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Background Inflammation may contribute to cognitive difficulties in patients with breast cancer. We tested 2 hypotheses: inflammation is elevated in patients with breast cancer vs noncancer control participants and inflammation in patients is associated with worse attention and processing speed over the course of chemotherapy. Methods Serum cytokines (interleukin [IL]–4, 6, 8, 10; tumor necrosis factor [TNF]–α) and soluble receptors [sTNFRI, II]) were measured in 519 females with breast cancer before and after chemotherapy and 338 females without cancer serving as control participants. Attention and processing speed were measured by Rapid Visual Processing (RVP), Backward Counting (BCT), and Trail Making-A (TMT-A) tests. Linear regression models examined patient vs control cytokines and receptor levels, adjusting for covariates. Linear regression models also examined relationships between patient cytokines and receptor levels and test performance, adjusting for age, body mass index, anxiety, depression, cognitive reserve, and chemotherapy duration. Statistical tests were 2-sided (α = .05). Results sTNFRI and sTNFRII increased over time in patients relative to controls, whereas IL-4, IL-6, and IL-10 decreased. Prechemotherapy, higher IL-8 associated with worse BCT (β = 0.610, SE = 0.241, P = .01); higher IL-4 (β = −1.098, SE = 0.516, P = .03) and IL-10 (β = −0.835, SE = 0.414, P = .04) associated with better TMT-A. Postchemotherapy, higher IL-8 (β = 0.841, SE = 0.260, P = .001), sTNFRI (β = 6.638, SE = 2.208, P = .003), and sTNFRII (β = 0.913, SE = 0.455, P = .045) associated with worse BCT; higher sTNFRII also associated with worse RVP (β = −1.316, SE = 0.587, P = .03). At prechemotherapy, higher IL-4 predicted RVP improvement over time (β = 0.820, SE = 0.336, P = .02); higher sTNFRI predicted worse BCT over time (β = 5.566, SE = 2.367, P = .02). Longitudinally, increases in IL-4 associated with BCT improvement (β = −0.564, SE = 0.253, P = .03). Conclusions Generally, worse attention and processing speed were associated with higher inflammatory cytokines and receptors and lower anti-inflammatory cytokines in patients; future confirmatory studies are needed.

Untreated tooth decays affect nearly one third of the world and is the most prevalent disease burden among children. The disease progression of tooth decay is multifactorial and involves a prolonged decrease in pH, resulting in the demineralization of tooth surfaces. Bacterial species that are capable of fermenting carbohydrates contribute to the demineralization process by the production of organic acids. The combined use of machine learning and 16s rRNA sequencing offers the potential to predict tooth decay by identifying the bacterial community that is present in an individual’s oral cavity. A few recent studies have demonstrated machine learning predictive modeling using 16s rRNA sequencing of oral samples, but they lack consideration of the multifactorial nature of tooth decay, as well as the role of fungal species within their models. Here, the oral microbiome of mother–child dyads (both healthy and caries-active) was used in combination with demographic–environmental factors and relevant fungal information to create a multifactorial machine learning model based on the LASSO-penalized logistic regression. For the children, not only were several bacterial species found to be caries-associated (Prevotella histicola, Streptococcus mutans, and Rothia muciloginosa) but also Candida detection and lower toothbrushing frequency were also caries-associated. Mothers enrolled in this study had a higher detection of S. mutans and Candida and a higher plaque index. This proof-of-concept study demonstrates the significant impact machine learning could have in prevention and diagnostic advancements for tooth decay, as well as the importance of considering fungal and demographic–environmental factors.

