Dataset on gene expression in the elderly after Mindfulness Awareness Practice or Health Education Program

It has been reported that relaxation techniques can improve physical health and cognitive function. A number of studies involving different types of relaxation practices showed changes in expression of genes. We investigated the gene expression pattern of a cohort of elderly subjects of Asian descent after weekly (for the first three months) and monthly (for the subsequent six months) intervention. Sixty consenting elderly subjects (aged 60–90 years) with mild cognitive impairment were assigned to either the Mindfulness Awareness Practice (MAP) or Health Education Program (HEP) group in a randomized controlled trial to assess the effectiveness of the programs in preventing further cognitive decline and evaluate the influence on neurological, cellular and biochemical factors. Blood samples were collected before the start of intervention and after nine months for gene expression profiling using Affymetrix Human Genome U133 Plus 2.0 arrays. The dataset is publicly available for further analyses

Endovascular Management of Traumatic Iliac Vessel Disruption—Report of Two Cases

AbstractVascular injuries in a multi-trauma patient are associated with significant cardiovascular instability and organ injury. Injuries with active bleeding are best treated with a quick, safe and the least less invasive procedure available to the trauma surgeon. We report two cases of blunt trauma induced common and external iliac vessel injury, managed by endovascular treatment. In the second case, endovascular treatment prevented histological examination of the artery, which would have revealed an alternative diagnosis

Artificial Intelligence-Driven Drug Discovery: Identifying Novel Compounds for Targeted Cancer Therapies

This study delves into the potential of artificial intelligence (AI) in revolutionizing drug discovery, specifically focusing on the identification of new compounds for targeted cancer therapies. Through the application of advanced machine learning algorithms, our methodology achieved impressive predictive accuracy, with an accuracy rate of 92.5%, an AUC-ROC of 0.94, and an AUC-PR of 0.91. The AI models successfully pinpointed 35 novel compounds predicted to demonstrate high efficacy against specific cancer targets, indicating promising prospects for advancements in cancer treatment. Examination of the molecular structures of these identified compounds unveiled positive characteristics, with 90% adhering to Lipinski's Rule of Five, indicating their suitability as potential drug candidates. Additionally, the average predicted half-life of 12 hours suggests advantageous pharmacokinetic properties, bolstering their potential viability. A comparative assessment highlighted the efficiency advantages of the AI-driven approach, revealing an 80% reduction in time and a 65% reduction in costs compared to traditional methods. Beyond its application in targeted cancer therapies, the success of our approach implies broader implications for the pharmaceutical research landscape, offering a more streamlined and accurate methodology. While these outcomes are promising, it is crucial to recognize limitations and stress the importance of sustained collaboration between computational and experimental researchers. Future directions encompass the refinement of models, incorporation of diverse datasets, and rigorous experimental validation. In summary, our study underscores the efficacy of AI-driven drug discovery in identifying new compounds for targeted cancer therapies. The identified compounds, characterized by favorable structural and pharmacokinetic attributes, present a promising avenue for overcoming challenges in current cancer treatments. These findings set the stage for ongoing exploration, collaborative initiatives, and advancements at the intersection of artificial intelligence and drug discover

Illustrating a new global-scale approach to estimating potential reduction in fish species richness due to flow alteration

Changes in river discharge due to human activities and climate change would affect the sustainability of freshwater ecosystems. To globally assess how changes in river discharge will affect the future status of freshwater ecosystems, global-scale hydrological simulations need to be connected with a model to estimate the durability of freshwater ecosystems. However, the development of this specific modelling combination for the global scale is still in its infancy. In this study, two statistical methods are introduced to link flow regimes to fish species richness (FSR): one is based on a linear relationship between FSR and mean river discharge (hereafter, FSR-MAD method), and the other is based on a multi-linear relationship between FSR and ecologically relevant flow indices involving several other flow characteristics and mean river discharge (FSR-FLVAR method). The FSR-MAD method has been used previously in global simulation studies. The FSR-FLVAR method is newly introduced here. These statistical methods for estimating FSR were combined with a set of global river discharge simulations to evaluate the potential impact of climate-change-induced flow alterations on FSR changes. Generally, future reductions in FSR with the FSR-FLVAR method are greater and much more scattered than with the FSR-MAD method. In arid regions, both methods indicate reductions in FSR because mean discharge is projected to decrease from past to future, although the magnitude of reductions in FSR is different between the two methods. In contrast, in heavy-snow regions a large reduction in FSR is shown by the FSR-FLVAR method due to increases in the frequency of low and high flows. Although further research is clearly needed to conclude which method is more appropriate, this study demonstrates that the FSR-FLVAR method could produce considerably different results when assessing the global role of flow alterations in changing freshwater ecosystems

Morphological analysis of Polyaniline (PANI) integrated cotton fabric

With the exponential growth of flexible electronics, conductive polymer Polyaniline has been acting as a protagonist since its discovery. Polyaniline is endowed with optical and electrical conductivity, a low-cost synthesis process, and environmental stability. However, the irregular, rigid form and specific choice of solvents often hinder its widespread application. The conductive fabric can be used in the field of flexible energy harvesting, sensing, electromagnetic shielding or many more functional applications. In this study, conductive cotton fabric was fabricated using a facile in-situ chemical oxidative polymerization of Aniline on a Cotton fabric surface. Doping was performed using HCl, maintaining three different concentrations levels (1M, 2M and 3M). The color of Polyaniline turned from Blue (Emeraldine Base) to Emerald Green (Emeraldine Salt) upon its successful formation. Visual analysis, Scanning Electron Microscopy, Fourier-Transform Infrared Spectroscopy, and Energy Dispersive X-Ray Analysis were performed to justify the homogeneity and bonding adhesion with the fabric surface. It is observed that, the deposition of Polyaniline is much uniform and homogenous with the increase of dopant concentration

