The tumour suppressor Fat1 is dispensable for normal murine hematopoiesis.

Loss and overexpression of FAT1 occurs among different cancers with these divergent states equated with tumor suppressor and oncogene activity, respectively. Regarding the latter, FAT1 is highly expressed in a high proportion of human acute leukemias relative to normal blood cells, with evidence pointing to an oncogenic role. We hypothesized that this occurrence represents legacy expression of FAT1 in undefined hematopoietic precursor subsets that is sustained following transformation, predicating a role for FAT1 during normal hematopoiesis. We explored this concept by using the Vav-iCre strain to construct conditional knockout (cKO) mice where Fat1 expression was deleted at the hematopoietic stem cell stage. Extensive analysis of precursor and mature blood populations using multi-panel flow cytometry revealed no ostensible differences between Fat1 cKO mice and normal littermates. Further functional comparisons involving colony forming unit and competitive bone marrow transplantation assays support the conclusion that Fat1 is dispensable for normal murine hematopoiesis.

The minimum mass ratio of W UMa-type contact binaries-a new calculation.

A model is developed to establish the relationship between the critical gyration radius k of the primary component and the mass ratio (q) by considering the different dimensionless gyration radii of main-sequence stars with varying masses. The next step involves obtaining the low mass ratio limit ( q min = 0.038 ∼ 0.041 for overcontact degree f = 0 ~ 1) of W UMa-type contact binaries. Furthermore, the radial density distributions are estimated within the range of 0.3 M ⊙ ∼ 4.0 M ⊙ , based on the mass-radius relationship of main-sequence stars. Subsequently, the physical meaning of the minimum k value is proposed, which leads to an explanation for the cause of the minimum mass ratio. Finally, a stability criterion is proposed, which is based on both the mass ratio (q) and the total mass of the two components ( M tot ).

Synthesis and crystal structure of the cluster (Et4N)[(Tp*)MoFe3S3(µ3-NSiMe3)(N3)3].

The title compound, tetra-ethyl-ammonium tri-azido-tri-µ3-sulfido-[µ3-(tri-methyl-sil-yl)aza-nediido][tris-(3,5-di-methyl-pyrazol-1-yl)hydro-borato]triiron(+2.33)molybdenum(IV), (C8H20N)[Fe3MoS3(C15H22BN6)(C3H9NSi)(N3)3] or (Et4N)[(Tp*)MoFe3S3(µ3-NSiMe3)(N3)3] [Tp* = tris-(3,5-di-methyl-pyrazol-1-yl)hydro-bor-ate(1-)], crystallizes as needle-like black crystals in space group P . In this cluster, the Mo site is in a distorted octa-hedral coordination model, coordinating three N atoms on the Tp* ligand and three µ3-bridging S atoms in the core. The Fe sites are in a distorted tetra-hedral coordination model, coordinating two µ3-bridging S atoms, one µ3-bridging N atom from Me3SiN2-, and another N atom on the terminal azide ligand. This type of heterometallic and heteroleptic single cubane cluster represents a typical example within the Mo-Fe-S cluster family, which may be a good reference for understanding the structure and function of the nitro-genase FeMo cofactor. The residual electron density of disordered solvent mol-ecules in the void space could not be reasonably modeled, thus the SQUEEZE [Spek (2015). Acta Cryst. C71, 9-18] function was applied. The solvent contribution is not included in the reported mol-ecular weight and density.

Integrating gated recurrent unit in graph neural network to improve infectious disease prediction: an attempt.

