Search results for: clinical prediction rule

Authors: Mohammad Hossain Validad

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Background and Aim: Epidemic keratoconjunctivitis is a type of conjunctivitis caused by adenoviruses that can spread rapidly through direct and indirect contact. The aim of this study was to evaluate the therapeutic effects of Povidone-Iodine 0.4% and 0.2% in improving the symptoms and signs of patients with epidemic keratoconjunctivitis. Materials and Methods: In this clinical trial study, 60 patients with a mean age of 27.8±8.4 years who were eligible for inclusion criteria were randomly divided into three groups. The first group received eye drops of Povidone-Iodine 0.4% and betamethasone 0.1%, the second group received PovidoneIodine 0.2% and betamethasone 0.1% and the third group received betamethasone 0.1%. Follow-ups were on the first, fourth, seventh and tenth days after starting treatment. Parameters examined at each examination were hyperaemia, mucopurulent discharge, eyelid edema, hemorrhage, and subepithelial infiltration. Results: The results showed that mucopurulent discharge on the fourth day of the examination (P = 0.005) and the seventh day of the examination (P = 0.001) were significantly different in the three treatment groups. Sub-epithelial infiltration on the tenth day after treatment did not show a significant difference in the 3 groups (P = 0.287). Conclusion: Based on the results of this study, Povidone-Iodine is more effective in relieving some of signs of EKC, such as reduced mucopurulent discharge than steroids alone.

Keywords: EKC, topical bethadine, adenovirus, sub epithelial opacity

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Authors: Marc Solé, Francesc Giné, Magda Valls, Nina Bijedic

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What people say on social media has turned into a rich source of information to understand social behavior. Specifically, the growing use of Twitter social media for political communication has arisen high opportunities to know the opinion of large numbers of politically active individuals in real time and predict the global political tendencies of a specific country. It has led to an increasing body of research on this topic. The majority of these studies have been focused on polarized political contexts characterized by only two alternatives. Unlike them, this paper tackles the challenge of forecasting Spanish political trends, characterized by multiple political parties, by means of analyzing the Twitters Users political tendency. According to this, a new strategy, named Tweets Analysis Strategy (TAS), is proposed. This is based on analyzing the users tweets by means of discovering its sentiment (positive, negative or neutral) and classifying them according to the political party they support. From this individual political tendency, the global political prediction for each political party is calculated. In order to do this, two different strategies for analyzing the sentiment analysis are proposed: one is based on Positive and Negative words Matching (PNM) and the second one is based on a Neural Networks Strategy (NNS). The complete TAS strategy has been performed in a Big-Data environment. The experimental results presented in this paper reveal that NNS strategy performs much better than PNM strategy to analyze the tweet sentiment. In addition, this research analyzes the viability of the TAS strategy to obtain the global trend in a political context make up by multiple parties with an error lower than 23%.

Keywords: political tendency, prediction, sentiment analysis, Twitter

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Authors: Peter Collett, Mike Pynn, Haseeb Ur Rahman

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For the last few years across the UK there has been a push towards implementing treatment escalation plans (TEP) for every patient admitted to hospital. This is a paper form which is completed by a junior doctor then countersigned by the consultant responsible for the patient's care. It is designed to address what level of care is appropriate for the patient in question at point of entry to hospital. It helps decide whether the patient would benefit for ward based, high dependency or intensive care. They are completed to ensure the patient's best interests are maintained and aim to facilitate difficult decisions which may be required at a later date. For example, a frail patient with significant co-morbidities, unlikely to survive a pathology requiring an intensive care admission is admitted to hospital the decision can be made early to state the patient would not benefit from an ICU admission. This decision can be reversed depending on the clinical course of the patient's admission. It promotes discussions with the patient regarding their wishes to receive certain levels of healthcare. This poster describes the steps taken in the Aneurin Bevan University Health Board (ABUHB) when implementing the TEP form. The team implementing the TEP form campaigned for it's use to the board of directors. The directors were eager to hear of experiences of other health boards who had implemented the TEP form. The team presented the data produced in a number of health boards and demonstrated the proposed form. Concern was raised regarding the legalities of the form and that it could upset patients and relatives if the form was not explained properly. This delayed the effectuation of the TEP form and further research and discussion would be required. When COVID 19 reached the UK the National Institute for Health and Clinical Excellence issued guidance stating every patient admitted to hospital should be issued a TEP form. The TEP form was accelerated through the vetting process and was approved with immediate effect. The TEP form in ABUHB has now been in circulation for a month. An audit investigating it's uptake and a survey gathering opinions have been conducted.

Keywords: acute medicine, clinical governance, intensive care, patient centered decision making

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Authors: Syeda Sahra, Abdullah Jahangir, Rachelle Hamadi, Ahmad Jahangir, Allison Glaser

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Background: Antimicrobial resistance is on the rise. The use of redundant and inappropriate antibiotics is contributing to recurrent infections and resistance. Newer antibiotics with more robust coverage for gram-negative bacteria are in great demand for complicated urinary tract infections (cUTIs), complicated intra-abdominal infections (cIAIs), hospital-acquired bacterial pneumonia (H.A.B.P.), and ventilator-associated bacterial pneumonia (V.A.B.P.). Objective: We performed this meta-analysis to evaluate the efficacy and safety profile of a new antibiotic, Imipenem/cilastatin/relebactam, compared to other broad-spectrum antibiotics for complicated infections. Search Strategy: We conducted a systemic review search on PubMed, Embase, and Central Cochrane Registry. Selection Criteria: We included randomized clinical trials (R.C.T.s) with the standard of care as comparator arm with Imipenem/cilastatin/relebactam as intervention arm. Analysis: For continuous variables, the mean difference was used. For discrete variables, we used the odds ratio. For effect sizes, we used a confidence interval of 95%. A p-value of less than 0.05 was used for statistical significance. Analysis was done using a random-effects model irrespective of heterogeneity. Heterogeneity was evaluated using the I2 statistic. Results: The authors observed similar efficacy at clinical and microbiologic response levels on early follow-up and late follow-up compared to the established standard of care. The incidence of drug-related adverse events, serious adverse events, and drug discontinuation due to adverse events were comparable across both groups. Conclusion: Imipenem/cilastatin/relebactam has a non-inferior safety and efficacy profile compared to peer antibiotics to treat severe bacterial infections (cUTIs, cIAIs, H.A.B.P., V.A.B.P.).

