Waste Fluid Research Articles

LSTM Algorithm in Predicting Chronic Kidney Disease Optimized Using Genetic Algorithm

Chronic Kidney Disease is a health condition in which the kidneys experience a progressive decline in function. Kidneys are vital organs that filter waste and excess blood fluids. CKD can lead to excess products in the body and cause various health issues, so early detection of CKD is necessary. While traditional machine learning techniques have performed well in predicting CKD in existing studies, this study investigates the potential of long short-term memory (LSTM) optimized with Genetic Algorithm to enhance predictive accuracy and efficiency by optimizing its hyperparameters, including number of units, hidden layers, activation function, recurrent activation, and dropout rate. The result demonstrates that the optimized LSTM slightly performs better than without optimization, achieving higher precision, recall, accuracy, and f1 score by 100% respectively. This outstanding result can be attributed to several key factors, such as ensuring rigorous data preprocessing and utilizing k-fold cross-validation to make the model more reliable. This indicates the hybrid approach can be a powerful method for the early detection of CKD, leading to better patient outcomes. Despite the promising performance, further research is suggested, specifically using a larger dataset to ensure applicability to more general population and exploring other optimization methods to reduce computational cost.

A Novel Approach for Chronic Kidney Disease Identification Empowered with Fuzzy Logic

Chronic kidney disease (CKD) is a non-communicable condition that often leads to renal failure, which is when the kidneys are no longer able to filter waste and excess fluid from the body's circulation. Early detection of CKD can slow the progression of the illness and reduce the overall cost of treatment. In this work, a novel approach for identifying CKD using a fuzzy logic system is proposed. The fuzzy system includes eight input parameters such as weight, age, serum creatinine, diastolic blood pressure, systolic blood pressure, glomerular filtration rate, blood glucose, and smoking. The output variable describes a specific patient’s stage of chronic renal disease based on these input factors. The output will indicate the current stage of a patient’s kidney disease. This system can therefore assist specialists in determining the stage of chronic renal disease. The MATLAB software is used to create the fuzzy system. The proposed system is tested on a real data set of patients and the results obtained are promising.

Non-Invasive Diagnostic Approaches for Kidney Disease: The Role of Electronic Nose Systems

Kidney diseases are a group of conditions related to the functioning of kidneys, which are in turn unable to properly filter waste and excessive fluids from the blood, resulting in the presence of dangerous levels of electrolytes, fluids, and waste substances in the human body, possibly leading to significant health effects. At the same time, the toxins amassing in the organism can lead to significant changes in breath composition, resulting in halitosis with peculiar features like the popular ammonia breath. Starting from this evidence, scientists have started to work on systems that can detect the presence of kidney diseases using a minimally invasive approach, minimizing the burden to the individuals, albeit providing clinicians with useful information about the disease’s presence or its main related features. The electronic nose (e-nose) is one of such tools, and its applications in this specific domain represent the core of the present review, performed on articles published in the last 20 years on humans to stay updated with the latest technological advancements, and conducted under the PRISMA guidelines. This review focuses not only on the chemical and physical principles of detection of such compounds (mainly ammonia), but also on the most popular data processing approaches adopted by the research community (mainly those relying on Machine Learning), to draw exhaustive conclusions about the state of the art and to figure out possible cues for future developments in the field.

Cardiac surgery associated acute kidney injury, incidence, and predictors. Prospective observational single center study.

