OBJECTIVE To introduce the development of an intelligent prescription review decision-support system for anti-tumor drugs and assess its clinical application outcomes. METHODS Relevant data sources， including national and local pharmaceutical administration policies， clinical practice guidelines/consensus， hospital information systems data， and genetic testing results， were integrated. Adhering to the principles of structure， standardization and dynamic updating， a knowledge base covering chemotherapeutic， targeted and immunotherapeutic agents was constructed using a dual-dimensional modeling approach that combined “drug attributes” and “clinical contexts”. This knowledge base was then embedded into the hospital’s electronic medical order system to establish the prescription review decision-support system. The application and performance of the system were evaluated at Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine. RESULTS A knowledge base containing 18 318 prescription review rules for anti-tumor drugs was constructed， and a closed-loop prescription review system was successfully established， encompassing pre-prescription real-time intervention， in-process interactive review， and post-prescription evaluation and analysis. From 2021 to 2024， the system generated a total of 57 879 alerts for prescriptions of five typical categories of anti-tumor drugs. For platinum-containing prescriptions， 22 577 alerts were generated， with Cisplatin for injection （lyophilized） being the most frequently alerted drug （13 445 alerts）， and “ototoxicity risk due to combined use” alerts remained high （7 682 alerts）. For methotrexate-containing prescriptions， 3 721 alerts were recorded， primarily related to “precaution-related issues” （76.4%， 2 843/3 721）. For doxorubicin-containing prescriptions， 17 301 alerts were triggered， primarily related to “dosage and administration” （14 315 alerts）. For human epidermal growth factor receptor 2-targeted agents-containing prescriptions， 1 007 alerts were issued， mostly related to “reimbursement restrictions” （956 alerts）. For programmed death-1/programmed death-ligand 1 inhibitors-containing prescriptions， the alerts increased year by year， totaling 13 273 alerts， primarily related to “inappropriate indication” （9 118 alerts）. Over the 4 years， the physician response rates to system alerts were 21.4%， 27.1%， 33.5% and 51.6%， respectively. CONCLUSIONS An intelligent decision-support system for anti-tumor drug prescription review， encompassing a closed-loop process of “real-time pre-event intervention， interactive in-event prescription review， post-event evaluation and analysis”， has been successfully constructed and implemented throughout the entire workflow. There is a discernible trend in this hospital， where the focus on monitoring anti-tumor drugs is shifting towards immunotherapy drugs. Additionally， the acceptance rate of physicians regarding prescription review opinions has been steadily increasing year by year.

ObjectiveThis study employs a special conformational engineering (CE) technology to construct an α-chymotrypsin-like active center, which includes a catalytic triad, an oxyanion hole, and a substrate-binding site, on silver nanoparticles (AgNPs), thereby creating an AgNP-based artificial hydrolase with high catalytic activity. This study provides a new approach for the design of highly efficient artificial enzymes and enzyme-mimicking. MethodsAgNPs were chosen as the scaffold to build the an α-chymotrypsin-like active center. A special CE procedure enables the designed peptide, Triad5, to adopt an α‑helical conformation on AgNPs, with the key catalytic residues located on one side of the α-helix forming a catalytic active center with a catalytic triad, an oxyanion hole, and a substrate-binding site. The CE procedure consists of three steps, including conformation induction via trifluoroethanol (TFE), conformation stabilization on AgNPs via Ag-S bonds, and TFE removal via lyophilization. Circular dichroism (CD) spectra were used to confirm the formation and stabilization of the α-helix conformation. Mutations of the key residues combined with stopped-flow kinetic experiments were used to demonstrate the indispensability of each key residue and the synergistic effects among the catalytic triad, the oxyanion hole, and the substrate-binding site. ResultsCD spectra show that the designed Triad5 alone is in random coil conformation; when conjugated on AgNPs, Triad5 still remains largely unstructured; but after the CE treatment, Triad5 adopts a typical α-helical conformation on AgNPs as designed, thus produces