Nevin Manimala

PLoS One. 2022 Oct 21;17(10):e0276401. doi: 10.1371/journal.pone.0276401. eCollection 2022.

ABSTRACT

In bottom-up proteomics, proteins are enzymatically digested into peptides before measurement with mass spectrometry. The relationship between proteins and their corresponding peptides can be represented by bipartite graphs. We conduct a comprehensive analysis of bipartite graphs using quantified peptides from measured data sets as well as theoretical peptides from an in silico digestion of the corresponding complete taxonomic protein sequence databases. The aim of this study is to characterize and structure the different types of graphs that occur and to compare them between data sets. We observed a large influence of the accepted minimum peptide length during in silico digestion. When changing from theoretical peptides to measured ones, the graph structures are subject to two opposite effects. On the one hand, the graphs based on measured peptides are on average smaller and less complex compared to graphs using theoretical peptides. On the other hand, the proportion of protein nodes without unique peptides, which are a complicated case for protein inference and quantification, is considerably larger for measured data. Additionally, the proportion of graphs containing at least one protein node without unique peptides rises when going from database to quantitative level. The fraction of shared peptides and proteins without unique peptides as well as the complexity and size of the graphs highly depends on the data set and organism. Large differences between the structures of bipartite peptide-protein graphs have been observed between database and quantitative level as well as between analyzed species. In the analyzed measured data sets, the proportion of protein nodes without unique peptides ranged from 6.4% to 55.0%. This highlights the need for novel methods that can quantify proteins without unique peptides. The knowledge about the structure of the bipartite peptide-protein graphs gained in this study will be useful for the development of such algorithms.

PMID:36269744 | DOI:10.1371/journal.pone.0276401

PLoS One. 2022 Oct 21;17(10):e0276638. doi: 10.1371/journal.pone.0276638. eCollection 2022.

ABSTRACT

Gastrointestinal disease (GI) is the most common illness in pre-weaned dairy calves. Therefore, effective strategies to manipulate the microbiome of dairy calves under commercial dairy operations are of great importance to improve animal health and reduce antimicrobial usage. The objective of this study was to develop a farm-specific FMT product and to investigate its effects on clinical outcomes and fecal microbial composition of dairy calves. The FMT product was derived from feces from healthy donors (5-24 days of age) raised in the same calf ranch facility as the FMT recipients. Healthy and diarrheic calves were randomly enrolled to a control (n = 115) or FMT (n = 112) treatment group (~36 g of processed fecal matter once daily for 3 days). Fecal samples were collected at enrollment and again 9 days later after the first FMT dose. Although the FMT product was rich in organisms typically known for their beneficial probiotic properties, the FMT therapy did not prevent or ameliorate GI disease in dairy calves. In fact, calves that received FMT were less likely to recover from GI disease, and more likely to die due to GI disease complications. Fecal microbial community analysis revealed an increase in the alpha-diversity in FMT calves; however, no major differences across treatment groups were observed in the beta-diversity analysis. Calves that received FMT had higher relative abundance of an uncultured organism of the genus Lactobacillus and Lactobacillus reuteri on day 10. Moreover, FMT calves had lower relative abundance of Clostridium nexile and Bacteroides vulgatus on day 10. Our results indicate the need to have an established protocol when developing FMT products, based on rigorous inclusion and exclusion criteria for the selection of FMT donors free of potential pathogens, no history of disease or antibiotic treatment.

PMID:36269743 | DOI:10.1371/journal.pone.0276638

PLoS One. 2022 Oct 21;17(10):e0276375. doi: 10.1371/journal.pone.0276375. eCollection 2022.

ABSTRACT

We investigated the associations between periodontal inflammation (gingivitis and periodontitis) and all-kind malignancies, specifically breast and prostate cancer, in a cohort followed-up for 30 years. The study hypothesis was based on the oral inflammation vs. systemic health paradigm. A sample of 2,168 subjects from an original cohort of 105,718 individuals from the greater Stockholm area in Sweden that had been followed since 1985 was investigated. Swedish national health registers were used in the study. Chi-square tests and logistic multiple regression analyses were conducted. The results showed that periodontitis was significantly associated with any cancer after adjusting for gender, age, income, and education (p = 0.015). The probability of getting cancer increased on average by 38% if the patient had periodontitis vs. had not; the odds ratio was 1.380 (95% confidence interval l.066-1.786). No significant association was observed between periodontitis and breast cancer (p = 0.608), while the association between periodontitis and prostate cancer tended towards significance (p = 0.082). However, no statistically significant difference was found between the observed and the calculated distribution of any cancer in gingivitis groups (p = 0.079). Thus, the study hypothesis was partly confirmed by showing a statistically significant association between periodontitis and any cancer.

