ObjectiveTo explore the role of the histone deacetylase Sirtuin-1 （SIRT1）/p53 signaling pathway in promoting apoptosis of non-small cell lung cancer cells （NSCLC） induced by the co-stimulatory molecule B7 homolog 3 （B7-H3）. MethodsThe GEPIA 2 platform was used for survival analysis of NSCLC patients based on B7⁃H3 gene expression levels. The Gene Enrichment Analysis （GSEA） method was used to analyze the enrichment characteristics of B7⁃H3 molecules in the gene set of cell apoptosis. In the non-small cell lung cancer A549 cell line， B7⁃H3 was knocked down， and the protein expression levels of SIRT1 and p53 were detected by Western blot. B7⁃H3 was overexpressed in A549 cells and the apoptosis rate was analyzed by flow cytometry after Annexin V/PI double staining. Overexpression of B7⁃H3 and knockdown of SIRT1 were performed in A549 cell line. The expression levels of p53 and apoptosis-related proteins B-cell lymphoma/leukemia-2 （Bcl-2） and Bcl-2-associated X protein （Bax） were detected respectively by Western blot. Cell apoptosis rate was analyzed by flow cytometry after Annexin V/PI double staining. ResultsThe overall survival of the B7-H3 high-expression group was significantly lower than that of the low-expression group （P<0.01）. B7-H3 was significantly enriched in the cell apoptosis signaling pathway and the p53 signaling pathway （P<0.05）. Compared with the control group， the expression of SIRT1 was significantly downregulated， and p53 was significantly upregulated in the B7⁃H3 knockdown group （both P<0.001）. Overexpression of B7-H3 significantly up-regulated SIRT1 protein expression （P<0.05）， down-regulated p53 expression （P<0.01）， and markedly increased the Bcl-2/Bax ratio of apoptosis-related proteins （P<0.001）. The results of Annexin V/PI double staining showed that the apoptosis rate of A549 cells with overexpressed B7⁃H3 decreased （the apoptosis rate of the control group was 26.72%±4.13%， while that of the B7⁃H3 overexpression group was 13.87%±0.82%； P<0.01）. In B7-H3-overexpressing cell lines， SIRT1 knockdown significantly reversed apoptosis （P<0.05）， up-regulated p53 protein expression （P<0.001）， and markedly reduced the Bcl-2/Bax ratio （P<0.001）. ConclusionB7-H3 molecule inhibits the apoptosis of non-small cell lung cancer cells via the SIRT1/p53 signaling pathway.

OBJECTIVE: To explore the application value of artificial intelligence (AI)-assisted chromosomal karyotype analysis in the diagnosis of prenatal chromosomal mosaicism. METHODS: A retrospective analysis was conducted on 172 pregnant women who underwent amniocentesis at the Department of Medical Genetics and Prenatal Diagnosis, the Third Affiliated Hospital of Zhengzhou University between January 2019 and December 2024. All cases whose fetuses were diagnosed with chromosomal mosaicism via karyotype analysis and stratified into two groups based on the analytical software employed: the conventional analysis group (n = 70), which utilized Leica analysis software for karyotype image recognition and cell counting; and the AI-assisted analysis group (n = 102), which utilized AI-assisted software for the same procedures. The clinical performance of AI-assisted karyotype analysis in diagnosing chromosomal mosaicism was comprehensively evaluated by comparing the types of mosaic karyotypes, distribution of mosaic ratios, and verification outcomes of different detection modalities between the two groups. This study was approved by the Medical Ethics Committee of the Third Affiliated Hospital of Zhengzhou University (Ethics No.: 2024-406-01). RESULTS: No statistically significant difference was observed in baseline characteristics (maternal age, gestational week, and indications for prenatal diagnosis) between the two groups. Regarding the detection efficacy for numerical and structural mosaicisms, no significant difference was found in the detection of numerical mosaicism. However, the conventional analysis group exhibited a significantly higher detection rate of autosomal structural mosaicism compared to the AI-assisted group (11.43% vs. 0.98%, P < 0.05). Numerical mosaicism cases were further verified using copy number variation sequencing (CNV-seq) and/or fluorescence in situ hybridization (FISH). The AI-assisted group demonstrated a significantly lower inconsistency rate (5.56% vs. 20.41%, P < 0.05) compared to the conventional group. For low-proportion (< 10%) chromosomal mosaicism, the AI-assisted group had a significantly lower detection rate (13.25% vs. 29.69%, P < 0.05). Subsequent validation of low-proportion mosaicism by CNV-seq and/or FISH showed a higher consistency rate in the AI-assisted group (81.82% vs. 54.55%), though the difference did not reach statistical significance (P = 0.360). CONCLUSION For the karyotyping analysis of prenatal chromosomal mosaicism, AI-assisted karyotype analysis shows high accuracy and consistency in identifying numerical chromosomal mosaicism, particularly in reducing the detection of low-proportion (< 10%) mosaicism while improving verification accuracy. AI-assisted analysis can significantly improve the detection accuracy of numerical mosaicism and mitigate the risk of misclassification for low-proportion (< 10%) mosaicism, thereby providing more precise clinical evidence for the prenatal diagnosis of chromosomal mosaicisms.
Humans ; Female ; Mosaicism ; Pregnancy ; Karyotyping/methods* ; Artificial Intelligence ; Prenatal Diagnosis/methods* ; Adult ; Retrospective Studies ; Chromosome Disorders/genetics* ; Amniocentesis

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.

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.

A growing body of research points out that gut microbiota plays a key role in tumor immunotherapy. By optimizing the composition of intestinal microbiota, it is possible to effectively improve immunotherapy resistance and enhance its therapeutic effect. This article comprehensively analyzes the mechanism of intestinal microbiota influencing tumor immunotherapy resistance, expounds the current strategies for targeted regulation of intestinal microbiota, such as traditional Chinese medicine and plant components, fecal microbiota transplantation, probiotics, prebiotics and dietary therapy, and explores the potential mechanisms of these strategies to improve patients' resistance to tumor immunotherapy. At the same time, the article also briefly discusses the prospects and challenges of targeting intestinal microbiota to improve tumor immunotherapy resistance, which provides a reference for related research to help the strategy research of reversing tumor immunotherapy resistance.

Objective To construct 5 machine-learning models and compare their performance in predicting the associations between pre-pregnancy socio-psycho-behavioral exposures of both spouses and preconception outcomes.Methods Based on Chongqing Preconception Reproductive Health and Birth Outcome Cohort of volunteers recruited from Chongqing Health Center for Women and Children during January 2019 and March 2022,5 447 couples were recruited and surveyed through interviewer-interview for the demographic and social-psychological-behavioral data of both spouses(221 variables).According to the inclusion and exclusion criteria,4 097 couples were finally included,and randomly assigned into a training set(n=2 867 spouses)and a validation set(n=1 230 spouses)at a ratio of 7∶3.Feature analysis and collinear screening were applied to select the potential exposure factors.In consideration of difficulty to carry out semen parameters analysis in primary healthcare institutions,feature Set 1 including sperm parameters and feature Set 2 excluding semen parameters were constructed by including or excluding sperm quality simultaneously in the training set and the validation set.Five algorithms,that is,Logistic Regression,Naive Bayes,Random Forest,Gradient Boosting Machine,and Support Vector Machine,were used to construct preconception outcome prediction models,and the parameters of each model were optimized using random search combined with grid search.The predictive performance of each model was compared using precision,recall,F1 score,area under the receiver operating characteristic curve(AUC),and calibration curve.The optimal model was then selected by comparing the changes in the predictive ability of the questionnaire data for fertility outcomes with or without semen parameters.Results There were 24 variables screened out in feature Set 1,and 16 variables in feature Set 2.In feature Set 1,the gradient boosting machine performed better,with a relatively higher AUC value(0.651)and better F1 score(0.61).The logistic regression model performed stably(AUC value=0.647)and was suitable as the reference model.The random forest(AUC value=0.641),Naive Bayes(AUC value=0.641),and support vector machine(AUC value=0.634)performed second-best.By utilizing the gradient boosting machine,comparable results were found between the predictions from feature sets with or without semen parameters,as in feature Set 1,the AUC value of its validation set was 0.651(95%CI:0.629～0.681),the prediction accuracy was 0.63,the recall rate was 0.65,and the average precision value F1 was 0.61;and in feature Set 2,the AUC value of its validation set was 0.649(95%CI:0.624～0.663),and both the calibration curves were close to the ideal curve.The prediction results indicated that in feature Set 1,the features highly negatively correlated with preconception outcomes were female age,male age,and no pregnancy within 1 year without contraception,while the features highly positively correlated with preconception outcomes were female pregnancy history,total sperm vitality,and use of contraceptive measures before enrollment.Conclusion Among the 5 machine-learning algorithms performed in this cohort data,the gradient boosting machine shows slightly better performance.There are 24 factors being associated with preconception outcomes in both spouses,and the performance of the simplified model excluding semen parameters is not significantly declined.It is feasible to use machine-learning methods to predict human preconception outcomes through social-psychological-behavioral questionnaires.

