Search results for: drug prediction

Authors: Meenakshi Barsaul Chauhan, Aastha Chauhan, Shilpa Hurmade, Rajeev Sen, Jyotsna Sen, Monika Dalal

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Introduction: Ovarian masses are common forms of neoplasm in women and represent 2/3rd of gynaecological malignancies. A pre-operative suggestion of malignancy can guide the gynecologist to refer women with suspected pelvic mass to a gynecological oncologist for appropriate therapy and optimized treatment, which can improve survival. In the younger age group preoperative differentiation into benign or malignant pathology can decide for conservative or radical surgery. Imaging modalities have a definite role in establishing the diagnosis. By using International Ovarian Tumor Analysis (IOTA) classification with sonography, costly radiological methods like Magnetic Resonance Imaging (MRI) / computed tomography (CT) scan can be reduced, especially in developing countries like India. Thus, this study is being undertaken to evaluate the role of clinical methods and sonography for diagnosis of the nature of the ovarian tumor. Material And Methods: This prospective observational study was conducted on 40 patients presenting with ovarian masses, in the Department of Obstetrics and Gynaecology, at a tertiary care center in northern India. Functional cysts were excluded. Ultrasonography and color Doppler were performed on all the cases.IOTA rules were applied, which take into account locularity, size, presence of solid components, acoustic shadow, dopper flow etc . Magnetic Resonance Imaging (MRI) / computed tomography (CT) scans abdomen and pelvis were done in cases where sonography was inconclusive. In inoperable cases, Fine needle aspiration cytology (FNAC) was done. The histopathology report after surgery and cytology report after FNAC was correlated statistically with the pre-operative diagnosis made clinically and sonographically using IOTA rules. Statistical Analysis: Descriptive measures were analyzed by using mean and standard deviation and the Student t-test was applied and the proportion was analyzed by applying the chi-square test. Inferential measures were analyzed by sensitivity, specificity, negative predictive value, and positive predictive value. Results: Provisional diagnosis of the benign tumor was made in 16(42.5%) and of the malignant tumor was made in 24(57.5%) patients on the basis of clinical findings. With IOTA simple rules on sonography, 15(37.5%) were found to be benign, while 23 (57.5%) were found to be malignant and findings were inconclusive in 2 patients (5%). FNAC/Histopathology reported that benign ovarian tumors were 14 (35%) and 26(65%) were malignant, which was taken as the gold standard. The clinical finding alone was found to have a sensitivity of 66.6% and a specificity of 90.9%. USG alone had a sensitivity of 86% and a specificity of 80%. When clinical findings and IOTA simple rules of sonography were combined (excluding inconclusive masses), the sensitivity and specificity were 83.3% and 92.3%, respectively. While including inconclusive masses, sensitivity came out to be 91.6% and specificity was 89.2. Conclusion: IOTA's simple sonography rules are highly sensitive and specific in the prediction of ovarian malignancy and also easy to use and easily reproducible. Thus, combining clinical examination with USG will help in the better management of patients in terms of time, cost and better prognosis. This will also avoid the need for costlier modalities like CT, and MRI.

Keywords: benign, international ovarian tumor analysis classification, malignant, ovarian tumours, sonography

Procedia PDF Downloads 80

Authors: Babak Forouraghi

Abstract:

A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations of previous approaches, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with attention mechanism. In a previous work on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: transformers, generative ai, gene expression design, classification

Procedia PDF Downloads 59

Authors: Alfredo Fortunato, Carmelofrancesco Origlia, Sara Laurita, Rossella Nicoletti

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In the post-pandemic recovery phase of tourism, the role of a Destination Management Organization (DMO) as a coordinated management system of all the elements that make up a destination (attractions, access, marketing, human resources, brand, pricing, etc.) is also becoming relevant for local territories. The objective of a DMO is to maximize the visitor's perception of value and quality while ensuring the competitiveness and sustainability of the destination, as well as the long-term preservation of its natural and cultural assets, and to catalyze benefits for the local economy and residents. In carrying out the multiple functions to which it is called, the DMO can leverage a collective intelligence that comes from the ability to pool information, explicit and tacit knowledge, and relationships of the various stakeholders: policymakers, public managers and officials, entrepreneurs in the tourism supply chain, researchers, data journalists, schools, associations and committees, citizens, etc. The DMO potentially has at its disposal large volumes of data and many of them at low cost, that need to be properly processed to produce value. Based on these assumptions, the paper presents a conceptual framework for building an information system to support the DMO in the intelligent management of a tourist destination tested in an area of southern Italy. The approach adopted is data-informed and consists of four phases: (1) formulation of the knowledge problem (analysis of policy documents and industry reports; focus groups and co-design with stakeholders; definition of information needs and key questions); (2) research and metadatation of relevant sources (reconnaissance of official sources, administrative archives and internal DMO sources); (3) gap analysis and identification of unconventional information sources (evaluation of traditional sources with respect to the level of consistency with information needs, the freshness of information and granularity of data; enrichment of the information base by identifying and studying web sources such as Wikipedia, Google Trends, Booking.com, Tripadvisor, websites of accommodation facilities and online newspapers); (4) definition of the set of indicators and construction of the information base (specific definition of indicators and procedures for data acquisition, transformation, and analysis). The framework derived consists of 6 thematic areas (accommodation supply, cultural heritage, flows, value, sustainability, and enabling factors), each of which is divided into three domains that gather a specific information need to be represented by a scheme of questions to be answered through the analysis of available indicators. The framework is characterized by a high degree of flexibility in the European context, given that it can be customized for each destination by adapting the part related to internal sources. Application to the case study led to the creation of a decision support system that allows: •integration of data from heterogeneous sources, including through the execution of automated web crawling procedures for data ingestion of social and web information; •reading and interpretation of data and metadata through guided navigation paths in the key of digital story-telling; •implementation of complex analysis capabilities through the use of data mining algorithms such as for the prediction of tourist flows.

Keywords: collective intelligence, data framework, destination management, smart tourism

Procedia PDF Downloads 121

Authors: Pinzhe Zhao

Abstract:

This study focuses on predicting university students' cheating tendencies using psychological traits and machine learning techniques. Academic dishonesty is a significant issue that compromises the integrity and fairness of educational institutions. While much research has been dedicated to detecting cheating behaviors after they have occurred, there is limited work on predicting such tendencies before they manifest. The aim of this research is to develop a model that can identify students who are at higher risk of engaging in academic misconduct, allowing for earlier interventions to prevent such behavior. Psychological factors are known to influence students' likelihood of cheating. Research shows that traits such as test anxiety, moral reasoning, self-efficacy, and achievement motivation are strongly linked to academic dishonesty. High levels of anxiety may lead students to cheat as a way to cope with pressure. Those with lower self-efficacy are less confident in their academic abilities, which can push them toward dishonest behaviors to secure better outcomes. Students with weaker moral judgment may also justify cheating more easily, believing it to be less wrong under certain conditions. Achievement motivation also plays a role, as students driven primarily by external rewards, such as grades, are more likely to cheat compared to those motivated by intrinsic learning goals. In this study, data on students’ psychological traits is collected through validated assessments, including scales for anxiety, moral reasoning, self-efficacy, and motivation. Additional data on academic performance, attendance, and engagement in class are also gathered to create a more comprehensive profile. Using machine learning algorithms such as Random Forest, Support Vector Machines (SVM), and Long Short-Term Memory (LSTM) networks, the research builds models that can predict students’ cheating tendencies. These models are trained and evaluated using metrics like accuracy, precision, recall, and F1 scores to ensure they provide reliable predictions. The findings demonstrate that combining psychological traits with machine learning provides a powerful method for identifying students at risk of cheating. This approach allows for early detection and intervention, enabling educational institutions to take proactive steps in promoting academic integrity. The predictive model can be used to inform targeted interventions, such as counseling for students with high test anxiety or workshops aimed at strengthening moral reasoning. By addressing the underlying factors that contribute to cheating behavior, educational institutions can reduce the occurrence of academic dishonesty and foster a culture of integrity. In conclusion, this research contributes to the growing body of literature on predictive analytics in education. It offers a approach by integrating psychological assessments with machine learning to predict cheating tendencies. This method has the potential to significantly improve how academic institutions address academic dishonesty, shifting the focus from punishment after the fact to prevention before it occurs. By identifying high-risk students and providing them with the necessary support, educators can help maintain the fairness and integrity of the academic environment.

