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This study evaluates the effects of two learning paradigms, intensive vs. baseline, on the posttraumatic acquisition of a water maze based place learning task. Rats were subjected either to a control operation (Sham) or to a fimbria-fornix (FF) transection, which renders the hippocampus dysfunctional and disrupts the acquisition of allocentric place learning. All animals were administered 30 post-lesion acquisition sessions, which spanned either 10 or 30days. The acquisition period was followed by a 7day pause after which a retention probe was administered. The lesioned animals were divided into 3 groups: i) Baseline Acquisition Paradigm (BAP) once daily for 30days starting 1week post-surgery; ii) Early Intensive Acquisition Paradigm (EIAP) 3 times daily for 10days starting 1week post-surgery; and iii) Late Intensive Acquisition Paradigm (LIAP) 3 times daily for 10days starting 3weeks post-surgery. Within the control animals, one group followed the schedule of BAP, and one group followed the schedule of Intensive Acquisition Paradigm (IAP). All lesioned animals showed an impaired task acquisition. LIAP was beneficial in FF animals, in that it led to a better acquisition of the place learning task than the two other acquisition paradigms. The FF/EIAP group did not show improved acquisition compared to the FF/BAP group. The control animals were not differentially affected by the two learning schedules. The findings have implications for cognitive rehabilitation after brain injury and support the assumption that intensive treatment can lead to an improved learning, even when the neural structures underlying such a process are compromised. However, the timing of intensive treatment needs to be considered further., (Copyright © 2012 Elsevier B.V. All rights reserved.)

Background: Urinary mercury concentrations are used in research exploring mercury exposure. Some theorists have proposed that autism is caused by mercury toxicity. We set out to test whether mercury concentrations in the urine of children with autism were significantly increased or decreased compared to controls or siblings., Methods: Blinded cohort analyses were carried out on the urine of 56 children with autism spectrum disorders (ASD) compared to their siblings (n = 42) and a control sample of children without ASD in mainstream (n = 121) and special schools (n = 34)., Results: There were no statistically significant differences in creatinine levels, in uncorrected urinary mercury levels or in levels of mercury corrected for creatinine, whether or not the analysis is controlled for age, gender and amalgam fillings., Conclusions: This study lends no support for the hypothesis of differences in urinary mercury excretion in children with autism compared to other groups. Some of the results, however, do suggest further research in the area may be warranted to replicate this in a larger group and with clear measurement of potential confounding factors.

Cancer testis antigens exhibit physiological expression within germ cells and are frequently expressed in malignant tissue. Interestingly, immunological tolerance to cancer testis proteins does not appear to be established, and the expression of CTAg proteins within malignant cells can therefore lead to induction of cellular and humoral immunity. A considerable body of evidence now indicates that CD8-specific immunity plays an important role in the control of cancer cell growth, and a number of vaccine studies are in progress to boost CTAg-specific cellular immune responses. We have previously identified CTAg-specific immune responses in patients with multiple myeloma and reported that recognition of the MAGE-A1(289-298) peptide, which is described as being restricted by HLA-B*0702, was the most frequent response seen with our peptide panel. Here, we studied seven CD8+ T-cell clones specific for this peptide which were isolated from three patients with myeloma at several time-points. The affinity of peptide recognition was high with 50% maximal interferon-γ production observed at a peptide concentration of 10(-10) M and variation of only one order of magnitude between the affinities of the clones. Importantly, all the clones were able to recognise and kill multiple myeloma cell lines. Interestingly, one patient did not express HLA-B*0702, but three clones from this patient recognised the MAGE-A1(289-298) peptide on a lymphoblastoid cell line (LCLs) expressing HLA-Cw7, and we now show evidence that the MAGE-A1(289-298) peptide is expressed and recognised through Cw7. The T-cell receptor gene usage was determined in five clones and showed conserved features in both the α and the β chain genes indicating correlation between T-cell receptor usage and peptide specificity of cancer testis antigen-specific T-cell clones.

Background: Abacavir-lamivudine and tenofovir DF-emtricitabine fixed-dose combinations are commonly used as first-line antiretroviral therapies. However, few studies have comprehensively compared their relative safety profiles., Methods: In this European, multicenter, open-label, 96-week study, antiretroviral-naive adult subjects with human immunodeficiency virus (HIV) infection were randomized to receive either abacavir-lamivudine or tenofovir-emtricitabine with efavirenz. Primary analyses were conducted after 48 weeks of treatment. Bone mineral density (BMD), a powered secondary end point, was assessed by dual energy x-ray absorptiometry. Bone turnover markers (osteocalcin, procollagen 1 N-terminal propeptide, bone specific alkaline phosphatase, and type 1 collagen cross-linked C telopeptide [CTx]) were assessed in an exploratory analysis., Results: A total of 385 subjects were enrolled in the study. BMD loss was observed in both treatment groups, with a significant difference in the change from baseline in both total hip (abacavir-lamivudine group, -1.9%; tenofovir-emtricitabine group, -3.6%; P < .001) and lumbar spine (abacavir-lamivudine group, -1.6%; tenofovir-emtricitabine group, -2.4%; P = .036). BMD loss of >or=6% was more common in the tenofovir-emtricitabine group (13% of the tenofovir-emtricitabine group vs 3% of the abacavir-lamivudine group had a loss of >or=6% in the hip; 15% vs 5% had a loss of >or=6% in the spine). Bone turnover markers increased in both treatment groups over the first 24 weeks, stabilizing or decreasing thereafter. Increases in all markers were significantly greater in the tenofovir-emtricitabine treatment group than in the abacavir-lamivudine group at week 24. All but CTx remained significantly different at week 48 (eg, osteocalcin: abacavir-lamivudine group, +8.07 mg/L; tenofovir-emtricitabine group, +11.92 mg/L; P < .001)., Conclusions: This study demonstrated the impact of first-line treatment regimens on bone. Greater increases in bone turnover and decreases in BMD were observed in subjects treated with tenofovir-emtricitabine than were observed in subjects treated with abacavir-lamivudine.

