Tag: pubmed

J Med Virol. 2021 Jul 21. doi: 10.1002/jmv.27218. Online ahead of print.

ABSTRACT

AIM: Both SARS-COV-2 and influenza viruses cause similar clinical presentations. It is essential to assess severely ill patients presenting with a viral syndrome for diagnostic and prognostic purposes. We aimed to compare clinical and biochemical features between pneumonia patients with COVID-19 and H1N1 METHOD: Sixty patients diagnosed with COVID-19 pneumonia and 61 patients diagnosed with influenza pneumonia hospitalized between October 2020- January 2021 and October 2017- December 2019 respectively. All the clinical data and laboratory results, Chest Computed Tomography(CT) scans, intensive care unit (ICU) admission, invasive mechanical ventilation (IMV), and outcomes were retrospectively evaluated.

RESULTS: The median age was 65 (range 32-96) years for patients with a COVID-19 diagnosis and 58 (range 18-83) years for patients with influenza (p= 0,002). Comorbidity index was significantly higher in COVID-19 patients. (p=0,010). DM and HT were statistically significantly more common in COVID-19 patients. (p:0,019, p: 0,008 respectively). Distribution of severe disease and mortality was not significantly different among COVID-19 patients than influenza patients.(p:0,096, p= 0,049).). In comparison to inflammation markers; CRP levels were significantly higher in influenza patients than COVID-19 patients. (p= 0,033). The presence of sputum was predictive for influenza (OR 0,342[95% CI, 2.1,130-0,899]). CRP and platelet were also predictive for COVID-19 (OR 4.764 [95% CI, 1,003-1,012] and OR 0,991 [95% CI 0,984-0,998] respectively.

CONCLUSION: We conclude that sputum symptom by itself much more detected in influenza patients. Besides that lower CRP and higher PLT count would be discriminative for COVID-19. This article is protected by copyright. All rights reserved.

PMID:34289142 | DOI:10.1002/jmv.27218

Cancer. 2021 Jul 21. doi: 10.1002/cncr.33582. Online ahead of print.

ABSTRACT

BACKGROUND: US population-based cancer registries can be used for surveillance of human papillomavirus (HPV) types found in HPV-associated cancers. Using this framework, HPV prevalence among high-grade cervical precancers and invasive cervical cancers were compared before and after HPV vaccine availability.

METHODS: Archived tissue from 2 studies of cervical precancers and invasive cervical cancers diagnosed from 1993-2005 (prevaccine) were identified from 7 central cancer registries in Florida; Hawaii; Iowa; Kentucky; Louisiana; Los Angeles County, California; and Michigan; from 2014 through 2015 (postvaccine) cases were identified from 3 registries in Iowa, Kentucky, and Louisiana. HPV testing was performed using L1 consensus polymerase chain reaction analysis. HPV-type-specific prevalence was examined grouped by hierarchical attribution to vaccine types: HPV 16, 18, HPV 31, 33, 45, 52, 58, other oncogenic HPV types, and other types/HPV negative. Generalized logit models were used to compare HPV prevalence in the prevaccine study to the postvaccine study by patient age, adjusting for sampling factors.

RESULTS: A total of 676 precancers (328 prevaccine and 348 postvaccine) and 1140 invasive cervical cancers (777 prevaccine and 363 postvaccine) were typed. No differences were observed in HPV-type prevalence by patient age between the 2 studies among precancers or invasive cancers.

CONCLUSIONS: The lack of reduction in vaccine-type prevalence between the 2 studies is likely explained by the low number of cases and low HPV vaccination coverage among women in the postvaccine study. Monitoring HPV-type prevalence through population-based strategies will continue to be important in evaluating the impact of the HPV vaccine.

PMID:34289090 | DOI:10.1002/cncr.33582

Cancer. 2021 Jul 21. doi: 10.1002/cncr.33810. Online ahead of print.

ABSTRACT

BACKGROUND: It is critical patients understand the terms used to describe oncology treatments; however, even basic chemotherapy terminology can be misunderstood. Rural communities tend to have especially low levels of health literacy compared with nonrural communities. To address low health literacy in rural communities, this study tested rural participants’ understanding of previously developed educational chemotherapy videos that were designed for an underserved urban population. Participants were also asked for feedback to determine if the videos could be improved.

METHODS: Fifty English-speaking patients who reside in counties classified as rural according to the Rural-Urban Continuum Code designations (RUCC 4-9) participated in the study. Participants were asked to define 6 chemotherapy terms before and after viewing a short, animated video explaining the term in English. Rates of correct and incorrect definitions provided by participants were also compared with previously published results from an urban cohort.

RESULTS: All participants had statistically significantly higher rates of correct definitions for all 6 terms following the video intervention. Palliative chemotherapy understanding improved the most (10% correct prevideo and 76% postvideo intervention). For each video, the majority of participants (77%-92%) suggested no changes to the videos.

CONCLUSION: Given the prevalence of low health literacy in rural communities, it is important to have effective educational interventions to improve the understanding of basic oncology-treatment terminology. This study found that short, educational videos, originally designed for an underserved urban population, can significantly improve understanding of commonly misunderstood chemotherapy terminology in a rural setting as well.

