Neural circuits of long-term thermoregulatory adaptations to cold temperatures and metabolic demands.

The mammalian brain controls heat generation and heat loss mechanisms that regulate body temperature and energy metabolism. Thermoeffectors include brown adipose tissue, cutaneous blood flow and skeletal muscle, and metabolic energy sources include white adipose tissue. Neural and metabolic pathways modulating the activity and functional plasticity of these mechanisms contribute not only to the optimization of function during acute challenges, such as ambient temperature changes, infection and stress, but also to longitudinal adaptations to environmental and internal changes. Exposure of humans to repeated and seasonal cold ambient conditions leads to adaptations in thermoeffectors such as habituation of cutaneous vasoconstriction and shivering. In animals that undergo hibernation and torpor, neurally regulated metabolic and thermoregulatory adaptations enable survival during periods of significant reduction in metabolic rate. In addition, changes in diet can activate accessory neural pathways that alter thermoeffector activity. This knowledge may be harnessed for therapeutic purposes, including treatments for obesity and improved means of therapeutic hypothermia.

Voriconazole metabolism is associated with the number of skin cancers per patient.

Voriconazole exposure is associated with skin cancer, but it is unknown how the full spectrum of its metabolizer phenotypes impacts this association. We conducted a retrospective cohort study to determine how variation in metabolism of voriconazole as measured by metabolizer status of CYP2C19 is associated with the total number of skin cancers a patient develops and the rate of development of the first skin cancer after treatment. There were 1,739 organ transplant recipients with data on CYP2C19 phenotype. Of these, 134 were exposed to voriconazole. There was a significant difference in the number of skin cancers after transplant based on exposure to voriconazole, metabolizer phenotype, and the interaction of these two (p < 0.01 for all three). This increase was driven primarily by number of squamous cell carcinomas among rapid metabolizes with voriconazole exposure (p < 0.01 for both). Patients exposed to voriconazole developed skin cancers more rapidly than those without exposure (Fine-Grey hazard ratio 1.78, 95% confidence interval 1.19-2.66). This association was similarly driven by development of SCC (Fine-Grey hazard ratio 1.83, 95% confidence interval 1.14-2.94). Differences in voriconazoles metabolism are associated with an increase in the number of skin cancers developed after transplant, particularly SCC.

Voriconazole Metabolism is Associated with the Number of Skin Cancers Per Patient.

Voriconazole exposure is associated with skin cancer, but it is unknown how the full spectrum of its metabolizer phenotypes impacts this association. We conducted a retrospective cohort study to determine how variation in metabolism of voriconazole as measured by metabolizer status of CYP2C19 is associated with the total number of skin cancers a patient develops and the rate of development of the first skin cancer after treatment. There were 1,739 organ transplant recipients with data on CYP2C19 phenotype. Of these, 134 were exposed to voriconazole. There was a significant difference in the number of skin cancers after transplant based on exposure to voriconazole, metabolizer phenotype, and the interaction of these two (p < 0.01 for all three). This increase was driven primarily by number of squamous cell carcinomas among rapid metabolizes with voriconazole exposure (p < 0.01 for both). Patients exposed to voriconazole developed skin cancers more rapidly than those without exposure (Fine-Grey hazard ratio 1.78, 95% confidence interval 1.19-2.66). This association was similarly driven by development of SCC (Fine-Grey hazard ratio 1.83, 95% confidence interval 1.14-2.94). Differences in voriconazoles metabolism are associated with an increase in the number of skin cancers developed after transplant, particularly SCC.

Evaluating urine volume and host depletion methods to enable genome-resolved metagenomics of the urobiome.

Background: The gut microbiome has emerged as a clear player in health and disease, in part by mediating host response to environment and lifestyle. The urobiome (microbiota of the urinary tract) likely functions similarly. However, efforts to characterize the urobiome and assess its functional potential have been limited due to technical challenges including low microbial biomass and high host cell shedding in urine. Here, to begin addressing these challenges, we evaluate urine sample volume (100 ml - 5 mL), and host DNA depletion methods and their effects on urobiome profiles in healthy dogs, which are a robust large animal model for the human urobiome. We collected urine from seven dogs and fractionated samples into aliquots. One set of samples was spiked with host (canine) cells to model a biologically relevant host cell burden in urine. Samples then underwent DNA extraction followed by 16S rRNA gene and shotgun metagenomic sequencing. We then assembled metagenome assembled genomes (MAGs) and compared microbial composition and diversity across groups. We tested six methods of DNA extraction: QIAamp BiOstic Bacteremia (no host depletion), QIAamp DNA Microbiome, Molzym MolYsis, NEBNext Microbiome DNA Enrichment, Zymo HostZERO, and Propidium Monoazide. Results: In relation to urine sample volume, 3 3.0 mL resulted in the most consistent urobiome profiling. In relation to host depletion, individual (dog) but not extraction method drove overall differences in microbial composition. DNA Microbiome yielded the greatest microbial diversity in 16S rRNA sequencing data and shotgun metagenomic sequencing data, and maximized MAG recovery while effectively depleting host DNA in host-spiked urine samples. As proof-of-principle, we then mined MAGs for core metabolic functions and environmental chemical metabolism. We identified long chain alkane utilization in two of the urine MAGs. Long chain alkanes are common pollutants that result from industrial combustion processes and end up in urine. Conclusions: This is the first study, to our knowledge, to demonstrate environmental chemical degradation potential in urine microbes through genome-resolved metagenomics. These findings provide guidelines for studying the urobiome in relation to sample volume and host depletion, and lay the foundation for future evaluation of urobiome function in relation to health and disease.

