Background: Brain oxidative lipid damage and inflammation are common in neurodegenerative diseases such as Alzheimer’s disease (AD). Paraoxonase-1 and 3 (PON1 and PON3) protein expression have been described in tissues with no PON1 and PON3 gene expression. In the present study, we aimed to examine differences in PON1 and PON3 protein expression in the brain of a mouse model of AD. Methods: We used peroxidase-based and fluorescence-based immunohistochemistry in 5 brain regions (olfactory bulb, forebrain, posterior midbrain, hindbrain and cerebellum) of transgenic (Tg2576) mice with the Swedish mutation (KM670/671NL) responsible for a familial form of AD and corresponding wild-type mice. Results: We found intense PON1 and PON3 positive staining in star-shaped cells surrounding Aβ plaques in all Tg2576 mouse brain regions studied. Although we could not co-localize PON1 and PON3 with astrocytes, brain star-shaped cells, we found some co-localization of PON3 with microglia. Conclusions: These results suggest that 1) PON1 and PON3 cross the blood-brain barrier in discoidal HDLs and are transferred to specific brain cell types, and 2) PON1 and PON3 play an important role in preventing oxidative stress and lipid peroxidation in particular cell types, likely astrocytes and microglia, in AD pathology, and potentially in other neurodegenerative diseases

Optical coherence tomography (OCT) is one of the most promising, innovative and rapidly emerging intraoperative imaging modalities for neurosurgical guidance in brain tissue imaging, "optical biopsy", brain cerebral vascular detection, nerve fibers and white matter tracts detection. In this article, we provide a short survey of cross-polarization OCT and different types of OCT probes that can be used in routine neurosurgical practice. Through different types of probes there are multiple applications where OCT can play a highly complementary role in offering the real-time microscopic assessment and imaging of normal and pathological brain tissues. The biopsy-needle based probe for CP OCT was shown to be an effective instrument for brain tissue mapping and express estimation of tissue status as well as for detecting large blood vessels to prevent causing bleeding during biopsy sampling. The folded CP OCT probe for intraoperative use for brain tissue examination was shown as a potentially efficient sensor head for CP OCT. The probe demonstrated high lateral resolution in diffractive limited probing beam quality. The length of dismountable probe tip allows using the probe under operating microscope. Due to the designed family of specialized probes CP OCT fills in the niche of devices for express brain tissue examination in situ.

In the last three decades, the robust scientific data emerged, demonstrating that the immune-inflammatory response is a fundamental component of the pathophysiology of major depressive disorder (MDD). Psychological stress and various inflammatory comorbidities contribute to such immune activation. Still, this is not uncommon that patients with depression do not have defined inflammatory comorbidities, and alternative mechanisms of immune activation need to take place. The gastrointestinal (GI) tract, along with gut-associated lymphoid tissue (GALT), constitutes the largest lymphatic organ in the human body and forms the biggest surface of contact with the external environment. It is also the most significant source of bacterial and food-derived antigenic material. There is a broad range of reciprocal interactions between the GI tract, intestinal microbiota, increased intestinal permeability, activation of immune-inflammatory response, and the CNS that has crucial implications in brain function and mental health. This intercommunication takes place within the microbiota-gut-immune-glia (MGIG) axis, and glial cells are the main orchestrator of this communication. A broad range of factors, including psychological stress, inflammation, dysbiosis and other, may compromise the permeability of this barrier. This leads to excessive bacterial translocation and the excessive influx of food-derived antigenic material that contributes to activation of the immune-inflammatory response and depressive psychopathology. This chapter summarizes the role of increased intestinal permeability in MDD and mechanisms of how the "leaky gut" may contribute to immune-inflammatory response in this disorder.

We derive time evolution equations, namely the Schrodinger-like equations and the Klein-Gordon equations for coherent fi elds and the Kadanoff-Baym (KB) equations for quantum fluctuations, in Quantum Electrodynamics (QED) with electric dipoles in 2 + 1 dimensions. Next we introduce a kinetic entropy current based on the KB equations in the 1st order of the gradient expansion. We show the H-theorem for the Leading-Order self-energy in the coupling expansion (the Hartree-Fock approximation). We show a conserved energy in the spatially homogeneous systems in the time evolution. We derive aspects of the super-radiance and the equilibration in our single Lagrangian. Our analysis can be applied to Quantum Brain Dynamics, that is QED with water electric dipoles. The total energy consumption to maintain super-radiant states in microtubules seems to be within the energy consumption to maintain the ordered systems in a brain.

The neurodegenerative diseases (Alzheimers, Parkinsons, amyotrophic lateral sclerosis, Huntingdons) and the prion disorders, have in common a dysregulation of metalloprotein chemistry involving redox metals (Cu,Fe,Mn). The consequent oxidative stress gives rise to protein plaques and neuronal cell death. An equilibrium exists between the functional requirement of the brain for Cu and Fe and their destructive potential with the production of reactive oxygen species. The importance of the brain barrier is highlighted in regulating the import of these metals. Upregulation of key transporters occurs in foetal and neonatal life when brain metal requirement is high and is down-regulated in adult life when need is minimal. By contrast a neonatal mode of CTR1 upregulation persists in feral N.Ronaldsay sheep. This has led to the premise that metal regulation may return to the default setting in ageing with implications for neurodegenerative disease.