an AgNP-based artificial hydrolase, Silverzyme. Silverzyme exhibits extremely high hydrolytic activity towards p-nitrophenyl acetate (p-NPA), with an extremely high catalytic turnover number per active site of 3.5 s^-1, which is even higher than that of α-chymotrypsin. As a comparison, the AgNP-Triad5 conjugate without CE treatment shows much lower catalytic activity than Silverzyme, highlighting the important role of the right conformation of the active center for the catalytic activity and the power of the CE treatment. When the key residues of the catalytic triad of Silverzyme were mutated to alanine, the overall catalytic efficiency of this mutant dropped by about 2 orders of magnitude, unambiguously demonstrating the key role of the designed catalytic triad. Similarly, when the residues for the oxyanion hole were deleted, the mutant with the intact catalytic triad also showed significantly decreased catalytic activity, highlighting the indispensable role of the oxyanion hole for the catalytic activity. Unexpectedly, when both the catalytic triad and the oxyanion hole were kept intact, a slight change of the binding site also resulted in significantly decreased catalytic activity, indicating that the designed binding site is at the right position to align the substrate in the right orientation in the active center for catalytic hydrolysis. These results confirm the synergy among the catalytic triad, the oxyanion hole, and the substrate-binding site, indicating successful mimicking of the active center of α-chymotrypsin. Moreover, Silverzyme shows better thermal stability than α-chymotrypsin, and can even hydrolyze the tough non-activated ester diethyl phthalate, a priority pollutant by the United States Environmental Protection Agency (USEPA). ConclusionThis study successfully mimicked the complex catalytic active center of α-chymotrypsin using a conformational engineering strategy, and produced a highly active artificial hydrolase with a well-defined structure and catalytic mechanism. The findings highlight the significant potential of conformational engineering.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Based on copper death, this study investigates the effect and mechanism of Shenmai Injection on isoproterenol(ISO)-induced myocardial fibrosis(MF) in rats. SPF-grade male SD rats were randomly divided into a normal group, model group, captopril(5 mg·kg~(-1)) positive control group, and Shenmai Injection low(6 mL·kg~(-1)), medium(9 mL·kg~(-1)), and high(12 mL·kg~(-1)) dose groups. Except for the normal group, the rats in the other groups were subcutaneously injected with ISO(5 mg·kg~(-1)) once a day for 10 consecutive days to establish an MF model. Starting from the second day after successful modeling, intraperitoneal injections of the respective treatments were administered for 28 consecutive days. Hematoxylin-eosin(HE) and Masson staining were used to observe pathological changes and fibrosis levels in the myocardial tissue. Colorimetry was employed to detect serum Cu~(2+) concentration in rats. The levels of inflammatory cytokines interleukin-6(IL-6), interleukin-1β(IL-1β), interleukin-18(IL-18), tumor necrosis factor-α(TNF-α), as well as mitochondrial energy metabolites adenosine triphosphate(ATP), adenosine diphosphate(ADP), and adenosine monophosphate(AMP) in serum were measured using enzyme-linked immunosorbent assay(ELISA). Western blot was performed to detect the expression of collagen Ⅰ(Col-Ⅰ), collagen Ⅲ(Col-Ⅲ), and copper death-related proteins dihydrolipoamide acetyltransferase(DLAT), ferredoxin 1(FDX1), lipoic acid synthetase(LIAS), and heat shock protein 70(HSP70) in myocardial tissue. Immunofluorescence was used to detect the expression of DLAT, FDX1, and HSP70, while immunohistochemistry was conducted to examine the expressions of DLAT, FDX1, LIAS, and HSP70. The results showed that, compared to the model group, the myocardial structure disorder and collagen fiber deposition in the drug treatment groups were significantly improved, the cardiac index level was reduced, serum Cu~(2+), IL-6, IL-1β, IL-18, TNF-α, ADP, and AMP levels were significantly decreased, ATP levels were significantly increased, and the expressions of Col-Ⅰ, Col-Ⅲ, and HSP70 proteins in myocardial tissue were significantly reduced, while the expressions of DLAT, FDX1, and LIAS proteins were significantly elevated. In conclusion, Shenmai Injection effectively alleviates myocardial structure disorder and interstitial collagen fiber deposition in ISO-induced MF rats, promotes copper excretion, and reduces copper death in the ISO-induced rat MF model.
