Journal of Ovarian Research最新文献

Background: Ovarian tissue cryopreservation followed by transplantation after cancer remission is a fertility preservation strategy available for certain patient groups, such as pre-pubertal and adolescent girls, as well as adult females requiring urgent gonadotoxic therapy. Quantitative assessment of follicular density in cryopreserved cortical tissue is critical for evaluating tissue quality and estimating its reproductive potential. Conventional analysis, based on manual follicle counts in serial histological sections, is time-consuming, labor-intensive, and prone to variability from uneven follicle distribution and inconsistent tissue orientation. To address these limitations, we developed a high-throughput, automated method combining micro-CT, machine learning, and morphological analysis to quantify oocyte density and other morphological features throughout entire ovarian cortical tissue samples.

Results: Three-dimensional segmentation analysis enabled quantification of oocyte density in the samples within the cortical region 1 mm below the surface epithelium. Oocytes in pediatric samples were located significantly closer to the surface compared to those in adult tissue, with median distances of 139.4 μm and 370.2 μm, respectively (P < 0.0001) and exhibited markedly higher local oocyte neighbor counts, with median values of 6 and 2 in pediatric and adult tissues, respectively (P < 0.0001), consistent with higher oocyte density and clustered spatial organization in younger individuals. Simulated histology using every 10th virtual sections -corresponding to 40 μm separated histology slices- closely approximated full-volume micro-CT estimates of oocyte density. Analysis based on only five virtual sections aligned with micro-CT data exclusively in pediatric samples with high oocyte density, whereas in adult samples it led to substantial inaccuracies in oocyte density estimation.

Conclusion: Micro-CT scanning combined with machine learning analysis represents a novel high-throughput and automated approach for estimating oocyte count in cryopreserved ovarian cortical samples. In addition, three-dimensional analysis offers valuable insights into oocyte localization and spatial distribution within the ovarian cortex, presenting a promising alternative to conventional histology for future clinical and research applications.

This study aimed to design, synthesize, and evaluate a peptide vaccine based on nanoliposomes loading multi-epitopes (PVNLME) of P53, WT1, and CA125. We selected the best epitope for each targeted protein and then, PVNLME was synthesized and characterized. Subsequently, BALB/c mice were randomly divided into two groups receiving 10 mg/ml or 100 mg/ml of PVNLME. Then, 100 µl of the vaccine were injected into each mouse every seven days for three consecutive weeks. In the fourth week, blood samples were taken, and both antibody titer and the serum level of different cytokines were measured. To further investigate, each mouse's serum sample was exposed to the OVCAR3 cell line. Subsequently, BAX to BCL2 gene expression ratio, cell viability, and apoptosis were evaluated. Finally, the efficacy of the peptide vaccine was analyzed in humanized PDX model mice. Based on Bioinformatics analysis, a merged peptide EENLRKKGEPHHELPPKKKKCKTCQRKFSRSDHLKTKKKDTTPSMTTSHGAESSS was selected as a multi-epitope peptide. We found that the size distribution of PVNLME was 72-198 nm with a mean size of 112 nm, zeta potential of + 30 mV, and 96% peptide loading. The level of cytokines and the titer of antibodies increased with increasing doses of PVNLME. Furthermore, we showed that this vaccine can increase the ratio expression of BAX /BCL2, which promotes apoptosis. Also, there was a decrease in cell viability and an increase in apoptosis rate in both doses and exposure times. Following the administration of this multi-epitope vaccine in PDX humanized mice, a notable reduction in the tumor volume was observed.

Ovarian aging is accompanied by a decline in the quantity and quality of follicles, leading to reduced fertility. Ovarian aging encompasses natural aging due to DNA damage, telomere attrition, and mitochondrial dysfunction, as well as a pathological functional failure caused by environmental toxins, known as a premature ovarian failure. Cell therapy is currently a focal point of research, with mesenchymal stem cells (MSCs) being particularly notable due to their wide availability, ease of expansion, strong self-renewal capabilities, multipotent differentiation, and paracrine functions. MSCs have shown great potential in the field of cell therapy, including delaying ovarian aging. MSCs can delay ovarian aging through various mechanisms: antioxidation, differentiation and regeneration, promotion of cell proliferation, inhibition of cell apoptosis, and anti-inflammatory responses. Currently, MSCs transplantation has achieved significant results in animal models, improving ovarian function and enhancing fertility. However, clinical applications still face numerous challenges, such as determining the optimal cell source, transplantation route, dosage, and long-term safety, which require further research. In this review, we will elaborate on the mechanisms of ovarian aging, the modes of action of MSCs, and the mechanisms by which MSCs delay ovarian aging, aiming to provide a theoretical basis for the clinical application of MSCs and to bring breakthroughs in the treatment of diseases such as premature ovarian failure.

