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Nevin Manimala Statistics

Using Google Trends to Identify Seasonal Variation in Foot and Ankle Pathology

J Am Podiatr Med Assoc. 2021 Jul 1;111(4):Article_18. doi: 10.7547/20-054.

ABSTRACT

BACKGROUND: Google Trends proves to be a novel tool to ascertain the level of public interest in pathology and treatments. From anticipating nascent epidemics with data-driven prevention campaigns to identifying interest in cosmetic or bariatric surgery, Google Trends provides physicians real-time insight into the latest consumer trends.

METHODS: We used Google Trends to identify temporal trends and variation in the search volume index of four groups of keywords that assessed practitioner-nomenclature inquiries, in addition to podiatric-specific searches for pain, traumatic injury, and common podiatric pathology over a 10-year period. The Mann-Kendall trend test was used to determine a trend in the series, and the Wilcoxon signed-rank test was used to determine whether there was a significant difference between summer and winter season inquiries. Significance was set at P ≤ .05.

RESULTS: The terms “podiatrist” and “foot doctor” experienced increasing Search Volume Index (SVI) and seasonal variation, whereas the terms “foot surgeon” and “podiatric surgeon” experienced no such increase. “Foot pain,” “heel pain,” “toe pain,” and “ankle pain” experienced a significant increase in SVI, with “foot pain” maintaining the highest SVI at all times. Similar results were seen with the terms “foot fractures,” “bunion,” “ingrown toenail,” and “heel spur.” These terms all experienced statistically significant increasing trends; moreover, the SVI was significantly higher in the summer than in the winter for each of these terms.

CONCLUSIONS: The results of this study show the utility in illustrating seasonal variation in Internet interest of pathologies today’s podiatrist commonly encounters. By identifying the popularity and seasonal variation of practitioner- and pathology-specific search inquiries, resources can be allocated to effectively address current public inquiries. With this knowledge, providers can learn what podiatric-specific interests are trending in their local communities and market their practice accordingly throughout the year.

PMID:34478531 | DOI:10.7547/20-054

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Nevin Manimala Statistics

PREVALENCE OF BLASTOCYSTIS SUBTYPES IN HEALTHY VOLUNTEERS IN NORTHEASTERN POLAND

J Parasitol. 2021 Sep 1;107(5):684-688. doi: 10.1645/20-170.

ABSTRACT

Blastocystis is a common enteric protist that is linked to intestinal and extra-intestinal diseases. At least 24 subtypes (STs) have been described, with the main colonization of ST1-ST4 in humans. In our attempt to determine the distribution of Blastocystis STs in Olsztyn and surroundings in northeastern Poland, 319 stool samples from volunteers were subjected to copro-ELISA and PCR testing. Positive findings were identified in 77, 48, and 46 of the samples via copro-ELISA, PCR, and sequencing, respectively. Blastocystis colonization was not associated with gender or dwelling place but was statistically higher in people age 60-69 yr (32.6%). Five STs (ST1-ST4, ST7) were identified, in which ST3 (37%) was most prevalent, followed by ST2 (19.6%), ST1 (17.4%), ST4 (13%), and ST7 (8.7%). The current study revealed a similar rate of microorganism colonization in Polish volunteers compared to other developed countries, without significant differences in gender and dwelling place. Significant statistical differences were found in different age groups, where Blastocystis was highly detected in elderly people. In the current study, PCR was the most plausible method based on the sequencing results.

PMID:34478522 | DOI:10.1645/20-170

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Nevin Manimala Statistics

Healthcare Navigation of Black and White Adolescents Following Sport-Related Concussion: A Path Towards Achieving Health Equity

J Athl Train. 2021 Sep 3. doi: 10.4085/1062-6050-0330.21. Online ahead of print.

ABSTRACT

CONTEXT: Care-seeking behaviors for sport-related concussion (SRC) are not consistent across demographic subgroups. These differences may not only stem from health inequities but can further perpetuate disparities in care for SRCs.

OBJECTIVE: To determine whether racial differences exist in the care pathway from injury to SRC clinic within adolescent athletes.

DESIGN: Retrospective cohort Setting: Regional SRC center Participants: Of 582 total athletes, 486 (83.5%) White and 96 (16.5%) Black adolescent athletes were diagnosed with SRC and evaluated within 3 months at the SRC clinic.

MAIN OUTCOME MEASURES: Race was the defined exposure, dichotomized as Black or White. The four primary outcomes included: 1)location of first health system contact, 2)time from injury to first health system contact 3) time to in-person SRC clinic visit, and 4) whether the athlete established care (>1 visit), was released immediately to an athletic trainer, or lost to follow-up.

