bluuebunny/crossref_metadata_2025_split huggingface dataset:
Social Cohesion Strengthens Compliance With COVID-19 Restrictions: Evidence From a Longitudinal Study
Authors: Borinca Islam , Griffin siobhan , McHugh Cillian , Bradshaw Daragh , Jay Sarah , Roth Jenny , Quayle Mike , McMahon Grace , Nightingale Alastair , Ryan Megan , Foran Aoife Marie , Galvin Rose , Muldoon Eavan G. , Muldoon Orla 
Published: October 2021

Abstract
Background: Although citizens in countries worldwide took coordinated steps to support collective public health during the COVID-19 pandemic, the processes that encourage citizens to adhere with COVID-19 restrictions are not fully understood. Method: A three-wave study with a sample of Irish citizens (N Wave 1 = 1,800) was conducted during the COVID-19 pandemic in order to examine the effect of national trust on individual and normative compliance with COVID-19 restrictions directly or indirectly through social cohesion. Two longitudinal mediation models were tested. Results: In the first model, national trust significantly and positively predicted social cohesion, which in turn significantly and positively predicted personal compliance with COVID-19 restrictions. The second model showed a similar pattern, whereby national trust significantly predicted social cohesion, which in turn predicted normative compliance with the restrictions. Conclusions: National trust and social cohesion both work to promote adherence to COVID19 guidelines.
Clonal Evolution Characteristics and Reduced Dimension Prognostic Model for Non-Metastatic Metachronous Bilateral Breast Cancer
Authors: Li Lingyu , Li Jiaxuan , Jia Jiwei , He Hua , Li Mingyang , Yan Xu , Yu Qing , Guo Hanfei , Wang Hong , Lv Zheng , Sun Haishuang , Liao Guidong , Cui Jiuwei 
Published: October 2021

Abstract
Background:How to evaluate the prognosis and develop overall treatment strategies of metachronous bilateral breast cancer (MBBC) remains confused in clinical practice.Methods:Data from Surveillance, Epidemiology, and End Results (SEER) database and the first hospital of Jilin university were analyzed for breast cancer-specific cumulative mortality (BCCM) by competing risk model. Whole-exome sequencing was applied for 10 lesions acquired at spatial-temporal distinct regions from 5 patients to reconstruct clonal evolutionary characteristics of MBBC. Dimensional reduction (DR) cumulative incidence function (CIF) curves of MBBC features were established on different point in diagnostic interval time, to build a novel DR nomogram.Results:Significant heterogeneity in genome and clinical features of MBBC was widespread. The mutational diversity of contralateral BC (CBC) was significantly higher than that in primary BC (PBC), and the most effective prognostic MATH ratio was significantly correlated with interval time (R2=0.85, p < .05). In SEER cohort study (n=13304), the interval time was not only significantly affected the BCCM by multivariate analysis (p < .000), but determined the weight of clinical features (T/N stage, grade and ER status) on PBC and CBC in prognostic evaluation. Thus, clinical parameters after DR based on interval time were incorporated into the nomogram for prognostic predicting BCCM. Concordance index was 0.773 (95% CI, 0.769 to 0.776) in training cohort (n=8869), and 0.819 (95% CI, 0.813 to 0.826) in validation cohort (n=4435).Conclusions:Bilateral heterogeneous characteristics and interval time were determinant prognostic factors of MBBC. The DR nomogram may help clinical prognostic evaluation.
Impact of Calcium Channel Blockers on Aspirin Reactivity in Patients With Coronary Artery Disease
Authors: Kodesh Afek , Lev Eli , Leshem-Lev Dorit , Solodky Alejandro , Kornowski Ran , Perl Leor 
Published: October 2021

