Miracle-dz/UniFAR-FTUs huggingface dataset:
Biallelic cGMP-dependent type II protein kinase gene (PRKG2) variants cause a novel acromesomelic dysplasia

Background C-type natriuretic peptide (CNP), its endogenous receptor, natriuretic peptide receptor-B (NPR-B), as well as its downstream mediator, cyclic guanosine monophosphate (cGMP) dependent protein kinase II (cGKII), have been shown to play a pivotal role in chondrogenic differentiation and endochondral bone growth. In humans, biallelic variants in NPR2, encoding NPR-B, cause acromesomelic dysplasia, type Maroteaux, while heterozygous variants in NPR2 (natriuretic peptide receptor 2) and NPPC (natriuretic peptide precursor C), encoding CNP, cause milder phenotypes. In contrast, no variants in cGKII, encoded by the protein kinase cGMP-dependent type II gene (PRKG2), have been reported in humans to date, although its role in longitudinal growth has been clearly demonstrated in several animal models. Methods Exome sequencing was performed in two girls with severe short stature due to acromesomelic limb shortening, brachydactyly, mild to moderate platyspondyly and progressively increasing metaphyseal alterations of the long bones. Functional characterisation was undertaken for the identified variants. Results Two homozygous PRKG2 variants, a nonsense and a frameshift, were identified. The mutant transcripts are exposed to nonsense-mediated decay and the truncated mutant cGKII proteins, partially or completely lacking the kinase domain, alter the downstream mitogen activation protein kinase signalling pathway by failing to phosphorylate c-Raf 1 at Ser43 and subsequently reduce ERK1/2 activation in response to fibroblast growth factor 2. They also downregulate COL10A1 and upregulate COL2A1 expression through SOX9. Conclusion In conclusion, we have clinically and molecularly characterised a new acromesomelic dysplasia, acromesomelic dysplasia, PRKG2 type (AMDP).
GENETIC DIVERGENCE STUDIES IN INDIGENOUS FRENCH BEAN (Phaseolus vulgaris L.) GERMPLASM

Mahalanobis D2 statistic was used to study genetic divergence for eighteen traits in a collection of forty four French bean genotypes, which were grouped into seven clusters. Hundred seed weight contributed 33.83% towards total divergence followed by pod weight and protein content. Maximum numbers of genotypes were found in cluster II and VI. Highest intracluster distance was observed for cluster V and lowest in cluster I, while maximum intercluster distance was observed between cluster III and cluster VI and minimum between cluster I and VI. Mean performance of individual clusters revealed that cluster VI genotypes performed better compared to genotypes of other cluster, which may be used for further improvement.
Effects of Environmental Diesel Exhaust Particles On Gastric Stem Cells

Even though the stem cells have attracted many scientists because of their unique properties and therapeutic applications, it is not known how the environmental toxic factors could affect their features and functions. This study is focusing on the interaction between environmental diesel exhaust particles (DEP) and the stomach stem cells. In the stomach, the stem cells are responsible for generating and maintaining different types of cells which are organized to form numerous tubular glands. The aim of this study was to examine the effects of DEP on the mouse gastric stem cells. The hypothesis is that DEP could have deleterious effects on the properties of mouse gastric stem cells such as their viability and migration. An immortalized mouse gastric stem cell line was used to develop a simple in vitro model to test the effects of exposure to various concentrations of DEP. Stem cells were cultured using routine tissue culture protocols. The DEP were added to the culture media at different concentrations: 1, 10, and 100 μg/ml for different time points up to 72 hours. Then, stem cells were analyzed using: cell viability assay, wound healing or migration assay, oxidative stress analysis by measurement of reduced glutathione, lipid peroxidation, and nitric oxide, expression analysis of genes specific for cell proliferation, cell death and oxidative stress using quantitative realtime polymerase chain reaction, and expression of stem cell specific proteins using western blotting. While DEP induced a reduction in the growth rate of gastric stem cells only at high concentration, no significant effects were found on cell migration, cell death related genes/proteins. Only minor changes were observed in oxidative stress parameters. However, these findings were interestingly associated with downregulation of Notch 1, 2 and 3 proteins. Since Notch signaling pathways play an important role in development and differentiation of stem cells, it will be interesting to determine which mechanisms and target genes are involved in an animal model of DEP exposure. In conclusion, this study establishes an in vitro model system to investigate the biological feature of gastric stem cells when exposed to environmental pollutants. In addition, demonstrating the effects of DEP on adult stem cells will help in raising public awareness about environmental hazardous agents.
Pre-trained Summarization Distillation