RESULTS: Black and White athletes mostly presented directly to SRC clinic (61.5% vs 62.3%) at a median[interquartile range] of 3[1,5] vs 4[1,8] days respectively (p=0.821). Similar proportions of Black and White athletes also first presented to the ED (30.2% vs 27.2%) at a median of 0[0,1] vs 0[0,1] days (p=0.941). Black athletes more frequently had care transferred to their athletic trainer (39.6% vs 29.6%) and less frequently established care (56.3% vs 64.0%), however these differences were not statistically significant (p=0.138). Lost to follow-up was uncommon among Black and White athletes alike (4.2% vs 6.4%).

CONCLUSIONS: This study demonstrated that within an established SRC referral network and multidisciplinary clinic, there were no observed racial disparities in how athletes were initially managed and/or ultimately presented to SRC clinic despite racial differences in school type and insurance coverage. SRC center assimilation and affiliation with school systems may be helpful in improving access and providing equitable care across diverse patient demographics.

PMID:34478524 | DOI:10.4085/1062-6050-0330.21

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Nevin Manimala Statistics

FRETraj: Integrating single-molecule spectroscopy with molecular dynamics

Bioinformatics. 2021 Sep 3:btab615. doi: 10.1093/bioinformatics/btab615. Online ahead of print.

ABSTRACT

SUMMARY: Quantitative interpretation of single-molecule FRET experiments requires a model of the dye dynamics to link experimental energy transfer efficiencies to distances between atom positions. We have developed FRETraj, a Python module to predict FRET distributions based on accessible-contact volumes (ACV) and simulated photon statistics. FRETraj helps to identify optimal fluorophore positions on a biomolecule of interest by rapidly evaluating donor-acceptor distances. FRETraj is scalable and fully integrated into PyMOL and the Jupyter ecosystem. Here we describe the conformational dynamics of a DNA hairpin by computing multiple ACVs along a molecular dynamics trajectory and compare the predicted FRET distribution with single-molecule experiments. FRET-assisted modeling will accelerate the analysis of structural ensembles in particular dynamic, non-coding RNAs and transient protein-nucleic acid complexes.

AVAILABILITY: FRETraj is implemented as a cross-platform Python package available under the GPL-3.0 on Github (https://github.com/RNA-FRETools/fretraj) and is documented at https://RNA-FRETools.github.io/fretraj.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:34478493 | DOI:10.1093/bioinformatics/btab615

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Nevin Manimala Statistics

Peptipedia: a user-friendly web application and a comprehensive database for peptide research supported by Machine Learning approach

Database (Oxford). 2021 Sep 3;2021:baab055. doi: 10.1093/database/baab055.

ABSTRACT

Peptides have attracted attention during the last decades due to their extraordinary therapeutic properties. Different computational tools have been developed to take advantage of existing information, compiling knowledge and making available the information for common users. Nevertheless, most related tools available are not user-friendly, present redundant information, do not clearly display the data, and usually are specific for particular biological activities, not existing so far, an integrated database with consolidated information to help research peptide sequences. To solve these necessities, we developed Peptipedia, a user-friendly web application and comprehensive database to search, characterize and analyse peptide sequences. Our tool integrates the information from 30 previously reported databases with a total of 92 055 amino acid sequences, making it the biggest repository of peptides with recorded activities to date. Furthermore, we make available a variety of bioinformatics services and statistical modules to increase our tool’s usability. Moreover, we incorporated a robust assembled binary classification system to predict putative biological activities for peptide sequences. Our tools’ significant differences with other existing alternatives become a substantial contribution for developing biotechnological and bioengineering applications for peptides. Peptipedia is available for non-commercial use as an open-access software, licensed under the GNU General Public License, version GPL 3.0. The web platform is publicly available at peptipedia.cl. Database URL: Both the source code and sample data sets are available in the GitHub repository https://github.com/ProteinEngineering-PESB2/peptipedia.

PMID:34478499 | DOI:10.1093/database/baab055

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Nevin Manimala Statistics

FORUM: Building a Knowledge Graph from public databases and scientific literature to extract associations between chemicals and diseases

Bioinformatics. 2021 Sep 3:btab627. doi: 10.1093/bioinformatics/btab627. Online ahead of print.