Abstract
Purpose: Calcium channel blockers (CCBs) do not reduce the risk of initial or recurrent myocardial infarction (MI) in patients diagnosed with stable coronary artery disease (CAD). The aim of this current study was to evaluate the association between CCBs and aspirin resistance in patients with CAD. Methods: Patients with stable CAD who were regularly taking aspirin (75-100 mg qd) for at least one month prior to enrollment in the study were included. The VerifyNow system was used for platelet function testing with high on-aspirin platelet reactivity (HAPR) defined as aspirin reaction units (ARU) >550. We compared patients treated with CCBs versus control group. Results: 503 patients with CAD were included in this study, 88 were treated with CCBs; Mean age (67.9±9.7 in the CCB group vs 66.5±11.4 in the control group, p=0.288), gender (77.3 male vs. 82.9%, p=0.214) and rates of diabetes mellitus (34.7 vs. 36.9%, p=.121) were similar. Rates of hypertension were higher in the CCB group (83.9 vs. 63.5%, p<0.01), but rates of past MI were lower (47.1 vs. 59.7%, p=0.039). The mean ARU was 465.4P70.0 for patients treated with CCBs versus 445.2u60.0 in controls (p=0.006). Similarly, 15.9% of CCB patients demonstrated HAPR compared to 7.0% (p=0.006). In a multivariate analysis, the administration of CCBs was independently associated with HAPR (OR- 1.72, 95% CI 1.04 – 8.91, p=0.047). Conclusions: Usage of CCBs is positively correlated with aspirin resistance. These findings may suggest an adverse pharmacologic effect of CCBs among patients with stable CAD treated with aspirin.
Studying and Mitigating the Effects of Data Drifts on ML Model Performance at the Example of Chemical Toxicity Data
Authors: Morger Andrea , de Lomana Marina Garcia , Norinder Ulf , Svensson Fredrik , Kirchmair Johannes , Mathea Miriam , Volkamer Andrea 
Published: October 2021

Abstract
Machine learning models are widely applied to predict molecular properties or the biological activity of small molecules on a specific protein. Models can be integrated in a conformal prediction (CP) framework which adds a calibration step to estimate the confidence of the predictions. CP models present the advantage of ensuring a predefined error rate under the assumption that test and calibration set are exchangeable. In cases where the test data have drifted away from the descriptor space of the training data, or where assay setups have changed, this assumption might not be fulfilled and the models are not guaranteed to be valid. In this study, the performance of internally valid CP models when applied to either newer time-split data or to external data was evaluated. In detail, temporal data drifts were analysed based on twelve datasets from the ChEMBL database. In addition, discrepancies between models trained on publicly available data and applied to proprietary data for the liver toxicity and MNT in vivo endpoints were investigated. In most cases, a drastic decrease in the validity of the models was observed when applied to the time-split or external (holdout) test sets. To overcome the decrease in model validity, a strategy for updating the calibration set with data more similar to the holdout set was investigated. Updating the calibration set generally improved the validity, restoring it completely to its expected value in many cases. The restored validity is the first requisite for applying the CP models with confidence. However, the increased validity comes at the cost of a decrease in model efficiency, as more predictions are identified as inconclusive. This study presents a strategy to recalibrate CP models to mitigate the effects of data drifts. Updating the calibration sets without having to retrain the model has proven to be a useful approach to restore the validity of most models.
A high-flux, self-cleaning solar water evaporation system
Authors: Dang Chenyang , Chen Meihua , Huang Lin , Chu Mingming , Li Yiming , Liu Lujia , Cao Xue 
Published: October 2021

Abstract
Solar interfacial evaporation is a promising technology to produce clean water from seawater or polluted water. However, the evaporation rate upon existing photothermal materials is normally limited to 2 kg m-2 h-1 or below, which is hard to fulfil the daily water demand of a family, let alone enormous water requirements in agricultural and industrial sectors. Herein, under the guidance of computational fluid dynamics (CFD) simulations, multichannel photothermal rod (MCPR) is proposed as solar interfacial material for evaporative disposal of real municipal sewage and concurrent production of freshwater. The production rate of the freshwater over 10-centimetre-high MCPR is 18.8 kg m-2 h-1 under 1 sun, with water quality equivalent to that of commercial pure water. When the light is incident at oblique angles, faster evaporation rates are obtained (e.g., 31.3 kg m-2 h-1 at 30° angle). Furthermore, the freshwater generation rate can even be promoted to 126.5 kg m-2 h-1 in outdoor environment via a magnified evaporation system constructed of 35-centimetre-high MCPRs array. These values were achievable due to a series of properties of the MCPR, including antigravity water transport, omnidirectional collection of solar energy, minimization of heat dissipation, and maximization of the evaporation interface.
Estimating Snakebite Risk in the Terai, Nepal: A High-Resolution Geospatial and One Health Analysis
Authors: Ochoa Carlos , Pittavino Marta , Martins Sara Babo , Alcoba Gabriel , Bolon Isabelle , de Castañeda Rafael Ruiz , Joost Stéphane , Sharma Sanjib , Chappuis François , Ray Nicolas 
Published: October 2021

