Background and Aims:Mucinous adenocarcinoma of the colorectum(MAC)is a distinct histologic subtype of colorectal cancer characterized by high malignancy and low diagnostic accuracy of preoperative biopsy,posing challenges for clinical decision-making.Given the critical role of the inflammatory microenvironment in tumor progression,this study aimed to develop and validate a nomogram model integrating preoperative systemic inflammatory indicators and clinical features to improve the preoperative diagnosis of MAC.Methods:Clinical data of 293 patients with colorectal cancer who underwent radical resection between June 2017 and June 2022 at the First Affiliated Hospital of the University of South China were retrospectively analyzed.Based on postoperative pathology,patients were classified into the mucinous adenocarcinoma(MAC)group and the non-specific adenocarcinoma(AC)group.Propensity score matching(PSM,1∶1)was used to balance age,T stage,and N stage.Differences in preoperative inflammatory indices were compared between groups.Univariate and multivariate logistic regression analyses were performed to identify independent predictors of MAC,which were incorporated into a diagnostic nomogram.The model's discrimination,calibration,and clinical utility were evaluated using the area under the receiver operating characteristic curve(AUC),calibration plots,and decision curve analysis(DCA).Results:Among the 293 patients,46 had MAC and 247 had AC,with a preoperative colonoscopic diagnostic rate of 54%for MAC.After PSM(43 pairs),platelet count,platelet lymphocyte ratio(PLR),systemic immune inflammation index(SII),inflammation related prognostic index(IPI),and systemic inflammation score(SIS)were significantly higher in the MAC group,while lymphocyte monocyte ratio(LMR)was lower(all P<0.05).Multivariate analysis identified tumor location,maximum tumor diameter,and preoperative IPI as independent predictors.The AUCs of the nomogram in the training(n=206)and validation(n=87)cohorts were 0.759(95%CI=0.662-0.856)and 0.776(95%CI=0.649-0.903),respectively.Calibration plots showed good agreement between predicted and observed probabilities,and DCA demonstrated satisfactory clinical applicability.Conclusion:A nomogram model integrating tumor location,tumor size,and preoperative IPI was successfully developed and validated for preoperative diagnosis of colorectal MAC.This model provides a practical,quantitative tool with good predictive performance to assist clinicians in individualized treatment planning,particularly for patients ineligible for surgical biopsy.

Objective:To construct an intelligent APP-assisted process assessment mode for standardized residency training and explore its application effect.Methods:Based on the "XUEYIKU" APP platform developed in Peking University Third Hospital, we built a standardized process of process assessment for standardized residency training assisted by intelligent APP and combining both online and offline components. We analyzed the frequency of APP use, satisfaction with the APP, the problems solved by the APP, and the aspects that need to be improved. SPSS 26.0 was used for t-test and Chi-square test. Results:The satisfaction score of teachers with the APP was (7.66±1.86) points. The satisfaction score of professional base teaching directors/process assessment coordinators was higher than that of clinical teachers [(8.28±1.30) vs. (7.42±1.99), P=0.013]. Most residents were satisfied with the APP (67.44%, 29/43), regarded its role in supporting the entire assessment process as important (55.81%, 24/43), and reviewed teacher feedback (65.12%, 28/43). Some teachers indicated that the APP solved problems such as paperless exam scoring (59.00%, 59/100), standardized exam processes (43.00%, 43/100), score statistics (42.00%, 42/100), and score reporting (42.00%, 42/100). The residents believed that the APP resolved issues such as exam notification (44.19%, 19/43), scheduling (41.86%, 18/43), and result feedback (41.86%, 18/43). Both teachers and residents mentioned the need for further strengthening the stability of the APP system and simplifying operational steps. Conclusions:With APP as a link, through the instant transmission and feedback of data, the intelligent APP-assisted process assessment mode drives the reflection and summarization of professional bases, clinical teachers, and residents, and promotes the post competence of residents.

