Search results for: enzymatic biomarkers

Authors: Danyi Wang, Andrew Schriefer, Dennis O'Rourke, Brajendra Kumar, Yang Liu, Fei Zhong, Juergen Scheuenpflug, Zheng Feng

Abstract:

Purpose: It has been recognized that the microbiome plays critical roles in disease pathogenesis, including cancer, autoimmune disease, and multiple sclerosis. To develop a clinical-grade assay for exploring microbiome-derived clinical biomarkers across disease areas, a two-phase approach is implemented. 1) Identification of the optimal sample preparation reagents using pre-mixed bacteria and healthy donor stool samples coupled with proprietary Sigma-Aldrich® bioinformatics solution. 2) Exploratory analysis of patient samples for enabling precision medicine. Study Procedure: In phase 1 study, we first compared the 16S sequencing results of two ATCC® microbiome standards (MSA 2002 and MSA 2003) across five different extraction kits (Kit A, B, C, D & E). Both microbiome standards samples were extracted in triplicate across all extraction kits. Following isolation, DNA quantity was determined by Qubit assay. DNA quality was assessed to determine purity and to confirm extracted DNA is of high molecular weight. Bacterial 16S ribosomal ribonucleic acid (rRNA) amplicons were generated via amplification of the V3/V4 hypervariable region of the 16S rRNA. Sequencing was performed using a 2x300 bp paired-end configuration on the Illumina MiSeq. Fastq files were analyzed using the Sigma-Aldrich® Microbiome Platform. The Microbiome Platform is a cloud-based service that offers best-in-class 16S-seq and WGS analysis pipelines and databases. The Platform and its methods have been extensively benchmarked using microbiome standards generated internally by MilliporeSigma and other external providers. Data Summary: The DNA yield using the extraction kit D and E is below the limit of detection (100 pg/µl) of Qubit assay as both extraction kits are intended for samples with low bacterial counts. The pre-mixed bacterial pellets at high concentrations with an input of 2 x106 cells for MSA-2002 and 1 x106 cells from MSA-2003 were not compatible with the kits. Among the remaining 3 extraction kits, kit A produced the greatest yield whereas kit B provided the least yield (Kit-A/MSA-2002: 174.25 ± 34.98; Kit-A/MSA-2003: 179.89 ± 30.18; Kit-B/MSA-2002: 27.86 ± 9.35; Kit-B/MSA-2003: 23.14 ± 6.39; Kit-C/MSA-2002: 55.19 ± 10.18; Kit-C/MSA-2003: 35.80 ± 11.41 (Mean ± SD)). Also, kit A produced the greatest yield, whereas kit B provided the least yield. The PCoA 3D visualization of the Weighted Unifrac beta diversity shows that kits A and C cluster closely together while kit B appears as an outlier. The kit A sequencing samples cluster more closely together than both the other kits. The taxonomic profiles of kit B have lower recall when compared to the known mixture profiles indicating that kit B was inefficient at detecting some of the bacteria. Conclusion: Our data demonstrated that the DNA extraction method impacts DNA concentration, purity, and microbial communities detected by next-generation sequencing analysis. Further microbiome analysis performance comparison of using healthy stool samples is underway; also, colorectal cancer patients' samples will be acquired for further explore the clinical utilities. Collectively, our comprehensive qualification approach, including the evaluation of optimal DNA extraction conditions, the inclusion of positive controls, and the implementation of a robust qualified bioinformatics pipeline, assures accurate characterization of the microbiota in a complex matrix for deciphering the deep biology and enabling precision medicine.

