Category: Nevin Manimala

PLoS One. 2021 Aug 4;16(8):e0254799. doi: 10.1371/journal.pone.0254799. eCollection 2021.

ABSTRACT

Why, contrary to theoretical predictions, do marine microbe communities harbor tremendous phenotypic heterogeneity? How can so many marine microbe species competing in the same niche coexist? We discovered a unifying explanation for both phenomena by investigating a non-cooperative game that interpolates between individual-level competitions and species-level outcomes. We identified all equilibrium strategies of the game. These strategies represent the probability distribution of competitive abilities (e.g. traits) and are characterized by maximal phenotypic heterogeneity. They are also neutral towards each other in the sense that an unlimited number of species can co-exist while competing according to the equilibrium strategies. Whereas prior theory predicts that natural selection would minimize trait variation around an optimum value, here we obtained a mathematical proof that species with maximally variable traits are those that endure. This discrepancy may reflect a disparity between predictions from models developed for larger organisms in contrast to our microbe-centric model. Rigorous mathematics proves that phenotypic heterogeneity is itself a mechanistic underpinning of microbial diversity. This discovery has fundamental ramifications for microbial ecology and may represent an adaptive reservoir sheltering biodiversity in changing environmental conditions.

PMID:34347817 | DOI:10.1371/journal.pone.0254799

PLoS One. 2021 Aug 4;16(8):e0254991. doi: 10.1371/journal.pone.0254991. eCollection 2021.

ABSTRACT

Human pluripotent stem cells (hPSCs) have the potential to differentiate into all cell types, a property known as pluripotency. A deeper understanding of how pluripotency is regulated is required to assist in controlling pluripotency and differentiation trajectories experimentally. Mathematical modelling provides a non-invasive tool through which to explore, characterise and replicate the regulation of pluripotency and the consequences on cell fate. Here we use experimental data of the expression of the pluripotency transcription factor OCT4 in a growing hPSC colony to develop and evaluate mathematical models for temporal pluripotency regulation. We consider fractional Brownian motion and the stochastic logistic equation and explore the effects of both additive and multiplicative noise. We illustrate the use of time-dependent carrying capacities and the introduction of Allee effects to the stochastic logistic equation to describe cell differentiation. We conclude both methods adequately capture the decline in OCT4 upon differentiation, but the Allee effect model has the advantage of allowing differentiation to occur stochastically in a sub-set of cells. This mathematical framework for describing intra-cellular OCT4 regulation can be extended to other transcription factors and developed into predictive models.

PMID:34347824 | DOI:10.1371/journal.pone.0254991

PLoS One. 2021 Aug 4;16(8):e0252878. doi: 10.1371/journal.pone.0252878. eCollection 2021.

ABSTRACT

PURPOSE: To study the effect of statin exposure on the progression from non-exudative to exudative age-related macular degeneration (AMD).

METHODS: Retrospective cohort study of commercially insured patients diagnosed with non-exudative AMD (n = 231,888) from 2007 to 2015. Time-to-event analysis of the association between exposure to lipid-lowering medications and time from non-exudative AMD to exudative AMD diagnosis was conducted. Outcome measures included progression to exudative AMD, indicated by diagnosis codes for exudative AMD or procedural codes for intravitreal injections.

RESULTS: In the year before and after first AMD diagnosis, 11,330 patients were continuously prescribed lipid-lowering medications and 31,627 patients did not take any lipid-lowering medication. Of those taking statins, 21 (1.6%) patients were on very-high-dose lipophilic statins, 644 (47.6%) on high-dose lipophilic statins, and 689 (50.9%) on low-dose lipophilic statins. We found no statistically significant relationship between exposure to low (HR 0.89, 95% CI 0.83 to 1.38) or high-dose lipophilic statins (HR 1.12, 95% CI 0.86 to 1.45) and progression to exudative AMD. No patients taking very-high-dose lipophilic statins converted from non-exudative to exudative AMD, though this difference was not statistically significant due to the subgroup size (p = .23, log-rank test).

