Nevin Manimala

PLoS One. 2021 May 6;16(5):e0250660. doi: 10.1371/journal.pone.0250660. eCollection 2021.

ABSTRACT

Alzheimer’s disease (AD) is the commonest progressive neurodegenerative condition in humans, and is currently incurable. A wide spectrum of comorbidities, including other neurodegenerative diseases, are frequently associated with AD. How AD interacts with those comorbidities can be examined by analysing gene expression patterns in affected tissues using bioinformatics tools. We surveyed public data repositories for available gene expression data on tissue from AD subjects and from people affected by neurodegenerative diseases that are often found as comorbidities with AD. We then utilized large set of gene expression data, cell-related data and other public resources through an analytical process to identify functional disease links. This process incorporated gene set enrichment analysis and utilized semantic similarity to give proximity measures. We identified genes with abnormal expressions that were common to AD and its comorbidities, as well as shared gene ontology terms and molecular pathways. Our methodological pipeline was implemented in the R platform as an open-source package and available at the following link: https://github.com/unchowdhury/AD_comorbidity. The pipeline was thus able to identify factors and pathways that may constitute functional links between AD and these common comorbidities by which they affect each others development and progression. This pipeline can also be useful to identify key pathological factors and therapeutic targets for other diseases and disease interactions.

PMID:33956862 | DOI:10.1371/journal.pone.0250660

PLoS One. 2021 May 6;16(5):e0250936. doi: 10.1371/journal.pone.0250936. eCollection 2021.

ABSTRACT

The mixture level of gum samples consisting of two colours can be assessed visually, using the electronic colorimetric method, employing digital image processing techniques and specially designed software. The study investigates the possibility of an alternative method called “digital texture image analysis” (DTIA) to assess improvement of masticatory efficiency in denture wearers. The objectives were i) to evaluate whether DTIA discriminates changes in the colour mixing ability within a group over time; ii) to determine whether DTIA can be used to detect improvement in chewing ability; iii) to select the most appropriate DTIA feature that sufficiently describes masticatory efficiency in CDs wearers. The study was designed as an intra-individual evaluation of masticatory efficiency, which was assessed in participants with new dentures in three follow-up times. A set of four texture features was used in the current study. Uniformity, Contrast, Homogeneity and Entropy of the obtained chewing-gum samples were correlated to the degree of gum comminution. A statistically significant difference in masticatory efficiency was observed based on the values of the analysed DTIA variables of gum samples-Uniformity, Contrast, Homogeneity, and Entropy-have changed in the participants during the observation period. The improvement of the masticatory function in relation to the mixing ability of two-coloured chewing gum could be traced by monitoring changes in the values of DTIA variables. The most increasement of masticatory efficiency was observed by monitoring DTIA parameters such as contrast, and homogeneity.

PMID:33956854 | DOI:10.1371/journal.pone.0250936

PLoS One. 2021 May 6;16(5):e0250550. doi: 10.1371/journal.pone.0250550. eCollection 2021.

ABSTRACT

INTRODUCTION: In 2018, Malaria accounted for 38% of the overall morbidity and 36% of the overall mortality in the Democratic Republic of Congo (DRC). This study aimed to identify malaria socioeconomic predictors among children aged 6-59 months in DRC and to describe a socioeconomic profile of the most-at-risk children aged 6-59 months for malaria infection.

MATERIALS AND METHODS: This study used data from the 2013 DRC Demographic and Health Survey. The sample included 8,547 children aged 6-59 months who were tested for malaria by microscopy. Malaria infection status, the dependent variable, is a dummy variable characterized as a positive or negative test. The independent variables were child’s sex, age, and living arrangement; mother’s education; household’s socioeconomic variables; province of residence; and type of place of residence. Statistical analyses used the chi-square automatic interaction detector (CHAID) model and logistic regression.

RESULTS: Of the 8,547 children included in the sample, 25% had malaria infection. Four variables-child’s age, mother’s education, province, and wealth index-were statistically associated with the prevalence of malaria infection in bivariate analysis and multivariate analysis (CHAID and logistic regression). The prevalence of malaria infection increases with child’s age and decreases significantly with mother’s education and the household wealth index. These findings suggest that the prevalence of malaria infection is driven by interactions among environmental factors, socioeconomic characteristics, and probably differences in the implementation of malaria programs across the country. The effect of mother’s education on malaria infection was only significant among under-five children living in Ituri, Kasaï-Central, Haut-Uele, Lomami, Nord-Ubangi, and Maniema provinces, and the effect of wealth index was significant in Mai-Ndombe, Tshopo, and Haut-Katanga provinces.

