Search Results (65)

Since the initial reports of Long COVID symptoms, numerous pathophysiological mechanisms have been proposed to explain them; nevertheless, no consensus has been reached. Some of these mechanisms are directly linked to microcirculation, while others are related indirectly. Those with a direct connection involve the respiratory system (such as pulmonary embolism), the cardiovascular system (including cardiac arrest, heart failure, myocardial inflammation, stroke, endothelial dysfunction, and microangiopathy), hematological conditions (like coagulopathy, deep vein thrombosis, microclots, and endothelial irregularities), and brain function. However, few of these mechanisms are grounded in quantitative data and fundamental physiological principles. Furthermore, diagnostic and therapeutic methods remain inadequate. This report provides a brief overview of these processes, focusing primarily on quantitative data, recently proposed mechanisms, and advances in microcirculation, with a special emphasis on the tissue blood supply reduction (TBSR or SR in short) mechanism. Then, the SR pathophysiological mechanism is assessed based on the total incidence rate of the Long COVID symptoms that can be directly attributed to this mechanism. The proposed SR mechanism can account for seven principal Long COVID symptoms with a total normalized incidence of 76%. Full article

Objective: This study aimed to investigate the application value of voxel-mirrored homotopic connectivity (VMHC) and regional homogeneity (ReHo) in evaluating cognitive impairment after heart transplantation. Methods: A total of 68 heart transplant patients and 56 healthy controls were included. ReHo and VMHC were calculated using DPARSF software. A two-sample t-test was applied to compare the differences in ReHo and VMHC between the two groups, and a Pearson correlation analysis was performed by extracting the VMHC and ReHo values of different brain regions and correlating them with cognitive scale scores of the patient groups. Results: Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores were lower in the heart transplant group than in the control group (MMSE: t = 4.028, p < 0.001; MoCA: t = 4.914, p < 0.001). Compared with the control group, the ReHo values of Frontal_Sup_R (t = −4.422, p < 0.001), Thalamus_L (t = −3.911, p < 0.001), and Calcarine_L (t = −3.640, p < 0.001) were lower in the heart transplantation group, while the ReHo of Temporal_Sup_L was higher (t = 4.609, p < 0.001). VMHC was elevated for bilateral Cerebellum_Crus1 (t = 3.803, p < 0.001) and decreased for bilateral calcarine (t = −3.424, p < 0.001). The ReHo of Frontal_Sup_R was positively correlated with MMSE (r = 0.345, p = 0.004) and MoCA (r = 0.376, p = 0.002). The ReHo of Temporal_Sup_L was also positively correlated with MMSE (r = 0.397, p < 0.001) and MoCA (r = 0.542, p < 0.001). The VMHC of bilateral calcarine showed a positive correlation with MMSE (r = 0.513, p < 0.001) and MoCA (r = 0.398, p < 0.001). Other differential brain regions showed no significant correlation with the MMSE and MoCA scale scores. Conclusions: Cognitive decline was observed in heart transplant patients. Heart transplant patients exhibited altered ReHo and VMHC in several brain regions compared with healthy controls. These changes may underlie impaired cognitive function in heart transplant patients. These findings may contribute to understanding the neural mechanisms of cognitive changes in heart transplant patients and could inform future research on potential intervention strategies. Full article

Over the past decade, deep learning techniques, particularly neural networks, have become essential in medical imaging for tasks like image detection, classification, and segmentation. These methods have greatly enhanced diagnostic accuracy, enabling quicker identification and more effective treatments. In chest X-ray analysis, however, challenges remain in accurately segmenting and classifying organs such as the lungs, heart, diaphragm, sternum, and clavicles, as well as detecting abnormalities in the thoracic cavity. Despite progress, these issues highlight the need for improved approaches to overcome segmentation difficulties and enhance diagnostic reliability. In this context, we propose a novel architecture named CXR-Seg, tailored for semantic segmentation of lungs from chest X-ray images. The proposed network mainly consists of four components, including a pre-trained EfficientNet as an encoder to extract feature encodings, a spatial enhancement module embedded in the skip connection to promote the adjacent feature fusion, a transformer attention module at the bottleneck layer, and a multi-scale feature fusion block at the decoder. The performance of the proposed CRX-Seg was evaluated on four publicly available datasets (MC, Darwin, and Shenzhen for chest X-rays, and TCIA for brain flair segmentation from MRI images). The proposed method achieved a Jaccard index, Dice coefficient, accuracy, sensitivity, and specificity of 95.63%, 97.76%, 98.77%, 98.00%, and 99.05%on MC; 91.66%, 95.62%, 96.35%, 95.53%, and 96.94% on V7 Darwin COVID-19; and 92.97%, 96.32%, 96.69%, 96.01%, and 97.40% on the Shenzhen Tuberculosis CXR Dataset, respectively. Conclusively, the proposed network offers improved performance in comparison with state-of-the-art methods, and better generalization for the semantic segmentation of lungs from chest X-ray images. Full article

