Inflammatory diseases (IDs) are a general term of diseases characterized by chronic inflammation as the primary pathogenetic mechanism, which seriously affect the quality of patient′s life and cause significant social and medical burden. Current drugs for IDs include nonsteroidal anti-inflammatory drugs, corticosteroids, immunomodulators, biologics, and antioxidants, but these drugs may cause gastrointestinal side effects, induce or worsen infections, and cause non-response or intolerance. Given the outstanding performance of metal polyphenol network (MPN) in the fields of drug delivery, biomedical imaging, and catalytic therapy, its application in the diagnosis and treatment of IDs has attracted much attention and significant progress has been made. In this paper, we first provide an overview of the types of IDs and their generating mechanisms, then sort out and summarize the different forms of MPN in recent years, and finally discuss in detail the characteristics of MPN and their latest research progress in the diagnosis and treatment of IDs. This research may provide useful references for scientific research and clinical practice in the related fields.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.

OBJECTIVES: According to the World Health Organization (WHO), infertility rates have been steadily rising worldwide. Identifying risk factors for contrast agent reflux into the myometrium during hysterosalpingo-contrast sonography (HyCoSy) is of clinical significance in reducing this complication and improving infertility treatment. However, there is currently no standardized pre-evaluation method for predicting intra-myometrial contrast reflux, with clinical assessment often relying on physician experience and patient symptoms. This study aims to identify imaging risk factors for contrast agent reflux into the myometrium using four-dimensional (4D) HyCoSy and to construct a nomogram-based predictive model to assist in clinical decision-making. METHODS: A retrospective analysis was conducted on 1 274 infertile women who underwent 4D HyCoSy at the Women and Children's Hospital of Hunan and the the Third Xiangya Hospital of Central South University from January 1, 2020, to December 15, 2022. Patients were divided into a reflux group (n=234) and a non-reflux group (n=1 040) based on the presence of intra-myometrial contrast reflux. Univariate and multivariable Logistic regression analyses were used to identify significant predictors, which were then used to construct a nomogram model. Internal validation was performed using 500 bootstrap resamples. RESULTS: The age of the reflux group was significantly higher than that of the non-reflux group [(31.82±5.27) years vs (30.66±4.83) years, P=0.001 1]. Primary infertility was more common in the non-reflux group (50.96%), while secondary infertility dominated in the reflux group (76.50%), with 72.65% having a history of gynecological surgery (P<0.001). Abnormal menstrual volume and discomfort during the procedure were more common in the reflux group, while the non-reflux group tolerated higher contrast agent doses (P<0.001). Imaging differences included endometrial thickness, tubal wall smoothness, and peritoneal contrast dispersion, with the non-reflux group showing thicker endometrium and smoother, more patent tubes. The nomogram model yielded an area under the curve (AUC) of 0.854, indicating good predictive performance. The AUC of the decision curve analysis (DCA) for internal validation of the model was 0.737. When the threshold probability for contrast agent reflux into the myometrium ranged from 0.05 to 0.95, the maximum net benefit reached 0.18. The net benefit of applying the nomogram predictive model exceeded that of either full intervention or no intervention, indicating that the model demonstrates good clinical predictive performance. CONCLUSIONS The nomogram model, based on infertility type, endometrial thickness, contrast agent dose, and discomfort symptoms, effectively predicts intra-myometrial contrast agent reflux after 4D HyCoSy. It provides a valuable tool for clinicians to implement early preventive measures and reduce the risk of contrast leakage and associated complications.
Humans ; Female ; Nomograms ; Contrast Media/adverse effects* ; Retrospective Studies ; Adult ; Ultrasonography/methods* ; Hysterosalpingography/methods* ; Infertility, Female/diagnostic imaging* ; Myometrium/diagnostic imaging* ; Risk Factors

