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.

OBJECTIVE To investigate the clinical characteristics and risk factors for batroxobin-related severe hypofibrinogenemia （HFIB） and construct a risk prediction model. METHODS A retrospective analysis was conducted on inpatients treated with batroxobin in the First Medical Center of a tertiary hospital from January 1， 2020， to December 31， 2024. Patients were categorized into non-severe HFIB group and severe HFIB group based on the severity of HFIB. Univariate and multivariate Logistic regression analyses were performed to identify the independent influencing factors for batroxobin-related severe HFIB. A nomogram was developed using the “rms” package in R 4.5 software. The predictive performance of the model was evaluated using the receiver operating characteristic curve. Calibration was assessed via the Bootstrap resampling method， and goodness-of-fit was evaluated with the Hosmer-Lemeshow test. RESULTS A total of 1 472 patients were included in this study. Of these， 1 445 developed HFIB， yi elding an incidence of 98.17%. Furthermore， 895 were classified as severe HFIB， accounting for 60.80% of the cohort. Multivariate Logistic regression analysis showed that increased age， high initial dose per 10 kg body weight， use of maintenance dose， and concomitant glucocorticoid use were independent risk factors for batroxobin-related severe HFIB， while high baseline fibrinogen （FIB） level was identified as a protective factor. The model demonstrated an area under the curve of 0.760 （95% CI： 0.735-0.785）. The mean absolute error of the calibration curve was 0.006. The P value of the Hosmer-Lemeshow test was 0.609. CONCLUSIONS Batroxobin can rapidly and significantly reduce FIB levels and carries a risk of inducing severe HFIB. Patients with advanced age， high initial dose per 10 kg body weight， use of maintenance dose and concomitant glucocorticoid use had a higher risk of batroxobin-related severe HFIB， while high baseline FIB level had a lower risk of batroxobin-related severe HFIB. The risk prediction model developed based on these factors can be used to predict the likelihood of batroxobin-related severe HFIB.

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.

ObjectiveBy comparing the composition and content of volatile components in raw products， wine-washed products and wine-fried products of Ligusticum sinense cv. Chaxiong rhizome（LSCR）， to investigate the influence of wine processing on the volatile components of LSCR， in order to provide a basis for the development of quality standards for LSCR and its processed products. MethodsElectronic nose was used to identify the odors of LSCR， wine-washed and wine-fried LSCR， and their volatile components were detected by headspace gas chromatography-mass spectrometry（HS-GC-MS）， and the relative mass fractions of these components were determined by peak area normalization method. Principal component analysis（PCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA） were performed on the obtained sample data by SIMCA 14.1 software， and the differential components of LSCR， wine-washed and wine-fried LSCR were screened according to the variable importance in the projection（VIP） value>1. Pearson correlation analysis was used to explore the relationship between volatile differential flavor components and electronic nose sensors. ResultsElectronic nose detection results showed that there were significant differences in the odors of LSCR， wine-washed and wine-fried LSCR， mainly reflected in the sensors S2， S4， S5， S6， S11， S12， S13. And a total of 62 compounds were identified from LSCR and its wine-processed products， among which 46， 50 and 51 compounds were identified from LSCR， wine-fried and wine-washed LSCR， respectively. There were 21 differential components between the raw products and wine-fried products， of which 10 components were increased and 11 were decreased after processing. There were 20 differential components between the raw products and wine-washed products， of which 11 constituents increased and 9 decreased after processing. There were 17 differential components between the wine-wash products and wine-fried products. Compared with the wine-washed products， the contents of 13 components in the wine-fried products increased， and the contents of 4 components decreased. The increasing trend of the content of phthalides in the wine-washed products was more obvious than that in the wine-fried products， but the content of total volatile components was higher in the wine-fried products than the wine-washed products. Correlation analysis showed that there were different degrees of correlation between the 7 differential sensors of electronic nose and 24 differential volatile components， mainly phthalides and olefins. ConclusionThe odor and the content of volatile components in LSCR changed obviously after wine processing， and n-butylphthalide， Z-butylidenephthalide and E-ligustilide can be used as the candidate differential markers of volatile components in LSCR before and after wine processing.

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 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.

