Miracle-dz/UniFAR-FTUs huggingface dataset:
Experiences of Home Care Nurses During the COVID-19 Pandemic

Background The COVID-19 pandemic has provoked several changes in home care. Understanding home care nurses’ experiences during the COVID-19 pandemic plays an essential role in home care management. Objective This study aimed to explore and articulate the experience of home care nurses during the COVID-19 pandemic in Spain. Design A qualitative study using hermeneutic phenomenology was carried out. Twenty home care nurses were interviewed by teleconference between January and March 2021. Interviews were audio-recorded, transcribed verbatim, and analyzed using qualitative data analysis software. Results Three main themes with five subthemes emerged from the data analysis: (a) “The effect of COVID-19 pandemic on home care,” with the subtheme “the reorganization of home care nurses’ competencies”; (b) “The role of telehealth in home care,” which included the subthemes “home care nurses’ satisfaction with telehealth” and “barriers to implement telehealth in home care”; and (c) “Effects of the pandemic on home care nurses’ lives,” including the subthemes “working in a pandemic is emotionally draining” and “the continuing fear of infecting others. ” Discussion The findings from this study demonstrate the profound effect that home care has experienced during the COVID-19 pandemic. Home care nurses’ competencies were modified to care for and diagnose COVID-19 patients. Face-to-face home care was replaced by telehealth. All home care nurses experienced physical and psychological symptoms and the fear of infecting others.
The translatome of neuronal cell bodies, dendrites, and axons

Significance Proteins are the key drivers of neuronal synaptic function. The regulation of gene expression is important for the formation and modification of synapses throughout the lifespan. The complexity of dendrites and axons imposes unique challenges for protein supply at remote locations. The discovery of messenger RNAs (mRNAs) and ribosomes near synapses has shown that local protein synthesis represents an important solution to this challenge. Here we used RNA sequencing and ribosome sequencing to determine directly the population of mRNAs that is present and in the process of translation in neuronal cell bodies, dendrites, and axons. Thousands of transcripts were differentially translated between the cell body and synaptic regions with over 800 mRNAs exhibiting more translation in the dendritic–axonal compartment. To form synaptic connections and store information, neurons continuously remodel their proteomes. The impressive length of dendrites and axons imposes logistical challenges to maintain synaptic proteins at locations remote from the transcription source (the nucleus). The discovery of thousands of messenger RNAs (mRNAs) near synapses suggested that neurons overcome distance and gain autonomy by producing proteins locally. It is not generally known, however, if, how, and when localized mRNAs are translated into protein. To investigate the translational landscape in neuronal subregions, we performed simultaneous RNA sequencing (RNA-seq) and ribosome sequencing (Ribo-seq) from microdissected rodent brain slices to identify and quantify the transcriptome and translatome in cell bodies (somata) as well as dendrites and axons (neuropil). Thousands of transcripts were differentially translated between somatic and synaptic regions, with many scaffold and signaling molecules displaying increased translation levels in the neuropil. Most translational changes between compartments could be accounted for by differences in RNA abundance. Pervasive translational regulation was observed in both somata and neuropil influenced by specific mRNA features (e.g., untranslated region [UTR] length, RNA-binding protein [RBP] motifs, and upstream open reading frames [uORFs]). For over 800 mRNAs, the dominant source of translation was the neuropil. We constructed a searchable and interactive database for exploring mRNA transcripts and their translation levels in the somata and neuropil [MPI Brain Research, The mRNA translation landscape in the synaptic neuropil. https://public.brain. mpg.de/dashapps/localseq/. Accessed 5 October 2021]. Overall, our findings emphasize the substantial contribution of local translation to maintaining synaptic protein levels and indicate that on-site translational control is an important mechanism to control synaptic strength.
Molecular Epidemiology of Mycobacterium tuberculosis strains isolated from pulmonary tuberculosis patients in south Ethiopia

