Miracle-dz/UniFAR-FTUs huggingface dataset:
Prevalence and determinants of using complementary and alternative medicine for the treatment of chronic illnesses: A multicenter study in Bangladesh

Background While conventional medicine (CM) is commonly used to treat non-communicable diseases (NCDs), complementary and alternative medicine (CAM) is gaining popularity as a healthcare option in Bangladesh. We aimed to investigate the prevalence and factors associated with using CAM solely and using CAM in conjunction with CM for chronic illness treatment among NCD patients in Bangladesh. Methods A multicenter cross-sectional study was conducted, including 549 adults with a confirmed chronic illness diagnosis from three tertiary care hospitals in Dhaka city. Interviews were used to gather socio-demographic data, while medical records were used to get information on chronic illnesses. A multinomial logistic regression model was used to determine the associated factors of utilizing CAM primarily and CAM use in conjunction with CM to manage the chronic disease. Results Out of 549 NCD patients (282 women [51.4%], mean [standard deviation] age 45.4 [12.8] years), 180 (32.8%) ever used CAM for the treatment of chronic illness. Also, 15.3% of patients exclusively used CAM among the NCD patients, while 17.5% used CAM in conjunction with CM. Homeopathy medicine was the most prevalent type of treatment among CAM users (52.2%). Furthermore, 55.5% of CAM users said they used it due to its less adverse effects, and 41.6% trusted its effectiveness for chronic illness. Elderly patients (≥60 years) preferred CAM in complementary with CM, but they did not rely only on CAM. According to the multinomial regression analysis, unmarried patients, predominantly in the younger age group, adopted CAM significantly for chronic illness treatment (Relative risk ratio, RRR = 0.29, 95% CI = 0.12–0.71, reference = Unmarried). Patients in the high-income group used CAM in conjunction with CM (RRR = 6.26, 95% CI = 1.35–18.90, reference: low-income), whereas patients in the high-income group did not rely on CAM alone (RRR = 0.99, 95% CI = 0.34–2.85). Conclusion Although CM remains the mainstream of health care in Bangladesh, CAM services play an essential role in people’s health care, particularly in treating chronic illnesses. Physicians of Bangladesh should be aware that their patients may be using other services and be prepared to ask and answer questions regarding the risks and benefits of using CAM in addition to regular medical care. Thus, clinicians required to follow best-practice guidelines, which are currently not practiced in Bangladesh, when disseminating information regarding integrative techniques that combine CM and CAM approaches.
A 12-hospital prospective evaluation of a clinical decision support prognostic algorithm based on logistic regression as a form of machine learning to facilitate decision making for patients with suspected COVID-19

Objective To prospectively evaluate a logistic regression-based machine learning (ML) prognostic algorithm implemented in real-time as a clinical decision support (CDS) system for symptomatic persons under investigation (PUI) for Coronavirus disease 2019 (COVID-19) in the emergency department (ED). Methods We developed in a 12-hospital system a model using training and validation followed by a real-time assessment. The LASSO guided feature selection included demographics, comorbidities, home medications, vital signs. We constructed a logistic regression-based ML algorithm to predict “severe” COVID-19, defined as patients requiring intensive care unit (ICU) admission, invasive mechanical ventilation, or died in or out-of-hospital. Training data included 1,469 adult patients who tested positive for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) within 14 days of acute care. We performed: 1) temporal validation in 414 SARS-CoV-2 positive patients, 2) validation in a PUI set of 13,271 patients with symptomatic SARS-CoV-2 test during an acute care visit, and 3) real-time validation in 2,174 ED patients with PUI test or positive SARS-CoV-2 result. Subgroup analysis was conducted across race and gender to ensure equity in performance. Results The algorithm performed well on pre-implementation validations for predicting COVID-19 severity: 1) the temporal validation had an area under the receiver operating characteristic (AUROC) of 0.87 (95%-CI: 0.83, 0.91); 2) validation in the PUI population had an AUROC of 0.82 (95%-CI: 0.81, 0.83). The ED CDS system performed well in real-time with an AUROC of 0.85 (95%-CI, 0.83, 0.87). Zero patients in the lowest quintile developed “severe” COVID-19. Patients in the highest quintile developed “severe” COVID-19 in 33.2% of cases. The models performed without significant differences between genders and among race/ethnicities (all p-values > 0.05). Conclusion A logistic regression model-based ML-enabled CDS can be developed, validated, and implemented with high performance across multiple hospitals while being equitable and maintaining performance in real-time validation.
Happiness at work: A cross-cultural validation of happiness at work scale

