OBJECTIVE To explore clinical characteristics and risk factors of drug-induced hypofibrinogenemia， providing a reference for rational clinical drug use. METHODS Retrospective case analyses literature on drug-induced hypofibrinogenemia were collected from domestic and international databases from their inception to December 31， 2024. The patients’ gender， age， fibrinogen （FIB） levels before and after treatment， drug types， the incidence of drug-induced hypofibrinogenemia， time of occurrence， bleeding rates， clinical manifestations， risk factors， and protective factors were all analyzed. RESULTS A total of 40 retrospective case analysis studies were included， involving 17 313 patients. Patient age ranged from 0.83 to 78.40 years， with males accounting for 16.90%-81.00%. The involved drugs comprised 5 categories and 13 specific agents， including tigecycline， snake venom hemocoagulase， tocilizumab， and alteplase， etc. The incidence of drug-induced hypofibrinogenemia ranged from 0 to 100%， occurring between 2 hours and 9 months after drug administration， and FIB levels rebounded in most patients after drug discontinuation. The bleeding rate varied from 0% to 91.30%， including epistaxis， airway bleeding， gastrointestinal bleeding， and cerebral hemorrhage. Risk factors included high drug dosage， prolonged treatment duration， abdominal infection， advanced age， and low baseline FIB levels. Protective factors were only mentioned in studies on tigecycline， including skin and soft tissue infections and high baseline FIB levels. CONCLUSIONS Drug-induced hypofibrinogenemia is commonly associated with tigecycline， hemocoagulase， and tocilizumab. Its clinical features vary depending on the drug， and risk factors include high drug dosage， prolonged treatment， low baseline FIB levels， and advanced age. For high-risk medications， individualized medication management and monitoring of FIB levels are recommended.

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.

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

OBJECTIVE: To investigate the effect of innovative perioperative pain management on prostate cancer patients with hematuria undergoing prostatic artery embolization (PAE). METHODS: A total of 60 patients undergoing PAE in the Interventional Therapy Department of General Hospital of Eastern Theater Command from May 2024 to January 2025 were selected by convenience sampling method and randomly divided into the intervention group and the control group, with 30 patients in each group. The control group received traditional pain management of nursing. An innovative perioperative pain management was performed in intervention group including preoperative "body-mind-pain" holistic assessment and preparation, intraoperative humanistic care and real-time support, postoperative multimodal analgesia and rehabilitation, dynamic monitoring and closed-loop feedback. The pain degree after 6 hours, 1 day, 3 days and 1 week of the operation, and the quality of life after 1 week of operation, as well as nursing satisfaction at discharge were compared between the two groups. RESULTS: The VAS scores of the intervention group were significantly lower than those of the control group after 6 hours, 1 day, 3 days and 1 week of operation (P<0.05). One week after the operation, the quality of life in the observation group was higher than that of the control group significantly (P<0.05). The nursing satisfaction of the observation group was significantly higher than that of the control group at discharge(P<0.05). CONCLUSION The application of innovative perioperative pain management can alleviate pain of patients with PAE, which improves the quality of life and nursing satisfaction of patients, and is conducive to the rehabilitation of patients.
Humans ; Male ; Embolization, Therapeutic ; Hematuria/therapy* ; Prostatic Neoplasms/surgery* ; Pain Management/methods* ; Quality of Life ; Prostate/blood supply* ; Perioperative Care ; Pain, Postoperative ; Middle Aged ; Aged ; Pain Measurement

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.

Physiologically based pharmacokinetic (PBPK) models have been widely used to predict various stages of drug absorption, distribution, metabolism and excretion. Models based on machine learning (ML) and artificial intelligence (AI) can provide better ideas for the construction of PBPK models, which can accelerate the prediction speed and improve the prediction quality of PBPK. ML and AL can complement the advantages of PBPK model to accelerate the progress of drug research and development. This review introduces the application of machine learning and artificial intelligence in pharmacokinetics, summarizes the research progress of physiological pharmacokinetic models based on machine learning and artificial intelligence, and analyzes the limitations of machine learning and artificial intelligence applications and their application prospects and prospects.

As a novel iron-dependent form of cell death, ferroptosis is characterized by the excessive accumulation of phospholipids containing polyunsaturated fatty acids (PUFA) on the cell membrane and peroxidation. Lipid droplets are always in the dynamic transition of generation and decomposition, play a central role in regulating lipid metabolism, and are always in the dynamic transition of generation and decomposition. Lipid droplet metabolism is closely related to the occurrence of ferroptosis and plays an important role in the disease caused by ferroptosis. This review firstly focuses on the lipid droplet metabolism process and its effects on the storage and release of PUFA, and further elucidates the regulatory mechanism and key regulatory proteins of lipid drop metabolism on ferroptosis, in order to reveal the intrinsic relationship between lipid droplets and ferroptosis, and provide a new strategy for disease prevention and treatment.