Staphylococcus aureus is a major cause of ocular infections, often resulting in devastating vision loss. Despite the significant morbidity associated with these infections, little is yet known regarding the specific strain types that may have a predilection for ocular tissues nor the set of virulence factors that drive its pathogenicity in this specific biological niche. Whole genome sequencing (WGS) can provide valuable insight in this regard by providing a prospective, comprehensive assessment of the strain types and virulence factors driving disease among specific subsets of clinical isolates. As such, a set of 163-member S. aureus ocular clinical strains were sequenced and assessed for both common strain types (multilocus sequence type (MLST), spa, agr) associated with ocular infections as well as the presence/absence of 235 known virulence factors in a high throughput manner. This ocular strain set was then directly compared to a fully sequenced 116-member non-ocular S. aureus strain set curated from NCBI in order to identify key differences between ocular and non-ocular S. aureus isolates. The most common sequence types found among ocular S. aureus isolates were ST5, ST8 and ST30, generally reflecting circulating non-ocular pathogenic S. aureus strains. However, importantly, ocular isolates were found to be significantly enriched for a set of enterotoxins, suggesting a potential role for this class of virulence factors in promoting ocular disease. Further genomic analysis revealed that these enterotoxins are located on mobile pathogenicity islands, thus horizontal gene transfer may promote the acquisition of enterotoxins, potentially amplifying S. aureus virulence in ocular tissues.

PURPOSE: Staphylococcus aureus is a leading cause of keratitis requiring urgent antimicrobial treatment. However, rising antibiotic resistance has rendered current ophthalmic antibiotics increasingly ineffective. First, a diverse, ocular S. aureus strain set was evaluated for resistance to six commonly used ophthalmic antibiotics. Next, a recently discovered antimicrobial drug combination containing polymyxin B/trimethoprim + rifampin that displayed impressive efficacy towards S. aureus in both in vitro and in vivo studies was evaluated as a potential novel keratitis therapeutic through testing this combination’s efficacy against the clinical strain set. METHODS: 163 S. aureus isolates were collected commercially or from the University of Rochester, Flaum Eye Institute. The minimum inhibitory concentrations (MICs) of moxifloxacin, levofloxacin, vancomycin, erythromycin, tobramycin, rifampin and polymyxin B/trimethoprim (PT) were determined for the entire strain set to establish the incidence of resistance to current treatment options among a contemporary clinical isolate set and compared to the performance of PT + rifampin. RESULTS: Among all 163 isolates tested, high rates of antibiotic resistance were found toward erythromycin (69% resistance), moxifloxacin (33%), levofloxacin (40%) and tobramycin (17%). Conversely, the entire strain set, including multi-drug resistant (MDR) isolates, was sensitive to PT + rifampin, demonstrating the potency of this combination. CONCLUSIONS: We establish that antibiotic resistance is pervasive among clinical S. aureus isolates, underscoring the concern for the effectiveness of current ophthalmic antibiotics. The drug combination of PT + rifampin, however, eradicated 100% of isolates tested, demonstrating the ability to overcome existing circulating resistance factors, and as such, may represent a promising therapeutic for S. aureus keratitis

Rationale: The oropharyngeal microbiome is a primary source of lung microbiota, contributes to lower respiratory infection, and is also a driver of oral health. Objectives: We sought to understand oropharyngeal microbial communities in advanced lung disease, community dynamics after lung transplantation, and ecological features of dysbiosis. Methods: Oropharyngeal wash samples were obtained from individuals with end-stage disease awaiting transplantation (n = 22) and longitudinally from individuals at 6 weeks, 3 months, and 6 months after transplantation (n = 33), along with healthy control subjects (n = 14). Bacterial 16S and fungal internal transcribed spacer rRNA regions were deep-sequenced, and bacterial community respiratory patterns were imputed from taxonomic composition. Results: Healthy subjects’ oropharyngeal microbiomes showed a gradient of community types reflecting relative enrichment of strictly anaerobic, aerobic, or facultative anaerobic bacteria. Patients with end-stage lung disease showed severe dysbiosis by both taxonomic composition and respiration phenotypes, with reduced richness and diversity, increased facultative and decreased aerobic bacteria, and absence of communities characterized by obligate aerobes. In patients at 6 weeks and 3 months post-transplant, richness and diversity were intermediate between healthy and pretransplant subjects, with near-normal distribution of community types. However, by 6 months post-transplant, oropharyngeal wash resembled the low-diversity facultative-dominated profile of pretransplant subjects. Community ecotype correlated with Candida abundance. Conclusions: End-stage lung disease is associated with marked upper respiratory tract dysbiosis involving both community structure and respiratory metabolism profiles of constituent bacteria. Dynamic changes occur after lung transplantation, with partial normalization early but later appearance of severe dysbiosis similar to pretransplant patients. Aberrant oropharyngeal communities may predispose to abnormal lung microbiota and infection risk both in advanced lung disease and after transplantation.