Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Objective To explore the drug selection, usage, dosage and effect of clinical pharmacists in the treatment of secondary Candida bloodstream infection in patients with digestive tract perforation, and provide reference for rational clinical use of such anti-infection therapy. Methods During the treatment of Candida infection, anti-infection specialist clinical pharmacists suggested replacing fluconazole for anti-infection treatment, and adjusted the usage and dosage of caspofungin to ensure the application of full treatment course. Results The patient’s Candida bloodstream infection was effectively controlled. Conclusion Echininocandins such as caspofungin are the first choice for Candida infection. The maintenance dose should be reduced to 35 mg qd in patient with moderate liver function injury, and the anti-infection treatment should be done at least 14 days after the blood culture being negative. Clinical pharmacists participate in clinical pharmaceutical care practices such as clinical ward rounds, and actively assist doctors to develop individualized anti-infection programs, which could improve the level of clinical drug use and the clinical outcome of diseases.

BACKGROUND: Growing evidence suggests that long non-coding RNAs (lncRNAs) exert pivotal roles in fostering chemoresistance across diverse tumors. Nevertheless, the precise involvement of lncRNAs in modulating chemoresistance within the context of gallbladder cancer (GBC) remains obscure. This study aimed to uncover how lncRNAs regulate chemoresistance in gallbladder cancer, offering potential targets to overcome drug resistance. METHODS: To elucidate the relationship between gemcitabine sensitivity and small nucleolar RNA host gene 1 ( SNHG1 ) expression, we utilized publicly available GBC databases, GBC tissues from Renji Hospital collected between January 2017 and December 2019, as well as GBC cell lines. The assessment of SNHG1, miR-23b-3p, and phosphatase and tensin homolog (PTEN) expression was performed using in situ  hybridization, quantitative real-time polymerase chain reaction, and western blotting. The cell counting kit-8 (CCK-8) assay was used to quantify the cell viability. Furthermore, a GBC xenograft model was employed to evaluate the impact of SNHG1 on the therapeutic efficacy of gemcitabine. Receiver operating characteristic (ROC) curve analyses were executed to assess the specificity and sensitivity of SNHG1. RESULTS: Our analyses revealed an inverse correlation between the lncRNA SNHG1 and gemcitabine resistance across genomics of drug sensitivity in cancer (GDSC) and Gene Expression Omnibus (GEO) datasets, GBC cell lines, and patients. Gain-of-function investigations underscored that SNHG1 heightened the gemcitabine sensitivity of GBC cells in both in vitro and in vivo  settings. Mechanistic explorations illuminated that SNHG1 could activate PTEN -a commonly suppressed tumor suppressor gene in cancers-thereby curbing the development of gemcitabine resistance in GBC cells. Notably, microRNA (miRNA) target prediction algorithms unveiled the presence of miR-23b-3p binding sites within SNHG1 and the 3'-untranslated region (UTR) of PTEN . Moreover, SNHG1 acted as a sponge for miR-23b-3p, competitively binding to the 3'-UTR of PTEN , thereby amplifying PTEN expression and heightening the susceptibility of GBC cells to gemcitabine. CONCLUSION The SNHG1/miR-23b-3p/PTEN axis emerges as a pivotal regulator of gemcitabine sensitivity in GBC cells, holding potential as a promising therapeutic target for managing GBC patients.
Humans ; Deoxycytidine/pharmacology* ; PTEN Phosphohydrolase/genetics* ; Gemcitabine ; RNA, Long Noncoding/metabolism* ; MicroRNAs/genetics* ; Gallbladder Neoplasms/genetics* ; Cell Line, Tumor ; Animals ; Mice ; Drug Resistance, Neoplasm/genetics* ; Mice, Nude ; Antimetabolites, Antineoplastic ; Gene Expression Regulation, Neoplastic

Prostate cancer (PCa) ranks as the second most prevalent malignancy among men worldwide. Early diagnosis, personalized treatment, and prognosis prediction of PCa play a crucial role in improving patients' survival rates. The advancement of artificial intelligence (AI), particularly the utilization of deep learning (DL) algorithms, has brought about substantial progress in assisting the diagnosis, treatment, and prognosis prediction of PCa. The introduction of the foundation model has revolutionized the application of AI in medical treatment and facilitated its integration into clinical practice. This review emphasizes the clinical application of AI in PCa by discussing recent advancements from both pathological and imaging perspectives. Furthermore, it explores the current challenges faced by AI in clinical applications while also considering future developments, aiming to provide a valuable point of reference for the integration of AI and clinical applications.
Humans ; Prostatic Neoplasms/diagnosis* ; Male ; Artificial Intelligence ; Deep Learning ; Prognosis