OBJECTIVE: This study aimed to investigate possible serum 25-hydroxyvitamin D [25(OH)D] cutoffs for the associations between 25(OH)D and Bone turnover markers (BTMs), and how GC gene variation influences such cutoffs in Chinese women of childbearing age. METHODS: In total, 1,505 non-pregnant or non-lactating women (18-45 years) were recruited from the 2015 Chinese Adult Chronic Disease and Nutrition Surveillance. Serum 25(OH)D, osteocalcin (OC), procollagen type 1 N-terminal propeptide (P1NP), β-CrossLaps of type 1 collagen containing cross-linked C-telopeptide (β-CTX), and single nucleotide polymorphisms were determined. Locally weighted regression and smoothing scatterplot and segmented regression were performed to estimate the 25(OH)D thresholds. RESULTS: The median serum 25(OH)D was 16.63 (11.96-22.55) ng/mL and the prevalence of low serum 25(OH)D (< 12 ng/mL) was 25.2%. Women with the lowest 25(OH)D had the highest β-CTX. After adjustment for the confounders, 25(OH)D cutoffs for OC [14.04 (12.84-15.23) ng/mL], β-CTX [13.94 (12.49-15.39) ng/mL], and P1NP [13.87 (12.37-15.37) ng/mL] in the whole population, cutoffs for OC [12.30 (10.68-13.91) ng/mL], β-CTX [12.23 (10.22-14.23) ng/mL], and P1NP [11.85 (10.40-13.31) ng/mL] in women with the GC rs2282679 G allele, and cutoffs for OC [12.75 (11.81-13.68) ng/mL], β-CTX [13.05 (11.78-14.32) ng/mL], and P1NP [12.81 (11.57-14.06) ng/mL] in women with the GC rs2282679 T allele, were observed. Below these cutoffs, BTMs were negatively associated with 25(OH)D, while above these cutoffs, BTMs plateaued. CONCLUSION In Chinese women of childbearing age, there were thresholds effect of serum 25(OH)D concentrations on BTMs. The results indicated that serum 25(OH)D concentrations < 13.87 ng/mL in this population had adverse influences on maintaining bone remodeling. BTMs were suppressed at a relatively lower serum 25(OH)D in women with the GC rs2282679 G allele compared with those with the T allele.
Humans ; Female ; Vitamin D/blood* ; Adult ; Middle Aged ; Polymorphism, Single Nucleotide ; Adolescent ; Young Adult ; China ; Biomarkers/blood* ; Bone Remodeling/genetics* ; Vitamin D-Binding Protein/genetics* ; Procollagen/blood* ; Osteocalcin/blood* ; Peptide Fragments/blood* ; East Asian People

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*

Objective To explore the diagnostic value of 68Ga-PSMA-11 PET/CT combined with abnormal prothrombin(PIVKA-Ⅱ)in the diagnosis of different tumors.Methods A total of 200 patients with suspected cancer who underwent examinations in the Affiliated Hospital of Southwest Medical University from September 2021 to December 2023 were retrospectively selected,including 51 suspected liver cancer,49 suspected pancreatic cancer,52 suspected rectal cancer and 48 suspected prostate cancer.All patients underwent both serum PIVKA-Ⅱ testing and 68Ga-PSMA-11 PET/CT imaging.Receiver operating characteristic(ROC)curve analysis was used to assess the diagnostic performance of 68Ga-PSMA-11 PET/CT and serum PIVKA-Ⅱ for liver cancer,pancreatic cancer,rectal cancer and prostate cancer.Results No significant differences were found in general data of 4 suspected tumor groups(P>0.05)except for age.Serum PIVKA-Ⅱ levels were significantly higher in patients with suspected liver cancer and rectal cancer compared with those with suspected pancreatic cancer and prostate cancer(P<0.05).No significant difference was observed in the serum PIVKA-Ⅱ levels between suspected pancreatic cancer group and suspected prostate cancer group(P>0.05).The positive rates of 68Ga-PSMA-11 PET/CT and serum PIVKA-Ⅱ for diagnosing liver,pancreatic,rectal,and prostate cancers were significantly lower than those of pathological examination(49.0%vs.47.1%vs.92.2%,57.1%vs.55.1%vs.87.8%,48.1%vs.44.2%vs.92.3%,64.6%vs.62.5%vs.89.6%,respectively,P<0.05).ROC curve analysis showed that serum PIVKA-Ⅱ had a sensitivity of 79.06%,specificity of 72.02%,area under ROC curve(AUC)of 0.822,and Youden index of 0.512.For 68Ga-PSMA-11 PET/CT,the sensitivity was 79.11%,specificity 72.07%,AUC 0.829,and Youden index 0.510.The combined use of 68Ga-PSMA-11 PET/CT and serum PIVKA-Ⅱ achieved higher diagnostic accuracy,with a sensitivity of 93.28%,specificity of 81.15%,AUC of 0.924 and Youden index of 0.744,all surpassing the single index.Conclusion Both 68Ga-PSMA-11 PET/CT and serum PIVKA-Ⅱ are effective diagnostic tools for liver,pancreatic,rectal,and prostate cancers,with the combined approach yielding superior diagnostic performance.