Abstract
Most efforts to understand snakebite burden in Nepal have been localized to relatively small areas and focused on humans through epidemiological studies. We present the outcomes of a geospatial analysis of the factors influencing snakebite risk in humans and animals, based on both a national-scale multi-cluster random survey and, environmental, climatic, and socio-economic gridded data for the Terai region of Nepal. The resulting Integrated Nested Laplace Approximation models highlight the importance of poverty as a fundamental risk-increasing factor, augmenting the snakebite odds in humans by 63.9 times. For animals, the minimum temperature of the coldest month was the most influential covariate, increasing the snakebite odds 23.4 times. Several risk hotspots were identified along the Terai, helping to visualize at multiple administrative levels the estimated population numbers exposed to different probability risk thresholds in one year. These analyses and findings could be replicable in other countries and for other diseases.
A Comparative Study of Natural Language Processing Algorithms Based on Cities Changing Diabetes’ Vulnerability Data
Authors: Wang Siting , Song Fuman , Qiao Qinqun , Liu Yuanyuan , Chen Jiageng , Ma Jun 
Published: October 2021

Abstract

Background: Diabetes has become a global public health priority resulting in significant workforce losses and health care expenditures. Therefore, research on diabetes vulnerability has become imperative. Current methods for studying disease vulnerability mainly use qualitative research methods represented by Thematic Analysis (TCA), which has the disadvantage of being staff-intensive for long periods of time. Natural Language Processing (NLP) could achieve efficient results in information mining tasks, but we didn't find many studies talking about NLP in non-infectious chronic diseases.Methods: In this study, hyperparameters were adjusted to obtain more cost-effective model applicable to The Cities Changing Diabetes’ vulnerability data by comparing Bidirectional Encoder Representation from Transformers (BERT) and Enhanced Language Representation with Informative Entities (ERNIE) in terms of test accuracy, completion time and evaluation metrics on classification.Results: The results showed that BERT took less time for the same hyperparameter cases, and the test accuracy of ERNIE was slightly better than that of BERT. We further adjusted the Batch size of ERNIE as we found that ERNIE with the splitting ratio of 8:1:1 and Batch size of 64 had the better efficiency with the test accuracy was 97.67%, the completion time was 12min36s and Macro-F1 score was 0.9734.Conclusions: In this study, BERT overwhelmed ERNIE in terms of completion speed with the same hyperparameters. ERNIE showed higher accuracy, especially the ideal performance at the split ratio of 8:1:1 after enhancing the Batch size. From the point of view, we pursue a model with high accuracy and fast processing speed, which means that we can obtain the highest accuracy in the shortest time. It could be selected according to the actual situation in the application process.
Psychometric Assessment of a Weight Management Social Provisions Survey in a Sample of Adults with Prediabetes
Authors: Wilson Kathryn E. , Michaud Tzeyu L. , Sweet Cynthia Castro , Katula Jeffrey A. , Almeida Fabio A. , Brito Fabiana A. , Schwab Robert , Estabrooks Paul A. 
Published: October 2021

Abstract
Background: The relevance of social support for weight management is not well documented in people with prediabetes. An important consideration is the adequate assessment of social provisions related to weight management in this population.Purpose: To assess the factor structure and measurement invariance of an adapted Social Provisions Scale specific to weight management (SPS-WM) in adults with prediabetes (n=599).Methods: Participants of a diabetes prevention trial completed a demographic survey, and the SPS-WM. Confirmatory analyses tested the factor structure of the SPS-WM, and measurement invariance was assessed for gender, weight status, education level, and age.Results: Removal of two collinear items resulted in acceptable model fit, supporting six correlated factors for social provisions specific to weight management. Measurement invariance was supported across all subgroups.Conclusion: Results support score interpretations for these scales reflecting distinct components of social support specific to weight management in alignment with those of the original survey.
A spatial vaccination strategy to reduce the risk of vaccine-resistant variants
Authors: Zhang Xiyun , Lobinska Gabriela , Feldman Michal , Dekel Eddie , Nowak Martin , Pilpel Yitzhak , Pauzner Yonatan , Barzel Baruch , Pauzner Ady 
Published: October 2021

