ObjectiveThis study aims to explore the potential of different orders of magnitude single-nucleotide polymorphism (SNP) locus combinations for predicting distant kinship relationships. A high-density SNP locus set was constructed, and a comprehensive assessment of its inference capability was conducted. MethodsFirstly, we selected three commercial chip panels, CGA (Chinese genotyping array, Illumina), GSA (Global screening array, Illumina), Affy (23MF_V2 high-density SNP array, Affymetrix) and merged them after quality control, forming a high-density SNP locus panel(1 180 k). Secondly, we selected 161 samples and collected their peripheral blood samples by using whole-genome sequencing technology. Within this sample population, the levels of kinship relationships fully covered the range from level 1 to level 9, and the number of kinship pairs at each level was consistently maintained at over 50 pairs. From 161 samples data of whole-genome sequencing, the 1 180 k locus set was extracted, which is referred to as the high-density SNP locus set in the following text. The kinship inference was conducted using the identity-by-descent (IBD) algorithm with the selected optimal parameters. To comprehensively evaluate the performance of the high-density SNP locus set in kinship inference, we compared it with the three commercial chip panels, the intersection of these three chip loci, and the control sets constructed by randomly reducing the number of the high-density SNP locus set. Based on the changes in the IBD lengths, as well as the dynamic trends in prediction accuracy, we conducted a scientific assessment of the kinship inference capability of the high-density SNP locus set. ResultsAfter screening, a set of 1 184 334 autosomal SNPs was obtained. During the process of screening the optimal IBD length threshold, the result revealed that 0 cM, 1 cM, and 2 cM all demonstrated good applicability. However, to avoid the issue of a large amount of redundant information caused by setting a too low IBD length threshold, this study ultimately selected 2 cM as the optimal threshold. Compared with the average results of three chip panels, the high-density SNP locus set increased the total IBD length and the average IBD length across levels 1-9; the accuracy of the confidence interval for level 8 was 70.97%, which represented a 3.50% improvement; the average confidence interval accuracy for levels 1-8 was 91.39%, representing a 1.00% increase; and the false negative rates at levels 8 and 9 were reduced by 2.42% and 6.76%, respectively. The system efficacy of the high-density SNP locus set for kinship inference of first to eighth degree relationships reached 98.91%. Through random reduction of the high-density SNP locus set results, it is found that increasing the number of SNPs with the panel, the detection efficiency of IBD length showed a significant upward trend. At the same time, the overall trend in the accuracy of kinship relationship prediction as well as the confidence interval accuracy also indicated that both metrics steadily increased with the addition of more loci. ConclusionThe results show that the high-density SNPs panel significantly enhances the efficacy of distant kinship inference, accurately covering kinship degrees, with the average confidence interval accuracy for first to eighth degree relationships stably above 90%. The study finds that increasing the number of SNPs panel can improve the ability to predict distant kinship.

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*

Objective： The aim of this study is to explore the predictive value of biparametric magnetic resonance imaging(bpMRI)for pelvic lymph node metastasis in prostate cancer patients with PSA≤20 μg/L and establish a nomogram. Methods： The imaging data and clinical data of 363 patients undergoing radical prostatectomy and pelvic lymph node dissection in the First Affiliated Hospital of Nanjing Medical University from July 2018 to December 2023 were retrospectively analyzed. Univariate analysis and multivariate logistic regression were used to screen independent risk factors for pelvic lymph node metastasis in prostate cancer, and a nomogram of the clinical prediction model was established. Calibration curves were drawn to evaluate the accuracy of the model. Results： Multivariate logistic regression analysis showed extrocapusular extension (OR=8.08,95%CI=2.62－24.97, P<0.01), enlargement of pelvic lymph nodes (OR=4.45,95%CI=1.16－17.11,P=0.030), and biopsy ISUP grade(OR=1.97,95%CI=1.12－3.46, P=0.018)were independent risk factors for pelvic lymph node metastasis. The C-index of the prediction model was 0.834, which indicated that the model had a good prediction ability. The actual value of the model calibration curve and the prediction probability of the model fitted well, indicating that the model had a good accuracy. Further analysis of DCA curve showed that the model had good clinical application value when the risk threshold ranged from 0.05 to 0.70.Conclusion： For prostate cancer patients with PSA≤20 μg/L, bpMRI has a good predictive value for the pelvic lymph node metastasis of prostate cancer with extrocapusular extension, enlargement of pelvic lymph nodes and ISUP grade≥4.
Humans ; Male ; Prostatic Neoplasms/diagnostic imaging* ; Lymphatic Metastasis ; Retrospective Studies ; Nomograms ; Prostate-Specific Antigen/blood* ; Lymph Nodes/pathology* ; Pelvis ; Predictive Value of Tests ; Prostatectomy ; Lymph Node Excision ; Risk Factors ; Magnetic Resonance Imaging ; Logistic Models ; Middle Aged ; Aged