Keywords: academic dishonesty, cheating prediction, intervention strategies, machine learning, psychological traits, academic integrity

Procedia PDF Downloads 20

Authors: Beatriz González-rodrigo, Diego Hidalgo-leiva, Omar Flores, Claudia Germoso, Maribel Jiménez-martínez, Laura Navas-sánchez, Belén Orta, Nicola Tarque, Orlando Hernández- Rubio, Miguel Marchamalo, Juan Gregorio Rejas, Belén Benito-oterino

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Cities facing seismic hazard necessitate detailed risk assessments for effective urban planning and vulnerability identification, ensuring the safety and sustainability of urban infrastructure. Comprehensive studies involving seismic hazard, vulnerability, and exposure evaluations are pivotal for estimating potential losses and guiding proactive measures against seismic events. However, broad-scale traditional risk studies limit consideration of specific local threats and identify vulnerable housing within a structural typology. Achieving precise results at neighbourhood levels demands higher resolution seismic hazard exposure, and vulnerability studies. This research aims to bolster sustainability and safety against seismic disasters in three Central American and Caribbean capitals. It integrates geospatial techniques and artificial intelligence into seismic risk studies, proposing cost-effective methods for exposure data collection and damage prediction. The methodology relies on prior seismic threat studies in pilot zones, utilizing existing exposure and vulnerability data in the region. Emphasizing detailed building attributes enables the consideration of behaviour modifiers affecting seismic response. The approach aims to generate detailed risk scenarios, facilitating prioritization of preventive actions pre-, during, and post-seismic events, enhancing decision-making certainty. Detailed risk scenarios necessitate substantial investment in fieldwork, training, research, and methodology development. Regional cooperation becomes crucial given similar seismic threats, urban planning, and construction systems among involved countries. The outcomes hold significance for emergency planning and national and regional construction regulations. The success of this methodology depends on cooperation, investment, and innovative approaches, offering insights and lessons applicable to regions facing moderate seismic threats with vulnerable constructions. Thus, this framework aims to fortify resilience in seismic-prone areas and serves as a reference for global urban planning and disaster management strategies. In conclusion, this research proposes a comprehensive framework for seismic risk assessment in high-risk urban areas, emphasizing detailed studies at finer resolutions for precise vulnerability evaluations. The approach integrates regional cooperation, geospatial technologies, and adaptive fragility curve adjustments to enhance risk assessment accuracy, guiding effective mitigation strategies and emergency management plans.

Keywords: assessment, behaviour modifiers, emergency management, mitigation strategies, resilience, vulnerability

Procedia PDF Downloads 68

Authors: Ankita Baidya, Vanishri Ganakumar, Ranveer S. Jadon, Piyush Ranjan, Rita Sood

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Septic embolism can have varied presentations and clinical considerations. Infected central venous catheters are commonly associated with septic emboli but peripheral vascular catheters are rarely implicated. We describe a rare case of septic pulmonary emboli related to infected peripheral venous cannulation caused by an unusual etiological agent. A young male presented with complaints of fever, productive cough, sudden onset shortness of breath and cellulitis in both the upper limbs. He was recently hospitalised for dengue fever and administered intravenous fluids through peripheral venous line. The patient was febrile, tachypneic and in respiratory distress, there were multiple pus filled bullae in left hand alongwith swelling and erythema involving right forearm that started at the site of cannulation. Chest examination showed active accessory muscles of respiration, stony dull percussion at the base of right lung and decreased breath sounds at right infrascapular, infraaxillary and mammary area. Other system examination was within normal limits. Chest X-ray revealed bilateral multiple patchy heterogenous peripheral opacities and infiltrates with right-sided pleural effusion. Contrast-enhanced computed tomography (CECT) chest showed feeding vessel sign confirming the diagnosis as septic emboli. Venous Doppler and 2D-echocardiogarm were normal. Laboratory findings showed marked leucocytosis (22000/mm3). Pus aspirate, blood sample, and sputum sample were sent for microbiological testing. The patient was started empirically on ceftriaxone, vancomycin, and clindamycin. The Pus culture and sputum culture showed Klebsiella pneumoniae sensitive to cefoperazone-sulbactum, piperacillin-tazobactum, meropenem and amikacin. The antibiotics were modified accordingly to antimicrobial sensitivity profile to Cefoperazone-sulbactum. Bronchoalveolar lavage (BAL) was done and sent for microbiological investigations. BAL culture showed Klebsiella pneumoniae with same antimicrobial resistance profile. On day 6 of starting cefoperazone-sulbactum, he became afebrile. The skin lesions improved significantly. He was administered 2 weeks of cefoperazone–sulbactum and discharged on oral faropenem for 4 weeks. At the time of discharge, TLC was 11200/mm3 with marked radiological resolution of infection and healed skin lesions. He was kept in regular follow up. Chest X-ray and skin lesions showed complete resolution after 8 weeks. Till date, only couple of case reports of septic emboli through peripheral intravenous line have been reported in English literature. This case highlights that a simple procedure of peripheral intravenous cannulation can lead to catastrophic complication of septic pulmonary emboli and widespread cellulitis if not done with proper care and precautions. Also, the usual pathogens in such clinical settings are gram positive bacteria, but with the history of recent hospitalization, empirical therapy should also cover drug resistant gram negative microorganisms. It also emphasise the importance of appropriate healthcare practices to be taken care during all procedures.

Keywords: antibiotics, cannula, Klebsiella pneumoniae, septic emboli

Procedia PDF Downloads 160

Authors: Fadi Al Khatib, Raouf Mbarki, Malek Adouni

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In various sport and recreational activities, the patellofemoral joint undergoes large forces and moments while accommodating the significant knee joint movement. In doing so, this joint is commonly the source of anterior knee pain related to instability in normal patellar tracking and excessive pressure syndrome. One well-observed explanation of the instability of the normal patellar tracking is the patellofemoral ligaments and patellar tendon damage. Improved knowledge of the damage mechanism mediating ligaments and tendon injuries can be a great help not only in rehabilitation and prevention procedures but also in the design of better reconstruction systems in the management of knee joint disorders. This damage mechanism, specifically due to excessive mechanical loading, has been linked to the micro level of the fibred structure precisely to the tropocollagen molecules and their connection density. We argue defining a clear frame starting from the bottom (micro level) to up (macro level) in the hierarchies of the soft tissue may elucidate the essential underpinning on the state of the ligaments damage. To do so, in this study a multiscale fibril reinforced hyper elastoplastic Finite Element model that accounts for the synergy between molecular and continuum syntheses was developed to determine the short-term stresses/strains patellofemoral ligaments and tendon response. The plasticity of the proposed model is associated only with the uniaxial deformation of the collagen fibril. The yield strength of the fibril is a function of the cross-link density between tropocollagen molecules, defined here by a density function. This function obtained through a Coarse-graining procedure linking nanoscale collagen features and the tissue level materials properties using molecular dynamics simulations. The hierarchies of the soft tissues were implemented using the rule of mixtures. Thereafter, the model was calibrated using a statistical calibration procedure. The model then implemented into a real structure of patellofemoral ligaments and patellar tendon (OpenKnee) and simulated under realistic loading conditions. With the calibrated material parameters the calculated axial stress lies well with the experimental measurement with a coefficient of determination (R2) equal to 0.91 and 0.92 for the patellofemoral ligaments and the patellar tendon respectively. The ‘best’ prediction of the yielding strength and strain as compared with the reported experimental data yielded when the cross-link density between the tropocollagen molecule of the fibril equal to 5.5 ± 0.5 (patellofemoral ligaments) and 12 (patellar tendon). Damage initiation of the patellofemoral ligaments was located at the femoral insertions while the damage of the patellar tendon happened in the middle of the structure. These predicted finding showed a meaningful correlation between the cross-link density of the tropocollagen molecules and the stiffness of the connective tissues of the extensor mechanism. Also, damage initiation and propagation were documented with this model, which were in satisfactory agreement with earlier observation. To the best of our knowledge, this is the first attempt to model ligaments from the bottom up, predicted depending to the tropocollagen cross-link density. This approach appears more meaningful towards a realistic simulation of a damaging process or repair attempt compared with certain published studies.

Keywords: tropocollagen, multiscale model, fibrils, knee ligaments

Procedia PDF Downloads 128

Authors: Shlomit Paz, Meir Broza

Abstract:

Cholera is an acute intestinal infection caused by ingestion of food or water contaminated with the bacterium Vibrio cholerae. It has a short incubation period and produces an enterotoxin that causes copious, painless, watery diarrhoea that can quickly lead to severe dehydration and death if treatment is not promptly given. In an epidemic, the source of the contamination is usually the feces of an infected person. The disease can spread rapidly in areas with poor treatment of sewage and drinking water. Cholera remains a global threat and is one of the key indicators of social development. An estimated 3-5 million cases and over 100,000 deaths occur each year around the world. The relevance of climatic events as causative factors for cholera epidemics is well known. However, the examination of the involvement of winds in intra-continental disease distribution is new. The study explore the hypothesis that the spreading of cholera epidemics may be related to the dominant wind direction over land by presenting the influence of the wind direction on windborn dissemination by flying insects, which may serve as vectors. Chironomids ("non-biting midges“) exist in the majority of freshwater aquatic habitats, especially in estuarine and organic-rich water bodies typical to Vibrio cholerae. Chironomid adults emerge into the air for mating and dispersion. They are highly mobile, huge in number and found frequently in the air at various elevations. The huge number of chironomid egg masses attached to hard substrate on the water surface, serve as a reservoir for the free-living Vibrio bacteria. Both male and female, while emerging from the water, may carry the cholera bacteria. In experimental simulation, it was demonstrated that the cholera-bearing adult midges are carried by the wind, and transmit the bacteria from one body of water to another. In our previous study, the geographic diffusions of three cholera outbreaks were examined through their linkage with the wind direction: a) the progress of Vibrio cholerae O1 biotype El Tor in Africa during 1970–1971 and b) again in 2005–2006; and c) the rapid spread of Vibrio cholerae O139 over India during 1992–1993. Using data and map of cholera dissemination (WHO database) and mean monthly SLP and geopotential data (NOAA NCEP-NCAR database), analysis of air pressure data at sea level and at several altitudes over Africa, India and Bangladesh show a correspondence between the dominant wind direction and the intra-continental spread of cholera. The results support the hypothesis that aeroplankton (the tiny life forms that float in the air and that may be caught and carried upward by the wind, landing far from their origin) carry the cholera bacteria from one body of water to an adjacent one. In addition to these findings, the current follow-up study will present new results regarding the possible involvement of winds in the spreading of cholera in recent outbreaks (2010-2013). The findings may improve the understanding of how climatic factors are involved in the rapid distribution of new strains throughout a vast continental area. Awareness of the aerial transfer of Vibrio cholerae may assist health authorities by improving the prediction of the disease’s geographic dissemination.