Keywords: bacterial pneumonia, complicated intra-abdominal infections, complicated urinary tract infection, Imipenem, cilastatin, relebactam

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Authors: Nareshkumar Harale, B. B. Meshram

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The continued exponential growth of successful cyber intrusions against today’s businesses has made it abundantly clear that traditional perimeter security measures are no longer adequate and effective. We evolved the network trust architecture from trust-untrust to Zero-Trust, With Zero Trust, essential security capabilities are deployed in a way that provides policy enforcement and protection for all users, devices, applications, data resources, and the communications traffic between them, regardless of their location. Information exchange over the Internet, in spite of inclusion of advanced security controls, is always under innovative, inventive and prone to cyberattacks. TCP/IP protocol stack, the adapted standard for communication over network, suffers from inherent design vulnerabilities such as communication and session management protocols, routing protocols and security protocols are the major cause of major attacks. With the explosion of cyber security threats, such as viruses, worms, rootkits, malwares, Denial of Service attacks, accomplishing efficient and effective intrusion detection and prevention is become crucial and challenging too. In this paper, we propose a design and analysis model for next generation network intrusion detection and protection system as part of layered security strategy. The proposed system design provides intrusion detection for wide range of attacks with layered architecture and framework. The proposed network intrusion classification framework deals with cyberattacks on standard TCP/IP protocol, routing protocols and security protocols. It thereby forms the basis for detection of attack classes and applies signature based matching for known cyberattacks and data mining based machine learning approaches for unknown cyberattacks. Our proposed implemented software can effectively detect attacks even when malicious connections are hidden within normal events. The unsupervised learning algorithm applied to network audit data trails results in unknown intrusion detection. Association rule mining algorithms generate new rules from collected audit trail data resulting in increased intrusion prevention though integrated firewall systems. Intrusion response mechanisms can be initiated in real-time thereby minimizing the impact of network intrusions. Finally, we have shown that our approach can be validated and how the analysis results can be used for detecting and protection from the new network anomalies.

Keywords: network intrusion detection, network intrusion prevention, association rule mining, system analysis and design

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Authors: Yuexin Liu, Gordon B. Mills, Russell R. Broaddus, John N. Weinstein

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The lethality of endometrioid endometrial cancer (EEC) is primarily attributable to the high-stage diseases. However, there are no available biomarkers that predict EEC patient staging at the time of diagnosis. We aim to develop a predictive scheme to help in this regards. Using reverse-phase protein array expression profiles for 210 EEC cases from The Cancer Genome Atlas (TCGA), we constructed a Protein Scoring of EEC Staging (PSES) scheme for surgical stage prediction. We validated and evaluated its diagnostic potential in an independent cohort of 184 EEC cases obtained at MD Anderson Cancer Center (MDACC) using receiver operating characteristic curve analyses. Kaplan-Meier survival analysis was used to examine the association of PSES score with patient outcome, and Ingenuity pathway analysis was used to identify relevant signaling pathways. Two-sided statistical tests were used. PSES robustly distinguished high- from low-stage tumors in the TCGA cohort (area under the ROC curve [AUC]=0.74; 95% confidence interval [CI], 0.68 to 0.82) and in the validation cohort (AUC=0.67; 95% CI, 0.58 to 0.76). Even among grade 1 or 2 tumors, PSES was significantly higher in high- than in low-stage tumors in both the TCGA (P = 0.005) and MDACC (P = 0.006) cohorts. Patients with positive PSES score had significantly shorter progression-free survival than those with negative PSES in the TCGA (hazard ratio [HR], 2.033; 95% CI, 1.031 to 3.809; P = 0.04) and validation (HR, 3.306; 95% CI, 1.836 to 9.436; P = 0.0007) cohorts. The ErbB signaling pathway was most significantly enriched in the PSES proteins and downregulated in high-stage tumors. PSES may provide clinically useful prediction of high-risk tumors and offer new insights into tumor biology in EEC.

Keywords: endometrial carcinoma, protein, protein scoring of EEC staging (PSES), stage

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Authors: Anuruddha Jayasuriya, Thanakorn Pheeraphan

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In this paper, a review of different mathematical models which can be used as prediction tools to assess the time to crack reinforced concrete (RC) due to corrosion is investigated. This investigation leads to an experimental study to validate a selected prediction model. Most of these mathematical models depend upon the mechanical behaviors, chemical behaviors, electrochemical behaviors or geometric aspects of the RC members during a corrosion process. The experimental program is designed to verify the accuracy of a well-selected mathematical model from a rigorous literature study. Fundamentally, the experimental program exemplifies both one-dimensional chloride diffusion using RC squared slab elements of 500 mm by 500 mm and two-dimensional chloride diffusion using RC squared column elements of 225 mm by 225 mm by 500 mm. Each set consists of three water-to-cement ratios (w/c); 0.4, 0.5, 0.6 and two cover depths; 25 mm and 50 mm. 12 mm bars are used for column elements and 16 mm bars are used for slab elements. All the samples are subjected to accelerated chloride corrosion in a chloride bath of 5% (w/w) sodium chloride (NaCl) solution. Based on a pre-screening of different models, it is clear that the well-selected mathematical model had included mechanical properties, chemical and electrochemical properties, nature of corrosion whether it is accelerated or natural, and the amount of porous area that rust products can accommodate before exerting expansive pressure on the surrounding concrete. The experimental results have shown that the selected model for both one-dimensional and two-dimensional chloride diffusion had ±20% and ±10% respective accuracies compared to the experimental output. The half-cell potential readings are also used to see the corrosion probability, and experimental results have shown that the mass loss is proportional to the negative half-cell potential readings that are obtained. Additionally, a statistical analysis is carried out in order to determine the most influential factor that affects the time to corrode the reinforcement in the concrete due to chloride diffusion. The factors considered for this analysis are w/c, bar diameter, and cover depth. The analysis is accomplished by using Minitab statistical software, and it showed that cover depth is the significant effect on the time to crack the concrete from chloride induced corrosion than other factors considered. Thus, the time predictions can be illustrated through the selected mathematical model as it covers a wide range of factors affecting the corrosion process, and it can be used to predetermine the durability concern of RC structures that are vulnerable to chloride exposure. And eventually, it is further concluded that cover thickness plays a vital role in durability in terms of chloride diffusion.

