Nevin Manimala

Brief Bioinform. 2021 Sep 25:bbab402. doi: 10.1093/bib/bbab402. Online ahead of print.

ABSTRACT

The identification of differentially expressed genes between different cell groups is a crucial step in analyzing single-cell RNA-sequencing (scRNA-seq) data. Even though various differential expression analysis methods for scRNA-seq data have been proposed based on different model assumptions and strategies recently, the differentially expressed genes identified by them are quite different from each other, and the performances of them depend on the underlying data structures. In this paper, we propose a new ensemble learning-based differential expression analysis method, scDEA, to produce a more stable and accurate result. scDEA integrates the P-values obtained from 12 individual differential expression analysis methods for each gene using a P-value combination method. Comprehensive experiments show that scDEA outperforms the state-of-the-art individual methods with different experimental settings and evaluation metrics. We expect that scDEA will serve a wide range of users, including biologists, bioinformaticians and data scientists, who need to detect differentially expressed genes in scRNA-seq data.

PMID:34571530 | DOI:10.1093/bib/bbab402

Neuropsychobiology. 2021 Sep 27:1-8. doi: 10.1159/000518996. Online ahead of print.

ABSTRACT

INTRODUCTION: Emotion regulation (ER), the ability to actively modulate one’s own emotion reactions, likely depends on the individual’s current emotional state. Here, we investigated whether negative emotions induced by an interpersonal autobiographic script affect the neuronal processes underlying ER.

METHODS: Twenty healthy participants were recruited and underwent functional magnetic resonance imaging (fMRI) during performance of distancing, a specific ER strategy, while viewing emotionally arousing pictures. Participants were instructed to either naturally experience (“permit” condition) or to actively downregulate (“regulate” condition) their emotional responses to the presented stimuli. Before each of the 4 runs in total, a neutral or negative autobiographical audio script was presented. The negative script comprised an emotionally negative event from childhood or adolescence that represented either emotional abuse or emotional neglect. The second event comprised an everyday neutral situation. We aimed at identifying the neural correlates of ER and their modulation by script-driven imagery.

RESULTS: fMRI analyses testing for greater responses in the “regulate” than the “permit” condition replicated previously reported neural correlates of ER in the right dorsolateral prefrontal cortex and the right inferior parietal lobule. A significant ER effect was also observed in the left orbitofrontal cortex. In the amygdala, we found greater responses in the “permit” compared to the “regulate” condition. We did not observe a significant modulation of the ER effects in any of these regions by the negative emotional state induced by autobiographical scripts. Bayesian statistics confirmed the absence of such modulations by providing marginal evidence for null effects.

DISCUSSION: While we replicated previously reported neural correlates of ER, we found no evidence for an effect of mood induction with individualized autobiographical scripts on the neural processes underlying ER in healthy participants.

PMID:34571510 | DOI:10.1159/000518996

Epilepsy Res. 2021 Sep 22;177:106774. doi: 10.1016/j.eplepsyres.2021.106774. Online ahead of print.

ABSTRACT

Previous findings have suggested that a preictal state might precede the epileptic seizure onset, which is the basis for seizure prediction attempts. Preictal states can be apprehended as outliers that differ from an interictal baseline and display clinical changes. We collected daily clinical scores from patients with epilepsy who underwent continuous video-EEG and assessed the ability of several outlier detection methods to identify preictal states. Results from 24 patients suggested that outlying clinical features were suggestive of preictal states and can be identified by statistical methods: AUC = 0.71, 95 % CI = [0.63 – 0.79]; PPV = 0.77, 95 % CI = [0.70 – 0.84]; FPR = 0.31, 95 % CI = [0.21 – 0.44]); and F1 score = 0.74, 95 % CI = [0.64 – 0.81]. Such algorithms could be straightforwardly implemented in a mobile device (e.g., tablet or smartphone), which would allow a longer data collection that could improve prediction performances. Additional clinical – and even multimodal – parameters could identify more subtle physiological modifications.

PMID:34571459 | DOI:10.1016/j.eplepsyres.2021.106774

Nurse Educ Today. 2021 Sep 10;107:105140. doi: 10.1016/j.nedt.2021.105140. Online ahead of print.

