Lactic acid bacteria (LAB) are promising candidates for live bacterial drug delivery systems owing to their safety, probiotic properties, and ability to colonize the intestinal tract. At present, most research focuses on engineering LAB as carriers for the delivery of therapeutic proteins. As model organisms equipped with a versatile set of genetic tools, LAB can be readily modified to target various diseases and yield significant therapeutic effects. LAB-based carriers offer multiple advantages, including non-invasive delivery, ease of genetic manipulation, and suitability for large-scale production. Consequently, the use of LAB as recombinant protein expression vectors has attracted extensive research interest worldwide. The foundational principles, strategies for enhancing bioavailability, genetic engineering approaches, and the current research and application status of LAB-based drug delivery systems were summarized in this paper.

This paper analyzed the characteristics of peer psychological counseling conducted by class committee member for psychology in universities and the dilemmas they faced in four aspects， including dual relationships， confidentiality issues， competence issues， and informed consent. It also examined the causes of these ethical dilemmas and corresponding countermeasures one by one. Specific work requirements were proposed for class committee member for psychology in conducting peer psychological counseling. These encompassed clarifying the nature and boundaries of the helping relationship， establishing appropriate settings， discussing the impacts of dual relationships， maintaining confidentiality awareness， adopting appropriate confidentiality measures， actively participating in training to improve competence， making timely referrals when exceeding their professional scope， ensuring proper informed consent， and maintaining value neutrality. Recommendations were also put forward for universities to strengthen the training and management of class committee member for psychology， enhance their ethical awareness， and ensure the effectiveness of peer counseling.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective:To investigate the completion rate of tumor evaluation at initial assessment and after neoadjuvant therapy for mid and low rectal cancer patients in the national multicenter real-world database.Methods:The prospective real-world study was conducted. The clinicopathological data of 1 074 patients who underwent surgical treatment for mid and low rectal cancer in 47 national medical institutions, including Peking Union Medical College Hospital et al, from May 12,2023 to May 11,2024 were collected. Observation indicators: (1) clinical characteristics of patients with mid and low rectal cancer; (2) initial colonoscopy and pathologic evaluation of tumors in patients with mid and low rectal cancer; (3) initial imaging evaluation of patients with mid and low rectal cancer; (4) imaging evaluation after neoadjuvant therapy for patients with mid and low rectal cancer. Measurement data with normal distribution were represented as Mean± SD, and measurement data with skewed distribution were represented as M( Q1, Q3). Count data were described as absoluter numbers and/or percentages. Results:(1) Clinical characteristics of patients with mid and low rectal cancer. Of the 1 074 patients, there were 713 males and 361 females, aged 63(56,70)years. The body mass index of 1 074 patients was 24(21,26)kg/m 2.For American Society of Anesthesiologists classification, there were 147 cases of stage Ⅰ, 641 cases of stage Ⅱ, 157 cases of stage Ⅲ, 2 cases of stage Ⅳ, and there were 127 cases missing data. (2) Initial colonoscopy and pathologic evaluation of tumors in patients with mid and low rectal cancer. Of the 1 074 patients, there were 787 cases (73.28%) undergoing complete colonoscopy, and there were only 197 cases (18.34%) undergoing immunohistochemical evaluation of all four mismatch repair proteins. (3) Initial imaging evaluation of patients with mid and low rectal cancer. Of the 1 074 patients, there were 842(78.40%) patients completing magnetic resonance imaging (MRI) or ultrasound evaluation, and there were 914(85.10%) patients completing chest, abdomen, and pelvis enhanced computed tomography (CT) evaluation. In the 149 patients completing rectal ultrasound evaluation, there were 122 cases (81.88%) comple-ting T staging evaluation, and there were 81 cases (54.36%) completing N staging evaluation. In the 808 patients completing rectal MRI evaluation, there were 708 cases (87.62%) completing T staging evaluation, and there were 590 cases (73.02%) completing N staging evaluation. (4) Imaging evalua-tion after neoadjuvant therapy for patients with mid and low rectal cancer. Of the 388 patients with neoadjuvant therapy, there were 332 patients (85.57%) completing MRI or ultrasound evaluation, and there were 327 patients (84.28%) completing chest, abdomen, and pelvis enhanced CT evalua-tion. In the 70 patients completing rectal ultrasound evaluation, there were 65 cases (92.86%) com-pleting T staging evaluation, and there were 49 cases (70.00%) completing N staging evaluation. In the 327 patients completing rectal MRI evaluation, there were 246 cases (75.23%) completing T staging, and there were 228 cases (69.72%) completing N staging evaluation. Conclusion:The com-pletion rate of tumor imaging evaluation at initial assessment and after neoadjuvant therapy for mid and low rectal cancer patients on a national scale is relatively good.