Keywords: accelerated corrosion, chloride diffusion, corrosion cracks, passivation layer, reinforcement corrosion

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Authors: Tahani Aljohani, Jialin Yu, Alexandra. I. Cristea

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The more an educational system knows about a learner, the more personalised interaction it can provide, which leads to better learning. However, asking a learner directly is potentially disruptive, and often ignored by learners. Especially in the booming realm of MOOC Massive Online Learning platforms, only a very low percentage of users disclose demographic information about themselves. Thus, in this paper, we aim to predict learners’ demographic characteristics, by proposing an approach using linguistically motivated Deep Learning Architectures for Learner Profiling, particularly targeting gender prediction on a FutureLearn MOOC platform. Additionally, we tackle here the difficult problem of predicting the gender of learners based on their comments only – which are often available across MOOCs. The most common current approaches to text classification use the Long Short-Term Memory (LSTM) model, considering sentences as sequences. However, human language also has structures. In this research, rather than considering sentences as plain sequences, we hypothesise that higher semantic - and syntactic level sentence processing based on linguistics will render a richer representation. We thus evaluate, the traditional LSTM versus other bleeding edge models, which take into account syntactic structure, such as tree-structured LSTM, Stack-augmented Parser-Interpreter Neural Network (SPINN) and the Structure-Aware Tag Augmented model (SATA). Additionally, we explore using different word-level encoding functions. We have implemented these methods on Our MOOC dataset, which is the most performant one comparing with a public dataset on sentiment analysis that is further used as a cross-examining for the models' results.

Keywords: deep learning, data mining, gender predication, MOOCs

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Authors: Rishabh Sharma

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The main design parameter of WSN (wireless sensor network) is the energy consumption. To compensate this parameter, hierarchical clustering is a technique that assists in extending duration of the networks life by efficiently consuming the energy. This paper focuses on dealing with the WSNs and the FIS (fuzzy interface system) which are deployed to enhance the BEENISH protocol. The node energy, mobility, pause time and density are considered for the selection of CH (cluster head). The simulation outcomes exhibited that the projected system outperforms the traditional system with regard to the energy utilization and number of packets transmitted to sink.

Keywords: wireless sensor network, sink, sensor node, routing protocol, fuzzy rule, fuzzy inference system

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Authors: Fatma Ahmed, Heba Mostafa, Bassem Ramdan, Azza El-Soussi

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Background: World Health Organization stated that by 2020 cardiac disease will be the number one cause of death worldwide and estimates that 25 million people per year will suffer from heart disease. Cardiac surgery is considered an effective treatment for severe forms of cardiovascular diseases that cannot be treated by medical treatment or cardiac interventions. In spite of the benefits of cardiac surgery, it is considered a major stressful experience for patients who are candidate for surgery. Prehabilitation can decrease incidences of postoperative complications as it prepares patients for surgical stress through enhancing their defenses to meet the demands of surgery. When patients anticipate the postoperative sequence of events, they will prepare themselves to act certain behaviors, identify their roles and actively participate in their own recovery, therefore, anxiety levels are decreased and functional capacity is enhanced. Prehabilitation programs can comprise interventions that include physical exercise, psychological prehabilitation, nutritional optimization and risk factor modification. Physical exercises are associated with improvements in the functioning of the various physiological systems, reflected in increased functional capacity, improved cardiac and respiratory functions and make patients fit for surgical intervention. Prehabilitation programs should also prepare patients psychologically in order to cope with stress, anxiety and depression associated with postoperative pain, fatigue, limited ability to perform the usual activities of daily living through acting in a healthy manner. Notwithstanding the benefits of psychological preparations, there are limited studies which investigated the effect of psychological prehabilitation to confirm its effect on psychological, quality of life and physiological outcomes of patients who had undergone cardiac surgery. Aim of the study: The study aims to determine the effect of prehabilitation interventions on outcomes of patients undergoing cardiac surgeries. Methods: Quasi experimental study design was used to conduct this study. Sixty eligible and consenting patients were recruited and divided into two groups: control and intervention group (30 participants in each). One tool namely emotional, physiological, clinical, cognitive and functional capacity outcomes of prehabilitation intervention assessment tool was utilized to collect the data of this study. Results: Data analysis showed significant improvement in patients' emotional state, physiological and clinical outcomes (P < 0.000) with the use of prehabilitation interventions. Conclusions: Cardiac prehabilitation in the form of providing information about surgery, circulation exercise, deep breathing exercise, incentive spirometer training and nutritional education implemented daily by patients scheduled for elective open heart surgery one week before surgery have been shown to improve patients' emotional state, physiological and clinical outcomes.

Keywords: emotional recovery, clinical recovery, coronary artery bypass grafting patients, prehabilitation

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Authors: Patricia Abigail B. Miranda, Imelda A. Luna

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Introduction: COVID-19 infection is a novel viral illness that began as a local epidemic in December 2019 in Wuhan, China which quickly emerged into a pandemic by February 2020. The virus causes a spectrum of signs and symptoms, ranging from mild upper respiratory symptoms to acute respiratory distress syndrome, which may lead to death. Among children and neonates, those afflicted with the disease may present asymptomatically or with mild symptoms. To date, there has been limited local data that describes the outcomes of the growing number of COVID-19 cases, specifically in neonates. Methods: A cross-sectional study was conducted to determine the outcomes of neonates born to COVID-19 Positive Mothers from March 2020 until June 2022. The prevalence of COVID-19 among these neonates was also determined. Results: COVID-positive prevalence after 24 hours of life is at 8%, while prevalence after 48 hours among those who still underwent testing was at 13.51%. Moreover, among those COVID-19-negative neonates who had symptoms, they mostly presented with tachypnea (5.7%). The prevalence of complications among COVID-19-negative neonates delivered to COVID-19-positive mothers is 22.7%. Conclusion: Neonates born to COVID-19-positive mothers who yielded positive COVID-19 results are generally asymptomatic. Moreover, there are no associated mortalities among those who yielded positive results.

Keywords: COVID-19, neonates, outcomes, clinical profile

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Authors: Adel Alblihy, Reem Ali, Mashael Algethami, Ahmed Shoqafi, Michael S. Toss, Juliette Brownlie, Natalie J. Tatum, Ian Hickson, Paloma Ordonez Moran, Anna Grabowska, Jennie N. Jeyapalan, Nigel P. Mongan, Emad A. Rakha, Srinivasan Madhusudan

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Platinum resistance is a clinical challenge in ovarian cancer. Platinating agents induce DNA damage which activate Mre11 nuclease directed DNA damage signalling and response (DDR). Upregulation of DDR may promote chemotherapy resistance. Here we have comprehensively evaluated Mre11 in epithelial ovarian cancers. In clinical cohort that received platinum- based chemotherapy (n=331), Mre11 protein overexpression was associated with aggressive phenotype and poor progression free survival (PFS) (p=0.002). In the ovarian cancer genome atlas (TCGA) cohort (n=498), Mre11 gene amplification was observed in a subset of serous tumours (5%) which correlated highly with Mre11 mRNA levels (p<0.0001). Altered Mre11 levels was linked with genome wide alterations that can influence platinum sensitivity. At the transcriptomic level (n=1259), Mre11 overexpression was associated with poor PFS (p=0.003). ROC analysis showed an area under the curve (AUC) of 0.642 for response to platinum-based chemotherapy. Pre-clinically, Mre11 depletion by gene knock down or blockade by small molecule inhibitor (Mirin) reversed platinum resistance in ovarian cancer cells and in 3D spheroid models. Importantly, Mre11 inhibition was synthetically lethal in platinum sensitive XRCC1 deficient ovarian cancer cells and 3D-spheroids. Selective cytotoxicity was associated with DNA double strand break (DSB) accumulation, S-phase cell cycle arrest and increased apoptosis. We conclude that pharmaceutical development of Mre11 inhibitors is a viable clinical strategy for platinum sensitization and synthetic lethality in ovarian cancer.

