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.

IgA nephropathy (IgAN) is the most common primary glomerulonephritis worldwide and a major cause of chronic kidney disease and kidney failure. IgAN exhibits marked heterogeneity in clinical presentation, histopathology, and pathogenic mechanisms, contributing to variable treatment responses and prognosisamong patients. Precise risk assessment and individualized intervention are therefore of critical importance. This review systematically traces the evolution of IgAN management from traditional risk stratification toward biomarker-driven precision medicine. We first review the clinical utility and limitations of established risk stratification tools, including the KDIGO guidelines, the Oxford MEST-C classification, and the International IgAN Prediction Tool. We then discuss emerging biomarkers closely linked to disease pathogenesis, including galactose-deficient IgA1 (Gd-IgA1), anti-Gd-IgA1 autoantibodies, B cell activating factor (BAFF), a proliferation-inducing ligand (APRIL), and complement components, as well as the targeted therapies they have informed. In addition, urinary biomarkers and multi-omics approaches show promise for dynamic disease monitoring and individualized risk stratification.

Metabolic dysfunction-associated steatotic liver disease (MASLD) has become the most prevalent chronic liver disease worldwide, affecting approximately 32%-38% of the adult population and posing a growing public health burden. MASLD represents a continuous disease spectrum ranging from simple steatosis to metabolic dysfunction-associated steatohepatitis (MASH), progressive hepatic fibrosis, cirrhosis, and ultimately hepatocellular carcinoma (HCC). The pathological core of MASLD lies in disruption of hepatic lipid metabolic homeostasis, characterized by an imbalance among de novo lipogenesis, fatty acid β-oxidation, and very-low-density lipoprotein (VLDL)-mediated lipid export. This metabolic disequilibrium subsequently drives inflammatory injury and fibrotic progression. Among the multiple regulatory pathways involved, thyroid hormone (TH) signaling has emerged as a central regulator of hepatic metabolic homeostasis. The liver is a major peripheral target organ of TH action, where TH predominantly exerts its metabolic effects through thyroid hormone receptor β (TRβ). Large-scale epidemiological studies and meta-analyses have demonstrated that hypothyroidism is significantly associated with increased MASLD prevalence, more severe histological injury, and advanced hepatic fibrosis, suggesting that dysregulation of TH signaling may participate throughout the entire MASLD disease spectrum. At the molecular level, TH regulates hepatic lipid metabolism by coordinating suppression of lipogenesis, enhancement of mitochondrial fatty acid oxidation, and promotion of VLDL assembly and secretion through integrated genomic actions of the T3-TRβ axis and non-genomic signaling pathways. Across different stages of MASLD, TH signaling exerts stage-dependent protective effects. In the steatosis stage, TH improves metabolic flexibility by modulating insulin sensitivity, glucose metabolism, and lipid droplet clearance, thereby alleviating early lipotoxic stress. During progression to MASH, TH attenuates inflammatory amplification by improving mitochondrial homeostasis, suppressing activation of the NOD-like receptor family pyrin domain containing 3 (NLRP3) inflammasome, and modulating the gut-liver axis microenvironment. In advanced stages, TH signaling influences hepatic stellate cell activation and extracellular matrix deposition, partly through interaction with the transforming growth factor-β (TGF-β)/SMAD pathway, while alterations in intrahepatic TH availability, mediated by dynamic changes in iodothyronine deiodinase 1 (DIO1), contribute to fibrosis progression and hepatocellular dedifferentiation. In hepatocellular carcinoma, coordinated downregulation of TRβ and DIO1 establishes a tumor-associated hypothyroid state that promotes metabolic reprogramming and tumor progression. The clinical relevance of TH signaling in MASLD has been underscored by the recent approval of Resmetirom, a liver-targeted TRβ‑selective agonist, for the treatment of non-cirrhotic MASH with moderate-to-severe fibrosis (F2-F3). This approval represents a landmark transition from mechanistic understanding to metabolism-centered precision therapy in MASLD. Clinical trials have demonstrated that Resmetirom not only improves key histological endpoints, including MASH resolution and fibrosis regression, but also favorably modulates atherogenic lipid profiles, highlighting the therapeutic potential of selectively targeting hepatic TH pathways. This review systematically summarizes the multidimensional regulatory roles of TH across the MASLD disease spectrum and discusses emerging diagnostic and therapeutic implications of TH-based interventions, aiming to inform future mechanistic research and optimize clinical management strategies.

