Illegal Substance Use among Italian High School Students: Trends over 11 Years (1999–2009)

Purpose: To monitor changes in habits in drug use among Italian high school students. Methods: Cross-sectional European School Survey Project on Alcohol and Other Drugs (ESPAD) carried out in Italy annually for 11 years (1999-2009) with representative samples of youth attending high school. The sample size considered ranges from 15,752 to 41,365 students and response rate ranged from 85.5% to 98.6%. Data were analyzed to obtain measures of life-time prevalence (LT), use in the last year (LY), use in the last 30 days (LM), frequent use. Comparisons utilized difference in proportion tests. Tests for linear trends in proportion were performed using the Royston p trend test. Results: When the time-averaged value was considered, cannabis (30% LT) was the most, and heroin the least (2%) frequently used, with cocaine (5%), hallucinogens (2%) and stimulants (2%) in between. A clear gender gap is evident for all drugs, more obvious for hallucinogens (average M/F LY prevalence ratio 2, range 1.7-2.4, p,0.05), less for cannabis (average M/F LY prevalence ratio 1.3, range 1.2-1.5, p,0.05). Data shows a change in trend between 2005 and 2008; in 2006 the trend for cannabis use and availability dropped and the price rose, while from 2005 cocaine and stimulant use prevalence showed a substantial increase and the price went down. After 2008 use of all substances seems to have decreased. Conclusions: Drug use is widespread among students in Italy, with cannabis being the most and heroin the least prevalent. Girls are less vulnerable than boys to illegal drug use. In recent years, a decrease in heroin use is overbalanced by a marked rise in hallucinogen and stimulant use.-

Prognostic impact of vitamin B6 metabolism in lung cancer

Patients with non-small cell lung cancer (NSCLC) are routinely treated with cytotoxic agents such as cisplatin. Through a genome-wide siRNA-based screen, we identified vitamin B6 metabolism as a central regulator of cisplatin responses in vitro and in vivo. By aggravating a bioenergetic catastrophe that involves the depletion of intracellular glutathione, vitamin B6 exacerbates cisplatin-mediated DNA damage, thus sensitizing a large panel of cancer cell lines to apoptosis. Moreover, vitamin B6 sensitizes cancer cells to apoptosis induction by distinct types of physical and chemical stress, including multiple chemotherapeutics. This effect requires pyridoxal kinase (PDXK), the enzyme that generates the bioactive form of vitamin B6. In line with a general role of vitamin B6 in stress responses, low PDXK expression levels were found to be associated with poor disease outcome in two independent cohorts of patients with NSCLC. These results indicate that PDXK expression levels constitute a biomarker for risk stratification among patients with NSCLC.publishedVersio

Abnormal fatty acid metabolism is a core component of spinal muscular atrophy

Objective: Spinal muscular atrophy (SMA) is an inherited neuromuscular disorder leading to paralysis and subsequent death in young children. Initially considered a motor neuron disease, extra-neuronal involvement is increasingly recognized. The primary goal of this study was to investigate alterations in lipid metabolism in SMA patients and mouse models of the disease. Methods: We analyzed clinical data collected from a large cohort of pediatric SMA type I-III patients as well as SMA type I liver necropsy data. In parallel, we performed histology, lipid analysis, and transcript profiling in mouse models of SMA. Results: We identify an increased susceptibility to developing dyslipidemia in a cohort of 72 SMA patients and liver steatosis in pathological samples. Similarly, fatty acid metabolic abnormalities were present in all SMA mouse models studied. Specifically, Smn2B/- mice displayed elevated hepatic triglycerides and dyslipidemia, resembling non-alcoholic fatty liver disease (NAFLD). Interestingly, this phenotype appeared prior to denervation. Interpretation: This work highlights metabolic abnormalities as an important feature of SMA, suggesting implementation of nutritional and screening guidelines in patients, as such defects are likely to increase metabolic distress and cardiovascular risk. This study emphasizes the need for a systemic therapeutic approach to ensure maximal benefits for all SMA patients throughout their life

Enantiomeric and Diastereomeric Self-Assembled Multivalent Nanostructures : Understanding the Effects of Chirality on Binding to Polyanionic Heparin and DNA

