Background: Chinese herbal pieces are an essential component of traditional Chinese medicine. Accurate identification and classification of these materials are crucial in clinical practice. Objective: This study aims to enhance the recognition efficiency of Chinese herbal pieces using deep learning technology, while addressing the limitations of traditional manual classification methods in terms of both quality and efficiency. Methods: A comprehensive dataset containing 201 types of Chinese herbal pieces was established. Based on Real-time Detection Transformer (RT-DETR), we designed and integrated a Feature-focused Diffusion Network (FDN), resulting in an improved model termed RT-DETR-FDN. The proposed FDN includes a Feature-focus Module and a feature diffusion mechanism, enabling the model to capture more extensive feature information from Chinese herbal pieces and diffuse it across multiple detection scales. Results: Experimental results show that RT-DETR-FDN achieved a precision of 0.925, a recall of 0.943, and an mAP50-95 of 0.851. In addition, the model was compared with representative You Only Look Once series models commonly used in object detection. Compared with these models, RT-DETR-FDN achieved higher recognition accuracy while maintaining a lightweight architecture. Conclusion: This study integrates deep learning with traditional Chinese medicine, providing a more effective solution for the recognition of Chinese herbal pieces.

Objective:To study the relationship between urinary arsenic methylation metabolism patterns and skin keratinization and pigmentation abnormalities in population exposed to arsenic through drinking water.Methods:Using a cross-sectional study method, a survey on endemic arsenic poisoning was conducted among permanent residents of drinking water endemic arsenic poisoning areas in Bayannur City, Inner Mongolia Autonomous Region in 2004 (before water improvement). In 2017 (after water improvement), 71 arsenic exposed individuals were followed up as survey subjects. According to the "Diagnosis of Endemic Arsenism" (WS/T 211-2015), the clinical grading of skin injuries (skin keratinization, pigmentation abnormalities) in the survey subjects was evaluated. Urine samples were collected for detection of arsenic methylation metabolite levels by high-performance liquid chromatography inductively coupled plasma mass spectrometry and calibrated with urinary creatinine. The changes and amplitudes of urinary arsenic methylation indicators before and after water improvement were calculated and analyzed according to the outcome of skin keratinization and pigmentation abnormalities which were divided into reduced, unchanged, and added groups.Results:(1) The changes in urinary total arsenic (TAs), inorganic arsenic (iAs), monomethyl arsenic (MMA), and dimethyl arsenic (DMA) levels in different outcome groups of skin keratinization were compared, and the differences were statistically significant ( H = 9.08, 8.77, 9.28, 8.57, P < 0.05). The changes in urinary TAs, iAs, MMA, DMA levels, iAs percentage (iAs%), DMA percentage (DMA%), and primary methylation index (PMI) in different outcome groups of skin pigmentation abnormalities were compared, and the differences were statistically significant ( H = 8.04, 10.67, 8.29, 9.14, 6.30, 9.10, 7.20, P < 0.05). (2) The comparison of amplitudes in urinary TAs, iAs, MMA, and DMA levels in different outcome groups of skin keratinization showed statistically significant differences ( H = 6.92, 7.34, 6.66, 6.16, P < 0.05). The amplitudes in urinary iAs level, iAs%, DMA%, and PMI in different outcome groups of skin pigmentation abnormalities were compared, and the differences were statistically significant ( H = 7.94, 7.61, 9.95, 7.22, P < 0.05). Conclusion:The changes pattern of urinary TAs, iAs, MMA, DMA, iAs%, DMA%, and PMI in population exposed to arsenic through drinking water is related to the transformation of skin keratinization and pigmentation abnormalities.