The idea of Happiness at Work is drawn from psychology and economic studies. It is often considered as a synonym with ‘wellbeing’ and defined as a state characterized by a high level of life satisfaction, a high level of positive emotions, and less negative emotions. This research aims to validate the Happiness at Work scale in the Indonesian context. In this study, the researchers conducted cross-cultural adaptation for the Happiness at Work scale following systematic procedures to produce the Scale of Happiness at Work in the Indonesian language. Afterward, the researchers evaluated the content validity with the help of professional judgment and measured the Content Validity Index at the item level and the scale level. Further, to examine the psychometric properties of the Happiness at Work scale, the researchers administer the questionnaire to a sample of 105 (35 male and 70 female) lecturers to conduct exploratory factor analysis to formulate the new dimensionality of the Happiness at Work scale. The results of Exploratory Factor Analysis indicated that Happiness at Work in the Indonesian context could be measured using four dimensions. To confirm that the extracted dimensions measure a single construct, the researchers administered the produced version to a sample of 370 (147 male and 223 female). Afterward, researchers conducted confirmatory factor analysis to evaluate the validity and reliability of the measurement model. This research found out that the Indonesian version of Happiness at Work measurement is reliable and valid. Thus, this study may contribute to the happiness at work literature of non-western context. In conclusion, the Indonesian-Happiness at Work scale shows robust psychometric properties that can be used for further research.
AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models

Abstract The AlphaFold Protein Structure Database (AlphaFold DB, https://alphafold.ebi.ac.uk) is an openly accessible, extensive database of high-accuracy protein-structure predictions. Powered by AlphaFold v2.0 of DeepMind, it has enabled an unprecedented expansion of the structural coverage of the known protein-sequence space. AlphaFold DB provides programmatic access to and interactive visualization of predicted atomic coordinates, per-residue and pairwise model-confidence estimates and predicted aligned errors. The initial release of AlphaFold DB contains over 360,000 predicted structures across 21 model-organism proteomes, which will soon be expanded to cover most of the (over 100 million) representative sequences from the UniRef90 data set.
Patients’ satisfaction with outpatient pharmacy services and associated factors in Debre Tabor comprehensive specialized hospital, Northwest Ethiopia: A cross-sectional study

Introduction By measuring patients’ satisfaction, providers can gain insight into several elements of health care services, including the effectiveness of their care and the level of empathy they exhibit. The aim of this study was to assess patient satisfaction with pharmaceutical services and associated factors in public hospitals located in Northwestern Ethiopia. Methods An institution-based quantitative cross-sectional study was used. The study was carried out in an outpatient pharmacy from January 1–June 30, 2021. Participants were selected by a systematic sampling technique. The IBM SPSS statistical package (version 23) was used to enter and analyze the collected data. The findings were presented using descriptive statistical methods. To find factors linked to satisfaction, binary logistic regression was used. Results The final analysis included a total of 401 samples. More than half of the participants (229, or 55.1%) were female. The overall mean score of satisfaction was 30.6 out of a maximum of 100 scores. By taking this mean score as a cut-off point, 204 (50.9%) of the study participants had satisfaction with the outpatient pharmacists’ service. Participants’ responses scored on the uncomfortable and inconvenient waiting areas [AOR = 0.31; 95%CI, (0.13, 0.49)] were found to be negatively associated with the level of patients’ satisfaction. Also, the unavailability of medications [AOR = 0.12; 95%CI, (0.02, 0.37)] was negatively associated with the respondent satisfaction. Uncomfortable and inconvenient private counseling areas [AOR = 1.37; 95%CI, (0.79, 4.42)] showed a negative association with their satisfaction. Conclusion Patients’ satisfaction levels with pharmacy service were found to be greater than 50%. The socio-demographic characteristics of patients have no association with their level of satisfaction, but their perception of uncomfortable private counseling areas and waiting areas was negatively associated with their satisfaction.
Functional assessment of somatic STK11 variants identified in primary human non-small cell lung cancers