ABSTRACT

MOTIVATION: Metabolomics studies aim at reporting a metabolic signature (list of metabolites) related to a particular experimental condition. These signatures are instrumental in the identification of biomarkers or classification of individuals, however their biological and physiological interpretation remains a challenge. To support this task, we introduce FORUM: a Knowledge Graph (KG) providing a semantic representation of relations between chemicals and biomedical concepts, built from a federation of life science databases and scientific literature repositories.

RESULTS: The use of a Semantic Web framework on biological data allows us to apply ontological based reasoning to infer new relations between entities. We show that these new relations provide different levels of abstraction and could open the path to new hypotheses. We estimate the statistical relevance of each extracted relation, explicit or inferred, using an enrichment analysis, and instantiate them as new knowledge in the KG to support results interpretation/further inquiries.

AVAILABILITY: A web interface to browse and download the extracted relations, as well as a SPARQL endpoint to directly probe the whole FORUM knowledge graph, are available at https://forum-webapp.semantic-metabolomics.fr. The code needed to reproduce the triplestore is available at https://github.com/eMetaboHUB/Forum-DiseasesChem.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:34478489 | DOI:10.1093/bioinformatics/btab627

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Nevin Manimala Statistics

Querying multiple sets of p-values through composed hypothesis testing

Bioinformatics. 2021 Sep 3:btab592. doi: 10.1093/bioinformatics/btab592. Online ahead of print.

ABSTRACT

MOTIVATION: Combining the results of different experiments to exhibit complex patterns or to improve statistical power is a typical aim of data integration. The starting point of the statistical analysis often comes as sets of p-values resulting from previous analyses, that need to be combined in a flexible way to explore complex hypotheses, while guaranteeing a low proportion of false discoveries.

RESULTS: We introduce the generic concept of composed hypothesis, which corresponds to an arbitrary complex combination of simple hypotheses. We rephrase the problem of testing a composed hypothesis as a classification task, and show that finding items for which the composed null hypothesis is rejected boils down to fitting a mixture model and classify the items according to their posterior probabilities. We show that inference can be efficiently performed and provide a thorough classification rule to control for type I error. The performance and the usefulness of the approach are illustrated on simulations and on two different applications. The method is scalable, does not require any parameter tuning, and provided valuable biological insight on the considered application cases.

AVAILABILITY: The QCH methodology is implemented in the qch R package hosted on CRAN.

PMID:34478490 | DOI:10.1093/bioinformatics/btab592

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Nevin Manimala Statistics

Spray mist reduction by means of a high-volume evacuation system-Results of an experimental study

PLoS One. 2021 Sep 3;16(9):e0257137. doi: 10.1371/journal.pone.0257137. eCollection 2021.

ABSTRACT

OBJECTIVES: High-speed tooth preparation requires effective cooling to avoid thermal damage, which generates spray mist, which is a mixture of an aerosol, droplets and particles of different sizes. The aim of this experimental study was to analyze the efficacy of spray mist reduction with an intraoral high-volume evacuation system (HVE) during simulated high-speed tooth preparation for suboptimal versus optimal suction positions of 16 mm sized cannulas and different flow rates of the HVE.

MATERIAL AND METHODS: In a manikin head, the upper first premolar was prepared with a dental turbine, and generated particles of 5-50 microns were analyzed fifty millimeters above the mouth opening with the shadow imaging technique (frame: 6.6×5.3×1.1 mm). This setup was chosen to generate a reproducible spray mist in a vertical direction towards an imaginary operator head (worst case scenario). The flow rate (FR) of the HVE was categorized into five levels (≤120 l/min up to 330 l/min). The number of particles per second (NP; p/s) was counted, and the mass volume flow of particles per second (MVF; μg/s*cm3) was calculated for 10 sec. Statistical tests were nonparametric and two-sided (p≤0.05).

RESULTS: With increasing flow rate, the NP/MVF values decreased significantly (eta: 0.671/0.678; p≤0.001). Using a suboptimally positioned cannula with an FR≤160 l/min, significantly higher NP values (mean±SD) of 731.67±54.24 p/s (p≤0.019) and an MVF of 3.72±0.42 μg/s*cm3 (p≤0.010) were measured compared to those of the optimal cannula position and FR≥300 l/min (NP/MVF: 0/0). No significant difference in NP and MVF was measurable between FR≥250 l/min and FR>300 l/min (p = 0.652, p = 0.664).

CONCLUSION: Within the limitations of the current experimental study, intraoral high-flow rate suction with ≥300 l/min with an HVE effectively reduced 5-50 μm sized particles of the spray mist induced by high-speed tooth preparation with a dental turbine.

