Traditional Chinese medicine(TCM) processing is a unique and highly distinctive pharmaceutical technology in China. Utilizing modern scientific methods to elucidate the connotations of traditional processing theory and its effects is expected to facilitate the inheritance, development, innovation, and enhancement of TCM processing, and lead to more original research outcomes in the field of TCM. The breakthrough in TCM processing lies in the study of its underlying principles, and analyzing these principles involves researching the transformation mechanisms of chemical components and the biological effect mechanisms of the transformed components. This paper proposed the concept of "TCM processing chemical biology"(TCMPCB) for the first time. Under the guidance of TCM theory, the active components transformed during TCM processing were used as chemical tools to study their targets and molecular regulatory mechanisms, aiming to clarify the scientific principles by which TCM processing affected biological effects in the organism. The research findings also provided new directions for discovering novel active components, new lead compounds, creating new decoction pieces, and developing new TCM drugs. This paper provided a detailed introduction to the background, definition, research content, research ideas, research methods, and prospects of TCMPCB, with the aim of offering new research perspectives for analyzing the principles of TCM processing and providing new pathways for achieving the "four new and eight transformations" in TCM processing.
Drugs, Chinese Herbal/chemistry* ; Medicine, Chinese Traditional/methods* ; Humans ; Animals

By employing the analytic hierarchy process(AHP), the CRITIC method(a weight determination method based on indicator correlations), and the AHP-CRITIC hybrid weighting method, the weight coefficients of evaluation indicators were determined, followed by a comprehensive score comparison. The grey correlation analysis was then performed to analyze the results calculated using the hybrid weighting method. Subsequently, a backpropagation-artificial neural network(BP-ANN) model was constructed to predict the extraction process parameters and optimize the extraction process for Shenxiong Huanglian Jiedu Granules(SHJG). In the extraction process, an L_9(3~4) orthogonal experiment was designed to optimize three factors at three levels, including extraction frequency, water addition amount, and extraction time. The evaluation indicators included geniposide, berberine, ginsenoside Rg_1 + Re, ginsenoside Rb_1, ferulic acid, and extract yield. Finally, the optimal extraction results obtained by the orthogonal experiment, grey correlation analysis, and BP-ANN method were compared, and validation experiments were conducted. The results showed that the optimal extraction process involved two rounds of aqueous extraction, each lasting one hour; the first extraction used ten times the amount of added water, while the second extraction used eight times the amount. In the validation experiments, the average content of each indicator component was higher than the average content obtained in the orthogonal experiment, with a higher comprehensive score. The optimized extraction process parameters were reliable and stable, making them suitable for subsequent preparation process research.
Drugs, Chinese Herbal/analysis* ; Neural Networks, Computer

The genome tagging project (GTP) plays a pivotal role in addressing a critical gap in the understanding of protein functions. Within this framework, we successfully generated a human influenza hemagglutinin-tagged sperm-specific protein 411 (HA-tagged Ssp411) mouse model. This model is instrumental in probing the expression and function of Ssp411. Our research revealed that Ssp411 is expressed in the round spermatids, elongating spermatids, elongated spermatids, and epididymal spermatozoa. The comprehensive examination of the distribution of Ssp411 in these germ cells offers new perspectives on its involvement in spermiogenesis. Nevertheless, rigorous further inquiry is imperative to elucidate the precise mechanistic underpinnings of these functions. Ssp411 is not detectable in metaphase II (MII) oocytes, zygotes, or 2-cell stage embryos, highlighting its intricate role in early embryonic development. These findings not only advance our understanding of the role of Ssp411 in reproductive physiology but also significantly contribute to the overarching goals of the GTP, fostering groundbreaking advancements in the fields of spermiogenesis and reproductive biology.
Animals ; Female ; Humans ; Male ; Mice ; Spermatids/metabolism* ; Spermatogenesis/physiology* ; Spermatozoa/metabolism* ; Thioredoxins/genetics*

Debates persist regarding the efficacy and safety of azvudine, particularly its real-world outcomes. This study involved patients aged ≥60 years who were admitted to 25 hospitals in mainland China with confirmed SARS-CoV-2 infection between December 1, 2022, and February 28, 2023. Efficacy outcomes were all-cause mortality during hospitalization, the proportion of patients discharged with recovery, time to nucleic acid-negative conversion (T _NANC), time to symptom improvement (T _SI), and time of hospital stay (T _HS). Safety was also assessed. Among the 5884 participants identified, 1999 received azvudine, and 1999 matched controls were included after exclusion and propensity score matching. Azvudine recipients exhibited lower all-cause mortality compared with controls in the overall population (13.3% vs. 17.1%, RR, 0.78; 95% CI, 0.67-0.90; P = 0.001) and in the severe subgroup (25.7% vs. 33.7%; RR, 0.76; 95% CI, 0.66-0.88; P < 0.001). A higher proportion of patients discharged with recovery, and a shorter T _NANC were associated with azvudine recipients, especially in the severe subgroup. The incidence of adverse events in azvudine recipients was comparable to that in the control group (2.3% vs. 1.7%, P = 0.170). In conclusion, azvudine showed efficacy and safety in older patients hospitalized with COVID-19 during the SARS-CoV-2 omicron wave in China.