A family of four self-assembling lipopeptides containing Ala-Lys peptides attached to a C16 aliphatic chain were synthesised. These compounds form two enantiomeric pairs that bear a diastereomeric relationship to one another (C16-l-Ala-l-Lys/C16-d-Ala-d-Lys) and (C16-d-Ala-l-Lys/C16-l-Ala-d-Lys). These diastereomeric pairs have very different critical micelle concentrations (CMCs). The self-assembled multivalent (SAMul) systems bind biological polyanions as a result of the cationic lysine groups on their surfaces. For heparin binding, there was no significant enantioselectivity, but there was a binding preference for the diastereomeric assemblies with lower CMCs. Conversely, for DNA binding, there was significant enantioselectivity for systems displaying d-lysine ligands, with a further slight preference for attachment to l-alanine, with the CMC being irrelevant

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

Racial differences in systemic sclerosis disease presentation: a European Scleroderma Trials and Research group study

Objectives. Racial factors play a significant role in SSc. We evaluated differences in SSc presentations between white patients (WP), Asian patients (AP) and black patients (BP) and analysed the effects of geographical locations.Methods. SSc characteristics of patients from the EUSTAR cohort were cross-sectionally compared across racial groups using survival and multiple logistic regression analyses.Results. The study included 9162 WP, 341 AP and 181 BP. AP developed the first non-RP feature faster than WP but slower than BP. AP were less frequently anti-centromere (ACA; odds ratio (OR) = 0.4, P < 0.001) and more frequently anti-topoisomerase-I autoantibodies (ATA) positive (OR = 1.2, P = 0.068), while BP were less likely to be ACA and ATA positive than were WP [OR(ACA) = 0.3, P < 0.001; OR(ATA) = 0.5, P = 0.020]. AP had less often (OR = 0.7, P = 0.06) and BP more often (OR = 2.7, P < 0.001) diffuse skin involvement than had WP.AP and BP were more likely to have pulmonary hypertension [OR(AP) = 2.6, P < 0.001; OR(BP) = 2.7, P = 0.03 vs WP] and a reduced forced vital capacity [OR(AP) = 2.5, P < 0.001; OR(BP) = 2.4, P < 0.004] than were WP. AP more often had an impaired diffusing capacity of the lung than had BP and WP [OR(AP vs BP) = 1.9, P = 0.038; OR(AP vs WP) = 2.4, P < 0.001]. After RP onset, AP and BP had a higher hazard to die than had WP [hazard ratio (HR) (AP) = 1.6, P = 0.011; HR(BP) = 2.1, P < 0.001].Conclusion. Compared with WP, and mostly independent of geographical location, AP have a faster and earlier disease onset with high prevalences of ATA, pulmonary hypertension and forced vital capacity impairment and higher mortality. BP had the fastest disease onset, a high prevalence of diffuse skin involvement and nominally the highest mortality

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Patient and Patient Group Engagement in Cancer Clinical Trials: A Stakeholder Charter

Background—to guide the implementation of patient centricity and engagement in cancer clinical trials (CTs) and to operationalize the Canadianized version of the Clinical Trials Transformation Initiative (C-CTTI) model, the development of a charter was identified by cancer CT stakeholders. Methods—the Canadian Cancer Trial Stakeholder Charter (the Charter) was initiated by Colorectal Cancer Canada (CCC) and developed via the—1—formation of an inclusive working group (WG) that drafted the document using recommendations collected during the development of the C-CTTI model; 2—socialization of the draft Charter to solicit feedback from cancer CT stakeholders, including those who attended the 2019 CCC Conference; and 3—incorporation of stakeholders’ feedback and finalization of the Charter by the WG. Results—the Charter was built around five guiding principles—1—patient centricity; 2—commitment to education and training; 3—collaboration as equal and independent partners in research; 4—transparency and accountability; and 5—high standards in data collection integrity and honesty. These principles led to the Charter’s five tenets, which stipulate stakeholder commitments, aiming to make CTs accessible to all patients, improve the design and implementation of CTs to benefit patients, expand recruitment and retention of patients in CTs, and further advance cancer research and treatment. Conclusions—the Charter is intended to integrate the patient voice into the Canadian cancer CT continuum. The next phases of the C-CTTI model include the adoption and implementation of the Charter, the establishment of a patient group training program, and the development of real-world evidence/real-world data methodologies