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Nevin Manimala Statistics

Transmission dynamics and forecasts of the COVID-19 pandemic in Mexico, March-December 2020

PLoS One. 2021 Jul 21;16(7):e0254826. doi: 10.1371/journal.pone.0254826. eCollection 2021.

ABSTRACT

Mexico has experienced one of the highest COVID-19 mortality rates in the world. A delayed implementation of social distancing interventions in late March 2020 and a phased reopening of the country in June 2020 has facilitated sustained disease transmission in the region. In this study we systematically generate and compare 30-day ahead forecasts using previously validated growth models based on mortality trends from the Institute for Health Metrics and Evaluation for Mexico and Mexico City in near real-time. Moreover, we estimate reproduction numbers for SARS-CoV-2 based on the methods that rely on genomic data as well as case incidence data. Subsequently, functional data analysis techniques are utilized to analyze the shapes of COVID-19 growth rate curves at the state level to characterize the spatiotemporal transmission patterns of SARS-CoV-2. The early estimates of the reproduction number for Mexico were estimated between Rt ~1.1-1.3 from the genomic and case incidence data. Moreover, the mean estimate of Rt has fluctuated around ~1.0 from late July till end of September 2020. The spatial analysis characterizes the state-level dynamics of COVID-19 into four groups with distinct epidemic trajectories based on epidemic growth rates. Our results show that the sequential mortality forecasts from the GLM and Richards model predict a downward trend in the number of deaths for all thirteen forecast periods for Mexico and Mexico City. However, the sub-epidemic and IHME models perform better predicting a more realistic stable trajectory of COVID-19 mortality trends for the last three forecast periods (09/21-10/21, 09/28-10/27, 09/28-10/27) for Mexico and Mexico City. Our findings indicate that phenomenological models are useful tools for short-term epidemic forecasting albeit forecasts need to be interpreted with caution given the dynamic implementation and lifting of social distancing measures.

PMID:34288969 | DOI:10.1371/journal.pone.0254826

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Nevin Manimala Statistics

The trade-off between design fixation and quality: Physical objects or multiperspective pictures?

PLoS One. 2021 Jul 21;16(7):e0254933. doi: 10.1371/journal.pone.0254933. eCollection 2021.

ABSTRACT

Physical objects and their pictures are two main kinds of design stimuli of creative activity, which can improve design quality but may induce design fixation. Previous studies are focused on the case where participants face a single picture, and their design stimulus may be incomplete as compared with the participants facing objects. To fully explore the influence of physical and pictorial examples on design novices, we investigated design fixation and design quality when they were provided with multiperspective pictures having information remarkably similar to physical objects. Specifically, two novice groups individually created their own designs after observing several examples by the way of the above two presentation modes. These designs were evaluated by two evaluators in terms of similarity, originality, and completeness. Statistical analysis showed that no significant difference was found in similarity and originality between the two groups, whereas the designs of the physical group outperformed those of the pictorial group in terms of completeness. This finding indicated that the two groups showed the same degree of design fixation, as multiperspective pictures presented most of the form information of the physical object. The results suggest that when instructing design novices, it is essential to control how to present design examples at different stages of the design process.

PMID:34288942 | DOI:10.1371/journal.pone.0254933

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Nevin Manimala Statistics

Substance use behavior and its lifestyle-related risk factors in Bangladeshi high school-going adolescents: An exploratory study

PLoS One. 2021 Jul 21;16(7):e0254926. doi: 10.1371/journal.pone.0254926. eCollection 2021.

ABSTRACT

Substance abuse is a major concern worldwide and is increasing rapidly in Bangladesh. However, there are no prior studies concerning lifestyle-related factors that influence adolescents’ substance use behavior. Therefore, the present study investigated the prevalence of substance use and its associated sociodemographic and lifestyle-related risk factors among a total of 424 Bangladeshi high school-going adolescents through a structured questionnaire interview study. The survey questionnaire consisted of socio-demographics, lifestyle-related information, and substance use-related questions. For data analysis, descriptive and inferential statistics were performed using SPSS (Statistical Package for Social Science) version 22.0, and a p-value of <0.05 determined statistical significance. Results showed that 21.2%, 14.4%, and 15.1% of the participants reported smoking, using a drug, and consuming alcohol, respectively, at least once during their lifespan; whereas the current (i.e., past-month) rates were reported to be 10.4%, 2.8%, and 3.1%, respectively. Overall, the current substance use risk factors were identified as being male, not being from science academic background, having less family influence on personal life, irregular teeth brushing, being smartphone users, using a smartphone for a longer time, and being late-night sleepers. From the list of identified risk factors of substance use, those that are modifiable may be targeted to evolve a prevention program to manage this problem in Bangladeshi adolescents.

