Objective To propose a lung artery segmentation method that integrates shape and position prior knowledge, aiming to solve the issues of inaccurate segmentation caused by the high similarity and small size differences between the lung arteries and surrounding tissues in CT images. Methods Based on the three-dimensional U-Net network architecture and relying on the PARSE 2022 database image data, shape and position prior knowledge was introduced to design feature extraction and fusion strategies to enhance the ability of lung artery segmentation. The data of the patients were divided into three groups: a training set, a validation set, and a test set. The performance metrics for evaluating the model included Dice Similarity Coefficient (DSC), sensitivity, accuracy, and Hausdorff distance (HD95). Results The study included lung artery imaging data from 203 patients, including 100 patients in the training set, 30 patients in the validation set, and 73 patients in the test set. Through the backbone network, a rough segmentation of the lung arteries was performed to obtain a complete vascular structure; the branch network integrating shape and position information was used to extract features of small pulmonary arteries, reducing interference from the pulmonary artery trunk and left and right pulmonary arteries. Experimental results showed that the segmentation model based on shape and position prior knowledge had a higher DSC (82.81%±3.20% vs. 80.47%±3.17% vs. 80.36%±3.43%), sensitivity (85.30%±8.04% vs. 80.95%±6.89% vs. 82.82%±7.29%), and accuracy (81.63%±7.53% vs. 81.19%±8.35% vs. 79.36%±8.98%) compared to traditional three-dimensional U-Net and V-Net methods. HD95 could reach (9.52±4.29) mm, which was 6.05 mm shorter than traditional methods, showing excellent performance in segmentation boundaries. Conclusion The lung artery segmentation method based on shape and position prior knowledge can achieve precise segmentation of lung artery vessels and has potential application value in tasks such as bronchoscopy or percutaneous puncture surgery navigation.

Transformer models have emerged as pivotal tools within the realm of drug discovery, distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes. Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data, these models showcase remarkable efficacy across various tasks, including new drug design and drug target identification. The adaptability of pre-trained transformer-based models renders them indispensable assets for driving data-centric advancements in drug discovery, chemistry, and biology, furnishing a robust framework that expedites innovation and discovery within these domains. Beyond their technical prowess, the success of transformer-based models in drug discovery, chemistry, and biology extends to their interdisciplinary potential, seamlessly combining biological, physical, chemical, and pharmacological insights to bridge gaps across diverse disciplines. This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields. In our review, we elucidate the myriad applications of transformers in drug discovery, as well as chemistry and biology, spanning from protein design and protein engineering, to molecular dynamics (MD), drug target identification, transformer-enabled drug virtual screening (VS), drug lead optimization, drug addiction, small data set challenges, chemical and biological image analysis, chemical language understanding, and single cell data. Finally, we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.

Polygonati Rhizoma demonstrates significant potential for addressing both chronic and hidden hunger. The supply of high-quality seedlings is a primary factor influencing the development of the Polygonati Rhizoma industry. Warm water soaking is often used in agriculture to promote the rapid germination of seeds, while its application and molecular mechanism in Polygonati Rhizoma have not been reported. To rapidly obtain high-quality seedlings, this study treated Polygonatum kingianum var. grandifolium seeds with sand storage at low temperatures, warm water soaking, and cultivation temperature gradients. The results showed that the culture at 25 ℃ or sand storage at 4 ℃ for 2 months rapidly broke the seed dormancy of P. kingianum var. grandifolium, while the culture at 20 ℃ or sand storage at 4 ℃ for 1 month failed to break the seed dormancy. Soaking seeds in 60 ℃ warm water further increased the germination rate, germination potential, and germination index. Specifically, the seeds soaked at 60 ℃ and cultured at 25 ℃ without sand storage treatment(Aa25) achieved a germination rate of 78. 67%±1. 53% on day 42 and 83. 40%±4. 63% on day 77. The seeds pretreated with sand storage at 4 ℃ for 2 months, soaked in 60 ℃ water, and then cultured at 25 ℃ achieved a germination rate comparable to that of Aa25 on day 77. Transcriptomic analysis indicated that warm water soaking might promote germination by triggering reactive oxygen species( ROS), inducing the expression of heat shock factors( HSFs) and heat shock proteins( HSPs), which accelerated DNA replication, transcript maturation, translation, and processing, thereby facilitating the accumulation and turnover of genetic materials. According to the results of indoor controlled experiments and field practices, maintaining a germination and seedling cultivation environment at approximately 25 ℃ was crucial for the one-year seedling cultivation of P. kingianum var. grandifolium.
Germination ; Seedlings/genetics* ; Water/metabolism* ; Seeds/metabolism* ; Polygonatum/genetics* ; Temperature ; Plant Proteins/genetics* ; Plant Dormancy

