Nevin Manimala

Metabolites. 2021 Oct 28;11(11):738. doi: 10.3390/metabo11110738.

ABSTRACT

Steroid hormones act as important regulators of physiological processes including gene expression. They provide possible mechanistic explanations of observed sex-dimorphisms in obesity and coronary artery disease (CAD). Here, we aim to unravel causal relationships between steroid hormones, obesity, and CAD in a sex-specific manner. In genome-wide meta-analyses of four steroid hormone levels and one hormone ratio, we identified 17 genome-wide significant loci of which 11 were novel. Among loci, seven were female-specific, four male-specific, and one was sex-related (stronger effects in females). As one of the loci was the human leukocyte antigen (HLA) region, we analyzed HLA allele counts and found four HLA subtypes linked to 17-OH-progesterone (17-OHP), including HLA-B*14*02. Using Mendelian randomization approaches with four additional hormones as exposure, we detected causal effects of dehydroepiandrosterone sulfate (DHEA-S) and 17-OHP on body mass index (BMI) and waist-to-hip ratio (WHR). The DHEA-S effect was stronger in males. Additionally, we observed the causal effects of testosterone, estradiol, and their ratio on WHR. By mediation analysis, we found a direct sex-unspecific effect of 17-OHP on CAD while the other four hormone effects on CAD were mediated by BMI or WHR. In conclusion, we identified the sex-specific causal networks of steroid hormones, obesity-related traits, and CAD.

PMID:34822396 | DOI:10.3390/metabo11110738

Metabolites. 2021 Oct 27;11(11):737. doi: 10.3390/metabo11110737.

ABSTRACT

Determining biomarkers and better characterizing the biochemical progression of nonalcoholic fatty liver disease (NAFLD) remains a clinical challenge. A targeted ¹H-NMR study of serum, combined with clinical variables, detected and localized biomarkers to stages of NAFLD in morbidly obese females. Pre-surgery serum samples from 100 middle-aged, morbidly obese female subjects, grouped on gold-standard liver wedge biopsies (non-NAFLD; steatosis; and fibrosis) were collected, extracted, and analyzed in aqueous (D₂O) buffer (¹H, 600 MHz). Profiled concentrations were subjected to exploratory statistical analysis. Metabolites varying significantly between the non-NAFLD and steatosis groups included the ketone bodies 3-hydroxybutyrate (↓; p = 0.035) and acetone (↓; p = 0.012), and also alanine (↑; p = 0.004) and a putative pyruvate signal (↑; p = 0.003). In contrast, the steatosis and fibrosis groups were characterized by 2-hydroxyisovalerate (↑; p = 0.023), betaine (↓; p = 0.008), hypoxanthine (↓; p = 0.003), taurine (↓; p = 0.001), 2-hydroxybutyrate (↑; p = 0.045), 3-hydroxyisobutyrate (↑; p = 0.046), and increasing medium chain fatty acids. Exploratory classification models with and without clinical variables exhibited overall success rates ca. 75-85%. In the study conditions, inhibition of fatty acid oxidation and disruption of the hepatic urea cycle are supported as early features of NAFLD that continue in fibrosis. In fibrosis, markers support inflammation, hepatocyte damage, and decreased liver function. Complementarity of NMR concentrations and clinical information in classification models is shown. A broader hypothesis that standard-of-care sera can yield metabolomic information is supported.

PMID:34822395 | DOI:10.3390/metabo11110737

Metabolites. 2021 Oct 22;11(11):723. doi: 10.3390/metabo11110723.

ABSTRACT

Gestational diabetes mellitus (GDM) is one of the most frequent pregnancy complications with potential adverse outcomes for mothers and newborns. Its effects on the newborn appear during the neonatal period or early childhood. Therefore, an early diagnosis is crucial to prevent the development of chronic diseases later in adult life. In this study, the urinary metabolome of babies born to GDM mothers was characterized. In total, 144 neonatal and maternal (second and third trimesters of pregnancy) urinary samples were analyzed using targeted metabolomics, combining liquid chromatographic mass spectrometry (LC-MS/MS) and flow injection analysis mass spectrometry (FIA-MS/MS) techniques. We provide here the neonatal urinary concentration values of 101 metabolites for 26 newborns born to GDM mothers and 22 newborns born to healthy mothers. The univariate analysis of these metabolites revealed statistical differences in 11 metabolites. Multivariate analyses revealed a differential metabolic profile in newborns of GDM mothers characterized by dysregulation of acylcarnitines, amino acids, and polyamine metabolism. Levels of hexadecenoylcarnitine (C16:1) and spermine were also higher in newborns of GDM mothers. The maternal urinary metabolome revealed significant differences in butyric, isobutyric, and uric acid in the second and third trimesters of pregnancy. These metabolic alterations point to the impact of GDM in the neonatal period.

