Objectives: To evaluate pelvic floor muscle strength using surface electromyography and risk factors for pelvic floor muscle strength in the early postpartum period. Methods: This retrospective study included 21,302 participants who visited Fujian Maternity and Child Health Hospital from September 2019 to February 2022. All participants were assessed by medical professionals for general information and surface electromyography. Results: Univariate analysis indicated that age was inversely related to tonic and endurance contractions. In contrast, all the other variables, including education level, body mass index, neonatal weight, and number of fetuses, had a positive impact on rapid, tonic, and endurance contractions. Likewise, parity was also positively associated with rapid contractions. In addition, compared with vaginal delivery, cesarean section delivery had a protective effect on the amplitude of the three types of contractions. Stepwise regression analysis showed that both age and neonatal weight had a negative linear relationship with the amplitude of rapid, tonic and endurance contractions. In contrast, the amplitude of rapid, tonic and endurance contractions significantly increased as body mass index, parity (≤ 3), education level and gestational weight gain (endurance contractions only) increased. Participants with cesarean section delivery showed positive effects on rapid, tonic, and endurance contractions compared to participants with vaginal delivery. Conclusions: We found that age, neonatal weight, vaginal delivery, episiotomy, and forceps delivery were risk factors for pelvic floor muscle strength; in contrast, body mass index, parity (≤ 3) and gestational weight gain had a positive relationship with pelvic floor muscle strength.

Background: Sapiens spondin-2 (SPON2) is a protein found in the extracellular matrix that plays a role in a number of processes, including immune reactions and cell adhesion, and is closely linked to the emergence of a number of tumor types. However, we know very little about Sapiens spondin-2. Therefore, we performed a systematic pan-carcinogenic analysis to explore the relationship between Sapiens spondin-2 and cancers. Materials and methods: By comprehensive use of datasets from TCGA, GEO, GTEx, HPA, CPTAC, GEPIA2, TIMER2, cBioPortal, STRING, we adopted bioinformatics methods to dig up the potential carcinogenesis of SPON2, including dissecting the correlation between SPON2 and gene expression, prognosis, gene mutation, Immunohistochemistry staining, immune cell infiltration, and constructed the interaction network of a total of 54 SPON2-binding proteins as well as explored the enrichment analysis of SPON2-related partners. Results: The expression of Sapiens spondin-2 in most tumor tissues was higher than that of normal tissues. In addition, SPON2 showed the early diagnostic value in 33 kinds of tumors and was positively or negatively associated with the prognosis of different tumors. It also validates that SPON2 is the gene associated with the majority of immune-infiltrating cells in pan-cancer. High SPON2 expression is associated with tumor progression related pathways. Conclusion: We found and validated the potential use of SPON2 in cancer detection for the first time through pan-cancer analysis. The expression levels of SPON2 in various tumors were quite different from those in normal tissues. Furthermore, the performance of SPON2 in tumorigenesis and tumor immunity verified our hypothesis. At the same time, it has high specificity and sensitivity in cancer detection. Therefore, SPON2 can be employed as an auxiliary index for the initial diagnosis of tumors and a prognostic marker for various types of tumors.

Objectives: ABCA1 is involved in the development and progression of a wide range of malignant tumors, so to further clarify the role of ABCA1 expression therein, and to search for new breakthroughs in the treatment of tumors and cancers, we launched a thorough pan-cancer analysis of ABCA1.Methods: Based on the manipulation of TCGA (The Cancer Genome Atlas), GEO (Gene Expression Omnibus), Human Protein Atlas (HPA) datasets and various bioinformatics tools, The oncogenic role of ABCA1 in 33 tumor types was explored from six aspects: gene expression, prognosis, variation, immunohistochemistry, correlation of tumor-associated fibroblastic infiltration, and enriched analysis of related genes. The potential value of ABCA1 was also mined, such as: ABCA1 may be a potential marker of tumor metastasis, play a role in cancer resistance, and its expression may inhibit the spread of tumor cells.Results: Based on the analysis results, we found that ABCA1 is expressed elevated and mutated in tumor samples of 33 cancer types compared with matched normal tissues, and these mutations may be related to the mechanism of cancer, metastatic ability, and prognosis, etc. Meanwhile, we also investigated the correlation between ABCA1 expression and tumor-associated fibroblast infiltration, and described its association with corresponding miRNAs, which can provide scientific basis for clinical diagnosis.Conclusions: Our study thoroughly illustrates the impact of ABCA1’s systemic presence across various forms of cancer. Given its specificity to tumors, ABCA1 holds promise as a biomarker for cancer diagnosis, monitoring for recurrence, and predicting outcomes. Consequently, our research could significantly bolster the case for utilizing ABCA1 in the therapeutic approach to cancer.