In recent years, there has been a growing interest in the research on NOD-like receptor thermal protein domain associated protein 3(NLRP3) inflammasome inhibitors in the treatment of inflammatory diseases. The NLRP3 inflammasome is integral to the innate immune response, and its abnormal activation can lead to the release of pro-inflammatory cytokine, consequently facilitating the progression of various pathological conditions. Therefore, investigating the pharmacological inhibition pathway of the NLRP3 inflammasome represents a promising strategy for the treatment of inflammation-related diseases. Currently, the Food and Drug Administration(FDA) has not approved drugs targeting the NLRP3 inflammasome for clinical use due to concerns regarding liver toxicity and gastrointestinal side effects associated with chemical small molecule inhibitors in clinical trials. Natural small molecule compounds such as polyphenols, flavonoids, and alkaloids are ubiquitously found in animals, plants, and other natural substances exhibiting pharmacological activities. Their abundant sources, intricate and diverse structures, high biocompatibility, minimal adverse reactions, and superior biochemical potency in comparison to synthetic compounds have attracted the attention of extensive scholars. Currently, certain natural small molecule compounds have been demonstrated to impede the activation of the NLRP3 inflammasome via various action mechanisms, so they are viewed as the innovative, feasible, and minimally toxic therapeutic agents for inhibiting NLRP3 inflammasome activation in the treatment of both acute and chronic inflammatory diseases. Hence, this study systematically examined the effects and potential mechanisms of natural small molecule compounds derived from traditional Chinese medicine on the activation of NLRP3 inflammasomes at their initiation, assembly, and activation stages. The objection is to furnish theoretical support and practical guidance for the effective clinical application of these natural small molecule inhibitors.
NLR Family, Pyrin Domain-Containing 3 Protein/metabolism* ; Inflammasomes/metabolism* ; Inflammation/drug therapy* ; Anti-Inflammatory Agents/therapeutic use* ; Humans ; Animals ; Disease Models, Animal ; Biological Products/therapeutic use* ; Drug Discovery ; Medicine, Chinese Traditional/methods*

A quantitative analytical method was established for 275 kinds of metabolites in plasma based on ultra-high performance liquid chromatography-triple quadrupole mass spectrometry/multiple reaction monitoring-selected ion monitoring(UHPLC-QQQ-MS/MRM-SIM)technique.Based on UHPLC-high resolution(HRMS)/full MS-parallel reaction monitoring(PRM)technique,165 kinds of lipid metabolites in plasma were qualitatively identified and quantitatively detected to address the analytical challenges of lipid isomers.This quantitative metabolomics approach was successfully applied to a rat myocardial infarction study,identifying and quantifying 372 kinds of metabolites in total.Comparative analysis with the sham-operated group revealed significant alterations in 59 kinds of plasma metabolites in myocardial infarction rats.Key metabolic pathways,which included amino acid metabolism(alanine,aspartate,and glutamate metabolism;glycine,serine,and threonine metabolism,etc.),one-carbon unit metabolism,and tricarboxylic acid cycle,were significantly disrupted.

