ObjectiveTo investigate the inhibitory effect of Huoluo Xiaolingdan on triple negative breast cancer （TNBC） in mice through its regulation of TCF1⁺CD8⁺ stem cell-like T cells infiltration. MethodsA mouse model of TNBC was established and the mice were randomly divided into the model group， low-dose （3.9 g·kg^-1）， medium-dose （7.8 g·kg^-1） and high-dose （15.6 g·kg^-1） Huoluo Xiaolingdan groups， and anti-PD-1 antibody treatment group. Each group was given a dose of 0.01 mL·g^-1， while the model group and the anti-PD-1 treatment group were also given an equivalent volume of normal saline. The drug was administered for 21 days. In the anti-PD-1 antibody group， mice were intraperitoneally injected with 100 μg of mouse anti-PD-1 antibody twice a week， for a total of five injections. The tumor volume， survival time and tumor mass were measured at different time points. Hematoxylin-eosin （HE） staining was used to observe the histological changes of the tumor. The expression of CD8⁺T cells and TCF1⁺CD8⁺ stem-like T cells in tumor tissues was detected by immunohistochemistry and immunofluorescence staining. Flow cytometry was used to detect the difference of immune cell subsets in tumors and the expression difference of TCF1⁺CD8⁺ stem cell-like T cells in tumors and peripheral blood. The expression level of PD-L1 in tumor tissues was detected by Western blot. ResultsCompared with model group， the tumor volume and mass of in low-， medium- and high-dose Huoluo Xiaolingdan groups and anti-PD-1 group were decreased （P<0.05， P<0.01）. The median survival time of mice in low-， medium- and high-dose Huoluo Xiaolingdan groups and anti-PD-1 group was as follows： 27.00 days （95%CI， 0.45-2.65）， 31.00 days （95%CI， 0.32-1.89）， 34.00 days （95%CI， 0.40-2.33）， and 35.00 days （95%CI， 0.42-2.47）. All of them were higher than that of the model group ［24.50 days （95%CI， 0.37-10.5）］. Flow cytometry showed that compared with the model group， the proportion and number of infiltrating CD8⁺ T cells in tumor were increased in low-， medium- and high-dose Huoluo Xiaolingdan groups and anti-PD-1 group （P<0.05， P<0.01）， while the proportion of tumor regulatory T cells （Treg） and M2 macrophages decreased （P<0.05）. Compared with the model group， the proportion of IFN-γ⁺CD8⁺ T and GrzB⁺CD8⁺ T cells in tumors in low-， medium- and high-dose Huoluo Xiaolingdan groups and anti-PD-1 group was increased （P<0.01）， and the proportion of TCF1⁺CD8⁺ T cells in tumor and peripheral blood was also increased. Immunofluorescence staining further showed that the number of TCF1⁺CD8⁺ T cells in tumor tissues increased in low-， medium- and high-dose Huoluo Xiaolingdan groups. Western blot analysis showed no significant decrease in the PD-L1 protein expression in tumor tissues between the Huoluo Xiaolingdan groups and the model group. ConclusionHuoluo Xiaolingdan can inhibit TNBC in mice by increasing tumor infiltration of TCF1⁺CD8⁺ stem-like T cells， enhancing CD8⁺ T cell activity， and regulating immune cell subgroups such as M2 macrophages and Treg cells to enhance anti-tumor immunity. This study provides a theoretical basis for the clinical application of Huoluo Xiaolingdan in breast cancer treatment and combination therapy.