Ischemic neuron loss contributes to brain dysfunction in patients with cardiac arrest (CA). Histidine–tryptophan–ketoglutarate (HTK) solution is a preservative used during organ transplantation. Can HTK also protect neurons from severe hypoxia (SH) following CA? We isolated rat primary cortical neurons and induced SH with or without HTK. Changes in caspase-3, hypoxia-inducible factor 1-alpha (HIF-1α), and NADPH oxidase-4 (NOX4) expression were evaluated at different time points till 72 h. Using a rat asphyxia model, we induced CA-mediated brain damage and then completed resuscitation. HTK or sterile saline was administered into the left carotid artery. Neurological deficit scoring and mortality were evaluated for 3 days. Then the rats were sacrificed for evaluating NOX4 and H2O2 level in blood and brain. In the in vitro study, HTK attenuated SH- and H2O2-mediated cytotoxicity in a volume- and time-dependent manner, associated with persisted HIF-1α expression, reductions in procaspase-3 activation and NOX4 expression. The inhibition of HIF-1α abrogated HTK’s effect on NOX4. In the in vivo study, neurological scores were significantly improved by HTK. H2O2 level, NOX4 activity and NOX4 gene expression were all decreased in the brain specimen of HTK-treated rats. Our results suggest that HTK acts as an effective neuroprotective solution.

Deployment of Level 3 and Level 4 autonomous vehicles (AVs) in urban environments is significantly constrained by adverse weather conditions, limiting their operation to clear weather due to safety concerns. Ensuring that AVs remain within their designated Operational Design Domain (ODD) is a formidable challenge, making boundary monitoring strategies essential for safe navigation. This study explores the critical role of an ODD monitoring system (OMS) in addressing these challenges. It reviews various methodologies for designing an OMS and presents a comprehensive visualization framework incorporating trigger points for ODD exits. These trigger points serve as essential references for effective OMS design. The study also delves into a specific use case concerning ODD exits: the reduction in road friction due to adverse weather conditions. It emphasizes the importance of contactless computer vision-based methods for road condition estimation (RCE), particularly using vision sensors such as cameras. The study details a timeline of methods involving classical machine learning and deep learning feature extraction techniques, identifying contemporary challenges such as class imbalance, lack of comprehensive datasets, annotation methods, and the scarcity of generalization techniques. Furthermore, it provides a factual comparison of two state-of-the-art RCE datasets. In essence, the study aims to address and explore ODD exits due to weather-induced road conditions, decoding the practical solutions and directions for future research in the realm of AVs.

OpenAI has managed to turn 100 million heads in two months towards their new Language model tool (LM) ChatGPT. The third generation Generative Pretrained Transformer (GPT-3) has the capacity to tackle simple to complex and sophisticated problems, while providing reasoning behind its generated answers. ChatGPT can be used to increase productivity and improve efficiency and face challenging problems. Programming mobile applications is a challenging task that requires professional software engineers, skills and abilities to be developed. The following paper takes a case study approach to assess how novice app developers can use ChatGPT to generate Java scripts that will be used in Android studio to create a functional application. The results after, many iterations and ongoing conversations with ChatGPT managed to create an application for the anticipated function. Important insights have been drawn from the case study that could set the ground for any novice user seeking to create applications using Java scripting and Android Studio.

Tracking and early identification of suspected cases are essential to control and prevent potential COVID-19 outbreaks. One of the most popular techniques used to track this disease is the use of Infrared cameras to identify individuals with elevated body temperatures. However, they are limited by their inability to be implemented in open public settings such as public parks or even outdoor recreational centers. This limits their ability to effectively track possible COVID-19 patients as open public recreational places such as parks, concert venues and other public venues are hotspots for the spreading of the virus. Other technological solutions such as thermal scanners require an individual to perform the actual testing as they are not individual standalone technologies. This method of testing can potentially cause the transmission of the virus between the tester and the individual getting tested. As can be seen, an alternative solution is essential to solving this issue. In this study, we aim to present the system, design and potential scope of a non-invasive system that can diagnose and identify potential COVID-19 patients using thermal and optical images of the individual using drone technology. The proposed system (COVIDRONE) combines multi-modal machine intelligence, computer vision and real-time monitoring to enable scalable monitoring. The system will also involve the use of machine learning algorithms for better and more accurate diagnosis. We envisage that development of such technologies may help in developing technological solutions to combat infectious disease threats in the future pandemics.

Fall prediction using machine learning has become one of the most fruitful and socially relevant applications of computer vision in gerontological research. Since its inception in the early 2000s, this subfield has proliferated into a robust body of research underpinned by various machine learning algorithms (including neural networks, support vector machines, and decision trees) as well as statistical modeling approaches (Markov chains, Gaussian mixture models, and hidden Markov models). Furthermore, some advancements have been translated into commercial and clinical practice, with companies in various stages of development capitalizing on the aging population to develop new commercially available products. Yet despite the marvel of modern machine learning-enabled fall prediction, little research has been conducted to shed light on the security and privacy concerns that such systems pose for older adults. The present study employs an interdisciplinary lens in examining privacy issues associated with machine learning fall prediction and exploring the implications of these models in elderly care and the Internet of Medical Things (IoMT). Ultimately, a justice-informed set of best practices rooted in social geroscience is suggested to help fall prediction researchers and companies continue to advance the field while preserving elderly privacy and autonomy.

