Search

BackgroundFew studies have compared the influencing factors of postpartum depression between primiparous and multiparous women. Therefore, this study is aimed to investigate the prevalence and influencing factors of postpartum depression in primiparous and multiparous women, and provide reference suggestions for clinical nursing.MethodsA total of 429 postpartum women who gave birth at a Maternal and Child Health Hospital in Shandong Province, China, from April to June 2024, were recruited by convenience sampling. A Sociodemographic Questionnaire, Edinburgh Postpartum Depression Scale, Pittsburgh Sleep Quality Index, and Perceived Social Support Scale were used for investigation. SPSS 26.0 was used to analyze the data, and multivariate regression was employed to analyze the influencing factors of postpartum depression between primiparous and multiparous women.ResultsThe total prevalence of postpartum depression among 429 postpartum women (191 primiparas and 238 multiparas) was 22.14%. The prevalence of postpartum depression among primiparous and multiparous women were 21.99% and 22.27%, respectively, with no statistically significant difference [OR=1.016, 95% CI (0.642, 1.608)]. Sleep quality is a common protective factor for postpartum depression in both primiparous and multiparous women, while perceived social support is another protective factor for multiparous women. The risk factors are different in both two group, there is no risk factor found in primiparous women, the newborns health and women’s expectation on newborns gender are risk factors for postpartum depression in multiparous women.ConclusionsBoth primiparous and multiparous women have a high risk of postpartum depression. In order to promote the mental health of postpartum women, precise nursing measures should be adopted for different parity of postpartum women in clinical practice.

ObjectiveThe aim of this research was to gain a thorough understanding of the processes involved in cell communication and discover potential indicators for treating multiple myeloma (MM) through the use of single-cell RNA sequencing (scRNA-seq). And explored the expression of multiple myeloma-related subgroups on metal ion-related pathways to explore the relationship between MM and metal ions.MethodsWe performed a fair examination using single-cell RNA sequencing on 32 bone marrow specimens collected from 22 individuals at different points of MM advancement and 9 individuals without any health issues. To analyze the scRNA-seq data, we employed advanced computational algorithms, including Slingshot, Monocle2, and other methodologies. Specifically, Slingshot and Monocle2 enabled us to simulate the biological functionalities of different cell populations and map trajectories of cell developmental pathways. Additionally, we utilized the UMAP algorithm, a powerful dimension reduction technique, to cluster cells and identify genes that were differentially expressed across clusters.ResultsOur study revealed distinct gene expression patterns and molecular pathways within each patient, which exhibited associations with disease progression. The analysis provided insights into the tumor microenvironment (TME), intra- and inter-patient heterogeneity, and cell-cell interactions mediated by ligand-receptor signaling. And found that multiple myeloma-related subgroups were expressed higher levels in MMP and TIMP pathways, there were some associations.ConclusionOur study presents a fresh perspective for future research endeavors and clinical interventions in the field of MM. The identified gene expression patterns and molecular pathways hold immense potential as therapeutic targets for the treatment of multiple myeloma. The utilization of scRNA-seq technology has significantly contributed to a more precise understanding of the complex cellular processes and interactions within MM. Through these advancements, we are now better equipped to unravel the underlying mechanisms driving the development and progression of this complex disease.

Abstract To investigate the molecular mechanism of Yiwei Decoction (YWD) in preventing Premature ovarian insufficiency (POI)-related osteoporosis from the hypothalamic perspective , and to screen for the key active and acting molecules in YWD. Cyclophosphamide was used to create the POI rat model. Groups A, B, and C were established. The Model + YWD group was group A, the model control group was group B, and the normal control group was group C. ELISA was used to determine serum GnRH and FSH levels after gavage. The transcription levels of mRNAs in each group's hypothalamus tissues were examined using RNA-seq sequencing technology. The GSEA method was used to enrich pathways based on the gene expression levels of each group. The TCM–active ingredient–target–disease network map was created using differentially expressed mRNAs (DEmRNAs) and network pharmacology. The molecular docking method was employed to investigate the affinity of the active ingredient with key targets. GnRH and FSH levels in POI rats' serum were reduced by YWD. Between groups A and B, there were 638 DEmRNAs (P

BackgroundCervical carcinoma (CC) represents a prevalent gynecological neoplasm, with a discernible rise in prevalence among younger cohorts observed in recent years. Nonetheless, the intrinsic cellular heterogeneity of CC remains inadequately investigated.MethodsWe utilized single-cell RNA sequencing (scRNA-seq) transcriptomic analysis to scrutinize the tumor epithelial cells derived from four specimens of cervical carcinoma (CC) patients. This method enabled the identification of pivotal subpopulations of tumor epithelial cells and elucidation of their contributions to CC progression. Subsequently, we assessed the influence of associated molecules in bulk RNA sequencing (Bulk RNA-seq) cohorts and performed cellular experiments for validation purposes.ResultsThrough our analysis, we have discerned C3 PLP2+ Tumor Epithelial Progenitor Cells as a noteworthy subpopulation in cervical carcinoma (CC), exerting a pivotal influence on the differentiation and progression of CC. We have established an independent prognostic indicator—the PLP2+ Tumor EPCs score. By stratifying patients into high and low score groups based on the median score, we have observed that the high-score group exhibits diminished survival rates compared to the low-score group. The correlations observed between these groups and immune infiltration, enriched pathways, single-nucleotide polymorphisms (SNPs), drug sensitivity, among other factors, further underscore their impact on CC prognosis. Cellular experiments have validated the significant impact of ATF6 on the proliferation and migration of CC cell lines.ConclusionThis study enriches our comprehension of the determinants shaping the progression of CC, elevates cognizance of the tumor microenvironment in CC, and offers valuable insights for prospective CC therapies. These discoveries contribute to the refinement of CC diagnostics and the formulation of optimal therapeutic approaches.

