OBJECTIVE To explore the association between the use of oral progesterone drugs in early pregnancy and gestational diabetes mellitus （GDM）. METHODS Through real-world retrospective cohort research method， pregnant women who underwent the oral glucose tolerance test （OGTT） at the Affiliated Maternal and Child Health Hospital of Nantong University between January 2022 and January 2023 were enrolled. Based on whether oral progesterone drugs were used in early pregnancy， they were divided into treatment group and control group； propensity score matching （PSM） with a 1∶1 ratio was employed to control for confounding factors； Logistic regression and linear regression were employed to analyze the association between drug factors （whether use of oral progesterone drug， duration of medication， dosage， and drug type） and outcome indicators （occurrence of GDM， fasting blood glucose levels， and OGTT 1 and 2 h blood glucose levels in late pregnancy）. RESULTS A total of 709 pregnant women were enrolled in the two groups before PSM； after PSM， 256 cases were included in both the treatment group and the control group. The results of association analysis indicated that there was no significant association between the use of oral progesterone drugs and GDM （P＞0.05）； but a significant correlation was found with OGTT 1 h blood glucose levels [β＝0.965， 95%CI （0.007，1.922）， P＜0.05]， specifically with Dydrogesterone tablets [β＝0.977， 95%CI （0.009， 1.944）， P＜0.05] and Progesterone soft capsules [β ＝1.089， 95%CI （0.077， 2.102）， P＜0.05]. There was no significant correlation between other drug factors and outcome indicators （P＞0.05）. CONCLUSIONS The use of oral progestogen drugs in early pregnancy is not significantly associated with GDM. The blood glucose levels in late pregnancy， especially OGTT 1 h blood glucose levels， have a certain correlation with Progesterone soft capsules and Dydrogesterone tablets.

ObjectiveTo investigate the effects of different fermentation methods and times on the fungal flora and chemical composition of Aurantii Fructus， in order to obtain the optimal fermentation conditions and flora structure， and to ensure the stability and controllability of the fermented varieties. MethodsScanning electron microscopy was used to observe and analyze the colony characteristics on the surface of Aurantii Fructus under different fermentation conditions. Internal transcribed spacer 2（ITS2） high-throughput sequencing， combined with fungal community diversity analysis and fungal community structure analysis， were used to obtain the fungal flora microbial categories of Aurantii Fructus under the conditions of traditional pressure-shelf fermentation and non-pressure-shelf natural fermentation for 7， 14， 21 d（numbered Y1-Y3 for the former， and numbered F1-F3 for the latter）， respectively. At the same time， the chemical components in the fermentation process were detected by ultra-high performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS/MS）， combined with principal component analysis（PCA）， partial least squares-discriminant analysis（PLS-DA） and compound retention time， parent ions， characteristic fragment ions and other information， the differential compounds between the different fermentation samples were screened and identified. ResultsThe analysis of fungal community diversity showed that the dominant flora did not change at different fermentation time points in the traditional pressure-shelf fermentation method， while in the non-pressure-shelf natural fermentation method， there was a significant difference with the fermentation process， and at the genus level， the dominant genus of samples Y1， Y2， Y3 and F2 was Aspergillus， while the dominant genera of samples F1 and F3 were both Rhizopus. This indicated that the microbial growth environment provided by the traditional fermentation method was more stable， and the microbial community structure was more stable， which was more conducive to the stable and controllable fermentation process and fermented products. A total of 155 compounds were identified by compositional analysis， including 70 flavonoids， 38 coumarins， 10 alkaloids， 34 organic acids and 3 other compounds. After fermentation， two new components of ribalinine and pranferin were produced. Different fermentation conditions also brought about differences in chemical composition， multivariate statistical analysis obtained 26 differential compounds under two different fermentation methods， mainly including flavonoids， organic acids and coumarins. Comprehensively， the microbial community structure of samples fermented by the traditional pressure-shelf method of Aurantii Fructus for 14 d was stable， the species richness was high and the overall content of differential compounds was high， which was the optimal processing condition. ConclusionCompared with non-pressure-shelf natural fermentation， the traditional method has obvious advantages in terms of the stability of the microbial community structure and the content of chemical compounds， and the optimal condition is 14 days of fermentation. This study is helpful to promote the quality stability and fermentation bioavailability of fermented products of Aurantii Fructus， as well as to provide an experimental basis for the further improvement of the quality control methods of this variety.

