Objective:To explore the application value of machine learning prediction model for neural invasion in gallbladder cancer based on enhanced computed tomography (CT) and clinical characteristics.Methods:The retrospective cohort study was conducted. The clinical and imaging data of 502 patients with gallbladder cancer who were admitted to The First Affiliated Hospital of Xinxiang Medical University from January 2010 to June 2024 were collected. There were 171 males and 331 females, aged 65(range, 35?91)years. All patients underwent preoperative abdominal enhanced CT and radical resection. The 502 patients were randomly divided into a training set of 351 cases and a test set of 151 cases at a 7:3 ratio. The training set was used to construct prediction model, and the test set was used to validate prediction model. Observation indicators: (1)neural invasion in gallbladder cancer and influencing factor analysis; (2) construction and validation of machine learning prediction models for neural invasion in gallbladder cancer. Comparison of count data between groups was conducted using the chi-square test. Comparison of ordinal data between groups was conducted using the Mann-Whitney U test. Logistic regression model was performed for univariate and multivariate analyses. Independent influencing factors were incor-porated to construct machine learning models using the standard library modules based on Python 3.9. Receiver operating characteristic (ROC) curves were plotted, and the accuracy, sensitivity, specificity, area under the curve (AUC), precision, F1 score, positive predictive value, negative predic-tive value, and Kappa value were calculated to evaluate the predictive performance of the models. The Delong test was used to assess the differences in AUC among different models in the test set. The Hosmer-Lemeshow test and Brier score were used to evaluate the calibration of the models. Results:(1) Neural invasion in gallbladder cancer and influencing factor analysis. Of the 502 patients with gallbladder cancer, 131 cases had neural invasion, and 371 cases had no neural invasion. Results of multivariate analysis showed that total bilirubin, carcinoembryonic antigen, CA199, CA125, neutrophil-lymphocyte ratio, liver invasion detected by CT, vascular invasion detected by CT, hilar or retroperi-toneal lymph node metastasis detected by CT, and tumor stages T3 and T4 were independent influencing factors for neural invasion in patients with gallbladder cancer [ odds ratios=3.747, 2.395, 3.917, 3.596, 2.805, 2.377, 3.523, 2.774, 5.080, 6.809, 95% confidence interval ( CI) as 1.890?7.430, 1.154?4.971, 2.054?7.472, 1.807?7.155, 1.506?5.225, 1.241?4.553, 1.666?7.449, 1.483?5.189, 2.050?12.589, 2.552?18.168, P<0.05]. (2) Construction and validation of machine learning predic-tion models for neural invasion in gallbladder cancer. Based on the independent influencing factors, seven machine learning models were constructed, including logistic regression, K-nearest neighbors, support vector machine, random forest, decision tree, back-propagation neural network, and gradient boosting machine. The ROC curves of seven machine learning models in the test set were plotted, and the AUC were 0.900(95% CI as 0.851?0.948), 0.741(95% CI as 0.646?0.829), 0.836(95% CI as 0.762?0.895), 0.782(95% CI as 0.701?0.855), 0.839(95% CI as 0.770?0.901), 0.817(95% CI as 0.738?0.887), 0.843(95% CI as 0.770?0.909), respectively. Results of Delong test showed that the logistic regression model had the highest AUC. The sensitivity and specificity of the logistic regression model were 0.868 and 0.805 respectively, indicating the best balance. Results of Hosmer-Lemeshow test showed that the logistic regression model had a good goodness-of-fit ( χ2=5.320, P>0.05). The Brier score of the logistic regression model was relatively low, as 0.168, which verified its calibration advantage. Conclusion:Total bilirubin, carcinoembryonic antigen, CA199, CA125, neutrophil-to-lymphocyte ratio, liver invasion detected by enhanced CT, vascular invasion detected by enhanced CT, hilar or retroperitoneal lymph node metastasis detected by enhanced CT, and tumor stages T3 and T4 are independent influencing factors for nerve invasion in patients with gallbladder cancer. Seven machine learning models are constructed based on enhanced CT and clinical characteristics to predict neural invasion in gallbladder cancer, of which the logistic regression model demonstrates good predictive performance.

