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Nevin Manimala Statistics

What Are the Effects on Palate of Early Lip Surgery in Children With Cleft Lip and Palate? Cross-Sectional Evaluation From 5-Year-Old

J Craniofac Surg. 2023 Jul 6. doi: 10.1097/SCS.0000000000009501. Online ahead of print.

ABSTRACT

This study aimed to evaluate the postsurgical effects from 5 years on the palate after surgical repair of the lip at 3 or 9 months of age in children with cleft lip and palate. Eighty-four digitized dental impressions were divided into the following groups: group 1 (G1): lip surgery at 3 months of life; group 2 (G2): lip surgery at 9 months of life; group 3 (G3): without orofacial cleft. Five angular (C’IC, ICM, IC’M’, CMM’, and C’M’M) and 3 linear parameters (C-C’, c-c’, and M-M’) were evaluated. Statistical analysis was applied with α=5%. Intraclass Correlation Coefficient was significantly smaller in G1 than in G3 (P=0.005), while IC’M’ was significantly smaller in G3 than in G1 (P<0.001). C’M’M was significantly smaller in G1 than in G2 and G3 (P<0.001). The distances C-C’ and c-c’ were significantly smaller in G1 than in G2 and G3 (P<0.001). There was a statistically significant difference in both G1 and G2 (P<0.001, in all) in the analysis of palatal symmetry. Linear regression analysis showed that the, 11.2% of outcomes determined by c-c’ distance can be explained by the age of lip repair (P=0.013). In conclusion, lip surgery at 3 months of life showed a tendency toward more restriction in 5-year postsurgery palate development. The age of cheiloplasty is one of the factors that can influence palatal development; however, other factors may be associated and should be studied.

PMID:37418613 | DOI:10.1097/SCS.0000000000009501

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Nevin Manimala Statistics

SETD2 loss in renal epithelial cells drives epithelial-to-mesenchymal transition in a TGF-β-independent manner

Mol Oncol. 2023 Jul 7. doi: 10.1002/1878-0261.13487. Online ahead of print.

ABSTRACT

Histone-lysine N-methyltransferase SETD2 (SETD2), the sole histone methyltransferase that catalyzes trimethylation of lysine 36 on histone H3 (H3K36me3), is often mutated in clear cell renal cell carcinoma (ccRCC). SETD2 mutation and/or loss of H3K36me3 is linked to metastasis and poor outcome in ccRCC patients. Epithelial-to-mesenchymal transition (EMT) is a major pathway that drives invasion and metastasis in various cancer types. Here, using novel kidney epithelial cell lines isogenic for SETD2, we discovered that SETD2 inactivation drives EMT and promotes migration, invasion and stemness in a transforming growth factor beta (TGF-β)-independent manner. This newly identified EMT program is triggered in part through secreted factors, including cytokines and growth factors, and through transcriptional reprogramming. RNA-seq and assay for transposase-accessible chromatin sequencing (ATAC-seq) uncovered key transcription factors upregulated upon SETD2 loss, including SOX2, POU2F2 (OCT2) and PRRX1, that could individually drive EMT and stemness phenotypes in SETD2 wild-type cells. Public expression data from SETD2 wild-type/mutant ccRCC support the EMT transcriptional signatures derived from cell line models. In summary, our studies reveal that SETD2 is a key regulator of EMT phenotypes through cell-intrinsic and cell-extrinsic mechanisms that help explain the association between SETD2 loss and ccRCC metastasis.

PMID:37418588 | DOI:10.1002/1878-0261.13487

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Nevin Manimala Statistics

Achieving the 3rd 95 in sub-saharan Africa: application of machine learning approaches to predict viral failure

AIDS. 2023 Jul 7. doi: 10.1097/QAD.0000000000003646. Online ahead of print.

ABSTRACT

OBJECTIVE: Viral failure in people living with HIV (PLWH) may be influenced by multiple socio-behavioral, clinical, and context-specific factors, and supervised learning approaches may identify novel predictors. We compared the performance of two supervised learning algorithms to predict viral failure in four African countries.

DESIGN: Cohort study.

METHODS: The African Cohort Study is an ongoing, longitudinal cohort enrolling PLWH at 12 sites in Uganda, Kenya, Tanzania, and Nigeria. Participants underwent physical examination, medical history-taking, medical record extraction, socio-behavioral interviews, and laboratory testing. In cross-sectional analyses of enrollment data, viral failure was defined as a viral load ≥1000 copies/mL among participants on antiretroviral therapy (ART) for at least six months. We compared the performance of lasso-type regularized regression and random forests by calculating area under the curve (AUC) and used each to identify factors associated with viral failure; 94 explanatory variables were considered.