PMID:36269741 | DOI:10.1371/journal.pone.0276375

PLoS One. 2022 Oct 21;17(10):e0276181. doi: 10.1371/journal.pone.0276181. eCollection 2022.

ABSTRACT

Since the spread of COVID-19 pandemic in early 2020, modeling the related factors became mandatory, requiring new families of statistical distributions to be formulated. In the present paper we are interested in modeling the vaccination rate in some African countries. The recorded data in these countries show less vaccination rate, which will affect the spread of new active cases and will increase the mortality rate. A new extension of the inverted Nadarajah-Haghighi distribution is considered, which has four parameters and is obtained by combining the inverted Nadarajah-Haghighi distribution and the odd Lomax-G family. The proposed distribution is called the odd Lomax inverted Nadarajah-Haghighi (OLINH) distribution. This distribution owns many virtuous characteristics and attractive statistical properties, such as, the simple linear representation of density function, the flexibility of the hazard rate curve and the odd ratio of failure, in addition to other properties related to quantile, the rth-moment, moment generating function, Rényi entropy, and the function of ordered statistics. In this paper we address the problem of parameter estimation from frequentest and Bayesian approach, accordingly a comparison between the performance of the two estimation methods is implemented using simulation analysis and some numerical techniques. Finally different goodness of fit measures are used for modeling the COVID-19 vaccination rate, which proves the suitability of the OLINH distribution over other competitive distributions.

PMID:36269740 | DOI:10.1371/journal.pone.0276181

PLoS One. 2022 Oct 21;17(10):e0276438. doi: 10.1371/journal.pone.0276438. eCollection 2022.

ABSTRACT

BACKGROUND: Human Papillomaviruses (HPV) are highly prevalent in the sexually active populations, with a significant burden in terms of health and psychological cost in all class ages. High-risk (HR) HPV genotypes are associated with anogenital dysplasia and cancers, and anal HPV-induced cancer is increasingly observed in women. The interactions of HPV genotype’s between the anus and the cervix, and the subsequent occurrence of dysplasia remains unclear. This clinical study set out to test the hypothesis that risk factors for anal HR-HPV and dysplasia may differ in women with or without cervical dysplasia or in HIV-positive women.

METHODS: Cervical and anal HPV genotypes and cytology testing will be performed prospectively in a cohort of women recruited in a tertiary university hospital in Switzerland. Women will be allocated to three groups: 1) normal previous cervical smear; 2) high-grade cervical dysplasia (H-SIL) at previous cervical smear; 3) HIV+, independently of previous cervical smear result. General inclusion criteria comprised the followings: Female-Age > = 18 years; Satisfactory understanding of French; No objection to HIV testing. Specific inclusion criteria are: Group 1, no past or current gynecological dysplasia and HIV negative; Group 2, Gynecological dysplasia (H-SIL) or carcinoma in situ demonstrated by histology (vulvar, vaginal or cervical) and HIV negative; Group 3: HIV-positive (regardless of viremia or CD4 count) with or without gynecological dysplasia. General exclusion criteria are: Pregnancy; History of anal dysplasia/cancer; Status after pelvic radiotherapy; Absence of anus and anal canal. Estimated prevalences of anal dysplasia are: in group 1, 1% (0-2%); in group 2, 15% (5-27%), and in group 3, 30% (19-45%). With a 10% margin error, a sample size of 120 women per group is required to reach 90% power for detecting statistical significance (unilateral α error of 5%).

DISCUSSION: The primary endpoint is the prevalence of anal and cervical dysplasia, and description of the respective HPV genotypes in each group. The results of this study could improve the standard of screening of cervical and anal dysplasia in women through evidence of concomitant presence of HPV’s and/or dysplasia in anus or cervix to support vaccination for instance. Beginning of recruitment started in September 2016. Results should be presented in end of 2022. Preliminary analysis for first 100 patients reveals that the mean age of the population is 39.6 (± 10.9) years with mean age of first sexual intercourse of 18.5 (± 3.9) years. In this cohort, 12% are vaccinated and 38% having had anal intercourse. Overall, 43% of the studied population had cervical HR-HPV in the studied population, and 53% had normal cytology. Anal LR HPV and HR HP were found in 27.6% and 38.4% of all patients respectively. Eighty percent had normal anal cytology. Groups 1,2 and 3 had a significant difference in terms of age, gestity, parity, age of first sexual intercourse, systematic use of condom, number of cervical LR HPV and HR HPV and abnormal cervical cytologies.

