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Heparan sulfate (HS) polysaccharides are master regulators of diverse biological processes via sulfated motifs that can recruit specific proteins. 3-O-sulfation of HS/heparin is crucial for anticoagulant activity, but despite emerging evidence for roles in many other functions, a lack of tools for deciphering structure-function relationships has hampered advances. Here, we describe an approach integrating synthesis of 3-O-sulfated standards, comprehensive HS disaccharide profiling, and cell engineering to address this deficiency. Its application revealed previously unseen differences in 3-O-sulfated profiles of clinical heparins and 3-O-sulfotransferase (HS3ST)–specific variations in cell surface HS profiles. The latter correlated with functional differences in anticoagulant activity and binding to platelet factor 4 (PF4), which underlies heparin-induced thrombocytopenia, a known side effect of heparin. Unexpectedly, cells expressing the HS3ST4 isoenzyme generated HS with potent anticoagulant activity but weak PF4 binding. The data provide new insights into 3-O-sulfate structure-function and demonstrate proof of concept for tailored cell-based synthesis of next-generation heparins.

This study aims to investigate the interaction between market volatility, economic growth, and cognitive biases over the period from April 2006 to March 2024. Market volatility and economic growth are critical indicators that influence economic stability and investment behavior. Financial market volatility, defined by abrupt and erratic changes in asset values, can have a big impact on the expansion and stability of the economy. According to conventional economic theory, there should be an inverse relationship between market volatility and economic growth since high volatility can discourage investment and erode trust. Market participants' cognitive biases are a major aspect that complicates this connection. Due to our innate susceptibility to cognitive biases, including herd mentality, overconfidence, and loss aversion, humans can make poor decisions and increase market volatility. These prejudices frequently cause investors to behave erratically and irrationally, departing from reasonable expectations and causing inefficiencies in the market. Cognitive biases have the capacity to sustain feedback loops, which heighten market turbulence and may hinder economic expansion. Similarly, cognitive biases have the potential to cause investors to misread economic indicators or ignore important details, which would increase volatility. This study uses the generalized autoregressive conditional heteroskedasticity (GARCH) model on GDP growth data from the US, the UK, and India, alongside S&P 500, FTSE 100, and NIFTY 50 data sourced from Bloomberg, to examine evidence of these biases. The results show evidence of the predictive nature of market fluctuations on economic performance across the markets and highlight the substantial effects of cognitive biases on market volatility, disregarding economic fundamentals and growth, emphasizing the necessity of considering psychological factors in financial market analyses and developing strategies to mitigate their adverse effects. [ABSTRACT FROM AUTHOR]

Mobile Ad-Hoc Networks (MANETs) represent a dynamic and decentralized communication paradigm, wherein devices can establish network connections on-the-fly, making them particularly suitable for scenarios with infrastructure challenges. However, the performance of MANETs depends significantly on the chosen routing protocol and the density of network nodes. In this research, we present a comprehensive analysis of three prominent routing protocols: the Intermediate Node Traffic Sharing Model (INTSM), Ad-Hoc On-Demand Distance Vector (AODV), and Destination-Sequenced Distance Vector (DSDV) under varying node density conditions. Our study involves extensive simulations and performance evaluations within the NS2 simulation framework to assess the effectiveness of these routing protocols in scenarios with node density variations. We investigate key performance metrics, including packet delivery ratio, end-to-end delay, network throughput, and routing overhead, across a spectrum of node densities. By conducting a systematic comparison, we aim to provide valuable insights into the behavior of these protocols and their adaptability to dynamic network environments. The findings of this research contribute to a deeper understanding of how INTSM, AODV, and DSDV routing protocols perform under node density fluctuations within the NS2 simulation environment, offering valuable guidance for selecting the most suitable protocol for specific MANET deployments. Furthermore, our study underscores the importance of considering network dynamics and varying node populations in the design and optimization of mobile ad-hoc communication systems, especially when using simulation tools like NS2 for evaluation and analysis. [ABSTRACT FROM AUTHOR]

From online social networks to life-or-death security systems, multimedia files (photos, movies, and audio recordings) have grown common in today's digital culture. Protecting people, businesses and infrastructure requires strict adherence to the encryption and decryption of multimedia data. We suggested an Ensemble Whale Optimized Recurrent Neural Network (EWO-RNN)used in this study to overcome these issues. With the help of this study, multimedia security will be evaluated in more accurate and comprehensive manner. Smarter decisions and proactive security measures may follow as a result of this. To increase the system quality and the overall performance, the collected data is pre-processed for normalized data by using Min-Max Normalization. Pre-processed data is extracted by using Kernel Principle Component Analysis (K-PCA). The EWO-RNN evaluates the effectiveness and efficiency of an approach by analyzing the performance of Accuracy (97.85%), Precision (92.2%), F1-score (96.1%), Mean Square Error (MSE) (0.086), Root Mean Square (RMSE) (0.12%) and Sensitivity (95%). The Enhanced Radial Base Deep Learning Algorithm for Predicting Multimedia Security Issues proposes a solution with improved resilience, accuracy, generalization, and decision-making capabilities. In a dynamic and evolving digital environment, this makes the algorithm a viable tool for multimedia security assessments. [ABSTRACT FROM AUTHOR]