Keywords: cholera, Vibrio cholerae, wind direction, Vibrio cholerae dissemination

Procedia PDF Downloads 367

Authors: Jungyeol Hong, Dongjoo Park

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The primary purpose of this study is to develop a methodological framework to predict daily subway ridership at a station-level and to examine the association between subway ridership and bus demand incorporating commercial business facility in the vicinity of each subway station. The socio-economic characteristics, land-use, and built environment as factors may have an impact on subway ridership. However, it should be considered not only the endogenous relationship between bus and subway demand but also the characteristics of commercial business within a subway station’s sphere of influence, and integrated transit network topology. Regarding a statistical approach to estimate subway ridership at a station level, therefore it should be considered endogeneity and heteroscedastic issues which might have in the subway ridership prediction model. This study focused on both discovering the impacts of bus demand, commercial business characteristics, and network topology on subway ridership and developing more precise subway ridership estimation accounting for its statistical bias. The spatial scope of the study covers entire Seoul city in South Korea and includes 243 stations with the temporal scope set at twenty-four hours with one-hour interval time panels each. The data for subway and bus ridership was collected Seoul Smart Card data from 2015 and 2016. Three-Stage Least Square(3SLS) approach was applied to develop daily subway ridership model as capturing the endogeneity and heteroscedasticity between bus and subway demand. Independent variables incorporating in the modeling process were commercial business characteristics, social-economic characteristics, safety index, transit facility attributes, and dummies for seasons and time zone. As a result, it was found that bus ridership and subway ridership were endogenous each other and they had a significantly positive sign of coefficients which means one transit mode could increase another transportation mode’s ridership. In other words, two transit modes of subway and bus have a mutual relationship instead of the competitive relationship. The commercial business characteristics are the most critical dimension among the independent variables. The variables of commercial business facility rate in the paper containing six types; medical, educational, recreational, financial, food service, and shopping. From the model result, a higher rate in medical, financial buildings, shopping, and food service facility lead to increment of subway ridership at a station, while recreational and educational facility shows lower subway ridership. The complex network theory was applied for estimating integrated network topology measures that cover the entire Seoul transit network system, and a framework for seeking an impact on subway ridership. The centrality measures were found to be significant and showed a positive sign indicating higher centrality led to more subway ridership at a station level. The results of model accuracy tests by out of samples provided that 3SLS model has less mean square error rather than OLS and showed the methodological approach for the 3SLS model was plausible to estimate more accurate subway ridership. Acknowledgement: This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science and ICT (2017R1C1B2010175).

Keywords: subway ridership, bus ridership, commercial business characteristic, endogeneity, network topology

Procedia PDF Downloads 144

Authors: Sagar Saroha, Sawan S. Sinha, Sunil Lakshmipathy

Abstract:

Reynolds averaged Navier-Stokes (RANS) model is the popular computational tool for prediction of turbulent flows. Being computationally less expensive as compared to direct numerical simulation (DNS), RANS has received wide acceptance in industry and research community as well. However, for high Reynolds number flows, the traditional RANS approach based on the Boussinesq hypothesis is incapacitated to capture all the essential flow characteristics, and thus, its performance is restricted in high Reynolds number flows of practical interest. RANS performance turns out to be inadequate in regimes like flow over curved surfaces, flows with rapid changes in the mean strain rate, duct flows involving secondary streamlines and three-dimensional separated flows. In the recent decade, partially averaged Navier-Stokes (PANS) methodology has gained acceptability among seamless bridging methods of turbulence- placed between DNS and RANS. PANS methodology, being a scale resolving bridging method, is inherently more suitable than RANS for simulating turbulent flows. The superior ability of PANS method has been demonstrated for some cases like swirling flows, high-speed mixing environment, and high Reynolds number turbulent flows. In our work, we intend to evaluate PANS in case of separated turbulent flows past bluff bodies -which is of broad aerodynamic research and industrial application. PANS equations, being derived from base RANS, continue to inherit the inadequacies from the parent RANS model based on linear eddy-viscosity model (LEVM) closure. To enhance PANS’ capabilities for simulating separated flows, the shortcomings of the LEVM closure need to be addressed. Inabilities of the LEVMs have inspired the development of non-linear eddy viscosity models (NLEVM). To explore the potential improvement in PANS performance, in our study we evaluate the PANS behavior in conjugation with NLEVM. Our work can be categorized into three significant steps: (i) Extraction of PANS version of NLEVM from RANS model, (ii) testing the model in the homogeneous turbulence environment and (iii) application and evaluation of the model in the canonical case of separated non-homogeneous flow field (flow past prismatic bodies and bodies of revolution at high Reynolds number). PANS version of NLEVM shall be derived and implemented in OpenFOAM -an open source solver. Homogeneous flows evaluation will comprise the study of the influence of the PANS’ filter-width control parameter on the turbulent stresses; the homogeneous analysis performed over typical velocity fields and asymptotic analysis of Reynolds stress tensor. Non-homogeneous flow case will include the study of mean integrated quantities and various instantaneous flow field features including wake structures. Performance of PANS + NLEVM shall be compared against the LEVM based PANS and LEVM based RANS. This assessment will contribute to significant improvement of the predictive ability of the computational fluid dynamics (CFD) tools in massively separated turbulent flows past bluff bodies.

Keywords: bridging methods of turbulence, high Re-CFD, non-linear PANS, separated turbulent flows

Procedia PDF Downloads 145

Authors: Babak Forouraghi

Abstract:

A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of the flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on the spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts, as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with an attention mechanism. In previous works on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work, with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on the presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: machine learning, classification and regression, gene circuit design, bidirectional transformers

Procedia PDF Downloads 61

Authors: Juan A. Arzate, Funda C. Ertem, M. Nicolas Cruz-Bournazou, Peter Neubauer, Stefan Junne

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— One of the biggest challenges the world faces today is global warming that is caused by greenhouse gases (GHGs) coming from the combustion of fossil fuels for energy generation. In order to mitigate climate change, the European Union has committed to reducing GHG emissions to 80–95% below the level of the 1990s by the year 2050. Renewable technologies are vital to diminish energy-related GHG emissions. Since water and biomass are limited resources, the largest contributions to renewable energy (RE) systems will have to come from wind and solar power. Nevertheless, high proportions of fluctuating RE will present a number of challenges, especially regarding the need to balance the variable energy demand with the weather dependent fluctuation of energy supply. Therefore, biogas plants in this content would play an important role, since they are easily adaptable. Feedstock availability varies locally or seasonally; however there is a lack of knowledge in how biogas plants should be operated in a stable manner by local feedstock. This problem may be prevented through suitable control strategies. Such strategies require the development of convenient mathematical models, which fairly describe the main processes. Modelling allows us to predict the system behavior of biogas plants when different feedstocks are used with different loading rates. Life cycle assessment (LCA) is a technique for analyzing several sides from evolution of a product till its disposal in an environmental point of view. It is highly recommend to use as a decision making tool. In order to achieve suitable strategies, the combination of a flexible energy generation provided by biogas plants, a secure production process and the maximization of the environmental benefits can be obtained by the combination of process modelling and LCA approaches. For this reason, this study focuses on the biogas plant which flexibly generates required energy from the co-digestion of maize, grass and cattle manure, while emitting the lowest amount of GHG´s. To achieve this goal AMOCO model was combined with LCA. The program was structured in Matlab to simulate any biogas process based on the AMOCO model and combined with the equations necessary to obtain climate change, acidification and eutrophication potentials of the whole production system based on ReCiPe midpoint v.1.06 methodology. Developed simulation was optimized based on real data from operating biogas plants and existing literature research. The results prove that AMOCO model can successfully imitate the system behavior of biogas plants and the necessary time required for the process to adapt in order to generate demanded energy from available feedstock. Combination with LCA approach provided opportunity to keep the resulting emissions from operation at the lowest possible level. This would allow for a prediction of the process, when the feedstock utilization supports the establishment of closed material circles within a smart bio-production grid – under the constraint of minimal drawbacks for the environment and maximal sustainability.