Background and Aims:Mucinous adenocarcinoma of the colorectum(MAC)is a distinct histologic subtype of colorectal cancer characterized by high malignancy and low diagnostic accuracy of preoperative biopsy,posing challenges for clinical decision-making.Given the critical role of the inflammatory microenvironment in tumor progression,this study aimed to develop and validate a nomogram model integrating preoperative systemic inflammatory indicators and clinical features to improve the preoperative diagnosis of MAC.Methods:Clinical data of 293 patients with colorectal cancer who underwent radical resection between June 2017 and June 2022 at the First Affiliated Hospital of the University of South China were retrospectively analyzed.Based on postoperative pathology,patients were classified into the mucinous adenocarcinoma(MAC)group and the non-specific adenocarcinoma(AC)group.Propensity score matching(PSM,1∶1)was used to balance age,T stage,and N stage.Differences in preoperative inflammatory indices were compared between groups.Univariate and multivariate logistic regression analyses were performed to identify independent predictors of MAC,which were incorporated into a diagnostic nomogram.The model's discrimination,calibration,and clinical utility were evaluated using the area under the receiver operating characteristic curve(AUC),calibration plots,and decision curve analysis(DCA).Results:Among the 293 patients,46 had MAC and 247 had AC,with a preoperative colonoscopic diagnostic rate of 54%for MAC.After PSM(43 pairs),platelet count,platelet lymphocyte ratio(PLR),systemic immune inflammation index(SII),inflammation related prognostic index(IPI),and systemic inflammation score(SIS)were significantly higher in the MAC group,while lymphocyte monocyte ratio(LMR)was lower(all P<0.05).Multivariate analysis identified tumor location,maximum tumor diameter,and preoperative IPI as independent predictors.The AUCs of the nomogram in the training(n=206)and validation(n=87)cohorts were 0.759(95%CI=0.662-0.856)and 0.776(95%CI=0.649-0.903),respectively.Calibration plots showed good agreement between predicted and observed probabilities,and DCA demonstrated satisfactory clinical applicability.Conclusion:A nomogram model integrating tumor location,tumor size,and preoperative IPI was successfully developed and validated for preoperative diagnosis of colorectal MAC.This model provides a practical,quantitative tool with good predictive performance to assist clinicians in individualized treatment planning,particularly for patients ineligible for surgical biopsy.

Objective:To construct an intelligent APP-assisted process assessment mode for standardized residency training and explore its application effect.Methods:Based on the "XUEYIKU" APP platform developed in Peking University Third Hospital, we built a standardized process of process assessment for standardized residency training assisted by intelligent APP and combining both online and offline components. We analyzed the frequency of APP use, satisfaction with the APP, the problems solved by the APP, and the aspects that need to be improved. SPSS 26.0 was used for t-test and Chi-square test. Results:The satisfaction score of teachers with the APP was (7.66±1.86) points. The satisfaction score of professional base teaching directors/process assessment coordinators was higher than that of clinical teachers [(8.28±1.30) vs. (7.42±1.99), P=0.013]. Most residents were satisfied with the APP (67.44%, 29/43), regarded its role in supporting the entire assessment process as important (55.81%, 24/43), and reviewed teacher feedback (65.12%, 28/43). Some teachers indicated that the APP solved problems such as paperless exam scoring (59.00%, 59/100), standardized exam processes (43.00%, 43/100), score statistics (42.00%, 42/100), and score reporting (42.00%, 42/100). The residents believed that the APP resolved issues such as exam notification (44.19%, 19/43), scheduling (41.86%, 18/43), and result feedback (41.86%, 18/43). Both teachers and residents mentioned the need for further strengthening the stability of the APP system and simplifying operational steps. Conclusions:With APP as a link, through the instant transmission and feedback of data, the intelligent APP-assisted process assessment mode drives the reflection and summarization of professional bases, clinical teachers, and residents, and promotes the post competence of residents.

BACKGROUND:Cellular senescence is closely related to the development and progression of osteoarthritis,but the specific targets and regulatory mechanisms are not yet clear. OBJECTIVE:To mine key genes in cellular senescence-mediated osteoarthritis by integrating bioinformatics and machine learning approaches and validate them via experiments to explore the role of cellular senescence in osteoarthritis. METHODS:The osteoarthritis gene expression profiles obtained from the GEO database were intersected with cellular senescence-related genes obtained from the CellAge database and the expression of the intersected genes was extracted for differential analysis,followed by GO and KEGG analysis of the differential genes.The key osteoarthritis cellular senescence genes were then screened by protein-protein interaction network analysis and machine learning,and in vitro cellular experiments were performed.Finally,the expression of the key genes was detected by qPCR. RESULTS AND CONCLUSION:A total of 31 osteoarthritis cell senescence differential genes were identified.GO analysis showed that these genes were mainly involved in the biological processes,such as regulation of leukocyte differentiation,monocyte differentiation,regulation of T cell differentiation and exerted roles in DNA transcription factor binding,histone deacetylase binding,chromatin DNA binding,and chemokine binding.KEGG analysis showed that osteoarthritis cell senescence differential genes were mainly activated in the JAK/STAT signaling pathway,PI3K/Akt signaling pathway and FoxO signaling pathway.MYC,a key gene for osteoarthritis cellular senescence,was identified by protein-protein interaction network topology analysis and machine learning methods.The results of the in vitro cellular assay showed that the mRNA expression of MYC was significantly lower in the experimental group(osteoarthritis group)than the control group(normal group)(P＜0.05).To conclude,MYC can be a key gene in the senescence of osteoarthritic cells and may be a new target in the prevention and treatment of osteoarthritis by mediating immune response,inflammatory response and transcriptional regulation.