Objective:To investigate the application value of Bama miniature pig model in endoscopic retrograde cholangiopancreatography (ERCP) training.Methods:The experimental study was conducted. Six Bama miniature pigs were selected to establish animal model for ERCP operation. The experimental equipments were the EP-6000 image processing system and ED-580T therapeutic duodenoscopy, and the surgery was performed by two experienced chief physicians. Observation indicators: (1) surgical operation status; (2) preoperative and postoperative physiological and biochemical indicators of experimental animals; (3) experimental endpoint indicators. Measurement data with normal distribution were represented as Mean± SD, and measurement data with skewed distribution were represented as M(range). Count data were expressed as absolute numbers. Results:(1) Surgical operation status. During the operation, the time required for the duodenoscope to pass from the esophageal inlet to the pylorus of the six experimental animals was 151(range, 46-227)seconds, the insertion length of the endoscope at the pylorus was 85(range, 80-90)cm, and the straightened length of the endoscope shaft was 47(range, 45-50)cm. For bile duct cannulation, the total number of cannulation attempts was 2.0(range, 1.0-3.0), the number of successful cannulation was 1.5(range, 1.0-2.0), and the time of successful cannulation was 44(range, 13-80)seconds. For pancreatic duct cannulation, the total number of cannulation attempts was 3.0(range, 1.0-8.0), and only one successful intubation was performed for each experimental animal, with the time of successful cannulation as 100(range, 53-320)seconds. (2) Preoperative and postoperative physiological and biochemical indicators of experimental animals. For six experimental animals, the preoperative body temperature was (38.8±0.1)℃, serum amylase was (55.3±0.2)U/dL, serum lipase was 232.9(range, 29.4-547.3)U/L, alanine aminotransferase was (51±10)U/L, aspartate aminotransferase was (38±12)U/L, and total bilirubin was (3.2±0.7)μmol/L. At 24 hours postoperatively, the body temperature was (38.6±0.1)℃, serum amylase was (53.0±6.0)U/dL, serum lipase was 62.4(range, 29.4-94.1)U/L, alanine amino-transferase was (54±5)U/L, aspartate aminotransferase was (67±27)U/L, and total bilirubin was (3.5±1.9)μmol/L. (3) Experimental endpoint indicators. At the experimental endpoint of 14 days after surgery, the bile duct length in the six experimental animals was (8.6±1.2)cm, and the bile duct inner diameter was (2.5±0.5)mm. The pancreatic duct length was 12.9(range, 3.7-20.8)cm, and the inner diameter was (1.6±0.2)mm. Results of histopathological examination revealed that both CD3 and CD68 staining were negative in the bile duct and surrounding hepatic tissue, as well as in the pancreatic duct and adjacent pancreatic tissue at the experimental endpoint of 14 days after surgery.Conclusion:Bama miniature pig model can be used for ERCP training.

Plastics are widely used in all areas of human life,providing convenience while also causing serious en-vironmental pollution problems.Microplastic pollution is one of its derivative problems.Microplastics are plastic parti-cles with a diameter of less than 5 mm.They are currently widely present in the environment,so humans are at considera-ble risk of exposure to microplastics.Humans are mainly exposed to microplastics through the respiratory tract,digestive tract and skin.When exposed to a large number of microplastics,some of them will enter the body and be transported throughout the body via the bloodstream,accumulating in multiple tissues and organs.A significant amount of microplas-tics has also been detected in the cardiovascular system.This paper systematically describes human exposure to and dam-age by microplastics,highlighting the distribution and pathological damage of microplastics in the cardiovascular system.The pathological mechanisms of cardiovascular damage caused by microplastics are analyzed,and relevant clinical research progress is followed.This paper aims to evaluate the pathological risk of microplastics from the perspective of cardiovascu-lar damage,and provide a basis for disease prevention and scientific prevention and control of microplastic pollution.