Keywords: AMOCO model, GHG emissions, life cycle assessment, modelling

Procedia PDF Downloads 188

Authors: F. Tang, S. Boskovich, A. Raheja, Z. Aliyazicioglu, S. Bhandari, N. Tsuchiya

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Calpoly Autonomous Transportation Experience (CATE) is a driverless vehicle that we are developing to provide safe, accessible, and efficient transportation of passengers throughout the Cal Poly Pomona campus for events such as orientation tours. Unlike the other self-driving vehicles that are usually developed to operate with other vehicles and reside only on the road networks, CATE will operate exclusively on walk-paths of the campus (potentially narrow passages) with pedestrians traveling from multiple locations. Safety becomes paramount as CATE operates within the same environment as pedestrians. As driverless vehicles assume greater roles in today’s transportation, this project will contribute to autonomous driving with pedestrian traffic in a highly dynamic environment. The CATE project requires significant interdisciplinary work. Researchers from mechanical engineering, electrical engineering and computer science are working together to attack the problem from different perspectives (hardware, software and system). In this abstract, we describe the software aspects of the project, with a focus on the requirements and the major components. CATE shall provide a GUI interface for the average user to interact with the car and access its available functionalities, such as selecting a destination from any origin on campus. We have developed an interface that provides an aerial view of the campus map, the current car location, routes, and the goal location. Users can interact with CATE through audio or manual inputs. CATE shall plan routes from the origin to the selected destination for the vehicle to travel. We will use an existing aerial map for the campus and convert it to a spatial graph configuration where the vertices represent the landmarks and edges represent paths that the car should follow with some designated behaviors (such as stay on the right side of the lane or follow an edge). Graph search algorithms such as A* will be implemented as the default path planning algorithm. D* Lite will be explored to efficiently recompute the path when there are any changes to the map. CATE shall avoid any static obstacles and walking pedestrians within some safe distance. Unlike traveling along traditional roadways, CATE’s route directly coexists with pedestrians. To ensure the safety of the pedestrians, we will use sensor fusion techniques that combine data from both lidar and stereo vision for obstacle avoidance while also allowing CATE to operate along its intended route. We will also build prediction models for pedestrian traffic patterns. CATE shall improve its location and work under a GPS-denied situation. CATE relies on its GPS to give its current location, which has a precision of a few meters. We have implemented an Unscented Kalman Filter (UKF) that allows the fusion of data from multiple sensors (such as GPS, IMU, odometry) in order to increase the confidence of localization. We also noticed that GPS signals can easily get degraded or blocked on campus due to high-rise buildings or trees. UKF can also help here to generate a better state estimate. In summary, CATE will provide on-campus transportation experience that coexists with dynamic pedestrian traffic. In future work, we will extend it to multi-vehicle scenarios.

Keywords: driverless vehicle, path planning, sensor fusion, state estimate

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Authors: Salam N. Abdo, Orien L. Tulp, George P. Einstein

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The purpose of this exploratory study was to gather the insights into psoriasis etiology, treatment, and patient experience, for developing psoriasis and psoriatic arthritis diagnostic test. Data collection methods consisted of a comprehensive meta-analysis of relevant studies and psoriasis patient survey. Established meta-analysis guidelines were used for the selection and qualitative comparative analysis of psoriasis and psoriatic arthritis research studies. Only studies that clearly discussed psoriasis etiology, treatment, and patient experience were reviewed and analyzed, to establish a qualitative data base for the study. Using the insights gained from meta-analysis, an existing psoriasis patient survey was modified and administered to collect additional data as well as triangulate the results. The hypothesis is that specific types of psoriatic disease have specific etiology and pathophysiologic pattern. The following etiology categories were identified: bacterial, environmental/microbial, genetic, immune, infectious, trauma/stress, and viral. Additional results, obtained from meta-analysis and confirmed by patient survey, were the common age of onset (early to mid-20s) and type of psoriasis (plaque; mild; symmetrical; scalp, chest, and extremities, specifically elbows and knees). Almost 70% of patients reported no prescription drug use due to severe side effects and prohibitive cost. These results will guide the development of psoriasis and psoriatic arthritis diagnostic test. The significant number of medical publications classified psoriatic arthritis disease as inflammatory of an unknown etiology. Thus numerous meta-analyses struggle to report any meaningful conclusions since no definitive results have been reported to date. Therefore, return to the basics is an essential step to any future meaningful results. To date, medical literature supports the fact that psoriatic disease in its current classification could be misidentifying subcategories, which in turn hinders the success of studies conducted to date. Moreover, there has been an enormous commercial support to pursue various immune-modulation therapies, thus following a narrow hypothesis/mechanism of action that is yet to yield resolution of disease state. Recurrence and complications may be considered unacceptable in a significant number of these studies. The aim of the ongoing study is to focus on a narrow subgroup of patient population, as identified by this exploratory study via meta-analysis and patient survey, and conduct an exhaustive work up, aiming at mechanism of action and causality before proposing a cure or therapeutic modality. Remission in psoriasis has been achieved and documented in medical literature, such as immune-modulation, phototherapy, various over-the-counter agents, including salts and tar. However, there is no psoriasis and psoriatic arthritis diagnostic test to date, to guide the diagnosis and treatment of this debilitating and, thus far, incurable disease. Because psoriasis affects approximately 2% of population, the results of this study may affect the treatment and improve the quality of life of a significant number of psoriasis patients, potentially millions of patients in the United States alone and many more millions worldwide.

Keywords: biologics, early diagnosis, etiology, immune disease, immune modulation therapy, inflammation skin disorder, phototherapy, plaque psoriasis, psoriasis, psoriasis classification, psoriasis disease marker, psoriasis diagnostic test, psoriasis marker, psoriasis mechanism of action, psoriasis treatment, psoriatic arthritis, psoriatic disease, psoriatic disease marker, psoriatic patient experience, psoriatic patient quality of life, remission, salt therapy, targeted immune therapy

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Authors: Bailey Houghtaling, Sarah Misyak

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Food access; the availability, affordability, convenience, and desirability of food and beverage products within communities, is influential on consumers’ purchasing and consumption decisions. These variables may contribute to lower dietary quality scores and a higher obesity prevalence documented among rural and disadvantaged populations in the United States (U.S.). Current research assessing linkages between food access and obesity outcomes has primarily focused on distance to a traditional grocery/supermarket store as a measure of optimality. However, low-income consumers especially, including U.S. Department of Agriculture’s Supplemental Nutrition Assistance Program (SNAP) participants, seem to utilize non-traditional food store formats with greater frequency for household dietary needs. Non-traditional formats have been associated with less nutritious food and beverage options and consumer purchases that are high in saturated fats, added sugars, and sodium. Authors’ formative research indicated differences by U.S. region and rurality in the distribution of traditional and non-traditional SNAP-authorized food store formats. Therefore, using Virginia as a case study, the purpose of this research was to determine if a relationship between store format, rurality, and obesity exists. This research applied SNAP-authorized food store data (food access points for SNAP as well as non-SNAP consumers) and obesity prevalence data by Virginia county using publicly available databases: (1) SNAP Retailer Locator, and; (2) U.S. County Health Rankings. The alpha level was set a priori at 0.05. All Virginia SNAP-authorized stores (n=6,461) were coded by format – grocery, drug, mass merchandiser, club, convenience, dollar, supercenter, specialty, farmers market, independent grocer, and non-food store. Simple linear regression was applied primarily to assess the relationship between store format and obesity. Thereafter, multiple variables were added to the regression to account for potential moderating relationships (e.g., county income, rurality). Convenience, dollar, non-food or restaurant, mass merchandiser, farmers market, and independent grocer formats were significantly, positively related to obesity prevalence. Upon controlling for urban-rural status and income, results indicated the following formats to be significantly related to county obesity prevalence with a small, positive effect: convenience (p=0.010), accounting for 0.3% of the variance in obesity prevalence; dollar (p=0.005; 0.5% of the variance), and; non-food (p=0.030; 1.3% of the variance) formats. These results align with current literature on consumer behavior at non-traditional formats. For example, consumers’ food and beverage purchases at convenience and dollar stores are documented to be high in saturated fats, added sugars, and sodium. Further, non-food stores (i.e., quick-serve restaurants) often contribute to a large portion of U.S. consumers’ dietary intake and thus poor dietary quality scores. Current food access research investigates grocery/supermarket access and obesity outcomes. These results suggest more research is needed that focuses on non-traditional food store formats. Nutrition interventions within convenience, dollar, and non-food stores, for example, that aim to enhance not only healthy food access but the affordability, convenience, and desirability of nutritious food and beverage options may impact obesity rates in Virginia. More research is warranted utilizing the presented investigative framework in other U.S. and global regions to explore the role and the potential of non-traditional food store formats to prevent and reduce obesity.

