Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring the association between religious participation and memory in middle- and older-aged adults in the Canadian Longitudinal Study on Aging

ABSTRACT To investigate the association between religious participation and memory in persons aged 45–85 years. Using the Canadian Longitudinal Study on Aging, frequency of religious participation was measured from “daily” to “never”; immediate and delayed recall memory were assessed with the Rey Auditory Verbal Learning Test. We regressed memory onto religious participation for persons aged < 65 years and persons aged ≥ 65 years. We found some evidence of effect modification: among persons < 65 years, monthly to yearly participation versus never attending was positively associated with immediate and delayed recall memory; among persons aged ≥ 65 years, weekly or more participation versus never attending was negatively associated with immediate and delayed recall memory. However, regression coefficients were small (−0.09 ≤ B ≤ 0.06) and most were not statistically significant (p < 0.05). Insufficient evidence existed to conclude that religious participation was associated with memory in our sample.
A general optimization protocol for molecular property prediction using a deep learning network

Abstract The key to generating the best deep learning model for predicting molecular property is to test and apply various optimization methods. While individual optimization methods from different past works outside the pharmaceutical domain each succeeded in improving the model performance, better improvement may be achieved when specific combinations of these methods and practices are applied. In this work, three high-performance optimization methods in the literature that have been shown to dramatically improve model performance from other fields are used and discussed, eventually resulting in a general procedure for generating optimized CNN models on different properties of molecules. The three techniques are the dynamic batch size strategy for different enumeration ratios of the SMILES representation of compounds, Bayesian optimization for selecting the hyperparameters of a model and feature learning using chemical features obtained by a feedforward neural network, which are concatenated with the learned molecular feature vector. A total of seven different molecular properties (water solubility, lipophilicity, hydration energy, electronic properties, blood–brain barrier permeability and inhibition) are used. We demonstrate how each of the three techniques can affect the model and how the best model can generally benefit from using Bayesian optimization combined with dynamic batch size tuning.
The complete mitochondrial genome of Sarcophaga tsinanensis (Diptera: Sarcophagidae)

Abstract Sarcophaga tsinanensis (Fan, 1964) (Diptera: Sarcophagidae), a species from subgenus Heteronychia. In this study, we report the complete mitochondrial genome (mitogenome) of S. tsinanensis. The length of this mitogenome was 14,972 bp in total, containing 13 protein-coding genes, 2 ribosomal RNAs, 22 transfer RNAs, and a non-coding control region. The arrangement of genes was the same as that of ancestral metazoan. Sarcophaga tsinanensis has a high nucleotide bias in A/T accounting for 76.80% of total nucleotides (A 39.9%, G 9.2%, C 13.9%, and T 36.9%). The result of phylogenetic analysis revealed that S. tsinanensis cluster together with species from the same subgenus Heteronychia, showing a clear monophyletic relationship. Sarcophaga tsinanensis is closely related to its sister species Sarcophaga depressifrons, Sarcophaga plotnikovi, and Sarcophaga shnitnikovi. This study provides the mitochondrial data of S. tsinanensis for further research on evolutionary relationships and species identification of flesh flies.
A meta‐analysis of deep brain structural shape and asymmetry abnormalities in 2,833 individuals with schizophrenia compared with 3,929 healthy volunteers via the ENIGMA Consortium

