Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of Drug Concentration of Isoniazid and Rifampicin between Daily and Intermittent Anti-Tubercular (ATT) Regimen, in Children treated for Tuberculosis

OBJECTIVES : 1. To measure the drug exposure as the area under the concentration time curve to six hours (AUC0-6h) for both isoniazid and rifampicin in children treated by either daily or intermittent ATT regimen. 2. To determine the inter-patient variability in plasma concentrations, as well to determine the basic pharmacokinetic parameters, for isoniazid and rifampicin in above population. METHODS : Children aged 2 to 16 years, initiated on either daily or intermittent (thrice weekly) ATT were recruited into the study, after obtaining informed consent. Towards the end of the intensive phase, blood specimens were collected pre-dose, followed by 0.5, 1, 1.5, 2, 2.5, 4 and 6hrs post-dose. The concentrations of isoniazid and rifampicin were analyzed using a validated LC-MS/MS and HPLC assays, respectively. Results were analyzed using non parametric methods with R version 3.1. 2. RESULTS : The median dose (mg/kg) *for isoniazid was 10.13 versus 8.10 (p=0.005) in the intermittent and daily dose regimens respectively. The C0 (μg/mL) * was below the limit of detection versus 0.15 (p=0.0009). The Cmax(μg/mL) * was 6.8 versus 6.86, C2(μg/mL) * was 5.1 versus 5.54 and C6(μg/mL) * was 2.01 versus 2.18. None of these were significantly different. Median AUC0-6h(mg.hr/L) *was 22.18 versus 24.55 (p =0.879) The median dose (mg/kg) * for rifampicin was 10.26 versus 10.77. C0(μg/mL) * was below the limit of detection, versus 0.01 (p=0.4), Cmax(μg/mL)* was 6.19 versus 5.59, C2(μg/mL)* was 4.3 versus 4.4 and C6(μg/mL) *was 1.01 versus 1.68. However, there was no significant difference. Median AUC0-6h (mg.hr/L) * was 16.87 versus 16.51 (p =0.879). CONCLUSION : All the patients (except 2) had isoniazid Cmax above 3μg/mL (recommended range: 3-6μg/mL) and 83% of the patients had rifampicin Cmax less than recommended range (8-24μg/mL). 31% of the patients had a very low Cmax for rifampicin, which is <4μg/mL. Cmax has a strong correlation with AUC0-6h in both regimens for both isoniazid and rifampicin. (r=0.889 and 0.97 for isoniazid; r=0.89 and 0.98 for rifampicin). Only 20% of the patients had Cmax at 2hrs for both isoniazid and rifampicin. Hence, pharmacokinetic studies in children for both drugs should include earlier time points to capture the Cmax accurately. Dose of rifampicin does not appear to have a correlation with the exposure. also rifampicin has a high interindividual variability (% CV of 54 % for AUC and 59% for Cmax). Therefore, we recommend the use of TDM for patients on rifampicin (especially for the patients who do not respond adequately or respond slowly). *indicates intermittent versus daily regimen respectively. Reference for therapeutic range of isoniazid and rifampicin: Verhagen LH, et al. Trop Med Int Health. 2012;17:1449-56
Pancreatic Islet Protein Complexes and Their Dysregulation in Type 2 Diabetes

