ZBTB20 Regulates SERCA2a Activity and Myocardial Contractility Through Phospholamban.

BACKGROUND: Intracellular Ca2+ cycling determines myocardial contraction and relaxation in response to physiological demands. SERCA2a (sarcoplasmic/endoplasmic reticulum Ca2+-ATPase 2a) is responsible for the sequestration of cytosolic Ca2+ into intracellular stores during cardiac relaxation, and its activity is reversibly inhibited by PLN (phospholamban). However, the regulatory hierarchy of SERCA2a activity remains unclear. METHODS: Cardiomyocyte-specific ZBTB20 knockout mice were generated by crossing ZBTB20flox mice with Myh6-Cre mice. Echocardiography, blood pressure measurements, Langendorff perfusion, histological analysis and immunohistochemistry, quantitative reverse transcription-PCR, Western blot analysis, electrophysiological measurements, and chromatin immunoprecipitation assay were performed to clarify the phenotype and elucidate the molecular mechanisms. RESULTS: Specific ablation of ZBTB20 in cardiomyocyte led to a significant increase in basal myocardial contractile parameters both in vivo and in vitro, accompanied by an impairment in cardiac reserve and exercise capacity. Moreover, the cardiomyocytes lacking ZBTB20 showed an increase in sarcoplasmic reticular Ca2+ content and exhibited a remarkable enhancement in both SERCA2a activity and electrically stimulated contraction. Mechanistically, PLN expression was dramatically reduced in cardiomyocytes at the mRNA and protein levels by ZBTB20 deletion or silencing, and PLN overexpression could largely restore the basal contractility in ZBTB20-deficient cardiomyocytes. CONCLUSIONS: These data point to ZBTB20 as a fine-tuning modulator of PLN expression and SERCA2a activity, thereby offering new perspective on the regulation of basal contractility in the mammalian heart.

Multi-task prediction-based graph contrastive learning for inferring the relationship among lncRNAs, miRNAs and diseases.

MOTIVATION: Identifying the relationships among long non-coding RNAs (lncRNAs), microRNAs (miRNAs) and diseases is highly valuable for diagnosing, preventing, treating and prognosing diseases. The development of effective computational prediction methods can reduce experimental costs. While numerous methods have been proposed, they often to treat the prediction of lncRNA-disease associations (LDAs), miRNA-disease associations (MDAs) and lncRNA-miRNA interactions (LMIs) as separate task. Models capable of predicting all three relationships simultaneously remain relatively scarce. Our aim is to perform multi-task predictions, which not only construct a unified framework, but also facilitate mutual complementarity of information among lncRNAs, miRNAs and diseases. RESULTS: In this work, we propose a novel unsupervised embedding method called graph contrastive learning for multi-task prediction (GCLMTP). Our approach aims to predict LDAs, MDAs and LMIs by simultaneously extracting embedding representations of lncRNAs, miRNAs and diseases. To achieve this, we first construct a triple-layer lncRNA-miRNA-disease heterogeneous graph (LMDHG) that integrates the complex relationships between these entities based on their similarities and correlations. Next, we employ an unsupervised embedding model based on graph contrastive learning to extract potential topological feature of lncRNAs, miRNAs and diseases from the LMDHG. The graph contrastive learning leverages graph convolutional network architectures to maximize the mutual information between patch representations and corresponding high-level summaries of the LMDHG. Subsequently, for the three prediction tasks, multiple classifiers are explored to predict LDA, MDA and LMI scores. Comprehensive experiments are conducted on two datasets (from older and newer versions of the database, respectively). The results show that GCLMTP outperforms other state-of-the-art methods for the disease-related lncRNA and miRNA prediction tasks. Additionally, case studies on two datasets further demonstrate the ability of GCLMTP to accurately discover new associations. To ensure reproducibility of this work, we have made the datasets and source code publicly available at https://github.com/sheng-n/GCLMTP.

Polycystic Ovary Syndrome Fuels Cardiovascular Inflammation and Aggravates Ischemic Cardiac Injury.

