Identification of Predictive Gene Signatures and Molecular Interactions Underlying Opioid Use Disorder in Brain Tissues and Peripheral Blood

Background: Opioid use disorder (OUD) is a chronic and relapsing condition influenced by genetic and environmental factors. OUD is associated with altered gene expression and epigenetic modifications in BA9 and the greater prefrontal cortex affecting regional function and connectivity. OUD may also involve the downregulation of genes related to synaptic transmission and neurogenesis in the amygdala, impairing its adaptability. In addition to the brain, peripheral blood can serve as a source of molecular markers for OUD as it is easily accessible and may reflect systemic and chronic inflammation changes prompted by OUD. Understanding the molecular mechanisms dysregulated by OUD may help identify novel biomarkers and therapeutic targets. This study aims to identify significantly predictive gene signatures using machine learning methods with bulk and miRNA-seq data across these tissues to elucidate their causal relationships with OUD and to explore their interactions with co-regulated factors. Methods: Raw counts tables were downloaded from the Gene Expression Omnibus (GEO) under accession numbers GSE182321 (BA9 RNA-seq), GSE221515 (BA9 miRNA-seq), GSE198121 (PBMC RNA-seq), GSE198122 (PBMC miRNA-seq), GSE194368 (amygdala RNA-seq). TMM normalized counts were obtained with edgeR and the Min-Max Scaler was used for feature pre-processing. Mutual information-based feature selection (feature importance \u3e 0.001) was used to identify significant mRNA, lncRNA, and miRNA in the tissue types predictive of OUD. Top targeting mRNA and lncRNA of each selected miRNA were retrieved using miRcode and SPMLMI. Selected genes were used in Support-Vector-Machine, Random Forest, and K-Nearest-Neighbor classifiers and 10 fold and leave one out cross validation (LOOCV) was applied to quantify their accuracy in determining OUD state across tissue types. Results: Several genes of overlapping significance concerned with neurological conditions were confirmed through LOOCV including TRBJ2-5 which may be involved in the modulation of the blood brain barrier and neuro-inflammatory processes. Further, both EGLN1 , playing a crucial role in the cellular response to hypoxia, and miR-223-3p are connected to neuroinflammation. Their large contribution in classifying OUD suggests a connection between altered barrier function, inflammation, and the development or progression of the disorder. LRP6 encodes a receptor involved in the Wnt signaling pathway, which plays a crucial role in neurodevelopment and synaptic plasticity. Dysregulation of the Wnt signaling pathway has been implicated in addiction, suggesting that LRP6 may play a larger role in the development or maintenance of the disorder. In the context of OUD, miR-219a-1-3p may have a regulatory role in modulating synaptic plasticity and neuronal adaptation to opioids since it targets genes involved in neuroplasticity, such as glutamate receptors and neurotrophins. Dysregulation of these targets may contribute to the maladaptive changes observed in the brain during opioid exposure and withdrawal, leading to the development and maintenance of OUD. Conclusions: This study highlights the significance of high predictive genes of BA9 and the amygdala in OUD, demonstrating their association with altered synaptic plasticity, which contribute to the dysfunction of these brain regions in OUD. Further, the potential of peripheral blood as a source of molecular markers for OUD is made evident, particularly its ability to reflect inflammatory pathway changes caused by OUD

Gliomatosis peritonei arising in setting of immature teratoma of ovary: a case report

A 14 years old girl presented to the gynecology OPD with pain abdomen and huge abdominal lump since 2 months. On clinical examination, a large mass of 20x15 cm size was found extended upto the xiphoid process. Serum studies showed rise of CA-125 up to 406.9U/mL and LDH up to 310U/L. USG shows right ovarian cyst of 14.8x14.1x12.8 cm with internal calcification. MRI revealed a well encapsulated mass of 21x19x17cm with solid and cystic mass and upward peritoneal extension. Exploratory laparotomy was performed with right sided salpingo- ophorectomy with infracolic omentectomy, as the omentum appeared granular. She had an uneventful post-operative recovery. Subsequently HPE showed immature teratoma NORRIS grade 3 with co-existent peritoneal gliomatosis (grade 0). She is under regular follow-up and decided to give six cycles of combination chemotherapy with BEP at regional cancer hospital

