Protective effect of salvianolic acid B against myocardial ischemia/reperfusion injury: preclinical systematic evaluation and meta-analysis.

Background: Salvianolic acid B is the most abundant water-soluble component in the traditional Chinese medicine Danshen and can reduce myocardial ischemia-reperfusion (MI/R) injury through multiple targets and pathways. However, the role of SalB in protecting the myocardium from ischemia/reperfusion injury remains unclear. Purpose: To perform a preclinical systematic review and meta-analysis to assess the efficacy of Sal B in an animal model of myocardial infarction/reperfusion (MI/R) and to summarize the potential mechanisms of Sal B against MI/R. Methods: Studies published from inception to March 2024 were systematically searched in PubMed, Web of Science, Embase, China National Knowledge Infrastructure Wanfang, and VIP databases. The methodological quality was determined using the SYRCLE RoB tool. The R software was used to analyze the data. The potential mechanisms are categorized and summarized. Results: 32 studies containing 732 animals were included. The results of the meta-analysis showed that Sal B reduced myocardial infarct size (p < 0.01), and the cardiological indices of CK-MB (p < 0.01), CK (p < 0.01), LDH (p < 0.01), and cTnI (p < 0.01) compared to the control group. In addition, Sal B increased cardiac function indices, such as LVFS (p < 0.01), -dp/dt max (p < 0.01), +dp/dt max (p < 0.01), and cardiac output (p < 0.01). The protective effects of Sal B on the myocardium after I/R may be mediated by attenuating oxidative stress and inflammation, promoting neovascularization, regulating vascular function, and attenuating cardiac myocyte apoptosis. Publication bias was observed in all the included studies. Further studies are required to elucidate the extent of the cardioprotective effects of SalB and the safety of its use. Conclusion: To the best of our knowledge, this is the first meta-analysis of Sal B in the treatment of MI/R injury, and Sal B demonstrated a positive effect on MI/R injury through the modulation of key pathological indicators and multiple signaling pathways. Further studies are needed to elucidate the extent to which SalB exerts its cardioprotective effects and the safety of its use. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/.

Machine learning-based model for worsening heart failure risk in Chinese chronic heart failure patients.

AIMS: This study aims to develop and validate an optimal model for predicting worsening heart failure (WHF). Multiple machine learning (ML) algorithms were compared, and the results were interpreted using SHapley Additive exPlanations (SHAP). A clinical risk calculation tool was subsequently developed based on these findings. METHODS AND RESULTS: This nested case-control study included 200 patients with chronic heart failure (CHF) from the China-Japan Friendship Hospital (September 2019 to December 2022). Sixty-five variables were collected, including basic information, physical and chemical examinations, and quality of life assessments. WHF occurrence within a 3-month follow-up was the outcome event. Variables were screened using LASSO regression, univariate analysis, and comparison of key variables in multiple ML models. Eighty per cent of the data was used for training and 20% for testing. The best models were identified by integrating nine ML algorithms and interpreted using SHAP, and to develop a final risk calculation tool. Among participants, 68 (34.0%) were female, with a mean age (standard deviation, SD) of 68.57 (12.80) years. During the follow-up, 60 participants (30%) developed WHF. N-terminal pro-brain natriuretic peptide (NT-proBNP), creatinine (Cr), uric acid (UA), haemoglobin (Hb), and emotional area score on the Minnesota Heart Failure Quality of Life Questionnaire were critical predictors of WHF occurrence. The random forest (RF) model was the best model to predict WHF with an area under the curve (AUC) (95% confidence interval, CI) of 0.842 (0.675-1.000), accuracy of 0.775, sensitivity of 0.900, specificity of 0.833, negative predictive value of 0.800, and positive predictive value of 0.600 for the test set. SHAP analysis highlighted NT-proBNP, UA, and Cr as significant predictors. An online risk predictor based on the RF model was developed for personalized WHF risk assessment. CONCLUSIONS: This study identifies NT-proBNP, Cr, UA, Hb, and emotional area scores as crucial predictors of WHF in CHF patients. Among the nine ML algorithms assessed, the RF model showed the highest predictive accuracy. SHAP analysis further emphasized NT-proBNP, UA, and Cr as the most significant predictors. An online risk prediction tool based on the RF model was subsequently developed to enhance early and personalized WHF risk assessment in clinical settings.