Objective To estimate adolescents and children age using stepwise regression and machine learning methods based on the pulp and tooth volumes of the left maxillary central incisor and cuspid on cone beam computed tomography(CBCT)images,and to compare and analyze the estimation re-sults.Methods A total of 498 Shanghai Han adolescents and children CBCT images of the oral and maxillofacial regions were collected.The pulp and tooth volumes of the left maxillary central incisor and cuspid were measured and calculated.Three machine learning algorithms(K-nearest neighbor,ridge regression,and decision tree)and stepwise regression were used to establish four age estimation models.The coefficient of determination,mean error,root mean square error,mean square error and mean ab-solute error were computed and compared.A correlation heatmap was drawn to visualize and the monotonic relationship between parameters was visually analyzed.Results The K-nearest neighbor model(R2=0.779)and the ridge regression model(R2=0.729)outperformed stepwise regression(R2=0.617),while the decision tree model(R2=0.494)showed poor fitting.The correlation heatmap demon-strated a monotonically negative correlation between age and the parameters including pulp volume,the ratio of pulp volume to hard tissue volume,and the ratio of pulp volume to tooth volume.Con-clusion Pulp volume and pulp volume proportion are closely related to age.The application of CBCT-based machine learning methods can provide more accurate age estimation results,which lays a founda-tion for further CBCT-based deep learning dental age estimation research.

Influenza virus causes serious threat to human life and health. Due to the inherent high variability of influenza virus, clinically resistant mutant strains of currently approved anti-influenza virus drugs have emerged. Therefore, it is urgent to develop antiviral drugs with new targets or mechanisms of action. RNA-dependent RNA polymerase is directly responsible for viral RNA transcription and replication, and plays key roles in the viral life cycle, which is considered an important target of anti-influenza drug design. From the point of view of medicinal chemistry, this review summarizes current advances in diverse small-molecule inhibitors targeting influenza virus RNA-dependent RNA polymerase, hoping to provide valuable reference for development of novel antiviral drugs.

G protein-coupled receptor (GPR) 40, as one of GPRs family, plays a potential role in regulating glucose and lipid metabolism. To study the effect of GPR40 novel agonist SZZ15-11 on hyperglycemia and hyperlipidemia and its potential mechanism, spontaneous type 2 diabetic KKA^y mice, human hepatocellular carcinoma HepG2 cells and murine mature adipocyte 3T3-L1 cells were used. KKA^y mice were divided into four groups, vehicle group, TAK group, SZZ (50 mg·kg^-1) group and SZZ (100 mg·kg^-1) group, with oral gavage of 0.5% sodium carboxymethylcellulose (CMC), 50 mg·kg^-1 TAK875, 50 and 100 mg·kg^-1 SZZ15-11 respectively for 45 days. Fasting blood glucose, blood triglyceride (TG) and total cholesterol (TC), non-fasting blood glucose were tested. Oral glucose tolerance test and insulin tolerance test were executed. Blood insulin and glucagon were measured via enzyme-linked immunosorbent assay (ELISA). After mice′s execution, liver tissue was harvested to test TG and TC content. Then pathological morphology of liver was observed through hematoxylin-eosin (HE) staining, and the lipid metabolism relative signal pathway was analyzed by Western blot and RT-PCR. The experiments were approved by the Institutional Animal Care and Use Committee of the Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College. At the same time, Akt phosphorylation level in HepG2 cells and adiponectin in 3T3-L1 cells treated with TNFα were measured with Western blot. The results show that SZZ15-11 not only decreased blood glucose and lipid, improved insulin sensitivity, but also increased fasting blood glucagon and promoted insulin secretion after glucose loading in KKA^y mice. Additionally, SZZ15-11 alleviated hepatic steatosis and liver dysfunction in KKA^y mice. In liver tissue, SZZ15-11 increased AMPKα phosphorylation level and cholesterol metabolism relative gene Abcg8 transcription. In HepG2 cells, SZZ15-11 increased Akt phosphorylation level. In adipocyte 3T3-L1, SZZ15-11 recovered the decreased adiponectin expression by TNFα. This study proved that GPR40 agonist SZZ15-11 could be a candidate compound for regulating glucolipid metabolic disorder.