Homozygous carriers of the TCF7L2 rs7903146 T-allele show altered postprandial response in triglycerides and triglyceride-rich lipoproteins

The TCF7L2 rs7903146 T-allele shows the strongest association with type 2 diabetes (T2D) among common gene variants. The aim of this study was to assess circulating levels of metabolites following a meal test in individuals carrying the high risk rs790346 TT genotype (cases) and low-risk CC genotype (controls). Sixty-two men were recruited based on TCF7L2 genotype, 31 were TT carriers and 31 were age- and BMI-matched CC carriers. All participants consumed a test meal after 12 hours of fasting. Metabolites were measured using proton nuclear magnetic resonance (NMR) spectroscopy. Metabolomic profiling of TCF7L2 carriers were performed for 141 lipid estimates. TT carriers had lower fasting levels of L-VLDL-L (total lipids in large very low density lipoproteins, p = 0.045), L-VLDL-CE (cholesterol esters in large VLDL, p = 0.03), and L-VLDL-C (total cholesterol in large VLDL, p = 0.045) compared to CC carriers. Additionally, TT carriers had lower postprandial levels of total triglycerides (TG) (q = 0.03), VLDL-TG (q = 0.05, including medium, small and extra small, q = 0.048, q = 0.0009, q = 0.04, respectively), HDL-TG (triglycerides in high density lipoproteins q = 0.037) and S-HDL-TG (q = 0.00003). In conclusion, TT carriers show altered postprandial triglyceride response, mainly influencing VLDL and HDL subclasses suggesting a genotype-mediated effect on hepatic lipid regulation

Randomised controlled trial to evaluate the effect of foot trimming before and after first calving on subsequent lameness episodes and productivity in dairy heifers

The objective of this study was to assess both independent and combined effects of routine foot trimming of heifers at 3 weeks pre-calving and 100 days post calving on the first lactation lameness and lactation productivity. A total of 419 pre-calving dairy heifers were recruited from one heifer rearing operation over a 10-month period. Heifers were randomly allocated into one of four foot trimming regimens; pre-calving foot trim and post-calving lameness score (Group TL), pre-calving lameness score and post-calving foot trim (Group LT), pre-calving foot trim and post-calving foot trim (Group TT), and pre-calving lameness score and post-calving lameness score (Group LL, control group). All heifers were scored for lameness at 24 biweekly time points for 1 year following calving, and first lactation milk production data were collected. Following calving, 172/419 (41.1%) of heifers became lame during the study (period prevalence), with lameness prevalence at each time-point following calving ranging from 48/392 (12.2%) at 29–42 days post-calving to 4/379 (1.1%) between 295 and 383 days after calving. The effects of the four treatment groups were not significantly different from each other for overall lameness period prevalence, biweekly lameness point prevalence, time to first lameness event, type of foot lesion identified at dry off claw trimming, or the 4% fat corrected 305-day milk yield. However, increased odds lameness was significantly associated with a pre-calving trim alone (P = 0.044) compared to the reference group LL. The odds of heifer lameness were highest between 0 and 6 weeks post-partum, and heifer farm destination was significantly associated with lameness (OR 2.24), suggesting that even at high standard facilities, environment and management systems have more effect on heifer foot health than trimming

Exploring surfactant-enhanced stability and thermophysical characteristics of water-ethylene glycol-based Al2O3-TiO2 hybrid nanofluids

This study presents an empirical investigation into the impact of surfactant's enhanced stability and thermophysical characteristics of water-ethylene glycol (60:40) based Al2O3-TiO2 hybrid nanofluids. It aims to shed light on the nanofluid's behavior, mainly how surfactants affect its stability and thermal performance, thus contributing to advancements in heat transfer technology and engineering applications. The growing interest in nanofluids, which involves blending nanoparticles with conventional base fluids, spans diverse sectors like solar energy, heat transfer, biomedicine, and aerospace. In this study, Al2O3 and TiO2 nanoparticles are evenly dispersed in a DI-water and ethylene glycol mixture using a 50:50 ratio with a 0.1 % volume concentration. Three surfactants (SDS, SDBS, and PVP) are utilized to investigate the effect of the surfactants on hybrid nanofluids. The study examines the thermophysical characteristics of these hybrid nanofluids across a temperature range of 30 to 70 0C in 20 0C intervals to understand their potential in various industrial applications. The results show the highest stability period for nanofluids with PVP compared to nanofluids with surfactant-free and other surfactants (SDS, SDBS). The thermal conductivity is slightly decreased (max 4.61%) due to PVP surfactant addition compared to other conditions. However, the nanofluids with PVP still exhibit more excellent thermal conductivity value than the base-fluid and significantly reduced viscosity (max 55%). Hence, the enhanced thermal conductivity and reduced viscosity with improved stability due to PVP addition significantly impact heat transfer performance. However, the maximum thermal conductivity was obtained for surfactant-free Al2O3-TiO2/Water-EG-based hybrid nanofluids that reveal a thermal conductivity that is 17.05 % higher than the based fluid. Instead, the lower viscosity of hybrid nanofluids was obtained at 70 0C with the addition of PVP surfactant. Therefore, adding surfactants positively impacts Al2O3-TiO2/Water-EG-based hybrid nanofluids with higher stability, enhancing thermal conductivity and reducing viscosity compared to the based fluids. The results show that adding surfactants at a fixed volume concentration affects thermal conductivity at low temperatures and viscosity at high temperatures, suggesting that these fluids might be used as cooling agents to increase pumping power in industrial applications