Correct Balance Research Articles

Promotion included in prevention (PIP)

Abstract Issue/problem Every year in Europe more than 20 million visits are carried out on workers. The opportunity to integrate health promotion into prevention is now under the attention of large companies, according to the American model known as Total Worker Health©. Description of the problem The main critical points of this strategy are the correct balance between promotion and prevention efforts and the extension of the projects to small companies. Furthermore, coordination is necessary between all the figures who promote health, particularly in the national health service. Results Occupational risk prevention activities, mandatory in all European countries, have been integrated with health promotion campaigns, addressing health topics chosen in a participatory way. The costs of designing the campaign, information material for employees and data processing are borne by the university, which covers the costs with research funds. No costs are borne by workers or companies. During their medical check-up in the workplace, workers are invited to fill in a questionnaire regarding the project topic, its outcome, and some related factors. Workers receive advice on how to improve their lifestyles and are referred to the National Health Service for any necessary tests or treatments. In the last 15 years, as many annual campaigns have been conducted. Projects have dealt with: Eating behavior disorders; Post-COVID syndrome; Syncope and presyncope; Headache; Musculoskeletal disorders; Work engagement; Sleep health promotion; Aging; Violence at work; Work organization; Indoor air quality; Mediterranean Diet; Hand skin disorders; Teleworking; Work Ability. More than 30,000 workers from 38 companies participated. Lessons The participatory character of the projects, their simplicity and cost-effectiveness, the integration between occupational medicine and basic medicine demonstrate that PIP projects are economical, sustainable, and effective. Key messages • Health promotion can be integrated into the prevention of occupational risks, without additional costs. • The creation of a network of occupational physicians who are involved in PIP projects respects corporate and professional independence and improves the work culture, health, and safety of workers.

A solution for the automatic detection of expansion joints in dam stilling pools using underwater robots

This research addresses the critical challenges of detecting and measuring underwater concrete structure expansion joints (CSEJ), with a particular focus on dam stilling basin environments. A full set of algorithms for detecting expansion joints with underwater robots is presented by the research, enabling real-time and offline analysis along with visualization. These algorithms introduce the use of Convolutional Neural Networks (CNNs) for image feature extraction and segmentation in CSEJ detection, significantly improving accuracy and adaptability over traditional methods. An automated approach known as the Underwater Dam Crack Detection Network (UDCD Network) was introduced by this research. And advanced attention gates and hybrid dilated convolutions to enhance its detection capabilities are incorporated in this system. Additionally, a three-phase deep transfer learning strategy during training was utilized in this research, which significantly improves the model's performance. The research suggests an underwater image restoration algorithm that uses a dark channel prior and dynamic white balance correction to improve image clarity. Furthermore, unique underwater environmental challenges were tackled by this research, such as non-contact measurement of expansion joint widths using a view-geometry-based algorithm and comprehensive detection of dam wall surfaces. Experimental validation demonstrates that the advanced imaging technologies of the proposed underwater robots hold significant potential for autonomous detection of expansion joints in dam stilling basins.

Self-correcting deep learning for estimating rice leaf nitrogen concentration with mobile phone images

As a pivotal role in crop development, the application of nitrogen fertilizers enhances yields, while excessive use poses environmental risks. Precision nitrogen management requires rapid crop nitrogen assessment in field conditions and mobile phone images can be a promising approach. However, few studies have investigated how arbitrary white balance and exposure value settings affect crop nitrogen diagnosis using phone photos. Therefore, a new deep learning framework: self-correcting leaf nitrogen concentration estimation network (SCLNC-Net), was proposed to explore the potential of mobile phone images for non-destructive nitrogen status monitoring. Imperfect camera metering and incorrect user operations were addressed through attention U-Net for automatic white balance and exposure correction. Then a lightweight deep learning algorithm MobileNetV3 was utilized to estimate rice leaf nitrogen concentration based on the self-corrected images. Compared with most deep learning models, SCLNC-Net has fewer parameters and higher computational efficiency, which is better suited for deployment on mobile platforms. The results revealed that SCLNC-Net enhanced image quality and acquired high accuracy in the estimation of rice leaf nitrogen concentration (R2 = 0.84, RMSE = 0.39 %, RRMSE = 13 %). Moreover, the robustness and effectiveness of the proposed SCLNC-Net remained excellent across various shooting angles, mobile phone types, and rice varieties. This study provides insights into rapid and cost-efficient nutrient assessment and precision nitrogen management.