PURPOSE: The rate of complications among patients undergoing surgery has increased due to infection with SARS-CoV-2 and other variants of concern. However, Omicron has shown decreased pathogenicity, raising questions about the risk of postoperative complications among patients who are infected with this variant. This study aimed to investigate complications and related factors among patients with recent Omicron infection prior to undergoing orthopedic surgery. METHODS: A historical control study was conducted. Data were collected from all patients who underwent surgery during 2 distinct periods: (1) between Dec 12, 2022 and Jan 31, 2023 (COVID-19 positive group), (2) between Dec 12, 2021 and Jan 31, 2022 (COVID-19 negative control group). The patients were at least 18 years old. Patients who received conservative treatment after admission or had high-risk diseases or special circumstances (use of anticoagulants before surgery) were excluded from the study. The study outcomes were the total complication rate and related factors. Binary logistic regression analysis was used to identify related factors, and odds ratio (OR) and 95% confidence interval (CI) were calculated to assess the impact of COVID-19 infection on complications. RESULTS: In the analysis, a total of 847 patients who underwent surgery were included, with 275 of these patients testing positive for COVID-19 and 572 testing negative. The COVID-19-positive group had a significantly higher rate of total complications (11.27%) than the control group (4.90%, p < 0.001). After adjusting for relevant factors, the OR was 3.08 (95% CI: 1.45-6.53). Patients who were diagnosed with COVID-19 at 3-4 weeks (OR = 0.20 (95% CI: 0.06-0.59), p = 0.005), 5-6 weeks (OR = 0.16 (95% CI: 0.04-0.59), p = 0.010), or ≥7 weeks (OR = 0.26 (95% CI: 0.06-1.02), p = 0.069) prior to surgery had a lower risk of complications than those who were diagnosed at 0-2 weeks prior to surgery. Seven factors (age, indications for surgery, time of operation, time of COVID-19 diagnosis prior to surgery, C-reactive protein levels, alanine transaminase levels, and aspartate aminotransferase levels) were found to be associated with complications; thus, these factors were used to create a nomogram. CONCLUSION Omicron continues to be a significant factor in the incidence of postoperative complications among patients undergoing orthopedic surgery. By identifying the factors associated with these complications, we can determine the optimal surgical timing, provide more accurate prognostic information, and offer appropriate consultation for orthopedic surgery patients who have been infected with Omicron.
Humans ; COVID-19/complications* ; Male ; Female ; Middle Aged ; Postoperative Complications/epidemiology* ; SARS-CoV-2 ; Orthopedic Procedures/adverse effects* ; Aged ; Nomograms ; Adult ; Retrospective Studies ; Risk Factors

Transformer models have emerged as pivotal tools within the realm of drug discovery,distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes.Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data,these models showcase remarkable efficacy across various tasks,including new drug design and drug target identification.The adaptability of pre-trained trans-former-based models renders them indispensable assets for driving data-centric advancements in drug discovery,chemistry,and biology,furnishing a robust framework that expedites innovation and dis-covery within these domains.Beyond their technical prowess,the success of transformer-based models in drug discovery,chemistry,and biology extends to their interdisciplinary potential,seamlessly combining biological,physical,chemical,and pharmacological insights to bridge gaps across diverse disciplines.This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields.In our review,we elucidate the myriad applications of transformers in drug discovery,as well as chemistry and biology,spanning from protein design and protein engineering,to molecular dynamics(MD),drug target iden-tification,transformer-enabled drug virtual screening(VS),drug lead optimization,drug addiction,small data set challenges,chemical and biological image analysis,chemical language understanding,and single cell data.Finally,we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.