italic>Artemisia argyi is a traditional Chinese medicine in China, which is used as medicine with its leaves. The leaves of A. argyi mainly contain flavonoids, phenolic acids, volatile oils and other compounds, and have a variety of pharmacological activities. AP2/ERF transcription factors are abundant in plants and are mainly involved in plant growth and development, abiotic stress response and secondary metabolite biosynthesis regulation. However, there are few reports on the AP2/ERF gene family and its functions in A. argyi. In this study, we systematically identified the AP2/ERF gene family in A. argyi genome, and analyzed its phylogenetic tree, protein physicochemical properties, subcellular localization, conserved motifs, promoter elements, and expression patterns. The results showed that a total of 204 AP2/ERF transcription factors were identified in A. argyi genome, encoding proteins consisting of 88-483 amino acids with a relative molecular mass of 10-52.94 kDa and a theoretical isoelectric point of 4.62-9.88. Subcellular prediction showed that the majority of AP2/ERFs were located in the nucleus, cytoplasm, and the minority of them is located in the membrane and chloroplasts. According to the Arabidopsis AP2/ERF family classification, A. argyi AP2/ERF proteins were divided into four subfamilies: Soloist, AP2, ERF (B3, B4, B5, B6), and DREB (A1, A2, A4, A5, A6), among which DREB family accounted for the largest proportion, and the same subfamily had similar conserved motifs. cis-Acting element analysis showed that AP2/ERF promoters have a large number of elements responding to light and abiotic stress. Expression pattern analysis showed that most of the genes of the AP2/ERF family were dominantly expressed mainly in roots and stems, of which 19 were dominantly expressed in leaves, 77 would be induced to be expressed by methyl jasmonate, of which 16 genes were both dominantly expressed in leaves and induced to be expressed by methyl jasmonate, and these AP2/ERF genes may be the key regulatory genes for the synthesis of active ingredients in A. argyi leaves.This study lays the foundation for the functional study of AP2/ERF family genes and their regulating roles in the active components biosynthesis in A. argyi leaves.

Objective To explore the effect of deep learning image reconstruction(DLIR)algorithm combined with"double low"[low voltage(kV)and low contrast agent dosage]technique on the image quality of coronary computed tomography angiography(CCTA)in overweight patients compared with adaptive statistical iterative reconstruction(ASIR-V)and filtered back projection(FBP).Methods Fifty-two patients with body mass index(BMI)between 25.1 kg/m2and 28 kg/m2 who underwent CCTA scanning were prospectively selected,all of whom scanned on a GE Revolution APEX-CT with a tube voltage of 80 kV,a smart mA(500-1 300 mA),a noise index of 30,and a contrast dosage of 0.5 mL/kg;four groups of images were reconstructed for each patient,FBP,50％ASIR-V,DLIR-M,and DLIR-H.The CT and SD values of the aorta(AO)root,the proximal segment of the right coronary artery(RCA),the left circumflex(LCX),the left anterior descending branch(LAD)and the pericardial fat were measured,and the signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)were calculated.Two doctors experienced in the diagnosis of cardiovascular disease were selected to subjectively score the reconstructed images using a double-blind method.The SD value,SNR value,CNR value and subjective scores of images in the four groups were compared.Results In the objective image quality evaluation,there were statistically significant differences in SD value,SNR value and CNR value of reconstructed images in the four groups(P＜0.05).As the four groups of reconstruction algorithms FBP,50％ASIR-V,DLIR-M,and DLIR-H were changed sequentially,the image SD value gradually decreased,the SNR value and CNR value gradually increased,and the DLIR-H group had the lowest SD value and the highest SNR and CNR values.In the subjective image quality evaluation,the subjective scores of the two doctors had good consistency(Kappa value=0.900),and the difference between them was statistically significant(P＜0.001).The subjective scores of DLIR-M and DLIR-H groups were higher.Conclusion DLIR algorithm combined with"double-low"technique can significantly improve the CCTA image quality of overweight patients,which is better than 50％ASIR-V and FBP.

Non-communicable diseases(NCDs),including cardiovascular diseases,cancer,metabolic diseases,and skeletal diseases,pose significant challenges to public health worldwide.The complex pathogenesis of these diseases is closely linked to oxidative stress and inflammatory damage.Nuclear factor erythroid 2-related factor 2(Nrf2),a critical transcription factor,plays an important role in regulating antioxidant and anti-inflammatory responses to protect the cells from oxidative damage and inflammation-mediated injury.Therefore,Nrf2-targeting therapies hold promise for preventing and treating NCDs.Quercetin(Que)is a widely available flavonoid that has significant antioxidant and anti-inflammatory properties.It modulates the Nrf2 signaling pathway to ameliorate oxidative stress and inflammation.Que modulates mitochondrial function,apoptosis,autophagy,and cell damage biomarkers to regulate oxidative stress and inflammation,highlighting its efficacy as a therapeutic agent against NCDs.Here,we discussed,for the first time,the close association between NCD pathogenesis and the Nrf2 signaling pathway,involved in neurodegenerative diseases(NDDs),cardiovascular disease,cancers,organ damage,and bone damage.Furthermore,we reviewed the availability,pharmacokinetics,pharmaceutics,and therapeutic applica-tions of Que in treating NCDs.In addition,we focused on the challenges and prospects for its clinical use.Que represents a promising candidate for the treatment of NCDs due to its Nrf2-targeting properties.