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Vaginal infections such as bacterial vaginosis (BV), chlamydia, gonorrhea, genital herpes, candidiasis, and trichomoniasis affect millions of women each year. They are caused by an overgrowth of microorganisms, generally sexually transmitted, which in turn can be favored by alterations in the vaginal flora. Conventional treatments of these infections consist in systemic or local antimicrobial therapies. However, in the attempt to reduce adverse effects and to contrast microbial resistance and infection recurrences, many efforts have been devoted to the development of vaginal systems for the local delivery of antimicrobials. Several topical dosage forms such as aerosols, lotions, suppositories, tablets, gels, and creams have been proposed, although they are sometimes ineffective due to their poor penetration and rapid removal from the vaginal canal. For these reasons, the development of innovative drug delivery systems, able to remain in situ and release active agents for a prolonged period, is becoming more and more important. Among all, nanosystems such as liposomes, nanoparticles (NPs), and micelles with tunable surface properties, but also thermogelling nanocomposites, could be exploited to improve local drug delivery, biodistribution, retention, and uptake in vulvovaginal tissues. The aim of this review is to provide a survey of the variety of nanoplatforms developed for the vaginal delivery of antimicrobial agents. A concise summary of the most common vaginal infections and of the conventional therapies is also provided.We aimed to identify whether lymphopenia is a reliable prognostic marker for COVID-19. Using data derived from a Korean nationwide longitudinal cohort of 5628 COVID-19 patients, we identified propensity-matched cohorts (n = 770) with group I of severe lymphopenia (absolute lymphocyte counts [ALC] less then 500/mm3, n = 110), group II of mild-to-moderate lymphopenia (ALC ≥500- less then 1000/mm3, n = 330), and group III, no lymphopenia (ALC ≥1000/mm3, n = 330). A significantly higher mortality rate was associated with lymphopenia severity 40% in group I, 22.7% in group II, and 13.0% in group III (p less then 0.001). At 28 days, the estimated inferior overall survival associated with intensified lymphopenia 62.7% in group I, 79.9% in group II, and 89.0% in group III (p less then 0.001). learn more Lymphopenia contributed significantly toward a greater need for interventions in all groups but at varying degrees requirements of invasive ventilation, intensive oxygen supply, or adequate oxygen supply, respectively (p less then 0.001). The lymphopenia intensity was independently associated with higher COVID-19 mortality in multivariable analysis; adjusted odds ratios of 5.63 (95% CI, 3.0-10.72), and 2.47 (95% CI, 1.5-4.13) for group I and group II, respectively. Lymphopenia and its severity levels may serve as reliable predictive factors for COVID-19 clinical outcomes; thus, lymphopenia may provide the prognostic granularity required for clinical use in the management of patients with COVID-19.Laboratory-based gait assessments are indicative of clinical outcomes (e.g., disease identification). Real-world gait may be more sensitive to clinical outcomes, as impairments may be exaggerated in complex environments. This study aims to investigate how different environments (e.g., lab, real world) impact gait. Different walking bout lengths in the real world will be considered proxy measures of context. Data collected in different dementia disease subtypes will be analysed as disease-specific gait impairments are reported between these groups. Thirty-two people with cognitive impairment due to Alzheimer’s disease (AD), 28 due to dementia with Lewy bodies (DLB) and 25 controls were recruited. Participants wore a tri-axial accelerometer for six 10 m walks in lab settings, and continuously for seven days in the real world. Fourteen gait characteristics across five domains were measured (i.e., pace, variability, rhythm, asymmetry, postural control). In the lab, the DLB group showed greater step length variability (p = 0.008) compared to AD. Both subtypes demonstrated significant gait impairments (p less then 0.01) compared to controls. In the real world, only very short walking bouts ( less then 10 s) demonstrated different gait impairments between subtypes. The context where walking occurs impacts signatures of gait impairment in dementia subtypes. To develop real-world gait assessment as a clinical tool, algorithms and metrics must accommodate for changes in context.A conceptually simple way to classify images is to directly compare test-set data and training-set data. The accuracy of this approach is limited by the method of comparison used, and by the extent to which the training-set data cover configuration space. Here we show that this coverage can be substantially increased using coarse-graining (replacing groups of images by their centroids) and stochastic sampling (using distinct sets of centroids in combination). We use the MNIST and Fashion-MNIST data sets to show that a principled coarse-graining algorithm can convert training images into fewer image centroids without loss of accuracy of classification of test-set images by nearest-neighbor classification. Distinct batches of centroids can be used in combination as a means of stochastically sampling configuration space, and can classify test-set data more accurately than can the unaltered training set. On the MNIST and Fashion-MNIST data sets this approach converts nearest-neighbor classification from a mid-ranking- to an upper-ranking member of the set of classical machine-learning techniques.The α and polyproline II (PPII) basins are the two most populated regions of the Ramachandran map when constructed from the protein coil library, a widely used denatured state model built from the segments of irregular structure found in the Protein Data Bank. This indicates the α and PPII conformations are dominant components of the ensembles of denatured structures that exist in solution for biological proteins, an observation supported in part by structural studies of short, and thus unfolded, peptides. Although intrinsic conformational propensities have been determined experimentally for the common amino acids in short peptides, and estimated from surveys of the protein coil library, the ability of these intrinsic conformational propensities to quantitatively reproduce structural behavior in intrinsically disordered proteins (IDPs), an increasingly important class of proteins in cell function, has thus far proven elusive to establish. Recently, we demonstrated that the sequence dependence of the mean hydrodynamic size of IDPs in water and the impact of heat on the coil dimensions, provide access to both the sequence dependence and thermodynamic energies that are associated with biases for the α and PPII backbone conformations.