This paper aims to discuss the application value and progress of artificial intelligence (AI) in the diagnosis and treatment of gastrointestinal tumors and teaching practice of gastrointestinal oncology. Through a comprehensive analysis of the current clinical research status and literature, this paper summarizes the application practice and exploratory thinking of AI and deep learning technologies in gastrointestinal oncology. In diagnosis, AI technologies have improved the early detection and diagnosis efficiency for gastrointestinal tumors by optimizing medical image analysis, especially in the recognition of liver metastases. Applications of AI in pathological diagnosis include automatic recognition of tumor cells and tissue structure, as well as improving diagnostic sensitivity and specificity through feature extraction and pattern recognition. In treatment, the application scenarios of AI include rapid diagnosis, accurate staging, personalized treatment plan formulation, drug development, and surgical assistance. In surgical assistance, AI technology improves the safety and effectiveness of surgery through preoperative evaluation, surgical navigation, and postoperative evaluation. In teaching, AI technology facilitates knowledge acquisition and clinical skill enhancement of medical students by providing a multidisciplinary learning platform, simulating clinical environment and case details, and establishing a remote learning platform. The application of AI technology in teaching also includes deep learning and assessment feedback, providing personalized teaching and real-time assessment for students. This paper discusses the application prospects for AI technology in the teaching practice of gastrointestinal oncology. Although AI technology shows great potential in the diagnosis and treatment of gastrointestinal tumors and teaching gastrointestinal oncology, it also has limitations and needs to be combined with traditional teaching methods to achieve the best teaching results.

Breast cancer is the most prevalent malignant tumor that poses a threat to women's health in China,with incidence and mortality rates persistently increasing.Given this critical situation,there is an urgent need to optimize therapeutic options through basic translational research to address current treatment challenges.This article provided a comprehensive overview of the significant advancements in fundamental translational breast cancer research in China over the past five years,aiming to provide a scientific basis and new directions for precision treatment of breast cancer.This research encompasses a range of subjects,including molecular typing,biomarker identification,exploration of drug resistance mechanisms,optimization of precision treatment strategies,and identification of new targets in breast cancer.In the domain of molecular typing,researchers have revealed substantial disparities in treatment responses among distinct subtypes of breast cancer through in-depth analysis.This has led to the proposal of specific therapeutic strategies for each subtype,thereby establishing a robust theoretical foundation for individualized treatment approaches.The identification of biomarkers plays a pivotal role in selecting appropriate treatment options for patients.Recent research advancements have demonstrated the potential of liquid biopsy and proteomics technologies in uncovering promising biomarkers,offering novel prospects for the early diagnosis and prognostic assessment of breast cancer.In the investigation of resistance mechanisms,researchers have elucidated the molecular underpinnings of resistance to endocrine therapy and human epidermal growth factor receptor 2(HER2)-targeted therapy and proposed potential strategies to overcome resistance.This has paved the way for novel approaches to enhance therapeutic efficacy.In the context of immunotherapy and targeted therapies,the discernment of novel targets and biomarkers has facilitated novel perspectives on breast cancer treatment.Based on advanced comprehension of tumor heterogeneity,researchers constantly optimize precision treatment strategies through multiomics analysis,thus offering patients with breast cancer enhanced personalized treatment options.Concurrently,the implementation of novel technologies has been instrumental in facilitating the advancement of precision treatment for breast cancer.For instance,the application of artificial intelligence technology has demonstrated considerable potential in the early screening,diagnosis,efficacy assessment and prognosis prediction of breast cancer.Conversely,the advent of innovative drug delivery systems facilitated by nanotechnology has led to enhanced targeting and efficacy of pharmaceutical agents.Furthermore,research into hydrogel patch technology and tumor vaccines has yielded novel strategies for the treatment of breast cancer.Overall,China has accomplished remarkable achievements in the field of basic translational research on breast cancer.These findings not only enhance our understanding of the molecular mechanisms of breast cancer,but also provide new directions and hope for the development of future therapeutic strategies.With the advancement of multidisciplinary integration and the application of new emerging technologies,precision therapy is expected to provide more benefits to breast cancer patients.

