Developmental Language Disorder (DLD) is frequent in childhood and may have long-term sequelae. By employing an evidence-based approach, this scoping review aims at identifying (a) early predictors of DLD; (b) the optimal age range for the use of screening and diagnostic tools; (c) effective diagnostic tools in preschool children. We considered systematic reviews, meta-analyses, and primary observational studies with control groups on predictive, sensitivity and specificity values of screening and diagnostic tools and psycholinguistic measures for the assessment of DLD in preschool children. We identified 37 studies, consisting of 10 systematic reviews and 27 primary studies. Delay in gesture production, receptive and/or expressive vocabulary, syntactic comprehension, or word combination up to 30 months emerged as early predictors of DLD, a family history of DLD appeared to be a major risk factor, and low socioeconomic status and environmental input were reported as risk factors with lower predictive power. Optimal time for screening is suggested between age 2 and 3, for diagnosis around age 4. Sumatriptan molecular weight Because of the high variability of sensitivity and specificity values, joint use of standardized and psycholinguistic measures is suggested to increase diagnostic accuracy. Monitoring risk situations and employing caregivers' reports, clinical assessment and multiple linguistic measures are fundamental for an early identification of DLD and timely interventions.Monitoring risk situations and employing caregivers' reports, clinical assessment and multiple linguistic measures are fundamental for an early identification of DLD and timely interventions.People who use crack-cocaine (PWUCC) have numerous vulnerabilities and pose a challenge to health and social assistance services. The exposure to pathogens and risk situations occur differently according to each individual, region and social group. This study identified the presence, genotypes and factors associated with hepatitis E virus (HEV) exposure among a community-recruited cohort of 437 PWUCC in northern Brazil. Epidemiological information was collected through community-based assessments and interviews. Thereafter, blood and fecal samples were collected and tested for HEV using an immunoenzymatic assay, and the genotype was identified by PCR. Logistic regressions were used to identify the risk factors independently associated with exposure to HEV. In total, 79 (18.1%) PWUCC were exposed to HEV 73 (16.7%) for IgG and six for IgG + IgM. HEV RNA was detected in six fecal samples and in two blood samples from PWUCC with IgM + IgG. Subtype 3c was identified in all of the samples. The factors associated with exposure to HEV were low monthly income, unstable housing (e.g., homelessness), crack-cocaine use ≥40 months, and the shared use of crack-cocaine equipment. The current study provides unique initial insights into HEV status and risk factors among PWUCC in a remote area in Brazil, with diverse implications for urgently improved diagnosis, prevention, and treatment intervention needs.Inflammation is a key mechanism for the clearance of infective agents and other inflammatory triggers and is pivotal for the repairing processes of the affected tissues. Inflammation is a multistep process driven by a great number of mediators which regulate specific aspects of the inflammatory response, in agreement with a well-defined chronobiological program. A great number of inflammation-related diseases show a deeply altered immune chronobiology (e.g., COVID-19-related cytokines storm). This aspect highlights the need for a deeper understanding of the inflammatory phenomenon. It is fundamental to study inflammation as a multilevel phenomenon. Of particular interest is the low-grade chronic inflammation, which is an etiological factor of many chronic diseases. Nowadays, the therapeutic approach to low grade chronic inflammation is one of the great challenges of traditional pharmacology. Currently, no drugs specifically designed for the treatment of chronic inflammatory forms are available. Today, bioregulatory systems medicine (BrSM) and low dose medicine (LDM), two pharmacological paradigms grounded in systems medicine, potentially represent new tools for the treatment of inflammation-related diseases. Scientific research has assessed the effectiveness and safety of both these therapeutic approaches, in particular for the management of chronic inflammatory conditions and chronic immunological dysregulations.Glioblastoma extensively infiltrates the brain; despite surgery and aggressive therapies, the prognosis is poor. A multidisciplinary approach combining mathematical, clinical and radiological data has the potential to foster our understanding of glioblastoma evolution in every single patient, with the aim of tailoring therapeutic weapons. In particular, the ultimate goal of biomathematics for cancer is the identification of the most suitable theoretical models and simulation tools, both to describe the biological complexity of carcinogenesis and to predict tumor evolution. In this report, we describe the results of a critical review about different mathematical models in neuro-oncology with their clinical implications. A comprehensive literature search and review for English-language articles concerning mathematical modelling in glioblastoma has been conducted. The review explored the different proposed models, classifying them and indicating the significative advances of each one. Furthermore, we present a specific case of a glioblastoma patient in which our recently proposed innovative mechanical model has been applied. The results of the mathematical models have the potential to provide a relevant benefit for clinicians and, more importantly, they might drive progress towards improving tumor control and patient's prognosis. Further prospective comparative trials, however, are still necessary to prove the impact of mathematical neuro-oncology in clinical practice.Tactile sensors are widely used by the robotics industries over decades to measure force or pressure produced by external stimuli. Piezoelectric-based pressure sensors have intensively been investigated as promising candidates for tactile sensing applications. In contrast, piezoelectric-based pressure sensors are expensive due to their high cost of manufacturing and expensive base materials. Recently, an effect similar to the piezoelectric effect has been identified in non-piezoelectric polymers such as poly(d,l-lactic acid (PDLLA), poly(methyl methacrylate) (PMMA) and polystyrene. Hence investigations were conducted on alternative materials to find their suitability. In this article, we used inexpensive atactic polystyrene (aPS) as the base polymer and fabricated functional fibers using an electrospinning method. Fiber morphologies were studied using a field-emission scanning electron microscope and proposed a unique pressure sensor fabrication method. A fabricated pressure sensor was subjected to different pressures and corresponding electrical and mechanical characteristics were analyzed.