CONCLUSION: Findings from this study could be used for targeting malaria interventions in DRC. Although malaria infection is common across the country, the prevalence of children at high risk for malaria infection varies by province and other background characteristics, including age, mother’s education, wealth index, and place of residence. In light of these findings, designing provincial and multisectoral interventions could be an effective strategy to achieve zero malaria infection in DRC.

PMID:33956848 | DOI:10.1371/journal.pone.0250550

PLoS One. 2021 May 6;16(5):e0250607. doi: 10.1371/journal.pone.0250607. eCollection 2021.

ABSTRACT

OBJECTIVES: We sought to determine the prevalence of phosphodiesterase type 5 inhibitor (PDE-5) mediated drug-drug interactions (DDIs) in males with HIV infection receiving antiretroviral therapy (ART) and identify factors associated with PDE-5-mediated DDIs.

METHODS: Male US Military HIV Natural History Study participants diagnosed with erectile dysfunction (ED) and having a PDE-5 inhibitor and potentially-interacting ART co-dispensed within 30 days were included. DDIs were defined according to criteria found in published guidelines and drug information resources. The primary outcome of interest was overall PDE-5 inhibitor-mediated DDI prevalence and episode duration. A secondary logistic regression analysis was performed on those with and without DDIs to identify factors associated with initial DDI episode.

RESULTS: A total of 235 male participants with ED met inclusion criteria. The majority were White (50.6%) or African American (40.4%). Median age at medication co-dispensing (45 years), duration of HIV infection (14 years), and duration of ED (1 year) did not differ between the two groups (p>0.05 for all). PDE-5 inhibitors included sildenafil (n = 124), vardenafil (n = 99), and tadalafil (n = 14). ART regimens included RTV-boosted protease inhibitors (PIs) atazanavir (n = 83) or darunavir (n = 34), and COBI-boosted elvitegravir (n = 43). Potential DDIs occurred in 181 (77.0%) participants, of whom 122 (67.4%) had multiple DDI episodes. The median DDI duration was 8 (IQR 1-12) months. In multivariate analyses, non-statistically significant higher odds of DDIs were observed with RTV-boosted PIs or PI-based ART (OR 2.13, 95% CI 0.85-5.37) and in those with a diagnosis of major depressive disorder (OR 1.74, 95% CI 0.83-3.64).

CONCLUSIONS: PDE-5-mediated DDIs were observed in the majority of males with HIV infection on RTV- or COBI-boosted ART in our cohort. This study highlights the importance of assessing for DDIs among individuals on ART, especially those on boosted regimens.

PMID:33956843 | DOI:10.1371/journal.pone.0250607

PLoS One. 2021 May 6;16(5):e0251080. doi: 10.1371/journal.pone.0251080. eCollection 2021.

ABSTRACT

Most lung cancer patients are diagnosed at an advanced stage, limiting their treatment options with very low response rate. Lung cancer is the most common cause of cancer death worldwide. Therapies that target driver gene mutations (e.g. EGFR, ALK, ROS1) and checkpoint inhibitors such anti-PD-1 and PD-L1 immunotherapies are being used to treat lung cancer patients. Identification of correlations between driver mutations and PD-L1 expression will allow for the best management of patient treatment. 851 cases of non-small cell lung cancer cases were profiled for the presence of biomarkers EGFR, KRAS, BRAF, and PIK3CA mutations by SNaPshot/sizing genotyping. Immunohistochemistry was used to identify the protein expression of ALK and PD-L1. Total PD-L1 mRNA expression (from unsorted tumor samples) was quantified by RT-qPCR in a sub-group of the cohort to assess its correlation with PD-L1 protein level in tumor cells. Statistical analysis revealed correlations between the presence of the mutations, PD-L1 expression, and the pathological data. Specifically, increased PD-L1 expression was associated with wildtype EGFR and vascular invasion, and total PD-L1 mRNA levels correlated weakly with protein expression on tumor cells. These data provide insights into driver gene mutations and immune checkpoint status in relation to lung cancer subtypes and suggest that RT-qPCR is useful for assessing PD-L1 levels.