Breast cancer is the most prevalent malignant tumor that poses a threat to women's health in China,with incidence and mortality rates persistently increasing.Given this critical situation,there is an urgent need to optimize therapeutic options through basic translational research to address current treatment challenges.This article provided a comprehensive overview of the significant advancements in fundamental translational breast cancer research in China over the past five years,aiming to provide a scientific basis and new directions for precision treatment of breast cancer.This research encompasses a range of subjects,including molecular typing,biomarker identification,exploration of drug resistance mechanisms,optimization of precision treatment strategies,and identification of new targets in breast cancer.In the domain of molecular typing,researchers have revealed substantial disparities in treatment responses among distinct subtypes of breast cancer through in-depth analysis.This has led to the proposal of specific therapeutic strategies for each subtype,thereby establishing a robust theoretical foundation for individualized treatment approaches.The identification of biomarkers plays a pivotal role in selecting appropriate treatment options for patients.Recent research advancements have demonstrated the potential of liquid biopsy and proteomics technologies in uncovering promising biomarkers,offering novel prospects for the early diagnosis and prognostic assessment of breast cancer.In the investigation of resistance mechanisms,researchers have elucidated the molecular underpinnings of resistance to endocrine therapy and human epidermal growth factor receptor 2(HER2)-targeted therapy and proposed potential strategies to overcome resistance.This has paved the way for novel approaches to enhance therapeutic efficacy.In the context of immunotherapy and targeted therapies,the discernment of novel targets and biomarkers has facilitated novel perspectives on breast cancer treatment.Based on advanced comprehension of tumor heterogeneity,researchers constantly optimize precision treatment strategies through multiomics analysis,thus offering patients with breast cancer enhanced personalized treatment options.Concurrently,the implementation of novel technologies has been instrumental in facilitating the advancement of precision treatment for breast cancer.For instance,the application of artificial intelligence technology has demonstrated considerable potential in the early screening,diagnosis,efficacy assessment and prognosis prediction of breast cancer.Conversely,the advent of innovative drug delivery systems facilitated by nanotechnology has led to enhanced targeting and efficacy of pharmaceutical agents.Furthermore,research into hydrogel patch technology and tumor vaccines has yielded novel strategies for the treatment of breast cancer.Overall,China has accomplished remarkable achievements in the field of basic translational research on breast cancer.These findings not only enhance our understanding of the molecular mechanisms of breast cancer,but also provide new directions and hope for the development of future therapeutic strategies.With the advancement of multidisciplinary integration and the application of new emerging technologies,precision therapy is expected to provide more benefits to breast cancer patients.

This paper aims to discuss the application value and progress of artificial intelligence (AI) in the diagnosis and treatment of gastrointestinal tumors and teaching practice of gastrointestinal oncology. Through a comprehensive analysis of the current clinical research status and literature, this paper summarizes the application practice and exploratory thinking of AI and deep learning technologies in gastrointestinal oncology. In diagnosis, AI technologies have improved the early detection and diagnosis efficiency for gastrointestinal tumors by optimizing medical image analysis, especially in the recognition of liver metastases. Applications of AI in pathological diagnosis include automatic recognition of tumor cells and tissue structure, as well as improving diagnostic sensitivity and specificity through feature extraction and pattern recognition. In treatment, the application scenarios of AI include rapid diagnosis, accurate staging, personalized treatment plan formulation, drug development, and surgical assistance. In surgical assistance, AI technology improves the safety and effectiveness of surgery through preoperative evaluation, surgical navigation, and postoperative evaluation. In teaching, AI technology facilitates knowledge acquisition and clinical skill enhancement of medical students by providing a multidisciplinary learning platform, simulating clinical environment and case details, and establishing a remote learning platform. The application of AI technology in teaching also includes deep learning and assessment feedback, providing personalized teaching and real-time assessment for students. This paper discusses the application prospects for AI technology in the teaching practice of gastrointestinal oncology. Although AI technology shows great potential in the diagnosis and treatment of gastrointestinal tumors and teaching gastrointestinal oncology, it also has limitations and needs to be combined with traditional teaching methods to achieve the best teaching results.