Objective: This study focuses on enhancing the precision of epidemic time series data prediction by integrating Gated Recurrent Unit (GRU) into a Graph Neural Network (GNN), forming the GRGNN. The accuracy of the GNN (Graph Neural Network) network with introduced GRU (Gated Recurrent Units) is validated by comparing it with seven commonly used prediction methods. Method: The GRGNN methodology involves multivariate time series prediction using a GNN (Graph Neural Network) network improved by the integration of GRU (Gated Recurrent Units). Additionally, Graphical Fourier Transform (GFT) and Discrete Fourier Transform (DFT) are introduced. GFT captures inter-sequence correlations in the spectral domain, while DFT transforms data from the time domain to the frequency domain, revealing temporal node correlations. Following GFT and DFT, outbreak data are predicted through one-dimensional convolution and gated linear regression in the frequency domain, graph convolution in the spectral domain, and GRU (Gated Recurrent Units) in the time domain. The inverse transformation of GFT and DFT is employed, and final predictions are obtained after passing through a fully connected layer. Evaluation is conducted on three datasets: the COVID-19 datasets of 38 African countries and 42 European countries from worldometers, and the chickenpox dataset of 20 Hungarian regions from Kaggle. Metrics include Average Root Mean Square Error (ARMSE) and Average Mean Absolute Error (AMAE). Result: For African COVID-19 dataset and Hungarian Chickenpox dataset, GRGNN consistently outperforms other methods in ARMSE and AMAE across various prediction step lengths. Optimal results are achieved even at extended prediction steps, highlighting the model's robustness. Conclusion: GRGNN proves effective in predicting epidemic time series data with high accuracy, demonstrating its potential in epidemic surveillance and early warning applications. However, further discussions and studies are warranted to refine its application and judgment methods, emphasizing the ongoing need for exploration and research in this domain.

Control of large amplitude limit cycle of a multi-dimensional nonlinear dynamic system of a composite cantilever beam.

For the first time, a control strategy based on Fuzzy Sliding Mode Control is implemented in the control of a large amplitude limit cycle of a composite cantilever beam in a multi-dimensional nonlinear form. In the dynamic model establishment of the investigated structure, the higher-order shearing effect is applied, as well as the second-order discretization. Numerical simulation demonstrates that a multi-dimensional nonlinear dynamic system of the investigated structure is demanded for accurate estimation of large amplitude limit cycle responses. Therefore, a control strategy is employed to effectively suppress such responses of the beam in multi-dimensional nonlinear form.

Salidroside Ameliorates Lung Injury Induced by PM 2.5by Regulating SIRT1-PGC-1α in Mice.

Objective: This study aimed to clarify the intervention effect of salidroside (SAL) on lung injury caused by PM 2.5 in mice and illuminate the function of SIRT1-PGC-1ɑ axis. Methods: Specific pathogen-free (SPF) grade male C57BL/6 mice were randomly assigned to the following groups: control group, SAL group, PM 2.5 group, SAL+PM 2.5 group. On the first day, SAL was given by gavage, and on the second day, PM 2.5 suspension was given by intratracheal instillation. The whole experiment consist of a total of 10 cycles, lasting 20 days. At the end of treatment, blood samples and lung tissues were collected and analyzed. Observation of pathological changes in lung tissue using inverted microscopy and transmission electron microscopy. The expression of inflammatory, antioxidants, apoptosis, and SIRT1-PGC-1ɑ proteins were detected by Western blotting. Results: Exposure to PM 2.5 leads to obvious morphological and pathologica changes in the lung of mice. PM 2.5 caused a decline in levels of antioxidant-related enzymes and protein expressions of HO-1, Nrf2, SOD2, SIRT1 and PGC-1ɑ, and an increase in the protein expressions of IL-6, IL-1ß, Bax, caspase-9 and cleaved caspase-3. However, SAL reversed the aforementioned changes caused by PM 2.5 by activating the SIRT1-PGC-1α pathway. Conclusion: SAL can activate SIRT1-PGC-1ɑ to ameliorate PM 2.5-induced lung injury.

Mitochondrial genomes of four slug moths (Lepidoptera, Limacodidae): Genome description and phylogenetic implications.