Abstract
The process of vaccinating the world population against COVID-19 is expected to take well over a year to complete. As vaccination progresses and population immunity increases, a counteracting relaxation of social distancing measures is observed. The result will be a prolonged period of high disease prevalence combined with a fitness advantage for vaccine-resistant variants, implying a considerably increased probability that a resistant variant will spread in the population. In this paper we propose a spatial vaccination strategy that has the potential to dramatically reduce this risk. Instead of spreading the vaccination effort equally throughout a country, distinct geographic regions of the country are sequentially vaccinated, quickly bringing each to effective herd immunity. Regions with high vaccination rates will then have low infection rates and vice versa. Since people primarily interact with others in their own region, spatial vaccination will reduce the number of encounters between infected people (the source of mutations) and vaccinated people (who facilitate the spread of vaccine-resistant strains). Thus with proper logistic preparations, a spatial vaccination campaign could be highly effective in reducing the global risk of vaccine-resistant variants.
Xiaoyao Pill Improves the Affective Dysregulation of Sleep-deprived Female
Mice by Inhibiting Brain Injury and Regulating the Content of Monoamine
Neurotransmitter
Authors: Li Yujie , Wei Dandan , Zhang Minghao , Yue Tiantian , Du Huimin , Liu Qi , Gan Shihu , Liu Hanbin , Dong Yijie , Qiao Xinyue , Zhang Yichi , Yang Liping 
Published: October 2021

Background:
Sleep curtailment is a serious problem in many societies. Clinical evidence has shown that sleep deprivation is associated with mood dysregulation, formation of false memory, cardio-metabolic risk factors and outcomes, inflammatory disease risk, and all-cause mortality. The affective disorder dysregulation caused by insufficient sleep has become an increasingly serious health problem. However, to date, not much attention has been paid to the mild affective dysregulation caused by insufficient sleep, and there is no clear and standard therapeutic method to treat it. The Xiaoyao Pill is a classic Chinese medicinal formula, with the effect of dispersing stagnated hepatoqi, invigorating the spleen, and nourishing the blood. Therefore, it is most commonly used to treat gynecological diseases in China. In the present study, the effects of the Xiaoyao Pill on affective dysregulation of sleep-deprived mice and its underlying molecular mechanisms were investigated.

Methods:
Forty adult female mice were used in the present study. The sleep deprivation model was established by improving the multi-platform water environment method. After 7 consecutive days of sleep deprivation, the mice were administrated low (LXYP, 0.32mg/kg) and high (HXYP, 0.64 mg/kg) doses of the Xiaoyao Pill for two weeks. Then, the body weight, behavioral deficits, and histopathology were evaluated. Meanwhile, the expression of c-fos protein and the concentrations of monoamine neurotransmitters in the hippocampus and prefrontal cortex were determined after two weeks of treatment.

Results:
Xiaoyao Pill treatment significantly increased body weight and sucrose consumption and decreased the irritability scores of the sleep-deprived mice. Meanwhile, Xiaoyao Pill treatment prevented brain injury and inhibited the expression of c-fos protein in the hippocampus and prefrontal cortex. In addition, HXYP treatment significantly upregulated the levels of NE in the hippocampus and prefrontal cortex (p < 0.01). LXYP treatment significantly up-regulated the levels of 5-HT in the prefrontal cortex. Meanwhile, both HXYP and LXYP treatment significantly up-regulated the levels of DA in the prefrontal cortex (p < 0.05 or p < 0.01) of sleep-deprived mice.

Conclusions:
The present study demonstrates that Xiaoyao Pill treatment prevented the behavioral deficits of mice induced by sleep deprivation by promoting the recovery of brain tissue injury and up-regulating the levels of NE, 5-HT, and DA in the brain tissue.
Clinical Efficacy of Functional Electrical Stimulation-assisted Rehabilitation
Cycling on the Function of Lower Limbs in Patients with Stroke
Authors: Zhang Xiao-Hua , Liu Jia-Yu , Han Ping , Wang Yu-Long , Xiao Peng 
Published: October 2021

Objective:
To explore the efficacy of functional electrical stimulation (FES)-assisted rehabilitation
cycling on the functional recovery of lower limbs in patients with hemiplegic stroke
and the assessment value of surface electromyography (sEMG).