Keywords: MRE11; XRCC1, ovarian cancer, platinum sensitization, synthetic lethality

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Authors: Navneet Singh Deora, Aastha Deswal, H. N. Mishra

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Pasta is one of the most widely consumed food products around the world. Rapid determination of the moisture content in pasta will assist food processors to provide online quality control of pasta during large scale production. Rapid Fourier transform near-infrared method (FT-NIR) was developed for determining moisture content in pasta. A calibration set of 150 samples, a validation set of 30 samples and a prediction set of 25 samples of pasta were used. The diffuse reflection spectra of different types of pastas were measured by FT-NIR analyzer in the 4,000-12,000 cm-1 spectral range. Calibration and validation sets were designed for the conception and evaluation of the method adequacy in the range of moisture content 10 to 15 percent (w.b) of the pasta. The prediction models based on partial least squares (PLS) regression, were developed in the near-infrared. Conventional criteria such as the R2, the root mean square errors of cross validation (RMSECV), root mean square errors of estimation (RMSEE) as well as the number of PLS factors were considered for the selection of three pre-processing (vector normalization, minimum-maximum normalization and multiplicative scatter correction) methods. Spectra of pasta sample were treated with different mathematic pre-treatments before being used to build models between the spectral information and moisture content. The moisture content in pasta predicted by FT-NIR methods had very good correlation with their values determined via traditional methods (R2 = 0.983), which clearly indicated that FT-NIR methods could be used as an effective tool for rapid determination of moisture content in pasta. The best calibration model was developed with min-max normalization (MMN) spectral pre-processing (R2 = 0.9775). The MMN pre-processing method was found most suitable and the maximum coefficient of determination (R2) value of 0.9875 was obtained for the calibration model developed.

Keywords: FT-NIR, pasta, moisture determination, food engineering

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Authors: Kayode Julius Oni

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Without mincing words, democracy is by far the most popular form of government in the world today. No matter how we look at it, and regardless of the variant, most leaders in the world today wish to be seen or labeled as Democrats. Perhaps, its attractions in terms of freedom of allocation, accountability, smooth successions of leadership and a lot more, account for its appeal to the ordinary people. The governance style in Nigeria since 1999 cannot be said to be different from the military. Elections are manipulated, judicial processes abused, and the ordinary people do not have access to the dividends of democracy. The paper seeks to address the existing failures experienced under democratic rule in Nigeria which have to transcend into violation of human rights in the conduct of government business. The paper employs the primary and secondary sources of data collection, and it is highly descriptive and critical.

Keywords: democracy, human rights, Nigeria, politics, republic

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Authors: Umamaheswari Shanmugam, Silvia Ronchi

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Software, artificial intelligence, and machine learning can improve healthcare through innovative and advanced technologies that can use the large amount and variety of data generated during healthcare services every day; one of the significant advantages of these new technologies is the ability to get experience and knowledge from real-world use and to improve their performance continuously. Healthcare systems and institutions can significantly benefit because the use of advanced technologies improves the efficiency and efficacy of healthcare. Software-defined as a medical device, is stand-alone software that is intended to be used for patients for one or more of these specific medical intended uses: - diagnosis, prevention, monitoring, prediction, prognosis, treatment or alleviation of a disease, any other health conditions, replacing or modifying any part of a physiological or pathological process–manage the received information from in vitro specimens derived from the human samples (body) and without principal main action of its principal intended use by pharmacological, immunological or metabolic definition. Software qualified as medical devices must comply with the general safety and performance requirements applicable to medical devices. These requirements are necessary to ensure high performance and quality and protect patients' safety. The evolution and the continuous improvement of software used in healthcare must consider the increase in regulatory requirements, which are becoming more complex in each market. The gap between these advanced technologies and the new regulations is the biggest challenge for medical device manufacturers. Regulatory requirements can be considered a market barrier, as they can delay or obstacle the device's approval. Still, they are necessary to ensure performance, quality, and safety. At the same time, they can be a business opportunity if the manufacturer can define the appropriate regulatory strategy in advance. The abstract will provide an overview of the current regulatory framework, the evolution of the international requirements, and the standards applicable to medical device software in the potential market all over the world.

Keywords: artificial intelligence, machine learning, SaMD, regulatory, clinical evaluation, classification, international requirements, MDR, 510k, PMA, IMDRF, cyber security, health care systems

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Authors: Pouya Karimi, Ramin Gasemi Shayan, Parsa Sheykhzade

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Ease shotgun DNA sequencing is changing the microbial sciences. Sequencing instruments are compelling to the point that example planning is currently the key constraining element. Here, we present a microfluidic test readiness stage that incorporates the key strides in cells to grouping library test groundwork for up to 96 examples and decreases DNA input prerequisites 100-overlay while keeping up or improving information quality. The universally useful microarchitecture we show bolsters work processes with subjective quantities of response and tidy up or catch steps. By decreasing the example amount necessities, we empowered low-input (∼10,000 cells) entire genome shotgun (WGS) sequencing of Mycobacterium tuberculosis and soil miniaturized scale settlements with prevalent outcomes. We additionally utilized the upgraded throughput to succession ∼400 clinical Pseudomonas aeruginosa libraries and exhibit magnificent single-nucleotide polymorphism discovery execution that clarified phenotypically watched anti-toxin opposition. Completely coordinated lab-on-chip test arrangement beats specialized boundaries to empower more extensive organization of genomics across numerous fundamental research and translational applications.