PMID:34288956 | DOI:10.1371/journal.pone.0254926

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Nevin Manimala Statistics

A power approximation for the Kenward and Roger Wald test in the linear mixed model

PLoS One. 2021 Jul 21;16(7):e0254811. doi: 10.1371/journal.pone.0254811. eCollection 2021.

ABSTRACT

We derive a noncentral [Formula: see text] power approximation for the Kenward and Roger test. We use a method of moments approach to form an approximate distribution for the Kenward and Roger scaled Wald statistic, under the alternative. The result depends on the approximate moments of the unscaled Wald statistic. Via Monte Carlo simulation, we demonstrate that the new power approximation is accurate for cluster randomized trials and longitudinal study designs. The method retains accuracy for small sample sizes, even in the presence of missing data. We illustrate the method with a power calculation for an unbalanced group-randomized trial in oral cancer prevention.

PMID:34288958 | DOI:10.1371/journal.pone.0254811

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Nevin Manimala Statistics

The effect of immediate dentin sealing with chlorhexidine pretreatment on the shear bond strength of dual-cure adhesive cement

Microsc Res Tech. 2021 Jul 19. doi: 10.1002/jemt.23878. Online ahead of print.

ABSTRACT

The purpose of this in vitro study was to evaluate the effect of immediate dentin sealing (IDS) with and without chlorhexidine (CHX) pretreatment on the shear bond strength (SBS) of dual-cure adhesive resin cement. Mid-coronal dentin surfaces were obtained from 75 human molars. They were randomly allocated into five groups in accordance to type of IDS [etch&rinse/ER (Adper Single Bond2) and universal/U adhesive systems (Single Bond Universal)] and presence of CHX application (n = 15): Group ER; Group ER + CHX; Group U; Group U + CHX; and Group C (no IDS). Dual-cure adhesive resin cements were bonded with a cylinder-shaped Teflon mold. The SBS was measured using a universal test machine. Fracture type was evaluated with stereomicroscope. The resin/dentin interfaces were examined with an environmental scanning electron microscope. Data were statistically analyzed with two-way analysis of variance and Bonferroni tests (p < .05). Regarding the IDS treatment groups with/without CHX, there were no significant differences in SBS (p > .05). Group U + CHX showed significantly higher SBS than Group C (p < .05). Regarding the presence of CHX, no significant differences in SBS were found (p > .05). The prevalent failure mode was the mixed type for most of the groups. Group C exhibited an intact and regular hybrid layer with no resin tag, whereas longer and clear resin-tag formation was visible for Group U + CHX. CHX pretreatment improved the bond strength between adhesive resin cement and dentin when IDS treatment was performed with a universal adhesive system.

PMID:34286901 | DOI:10.1002/jemt.23878

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Nevin Manimala Statistics

Cancer: Information theory to fight resistance to treatments

A major challenge in cancer therapy is the adaptive response of cancer cells to targeted therapies. Although this adaptive response is theoretically reversible, such a reversal is hampered by numerous molecular mechanisms that allow the cancer cells to adapt to the treatment. A team has used information theory, in order to objectify in vivo the molecular regulations at play in the mechanisms of the adaptive response and their modulation by a therapeutic combination.
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Nevin Manimala Statistics

Novel method predicts if COVID-19 clinical trials will fail or succeed

Researchers have modeled COVID-19 completion versus cessation in clinical trials using machine learning algorithms and ensemble learning.
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Nevin Manimala Statistics

Trends in computational molecular catalyst design

Dalton Trans. 2021 Jul 21. doi: 10.1039/d1dt01754c. Online ahead of print.