Slim U-Net: Efficient Anatomical Feature Preserving U-net Architecture for Ultrasound Image Segmentation

We investigate the applicability of U-Net based models for segmenting Urinary Bladder (UB) in male pelvic view UltraSound (US) images. The segmentation of UB in the US image aids radiologists in diagnosing the UB. However, UB in US images has arbitrary shapes, indistinct boundaries and considerably large inter- and intra-subject variability, making segmentation a quite challenging task. Our study of the state-of-the-art (SOTA) segmentation network, U-Net, for the problem reveals that it often fails to capture the salient characteristics of UB due to the varying shape and scales of anatomy in the noisy US image. Also, U-net has an excessive number of trainable parameters, reporting poor computational efficiency during training. We propose a Slim U-Net to address the challenges of UB segmentation. Slim U-Net proposes to efficiently preserve the salient features of UB by reshaping the structure of U-Net using a less number of 2D convolution layers in the contracting path, in order to preserve and impose them on expanding path. To effectively distinguish the blurred boundaries, we propose a novel annotation methodology, which includes the background area of the image at the boundary of a marked region of interest (RoI), thereby steering the model's attention towards boundaries. In addition, we suggested a combination of loss functions for network training in the complex segmentation of UB. The experimental results demonstrate that Slim U-net is statistically superior to U-net for UB segmentation. The Slim U-net further decreases the number of trainable parameters and training time by 54% and 57.7%, respectively, compared to the standard U-Net, without compromising the segmentation accuracy.Comment: Accepted in 9th ACM International Conference on Biomedical and Bioinformatics Engineering (ICBBE) 2022 http://www.icbbe.com

Human iPSC derived cardiomyocyte model reveals the transcriptomic bases of COVID-19 associated myocardial injury

Background: Multi-organ complications have been the hallmark of severe COVID-19; cardiac injuries were reported in 20% to 30% of hospitalized COVID-19 patients, although the disease etiology remains poorly understood. This study leveraged genome-wide RNA-sequence data generated using induced pluripotent stem cell (iPSC) differentiated cardiomyocytes (CMs) and in vitro modeling of SARS-CoV-2 infection in CMs, to understand the molecular mechanisms of COVID-19 myocardial injuries for novel diagnostic and therapeutic development. Methods: Raw RNA-sequence data sets, GSE165242 and GSE150392 were aligned to human genome assembly GRCh38 and gene expressions were quantified. Differentially expressed (DE) genes between experimental groups were identified using moderated t-statistics (FDR-corrected p-value ≤ 0.05) and Fold-Change analysis (FC absolute ≥ 2.0). Results: A total of 2,148 genes were significantly DE between SARS-CoV-2 infected and vehicle treated CMs and showed significant enrichment in cytokine signaling pathways (p-value=4.89E-25) and regulation of heart contraction (p-value=2.51E-19) gene-ontology biological processes. 606 of these DE genes were significantly upregulated during iPSC to CM differentiation. Disease and function annotation analysis of these 606 genes showed significant enrichment and activation of angiogenesis (p-value=4.04E-23; activation Z-score=3.7) and downregulation of heart contraction and related functions (p-value=4.24E-29; activation Z-score=-2.2) in SARS-CoV-2 infected CMs. The upstream regulator analysis identified upregulation of AGT associated proinflammatory genes and significant downregulation of TBX5 and MYOCD transcription factors and their gene networks, suggesting remodeling of CM contractility architecture. Conclusions: This study identified several AGT associated proinflammatory genes and TBX5 and MYOCD gene networks as potential targets for drug development to address COVID-19 associated cardiac injury