ABSTRACT

BACKGROUND: In 2018, the Korean version of the Clinical Learning Environment, Supervision, and Nurse Teacher scale was evaluated for validity and reliability.

OBJECTIVES: This study aimed to test the instrument’s measurement invariance and to compare the latent means of groups.

DESIGN: This was a cross-sectional study.

SETTINGS: Nursing departments in four metropolitan cities and five regions of Korea. The study sample comprised 507 nursing students.

PARTICIPANTS: Bachelor’s-level nursing students in their third and fourth years who have experienced clinical practicum.

METHODS: Data were collected from November 11 to December 24, 2018 using the Korean Clinical Learning Environment, Supervision, and Nurse Teacher scale. Confirmatory factor analysis and multi-group confirmatory factor analysis were conducted. Measurement invariance of the Korean Clinical Learning Environment, Supervision, and Nurse Teacher scale was tested in the following order: configural invariance, factor-loading invariance, intercept invariance, factor variance/covariance invariance, and residual invariance, by student year, hospital grade (tertiary or general hospital) and assignment of a nurse instructor (or not).

RESULTS: The measurement invariance of the Korean Clinical Learning Environment, Supervision, and Nurse Teacher scale by student year and hospital grade were confirmed by configural invariance, factor-loading invariance, intercept invariance, factor variance/covariance invariance, and residual invariance. The measurement invariance of the scale by assignment of a nurse instructor (or not) was also confirmed for configural invariance, factor-loading invariance, partial intercept invariance, partial factor variance/covariance invariance, and partial residual invariance. Comparing latent mean values, there was a statistically significant difference in the mean of the sub-dimensions of the Korean Clinical Learning Environment, Supervision, and Nurse Teacher scale by student year, hospital grade, and nurse assignment (or not).

CONCLUSIONS: The Korean Clinical Learning Environment, Supervision, and Nurse Teacher scale is an appropriate instrument for measuring the clinical learning environment regardless of student year, hospital grade, or nurse assignment.

PMID:34571445 | DOI:10.1016/j.nedt.2021.105140

Public Health. 2021 Sep 24;199:87-95. doi: 10.1016/j.puhe.2021.07.011. Online ahead of print.

ABSTRACT

OBJECTIVES: Safe blood transfusion plays an important role in the prevention of transfusion-transmissible infections, and hepatitis C virus (HCV) infection is one of the major problems associated with this procedure. This meta-analysis aimed to determine the prevalence of HCV infection in Chinese blood donors.

STUDY DESIGN: The study design of this study is a meta-analysis.

METHODS: Eligible studies were retrieved from PubMed, Embase, China National Knowledge Infrastructure, China Science and Technology Journal Database and Wanfang literature databases from 2010 to 2020. The effect measure was presented as HCV prevalence with a 95% confidence interval (CI). Q test was used to assess the heterogeneity, and the I² statistics was determined to decide whether a random effects model or a fixed effects model should be used as the pooling method. Subgroup analyses were also conducted.

RESULTS: A total of 62 eligible studies, including 9,007,220 HCV blood donors, were analysed. Of the total blood donors, 35,017 were infected with HCV. The pooled HCV prevalence was 0.415% (95% CI: 0.371-0.458). The subgroup analysis revealed that the prevalence of positivity to anti-HCV antibodies was significantly different in each year (P < 0.05). However, no significant difference was observed in HCV prevalence in terms of sex. Moreover, the prevalence of positivity to anti-HCV was remarkably higher in first-time blood donors than in repeat blood donors (P < 0.05), and the rate of HCV infection among university students was significantly lower than that among soldiers (P < 0.05).

CONCLUSIONS: The rate of HCV infection showed a downward trend from 2010 to 2014, increased in 2015-2016, and finally decreased in 2017-2018. Thus, the prevalence of HCV infection has decreased in Chinese blood donors after comprehensive prevention and treatment.

PMID:34571442 | DOI:10.1016/j.puhe.2021.07.011

Food Chem. 2021 Sep 13;371:131113. doi: 10.1016/j.foodchem.2021.131113. Online ahead of print.