Objective To observe the protective effect of Zhilong Huoxue Tongyu Capsule(Zhilong Capsule)on myocardial ischemia reperfusion injury(MIRI)in mice,and explore its regulatory mechanism using metabolomics.Methods Using a random number table method,30 C57BL/6J mice were randomly divided into the following three groups:sham operation group,model group,and Zhilong Capsule group(6.24 g/kg),with 10 mice in each group.In mice in the model group and the Zhilong Capsule group,a mouse MIRI model was established by ligating the left anterior descending branch,while mice in the sham operation group underwent threading without ligation.The Zhilong Capsule group began modeling one week after pre-administration and continued to receive intragastric administration for two weeks after modeling once daily.The cardiac function,including the left ventricular ejection fraction(LVEF)and left ventricular fraction shortening(LVFS),was assessed by color echocardiography.The myocardial fibrosis and apoptosis were observed by Masson staining and TUNEL staining,respectively.Enzyme-linked immunosorbent assay was used to measure the serum contents of lactate dehydrogenase(LDH)and brain natriuretic peptide(BNP).Liquid chromatography-mass spectrometry combined with multivariate statistical method was performed for serum metabolite detection and identification analysis.Results Compared with the model group,the mice in the Zhilong Capsule group exhibited an increase in LVEF and LVFS,a reduction in cardiac tissue structure disorder,a decrease in myocardial fibrosis,a decrease in cell apoptosis rate,and a decrease in serum LDH and BNP contents(P<0.05).Metabolomics result showed that intervention with Zhilong Capsule significantly regulated 30 differential metabolites related to MIRI.Important metabolic pathways involved 20 pathways related to tyrosine metabolism,arginine and proline metabolism,and vitamin digestion and absorption.Conclusion Zhilong Capsule has a protective effect on MIRI,and it may achieve this effect by regulating pathways related to tyrosine metabolism,arginine and proline metabolism,and vitamin digestion and absorption.

Objective:To analyze the activation of primary somatosensory cortex(S1)neurons in post-traumatic stress disorder(PTSD)mice after tactile stimulation of whiskers and the changes of S1 cortical neurons in PTSD mice.Methods:Using the neuron cytoskeleton-associated protein(Arc)labeling strategy and immunofluorescence staining technique,the Arc of S1 cortical neurons in PTSD mice and control mice after whisker stimulation was marked and ob-served.By analyzing the difference in the spatial expression position of Arc labeled neurons and the number of positive cells,the activation level of S1 cortical neurons in the two groups was compared and analyzed.The pyramidal neurons of S1 cortex were labeled by sparse virus labeling method,and the number of dendrites and the morphology and number distribution of dendritic spines were compared between the two groups.Results:After whisker stimulation,it was found that Arc positive neurons were distributed from shallow layer to deep layer of S1,and more densely distributed in layersⅡ/Ⅲ and V.Compared with the control group,the number of positive neurons in different layers of the PTSD group was significantly increased.The results of cell morphology and structure analysis showed that,compared with the control group,the density of dendritic spines in layer Ⅱ/Ⅲ of mice with PTSD increased,and the number of mushroom dendrit-ic spines increased,while the number of filamentous pseudopod dendritic spines decreased.The number of dendritic spines of Si V layer mushroom type and slender type was higher,but the total number of dendritic spines was not sig-nificantly different.Conclusion:After whisker stimulation in PTSD mice,S1 neurons were over-activated,and the structure and morphology of neurons changed significantly.

