Objective To evaluate the applicability and guideline concordance of the Chinese Society of Clinical Oncology(CSCO)arti-ficial intelligence(AI)system in clinical decision-making for colorectal cancer(CRC)patients,and to explore its feasibility in real-world clinical applications.Methods A total of 972 CRC patients diagnosed and treated at the Second Affiliated Hospital,Zhejiang University School of Medicine,from January 2010 to December 2021,were included.Patient data were analyzed by the CSCO AI system to gener-ate treatment decisions,and decision concordance was assessed by a blinded independent central review(BICR)panel.The applicability and guideline concordance rates of the CSCO AI system were calculated for different treatment stages,and a logistic regression model was used to analyze factors influencing the system's decision discrepancies with actual treatments.Results The overall applicability rate of the CSCO AI system was 96.2%,and the overall guideline concordance rate was 94.9%.In the adjuvant and palliative treatment stages,the system's applicability rates were 95.8%and 96.7%,respectively,and the guideline concordance rates were 95.0%and 94.9%,respective-ly.Multivariate logistic regression analysis showed that age≥65 years and high-risk stage Ⅱ treatment were significant factors affecting guideline concordance in the adjuvant treatment stage(both P<0.05).Conclusions The CSCO AI system demonstrated high applicability and guideline concordance in the adjuvant and palliative treatment stages for CRC.The system's clinical decision-making potential is sig-nificant,and it can be further optimized for specific clinical scenarios and promoted for use across various medical institutions.

Colorectal tumorigenesis generally progresses from adenoma to adenocarcinoma, accompanied by dynamic changes in the tumor microenvironment (TME). A randomized controlled trial has confirmed the efficacy and safety of Shen-Bai-Jie-Du decoction (SBJDD) in preventing colorectal tumorigenesis. However, the mechanism remains unclear. In this study, we employed single-cell RNA sequencing (scRNA-seq) to investigate the dynamic evolution of the TME and validated cell infiltration with multiplex immunohistochemistry and flow cytometry. Bulk RNA sequencing was utilized to assess the underlying mechanisms. Our results constructed the mutually verifiable single-cell transcriptomic atlases in Apc ^Min/+ mice and clinical patients. There was a marked accumulation of CCL22⁺ dendritic cells (DCs) and an enhanced immunosuppressive action, which SBJDD and berberine reversed. Combined treatment with cholesterol and lipopolysaccharide induced characteristic gene expression of CCL22⁺ DCs, which may represent "exhausted DCs". Intraperitoneal injection of these DCs after SBJDD treatment eliminated its therapeutic effects. TMEM131 derived CCL22⁺ DCs generation by TNF signaling pathway and may be a potential target of berberine in retarding colorectal tumorigenesis. These findings emphasize the role of exhausted DCs and the regulatory mechanisms of SBJDD and berberine in colorectal cancer (CRC), suggesting that the multi-component properties of SBJDD may help restore TME homeostasis and offer novel cancer therapy.

Objective To evaluate the applicability and guideline concordance of the Chinese Society of Clinical Oncology(CSCO)arti-ficial intelligence(AI)system in clinical decision-making for colorectal cancer(CRC)patients,and to explore its feasibility in real-world clinical applications.Methods A total of 972 CRC patients diagnosed and treated at the Second Affiliated Hospital,Zhejiang University School of Medicine,from January 2010 to December 2021,were included.Patient data were analyzed by the CSCO AI system to gener-ate treatment decisions,and decision concordance was assessed by a blinded independent central review(BICR)panel.The applicability and guideline concordance rates of the CSCO AI system were calculated for different treatment stages,and a logistic regression model was used to analyze factors influencing the system's decision discrepancies with actual treatments.Results The overall applicability rate of the CSCO AI system was 96.2%,and the overall guideline concordance rate was 94.9%.In the adjuvant and palliative treatment stages,the system's applicability rates were 95.8%and 96.7%,respectively,and the guideline concordance rates were 95.0%and 94.9%,respective-ly.Multivariate logistic regression analysis showed that age≥65 years and high-risk stage Ⅱ treatment were significant factors affecting guideline concordance in the adjuvant treatment stage(both P<0.05).Conclusions The CSCO AI system demonstrated high applicability and guideline concordance in the adjuvant and palliative treatment stages for CRC.The system's clinical decision-making potential is sig-nificant,and it can be further optimized for specific clinical scenarios and promoted for use across various medical institutions.

