6664 research outputs found
Sort by
Gut microbiota regulates hepatic ischemia-reperfusion injury-induced cognitive dysfunction via the HDAC2-ACSS2 axis in mice
Get PDFAbstract
Hepatic inflow occlusion is a common procedure in liver surgery aimed at reducing intraoperative bleeding and improving surgical visualization. However, as a complication, hepatic ischemia-reperfusion injury (HIRI) resulting from this procedure is inevitable. Research has confirmed that cognitive dysfunction induced by HIRI is closely related to dysbiosis of the gut microbiota.
To investigate the mechanisms underlying this complication, gut microbiota transplantation, HDAC2-ACSS2 axis detection, and LC/MS short-chain fatty acid detection were employed. Results showed a significant decrease in ACSS2 expression in the hippocampus of mice with hepatic ischemia-reperfusion injury, highlighting impaired acetate metabolism in this region. Moreover, both the phenotype of cognitive impairment and the dysregulation of the HDAC2-ACSS2 axis could be transferred to germ-free mice through fecal microbial transplantation. Enzyme-linked immunosorbent assay also revealed reduced Acetyl-coenzyme A (acetyl-CoA) levels in the hippocampus. These findings suggest that acetate metabolism is impaired in the hippocampus of HIRI-induced cognitive impairment mice and related to dysbiosis, leading to compromised histone acetylation.
Keywords： hepatic ischemia, reperfusion injury, cognitive dysfunction, gut microbiota, HDAC2-ACSS2 axi
Malnutrition enteropathy in Zambian and Zimbabwean children with severe acute malnutrition: A multi-arm randomized phase II trial
Get PDFMalnutrition underlies almost half of all child deaths globally. Severe Acute Malnutrition (SAM) carries unacceptable mortality, particularly if accompanied
by infection or medical complications, including enteropathy. We evaluated four interventions for malnutrition enteropathy in a multi-centre
phase II multi-arm trial in Zambia and Zimbabwe and completed in 2021. The purpose of this trial was to identify therapies which could be taken forward into phase III trials. Children of either sex were eligible for inclusion if aged 6–59 months and hospitalised with SAM (using WHO definitions: WLZ <−3, and/or MUAC <11.5 cm, and/or bilateral pedal oedema), with written, informed consent from the primary caregiver.We randomised 125 children hospitalised
with complicated SAM to 14 days treatment with (i) bovine colostrum(n = 25), (ii) N-acetyl glucosamine (n = 24), (iii) subcutaneous teduglutide (n = 26), (iv) budesonide (n = 25) or (v) standard care only (n = 25). The primary endpoint
was a composite of faecal biomarkers (myeloperoxidase, neopterin, α1-antitrypsin). Laboratory assessments, but not treatments, were blinded. Perprotocol analysis used ANCOVA, adjusted for baseline biomarker value, sex, oedema, HIV status, diarrhoea, weight-for-length Z-score, and study site, with pre-specified significance of P < 0.10. Of 143 children screened, 125 were randomised. Teduglutide reduced the primary endpoint of biomarkers of
mucosal damage (effect size −0.89 (90% CI: −1.69,−0.10) P = 0.07), while colostrum (−0.58 (−1.4, 0.23) P = 0.24), N-acetyl glucosamine (−0.20 (−1.01, 0.60) P = 0.67), and budesonide (−0.50 (−1.33, 0.33) P = 0.32) had no significant effect. All interventions proved safe. This work suggests that treatment of enteropathy may be beneficial in children with complicated malnutrition. The trial was registered at ClinicalTrials.gov with the identifier NCT0371611
On the emergent “Quantum” theory in complex adaptive systems
Get PDFWe explore the concept of emergent quantum-like theory in complex adaptive systems, and examine in particular the concrete example of such an emergent (or “mock”) quantum theory in the Lotka–Volterra system. In general, we investigate the possibility of implementing the mathematical formalism of quantum mechanics on classical systems, and what would be the conditions for using such an approach. We start from a standard description of a classical system via Hamilton–Jacobi (HJ) equation and reduce it to an effective Schrodinger-type equation, with a (mock) Planck constant , which is system-dependent. The condition for this is that the so-called quantum potential
, which is state-dependent, is canceled out by some additional term in the HJ equation. We consider this additional term to provide for the coupling of the classical system under consideration to the ‘environment’. We assume that a classical system could cancel out the
term (at least approximately) by fine tuning to the environment. This might provide a mechanism for establishing a stable, stationary states in (complex) adaptive systems, such as biological systems. In particular, we present a general argument as to why the non-equilibrium dynamics of a classical system could lead to a mock quantum description that ensures stability compatible with adaptability. In this context we emphasize the state dependent nature of the mock quantum dynamics and we also introduce the new concept of the mock quantum, state dependent, statistical field theory. We also discuss some universal features of the quantum-to-classical as well as the mock-quantum-to-classical transition found in the turbulent phase of the hydrodynamic formulation of our proposal. In this way we re-frame the concept of decoherence into the concept of ‘quantum turbulence’, i.e. that the transition between quantum and classical could be defined in analogy to the transition from laminar to turbulent flow in hydrodynamics
