Minimal Hepatic Encephalopathy: Silent Tragedy

Hepatic encephalopathy (HE) is brain dysfunction caused by both acute and chronic liver diseases that produces a spectrum of neuropsychiatric symptoms in the absence of other known brain diseases. Minimal hepatic encephalopathy (MHE) is the mildest form of this spectrum. MHE is defined as HE without symptoms on clinical or neurological examination, but with deficits in the performance of psychometric tests, working memory, psychomotor speed, and visuospatial ability. Minimal hepatic encephalopathy is associated with impaired driving skills and increased risk of motor vehicle accidents and has been associated with increased hospitalizations and death. Despite its clinical importance, a large number of clinicians had never investigated whether their cirrhotic patients might have MHE. Although, there is no single gold standard test for diagnosis of MHE, a combination of two neuropsychological tests or psychometric hepatic encephalopathy score battery test and/or neurophysiological test is standard for diagnosis of MHE. It was found that, treatment for MHE improves neuropsychiatric performance and quality of life and decreases the risk of developing overt HE (OHE). The agents used to treat OHE have been tested in patients with MHE. In particular, lactulose, rifaximin, probiotics and l-ornithine and l-aspartate (LOLA) have all been shown to be beneficial, with documented improvement in psychometric performance after treatment

ENHANCING HUMAN-ROBOT INTERACTION THROUGH GROUP EMOTION RECOGNITION

Abstract - This article explores within the field of Human-Robot Interaction (HRI), focusing on the complicated relationship between emotions, decision-making, and robot behaviors. Emotions are essential to effective communication and interaction, requiring the development of emotion recognition systems in robots. The article explores both individual and group emotion recognition, including microexpressions and macroexpressions. Group emotion dynamics, encompassing phenomena like emotional contagion, convergence, and social influence, are separated to understand how emotions combine within collective settings. A concept, Group Emotion Recognition (GER), is introduced, providing a framework for recognizing emotions within groups. GER involves proximity metrics, emotion classification, and entropy-based analysis to quantify emotion diversity. The article also outlines how GER can enhance user engagement, personalize interactions, improve group dynamics, and foster social acceptance in various human-robot interaction scenarios. Decision-making based on GER, driven by positive or negative emotion labels, is discussed, highlighting the adaptability and sensitivity required for effective human-robot interactions. Ethical considerations regarding the use of emotion recognition technology are addressed throughout the article, emphasizing responsible implementation. Overall, this work lays a solid foundation for advancing the field of HRI by integrating emotion recognition and decision-making to create emotionally intelligent and socially aware robots

Distinct cytokine patterns in Occult Hepatitis C and Chronic Hepatitis C Virus Infection

Background & Aim: 
The immunopathogenesis of chronic hepatitis C virus (HCV) infection is a matter of great controversy. The imbalance of T-helper lymphocyte cell cytokine production was believed to play an important pathogenic role in chronic viral hepatitis. Occult hepatitis C infection is regarded as a new entity that should be considered when diagnosing patients with a liver disease of unknown origin. The aim of this study was to determine serum T-helper 1 and T-helper 2 cytokine production in patients with occult HCV infection and its role in pathogenesis versus chronic viral hepatitis C infection.

Methods: 
Serum levels of cytokines of T-helper 1 (IL-2, IFN-[gamma]) and T-helper 2 (IL-4) were measured in 27 patients with occult HCV infection and 50 patients with chronic hepatitis C infection.

Results: 
The levels of the T-helper 1 cytokines, IL-2 and IFN-[gamma], were highly and significantly increased in patients with chronic HCV infection as compared with occult HCV infection (p<0.001). The T-helper 2 cytokine IL-4 was highly and significantly increased in occult HCV infection as compared with chronic HCV infection (p<0.001). Necroinflammation (P<0.001) fibrosis (P<0.001) and cirrhosis (P =0.03) were significantly increased in chronic HCV than occult HCV. 