Disease Modeling and Disease Gene Discovery in Cardiomyopathies: A Molecular Study of Induced Pluripotent Stem Cell Generated Cardiomyocytes

The in vitro modeling of cardiac development and cardiomyopathies in human induced pluripotent stem cell (iPSC)-derived cardiomyocytes (CMs) provides opportunities to aid the discovery of genetic, molecular, and developmental changes that are causal to, or influence, cardiomyopathies and related diseases. To better understand the functional and disease modeling potential of iPSC-differentiated CMs and to provide a proof of principle for large, epidemiological-scale disease gene discovery approaches into cardiomyopathies, well-characterized CMs, generated from validated iPSCs of 12 individuals who belong to four sibships, and one of whom reported a major adverse cardiac event (MACE), were analyzed by genome-wide mRNA sequencing. The generated CMs expressed CM-specific genes and were highly concordant in their total expressed transcriptome across the 12 samples (correlation coefficient at 95% CI =0.92 ± 0.02). The functional annotation and enrichment analysis of the 2116 genes that were significantly upregulated in CMs suggest that generated CMs have a transcriptomic and functional profile of immature atrial-like CMs; however, the CMs-upregulated transcriptome also showed high overlap and significant enrichment in primary cardiomyocyte (p-value = 4.36 × 10−9), primary heart tissue (p-value = 1.37 × 10−41) and cardiomyopathy (p-value = 1.13 × 10−21) associated gene sets. Modeling the effect of MACE in the generated CMs-upregulated transcriptome identified gene expression phenotypes consistent with the predisposition of the MACE-affected sibship to arrhythmia, prothrombotic, and atherosclerosis risk

Enhancement of bioavailability of herbal drugs for treating viral therapy using SNEDDS as the delivery system

SNEDDS were developed with the objective of treating low bioavailability of drugs for antiviral drugs due to its low solubility. The scientist has increased their interest in improving bioavailability and absorption of poorly-water soluble drugs using Self-Emulsifying lipid technology. SNEDDS was an isocratic mixture contains an Oil, Surfactant, Co-surfactant, and Drug in accurate amount. The SNEDDS was primarily prepared as liquid-SNEDDS, but S-SNEDDS was more stable as compared to L-SNEDDS. As viral infection was major threat for people due to its limited efficacy and Serious adverse effects. The most damaging viral diseases was treated with help of SNEDDS as delivery system. They were a leading cause of morbidity and mortality. The plant and plant source were major source from which the extracted metabolites used for synthesis of drug through metabolic pathway. The phytochemicals and extracts were better and safe alternative for synthetic drugs. The phytochemicals like Curcumin, Myricetin, Apigenin etc. used as drug for treating antivirals using SNEDDS. This technique was used for quantitative and qualitative analysis. Also, the ternary phase diagram gives dramatic representation of Oil, surfactant and Co-surfactant which shows its concentration. Some characterization techniques were Droplet size, Zeta potential, XRD, DSC, FTIR, and TGA. Also, QbD provides a platform for systemic production of drug formulations. QbD was used for its better bioavailability

Similar Events but Contrasting Impact: Appraising the Global Digital Reach of World Heart Day and Atrial Fibrillation Awareness Month