PMID:33956842 | DOI:10.1371/journal.pone.0251080

PLoS One. 2021 May 6;16(5):e0251130. doi: 10.1371/journal.pone.0251130. eCollection 2021.

ABSTRACT

Polar bears are of international conservation concern due to climate change but are difficult to study because of low densities and an expansive, circumpolar distribution. In a collaborative U.S.-Russian effort in spring of 2016, we used aerial surveys to detect and estimate the abundance of polar bears on sea ice in the Chukchi Sea. Our surveys used a combination of thermal imagery, digital photography, and human observations. Using spatio-temporal statistical models that related bear and track densities to physiographic and biological covariates (e.g., sea ice extent, resource selection functions derived from satellite tags), we predicted abundance and spatial distribution throughout our study area. Estimates of 2016 abundance ([Formula: see text]) ranged from 3,435 (95% CI: 2,300-5,131) to 5,444 (95% CI: 3,636-8,152) depending on the proportion of bears assumed to be missed on the transect line during Russian surveys (g(0)). Our point estimates are larger than, but of similar magnitude to, a recent estimate for the period 2008-2016 ([Formula: see text]; 95% CI 1,522-5,944) derived from an integrated population model applied to a slightly smaller area. Although a number of factors (e.g., equipment issues, differing platforms, low sample sizes, size of the study area relative to sampling effort) required us to make a number of assumptions to generate estimates, it establishes a useful lower bound for abundance, and suggests high spring polar bear densities on sea ice in Russian waters south of Wrangell Island. With future improvements, we suggest that springtime aerial surveys may represent a plausible avenue for studying abundance and distribution of polar bears and their prey over large, remote areas.

PMID:33956835 | DOI:10.1371/journal.pone.0251130

PLoS One. 2021 May 6;16(5):e0250692. doi: 10.1371/journal.pone.0250692. eCollection 2021.

ABSTRACT

BACKGROUND: Although abortion is a common gynecological procedure around the globe, we lack synthesis of the known macroeconomic costs and outcomes of abortion care and abortion policies. This scoping review synthesizes the literature on the impact of abortion-related care and abortion policies on economic outcomes at the macroeconomic level (that is, for societies and nation states).

METHODS AND FINDINGS: Searches were conducted in eight electronic databases. We conducted the searches and application of inclusion/exclusion criteria using the PRISMA extension for Scoping Reviews. For inclusion, studies must have examined one of the following macroeconomic outcomes: costs, impacts, benefits, and/or value of abortion care or abortion policies. Quantitative and qualitative data were extracted for descriptive statistics and thematic analysis. Of the 189 data extractions with macroeconomic evidence, costs at the national level are the most frequently reported economic outcome (n = 97), followed by impacts (n = 66), and benefits/value (n = 26). Findings show that post-abortion care services can constitute a substantial portion of national expenditures on health. Public sector coverage of abortion costs is sparse, and individuals bear most of the costs. Evidence also indicates that liberalizing abortion laws can have positive spillover effects for women’s educational attainment and labor supply, and that access to abortion services contributes to improvements in children’s human capital. However, the political economy around abortion legislation remains complicated and controversial.

CONCLUSIONS: Given the highly charged political nature of abortion around the global and the preponderance of rhetoric that can cloud reality in policy dialogues, it is imperative that social science researchers build the evidence base on the macroeconomic outcomes of abortion services and regulations.

PMID:33956826 | DOI:10.1371/journal.pone.0250692

PLoS One. 2021 May 6;16(5):e0251026. doi: 10.1371/journal.pone.0251026. eCollection 2021.

ABSTRACT

BACKGROUND: Major depression is a common comorbidity in cancer patients. Oncology clinics lack practical, objective tools for simultaneous evaluation of cancer and major depression. Fludeoxyglucose F-18 positron emission tomography-computed tomography (FDG PET/CT) is universally applied in modern medicine.

METHODS: We used a retrospective analysis of whole-body FDG PET/CT images to identify brain regional metabolic patterns of major depression in multiple myeloma patients. The study included 134 multiple myeloma (MM) patients, 38 with major depression (group 1) and 96 without major depression (group 2).