Keywords: clinical microbiology, DNA, microbiology, microbial genomics

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Authors: Mohd Asharf Ganie, Aafia Rashid, Mohd Afzal Zargar, Showkat Ali Zargar, Syed Mudasar, Tabasum Parvaiz, Zafar Amin Shah

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Accumulating evidence suggests that Vitamin D deficiency (VDD) might at least contribute to the metabolic co-morbidities in PCOS. Hence, we aimed to study the effect of vitamin D supplementation in co-prescription with insulin sensitizers like metformin and pioglitazone on clinical, hormonal and metabolic parameters in women with PCOS. In this open label randomized, controlled trial a total of 120 women with PCOS diagnosis (AE-PCOS 2009 Criteria) were assigned to four treatment groups (n= 30 in each): group I (metformin 1 gm/day in combination with cholecalciferol 4000 IU/day), group II (pioglitazone 30 mg/day in combination with cholecalciferol 4000 IU/day), group III (metformin 1 gm /day) and group IV (pioglitazone 30 mg/day). Vitamin D supplementation was given as 60,000 units every two weeks for 24 weeks. All the subjects were routinely evaluated for clinical, biochemical, hormonal and insulin sensitivity parameters in addition to various safety parameters especially serum calcium levels at baseline and after 24 weeks of the treatment. Our results indicate that 95.5% of PCOS women were vitamin D deficient at baseline. Serum 25 (OH) D levels increased significantly (p < 0.001) in groups I and II without any adverse effects after 24 weeks of oral administration of 4000 IU cholecalciferol daily. However, serum 25 (OH) D levels remained unchanged in group III and IV. By six months, number of menstrual cycles per year increased whereas Ferriman-Gallwey score, serum total testosterone and HOMA-IR decreased significantly (P < 0.001) in the treatment groups supplemented with cholecalciferol as compared to those treated either drug alone. No significant beneficial changes were observed on weight, BMI, blood pressure, glucose tolerance and serum lipids in any of the groups supplemented with cholecalciferol. We conclude that daily dose of 4000 IU cholecalciferol might be a useful adjunct in complex treatment of PCOS with fewer adverse events. Furthermore, pioglitazone and cholecalciferol combination seems to be marginally better although there was no statistical significance.

Keywords: PCOS, vitamin D supplementation, insulin resistance, spironolactone, metformin, pioglitazone

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Authors: Tuula Heinonen, Wilhelm Gaus

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At present safety, assessment starts with animal tests although their predictivity is often poor. Even after extended human use experimental data are often judged as the core information for risk assessment. However, the best opportunity to generate true evidence is to match all available information. Cross matching methodology combines the different fields of knowledge and types of data (e.g. in-vitro and in-vivo experiments, clinical observations, clinical and epidemiological studies, and daily life observations) and gives adequate weight to individual findings. To achieve a consolidated outcome, the information from all available sources is analysed and compared with each other. If single pieces of information fit together a clear picture becomes visible. If pieces of information are inconsistent or contradictory careful consideration is necessary. 'Cross' can be understood as 'orthographic' in geometry or as 'independent' in mathematics. Results coming from different sources bring independent and; therefore, they result in new information. Independent information gives a larger contribution to evidence than results coming repeatedly from the same source. A successful example of cross matching is the assessment of Ginkgo biloba where we were able to come to the conclusive result: Ginkgo biloba leave extract is well tolerated and safe for humans.

Keywords: cross-matching, human use, safety assessment, Ginkgo biloba leave extract

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Authors: Haralabos C. karantonis, Afroditi Michalaki

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High intakes of carbohydrates and fats have been associated with an increased risk of chronic diseases due to the role of postprandial oxidative stress. This pilot nutritional intervention aimed to examine the acute effect of consuming two different types of breadsticks prepared from durum wheat flour mixtures differing in total phenolic content on postprandial inflammatory and oxidant responses in healthy volunteers. A cross-over, controlled, and single-blind clinical trial was designed, and two isocaloric high-fat and high-carbohydrate meals were tested. Serum total, High Density Lipoprotein (HDL)- and Low Density Lipoprotein (LDL)-cholesterol, triglycerides, glucose, C-reactive protein (CRP), uric acid, plasma total antioxidant capacity, and antiplatelet activity were determined in fasting and 30, 60, and 120 min after consumption. The results showed a better postprandial HDL-cholesterol and total antioxidant activity response in the intervention group. The choice of durum wheat flours with higher phenolic content and antioxidant activity is presented as promising for human health, and clinical studies will expand to draw safer conclusions.

Keywords: antioxidant, antiplatelet, durum wheat, nutritional value

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Authors: S.K. Bhandari, E. Veneklaas, L. McCaw, R. Mazanec, K. Whitford, M. Renton

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Eucalyptus marginata, E. diversicolor and Corymbia calophylla form widespread forests in south-west Western Australia (SWWA). These forests have economic and ecological importance, and therefore, tree growth and sustainable management are of high priority. This paper aimed to analyse and model the growth of these species at both stand and individual levels, but this presentation will focus on predicting the growth of E. Marginata at the individual tree level. More specifically, the study wanted to investigate how well individual E. marginata tree growth could be predicted by considering the diameter and height of the tree at the start of the growth period, and whether this prediction could be improved by also accounting for the competition from neighbouring trees in different ways. The study also wanted to investigate how many neighbouring trees or what neighbourhood distance needed to be considered when accounting for competition. To achieve this aim, the Pearson correlation coefficient was examined among competition indices (CIs), between CIs and dbh growth, and selected the competition index that can best predict the diameter growth of individual trees of E. marginata forest managed under different thinning regimes at Inglehope in SWWA. Furthermore, individual tree growth models were developed using simple linear regression, multiple linear regression, and linear mixed effect modelling approaches. Individual tree growth models were developed for thinned and unthinned stand separately. The developed models were validated using two approaches. In the first approach, models were validated using a subset of data that was not used in model fitting. In the second approach, the model of the one growth period was validated with the data of another growth period. Tree size (diameter and height) was a significant predictor of growth. This prediction was improved when the competition was included in the model. The fit statistic (coefficient of determination) of the model ranged from 0.31 to 0.68. The model with spatial competition indices validated as being more accurate than with non-spatial indices. The model prediction can be optimized if 10 to 15 competitors (by number) or competitors within ~10 m (by distance) from the base of the subject tree are included in the model, which can reduce the time and cost of collecting the information about the competitors. As competition from neighbours was a significant predictor with a negative effect on growth, it is recommended including neighbourhood competition when predicting growth and considering thinning treatments to minimize the effect of competition on growth. These model approaches are likely to be useful tools for the conservations and sustainable management of forests of E. marginata in SWWA. As a next step in optimizing the number and distance of competitors, further studies in larger size plots and with a larger number of plots than those used in the present study are recommended.