Keywords: 16S rRNA sequencing, analytical validation, bioinformatics pipeline, metagenomics

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Authors: Pauline Nyssen, Ange Mouithys-Mickalad, Maryse Hoebeke

Abstract:

Inflammation is a complex physiological phenomenon involving chemical and enzymatic mechanisms. Polymorphonuclear neutrophil leukocytes (PMNs) play an important role by producing reactive oxygen species (ROS) and releasing myeloperoxidase (MPO), a pro-oxidant enzyme. Released both in the phagolysosome and the extracellular medium, MPO produces during its peroxidase and halogenation cycles oxidant species, including hypochlorous acid, involved in the destruction of pathogen agents, like bacteria or viruses. Inflammatory pathologies, like rheumatoid arthritis, atherosclerosis induce an excessive stimulation of the PMNs and, therefore, an uncontrolled release of ROS and MPO in the extracellular medium, causing severe damages to the surrounding tissues and biomolecules such as proteins, lipids, and DNA. The treatment of chronic inflammatory pathologies remains a challenge. For many years, MPO has been used as a target for the development of effective treatments. Numerous studies have been focused on the design of new drugs presenting more efficient MPO inhibitory properties. However, some designed inhibitors can be toxic. An alternative consists of assessing the potential inhibitory action of clinically-known molecules, having antioxidant activity. Propofol, 2,6-diisopropyl phenol, which is used as an intravenous anesthetic agent, meets these requirements. Besides its anesthetic action employed to induce a sedative state during surgery or in intensive care units, propofol and its injectable form Diprivan indeed present antioxidant properties and act as ROS and free radical scavengers. A study has also evidenced the ability of propofol to inhibit the formation of the neutrophil extracellular traps fibers, which are important to trap pathogen microorganisms during the inflammation process. The aim of this study was to investigate the potential inhibitory action mechanism of propofol and Diprivan on MPO activity. To go into the anti-inflammatory action of propofol in-depth, two of its oxidative derivatives, 2,6-diisopropyl-1,4-p-benzoquinone (PPFQ) and 3,5,3’,5’-tetra isopropyl-(4,4’)-diphenoquinone (PPFDQ), were studied regarding their inhibitory action. Specific immunological extraction followed by enzyme detection (SIEFED) and molecular modeling have evidenced the low anti-catalytic action of propofol. Stopped-flow absorption spectroscopy and direct MPO activity analysis have proved that propofol acts as a reversible MPO inhibitor by interacting as a reductive substrate in the peroxidase cycle and promoting the accumulation of redox compound II. Overall, Diprivan exhibited a weaker inhibitory action than the active molecule propofol. In contrast, PPFQ seemed to bind and obstruct the enzyme active site, preventing the trigger of the MPO oxidant cycles. PPFQ induced a better chlorination cycle inhibition at basic and neutral pH in comparison to propofol. PPFDQ did not show any MPO inhibition activity. The three interest molecules have also demonstrated their inhibition ability on an important step of the inflammation pathway, the PMNs superoxide anions production, thanks to EPR spectroscopy and chemiluminescence. In conclusion, propofol presents an interesting immunomodulatory activity by acting as a reductive substrate in the peroxidase cycle of MPO, slowing down its activity, whereas PPFQ acts more as an anti-catalytic substrate. Although PPFDQ has no impact on MPO, it can act on the inflammation process by inhibiting the superoxide anions production by PMNs.

Keywords: Diprivan, inhibitor, myeloperoxidase, propofol, spectroscopy

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Authors: Marcela Parra-Vargas, Ana Sandoval-Rodriguez, Roberto Rodriguez-Echevarria, Jose Dominguez-Rosales, Juan Armendariz-Borunda

Abstract:

