Nevin Manimala

Acta Crystallogr D Struct Biol. 2023 Jan 1;79(Pt 1):50-65. doi: 10.1107/S2059798322011871. Epub 2023 Jan 1.

ABSTRACT

It is investigated whether molecular-dynamics (MD) simulations can be used to enhance macromolecular crystallography (MX) studies. Historically, protein crystal structures have been described using a single set of atomic coordinates. Because conformational variation is important for protein function, researchers now often build models that contain multiple structures. Methods for building such models can fail, however, in regions where the crystallographic density is difficult to interpret, for example at the protein-solvent interface. To address this limitation, a set of MD-MX methods that combine MD simulations of protein crystals with conventional modeling and refinement tools have been developed. In an application to a cyclic adenosine monophosphate-dependent protein kinase at room temperature, the procedure improved the interpretation of ambiguous density, yielding an alternative water model and a revised protein model including multiple conformations. The revised model provides mechanistic insights into the catalytic and regulatory interactions of the enzyme. The same methods may be used in other MX studies to seek mechanistic insights.

PMID:36601807 | DOI:10.1107/S2059798322011871

Acta Crystallogr D Struct Biol. 2023 Jan 1;79(Pt 1):31-39. doi: 10.1107/S2059798322011858. Epub 2023 Jan 1.

ABSTRACT

Proteins often assemble into functional complexes, the structures of which are more difficult to obtain than those of the individual protein molecules. Given the structures of the subunits, it is possible to predict plausible complex models via computational methods such as molecular docking. Assessing the quality of the predicted models is crucial to obtain correct complex structures. Here, an energy-scoring function was developed based on the interfacial residues of structures in the Protein Data Bank. The statistically derived energy function (Nepre) imitates the neighborhood preferences of amino acids, including the types and relative positions of neighboring residues. Based on the preference statistics, a program iNepre was implemented and its performance was evaluated with several benchmarking decoy data sets. The results show that iNepre scores are powerful in model ranking to select the best protein complex structures.

PMID:36601805 | DOI:10.1107/S2059798322011858

J Med Econ. 2023 Jan 5:1-15. doi: 10.1080/13696998.2023.2165365. Online ahead of print.

ABSTRACT

Background: Galcanezumab (GMB) improved quality of life and reduced disability of patients with episodic (EM) and chronic migraine (CM) in Phase 3 trials.Aim: To estimate indirect cost savings associated with GMB treatment in patients with migraine in the United States (US).Methods: We analyzed data of patients from the US from three randomized, Phase 3, double-blind, placebo (PBO)-controlled GMB studies: EVOLVE-1 and EVOLVE-2 (EM patients), REGAIN (CM patients). Annual indirect costs were calculated using items of Migraine Disability Assessment (MIDAS) questionnaire: lost time/productivity at work/school, household work, and leisure time. All costs were annualized and expressed in 2019 US dollars. While the main analysis considered lost time/productivity at work/school and household work as a full day, a sensitivity analysis was performed by discounting them by half. For EM, annual indirect costs savings were estimated using mixed model repeated measures analysis. For CM, ANCOVA models were used to estimate annual indirect costs savings as change from baseline.Results: The analysis included 805 patients with EM (mean age = 41.4y; PBO = 534; GMB = 271) and 423 patients with CM (mean age = 38.9y; PBO = 279; GMB = 144). Compared to PBO, GMB significantly reduced annual indirect costs among patients with EM at 3 months (least square mean [95% confidence interval] work/school=$1883.6 [603.64, 3163.65], p = 0.0040, household work=$628.9 [352.95, 904.88], p < 0.0001, and leisure activity=$499.17 [42.36, 955.98], p = 0.0323) and 6 months (work/school=$2382.29 [1065.48, 3699.10], p = 0.0004, household work=$559.45 [268.99, 849.90], p = 0.0002, and leisure activity=$753.81 [334.35, 1173.27], p = 0.0004), whereas significant difference was not observed among patients with CM. Sensitivity analysis results were similar to primary analysis results.Conclusions: GMB treatment versus PBO resulted in significantly greater indirect cost savings in patients with EM through improved productivity at work/school, household work, and leisure days. Patients with CM receiving GMB versus PBO attained greater cost savings, although not statistically significant, through reduced lost productivity at work/school.

PMID:36601798 | DOI:10.1080/13696998.2023.2165365

Biomed Chromatogr. 2023 Jan 5:e5578. doi: 10.1002/bmc.5578. Online ahead of print.

