In order to investigate whether the effect of Yuxuebi Tablets on the peripheral and central inflammation resolution of mice with inflammatory pain is related to their regulation of G protein-coupled receptor 37(GPR37), an inflammatory pain model was established by injecting complete Freund's adjuvant(CFA) into the paws of mice, with a sham-operated group receiving a similar volume of normal saline. The mice were assigned randomly to the sham-operated group, model group, ibuprofen group(91 mg·kg~(-1)), and low-, medium-, and high-dose groups of Yuxuebi Tablets(60, 120, and 240 mg·kg~(-1)). The drug was administered orally from days 1 to 19 after modeling. Von Frey method and the hot plate test were used to detect mechanical pain thresholds and heat hyperalgesia. The levels of interleukin-10(IL-10) and transforming growth factor-beta(TGF-β) in the spinal cord were quantified using enzyme-linked immunosorbent assay(ELISA), and the mRNA and protein expression of GPR37 in the spinal cord was measured by real-time quantitative reverse transcription PCR(qRT-PCR) and Western blot. Additionally, immunofluorescence was used to detect the expression of macrosialin antigen(CD68), mannose receptor(MRC1 or CD206), and GPR37 in dorsal root ganglia, as well as the expression of calcium-binding adapter molecule 1(IBA1), CD206, and GPR37 in the dorsal horn of the spinal cord. The results showed that compared with those of the sham-operated group, the mechanical pain thresholds and hot withdrawal latency of the model group significantly declined, and the expression of CD68 in the dorsal root ganglia and the expression of IBA1 in the dorsal horn of the spinal cord significantly increased. The expression of CD206 and GPR37 significantly decreased in the dorsal root ganglion and dorsal horn of the spinal cord, and IL-10 and TGF-β levels in the spinal cord were significantly decreased. Compared with those of the model group, the mechanical pain thresholds and hot withdrawal latency of the high-dose group of Yuxuebi Tablets significantly increased, and the expression of CD68 in the dorsal root ganglion and IBA1 in the dorsal horn of the spinal cord significantly decreased. The expression of CD206 and GPR37 in the dorsal root ganglion and dorsal horn of the spinal cord significantly increased, as well as IL-10 and TGF-β levels in the spinal cord. These findings indicated that Yuxuebi Tablets may reduce macrophage(microglial) infiltration and foster M2 macrophage polarization by enhancing GPR37 expression in the dorsal root ganglia and dorsal horn of the spinal cord of CFA-induced mice, so as to improve IL-10 and TGF-β levels, promote resolution of both peripheral and central inflammation, and play analgesic effects.
Inflammation/genetics* ; Pain/genetics* ; Drugs, Chinese Herbal/administration & dosage* ; Animals ; Mice ; Freund's Adjuvant/pharmacology* ; Ibuprofen ; Pain Threshold/drug effects* ; Hyperalgesia/genetics* ; Ganglia, Spinal ; Interleukin-10/genetics* ; Transforming Growth Factor beta/genetics* ; Reverse Transcriptase Polymerase Chain Reaction ; Tablets ; Receptors, G-Protein-Coupled

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 study the clinical and genetic characteristics of osteopetrosis (OPT) in children. METHODS: A retrospective analysis was performed on the clinical data of 14 children with OPT. Whole-exome sequencing was used to detect pathogenic genes, and clinical phenotypes and genotypic features were summarized. RESULTS: Among the 14 children (10 males and 4 females), the median age at diagnosis was 8 months. Clinical manifestations included systemic osteosclerosis (14 cases, 100%), anemia (12 cases, 86%), infections (10 cases, 71%), thrombocytopenia (9 cases, 64%), hepatosplenomegaly (8 cases, 57%), and developmental delay (5 cases, 36%). Malignant osteopetrosis (MOP) cases had lower platelet counts, creatine kinase isoenzyme, and serum calcium levels, but higher white blood cell counts, lactate dehydrogenase, and alkaline phosphatase levels compared to non-MOP cases (P<0.05). Genetic testing identified 15 variants in 12 patients, including 8 variants in the CLCN7 gene (53%), 6 in the TCIRG1 gene (40%), and 1 in the TNFRSF11A gene (7%). Three novel CLCN7 variants were identified: c.2351G>C, c.1215-43C>T, and c.1534G>A. All four patients with TCIRG1 variants exhibited MOP clinical phenotypes. Of the seven patients with CLCN7 variants, 4 presented with intermediate OPT, 2 with benign OPT, and 1 with MOP. CONCLUSIONS Clinical phenotypes of OPT in children are heterogeneous, predominantly involving CLCN7 and TCIRG1 gene variants, with a correlation between clinical phenotypes and genotypes.
Humans ; Osteopetrosis/genetics* ; Male ; Female ; Infant ; Child, Preschool ; Retrospective Studies ; Vacuolar Proton-Translocating ATPases/genetics* ; Child ; Chloride Channels/genetics* ; Mutation ; Receptor Activator of Nuclear Factor-kappa B

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.