Type 2 diabetes (T2D) is a complex disease that involves multiple genes. Numerous risk loci have already been associated with T2D, although many susceptibility genes remain to be identified given heritability estimates. Systems biology approaches hold potential for discovering novel T2D genes by considering their biological context, such as tissue-specific protein interaction partners. Pancreatic islets are a key T2D tissue and many of the known genetic risk variants lead to impaired islet function, hence a better understanding of the islet-specific dysregulation in the disease-state is essential to unveil the full potential of person-specific profiles. Here we identify 3,692 overlapping pancreatic islet protein complexes (containing 10,805 genes) by integrating islet gene and protein expression data with protein interactions. We found 24 of these complexes to be significantly enriched for genes associated with diabetic phenotypes through heterogeneous evidence sources, including genetic variation, methylation, and gene expression in islets. The analysis specifically revealed ten T2D candidate genes with probable roles in islets (ANPEP, HADH, FAM105A, PDLIM4, PDLIM5, MAP2K4, PPP2R5E, SNX13, GNAS, and FRS2), of which the last six are novel in the context of T2D and the data that went into the analysis. Fifteen of the twenty-four complexes were further enriched for combined genetic associations with glycemic traits, exemplifying how perturbation of protein complexes by multiple small effects can give rise to diabetic phenotypes. The complex nature of T2D ultimately prompts an understanding of the individual patients at the network biology level. We present the foundation for such work by exposing a subset of the global interactome that is dysregulated in T2D and consequently provides a good starting point when evaluating an individual's alterations at the genome, transcriptome, or proteome level in relation to T2D in clinical settings.
Dynamics of COVID‐19 epidemics: SEIR models underestimate peak infection rates and overestimate epidemic duration

Compartment models of infectious diseases, such as SEIR, are being used extensively to model the COVID-19 epidemic. Transitions between compartments are modelled either as instantaneous rates in differential equations, or as transition probabilities in discrete time difference or matrix equations. These models give accurate estimates of the position of equilibrium points, when the rate at which individuals enter each stage is equal to the rate at which they exit from it. However, they do not accurately capture the distribution of times that an individual spends in each compartment, so do not accurately capture the transient dynamics of epidemics. Here we show how matrix models can provide a straightforward route to accurately model stage durations, and thus correctly reproduce epidemic dynamics. We apply this approach to modelling the dynamics of a COVID-19 epidemic. We show that a SEIR model underestimates peak infection rates (by a factor of three using published parameter estimates based on the progress of the epidemic in Wuhan) and substantially overestimates epidemic persistence after the peak has passed.
Repurposing therapeutics for COVID-19: Rapid prediction of commercially available drugs through machine learning and docking

Background The outbreak of the novel coronavirus disease COVID 19, caused by the SARS-CoV-2 virus has spread rapidly around the globe during the past 3 months. As the virus infected cases and mortality rate of this disease is increasing exponentially, scientists and researchers all over the world are relentlessly working to understand this new virus along with possible treatment regimens by discovering active therapeutic agents and vaccines. So, there is an urgent requirement of new and effective medications that can treat the disease caused by SARS CoV 2. Methods and findings We perform the study of drugs that are already available in the market and being used for other diseases to accelerate clinical recovery, in other words repurposing of existing drugs. The vast complexity in drug design and protocols regarding clinical trials often prohibit developing various new drug combinations for this epidemic disease in a limited time. Recently, remarkable improvements in computational power coupled with advancements in Machine Learning (ML) technology have been utilized to revolutionize the drug development process. Consequently, a detailed study using ML for the repurposing of therapeutic agents is urgently required. Here, we report the ML model based on the Naive Bayes algorithm, which has an accuracy of around 73% to predict the drugs that could be used for the treatment of COVID-19. Our study predicts around ten FDA approved commercial drugs that can be used for repurposing. Among all, we suggest that the antiretroviral drug Atazanavir (DrugBank ID DB01072) would probably be one of the most effective drugs based on the selected criterions. Conclusions Our study can help clinical scientists in being more selective in identifying and testing the therapeutic agents for COVID 19 treatment. The ML based approach for drug discovery as reported here can be a futuristic smart drug designing strategy for community applications.
Reliability of self-sampling for accurate assessment of respiratory virus viral and immunologic kinetics

The SARS-CoV-2 pandemic demonstrates the need for accurate and convenient approaches to diagnose and therapeutically monitor respiratory viral infections. We demonstrated that self-sampling with foam swabs at home is well-tolerated and provides quantitative viral output concordant with flocked swabs. Nasal cytokine levels correlate and cluster according to immune cell of origin. Periods of stable viral loads are followed by rapid elimination, which could be coupled with cytokine expansion and contraction using mathematical models. Nasal foam swab self-sampling at home provides a precise, mechanistic readout of respiratory virus shedding and local immune responses.
A phased lift of control: a practical strategy to achieve herd immunity against Covid-19 at the country level