Schizophrenia is associated with widespread alterations in subcortical brain structure. While analytic methods have enabled more detailed morphometric characterization, findings are often equivocal. In this meta‐analysis, we employed the harmonized ENIGMA shape analysis protocols to collaboratively investigate subcortical brain structure shape differences between individuals with schizophrenia and healthy control participants. The study analyzed data from 2,833 individuals with schizophrenia and 3,929 healthy control participants contributed by 21 worldwide research groups participating in the ENIGMA Schizophrenia Working Group. Harmonized shape analysis protocols were applied to each site's data independently for bilateral hippocampus, amygdala, caudate, accumbens, putamen, pallidum, and thalamus obtained from T1‐weighted structural MRI scans. Mass univariate meta‐analyses revealed more‐concave‐than‐convex shape differences in the hippocampus, amygdala, accumbens, and thalamus in individuals with schizophrenia compared with control participants, more‐convex‐than‐concave shape differences in the putamen and pallidum, and both concave and convex shape differences in the caudate. Patterns of exaggerated asymmetry were observed across the hippocampus, amygdala, and thalamus in individuals with schizophrenia compared to control participants, while diminished asymmetry encompassed ventral striatum and ventral and dorsal thalamus. Our analyses also revealed that higher chlorpromazine dose equivalents and increased positive symptom levels were associated with patterns of contiguous convex shape differences across multiple subcortical structures. Findings from our shape meta‐analysis suggest that common neurobiological mechanisms may contribute to gray matter reduction across multiple subcortical regions, thus enhancing our understanding of the nature of network disorganization in schizophrenia.
Physiologically Based Pharmacokinetic Modelling to Investigate the Impact of the Cytokine Storm on CYP3A Drug Pharmacokinetics in COVID‐19 Patients

Patients with coronavirus disease 2019 (COVID‐19) may experience a cytokine storm with elevated interleukin‐6 (IL‐6) levels in response to severe acute respiratory syndrome‐coronavirus 2 (SARS‐CoV‐2). IL‐6 suppresses hepatic enzymes, including CYP3A; however, the effect on drug exposure and drug‐drug interaction magnitudes of the cytokine storm and resulting elevated IL‐6 levels have not been characterized in patients with COVID‐19. We used physiologically‐based pharmacokinetic (PBPK) modeling to simulate the effect of inflammation on the pharmacokinetics of CYP3A metabolized drugs. A PBPK model was developed for lopinavir boosted with ritonavir (LPV/r), using clinically observed data from people living with HIV (PLWH). The inhibition of CYPs by IL‐6 was implemented by a semimechanistic suppression model and verified against clinical data from patients with COVID‐19, treated with LPV/r. Subsequently, the verified model was used to simulate the effect of various clinically observed IL‐6 levels on the exposure of LPV/r and midazolam, a CYP3A model drug. Clinically observed LPV/r concentrations in PLWH and patients with COVID‐19 were predicted within the 95% confidence interval of the simulation results, demonstrating its predictive capability. Simulations indicated a twofold higher LPV exposure in patients with COVID‐19 compared with PLWH, whereas ritonavir exposure was predicted to be comparable. Varying IL‐6 levels under COVID‐19 had only a marginal effect on LPV/r pharmacokinetics according to our model. Simulations showed that a cytokine storm increased the exposure of the CYP3A paradigm substrate midazolam by 40%. Our simulations suggest that CYP3A metabolism is altered in patients with COVID‐19 having increased cytokine release. Caution is required when prescribing narrow therapeutic index drugs particularly in the presence of strong CYP3A inhibitors.
In situ pedicle lengthening and perforator shifting technique for overcoming the perforator variation of the anterolateral thigh free flap during head and neck reconstruction

Anterolateral thigh (ALT) free flap is one of the most popular options for surgeons when reconstructing head and neck defects. When the recipient vessels are located in a remote site, a flap with adequate pedicle length is essential. The conventional methods of either pedicle elongation or fabricating combined flap increase the total surgical time. We present the experience on the use of what in situ pedicle lengthening and perforator shifting technique to overcome these problems.
Blood fibrocytes are associated with severity and prognosis in COVID-19 pneumonia