BACKGROUND: Reducing cardiovascular disease burden among women remains challenging. Epidemiologic studies have indicated that polycystic ovary syndrome (PCOS), the most common endocrine disease in women of reproductive age, is associated with an increased prevalence and extent of coronary artery disease. However, the mechanism through which PCOS affects cardiac health in women remains unclear. METHODS: Prenatal anti-Müllerian hormone treatment or peripubertal letrozole infusion was used to establish mouse models of PCOS. RNA sequencing was performed to determine global transcriptomic changes in the hearts of PCOS mice. Flow cytometry and immunofluorescence staining were performed to detect myocardial macrophage accumulation in multiple PCOS models. Parabiosis models, cell-tracking experiments, and in vivo gene silencing approaches were used to explore the mechanisms underlying increased macrophage infiltration in PCOS mouse hearts. Permanent coronary ligation was performed to establish myocardial infarction (MI). Histologic analysis and small-animal imaging modalities (eg, magnetic resonance imaging and echocardiography) were performed to evaluate the effects of PCOS on injury after MI. Women with PCOS and control participants (n=200) were recruited to confirm findings observed in animal models. RESULTS: Transcriptomic profiling and immunostaining revealed that hearts from PCOS mice were characterized by increased macrophage accumulation. Parabiosis studies revealed that monocyte-derived macrophages were significantly increased in the hearts of PCOS mice because of enhanced circulating Ly6C+ monocyte supply. Compared with control mice, PCOS mice showed a significant increase in splenic Ly6C+ monocyte output, associated with elevated hematopoietic progenitors in the spleen and sympathetic tone. Plasma norepinephrine (a sympathetic neurotransmitter) levels and spleen size were consistently increased in women with PCOS when compared with those in control participants, and norepinephrine levels were significantly correlated with circulating CD14++CD16- monocyte counts. Compared with animals without PCOS, PCOS animals showed significantly exacerbated atherosclerotic plaque development and post-MI cardiac remodeling. Conditional Vcam1 silencing in PCOS mice significantly suppressed cardiac inflammation and improved cardiac injury after MI. CONCLUSIONS: Our data documented previously unrecognized mechanisms through which PCOS could affect cardiovascular health in women. PCOS may promote myocardial macrophage accumulation and post-MI cardiac remodeling because of augmented splenic myelopoiesis.

TSHR signaling promotes hippocampal dependent memory formation through modulating Wnt5a/ß-catenin mediated neurogenesis.

Subclinical hyperthyroidism is defined biochemically as a low or undetectable thyroid-stimulating hormone (TSH) with normal thyroid hormone levels. Low TSHR signaling is considered to associate with cognitive impairment. However, the underlying molecular mechanism by which TSHR signaling modulates memory is poorly understood. In this study, we found that Tshr-deficient in the hippocampal neurons impairs the learning and memory abilities of mice, accompanying by a decline in the number of newborn neurons. Notably, Tshr ablation in the hippocampus decreases the expression of Wnt5a, thereby inactivating the ß-catenin signaling pathway to reduce the neurogenesis. Conversely, activating of the Wnt/ß-catenin pathway by the agonist SKL2001 results in an increase in hippocampal neurogenesis, resulting in the amelioration in the deficits of memory caused by Tshr deletion. Understanding how TSHR signaling in the hippocampus regulates memory provides insights into subclinical hyperthyroidism affecting cognitive function and will suggest ways to rationally design interventions for neurocognitive disorders.

Mitochondrial stress: a key role of neuroinflammation in stroke.

Stroke is a clinical syndrome characterized by an acute, focal neurological deficit, primarily caused by the occlusion or rupture of cerebral blood vessels. In stroke, neuroinflammation emerges as a pivotal event contributing to neuronal cell death. The occurrence and progression of neuroinflammation entail intricate processes, prominently featuring mitochondrial dysfunction and adaptive responses. Mitochondria, a double membrane-bound organelle are recognized as the "energy workshop" of the body. Brain is particularly vulnerable to mitochondrial disturbances due to its high energy demands from mitochondria-related energy production. The interplay between mitochondria and neuroinflammation plays a significant role in the pathogenesis of stroke. The biological and pathological consequences resulting from mitochondrial stress have substantial implications for cerebral function. Mitochondrial stress serves as an adaptive mechanism aimed at mitigating the stress induced by the import of misfolded proteins, which occurs in response to stroke. This adaptive response involves a reduction in misfolded protein accumulation and overall protein synthesis. The influence of mitochondrial stress on the pathological state of stroke is underscored by its capacity to interact with neuroinflammation. The impact of mitochondrial stress on neuroinflammation varies according to its severity. Moderate mitochondrial stress can bolster cellular adaptive defenses, enabling cells to better withstand detrimental stressors. In contrast, sustained and excessive mitochondrial stress detrimentally affects cellular and tissue integrity. The relationship between neuroinflammation and mitochondrial stress depends on the degree of mitochondrial stress present. Understanding its role in stroke pathogenesis is instrumental in excavating the novel treatment of stroke. This review aims to provide the evaluation of the cross-talk between mitochondrial stress and neuroinflammation within the context of stroke. We aim to reveal how mitochondrial stress affects neuroinflammation environment in stroke.