ObjectiveTo investigate the effects of different fermentation methods and times on the fungal flora and chemical composition of Aurantii Fructus， in order to obtain the optimal fermentation conditions and flora structure， and to ensure the stability and controllability of the fermented varieties. MethodsScanning electron microscopy was used to observe and analyze the colony characteristics on the surface of Aurantii Fructus under different fermentation conditions. Internal transcribed spacer 2（ITS2） high-throughput sequencing， combined with fungal community diversity analysis and fungal community structure analysis， were used to obtain the fungal flora microbial categories of Aurantii Fructus under the conditions of traditional pressure-shelf fermentation and non-pressure-shelf natural fermentation for 7， 14， 21 d（numbered Y1-Y3 for the former， and numbered F1-F3 for the latter）， respectively. At the same time， the chemical components in the fermentation process were detected by ultra-high performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS/MS）， combined with principal component analysis（PCA）， partial least squares-discriminant analysis（PLS-DA） and compound retention time， parent ions， characteristic fragment ions and other information， the differential compounds between the different fermentation samples were screened and identified. ResultsThe analysis of fungal community diversity showed that the dominant flora did not change at different fermentation time points in the traditional pressure-shelf fermentation method， while in the non-pressure-shelf natural fermentation method， there was a significant difference with the fermentation process， and at the genus level， the dominant genus of samples Y1， Y2， Y3 and F2 was Aspergillus， while the dominant genera of samples F1 and F3 were both Rhizopus. This indicated that the microbial growth environment provided by the traditional fermentation method was more stable， and the microbial community structure was more stable， which was more conducive to the stable and controllable fermentation process and fermented products. A total of 155 compounds were identified by compositional analysis， including 70 flavonoids， 38 coumarins， 10 alkaloids， 34 organic acids and 3 other compounds. After fermentation， two new components of ribalinine and pranferin were produced. Different fermentation conditions also brought about differences in chemical composition， multivariate statistical analysis obtained 26 differential compounds under two different fermentation methods， mainly including flavonoids， organic acids and coumarins. Comprehensively， the microbial community structure of samples fermented by the traditional pressure-shelf method of Aurantii Fructus for 14 d was stable， the species richness was high and the overall content of differential compounds was high， which was the optimal processing condition. ConclusionCompared with non-pressure-shelf natural fermentation， the traditional method has obvious advantages in terms of the stability of the microbial community structure and the content of chemical compounds， and the optimal condition is 14 days of fermentation. This study is helpful to promote the quality stability and fermentation bioavailability of fermented products of Aurantii Fructus， as well as to provide an experimental basis for the further improvement of the quality control methods of this variety.

Based on the high-fat diet-induced hyperlipidemia rat model, this study aimed to evaluate the lipid-lowering effect of Arisaema Cum Bile and explore its mechanisms, providing experimental evidence for its clinical application. Biochemical analysis was used to detect serum levels of alanine aminotransferase(ALT), aspartate aminotransferase(AST), high-density lipoprotein cholesterol(HDL-C), low-density lipoprotein cholesterol(LDL-C), triglycerides(TG), and total cholesterol(TC) to assess the lipid-lowering activity of Arisaema Cum Bile. Additionally, 16S rDNA sequencing and metabolomics techniques were employed to jointly elucidate the lipid-lowering mechanisms of Arisaema Cum Bile. The experimental results showed that high-dose Arisaema Cum Bile(PBA-H) significantly reduced serum ALT, AST, LDL-C, TG, and TC levels(P<0.01), and significantly increased HDL-C levels(P<0.01). The effect was similar to that of fenofibrate, with no significant difference. Furthermore, Arisaema Cum Bile significantly alleviated hepatocyte ballooning and mitigated fatty degeneration in liver tissues. As indicated by 16S rDNA sequencing results, PBA-H significantly enhanced both alpha and beta diversity of the gut microbiota in the model rats, notably increasing the relative abundance of Akkermansia and Subdoligranulum species(P<0.01). Liver metabolomics analysis revealed that PBA-H primarily regulated pathways involved in arachidonic acid metabolism, vitamin B_6 metabolism, and steroid biosynthesis. In summary, Arisaema Cum Bile significantly improved abnormal blood lipid levels and liver pathology induced by a high-fat diet, regulated hepatic metabolic disorders, and improved the abundance and structural composition of gut microbiota, thereby exerting its lipid-lowering effect. The findings of this study provide experimental evidence for the clinical application of Arisaema Cum Bile and the treatment of hyperlipidemia.
Animals ; Gastrointestinal Microbiome/drug effects* ; Rats ; Male ; Metabolomics ; Hyperlipidemias/microbiology* ; Drugs, Chinese Herbal/administration & dosage* ; Rats, Sprague-Dawley ; Hypolipidemic Agents/pharmacology* ; Liver/metabolism* ; Humans ; Alanine Transaminase/metabolism* ; Triglycerides/metabolism* ; Aspartate Aminotransferases/metabolism*