Objectives: HLA-B*5701 is a major histocompatibility complex class I allele associated with an immunologically-mediated hypersensitivity reaction to abacavir. The objectives of this study were to evaluate HLA-B*5701 prevalence among European, HIV-1-infected patients and to compare the local and central laboratory screening results., Methods: Data were combined from six multicentre, prospective studies involving 10 European countries in which HIV-1-infected patients (irrespective of treatment experience or previous HLA-B*5701 screening), >or=18 years of age, were evaluated for HLA-B*5701 carriage, determined by the central and local laboratory methods., Results: A total of 9720 patients from 272 centres were included in the analysis. The overall estimate of HLA-B*5701 prevalence in Europe was 4.98%, with country-specific estimates ranging from 1.53 to 7.75%. HLA-B*5701 prevalence was highest in the self-reported white population (6.49%) and lowest in the black population (0.39%). Local laboratory results had a high specificity (99.9%) and sensitivity (99.2%) when compared with the central laboratory results., Conclusion: This study supports data from previous studies regarding the prevalence of HLA-B*5701 in the HIV population and the variation of HLA-B*5701 prevalence between different racial groups. The high specificity and sensitivity of local laboratory results, suggests that clinicians can be confident in using local laboratories for pretreatment HLA-B*5701 screening. However, it is essential that local laboratories participate in HLA-B*5701-specific quality assurance programs to maintain 100% sensitivity. In HIV-infected patients, pretreatment HLA-B*5701 screening may allow more informed decisions regarding abacavir use and has the potential to significantly reduce the frequency of abacavir-related hypersensitivity reactions and costs associated with managing these reactions.

The significant threat of wildfires to forest ecology and biodiversity, particularly in tropical and subtropical regions, underscores the necessity for advanced predictive models amidst shifting climate patterns. There is a need to evaluate and enhance wildfire prediction methods, focusing on their application during extended periods of intense heat and drought. This study reviews various wildfire modelling approaches, including traditional physical, semi-empirical, numerical, and emerging machine learning (ML)-based models. We critically assess these models' capabilities in predicting fire susceptibility and post-ignition spread, highlighting their strengths and limitations. Our findings indicate that while traditional models provide foundational insights, they often fall short in dynamically estimating parameters and predicting ignition events. Cellular automata models, despite their potential, face challenges in data integration and computational demands. Conversely, ML models demonstrate superior efficiency and accuracy by leveraging diverse datasets, though they encounter interpretability issues. This review recommends hybrid modelling approaches that integrate multiple methods to harness their combined strengths. By incorporating data assimilation techniques with dynamic forecasting models, the predictive capabilities of ML-based predictions can be significantly enhanced. This review underscores the necessity for continued refinement of these models to ensure their reliability in real-world applications, ultimately contributing to more effective wildfire mitigation and management strategies. Future research should focus on improving hybrid models and exploring new data integration methods to advance predictive capabilities. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic has had an unprecedented impact in the global research production and has also increased research waste. Living evidence syntheses (LESs) seek to regularly update a body of evidence addressing a specific question. During the COVID-19 pandemic, the production and dissemination of LESs emerged as a cornerstone of the evidence infrastructure. This critical interpretive synthesis answers the questions: What constitutes an LES to support decision-making?; when should one be produced, updated, and discontinued?; and how should one be disseminated? Methods: Searches included the Cochrane Library, EMBASE (Ovid), Health Systems Evidence, MEDLINE (Ovid), PubMed, and Web of Science up to 23 April 2024 and included articles that provide any insights on addressing the compass questions on LESs. Articles were selected and appraised, and their insights extracted. An interpretive and iterative coding process was used to identify relevant thematic categories and create a conceptual framework. Results: Among the 16,630 non-duplicate records identified, 208 publications proved eligible. Most were non-empirical articles, followed by actual LESs. Approximately one in three articles were published in response to the COVID-19 pandemic. The conceptual framework addresses six thematic categories: (1) what is an LES; (2) what methodological approaches facilitate LESs production; (3) when to produce an LES; (4) when to update an LES; (5) how to make available the findings of an LES; and (6) when to discontinue LES updates. Conclusion: LESs can play a critical role in reducing research waste and ensuring alignment with advisory and decision-making processes. This critical interpretive synthesis provides relevant insights on how to better organize the global evidence architecture to support their production. Trial registration: PROSPERO registration: CRD42021241875. [ABSTRACT FROM AUTHOR]

The climate crisis is both an environmental and moral issue. The United Nations' (UN) Sustainable Development Goals (SDGs) provide a framework for a global response to systematically challenge the world's reactions to the climate crisis, making sustainable education for all a priority. For such sustainability education to be effective, it should engage children in early childhood in, about, and for the environment, emphasizing the moral ramifications of climate equity and justice. We investigated in what ways 19 United States (US) nature-based early childhood educators focused their sustainability education (ECEfS) in, about, and for the environment. The types of activities that engaged about and for experiences were related to the moral principles of welfare, harm reduction, resource allocation, and equality, as well as teachers' reasoning about these experiences with children. Our findings suggest that educators' curricula and activities reflect potential moral issues related to sustainable development. However, educators did not engage children in moral reasoning about these issues. A possible explanation is US teachers' beliefs about developmental practice and children's capabilities leading them to rarely engage in moral reasoning about sustainability issues instead of scaffolding children to develop personal psychological resources, thereby supporting the SDG for sustainable education. [ABSTRACT FROM AUTHOR]

The epidemic outbreaks of the last two decades have led governments to rely more on computational tools for establishing protection policies. Computational approaches to modeling epidemics traditionally rely on compartmental models, network models, or agent-based models (ABMs); however, each approach has its limitations, ranging from reduced realism to lack of tractability. Furthermore, the recent literature emphasizes the importance of points of interest (POIs) as sources of population mixing and potential outbreak hotspots. In response, this study proposes a novel urban spatial ABM validated using our augmented SICARQD epidemic model. To replicate daily activities more accurately, the urban area is divided into a matrix of points of interest (POIs) with agents that have unique paths that only permit infectious transmission within POIs. Our results provide a qualitative assessment of how urban characteristics and individual mobility patterns impact the infected population during an outbreak. That is, we study how population density, the total number of POIs (where the population concentrates), the average number of POIs visited by an agent, the maximum travel distance from the home location, and the quarantine ratio impact the dynamics of an outbreak. Our ABM simulation framework offers a valuable tool for investigating and controlling infectious disease outbreaks in urban environments with direct applicability to global policy makers. [ABSTRACT FROM AUTHOR]

