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Examining the moderating effects of biopsychosocial factors on the relationship between HIV-related depression and cognitive function among adolescents living with HIV in Tanzania: A protocol for an analytical cross-sectional study

Background Adolescents living with HIV face unique challenges, including mental health issues such as depression and cognitive dysfunction. Despite this significant burden, there is a lack of evidence focusing on this population. This study therefore aims to examine the moderating effects of biopsychosocial factors on the bi-directional relationship between HIV-related depression and cognitive function among adolescents living with HIV in the Mbeya region, Tanzania. Methods The analytical cross-sectional study will be conducted in public healthcare facilities in the Mbeya region, involving 207 adolescents living with HIV who will be selected using a systematic random sampling technique. Depression will be assessed using a standardized PHQ-9 tool, while cognitive functioning will be evaluated using a validated Montreal Cognitive Assessment Tool Version 8.3. A biopsychosocial model will be used to guide this study. Descriptive statistics will be used to describe the frequency distribution of the study variables, a chi-square test will be used to describe the relationship between the variables and a binary logistic regression model will be used to predict the moderating effects of biopsychosocial factors on the relationship between HIV-related depression and cognitive function. The odds ratio and a 95% confidence interval will be reported, and the p-value of 0.05 will be considered statistical significance. This study is expected to be conducted for three months. The high prevalence of mental health issues among HIV-positive adolescents, the detrimental effect of HIV on cognitive development, and the lack of studies focused on this population raised the need to conduct this study. Discussion The findings of this study will inform the development of a comprehensive integrated care model that addresses both the mental and cognitive aspects of living with HIV during adolescence. Moreover, the identification of factors associated with depression and cognitive performance will help healthcare providers in identifying at-risk adolescents and proper management of the conditions. This study’s results will also help reveal areas that need in-depth exploration that will lead to a better understanding of the responsible factors.

Factors associated with trunk skeletal muscle thickness and echo intensity in young Japanese men and women

The present study examined factors associated with trunk skeletal muscle thickness (MT, an index for the amount of skeletal muscle) and echo intensity (EI, an index for the content of non-contractile tissue, such as intramuscular adipose tissue) in young Japanese men and women in consideration of habitual dietary intake. Healthy men (n = 26) and women (n = 24) aged 20 to 26 were enrolled. Trunk MT and EI were evaluated using ultrasound imaging at the height of the 3rd lumbar vertebra. In addition to morphological variables, brachial-ankle pulse wave velocity (baPWV) and blood properties (e.g., triglycerides, total cholesterol, and fasting blood glucose) were measured. Habitual dietary intake was also evaluated by a self-administered diet history questionnaire. The results obtained for young men revealed significant correlations between trunk MT/body mass1/3 and the percentages of energy from polyunsaturated fatty acids (rs = 0.476, p <0.05) and carbohydrates (rs = -0.402, p <0.05). Trunk EI significantly and positively correlated with the percentage of energy from saturated fatty acids (rs = 0.397, p <0.05). In young women, trunk EI showed a significant and positive correlation with baPWV (rs = 0.504, p <0.05). These results suggest that the effects of habitual dietary intake on trunk skeletal muscle differ between young men and women.

Influence mechanism of Internet use on the physical and mental health of the Chinese elderly—Based on Chinese General Social Survey

Based on Chinese General Social Survey data (CGSS 2021), binary logistic regression and stepwise regression were used to explore how Internet use improves the physical and mental health of elderly people and its influence mechanisms. The research found that Internet use has a positive and significant impact on the physical and mental health of the Chinese elderly, and the results are robust with variable replacement and model replacement tests. In its influence mechanism, it found that Internet use promotes the physical and mental health of elderly people through physical exercise, social interaction, and learning frequency, which have a partial mediating effect. The effectiveness of the Internet use in promoting physical and mental health of the Chinese elderly through learning frequency is higher than physical exercise and social interaction, highlighting the importance of continuous learning for the Chinese elderly in the digital age. At the same time, Internet use has an unequal influence on the physical and mental health of the Chinese elderly, and has a greater influence on the mental health of the elderly with higher socio-economic status. Therefore, the research proposes the following three suggestions. First, improve the popularity of Internet use among the Chinese elderly. Second, accelerate the development of Internet application products suitable for the Chinese elderly. Third, provide Internet education for different regions elderly groups, and implement targeted assistance for elderly people with poor socio-economic status.