Objective:To systematically summarize the psychological experience of cancer patients caregivers, and comprehensively understand their inner needs, so as to provide basis for better clinical medical work.Methods:CNKI, Wanfang DATA, VIP, EMBASE, PubMed, BMJ Journals, CINAHL, Cochrane Library, ProQuest, and other databases were searched from their inception to May 2020, to collect qualitative studies on psychological experience of cancer patients caregivers. The quality of included studies was evaluated according to JBI Critical Appraisal Tool for Qualitative Studies in Australia. The results were integrated by integrating methods.Results:A total of 10 studies were included. 22 research results were extracted and grouped into 9 new categories according to similarities. These categories resulted in 3 synthesized findings: caregivers suffered from physical and psychological sufferings, and were tortured with mainly negative emotions and mixed positive emotions; after self adjustment, the role of caregiver grew; their thirst for information and support.Conclusion:Healthcare workers should pay attention to psychological changes and information needs of cancer patients caregivers, provide necessary support to help them adapt their roles, and improve their quality of life.

Objective: To understand the consciousness of the cancer early treatment and its demographic and socioeconomic factors. Methods: A cross-sectional survey was conducted in 16 provinces covered by the Cancer Screening Program in Urban China (CanSPUC) from 2015 to 2017. A total of 32 257 local residents aged ≥18 years old who could understand the investigation procedure were included in the study by using the cluster sampling method and convenient sampling method. All local residents were categorized into four groups, which contained 15 524 community residents, 8 016 cancer risk assessment/screening population, 2 289 cancer patients and 6 428 occupational population, respectively. The questionnaire collected personal information, the consciousness of the cancer early treatment and relevant factors. The Chi square test was used to compare the difference between the consciousness of the cancer early treatment and relevant factors among the four groups. The logistic regression model was used to analyze the influencing factors related to the consciousness of the cancer early treatment. Results: With the assumption of being diagnosed as precancer or cancer, 89.97% of community residents, 91.84% of cancer risk assessment/screening population, 93.00% of cancer patients and 91.52% of occupational population would accept active treatments (P<0.001). If the immediate family members were diagnosed as precancer or cancer, people who would encourage their family members to receive early treatment in the four groups accounted for 91.96%, 91.94%, 92.44% and 91.55%, respectively (P<0.001). The company employees, annual household income with 40 000 yuan and more and other three groups had a relatively better consciousness of the cancer early treatment (P<0.05). Male, widowed, unemployed and from the central and western regions had a relatively worse consciousness of the cancer early treatment (P<0.05). Conclusion Residents in urban China participants had a good consciousness of the cancer early treatment. The marital status, occupation, annual household income and residential regions were major factors related to the consciousness of the cancer early treatment.

Objective: To understand the prevalence of carotid plaque (CP) in population at high-risk for cardiovascular disease (CVD) in Jiangsu province and identify related influencing factors. Methods: Based on the China Patient-centered Evaluative Assessment of Cardiac Events Million Persons Project from 2015 to 2016, a total of 11 392 persons at high-risk for CVD were selected from six project areas in Jiangsu province for the questionnaire survey, physical measurement, laboratory test and bilateral ultrasound examination of carotid arteries. The prevalence of CP and influencing factors of abnormal carotid arteries, CP and plaque burden (CP≥2) were analyzed. Results: Among the persons surveyed, 4 821 (42.3%) were males. The age of the persons surveyed was (59.4±8.9) years. There were 5 971 abnormal carotid arteries cases (52.4%), including 1 782 carotid intima-media thickness thickening cases (15.6%), 3 811 CP cases (33.5%) and 378 carotid stenosis cases (3.3%). Older age (OR=2.253, 95%CI: 2.127-2.386), urban residence (OR=2.622, 95%CI: 2.375-2.895), hypertension (OR=1.439, 95%CI: 1.195-1.732), smoking (OR=1.441, 95%CI: 1.259- 1.650), pulse pressure difference (OR=1.270, 95%CI: 1.198-1.347), fasting plasma glucose (FPG) (OR=1.109, 95%CI: 1.059-1.161) and LDL-C/HDL-C (OR=1.225, 95%CI: 1.164-1.288) were possible risk factors of CP in population at high risk for CVD. Being women (OR=0.558, 95%CI: 0.494-0.630), high BMI (OR=0.948, 95%CI: 0.904-0.994), higher levels of education (OR=0.708, 95%CI: 0.531-0.945), and higher annual household income (OR=0.773, 95%CI: 0.669-0.894) were the possible protective factors. Conclusions Over half of the population at high-risk for CVD in Jiangsu showed abnormal carotid arteries. High blood pressure, high blood glucose, high blood lipids and smoking were the main factors that could be changed.