PMID:34478480 | DOI:10.1371/journal.pone.0257137

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Nevin Manimala Statistics

Health care workers intention to accept COVID-19 vaccine and associated factors in southwestern Ethiopia, 2021

PLoS One. 2021 Sep 3;16(9):e0257109. doi: 10.1371/journal.pone.0257109. eCollection 2021.

ABSTRACT

INTRODUCTION: Health care workers are the most affected part of the world population due to the COVID-19 pandemic. Countries prioritize vaccinating health workers against COVID-19 because of their susceptibility to the virus. However, the acceptability of the vaccine varies across populations. Thus, this study aimed to determine the health care worker’s intentions to accept the COVID-19 vaccine and its associated factors in southwestern Ethiopia, 2021.

METHODS: A facility-based cross-sectional study was conducted among health care workers in public hospitals in southwestern Ethiopia from March 15 to 28, 2021. A simple random sampling method was used to select 405 participants from each hospital. Data were collected using self-administered questionnaires. Descriptive statistics, such as frequency and percentage, were calculated. Multivariable logistic regression was also performed to identify factors associated with health care worker’s intention to accept the COVID-19 vaccine. Statistically significant variables were selected based on p-values (<0.05) and the adjusted odds ratio was used to describe the strength of association with 95% confidence intervals.

RESULT: Among the respondents, 48.4% [95% CI: 38.6, 58.2] of health care workers intended to accept COVID-19. Intention to accept COVID-19 vaccination was significantly associated with physicians (AOR = 9.27, 95% CI: 1.27-27.32), professionals with a history of chronic illness (AOR = 4.07, 95% CI: 2.02-8.21), perceived degree of risk of COVID-19 infection (AOR = 4.63, 95% CI: 1.26-16.98), positive attitude toward COVID-19 prevention (AOR = 6.08, 95% CI: 3.39-10.91) and good preventive practices (AOR = 2.83, 95% CI: 1.58-5.08).

CONCLUSION: In this study, the intention of health care workers to accept the COVID-19 vaccine was low. Professional types, history of chronic illness, perceived degree of risk to COVID-19 infection, attitude toward COVID-19 and preventive practices were found to be factors for intention to accept COVID-19 vaccine in professionals. It is important to consider professional types, history of chronic illness, perceived degree of risk to COVID-19, attitude of professionals and preventive behaviors to improve the intention of professionals’ vaccine acceptance.

PMID:34478470 | DOI:10.1371/journal.pone.0257109

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Nevin Manimala Statistics

[68Ga]DOTA-TATE PET for the detection of early transplant rejection in a heterotopic allograft heart transplantation model of the rat. A pilot study

Q J Nucl Med Mol Imaging. 2021 Sep 3. doi: 10.23736/S1824-4785.21.03387-2. Online ahead of print.

ABSTRACT

BACKGROUND: The most important cause of heart transplant loss is early acute allograft rejection, caused by the infiltration of lymphocytes, development of edema and myocardial necrosis. It has been propagated that [68Ga]DOTA-TATE PET might be suitable to quantify the presence of SSTR over-expressing lymphocytes. With heterotopic allogenic heart transplant models in the rat readily available, we aimed to investigate, if monitoring and quantification of acute allograft rejection after heterotopic allogenic heart transplantation was feasible by non-invasive serial [68Ga]DOTA-TATE PET.

METHODS: 17 Lewis rats (9 for serial PET imaging, 8 for histological correlation) received allogenic heterotopic heart transplants from 17 Brown-Norway rats. On days 4, 6 and 7 a [68Ga]DOTA-TATE PET scan was performed.

RESULTS: Imaging of acute transplant rejection until 7 days after allogenic heart transplantation in the rat is feasible. Heterotopic allografts showed significantly increased tracer uptake on day 4 until day 7 after transplantation, reflecting the process of histologically detected myocardial lymphocytic infiltration. Both the area of infarction and the amount of necrosis increased over the course of 7 days, with necrosis reaching statistical significance.

CONCLUSIONS: We purport that the detected PET signal is primarily a specific marker of lymphocyte infiltration and only to a lesser extent an unspecific marker of infarction and necrosis. Thus, [68Ga]DOTA-TATE PET might be a suitable tool for serial imaging and quantification of lymphocyte infiltration as a direct mediator of acute allograft rejection at an early stage after heart transplantation.

PMID:34477347 | DOI:10.23736/S1824-4785.21.03387-2