Search

Epigenetic regulation serves as the basis for stem cell differentiation into distinct cell types, but it is unclear how global epigenetic changes are regulated during this process. Here, we tested the hypothesis that global chromatin organization affects the lineage potential of stem cells and that manipulation of chromatin dynamics influences stem cell function. Using nuclease sensitivity assays, we found a progressive decrease in chromatin digestion among pluripotent embryonic stem cells (ESCs), multipotent hematopoietic stem cells (HSCs), and mature hematopoietic cells. Quantitative high-resolution microscopy revealed that ESCs contain significantly more euchromatin than HSCs, with a further reduction in mature cells. Increased cellular maturation also led to heterochromatin localization to the nuclear periphery. Functionally, prevention of heterochromatin formation by inhibition of the histone methyltransferase G9A resulted in delayed HSC differentiation. Our results demonstrate global chromatin rearrangements during stem cell differentiation and that heterochromatin formation by H3K9 methylation regulates HSC differentiation.

Abstract There is a significant lack of comprehensive research that systematically examines public perceptions of liability (related to cyber risks), consumer data, and how these factors influence the adoption of automated vehicles (AVs). To fill this knowledge gap, the authors' research used a survey of 2062 adults across Australia, New Zealand, the UK, and the US to develop a scale for Liability, Data concerns, Data sharing and Patching and updates. This analytical approach employed various statistical methods to analyze the data (summarizing, finding patterns, measuring relationships). The results indicate that 70% of respondents express concerns about AV liability based on cyber risks, highlighting a significant level of liability anxiety. Individuals with high liability concerns also exhibit heightened concerns about AV data, are less comfortable sharing AV data, and display lower intent to adopt AVs. Conversely, individuals comfortable with data sharing are more willing to engage in patching and express a greater intent to adopt AVs. Interestingly, individuals with AV data concerns do not exhibit a negative correlation with their intent to adopt AVs. Additionally, those willing for patches also show a stronger intent to adopt AVs, challenging the notion that software updates hinder AV adoption.

Background: Canine cognitive dysfunction (CCD) is considered the canine version of human Alzheimer's disease (AD). As with AD, CCD is a multifactorial and progressive neurodegenerative disorder for which effective treatment options are continuously being sought. Transcranial photobiomodulation (tPBMT), or transcranial laser therapy, has shown promise as a treatment for cognitive impairment in rodent AD investigations and several human AD clinical trials. Aim: The purpose of this prospective case series was to evaluate the effect of transcranial photobiomodulation (tPBMT) on cognitive scores when applied to senior dogs with CCD over a 60-day period. Methods: Five senior (>9-year-old) dogs with moderate (16-33) to severe (>33) cognitive scores were enrolled. Owners were instructed on the use of a Class IM laser device and administered a specific dose of laser energy transcranially to both sides of the patient's head, 3 times per week for one month and 2 times per week for a second month. No additional therapeutic measures aimed at enhancing cognitive ability were permitted during the 60-day evaluation time. Baseline cognitive scores were compared with scores obtained at 30-and 60-days post-treatment. Results: Cognitive scores showed improvement in 4/5 dogs at 30 days (27.6% reduction) and all dogs at 60 days (43.4% reduction). There were no adverse effects attributable to tPBMT. Conclusion: Results of our small case series suggest that tPBMT may improve cognitive scores in dogs with moderate to severe CCD by 30 days of application and the improvement is sustained at 60 days. Further studies are needed to ascertain optimal tPBMT protocols for CCD. [Open Vet J 2024; 14(5.000): 1167-1171]