With an aging population, the incidence of both ischemic heart disease and strokes have become the most prevalent diseases globally. These diseases have similar risk factors, such as hypertension, diabetes, and smoking. However, there is also evidence of a relationship between the heart and the brain, referred to as the heart–brain axis. In this relationship, dysfunction of either organs can lead to injury to the other. There are several proposed physiologies to explain this relationship. These theories usually involve vascular, neuromodulatory, and inflammatory processes; however, few articles have explored and compared these different mechanisms of interaction between the heart and brain. A better understanding of the heart–brain axis can inform physicians of current and future treatment and preventive care options in heart and brain pathologies. The relationship between the brain and heart depends on inflammation, vascular anatomy and function, and neuromodulation. The pathways connecting these organs often become injured or dysfunctional when a major pathology, such as a myocardial infarction or stroke, occurs. This leads to long-term impacts on the patient’s overall health and risk for future disease. This study summarizes the current research involved in the heart–brain axis, relates these interactions to different diseases, and proposes future research in the field of neurocardiology. Conditions of the brain and heart are some of the most prevalent diseases. Through understanding the connection between these two organs, we can help inform patients and physicians of novel therapeutics for these pathologies. Full article

Background: The Default Mode Network (DMN) is involved in self-referential and emotional processes, while the insula integrates emotional and interoceptive signals. Functional connectivity between the insula and the DMN is proposed to enhance these processes by linking internal bodily states with self-referential thoughts and emotional regulation. Heart Rate Variability (HRV), a measure of parasympathetic regulation of cardiac activity, has been associated with the capacity to regulate autonomic arousal. This study explored the relationship between insula–DMN functional connectivity and HRV. We hypothesized that (1) insula’s functional activity and volume would be related to HRV; (2) insula activation would be functionally connected with the DMN; and (3) stronger insula–DMN connectivity would correlate with higher HRV. Methods: Forty-three healthy adults underwent a structural and functional MRI acquisition to assess insula–DMN connectivity during resting state. HRV was measured also at rest using the BIOPAC system. Results: A significant positive correlation was found between insula–DMN connectivity, but no correlation was observed between insula–DMN connectivity and HRV. We also found a positive significant association between left insula volume and HRV. Conclusions: These findings suggest that while the AI and DMN are functionally interconnected, this connectivity may not be directly related to HRV. The results highlight the complexity of the relationship between brain connectivity and autonomic function, suggesting that other factors may influence HRV. Full article

Background: Automated Mechanical Peripheral Stimulation (AMPS) is emerging as a potential therapeutic tool for managing motor and non-motor symptoms in individuals with Parkinson’s disease (PD), particularly in terms of improving gait, balance, and autonomic regulation. This scoping review aims to synthesize current evidence on AMPS’s effectiveness for these outcomes. Methods: A review was conducted on MEDLINE, Cochrane Central, Scopus, PEDro, and Web of Science. Studies were included if they examined AMPS interventions for PD patients and reported outcomes related to gait, balance, neurological function, or autonomic regulation. Data extraction focused on study design, intervention details, sample characteristics, and key outcomes. Quality was assessed using the PEDro and RoB-2 scales. Results: Six randomized controlled trials met the inclusion criteria. AMPS consistently improved gait kinematic parameters, including step length and gait velocity, and reduced gait asymmetry. In addition, increased brain connectivity between motor regions was correlated with enhanced gait speed, suggesting neuroplastic effects. Some studies reported improved autonomic regulation, with enhanced heart rate variability and blood pressure stability. However, limitations such as small sample sizes, short follow-ups, and varied protocols affected the consistency of the findings. Conclusions: AMPS shows potential as an adjunct therapy for PD, improving gait, balance, and possibly autonomic function. These preliminary findings will support further research into establishing standardized protocols, confirming long-term efficacy, and exploring AMPS’s impact on non-motor symptoms. With robust evidence, AMPS could complement existing PD management strategies and improve patient outcomes. Full article

