OBJECTIVE To establish a high-risk medication list and preventive and therapeutic measures for drug-induced hypofibrinogenemia， and to provide a reference for the prevention and treatment of this condition. METHODS By integrating domestic and international case reports， retrospective case-control studies， and spontaneous adverse drug reaction reporting databases， 19 domestically marketed high-risk drugs for drug-induced hypofibrinogenemia were identified. Based on the clinical characteristics and mechanisms of these drugs， relevant risk factors were systematically reviewed， and existing treatment options were summarized， leading to the preliminary development of recommended preventive and therapeutic measures. A two-round Delphi consultation was conducted to evaluate， revise， and ultimately reach consensus on the preliminary findings， using a mean importance score of ≥3.5 points for indicators and a coefficient of variation ＜0.3 as screening criteria. RESULTS The coefficient of expert authority for both rounds of expert consultation was 0.904. In the first round， the Kendall coordination coefficients （Kendall’s W ） for the high-risk medication list and the proposed preventive and therapeutic measures were 0.390 and 0.223 （ P ＜0.05）， respectively. In the second round， the Kendall’s W were 0.227 and 0.200 （ P ＜0.05）， respectively. After two rounds of expert consultation and discussion， 11 high-risk drugs for drug-induced hypofibrinogenemia， represented by hemocoagulase and certain anti-infective agents， were ultimately identified， along with 5 preventive and therapeutic measures spanning the entire process of “pre-medication assessment， intra-medication monitoring， and bleeding event management”. CONCLUSIONS This study has established a scientific and reliable high-risk medication list， and corresponding preventive and therapeutic measures for drug-induced hypofibrinogenemia， providing a theoretical basis and practical support for the early identification， stratified management， and precise intervention of this condition.

Lung cancer exhibits the highest incidence and mortality rates among cancers globally,with a five-year overall survival rate alarmingly below 20％.Targeting autophagy,though a controversial therapeutic strategy,is extensively employed in clinical practice.Current research is actively pursuing various therapeutic strategies using small molecules to exploit the dual function of autophagy.Nevertheless,the pivotal question of enhancing or inhibiting autophagy in cancer therapy merits further attention.This review aims to provide a comprehensive overview of the mechanisms of autophagy in lung cancer.It also explores recent advances in targeting cytotoxic autophagy and inhibiting protective autophagy with small molecules to induce cell death in lung cancer cells.Notably,most autophagy-targeting drugs,primarily natural small molecules,have demonstrated that activating cytotoxic autophagy effectively induces cell death in lung cancer,as opposed to inhibiting protective autophagy.These insights contribute to identifying druggable targets and drug candidates for potential autophagy-related lung cancer therapies,offering promising approaches to combat this disease.

Objective:To compare the clinical characteristics and laboratory findings between elderly rheumatoid arthritis(ERA)with those of non-elderly rheumatoid arthritis(NERA)patients.Methods:A cross-sectional study was conducted.The study collected laboratory indicators of 1, 286 ERA and 3, 211 NERA patients admitted to the Affiliated Hospital of Zunyi Medical University between January 2015 and December 2022, including inflammatory indicators, complete blood count, liver/kidney function tests, blood lipid, and glycated hemoglobin(HbA 1c), etc. Results:Erythrocyte sedimentation rate, high-sensitivity C-reactive protein and rheumatoid factor in ERA patients were higher than those in NERA patients( t=13.940, 8.453, 3.400, all P<0.001). Hemoglobin, red blood cell count, red blood cell distribution width, albumin and total protein in ERA patients were lower than those in NERA patients( t=2.380, 6.546, 1.954, 12.800, 10.490, all P<0.05). The levels of aspartate aminotransferase, alkaline phosphatase, γ-glutamyl transferase, total bile acid, globulin, lactate dehydrogenase, creatinine and urea nitrogen in ERA patients were higher than those in NERA patients( t=3.366, 3.422, 2.760, 4.520, 3.676, Z=8.678, t=10.630, 17.640, all P<0.05). The levels of uric acid, alanine aminotransferase, total cholesterol, triglyceride, blood glucose and HbA 1c in female ERA patients were higher than those in NERA group( t=6.009, 1.100, 2.111, 3.954, 4.262, 2.667, all P<0.05). Decreased RBC, ALB, TP, GLB( OR=0.279, 95% CI: 0.133-0.582; OR=0.867, 95% CI: 0.809-0.930; OR=0.948, 95% CI: 0.903-0.996; OR=0.817, 95% CI: 0.798-0.833), and increased ALT, AST, Scr, BUN, LDL-C and TC( OR=1.013, 95% CI: 0.997-1.018; OR=1.046, 95% CI: 1.015-1.079; OR=1.026, 95% CI: 1.005-1.047; OR=1.034, 95% CI: 1.019-1.051; OR=1.373, 95% CI: 1.088-1.733; OR=1.266, 95% CI: 1.022-1.569)were independent influencing factors of ERA. Conclusions:ERA patients exhibit elevated inflammatory markers and are more prone to anemia, liver and kidney function damage, and malnutrition.Furthermore, female ERA patients are more likely to have abnormal uric acid, alanine aminotransferase, blood lipids, and blood glucose.