RESULTS: Between January 2013 and December 2020, 2,941 PLWH were enrolled, 1,602 had been on ART for at least 6 months, and 1,571 participants with complete case data were included. At enrollment, 190 (12.0%) had viral failure. The lasso regression model was slightly superior to the random forest in its ability to identify PLWH with viral failure (AUC: 0.82 vs 0.75). Both models identified CD4 count, ART regimen, age, self-reported ART adherence and duration on ART as important factors associated with viral failure.

CONCLUSION: These findings corroborate existing literature primarily based on hypothesis-testing statistical approaches and help to generate questions for future investigations that may impact viral failure.

PMID:37418549 | DOI:10.1097/QAD.0000000000003646

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Nevin Manimala Statistics

A flexible empirical Bayes approach to multivariate multiple regression, and its improved accuracy in predicting multi-tissue gene expression from genotypes

PLoS Genet. 2023 Jul 7;19(7):e1010539. doi: 10.1371/journal.pgen.1010539. Online ahead of print.

ABSTRACT

Predicting phenotypes from genotypes is a fundamental task in quantitative genetics. With technological advances, it is now possible to measure multiple phenotypes in large samples. Multiple phenotypes can share their genetic component; therefore, modeling these phenotypes jointly may improve prediction accuracy by leveraging effects that are shared across phenotypes. However, effects can be shared across phenotypes in a variety of ways, so computationally efficient statistical methods are needed that can accurately and flexibly capture patterns of effect sharing. Here, we describe new Bayesian multivariate, multiple regression methods that, by using flexible priors, are able to model and adapt to different patterns of effect sharing and specificity across phenotypes. Simulation results show that these new methods are fast and improve prediction accuracy compared with existing methods in a wide range of settings where effects are shared. Further, in settings where effects are not shared, our methods still perform competitively with state-of-the-art methods. In real data analyses of expression data in the Genotype Tissue Expression (GTEx) project, our methods improve prediction performance on average for all tissues, with the greatest gains in tissues where effects are strongly shared, and in the tissues with smaller sample sizes. While we use gene expression prediction to illustrate our methods, the methods are generally applicable to any multi-phenotype applications, including prediction of polygenic scores and breeding values. Thus, our methods have the potential to provide improvements across fields and organisms.

PMID:37418505 | DOI:10.1371/journal.pgen.1010539

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Nevin Manimala Statistics

Repurposing the Medicines for Malaria Venture’s COVID Box to discover potent inhibitors of Toxoplasma gondii, and in vivo efficacy evaluation of almitrine bismesylate (MMV1804175) in chronically infected mice

PLoS One. 2023 Jul 7;18(7):e0288335. doi: 10.1371/journal.pone.0288335. eCollection 2023.

ABSTRACT

Toxoplasmosis, caused by the obligate intracellular parasite Toxoplasma gondii, affects about one-third of the world’s population and can cause severe congenital, neurological and ocular issues. Current treatment options are limited, and there are no human vaccines available to prevent transmission. Drug repurposing has been effective in identifying anti-T. gondii drugs. In this study, the screening of the COVID Box, a compilation of 160 compounds provided by the “Medicines for Malaria Venture” organization, was conducted to explore its potential for repurposing drugs to combat toxoplasmosis. The objective of the present work was to evaluate the compounds’ ability to inhibit T. gondii tachyzoite growth, assess their cytotoxicity against human cells, examine their absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties, and investigate the potential of one candidate drug through an experimental chronic model of toxoplasmosis. Early screening identified 29 compounds that could inhibit T. gondii survival by over 80% while keeping human cell survival up to 50% at a concentration of 1 μM. The Half Effective Concentrations (EC50) of these compounds ranged from 0.04 to 0.92 μM, while the Half Cytotoxic Concentrations (CC50) ranged from 2.48 to over 50 μM. Almitrine was chosen for further evaluation due to its favorable characteristics, including anti-T. gondii activity at nanomolar concentrations, low cytotoxicity, and ADMET properties. Administering almitrine bismesylate (Vectarion®) orally at dose of 25 mg/kg/day for ten consecutive days resulted in a statistically significant (p < 0.001) reduction in parasite burden in the brains of mice chronically infected with T. gondii (ME49 strain). This was determined by quantifying the RNA of living parasites using real-time PCR. The presented results suggest that almitrine may be a promising drug candidate for additional experimental studies on toxoplasmosis and provide further evidence of the potential of the MMV collections as a valuable source of drugs to be repositioned for infectious diseases.

PMID:37418497 | DOI:10.1371/journal.pone.0288335

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Nevin Manimala Statistics

Regularized sequence-context mutational trees capture variation in mutation rates across the human genome

PLoS Genet. 2023 Jul 7;19(7):e1010807. doi: 10.1371/journal.pgen.1010807. Online ahead of print.