Background: The human sensorimotor system can naturally synchronize with environmental rhythms, such as light pulses or sound beats. Several studies showed that different styles and tempos of music, or other rhythmic stimuli, have an impact on physiological rhythms, including electrocortical brain activity, heart rate, and motor coordination. Such synchronization, also known as the “entrainment effect”, has been identified as a crucial mechanism impacting cognitive, motor, and affective functioning. Objectives: This review examines theoretical and empirical contributions to the literature on entrainment, with a particular focus on the physiological mechanisms underlying this phenomenon and its role in cognitive, motor, and affective functions. We also address the inconsistent terminology used in the literature and evaluate the range of measurement approaches used to assess entrainment phenomena. Finally, we propose a definition of “physiological entrainment” that emphasizes its role as a fundamental mechanism that encompasses rhythmic interactions between the body and its environment, to support information processing across bodily systems and to sustain adaptive motor responses. Methods: We reviewed the recent literature through the lens of the “embodied cognition” framework, offering a unified perspective on the phenomenon of physiological entrainment. Results: Evidence from the current literature suggests that physiological entrainment produces measurable effects, especially on neural oscillations, heart rate variability, and motor synchronization. Eventually, such physiological changes can impact cognitive processing, affective functioning, and motor coordination. Conclusions: Physiological entrainment emerges as a fundamental mechanism underlying the mind–body connection. Entrainment-based interventions may be used to promote well-being by enhancing cognitive, motor, and affective functions, suggesting potential rehabilitative approaches to enhancing mental health. Full article

Background and objective: It is commonly known that there is a connection between heart disease and depression symptoms. Compared to heart failure patients without concurrent depression, those with depressive symptoms are more likely to have longer hospital stays and more outpatient visits following discharge. Although the exact neurobiological mechanisms causing the correlation between heart disease and depression symptoms are unknown, it is thought that vascular abnormalities may be a major factor. The purpose of this review was to examine the connection between brain networks linked to depression and heart failure (HF). Methods: PRISMA guidelines were followed. We included studies that reported both heart failure as well as depression and neuroimaging. Results: We identified 159 papers, but only 12 articles were included. Our findings show that reduced cerebral blood flow (CBF) following HF, along with other contributing factors such as chronic inflammation and neurovascular dysfunction, can lead to significant brain tissue damage and disruption of neural networks. The resulting alteration in the brain increases the risk of developing depression, as the neural circuits responsible for emotional regulation become compromised. Conclusions: Individuals with heart failure (HF) exhibit reduced regional cerebral blood flow across multiple brain areas, many of which are critical for mood regulation and are commonly implicated in depression, such as the left frontal cortex and right hippocampus. Full article

Schizophrenia is a complex neuropsychiatric disorder characterized by disruptions in brain connectivity and cognitive functioning. Continuous monitoring of neural activity is essential, as it allows for the detection of subtle changes in brain connectivity patterns, which could provide early warnings of cognitive decline or symptom exacerbation, ultimately facilitating timely therapeutic interventions. This paper proposes a novel approach for detecting schizophrenia-related abnormalities using deep learning (DL) techniques applied to electroencephalogram (EEG) data. Using an openly available EEG dataset on schizophrenia, the focus is on preprocessed event-related potentials (ERPs) from key electrode sites and applied transfer entropy (TE) analysis to quantify the directional flow of information between brain regions. TE matrices were generated to capture neural connectivity patterns, which were then used as input for a hybrid DL model, combining convolutional neural networks (CNNs) and Bidirectional Long Short-Term Memory (BiLSTM) networks. The model achieved a performant accuracy of 99.94% in classifying schizophrenia-related abnormalities, demonstrating its potential for real-time mental health monitoring. The generated TE matrices revealed significant differences in connectivity between the two groups, particularly in frontal and central brain regions, which are critical for cognitive processing. These findings were further validated by correlating the results with EEG data obtained from the Muse 2 headband, emphasizing the potential for portable, non-invasive monitoring of schizophrenia in real-world settings. The final model, integrated into the NeuroPredict platform, offers a scalable solution for continuous mental health monitoring. By incorporating EEG data, heart rate, sleep patterns, and environmental metrics, NeuroPredict facilitates early detection and personalized interventions for schizophrenia patients. Full article

