Background: High-mobility group box protein 1 (HMGB1) is a chromatin-binding protein involved in arthritis, ischemia, sepsis, atherosclerosis, neurodegenerative disorders, meningitis, and cancer. HMGB1 exhibits dual roles in cancer, acting as either a tumor suppressor or oncoprotein depending on context. Objective: This research aimed to elucidate HMGB1’s functional significance in cutaneous squamous cell carcinoma (cSCC). Methods: We overexpressed HMGB1 in cSCC cell lines using recombinant adenovirus and examined its effects on cell proliferation, colony formation, and cell migration. Results: Immunohistochemical analysis revealed elevated HMGB1 expression levels in cSCC tissue relative to normal epidermis. To assess the influence of HMGB1, we employed recombinant adenoviruses expressing HMGB1 to transduce SCC cell lines (SCC12 and SCC13). Enhanced HMGB1 expression significantly promoted cellular proliferation and colony formation capacity.Notably, HMGB1 overexpression elevated the levels of proliferation regulators, including P63, SOX2, CDK4 and CDK6. Furthermore, HMGB1 overexpression substantially enhanced tumor invasiveness, accompanied by upregulation of epithelial-mesenchymal transition (EMT) biomarkers. Mechanistically, overexpression of HMGB1 enhanced transforming growth factor-β signaling by increasing phosphorylation of SMAD2/3, the key mediators of EMT. Conclusion These data imply that HMGB1 acts as a tumor-promoting factor in cSCC.

Objective To establish a method for rapid determination of 25 elements in aquatic vegetables by microwave digestion-inductively coupled plasma triple quadrupole mass spectrometry (ICP-QQQ) and master the relevant determination techniques. Methods Microwave digestion was used for sample pre-treatment, and ICP-QQQ was used for rapid determination of 25 elements in aquatic vegetable samples such as Artemisia selengensis. Feasibility tests were carried out on the linear equations, correlation coefficients, detection limits, precision and recovery rates of the method. The interferences in determination and their elimination were discussed. Results The method established in the present study showed good linearity (γ≥0.999). The recoveries of 17 trace elements such as ⁷Li ranged from 83.90% to 115.48%, with relative standard deviations (RSDs) all <10%; the recoveries of 8 major elements such as ²³Na in various samples ranged from 81.18% to 115.29%, with RSDs all <5%. The method detection limits were 0.000048 mg/kg–0.19 mg/kg. Conclusion This method features simple operation, minimal interference, high sensitivity, low detection limit, good precision, and high accuracy, and it is suitable for rapid batch determination of 25 elements in samples such as aquatic vegetable Artemisia selengensis.

ObjectiveMigraine is a leading neurological disorder and the fourth most common cause of years lived with disability worldwide, affecting nearly 116 million individuals. Although pharmacological treatments are available, their efficacy is often limited by side effects and variable response rates. Repetitive transcranial magnetic stimulation (rTMS) over the dorsolateral prefrontal cortex (DLPFC) offers a safe, non-invasive alternative for migraine management. However, the neurophysiological mechanisms, particularly how rTMS modulates local cortical excitability and distributed pain-related circuits, remain poorly understood. Elucidating these mechanisms is essential for optimizing treatment protocols and improving clinical outcomes. MethodsThis study employed concurrent transcranial magnetic stimulation and electroencephalography (TMS-EEG) to investigate neuroplastic and neurocircuitry mechanisms of DLPFC-rTMS in migraine. Study 1 compared 30 migraineurs and 28 healthy controls to identify abnormalities in TMS-evoked potentials (TEPs) and significant current density (SCD) within sensory-discriminative regions including the primary somatosensory cortex (S1) and posterior insula (pINS), cognitive-affective regions including the anterior insula (aINS) and midcingulate cortex (MCC), and a descending modulatory region, the periaqueductal gray (PAG). Study 2 used a single-blind, crossover, sham-controlled design in 34 healthy participants. Each participant received both active (10 Hz, 80% RMT, 1 500 pulses) and sham DLPFC-rTMS in counterbalanced order. TMS-EEG and cold pain tolerance were assessed before and after each session. ResultsIn Study 1, migraineurs showed a significantly less negative N120 amplitude compared to healthy controls (P=0.027, Cohen’s d=0.60), indicating local intracortical disinhibition. No group differences were observed for N40, P60, or P180 components. At the source level, migraineurs exhibited significantly higher SCD in the S1, pINS, aINS, and MCC (allQ<0.05), but not in the ventroposterior thalamus (vpTHAL), mediodorsal thalamus (mdTHAL), or PAG. In Study 2, active rTMS significantly reduced SCD from pre- to post-stimulation in the S1, aINS, and MCC (all Q<0.05). Sham stimulation also reduced SCD in the S1 (Q<0.05) but not in the aINS or MCC. Although no significant group-level analgesic effect was observed between active and sham conditions (P=0.107), correlation analyses revealed that greater SCD reductions in the S1 and MCC were significantly associated with higher post-rTMS pain tolerance (R=-0.487 and -0.495, both Q<0.01) and larger improvements in pain tolerance(R=-0.487 and -0.451, both Q<0.05). No such correlations were found following sham stimulation, suggesting that the behavioural relevance of neural changes is specific to active rTMS. ConclusionThis study provides novel evidence that migraineurs exhibit both local neuroplastic abnormalities (reduced N120 amplitude) and hyperactivity in key pain-processing regions (S1, pINS, aINS, MCC). A single session of DLPFC-rTMS reduced hyperactivity in the aINS, MCC, and S1. Notably, greater reductions in the S1 and MCC were associated with improved pain tolerance. These findings identify distinct cortical circuitries, particularly within the cognitive-affective pain network, that may serve as potential biomarkers for optimizing rTMS treatment in migraine and other chronic pain conditions. Future studies should validate these results in patient populations experiencing spontaneous migraine attacks and explore multi-session or accelerated rTMS protocols.

Objective To explore a deep learning-based automatic bone age estimation model for elbow joint X-ray images of Chinese Han adolescents and children and evaluate its performance.Methods A total of 943(517 males and 426 females)elbow joint frontal view X-ray images of Chinese Han ado-lescents and children aged 6.00 to<16.00 years were collected from East,South,Central and North-west China.Three experimental schemes were adopted for bone age estimation.Scheme 1:Directly in-put preprocessed images into the regression model;Scheme 2:Train a segmentation network using"key elbow joint bone annotations"as labels,then input segmented images into the regression model;Scheme 3:Train a segmentation network using"full elbow joint bone annotations"as labels,then in-put segmented images into the regression model.For segmentation,the optimal model was selected from U-Net,UNet++and TransUNet.For regression,VGG16,VGG19,InceptionV2,InceptionV3,ResNet34,ResNet50,ResNet101 and DenseNet121 models were selected for bone age estimation.The dataset was randomly split into 80%(754 samples)for training and validation for model fitting and hyperparameter tuning,and 20%(189 samples)as an internal test set to test the performance of the trained model.An additional 104 elbow joint X-ray images from the same demographic and age group were col-lected and used as an external test set.Model performance was evaluated by comparing the mean ab-solute error(MAE),root mean square error(RMSE),accuracies within±0.7 years(P±0.7 years)and±1.0 years(P±1.0 years)between the estimated age and the actual age,and by drawing radar charts,scat-ter plots,and heatmaps.Results When segmented with Scheme 3,the UNet++model achieved good segmentation performance with a segmentation loss of 0.000 4 and an accuracy of 93.8%at a learning rate of 0.000 1.In the internal test set,the DenseNet121 model with Scheme 3 yielded the best results with MAE,P±0.7 years and P±1.0 years being 0.83 years,70.03%,and 84.30%,respectively.In the external test set,the DenseNet121 model with Scheme 3 also performed best,with an average MAE of 0.89 years and an average RMSE of 1.00 years.Conclusion When performing automatic bone age estima-tion using elbow joint X-ray images in Chinese Han adolescents and children,it is recommended to use the UNet++model for segmentation.The DenseNet121 model with Scheme 3 achieves optimal per-formance.Using segmentation networks,especially that trained with annotation areas encompassing the full elbow joint including the distal humerus,proximal radius,and proximal ulna,can improve the ac-curacy of bone age estimation based on elbow joint X-ray images.

Objective To explore a deep learning network model suitable for bone age estimation using shoulder joint X-ray images in Chinese Han adolescents.Methods A retrospective collection of 1 286 shoulder joint X-ray images of Chinese Han adolescents aged 12.0 to<18.0 years(708 males and 578 females)was conducted.Using random sampling,approximately 80%of the samples(1 032 cases)were selected as the training and validation sets for model learning,selection and optimization,and the other 20%samples(254 cases)were used as the test set to evaluate the model's generalization ability.The original single-channel shoulder joint X-ray images and dual-channel inputs combining original images with segmentation labels(manually annotated shoulder joint regions multiplied pixel-by-pixel with original images,followed by segmentation via the U-Net++network to retain only key shoulder joint region information)were respectively input into four network models,namely VGG16,ResNet18,ResNet50 and DenseNet121 for bone age estimation.Additionally,manual bone age estimation was con-ducted on the test set data,and the results were compared with the four network models.The mean absolute error(MAE),root mean square error(RMSE),coefficient of determination(R2),and Pear-son correlation coefficient(PCC)were used as main evaluation indicators.Results In the test set,the bone age estimation results of the four models with dual-channel input of shoulder joint X-ray images outperformed those with single-channel input in all four evaluation indicators.Among them,DenseNet121 with dual-channel input achieved best results with MAE of 0.54 years,RMSE of 0.82 years,R2 of 0.76,and PCC(r)of 0.88.Manual estimation yielded an MAE of 0.82 years,ranking second only to dual-channel DenseNet121.Conclusion The DenseNet121 model with dual-channel input combined with original images and segmentation labels is superior to manual evaluation results,and can effectively estimate the bone age of Chinese Han adolescents.