Colloidal photonic crystals towards biological applications.

Colloidal photonic crystals (CPCs), fabricated from the assembly of micro-/nano-particles, have attracted considerable interest due to their unique properties, such as structural color, slow-photon effect, and high specific surface area (SSA). Benefiting from these properties, significant progress has been made in the biological applications of CPCs. In this perspective, these properties and relative manipulation strategies are firstly discussed, building bridges between properties and biological applications of CPCs. Structural color endows CPCs with naked-eye sensing capability, which can be applied to physiological state assessment and diagnosis, as well as self-report of CPC-based diagnostic and therapeutic devices. The slow-photon effect contributes to enhanced fluorescence, surface-enhanced Raman scattering, and efficacy of photodynamic/photothermal therapy, when CPCs are combined with corresponding functional materials. High SSA provides CPCs with abundant binding sites and superior capabilities for loading, adsorption, delivery, etc. These properties can be utilized individually or synergistically to grant CPCs superior performance in biological applications. Next, the recent advancements of CPCs towards biological applications are summarized, including biosensors, wound dressings, cells-on-a-chip, and phototherapy. Finally, a perspective on the challenges and future development of CPCs for biological applications is presented.

Two-dimensional confined topotactic transformation to produce Co-Pi/Co3O4 hybrid porous nanosheets for promoted water oxidation.

Exploring advanced electrocatalyst for the oxygen evolution reaction (OER) is of great importance in pursuing efficient and sustainable hydrogen production via electrolytic water splitting. Considering the structure-activity-stability relationship for designing advanced OER catalysts, two-dimensional (2D) porous catalyst with single crystallinity is deemed to be an ideal platform which could simultaneously endow enriched active sites, facile mass and charge transport ability as well as robust structural stability. Herein, we proposed a facile 2D confined topotactic phase transformation approach, which realizes the fabrication of highly porous single-crystalline Co3O4 nanosheets with in-situ surface modification of amorphous Co-Pi active species. Benefitted from the highly exposed undercoordinated cobalt sites, facilitated mass transport and facile 2D charge transfer pathway, the Co-Pi/Co3O4 hybrid porous nanosheets display enhanced OER activity with obvious pre-oxidation-induced activation. In addition, the operational stability was significantly improved owing to the strengthened structural stability which effectively buffers the internal strains and avoids the structural collapse during the electrochemical process. This work proposed a facile and mild method for the synthesis of amorphous/single-crystalline hybrid porous materials, and the achievement of synergistic modulation of active site density and charge transfer ability via targeted microstructural construction will shed light on catalyst design in the future.

G-MBRMD: Lightweight liver segmentation model based on guided teaching with multi-head boundary reconstruction mapping distillation.

BACKGROUND AND OBJECTIVES: Liver segmentation is pivotal for the quantitative analysis of liver cancer. Although current deep learning methods have garnered remarkable achievements for medical image segmentation, they come with high computational costs, significantly limiting their practical application in the medical field. Therefore, the development of an efficient and lightweight liver segmentation model becomes particularly important. METHODS: In our paper, we propose a real-time, lightweight liver segmentation model named G-MBRMD. Specifically, we employ a Transformer-based complex model as the teacher and a convolution-based lightweight model as the student. By introducing proposed multi-head mapping and boundary reconstruction strategies during the knowledge distillation process, Our method effectively guides the student model to gradually comprehend and master the global boundary processing capabilities of the complex teacher model, significantly enhancing the student model's segmentation performance without adding any computational complexity. RESULTS: On the LITS dataset, we conducted rigorous comparative and ablation experiments, four key metrics were used for evaluation, including model size, inference speed, Dice coefficient, and HD95. Compared to other methods, our proposed model achieved an average Dice coefficient of 90.14±16.78%, with only 0.6 MB memory and 0.095 s inference speed for a single image on a standard CPU. Importantly, this approach improved the average Dice coefficient of the baseline student model by 1.64% without increasing computational complexity. CONCLUSION: The results demonstrate that our method successfully realizes the unification of segmentation precision and lightness, and greatly enhances its potential for widespread application in practical settings.

Model informed precision medicine of Chinese herbal medicines formulas-A multi-scale mechanistic intelligent model.

