Colorectal cancer （CRC） is one of the most common cancers， with its incidence ranking high among cancers. It stands as the second leading cause of cancer-related death worldwide. In the early stages， CRC lacks specific symptoms， and most patients are diagnosed at advanced stages， making it a major research focus in the field of gastrointestinal tumors. Currently， clinical CRC treatments face several common challenges， including high surgical risks， frequent metastasis and recurrence， drug resistance， and significant side effects from chemotherapy and radiation therapy. With the development and application of traditional Chinese medicine （TCM）， it has been found that TCM and its active ingredients can effectively inhibit CRC cell proliferation， invasion， migration， and angiogenesis， and promote apoptosis and autophagy， thereby slowing the progression of CRC. This has become a key focus of CRC treatment research. Salvia Miltiorrhiza has multiple pharmacological effects， including activating blood circulation to dispel blood stasis， unlocking meridians to relieve pain， clearing heat to calm irritability， and cooling blood to reduce abscesses. It contains a variety of chemical components， including diterpenoids， phenolic acids， flavonoids， polysaccharides， nitrogen-containing compounds， steroids， and lactone compounds. This review summarized the molecular mechanisms of Salvia miltiorrhiza and its active ingredients in the treatment of CRC. It is found that these ingredients exert anti-CRC effects through various molecular mechanisms， including cell cycle arrest， promotion of apoptosis， inhibition of cell invasion and migration， induction of autophagy， suppression of tumor angiogenesis， and remodeling of the tumor microenvironment. The review aims to provide new insights for the drug development and clinical application of Salvia miltiorrhiza in CRC treatment.

ObjectiveTo explore the relationship between acne vulgaris and gut microbiota. MethodsA total of 29 clinical cases diagnosed with moderate-to-severe acne vulgaris and 26 healthy individuals as control subjects were recruited. Fecal specimens were collected from all participants， and further analysis of gut microbial communities was performed by leveraging high-throughput sequencing techniques that target the hypervariable regions of 16S rRNA genes. ResultsAssociations between acne vulgaris and alterations in gut microbiota were identified. At the phylum level， the relative abundance of Bacteroidota exhibited a statistically significant elevation in the acne vulgaris cohort when compared with the healthy control group （P<0.01）， while Cyanobacteria was significantly lower in the acne group （P<0.01）. At the genus level， the top five different bacterial taxa in both groups were Bacteroides， Escherichia⁃Shigella， Klebsiella， Roseburia， and Parabacteroides. Among them， Bacteroides， Roseburia， and Parabacteroides were more abundant in acne patients. Linear discriminant analysis identified five biomarkers all belonging to the Bacteroidota phylum in the acne and control groups. These biomarkers belong to the phylum Bacteroidetes. ConclusionThere are significant differences in the composition of intestinal microbiota between acne patients and healthy people. Changes in the richness of specific bacterial genera may become new targets for the diagnosis and treatment of acne.

Natural flavonoids have attracted considerable attention owing to their favorable biosafety profiles and multiple pharmacological properties in recent years. Luteolin, a representative flavonoid compound, exhibits anti-inflammatory, antioxidant, anti-angiogenic, and neuroprotective effects in multiple ocular disease models by modulating key signaling pathways, including NF-κB, PI3K/Akt, Nrf2/HO-1, and AGE-RAGE. Accumulating experimental evidence supports the potential application of luteolin in various ocular diseases, including corneal and ocular surface diseases, inflammatory eye diseases, glaucoma, cataract, diabetic retinopathy, and age-related macular degeneration. However, clinical evidence remains limited. This review systematically summarizes research progress on luteolin in ocular diseases over the past five years, analyzes its molecular mechanisms and therapeutic potential, and discusses future directions,so as toprovide a theoretical basis for clinical translation.