Keywords: competition, growth, model, thinning

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Authors: Edgar Santoyo, Daniel Perez-Zarate, Agustin Acevedo, Lorena Diaz-Gonzalez, Mirna Guevara

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Four new gas geothermometers have been derived from a multivariate geo chemometric analysis of a geothermal fluid chemistry database, two of which use the natural logarithm of CO₂ and H2S concentrations (mmol/mol), respectively, and the other two use the natural logarithm of the H₂S/H₂ and CO₂/H₂ ratios. As a strict compilation criterion, the database was created with gas-phase composition of fluids and bottomhole temperatures (BHTM) measured in producing wells. The calibration of the geothermometers was based on the geochemical relationship existing between the gas-phase composition of well discharges and the equilibrium temperatures measured at bottomhole conditions. Multivariate statistical analysis together with the use of artificial neural networks (ANN) was successfully applied for correlating the gas-phase compositions and the BHTM. The predicted or simulated bottomhole temperatures (BHTANN), defined as output neurons or simulation targets, were statistically compared with measured temperatures (BHTM). The coefficients of the new geothermometers were obtained from an optimized self-adjusting training algorithm applied to approximately 2,080 ANN architectures with 15,000 simulation iterations each one. The self-adjusting training algorithm used the well-known Levenberg-Marquardt model, which was used to calculate: (i) the number of neurons of the hidden layer; (ii) the training factor and the training patterns of the ANN; (iii) the linear correlation coefficient, R; (iv) the synaptic weighting coefficients; and (v) the statistical parameter, Root Mean Squared Error (RMSE) to evaluate the prediction performance between the BHTM and the simulated BHTANN. The prediction performance of the new gas geothermometers together with those predictions inferred from sixteen well-known gas geothermometers (previously developed) was statistically evaluated by using an external database for avoiding a bias problem. Statistical evaluation was performed through the analysis of the lowest RMSE values computed among the predictions of all the gas geothermometers. The new gas geothermometers developed in this work have been successfully used for predicting subsurface temperatures in high-temperature geothermal systems of Mexico (e.g., Los Azufres, Mich., Los Humeros, Pue., and Cerro Prieto, B.C.) as well as in a blind geothermal system (known as Acoculco, Puebla). The last results of the gas geothermometers (inferred from gas-phase compositions of soil-gas bubble emissions) compare well with the temperature measured in two wells of the blind geothermal system of Acoculco, Puebla (México). Details of this new development are outlined in the present research work. Acknowledgements: The authors acknowledge the funding received from CeMIE-Geo P09 project (SENER-CONACyT).

Keywords: artificial intelligence, gas geochemistry, geochemometrics, geothermal energy

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Authors: Fumihiro Ima, Shinichi Watanabe, Shingo Maeda, Haruna Imai, Hiroki Niimi

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It is important to know growth rate of brain tumors before surgery because it influences treatment planning including not only surgical resection strategy but also adjuvant therapy after surgery. Amide proton transfer (APT) imaging is an emerging molecular magnetic resonance imaging (MRI) technique based on chemical exchange saturation transfer without administration of contrast medium. The underlying assumption in APT imaging of tumors is that there is a close relationship between the proliferative activity of the tumor and mobile protein synthesis. We aimed to evaluate the diagnostic performance of APT imaging of pre-and post-treatment brain tumors. Ten patients with brain tumor underwent conventional and APT-weighted sequences on a 3.0 Tesla MRI before clinical intervention. The maximum and the minimum APT-weighted signals (APTWmax and APTWmin) in each solid tumor region were obtained and compared before and after clinical intervention. All surgical specimens were examined for histopathological diagnosis. Eight of ten patients underwent adjuvant therapy after surgery. Histopathological diagnosis was glioma in 7 patients (WHO grade 2 in 2 patients, WHO grade 3 in 3 patients and WHO grade 4 in 2 patients), meningioma WHO grade1 in 2 patients and primary lymphoma of the brain in 1 patient. High-grade gliomas showed significantly higher APTW-signals than that in low-grade gliomas. APTWmax in one huge parasagittal meningioma infiltrating into the skull bone was higher than that in glioma WHO grade 4. On the other hand, APTWmax in another convexity meningioma was the same as that in glioma WHO grade 3. Diagnosis of primary lymphoma of the brain was possible with APT imaging before pathological confirmation. APTW-signals in residual tumors decreased dramatically within one year after adjuvant therapy in all patients. APT imaging demonstrated excellent diagnostic performance for the planning of surgery and adjuvant therapy of brain tumors.

Keywords: amides, magnetic resonance imaging, brain tumors, cell proliferation

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Authors: Hung-Chi Chang

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For an extended EPQ model with random yield, the existent study revealed that both the disaggregating and consolidating shipment policies for the imperfect quality items are independent of holding cost, and recommended a model with economic benefit by comparing the least total cost for each of the three models investigated. To better capture the real situation, we generalize the existent study to include different holding costs for perfect and imperfect quality items. Through analysis, we show that the above shipment policies are dependent on holding costs. Furthermore, we derive a simple decision rule solely based on the thresholds of problem parameters to select a superior model. The results are illustrated analytically and numerically.

Keywords: consolidating shipments, disaggregating shipments, EPQ, imperfect quality, inventory

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Authors: Fae Princess Bermudez

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Background: One of the least significant leads on a 12-lead electrocardiogram is the augmented right lead (aVR), as it is not as specific compared to the other leads. In this case series, the value of lead aVR, which is more often than not ignored, is highlighted. Three cases of aVR ST segment elevation on 12-lead electrocardiogram are described, with the end outcome of demise of all three patients. The importance of immediate revascularization is described to improve prognosis in this group of patients. Objectives: This case series aims to primarily present under-reported cases of isolated aVR ST-segrment elevation myocardial infarction (STEMI), their course and outcome. More specific aims are to identify the criteria in determination of isolated aVR STEMI, know its clinical significance, and determine appropriate management for patients with this ECG finding. Method: A short review of previous studies, case reports, articles and guidelines from 2011-2016 was done. The author reviewed available literature, sorted out those that proved to be significant for the presented cases, and described them in conjunction with the aforementioned cases. Findings: Based on the limited information on these rare or under-reported cases, it was found that isolated aVR STEMI had a poorer prognosis that led to significant mortality and morbidity of patients. The significance of aVR ST-elevation was that of an occlusion of the left coronary artery or a severe three-vessel disease in the presence of an Acute Coronary Syndrome. Guidelines from American Heart Association/American College of Cardiology Foundation in 2013 already recognized ST-elevation of lead aVR in isolation as a STEMI; hence, recommended that patients with this particular ECG finding should undergo reperfusion strategies to improve prognosis. Conclusion: The indispensability of isolated aVR ST-segment elevation on ECG should alert physicians, especially Emergency physicians, to the high probability of Acute Coronary Syndrome with a very poor prognosis. If this group of patients is not promptly managed, demise may ensue, with cardiogenic shock as the most probable cause. With this electrocardiogram finding, physicians must be quick to make clinical decisions to increase chances of survival of this group of patients.