Non-alcoholic fatty liver disease (NAFLD) is characterized by an excess of hepatic lipids, and it is to author’s best knowledge, the most prevalent chronic liver disorder. Anthocyanin-rich food consumption is linked to health benefits in metabolic disorders associated with obesity and NAFLD, although the precise functional role of anthocyanidin delphinidin (Dp) has yet to be established. The aim of this study was to investigate the effect of the Dp in NAFLD metabolic alterations by evaluating prevention or amelioration of hepatic lipid accumulation, as well as molecular mechanisms in two experimental obesity-related models of NALFD. In vitro: HepG2 cells were incubated with sodium palmitate (PA, 1 mM) to induce lipotoxic damage, and concomitantly treated with Dp (180 uM) for 24 h. Subsequently, total lipid accumulation was measured by colorimetric staining with Oil Red O, and total intrahepatic triglycerides were determined by an enzymatic assay. To assess molecular mechanisms, cells were pre-treated with PA for 24 h and then exposed to Dp for 1 h. In vivo: four-week-old male C57BL/6Nhsd mice were allocated in two main groups. Mice were fed with standard diet (control) or high-fat and high-carbohydrate diet (45% fat, HFD) for 16 wk to induce NAFLD. Then HFD was divided into subgroups: one treated orally with Dp (15 mg/kg bw, HFD-Dp) every day for 4 wk, while HFD group treated with vehicle (DMSO). Weight and fasting glucose were recorded weekly, while dietary ingestion was measured daily. Insulin tolerance test was performed at the end of treatment. Liver histology was evaluated with H&E and Masson’s trichrome stain. RT-PCR was used to evaluate gene expression and Western Blot to determine levels of protein in both experimental models. Parametric data were analyzed with one-way ANOVA and Tukey’s post-hoc test. Kruskal-Wallis and Mann-Whitney U test for non-parametric data, and P < 0.5 were considered significant. Dp prevented hepatic lipid accumulation by PA in HepG2 hepatocytes. Furthermore, Dp down-regulated gene expression of SREBP1c, FAS, and CPT1a without modifying AMPK phosphorylation levels. In vivo, Dp oral administration did not ameliorate lipid metabolic alterations raised by HFD. Adiposity, dietary ingestion, fasting glucose, and insulin sensitivity after Dp treatment remained similar to HFD group. Histological analysis showed hepatic damage in HFD groups and no differences between HFD and HFD-Dp groups were found. Hepatic gene expression of ACC and FAS were not altered by HFD. SREBP1c was similar in both HFD and HFD-Dp groups. No significant changes were observed in SREBP1c, ACC, and FAS adipose tissue gene expression by HFD or Dp treatment. Additionally, immunoblotting analysis revealed no changes in pathway SIRT1-LKB-AMPK and PPAR alpha by both HFD groups compared to control. In conclusion, the antioxidant Dp may provoke beneficial effects in the prevention of hepatic lipid accumulation. Nevertheless, the oral dose administrated in mice that simulated the total intake of anthocyanins consumed daily by humans has no effect as a treatment on hepatic lipid metabolic alterations and histological abnormalities associated with exposure to chronic HFD. A healthy lifestyle with regular intake of antioxidants such as anthocyanins may prevent metabolic alterations in NAFLD.

Keywords: anthocyanins, antioxidants, delphinidin, non-alcoholic fatty liver disease, obesity

Procedia PDF Downloads 178

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 55

Authors: Dmitriy Berillo, Areej K. A. Al-Jwaid, Jonathan L. Caplin, Andrew Cundy, Irina Savina

Abstract:

