Minimally invasive palliative treatment of malignant tracheoesophageal fistula using cardiac septal occluder.

INTRODUCTION: Tracheoesophageal fistula (TEF) especially malignant TEF (mTEF) is an uncommon yet critical medical condition necessitating immediate intervention. This life-threatening condition frequently manifests in critically ill patients who are dependent on prolonged mechanical ventilation and are unsuitable candidates for thoracotomy due to their compromised health status. The Management of these mTEF patients remain a significant challenge.This study aimed to evaluate the safety and efficacy of using a cardiac septal occluder for the closure of mTEF. METHODS: 8 patients with mTEF underwent closure surgery using atrial/ventricular septal defect (ASD/VSD) septal occluders at the Respiratory Department of HuBei Yichang Central People's Hospital from 2021 to 2023. The procedure involved percutaneous placement of the occluder through the fistula to achieve closure. RESULTS: The placement of the cardiac septal occluder was successfully achieved with ease and efficiency in all patients. The study demonstrated that the use of cardiac septal occluder therapy in patients with mTEF can alleviate symptoms, improve quality of life, and enhance survival rates, with no significant complications observed. Furthermore, the study provided comprehensive details on surgical indications, preoperative evaluation and diagnosis, selection of occluder, methods of occlusion, and postoperative care. CONCLUSIONS: The application of cardiac septal occluder in the treatment of mTEF is a safe and effective palliative treatment. This approach may be particularly beneficial for patients with a high risk of complications and mortality associated with traditional surgical interventions.

Modulation format recognition in a UVLC system based on an ultra-lightweight model with communication-informed knowledge distillation.

Modulation format recognition (MFR) is a key technology for adaptive optical systems, but it faces significant challenges in underwater visible light communication (UVLC) due to the complex channel environment. Recent advances in deep learning have enabled remarkable achievements in image recognition, owing to the powerful feature extraction of neural networks (NN). However, the high computational complexity of NN limits their practicality in UVLC systems. This paper proposes a communication-informed knowledge distillation (CIKD) method that achieves high-precision and low-latency MFR with an ultra-lightweight student model. The student model consists of only one linear dense layer under a communication-informed auxiliary system and is trained under the guidance of a high-complexity and high-precision teacher model. The MFR task involves eight modulation formats: PAM4, QPSK, 8QAM-CIR, 8QAM-DIA, 16QAM, 16APSK, 32QAM, and 32APSK. Experimental results show that the student model based on CIKD can achieve comparable accuracy to the teacher model. After knowledge transfer, the prediction accuracy of the student model can be increased by up to 87%. Besides, it is worth noting that CIKD's inference accuracy can reach up to 100%. Moreover, the parameters constituting the student model in CIKD correspond to merely 18% of the parameters found in the teacher model, which facilitates the hardware deployment and online data processing of MFR algorithms in UVLC systems.

[Factors associated with the care needs of the older adults based on different disability levels].