Animals ; Male ; Drugs, Chinese Herbal/administration & dosage* ; Rats, Sprague-Dawley ; Rats ; Myocardium/metabolism* ; Drug Combinations ; Fibrosis/metabolism* ; Copper/blood* ; Cardiomyopathies/genetics* ; Humans

Background/Aims: Metabolic dysfunction-associated steatohepatitis (MASH) is a significant risk factor for gallstone formation, but mechanisms underlying MASH-related gallstone formation remain unclear. Golgi membrane protein 1 (GOLM1) participates in hepatic cholesterol metabolism and is upregulated in MASH. Here, we aimed to explore the role of GOLM1 in MASH-related gallstone formation. Methods: The UK Biobank cohort was used for etiological analysis. GOLM1 knockout (GOLM1-/-) and wild-type (WT) mice were fed with a high-fat diet (HFD). Livers were excised for histology and immunohistochemistry analysis. Gallbladders were collected to calculate incidence of cholesterol gallstones (CGSs). Biles were collected for biliary lipid analysis. HepG2 cells were used to explore underlying mechanisms. Human liver samples were used for clinical validation. Results: MASH patients had a greater risk of cholelithiasis. All HFD-fed mice developed MASH, and the incidence of gallstones was 16.7% and 75.0% in GOLM1-/- and WT mice, respectively. GOLM1-/- decreased biliary cholesterol concentration and output. In vivo and in vitro assays confirmed that GOLM1 facilitated cholesterol efflux through upregulating ATP binding cassette transporter subfamily G member 5 (ABCG5). Mechanistically, GOLM1 translocated into nucleus to promote osteopontin (OPN) transcription, thus stimulating ABCG5-mediated cholesterol efflux. Moreover, GOLM1 was upregulated by interleukin-1β (IL-1β) in a dose-dependent manner. Finally, we confirmed that IL-1β, GOLM1, OPN, and ABCG5 were enhanced in livers of MASH patients with CGSs. Conclusions In MASH livers, upregulation of GOLM1 by IL-1β increases ABCG5-mediated cholesterol efflux in an OPN-dependent manner, promoting CGS formation. GOLM1 has the potential to be a molecular hub interconnecting MASH and CGSs.

Spermatogenesis is a fundamental process that requires a tightly controlled epigenetic event in spermatogonial stem cells (SSCs). The mechanisms underlying the transition from SSCs to sperm are largely unknown. Most studies utilize gene knockout mice to explain the mechanisms. However, the production of genetically engineered mice is costly and time-consuming. In this study, we presented a convenient research strategy using an RNA interference (RNAi) and testicular transplantation approach. Histone H3 lysine 9 (H3K9) methylation was dynamically regulated during spermatogenesis. As Jumonji domain-containing protein 1A (JMJD1A) and Jumonji domain-containing protein 2C (JMJD2C) demethylases catalyze histone H3 lysine 9 dimethylation (H3K9me2), we firstly analyzed the expression profile of the two demethylases and then investigated their function. Using the convenient research strategy, we showed that normal spermatogenesis is disrupted due to the downregulated expression of both demethylases. These results suggest that this strategy might be a simple and alternative approach for analyzing spermatogenesis relative to the gene knockout mice strategy.
Spermatogenesis/physiology* ; Animals ; Male ; Mice ; Epigenesis, Genetic ; Jumonji Domain-Containing Histone Demethylases/metabolism* ; Histones/metabolism* ; RNA Interference ; Testis/metabolism* ; Methylation ; Mice, Knockout ; Histone Demethylases

OBJECTIVE: To explore a predictive model that can better predict the prognosis of patients with diffuse large B-cell lymphoma (DLBCL), and validate its clinical value. METHODS: Clinical data of 134 newly treated DLBCL patients were collected from Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from January 2015 to January 2020. Several risk factors of the patients were screened and analyzed, a novel prognostic model were then established based on this, and its clinical application potential was validated. RESULTS: In the novel model, predicting progression-free survival (PFS) based on the age at initial treatment, albumin level, Hans classification, Ann Arbor stage, and BCL2 expression showed better predictive performance than International Prognostic Index (IPI) score (AUC: 0.788 vs 0.620，P <0.001). Predicting overall survival (OS) based on the age at initial treatment, albumin level, lactate dehydrogenase (LDH) level, and expressions of BCL2 and MUM1 proteins also showed better predictive performance for mortality risk than IPI score (AUC: 0.817 vs 0.624，P <0.001). CONCLUSION This novel prognostic model can better predict the survival prognosis of DLBCL patients compared to the IPI scoring system.