A Hybrid Approach for Face Morphing Detection

Background: In biometrics, one of the most popular study topics is the detection of face morphing attacks. However, because present methods are unable to capture significant feature changes, they are unable to strike the correct balance between accuracy and complexity. Survey investigation and analysis have shown that the existing method of face morphing detection take a bit longer time to detect the image attack due to the high computation required by facial feature extraction approaches. Conversely, further study is needed to develop a model to enhance the computational time and accuracy of the current face morphing recognition methods. The paper developed a hybrid model for face morphing detection. The FERET database was created to aid in the evaluation and development of algorithms. Local Binary Pattern (LBP) was used as feature extraction algorithm and Residue Number System (RNS) was introduced to reduce the lengthy computational time of LBP during the extraction of images. The classification accuracy of 98% was achieved for the FERET database, while an accuracy of 96% was achieved for the FRGCv2 database. An average training time of 0.0532seconds was recorded for the FERET database, while an average training time of 0.0582seconds was achieved for the FRGCv2 database. The study concluded that the high dimensionality of LBP was well reduced and optimized by the RNS algorithm, which improved the performance of face morphing recognition.

Relevance Pooling Guidance and Class-Balanced Feature Enhancement for Fine-Grained Oriented Object Detection in Remote Sensing Images

Fine-grained object detection in remote sensing images is highly challenging due to class imbalance and high inter-class indistinguishability. The strategies employed by most existing methods to resolve these two challenges are relatively rudimentary, resulting in suboptimal model performance. To address these issues, we propose a fine-grained object-oriented detection method based on relevance pooling guidance and class balance feature enhancement. Firstly, we propose a global attention mechanism that dynamically retains spatial features pertinent to objects through relevance pooling during down-sampling, thereby enabling the model to acquire more discriminative features. Next, a class balance correction module is proposed to alleviate the class imbalance problem. This module employs feature translation and a learnable reinforcement coefficient to highlight the boundaries of tail class features while maintaining their distinctiveness. Furthermore, we present an enhanced contrastive learning strategy. By dynamically adjusting the contribution of inter-class samples and intra-class similarity measures, this strategy not only constrains inter-class feature distances but also facilitates tighter intra-class clustering, making it more suitable for imbalanced datasets. Evaluation on the FAIR1M and MAR20 datasets demonstrates that our method is superior compared to other methods in object detection and achieves 46.44 and 85.05% mean average precision, respectively.

A Comparison of Paddle Forces between Whitewater and Flatwater Training in C1 Canoe Slalom.

Becoming an elite canoe slalom athlete requires thousands of hours of training, spread over many years. It is difficult to assess the correct balance between flatwater and whitewater training because differences in the paddle forces on these terrains are not known. The aim of this study was to describe paddle forces during canoe slalom training on flatwater and whitewater courses for the C1 canoe category. Paddle forces for twenty C1 canoe slalom athletes were quantified during all-out figure-of-eight tests on a flatwater course and during race simulations on a whitewater course. Paddle forces were measured using strain gauges embedded in the paddle shaft and quantified by their force, impulse, and stroke durations. The mean force during the pull phase of the paddle strokes was not significantly different between the flatwater and whitewater courses; however, the longer pull phase durations led to a greater pull phase impulse when paddling on the whitewater course. This study indicates that training for all-out runs on a whitewater course is more demanding for canoe slalom athletes than performing all-out trials on a flatwater figure-of-eight course. This evidence may help to develop effective training plans that are essential to reach the highest levels of the sport.

Study of New Material Management System in Construction Sector

Construction is a major component, which forms 45% to 50% of the country’s development activity. Construction materials and components contribute about 50% to 60% of the total value of construction. There will be some difficulty in defining construction materials. Some are exclusively used in construction and others in other industries also. Some form heavy percentage and some very minor percentage, but critical in their nature and affect the construction activity. The management and control of inventory is a problem common to all organizations in any sector of the economy. The wealth of shareholders also lies in the warehouse. More than 60% of working capital is normally being invested in the inventory. There can be disadvantages in holding either too much or too little inventory. Therefore inventory management is primarily concerned with obtaining correct balance between two extremes. Inventory management involves the development and administration of policies, system and procedures which will minimizes total cost relative to inventory decisions and related functions such as customer service requirement, production scheduling, purchasing etc.., Viewed in that perspective, inventory management has a broad scope and affects a great or number of activities in an Organization. For the past few years the concept of inventory system has gained more importance in our country. It is due to intense competition in the market, which has forced organizations to search for proper inventory control technique to reduce investment in inventories and thereby reducing overall cost. In this study the study of current inventory system is carried out and by combining the different inventory system the one new inventory system developed .By comparing the cost benefit analysis between current inventory control system and new inventory system by taking suitable actual case study will be carried out

Relationship Between Vitamin D Level and Index of CardioElectrophysiological Balance in Children.

Vitamin D deficiency has been found to be associated with various cardiovascular disorders, including hypertension, coronary artery disease, heart failure, peripheral vascular diseases, and sudden cardiac death. In the literature, it has been reported that many electrocardiographic parameters have been developed to predict ventricular arrhythmias. In recent studies, it is noteworthy that the index of cardio-electrophysiological balance (iCEB) and correct cardioelectrophysiological balance (iCEBc), which are electrocardiographic parameters, can be used as new, easy, cheap and non-invasive parameters to predict ventricular arrhythmias. This study aimed to investigate the relationship between vitamin D deficiency and iCEB and iCEBc values in children. A total of 186 patients were included in this study. Group 1 included 114 patients with vitamin D levels below 20 ng/ml; 50 patients with vitamin D levels of 21-29 ng/ml were included in Group 2; Group 3 consisted of 36 patients with a vitamin D level above 30 ng/ml. iCEB and iCEBc values were calculated by taking 12-lead ECG from all individuals and comparing them between groups. A total of 186 children, 114 subjects in Group 1, 36 subjects in Group 2, and 36 subjects in Group 3, were included in the study. Demographic characteristics and height-weight values of the groups were similar. Significant differences were found between the groups in terms of QT, QTc, QT/QRS, and QTc/QRS levels (p: 0.003, 0.028, 0.001, and 0.001, respectively). In the correlation analysis, a negative correlation was found between QTc/QRS and vitamin D level (r=-0.320, p=<0.001) and between QT/QRS and vitamin D level (r=-0.268, p=<0.001). Moreover, vitamin D level (β=0.389, p<0.001) was determined as an independent predictor of QTc/QRS in multivariate logistic regression analysis. iCEB and iCEBc parameters increase significantly in children with low vitamin D levels. These parameters are also evaluated during the follow-up of children with vitamin D deficiency in terms of the risk of ventricular arrhythmia. iCEBc can be used as an easy, inexpensive, non-invasive, and reproducible parameter.

KNEE DEFORMITIES AND KNEE REPLACEMENTS IN SAUDI POPULATION: OUR EXPERIENCE AND LITERATURE REVIEW

It takes precise alignment, adequate balance, and deformity correction to accomplish a successful total knee arthroplasty (TKA). In main TKA, this can be successfully achieved with a posterior stabilized (PS) design, either with or without sub-periosteal release. However, severe abnormalities with a major bone defect, stiffness, and instability are often associated with these disorders in some circumstances, such as knee osteoarthritis. Additional restrictive prostheses are required since it is extremely difficult to balance these anomalies with soft tissue release alone, even after main TKA. In this situation, the constrained condylar knee (CCK) design is the optimum choice. This studys primary objectives were to characterize the clinical outcomes, function recovery, and complications of patients who underwent primary CCK-TKA for severe knee osteoarthritis related knee deformity. The secondary aim was to find out the mid-term prostheses survival. Methods: Between March 2021 and March 2022, 36 consecutive patients with knee osteoarthritis had cemented primary CCK-TKA. Twenty-Eight women and eight men, totaling 36 patients, had at least a 6 month follow-up for this retrospective analysis. We used the Knee Society Score (KSS), the Hospital for Special Surgery (HSS) score, and the roentgenographic evaluation form to assess the patients. The survival of prosthesis was assessed using Kaplan-Meiers survival analysis. The patients follow-up periods averaged 12 month. The KSS knee score rose from 44 points (23–68) to 91 points (76–100) following surgery [P &lt; 0.001]. Following the procedure, the mean KSS functional score rose from 20–75 points to 91 points (65–100) [P &lt; 0.001]. The average HSS score rose from 51 points (27–83) to 91 points (75–100) following surgery [P &lt; 0.001]. The average range of motion (ROM) also increased after surgery, going from 68.09° ± 35.99° (0°–120°) to 113.68° ± 8.90° (100°–130°) [P &lt; 0.001]. The average hip-knee-ankle (HKA) angle was 180.24° ± 1.77° (175°–184°) following surgery, compared to 176.88° ± 14.48° (135°–199°) before to surgery. Radiolucencies were seen in thirteen knees, mostly on the tibial side. After an average follow-up of 12 month, 94.7% of prosthesis were still in use. Despite severe deformity, instability, and stiffness at a relatively young age, the mid-term follow-up of primary CCK-TKA in knee osteoarthritis gives satisfactory clinical and functional outcomes with 94.7% prosthesis survival. However, there are a few issues.