OBJECTIVE: To construct an integrated management model for early screening and diagnosis of PCa based on the Innovative Care for Chronic Conditions Framework (ICCC) and the 1+1 contract-based tiered diagnosis and treatment system (TDTS) in China. METHODS: Based on the 1+1 contract-based TDTS platform, we conducted PCa screening for the male residents aged 60 years and above during health check-ups in Pujin Community Health Center from January 1, 2023 to December 31, 2023. For those with abnormal total prostate-specific antigen (tPSA) ≥ 4 μg/L, we promptly referred them to higher-level hospitals for further diagnosis and treatment via the two-way referral green channel platform and information sharing service using the 1+1 contract model. We further analyzed the relevant data on screening and diagnosis. RESULTS: A total of 4 080 males aged 71.39±5.059 years received PCa screening from January to December 2023. PSA screening was performed in 43.96% of the male residents, revealing 654 cases of PSA abnormality, with a PSA positivity rate of 16.03%, which was higher than that found in the previous large-scale PCa screenings in other regions of China. Among the males with PSA abnormality, 292 (44.65%) expressed their willingness for medical referral, while the others did not seek further medical attention for reasons of being asymptomatic, low awareness of the disease, no accompany for medical visits, and concerns about further costs of diagnosis and treatment. Prostate biopsy was recommended to 154 cases after further examinations, which was accepted by 92 (59.74%). Fifty-eight cases were diagnosed with Pa, and thedetection rate reached 63.04%. CONCLUSION The integrated management model for PSA examination-based early screening and diagnosis of PCa using the 1+1 contract-based TDTS platform is plays a significant role in enhancing people's awareness and knowledge of PCa and improving the early detection rate of the malignancy.
Humans ; Male ; Prostatic Neoplasms/diagnosis* ; Early Detection of Cancer ; Prostate-Specific Antigen/blood* ; Aged ; China ; Mass Screening ; Middle Aged ; Chronic Disease

Cardiovascular damage caused by cancer treatment has become an important cause of death for tumor survivors. With the recognition of cardiovascular diseases and cancer therapy-related cardiovascular toxicity (CTR-CVT) in tumor patients, noninvasive imaging technologies play pivotal roles in the risk stratification, early diagnosis, monitoring and follow-up for CTR-CVT. In recent years, the field of cardio-oncology has witnessed continual updates in diagnostic and therapeutic strategies, with several pertinent guidelines and expert consensus documents issued in China and abroad. However, there remains a conspicuous absence of systematic guidance documents on the application of imaging techniques in the clinical practice of cardio-oncology. Therefore, the Chinese Anti-Cancer Association Society of Integrative Cardio-oncology, the Ultrasound Branch of the Chinese Medical Association, and the Chinese Society of Echocardiography convened experts to formulate the "Chinese guideline for the clinical application of noninvasive imaging technology in accessing cancer therapy-related cardiovascular toxicity". Building upon the systematic evaluation of guidelines and the latest evidence-based medical research in the field of cardio-oncology domestically and abroad, and in conjunction with data derived from evidence-based medical research in China, this guideline proposes noninvasive imaging examination methods and monitoring strategies for CTR-CVT, aiming to further standardize and guide the clinical practice of multidisciplinary physicians specializing in cardio-oncology in China.

The nervous system is the dominant regulatory system in the human body. The traditional theory is that tumors lack innervation. However, an increasing number of studies have shown complex bidirectional interactions between tumors and the nervous system. Globally, colorectal cancer (CRC) is the third most common cancer. With the rise of tumor neuroscience, the role of nervous system imbalances in the occurrence and development of CRC has attracted increasing amounts of attention. However, there are still many gaps in the research on the interactions and mechanisms involved in the nervous system in CRC. This article systematically reviews emerging research on the bidirectional relationships between the nervous system and CRC, focusing on the following areas: (1) Effects of the nervous system on colon cancer. (2) Effects of CRC on the nervous system. (3) Treatment of CRC associated with the nervous system.
Humans ; Colorectal Neoplasms/therapy* ; Animals ; Nervous System/metabolism*