Objective Objective To analyze the potential spatial factors affecting the genetic differentiation of Oncomelania hupensis robertsoni in Yunnan Province. Methods A total of 13 administrative villages were selected from schistosomiasis-endemic areas of Yunnan Province as O. hupensis snail sampling sites. At least 200 snails were collected in each site, and the spatial variable data of each site were recorded, including longitude, latitude and altitude. Thirty active and Schistosoma japonicum uninfected O. hupensis snails were selected from each sampling site by means of the crawling method and the cercarial shedding method. Genomic DNA was extracted from O. hupensis snails. Following PCR amplification, purification of PCR amplification products and sequencing, the gene sequences of O. hupensis snail samples were spliced and edited using the DNAstar software and the NCBI database to yield the complete mitochondrial sequences of O. hupensis snails at each sampling site, and the mitochondrial genetic distance matrix of O. hupensis robertsoni was calculated at each sampling site. The geographical coordinates of each sampling site were marked using the software ArcGIS 10.2, and the straight-line geographical distance between each sampling site was calculated. The altitude difference, longitude difference and latitude difference between each sampling site were calculated using the Excel software, and the correlation between the mitochondrial genetic distance matrix of O. hupensis robertsoni and each spatial variable matrix was examined by using the Mantel test at 13 sampling sites in Yunnan Province. Results Among the 13 O. hupensis snail sampling sites in Yunnan Province, the largest mitochondrial genetic distance of O. hupensis robertsoni snail populations was seen between Anding Village, Nanjian Yi Autonomous County and Caizhuang Village, Midu County (26.244 2), and the largest geographical distance was seen between Dongyuan Village, Gucheng District and Cangling Village, Chuxiong County (272.64 km). The highest altitude difference was seen between Anding Village, Nanjian Yi Autonomous County and Dongyuan Village, Gucheng District (1 086.10 m), and the largest longitude difference was found between Qiandian Village, Eryuan County and Cangling Village, Chuxiong County (1.86°), while the largest latitude difference was measured between Leqiu Village, Nanjian Yi Autonomous County and Dongyuan Village, Gucheng District (1.81°). In addition, the mitochondrial genetic distance of O. hupensis robertsoni snail populations was positively correlated with altitude at 13 snail sampling sites in Yunnan Province (r = 0.542 8, P < 0.001), and showed no significant correlations with geographical distance (r = 0.093 4, P > 0.05), longitude (r = −0.199 5, P > 0.05) or latitude (r = 0.205 7, P > 0.05). Conclusion Altitude may be a potential spatial factor affecting the genetic differentiation of O. hupensis robertsoni in Yunnan Province.

Chronic pain is a complex condition shaped by long-standing alterations in both physiological and psychological processes. Rather than representing a simple continuation of acute nociceptive signaling, chronic pain is increasingly understood as the outcome of progressive dysregulation within distributed neural systems that govern sensation, affect, motivation, and cognitive control. Neuroimaging and electrophysiological studies indicate that this state is accompanied by extensive plastic changes in deep brain structures and large-scale networks. Beyond well-described central sensitization processes, chronic pain is characterized by disrupted oscillatory rhythms and altered connectivity within large-scale brain networks, including thalamo-cortical circuits and prefrontal-limbic-reward networks. These findings support a conceptual shift from viewing chronic pain as a focal, lesion-driven phenomenon toward recognizing it as a disorder of distributed network pathology. Pharmacological treatments remain central to clinical practice, yet their long-term efficacy is often limited and frequently accompanied by substantial side effects. The ongoing concerns about opioid-related risks and the inadequate therapeutic response in a subset of patients highlight the need for safe, non-pharmacological approaches that can address not only pain but also comorbid disturbances in mood, sleep, and social functioning. Neuromodulation provides a promising path toward mechanism-based and non-pharmacological management of chronic pain by employing physical or chemical stimulation to alter the excitability and synchrony of specific neural populations within central, peripheral, and autonomic systems. While invasive deep brain stimulation demonstrates that targeting deep brain structures can be effective, its clinical application is restricted by surgical risks and cost, highlighting the importance of non-invasive techniques capable of reaching deep targets. Current non-invasive approaches, such as transcranial electric stimulation, are constrained by limited penetration depth and insufficient spatial precision. These limitations hinder reliable engagement of deep regions implicated in pain, including the thalamus and nucleus accumbens, and tend to produce broad, non-specific modulation of cross-network oscillatory activity. Temporal interference (TI) stimulation has emerged as a means of overcoming these obstacles. By delivering interacting high-frequency currents that generate a low-frequency envelope within