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Nevin Manimala Statistics

Bayesian interaction selection model for multi-modal neuroimaging data analysis

Biometrics. 2022 Feb 27. doi: 10.1111/biom.13648. Online ahead of print.

ABSTRACT

Multi-modality or multi-construct data arise increasingly in functional neuroimaging studies to characterize brain activity under different cognitive states. Relying on those high-resolution imaging collections, it is of great interest to identify predictive imaging markers and inter-modality interactions with respect to behavior outcomes. Currently, most of the existing variable selection models do not consider predictive effects from interactions, and the desired higher-order terms can only be included in the predictive mechanism following a two-step procedure, suffering from potential mis-specification. In this paper, we propose a unified Bayesian prior model to simultaneously identify main effect features and inter-modality interactions within the same inference platform in the presence of high dimensional data. To accommodate the brain topological information and correlation between modalities, our prior is designed by compiling the intermediate selection status of sequential partitions in light of the data structure and brain anatomical architecture, so that we can improve posterior inference and enhance biological plausibility. Through extensive simulations, we show the superiority of our approach in main and interaction effects selection, and prediction under multi-modality data. Applying the method to the Adolescent Brain Cognitive Development (ABCD) study, we characterize the brain functional underpinnings with respect to general cognitive ability under different memory load conditions. This article is protected by copyright. All rights reserved.

PMID:35220581 | DOI:10.1111/biom.13648

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Nevin Manimala Statistics

Multi-source single-cell data integration by MAW barycenter for gaussian mixture models

Biometrics. 2022 Feb 27. doi: 10.1111/biom.13630. Online ahead of print.

ABSTRACT

One key challenge encountered in single-cell-data clustering is to combine clustering results of datasets acquired from multiple sources. We propose to represent the clustering result of each dataset by a Gaussian mixture model (GMM) and produce an integrated result based on the notion of Wasserstein barycenter. However, the precise barycenter of GMMs, a distribution on the same sample space, is computationally infeasible to solve. Importantly, the barycenter of GMMs may not be a GMM containing a reasonable number of components. We thus propose to use the Minimized Aggregated Wasserstein (MAW) distance to approximate the Wasserstein metric and develop a new algorithm for computing the barycenter of GMMs under MAW. Recent theoretical advances further justify using the MAW distance as an approximation for the Wasserstein metric between GMMs. We also prove that the MAW barycenter of GMMs has the same expectation as the Wasserstein barycenter. Our proposed algorithm for clustering integration scales well with the data dimension and the number of mixture components, with complexity independent of data size. We demonstrate that the new method achieves better clustering results on several single-cell RNA-seq datasets than some other popular methods. This article is protected by copyright. All rights reserved.

PMID:35220585 | DOI:10.1111/biom.13630

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Nevin Manimala Statistics

Mucormycosis: risk factors, diagnosis, treatments, and challenges during COVID-19 pandemic

Folia Microbiol (Praha). 2022 Feb 26. doi: 10.1007/s12223-021-00934-5. Online ahead of print.

ABSTRACT

Mucormycosis is a deadly opportunistic disease caused by a group of fungus named mucormycetes. Fungal spores are normally present in the environment and the immune system of the body prevents them from causing disease in a healthy immunocompetent individual. But when the defense mechanism of the body is compromised such as in the patients of diabetes mellites, neustropenia, organ transplantation recipients, and other immune-compromised states, these fungal spores invade our defense mechanism easily causing a severe systemic infection with approximately 45-80% of case fatality. In the present scenario, during the COVID-19 pandemic, patients are on immunosuppressive drugs, glucocorticoids, thus are at high risk of mucormycosis. Patients with diabetes mellitus are further getting a high chance of infection. Usually, the spores gain entry through our respiratory tract affecting the lungs and paranasal sinuses. Besides, they can also enter through damage into the skin or through the gastrointestinal route. This review article presents the current statistics, the causes of this infection in the human body, and its diagnosis with available recent therapies through recent databases collected from several clinics and agencies. The diagnosis and identification of the infection were made possible through various latest medical techniques such as computed tomography scans, direct microscopic observations, MALDI-TOF mass spectrometry, serology, molecular assay, and histopathology. Mucormycosis is so uncommon, no randomized controlled treatment studies have been conducted. The newer triazoles, posaconazole (POSA) and isavuconazole (ISAV) (the active component of the prodrug isavuconazonium sulfate) may be beneficial in patients who are refractory to or intolerant of Liposomal Amphotericin B. but due to lack of early diagnosis and aggressive surgical debridement or excision, the mortality rate remains high. In the course of COVID-19 treatments, there must be more vigilance and alertness are required from clinicians to evaluate these invasive fungal infections.

PMID:35220559 | DOI:10.1007/s12223-021-00934-5

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Nevin Manimala Statistics

Sexual Dimorphism in Telomere Length in Childhood Autism

J Autism Dev Disord. 2022 Feb 27. doi: 10.1007/s10803-022-05486-2. Online ahead of print.

