Objective:To establish a rapid quantitative model for the determination of moisture,extractives,and content in Pollen Typhae.Methods:Near-infrared spectra of 91 batches of Pollen Typhae samples were collected.Spectral preprocessing was performed using S-G,MSC,SNV,and CWT methods.Variable selection was conducted using CARS,SPA,and VIP methods,and compared with full-spectrum modeling.Partial least squares(PLS)mod-els were established for the quantitative determination of moisture,total ash,extractives,and content.The model performance was evaluated by calculating the coefficient of determination for the calibration set and validation set(R2 c,R2v),root mean square error of calibration and validation(RMSEc,RMSEv),and residual prediction devia-tion(RPD).Results:The PLS models for moisture,extractives,and content in Pollen Typhae showed R2c and R2v values greater than 0.9,RMSEc and RMSEv values approaching 0,and RPD values greater than 3.Conclusion:In this study,near-infrared spectroscopy was used to construct quantitative prediction models for moisture,extractives,typhaneoside,and isorhamnetin-3-O-neohesperidoside content in Pollen Typhae.This method enables rapid detection of the main quality control indicators of Pollen Typhae,providing strong technical support for its quality supervision.

Endometriosis (EMS) is a chronic systemic disease prevalent in women of reproductive age. The signs and symptoms of this disease are not specific, and the severity of the disease varies, leading to clinical heterogeneity, which increases the difficulty of diagnosis. It seriously affects the quality of life of patients and also occupies a large amount of social health resources. Artificial intelligence (AI) refers to the ability of a computer technology to enable machines to simulate human intelligence, including perception, learning, reasoning, decision making and language understanding. AI serves as a powerful data-mining tool capable of processing large amounts of medical data and diagnosing, managing, and treating patients according to their specific conditions. Especially in the diagnostic process of EMS, the use of AI can improve the detection rate and shorten the diagnostic time while increasing the diagnostic sensitivity and specificity. In this paper, we provide an overview of the application of medical big data and AI to the diagnosis and treatment of EMS in order to provide new aids to further improve diagnostic efficiency and therapeutic efficacy.

ObjectiveTo investigate the distribution of traditional Chinese medicine （TCM） syndromes in intrahepatic cholestasis of pregnancy （ICP） and its association with perinatal outcomes， and to provide a basis for precise treatment based on TCM syndrome differentiation. MethodsA cross-sectional study was conducted among 275 patients with ICP who were admitted to The Affiliated Hospital of Chengdu University of Traditional Chinese Medicine from April 2023 to April 2025. A hierarchical cluster analysis was used to summarize TCM syndromes. The Kruskal-Wallis H test was used for comparison of non-normally distributed continuous data between groups， and the chi-square test was used for comparison of categorical data between groups. A multivariate Logistic regression analysis was used to identify the clinical features significantly associated with TCM syndrome. ResultsThe cluster analysis identified three core TCM syndromes among the 275 patients with ICP， i.e.， liver-gallbladder damp-heat syndrome （45.8%）， syndrome of blood deficiency generating wind （30.9%）， and liver depression and spleen deficiency syndrome （23.3%）. There was a significant difference in the distribution of TCM syndromes between different groups stratified by maternal age at delivery， parity， history of ICP recurrence， gestational weeks at disease onset， total bile acid （TBA）， alanine aminotransferase （ALT）， and comorbidity with gestational diabetes mellitus （GDM） （all P<0.05）. The multivariate Logistic regression analysis showed that<34 gestational weeks at disease onset was significantly associated with all three syndromes （damp-heat： odds ratio ［OR］=3.769， P<0.001； blood deficiency： OR=4.031， P<0.001； liver stagnation： OR=3.552， P<0.001）. Liver-gallbladder damp-heat syndrome was associated with maternal age ≥35 years at disease onset （OR=2.048， P=0.014）， parity ≥2 times （OR=1.921， P=0.034）， history of ICP recurrence （OR=2.404， P=0.030）， ALT ≥200 U/L （OR=2.051， P=0.018）， comorbidity with GDM （OR=1.944， P=0.029）， and TBA ≥40 μmol/L （OR=2.542， P=0.024）. The syndrome of blood deficiency generating wind syndrome was associated with maternal age ≥35 years （OR=2.939， P=0.003）， parity ≥2 time （OR=3.222， P=0.003）， history of ICP recurrence （OR=3.809， P=0.010）， ALT ≥200 U/L （OR=2.889， P=0.006）， comorbidity with GDM （OR=3.711， P=0.001）， and comorbidity with hypertensive disorders of pregnancy （OR=4.472， P=0.011）. Liver depression and spleen deficiency syndrome was associated with TBA ≥40 μmol/L （OR=2.995， P=0.044）. The analysis of perinatal outcomes showed that there were significant differences in mode of delivery， gestational weeks at the time of delivery， postpartum blood loss， and neonatal birth weight between the three groups with different TCM syndromes （all P<0.05）. ConclusionLiver-gallbladder damp-heat syndrome， syndrome of blood deficiency generating wind， and liver depression and spleen deficiency syndrome are the main TCM syndrome types in ICP， and the distribution of TCM syndromes is closely associated with clinical factors and perinatal outcomes， which provides a basis for precise TCM syndrome differentiation and individualized treatment.