Objective To establish a noninvasive diagnostic model for liver fibrosis in chronic hepatitis B(CHB)patients with normal alanine aminotransferase(ALT)and an age of≤30 years by selecting specific indicators from the commonly used noninvasive indicators such as clinical,biochemical,and imaging indicators,to avoid invasive liver biopsy in such patients to some extent,and to guide the timing of antiviral therapy.Methods A total of 251 CHB patients with normal ALT and an age of≤30 years who underwent liver biopsy in Shenzhen Third People's Hospital and The First Hospital of Changsha from January 2019 to January 2022 were enrolled,with 175 patients in the model group and 76 patients in the validation group,and commonly used clinical indicators were obtained based on clinical experience and related articles.The two-independent-samples t test or the two-independent-samples Mann-Whitney U rank sum test was used for comparison of continuous data between groups,and the chi-square test was used for comparison of categorical data between groups.A Spearman rank correlation analysis was used to investigate the correlation between each indicator and liver fibrosis and identify the indicators with correlation(P<0.01,r>0.200);a Logistic regression analysis was used to establish a noninvasive diagnostic model,and the receiver operating characteristic(ROC)curve was used to evaluate its performance and perform validation of the model;this model was then compared with the widely used models of aspartate aminotransferase-to-platelet ratio index(APRI)and fibrosis-4(FIB-4).The Kappa consistency test was used to investigate the consistency of pathological results.Results A total of 17 commonly used clinical indicators were obtained,among which 9 indicators(ALT,aspartate aminotransferase[AST],gamma-glutamyl transpeptidase[GGT],ferritin[FERR],platelet count[PLT],procollagen type Ⅲ amino-terminal peptide[PⅢP],collagen Ⅳ[CⅣ],HBV DNA,and spleen thickness)were correlated with liver fibrosis(P<0.01,r>0.232).Based on the above indicators,the predictive model was established as P=1/(1+e-γ),γ=-1.902+0.106×AST-0.011×PLT-0.265×HBV DNA+0.059×PⅢP,in which P was the probability for predicting≥S2 liver fibrosis and γ was the predictive index.The comparison between each indicator and the model showed that the model had the largest area under the ROC curve of 0.852,with a sensitivity of 92.7%and a specificity of 76.9%.The model was validated in 76 patients and showed an accuracy of 77.600%.The model was compared with APRI and FIB-4,and the results showed that the model has good accuracy.Conclusion Compared with the models of APRI and FIB-4 commonly used in the world,this model can more accurately judge the degree of liver fibrosis in such patients,thereby replacing liver biopsy to some extent and guiding the timing of antiviral therapy.

Objective Exploring the relationship between changes in serum Golgi apparatus transmem-brane glycoprotein 73(GP73)and chitosanase 3-like protein 1(CHI3L1)levels and liver fibrosis and lesion sever-ity in patients with hepatitis B(CHB).Methods Using a case-control study,80 patients diagnosed with CHB infection and developing liver fibrosis in the Infectious Disease Department of Changsha First Hospital from June 2020 to June 2023 were selected as the liver fibrosis group,while 120 patients diagnosed with CHB infection but not developing liver fibrosis in the Infectious Disease Department of our hospital were selected as the control group.The serum GP3,CHI3L1,liver function,and fibrosis indicators of the two groups of patients were compared,and the liver fibrosis group was divided into mild according to Scheuer system standards Perform stratified analysis on patients with significant liver fibrosis.Results The serum GP3 and CHI3L1 levels in the liver fibrosis group were significantly higher than those in the control group,with statistical significance(P＜0.05);The ROC curves were plotted using serum GP3,CHI3L1,and GP3+CHI3L1,respectively.The sensitivity for diagnosing liver fibrosis in CHB patients was 62.81%,60.94%,and 96.33%,with specificity of 80.66%,80.05%,and 75.30%.The AUC values under the curves were 0.792,0.756,and 0.908,respectively;The levels of ALT,AST,HA,LN,PC III NP,C IV,and CG in the liver fibrosis group were higher than those in the control group,and the PLT measurement values were lower than those in the control group,with statistical significance(P＜0.05);49 patients with moderate to severe liver fibrosis(33 in S2 phase and 16 in S3 phase)and 31 patients with mild liver fibrosis(all in S1 phase)had significantly higher serum GP3 and CHI3L1 levels than mild patients,with statistical significance(P＜0.05);The levels of DBIL,ALT,AST,HA,LN,PC III NP,C IV,and CG in patients with moderate to severe liver fibrosis were higher than those in the mild group,and the PLT measurement values were lower than those in the mild group,with statistical significance(P＜0.05).Conclusion The serum GP3 and CHI3L1 levels in CHB patients with liver fibrosis are significantly elevated,and there is a certain correlation with the degree of liver fibro-sis.The combination of these two indicators is beneficial for diagnosing liver fibrosis in CHB patients.