Effect of Paravertebral Muscle Degeneration on Lumbar and Pelvic Sagittal Alignment in Patients With Degenerative Scoliosis.

Retrospective study. To explore the relationship between lumbar spine muscle mass and lumbar pelvic sagittal parameters in patients with degenerative scoliosis. This study included ADS patients who were treated in our hospital from 2019 to 2023. The spinal parameters were evaluated through X-rays, and the relative muscle volume (RMV) and fat infiltration (FI) were measured through three-dimensional reconstruction. Patients were categorized into 3 groups based on SRS-Schwab sagittal balance correction (0, +, ++), and into 3 groups based on GAP score (proportioned, moderately dis-proportioned, severely dis-proportioned). Finally, patients were classified into low-quality and high-quality groups based on the FI of Paraspinal muscles (PSM). The study included a total of 63 patients. Significant statistical differences were observed in the FI and RMV of MF, ES and PS among patients classified by SRS-Schwab PT classification. Additionally, significant statistical differences were found in the RMV of MF and PS among patients classified by SRS-Schwab PI-LL classification and GAP score. Furthermore, a significant correlation was found between the FI and RMV of PSM and lumbopelvic sagittal parameters. The ordinal regression model analysis revealed that FI of ES significantly impacted PT imbalance, while RMV of MF significantly impacted PI-LL imbalance. Moreover, significant differences were noted in PT and PI between the low-quality and high-quality multifidus groups. As sagittal imbalance worsens, PSM degeneration also intensifies, primarily characterized by an increase in FI and a decrease in RMV. Notably, PT and PI-LL are positively correlated with RMV and negatively correlated with FI.

The Correct Combination and Balance of Macronutrients Nitrogen, Phosphorus and Potassium Promote Plant Yield and Quality Through Enzymatic and Antioxidant Activities in Potato

The Correct Combination and Balance of Macronutrients Nitrogen, Phosphorus and Potassium Promote Plant Yield and Quality Through Enzymatic and Antioxidant Activities in Potato

Comparison of KF-Based Vehicle Sideslip Estimation Logics with Increasing Complexity for a Passenger Car.

Nowadays, control is pervasive in vehicles, and a full and accurate knowledge of vehicle states is crucial to guarantee safety levels and support the development of Advanced Driver-Assistance Systems (ADASs). In this scenario, real-time monitoring of the vehicle sideslip angle becomes fundamental, and various virtual sensing techniques based on both vehicle dynamics models and data-driven methods are widely presented in the literature. Given the need for on-board embedded device solutions in autonomous vehicles, it is mandatory to find the correct balance between estimation accuracy and the computational burden required. This work mainly presents different physical KF-based methodologies and proposes both mathematical and graphical analysis to explore the effectiveness of these solutions, all employing equal tire and vehicle simplified models. For this purpose, results are compared with accurate sensor acquisition provided by the on-track campaign on passenger vehicles; moreover, to truthfully represent the possibility of using such virtual sensing techniques in real-world scenarios, the vehicle is also equipped with low-end sensors that provide information to all the employed observers.

Post-operative medication considerations in cardiac transplant patients

The first successful heart transplant was carried out in 1979, and there are now approximately 200 transplants undertaken in the UK each year. Many medications are used to prevent rejection of the transplanted organ, but this needs to be balanced with the risk of complications of immunosuppression, such as infection, organ dysfunction, graft dysfunction and vasculopathy. Patients must be able to adhere to the complex and vast regimen of medications started post-transplant, and extensive monitoring is required to ensure the correct balance of rejection risk and adverse effects, depending on where the patient is in their postoperative journey. Immediately after the transplant is when the patient is at highest risk of rejecting their new heart. Guidance is available to recommend regimens to prevent rejection, but needs to be adapted to each patient, taking into consideration their clinical picture, together with comorbidities, drug interactions and organ dysfunction.

Monetary policy effect on balance of payment in West Africa

The study examined monetary policy regimes and the balance of payment in West Africa. The study's objective was to examine the effect of monetary policy regimes on the balance of payment in West Africa. The study adopted an ex-post facto research design and obtained secondary data from documents of the Central Banks of the WAMZ countries, the World Bank Development Indicator (WDI), and the International Monetary Fund (IMF) database from 2001 to 2021. The estimation technique employed was the Panel Autoregressive Distribution Lag model, complemented by the Juodis, Karavias, and Sarafidis (2021) granger-causality test. According to the findings, the various monetary policy regimes in West Africa had conflicting effects on the balance of payments. It demonstrates how that goal can be achieved in the short term using the money supply and monetary policy rate. However, over time, policy rate had a positive effect on the balance of payments, as the money supply was insignificant. These results are particularly importantcrucial given the goal of unifying the monetary policy regime in the ECOWAS in 2027. Based on the findings, the paper concluded and recommends that to achieve a balance of payment equilibrium in West Africa, the monetary policy rate is an effective tool, this is because it is significant in explaining the changes in the balance of payment in the countries in West Africa. Thus, monetary authorities should ensure a correct balance of the rate when to increase or decrease the policy rate with the hindsight of implications on the current account.

The Role of Antioxidants in the Treatment of Metabolic Dysfunction-Associated Fatty Liver Disease: A Systematic Review.

Non-alcoholic fatty liver disease (NAFLD) is a global public health problem that causes liver-related morbidity and mortality. It is also an independent risk factor for non-communicable diseases. In 2020, a proposal was made to refer to it as "metabolic dysfunction-associated fatty liver disease (MAFLD)", with concise diagnostic criteria. Given its widespread occurrence, its treatment is crucial. Increased levels of oxidative stress cause this disease. This review aims to evaluate various studies on antioxidant therapies for patients with MAFLD. A comprehensive search for relevant research was conducted on the PubMed, SCOPUS, and ScienceDirect databases, resulting in the identification of 87 studies that met the inclusion criteria. In total, 31.1% of human studies used natural antioxidants, 53.3% used synthetic antioxidants, and 15.5% used both natural and synthetic antioxidants. In human-based studies, natural antioxidants showed 100% efficacy in the treatment of MAFLD, while synthetic antioxidants showed effective results in only 91% of the investigations. In animal-based research, natural antioxidants were fully effective in the treatment of MAFLD, while synthetic antioxidants demonstrated effectiveness in only 87.8% of the evaluations. In conclusion, antioxidants in their natural form are more helpful for patients with MAFLD, and preserving the correct balance of pro-oxidants and antioxidants is a useful way to monitor antioxidant treatment.

Illumination-Aware Low-Light Image Enhancement with Transformer and Auto-Knee Curve

Images captured under low-light conditions suffer from several combined degradation factors, including low brightness, low contrast, noise, and color bias. Many learning-based techniques attempt to learn the low-to-clear mapping between low-light and normal-light images. However, they often fall short when applied to low-light images taken in wide-contrast scenes because uneven illumination brings illumination-varying noise and the enhanced images are easily over-saturated in highlight areas. In this article, we present a novel two-stage method to tackle the problem of uneven illumination distribution in low-light images. Under the assumption that noise varies with illumination, we design an illumination-aware transformer network for the first stage of image restoration. In this stage, we introduce the Illumination-aware Attention Block featured with Illumination-aware Multi-head Self-attention, which incorporates different scales of illumination features to guide the attention module, thereby enhancing the denoising and reconstruction capabilities of the restoration network. In the second stage, we innovatively introduce a cubic auto-knee curve transfer with a global parameter predictor to alleviate the over-exposure caused by uneven illumination. We also adopt a white balance correction module to address color bias issues at this stage. Extensive experiments on various benchmarks demonstrate the advantages of our method over state-of-the-art methods qualitatively and quantitatively.

Convex and Lorenz orders under balance correction in nonlife insurance pricing: Review and new developments

By exploiting massive amounts of data, machine learning techniques provide actuaries with predictors exhibiting high correlation with claim frequencies and severities. However, these predictors generally fail to achieve financial equilibrium and thus do not qualify as pure premiums. Autocalibration effectively addresses this issue since it ensures that every group of policyholders paying the same premium is on average self-financing. Balance correction has been proposed as a way to make any candidate premium autocalibrated with the added advantage that it improves out-of-sample Bregman divergence and hence predictive Tweedie deviance. This paper proves that balance correction is also beneficial in terms of concentration curves and derives conditions ensuring that the initial predictor and its balance-corrected version are ordered in Lorenz order. Finally, criteria are proposed to rank the balance-corrected versions of two competing predictors in the convex order.

The Behavioural Change of Distribution Networks with Increasing Circuit Length and Load

Purpose: This study investigated the behavioural change of distribution networks with increasing circuit length and load. Design/Methodology/Approach: This study employed a simulation-based experimental design using OpenDSS to model and analyse the behaviour of the distribution network under different scenarios. A combination of varying network lengths and loading levels was chosen to determine the behavioural changes of a network. A total of 100 simulations were conducted, representing 10 different circuit lengths and 10 different loading conditions. Data collection on voltage levels at various points along the circuit, focusing on the voltage at the end of the circuit was carried out. Each scenario will be modelled and analysed to study the voltage drop and stability. The simulation results were validated by comparing them with theoretical calculations and real-world measurements from similar networks. Findings: It has been shown that, for every circuit length there is a maximum load that will result in a linear relationship maintaining the correct energy balance to respond to voltage regulation and power flow. With circuit length increase, capacitive reactance reduces while resistance and inductive reactance increase leading to a more inductive circuit. Research Limitation/Implications: The research considered only changes in circuit length and loading as it was based on a simplified source-load equivalent circuit. Practical implication: It draws the attention of practising engineers and designers to be mindful of the implications of load increase and network expansions on system characteristics. It forms a guide to the limit a circuit could be extended or loaded if system balance is to be maintained. Social Implication: A stable and reliable power supply supports economic growth, public health, and safety, leading to improved quality of life. Ensuring all communities have reliable electricity fosters social equity and inclusion, promoting fairness and improving the quality of life for disadvantaged groups. Originality/Value: The novelty of this research lies in its comprehensive, realistic, and advanced approach to studying the behavioural changes in distribution networks with increasing circuit length and load. By addressing previously overlooked aspects and integrating modern computational and data analysis techniques, the study provides valuable new insights that can significantly improve the design, operation, and management of long distribution networks.

Changes in Blood Electrolytes Induced by Anesthesia

Electrolyte imbalances can significantly impact anaesthesia management, potentially leading to complications during procedures. Hyponatremia, hyperkalemia, and metabolic acidosis can disrupt crucial physiological processes required for safe anaesthesia, affecting nerve transmission and heart function. Maintaining the proper fluid and electrolyte balance is essential for the body to function normally, emphasizing the importance of monitoring electrolytes during anaesthesia to prevent complications. To investigate the effects of anaesthesia on blood electrolytes, a prospective Cross-sectional design; An observational study was conducted in four hospitals from May to September 2023, involving 50 patients. The study utilized statistical analysis with SPSS, using the Wilcoxon signed-rank test to assess electrolyte levels before and after anaesthesia. A significance level of p&lt;0.05 was considered significant in the analysis. The study sample comprised 50 individuals, with 66% females and 34% males, the majority of them were within the 18-60 age range, with the highest proportion in the 20-29 category. Blood tests conducted pre- and post-anaesthesia showed varying distributions: 58% under general anaesthesia, 34% under spinal anaesthesia, and 8% under local anaesthesia. The Wilcoxon signed-rank test results indicated no statistically significant differences in electrolyte means immediately after anaesthesia, suggesting that anaesthesia did not directly impact electrolyte levels. Maintaining correct electrolyte balance is crucial during anaesthesia to ensure normal physiological function and prevent complications that could influence patient outcomes. By recognising the significance of electrolytes, addressing imbalances, and leveraging advancements in research and technology, patient safety and surgical outcomes can be enhanced.

Water exchange across the blood-brain barrier and epilepsy: Review on pathophysiology and neuroimaging.

The blood-brain barrier (BBB) is a barrier protecting the brain and a milieu of continuous exchanges between blood and brain. There is emerging evidence that the BBB plays a major role in epileptogenesis and drug-resistant epilepsy, through several mechanisms, such as water homeostasis dysregulation, overexpression of drug transporters, and inflammation. Studies have shown abnormal water homeostasis in epileptic tissue and altered aquaporin-4 water channel expression in animal epilepsy models. This review focuses on abnormal water exchange in epilepsy and describes recent non-invasive MRI methods of quantifying water exchange. PLAIN LANGUAGE SUMMARY: Abnormal exchange between blood and brain contribute to seizures and epilepsy. The authors describe why correct water balance is necessary for healthy brain functioning and how it is impacted in epilepsy. This review also presents recent MRI methods to measure water exchange in human brain. These measures would improve our understanding of factors leading to seizures.