This study aims to systematically characterize the targeted effects of Quanduzhong Capsules on cartilage lesions in knee osteoarthritis by integrating spatial transcriptomics data mining and animal experiments validation, thereby elucidating the related molecular mechanisms. A knee osteoarthritis model was established using Sprague-Dawley(SD) rats, via a modified Hulth method. Hematoxylin and eosin(HE) staining was employed to detect knee osteoarthritis-associated pathological changes in knee cartilage. Candidate targets of Quanduzhong Capsules were collected from the HIT 2.0 database, followed by bioinformatics analysis of spatial transcriptomics datasets(GSE254844) from cartilage tissues in clinical knee osteoarthritis patients to identify spatially specific disease genes. Furthermore, a "formula candidate targets-spatially specific genes in cartilage lesions" interaction network was constructed to explore the effects and major mechanisms of Quanduzhong Capsules in distinct cartilage regions. Experimental validation was conducted through immunohistochemistry using animal-derived biospecimens. The results indicated that Quanduzhong Capsules effectively inhibited the degenerative changes in the cartilage of affected joints in rats, which was associated with the regulation of Quanduzhong Capsules on the thioredoxin-interacting protein(TXNIP)-NOD-like receptor family pyrin domain containing 3(NLRP3)-bone morphogenetic protein receptor type 2(BMPR2)-fibronectin 1(FN1)-matrix metallopeptidase 2(MMP2) signal axis in the articular cartilage surface and superficial zones, subsequently inhibiting cartilage matrix degradation leading to oxidative stress and inflammatory diffusion. In summary, this study clarifies the spatially specific targeted effects and protective mechanisms of Quanduzhong Capsules within pathological cartilage regions in knee osteoarthritis, providing theoretical and experimental support for the clinical application of this drug in the targeted therapy on the inflamed cartilage.
Animals ; Osteoarthritis, Knee/metabolism* ; Drugs, Chinese Herbal/administration & dosage* ; Rats, Sprague-Dawley ; Rats ; Male ; Humans ; Capsules ; Female ; Disease Models, Animal

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

To determine the optimal cultivation duration and harvest period for cultivated Notopterygium incisum and promote its industrial development, this study established a characteristic chromatographic profile of cultivated N. incisum and employed chemometrics combined with entropy-weighted grey correlation analysis to assess differences in agronomic traits and quality indicators across different cultivation years and harvest periods. By comparing with reference substances, ten common peaks were identified, including chlorogenic acid, p-coumaric acid, ferulic acid, marmesinin, nodakenin, isochlorogenic acid B, notopterol, phenethyl ferulate, isoimperatorin, and falcarindiol. The similarity between the characteristic chromatographic profiles of N. incisum at different cultivation years and the reference profile was all above 0.932. Principal component analysis(PCA) and orthogonal partial least squares discriminant analysis(OPLS-DA) revealed that the quality of 1-to 3-year-old cultivated N. incisum was highly dispersed and unstable, whereas the quality of 4-year-old cultivated N. incisum remained relatively stable across different harvest periods. This suggests that the accumulation of relevant compounds in the medicinal material had reached a plateau, confirming that the optimal cultivation period for N. incisum is four years. Entropy-weighted grey correlation analysis indicated that the quality of 4-year-old cultivated N. incisum across different harvest periods ranked from highest to lowest as follows: November, December, October, August, July, and September, demonstrating that November is the optimal harvest time. The findings of this study establish the suitable cultivation duration and optimal harvest period for N. incisum, providing a scientific basis for cultivation guidance and quality standardization.
Chromatography, High Pressure Liquid/methods* ; Apiaceae/chemistry* ; Entropy ; Chemometrics/methods* ; Drugs, Chinese Herbal/chemistry* ; Principal Component Analysis ; Quality Control

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.