Objective: To characterize perioperative dynamic changes in immune-cell phenotypes and inflammatory cytokines in patients undergoing CPB (cardiopulmonary bypass) cardiac surgery, and to explore their associations with postoperative outcomes. Methods: In this prospective cohort study, 120 adult patients who underwent elective cardiac surgery under CPB at West China Hospital from May 2022 to March 2023 were enrolled. Perioperative immune-cell phenotypes and concentrations of 40 inflammation-related cytokines were measured. The primary outcomes were the sequential organ failure assessment (SOFA) score at 24 h after surgery and ΔSOFA (the peak SOFA score within 48 h after surgery minus the preoperative SOFA score). Secondary outcomes included major adverse cardiovascular events (MACE), acute kidney injury (AKI), respiratory failure, severe liver injury, and infection. Results: The mean age of enrolled patients was 57±10 years. Of these, 52% (62/120) were male and 90% (108/120) underwent valve surgery. During the rewarming to the end of CPB, neutrophil counts rapidly increased (7.39×10 /L vs preoperative 3.07×10 /L, P<0.001), with significant upregulation of CD11b (7.30×10 /L vs preoperative 3.05×10 /L, P<0.001) and CD54 (7.15×10 /L vs preoperative 2.99×10 /L, P<0.001). Lymphocyte counts increased at the end of CPB (1.75×10 /L vs preoperative 1.12×10 /L, P<0.001) but decreased significantly at 24 h after surgery (0.59×10 /L vs preoperative 1.12×10 /L, P<0.001). Plasma analysis showed that multiple pro-inflammatory cytokines increased during CPB and remained elevated up to 24 h after surgery; five chemokines and the anti-inflammatory cytokine IL-10 peaked at the end of CPB. The SOFA score increased from 1 (1, 2) preoperatively to 7 (5, 10) at 24 h after surgery, with a ΔSOFA of 6 (4, 8). Within 30 days after surgery, 48 patients (40.0%) developed AKI, 17 (14.2%) developed infection, 4 (3.3%) developed severe liver injury, 3 (2.5%) developed respiratory failure, and 3 (2.5%) experienced MACE. During the 2-year follow-up, 8 patients (6.7%) experienced MACE and 5 (4.2%) died. Conclusion: Multi-organ dysfunction is common after cardiac surgery under CPB (median ΔSOFA, 6), accompanied by perioperative activation of multiple immune-cell subsets and upregulation of pro-inflammatory, anti-inflammatory, and chemotactic mediators. This study provides data-driven evidence and research clues for further investigation of the associations between CPB-related immune perturbations and postoperative organ dysfunction and clinical outcomes.

Objective This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

Gastric cancer remains a highly prevalent malignancy worldwide, with surgical resection currently constituting the cornerstone of treatment aimed at improving long-term patient survival. Owing to their notable advantages, including reduced surgical trauma and accelerated postoperative recovery, minimally invasive procedures are progressively supplanting conventional open surgery and have become the mainstream approach in gastric cancer management. Concurrently, the rapid advancement of artificial intelligence (AI) technologies has enabled real-time intraoperative monitoring of surgical scenes, thereby furnishing novel technical support for adjunctive decision-making, surgical navigation, and skill assessment during gastrectomy. This article provides a systematic review of the current status of AI applications in minimally invasive gastric cancer surgery, with a particular focus on research progress pertaining to instrument recognition, surgical phase identification, delineation of normal anatomical structures, detection of metastatic foci, and early warning of intraoperative adverse events. Furthermore, we discuss the potential value of AI in enhancing surgical efficiency, ensuring patient safety, and optimizing surgical education. On this basis, we further analyze the principal challenges and inherent risks confronting current AI systems, with the aim of informing future technological innovation and facilitating clinical translation.

This study aims to explore the pharmacodynamic material basis of Jinbei Oral Liquid(JBOL) against idiopathic pulmonary fibrosis(IPF) based on serum pharmacochemistry and network pharmacology. The ultra-high performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry(UHPLC-Q-TOF-MS/MS) technology was employed to analyze and identify the components absorbed into rat blood after oral administration of JBOL. Combined with network pharmacology, the study explored the pharmacodynamic material basis and potential mechanism of JBOL against IPF through protein-protein interaction(PPI) network construction, "component-target-pathway" analysis, Gene Ontology(GO) functional enrichment, and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis. First, a total of 114 compounds were rapidly identified in JBOL extract according to the exact relative molecular mass, fragment ions, and other information of the compounds with the use of reference substances and a self-built compound database. Second, on this basis, 70 prototype components in blood were recognized by comparing blank serum with drug-containing serum samples, including 28 flavonoids, 25 organic acids, 4 saponins, 4 alkaloids, and 9 others. Finally, using these components absorbed into blood as candidates, the study obtained 212 potential targets of JBOL against IPF. The anti-IPF mechanism might involve the action of active ingredients such as glycyrrhetinic acid, cryptotanshinone, salvianolic acid B, and forsythoside A on core targets like AKT1, TNF, and ALB and thereby the regulation of multiple signaling pathways including PI3K/AKT, HIF-1, and TNF. In conclusion, JBOL exerts the anti-IPF effect through multiple components, targets, and pathways. The results would provide a reference for further study on pharmacodynamic material basis and pharmacological mechanism of JBOL.
Drugs, Chinese Herbal/pharmacokinetics* ; Animals ; Tandem Mass Spectrometry ; Network Pharmacology ; Rats ; Chromatography, High Pressure Liquid ; Rats, Sprague-Dawley ; Male ; Idiopathic Pulmonary Fibrosis/metabolism* ; Humans ; Administration, Oral ; Protein Interaction Maps/drug effects* ; Signal Transduction/drug effects*