Chlorophenols (CPs) are used as a precursor in the production of higher CPs and dyestuffs, and as a preservative. Contamination by CPs of the ground water is located in the range from 0.15-100mg/L. The EU has set maximum concentration limits for pesticides and their degradation products of 0.1μg/L and 0.5μg/L, respectively. People working in industries which produce textiles, leather products, domestic preservatives, and petrochemicals are most heavily exposed to CPs. The International Agency for Research on Cancers categorized CPs as potential human carcinogens. Existing multistep water purification processes for CPs such as hydrogenation, ion exchange, liquid-liquid extraction, adsorption by activated carbon, forward and inverse osmosis, electrolysis, sonochemistry, UV irradiation, and chemical oxidation are not always cost effective and can cause the formation of even more toxic or mutagenic derivatives. Bioremediation of CPs derivatives utilizing microorganisms results in 60 to 100% decontamination efficiency and the process is more environmentally-friendly compared with existing physico-chemical methods. Microorganisms immobilized onto a substrate show many advantages over free bacteria systems, such as higher biomass density, higher metabolic activity, and resistance to toxic chemicals. They also enable continuous operation, avoiding the requirement for biomass-liquid separation. The immobilized bacteria can be reused several times, which opens the opportunity for developing cost-effective processes for wastewater treatment. In this study, we develop a bioremediation system for CPs based on macroporous materials, which can be efficiently used for wastewater treatment. Conditions for the preparation of the macroporous material from specific bacterial strains (Pseudomonas mendocina and Rhodococus koreensis) were optimized. The concentration of bacterial cells was kept constant; the difference was only the type of cross-linking agents used e.g. glutaraldehyde, novel polymers, which were utilized at concentrations of 0.5 to 1.5%. SEM images and rheology analysis of the material indicated a monolithic macroporous structure. Phenol was chosen as a model system to optimize the function of the cryogel material and to estimate its enzymatic activity, since it is relatively less toxic and harmful compared to CPs. Several types of macroporous systems comprising live bacteria were prepared. The viability of the cross-linked bacteria was checked using Live/Dead BacLight kit and Laser Scanning Confocal Microscopy, which revealed the presence of viable bacteria with the novel cross-linkers, whereas the control material cross-linked with glutaraldehyde(GA), contained mostly dead cells. The bioreactors based on bacteria were used for phenol degradation in batch mode at an initial concentration of 50mg/L, pH 7.5 and a temperature of 30°C. Bacterial strains cross-linked with GA showed insignificant ability to degrade phenol and for one week only, but a combination of cross-linking agents illustrated higher stability, viability and the possibility to be reused for at least five weeks. Furthermore, conditions for CPs degradation will be optimized, and the chlorophenol degradation rates will be compared to those for phenol. This is a cutting-edge bioremediation approach, which allows the purification of waste water from sustainable compounds without a separation step to remove free planktonic bacteria. Acknowledgments: Dr. Berillo D. A. is very grateful to Individual Fellowship Marie Curie Program for funding of the research.

Keywords: bioremediation, cross-linking agents, cross-linked microbial cell, chlorophenol degradation

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

Abstract:

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

Procedia PDF Downloads 104

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

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Authors: Subhash Nerella, Ziyuan Guan, Azra Bihorac, Parisa Rashidi

Abstract:

Intensive care units (ICUs) provide care to critically ill patients in severe and life-threatening conditions. However, patient monitoring in the ICU is limited by the time and resource constraints imposed on healthcare providers. Many critical care indices such as mobility are still manually assessed, which can be subjective, prone to human errors, and lack granularity. Other important aspects, such as environmental factors, are not monitored at all. For example, critically ill patients often experience circadian disruptions due to the absence of effective environmental “timekeepers” such as the light/dark cycle and the systemic effect of acute illness on chronobiologic markers. Although the occurrence of delirium is associated with circadian disruption risk factors, these factors are not routinely monitored in the ICU. Hence, there is a critical unmet need to develop systems for precise and real-time assessment through novel enabling technologies. We have developed the mobility and circadian disruption quantification system (Mobi-DiQ) by augmenting biomarker and clinical data with pervasive sensing data to generate mobility and circadian cues related to mobility, nightly disruptions, and light and noise exposure. We hypothesize that Mobi-DiQ can provide accurate mobility and circadian cues that correlate with bedside clinical mobility assessments and circadian biomarkers, ultimately important for delirium risk assessment and prevention. The collected multimodal dataset consists of depth images, Electromyography (EMG) data, patient extremity movement captured by accelerometers, ambient light levels, Sound Pressure Level (SPL), and indoor air quality measured by volatile organic compounds, and the equivalent CO₂ concentration. For delirium risk assessment, the system recognizes mobility cues (axial body movement features and body key points) and circadian cues, including nightly disruptions, ambient SPL, and light intensity, as well as other environmental factors such as indoor air quality. The Mobi-DiQ system consists of three major components: the pervasive sensing system, a data storage and analysis server, and a data annotation system. For data collection, six local pervasive sensing systems were deployed, including a local computer and sensors. A video recording tool with graphical user interface (GUI) developed in python was used to capture depth image frames for analyzing patient mobility. All sensor data is encrypted, then automatically uploaded to the Mobi-DiQ server through a secured VPN connection. Several data pipelines are developed to automate the data transfer, curation, and data preparation for annotation and model training. The data curation and post-processing are performed on the server. A custom secure annotation tool with GUI was developed to annotate depth activity data. The annotation tool is linked to the MongoDB database to record the data annotation and to provide summarization. Docker containers are also utilized to manage services and pipelines running on the server in an isolated manner. The processed clinical data and annotations are used to train and develop real-time pervasive sensing systems to augment clinical decision-making and promote targeted interventions. In the future, we intend to evaluate our system as a clinical implementation trial, as well as to refine and validate it by using other data sources, including neurological data obtained through continuous electroencephalography (EEG).