Conclusion: 
Patients with occult HCV infection exhibited distinct immunoregulatory cytokine patterns, favoring viral persistence in the liver in spite of its absence from peripheral blood and explaining the less aggressive course of this disease entity than chronic hepatitis C virus infection

Increased α-Fetoprotein Predicts Steatosis among Patients with Chronic Hepatitis C Genotype 4

Background. The prognostic importance of α-fetoprotein (AFP) level elevation in patients with chronic hepatitis C and its clinical significance in steatosis associated with HCV infection remain to be determined. The present paper assessed clinical significance of elevated AFP in patients with CHC with and without steatosis. Methods. One hundred patients with CHC were divided into 50 patients with CHC and steatosis and 50 patients with CHC and no steatosis based on liver biopsy. Results. AFP was significantly increased in CHC with steatosis than patients without steatosis (P < 0.001). Highly significant positive correlation was found between serum AFP and necroinflammation as well as the severity of fibrosis/cirrhosis and negative significant correlation with albumin level in chronic HCV with steatosis (P < 0.001) but negative nonsignificant correlation with ALT and AST level (P ≤ 0.778 and 0.398), respectively. Highly significant increase was found in chronic hepatitis patients with steatosis than CHC without steatosis regarding necroinflammation as well as the severity of fibrosis/cirrhosis and AFP (P < 0.001). Conclusion. Patients with chronic HCV and steatosis have a higher AFP levels than those without steatosis. In chronic HCV with steatosis, elevated AFP levels correlated positively with HAI and negative significant correlation with albumin level

Increased α-Fetoprotein Predicts Steatosis among Patients with Chronic Hepatitis C Genotype 4

Background. The prognostic importance of α-fetoprotein (AFP) level elevation in patients with chronic hepatitis C and its clinical significance in steatosis associated with HCV infection remain to be determined. The present paper assessed clinical significance of elevated AFP in patients with CHC with and without steatosis. Methods. One hundred patients with CHC were divided into 50 patients with CHC and steatosis and 50 patients with CHC and no steatosis based on liver biopsy. Results. AFP was significantly increased in CHC with steatosis than patients without steatosis (P &lt; 0.001). Highly significant positive correlation was found between serum AFP and necroinflammation as well as the severity of fibrosis/cirrhosis and negative significant correlation with albumin level in chronic HCV with steatosis (P &lt; 0.001) but negative nonsignificant correlation with ALT and AST level (P ≤ 0.778 and 0.398), respectively. Highly significant increase was found in chronic hepatitis patients with steatosis than CHC without steatosis regarding necroinflammation as well as the severity of fibrosis/cirrhosis and AFP (P &lt; 0.001). Conclusion. Patients with chronic HCV and steatosis have a higher AFP levels than those without steatosis. In chronic HCV with steatosis, elevated AFP levels correlated positively with HAI and negative significant correlation with albumin level

Techno-Economic Analysis of Hybrid Renewable Energy Systems Designed for Electric Vehicle Charging: A Case Study from the United Arab Emirates

The United Arab Emirates is moving towards the use of renewable energy for many reasons, including the country&rsquo;s high energy consumption, unstable oil prices, and increasing carbon dioxide emissions. The usage of electric vehicles can improve public health and reduce emissions that contribute to climate change. Thus, the usage of renewable energy resources to meet the demands of electric vehicles is the major challenge influencing the development of an optimal smart system that can satisfy energy requirements, enhance sustainability and reduce negative environmental impacts. The objective of this study was to examine different configurations of hybrid renewable energy systems for electric vehicle charging in Abu Dhabi city, UAE. A comprehensive study was conducted to investigate previous electric vehicle charging approaches and formulate the problem accordingly. Subsequently, methods for acquiring data with respect to the energy input and load profiles were determined, and a techno-economic analysis was performed using Hybrid Optimization of Multiple Energy Resources (HOMER) software. The results demonstrated that the optimal electric vehicle charging model comprising solar photovoltaics, wind turbines, batteries and a distribution grid was superior to the other studied configurations from the technical, economic and environmental perspectives. An optimal model could produce excess electricity of 22,006 kWh/year with an energy cost of 0.06743 USD/kWh. Furthermore, the proposed battery&ndash;grid&ndash;solar photovoltaics&ndash;wind turbine system had the highest renewable penetration and thus reduced carbon dioxide emissions by 384 tons/year. The results also indicated that the carbon credits associated with this system could result in savings of 8786.8 USD/year. This study provides new guidelines and identifies the best indicators for electric vehicle charging systems that will positively influence the trend in carbon dioxide emissions and achieve sustainable electricity generation. This study also provides a valid financial assessment for investors looking to encourage the use of renewable energy

