OBJECTIVE To analyze the prototype components absorbed into blood and brain of Lithocarpus litseifolius leaves， so as to provide a reference for clarifying the pharmacological material basis of its prevention and treatment of central nervous system dis eases. METHODS The ethanol extract of L. litseifolius leaves， as well as the gastric lavage fluid and perfusion solution were prepared. Using rats as subjects， plasma samples of intestinal wall metabolism， intestinal flora metabolism and hepatic metabolism were prepared via in situ intestinal perfusion and closed intestinal loop method； while comprehensive metabolic plasma samples， brain tissue samples， and cerebrospinal fluid samples were collected after intragastric administration. UPLC-HRMS technology was utilized to analyze and identify chemical components and prototype components absorbed into blood and brain of L. litseifolius leaves. RESULTS A total of 66 chemical constituents were identified in L. litseifolius leaves， primarily consisting of flavonoids， organic acids， and others. A total of 16， 13， 11， and 5 prototype components were identified in intestinal wall metabolism， intestinal flora metabolism， hepatic metabolism， and comprehensive metabolic plasma samples， respectively. Additionally， 4 prototype components were detected in brain tissue and 9 in cerebrospinal fluid. Phloridzin， trilobatin， phloretin-2- O -malonyl hexoside， and phloretin were identified as common components across all sample types. CONCLUSIONS Prototype components absorbed into blood and brain of L. litseifolius leaves， such as phloridzin， trilobatin， phloretin， and other components may serve as the pharmacological material basis for their therapeutic effects on central nervous system diseases.

BACKGROUND:Currently,treatment method for knee osteoarthritis includes oral medicine,joint cavity drug injection,and physiotherapy,but the curative effect is limited.Existing studies have confirmed that silicon-based bioceramics can promote cartilage and subchondral bone repair and vascular regeneration.OBJECTIVE:To explore the effect of different concentrations of silicon-based bioceramics injected into the knee joint cavity in the treatment of knee osteoarthritis in rats.METHODS:Silicon-based bioceramics-calcium silicate was prepared.Twenty-five SD rats were randomly divided into five groups,with five rats in each group.The healthy group did not receive any intervention,and the modeling group,low-dose calcium silicate group,high-dose calcium silicate group,and saline group used anterior cruciate ligament transection to establish bilateral knee osteoarthritis models.Four weeks after modeling,0.05 mL of 50 and 100 mg/mL calcium silicate solution were injected into the knee joint cavity in the low-dose calcium silicate group and high-dose calcium silicate group,respectively,and 0.05 mL of saline was injected into the knee joint cavity in the saline group,once a week for 4 consecutive weeks.In the fifth week of administration,bilateral knee joint Micro-CT detection,knee joint cartilage hematoxylin-eosin staining,and modified Mankin score were performed.RESULTS AND CONCLUSION:(1)Micro-CT quantitative analysis showed that compared with the healthy group,the volume fraction and number of trabeculae of the medial tibial plateau in the modeling group decreased(P＜0.05),and the separation of trabeculae increased(P＜0.05).Compared with the modeling group,the volume fraction and number of trabeculae of the medial tibial plateau in the low-dose calcium silicate group and the saline group increased(P＜0.05),and the separation of trabeculae decreased(P＜0.05).(2)Hematoxylin-eosin staining showed that the cartilage surface of the healthy group and the low-dose calcium silicate group was relatively smooth and flat,the chondrocytes were evenly distributed,without clustered chondrocytes,the tide line was complete,and the staining was uniform;the cartilage surface of the high-dose calcium silicate group was slightly uneven,the middle and deep cells were disordered,with a small number of clustered chondrocytes,the tide line was discontinuous,and the staining was uneven;the cartilage surface of the saline group and the modeling group was obviously rough,the cells were disordered,with a large number of clustered chondrocytes,the tide line disappeared,and the staining was uneven.The modified Mankin score of the healthy group was lower than that of the high-dose calcium silicate group,the saline group,and the modeling group(P＜0.05).The modified Mankin score of the high-dose calcium silicate group and the low-dose calcium silicate group was lower than that of the saline group and the modeling group(P＜0.05).(3)The results show that calcium silicate knee joint injection has a certain effect in the treatment of knee osteoarthritis.Compared with 100 mg/mL calcium silicate solution,50 mg/mL calcium silicate solution can promote the recovery of subchondral bone and cartilage.