ABSTRACT

Germline mutation is the mechanism by which genetic variation in a population is created. Inferences derived from mutation rate models are fundamental to many population genetics inference methods. Previous models have demonstrated that nucleotides flanking polymorphic sites-the local sequence context-explain variation in the probability that a site is polymorphic. However, limitations to these models exist as the size of the local sequence context window expands. These include a lack of robustness to data sparsity at typical sample sizes, lack of regularization to generate parsimonious models and lack of quantified uncertainty in estimated rates to facilitate comparison between models. To address these limitations, we developed Baymer, a regularized Bayesian hierarchical tree model that captures the heterogeneous effect of sequence contexts on polymorphism probabilities. Baymer implements an adaptive Metropolis-within-Gibbs Markov Chain Monte Carlo sampling scheme to estimate the posterior distributions of sequence-context based probabilities that a site is polymorphic. We show that Baymer accurately infers polymorphism probabilities and well-calibrated posterior distributions, robustly handles data sparsity, appropriately regularizes to return parsimonious models, and scales computationally at least up to 9-mer context windows. We demonstrate application of Baymer in three ways-first, identifying differences in polymorphism probabilities between continental populations in the 1000 Genomes Phase 3 dataset, second, in a sparse data setting to examine the use of polymorphism models as a proxy for de novo mutation probabilities as a function of variant age, sequence context window size, and demographic history, and third, comparing model concordance between different great ape species. We find a shared context-dependent mutation rate architecture underlying our models, enabling a transfer-learning inspired strategy for modeling germline mutations. In summary, Baymer is an accurate polymorphism probability estimation algorithm that automatically adapts to data sparsity at different sequence context levels, thereby making efficient use of the available data.

PMID:37418489 | DOI:10.1371/journal.pgen.1010807

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Nevin Manimala Statistics

An investigation into the associations between psychological skills, anaerobic fitness, and aerobic fitness in elite Iranian taekwondo athletes

PLoS One. 2023 Jul 7;18(7):e0288227. doi: 10.1371/journal.pone.0288227. eCollection 2023.

ABSTRACT

This study investigated the relationship between psychological skills and fitness levels among elite taekwondo athletes. A total of ten Iranian male elite taekwondo athletes (mean age of 20.6±2 years, BMI 18.78±0.62 kg/m2, and fat percentage of 8.87±1.46%) participated in the study. The Sports Emotional Intelligence Questionnaire, Sports Success Scale, Sport Mental Toughness Questionnaire, and Mindfulness Inventory for Sport were used to assess psychological factors. The Wingate test was used to determine anaerobic power, and the Bruce test to determine aerobic fitness. Descriptive statistics and Spearman rank correlation coefficients were utilised to examine any relationships between subscales. Statistically significant correlations were recorded between the evaluation of feelings (EI scale) and VO2peak (ml/kg/min) (r = -0.70, p = 0.0235) and between social skills (EI scale) and relative peak power (W/kg) (r = 0.84, p = 0.0026). Also, between optimism (EI scale) and VO2peak (ml/kg/min) (r = -0.70, p = 0.0252) and between optimism (EI scale) and HR-MAX (r = -0.75, p = 0.0123); and, finally, between control (mental toughness scale) and relative peak power (W/kg) (r = 0.67, p = 0.0360). These findings demonstrate relationships between psychological factors and the advantages of good anaerobic and aerobic capabilities. Finally, the study also demonstrated that elite taekwondo athletes have high mental performance abilities that are interrelated with anaerobic and aerobic performance.

PMID:37418479 | DOI:10.1371/journal.pone.0288227

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Nevin Manimala Statistics

Model-based image updating in deep brain stimulation with assimilation of deep brain sparse data

Med Phys. 2023 Jul 7. doi: 10.1002/mp.16578. Online ahead of print.

ABSTRACT

BACKGROUND: Accuracy of electrode placement for deep brain stimulation (DBS) is critical to achieving desired surgical outcomes and impacts the efficacy of treating neurodegenerative diseases. Intraoperative brain shift degrades the accuracy of surgical navigation based on preoperative images.

PURPOSE: We extended a model-based image updating scheme to address intraoperative brain shift in DBS surgery and improved its accuracy in deep brain.

METHODS: We evaluated 10 patients, retrospectively, who underwent bilateral DBS surgery and classified them into groups of large and small deformation based on a 2 mm subsurface movement threshold and brain shift index of 5%. In each case, sparse brain deformation data were used to estimate whole brain displacements and deform preoperative CT (preCT) to generate updated CT (uCT). Accuracy of uCT was assessed using target registration errors (TREs) at the Anterior Commissure (AC), Posterior Commissure (PC), and four calcification points in the sub-ventricular area by comparing their locations in uCT with their ground truth counterparts in postoperative CT (postCT).