Challenges And Solutions In Radiation Protection For X-Ray Procedures

Chapter 1 introduces the basic concepts and quantities used in radiation protection. Depending on the type of imaging procedure, the radiation dose given to the patient has the potential to cause harmful biological effects. Understanding these effects requires knowledge of radiation physics, the interaction of X-rays with human tissue, and the biological changes at the cellular and molecular levels. This chapter provides radiologists and other clinicians with the information needed to make informed decisions about how much radiation is acceptable for a given imaging task and the potential benefit to the patient. This information is also important for researchers developing and testing new imaging methods who must weigh the benefits of improved diagnostics or therapy with any potential risks to the patient. An understanding of radiation physics and biology is also essential for epidemiologic studies aiming to assess health risks from medical radiation at the population level. Radiation exposure from X-ray procedures has been identified as a public health problem. Increased utilization of X-ray examinations and the high radiation doses associated with computed tomography (CT) scans have raised concerns about the long-term effects of ionizing radiation on the population. In response to these concerns, the U.S. National Institutes of Health formed the Biomedical Imaging Program in 2004 to investigate and develop novel imaging methods that reduce the radiation dose to patients. This dissertation supports the objectives of the NIH program and presents original research addressing radiation protection for X-ray and CT procedures. The specific aims of this work are: (1) to investigate the radiation dose and potential biological effects from current and novel X-ray imaging procedures; (2) to develop and validate methods for estimating, monitoring, and reducing patient radiation dose; and (3) to investigate the effectiveness and implications of reducing radiation dose in terms of image quality and patient outcomes. These aims are addressed using specific research projects involving exposure assessment and epidemiology, physics and engineering, clinical image interpretation, and image-guided intervention

Using CRISPR-Cas9 Gene Editing Methods to Create Novel Diagnostic Exams

In order to monitor the spread of diseases globally, diagnostic testing is essential. It consists of three main stages: detection, analysis, and outcomes. The diagnosis of many infectious diseases is based on symptoms, which can frequently overlap between infections and result in incorrect diagnoses. For many illnesses, conventional antibody testing is quite slow and not particularly economical. Using blood or urine samples from patients, CRISPR-based diagnostics could detect the disease-specific DNA sequences in less than a day. The type of disease might then be quickly identified using this data, and the appropriate course of treatment could be started. There is currently a CRISPR-based influenza diagnostic available. Research has shown that Cas9 is useful in differentiating between the virus\u27s strains. The next stage would be to modify this test to make it easier to use than the PCR techniques that are now in use. As a result of the flu\u27s symptoms\u27 resemblance to those of other respiratory illnesses, misdiagnosis rates of influenza would decline. The traditional ways of diagnosing different diseases are covered in this literature review, along with an analysis of how CRISPR technology can improve the detection of tests that are now on the market. This review focuses on non-communicable diseases (diabetes and cancer) and communicable diseases (dengue, influenza, and HIV) using data and research that is already available. Novel approaches in the field of molecular diagnostics have been introduced as a result of recent developments in the genomic sciences. The application of CRISPR-Cas9 (Clustered Regularly Interspaced Short Palindromic Repeats)-based gene editing to the development of quick, inexpensive, and extremely sensitive diagnostic tests for the identification of communicable and non-communicable diseases is one of the most promising future directions. The way diagnostic tests are performed could be completely changed by CRISPR technology, creating a whole new set of opportunities that the world\u27s health desperately needs

Glaucoma Care Plan and Role of Social Service, Health Informatics, Nurses Together with the Ophthalmology Team and their Impact on Patient

The condition known as glaucoma is one of the leading causes of blindness that cannot be reversed. If the necessary diagnostic testing and therapy are administered, glaucomatous visual loss can be avoided through prevention. In order to ensure that glaucoma diagnosis and treatment are successful, ophthalmic nurses play a significant role throughout the process. Through the use of adequate theoretical knowledge and practical training, this service evaluation reveals how nurse practitioners, social service workers, and health informaticists can gain the skills necessary to achieve a high level of agreement in patient assessment and care for patients who are suspected of having glaucoma