the head, TI enables focal stimulation of deep targets while minimizing superficial current delivery. Recent multiscale modeling and animal studies indicate that TI exploits the nonlinear rectification properties of neuronal membranes in response to high-frequency carriers, as well as their phase-locked responses to low-frequency envelopes, to generate “peak-focused” electric fields in deep regions under relatively low superficial current loads. Moreover, TI appears to exhibit potential advantages in terms of cell-type selectivity and rhythm-specific engagement, including differential responses across neuronal subtypes and distinct coupling to θ-, β-, and γ-band oscillations. These features suggest a promising avenue for correcting abnormal rhythms and network dynamics that contribute to chronic pain. This review summarizes current knowledge of the neural mechanisms underlying chronic pain and recent advances in TI research. It examines functional disturbances across key pain-related regions and networks, outlines the principles and technical characteristics of TI, and discusses potential deep-brain targets and stimulation strategies relevant to chronic pain. Evidence to date indicates that TI, with its non-invasiveness, tolerability, and capacity for precise deep brain modulation, holds great promise for the management of treatment-resistant chronic pain and may evolve into a new generation of precise and efficient non-pharmacological analgesic strategies.

Chronic pain is a complex condition shaped by long-standing alterations in both physiological and psychological processes. Rather than representing a simple continuation of acute nociceptive signaling, chronic pain is increasingly understood as the outcome of progressive dysregulation within distributed neural systems that govern sensation, affect, motivation, and cognitive control. Neuroimaging and electrophysiological studies indicate that this state is accompanied by extensive plastic changes in deep brain structures and large-scale networks. Beyond well-described central sensitization processes, chronic pain is characterized by disrupted oscillatory rhythms and altered connectivity within large-scale brain networks, including thalamo-cortical circuits and prefrontal-limbic-reward networks. These findings support a conceptual shift from viewing chronic pain as a focal, lesion-driven phenomenon toward recognizing it as a disorder of distributed network pathology. Pharmacological treatments remain central to clinical practice, yet their long-term efficacy is often limited and frequently accompanied by substantial side effects. The ongoing concerns about opioid-related risks and the inadequate therapeutic response in a subset of patients highlight the need for safe, non-pharmacological approaches that can address not only pain but also comorbid disturbances in mood, sleep, and social functioning. Neuromodulation provides a promising path toward mechanism-based and non-pharmacological management of chronic pain by employing physical or chemical stimulation to alter the excitability and synchrony of specific neural populations within central, peripheral, and autonomic systems. While invasive deep brain stimulation demonstrates that targeting deep brain structures can be effective, its clinical application is restricted by surgical risks and cost, highlighting the importance of non-invasive techniques capable of reaching deep targets. Current non-invasive approaches, such as transcranial electric stimulation, are constrained by limited penetration depth and insufficient spatial precision. These limitations hinder reliable engagement of deep regions implicated in pain, including the thalamus and nucleus accumbens, and tend to produce broad, non-specific modulation of cross-network oscillatory activity. Temporal interference (TI) stimulation has emerged as a means of overcoming these obstacles. By delivering interacting high-frequency currents that generate a low-frequency envelope within the head, TI enables focal stimulation of deep targets while minimizing superficial current delivery. Recent multiscale modeling and animal studies indicate that TI exploits the nonlinear rectification properties of neuronal membranes in response to high-frequency carriers, as well as their phase-locked responses to low-frequency envelopes, to generate “peak-focused” electric fields in deep regions under relatively low superficial current loads. Moreover, TI appears to exhibit potential advantages in terms of cell-type selectivity and rhythm-specific engagement, including differential responses across neuronal subtypes and distinct coupling to θ-, β-, and γ-band oscillations. These features suggest a promising avenue for correcting abnormal rhythms and network dynamics that contribute to chronic pain. This review summarizes current knowledge of the neural mechanisms underlying chronic pain and recent advances in TI research. It examines functional disturbances across key pain-related regions and networks, outlines the principles and technical characteristics of TI, and discusses potential deep-brain targets and stimulation strategies relevant to chronic pain. Evidence to date indicates that TI, with its non-invasiveness, tolerability, and capacity for precise deep brain modulation, holds great promise for the management of treatment-resistant chronic pain and may evolve into a new generation of precise and efficient non-pharmacological analgesic strategies.

