BACKGROUND:Traumatic brain injury is a condition in which the normal function of the brain is disrupted by a bump or impact to the head.It is necessary to find effective treatments and objective targets that can help doctors diagnose the injury status and restore the brain function of patients. OBJECTIVE:To explore the effect of electroacupuncture combined with low-frequency transcranial ultrasound stimulation on the electroencephalographic signals of rats with traumatic brain injury. METHODS:Forty 6-week-old SPF male Sprague-Dawley rats were randomly divided into five groups:sham group,model group,electroacupuncture group,low-frequency transcranial ultrasound stimulation group and combined group(electroacupuncture+low-frequency transcranial ultrasound stimulation),with eight rats in each group.Feeney weight-drop method was used to establish the animal model of traumatic brain injury.In the sham group,the bone window was only opened without impact.Interventions were started at 1 day after modeling.Electroacupuncture in the electroacupuncture group,low-frequency transcranial ultrasound stimulation in the low-frequency transcranial ultrasound stimulation group,and electroacupuncture+low-frequency transcranial ultrasound stimulation in the combined group were performed for days in total.The modified neurological severity scale score for assessing rats'neurological deficits was performed at 8 hours after modeling.The percentage of spontaneous alternation behavior in the Y-maze was measured at 7 days after modeling.Then,the electroencephalographic signals were collected and electroencephalographic data of α,β,θ,and δ waves were extracted by fast Fourier transform,and the value of oscillation amplitude and energy ratio were calculated in α,β,θ,and δ waves,as well as the Lempel-Ziv complexity and sample entropy. RESULTS AND CONCLUSION:Compared with the sham group,the modified neurological severity scale scores in the model group,electroacupuncture group,low-frequency transcranial ultrasound stimulation group and combined group were significantly increased at 8 hours after modeling(P<0.05).Compared with the sham group,the value of oscillation amplitude in δ wave and the value of δ energy ratio were significantly increased in the model group at 7 days after modeling,meanwhile the percentage of spontaneous alternation behavior in Y-maze,and the value of α/β energy ratio,Lempel-Ziv complexity,and sample entropy were significantly decreased(P<0.05).Compared with the model group,the value of oscillation amplitude in α and δ waves was significantly decreased in the combined group(P<0.05),while the value of α/β energy ratio was significantly increased(P<0.05)and the value of δ energy ratio was significantly decreased(P<0.05)in the electroacupuncture group,low-frequency transcranial ultrasound stimulation group and combined group.Compared with the electroacupuncture group and low-frequency transcranial ultrasound stimulation group,the value of δ energy ratio was significantly decreased in the combined group(P<0.05),while the percentage of spontaneous alternation behavior,the value of α/β energy ratio,the Lempel-Ziv complexity,and the sample entropy were significantly increased(P<0.05).To conclude,abnormal electroencephalographic signals can appear in rats with traumatic brain injury,while the electroacupuncture combined with low-frequency transcranial ultrasound stimulation can alleviate the abnormal electroencephalographic signals in rats,which suggests the electroencephalographic frequency domain value and nonlinear features can be used to assess the severity of traumatic brain injury.