As a critical part of the circulatory system, blood vessels transport oxygen and nutrients to every corner of the body, nourishing each cell, and also remove waste and toxins. Defects in vascular development and function are closely associated with many diseases, such as heart disease, stroke, and atherosclerosis. In the nervous system, the nervous and vascular systems are intricately connected in both development and function. First, peripheral blood vessels and nerves exhibit parallel distribution patterns. In the central nervous system (CNS), nerves and blood vessels form a complex interface known as the neurovascular unit. Second, the vascular system employs similar cellular and molecular mechanisms as the nervous system for its development. Third, the development and function of CNS vasculature are tightly regulated by CNS-specific signaling pathways and neural activity. Additionally, vascular endothelial cells within the CNS are tightly connected and interact with pericytes, astrocytes, neurons, and microglia to form the blood–brain barrier (BBB). The BBB strictly controls material exchanges between the blood and brain, maintaining the brain’s microenvironmental homeostasis, which is crucial for the normal development and function of the CNS. Here, we comprehensively summarize research on neural regulation of vascular and BBB development and propose directions for future research. Full article

Acute respiratory distress syndrome (ARDS) is a critical illness in critically unwell patients, characterized by refractory hypoxemia and shock. This study evaluates an early detection tool and investigates the relationship between hypoxia and circulatory shock in ARDS, to improve diagnostic precision and therapy customization. We used a porcine model, inducing ARDS with mechanical ventilation and intratracheal plus intravenous lipopolysaccharide (LPS) injection. Hemodynamic changes were monitored using an Acumen IQ sensor and a ForeSight Elite sensor connected to the HemoSphere platform. We evaluated tissue damage, inflammatory response, and hypoxia-inducible factor (HIF) alterations using enzyme-linked immunosorbent assay and immunohistochemistry. The results showed severe hypotension and increased heart rates post-LPS exposure, with a notable rise in the hypotension prediction index (HPI) during acute lung injury (p = 0.024). Tissue oxygen saturation dropped considerably in the right brain region. Interestingly, post-injury HIF-2α levels were lower at the end of the experiment. Our findings imply that the HPI can effectively predict ARDS-related hypotension. HIF expression levels may serve as possible markers of rapid ARDS progression. Further research should be conducted on the clinical value of this novel approach in critical care, as well as the relationship between the HIF pathway and ARDS-associated hypotension. Full article

Cardiovascular and neurological diseases are a major cause of mortality and morbidity worldwide. Such diseases require careful monitoring to effectively manage their progression. Artificial intelligence (AI) offers valuable tools for this purpose through its ability to analyse data and identify predictive patterns. This review evaluated the application of AI in cardiac and neurological diseases for their clinical impact on the general population. We reviewed studies on the application of AI in the neurological and cardiological fields. Our search was performed on the PubMed, Web of Science, Embase and Cochrane library databases. Of the initial 5862 studies, 23 studies met the inclusion criteria. The studies showed that the most commonly used algorithms in these clinical fields are Random Forest and Artificial Neural Network, followed by logistic regression and Support-Vector Machines. In addition, an ECG-AI algorithm based on convolutional neural networks has been developed and has been widely used in several studies for the detection of atrial fibrillation with good accuracy. AI has great potential to support physicians in interpretation, diagnosis, risk assessment and disease management. Full article

