Circular RNA circTMEM59 inhibits progression of pancreatic ductal adenocarcinoma by targeting miR-147b/SOCS1: An in vitro study

Purpose

This study aimed to detect the role and mechanism of circTMEM59 in pancreatic ductal adenocarcinoma (PDAC).

Methods

66 paired PDAC tissues and normal samples were harvested from patients diagnosed and undergoing pancreatic cancer surgery in our hospital. The expression of circTMEM59 in PDAC tissues and cell lines was detected. Based on bioinformatics information, the circTMEM59 mimics, miR-147b mimics, miR-147b inhibitor and si-suppressor of cytokine signaling 1 (SOCS1) were transfected into PDAC cells. The expression levels of circTMEM59, miR-147b and SOCS1 were detected by quantitative real-time polymerase chain reaction (qRT-PCR). RNA interaction was confirmed by dual-luciferase reporter and RNA immunoprecipitation (RIP) assays. Cell invasion and proliferation were evaluated by Transwell and Cell Counting Kit-8 (CCK-8) assays. The protein expression was detected by Western blot.

Results

CircTMEM59 was confirmed to be downregulated in PDAC tumor tissues and cells. Low expression of circTMEM59 was closely correlated with the short survival time and poor clinicopathological characteristics. By up-regulating the expression of circTMEM59 in PDAC cells, cell proliferation, invasion and epithelial-mesenchymal transition (EMT) were inhibited. More importantly, miR-147b could be sponged by circTMEM59, and knockdown of miR-147b inhibited progression of PDAC cells. Further study revealed that SOCS1 was targeted by miR-147b. SOCS1 expression was negatively related to miR-147b expression and positively related to circTMEM59 expression in PDAC tissues. Upregulated miR-147b and downregulated SOCS1 could rescue the effects of circTMEM59 on cell proliferation, EMT and invasion.

Conclusion

Our data indicated that circTMEM59 inhibited cell proliferation, invasion and EMT of PDAC by regulating miR-147b/SOCS1 axis.

Direct Observation of the Mutual Coupling Effect in the Protein-Water-Glycerol Mixture by Combining Neutron Scattering and Selective Deuteration

Numerous studies have discussed the impact of cosolvents on the structure, dynamics, and stability of proteins in aqueous solutions. However, the dynamics of cosolvents in the protein-water-cosolvent ternary system is largely unexplored in experiments due to technical difficulty. Consequently, a comprehensive understanding of the interplay among proteins, water, and cosolvents is still lacking. Here, we employed selective deuteration and neutron scattering techniques to characterize the individual motions of each component in the protein/water/glycerol (GLY) mixture across various temperatures. The consistent dynamic onset temperatures and the correlation between the MSD of the protein and the viscosity of solvents revealed the mutual coupling effects among the three components. Furthermore, our experimental and simulation results showed that the hydrogen bond relaxation energy barrier in the ternary system is ∼43 kJ/mol, whereas in the protein-water binary system it is merely ∼35 kJ/mol. Therefore, we suggest that GLY can enhance hydrogen bond interactions in the ternary system through the mutual coupling effect, thereby serving as one of the protective mechanisms of protein preservation by GLY.

Design and synthesis of dual BRD4/Src inhibitors for treatment of triple-negative breast cancer

Triple-negative breast cancer (TNBC) is an extremely aggressive tumor with limited treatment options and effectiveness. Dual-target inhibitors capable of simultaneously suppressing invasion may represent a promising therapeutic approach for TNBC. In this work, we developed a series of dual BRD4/Src inhibitors by connecting JQ1 and dasatinib using various linkers and evaluated their efficacy against TNBC both in vitro and in vivo. Among these compounds, HL403 demonstrated IC50 values of 133 nM for BRD4 inhibition and 4.5 nM for Src inhibition. Most importantly, HL403 not only exhibited potent anti-proliferative capabilities, but also effectively suppressed the invasion of MDA-MB-231 cells in vitro. Finally, the anti-tumor efficacy of HL403 was validated in a mouse MDA-MB-231 xenograft tumor model, achieving a tumor growth inhibition rate (TGI) of 70.7 %, which was superior to the combination of JQ1 and dasatinib (TGI = 54.0 %). Our research provides a promising and feasible new strategy for improving the treatment of TNBC.

M335, a novel small-molecule STING agonist activates the immune response and exerts antitumor effects

In the context of antitumor immune responses, the activation of the stimulator of interferon genes (STING) assumes a critical role and imparts enhanced immunogenicity. An effective strategy for exogenously activating the immune system involves the utilization of STING agonists, and prior investigations primarily concentrated on modifying endogenous cyclic dinucleotides (CDNs) to achieve this. Nevertheless, the practical utility of CDNs was restricted due to limitations associated with their physicochemical attributes and administration protocols. In this article, we present the discovery of a novel small-molecule agonist denoted as M335, identified through high-throughput screening using surface plasmon resonance (SPR). M335 demonstrates the ability to activate the TBK1-IRF3-IFN axis in a STING-dependent manner in vitro. Through experimentation on mouse models bearing tumors, we observed that the administration of M335 resulted in the activation of immune cells. Notably, significant antitumor effects were achieved with both intratumoral and intraperitoneal administration of M335. These findings suggest the potential of M335 as a promising agent for cancer immunotherapy, which will promote the development of STING agonists in anti-tumor applications.

