Bacterial interactome disturbance in chronic obstructive pulmonary disease clinical stability and exacerbations.

Rationale: Our understanding of airway dysbiosis in chronic obstructive pulmonary disease (COPD) remains incomplete, which may be improved by unraveling the complexity in microbial interactome.

Objectives: To characterize reproducible features of airway bacterial interactome in COPD at clinical stability and during exacerbation, and evaluate their associations with disease phenotypes.

Methods: We performed weighted ensemble-based co-occurrence network analysis of 1742 sputum microbiomes from published and new microbiome datasets, comprising two case-control studies of stable COPD versus healthy control, two studies of COPD stability versus exacerbation, and one study with exacerbation-recovery time series data.

Digital dual test syphilis/HIV detection based on Fourier Descriptors of Cyclic Voltammetry curves.

Background: Effective and timely detection is vital for mitigating the severe impacts of Sexually Transmitted Infections (STI), including syphilis and HIV. Cyclic Voltammetry (CV) sensors have shown promise as diagnostic tools for these STI, offering a pathway towards cost-effective solutions in primary health care settings.

Objective: This study aims to pioneer the use of Fourier Descriptors (FDs) in analyzing CV curves as 2D closed contours, targeting the simultaneous detection of syphilis and HIV.

Causal relationship between gut microbiota and rosacea: a two-sample Mendelian randomization study.

Background: Rosacea, a chronic inflammatory skin condition affecting millions worldwide, is influenced by complex interactions between genetic and environmental factors. Although gut microbiota's role in skin health is well-acknowledged, definitive causal links between gut microbiota and rosacea remain under-explored.

Methods: Using a two-sample Mendelian randomization (MR) design, this study examined potential causal relationships between gut microbiota and rosacea.

Feasibility of Remote Blood Pressure Monitoring for Detection and Management of Maternal Hypertension in a predominantly Black, Rural and Medicaid Population in Mississippi.

Remote patient monitoring (RPM) has potential in hypertension management, but limited studies have focused on maternal hypertension, especially among vulnerable populations. The objective of this study was to integrate RPM into perinatal care for pregnant patients at elevated risk of hypertensive disorders to show feasibility, acceptability, and safety. A prospective pilot cohort study was conducted at the University of Mississippi Medical Center 2021-2023.

The PTM profiling of CTCF reveals the regulation of 3D chromatin structure by O-GlcNAcylation.

CCCTC-binding factor (CTCF), a ubiquitously expressed and highly conserved protein, is known to play a critical role in chromatin structure. Post-translational modifications (PTMs) diversify the functions of protein to regulate numerous cellular processes. However, the effects of PTMs on the genome-wide binding of CTCF and the organization of three-dimensional (3D) chromatin structure have not been fully understood.

Rational design of a cyclohexanone dehydrogenase for enhanced α,β-desaturation and substrate specificity.

The selective α,β-desaturation of cyclic carbonyl compounds, which are found in the core of many steroid and bioactive molecules, using green chemistry is highly desirable. To achieve this task, we have for the first time described and solved the structure of a member of the cyclohexanone dehydrogenase class of enzymes. The breadth of substrate specificity was investigated by assaying the cyclohexanone dehydrogenase, from , against several cyclic ketones, lactones and lactams.

Utilizing genomic signatures to gain insights into the dynamics of SARS-CoV-2 through Machine and Deep Learning techniques.

The global spread of the SARS-CoV-2 pandemic, originating in Wuhan, China, has had profound consequences on both health and the economy. Traditional alignment-based phylogenetic tree methods for tracking epidemic dynamics demand substantial computational power due to the growing number of sequenced strains. Consequently, there is a pressing need for an alignment-free approach to characterize these strains and monitor the dynamics of various variants.

Hydrogels in Cutaneous Wound Healing: Insights into Characterization, Properties, Formulation and Therapeutic Potential.