Objective:To investigate the value of biparametric-MRI (bpMRI) based peritumoral radiomics for preoperative prediction of extraprostatic extension (EPE) in prostate cancer (PCa).Methods:In this cross-sectional study, consecutive bpMRI of patients undergoing prostatectomy for PCa were retrospectively collected from the First Medical Center (center 1) and the Third Medical Center (center 2) of Chinese PLA General Hospital. A total of 274 patients were finally enrolled. Patients at center 1 from January 2020 to December 2022 were randomly divided into a training set (149 cases) and an internal validation set (63 cases) by stratified random sampling. Patients at center 2 from January 2023 to March 2024 were assigned to the external test set (62 cases). Patients were categorized into EPE-positive group and EPE-negative group according to pathological assessment postoperatively. In the training set, there were 49 cases in EPE-positive group and 100 cases in EPE-negative group. In the internal validation set, there were 26 cases in EPE-positive group and 37 cases in EPE-negative group. In the external test set, there were 22 cases in EPE-positive group and 40 cases in EPE-negative group. Axial T 2WI and apparent diffusion coefficient (ADC) images were manually annotated to obtain index lesion regions of interest (ROIs), with the peritumoral ROIs subsequently delineated by semi-automatic segmentation technique. Radiomics features were extracted from intra-tumoral, peri-tumoral, and intra-tumoral plus peri-tumoral ROIs. The training set data was employed to select and optimize features to build the radiomics models. The logistic regression analysis was used to develop radiomics, clinical, and integrated models. The predictive performance was assessed by the area under the receiver operating characteristic curve (AUC) in the external test set, and compared by the DeLong test. The sensitivity and specificity were compared by the exact McNemar test. Results:In the external test set, the peri-tumoral radiomics model based on bpMRI showed the highest performance in evaluating EPE, with an AUC of 0.739 (95% CI 0.611-0.842), which was identified as the optimal radiomics model. EPE grade ( OR=6.151, 95% CI 3.371-11.226, P<0.001) was incorporated into the clinical model, with an AUC of 0.780 (95% CI 0.657-0.875) in the external test set. The integrated model had an AUC of 0.817 (95% CI 0.698-0.904) in the external test set. There was no statistically significant difference in comparisons of AUCs among the three models (all P>0.05). The sensitivity of the integrated model (68.2%) showed no significant difference from those of the clinical model and the optimal radiomics model (77.3% and 86.4%, respectively; P=0.500 and P=0.289). However, the specificity of the integrated model (85.0%) was significantly higher than those of the clinical model (67.5%, P=0.016) and the optimal radiomics model (50.0%, P<0.001). Conclusion:A bpMRI-based peritumoral radiomics integrating clinical model demonstrates high performance for preoperative prediction of EPE in PCa.

Cytochrome P450 (CYP450) enzymes, as versatile biocatalysts with the broadest range of catalytic reactions in nature, play critical roles in the metabolism of medicinal plants. They are involved in various oxidative modification processes of active ingredients, facilitating both the synthesis and degradation of bioactive substances. This review delves into the classification, structure, and catalytic mechanisms of CYP450 enzymes, emphasizing their indispensable roles in plant biosynthesis. Using representative cases, including the biosynthetic pathways of tanshinones, artemisinin, celastrol, paclitaxel, and berberine, this review highlights the functional importance of specific CYP450s. For instance, CYP71AV1 catalyzes the production of artemisinin and artemisinic aldehyde, with its activity directly affecting artemisinin yield. Similarly, CYP76AH1 and CYP76AK1 play pivotal roles in the backbone construction and postmodification of tanshinones, acting as key players in their metabolic network. In the case of celastrol, CYP712K1, CYP712K2, and CYP712K3 initiate the first oxidative reaction, providing a solid foundation for subsequent biosynthetic processes. These examples highlight the pivotal role of CYP450 enzymes in the biosynthesis of medicinal plants, showcasing both their complexity and significance in plant metabolic pathways. Furthermore, this review examines the oxidative metabolism of CYP450 enzymes under aerobic conditions and their reductive metabolism in specific environments, offering deeper insights into their catalytic mechanisms. A comprehensive understanding of these processes lays the groundwork for the effective application of CYP450 enzymes in biotechnology and plant metabolic engineering.