Cells receive external stimuli to incur structural and functional damages. On scanning acoustic microscopy (SAM), speed-of-sound (SOS), attenuation-of-sound (AOS), and thickness values are plotted on the screen to create cellular images, which are related to stiffness, viscosity, and cell size, respectively. The obtained digital data compared using statistical analysis. We aimed to investigate the effects of anticancer drugs, acidic fluids, and heat effects on the cells by using SAM. Anticancer drug cisplatin induced cancer cell apoptosis/necrosis and regeneration in culture, causing elevated SOS, reduced AOS, and thickness. During a more prolonged incubation, the SAM values fluctuated differently between the cisplatin-treated and untreated cells. The tannic and acetic acid and microwave stimuli induced SOS and AOS elevations. These stimuli altered the cell size, number, differentiation, viscosity, and stiffness, which corresponded well to the fluctuation of the SOS and AOS values after incubation. Different anticancer drugs interacted with cancer cells to induce the characteristic alterations of the SAM values. These structural and mechanical alterations induced in cells was difficult to observe on light microscopy. Cellular damages were statistically compared between different stimuli and time-lapse cellular changes were observed using a SAM analysis. SAM is a useful modality to evaluate cellular damage.

Lung cancer is a deadly disease if not diagnosed in its early stages. However, early detection of lung cancer is a challenging task due to the shape and size of its nodules. Radiologists need support from automated tools for precise opinion. Automated detection of the affected lungs nodule is difficult because of the shape similarity among healthy tissues. Over the years, several expert systems have been developed that help radiologists to diagnose lung cancer. In this article, we propose a framework to precisely detect lungs cancer by classifying it between benign and malignant nodules. The framework is tested using the subset of the publicly available at the Lung Image Database Consortium image collection (LIDC-IDRI). Multiple techniques including filtering and noise removing are applied for pre-processing. Subsequently, the OTSU and the semantic segmentation are used to accurately detect the unhealthy lungs nodules. In total, 13 nodules features were extracted using Principal Components Analysis (PCA) algorithm. Four optimal features are selected based on the classification performance. In the classification phase, 9 different classifiers are used along with two types of validation schemes i.e. train test holdout validation with 70-30 data split and 10 fold cross-validation. Our experiments show that the proposed system provides 99.23\% accuracy using logic boost classifier.

Neurotrophins, particularly brain-derived neurotrophic factor (BDNF), act as key regulators of neuronal development, survival and plasticity. In this review, we focus on the role of BDNF for corticostriatal plasticity in movement disorders, including Parkinson’s Disease (PD) and dystonia. We discuss the mechanisms how dopaminergic input modulates BDNF/TrkB signaling at corticostriatal synapses and the involvement of these mechanisms in neuronal function and synaptic plasticity. Disruption of these pathways can lead to aberrant plasticity, ultimately affecting motor function. Advancing our understanding of these mechanisms could pave the way towards innovative therapeutic strategies aiming at restoring neuroplasticity and enhancing motor function in these diseases.

: Rasmussen’s encephalitis (RE) stands as a rare neurological disorder marked by progressive cerebral hemiatrophy and epilepsy resistant to medical treatment. Despite extensive study, the primary cause of RE remains elusive, while its histopathological features encompass cortical inflammation, neuronal degeneration, and gliosis. The underlying molecular mechanisms driving disease progression remain largely unexplored. In this case study, we present a patient with RE who underwent hemispherectomy and has remained seizure-free for over six months, experiencing gradual motor improvement. Further-more, we conducted molecular analysis on the excised brain tissue, unveiling a decrease in the expres-sion of cell cycle-associated genes coupled with elevated levels of BDNF and TNF-α proteins. These findings suggest potential involvement of cell cycle regulators in the progression of RE.

Huntington’s disease (HD) is a rare but progressive and devastating neurodegenerative disease characterized by involuntary movements, cognitive decline, executive dysfunction, and neuropsychiatric conditions such as anxiety and depression. It follows an autosomal dominant inheritance pattern. Thus, a child who has a parent with the mutated huntingtin (mHTT) gene has a 50% chance of developing the disease. Since HTT protein is involved in many critical cellular processes including neurogenesis, brain development, energy metabolism, transcriptional regulation, synaptic activity, vesicle trafficking, cell signaling, and autophagy, its aberrant aggregates lead to disruption of numerous cellular pathways and neurodegeneration. Essential heavy metals are vital at low concentrations, however, at higher concentrations, can exacerbate HD by disrupting the glial-neuronal communication, and/or causing dysbiosis (disturbance in the gut microbiota, GM), both of which can lead to neuroinflammation and further neurodegeneration. Here, we discuss in detail the interactions of iron, manganese and copper with glial-neuron communication and GM and indicate how this knowledge may pave the way for development of a new generation of disease-modifying therapies in HD.

Objective. To test the hypothesis that a session of unilateral tSMS over the dominant primary motor cortex (M1) in healthy subjects produces a transient decrease in manual dexterity. Methods. A triple-blinded randomized control trial was conducted in 40 healthy participants who were allocated to real- or sham-tSMS group. Each participant underwent one session of tSMS and were assessed before, immediately after, 15 minutes, and 40 minutes after stimulation. Outcome measures were Finger Tapping Test (FTT), 5-seconds FTT, nine Hole Peg Test, and the hand grip assessment. Results: Significant differences were found between groups 15 minutes after stimulation in favor of the tSMS group in the FTT (2.2 ± 0.99; CI= .18-4.22; d= .84p=.034), and 5-second FTT (4.2 ± 1.98; CI= .199-8.2, d= .68; p=.04). In the intragroup analysis, a significantly lower number of taps 15 minutes after stimulation was observed in sham group (3.3 ± 1.01; CI= .47-6.13; d= .42; p=.015), but not in the real stimulation group. Conclusion: A unilateral session of tSMS in the M1 of the dominant hemisphere of healthy individuals does not reduce manual dexterity or grip strength. This technique could have benefits on the motor performance of the arm contralateral to the stimulated motor cortex

