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Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Medical University of Warsaw and São Paulo Research Foundation (FAPESP). Introduction Coronavirus disease 2019 (COVID-19) is associated with an increased risk of mortality and adverse cardiovascular (CV) occurrences, especially in a group of patients with CV diseases (CVD). SARS-CoV-2 virus enters cells through angiotensin converting enzyme 2 (ACE2) cell membrane enzymes, leading to the downregulation in the ACE2-related pathways. Based on our previous in silico [1] results we hypothesized that alteration in the ACE2 interaction network caused by virus infection can affect the expression of miRNAs and influence severity of the disease. Purpose In this study we aimed to analyse the diagnostic and predictive utility of ACE2-related miRNAs, which were identified in our previous in silico analysis (miR-10b-5p, miR-124-3p, miR-200b-3p, miR-26b-5p, miR-302c-5p) in patients with COVID-19. We also aimed to unravel the functions of analyzed miRNAs, by using machine learning based tools, including SHAP for clinical data analysis, and bioinformatic tools for data mining, target predictions and enrichment analyses. Methods Blood samples and clinical data of 79 COVID-19 patients were collected at three different time points, including the day of admission, 7-days and 21-days after admission, as well as one time-point of 32 healthy volunteers. The composite endpoint was hospitalisation length of stay (>21 days) and/or death in follow-up. Results Delta low miR-200b-3p expression (after 7-days of admission) presents predictive utility in assessment of the hospital length of stay and/or death in ROC curve analysis (AUC:0.730, p=0.002) (Fig. 1). Delta low miR-200b-3p expression, together with diabetes mellitus (DM) are independent predictors of increased hospital length of stay and/or death (OR= 5.775; CI= 1.572- 21.214; p= 0.008, OR= 4.888; CI= 1.001- 23.858; p= 0.050, respectively). The expression levels of miR-26b-5p and miR-10b-5p in COVID-19 patients were found lower at the baseline, 7 and 21-days after admission compared to the healthy controls (p SHAP analysis indicated levels of miR 200b-3p (day 7th), miR-302c-5p (day 7th), CRP (day 7th), neutrophils (day 0), and D-Dimer (day 0) as the most promising predictors of long hospitalisation for the COVID-19 patients. Pathway enrichment analysis showed that among top shared pathways between targets of analyzed miRNAs were IL-2 signaling pathway, and Pathways in cancer. miR-200b-3p showed regulation of COVID-19-related targets associated with T cell protein tyrosine phosphatase and HIF-1 transcriptional activity in hypoxia, key pathways in COVID-19. Bioinformatics analysis pointed out the role of those miRNAs in multiple CVD phenotypes associated with COVID-19 (Fig. 2). Conclusions In this study we validated and characterized miRNAs which could serve as novel, predictive biomarkers of the COVID-19 long term hospitalisation and can be used for early stratification of patients and prediction of severity of infection development in an individual.

Background:Dissociative disorder is a stress-related disorder usually present in adolescent and younger age group. It is also accompanied with significant impairment in activity of daily living and family relationship. Family environment plays important role in initiation and maintenance of symptoms and this put significant burden on family. To assess different types of clinical presentations, level of stress and role of family environment among dissociative disorder patients and check for association between sex distributions. Material and Method:This cross-sectional descriptive study was carried out on patients with primary diagnosis of dissociative disorder as per ICD-10 criteria coming to psychiatry outpatient department of Sri Aurobindo Medical College and Postgraduate Institute, Indore a premier tertiary care hospital situated at northern part of India, covering, and serving a large catchment area, during the period of 18 months. 80 patients were recruited for the purpose of study. The procedure and rationale for the study was explained to all subjects and informed written consent were taken in their local language. Patients were included after fulfilling inclusion criteria from both inpatients and outpatient department of psychiatry. Result:In our study, majority of the patients (48.75%) belonged to the age group 18-30 years. The prevalence rates decrease with age. 37.5% of the patients were between the age group 31-40 years and 13.75% were over the age of 40 years. In a study of 80 patients with dissociative (conversion) disorder, 77.5% were females and 22.5% were male. There was female predominance. Conclusion:Dissociative disorders are more common in females than males. It always occurs in the background of increased stressful life events and in the presence of significant psychosocial stressors. Future studies should be undertaken in a large sample with a prospective design to examine the impact of disease duration and other mediators, such as family type and coping style. &nbsp

Tables containing detailed results of statistical data analysis as additional supplementary material to complement the results presented in the research article.