TRIAL REGISTRATION: The study was approved by the institutional review board-CER-VD#2015-00200-on the 29th of June 2016 and is registered on the Swiss National Clinical Trials Portal (SNCTP), SNCTP000002567, Registered 29 June 2016, https://www.kofam.ch/en/snctp-portal/study/40742/.

PMID:36269726 | DOI:10.1371/journal.pone.0276438

PLoS One. 2022 Oct 21;17(10):e0265293. doi: 10.1371/journal.pone.0265293. eCollection 2022.

ABSTRACT

Though native to Scotland, the grey wolf (Canis lupus) was extirpated c.250 years ago as part of a global eradication drive. The global population has recently expanded, now occupying 67% of its former range. Evidence is growing that apex predators provide a range of ecological benefits, most stemming from the reduction of overgrazing by deer-something from which Scotland suffers. In this study, we build a rule-based habitat suitability model for wolves on the Scottish mainland. From existing literature, we identify the most important variables as land cover, prey density, road density and human density, and establish thresholds of suitability for each. Fuzzy membership functions are used to assign suitability values to each variable, followed by fuzzy overlay to combine all four: a novel approach to habitat suitability modelling for terrestrial mammals. Model sensitivity is tested for land cover and prey density, as these variables constitute a knowledge gap and an incomplete dataset, respectively. The Highlands and Grampian mountains emerge strongly and consistently as the most suitable areas, largely due to high negative covariance between prey density and road/human density. Sensitivity testing reveals the models are fairly robust to changes in prey density, but less robust to changes in the scoring of land cover, with the latter altering the distribution of land mainly through the 70-100% suitability range. However, in statistical significance tests, only the least and most generous versions of the model emerge as giving significantly different results. Depending on the version of the model, a contiguous area of between 10,139km2 and 18,857km2 is shown to be 80 to 100% suitable. This could be sufficient to support between 50 and 94 packs of four wolves, if the average pack range size is taken to be 200km2. We conclude that in terms of habitat availability, reintroduction should be feasible.

PMID:36269698 | DOI:10.1371/journal.pone.0265293

J Adolesc Young Adult Oncol. 2022 Oct 20. doi: 10.1089/jayao.2022.0044. Online ahead of print.

ABSTRACT

Significance: Elevated survival rates in young adult cancer survivors (YACS) are accompanied by high morbidity levels resulting in an array of unmet needs limiting full life potential. Physical activity (PA) improves physical, psychological, and social aspects of health after a cancer diagnosis. There are no standardized PA guidelines tailored to YACS. Therefore, there is a critical need to understand areas of clinical relevance/agreement on PA use and implementation in young adult (YA) survivorship care. Aim: To identify expert consensus areas on the assessment, prescription, and implementation of PA in YA survivorship care; identify areas of clinical relevance and endorsement of PA as a health optimization strategy in YA survivorship care. Methods: A four-round modified Delphi study of international multidisciplinary experts (Round I/II n = 18; Round III n = 57, Round IV n = 45) in exercise oncology, symptom management, survivorship care, youth cancer care was conducted. Qualitative content analysis, descriptive statistics (% agreement, standard deviation, mean), and inter-rater reliability (Kappa) were calculated. Results: Experts reached a consensus on clinical providers needed to assess, refer, and provide PA interventions, the need for guidelines, and essential care delivery system components to foster the integration of PA integration in YA survivorship care as a health optimization activity. Conclusions/Implications: Cancer care integration models should optimize the unique preferences, strengths, and developmental stage of YA affected by cancer. The study adds to the existing literature on multidisciplinary teams needed to provide clinical expertise and organizational support to foster PA integration into YA survivorship care.

PMID:36269579 | DOI:10.1089/jayao.2022.0044

Mol Pharm. 2022 Oct 21. doi: 10.1021/acs.molpharmaceut.2c00662. Online ahead of print.