Recent trends suggest that Chinese herbal medicine formulas (CHM formulas) are promising treatments for complex diseases. To characterize the precise syndromes, precise diseases and precise targets of the precise targets between complex diseases and CHM formulas, we developed an artificial intelligence-based quantitative predictive algorithm (DeepTCM). DeepTCM has gone through multilevel model calibration and validation against a comprehensive set of herb and disease data so that it accurately captures the complex cellular signaling, molecular and theoretical levels of traditional Chinese medicine (TCM). As an example, our model simulated the optimal CHM formulas for the treatment of coronary heart disease (CHD) with depression, and through model sensitivity analysis, we calculated the balanced scoring of the formulas. Furthermore, we constructed a biological knowledge graph representing interactions by associating herb-target and gene-disease interactions. Finally, we experimentally confirmed the therapeutic effect and pharmacological mechanism of a novel model-predicted intervention in humans and mice. This novel multiscale model opened up a new avenue to combine "disease syndrome" and "macro micro" system modeling to facilitate translational research in CHM formulas.

Photoacoustic Imaging-Guided Self-Adaptive Hyperthermia Supramolecular Cascade Nano-Reactor for Diabetic Periodontal Bone Regeneration.

Commencing with the breakdown of the diabetic osteoimmune microenvironment, multiple pathogenic factors, including hyperglycemia, inflammation, hypoxia, and deleterious cytokines, are conjointly involved in the progression of diabetic periodontal bone regeneration. Based on the challenge of periodontal bone regeneration treatment and the absence of real-time feedback of blood oxygen fluctuation in diabetes mellitus, a novel self-adaptive hyperthermia supramolecular cascade nano-reactor ACFDG is constructed via one-step supramolecular self-assembly strategy to address multiple factors in diabetic periodontal bone regeneration. Hyperthermia supramolecular ACFDG possesses high photothermal conversion efficiency (32.1%), and it can effectively inhibit the vicious cycle of ROS-inflammatory cascade through catalytic cascade reactions, up-regulate the expression of heat shock proteins (HSPs) under near-infrared (NIR) irradiation, which promotes periodontal bone regeneration. Remarkably, ACFDG can provide real-time non-invasive diagnosis of blood oxygen changes during periodontal bone regeneration through photoacoustic (PA) imaging, thus can timely monitor periodontal hypoxia status. In conclusion, this multifunctional supramolecular nano-reactor combined with PA imaging for real-time efficacy monitoring provides important insights into the biological mechanisms of diabetic periodontal bone regeneration and potential clinical theranostics.

​Comprehensive mendelian randomization analysis of plasma proteomics to identify new therapeutic targets for the treatment of coronary heart disease and myocardial infarction.

BACKGROUND: Ischemic heart disease is one of the leading causes of mortality worldwide, and thus calls for development of more effective therapeutic strategies. This study aimed to identify potential therapeutic targets for coronary heart disease (CHD) and myocardial infarction (MI) by investigating the causal relationship between plasma proteins and these conditions. METHODS: A two-sample Mendelian randomization (MR) study was performed to evaluate more than 1600 plasma proteins for their causal associations with CHD and MI. The MR findings were further confirmed through Bayesian colocalization, Summary-data-based Mendelian Randomization (SMR), and Transcriptome-Wide Association Studies (TWAS) analyses. Further analyses, including enrichment analysis, single-cell analysis, MR analysis of cardiovascular risk factors, phenome-wide Mendelian Randomization (Phe-MR), and protein-protein interaction (PPI) network construction were conducted to verify the roles of selected causal proteins. RESULTS: Thirteen proteins were causally associated with CHD, seven of which were also causal for MI. Among them, FES and PCSK9 were causal proteins for both diseases as determined by several analytical methods. PCSK9 was a risk factor of CHD (OR = 1.25, 95% CI: 1.13-1.38, P = 7.47E-06) and MI (OR = 1.36, 95% CI: 1.21-1.54, P = 2.30E-07), whereas FES was protective against CHD (OR = 0.68, 95% CI: 0.59-0.79, P = 6.40E-07) and MI (OR = 0.65, 95% CI: 0.54-0.77, P = 5.38E-07). Further validation through enrichment and single-cell analysis confirmed the causal effects of these proteins. Moreover, MR analysis of cardiovascular risk factors, Phe-MR, and PPI network provided insights into the potential drug development based on the proteins. CONCLUSIONS: This study investigated the causal pathways associated with CHD and MI, highlighting the protective and risk roles of FES and PCSK9, respectively. FES. Specifically, the results showed that these proteins are promising therapeutic targets for future drug development.