Acute kidney injury (AKI) is a condition characterized by a sudden decline in kidney function, leading to accumulation of waste products and fluids in the body. It is a common and serious complication in patients with cardiovascular diseases, and it is associated with increased morbidity and mortality.<br /> <br /> <b>Aim</b><br /> In this study, we explore the relationship between cardiac issues and the development of AKI, as well as strategies for its prevention and management. The primary aim of this study is to examine the incidence and risk factors for the AKI in patients admitted to the cardiac intensive care unit/CICU), as well as the impact of AKI on patient outcomes.<br /> <b> </b><br /> <b>Methods</b><br /> We conducted prospective observational single center study. 292 consecutive patients admitted to ICU after open heart surgery by sternotomy were included. Patients were monitored in ICU for frequency of AKI, perioperative risk factors, cardiac surgery-associated acute kidney injury (CSA-AKI) and their impact on patients’ outcome.<br /> <b>Results</b><br /> After admission to the intensive care unit, 33 patients (11.3%) developed CSA-AKI in the postoperative period. According to the analysis, male gender (p=0.03), decreased GFR (p=0.02) as well as high EuroSCORE II (p=0.013), hemoglobin level before surgery (p = 0.002) and the presence of diabetes and chronic kidney disease (p=0.03) were independent predictors of AKI after open-heart surgery. In patients who developed AKI, the duration of artificial lung ventilation was increased (21.3 vs 9.9 hours p = 0.001) and the duration of stay in the intensive care unit (4.3 vs. 1.9 days, P = 0.02).<br /> <b> Conclusion:</b><br /> Patients often have AKI after heart surgery. EuroSCORE II, gender, diabetes, time of cardiopulmonary bypass and chronic kidney disease are independent predictors of AKI development. The appearance of AKI is due to an unfavorable outcome of events. The appearance of acute kidney injury is associated with adverse consequences.<br /> <b> Key words: </b>Acute kidney injury, cardiac surgery, predictors of AKI, postoperative period.<br /> <br />  <b>Conflict of interests: </b>The authors declare no conflict of interest.

Sustainable sonoprocess for synthesizing γ-Ga2O3/In3Sn core–shell submicron particles via acoustic emulsification and oxidation of molten EGaInSn at room temperature

This study investigated the sustainable room-temperature synthesis of In3Sn/γ-Ga2O3 core–shell particles via an acoustic route using molten eutectic Ga–In–Sn alloy (EGaInSn). Sonication was used for the emulsification and oxidation steps. During the emulsification step, the sonication of molten EGaInSn in ethanol (EtOH) at 45 kHz facilitated the formation of the smallest EGaInSn particles (average diameter, Dav = 782 nm). In terms of EGaInSn particle size, 45 kHz sonication was suitable for emulsification of molten EGaInSn and ethanol system than 24 kHz sonication.During the oxidation step, the preferential oxidation of Ga in the EGaInSn particles occurred via sonication in a solution of EtOH and hydrazine monohydrate (N2H4·H2O). This selective oxidation of Ga on the surface of the EGaInSn particles resulted in the formation of In3Sn/γ-Ga2O3 core–shell particles via sonication at 45 kHz and room temperature.The entire process eliminated the need for dispersants and high-temperature treatments. Additionally, the process did not generate waste fluid containing counter anions, such as chloride anions. This sustainable sonochemical method offers a carbon–neutral approach for synthesizing functional nanocomposites with improved safety, simplicity, and energy efficiency.

Role of the Glymphatic System in Alzheimer's Disease and Treatment Approaches: A Narrative Review.

Currently, there is unavailability of disease-modifying medication for Alzheimer's disease (AD), a debilitating neurological disorder. The pathogenesis of AD appears to be complex and could be influenced by the glymphatic system present in the central nervous system (CNS). Amyloid-beta (Aβ) and other metabolic wastes are eliminated from the brain interstitium by the glymphatic system, which encompasses perivascular channels and astroglial cells. Dysfunction of the glymphatic system, which could occur due to decreased aquaporin 4 (AQP4) expression, aging-related alterations in the human brain, and sleep disruptions, may contribute to the pathogenesis of AD and also accelerate the development of AD by causing a buildup of harmful proteins like Aβ. Promising approaches have been examined for reducing AD pathology, including non-pharmacological therapies that target glymphatic function, like exercise and sleep regulation. In addition, preclinical research has also demonstrated the therapeutic potential of pharmaceutical approaches targeted at augmenting AQP4-mediated glymphatic flow. To identify the precise processes driving glymphatic dysfunction in AD and to find new treatment targets, more research is required. Innovative diagnostic and treatment approaches for AD could be made possible by techniques such as dynamic contrast-enhanced MRI, which promises to evaluate glymphatic function in neurodegenerative diseases. Treatment options for AD and other neurodegenerative diseases may be improved by comprehending and utilizing the glymphatic system's function in preserving brain homeostasis and targeting the mechanisms involved in glymphatic functioning. This review intends to enhance the understanding of the complex link between AD and the glymphatic system and focuses on the function of AQP4 channels in promoting waste clearance and fluid exchange.