Multi-channel graph attention autoencoders for disease-related lncRNAs prediction.

MOTIVATION: Predicting disease-related long non-coding RNAs (lncRNAs) can be used as the biomarkers for disease diagnosis and treatment. The development of effective computational prediction approaches to predict lncRNA-disease associations (LDAs) can provide insights into the pathogenesis of complex human diseases and reduce experimental costs. However, few of the existing methods use microRNA (miRNA) information and consider the complex relationship between inter-graph and intra-graph in complex-graph for assisting prediction. RESULTS: In this paper, the relationships between the same types of nodes and different types of nodes in complex-graph are introduced. We propose a multi-channel graph attention autoencoder model to predict LDAs, called MGATE. First, an lncRNA-miRNA-disease complex-graph is established based on the similarity and correlation among lncRNA, miRNA and diseases to integrate the complex association among them. Secondly, in order to fully extract the comprehensive information of the nodes, we use graph autoencoder networks to learn multiple representations from complex-graph, inter-graph and intra-graph. Thirdly, a graph-level attention mechanism integration module is adopted to adaptively merge the three representations, and a combined training strategy is performed to optimize the whole model to ensure the complementary and consistency among the multi-graph embedding representations. Finally, multiple classifiers are explored, and Random Forest is used to predict the association score between lncRNA and disease. Experimental results on the public dataset show that the area under receiver operating characteristic curve and area under precision-recall curve of MGATE are 0.964 and 0.413, respectively. MGATE performance significantly outperformed seven state-of-the-art methods. Furthermore, the case studies of three cancers further demonstrate the ability of MGATE to identify potential disease-correlated candidate lncRNAs. The source code and supplementary data are available at https://github.com/sheng-n/MGATE. CONTACT: huanglan@jlu.edu.cn, wy6868@jlu.edu.cn.

Heterogeneous multi-scale neighbor topologies enhanced drug-disease association prediction.

MOTIVATION: Identifying new uses of approved drugs is an effective way to reduce the time and cost of drug development. Recent computational approaches for predicting drug-disease associations have integrated multi-sourced data on drugs and diseases. However, neighboring topologies of various scales in multiple heterogeneous drug-disease networks have yet to be exploited and fully integrated. RESULTS: We propose a novel method for drug-disease association prediction, called MGPred, used to encode and learn multi-scale neighboring topologies of drug and disease nodes and pairwise attributes from heterogeneous networks. First, we constructed three heterogeneous networks based on multiple kinds of drug similarities. Each network comprises drug and disease nodes and edges created based on node-wise similarities and associations that reflect specific topological structures. We also propose an embedding mechanism to formulate topologies that cover different ranges of neighbors. To encode the embeddings and derive multi-scale neighboring topology representations of drug and disease nodes, we propose a module based on graph convolutional autoencoders with shared parameters for each heterogeneous network. We also propose scale-level attention to obtain an adaptive fusion of informative topological representations at different scales. Finally, a learning module based on a convolutional neural network with various receptive fields is proposed to learn multi-view attribute representations of a pair of drug and disease nodes. Comprehensive experiment results demonstrate that MGPred outperforms other state-of-the-art methods in comparison to drug-related disease prediction, and the recall rates for the top-ranked candidates and case studies on five drugs further demonstrate the ability of MGPred to retrieve potential drug-disease associations.

Prediction of drug-disease associations by integrating common topologies of heterogeneous networks and specific topologies of subnets.