Introduction: Understanding the epidemiology of tuberculosis is limited by lack of genotyping data. We sought to characterize the drug susceptibility testing patterns and genetic diversity of M. tuberculosis isolates in southern Ethiopia. Methodology: A cross-sectional study was conducted among newly diagnosed sputum smear positive patients with tuberculosis visiting nine health facilities in southern Ethiopia from June 2015 to May 2016. Three consecutive sputum samples (spot-morning-spot) per patient were examined using acid-fast bacilli smear microscopy with all smear positive specimens having acid-fast bacilli cultures performed. M. tuberculosis isolates had drug susceptibility testing performed using indirect proportion method and were genotyped with RD9 deletion analysis and spoligotyping. Mapping of strain was made using geographic information system. Results: Among 250 newly diagnosed patients with tuberculosis, 4% were HIV co-infected. All 230 isolates tested were M. tuberculosis strains belonging to three lineages: Euro-American, 187 (81%), East-African-Indian, 31 (14%), and Lineage 7 (Ethiopian lineage), 8 (4%); categorized into 63 different spoligotype patterns, of which 85% fell into 28 clusters. M. tuberculosis strains were clustered by geographic localities. The dominant spoligotypes were SIT149 (21%) and SIT53 (19%). Drug susceptibility testing found that 14% of isolates tested were resistant to ≥ 1 first line anti- tuberculosis drugs and 11% to INH. SIT 149 was dominant among drug resistant isolates. Conclusions: The study revealed several clusters and drug resistant strains of M. tuberculosis in the study area, suggesting recent transmission including of drug resistant tuberculosis. Wider monitoring of drug susceptibility testing and geospatial analysis of transmission trends is required to control tuberculosis in southern Ethiopia.
Eye colour and skin pigmentation as significant factors for refractive outcome and residual accommodation in hypermetropic children: a randomized clinical trial using cyclopentolate 1% and tropicamide 1%

To compare the refractive outcome and residual accommodation with respect to various degrees of iris and skin pigmentation in hypermetropic children using 2 drops of cyclopentolate 1% (C + C) or 1 drop of cyclopentolate 1% and 1 drop of tropicamide 1% (C + T).
Post‐infection functional gastrointestinal disorders following coronavirus disease‐19: A case–control study

Because acute infectious gastroenteritis may cause post‐infection irritable bowel syndrome and functional dyspepsia and the severe acute respiratory syndrome coronavirus‐2 affects gastrointestinal (GI) tract, coronavirus disease‐19 (COVID‐19) may cause post‐infection‐functional GI disorders (FGIDs). We prospectively studied the frequency and spectrum of post‐infection‐FGIDs among COVID‐19 and historical healthy controls and the risk factors for its development.
Deep-AFPpred: identifying novel antifungal peptides using pretrained embeddings from seq2vec with 1DCNN-BiLSTM

Fungal infections or mycosis cause a wide range of diseases in humans and animals. The incidences of community acquired; nosocomial fungal infections have increased dramatically after the emergence of COVID-19 pandemic. The increase in number of patients with immunodeficiency / immunosuppression related diseases, resistance to existing antifungal compounds and availability of limited therapeutic options has triggered the search for alternative antifungal molecules. In this direction, antifungal peptides (AFPs) have received a lot of interest as an alternative to currently available antifungal drugs. Although the AFPs are produced by diverse population of living organisms, identifying effective AFPs from natural sources is time-consuming and expensive. Therefore, there is a need to develop a robust in silico model capable of identifying novel AFPs in protein sequences. In this paper, we propose Deep-AFPpred, a deep learning classifier that can identify AFPs in protein sequences. We developed Deep-AFPpred using the concept of transfer learning with 1DCNN-BiLSTM deep learning algorithm. The findings reveal that Deep-AFPpred beats other state-of-the-art AFP classifiers by a wide margin and achieved approximately 96% and 94% precision on validation and test data, respectively. Based on the proposed approach, an online prediction server is created and made publicly available at https://afppred.anvil. app/. Using this server, one can identify novel AFPs in protein sequences and the results are provided as a report that includes predicted peptides, their physicochemical properties and motifs. By utilizing this model, we identified AFPs in different proteins, which can be chemically synthesized in lab and experimentally validated for their antifungal activity.
Rational, emotional, or both? Subcomponents of psychopathy predict opposing moral decisions