In the central nervous system (CNS), the myelin sheath, a specialized membrane structure that wraps around axons, is formed by oligodendrocytes through a highly coordinated spatiotemporal developmental program. The process begins with the directed differentiation of neural precursor cells into oligodendrocyte precursor cells (OPCs), followed by their migration, proliferation, differentiation, and maturation, ultimately leading to the formation of a multi-segmental myelin sheath structure. Recent single-cell sequencing research has revealed that this process involves the temporal regulation of over 200 key genes, with a regulatory network composed of transcription factors such as Sox10 and Olig2 playing a central role. The primary function of the myelin sheath is to accelerate nerve signal transmission and protect nerve fibers from damage. Its insulating properties not only increase nerve conduction speed by 50-100 times but also ensure the long-term functional integrity of the nervous system by maintaining axonal metabolic homeostasis and providing mechanical protection. The pathological effects of myelin sheath injury exhibit a cascade amplification pattern: acute demyelination leads to action potential conduction block, while chronic lesions may cause axonal damage and neuronal death in severe or long-term cases, ultimately resulting in irreversible neurological dysfunction with neurodegenerative characteristics. Multiple sclerosis (MS) is a neurodegenerative disease characterized by chronic inflammatory demyelination of the CNS. Clinically, the distribution of lesions in MS exhibits spatial heterogeneity, which is closely related to differences in the regenerative capacity of oligodendrocytes within the local microenvironment. Emerging evidence suggests that astrocytes form a dynamic “neural-immune-metabolic interface” and play a multidimensional regulatory role in myelin development and regeneration by forming heterogeneous populations composed of different subtypes. During embryonic development, astrocytes induce the targeted differentiation of OPCs in the ventricular region through the Wnt/β-catenin pathway. In the mature stage, they secrete platelet-derived growth factor AA (PDGF-AA) to establish a chemical gradient that guides the precise migration of OPCs along axonal bundles. Notably, astrocytes also provide crucial metabolic support by supplying energy substrates for high-energy myelin formation through the lactate shuttle mechanism. In addition, astrocytes play a dual role in myelin regulation. During the acute injury phase, reactive astrocytes establish a triple defense system within 72 h: upregulating glial fibrillary acidic protein (GFAP) to form scars that isolate lesions, activating the JAK-STAT3 regeneration pathway in oligodendrocytes via leukemia inhibitory factor (LIF), and releasing tumor necrosis factor-stimulated gene-6 (TSG-6) to inhibit excessive microglial activation. However, in chronic neurodegenerative diseases, the phenotypic transformation of astrocytes contributes to microenvironmental deterioration. The secretion of chondroitin sulfate proteoglycans (CSPGs) inhibits OPC migration via the RhoA/ROCK pathway, while the persistent release of reactive oxygen species (ROS) leads to mitochondrial dysfunction and the upregulation of complement C3-mediated synaptic pruning. This article reviews the mechanisms by which astrocytes regulate the development and regeneration of myelin sheaths in the CNS, with a focus on analyzing the multifaceted roles of astrocytes in this process. It emphasizes that astrocytes serve as central hubs in maintaining myelin homeostasis by establishing a metabolic microenvironment and signaling network, aiming to provide new therapeutic strategies for neurodegenerative diseases such as multiple sclerosis.

ObjectiveThe aim of this study was to investigate the prophylactic effects of caloric restriction (CR) on lipopolysaccharide (LPS)-induced septic cardiomyopathy (SCM) and to elucidate the mechanisms underlying the cardioprotective actions of CR. This research aims to provide innovative strategies and theoretical support for the prevention of SCM. MethodsA total of forty-eight 8-week-old male C57BL/6 mice, weighing between 20-25 g, were randomly assigned to 4 distinct groups, each consisting of 12 mice. The groups were designated as follows: CON (control), LPS, CR, and CR+LPS. Prior to the initiation of the CR protocol, the CR and CR+LPS groups underwent a 2-week acclimatization period during which individual food consumption was measured. The initial week of CR intervention was set at 80% of the baseline intake, followed by a reduction to 60% for the subsequent 5 weeks. After 6-week CR intervention, all 4 groups received an intraperitoneal injection of either normal saline or LPS (10 mg/kg). Twelve hours post-injection, heart function was assessed, and subsequently, heart and blood samples were collected. Serum inflammatory markers were quantified using enzyme-linked immunosorbent assay (ELISA). The serum myocardial enzyme spectrum was analyzed using an automated biochemical instrument. Myocardial tissue sections underwent hematoxylin and eosin (HE) staining and immunofluorescence (IF) staining. Western blot analysis was used to detect the expression of protein in myocardial tissue, including inflammatory markers (TNF-α, IL-9, IL-18), oxidative stress markers (iNOS, SOD2), pro-apoptotic markers (Bax/Bcl-2 ratio, CASP3), and SIRT3/SIRT6. ResultsTwelve hours after LPS injection, there was a significant decrease in ejection fraction (EF) and fractional shortening (FS) ratios, along with a notable increase in left ventricular end-systolic diameter (LVESD). Morphological and serum indicators (AST, LDH, CK, and CK-MB) indicated that LPS injection could induce myocardial structural disorders and myocardial injury. Furthermore, 6-week CR effectively prevented the myocardial injury. LPS injection also significantly increased the circulating inflammatory levels (IL-1β, TNF-α) in mice. IF and Western blot analyses revealed that LPS injection significantly up-regulating the expression of inflammatory-related proteins (TNF-α, IL-9, IL-18), oxidative stress-related proteins (iNOS, SOD2) and apoptotic proteins (Bax/Bcl-2 ratio, CASP3) in myocardial tissue. 6-week CR intervention significantly reduced circulating inflammatory levels and downregulated the expression of inflammatory, oxidative stress-related proteins and pro-apoptotic level in myocardial tissue. Additionally, LPS injection significantly downregulated the expression of SIRT3 and SIRT6 proteins in myocardial tissue, and CR intervention could restore the expression of SIRT3 proteins. ConclusionA 6-week CR could prevent LPS-induced septic cardiomyopathy, including cardiac function decline, myocardial structural damage, inflammation, oxidative stress, and apoptosis. The mechanism may be associated with the regulation of SIRT3 expression in myocardial tissue.