Recent state-of-the-art approaches to summarization utilize large pre-trained Transformer models. Distilling these models to smaller student models has become critically important for practical use; however there are many different distillation methods proposed by the NLP literature. Recent work on distilling BERT for classification and regression tasks shows strong performance using direct knowledge distillation. Alternatively, machine translation practitioners distill using pseudo-labeling, where a small model is trained on the translations of a larger model. A third, simpler approach is to 'shrink and fine-tune' (SFT), which avoids any explicit distillation by copying parameters to a smaller student model and then fine-tuning. We compare these three approaches for distillation of Pegasus and BART, the current and former state of the art, pre-trained summarization models, and find that SFT outperforms knowledge distillation and pseudo-labeling on the CNN/DailyMail dataset, but under-performs pseudo-labeling on the more abstractive XSUM dataset. PyTorch Code and checkpoints of different sizes are available through Hugging Face transformers here this http URL.
COVID-19: urgency for distancing from domestic violence

ABSTRACT Background: Although COVID-19 is a major worldwide health threat, there is another global public health emergency that is becoming a growing challenge. Domestic violence is a public health and human rights issue that primarily affects women and children worldwide. Several countries have reported a significant increase in domestic violence cases since the COVID-19-induced lockdowns and physical distancing measures were implemented. The COVID-19 health crisis is exacerbating another pre-existing public health problem by increasing the severity and frequency of domestic violence, thus demonstrating the need to adopt significant and long-term measures. Objective: Therefore, it is urgently necessary to promote and increase actions and policies to guarantee the safety and dignity of all victims of domestic violence worldwide. Methods: This paper describes preventive measures and action plans to combat violence against women and children during the COVID-19 pandemic. Conclusion: The prevention of domestic violence must indeed be every government’s priority and every citizen’s responsibility. HIGHLIGHTS • Violence against women 45 and children (VAWC) is a global health issue with important physical and psychological consequences. • COVID-19 is associated 50 with increased VAWC worldwide. • COVID-19 outbreak is anopportunity to take longlasting preventive actions of 55 VAWC.
Caring for Persons Living With Dementia During the COVID-19 Pandemic: Advocacy Perspectives From India

The Coronavirus disease 2019 (COVID-19) pandemic has presented an unprecedented threat to global public and psychosocial health. Certain vulnerable populations, especially the older adults, are at disproportionate risks both to the physiological and social effects of the outbreak. A special section among them who face unique challenges during this pandemic, are those living with neurocognitive disorders, like dementia. Limited research in the field shows ApoE4 allele to confer an increased risk for COVID-19 severity, while the behavioral problems associated with dementia reduces compliance to precautionary measures, thereby exposing them to the virus and increasing caregiver strain. Reduced healthcare access, limited resources and fear of the infection act as major barriers to dementia care during such a crisis. Besides, there are the additional burden of stigma, abuse, ageism and financial impoverishment. Institutionalization, loneliness and lack of stimulation can potentially accelerate the cognitive decline and worsen the behavioral and psychological problems. India has been one of the worst hit countries by COVID-19 and shares a significant dementia load. As the country is aging fast along with the world, this commentary reviews the risks of people living with dementia during the pandemic and discusses certain advocacies for their care.
Integration and Isolation in the Global Petrochemical Industry: A Multiscalar Corporate Network Analysis