MOTIVATION: The development process of a new drug is time-consuming and costly. Thus, identifying new uses for approved drugs, named drug repositioning, is helpful for speeding up the drug development process and reducing development costs. Existing drug-related disease prediction methods mainly focus on single or multiple drug-disease heterogeneous networks. However, heterogeneous networks, and drug subnets and disease subnet contained in heterogeneous networks cover the common topology information between drug and disease nodes, the specific information between drug nodes and the specific information between disease nodes, respectively. RESULTS: We design a novel model, CTST, to extract and integrate common and specific topologies in multiple heterogeneous networks and subnets. Multiple heterogeneous networks composed of drug and disease nodes are established to integrate multiple kinds of similarities and associations among drug and disease nodes. These heterogeneous networks contain multiple drug subnets and a disease subnet. For multiple heterogeneous networks and subnets, we then define the common and specific representations of drug and disease nodes. The common representations of drug and disease nodes are encoded by a graph convolutional autoencoder with sharing parameters and they integrate the topological relationships of all nodes in heterogeneous networks. The specific representations of nodes are learned by specific graph convolutional autoencoders, respectively, and they fuse the topology and attributes of the nodes in each subnet. We then propose attention mechanisms at common representation level and specific representation level to learn more informative common and specific representations, respectively. Finally, an integration module with representation feature level attention is built to adaptively integrate these two representations for final association prediction. Extensive experimental results confirm the effectiveness of CTST. Comparison with six latest methods and case studies on five drugs further verify CTST has the ability to discover potential candidate diseases.

Drp1-dependent mitochondrial fragmentation mediates photoreceptor abnormalities in type 1 diabetic retina.

Recent studies have highlighted that retinal neurodegeneration precedes microvascular changes in diabetic retinopathy (DR), but the specific mechanisms remain unclear. Given the pivotal role of dysfunctional mitochondria and oxidative stress in early DR, our objective was to observe mitochondria-related alterations in the neural retina of type one diabetic mellitus mice with no evidence of DR (T1DM-NDR). We aimed to identify the key mitochondrial-related proteins contributing to mitochondrial injury. Our study revealed that T1DM-NDR mice exhibited outer retina thinning, including the ellipsoid zone, inner segment, and outer segment. Additionally, there was an impaired amplitude of the b-wave in electroretinogram (ERG) and a disorganized arrangement of the photoreceptor layer. In both the retina of DM mice and high glucose (HG)-treated 661w cells, mitochondria appeared swollen and fragmented, with disrupted cristae, disorganized or shortened branches in the mitochondrial network, and decreased mitochondrial membrane potential. Among the mitochondrial-related proteins, dynamin-related protein 1 (Drp1) was upregulated, and the ratio of phosphorylated Drp1 protein at serine 616 (S616) and serine 637 (S637) sites significantly increased in the retina of DM mice. The administration of Mdivi-1 ameliorated high-glucose-induced dysfunctional mitochondria, thereby protecting T1DM-NDR mice retina from morphological and functional injuries. Our findings suggest that hyperglycemia promotes Drp1-mediated mitochondrial dysfunction, which may be a significant factor in the development of DR. The inhibition of high-glucose-induced mitochondrial fission emerges as a potential and innovative intervention strategy for preventing DR.

O-GlcNAcylation: roles and potential therapeutic target for bone pathophysiology.

O-linked N-acetylglucosamine (O-GlcNAc) protein modification (O-GlcNAcylation) is a critical post-translational modification (PTM) of cytoplasmic and nuclear proteins. O-GlcNAcylation levels are regulated by the activity of two enzymes, O-GlcNAc transferase (OGT) and O­GlcNAcase (OGA). While OGT attaches O-GlcNAc to proteins, OGA removes O-GlcNAc from proteins. Since its discovery, researchers have demonstrated O-GlcNAcylation on thousands of proteins implicated in numerous different biological processes. Moreover, dysregulation of O-GlcNAcylation has been associated with several pathologies, including cancers, ischemia-reperfusion injury, and neurodegenerative diseases. In this review, we focus on progress in our understanding of the role of O-GlcNAcylation in bone pathophysiology, and we discuss the potential molecular mechanisms of O-GlcNAcylation modulation of bone-related diseases. In addition, we explore significant advances in the identification of O-GlcNAcylation-related regulators as potential therapeutic targets, providing novel therapeutic strategies for the treatment of bone-related disorders.

