Volatile molecules for COVID-19: A possible pharmacological strategy?

COVID-19 is a novel coronavirus disease with a higher incidence of bilateral pneumonia and pleural effusion. The high pulmonary tropism and contagiousness of the virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), have stimulated new approaches to combat its widespread diffusion. In developing new pharmacological strategies, the chemical characteristic of volatility can add therapeutic value to the hypothetical drug candidate. Volatile molecules are characterized by a high vapor pressure and are consequently easily exhaled by the lungs after ingestion. This feature could be exploited from a pharmacological point of view, reaching the site of action in an uncommon way but allowing for drug delivery. In this way, a hypothetical molecule for COVID-19 should have a balance between its lung exhalation characteristics and both antiviral and anti-inflammatory pharmacological action. Here, the feasibility, advantages, and disadvantages of a therapy based on oral administration of possible volatile drugs for COVID-19 will be discussed. Both aerosolized antiviral therapy and oral intake of volatile molecules are briefly reviewed, and an evaluation of 1,8-cineole is provided in view of a possible clinical use and also for asymptomatic COVID-19.     

Accuracy of MRI-guided Versus Systematic Prostate Biopsy in Patients Under Active Surveillance: A Systematic Review and Meta-analysis

This meta-analysis focuses on the accuracy of upgrading to clinically significant prostate cancer (PCa) by multiparametric magnetic resonance imaging-targeted biopsy (MRI-TB) versus systematic biopsy (SB). We searched the Medline, Embase, Cochrane Central Register of Controlled Trials, Web of Science, Scopus, and Literatura Latino Americana em Ciências da Saúde databases through January 2020 for comparative, retrospective/prospective, paired-cohort, and randomized clinical trials with paired comparisons. The population consisted of patients with low-risk PCa in active surveillance with at least 1 index lesion on imaging. We evaluated the quality of evidence by using the Quality Assessment of Diagnostic Accuracy Studies-2 score. Group comparisons considered the differences between the area under the curve summary receiver operating characteristic curve in a 2-tailed method. We also compared the positive predictive value of the best single method (MRI-TB or SB) and the referral study test (combined biopsy, a combination of MRI-TB and SB). The meta-analysis included 6 studies enrolling 741 patients. The pooled sensitivity for the 2 groups was 0.79 (95% confidence interval, 0.74-0.83; I² = 75%) and 0.67 (95% confidence interval, 0.63-0.74; I² = 55.4%), respectively. The area under the curve for the MRI-TB and SB groups were 0.99 and 0.92 (P < .001), respectively. The positive predictive value for the MRI-TB and combined biopsy groups were similar. The accumulated evidence suggests better results for MRI-TB compared with SB. Therefore, use of MRI-TB alone may be preferable in patients in active surveillance harboring low-risk PCa.     

Variation of resting energy expenditure after the first chemotherapy cycle in acute leukemia patients

Changes in resting energy expenditure (REE) of cancer patients vary depending on type of tumor, treatment time point and kind of treatment. Little is known about REE of acute leukemia adult patients after treatment, especially with results related to body weight or fat free mass (FFM). This study aimed to assess changes in REE of acute leukemia adult patients before and after the first remission induction. Evaluation of REE was performed by indirect calorimetry and predicted REE was calculated by Harris-Benedict equation. Weight and height were measured and compared to a control group of healthy individuals. FFM was assessed by bioelectrical impedance for adjusting REE values. We evaluated 18 patients and 26 healthy individuals. At diagnosis, patients presented REE, REE/weight, and REE/FFM higher than the controls. Reductions of REE, REE/weight, and REE/FFM were also observed in patients after the first cycle of chemotherapy. The predicted REE for the patients group showed significant lower value compared with measured REE. Before the first cycle of chemotherapy REE was increased but undergoes a reduction after treatment, reaching values similar to the controls. For predictive Harris-Benedict equation, stress factors should be added to avoid underestimation of REE before and after chemotherapy.