PMID:34822382 | DOI:10.3390/metabo11110723

Medicines (Basel). 2021 Nov 12;8(11):70. doi: 10.3390/medicines8110070.

ABSTRACT

COVID-19 has had a significant impact on global health systems. The aim of this study was to evaluate how imaging volumes and imaging types in radiology departments have been affected by the COVID-19 pandemic across different locations.

METHODS: Imaging volumes in the Aseer region (in the south of Saudi Arabia) across main hospitals were reviewed retrospectively including all cases referred from different locations (outpatient, inpatient and emergency departments). Data for years 2019 and 2020 were compared. The mean monthly cases were compared using a t-test.

RESULTS: The total imaging volumes in 2019 were 205,805 compared to 159,107 in 2020 with a 22.7% overall reduction. A substantial decline was observed in both the April to June and the July to September periods of approximately 42.9% and 44.4%, respectively. With respect to location, between April and June, the greatest decline was observed in outpatient departments (76% decline), followed by emergency departments (25% decline), and the least impact was observed in inpatient departments, with only 6.8% decline over the same period. According to modality type, the greatest decreases were reported in nuclear medicine, ultrasound, MRI, and mammography, by 100%, 76%, 74%, and 66%, respectively. Our results show a statistically significant (p-value ≤ 0.05) decrease of cases in 2020 compared to 2019, except for mammography procedures.

CONCLUSION: There has been a significant decline in radiology volumes due to COVID-19. The overall reduction in radiology volumes was dependent on the stage/period of lockdown, location, and imaging modality.

PMID:34822367 | DOI:10.3390/medicines8110070

JMIR Aging. 2021 Nov 24;4(4):e16006. doi: 10.2196/16006.

ABSTRACT

BACKGROUND: The rapid diffusion of the internet has decreased consumer reliance on health care providers for health information and facilitated the patients’ ability to be an agent in control of their own health. However, empirical evidence is limited regarding the effects of health-related internet use among older adults, which is complicated by the proliferation of online health and medical sources of questionable scientific accuracy.

OBJECTIVE: We explore the effects of health-related internet use, education, and eHealth literacy on medical encounters and patient-reported outcomes. Patient-reported outcomes are categorized into two dimensions: (1) self-reported health problem and (2) affective distress (feeling worried and anxious) due to information obtained. We were particularly interested in whether education and eHealth literacy moderate the association between perceived strain in medical encounters and patient-reported outcomes.

METHODS: Our study sample consisted of online panel members who have used the internet as a resource for health information, randomly drawn from one of the largest probability-based online research panels. This paper specifically reports results obtained from older panel members (age≥60 years: n=194). First, we examined descriptive statistics and bivariate associations (Pearson correlations and independent samples t tests). We used hierarchical ordinary least squares regression analyses by running separate regressions for each patient-reported outcome. In model 1, we entered the main effects. In model 2, technology and medical encounter variables were included. Model 3 added the statistical interaction terms.

RESULTS: Age (β=-.17; P=.02), gender (β=-.22; P=.01), and medical satisfaction (β=-.28; P=.01) were significant predictors of self-reported health problems. Affective distress was positively predicted by gender (β=.13; P=.05) and satisfaction with medical encounters (β=.34; P<.001) but negatively predicted by education (β=-.18; P=.03) and eHealth literacy (β=-.32; P=.01). The association between experiencing a health problem in relation to health-related internet use and perception of strained medical encounters was greater among respondents with lower levels of education (β=-.55; P=.04). There was also a significant interaction between education and eHealth literacy in predicting the level of affective distress (β=-.60; P=.05), which indicated that higher levels of education predicted lower averages of feeling anxiety and worry despite lower eHealth literacy. Older women reported higher averages of affective distress (β=.13; P=.05), while older men reported higher averages of experiencing a self-reported health problem (β=-.22; P=.01).