A Survey of Kidney Cancer Analysis Using Machine Learning and Deep Learning Algorithms

A recent and emerging public health concern is kidney disease, particularly Chronic Kidney Disease (CKD), characterized by a gradual decline in kidney function due to various ailments. Kidney cancer, a potentially fatal form of cancer, requires accurate staging for effective treatment selection, with Stage 1 being a crucial point for decisions. Physicians often face challenges in accurately determining cancer stages, leading to potential under- or over-treatment. Kidneys play a vital role in filtering blood, removing waste and excess fluids, excreted as urine. Advanced renal disease can cause dangerous build-ups of fluids, electrolytes, and waste. In early stages, kidney disease may exhibit minimal symptoms, often progressing unnoticed until more advanced stages. Kidney cancer arises when kidney cells undergo abnormal growth and lose control. Treatments for kidney cancer encompass a range of options, including surgical procedures, chemotherapy, and radiation therapy. Early detection remains pivotal for effective intervention, echoing the universal importance seen in managing all types of cancer. In contrast, managing chronic kidney disease focuses on minimizing kidney damage by targeting its root causes, although addressing these factors may not always halt the disease's progression. In advanced stages, kidney cancer can potentially lead to kidney failure, a life-threatening condition necessitating artificial filtration methods like hemodialysis or surgical interventions for survival. “Various risk factors encompassing dietary habits, environmental exposures, and living conditions contribute significantly to sudden and often unnoticed illnesses among many individuals. Physicians commonly encounter challenges in accurately determining the stages of cancer, potentially leading to either under treatment or overtreatment. The diagnosis process for chronic renal disease is often fraught with risks, high costs, time-intensive procedures, and invasiveness. Consequently, numerous illnesses remain untreated until they reach advanced stages, especially prevalent in regions with limited resources, highlighting disparities in healthcare accessibility and early detection. Early detection is vital for doctors to save lives. Detecting kidney conditions early can help prevent kidney damage and slow down Kidney Cancer progression. “Researchers are exploring various methods to identify kidney disease at an early stage. This research aims to understand and improve early prediction techniques for this condition. To categorize Kidney cancer, researchers use different classification strategies like Artificial Neural Networks (ANN), Naive Bayes, Support Vector Machines (SVM), Adaptive Deep Convolutional Neural Network (AHDCNN), Alex Net, U-Net 2D, ada boost classifiers, and Linear Discriminant methods.

One-dimensional modelling of air injection into abandoned oil fields for heat generation

With the global drive for net-zero emissions, it has never been more important to find clean energy sources. There are thousands of abandoned oilfields worldwide with the potential to be reactivated to produce clean energy with air injection and subsequent waste fluid sequestration. Air injection, and the development of a fire-front, may be used with enhanced geothermal systems by taking advantage of the inherent increase in heat and pressure. Conventionally used as an enhanced oil recovery technique, air injection has gained the reputation of being a high-risk intervention due to the many failures in its history. Knowledge of how petrophysical rock properties and oil physical and chemical properties control the consequences of air injection is key to optimzing the selection of late-life, or even abandoned oilfields for use in such systems. Here we use one-dimensional modelling to test the effect of varying porosity, permeability, oil viscosity and API gravity on the success of air injection. Modelling shows that the most important factor controlling temperature is the porosity of the reservoir, followed by the API gravity and then the viscosity of the oil. The most important factors controlling velocity of the fire-front are API gravity followed by oil viscosity. We show that reservoirs with high porosity and low permeability with high viscosity and low API gravity oil reach the highest fire-front temperatures. The significance of this work is that it provides several geoscience-related criteria to rank possible candidate reservoirs for reactivation and clean energy generation via air injection: the best candidates will have the highest total porosity, relatively low permeability, highest oil viscosity and lowest API gravity, such fields can then move on to bespoke and more complex simulations.

The Neglected Role of Asphaltene in the Synthesis of Mesophase Pitch.

This study investigates the synthesis of mesophase pitch using low-cost fluid catalytic cracking (FCC) slurry and waste fluid asphaltene (WFA) as raw materials through the co-carbonization method. The resulting mesophase pitch product and its formation mechanism were thoroughly analyzed. Various characterization techniques, including polarizing microscopy, softening point measurement, Fourier-transform infrared spectroscopy (FTIR), and thermogravimetric analysis (TGA), were employed to characterize and analyze the properties and structure of the mesophase pitch. The experimental results demonstrate that the optimal optical texture of the mesophase product is achieved under specific reaction conditions, including a temperature of 420 °C, pressure of 1 MPa, reaction time of 6 h, and the addition of 2% asphaltene. It was observed that a small amount of asphaltene contributes to the formation of mesophase pitch spheres, facilitating the development of the mesophase. However, excessive content of asphaltene may cover the surface of the mesophase spheres, impeding the contact between them and consequently compromising the optical texture of the mesophase pitch product. Furthermore, the inclusion of asphaltene promotes polymerization reactions in the system, leading to an increase in the average molecular weight of the mesophase pitch. Notably, when the amount of asphaltene added is 2%, the mesophase pitch demonstrates the lowest ID/IG value, indicating superior molecular orientation and larger graphite-like microcrystals. Additionally, researchers found that at this asphaltene concentration, the mesophase pitch exhibits the highest degree of order, as evidenced by the maximum diffraction angle (2θ) and stacking height (Lc) values, and the minimum d002 value. Moreover, the addition of asphaltene enhances the yield and aromaticity of the mesophase pitch and significantly improves the thermal stability of the resulting product.

Incorporating a hemodialysis filter into a commercial normothermic perfusion system to facilitate long-term preservation of human split-livers.

Normothermic machine perfusion (NMP) allows for the assessment and resuscitation of ex-vivo human livers prior to transplantation. Commercially available NMP systems are closed circuits that accumulate metabolic waste and cytokines over time, potentially limiting organ preservation times. Dialysis has been proposed as a method to remove waste and excess fluid from such systems. This study aimed to demonstrate the utility of integrating dialysis into a commercially available system by quantifying solute removal. A dialysis filter was attached in parallel to a commercially available liver perfusion system. Three livers declined for transplantation were split before undergoing long-term NMP with blood using the modified system. During perfusion, dialysate flow rates were set in the range of 100-600 mL/h for short periods of time. At each flow rate, perfusate and spent dialysate samples were collected and analyzed for solute clearance. The addition of dialysis to a commercial NMP system removed water-soluble waste and helped regulate electrolyte concentrations. Interleukin-6 was successfully removed from the perfusate. Solute clearance was proportional to dialysate flow rate. A guide for our perfusion setup was created for the appropriate selection of dialysis flow rates and duration based on real-time perfusate composition. Dialysis circuits can efficiently remove waste and regulate perfusate composition, and can be easily incorporated to improve the performance of commercially available systems. Quantification of the effect of dialysis on perfusate composition enables refined dialysis control to optimize electrolyte profiles and avoid the over- or under-correction of key solutes.

An intelligent continuous bladder irrigation monitoring and control system: Development and preliminary assessment

Abstract Objectives: To design an intelligent continuous bladder irrigation monitoring and control system and preliminarily assess its sensitivity of the early warning of flushing anomalies. Methods: According to the principle of bladder irrigation, an intelligent continuous bladder irrigation monitoring and control system was designed. The Amesim fluid simulation software was used to establish a parameterized simulation model for the bladder perfusion process and simulate the dynamic changes of bladder pressure and volume under different perfusion speeds to assess the sensitivity of the early warning of flushing anomalies. Results: The intelligent system consisted of 3 parts: the monitoring part (a flushing fluid inlet flow monitoring device, a flushing fluid outlet flow monitoring device, and a flushing fluid outlet color recognition sensor), the transition part (a control motherboard), and the regulation part (an alarm device, an electric control device for flushing fluid input speed, and a squeezing device for flushing waste fluid line). The data of the parameterized simulation model for the bladder perfusion process suggested that the sensitivity of the system was acceptable. Conclusion: The intelligent bladder irrigation system can automatically detect, report, and resolve signal abnormalities, thereby achieving the closed-loop management of bladder irrigation. The intelligent system might be used in clinical settings to reduce the burdens of nurses and promote patients’ recovery.