Objective: To analyze adverse event following immunization(AEFI) with the domestic bivalent human papilloma virus (HPV) vaccine among female students in primary, junior, and senior high schools in Hebei Province from 2022 to 2024, aiming to provide evidence for the vaccination program. Methods: On May 14, 2025, AEFI case data and vaccination data for the domestic bivalent HPV vaccine among female students in primary, junior, and senior high schools in Hebei Province from 2022 to 2024 were collected from the China Disease Control and Prevention Information System and the Hebei Provincial Immunization Program Information Management System, respectively. Statistical analysis was performed by using descriptive and analytical epidemiological methods, with intergroup comparisons conducted by using the Chi square test or Fisher s exact probability test. Results: From 2022 to 2024, a total of 817 900 doses of the domestic bivalent HPV vaccine were administered to female students in primary, junior, and senior high schools in Hebei Province. A total of 68 AEFI cases were reported, comprising 57 common vaccine reactions, 7 rare vaccine reactions, 3 coincidental events, and 1 psychogenic reaction. The overall AEFI reporting rate was 8.31 per 100 000 doses, 4 cases (2.30/100 000 doses), 31 cases (8.73/100 000 doses), and 33 cases (11.41/100 000 doses) were reported in 2022, 2023, and 2024, respectively, with a statistically significant difference across years ( χ 2=10.97, P <0.01). The reporting rates for common and rare vaccine reactions were 6.97 per 100 000 doses and 0.86 per 100 000 doses, respectively. The AEFI reporting rates were 15.14 per 100 000 doses among primary school girls and 8.20 per 100 000 doses among secondary school girls, though the difference was not statistically significant (Fisher s exact test, P =0.30). The reporting rate was higher after the first dose (10.91/100 000 doses) than after the second dose (5.96/100 000 doses; χ 2=5.85, P =0.02).The second quarter recorded the highest AEFI reporting rate at 11.21 per 100 000 doses. The majority of AEFI cases (56 cases, 82.35%) occurred within 24 hours post vaccination. Conclusion The domestic bivalent HPV vaccine demonstrates a favorable safety profile among female students in Hebei Province, with a low overall AEFI reporting rate that consisted predominantly of general reactions and occasional cardiac related reactions.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

ObjectiveType I interferon (IFN-I) signaling is essential for antiviral innate immunity, yet its sustained or excessive activation contributes to the pathogenesis of several autoimmune diseases and interferonopathies, such as systemic lupus erythematosus and Aicardi-Goutières syndrome. Current strategies targeting this pathway, exemplified by JAK inhibitors, act mainly on downstream signal transduction and provide limited direct control over upstream IFN-I production, while also carrying the risk of broad immunosuppression. Phyllanthus emblica L. has long been used in traditional medicine for inflammatory disorders, but the bioactive constituent responsible for its regulation of IFN-I signaling and the underlying molecular mechanism have not been clearly defined. This study aimed to identify the active anti-inflammatory component of P. emblica and to characterize its mechanism of action on the IFN-I pathway in macrophages. MethodsActive components ofP. emblica and their candidate targets were screened by network pharmacology using the TCMSP and DrugBank databases (oral bioavailability≥30%, drug-likeness≥0.18) and intersected with inflammation-related genes retrieved from public databases. The predicted interaction between EGCG and IFN-I pathway proteins (TBK1, IRF3, STAT1) was evaluated by molecular docking, with BX795 and GSK8612 used as reference TBK1 inhibitors. Mechanistic experiments were performed in THP-1-derived macrophages and primary bone marrow-derived macrophages (BMDM). Upstream signaling was activated by transfection of the nucleic acid analogs poly(I∶C) and poly(dA∶dT) or by lipopolysaccharide (LPS) stimulation, whereas downstream signaling was activated by exogenous IFN-β. An siRNA-mediated TREX1 knockdown model was used to mimic endogenous nucleic acid-driven interferonopathy. Expression of IFN-β1 and interferon-stimulated genes (ISGs) was measured by RT-qPCR, protein phosphorylation by Western blot, and IFN-β secretion by ELISA. Cellular thermal