ObjectiveTo investigate the regulatory effect of icariin （ICA） on transforming growth factor-β₁ （TGF-β₁）/Smad pathway in bone microvascular endothelial cells （BMECs） and the effect on autophagy in BMECs. MethodsBMECs were isolated and cultured， and the cell types were identified by immunofluorescence. Cells were divided into the control group， model group （0.1 g·L^-1 methyl prednisolone）， ICA group （0.1 g·L^-1 methyl prednisolone +1×10^-5 mol·L^-1 ICA）， and TGF-β inhibitor group （0.1 g·L^-1 methyl prednisolone +1×10^-5 mol·L^-1 ICA +1×10^-5 mol·L^-1 LY2157299）. Transmission electron microscopy was used to observe the ultrastructure and autophagosome number of BMECs. Autophagy double-standard adenovirus was used to monitor the confocal autophagy flow generation of each cell. Real-time quantitative polymerase chain reaction （Real-time PCR） and Western blot were used to detect the gene and protein expression of autophagy in the TGF-β₁/ Smad pathway. ResultsAfter cell separation culture， platelet endothelial cell adhesion molecule （CD31） and von willebrand factor （vWF） immunofluorescence identified BMECs. Transmission electron microscopy showed that the cell membrane was damaged， and the nucleus was pyknotic and broken in the model group. Compared with the model group， the ICA group had complete cell membranes， clear structures， with autophagy-lysosome sparsely distributed. The confocal photo showed that BMECs had autophagosomes and autophagy-lysosomes， and the autophagy expression of the ICA group was similar to that of the blank group. Compared with the blank group， in the model group and the LY2157299 group， autophagosomes and autophagy-lysosomes were barely seen in the autophagy flow. Compared with the blank group， the mRNA and protein expressions of autophagy effector protein 1 （Beclin1） and microtubule-associated protein 1 light chain 3B （LC3B） in the model group were significantly decreased （P<0.01）， and those of ubiquitin-binding protein （p62） were significantly increased （P<0.01）. The mRNA expression of TGF-β₁， Smad homolog 2 （Smad2）， and Smad homolog 3 （Smad3） decreased （P<0.05， P<0.01）. The protein expressions of TGF-β₁， p-Smad2， and p-Smad3 were significantly decreased （P<0.01）. Compared with those of the model group， the mRNA and protein expression of Beclin1 and LC3B in BMECs of the ICA group increased （P<0.01）， and those of p62 significantly reduced （P<0.01）. The mRNA expression of TGF-β₁， Smad2， and Smad3 increased significantly （P<0.01）. The protein expression of TGF-β₁， p-Smad2， and p-Smad3 increased significantly （P<0.01）. Compared with those in the model group， the mRNA and protein expressions of Beclin1， LC3B， and p62 in the inhibitor group were not statistically significant. The expression of key genes and proteins of the TGF-β₁ pathway in the inhibitor group was not statistically significant. ConclusionICA can promote glucocorticoid-induced autophagy expression of BMECs， and its mechanism may be related to activating the TGF-β₁/Smad signaling pathway.

Objective: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for fullfield digital mammography (FFDM) when applied to synthetic mammography (SM). Materials and Methods: We analyzed 501 women (mean age, 57 ± 11 years) who underwent preoperative mammography and breast cancer surgery. This cohort consisted of 1002 breasts, comprising 517 with cancer and 485 without. All patients underwent digital breast tomosynthesis (DBT) and FFDM during the preoperative workup. The SM is routinely reconstructed using DBT. Commercial AI-CAD (Lunit Insight MMG, version 1.1.7.2) was retrospectively applied to SM and FFDM to calculate the abnormality scores for each breast. The median abnormality scores were compared for the 517 breasts with cancer using the Wilcoxon signed-rank test. Calibration curves of abnormality scores were evaluated. The discrimination performance was analyzed using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 10% preset threshold. Sensitivity and specificity were further analyzed according to the mammographic and pathological characteristics.The results of SM and FFDM were compared. Results: AI-CAD demonstrated a significantly lower median abnormality score (71% vs. 96%, P < 0.001) and poorer calibration performance for SM than for FFDM. SM exhibited lower sensitivity (76.2% vs. 82.8%, P < 0.001), higher specificity (95.5% vs.91.8%, P < 0.001), and comparable AUC (0.86 vs. 0.87, P = 0.127) than FFDM. SM showed lower sensitivity than FFDM in asymptomatic breasts, dense breasts, ductal carcinoma in situ, T1, N0, and hormone receptor-positive/human epidermal growth factor receptor 2-negative cancers but showed higher specificity in non-cancerous dense breasts. Conclusion AI-CAD showed lower abnormality scores and reduced calibration performance for SM than for FFDM.Furthermore, the 10% preset threshold resulted in different discrimination performances for the SM. Given these limitations, off-label application of the current AI-CAD to SM should be avoided.