Objective:To investigate the value of biparametric-MRI (bpMRI) based peritumoral radiomics for preoperative prediction of extraprostatic extension (EPE) in prostate cancer (PCa).Methods:In this cross-sectional study, consecutive bpMRI of patients undergoing prostatectomy for PCa were retrospectively collected from the First Medical Center (center 1) and the Third Medical Center (center 2) of Chinese PLA General Hospital. A total of 274 patients were finally enrolled. Patients at center 1 from January 2020 to December 2022 were randomly divided into a training set (149 cases) and an internal validation set (63 cases) by stratified random sampling. Patients at center 2 from January 2023 to March 2024 were assigned to the external test set (62 cases). Patients were categorized into EPE-positive group and EPE-negative group according to pathological assessment postoperatively. In the training set, there were 49 cases in EPE-positive group and 100 cases in EPE-negative group. In the internal validation set, there were 26 cases in EPE-positive group and 37 cases in EPE-negative group. In the external test set, there were 22 cases in EPE-positive group and 40 cases in EPE-negative group. Axial T 2WI and apparent diffusion coefficient (ADC) images were manually annotated to obtain index lesion regions of interest (ROIs), with the peritumoral ROIs subsequently delineated by semi-automatic segmentation technique. Radiomics features were extracted from intra-tumoral, peri-tumoral, and intra-tumoral plus peri-tumoral ROIs. The training set data was employed to select and optimize features to build the radiomics models. The logistic regression analysis was used to develop radiomics, clinical, and integrated models. The predictive performance was assessed by the area under the receiver operating characteristic curve (AUC) in the external test set, and compared by the DeLong test. The sensitivity and specificity were compared by the exact McNemar test. Results:In the external test set, the peri-tumoral radiomics model based on bpMRI showed the highest performance in evaluating EPE, with an AUC of 0.739 (95% CI 0.611-0.842), which was identified as the optimal radiomics model. EPE grade ( OR=6.151, 95% CI 3.371-11.226, P<0.001) was incorporated into the clinical model, with an AUC of 0.780 (95% CI 0.657-0.875) in the external test set. The integrated model had an AUC of 0.817 (95% CI 0.698-0.904) in the external test set. There was no statistically significant difference in comparisons of AUCs among the three models (all P>0.05). The sensitivity of the integrated model (68.2%) showed no significant difference from those of the clinical model and the optimal radiomics model (77.3% and 86.4%, respectively; P=0.500 and P=0.289). However, the specificity of the integrated model (85.0%) was significantly higher than those of the clinical model (67.5%, P=0.016) and the optimal radiomics model (50.0%, P<0.001). Conclusion:A bpMRI-based peritumoral radiomics integrating clinical model demonstrates high performance for preoperative prediction of EPE in PCa.

Objective To retrospectively analyze the clinical risk factors and prognosis of perioperative myocardial injury(MINS)in non-cardiac surgery patients admitted to the intensive care unit(ICU).Methods A total of 478 postoperative patients admitted to the Department of Intensive Medicine,Minhang Hospital,Fudan University from Jan 2020 to Dec 2023 were selected.They were divided into MINS group(n=302)and normal group(n=176)based on whether myocardial injury occurred within 7 days after surgery.The differences in clinical characteristics between the two groups were compared,and risk factors for perioperative myocardial injury were identified.Risk factors for mortality in the MINS group were analyzed with 30-day mortality as the clinical endpoint.Results The prevalence of acute physiology and chronic health evaluation Ⅱ(Apache Ⅱ)score,coronary artery disease,and chronic kidney disease were all higher in the MINS group than those in the normal group,with statistically significant differences(P<0.05).The proportion of emergency surgeries,co-infection,and perioperative hypotension were significantly different between the MINS group and the normal group(P<0.05).Multivariate logistic regression analysis revealed that chronic kidney disease,emergency surgery,co-infection,and intraoperative and postoperative hypotension were risk factors for MINS occurrence.Prognostic analysis indicated that perioperative hypotension was a risk factor for 30-day mortality in MINS patients.Conclusion MINS is closely associated with patients'underlying conditions,timing of surgery,and perioperative hypotension status,and especially perioperative hypotension affects the final outcomes.