This study selected 6 529 plant-based Chinese materia medica(PCMM) from Chinese Materia Medica as research subjects and applied a random permutation test to explore the overall correlation characteristics between nature and flavor, as well as the correlation characteristics after distinguishing different medicinal parts and harvest seasons. The results showed that the overall correlation characteristics between nature and flavor in PCMM were significantly associated in the following pairs: cold and bitter, cool and bitter, cool and astringent, cool and light, neutral and sweet, neutral and astringent, neutral and light, neutral and sour, hot and pungent, and warm and pungent. When analyzing the data by distinguishing medicinal parts and/or harvest seasons, new correlation patterns emerged, characterized by the disappearance of some significant correlations and the emergence of new ones. When analyzing by medicinal parts alone, significant correlations were found in the following cases: cold and light in leaves, cold and salty in barks, cool and sweet in fruits and seeds, neutral and pungent in whole herbs, neutral and salty in stems, and warm and salty in flowers. However, no significant correlations were found between cool and bitter in stems and other types of herbs, cool and astringent in fruits, seeds, flowers, and other types of herbs, cool and light in leaves, fruits, seeds, barks, flowers and other types of herbs, neutral and sweet in barks, neutral and astringent in whole herbs and stems, neutral and light in leaves, fruits, seeds, and flowers, neutral and sour in whole herbs, stems, barks, flowers, and other types of herbs, and hot and pungent in whole herbs, stems, flowers, and other types of herbs. When analyzing by harvest season alone, significant correlations were found in the following cases: cold and salty, and cool and sour in herbs harvested in winter, and neutral and salty in herbs harvested year-round. However, no significant correlation was found between cool and light in herbs harvested in winter. When considering both medicinal parts and harvest seasons, compared to the independent influence of medicinal parts, 14 new significant correlations emerged(e.g., the correlation between cool and bitter in stems harvested in spring), while 53 previously significant correlations disappeared(e.g., the correlation between cool and bitter in barks harvested in summer). Compared to the independent influence of harvest seasons, 11 new significant correlations appeared(e.g., the correlation between cold and light in barks harvested in autumn), while 50 previously significant correlations disappeared(e.g., the correlation between hot and pungent in leaves harvested in winter). This study is the first to reveal the influence of medicinal parts and harvest seasons on the correlation between nature and flavor in PCMM, which highlights that these two factors can interact and jointly affect nature-flavor correlations. Further research is needed to explore the underlying mechanisms. This study provides a deeper understanding of the inherent scientific connotations of herbal properties and offers a theoretical foundation for the cultivation and harvesting of PCMM.
Seasons ; Plants, Medicinal/growth & development* ; Drugs, Chinese Herbal/chemistry* ; Taste

OBJECTIVE: To investigate the associations between eight serum per- and polyfluoroalkyl substances (PFASs) and regional fat depots, we analyzed the data from the National Health and Nutrition Examination Survey (NHANES) 2011-2018 cycles. METHODS: Multiple linear regression models were developed to explore the associations between serum PFAS concentrations and six fat compositions along with a fat distribution score created by summing the concentrations of the six fat compositions. The associations between structurally grouped PFASs and fat distribution were assessed, and a prediction model was developed to estimate the ability of PFAS exposure to predict obesity risk. RESULTS: Among females aged 39-59 years, trunk fat mass was positively associated with perfluorooctane sulfonate (PFOS). Higher concentrations of PFOS, perfluorohexane sulfonate (PFHxS), perfluorodecanoate (PFDeA), perfluorononanoate (PFNA), and n-perfluorooctanoate (n-PFOA) were linked to greater visceral adipose tissue in this group. In men, exposure to total perfluoroalkane sulfonates (PFSAs) and long-chain PFSAs was associated with reductions in abdominal fat, while higher abdominal fat in women aged 39-59 years was associated with short-chain PFSAs. The prediction model demonstrated high accuracy, with an area under the curve (AUC) of 0.9925 for predicting obesity risk. CONCLUSION PFAS exposure is associated with regional fat distribution, with varying effects based on age, sex, and PFAS structure. The findings highlight the potential role of PFAS exposure in influencing fat depots and obesity risk, with significant implications for public health. The prediction model provides a highly accurate tool for assessing obesity risk related to PFAS exposure.
Humans ; Fluorocarbons/blood* ; Female ; Adult ; Middle Aged ; Male ; Environmental Pollutants/blood* ; Abdominal Fat ; Nutrition Surveys ; Alkanesulfonic Acids/blood* ; Obesity ; Environmental Exposure