BACKGROUND:Currently,treatment method for knee osteoarthritis includes oral medicine,joint cavity drug injection,and physiotherapy,but the curative effect is limited.Existing studies have confirmed that silicon-based bioceramics can promote cartilage and subchondral bone repair and vascular regeneration.OBJECTIVE:To explore the effect of different concentrations of silicon-based bioceramics injected into the knee joint cavity in the treatment of knee osteoarthritis in rats.METHODS:Silicon-based bioceramics-calcium silicate was prepared.Twenty-five SD rats were randomly divided into five groups,with five rats in each group.The healthy group did not receive any intervention,and the modeling group,low-dose calcium silicate group,high-dose calcium silicate group,and saline group used anterior cruciate ligament transection to establish bilateral knee osteoarthritis models.Four weeks after modeling,0.05 mL of 50 and 100 mg/mL calcium silicate solution were injected into the knee joint cavity in the low-dose calcium silicate group and high-dose calcium silicate group,respectively,and 0.05 mL of saline was injected into the knee joint cavity in the saline group,once a week for 4 consecutive weeks.In the fifth week of administration,bilateral knee joint Micro-CT detection,knee joint cartilage hematoxylin-eosin staining,and modified Mankin score were performed.RESULTS AND CONCLUSION:(1)Micro-CT quantitative analysis showed that compared with the healthy group,the volume fraction and number of trabeculae of the medial tibial plateau in the modeling group decreased(P＜0.05),and the separation of trabeculae increased(P＜0.05).Compared with the modeling group,the volume fraction and number of trabeculae of the medial tibial plateau in the low-dose calcium silicate group and the saline group increased(P＜0.05),and the separation of trabeculae decreased(P＜0.05).(2)Hematoxylin-eosin staining showed that the cartilage surface of the healthy group and the low-dose calcium silicate group was relatively smooth and flat,the chondrocytes were evenly distributed,without clustered chondrocytes,the tide line was complete,and the staining was uniform;the cartilage surface of the high-dose calcium silicate group was slightly uneven,the middle and deep cells were disordered,with a small number of clustered chondrocytes,the tide line was discontinuous,and the staining was uneven;the cartilage surface of the saline group and the modeling group was obviously rough,the cells were disordered,with a large number of clustered chondrocytes,the tide line disappeared,and the staining was uneven.The modified Mankin score of the healthy group was lower than that of the high-dose calcium silicate group,the saline group,and the modeling group(P＜0.05).The modified Mankin score of the high-dose calcium silicate group and the low-dose calcium silicate group was lower than that of the saline group and the modeling group(P＜0.05).(3)The results show that calcium silicate knee joint injection has a certain effect in the treatment of knee osteoarthritis.Compared with 100 mg/mL calcium silicate solution,50 mg/mL calcium silicate solution can promote the recovery of subchondral bone and cartilage.

In recent years, China has been facing the dual challenges of declining fertility rates and births, with male reproductive health issues, especially the decline in semen quality, identified as a pivotal contributor to this phenomenon. Meanwhile, accumulating evidence indicates that air pollutants, an increasingly severe environmental problem, can damage semen quality not only directly through their biological toxicity but also indirectly by disrupting the composition of microbial communities in the gut and semen, thereby dysregulating immune function, endocrine homeostasis, and oxidative stress responses. The gut microbiota and semen microbiota, as important components of the human microecosystem, play crucial roles in maintaining reproductive health. This article comprehensively reviewed the research progress on the potential effects of air pollutants (particulate matter and gaseous pollutants), gut microbiota, and semen microbiota on semen quality. Specifically, it elucidated the mechanisms of interaction between these factors and explored how they affect male fertility.

BACKGROUND: The effect of the interval between previous Helicobacter pylori (H. pylori) eradication and rescue treatment on therapeutic outcomes remains unknown. The aim of this study was to investigate the association between eradication rates and treatment interval durations in H. pylori infections. METHODS: This prospective observational study was conducted from December 2021 to February 2023 at six tertiary hospitals in Shandong, China. We recruited patients who were positive for H. pylori infection and required rescue treatment. Demographic information, previous times of eradication therapy, last eradication therapy date, and history of antibiotic use data were collected. The patients were divided into four groups based on the rescue treatment interval length: Group A, ≥4 weeks and ≤3 months; Group B, >3 and ≤6 months; Group C, >6 and ≤12 months; and Group D, >12 months. The primary outcome was the eradication rate of H. pylori . Drug compliance and adverse events (AEs) were also assessed. Pearson's χ2 test or Fisher's exact test was used to compare eradication rates between groups. RESULTS: A total of 670 patients were enrolled in this study. The intention-to-treat (ITT) eradication rates were 88.3% (158/179) in Group A, 89.6% (120/134) in Group B, 89.1% (123/138) in Group C, and 87.7% (192/219) in Group D. The per-protocol (PP) eradication rates were 92.9% (156/168) in Group A, 94.5% (120/127) in Group B, 94.5% (121/128) in Group C, and 93.6% (190/203) in Group D. There was no statistically significant difference in the eradication rates between groups in either the ITT ( P = 0.949) or PP analysis ( P = 0.921). No significant differences were observed in the incidence of AEs ( P = 0.934) or drug compliance ( P = 0.849) between groups. CONCLUSION: The interval duration of rescue treatment had no significant effect on H. pylori eradication rates or the incidence of AEs. REGISTRATION ClinicalTrials.gov , NCT05173493.
Humans ; Helicobacter Infections/drug therapy* ; Helicobacter pylori/pathogenicity* ; Male ; Female ; Prospective Studies ; Middle Aged ; Anti-Bacterial Agents/adverse effects* ; Adult ; Aged ; Treatment Outcome ; Proton Pump Inhibitors/therapeutic use*