Objective To investigate the genetic differences among different populations based on 13 autosomal STR loci in CODIS core.Methods Data of 13 autosomal STR loci(CSF1PO,FGA,THO1,TPOX,vWA,D3S1358,D5S818,D7S820,D8S1179,D13S317,D16S539,D18S51,D21S11)were collected from 95 populations in scientific journals between 1999 and 2021,soursed from the PubMed database,which had been published.Allele frequencies of loci were sorted out and forensic genetic parameters including gene differentiation coefficient(Gst),total heterozygosity(Ht),subpopula-tion heterozygosity(Hs)values,and Nei's DA genetic distance were calculated.Principal component analysis,phylogenetic tree,and multidimensional scale analysis were conducted to assess population ge-netic structure.Results A total of 265 alleles were detected at the 13 STR loci in these 95 popula-tions.The mean values of Gst,Ht,and Hs were 0.023 247,0.797 915 and 0.779 365.Population genetic analyses reflected significant differences among populations from Asia,Africa and Europe.In Asian populations,there was a certain degree of distinction between mainland and island populations;the Han population showed a certain degree of distinction with surrounding populations in mainland;while within the Han population,there were two distinct clusters formed by the northern Han and the south-ern Han.Conclusion The 13 autosomal STR loci in CODIS core demonstrate potential value for popu-lation identification across different groups,and may be used for the differentiation of ethnic groups,among different continental populations.

OBJECTIVE: To explore the impact of age on the genetic variant spectrum and prognosis of patients with previously untreated Diffuse large B-cell lymphoma (DLBCL). METHODS: A retrospective analysis was conducted on the clinical data and follow-up information of 254 previously untreated DLBCL patients from 14 hospitals in the Jiangsu Cooperative Lymphoma Group (JCLG) enrolled from July 2018 and July 2023. Following extraction of DNA from tumor tissue samples, next-generation sequencing (NGS) technique was employed to analyze the genetic variant spectrum of the DLBCL patients, with an evaluation of the relationship between age and genetic variants as well as prognosis. This study was approved by the Medical Ethics Committee of the Affiliated Hospital of Nantong University (Ethics No.: 2023-K048-01). RESULTS: The median age of the 254 DLBCL patients was 62 years old, with 55% of patients aged 60 years or above. Clinical evaluation showed that younger (< 60 years) patients had higher complete response (CR) (70% vs. 59%), and objective response rate (ORR) (88% vs. 79%) than older patients, though the difference between the two groups was not statistically. Survival analysis indicated that both the five-year overall survival (OS) (82.7% vs. 71.7%, P = 0.006) and progression-free survival (PFS) (70.6% vs. 50.2%, P < 0.05) rates were significantly higher in younger patients. NGS showed that 99.6% of the patients harbored genetic variants, with PIM1, KMT2D, TP53, MYD88, and CD79B being the most common genes. Age significantly affected the variant frequency of certain genes, with MYC variants serving an adverse prognostic factor for OS in younger patients (P = 0.002), while TP53 (P = 0.024) and BCL2 (P = 0.002) variants significantly impacted OS in older patients. Prognostic analysis identified age ≥ 60 years (HR = 3.439, 95%CI: 1.318~9.874), presence of B symptoms (HR = 2.871, 95%CI = 1.133~7.307), and elevated lactate dehydrogenase (HR = 3.528, 95%CI = 1.231~10.66) as independent adverse prognostic factors. CONCLUSION Age, genetic variants, and clinical factors may significantly affect the prognosis of the DLBCL patients. Younger patients have better survival compared to older patients. Variants of the MYC, BCL2, and TP53 genes are closely associated with poor prognosis.
Humans ; Lymphoma, Large B-Cell, Diffuse/diagnosis* ; Middle Aged ; Female ; Male ; Retrospective Studies ; Aged ; Prognosis ; Adult ; Aged, 80 and over ; High-Throughput Nucleotide Sequencing ; Young Adult ; Adolescent ; Genetic Variation