ObjectiveBased on analytic hierarchy process（AHP）-criteria importance through intercriteria correlation（CRITIC） hybrid weighting method， grey relational analysis and backpropagation artificial neural network（BP-ANN）， to optimize the water extraction process of Qizhi prescription， so as to provide an experimental basis for optimization of the preparation process of this prescription and the establishment of quality standards. MethodsL₉（3⁴） orthogonal test was employed， and the AHP-CRITIC hybrid weighting method was utilized to determine the weight coefficients of the quality fractions of various components， including astragaloside Ⅳ， polygalaxanthone Ⅲ， calycosin-7-O-β-D-glucoside， tenuifolin， and 3，6′-disinapoylsucrose， as well as the dry extract yield. The comprehensive score of each factor level combination in the orthogonal test were calculated as evaluation indicator to select the optimal extraction process parameters. The effects of extraction times， extraction time， and solvent dosage on the aqueous extraction process of the formula were investigated through intuitive analysis， variance analysis， and grey relational analysis. Meanwhile， a BP-ANN model was established to reverse-predict the optimal extraction process parameters of Qizhi prescription， and the optimized process parameters were validated. ResultsThe weight coefficients of the five index components（astragaloside Ⅳ， tenuifolin， calycosin-7-O-β-D-glucoside， polygalaxanthone Ⅲ， and 3，6′-disinapoylsucrose） and dry extract yield were 25.7%， 20.82%， 16.41%， 12.45%， 15.96% and 8.67%， respectively. The optimized extraction process parameters were extracted 3 times with 8， 6， 6 times the amount of water， each time for 1 h. The network prediction results of BP-ANN test samples were consistent with the orthogonal test results， and the mean square error（MSE） of the predicted and measured values of the network was <1%. The water extraction process of Qizhi prescription analyzed and predicted by relevant mathematical models was stable and feasible， which could effectively improve the extraction efficiency of the active ingredients of Astragali Radix and Polygalae Radix， and the average comprehensive score of the validation test was 90.85 with the relative standard deviation（RSD） of 1.55%. ConclusionThis study establishes a water extraction process for compound Qizhi granules， and the optimized extraction process can effectively improve the extraction efficiency of active ingredients， which provides useful references for the optimization of preparation process and the establishment of quality standards for other clinical experience formulas.

Background Exposure to polycyclic aromatic hydrocarbons (PAHs) is associated with the development of metabolic syndrome (MS). However, the role of amino acids in PAH-induced MS remains unclear. Objective To explore the impact of PAHs exposure on the incidence of MS among coking workers, and to determine potential modifying effect of amino acid on this relationship. Methods Unmatched nested case-control design was adopted and the baseline surveys of coking workers were conducted in two plants in Taiyuan in 2017 and 2019, followed by a 4-year follow-up. The cohort comprised 667 coking workers. A total of 362 participants were included in the study, with 84 newly diagnosed cases of MS identified as the case group and 278 as the control group. Urinary levels of 11 PAH metabolites and plasma levels of 17 amino acids were measured by ultrasensitive performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Logistic regression was used to estimate the association between individual PAH metabolites and MS. Stratified by the median concentration of amino acids, Bayesian kernel machine regression (BKMR) model was employed to assess the mixed effects of PAHs on MS. Due to the skewed data distribution, all PAH metabolites and amino acids in the analysis were converted by natural logarithm ln (expressed as lnv). Results The median age of the 362 participants was 37 years, and 83.2% were male. Compared to the control group, the case group exhibited higher concentrations of urinary 2-hydroxyphenanthrene (2-OHPhe), 9-hydroxyphenanthrene (9-OHPhe), and hydroxyphenanthrene (OHPhe) (P=0.005, P=0.049, and P=0.004, respectively), as well as elevated levels of plasma branched chain amino acid (BCAA) and aromatic amino acid (AAA) (P<0.05). After being adjusted for confounding factors, for every unit increase in lnv_2-OHPhe in urine, the OR (95%CI) of MS was 1.57 (1.11, 2.26), and for every unit increase in lnv_OHPhe, the OR (95%CI) of MS was 1.82 (1.16, 2.90). Tyrosine, leucine, and AAA all presented a significant nonlinear correlation with MS. At low levels, tyrosine, leucine, and AAA did not significantly increase the risk of MS, but at high levels, they increased the risk of MS. In the low amino acid concentration group, as well as in the low BCAA and low AAA concentration groups, it was found that compared to the PAH metabolite levels at the 50th percentile (P₅₀), the log-odds of MS when the PAH metabolite levels was at the 75th percentile (P₇₅) were 0.158 (95%CI: 0.150, 0.166), 0.218 (95%CI: 0.209, 0.227), and 0.262 (95% CI: 0.241, 0.282), respectively, However, no correlation between PAHs and MS was found in the high amino acid concentration group. Conclusion Amino acids modify the effect of PAHs exposure on the incidence of MS. In individuals with low plasma amino acid levels, the risk of developing MS increases with higher concentrations of mixed PAH exposure. This effect is partly due to the low concentrations of BCAA and AAA.