OBJECTIVE: To identify the factors associated with the care needs of the older adults aged 65-105 by age groups, and to compare these factors across different age groups. METHODS: A total of 12 244 older adults from the Chinese longitudinal healthy longevity survey (CLHLS) conducted in 2018 were included in the analyses. The participants were categorized into three age groups: young-old (aged 65-79), middle-old (aged 80-89), and oldest-old (aged 90-105). The level of disability was measured by the disability index (DI) in four dimensions, reflecting their care needs. Potential factors associated with care needs were selected based on the health ecological model (HEM), including perspectives of personal characteristics, behavioral characteristics, interpersonal network, living and working conditions, and policy environment. Multifactor analysis was performed using multinomial Logistic regression. RESULTS: Among China ' s 12 244 older adults, 43.4% had medium or high care needs. Factors for higher care needs of older adults included higher age, higher number of chronic diseases, no exercise habit, excessive sleep duration (≥9 h/d), depressive tendency, living with children or spouse, and uneducated (all P < 0.05). In addition, the young-old group who were past smokers (OR=2.009, 95% CI: 1.019-3.959), were past drinkers (OR=2.213, 95% CI: 1.141-4.291), and reported self-perceived poverty (OR=2.051, 95% CI: 1.189-3.540), had higher level of care needs. The middle-old group who were female (OR=1.373, 95% CI: 1.038-1.817), never drank alcohol (OR=1.551, 95% CI: 1.059-2.269), and were lack of medical insurance (OR=1.598, 95% CI: 1.053-2.426), and had higher level of care needs. The oldest-old group who were female (medium care needs vs. low care needs: OR=1.412, 95% CI: 1.062-1.878; high care needs vs. low care needs: OR=1.506, 95% CI: 1.137-1.993), reported self-perceived poverty (OR=2.064, 95% CI: 1.282-3.323), and were lack of medical insurance (OR=1.621, 95% CI: 1.148-2.291), and had higher level of care needs. CONCLUSION: The identical factors associated with care needs across different age groups include age, chronic disease, exercise, sleep, depression, living arrangement, and education. Smoking, alcohol consumption, and economic status are specific factors among the young-old group of the older adults, while gender and medical insurance are specific factors among the middle-old and the oldest-old group of the older adults. We recommend conducting prospective cohort studies and intervention studies among specific age groups on the above factors to provide reliable evidence for policy formulation.

Ion pair sites for efficient electrochemical extraction of uranium in real nuclear wastewater.

Electrochemical uranium extraction from nuclear wastewater represents an emerging strategy for recycling uranium resources. However, in nuclear fuel production which generates the majority of uranium-containing nuclear wastewater, fluoride ion (F-) co-exists with uranyl (UO22+), resulting in the complex species of UO2Fx and thus decreasing extraction efficiency. Herein, we construct Tiδ+-PO43- ion pair extraction sites in Ti(OH)PO4 for efficient electrochemical uranium extraction in wastewater from nuclear fuel production. These sites selectively bind with UO2Fx through the combined Ti-F and multiple O-U-O bonds. In the uranium extraction, the uranium species undergo a crystalline transition from U3O7 to K3UO2F5. In real nuclear wastewater, the uranium is electrochemically extracted with a high efficiency of 99.6% and finally purified as uranium oxide powder, corresponding to an extraction capacity of 6829 mg g-1 without saturation. This work paves an efficient way for electrochemical uranium recycling in real wastewater of nuclear production.

Potential Gradient-Driven Dual-Functional Electrochromic and Electrochemical Device Based on a Shared Electrode Design.

The integration of electrochromic devices and energy storage systems in wearable electronics is highly desirable yet challenging, because self-powered electrochromic devices often require an open system design for continuous replenishment of the strong oxidants to enable the coloring/bleaching processes. A self-powered electrochromic device has been developed with a close configuration by integrating a Zn/MnO2 ionic battery into the Prussian blue (PB)-based electrochromic system. Zn and MnO2 electrodes, as dual shared electrodes, the former one can reduce the PB electrode to the Prussian white (PW) electrode and serves as the anode in the battery; the latter electrode can oxidize the PW electrode to its initial state and acts as the cathode in the battery. The bleaching/coloring processes are driven by the gradient potential between Zn/PB and PW/MnO2 electrodes. The as-prepared Zn||PB||MnO2 system demonstrates superior electrochromic performance, including excellent optical contrast (80.6%), fast self-bleaching/coloring speed (2.0/3.2 s for bleaching/coloring), and long-term self-powered electrochromic cycles. An air-working Zn||PB||MnO2 device is also developed with a 70.3% optical contrast, fast switching speed (2.2/4.8 s for bleaching/coloring), and over 80 self-bleaching/coloring cycles. Furthermore, the closed nature enables the fabrication of various flexible electrochromic devices, exhibiting great potentials for the next-generation wearable electrochromic devices.

Advances in sequencing and omics studies in prostate cancer: unveiling molecular pathogenesis and clinical applications.