Experimental investigation of three fluid heat exchangers using roughness on the outer surface of a helical coil

AbstractThe aim of this study is to utilize waste thermal energy from industries into useful heat for water and air heating. In this paper, the thermal modeling and performance of three fluid heat exchangers (TFHE) have been experimentally investigated. The TFHE considered here is an enhanced version of the double‐pipe heat exchanger. A novel TFHE having fin (1 mm thin copper wire of 10 mm pitch) acts as a roughness element, which is wrapped on the helical coil's outer surface for increasing heat transfer (HT) rate and the turbulence effect for normal water, and this outer surface finned helical coil is inserted between two concentric straight tubes. The innermost tube carries atmospheric air, the finned helical coil tube carries waste hot fluid while normal water flows in the inner annulus of the outermost tube. The coiled‐side Reynolds number is varied in the range of 7000–30,000, while the curvature ratio of 0.1315, pitch‐to‐inside diameter ratio of 2.88 and wire‐to‐tube diameter of the helical tube is kept constant. A counterflow arrangement has been made for experimentation. Nusselt number is calculated using the traditional Wilson plot method that is compared and validated with results available in the literature. The overall HT coefficient is found to increase by increasing the volume flow rate of fluids, while effectiveness decreases or increases depending on residence time and capacity ratio. The percentage increment in the Nusselt number, maximum friction factor, overall HT coefficient between waste hot fluid to normal water, effectiveness is found to be 21.10%–23.88%, 90.91%, 3.40%–29.45%, 3.40%–25.33%, respectively, for the coil side. TFHE is thus proposed for heating water and space simultaneously.

Processing of slaughterhouse blood for antianemic food products

Currently, rational processing of blood from slaughterhouses remains as a waste fluid in many regions. Traditional approaches to use the blood for food are significantly limited because of specific and non-favorable organoleptic characteristics. Present study provides a comparison of various methods for modifying the red blood cell (RBC) mass of animals and a more in-depth study of acid hemolysis. The solution of ascorbic acid has been proposed as a hemolyzing agent. There has been established experimentally that the addition of equal volumes of RBC and a solution of an ascorbic acid with a concentration of 0.75 mol/dm3 can effectively destroy the stroma more up 90% of red blood cells within 15 minutes. By this, the hemoglobin oxidation degree to methemoglobin is about 50%, which forms the desired color of the resulting hydrolysate. The dry semi-finished product has a neutral odor and brown color with high functional and technological properties. It also contains 0.9% organic iron with good biological value. Thus, the study shows that blood products can effectively use in various foods such as meat products, and also as a dietary supplement for various proposes. Consumption of these products has potent positive effect on hemoglobin levels and it is recommending for people with iron deficiency anemia.

Power generation prediction of a geothermal-thermoelectric hybrid system using intelligent models

This study focuses on the most effective use of energy resources, which is the main goal of sustainable energy systems. The first contribution of the research is to ensure that the waste and geothermal fluids generated during the geothermal energy production process are evaluated in the most efficient way and reused for energy production. For this purpose, a geothermal-thermoelectric hybrid experimental system has been designed to produce electrical energy through heat exchange and how waste thermal energy could be reused in this process has been examined. Experimental tests have been performed under electrical load and in the presence of real-time uncertainties such as temperature changes, thermal conductivity, electrical noise, heat losses and random variations in thermal interaction. The second main contribution of the study is to predict and evaluate different power generation performances in the Thermoelectric Generator (TEG) system, which is affected by the mentioned experimental limitations based on artificial intelligence models. In addition, the optimal prediction performance of artificial intelligence models using hyper-parameter optimization has also been compared. Experimental results have shown that intelligent models are a successful tool for energy prediction in geothermal power generation. As a result of the hyper-parameter optimization, each model is improved by ∼5 % to ∼30 % in various error metrics. However, it was observed that the decision tree-based learning techniques resulted in ∼46 % to ∼96 % less inaccurate predictions on various error metrics compared to other methods. Power production predictions obtained using intelligent models have been obtained with 98.7 % accuracy with LightGBM learning algorithms. Most of the models used to classify different hot and cold water levels exhibit very high classification performance. The results show the successful integration of artificial intelligence models in effectively utilizing waste thermal energy and adopting a sustainable approach to energy production.