Correction: The VertiGO! Trial protocol: A prospective, single-center, patient-blinded study to evaluate efficacy and safety of prolonged daily stimulation with a multichannel vestibulocochlear implant prototype in bilateral vestibulopathy patients

The use of miniaturised Bluetooth Low Energy proximity loggers to study contacts among small rodents in agricultural settings

Small rodents can cause problems on farms such as infrastructure damage, crop losses or pathogen transfer. The latter threatens humans and livestock alike. Frequent contacts between wild rodents and livestock favour pathogen transfer and it is therefore important to understand the movement patterns of small mammals in order to develop strategies to prevent damage and health issues. Miniaturised proximity loggers are a newly developed tool for monitoring spatial behaviour of small mammals. The strength of the Bluetooth Low Energy (BLE) signal can be used as an indicator of close contacts between wild rodents and livestock feeding sites, which is relevant for identifying possible transmission routes. This method study focussed on the use of the technology in an agricultural setting as well as dry runs for testing and calibrating this technology in farming environments used for animal husbandry. Results show that the battery life of the loggers was mainly influenced by the pre-set scan interval. Short scan intervals resulted in reduced battery lifespan and should be maximised according to the activity patterns of the target species. Habitat affects BLE signal strength resulting in higher signal strength indoors than outdoors. The height of the location of the loggers positively affected signal strength in livestock stables. Signal reception generally decreased with increasing distance and differed among loggers making calibration necessary. Within habitat specific distances, BLE proximity logging systems can identify contacts among small mammals and between animals and particular structures of interest. These results support the use of BLE based systems in animal husbandry environments and contribute to a body of evidence of validated techniques. In addition, such approaches can provide valuable insights into possible pathogen transmission routes.

Current food trade helps mitigate future climate change impacts in lower-income nations

The risk of national food supply disruptions is linked to both domestic production and food imports. But assessments of climate change risks for food systems typically focus on the impacts on domestic production, ignoring climate impacts in supplying regions. Here, we use global crop modeling data in combination with current trade flows to evaluate potential climate change impacts on national food supply, comparing impacts on domestic production alone (domestic production impacts) to impacts considering how climate change impacts production in all source regions (consumption impact). Under 2°C additional global mean warming over present day, our analysis highlights that climate impacts on national supply are aggravated for 53% high income and 56% upper medium income countries and mitigated for 60% low- and 71% low-medium income countries under consumption-based impacts compared to domestic impacts alone. We find that many countries are reliant on a few mega-exporters who mediate these climate impacts. Managing the risk of climate change for national food security requires a global perspective, considering not only how national production is affected, but also how climate change affects trading partners.

Repellency and toxicity of long-lasting insecticide-treated bed nets (LLINs) to bed bugs

Vector control is essential for eliminating malaria, a vector-borne parasitic disease responsible for over half a million deaths annually. Success of vector control programs hinges on community acceptance of products like long-lasting insecticide-treated nets (LLINs). Communities in malaria-endemic regions often link LLIN efficacy to their ability to control indoor pests such as bed bugs (Cimex lectularius L. and Cimex hemipterus (F.)) (Hemiptera: Cimicidae). Despite this, little is known about the potential repellent effects and toxicity of LLINs to bed bugs. Herein, we demonstrate for the first time that commonly deployed LLINs lack olfactory and contact-based repellency to host-seeking C. lectularius from both insecticide-susceptible and insecticide-resistant populations. One LLIN (PermaNet Dual) was significantly attractive to both populations when exposed olfactorily, but not in contact assays, highlighting the complexity of bed bug-LLIN interactions. The insecticide resistant bed bugs experienced low mortality in 4 d of continuous exposure to LLINs. These results suggest that LLINs would likely not repel or eliminate bed bug infestations in malaria-endemic communities, further selecting for insecticide resistance and potentially disrupting vector control programs.