Increased blood fibrocytes are associated with a poor prognosis in fibrotic lung diseases. We aimed to determine whether the percentage of circulating fibrocytes could be predictive of severity and prognosis during coronavirus disease 2019 (COVID-19) pneumonia. Blood fibrocytes were quantified by flow cytometry as CD45+/CD15−/CD34+/collagen-1+ cells in patients hospitalized for COVID-19 pneumonia. In a subgroup of patients admitted in an intensive care unit (ICU), fibrocytes were quantified in blood and bronchoalveolar lavage (BAL). Serum amyloid P (SAP), transforming growth factor-β1 (TGF-β1), CXCL12, CCL2, and FGF2 concentrations were measured. We included 57 patients in the hospitalized group (median age = 59 yr [23–87]) and 16 individuals as healthy controls. The median percentage of circulating fibrocytes was higher in the patients compared with the controls (3.6% [0.2–9.2] vs. 2.1% [0.9–5.1], P = 0.04). Blood fibrocyte count was lower in the six patients who died compared with the survivors (1.6% [0.2–4.4] vs. 3.7% [0.6–9.2], P = 0.02). Initial fibrocyte count was higher in patients showing a complete lung computed tomography (CT) resolution at 3 mo. Circulating fibrocyte count was decreased in the ICU group (0.8% [0.1–2.0]), whereas BAL fibrocyte count was 6.7% (2.2–15.4). Serum SAP and TGF-β1 concentrations were increased in hospitalized patients. SAP was also increased in ICU patients. CXCL12 and CCL2 were increased in ICU patients and negatively correlated with circulating fibrocyte count. We conclude that circulating fibrocytes were increased in patients hospitalized for COVID-19 pneumonia, and a lower fibrocyte count was associated with an increased risk of death and a slower resolution of lung CT opacities.
Coping Through COVID-19: A Mixed Method Approach to Understand How Palliative Care Teams Managed the COVID-19 Pandemic

Objective: While previous work documented a substantial increase in patient mortality consultations and workload for palliative teams, little is known about how these team members managed their mental and physical health during the COVID-19 pandemic. We investigated how job resources (coworker and supervisor support) and personal resources (coping strategies) reduced perceptions of burnout and increased perceptions of well-being. Method: An anonymous electronic survey was sent to all members (N = 64) of the palliative medical team among 14 hospitals of a New York State health system. Data were collected between September 2020 to October 2020. Measures included validated scales for burnout (Oldenburg Burnout Inventory), coping strategies (Cybernetic Coping Scale), subjective well-being (BBC Subjective Well-being scale), and coworker/supervisor support (7 items from Yang et al). Results: Results indicated devaluation coping tactics were used to reduce perceptions of burnout and to increase perceptions of physical health. Higher burnout was identified when using avoidance coping techniques. Furthermore, coworkers and supervisor(s) support significantly reduced disengagement when compared to coworker support alone. Conclusion: COVID-19 exacerbated burnout experienced by palliative care teams, yet the use of coping behaviors (devaluation/avoidance) and external resources (coworker and supervisor support) utilized by these teams were found to have positive effects. Further research should investigate these antagonizing factors to help preventing and addressing burn out during times of crises and in the everyday of palliative care teams.
RGN1 controls grain number and shapes panicle architecture in rice

Summary Yield in rice is determined mainly by panicle architecture. Using map‐based cloning, we identified an R2R3 MYB transcription factor REGULATOR OF GRAIN NUMBER1 (RGN1) affecting grain number and panicle architecture. Mutation of RGN1 caused an absence of lateral grains on secondary branches. We demonstrated that RGN1 controls lateral grain formation by regulation of LONELY GUY (LOG) expression, thus controlling grain number and shaping panicle architecture. A novel favourable allele, RGN1 C, derived from the Or‐I group in wild rice affected panicle architecture by means longer panicles. Identification of RGN1 provides a theoretical basis for understanding the molecular mechanism of lateral grain formation in rice; RGN1 will be an important gene resource for molecular breeding for higher yield.
Profiling nonhuman primate germline RNA to understand the legacy of early life stress