The emergence of SARS-CoV-2 led to a global health crisis and the burden of the disease continues to persist. The rapid development and emergency authorization of various vaccines, including mRNA-based vaccines, played a pivotal role in mitigating severe illness and mortality. However, rapid viral mutations, leading to several variants of concern, challenged vaccine effectiveness, particularly concerning immune evasion. Research on immunity, both from natural infection and vaccination, revealed that while neutralizing antibodies provide protection against infection, their effect is short-lived. The primary defense against severe COVID-19 is derived from the cellular immune response. Hybrid immunity, developed from a combination of natural infection and vaccination, offers enhanced protection, with convalescent vaccinated individuals showing significantly higher levels of neutralizing antibodies. As SARS-CoV-2 continues to evolve, understanding the durability and breadth of hybrid immunity becomes crucial. This narrative review examines the latest data on humoral and cellular immunity from both natural infection and vaccination, discussing how hybrid immunity could inform and optimize future vaccination strategies in the ongoing battle against COVID-19 and in fear of a new pandemic. [ABSTRACT FROM AUTHOR]

Recent studies have established the pivotal roles of patient‐derived tumour organoids (PDTOs), innovative three‐dimensional (3D) culture systems, in various biological and medical applications. PDTOs, as promising tools, have been established and extensively used for drug screening, prediction of immune response and assessment of immunotherapeutic effectiveness in various cancer types, including glioma, ovarian cancer and so on. The overarching goal is to facilitate the translation of new therapeutic modalities to guide personalised immunotherapy. Notably, there has been a recent surge of interest in the co‐culture of PDTOs with immune cells to investigate the dynamic interactions between tumour cells and immune microenvironment. A comprehensive and in‐depth investigation is necessary to enhance our understanding of PDTOs as promising testing platforms for cancer immunotherapy. This review mainly focuses on the latest updates on the applications and challenges of PDTO‐based methods in anti‐cancer immune responses. We strive to provide a comprehensive understanding of the potential and prospects of PDTO‐based technologies as next‐generation strategies for advancing immunotherapy approaches. [ABSTRACT FROM AUTHOR]

Software security is an important topic that is gaining more and more attention due to the rising number of publicly known cybersecurity incidents. Previous research has shown that one way to address software security is by means of a serious game, the CyberSecurity Challenges, which are designed to raise awareness of software developers of secure coding guidelines. This game, proven to be very successful in the industry, makes use of an artificial intelligence technique (laddering technique) to implement a chatbot for human–machine interaction. Recent advances in machine learning have led to a breakthrough, with the implementation and release of large language models, now freely available to the public. Such models are trained on a large amount of data and are capable of analyzing and interpreting not only natural language but also source code in different programming languages. With the advent of ChatGPT, and previous state-of-the-art research in secure software development, a natural question arises: to what extent can ChatGPT aid software developers in writing secure software? In this work, we draw on our experience in the industry, and also on extensive previous work to analyze and reflect on how to use ChatGPT to aid secure software development. Towards this, we conduct two experiments with large language models. Our engagements with ChatGPT and our experience in the field allow us to draw conclusions on the advantages, disadvantages, and limitations of the usage of this new technology. [ABSTRACT FROM AUTHOR]

Software vulnerabilities pose a significant threat to computer systems because they can jeopardize the integrity of both software and hardware. The existing tools for detecting vulnerabilities are inadequate. Machine learning algorithms may struggle to interpret enormous datasets because of their limited ability to understand intricate linkages within high-dimensional data. Traditional procedures, on the other hand, take a long time and require a lot of manual labor. Furthermore, earlier deep-learning approaches failed to acquire adequate feature data. Self-attention mechanisms can process information across large distances, but they do not collect structural data. This work addresses the critical problem of inadequate vulnerability detection in software systems. We propose a novel method that combines self-attention with convolutional networks to enhance the detection of software vulnerabilities by capturing both localized, position-specific features and global, content-driven interactions. Our contribution lies in the integration of these methodologies to improve the precision and F1 score of vulnerability detection systems, achieving unprecedented results on complex Python datasets. In addition, we improve the self-attention approaches by changing the denominator to address the issue of excessive attention heads creating irrelevant disturbances. We assessed the effectiveness of this strategy using six complex Python vulnerability datasets obtained from GitHub. Our rigorous study and comparison of data with previous studies resulted in the most precise outcomes and F1 score (99%) ever attained by machine learning systems. [ABSTRACT FROM AUTHOR]

This review explores the challenges and emerging trends in pancreatic cancer therapy. In particular, we focus on the tumor microenvironment and the potential of immunotherapy for pancreatic cancer. Pancreatic ductal adenocarcinoma, characterized by its dense stromal architecture, presents unique challenges for effective treatment. Recent advancements have emphasized the role of the tumor microenvironment in therapeutic resistance and disease progression. We discuss novel strategies targeting the desmoplastic barrier and immunosuppressive cells to enhance immune cell infiltration and activation. Recent clinical trials, particularly those involving novel immunotherapeutic agents and tumor vaccines, are examined to understand their efficacy and limitations. Our analysis reveals that combining immunotherapy with chemotherapy, radiation therapy, or drugs targeting epigenetic processes shows promise, improving overall survival rates and response to treatment. For instance, trials utilizing checkpoint inhibitors in combination with standard chemotherapies have extended disease-free survival by up to 6 months compared to chemotherapy alone. Importantly, vaccines targeting specific tumor neoantigens have shown the potential to increase patient survival. However, these approaches also face significant challenges, including overcoming the immunosuppressive tumor microenvironment and enhancing the delivery and efficacy of therapeutic agents. By providing an overview of both the promising results and the obstacles encountered, this review aims to highlight ongoing efforts to refine immunotherapy approaches for better patient outcomes. [ABSTRACT FROM AUTHOR]