CONCLUSIONS: This study provides evidence for the effect of health-related internet use on patient-reported outcomes with implications for medical encounters. The results could be used to guide educational and eHealth literacy interventions for older individuals.

PMID:34822340 | DOI:10.2196/16006

Ceylon Med J. 2020 Dec 31;65(4):79-85. doi: 10.4038/cmj.v65i4.9276.

ABSTRACT

INTRODUCTION: The majority of Sri Lankan Moors fast during Ramadan. This may have an effect on their glycaemic control and anthropometric parameters. However, limited information exists about the impact of Ramadan fasting on diabetes in Sri Lanka.

OBJECTIVES: The main objective of this study was to investigate the effect of Ramadan fasting on glycaemic control and anthropometric parameters in patients with type 2 diabetes mellitus (T2DM). Patients were also observed for symptoms of hypoglycaemia, timing and association with different antidiabetic agents.

METHODS: One hundred and twenty Sri Lankan Moors with T2DM were recruited for this study. Biochemical investigations and anthropometric parameters were done before and after Ramadan fasting. The statistical analysis was done with paired t test to compare glycaemic control and anthropometric parameters before and after Ramadan.

RESULTS: There was a significant decrease in body weight (mean body weight 66.17 to 65.52 kg; p= < 0.001) and waist circumference (93.84 to 92.16cm; p= < 0.001). However, the glycaemic control worsened in all patients during Ramadan with rise in mean fructosamine value of 354.1 to 996.9µmol/L. Out of 104 participants 43 participants experienced symptoms of hypoglycaemia.

CONCLUSIONS: The current study showed an improvement in the body weight and waist circumference during Ramadan fasting, however the glycaemic control has been worsened. More follow-up studies are warranted in order to draw a conclusion on the effect of Ramadan fasting in glycaemic control and anthropometric parameters in diabetes patients.

PMID:34821486 | DOI:10.4038/cmj.v65i4.9276

Vet Ophthalmol. 2021 Nov 25. doi: 10.1111/vop.12947. Online ahead of print.

ABSTRACT

OBJECTIVE: The aim of this retrospective study was to review the clinical data and outcomes of patients that suffered ectopic cilium (EC).

ANIMALS STUDIED: One hundred and twelve dogs from multiple private practices in France, with a clinical diagnosis of EC were included in the study.

RESULTS: The mean age of affected dogs was 2.3 years. There were 64 females and 48 males. The most represented breeds were the Shi Tzu, the French Bulldog, the English Bulldog and the Chihuahua. Eleven dogs were affected bilaterally. The upper eyelid was implicated in 93.5% of the cases, with the median portion being the most affected. No statistical difference was observed between the right and the left eye. EC were associated with distichiasis in 50% of the cases. Pigmentation of the conjunctiva at the point of exit of the EC was present in 58% of the cases. EC were short in 75% and long in 25% of the cases. Corneal complications were statistically associated with short EC. The corneal lesions associated with EC were keratitis (94%), corneal granuloma (0.8%), corneal fibrosis (2.7%), corneal degeneration (0.8%), superficial corneal ulcer (68.7%), deep corneal ulcer (8%) and perforating corneal ulcer (0.8%). The surgeries which consisted of the removal of the hair follicle was successful in 88.4% of the cases.

CONCLUSION: EC is a rare condition which can be treated successfully by the removal of the hair follicles. It must be suspected in cases of corneal lesions unresponsive to medical treatment.

PMID:34821455 | DOI:10.1111/vop.12947

Biom J. 2021 Nov 25. doi: 10.1002/bimj.202000015. Online ahead of print.

ABSTRACT

In many biomedical studies or clinical trials, we have data with more than one response variable on the same subject repeatedly measured over time. In analyzing such data, we adopt a multivariate linear mixed-effects longitudinal model. On the other hand, in longitudinal data, we often find features that do not impact modeling the response variable and are eliminated from the study. In this paper, we consider the problem of simultaneous variable selection and estimation in a multivariate t linear mixed-effects model (MtLMM) for analyzing longitudinally measured multioutcome data. This work’s motivation comes from a cohort study of patients with primary biliary cirrhosis. The interest is eliminating insignificant variables using the smoothly clipped and absolute deviation penalty function in the MtLMM. The proposed penalized model offers robustness and flexibility to accommodate fat tails. An expectation conditional maximization algorithm is employed for the computation of maximum likelihood estimates of parameters. The calculation of standard errors is affected by an information-based method. The methodology is illustrated by analyzing Mayo Clinic Primary Biliary Cirrhosis sequential (PBCseq) data and a simulation study. We found drugs and sex can be eliminated from the PBCseq analysis, and over time the disease progresses.