Factors related to pre-operative cough strength in cardiac surgical patients: a cross-sectional study

BACKGROUND

Pulmonary complications often arise from ineffective coughing, yet limited research exists on the determinants of cough strength in patients undergoing cardiac surgery.

OBJECTIVES

The aim is to explore preoperative cough strength in patients scheduled for cardiac surgery and identify factors associated with diminished cough strength.

METHODS

A cross-sectional study was conducted on 330 adult patients admitted for cardiac surgery at a tertiary Grade A hospital in Jiangsu Province, China between August 2022 and February 2023. Cough strength was assessed using cough peak flow, with values below 270 L/min classified as reduced cough strength. The study adhered to the STROBE guidelines.

RESULTS

The study comprised 228 males (69.1 %) and 102 females (30.9 %), aged 23 to 81 years. Types of cardiac surgery included coronary artery bypass surgery, heart valvuloplasty, or heart valve replacement among others. The mean preoperative cough peak flow was 250.38 ± 119.71 L/min, with 60.3 % of patients exhibiting reduced cough strength. A multiple linear regression analysis identified gender, age, exercise regimen, pulmonary arterial hypertension, left ventricular ejection fraction, inspiratory capacity, and proficiency in coughing techniques as primary factors affecting cough strength.

CONCLUSIONS

Our findings indicate an association between diminished cough strength and factors such as female gender, advanced age, absence of systematic exercise, presence of pulmonary arterial hypertension, lower left ventricular ejection fraction, reduced inspiratory capacity, and inadequate mastery of coughing techniques. Healthcare staff should prioritize regular assessment of cough strength and manage the pertinent factors to enhance preoperative coughing ability.

TEPCAM: Prediction of T-cell receptor-epitope binding specificity via interpretable deep learning

The recognition of T-cell receptor (TCR) on the surface of T cell to specific epitope presented by the major histocompatibility complex is the key to trigger the immune response. Identifying the binding rules of TCR-epitope pair is crucial for developing immunotherapies, including neoantigen vaccine and drugs. Accurate prediction of TCR-epitope binding specificity via deep learning remains challenging, especially in test cases which are unseen in the training set. Here, we propose TEPCAM (TCR-EPitope identification based on Cross-Attention and Multi-channel convolution), a deep learning model that incorporates self-attention, cross-attention mechanism, and multi-channel convolution to improve the generalizability and enhance the model interpretability. Experimental results demonstrate that our model outperformed several state-of-the-art models on two challenging tasks including a strictly split dataset and an external dataset. Furthermore, the model can learn some interaction patterns between TCR and epitope by extracting the interpretable matrix from cross-attention layer and mapping them to the three-dimensional structures. The source code and data are freely available at https://github.com/Chenjw99/TEPCAM.

Atomic force microscopy based conformation and immunological activity of Lentinan injections

The purpose of this study was to investigate the morphological characteristics of different brands of lentinan injections produced in China using atomic force microscopy (AFM) and their relationship to immunological activity. Based on AFM imaging, chain height could be used as characterizing the conformation of lentinan, and the heights of 95 % confidence interval for triple, double and single helix were 1.746 ± 0.039 nm, 1.564 ± 0.037 nm and 1.243 ± 0.031 nm, respectively, which were calculated using self-developed MATLAB protocol. AFM characters and their immunological activity of different lentinan injection were compared. In detail, two parameters, triple helix ratio 51.3 % and adhesion force 800 pN, of Jinling (JL) lentinan injection are much higher than samples of other four manufacturers. In addition, immunological activity of JL lentinan injection is also significantly higher than Yineng's. High performance size exclusion chromatography (HPSEC) profiles of different lentinans were also compared, and the data were in accordance with those from AFM. Molecular weight accumulation curves could be used for evaluation of quality consistence of different batches of lentinan from same manufacturer and/or different manufacturers. The results showed that quality consistence of lentinan from different manufactures is poor, which should be greatly improved.

Association between Left Ventricular Longitudinal Strain (GLS) and Prognosis of the Patients Undergoing Heart Valve Surgery with Preserved Left Ventricular Ejection Fraction

PURPOSE

Global longitudinal strain (GLS) seems accurate for detecting subclinical myocardial dysfunction. This study aimed to determine the association between GLS and postoperative intensity of inotropic support in the patients undergoing heart valve surgery with preserved left ventricular ejection fraction.