Hydrogels are polymeric materials that possess a set of characteristics meeting various requirements of an ideal wound dressing, making them promising for wound care. These features include, among others, the ability to absorb and retain large amounts of water and the capacity to closely mimic native structures, such as the extracellular matrix, facilitating various cellular processes like proliferation and differentiation. The polymers used in hydrogel formulations exhibit a broad spectrum of properties, allowing them to be classified into two main categories: natural polymers like collagen and chitosan, and synthetic polymers such as polyurethane and polyethylene glycol.

Precise prediction of phase-separation key residues by machine learning.

Understanding intracellular phase separation is crucial for deciphering transcriptional control, cell fate transitions, and disease mechanisms. However, the key residues, which impact phase separation the most for protein phase separation function have remained elusive. We develop PSPHunter, which can precisely predict these key residues based on machine learning scheme.

Perspectives on the role of industry in informatics research and authorship.

Objectives: Advances in informatics research come from academic, nonprofit, and for-profit industry organizations, and from academic-industry partnerships. While scientific studies of commercial products may offer critical lessons for the field, manuscripts authored by industry scientists are sometimes categorically rejected. We review historical context, community perceptions, and guidelines on informatics authorship.

Puzzling out the role of LncRNA in hepatocellular carcinoma.

A non-negligible part of our DNA has been proven to be transcribed into non-protein coding RNA and its intricate involvement in several physiological processes has been highly evidenced. The significant biological role of non-coding RNAs (ncRNAs), including long non-coding RNAs (lncRNAs) has been variously reported. In the current review, the authors highlight the multifaceted role of myocardial infarction-associated transcript (), a well-known lncRNA, in hepatocellular carcinoma (HCC).

LncRNA: A multifunctional key player in non-oncological pathological conditions.

The discovery of non-coding RNAs (ncRNAs) has unveiled a wide range of transcripts that do not encode proteins but play key roles in several cellular and molecular processes. Long noncoding RNAs (lncRNAs) are specific class of ncRNAs that are longer than 200 nucleotides and have gained significant attention due to their diverse mechanisms of action and potential involvement in various pathological conditions. In the current review, the authors focus on the role of lncRNAs, specifically highlighting the Myocardial Infarction Associated Transcript (), in non-oncological context.

Construction and applications of the EOMA spheroid model of Kaposiform hemangioendothelioma.

Background: Kaposiform hemangioendothelioma (KHE) is a rare intermediate vascular tumor with unclear pathogenesis. Recently, three dimensional (3D) cell spheroids and organoids have played an indispensable role in the study of many diseases, such as infantile hemangioma and non-involuting congenital hemangiomas. However, few research on KHE are based on the 3D model.

Thematic evolution of smart learning environments, insights and directions from a 20-year research milestones: A bibliometric analysis.

Smart learning environments (SLEs) have been developed to create an effective learning environment gradually and sustainably by applying technology. Given the growing dependence on technology daily, SLE will inevitably be incorporated into the teaching and learning process. Without transforming technology-enhanced learning environments into SLE, they are restricted to adding sophistication and lack pedagogical benefits, leading to wasteful educational investments.

Healthcare facilities management: A novel data-driven model for predictive maintenance of computed tomography equipment.

Background: The breakdown of healthcare facilities is a huge challenge for hospitals. Medical images obtained by Computed Tomography (CT) provide information about the patients' physical conditions and play a critical role in diagnosis of disease. To deliver high-quality medical images on time, it is essential to minimize the occurrence frequencies of anomalies and failures of the equipment.

Comparison between epileptic seizure prediction and forecasting based on machine learning.

Epilepsy affects around 1% of the population worldwide. Anti-epileptic drugs are an excellent option for controlling seizure occurrence but do not work for around one-third of patients. Warning devices employing seizure prediction or forecasting algorithms could bring patients new-found comfort and quality of life.

Harnessing the supremacy of MEG3 LncRNA to defeat gastrointestinal malignancies.