Most countries are affected by the Covid-19 pandemic and experience rapidly increasing numbers of cases and deaths. Many have implemented nationwide stringent control to avoid overburdening the health care system. This paralyzes economic and social activities until the availability of a vaccine, which may take years. We propose an alternative exit strategy to develop herd immunity in a predictable and controllable way: a phased lift of control. This means that successive parts of the country (e.g. provinces) stop stringent control, and Covid-19-related IC admissions are distributed over the country as the whole. Importantly, vulnerable individuals need to be shielded until herd immunity has developed in their area. We explore the characteristics and duration of this strategy using a novel individual-based model for geographically stratified transmission of Covid-19 in a country. The model predicts that individuals will have to experience stringent control for about 14 months on average, but this duration may be significantly shortened by future developments (more IC beds, better drugs). Clearly, the strategy will have a profound impact on individuals and society, and should therefore be considered carefully by various other disciplines (e.g. health systems, ethics, economics) before actual implementation.
Covid-19 clinical data analysis using Ball Mapper

In this note we provide a result of analysis of blood test data from patients with SARS-Cov-2 using Ball Mapper Algorithm. We observe that patients with the virus and in particularly patients who end up in Intensive Care Unit have quite narrow values of those parameters. Please note that this is a preliminary work and it need to be validated on much larger dataset which we are trying to acquire at the moment.
CoViD19 Meta heuristic optimization based forecast method on time dependent bootstrapped data

A compounded method, exploiting the searching capabilities of an operation research algorithm and the power of bootstrap techniques, is presented. The resulting algorithm has been successfully tested to predict the turning point reached by the epidemic curve followed by the CoViD19 virus in Italy. Futures lines of research, which include the generalization of the method to a broad set of distribution, will be finally given.
Factors for minimizing cyber harassment among university students: Case study in kingdom of saudi arabia (KSA)

This study attempted to mitigate the gap in literature concerning a one serious problem in Saudi society and government is cyber harassment. This problem is caused through the increasing use of technology. Accordingly, the main objective was to explore the factors that influence the intention to minimize cyber harassment among Saudi citizen. In this research were employed two theories the first Theory of Planned Behavior (TPB), the second selected Technology Acceptance Model TAM. However, based on TPB, the researcher has identified eight factors, to minimize cyber harassment, which is: technological support, attitude, subjective norms, social pressure, the influence of the mass media, perceived behavioral control, regulatory support and the role of the government, and security awareness. Nevertheless, the researcher has assured that the Saudis will remain at risk of cyber harassment, until these factors are fully investigated among the Saudi community. In conclusion, this research specifically proposed in future a model and framework for identifying the significant factors that are anticipated to play a major in minimizing cyber harassment among Saudis. The proposed framework will help the administration and decision-makers in the KSA to formulate strategies that can significantly affect anti-cyber harassment among youths.
COX-2 as a potential biomarker and therapeutic target in melanoma

With a constantly increasing incidence, cutaneous melanoma has raised the need for a better understanding of its complex microenvironment that may further guide therapeutic options. Melanoma is a model tumor in immuno-oncology. Inflammation represents an important hallmark of cancer capable of inducing and sustaining tumor development. The inflammatory process also orchestrates the adaptative immunosuppression of tumor cells that helps them to evade immune destruction. Besides its role in proliferation, angiogenesis, and apoptosis, cyclooxygenase-2 (COX-2) is a well-known promoter of immune suppression in melanoma. COX-2 inhibitors are closely involved in this condition. This review attempts to answer two controversial questions: is COX-2 a valuable prognostic factor? Among all COX-2 inhibitors, is celecoxib a suitable adjuvant in melanoma therapy?
Social inequalities in care for the elderly with diabetes in Brazil