Objective To explore the correlation of MET status in patients with advanced prostatic acinar adenocarcinoma with the clinical pathological parameters and prognosis. Methods The specimen from 135 patients with advanced prostatic acinar adenocarcinoma was included. The expression of c-MET protein was detected via immunohistochemistry, and MET gene amplification was assessed by fluorescence in situ hybridization. The relationships of c-MET expression and gene amplification with clinicopathological features and prognosis were analyzed. Results The positive expression rate of c-MET was 52.60% (71/135). Compared with the c-MET expression in adjacent tissues, that in tumor tissues showed lower heterogeneous expression. Among the cases, 1.71% (2/117) exhibited MET gene polyploidy, but no gene amplification was detected. Positive c-MET expression was significantly correlated with high Gleason scores and grade groups (P=0.0073). However, no significant relationship was found between c-MET expression and progression-free survival or post-treatment t-PSA levels. Conclusion c-MET protein is expressed at a relatively low level in advanced prostatic acinar adenocarcinoma, suggesting that c-MET may not be a viable target for ADC drug development in prostatic acinar adenocarcinoma.

Iron overload is strongly associated with heart disease. Ferroptosis is a new form of regulated cell death indicated in cardiac ischemia-reperfusion (I/R) injury. However, the specific molecular mechanism of myocardial injury caused by iron overload in the heart is still unclear, and the involvement of ferroptosis in iron overload-induced myocardial injury is not fully understood. In this study, we observed that ferroptosis participated in developing of iron overload and I/R-induced cardiomyopathy. Mechanistically, we discovered that Parkin inhibited iron overload-induced ferroptosis in cardiomyocytes by promoting the ubiquitination of long-chain acyl-CoA synthetase 4 (ACSL4), a crucial protein involved in ferroptosis-related lipid metabolism pathways. Additionally, we identified p53 as a transcription factor that transcriptionally suppressed Parkin expression in iron-overloaded cardiomyocytes, thereby regulating iron overload-induced ferroptosis. In animal studies, cardiac-specific Parkin knockout mice (Myh6-CreER ^T2 /Parkin ^fl/fl ) fed a high-iron diet presented more severe myocardial damage, and the high iron levels exacerbated myocardial I/R injury. However, the ferroptosis inhibitor Fer-1 significantly suppressed iron overload-induced ferroptosis and myocardial I/R injury. Moreover, Parkin effectively protected against impaired mitochondrial function and prevented iron overload-induced mitochondrial lipid peroxidation. These findings unveil a novel regulatory pathway involving p53-Parkin-ACSL4 in heart disease by inhibiting of ferroptosis.

Lung cancer exhibits the highest incidence and mortality rates among cancers globally, with a five-year overall survival rate alarmingly below 20%. Targeting autophagy, though a controversial therapeutic strategy, is extensively employed in clinical practice. Current research is actively pursuing various therapeutic strategies using small molecules to exploit the dual function of autophagy. Nevertheless, the pivotal question of enhancing or inhibiting autophagy in cancer therapy merits further attention. This review aims to provide a comprehensive overview of the mechanisms of autophagy in lung cancer. It also explores recent advances in targeting cytotoxic autophagy and inhibiting protective autophagy with small molecules to induce cell death in lung cancer cells. Notably, most autophagy-targeting drugs, primarily natural small molecules, have demonstrated that activating cytotoxic autophagy effectively induces cell death in lung cancer, as opposed to inhibiting protective autophagy. These insights contribute to identifying druggable targets and drug candidates for potential autophagy-related lung cancer therapies, offering promising approaches to combat this disease.

Drug toxicity is closely related to both clinical drug safety and new drug development. Therefore, it is vital to understand the mechanisms of drug toxicity fully and to use appropriate research models with advanced technologies. Zebrafish has become an important vertebrate animal model for high-throughput drug screening and toxicity assessment. At the same time, zebrafish has an intact biological complexity, reflecting the whole organism's toxicity, which gives it an advantage over other high-throughput models in toxicity studies. Despite the gradual increase in toxicity studies utilizing zebrafish, a comprehensive and systematic review of the underlying mechanisms and new techniques is still lacking. This review aims to analyze common toxicity mechanisms in zebrafish models, such as oxidative stress, endoplasmic reticulum stress, inflammation, and apoptosis, and macroscopic changes in biological processes like lipid metabolism disorders and neurotransmitter expression abnormalities. It also introduces new technologies applied in toxicity assessment, such as gene editing, novel fluorescence imaging technology, 3D imaging technology, and novel automated technology for high-throughput screening, such as fish capsules. In addition, it also summarizes the advantages and disadvantages of the model. By doing so, it will provide new suggestions for the development and improvement of the model, make it better serve the toxicity study of clinical drugs and provide a more comprehensive perspective for drug toxicity study, thus promoting the development of the field of drug toxicity study.