Characteristics of split-step skills of the world’s top athletes in badminton

Objective The purpose of this study was to quantitatively measure the split-step skills of the world’s top badminton players to clarify the characteristics underlying these skills when moving into the forehand position in the rear court. Methods We analyzed the four best ranking players (1st to 4th) in the men’s singles competition at the World Badminton Federation (BWF) World Championships 2023, a world tournament whose match videos are available online. Analysis 1 was conducted to determine the location of the players’ feet on the court when performing a split-step while moving to the forehand rear court, as well as the width of the stance and the reaction time from that stance to taking the first step. To define the characteristics of top athletes, the split-step skill performance of these athletes was evaluated during play. Analysis 2 was used to determine whether the performance of the split-step when moving to the forehand rear court varied depending on the position of the opposing player. Results Analysis 1 showed that the split-step position was gathered close to the base, with an average split-step reaction time of 0.25 s and a split-step stance width comprising 50% of the players’ height. These results were similar among all top players evaluated. Analysis 2 showed that the difference in the number of shuttlecocks that hit the opponent’s backhand rear court (LR) affected their degree of split-step skill. Conclusion In this study, we quantitatively measured the split-step skills of the world’s top badminton athletes and clarified the characteristics of their positioning into the forehand rear court during active play. Herein, movement and performance analysis using match videos available online was used to gain novel insights into the performance of these athletes.

De novo transcriptome assembly and discovery of drought-responsive genes in white spruce (Picea glauca)

Forests face an escalating threat from the increasing frequency of extreme drought events driven by climate change. To address this challenge, it is crucial to understand how widely distributed species of economic or ecological importance may respond to drought stress. In this study, we examined the transcriptome of white spruce (Picea glauca (Moench) Voss) to identify key genes and metabolic pathways involved in the species’ response to water stress. We assembled a de novo transcriptome, performed differential gene expression analyses at four time points over 22 days during a controlled drought stress experiment involving 2-year-old plants and three genetically distinct clones, and conducted gene enrichment analyses. The transcriptome assembly and gene expression analysis identified a total of 33,287 transcripts corresponding to 18,934 annotated unique genes, including 4,425 genes that are uniquely responsive to drought. Many transcripts that had predicted functions associated with photosynthesis, cell wall organization, and water transport were down-regulated under drought conditions, while transcripts linked to abscisic acid response and defense response were up-regulated. Our study highlights a previously uncharacterized effect of drought stress on lipid metabolism genes in conifers and significant changes in the expression of several transcription factors, suggesting a regulatory response potentially linked to drought response or acclimation. Our research represents a fundamental step in unraveling the molecular mechanisms underlying short-term drought responses in white spruce seedlings. In addition, it provides a valuable source of new genetic data that could contribute to genetic selection strategies aimed at enhancing the drought resistance and resilience of white spruce to changing climates.

Ratio of remnant cholesterol to high-density lipoprotein cholesterol in relation to gestational diabetes mellitus risk in early pregnancy among Korean women

Objective There is no evidence to suggest that an association exists between the remnant cholesterol (RC) to high-density lipoprotein cholesterol (HDL-C) ratio and gestational diabetes mellitus (GDM). In this study, the RC/HDL-C ratio during the first trimester was examined as a potential indicator of the onset of GDM during the second trimester. Methods This was a secondary analysis of data from a Korea-based prospective cohort study. The study involved 582 women within 14 weeks of pregnancy who were examined between November 2014 and July 2016 at two Korean hospitals. RC was calculated as total cholesterol (TC) minus the sum of low-density lipoprotein cholesterol (LDL-C) and HDL-C. The RC/HDL-C ratio was determined by dividing the RC content by the HDL-C content. The RC/HDL-C ratio and GDM occurrence were investigated utilizing a binary logistic regression model, various sensitivity analyses, and subgroup analyses. Additionally, the RC/HDL-C ratio was evaluated using receiver operating characteristic (ROC) analysis. Results The average age of the pregnant women was 32.07 ± 3.78 years, and the RC/HDL-C ratio had a median value of 0.39. The prevalence of GDM was 6.01%. There was a positive association between the RC/HDL-C ratio and the incidence of GDM after adjusting for potential confounding variables (odds ratio: 21.78, 95% confidence interval [CI]: 3.55–133.73, P < 0.001). Furthermore, this association was validated by subgroup and sensitivity analyses. The results indicated that the RC/HDL-C ratio was a robust predictor of GDM, with an area under the ROC curve of 0.795 (95% CI: 0.723–0.868). The optimal threshold value was 0.45, with a sensitivity of 71.4% and a specificity of 75.3%. Compared with traditional lipid markers, including LDL-C, HDL-C, triglycerides, TC, and the emerging marker RC, the RC/HDL-C exhibited higher diagnostic efficacy. Conclusion There is an increased risk of GDM associated with higher levels of the RC/HDL-C ratio between 12 and 14 weeks of gestation, independent of traditional risk factors. The RC/HDL-C ratio is more effective in diagnosing GDM than traditional lipid markers.

