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The study does not account for the estrous cycle stage during hormonal, histological, or transcriptomic analyses. Given the marked physiological fluctuations in ovarian hormones across proestrus and diestrus, the observed differences between control and CUMS groups may partially reflect cycle-stage variability rather than the direct effects of chronic stress. Stage-specific analyses would substantially strengthen the conclusions.
Although bulk RNA-seq identified stress-associated transcriptional changes, it does not reveal the cellular populations driving these alterations. Incorporating cell-type-specific analyses (e.g., computational deconvolution, immunostaining, or single-cell transcriptomics) would help determine whether astrocytes, microglia, oligodendrocytes/OPCs, excitatory neurons, inhibitory neurons, or dentate granule neurons are primarily affected by CUMS.
The study reports transcriptomic alterations without validating changes in specific neural cell populations. Confirmation using established cell identity markers would provide stronger mechanistic evidence linking chronic stress to cell-type-specific responses within the brain.
The study measures endocrine alterations primarily in serum but does not investigate corresponding molecular changes within the brain. Quantifying stress- and reproduction-related hormones (where technically appropriate) or their downstream signaling in relevant brain regions (e.g., hippocampus and hypothalamus) would help establish a mechanistic link between peripheral endocrine alterations and central nervous system dysfunction.
Although the study reports endocrine and transcriptomic alterations following CUMS, it does not evaluate whether these changes are accompanied by alterations in synaptic structure. Assessing synaptic density using established pre- and postsynaptic markers (e.g., Synaptophysin, PSD-95, Bassoon, Homer1) would provide important mechanistic insight into how chronic stress affects neuronal connectivity.
Including transcriptomic or epigenetic comparisons between proestrus and diestrus, together with comparisons to male animals, would help determine whether biological variability across the estrous cycle is comparable to or smaller than sex-dependent variability.
Correlating corticosterone, reproductive hormone levels, behavioral outcomes, and transcriptomic alterations at the individual-animal level would strengthen the biological interpretation of the CUMS model.
Future studies should investigate whether therapeutic interventions produce different outcomes when administered during proestrus versus diestrus, as hormonal status may influence treatment efficacy and translational relevance.
The author declares that they have no competing interests.
The author declares that they used generative AI to come up with new ideas for their review.
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