LAY SUMMARY: Chemotherapy terminology can be confusing to patients. Understanding can be especially difficult in areas with low health literacy, such as underserved urban and rural communities. To address this concern, previously developed short, animated videos describing basic chemotherapy terminology were found to improve patient understanding in an underserved urban setting. In this study, the videos were tested in a rural population and their effectiveness was established. Participants in the rural setting were significantly more likely to correctly define all 6 tested terms after watching the videos. Educational tools for high-need populations are essential to ensure patients can understand the treatment they receive.

PMID:34289098 | DOI:10.1002/cncr.33810

Cereb Cortex. 2021 Jul 21:bhab131. doi: 10.1093/cercor/bhab131. Online ahead of print.

ABSTRACT

We aimed to identify symptom-related neuroimaging biomarkers for patients with dysgenesis of the corpus callosum (dCC) by summarizing neurological symptoms reported in clinical evaluations and correlating them with retrospectively collected structural/diffusion brain magnetic resonance imaging (MRI) measures from 39 patients/controls (mean age 8.08 ± 3.98). Most symptoms/disorders studied were associated with CC abnormalities. Total brain (TB) volume was related to language, cognition, muscle tone, and metabolic/endocrine abnormalities. Although white matter (WM) volume was not related to symptoms studied, gray matter (GM) volume was related to cognitive, behavioral, and metabolic/endocrine disorders. Right hemisphere (RH) cortical thickness (CT) was linked to language abnormalities, while left hemisphere (LH) CT was linked to epilepsy. While RH gyrification index (GI) was not related to any symptoms studied, LH GI was uniquely related to cognitive disorders. Between patients and controls, GM volume and LH/RH CT were significantly greater in dCC patients, while WM volume and LH/RH GI were significantly greater in controls. TB volume and diffusion indices for tissue microstructures did not show differences between the groups. In summary, our brain MRI-based measures successfully revealed differential links to many symptoms. Specifically, LH GI abnormality can be a predictor for dCC patients, which is uniquely associated with the patients’ symptom. In addition, patients with CC abnormalities had normal TB volume and overall tissue microstructures, with potentially deteriorated mechanisms to expand/fold the brain, indicated by GI.

PMID:34289021 | DOI:10.1093/cercor/bhab131

Genome Biol Evol. 2021 Jul 20:evab167. doi: 10.1093/gbe/evab167. Online ahead of print.

ABSTRACT

Tests based on the dN/dS statistic are used to identify positive selection of non-synonymous polymorphisms. Using these tests on alignments of all orthologues from related species can provide insights into which gene categories have been most frequently positively selected. However, longer alignments have more power to detect positive selection, creating a detection bias that could create misleading results from functional enrichment tests. Most studies of positive selection in plant pathogens focus on genes with specific virulence functions, with little emphasis on broader molecular processes. Furthermore, no studies in plant pathogens have accounted for detection bias due to alignment length when performing functional enrichment tests. To address these research gaps, we analyse 12 genomes of the phytopathogenic fungal genus Botrytis, including two sequenced in this study. To establish a temporal context, we estimated fossil-calibrated divergence times for the genus. We find that Botrytis likely originated 16-18 million years ago in the Miocene and underwent continuous radiation ending in the Pliocene. An untargeted scan of Botrytis single copy orthologues for positive selection with three different statistical tests uncovered evidence for positive selection among proteases, signalling proteins, CAZymes and secreted proteins. There was also a strong over-representation of transcription factors among positively selected genes. This over-representation was still apparent after two complementary controls for detection bias due to sequence length. Positively selected sites were depleted within DNA binding domains, suggesting changes in transcriptional responses to internal and external cues or protein-protein interactions have undergone positive selection more frequently than changes in promoter fidelity.

PMID:34289036 | DOI:10.1093/gbe/evab167

Syst Biol. 2021 Jul 21:syab060. doi: 10.1093/sysbio/syab060. Online ahead of print.

ABSTRACT

Whole genome comparisons based on Average Nucleotide Identities (ANI) and the Genome-to-genome distance calculator have risen to prominence in rapidly classifying prokaryotic taxa using whole genome sequences. Some implementations have even been proposed as a new standard in species classification and have become a common technique for papers describing newly sequenced genomes. However, attempts to apply whole genome divergence data to delineation of higher taxonomic units and to phylogenetic inference have had difficulty matching those produced by more complex phylogenetic methods. We present a novel method for generating statistically supported phylogenies of archaeal and bacterial groups using a combined ANI and alignment fraction-based metric. For the test cases to which we applied the developed approach we obtained results comparable with other methodologies up to at least the family-level. The developed method uses non-parametric bootstrapping to gauge support for inferred groups. This method offers the opportunity to make use of whole-genome comparison data, that are already being generated, to quickly produce phylogenies including support for inferred groups. Additionally, the developed ANI methodology can assist classification of higher taxonomic groups.

PMID:34289044 | DOI:10.1093/sysbio/syab060

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