Introduction: Early in the pandemic, older people were identified as one of the most vulnerable population. More than 80% of deaths occur in adults over the age of 65. Several conditions have been clearly established to protect the elderly, such as banning visits to nursing homes. Therefore, it is important to fully understand how this pandemic has affected the elderly. This study covers the negative effects on the physical and mental health of the elderly during COVID-19 pandemic. Methodology: A systematic review of the literature to identify COVID-19 papers with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) using PubMed, Google Scholar, Science Direct, BioMed Central (BMC) and Frontier in 2020 and 2021. Included studies are those that investigate the psychological and physical impact on elderly (>=60 years old) resulting from the impact of the COVID-19 pandemic. Unrelated, duplicated, unavailable full texts/abstract-only papers, and studies that analyzed mental and behavioral disorders due to the use of alcohol and other drugs are excluded. Results: A total of 12 studies are included out of 352. Impact of COVID-19 on physical health to elderly were weight loss, lesser time of exercise, decreased social activities, increased respiratory and heart diseases, and increased mortality. On the other hand, identified impact on mental health were higher depression, anxiety, fear of acquiring COVID due to irresponsible younger generations, discrimination and isolation, increased levels of loneliness, and generalized anxiety. Conclusion: The findings summarized in this review suggest that older adults experienced negative consequences for the ongoing pandemic, both physically and mentally. This information will be useful to responsible institutions when acting and making decisions for elderly regarding health care access and public health measures. [ABSTRACT FROM AUTHOR]

Earth’s biodiversity is being lost at an alarming rate. Researchers have consistently underscored the need to conserve biodiversity not only for the sake of the environment, but also to safeguard human health itself. Biodiversity loss is a chronic, largely abstract risk that is difficult for people to visualize tangibly. This can limit what people think they can do to help conserve it. However, experts regularly implore the wider adoption of more sustainable behaviors because these are linked to both conserving biodiversity and improving the long-term quality of human life. This study centrally examines whether framing the risk of biodiversity loss in terms of its impacts on human health can persuade people to adopt recommended sustainable behaviors to protect themselves against its harmful effects on their health. A survey-based experiment testing the effect of risk-framed messages found that low-risk messages were associated with higher risk perceptions, fear, efficacy, and protection motivation than high-risk messages. The primary contribution of this study is the mapping of causal pathways between factors in the protection motivation model in the context of a chronic, global environmental and health risk. A moderated serial mediation analysis demonstrates how risk perceptions, fear, response and self-efficacy, maladaptive rewards, and response costs influence intentions to adopt sustainable behaviors. In exploring the effects of efficacy independent of the coping appraisal additive, findings show that efficacy moderates the impact of risk perceptions on fear, and coping appraisal moderates the impact of fear on protection motivation. A broader conceptualization of efficacy and implications for sustainability campaigns, practice, and future research are discussed. [ABSTRACT FROM AUTHOR]

Time-dependent changes in the lipid body (LB) lipidome of two oleaginous yeasts, Yarrowia lipolytica NCIM 3589 and Yarrowia bubula NCIM 3590 differing in growth temperature was investigated. LB size and lipid content were higher in Y. lipolytica based on microscopy, Feret, and integrated density analysis with lipid accumulation and mobilization occurring at 48 h in both strains. Variations in LB lipidome were reflected in interfacial tension (59.67 and 68.59 mN m-1) and phase transition temperatures (30°C-100°C and 60°C-100°C) for Y. lipolytica and Y. bubula, respectively. Liquid Chromatography-Mass Spectroscopy (LC-MS) analysis revealed neutral lipids (NLs), phospholipids, sphingolipids, sterols, and fatty acids as the major classes present in both strains while fatty acid amides were seen only in Y. lipolytica. Amongst the lipid classes, a few species were present in abundance with a number of lipids being less dominant. Permutational multivariate analysis of variance (PERMANOVA) and Analysis of covariance (ANOCOVA) analysis suggest 22 lipids belonging to NLs, fatty acid amides, and free fatty acids were found to be statistically different between the two strains. Analysis of the ratios between different lipid components suggest changes in LB size and mobilization as a function of time. The results indicate influence of temperature and strain variation on the dynamics of LB lipidome in Yarrowia species., (© The Author(s) 2024. Published by Oxford University Press on behalf of FEMS.)