Brain Cell-based Genetic Subtyping and Drug Repositioning for Alzheimer Disease.

Alzheimer's Disease (AD) is characterized by its complex and heterogeneous etiology and gradual progression, leading to high drug failure rates in late-stage clinical trials. In order to better stratify individuals at risk for AD and discern potential therapeutic targets we employed a novel procedure utilizing cell-based co-regulated gene networks and polygenic risk scores (cbPRSs). After defining genetic subtypes using extremes of cbPRS distributions, we evaluated correlations of the genetic subtypes with previously defined AD subtypes defined on the basis of domain-specific cognitive functioning and neuroimaging biomarkers. Employing a PageRank algorithm, we identified priority gene targets for the genetic subtypes. Pathway analysis of priority genes demonstrated associations with neurodegeneration and suggested candidate drugs currently utilized in diabetes, hypertension, and epilepsy for repositioning in AD. Experimental validation utilizing human induced pluripotent stem cell (hiPSC)-derived astrocytes demonstrated the modifying effects of estradiol, levetiracetam, and pioglitazone on expression of APOE and complement C4 genes, suggesting potential repositioning for AD.

M2 Macrophage-Derived Small Extracellular Vesicles Ameliorate Pyroptosis and Intervertebral Disc Degeneration.

Intervertebral discs (IVDs) have a limited self-regenerative capacity and current strategies for IVD regeneration are unsatisfactory. Recent studies showed that small extracellular vesicles derived from M2 macrophage cells (M2-sEVs) inhibited inflammation by delivery of various bioactive molecules to recipient cells, which indicated that M2-sEVs may offer a therapeutic strategy for the repair of IVDs. Herein, we investigated the roles and mechanisms of M2-sEVs on IVD regeneration. The in vitro results demonstrated that M2-sEVs inhibited pyroptosis, preserved cellular viability, and promoted migration of nucleus pulposus cells (NPCs). Bioinformatics analysis and verification experiments of microRNA (miR) expression showed that miR-221-3p was highly expressed in M2-sEVs. The mechanism of action was explored and indicated that M2-sEVs inhibited pyroptosis of NPCs through transfer of miR-221-3p, which suppressed the expression levels of phosphatase and tensin homolog and NOD-, LRR-, and pyrin domain-containing protein 3. Moreover, we fabricated decellularized ECM-hydrogel (dECM) for sustained release of M2-sEVs, which exhibited biocompatibility and controlled release properties. The in vivo results revealed that dECM-hydrogel containing M2-sEVs (dECM/M2-sEVs) delayed the degeneration of intervertebral disc degeneration (IDD) models. In addition to demonstrating a promising therapeutic for IDD, this study provided valuable data for furthering the understanding of the roles and mechanisms of M2-sEVs in IVD regeneration.

Mono-methylation of lysine 27 at histone 3 confers lifelong susceptibility to stress.

Histone post-translational modifications are critical for mediating persistent alterations in gene expression. By combining unbiased proteomics profiling and genome-wide approaches, we uncovered a role for mono-methylation of lysine 27 at histone H3 (H3K27me1) in the enduring effects of stress. Specifically, mice susceptible to early life stress (ELS) or chronic social defeat stress (CSDS) displayed increased H3K27me1 enrichment in the nucleus accumbens (NAc), a key brain-reward region. Stress-induced H3K27me1 accumulation occurred at genes that control neuronal excitability and was mediated by the VEFS domain of SUZ12, a core subunit of the polycomb repressive complex-2, which controls H3K27 methylation patterns. Viral VEFS expression changed the transcriptional profile of the NAc, led to social, emotional, and cognitive abnormalities, and altered excitability and synaptic transmission of NAc D1-medium spiny neurons. Together, we describe a novel function of H3K27me1 in the brain and demonstrate its role as a "chromatin scar" that mediates lifelong stress susceptibility.

Biofilm-producing ability of methicillin-resistant Staphylococcus aureus clinically isolated in China.

