Suggestive evidence of a multi-cytokine resistin pathway in humans and its role on cardiovascular events in high-risk individuals

In cells and tissues resistin affects IL-1β, IL-6, IL-8, IL-12 and TNF-α expression, thus suggesting the existence of a multi-cytokine "resistin pathway". We investigated whether such pathway does exist in humans and, if so, if it is associated with cardiovascular risk factors and with major adverse cardiovascular events (MACE). Serum cytokines were measured in 280 healthy subjects from the Gargano Study 2 (GS2) whose BMI, waist circumference, HOMA IR, triglycerides, HDL-cholesterol, systolic and diastolic blood pressure data were available and in 353 patients with type 2 diabetes and coronary artery disease from the Gargano Heart Study (GHS)-prospective design (follow-up 5.4 ± 2.5 years; 71 MACE). In GS2, cytokines mRNA levels in white blood cells were also measured. In GS2, resistin mRNA was correlated with all cytokines expression (all p < 0.001), but IL-12B. Consistently, serum resistin was correlated with all serum cytokines (all p < 0.001), but IL-12. Expression (eRPS) and serum (sRPS) resistin pathway scores (excluding IL-12) were each other correlated (p < 0.001) and both associated with cardiovascular risk factors (all p < 0.01). In GHS, sRPS was independently associated with MACE (HR = 1.44, 95% CI = 1.10-1.90). Our data indicate the existence of a resistin pathway, which is associated with cardiovascular risk factors and which strongly and independently predicts MACE

Autism Spectrum Disorders: Is Mesenchymal Stem Cell Personalized Therapy the Future?

Autism and autism spectrum disorders (ASDs) are heterogeneous neurodevelopmental disorders. They are enigmatic conditions that have their origins in the interaction of genes and environmental factors. ASDs are characterized by dysfunctions in social interaction and communication skills, in addition to repetitive and stereotypic verbal and nonverbal behaviours. Immune dysfunction has been confirmed with autistic children. There are no defined mechanisms of pathogenesis or curative therapy presently available. Indeed, ASDs are still untreatable. Available treatments for autism can be divided into behavioural, nutritional, and medical approaches, although no defined standard approach exists. Nowadays, stem cell therapy represents the great promise for the future of molecular medicine. Among the stem cell population, mesenchymal stem cells (MSCs) show probably best potential good results in medical research. Due to the particular immune and neural dysregulation observed in ASDs, mesenchymal stem cell transplantation could offer a unique tool to provide better resolution for this disease

Engineering the Selectivity of the DNA-SWCNT Sensor

Single-walled carbon nanotubes (SWCNTs) demonstrate a unique combination of optical, chemical, and physical properties that render them suitable for a variety of sensing applications. Their photostable near-infrared (nIR) fluorescence emissions are highly sensitive to perturbations in the surrounding SWCNT environment, enabling optical sensors with single-molecule detection limits. Despite these immanent advantages, SWCNTs lack the inherent molecular recognition capabilities required for selective sensing applications. One approach to tuning sensor selectivity is to engineer synthetic and biological wrappings that cover the nanotube's surface in a manner that limits chemical access to the surface to specific target analytes. Among the numerous possible wrappings, deoxyribonucleic acid (DNA) has emerged as the most studied polymeric wrapping. In addition to the sequence-dependent tunability DNA offers in engineering selectivity, DNA assumes a peculiar helical wrapping conformation along the SWCNT surface that has been the focus of many experimental and computational studies. In this review, we summarize some of the major findings in the field, focusing on the underlying molecular interactions responsible for the conformational and molecular recognition elements of the wrapping. Special focus is given to characterizing the nucleotide binding affinity, DNA sequence dependency, DNA length variation, SWCNT chirality, and sugar backbone (RNA vs. DNA) contributions to the wrapping conformation and SWCNT fluorescence. This article concludes with an assessment of the latest DNA-SWCNT-based sensing platforms used for the selective, single- and multi-modal detection of target analytes

Machine learning-based ability to classify psychosis and early stages of disease through parenting and attachment-related variables is associated with social cognition

Background: Recent views posited that negative parenting and attachment insecurity can be considered as general environmental factors of vulnerability for psychosis, specifically for individuals diagnosed with psychosis (PSY). Furthermore, evidence highlighted a tight relationship between attachment style and social cognition abilities, a key PSY behavioral phenotype. The aim of this study is to generate a machine learning algorithm based on the perceived quality of parenting and attachment style-related features to discriminate between PSY and healthy controls (HC) and to investigate its ability to track PSY early stages and risk conditions, as well as its association with social cognition performance. Methods: Perceived maternal and paternal parenting, as well as attachment anxiety and avoidance scores, were trained to separate 71 HC from 34 PSY (20 individuals diagnosed with schizophrenia + 14 diagnosed with bipolar disorder with psychotic manifestations) using support vector classification and repeated nested cross-validation. We then validated this model on independent datasets including individuals at the early stages of disease (ESD, i.e. first episode of psychosis or depression, or at-risk mental state for psychosis) and with familial high risk for PSY (FHR, i.e. having a first-degree relative suffering from psychosis). Then, we performed factorial analyses to test the group x classification rate interaction on emotion perception, social inference and managing of emotions abilities. Results: The perceived parenting and attachment-based machine learning model discriminated PSY from HC with a Balanced Accuracy (BAC) of 72.2%. Slightly lower classification performance was measured in the ESD sample (HC-ESD BAC = 63.5%), while the model could not discriminate between FHR and HC (BAC = 44.2%). We observed a significant group x classification interaction in PSY and HC from the discovery sample on emotion perception and on the ability to manage emotions (both p = 0.02). The interaction on managing of emotion abilities was replicated in the ESD and HC validation sample (p = 0.03). Conclusion: Our results suggest that parenting and attachment-related variables bear significant classification power when applied to both PSY and its early stages and are associated with variability in emotion processing. These variables could therefore be useful in psychosis early recognition programs aimed at softening the psychosis-associated disability