ABSTRACT

Computational methods have emerged as a powerful tool to augment traditional experimental molecular catalyst design by providing useful predictions of catalyst performance and decreasing the time needed for catalyst screening. In this perspective, we discuss three approaches for computational molecular catalyst design: (i) the reaction mechanism-based approach that calculates all relevant elementary steps, finds the rate and selectivity determining steps, and ultimately makes predictions on catalyst performance based on kinetic analysis, (ii) the descriptor-based approach where physical/chemical considerations are used to find molecular properties as predictors of catalyst performance, and (iii) the data-driven approach where statistical analysis as well as machine learning (ML) methods are used to obtain relationships between available data/features and catalyst performance. Following an introduction to these approaches, we cover their strengths and weaknesses and highlight some recent key applications. Furthermore, we present an outlook on how the currently applied approaches may evolve in the near future by addressing how recent developments in building automated computational workflows and implementing advanced ML models hold promise for reducing human workload, eliminating human bias, and speeding up computational catalyst design at the same time. Finally, we provide our viewpoint on how some of the challenges associated with the up-and-coming approaches driven by automation and ML may be resolved.

PMID:34286781 | DOI:10.1039/d1dt01754c

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Nevin Manimala Statistics

Cardiac involvement in MRI in young population after COVID-19: A single tertiary center experience

Echocardiography. 2021 Jul 19. doi: 10.1111/echo.15160. Online ahead of print.

ABSTRACT

BACKGROUND: Coronavirus 2019 (COVID-19) causes morbidity and mortality in an increasing number of people worldwide. Although it mainly affects the respiratory system, it influences all organs, including the heart. It is associated with a broad spectrum of widespread cardiovascular problems ranging from mild myocardial injury to fulminant myocarditis. We aimed to evaluate the presence and prevalence of cardiac involvement in asymptomatic or symptomatic patients after they recovered from COVID 19 infection.

METHODS: A total of 100 consecutive patients with COVID-19 proven by reverse transcription polymerase chain reaction (RT-PCR), under 40 years of age and without any known additional chronic diseases were analyzed retrospectively for cardiac magnetic resonance (CMR) results and symptoms.

RESULTS: Cardiac involvement was detected in 49 out of 100 patients on CMR imaging. In the cardiac involvement group, the number of patients with chest pain and/or dyspnea was 41 (84%), which was statistically significant (p = 0.001). Twenty-four patients (47%) in the without cardiac involvement group were asymptomatic and this was also statistically significant (p = 0.001). LV ejection fraction was statistically significantly lower in the group with cardiac involvement (61% vs 66%, p = 0.001). LV stroke volume and tricuspid annular plane systolic excursion (TAPSE) were statistically significantly lower in patients with cardiac involvement (p = 0.028 and p = 0.019, respectively).

CONCLUSION: Based on single center experience, myocardial involvement is common in symptomatic patients after COVID-19. More studies are needed for long-term side effects and clinical results in these patients.

PMID:34286876 | DOI:10.1111/echo.15160

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Nevin Manimala Statistics

Associations between financial gambling motives, gambling frequency, and level of problem gambling: A meta-analytic review

Addiction. 2021 Jul 19. doi: 10.1111/add.15642. Online ahead of print.

ABSTRACT

BACKGROUND AND AIMS: Money is central to psychological definitions of gambling, but contemporary accounts are ambiguous regarding the role of financial motives in disordered gambling. The aims of the current research were to obtain meta-analytic weighted effect sizes for zero-order associations of financial motives against gambling frequency and level of problem gambling, as well as partial associations after controlling for other motives (e.g., coping).

METHODS: A meta-analysis of the literature through February 2021 was undertaken. Studies were identified from multiple sources (e.g., database search, other researchers). PRISMA standards were followed when screening identified records and extracting relevant data. The data analytic plan was pre-registered. We included 44 cross-sectional studies that involved student, community, and clinical samples of people who gamble (sample sizes ranged from 22 to 5,666), using validated self-report measures of financial gambling motives alongside measures of either gambling frequency and/or problem gambling.

RESULTS: Financial gambling motives were positively associated with gambling frequency, r = .29, [.21, .37], N= 22,738 and level of problem gambling, r = .35, [.31, .38], N = 38,204 with moderate effect sizes. Partial associations after controlling for overlapping variance with other gambling motives were also positive (gambling frequency: β = .14, [.05, .22], N = 13,844; level of problem gambling: β = .18, [.13, .22], N = 28,146), with small-to-moderate effect sizes. Effect sizes were heterogeneous and the extent of heterogeneity was high. Analyses of the zero-order association involving gambling frequency indicated that gambling motives measure (greater for Gambling Motives Questionnaire-Financial) and sample mean age (greater for younger samples) were moderators. No other moderators were statistically significant.

CONCLUSIONS: Financial gambling motives appear to be reliably and positively associated with both gambling frequency and level of problem gambling.

PMID:34286879 | DOI:10.1111/add.15642