Idebenone Antagonizes P53-Mediated Neuronal Oxidative Stress Injury by Regulating CD38-SIRT3 Protein Level.

Idebenone, an antioxidant used in treating oxidative damage-related diseases, has unclear neuroprotective mechanisms. Oxidative stress affects cell and mitochondrial membranes, altering Adp-ribosyl cyclase (CD38) and Silent message regulator 3 (SIRT3) protein expression and possibly impacting SIRT3's ability to deacetylate Tumor protein p53 (P53). This study explores the relationship between CD38, SIRT3, and P53 in H2O2-injured HT22 cells treated with Idebenone. Apoptosis was detected using flow cytometry and terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling (TUNEL) staining after determining appropriate H2O2 and Idebenone concentrations.In this study, Idebenone was found to reduce apoptosis and decrease P53 and Caspase3 expression in H2O2-injured HT22 cells by detecting apoptosis-related protein expression. Through bioinformatics methods, CD38 was identified as the target of Idebenone, and it further demonstrated that Idebenone decreased the expression of CD38 and increased the level of SIRT3. An increased NAD+/NADH ratio was detected, suggesting Idebenone induces SIRT3 expression and protects HT22 cells by decreasing apoptosis-related proteins. Knocking down SIRT3 downregulated acetylated P53 (P53Ac), indicating SIRT3's importance in P53 deacetylation.These results supported that CD38 was used as a target of Idebenone to up-regulate SIRT3 to deacetylate activated P53, thereby protecting HT22 cells from oxidative stress injury. Thus, Idebenone is a drug that may show great potential in protecting against reactive oxygen species (ROS) induced diseases such as Parkinson's disease, and Alzheimer's disease. And it might be able to compensate for some of the defects associated with CD38-related diseases.

Telluride-Based Materials: A Promising Route for High Performance Supercapacitors.

As supercapacitor (SC) technology continues to evolve, there is a growing need for electrode materials with high energy/power densities and cycling stability. However, research and development of electrode materials with such characteristics is essential for commercialization the SC. To meet this demand, the development of superior electrode materials has become an increasingly critical step. The electrochemical performance of SCs is greatly influenced by various factors such as the reaction mechanism, crystal structure, and kinetics of electron/ion transfer in the electrodes, which have been challenging to address using previously investigated electrode materials like carbon and metal oxides/sulfides. Recently, tellurium and telluride-based materials have garnered increasing interest in energy storage technology owing to their high electronic conductivity, favorable crystal structure, and excellent volumetric capacity. This review provides a comprehensive understanding of the fundamental properties and energy storage performance of tellurium- and Te-based materials by introducing their physicochemical properties. First, we elaborate on the significance of tellurides. Next, the charge storage mechanism of functional telluride materials and important synthesis strategies are summarized. Then, research advancements in metal and carbon-based telluride materials, as well as the effectiveness of tellurides for SCs, were analyzed by emphasizing their essential properties and extensive advantages. Finally, the remaining challenges and prospects for improving the telluride-based supercapacitive performance are outlined.

Enhancing the management of locally advanced head and neck malignancies and cases with local/neck recurrence and metastasis through the integration of anlotinib with concurrent radiochemotherapy.

The aim of this study is to assess the effectiveness and safety of anlotinib in conjunction with concurrent radiochemotherapy for the treatment of locally advanced head and neck malignant tumors, including cases exhibiting local or neck recurrence and metastasis. Between June 2020 and June 2023, 42 patients diagnosed with locally advanced head and neck malignant tumors or presenting with local or neck recurrence and metastasis were recruited. These individuals received treatment that combined anlotinib with concurrent radiochemotherapy, followed by a minimum of two cycles of oral anlotinib upon completion of the initial treatment regimen. Among the 19 patients diagnosed with nasopharyngeal carcinoma, 14 patients attained a complete response, while four patients achieved partial response, resulting in an overall response rate of 94.74% (18/19). Conversely, among the 23 patients with non-nasopharyngeal carcinoma, two patients achieved complete response and 16 attained partial response, yielding a response rate of 78.26% (18/23). The 6-month progression-free survival rate was 95.24%. After treatment, serum vascular endothelial growth factor receptor levels exhibited a significant decrease compared with pretreatment levels. Notably, no instances of treatment-related serious adverse reactions were recorded. The combination of anlotinib with concurrent radiochemotherapy demonstrates favorable efficacy in managing locally advanced head and neck malignant tumors, including instances of local or neck recurrence and metastasis. Furthermore, the treatment regimen is characterized by an acceptable safety profile and tolerability.