We sought to develop machine learning (ML) models trained on administrative data which predict risk of readmission in patients with heart failure and to evaluate and compare the ML model with the currently used LaCE score using clinically informative metrics.This prognostic study was conducted in Alberta, Canada, on 9845 patients with confirmed heart failure admitted to hospital between 2012 and 2019. The outcome was unplanned all-cause hospital readmission within 30 days of discharge. We used 80% of the data for the ML model development and 20% for independent validation. We reported, using the validation set, c-statistics (area under the receiver operating characteristic curves)and performance metrics (likelihood ratio, positive predictive values) for the XGBoost model and a modified LaCE score within their respective predictive thresholds. Boosted tree-based classifiers had higher area under the receiver operating characteristic curves (0.65 for XGBoost) compared with others (0.58 for neural networks) and 0.57 for the modified LaCE. Within the predicted threshold range of the XGBoost classifier, the positive likelihood ratio was 1.00 at the low end of predicted risk and 6.12 at the high end, resulting in a positive predictive value (post-test probability) range of 21%-62%; the pretest probability of readmission was 20.9% using prevalence. The corresponding positive likelihood ratios and positive predictive values across LaCE score thresholds were 1.00-1.20 and 21%-24%, respectively.Despite predicting readmissions better than the LaCE, even the best ML model trained on administrative health data (XGBoost) did not provide substantially informative prediction performance as it only generated a moderate shift from pre to post-test probability. Health systems wishing to deploy such a tool should consider training ML models with additional data. Adding other techniques like natural language processing, along with ML, to use other clinical information (like chart notes) might improve prediction performance.

Fulvestrant is a selective oestrogen receptor (ER) degrader used in postmenopausal women with hormone receptor-positive advanced breast cancer. The study aim was to analyse demographics and outcomes of UK patients treated with fulvestrant monotherapy at nine representative centres.Medical records of 459 patients with locally advanced or metastatic ER-positive, HER2-negative breast cancer treated with fulvestrant between August 2011 and November 2018 at nine UK centres were reviewed. Data were collated on demographics, progression-free survival, overall survival and disease response at first radiological assessment following fulvestrant initiation. Patients still alive by December 2018 were censored.Data from 429 of the 459 patients identified were eligible for inclusion in the analysis. The median age was 69 (range 21-95) and 64% (n = 275) had Eastern Cooperative Oncology Group performance status 0-1. Bone was the most commonly involved metastatic site (72%, n = 306). However, 295 (69%) patients had visceral involvement. Patients had received a median 2 (range 0-5) prior lines of endocrine therapy and median 0 (range 0-6) prior chemotherapies. Fulvestrant was first-line therapy in 43 patients (10%). The median duration of treatment was 5 months (range 1-88). The median progression-free survival was 5.5 months. In 51% of 350 patients radiologically assessed, there was evidence of disease response to fulvestrant. Fifteen per cent of these had a complete/partial response. Fulvestrant was discontinued predominantly due to disease progression, with 3% discontinued solely due to adverse events. The median overall survival for the whole cohort was 22.5 months (range 0-88).This is one of the largest studied cohorts of breast cancer patients treated with fulvestrant. This heavily endocrine-pretreated population reflects real-life use in the UK. Within this context, our retrospective data show that patients can experience maintained disease response when treated with fulvestrant, supporting the importance of equitable availability for all UK patients.

Highlights Accounting for variability and uncertainty empowers stakeholders to make better-informed decisions. Considering spatial and temporal sources of variability contributes to more robust modeling systems. Stochastic methods that factor in uncertainty contribute to a better understanding of the FEW nexus systems. A robust modeling system will contribute to the design of resilient FEW nexus systems. Abstract. A nexus approach contributes to the strategic allocation of resources to secure food, energy, and water for the world population. Integrated models considering the complex interactions across food, energy, and water (FEW) enhance decision-making and strategic planning towards resilience. However, a significant number of the existing integrated models leave unaddressed the inherent variability and uncertainty present in the FEW sectors. Here, we review the importance of characterizing variability over spatial and temporal scales and the importance of decreasing the uncertainty present within a FEW nexus systems. The review also discusses existing modeling tools that address variability and uncertainty on single and paired elements of the FEW nexus systems, as well as integrated tools that address the sources of variability and uncertainty across the nexus. Finally, the review highlights the opportunity to address the limitations of existing models through multidisciplinary approaches and the potential to integrate publicly available models, as has already been the case for single and coupled elements of the FEW nexus. Addressing variability and uncertainty would improve the robustness of a FEW systems modeling and would provide stakeholders with the capacity to make better-informed decisions. Keywords: Climate variability, Food-water-energy nexus, Modeling, Spatial variability, Temporal variability, Uncertainty.

