Gonadotropin-releasing hormone (GnRH) neurons produce the central output controlling fertility and are regulated by steroid feedback. A switch from estradiol negative to positive feedback initiates the GnRH surge, ultimately triggering ovulation. This occurs on a daily basis in ovariectomized, estradiol-treated (OVX+E) mice; GnRH neurons are suppressed in the morning and activated in the afternoon. To test the hypotheses that estradiol and time of day signals alter GnRH neuron responsiveness to stimuli, GFP-identified GnRH neurons in brain slices from OVX+E or OVX female mice were recorded during the morning or afternoon. No differences were observed in baseline membrane potential. Current-clamp revealed GnRH neurons fired more action potentials in response to current injection during positive feedback relative to all other groups, which were not different from each other despite reports of differing ionic conductances. Kisspeptin increased GnRH neuron response in cells from OVX and OVX+E mice in the morning but not afternoon. Paradoxically, excitability in kisspeptin knock-out mice was similar to the maximum observed in control mice but was unchanged by time of day or estradiol. A mathematical model applying a Markov Chain Monte Carlo method to estimate probability distributions for estradiol- and time of day-dependent parameters was used to predict intrinsic properties underlying excitability changes. A single identifiable distribution of solutions accounted for similar GnRH neuron excitability in all groups other than positive feedback despite different underlying conductance properties; this was attributable to interdependence of voltage-gated potassium channel properties. In contrast, redundant solutions may explain positive feedback, perhaps indicative of the importance of this state for species survival. Infertility affects 15%-20% of couples; failure to ovulate is a common cause. Understanding how the brain controls ovulation is critical for new developments in both infertility treatment and contraception. Gonadotropin-releasing hormone (GnRH) neurons are the final common pathway for central neural control of ovulation. We studied how estradiol feedback regulates GnRH excitability, a key determinant of neural firing rate using laboratory and computational approaches. GnRH excitability is upregulated during positive feedback, perhaps driving increased neural firing rate at this time. Kisspeptin increased GnRH excitability and was essential for estradiol regulation of excitability. Modeling predicts that multiple combinations of changes to GnRH intrinsic conductances can produce the firing response in positive feedback, suggesting the brain has many ways to induce ovulation.

Despite recent advances in targeted therapies, the molecular mechanisms driving breast cancer initiation, progression, and metastasis are minimally understood. Growing evidence indicate that transfer RNA (tRNA)‐derived small RNAs (tsRNA) contribute to biological control and aberrations associated with cancer development and progression. The runt‐related transcription factor 1 (RUNX1) transcription factor is a tumor suppressor in the mammary epithelium whereas RUNX1 downregulation is functionally associated with breast cancer initiation and progression. We identified four tsRNA (ts‐19, ts‐29, ts‐46, and ts‐112) that are selectively responsive to expression of the RUNX1 tumor suppressor. Our finding that ts‐112 and RUNX1 anticorrelate in normal‐like mammary epithelial and breast cancer lines is consistent with tumor‐related activity of ts‐112 and tumor suppressor activity of RUNX1. Inhibition of ts‐112 in MCF10CA1a aggressive breast cancer cells significantly reduced proliferation. Ectopic expression of a ts‐112 mimic in normal‐like mammary epithelial MCF10A cells significantly increased proliferation. These findings support an oncogenic potential for ts‐112. Moreover, RUNX1 may repress ts‐112 to prevent overactive proliferation in breast epithelial cells to augment its established roles in maintaining the mammary epithelium.

Abstract. TP53-regulated inhibitor of apoptosis 1 (TRIAP1) is a novel apoptosis inhibitor that binds HSP70 in the cytoplasm and blocks the formation of the apoptosome and caspase-9 activation. TRIAP1 has been shown to be upregulated in many types of cancers; however, its role remains elusive. We determined the TRIAP1 mRNA levels in a panel of human tissues and found its expression to be ubiquitous. Normal breast, as well as non-tumorigenic breast cells, exhibited lower TRIAP1 mRNA levels than breast cancer cells or their drug-resistant derivatives. TRIAP1 is a small, evolutionarily conserved protein that is 76 amino acids long. We found that yeast cells, in which the TRIAP1 homologue was knocked out, had increased sensitivity to doxorubicin. Equally, RNA interference in breast cancer drug-resistant cells demonstrated that downregulation of TRIAP1 impaired cell growth in the presence of doxorubicin. As expected, caspase-9 activation was diminished after overexpression of TRIAP1 in drug-resistant cells. Importantly, stable transfections of a TRIAP1 expression plasmid in CAL51 cells led to a marked increase in the number of doxorubicin-resistant clones, that was abolished when cells expressed hairpins targeting TRIAP1. In addition, we showed that TRIAP1 expression was also triggered by estrogen deprivation in MCF-7 cells. Although both polyclonal and monoclonal antibodies generated for the present study failed to robustly detect TRIAP1, we demonstrated that TRIAP1 represents a novel marker for drug resistance in breast cancer cells and it may be used in the stratification of breast cancer patients once a suitable antibody has been developed. Equally, these studies open potential drug development strategies for blocking TRIAP1 activity and avoiding drug resistance.

Objective: To evaluate the associations between the number of chronic conditions and maternal race and ethnicity ("race") with the risk of severe maternal morbidity. Methods:Using the National Inpatient Sample, Healthcare Cost and Utilization Project, Agency for Healthcare Research and Quality, years 2016-2017, we examined risk of severe maternal morbidity among 1,480,925 delivery hospitalizations among women of different races and with different numbers of comorbid conditions using multivariable logistic regression. Results:The rate of severe maternal morbidity was 139.7 per 10,000 deliveries. Compared to women with no comorbidities (rate=48.5 per 10,000), there was increased risk of severe maternal morbidity among women with one comorbidity (rate=238.6; OR=5.0 [95% CI: 4.8-5.2]), two comorbidities (rate=379.9; OR=8.1 [95% CI: 7.8-8.5]), or three or more comorbidities (rate=560; OR=12.1 [95% CI: 11.5-12.7]). In multivariable regressions, similar associations were noted for women with one (aOR=4.4 [95% CI: 4.2-4.6]), two (aOR=6.6 [95% CI: 6.3-6.9]), or three or more comorbidities (aOR=9.1 [95% CI: 8.7-9.6]). Black women had higher rates of comorbid conditions than all other racial and ethnic groups, with 55% (95% CI: 54%-56%) of black women having no comorbidities, compared to 67% (95% CI: 67%-68%) of white women, 68% (95% CI: 67%-69%) of Hispanic women, and 72% (95% CI: 71%-73%) of Asian women. Conclusions:We found a dose-response relationship between number of comorbidities and risk of severe maternal morbidity, with the highest rates of severe maternal morbidity among women with three or more comorbidities. Focusing on the prevention and treatment of chronic conditions