abstract The global petrochemical industry has long been characterized by stable patterns of Western corporate and geographic leadership, but since the early 2000s, the global playing field has changed significantly. China has overtaken the US and Europe as the world’s largest petrochemical producer, and other emerging economies have become global petrochemical players. Combining insights from scholarship on global corporate elites, world city networks, and relational economic geography, this article examines patterns in the corporate networks of leading petrochemical corporations. The research is based on a multiscalar corporate network analysis, applying social network analysis to identify board interlocks, joint venture interlocks, and spatial interlocks between corporations. Through analyzing corporate networks across multiple scales, the research reveals patterns of both integration and isolation within the petrochemical industry. Isolation is evident in disconnected regional corporate elite networks, where the established North Atlantic corporate elite is interconnected through board interlocks, while corporate networks in Asia and other emerging economies remain disconnected. However, high levels of integration within the industry are also evident in an interconnected international company system formed through joint venture collaborations and in overlapping subsidiary networks centered on petrochemical hubs around the world. The article argues that the results demonstrate a combination of resilience and change, or path dependence and contingency, in patterns of corporate power and collaboration. Western company networks still form the social and spatial backbone of the industry, but these have been challenged by emerging strategic centers and isolated elite networks in other parts of the world. This article contributes to debates on industrial corporate elites, multiple globalizations, and the multipolar global economy.
Association between Inflammatory Bowel Disease and Lactose Intolerance: Fact or Fiction.

Background/Aims Inflammatory bowel disease (IBD) is a complex condition precipitated by genetic susceptibility and possibly a disturbed microbiome. The role of dairy foods in IBD is controversial. This study examined the association between lactose intolerance (LI) and IBD. Methods Data on hospital admissions of all IBD adult patients were extracted from the National Inpatient Sample database between 2004 and 2014. The comorbidities and outcomes of interest were defined by querying all the diagnostic and procedural fields for the corresponding International Classification of Diseases 9th version (ICD-9) codes. Patients with IBD were defined as the "study group," and the patients who did not have IBD were defined as the "control group". LI was identified in both groups using the ICD-9 codes. Multivariate logistic regression was performed to examine the association between IBD and LI. Results The total population was 71,342,237 patients, of which 598,129 (0.83%) had IBD. The IBD patients were younger (52 years vs. 57 years) and with fewer females (57.5% vs. 60.1%) (p<0.001 for all). After adjusting for the potential confounding factors, the IBD group had a significantly higher rate of LI (OR 2.71, 95% CI 2.55-2.88, p<0.001) compared to the non-IBD group. The findings were similar on the further stratification of IBD into Crohn's disease compared to the control group (OR 2.70, 95% CI 2.50-2.92, p<0.001) and ulcerative colitis compared to the control group (OR 2.71, 95% CI 2.46-2.98, p<0.001). Conclusions IBD patients have a 2.7 times higher risk of LI. Screening for LI in this population is warranted to avoid confusing or overlapping symptomatology.
Anxiety and depression in frontline health care workers during the outbreak of Covid-19

Background: The pandemic of coronavirus disease (Covid-19) seriously impacts the health and well-being of all of us. Aims: We aim to assess the psychological impact of Covid-19 on frontline health care workers (HCWs), including anxiety, depression and stress of threat of the disease. Method: The study was a cross-sectional survey among the frontline HCWs in a hospital at Jinan, China. Data were collected through an anonymous, self-rated questionnaire, including basic demographic data, a 10-item Covid-19 stress questionnaire, the Self-Rating Anxiety Scale (SAS) and the Self-Rating Depression Scale (SDS). The risk and rate of anxiety, depression and stress of Covid-19 were estimated. Results: Among the 309 participants, there were 88 (28.5%) with anxiety and 172 (56.0%) with depression. Multivariate logistic regression analyses showed that age ⩽ 30 years, age > 30 to 45 years, working in confirmed case isolation wards, and worrying about disinfection measures being not sufficient were independently associated with anxiety with an odds ratio (95% confidence interval, CI) of 4.4 (1.6–12.2), 3.1 (1.1–8.8), 2.3 (1.4–4.0) and 2.5 (1.5–4.3), respectively; age ⩽ 30 years, age > 30 to 45 years, nurse and worrying about disinfection measure being not sufficient were independently associated with depression with an odds ratio (95% CI) of 3.8 (1.8–7.8), 2.7 (1.3–5.7), 2.5 (1.1–5.6) and 2.1 (1.3–3.5), respectively. Conclusions: A high prevalence of anxiety and depression was found among frontline HCWs during the COVID-19 outbreak. More psychological care should be given to young staffs and nurses. Measures to prevent professional exposure is important for HCWs’ physical and mental health.
A novel checkpoint pathway controls actomyosin ring constriction trigger in fission yeast