This study aims to explore the mechanism of Jiaotai Pills in treating depression based on metabolomics and network pharmacology. The chemical constituents of Jiaotai Pills were identified by UHPLC-Orbitrap Exploris 480, and the targets of Jiaotai Pills and depression were retrieved from online databases. STRING and Cytoscape 3.7.2 were used to construct the protein-protein interaction network of core targets of Jiaotai Pills in treating depression and the "compound-target-pathway" network. DAVID was used for Gene Ontology(GO) function and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analyses of the core targets. The mouse model of depression was established with chronic unpredictable mild stress(CUMS) and treated with different doses of Jiaotai Pills. The behavioral changes and pathological changes in the hippocampus were observed. UHPLC-Orbitrap Exploris 120 was used for metabolic profiling of the serum, from which the differential metabolites and related metabolic pathways were screened. A "metabolite-reaction-enzyme-gene" network was constructed for the integrated analysis of metabolomics and network pharmacology. A total of 34 chemical components of Jiaotai Pills were identified, and 143 core targets of Jiaotai Pills in treating depression were predicted, which were mainly involved in the arginine and proline, sphingolipid, and neurotrophin metabolism signaling pathways. The results of animal experiments showed that Jiaotai Pills alleviated the depression behaviors and pathological changes in the hippocampus of the mouse model of CUMS-induced depression. In addition, Jiaotai Pills reversed the levels of 32 metabolites involved in various pathways such as arginine and proline metabolism, sphingolipid metabolism, and porphyrin metabolism in the serum of model mice. The integrated analysis showed that arginine and proline metabolism, cysteine and methionine metabolism, and porphyrin metabolism might be the key pathways in the treatment of depression with Jiaotai Pills. In conclusion, metabolomics combined with network pharmacology clarifies the antidepressant mechanism of Jiaotai Pills, which may provide a basis for the clinical application of Jiaotai Pills in treating depression.
Animals ; Drugs, Chinese Herbal/chemistry* ; Depression/genetics* ; Mice ; Network Pharmacology ; Metabolomics ; Male ; Disease Models, Animal ; Humans ; Protein Interaction Maps/drug effects* ; Antidepressive Agents

The chemical constituents were systematically separated from the roots of Berberis polyantha by various chromatographic methods, including silica gel column chromatography, HP20 column chromatography, polyamide column chromatography, reversed-phase C_(18) column chromatography, and preparative high-performance liquid chromatography. The structures of the compounds were identified by physicochemical properties and spectroscopic techniques(1D NMR, 2D NMR, UV, MS, and CD). Four phenylpropanoids were isolated from the methanol extract of the roots of B. polyantha, and they were identified as(2R)-1-(4-hydroxy-3,5-dimethoxyphenyl)-1-propanone-O-β-D-glucopyranoside(1), methyl 4-hydroxy-3,5-dimethoxybenzoate(2),(+)-syringaresinol(3), and syringaresinol-4-O-β-D-glucopyranoside(4). Compound 1 was a new compound, and other compounds were isolated from this plant for the first time. The anti-inflammatory activity of these compounds was evaluated based on the release of nitric oxide(NO) in the culture of lipopolysaccharide(LPS)-induced RAW264.7 macrophages. At a concentration of 10 μmol·L~(-1), all the four compounds inhibited the LPS-induced release of NO in RAW264.7 cells, demonstrating potential anti-inflammatory properties.
Plant Roots/chemistry* ; Animals ; Mice ; Berberis/chemistry* ; RAW 264.7 Cells ; Macrophages/immunology* ; Drugs, Chinese Herbal/isolation & purification* ; Nitric Oxide/metabolism* ; Molecular Structure ; Anti-Inflammatory Agents/isolation & purification*