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Hence, the developed nanocomposite starch hydrogel serves as a highly desirable bio-ink for advancing 3D tissue engineering.COVID-19 is a global health crisis that has caused ripples in every aspect of human life. Amid widespread vaccinations testing, manufacture and distribution efforts, nations still rely on human mobility restrictions to mitigate infection and death tolls. New waves of infection in many nations, indecisiveness on the efficacy of existing vaccinations, and emerging strains of the virus call for intelligent mobility policies that utilize contact pattern and epidemiological data to check contagion. Our earlier work leveraged network science principles to design social distancing optimization approaches that show promise in slowing infection spread however, they prove to be computationally prohibitive and require complete knowledge of the social network. In this work, we present scalable and distributed versions of the optimization approaches based on Markov Chain Monte Carlo Gibbs sampling and grid-based spatial parallelization that tackle both the challenges faced by the optimization strategies. We perform extensive simulation experiments to show the ability of the proposed strategies to meet necessary network science measures and yield performance comparable to the optimal counterpart, while exhibiting significant speed-up. We study the scalability of the proposed strategies as well as their performance in realistic scenarios when a fraction of the population temporarily flouts the location recommendations.Hemodialysis constitutes the lifeline of patients with end stage renal disease, yet the parameters that affect hemodialyzer performance remain incompletely understood. We developed a computational model of mass transfer and solute transport in a hollow-fiber dialyzer to gain greater insight into the determinant factors. The model predicts fluid velocity, pressure, and solute concentration profiles for given geometric characteristics, membrane transport properties, and inlet conditions. We examined the impact of transport and structural parameters on uremic solute clearance by varying parameter values within the constraints of standard clinical practice. The model was validated by comparison with published experimental data. Our results suggest solute clearance can be significantly altered by changes in blood and dialysate flow rates, fiber radius and length, and net ultrafiltration rate. Our model further suggests that the main determinant of the clearance of unreactive solutes is their diffusive permeability. The clearance of protein-bound toxins is also strongly determined by blood hematocrit and plasma protein concentrations. Results from this model may serve to optimize hemodialyzer operating conditions in clinical practice to achieve better clearance of pathogenic uremic solutes.The study provides baseline data regarding 17- β -estradiol (E 2 ), progesterone (P 4 ), and cortisol profile of 30 Nicastrese goats during different physiological periods. Animals were evaluated monthly from the pre-mating period (non-pregnant), during pregnancy, and from 30 to 105 d of lactation. The effects of single or twin births and the kid's sex were also considered. Serum E 2 , P 4 , and cortisol concentrations were measured using immunoenzymatic assay kits. The highest concentrations of E 2 and P 4 ( P  130-150 d of gestation. Different physiological conditions induced a temporal relationship with the endocrine profile in Nicastrese goats. Understanding the effects of single or twin fetuses on the gestation and lactation will also be helpful to improve the managemental approach for the health of mothers and their kids.Although it is one of the core cultural values of Asian American families and an influential determinant of youth development, familism remains under-studied among Asian Americans and, despite crucial within-group heterogeneity, lacks subgroup specificity. This study describes the ways in which two major Asian American subgroups of youth, i.e., Filipino Americans and Korean Americans, maintain traditional familism. Specifically, this study constructed six self-report subscales of familism utilizing underused and new survey items and tested their psychometric properties. Using data collected from Filipino American (n=150) and Korean American (n=188) adolescents living in a Midwest metropolitan area, the measures were examined for validity and reliability for each group and, when appropriate, for measurement invariance across the groups. The main findings are that the finalized scales demonstrated solid reliability and validity (e.g., content and construct) in each group and some invariance and that core traditions, in the form of familism values and behaviors, persevere among second-generation Asian Americans, although familism was more evident among Filipino American youth than in Korean American youth. In both groups, subdomains of familism were not as discrete as found among their parents, who were predominantly foreign-born first-generation immigrants. The finalized familism scales were associated differently with several correlates including acculturation variables and youth outcomes. The findings are discussed with a call for further empirical research of diverse ethnic groups and immigrant generations to more accurately account for how family process interacts with cultural origin and acculturation.Home confinement during the Covid-19 pandemic is usually associated with worsening mental health. In the case of older adults, although they have been identified as a vulnerable group in terms of mental health, the results of studies on the relationship between home confinement and mental health are not consistent and few studies have adopted a gender perspective. Using data from the SHARE Corona Survey (2020), we aimed to analyse the role of gender on the relationship between home confinement and increased depression in individuals aged 50 and over living in Europe and Israel. Our study shows that, although women reported increased depression/sadness during the Covid-19 pandemic more often than men, it was the latter who experienced the greatest increase.The study of premature deaths from causes that are generally preventable given the current availability of healthcare - called amenable deaths due to healthcare - provides information on the quality of services. However, they are not only impacted by healthcare characteristics other factors are also likely to influence. Therefore, identifying the association between amenable deaths due to healthcare and health determinants, such as education, might be the key to preventing these deaths in the future. Still unclear however, is how this works and how amenable deaths due to healthcare are distributed and evolve within the European Union (EU) below the national level. We therefore studied the geographical and temporal patterns of amenable deaths due to healthcare in the 259 EU regions from 1999 to 2016, including the 2007-2008 financial crisis and the post-2008 economic downturn, and identified whether any association with education exists. A cross-sectional ecological study was carried out. Using a hierarchical anding of the amenable deaths due to healthcare and allow for the application of more effective policies.Since facing outbreaks of severe acute respiratory syndrome and avian influenza A in 2003, Vietnam has increasingly applied a One Health approach to address emerging infectious diseases of animal origin. Here, we reflect on the challenges and opportunities of One Health in the context of zoonoses, food safety, and antimicrobial resistance, drawing on a stocktake of One Health training, policy, and research in Vietnam. We also report on the results of a virtual consultation workshop held on July 2021 with representatives from 32 institutions in Vietnam to explore future One Health directions. As Vietnam approaches nearly two decades of disease preparedness and response, we hope our experiences can provide practical insights to support countries in developing coordination mechanisms and moving the One Health agenda forward toward better public health outcomes.