The global pandemic sparked by the emergence of SARS-CoV-2 and its variants has imposed a substantial burden of morbidity and mortality. Central to the battle against these viral threats is the immune response, with a spotlight on the pivotal role played by neutralizing antibodies. This comprehensive review delves into current research, unravelling the dual functionality of neutralizing antibodies acting as formidable barriers to viral replication and crucial facilitators of adaptive immune memory. Beyond this dual purpose, the review illuminates the nuanced variability characterizing neutralizing antibody responses to SARS-CoV-2. Emphasizing the dynamic nature of these responses, the review advocates for the plausible challenges in targeted therapeutic interventions. This review also attempts to compare various vaccination approaches and their impact on SARS-CoV-2, as well as offer insights into various Omicron variations. Recognizing the ever-evolving viral landscape, this exploration underscores the necessity of flexible approaches to address the diverse challenges posed by SARS-CoV-2 and its variants, contributing valuable insights to the ongoing global efforts in pandemic mitigation and public health safeguarding. [ABSTRACT FROM AUTHOR]

In recent times, large language models (LLMs) have made significant strides in generating computer code, blurring the lines between code created by humans and code produced by artificial intelligence (AI). As these technologies evolve rapidly, it is crucial to explore how they influence code generation, especially given the risk of misuse in areas such as higher education. The present paper explores this issue by using advanced classification techniques to differentiate between code written by humans and code generated by ChatGPT, a type of LLM. We employ a new approach that combines powerful embedding features (black-box) with supervised learning algorithms including Deep Neural Networks, Random Forests, and Extreme Gradient Boosting to achieve this differentiation with an impressive accuracy of 98 % . For the successful combinations, we also examine their model calibration, showing that some of the models are extremely well calibrated. Additionally, we present white-box features and an interpretable Bayes classifier to elucidate critical differences between the code sources, enhancing the explainability and transparency of our approach. Both approaches work well, but provide at most 85–88% accuracy. Tests on a small sample of untrained humans suggest that humans do not solve the task much better than random guessing. This study is crucial in understanding and mitigating the potential risks associated with using AI in code generation, particularly in the context of higher education, software development, and competitive programming. [ABSTRACT FROM AUTHOR]

We evaluate and compare the simulation of the main features (low-level westerlies (LLWs) and the Congo basin (CB) cell) of low-level circulation in Central Equatorial Africa (CEA) with eight climate models from Phase 6 of the Coupled Model Intercomparison Project (CMIP6) and the corresponding eight previous models from CMIP5. Results reveal that, although the main characteristics of the two features are reasonably well depicted by the models, they bear some biases. The strength of LLWs is generally overestimated in CMIP5 models. The overestimation is attributed to both divergent and rotational components of the total wind with the rotational component contributing the most in the overestimation. In CMIP6 models, thanks to a better performance in the simulation of both divergent and rotational circulation, LLWs are slightly less strong compared to the CMIP5 models. The improvement in the simulated divergent component is associated with a better representation of the near-surface pressure and/or temperature difference between the Central Africa landmass and the coastal Atlantic Ocean. Regarding the rotational circulation, and especially for HadGEM3-GC31-LL and BCC-CSM2-MR, a simulated higher 850 hPa pressure is associated with less pronounced negative vorticity and a better representation of the rotational circulation. Most CMIP5 models also overestimate the CB cell intensity and width in association with the simulated strength of LLWs. However, in CMIP6 models, the strength of key cell characteristics (intensity and width) are reduced compared to CMIP5 models. This depicts an improvement in the representation of the cell in CMIP6 models and this is associated with the improvement in the simulated LLWs. [ABSTRACT FROM AUTHOR]

[{SiNDipp}BeClM]2 ({SiNDipp} = {CH2SiMe2N(Dipp)}2; M = Li, Na, K, Rb) are converted to ionic species by treatment with a crown ether. Whereas the lithium derivative reacts with Na or K to provide [{SiNDipp}BeCl]−[M(12-cr-4)2]+ (M = Na, K), the resultant sodium species is resistant to reduction by potassium. These observations are rationalised by a hybrid experimental/theoretical analysis. [ABSTRACT FROM AUTHOR]

In recent years, immunotherapy has emerged as a crucial component of cancer treatment. However, its efficacy remains limited across various cancer types, highlighting unmet needs. Poliovirus receptor-related 2 (PVRL2) and Poliovirus receptor (PVR) are members of the Nectin and Nectin-like Molecules family, known for their role as cell-cell adhesion molecules. With the development of immunotherapy, their involvement in tumor immune mechanisms as immune checkpoint factors has garnered significant attention. PVRL2 and PVR are predominantly expressed on tumor cells and antigen-presenting cells, binding to PVRIG and TIGIT, respectively, which are primarily found on T and NK cells, thereby suppressing antitumor immunity. Notably, gynecological cancers such as ovarian and endometrial cancers exhibit high expression levels of PVRL2 and PVR, with similar trends observed in various other solid and hematologic tumors. Targeting these immune checkpoint pathways offers a promising therapeutic avenue, potentially in combination with existing treatments. However, the immunomodulatory mechanism involving these bindings, known as the DNAM-1 axis, is complex, underscoring the importance of understanding it for developing novel therapies. This article comprehensively reviews the immunomodulatory mechanisms centered on PVRL2 and PVR, elucidating their implications for various cancer types. [ABSTRACT FROM AUTHOR]

Background: StrokeLine is a stroke‐specific helpline used by stroke survivors and their families in Australia to access professional support. There has been little research exploring stroke survivors' experiences of using helplines and their perceived impact on their stroke recovery. Aim: The aim of this study is to explore the reasons prompting stroke survivors to call StrokeLine and their experiences and to describe the perceived impact of calling StrokeLine on their recovery. Methods: An exploratory descriptive qualitative study was undertaken using thematic analysis of data collected through semi‐structured interviews of stroke survivors between December 2020 and May 2022. Participants were recruited using purposive sampling. Interviews were conducted via audio‐recorded Zoom conference calling and transcribed verbatim for thematic analysis. Results: A total of eight callers (four men and women women) participated, with the time since stroke ranging from 3.5 months to 5 years. Four major themes were identified, including 17 sub‐themes. Key themes included (1) factors prompting use of StrokeLine; (2) experience of using StrokeLine; (3) perceived impact of using StrokeLine; and (4) conceptualising StrokeLine service provision. Conclusions: Participants perceived their experience of contacting StrokeLine as having a positive impact on their stroke recovery, leaving them feeling empowered and motivated to self‐manage their condition. Patient or Public Contribution: Stroke survivors with lived experience influenced the conceptualisation of this study through conversations with consumers and the Stroke Foundation. Eight stroke survivors were involved as participants in the research study. [ABSTRACT FROM AUTHOR]