RESULTS: In the current study, Statistic Parameter Mapping (SPM) demonstrated that the major depression patient group (n = 38) had significant regional metabolic differences (clusters of continuous voxels) as compared to the non-major depression group (n = 96) with the criteria of height threshold T = 4.38 and extent threshold > 100 voxels. The five significant hypo- and three hyper-metabolic clusters from the computed T contrast maps were localized on the glass-brain view, consistent with published brain metabolic changes in major depression patients. Subsequently, using these clusters as features for classification learner, the fine tree and medium tree algorithms from 25 classification algorithms best fitted our data (accuracy 0.85%; AUC 0.88; sensitivity 79%; and specificity 88%).

CONCLUSION: This study demonstrated that whole-body FDG PET/CT scans could provide added value for screening for major depression in cancer patients in addition to staging and evaluating response to chemoradiation therapies.

PMID:33956824 | DOI:10.1371/journal.pone.0251026

PLoS One. 2021 May 6;16(5):e0250804. doi: 10.1371/journal.pone.0250804. eCollection 2021.

ABSTRACT

BACKGROUND: Drug resistance tuberculosis (DR-TB) patients’ mortality and loss to follow-up (LTF) from treatment and care is a growing worry in Ethiopia. However, little is known about predictors of mortality and LTF among drug-resistant tuberculosis patients in Oromia region, Ethiopia. The current study aimed to identify predictors of mortality and loss to follow-up among drug resistance tuberculosis patients in Oromia Hospitals, Ethiopia.

METHODS: A retrospective follow up study was carried out from 01 November 2012 to 31 December 2017 among DR-TB patients after calculating sample size using single proportion population formula. Mean, median, Frequency tables and bar charts were used to describe patients’ characteristics in the cohort. The Kaplan-Meier curve was used to estimate the probability of death and LTF after the treatment was initiated. The log-rank test was used to compare time to death and time to LTF. The Cox proportional hazard model was used to determine predictors of mortality and LTF after DR-TB diagnosis. The Crude and adjusted Cox proportional hazard ratio was used to measure the strength of association whereas p-value less than 0.05 were used to declare statistically significant predictors.

RESULT: A total of 406 DR-TB patients were followed for 7084 person-months observations. Among the patients, 71 (17.5%) died and 32 (7.9%) were lost to follow up (LTF). The incidence density of death and LTF in the cohort was 9.8 and 4.5 per 1000 person-months, respectively. The median age of the study participants was 28 years (IQR: 27.1, 29.1). The overall cumulative survival probability of patients at the end of 24 months was 77.5% and 84.5% for the mortality and LTF, respectively. The independent predictors of death was chest radiographic findings (AHR = 0.37, 95% CI: 0.17-0.79) and HIV serostatus 2.98 (95% CI: 1.72-5.19). Drug adverse effect (AHR = 6.1; 95% CI: 2.5, 14.34) and culture test result (AHR = 0.1; 95% CI: 0.1, 0.3) were independent predictors of LTF.

CONCLUSION: This study concluded that drug-resistant tuberculosis mortality and LTF remains high in the study area. Continual support of the integration of TB/HIV service with emphasis and work to identified predictors may help in reducing drug-resistant tuberculosis mortality and LTF.

PMID:33956812 | DOI:10.1371/journal.pone.0250804

PLoS One. 2021 May 6;16(5):e0250784. doi: 10.1371/journal.pone.0250784. eCollection 2021.

ABSTRACT

Scholars have offered multiple theoretical resolutions to explain inconsistent findings about the relationship of state repression and protests, but this repression-dissent puzzle remains unsolved. We simulate the spread of protest on social networks to suggest that the repression-dissent puzzle arises from the nature of statistical sampling. Even though the paper’s simulations construct repression so it can only decrease protest size, the strength of repression sometimes correlates with a decrease, increase, or no change in protest size, regardless of the type of network or sample size chosen. Moreover, the results are most contradictory when the repression rate most closely matches that observed in real-world data. These results offer a new framework for understanding state and protester behavior and suggest the importance of collecting network data when studying protests.

PMID:33956806 | DOI:10.1371/journal.pone.0250784