shift assay (CETSA) and drug affinity responsive target stability (DARTS) were used to probe the interactionbetween EGCG and IRF3. ResultsNetwork pharmacology identified (-)-epigallocatechin-3-gallate (EGCG) as a candidate IFN-I-suppressive constituent of P. emblica, with predicted binding to TBK1, IRF3, and STAT1. Molecular docking yielded binding energies of -9.2, -7.2, and -8.2 kcal/mol for TBK1, IRF3, and STAT1, respectively, indicating an affinity for TBK1 comparable to that of the reference inhibitors BX795 (-5.7 kcal/mol) and GSK8612 (-6.4 kcal/mol). EGCG suppressed IFN-β1 and ISG mRNA expression under poly (I∶C), poly (dA∶dT), and LPS stimulation in both THP-1 macrophages and BMDM. At the protein level, EGCG reduced the phosphorylation of TBK1 and IRF3 without affecting the levels of the upstream sensors cGAS and RIG-I, and lowered IFN-β secretion in a concentration-dependent manner. CETSA and DARTS showed that EGCG did not enhance the thermal stability or protease resistance of IRF3, indicating that its effect on IRF3 is indirect. Following IFN-β stimulation, prolonged EGCG treatment reduced STAT1 phosphorylation in a time-dependent manner without an apparent change in IRF9, and partially attenuated ISG transcription; this effect was not monotonicly concentration-dependent, and CXCL10 showed the most consistent suppression. In TREX1-knockdown cells, the elevated mRNA levels of ISG15, ISG56, and CXCL10 were reduced by EGCG. ConclusionEGCG suppresses IFN-I responses by concurrently inhibiting TBK1-IRF3-dependent IFN‑β production and JAK-STAT1-mediated downstream transcription. These in vitro findings provide a mechanistic basis for the anti-inflammatory use of P. emblica in traditional medicine and identify EGCG as a candidate for further evaluation in interferon-driven autoimmune disease models.

Objective To analyze the spatiotemporal distribution characteristics of and trends in the disease burden of dengue fever in China from 2005 to 2024, so as to provide insights into formulation of dengue fever control strategies. Methods Data pertaining to dengue fever cases in China from 2005 to 2024 were retrieved from the Infectious Disease Reporting Information System of Chinese Center for Disease Control and Prevention, and city population, gross domestic product (GDP), GDP per capita, and consumer price index in China were captured from the China Statistical Yearbook, National Bureau of Statistics of China, the China City Statistical Yearbook, and bureaus of statistics in each city. The disability-adjusted life years (DALYs), years of life lost (YLLs), and years lived with disability (YLDs) due to dengue fever were calculated in China from 2005 to 2024. The direct and indirect economic burdens of dengue fever were estimated to calculate the total economic burden. The trends in the disease burden of dengue fever were estimated in China from 2005 to 2024 using a Joinpoint regression model with the software Joinpoint 4.9.0.0, and the average annual percent change (AAPC) and its 95% confidence interval (CI) were calculated. In addition, the DALYs rate and economic burden of dengue fever in China were subjected to global and local spatial autocorrelation analyses using the software ArcGIS 10.8. Results The gross DALYs due to dengue fever were 5 558 person-years in China from 2005 to 2024, and the DALYs of dengue fever increased from 36 person-years in 2005 to 899 person-years in 2024, with an increase of 23.97 folds. The average annual DALYs rate of dengue fever was 0.02 person-years/10⁵ in China during the 20-year study period from 2005 to 2024, and the DALYs rate peaked in 2014 (0.13 person-years/10⁵) and reduced during the COVID-19 pandemic from 2020 to 2022. YLDs were the main contributor of DALYs due to dengue fever in China from 2005 to 2024, with a total of 5 354 person-years, accounting for 96.33% (5 354 person-years/5 558 person-years) of the gross DALYs. The gross DALYs of dengue fever were 2 982 person-years among men (53.66%) and 2 575 person-years among women (46.34%) in China from 2005 to 2024, and high DALYs of dengue fever were measured among residents at ages of 15 to 30 years (1 639 person-years), 30 to 45 years (1 857 person-years), and 45 to 60 years (1 204 person-years), respectively, accounting for 84.56% (4 700 person-years/5 558 person-years) of total DALYs due to dengue fever in China. The total economic burden of dengue fever was estimated to be 612 million Yuan in