The family Limacodidae belongs to the superfamily Zygaenoidea, which includes 1672 species commonly referred to as slug moths. Limacodidae larvae are major pests for many economically important plant species and can cause human dermatitis. At present, the structure of the mitochondrial genome (mitogenome), phylogenetic position, and adaptive evolution of slug moths are poorly understood. Herein, the mitogenomes of Parasa lepida, Phlossa conjuncta, Thosea sinensis, and Setora sinensis were sequenced and compared with other available mitogenome sequences to better characterize the mitogenomic diversity and evolution of this moth family. The mitogenomes of P. lepida, P. conjuncta, T. sinensis, and S. sinensis were confirmed to be circular in structure with lengths of 15,575 bp, 15,553 bp, 15,535 bp, and 15,529 bp, respectively. The Limacodidae mitogenomes exhibited similar nucleotide composition, codon usage, RNA structure, and control region patterns, indicating the conservation of the mitogenome in the family Limacodidae. A sliding window, Ka/Ks, and genetic distance analyses revealed that the atp8 and nad6 genes exhibited the highest levels of variability and the most rapid evolutionary rates among the 13 protein-coding genes (PCGs) encoded in these Limacodidae mitogenomes, suggesting that they may offer value as candidate DNA markers. The phylogenetic analysis recovered the overall relationship as Tortricoidea + (Sesiidae + (Zygaenoidea + (Cossoidea/+Choreutoidea + (others)))). Within Zygaenoidea, Limacodidae was recovered as monophyletic, and the phylogenetic relationships were recovered as (Phaudidae + Zyganidae) + Limacodidae in all six phylogenetic trees. The analysis indicated that P. lepida, P. conjuncta, T. sinensis, and S. sinensis are members of the Limacodidae.

A contrastive learning approach to integrate spatial transcriptomics and histological images.

The rapid growth of spatially resolved transcriptomics technology provides new perspectives on spatial tissue architecture. Deep learning has been widely applied to derive useful representations for spatial transcriptome analysis. However, effectively integrating spatial multi-modal data remains challenging. Here, we present ConGcR, a contrastive learning-based model for integrating gene expression, spatial location, and tissue morphology for data representation and spatial tissue architecture identification. Graph convolution and ResNet were used as encoders for gene expression with spatial location and histological image inputs, respectively. We further enhanced ConGcR with a graph auto-encoder as ConGaR to better model spatially embedded representations. We validated our models using 16 human brains, four chicken hearts, eight breast tumors, and 30 human lung spatial transcriptomics samples. The results showed that our models generated more effective embeddings for obtaining tissue architectures closer to the ground truth than other methods. Overall, our models not only can improve tissue architecture identification's accuracy but also may provide valuable insights and effective data representation for other tasks in spatial transcriptome analyses.

M6A RNA methylation-mediated dysregulation of AGAP2-AS1 promotes trastuzumab resistance of breast cancer.

INTRODUCTION: Trastuzumab is commonly used in the treatment of human epidermal growth factor receptor-2 positive (HER-2+) breast cancer patients, but its efficacy is often limited by chemotherapy resistance. Recent studies indicate that long noncoding RNAs (lncRNAs) play important roles in tumor progression and response to therapy. However, the regulatory mechanism of lncRNAs in trastuzumab resistance is still unknown to date. METHODS: qPCR was performed to detect the expression of related genes. Western blot and immunofluorescence assays were used for the evaluation of protein expression levels. A series of gain- or loss-functional assays confirmed the function of AGAP2-AS1 in trastuzumab resistance, both in vitro and in vivo. RNA immunoprecipitation and pulldown analysis was conducted to verify the interaction between METTL3/YTHDF2 and lncRNA AGAP2-AS1. , Results: AGAP2-AS1 was upregulated in trastuzumab-resistant cells and SKBR-3R-generated xenograft in nude mice. Silence of AGAP2-AS1 significantly decreased trastuzumab-induced cell cytotoxicity both in vitro and in vivo. The m6A methylation of AGAP2-AS1 was found to be reduced in trastuzumab resistant cells compared to parental cells. In addition, METTL3 increased the m6A methylation of AGAP2-AS1, which finally induced the suppression of AGAP2-AS1 expression. Moreover, YTHDF2 was essential for METTL3-mediated m6A methylation of AGAP2-AS1. Functionally, AGAP2-AS1 regulated trastuzumab resistance via inducing autophagy and increasing ATG5 protein level. CONCLUSION: Taken together, we proved that METTL3/YTHDF2-mediated m6A methylation indued the increased expression AGAP2-AS1, which could promote the trastuzumab resistance of breast cancer. In addition, AGAP2-AS1 also regulates trastuzumab resistance via inducing autophagy. Therefore, AGAP2-AS1 may be promising predictive biomarker and therapeutic target breast cancer patients.