Background: With over 18.6 million deaths annually, cardiovascular diseases (CVDs) are the leading cause of mortality worldwide. One such complication of CVDs that can result in stroke is atrial fibrillation (Afib). As part of global outreach and awareness, World Heart Day and Atrial Fibrillation Awareness Month are celebrated annually on 29 September and the month of September, respectively. Both of these events are important cardiovascular awareness initiatives to assist public education and develop awareness strategies, and they have received considerable support from leading international organizations. Objective: We studied the global digital impact of these campaigns via Google Trends and Twitter. Methods: We evaluated the overall number of tweets, impressions, popularity and top keywords/hashtags, and interest by region to determine the digital impact using various analytical tools. Hashtag network analysis was done using ForceAtlas2 model. Beyond social media, Google Trends web search analysis was carried out for both awareness campaigns to examine ‘interest by region’ over the past five years by analyzing relative search volume. Results: #WorldHeartDay and #UseHeart (dedicated social media hashtags for World Heart Day by the World Heart Federation) alone amassed over 1.005 billion and 41.89 million impressions as compared with the 1.62 million and 4.42 million impressions of #AfibMonth and #AfibAwarenessMonth, respectively. On Google Trends web search analysis, the impact of Afib awareness month was limited to the USA, but World Heart Day had a comparatively global reach with limited digital involvement in the African continent. Conclusions: World Heart Day and Afib awareness month present a compelling case study of vast digital impact and the effectiveness of targeted campaigning using specific themes and keywords. Though the efforts of the backing organizations are commended, planning and collaboration are needed to further widen the reach of Afib awareness month

Assessment of the quality, content, and reliability of YouTube® videos on diabetes mellitus and polycystic ovary syndrome:a systematic review with cross-sectional analysis comparing peer-reviewed videos

YouTube® is one of the leading platforms for health information. However, the lack of regulation of content and quality raises concerns about accuracy and reliability. CoMICs (Concise Medical Information Cines) are evidence-based short videos created by medical students and junior doctors and reviewed by experts to ensure clinical accuracy. We performed a systematic review to understand the impact of videos on knowledge and awareness about diabetes and PCOS. We then evaluated the quality of YouTube® videos about diabetes and PCOS using various validated quality assessment tools and compared these with CoMICs videos on the same topics. Quality assessment tools like DISCERN, JAMA benchmark criteria, and global quality scale (GQS) score were employed. Some of the authors of this study also co-authored the creation of some of the CoMICs evaluated. Our study revealed that while videos effectively improve understanding of diabetes and PCOS, there are notable differences in quality and reliability of the videos on YouTube®. For diabetes, CoMICs videos had higher DISCERN scores (CoMICs vs YouTube®: 2.4 vs 1.6), superior reliability (P &lt; 0.01), and treatment quality (P &lt; 0.01) and met JAMA criteria for authorship (100% vs 30.6%) and currency (100% vs 53.1%). For PCOS, CoMICs had higher DISCERN scores (2.9 vs 1.9), reliability (P &lt; 0.01), and treatment quality (P &lt; 0.01); met JAMA criteria for authorship (100% vs 34.0%) and currency (100% vs 54.0%); and had higher GQS scores (4.0 vs 3.0). In conclusion, CoMICs outperformed other similar sources on YouTube® in providing reliable evidence-based medical information which may be used for patient education.</p

Case Report: Multiple atherosclerotic plaques at its extreme in synchrony [version 3; peer review: 2 approved]

Peripheral artery (PAD) disease in association with renal artery stenosis is an important association which predicts the severity of the disease. An increase in the number of vessels affected by peripheral artery disease increases the chances of renal artery stenosis. In our case, the patient had primarily presented with anginal chest pain with complaints of claudication which on further investigation was diagnosed to be a triple vessel coronary artery disease along with bilateral subclavian and bilateral renal stenosis. On detailed history taking, risk factors like hypertension and chronic smoking was found to be present in our case which predisposed to peripheral artery disease secondary to atherosclerosis which was diagnosed on further investigations. Although the association of renal artery stenosis is not very rare in cases of severe peripheral vascular diseases, the presence of a triple vessel coronary artery disease in synchrony is what makes it unique. Take away lesson from this case report is importance of early diagnosis of dyslipidemia causing atherosclerosis and its complications. Multiple atherosclerotic lesions in synchrony i.e, bilateral renal artery stenosis with bilateral subclavian artery stenosis with coronary artery triple vessel atherosclerotic disease like in our case and its severity should create awareness among health care individuals and early treatment measures including lifestyle modifications should be considered to avoid such drastic events

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic