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Prevalence and determinants of chronic kidney disease among community-dwelling adults, 50 years and older in Ireland
No full textBackground. Using the Irish Longitudinal Study on Ageing (TILDA), we evaluated the prevalence and distribution of chronic kidney disease (CKD), and its determinants in order to identify risk groups for population health planning in Ireland. Methods. Data were analysed from Wave 1 (2009–2011) of the TILDA, a national cohort of participants aged 50+ years who had both plasma creatinine and cystatin C measured at baseline. Kidney function was estimated using the 2012 and 2021 Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations. CKD was defined as estimated glomerular filtration rate <60 mL/min/1.73 m2. Multivariable logistic regression explored associations using adjusted odds ratios (OR). Results. Prevalence of CKD was significantly higher using the CKD-EPI 2012(Scr-CysC) compared with the CKD-EPI 2021(Scr-CysC) (14.7% vs 11.3%, respectively). The prevalence was highest in patients with cardiovascular disease (CVD) (33.9%), diabetes (28.0%), cancer (25.5%), urinary incontinence (23.7%), bone diseases (21.5%), hypertension (19.8%) and obesity (19.5%). In multivariable analysis, individuals with hypertension (OR 1.78), diabetes (OR 1.45), CVD (OR 1.43), cancer (OR 1.53), overweight (OR 1.37) and obesity (OR 2.33) experienced greater likelihood of CKD. In addition, individuals with a history of previous hospitalization (OR 1.50), free or subsidized healthcare (OR 1.31), and unemployed individuals (OR 1.86) were also significantly more likely to have CKD. Conclusion. Compared with the national average, the burden of CKD is far greater in older individuals with major chronic conditions and socioeconomic deprivation. The identification and targeting of these groups through national surveillance programmes is likely to yield substantial benefits from more effective disease management and proactive population health planning.</p
A randomized controlled trial of unresisted vs. heavy resisted sprint training programs: effects on strength, jump, unresisted and resisted sprint performance in youth rugby union players
No full textThis study aimed to compare: 1) the effects of a 4-week unresisted vs. resisted sprint training programs (UST and RST with 50% body mass, respectively) on both resisted and unresisted sprint performance; and 2) the effects of these sprint training schemes on various strength-power measures (i.e., one-repetition maximum [1RM] and the isometric squat test (ISqT), eccentric hamstring strength in the Nordic hamstring exercise [NHE], and vertical and horizontal jump distances). Thirty-five under-19 male academy rugby players participated in the study and were randomly assigned to one of the two training groups. Players’ unresisted and resisted (50% BM) 30-m sprint performance, squat 1RM, ISqT, NHE, and jump capabilities were tested on different occasions. Only UST produced a significant reduction in unresisted 30-m sprint time (p < 0.05), whereas both groups exhibited significant changes in resisted sprint times at 10 m and 30 m, as well as maximum velocity (p < 0.005; ES: large). Regarding strength measures, RST led to significant increases in ISqT peak force, horizontal jump distance, and NHE strength (p < 0.011; ES: large). Overall, no significant differences were detected between UST and RST in any of the primary or secondary measures after the intervention. Both training methods were equally effective in improving resisted sprint performance in youth male rugby players. Moreover, UST and RST could be effective options for maintaining or even improving various neuromuscular measures (e.g., dynamic-explosive, isometric, and eccentric strength) when lower limb resistance training is reduced during the competitive season due to the congested schedule.</p
Loneliness and cognition in older adults: A meta-analysis of harmonized studies from the United States, England, India, China, South Africa, Mexico, and Chile
No full textBackground. Loneliness is a risk factor for late-life dementia. There is less consistent evidence of its association with cognitive performance. This study examined the replicability of the association between loneliness and overall and domain-specific cognitive function and informant-rated cognitive decline in cohorts from seven countries: the United States, England, India, China, South Africa, Mexico, and Chile. Methods. Data were from the Harmonized Cognitive Assessment Protocol administered in seven population-based studies (total N > 20,000). Participants reported their loneliness, completed a battery of cognitive tests, and nominated a knowledgeable informant to rate their cognitive decline. Random-effect meta-analyses were used to summarize the associations from each cohort. Results. Loneliness was associated with poor overall cognitive performance and informant-rated cognitive decline controlling for sociodemographic factors (meta-analytic correlation for overall cognition = .10 [95% CI = .13, .06] and informant-rated decline = .16 [95% CI = .14, .17]). Despite some heterogeneity, the associations were significant across samples from Africa, Asia, Europe, North, Central, and South America. The meta-analysis also indicated an association with specific cognitive domains: episodic memory, speed-attention, visuospatial abilities, numeric reasoning, and verbal fluency. The associations were attenuated but persisted when depressive symptoms were added as a covariate. Depression, cognitive impairment, and socio-demographic factors did not consistently moderate the associations across samples. Conclusions. Loneliness is associated with poor performance across multiple domains of cognition and observer-rated cognitive decline, associations that replicated across diverse world regions and cultures.</p