Abstract Serine/Threonine Kinase 11 (STK11) encodes an important tumor suppressor that is frequently mutated in lung adenocarcinoma. Clinical studies have shown that mutations in STK11 resulting in loss of function correlate with resistance to anti-PD-1 monoclonal antibody therapy in KRAS-driven non-small cell lung cancer (NSCLC), but the molecular mechanisms responsible remain unclear. Despite this uncertainty, STK11 functional status is emerging as a reliable biomarker for predicting non-response to anti-PD-1 therapy in NSCLC patients. The clinical utility of this biomarker ultimately depends upon accurate classification of STK11 variants. For nonsense variants occurring early in the STK11 coding region, this assessment is straightforward. However, rigorously demonstrating the functional impact of missense variants remains an unmet challenge. Here we present data characterizing four STK11 splice-site variants by analyzing tumor mRNA, and 28 STK11 missense variants using an in vitro kinase assay combined with a cell-based p53-dependent luciferase reporter assay. The variants we report were identified in primary human NSCLC biopsies in collaboration with the University of Vermont Genomic Medicine group. Additionally, we compare our experimental results with data from 22 in silico predictive algorithms. Our work highlights the power, utility and necessity of functional variant assessment and will aid STK11 variant curation, provide a platform to assess novel STK11 variants and help guide anti-PD-1 therapy utilization in KRAS-driven NSCLCs.
Discovering novel mechanisms of taxane resistance in human breast cancer by whole-exome sequencing

Taxanes are important drugs used in the treatment of breast cancer; however, some cancer types are taxane-resistant. The aim of the present study was to investigate the underlying mechanisms of taxane resistance using whole-exome sequencing (WES). Six patients with breast cancer whose tumors responded well to anthracycline treatment but grew rapidly during neoadjuvant taxane-based chemotherapy, were included in the present study. WES of samples from these patients was carried out to identify somatic mutations of candidate genes thought to affect taxane resistance, and the candidate proteins were structurally modeled. The mRNA and protein expression levels of these candidate genes in other breast cancers treated with taxanes were also examined. Nine variants common to all six patients were identified and two of these [R552P in V-type proton ATPase catalytic subunit A (ATP6V1A) and T114P in apolipoprotein B MRNA editing enzyme catalytic subunit 3F (APOBEC3F)] were selected. The results also showed that, protein-structure visualization suggested that these mutations may cause structural changes. The Kaplan-Meier analyses revealed that higher APT6V1A and APOBEC3F expression levels were significantly associated with poorer disease-free survival (DFS) and overall survival. Moreover, multivariate analysis identified high ATP6V1A mRNA expression as an independent risk factor for poor DFS. Two specific mutations that might affect taxane resistance were identified. Thus, these results suggest that breast cancer patients receiving taxanes who have high ATP6V1A or APOBEC3F expression levels may have shorter survival.
Biofabrication of ZnO nanoparticles using Acacia arabica leaf extract and their antibiofilm and antioxidant potential against foodborne pathogens