Objective:To study the relationship between urinary arsenic methylation metabolism patterns and skin keratinization and pigmentation abnormalities in population exposed to arsenic through drinking water.Methods:Using a cross-sectional study method, a survey on endemic arsenic poisoning was conducted among permanent residents of drinking water endemic arsenic poisoning areas in Bayannur City, Inner Mongolia Autonomous Region in 2004 (before water improvement). In 2017 (after water improvement), 71 arsenic exposed individuals were followed up as survey subjects. According to the "Diagnosis of Endemic Arsenism" (WS/T 211-2015), the clinical grading of skin injuries (skin keratinization, pigmentation abnormalities) in the survey subjects was evaluated. Urine samples were collected for detection of arsenic methylation metabolite levels by high-performance liquid chromatography inductively coupled plasma mass spectrometry and calibrated with urinary creatinine. The changes and amplitudes of urinary arsenic methylation indicators before and after water improvement were calculated and analyzed according to the outcome of skin keratinization and pigmentation abnormalities which were divided into reduced, unchanged, and added groups.Results:(1) The changes in urinary total arsenic (TAs), inorganic arsenic (iAs), monomethyl arsenic (MMA), and dimethyl arsenic (DMA) levels in different outcome groups of skin keratinization were compared, and the differences were statistically significant ( H = 9.08, 8.77, 9.28, 8.57, P < 0.05). The changes in urinary TAs, iAs, MMA, DMA levels, iAs percentage (iAs%), DMA percentage (DMA%), and primary methylation index (PMI) in different outcome groups of skin pigmentation abnormalities were compared, and the differences were statistically significant ( H = 8.04, 10.67, 8.29, 9.14, 6.30, 9.10, 7.20, P < 0.05). (2) The comparison of amplitudes in urinary TAs, iAs, MMA, and DMA levels in different outcome groups of skin keratinization showed statistically significant differences ( H = 6.92, 7.34, 6.66, 6.16, P < 0.05). The amplitudes in urinary iAs level, iAs%, DMA%, and PMI in different outcome groups of skin pigmentation abnormalities were compared, and the differences were statistically significant ( H = 7.94, 7.61, 9.95, 7.22, P < 0.05). Conclusion:The changes pattern of urinary TAs, iAs, MMA, DMA, iAs%, DMA%, and PMI in population exposed to arsenic through drinking water is related to the transformation of skin keratinization and pigmentation abnormalities.

BACKGROUND: The available evidence regarding the benefits of percutaneous coronary intervention (PCI) on patients receiving dialysis with coronary artery disease (CAD) is limited and inconsistent. This study aimed to evaluate the association between PCI and clinical outcomes as compared with medical therapy alone in patients undergoing dialysis with CAD in China. METHODS: This multicenter, retrospective study was conducted in 30 tertiary medical centers across 12 provinces in China from January 2015 to June 2021 to include patients on dialysis with CAD. The primary outcome was major adverse cardiovascular events (MACE), defined as a composite of cardiovascular death, non-fatal myocardial infarction, and non-fatal stroke. Secondary outcomes included all-cause death, the individual components of MACE, and Bleeding Academic Research Consortium criteria types 2, 3, or 5 bleeding. Multivariable Cox proportional hazard models were used to assess the association between PCI and outcomes. Inverse probability of treatment weighting (IPTW) and propensity score matching (PSM) were performed to account for potential between-group differences. RESULTS: Of the 1146 patients on dialysis with significant CAD, 821 (71.6%) underwent PCI. After a median follow-up of 23.0 months, PCI was associated with a 43.0% significantly lower risk for MACE (33.9% [ n  = 278] vs . 43.7% [ n  = 142]; adjusted hazards ratio 0.57, 95% confidence interval 0.45-0.71), along with a slightly increased risk for bleeding outcomes that did not reach statistical significance (11.1% vs . 8.3%; adjusted hazards ratio 1.31, 95% confidence interval, 0.82-2.11). Furthermore, PCI was associated with a significant reduction in all-cause and cardiovascular mortalities. Subgroup analysis did not modify the association of PCI with patient outcomes. These primary findings were consistent across IPTW, PSM, and competing risk analyses. CONCLUSION This study indicated that PCI in patients on dialysis with CAD was significantly associated with lower MACE and mortality when comparing with those with medical therapy alone, albeit with a slightly increased risk for bleeding events that did not reach statistical significance.
Humans ; Percutaneous Coronary Intervention/methods* ; Male ; Female ; Coronary Artery Disease/drug therapy* ; Retrospective Studies ; Renal Dialysis/methods* ; Middle Aged ; Aged ; China ; Proportional Hazards Models ; Treatment Outcome