Multi-sensor fusion for efficient and robust UAV state estimation
No full textUAV State estimation is fundamental aspect across a wide range of applications, including robot navigation, autonomous driving, virtual reality, and augmented reality (AR). The proposed research emphasizes the vital role of robust state estimation in ensuring the safe navigation of autonomous UAVs. In this paper, we developed an optimization-based odometry state estimation framework that is compatible with multiple sensor setups. Our evaluation of the system is conducted using inhouse integrated UAV platform outfitted with multiple sensors including stereo cameras, an IMU, LiDAR sensors and GPS-RTK for ground truth comparison. The algorithm delivers robust and consistent UAV state estimation in various conditions including illumination changes, feature or structureless environment or even during degraded Global Positioning System (GPS) signals or total signal loss, where single sensor SLAM mostly fails. The experimental findings demonstrate that the proposed method is superior in compare to current state-of-the-art techniques.</p
Modelling of continuous synthesis of bio-inspired silica particles using gaseous CO2 ☆
No full textBio-inspired route to synthesis of porous silica particles involves fast reactive precipitation (solid–liquid system). The concentration and pH profiles within the reactor determine the properties of produced silica particles and therefore need to be controlled tightly. Unlike conventional synthesis of bio-inspired silica (BIS) using strong aqueous acids, recently we developed a process of synthesizing BIS particles using gaseous CO2. This gas-liquid-solid (G-L-S) system looks promising as it is easy to maintain desired pH profiles and hence control particle properties by manipulating the mass transfer rate. In this work, we present the mathematical model for simulating pH profile and yield in BIS synthesis using CO2. The developed model was used to simulate specific silica synthesis experiments. The model was able to capture the experimental data well. It was then used to carry out several numerical experiments for understanding the sensitivity of BIS synthesis using CO2 to various design and operating parameters. The simulated data was used to train the surrogate models for the silica yield prediction. The models demonstrated good performance with the unseen experimental data. The presented results provide useful insights and guidelines for optimizing CO2 based silica synthesis process. The presented model is generic and may be extended to other similar fast reactions.</p
Bacterial community structure analysis on Listeria monocytogenes inoculated spinach leaves is affected by PCR based methods to exclude chloroplast co-amplification
No full textConsumption of ready-to-eat leafy vegetables has increased in popularity due to their anticipated health benefits, but their consumption also poses a potential health risk in the form of foodborne pathogens. Factors determining growth of pathogens goes beyond plant species and cultivation practice and may include the phyllosphere bacteriome. This study investigated the bacteriome of spinach leaves, stored under EURL challenge conditions for 9 days after inoculation with L. monocytogenes using two methods of excluding chloroplast co-amplification (COMPETE, BLOCK) at the PCR step as well as a post-PCR chloroplast sequence filter option (CONTROL). While all three approaches allowed to charcterize a change of bacterial communities over time, the BLOCK (peptide nucleic acid, pPNA) approach resulted in greater diversity similarities to the CONTROL option. The COMPETE (competing primer) solution with a specifically designed primer to prevent chloroplast amplification had a strong underrepresentation of the phylum Planctomycetota and to a lesser extend underrepresentation of Verrucomicrobiota due to the inheritance of the selected primer region that allowed to deselect chloroplast co-amplification. However, the COMPETE approach achieved a 180-fold reduction in chloroplast co-amplification, while BLOCK only achieved a 40-fold reduction. Higher relative abundances of Pseudomonadaceae and lower numbers of Lactobacillales coincided with higher growth potential of L. monocytogenes from day 7–9, suggesting that particular phylogenetic groups may support or restrict growth of L. monocytogenes. While chloroplast co-amplification with spinach in the present study was relatively modest (<16.3 %), other leafy vegetables may require one of the demonstrated co-amplification prevention solutions. Although the COMPETE solution in the present study was linked to some amplification bias, the approach may be useful when otherwise co-amplification is very high and the demonstrated BLOCK approach with pPNA is insufficient</p
Palladium nanocubes with {100} facets for hydrogen evolution reaction: synthesis, experiment and theory
No full textSpatially separated palladium nanocubes (Pd NCs) terminated by {100} facets are synthesized using direct micelles approach. The stepwise seed-mediated growth of Pd NCs is applied for the first time. The resulting Pd NCs are thoroughly characterized by HR-TEM, XPS, Raman, ATR-FTIR, TGA, and STEM-EDX spectroscopies. Some traces of residual stabilizer (polyvinylpyrrolidone, PVP) attached to the vertices of Pd NCs are identified after the necessary separation-washing procedure, however, it is vital to avoid aggregation of the NCs. Pd NCs are subsequently and uniformly loaded on Vulcan carbon (≈20 wt.%) for the electrochemical hydrogen cycling. By post-mortem characterizations, it is revealed that their shape and size remained very stable after all electrochemical experiments. However, a strong effect of the NCs size on their hydrogen interaction is revealed. Hydrogen absorption capacity, measured as the H:Pd ratio, ranges from 0.28 to 0.48, while hydrogen evolution and oxidation reactions (HER and HOR) kinetics decrease from 15.5 to 4.6 mA.mg Pd−1 between ≈15 and 34 nm of Pd NCs, respectively. Theoretical calculations further reveal that adsorption of H atoms and their penetration into the Pd lattice tailors the NCs electronic structure, which in turn controls the kinetics of HER, experimentally observed by the electrochemical tests. This work may pave the way to the design of highly active electrocatalysts for efficient HER stable for a long reactive time. In particular, obtained results might be transferred to active Pd-alloy-based NCs terminated by {100} facets.</p