Keywords: deep learning, delirium, healthcare, pervasive sensing

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Authors: Denis Jordan, Daniel Golkowski, Mathias Lukas, Katharina Merz, Caroline Mlynarcik, Max Maurer, Valentin Riedl, Stefan Foerster, Eberhard F. Kochs, Andreas Bender, Ruediger Ilg

Abstract:

Introduction: So far, clinical assessments that rely on behavioral responses to differentiate coma states or even predict outcome in coma patients are unreliable, e.g. because of some patients’ motor disabilities. The present study was aimed to provide prognosis in coma patients using markers from electroencephalogram (EEG), blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) and [18F]-fluorodeoxyglucose (FDG) positron emission tomography (PET). Unsuperwised principal component analysis (PCA) was used for multimodal integration of markers. Methods: Approved by the local ethics committee of the Technical University of Munich (Germany) 20 patients (aged 18-89) with severe brain damage were acquired through intensive care units at the Klinikum rechts der Isar in Munich and at the Therapiezentrum Burgau (Germany). At the day of EEG/fMRI/PET measurement (date I) patients (<3.5 month in coma) were grouped in the minimal conscious state (MCS) or vegetative state (VS) on the basis of their clinical presentation (coma recovery scale-revised, CRS-R). Follow-up assessment (date II) was also based on CRS-R in a period of 8 to 24 month after date I. At date I, 63 channel EEG (Brain Products, Gilching, Germany) was recorded outside the scanner, and subsequently simultaneous FDG-PET/fMRI was acquired on an integrated Siemens Biograph mMR 3T scanner (Siemens Healthineers, Erlangen Germany). Power spectral densities, permutation entropy (PE) and symbolic transfer entropy (STE) were calculated in/between frontal, temporal, parietal and occipital EEG channels. PE and STE are based on symbolic time series analysis and were already introduced as robust markers separating wakefulness from unconsciousness in EEG during general anesthesia. While PE quantifies the regularity structure of the neighboring order of signal values (a surrogate of cortical information processing), STE reflects information transfer between two signals (a surrogate of directed connectivity in cortical networks). fMRI was carried out using SPM12 (Wellcome Trust Center for Neuroimaging, University of London, UK). Functional images were realigned, segmented, normalized and smoothed. PET was acquired for 45 minutes in list-mode. For absolute quantification of brain’s glucose consumption rate in FDG-PET, kinetic modelling was performed with Patlak’s plot method. BOLD signal intensity in fMRI and glucose uptake in PET was calculated in 8 distinct cortical areas. PCA was performed over all markers from EEG/fMRI/PET. Prognosis (persistent VS and deceased patients vs. recovery to MCS/awake from date I to date II) was evaluated using the area under the curve (AUC) including bootstrap confidence intervals (CI, *: p<0.05). Results: Prognosis was reliably indicated by the first component of PCA (AUC=0.99*, CI=0.92-1.00) showing a higher AUC when compared to the best single markers (EEG: AUC<0.96*, fMRI: AUC<0.86*, PET: AUC<0.60). CRS-R did not show prediction (AUC=0.51, CI=0.29-0.78). Conclusion: In a multimodal analysis of EEG/fMRI/PET in coma patients, PCA lead to a reliable prognosis. The impact of this result is evident, as clinical estimates of prognosis are inapt at time and could be supported by quantitative biomarkers from EEG, fMRI and PET. Due to the small sample size, further investigations are required, in particular allowing superwised learning instead of the basic approach of unsuperwised PCA.