BACKGROUND: Staphylococcus aureus, a commensal bacterium, colonizes the skin and mucous membranes of approximately 30% of the human population. Apart from conventional resistance mechanisms, one of the pathogenic features of S. aureus is its ability to survive in a biofilm state on both biotic and abiotic surfaces. Due to this characteristic, S. aureus is a major cause of human infections, with Methicillin-Resistant Staphylococcus aureus (MRSA) being a significant contributor to both community-acquired and hospital-acquired infections. RESULTS: Analyzing non-repetitive clinical isolates of MRSA collected from seven provinces and cities in China between 2014 and 2020, it was observed that 53.2% of the MRSA isolates exhibited varying degrees of ability to produce biofilm. The biofilm positivity rate was notably high in MRSA isolates from Guangdong, Jiangxi, and Hubei. The predominant MRSA strains collected in this study were of sequence types ST59, ST5, and ST239, with the biofilm-producing capability mainly distributed among moderate and weak biofilm producers within these ST types. Notably, certain sequence types, such as ST88, exhibited a high prevalence of strong biofilm-producing strains. The study found that SCCmec IV was the predominant type among biofilm-positive MRSA, followed by SCCmec II. Comparing strains with weak and strong biofilm production capabilities, the positive rates of the sdrD and sdrE were higher in strong biofilm producers. The genetic determinants ebp, icaA, icaB, icaC, icaD, icaR, and sdrE were associated with strong biofilm production in MRSA. Additionally, biofilm-negative MRSA isolates showed higher sensitivity rates to cefalotin (94.8%), daptomycin (94.5%), mupirocin (86.5%), teicoplanin (94.5%), fusidic acid (81.0%), and dalbavancin (94.5%) compared to biofilm-positive MRSA isolates. The biofilm positivity rate was consistently above 50% in all collected specimen types. CONCLUSIONS: MRSA strains with biofilm production capability warrant increased vigilance.

Aggravating effect of abnormal low-density protein cholesterol level on coronary atherosclerotic plaque in type 2 diabetes mellitus patients assessed by coronary computed tomography angiography.

BACKGROUND: The abnormal low-density protein cholesterol (LDL-C) level in the development of atherosclerosis is often comorbid in individuals with type 2 diabetes mellitus(T2DM). This study aimed to investigate the aggravating effect of abnormal LDL-C levels on coronary artery plaques assessed by coronary computed tomography angiography (CCTA) in T2DM. MATERIALS AND METHODS: This study collected 3439 T2DM patients from September 2011 to February 2022. Comparative analysis of differences in coronary plaque characteristics was performed for the patients between the normal LDL-C level group and the abnormal LDL-C level group. Factors with P < 0.1 in the univariable linear regression analyses were included in the multivariable linear stepwise regression. RESULTS: A total of 2820 eligible T2DM patients were included and identified as the normal LDL-C level group (n = 973) and the abnormal LDL-C level group (n = 1847). Compared with the normal LDL-C level group, both on a per-patient basis and per-segment basis, patients with abnormal LDL-C level showed more calcified plaques, partially calcified plaques, low attenuation plaques, positive remodellings, and spotty calcifications. Multivessel obstructive disease (MVD), nonobstructive stenosis (NOS), obstructive stenosis (OS), plaque involvement degree (PID), segment stenosis score (SSS), and segment involvement scores (SIS) were likely higher in the abnormal LDL-C level group than that in the normal LDL-C level group (P < 0.001). In multivariable linear stepwise regression, the abnormal LDL-C level was validated as an independent positive correlation with high-risk coronary plaques and the degree and extent of stenosis caused by plaques (low attenuation plaque: ß = 0.116; positive remodelling: ß = 0.138; spotty calcification: ß = 0.091; NOS: ß = 0.427; OS: ß = 0.659: SIS: ß = 1.114; SSS: ß = 2.987; PID: ß = 2.716, all P value < 0.001). CONCLUSIONS: Abnormal LDL-C levels aggravate atherosclerotic cardiovascular disease (ASCVD) in patients with T2DM. Clinical attention deserves to be caught by the tailored identification of cardiovascular risk categories in T2DM individuals and the achievement of the corresponding LDL-C treatment goal.

Impact of the gut microbiome on atherosclerosis.