China from 2005 to 2024, with an average annual economic burden of 30.584 million Yuan. The economic burden of dengue fever increased from 196 000 Yuan in 2005 to 121 million Yuan in 2024 in China, with an increase of 616.35 folds, and the per capita economic burden increased from 3 322.21 Yuan in 2005 to 4 940.01 Yuan in 2024, with an increase of 48.70%. Dengue fever cases were reported in 274 cities (counties) across 31 provinces (autonomous regions, municipalities) in China from 2005 to 2024, with relatively higher DALYs in Guangdong Province and Yunnan Province. Spatial autocorrelation analysis revealed that the disease burden of dengue fever appeared positive aggregation in Chinese cities (counties) from 2005 to 2024 (global Moran’s I = 0.045, Z = 2.24, P < 0.05), with high-high clusters mainly concentrated in the Pearl River Delta region in Guangdong Province and Xishuangbanna Dai Autonomous Prefecture and Pu’er City in Yunnan Province, and the total economic burden (global Moran’s I = 0.032, Z = 9.55, P < 0.001), per capita economic burden (global Moran’s I = 0.208, Z = 27.34, P < 0.001), and the proportion of total economic burdens in GDP in 2024 (global Moran’s I = 0.017, Z = 5.91, P < 0.001) all presented positive aggregation, with relatively higher total economic burdens mainly concentrated in Guangdong Province and Yunnan Province. Joinpoint regression analysis showed that the gross DALYs rates of dengue fever appeared an overall tendency towards a rise in China from 2005 to 2024 (AAPC = 16.24%, P = 0.029), and the DALYs rate presented an overall tendency towards a rise among both men (AAPC = 14.75%, P = 0.028) and women (AAPC = 14.93%, P = 0.037) during the study period. The per capita direct economic burden appeared an overall tendency towards a rise among dengue fever patients in China from 2005 to 2024 (AAPC = 2.16%, P = 0.012); however, there was no significant difference in the trends in the per capita indirect economic burden (AAPC = 0.46%, P = 0.470). In addition, the DALYs rate of dengue fever appeared a tendency towards a rise in 84.67% (232/274) of cities (counties) in China from 2005 to 2024, and the per capita economic burden appeared a tendency towards a rise in 85.40% (234/274) of cities (counties), while the DALYs rate and per capita economic burden of dengue fever appeared a tendency towards a rise in 77.01% (211/274) of cities (counties). Conclusions The disease burden of dengue fever significantly increased in China from 2005 to 2024. It is recommended to reinforce integrated dengue fever control in high-risk areas and among high-risk populations, and to improve the surveillance of imported dengue fever cases and vector control.

ObjectiveThis paper aims to investigate the efficacy and related actions of Guizhi Fulingwan in intervening in the mice with colitis-associated colon cancer （CAC） based on the immunosuppressive microenvironment associated with myeloid-derived suppressor cells （MDSCs）. MethodsSixty male C57BL/6 mice were randomly assigned to a blank group， a model group， an aspirin group （0.04 g·kg^-1）， and low-， medium-， and high-dose Guizhi Fulingwan groups （4.87， 9.75， and 19.50 g·kg^-1）， with ten mice per group. The CAC mouse model was established via combined induction of azoxymethane （AOM）/dextran sulphate sodium （DSS）. Drug intervention commenced in week five， with continuous intragastric administration for nine weeks. The food intake， body weight， fecal characteristics， and haematochezia were observed and recorded， and disease activity index （DAI） scores were calculated according to scoring criteria. Hematoxylin and eosin （HE） staining was used to observe the histopathological changes in the colon tissues of the mice. Immunohistochemistry was used to determine proliferating cell nuclear antigen-67 （Ki67） expression in the colon tissues， and enzyme-linked immunosorbent assay （ELISA） was used to detect the contents of interleukin-6 （IL-6）， IL-1β， and tumor necrosis factor-α （TNF-α） in the serum of the mice. Flow cytometry was employed to determine the proportion levels of MDSCs， CD4⁺ T cells， and CD8⁺ T cells in the spleen tissues of the mice. The mRNA expressions of MDSC-associated effector molecules， including arginase 1 （Arg1） and inducible nitric oxide synthase （iNOS）， were detected by real-time quantitative polymerase chain reaction （Real-time PCR）. After that， an in vitro co-culture model of MDSCs and CD8⁺ T cells was established， and drug-containing