ABSTRACT

Determining the geographical origin of wines is a major challenge in wine authentication, but little information is available regarding non-parametric statistical approaches for wines. In this study, we collected 33 domestic Chardonnay wines vinified on a small scale from grapes cultivated in Japan, and 42 Chardonnay wines imported from 8 countries, for oxygen stable isotope and multi-element analyses. Non-metric multidimensional scaling (NMDS), kernel principal component analysis (KPCA) and principal component analysis (PCA) were applied to the oxygen stable isotopic compositions (δ¹⁸O) and the concentrations of 18 elements in the wines to compare the extractions by parametric and non-parametric methods. The non-parametric methods, NMDS and KPCA, separated domestic from imported Chardonnay wines better than the parametric method, PCA. Of 19 variables, 18 were important for geographical discrimination, with the δ¹⁸O value being the most significant in all statistic methods. Non-parametric multivariate analyses will help discriminate domestic from imported Chardonnay wines.

PMID:34571407 | DOI:10.1016/j.foodchem.2021.131113

Mar Pollut Bull. 2021 Sep 24;173(Pt A):112989. doi: 10.1016/j.marpolbul.2021.112989. Online ahead of print.

ABSTRACT

The principal objective of this study is to assess the saltwater intrusion and hydrogeochemical processes that affect groundwater geochemistry in the coastal aquifers of southwestern India. Groundwater samples were collected seasonally and the physico-chemical parameters determined on-site. Major ions were determined in the laboratory. Hydrochemical diagrams, ionic ratios, and multivariate statistical analysis were adopted for understanding the groundwater chemistry. Gibbs plot identified that rock-water interaction and evaporation were the mechanisms regulating hydrogeochemistry. Ionic ratios have shown that coastal wells were contaminated with saltwater intrusion during the pre-monsoon season. Hierarchical cluster analysis classified the samples based on their quality; sample clusters with high NO₃^– were in densely populated areas, whereas sample clusters with moderate salt content in the coastal areas. Another cluster showed high concentrations of salts, typically the zones of saltwater intrusion. The study concludes that influence of seasons, geogenic and anthropogenic factors contribute to the heterogeneous chemistry of groundwater.

PMID:34571386 | DOI:10.1016/j.marpolbul.2021.112989

J Biomech. 2021 Sep 22;129:110757. doi: 10.1016/j.jbiomech.2021.110757. Online ahead of print.

ABSTRACT

In infancy, plantar pressure data during walking has been investigated through regional approaches, whilst the use pedobarographic Statistical Parametric Mapping (pSPM) has not been reported. Analysis of pressure data using pSPM is higher in resolution and can enhance understanding of foot function development, providing novel insights into plantar pressure changes. This work aims to detail the implementation of the pSPM data processing framework on infants’ pressure data, comparing plantar pressure patterns between new and confident walking steps. Twelve infants walked across an EMED- xl platform. Steps were extracted and imported into MATLAB for analysis. Maximum pressure pictures were transformed to point clouds and registered within and between participants with iterative closest point and coherent point drift algorithms, respectively. Root mean square error (RMSE) was calculated within both registrations as a quality measure. Pressure patterns were compared between new and confident walking using nonparametric-paired sample SPM1D t-test. RMSEs were under 1 mm for both registration algorithms. In the transition to confident walking, significantly increasing pressure was detected in the left central forefoot. Implementing pSPM to infants’ pressure data was non-trivial, as several phases of data processing were required to ensure a robust approach. Our analysis highlighted the presence of significant changes in pressure in central left forefoot after 2.2 months of walking, which have not been reported before. This can be explained as previous regional approaches in infancy considered the forefoot as whole, preventing detection of changes in discrete anatomical regions.

PMID:34571379 | DOI:10.1016/j.jbiomech.2021.110757

EBioMedicine. 2021 Sep 24;72:103590. doi: 10.1016/j.ebiom.2021.103590. Online ahead of print.