CONCLUSIONS: No statistically significant relationship was found between statin exposure and risk of AMD progression. Interestingly, no patients taking very-high-dose lipophilic statins progressed to exudative AMD, a finding that warrants further exploration.

PMID:34347799 | DOI:10.1371/journal.pone.0252878

PLoS One. 2021 Aug 4;16(8):e0254755. doi: 10.1371/journal.pone.0254755. eCollection 2021.

ABSTRACT

The association between obesity and vertebral fracture remains controversial. This study aimed to investigate the association between obesity/abdominal obesity and vertebral fracture according to menopausal status. This nationwide population-based epidemiologic study collected data from the Korean National Health Insurance Services to investigate the association between obesity/abdominal obesity and vertebral fracture in pre and postmenopausal women who underwent national cancer screening in 2009. We used three body composite indices of obesity, body mass index, waist circumference and waist-to-height ratio, to classify participants into obesity and abdominal obesity groups. In both pre and postmenopausal groups, participants with obesity showed a higher risk of vertebral fracture and the association was stronger in those with abdominal obesity (p < 0.001). Participants with obesity showed a high risk of vertebral fracture, and the association was stronger in participants with abdominal obesity (p < 0.001). In both pre and postmenopausal groups, participants with obesity showed a higher risk of vertebral fracture (adjusted HR, 1.24; 95% CI, 1.19-1.30), (adjusted HR, 1.04; 95% CI, 1.03-1.05, and those with abdominal obesity showed even higher risk of vertebral fractures (adjusted HR, 1.35; 95% CI, 1.27-1.43), (adjusted HR, 1.13; 95% CI, 1.11-1.14). Vertebral fracture risk is higher in pre and postmenopausal women with obesity and even higher in those with abdominal obesity. Therefore, weight management can prevent vertebral fractures.

PMID:34347809 | DOI:10.1371/journal.pone.0254755

PLoS One. 2021 Aug 4;16(8):e0254340. doi: 10.1371/journal.pone.0254340. eCollection 2021.

ABSTRACT

The COVID-19 pandemic has impelled the majority of schools and universities around the world to switch to remote teaching. One of the greatest challenges in online education is preserving the academic integrity of student assessments. The lack of direct supervision by instructors during final examinations poses a significant risk of academic misconduct. In this paper, we propose a new approach to detecting potential cases of cheating on the final exam using machine learning techniques. We treat the issue of identifying the potential cases of cheating as an outlier detection problem. We use students’ continuous assessment results to identify abnormal scores on the final exam. However, unlike a standard outlier detection task in machine learning, the student assessment data requires us to consider its sequential nature. We address this issue by applying recurrent neural networks together with anomaly detection algorithms. Numerical experiments on a range of datasets show that the proposed method achieves a remarkably high level of accuracy in detecting cases of cheating on the exam. We believe that the proposed method would be an effective tool for academics and administrators interested in preserving the academic integrity of course assessments.

PMID:34347794 | DOI:10.1371/journal.pone.0254340

PLoS One. 2021 Aug 4;16(8):e0255073. doi: 10.1371/journal.pone.0255073. eCollection 2021.

ABSTRACT

BACKGROUND: The burden of child under-nutrition still remains a global challenge, with greater severity being faced by low- and middle-income countries, despite the strategies in the Sustainable Development Goals (SDGs). Globally, malnutrition is the one of the most important risk factors associated with illness and death, affecting hundreds of millions of pregnant women and young children. Sub-Saharan Africa is one of the regions in the world struggling with the burden of chronic malnutrition. The 2018 Zambia Demographic and Health Survey (ZDHS) report estimated that 35% of the children under five years of age are stunted. The objective of this study was to analyse the distribution, and associated factors of stunting in Zambia.