BACKGROUND:Skin wound repair is an extremely complex process.The nervous system plays an important role in regulating wound repair and scar healing.OBJECTIVE:To review the role of the nervous system in the process of skin wound repair,including the roles of related factors and various cells in the repair of skin injury.METHODS:The PubMed and CNKI databases were searched with the key words of"skin wound healing,nervous system,nerve regeneration,growth factor"in English and"skin wound healing,skin innervation,neuropeptide,growth factor,cell synergy"in Chinese.The time range of literature search was from 2003 to 2024,and 83 documents were finally included and analyzed.RESULTS AND CONCLUSION:(1)The skin is densely innervated by autonomic and sensory nerves,and there is growing evidence that the cutaneous nervous system is not only responsible for transmitting sensory information to the central nervous system,but also plays an important role in a variety of skin functions,including wound healing.(2)The nervous system acts on different stages of skin wound healing,which can regulate revascularization,promote the release of related growth factors and neurotransmitters,and cooperate with different types of cells to promote skin wound healing.Therefore,research on the underlying mechanisms of the nervous system has become a powerful target to promote skin wound healing.

Objective To investigate the effects of scribble planar cell polarity protein(SCRIB)on proliferation,apoptosis,and autophagy of glioblastoma(GBM)and elucidate its potential underlying mechanisms.Methods The expression level of SCRIB in GBM tissue was queried through the Biomarker Exploration of Solid Tumors(BEST)database.Lentivirus-mediated shRNA interference was employed to downregulate SCRIB expression in human glioblastoma cell lines U87 and U251,which were divided into negative control group(mock)and SCRIB shRNA interference groups(kd1 and kd2).SCRIB expression levels were detected using Western blotting(WB)and quantitative polymerase chain reaction(qPCR).EdU incorporation and cell apoptosis rates were detected by flow cytometry(FCM).CCK-8 assay was used to detect the proliferation vitality of U87 and U251 cells,and WB was used to detect the expression of proliferation-related proteins.Immunofluorescence(IF)staining was conducted to detect the expression of autophagy-related proteins LC3 and p62,followed by quantitative analysis across multiple fields.WB was also used to detect the expression levels of LC3,p62,and proteins in the JAK-STAT3 signaling pathway.Results Compared with that of normal tissues,SCRIB mRNA expression level was significantly upregulated in GBM tissues(P＜0.05).FCM results showed that EdU incorporation rates were significantly reduced(P＜0.001)while cell apoptosis rates were markedly increased(P＜0.001)in U87 and U251 cells with SCRIB knockdown.CCK-8 results indicated that compared with the mock group,the proliferation vitality of U87 and U251 cells in the SCRIB knockdown group was significantly downregulated(P＜0.001).IF staining showed that LC3 fluorescence aggregation was significantly enhanced(P＜0.001),while p62 fluorescence aggregation was significantly reduced(P＜0.001)in the SCRIB knockdown group.WB results showed that compared with the mock group,the protein expression levels of p27,LC3,p-JAK2 and p-STAT3 were upregulated,while C-Myc,Cyclin D1,MCM,PCNA and p62 were downregulated,with statistically significant differences(P＜0.05).Conclusion Downregulation of SCRIB may induce autophagy and apoptosis in glioblastoma cells by inhibiting the JAK-STAT3 signaling pathway,thereby suppressing cell proliferation.

Immunotherapy for cancer,as an emerging treatment modality,has made significant strides in recent years and has become a crucial therapeutic approach following surgery,radiotherapy,chemotherapy,and targeted therapy.In particular,the clinical utilization of immune checkpoint inhibitors(ICIs)has not only enhanced the survival rates of patients with refractory or recurrent tumors but has also significantly optimized the overall strategy for cancer treatment.However,as the population undergoing cancer immunotherapy continues to grow,this expansion not only yields clinical benefits but also precipitates a range of specific adverse reactions known as immune-related adverse events(irAEs).Pleural effusion is a common and severe complication in cancer patients,significantly affecting both their quality of life and treatment outcomes.Typically,tumor-related pleural effusion is often due to pleural metastasis,with malignant pleural effusion(MPE)characterized by rapid growth,being difficult to control,and tendency for recurrence.With the approval of new drugs and the expansion of indications for existing medications,the number of cancer patients receiving ICIs treatment is increasing,bringing ICIs-related pleural effusion into focus.While ICIs treatment-related pleural effusion is relatively rare in clinical practice,it is closely linked to treatment choices of patients and prognosis.Unlike MPE,the pathogenesis of ICIs treatment-related pleural effusion is more complex,not only involving non-specific immune activation leading to autoimmune inflammatory reactions but also potentially related to nodular pleural granulomatous reactions,eosinophilic chronic pleurisy,and tumor-infiltrating lymphocytes.In terms of diagnosis,ICIs treatment-related pleural effusion is typically diagnosed through exclusion,requiring the exclusion of other causes such as tumor progression,radiotherapy,and chemotherapy-induced pleural effusion,adding complexity and difficulty to the diagnostic process.Treatment for ICIs treatment-related pleural effusion often involves glucocorticoids,tocilizumab,or infliximab,aiming to alleviate symptoms and improve prognosis by suppressing excessive immune reactions.Preventing the occurrence of ICIs treatment-related pleural effusion is equally crucial,necessitating comprehensive patient assessment before ICIs administration and continuous monitoring during treatment to promptly detect and manage potential adverse reactions.Through this comprehensive management approach,the impact of ICIs treatment-related pleural effusion on patient quality of life and treatment outcomes can be minimized,optimizing overall treatment results.This review aimed to explore the pathogenesis,histological features,clinical manifestations,diagnostic methods and treatment strategies of ICIs treatment-related pleural effusion,and delve into the characteristics of ICIs treatment-related pleural effusion,in order to enhance understanding of this complication and provide a reference for clinical practice.