Feasibility and acceptability of NIDUS-professional,a training and support intervention for homecare workers caring for clients living with dementia:a cluster-randomised feasibility trial
Get PDFIntroduction: In the first randomised controlled trial of a dementia training and support intervention in UK homecare agencies, we aimed to assess: acceptability of our co-designed, manualised training, delivered by non-clinical facilitators; outcome completion feasibility; and costs for a future trial. Methods: This cluster-randomised (2:1) single-blind, feasibility trial involved English homecare agencies. Intervention arm agency staff were offered group videocall sessions: 6 over 3 months, then monthly for 3 months (NIDUS-professional). Family carers (henceforth carers) and clients with dementia (dyads) were offered six to eight complementary, individual intervention sessions (NIDUS-Family). We collected potential trial measures as secondary outcomes remotely at baseline and 6 months: HCW(homecare worker) Work-related Strain Inventory (WRSI), Sense of Competence (SoC); proxy-rated Quality of Life (QOL), Disability Assessment for Dementia scale (DAD), Neuropsychiatric Inventory (NPI) and Homecare Satisfaction (HCS). Results: From December 2021 to September 2022, we met agency (4 intervention, 2 control) and HCWs (n=62) recruitment targets and recruited 16 carers and 16/60 planned clients. We met a priori progression criteria for adherence (≥4/6 sessions: 29/44 [65.9%,95% confidence interval (CI): 50.1,79.5]), HCW or carer proxy-outcome completion (15/16 (93.8% [69.8,99.8]) and proceeding with adaptation for HCWs outcome completion (46/63 (73.0% [CI: 60.3,83.4]). Delivery of NIDUS-Professional costs was £6,423 (£137 per eligible client). WRSI scores decreased and SoC increased at follow-up, with no significant between-group differences. For intervention arm proxy-rated outcomes, carer-rated QOL increased, HCWrated was unchanged; carer and HCW-rated NPI decreased; DAD decreased (greater disability) and HCS was unchanged. Conclusion: A pragmatic trial is warranted; we will consider using aggregated, agency-level client outcomes, including neuropsychiatric symptoms
Chatting: Family Carers’ Perspectives on Receiving Support from Dementia Crisis Teams
Get PDFFamily caregivers are vital to enabling people with dementia to live longer in their own homes. For these caregivers, chatting with clinicians—being listened to empathetically and receiving reassurance—can be seen as not incidental but important to supporting them. This paper considers and identifies the significance of this relational work for family carers by re-examining data originally collected to document caregivers’ perspectives on quality in crisis response teams. This reveals that chatting, for family caregivers, comprises three related features: (i) that family caregivers by responding to a person’s changing and sometimes challenging needs and behaviors inhabit a precarious equilibrium; (ii) that caregivers greatly appreciate ‘chatting’ with visiting clinicians; and (iii) that while caregivers appreciate these chats, they can be highly critical of the institutionalized character of a crisis response team’s involvement with them
The global burden, trends, and inequalities of individuals with developmental and intellectual disabilities attributable to iodine deficiency from 1990 to 2019 and its prediction up to 2030
Get PDFAbstract
Using data from the Global Burden of Disease (GBD) 2019, we conducted a cross-country inequity analysis to examine the worldwide burden of developmental and intellectual disabilities caused by the re-emerging issue of iodine deficiency from 1990 to 2019. After summarizing the latest evidence, we also made predictions up until the year 2030. According to our results, we observed a significant decline in age-standardized prevalence and annual Years Lived with Disability (YLD) rates during this period. Data analysis indicates that females are more susceptible, with adolescents being particularly vulnerable. Geographic distribution also suggests that areas with lower Socio-Demographic Index (SDI) are most severely affected. A correlation emerged between higher SDI and lower prevalence rates, highlighting the role of economic and social factors in the disease's incidence. The cross-national inequity analysis demonstrates that despite improvements in health inequalities, disparities still exist. Projections, in addition, show that the burden of disease is likely to head into a decline until 2030. This research underscores the necessity for targeted interventions, such as enhancing iodine supplementation and nutritional education, especially in areas with lower SDI. We aim to provide a foundation for policymakers to further research effective preventative and potential alternative treatment strategies.