Abstract Recent research has documented a small but significant correlation between psychopathic capacities and utilitarian moral judgment, although the findings are generally inconsistent and unclear. We propose that one way to make sense of mixed findings is to consider variation in perspective‐taking capacities of psychopathic individuals. With this in mind, we had criminal offenders (n = 60), who varied in their psychopathy levels according to the Psychopathy Checklist‐Revised (PCL‐R), respond to common sacrificial moral dilemmas (e.g., trolley dilemmas) under different conditions. In a baseline condition, participants simply responded to the sacrificial moral dilemmas as is typically done in previous research. In an “emotion‐salient” condition, participants had to reason about the emotions of another person after solving moral dilemmas (deliberative processing). In the “emotion‐ambiguous” condition, participants saw images of people in distress, after solving moral dilemmas, but did not have to explicitly reason about such emotions (spontaneous processing). The four PCL‐R facets predicted distinct interference effects depending on spontaneous versus deliberative processing of hypothetical victim's emotions. The findings suggest that the use of a multi‐faceted approach to account for cognitive and moral correlates of psychopathy may help address previously mixed results. Implications and future directions for theory and research are discussed.
Causes and Consequences of Polycystic Ovary Syndrome: Insights from Mendelian Randomization.

CONTEXT Though polycystic ovarian syndrome (PCOS) is the most common endocrinopathy affecting women of reproductive age, risk factors that may cause the syndrome are poorly understood. Based on epidemiologic studies, PCOS is thought to cause several adverse outcomes such as cardiovascular disease; however, the common presence of co-morbidities such as obesity may be responsible for such associations, rather than PCOS in and of itself. To overcome the limitations of observational studies, investigators have employed Mendelian randomization (MR), which uses genetic variants to interrogate causality between exposures and outcomes. EVIDENCE ACQUISITION To clarify causes and consequences of PCOS, this review will describe MR studies involving PCOS, both as an exposure and as an outcome. The literature was searched using the terms Mendelian randomization, Mendelian randomization, polycystic ovary syndrome, polycystic ovarian syndrome, and PCOS (to May 2021). EVIDENCE SYNTHESIS MR studies have suggested that obesity, testosterone levels, fasting insulin, serum SHBG concentrations, menopause timing, male-pattern balding and depression may play a causal role in PCOS. In turn, PCOS may increase the risk of estrogen receptor positive breast cancer, decrease the risk of endometrioid ovarian cancer, and have no direct causal effect on type 2 diabetes, coronary heart disease, or stroke. CONCLUSIONS The accumulation of genome-wide association studies in PCOS has enabled multiple MR analyses identifying factors that may cause PCOS or be caused by PCOS. This knowledge will be critical to future development of measures to prevent PCOS in girls at risk as well as prevent complications in those who have PCOS.
In‐vivo estimation of tissue electrical conductivities of a rabbit eye for precise simulation of electric field distributions during ocular iontophoresis

Precise estimation of electrical conductivity of the eyes is important for the accurate analysis of electric field distributions in the eyes during ocular iontophoresis. In this study, we estimated the tissue electrical conductivities of a rabbit eye, which has been widely employed for neuro‐ophthalmological experiments, through an in vivo experiment for the first time. Electrical potentials were measured at multiple locations on the skin, while weak currents were transmitted into the skin via two surface electrodes attached to the skin around the eye. A finite element model was constructed to calculate the electric potentials at the measurement locations. The conductivity values of different tissues were then estimated using an optimization procedure to minimize the difference between the measured and calculated electric potentials. The accuracy of the estimated tissue conductivity values of the rabbit eye was validated by comparing the measured and calculated electric potential values for different electrode montages. Further multi‐physical analyses of iontophoretic drug delivery to the rabbit eye showed a significant influence of the conductivity profile on the resultant particle distribution. Overall, our results provide an important reference for the tissue electrical conductivity values of the rabbit eye, which could be further utilized for designing new medical devices for delivering electric fields to the eyes, such as transorbital and transscleral electrical stimulations.
Risk factors for poor outcome of patients with Coronavirus disease 2019 (COVID-19) in Albania.