Insufficient Sleep is Associated With Increasing Trends in Adolescent Suicidal Behaviors.

PURPOSE: Youth suicide has been increasing and became a public health concern worldwide. Identifying insufficient sleep as the potential risk factor is critical to reducing suicide risk and increasing trends. This study aimed to determine whether insufficient sleep is associated with increasing trends in suicidal behaviors and disparities by sex, age, and race/ethnicity among school adolescents. METHODS: The present study used biennial data from the US nationally representative Youth Risk Behavior Survey from 2007 to 2019. Joinpoint regression models were used to estimate biennial percent changes (BPCs) and average BPCs (ABPCs) of suicidal behaviors by sleep duration. Logistic regression models were used to examine the association between insufficient sleep and suicidal behaviors. RESULTS: Of 73,356 adolescent students included (mean [standard deviation] age, 16.11 [1.23] years), 50.03% were female. Suicidal ideation and suicide plan among insufficient sleep group increased from 2007 to 2019 (BPC = 2.88% [95% confidence interval {CI}: 1.65%, 4.13%]; BPC = 3.42% [95% CI: 2.09%, 4.77%]), but were nonsignificant among sufficient sleep group. Trends in suicidal ideation (ABPC = 3.03% [95% CI: 1.35%, 4.73%]) and suicide plan (ABPC = 4.03% [95% CI: 2.47%, 5.62%]) among female adolescents with insufficient sleep increased, but nonsignificant among male adolescents with insufficient sleep. Suicidal ideation (ABPC = 1.73% [95% CI: 0.51%, 2.97%]) and suicide plan (ABPC = 2.31% [95% CI: 0.70%, 3.95%]) increased among younger adolescents only with insufficient sleep, whereas suicide trends by sleep duration were similar among older adolescents. Suicide plan among insufficient sleep group increased across the four racial groups, with BPC highest for the White (BPC = 3.48% [95% CI: 1.31%, 5.69%]), and lowest for the Hispanic/Latino (BPC = 1.18% [95% CI: 0.15%, 2.23%]), but were nonsignificant among sufficient sleep group except for the White (BPC = 2.83% [95% CI: 0.62%, 5.09%]). DISCUSSION: Insufficient sleep was disproportionately associated with increasing trends in suicidal behaviors among female, younger, and non-White adolescent students. Ensuring sufficient sleep can potentially reduce suicide among school adolescents.

Effects of Habitual Dietary Change on the Gut Microbiota and Health of Silkworms.

Diet plays a crucial role in shaping the gut microbiota and overall health of animals. Traditionally, silkworms are fed fresh mulberry leaves, and artificial diets do not support good health. The aim of this study was to explore the relationship between the dietary transition from artificial diets to mulberry leaves and the effects on the gut microbiota and physiological changes in silkworms as a model organism. With the transition from artificial diets to mulberry leaves, the diversity of the silkworm gut microbiota increased, and the proportion of Enterococcus and Weissella, the dominant gut bacterial species in silkworms reared on artificial diets, decreased, whereas the abundance of Achromobacter and Rhodococcus increased. Dietary transition at different times, including the third or fifth instar larval stages, resulted in significant differences in the growth and development, immune resistance, and silk production capacity of silkworms. These changes might have been associated with the rapid adaptation of the intestinal microbiota of silkworms to dietary transition. This study preliminarily established a dietary transition-gut microbial model in silkworms based on the conversion from artificial diets to mulberry leaves, thus providing an important reference for future studies on the mechanisms through which habitual dietary changes affect host physiology through the gut microbiome.

Hydrogel-Based Biosensors for Bacterial Infections.