ObjectiveTo analyze the infection characteristics of human respiratory syncytial virus (HRSV) among children hospitalized with acute lower respiratory tract infection (ALRTI) in a specialized pediatric hospital in Shanghai, so as to provide evidence-based support for optimizing the prevention and control strategies and clinical diagnosis and treatment of respiratory tract infections in children in this region. MethodsA retrospective analysis was performed to the clinical and etiological data of 29 260 children hospitalized for ALRTI in Shanghai Children’s Hospital from January 2021 to December 2024. HRSV and 12 other common respiratory pathogens were detected with multiplex polymerase chain reaction (PCR) and capillary electrophoresis. Demographic and clinical data were collected for statistical analyses. A total of2 412 cases with positive HRSV were divided into the severe group and the non-severe group. Clinical characteristics between the two groups were compared using the Mann-Whitney U test and the chi- square (χ²) test. Additionally, the related influencing factors of severe HRSV infection were explored. ResultsThe overall positivity rate of HRSV from 2021 to 2024 was 8.24% (2 412/29 260), with statistically significant differences observed across the four years (χ²=389.42, P<0.001). The highest positivity rate was in 2021 (14.76%), with a high prevalence throughout the year. In 2022, when non-pharmaceutical interventions (NPIs) were implemented, the HRSV positivity rate was the lowest (4.93%), with a winter-dominant epidemic pattern. In 2023, after the NPIs were lifted, the HRSV positivity rate showed a slight rebound (8.14%), presenting a double-peak pattern. In 2024, the HRSV positivity rate slightly decreased compared to that in 2023 (6.29%), exhibiting a winter and spring-dominant epidemic pattern. Among the hospitalized children with ALRTI, the HRSV positivity rate in males (8.85%) was higher than that in females (7.51%), and the difference was statistically significant (χ²=17.33, P<0.001). Age distribution showed that 82.26% (1 984/2 412) of HRSV infections occurred in children aged 3 years old and below. Besides, as age increased, the infection rate of HRSV showed a gradually decreasing trend (P<0.001). Among the 2 412 children with HRSV infection, the proportion of severe cases was 22.31% (538/2 412), while the non-severe cases accounted for 77.69% (1 874/2 412). Compared with non-severe cases, severe cases were more frequently presented with high fever, longer duration of wheezing, as well as higher rates of underlying diseases or co-infection with Mycoplasma pneumoniae (P<0.001). ConclusionThe prevalence intensity of HRSV varied yearly from 2021 to 2024. After the removal of NPIs in 2023, a slight rebound with a double-peak epidemic pattern was observed. HRSV remained a common pathogen in children hospitalized for ARLTI, and children aged 3 years old and below constituted the highest proportion for infection. Compared with non-severe cases, those with severe HRSV infections were more prone to presenting with high fever and a longer duration of wheezing. Children with positive HRSV who had underlying diseases or co-infection with Mycoplasma pneumonia were more likely to develop severe conditions.

ObjectiveThis paper aims to explore the risk factors for chronic atrophic gastritis （CAG） with turbidity toxin accumulation syndrome and establish a prediction model. MethodsClinical data of 180 patients with CAG who participated in the "clinical study of Xianglian Huazhuo Particles blocking CAG cancer transformation" of Hebei Sheng Zhong Yi Yuan from July 2021 to March 2022 were collected. After confounding factors were controlled by propensity score matching， patients were divided into a training set （namely dev） and a validation set （namely vad） in a seven to three ratio. The risk factors for CAG with turbidity toxin accumulation syndrome in the training set were investigated by using univariate Logistic regression analysis and least absolute shrinkage and selection operator （namely Lasso） regression algorithms. Subsequently， a model， named model 1se， was developed by using the training set data to predict the risk factors for CAG with turbidity toxin accumulation syndrome. The accuracy of the prediction model was assessed by using various methods， including the receiver operating characteristic （ROC） curve， Hosmer-Lemeshow test （H-L）， calibration plot， and decision curve analysis （DCA）. ResultsAge， body mass index （BMI）， family history of cancer， job and life satisfaction， yellow and greasy fur with slippery pulse， and heavy body sensation were independent risk factors of the model. The prediction model showed excellent predictive value for both the training and validation sets. ConclusionThe established prediction model for CAG with turbidity toxin accumulation syndrome has high discrimination and excellent calibration， which could provide an excellent clinical basis for disease diagnosis and individualized treatment of patients.