Methods:
A total of 66 patients with stroke accompanied by hemiplegia of the lower limbs were enrolled
in the present prospective study and randomly divided into the experimental group and control
group, with 33 patients in each group. FES-assisted rehabilitation cycling was applied in the experimental
group, while only rehabilitation cycling was performed without setting the stimulation
parameters in the control group. sEMG and the Fugl-Meyer assessment (FMA) were carried out,
and the modified Barthel index (MBI) of the lower limbs was assessed before treatment and after 4
weeks and 8 weeks of treatment.

Results:
There were no significant differences in the evaluation results of sEMG, FMA, and MBI
of the lower limbs between the two groups of patients before the treatment (p > 0.05). After 4
weeks of treatment, compared with the control group, there were significant differences in the results
of sEMG, FMA, and MBI of the lower limbs in the experimental group (p < 0.05). In the experimental
group, the difference in sEMG was statistically significant (p < 0.05). After 8 weeks of
treatment, compared with the control group, there were significant differences in the results of
sEMG, FMA, and MBI of the lower limbs in the experimental group (p < 0.05). In the experimental
group, the differences in the results of sEMG, FMA, and MBI of the lower limbs were statistically
significant (p < 0.05). The inter-group comparison of the results of sEMG, FMA and MBI of the
lower limbs was statistically significant (p < 0.05) in the control group.

Conclusion:
FES-assisted rehabilitation cycling might promote the recovery of the motor function
of the lower limbs in patients with stroke and improve the sEMG signal of the lower limbs.
Therapeutic Potential of Indole Derivatives as Anti-HIV Agents: A
Mini-review
Authors: Chen Qingtai , Wu Chongchong , Zhu Jinjin , Li Enzhong , Xu Zhi 
Published: October 2021

:
Acquired immunodeficiency syndrome (AIDS), caused by the human immunodeficiency virus (HIV), is one of the leading causes of human deaths. The advent of different anti-HIV drugs has turned AIDS/HIV from a deadly infection to chronic and manageable disease. However, the devel-opment of multidrug-resistant viruses, along with the severe side effects of anti-HIV agents, has com-promised their efficacy and limited the treatment options. Indoles, the most common frameworks in the bioactive molecules, represent attractive scaffolds for designing and developing novel drugs. In-dole derivatives are potent inhibitors of HIV enzymes such as reverse transcriptase, integrase, and protease. Furthermore, some indole-based agents, like delavirdine, have already been applied in clin-ics or are under clinical evaluations for the treatment of AIDS/HIV, revealing that indole moiety is a useful template for the development of anti-HIV agents. This review focuses on the recent advance-ment in indole derivatives, including indole alkaloids, hybrids, and dimers with anti-HIV potential, covering articles published between 2010 and 2020. The chemical structures, structure-activity rela-tionship, and mechanisms of action are also discussed.
Advances in the Design and Development of PROTAC-mediated HDAC Degradation
Authors: Rodrigues Daniel Alencar , Roe Andrew , Griffith Darren , Chonghaile Tríona Ní 
Published: October 2021

:Due to developments in modern chemistry, previously uundruggable substrates are now targetable thanks to selective degradation using the ubiquitin-proteasomal degradation system. PROteolysis TArgeting Chimeras (PROTACs) are heterobifunctional molecules designed specifically to degrade target proteins. They are of significant interest to industry and academia as they are highly specific and can target previously undruggable target proteins from transcription factors to enzymes. More than 15 degraders are expected to be evaluated in clinical trials by the end of 2021. Herein, we describe recent advances in the design and development of PROTAC-mediated degradation of histone deacetylases (HDACs). PROTAC-mediated degradation of HDACs can offer some significant advantages over direct inhibition, such as the use of substoichiometric doses and the potential to disrupt enzyme-independent HDAC function. We discuss the potential implication of the degradation of HDACs in comparison with HDAC knockout studies. Along with the selection of HDAC inhibitors and E3 ligase ligands for the design of PROTACs. The potential utility of HDAC PROTACs in various disease pathologies from cancer to inflammation to neurodegeneration is driving the interest in this field.