ABSTRACT Objective. To measure the prevalence of various care services offered to the elderly with diabetes mellitus in Brazil, and to assess the social inequalities in these services. Methods. This cross-sectional, population-based study was carried out in 2013. The care services offered were evaluated in terms of the following eight indicators: recommendations to lower carbohydrates, to measure blood glucose, and to examine the feet; requests made for blood tests, for glycated hemoglobin tests, and for glycemic curve tests; and whether service users had had their eyes or feet examined in the previous year. We used the slope index of inequality and the concentration index to assess the inequalities among wealth quintiles. Results. A total of 1 685 elderly persons with diabetes were evaluated. Overall, 41.7% of them had had their eyes examined in the preceding year, 35.4% had had their feet examined in the preceding year, and 10.9% had been offered all eight of the care services. The largest absolute differences (in percentage points) between the first (poorest) and fifth (richest) wealth quintiles in terms of the care services that were offered to the users were for: a recommendation to measure blood glucose (25.8), a glycated hemoglobin test request (27.4), a glycemic curve test request (31.9), having the eyes examined in the preceding year (29.3), and having the feet examined in the preceding year (27.0). Conclusion. There were notable inequalities in the prevalences of the care services. In the future, measurement of blood glucose and examination of the feet should be emphasized, especially for elderly persons in a lower socioeconomic level.
Choosing what is left: the spatial structure of a wild herbivore population within a livestock-dominated landscape

Shrublands and grasslands comprise over 30% of the land surface and are among the most exploited ecosystems for livestock production. Across natural landscapes, the distribution and abundance of wild herbivores are affected by interspecific competition for foraging resources, hunting and the development of infrastructure among other factors. In Argentine Patagonia, the abundance of domestic sheep grazing on native vegetation outnumbers the widely distributed guanaco (Lama guanicoe) and sheep ranching monopolizes the most productive lands. In this work, we aimed to assess the spatial variation in the abundance of guanacos in Península Valdés, a representative landscape of Patagonia, investigating the incidence of natural and human-related factors. We conducted ground surveys during the austral autumn in 2017 totaling 383.4 km along areas with and without sheep ranching. We built density surface models to account for the variation in guanaco abundance and obtained a map of guanaco density at a resolution of 4 km2. We estimated an overall density of 11.71 guanacos.km−2 for a prediction area of 3,196 km2, although the density of guanacos tripled in areas where sheep ranching was terminated (in around 20% of the surface of Península Valdés) compared to areas with sheep. Guanacos were more abundant at lower values of primary productivity and sheep stocking rates and further from inhabited ranch buildings, suggesting competition with sheep and conflict with humans. Although guanacos selected open, grass-dominated habitats across sheep-free sites, fences dividing properties and paddocks played a significant role in the spatial structure of their population in Península Valdés affecting negatively the abundance of guanacos. Our results indicate that actions to improve habitat connectivity for guanacos, favor the coexistence among guanacos and sheep ranching, and promote responsible human activities and attitudes towards wildlife are needed.
The effect of positive airway pressure therapy on lipid profile

CONTEXT: Obstructive sleep apnea syndrome (OSAS) emphasize the concurrence and interaction of disorders of lipid metabolism and components of metabolic syndrome (MS) such as insulin resistance. AIMS: The aim of this study is to observe the effect of positive airway pressure (PAP) treatment on the lipid profile during 1-year follow-up of patients diagnosed with OSAS. SETTINGS AND DESIGN: This was a single-center, retrospective, observational study. MATERIALS AND METHODS: A total of 168 OSAS patients were diagnosed in our sleep laboratory and were recommended for PAP therapy. Among these patients, 64 patients who received effective PAP treatment for 1 year, and who did not have the comorbid disease, history of lipid-lowering treatment, or history of lifestyle change, dietary regulation or attempt to loose weight during the 1-year follow-up period were included in the study. Pretreatment measurement parameters including body weight, waist, neck and hip circumference, body mass index (BMI), blood lipid levels (total cholesterol [TC], triglyceride [TG], high-density lipoprotein [HDL], low-density lipoprotein [LDL]), and Epworth sleepiness scale (ESS) score were compared with the 3rd and 12th months parameters. STATISTICAL ANALYSIS USED: SPSS version 16 (SPSS Inc., Chicago, IL, USA) was used for the statistical analyses. RESULTS: The study included 64 (38 M, 26 F) patients (mean age of 53.1 years). The mean apnea-hypopnea index was 50.84 h. Although TC, HDL, LDL, and TG levels did improve with the PAP treatment (all P < 0.05), no significant decrease was observed with respect to the BMI, hip, neck, and waist circumference (all P > 0.05). There were statistically significant changes in sleep efficiency, oxygen desaturation index, and ESS score (P < 0.05). CONCLUSIONS: The results show that effective PAP treatment has beneficial effects on the blood lipid profile, which enhances sleep efficiency and sleep quality in patients.
Tracheostomy: Complications and Causes of Complications