Atherosclerosis is a chronic inflammatory metabolic disease with a complex pathogenesis. However, the exact details of its pathogenesis are still unclear, which limits effective clinical treatment of atherosclerosis. Recently, multiple studies have demonstrated that the gut microbiota plays a pivotal role in the onset and progression of atherosclerosis. This review discusses possible treatments for atherosclerosis using the gut microbiome as an intervention target and summarizes the role of the gut microbiome and its metabolites in the development of atherosclerosis. New strategies for the treatment of atherosclerosis are needed. This review provides clues for further research on the mechanisms of the relationship between the gut microbiota and atherosclerosis.

Left Atrial Phasic Function Impairment in Subacute and Chronic Pulmonary Embolism Patients With Different Degrees of Obstruction: An MRI Feature Tracking Study.

BACKGROUND: The alteration of left atrial (LA) phasic function in subacute and chronic pulmonary embolism (PE) patients is unclear. PURPOSE: To investigate LA phasic strain and LA-right ventricular (RV) interaction in subacute and chronic PE patients with different degrees of obstruction by MRI-feature tracking (MRI-FT). STUDY TYPE: Retrospective. POPULATION: One hundred three PE patients (54 subacute [2 weeks to 3 months after initial symptoms], 49 chronic [>3 months after initial symptoms]) and 80 controls. FIELD STRENGTH/SEQUENCE: 3.0 T/balanced steady state free precession sequence. ASSESSMENT: Patients were divided into mild (pulmonary artery obstruction index [PAOI] < 30%, N = 57), moderate (30% ≤ PAOI < 50%, N = 27), and severe (50% ≥ PAOI, N = 19) PE subgroups. LA reservoir, conduit, and active pump longitudinal strains (εs, εe, and εa) and strain rates (SRs, SRe, and SRa) and biventricular global strains were measured. Determinants of LA strains were investigated. STATISTICAL TESTS: ANOVA, t-tests, Mann-Whitney U tests, linear regression. P < 0.05 was considered statistically significant. RESULTS: For both subacute and chronic PE patients, LA reservoir, conduit, and active pump strains and strain rates were significantly lower than in controls. However, there were no significant differences in LA strains between patients with subacute and chronic PE (P = 0.933, 0.625, and 0.630 for εs, εe, and εa). The severe PE subgroup had significantly higher εa and SRa than the mild and moderate PE subgroups. LA strains were significantly correlated with RV diameter and biventricular strains, and RV diameter (ß = -6.836, -4.084, and -1.899 for εs, εe, and εa) was independently associated with LA strains after adjustment for other factors (R2 = 0.627, 0.536, and 0.437 for εs, εe, and εa). DATA CONCLUSION: LA phasic function evaluated by MRI-FT was significantly impaired in subacute and chronic PE patients, and LA active pump function in the severe PE subgroup was higher than that in the mild and moderate PE subgroups. The independent association between RV diameter and LA strains demonstrates that RV diameter may be an important indicator for monitoring LA dysfunction in PE patients. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 3.

Construction of Reverse Type-II InP/ZnxCd1-xS Core/Shell Quantum Dots with Low Interface Strain to Enhance Photocatalytic Hydrogen Evolution.

The InP-based quantum dots (QDs) have attracted much attention in the field of photocatalytic H2 evolution. However, a shell should be used for InP-based photocatalytic systems to passivate the numerous surface defects. Different from the traditional InP-based core/shell QDs with Type-I or Type-II band alignment, herein, the "reverse Type-II" core/shell QDs in which both the conduction and valence bands of shell materials are more negative than those of core materials have been well-designed by regulating the ratio of Cd/Zn of the alloyed ZnxCd1-xS shell. The reverse Type-II band alignment would realize the spatial separation of photogenerated carriers. More importantly, the photogenerated holes tend to rest on the shell in the reverse Type-II QDs, which facilitate hole transfer to the surface, the rate-determining step for solar H2 evolution using QDs. Therefore, the obtained InP/Zn0.25Cd0.75S core/shell QDs exhibit superior photocatalytic activity and stability under visible light irradiation. The rate of solar H2 evolution reaches 376.19 µmol h-1 mg-1 at the initial 46 h, with a turnover number of ∼2,157,000 per QD within 70 h irradiation.

Employing Informatics Strategies in Alzheimer's Disease Research: A Review from Genetics, Multiomics, and Biomarkers to Clinical Outcomes.