Background: Prostate cancer (PCa) is one of the most threatening health problems for the elderly males. However, our understanding of the disease has been limited by the research technology for a long time. Recently, the maturity of sequencing technology and omics studies has been accelerating the studies of PCa, establishing themselves as an essential impetus in this field. Methods: We assessed Web of Science (WoS) database for publications of sequencing and omics studies in PCa on July 3rd, 2023. Bibliometrix was used to conduct ulterior bibliometric analysis of countries/affiliations, authors, sources, publications, and keywords. Subsequently, purposeful large amounts of literature reading were proceeded to analyze research hotspots in this field. Results: 3325 publications were included in the study. Research associated with sequencing and omics studies in PCa had shown an obvious increase recently. The USA and China were the most productive countries, and harbored close collaboration. CHINNAIYAN AM was identified as the most influential author, and CANCER RESEARCH exhibited huge impact in this field. Highly cited publications and their co-citation relationships were used to filtrate literatures for subsequent literature reading. Based on keyword analysis and large amounts of literature reading, 'the molecular pathogenesis of PCa' and 'the clinical application of sequencing and omics studies in PCa' were summarized as two research hotspots in the field. Conclusion: Sequencing technology had a deep impact on the studies of PCa. Sequencing and omics studies in PCa helped researchers reveal the molecular pathogenesis, and provided new possibilities for the clinical practice of PCa.

Enrichment of Nutmeg Essential Oil from Oil-in-Water Emulsions with PAN-Based Membranes.

This study used polyacrylonitrile (PAN) and heat-treated polyacrylonitrile (H-PAN) membranes to enrich nutmeg essential oils, which have more complex compositions compared with common oils. The oil rejection rate of the H-PAN membrane was higher than that of the PAN membrane for different oil concentrations of nutmeg essential oil-in-water emulsions. After heat treatment, the H-PAN membrane showed a smaller pore size, narrower pore size distribution, a rougher surface, higher hydrophilicity, and higher oleophobicity. According to the GC-MS results, the similarities of the essential oils enriched by the PAN and H-PAN membranes to those obtained by steam distillation (SD) were 0.988 and 0.990, respectively. In addition, these two membranes also exhibited higher essential oil rejection for Bupleuri Radix, Magnolia Officinalis Cortex, Caryophylli Flos, and Cinnamomi Cortex essential oil-in-water emulsions. This work could provide a reference for membrane technology for the non-destructive separation of oil with complex components from oil-in-water emulsions.

Development of novel N-aryl-2,4-bithiazole-2-amine-based CYP1B1 degraders for reversing drug resistance.

Extrahepatic cytochrome P450 1B1 (CYP1B1), which is highly expressed in non-small cell lung cancer, is an attractive target for cancer prevention, therapy, and overcoming drug resistance. Historically, CYP1B1 inhibition has been the primary therapeutic approach for treating CYP1B1-related malignancies, but its success has been limited. This study introduced CYP1B1 degradation as an alternative strategy to counter drug resistance and metastasis in CYP1B1-overexpressing non-small cell lung cancer A549/Taxol cells via a PROTAC strategy. Our investigation revealed that the identification of the potent CYP1B1 degrader PV2, achieving DC50 values of 1.0 nM and inducing >90 % CYP1B1 degradation at concentrations as low as 10 nM in A549/Taxol cells. Importantly, PV2 enhanced the sensitivity of the A549/Taxol subline to Taxol, possibly due to its stronger inhibitory effects on P-gp through CYP1B1 degradation. Additionally, compared to the CYP1B1 inhibitor A1, PV2 effectively suppressed the migration and invasion of A549/Taxol cells by inhibiting the FAK/SRC and EMT pathways. These findings hold promise for a novel therapy targeting advanced CYP1B1+ non-small cell lung cancer.

Genome-wide association analyses of breast cancer in women of African ancestry identify new susceptibility loci and improve risk prediction.