ABSTRACT

Autism spectrum disorders (ASD) are strikingly more prevalent in males, but the molecular mechanisms responsible for ASD sex-differential risk are poorly understood. Abnormally shorter telomeres have been associated with autism. Examination of relative telomere lengths (RTL) among non-syndromic male (N = 14) and female (N = 10) children with autism revealed that only autistic male children had significantly shorter RTL than typically-developing controls (N = 24) and paired siblings (N = 10). While average RTL of autistic girls did not differ significantly from controls, it was substantially longer than autistic boys. Our findings indicate a sexually-dimorphic pattern of RTL in childhood autism and could have important implications for RTL as a potential biomarker and the role/s of telomeres in the molecular mechanisms responsible for ASD sex-biased prevalence and etiology.

PMID:35220523 | DOI:10.1007/s10803-022-05486-2

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Nevin Manimala Statistics

Ultrafast pulse wave velocity and ensemble learning to predict atherosclerosis risk

Int J Cardiovasc Imaging. 2022 Feb 27. doi: 10.1007/s10554-022-02574-3. Online ahead of print.

ABSTRACT

Pulse wave velocity (PWV) can evaluate potential atherosclerosis (AS) and ultrafast pulse wave velocity (ufPWV) is a new technique to accurately assess PWV. However, few studies have examined the predictive value of ufPWV for AS risk. We aimed to establish a classification model for AS risk diagnosis based on ufPWV, so that AS can be diagnosed and prevented in advance. We collected imaging data, as well as clinical and laboratory data. A total of 613 patients with 20 attributes were admitted in this study. There were 392 patients with hyperlipidemia (AS risk group) and 221 healthy adults as the control group. In order to build AS risk prediction models, we considered decision tree, five different ensemble learning (EL) models [random forest (RF), adaptive boosting (AdaBoost), gradient boosting decision tree (GBDT), extreme gradient boosting (XGBoost) and light gradient boosting machine (LGBM)] and two different feature selection methods [statistical analysis and RF]. Accuracy and the area under the ROC curve (AUC) were used as the main criterion for model evaluation. In the prediction of AS risk with statistical analysis as the feature selection method, the performances of XGBoost (accuracy: 0.851; AUC: 0.884) and RF (accuracy: 0.844; AUC: 0.889) were better than other models. Besides, in the prediction of AS risk with RF as the feature selection method, the performances of LGBM (accuracy: 0.870; AUC: 0.903) and XGBoost (accuracy: 0.857; AUC: 0.903) were better than other models. In conclusions, EL models with RF as the feature selection method might provide accurate results in predicting AS risk. Besides, ufPWV, especially PWV of left common carotid artery at the end of systole, was an important feature in the AS risk prediction models.

PMID:35220527 | DOI:10.1007/s10554-022-02574-3

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Nevin Manimala Statistics

Assessing the distributional effects of financial development on consumption-based carbon emissions in Sub-Saharan Africa: a quantile-based analysis

Environ Sci Pollut Res Int. 2022 Feb 27. doi: 10.1007/s11356-022-18671-8. Online ahead of print.

ABSTRACT

This study assessed the role of financial development (FD) and its distributional effects in explaining consumption-based carbon (ConCO2) emissions, in a framework that also examined the environmental Kuznets curve (EKC) hypothesis, in the context of 19 Sub-Saharan African countries. A composite index was used as measure of FD in a set of data spanning over the period 1995-2017, while controlling for population size (PS), energy intensity (EI) and natural resource rents (Nrr). Given that the variables deviate from expected normal distribution as adjudged by results of pre-estimation tests, the method of moments quantile regression (MM-QR) estimation technique was used to account for distributional effects of FD on ConCO2. Results of the fixed-effect regression based on Driscoll-Kray standard errors (FE-DK) which was validated by three other estimators (fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (DOLS), canonical cointegration regression (CCR)) statistically provided support for FD, PS and EI as drivers of ConCO2. Distributional effects of this show that FD exerts significant positive effect on ConCO2 among countries in the higher quantiles, but insignificant positive effect among those at the lower quantiles. The model provided no support for the EKC hypothesis for SSA; policy implications of these results were presented.

PMID:35220518 | DOI:10.1007/s11356-022-18671-8

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Nevin Manimala Statistics

Inflammatory myopathies overlapping with systemic sclerosis: a systematic review

Clin Rheumatol. 2022 Feb 27. doi: 10.1007/s10067-022-06115-0. Online ahead of print.

