The field of infectious diseases currently takes a reactive approach and treats infections as they present in patients. Although certain populations are known to be at greater risk of developing infection (eg, immunocompromised), we lack a systems approach to define the true risk of future infection for a patient. Guided by impressive gains in “omics” technologies, future strategies to infectious diseases should take a precision approach to infection through identification of patients at intermediate and high-risk of infection and deploy targeted preventative measures (ie, prophylaxis). The advances of high-throughput immune profiling by multiomics approaches (ie, transcriptomics, epigenomics, metabolomics, proteomics) hold the promise to identify patients at increased risk of infection and enable risk-stratifying approaches to be applied in the clinic. Integration of patient-specific data using machine learning improves the effectiveness of prediction, providing the necessary technologies needed to propel the field of infectious diseases medicine into the era of personalized medicine.

Background: Primary spontaneous pneumothorax is a common disorder occurring in young adults without underlying lung disease. Although tobacco smoking is a well-documented risk factor for spontaneous pneumothorax, an association between electronic cigarette use (that is, vaping) and spontaneous pneumothorax has not been noted. We report a case of spontaneous pneumothoraces correlated with vaping. Case presentation: An 18-year-old Caucasian man presented twice with recurrent right-sided spontaneous pneumothoraces within 2 weeks. He reported a history of vaping just prior to both episodes. Diagnostic testing was notable for a right-sided spontaneous pneumothorax on chest X-ray and computed tomography scan. His symptoms improved following insertion of a chest tube and drainage of air on each occasion. In the 2-week follow-up visit for the recurrent episode, he was asymptomatic and reported that he was no longer using electronic cigarettes. Conclusions: Providers and patients should be aware of the potential risk of spontaneous pneumothorax associated with electronic cigarettes.

Diabetes increases the risk and severity of cognitive impairment, especially after ischemic stroke. Pathological remodeling of the cerebrovasculature has been postulated to contribute to poor neuronal repair and worsened cognitive deficits in diabetes. However, little is known about the effect of diabetes on the vascularization of hippocampus, a domain critical to memory and learning. Therefore, we had two aims for this study: 1) to determine the impact of diabetes on hippocampal neurovascular remodeling and the resulting cognitive impairment after stroke using two models with varying disease severity, and 2) to compare the effects of ischemia on hippocampal neurovascular injury in diabetic male and female animals. Stroke was induced by middle cerebral artery occlusion (MCAO) by either the suture or embolic method in control and diabetic age-matched male and female Wistar rats. Hippocampal neuronal density, vascular architecture, and microglial activation as well as cognitive outcomes were measured. Embolic MCAO induced greater neuronal degeneration, pathological vascularization, microglial activation, and cognitive impairment in diabetes as compared with control animals or 60-min MCAO. Although diabetic males had lower neuronal density at baseline, diabetic females had more neurodegeneration after stroke. Control animals recovered cognitive function by day 14 after stroke; diabetic animals showed deficits regardless of sex. These results suggest that mechanisms underlying cognitive decline in diabetes may differ in males and females and provide further insight to the impact of diabetes on stroke severity and poststroke cognitive impairment. NEW & NOTEWORTHY The present study is the first to provide comparative information on the effects of diabetes and ischemia on cognitive outcomes in both sexes while also evaluating the neurovascular structure in the hippocampus, a critical region for cognitive and memory-related tasks.

Tetraspanins are a family of proteins possessing four transmembrane domains that help in lateral organization of plasma membrane proteins. These proteins interact with each other as well as other receptors and signaling proteins, resulting in functional complexes called “tetraspanin microdomains.” Tetraspanins, including CD82, play an essential role in the pathogenesis of fungal infections. Dectin-1, a receptor for the fungal cell wall carbohydrate β-1,3-glucan, is vital to host defense against fungal infections. The current study identifies a novel association between tetraspanin CD82 and Dectin-1 on the plasma membrane of Candida albicans–containing phagosomes independent of phagocytic ability. Deletion of CD82 in mice resulted in diminished fungicidal activity, increased C. albicans viability within macrophages, and decreased cytokine production (TNF-α, IL-1β) at both mRNA and protein level in macrophages. Additionally, CD82 organized Dectin-1 clustering in the phagocytic cup. Deletion of CD82 modulates Dectin-1 signaling, resulting in a reduction of Src and Syk phosphorylation and reactive oxygen species production. CD82 knockout mice were more susceptible to C. albicans as compared with wild-type mice. Furthermore, patient C. albicans–induced cytokine production was influenced by two human CD82 single nucleotide polymorphisms, whereas an additional CD82 single nucleotide polymorphism increased the risk for candidemia independent of cytokine production. Together, these data demonstrate that CD82 organizes the proper assembly of Dectin-1 signaling machinery in response to C. albicans. Key Points Dectin-1 clustering via CD82 enables robust downstream Dectin-1 signaling. Lack of CD82 reduces macrophage fungal killing and survival of Candida infection. CD82 SNPs modulate cytokine production or risk of Candida infections. Visual Abstract