The risk stratification of adverse neonatal outcomes in women with gestational diabetes (STRONG) study

Aims: To assess the risk of adverse neonatal outcomes in women with gestational diabetes (GDM) by identifying subgroups of women at higher risk to recognize the characteristics most associated with an excess of risk. Methods: Observational, retrospective, multicenter study involving consecutive women with GDM. To identify distinct and homogeneous subgroups of women at a higher risk, the RECursive Partitioning and AMalgamation (RECPAM) method was used. Overall, 2736 pregnancies complicated by GDM were analyzed. The main outcome measure was the occurrence of adverse neonatal outcomes in pregnancies complicated by GDM. Results: Among study participants (median age 36.8 years, pre-gestational BMI 24.8 kg/m2), six miscarriages, one neonatal death, but no maternal death was recorded. The occurrence of the cumulative adverse outcome (OR 2.48, 95% CI 1.59–3.87), large for gestational age (OR 3.99, 95% CI 2.40–6.63), fetal malformation (OR 2.66, 95% CI 1.00–7.18), and respiratory distress (OR 4.33, 95% CI 1.33–14.12) was associated with previous macrosomia. Large for gestational age was also associated with obesity (OR 1.46, 95% CI 1.00–2.15). Small for gestational age was associated with first trimester glucose levels (OR 1.96, 95% CI 1.04–3.69). Neonatal hypoglycemia was associated with overweight (OR 1.52, 95% CI 1.02–2.27) and obesity (OR 1.62, 95% CI 1.04–2.51). The RECPAM analysis identified high-risk subgroups mainly characterized by high pre-pregnancy BMI (OR 1.68, 95% CI 1.21–2.33 for obese; OR 1.38 95% CI 1.03–1.87 for overweight). Conclusions: A deep investigation on the factors associated with adverse neonatal outcomes requires a risk stratification. In particular, great attention must be paid to the prevention and treatment of obesity

Preliminary results on the long term operation of RPCs with eco-friendly gas mixtures under irradiation at the CERN Gamma Irradiation Facility

Since 2019 a collaboration between researchers from various institutes and experiments (i.e. ATLAS, CMS, ALICE, LHCb/SHiP and the CERN EP-DT group), has been operating several RPCs with diverse electronics, gas gap thicknesses and detector layouts at the CERN Gamma Irradiation Facility (GIF++). The studies aim at assessing the performance of RPCs when filled with new eco-friendly gas mixtures in avalanche mode and in view of evaluating possible ageing effects after long high background irradiation periods, e.g. High-Luminosity LHC phase. This challenging research is also part of a task of the European AidaInnova project. A promising eco-friendly gas identified for RPC operation is the tetrafluoruropropene (C$_{3}$H$_{2}$F$_{4}$, commercially known as HFO-1234ze) that has been studied at the CERN GIF++ in combination with different percentages of CO$_2$. Between the end of 2021 and 2022 several beam tests have been carried out to establish the performance of RPCs operated with such mixtures before starting the irradiation campaign for the ageing study. Results of these tests for different RPCs layouts and different gas mixtures, under increasing background rates are presented here, together with the preliminary outcome of the detector ageing tests

High-rate tests on Resistive Plate Chambers operated with eco-friendly gas mixtures

Results obtained by the RPC ECOgas@GIF++ Collaboration, using Resistive Plate Chambers operated with new, eco-friendly gas mixtures, based on Tetrafluoropropene and carbon dioxide, are shown and discussed in this paper. Tests aimed to assess the performance of this kind of detectors in high-irradiation conditions, analogous to the ones foreseen for the coming years at the Large Hadron Collider experiments, were performed, and demonstrate a performance basically similar to the one obtained with the gas mixtures currently in use, based on Tetrafluoroethane, which is being progressively phased out for its possible contribution to the greenhouse effect. Long term aging tests are also being carried out, with the goal to demonstrate the possibility of using these eco-friendly gas mixtures during the whole High Luminosity phase of the Large Hadron Collider.Comment: Submitted to European Physical Journal C on October 24, 2023, 15 pages, 14 figure