Keywords: AVR ST-elevation, diffuse ST-segment depression, left coronary artery infarction, myocardial infarction

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Authors: Milca F. Coelho, K. Bousson, Kawser Ahmed

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To accurately track an aerospace vehicle in a time-critical situation and in a highly nonlinear environment, is one of the strongest interests within the aerospace community. The tracking is achieved by estimating accurately the state of a moving target, which is composed of a set of variables that can provide a complete status of the system at a given time. One of the main ingredients for a good estimation performance is the use of efficient estimation algorithms. A well-known framework is the Kalman filtering methods, designed for prediction and estimation problems. The success of the Kalman Filter (KF) in engineering applications is mostly due to the Extended Kalman Filter (EKF), which is based on local linearization. Besides its popularity, the EKF presents several limitations. To address these limitations and as a possible solution to tracking problems, this paper proposes the use of the Ensemble Kalman Filter (EnKF). Although the EnKF is being extensively used in the context of weather forecasting and it is being recognized for producing accurate and computationally effective estimation on systems with a very high dimension, it is almost unknown by the tracking community. The EnKF was initially proposed as an attempt to improve the error covariance calculation, which on the classic Kalman Filter is difficult to implement. Also, in the EnKF method the prediction and analysis error covariances have ensemble representations. These ensembles have sizes which limit the number of degrees of freedom, in a way that the filter error covariance calculations are a lot more practical for modest ensemble sizes. In this paper, a realistic simulation of a radar tracking was performed, where the EnKF was applied and compared with the Extended Kalman Filter. The results suggested that the EnKF is a promising tool for tracking applications, offering more advantages in terms of performance.

Keywords: Kalman filter, nonlinear state estimation, optimal tracking, stochastic environment

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Authors: Le Jiang, Chua Jinxing

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Introduction: The recent outbreak of Ebola virus disease in the west Africa has drawn global concern. With a high fatality rate and direct human-to-human transmission, it has spread between countries and caused great damages for patients and family who are affected. Being the designated hospital to manage epidemic outbreak in Singapore, Tan Tock Seng Hospital (TTSH) is facing great challenges in preparation and managing of potential outbreak of emerging infectious disease such as Ebola virus disease. Aim: We conducted an infection control drill in TTSH emergency department to assess the readiness of healthcare and allied health workers in managing suspected Ebola patients. It also helps to review current Ebola clinical protocol and work instruction to ensure more smooth and safe practice in managing Ebola patients in TTSH emergency department. Result: General preparedness level of staffs involved in managing Ebola virus disease in TTSH emergency department is not adequate. Knowledge deficits of staffs on Ebola personal protective equipment gowning and degowning process increase the risk of potential cross contamination in patient care. Loopholes are also found in current clinical protocol, such as unclear instructions and inaccurate information, which need to be revised to promote better staff performance in patient management. Logistic issues such as equipment dysfunction and inadequate supplies can lead to ineffective communication among teams and causing harm to patients in emergency situation. Conclusion: The infection control drill identified the need for more well-structured and clear clinical protocols to be in place to promote participants performance. In addition to quality protocols and guidelines, systemic training and annual refresher for all staffs in the emergency department are essential to prepare staffs for the outbreak of Ebola virus disease. Collaboration and communication with allied health staffs are also crucial for smooth delivery of patient care and minimising the potential human suffering, properties loss or injuries caused by disease. Therefore, more clinical drills with collaboration among various departments involved are recommended to be conducted in the future to monitor and assess readiness of TTSH emergency department in managing Ebola virus disease.

Keywords: ebola, emergency department, infection control drill, Tan Tock Seng Hospital

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Authors: Aleksandra Rajewska-Rager, Maria Skibinska, Monika Dmitrzak-Weglarz, Natalia Lepczynska, Pawel Kapelski, Joanna Pawlak, Joanna Hauser

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Introduction: Inflammation and cytokines have emerged as a promising target in mood disorders research; however there are still very limited numbers of study regarding inflammatory alterations among adolescents and young adults with mood disorders. The Macrophage Migration Inhibitory Factor (MIF) and Stem Cell Factor (SCF) are the pleiotropic cytokines which may play an important role in mood disorders pathophysiology. The aim of this study was to investigate levels of these factors in serum of adolescent and young adults with mood disorders compared to healthy controls. Subjects: We involved 79 patients aged 12-24 years in 2-year follow-up study with a primary diagnosis of mood disorders: bipolar disorder (BP) and unipolar disorder with BP spectrum. Study group includes 23 males (mean age 19.08, SD 3.3) and 56 females (18.39, SD 3.28). Control group consisted 35 persons: 7 males (20.43, SD 4.23) and 28 females (21.25, SD 2.11). Clinical diagnoses according to DSM-IV-TR criteria were assessed using Kiddie-Schedule for Affective Disorders and Schizophrenia-Present and Lifetime Version (K-SADS-PL) and Structured Clinical Interview for the Diagnostic and Statistical Manual (SCID) in young adults respectively. Clinical assessment includes evaluation of clinical factors and symptoms severity (rated using the Hamilton Depression Rating Scale and Young Mania Rating Scale). Clinical and biological evaluations were made at control visits respectively at baseline (week 0), euthymia (at month 3 or 6) and after 12 and 24 months. Methods: Serum protein concentration was determined by Enzyme-Linked Immunosorbent Assays (ELISA) method. Human MIF and SCF DuoSet ELISA kits were used. In the analyses non-parametric tests were used: Mann-Whitney U test, Kruskal-Wallis ANOVA, Friedman’s ANOVA, Wilcoxon signed rank test, Spearman correlation. We defined statistical significance as p < 0.05. Results: Comparing MIF and SCF levels between acute episode of depression/hypo/mania at baseline and euthymia (at month 3 or 6) we did not find any statistical differences. At baseline patients with age above 18 years old had decreased MIF level compared to patients younger than 18 years. MIF level at baseline positively correlated with age (p=0.004). Positive correlations of SCF level at month 3 and 6 with depression or mania occurrence at month 24 (p=0.03 and p=0.04, respectively) was detected. Strong correlations between MIF and SCF levels at baseline (p=0.0005) and month 3 (p=0.03) were observed. Discussion: Our results did not show any differences in MIF and SCF levels between acute episode of depression/hypo/mania and euthymia in young patients. Further studies on larger groups are recommended. Grant was founded by National Science Center in Poland no 2011/03/D/NZ5/06146.