ObjectiveThis paper aims to explore the risk factors for chronic atrophic gastritis （CAG） with turbidity toxin accumulation syndrome and establish a prediction model. MethodsClinical data of 180 patients with CAG who participated in the "clinical study of Xianglian Huazhuo Particles blocking CAG cancer transformation" of Hebei Sheng Zhong Yi Yuan from July 2021 to March 2022 were collected. After confounding factors were controlled by propensity score matching， patients were divided into a training set （namely dev） and a validation set （namely vad） in a seven to three ratio. The risk factors for CAG with turbidity toxin accumulation syndrome in the training set were investigated by using univariate Logistic regression analysis and least absolute shrinkage and selection operator （namely Lasso） regression algorithms. Subsequently， a model， named model 1se， was developed by using the training set data to predict the risk factors for CAG with turbidity toxin accumulation syndrome. The accuracy of the prediction model was assessed by using various methods， including the receiver operating characteristic （ROC） curve， Hosmer-Lemeshow test （H-L）， calibration plot， and decision curve analysis （DCA）. ResultsAge， body mass index （BMI）， family history of cancer， job and life satisfaction， yellow and greasy fur with slippery pulse， and heavy body sensation were independent risk factors of the model. The prediction model showed excellent predictive value for both the training and validation sets. ConclusionThe established prediction model for CAG with turbidity toxin accumulation syndrome has high discrimination and excellent calibration， which could provide an excellent clinical basis for disease diagnosis and individualized treatment of patients.

[Objective] To analyze the clinicopathological characteristics of treatment-naive patients with highly suspected prostate cancer (PCa) with prostate-specific antigen (PSA) level ≥20 ng/mL, to provide reference for promoting early screening of PCa. [Methods] A retrospective analysis was conducted on the clinical data of treatment-naive patients with PSA level ≥20 ng/mL, undergoing prostate biopsy for highly suspected PCa at the Department of Urology, Tianjin Medical University Second Hospital during Jan.2013 and Jun.2023. The correlation between patients' age, body mass index (BMI), PSA, prostate volume (PV), prostate cancer-specific antigen density (PSAD), prostate imaging reporting and data system (PI-RADS) score, and International Society of Urological Pathology (ISUP) grade with highly suspected PCa metastasis and PSA stratification were analyzed. [Results] A total of 1778 suspected patients were enrolled. Pathological findings confirmed PCa in 1465 cases (82.4%), with 487(33.2%) diagnosed as metastatic PCa. Over the past decade, the number of patients undergoing prostate biopsy for highly suspected PCa and being confirmed has been increasing annually, with the proportion of metastatic cases remaining at around 30%. Compared with those with PSA level being 20-50 ng/mL, patients with PSA level >50 ng/mL had older age, lower BMI, higher PSAD, higher PI-RADS, higher ISUP, more diverse pathological types, and a higher incidence of metastasis (P<0.05) with lower proportion of urban residents. Additionally, analysis of metastatic PCa cases showed that 46.8%(228/487) had oligometastasis (≤5 metastatic lesions), including 99.0% bone metastasis, 4.1% extraregional lymph node metastasis, and 4.3% other organ metastasis. [Conclusion] Over the past 10 years, there has been a continuous increase in the number of treatment-naive biopsied cases and newly diagnosed cases of highly suspicious PCa with PSA level ≥20 ng/mL, while the proportion of metastatic cases remains high. Therefore, proactive efforts should be made to promote early screening of high-risk suspected cases.

