Category: Nevin Manimala

Eur J Dent. 2021 Dec 14. doi: 10.1055/s-0041-1735932. Online ahead of print.

ABSTRACT

OBJECTIVES: Due to time-consuming curricular and extracurricular activities, students in dentistry and medicine can profit from efficient learning strategies. One strategy could be the preparation with individually designed educational software that embed different multimedia sources. The aim of this study was to determine the efficiency of such a program compared with an e-book similar to a traditional textbook.

MATERIALS AND METHODS: Dentistry students of the Johannes Gutenberg-University of Mainz passed an entrance multiple-choice test on the topic of odontogenic tumors and were then randomized into two groups. Afterward, both groups had 14 days to study on the topic of odontogenic tumors either with a learning software or an e-book. A final exam was then taken and the two groups were compared.

STATISTICAL ANALYSIS: A least significant difference post hoc analysis comparing the group average values was performed. The level of significance was p <0.05.

RESULTS: Seventy-one students took part in the study. While students from the first and second clinical semester showed significantly better results and improvements with the e-book, an opposite effect was observed in students from the third and fifth clinical semester with significantly better results and improvements with the software.

CONCLUSION: Depending on the clinical experience and knowledge, a multimedia educational software can help students in dentistry to enhance efficiency in the preparation for exams.

PMID:34905779 | DOI:10.1055/s-0041-1735932

Menopause. 2021 Dec 12. doi: 10.1097/GME.0000000000001901. Online ahead of print.

ABSTRACT

OBJECTIVES: To examine the efficacy and acceptability of decision aids (DAs) in counseling urogynecology patients with prolapse, stress urinary incontinence, or refractory overactive bladder.

METHODS: This pilot study enrolled 33 patients into a control group that underwent usual care without a DA, followed by 33 patients into an intervention group where providers utilized a DA for counseling. Postvisit patient surveys assessed differences in treatment preference, knowledge, and in patient-physician collaboration using SURE, CollaboRATE, and Shared Decision Making (SDM) Process scales. Postvisit provider surveys assessed their perception of the usefulness and the difficulty of using a DA and visit length. Independent t tests were used for continuous variables (Knowledge and SDM Process scores) and Chi-Square for categorical variables (treatment preference, SURE, and CollaboRATE).

RESULTS: The majority of eligible patients 66/71 (93%) completed the survey. The intervention group trended toward higher knowledge scores (72% vs 60%, P = 0.06), clearer treatment preferences (85% vs 67%, P = 0.08), higher rates of top SURE scale scores (91% vs 73%, P = 0.11), and top CollaboRATE scores (75% vs 52%, P = 0.07). SDM process scores were similar across groups (3.2 vs 3.2, P = 0.96). Providers used the DA in 73% of intervention group visits and rated the visit length as “normal” in both groups (70% vs 76%, P = 0.78).

CONCLUSIONS: There were no statistically significant differences between the control group and the intervention group. The use of DAs was acceptable to providers and indicated a trend toward increased patient knowledge, treatment preference, and satisfaction. A larger study is warranted to examine the impact of DAs on decision making and patient experience.

Video Summary:http://links.lww.com/MENO/A856.

PMID:34905749 | DOI:10.1097/GME.0000000000001901

Brief Bioinform. 2021 Dec 15:bbab521. doi: 10.1093/bib/bbab521. Online ahead of print.

ABSTRACT

Proteins with intrinsically disordered regions (IDRs) are common among eukaryotes. Many IDRs interact with nucleic acids and proteins. Annotation of these interactions is supported by computational predictors, but to date, only one tool that predicts interactions with nucleic acids was released, and recent assessments demonstrate that current predictors offer modest levels of accuracy. We have developed DeepDISOBind, an innovative deep multi-task architecture that accurately predicts deoxyribonucleic acid (DNA)-, ribonucleic acid (RNA)- and protein-binding IDRs from protein sequences. DeepDISOBind relies on an information-rich sequence profile that is processed by an innovative multi-task deep neural network, where subsequent layers are gradually specialized to predict interactions with specific partner types. The common input layer links to a layer that differentiates protein- and nucleic acid-binding, which further links to layers that discriminate between DNA and RNA interactions. Empirical tests show that this multi-task design provides statistically significant gains in predictive quality across the three partner types when compared to a single-task design and a representative selection of the existing methods that cover both disorder- and structure-trained tools. Analysis of the predictions on the human proteome reveals that DeepDISOBind predictions can be encoded into protein-level propensities that accurately predict DNA- and RNA-binding proteins and protein hubs. DeepDISOBind is available at https://www.csuligroup.com/DeepDISOBind/.

PMID:34905768 | DOI:10.1093/bib/bbab521

J Am Coll Health. 2021 Dec 14:1-11. doi: 10.1080/07448481.2021.2013237. Online ahead of print.