Glioblastoma (GBM) is the most aggressive brain cancer. To model GBM in research, orthotopic brain tumor models, including syngeneic models like GL261 and genetically engineered mouse models like TRP, are used. In longitudinal studies, tumor growth and treatment response are typ-ically tracked with in vivo imaging, including bioluminescence imaging (BLI), which is quick, cost-effective, and easily quantifiable. However, BLI requires luciferase-tagged cells, and recent studies indicate that the luciferase gene can elicit an immune response, leading to tumor rejection and experimental variation. We sought to optimize the engraftment of two luciferase-expressing GBM models, GL261 Red-FLuc and TRP-mCherry-FLuc, showing differences in tumor take, with GL261 Red-FLuc cells requiring immunocompromised mice for 100% engraftment. Immuno-histochemistry and MRI revealed distinct tumor characteristics: GL261 Red-FLuc tumors were well-demarcated with densely packed cells, high mitotic activity, and vascularization. In con-trast, TRP-mCherry-FLuc tumors were large, invasive, and necrotic, with perivascular invasion. Quantifying tumor volume using the HALO® AI analysis platform yielded results comparable to manual measurements, providing a standardized and efficient approach for reliable high-throughput analysis of luciferase-expressing tumors. Our study highlights the importance of considering tumor engraftment when using luciferase-expressing GBM models, providing in-sights for preclinical research design.

Objective: Mechanical bowel preparation is essential for the visualisation of the colon during colonoscopy, and previous studies have identified changes in gut microbiota composition after bowel preparation and colonoscopy. Considering the gut microbiota is increasingly implicated in mood, we aimed to explore the potential impact of this intervention on mood and the microbiota-gut-brain axis. Methods: We conducted a pre-post intervention study, with timepoints of one week before and one month after bowel preparation and colonoscopy, in community-dwelling adults referred for colonoscopy. Our primary outcome was change in average Hospital Anxiety and Depression Scale depression sub-scores using generalised estimating equations. We also examined changes in average anxiety, stress, and quality of life scores, and faecal microbiota composition and potential function using 16S rRNA sequencing. We further explored associations between changes in depressive symptoms and the gut microbiota and conducted post-hoc analyses to explore potential effect modifiers. Key Results: 59 participants were included in the analyses. Depressive symptoms decreased one-month post-procedure compared to baseline (adjusted β=−0.64; 95%CI: −1.18, −0.11). Irritable bowel syndrome (IBS) appeared to moderate this relationship (1.78; 0.292, 3.26); depressive symptoms increased in those with, and decreased in those without, IBS. Changes in gut microbiome composition included reduced alpha diversity, modest effects on beta-diversity, and increases in genera associated with potential health benefits, one-month post-procedure compared to baseline. Increases in the CLR-transformed abundance of Ruminococcaceae UCG-009 were associated with improvements in depressive symptoms. Conclusions: There is preliminary evidence of a potential mental health effect of bowel preparation and colonoscopy, which may be associated with changes to the gut microbiota. There may also be a differential mental health impact of this procedure for those with and without IBS. Considering the limitations of our study, further research is required to confirm these findings and their clinical relevance.

Hydrogen sulfide (H2S) is an environmental toxicant of health concern. The brain is a major target in acute H2S poisoning. This study was to test the hypothesis that acute and subchronic ambient H2S exposures alter the brain metabolome. Male 7-8 week-old C57BL/6J mice were exposed by whole-body inhalation to 1000 ppm H2S for 45 min and euthanized at 5 min or 72 h for acute exposure. For subchronic study, mice were exposed to 5 ppm H2S 2 h/day, 5 days/week for 5 weeks. The brainstem was removed for metabolomic analysis. Enrichment analysis showed the metabolomic profiles in acute and subchronic H2S exposures matched with those of cerebral spinal fluid from patients with seizures or Alzheimer’s disease. Acute H2S exposure decreased excitatory neurotransmitters, aspartate and glutamate, while the inhibitory neurotransmitter, serotonin, was increased, which may explain H2S-induced loss of consciousness. Branched-chain amino acids and glucose were increased by acute H2S exposure. Subchronic H2S exposure within OSHA guideline surprisingly decreased serotonin altering central nervous system. In subchronic H2S exposure, glucose was decreased while polyunsaturated fatty acids, inosine, and hypoxanthine were increased. Collectively, these results provide important mechanistic clues of acute and subchronic ambient H2S poisonings and show that H2S alters brainstem metabolome.

Temporal lobe epilepsy (TLE) is associated with reorganization of hippocampal neuronal net-works, gliosis, neuroinflammation, loss of integrity of the blood-brain barrier (BBB) in humans and animal models. More than 30% of epilepsies remain intractable and characterization of the molecular mechanisms involved in BBB dysfunction is essential to the identification of new thera-peutic strategies. In this work, we induced status epilepticus in rats by injection of the proconvul-sant drug pilocarpine that leads to TLE. Using RT-qPCR, double immunohistochemistry and con-focal imaging, we studied at different time points of epileptogenesis (latent phase, 3, 7, 14 days; chronic phase, 1 and 3 months) the regulation of reactive glia and vascular markers. In the hippo-campus, increased expression of mRNA encoding the glial proteins GFAP and Iba1 confirmed neu-roinflammatory status. We report for the first time the concomitant induction in endothelial cells, pericytes and basement membrane of the BBB of specific proteins CD31, PDGFR and ColIV, that peaks at the same time points as inflammation. The altered expression of these proteins occurs ear-ly in TLE, during the latent phase, suggesting that they could be associated with early rupture and pathogenicity of the BBB that will contribute to the chronic phase of epilepsy.