Keywords: developmental and intellectual disabilities, iodine deficiency, systematic analysis, Global Burden of Diseas
Application of Internet of Things in Real-Time Urban Flood Risk Management
Get PDFToday, IoT devices are becoming integral to the real-time management of flooding through the implementation of flood early warning systems [1]. With the assistance of advancements in remote sensing, the expanding band board of the internet, and satellite technology, numerous
local sensors, such as ultrasonic water level detectors, flowmeters, wind speed and direction meters, and soil moisture sensors, have been introduced to provide essential real-time data for flood early warning systems [2]. Importantly, the application of IoT in urban flood risk
management extends beyond the establishment of early warning systems, encompassing a comprehensive stakeholder engagement throughout all stages and applicable to a wide range of
scenarios [3].
Although this concept is currently undergoing testing worldwide, there is still a notable gap in the existence of a comprehensive framework that classifies and explains the roles of all sensors [4]. This research aims to fill that gap. The identification of five pivotal stages in flood risk
management - prevention, mitigation, preparedness, response, and recovery - emphasizes the comprehensive nature of the challenge. In the prevention stage, IoT sensors are strategically deployed to monitor meteorological conditions and hydraulics information, providing real-time
data essential for predicting potential flooding. Integrating IoT into infrastructure, such as smart
dams or levees, enables continuous monitoring and adjustment to prevent breaches or overflows.
In the mitigation stage, IoT-controlled devices, like smart pumps or floodgates, can be autonomously activated based on real-time data, aiding in managing water levels and mitigating flood impacts. Furthermore, IoT devices, by collecting data on evolving conditions, enable
predictive analytics for assessing potential flood risks. This empowers authorities to proactively devise and implement mitigation measures. In the preparedness phase, sensors trigger automated alerts and notifications to authorities and the affected population, facilitating timely evacuation and preparedness measures. During the
response stage, IoT facilitates real-time monitoring of flood events, empowering emergency responders to make informed decisions and allocate resources judiciously. Concurrently, IoT supports communication during emergencies, ensuring seamless connectivity among response teams, affected individuals, and pertinent authorities for coordinated efforts. In the recovery phase of flood risk management, IoT sensors prove invaluable in assessing the extent of damage in affected areas, providing indispensable data for recovery planning. Moreover, IoT applications,
such as monitoring air and water quality, contribute to ensuring a safe environment during the recovery period
Machine learning models for stream-level predictions using readings from satellite and ground gauging stations
Get PDFWhile the accuracy of flood predictions is likely to improve with increasing gauging station networks and robust radar coverage, challenges arise when such sources are spatially limited [1]. For instance, severe rainfall events in the UK come mostly from the North Atlantic area where
gauges are ineffective and radar instruments are limited to it 250km range. In these cases, NASA’s IMERG is an alternative source of precipitation estimates offering global coverage with 0.1-degree spatial resolution at 30-minute intervals. The IMERG estimates for the UK’s case can offer an opportunity to extend the zone of rainfall detection beyond the radar range and increase lead
time on flood risk predictions [2]. This study investigates the ability of machine learning (ML) models to capture the patterns between rainfall and stream level, observed during 20 years in the River Crane in the UK. To compare performances, the models use two sources of rainfall data as input for stream level prediction, the IMERG final run estimates and rain gauge readings. Among the three IMERG
products (early, late, and final), the final run was selected for this study due to its higher accuracy
in rainfall estimates. The rainfall data was retrieved from rain gauges and the pixel in the IMERG dataset grid closest to the point where stream level readings were taken.