BACKGROUND: The profile and clinical significance of the oral microbiome in patients with non-obstructive hypertrophic cardiomyopathy (noHCM) and obstructive hypertrophic cardiomyopathy (oHCM) remain unexplored. The objective of this study was to evaluate the difference of oral microbiome between noHCM and oHCM patients. METHODS: This cross-sectional study enrolled 18 noHCM patients and 26 oHCM patients from Fuwai Hospital, Chinese Academy of Medical Sciences between 2020 and 2021. Clinical and periodontal evaluations were conducted, and subgingival plaque samples were collected. Metagenomic sequencing and subsequent microbial composition and functional analyses were performed. RESULTS: Compared to oHCM patients, those with noHCM had higher systolic blood pressure (138.1 ± 18.8 mmHg vs . 124.2 ± 13.8 mmHg, P = 0.007), a larger body circumference (neck circumference: 39.2 ± 4.0 cm vs . 35.1 ± 3.7 cm, P = 0.001; waist circumference: 99.7 ± 10.5 cm vs . 92.2 ± 10.8 cm, P = 0.027; hip circumference: 102.5 ± 5.6 cm vs . 97.5 ± 9.1 cm, P = 0.030), a greater left ventricular end-diastolic diameter (46.6 ± 4.9 mm vs . 43.1 ± 4.9 mm, P = 0.026), and a lower left ventricular ejection fraction (64.1 ± 5.7 % vs . 68.5 ± 7.8%, P = 0.048). While overall biodiversity and general microbial composition were similar between the noHCM and oHCM groups, ten taxa displayed significant differences at the genus and species levels, with Porphyromonas gingivalis showing the highest abundance and greater enrichment in noHCM (relative abundance: 7.79535 vs . 4.87697, P = 0.043). Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis identified ten distinct pathways, with pathways related to energy and amino acid metabolism being enriched in oHCM patients, and those associated with genetic information processing less abundant in the oHCM group. Metabolic potential analysis revealed ten significantly altered metabolites primarily associated with amino sugar and nucleotide sugar metabolism, porphyrin metabolism, pentose and glucuronate interconversion, and lysine degradation. CONCLUSIONS The higher abundance of Porphyromonas gingivalis , which is known to impact cardiovascular health, in noHCM patients may partially account for clinical differences between the groups. Pathway enrichment and metabolic potential analyses suggest microbial functional shifts between noHCM and oHCM patients, potentially reflecting inherent metabolic changes in HCM.
Humans ; Cardiomyopathy, Hypertrophic/microbiology* ; Female ; Male ; Microbiota/genetics* ; Middle Aged ; Cross-Sectional Studies ; Adult ; Mouth/microbiology* ; Aged

With the emergence of deep learning techniques based on convolutional neural networks, artificial intelligence (AI) has driven transformative developments in the field of medical image analysis. Recently, large language models (LLMs) such as ChatGPT have also started to achieve distinction in this domain. Increasing research shows the undeniable role of AI in reshaping various aspects of medical image analysis, including processes such as image enhancement, segmentation, detection in image preprocessing, and postprocessing related to medical diagnosis and prognosis in clinical settings. However, despite the significant progress in AI research, studies investigating the recent advances in AI technology in the aforementioned aspects, the changes in research hotspot trajectories, and the performance of studies in addressing key clinical challenges in this field are limited. This article provides an overview of recent advances in AI for medical image analysis and discusses the methodological profiles, advantages, disadvantages, and future trends of AI technologies.
Artificial Intelligence ; Humans ; Image Processing, Computer-Assisted/methods* ; Neural Networks, Computer ; Deep Learning ; Diagnostic Imaging/methods*