The formation of memory T cells is a fundamental feature of adaptative immunity, allowing the establishment of long-term protection against pathogens. Although emerging evidence suggests that metabolic reprogramming is crucial for memory T cell differentiation and survival, the underlying mechanisms that drive metabolic rewiring in memory T cells remain unclear. Here, we found that up-regulation of the nuclear receptor peroxisome proliferator–activated receptor β/δ (PPARβ/δ) instructs the metabolic reprogramming that occurs during the establishment of central memory CD8+ T cells. PPARβ/δ-regulated changes included suppression of aerobic glycolysis and enhancement of oxidative metabolism and fatty acid oxidation. Mechanistically, exposure to interleukin-15 and expression of T cell factor 1 facilitated activation of the PPARβ/δ pathway, counteracting apoptosis induced by antigen clearance and metabolic stress. Together, our findings indicate that PPARβ/δ is a master metabolic regulator orchestrating a metabolic switch that may be favorable for T cell longevity. Editor's summary: After initial antigen encounter, some T cells persist and differentiate into long-lived memory cells. This process is accompanied by metabolic reprogramming that supports survival and memory functions, but the key factors driving memory T cell metabolic adaptation remain unclear. Using mouse models of viral infection and melanoma, Bevilacqua et al. found that the nuclear receptor peroxisome proliferator–activated receptor β/δ (PPARβ/δ) supports the switch from aerobic glycolysis to oxidative metabolism during central memory CD8+ T cell formation. PPARβ/δ expression was required for memory T cell responses upon rechallenge, as well as the generation of TCF-1+ progenitor exhausted T cells during chronic antigen exposure. Together, these findings identify PPARβ/δ as a key regulator of metabolic reprogramming during memory T cell differentiation. —Claire Olingy [ABSTRACT FROM AUTHOR]

We perform new measurements of the expansion rate and the sound horizon at the end of the baryon decoupling, and derive constraints on cosmic key parameters in the framework of the Λ CDM model, wCDM model, non-flat Λ CDM model and the phenomenological emergent dark energy (PEDE) model. We keep r d and H 0 completely free, and use the recent Dark Energy Spectroscopic Instrument (DESI) Year 1 and Dark Energy Survey (DES) Year 6 BAO measurements in the effective redshift range 0.3 < z < 2.33 , combined with the compressed form of the Pantheon sample of Type Ia supernovae, the latest 34 observational H (z) measurements based on the differential age method, and the recent H 0 measurement from SH0ES 2022 as an additional Gaussian prior. Combining BAO data with the observational H (z) measurements, and the Pantheon SNe Ia data, we obtain H 0 = 69.70 ± 1.11 km s − 1 Mpc − 1 , r d = 147.14 ± 2.56 Mpc in flat Λ CDM model, H 0 = 70.01 ± 1.14 km s − 1 Mpc − 1 , r d = 146.97 ± 2.45 Mpc in PEDE model. The spatial curvature is Ω k = 0.023 ± 0.025 , and the dark energy equation of state is w = − 1.029 ± 0.051 , consistent with a cosmological constant. We apply the Akaike information and the Bayesian information criterion test to compare the four models, and see that the PEDE model performs better. [ABSTRACT FROM AUTHOR]

Recently, using Bayesian Machine Learning, a deviation from the cold dark matter model on cosmological scales has been put forward. Such a model might replace the proposed non-gravitational interaction between dark energy and dark matter, and help solve the H 0 tension problem. The idea behind the learning procedure relies on a generated expansion rate, while the real expansion rate is just used to validate the learned results. In the present work, however, the emphasis is put on a Gaussian Process (GP), with the available H (z) data confirming the possible existence of the already learned deviation. Three cosmological scenarios are considered: a simple one, with an equation-of-state parameter for dark matter ω d m = ω 0 ≠ 0 , and two other models, with corresponding parameters ω d m = ω 0 + ω 1 z and ω d m = ω 0 + ω 1 z / (1 + z) . The constraints obtained on the free parameters ω 0 and ω 1 hint towards a dynamical nature of the deviation. The dark energy dynamics is also reconstructed, revealing interesting aspects connected with the H 0 tension problem. It is concluded, however, that improved tools and more data are needed, to reach a better understanding of the reported deviation. [ABSTRACT FROM AUTHOR]

The SARS-CoV-2 Omicron variant and its sublineages continue to cause COVID-19-associated pediatric hospitalizations, severe disease, and death globally. BNT162b2 and CoronaVac are the main vaccines used in Chile. Much less is known about the Wuhan-Hu-1 strain-based vaccines in the pediatric population compared to adults. Given the worldwide need for booster vaccinations to stimulate the immune response against new Omicron variants of SARS-CoV-2, we characterized the humoral and cellular immune response against Omicron variant BA.1 in a pediatric cohort aged 10 to 16 years who received heterologous vaccination based on two doses of CoronaVac, two doses of CoronaVac (2x) plus one booster dose of BNT162b2 [CoronaVac(2x) + BNT162b2 (1x)], two doses of CoronaVac plus two booster doses of BNT162b2 [CoronaVac(2x) + BNT162b2 (2x)], and three doses of BNT162b2. We observed that the [CoronaVac(2x) + BNT162b2 (2x)] vaccination showed higher anti-S1 and neutralizing antibody titers and CD4 and CD8 T cell immunity specific to the Omicron variant compared to immunization with two doses of CoronaVac alone. Furthermore, from all groups tested, immunity against Omicron was highest in individuals who received three doses of BNT162b2. We conclude that booster vaccination with BNT162b2, compared to two doses of CoronaVac alone, induces a greater protective immunity. [ABSTRACT FROM AUTHOR]

The ongoing COVID-19 pandemic has significantly impacted special populations, including immunocompromised individuals, people living with HIV (PLWHIV), pediatric patients, and those with chronic liver disease (CLD). This scoping review aims to map the clinical outcomes of these vulnerable groups when infected with various SARS-CoV-2 variants. The review identifies trends and patterns, noting that early variants, such as Alpha and Delta, are associated with more severe outcomes, including higher hospitalization and mortality rates. In contrast, the Omicron variant, despite its increased transmissibility, tends to cause milder clinical manifestations. The review highlights the necessity for ongoing surveillance and tailored healthcare interventions due to the heterogeneity of patient populations and the evolving nature of the virus. Continuous monitoring and adaptive healthcare strategies are essential to mitigate the impact of COVID-19 on these high-risk groups. [ABSTRACT FROM AUTHOR]