We performed genome-wide association studies of breast cancer including 18,034 cases and 22,104 controls of African ancestry. Genetic variants at 12 loci were associated with breast cancer risk (P < 5 × 10-8), including associations of a low-frequency missense variant rs61751053 in ARHGEF38 with overall breast cancer (odds ratio (OR) = 1.48) and a common variant rs76664032 at chromosome 2q14.2 with triple-negative breast cancer (TNBC) (OR = 1.30). Approximately 15.4% of cases with TNBC carried six risk alleles in three genome-wide association study-identified TNBC risk variants, with an OR of 4.21 (95% confidence interval = 2.66-7.03) compared with those carrying fewer than two risk alleles. A polygenic risk score (PRS) showed an area under the receiver operating characteristic curve of 0.60 for the prediction of breast cancer risk, which outperformed PRS derived using data from females of European ancestry. Our study markedly increases the population diversity in genetic studies for breast cancer and demonstrates the utility of PRS for risk prediction in females of African ancestry.

Magnesium Ions Promote the Induction of Immunosuppressive Bone Microenvironment and Bone Repair through HIF-1α-TGF-ß Axis in Dendritic Cells.

The effect of immunoinflammation on bone repair during the recovery process of bone defects needs to be further explored. It is reported that Mg2+ can promote bone repair with immunoregulatory effect, but the underlying mechanism on adaptive immunity is still unclear. Here, by using chitosan and hyaluronic acid-coated Mg2+ (CSHA-Mg) in bone-deficient mice, it is shown that Mg2+ can inhibit the activation of CD4+ T cells and increase regulatory T cell formation by inducing immunosuppressive dendritic cells (imDCs). Mechanistically, Mg2+ initiates the activation of the MAPK signaling pathway through TRPM7 channels on DCs. This process subsequently induces the downstream HIF-1α expression, a transcription factor that amplifies TGF-ß production and inhibits the effective T cell function. In vivo, knock-out of HIF-1α in DCs or using a HIF-1α inhibitor PX-478 reverses inhibition of bone inflammation and repair promotion upon Mg2+-treatment. Moreover, roxadustat, which stabilizes HIF-1α protein expression, can significantly promote immunosuppression and bone repair in synergism with CSHA-Mg. Thus, the findings identify a key mechanism for DCs and its HIF-1α-TGF-ß axis in the induction of immunosuppressive bone microenvironment, providing potential targets for bone regeneration.

An ensemble penalized regression method for multi-ancestry polygenic risk prediction.

Great efforts are being made to develop advanced polygenic risk scores (PRS) to improve the prediction of complex traits and diseases. However, most existing PRS are primarily trained on European ancestry populations, limiting their transferability to non-European populations. In this article, we propose a novel method for generating multi-ancestry Polygenic Risk scOres based on enSemble of PEnalized Regression models (PROSPER). PROSPER integrates genome-wide association studies (GWAS) summary statistics from diverse populations to develop ancestry-specific PRS with improved predictive power for minority populations. The method uses a combination of L 1 (lasso) and L 2 (ridge) penalty functions, a parsimonious specification of the penalty parameters across populations, and an ensemble step to combine PRS generated across different penalty parameters. We evaluate the performance of PROSPER and other existing methods on large-scale simulated and real datasets, including those from 23andMe Inc., the Global Lipids Genetics Consortium, and All of Us. Results show that PROSPER can substantially improve multi-ancestry polygenic prediction compared to alternative methods across a wide variety of genetic architectures. In real data analyses, for example, PROSPER increased out-of-sample prediction R2 for continuous traits by an average of 70% compared to a state-of-the-art Bayesian method (PRS-CSx) in the African ancestry population. Further, PROSPER is computationally highly scalable for the analysis of large SNP contents and many diverse populations.

Sucrose-associated SnRK1a1-mediated phosphorylation of Opaque2 modulates endosperm filling in maize.