Long Covid is a heterogeneous clinical condition in which Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) and brain fog stand out among the different clinical symptoms and syndromes. The cerebral metabolic alterations and neuroendocrine disorders seem to constitute an important part of Long Covid. Given the substantial lack of drugs and effective therapeutic strategies, hypothalamic phospholipid liposomes which have been on the market for several years as adjuvant therapy of cerebral metabolic alterations resulting from neuroendocrine disorders, can be taken into consideration in an overall therapeutic strategy that aims to control the Long Covid associated symptoms and syndromes. Their pharmacological mechanisms and clinical effects strongly support their usefulness in Long Covid. Our initial clinical experience corroborates this rationale. Further research is imperative in order to obtain robust clinical evidence.

Background: Post-delivery period could be characterized by psychological distress (e.g., anxiety, sadness, and irritability), leading to post-partum depression (PPD). Objective: The present clinical study assess the effect of probiotic supplementation containing Limosilactobacillus reuteri PBS072 and Bifidobacterium breve BB077 (4x10⁹ CFU/day) on mother’s mood and breastfeeding quality during the first trimester after delivery. Methods: A Randomized Double Blind Controlled (RDBPC) trial has been carried out in 200 healthy new mothers divided into an active group taking a supplement containing Limosilactobacillus reuteri PBS072 and Bifidobacterium breve BB077 (4x10⁹ CFU/day) plus multivitamins, and a control group (multivitamin complex only) for 90 days. Symptoms related to maternal depression and breastfeeding quality were evaluated at days 45 and 90 by Edinburgh Postnatal Depression Scale (EPDS) and Breastfeeding Self-Efficacy Scale Short-Form (BSES-SF). Results: At days 45 and 90, probiotic treatment significantly ameliorated the mothers’ mood compared to the control treatment (p<0.001). Likewise, breastfeeding quality and baby’s cries significantly improved in the probiotic group (p<0.001). Conclusions: Microbiota alterations could influence post-delivery woman’s mental state. According to our results, L. reuteri PBS072 and B. breve BB077 are potential candidates able to improve stress resilience in the post-partum period.

Deep brain stimulation (DBS) is an effective and safe medical treatment that improves the lives of patients with a wide range of neurological and psychiatric diseases, and has been consolidated as a first-line tool in the last two decades. Closed loop deep brain stimulation (CLDBS) pushes this tool further by automatically adjusting the stimulation parameters to the brain response in real-time. This paper presents a CLDBS with 2 stimulation channels and 2 acquisition channels. Each channel has a low-noise amplifier (LNA) buffer in differential configuration to eliminate the DC signal component of the input. Energy management is efficiently done by the control and communication unit. The battery supports almost 9 hours with both the acquisition and stimulation circuits active. If only the stimulation circuit is used as an Open Loop DBS (OLDBS), the battery can hold sufficient voltage for 24 hours of operation. The whole system is low-cost and portable and therefore it could be used as a wearable.

As the name implies, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a single-stranded RNA virus and a member of the corona virus family, primarily affecting the upper respiratory system and the lungs. Like many other respiratory viruses, SARS-CoV-2 can spread to other organ systems. Apart from causing diarrhea, another most common but debilitating complication caused by the SARS-CoV-2 is neurological symptoms and cognitive difficulties, which occur in up to two thirds of hospitalized covid patients and ranging from shortness of concentration, overall declined cognitive speed to executive or memory function impairment. Neuro-cognitive dysfunction and “brain fog” are frequently present in COVID-19 cases, which can last several months after the infection, leading to disruption of daily life. Cumulative evidence suggests that SARS-CoV-2 affects vasculature in the extra pulmonary systems directly or indirectly, leading to impairment of endothelial function and even multi-organ damage. The post COVID-19 long-lasting neurocognitive impairments have not been studied fully; and the underlying mechanism remains elusive. In this review, we summarize the current understanding of the effects of COVID-19 on vascular dysfunction and how vascular dysfunction leads to cognitive impairment in patients.

The enteric nervous system (ENS) is a neural network referred to as "the brain in the gut" because of its similarities to the central nervous system (CNS). The ENS consists of numerous types of neurons and glial cells distributed in two intramuscular plexuses that span the length of the intestine and control coordinated smooth muscle contractile activity and other intestinal functions. It is well-established that reciprocal communication exists between the brain and the gastrointestinal tract. Although the ENS can function independently, it is connected to the CNS through the afferent and efferent pathways of the parasympathetic and sympathetic nervous systems. In addition to regulating ENS function by the CNS, these connections are likely to be critically involved in the pathophysiology of Parkinson's disease (PD). PD is a common neurodegenerative disorder that presents with non-motor and motor symptoms. Surprisingly, ENS lesions have been shown to occur very early in the disease, even before CNS involvement. This has led to the postulation that the ENS may be central to the pathophysiology of PD. Autopsy studies have shown that α-synuclein (αS) aggregates in PD patients are found both in the substantia nigra (SN) and the ENS. Therefore, it has been hypothesized that the pathological process leading to PD may initially occur in the ENS years before the appearance of motor features. This process induces misfolding and aggregation of αS in specific subtypes of neurons in the CNS. Finally, it spreads retrogradely in the CNS through preganglionic vagal fibers to the dorsal motor nucleus of this nerve and to other central nervous structures. In addition to the presumed role in the spread of the disease process, it has also been suggested that pathological changes in the ENS might be involved in the gastrointestinal dysfunction frequently seen in Pd patients. Starting from the evidence in animal models and using a translational point of view, in this review, we aim to summarize the role of the ENS in the pathogenesis of PD and how this system could be modulated for a novel therapeutic approach. While acknowledging the presumed role of the microbiome in the gut-brain axis, we will shift the focus from this point of view to focus more on the neurons of the ENS.