Simple Summary: Esophageal cancer, a highly lethal tumor, contributes to 5% of all cancer deaths, with its primary subtypes being esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC). While most studies focus on ESCC, this study investigates EAC using single-cell RNA sequencing (scRNA-seq) to analyze CD45+ immune cells from tumors and matched non-tumor tissues in therapy-naïve patients. By examining the transcriptional profiles of these immune cells and the entire transcriptome in a cohort of 23 patients, this study identifies distinct transcriptional signatures. These signatures were used to stratify a large cohort of TCGA EAC patients, revealing strong associations with prognosis and clinical outcomes. The findings suggest that these transcriptional profiles can improve prognosis accuracy post-surgery and potentially guide effective therapies, including immunotherapy, for EAC patients. Esophageal cancer is a highly lethal malignancy, representing 5% of all cancer-related deaths. The two main subtypes are esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC). While most research has focused on ESCC, few studies have analyzed EAC for transcriptional signatures linked to diagnosis or prognosis. In this study, we utilized single-cell RNA sequencing and bulk RNA sequencing to identify specific immune cell types that contribute to anti-tumor responses, as well as differentially expressed genes (DEGs). We have characterized transcriptional signatures, validated against a wide cohort of TCGA patients, that are capable of predicting clinical outcomes and the prognosis of EAC post-surgery with efficacy comparable to the currently accepted prognostic factors. In conclusion, our findings provide insights into the immune landscape and therapeutic targets of EAC, proposing novel immunological biomarkers for predicting prognosis, aiding in patient stratification for post-surgical outcomes, follow-up, and personalized adjuvant therapy decisions. [ABSTRACT FROM AUTHOR]

Nucleocapsid antibody assays can be used to estimate SARS-CoV-2 infection prevalence in regions implementing spike-based COVID-19 vaccines. However, poor sensitivity of nucleocapsid antibody assays in detecting infection after vaccination has been reported. We derived a lower cutoff for identifying previous infections in a large blood donor cohort (N = 142,599) by using the Ortho VITROS Anti-SARS-CoV-2 Total-N Antibody assay, improving sensitivity while maintaining specificity >98%. We validated sensitivity in samples donated after self-reported swab-confirmed infection diagnoses. Sensitivity for first infections in unvaccinated donors was 98.1% (95% CI 98.0-98.2) and for infection after vaccination was 95.6% (95% CI 95.6-95.7) based on the standard cutoff. Regression analysis showed sensitivity was reduced in the Delta compared with Omicron period, in older donors, in asymptomatic infections, <30 days after infection, and for infection after vaccination. The standard Ortho N antibody threshold demonstrated good sensitivity, which was modestly improved with the revised cutoff. [ABSTRACT FROM AUTHOR]

With the global prevalence of allergic disease continuing to rise at an alarming rate, the need for effective and safe therapeutics is paramount. Given the critical role of the early-life microbiota on immune development, emerging research suggests the potential use of live biotherapeutic products (LBP) for the prevention and treatment of childhood allergy. However, findings are limited and inconsistent. Therefore, the present review critically evaluates the current animal and human data on the therapeutic value of LBPs in allergy, the underlying immunological mechanisms by which LBPs may mediate allergy susceptibility, limitations of the current research that need to be addressed, and future research directions. Accordingly, LBPs may protect against allergic disease through several immunological and physiological mechanisms during early-life, including regulation of Th1/Th2 balance, SCFA-induced activation of GPR41/43 and HDAC inhibition, and maturation of epithelial barrier integrity. Taken together, current findings indicate powerful immunomodulatory properties of LBPs on allergic immune response, with LBPs offering exciting potential as a novel therapeutic tool for childhood allergy. However, the efficacy of LBPs in allergy is complex and influenced by many population and methodological factors, resulting in varied therapeutic benefits. While research thus far has focused on traditional probiotic strains, greater investigation into microbial consortiums selected from the microbiota of non-allergic infants may provide greater promise as a therapeutic tool for allergic disease. Further investigation, particularly into long-term efficacy, strain-specific effects, optimal supplementation regimes, and use of multi-strain consortiums, is necessary before findings can be translated into clinical applications to tackle childhood allergic disease. [ABSTRACT FROM AUTHOR]

The gut microbiome plays a significant role in the pathogenesis of pancreatic ductal adenocarcinoma (PDAC), influencing oncogenesis, immune responses, and treatment outcomes. Studies have identified microbial species like Porphyromonas gingivalis and Fusobacterium nucleatum, that promote PDAC progression through various mechanisms. Additionally, the gut microbiome affects immune cell activation and response to immunotherapy, including immune checkpoint inhibitors and CAR-T therapy. Specific microbes and their metabolites play a significant role in the effectiveness of immune checkpoint inhibitors (ICIs). Alterations in the gut microbiome can either enhance or diminish responses to PD-1/PD-L1 and CTLA-4 blockade therapy. Additionally, bacterial metabolites like trimethylamine N-oxide (TMAO) and lipopolysaccharide (LPS) impact antitumor immunity, offering potential targets to augment immunotherapy responses. Modulating the microbiome through fecal microbiota transplantation, probiotics, prebiotics, dietary changes, and antibiotics shows promise in PDAC treatment, although outcomes are highly variable. Dietary modifications, particularly high-fiber diets and specific fat consumption, influence microbiome composition and impact cancer risk. Combining microbiome-based therapies with existing treatments holds potential for improving PDAC therapy outcomes, but further research is needed to optimize their effectiveness. [ABSTRACT FROM AUTHOR]

