1. This study aimed to evaluate the effects of dietary ascorbic acid (vitamin C) supplementation on the reproductive performance, follicular development, antioxidant capacity, serum steroid hormone concentration and expression of genes involved in steroid hormone synthesis in Yangzhou geese.2. A total of 540, 221-day-old geese (450 females and 90 males) were randomly divided into five groups that received different diets. Treatments included vitamin C levels of 0, 100, 200, 300 or 400 mg/kg, respectively.3. Dietary vitamin C supplementation led to a highly significant linear increase in laying rate (p < 0.01), with significant improvements detected at 300 mg/kg and 400 mg/kg (p < 0.01). Thus, within the supplement range of 0-400 mg/kg, graded additions of vitamin C linearly improved reproductive performance with economic benefits. In consideration of commercial breeding practices together with the observed physiological and productive indices, dietary vitamin C supplementation at 300 mg/kg was effective.4. Feeding 300 mg/kg prompted oestradiol and progesterone concentrations in both serum and hierarchical follicular yolks (p < 0.05) and the number of primordial follicles increased significantly (p < 0.01). This level of vitamin C in the feed resulted in elevated activity levels of total antioxidant capacity, superoxide dismutase and catalase in both serum and follicles, along with a reduction in malondialdehyde levels.5. Dietary supplementation with 300 mg/kg vitamin C increased the expressions of StAR, HSD3B1 and CYP11A1 in granulosa layer. Similar expression patterns of CYP17A1, CYP19A1, HSD3B1 and HSD17B1 were detected in the theca layer.

Iron homeostasis in premenopausal women is governed by a dual regulatory architecture that has been incompletely characterized in the clinical literature. The hepcidin-ferroportin axis, established as the master regulator of systemic iron flux, operates within a second-order hormonal framework in females of reproductive age: 17β-estradiol (E2) and progesterone (P4) directly modulate hepatic hepcidin transcription, superimposing a predictable, cycle-dependent oscillation on baseline iron availability. This review summarizes the molecular mechanisms underlying this cyclical regulation. E2 suppresses hepcidin expression through estrogen receptor-dependent regulation of the HAMP gene, mapped in hepatocyte models to an estrogen-responsive element (ERE) half-site. Preclinical evidence also implicates a competing pathway, mediated by the G protein-coupled estrogen receptor 1 (GPR30, also designated GPER1) and bone morphogenetic protein 6 (BMP6), with opposing upregulatory effects on hepcidin. Progesterone has an opposing effect, raising hepcidin in women when administered exogenously, an effect attributed in preclinical models to the progesterone receptor membrane component-1 (PGRMC1). When mapped onto the menstrual cycle, these hormonal actions predict a follicular phase of enhanced iron acquisition and a luteal phase of iron restriction. We distinguish that prediction from the evidence: the predicted late luteal hepcidin maximum is not evident in cohorts sampled serially across the cycle, and circulating interleukin-6 does not rise in the luteal phase, so the cycle-level consequence of the hormonal mechanism remains the central open question. The clinical implications extend to diagnostics and therapeutics: standard iron status biomarkers fluctuate predictably with cycle phase, confounding single-time-point assessments; and the clinical significance of these fluctuations differs mechanistically depending on whether the underlying deficit reflects absolute storage depletion, impaired functional delivery, or erythropoietic cellular restriction. This review proposes a mechanism-oriented biomarker subtyping framework to address this diagnostic gap and discusses cycle-synchronized iron supplementation as a biologically plausible hypothesis that warrants rigorous evaluation in future clinical trials.

Although depression exhibits prominent sex differences, mechanisms linking estrogen fluctuations to this vulnerability remain unclear. Here, we reveal that disrupted estrogen homeostasis induces depressive- and anxiety-like behaviors via convergent downregulation of estrogen receptor alpha (ERα) and subsequent neuroinflammation in the female ventral hippocampus (vHPC). In humans (n=6,481), serum estradiol (E2) showed a U-shaped association with depression, increasing risk at both extremes. In mice, while chronic restraint stress (CRS) induced depressive-like behaviors across sexes, it selectively triggered E2 deficiency, anxiety-like behaviors, and decreased vHPC ERα (but not ERβ) in females. Therefore, focusing on females, both supraphysiological E2 (sE2)-induced elevation and CRS-induced E2 deficiency produced depressive- and anxiety-like behaviors converging on vHPC ERα downregulation. Cross-species transcriptomics and multi-omics revealed global concordance between female major depressive disorder (MDD) and both mouse models, identifying ERα as a top upstream regulator associated with neuroinflammation, lipid dysregulation, and synaptic dysfunction. Pharmacological inhibition of ERα exacerbated depressive- and anxiety-like behaviors and neuroinflammation under subthreshold CRS, whereas vHPC ERα overexpression rescued CRS-induced behavioral deficits and neuroinflammatory responses. Integrating human MDD GWAS and PsyGeNET datasets supported this pathway's genetic and clinical relevance. Collectively, we identify vHPC ERα as a unifying therapeutic target for female depression.