Toward personalized skin cancer care: multiple skin cancer development in five cohorts.

Importance: Many patients will develop more than one skin cancer, however most research to date has examined only case status. Objective: Describe the frequency and timing of the treatment of multiple skin cancers in individual patients over time. Design: Longitudinal claims and electronic health record-based cohort study. Setting: Vanderbilt University Medical Center database called the Synthetic Derivative, VA, Medicare, Optum Clinformatics® Data Mart Database, IBM Marketscan. Participants: All patients with a Current Procedural Terminology code for the surgical management of a skin cancer in each of five cohorts. Exposures: None. Main Outcomes and Measures: The number of CPT codes for skin cancer treatment in each individual occurring on the same day as an ICD code for skin cancer over time. Results: Our cohort included 5,508,374 patients and 13,102,123 total skin cancers treated. Conclusions and Relevance: Nearly half of patients treated for skin cancer were treated for more than one skin cancer. Patients who have not developed a second skin cancer by 2 years after the first are unlikely to develop multiple skin cancers within the following 5 years. Better data formatting will allow for improved granularity in identifying individuals at high risk for multiple skin cancers and those unlikely to benefit from continued annual surveillance. Resource planning should take into account not just the number of skin cancer cases, but the individual burden of disease.

Profiles of Cognitive Functioning at 6 Months After Traumatic Brain Injury Among Patients in Level I Trauma Centers: A TRACK-TBI Study.

Importance: Cognitive dysfunction is common after traumatic brain injury (TBI), with a well-established dose-response relationship between TBI severity and likelihood or magnitude of persistent cognitive impairment. However, patterns of cognitive dysfunction in the long-term (eg, 6-month) recovery period are less well known. Objective: To characterize the prevalence of cognitive dysfunction within and across cognitive domains (processing speed, memory, and executive functioning) 6 months after injury in patients with TBI seen at level I trauma centers. Design, Setting, and Participants: This prospective longitudinal cohort study used data from Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) and included patients aged 17 years or older presenting at 18 US level I trauma center emergency departments or inpatient units within 24 hours of head injury, control individuals with orthopedic injury recruited from the same centers, and uninjured friend and family controls. Participants were enrolled between March 2, 2014, and July 27, 2018. Data were analyzed from March 5, 2020, through October 3, 2023. Exposures: Traumatic brain injury (Glasgow Coma Scale score of 3-15) or orthopedic injury. Main Outcomes and Measures: Performance on standard neuropsychological tests, including premorbid cognitive ability (National Institutes of Health Toolbox Picture Vocabulary Test), verbal memory (Rey Auditory Verbal Learning Test), processing speed (Wechsler Adult Intelligence Scale [4th edition] Processing Speed Index), and executive functioning (Trail Making Test). Results: The sample included 1057 persons with TBI (mean [SD] age, 39.3 [16.4] years; 705 [67%] male) and 327 controls without TBI (mean [SD] age, 38.4 [15.1] years; 222 [68%] male). Most persons with TBI demonstrated performance within 1.5 SDs or better of the control group (49.3% [95% CI, 39.5%-59.2%] to 67.5% [95% CI, 63.7%-71.2%] showed no evidence of impairment). Similarly, 64.4% (95% CI, 54.5%-73.4%) to 78.8% (95% CI, 75.4%-81.9%) of participants demonstrated no evidence of cognitive decline (defined as performance within 1.5 SDs of estimated premorbid ability). For individuals with evidence of either cognitive impairment or decline, diverse profiles of impairment across memory, speed, and executive functioning domains were observed (ie, the prevalence was >0 in each of the 7 combinations of impairment across these 3 cognitive domains for most TBI subgroups). Conclusions and Relevance: In this cohort study of patients seen at level I trauma centers 6 months after TBI, many patients with TBI demonstrated no cognitive impairment. Impairment was more prevalent in persons with more severe TBI and manifested in variable ways across individuals. The findings may guide future research and treatment recommendations.