Abstract Exposure to stress is a risk factor for perturbed mental health, including impoverished regulation of emotional and physiological responses that accompany anxiety and mood disorders, substance abuse and behavioral disorders. Such disruptions to well‐being could be triggered by discrete environmental events or pervasive early life stress (ELS) resulting for example from adverse caregiving. Recent data mostly collected from rodents exposed to anthropogenic stressors suggest that one way via which the detrimental effects of such stress extend beyond the exposed population to future offspring is via stress‐induced alterations of RNA found in the paternal germline. In contrast, less attention has been paid to how naturally occurring stress in males might influence offspring biology and behavior. In this study, we used a translational nonhuman primate model of ELS caused by naturally occurring adverse caregiving of infant macaques to (1) profile total RNA in the adolescent male germline, and (2) identify how those RNA profiles are affected by exposure to ELS. Our findings that the top 100 transcripts identified correspond to transcripts related to germline biology and reproduction demonstrate the validity and feasibility of profiling RNA in the germline of rhesus macaques. While our small sample sizes precluded definitive assessment of stress‐induced alterations of RNA in the male germline of rhesus macaques that experienced ELS, our study sets the foundation for future investigations of how early adversity might alter the male germline, across species and in experimental protocols that involve anthropogenic vs natural stressors.
EFFECT OF DI-(2-ETHYLHEXYL) PHTHALATE (DEHP) EXPOSURE ON MICROARCHITECTURE OF FEMORAL BONE IN MALE LABORATORY MOUSE: PRELIMINARY RESULTS

Di-2-ethylhexyl phthalate (DEHP) is a toxic and hazardous endocrine disruptor with adverse effects on animal and human health. However, its impact on bone tissue has not been sufficiently investigated. Therefore, the purpose of our preliminary study was to examine the effects of DEHP on compact bone structure in two 57-days-old male mice. Daily oral administration of DEHP (4.5 mg/kg body weight dissolved in 500 µl of peanut oil per 15 days) was studied, compared to a control. We observed a significant effect of DEHP exposure on macroscopic bone characteristics. Similarly, we identified differences in qualitative characteristics, such as the presence of resorption lacunae and absence of non-vascular and primary vascular radial bone tissue near the endosteal border, compared to the control. On the contrary, quantitative analysis showed no demonstrable alterations in morphometric parameters. Our preliminary findings support the hypothesis about the negative impact of DEHP on bone tissue. However, further investigation is needed to understand this issue better and more precisely.
A Survey on Affective and Cognitive VR

In Virtual Reality (VR), users can be immersed in emotionally intense and cognitively engaging experiences. Yet, despite strong interest from scholars and a large amount of work associating VR and Affective and Cognitive States (ACS), there is a clear lack of structured and systematic form in which this research can be classified. We define “Affective and Cognitive VR” to relate to works which (1) induce ACS, (2) recognize ACS, or (3) exploit ACS by adapting virtual environments based on ACS measures. This survey clarifies the different models of ACS, presents the methods for measuring them with their respective advantages and drawbacks in VR, and showcases Affective and Cognitive VR studies done in an Immersive Virtual Environment (IVE) in a non-clinical context. Our article covers the main research lines in Affective and Cognitive VR. We provide a comprehensive list of references with the analysis of 63 research articles and summarize future works directions.
Development of Keratinocyte Cell Lines Containing Extrachromosomal Human Papillomavirus Genomes

Human papillomaviruses (HPVs) cause persistent infections in stratified cutaneous and mucosal epithelia. In these infections, the viral DNA replicates as low‐copy‐number, extrachromosomal, double‐stranded‐DNA circular plasmids in the nucleus of the dividing basal cells. When the infected cells begin the process of differentiation, the viral DNA amplifies to a high copy number and virions are assembled in the superficial cells. To study HPV DNA replication, our laboratory generates primary keratinocyte cell lines that contain replicating extrachromosomal HPV genomes. Here, we describe protocols to culture human keratinocytes, to transfect viral DNA into cells using electroporation, to determine the efficiency of genome establishment in cells with a colony‐forming assay, and to measure the copy number and extrachromosomal status of viral genomes using Southern blotting. These methods can be used to study DNA replication of different oncogenic Alphapapillomavirus HPV types. Published 2021. This article is a U.S. Government work and is in the public domain in the USA.
Frequency and predictability effects in first and second language of different script bilinguals.