Root caries is a prevalent chronic oral disease with an average global prevalence of 41.5%, characterized by high incidence, low rate of treatment, and high rate of retreatment. Root caries is primarily caused by core microbiome-induced dysbiosis and has multiple risk factors, including gingival recession, root surface exposure, and salivary dysfunction. The traditional preventive measures and treatments such as fluoride, mineralizing agents, and restorative materials, are unable to restore or maintain oral microecological homeostasis. Recent studies have demonstrated that probiotics, prebiotics, synbiotics, and antimicrobial peptides may prevent and treat root caries by reversing dysbiosis. In addition, these biotherapeutics can reduce acid production by acidiferous bacteria, promote alkali production (hydrogen peroxide and ammonia) by alkali-producing bacteria, inhibit biofilm formation, decrease extracellular polysaccharide production, and suppress microbial adhesion and aggregation. It is expected to play an important role in the prevention and control of root caries. This article aims to review oral probiotics (Streptococcus oligofermentans, Streptococcus oralis subsp. dentisani, and Streptococcus salivarius), prebiotics (arginine, nitrates, and synthetic compounds), synbiotics, and antimicrobial peptides (gallic acid-polyphemusin I and LH12) to provide evidence and guidance for root caries management through microecological modulation.

Objective To explore the risk factors for postoperative respiratory failure (RF) in patients with esophageal cancer, construct a predictive model based on the least absolute shrinkage and selection operator (LASSO)-logistic regression, and visualize the constructed model. Methods A retrospective analysis was conducted on patients with esophageal cancer who underwent surgical treatment in the Department of Thoracic Surgery, Sun Yat-sen University Cancer Center Gansu Hospital from 2020 to 2023. Patients were divided into a RF group and a non-RF (NRF) group according to whether RF occurred after surgery. Clinical data of the two groups were collected, and LASSO-logistic regression was used to optimize feature selection and construct the predictive model. The model was internally validated by repeated sampling 1000 times based on the Bootstrap method. Results A total of 217 patients were included, among which 24 were in the RF group, including 22 males and 2 females, with an average age of (63.33±9.10) years; 193 were in the NRF group, including 161 males and 32 females, with an average age of (62.14±8.44) years. LASSO-logistic regression analysis showed that the percentage of forced expiratory volume in one second/forced vital capacity (FEV1/FVC) to predicted value (FEV1/FVC%pred) [OR=0.944, 95%CI (0.897, 0.993), P=0.026], postoperative anastomotic fistula [OR=4.106, 95%CI (1.457, 11.575), P=0.008], and postoperative lung infection [OR=3.776, 95%CI (1.373, 10.388), P=0.010] were risk factors for postoperative RF in patients with esophageal cancer. Based on the above risk factors, a predictive model was constructed, with an area under the receiver operating characteristic curve of 0.819 [95%CI (0.737, 0.901)]. The Hosmer-Lemeshow test for the calibration curve showed that the model had good goodness of fit (P=0.527). The decision curve showed that the model had good clinical net benefit when the threshold probability was between 5% and 50%. Conclusion FEV1/FVC%pred, postoperative anastomotic fistula, and postoperative lung infection are risk factors for postoperative RF in patients with esophageal cancer. The predictive model constructed based on LASSO-logistic regression analysis is expected to help medical staff screen high-risk patients for early individualized intervention.

With the completion of the "Human Genome Project" and the smooth progress of the "Herbal Genome Project", the research wave of RNAomics is gradually advancing, opening the research gateway for the modernization of traditional Chinese medicine (TCM) and initiating the post-genome era of medicinal plant RNA research. Therefore, this article proposes for the first time the concept of HerbRNomes, which involves constructing databases of medicinal plant, medicinal fungus, and medicinal animal RNA at different stages, from different origins, and in different organs. This research aims to explore the role of HerbRNA in self-genetic information transmission, functional regulation, as well as cross-species regulation functional mechanisms and key technologies. It also investigates application scenarios, providing a theoretical basis and research ideas for the resistance of TCM or medicinal plants to adversity and stress, molecular assistant breeding, and the development of small nucleic acid drugs. This article reviews recent research progress in elucidating the molecular mechanisms of the transmission and expression of genetic information, self-regulation and cross-species regulation of herbs at the RNA level, along with key technologies. It proposes a development strategy for small nucleic acid drugs based on HerbRNomes, providing theoretical support and guidance for the modernization of TCM based on HerbRNomes research.

