Donor genetic determinant of thymopoiesis, rs2204985, and stem cell transplantation outcome in a multipopulation cohort

\ua9 2024 The Author(s)Background: A genetic polymorphism, rs2204985, has been reported to be associated with the diversity of T-cell antigen receptor repertoire and TREC levels, reflecting the function of the thymus. As the thymus function can be assumed to be an important factor regulating the outcome of stem cell transplantation (SCT), it was of great interest that rs2204985 showed a genetic association to disease-free and overall survival in a German SCT donor cohort. Tools to predict the outcome of SCT more accurately would help in risk assessment and patient safety. Objective: To evaluate the general validity of the original genetic association found in the German cohort, we determined genetic associations between rs2204985 and the outcome of SCT in 1,473 SCT donors from four different populations. Study design: Genetic associations between rs2204985 genotype AA versus AG/GG and overall survival (OS) and disease-free survival (DFS) in 1,473 adult, allogeneic SCT from Finland, the United Kingdom, Spain, and Poland were performed using the Kaplan-Meier analysis and log-rank tests. We adjusted the survival models with covariates using Cox regression. Results: In unrelated SCT donors (N = 425), the OS of genotype AA versus AG/GG had a trend for a similar association (p = 0.049, log-rank test) as previously reported in the German cohort. The trend did not remain significant in the Cox regression analysis with covariates. No other associations were found. Conclusion: Weak support for the genetic association between rs2204985, previously also associated with thymus function, and the outcome of SCT could be found in a cohort from four populations

Using animal-mounted sensor technology and machine learning to predict time-to-calving in beef and dairy cows

Worldwide, there is a trend towards increased herd sizes, and the animal-to-stockman ratio is increasing within the beef and dairy sectors; thus, the time available to monitoring individual animals is reducing. The behaviour of cows is known to change in the hours prior to parturition, for example, less time ruminating and eating and increased activity level and tail-raise events. These behaviours can be monitored non-invasively using animal-mounted sensors. Thus, behavioural traits are ideal variables for the prediction of calving. This study explored the potential of two sensor technologies for their capabilities in predicting when calf expulsion should be expected. Two trials were conducted at separate locations: (i) beef cows (n = 144) and (ii) dairy cows (n = 110). Two sensors were deployed on each cow: (1) Afimilk Silent Herdsman (SHM) collars monitoring time spent ruminating (RUM), eating (EAT) and the relative activity level (ACT) of the cow, and (2) tail-mounted Axivity accelerometers to detect tail-raise events (TAIL). The exact time the calf was expelled from the cow was determined by viewing closed-circuit television camera footage. Machine learning random forest algorithms were developed to predict when calf expulsion should be expected using single-sensor variables and by integrating multiple-sensor data-streams. The performance of the models was tested using the Matthew’s correlation coefficient (MCC), the area under the curve, and the sensitivity and specificity of predictions. The TAIL model was slightly better at predicting calving within a 5-h window for beef cows (MCC = 0.31) than for dairy cows (MCC = 0.29). The TAIL + RUM + EAT models were equally as good at predicting calving within a 5-h window for beef and dairy cows (MCC = 0.32 for both models). Combining data-streams from SHM and tail sensors did not substantially improve model performance over tail sensors alone; therefore, hour-by-hour algorithms for the prediction of time of calf expulsion were developed using tail sensor data. Optimal classification occurred at 2 h prior to calving for both beef (MCC = 0.29) and dairy cows (MCC = 0.25). This study showed that tail sensors alone are adequate for the prediction of parturition and that the optimal time for prediction is 2 h before expulsion of the calf

The longitudinal NIHR ARC North West Coast Household Health Survey: exploring health inequalities in disadvantaged communities.

BACKGROUND: The Household Health Survey (HHS) was developed to understand the socioeconomic determinants of mental and physical health, and health inequalities in health and social care. This paper aims to provide a detailed rationale of the development and implementation of the survey and explore socio-economic variations in physical and mental health and health care. METHODS: This comprehensive longitudinal public health survey was designed and piloted in a disadvantaged area of England, comprising questions on housing, physical health, mental health, lifestyle, social issues, environment, work, and finances. After piloting, the HHS was implemented across 28 neighbourhoods - 10 disadvantaged neighbourhoods for learning (NfLs), 10 disadvantaged comparator sites, and eight relatively advantaged areas, in 2015 and 2018. Participants were recruited via random sampling of households in pre-selected neighbourhoods based on their areas of deprivation. RESULTS: 7731 residents participated in Wave 1 (N = 4319) and 2 (n = 3412) of the survey, with 871 residents having participated in both. Mental health, physical health, employment, and housing quality were poorer in disadvantaged neighbourhoods than in relatively advantaged areas. CONCLUSIONS: This survey provides important insights into socio-economic variations in physical and mental health, with findings having implications for improved care provision to enable residents from any geographical or socio-economic background to access suitable care

Odd Frequency Pairing in the Kondo Lattice

We discuss the possibility that heavy fermion superconductors involve odd-frequency pairing of the kind first considered by Berezinskii. Using a toy model for odd frequency triplet pairing in the Kondo lattice we are able to examine key properties of this new type of paired state. To make progress treating the strong $n_f=1$ constraint in the Kondo lattice model we use the technical trick of a Majorana representation of the local moments, which permits variational treatments of the model without a Gutzwiller approximation. The simplest mean field theory involves the development of bound states between the local moments and conduction electrons, characterized by a spinor order parameter. We show that this state is a stable realization of odd frequency triplet superconductivity with surfaces of gapless excitations whose spin and charge coherence factors vanish linearly in the quasiparticle energy. A $T^3$ NMR relaxation rate coexists with a linear specific heat. We discuss possible extensions of our toy model to describe heavy fermion superconductivity.Comment: 67 page