Optimization of carbon footprint management model of electric power enterprises based on artificial intelligence

This study intends to optimize the carbon footprint management model of power enterprises through artificial intelligence (AI) technology to help the scientific formulation of carbon emission reduction strategies. Firstly, a carbon footprint calculation model based on big data and AI is established, and then machine learning algorithm is used to deeply mine the carbon emission data of power enterprises to identify the main influencing factors and emission reduction opportunities. Finally, the driver-state-response (DSR) model is used to evaluate the carbon audit of the power industry and comprehensively analyze the effect of carbon emission reduction. Taking China Electric Power Resources and Datang International Electric Power Company as examples, this study uses the comprehensive evaluation method of entropy weight- technique for order preference by similarity to ideal solution (TOPSIS). China Electric Power Resources Company has outstanding performance in promoting renewable energy, with its comprehensive evaluation index rising from 0.5458 in 2020 to 0.627 in 2022, while the evaluation index of Datang International Electric Power Company fluctuated and dropped to 0.421 in 2021. The research conclusion reveals the actual achievements and existing problems of power enterprises in energy saving and emission reduction, and provides reliable carbon information for the government, enterprises, and the public. The main innovation of this study lies in: using artificial intelligence technology to build a carbon footprint calculation model, combining with the data of International Energy Agency Carbon Dioxide (IEA CO2) emission database, and using machine learning algorithm to deeply mine the important factors in carbon emission data, thus putting forward a carbon audit evaluation system of power enterprises based on DSR model. This study not only fills the blank of carbon emission management methods in the power industry, but also provides a new perspective and basis for the government and enterprises to formulate carbon emission reduction strategies.

Properties characterization and microstructural analysis of alkali-activated solid waste-based materials with sawdust and wastewater integration

Construction materials are significantly exposed to ecological hazards due to the presence of hazardous chemical constituents found in industrial and agricultural solid wastes. This study aims to investigate the use of sawdust particles (SDPs) and sawdust wastewater (SDW) in alkali-activated composites (AACs) made from a mixture of different silicon-aluminum-based solid wastes (slag powder-SP, red mud-RM, fly ash-FA, and carbide slag-CS). The study examines the impact of SDP content, treated duration of SDPs, and SDW content on both fresh and hardened properties of the AACs, including electrical conductivity, fluidity, density, flexural and compressive strengths, and drying shrinkage. The study also analyzes the microstructures and product compositions of the AACs influenced by SDW through a comprehensive analysis of microstructures and product compositions by using XRD, SEM-EDS, and FTIR. The results show that treating SDPs with a 2.5 mol/L NaOH solution for 12 hours decreases the fluidity and electrical conductivity of the AACs but improves their flexural and compressive strengths. Additionally, in the synthesis of a composite material incorporating binder materials SP, RM, and FA in a mass ratio of 10:3:18, a 2.0 mol/L NaOH solution is employed. The liquid-to-solid ratio is maintained at 20:31, and the sand-to-binder ratio is set at 3:1. The substitution of 12.28% SDW to NaOH solution improves the resistance to drying shrinkage and long-term mechanical strength development of the AACs. Interestingly, the addition of SDW does not affect the product compositions due to the generation and decomposition of organic acid salts from organic impurities in the acidic SDW during long-term curing at room temperature. These findings provide valuable insights for the sustainable recycling of bioresources and solid wastes containing silicon-aluminum in construction materials.

Turning the spotlight: Hostile behavior in creative higher education and links to mental health in marginalized groups

Hostile, discriminatory, and violent behavior within the creative industries has attracted considerable public interest and existing inequalities have been discussed broadly. However, few empirical studies have examined experiences of hostile behavior in creative higher education and associated mental health outcomes of early career artists. To address this gap, we conducted a survey among individuals studying at higher education institutions for art and music (N = 611). In our analyses of different types of hostile behaviors and their associations with mental health and professional thriving, we focused on differences and similarities between marginalized and more privileged groups across multiple diversity domains. A substantial percentage of participants reported hostile behaviors in their creative academic environments. Individuals from marginalized groups reported more hostile behaviors, which partially explained their worse mental health and lower professional thriving. These findings indicate a clear need for the creative sector to implement strategies to create safer environments, particularly for early career artists from specific socio-demographic backgrounds. We conclude by suggesting strategies for prevention in this highly competitive industry.