Wide band-gap organic solar cells are gaining interest due to their applications in emergent light-harvesting technologies such as underwater photovoltaics, multi-junction solar cells, or indoor photovoltaics. In this work, a combinatorial screening approach is used to explore binary combinations of three wide band-gap donors (PTQ10, PM6, and D18) and three wide band-gap acceptors (PMI-FF-PMI, O-IDFBR, and IO-4Cl) deposited from solution in two solvents (CB and CF). In total, 18 combinations are blade-coated with active layers exhibiting a thickness gradient generating solar cells with 12 different thicknesses. PTQ10:IO-4Cl and PTQ10:O-IDFBR are the most efficient blends with efficiencies of 7.31% and 6.87%, respectively. The voltage loss analysis shows that PTQ10-based devices exhibit the lowest non-radiative voltage losses, whereby the PTQ10:O-IDFBR combination has the lowest voltage loss of all studied blends, with a remarkably high open-circuit voltage (Voc) of 1.35 V. Due to their high performance and Voc, PTQ10:O-IDFBR devices were also studied for indoor light harvesting, achieving an efficiency of 22.6% and a Voc of 1.21 V under 560 lux indoor illumination. To the best of our knowledge, this indoor Voc value is the highest achieved in the field of indoor organic photovoltaics. [ABSTRACT FROM AUTHOR]

Although Three-dimensional (3D) printers have legitimate applications in various fields, they also present opportunities for misuse by criminals who can infringe upon intellectual property rights, manufacture counterfeit medical products, or create unregulated and untraceable firearms. The rise of affordable 3D printers for general consumers has exacerbated these concerns, making it increasingly vital for digital forensics investigators to identify and analyze vital artifacts associated with 3D printing. In our study, we focus on the identification and analysis of digital forensic artifacts related to 3D printing stored in both Linux and Windows operating systems. We create five distinct scenarios and gather data, including random-access memory (RAM), configuration data, generated files, residual data, and network data, to identify when 3D printing occurs on a device. Furthermore, we utilize the 3D printing slicing software Ultimaker Cura version 5.7 and RepetierHost version 2.3.2 to complete our experiments. Additionally, we anticipate that criminals commonly engage in anti-forensics and recover valuable evidence after uninstalling the software and deleting all other evidence. Our analysis reveals that each data type we collect provides vital evidence relating to 3D printing forensics. [ABSTRACT FROM AUTHOR]

This study examines mesoscale convective systems (MCSs) in relation to 1‐min automatic weather station data for 2 years over the city of Yaounde. The focus is on characterising the atmospheric variability associated with MCS activity while distinguishing the days with and without MCS activities. This paper aims to determine the diurnal cycles of occurrence frequencies and percentages of rainfall, relative humidity, dew point temperature, solar radiation, temperature, and wind speed for days with and without MCSs. There are more than 623 MCS events during the study period (over 150 events per rainy season). The link between MCS activity and regional‐scale circulation and atmospheric instability is investigated. The diurnal cycle of the number of MCSs shows a maximum in the afternoon (around 1,600–2,200 LT), a morning minimum (around 0700–1,300 LT), and substantial activity during the night. Surface relative humidity is 5% lower on non‐MCS days, surface dew point 2% higher on MCS days between 0700 and 1800 hr, and solar radiation higher on MCS days between 0500 and 1000 hr. The percentage of rainfall associated with MCSs can exceed 60% on an annual scale and up to 80% on a seasonal scale. MCS activity is associated with instability in the lower troposphere, and this convective instability is maximal during the peak of the MCS activity. [ABSTRACT FROM AUTHOR]

Background: Pancreatic Ductal Adenocarcinoma (PDAC) is an aggressive cancer characterized by an immunosuppressive microenvironment. Patients from specific ethnicities and population groups have poorer prognoses than others. Therefore, a better understanding of the immune landscape in such groups is necessary for disease elucidation, predicting patient outcomes and therapeutic targeting. This study investigated the expression of circulating key immune cell markers in South African PDAC patients of African ancestry. Methods: Blood samples were obtained from a total of 6 healthy volunteers (HC), 6 Chronic Pancreatitis (CP) and 34 PDAC patients consisting of 22 resectable (RPC), 8 locally advanced (LAPC) and 4 metastatic (MPC). Real-time Quantitative Polymerase Chain reactions (RT-qPCR), Metabolomics, Enzyme-Linked Immunosorbent Assay (ELISA), Reactive Oxygen Species (ROS), and Immunophenotyping assays were conducted. Statistical analysis was conducted in R (v 4.3.2). Additional analysis of single-cell RNA data from 20 patients (16 PDAC and 4 controls) was conducted to interrogate the distribution of T-cell and Natural Killer cell populations. Results: Granulocyte and neutrophil levels were significantly elevated while lymphocytes decreased with PDAC severity. The total percentages of CD3 T-cell subpopulations (helper and double negative T-cells) decreased when compared to HC. Although both NK (p = 0.014) and NKT (p < 0.001) cell levels increased as the disease progressed, their subsets: NK CD56dimCD16− (p = 0.024) and NKTs CD56+ (p = 0.008) cell levels reduced significantly. Of note is the negative association of NK CD56dimCD16− (p < 0.001) cell levels with survival time. The gene expression analyses showed no statistically significant correlation when comparing the PDAC groups with the controls. The inflammatory status of PDAC was assessed by ROS levels of serum which were elevated in CP (p = 0.025), (RPC (p = 0.003) and LAPC (p = 0.008)) while no significant change was observed in MPC, compared to the HC group. ROS was shown to be positively correlated with GlycA (R = 0.45, p = 0.0096). Single-cell analyses showed a significant difference in the ratio of NKT cells per total cell counts in LAPC (p < 0.001) and MPC (p < 0.001) groups compared with HC, confirming observations in our sample group. Conclusion: The expression of these immune cell markers observed in this pilot study provides insight into their potential roles in tumour progression in the patient group and suggests their potential utility in the development of immunotherapeutic strategies. [ABSTRACT FROM AUTHOR]