Humans ; Lymphoma, Large B-Cell, Diffuse/diagnosis* ; Prognosis ; Proto-Oncogene Proteins c-bcl-2/metabolism* ; Risk Factors ; Male ; Female ; Middle Aged

BACKGROUND: Based on the China-VHD database, this study sought to develop and validate a Valvular Heart Disease- specific Age-adjusted Comorbidity Index (VHD-ACI) for predicting mortality risk in patients with VHD. METHODS & RESULTS: The China-VHD study was a nationwide, multi-centre multi-centre cohort study enrolling 13,917 patients with moderate or severe VHD across 46 medical centres in China between April-June 2018. After excluding cases with missing key variables, 11,459 patients were retained for final analysis. The primary endpoint was 2-year all-cause mortality, with 941 deaths (10.0%) observed during follow-up. The VHD-ACI was derived after identifying 13 independent mortality predictors: cardiomyopathy, myocardial infarction, chronic obstructive pulmonary disease, pulmonary artery hypertension, low body weight, anaemia, hypoalbuminaemia, renal insufficiency, moderate/severe hepatic dysfunction, heart failure, cancer, NYHA functional class and age. The index exhibited good discrimination (AUC, 0.79) and calibration (Brier score, 0.062) in the total cohort, outperforming both EuroSCORE II and ACCI (P < 0.001 for comparison). Internal validation through 100 bootstrap iterations yielded a C statistic of 0.694 (95% CI: 0.665-0.723) for 2-year mortality prediction. VHD-ACI scores, as a continuous variable (VHD-ACI score: adjusted HR (95% CI): 1.263 (1.245-1.282), P < 0.001) or categorized using thresholds determined by the Yoden index (VHD-ACI ≥ 9 vs. < 9, adjusted HR (95% CI): 6.216 (5.378-7.184), P < 0.001), were independently associated with mortality. The prognostic performance remained consistent across all VHD subtypes (aortic stenosis, aortic regurgitation, mitral stenosis, mitral regurgitation, tricuspid valve disease, mixed aortic/mitral valve disease and multiple VHD), and clinical subgroups stratified by therapeutic strategy, LVEF status (preserved vs. reduced), disease severity and etiology. CONCLUSION The VHD-ACI is a simple 13-comorbidity algorithm for the prediction of mortality in VHD patients and providing a simple and rapid tool for risk stratification.

Background/Aims: Metabolic dysfunction-associated steatohepatitis (MASH) is a significant risk factor for gallstone formation, but mechanisms underlying MASH-related gallstone formation remain unclear. Golgi membrane protein 1 (GOLM1) participates in hepatic cholesterol metabolism and is upregulated in MASH. Here, we aimed to explore the role of GOLM1 in MASH-related gallstone formation. Methods: The UK Biobank cohort was used for etiological analysis. GOLM1 knockout (GOLM1-/-) and wild-type (WT) mice were fed with a high-fat diet (HFD). Livers were excised for histology and immunohistochemistry analysis. Gallbladders were collected to calculate incidence of cholesterol gallstones (CGSs). Biles were collected for biliary lipid analysis. HepG2 cells were used to explore underlying mechanisms. Human liver samples were used for clinical validation. Results: MASH patients had a greater risk of cholelithiasis. All HFD-fed mice developed MASH, and the incidence of gallstones was 16.7% and 75.0% in GOLM1-/- and WT mice, respectively. GOLM1-/- decreased biliary cholesterol concentration and output. In vivo and in vitro assays confirmed that GOLM1 facilitated cholesterol efflux through upregulating ATP binding cassette transporter subfamily G member 5 (ABCG5). Mechanistically, GOLM1 translocated into nucleus to promote osteopontin (OPN) transcription, thus stimulating ABCG5-mediated cholesterol efflux. Moreover, GOLM1 was upregulated by interleukin-1β (IL-1β) in a dose-dependent manner. Finally, we confirmed that IL-1β, GOLM1, OPN, and ABCG5 were enhanced in livers of MASH patients with CGSs. Conclusions In MASH livers, upregulation of GOLM1 by IL-1β increases ABCG5-mediated cholesterol efflux in an OPN-dependent manner, promoting CGS formation. GOLM1 has the potential to be a molecular hub interconnecting MASH and CGSs.