Keywords: food access, food store format, non-traditional food stores, obesity prevalence

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Authors: Laura Norfolk, Georgina Zimbitas, Jan Sefcik, Sarah Staniland

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Magnetite nanoparticles (MNP) have been an area of increasing research interest due to their extensive applications in industry, such as in carbon capture, water purification, and crucially, the biomedical industry. The use of MNP in the biomedical industry is rising, with studies on their effect as Magnetic resonance imaging contrast agents, drug delivery systems, and as hyperthermic cancer treatments becoming prevalent in the nanomaterial research community. Particles used for biomedical purposes must meet stringent criteria; the particles must have consistent shape and size between particles. Variation between particle morphology can drastically alter the effective surface area of the material, making it difficult to correctly dose particles that are not homogeneous. Particles of defined shape such as octahedral and cubic have been shown to outperform irregular shaped particles in some applications, leading to the need to synthesize particles of defined shape. In nature, highly homogeneous MNP are found within magnetotactic bacteria, a unique bacteria capable of producing magnetite nanoparticles internally under ambient conditions. Biomineralisation proteins control the properties of the MNPs, enhancing their homogeneity. One of these proteins, Mms6, has been successfully isolated and used in vitro as an additive in room-temperature co-precipitation reactions (RTCP) to produce particles of defined mono-dispersed size & morphology. When considering future industrial scale-up it is crucial to consider the costs and feasibility of an additive, as an additive that is not readily available or easily synthesized at a competitive price will not be sustainable. As such, additives selected for this research are inspired by the functional groups of biomineralisation proteins, but cost-effective, environmentally friendly, and compatible with scale-up. Diethylenetriamine (DETA), triethylenetetramine (TETA), tetraethylenepentamine (TEPA), and pentaethylenehexamine (PEHA) have been successfully used in RTCP to modulate the properties of particles synthesized, leading to the formation of octahedral nanoparticles with no use of organic solvents, heating, or toxic precursors. By extending this principle to a fluidic system, ongoing research will reveal whether the amine additives can also exert morphological control in an environment which is suited toward higher particle yield. Two fluidic systems have been employed; a peristaltic turbulent flow mixing system suitable for the rapid production of MNP, and a macrofluidic system for the synthesis of tailored nanomaterials under a laminar flow regime. The presence of the amine additives in the turbulent flow system in initial results appears to offer similar morphological control as observed under RTCP conditions, with higher proportions of octahedral particles formed. This is a proof of concept which may pave the way to green synthesis of tailored MNP on an industrial scale. Mms6 and amine additives have been used in the macrofluidic system, with Mms6 allowing magnetite to be synthesized at unfavourable ferric ratios, but no longer influencing particle size. This suggests this synthetic technique while still benefiting from the addition of additives, may not allow additives to fully influence the particles formed due to the faster timescale of reaction. The amine additives have been tested at various concentrations, the results of which will be discussed in this paper.

Keywords: bioinspired, green synthesis, fluidic, magnetite, morphological control, scale-up

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Authors: Maria Ledinskaya

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This paper examines the Morris Collection Conservation Project at the Sainsbury Centre for Visual Arts in the context of Agile, Lean, and Hybrid project management. It is part case study and part literature review. To date, relatively little has been written about non-traditional project management approaches in heritage conservation. This paper seeks to introduce Agile, Lean, and Hybrid project management concepts from business, software development, and manufacturing fields to museum conservation, by referencing their practical application on a recent museum-based conservation project. The Morris Collection Conservation Project was carried out in 2019-2021 in Norwich, UK, and concerned the remedial conservation of around 150 Abstract Constructivist artworks bequeathed to the Sainsbury Centre for Visual Arts by private collectors Michael and Joyce Morris. The first part introduces the chronological timeline and key elements of the project. It describes a medium-size conservation project of moderate complexity, which was planned and delivered in an environment with multiple known unknowns – unresearched collection, unknown condition and materials, unconfirmed budget. The project was also impacted by the unknown unknowns of the COVID-19 pandemic, such as indeterminate lockdowns, and the need to accommodate social distancing and remote communications. The author, a staff conservator at the Sainsbury Centre who acted as project manager on the Morris Collection Conservation Project, presents an incremental, iterative, and value-based approach to managing a conservation project in an uncertain environment. Subsequent sections examine the project from the point of view of Traditional, Agile, Lean, and Hybrid project management. The author argues that most academic writing on project management in conservation has focussed on a Traditional plan-driven approach – also known as Waterfall project management – which has significant drawbacks in today’s museum environment, due to its over-reliance on prediction-based planning and its low tolerance to change. In the last 20 years, alternative Agile, Lean and Hybrid approaches to project management have been widely adopted in software development, manufacturing, and other industries, although their recognition in the museum sector has been slow. Using examples from the Morris Collection Conservation Project, the author introduces key principles and tools of Agile, Lean, and Hybrid project management and presents a series of arguments on the effectiveness of these alternative methodologies in museum conservation, as well as the ethical and practical challenges to their implementation. These project management approaches are discussed in the context of consequentialist, relativist, and utilitarian developments in contemporary conservation ethics, particularly with respect to change management, bespoke ethics, shared decision-making, and value-based cost-benefit conservation strategy. The author concludes that the Morris Collection Conservation Project had multiple Agile and Lean features which were instrumental to the successful delivery of the project. These key features are identified as distributed decision making, a co-located cross-disciplinary team, servant leadership, focus on value-added work, flexible planning done in shorter sprint cycles, light documentation, and emphasis on reducing procedural, financial, and logistical waste. Overall, the author’s findings point largely in favour of a Hybrid model which combines traditional and alternative project processes and tools to suit the specific needs of the project.

Keywords: project management, conservation, waterfall, agile, lean, hybrid

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Authors: Danlei Yang, Luofeng Huang

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The integration of digital twin technology with renewable energy systems offers an innovative approach to predicting and optimising performance throughout the entire lifecycle. A digital twin is a continuously updated virtual replica of a real-world entity, synchronised with data from its physical counterpart and environment. Many digital twin companies today claim to have mature digital twin products, but their focus is primarily on equipment visualisation. However, the core of a digital twin should be its model, which can mirror, shadow, and thread with the real-world entity, which is still underdeveloped. For a floating solar energy system, a digital twin model can be defined in three aspects: (a) the physical floating solar energy system along with environmental factors such as solar irradiance and wave dynamics, (b) a digital model powered by artificial intelligence (AI) algorithms, and (c) the integration of real system data with the AI-driven model and a user interface. The experimental setup for the floating solar energy system, is designed to replicate real-ocean conditions of floating solar installations within a controlled laboratory environment. The system consists of a water tank that simulates an aquatic surface, where a floating catamaran structure supports a solar panel. The solar simulator is set up in three positions: one directly above and two inclined at a 45° angle in front and behind the solar panel. This arrangement allows the simulation of different sun angles, such as sunrise, midday, and sunset. The solar simulator is positioned 400 mm away from the solar panel to maintain consistent solar irradiance on its surface. Stability for the floating structure is achieved through ropes attached to anchors at the bottom of the tank, which simulates the mooring systems used in real-world floating solar applications. The floating solar energy system's sensor setup includes various devices to monitor environmental and operational parameters. An irradiance sensor measures solar irradiance on the photovoltaic (PV) panel. Temperature sensors monitor ambient air and water temperatures, as well as the PV panel temperature. Wave gauges measure wave height, while load cells capture mooring force. Inclinometers and ultrasonic sensors record heave and pitch amplitudes of the floating system’s motions. An electric load measures the voltage and current output from the solar panel. All sensors collect data simultaneously. Artificial neural network (ANN) algorithms are central to developing the digital model, which processes historical and real-time data, identifies patterns, and predicts the system’s performance in real time. The data collected from various sensors are partly used to train the digital model, with the remaining data reserved for validation and testing. The digital twin model combines the experimental setup with the ANN model, enabling monitoring, analysis, and prediction of the floating solar energy system's operation. The digital model mirrors the functionality of the physical setup, running in sync with the experiment to provide real-time insights and predictions. It provides useful industrial benefits, such as informing maintenance plans as well as design and control strategies for optimal energy efficiency. In long term, this digital twin will help improve overall solar energy yield whilst minimising the operational costs and risks.

