Cervicovaginal fluid (CVF) is a valuable source of clinical information about the female reproductive tract in both nonpregnant and pregnant women. The aim of this study is to specify the CVF proteome at different stages of cervix neoplastic transformation by label-free quantitation approach based on liquid chromatography tandem mass spectrometry (LC-MS/MS) method. The proteome composition of CVF from 40 women of reproductive age with human papillomavirus (HPV)-associated cervix neoplastic transformation (low-grade squamous intraepithelial lesion [LSIL], high-grade squamous intraepithelial lesion [HSIL], and CANCER) was investigated. Hierarchical clustering and principal component analysis (PCA) of the proteomic data obtained by a label-free quantitation approach show the distribution of the sample set between four major clusters (no intraepithelial lesion or malignancy [NILM], LSIL, HSIL and CANCER) depending on the form of cervical lesion. Multisample ANOVA with subsequentWelch's t test resulted in 117 that changed significantly across the four clinical stages, including 27 proteins significantly changed in cervical cancer. Some of them were indicated as promising biomarkers previously (ACTN4, VTN, ANXA1, CAP1, ANXA2, and MUC5B). CVF proteomic data from the discovery stage were analyzed by the partial least squares-discriminant analysis (PLS-DA) method to build a statistical model, allowing to differentiate severe dysplasia (HSIL and CANCER) from the mild/normal stage (NILM and LSIL), and receiver operating characteristic (ROC) area under the curve (AUC) were obtained on an independent set of 33 samples. The sensitivity of the model was 77%, and the specificity was 94%; AUC was equal to 0.87. CVF proteome proved to be reflect the stage of cervical epithelium neoplastic process.
The review article presents data on the prevalence of candidiasis of various localization against the history of coronavirus infection (COVID-19). The predisposing factors for the development and recurrence of candidiasis in patients after therapy for coronavirus infection have been analysed. Candida is one of the most common pathogens in intensive care units (ICUs), affecting 6 to 10% of patients, and some studies have reported an increasing trend in the prevalence of candidemia. The literature data that we analysed showed that the most common types of fungal infection among patients with a severe course of COVID-19 were C. albicans, then C. auris, C. glabrata, C. parapsilosis, C. tropicalis, S. cerevisiae, C. krusei and Rhodotorula spp. Candida non-albicans species, in particular C. glabrata, C. auris, were the most common causes of death. The previous treatment regimens for patients with COVID-19 included antibiotics, but at present time corticosteroids are more often used, which have an immunosuppressive effect and, accordingly, predispose to the development of candidiasis. The epithelial injury caused by SARS-CoV-2 also enables Candida to attach to the basement membrane, subsequently triggering the development of mucosal candidiasis. As the systemic and local candidiasis are conditioned by common immune mechanisms that are affected by coronavirus infection, vulvovaginal candidiasis (VVC) may recur during COVID-19 therapy. The timely diagnosis and treatment of fungal infections in patients who underwent COVID-19 are crucial for achieving a positive clinical outcome. The article provides an algorithm for the management of patients with recurrent VVC, the principles of action of antifungal drugs, their acceptability and efficacy.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.