METHODS

74 patients with preserved left ventricular ejection fraction who underwent valve surgery during the period between March 2021 and June 2022 were included in this prospective observational study. Transthoracic echocardiography including strain analysis with speckle tracking was performed before surgery. Patients were stratified according to the left ventricle (LV) GLS: LV-GLS ≥-16% (Impaired GLS group) and LV-GLS <-16% (Normal GLS group). The primary endpoint was postoperative vasoactive inotropic score. A high vasoactive inotropic score (VIS) was defined as a maximum VIS of ≥15 within 24 hours postoperatively. Postoperative adverse events, baseline clinical and echocardiographic data were also recorded. We invested the ability of preoperative GLS in predicting adverse postoperative outcomes, such as prolonged mechanical ventilation and the need for pharmacologic hemodynamic support after cardiac surgery.

RESULTS

Seventy-four patients were included and analyzed in this study, including thirty-three in impaired GLS group and forty-one in normal GLS group. In-hospital mortality was 1.27% (1/74). Patients in impaired GLS group were more likely to have prolonged mechanical ventilation (p = 0.041). Multivariable logistic regression analysis revealed that the apical four-chamber view of the left ventricle (A4C)-GLS was significantly associated with high VIS (OR 1.373, p = 0.007). A4C-GLS had a sensitivity of 62.5% and a specificity of 89.66% for predicting high VIS (area under the curve, 0.78). The relationships between GLS and other secondary outcome measures were not statistically significant. The optimal cutoff of A4C-GLS for postoperative high vasoactive inotropic score was -10.85%.

CONCLUSION

Preoperative LV dysfunction is an independent risk factor for postoperative high VIS. A4C-GLS may be a reliable tool in predicting high VIS after cardiac surgery. Those patients with impaired contractility were at high risk for elevated inotropic support and prolonged mechanical ventilation after cardiac surgery. These findings suggest an important role for echocardiographic GLS in perioperative assessment of cardiac function in the patients undergoing cardiac surgery.

Forensic Validation and Application Evaluation of IDentifier DNA Typing Kit (Yan-Huang34)

OBJECTIVES

To investigate the technical performance of IDentifier DNA typing kit (YanHuang34) and evaluate its forensic application value.

METHODS

Following the Criterion of Forensic Science Human Fluorescence STR Multiplex Amplification Reagent (GB/T 37226-2018), IDentifier DNA typing kit (YanHuang34) was verified in 11 aspects of species specificity, veracity, sensibility, adaptability, inhibitor tolerance, consistency, balance, reaction condition verification, mixed samples, stability and inter batch consistency. The system efficiency of IDentifier DNA typing kit (YanHuang34) was compared with the PowerPlex® Fusion 6C System, VersaPlex® 27PY System and VeriFilerTM Plus PCR Amplification Kit. The IDentifier DNA typing kit (YanHuang34) was used to detect the swabs of biological samples in daily cases and the STR performances were observed.

RESULTS

IDentifier DNA typing kit (YanHuang34) had good species specificity, veracity, adaptability, inhibitor tolerance and balance. The sensibility was up to 0.062 5 ng. It was able to detect different types of samples, degraded samples and inhibitor mixed samples. Complete DNA typing could be obtained for samples with the mixture ratio less than 4∶1. The system efficiency of IDentifier DNA typing kit (YanHuang34) was very high, with TDP up to 1-1.08×10-37, CPEtrio and CPEduo up to 1-5.47×10-14 and 1-6.43×10-9, respectively. For the touched biological samples in actual cases, the effective detection rate was 21.05%. The system efficiency of kinship, single parent and full sibling identifications was effectively improved.

CONCLUSIONS

The IDentifier DNA typing kit (YanHuang34) is adaptive to the GB/T 37226-2018 requirements. It can be used for individual identification and paternity identification, and is suitable for application in the field of forensic science.

A novel interpretative tool for early prediction of low cardiac output syndrome after valve surgery: online machine learning models

OBJECTIVE

Low cardiac output syndrome (LCOS) is a severe complication after valve surgery, with no uniform standard for early identification. We developed interpretative machine learning (ML) models for predicting LCOS risk preoperatively and 0.5 h postoperatively for intervention in advance.

METHODS

A total of 2218 patients undergoing valve surgery from June 2019 to Dec 2021 were finally enrolled to construct preoperative and postoperative models. Logistic regression, support vector machine (SVM), random forest classifier, extreme gradient boosting, and deep neural network were executed for model construction, and the performance of models was evaluated by area under the curve (AUC) of the receiver operating characteristic and calibration curves. Our models were interpreted through SHapley Additive exPlanations, and presented as an online tool to improve clinical operability.

RESULTS

The SVM algorithm was chosen for modeling due to better AUC and calibration capability. The AUCs of the preoperative and postoperative models were 0.786 (95% CI 0.729-0.843) and 0.863 (95% CI 0.824-0.902), and the Brier scores were 0.123 and 0.107. Our models have higher timeliness and interpretability, and wider coverage than the vasoactive-inotropic score, and the AUC of the postoperative model was significantly higher. Our preoperative and postoperative models are available online at http://njfh-yxb.com.cn:2022/lcos.