serum of Guizhi Fulingwan was used for intervention. The Flow cytometry was employed to assess the effects of drug-containing serum of Guizhi Fulingwan with different concentrations on the levels of reactive oxygen species （ROS） and iNOS in MDSCs and the proliferation of CD8⁺ T cells. The levels of granzyme B （GZMB） and interferon-γ （IFN-γ） in cell supernatant were detected by ELISA. ResultsCompared with those in the control group， the mice in the model group exhibited significantly reduced body weight， elevated DAI scores， shortened colon length （P<0.01）， increased number of tumors and Ki67 expression （P<0.01）， and significantly elevated contents of IL-6， IL-1β， and TNF-α in the serum （P<0.01）. Significant increases in the number of MDSCs were observed in mouse spleens， alongside marked reductions in the levels of CD4⁺ T and CD8⁺ T cells （P<0.01）. Furthermore， the mRNA expressions of MDSC function-associated effector molecules Arg1 and iNOS were significantly upregulated （P<0.01）. Compared with those in the model group， the mice in the middle-dose Guizhi Fulingwan group exhibited increased body weight and significantly decreased DAI scores （P<0.05， P<0.01）. The mice in the middle- and high-dose Guizhi Fulingwan groups exhibited significantly improved colon shortening， significantly decreased number of tumors and Ki67 expression （P<0.05， P<0.01）， and significantly decreased contents of IL-6， IL-1β， and TNF-α in the serum （P<0.05， P<0.01）. Furthermore， administration of Guizhi Fulingwan markedly reduced MDSC infiltration in the spleen of the mice， with different degrees of increase in the levels of both CD4⁺ T and CD8⁺ T cells （P<0.05， P<0.01）， alongside significant decreases in the mRNA expressions of Arg1 and iNOS （P<0.05， P<0.01）. In vitro cell co-culture shows that administration of drug-containing serum of Guizhi Fulingwan significantly decreases the activity levels of ROS and iNOS in MDSCs and promotes the proliferation of CD8⁺ T cells and the secretion of GZMB and IFN-γ （P<0.05， P<0.01）. ConclusionGuizhi Fulingwan can reduce pro-inflammatory cytokine secretion and inhibit tumor proliferation in the colon tissues of CAC mice. Its potential mechanism may involve reducing MDSC infiltration， enhancing effector T cells， particularly CD8⁺ T cell response， and improving the tumor immunosuppressive microenvironment.

ObjectiveColorectal cancer (CRC) is a highly heterogeneous malignancy, and traditional Chinese medicine (TCM) syndrome differentiation is widely used in its clinical management. However, the biological basis underlying different TCM syndromes remains insufficiently understood. This study aimed to investigate the proteomic differences between qi-blood deficiency syndrome (QBDS) and damp-heat syndrome (DHS) in CRC patients and to establish a “syndrome-differential protein-herbal component” network for exploring potential molecular mechanisms and therapeutic targets associated with syndrome-specific treatment strategies. MethodsTumor tissue samples were collected from 10 patients with pathologically confirmed CRC, including 5 patients diagnosed with QBDS and 5 with DHS according to standardized TCM syndrome differentiation criteria. Tandem mass tag (TMT)-based quantitative proteomics was employed to identify differentially expressed proteins (DEPs) between the two syndrome groups. Functional enrichment analyses, including Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, were performed to characterize the biological functions and signaling pathways associated with the identified DEPs. Least absolute shrinkage and selection operator (LASSO) regression analysis was further applied to screen key syndrome-related proteins and construct a core protein prediction model. Subsequently, molecular docking was conducted to evaluate the binding affinities between representative herbal compounds, astragaloside IV and berberine, and the identified core proteins. Finally, cell counting kit-8 (CCK-8) assays were performed in HCT 116 and HT-29 colorectal cancer cell lines to validate the anti-proliferative activities of these compounds in vitro. ResultsA total of 44 DEPs were identified between QBDS and DHS tissues, including 21 upregulated and 23 downregulated proteins in the QBDS group relative to the DHS group. Functional enrichment analyses revealed that these proteins were primarily associated with antiviral immune responses, regulation of inflammatory signaling, NF‑κB signaling