Estrogens regulate key processes in parturition, yet the specific effects of estradiol (E2) on maternal reproductive tissues in sheep remain unclear. This study investigated the impact of exogenous E2, mimicking physiological prepartum levels, on gene expression in the myometrium, endometrium, cervix, and placental membranes, as well as sex steroid receptor protein expression in uterine compartments of late pregnant ewes. Pregnant ewes (139-142 d gestation) received Silastic implants containing either E2 (200 µg/ewe, n = 6) or control (n = 6), and tissues were collected 26 h post-treatment. Bulk RNA sequencing assessed differential gene expression, while fluorescence immunohistochemistry evaluated nuclear receptor localization and intensity. Transcriptomic analysis (FDR < 0.05) revealed a tissue-specific response, with the cervix showing the most robust transcriptional changes. Gene ontology enrichment indicated downregulation of extracellular matrix organization pathways associated with cervical dilation at parturition. Targeted analyses revealed regulation of genes related to prostaglandin synthesis, steroid metabolism, immune signaling, and ECM remodeling. The endometrium displayed a moderate response, whereas the myometrium and placental tissues exhibited minimal changes. At the protein level, myometrial progesterone receptor (PR) expression was significantly reduced (p < 0.05), while ERα and ERβ were unaffected. These findings demonstrate that the prepartum rise in E2 is associated with tissue-specific gene expression changes in the ewe uterine tract. In the cervix, the most affected tissue, transcriptomic changes are consistent with cervical ripening. Reduced myometrial PR expression suggests decreased progesterone responsiveness.

Objective and reproducible assessment of endometrial receptivity is essential for optimizing in vitro fertilization (IVF) success, yet traditional histological dating suffers from observer variability. This study investigated whether deep learning of hematoxylin and eosin histology images could support cumulative live birth prediction in IVF. An end-to-end ResNet-18 was compared with a UNI2-h-based pipeline, using UNI2-h as a frozen feature extractor. Ten-fold cross-validation ensembles were developed from natural-cycle endometrial biopsies and evaluated in an internal held-out cohort with live birth outcomes. Additional phase-based evaluation was performed, which tested the performance in distinguishing LH + 7 versus non-LH + 7 phases. A luminal epithelium (LE)-focused design was also assessed to examine whether concentrating on maternal-embryo interface could improve fertility-oriented learning. The whole-slide ResNet-18 model performed well in internal outcome-based testing but near random in external phase-based testing. In contrast, the UNI2-h model with mean pooling and a multilayer perceptron classifier showed less divergent performance, with ensembled AUROCs of 0.74 ± 0.03 in internal outcome-based evaluation, and 0.90 ± 0.05 in external phase-based testing. Despite a smaller training set, LE-focused models retained comparable performance. In internal outcome-based testing, LE-focused ResNet-18 and UNI2-h models achieved AUROCs of 0.71 ± 0.03 and 0.74 ± 0.09 respectively. External phase-based testing yielded AUROCs of 0.80 ± 0.16 for ResNet-18, and 0.84 ± 0.06 for UNI2-h. Grad-CAM review of LE-focused ResNet-18 models showed attention commonly on LE-alone or mixed with adjacent stroma. In multimodal analyses, integrated models incorporating histology significantly outperformed the clinical metadata-only model. Integrated model's feature weighting showed dominant histology outputs, smaller contributions from estradiol and maternal age, and negligible contributions from progesterone, endometrial thickness, and BMI. These findings support histology-based AI for fertility-oriented endometrial assessment and highlight biologically informed design and repurposed foundation models as promising bases for clinically meaningful prediction.