Objective:Human leukocyte antigen(HLA)B27 is a susceptibility allele of ankylosing spondylitis(AS),and HLA-B27 antigen typing is an important indicator for clinical diagnosis of AS,but current typing methods such as sequence specific primer polymerase chain reaction(PCR-SSP)still possess limitation.Therefore,this study aims to analyze the correlation between B27 subtypes and susceptibility to AS in Hunan Province by applying high-resolution polymerase chain reaction-sequence-based typing(PCR-SBT). Methods:Peripheral blood of 116 patients with suspected AS(suspected AS group)and 121 healthy volunteers(control group)admitted to the Second Xiangya Hospital from January 2020 to December 2020 were collected for HLA-B genotyping by PCR-SBT.Among the patients in the suspected AS group,23 patients were finally diagnosed with AS(confirmed AS group),and the remaining 93 undiagnosed patients served as the non-confirmed AS group.PCR-SBT and PCR-SSP were used to detect HLA-B27 typing in 116 patients with suspected AS,and the results of the 2 methods were compared. Results:The HLA-B27 allele frequency in the suspected AS group was significantly higher than that in the control group[11.63%vs 2.48%;P<0.001,odds ratio(OR)=5.18,95%confidence interval(CI)2.097 to 12.795].B*27:04,B*27:05,B*27:06,and B*27:07 were detected in the suspected AS group and the control group.The frequency of the B*27:04 allele in the suspected AS group was significantly higher than that in the control group(9.48%vs 1.24%;P<0.001,OR=8.346,95%CI 2.463 to 28.282).The positive rate of B27 in the suspected AS group and the confirmed AS group(B27+/+ and B27+/-)was significantly higher than that in the control group(χ2=16.579,P<0.001;χ2=94.582,P<0.001,respectively).Among the confirmed AS group,21 were HLA-B27 carriers,and the B27 positive rate in the confirmed AS group was 91.3%.PCR-SBT could achieve high resolution typing of the HLA-B gene locus,with higher sensitivity,specificity,positive predictive value,negative predictive value,and accuracy than PCR-SSP. Conclusion:PCR-SBT typing analysis shows a strong correlation between HLA-B * 27:04 and AS in Hunan province.The PCR-SBT method can be used as the preferred option for the auxiliary diagnosis of clinical AS.

ObjectiveTo observe the effects of scalp moxibustion combined with treadmill training on the learning and memory function, and oxidative stress in rats with vascular dementia (VaD). MethodsA total of 40 male Sprague-Dawley rats were randomly divided into sham group (n = 10), model group (n = 10), acupuncture-rehabilitation group (n = 10) and moxibustion-rehabilitation group (n = 10). The latter three groups were induced VaD with 2 vessels occlusion. Eight rats with obvious cognitive impairment were selected from the model groups six weeks after modeling, according to the results of Morris Water Maze; and random eight rats in the sham group were selected. The acupuncture-rehabilitation group accepted scalp acupuncture combined with treadmill training, while the moxibustion-rehabilitation group accepted scalp moxibustion combined with treadmill training. All the rats were tested with Morris Water Maze after four weeks of intervention, and measured the levels of maleic dialdehyde (MDA), superoxide orgotein dismutase (SOD), glutathione (GSH) and glutathione peroxidase reductase (GSH-Px) of hippocampus. ResultsCompared with the sham group, escape latency increased in the model group, and the number of crossing platforms and the stay time in the target quadrant decreased (P < 0.001); while the levels of SOD, GSH and GSH-Px decreased, and the level of MDA increased (P < 0.001). Compared with the model group, escape latency decreased in the acupuncture- and moxibustion-rehabilitation groups (P < 0.001), the number of crossing platforms and the stay time in the target quadrant increased (P < 0.001) from the third day; while the levels of SOD, GSH and GSH-Px increased, and the level of MDA decreased (P < 0.001); all the indexes imporved more in the moxibustion-rehabilitation group than in the acupuncture-rehabilitation group (P < 0.001). ConclusionScalp moxibustion combined with treadmill training can further relieve the oxidative stress in the hippocampus of VaD rats, to improve the learning and memory function compared with the acupuncture-rehabilitation.