CONCLUSIONS

The first interpretable ML tool with two prediction periods for online early prediction of LCOS risk after valve surgery was successfully built in this study, in which the SVM model has the best performance, reserving enough time for early precise intervention in critical care.

Enantioselective Synthesis of N-N Amide-Pyrrole Atropisomers via Paal-Knorr Reaction

The catalytic asymmetric construction of monoheteroaryl N-N axially chiral compounds and chiral five-membered aryl-based scaffolds remains challenging. Herein, we present a highly efficient enantioselective synthesis of monoheteroaryl N-N atropisomers via an asymmetric Paal-Knorr reaction, affording a diverse array of N-N amide-pyrrole atropisomers with excellent enantioselectivities. Gram-scale synthesis and post-transformations of the product demonstrated the synthesis utility of this method. Racemization experiments confirmed the configurational stability of these N-N axially chiral products. This study not only provides the first de novo cyclization example for accessing an asymmetric monoheteroaryl N-N scaffold but also offers a new member of the N-N atropisomer family with potential synthetic and medicinal applications.

Noncanonical autophagy is a new strategy to inhibit HSV-1 through STING1 activation

STING1 (stimulator of interferon response cGAMP interactor 1) plays an essential role in immune responses for virus inhibition via inducing the production of type I interferon, inflammatory factors and macroautophagy/autophagy. In this study, we found that STING1 activation could induce not only canonical autophagy but also non-canonical autophagy (NCA) which is independent of the ULK1 or BECN1 complexes to form MAP1LC3/LC3-positive structures. Whether STING1-induced NCA has similar characters and physiological functions to canonical autophagy is totally unknown. Different from canonical autophagy, NCA could increase single-membrane structures and failed to degrade long-lived proteins, and could be strongly suppressed by interrupting vacuolar-type H+-translocating ATPase (V-ATPase) activity. Importantly, STING1-induced NCA could effectively inhibit DNA virus HSV-1 in cell model. Moreover, STING1 [1-340], a STING1 mutant lacking immunity and inflammatory response due to deletion of the tail end of STING1, could degrade virus through NCA alone, suggesting that the antiviral effect of activated STING1 could be separately mediated by inherent immunity, canonical autophagy, and NCA. In addition, the translocation and dimerization of STING1 do not rely on its immunity function and autophagy pathway. Similar to canonical autophagy, LC3-positive structures of NCA induced by STING1 could finally fuse with lysosomes, and the degradation of HSV-1 could be reverted by inhibition of lysosome function, suggesting that the elimination of DNA virus via NCA still requires the lysosome pathway. Collectively, we proved that besides its classical immunity function and canonical autophagy pathway, STING1-induced NCA is also an efficient antiviral pathway for the host cell.Abbreviations: ATG: autophagy related; Baf: bafilomycin A1; CASM: conjugation of LC3 to a single membrane; CGAS: cyclic GMP-AMP synthase; cGAMP: cyclic GMP-AMP; CQ: chloroquine; CTD: C-terminal domain; CTT: C-terminal tail; ER: endoplasmic reticulum; ERGIC: ER-Golgi intermediate compartment; HSV-1: herpes simplex virus 1; IRF3: interferon regulatory factor 3; IFNs: interferons; LAMP1: lysosomal associated membrane protein 1; LAP: LC3-associated phagocytosis; MAP1LC3/LC3: microtubule associated protein 1 light chain 3; MOI: multiplicity of infection; RB1CC1/FIP200: RB1 inducible coiled-coil 1; STING1: stimulator of interferon response cGAMP interactor 1; TBK1: TANK binding kinase 1; TGOLN2/TGN46: trans-golgi network protein 2; ULK1: unc-51 like autophagy activating kinase 1; V-ATPase: vacuolar-type H+-translocating ATPase; VSV: vesicular stomatitis virus.

Colossal electrocaloric effect in an interface-augmented ferroelectric polymer

The electrocaloric effect demands the maximized degree of freedom (DOF) of polar domains and the lowest energy barrier to facilitate the transition of polarization. However, optimization of the DOF and energy barrier-including domain size, crystallinity, multiconformation coexistence, polar correlation, and other factors in bulk ferroelectrics-has reached a limit. We used organic crystal dimethylhexynediol (DMHD) as a three-dimensional sacrificial master to assemble polar conformations at the heterogeneous interface in poly(vinylidene fluoride)-based terpolymer. DMHD was evaporated, and the epitaxy-like process induced an ultrafinely distributed, multiconformation-coexisting polar interface exhibiting a giant conformational entropy. Under a low electric field, the interface-augmented terpolymer had a high entropy change of 100 J/(kg·K). This interface polarization strategy is generally applicable to dielectric capacitors, supercapacitors, and other related applications.