In-situ evaluation of hole quality and cutting tool condition in robotic drilling of composite materials using machine learning
No full textThe massive adoption of industrial robots in the manufacturing sector has significantly increased automation of installation and inspection procedures, particularly benefiting the aerospace industry, where large volumes of holes are drilled in each aircraft. However, mechanical drilling remains challenging when dealing with composite materials due to their inherently heterogeneous structure. This work presents a novel approach for in-situ hole quality inspection utilising integrated sensor data of an industrial robotic drill, combined with a machine learning model. Additionally, a novel classification approach for evaluating hole quality is proposed. This study employed a KUKA industrial robot, fitted with a multifunctional end-effector, to drill holes in a composite material used in aerospace applications. An ensemble neural network (ENN) model, which combines an artificial neural network with a genetic algorithm, was used to assess the quality of these drilled holes. The model was specifically developed and tested on the machined holes to relate process input parameters and drilling torques to hole quality. The model predictions were validated with six unseen datasets, of which five were predicted accurately. A full factorial study of the process parameters was conducted using analysis of variance (ANOVA) to investigate the relationship between tool condition and drilling torque. The results of the ANOVA show that tool condition is the largest contributor to drilling torque. The method proposed in this work, which allows real-time monitoring of hole quality, has the potential to improve manufacturing productivity of drilled components while ensuring high-quality end products.</p
Post-buckling behaviour and delamination growth in defected variable angle tow composite laminates
No full textDue to their specific strength and stiffness properties, composite materials are largely used in lightweight structural applications in aerospace, automotive and mechanical engineering. Understanding how these materials fail under service loads is a challenging aspect of designing advanced composite structures. In fact, the failure of composite laminated structures is often governed by complex interactions of multiple interlaminar failure and damage mechanisms. Among them, delamination is one of the damage modes requiring large attention due to the low interlaminar resistance between the different layers comprised in a composite laminate. In addition, this phenomenon may be triggered by defects introduced in the construction phase or by the presence of connections leading to stress concentrations. When coupled with buckling phenomena, delamination inevitably decreases the load-carrying capacity of lightweight composite structures. Variable Angle Tow (VAT) laminates have been proven to improve the buckling and post-buckling response of those structures significantly. However, little is known about the geometrically nonlinear behaviour of VAT composite laminates with delaminations. This work applies the cohesive finite element method to model delamination growth in VAT composite laminates containing initial defects under compressive loading conditions. Numerical simulations investigate the effects of the fibre angle variation on the geometrically nonlinear static response of VAT composite laminates compared to that of their classical straight fibre counterparts.</p
Pre-Clinical rationale for amcenestrant combinations in HER2+/ER+ Breast cancer
No full textHER2-positive/oestrogen receptor-positive (HER2+/ER+) represents a unique breast cancer subtype. The use of individual HER2- or ER-targeting agents can lead to the acquisition of therapeutic resistance due to compensatory receptor crosstalk. New drug combinations targeting HER2 and ER could improve outcomes for patients with HER2+/ER+ breast cancer. In this study, the pre-clinical rationale is explored for combining amcenestrant (Amc), a selective oestrogen receptor degrader (SERD), with HER2-targeted therapies including trastuzumab, trastuzumab-emtansine (T-DM1) and tyrosine kinase inhibitors (TKIs). The combination of Amc and anti-HER2 therapies was investigated in a panel of four HER2+/ER+ cell lines: BT-474, MDA-MB-361, EFM-192a and a trastuzumab resistant variant BT-474-T. Proliferation (IC50 and matrix combination assays) was determined using acid phosphatase assays. HER2/ER and intracellular signalling pathway protein levels/activity were investigated by western blot. Apoptosis was assessed using caspase 3/7 assays. Additivity and synergy were observed between Amc and the TKIs neratinib, lapatinib and tucatinib in all cell lines. Amc increased the anti-proliferative effect of trastuzumab in MDA-MB-361 and BT-474-T. Addition of Amc also increased anti-proliferative efficacy of T-DM1 in BT-474-T. TKI/Amc combinations reduced p-HER2 and ER levels and resulted in increased apoptosis. Higher ER expression in MDA-MB-361 and BT-474-T was associated with greater potential for synergy. In conclusion, the combination of Amc- and HER2-targeted treatments has potential as a therapeutic strategy for the treatment of HER2+/ER+ breast cancer and warrants further clinical investigation to validate safety and efficacy in patients.</p