pathways, cholesterol metabolism, and other biological processes relevant to tumor progression and host immune regulation. LASSO regression analysis identified eight core proteins with potential syndrome-specific significance. Among them, ST7, GPCPD1, and PODXL were closely associated with QBDS, whereas FAT1, GRB7, KRT7, MAFF, and MMP8 were associated with DHS. Molecular docking demonstrated favorable interactions between astragaloside IV and QBDS-related proteins, with binding energies lower than -5 kcal/mol, indicating stable binding activity. Berberine exhibited even lower binding energies and stronger binding specificity toward DHS-related core proteins. In vitro experiments further confirmed that both compounds inhibited CRC cell proliferation, while berberine displayed significantly greater anti-proliferative efficacy. The lowest 48 h IC₅₀ value of berberine reached 15.21 mg/L in CRC cells, indicating a stronger growth-inhibitory effect than astragaloside IV. ConclusionCRC patients with QBDS and DHS exhibit distinct proteomic characteristics, suggesting that different TCM syndromes possess unique molecular signatures. The identified core proteins may serve as potential biomarkers for syndrome differentiation, while astragaloside IV and berberine may exert therapeutic effects through targeting syndrome-specific molecular networks. These findings provide preliminary proteomic evidence supporting syndrome-guided precision integrative medicine in CRC and offer new insights into the biological basis of TCM syndrome differentiation and individualized therapeutic strategies.

OBJECTIVE To evaluate the clinical efficacy of Chaihu anxin capsules in the treatment of mild-to-moderate depression， analyze the influencing factors of its efficacy, construct a nomogram prediction model.METHODS Patients with mild-to-moderate depression treated at The First Hospital of Hebei Medical University from May 1， 2023 to March 10， 2025 were retrospectively included and categorized into Chaihu anxin capsules group and milnacipran group according to treatment regimen. Propensity score matching （PSM） was used to balance baseline characteristics， and treatment efficacy was compared after 8 weeks， including 24 Hamilton Depression Scale （HAMD-24） scores and changes， Hamilton Anxiety Scale （HAMA） scores and changes， and treatment response rate after 8 weeks of treatment. Patients receiving Chaihu anxin capsules were further classified as responders or non-responders based on the occurrence of treatment response. Univariate and multivariate Logistic regression analyses were conducted to identify the influencing factors of treatment response， and a nomogram model was constructed to predict the probability of treatment response， its predictive performance was evaluated using receiver operating characteristic （ROC） curves， calibration curves， and decision curve analysis.RESULTS A total of 297 patients were included before PSM， including 196 patients in the Chaihu anxin capsules group and 101 patients in the milnacipran group. After PSM， each group included 44 patients. After PSM， the HAMD-24 scores and HAMA scores at 8 weeks after treatment in the Chaihu anxin capsules group， as well as the HAMD-24 scores in the milnacipran group， were significantly lower than their respective baseline values （ P ＜0.05）； the change in HAMA score in the Chaihu anxin capsules group was significantly greater than that in the milnacipran group （ P ＝0.04）. Multivariable Logistic regression identified age， total bilirubin， and baseline HAMD-24 score as independent predictors of treatment response （ P ＜0.05）. The area under the ROC curve of the constructed nomogram prediction model was 0.72 （95% confidence interval： 0.637-0.799）， and the corrected Brier score was 0.143 （95% confidence interval： 0.112-0.176）； compared with the “all intervention” and “all non intervention” strategies， applying this nomogram prediction model could achieve higher net benefits within the threshold probability range of 8% to 37%.CONCLUSIONS The efficacy of Chaihu anxin capsules in improving mild-to-moderate depression is comparable to that of milnacipran， and it has certain advantages in improving anxiety symptoms； age， total bilirubin， and baseline HAMD-24 score are independent influencing factors for the treatment response of Chaihu anxin capsules. The nomogram prediction model constructed based on these factors has good discrimination， calibration， and clinical applicability.