Introduction: Early treatment for hypertension (HTN) portends better outcomes. However, few real-world studies have assessed initial antiHTN regimens and how they differ by baseline blood pressure (BP). We sought to compare initial treatment patterns, stratified by BP, between Medicaid and Medicare recipients. Methods: We performed a cross-sectional study of adults with newly-treated HTN in the One Florida+ Consortium(2012-2020) who had linked claims-EHR data from the treatment initiation visit. Eligible patients were Floridians with Medicaid or Medicare aged ≥18 years, with diagnosed HTN, who filled ≥1 first-line antiHTN class with no evidence of anti HTN fills during the year prior (in which continuous insurance enrollment was required). Baseline BP was categorized per current HTN guidelines, and logistic regression was used to estimate age-adjusted odds of combination vs. monotherapy, per 10 mmHg increase in systolic BP (SBP) or diastolic BP (DBP). Results: We included 2,902 patients (47% Medicaid, 53% Medicare); mean age was 44 (Medicaid) and 67 yrs(Medicare); 60% (64% and 56%, respectively) were women and 42% (57% and 29%, respectively) were Black. Initial antiHTN classes were similar comparing cohorts: ACEI, ARB and thiazide initiation varied little by BP category, in contrast to CCBs and β-blockers (Figure, panels A-B). In age-adjusted analyses, use of initial combination therapy was 40% more likely (OR, 1.40; 95% CI, 1.11, 1.76) among Medicare recipients and inversely related to BP category (panels C-D) among Medicare patients, in which each 10mmHg greater SBP (OR, 0.93; 95% CI, 0.88, 0.97) and DBP (OR 0.82; 95% CI, 0.75, 0.90) had lower odds of combination therapy. Among Medicaid recipients, only SBP associated with combination therapy (OR1.11; 95% CI, 1.03, 1.20). Conclusions: We observed similar initial class patterns among Medicaid & Medicare recipients across baseline BP, but differential use of combination therapy was less likely at higher baseline BP in Medicare recipients, which contrasts current guidance.

Background Sickle cell disease causes microvascular occlusion in different vascular beds. In kidneys, it leads to occult glomerular dysfunction causing asymptomatic microalbuminuria, proximal tubulopathy causing hyposthenuria and increased free water loss and distal tubulopathy causing poor urine acidification. We studied the prevalence of various types of renal dysfunction, the ability of different tests to detect it at an early stage and the correlation of these parameters in children receiving hydroxyurea (HU). Procedure Fifty-six children (sample size calculated using SAS9.2 package) attending paediatric clinical services in a tertiary care hospital between 2 and 12 years of age diagnosed by high-performance liquid chromatography (HPLC) were enrolled. Their demographic and laboratory data including renal and urine parameters were collected. Parameters like fractional excretion of sodium (FeNa), trans tubular potassium gradient (TtKg) and free water clearance (TcH2O) were derived by calculations. Data were analysed using IBM SPSS Version 21.0 and Microsoft Office Excel 2007. Results We found a significant number of children to have microalbuminuria (17.8%), hyposthenuria (30.4%) and impaired renal tubular potassium excretion (TtKg) (81.3%). A significant correlation was found between the dose of HU with urine osmolality (p Conclusion Renal dysfunction is common in children with SCD and can be detected early using simple urine parameters and can be prevented with an early and appropriate dosage of HU with good compliance.

Product design is a key aspect of human intelligence and creativity, attracting not only experts but also people without any formal design training. Although numerous people in developing countries design and manufacture products in metalworking microenterprises in the informal sector, there is still little knowledge about their design process. This paper aims to fill this gap in design knowledge. We aim to investigate the design processes in metalworking microenterprises in the informal sector of Tanzania. In particular, we aim to explore how these microenterprises identify consumer needs and requirements, how they determine the specifications for the product, how they generate and evaluate alternative product concepts, and how they define product details. To address these aims, semistructured interviews were carried out in metalworking microenterprises operating in the informal sector of Tanzania. The findings reveal many facets of their design processes, providing a sound basis upon which design methods and tools can be developed to support their design activities.