In fission yeast, the septation initiation network (SIN) ensures temporal coordination between actomyosin ring (CAR) constriction with membrane ingression and septum synthesis. However, questions remain about CAR regulation under stress conditions. We show that Rgf1p (Rho1p GEF), participates in a delay of cytokinesis under cell wall stress (blankophor, BP). BP did not interfere with CAR assembly or the rate of CAR constriction, but did delay the onset of constriction in the wild type cells but not in the rgf1Δ cells. This delay was also abolished in the absence of Pmk1p, the MAPK of the cell integrity pathway (CIP), leading to premature abscission and a multi-septated phenotype. Moreover, cytokinesis delay correlates with maintained SIN signaling and depends on the SIN to be achieved. Thus, we propose that the CIP participates in a checkpoint, capable of triggering a CAR constriction delay through the SIN pathway to ensure that cytokinesis terminates successfully.
Response heterogeneity in a randomized controlled trial of telerehabilitation interventions among adults with multiple sclerosis

Introduction Telerehabilitation may be effective on average but is not equally effective among all people with multiple sclerosis (MS). Thus, the purpose of this secondary analysis of a randomized controlled trial was to explore whether baseline characteristics of participants with MS influence fatigue and physical activity outcomes of three telerehabilitation interventions. Methods Participants were randomized to contact-control intervention (CC), physical activity-only intervention (PA-only), and physical activity plus fatigue self-management intervention (FM+). The 12-week interventions were delivered over the phone. Sociodemographic (age and income), clinical (comorbidities, mental function and physical function), psychosocial (self-efficacy, outcome expectations and goal-setting), and behavioural baseline characteristics (step count and fatigue self-management behaviors) were used in a moderated regression analysis and a responder analysis to examine their influence on the Fatigue Impact Scale (FIS) and Godin Leisure-Time Exercise Questionnaire (GLTEQ) at post-test (i.e. immediately post-interventions). Results No interactions terms were statistically significant in the moderation analysis. However, the responder analysis showed that baseline psychosocial characteristics and mental function were significantly different (p < 0.05) between responders and non-responders. Specifically, non-responders on the FIS at post-test in the PA-only intervention had significantly lower baseline scores in goal setting for engaging in fatigue self-management behaviours. Also, non-responders on the GLTEQ at post-test in the FM+ intervention had significantly worse baseline scores in mental function. Discussion Further research is needed to understand the complex relationship among baseline characteristics, telerehabilitation and response heterogeneity. We discuss how research on examining response heterogeneity may be advanced by conducting mega-clinical trials, secondary analyses of big data, meta-analyses and employing non-traditional research designs. Trial registration Clinicaltrials.gov (NCT01572714).
The effectiveness of diacutaneous fibrolysis on pain, range of motion and functionality in musculoskeletal disorders: A systematic review and meta-analysis