INTRODUCTION The study aims to identify potential risk factors for the poor outcome of hospitalized patients with SARS-CoV-2 infection in Albania. METHODOLOGY A retrospective observational study on 133 consecutive hospitalized patients at "COVID 1" Hospital, University Hospital Center of Tirana. The study analyzed the correlation between potential risk factors and in-hospital mortality. RESULTS The study included 133 patients, 65.4% of the patients were male, age 60.46 ± 13.53 years. The mortality rate resulted in 22.6%. Univariate analysis revealed that early risk factors for mortality included: laboratory alterations on admission, such as lymphocytes count < 1.000/mm3 (OR = 3.30, 95% CI = 1.17-9.33), lactate dehydrogenase > 250 U/L (OR = 12.48, 95% CI = 1.62-95.78) and D dimer > 2 mg/L (OR = 4.72, 95% CI = 1.96-11.36); lung parenchymal involvement > 75% on chest computed tomography on admission (OR = 54.00, 95% CI = 11.89 - 245.11). Cox proportional hazard regression showed that independent risk factors for mortality were lung parenchymal involvement > 75% on chest computed tomography (HR = 8.31, 95%CI: 1.62-42.45) and occurrence of complications during hospital stay (OR = 10.28, 95% CI = 2.02-52.33). CONCLUSIONS The risk of poor outcome can be predicted from the early stage of COVID 19 disease, using laboratory data and chest computed tomography. Among patients with COVID 19, lung parenchymal involvement and alterations > 75% on chest computed tomography on admission and laboratory findings, such as lymphocytopenia, and elevated lactate dehydrogenase and D dimer levels, turned out to be early risk factors for in-hospital mortality.
EMS Experience Caring and Communicating with Patients and Families with a Life-Limiting-Illness

Abstract Introduction: The emergency medical services (EMS) system was designed to reduce death and disability and EMS training focuses on saving lives through resuscitation, aggressive treatment and transportation to the emergency department. EMS providers commonly care for patients who have life-limiting illnesses. The objective was to explore EMS provider challenges, self-perceived roles and training experiences caring for patients and families with life-limiting illness. Methods: Qualitative content analysis of semi-structured interviews with EMS providers (n = 15) in Alameda County, CA. Purposive sampling was used to ensure a variety of perspectives including provider age, years of EMS experience, emergency medical technicians and paramedics, fire-based versus private, transport versus non-transporting. Recorded and transcribed interviews were analyzed using a thematic approach. Results: In their work with patients with life-limiting illness, participating EMS providers were interviewed and reported challenges for which their formal training had not prepared them: responding to grief and emotion expressed by families during traumatic events or death notification, and performing in the moment decision-making to determine the course of action after acute, unexpected, and traumatic events. Many participants reported becoming comfortable with grief counseling and death notification after acquiring some clinical experience. In the moment decision-making was eased when patients and families had had advance care planning discussions, however many patients, especially those from vulnerable and underserved populations, lacked advance care planning. In the face of situations where the course of action was not immediately clear, EMS providers voiced two frames for their role in caring for patients with life-limiting illness: transportation only (“transport people”) versus a more “holistic” view, where EMS providers provided counseling and information about available resources. Conclusions: EMS providers interface with patients who have life-limiting illness and their families in the setting of traumatic events where the course of action is often unclear. There is an opportunity to provide formal training to EMS providers around grief counseling as well as how they can assist patients and families in in the moment decision-making to support previously identified goals and align care with patient goals and preferences.
Mendelian randomization in the multivariate general linear model framework