Proteomic analysis revealed the preservation of many proteins in the “Heslington brain” (which is at least 2,600-year-old brain tissue uncovered within the skull excavated in 2008 from a pit in Heslington, Yorkshire, England). Five of these proteins (“main proteins”), heavy, medium, and light neurofilament proteins (NFH, NFM, and NFL), glial fibrillary acidic protein (GFAP), and myelin basic (MBP) protein are engaged in the formation non-amyloid protein aggregates, such as intermediate filaments and myelin sheath. We used a wide spectrum of bioinformatics tools to evaluate the prevalence of functional disorder in several related sets of proteins, such as “main proteins” and their 44 interactors, as well as all other protein identified in the Heslington brain. These analyses revealed that all five “main proteins”, half of their interactors and almost one third of the Heslington brain proteins are expected to be mostly disordered. Furthermore, most of the remaining proteins are expected to contain sizable disordered regions. This is in contrary the expected substantial (if not complete) elimination of the disordered proteins from the Heslington brain. Therefore, it seems that the intrinsic disorder of NFH, NFM, NFL, GFAP, and MBP, their interactors and many other proteins might play a crucial role in preserving the Heslington brain by forming tightly folded brain protein aggregates, in which different parts are glued together via the disorder-to-order transitions.

Surgical methods for treating spasmodic torticollis include denervation and myotomy (DAM) of the affected muscles, and deep brain stimulation (DBS). This study reports on the long-term efficacy, prognostic factors, safety, and hospitalization costs following these two procedures. We collected data from 94 patients with spasmodic torticollis, of whom 41 and 53 were treated with DAM and DBS, respectively, from June 2008 to December 2020 at the Chinese People’s Liberation Army General Hospital. We used the Tsui scale and the global outcome score of the Toronto Western Spasmodic Torticollis Rating Scale (TWSTRS) to evaluate the preoperative and postoperative clinical condition in all patients. We also determined the cost of hospitalization, prognostic factors, and serious adverse events following the two surgical procedures. The mean follow-up time was 68.83 months (range = 13–116). Both resection surgery and DBS showed good results in terms of Tsui (Z = -5.103, P = 0.000; Z = -6.210, P = 0.000) and TWSTRS scores (t = 8.762, P = 0.000; Z = -6.308, P = 0.000). Compared with the DAM group, the preoperative (47.71, range 24–67.25) and postoperative (18.57, range 0–53) TWSTRS scores in the DBS group were significantly higher (Z = -3.161, P = 0.002). We found no correlation between prognostic factors and the patient age, gender, or disease duration for either surgical procedure. However, prognostic factors were related to the length of the postoperative follow-up period in the DBS surgery group (Z = -2.068, P = 0.039; Z = -3.287, P = 0.001). The mean hospitalization cost in the DBS group was 6.85 times that found in the resection group (Z = -8.284, P = 0.000). The total complication rate was 4.26%. We found, both resection surgery and DBS, showed good results in the patients with spasmodic torticollis. Although DBS had a greater impact on the quality of life and the degree of pain relief, it was more expensive. Prognostic factors were related to the length of the postoperative follow-up period in patients who underwent DBS surgery.

Our brain continuously interacts with the body as we engage with the world. Although we are mostly unaware of internal bodily processes, such as our heartbeats, they may be influenced by and in turn influence our perception and emotional feelings. While there is a recent focus on understanding cardiac interoceptive activity and interaction with brain activity during emotion processing, the investigation of cardiac-brain interactions with more ecologically valid naturalistic emotional stimuli is still very limited. We also do not understand how an essential aspect of emotions like context familiarity influences affective feelings and is linked to cardiac-brain interactions. Hence to answer these questions, we designed an exploratory study by recording ECG and EEG signals for the emotional events while participants were watching emotional movie clips. Participants also rated their familiarity with the stimulus on the familiarity scale. Linear mixed effect modelling was performed in which the ECG power and familiarity were considered as predictors of EEG power. We focused on three brain regions, including prefrontal (PF), frontocentral (FC) and parietooccipital (PO). The analyses showed that cardiac-brain interaction is dependent on familiarity such that the interaction is stronger with high familiarity. In addition, the results indicate that arousal is predicted by cardiac-brain interaction, which also depends on familiarity. The results support emotional theories that emphasize context dependency and interoception. Multimodal studies with more realistic stimuli would further enable us to understand and predict different aspects of emotional experience.