Mitogen-activated kinase kinase kinase 1 inhibits hedgehog signaling and medulloblastoma growth through GLI1 phosphorylation

The aberrant activation of hedgehog (HH) signaling is a leading cause of the development of medulloblastoma, a pediatric tumor of the cerebellum. The FDA‑approved HH inhibitor, Vismodegib, which targets the transmembrane transducer SMO, has shown limited efficacy in patients with medulloblastoma, due to compensatory mechanisms that maintain an active HH‑GLI signaling status. Thus, the identification of novel actionable mechanisms, directly affecting the activity of the HH‑regulated GLI transcription factors is an important goal for these malignancies. In this study, using gene expression and reporter assays, combined with biochemical and cellular analyses, we demonstrate that mitogen‑activated kinase kinase kinase 1 (MEKK1), the most upstream kinase of the mitogen‑activated protein kinase (MAPK) phosphorylation modules, suppresses HH signaling by associating and phosphorylating GLI1, the most potent HH‑regulated transcription factor. Phosphorylation occurred at multiple residues in the C‑terminal region of GLI1 and was followed by an increased association with the cytoplasmic proteins 14‑3‑3. Of note, the enforced expression of MEKK1 or the exposure of medulloblastoma cells to the MEKK1 activator, Nocodazole, resulted in a marked inhibitory effect on GLI1 activity and tumor cell proliferation and viability. Taken together, the results of this study shed light on a novel regulatory mechanism of HH signaling, with potentially relevant implications in cancer therapy

Vitamin D as Modulator of Drug Concentrations: A Study on Two Italian Cohorts of People Living with HIV Administered with Efavirenz

To date, vitamin D seems to have a significant role in affecting the prevention and immunomodulation in COVID-19 disease. Nevertheless, it is important to highlight that this pro-hormone has other several activities, such as affecting drug concentrations, since it regulates the expression of cytochrome P450 (CYP) genes. Efavirenz (EFV) pharmacokinetics is influenced by CYPs, but no data are available in the literature concerning the association among vitamin D levels, seasonality (which affects vitamin D concentrations) and EFV plasma levels. For this reason, the aim of this study was to evaluate the effect of 25-hydroxy vitamin D (25(OH)D3) levels on EFV plasma concentrations in different seasons. We quantified 25(OH)D3 by using chemiluminescence immunoassay, whereas EFV plasma concentrations were quantified with the HPLC–PDA method. A total of 316 patients were enrolled in Turin and Rome. Overall, 25(OH)D3levels resulted in being inversely correlated with EFV concentrations. Some patients with EFV levels higher than 4000 ng/mL showed a deficient 25(OH)D3 concentration in Turin and Rome cohorts and together. EFV concentrations were different in patients without vitamin D supplementation, whereas, for vitamin D-administered individuals, no difference in EFV exposure was present. Concerning seasonality, EFV concentrations were associated with 25(OH)D3 deficiency only in winter and in spring, whereas a significant influence was highlighted for 25(OH)D3 stratification for deficient, insufficient and sufficient values in winter, spring and summer. A strong and inverse association between 25(OH)D3and EFV plasma concentrations was suggested. These data suggest that vitamin D is able to affect drug exposure in different seasons; thus, the achievement of the clinical outcome could be improved by also considering this pro-hormone

Pregnancy and COVID-19: The Possible Contribution of Vitamin D

Background: Vitamin D deficiency has been associated with the severity of COVID-19. The role of vitamin D in pregnant women with COVID-19 has been poorly investigated to date. The aim of this study was to evaluate the influence of vitamin D in affecting some clinical features in pregnancy between SARS-CoV-2 positive and negative patients. Methods: Vitamin D pathway related polymorphisms and 25-hydroxyvitamin D levels were quantified in pregnant women followed from the first to the third trimester of pregnancy. Vitamin D deficiency was considered with values ≤ 30 ng/mL. Results: In total, 160 women were enrolled: 23 resulted positive for at least one SARS-CoV-2 related test (molecular swab or antibody tests). Vitamin D-associated polymorphisms were able to affect vitamin D levels in SARS-CoV-2 negative and positive subjects: remarkably, all the VDR TaqICC genotype patients were negative for SARS-CoV-2. In a sub-population (118 patients), vitamin D levels correlated with pregnancy-related factors, such as alpha-fetoprotein levels. Third-trimester vitamin D levels were lower in preterm births compared to full-term pregnancy: this trend was highlighted for SARS-CoV-2 positive patients. Conclusions: This is the first study demonstrating a role of vitamin D in affecting the clinical characteristics of pregnant women during the COVID-19 era. Further studies in larger and different cohorts of patients are required to confirm these findings