Controlling the nutritional status score: a new tool for predicting postoperative mortality in patients with infrarenal abdominal aortic aneurysm treated with endovascular aneurysm repair.

Background: AAA is a fatal condition that commonly occurs during vascular surgery. Nutritional status exerts a significant influence on the prognosis of various pathological conditions Scores from the CONUT screening tool have been shown to predict outcomes of certain malignancies and chronic diseases. However, the ramifications of nutritional status on AAA patients undergoing EVAR have not been elucidated in prior studies. In this study, we aimed to elucidate the correlation between CONUT scores and postoperative prognostic outcomes in patients with AAA undergoing EVAR. Methods: This was a retrospective review of 177 AAA patients treated with EVAR from June 2018 to November 2019 in a single center. Patient characteristics, CONUT scores, and postoperative status were collected. These patients were stratified into groups A and B according to CONUT scores. Subsequently, a comparative analysis of the baseline characteristics between the two cohorts was conducted. Cox proportional hazards and logistic regression analyses were employed to identify the autonomous predictors of mid-term mortality and complications, respectively. Results: Compared with group A, patients in group B had higher midterm mortality (p < 0.001). Univariate analysis showed that CONUT scores; respiratory diseases; stent types; preoperative Hb, CRP, PT, and Fb levels were risk factors for death. Multivariate analysis confirmed that CONUT score [HR, 1.276; 95% CI, 1.029-1.584; p = 0.027] was an independent risk factor for mortality. Logistic regression analysis showed that prior arterial disease, smoking, and D-dimer levels were risk factors, although multivariate analysis showed smoking (OR, 3.492; 95% CI, 1.426-8.553; p = 0.006) was an independent risk factor. Kaplan-Meier curves showed that patients in group B had shorter mid-term survival than those in group A (log-rank p < 0.001). Conclusion: Malnutrition was strongly associated with mid-term mortality in patients with infrarenal AAA treated with EVAR.

scBSP: A fast and accurate tool for identifying spatially variable genes from spatial transcriptomic data.

Spatially resolved transcriptomics have enabled the inference of gene expression patterns within two and three-dimensional space, while introducing computational challenges due to growing spatial resolutions and sparse expressions. Here, we introduce scBSP, an open-source, versatile, and user-friendly package designed for identifying spatially variable genes in large-scale spatial transcriptomics. scBSP implements sparse matrix operation to significantly increase the computational efficiency in both computational time and memory usage, processing the high-definition spatial transcriptomics data for 19,950 genes on 181,367 spots within 10 seconds. Applied to diverse sequencing data and simulations, scBSP efficiently identifies spatially variable genes, demonstrating fast computational speed and consistency across various sequencing techniques and spatial resolutions for both two and three-dimensional data with up to millions of cells. On a sample with hundreds of thousands of sports, scBSP identifies SVGs accurately in seconds to on a typical desktop computer.

Mild-Temperature Supercritical Water Confined in Hydrophobic Metal-Organic Frameworks.

Fluids under extreme confinement show characteristics significantly different from those of their bulk counterpart. This work focuses on water confined within the complex cavities of highly hydrophobic metal-organic frameworks (MOFs) at high pressures. A combination of high-pressure intrusion-extrusion experiments with molecular dynamic simulations and synchrotron data reveals that supercritical transition for MOF-confined water takes place at a much lower temperature than in bulk water, ∼250 K below the reference values. This large shifting of the critical temperature (Tc) is attributed to the very large density of confined water vapor in the peculiar geometry and chemistry of the cavities of Cu2tebpz (tebpz = 3,3',5,5'-tetraethyl-4,4'-bipyrazolate) hydrophobic MOF. This is the first time the shift of Tc is investigated for water confined within highly hydrophobic nanoporous materials, which explains why such a large reduction of the critical temperature was never reported before, neither experimentally nor computationally.