Objective To explore the value of droplet digital polymerase chain reaction(ddPCR)in the etiological diagnosis of severe acute pancreatitis(SAP)patients with suspected bloodstream infection(BSI).Methods SAP patients admitted to the department of critical care medicine in a hospital July to September 2022 were enrolled.When BSI was suspected,venous blood was collected for both ddPCR detection and blood culture(BC)with antimi-crobial susceptibility testing(AST)simultaneously.The time required for two detection methods was recorded,and the detection results of ddPCR and BC were compared.The etiological diagnostic efficacy of ddPCR was calculated,and the correlation between the value of pathogen load detected by ddPCR and the level of infection parameters was explored.Results A total of 22 patients were included in the analysis,and 52 venous blood specimens were collec-ted for detection.BC revealed 17 positive specimens(32.7％)and 29 pathogenic strains,while ddPCR showed 41 positive specimens(78.8％)and 73 pathogenic strains.Detection time required for ddPCR was significantly lower than that of BC([0.16±0.03]days vs[5.92±1.20]days,P＜0.001).Within the detection range of ddPCR and taking BC results as the gold standard,the sensitivity and specificity of ddPCR were 80.0％and 28.6％,respective-ly.With the combined assessment of BSI based on non-blood specimen microbial evidence within a week,the sensi-tivity and specificity of ddPCR detection increased to 91.9％and 76.9％,respectively.ddPCR detected resistance genes of blaKPC,blaNDM/IMP,VanA/VanM,and mecA from 19,9,6,and 5 specimens,respectively.Correlation analysis showed a positive correlation between pathogen load and levels of C-reactive protein as well as procalcitonin(r=0.347,0.414,P＜0.05).Conclusion As a supplementary detection method for BC in BSI diagnosis,ddPCR has the advantages of higher sensitivity and shorter detection time,and is worthy of further exploration in clinical application.

Objective:To evaluate the effectiveness and safety of fistula-tract lase closure (FiLaC TM) surgery combined with the infliximab (IFX) for treating complex perianal fistulizing Crohn's disease (pfCD) . Methods:A retrospective was conducted. Patients with pfCD undergoing FiLaC TM at Renji Hospital, Shanghai Jiaotong University School of Medicine between February 2019 and August 2020 were retrospectively enrolled. The preoperative protocol included seton drainage and pharmacological induction, utilizing IFX alone or in combination with immunosuppressants. After achieving remission in CD, patients underwent definitive surgery with FiLaC TM. Clinical outcomes and adverse events such as bleeding, pain, and fecal incontinence following FiLaC TM were recorded. The Wexner fecal incontinence score and Crohn's anal fistula quality of life scale (CAF-QoL) were assessed both preoperatively and 24 months postoperatively. Results:The study included 30 patients (23 males, 7 females) with a median age of 23.6 (18.0, 30.5) years. At 24 months postoperatively, 21 patients (70.0%) achieved clinical cure; 2 patients (6.7%) showed improvement; 2 patients (6.7%) did not heal, with one eventually healing after a repeat FiLaC TM procedure and the other requiring re-seton placement; 5 patients (16.7%) relapsed and required re-seton. The Wexner fecal incontinence score at 24 months postoperatively was lower compared to preoperative scores [2.0 (1.8, 3.0) vs. 2.0 (2.0, 3.0), P = 0.001]. The postoperative CAF-QoL scores were higher as compared to the preoperative score[39.5 (33.8, 62.3) vs. 37.5 (30.0, 56.3), P = 0.03]. There were no complications such as fecal incontinence, urinary incontinence, or bleeding postoperatively. Twenty-seven patients (90%) experienced mild pain, and 1 (3.3%) reported moderate pain, all resolving without intervention. Conclusion:Combined treatment with FiLaC TM and IFX is both effective and safe for managing complex pfCD.