Polygonatum sibiricum， as a traditional Chinese medicine with both medicinal and edible properties， has attracted considerable attention due to its functions of nourishing Yin and moistening the lungs， tonifying the spleen and benefiting Qi， and nourishing the kidneys and filling essence. Recent studies have demonstrated that Polygonatum sibiricum plays a significant role in regulating the immune system， effectively enhancing and improving the morphology and function of immune organs， stimulating the proliferation and activation of immune cells， and regulating the secretion and release of immune factors， thereby enhancing the immune function of the body and improving various immune-related diseases. Although a large number of studies have explored the pharmacological effects and mechanisms of P. sibiricum， there has been no systematic review and summary of its immune regulatory activity and mechanisms. Therefore， this article comprehensively reviews the research achievements of P. sibiricum polysaccharides and saponins in the field of immune regulation in recent years， and further sorts out the immune regulatory mechanisms of P. sibiricum in multiple aspects： including increasing the organ index of the spleen and thymus， increasing the number and activity of tumor-suppressive bone marrow hematopoietic stem cells， improving intestinal flora imbalance， regulating the quantity and proportion of T lymphocyte subsets， increasing the level of immunoglobulin， promoting the proliferation of macrophages， enhancing the activity of natural killer cells， increasing the number of white blood cells， and promoting the maturation of dendritic cells， providing a solid theoretical basis and scientific evidence for the research and application of P. sibiricum， and promoting its development and application in traditional Chinese medicine immune enhancers and various functional products.

BACKGROUND: It is inaccurate to reflect the level of dust exposure through working years. Furthermore, identifying a predictive indicator for lung function decline is significant for coal miners. The study aimed to explored whether club cell secretory protein (CC16) levels can reflect early lung function changes. METHODS: The cumulative respiratory dust exposure (CDE) levels of 1,461 coal miners were retrospectively assessed by constructed a job-exposure matrix to replace working years. Important factors affecting lung function and CC16 were selected by establishing random forest models. Subsequently, the potential of CC16 to reflect lung injury was explored from multiple perspectives. First, restricted cubic spline (RCS) models were used to compare the trends of changes in lung function indicators and plasma CC16 levels after dust exposure. Then mediating analysis was performed to investigate the role of CC16 in the association between dust exposure and lung function decline. Finally, the association between baseline CC16 levels and follow-up lung function was explored. RESULTS: The median CDE were 35.13 mg/m³-years. RCS models revealed a rapid decline in forced vital capacity (FVC), forced expiratory volume in the first second (FEV₁), and their percentages of predicted values when CDE exceeded 25 mg/m³-years. The dust exposure level (<5 mg/m³-years) causing significant changes in CC16 was much lower than the level (25 mg/m³-years) that caused changes in lung function indicators. CC16 mediated 11.1% to 26.0% of dust-related lung function decline. Additionally, workers with low baseline CC16 levels experienced greater reductions in lung function in the future. CONCLUSIONS CC16 levels are more sensitive than lung indicators in reflecting early lung function injury and plays mediating role in lung function decline induced by dust exposure. Low baseline CC16 levels predict poor future lung function.
Uteroglobin/blood* ; Humans ; Dust/analysis* ; Occupational Exposure/analysis* ; Male ; Middle Aged ; Adult ; Retrospective Studies ; Lung Injury/chemically induced* ; Coal Mining ; Biomarkers/blood* ; China/epidemiology* ; Air Pollutants, Occupational ; Female