Travelling wave structures for lossless ion manipulations(TW-SLIM)employ travelling wave electric fields to propel ions forward,enabling exceptionally long transmission paths and holding great potential for applications in material transportation and separation.In this study,different from previous studies focusing on the transport performance of macromolecules such as proteins in TW-SLIM,the transmission performance of small molecules(<200 amu)was investigated and analyzed in the turning TW-SLIM through the COMSOL simulation platform,to explore the influence of electrostatic field of protective electrode and radio frequency(RF)electric field on ion transport efficiency,and obtain the optimal value.Compared to macromolecules,small molecules required lower voltage amplitudes from guard electrodes but stricter requirements in terms of the peak-to-peak amplitude and frequency of RF voltage for lossless transmission.Using dimethyl methylphosphonate(DMMP)as a sample and testing it on the TW-SLIM experimental platform,when the protective voltage amplitude was 5 V and the peak-to-peak voltage of the radio-frequency electrode was 440 V at 1.5 MHz,the ion transmission efficiency reached 100%,achieving lossless transmission.The experimental results provided valuable references for application of TW-SLIM in separation and detection of small molecular substances,such as explosives and drugs.

Mineral oil contaminants composed of saturated hydrocarbons(MOSH)and aromatic hydrocarbons(MOAH)are commonly found in edible oils and related processed foods.Currently,the analysis of mineral oils primarily employs the liquid chromatography-gas chromatography-flame ionization detector(LC-GC-FID)method.Liquid chromatography is used to purify and separate MOSH and MOAH from interfering substances,and the interface technology transfers MOSH or MOAH into different GC channels for quantitative analysis.The MOSH and MOAH chromatograms typically exhibit an irregular hump shape,with sharp peaks above the hump representing natural hydrocarbon interferences,which usually do not affect the identification of the hump profile.However,when the purification of interferences is incomplete,they can form one or more gaps above the hump,interfering with the accurate judgment and delineation of the hump profile,and leading to poor reproducibility of analysis results of mineral oil.In this study,an algorithm that mimicked the manual drawing of the hump shape or contour was proposed for automatically determining the mineral oil hump contour(i.e.,the lower envelope line).The algorithm used a multiple second-order difference quotient filtering method to identify and remove the gaps above the hump.The method involved first searching and determining the lowest value of the mineral oil hump,which was the valley point sequence,and then applying second-order difference quotient filtering to the valley point sequence.Compared to the hump,the second-order difference quotient of sharp peaks was a significantly larger negative value.By filtering out the points in the valley point sequence with larger negative second-order difference quotients(or multiple second-order difference quotients),the sharp peaks above the hump were removed.To verify the accuracy of the algorithm,42 different types of samples,including edible oils and milk powders were analyzed,using both the automatic algorithm and manual methods.The results showed that there were no significant differences in the detected mineral oil contents between these two methods.

ObjectiveTo investigate the distribution of traditional Chinese medicine （TCM） syndrome elements in type 2 diabetes mellitus （T2DM） patients based on maximum body mass index （maxBMI） and explore their association with complication risks. MethodsA retrospective cross-sectional study was used to collect clinical data from hospitalized T2DM patients， extracting age， gender， smoking history， alcohol consumption history， duration of disease， HbA1c level， complications， and TCM syndromes， and extracting the syndrome elements of disease location and disease nature based on their TCM syndromes. MaxBMI was calculated by telephone survey of patients' self-reported maximum body weight； patients with maxBMI ≥24 kg/m² were classified into spleen-heat syndrome group， and those with maxBMI ＜24 kg/m² were classified into consumptive-heat syndrome group. The distribution of TCM syndrome types and syndrome elements of patients in the two groups were analysed. Then the propensity score matching method was used to balance the baseline characteristics between the two groups and compare the differences in the distribution of syndrome types and syndrome elements and the risk of macrovascular and microvascular complications between the two groups. ResultsAmong the 1178 T2DM patients， syndrome elements in spleen-heat patients （1034 cases） were primarily located in the spleen （351 cases， 33.95%）， liver （240 cases， 23.21%）， and stomach （139 cases， 13.44%）， while in consumptive-heat patients （144 cases）， they were concentrated in the spleen （57 cases， 39.58%）， liver （34 cases， 23.61%）， and kidneys （17 cases， 11.81%）； regarding syndrome elements of disease nature， spleen-heat patients were predominantly characterized by qi deficiency （481 cases， 46.52%）， phlegm （353 cases， 22.73%）， and dampness （241 cases， 23.31%）， whereas consumptive-heat patients showed more qi deficiency （84 cases， 58.33%） and yin deficiency （44 cases， 30.56%）. After propensity score matching， 132 cases were included in each group， and no statistically significant differences were observed in the distribution of syndrome elements of disease location between the two groups （P＞0.05）， but the phlegm element was significantly more prevalent in spleen-heat patients than in consumptive-heat patients （P = 0.006）. Regarding the risk of complications， spleen-heat patients had a significantly higher risk of developing macrovascular complications compared to consumptive-heat patients （OR=2.04， P=0.010）， while no significant differences were found between groups in the occurrence of microvascular complications （P＞0.05）. ConclusionThe spleen-heat T2DM patients show a more frequent syndrome element of disease nature of phlegm， and a higher risk of developing macrovascular complications compared to consumptive-heat patients.