Keywords: digital twin, floating solar energy system, experiment setup, artificial intelligence

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Authors: Artem Kim, Clara Savary, Christele Dubourg, Wilfrid Carre, Houda Hamdi-Roze, Valerie Dupé, Sylvie Odent, Marie De Tayrac, Veronique David

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Holoprosencephaly (HPE) is a rare congenital brain malformation resulting from the incomplete separation of the two cerebral hemispheres. It is characterized by a wide phenotypic spectrum and a high degree of locus heterogeneity. Genetic defects in 16 genes have already been implicated in HPE, but account for only 30% of cases, suggesting that a large part of genetic factors remains to be discovered. HPE has been recently redefined as a complex multigenic disorder, requiring the joint effect of multiple mutational events in genes belonging to one or several developmental pathways. The onset of HPE may result from accumulation of the effects of multiple rare variants in functionally-related genes, each conferring a moderate increase in the risk of HPE onset. In order to decipher the genetic basis of HPE, unconventional patterns of inheritance involving multiple genetic factors need to be considered. The primary objective of this study was to uncover possible disease causing combinations of multiple rare variants underlying HPE by performing trio-based Whole Exome Sequencing (WES) of familial cases where no molecular diagnosis could be established. 39 families were selected with no fully-penetrant causal mutation in known HPE gene, no chromosomic aberrations/copy number variants and without any implication of environmental factors. As the main challenge was to identify disease-related variants among a large number of nonpathogenic polymorphisms detected by WES classical scheme, a novel variant prioritization approach was established. It combined WES filtering with complementary gene-level approaches: transcriptome-driven (RNA-Seq data) and clinically-driven (public clinical data) strategies. Briefly, a filtering approach was performed to select variants compatible with disease segregation, population frequency and pathogenicity prediction to identify an exhaustive list of rare deleterious variants. The exome search space was then reduced by restricting the analysis to candidate genes identified by either transcriptome-driven strategy (genes sharing highly similar expression patterns with known HPE genes during cerebral development) or clinically-driven strategy (genes associated to phenotypes of interest overlapping with HPE). Deeper analyses of candidate variants were then performed on a family-by-family basis. These included the exploration of clinical information, expression studies, variant characteristics, recurrence of mutated genes and available biological knowledge. A novel bioinformatics pipeline was designed. Applied to the 39 families, this final integrated workflow identified an average of 11 candidate variants per family. Most of candidate variants were inherited from asymptomatic parents suggesting a multigenic inheritance pattern requiring the association of multiple mutational events. The manual analysis highlighted 5 new strong HPE candidate genes showing recurrences in distinct families. Functional validations of these genes are foreseen.

Keywords: complex genetic disorder, holoprosencephaly, multiple rare variants, whole exome sequencing

Procedia PDF Downloads 203

Authors: Wiam El Kheir, Anais Dumais, Maude Beaudoin, Bernard Marcos, Nick Virgilio, Benoit Paquette, Nathalie Faucheux, Marc-Antoine Lauzon

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The high infiltrative pattern of glioblastoma multiforme cells (GBM) is the main cause responsible for the actual standard treatments failure. The tumor high heterogeneity, the interstitial fluid flow (IFF) and chemokines guides GBM cells migration in the brain parenchyma resulting in tumor recurrence. Drug delivery systems emerged as an alternative approach to develop effective treatments for the disease. Some recent studies have proposed to harness the effect CXC-lchemokine-ligand-12 to direct and control the cancer cell migration through delivery system. However, the dynamics of the brain environment on the delivery system remains poorly understood. Nanoparticles (NPs) and hydrogels are known as good carriers for the encapsulation of different agents and control their release. We studied the release of CXCL12 (free or loaded into NPs) from an alginate-based hydrogel under static and indirect perfusion (IP) conditions. Under static conditions, the main phenomena driving CXCL12 release from the hydrogel was diffusion with the presence of strong interactions between the positively charged CXCL12 and the negatively charge alginate. CXCL12 release profiles were independent from the initial mass loadings. Afterwards, we demonstrated that the release could tuned by loading CXCL12 into Alginate/Chitosan-Nanoparticles (Alg/Chit-NPs) and embedded them into alginate-hydrogel. The initial burst release was substantially attenuated and the overall cumulative release percentages of 21%, 16% and 7% were observed for initial mass loadings of 0.07, 0.13 and 0.26 µg, respectively, suggesting stronger electrostatic interactions. Results were mathematically modeled based on Fick’s second law of diffusion framework developed previously to estimate the effective diffusion coefficient (Deff) and the mass transfer coefficient. Embedding the CXCL12 into NPs decreased the Deff an order of magnitude, which was coherent with experimental data. Thereafter, we developed an in-vitro 3D model that takes into consideration the convective contribution of the brain IFF to study CXCL12 release in an in-vitro microenvironment that mimics as faithfully as possible the human brain. From is unique design, the model also allowed us to understand the effect of IP on CXCL12 release in respect to time and space. Four flow rates (0.5, 3, 6.5 and 10 µL/min) which may increase CXCL12 release in-vivo depending on the tumor location were assessed. Under IP, cumulative percentages varying between 4.5-7.3%, 23-58.5%, 77.8-92.5% and 89.2-95.9% were released for the three initial mass loadings of 0.08, 0.16 and 0.33 µg, respectively. As the flow rate increase, IP culture conditions resulted in a higher release of CXCL12 compared to static conditions as the convection contribution became the main driving mass transport phenomena. Further, depending on the flow rate, IP had a direct impact on CXCL12 distribution within the simulated brain tissue, which illustrates the importance of developing such 3D in-vitro models to assess the efficiency of a delivery system targeting the brain. In future work, using this very model, we aim to understand the impact of the different phenomenon occurring on GBM cell behaviors in response to the resulting chemokine gradient subjected to various flow while allowing them to express their invasive characteristics in an in-vitro microenvironment that mimics the in-vivo brain parenchyma.

Keywords: 3D culture system, chemokines gradient, glioblastoma multiforme, kinetic release, mathematical modeling

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Authors: Mumtaz Mooncey, Alexander Jolly, Megan Fisher, Kerry Robinson, Robert Lloyd, Dave Fielding

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Introduction: The integration of the WingFactors in-situ simulation programme has transformed the education landscape at the Whittington Health NHS Trust. To date, there have been a total of 90 simulations - 19 aimed at Paediatric trainees, including 2 Child and Adolescent Mental Health (CAMHS) scenarios. The opportunity for joint debriefs provided by clinical faculty and airline pilots, has created a new exciting avenue to explore human factors within psychiatry. Through the use of real clinical environments and primed actors; the benefits of high fidelity simulation, interdisciplinary and interprofessional learning has been highlighted. The use of in-situ simulation within Psychiatry is a newly emerging concept and its success here has been recognised by unanimously positive feedback from participants and acknowledgement through nomination for the Health Service Journal (HSJ) Award (Best Education Programme 2021). Methodology: The first CAMHS simulation featured a collapsed patient in the toilet with a ligature tied around her neck, accompanied by a distressed parent. This required participants to consider:; emergency physical management of the case, alongside helping to contain the mother and maintaining situational awareness when transferring the patient to an appropriate clinical area. The second simulation was based on a 17- year- old girl attempting to leave the ward after presenting with an overdose, posing potential risk to herself. The safe learning environment enabled participants to explore techniques to engage the young person and understand their concerns, and consider the involvement of other members of the multidisciplinary team. The scenarios were followed by an immediate ‘hot’ debrief, combining technical feedback with Human Factors feedback from uniformed airline pilots and clinicians. The importance of psychological safety was paramount, encouraging open and honest contributions from all participants. Key learning points were summarized into written documents and circulated. Findings: The in-situ simulations demonstrated the need for practical changes both in the Emergency Department and on the Paediatric ward. The presence of airline pilots provided a novel way to debrief on Human Factors. The following key themes were identified: -Team-briefing (‘Golden 5 minutes’) - Taking a few moments to establish experience, initial roles and strategies amongst the team can reduce the need for conversations in front of a distressed patient or anxious relative. -Use of checklists / guidelines - Principles associated with checklist usage (control of pace, rigor, team situational awareness), instead of reliance on accurate memory recall when under pressure. -Read-back - Immediate repetition of safety critical instructions (e.g. drug / dosage) to mitigate the risks associated with miscommunication. -Distraction management - Balancing the risk of losing a team member to manage a distressed relative, versus it impacting on the care of the young person. -Task allocation - The value of the implementation of ‘The 5A’s’ (Availability, Address, Allocate, Ask, Advise), for effective task allocation. Conclusion: 100% of participants have requested more simulation training. Involvement of airline pilots has led to a shift in hospital culture, bringing to the forefront the value of Human Factors focused training and multidisciplinary simulation. This has been of significant value in not only physical health, but also mental health simulation.