METHODS: We analysed the relationships between socio-economic, and remote sensed characteristics and anthropometric outcomes in under five children, using Bayesian distributional regression. Georeferenced data was available for 25,852 children from two waves of the ZDHS, 31% observation were from the 2007 and 69% were from the 2013/14. We assessed the linear, non-linear and spatial effects of covariates on the height-for-age z-score.

RESULTS: Stunting decreased between 2007 and 2013/14 from a mean z-score of 1.59 (credible interval (CI): -1.63; -1.55) to -1.47 (CI: -1.49; -1.44). We found a strong non-linear relationship for the education of the mother and the wealth of the household on the height-for-age z-score. Moreover, increasing levels of maternal education above the eighth grade were associated with a reduced variation of stunting. Our study finds that remote sensed covariates alone explain little of the variation of the height-for-age z-score, which highlights the importance to collect socio-economic characteristics, and to control for socio-economic characteristics of the individual and the household.

CONCLUSIONS: While stunting still remains unacceptably high in Zambia with remarkable regional inequalities, the decline is lagging behind goal two of the SDGs. This emphasises the need for policies that help to reduce the share of chronic malnourished children within Zambia.

PMID:34347795 | DOI:10.1371/journal.pone.0255073

PLoS Negl Trop Dis. 2021 Aug 4;15(8):e0009633. doi: 10.1371/journal.pntd.0009633. eCollection 2021 Aug.

ABSTRACT

Dengue fever virus (DENV) is a global health threat that is becoming increasingly critical. However, the pathogenesis of dengue has not yet been fully elucidated. In this study, we employed bioinformatics analysis to identify potential biomarkers related to dengue fever and clarify their underlying mechanisms. The results showed that there were 668, 1901, and 8283 differentially expressed genes between the dengue-infected samples and normal samples in the GSE28405, GSE38246, and GSE51808 datasets, respectively. Through overlapping, a total of 69 differentially expressed genes (DEGs) were identified, of which 51 were upregulated and 18 were downregulated. We identified twelve hub genes, including MX1, IFI44L, IFI44, IFI27, ISG15, STAT1, IFI35, OAS3, OAS2, OAS1, IFI6, and USP18. Except for IFI44 and STAT1, the others were statistically significant after validation. We predicted the related microRNAs (miRNAs) of these 12 target genes through the database miRTarBase, and finally obtained one important miRNA: has-mir-146a-5p. In addition, gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were carried out, and a protein-protein interaction (PPI) network was constructed to gain insight into the actions of DEGs. In conclusion, our study displayed the effectiveness of bioinformatics analysis methods in screening potential pathogenic genes in dengue fever and their underlying mechanisms. Further, we successfully predicted IFI44L and IFI6, as potential biomarkers with DENV infection, providing promising targets for the treatment of dengue fever to a certain extent.

PMID:34347790 | DOI:10.1371/journal.pntd.0009633

PLoS One. 2021 Aug 4;16(8):e0255024. doi: 10.1371/journal.pone.0255024. eCollection 2021.

ABSTRACT

Comparison of normality tests based on absolute or average powers are bound to give ambiguous results, since these statistics critically depend upon the alternative distribution which cannot be specified. A test which is optimal against a certain type of alternatives may perform poorly against other alternative distributions. Thus, an invariant benchmark is proposed in the recent normality literature by computing Neyman-Pearson tests against each alternative distribution. However, the computational cost of this benchmark is significantly high, therefore, this study proposes an alternative approach for computing the benchmark. The proposed min-max approach reduces the calculation cost in terms of computing and estimating the Neyman-Pearson tests against each alternative distribution. An extensive simulation study is conducted to evaluate the selected normality tests using the proposed methodology. The proposed min-max method produces similar results in comparison with the benchmark based on Neyman-Pearson tests but at a low computational cost.