Hydrogels are known to have the advantages such as good biodegradability, biocompatibility, and easy functionalization, making them ideal candidates for biosensors. Hydrogel-based biosensors that respond to bacteria-induced microenvironmental changes such as pH, enzymes, antigens, etc., or directly interact with bacterial surface receptors, can be applied for early diagnosis of bacterial infections, providing information for timely treatment while avoiding antibiotic abuse. Furthermore, hydrogel biosensors capable of both bacteria diagnosis and treatment will greatly facilitate the development of point-of-care monitoring of bacterial infections. In this review, the recent advancement of hydrogel-based biosensors for bacterial infection is summarized and discussed. First, the biosensors based on pH-sensitive hydrogels, bacterial-specific secretions-sensitive hydrogels, and hydrogels directly in contact with bacterial surfaces are presented. Next, hydrogel biosensors capable of detecting bacterial infection in the early stage followed by immediate on-demand treatment are discussed. Finally, the challenges and future development of hydrogel biosensors for bacterial infections are proposed.

High-entropy wire-on-sheet nanoarray catalyst with boosted pre-oxidation for efficient oxygen evolution reaction.

Herein, a septenary NiCoZnFeCuMnCe hydroxide nanoarray catalyst with a unique wire-on-sheet morphology and high-entropy feature was fabricated, which exhibits boosted pre-oxidation behavior and synergistically enhanced catalytic activity and durability towards the oxygen evolution reaction.

Increased PDGFRB and NF-κB signaling caused by highly prevalent somatic mutations in intracranial aneurysms.

Intracranial aneurysms (IAs) are a high-risk factor for life-threatening subarachnoid hemorrhage. Their etiology, however, remains mostly unknown at present. We conducted screening for sporadic somatic mutations in 65 IA tissues (54 saccular and 11 fusiform aneurysms) and paired blood samples by whole-exome and targeted deep sequencing. We identified sporadic mutations in multiple signaling genes and examined their impact on downstream signaling pathways and gene expression in vitro and an arterial dilatation model in mice in vivo. We identified 16 genes that were mutated in at least one IA case and found that these mutations were highly prevalent (92%: 60 of 65 IAs) among all IA cases examined. In particular, mutations in six genes (PDGFRB, AHNAK, OBSCN, RBM10, CACNA1E, and OR5P3), many of which are linked to NF-κB signaling, were found in both fusiform and saccular IAs at a high prevalence (43% of all IA cases examined). We found that mutant PDGFRBs constitutively activated ERK and NF-κB signaling, enhanced cell motility, and induced inflammation-related gene expression in vitro. Spatial transcriptomics also detected similar changes in vessels from patients with IA. Furthermore, virus-mediated overexpression of a mutant PDGFRB induced a fusiform-like dilatation of the basilar artery in mice, which was blocked by systemic administration of the tyrosine kinase inhibitor sunitinib. Collectively, this study reveals a high prevalence of somatic mutations in NF-κB signaling pathway-related genes in both fusiform and saccular IAs and opens a new avenue of research for developing pharmacological interventions.

Prevalence, co-occurring difficulties, and risk factors of developmental language disorder: first evidence for Mandarin-speaking children in a population-based study.

Background: Developmental language disorder (DLD) is a condition that significantly affects children's achievement but has been understudied. We aim to estimate the prevalence of DLD in Shanghai, compare the co-occurrence of difficulties between children with DLD and those with typical development (TD), and investigate the early risk factors for DLD. Methods: We estimated DLD prevalence using data from a population-based survey with a cluster random sampling design in Shanghai, China. A subsample of children (aged 5-6 years) received an onsite evaluation, and each child was categorized as TD or DLD. The proportions of children with socio-emotional behavior (SEB) difficulties, low non-verbal IQ (NVIQ), and poor school readiness were calculated among children with TD and DLD. We used multiple imputation to address the missing values of risk factors. Univariate and multivariate regression models adjusted with sampling weights were used to estimate the correlation of each risk factor with DLD. Findings: Of 1082 children who were approached for the onsite evaluation, 974 (90.0%) completed the language ability assessments, of whom 74 met the criteria for DLD, resulting in a prevalence of 8.5% (95% CI 6.3-11.5) when adjusted with sampling weights. Compared with TD children, children with DLD had higher rates of concurrent difficulties, including SEB (total difficulties score at-risk: 156 [17.3%] of 900 TD vs. 28 [37.8%] of 74 DLD, p < 0.0001), low NVIQ (3 [0.3%] of 900 TD vs. 8 [10.8%] of 74 DLD, p < 0.0001), and poor school readiness (71 [7.9%] of 900 TD vs. 13 [17.6%] of 74 DLD, p = 0.0040). After accounting for all other risk factors, a higher risk of DLD was associated with a lack of parent-child interaction diversity (adjusted odds ratio [aOR] = 3.08, 95% CI = 1.29-7.37; p = 0.012) and lower kindergarten levels (compared to demonstration and first level: third level (aOR = 6.15, 95% CI = 1.92-19.63; p = 0.0020)). Interpretation: The prevalence of DLD and its co-occurrence with other difficulties suggest the need for further attention. Family and kindergarten factors were found to contribute to DLD, suggesting that multi-sector coordinated efforts are needed to better identify and serve DLD populations at home, in schools, and in clinical settings. Funding: The study was supported by Shanghai Municipal Education Commission (No. 2022you1-2, D1502), the Innovative Research Team of High-level Local Universities in Shanghai (No. SHSMU-ZDCX20211900), Shanghai Municipal Health Commission (No.GWV-10.1-XK07), and the National Key Research and Development Program of China (No. 2022YFC2705201).