Functional significance of O-linked N-acetylglucosamine protein modification in regulating autophagy.

Autophagy is a core molecular pathway that preserves cellular and organismal homeostasis. Being susceptible to nutrient availability and stress, eukaryotic cells recycle or degrade internal components via membrane transport pathways to provide sustainable biological molecules and energy sources. The dysregulation of this highly conserved physiological process has been strongly linked to human disease. Post-translational modification, a mechanism that regulates protein function, plays a crucial role in autophagy regulation. O-linked N-acetylglucosamine protein modification (O-GlcNAcylation), a monosaccharide post-translational modification of intracellular proteins, is essential in nutritional and stress regulatory mechanisms. O-GlcNAcylation has emerged as an essential regulatory mechanism of autophagy. It regulates autophagy throughout its lifetime by targeting the core components of the autophagy regulatory network. This review provides an overview of the O-GlcNAcylation of autophagy-associated proteins and their regulation and function in the autophagy pathway. Therefore, this article may contribute to further understanding of the role of O-GlcNAc-regulated autophagy and provide new perspectives for the treatment of human diseases.

Regulation mechanism and bioactivity characteristic of surfactin homologues with C14 and C15 fatty acid chains.

BACKGROUND: Surfactin, a green lipopeptide bio-surfactant, exhibits excellent surface, hemolytic, antibacterial, and emulsifying activities. However, a lack of clear understanding of the synthesis regulation mechanism of surfactin homologue components has hindered the customized production of surfactin products with different biological activities. RESULTS: In this study, exogenous valine and 2-methylbutyric acid supplementation significantly facilitated the production of C14-C15 surfactin proportions (up to 75% or more), with a positive correlation between the homologue proportion and fortified concentration. Subsequently, the branched-chain amino acid degradation pathway and the glutamate synthesis pathway are identified as critical pathways in regulating C14-C15 surfactin synthesis by transcriptome analysis. Overexpression of genes bkdAB and glnA resulted in a 1.4-fold and 1.3-fold increase in C14 surfactin, respectively. Finally, the C14-rich surfactin was observed to significantly enhance emulsification activity, achieving an EI24 exceeding 60% against hexadecane, while simultaneously reducing hemolytic activity. Conversely, the C15-rich surfactin demonstrated an increase in both hemolytic and antibacterial activities. CONCLUSION: This study presents the first evidence of a potential connection between surfactin homologue synthesis and the conversion of glutamate and glutamine, providing a theoretical basis for targeting the synthesis regulation and structure-activity relationships of surfactin and other lipopeptide compounds.

Association between the triglyceride-glucose index and cognitive impairment in China: a community population-based cross-sectional study.

INTRODUCTION: Insulin resistance (IR) is a feature of metabolic syndrome and plays an important role in cognitive impairment (CI). The triglyceride-glucose (TyG) index is a convenient and cost-effective surrogate for assessing IR. This study aimed to assess the association between the TyG index and CI. METHODS: This community population-based cross-sectional study used a cluster-sampling methodology. All participants underwent the education-based Mini-Mental State Examination (MMSE), and those with CI were identified using standard thresholds. The fasting blood triglyceride and glucose levels were measured in the morning, and the TyG index was calculated as ln (½ fasting triglyceride level [mg/dL] × fasting blood glucose level [mg/dL]). Multivariable logistic regression and subgroup analysis were used to assess the relationship between the TyG index and CI. RESULTS: This study included 1484 subjects, of which 93 (6.27%) met the CI criteria. Multivariable logistic regression showed that CI incidence increased by 64% per unit increase in the TyG index (odds ratio [OR] = 1.64, 95% confidence interval [CI]: 1.02-2.63, p = 0.042). CI risk was 2.64-fold higher in the highest TyG index quartile compared to the lowest TyG index quartile (OR = 2.64, 95% CI: 1.19-5.85, p = 0.016). Finally, interaction analysis showed that sex, age, hypertension, and diabetes did not significantly affect the association between the TyG index and CI. CONCLUSION: The present study suggested that an elevated TyG index was associated with a higher CI risk. Subjects with a higher TyG index should manage and treat at an early stage to alleviate the cognitive decline.