Laparoscopic ileocecal-sparing vs traditional right hemicolectomy for cancer of the hepatic flexure or proximal transverse colon: a dual-center propensity score-matched study.

Background: Traditional right hemicolectomy (TRH) is the standard treatment for patients with nonmetastatic right colon cancer. However, the ileocecum, a vital organ with mechanical and immune functions, is removed in these patients regardless of the tumor location. This study aimed to evaluate the technical and oncological safety of laparoscopic ileocecal-sparing right hemicolectomy (LISH). Method: Patients who underwent LISH at two tertiary medical centers were matched 1:2 with patients who underwent TRH by propensity score matching based on sex, age, body mass index, tumor location, and disease stage. Data on surgical and perioperative outcomes were collected. Oncological safety was evaluated in a specimen-oriented manner. Lymph nodes (LNs) near the ileocolic artery (ICA) were examined independently in the LISH group. Disease outcomes were recorded for patients who completed one year of follow-up. Results: In all, 34 patients in the LISH group and 68 patients in the TRH group were matched. LISH added 8 minutes to the dissection of LNs around the ileocolic vessels (groups 201/201d, 202, and 203 LNs), without affecting the total operation time, blood loss, or perioperative adverse event rate. Compared with TRH, LISH had a comparable lymphadenectomy quality, specimen quality, and safety margin while preserving a more functional bowel. The LISH group had no cases of LN metastasis near the ICA. No difference was detected in the recurrence rate at the 1-year follow-up time point between the two groups. Conclusion: In this dual-center study, LISH presented comparable surgical and oncological safety for patients with hepatic flexure or proximal transverse colon cancer.

Microarray analysis of microrna expression in peripheral blood mononuclear cells of patients with polymyositis and dermatomyositis.

Background and Objectives: MicroRNAs (miRNAs) represent a new class of biomarkers in the context of connective tissue disorders. The miRNA expression profiles in peripheral blood mononuclear cells (PBMCs) of patients with polymyositis (PM) and dermatomyositis (DM) have not been fully elucidated. The objective is to investigate miRNAs expression profile in PBMCs of patients with PM/DM. Methods: Microarray technology was used to identify differentially expressed miRNAs in PBMCs obtained from 6 untreated PM/DM patients and 3 healthy controls (HCs). TaqMan-based stem-loop real-time PCR detection was used for validation in a cohort of 34 PM/DM patients and 20 HCs. Results: Microarray analysis revealed 38 differentially expressed miRNAs (24 up-regulated and 14 down-regulated) in PM/DM patients compared to HCs. Four miRNAs (miR-320a, miR-335-3p, miR-34a-5p and miR-454-3p) were chosen for real-time PCR validation. The expression of miR-34a-5p was significantly upregulated in PM/DM group (P < 0.05). In subgroup analysis, miR-34a-5p was significantly upregulated in interstitial lung disease (ILD) group and DM group (P < 0.001). The level of SIRT1, a validated target of miR-34a, was significantly lower in PBMCs of PM/DM patients compared with HCs. Conclusions: MiR-34a-5p may potentially participate in the pathogenesis of PM/DM through SIRT1, and may serve as a potential new biomarker for PM/DM-ILD.

Diagnostic Efficiency of ACR-TIRADS Score for Differentiating Benign and Malignant Thyroid Nodules of Various Pathological Types.