With the increasingly wide application of herbal medicines and dietary supplements worldwide,herb-induced liver injury(HILI)has become an important etiology of drug-induced liver injury.Due to the diverse manifestations of HILI,the difficulty in medical history collection,and the lack of specific biomarkers,how to identify suspected patients and make a correct diagnosis has become a major challenge in practice.Causality assessment is commonly used in the diagnosis of HILI,but there is still a lack of prospective cohort studies with a large sample size.In addition,further studies are needed to search for the specific biomarkers for the diagnosis of HILI.The diagnosis and differential diagnosis of HILI are challenging,and currently there is still no universally accepted uniform and standard method for the diagnosis of all-cause HILI.

Cancer has become a major life-threatening disease globally.In recent years,precision therapy for cancer has gradually emerged,and significant success has been achieved with targeted therapies,immune checkpoint inhibitors,and the newly emerging antibody-drug conjugates(ADC).The development of ADC has been rapid,with up to 15 ADC drugs currently approved worldwide.However,the hepatotoxicity of ADC has gained increasing attention,with reports of fatal hepatotoxic events.In this article,we briefly reviewed the ADC approved globally,summarized the liver-related adverse events and hepatotoxic manifestations reported in current clinical trials of ADC,and compiled research on possible hepatotoxicity mechanisms.Our aim is to assist clinicians in understanding and managing the hepatotoxicity characteristics of ADC,enabling timely identification of patients at risk of hepatotoxicity and implementing effective measures to manage these risks,thus reducing and preventing serious adverse events.

With the increasing application of immune checkpoint inhibitors(ICIs)in tumor therapy,ICIs hepatotoxicity has emerged as an inevitable challenge.Despite the fact that relevant guidelines have specifically addressed this issue in recent years,many difficulties still exist in clinical practice.In terms of diagnosis,the lack of specific diagnostic biomarkers for ICIs hepatotoxicity and the complexity of the etiology of liver injury,concomitant medications,and the clinical phenotypes of hepatotoxicity in cancer patients can make the diagnosis of ICIs hepatotoxicity difficult.In terms of management,the optimal dose and duration of steroid therapy,the choice of different immunosuppressants as rescue therapy,and the reintroduction of ICIs therapy are yet to be supported by high-quality evidence-based medical evidence.We discussed the above-mentioned challenges faced by clinicians in this article.

Cancer has become a major life-threatening disease globally.In recent years,precision therapy for cancer has gradually emerged,and significant success has been achieved with targeted therapies,immune checkpoint inhibitors,and the newly emerging antibody-drug conjugates(ADC).The development of ADC has been rapid,with up to 15 ADC drugs currently approved worldwide.However,the hepatotoxicity of ADC has gained increasing attention,with reports of fatal hepatotoxic events.In this article,we briefly reviewed the ADC approved globally,summarized the liver-related adverse events and hepatotoxic manifestations reported in current clinical trials of ADC,and compiled research on possible hepatotoxicity mechanisms.Our aim is to assist clinicians in understanding and managing the hepatotoxicity characteristics of ADC,enabling timely identification of patients at risk of hepatotoxicity and implementing effective measures to manage these risks,thus reducing and preventing serious adverse events.

With the increasing application of immune checkpoint inhibitors(ICIs)in tumor therapy,ICIs hepatotoxicity has emerged as an inevitable challenge.Despite the fact that relevant guidelines have specifically addressed this issue in recent years,many difficulties still exist in clinical practice.In terms of diagnosis,the lack of specific diagnostic biomarkers for ICIs hepatotoxicity and the complexity of the etiology of liver injury,concomitant medications,and the clinical phenotypes of hepatotoxicity in cancer patients can make the diagnosis of ICIs hepatotoxicity difficult.In terms of management,the optimal dose and duration of steroid therapy,the choice of different immunosuppressants as rescue therapy,and the reintroduction of ICIs therapy are yet to be supported by high-quality evidence-based medical evidence.We discussed the above-mentioned challenges faced by clinicians in this article.