Objective: To assess the effectiveness of diacutaneous fibrolysis in reducing musculoskeletal disorders symptoms such as pain, range of motion and functionality. Data sources: A systematic review of MEDLINE, Cochrane, PEDro and Science Direct was conducted until September 2020. Review methods: Computerized search strategy was performed to identify randomized controlled trials applying diacutaneous fibrolysis, on subjects with musculoskeletal disorders. Eligible articles and data extraction were conducted independently by two reviewers. Methodology quality and risk of bias were assessed by Risk of Bias 2 tool from the Cochrane Collaboration and Physiotherapy Evidence Database. Outcomes assessed were pain intensity, range of motion and functionality. Results: Search strategy identified 98 potential randomized control trials and six studies involving 386 participants, were finally included. Diacutaneous fibrolysis intervention added to usual physiotherapy treatment was compared to control group. Pain intensity immediately after treatment showed a pooled Standard Mean Difference (SMD) of –0.58 with 95% confidence interval (CI) from –1.12 to –0.04, and in the longest follow-up SMD was –0.63 with 95% CI (–1.21 to –0.05). Functionality showed a pooled SMD of –1.02 with 95% CI (–1.67 to –0.36) immediately after intervention and a SMD of –0.84 with 95% CI (–1.54 to –0.14). Range of motion could not be included in the quantitative synthesis. Conclusion: Diacutaneous fibrolysis is an effective treatment, when combined with conventional physiotheraphy, reducing pain immediately after treatment and long term follow-up and improving function in both, short and long term in musculoskeletal disorders.
AlSi10Mg alloy produced by Selective Laser Melting: relationships between Vickers microhardness, Rockwell hardness and mechanical properties

Selective Laser Melted Al10SiMg samples were directly aged at different temperatures and times to establish the best mechanical properties for this alloy. The problem of finding meaningful relationships between hardness and tensile strengths has been addressed for materials produced by additive manufacturing technology. Relationships between hardness and yield and ultimate tensile strengths have been calculated by combining Hollomon parameters (the strain hardening exponent ‘n’ and the strength coefficient ‘K’) for the Selective Laser Melted Al10SiMg alloy. Firstly, the pre-existing relationships were considered and verified for AlSi10Mg SLMed alloy. Moreover, the relationship derived from ASTM standards and Hollomon parameters were calculated from the engineering stress – strain curves. Afterwards, the measured values of Rockwell hardness (HRF) and Vickers hardness (HV) were related to each other by a simple equation according to theory. The results showed the accuracy of this equation with respect to the theoretical one. Finally, the yield strength, UTS and ultimate strength (σb, in function of strain hardening exponent and natural base e) obtained by different condition of thermal treatments (175 °C, 200 °C and 225 °C for 2h, 4h and 6h) were related to Vickers hardness values.
Implementation of machine learning models for the prediction of vaginal birth after cesarean delivery

Abstract Objective Accurate prediction of vaginal birth after cesarean is crucial for selecting women suitable for a trial of labor after cesarean (TOLAC). We sought to develop a machine learning (ML) model for prediction of TOLAC success and to compare its accuracy with that of the MFMU model. Methods All consecutive singleton TOLAC deliveries from a tertiary academic medical center between February 2017 and December 2018 were included. We developed models using the following ML algorithms: random forest (RF), regularized regression (GLM), and eXtreme gradient-boosted decision trees (XGBoost). For developing the ML models, we disaggregated BMI into height and weight. Similarly, we disaggregated prior arrest of progression into prior arrest of dilatation and prior arrest of descent. We applied a nested cross-validation approach, using 100 random splits of the data to training (80%, 792 samples) and testing sets (20%, 197 samples). We used the area under the precision-recall curve (AUC-PR) as a measure of accuracy. Results Nine hundred and eighty-nine TOLAC deliveries were included in the analysis with an observed TOLAC success rate of 85.6%. The AUC-PR in the RF, XGBoost and GLM models were 0.351 0.028, 0.350 0.028 and 0.336 0.024, respectively, compared to 0.325 0.067 for the MFMU-C. The algorithms performed significantly better than the MFMU-C (p-values = .0002, .0004, .0393 for RF, XGBoost, GLM respectively). In the XGBoost model, eight variables were sufficient for accurate prediction. In all ML models, previous vaginal delivery and height were among the three most important predictors of TOLAC success. Prior arrest of descent contributed to prediction more than prior arrest of dilatation, maternal height contributed more than weight. Conclusion All ML models performed significantly better than the MFMU-C. In the XGBoost model, eight variables were sufficient for accurate prediction. Prior arrest of descent and maternal height contribute to prediction more than prior arrest of dilation and maternal weight.