Early warning and objective evidence of systematic errors in laboratory diagnosis ensures evidence based corrective and preventive actions that instill patient safety and confidence. External quality assessment contributes significantly to the above as an essential component of laboratory quality assurance. However, implementation of External Quality Assessment in resource-limited settings is challenged by high costs of enrolling in international schemes. To ensure sustainability, a National External Quality Assessment Program in Armenia was developed using a One Health approach.

Through engagement of stakeholders from Ministry of Health and Department of Agriculture under Ministry of Economy the government of Armenia started the implementation of the Armenia Laboratory External Quality Assessment (ALEQA) program. Policies and procedures were defined, a web interface for return of results and feedback reporting was created. A training was offered for characterization of simulated samples for bacterial pathogens. Following a pilot survey, the program was successfully scaled up, with later addition of a Brucella serology discipline.

The return rate of results was 100% for all surveys. There was an improvement in the performance of the laboratories from the 2015 to the 2019 surveys. The bacterial pathogens EQA survey's, was interrupted between 2017 and 2019. The Brucella Serology survey showed 77% of the 26 participating laboratories had satisfactory performance.

This is one of the few National EQA Programs that have embraced the One Health approach to improve reach of EQA Programs in resource-limited settings in both human and veterinary laboratories.

This is one of the few National EQA Programs that have embraced the One Health approach to improve reach of EQA Programs in resource-limited settings in both human and veterinary laboratories.Progressive disorders are highly heterogeneous. Symptom-based clinical classification of these disorders may not reflect the underlying pathobiology. Data-driven subtyping and staging of patients has the potential to disentangle the complex spatiotemporal patterns of disease progression. Tools that enable this are in high demand from clinical and treatment-development communities. Here we describe the pySuStaIn software package, a Python-based implementation of the Subtype and Stage Inference (SuStaIn) algorithm. SuStaIn unravels the complexity of heterogeneous diseases by inferring multiple disease progression patterns (subtypes) and individual severity (stages) from cross-sectional data. GSK-3 activation The primary aims of pySuStaIn are to enable widespread application and translation of SuStaIn via an accessible Python package that supports simple extension and generalization to novel modelling situations within a single, consistent architecture.Accurately predicting users' perceived stress is beneficial to aid early intervention and prevent both mental illness and physical disease during the COVID-19 pandemic. However, the existing perceived stress predicting system needs to collect a large amount of previous data for training but has a limited prediction range (i.e., next 1-2 days). Therefore, we propose a perceived stress prediction system based on the history data of micro-EMA for identifying risks 7 days earlier. Specifically, we first select and deliver an optimal set of micro-EMA questions to users every Monday, Wednesday, and Friday for reducing the burden. Then, we extract time-series features from the past micro-EMA responses and apply an Elastic net regularization model to discard redundant features. After that, selected features are fed to an ensemble prediction model for forecasting fine-grained perceived stress in the next 7 days. Experiment results show that our proposed prediction system can achieve around 4.26 (10.65% of the scale) mean absolute error for predicting the next 7 day's PSS scores, and higher than 81% accuracy for predicting the next 7 day's stress labels.