Endometriosis (EMS) is a chronic systemic disease prevalent in women of reproductive age. The signs and symptoms of this disease are not specific, and the severity of the disease varies, leading to clinical heterogeneity, which increases the difficulty of diagnosis. It seriously affects the quality of life of patients and also occupies a large amount of social health resources. Artificial intelligence (AI) refers to the ability of a computer technology to enable machines to simulate human intelligence, including perception, learning, reasoning, decision making and language understanding. AI serves as a powerful data-mining tool capable of processing large amounts of medical data and diagnosing, managing, and treating patients according to their specific conditions. Especially in the diagnostic process of EMS, the use of AI can improve the detection rate and shorten the diagnostic time while increasing the diagnostic sensitivity and specificity. In this paper, we provide an overview of the application of medical big data and AI to the diagnosis and treatment of EMS in order to provide new aids to further improve diagnostic efficiency and therapeutic efficacy.

Objective:To establish a rapid quantitative model for the determination of moisture,extractives,and content in Pollen Typhae.Methods:Near-infrared spectra of 91 batches of Pollen Typhae samples were collected.Spectral preprocessing was performed using S-G,MSC,SNV,and CWT methods.Variable selection was conducted using CARS,SPA,and VIP methods,and compared with full-spectrum modeling.Partial least squares(PLS)mod-els were established for the quantitative determination of moisture,total ash,extractives,and content.The model performance was evaluated by calculating the coefficient of determination for the calibration set and validation set(R2 c,R2v),root mean square error of calibration and validation(RMSEc,RMSEv),and residual prediction devia-tion(RPD).Results:The PLS models for moisture,extractives,and content in Pollen Typhae showed R2c and R2v values greater than 0.9,RMSEc and RMSEv values approaching 0,and RPD values greater than 3.Conclusion:In this study,near-infrared spectroscopy was used to construct quantitative prediction models for moisture,extractives,typhaneoside,and isorhamnetin-3-O-neohesperidoside content in Pollen Typhae.This method enables rapid detection of the main quality control indicators of Pollen Typhae,providing strong technical support for its quality supervision.

Objective To investigate the ameliorative effects and mechanisms of six types of tea(green tea,cyan tea,red tea,white tea,black tea and yellow tea)on metabolic disorders in obesity mice induced by high-fat diet(HFD).Methods Four-week-old male C57BL/6J mice were randomly divided into 8 groups with 7 mice per group.An HFD-induced obese mouse model was established,and the mice in control group maintained on standard diet followed by intragastric administration of different teas for 5 weeks.The body weight,liver weight ratio,fasting blood glucose,and lipid profile of the mice were measured to assess glucose and lipid metabolism.Serum inflammatory factors including IL-6,tumor necrosis factor-alpha(TNF-α)and oxidative stress markers[malondialdehyde(MDA)and superoxide dismutase(SOD)were measured.Additionally,liver histopathology and the expression of key glycolipid metabolism-related genes,adenosine monophosphate-activated protein kinase(AMPK)and carnitine palmitoyltransferase 1(CPT-1),were analyzed to explore underlying mechanisms.Results Cyan tea significantly suppressed weight gain,demonstrating superior weight control.White tea markedly reduced fasting blood glucose levels and decreased the area under the curve of oral glucose tolerance test(OGTT)and insulin tolerance test(ITT),indicating synergistic improvements in glucose metabolism and insulin sensitivity.Yellow tea exhibited exceptional anti-inflammatory and antioxidant effects,reducing hepatic IL-6 and MDA while enhancing SOD activity.Green tea activated the lipid oxidation pathway by upregulating AMPK/CPT-1 expression.All kinds of tea significantly attenuated hepatic lipid droplet accumulation.Conclusion All six types of tea alleviated metabolic disorders by reducing hepatic fat content in obesity mice.However,different types of tea exert their unique effects on improving metabolic disorders through differential mechanisms such as glucose metabolism regulation,lipid oxidation,and anti-inflammatory and antioxidant actions.