MATT-DDI: Predicting multi-type drug-drug interactions via heterogeneous attention mechanisms

The joint use of multiple drugs can result in adverse drug-drug interactions (DDIs) and side effects that harm the body. Accurate identification of DDIs is crucial for avoiding accidental drug side effects and understanding potential mechanisms underlying DDIs. Several computational methods have been proposed for multi-type DDI prediction, but most rely on the similarity profiles of drugs as the drug feature vectors, which may result in information leakage and overoptimistic performance when predicting interactions between new drugs. To address this issue, we propose a novel method, MATT-DDI, for predicting multi-type DDIs based on the original feature vectors of drugs and multiple attention mechanisms. MATT-DDI consists of three main modules: the top k most similar drug pair selection module, heterogeneous attention mechanism module and multi‑type DDI prediction module. Firstly, based on the feature vector of the input drug pair (IDP), k drug pairs that are most similar to the input drug pair from the training dataset are selected according to cosine similarity between drug pairs. Then, the vectors of k selected drug pairs are averaged to obtain a new drug pair (NDP). Next, IDP and NDP are fed into heterogeneous attention modules, including scaled dot product attention and bilinear attention, to extract latent feature vectors. Finally, these latent feature vectors are taken as input of the classification module to predict DDI types. We evaluated MATT-DDI on three different tasks. The experimental results show that MATT-DDI provides better or comparable performance compared to several state-of-the-art methods, and its feasibility is supported by case studies. MATT-DDI is a robust model for predicting multi-type DDIs with excellent performance and no information leakage.

A large-scale study integrating nutritional indicators and clinicopathological parameters to evaluate prognosis, follow-up, and postoperative chemotherapy decisions in rectal cancer patients

OBJECTIVE

The aim of this study was to evaluate the role of nutritional indicators and clinicopathological parameters in predicting the progression and prognosis for pathological stage II-III rectal cancer (RC) patients without neoadjuvant radiotherapy. In addition, we sought to explore the high-risk population who may require postoperative chemotherapy.

METHODS

A total of 894 consecutive RC patients were enrolled in this study. Univariate and multivariate Cox analysis were performed to identify the independent risk factors for PFS and OS. The nomogram and calibration curves were conducted according to multivariable analysis result. Kaplan-Meier survival curves and log-rank tests were performed for different groups. Finally, random survival forest (RSF) model was developed to predict the probability of progression.

RESULTS

Our results revealed that CEA level, pathological stage, tumor deposit, and PNI were independently associated with PFS in RC patients. Similarly, the results indicated that CEA level, pathological stage, tumor deposit, PNI, and NRI were independently associated with OS. RSF model revealed that group 1 had the highest risk of progression at the 12th month of follow-up, group 2 had the highest risk of progression at the 15th month of follow-up, while group 3 had the highest risk of progression at the 9th month of follow-up. Besides, subgroup analysis suggested that the high-risk group needs postoperative adjuvant chemotherapy, while patients in the low- and moderate-risk groups may not need postoperative adjuvant chemotherapy. Finally, we validated our results with the SEER database.

CONCLUSIONS

In conclusion, we demonstrated that preoperative nutritional indicator and clinicopathological parameters could act as auxiliary prognostication tools for RC patients without neoadjuvant radiotherapy. We also established follow-up strategies for different groups of patients. Collectively, incorporating nutritional assessment into risk stratification for RC resection is crucial and should be an integral part of preoperative planning.

The diagnosis of tuberculous meningitis: advancements in new technologies and machine learning algorithms

Tuberculous meningitis (TBM) poses a diagnostic challenge, particularly impacting vulnerable populations such as infants and those with untreated HIV. Given the diagnostic intricacies of TBM, there's a pressing need for rapid and reliable diagnostic tools. This review scrutinizes the efficacy of up-and-coming technologies like machine learning in transforming TBM diagnostics and management. Advanced diagnostic technologies like targeted gene sequencing, real-time polymerase chain reaction (RT-PCR), miRNA assays, and metagenomic next-generation sequencing (mNGS) offer promising avenues for early TBM detection. The capabilities of these technologies are further augmented when paired with mass spectrometry, metabolomics, and proteomics, enriching the pool of disease-specific biomarkers. Machine learning algorithms, adept at sifting through voluminous datasets like medical imaging, genomic profiles, and patient histories, are increasingly revealing nuanced disease pathways, thereby elevating diagnostic accuracy and guiding treatment strategies. While these burgeoning technologies offer hope for more precise TBM diagnosis, hurdles remain in terms of their clinical implementation. Future endeavors should zero in on the validation of these tools through prospective studies, critically evaluating their limitations, and outlining protocols for seamless incorporation into established healthcare frameworks. Through this review, we aim to present an exhaustive snapshot of emerging diagnostic modalities in TBM, the current standing of machine learning in meningitis diagnostics, and the challenges and future prospects of converging these domains.