Influenza strains circulating among swine populations can cause outbreaks in humans. In October 2020, we detected a variant influenza A subtype H1N2 of swine origin in a person in Alberta, Canada. We initiated a public health, veterinary, and laboratory investigation to identify the source of the infection and determine whether it had spread. We identified the probable source as a local pig farm where a household contact of the index patient worked. Phylogenetic analysis revealed that the isolate closely resembled strains found at that farm in 2017. Retrospective and prospective surveillance using molecular testing did not identify any secondary cases among 1,532 persons tested in the surrounding area. Quick collaboration between human and veterinary public health practitioners in this case enabled a rapid response to a potential outbreak.

Background Knowledge of real‐world antihypertensive use is limited to prevalent hypertension, limiting our understanding of how treatment evolves and its contribution to persistently poor blood pressure control. We sought to characterize antihypertensive initiation among new users. Methods and Results Using Medicaid and Medicare data from the OneFlorida+ Clinical Research Consortium, we identified new users of ≥1 first‐line antihypertensives (angiotensin‐converting enzyme inhibitor, calcium channel blocker, angiotensin receptor blocker, thiazide diuretic, or β‐blocker) between 2013 and 2021 among adults with diagnosed hypertension, and no antihypertensive fill during the prior 12 months. We evaluated initial antihypertensive regimens by class and drug overall and across study years and examined variation in antihypertensive initiation across demographics (sex, race, and ethnicity) and comorbidity (chronic kidney disease, diabetes, and atherosclerotic cardiovascular disease). We identified 143 054 patients initiating 188 995 antihypertensives (75% monotherapy; 25% combination therapy), with mean age 59 years and 57% of whom were women. The most commonly initiated antihypertensive class overall was angiotensin‐converting enzyme inhibitors (39%) followed by β‐blockers (31%), calcium channel blockers (24%), thiazides (19%), and angiotensin receptor blockers (11%). With the exception of β‐blockers, a single drug accounted for ≥75% of use of each class. β‐blocker use decreased (35%–26%), and calcium channel blocker use increased (24%–28%) over the study period, while initiation of most other classes remained relatively stable. We also observed significant differences in antihypertensive selection across demographic and comorbidity strata. Conclusions These findings indicate that substantial variation exists in initial antihypertensive prescribing, and there remain significant gaps between current guideline recommendations and real‐world implementation in early hypertension care.

Introduction SARS-CoV-2 tropism for the ACE2 receptor, along with the multifaceted inflammatory reaction, is likely to drive the generalized hypercoagulable state seen in patients with COVID-19. Methodology Using the original bioinformatic workflow and network medicine approaches we reanalyzed four coronavirus-related expression datasets and performed co-expression analysis focused on thrombosis and ACE2 related genes. We identified microRNAs (miRNAs) which play role in ACE2-related thrombosis in coronavirus infection and further, we validated the expressions of those miRNAs in 79 hospitalized COVID-19 patients and 32 healthy volunteers by PCR and monitored miRNAs patterns during the acute phase of COVID-19, as well as the prognostic potential of these miRNAs as biomarkers. Results We identified EGFR, HSP90AA1, APP, TP53, PTEN, UBC, FN1, ELAVL1 and CALM1 as regulatory genes which could play a pivotal role in COVID-19 related thrombosis. We also found miR-16-5p, miR-27a-3p, Let-7b-5p and miR-155-5p as regulators in coagulation and thrombosis process. We observed in separate cohort of COVID-19 patients and healthy controls that (i) expression of miR-16-5p, miR-27a-3p and miR-155-5p increased during observation, compared to the baseline measurement; (ii) a low baseline miR-16-5p expression presents predictive utility in assessment of the hospital length of stay or death in follow-up as a composite endpoint (AUC: 0.810, 95% CI, 0.71–0.91, p Conclusion This study enabled us to better characterize changes in gene expression and signaling pathways related to COVID-19 thrombosis. In this study we identified, characterized and validated miRNAs which could serve as novel, thrombosis-related biomarkers of the COVID-19, can be used for early stratification of patients and prediction of severity of infection development in an individual. Funding Acknowledgement Type of funding sources: Public Institution(s). Main funding source(s): Medical University of Warsaw