BACKGROUND: Atrial fibrillation (AF) is a common cardiac arrhythmia in the elderly. This study aimed to evaluate urban-rural disparities in its prevalence and management in elderly Chinese. METHODS: Consecutive participants aged ≥ 65 years attending outpatient clinics were enrolled for AF screening using handheld single-lead electrocardiogram (ECG) from April 2017 to December 2022. Each ECG rhythm strip was reviewed from the research team. AF or uninterpretable single-lead ECGs were referred for 12-lead ECG. Primary study outcome comparison was between rural and urban areas for the prevalence of AF. The Student's t-test was used to compare mean values of clinical characteristics between rural and urban participants, while the Pearson's chi-square test was used to compare between-group proportions. Multivariate stepwise logistic regression analysis was performed to estimate the association between AF and various patient characteristics. RESULTS: The 29,166 study participants included 13,253 men (45.4%) and had a mean age of 72.2 years. The 7073 rural participants differed significantly (P ≤ 0.02) from the 22,093 urban participants in several major characteristics, such as older age, greater body mass index, and so on. The overall prevalence of AF was 4.6% (n = 1347). AF was more prevalent in 7073 rural participants than 22,093 urban participants (5.6% vs. 4.3%, P < 0.01), before and after adjustment for age, body mass index, blood pressure, pulse rate, cigarette smoking, alcohol consumption and prior medical history. Multivariate logistic regression analysis identified overweight/obesity (OR = 1.35, 95% CI: 1.17-1.54) in urban areas and cigarette smoking (OR = 1.62, 95% CI: 1.20-2.17) and alcohol consumption (OR = 1.42, 95% CI: 1.04-1.93) in rural areas as specific risk factors for prevalent AF. In patients with known AF in urban areas (n = 781) and rural areas (n = 338), 60.6% and 45.9%, respectively, received AF treatment (P < 0.01), and only 22.4% and 17.2%, respectively, received anticoagulation therapy (P = 0.05). CONCLUSIONS In China, there are urban-rural disparities in AF in the elderly, with a higher prevalence and worse management in rural areas than urban areas. Our study findings provide insight for health policymakers to consider urban-rural disparity in the prevention and treatment of AF.

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

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.

Objective To explore the clinical efficacy of Du's bone-setting manipulation reduction combined with proximal femoral nail antirotation(PFNA)in the treatment of femoral intertrochanteric fracture.Methods A total of 79 femoral intertrochanteric fracture patients who underwent PFNA surgery in Sichuan Second Hospital of Traditional Chinese Medicine from January 2018 to December 2023 were selected.40 patients who underwent Du's bone-setting manipulation reduction combined with PFNA were included in manipulation group,and 39 patients who used a traction bed followed by PFNA were included in traction group.The operation time,intraoperative blood loss,recovery of neck-shaft angle and anteversion angle of femur,and fracture healing time of two groups of patients were compared.Results The operation time and fracture healing time of patients in manipulation group were significantly shorter than those in traction group,intraoperative blood loss was significantly less than that in traction group,and the Harris score of hip joint and the excellent and good rate of reduction were significantly higher than those in traction group(P＜0.05).There was no statistically significant difference in postoperative hospital stay,the degree of recovery of neck-shaft angle and anteversion angle of femur between two groups of patients(P＞0.05).Conclusion Du's bone-setting manipulation reduction combined with PFNA in the treatment of femoral intertrochanteric fracture has the advantages of short operation time,less intraoperative blood loss,short fracture healing time and good functional recovery of the affected limb.

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=0.001), 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.