Proteins of Leishmania (Viannia) shawi confer protection associated with Th1 immune response and memory generation

<p>Abstract</p> <p>Background</p> <p><it>Leishmania (Viannia) shawi </it>parasite was first characterized in 1989. Recently the protective effects of soluble leishmanial antigen (SLA) from <it>L. (V.) shawi </it>promastigotes were demonstrated using BALB/c mice, the susceptibility model for this parasite. In order to identify protective fractions, SLA was fractionated by reverse phase HPLC and five antigenic fractions were obtained.</p> <p>Methods</p> <p>F1 fraction was purified from L. (V.) shawi parasite extract by reverse phase HPLC. BALB/c mice were immunized once a week for two consecutive weeks by subcutaneous routes in the rump, using 25 μg of F1. After 1 and 16 weeks of last immunization, groups were challenged in the footpad with L. (V.) shawi promastigotes. After 2 months, those same mice were sacrificed and parasite burden, cellular and humoral immune responses were evaluated.</p> <p>Results</p> <p>The F1 fraction induced a high degree of protection associated with an increase in IFN-γ, a decrease in IL-4, increased cell proliferation and activation of CD8⁺T lymphocytes. Long-term protection was acquired in F1-immunized mice, associated with increased CD4⁺central memory T lymphocytes and activation of both CD4⁺and CD8⁺T cells. In addition, F1-immunized groups showed an increase in IgG2a levels.</p> <p>Conclusions</p> <p>The inductor capability of antigens to generate memory lymphocytes that can proliferate and secrete beneficial cytokines upon infection could be an important factor in the development of vaccine candidates against American Tegumentary Leishmaniasis.</p

Burden and risk factors for Pseudomonas aeruginosa community-acquired pneumonia:a Multinational Point Prevalence Study of Hospitalised Patients

Pseudornonas aeruginosa is a challenging bacterium to treat due to its intrinsic resistance to the antibiotics used most frequently in patients with community-acquired pneumonia (CAP). Data about the global burden and risk factors associated with P. aeruginosa-CAP are limited. We assessed the multinational burden and specific risk factors associated with P. aeruginosa-CAP. We enrolled 3193 patients in 54 countries with confirmed diagnosis of CAP who underwent microbiological testing at admission. Prevalence was calculated according to the identification of P. aeruginosa. Logistic regression analysis was used to identify risk factors for antibiotic-susceptible and antibiotic-resistant P. aeruginosa-CAP. The prevalence of P. aeruginosa and antibiotic-resistant P. aeruginosa-CAP was 4.2% and 2.0%, respectively. The rate of P. aeruginosa CAP in patients with prior infection/colonisation due to P. aeruginosa and at least one of the three independently associated chronic lung diseases (i.e. tracheostomy, bronchiectasis and/or very severe chronic obstructive pulmonary disease) was 67%. In contrast, the rate of P. aeruginosa-CAP was 2% in patients without prior P. aeruginosa infection/colonisation and none of the selected chronic lung diseases. The multinational prevalence of P. aeruginosa-CAP is low. The risk factors identified in this study may guide healthcare professionals in deciding empirical antibiotic coverage for CAP patients

Single-cell analysis tools for drug discovery and development

The genetic, functional or compositional heterogeneity of healthy and diseased tissues presents major challenges in drug discovery and development. Such heterogeneity hinders the design of accurate disease models and can confound the interpretation of biomarker levels and of patient responses to specific therapies. The complex nature of virtually all tissues has motivated the development of tools for single-cell genomic, transcriptomic and multiplex proteomic analyses. Here, we review these tools and assess their advantages and limitations. Emerging applications of single cell analysis tools in drug discovery and development, particularly in the field of oncology, are discussed