In vivo exposure to electronic waste (e-waste) leachate and hydraulic fracturing fluid adversely impacts the male reproductive system

Human health effects can arise from unregulated manual disassembly of electronic waste (e-waste) and/or hydraulic fracturing fluid spills. There is limited literature on the effects of e-waste and hydraulic fracturing wastewater exposure on the male reproductive system. Thus, this proof-of-concept study begins to address the question of how wastewater from two potentially hazardous environmental processes could affect sperm quality. Therefore, three groups of eight-week-old adult mice were exposed (5 d/wk for 6 wks) via a mealworm (Tenebrio molitor and Zophabas morio) feeding route to either: (1) e-waste leachate (50% dilution) from the Alaba Market (Lagos, Nigeria); (2) West Virginia hydraulic fracturing flowback (HFF) fluid (50% dilution); or, (3) deionized water (control). At 24-hours (hr), 3 weeks (wk), or 9-wk following the 6-wk exposure period, cohorts of mice were necropsied and adverse effects/persistence on the male reproductive system were examined. Ingestion of e-waste leachate or HFF fluid decreased number and concentration of sperm and increased both chromatin damage and numbers of morphological abnormalities in the sperm when compared to control mice. Levels of serum testosterone were reduced post-exposure (3- and 9-wk) in mice exposed to e-waste leachate and HFF when compared to time-matched controls, indicating the long-term persistence of adverse effects, well after the end of exposure. These data suggest that men living around or working in vicinity of either e-waste or hydraulic fracturing could face harmful effects to their reproductive health. From both a human health and economic standpoint, development of prevention and intervention strategies that are culturally relevant and economically sensitive are critically needed to reduce exposure to e-waste and HFF-associated toxic contaminants.

Is cerebral small vessel disease a central nervous system interstitial fluidopathy?

A typical anatomical congregate and functionally distinct multicellular cerebrovascular dynamic confer diverse blood-brain barrier (BBB) and microstructural permeabilities to conserve the health of brain parenchymal and its microenvironment. This equanimity presupposes the glymphatic system that governs the flow and clearance of metabolic waste and interstitial fluids (ISF) through venous circulation. Following the introduction of glymphatic system concept, various studies have been carried out on cerebrospinal fluid (CSF) and ISF dynamics. These studies reported that the onset of multiple diseases can be attributed to impairment in the glymphatic system, which is newly referred as central nervous system (CNS) interstitial fluidopathy. One such condition includes cerebral small vessel disease (CSVD) with poorly understood pathomechanisms. CSVD is an umbrella term to describe a chronic progressive disorder affecting the brain microvasculature (or microcirculation) involving small penetrating vessels that supply cerebral white and deep gray matter. This review article proposes CSVD as a form of “CNS interstitial fluidopathy”. Linking CNS interstitial fluidopathy with CSVD will open a better insight pertaining to the perivascular space fluid dynamics in CSVD pathophysiology. This may lead to the development of treatment and therapeutic strategies to ameliorate the pathology and adverse effect of CSVD.

Determination of the optimal construction parameters of dust collection facilities after pneumatic transport installation

In metallurgy pneumatic transport installations for powders and metal particles (swarfs, shav- ings, etc.) generated during production processes are widely used. Fine-grained metal waste and/ or intermediate products are characterized by a wide range of particle size composition, different particle shapes and significant differences in the densities of individual components of the disperse system (from 2 to 10 g·cm-3). The listed features of the materials intended for pneumatic transport create certain difficulties in determining the parameters of the disperse system intended for carrying out the transport purposes. The differences in the physical characteristics and properties of the dispersed particles also cause significant differences in their aerodynamic behaviour in the facilities for separating the two phases (solid and gaseous) and for purifying the fluid (most often air) before releasing it into the environment. Unlike dust collection systems for process flue gases, pneumatic conveying systems require initial sedimentation of the transported material and subsequent purification of the transporting fluid (air). The present report summarizes the results of analytical determination of the physical characteristics of waste fine-grained metal materials and calculation of the aerodynamic parameters of dust collection equipment included in the system for the separation of solid-phase particles with sizes greater than 100 μm and subsequent purification of the waste gas to achieve concentration of fine dust particles lower than 5 mg·m-3. Based on the physical parameters of the disperse system, the best available techniques are de- termined for the separation of the solid phase particles and the purification of the waste fluid that is released into the atmosphere, as follow: gravity dust chamber;inertia cylindric cyclone. As a result of calculating the design parameters of the specified dust collection devices, the optimal conditions have been determined for the most complete separation of the transported material from the air flow and the subsequent purification of the air released into the atmosphere to meet the legal limit for emissions of dust particles.