Keywords: coma states and prognosis, electroencephalogram, entropy, functional magnetic resonance imaging, machine learning, positron emission tomography, principal component analysis

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Authors: David J. Foran, Nhan Do, Samuel Ajjarapu, Wenjin Chen, Tahsin Kurc, Joel H. Saltz

Abstract:

The large-scale data and computational requirements of investigators throughout the clinical and research communities demand an informatics infrastructure that supports both existing and new investigative and translational projects in a robust, secure environment. In some subspecialties of medicine and research, the capacity to generate data has outpaced the methods and technology used to aggregate, organize, access, and reliably retrieve this information. Leading health care centers now recognize the utility of establishing an enterprise-wide, clinical data warehouse. The primary benefits that can be realized through such efforts include cost savings, efficient tracking of outcomes, advanced clinical decision support, improved prognostic accuracy, and more reliable clinical trials matching. The overarching objective of the work presented here is the development and implementation of a flexible Intelligent Retrieval and Interrogation System (IRIS) that exploits the combined use of computational imaging, genomics, and data-mining capabilities to facilitate clinical assessments and translational research in oncology. The proposed System includes a multi-modal, Clinical & Research Data Warehouse (CRDW) that is tightly integrated with a suite of computational and machine-learning tools to provide insight into the underlying tumor characteristics that are not be apparent by human inspection alone. A key distinguishing feature of the System is a configurable Extract, Transform and Load (ETL) interface that enables it to adapt to different clinical and research data environments. This project is motivated by the growing emphasis on establishing Learning Health Systems in which cyclical hypothesis generation and evidence evaluation become integral to improving the quality of patient care. To facilitate iterative prototyping and optimization of the algorithms and workflows for the System, the team has already implemented a fully functional Warehouse that can reliably aggregate information originating from multiple data sources including EHR’s, Clinical Trial Management Systems, Tumor Registries, Biospecimen Repositories, Radiology PAC systems, Digital Pathology archives, Unstructured Clinical Documents, and Next Generation Sequencing services. The System enables physicians to systematically mine and review the molecular, genomic, image-based, and correlated clinical information about patient tumors individually or as part of large cohorts to identify patterns that may influence treatment decisions and outcomes. The CRDW core system has facilitated peer-reviewed publications and funded projects, including an NIH-sponsored collaboration to enhance the cancer registries in Georgia, Kentucky, New Jersey, and New York, with machine-learning based classifications and quantitative pathomics, feature sets. The CRDW has also resulted in a collaboration with the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) at the U.S. Department of Veterans Affairs to develop algorithms and workflows to automate the analysis of lung adenocarcinoma. Those studies showed that combining computational nuclear signatures with traditional WHO criteria through the use of deep convolutional neural networks (CNNs) led to improved discrimination among tumor growth patterns. The team has also leveraged the Warehouse to support studies to investigate the potential of utilizing a combination of genomic and computational imaging signatures to characterize prostate cancer. The results of those studies show that integrating image biomarkers with genomic pathway scores is more strongly correlated with disease recurrence than using standard clinical markers.

Keywords: clinical data warehouse, decision support, data-mining, intelligent databases, machine-learning.

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