Mendelian randomization (MR) is an application of instrumental variable (IV) methods to observational data in which the IV is a genetic variant. MR methods applicable to the general exponential family of distributions are currently not well characterized. We adapt a general linear model framework to the IV setting and propose a general MR method applicable to any full‐rank distribution from the exponential family. Empirical bias and coverage are estimated via simulations. The proposed method is compared to several existing MR methods. Real data analyses are performed using data from the REGARDS study to estimate the potential causal effect of smoking frequency on stroke risk in African Americans. In simulations with binary variates and very weak instruments the proposed method had the lowest median [Q1, Q3] bias (0.10 [−3.68 to 3.62]); compared with 2SPS (0.27 [−3.74 to 4.26]) and the Wald method (−0.69 [−1.72 to 0.35]). Low bias was observed throughout other simulation scenarios; as well as more than 90% coverage for the proposed method. In simulations with count variates, the proposed method performed comparably to 2SPS; the Wald method maintained the most consistent low bias; and 2SRI was biased towards the null. Real data analyses find no evidence for a causal effect of smoking frequency on stroke risk. The proposed MR method has low bias and acceptable coverage across a wide range of distributional scenarios and instrument strengths; and provides a more parsimonious framework for asymptotic hypothesis testing compared to existing two‐stage procedures.
Artificial Intelligence in Toxicological Pathology: Quantitative Evaluation of Compound-Induced Follicular Cell Hypertrophy in Rat Thyroid Gland Using Deep Learning Models

Digital pathology has recently been more broadly deployed, fueling artificial intelligence (AI) application development and more systematic use of image analysis. Here, two different AI models were developed to evaluate follicular cell hypertrophy in hematoxylin and eosin-stained whole-slide-images of rat thyroid gland, using commercial AI-based-software. In the first, mean cytoplasmic area measuring approach (MCA approach), mean cytoplasmic area was calculated via several sequential deep learning (DL)-based algorithms including segmentation in microanatomical structures (separation of colloid and stroma from thyroid follicular epithelium), nuclear detection, and area measurements. With our additional second, hypertrophy area fraction predicting approach (HAF approach), we present for the first time DL-based direct detection of the histopathological change follicular cell hypertrophy in the thyroid gland with similar results. For multiple studies, increased output parameters (mean cytoplasmic area and hypertrophic area fraction) were shown in groups given different hypertrophy-inducing reference compounds in comparison to control groups. Quantitative results correlated with the gold standard of board-certified veterinary pathologists’ diagnoses and gradings as well as thyroid hormone dependent gene expressions. Accuracy and repeatability of diagnoses and grading by pathologists are expected to be improved by additional evaluation of mean cytoplasmic area or direct detection of hypertrophy, combined with standard histopathological observations.
Effect of modified levonorgestrel‐releasing intrauterine system in human adenomyosis with heavy menstrual bleeding

The levonorgestrel‐releasing intrauterine (LNG‐IUS) system is an effective primary treatment for adenomyosis; however, it has high expulsion rates. We aimed to modify the system—allowing affixion to the myometrium—and evaluate the expulsion rate, effectiveness, and side effects in patients with adenomyosis and heavy menstrual bleeding.
COVID-19 mRNA vaccine allergy

Supplemental Digital Content is available in the text Purpose of review A known history of a severe allergic reaction (e.g., anaphylaxis) to any component of the vaccine is the only contraindication to coronavirus disease 2019 (COVID-19) mRNA vaccination. It is important for pediatricians to understand the likelihood of an allergic reaction to COVID-19 mRNA vaccines, including its excipients. Recent findings Episodes concerning for anaphylaxis were immediately reported following early administration of COVID-19 mRNA vaccines to adults. Although allergic type symptoms were reported equally in recipients of placebos and test vaccines in phase 3 clinical trials, post-authorization prospective studies state that 0.2–2% of vaccine recipients have experienced allergic reactions. Subsequent allergy testing of affected individuals has focused largely on evaluation of allergic sensitization to a novel vaccine excipient, polyethylene glycol (PEG). PEG is a polymer incorporated in numerous pharmaceutical products because of its favorable, inert properties. The results of allergy testing in adults to date indicate that IgE mediated anaphylaxis to PEG allergy is rarely identified after COVID-19 mRNA vaccine reactions. Numerous individuals with presumed anaphylaxis have tolerated a second vaccine after evaluation and testing by an allergist, suggesting either misdiagnosis or a novel immune mechanism. Summary Confirmed anaphylactic reactions to COVID-19 mRNA vaccines are rare, likely due to a lack of preexisting IgE against the vaccine components, including PEG.