Immunotherapy treatments aim to modulate the host’s immune response to either mitigate it in inflammatory/autoimmune disease or enhance it against infection or cancer. Among different immunotherapies reaching clinical application during the last years, chimeric antigen receptor (CAR) immunotherapy has emerged as an effective treatment for cancer where different CAR T cells have already been approved. Yet their use against infectious diseases is an area still relatively poorly explored, albeit with tremendous potential for research and clinical application. Infectious diseases represent a global health challenge, with the escalating threat of antimicrobial resistance underscoring the need for alternative therapeutic approaches. This review aims to systematically evaluate the current applications of CAR immunotherapy in infectious diseases and discuss its potential for future applications. Notably, CAR cell therapies, initially developed for cancer treatment, are gaining recognition as potential remedies for infectious diseases. The review sheds light on significant progress in CAR T cell therapy directed at viral and opportunistic fungal infections.

Background: Detecting and managing antimicrobial drug interactions (ADIs) is one of the facets of prudent antimicrobial prescribing. Our aim is to compare the capability of several electronic drug–drug interaction (DDI) checkers to detect and report ADIs. Methods: Six electronic DDI checking platforms were evaluated: Drugs.com^®, Medscape^®, Epocrates^®, Medimecum^®, iDoctus^®, and Guía IF^®. Lexicomp^® Drug Interactions was selected as the gold standard. Ten ADIs addressing different mechanisms were evaluated with every electronic DDI checker. For each ADI, we assessed five dimensions and calculated an overall performance score (maximum possible score: 10 points). The explored dimensions were sensitivity (capability to detect ADI), clinical effect (type and severity), mechanism of interaction, recommended action(s), and documentation (quality of evidence and availability of references). Results: The electronic DDI checkers did not detect a significant proportion of the ADI assessed. The overall performance score ranged between 4.4 (Medimecum) and 8.8 (Drugs.com). Drugs.com was the highest ranked platform in four out of five dimensions (sensitivity, effect, mechanism, and recommended action). Conclusions: There is significant variability in the performance of the available platforms in detecting and assessing ADI. Although some ADI checkers have proven to be very accurate, others missed almost half of the explored interactions.

During respiratory infections, host-pathogen interaction alters metabolism, leading to changes in the composition of expired volatile organic compounds (VOCs) and soluble immunomodulators. This study aims to identify VOC and blood biomarker signatures to develop machine learning-based prognostic models capable of distinguishing infections with similar symptoms. Twenty-one VOCs and fifteen serum biomarkers were quantified in samples from 86 COVID-19 patients, 75 patients with non-COVID-19 respiratory infections, and 72 healthy donors. The populations were categorized into severity subgroups based on their oxygen support requirements. Descriptive and statistical analyses were conducted to assess group differentiation. Additionally, machine learning classifiers were developed to predict disease severity in both COVID-19 and non-COVID-19 patients. VOC and biomarker profiles differed significantly among groups. Random Forest models demonstrated the best performance for severity prediction. The COVID-19 model achieved 93% accuracy, 100% sensitivity, and 89% specificity, identifying IL-6, IL-8, thrombomodulin, and toluene as key severity predictors. In non-COVID-19 patients, the model reached 89% accuracy, 100% sensitivity, and 67% specificity, with CXCL10 and methyl-isobutyl-ketone as key markers. VOCs and serum biomarkers differentiated HD, COVID-19, and non-COVID-19 patients, and enabled the development of high-performance severity prediction models. While promising, these findings require validation in larger independent cohorts.

A 76-year-old woman presented in cardiology clinic with New York Heart Association class II dyspnoea for the last 4 months. She had a history of severe mitral and moderate aortic stenosis that required double mechanical valve replacement 15 years ago. B-type natriuretic peptide was normal, and transthoracic echocardiogram showed that both prostheses had similar gradients to the last ones measured. Pulmonary function tests were normal. The patient kept referring persistent dyspnoea and other non-specific symptoms. Physical examination revealed significant aortic and mitral systolic murmurs. Erythematous painless macules on the palms and dark red subungual lesions in the nail beds of the fourth finger were found on both hands ( Figure 1). Routine blood cultures detected growth of Streptococcus gordonii. Although initial transthoracic echocardiogram could not detect any vegetation, a transoesophageal echocardiogram was performed and showed two mobile images in the atrial side of the mitral ring of 7 mm in length, suggesting vegetation, causing a mild periprosthetic leak in the mitral–aortic junction. F-fluorodeoxyglucose (F-FDG) positron emission tomography (PET)/computed tomography (CT) was performed due to the limitation of echocardiogram, and revealed two foci of hypermetabolism, in the aortic and predominantly the mitral valve ( Figure 2). According to modified Duke Criteria, patient was diagnosed of definite infective endocarditis fulfilling two major (positive echocardiography, abnormal activity around the site of prosthetic valve implantation by ¹⁸F-FDG PET/CT) and three minor criteria (predisposing heart condition, vascular phenomena—Janeway lesions—and positive blood culture). The case was discussed in a multidisciplinary heart team and a conservative medical approach based on ceftriaxone was decided. Janeway lesions are irregular, painless, erythematous or haemorrhagic macules, or papules commonly found on the palms and soles. The pathogenesis of Janeway lesions is still a controversial topic in the literature, but the main hypothesis is based on septic embolic events. Although current diagnosis of endocarditis is unlikely to be made only on the basis of Janeway lesions, the use of classic cutaneous signs of this entity could not be forgotten by clinicians, even in the post-antibiotic era of the developed world, to achieve the correct diagnosis.