Diterpenoid ferruginol is a key intermediate in biosynthesis of active ingredients such as tanshinone and carnosic acid.However, the traditional process of obtaining ferruginol from plants is often cumbersome and inefficient. In recent years, the increasingly developing gene editing technology has been gradually applied to the heterologous production of natural products, but the production of ferruginol in microbe is still very low, which has become an obstacle to the efficient biosynthesis of downstream chemicals, such as tanshinone. In this study, miltiradiene was produced by integrating the shortened diterpene synthase fusion protein,and the key genes in the MVA pathway were overexpressed to improve the yield of miltiradiene. Under the shake flask fermentation condition, the yield of miltiradiene reached about(113. 12±17. 4)mg·L~(-1). Subsequently, this study integrated the ferruginol synthase Sm CYP76AH1 and Sm CPR1 to reconstruct the ferruginol pathway and thereby realized the heterologous synthesis of ferruginol in Saccharomyces cerevisiae. The study selected the best ferruginol synthase(Il CYP76AH46) from different plants and optimized the expression of pathway genes through redox partner engineering to increase the yield of ferruginol. By increasing the copy number of diterpene synthase, CYP450, and CPR, the yield of ferruginol reached(370. 39± 21. 65) mg·L~(-1) in the shake flask, which was increased by 21. 57-fold compared with that when the initial ferruginol strain JMLT05 was used. Finally, 1 083. 51 mg·L~(-1) ferruginol was obtained by fed-batch fermentation, which is the highest yield of ferruginol from biosynthesis so far. This study provides not only research ideas for other metabolic engineering but also a platform for the construction of cell factories for downstream products.
Saccharomyces cerevisiae/genetics* ; Diterpenes/metabolism* ; Metabolic Engineering ; Fermentation ; Abietanes

This study primarily investigates the effect of Liuwei Dihuang Pills on the activation and proliferation of female germline stem cells(FGSCs) in the ovaries and cortex of mice with premature ovarian failure(POF), and how it improves ovarian function. ICR mice were randomly divided into the control group, model group, Liuwei Dihuang Pills group, Liuwei Dihuang Pills double-dose group, and estradiol valerate group. A mouse model of POF was established by intraperitoneal injection of cyclophosphamide. After successful modeling, the mice were treated with Liuwei Dihuang Pills or estradiol valerate for 28 days. Vaginal smears were prepared to observe the estrous cycle and body weight. After the last administration, mice were sacrificed and sampled. Serum levels of estradiol(E_2), follicle-stimulating hormone(FSH), luteinizing hormone(LH), and anti-Müllerian hormone(AMH) were measured by enzyme-linked immunosorbent assay(ELISA). Hematoxylin-eosin(HE) staining was used to observe ovarian morphology and to count follicles at all stages to evaluate ovarian function. Immunohistochemistry was used to detect the expression of mouse vasa homolog(MVH), a marker of ovarian FGSCs. Immunofluorescence staining, using co-labeling of MVH and proliferating cell nuclear antigen(PCNA), was used to detect the expression and localization of specific markers of FGSCs. Western blot was employed to assess the protein expression of MVH, octamer-binding transcription factor 4(Oct4), and PCNA in the ovaries. The results showed that compared with the control group, the model group exhibited disordered estrous cycles, decreased ovarian index, increased atretic follicles, and a reduced number of follicles at all stages. FSH and LH levels were significantly elevated, while AMH and E_2 levels were significantly reduced, indicating the success of the model. After treatment with Liuwei Dihuang Pills or estradiol valerate, hormone levels improved, the number of atretic follicles decreased, and the number of follicles at all stages increased. MVH marker protein and PCNA proliferative protein expression in ovarian tissue also increased. These results suggest that Liuwei Dihuang Pills regulate estrous cycles and hormone disorders in POF mice, promote the proliferation of FGSCs, improve follicular development in POF mice, and enhance ovarian function.
Animals ; Female ; Drugs, Chinese Herbal/administration & dosage* ; Mice ; Cell Proliferation/drug effects* ; Mice, Inbred ICR ; Ovary/cytology* ; Primary Ovarian Insufficiency/genetics* ; Follicle Stimulating Hormone/metabolism* ; Humans ; Anti-Mullerian Hormone/blood* ; Antineoplastic Agents/adverse effects* ; Luteinizing Hormone/metabolism* ; Cyclophosphamide/adverse effects*