Objective To explore the application value of physical examination information annotation combined with artificial intelli-gence (AI) in CT diagnosis of rib fractures. Methods The clinical data of 100 patients with chest trauma who underwent rib CT examina-tion with physical examination information annotation were collected. The images were analyzed by two physicians in the department of radiology with different seniorities using four methods[diagnosed by physicians independently (group A),diagnosed by physicians combined with physical examination information annotation (group B),diagnosed by physicians under the assistance of AI (group C),and diagnosed by physicians combined with physical examination information annotation under the assistance of AI (group D)]. The diagnostic efficacy and diagnostic time of two radiologists using different methods for rib fractures were compared. Results The sensitivities of two radiologists with different seniorities in the diagnosis of rib fracture in the group A were lower than those in the groups B,C and D (P<0.05),but there was no significant difference in the sensitivity of rib fracture among groups B,C and D (P>0.05). The diagnostic sensitivity of resident physician in the group A was lower than that of the attending physicians (P<0.05),and there was no significant difference in the diagnostic sensitivity of rib fracture in the other groups between the two physicians (P>0.05). There was no statistically significant difference in the false-positive rate of rib fractures among groups between two physicians (P>0.05). There was statistically significant difference in the diagnostic time among groups between two physicians (P<0.05),among which group A took the longest diagnosis time and group C took the shortest. Conclusion The assistance of AI and conbinatin of physical examination information annotation can increase the sensitivity of the physician in the diagnosis of rib fractures,shorten the diagnostic time and improve the work efficiency.

Objective To explore the application value of physical examination information annotation combined with artificial intelli-gence (AI) in CT diagnosis of rib fractures. Methods The clinical data of 100 patients with chest trauma who underwent rib CT examina-tion with physical examination information annotation were collected. The images were analyzed by two physicians in the department of radiology with different seniorities using four methods[diagnosed by physicians independently (group A),diagnosed by physicians combined with physical examination information annotation (group B),diagnosed by physicians under the assistance of AI (group C),and diagnosed by physicians combined with physical examination information annotation under the assistance of AI (group D)]. The diagnostic efficacy and diagnostic time of two radiologists using different methods for rib fractures were compared. Results The sensitivities of two radiologists with different seniorities in the diagnosis of rib fracture in the group A were lower than those in the groups B,C and D (P<0.05),but there was no significant difference in the sensitivity of rib fracture among groups B,C and D (P>0.05). The diagnostic sensitivity of resident physician in the group A was lower than that of the attending physicians (P<0.05),and there was no significant difference in the diagnostic sensitivity of rib fracture in the other groups between the two physicians (P>0.05). There was no statistically significant difference in the false-positive rate of rib fractures among groups between two physicians (P>0.05). There was statistically significant difference in the diagnostic time among groups between two physicians (P<0.05),among which group A took the longest diagnosis time and group C took the shortest. Conclusion The assistance of AI and conbinatin of physical examination information annotation can increase the sensitivity of the physician in the diagnosis of rib fractures,shorten the diagnostic time and improve the work efficiency.

Objective:To analyze two families with inherited dysfibrinogenemia,and explore the molecular pathogenic mechanisms.Methods:The coagulation indexes of the probands and their family members were detected.The FGA,FGB,and FGG exons and their flanking sequences were amplified by PCR,and the mutation sites were identified by sequencing.SIFT,PolyPhen2,LRT,ReVe,MutationTaster,phyloP,and phastCons bioinformatics software were used to predict the functional impact of the mutation sites.Protein structure and amino acid conservation analysis of the variant were conducted using PyMOL and Clustal X software.Results:The thrombin time(TT)of the proband in family 1 was prolonged to 37.00 s,and Fg:C decreased to 0.52 g/L.The TT of the proband in family 2 was 20.30 s,and Fg:C was 1.00 g/L,which was lower than the normal range.Genetic analysis revealed that the proband in family 1 had a heterozygous mutation c.80T＞C in FGA,resulting in the substitution of phenylalanine 27 with serine(Phe27Ser).The proband in family 2 had a heterozygous mutation c.1007T＞A in FGG,resulting in the substitution of methionine 336 with lysine(Met336Lys).Bioinformatics software prediction analysis indicated that both mutations were deleterious variants.PyMOL mutation models revealed that the Aα chain mutation(Phe27Ser)in family 1 and y chain mutation(Met336Lys)in family 2 resulted in alterations in spatial structure and reduced protein stability.Clustal X results showed that both Aα Phe27 and γMet336 were highly conserved across homologous species.Conclusion:Heterozygous mutations of FGA gene c.80T＞C and FGG gene c.1007T＞A are both pathogenic variants,causing inherited dysfibrinogenemia.

