The pro-inflammatory cytokine interleukin (IL)-1β is critical for normal hippocampus (HP)-dependent cognition, whereas high levels can disrupt memory and are implicated in neurodegeneration. However, the cellular source of IL-1β during learning has not been shown, and little is known about the risk factors leading to cytokine dysregulation within the HP. We have reported that neonatal bacterial infection in rats leads to marked HP-dependent memory deficits in adulthood. However, deficits are only observed if unmasked by a subsequent immune challenge (lipopolysaccharide, LPS) around the time of learning. These data implicate a long-term change within the immune system that, upon activation with the “second hit”, LPS, acutely impacts the neural processes underlying memory. Indeed, inhibiting brain IL-1β prior to the LPS challenge prevents memory impairment in neonatally-infected (NI) rats. We aimed to determine the cellular source of IL-1β during normal learning, and thereby lend insight into the mechanism by which this cytokine is enduringly altered by early-life infection. We show for the first time that CD11b+ enriched cells are the source of IL-1β during normal HP-dependent learning. CD11b+ cells from NI rats are functionally sensitized within the adult HP and produce exaggerated IL-1β ex vivo compared to controls. However, an exaggerated IL-1β response in vivo requires LPS prior to learning. Moreover, preventing microglial activation during learning prevents memory impairment in NI rats, even following an LPS challenge. Thus, early-life events can significantly modulate normal learning-dependent cytokine activity within the HP, via a specific, enduring impact on brain microglial function.

Objective To assess the influence of patient preferences and urologist recommendations in treatment decisions for clinically localized prostate cancer. Methods We enrolled 257 men with clinically localized prostate cancer (PSA < 20; Gleason 6 or 7) seen by urologists (primarily residents and fellows) in 4 Veterans Affairs Medical Centers. We measured patients’ baseline preferences prior to their urology appointments, including initial treatment preference, cancer-related anxiety, and interest in sex. In longitudinal follow-up, we determined which treatment patients received. We used hierarchical logistic regression to determine the factors that predicted treatment received (active treatment vs. active surveillance) and urologist recommendations. We also conducted a directed content analysis of recorded clinical encounters to determine if urologists discussed patients’ interest in sex. Results Patients’ initial treatment preferences did not predict receipt of active treatment versus surveillance (Δχ2 (4) = 3.67, p = .45). Instead, receipt of active treatment was predicted primarily by urologists’ recommendations (Δχ2(2) = 32.81 p < .001). Urologists’ recommendations, in turn, were influenced heavily by medical factors (age and Gleason score) but unrelated to patient preferences (Δχ2 (6) = 0, p = 1). Urologists rarely discussed patients’ interest in sex (< 15% of appointments). Conclusions Patients’ treatment decisions were based largely upon urologists’ recommendations, which, in turn, were based on medical factors (age and Gleason score) and not on patients’ personal views of the relative pros and cons of treatment alternatives.