ABSTRACT

In this study, we utilized a serum metabolomics methodology based on gas chromatography coupled with mass spectrometry (GC/MS) to investigate the liver-protective effects of raw and stir-fried semens of Hovenia dulcis in rats models of carbon tetrachloride-induced liver injury. Multivariate statistical analysis, such as principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA), were conducted to examine changes in the metabolic state of rats with carbon tetrachloride-induced liver injury, as well as the recovery pattern of rats pretreated with the raw and stir-fried semens of Hovenia dulcis. Liver tissues were subjected to histopathological examination. A total of 47 biomarkers were predicted to contribute to the dynamic pathological processes in the liver injury, such as phenylalanine, glutamic acid, glycine, arachidonic acid and linoleic acid. Further analysis revealed that pathways associated with phenylalanine, tyrosine and tryptophan biosynthesis, and linoleic acid metabolism were altered in the injured liver, and that pretreatment with raw and stir-fried semens of Hovenia dulcis abolished the changes in the aforementioned metabolic pathways.

PMID:36601730 | DOI:10.1002/bmc.5578

J Community Psychol. 2023 Jan 5. doi: 10.1002/jcop.22989. Online ahead of print.

ABSTRACT

This article explores the factors contributing to drug-related deaths in English and Welsh prisons between 2015 and 2020. Based on content analysis of all Prison and Probation Ombudsman ‘other non-natural’ fatal incident investigation reports, descriptive statistics were generated. Qualitative analysis explored the circumstances surrounding deaths and key risk factors. Most deaths were of men, whose mean age was 39 years. Drug toxicity was the main factor in causing death, exacerbated by underlying physical health conditions and risk-taking behaviours. A variety of substances were involved. New psychoactive substances became more important over time. A high proportion had recorded histories of substance use and mental illness. During this period, the prison system was under considerable stress creating dangerous environments for drug-related harm. This study highlights the process of complex interaction between substances used, individual characteristics, situational features and the wider environment in explaining drug-related deaths in prisons. Implications for policy and practice are discussed.

PMID:36601729 | DOI:10.1002/jcop.22989

Stat Med. 2023 Jan 5. doi: 10.1002/sim.9642. Online ahead of print.

ABSTRACT

The interpretability of machine learning models, even though with an excellent prediction performance, remains a challenge in practical applications. The model interpretability and variable importance for well-performed supervised machine learning models are investigated in this study. With the commonly accepted concept of odds ratio (OR), we propose a novel and computationally efficient Variable Importance evaluation framework based on the Personalized Odds Ratio (VIPOR). It is a model-agnostic interpretation method that can be used to evaluate variable importance both locally and globally. Locally, the variable importance is quantified by the personalized odds ratio (POR), which can account for subject heterogeneity in machine learning. Globally, we utilize a hierarchical tree to group the predictors into five groups: completely positive, completely negative, positive dominated, negative dominated, and neutral groups. The relative importance of predictors within each group is ranked based on different statistics of PORs across subjects for different application purposes. For illustration, we apply the proposed VIPOR method to interpreting a multilayer perceptron (MLP) model, which aims to predict the mortality of subarachnoid hemorrhage (SAH) patients using real-world electronic health records (EHR) data. We compare the important variables derived from MLP with other machine learning models, including tree-based models and the L1-regularized logistic regression model. The top importance variables are consistently identified by VIPOR across different prediction models. Comparisons with existing interpretation methods are also conducted and discussed based on publicly available data sets.

PMID:36601725 | DOI:10.1002/sim.9642

Int J Nurs Pract. 2023 Jan 5:e13129. doi: 10.1111/ijn.13129. Online ahead of print.

ABSTRACT

BACKGROUND: Occupational stress is generally acknowledged as a major issue in the health sector that may have a detrimental impact on nurses’ psychological and physical health, particularly during the COVID-19 epidemic.

AIM: This study evaluated the effectiveness of a psychoeducational interventional programme in decreasing occupational stress and improving coping methods among nurses during the COVID-19 pandemic.

METHODS: This study used a cluster-randomized approach. Data were collected from 80 nurses working in two public health-care centres from May to August 2020 in Jordan. Two centres were assigned randomly to the intervention and control groups. The psychoeducational programme was delivered to the intervention group in six sessions over 6 days for 2 weeks. The collected data were analysed using SPSS through descriptive and inferential statistics. Occupational stress and coping strategies were measured.

RESULTS: Repeated-measures analysis of variance (ANOVA) indicated that the degrees of occupational stress and coping strategies significantly differed between study groups over the three points of data collection.

CONCLUSION: This psychoeducational interventional programme is a valuable noninvasive method that can improve individual coping strategies to manage stress in practice during the COVID-19 pandemic.

PMID:36601722 | DOI:10.1111/ijn.13129

Brain Behav. 2023 Jan 4:e2863. doi: 10.1002/brb3.2863. Online ahead of print.