ObjectiveTo observe the clinical effectiveness and safety of Xiaozhong Zhitong Mixture （消肿止痛合剂） combined with antibiotic bone cement in the treatment of diabetic foot ulcer （DFU） with damp-heat obstructing syndrome. MethodsA total of 72 DFU patients with damp-heat obstructing syndrome were randomly assigned to treatment group （36 cases） and the control group （36 cases）. Both groups received standard treatment and topical antibiotic bone cement for ulcer wounds， while the treatment group received oral Xiaozhong Zhitong Mixture （50 ml per time， three times daily） in additionally. Both groups underwent daily wound dressing changes for 21 consecutive days. Ulcer healing rate， serum levels of tumor necrosis factor-alpha （TNF-α）， interleukin-1 beta （IL-1β）， malondialdehyde （MDA）， superoxide dismutase （SOD）， C-reactive protein （CRP）， and white blood cell （WBC） count were observed before and after treatment， and visual analog scale （VAS） scores for wound pain， traditional Chinese medicine （TCM） syndrome scores， and the DFU Healing Scale （DMIST scale） were also compared. Liver and kidney function were evaluated before and after treatment， and adverse events such as allergic reactions， worsening ulcer pain were recorded. ResultsTotally 35 patients in the treatment group and 33 in the control group were included in the final analysis. The ulcer healing rate in the treatment group was （87.93±9.34）%， significantly higher than （81.82±12.02）% in the control group （P = 0.035）. Compared to pre-treatment levels， both groups showed significant reductions in serum CRP， WBC， MDA， IL-1β， and TNF-α levels， with an increase in SOD level （P＜0.05）. TCM syndrome scores， VAS， and DMIST scores also significantly decreased in both groups （P＜0.05）， with greater improvements in the treatment group （P＜0.05）. No significant adverse reactions were observed in either group during treatment. ConclusionXiaozhong Zhitong Mixture combined with antibiotic bone cement has significant advantages in promoting DFU healing， reducing inflammatory response， and alleviating oxidative stress in DFU patients with damp-heat obstructing syndrome， with good safety for DFU patients with damp-heat obstructing syndrome.

ObjectiveTo investigate the differences in efficacy and endogenous metabolic mechanisms of Anmeidan with combined use of raw and fried Ziziphi Spinosae Semen and its disassembled prescriptions in treating anxiety and cognitive impairment in insomnia rats. MethodsSixty rats were randomly divided into six groups （n=10 per group）： blank group， model group， suvorexant group （30 mg·kg^-1）， Anmeidan group （9.09 g·kg^-1）， Anmeidan with absence of raw Ziziphi Spinosae Semen group （7.38 g·kg^-1）， and Anmeidan with absence of fried Ziziphi Spinosae Semen group （7.38 g·kg^-1）. An insomnia model was constructed by intraperitoneal injection of para-chlorophenylalanine （PCPA）， followed by gavage administration of Anmeidan or its disassembled prescriptions. Anxiety levels were assessed using the open field test， while cognitive ability was evaluated via the novel object recognition test. The pathological morphology of hippocampal neurons was examined using electron microscopy. Serum samples were analyzed by ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry （UPLC-Q-TOF-MS） for principal component analysis， metabolic profiling， identification of differential metabolites， and metabolic pathway analysis. ResultsCompared with the blank group， the model group exhibited significantly increased exercise mileage， exercise time， and the ratio of the number of entries into the peripheral zone to the total number of entries into both the peripheral and central zones exhibited a marked increase （P<0.05， P<0.01）， while the novel object recognition index significantly decreased （P<0.05）. Compared with the model group， the Anmeidan and suvorexant groups showed significantly reduced exercise mileage and exercise time （P<0.01）. The ratio of the number of entries into the peripheral zone to the total number of entries into both the peripheral and central zones decreased （P<0.05）， and a significant increase in the novel object recognition index （P<0.01）. However， the disassembled prescription groups showed no significant improvement in open field test and novel object recognition test indices. Electron microscopy revealed that the Anmeidan group improved the pathological morphology of hippocampal neurons in insomnia rats. Metabolomics analysis identified 10 potential differential metabolites associated with Anmeidan's therapeutic effects， involving metabolic pathways related to phenylalanine and tryptophan biosynthesis and metabolism， as well as the serotonergic pathway. ConclusionThe combined use of raw and fried Ziziphi Spinosae Semen in Anmeidan is more effective than its disassembled prescriptions in alleviating anxiety and cognitive impairment in PCPA-induced insomnia rats. The underlying mechanism may be associated with metabolic pathways related to phenylalanine， tryptophan， and serotonin.