The RNA-binding protein ZFP36 is involved in tumorigenesis. To systematically elucidate its pan-cancer role, we conducted an integrated analysis of ZFP36 across malignancies, combining bioinformatic exploration with experimental validation. Utilizing datasets from TCGA, GEO, GTEx, HPA, CPTAC, GEPIA2, TIMER2, cBioPortal, and STRING, we employed bioinformatics methods to investigate the potential carcinogenic properties of ZFP36 . This included examining correlations between ZFP36 and gene expression, prognosis, gene mutation, immunohistochemistry staining, immune cell infiltration, and constructing an interaction network of 50 ZFP36 -binding proteins. Additionally, we performed enrichment analysis of ZFP36 -related partners. Furthermore, to validate key bioinformatic predictions, quantitative real-time PCR (qRT-PCR) was performed on paired cancer/normal cell lines (LIHC, LUAD, BRCA). ZFP36 expression was found to be dysregulated in a cancer type-dependent manner, with significant upregulation observed in most tumor types analyzed, including BLCA, BRCA, LIHC, and LUAD. Furthermore, ZFP36 demonstrated early diagnostic value across 33 types of tumors and showed varying associations with prognosis depending on the tumor type. ZFP36 was also significantly associated with most immune-infiltrating cells in pan-cancer analyses. High ZFP36 expression was linked to pathways related to tumor progression. Critically, these bioinformatic predictions were experimentally validated, as qRT-PCR confirmed the significant upregulation of ZFP36 and its functional network genes ( SOCS3 , JUN , SLC7A11 , CSRNP1 ) in LIHC, LUAD, and BRCA cell lines. This study provides a comprehensive pan-cancer analysis of ZFP36 , integrating bioinformatics with experimental validation. We demonstrated its dysregulation across cancers in a type-dependent manner, correlations with immune infiltration and tumor-associated pathways. Critically, qRT-PCR experiments confirmed the significant co-upregulation of ZFP36 and its functional network genes ( SOCS3 , JUN , SLC7A11 , CSRNP1 ) in LIHC, LUAD, and BRCA cell lines. These findings establish ZFP36 as a promising diagnostic and prognostic biomarker and suggest its role as a pivotal post-transcriptional regulator in tumorigenesis, supporting its potential for clinical application in cancer assessment.

Currently, the incidence of diabetes mellitus is increasing rapidly, particularly in China, and its pathogenesis is still unclear. The goal of this study was to find meaningful biomarkers of metastasis in patients with diabetes and cancer using bioinformatic analysis in order to predict gene expression and prognostic importance for survival. We used the Differentially Expressed Gene, Database for Annotation Visualization and Integrated Discovery, and Gene Set Enrichment Analyses databases, as well as several bioinformatics tools, to explore the key genes in diabetes. Based on the above database, we ended up with 10 hub genes (FOS, ATF3, JUN, EGR1, FOSB, JUNB, BTG2, EGR2, ZFP36, and NR4A2). A discussion of the 10 critical genes, with extensive literature mentioned to validate the association between the 10 key genes and patients with diabetes and cancer, to demonstrate the importance of gene expression and survival prognosis. This study identifies several biomarkers associated with diabetes and cancer development and metastasis that may provide novel therapeutic targets for diabetes combined with cancer patients.

The precise detection and profiling of biotoxins are of paramount importance in analytical and forensic toxicology. Investigating these toxicants within highly chaotic background matrices—ranging from postmortem biological fluids to suspected poisoning vehicles such as complex dietary and environmental samples—requires robust recognition molecules capable of overcoming severe interference. This comprehensive review summarizes recent analytical developments in biotoxin detection, categorizing molecular recognition platforms into three primary types: immunological recognition (antibodies and recombinant derivatives), aptamer-based recognition, and entirely synthetic recognition (molecularly imprinted polymer, MIP). To meet the rigorous ultra-trace demands of medicolegal analysis, we further discuss the strategic integration of these recognition elements with powerful catalytic amplification cascades, highlighting the transition from natural biological enzymes to highly durable nanozymes and DNAzymes. By detailing recent structural optimizations and preparation strategies, this review critically evaluates the respective advantages, matrix tolerances, and limitations of each recognition mode when applied to diverse and challenging analytical samples. Finally, we provide a forward-looking perspective on the translational potential of these specific binding agents, emphasizing how computational rational design and portable integration will overcome practical bottlenecks in modern toxicological investigations.