Objective To explore the possible mechanism of T cell immunoglobulin and mucin domain-containing protein-3(TIM-3)regulating M2 macrophage polarization through Galectin-3 in lung injury induced by Streptococcals pneumoniae pneumonia(SPP)in mice.Methods Thirty mice were divided into control group,SPP group and SPP+TIM-3 inhibition group,with 10 mice in each group.The macrophage cell line RAW 264.7 was cultured and divided into a control group,with the SPP group versus the SPP+TIM-3 inhibition group.Lung histopathology was detected by hematoxylin-eosin(H&E)staining.Serum and cell supernatant tumor necrosis factor-α(TNF-α),interleukin-1β(IL-1β)and IL-6 content were measured by enzyme-linked immunosorbent assay(ELISA).Western blotting the protein levels of TIM-3 and Galectin-3 were determined in lung tissues and macrophages.Cluster of differentiation(CD)206,CD86 mRNA levels in lung tissue and macrophages were determined by real time quantitative PCR(RT-qPCR).Results Compared with the control group,the SPP group had significantly abnormal lung tissue pathological structure,thickened alveolar septum,a large number of inflammatory cells infiltration,a large amount of exudate in alveolar space,and increased serum inflammatory factors TNF-α,IL-6 and IL-1β,the protein and mRNA expressions of CD86,the marker protein of M1 macrophages,and the protein and mRNA expressions of CD206,the marker protein of M2 macrophages,and the protein expressions of TIM-3 and Galectin-3 in lung tissues were significantly increased in the model group,and the differences were statistically significally(t=8.36～76.30,all P<0.05).Compared with the SPP group,the SPP+TIM-3 inhibition group had improved lung tissue pathological damage,reduced alveolar septum thickness,inflammatory cell infiltration,reduced exudate in alveolar space,decreased serum inflammatory factors TNF-α,IL-6 and IL-1β content,and decreased expression of CD86 protein and mRNA in lung tissue.The expression of CD206 protein and mRNA was increased,the expression of TIM-3 protein was decreased,and the expression of Galectin-3 protein was increased,and the differences were statistically significant(t=10.67～63.32,all P<0.05).Cell experiments were consistent with this result.Conclusion Inhibition of TIM-3 can improve lung injury in SPP mice by down-regulating the expression of Galectin-3 and promoting M2 macrophage polarization.

Aim To investigate the effects of m6A demethylase ALKBH5 on cardiomyocytes pyroptosis in mice with myocardial infarction(MI).Methods The MI model of left anterior descending coronary artery ligation surgery was established by knocking down ALKBH5 using adeno-associated virus,and the hypox-ia model of mouse cardiomyocytes(HL-1)was estab-lished by knocking down small interfering RNA.The effects of ALKBH5 on the pyroptosis of MI mice and hypoxic HL-1 cells were observed.Subsequently,mechanism studies were conducted at the cellular lev-el,and the binding of ALKBH5 and IGF2BP2 to NL-RP3 mRNA was detected through RNA pull down and RNA immunoprecipitation(RIP)experiments.The MeRIP-qPCR method was used to determine the effects of ALKBH5 on the mRNA m6A level of NLRP3.Acti-nomycin D for RNA stability experiments were conduc-ted to detect the effects of ALKBH5 and IGF2BP2 on the stability of NLRP3 mRNA.Results Knocking down ALKBH5 in vivo and in vitro both inhibited NL-RP3 inflammasome activation and alleviated pyroptosis in MI mice and hypoxic HL-1 cells.Mechanistically,the results showed that NLRP3 mRNA could bind to ALKBH5 protein in HL-1 cells;knocking down ALK-BH5 could increase the m6A level of NLRP3 and re-duce the stability of NLRP3 mRNA;subsequently,it was confirmed that NLRP3 mRNA and IGF2BP2 pro-tein bound to each other;knocking down IGF2BP2 in-creased the mRNA stability of NLRP3.The Rescue ex-periment showed that knocking down IGF2BP2 re-versed the decrease in NLRP3 mRNA expression caused by knocking down ALKBH5.Conclusions ALKBH5 mediated m6A modification of NLRP3 pro-motes cardiomyocytes pyroptosis in mice with myocardi-al infarction.

Endometriosis(EMs)is a common estrogen-depend-ent clinical disease with the pathological characteristics of malig-nant tumors,which has great impact on women's physical and mental health.In recent years,experimental exploration has re-vealed that ectopic foci are in a hypoxic environment outside the uterine cavity,and mitochondria,as the"functional factories"of the cells,play an important role in the process of planting and in-vasion,and the mitochondrial quality control system,which in-cludes mitochondrial oxidative stress,kinetics,autophagy,bio-genesis and calcium homeostasis,is a key mechanism for the e-quilibrium of the mitochondrial function.The mitochondrial quality control system,including mitochondrial oxidative stress kinetics,autophagy,biogenesis and calcium homeostasis,is a key mechanism for mitochondrial functional balance.Therefore,to clarify the role of the mitochondrial quality control system in the development of EMs with the help of rational and rigorous experi-mental and clinical studies can not only help to clarify the patho-genesis of the disease,but also explore the key targets in the prevention and treatment of the disease.Therefore,this article summarizes the research progress of mitochondrial quality control system in endometriosis,with a view to providing reference and theoretical basis for the etiology,pathogenesis and prevention strategies of EMs.

