Arunachalam, Shivaram P.

The association and interaction between the central nervous system (CNS) and enteric nervous system (ENS) is well established. Essentially ENS is the second brain, as we call it. We tried to understand the structure and function, to throw light on the functional aspect of neurons, and address various disease manifestations. We summarized how various neurological disorders influence the gut via the enteric nervous system and/or bring anatomical or physiological changes in the enteric nervous system or the gut and vice versa. It is known that stress has an effect on Gastrointestinal (GI) motility and causes mucosal erosions. In our literature review, we found that stress can also affect sensory perception in the central nervous system. Interestingly, we found that mutations in the neurohormone, serotonin (5-HT), would result in dysfunctional organ development and further affect mood and behavior. We focused on the developmental aspects of neurons and cognition and their relation to nutritional absorption via the gastrointestinal tract, the development of neurodegenerative disorders in relation to the alteration in gut microbiota, and contrariwise associations between CNS disorders and ENS. This paper further summarizes the synergetic relation between gastrointestinal and neuropsychological manifestations and emphasizes the need to include behavioral therapies in management plans.

Multiple sclerosis (MS) and myalgic encephalomyelitis (ME)/chronic fatigue syndrome (CFS) share the symptom of fatigue, and might even coexist together. Specifically focusing on genetics, pathophysiology, and neuroimaging data, the authors discuss an overview of the parallels, correlation, and differences in fatigue between MS and ME/CFS along with ME/CFS presence in MS. Studies have revealed that the prefrontal cortex and basal ganglia regions, which are involved in fatigue regulation, have similar neuroimaging findings in the brains of people with both MS and ME/CFS. Additionally, in both conditions, genetic factors have been implicated, with particular genes known to enhance susceptibility to MS and CFS. Management approaches for fatigue in MS and ME/CFS differ based on the underlying factors contributing to fatigue. The authors also focus on the recent updates and the relationship between MS and sleep disorders, including restless legs syndrome, focusing on pathophysiology and therapeutic approaches. Latest therapeutic approaches like supervised physical activity and moderate-intensity exercises have shown better outcomes.

Electrophysiology is the study of the electrical properties of biological tissues, which involves the movement of ions across cell membranes. The analysis of the movement of electrical charges through the body has a wide range of biomedical applications, such as diagnosing and planning treatment in cardiovascular, nervous systems, muscular, and gastrointestinal disorders. The dielectric properties of biological tissues change according to the water content in the tissue and are measured as permittivity and conductivity relative to the frequency of the electrical field. This principle has been applied in diagnostics and therapeutics using microwave energysuch as imaging and ablation, etc. This review article summarizes the potential use of measuring dielectric properties using microwave imaging and how it can augment electrophysiological studies in medicine.

Pancreatic carcinoma (Ca Pancreas) is the third leading cause of cancer-related deaths in the world. The malignancies of the pancreas can be diagnosed with the help of various imaging modalities. An endoscopic ultrasound with a tissue biopsy is so far considered to be the gold standard in terms of the detection of Ca Pancreas, especially for lesions <2 mm. However, other methods, like computed tomography (CT), ultrasound, and magnetic resonance imaging (MRI), are also conventionally used. Moreover, newer techniques, like proteomics, radiomics, metabolomics, and artificial intelligence (AI), are slowly being introduced for diagnosing pancreatic cancer. Regardless, it is still a challenge to diagnose pancreatic carcinoma non-invasively at an early stage due to its delayed presentation. Similarly, this also makes it difficult to demonstrate an association between Ca Pancreas and other vital organs of the body, such as the heart. A number of studies have proven a correlation between the heart and pancreatic cancer. The tumor of the pancreas affects the heart at the physiological, as well as the molecular, level. An overexpression of the SMAD4 gene; a disruption in biomolecules, such as IGF, MAPK, and ApoE; and increased CA19-9 markers are a few of the many factors that are noted to affect cardiovascular systems with pancreatic malignancies. A comprehensive review of this correlation will aid researchers in conducting studies to help establish a definite relation between the two organs and discover ways to use it for the early detection of Ca Pancreas.

The measurement of physiologic pressure helps diagnose and prevent associated health complications. From typical conventional methods to more complicated modalities, such as the estimation of intracranial pressures, numerous invasive and noninvasive tools that provide us with insight into daily physiology and aid in understanding pathology are within our grasp. Currently, our standards for estimating vital pressures, including continuous BP measurements, pulmonary capillary wedge pressures, and hepatic portal gradients, involve the use of invasive modalities. As an emerging field in medical technology, artificial intelligence (AI) has been incorporated into analyzing and predicting patterns of physiologic pressures. AI has been used to construct models that have clinical applicability both in hospital settings and at-home settings for ease of use for patients. Studies applying AI to each of these compartmental pressures were searched and shortlisted for thorough assessment and review. There are several AI-based innovations in noninvasive blood pressure estimation based on imaging, auscultation, oscillometry and wearable technology employing biosignals. The purpose of this review is to provide an in-depth assessment of the involved physiologies, prevailing methodologies and emerging technologies incorporating AI in clinical practice for each type of compartmental pressure measurement. We also bring to the forefront AI-based noninvasive estimation techniques for physiologic pressure based on microwave systems that have promising potential for clinical practice.