem growth will be monitored by dendrometers and/or estimated by tree ring analyses, whilst the tree response to past fire events will be assessed by isotopic discrimination. Moreover, the fire characterization and the visual assessment procedure will be used to assign burnt trees to a vitality class. At the end of the project, a well-defined procedure combining biosensor signal and visual assessment will be produced and applied to a study case. The project outcomes and the results obtained will be properly packaged to reach, engage and address the needs of the final users and widely shared with relevant stakeholders involved in the optimal use of biosensors and in the management of post-fire areas. This project was funded by National Recovery and Resilience Plan (NRRP), Mission 4, Component C2, Investment 1.1 - Call for tender No. 1409 of 14 September 2022 – ‘Progetti di Ricerca di Rilevante interesse Nazionale – PRIN’ of Italian Ministry of University and Research funded by the European Union – NextGenerationEU; Grant N° P2022Z5742, CUP B53D23023780001.

Keywords: phloem, scorched crown, conifers, prescribed burning, biosensors

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Authors: Vincent Schlageter, Maroua Mestiri, Florian Denzinger, Hugo Raetzo, Michel Demierre

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Precise landslide monitoring with differential global navigation satellite system (GNSS) is well known, but technical or economic reasons limit its application by geotechnical companies. This study demonstrates the reliability and the usefulness of Geomon (Infrasurvey Sàrl, Switzerland), a stand-alone and cost-effective rover network. The system permits deploying up to 15 rovers, plus one reference station for differential GNSS. A dedicated radio communication links all the modules to a base station, where an embedded computer automatically provides all the relative positions (L1 phase, open-source RTKLib software) and populates an Internet server. Each measure also contains information from an internal inclinometer, battery level, and position quality indices. Contrary to standard GNSS survey systems, which suffer from a limited number of beacons that must be placed in areas with good GSM signal, Geomon offers greater flexibility and permits a real overview of the whole landslide with good spatial resolution. Each module is powered with solar panels, ensuring autonomous long-term recordings. In this study, we have tested the system on several sites in the Swiss mountains, setting up to 7 rovers per site, for an 18 month-long survey. The aim was to assess the robustness and the accuracy of the system in different environmental conditions. In one case, we ran forced blind tests (vertical movements of a given amplitude) and compared various session parameters (duration from 10 to 90 minutes). Then the other cases were a survey of real landslides sites using fixed optimized parameters. Sub centimetric-accuracy with few outliers was obtained using the best parameters (session duration of 60 minutes, baseline 1 km or less), with the noise level on the horizontal component half that of the vertical one. The performance (percent of aborting solutions, outliers) was reduced with sessions shorter than 30 minutes. The environment also had a strong influence on the percent of aborting solutions (ambiguity search problem), due to multiple reflections or satellites obstructed by trees and mountains. The length of the baseline (distance reference-rover, single baseline processing) reduced the accuracy above 1 km but had no significant effect below this limit. In critical weather conditions, the system’s robustness was limited: snow, avalanche, and frost-covered some rovers, including the antenna and vertically oriented solar panels, leading to data interruption; and strong wind damaged a reference station. The possibility of changing the sessions’ parameters remotely was very useful. In conclusion, the rover network tested provided the foreseen sub-centimetric-accuracy while providing a dense spatial resolution landslide survey. The ease of implementation and the fully automatic long-term survey were timesaving. Performance strongly depends on surrounding conditions, but short pre-measures should allow moving a rover to a better final placement. The system offers a promising hazard mitigation technique. Improvements could include data post-processing for alerts and automatic modification of the duration and numbers of sessions based on battery level and rover displacement velocity.

Keywords: GNSS, GSM, landslide, long-term, network, solar, spatial resolution, sub-centimeter.

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Authors: Reza Nematirad, Anil Pahwa, Balasubramaniam Natarajan

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Time series data consist of successive data points collected over a period of time. Accurate prediction of future values is essential for informed decision-making in several real-world applications, including electricity load demand forecasting, lifetime estimation of industrial machinery, traffic planning, weather prediction, and the stock market. Due to their critical relevance and wide application, there has been considerable interest in time series forecasting in recent years. However, the proliferation of sensors and IoT devices, real-time monitoring systems, and high-frequency trading data introduce significant intricate temporal variations, rapid changes, noise, and non-linearities, making time series forecasting more challenging. Classical methods such as Autoregressive integrated moving average (ARIMA) and Exponential Smoothing aim to extract pre-defined temporal variations, such as trends and seasonality. While these methods are effective for capturing well-defined seasonal patterns and trends, they often struggle with more complex, non-linear patterns present in real-world time series data. In recent years, deep learning has made significant contributions to time series forecasting. Recurrent Neural Networks (RNNs) and their variants, such as Long short-term memory (LSTMs) and Gated Recurrent Units (GRUs), have been widely adopted for modeling sequential data. However, they often suffer from the locality, making it difficult to capture local trends and rapid fluctuations. Convolutional Neural Networks (CNNs), particularly Temporal Convolutional Networks (TCNs), leverage convolutional layers to capture temporal dependencies by applying convolutional filters along the temporal dimension. Despite their advantages, TCNs struggle with capturing relationships between distant time points due to the locality of one-dimensional convolution kernels. Transformers have revolutionized time series forecasting with their powerful attention mechanisms, effectively capturing long-term dependencies and relationships between distant time points. However, the attention mechanism may struggle to discern dependencies directly from scattered time points due to intricate temporal patterns. Lastly, Multi-Layer Perceptrons (MLPs) have also been employed, with models like N-BEATS and LightTS demonstrating success. Despite this, MLPs often face high volatility and computational complexity challenges in long-horizon forecasting. To address intricate temporal variations in time series data, this study introduces Times2D, a novel framework that parallelly integrates 2D spectrogram and derivative heatmap techniques. The spectrogram focuses on the frequency domain, capturing periodicity, while the derivative patterns emphasize the time domain, highlighting sharp fluctuations and turning points. This 2D transformation enables the utilization of powerful computer vision techniques to capture various intricate temporal variations. To evaluate the performance of Times2D, extensive experiments were conducted on standard time series datasets and compared with various state-of-the-art algorithms, including DLinear (2023), TimesNet (2023), Non-stationary Transformer (2022), PatchTST (2023), N-HiTS (2023), Crossformer (2023), MICN (2023), LightTS (2022), FEDformer (2022), FiLM (2022), SCINet (2022a), Autoformer (2021), and Informer (2021) under the same modeling conditions. The initial results demonstrated that Times2D achieves consistent state-of-the-art performance in both short-term and long-term forecasting tasks. Furthermore, the generality of the Times2D framework allows it to be applied to various tasks such as time series imputation, clustering, classification, and anomaly detection, offering potential benefits in any domain that involves sequential data analysis.

Keywords: derivative patterns, spectrogram, time series forecasting, times2D, 2D representation

Procedia PDF Downloads 42