OBJECTIVE To construct an intelligent pharmaceutical Q&A platform for precision medication with low “artificial intelligence （AI） hallucination”， aiming to enhance the accuracy， consistency， and traceability of medication consultations. METHODS Medication package inserts were batch-processed and converted into structured data through Python programming to build a local pharmaceutical knowledge base. The retrieval and question-answering processes were designed based on large language models， and system integration and localized deployment were completed on Dify platform. By designing typical clinical medication questions and comparing the output of the intelligent pharmaceutical Q&A platform with the online version of DeepSeek across dimensions such as peak time retrieval， half-life， and dosage adjustment reasoning for patients with renal impairment， the accuracy and reliability of its retrieval and reasoning results were evaluated. RESULTS The intelligent pharmaceutical Q&A platform， constructed based on local drug package inserts， achieved 100% accuracy in retrieval and reasoning for peak time， half-life， and dosage adjustment schemes. In comparison， the online version of DeepSeek demonstrated accuracies of 30%（6/20）， 50%（10/20）， and 38%（23/60） across these three dimensions， respectively. CONCLUSIONS The constructed intelligent pharmaceutical Q&A platform is capable of accurately retrieving and extracting information from the local knowledge base based on clinical inquiries， thereby avoiding the occurrence of AI hallucinations and providing reliable medication decision support for healthcare professionals.

ObjectiveTo investigate the mechanism of modified Si Junzitang and Shashen Maidong Tang ［Yiqi Yangyin Jiedu prescription （YQYYJD）］ in enhancing the sensitivity of cisplatin in epidermal growth factor receptor tyrosine kinase inhibitor （EGFR-TKI）-resistant lung adenocarcinoma cells based on aerobic glycolysis. MethodsThe effects of different concentrations of YQYYJD （0， 2， 3， 4， 5， 6， 7， 8 g·L^-1） and cisplatin （0， 3， 6， 9， 12， 15， 18， 21， 24， 27 mg·L^-1） on the proliferation and activity of PC9/GR cells were detected by the cell counting kit-8 （CCK-8） assay after 24 hours of intervention. The half-maximal inhibitory concentration （IC₅₀） for PC9/GR cells was calculated to determine the concentrations used in subsequent experiments. PC9/GR cells were divided into blank group （complete medium）， YQYYJD group （5 g·L^-1）， cisplatin group （12 mg·L^-1）， and combined group （YQYYJD 5 g·L^-1 + cisplatin 12 mg·L^-1）. After 24 hours of intervention， cell viability was measured using CCK-8 assay. Cell proliferation was assessed by colony formation assay， and cell migration was evaluated by scratch and Transwell assays. Glucose consumption， lactate production， and adenosine triphosphate （ATP） levels were measured by colorimetric assays. The expression levels of glycolysis-related proteins， including hexokinase 2 （HK2）， phosphofructokinase P （PFKP）， pyruvate kinase M2 （PKM2）， lactate dehydrogenase A （LDHA）， glucose transporter 1 （GLUT1）， and monocarboxylate transporter 4 （MCT4）， were determined by Western blot. ResultsBoth YQYYJD and cisplatin inhibited the viability of PC9/GR cells in a concentration-dependent manner. The IC₅₀ of PC9/GR cells for YQYYJD and cisplatin were 5.15 g·L^-1 and 12.91 mg·L^-1， respectively. In terms of cell proliferation， compared with the blank group， the cell survival rate and the number of colonies formed in the YQYYJD group， cisplatin group， and combined group were significantly decreased （P<0.01）. Compared with the YQYYJD and cisplatin groups， the combined group showed a further significant reduction in cell survival rate and colony formation （P<0.01）. In terms of cell migration， compared with the blank group， the cell migration rate and the number of cells passing through the Transwell membrane in the YQYYJD group， cisplatin group， and combined group were significantly decreased （P<0.01）. Compared with the YQYYJD and cisplatin groups， the combined group exhibited a further significant reduction in cell migration rate and the number of cells passing through the Transwell membrane （P<0.01）. In terms of glycolysis， compared with the blank group， glucose consumption， lactate production， and ATP levels in the YQYYJD group， cisplatin group， and combined group were significantly decreased （P<0.01）. Compared with the YQYYJD and cisplatin groups， the combined group showed a further significant reduction in glucose consumption， lactate production， and ATP levels （P<0.05）. Compared with the blank group， the protein expression levels of HK2， PFKP， PKM2， and LDHA in the YQYYJD， cisplatin， and combined groups were significantly decreased （P<0.01）. The combined group showed a further significant reduction in the expression levels of these proteins compared with the YQYYJD and cisplatin groups （P<0.01）. No significant differences were observed in the protein expression levels of GLUT1 and MCT4 among the groups. ConclusionYQYYJD can synergistically inhibit the proliferation and migration of PC9/GR cells and enhance their sensitivity to cisplatin. The mechanism may be related to the downregulation of the expression of glycolysis-related rate-limiting enzymes， including HK2， PFKP， PKM2， and LDHA， thereby inhibiting glycolysis.