Premature ovarian insufficiency（POI）is a female reproductive aging illness. Yiwei decoction（YWD） is a traditional treatment for Yangming nourishment. YWD can treat premature ovarian insufficiency, but the exact molecular mechanism is unknown. As a result, the differential expression of Long noncoding RNAs (LncRNAs) and Circular RNAs(CircRNAs) in the ovary of POI rats after YWD treatment was investigated in this paper, and the CeRNA regulatory network was built.The model was created using cyclophosphamide. The model group + YWD was in Group A, the model control group was in Group B, and the regular control group was in Group C. In this study, 177 differential expression Long noncoding RNAs(DELncRNAs) and 190 differential expression Circular RNAs (DECircRNAs) were discovered between A and B (P＜0.05,|LogFC|＞1). Following the analysis, 27 DELncRNAs and 96 DECircRNAs (P-adjusted＜0.05,|LogFC|＞1) were discovered. At the same time, we built the CeRNA network using differentially expressed mRNAs and microRNAs (miRNAs) expression between groups A and B. The DELncRNAs were used to construct a lncRNA-miRNA-mRNA ceRNA network with 27 LncRNAs, 4 miRNAs, and 19 mRNAs. The DECircRNAs were utilized to establish a CircRNA-miRNA-mRNA ceRNA network that was made up of 15 CircRNAs, 4 miRNAs, and 20 mRNA. The highly correlated regulatory networks were the LncMSTRG.22691.3/miR-3102/ANGPT4 and Circ10_34698898_34699378/miR-33-5p/TTC22. Circ20_12035276_12036793、Circ20_30693935_30696337、Circ4_157723097_157723378 and Circ4_157923266_157923904 occurred concurrently in AvsB, BvsC, and AvsC. MiRDB predicted eight target miRNAs for these CircRNAs. The miRanda(score = 140，energy = −1) binding energy calculation revealed that seven miRNAs were well combined with three CircRNA base complementary pairs. This implies that 3 DECircRNAs could serve as spongy bodies for these miRNAs. Network pharmacological analysis showed that ten active components in YWD may regulate the expression of LncRNAs and CircRNAs, such as Stigmasterol, Uridine, Ophiopogonanone A, Gamma-Aminobutyric Acid, and others.In conclusion, this study combined transcriptomics and network pharmacological analysis to identify differentially expressed lncRNAs as well as CircRNAs in ovaries of YWD-treated POI rats, thereby constructing ceRNA networks implicated in POI. This would contribute to clarifying the pathways by which Chinese herbal compounds regulate gene expression in POI.

Infertility and menstrual abnormalities in endometriosis patients are frequently caused by aberrant follicular growth or a reduced ovarian reserve. Endometriosis typically does not directly harm the oocyte, but rather inhibits the function of granulosa cells, resulting in a decrease in oocyte quality. Granulosa cells, as oocyte nanny cells, can regulate meiosis, provide the most basic resources required for oocyte development, and influence ovulation. Endometriosis affects oocyte development and quality by causing granulosa cells apoptosis, inflammation, oxidative stress, steroid synthesis obstacle, and aberrant mitochondrial energy metabolism. These aberrant states frequently interact with one another, however there is currently relatively little research in this field to understand the mechanism of linkage between abnormal states.

Extracellular vesicles (EVs) have become a research hotspot in recent years because they act as messengers between cells in the physiological and pathological processes of the human body. It can be produced by the follicle, prostate, embryo, uterus, and oviduct in the reproductive field and exists in the extracellular environment as follicular fluid, semen, uterine cavity fluid, and oviduct fluid. Because extracellular vesicles are more stable at transmitting information, it allows all cells involved in the physiological processes of embryo formation, development, and implantation to communicate with one another. Extracellular vesicles carried miRNAs and proteins as mail, and when the messenger delivers the mail to the recipient cell, the recipient cell undergoes a series of changes. Current research begins with intercepting and decoding the information carried by extracellular vesicles. This information may help us gain a better understanding of the secrets of reproduction, as well as assist reproductive technology as an emerging marker and treatment.

In order to track complex-path tasks in three dimensional space without joint-drifts, a neural-dynamic based synchronous-optimization (NDSO) scheme of dual redundant robot manipulators is proposed and developed. To do so, an acceleration-level repetitive motion planning optimization criterion is derived by the neural-dynamic method twice. Position and velocity feedbacks are taken into account to decrease the errors. Considering the joint-angle, joint-velocity, and joint-acceleration limits, the redundancy resolution problem of the left and right arms are formulated as two quadratic programming problems subject to equality constraints and three bound constraints. The two quadratic programming schemes of the left and right arms are then integrated into a standard quadratic programming problem constrained by an equality constraint and a bound constraint. As a real-time solver, a linear variational inequalities-based primal-dual neural network (LVI-PDNN) is used to solve the quadratic programming problem. Finally, the simulation section contains experiments of the execution of three complex tasks including a couple task, the comparison with pseudo-inverse method and robustness verification. Simulation results verify the efficacy and accuracy of the proposed NDSO scheme.