ObjectiveTo explore the possible mechanisms of Modified Shoutai Pill （寿胎丸加味方， MSP） in treating polycystic ovary syndrome （PCOS） with hyperandrogenism， insulin resistance， and miscarriage， focusing on inflammatory response and endometrial receptivity. MethodsThirty female SPF-grade SD rats with regular estrous cycles and in proestrus， and 15 male SPF-grade SD rats were housed together in a 2∶1 ratio at 18：00. At 8：00 next morning， rats showing abundant sperm and vaginal plugs were considered pregnant on the day 0.5. The 30 pregnant rats were randomly divided into three groups， normal group， model group， and MSP group， with 10 rats in each group. From day 0.5 to day 13.5 of pregnancy， the MSP group was given 26.6 g/（kg·d） of the MSP via gavage twice a day for 14 consecutive days. The normal group and the model group received 4 ml of normal saline daily. From day 7.5 to day 13.5 of pregnancy， the rats in the model group and MSP group were intraperitoneally injected with dihydrotestosterone （DHT） and insulin （INS） for 7 consecutive days to establish a PCOS model with hyperandrogenism， insulin resistance， and miscarriage. On day 13.5 of pregnancy， an oral glucose tolerance test （OGTT） was performed to measure blood glucose levels at 0， 30， 60， 90， and 120 minutes. On day 14.5， serum level of progesterone （P₄）， estradiol （E₂）， fasting insulin （FINS）， interleukin-6 （IL-6）， and tumor necrosis factor-alpha （TNF-α） were measured by ELISA. The insulin resistance index （HOMA-IR） was calculated. Embryo implantation， miscarriage rate， and average number of live fetuses were observed. Uterine tissue pathology was examined by HE staining， and mRNA expression of Il-6， Tnf-α， leukemia inhibitory factor （Lif）， homeobox gene 10 （Hoxa10）， prolactin family 8 subfamily A member 2 （Prl8a2）， and insulin-like growth factor-binding protein 1 （Igfbp1） in the uterine tissue was detected by qRT-PCR. ResultsCompared with the normal group， the model group had significantly higher blood glucose level at 0， 30， 60， 90， and 120 minutes， increased miscarriage rate， elevated HOMA-IR， decreased average number of live fetuses， lower level of P₄ and E₂， higher level of IL-6， TNF-α， and FINS， and higher mRNA expression of Il-6 and Tnf-α in the uterine tissue. The mRNA expression of Lif， Hoxa10， and Prl8a2 was reduced （P＜0.05 or P＜0.01）. The uterus had a dark red color， visible areas of bleeding， fewer embryos with developmental abnormalities， and increased placental necrosis. Pathological examination revealed thrombus in the decidual layer， unclear decidual cell morphology， loose arrangement， scattered distribution， edema degeneration in the cytoplasm， and nuclear shrinkage or disappearance， with extensive infiltration of inflammatory cells. In contrast， compared with the model group， the MSP group showed significantly lower blood glucose level at 0， 30， 60， 90， and 120 min， reduced miscarriage rate， lower HOMA-IR， increased number of live fetuses， higher level of P₄ and E₂， and lower level of IL-6， TNF-α， and FINS. The mRNA expression of Il-6 and Tnf-α in the uterine tissue was lower， while the expression of Lif， Hoxa10， and Prl8a2 mRNA was higher （P＜0.05 or P＜0.01）. There was significant improvement in uterine and embryo conditions， as well as in uterine tissue pathology. ConclusionThe MSP can reduce the miscarriage rate in a PCOS model with hyperandrogenism， insulin resistance， and miscarriage. Its mechanism may involve inhibiting inflammation， improving endometrial receptivity， and restoring the defects in endometrial decidualization.

Objective To develop an artificial intelligence (AI)-driven lung cancer database by structuring and standardizing clinical data, enabling advanced data mining for lung cancer research, and providing high-quality data for real-world studies. Methods Building on the extensive clinical data resources of the Department of Thoracic Surgery at Peking Union Medical College Hospital, this study utilized machine learning techniques, particularly natural language processing (NLP), to automatically process unstructured data from electronic medical records, examination reports, and pathology reports, converting them into structured formats. Data governance and automated cleaning methods were employed to ensure data integrity and consistency. Results As of September 2024, the database included comprehensive data from 18 811 patients, encompassing inpatient and outpatient records, examination and pathology reports, physician orders, and follow-up information, creating a well-structured, multi-dimensional dataset with rich variables. The database’s real-time querying and multi-layer filtering functions enabled researchers to efficiently retrieve study data that meet specific criteria, significantly enhancing data processing speed and advancing research progress. In a real-world application exploring the prognosis of non-small cell lung cancer, the database facilitated the rapid analysis of prognostic factors. Research findings indicated that factors such as tumor staging and comorbidities had a significant impact on patient survival rates, further demonstrating the database’s value in clinical big data mining. Conclusion The AI-driven lung cancer database enhances data management and analysis efficiency, providing strong support for large-scale clinical research, retrospective studies, and disease management. With the ongoing integration of large language models and multi-modal data, the database’s precision and analytical capabilities are expected to improve further, providing stronger support for big data mining and real-world research of lung cancer.

In the context of the rapid development of 5G technology， the development of artificial intelligence （AI） in traditional Chinese medicine （TCM） faces new opportunities and challenges. Focusing on how to uphold tradition while innovating in the development of AI in TCM， starting from the current development status of AI in Chinese medicine， including the integration of four diagnostic methods， syndrome differentiation and treatment， auxiliary diagnosis and treatment， research and development of Chinese herbal medicine， prevention and treatment of diseases， knowledge inheritance， and other aspects， this paper discussed the support of policies and technical advancements， as well as development opportunities such as increased demand for health. Regarding machine ethics， data ethics， regulatory review， and other aspects， it also proposed some suggestions that the training algorithm should be improved to assist medical work； data ownership should be clarified to ensure data security； and an AI ethics committee should be set up to improve the review system， aiming to maximize the advantages of smart healthcare and accelerate the modernization of TCM for the benefit of patients and the service of human health.