Associations Between Metabolic Obesity Phenotypes and Pathological Characteristics of Papillary Thyroid Carcinoma.

OBJECTIVE: The association between obesity, metabolic dysregulation, and the aggressive pathological traits of papillary thyroid carcinoma (PTC) continues to be a contentious issue. To date, no investigations have examined the impact of metabolic status on the malignant pathological features of PTC in relation to obesity. METHODS: This research involved 855 adult patients with PTC from Shandong Provincial Hospital, classified into 4 groups based on metabolic and obesity status: metabolically healthy nonobese, metabolically unhealthy nonobese (MUNO), metabolically healthy obese, and metabolically unhealthy obese. We employed logistic regression to investigate the relationship between these metabolic obesity phenotypes and PTC's pathological characteristics. Mediation analysis was also performed to determine metabolic abnormalities' mediating role in the nexus between obesity and these characteristics. RESULTS: Relative to metabolically healthy nonobese individuals, the metabolically unhealthy obese group was significantly associated with an elevated risk of larger tumor sizes and a greater number of tumor foci in PTC. Mediation analysis indicated that obesity directly influences tumor size, whereas its effect on tumor multifocality is mediated through metabolic dysfunctions. Specifically, high-density lipoprotein cholesterol levels were notably associated with tumor multifocality within obese subjects, serving as a mediator in obesity's impact on this trait. CONCLUSION: The concurrent presence of obesity and metabolic dysregulation is often connected to more aggressive pathological features in PTC. The mediation analysis suggests obesity directly affects tumor size and indirectly influences tumor multifocality via low high-density lipoprotein cholesterol levels.

Hypermethylation of the Bmp4 promoter dampens binding of HIF-1α and impairs its cardiac protective effects from oxidative stress in prenatally GC-exposed offspring.

The exposure to an unhealthy environment in utero can lead to the occurrence of cardiovascular diseases in the offspring. Glucocorticoids (GC) are essential for normal development and maturation of fetal organs and is a first-line treatment for pregnant women affected by autoimmune diseases. However, excess prenatal GC exposure might program the development of fetal organs and cause a number of chronic diseases in later life. Our previous studies indicated that cardiac functions were significantly compromised in rat offspring prenatally exposed to the synthetic glucocorticoid dexamethasone (DEX), only after ischemia-reperfusion. In the present study, we further observed that DNA hypermethylation of bone morphogenetic protein 4 (Bmp4) promoter in cardiomyocytes caused by prenatal DEX exposure substantially dampened the binding activity of transcription factor HIF-1α induced by cardiac ischemia. Therefore, prenatal DEX exposure inhibits the induction of BMP4 upon I/R and attenuates the protective effects of BMP4 in cardiomyocytes, which eventually manifests as malfunction of the adult heart. Moreover, we employed two cardiac-specific Bmp4 knock-in mouse models and found that in vivo BMP4 overexpression could rescue the cardiac dysfunction caused by prenatal GC exposure. In depth mechanistic research revealed that BMP4 protects the cardiomyocytes from mitophagy and apoptosis by attenuating mitochondrial PGC-1α expression in a p-Smad and Parkin-dependent manner. These findings suggest that prenatal GC exposure increases the susceptibility of the offspring's heart to a "second strike" after birth, due to the failure of hypoxia-induced HIF-1α transactivation of the hypermethylated Bmp4 promoter in cardiomyocytes. Pretreatment with the DNA methylation inhibitor, 5-Aza-2'-deoxycytidine, could be a potential therapeutic method for this programming effect of GC exposure during pregnancy on neonatal cardiac dysfunction.

Gastroesophageal reflux disease increases the risk of essential hypertension: results from the Nationwide Readmission Database and Mendelian randomization analysis.