[Screening for asymptomatic atrial fibrillation in elder community populations in Dalian: a single center study]

Objective: We aimed to determine the epidemiological characteristics of asymptomatic AF in elder community population (≥65 years old) to analyze the detection rate of different screening methods. Methods: The study was a prospective cohort study. The elder (≥65 years old) residents who voluntarily participated in free physical examination in Dalian community were selected. The participants were randomly divided into screening group (including intensive screening group and single screening group) and control group. The control group received interrogation, medical history collection and routine 12-lead electrocardiogram (ECG) examination. Screening group received an additional single-lead ambulatory ECG equipment worn for 5-7 days. Intensive screening group received two equal-length wearings in 2020 and 2021 respectively, while one screening group only wore once in 2020. Results: Finally 3 340 residents ((70.7±5.0) years old) which consisted of 1 488 males (44.55%) were enrolled. There were 1 945 residents in screening group, including 859 in intensive screening group and 1 086 in one-time screening group. The control group included 1 395 people. Detection rate of asymptomatic AF was significantly higher in screening group than control group (79(4.06%) vs. 24(1.72%), P<0.001). Higher detection rate was found in screening group than control group in AF risk factors (1 or 2-3) subgroups and CHA2DS2-VASc score (2-3 or≥4) subgroups (P<0.05). Additionally, no difference was found between intensive screening group and single screening group (42(4.89%) vs. 37(3.41%), P=0.100). Intensive screening increased detection rate (7(6.93%) vs. 1(0.58%), P=0.009) only in residents those with low thrombosis risk (CHA2DS2-VaSc<2). Conclusions: Screening in elderly (≥65 years old) can significantly improve the detection rate of asymptomatic AF by wearing single lead dynamic ECG device. The rate increased significantly with the increase of risk factors associated with AF by single screening. In addition, repeat screening of the same method may only improve detection rates in the group with low risk thrombotic scores and non-combination of AF risk factors.Screening methods that are appropriate for different populations may require further exploration.

ScaffoldGVAE: scaffold generation and hopping of drug molecules via a variational autoencoder based on multi-view graph neural networks

In recent years, drug design has been revolutionized by the application of deep learning techniques, and molecule generation is a crucial aspect of this transformation. However, most of the current deep learning approaches do not explicitly consider and apply scaffold hopping strategy when performing molecular generation. In this work, we propose ScaffoldGVAE, a variational autoencoder based on multi-view graph neural networks, for scaffold generation and scaffold hopping of drug molecules. The model integrates several important components, such as node-central and edge-central message passing, side-chain embedding, and Gaussian mixture distribution of scaffolds. To assess the efficacy of our model, we conduct a comprehensive evaluation and comparison with baseline models based on seven general generative model evaluation metrics and four scaffold hopping generative model evaluation metrics. The results demonstrate that ScaffoldGVAE can explore the unseen chemical space and generate novel molecules distinct from known compounds. Especially, the scaffold hopped molecules generated by our model are validated by the evaluation of GraphDTA, LeDock, and MM/GBSA. The case study of generating inhibitors of LRRK2 for the treatment of PD further demonstrates the effectiveness of ScaffoldGVAE in generating novel compounds through scaffold hopping. This novel approach can also be applied to other protein targets of various diseases, thereby contributing to the future development of new drugs. Source codes and data are available at https://github.com/ecust-hc/ScaffoldGVAE .

Improvement of soil acidification and ammonium nitrogen content in tea plantations by long-term use of organic fertilizer

Soil acidification is common in some Chinese tea plantations, which seriously affected growth of tea trees. Hence, it is essential to explore soil remediation in acidified tea plantations for sustainable development of the tea industry. We sought to determine how different fertilizers affect acidified soil and their N transformation in tea plantations. Different fertilizers were used on acidified tea plantation soils for 4 years (2017-2021), and changes in soil pH, indices related to soil N transformation and tea yield were analysed to construct interaction networks of these indices and find which had the largest influence on fertilization. Long-term use of sheep manure reduced soil acidification, increased soil pH, enhanced the number and intensity of N-fixing and ammonifying bacteria, urease, protease, asparaginase and N-acetamide glucose ribosidase activity and nifH gene expression. This treatment reduced the number and intensity of soil nitrifying and denitrifying bacteria, nitrate reductase and nitrite reductase activity, while the expression of amoA-AOA, nirK, nirS, narG and nosZ in turn increased ammonium N content of the soil, reduced nitrate N content, and enhanced tea yield. Topsis index weight analysis showed that ammonium N content in the soil had the largest impact among fertilization effects. Long-term use of sheep manure was beneficial in restoring the balance of the micro-ecosystem in acidified soil. This study provides an important practical basis for soil remediation and fertilizer management in acidified tea plantation soils.

