Recent studies have revealed that microbes play an important role in the pathogenesis of gastrointestinal (GI) diseases in various animal species, but only limited data is available about the microbiome in cats with GI disease. The aim of this study was to evaluate the fecal microbiome in cats with diarrhea. Fecal samples were obtained from healthy cats (n = 21) and cats with acute (n = 19) or chronic diarrhea (n = 29) and analyzed by sequencing of 16S rRNA genes, and PICRUSt was used to predict the functional gene content of the microbiome. Linear discriminant analysis (LDA) effect size (LEfSe) revealed significant differences in bacterial groups between healthy cats and cats with diarrhea. The order Burkholderiales, the families Enterobacteriaceae, and the genera Streptococcus and Collinsella were significantly increased in diarrheic cats. In contrast the order Campylobacterales, the family Bacteroidaceae, and the genera Megamonas, Helicobacter, and Roseburia were significantly increased in healthy cats. Phylum Bacteroidetes was significantly decreased in cats with chronic diarrhea (>21 days duration), while the class Erysipelotrichi and the genus Lactobacillus were significantly decreased in cats with acute diarrhea. The observed changes in bacterial groups were accompanied by significant differences in functional gene contents: metabolism of fatty acids, biosynthesis of glycosphingolipids, metabolism of biotin, metabolism of tryptophan, and ascorbate and aldarate metabolism, were all significantly (p<0.001) altered in cats with diarrhea. In conclusion, significant differences in the fecal microbiomes between healthy cats and cats with diarrhea were identified. This dysbiosis was accompanied by changes in bacterial functional gene categories. Future studies are warranted to evaluate if these microbial changes correlate with changes in fecal concentrations of microbial metabolites in cats with diarrhea for the identification of potential diagnostic or therapeutic targets.

Research indicates that after advanced age, the major risk factor for late-onset Alzheimer's disease (AD) is female sex. Out of every three AD patients, two are females with postmenopausal women contributing to over 60% of all those affected. Sex- and gender-related differences in AD have been widely researched and several emerging lines of evidence point to different vulnerabilities that contribute to dementia risk. Among those being considered, it is becoming widely accepted that gonadal steroids contribute to the gender disparity in AD, as evidenced by the "estrogen hypothesis." This posits that sex hormones, 17β-estradiol in particular, exert a neuroprotective effect by shielding females' brains from disease development. This theory is further supported by recent findings that the onset of menopause is associated with the emergence of AD-related brain changes in women in contrast to men of the same age. In this review, we discuss genetic, medical, societal, and lifestyle risk factors known to increase AD risk differently between the genders, with a focus on the role of hormonal changes, particularly declines in 17β-estradiol during the menopause transition (MT) as key underlying mechanisms.

Background

As medical education shifted to a virtual environment during the early coronavirus disease 2019 (COVID-19) pandemic, we evaluated how neurology podcasting may have been utilized during this period, and which features of podcasts have been more highly sought by a medical audience.

Methods

We conducted a retrospective analysis of neurology-themed blogs and/or podcasts between April 2019 and May 2020. Programs were eligible if they reported mean monthly downloads > 2000, were affiliated with an academic society, or offered continuing medical education credit. Thirty-day download counts were compared between study months, with adjustment for multiple testing. Exploratory analyses were performed to determine which podcast features were associated with higher downloads.

Results

Of the 12 neurology podcasts surveyed, 8 completed the survey and 5 met inclusion criteria. The median monthly download count was 2865 (IQR 869-7497), with significant variability between programs (p < 0.001). While there was a 358% increase in downloads during April 2020 when compared to the previous month, this was not significant (median 8124 [IQR 2913-14,177] vs. 2268 [IQR 540-6116], p_adj = 0.80). The non-significant increase in overall downloads during April 2020 corresponded to an increase in unique episodes during that month (r = 0.48, p = 0.003). There was no difference in 30-day downloads among episodes including COVID-19 content versus not (median 1979 [IQR 791-2873] vs. 1171 [IQR 405-2665], p = 0.28).

Conclusions

In this unique, exploratory study of academic neurology-themed podcasts, there was no significant increase in episode downloads during the early COVID-19 pandemic. A more comprehensive analysis of general and subspecialty medical podcasts is underway.