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ObjectiveWith the emergence of the COVID-19 virus, there was a widespread infection rate among college campuses, creating a need to understand the impact of COVID-19 infection on the health and wellbeing of adolescents. The aim of this study was to examine COVID-19 incidence and cardiorespiratory fitness (CRF) among undergraduate students in the 2 years post-COVID-19 pandemic lock-down.ParticipantsParticipants (n = 151) included undergraduate college freshmen students during the 2021–2022 and 2022–2023 academic years.MethodsA series of annual surveys (n = 151) and laboratory measures among a sub-sample of participants (n = 28) were conducted to assess COVID-19 incidence, CRF, anthropometrics, and physical activity (PA).ResultsOver half of participants self-reported COVID-19 infection (59%), “good” or better CRF, a healthy body mass index (BMI), and 25% met PA recommendations. Nearly a quarter, (24%) perceived a negative impact of COVID-19 on their CRF and although not statistically significant, participants who contracted COVID-19 had 46% lower odds of having a positive perception of CRF than those who did not contract COVID-19 before. However, students who were more physically active were more likely to perceive a negative impact of COVID-19 incidence on their CRF (p = 0.035).ConclusionAlthough no relationship was detected between COVID-19 and CRF, those who perceived a negative impact of COVID-19 on their CRF reported engaging in more physical activity.

In evaluation research, "programs" are often conceptualized as clearly bounded, narrow in scope, focused on specific outcomes, using a well-defined linear causal model, and hence, suitable for standard evaluation methods. The evaluation work reported here was carried out in a more challenging context, where large, complex, interwoven systems were targets for change as a means to influence a diffuse array of outcomes. Our evaluation of an NIH-funded program to improve statewide infrastructure for clinical and translational health research ("Advance-CTR") used qualitative data provided by investigators who used the program's services, were funded awardees, or were members of an internal advisory committee (leadership representatives from partnering institutions). We examined perceived barriers to systemic changes to enhance research, as well as how systems have changed due to the Rhode Island Advance-CTR program's efforts, to what degree, and with what effects. Using the causal logic of our program to connect these more distal systemic outcomes to the services and components of Advance-CTR, we discuss the effects this program has had on researchers and their environments, contributing to the development of sustainable programs of research that ultimately improve the health and well-being of our state's residents.

Olive phenolic compounds like hydroxytyrosol (OH-Tyr), tyrosol (Tyr), and their precursors have different health-promoting properties, mainly based on their strong antioxidant capacity. However, their presence in extra-virgin olive oil (EVOO) is scarce since they are primarily contained in the by-products of oil production, such as olive pomace (OP). The aim of this work was to extract and encapsulate OP phenolic compounds into chitosan–tripolyphosphate nanoparticles (NPs) using an ionotropic gelation lyophilization approach to increase their resistance to environmental and chemical stress. NPs resulted in a monodisperse (PDI: 0.21) population of cationic NPs (ζ-potential: 33 mV, size: 229 nm) with an encapsulation efficiency (EE%), expressed as total phenolic content (TPC) and total OH-Tyr + Tyr content, of 64–65%. Mannitol and maltodextrin DE 19 (MD-19) were evaluated as lyoprotectants to counteract irreversible NP aggregation during lyophilization. The NP powder freeze dried using 0.7% of MD-19 showed the best performance, returning a monodispersed population of particles after rehydration. The antioxidant capacity of the obtained NPs was confirmed both in cell-free assays and in a THP-1 cell model of oxidative stress. This method represents a promising way to deliver health-promoting olive phenols for nutraceutical purposes and, hence, to valorize otherwise wasted by-products.