Objective To investigate the ameliorative effects and mechanisms of six types of tea(green tea,cyan tea,red tea,white tea,black tea and yellow tea)on metabolic disorders in obesity mice induced by high-fat diet(HFD).Methods Four-week-old male C57BL/6J mice were randomly divided into 8 groups with 7 mice per group.An HFD-induced obese mouse model was established,and the mice in control group maintained on standard diet followed by intragastric administration of different teas for 5 weeks.The body weight,liver weight ratio,fasting blood glucose,and lipid profile of the mice were measured to assess glucose and lipid metabolism.Serum inflammatory factors including IL-6,tumor necrosis factor-alpha(TNF-α)and oxidative stress markers[malondialdehyde(MDA)and superoxide dismutase(SOD)were measured.Additionally,liver histopathology and the expression of key glycolipid metabolism-related genes,adenosine monophosphate-activated protein kinase(AMPK)and carnitine palmitoyltransferase 1(CPT-1),were analyzed to explore underlying mechanisms.Results Cyan tea significantly suppressed weight gain,demonstrating superior weight control.White tea markedly reduced fasting blood glucose levels and decreased the area under the curve of oral glucose tolerance test(OGTT)and insulin tolerance test(ITT),indicating synergistic improvements in glucose metabolism and insulin sensitivity.Yellow tea exhibited exceptional anti-inflammatory and antioxidant effects,reducing hepatic IL-6 and MDA while enhancing SOD activity.Green tea activated the lipid oxidation pathway by upregulating AMPK/CPT-1 expression.All kinds of tea significantly attenuated hepatic lipid droplet accumulation.Conclusion All six types of tea alleviated metabolic disorders by reducing hepatic fat content in obesity mice.However,different types of tea exert their unique effects on improving metabolic disorders through differential mechanisms such as glucose metabolism regulation,lipid oxidation,and anti-inflammatory and antioxidant actions.

Objective:To investigate the effects of marathon exercise on knee cartilage volume and T2 relaxation time (T2 value) based on MRI.Methods:From December 2018 to December 2021, 25 healthy volunteers without long-distance running habits and 32 non-professional marathon runners with long-term long-distance running were recruited to undergo knee MRI 3D water-selective excitation (three dimensional water-selective excitation, 3D-WATS) and T2 mapping imaging were performed, and the cartilage volumes in 5 knee areas and T2 values in 42 subareas were extracted for analysis. To compare the cartilage volume and its ratio to body surface area of knee joint of healthy volunteers and non-professional marathon runners, the T2 value of cartilage in each subregion, and the correlation between marathon exercise intensity and the volume and T2 value of cartilage in different regions.Results:Compared with healthy volunteers, there was no significant difference in cartilage volume or the ratio of body surface area to body volume of non-professional marathon runners ( P>0.05). There were significant differences between healthy volunteers and non-professional marathon runners in cartilage T2 values of the median layer of medial condyle of femur (47.61±5.65 ms and 44.29±6.10 ms) and the deep layer of medial condyle of femur (36.82±9.05 ms and 31.67±7.59 ms), deep precondylar area of medial femur (38.37±4.68 ms and 34.09±4.19 ms), shallow area of medial condylar area of femur (52.17±11.11 ms and 45.51±7.76 ms), middle layer of medial condylar area of femur (49.09±5.08 ms and 45.63±5.04 ms), medial layer of anterior condylar region of lateral femur (45.69±4.68 ms and 42.57±5.77 ms), superficial layer of posterior condylar region of lateral femur (55.42±18.41 ms and 47.99±8.39 ms), deep layer of anterior tibial medial plateau (33.40±7.76 ms and 29.03±5.69 ms), deep layer of posterior tibial medial plateau (31.28±5.02 ms and 27.92±5.99 ms), deep layer of patellofemoral surface (35.65±6.99 ms and 32.30±5.28 ms), respectively ( P<0.05). In non-professional marathon runners, the medial tibial plateau cartilage volume was negatively correlated with step frequency ( r=-0.371, P=0.035), the lateral femoral condylar cartilage volume was negatively correlated with step frequency ( r=-0.365, P=0.043), and the lateral tibial plateau cartilage volume was negatively correlated with step frequency ( r=-0.550, P=0.001). The T2 value of the medial layer cartilage in the anterior tibial medial plateau region was negatively correlated with body weight ( r=-0.277, P=0.039) and body mass index ( r=-0.290, P=0.030). The T2 value of the superficial layer of patellofemoral surface was negatively correlated with the amount of running in 3 months ( r=-0.457, P=0.010). The superficial T2 value in the posterior lateral plateau of the tibia was negatively correlated with stride length ( r=-0.437, P=0.014), and the medial layer cartilage T2 value in the anterior condylar area of the lateral femur was negatively correlated with stride frequency ( r=-0.380, P=0.035). Conclusion:Marathon exercise had little effect on the knee cartilage volume, but had a certain effect on the cartilage T2 value, resulting in changes in cartilage structure. The higher the step frequency, the smaller the cartilage volume. The greater the body weight or body mass index, the greater the amount of running in 3 months, and the greater the stride length, the lower the cartilage T2 value.