No study has systematically investigated the public's perceptions of cybersecurity regulation, data generated by Autonomous Vehicles (AVs), and their relationship with the acceptance of AVs. To fill this knowledge gap, we conducted an exploratory study on public perceptions of cybersecurity regulation and consumer data in AVs acceptance by surveying nationally representative individuals from four OECD countries (US, UK, Australia, and New Zealand). A total of 2062 responses collected from the survey underwent Exploratory Factor Analysis (EFA) to examine constructs such as Cybersecurity Regulation, Data Sharing, Data Usage, Data Concerns, and intention to use AVs. Correlation analysis further explored the relationships between these constructs, while Mann-Whitney U and Kruskal-Wallis H tests assessed the significance of differences across participant groups.The empirical findings indicate that 80% of respondents agreed on the necessity of cybersecurity regulation for AV operations, with 67% perceiving it as a means to enhance AV safety. Surprisingly, 66% supported cybersecurity regulation despite the potential risk of exposing their personal information. Individuals who are more willing to share AV data also expressed a higher likelihood of using AVs. Furthermore, those who agreed more with cybersecurity regulations were more inclined to be compensated for their data transmission while expressing concerns about data storage and processing. Moreover, around 53% of participants feel they should be compensated for sharing their AV data, with 68% expressing concern about AVs' data storage and processing and 71% supporting the destruction of AV data post-sale. Regarding data privacy concerns, “In-vehicle Private Conversation” draws notable attention, rated very important or extremely important by 64% of the participants. The findings highlight the importance of cybersecurity regulation, data sharing, and data concerns in shaping individuals' intentions to use AVs, as well as the influence of socio-technological attributes.

Objective: In this article we present a conceptual framework for enhancing effective healthcare communication in Australia and Aotearoa New Zealand. Methods: Through an iterative, deliberative dialogue approach, we, as experts from a variety of health professions and academic disciplines, worked together to identify core values and considerations for healthcare communication across numerous health professions and disciplines and within research, teaching, policy, and practice contexts. Results: The framework developed includes five core values at its centre: equitable, inclusive, evidence-based, collaborative, reflective. Around this are concentric circles showing key elements of collaborators, modality, context, and purpose. Each of these is explored. Conclusion: This work may support benchmarking for healthcare providers, researchers, policymakers, and educators across a breadth of professions to help improve communication in clinical practice. The framework will also help to identify areas across disciplines that are shared and potentially idiosyncratic for various professions to promote interprofessional recognition, education, and collaboration. Innovation: This framework is designed to start conversations, to form the foundation of a dialogue about the priorities and key considerations for developing teaching curricula, professional development, and research programs related to healthcare communication, providing a set of values specifically for the unique contexts of Australia and Aotearoa New Zealand. It can also be used to guide interdisciplinary healthcare professionals in advancing research, teaching, policy, and practice related to healthcare communication.

Abstract The digital transformation of Automated Vehicles (AVs) has raised concerns in the cyber realm among prospective AV consumers. However, there is a dearth of empirical research on how cyber obstacles may impact the operation of AVs. To address this knowledge gap, this study examines the six critical cyber impediments (data privacy, AV connectivity, ITS infrastructure, lack of cybersecurity regulations, AV cybersecurity understanding, and AV cyber-insurance) that influence the deployment of AVs. The impact of gender, age, income level, and individual AV and cybersecurity knowledge on these obstacles are statistically assessed using a sample of 2061 adults from the United States, the United Kingdom, New Zealand, and Australia. The research revealed intriguing empirical findings on all cyber barriers in the form of a trichotomy: participants' education level, understanding of AVs, and cybersecurity knowledge. As education levels increase, the significance of a cyber barrier to AV deployment decreases; however, as AV comprehension and cybersecurity knowledge increase, the perception of a cyber barrier becomes significantly more important. In addition, the study demonstrates differences in perceptions of cyber barriers and AV deployments based on gender, age, income, and geographic location. This study's findings on cyber barriers and AV deployment have implications for academia and industry.

Alzheimer’s disease (AD) is a common degenerative brain disorder of aging people which shares many clinical and pathological features with canine cognitive dysfunction (CCD). CCD is considered a naturally occurring model of human AD. Transcranial photobiomodulation (tPBMT) therapy, also known as transcranial laser therapy, entails delivering photons of near infrared to infrared light from the skin surface of the scalp to the underlying brain. Specific molecular cellular receptors, called chromophores, absorb this energy, and use it to initiate biological reactions with potential therapeutic benefit. Improvement in cognitive ability using tPBMT has been documented in rodent AD models and human clinical trials. The purposes of this review are to provide an overview of the suspected molecular mechanisms of action of tPBMT for treatment of cognitive decline and to propose potential application of this treatment modality for dogs affected by CCD.