The impact of bariatric surgery on hospitalization due to peripheral artery disease and critical limb ischemia: a nationwide analysis

BACKGROUND

Severe obesity could be an independent risk factor for peripheral artery disease (PAD) and critical limb ischemia (CLI). Bariatric surgery reduces cardiac risk factors, decreasing cardiovascular morbidity and mortality in subjects with severe obesity.

OBJECTIVES

We aimed to describe the impact of bariatric surgery on risk of hospitalization due to PAD and CLI.

SETTING

Academic hospital.

METHODS

The National Inpatient Sample data collected from 2010 to 2015 were examined. Patients were classified as treatment and control groups. Treatment was defined as patients with a previous history of bariatric surgery, and control was defined as patients with a body mass index ≥35 without a history of bariatric surgery. The primary outcome was hospitalization due to PAD; secondary outcomes were CLI, revascularization, major amputation, length of hospital stay (LOS), and total cost of hospitalization. Univariate and multivariate analyses were performed to assess the differences between groups.

RESULTS

There were a total of 2,300,845 subjects: 2,004,804 controls and 296,041 treatment patients. Hospitalization rate for PAD was significantly lower compared to the control group (.10% versus .21%, P < .0001), which was confirmed after adjusting for covariables (control versus treatment: odds ratio= 1.20, confidence interval: 1.15-1.47). Subgroup analysis showed patients without a history of bariatric surgery had a higher prevalence of CLI (59.3% versus 52.4%, P < .0219) and a higher mean LOS (6.7 versus 5.7 days, P = .0023) and cost of hospitalization (78.756 versus 72.621$, P = .0089), with no significant differences in other outcomes. After multivariate analysis, only LOS and total costs were significantly different.

CONCLUSIONS

Bariatric surgery may decrease the risk of hospitalization due to PAD, similarly to the LOS and total cost of hospitalization. Prospective studies should be performed to describe this relationship.

Rapid Fog-Removal Strategies for Traffic Environments

In a foggy traffic environment, the vision sensor signal of intelligent vehicles will be distorted, the outline of obstacles will become blurred, and the color information in the traffic road will be missing. To solve this problem, four ultra-fast defogging strategies in a traffic environment are proposed for the first time. Through experiments, it is found that the performance of Fast Defogging Strategy 3 is more suitable for fast defogging in a traffic environment. This strategy reduces the original foggy picture by 256 times via bilinear interpolation, and the defogging is processed via the dark channel prior algorithm. Then, the image after fog removal is processed via 4-time upsampling and Gaussian transform. Compared with the original dark channel prior algorithm, the image edge is clearer, and the color information is enhanced. The fast defogging strategy and the original dark channel prior algorithm can reduce the defogging time by 83.93-84.92%. Then, the image after fog removal is inputted into the YOLOv4, YOLOv5, YOLOv6, and YOLOv7 target detection algorithms for detection and verification. It is proven that the image after fog removal can effectively detect vehicles and pedestrians in a complex traffic environment. The experimental results show that the fast defogging strategy is suitable for fast defogging in a traffic environment.

[The association between cortical venous outflow and futile recanalization in patients with acute ischemic stroke due to large vessel occlusion in the anterior circulation]

Objective: To explore the association of baseline venous outflow (VO) profile with futile recanalization in patients with acute ischemic stroke due to large vessel occlusion in the anterior circulation. Methods: The clinical and imaging data of patients presented with large vessel occlusion in the anterior circulation and underwent emergency endovascular treatment at Huashan Hospital from March 2015 to December 2021 were retrospectively included in the study. All patients were assessed by the National Institutes of Health Stroke Scale (NIHSS) at baseline.Baseline VO profile was determined by a 0-6 semi-quantitative scoring system which assessed opacification of the ipsilateral superficial middle cerebral vein, vein of Labbé and vein of Trolard on single-phase CT angiography (CTA) images. A 90-day telephone follow-up was performed and functional outcome was evaluated by 90 d modified Rankin scale (mRS). Successful recanalization of the occluded artery, defined as final modified Thrombolysis in Cerebral Infarction scale (mTICI) 2b-3, was considered to be futile if patients failed to achieve functional independence (90 d mRS 0-2). Univariate analysis and receiver operating characteristic (ROC) curve analysis were used to explore the optimal cutoff predicting functional indendence. The associations between cortical VO in ischemic area and futile recanalization were evaluated using binary logistic regression analysis and backward linear regression based on Akaike information criterion (AIC). Results: A total of 150 patients met the inclusion criteria, with 92 males (61.3%) and 58 females (38.7%). The median age [M(Q1, Q3)]was 71 (61, 78) years and the median baseline National Institute of Health Stroke Scale (NIHSS) score [M(Q1, Q3)]was 15 (11, 18). Univariate logistic regression analysis showed that baseline VO was associated with 90-day functional independence (OR=1.587, 95%CI: 1.185-2.1873). After classifying VO into two categories based on the receiver operating characteristic (ROC) curve, VO≥4 showed an independent association with functional independence (OR=5.133, 95%CI: 1.530-9.361) after adjusting for age, baseline glucose, NIHSS score, baseline infarct core volume, modified Tan (mTan) score, hypoperfusion intensity ratio (HIR), etiological classification, recanalization, presence of any hemorrhagic transformation and final infarct volume. Futile recanalization was observed in 44 (48.4%) of the 91 patients who achieved successful recanalization. Stepwise logistic regression revealed that VO≥4 was an independent protective factor for futile recanalization (OR=0.234, 95%CI: 0.054-0.878). Moreover, in patients with mTICI 2c-3, VO≥4 showed a stronger association with futile recanalization (OR=0.018, 95%CI: 0-0.255). Conclusion: A favorable VO profile at onset protects against futile recanalization in patients with large vessel occlusion in the anterior circulation, and provides a simple and feasible auxiliary method for predicting the prognosis of endovascular therapy in such patients.

