The relative validity of nutrition assessment methods for estimating infant carotenoid intake differs by assessment tool, nutrient database, and milk carotenoid adjustment method.

Validated carotenoid assessment methods are needed to study infant carotenoid nutrition. This is a secondary analysis of repeated diet assessments of healthy participants collected at 4- (n = 21), 6- (n = 12), and 8- (n = 9) months of age in Houston, TX between April 2019 and June 2020. Intake was assessed with 3 assessment tools, analyzed with 3 nutrient databases, and underwent 3 adjustments to account for milk composition variability. We hypothesized that manual adjustment of milk carotenoid intake based on laboratory measurements would improve the validity of all assessment approaches and that using a database with greater coverage of infant food carotenoid compositions would improve accuracy. Generalized linear mixed models assessed associations between tool, nutrient database, age, and milk carotenoid adjustment variables with carotenoid, energy, fruit, and vegetable intakes. The effect of the number of food diary days on intake estimate precision was evaluated by testing the correlation between intake estimates derived from 1, 3, or 5, vs. 7 days. Visit age influenced energy intake estimates (p = .029), along with assessment tool (p = .020). Estimates of vegetable intake were influenced by tool (p = .009). Combined fruit and vegetable intake differed by nutrient database (p = .007). Carotenoid intake differed by age (p =<.0001), tool (p = .002), and nutrient database (p = .004). A minimum of 3 food diary days strongly correlated (rho = 0.79-1) with reference estimates across ages. Milk carotenoid adjustment was most influential in estimating 4-month olds' carotenoid intake, while nutrient database and tool were important for 6- and 8-month-olds', highlighting the dynamic nature of infant diet assessment validity across feeding stages.

Sex differences in global metabolomic profiles of COVID-19 patients.

Coronavirus disease (COVID-19), caused by SARS-CoV-2, leads to symptoms ranging from asymptomatic disease to death. Although males are more susceptible to severe symptoms and higher mortality due to COVID-19, patient sex has rarely been examined. Sex-associated metabolic changes may implicate novel biomarkers and therapeutic targets to treat COVID-19. Here, using serum samples, we performed global metabolomic analyses of uninfected and SARS-CoV-2-positive male and female patients with severe COVID-19. Key metabolic pathways that demonstrated robust sex differences in COVID-19 groups, but not in controls, involved lipid metabolism, pentose pathway, bile acid metabolism, and microbiome-related metabolism of aromatic amino acids, including tryptophan and tyrosine. Unsupervised statistical analysis showed a profound sexual dimorphism in correlations between patient-specific clinical parameters and their global metabolic profiles. Identification of sex-specific metabolic changes in severe COVID-19 patients is an important knowledge source for researchers striving for development of potential sex-associated biomarkers and druggable targets for COVID-19 patients.

Brain injury, endothelial injury and inflammatory markers are elevated and express sex-specific alterations after COVID-19.

OBJECTIVE: Although COVID-19 is a respiratory disease, all organs can be affected including the brain. To date, specific investigations of brain injury markers (BIM) and endothelial injury markers (EIM) have been limited. Additionally, a male bias in disease severity and mortality after COVID-19 is evident globally. Sex differences in the immune response to COVID-19 may mediate this disparity. We investigated BIM, EIM and inflammatory cytokine/chemokine (CC) levels after COVID-19 and in across sexes. METHODS: Plasma samples from 57 subjects at < 48 h of COVID-19 hospitalization, and 20 matched controls were interrogated for the levels of six BIMs-including GFAP, S100B, Syndecan-1, UCHLI, MAP2 and NSE, two EIMs-including sICAM1 and sVCAM1. Additionally, several cytokines/chemokines were analyzed by multiplex. Statistical and bioinformatics methods were used to measure differences in the marker profiles across (a) COVID-19 vs. controls and (b) men vs. women. RESULTS: Three BIMs: MAP2, NSE and S100B, two EIMs: sICAM1 and sVCAM1 and seven CCs: GRO IL10, sCD40L, IP10, IL1Ra, MCP1 and TNFα were significantly (p < 0.05) elevated in the COVID-19 cohort compared to controls. Bioinformatics analysis reveal a stronger positive association between BIM/CC/EIMs in the COVID-19 cohort. Analysis across sex revealed that several BIMs and CCs including NSE, IL10, IL15 and IL8 were significantly (p < 0.05) higher in men compared to women. Men also expressed a more robust BIM/ EIM/CC association profile compared to women. CONCLUSION: The acute elevation of BIMs, CCs, and EIMs and the robust associations among them at COVID-19 hospitalization are suggestive of brain and endothelial injury. Higher BIM and inflammatory markers in men additionally suggest that men are more susceptible to the risk compared to women.

Pain and Other Neurological Symptoms Are Present at 3 Months After Hospitalization in COVID-19 Patients.

COVID-19 is an ongoing pandemic with a devastating impact on public health. Acute neurological symptoms have been reported after a COVID-19 diagnosis, however, the long-term neurological symptoms including pain is not well established. Using a prospective registry of hospitalized COVID-19 patients, we assessed pain and neurological function (including functional, cognitive and psychiatric assessments) of several hospitalized patients at 3 months. Our main finding is that 60% of the patients report pain symptoms. 71% of the patients still experienced neurological symptoms at 3 months and the most common symptoms being fatigue (42%) and PTSD (25%). Cognitive symptoms were found in 12%. Our preliminary findings suggests the importance of investigating long-term outcomes and rationalizes the need for further studies investigating the neurologic outcomes and symptoms of pain after COVID-19.

Use of Antibiotics Without a Prescription in the U.S. Population: A Scoping Review.

Background: Use of antibiotics without a prescription may increase unnecessary and inappropriate drug use or doses as well as global risk for antimicrobial resistance. Purpose: To perform a scoping review of research on the prevalence of nonprescription antibiotic use in the United States and to examine the factors that influence it. Data Sources: Searches of PubMed, EMBASE, CINAHL, Scopus, and relevant Web sites without language restrictions from January 2000 to March 2019. Study Selection: Studies reporting nonprescription use of antibiotics, storage of antibiotics, intention to use antibiotics without a prescription, and factors influencing nonprescription use. Data Extraction: Two reviewers independently screened citations and full texts and performed data abstraction. Data Synthesis: Of 17 422 screened articles, 31 met inclusion criteria. Depending on population characteristics, prevalence of nonprescription antibiotic use varied from 1% to 66%, storage of antibiotics for future use varied from 14% to 48%, and prevalence of intention to use antibiotics without a prescription was 25%. Antibiotics were obtained without a prescription from various sources, including previously prescribed courses, local markets or stores, and family or friends. Reported factors contributing to nonprescription use included easy access through markets or stores that obtain antibiotics internationally for under-the-counter sales, difficulty accessing the health care system, costs of physician visits, long waiting periods in clinics, and transportation problems. Limitation: Scarce evidence and heterogeneous methods and outcomes. Conclusion: Nonprescription antibiotic use is a seemingly prevalent and understudied public health problem in the United States. An increased understanding of risk factors and pathways that are amenable to intervention is essential to decrease this unsafe practice. Primary Funding Source: None.