These datasets were assessed regarding their correlation with stream level using cross-correlation analysis. The assessment revealed a small variance in the lags and correlation coefficients between the stream-level and the IMERG dataset compared to the lags and coefficients found
between stream-level and the gauge’s datasets. To evaluate and compare the performance of each dataset as input in ML models for stream-level predictions, three models were selected:NARX, LSTM, and GRU. Both inputs performed well in the NARX model and produced stream-level predictions of high precision with MSE equal to 1.5×10-5 while using gauge data and 1.9×10-5 for the IMERG data. The LSTM model also produced good predictions, however, the MSE was
considerably higher, MSE of 1.8×10-3 for gauging data and 4.9×10-3 for IMERG data. Similar performance was observed in the GRU predictions with MSE of 1.9×10-3 for gauging data and 5.6×10-3 for IMERG. Nonetheless, the results of all models are within acceptable ranges of efficacy
confirming the applicability of ML models on stream-level prediction based just on rainfall and stream-level information. More importantly, the small difference between the results obtained from IMERG estimates and gauging data seems promising for future tests of IMERG rainfall data
sourced from other pixels of the dataset’s grid and to explore the potential for increased lead time
of predictions
"Yoga is a way of life” exploring experiences of yoga as a treatment for substance use: An interpretative phenomenological analysis.
Get PDFIntroduction: Yoga is a form of complementary medicine for substance use disorder (SUD). Randomized controlled trials involving yoga for the treatment of SUD found that yoga practice reduces the risk of relapse, improves mood and wellbeing for people undergoing treatment for SUD; however, the lived experience of yoga practice involving the benefits on reducing SUD is unknown. The aim of the present study was to examine the in-depth experience of yoga to inform the treatment of SUD.
Methods: Five semi structured interviews exploring experiences of yoga among people with a prior history of substance use. Four out of the five participants reported prior use of alcohol, and one reported the use of ‘GBL’ and methamphetamine. Data were analysed using Interpretative Phenomenological Analysis.
Results: Analysis resulted in three final Superordinate themes 1) Growing awareness of the body, mind, and emotions 2) Yoga opens a positive way of life and 3) Blending the worlds of yoga and 12 step recovery. Yoga was reported to enhance awareness of muscle tension, reduce physical stress, increase positive emotions, and build tolerance to negative emotions. The integration of the eight-limb philosophy of yoga, notably withdrawing of the senses, helped combat internal cues and triggers (negative thoughts and emotions) for relapse. Yoga was reported to be compatible with an abstinence-based lifestyle found in 12-step mutual aid programs and helped extend social networks to support long term abstinence.
Conclusions: The experience of integrating the eight-limb philosophy to support abstinence and the asana practice helped participants to reduce cue reactivity. Yoga appeared to enhance interoceptive awareness which is useful for reducing physical stress related to triggers for relapse, making yogic practice a valuable tool to integrate within mainstream group and individual relapse prevention programs. Therefore, programs and health policymakers may want to consider treatments that integrate yogic practices to enhance and support long term abstinence for SUD
Evolution of Soil Pore Structure and Shear Strength Deterioration of Compacted Soil under Controlled Wetting and Drying Cycles
Get PDFThe study investigates the evolution of soil pore structure and shear strength deterioration in compacted clayey soil under controlled wetting and drying (wd) cycles, which are expected to become more frequent due to climate change. Thirty soil samples were compacted at optimal moisture content and 90% of maximum dry density. These samples were then subjected to 0, 1, 5, 10, and 15 controlled wd cycles from saturation to the wilting point, and volumetric changes were recorded during each cycle. After the wd treatment, the soil samples were scanned using X-ray Computed Tomography (CT) at 50 μm resolution and then sheared under unconsolidated-undrained and consolidated-undrained conditions in a triaxial test. Significant shrinkage and swelling of soil samples were observed during wd cycles, with average volumetric strain fluctuating between +12% at saturation and -5% at the wilting point. X-ray CT visualisation and analysis revealed higher porosity, more prominent pores and increased pore length in soil samples with increasing wd cycles. Both undrained and effective soil shear strength markedly decreased with increasing wd cycles. CT-derived macroporosity and pore length were significant predictors of the soil's undrained and effective shear strength when exposed to wd cycles. The findings emphasise the considerable impact of climate change, specifically wd cycles, on clayey soil, highlighting the need for consideration in the design of earth-based infrastructure