PMID:34821410 | DOI:10.1002/bimj.202000015

Stat Med. 2021 Nov 25. doi: 10.1002/sim.9265. Online ahead of print.

ABSTRACT

A Bayesian biomarker-based phase I/II design (BIPSE) is presented for immunotherapy trials with a progression-free survival (PFS) endpoint. The objective is to identify the subgroup-specific optimal dose, defined as the dose with the best risk-benefit tradeoff in each biomarker subgroup. We jointly model the immune response, toxicity outcome, and PFS with information borrowing across subgroups. A plateau model is used to describe the marginal distribution of the immune response. Conditional on the immune response, we model toxicity using probit regression and model PFS using the mixture cure rate model. During the trial, based on the accumulating data, we continuously update model estimates and adaptively randomize patients to doses with high desirability within each subgroup. Simulation studies show that the BIPSE design has desirable operating characteristics in selecting the subgroup-specific optimal doses and allocating patients to those optimal doses, and outperforms conventional designs.

PMID:34821409 | DOI:10.1002/sim.9265

Med Phys. 2021 Nov 25. doi: 10.1002/mp.15380. Online ahead of print.

ABSTRACT

PURPOSE: The common practice in acquiring the magnetic resonance (MR) images is to obtain two-dimensional (2D) slices at coarse locations while keeping the high in-plane resolution in order to ensure enough body coverage while shortening the MR scan time. The aim of this study is to propose a novel method to generate HR MR images from low resolution MR images along the longitudinal direction. In order to address the difficulty of collecting paired low- and high-resolution MR images in clinical settings and to gain the advantage of parallel cycle consistent generative adversarial networks (CycleGANs) in synthesizing realistic medical images, we developed a parallel CycleGANs based method using a self-supervised strategy.

METHODS AND MATERIALS: The proposed workflow consists of two parallelly trained CycleGANs to independently predict the HR MR images in the two planes along the directions that is orthogonal to the longitudinal MR scan direction. Then the final synthetic HR MR images are generated by fusing the two predicted images. MR images, including T1-weighted (T1), contrast enhanced T1-weighted (T1CE), T2-weighted (T2) and T2 Fluid Attenuated Inversion Recovery (FLAIR), of the multimodal brain tumor segmentation challenge 2020 (BraTS2020) dataset were processed to evaluate the proposed workflow along the cranial-caudal (CC), lateral and anterior-posterior directions. Institutional collected MR images were also processed for evaluation of the proposed method. The performance of the proposed method was investigated via both qualitative and quantitative evaluations. Metrics of normalized mean absolute error (NMAE), peak signal-to-noise ratio (PSNR), edge keeping index (EKI), structural similarity index measurement (SSIM), information fidelity criterion (IFC) and visual information fidelity in pixel domain (VIFP) were calculated.

RESULTS: It is shown that the proposed method can generate HR MR images visually indistinguishable from the ground truth in the investigations on the BraTS2020 dataset. In addition, the intensity profiles, difference images and SSIM maps can also confirm the feasibility of the proposed method for synthesizing HR MR images. Quantitative evaluations on the BraTS2020 dataset shows that the calculated metrics of synthetic HR MR images can all be enhanced for the T1, T1CE, T2 and FLAIR images. The enhancements in the numerical metrics over the low-resolution and bi-cubic interpolated MR images are statistically significant. Qualitative evaluation of the synthetic HR MR images of the clinical collected dataset could also confirm the feasibility of the proposed method.

CONCLUSIONS: The proposed method is feasible to synthesize HR MR images using self-supervised parallel CycleGANs, which can be expected to shorten MR acquisition time in clinical practices. This article is protected by copyright. All rights reserved.

PMID:34821395 | DOI:10.1002/mp.15380