MRI‐Based Water Exchange Rate Across the Blood‐Brain‐Barrier is Associated with Diffusion MRI Free Water in Older Adults

AbstractBackgroundThe blood brain barrier (BBB) tightly regulates the clearance of waste from the central nervous system. Changes in BBB function may disrupt such clearance mechanisms, resulting in increased waste and unrestricted fluid, or free water (FW), which can be measured using diffusion‐weighted imaging. Here, we explored whether MRI‐based BBB water exchange rate (kw; measure of BBB function) is associated with FW within white matter tracts connecting the executive control network (ECN). We further explored whether FW within the ECN would likewise be associated with executive function performance.MethodFifty‐three older adults (ages 65‐85) without dementia were scanned using a 3‐Tesla MRI Siemens Magnetom Prisma with a 64‐channel head coil. A 3D gradient‐and‐spin‐echo diffusion‐prepared arterial spin labeling (DP‐ASL) sequence and a 126‐direction main diffusion MRI sequence using 4 b‐values (0, 500, 1000, and 2000 s/mm2) were acquired. Each participant’s mean kw values averaged over the entire brain were calculated from the DP‐ASL data. FW maps were calculated, registered to FMRIB space, and skeletonized using FSL’s tract‐based spatial statistics (TBSS). Skeletonized FW values were averaged across the white matter tracts connecting the ECN using a previously defined fMRI template. All participants completed the cognitive assessment from the Uniform Data Set Version 3 within one year of the scan date. Executive function was assessed for each participant based on a composite measure including digit span backwards and trails making part B test minus part A. A multivariate linear regression model first tested the association between whole brain kw values (predictor) and FW in the ECN as the dependent variable. A second multivariate linear regression model then tested the association between FW in the ECN (predictor) and EF performance as the dependent variable. Models controlled for age and sex.ResultsWhole brain kw values were negatively associated with FW in the ECN (r = ‐0.338, p = 0.031). FW in the ECN was negatively associated with EF performance (r = ‐0.318, p = 0.024).ConclusionOur results suggest that BBB dysfunction is associated with free water in large‐scale cognitive networks. Subsequent free water changes in these networks are linked with associated decreases in cognitive performance.

Diffusion tensor image analysis along the perivascular space inversely correlates with age in healthy subjects

AbstractBackgroundThe glymphatic system is a brain waste fluid clearance system. Glymphatic dysfunction of glymphatic system has been seen in normal aging in many neurological diseases. Diffusion tensor image analysis along the perivascular space (DTI‐ALPS) is a novel MRI method to assess the glymphatic function. In this study, we aim to evaluate the changes in glymphatic system by aging with DTI‐ALPS method.MethodWe investigated DTI‐ALPS indices of 49 healthy subjects underwent MRI scans. Anatomical T1w MPRAGE and multi‐shell diffusion‐weighted MRI were acquired on a 3T Siemens Prisma scanner. Diffusion MRI (dMRI) images were corrected for distortions induced by susceptibility and eddy current. To evaluate the glymphatic system activity, an index called ALPS index was calculated. Linear regression analysis was used to evaluate the correlation of age and ALPS.ResultResults showed that DTI‐ALPS index inversely correlates with age: R = ‐0.42, p<0.05, meaning glymphatic system activity inversely correlates with aging in healthy subjects.ConclusionUnderstanding the factors affecting glymphatic function might help better understanding the underlying mechanism of neurological diseases and healthy aging.

The Role of a Nurse in Preventing Patient Falls in Dialysis Unit (Literature Review)

Hemodialysis is a medical procedure aimed at replacing the kidney's function in filtering waste and excess fluid in the patient's blood. This article discusses the role of nurses in preventing patient falls. The purpose of this writing is to explore the crucial role played by nurses in ensuring patient safety during hemodialysis procedures and how this role becomes a critical focus in the supervision and evaluation by accreditation surveyors in the context of healthcare services. The writing method employs a literature review, and the discussion is conducted with various theoretical reviews and experiences regarding the importance of preventing patient falls. From this article, we can conclude that the nurse's role is crucial in providing nursing care to prevent patient falls.