ABSTRACT

The uptake transporter OATP1B1 (SLC01B1) is largely localized to the sinusoidal membrane of hepatocytes and is a known victim of unwanted drug-drug interactions. Computational models are useful for identifying potential substrates and/or inhibitors of clinically relevant transporters. Our goal was to generate OATP1B1 in vitro inhibition data for [³H] estrone-3-sulfate (E3S) transport in CHO cells and use it to build machine learning models to facilitate a comparison of seven different classification models (Deep learning, Adaboosted decision trees, Bernoulli naïve bayes, k-nearest neighbors (knn), random forest, support vector classifier (SVC), logistic regression (lreg), and XGBoost (xgb)] using ECFP6 fingerprints to perform 5-fold, nested cross validation. In addition, we compared models using 3D pharmacophores, simple chemical descriptors alone or plus ECFP6, as well as ECFP4 and ECFP8 fingerprints. Several machine learning algorithms (SVC, lreg, xgb, and knn) had excellent nested cross validation statistics, particularly for accuracy, AUC, and specificity. An external test set containing 207 unique compounds not in the training set demonstrated that at every threshold SVC outperformed the other algorithms based on a rank normalized score. A prospective validation test set was chosen using prediction scores from the SVC models with ECFP fingerprints and were tested in vitro with 15 of 19 compounds (84% accuracy) predicted as active (≥20% inhibition) showed inhibition. Of these compounds, six (abamectin, asiaticoside, berbamine, doramectin, mobocertinib, and umbralisib) appear to be novel inhibitors of OATP1B1 not previously reported. These validated machine learning models can now be used to make predictions for drug-drug interactions for human OATP1B1 alongside other machine learning models for important drug transporters in our MegaTrans software.

PMID:36269563 | DOI:10.1021/acs.molpharmaceut.2c00662

J Endocrinol Invest. 2022 Oct 21. doi: 10.1007/s40618-022-01935-y. Online ahead of print.

ABSTRACT

PURPOSE: Adrenal cortical adenomas (ACAs) represent one of the most common endocrine neoplasms. Recently, a genetic syndrome, characterized by tumor-suppressor ARMC5-gene mutations and causing primary macronodular bilateral adrenal hyperplasia with concomitant meningiomas of the central nervous system, has been described. Apart from this rare disorder and despite the well-known influence of steroid hormones on meningiomas, no data are available about the association between ACAs and meningiomas.

METHODS: We investigated the prevalence of ACAs in a group of patients with cerebral meningioma undergoing unenhanced chest CT scans before attending surgical treatment. Patients with meningioma were age- and sex-matched in a 1:3 ratio with hospitalized patients for COVID-19.

RESULTS: Fifty-six patients with meningioma were included and matched with 168 control patients with COVID-19. One-hundred forty-four (66.1%) were female and the median age was 63 years. Twenty ACAs were detected in the overall population (8.9% of the subjects): 10 in patients with meningioma (18%) and the remaining 10 (6%) in the control group (p = 0.007). Multivariate analysis showed that age and presence of meningioma were statistically associated with the presence of ACAs (p = 0.01, p = 0.008).

CONCLUSION: We report, for the first time, a higher prevalence of ACAs in patients with meningioma as compared to age- and sex-matched controls. Larger studies are needed to confirm our data and to clarify the characteristics of the ACAs in patients with meningioma. Whether the detection of ACAs should prompt a neuroimaging evaluation to exclude the presence of meningiomas needs also to be considered.

PMID:36269557 | DOI:10.1007/s40618-022-01935-y

Ther Innov Regul Sci. 2022 Oct 21. doi: 10.1007/s43441-022-00470-5. Online ahead of print.

ABSTRACT

BACKGROUND: Central monitoring, which typically includes the use of key risk indicators (KRIs), aims at improving the quality of clinical research by pro-actively identifying and remediating emerging issues in the conduct of a clinical trial that may have an adverse impact on patient safety and/or the reliability of trial results. However, there has to-date been a relative lack of direct quantitative evidence published supporting the claim that central monitoring actually leads to improved quality.

MATERIAL AND METHODS: Nine commonly used KRIs were analyzed for evidence of quality improvement using data retrieved from a large central monitoring platform. A total of 212 studies comprising 1676 sites with KRI signals were used in the analysis, representing central monitoring activity from 23 different sponsor organizations. Two quality improvement metrics were assessed for each KRI, one based on a statistical score (p-value) and the other based on a KRI’s observed value.

RESULTS: Both KRI quality metrics showed improvement in a vast majority of sites (82.9% for statistical score, 81.1% for observed KRI value). Additionally, the statistical score and the observed KRI values improved, respectively by 66.1% and 72.4% on average towards the study average for those sites showing improvement.

CONCLUSION: The results of this analysis provide clear quantitative evidence supporting the hypothesis that use of KRIs in central monitoring is leading to improved quality in clinical trial conduct and associated data across participating sites.

PMID:36269551 | DOI:10.1007/s43441-022-00470-5