Weeds and agro by-products for sustainable farming of edible field cricket, Gryllus madagascarensis (Orthoptera: Gryllidae)

Gryllus madagascarensis (Orthoptera: Gryllidae) is a cricket species that shows promise to mitigate food insecurity and malnutrition. But whether this species will accept low- to no-cost weeds and agro by-products as feed, and how these feeds affect its performance, remains unknown. This study assessed the acceptability of 66 weed species and agro by-products (derived from a single plant species) by adult G. madagascarensis and compared the results to a reference feed (chicken feed). We further examined how the 11 top acceptable single plant products affected growth parameters of G. madagascarensis. The parameters assessed included development, survivorship, body mass and body length and reproductive fitness of the crickets on each of these diets. Finally, the costs of the 11 top accepted single plant products were compared. Our results demonstrated that the cricket accepted all 66 single plant products at varying degrees. Tropical white morning glory (Ipomoea alba), cassava tops (Manhot esculentum), taro leaves (Colocasia esculenta), cowpea bran (Vigna unguiculata), American hog-peanut (Afroamphica africana), gallant soldier (Galinsoga parviflora), wheat bran (Triticum aestivum), glycine (Neonotonia wightii), silver leaf Desmodium (Desmodium uncinatum), maize bran (Zea mays) and rice bran (Oryza sativa) were the most accepted. The analysed nutrient content varied across the top 11 accepted single plant products and the reference feed. The shortest development and highest survival rate were recorded with gallant soldier and cowpea bran powders. Wet body mass and body length were highly impacted by various single plant products tested compared to the reference feed. Reproductive parameters were significantly briefer on tropical white morning glory compared to other feeds and the reference diet. Single plant products cost two- to four-fold less than reference feed. The findings are valuable for developing blended diets that balance performance, cost and availability for household and commercial production of crickets as a “green” technology for producing edible sources of protein.

Parkinson’s disease screening using a fusion of gait point cloud and silhouette features

Parkinson’s Disease (PD) is a neurodegenerative disorder that is often accompanied by slowness of movement (bradykinesia) or gradual reduction in the frequency and amplitude of repetitive movement (hypokinesia). There is currently no cure for PD, but early detection and treatment can slow down its progression and lead to better treatment outcomes. Vision-based approaches have been proposed for the early detection of PD using gait. Gait can be captured using appearance-based or model-based approaches. Although appearance-based gait contains comprehensive features, it is easily affected by factors such as dressing. On the other hand, model-based gait is robust against changes in dressing and external contours, but it is often too sparse to contain sufficient information. Therefore, we propose a fusion of appearance-based and model-based gait features for PD prediction. First, we extracted keypoint coordinates from gait captured in videos and modeled these keypoints as a point cloud. The silhouette images are also segmented from the videos to obtain an overall appearance representation of the subject. We then perform a binary classification of gait as normal or Parkinsonian using a novel fusion of the gait point cloud and silhouette features, obtaining AUC up to 0.87 and F1-Scores up to 0.82 (precision: 0.85, recall: 0.80).

Exploring data literacy self-perception among Indonesian high school students

Data is becoming increasingly ubiquitous today, and data literacy has emerged an essential skill in the workplace. Therefore, it is necessary to equip high school students with data literacy skills in order to prepare them for further learning and future employment. In Indonesia, there is a growing shift towards integrating data literacy in the high school curriculum. As part of a pilot intervention project, academics from two leading Universities organised data literacy boot camps for high school students across various cities in Indonesia. The boot camps aimed at increasing participants’ awareness of the power of analytical and exploration skills, which in turn, would contribute to creating independent and data-literate students. This paper explores student participants’ self-perception of their data literacy as a result of the skills acquired from the boot camps. Qualitative and quantitative data were collected through student surveys and a focus group discussion, and were used to analyse student perception post-intervention. The findings indicate that students became more aware of the usefulness of data literacy and its application in future studies and work after participating in the boot camp. Of the materials delivered at the boot camps, students found the greatest benefit in learning basic statistical concepts and applying them through the use of Microsoft Excel as a tool for basic data analysis. These findings provide valuable policy recommendations that educators and policymakers can use as guidelines for effective data literacy teaching in high schools.