Performance-based neuropsychological assessment tools for executive function among preschoolers in China: A systematic review.

Objective: There is an increasing demand for the assessment of executive function (EF) among Chinese preschoolers. However, there exists methodological and cross-cultural challenges of performance-based EF assessment. The current review aims to 1) identify and summarize the current application of performance-based EF assessment tools for Chinese preschoolers in China and 2) offer recommendation guidelines for different application scenarios, such as clinical or scientific research, and for related personnel.Method: A literature search was conducted from Web of Science, PubMed, PsycInfo, Scopus and China National Knowledge Infrastructure databases. We focused exclusively on performance-based tools assessing EF among children aged three to six years, encompassing tasks of inhibition, working memory, cognitive flexibility, reasoning, problem solving, and/or planning. Clinical (e.g. children with autism spectrum disorders) and multilingual populations residing outside of China (e.g. Chinese Americans) were excluded. Two authors independently screened, extracted, and evaluated each tool for characteristics (e.g. name, domain, type, version, language, approach of administration, and scoring) and sample information (e.g. sample size, age, and region). Results: A total of 98 articles were included, with 255 tools being identified that were further classified into 44 unique types, covering nine EF domains. Most tools were original or informally sinicized, with notable variations in tool selection, administration, and interpretation process. Given that a complete set of EF tools has not been identified as perfectly suitable for Chinese preschoolers, we also offered recommendations based on empirically adapted evaluation criteria. Conclusions: Our findings highlighted the need for appropriate adaptation, administration, and interpretation of the current EF tools.

Long Term Outcomes and Potential Risk Factors for Endovascular Repair of Aortic Pseudoaneurysms in Vascular Behçet's Disease.

OBJECTIVE: This study aimed to analyse long term outcomes and risk factors for endovascular repair of aortic pseudoaneurysms in patients with vascular Behçet's disease (BD). METHODS: Medical records of 26 aortic vascular BD patients who underwent endovascular treatment at the vascular department of Peking Union Medical College Hospital between January 2002 and December 2021 were reviewed retrospectively. Erythrocyte sedimentation rate (ESR) and C reactive protein were used to assess BD activity. Computed tomography angiography (CTA) was obtained pre- and post-operatively for almost all patients. Univariable logistic regression analysis was used to analyse risk factors for endovascular repair, such as inflammatory indicators, drug usage, and stent graft parameters. RESULTS: The abdominal aorta (n = 17) was the most common site of 27 vascular BD pseudoaneurysms in this study. CTA also revealed one aortic arch pseudoaneurysm, seven descending thoracic aortic pseudoaneurysms, one thoraco-abdominal aortic pseudoaneurysm, and one pseudoaneurysm at the aortic bifurcation. Most of the pseudoaneurysms were treated with covered stent grafts. The technical success rate was 96% and no deaths occurred during hospital stay. The mean follow up was 5.8 ± 5.5 years and 31% (8/26) experienced post-operative complications. Overall one, three, and five year event free survival rates were 87%, 78%, and 74%, respectively. Univariable logistic regression analysis revealed that pre-operative ESR ≥ 16.0 mm/h (p = .040), pre-operative glucocorticoid (GC) use ≤ 11.5 days (p = .024), pre-operative immunosuppressant use ≤ 15.5 days (p = .028), and length of proximal landing zone ≤ 1.95 cm (p = .034) were associated with a worse prognoses following endovascular treatment. Proximal oversize ≥ 9.5% (p = .074) was also regarded as a risk factor, although not statistically significant. CONCLUSION: This study further confirmed the feasibility of endovascular repair for aortic vascular BD patients. Risk factors predicting poor prognoses included elevated pre-operative ESR, insufficient pre-operative GC use or immunosuppressant use, inadequate proximal landing zone, and larger proximal oversize percentage.