Background: Tracheostomy is one of the critical surgical procedures in the case of airway obstruction and in patients with long-term intubation; on the other hand, it has complications, that some of which are common. Objectives: The aim of this study was to determine the complications and their underlying causes in patients admitted to the intensive care unit (ICU). Methods: This descriptive, analytical study was performed on 107 patients eligible to participate in the research in ICU wards of Babol hospitals, in northern Iran, in 1394. Patients were evaluated for 16 common Tracheostomy complications immediately after tracheostomy, up to 1 month after removal of the tracheal tube, using the checklist for 4 months. The underlying causes of complications were determined by assessed the causes of admission, the method of tracheostomy, the history of diseases affecting complications and the quality of nursing care from tracheostomy through a standard care checklist. Results: The highest percentage of units (21.5%) was experienced one complication, 19.6% units were two complications, and 5.6% had no complication and 0.9% of the units showed most complications (11). The most common complications were infections and redness (46.7%(, swelling (43.9%), and bleeding and air leakage from tracheostomy (33.6%), respectively. Patients with diabetes and high blood pressure, patients with a surgical tracheostomy, and patients with ischemic heart disease, experienced the most complications, respectively. The quality of nursing care was determined 66.4% in average grade. Conclusions: Tracheostomy is a way to continue the patient’s respiration, in spite of inevitable complications. The method of stoma formation, underlying diseases and the quality of nursing care has a direct relationship with its complications. It is suggested that nurses improve the quality of nursing care to reduce the complications.
Determinants of selective reporting: A taxonomy based on content analysis of a random selection of the literature

Background Selective reporting is wasteful, leads to bias in the published record and harms the credibility of science. Studies on potential determinants of selective reporting currently lack a shared taxonomy and a causal framework. Objective To develop a taxonomy of determinants of selective reporting in science. Design Inductive qualitative content analysis of a random selection of the pertinent literature including empirical research and theoretical reflections. Methods Using search terms for bias and selection combined with terms for reporting and publication, we systematically searched the PubMed, Embase, PsycINFO and Web of Science databases up to January 8, 2015. Of the 918 articles identified, we screened a 25 percent random selection. From eligible articles, we extracted phrases that mentioned putative or possible determinants of selective reporting, which we used to create meaningful categories. We stopped when no new categories emerged in the most recently analyzed articles (saturation). Results Saturation was reached after analyzing 64 articles. We identified 497 putative determinants, of which 145 (29%) were supported by empirical findings. The determinants represented 12 categories (leaving 3% unspecified): focus on preferred findings (36%), poor or overly flexible research design (22%), high-risk area and its development (8%), dependence upon sponsors (8%), prejudice (7%), lack of resources including time (3%), doubts about reporting being worth the effort (3%), limitations in reporting and editorial practices (3%), academic publication system hurdles (3%), unfavorable geographical and regulatory environment (2%), relationship and collaboration issues (2%), and potential harm (0.4%). Conclusions We designed a taxonomy of putative determinants of selective reporting consisting of 12 categories. The taxonomy may help develop theory about causes of selection bias and guide policies to prevent selective reporting.