italic>Anoectochilus roxburghii liquid (spray, a hospital preparation of Wu Mengchao Hepatobiliary Hospital of Fujian Medical University) has shown a good clinical treatment effect during the COVID-19 pandemic, but its material basis and mechanism of action are still unclear. In this study, network pharmacology and molecular docking methods were used to predict the molecular mechanism of A. roxburghii liquid against COVID-19, and pharmacodynamic experiments in vitro were conducted to study the interaction between the current targets with clear preventive and therapeutic effects and the key components of A. roxburghii liquid. UPLC-MS and database were used to compare and analyze the active ingredients in the liquid, and 17 potential active ingredients with good drug-like properties were screened by in vivo pharmacokinetics process in SwissADME database. SwissTargetPrediction and GeneCards were searched to find 93 common targets. Cytoscape 3.8.2 software was used to construct the "component-target" network map, and the Metascape platform was used for gene function annotation and pathway enrichment analysis. It was found that the extract could regulate the positive response to external stimuli, inflammatory response, cytokine production and other biological processes by binding the active ingredients such as isorhamnetin, kaempferol, luteolin, quercetin and apigenin to the common targets (NOS3, MPO, MMP3, etc.), and play an anti-COVID-19 role. In the angiotensin-converting enzyme 2 (ACE2) activity inhibition assay, it was found that the stock solution of A. roxburghii liquid (for spray), and the supernatant after removing polysaccharides (mainly containing flavonoids) could to some extent inhibit the activity of ACE2. Crucially, in the experiment of 2019-nCOV-S pseudovirus infecting HEK-293T-ACE2 cells, we found that A. roxburghii liquid may exert anti-COVID-19 effects by blocking the binding of SARS-CoV-S protein to ACE2.

Following the principles of evidence-based medicine,in accordance with the structure and drafting rules of standardized documents,based on literature research,according to the characteristics of chronic cough in children and issues that need to form a consensus,the TCM Guidelines for Diagnosis and Treatment of Chronic Cough in Children was formulated based on the Delphi method,expert discussion meetings,and public solicitation of opinions.The guideline includes scope of application,terms and definitions,eti-ology and diagnosis,auxiliary examination,treatment,prevention and care.The aim is to clarify the optimal treatment plan of Chinese medicine in the diagnosis and treatment of this disease,and to provide guidance for improving the clinical diagnosis and treatment of chronic cough in children with Chinese medicine.

Background: Triglyceride glucose (TyG) and TyG-body mass index (TyG-BMI) are reliable surrogate indices of insulin resistance and used for risk stratification and outcome prediction in patients with atherosclerotic cardiovascular disease (ASCVD). Here, we inserted estimated average glucose (eAG) into the TyG (TyAG) and TyG-BMI (TyAG-BMI) as derived parameters and explored their clinical significance in cardiovascular risk prediction. Methods: This was a population-based cohort study of 9,944 Chinese patients with ASCVD. The baseline admission fasting glucose and A1C-derived eAG values were recorded. Cardiovascular events (CVEs) that occurred during an average of 38.5 months of follow-up were recorded. We stratified the patients into four groups by quartiles of the parameters. Baseline data and outcomes were analyzed. Results: Distribution of the TyAG and TyAG-BMI indices shifted slightly toward higher values (the right side) compared with TyG and TyG-BMI, respectively. The baseline levels of cardiovascular risk factors and coronary severity increased with quartile of TyG, TyAG, TyG-BMI, and TyAG-BMI (all P<0.001). The multivariate-adjusted hazard ratios for CVEs when the highest and lowest quartiles were compared from low to high were 1.02 (95% confidence interval [CI], 0.77 to 1.36; TyG), 1.29 (95% CI, 0.97 to 1.73; TyAG), 1.59 (95% CI, 1.01 to 2.58; TyG-BMI), and 1.91 (95% CI, 1.16 to 3.15; TyAG-BMI). The latter two showed statistical significance. Conclusion This study suggests that TyAG and TyAG-BMI exhibit more information than TyG and TyG-BMI in disease progression among patients with ASCVD. The TyAG-BMI index provided better predictive performance for CVEs than other parameters.