The Neuroscience Chronicles

Multiple sclerosis (MS) is central nervous system (CNS) based disease. It is a chronic inflammatory demyelinating disease [1]. The main causes for MS are genetic and environmental factors. It is a disease of young people (median age of onset is around 28 years) but is lifetime and is often disabling; 50% of patients need a cane to walk 15 years after disease onset; and Worldwide more than 2.5 Million persons are affected.

Diabetes is a complex, multi-symptomatic disease whose complications drives increases in healthcare costs as the diabetes prevalence grows rapidly world-wide. Real-world electronic health records (EHRs) coupled with patient biospecimens, biological understanding, and technologies can characterize emerging diagnostic autoimmune markers resulting from proteomic discoveries.

Stroke is among the leading causes of disability and mortality in many countries of the world. The pathogenic mechanisms of ischemic stroke are very complex and have not been completely understood. The aim of this study was to estimate the amino acid (AA) pool in the brain hemisphere cortex of rats during Subtotal Cerebral Ischemia (SCI).

Participating in physical activity and exercise has significant benefits, including treating, preventing, and reducing risk factors for chronic conditions such as diabetes, hypertension, coronary heart disease, and osteoarthritis. Physical activity can also positively play a role in palliative care among individuals with terminal diseases. 

Transfusion Medicine (TM) is a relatively young medical discipline supporting a large number of medical specialties on an almost daily basis. In de routine of TM large amounts of data are collected and processed in a standardized way and depending on the economy of scale practiced. Blood and its components are not without risk when transfused. 

CNS myelination is a well-known biological phenomenon related to increase in action potential conduction speed and synaptic integration. Demyelination or abnormal myelination has been related to seizures and epilepsy either in patients or animal models. Although its role in fastening action potential propagation has been confirmed, few additional biological functions of CNS myelin has been described.

A close and contemplative look at the published neurology literature makes it clear to the reader that epilepsy research possesses more popularity and occupies a higher position in the plethora of scholarly medical writings. Perhaps the reason behind this is that epilepsy nowadays has become more than just transient seizures that are treated with drugs to put an end to seizure recurrence, but rather it is a disease that permeates all aspects of the patient’s life.

The article entitled “N,N-Dimethyltryptamine [DMT] attenuates spreading depolarization and restrains neurodegeneration by sigma-1 receptor activation in the ischemic rat brain” by Szabo et al. published recently in Neuropharmacology [1] is the last one in the series of studies on the potential benefits of DMT administration in different clinical forms of ischemia-reperfusion injury (IRI). The larger scope of the project – initiated and organized by Ede Frecska – is to collect support for a hypothesized biological function of this and related endogenous hallucinogen compounds such as 5-methoxy-N,N-dimethyltryptamine (5-MeO-DMT), 5-hydroxy-N,N-dimethyl-tryptamine (bufotenine) [2].

The increasing prevalence of drug-resistant pathogens has highlighted the need for innovative approaches in drug discovery, including drug re-purposing. Artificial intelligence (AI) has emerged as a transformative tool in this endeavor, with the potential to revolutionize not only drug re-purposing for infectious diseases but also the field of hematology.

Machine learning (ML) is a branch of artificial intelligence that uses an algorithm to process the data, retrieve valuable information, learn from it, find a pattern, and make predictions. Manual data analyses suffer from several disadvantages including it is time-consuming and subject to error.

Modern advances in artificial intelligence are phenomenal as trained machine learning models are learning to solve humanities greatest problems. In addition to the many technical problems machine learning models are attempting to solve, there is a plethora of research on the possible clinical applications of machine learning.

The mental and emotional resources that an individual can draw upon to manage stress, solve problems, and maintain well-being. It includes cognitive abilities, emotional strength, resilience, and coping mechanisms. When psychological capacity is overwhelmed by excessive stress or demands, it can lead to a decrease in mental health, known as psychological capacity compression.

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) led to a pandemic in the late 2019 and affected the worldwide population resulting in almost five million deaths and more than 200 million confirmed cases. Since the pandemic progressed, more studies shed light on the topic and researchers started speculating that comorbidities can increase the risk of adverse outcomes in COVID-19 disease.

The onset of menstruation is a landmark event in women’s life which is known to bring many psychological and emotional changes along with physical changes. In many countries, particularly in developing and emerging countries, such as India, it also brings various challenges for women to manage menstruation hygienically.

Prostate cancer (Pca) is one of the most common cancers among men worldwide. The current screening methods lack effectiveness such as prostate-specific antigen (PSA) and Magnetic resonance imaging (MRI), and some others come with pain such as biopsy. Understanding the genomic behavior of the disease may play a key part in designing more effective, accurate, and less invasive diagnosis measures. Pca has many clinical features to describe the spread and the aggressiveness of the tumor including Gleason score, TNM staging system, and the location of the tumor in the prostate gland which is known as laterality.

The coronavirus disease 2019 (COVID-19) pandemic has been placing enormous pressure on global healthcare systems. Considerable resource allocation to the treatment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, although fully inevitable, originated remarkable constraints in the access of patients with other diseases – in fact, elective admissions and nonurgent procedures or interventions were mostly canceled or deferred worldwide.

Poor oral health, particularly gum disease, has been linked to an increased risk of atherosclerosis and ischemic stroke. The theory behind this connection is that the bacteria involved in gum disease can enter the bloodstream and contribute to inflammation in the arteries, potentially promoting the development of atherosclerosis.

Vitamin B12 is one of the most complex non-protein compounds as described by Dorothy Hodgkin, a Nobel Prize-winning chemist, who discovered the molecular crystal structure of B12. Cobalamins (vitamin B12 derivatives) contain the rare transition metal, cobalt (Co), positioned in the center of a corrin ring and weakly bound to carbon.  While cobalamins are synthesized only in certain bacteria and archaea, not in mice or humans, they are co-enzymes essential for all life except for plants. For example, in higher vertebrates, methyl-cobalamin and 5’-deoxyadenosyl-cobalamin are essential for the function of methionine synthase and methylmalonyl CoA mutase, respectively.

This paper interprets subjective psychological time in a model of consciousness called the HLbC model proposed by the authors. Time has an objective physical time and a subjective psychological time. Subjective psychological time is thought to vary in its flow depending on the individual and the situation. For this explanation, this paper introduces surreal numbers into the perception of subjective psychological time.

A 2006 publication entitled ‘Catalytic Antioxidants to Treat Amyotrophic Lateral Sclerosis’ summarized the therapeutic effects of metalloporphyrins (MPs) and metallotexaphyrins (MTs) in the G93A superoxide dismutase (SOD1) mouse model of amyotrophic lateral sclerosis (ALS)