Expert Elicitation on Wind Farm Control

Wind farm control is an active and growing field of research in which the control actions of individual turbines in a farm are coordinated, accounting for inter-turbine aerodynamic interaction, to improve the overall performance of the wind farm and to reduce costs. The primary objectives of wind farm control include increasing power production, reducing turbine loads, and providing electricity grid support services. Additional objectives include improving reliability or reducing external impacts to the environment and communities. In 2019, a European research project (FarmConners) was started with the main goal of providing an overview of the state-of-the-art in wind farm control, identifying consensus of research findings, data sets, and best practices, providing a summary of the main research challenges, and establishing a roadmap on how to address these challenges. Complementary to the FarmConners project, an IEA Wind Topical Expert Meeting (TEM) and two rounds of surveys among experts were performed. From these events we can clearly identify an interest in more public validation campaigns. Additionally, a deeper understanding of the mechanical loads and the uncertainties concerning the effectiveness of wind farm control are considered two major research gaps

What are the social predictors of accident and emergency attendance in disadvantaged neighbourhoods? Results from a cross-sectional household health survey in the north west of England.

OBJECTIVES: The aim of this study was to identify the most important determinants of accident and emergency (A&E) attendance in disadvantaged areas. DESIGN, SETTING AND PARTICIPANTS: A total of 3510 residents from 20 disadvantaged neighbourhoods in the North West Coast area in England completed a comprehensive public health survey. MAIN OUTCOME MEASURES: Participants were asked to complete general background information, as well as information about their physical health, mental health, lifestyle, social issues, housing and environment, work and finances, and healthcare service usage. Only one resident per household could take part in the survey. Poisson regression analysis was employed to assess the predictors of A&E attendance frequency in the previous 12 months. RESULTS: 31.6% of the sample reported having attended A&E in the previous 12 months, ranging from 1 to 95 visits. Controlling for demographic and health factors, not being in employment and living in poor quality housing increased the likelihood of attending an A&E service. Service access was also found to be predictive of A&E attendance insofar as there were an additional 18 fewer A&E attendances per 100 population for each kilometre closer a person lived to a general practitioner (GP) practice, and 3 fewer attendances per 100 population for each kilometre further a person lived from an A&E department. CONCLUSIONS: This is one of the first surveys to explore a comprehensive set of socio-economic factors as well as proximity to both GP and A&E services as predictors of A&E attendance in disadvantaged areas. Findings from this study suggest the need to address both socioeconomic issues, such as employment and housing quality, as well as structural issues, such as public transport and access to primary care, to reduce the current burden on A&E departments

MAGE expression in head and neck squamous cell carcinoma primary tumors, lymph node metastases and respective recurrences-implications for immunotherapy

Melanoma associated antigens (MAGE) are potential targets for immunotherapy and have been associated with poor overall survival (OS) in head and neck squamous cell carcinoma (HNSCC). However, little is known about MAGE in lymph node metastases (LNM) and recurrent disease (RD) of HNSCC. To assess whether MAGE expression increases with metastasis or recurrence, a tissue microarray (TMA) of 552 primary tumors (PT), 219 LNM and 75 RD was evaluated by immunohistochemistry for MAGE antigens using three monoclonal antibodies to multiple MAGE family members. Mean expression intensity (MEI) was obtained from triplicates of each tumor specimen. The median MEI compared between PT, LNM and RD was significantly higher in LNM and RD. In paired samples, MEI was comparable in PT to respective LNM, but significantly different from RD. Up to 25% of patients were negative for pan-MAGE or MAGE-A3/A4 in PT, but positive in RD. The prognostic impact of MAGE expression was validated in the TMA cohort and also in TCGA data (mRNA). OS was significantly lower for patients expressing pan-MAGE or MAGE-A3/A4 in both independent cohorts. MAGE expression was confirmed as a prognostic marker in HNSCC and may be important for immunotherapeutic strategies as a shared antigen

A systematic review of digital access to post-diagnostic health and social care services for dementia

Objectives For many people with dementia and unpaid carers, using technology for care and support has become essential. Rapid proliferation of technology highlights the need to understand digital access to health and social care services for dementia. This mixed-methods systematic review aims to explore digital access to health and social care services for dementia, from the perspective of people with dementia and unpaid carers. Methods Nine electronic databases were searched in May 2023 for qualitative, quantitative, or mixed-method studies, published in English or German, focused on experiences of using technology-delivered health and social care services for people with dementia and unpaid carers. After removal of duplicates and screening, 44 empirical papers were included. Results From the 44 studies, findings were grouped into five categories, highlighting experiences for people with dementia and unpaid carers: (1) Adapting to technology, (2) Inequalities and variations in outcomes, (3) Impact on caring, (4) Impact on health, and (5) Impact on relationships. Proliferation of technology in care access emphasised the need for quick adaptation to technology and examination of its impact. The impact of such service delivery has evidenced mixed findings. There were improvements in the health and wellbeing of people with dementia and unpaid carers, and benefits for their dyadic relationship. However, using technology for health and social care access is not always possible and is often reliant on unpaid carers for support. Lower tech-literacy, lack of equipment or money to buy equipment and poor internet connection can impact the potential for positive outcomes. Conclusions Technology can bring great benefits: social inclusion, improved service access and care. However, using technology in service delivery in dementia needs careful thought. Professionals and service providers need to be cognizant of the complex nature of dementia, and the benefits and challenges of hybrid service delivery