The network of commodity risk

In this paper, we investigate the interconnections among and within the Energy, Agricultural, and Metal commodities, operating in a risk management framework with a twofold goal. First, we estimate the Value-at-Risk (VaR) employing GARCH and Markov-switching GARCH models with different error term distributions. The use of such models allows us to take into account well-known stylized facts shown in the time series of commodities as well as possible regime changes in their conditional variance dynamics. We rely on backtesting procedures to select the best model for each commodity. Second, we estimate the sparse Gaussian Graphical model of commodities exploiting the Graphical LASSO (GLASSO) methodology to detect the most relevant conditional dependence structure among and within the sectors. A novel feature of our framework is that GLASSO estimation is achieved exploring the precision matrix of the multivariate Gaussian distribution obtained using a Gaussian copula with marginals given by the residuals of the aforementioned selected models. We apply our approach to the sample of twenty-four series of commodity futures prices over the years 2005–2022. We find that Soybean Oil, Cotton, and Coffee represent the major sources of propagation of financial distress in commodity markets while Gold, Natural Gas UK, and Heating Oil are depicted as safe-haven commodities. The impact of Covid-19 is reflected in increased heterogeneity, as captured by the strongest relationships between commodities belonging to the same commodity sector and by weakened inter-sectorial connections. This finding suggests that connectedness does not always increase in response to crisis events

Kiri Karl Morgensternile, Venetiis

http://tartu.ester.ee/record=b1819394~S1*es

Design, Preparation, and Characterization of Thermoresponsive Hybrid Nanogels Using a Novel Ulvan-Acrylate Crosslinker as Potential Carriers for Protein Encapsulation

The aim of the present study is the design and development of thermoresponsive nanogels based on ulvan, a sulphated heteropolysaccharide of algal origins with unique biological and chemical properties. Hybrid nanogels are successfully synthesized by means of UV-initiated radical copolymerization of N-vinylcaprolactam with an ulvan derivate as a novel crosslinker. In nanogels, the ulvan-grafted poly(N-vinylcaprolactam) chains represent the thermoresponsive component. The most promising candidates, selected after a thorough physical-chemical characterization of nanogels in terms of size and responsivity to thermal variation at physiological conditions, are loaded with bovine serum albumin (BSA) as model bioactive compound. The developed nanogels display BAS loading efficiency values similar to those obtained by using synthetic crosslinkers, and thus indicating the suitability of the developed ulvan-acrylate to act as novel macromolecular crosslinker for thermoresponsive nanogels preparation

PRESENCE OF TRICHINELLA BRITOVI IN WILD BOAR IN THE MARCHE REGION REGULARLY SLAUGHTERED

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The Impact of Highly Effective Treatment in Pediatric-Onset Multiple Sclerosis: A Case Series

Pediatric-onset multiple sclerosis (POMS) is characterized by high inflammatory disease activity. Our aim was to describe the treatment sequencing and report the impact highly effective disease-modifying treatment (HET) had on disease activity

Relationship between immune response to SARS-CoV2 vaccines and development of breakthrough infection in solid organ transplant recipients: the CONTRAST cohort

Background: SARS-CoV-2 vaccination in solid organ transplant (SOT) is associated with poorer antibody response (AbR) compared to non-SOT recipients. However, its impact on the risk of breakthrough infection (BI) should yet be assessed. Methods: Single-center prospective longitudinal cohort study enrolling adult SOT recipients who received SARS-CoV2 vaccination during 1-year period from February 2021, and followed-up to April 30th 2022. Patients were tested for AbR at multiple timepoints. Primary endpoint was BI (laboratory confirmed SARS-CoV2 infection ≥14 days after 2nd dose). Immunization (positive AbR) was considered an intermediate state between vaccination and BI. Probabilities of being in vaccination, immunization and BI states were obtained for each type of graft and vaccination sequence with multistate survival analysis, then multivariable logistic regression was performed to analyse the risk of BI in AbR levels. Results: 614 SOT (275 kidney, 163 liver, 137 heart, 39 lung) recipients were included. Most patients (84.7%) received three vaccine doses, the first two consisted of BNT162b2 and mRNA-1273 in 73.5% and 26.5% of cases, respectively; while at the third dose mRNA-1273 was administered in 59.8% of patients. Overall, 75.4% of patients reached immunization and 18.4% developed BI. Heart transplant recipients showed lowest probability of immunization (0.418) and highest of BI (0.323), all-mRNA-1273 vaccine-sequence showed higher probability of immunization (0.732) and lowest of BI (0.098). Risk of BI was higher for non-high-level AbR, younger age and shorter time from transplant. Conclusions: SOT patients with non-high-level AbR, shorter time from transplantation, and heart recipients are at highest risk of BI

SARS-CoV-2 vaccination modelling for safe surgery to save lives: Data from an international prospective cohort study

Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population