Evidence suggests that long non-coding RNAs (lncRNAs) play a pivotal role in the carcinogenesis and progression of various human malignancies including gastrointestinal malignancies. This comprehensive review reports the functions and mechanisms of the lncRNA maternally expressed gene 3 (MEG3) involved in gastrointestinal malignancies. It summarizes its roles in mediating the regulation of cellular proliferation, apoptosis, migration, invasiveness, epithelial-to-mesenchymal transition, and drug resistance in several gastrointestinal cancers such as colorectal cancer, gall bladder cancer, pancreatic cancer, gastric cancer, esophageal cancer, cholangiocarcinoma, gastrointestinal stromal tumors and most importantly, hepatocellular carcinoma.

Efficacy and acceptability of psilocybin for primary or secondary depression: A systematic review and meta-analysis of randomized controlled trials.

Introduction: Psilocybin is a classic psychedelics, which has been shown to have antidepressant effects by many studies in recent years. In this study, we aim to evaluate the efficacy, acceptability and tolerability of psilocybin in the treatment of primary (major depressive disorder) or secondary (experiencing distress related to life-threatening diagnoses and terminal illness) depression.

Methods: We searched PubMed, EMBASE, Web of Science, Cochrane Library and ClinicalTrials.

Identification of ipsilateral supraclavicular lymph node metastasis in breast cancer based on LASSO regression with a high penalty factor.

Aiming at the problems of small sample size and large feature dimension in the identification of ipsilateral supraclavicular lymph node metastasis status in breast cancer using ultrasound radiomics, an optimized feature combination search algorithm is proposed to construct linear classification models with high interpretability. The genetic algorithm (GA) is used to search for feature combinations within the feature subspace using least absolute shrinkage and selection operator (LASSO) regression. The search is optimized by applying a high penalty to the L1 norm of LASSO to retain excellent features in the crossover operation of the GA.

Key subphenotypes of bipolar disorder are differentially associated with polygenic liabilities for bipolar disorder, schizophrenia, and major depressive disorder.

Bipolar disorder (BD) features heterogenous clinical presentation and course of illness. It remains unclear how subphenotypes associate with genetic loadings of BD and related psychiatric disorders. We investigated associations between the subphenotypes and polygenic risk scores (PRS) for BD, schizophrenia, and major depressive disorder (MDD) in two BD cohorts from Sweden (N = 5180) and the UK (N = 2577).

Disease clusters subsequent to anxiety and stress-related disorders and their genetic determinants.

Anxiety/stress-related disorders have been associated with multiple diseases, whereas a comprehensive assessment of the structure and interplay of subsequent associated diseases and their genetic underpinnings is lacking. Here, we first identify 136, out of 454 tested, medical conditions associated with incident anxiety/stress-related disorders attended in specialized care using a population-based cohort from the nationwide Swedish Patient Register, comprising 70,026 patients with anxiety/stress-related disorders and 1:10 birth year- and sex-matched unaffected individuals. By combining findings from the comorbidity network and disease trajectory analyses, we identify five robust disease clusters to be associated with a prior diagnosis of anxiety/stress-related disorders, featured by predominance of psychiatric disorders, eye diseases, ear diseases, cardiovascular diseases, and skin and genitourinary diseases.

Childhood maltreatment and risk of endocrine diseases: an exploration of mediating pathways using sequential mediation analysis.

Background: Adverse childhood experiences (ACEs), including childhood maltreatment, have been linked with increased risk of diabetes and obesity during adulthood. A comprehensive assessment on the associations between childhood maltreatment and all major endocrine diseases, as well as the relative importance of different proposed mechanistic pathways on these associations, is currently lacking.

Methods: Based on the UK Biobank, we constructed a cohort including 151,659 participants with self-reported data on childhood maltreatment who were 30 years of age or older on/after January 1, 1985.

Long-term follow-up of brain regional changes and the association with cognitive impairment in quarantined COVID-19 survivors.

Objective: This study aimed to evaluate the neuropsychiatric symptoms of quarantined COVID-19 survivors 15 months after discharge and explore its potential association with structural and functional brain changes and inflammation.

Methods: A total of 51 quarantined COVID-19 survivors and 74 healthy controls were included in this study. Cognitive function was assessed using the THINC-integrated tool.