To explore the feasibility of using UAV-LiDAR for measuring the leaf area index (LAI) of crop canopies, we employed UAV-LiDAR to scan sugarcane canopies during the tillering and elongation stages, acquiring canopy point cloud data. Subsequently, features such as average row height, projected row area, point cloud density at different canopy layers, and the ratios between these parameters were extracted. Three feature selection methods-partial least squares regression (PLSR), XGBoost feature importance (XGBoost-FI), and random forest-recursive feature elimination (RF-RFE)-were adopted to evaluate and identify the optimal input variables for modeling. With these selected variables, LAI inversion models were developed based on random forest (RF) and adaptive boosting (AdaBoost) algorithms, and their performance was assessed. Among the extracted features, the projected row area S_p and the total row point count C_total exhibited strong correlations with LAI, with correlation coefficients of 0.73 and 0.72, respectively. The AdaBoost-based LAI inversion model, using the projected row area S_p, average height H_avg, mid-layer point cloud density C_m, and total row point count C_total as input variables, achieved the best performance, with a coefficient of determination (R_v²) of 0.713 and a root mean square error (RMSE_v) of 0.25 on the validation set. This study provides an effective method for high-throughput acquisition of LAI in field crops, offering valuable scientific support for sugarcane field management and breeding efforts.
Plant Leaves/growth & development* ; Saccharum/growth & development* ; Algorithms ; Unmanned Aerial Devices ; Remote Sensing Technology/methods* ; Crops, Agricultural/growth & development*

The research on the cardiovascular toxicity of air pollutants is in urgent need of collaborative innovation across multiple models. This paper systematically reviewed the advantages and limitations of four principal research models of cardiotoxicity, including epidemiological model, mammalian model, zebrafish model, and in vitro model. Epidemiological models have been used to demonstrate a significant correlation between exposure to PM_2.5 and both the incidence and mortality of cardiovascular diseases within populations; however, these models face challenges in establishing causal inferences and interpreting individual mechanisms. Mammalian models have been applied to elucidate the pathogenic mechanisms of PM_2.5 at both the systemic and organ-specific levels, yet they encounter difficulties related to interspecies differences and throughput constraints. Zebrafish models, with their transparent embryos and observable development, offer a distinctive opportunity for high-throughput screening and mechanistic investigation of PM_2.5-induced cardiac developmental toxicity. Nonetheless, their cardiac physiological structure diverges from that of mammals, limiting their capacity to accurately model chronic conditions such as coronary heart disease. In vitro models, particularly human heart organoids and chip technologies, have provided profound insights into the direct toxic mechanisms of PM_2.5, including disruptions in calcium homeostasis, cellular senescence, and electrophysiological irregularities at the cellular and molecular levels. Despite these advancements, the complexity and developmental maturity of these models present challenges to their broader application. This paper proposed that the key to overcoming the bottlenecks of single models lies in the construction of an integrated evaluation system that combines “epidemiological studies, mammalian models, zebrafish models, and in vitro models”. By focusing on three aspects, namely model integration, technological convergence, and policy support, it is intended to collaboratively address issues such as standardization of multi-model data, simulation of complex exposure scenarios and susceptible life stages, and transformation pathways. This will provide innovative methodological support for the analysis of the cardiotoxic mechanisms of air pollutants, the assessment of environmental health impacts, and the formulation of precise prevention and control strategies.

Objective Focusing on gynecological surgery,we constructed a prediction model for surgical duration by extracting features from unstructured surgical planning texts and integrating multimodal data via artificial intelligence technology.Methods The clinical data of 34 614 patients who underwent gynecologic surgeries at West China Second University Hospital,Sichuan University between January 2022 and October 2024 were collected.An embedding-transformer model was constructed to convert surgical planning texts into a one-dimensional numerical feature,referred to as the step feature.The predictive value of the step feature was assessed by comparing the performance improvements of linear regression,random forest,eXtreme Gradient Boosting(XGBoost),support vector regression,K-nearest neighbor regression,and artificial neural network algorithms in two scenarios—with and without the step feature as an input.The out-of-sample prediction accuracy of the models was assessed using mean absolute error(MAE),root mean squared error(RMSE),and R-squared(R2).Furthermore,the model interpretability was examined using SHapley Additive exPlanations(SHAP)values.Results SHAP results showed that the step feature had the highest predictive contribution.Temporal factors in surgical scheduling also influenced gynecological surgery duration.The XGBoost model demonstrated optimal performance on the test set,significantly improving prediction accuracy with a 40.43%increase in R2,while reducing MAE and RMSE by 21.27%and 20.13%,respectively,compared to the baseline model without the step feature.Conclusion The embedding-transformer model developed in this study effectively extracts features from surgical planning texts and enhances the predictive performance of machine learning models.The XGBoost prediction model can assist hospital administrators in implementing more refined management of gynecological surgeries and improving the utilization efficiency of surgical resources.