BACKGROUND: The link between gastroesophageal reflux disease (GERD) and essential hypertension (EH) and its causal nature remains controversial. Our study examined the connection between GERD and the risk of hypertension and assessed further whether this correlation has a causal relationship. METHODS: First, we utilized the National Readmission Database including 14 422 183 participants to conduct an observational study. Dividing the population into GERD and non-GERD groups, we investigated the correlation between GERD and EH using multivariate logistic regression. Next, bidirectional two-sample Mendelian randomization was adopted. The summary statistics for GERD were obtained from a published genome-wide association study including 78 707 cases and 288 734 controls. We collected summary statistics for hypertension containing 70 651 cases and 223 663 controls from the FinnGen consortium. We assessed causality primarily by the inverse-variance weighted method with validation by four other Mendelian randomization approaches as well as an array of sensitivity analyses. RESULTS: In the unadjusted model, GERD patients had a higher risk of EH than the non-GERD group, regardless of gender (odds ratio, 1.43; 95% confidence interval: 1.42-1.43; P < .001). Further adjusting for critical confounders did not change this association. For Mendelian randomization, we found that genetically predicted GERD was causally linked to an enhanced risk of EH in inverse-variance weighted technique (odds ratio, 1.52; 95% confidence interval: 1.39-1.67; P = 3.51 × 10-18); conversely, EH did not raise the risk of GERD causally. CONCLUSIONS: GERD is a causal risk factor for EH. Further research is required to probe the mechanism underlying this causal connection.

The Impact of Doctor-Nurse Complementary Model Combined with Disease Tracking on Stroke Patients.

Objective: The incidence of stroke worldwide is increasing year by year. With the enhancement of public health awareness, people's demand for the quality of stroke rehabilitation is getting higher and higher, so better quality care measures are needed in the treatment of stroke. Based on this, this paper explores the impact of a new type of nursing care measure, the complementary health care model combined with condition tracking, on stroke patients. Methods: 238 stroke patients were randomly divided into a conventional group (n=119) and a combined group (n=119). 238 stroke patients were randomly divided into conventional group (n=119) and combined group (n=119). The conventional group received routine care, in which doctors and nursing carried out their own work without cooperation after the patients were admitted to the hospital; the combined group received a complementary health care model and condition tracking, in which doctors and nurses jointly checked the rooms, discussed cases, jointly formulated treatments and nursing care plans, and jointly formulated the patients' discharge and rehabilitation plans after the patients were admitted to the hospital. Before the intervention, at the time of discharge, and 6 months after discharge, the neurological function of the patients in both groups was assessed using the National Institutes of Health Stroke Scale (NIHSS) and the Fugl-Meyer (FMA) scale, the cognitive function of the patients in both groups was assessed using the Montreal Cognitive Assessment (MoCA) scale and the Measured Mental State Examination (MMSE), and the cognitive function of the patients in both groups was assessed using the General Self-Efficacy Scale (GSS) and the Montreal Cognitive Assessment (MCA) scale. General Self-Efficacy Scale (GSES) to assess self-efficacy, Exercise Adherence Questionnaire (EAQ) to assess adherence to functional exercise and Specific Quality of Life Scale (SSQoL-12) to assess the quality of life of patients in both groups, and the self-developed satisfaction with nursing care to assess patients' satisfaction with the care model. Results: Before the intervention, there was no difference in the National Institutes of Health Stroke Scale (NIHSS), the Fugl-Meyer Assessment (FMA), the Montreal Cognitive Assessment (MoCA), the Mental State Examination (MMSE), the General Self-Efficacy Scale (GSES), the Exercise Adherence Questionnaire (EAQ) and the Stroke-Specific Quality of Life Scale-12 (SSQoL-12) scores between the two groups (P > .05). At discharge and six months later, NIHSS scores continued to decrease in both groups, with the joint group being lower than the conventional group (P < .05); scores for all other items continued to increase, with the joint being higher than the conventional group (P < .05). Satisfaction with care was higher in the combined group than in the conventional group (P < .05). Conclusion: The complementary healthcare model combined with condition tracking can effectively promote the prognosis of rehabilitation of stroke patients, and has a positive effect in promoting the recovery of neurological and cognitive functions, strengthening self-efficacy, and improving the quality of life, which can be promoted in the clinic.