Osteopontin May Improve Postinjury Muscle Repair Via Matrix Metalloproteinases And tgf-β Activation in Regular Exercise

Skeletal muscle injuries are commonly observed during sports and trauma. Regular exercise promotes muscle repair; however, the underlying mechanisms require further investigation. In addition to exercise, osteopontin (OPN) contributes to skeletal muscle regeneration and fibrosis following injury. However, whether and how OPN affects matrix proteins to promote post-injury muscle repair remains uncertain. We recruited regular exercise (RE) and sedentary control (SC) groups to determine plasma OPN levels. Additionally, we developed a murine model of muscle contusion injury and compared the extent of damage, inflammatory state, and regeneration-related proteins in OPN knockout (OPN KO) and wild-type (WT) mice. Our results show that regular exercise induced the increase of OPN, matrix metalloproteinases (MMPs), and transforming growth factor-β (TGF-β) expression in plasma. Injured muscle fibers were repaired more slowly in OPN-KO mice than in WT mice. The expression levels of genes and proteins related to muscle regeneration were lower in OPN-KO mice after injury. OPN also promotes fibroblast proliferation, differentiation, and migration. Additionally, OPN upregulates MMP expression by activating TGF-β, which promotes muscle repair. OPN can improve post-injury muscle repair by activating MMPs and TGF-β pathways. It is upregulated by regular exercise. Our study provides a potential target for the treatment of muscle injuries and explains why regular physical exercise is beneficial for muscle repair.

A novel approach to expedite wound healing with plasma brush of cold flame

Excessive or persistent infection is a major contributing factor in impeding chronic wound healing. Wound bed preparations using antiseptics do not necessarily target the entire bacterial spectrum, and the highly proliferating granulation tissue may be sensitive to the cytotoxic effects, impairing tissue repair. Non-thermal gas atmospheric pressure plasmas are partially ionized gases that contain highly reactive particles while the gas phase remains near room temperature, thus having the capability of accessing small irregular cavities and fissures and killing bacteria because of the diffusive nature of gas phase plasma species that are chemically reactive, providing an ideal approach to topical wound disinfection. A non-thermal plasma brush device of novel design has been developed that is suitable for clinical application in the disinfection of oral and wound bacteria. In vivo studies have indicated that the plasma brush treatment rendered no harmful effect on healthy skin or tissues, while it could improve wound healing in Pseudomonas aeruginosa biofilm infected wounds exposed to an optimized treatment with argon plus 1% nitrogen (Ar + N2) plasma.

M1 macrophage-derived exosomes promote autoimmune liver injury by transferring long noncoding RNA H19 to hepatocytes

Exosomes mediate intercellular communication by transmitting active molecules. The function of long noncoding RNA (lncRNA) H19 in autoimmune liver injury is unclear. Concanavalin A (ConA)-induced liver injury is well-characterized immune-mediated hepatitis. Here, we showed that lncRNA H19 expression was increased in the liver after ConA treatment, accompanied by increased exosome secretion. Moreover, injection of AAV-H19 aggravated ConA-induced hepatitis, with an increase in hepatocyte apoptosis. However, GW4869, an exosome inhibitor, alleviated ConA-induced liver injury and inhibited the upregulation of lncRNA H19. Intriguingly, lncRNA H19 expression in the liver was significantly downregulated, after macrophage depletion. Importantly, the lncRNA H19 was primarily expressed in type I macrophage (M1) and encapsulated in M1-derived exosomes. Furthermore, H19 was transported from M1 to hepatocytes via exosomes, and exosomal H19 dramatically induced hepatocytes apoptosis both in vitro and vivo. Mechanistically, H19 upregulated the transcription of hypoxia-inducible factor-1 alpha (HIF-1α), which accumulated in the cytoplasm and mediated hepatocyte apoptosis by upregulating p53. M1-derived exosomal lncRNA H19 plays a pivotal role in ConA-induced hepatitis through the HIF-1α-p53 signaling pathway. These findings identify M1 macrophage-derived exosomal H19 as a novel target for the treatment of autoimmune liver diseases.