Keywords: cytokines, MIF, mood disorders, SCF

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Authors: Gitanjali Pagare, Hansa Devi, S. P. Sanyal

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Full-potential linearized augmented plane wave (FLAPW) method has been employed within the generalized gradient approximation (GGA) and local spin density approximation (LSDA) as the exchange correlation potential to investigate elastic properties of LaX (X = Cd and Hg) in their B2-type (CsCl) crystal structure. The calculated ground state properties such as lattice constant (a0), bulk modulus (B) and pressure derivative of bulk modulus (B') agree well with the available experimental results. The second order elastic constants (C11, C12 and C44) have been calculated. The ductility or brittleness of these intermetallic compounds is predicted by using Pugh’s rule B/GH and Cauchy’s pressure (C12-C44). The calculated results indicate that LaHg is the ductile whereas LaCd is brittle in nature.

Keywords: ductility/brittleness, elastic constants, equation of states, FP-LAPW method, intermetallics

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Authors: Jane E. Hill

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Many variables led to the changes in the insanity defense since the Wild Beast Standard of 1723 until the Federal Insanity Defense Reform Act of 1984. The insanity defense is used in criminal trials and argued that the defendant is ‘not guilty by reason of insanity’ because the individual was unable to distinguish right from wrong during the time they were breaking the law. The issue that surrounds whether or not to use the insanity defense in the criminal court depends on the mental state of the defendant at the time the criminal act was committed. This leads us to the question of did the defendant know right from wrong when they broke the law? In 1723, The Wild Beast Test stated that to be exempted from punishment the individual is totally deprived of their understanding and memory and doth not know what they are doing. The Wild Beast Test became the standard in England for over seventy-five years. In 1800, James Hadfield attempted to assassinate King George III. He only made the attempt because he was having delusional beliefs. The jury and the judge gave a verdict of not guilty. However, to legal confine him; the Criminal Lunatics Act was enacted. Individuals that were deemed as ‘criminal lunatics’ and were given a verdict of not guilty would be taken into custody and not be freed into society. In 1843, the M'Naghten test required that the individual did not know the quality or the wrongfulness of the offense at the time they committed the criminal act(s). Daniel M'Naghten was acquitted on grounds of insanity. The M'Naghten Test is still a modern concept of the insanity defense used in many courts today. The Irresistible Impulse Test was enacted in the United States in 1887. The Irresistible Impulse Test suggested that offenders that could not control their behavior while they were committing a criminal act were not deterrable by the criminal sanctions in place; therefore no purpose would be served by convicting the offender. Due to the criticisms of the latter two contentions, the federal District of Columbia Court of Appeals ruled in 1954 to adopt the ‘product test’ by Sir Isaac Ray for insanity. The Durham Rule also known as the ‘product test’, stated an individual is not criminally responsible if the unlawful act was the product of mental disease or defect. Therefore, the two questions that need to be asked and answered are (1) did the individual have a mental disease or defect at the time they broke the law? and (2) was the criminal act the product of their disease or defect? The Durham courts failed to clearly define ‘mental disease’ or ‘product.’ Therefore, trial courts had difficulty defining the meaning of the terms and the controversy continued until 1972 when the Durham rule was overturned in most places. Therefore, the American Law Institute combined the M'Naghten test with the irresistible impulse test and The United States Congress adopted an insanity test for the federal courts in 1984.

Keywords: insanity defense, psychology law, The Federal Insanity Defense Reform Act of 1984, The Wild Beast Standard in 1723

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Authors: Jayeon Kim, Eunjung Yu, Taeki Yoon

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Most spontaneous miscarriage is believed to be a consequence of embryo aneuploidies. Transferring eukaryotic embryos selected by PGS is expected to decrease the miscarriage rate. Current PGS indications include advanced maternal age, recurrent pregnancy loss, repeated implantation failure. Recently, use of PGS for healthy women without above indications for the purpose of improving in vitro fertilization (IVF) outcomes is on the rise. However, it is still controversy about the beneficial effect of PGS in this population, especially, in women with a history of no more than 2 miscarriages or miscarriage of eukaryotic abortus. This study aimed to investigate if karyotyping result of abortus is a good indicator of preimplantation genetic screening (PGS) in subsequent IVF cycle in women with a history of spontaneous abortion. A single-center retrospective cohort study was performed. Women who had spontaneous abortion(s) (less than 3) and dilatation and evacuation, and subsequent IVF from January 2016 to November 2016 were included. Their medical information was extracted from the charts. Clinical pregnancy was defined as presence of a gestational sac with fetal heart beat detected on ultrasound in week 7. Statistical analysis was performed using SPSS software. Total 234 women were included. 121 out of 234 (51.7%) underwent karyotyping of the abortus, and 113 did not have the abortus karyotyped. Embryo biopsy was performed on 3 or 5 days after oocyte retrieval, followed by embryo transfer (ET) on a fresh or frozen cycle. The biopsied materials were subjected to microarray comparative genomic hybridization. Clinical pregnancy rate per ET was compared between PGS and non-PGS group in each study group. Patients were grouped by two criteria: karyotype of the abortus from previous miscarriage (unknown fetal karyotype (n=89, Group 1), eukaryotic abortus (n=36, Group 2) or aneuploidy abortus (n=67, Group 3)), and pursuing PGS in subsequent IVF cycle (pursuing PGS (PGS group, n=105) or not pursuing PGS (non-PGS group, n=87)). The PGS group was significantly older and had higher number of retrieved oocytes and prior miscarriages compared to non-PGS group. There were no differences in BMI and AMH level between those two groups. In PGS group, the mean number of transferable embryos (eukaryotic embryo) was 1.3 ± 0.7, 1.5 ± 0.5 and 1.4 ± 0.5, respectively (p = 0.049). In 42 cases, ET was cancelled because all embryos biopsied turned out to be abnormal. In all three groups (group 1, 2, and 3), clinical pregnancy rates were not statistically different between PGS and non-PGS group (Group 1: 48.8% vs. 52.2% (p=0.858), Group 2: 70% vs. 73.1% (p=0.730), Group 3: 42.3% vs. 46.7% (p=0.640), in PGS and non-PGS group, respectively). In both groups who had miscarriage with eukaryotic and aneuploidy abortus, the clinical pregnancy rate between IVF cycles with and without PGS was not different. When we compare miscarriage and ongoing pregnancy rate, there were no significant differences between PGS and non-PGS group in all three groups. Our results show that the routine application of PGS in women who had less than 3 miscarriages would not be beneficial, even in cases that previous miscarriage had been caused by fetal aneuploidy.

Keywords: preimplantation genetic diagnosis, miscarriage, kpryotyping, in vitro fertilization

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