Keywords: human factors, in-situ simulation, inter-professional, multidisciplinary

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Authors: V. Saccà, A. Sarica, F. Novellino, S. Barone, T. Tallarico, E. Filippelli, A. Granata, P. Valentino, A. Quattrone

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The work aim was to evaluate how well Random Forest (RF) and Support Vector Machine (SVM) algorithms could support the early diagnosis of Multiple Sclerosis (MS) from resting-state functional connectivity data. In particular, we wanted to explore the ability in distinguishing between controls and patients of mean signals extracted from ICA components corresponding to 15 well-known networks. Eighteen patients with early-MS (mean-age 37.42±8.11, 9 females) were recruited according to McDonald and Polman, and matched for demographic variables with 19 healthy controls (mean-age 37.55±14.76, 10 females). MRI was acquired by a 3T scanner with 8-channel head coil: (a)whole-brain T1-weighted; (b)conventional T2-weighted; (c)resting-state functional MRI (rsFMRI), 200 volumes. Estimated total lesion load (ml) and number of lesions were calculated using LST-toolbox from the corrected T1 and FLAIR. All rsFMRIs were pre-processed using tools from the FMRIB's Software Library as follows: (1) discarding of the first 5 volumes to remove T1 equilibrium effects, (2) skull-stripping of images, (3) motion and slice-time correction, (4) denoising with high-pass temporal filter (128s), (5) spatial smoothing with a Gaussian kernel of FWHM 8mm. No statistical significant differences (t-test, p < 0.05) were found between the two groups in the mean Euclidian distance and the mean Euler angle. WM and CSF signal together with 6 motion parameters were regressed out from the time series. We applied an independent component analysis (ICA) with the GIFT-toolbox using the Infomax approach with number of components=21. Fifteen mean components were visually identified by two experts. The resulting z-score maps were thresholded and binarized to extract the mean signal of the 15 networks for each subject. Statistical and machine learning analysis were then conducted on this dataset composed of 37 rows (subjects) and 15 features (mean signal in the network) with R language. The dataset was randomly splitted into training (75%) and test sets and two different classifiers were trained: RF and RBF-SVM. We used the intrinsic feature selection of RF, based on the Gini index, and recursive feature elimination (rfe) for the SVM, to obtain a rank of the most predictive variables. Thus, we built two new classifiers only on the most important features and we evaluated the accuracies (with and without feature selection) on test-set. The classifiers, trained on all the features, showed very poor accuracies on training (RF:58.62%, SVM:65.52%) and test sets (RF:62.5%, SVM:50%). Interestingly, when feature selection by RF and rfe-SVM were performed, the most important variable was the sensori-motor network I in both cases. Indeed, with only this network, RF and SVM classifiers reached an accuracy of 87.5% on test-set. More interestingly, the only misclassified patient resulted to have the lowest value of lesion volume. We showed that, with two different classification algorithms and feature selection approaches, the best discriminant network between controls and early MS, was the sensori-motor I. Similar importance values were obtained for the sensori-motor II, cerebellum and working memory networks. These findings, in according to the early manifestation of motor/sensorial deficits in MS, could represent an encouraging step toward the translation to the clinical diagnosis and prognosis.

Keywords: feature selection, machine learning, multiple sclerosis, random forest, support vector machine

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Authors: Gousilin Leandra Rocha Da Silva, Stéfani T. A. Dantas, Bruna F. Rossi, Erika R. Bonsaglia, Ivana G. Castilho, Terue Sadatsune, Ary Fernandes Júnior, Vera l. M. Rall

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Kidney failure causes decreased diuresis and accumulation of nitrogenous substances in the body. To increase patient survival, hemodialysis is used as a partial substitute for renal function. However, contamination of the water used in this treatment, causing bacteremia in patients, is a worldwide concern. The Burkholderia cepacia complex (Bcc), a group of bacteria with more than 20 species, is frequently isolated from hemodialysis water samples and comprises opportunistic bacteria, affecting immunosuppressed patients, due to its wide variety of virulence factors, in addition to innate resistance to several antimicrobial agents, contributing to the permanence in the hospital environment and to the pathogenesis in the host. The objective of the present work was to characterize molecularly and phenotypically Bcc isolates collected from the water and dialysate of the Hemodialysis Unit and from the blood of patients at a Public Hospital in Botucatu, São Paulo, Brazil, between 2019 and 2021. We used 33 Bcc isolates, previously obtained from blood cultures from patients with bacteremia undergoing hemodialysis treatment (2019-2021) and 24 isolates obtained from water and dialysate samples in a Hemodialysis Unit (same period). The recA gene was sequenced to identify the specific species among the Bcc group. All isolates were tested for the presence of some genes that encode virulence factors such as cblA, esmR, zmpA and zmpB. Considering the epidemiology of the outbreak, the Bcc isolates were molecularly characterized by Multi Locus Sequence Type (MLST) and by pulsed-field gel electrophoresis (PFGE). The verification and quantification of biofilm in a polystyrene microplate were performed by submitting the isolates to different incubation temperatures (20°C, average water temperature and 35°C, optimal temperature for group growth). The antibiogram was performed with disc diffusion tests on agar, using discs impregnated with cefepime (30µg), ceftazidime (30µg), ciprofloxacin (5µg), gentamicin (10µg), imipenem (10µg), amikacin 30µg), sulfametazol/trimethoprim (23.75/1.25µg) and ampicillin/sulbactam (10/10µg). The presence of ZmpB was identified in all isolates, while ZmpA was observed in 96.5% of the isolates, while none of them presented the cblA and esmR genes. The antibiogram of the 33 human isolates indicated that all were resistant to gentamicin, colistin, ampicillin/sulbactam and imipenem. 16 (48.5%) isolates were resistant to amikacin and lower rates of resistance were observed for meropenem, ceftazidime, cefepime, ciprofloxacin and piperacycline/tazobactam (6.1%). All isolates were sensitive to sulfametazol/trimethoprim, levofloxacin and tigecycline. As for the water isolates, resistance was observed only to gentamicin (34.8%) and imipenem (17.4%). According to PFGE results, all isolates obtained from humans and water belonged to the same pulsotype (1), which was identified by recA sequencing as B. cepacia¸, belonging to sequence type ST-767. By observing a single pulse type over three years, one can observe the persistence of this isolate in the pipeline, contaminating patients undergoing hemodialysis, despite the routine disinfection of water with peracetic acid. This persistence is probably due to the production of biofilm, which protects bacteria from disinfectants and, making this scenario more critical, several isolates proved to be multidrug-resistant (resistance to at least three groups of antimicrobials), turning the patient care even more difficult.

Keywords: hemodialysis, burkholderia cepacia, PFGE, MLST, multi drug resistance

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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: Charalabos Antonatos, Mariza Panoutsopoulou, Georgios K. Georgakilas, Evangelos Evangelou, Yiannis Vasilopoulos

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The extended tissue damage and severe clinical outcomes of autoimmune diseases, accompanied by the high annual costs to the overall health care system, highlight the need for an efficient therapy. Increasing knowledge over the pathophysiology of specific chronic inflammatory diseases, namely Psoriasis (PsO), Inflammatory Bowel Diseases (IBD) consisting of Crohn’s disease (CD) and Ulcerative colitis (UC), and Rheumatoid Arthritis (RA), has provided insights into the underlying mechanisms that lead to the maintenance of the inflammation, such as Tumor Necrosis Factor alpha (TNF-α). Hence, the anti-TNFα biological agents pose as an ideal therapeutic approach. Despite the efficacy of anti-TNFα agents, several clinical trials have shown that 20-40% of patients do not respond to treatment. Nowadays, high-throughput technologies have been recruited in order to elucidate the complex interactions in multifactorial phenotypes, with the most ubiquitous ones referring to transcriptome quantification analyses. In this context, a random effects meta-analysis of available gene expression cDNA microarray datasets was performed between responders and non-responders to anti-TNFα therapy in patients with IBD, PsO, and RA. Publicly available datasets were systematically searched from inception to 10th of November 2020 and selected for further analysis if they assessed the response to anti-TNFα therapy with clinical score indexes from inflamed biopsies. Specifically, 4 IBD (79 responders/72 non-responders), 3 PsO (40 responders/11 non-responders) and 2 RA (16 responders/6 non-responders) datasetswere selected. After the separate pre-processing of each dataset, 4 separate meta-analyses were conducted; three disease-specific and a single combined meta-analysis on the disease-specific results. The MetaVolcano R package (v.1.8.0) was utilized for a random-effects meta-analysis through theRestricted Maximum Likelihood (RELM) method. The top 1% of the most consistently perturbed genes in the included datasets was highlighted through the TopConfects approach while maintaining a 5% False Discovery Rate (FDR). Genes were considered as Differentialy Expressed (DEGs) as those with P ≤ 0.05, |log2(FC)| ≥ log2(1.25) and perturbed in at least 75% of the included datasets. Over-representation analysis was performed using Gene Ontology and Reactome Pathways for both up- and down-regulated genes in all 4 performed meta-analyses. Protein-Protein interaction networks were also incorporated in the subsequentanalyses with STRING v11.5 and Cytoscape v3.9. Disease-specific meta-analyses detected multiple distinct pro-inflammatory and immune-related down-regulated genes for each disease, such asNFKBIA, IL36, and IRAK1, respectively. Pathway analyses revealed unique and shared pathways between each disease, such as Neutrophil Degranulation and Signaling by Interleukins. The combined meta-analysis unveiled 436 DEGs, 86 out of which were up- and 350 down-regulated, confirming the aforementioned shared pathways and genes, as well as uncovering genes that participate in anti-inflammatory pathways, namely IL-10 signaling. The identification of key biological pathways and regulatory elements is imperative for the accurate prediction of the patient’s response to biological drugs. Meta-analysis of such gene expression data could aid the challenging approach to unravel the complex interactions implicated in the response to anti-TNFα therapy in patients with PsO, IBD, and RA, as well as distinguish gene clusters and pathways that are altered through this heterogeneous phenotype.