Microplastics are widely present in various environments such as water bodies,land,and atmosphere,which pose threats to the ecological environment and human health through transmission and accumulation in the food chain.The existing detection techniques for microplastics face challenges such as complex preparation procedure of samples,low efficiency in processing large batches of samples,and difficulties in handling complex samples.Therefore,there is an urgent need for rapid and efficient detection techniques suitable for complex microplastics samples in the field of environmental monitoring.Raman spectroscopy,known for its advantages such as rapidity,accuracy,high sensitivity,non-destructiveness,and non-contact,demonstrates great application potential in detection of microplastics.Deep learning,an artificial intelligence method known for its large-scale data processing,nonlinear modeling and automatic feature extraction capabilities,is receiving increasing attention in the analysis of Raman spectroscopy signals.The application of deep learning-based Raman spectroscopy has significantly improved performance indicators such as detection efficiency and accuracy.This article introduced the existing Raman enhancement techniques,summarized the deep learning methods applied in Raman spectroscopy signal analysis,reviewed the recent research and application progress of deep learning-based Raman spectroscopy in detection of microplastics,and finally discussed the challenges and future prospects of deep learning-based Raman spectroscopy in detection of microplastics.

A pair of positively charged stable isotope labelling agents,4-((2,5-dioxocyclopentyloxy)carbonyl)-N,N,N-trimethylnaphthalen-1-aminium iodide(DPTNA)and its deuterated counterpart d3-DPTNA,were designed and synthesized,which were applied to pre-column labelling of alkylphenols to enhance the sensitivity and accuracy of liquid chromatography-tandem mass spectrometry(LC-MS/MS).By crosslinking covalent organic framework(COF)with hydrophilic sodium alginate and Ca2+in the presence of pore forming agent NH4HCO3 and surfactant P123,abundant of"gas pocket"were created before and during the beads formation process,and high porous COF beads with macroporous and open structure were achieved after removal of gas.Compared with traditional powdered adsorbents,COF beads demonstrated superior operability and recyclability.The proposed method was applied to analysis of alkylphenols in water samples with method LODs of 0.25-0.50 ng/L,while the method LOQs were in the range of 0.80-1.52 ng/L,and recoveries ranged from 92.2%to 98.3%.The proposed method could be well applied to the simultaneous enrichment and analysis of alkylphenols in water samples.

Traditional mass measurement methods are not applicable in microgravity environments,and the main challenge for in-orbit body mass measurement technology based on inertial principles is to address the random errors brought about by the weightless environment.These include additional torques due to shifts in the center of mass,nonlinear accelerations due to non-rigid human bodies,mechanical energy consumption due to organ vibrations,and random vibrations of the measurement device itself.To address the above difficulties,the project proposes a technical scheme based on the principle of linear acceleration,designs and constructs a ground-specific air-floating experimental and simulation platform,studies key data such as motion trajectory,acceleration change,and vibration frequency amplitude during the mass measurement process,and simulates the changes in the center of mass and random vibrations of the human body in a weightless environment.The project has designed an adjustable posture bracket to adapt to changes in the center of mass,enhance body restraint,and greatly reduce shaking;it has also developed an integrated four-bar linkage motion guidance mechanism,high-precision integrated photoelectric distance measurement,and modular motion constant force measurement device to ensure the accurate measurement of acceleration and constant force data.The product has undergone simulation calculations,ground human applicability tests,and in-orbit applicability verification in the space station.Ground test results show that the device achieves a body mass measurement accuracy better than 0.5%,and the dispersion is better than 0.38%;after flight mission verification and evaluation,the in-orbit body mass measurement dispersion is less than 0.4%,which is superior to the SLAMMD,a mass measurement device of the same principle on the International Space Station,and is at the forefront internationally,achieving accurate body mass measurement.

Rodent models play a crucial role in research on human periodontal diseases,providing key evidence for investigation into the pathological mechanisms of periodontal bone defects.Relevant research in the field involves gene expression,inflammatory regulation mechanisms,host-microbial interactions,as well as disease resolution and healing processes.Research methodology in the field falls under 2 categories-periodontal inflammation models and surgical defect models.The former simulates periodontal defects by inducing periodontal diseases,while the latter constructs clinically simulated periodontal defects through surgical removal of periodontal tissue.However,the currently available animal models of periodontitis face challenges in simultaneously capturing the disease complexity,tracking dynamic repair processes,and meeting translational needs.Herein,we reviewed and summarized the methods and characteristics of periodontal disease modeling in recent years.We proposed the establishment of a multimodal assessment framework integrating technologies such as spatial transcriptomics,single-cell sequencing,and in vivo fluorescence imaging,which may serve as a critical pathway for overcoming existing research challenges.