Tag: pubmed

Rheumatology (Oxford). 2021 Jul 21:keab581. doi: 10.1093/rheumatology/keab581. Online ahead of print.

ABSTRACT

OBJECTIVE: To evaluate key factors for Presenteeism and Activity impairment in multinational patients with Behçet’s syndrome (BS) and recurrent aphthous stomatitis (RAS).

METHODS: In this cross-sectional study, 364 BS patients from Jordan, Brazil, the United Kingdom and Turkey and 143 RAS patients from the United Kingdom and Turkey were included. Work Productivity Activity Impairment (WPAI) scale was used for Presenteeism and Activity impairment. Mediation analyses were performed to evaluate both direct and indirect causal effects.

RESULTS: Presenteeism score was higher in active patients with genital ulcers and eye involvement as well as patients with comorbidities and current smokers than the others in BS (p< 0.05). In RAS, Presenteeism score was elevated by oral ulcer activity in the direct path (p= 0.0073) and long disease duration as a mediator in the indirect path (p= 0.0191).Patients with active joint involvement had poor scores in Absenteeism, Presenteeism, Overall impairment and Activity impairment compared with those of inactive patients (p < 0.05). Using mediation analysis, the Activity impairment score was directly mediated by joint activity (p = 0.0001) and indirectly mediated through oral ulcer-related pain in BS (p = 0.0309).

CONCLUSION: In BS, Presenteeism was associated with disease activity, presence of comorbidities and being a current smoker, whereas in RAS, Presenteeism was associated with oral ulcer activity and increased length of the disease. Moreover, Activity impairment was adversely affected by joint activity and oral ulcer related pain in BS. Patients need to be empowered by using appropriate treatment strategies in their working environment and daily life.

PMID:34289015 | DOI:10.1093/rheumatology/keab581

Brain. 2021 Jul 20:awab274. doi: 10.1093/brain/awab274. Online ahead of print.

ABSTRACT

Wilson’s disease is an autosomal-recessive disorder of copper metabolism with neurological and hepatic presentations. Chelation therapy is used to ‘de-copper’ patients but neurological outcomes remain unpredictable. A range of neuroimaging abnormalities have been described and may provide insights into disease mechanisms, in addition to prognostic and monitoring biomarkers. Previous quantitative MRI analyses have focussed on specific sequences or regions of interest, often stratifying chronically-treated patients according to persisting symptoms as opposed to initial presentation. In this cross-sectional study, we performed a combination of unbiased, whole-brain analyses on T1-weighted, fluid-attenuated inversion recovery, diffusion-weighted and susceptibility-weighted imaging data from 40 prospectively-recruited patients with Wilson’s disease (age range 16-68). We compared patients with neurological (n = 23) and hepatic (n = 17) presentations to determine the neuroradiological sequelae of the initial brain injury. We also subcategorized patients according to recent neurological status, classifying those with neurological presentations or deterioration in the preceding six months as having ‘active’ disease. This allowed us to compare patients with active (n = 5) and stable (n = 35) disease and identify imaging correlates for persistent neurological deficits and copper indices in chronically-treated, stable patients. Using a combination of voxel-based morphometry and region-of-interest volumetric analyses, we demonstrate that grey matter volumes are lower in the basal ganglia, thalamus, brainstem, cerebellum, anterior insula and orbitofrontal cortex when comparing patients with neurological and hepatic presentations. In chronically-treated, stable patients, the severity of neurological deficits correlated with grey matter volumes in similar, predominantly subcortical regions. In contrast, the severity of neurological deficits did not correlate with the volume of white matter hyperintensities, calculated using an automated lesion segmentation algorithm. Using tract-based spatial statistics, increasing neurological severity in chronically-treated patients was associated with decreasing axial diffusivity in white matter tracts whereas increasing serum non-caeruloplasmin-bound (‘free’) copper and active disease were associated with distinct patterns of increasing mean, axial and radial diffusivity. Whole-brain quantitative susceptibility mapping identified increased iron deposition in the putamen, cingulate and medial frontal cortices of patients with neurological presentations relative to those with hepatic presentations and neurological severity was associated with iron deposition in widespread cortical regions in chronically-treated patients. Our data indicate that composite measures of subcortical atrophy provide useful prognostic biomarkers, whereas abnormal mean, axial and radial diffusivity are promising monitoring biomarkers. Finally, deposition of brain iron in response to copper accumulation may directly contribute to neurodegeneration in Wilson’s disease.

PMID:34289020 | DOI:10.1093/brain/awab274

PLoS One. 2021 Jul 21;16(7):e0254976. doi: 10.1371/journal.pone.0254976. eCollection 2021.

ABSTRACT

This paper identifies prognosis factors for survival in patients with acute myeloid leukemia (AML) using machine learning techniques. We have integrated machine learning with feature selection methods and have compared their performances to identify the most suitable factors in assessing the survival of AML patients. Here, six data mining algorithms including Decision Tree, Random Forrest, Logistic Regression, Naive Bayes, W-Bayes Net, and Gradient Boosted Tree (GBT) are employed for the detection model and implemented using the common data mining tool RapidMiner and open-source R package. To improve the predictive ability of our model, a set of features were selected by employing multiple feature selection methods. The accuracy of classification was obtained using 10-fold cross-validation for the various combinations of the feature selection methods and machine learning algorithms. The performance of the models was assessed by various measurement indexes including accuracy, kappa, sensitivity, specificity, positive predictive value, negative predictive value, and area under the ROC curve (AUC). Our results showed that GBT with an accuracy of 85.17%, AUC of 0.930, and the feature selection via the Relief algorithm has the best performance in predicting the survival rate of AML patients.

PMID:34288963 | DOI:10.1371/journal.pone.0254976

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

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

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

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

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

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

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