ABSTRACT

BACKGROUND: Easily accessible biomarkers enabling the identification of those patients with multiple sclerosis (MS) who will accumulate irreversible disability in the long term are essential to guide early therapeutic decisions. We here examine the utility of serum neurofilament light chain (sNfL) for forecasting relapse-free disability progression and conversion to secondary progressive MS (SPMS) in the prospective Neurofilamentandlongtermoutcome inMS (NaloMS) cohort.

METHODS: The predictive ability of sNfL at Baseline and sNfL follow-up (FU)/ Baseline (BL) ratio with regard to disability progression was assessed within a development cohort (NaloMS, n=196 patients with relapsing-remitting MS (RRMS) or clinically isolated syndrome) and validated with an external independent cohort (Düsseldorf, Essen, n=204). Both relapse-free EDSS-progression (RFP: inflammatory-independent EDSS-increase 12 months prior to FU) and SPMS-transition (minimum EDSS-score of 3.0) were investigated.

FINDINGS: During the study period, 17% (n=34) of NaloMS patients suffered from RFP and 14% (n=27) converted to SPMS at FU (validation cohort RFP n=42, SPMS-conversion n=24). sNfL at BL was increased in patients with RFP (10.8 pg/ml (interquartile range (IQR) 7.7-15.0) vs. 7.2 pg/ml (4.5-12.5), p<0.017). In a multivariable logistic regression model, increased sNfL levels at BL (Odds Ratio (OR) 1.02, 95% confidence interval (CI) 1.01-1.04, p=0.012) remained an independent risk factor for RFP and predicted individual RFP risk with an accuracy of 82% (NaloMS) and 83% (validation cohort) as revealed by support vector machine. In addition, the sNfL FU/BL ratio was increased in SPMS-converters (1.16 (0.89-1.70) vs. 0.96 (0.75-1.23), p=0.011). This was confirmed by a multivariable logistic regression model, as sNfL FU/BL ratio remained in the model (OR 1.476, 95%CI 1.078-2,019, p=0.015) and individual sNfL FU/BL ratios showed a predictive accuracy of 72% in NaloMS (63% in the validation cohort) as revealed by machine learning.

INTERPRETATION: sNfL levels at baseline predict relapse-free disability progression in a prospective longitudinal cohort study 6 years later. While prediction was confirmed in an independent cohort, sNfL further discriminates patients with SPMS at follow-up and supports early identification of patients at risk for later SPMS conversion.

FUNDING: This work was supported by the German Research Council (CRC-TR-128), Else Kröner Fresenius Foundation and Hertie-Stiftung.

PMID:34571362 | DOI:10.1016/j.ebiom.2021.103590

Diabetes Metab Syndr. 2021 Sep 23;15(6):102297. doi: 10.1016/j.dsx.2021.102297. Online ahead of print.

ABSTRACT

BACKGROUND AND AIMS: India officially launched the world’s biggest COVID-19 vaccination drive on January 16, 2021, operating 3006 vaccination sites at the beginning. At present 21872 sites conducting vaccination as on August 24, 2021. The process of vaccination is not yet mandatory in India. Vaccination is conducted free of cost at 20242 Government sites and paid at 1630 private sites. This study involves Hypothesis Testing for analyzing the gender disparities towards COVID-19 vaccination.

METHODS: For this study, we have used Maharashtra States district wise COVID-19 vaccination data. Using Hypothesis Testing method Pearson’s Chi-square test for independence compares two variables gender disparities and vaccination in a contingency table to see if they are related. To test the Effect size of gender disparities is small, medium or large Cohen Cramer’s rule is used.

RESULTS: Our result shows that, just 84 women were vaccinated for every 100 men in Maharashtra State, India. This ratio is even lower than India’s gender ratio i.e. 90:100. Men were more aware and ahead of women in COVID-19 Vaccination Drive. Effect size shows that size of gender disparities is small.

CONCLUSION: As per the result it is seen that COVID-19 Vaccination awareness is slightly less amongst the women in Maharashtra, India. To improve this statistics of COVID-19 Vaccination, Authorities should start the awareness campaign amongst the citizen towards the importance of vaccination.

PMID:34571358 | DOI:10.1016/j.dsx.2021.102297