Alzheimer's disease (AD) is a critical national concern, affecting 5.8 million people and costing more than 250 billion annually. However, there is no available cure. Thus, effective strategies are in urgent need to discover AD biomarkers for disease early detection and drug development. In this review, we study AD from a biomedical data scientist perspective to discuss the four fundamental components in AD research: genetics (G), molecular multiomics (M), multimodal imaging biomarkers (B), and clinical outcomes (O) (collectively referred to as the GMBO framework). We provide a comprehensive review of common statistical and informatics methodologies for each component within the GMBO framework, accompanied by the major findings from landmark AD studies. Our review highlights the potential of multimodal biobank data in addressing key challenges in AD, such as early diagnosis, disease heterogeneity, and therapeutic development. We identify major hurdles in AD research, including data scarcity and complexity, and advocate for enhanced collaboration, data harmonization, and advanced modeling techniques. This review aims to be an essential guide for understanding current biomedical data science strategies in AD research, emphasizing the need for integrated, multidisciplinary approaches to advance our understanding and management of AD.

Retinal vascular morphological characteristics in diabetic retinopathy: an artificial intelligence study using a transfer learning system to analyze ultra-wide field images.

AIM: To investigate the morphological characteristics of retinal vessels in patients with different severity of diabetic retinopathy (DR) and in patients with or without diabetic macular edema (DME). METHODS: The 239 eyes of DR patients and 100 eyes of healthy individuals were recruited for the study. The severity of DR patients was graded as mild, moderate and severe non-proliferative diabetic retinopathy (NPDR) according to the international clinical diabetic retinopathy (ICDR) disease severity scale classification, and retinal vascular morphology was quantitatively analyzed in ultra-wide field images using RU-net and transfer learning methods. The presence of DME was determined by optical coherence tomography (OCT), and differences in vascular morphological characteristics were compared between patients with and without DME. RESULTS: Retinal vessel segmentation using RU-net and transfer learning system had an accuracy of 99% and a Dice metric of 0.76. Compared with the healthy group, the DR group had smaller vessel angles (33.68±3.01 vs 37.78±1.60), smaller fractal dimension (Df) values (1.33±0.05 vs 1.41±0.03), less vessel density (1.12±0.44 vs 2.09±0.36) and fewer vascular branches (206.1±88.8 vs 396.5±91.3), all P<0.001. As the severity of DR increased, Df values decreased, P=0.031. No significant difference between the DME and non-DME groups were observed in vascular morphological characteristics. CONCLUSION: In this study, an artificial intelligence retinal vessel segmentation system is used with 99% accuracy, thus providing with relatively satisfactory performance in the evaluation of quantitative vascular morphology. DR patients have a tendency of vascular occlusion and dropout. The presence of DME does not compromise the integral retinal vascular pattern.

Multi-organ imaging-derived polygenic indexes for brain and body health.

The UK Biobank (UKB) imaging project is a crucial resource for biomedical research, but is limited to 100,000 participants due to cost and accessibility barriers. Here we used genetic data to predict heritable imaging-derived phenotypes (IDPs) for a larger cohort. We developed and evaluated 4,375 IDP genetic scores (IGS) derived from UKB brain and body images. When applied to UKB participants who were not imaged, IGS revealed links to numerous phenotypes and stratified participants at increased risk for both brain and somatic diseases. For example, IGS identified individuals at higher risk for Alzheimer's disease and multiple sclerosis, offering additional insights beyond traditional polygenic risk scores of these diseases. When applied to independent external cohorts, IGS also stratified those at high disease risk in the All of Us Research Program and the Alzheimer's Disease Neuroimaging Initiative study. Our results demonstrate that, while the UKB imaging cohort is largely healthy and may not be the most enriched for disease risk management, it holds immense potential for stratifying the risk of various brain and body diseases in broader external genetic cohorts.

Cluster Analysis of Cortical Amyloid Burden for Identifying Imaging-driven Subtypes in Mild Cognitive Impairment.