BACKGROUND Thyroid nodule prevalence reaches 65% in the general population. Hence, appropriate ultrasonic examination is key in disease monitoring and management. We investigated the American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS) score for diagnosis of benign and malignant thyroid nodules and pathological types. MATERIAL AND METHODS A retrospective study was conducted. According to ultrasound images, ultrasonic characteristics of benign and malignant thyroid nodules and different pathological types were analyzed using ACR-TIRADS score, and diagnostic value was determined. AUCs were compared for tumor diagnosis and differentiation. RESULTS Overall, 1675 thyroid nodules from 1614 patients were included. AUC value of papillary thyroid carcinoma (PTC) diagnosed with ACR-TIRADS was highest (0.955 [95% CI=0.946-0.965]), while that of follicular thyroid carcinoma (FTC) was lowest (0.877 [95% CI=0.843-0.912]). FTC had the highest sensitivity (95.1%) and lowest specificity (64.8%). When the cut-off value was 5.5 points, accuracy of diagnosing PTC and anaplastic thyroid carcinoma (ATC) was highest, 80.5% and 78.7% respectively. Comparison of the multi-index prediction model constructed by multivariable logistic regression analysis and prediction model constructed by ACR-TIRADS score showed, when evaluating PTC and ATC, the multi-index model was better: AUCs of PTC were 0.966 vs 0.955, and AUCs of ATC were 0.982 vs 0.952, respectively, (P<0.05). CONCLUSIONS ACR-TIRADS score-based ultrasound examination of thyroid nodules aids diagnosis of benign and malignant thyroid nodules. TIRADS criteria favor diagnosis of PTC (and ATC) over FTC. ACR-TIRADS score can help clinicians diagnose thyroid nodules quickly and earlier, exhibits good clinical value, and can prevent missed diagnoses.

Celastrol inhibits mouse B16-F10 melanoma cell survival by regulating the PI3K/AKT/mTOR signaling pathway and repressing HIF-1α expression.

OBJECTIVE: Melanoma, with its high degree of malignancy, stands as one of the most dangerous skin cancers and remains the primary cause of death from skin cancer. With studies demonstrating the potential of traditional Chinese medicine to intervene and treat melanoma, we turned our attention to celastrol. Celastrol is a triterpene compound extracted from the traditional Chinese medicine derived from Tripterygium wilfordii. Previous studies have shown that celastrol exerts inhibitory effects on various malignant tumors, including melanoma. Hence, our goal was to clarify the impact of celastrol on cell viability, apoptosis, and cell cycle progression by elucidating its effects on the PI3K/AKT/mTOR pathway. METHODS: CCK-8 and wound healing assays were used to determine the effect of celastrol on the viability and migration of B16-F10 cells. Changes in cell apoptosis, cell cycle, reactive oxygen species (ROS), and mitochondrial membrane potential were detected by flow cytometry. PI3K/AKT/mTOR pathway proteins and HIF-α mRNA expression in B16-F10 cells were detected by western blotting and qPCR. Moreover, the addition of a PI3K activator demonstrated that celastrol could inhibit the function of B16-F10 cells via the PI3K/AKT/mTOR pathway. RESULTS: Celastrol inhibited the viability and migration of B16-F10 cells. Through the inhibition of the PI3K/AKT/mTOR pathway down-regulates the expression of HIF-α mRNA, thereby causing an increase of ROS in cells and a decrease in the mitochondrial membrane potential to promote cell apoptosis and cell cycle arrest. The inhibitory effect of celastrol on B16-F10 cells was further demonstrated by co-culturing with a PI3K activator. CONCLUSION: Celastrol inhibits the function of B16-F10 cells by inhibiting the PI3K/AKT/mTOR cellular pathway and regulating the expression of downstream HIF-α mRNA.

MRI-based radiomics feature combined with tumor markers to predict TN staging of rectal cancer.