Sleep， skin， and health are closely interconnected. Clinically， insomnia has a high incidence and is often accompanied by or secondary to skin aging. The two conditions exhibit "different diseases with the same syndrome"， significantly affecting the physical and mental health of the Chinese population. Preventing and treating skin aging by improving insomnia is an important strategy， with the principle of "treating different diseases with the same approach" serving as a crucial therapeutic guideline. However， effective clinical prevention and treatment methods for both conditions remain lacking. Traditional Chinese medicine （TCM） has a profound theoretical foundation and notable efficacy in the concurrent treatment of insomnia and skin aging， yet there are few reports on the etiology， pathogenesis， therapeutic principles， and treatment methods of their shared treatment， warranting further exploration. Based on holistic view and syndrome differentiation and treatment in TCM， this study systematically investigates the theoretical origins of the shared manifestations of insomnia and skin aging from multiple dimensions， including etiology， pathological location， pathogenesis， disease nature， and prevention and treatment strategies. As early as Huangdi's Internal Classic （Huangdi Neijing）， it was recognized that mental clarity during the day， sound sleep at night， and firm， healthy skin are key indicators of external health， whereas daytime lethargy， poor sleep quality， and dry， withered skin are prominent signs of aging. Maintaining mental clarity during the day and restful sleep at night is essential for skin integrity and healthy aging. Later medical scholars proposed that the common etiology of insomnia and skin aging lies in "internal-external interactions"， with the pathological location involving "the five organ systems". The primary pathogenesis includes "deficiency， fire， stagnation， phlegm， and blood stasis"， while the disease nature is often characterized by "a combination of deficiency and excess". Treatment should be guided by syndrome differentiation， following the principle of balancing Yin and Yang. This theoretical exploration enriches and advances TCM understanding of disease onset and prevention， providing theoretical guidance for the clinical prevention and treatment of insomnia-associated skin aging and contributing to the realization of the "Healthy China" initiative.

OBJECTIVE To construct and evaluate nomogram prediction model for refractory chemotherapy-induced nausea and vomiting （CINV）. METHODS The data of malignant tumor patients who received chemotherapy at the Third People’s Hospital of Zhengzhou from January 2017 to December 2023 were collected. These patients were categorized into the occurrence group and the non-occurrence group according to the occurrence of refractory CINV. Multivariate Logistic regression analysis was employed to screen predictive factors for refractory CINV and constructing a nomogram prediction model. Model performance was assessed via receiver operating characteristic curve analysis. Model calibration was evaluated using Bootstrap resampling. Decision curve analysis （DCA） was used to determine the clinical net benefit of three strategies under different risk thresholds. Clinical impact curves were utilized to assess the clinical value of the model at different risk thresholds. Shapley additive explanations （SHAP） analysis was performed to evaluate individual factor contributions to the predictive model. RESULTS A total of 388 patients were included， with 219 experiencing refractory CINV. Multivariate Logistic regression identified 11 predictive factors for refractory CINV， including gastrointestinal disease history， anticipated nausea and vomiting， chemotherapy-induced emetic risk classification， and electrolyte levels， etc. The model’s area under the curve was 0.80 [95% confidence interval （0.76， 0.84）]， with a mean error of 0.036. DCA demonstrated the prediction model had higher clinical net benefit when the risk threshold was between 0.05 and 0.85. SHAP analysis revealed the top three predictive factors as gastrointestinal disease history （0.924）， chemotherapy- induced emetic risk classification （0.866）， and electrolyte levels （0.581）. CONCLUSIONS Eleven factors， including gastrointestinal disease history， anticipated nausea and vomiting， chemotherapy-induced emetic risk classification， and electrolyte levels， are identified as predictors of refractory CINV. The model based on these factors has good predictive ability， which can be used to predict the risk of refractory CINV.