Over the past decade, Alzheimer's disease (AD) has become increasingly severe and gained greater attention. Mild Cognitive Impairment (MCI) serves as an important prodromal stage of AD, highlighting the urgency of early diagnosis for timely treatment and control of the condition. Identifying the subtypes of MCI patients exhibits importance for dissecting the heterogeneity of this complex disorder and facilitating more effective target discovery and therapeutic development. Conventional method uses clinical measurements such as cognitive score and neurophysical assessment to stratify MCI patients into two groups with early MCI (EMCI) and late MCI (LMCI), which shows their progressive stages. However, such clinical method is not designed to de-convolute the heterogeneity of the disorder. This study uses a data-driven approach to divide MCI patients into a novel grouping of two subtypes based on an amyloid dataset of 68 cortical features from positron emission tomography (PET), where each subtype has a homogeneous cortical amyloid burden pattern. Experimental evaluation including visual two-dimensional cluster distribution, Kaplan-Meier plot, genetic association studies, and biomarker distribution analysis demonstrates that the identified subtypes performs better across all metrics than the conventional EMCI and LMCI grouping.

PFERM: A Fair Empirical Risk Minimization Approach with Prior Knowledge.

Fairness is crucial in machine learning to prevent bias based on sensitive attributes in classifier predictions. However, the pursuit of strict fairness often sacrifices accuracy, particularly when significant prevalence disparities exist among groups, making classifiers less practical. For example, Alzheimer's disease (AD) is more prevalent in women than men, making equal treatment inequitable for females. Accounting for prevalence ratios among groups is essential for fair decision-making. In this paper, we introduce prior knowledge for fairness, which incorporates prevalence ratio information into the fairness constraint within the Empirical Risk Minimization (ERM) framework. We develop the Prior-knowledge-guided Fair ERM (PFERM) framework, aiming to minimize expected risk within a specified function class while adhering to a prior-knowledge-guided fairness constraint. This approach strikes a flexible balance between accuracy and fairness. Empirical results confirm its effectiveness in preserving fairness without compromising accuracy.

Interpretability Study for Long Interview Transcripts from Behavior Intervention Sessions for Family Caregivers of Dementia Patients.

Mental health challenges are significant global public health concerns, affecting millions of people and impacting individuals, families, and communities alike. Therapists play a crucial role in supporting those with mental health issues by providing emotional, practical, and financial assistance, as well as facilitating access to treatment and services. Utilizing one-to-one interviews is an effective approach that yields valuable transcripts for further study. In this paper, we focus on interview transcripts between therapists and caregivers with family members suffering from dementia. We propose a method to efficiently handle long interview transcripts for classification. Then we employ the Shapley-value based interpretability technique to identify important contents that significantly contribute to classification results and build a corpus containing sentences potentially beneficial to the therapy. This approach offers valuable insights for enhancing the treatment of mental health issues.

Multivariate mediation analysis with voxel-based morphometry revealed the neurodegeneration pathways from genetic variants to Alzheimer's Disease.

Neurodegenerative processes are increasingly recognized as potential causative factors in Alzheimer's disease (AD) pathogenesis. While many studies have leveraged mediation analysis models to elucidate the underlying mechanisms linking genetic variants to AD diagnostic outcomes, the majority have predominantly focused on regional brain measure as a mediator, thereby compromising the granularity of the imaging data. In our investigation, using the imaging genetics data from a landmark AD cohort, we contrasted both region-based and voxel-based brain measurements as imaging endophenotypes, and examined their roles in mediating genetic effects on AD outcomes. Our findings underscored that using voxel-based morphometry offers enhanced statistical power. Moreover, we delineated specific mediation pathways between SNP, brain volume, and AD outcomes, shedding light on the intricate relationship among these variables.

Topology-based Clustering of Functional Brain Networks in an Alzheimer's Disease Cohort.

Alzheimer's disease is a progressive neurodegenerative disease with many identifying biomarkers for diagnosis. However, whole-brain phenomena, particularly in functional MRI modalities, are not fully understood nor characterized. Here we employ the novel application of topological data analysis (TDA)-based methods of persistent homology to functional brain networks from ADNI-3 cohort to perform a subtyping experiment using unsupervised clustering techniques. We then investigate variations in QT-PAD challenge features across the identified clusters. Using a Wasserstein distance kernel with a variety of clustering algorithms, we found that the 0th-homology Wasserstein distance kernel and spectral clustering yielded clusters with significant differences in whole brain and medial temporal lobe (MTL) volume, thus demonstrating an intrinsic link between whole brain functional topology and brain morphometric structure. These findings demonstrate the importance of MTL in functional connectivity and the efficacy of using TDA-based machine learning methods in network neuroscience and neurodegenerative disease subtyping.