Combining bioinformatics and machine learning to identify common mechanisms and biomarkers of chronic obstructive pulmonary disease and atrial fibrillation.

Background: Patients with chronic obstructive pulmonary disease (COPD) often present with atrial fibrillation (AF), but the common pathophysiological mechanisms between the two are unclear. This study aimed to investigate the common biological mechanisms of COPD and AF and to search for important biomarkers through bioinformatic analysis of public RNA sequencing databases. Methods: Four datasets of COPD and AF were downloaded from the Gene Expression Omnibus (GEO) database. The overlapping genes common to both diseases were screened by WGCNA analysis, followed by protein-protein interaction network construction and functional enrichment analysis to elucidate the common mechanisms of COPD and AF. Machine learning algorithms were also used to identify key biomarkers. Co-expression analysis, "transcription factor (TF)-mRNA-microRNA (miRNA)" regulatory networks and drug prediction were performed for key biomarkers. Finally, immune cell infiltration analysis was performed to evaluate further the immune cell changes in the COPD dataset and the correlation between key biomarkers and immune cells. Results: A total of 133 overlapping genes for COPD and AF were obtained, and the enrichment was mainly focused on pathways associated with the inflammatory immune response. A key biomarker, cyclin dependent kinase 8 (CDK8), was identified through screening by machine learning algorithms and validated in the validation dataset. Twenty potential drugs capable of targeting CDK8 were obtained. Immune cell infiltration analysis revealed the presence of multiple immune cell dysregulation in COPD. Correlation analysis showed that CDK8 expression was significantly associated with CD8+ T cells, resting dendritic cell, macrophage M2, and monocytes. Conclusions: This study highlights the role of the inflammatory immune response in COPD combined with AF. The prominent link between CDK8 and the inflammatory immune response and its characteristic of not affecting the basal expression level of nuclear factor kappa B (NF-kB) make it a possible promising therapeutic target for COPD combined with AF.

Gastrodia elata Blume: A review of its mechanisms and functions on cardiovascular systems.

Gastrodia elata Blume (GEB), commonly called Tianma in Chinese, is a valuable and extensively used herbal Traditional Chinese Medicine with a wide range of clinical applications. It has been used to treat headaches, dizziness, stroke, epilepsy, amnesia, spasm, and other disorders since ancient times. Hundreds of compounds, including phenols, glycosides, polysaccharides, steroids, organic acids, and others, have been isolated and identified from this plant. Modern pharmacological studies have shown that its active ingredients possess many pharmacological effects, such as neuroprotective, analgesic, sedation and hypnosis, anti-anxiety, anti-depressant, anti-convulsant, anti-dizziness, blood pressure lowering, blood lipids lowering, liver protection, anti-tumor, and immunity enhancement effects. The present review discusses the pharmacological actions and mechanisms of various components of GEB in cardiovascular diseases to provide a reference for further study of GEB.

Open people are more likely to trust their new team members under subliminal influence.

The activation of subliminal stimuli plays an indispensable role in trust research. This study aimed to investigate the effect of subliminal stimuli on team trust and the moderating role of openness on the relationship between subliminal stimuli and team trust. A total of 155 participants were recruited to complete five tasks. The results suggested a significant influence of subliminal stimuli on team trust and the significant moderating role of openness. This study revealed the mechanism of the effect of subliminal stimuli on team trust, which lays an empirical foundation for individualized team trust improvement intervention. The current study provided novel insights that subliminal priming technology offers a new way to improve team trust.