ABSTRACT

The causes of the neurodegenerative processes in Alzheimer’s disease (AD) are not completely known. Recent studies have shown that white matter (WM) damage could be more severe and widespread than whole-brain cortical atrophy and that such damage may appear even before the damage to the gray matter (GM). In AD, Amyloid-beta (Aβ₄₂ ) and tau proteins could directly affect WM, spreading across brain networks. Since hippocampal atrophy is common in the early phase of disease, it is reasonable to expect that hippocampal volume (HV) might be also related to WM integrity. Our study aimed to evaluate the integrity of the whole-brain WM, through diffusion tensor imaging (DTI) parameters, in mild AD and amnestic mild cognitive impairment (aMCI) due to AD (with Aβ₄₂ alteration in cerebrospinal fluid [CSF]) in relation to controls; and possible correlations between those measures and the CSF levels of Aβ₄₂ , phosphorylated tau protein (p-Tau) and total tau (t-Tau). We found a widespread WM alteration in the groups, and we also observed correlations between p-Tau and t-Tau with tracts directly linked to mesial temporal lobe (MTL) structures (fornix and hippocampal cingulum). However, linear regressions showed that the HV better explained the variation found in the DTI measures (with weak to moderate effect sizes, explaining from 9% to 31%) than did CSF proteins. In conclusion, we found widespread alterations in WM integrity, particularly in regions commonly affected by the disease in our group of early-stage disease and patients with Alzheimer’s disease. Nonetheless, in the statistical models, the HV better predicted the integrity of the MTL tracts than the biomarkers in CSF.

PMID:36601694 | DOI:10.1002/brb3.2863

CNS Neurosci Ther. 2023 Jan 4. doi: 10.1111/cns.14080. Online ahead of print.

ABSTRACT

AIMS: The aim of this study was to explore the interaction between reperfusion and treatment time on the outcomes of patients undergoing endovascular treatment presenting within 24 h of last known well, and to compare the predictive ability of different reperfusion measurements on outcomes.

METHODS: Eligible patients from a single-center cohort were enrolled in this study. Reperfusion was assessed using reperfusion index (decreased volume of hypoperfusion lesion compared with baseline) measured by repeated perfusion imaging, and modified treatment in cerebral ischemia score measured by digital subtraction angiography, respectively. The interactions between reperfusion measurements and treatment time on outcomes were explored using multivariate-adjusted logistic and linear regression models. The predictive abilities of reperfusion measurements on outcomes were compared using area under the receiver operating characteristic curve (ROC-AUC) and values of R-square.

RESULTS: Reperfusion index and treatment time had significant interactions on 3-month modified Rankin Scale (mRS) 0-2 and infarct growth (p for interaction <0.05). Although the AUCs were statistically similar (AUCs of mRS 0-2 prediction, mTICI≥2b:0.63, mTICI≥2c:0.59, reperfusion index≥0.5:0.66, reperfusion index ≥0.9:0.73, P value of any of the two AUCs >0.05), reperfusion index≥0.9 showed the highest R-square values in outcome prediction (R-square values of 3-month mRS 0-2 and infarct growth = 0.21) among all the reperfusion measurements.

CONCLUSION: Treatment time mitigated the effect of reperfusion on outcomes of patients receiving endovascular treatment within 24 h of last known well. Reperfusion index≥0.9 might serve as a better proxy of good outcomes compared with other reperfusion measurements.

PMID:36601659 | DOI:10.1111/cns.14080

BMJ Open Respir Res. 2022 Dec;9(1):e001355. doi: 10.1136/bmjresp-2022-001355.

ABSTRACT

BACKGROUND AND OBJECTIVE: Obesity and asthma impose a heavy health and economic burden on millions of people around the world. The complex interaction between genetic traits and phenotypes caused the mechanism between obesity and asthma is still vague. This study investigates the relationship among obesity-related polygenic risk score (PRS), obesity phenotypes and the risk of having asthma.

METHODS: This is a matched case-control study, with 4 controls (8288 non-asthmatic) for each case (2072 asthmatic). Data were obtained from the 2008-2015 Taiwan Biobank Database and linked to the 2000-2016 National Health Insurance Research Database. All participants were ≥30 years old with no history of cancer and had a complete questionnaire, as well as physical examination, genome-wide single nucleotide polymorphisms and clinical diagnosis data. Environmental exposure, PM_2.5, was also considered. Multivariate adjusted ORs and 95% CIs were calculated using conditional logistic regression stratified by age and sex. Mediation analysis was also assessed, using a generalised linear model.

RESULTS: We found that the obese phenotype was associated with significantly increased odds of asthma by approximately 26%. Four obesity-related PRS, including body mass index (OR=1.07 (1.01-1.13)), waist circumference (OR=1.10 (1.04-1.17)), central obesity as defined by waist-to-height ratio (OR=1.09 (1.03-1.15)) and general-central obesity (OR=1.06 (1.00-1.12)), were associated with increased odds of asthma. Additional independent risk factors for asthma included lower educational level, family history of asthma, certain chronic diseases and increased PM_2.5 exposure. Obesity-related PRS is an indirect risk factor for asthma, the link being fully mediated by the trait of obesity.

CONCLUSIONS: Obese phenotypes and obesity-related PRS are independent risk factors for having asthma in adults in the Taiwan Biobank. Overall, genetic risk for obesity increases the risk of asthma by affecting the obese phenotype.

PMID:36600406 | DOI:10.1136/bmjresp-2022-001355