Current lines of research into mood disorders indicate that immune mediators participating in the pathophysiology of chronic somatic disorders have potent influences on brain functions, even when these mediators are produced in peripheral tissues. Elevated levels of circulating immune molecules have been consistently associated with depressive symptoms in a number of clinical populations and experimental models, to the extent that major depressive disorder (MDD) is now seen, at least in part, as a disorder of immunity. This paradigm has brought to the fore the use of anti-inflammatory therapies as adjunctive to standard antidepressant therapy with the hope to improve treatment efficacy, particularly in those cohorts that do not respond well to standard medication. Such new practice requires the availability of biomarkers to tailor these new therapies to those most likely to benefit but also clear mechanisms of action describing the interaction between peripheral immunity and brain function. These mechanisms are generally studied in preclinical models that try to recapitulate the human disease through peripherally induced sickness behaviour as the model for immune-induced MDD. After an appraisal of the data in rodent models and their adherence to the data in clinical cohorts, we propose a modified model of periphery-brain interaction that goes beyond the currently established view of interaction between peripheral cytokines and microglia cells as the driver of depression. Instead, we suggest that brain barriers are primary actors in the communication between body and brain and, as a consequence, in the pathophysiology of the disease. This model suggests novel biomarkers, novel targets for therapies as well as a novel mechanism for resistance to standard treatments.

Image segmentation is a new challenge prob- lem in medical application. The use of medical imaging has become an integral part of research, as it allows us to see inside the human body without surgical intervention. Many researcher have studied brain segmentation. One stage method is used to segment the brain tissues. In this paper, we proposed the multi-stage generative ad- versarial network to solve the problem of information loss in the one-stage. We utilize the coarse-to-fine to improve brain segmentation using multi-stage generative adversar- ial networks (GAN). In the first stage, our model generated a coarse outline for (i) background and (ii) brain tissues. Then, in the second stage, the model generated outline for (i) white matter (WM), (ii) gray matter (GM) and (iii) cerebrospinal fluid (CSF). A good result can be achieved by fusing the coarse outline and refine outline. We conclude that our model is more efficient and accu- rate in practice for both infant and adult brain segmenta- tion. Moreover, we observe that multi-stage model is faster than prior models. To be more specific, the main goal of multi-stage model is to see the performance of the model in a few shot learning case where a few labeled data are available. For medical image, this proposed model can work in a wide range of image segmentation where the convolution neural networks and one-stage methods have failed.

Psychotic disorders occur as a result of pathobiochemical processes in the brain, which disrupt the central neurotransmission of molecules such as dopamine and glutamate. The dopamine hypothesis, adopted more than 2 decades ago, has repeatedly asserted its position as an etiopathogenetic substrate through the action of psychostimulants and neuroleptics on the mesolimbic and mesocortical systems, giving insight into the origin of positive and negative schizophrenic symptoms. On the other hand, cognitive impairments in schizophrenia remain not fully understood but are thought to be present during all stages of the disease, as well as in the prodromal the interictal and residual phases. Over the last decade, functional magnetic resonance imaging has focused on research of brain networks like the Default mode network, the Salience network and Central executive network, enabling a deeper understanding of cognitive deficits, as well as other phenomena such as disorganization of thought and behavior. The study of the nodes of these networks, such as the precuneus and insula, informs about their complex significant roles as structures responsible for important cognitive domains such as concentration, attention, ability to understand and reproduce information, as well as memory functions. It is suggested that the neurotransmission of dopamine and glutamate play a key role in these processes and their successful modulation in the correct brain regions through psychopharmacological and biomedical instrumental methods may lead to a significant reversal of conventional paradigms. Pharmaco-magnetic resonance imaging is a neuroimaging method that can provide the translation of scientific knowledge about the neural networks and the disruptions in and between different brain regions, into clinically applicable and effective therapeutic results in the management of severe psychotic disorders.

Sedation is a ubiquitous practice in ICUs and NCCUs. It has the benefit of reducing cerebral energy demands, but also precludes an accurate neurologic assessment. Because of this, sedation is intermittently stopped for the purposes of a neurologic assessment, which is termed a neurologic wake-up test (NWT). NWTs are considered to be the gold-standard in continued assessment of brain-injured patients under sedation. NWTs also produce an acute stress response that is accompanied by elevations in blood pressure, respiratory rate, heart rate, and ICP. Utilization of cerebral microdialysis and brain tissue oxygen monitoring indicates that this is not mirrored by alterations in overall cerebral metabolism, and seldom affects oxygenation. The hard contraindications for the NWT are preexisting intracranial hypertension, barbiturate treatment, status epilepticus, and hyperthermia. However, hemodynamic instability, sedative use for primary ICP control, and sedative use for severe agitation or respiratory distress are considered significant safety concerns. Despite ubiquitous recommendation, it is not clear if additional clinically relevant information is gleaned through its use, especially with the contemporaneous utilization of multimodality monitoring. Various monitoring modalities provide unique and pertinent information about neurologic function, however, their role in improving patient outcomes and guiding treatment plans has not been fully elucidated. There is a paucity of information pertaining to the optimal frequency of NWTs, and if it differs based on type of injury. Only one concrete recommendation was found in the literature, exemplifying the uncertainty surrounding its utility. The most common sedative used and recommended is propofol because of its rapid onset, short duration, and reduction of cerebral energy requirements. Dexmedetomidine may be employed to facilitate serial NWTs, and should always be used in the non-intubated patient or if propofol infusion syndrome (PRIS) develops. Midazolam is not recommended due to tissue accumulation and residual sedation confounding a reliable NWT. Thus, NWTs are well tolerated in most patients and remain recommended as the gold-standard for continued neuromonitoring. Predicated upon one expert panel, they should be performed at least one time per day. Propofol or dexmedetomidine are the main sedative choices, both enabling a rapid awakening and consistent NWT.