【Objective】 To establish and optimize a method for the determination of aluminum (Al) residue by inductively coupled plasma mass spectrometry (ICP-MS). 【Methods】 Nitric acid solution was used to treat samples and standards. The concentration of nitric acid solution and equipment parameters were optimized, and the specificity, linearity, repeatability, accuracy, detection limit, quantitative limit and intermediate precision of the optimized detection method were investigated to confirm whether it was suitable for the determination of Al residue in human serum albumin. 【Results】 The concentration of nitric acid was 5%, and digest time was 4 h. The equipment condition of ICP-MS was as follows: RF power: 1600 W, sampling depth: 10 mm, atomizer / carrier gas flow rate: 1.0 L/ min, compensation flow rate: 0.5 L/ min, experimental mode: standard mode, integration time: 0.2 s, data acquisition: 3 times. Specificity: The recoveries of Al: 92% (high concentration, RSD=3.5%), 98% (low concentration, RSD=4.9%). Linearity: In the range of (0~40) μg/L, the correlation coefficient between concentration and optical energy signal (CPS) of standard / sample were higher than 0.999 0. Accuracy/ Repeatability: The recoveries of sample (3 concentration): 108% (RSD=4.7%), 110% (RSD=4.9%) and 110% (RSD=2.8%). The detection limit was 0.006 μg/L, and the quantitation limit was 0.019 μg/L. Intermediate precision: personnel factor and date factor, P>0.05, RSD (12 times)=2%. Comparison between ICP-MS and atomic absorption spectrometry (AAS): the deviation between ICP-MS and AAS was 8%, and that of samples was 3%, with no significant difference noticed between the two methods. 【Conclusion】 After optimization, ICP-MS method has shown good performance in terms of specificity, linearity, repeatability, accuracy, detection limit, quantitative limit and intermediate precision, and is suitable for the determination of Al residue in human albumin products of our company.

OBJECTIVE: To investigate the effect of 1,2-dichloroethane(1,2-DCE) acute inhalation exposure on the differential gene expression of phase Ⅰ metabolic enzymes. METHODS: The specific pathogen free SD rats were randomly divided into control group(16 rats), low-and high-dose groups(24 rats in each group, half males and half females). Low-and high-dose group were given daily 600, 1 800 mg/m~(3 ) of 1,2-DCE, and the control group given the fresh air by dynamic inhalation for 8 hours per day for consecutive 7 days. After the end of exposure, the relative mRNA expression of cytochrome P450 2 E1(CYP2 E1), alcohol dehydrogenase(ADH1) and acetaldehyde dehydrogenase 3 alpha 1(ALDH3α1) in the liver tissue was detected by real-time fluorescence quantitative polymerase chain reaction. RESULTS: The relative expression of CYP2 E1 in male high-dose group was higher than that in male low-dose group and female high-dose group(P<0.05). The relative expression of ADH1 in male low-and high-dose groups was higher than that in male control group(P<0.05). The relative expression of ADH1 in male high-dose group was higher than that in male low-dose group and female high-dose group(P<0.05). The relative expression of ALDH3α1 in high-dose group was higher than that in control group and low-dose group(P<0.05). CONCLUSION: High dose 1,2-DCE could increase the gene expression of phase Ⅰ metabolic enzymes in rat liver. The 1,2-DCE has more obvious effect in male rats than in female rats.