During maize endosperm filling, sucrose not only serves as a source of carbon skeletons for storage-reserve synthesis but also acts as a stimulus to promote this process. However, the molecular mechanisms underlying sucrose and endosperm filling are poorly understood. In this study, we found that sucrose promotes the expression of endosperm-filling hub gene Opaque2 (O2), coordinating with storage-reserve accumulation. We showed that the protein kinase SnRK1a1 can attenuate O2-mediated transactivation, but sucrose can release this suppression. Biochemical assays revealed that SnRK1a1 phosphorylates O2 at serine 41 (S41), negatively affecting its protein stability and transactivation ability. We observed that mutation of SnRK1a1 results in larger seeds with increased kernel weight and storage reserves, while overexpression of SnRK1a1 causes the opposite effect. Overexpression of the native O2 (O2-OE), phospho-dead (O2-SA), and phospho-mimetic (O2-SD) variants all increased 100-kernel weight. Although O2-SA seeds exhibit smaller kernel size, they have higher accumulation of starch and proteins, resulting in larger vitreous endosperm and increased test weight. O2-SD seeds display larger kernel size but unchanged levels of storage reserves and test weight. O2-OE seeds show elevated kernel dimensions and nutrient storage, like a mixture of O2-SA and O2-SD seeds. Collectively, our study discovers a novel regulatory mechanism of maize endosperm filling. Identification of S41 as a SnRK1-mediated phosphorylation site in O2 offers a potential engineering target for enhancing storage-reserve accumulation and yield in maize.

Residual Partial Least Squares Learning: Brain Cortical Thickness Simultaneously Predicts Eight Non-pairwise-correlated Behavioural and Disease Outcomes in Alzheimer's Disease.

Alzheimer's Disease (AD) is the leading cause of dementia. It results in cortical thickness changes and is associated with a decline in cognition and behaviour. Such decline affects multiple important day-to-day functions, including memory, language, orientation, judgment and problem-solving. Recent research has made important progress in identifying brain regions associated with single outcomes, such as individual AD status and general cognitive decline. The complex projection from multiple brain areas to multiple AD outcomes, however, remains poorly understood. This makes the assessment and especially the prediction of multiple AD outcomes - each of which may unveil an integral yet different aspect of the disease - challenging, particularly when some are not strongly correlated. Here, uniting residual learning, partial least squares (PLS), and predictive modelling, we develop an explainable, generalisable, and reproducible method called the Residual Partial Least Squares Learning (the re-PLS Learning) to (1) chart the pathways between large-scale multivariate brain cortical thickness data (inputs) and multivariate disease and behaviour data (outcomes); (2) simultaneously predict multiple, non-pairwise-correlated outcomes; (3) control for confounding variables (e.g., age and gender) affecting both inputs and outcomes and the pathways in-between; (4) perform longitudinal AD disease status classification and disease severity prediction. We evaluate the performance of the proposed method against a variety of alternatives on data from AD patients, subjects with mild cognitive impairment (MCI), and cognitively normal individuals (n=1,196) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Our results unveil pockets of brain areas in the temporal, frontal, sensorimotor, and cingulate areas whose cortical thickness may be respectively associated with declines in different cognitive and behavioural subdomains in AD. Finally, we characterise re-PLS' geometric interpretation and mathematical support for delivering meaningful neurobiological insights and provide an open software package (re-PLS) available at https://github.com/thanhvd18/rePLS.

MUSSEL: Enhanced Bayesian polygenic risk prediction leveraging information across multiple ancestry groups.

Polygenic risk scores (PRSs) are now showing promising predictive performance on a wide variety of complex traits and diseases, but there exists a substantial performance gap across populations. We propose MUSSEL, a method for ancestry-specific polygenic prediction that borrows information in summary statistics from genome-wide association studies (GWASs) across multiple ancestry groups via Bayesian hierarchical modeling and ensemble learning. In our simulation studies and data analyses across four distinct studies, totaling 5.7 million participants with a substantial ancestral diversity, MUSSEL shows promising performance compared to alternatives. For example, MUSSEL has an average gain in prediction R2 across 11 continuous traits of 40.2% and 49.3% compared to PRS-CSx and CT-SLEB, respectively, in the African ancestry population. The best-performing method, however, varies by GWAS sample size, target ancestry, trait architecture, and linkage disequilibrium reference samples; thus, ultimately a combination of methods may be needed to generate the most robust PRSs across diverse populations.

Genomic Insights for Personalized Care: Motivating At-Risk Individuals Toward Evidence-Based Health Practices.