OBJECTIVES: To investigate the active ingredients in Hedyotis diffusa-Scutellaria barbata D. Don and the main biological processes and signaling pathways mediating their inhibitory effect on primary hepatocellular carcinoma (HCC). METHODS: The core intersecting genes of HCC and the two drugs were screened from TCMSP, Uniport, Genecards, and String databases using Cytoscape software, and GO and KEGG enrichment analyses of the intersecting genes were conducted. Molecular docking between the active ingredients of the drugs and the core genes was carried out using Pubcham, RCSB and Autoduckto to identify the active ingredients with the highest binding energy, whose inhibitory effect on HepG2 cells was verifies using CCK-8 assay, flow cytometry and Western blotting. RESULTS: TP53 and ESR1 were identified as the core genes of HCC and the two drugs. GO and KEGG analyses showed that the two genes were mainly involved in regulation of apoptotic signaling pathway, cell population proliferation, methane raft, and protein kinase activity, and participated in the signaling pathways of apoptosis, proteoglycans in cancer, PI3K Akt signaling pathway, and hepatitis B. Molecular docking studies showed that the active ingredients of the drugs could be docked with TP53 and ESR1 genes under natural conditions, and ursolic acid had the highest binding energy to ESR1 (-4.98 kcal/mol). The results of CCK-8 assay, flow cytometry and Western blotting all demonstrated significant inhibitory effect of ursolic acid on HepG2 cells. CONCLUSIONS The inhibitory effect of Hedyotis diffusa-scutellariae barbatae on HCC is mediated by multiple active ingredients in the two drugs.
Humans ; Molecular Docking Simulation ; Liver Neoplasms/drug therapy* ; Hep G2 Cells ; Network Pharmacology ; Carcinoma, Hepatocellular/drug therapy* ; Hedyotis/chemistry* ; Signal Transduction/drug effects* ; Cell Proliferation/drug effects* ; Tumor Suppressor Protein p53/metabolism* ; Apoptosis/drug effects* ; Estrogen Receptor alpha/metabolism* ; Drugs, Chinese Herbal/pharmacology*

OBJECTIVES: We propose a novel deep learning segmentation algorithm (DSRF) based on multi-scale supervision and residual feedback strategy for precise segmentation of the optic chiasm and optic nerves in CT images of nasopharyngeal carcinoma (NPC) patients. METHODS: We collected 212 NPC CT images and their ground truth labels from SegRap2023, StructSeg2019 and HaN-Seg2023 datasets. Based on a hybrid pooling strategy, we designed a decoder (HPS) to reduce small organ feature loss during pooling in convolutional neural networks. This decoder uses adaptive and average pooling to refine high-level semantic features, which are integrated with primary semantic features to enable network learning of finer feature details. We employed multi-scale deep supervision layers to learn rich multi-scale and multi-level semantic features under deep supervision, thereby enhancing boundary identification of the optic chiasm and optic nerves. A residual feedback module that enables multiple iterations of the network was designed for contrast enhancement of the optic chiasm and optic nerves in CT images by utilizing information from fuzzy boundaries and easily confused regions to iteratively refine segmentation results under supervision. The entire segmentation framework was optimized with the loss from each iteration to enhance segmentation accuracy and boundary clarity. Ablation experiments and comparative experiments were conducted to evaluate the effectiveness of each component and the performance of the proposed model. RESULTS: The DSRF algorithm could effectively enhance feature representation of small organs to achieve accurate segmentation of the optic chiasm and optic nerves with an average DSC of 0.837 and an ASSD of 0.351. Ablation experiments further verified the contributions of each component in the DSRF method. CONCLUSIONS The proposed deep learning segmentation algorithm can effectively enhance feature representation to achieve accurate segmentation of the optic chiasm and optic nerves in CT images of NPC.
Humans ; Tomography, X-Ray Computed/methods* ; Optic Chiasm/diagnostic imaging* ; Optic Nerve/diagnostic imaging* ; Algorithms ; Nasopharyngeal Carcinoma ; Deep Learning ; Nasopharyngeal Neoplasms/diagnostic imaging* ; Neural Networks, Computer ; Image Processing, Computer-Assisted/methods*

This review systematically summarizes the unique metabolic mechanisms of breast cancer,their interac-tions with the tumor microenvironment(TME),and the latest advances in targeted therapies.The interplay between metabolic reprogramming and the TME underpins malignant progression and therapeutic resistance.Breast cancer cells reshape energy supply through the Warburg effect,aberrant fatty acid synthesis,and amino acid metabolism,while immune cells,fibroblasts,and the acidic milieu within the TME promote immune evasion and drug resistance via metabolic coupling.Although traditional strategies targeting key metabolic enzymes remain valuable,they are often insufficient to overcome metabolic adaptability.In recent years,combined metabolic and immunotherapeutic approaches have emerged as promising strategies:by reducing lactate accumulation,restoring T-cell function,and reprogramming tumor-associated macrophages and cancer-associated fibroblasts,these therapies can remodel the immunosuppressive microenvironment and enhance immunotherapy efficacy.The application of metabolomics and single-cell sequencing further elucidates breast cancer heterogeneity,providing a basis for individualized precision treatment.Future challenges include deciphering resistance mechanisms,developing highly selective metabolic in-hibitors,and designing integrated multi-omics-based therapeutic regimens.