ABSTRACT

OBJECTIVE: The objective was to examine mental health of undergraduate researchers (UGRs) during the COVID-19 pandemic.

PARTICIPANTS: We surveyed 962 UGRs who were conducting research in Spring 2020 at over 100 US universities.

METHODS: We conducted an online survey in July 2020. We analyzed data using descriptive statistics and multivariable generalized estimating equations.

RESULTS: 63% reported at least mild anxiety and 73% reported at least mild depression based on GAD-7 and PHQ-9 scores; 15.2% reported severe anxiety (score ≥ 15) and 23.4% reported severe depression (score ≥ 15). More COVID-19-related adverse event experiences were associated with more severe anxiety and depression, as were first-generation status, woman gender, and LGBQ status. Greater social support was protective, and significantly more so for men (vs. women) and continuing generation (vs. first generation) students.

CONCLUSION: Faculty have an important role in the mental health of their mentees. Additional interventions are needed to better support women and first-generation students.

Supplemental data for this article can be accessed online at.

PMID:34905697 | DOI:10.1080/07448481.2021.2013237

PLoS One. 2021 Dec 14;16(12):e0261432. doi: 10.1371/journal.pone.0261432. eCollection 2021.

ABSTRACT

INTRODUCTION: Coronavirus disease 2019 (COVID-19) is the ongoing pandemic with multitude of manifestations and association of ABO blood group in South-East Asian population needs to be explored.

METHODS: It was a retrospective study of patients with COVID-19. Blood group A, B, O, and AB were identified in every participant, irrespective of their RH type and allotted groups 1, 2,3, and 4, respectively. Correlation between blood group and lab parameters was presented as histogram distributed among the four groups. Multivariate regression and logistic regression were used for inferential statistics.

RESULTS: The cohort included 1067 patients: 521 (48.8%) participants had blood group O as the prevalent blood type. Overall, 10.6% COVID-19-related mortality was observed at our center. Mortality was 13.9% in blood group A, 9.5% in group B, 10% in group C, and 10.2% in AB blood group (p = 0.412). IL-6 was elevated in blood group A (median [IQR]: 23.6 [17.5,43.8]), Procalcitonin in blood group B (median [IQR]: 0.54 [0.3,0.7]), D-dimers and CRP in group AB (median [IQR]: 21.5 [9,34]; 24 [9,49], respectively). Regarding severity of COVID-19 disease, no statistical difference was seen between the blood groups. Alteration of the acute phase reactants was not positively associated with any specific blood type.

CONCLUSION: In conclusion, this investigation did not show significant association of blood groups with severity and of COVID-19 disease and COVID-19-associated mortality.

PMID:34905588 | DOI:10.1371/journal.pone.0261432

Prostate. 2021 Dec 14. doi: 10.1002/pros.24283. Online ahead of print.

ABSTRACT

BACKGROUND: Smaller prostates have been linked to unfavorable clinical characteristics and poor short-term outcomes following radical prostatectomy (RP). We examined the relation between prostate weight at RP and prostate cancer (PC) outcomes post-RP.

METHODS: Men in the SEARCH cohort undergoing RP between 1988 and 2017 (N = 6242) were studied for PC-specific mortality (PCSM) as the primary outcome, and for biochemical recurrence (BCR), castration-resistant PC (CRPC) and metastasis as secondary outcomes. Hazard ratios (HR) and 95% confidence intervals (CI) were determined for associations between prostate weight and outcomes using Fine-Gray competing risk regression multivariable analyses. Sensitivity analyses were also carried out following exclusion of: (i) men with extreme prostate weights (<20 g and ≥100 g); and (ii) men with elevated prostate specific antigen (PSA) levels.

RESULTS: Median values for age, pre-RP PSA and prostate weight were 63 years, 6.6 ng/ml, and 42.0 g, respectively. During a median follow-up of 7.9 years, 153 (3%) died from PC, 2103 (34%) had BCR, 203 (3%) developed CRPC, and 289 (5%) developed metastases. Prostate weight was not associated with PCSM in the main analyses (multivariable HR = 1.43; 95% CI: 0.87-2.34) or in sensitivity analyses. Prostate weight was inversely associated with BCR in the main analyses (multivariable HR = 0.70; 95%CI: 0.61-0.79) which was unchanged in sensitivity analyses. HRs for prostate weight and CRPC and metastasis were elevated but statistical significance was not attained. Similar results were observed in sensitivity analyses.

CONCLUSIONS: Inconsistent results for prostate weight and short-term vs longer-term outcomes highlight the need to better understand the complex biology leading to prostate size and the relevance of prostate size as a predictor of PC outcomes.

PMID:34905632 | DOI:10.1002/pros.24283

PLoS One. 2021 Dec 14;16(12):e0261144. doi: 10.1371/journal.pone.0261144. eCollection 2021.