Emergence of multidrug resistant pathogens is increasing globally at an alarming rate with a need to discover novel and effective methods to cope infections due to these pathogens. Green nanoparticles have gained attention to be used as efficient therapeutic agents because of their safety and reliability. In the present study, we prepared zinc oxide nanoparticles (ZnO NPs) from aqueous leaf extract of Acacia arabica. The nanoparticles produced were characterized through UV-Visible spectroscopy, scanning electron microscopy, and X-ray diffraction. In vitro antibacterial susceptibility testing against foodborne pathogens was done by agar well diffusion, growth kinetics and broth microdilution assays. Effect of ZnO NPs on biofilm formation (both qualitatively and quantitatively) and exopolysaccharide (EPS) production was also determined. Antioxidant potential of green synthesized nanoparticles was detected by DPPH radical scavenging assay. The cytotoxicity studies of nanoparticles were also performed against HeLa cell lines. The results revealed that diameter of zones of inhibition against foodborne pathogens was found to be 16–30 nm, whereas the values of MIC and MBC ranged between 31.25–62.5 μg/ml. Growth kinetics revealed nanoparticles bactericidal potential after 3 hours incubation at 2 × MIC for E. coli while for S. aureus and S. enterica reached after 2 hours of incubation at 2 × MIC, 4 × MIC, and 8 × MIC. 32.5–71.0% inhibition was observed for biofilm formation. Almost 50.6–65.1% (wet weight) and 44.6–57.8% (dry weight) of EPS production was decreased after treatment with sub-inhibitory concentrations of nanoparticles. Radical scavenging potential of nanoparticles increased in a dose dependent manner and value ranged from 19.25 to 73.15%. Whereas cytotoxicity studies revealed non-toxic nature of nanoparticles at the concentrations tested. The present study suggests that green synthesized ZnO NPs can substitute chemical drugs against antibiotic resistant foodborne pathogens.
Genome-wide identification of CCT genes in wheat (Triticum aestivum L.) and their expression analysis during vernalization

Numerous CCT genes are known to regulate various biological processes, such as circadian rhythm regulation, flowering, light signaling, plant development, and stress resistance. The CCT gene family has been characterized in many plants but remains unknown in the major cereal wheat (Triticum aestivum L.). Extended exposure to low temperature (vernalization) is necessary for winter wheat to flower successfully. VERNALIZATION2 (VRN2), a specific CCT-containing gene, has been proved to be strongly associated with vernalization in winter wheat. Mutation of all VRN2 copies in three subgenomes results in the eliminated demands of low temperature in flowering. However, no other CCT genes have been reported to be associated with vernalization to date. The present study screened CCT genes in the whole wheat genome, and preliminarily identified the vernalization related CCT genes through expression analysis. 127 CCT genes were identified in three subgenomes of common wheat through a hidden Markov model-based method. Based on multiple alignment, these genes were grouped into 40 gene clusters, including the duplicated gene clusters TaCMF6 and TaCMF8, each tandemly arranged near the telomere. The phylogenetic analysis classified these genes into eight groups. The transcriptome analysis using leaf tissues collected before, during, and after vernalization revealed 49 upregulated and 31 downregulated CCT genes during vernalization, further validated by quantitative real-time PCR. Among the differentially expressed and well-investigated CCT gene clusters analyzed in this study, TaCMF11, TaCO18, TaPRR95, TaCMF6, and TaCO16 were induced during vernalization but decreased immediately after vernalization, while TaCO1, TaCO15, TaCO2, TaCMF8, and TaPPD1 were stably suppressed during and after vernalization. These data imply that some vernalization related CCT genes other than VRN2 may exist in wheat. This study improves our understanding of CCT genes and provides a foundation for further research on CCT genes related to vernalization in wheat.
Candida Pneumonia with Lung Abscess as a Complication of Severe COVID-19 Pneumonia

Abstract A South Asian male patient in his mid-forties presented with symptoms of severe 2019-nCoV (COVID-19) and recent brain infarction. Subsequently, he was found to have evidence of sepsis, underlying undetected diabetes mellitus (DM) and oral candida mucositis, possibly leading to the rare occurrence of direct spread to the lung, manifesting as a necrotizing candida lung abscess. We describe the diagnosis, clinical course, and management of the unique complication in this case that occurred during his admission, hospitalization, and eventual successful discharge from the hospital. This case highlights the importance of early identification and treatment of suspected COVID-19 infection based on clinical and radiological assessments before the confirmation of COVID-19 by real-time polymerase chain reaction (rtPCR) test result, especially in patients with hyperglycemia. It also indicates the complications that can occur due to COVID-19 such as arteriovenous manifestations and the rare occurrence of pulmonary candida lung abscess. Early detection and prompt management by interdisciplinary teams in the emergency room, followed by close monitoring of complications in the intensive care unit (ICU), can lead to successful outcomes in severe/critical COVID-19 infection.
Considerations When Choosing High-Fat, High-Fructose, and High-Cholesterol Diets to Induce Experimental Nonalcoholic Fatty Liver Disease in Laboratory Animal Models