The aim of this study is to evaluate the predictive ability of MRI-based radiomics combined with tumor markers for TN staging in patients with rectal cancer and to develop a prediction model for TN staging. A total of 190 patients with rectal adenocarcinoma who underwent total mesorectal excision at the First Affiliated Hospital of the Air Force Medical University between January 2016 and December 2020 were included in the study. An additional 54 patients from a prospective validation cohort were included between August 2022 and August 2023. Preoperative tumor markers and MRI imaging data were collected from all enrolled patients. The 190 patients were divided into a training cohort (n = 133) and a validation cohort (n = 57). Radiomics features were extracted by outlining the region of interest (ROI) on T2WI sequence images. Feature selection and radiomics score (Rad-score) construction were performed using least absolute shrinkage and selection operator regression analysis (LASSO). The postoperative pathology TNM stage was used to differentiate locally advanced rectal cancer (T3/4 or N1/2) from locally early rectal cancer (T1/2, N0). Logistic regression was used to construct separate prediction models for T stage and N stage. The models' predictive performance was evaluated using DCA curves and calibration curves. The T staging model showed that Rad-score, based on 8 radiomics features, was an independent predictor of T staging. When combined with CEA, tumor diameter, mesoretal fascia (MRF), and extramural venous invasion (EMVI), it effectively differentiated between T1/2 and T3/4 stage rectal cancers in the training cohort (AUC 0.87 [95% CI: 0.81-0.93]). The N-staging model found that Rad-score, based on 10 radiomics features, was an independent predictor of N-staging. When combined with CA19.9, degree of differentiation, and EMVI, it effectively differentiated between N0 and N1/2 stage rectal cancers. The training cohort had an AUC of 0.84 (95% CI: 0.77-0.91). The calibration curves demonstrated good precision between the predicted and actual results. The DCA curves indicated that both sets of predictive models could provide net clinical benefits for diagnosis. MRI-based radiomics features are independent predictors of T staging and N staging. When combined with tumor markers, they have good predictive efficacy for TN staging of rectal cancer.

[A new cucurbitane glycoside from Picrorhiza scrophulariiflora].

Chemical constituents from the ethanol extract of Picrorhiza scrophulariiflora were isolated and purified by column chromatography. Their structures were identified by HR-MS, 1D and 2D-NMR, and their cytotoxicity was assessed by CCK-8 assay. Four compounds were isolated and identified as follows: 2ß-D-glucosyloxy-3ß,16α,20ß-trihydroxy-9-methyl-19-norlanosterol-5,25-diene-22-one(1), 2ß-D-glucosyloxy-3ß,16α,20ß-trihydroxy-9-methyl-19-norlanosta-5,24-diene-22-one(2), 25-acetoxy-2ß-glucosyloxy-3ß,16α,20ß-trihydroxy-9-methyl-19-norlanosta-5-ene-22-one(3) and 25-acetoxy-2ß-glucosyloxy-3ß,16α,20ß-trihydroxy-9-methyl-19-norlanosta-5,23-(E)-diene-22-one(4). Compound 1 represents a new cucurbitane glycoside. The half inhibitory concentrations of the 4 compounds exceeded 100 µmol·L~(-1) against four tumor cell lines, indicating no significant cytotoxicity.

Symptom-to-balloon time and risk of ventricular arrhythmias in patients with STEMI undergoing percutaneous coronary intervention: The VERY-STEMI study.

Background: Ventricular arrhythmias (VAs) mainly occur in the early post-myocardial infarction (MI) period. However, studies examining the association between total myocardial ischemia time interval and the risk of new-onset VAs during a long-term follow-up are scarce. Methods: This study (symptom-to-balloon time and VEntricular aRrhYthmias in patients with STEMI, VERY-STEMI study) was a multicenter, observational cohort and real-world study, which included patients with ST-segment elevation MI (STEMI) undergoing percutaneous coronary intervention (PCI). The primary endpoint was cumulative new-onset VAs during follow-up. The secondary endpoints were the major adverse cardiovascular events (MACE) and changes in left ventricular ejection fraction (ΔLVEF, %). Results: A total of 517 patients with STEMI were included and 236 primary endpoint events occurred. After multivariable adjustments, compared to patients with S2BT of 24 h-7d, those with S2BT ≤ 24 h and S2BT > 7d had a lower risk of primary endpoint. RCS showed an inverted U-shaped relationship between S2BT and the primary endpoint, with an S2BT of 68.4 h at the inflection point. Patients with S2BT ≤ 24 h were associated with a lower risk of MACE and a 4.44 increase in LVEF, while there was no significant difference in MACE and LVEF change between the S2BT > 7d group and S2BT of 24 h-7d group. Conclusions: S2BT of 24 h-7d in STEMI patients was associated with a higher risk of VAs during follow-up. There was an inverted U-shaped relationship between S2BT and VAs, with the highest risk at an S2BT of 68.4 h.