ABSTRACT

We performed a systematic review of the clinical manifestations and complementary exams of patients with myopathies and systemic sclerosis overlap syndrome (MyoSScOS). Systematic review from January 1976 to November 2021 according PRISMA protocol on three electronic databases: PubMed, Web of Science, and Scopus. Studies were analyzed based on the following eligibility criteria: at least one combination of the terms described in the search strategy appears in the title; written in English, Portuguese, or Spanish; and addresses MyoSScOS. Brief communications, reviews, studies that addressed myopathies in children, congress proceedings, monographs, and dissertations were excluded. Thirty-five articles were selected. MyoSScOS seems to be more common in women. It also commonly affects the esophagus and joints with symmetrical and bilateral muscle involvement, Raynaud’s phenomenon, and impairment of forced vital capacity. Concerning SSc, the most common subtype was the diffuse form. Cardiovascular and pulmonary complications are an important cause of death. Anti-centromere, anti-PM/Scl, anti-Scl70, anti-RNA polymerase III, anti-Ku, and anti-RNP were more correlated with this entity, and muscle biopsies may present a more aggressive pattern. Electroneuromyography patterns are quite similar to those found in inflammatory myopathies. The absence of studies with robust methodologies and the large number of case reports and series make more robust statistical analyses such as meta-analyses unfeasible. The characterization of MyoSScOS is important for the formulation of therapeutic measures and specific treatments aiming at better quality of life and prognosis. Greater and better theoretical contributions are necessary to better characterize it.

PMID:35220464 | DOI:10.1007/s10067-022-06115-0

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Nevin Manimala Statistics

Reference values of fetal ultrasound biometry: results of a prospective cohort study in Lithuania

Arch Gynecol Obstet. 2022 Feb 27. doi: 10.1007/s00404-022-06437-z. Online ahead of print.

ABSTRACT

PURPOSE: The aim of the study was to construct a reference range for the Lithuanian population for fetal biparietal diameter (BPD), occipitofrontal diameter (OFD), head circumference (HC), abdominal circumference (AC) and femur length (FL) and to compare them with the old local and current international reference values.

METHODS: A prospective cross-sectional study was carried out in secondary referral centres Vilnius University Hospital Santariškių Klinikos Centro Affiliate in 2008-2009 and Vilnius Maternity Hospital in 2009-2014. The fetal biometry of 556 fetuses between 12 and 42 weeks gestation was performed. BPD, OFD, HC, AC and FL were measured. The data were collected and the analysis was performed using statistical programs MS Excel, SPSS and Matlab. Different regression models were fitted to calculate the mean and standard deviation at each gestational age for each parameter.

RESULTS: The biometric measurements of HC, BPD, OFD as well as AC and FL were performed for 556 fetuses. The centile charts, tables and regression formulae of the biometric parameters were constructed. The comparison of the current charts with those of other two studies revealed no significant differences of HC centiles. AC values were similar to those presented in the international study INTERGROWTH-21 and significantly higher in comparison to the study for the Lithuanian population conducted by Ališauskas (1980). FL values, especially in late pregnancy, were significantly smaller in the INTERGROWTH-21 study compared to our charts; however, there were no significant differences of the 50th centile compared to the results from Ališauskas.

CONCLUSIONS: We have constructed and presented centile charts, tables and regression formulae for fetal biometry for the Lithuanian population and compared them with the results of two other studies. The significant differences between our centile charts and those from INTERGROWTH-21 imply the necessity to have local standards of fetal biometry, while the differences of our results from the older study in the same population show the importance of updating fetal biometry reference charts for every generation.

PMID:35220480 | DOI:10.1007/s00404-022-06437-z

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Nevin Manimala Statistics

Perforators of the posterior communicating artery and memory disturbance

Acta Neurochir (Wien). 2022 Feb 27. doi: 10.1007/s00701-022-05147-4. Online ahead of print.

NO ABSTRACT

PMID:35220461 | DOI:10.1007/s00701-022-05147-4

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Nevin Manimala Statistics

Mean platelet volume as a predictor of platelet count recovery in dengue patients

Trans R Soc Trop Med Hyg. 2022 Feb 26:trac008. doi: 10.1093/trstmh/trac008. Online ahead of print.

ABSTRACT

BACKGROUND: Thrombocytopenia is a marker of severity in dengue, and its resolution predicts clinical improvement. The objective was to evaluate mean platelet volume (MPV) trajectories as a predictor of platelet count (PC) recovery in dengue patients.

METHODS: An observational, longitudinal and analytical study was conducted at Fundación Valle del Lili (Cali, Colombia). Patients diagnosed with dengue during 2016-2020 were included. The association between PC and the covariates was evaluated using simple linear, quadratic and non-parametric spline smoothing regression models. A longitudinal linear mixed model was adjusted and then validated for PC measurements.

RESULTS: A total of 71 patients were included. The median age was 27 y, 38.5% were women and half had dengue with warning signs. A statistically significant PC decrease was observed when MPV was 13.87 fL and 4.46 d from the onset of symptoms, while PC displayed a significant constant increase with neutrophils count. Then, PC recovery was achieved with an MPV of 13.58 fL, 4.5 d from the onset of symptoms and a minimum neutrophils count of 150 μL.

CONCLUSION: MPV may be a predictor of PC recovery in dengue patients. PC recovery is expected when a patient has an MPV of 13.58 fL, an onset time of 4.5 d and a neutrophils count of 150 μL.

PMID:35220437 | DOI:10.1093/trstmh/trac008