ABSTRACT

This paper considers the quantile regression model with individual fixed effects for spatial panel data. Efficient minimum distance quantile regression estimators based on instrumental variable (IV) method are proposed for parameter estimation. The proposed estimator is computational fast compared with the IV-FEQR estimator proposed by Dai et al. (2020). Asymptotic properties of the proposed estimators are also established. Simulations are conducted to study the performance of the proposed method. Finally, we illustrate our methodologies using a cigarettes demand data set.

PMID:34905573 | DOI:10.1371/journal.pone.0261144

PLoS One. 2021 Dec 14;16(12):e0261092. doi: 10.1371/journal.pone.0261092. eCollection 2021.

ABSTRACT

BACKGROUND: To determine the prevalence of food allergy (FA) and factors associated with these occurrences in different populations from different regions.

MATERIALS AND METHODS: The literature search will be conducted via Pubmed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure (CNKI), Vip and Wanfang databases. Ratio rate (RR), odds ratio (OR) and 95% confidence intervals (CIs) will be adopted to evaluate prevalence and factors for FA in different populations from different regions. When the heterogeneity is small (I2<50%), the fixed effect model will be analyzed, otherwise, random effects model analysis will be performed. When the heterogeneity is large (I2≥50%), Meta regression will be used to explore the sources of inter-study heterogeneity. When the heterogeneity is large (I2≥50%) and the results are statistically significant (P<0.05), subgroup analysis will be analyzed based on age, gender, race/region, literature quality and other factors. Funnel plots will be used to reflect reporting bias and the Begg’s test will be used to test the symmetry of the funnel plots. When publication bias occurs, “cut-and-fill” method will be adopted to adjust publication bias. And sensitivity analysis will be performed for all outcome indicators.

DISCUSSION: This meta-analysis will evaluate the prevalence of FA and factors associated with these occurrences in different populations from different regions on the basis of existing evidences. Our study may be crucial to analyze similarities and differences regarding FA between different individuals from diverse regions and eventually define preventive or diagnostic approaches specifically tailored to certain populations and regions.

SYSTEMATIC REVIEW REGISTRATION: OSF registration number: 10.17605/OSF.IO/VQXU9.

PMID:34905577 | DOI:10.1371/journal.pone.0261092

PLoS One. 2021 Dec 14;16(12):e0260854. doi: 10.1371/journal.pone.0260854. eCollection 2021.

ABSTRACT

The present study is related to the analytical investigation of the magnetohydrodynamic flow of Ag – MgO/ water hybrid nanoliquid with slip conditions via an extending surface. The thermal radiation and Joule heating effects are incorporated within the existing hybrid nanofluid model. The system of higher-order partial differential equations is converted to the nonlinear system of ordinary differential equations by interpreting the similarity transformations. With the implementation of a strong analytical method called HAM, the solution of resulting higher-order ordinary differential equations is obtained. The results of the skin friction coefficient, Nusselt number, velocity profile, and temperature profile of the hybrid nanofluid for varying different flow parameters are attained in the form of graphs and tables. Some important outcomes showed that the Nusselt number and skin friction are increased with the enhancement in Eckert number, stretching parameter, heat generation parameter and radiation parameter for both slip and no-slip conditions. The thermal profile of the hybrid nanofluid is higher for suction effect but lower for Eckert number, stretching parameter, magnetic field, heat generation and radiation parameter. For both slip and no-slip conditions, the hybrid nanofluid velocity shows an upward trend for both the stretching and mixed convection parameters.

PMID:34905556 | DOI:10.1371/journal.pone.0260854

PLoS One. 2021 Dec 14;16(12):e0260995. doi: 10.1371/journal.pone.0260995. eCollection 2021.

ABSTRACT

In this work, we proposed a hybrid pointer network (HPN), an end-to-end deep reinforcement learning architecture is provided to tackle the travelling salesman problem (TSP). HPN builds upon graph pointer networks, an extension of pointer networks with an additional graph embedding layer. HPN combines the graph embedding layer with the transformer’s encoder to produce multiple embeddings for the feature context. We conducted extensive experimental work to compare HPN and Graph pointer network (GPN). For the sack of fairness, we used the same setting as proposed in GPN paper. The experimental results show that our network significantly outperforms the original graph pointer network for small and large-scale problems. For example, it reduced the cost for travelling salesman problems with 50 cities/nodes (TSP50) from 5.959 to 5.706 without utilizing 2opt. Moreover, we solved benchmark instances of variable sizes using HPN and GPN. The cost of the solutions and the testing times are compared using Linear mixed effect models. We found that our model yields statistically significant better solutions in terms of the total trip cost. We make our data, models, and code publicly available https://github.com/AhmedStohy/Hybrid-Pointer-Networks.

PMID:34905571 | DOI:10.1371/journal.pone.0260995