In recent years, polysaccharides have received much attention because of their high safety and good immunological activity. The study of polysaccharide in vivo process is a key scientific problem that needs to be solved for polysaccharide drug development. Some progress has been made in the field of polysaccharide pharmacokinetics and immunomodulation. However, due to the lack of both chromogenic and light-absorbing groups and the complex molecular structure of polysaccharides, the in vivo processes and immunomodulatory mechanisms of polysaccharides have been slow to be investigated. The effective combination of multiple techniques can break the bottleneck of difficult tracing and unknown immunomodulatory mechanism of polysaccharides in vivo, and promote the development and utilization of polysaccharides. In this paper, we systematically summarize the key techniques in the study of polysaccharide in vivo processes and immunomodulatory mechanisms in order to provide technical references and research ideas for the study of polysaccharide in vivo processes and immunomodulatory mechanisms.

Objective To investigate the diagnostic efficiency of artificial intelligence(AI)in rib frac-ture under the computed tomography(CT)images with different reconstruction slice thickness.Methods The first CT images of 100 patients with rib fractures were selected,and the interval-free recon-struction was carried out with the thickness of 0.625 mm,1.250 mm,2.500 mm and 5.000 mm,respectively.The rib fracture screening function of AI was used to automatically detect the CT images of four groups,and the diagnostic efficiency of AI for rib fracture under different reconstruction thickness conditions was com-pared.Results The sensitivity of AI in the diagnosis of rib fracture at 0.625 mm,1.250 mm,2.500 mm and 5.000 mm thickness was 99.32%(436/439),98.41%(432/439),89.52%(393/439)and 83.60%(367/439),respectively.The false positive rate was 4.80%(22/458),0.92%(4/436),0.76%(3/396)and 0.27%(1/368).The diagnostic sensitivity of AI in 0.625 mm and 1.250 mm thickness was higher than that in 2.500 mm and 5.000 mm,and the difference was statistically significant(P<0.05),while there was no significant difference in the thickness of 0.625 mm and 1.250 mm.The false positive rate of AI in the diagnosis of 0.625 mm slice thickness was higher than that of 1.250 mm,2.500 mm and 5.000 mm,and the difference was sta-tistically significant(P<0.05),while there was no significant difference in the thickness of 1.250 mm,2.500 mm and 5.000 mm(P>0.05).Conclusion The diagnostic efficiency of AI in 1.250 mm CT images is better than that in 0.625 mm,2.500 mm and 5.000 mm CT images.

Evaluate the interventional effect of Lycium barbarum leaves extract on cataract rats and its effects on plasma and liver tissue metabolites. The ultimate goal is to explore the scientific connotation of Lycium barbarum leaves extract on vision improvement. All experiments were approved by the experimental animal ethics committee from Nanjing University of Chinese Medicine (202306A067). D-Galactose (D-gal) induced cataract model in rats was established. The lens opacity, lens and liver tissue pathology, level of oxidative stress and polyol metabolism regulation in the lens, level of oxidative stress in serum and liver tissue, and the content of inflammatory cytokines such as tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) in serum and liver tissue were analysed to evaluate the effect of Lycium barbarum leaves extract on cataract. The metabolite profiles of plasma and liver tissue of rats were analyzed by UPLC-QTOF-MS/MS. Principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) were used to compare and analyze the metabolic data in control group and cataract group, and screen potential biomarkers. The related metabolic pathways were further constructed by KEGG database analysis. The results showed that lens and liver pathology of cataract rats were improved after being intervened by the leaves extract of Lycium barbarum. The contents of AR and Ca²⁺ were significantly decreased in lens, and the contents of SDH and GSH and the ability of CAT were significantly increased; the content of GSH and the ability of SOD were significantly improved in serum and liver tissue, the content of MDA, the abilities of ALT and AST and the level of inflammatory factors were significantly reduced. The metabolomics results showed that there were 15 different metabolites in plasma and liver tissue of cataract rats, and 9 different biomarkers including retinyl ester, stearic acid, and palmitic acid, were returned by Lycium barbarum leaves extract. As revealed by pathway enrichment in plasma and liver tissue, it was found that the retinol metabolic pathway was mainly regulated by Lycium barbarum leaves extract. In summary, Lycium barbarum leaves can effectively alleviate the pathological changes of cataract, inhibit inflammation and improve antioxidant capacity, which may relate to the retinol metabolic pathway. It provides scientific basis and support for revealing the scientific connotation of the effect of Lycium barbarum leaves on vision improvement.