Keywords: anti-TNFα, autoimmune, meta-analysis, microarrays

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Authors: Jia H. Wong, Jingli Zhang, Habsah Mohamad, Iswatun H. Abdullah Ripain, Muhammad Bilal, Amelia J. Lloyd, Abdul A. Mohamed Yusoff, Jafri M. Abdullah

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Epilepsy is one of the most common neurological diseases affecting more than 50 million of people worldwide. Epilepsy is a state of recurrent, spontaneous seizures with multiple syndromes and symptoms of different causes of brain dysfunction, prognosis, and treatments; characterized by transient, occasional and stereotyped interruptions of behavior whereby the excitatory-inhibitory activities within the central nervous system (CNS) are thrown out of balance due to various kinds of interferences. The goal of antiepileptic treatment is to enable patients to be free from seizures or to achieve control of seizures through surgical treatment and/or pharmacotherapy. Pharmacotherapy through AED plays an important role especially in countries with epilepsy treatment gap due to costs and availability of health facilities, skills and resources, yet there are about one-third of the people with epilepsy have drug-resistant seizures. Hence, this poses considerable challenges to the healthcare system and the effort in providing cost-effective treatment as well as the search for alternatives to treatment and management of epilepsy. Enhancement of γ-aminobutyric acid (GABA)-mediated inhibitory neurotransmission is one of the key mechanisms of actions of antiepileptic drugs. GABA type > a receptors (GABAAR) are ligand-gated ion channels that mediate rapid inhibitory neurotransmission upon the binding of GABA with a heteropentameric structure forming a central pore that is permeable to the influx of chloride ions in its activated state. The major isoform of GABAA receptors consists of two α1, two β2, and one γ2 subunit. It is the most abundantly expressed combinations in the brain and the most commonly researched through Xenopus laevis oocytes. With the advancing studies on ethnomedicine and traditional treatments using medicinal plants, increasing evidence reveal that spice and herb plants with medicinal properties play an important role in the treatment of ailments within communities across different cultures. Capsaicin is the primary natural capsaicinoid in hot peppers of plant genus Capsicum, consist of an aromatic ring, an amide linkage and a hydrophobic side chain. The study showed that capsaicins conferred neuroprotection in status epilepticus mouse models through anti-ictogenic, hypothermic, antioxidative, anti-inflammatory, and anti-apoptotic actions in a dose-dependent manner. In this study, five capsaicin derivatives were tested for their ability to increase the GABA-induced chloride current on α1β2γ2S of GABAAR expressed on Xenopus laevis oocytes using the method of two-microelectrode voltage clamp. Two of the capsaicin derivatives, IS5 (N-(4-hydroxy-3-methoxybenzyl)-3-methylbutyramide) and IS10 (N-(4-hydroxy-3-methoxybenzyl)-decanamide) at a concentration of 30µM were able to significantly increase the GABA-induced chloride current with p=0.002 and p=0.026 respectively. This study were able to show the enhancement effect of two capsaicin derivatives with moderate length of hydrocarbon chain on this receptor subtype, revealing the promising inhibitory activity of capsaicin derivatives through enhancement of GABA-induced chloride current and further investigations should be carried out to verify its antiepileptic effects in animal models.

Keywords: α1β2γ2 GABAA receptors, α1β2γ2S, antiepileptic, capsaicin derivatives, two-microelectrode voltage clamp, Xenopus laevis oocytes

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

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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: 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: Pallab Datta, Jyotirmoy Chatterjee, Santanu Dhara

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Over the past few years, phosphorous containing polymers have received widespread attention for applications such as high performance optical fibers, flame retardant materials, drug delivery and tissue engineering. Being pentavalent, phosphorous can exist in different chemical environments in these polymers which increase their versatility. In human biochemistry, phosphorous based compounds exert their functions both in soluble and insoluble form occurring as inorganic or as organophosphorous compounds. Specifically in case of biomacromolecules, phosphates are critical for functions of DNA, ATP, phosphoproteins, phospholipids, phosphoglycans and several coenzymes. Inspired by the role of phosphorous in functional biomacromolecules, design and synthesis of biomimetic materials are thus carried out by several authors to study macromolecular function or as substitutes in clinical tissue regeneration conditions. In addition, many regulatory signals of the body are controlled by phoshphorylation of key proteins present either in form of growth factors or matrix-bound scaffold proteins. This inspires works on synthesis of phospho-peptidomimetic amino acids for understanding key signaling pathways and this is extended to obtain molecules with potentially useful biological properties. Apart from above applications, phosphate groups bound to polymer backbones have also been demonstrated to improve function of osteoblast cells and augment performance of bone grafts. Despite the advantages of phosphate grafting, however, there is limited understanding on effect of degree of phosphorylation on macromolecular physicochemical and/or biological properties. Such investigations are necessary to effectively translate knowledge of macromolecular biochemistry into relevant clinical products since they directly influence processability of these polymers into suitable scaffold structures and control subsequent biological response. Amongst various techniques for fabrication of biomimetic scaffolds, nanofibrous scaffolds fabricated by electrospinning technique offer some special advantages in resembling the attributes of natural extracellular matrix. Understanding changes in physico-chemical properties of polymers as function of phosphorylation is therefore going to be crucial in development of nanofiber scaffolds based on phosphorylated polymers. The aim of the present work is to investigate the effect of phosphorous grafting on the electrospinning behavior of polymers with aim to obtain biomaterials for bone regeneration applications. For this purpose, phosphorylated derivatives of two polymers of widely different electrospinning behaviors were selected as starting materials. Poly(vinyl alcohol) is a conveniently electrospinnable polymer at different conditions and concentrations. On the other hand, electrospinning of chitosan backbone based polymers have been viewed as a critical challenge. The phosphorylated derivatives of these polymers were synthesized, characterized and electrospinning behavior of various solutions containing these derivatives was compared with electrospinning of pure poly (vinyl alcohol). In PVA, phosphorylation adversely impacted electrospinnability while in NMPC, higher phosphate content widened concentration range for nanofiber formation. Culture of MG-63 cells on electrospun nanofibers, revealed that degree of phosphate modification of a polymer significantly improves cell adhesion or osteoblast function of cultured cells. It is concluded that improvement of cell response parameters of nanofiber scaffolds can be attained as a function of controlled degree of phosphate grafting in polymeric biomaterials with implications for bone tissue engineering applications.

Keywords: bone regeneration, chitosan, electrospinning, phosphorylation

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Authors: Rob Schindler

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Industry-standard methods of mitigating erosion of seabed sediments rely on ‘hard engineering’ approaches which have numerous environmental shortcomings: (1) direct loss of habitat by smothering of benthic species, (2) disruption of sediment transport processes, damaging geomorphic and ecosystem functionality (3) generation of secondary erosion problems, (4) introduction of material that may propagate non-local species, and (5) provision of pathways for the spread of invasive species. Recent studies have also revealed the importance of biological cohesion, the result of naturally occurring extra-cellular polymeric substances (EPS), in stabilizing natural sediments. Mimicking the strong bonding kinetics through the deliberate addition of EPS to sediments – henceforth termed ‘biostabilisation’ - offers a means in which to mitigate against erosion induced by structures or episodic increases in hydrodynamic forcing (e.g. storms and floods) whilst avoiding, or reducing, hard engineering. Here we present unique experiments that systematically examine how biostabilisation reduces scour around a monopile in a current, a first step to realizing the potential of this new method of scouring reduction for a wide range of engineering purposes in aquatic substrates. Experiments were performed in Plymouth University’s recirculating sediment flume which includes a recessed scour pit. The model monopile was 0.048 m in diameter, D. Assuming a prototype monopile diameter of 2.0 m yields a geometric ratio of 41.67. When applied to a 10 m prototype water depth this yields a model depth, d, of 0.24 m. The sediment pit containing the monopile was filled with different biostabilised substrata prepared using a mixture of fine sand (D50 = 230 μm) and EPS (Xanthan gum). Nine sand-EPS mixtures were examined spanning EPS contents of 0.0% < b0 < 0.50%. Scour development was measured using a laser point gauge along a 530 mm centreline at 10 mm increments at regular periods over 5 h. Maximum scour depth and excavated area were determined at different time steps and plotted against time to yield equilibrium values. After 5 hours the current was stopped and a detailed scan of the final scour morphology was taken. Results show that increasing EPS content causes a progressive reduction in the equilibrium depth and lateral extent of scour, and hence excavated material. Very small amounts equating to natural communities (< 0.1% by mass) reduce scour rate, depth and extent of scour around monopiles. Furthermore, the strong linear relationships between EPS content, equilibrium scour depth, excavation area and timescales of scouring offer a simple index on which to modify existing scour prediction methods. We conclude that the biostabilisation of sediments with EPS may offer a simple, cost-effective and ecologically sensitive means of reducing scour in a range of contexts including OWFs, bridge piers, pipeline installation, and void filling in rock armour. Biostabilisation may also reduce economic costs through (1) Use of existing site sediments, or waste dredged sediments (2) Reduced fabrication of materials, (3) Lower transport costs, (4) Less dependence on specialist vessels and precise sub-sea assembly. Further, its potential environmental credentials may allow sensitive use of the seabed in marine protection zones across the globe.

Keywords: biostabilisation, EPS, marine, scour

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