On Transforming Reinforcement Learning With Transformers: The Development Trajectory.

Transformers, originally devised for natural language processing (NLP), have also produced significant successes in computer vision (CV). Due to their strong expression power, researchers are investigating ways to deploy transformers for reinforcement learning (RL), and transformer-based models have manifested their potential in representative RL benchmarks. In this paper, we collect and dissect recent advances concerning the transformation of RL with transformers (transformer-based RL (TRL)) to explore the development trajectory and future trends of this field. We group the existing developments into two categories: architecture enhancements and trajectory optimizations, and examine the main applications of TRL in robotic manipulation, text-based games (TBGs), navigation, and autonomous driving. Architecture enhancement methods consider how to apply the powerful transformer structure to RL problems under the traditional RL framework, facilitating more precise modeling of agents and environments compared to traditional deep RL techniques. However, these methods are still limited by the inherent defects of traditional RL algorithms, such as bootstrapping and the "deadly triad". Trajectory optimization methods treat RL problems as sequence modeling problems and train a joint state-action model over entire trajectories under the behavior cloning framework; such approaches are able to extract policies from static datasets and fully use the long-sequence modeling capabilities of transformers. Given these advancements, the limitations and challenges in TRL are reviewed and proposals regarding future research directions are discussed. We hope that this survey can provide a detailed introduction to TRL and motivate future research in this rapidly developing field.

Effect of Sacubitril/Valsartan on Cognitive Function in Patients With Heart Failure With Preserved Ejection Fraction: A Prespecified Analysis of PARAGON-HF.

BACKGROUND: A hypothetical concern has been raised that sacubitril/valsartan might cause cognitive impairment because neprilysin is one of several enzymes degrading amyloid-ß peptides in the brain, some of which are neurotoxic and linked to Alzheimer-type dementia. To address this, we examined the effect of sacubitril/valsartan compared with valsartan on cognitive function in patients with heart failure with preserved ejection fraction in a prespecified substudy of PARAGON-HF (Prospective Comparison of Angiotensin Receptor Neprilysin Inhibitor With Angiotensin Receptor Blocker Global Outcomes in Heart Failure With Preserved Ejection Fraction). METHODS: In PARAGON-HF, serial assessment of cognitive function was conducted in a subset of patients with the Mini-Mental State Examination (MMSE; score range, 0-30, with lower scores reflecting worse cognitive function). The prespecified primary analysis of this substudy was the change from baseline in MMSE score at 96 weeks. Other post hoc analyses included cognitive decline (fall in MMSEs score of ≥3 points), cognitive impairment (MMSE score <24), or the occurrence of dementia-related adverse events. RESULTS: Among 2895 patients included in the MMSE substudy with baseline MMSE score measured, 1453 patients were assigned to sacubitril/valsartan and 1442 to valsartan. Their mean age was 73 years, and the median follow-up was 32 months. The mean±SD MMSE score at randomization was 27.4±3.0 in the sacubitril/valsartan group, with 10% having an MMSE score <24; the corresponding numbers were nearly identical in the valsartan group. The mean change from baseline to 96 weeks in the sacubitril/valsartan group was -0.05 (SE, 0.07); the corresponding change in the valsartan group was -0.04 (0.07). The mean between-treatment difference at week 96 was -0.01 (95% CI, -0.20 to 0.19; P=0.95). Analyses of a ≥3-point decline in MMSE, decrease to a score <24, dementia-related adverse events, and combinations of these showed no difference between sacubitril/valsartan and valsartan. No difference was found in the subgroup of patients tested for apolipoprotein E ε4 allele genotype. CONCLUSIONS: Patients with heart failure with preserved ejection fraction in PARAGON-HF had relatively low baseline MMSE scores. Cognitive change, measured by MMSE, did not differ between treatment with sacubitril/valsartan and treatment with valsartan in patients with heart failure with preserved ejection fraction. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT01920711.

Endoscopic resection for esophageal gastrointestinal stromal tumors: a multi-center feasibility study.

