BACKGROUND:Fibromyalgia syndrome,as a common rheumatic disease,is related to central sensitization and immune abnormalities.However,the specific mechanism has not been elucidated,and there is a lack of specific diagnostic markers.Exploring the possible pathogenesis of this disease has important clinical significance. OBJECTIVE:To screen the potential diagnostic marker genes of fibromyalgia syndrome and analyze the possible immune infiltration characteristics based on bioinformatics methods,such as weighted gene co-expression network analysis(WGCNA),and machine learning. METHODS:Gene expression profiles in peripheral serum of fibromyalgia syndrome patients and healthy controls were obtained from the gene expression omnibus(GEO)database.The differentially co-expressed genes were screened in the expression profile by differential analysis and WGCNA analysis.Least absolute shrinkage and selection operator(LASSO)and support vector machine-recursive feature elimination(SVM-RFE)machine learning algorithm were further used to identify hub biomarkers,and draw receiver operating characteristic curve(ROC)to evaluate the accuracy of diagnosing fibromyalgia syndrome.Finally,single sample gene set enrichment analysis(ssGSEA)and gene set enrichment analysis(GSEA)were used to evaluate the immune cell infiltration and pathway enrichment in patients with fibromyalgia syndrome. RESULTS AND CONCLUSION:Eight down-regulated differentially expressed genes(DEGs)were obtained after differential analysis of the GSE67311 dataset according to the conditions of log2|(FC)|>0 and P<0.05.After WGCNA analysis,497 genes were included in the module(MEdarkviolet)with the highest positive correlation(r=0.22,P=0.04),and 19 genes were included in the module(MEsalmon2)with the highest negative correlation(r=-0.41,P=6×10-5).After intersecting DEGs and the module genes of WGCNA,seven genes were obtained.Four genes were screened out by LASSO regression algorithm and five genes were screened out by SVM-RFE machine learning algorithm.After the intersection of the two,three core genes were identified,which were germinal center associated signaling and motility like,integrin beta-8,and carboxypeptidase A3.The areas under the ROC curve of the three core genes were 0.744,0.739,and 0.734,respectively,indicating that they have good diagnostic value and can be used as biomarkers for fibromyalgia syndrome.The results of immune infiltration analysis showed that memory B cells,CD56 bright NK cells,and mast cells were significantly down-regulated in patients with fibromyalgia syndrome compared with the control group(P<0.05),and were significantly positively correlated with the above three biomarkers(P<0.05).The enrichment analysis suggested that there were nine fibromyalgia syndrome enrichment pathways,mainly related to olfactory transduction pathway,neuroactive ligand-receptor interaction,and infection pathway.The above results showed that the occurrence and development of fibromyalgia syndrome are related to the involvement of multiple genes,abnormal immune regulation,and multiple pathways imbalance.However,the interactions between these genes and immune cells,as well as their relationships with various pathways need to be further investigated.

Objective To explore the association between different levels of fluoride exposure and dyslipidemia in elderly people, and to analyze the influencing factors and their interactions. Methods A total of 1 143 elderly people over 60 years old were randomly selected from historical high water fluorosis areas and control areas in Tianjin. Logistic regression model and classification tree model were used to analyze the influencing factors of dyslipidemia, and to analyze the interaction between high fluoride exposure and relevant influencing factors on dyslipidemia. Results The prevalence of elevated low density lipoprotein cholesterol (LDL-C) was 5.69% (65/1 143). There was a significant difference in the prevalence of high LDL-C in different fluoride-exposed areas (2 = 0.092，P = 0.762). Multivariate logistic analysis showed that high fluoride exposure (OR=2.306，95%CI：1.185-4.491) and abdominal obesity (OR=2.274，95%CI：1.299-3.978) were risk factors for high LDL-C, while type B personality (OR=0.529，95%CI：0.308-0.908) was a protective factor for high LDL-C. The results of classification tree model showed that abdominal obesity contributed the most to the prevalence of high LDL-C in the elderly, followed by high fluoride exposure and hyperglycemia. There was a significant multiplicative interaction between high fluoride exposure and abdominal obesity on dyslipidemia (OR=5.191,95%CI：1.609-16.745，P=0.006). Conclusion High fluoride exposure may increase the risk of high LDL-C, and there is a multiplicative interaction between high fluoride exposure and abdominal obesity on dyslipidemia.

Hepatocellular carcinoma (HCC) is one of the fastest growing cancers in the world, ranking fourth among the causes of cancer-induced death in the world. At present, the field of HCC treatment is developing rapidly, and immunotherapy has been recognized as a promising treatment method, in which T cells play a key role in HCC immunotherapy. However, in the case of virus infection or in tumor microenvironment (TME), T cells will be continuously stimulated by antigens and then fall into the state of T cell exhaustion (Tex). This state will not only reduce the immunity of patients but also lead to poor efficacy of immunotherapy. Therefore, to deeply analyze the mechanism of Tex and to explore effective strategies to reverse Tex is the key point in the immunotherapy for HCC. This review aims to summarize the mechanism of Tex in HCC patients, and the current situation and shortcomings of drug research and development to reverse Tex at this stage, in order to provide theoretical basis for the optimization of immunotherapy regimen for HCC patients.
Humans ; Carcinoma, Hepatocellular/therapy* ; Liver Neoplasms/therapy* ; Immunotherapy/methods* ; T-Lymphocytes/immunology* ; Tumor Microenvironment/immunology* ; Animals ; T-Cell Exhaustion

Objective: To understand the dose response relationship between urinary fluoride and dental fluorosis among children from drinking water borne endemic fluorosis areas in Tianjin, so as to provide a scientific basis for assessing fluoride exposure risk among children from endemic areas and establishing reference values for urinary fluoride. Methods: From January to December 2024, 83 endemic villages were selected in Tianjin. A total of 2 382 children aged 8-12 years from these villages underwent dental fluorosis examination, along with water fluoride and urinary fluoride testing. Additionally, data from areas where the drinking water fluorosis control target was achieved for more than 12 years (10 villages, 50 people per village) were included as controls. A restricted cubic spline model was used to analyze the relationship between urinary fluoride levels and dental fluorosis prevalence, and benchmark dose (BMD) and benchmark dose lower bound (BMDL), as well as reference dose (RfD), were calculated using the benchmark dose method. Results: The prevalence rates of dental fluorosis among children in drinking water borne endemic fluorosis areas and areas of normal fluoride content in water in Tianjin were 10.58%, 7.60%, with a geometric mean urinary fluoride level of 0.72 and 0.60 mg/L,respectively. There were statistically significant differences in both dental fluorosis prevalence and geometric mean urinary fluoride levels between the drinking water borne endemic fluorosis areas group and the areas of normal fluoride content in water ( χ 2/Z = 4.05 , -7.31, both P <0.05). Across different periods of water source improvement, there were statistically significant differences in overall population, male, and female dental fluorosis prevalence rates and geometric mean urinary fluoride levels ( χ 2/H =44.95, 23.96, 21.05; 168.39, 63.93, 107.50, all P <0.01). Significant differences were also observed across age groups among children from drinking water borne endemic fluorosis areas in terms of dental fluorosis prevalence and geometric mean urinary fluoride levels ( χ 2/H =32.14, 79.73, both P <0.01). The results of the restricted cubic spline model showed that the risk of dental fluorosis in different sex, age and overall children in the drinking water borne endemic fluorosis areas increased significantly with rising urinary fluoride concentration(all P-general trend <0.05). The BMD value for the drinking water borne endemic fluorosis areas was 1.72 mg/L, the BMDL was 1.31 mg/L, and the RfD was 1.31 mg/L. Conclusions The prevalence of dental fluorosis among children in the drinking water borne endemic fluorosis areas in Tianjin has been effectively controlled, but it is still higher than that in the areas of normal fluoride content in water. Moreover, urinary fluoride levels and dental fluorosis prevalence among children from drinking water borne endemic fluorosis areas show a clear dose response relationship.

Objective:To explore the correlation between clinical phenotypes and genotypes among 46 children with SCN1A-related developmental epileptic encephalopathy (DEE). Methods:Clinical data of 46 children with DEE and SCN1A variants identified at the Guangzhou Women and Children′s Medical Center between January 2018 and June 2022 were collected. The children were grouped based on their age of onset, clinical manifestations, neurodevelopmental status, and results of genetic testing. The correlation between SCN1A genotypes and clinical phenotypes was analyzed. Results:Among the 46 patients, 2 children (4.35%) had developed the symptoms before 3 months of age, 42 (91.30%) were between 3 to 9 months, and 2 cases (4.35%) were after 10 months. Two cases (4.35%) presented with epilepsy of infancy with migrating focal seizures (EIMFS), while 44 (95.7%) had presented with Dravet syndrome (DS), including 28 cases (63.6%) with focal onset (DS-F), 13 cases (29.5%) with myoclonic type (DS-M), 1 case (2.27%) with generalized type (DS-G), and 2 cases (4.55%) with status epilepticus type (DS-SE). Both of the two EIMFS children had severe developmental delay, and among the DS patients, 7 cases had normal development, while the remaining had developmental delay. A total of 44 variants were identified through genetic sequencing, which included 16 missense variants and 28 truncating variants. All EIMFS children had carried the c. 677C>T (p.Thr226Met) missense variant. In the DS group, there was a significant difference in the age of onset between the missense variants group and the truncating variants group ( P < 0.05). Missense variants were more common in D1 (7/15, 46.7%) and pore regions (8/15, 53.3%), while truncating variants were more common in D1 (12/28, 42.9%). Children with variants outside the pore region were more likely to develop myoclonic seizures. Conclusion:The clinical phenotypes of DEE are diverse. There is a difference in the age of onset between individuals with truncating and missense variants in the SCN1A gene. Missense variants outside the pore region are associated with a higher incidence of myoclonic seizures.

Objective:To assess the capability of seven reference medical laboratories to detect BCR::ABL1 p210 transcription levels and to compare the results among those laboratories.Methods:The interlaboratory comparison was carried out in two stages. The samples were prepared by the reference laboratory. The quantitative values of BCR::ABL1 p210 of the comparison samples covered 0.001%-0.01%, 0.01%-0.1%, 0.1%-1%, 1%-10% and>10% in each stage. Real-time quantitative PCR (RT-PCR) and dPCR (digital PCR) were used to examine the samples. The conversion factor (CF) was calculated and validated for each laboratory.Results:In the RT-PCR comparison, one laboratory was failed to detect BCR::ABL1 p210 in fourteen samples at the first stage. The results of the other six laboratories were qualified with the bias <±1.2 folds (-0.133-0.338) and 95% limits of agreement within ±5 folds (upper limit 0.147-0.785, lower limit -0.770--0.109), and the corresponding CF values were calculated and validated. In the dPCR comparison, one laboratory did not report results at the second stage. The results of the other six laboratories were qualified with the bias <±1.2 folds (-0.026-0.267) and 95% limits of agreement within±5 folds (upper limit 0.084-0.991, lower limit -0.669--0.135), and the corresponding CF values were calculated and validated. The samples with BCR::ABL1 p210 quantitative values of 0.01%-0.1%, 0.1%-1%, 1%-10% and >10% could be detected by both RT-PCR and qPCR. When the quantitative value of BCR::ABL1 p210 was 0.001%-0.01%, the detection rate of dPCR was higher than that of RT-PCR (85.56% vs. 68.00%).Conclusions:A good consistency is present among various laboratories. The quantitative value of BCR::ABL1 p210 is comparable among laboratories as shown by the CF value conversion. For quantitative detection of BCR::ABL1 p210 deep molecular reaction, dPCR has a higher positive detection rate and more advantages than RT-PCR. To ensure the accuracy and reproducibility of the BCR::ABL1 p210 test, it is imperative for every laboratory to enhance their daily quality control practices.

Objective To investigate the status and the influencing factors of thyroid volume of children aged 8-10 years in Tianjin. Methods Among the 1-2 primary schools were randomly selected from 12 districts in Tianjin. A total of 1 090 children were selected by class cluster sampling method (half male and half female, with a balanced age distribution). A questionnaire survey was conducted. Children’s height, weight and thyroid volume were measured, and their salt iodine content and urinary iodine content were detected. Results I n this study, the median urinary iodine in children was 161.35 µg/L, the mean thyroid volume was 2.56 mL, and the goiter rate was 3.58%. Univariate analysis showed that age, BSA, salt iodine content, urinary iodine content, eating habits, food taste, eating lunch at school, father's work, anxiety and depression, pressure, and different regional grouping were the influencing factors of thyroid volume (P<0.05). Multivariate linear regression showed that BSA, age, food taste, and urinary iodine content had significant independent effects on thyroid volume (P<0.05). Conclusion In Tianjin, the iodine nutrition level of children aged 8-10 years is at an appropriate level. When evaluating the thyroid volume of children, in addition to age factors, other factors such as physical development level and iodine intake should also be considered.

Hepatocellular carcinoma(HCC)is the most common type of primary liver cancer and the third leading cause of cancer-related deaths,and it is a serious threat to human health and has become a clinical problem that needs to be solved urgently.Extracellular vesicles(EV)are membrane vesicles containing multiple components and play an important role in the development and progression of HCC.This article summarizes the effect of EVs of different origins on HCC and analyzes the mechanism of action of EV on HCC,so as to provide new perspectives for the diagnosis and treatment of HCC.

Tumor necrosis factor-α(TNF-α)is involved in the regulation of multiple biological processes such as the proliferation,invasion,migration,and chemotherapy resistance of hepatocellular carcinoma(HCC)cells through TNF receptor-mediated signaling pathways.At the same time,TNF-α also plays a role in inducing the apoptosis of HCC cells.Some TNF-α inhibitors have been shown to inhibit the progression of HCC and prolong survival time.At present,the potential mechanism of action of TNF-α in HCC remains unclear,and exploration of the interaction between TNF-α and HCC can help to determine the potential therapeutic targets for HCC.This article summarizes the latest research advances in the mechanism of action of TNF-α in HCC and introduces the possibility of targeting TNF-α as a treatment method for HCC,in order to provide a theoretical basis for the prevention and treatment of liver cancer and drug research and development.

Objective To explore the independent risk factors that affect the overall survival(OS)of elderly patients with hepatocellular carcinoma(HCC,≥60 years old)and build a nomogram prediction model.Methods Clinical data of all elderly patients with HCC from the SEER database from 2005 to 2020 were downloaded from SEER database.In accordance with the inclusion and exclusion criteria,the screened patients were randomly assigned to a training group(70%)and a validation group(30%).The independent risk factors of elderly patients with HCC were determined by univariate and multivariate Cox regression analyses and further validated by Kaplan-Meier survival analysis.On the basis of the determined variables,nomograms were developed and verified to predict the OS of elderly patients with HCC at 6,12,and 24 months.The consistency index(C index),calibration curve,receiver's operating characteristic(ROC)curve,and area under curve(AUC)were used to evaluate the prediction efficiency and discrimination ability of the prediction model,and decision curve analysis(DCA)was used to evaluate the potential clinical application value of the nomogram.Results A total of 1134 elderly patients with HCC were included,with 793 in the training group and 341 in the validation group.Seven variables,including age,clinical grade,clinical stage,M stage,tumor size classification,and radiotherapy,were identified as independent prognostic factors of this population.The constructed nomogram shows excellent prediction performance,with C indices of 0.745 in the training group and 0.704 in the validation group.The AUC values of the training group at 6,12,and 24 months were 0.785,0.788,and 0.798,respectively,and those of the validation group were 0.780,0.725,and 0.607,respectively.The calibration curve shows good consistency from the predicted survival probability to the actual probability.The ROC curve and DCA show that the nomogram proposed in this study has good prediction ability.Conclusion Age,clinical grade,clinical stage,M stage,tumor size classification,and radiotherapy are important influencing factors for the survival of elderly patients with HCC.The prediction model of prognosis nomogram constructed in this study has good predictive value,and it can be used to predict the OS of elderly patients with HCC,which could be helpful for individualized survival assessment and clinical management of these patients.