Objective To investigate the ameliorative effects and mechanisms of six types of tea(green tea,cyan tea,red tea,white tea,black tea and yellow tea)on metabolic disorders in obesity mice induced by high-fat diet(HFD).Methods Four-week-old male C57BL/6J mice were randomly divided into 8 groups with 7 mice per group.An HFD-induced obese mouse model was established,and the mice in control group maintained on standard diet followed by intragastric administration of different teas for 5 weeks.The body weight,liver weight ratio,fasting blood glucose,and lipid profile of the mice were measured to assess glucose and lipid metabolism.Serum inflammatory factors including IL-6,tumor necrosis factor-alpha(TNF-α)and oxidative stress markers[malondialdehyde(MDA)and superoxide dismutase(SOD)were measured.Additionally,liver histopathology and the expression of key glycolipid metabolism-related genes,adenosine monophosphate-activated protein kinase(AMPK)and carnitine palmitoyltransferase 1(CPT-1),were analyzed to explore underlying mechanisms.Results Cyan tea significantly suppressed weight gain,demonstrating superior weight control.White tea markedly reduced fasting blood glucose levels and decreased the area under the curve of oral glucose tolerance test(OGTT)and insulin tolerance test(ITT),indicating synergistic improvements in glucose metabolism and insulin sensitivity.Yellow tea exhibited exceptional anti-inflammatory and antioxidant effects,reducing hepatic IL-6 and MDA while enhancing SOD activity.Green tea activated the lipid oxidation pathway by upregulating AMPK/CPT-1 expression.All kinds of tea significantly attenuated hepatic lipid droplet accumulation.Conclusion All six types of tea alleviated metabolic disorders by reducing hepatic fat content in obesity mice.However,different types of tea exert their unique effects on improving metabolic disorders through differential mechanisms such as glucose metabolism regulation,lipid oxidation,and anti-inflammatory and antioxidant actions.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective To investigate the ameliorative effects and mechanisms of six types of tea(green tea,cyan tea,red tea,white tea,black tea and yellow tea)on metabolic disorders in obesity mice induced by high-fat diet(HFD).Methods Four-week-old male C57BL/6J mice were randomly divided into 8 groups with 7 mice per group.An HFD-induced obese mouse model was established,and the mice in control group maintained on standard diet followed by intragastric administration of different teas for 5 weeks.The body weight,liver weight ratio,fasting blood glucose,and lipid profile of the mice were measured to assess glucose and lipid metabolism.Serum inflammatory factors including IL-6,tumor necrosis factor-alpha(TNF-α)and oxidative stress markers[malondialdehyde(MDA)and superoxide dismutase(SOD)were measured.Additionally,liver histopathology and the expression of key glycolipid metabolism-related genes,adenosine monophosphate-activated protein kinase(AMPK)and carnitine palmitoyltransferase 1(CPT-1),were analyzed to explore underlying mechanisms.Results Cyan tea significantly suppressed weight gain,demonstrating superior weight control.White tea markedly reduced fasting blood glucose levels and decreased the area under the curve of oral glucose tolerance test(OGTT)and insulin tolerance test(ITT),indicating synergistic improvements in glucose metabolism and insulin sensitivity.Yellow tea exhibited exceptional anti-inflammatory and antioxidant effects,reducing hepatic IL-6 and MDA while enhancing SOD activity.Green tea activated the lipid oxidation pathway by upregulating AMPK/CPT-1 expression.All kinds of tea significantly attenuated hepatic lipid droplet accumulation.Conclusion All six types of tea alleviated metabolic disorders by reducing hepatic fat content in obesity mice.However,different types of tea exert their unique effects on improving metabolic disorders through differential mechanisms such as glucose metabolism regulation,lipid oxidation,and anti-inflammatory and antioxidant actions.