ObjectiveTo construct a rat model of psoriasis with spleen deficiency and dampness obstruction syndrome （external dampness type）， and evaluate the macroscopic manifestations and microscopic indicators of the model. MethodsTwenty-two SD rats were divided into normal group （n=3）， common psoriasis group （n=5）， spleen deficiency and dampness obstruction syndrome （external dampness type） group （n=7）， and psoriasis with spleen deficiency and dampness obstruction syndrome （external dampness type） group （n=7）. The spleen deficiency and dampness obstruction syndrome （external dampness type） rat model was established through 32-week exposure to an artificially simulated high-humidity environment， while the common psoriasis model was developed via 7-day topical application of imiquimod cream， and these two approaches were combined to construct a composite model of psoriasis with spleen deficiency and dampness obstruction syndrome （external dampness type）. Rats in the normal group were housed under normal humidity conditions. The general state， tongue manifestation of rats were observed to evaluate the macroscopic syndrome manifestations； the microscopic syndrome manifestations of rats were evaluated through adipose tissue and liver tissue changes； the severity of psoriasis in rats was evaluated through skin pathological changes， psoriasis area and severity index （PASI）， proliferating cell nuclear antigen （PCNA） expression and spleen tissue changes； changes in rat CD4⁺ interferon-γ⁺ cells （CD4⁺IFN-γ⁺ cells）， CD4⁺ tumour necrosis factor-α+ cells （CD4⁺ TNF-α⁺ cells）， and forkhead framing protein P3⁺ regulatory T cells （CD3⁺CD4⁺FoxP3⁺ Treg cells） were detected by flow cytometry. ResultsMacroscopically， both the spleen deficiency and dampness obstruction syndrome （external dampness type） group and psoriasis with spleen deficiency and dampness obstruction syndrome （external dampness type） group exhibited manifestations of spleen deficiency and dampness obstruction， including lethargy， huddling behavior， dull and disheveled fur， as well as soft or loose stools and perianal soiling in some individuals； both these two groups displayed enlarged tongue， swollen， and moist tongue texture， accompanied by slippery tongue surface. Microscopically， compared to the common psoriasis group， the psoriasis with spleen deficiency and dampness obstruction syndrome （external dampness type） group showed increased epididymal fat index （P＜0.05）； compared to the normal group and spleen deficiency and dampness obstruction syndrome （external dampness type） group， the psoriasis with spleen deficiency and dampness obstruction syndrome （external dampness type） group demonstrated significantly elevated spleen mass （P＜0.05）， while hepatic gross morphology and HE staining revealed no significant histopathological changes across all groups. Dorsal skin lesions were markedly exacerbated in the psoriasis with spleen deficiency and dampness obstruction syndrome （external dampness type） group when compared to those in common psoriasis group. Both the common psoriasis group and psoriasis with spleen deficiency and dampness obstruction syndrome （external dampness type） group exhibited significantly higher erythema scores， scaling scores， infiltration scores， PASI total scores， and proportions of CD3⁺CD4⁺FoxP3⁺Treg cells compared to the normal group and spleen deficiency and dampness obstruction syndrome （external dampness type） group （P＜0.05）， with pronounced PCNA-positive expression observed in the epidermal basal layer and dermis； the psoriasis with spleen deficiency and dampness obstruction syndrome （external dampness type） group displayed significantly increased proportions of CD4⁺TNF-α⁺cells compared to the spleen deficiency and dampness obstruction syndrome （external dampness type） group （P＜0.05）； whereas no significant differences were detected in CD4⁺IFN-γ⁺cell proportions among groups （P＞0.05）. ConclusionThe rat model of psoriasis with spleen deficiency and dampness obstruction syndrome （external dampness type） can be successfully constructed by artificially simulating a high-humidity environment combined with imiquimod induction.