Cancer is the main cause of death,and drug therapy has greatly improved the effectiveness of anti-tumor treatment.However,there are problems such as high adverse reactions and the risk of developing drug resistance after long-term use.There is an urgent need to seek new drug targets.Human antigen R(HuR),as an RNA binding protein,promotes the whole process of tumor occurrence,development and metastasis through post transcriptional regulation of mRNA stability,and HuR is general-ly highly expressed in tumor tissue,making it a new target for an-ti-tumor therapy and a standard for prognosis evaluation.Tradi-tional Chinese medicine formulas and their various chemical components can inhibit tumor proliferation,induce tumor cell ap-optosis,inhibit angiogenesis,suppress immune escape,and re-verse tumor drug resistance by regulating HuR activity.This re-view summarizes the importance of HuR in regulation of tumor progression,as well as analyzes the mechanisms of the antitumor effects through active ingredients of Chinese medicine with the regulation of HuR.It is expected to provide new ideas for tumor therapy and guidance for the development of HuR-targeted anti-tumor drugs.

Objective To investigate the effect and mechanism of methyl oxofulnonone A(META)on high glucose(HG)-induced H9c2 cell injury.Methods H9c2 cells were divided into control group(normal culture),model group(55 mmol·L-1 glucose)and experimental-L,-M,-H groups(55 mmol·L-1 glucose+12.5,25.0,50.0 μmol·L-1 META).Cell viability was detected by cell counting kit-8;intracellular reactive oxygen species(ROS)level was detected by DCFH-DA fluorescent probe;intracellular adenosine triphosphate(ATP)content was detected by luciferase;and autophagy-related protein expression was detected by Western blotting.Results The optical density values of 72-hour cells in the control group,model group and experimental-M,-H groups were 0.91±0.03,0.61±0.01,0.69±0.02 and 0.72±0.03;the ROS levels were(40.75±1.53)％,(43.73±1.30)％,(30.87±1.27)％and(28.28±1.43)％;the ATP contents were(8.16±0.71),(4.03±0.29),(5.29±0.31)and(5.83±0.31)nmol·mg-1;the relative expression levels of autophagy-related gene 5 protein were 1.05±0.06,1.46±0.09,0.98±0.11 and 0.89±0.09;the relative expression levels of ubiquitin-binding protein were 1.05±0.10,0.55±0.13,0.89±0.04 and 0.98±0.04;the ratios of microtubule-associated protein 1 light chain 3 11/Ⅰ protein were 1.09±0.09,1.82±0.05,1.67±0.29 and 1.09±0.15,respectively.Among the above indicators,there were statistically significant differences between the model group and the control and experimental-M,-H groups(P＜0.05,P＜0.01).Conclusion META significantly ameliorates H9c2 cardiomyocyte damage caused by high glucose,ameliorates oxidative stress,protects mitochondrial respiration and inhibits autophagy.

Aim To investigate the effects of acteoside(ACT)on ulcerative colitis(UC)mice from the per-spective of inflammation and intestinal flora.Methods The UC model was prepared by dextran sulfate sodi-um(DSS)drinking method and treated with ACT for 14 d,during which the activity of the mice was ob-served and the disease activity index(DAI)was scored.ELISA was used to detect the expression of in-flammatory factors.HE staining was used to observe the injury of colon tissue.16S rRNA high-throughput sequencing method was used to detect the structure and abundance of fecal intestinal flora in mice,and the correlation between the flora and inflammatory indica-tors was analyzed.Results After ACT administra-tion,the fear of cold and lazy movement of mice were improved,and the DAI of mice was reduced.The in-tegrity of colon mucosal epithelial cells was restored and mucosal damage was alleviated.The expressions of pro-inflammatory factors MPO,IL-1 β,IL-6,TNF-α,TF and PAF decreased,while the expression of anti-in-flammatory factor IL-10 increased.The abundance of harmful bacteria such as Firmicutes and Bacteroides de-creased,while the abundance of beneficial bacteria such as Bacteroidetes and Alistipes increased.Protective bacteria such as Bacteroidetes and Lachnospira were negatively correlated with IL-1β,IL-6 and other pro-inflammatory factors,while harmful bacteria such as Proteobacteria and Streptococcus were positively correla-ted with the above pro-inflammatory factors.Conclu-sions The therapeutic mechanism of ACT on chronic UC mice is related to its alleviation of inflammation and regulation of intestinal flora,and there is a correlation between inflammatory factors and intestinal flora.