ObjectiveTo establish a model that can quickly identify the aroma components in different parts of Nardostachys jatamansi， so as to provide a quality control basis for the market circulation and clinical use of N. jatamansi. MethodsHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） combined with Smart aroma database and National Institute of Standards and Technology（NIST） database were used to characterize the aroma components in different parts of N. jatamansi， and the aroma components were quantified according to relative response factor（RRF） and three internal standards， and the markers of aroma differences in different parts of N. jatamansi were identified by orthogonal partial least squares-discriminant analysis（OPLS-DA） and cluster thermal analysis based on variable importance in the projection（VIP） value >1 and P<0.01. The odor data of different parts of N. jatamansi were collected by Heracles Ⅱ Neo ultra-fast gas phase electronic nose， and the correlation between compound types of aroma components collected by the ultra-fast gas phase electronic nose and the detection results of HS-SPME-GC-MS was investigated by drawing odor fingerprints and odor response radargrams. Chromatographic peak information with distinguishing ability≥0.700 and peak area≥200 was selected as sensor data， and the rapid identification model of different parts of N. jatamansi was established by principal component analysis（PCA）， discriminant factor alysis（DFA）， soft independent modeling of class analogies（SIMCA） and statistical quality control analysis（SQCA）. ResultsThe HS-SPME-GC-MS results showed that there were 28 common components in the underground and aboveground parts of N. jatamansi， of which 22 could be quantified and 12 significantly different components were screened out. Among these 12 components， the contents of five components（ethyl isovalerate， 2-pentylfuran， benzyl alcohol， nonanal and glacial acetic acid，） in the aboveground part of N. jatamansi were significantly higher than those in the underground part（P<0.01）， the contents of β-ionone， patchouli alcohol， α-caryophyllene， linalyl butyrate， valencene， 1，8-cineole and p-cymene in the underground part of N. jatamansi were significantly higher than those in the aboveground part（P<0.01）. Heracles Ⅱ Neo electronic nose results showed that the PCA discrimination index of the underground and aboveground parts of N. jatamansi was 82， and the contribution rates of the principal component factors were 99.94% and 99.89% when 2 and 3 principal components were extracted， respectively. The contribution rate of the discriminant factor 1 of the DFA model constructed on the basis of PCA was 100%， the validation score of the SIMCA model for discrimination of the two parts was 99， and SQCA could clearly distinguish different parts of N. jatamansi. ConclusionHS-SPME-GC-MS can clarify the differential markers of underground and aboveground parts of N. jatamansi. The four analytical models provided by Heracles Ⅱ Neo electronic nose（PCA， DFA， SIMCA and SQCA） can realize the rapid identification of different parts of N. jatamansi. Combining the two results， it is speculated that terpenes and carboxylic acids may be the main factors contributing to the difference in aroma between the underground and aboveground parts of N. jatamansi.

Objective:To establish a preliminary performance validation protocol for the bioinformatics procedure of metagenomic next-generation sequencing (mNGS) in clinical laboratories.Methods:Three types of simulated datasets were designed and the CatⅠ dataset mainly consisted of pathogen reference genomes and human sequences. CatⅠA was a dataset composed of common pathogens mixed with human sequences and was used to evaluate the inclusiveness, accuracy, recall rates, precision, F1-Score, and other indicators of the mNGS bioinformatics procedure. CatⅠB was a dataset composed of closely related species of common pathogens mixed with human sequences, which was used to evaluate the discriminating ability of closely related species of bioinformatics procedure by calculating the detection rates and the relative abundance ratio of closely related species. The real data of 200 clinical samples was selected to construct CatⅡ and the simulated dataset consisted of colonized bacteria, experimental environment bacteria, reagent engineering bacteria, pathogen reference genomes, and human sequences, which was used to evaluate the sensitivity, specificity, and accuracy of bioinformatics pipeline for pathogens detection. The CatⅢ dataset was obtained from the negative bronchoalveolar lavage fluid BALF sequencing data mixed with 20 rare pathogens sequences in order to evaluate the positive detection rates and recall rates of rare pathogens in the bioinformatics analysis.Results:The analysis of the CatⅠA dataset showed that the positive consistency rate, inclusiveness, precision and accuracy of the bioinformatics peocedure under three sequence gradients were all greater than 99%, with a recall rate of 72.31% (95% CI 69.61%-75.01%) and a F1 Score of 82.00% (95% CI 79.77%-84.22%). In the CatⅠB dataset, the closely related species could be effectively detected at all sequence and proportion gradients, and the relative abundance ratio of closely related species was within 2 times of the design ratio except for the coronavirus, haemophilus, primate bocaparvovirus, human respiratory syncytial virus, and eimeria, indicating good ability to identify the closely related species. All the 24 species of pathogens included in CatⅡ dataset were effectively detected, with the sensitivity, specificity, and accuracy all greater than 90%. All rare pathogens were detected in the CatⅢ dataset, with a detection rate of 100%. Conclusions:With the simulated datasets, the performance validation scheme for the mNGS bioinformatics analysis was preliminary established and could evaluate the accuracy of sequence classification, the ability to identify the closely related species, and detection ability of common and rare pathogens, which may provide some references for the construction of mNGS process.