Background: Heat-related illness (HRI) is commonly considered an acute condition, and its potential long-term consequences are not well understood. We conducted a population-based cohort study and an animal experiment to evaluate whether HRI is associated with dementia later in life. Methods: The Taiwan National Health Insurance Research Database was used in the epidemiological study. We identified newly diagnosed HRI patients between 2001 and 2015, but excluded those with any pre-existing dementia, as the study cohort. Through matching by age, sex, and the index date with the study cohort, we selected individuals without HRI and without any pre-existing dementia as a comparison cohort at a 1:4 ratio. We followed each cohort member until the end of 2018 and compared the risk between the two cohorts using Cox proportional hazards regression models. In the animal experiment, we used a rat model to assess cognitive functions and the histopathological changes in the hippocampus after a heat stroke event. Results: In the epidemiological study, the study cohort consisted of 70,721 HRI patients and the comparison cohort consisted of 282,884 individuals without HRI. After adjusting for potential confounders, the HRI patients had a higher risk of dementia (adjusted hazard ratio [AHR] = 1.24; 95% confidence interval [CI]: 1.19–1.29). Patients with heat stroke had a higher risk of dementia compared with individuals without HRI (AHR = 1.26; 95% CI: 1.18–1.34). In the animal experiment, we found cognitive dysfunction evidenced by animal behavioral tests and observed remarkable neuronal damage, degeneration, apoptosis, and amyloid plaque deposition in the hippocampus after a heat stroke event. Conclusions: Our epidemiological study indicated that HRI elevated the risk of dementia. This finding was substantiated by the histopathological features observed in the hippocampus, along with the cognitive impairments detected, in the experimental heat stroke rat model. [ABSTRACT FROM AUTHOR]

In a warming climate, an intensifying fire regime and higher likelihood of extreme rain are expected to increase watershed sediment yield in many regions. Understanding regional variability in landscape response to fire and post‐fire rainfall is essential for managing water resources and infrastructure. We measured sediment yield resulting from sequential wildfire and extreme rain and flooding in the upper Carmel River watershed (116 km2), on the central California coast, USA, using changes in sediment volume mapped in a reservoir. We determined that the sediment yield after fire and post‐fire flooding was 854–1,100 t/km2/yr, a factor of 3.5–4.6 greater than the long‐term yield from this watershed and more than an order of magnitude greater than during severe drought conditions. In this first large‐scale field validation test of the WEPPcloud/wepppy framework for the Water Erosion Prediction Project (WEPP) model on a burned landscape, WEPP predicted 81%–106% of the measured sediment yield. These findings will facilitate assessing and predicting future fire effects in steep watersheds with a Mediterranean climate and indicate that the increasingly widespread use of WEPP is appropriate for evaluating post‐fire hillslope erosion even across 100‐km2 scales under conditions without debris flows. Plain Language Summary: In a warming climate, more wildfire and more extreme rain will cause more erosion, producing more sediment that will be carried downstream by rivers. Understanding how much sediment a landscape produces after fire and extreme rain is essential for managing water resources and infrastructure, because sediment fills up storage space in reservoirs and can interfere with proper functioning of water systems and roads. We measured how much sediment was produced in a watershed due to wildfire followed by extreme rain and flooding, studying the Carmel River on the central California coast, USA. We evaluated how much sediment this watershed produced by measuring the volume of sediment deposited within a reservoir that the watershed drains into. We determined that the rate of sediment exported from the study watershed due to a large fire and post‐fire floods was much greater than the long‐term rate there. Having compared our results with the amount of sediment predicted by a model called the Water Erosion Prediction Project model, we found that the model performed well and realistically predicted the amount of sediment that this landscape would shed. These findings will facilitate assessing and predicting future fire effects in steep watersheds with a Mediterranean‐type climate. Key Points: A 116‐km2 central California watershed produced sediment yield of 854–1,100 t/km2/yr in the first year after a fire and extreme rainPost‐fire sediment yield in an extremely wet year without debris flows was 3.5–4.6 times greater than the long‐term rateThe Water Erosion Prediction Project model predicted 81%–106% of the measured post‐fire sediment eroded from hillslopes [ABSTRACT FROM AUTHOR]

Despite substantial improvements in survival rates for most cancers, pancreatic cancer still remains a leading cause of death from malignancy. The disease has no symptoms in the initial stages, it can early invade the surrounding organs, and treatment methods have poor long-term prognosis. In addition, this neoplasia is starting to be diagnosed more and more frequently in young people. High incidences have been found in developed regions such as Europe, North America, Australia, but recent data show that this condition is increasing in other regions as well. Pancreatic cancer involves multiple factors such as cigarette smoking, obesity, diabetes, alcohol consumption, inherited genetic factors, recent studies also correlating pancreatic cancer with abnormal metabolism of human microorganisms, blood type, as well as glucose and lipid levels. This review aims to update knowledge on the epidemiology, pathophysiology, diagnosis and treatment of pancreatic cancer. The goal is to encourage screening and early diagnosis methods, as well as to stimulate further research on this oncological topic, insufficiently studied to date. [ABSTRACT FROM AUTHOR]

This article explores the impact of values and information publicity on tourists' intentions to visit green hotels. The study finds that egoistic values have the greatest influence on pro-environmental beliefs, and both pro-environmental beliefs and information publicity have a positive impact on personal norms, which in turn lead to the intention to visit green hotels. The research highlights the importance of incorporating information publicity into the value-belief norm framework to understand tourists' intentions. The findings have practical implications for hotel managers in developing effective marketing strategies for green hotels. [Extracted from the article]

Online mental health services offer programs and resources for users to better manage their mental health, where part of the process of engaging in these services involves initiatives that attempt to motivate a transition from online to face-to-face support. What can we make of those initiatives through the insight of users? This research, platforming the voices of young adults aged 18–25 years, provides valuable insights into the unique help-seeking experiences of this demographic and the effectiveness of online mental health services in facilitating a transition to face-to-face support. Using an online survey comprising of open-response and Likert scale questions, 101 participants provided qualitative and quantitative feedback. Key quantitative findings revealed 66% of participants had transitioned from online mental health services to face-to-face supports following their initial engagement. Moreover, a substantial 57.05% of participants expressed satisfaction with their online experiences. Mental health education pages were the most accessed resource by service users, with 82.18% of participants having used them. Emerging from a series of 10-point Likert scale questions, "contact with a professional" (7.58) and "receiving a referral" (9.25) were the highest rated predictors of transition, while barriers such as a "lack of motivation" and "bureaucratic complexities" were identified from qualitative data as the dominant inhibiting factors. Lastly, psychoeducation emerged as a crucial tool for empowering participants toward overcoming stigma, with the theme of trust highlighted as the most critical factor in determining the confidence of young adults attempting to transition from online to face-to-face support. [ABSTRACT FROM AUTHOR]