This study was aimed at understanding the antimicrobial resistance patterns,virulence characteristics,and phyloge-netic relationships of foodborne Listeria monocytogenes in Weifang.A total of 67 strains of Listeria monocytogenes were isolated from livestock,poultry meat,and clinical samples in Weifang between 2020 and 2023.The susceptibility of these isolates was determined through broth microdilution.Whole-genome sequencing and genetic characterization of these isolates were conducted.The 67 strains were divided into 12 STs,among which ST121,ST8,ST9,and ST87 predominated(76.12%).Eight groups of closely related strains were identified through cgMLST typing.Three Listeria pathogenicity islands and two genomic islands were identified in all strains:100%of the strains carried LIPI-1,5.97%carried LIPI-3,14.93%carried LIPI-4,2.99%carried LGI-2,and 4.48%of the strains carried LGI-3.No antibiotic resistance genes were found in any strains.All isolates were susceptible to ampicillin,penicillin,merope-nem,trimethoprim-sulfamethoxazole,and vancomycin.Five isolates were resistant to tetracycline,and three strains of ST87,one strain of ST8,one strain of ST224,and two strains of ST87 were simultaneously resistant to erythromycin.The tet(M)tetracycline re-sistance genes and msr(D)and mef(A)erythromycin resistance genes from three strains of ST87 and one strain of ST8 were carried by a phage similar to phi1605 in Erysipelothrix,with>95%identity.The tet(M)gene from the ST224 isolates was carried by a transposon similar to Tn5801_B15 in Enterococcus faecalis,with>95%identity.Drug-resistant strains of Listeria monocytogenes were found in livestock and poultry meat on sale in Weifang,particularly strains of type ST87 and ST224 simultaneously carrying highly pathogenic virulence islands,thus posing a threat to food safety and public health.These findings therefore warrant attention from relevant depart-ments and strengthened monitoring efforts.

OBJECTIVE: To investigate the predictive value of the prognostic nutritional index (PNI) and systemic inflammatory response index (SIRI) for short-term efficacy and prognosis in newly treated patients with peripheral T-cell lymphoma (PTCL). METHODS: The general data, laboratory indicators, disease stage and other clinical data of 91 newly treated PTCL patients admitted to the Affiliated Hospital of Xuzhou Medical University from January 2015 to December 2023 were retrospectively analyzed. The optimal cutoff values for PNI and SIRI were determined using receiver operating characteristic (ROC) curves, and the patients were stratified into groups based on these cutoffs to compare clinical features and short-term efficacy between the different groups. Kaplan-Meier method was used to plot survival curves, and univariate and multivariate analyses were performed to identify the factors affecting overall survival (OS). RESULTS: The optimal cutoff values for PNI and SIRI were 45.30 and 1.74×10⁹/L, respectively. Patients in different PNI groups showed statistically significant differences in age, Ann Arbor stage, lactate dehydrogenase (LDH) level, international prognostic index (IPI), prognostic index for PTCL-not otherwise specified (PIT), pathological subtypes, and complete response (CR) rate (P < 0.05). PTCL patients in different SIRI groups exhibited significant differences in Ann Arbor stage, LDH level, IPI score, PIT score, and CR rate (P < 0.05). Logistic regression analysis showed that age ≥60 years old (OR =2.750), Ann Arbor stage Ⅲ-Ⅳ (OR =5.200), IPI score ≥2 (OR =7.650), low PNI (OR =3.296), and high SIRI (OR =3.130) were independent risk factors affecting treatment efficacy in PTCL patients (P < 0.05). Cox proportional hazards regression model analysis showed that low PNI and elevated β₂-microglobulin (β₂-MG) levels were independent risk factors affecting OS (P < 0.05). CONCLUSION PNI and SIRI have certain application value in evaluating short-term efficacy and prognosis in patients with PTCL. Compared with SIRI, PNI demonstrates greater predictive value for patient prognosis.
Humans ; Prognosis ; Lymphoma, T-Cell, Peripheral/therapy* ; Retrospective Studies ; Nutrition Assessment ; Male ; Female ; Middle Aged ; ROC Curve ; Inflammation