Background: Esophageal gastrointestinal stromal tumors (E-GISTs) are highly uncommon and have not been thoroughly examined. Objectives: The objective of this multi-center study was to assess the viability of endoscopic resection (ER) in the treatment of E-GISTs and to explore its clinical implications. Design: This was a multi-center retrospective study. Consecutive patients referred to the four participating centers. Methods: E-GISTs among the consecutive subepithelial tumors (SETs) treated by ER methods were enrolled from April 2019 to August 2022. Clinicopathological, endoscopic, and follow-up data were collected and analyzed. Results: A total of 23 patients with E-GISTs were included for analysis, accounting for 1.9% of all the esophageal SETs (1243 patients). The average size of the tumor lesions was 2.3 cm (range 1.0-4.0 cm). We observed that tumors larger than 2.0 cm were more likely to grow deeper, with a statistically significant difference (p < 0.001). End bloc resection was achieved in all 23 patients. The mean operation time was 53.6 min (range 25-111 min). One patient experienced significant intraoperative bleeding, which was promptly managed endoscopically without necessitating surgery. The average hospital stay was 4.5 days (range 3-8 days). The overall median follow-up period was 31 months (range 13-47 months). No tumor recurrence, residual tumor, distal metastasis, or death was observed during the follow-up period. Conclusion: Based on our limited data, our study indicates that ER may be a feasible and effective option for treating esophageal GISTs measuring 4 cm or less. We suggest submucosal tunnel endoscopic resection as the preferred approach, as all E-GISTs in our study were situated in the muscularis propria layer. Additionally, tumors larger than 2 cm were more prone to deeper growth or extraluminal extension.

Impact of Functional Mitral Regurgitation on Left Ventricular Strain in Nonischemic Dilated Cardiomyopathy Patients with Type 2 Mellitus Diabetes: A Magnetic Resonance Feature Tracking Study.

BACKGROUND: The impact of functional mitral regurgitation and type 2 mellitus diabetes (T2DM) on left ventricular (LV) strain in nonischemic dilated cardiomyopathy (NIDCM) patients remains unclear. PURPOSE: To evaluate the impact of mitral regurgitation severity on LV strain, and explore additive effect of T2DM on LV function across varying mitral regurgitation severity levels in NIDCM patients. STUDY TYPE: Retrospective. POPULATION: 352 NIDCM (T2DM-) patients (49.1 ± 14.6 years, 67% male) (207, 85, and 60 no/mild, moderate, and severe mitral regurgitation) and 96 NIDCM (T2DM+) patients (55.2 ± 12.4 years, 77% male) (47, 30, and 19 no/mild, moderate, and severe mitral regurgitation). FIELD STRENGTH/SEQUENCE: 3.0 T/balanced steady-state free precession sequence. ASSESSMENT: LV geometric parameters and strain were measured and compared among groups. Determinants of LV strain were investigated. STATISTICAL TEST: Student's t-test, Mann-Whitney U test, one-way ANOVA, Kruskal-Wallis test, univariable and multivariable linear regression. P < 0.05 was considered statistically significant. RESULTS: LV GLPS and longitudinal PDSR decreased gradually with increasing mitral regurgitation severity in NIDCM patients with T2DM(GLPS: -5.7% ± 2.1% vs. -4.3% ± 1.6% vs. -2.6% ± 1.3%; longitudinal PDSR:0.5 ± 0.2 sec-1 vs. 0.4 ± 0.2 sec-1 vs. 0.3 ± 0.1 sec-1). NIDCM (T2DM+) demonstrated decreased GCPS and GLPS in the no/mild subgroup, reduced LV GCPS, GLPS, and longitudinal PDSR in the moderate subgroup, and reduced GRPS, GCPS, GLPS, and longitudinal PDSR in the severe subgroup compared with NIDCM (T2DM-) patients. Multivariable regression analysis identified that mitral regurgitation severity (ß = -0.13, 0.15, and 0.25 for GRPS, GCPS, and GLPS) and the presence of T2DM (ß = 0.14 and 0.13 for GCPS and GLPS) were independent determinants of LV strains in NIDCM patients. DATA CONCLUSION: Increased mitral regurgitation severity is associated with reduced LV strains in NIDCM patients with T2DM. The presence of T2DM exacerbated the decline of LV function across various mitral regurgitation levels in NIDCM patients, resulting in reduced LV strains. TECHNICAL EFFICACY: Stage 3.