ABSTRACT Nonalcoholic fatty liver disease (NAFLD) is intricately linked to metabolic disease (including obesity, glucose intolerance, and insulin resistance) and encompasses a spectrum of disorders including steatosis, nonalcoholic steatohepatitis (NASH), and fibrosis. Rodents consuming high-fat (HF; ∼40 kcal% fat including fats containing higher concentrations of saturated and trans fats), high-fructose (HFr), and high-cholesterol (HC) diets display many clinically relevant characteristics of NASH, along with other metabolic disorders. C57BL/6 mice are the most commonly used animal model because they can develop significant metabolic disorders including severe NASH with fibrosis after months of feeding, but other models also are susceptible. The significant number of diets that contain these different factors (i.e., HF, HFr, and HC), either alone or in combination, makes the choice of diet difficult. This methodology review describes the efficacy of these nutrient manipulations on the NAFLD phenotype in mice, rats, guinea pigs, hamsters, and nonhuman primates.
DisProt in 2022: improved quality and accessibility of protein intrinsic disorder annotation

Abstract The Database of Intrinsically Disordered Proteins (DisProt, URL: https://disprot.org) is the major repository of manually curated annotations of intrinsically disordered proteins and regions from the literature. We report here recent updates of DisProt version 9, including a restyled web interface, refactored Intrinsically Disordered Proteins Ontology (IDPO), improvements in the curation process and significant content growth of around 30%. Higher quality and consistency of annotations is provided by a newly implemented reviewing process and training of curators. The increased curation capacity is fostered by the integration of DisProt with APICURON, a dedicated resource for the proper attribution and recognition of biocuration efforts. Better interoperability is provided through the adoption of the Minimum Information About Disorder (MIADE) standard, an active collaboration with the Gene Ontology (GO) and Evidence and Conclusion Ontology (ECO) consortia and the support of the ELIXIR infrastructure.
The metabolic core of the prokaryotic community from deep-sea sediments of the southern Gulf of Mexico shows different functional signatures between the continental slope and abyssal plain

Marine sediments harbor an outstanding level of microbial diversity supporting diverse metabolic activities. Sediments in the Gulf of Mexico (GoM) are subjected to anthropic stressors including oil pollution with potential effects on microbial community structure and function that impact biogeochemical cycling. We used metagenomic analyses to provide significant insight into the potential metabolic capacity of the microbial community in Southern GoM deep sediments. We identified genes for hydrocarbon, nitrogen and sulfur metabolism mostly affiliated with Alpha and Betaproteobacteria, Acidobacteria, Chloroflexi and Firmicutes, in relation to the use of alternative carbon and energy sources to thrive under limiting growth conditions, and metabolic strategies to cope with environmental stressors. In addition, results show amino acids metabolism could be associated with sulfur metabolism carried out by Acidobacteria, Chloroflexi and Firmicutes, and may play a crucial role as a central carbon source to favor bacterial growth. We identified the tricarboxylic acid cycle (TCA) and aspartate, glutamate, glyoxylate and leucine degradation pathways, as part of the core carbon metabolism across samples. Further, microbial communities from the continental slope and abyssal plain show differential metabolic capacities to cope with environmental stressors such as oxidative stress and carbon limiting growth conditions, respectively. This research combined taxonomic and functional information of the microbial community from Southern GoM sediments to provide fundamental knowledge that links the prokaryotic structure to its potential function and which can be used as a baseline for future studies to model microbial community responses to environmental perturbations, as well as to develop more accurate mitigation and conservation strategies.