Wilson disease is a genetic disorder of the liver characterized by excess accumulation of copper, which is found ubiquitously on earth and normally enters the human body in small amounts via the food chain. Many interesting disease details were published on the mechanistic steps, such as the generation of reactive oxygen species (ROS) and cuproptosis causing a copper dependent cell death. In the liver of patients with Wilson disease, also, increased iron deposits were found that may lead to iron-related ferroptosis responsible for phospholipid peroxidation within membranes of subcellular organelles. All topics are covered in this review article, in addition to the diagnostic and therapeutic issues of Wilson disease. Excess Cu²⁺ primarily leads to the generation of reactive oxygen species (ROS), as evidenced by early experimental studies exemplified with the detection of hydroxyl radical formation using the electron spin resonance (ESR) spin-trapping method. The generation of ROS products follows the principles of the Haber–Weiss reaction and the subsequent Fenton reaction leading to copper-related cuproptosis, and is thereby closely connected with ROS. Copper accumulation in the liver is due to impaired biliary excretion of copper caused by the inheritable malfunctioning or missing ATP7B protein. As a result, disturbed cellular homeostasis of copper prevails within the liver. Released from the liver cells due to limited storage capacity, the toxic copper enters the circulation and arrives at other organs, causing local accumulation and cell injury. This explains why copper injures not only the liver, but also the brain, kidneys, eyes, heart, muscles, and bones, explaining the multifaceted clinical features of Wilson disease. Among these are depression, psychosis, dysarthria, ataxia, writing problems, dysphagia, renal tubular dysfunction, Kayser–Fleischer corneal rings, cardiomyopathy, cardiac arrhythmias, rhabdomyolysis, osteoporosis, osteomalacia, arthritis, and arthralgia. In addition, Coombs-negative hemolytic anemia is a key feature of Wilson disease with undetectable serum haptoglobin. The modified Leipzig Scoring System helps diagnose Wilson disease. Patients with Wilson disease are well-treated first-line with copper chelators like D-penicillamine that facilitate the removal of circulating copper bound to albumin and increase in urinary copper excretion. Early chelation therapy improves prognosis. Liver transplantation is an option viewed as ultima ratio in end-stage liver disease with untreatable complications or acute liver failure. Liver transplantation finally may thus be a life-saving approach and curative treatment of the disease by replacing the hepatic gene mutation. In conclusion, Wilson disease is a multifaceted genetic disease representing a molecular and clinical challenge. Full article

Diabetes is a chronic metabolic condition associated with high levels of blood glucose which leads to serious damage to the heart, kidney, eyes, and nerves. Elevated blood glucose levels damage brain function and cognitive abilities. They also lead to various neurological and neuropsychiatric disorders, including chronic neurodegeneration and cognitive decline. High neuronal glucose levels can cause drastic neuronal damage due to glucose neurotoxicity. Astrocytes, a type of glial cell, play a vital role in maintaining brain glucose levels through neuron–astrocyte coupling. Hyperglycemia leads to progressive decline in neuronal networks and cognitive impairment, contributing to neuronal dysfunction and fostering a neurodegenerative environment. In this review, we summarize the various connections, functions, and impairments of glial cells due to metabolic dysfunction in the diabetic brain. We also summarize the effects of hyperglycemia on various neuronal functions in the diabetic brain. Full article

Up to 50% of patients with severe congenital heart disease (CHD) develop life-altering neurodevelopmental disability (NDD). It has been presumed that NDD arises in CHD cases because of hypoxia before, during, or after cardiac surgery. Recent studies detected an enrichment in de novo mutations in CHD and NDD, as well as significant overlap between CHD and NDD candidate genes. However, there is limited evidence demonstrating that genes causing CHD can produce NDD independent of hypoxia. A patient with hypoplastic left heart syndrome and gross motor delay presented with a de novo mutation in SMC5. Modeling mutation of smc5 in Xenopus tropicalis embryos resulted in reduced heart size, decreased brain length, and disrupted pax6 patterning. To evaluate the cardiac development, we induced the conditional knockout (cKO) of Smc5 in mouse cardiomyocytes, which led to the depletion of mature cardiomyocytes and abnormal contractility. To test a role for Smc5 specifically in the brain, we induced cKO in the mouse central nervous system, which resulted in decreased brain volume, and diminished connectivity between areas related to motor function but did not affect vascular or brain ventricular volume. We propose that genetic factors, rather than hypoxia alone, can contribute when NDD and CHD cases occur concurrently. Full article