Abstract Esophageal cancer is one of the most common malignant tumors of the digestive system in China , with e-sophageal squamous cell carcinoma (ESCC) being the predominant pathological type. The exact etiology of ESCC remains incompletely understood. With advances in 16S rRNA gene sequencing and metagenomics , microbial dys- biosis has been suggested to play a significant role in the pathogenesis of ESCC. Currently , research on the rela- tionship between microorganisms and ESCC is still in its early stages. This review summarizes the association be- tween oral and esophageal microbiota and ESCC , factors influencing microbial composition , and microbial commu- nities linked to ESCC prognosis , which may contribute to early detection and optimized treatment strategies for ES- CC.

ObjectiveTo investigate the brain absorption components of Tianyuan Zhitong prescription and their distribution based on ultra-high performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS）， desorption electrospray ionization mass spectrometry imaging（DESI-MSI） and hyperspectral imaging techniques. MethodTen BALB/c mice were randomly divided into blank group（n=3） and administration group（n=7）， the administration group was gavaged with 0.3 mL of Tianyuan Zhitong prescription liquid at a concentration of about 5 g·mL^-1 of the raw material， and the blank group was gavaged with an equal volume of normal saline， and the whole brain of the mice were taken for the preparation of tissue homogenates and frozen sections， respectively. The tissue homogenates were qualitatively analyzed by UPLC-Q-TOF-MS for the brain absorption components in positive and negative ion modes， frozen sections were used for imaging to observe the distribution of these components in the brain. Cytoviva dark-field enhancement microscope was used to perform hyperspectral imaging scanning on the brain sections of mice from each group， and the scattered light data of at least 1 000 pixels in the visible-near-infrared（400-1 000 nm） band in the microscopic field of view were collected and average spectrum were created， which were used to compare the components in the brain tissues of mice from the blank and administration groups. ResultA total of 27 brain absorption components of Tianyuan Zhitong prescription were identified by UPLC-Q-TOF-MS， including 10 organic acids， 5 glycosides， 4 alkaloids， 1 phenol， 4 flavonoids， 2 phthalides and 1 other compound， which were mainly derived from Gastrodiae Rhizoma， Chuanxiong Rhizoma， vinegar-processed Corydalis Rhizoma， Ziziphi Spinosae Semen and processed Morindae Officinalis Radix. A total of 14 components were identified by mass spectrometry imaging， of which ferulic acid， tetrahydropalmatine and N-methyl dehydroberberine were mainly distributed in the cerebral cortex， vitamin B₅， vemonoic acid and ricinoleic acid were mainly distributed in the hypothalamus， elemicin， octadecenic acid and octadecanoic acid were mainly distributed in the cortex and hypothalamus， while senkyunolide B， ligustilide， linoleic acid， 9，12-octadecadienoyl ethyl ester and spinosin were distributed in most regions of the brain tissues. Hyperspectral imaging showed that in the visible-near-infrared band range， the average spectrum of the brain tissues of mice in the administration group was significantly red-shifted， indicating that there were differences in the physical properties or contents of the chemical components in the brain between mice in the blank group and those in the administration group， and further verified the results of mass spectrometry imaging. ConclusionThrough the combination of UPLC-Q-TOF-MS and imaging techniques， the pharmacodynamic components of Tianyuan Zhitong prescription in the treatment of headache and the regional characteristics in brain tissue are clarified， which can provide reference for the selection of the index components of the research on the quality standard of this prescription and the research on the mechanism of the pharmacological effect.