Objective To observe the efficacy and safety of Morinda officinalis oligosaccharides in the continuation treatment of mild and moderate depression.Methods An open,single-arm,multi-center design was adopted in our study.Adult patients with mild and moderate depression who had received acute treatment of Morinda officinalis oligosaccharides were enrolled and continue to receive Morinda officinalis oligosaccharides capsules for 24 weeks,the dose remained unchanged during continuation treatment.The remission rate,recurrence rate,recurrence time,and the change from baseline to endpoint of Hamilton Depression Scale(HAMD),Hamilton Anxiety Scale(HAMA),Clinical Global Impression-Severity(CGI-S)and Arizona Sexual Experience Scale(ASEX)were evaluated.The incidence of treatment-related adverse events was reported.Results The scores of HAMD-17 at baseline and after treatment were 6.60±1.87 and 5.85±4.18,scores of HAMA were 6.36±3.02 and 4.93±3.09,scores of CGI-S were 1.49±0.56 and 1.29±0.81,scores of ASEX were 15.92±4.72 and 15.57±5.26,with significant difference(P＜0.05).After continuation treatment,the remission rate was 54.59％(202 cases/370 cases),and the recurrence rate was 6.49％(24 cases/370 cases),the recurrence time was(64.67±42.47)days.The incidence of treatment-related adverse events was 15.35％(64 cases/417 cases).Conclusion Morinda officinalis oligosaccharides capsules can be effectively used for the continuation treatment of mild and moderate depression,and are well tolerated and safe.

Objective To study the clinical manifestations,laboratory features,and labial gland pathological features in children with systemic lupus erythematosus(SLE)complicated by Sj?gren's syndrome(SS).Methods A retrospective analysis was conducted on 102 children with SLE who underwent labial gland biopsies at Renji Hospital,Shanghai Jiao Tong University School of Medicine from January 2013 to December 2022.The children were divided into two groups based on the presence of SS:the SLE with SS group(SLE-SS;60 children)and the SLE-only group(42 children).According to the focus score(FS)of the labial glands,children in the SLE-SS group were further subdivided into FS≥4 subgroup(26 children)and FS<4 subgroup(34 children).The clinical data of the groups were compared.Results Compared to the SLE-only group,children in the SLE-SS group had less skin and mucosal involvement,were more likely to have positive anti-SSA and anti-SSB antibodies,and had higher levels of rheumatoid factor(P<0.05).There was no significant difference in treatment protocols between the two groups(P>0.05).Compared to the FS<4 subgroup,the FS≥4 subgroup had more frequent musculoskeletal involvement(P<0.05),but there was no significant difference in SLE disease activity or other major organ involvement between the subgroups(P>0.05).Conclusions Children with SLE complicated by SS are less likely to have skin and mucous membrane involvement and exhibit specific serological characteristics.The SLE-SS children with an FS≥4 are more likely to experience musculoskeletal involvement.However,FS is not associated with disease activity or other significant organ damage.