Lung cancer and tobacco use pose significant global health challenges and require a comprehensive translational roadmap for improved prevention strategies. We propose the GREAT care paradigm ( G enomic Informed Care for Motivating High R isk Individuals E ligible for Evidence-b a sed Prevention), which employs polygenic risk scores (PRSs) to stratify disease risk and personalize interventions, such as lung cancer screening and tobacco treatment. We developed PRSs using large-scale multi-ancestry genome-wide association studies and adjusted for genetic ancestry for standardized risk stratification across diverse populations. We applied our PRSs to over 340,000 individuals of diverse ethnic background and found significant odds ratios for lung cancer and difficulty quitting smoking. These findings enable the evaluation of PRS-based interventions in ongoing trials aimed at motivating health behavior changes in high-risk patients. This pioneering approach enhances primary care with genomic insights, promising improved outcomes in cancer prevention and tobacco treatment, and is currently under assessment in clinical trials.

Synergistic control potential of flue gas pollutants under Ultra-Low emission standards in waste incineration plants.

As the dominant waste disposal process, incineration is regarded as the main incentive for the "not-in-my-backyard" syndrome, and faces an inescapable pressures of ultra-low emissions (ULE). Establishing precise response relationships between emission factors (EFs) and full-process influencing factors can provide guidance for the synergistic mitigation of flue gas pollutants (FGPs). In this work, the multi-dimensional EFs of FGPs were identified by initially integrating FGPs concentration monitoring data of existing 1,226 processing lines in China, technologies applied and operational experience (OE), local economic and political characteristics. Significant regional imbalance performance was observed, which EFs in the coastal regions were 3.55-92.39 % lower than those of the inland areas. NOx, SO2, HCl were identified as critical components requiring further reduction under the ULE standards, with exceedance rates recorded at 73.07 %, 38.90 %, and 56.69 %, respectively. An indicative value of 20 mg/m3 for PM is recommended for the control of heavy metals of Cd + Tl and Sb + As + Pb + Cr + Co + Cu + Mn + Ni based on the correlation coefficients of r = 0.28 (p < 0.001) and r = 0.20 (p = 0.002), respectively. Waste composition and OE were quantified as the main contributors of EFs' disparities by the tree-branching controlled variable approach established in this study. Predictive models for FGPs control process and corresponding EFs were constructed. EFs of nine FGPs in 2030 would decrease by 0.97-65.42 %, due to more complex purification processes employed to meet ULE's limitations, such as the application of five-stage processes growing from 45.60 % to 58.28 %. While regional imbalance in EFs-SO2 and EFs-HCl were extended with increases from 25.83 % to 33.07 % and 9.91 % to 32.32 %, respectively, due to the consistent disparities of OE and growing heterogeneity of control policies. Enhancing interregional empirical exchanges, reducing the regional market monopolies, and formulating technical guidelines would be beneficial to synergize the reduction of FGPs emissions and alleviate regional imbalance.

Admix-kit: an integrated toolkit and pipeline for genetic analyses of admixed populations.

SUMMARY: Admixed populations, with their unique and diverse genetic backgrounds, are often underrepresented in genetic studies. This oversight not only limits our understanding but also exacerbates existing health disparities. One major barrier has been the lack of efficient tools tailored for the special challenges of genetic studies of admixed populations. Here, we present admix-kit, an integrated toolkit and pipeline for genetic analyses of admixed populations. Admix-kit implements a suite of methods to facilitate genotype and phenotype simulation, association testing, genetic architecture inference, and polygenic scoring in admixed populations. AVAILABILITY AND IMPLEMENTATION: Admix-kit package is open-source and available at https://github.com/KangchengHou/admix-kit. Additionally, users can use the pipeline designed for admixed genotype simulation available at https://github.com/UW-GAC/admix-kit_workflow.

Improving Fine Particle Removal Using a Single-Channel Slit Bubbling Device in Wet Flue Gas Desulfurization System.