Objective:To analyze the human immunodeficiency virus (HIV) screening status and the resulting residual risk (RR) among blood donors across 17 provincial blood centers in China.Methods:This study used a cross-sectional study. Data on HIV infection markers per 100 000 first-time donors (FD) and repeat donors (RD) from January 2015 to December 2024 were extracted from the National Blood Establishment Performance Comparison Information Management System. Questionnaires were used to collect each center′s HIV screening strategy, algorithm, serological test (ST) kit manufacturers, gray-zone setting for ST, and nucleic acid test (NAT) modality, method, and platform. The incidence-window-period model was used to calculate the residual risk for first-time donors (RR FD), repeat donors (RR RD), and total donors (RR TD) at each center. Horizontal and vertical analysis of RR FD, RR RD, and RR TD across centers and years were performed. Results:All 17 centers applied the same HIV screening strategy which was two rounds of ST followed by one round of NAT. Eight of them operated a single screening algorithm, six employed two algorithms and three used three. Eleven centers used both imported and domestic ST kits, five relied on domestic ST kits only, and one used imported ST kits only, while four centers never set a grey zone for ST throughout the decade. For NAT modalities, eight centers adopted both individual nucleic acid test (ID-NAT) and minipool nucleic acid test (MP-NAT), eight used MP-NAT only and one used ID-NAT only. Seven centers combined transcription mediated amplification (TMA) and polymerase chain reaction (PCR), nine used PCR only and one used TMA only, and fourteen centers ran both imported and domestic NAT systems, two used imported systems only and one used a domestic system only. Over the ten-year period, the mean RR FD across the centers ranged from 2.22 to 12.33 per 10 6 person-years, RR RD from 0.83 to 3.29 per 10 6 person-years and RR TD from 1.59 to 9.29 per 10 6 person-years, with center Z4 consistently showing the lowest values for all three metrics and center U4 recording the highest RR FD and RR TD, while center D2 had the highest RR RD. In 2024 compared with 2015, eleven centers achieved a lower RR FD and ten centers achieved lower RR RD and RR TD. The RR FD and RR TD of centers W2 and U4 displayed pronounced fluctuations and an upward trend in recent years. Conclusions:The 17 provincial blood centers maintain consistent HIV screening strategies, while demonstrating variations in screening algorithm, ST kit manufacturers, NAT modalities, methods, and platform. And the RR FD, RR RD, and RR TD differ across centers. Although most centers show declining trend in RR over the ten-year period, some centers exhibite data fluctuations with a rising trend, suggesting potential for further optimization of HIV screening protocols.

Kinesiophobia is prevalent among school-aged children with asthma,and severe kinesiophobia can hinder their participation in physical activities and disease control,adversely affecting their physical and mental health.This paper reviews the concept,development,assessment tools,influencing factors,and intervention strategies of kinesiophobia in school-aged children with asthma,analyzes existing challenges,and proposes directions for future research.It aims to provide insights for developing scientific and personalized intervention plans to enhance children's exercise levels and improve their quality of life.

Hepatocellular carcinoma(HCC)expresses abundant glycolytic enzymes and displays comprehensive glucose metabolism reprogramming.Aldolase A(ALDOA)plays a prominent role in glycolysis;however,little is known about its role in HCC development.In the present study,we aim to explore how ALDOA is involved in HCC proliferation.HCC proliferation was markedly suppressed both in vitro and in vivo following ALDOA knockout,which is consistent with ALDOA overexpression encouraging HCC prolifera-tion.Mechanistically,ALDOA knockout partially limits the glycolytic flux in HCC cells.Meanwhile,ALDOA translocated to nuclei and directly interacted with c-Jun to facilitate its Thr93 phosphorylation by P21-activated protein kinase;ALDOA knockout markedly diminished c-Jun Thr93 phosphorylation and then dampened c-Jun transcription function.A crucial site Y364 mutation in ALDOA disrupted its interaction with c-Jun,and Y364S ALDOA expression failed to rescue cell proliferation in ALDOA deletion cells.In HCC patients,the expression level of ALDOA was correlated with the phosphorylation level of c-Jun(Thr93)and poor prognosis.Remarkably,hepatic ALDOA was significantly upregulated in the promotion and progression stages of diethylnitrosamine-induced HCC models,and the knockdown of Aldoa strikingly decreased HCC development in vivo.Our study demonstrated that ALDOA is a vital driver for HCC development by activating c-Jun-mediated oncogene transcription,opening additional avenues for anti-cancer therapies.