In order to ensure the normal and stable flights in the aircraft, a variety of sensors and corresponding instrumentation systems have been applied on the aircraft to monitor/control the current flight status, and the resulted data ensure the flight safety with a heavy burden on the pilot. In views of this, nowadays, the aircraft cockpit automation assistance system has become a hot topic. This paper is based on the pilot's future operational behavior which can be predicted through different stages of flight operations after the automated assistance system is triggered, thus providing the pilot with assistance in accordance with his operating habits. We have established a MDP (Markov Decision Process) model via analyzing and modeling of pilot operational behavior and mission requirements for flight processes, and we also use value iterative algorithm to find the optimal prediction sequence, lastly, we verify the operability of the algorithm by flight operation simulation experiment. It provides a new solution for the safety of pilot operations and the intrusiveness of the cockpit adaptive automation assistance system.

Abstract Background A large proportion of the world’s tropical peatlands occur in Indonesia where rapid conversion and associated losses of carbon, biodiversity and ecosystem services have brought peatland management to the forefront of Indonesia’s climate mitigation efforts. We evaluated peat volume from two commonly referenced maps of peat distribution and depth published by Wetlands International (WI) and the Indonesian Ministry of Agriculture (MoA), and used regionally specific values of carbon density to calculate carbon stocks. Results Peatland extent and volume published in the MoA maps are lower than those in the WI maps, resulting in lower estimates of carbon storage. We estimate Indonesia’s total peat carbon store to be within 13.6 GtC (the low MoA map estimate) and 40.5 GtC (the high WI map estimate) with a best estimate of 28.1 GtC: the midpoint of medium carbon stock estimates derived from WI (30.8 GtC) and MoA (25.3 GtC) maps. This estimate is about half of previous assessments which used an assumed average value of peat thickness for all Indonesian peatlands, and revises the current global tropical peat carbon pool to 75 GtC. Yet, these results do not diminish the significance of Indonesia’s peatlands, which store an estimated 30% more carbon than the biomass of all Indonesian forests. The largest discrepancy between maps is for the Papua province, which accounts for 62–71% of the overall differences in peat area, volume and carbon storage. According to the MoA map, 80% of Indonesian peatlands are

Abstract Understanding soil systems is critical because they form the structural and nutritional foundation for plants and thus every terrestrial habitat and agricultural system. In this paper, we encourage increased use of mathematical models to drive forward understanding of interactions in soil ecological systems. We discuss several distinctive features of soil ecosystems and empirical studies of them. We explore some perceptions that have previously deterred more extensive use of models in soil ecology and some advances that have already been made using models to elucidate soil ecological interactions. We provide examples where mathematical models have been used to test the plausibility of hypothesized mechanisms, to explore systems where experimental manipulations are currently impossible, or to determine the most important variables to measure in experimental and natural systems. To aid in the development of theory in this field, we present a table describing major soil ecology topics, the theory previously used, and providing key terms for theoretical approaches that could potentially address them. We then provide examples from the table that may either contribute to important incremental developments in soil science or potentially revolutionize our understanding of plant–soil systems. We challenge scientists and mathematicians to push theoretical explorations in soil systems further and highlight three major areas for the development of mathematical models in soil ecology: theory spanning scales and ecological hierarchies, processes, and evolution.

The unaddressed palliative care needs of patients with advanced, nonmalignant, lung disease highlight the urgent requirement for new models of care. This study describes a new integrated respiratory and palliative care service and examines outcomes from this service. The Advanced Lung Disease Service (ALDS) is a long-term, multidisciplinary, integrated service. In this single-group cohort study, demographic and prospective outcome data were collected over 4 years, with retrospective evaluation of unscheduled healthcare usage. Of 171 patients included, 97 (56.7%) were male with mean age 75.9 years and 142 (83.0%) had chronic obstructive pulmonary disease. ALDS patients had severely reduced pulmonary function (median (interquartile range (IQR)) forced expiratory volume in 1 s 0.8 (0.6–1.1) L and diffusing capacity of the lung for carbon monoxide 37.5 (29.0–48.0) % pred) and severe breathlessness. All patients received nonpharmacological breathlessness management education and 74 (43.3%) were prescribed morphine for breathlessness (median dose 9 mg·day−1). There was a 52.4% reduction in the mean number of emergency department respiratory presentations in the year after ALDS care commenced (p=0.007). 145 patients (84.8%) discussed and/or completed an advance care plan. 61 patients died, of whom only 15 (24.6%) died in an acute hospital bed. While this was a single-group cohort study, integrated respiratory and palliative care was associated with improved end-of-life care and reduced unscheduled healthcare usage.