A new extended Chen distribution for modelling COVID-19 data

In this paper, we propose a new flexible statistical distribution, the Topp-Leone Exponentiated Chen distribution, to model real-world data effectively, with a particular focus on COVID-19 data. The motivation behind this study is the need for a more flexible distribution that can capture various hazard rate shapes (e.g., increasing, decreasing, bathtub) and provide better fitting performance compared to existing models such as the Chen and exponentiated Chen distributions. The principal results include the derivation of key statistical properties such as the probability density function, cumulative distribution function, moments, hazard rate function, and order statistics. Maximum likelihood estimation is employed to estimate the parameters of the TLEC distribution, and simulation studies demonstrate the efficiency of the maximum likelihood method. The innovation of this work is further validated by applying the TLEC distribution to real COVID-19 data, where it outperforms several related models. The study concludes with significant insights into how the TLEC distribution provides a more accurate and flexible approach to modeling real-world phenomena.

Factors associated with adherence to antiretroviral therapy among HIV-positive adolescents and young adult patients attending HIV care and treatment clinic at Bombo Hospital in Tanga region-Tanzania

Background Adherence to HIV treatment regimens involves the consistent and correct intake of all prescribed medications. The implementation of antiretroviral therapy (ART) program has significantly reduced mortality among adolescents living with HIV. However, adherence to ART is lower among adolescents compared to other sub-populations and even lower in sub-Saharan Africa. The factors influencing ART adherence are context-specific and vary across countries and regions. In the Tanzanian context, there is a paucity of data regarding these factors. Methodology This cross-sectional study involved 385 adolescents and young adults living with HIV receiving treatment at Bombo Hospital Referral Hospital’s Care and Treatment Clinic, in Tanga, Tanzania. To assess adherence, a one-month self-recall medication adherence scale was used while a structured questionnaire was used to gather data on determinants of adherence. Data were collected using Google Forms and subsequently exported as a Microsoft Excel file. The data were then entered into Stata software version 15 for cleaning for descriptive and logistic regression analyses. Results More than a third (35.3%) of adolescents and young adults living with HIV in Tanga were not adherent to the effective and available ART. Adolescents and young adults living in households experiencing moderate food insecurity were 67% less likely to adhere to ART (95%CI 0.16–0.66) compared to those who were food secure. Those with secondary education were 2.3 times more likely to adhere to ART (95%CI 1.02–5.23), compared to those without formal education. While participants who consistently obtain their ART at the clinic were more 4.2 times more likely to adhere to medication (95%CI 1.29–13.72), those experiencing ART side effects were 39% less likely to adhere to ART (95%CI 0.38–0.98). Conclusion More than one-third of adolescents and young adults were not adherent to ART in Tanga, Tanzania. Addressing such unprecedented challenges calls for efforts targeting adolescents and young adults with limited education, from households with food insecurity, and ensuring counseling and management of ART side effects.

Correction: Genetic differentiation at extreme latitudes in the socially plastic sweat bee Halictus rubicundus

The involvement of Elf5 in regulating keratinocyte proliferation and differentiation processes in skin

Skin and hair development is regulated by multitude of programs of activation and silencing of gene expression to maintain normal skin and hair follicle (HF) development, homeostasis, and cycling. Here, we have identified E74-like factor 5 (Elf5) transcription factor, as a novel regulator of keratinocyte proliferation and differentiation processes in skin. Expression analysis has revealed that Elf5 expression was localised and elevated in stem/progenitor cell populations of both the epidermis (basal and suprabasal) and in HF bulge and hair germ stem cell (SCs) compartments during skin and hair development and cycling. Expressional and functional analysis using RT-qPCR, western blot and colony forming assays, revealed that Elf5 plays an important role in regulating keratinocyte proliferation and differentiation processes as well as potentially determining cell fate by regulating the stem/progenitor cell populations in skin and HFs. These data will provide a platform for pharmacological manipulation of Elf5 in skin, leading to advancements in many areas of research, including stem cell, regenerative medicine, and ageing.