Background: Early and accurate triage of adnexal masses remains challenging due to the heterogeneous presentation of ovarian cancer and the fragmented nature of existing diagnostic tools. While several validated algorithms exist-such as NICE NG12, HSE, IOTA Simple Rules, O-RADS v2022, RMI2, and ROMA-each evaluates different aspects of risk, and none provide an integrated, clinically actionable output. We developed MOCRA (Multivariate Ovarian Cancer Risk Assessment), a deterministic, rule-based clinical decision support system (CDSS) designed to harmonize these tools into a unified risk stratification.

Methods: This retrospective, single-center diagnostic accuracy study included 68 analyzable patients with adnexal masses. MOCRA encoded six validated diagnostic algorithms using object-oriented architecture and combined their outputs through transparent precedence rules to produce a four-level risk classification (low, intermediate, high, indeterminate). Diagnostic performance was evaluated against physician-confirmed outcomes (histopathology or ≥ 6-month follow-up). Functional reliability was assessed using predefined test cases, and usability was evaluated by 15 gynecologic oncologists using the Post-Study System Usability Questionnaire (PSSUQ).

Results: Among 68 patients (7 malignant, 61 benign), MOCRA achieved an accuracy of 97.1%, sensitivity 100.0%, specificity 96.7%, F1-score 87.5%, and AUC 0.984. No malignancies occurred in the MOCRA low-risk category. Compared with single algorithms, MOCRA reduced false negatives while maintaining high specificity by cross-validating symptom, biomarker, and ultrasound signals. Functional testing confirmed deterministic and stable performance (mean reliability 4.8/5). Usability ratings were uniformly positive (overall PSSUQ score 4.6/5), with clinicians highlighting the interpretability of the four-tier risk level and the clarity provided by side-by-side algorithm outputs.

Conclusions: MOCRA demonstrates strong diagnostic performance and high clinician usability in this pilot evaluation, suggesting that deterministic integration of multiple validated algorithms can improve consistency and reduce missed high-risk cases. However, the small, single-center dataset-particularly the limited number of malignant cases-warrants cautious interpretation. Larger multicenter and prospective studies with extended follow-up are needed to confirm generalizability and real-world clinical impact.

Background: Vitamins, as essential trace organic compounds for the human body, are crucial substances in the maintenance of normal reproductive function. Nevertheless, the effects of vitamins on the activation of primordial follicles and the underlying mechanisms remain unclear.

Methods: We used the in vitro culture model of newborn mouse ovaries to identify the vitamins that promote primordial follicle activation and study the mechanism of vitamin B6. The mechanism of VB6 was verified by in vivo injection model of newborn mice, oral feeding of adolescent mice, and in vitro culture model of human ovarian tissue.

Results: Thiamine monochloride (VB1), riboflavin (VB2), nicotinic acid (VB3), D-pantothenic acid (VB5), pyridoxine (VB6), folic acid (VB9), vitamin B12, L-ascorbic acid (VC), and tocopherol (VE) increased the number of growing follicles in the cultured newborn mouse ovaries. Next, we studied the molecular mechanism by using VB6. VB6 increased the protein levels of phosphorylated protein kinase B (p-Akt) and forkhead box O3a (p-FOXO3a), as well as the proportion of primordial follicle oocytes with FOXO3a nuclear export in the cultured mouse ovaries. The addition of PI3K inhibitor LY294002 blocked VB6-induced increase of growing follicles. Furthermore, intraperitoneal injection of VB6 in newborn mice and oral administration of VB6 to adolescent mice significantly increased the number of growing follicles and the protein levels of p-Akt. Importantly, VB6 also significantly increased the number of growing follicles and the protein levels of p-Akt in the cultured human ovarian tissues.

Conclusion: Our findings indicate that VB6 promotes primordial follicle activation through the PI3K/Akt signaling pathway.