PMID:34347791 | DOI:10.1371/journal.pone.0255024

PLoS One. 2021 Aug 4;16(8):e0253809. doi: 10.1371/journal.pone.0253809. eCollection 2021.

ABSTRACT

BACKGROUND: Self-harm occurring within pregnancy and the postnatal year (“perinatal self-harm”) is a clinically important yet under-researched topic. Current research likely under-estimates prevalence due to methodological limitations. Electronic healthcare records (EHRs) provide a source of clinically rich data on perinatal self-harm.

AIMS: (1) To create a Natural Language Processing (NLP) tool that can, with acceptable precision and recall, identify mentions of acts of perinatal self-harm within EHRs. (2) To use this tool to identify service-users who have self-harmed perinatally, based on their EHRs.

METHODS: We used the Clinical Record Interactive Search system to extract de-identified EHRs of secondary mental healthcare service-users at South London and Maudsley NHS Foundation Trust. We developed a tool that applied several layers of linguistic processing based on the spaCy NLP library for Python. We evaluated mention-level performance in the following domains: span, status, temporality and polarity. Evaluation was done against a manually coded reference standard. Mention-level performance was reported as precision, recall, F-score and Cohen’s kappa for each domain. Performance was also assessed at ‘service-user’ level and explored whether a heuristic rule improved this. We report per-class statistics for service-user performance, as well as likelihood ratios and post-test probabilities.

RESULTS: Mention-level performance: micro-averaged F-score, precision and recall for span, polarity and temporality >0.8. Kappa for status 0.68, temporality 0.62, polarity 0.91. Service-user level performance with heuristic: F-score, precision, recall of minority class 0.69, macro-averaged F-score 0.81, positive LR 9.4 (4.8-19), post-test probability 69.0% (53-82%). Considering the task difficulty, the tool performs well, although temporality was the attribute with the lowest level of annotator agreement.

CONCLUSIONS: It is feasible to develop an NLP tool that identifies, with acceptable validity, mentions of perinatal self-harm within EHRs, although with limitations regarding temporality. Using a heuristic rule, it can also function at a service-user-level.

PMID:34347787 | DOI:10.1371/journal.pone.0253809

Leadersh Health Serv (Bradf Engl). 2021 Aug 5;ahead-of-print(ahead-of-print). doi: 10.1108/LHS-01-2021-0007.

ABSTRACT

PURPOSE: The Health Service Executive in Ireland seeks to further develop healthcare in the community. It has identified that this reform requires developing leadership amongst the staff. This study aims to identify what kind of leadership staff in community healthcare observe in practice and their leadership preferences. The core objective has been to identify the readiness of the organisation to implement the adopted national policy of integrated community care reform in terms of leadership development.

DESIGN/METHODOLOGY/APPROACH: An online cross-sectional survey was conducted using the Organisational Cultural Assessment Instrument, based on the Competing Values Framework. This tool identifies four overarching leadership types: Clan (Collaborative), Adhocracy (Creative), Market (Competitive) and Hierarchy (Controlling). Participants (n = 445) were a representative sample of regional community health care employees. They were asked to identify presently observed leadership and preferred leadership in practice. The statistical analysis emphasised a comparison of observed and preferred leadership types.

FINDINGS: Participants reported the current prevailing leadership type as Market (M = 34.38, SD = 6.22) and Hierarchical (M = 34.38, SD = 22.62), whilst the preferred or future style was overwhelmingly Clan (M = 40.38, SD = 18.08). Differences were significant (all p‘s < 0.001). The overall outcome indicates a predominance of controlling and competitive leadership and a lack of collaborative leadership to implement the planned reform.

ORIGINALITY/VALUE: During reform in healthcare, leadership in practice must be aligned to the reform strategy, demonstrating collaboration, flexibility and support for innovation. This unique study demonstrates the importance of examining leadership type and competencies to indicate readiness to deliver national community health care reform.

PMID:34346663 | DOI:10.1108/LHS-01-2021-0007