RESULTS: In the large deformation group, TREs were reduced from 2.5 mm in preCT to 1.2 mm in uCT (53% compensation); in the small deformation group, errors were reduced from 1.25 to 0.74 mm (41%). Average reduction of TREs at AC, PC and pineal gland were significant, statistically (p ⩽ 0.01).

CONCLUSIONS: With more rigorous validation of model results, this study confirms the feasibility of improving the accuracy of model-based image updating in compensating for intraoperative brain shift during DBS procedures by assimilating deep brain sparse data.

PMID:37418478 | DOI:10.1002/mp.16578

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Nevin Manimala Statistics

Food safety knowledge, attitudes, and practices among Jordanian women handling food at home during COVID-19 pandemic

PLoS One. 2023 Jul 7;18(7):e0288323. doi: 10.1371/journal.pone.0288323. eCollection 2023.

ABSTRACT

Concerns over food safety issues during the coronavirus pandemic (COVID-19) have sparked worldwide interest. Being part of a farm-to-fork food safety chain, food handlers at home are the final line of defense in reducing foodborne diseases. The present study used a cross-sectional survey to investigate the knowledge, attitudes, and practices (KAP) of women food handlers in Jordan. The survey investigated the effect of the COVID-19 pandemic on women who handle food at home in terms of food safety KAP. One thousand one hundred twenty-six respondents completed a food safety questionnaire during the COVID-19 pandemic. With a mean score of 22.1 points out of 42, the results showed that women who handle food in their houses had insufficient knowledge, negative attitudes, and incorrect practices concerning food safety. The respondents demonstrated high knowledge, attitudes, and practices in the personal hygiene, cleaning and sanitation areas (≥ 60.0%). On the other hand, participants’ knowledge, attitudes, and practices regarding contamination prevention, health issues that would affect food safety, symptoms of foodborne illnesses, safe storage, thawing, cooking, keeping, and reheating of foods, as well as COVID-19 were all low (< 60.0%). The correlations between participants’ total food safety KAP scores and education, age, experience, region, and the pandemic effect on food safety were statistically significant (P ≤ 0.05). To the best of our knowledge, this study is the first conducted in Jordan to investigate food safety knowledge, attitudes, and practices by women handling food at home during the COVID-19 pandemic.

PMID:37418464 | DOI:10.1371/journal.pone.0288323

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Nevin Manimala Statistics

Indirect estimation of the need for palliative care during the COVID-19 pandemic: A descriptive cross-sectional study using mortality data in the Biobío Region, Chile

PLoS One. 2023 Jul 7;18(7):e0288020. doi: 10.1371/journal.pone.0288020. eCollection 2023.

ABSTRACT

BACKGROUND: People with chronic diseases in their advanced phase require palliative care. This is essential to ensure their quality of life as it ends. However, a very low percentage of patients receive the necessary palliative care. The COVID-19 pandemic has adversely affected the planning and provision of palliative care. Despite this, in Chile, palliative care coverage was extended by law to cover nononcological chronic diseases. Implementation of this law is expected to be a significant challenge in terms of material resources, as well as the need for the formation of specialized palliative care teams. Therefore, it is essential to estimate the need for palliative care for all chronic diseases to generate useful input for planning and decision-making in public health.

OBJECTIVES: To indirectly estimate the need for palliative care among people with Chronic Oncological Diseases (COD) and Chronic Non-Oncological Diseases (CNOD) during the prepandemic and pandemic context due to COVID-19 in the Biobío Region in Chile.

METHODS: Cross-sectional study based on mortality data from chronic oncological and nononcological diseases during the prepandemic (2010-2018) and pandemic (2020-2021) contexts due to COVID-19 in a Region of Chile through indirect estimation using minimal estimate, standardized mortality rates and geographically weighted regression.

RESULTS: It was estimated that 76.25% of deaths from chronic diseases in the Biobío Region would have required palliative care, which represents 77,618 people who should have been included in these health benefits. The pandemic had a significant effect on the average number of deaths from CNOD. People belonging to this group were more likely to die from COVID-19 than from their baseline disease, unlike the deaths of people from COD, where no significant changes were observed.

CONCLUSION: These estimates highlight the potential size of the population requiring palliative care and emphasize the importance of recognizing the rights of individuals with COD and CNOD conditions. It is evident that there is a significant demand for palliative care services, as well as a pressing need for adequate resources, effective management, and strategic planning to cater to the needs of this population. This is particularly crucial in the heavily impacted areas and communes of the Biobío Region, Chile.

PMID:37418462 | DOI:10.1371/journal.pone.0288020