Objective To establish a stable,reliable,and clinically relevant porcine model of endotoxin-induced acute respiratory distress syndrome(ARDS).Methods Ten 8-month-old male Bama minipigs were deeply sedated,followed by invasive mechanical ventilation and electrocardiographic monitoring.Lipopolysaccharide(LPS)was intravenously pumped at 600 μg/(kg·h)for 3 hours,then maintained at 15 μg/(kg·h)thereafter.Dynamic monitoring was performed at five time points after LPS injection(LPS 0,1,3,5,and 8 h),including arterial blood gas analysis and chest computed tomography(CT)scans.Pathological examination of lung tissues obtained via bronchoscopic biopsy(HE staining and transmission electron microscopy)was conducted.These indicators were comprehensively used to evaluate the success of the animal model.Results At 5 hours after LPS administration,8 minipigs developed symptoms such as skin cyanosis,elevated body temperature,and respiratory distress.The oxygenation index decreased to<300 mmHg.Chest CT scans showed diffuse pulmonary infiltrates.Histopathology revealed alveolar edema and hyaline membrane formation.Transmission electron microscopy demonstrated disruption of pulmonary blood-air barrier,depletion of lamellar bodies in type Ⅱ pneumocytes,inflammatory cell infiltration,and exudation of plasma proteins and fibrin.Compared with LPS 0 h,at LPS 8 h,the oxygenation index and arterial blood pH were significantly decreased(P<0.001),while blood lactic acid and serum potassium were significantly increased(P<0.05);serum calcium and base excess were significantly decreased(P<0.05),and the lung injury score based on HE-stained lung sections was significantly increased(P<0.01).Conclusion The porcine ARDS model established by continuous LPS injection can dynamically simulate the pathophysiological characteristics and typical pathological manifestations of clinical septic ARDS,making it an effective tool to study the pathogenesis,prevention,and treatment strategies of septic ARDS.

With the rapid development of deep learning(DL)technology,its potential applications in the medical field have become increasingly prominent.As a refractory disease,osteonecrosis of the femoral head(ONFH)has certain limitations in traditional diagnostic and therapeutic approaches.The application of DL technology is expected to overcome these limitations and improve diagnosis and treatment outcomes.At present,the applications of DL models-including enhancing image clarity,improving diagnostic accuracy and efficiency,conducting prognostic evaluations,optimizing preoperative planning,assisting intraoperative imaging,and customizing personalized treatment plans-have fully demonstrated their tremendous potential in the diagnosis and treatment of ONFH.This review summarizes the current application status of DL in ONFH diagnosis and treatment,aiming to provide references and insights for future related research.

Objective To analyze the relationship between obesity indicators,muscle mass indices and hypertension in Dongxiang adults,and establish and evaluate a Nomogram model based on these indicators used to predict the risk of hypertension in this population.Methods A total of 1209 Dongxiang adults from Linxia Prefecture,Gansu Province were selected,11 obesity indicators and 5 muscle mass indicators,including neck circumference(NC),waist-to-hip ratio(WHR),BMI,ponderal index(PI),conicity index(CI),a body shape index(ABSI),body roundness index(BRI),abdominal volume index(AVI),hip index(HI),body adiposity index(BAI),and the ratio of limb fat mass to body weight(LFWR),appendicular skeletal muscle mass(ASM),appendicular skeletal muscle mass index(ASMI),appendicular skeletal muscle mass to BMI ratio(ASMBMI),skeletal muscle index(SMI),and trunk muscle mass to body weight ratio(TMWR)were measured.Logistic regression analysis was used to explore the relationship between each indicator and hypertension.Nomogram prediction model was constructed and validated by using R language.Results Among Dongxiang males,the NC,BMI,PI,WHR,CI,AVI,BRI,BAI,ASM,ASMI,and LFWR were lower in the normal and high-normal blood pressure groups compared to the hypertensive group,while SMI,ASMBMI,and TMWR were higher.Among females,similar trends were observed,with lower NC,BMI,PI,WHR,CI,AVI,BRI,BAI,and LFWR in the normal blood pressure and high-normal blood pressure groups compared to the hypertensive group,but SMI,ASMBMI,and TMWR higher than the hypertensive group(P＜0.05).Results of multivariate Logistic regression analysis indicated that age,NC,and WHR were risk factors for hypertension in Dongxiang adults,while was protective factor(P＜0.05).The area under curve(AUC)of the Nomogram model constructed based on these factors was 0.796,and the Bootstrap internal validation C-index was 0.7957,indicating good calibration of the model.Conclusion The Nomogram model constructed based on obesity and muscle mass indicators has good predictive efficiency for predicting the risk of hypertension in Dongxiang adults.