This study conducts a comprehensive analysis of deep reinforcement learning (DRL) algorithms applied to supply chain inventory management (SCIM), which consists of a sequential decision-making problem focussed on determining the optimal quantity of products to produce and ship across multiple capacitated local warehouses over a specific time horizon. In detail, we formulate the problem as a Markov decision process for a divergent two-echelon inventory control system characterised by stochastic and seasonal demand, also presenting a balanced allocation rule designed to prevent backorders in the first echelon. Through numerical experiments, we evaluate the performance of state-of-the-art DRL algorithms and static inventory policies in terms of both cost minimisation and training time while varying the number of local warehouses and product types and the length of replenishment lead times. Our results reveal that the Proximal Policy Optimization algorithm consistently outperforms other algorithms across all experiments, proving to be a robust method for tackling the SCIM problem. Furthermore, the (s, Q)-policy stands as a solid alternative, offering a compromise in performance and computational efficiency. Lastly, this study presents an open-source software library that provides a customisable simulation environment for addressing the SCIM problem, utilising a wide range of DRL algorithms and static inventory policies. [ABSTRACT FROM AUTHOR]

Systemic lupus erythematosus (SLE, lupus) is a debilitating, multisystem autoimmune disease that can affect any organ in the body. The disease is characterized by circulating autoantibodies that accumulate in organs and tissues, which triggers an inflammatory response that can cause permanent damage leading to significant morbidity and mortality. Lyn, a member of the Src family of non-receptor protein tyrosine kinases, is highly implicated in SLE as remarkably both mice lacking Lyn or expressing a gain-of-function mutation in Lyn develop spontaneous lupus-like disease due to altered signaling in B lymphocytes and myeloid cells, suggesting its expression or activation state plays a critical role in maintaining tolerance. The past 30 years of research has begun to elucidate the role of Lyn in a duplicitous signaling network of activating and inhibitory immunoreceptors and related targets, including interactions with the interferon regulatory factor family in the toll-like receptor pathway. Gain-of-function mutations in Lyn have now been identified in human cases and like mouse models, cause severe systemic autoinflammation. Studies of Lyn in SLE patients have presented mixed findings, which may reflect the heterogeneity of disease processes in SLE, with impairment or enhancement in Lyn function affecting subsets of SLE patients that may be a means of stratification. In this review, we present an overview of the phosphorylation and protein-binding targets of Lyn in B lymphocytes and myeloid cells, highlighting the structural domains of the protein that are involved in its function, and provide an update on studies of Lyn in SLE patients.

The Italian National Strategy for Sustainable Development plays an important role in the national implementation of the 17 Goals for sustainable development set globally through the 2030 Agenda of the United Nations. The achievement of such goals in Italy is linked to the strategic choices and objectives established at the national level. The purpose of this work is to monitor the performance of the 20 Italian regions in 4 of the 5 areas of the Agenda (People, Planet, Prosperity, Peace) over a period of time ranging from the implementation of the National Strategy to the post-pandemic. To do this, a set of representative indicators was created and a geographical sustainability assessment tool (SSAM) was used, which operates through a multicriteria analysis model perfectly integrated into a GIS environment. The results showed a strong regional variability and a radicalized North-South gap. Moreover, the monitoring between the different years (2017-2019-2021) showed the initially positive impact of the strategy, mainly due to the Planet dimension, but also the negative one that COVID-19 caused to all the regions, with different intensity depending on the dimensions considered.

Background: This study was designed to assess the diagnostic utility for FIP of cytology, protein measurement and RT-PCR for feline coronaviruses (FCoV) on aqueous humor (AH), since little information is currently available. Methods: AH samples (n = 85) were collected post-mortem from 13 cats with effusive FIP (E-FIP), 15 with non-effusive FIP (NE-FIP) and 16 without FIP, to perform cytology (n = 83) and RT-PCR (n = 66) and to calculate their sensitivity, specificity and positive and negative likelihood ratios (LR+ and LR−). The protein concentration was measured on 80 fluids. Results: The proportion of RT-PCR positive samples did not differ among groups, while positive cytology was more frequent in samples with FIP (p = 0.042) or positive RT-PCR (p = 0.007). Compared with other groups, the protein concentration was higher in samples with NE-FIP (p = 0.017), positive RT-PCR (p = 0.005) or positive cytology (p < 0.001). The specificity of cytology together with RT-PCR, cytology alone, RT-PCR alone and cytological proteinaceous background were 90.0%, 84.6%, 70.0%, 61.5%, and the LRs 3.48, 2.65, 1.83, 1.64, respectively. However, their sensitivities were low (34.8–63.0%) and their LR− high (0.60–0.72). Conclusions: Based on the LR+, cytology and/or RT-PCR may support the diagnosis when the pre-test probability of FIP is high. The concentration of intraocular protein is a promising marker, especially in NE-FIP.