To improve the cleanliness of coal-fired power plants' particulate matter emissions, a novel device (single-channel slit bubbling particle removal device (SCSB-PRD)) is proposed to improve the wet flue gas desulfurization system's (WFGDs) collaborative particle removal effect. Actual coal-fired flue gas was used to test the particle removal performance. The results showed that the flue gas temperature had no obvious effect on the scrubbing effect of the SCSB-PRD. The scrubbing space, scrubbing liquid volume, and flue gas flow rate effectively changed the gas-liquid flow state, and the bubbling state was the key factor in particle removal. The jet-bubbling contact state was more conducive to removing particles than the foam bubbling state. The jet-bubbling state improved the removal efficiency of fine particles by approximately 30% compared to the foam bubbling state. The device operated in a single stage, and the removal performance of the particulate matter reached more than 60%. Even the submicron particles had a satisfactory removal performance of greater than 50%. The particulate matter concentration at the outlet of the WFGDs was reduced to less than 10 mg/m3, which provides a feasible transformation path for ultraultra-low emissions of particulate matter from coal-fired power plants.

Association between triglyceride-glucose index and endothelial dysfunction.

BACKGROUND: Triglyceride-glucose (TyG) index, a simple surrogate marker for insulin resistance (IR), has been reported as an independent predictor of arterial structural damage and future cardiovascular events. The association between TyG index and endothelial dysfunction remains uncertain. OBJECTIVE: The purpose of this study was to investigate the association between TyG index and endothelial dysfunction. METHODS: Endothelial dysfunction was measured using flow-mediated dilation (FMD). A total of 840 subjects, who voluntarily accepted FMD measurement at the Health Management Department of Xuanwu Hospital from October 2016 to January 2020, were included in this study. TyG index was calculated as Ln [fasting triglyceride (TG)(mg/dL) × fasting plasma glucose (FPG) (mg/dL)/2]. RESULTS: The mean age was 59.92 ± 10.28 years and 559 (66.55%) participants were male. The TyG index was correlated with FMD values (P = 0.022). Each unit increment in TyG index was associated with lower FMD values (ß = -0.330, 95%CI -0.609 to -0.052, P = 0.020) after adjusting for covariates. Age (ß = -0.069, 95%CI -0.088 to -0.051, P < 0.001), female (ß = 0.592, 95%CI 0.172 to1.012, P = 0.006), smoking (ß = -0.430, 95%CI -0.859 to -0.002, P = 0.049) and hypertension (ß = -0.741, 95%CI -1.117 to -0.365, P < 0.001) were also independent predictors for endothelial dysfunction. A significant association between the TyG index and endothelial dysfunction was found only in populations younger than 60 years (ß = -0.843, 95%CI -1.371 to -0.316, P = 0.002), females (ß = -0.612, 95%CI -1.147 to -0.077, P = 0.025), and populations without diabetes mellitus (DM) (ß = -0.594, 95%CI -1.042 to -0.147, P = 0.009). CONCLUSIONS: Subjects with an elevated TyG index are more likely to have endothelial dysfunction, particularly in populations without DM.

Insights into the selective mechanism of PDE2/9a inhibitors from silico aspects.

The selective design of competitive enzyme inhibitors is an extremely difficult task but necessary work for certain types of systems, such as the phosphodiesterase (PDE) system addressed in this article. In the PDE family, PDE2A and PDE9 respectively target the central nervous system and heart failure, and share many conserved amino acids at their binding sites. Therefore, gaining a deep understanding of the selective mechanisms of PDE2A/9A is crucial for designing highly selective drugs. In this study, various computer-aided drug design (CADD) methods, including molecular docking, molecular dynamics simulations (MD), and binding free energy calculations, are employed to explore the selective mechanisms of PDE2A/9A. Overall, our research results indicate a selective design strategy for PDE2A, which involves incorporating hydrophobic or aromatic moieties into the molecular structure to better accommodate the hydrophobic pocket of PDE2A. Additionally, it is recommended to introduce functional groups capable of forming connections with selective residues, such as Phe830 and Gln812 for PDE2A, or Ala452 and Tyr424 for PDE9A, to enhance the selectivity of inhibitors targeting PDE2A/9A. This achievement is anticipated to pave the way for the development of innovative and selective small molecules targeting PDE2A/9A.Communicated by Ramaswamy H. Sarma.