With the growing awareness of public health, the value and importance of traditional Chinese medicine(TCM) resources have become increasingly prominent. Despite the undeniable significance of TCM in medical treatment and healthcare, the protection, development, and utilization of TCM resources still face numerous challenges. Under the traditional model, the development and utilization of TCM resources heavily rely on manual labor and empirical decision-making, which not only leads to inefficiencies and high costs but also causes serious issues such as unstable drug quality and imbalances in market supply and demand. In the current era of rapid advancements in artificial intelligence(AI) and technology, AI has emerged as a new engine to address many challenges and difficulties throughout the entire TCM resource industry chain. By leveraging AI technology, intelligent management, precise production, and optimized utilization of TCM resources can be achieved, thereby improving efficiency, reducing costs, ensuring stable quality, and balancing market supply and demand. This article primarily explores the application of AI technology in the entire TCM resource industry chain from different perspectives and provides an in-depth analysis of the future development of AI in the TCM industry. It holds significant importance and value in promoting the intelligent development of the TCM sector and facilitating the healthy development of the entire TCM resource industry chain.
Artificial Intelligence ; Medicine, Chinese Traditional/economics* ; Humans ; Drugs, Chinese Herbal/economics* ; Drug Industry

OBJECTIVES: To evaluate the application value of genetic newborn screening (gNBS) in the Yunnan region. METHODS: A prospective study was conducted with a random selection of 3 001 newborns born in the Yunnan region from February to December 2021. Traditional newborn screening (tNBS) was used to test biochemical indicators, and targeted next-generation sequencing was employed to screen 159 genes related to 156 diseases. Positive-screened newborns underwent validation and confirmation tests, and confirmed cases received standardized treatment and long-term follow-up. RESULTS: Among the 3 001 newborns, 166 (5.53%) were initially positive for genetic screening, and 1 435 (47.82%) were genetic carriers. The top ten genes with the highest variation frequency were GJB2 (21.29%), DUOX2 (7.27%), HBA (6.14%), GALC (3.63%), SLC12A3 (3.33%), HBB (3.03%), G6PD (2.94%), SLC25A13 (2.90%), PAH (2.73%), and UNC13D (2.68%). Among the initially positive newborns from tNBS and gNBS, 33 (1.10%) and 47 (1.57%) cases were confirmed, respectively. A total of 48 (1.60%) cases were confirmed using gNBS+tNBS. The receiver operating characteristic curve analysis demonstrated that the areas under the curve for tNBS, gNBS, and gNBS+tNBS in diagnosing diseases were 0.866, 0.982, and 0.968, respectively (P<0.05). DeLong's test showed that the area under the curve for gNBS and gNBS+tNBS was higher than that for tNBS (P<0.05). CONCLUSIONS gNBS can expand the range of disease detection, and its combined use with tNBS can significantly shorten diagnosis time, enabling early intervention and treatment.
Humans ; Infant, Newborn ; Neonatal Screening ; Genetic Testing ; Female ; Male ; Follow-Up Studies ; Prospective Studies ; China

To investigate the molecular mechanisms underlying the mechanosensitive ion channel PI-EZO2 in osteoarthritis(OA),we developed a lentiviral vector for endogenous PIEZO2 overexpression and established a stable PIEZO2-high-expressing immortalized human primary chondrocyte line.By map-ping the open reading frame of the PIEZO2 locus and designing sequence-specific sgRNA,we employed the CRISPR/Cas9 synergistic activation mediator(SAM)system to precisely integrate transcriptional ac-tivation elements into the PIEZO2 promoter region.Lentiviral-mediated targeted genomic integration en-sured endogenous PIEZO2 overexpression,confirmed by mCherry fluorescence tracing coupled with flow cytometric sorting,which revealed membrane-specific localization of PIEZO2 protein(localization effi-ciency:78.49％).Quantitative PCR demonstrated a 17-fold upregulation of PIEZO2 mRNA,while Western blotting validated enhanced membrane-localized protein expression.Strikingly,PIEZO2-overex-pressing chondrocytes exhibited hallmark OA metabolic phenotypes compared to wild-type controls:typeⅡ collagen mRNA expression decreased to 50％of baseline levels,whereas matrix metalloproteinase 13(MMP13)mRNA surged by 20-fold.These alterations recapitulated the pathological matrix metabolic phenotype observed in biomechanical OA models induced by cyclic mechanical stress(10％strain,0.5 Hz,8 h/day for 2 consecutive days).Collectively,we successfully generated a human chondrocyte model with stable PIEZO2 overexpression,which faithfully mirrors mechanotransduction-driven OA progression.This engineered cellular system provides a robust platform for dissecting PIEZO2-mediated mechanosig-naling networks and advancing targeted therapeutic discovery.