Reading efficiently in a second language (L2) is a crucial skill, but it is not universally achieved. Here we ask whether L2 reading efficiency is better captured as a language specific skill or whether it is mostly shared across L1 and L2, relying on general language abilities. To this end, we examined word frequency and predictability effects in sentence reading, and tested the same readers in L1 and L2, recording participants' eye-movements. Participants were 57 undergraduate bilingual speakers of Hebrew and English, languages that use different scripts, allowing for a clearer distinction between L1 and L2 processing. Both word frequency and word predictability effects were more pronounced in participants' L2 than in the L1, suggesting that both lower level and higher-order processes in reading are sensitive to language proficiency. Further, frequency effects in the L2 were linked with L2 proficiency but not general language abilities, and L2 predictability effects were not associated with either variable. Finally, readers' frequency and predictability effects in L1 and L2 were not associated with each other. Taken together, these results suggest that for different-script bilinguals, efficient reading in the L2 is a highly specific skill, dependent upon proficiency in that language, and drawing less on L1 and general language ability. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
Raman spectroscopy as a process analytical technology to investigate biopharmaceutical freeze concentration processes

Freezing processes are a well‐established unit operation in the biopharmaceutical industry to increase the shelf‐life of protein‐based drugs. While freezing reduces degradation reaction rates, it may also exert stresses such as freeze concentration. Macroscopic freeze concentration in large‐scale freezing processes has been described thoroughly by examination of frozen bulk material, but the transient process leading to such freeze concentration profiles has not been monitored yet for biopharmaceutical solutions. In this study, Raman spectroscopy as a process analytical technology is demonstrated for model formulations containing monoclonal antibodies (mAbs) or bovine serum albumin (BSA) in varying concentrations of sucrose and buffer salts. Therefore, a Raman probe was immersed into a bulk volume at different heights, monitoring the freeze concentration in the liquid phase during the freezing processes. Partial least square regression models were used to quantitatively discriminate between the protein and excipients simultaneously. The freeze concentration profiles were dependend on freezing temperature and formulation with freeze concentrations up to 2.4‐fold. Convection currents at the bottom of the freezing container were observed with a maximum height of 1 mm. Furthermore, freeze concentration was correlated with the sucrose concentration in a formulation. Analysis of the freeze concentration slope indicated diffusion from the bottom to the top of the container. In summary, Raman spectroscopy is a valuable tool for process validation of freeze concentration simulations and to overcome scale‐dependent challenges.
Unsupervised Feature Selection Using an Integrated Strategy of Hierarchical Clustering With Singular Value Decomposition: An Integrative Biomarker Discovery Method With Application to Acute Myeloid Leukemia

In this article, we propose a novel unsupervised feature selection method by combining hierarchical feature clustering with singular value decomposition (SVD). The proposed algorithm first generates several feature clusters by adopting the hierarchical clustering on the feature space and then applies SVD to each of these feature clusters to find out the feature that contributes most to the SVD-entropy. The proposed feature selection method selects an optimal feature subset that not only minimizes the mutual dependency among the selected features but also maximizes the mutual dependency of the selected features against their nearest neighbor non-selected features to some extent. Each of the selected features also contributes the maximum SVD-entropy among all features of the same feature cluster. The experimental results demonstrate that the proposed algorithm performs well against several state-of-the-art methods of feature selection in terms of various evaluation criteria such as classification accuracy, redundancy rate, and representation entropy. The superiority of the proposed algorithm is demonstrated through analysis of Acute Myeloid Leukemia (AML) multi-omics data that consist of five datasets: gene expression, exon expression, methylation, microRNA, and pathway activity dataset (paradigm IPLs) from The Cancer Genome Atlas (TCGA). Our analysis pinpoints a candidate gene-marker, EREG for AML with an integrative omics evidence. EREG is targeted by two top ranked microRNAs, hsa-miR-1286 and hsa-miR-1976, here in the datasets. The method and results will be useful for biomarker discovery in the era of in precision medicine.
Biogenic silver nanoparticle (Bio‐AgNP) has an antibacterial effect against carbapenem‐resistant Acinetobacter baumannii with synergism and additivity when combined with polymyxin B

Carbapenem‐resistant Acinetobacter baumannii represents a public health problem, and the search for new antibacterial drugs has become a priority. Here, we investigate the antibacterial activity of biogenic silver nanoparticles (Bio‐AgNPs) synthesized by Fusarium oxysporum, used alone or in combination with polymyxin B against carbapenem‐resistant A. baumannii.