Intranasal (i.n.) administration became an alternative strategy to bypass the blood-brain barrier and improve drug bioavailability in the brain. The main goal of this work was to preliminarily study the biodistribution of mixed amphiphilic mucoadhesive nanoparticles made of chitosan-g-poly(methyl methacrylate) and poly(vinyl alcohol)-g-poly(methyl methacrylate) and ionotropically crosslinked with sodium tripolyphosphate in the brain after intravenous (i.v.) and i.n. administration to Hsd:ICR mice. After i.v. administration, the highest nanoparticle accumulation was detected in the liver, among other peripheral organs. After i.n. administration of a 10-times smaller nanoparticle dose, the accumulation of the nanoparticles in off-target organs was much lower than after i.v. injection. In particular, the accumulation of the nanoparticles in the liver was 20 times lower than by i.v. When brains were analyzed separately, intravenously administered nanoparticles accumulated mainly in the “top” brain, reaching a maximum after 1h. Conversely, in i.n. administration, nanoparticles were detected in the “bottom” brain and the head (maximum reached after 2 h) owing to their retention in the nasal mucosa and could serve as a reservoir from which the drug is released and transported to the brain over time. Overall results indicate that i.n. nanoparticles reach similar brain bioavailability, though with a 10-fold smaller dose, and accumulate in off-target organs to a more limited extent and only after redistribution through the systemic circulation. At the same time, both administration routes seem to lead to differential accumulation in brain regions and thus, they could be beneficial in the treatment of different medical conditions.

Purpose: Dysarthria, a neurological injury of the motor component of the speech circuitry, is of common consequences of traumatic brain injury (TBI). Palilalia is a speech disorder characterized by involuntary repetition of words, phrases, or sentences. Based on the evidence supporting the effectiveness of transcranial direct current stimulation (tDCS) in some speech and language disorders, we hypothesized that using tDCS would enhances the effectiveness of speech therapy in a client with chronic dysarthria following TBI. Method: We applied the constructs of the “Be Clear” protocol, a relatively new approach in speech therapy in dysarthria, together with tDCS on a chronic subject who affected by dysarthria and palilalia after TBI. Since there was no research on the use of tDCS in such cases, regions of interest (ROIs) were identified based on deviant brain electrophysiological patterns in speech tasks and resting state compared with normal expected patterns using the Quantitative Electroencephalography (QEEG) analysis. Results: Measures of perceptual assessments of intelligibility, an important index in the assessment of dysarthria, ​​were superior to the primary protocol results immediately and 4 months after intervention. We did not find any factor other than the use of tDCS to justify this superiority. The percentage of repeated words, an index in palilalia assessment, had a remarkable improvement immediately after intervention but fell somewhat after 4 months. We justified this case with subcortical origins of palilalia. Conclusion: Our present case-based findings suggested that applying tDCS together with speech therapy may improve intelligibility in similar case profiles as compared to traditional speech therapy. To reconfirm the effectiveness of the above approach in cases with dysarthria following TBI, more investigation need to be pursued.

People who suffer a mild traumatic brain injury (mTBI) have heterogeneous symptoms and disease trajectories, which make it difficult to precisely diagnose and assess complications long-term. Insufficient information is available regarding how to precisely diagnose and assess mTBI. This study identified and compared deficits in cognitive, psychosocial, visual functions, and balance performance between college students with and without histories of mTBI. Global DNA methylation ratio (5-mC%) in blood was also compared as a peripheral epigenetic marker. Twenty-five volunteers participated in this pilot study, including 11 mTBI cases (27.3% females; mean age of 28.7 years, SD=5.92) and 14 healthy controls (64.3% females; mean age of 22.0, SD=4.13). All the participants were assessed for cognitive (by NIH toolbox—executive function, memory, and processing speed), psychological (by PROMIS—depression, anxiety, and sleep disturbances), visual function (by King-Devick and binocular accommodative tests), postural balance performance (by a force plate), and blood 5-mC% (global methylation) levels. Students with mTBI reported significantly poorer episodic memory, severe anxiety, and more sleep disturbance problems. They also had higher blood 5-mC% level (all p’s<.05). No significant differences were found in visual function and postural balance. These findings validate changes in cognitive, psychosocial, and global DNA methylation long after mTBI.

Cancer cell lines are widely used as in vitro models of tumorigenesis, facilitating fundamental discoveries in cancer biology and translational medicine. Currently, there are few options for glioblastoma (GBM) treatment and limited in vitro models with accurate genomic and transcriptomic characterization. Here, a detailed characterization of a new GBM cell line, namely AHOL1, was conducted in order to fully characterize its molecular composition based on its copy number alteration (CNA) and transcriptome profiling, followed by the validation of key elements associated with GBM tumorigenesis. Large numbers of CNAs and differentially expressed genes (DEGs) were identified. CNAs were distributed throughout the genome, including gains at Xq11.1-q28, Xp22.33-p11.1, Xq21.1-q21.33, 4p15.1-p14, 8q23.2-q23.3 and losses at Yq11.21-q12, Yp11.31-p11.2 and 12p13.31 positions. Nine druggable genes were identified, including HCRTR2, ETV1, PTPRD, PRKX, STS, RPS6KA6, ZFY, USP9Y and KDM5D. By integrating DEGs and CNAs, we identified 57 overlapping genes enriched in fourteen pathways. Altered expression of several cancer-related candidates found in the DEGs-CNA dataset was confirmed by RT-qPCR. Taken together, this first comprehensive genomic and transcriptomic landscape of AHOL1 provides unique resources for further studies and identifies several druggable targets that may be useful for therapeutics and biologic and molecular investigation of GBM.

In quantum approaches to consciousness, the authors try to propose a model and mechanism for the mind-brain interaction using modern physics and some quantum concepts which do not exist in the classical physics. The independent effect of mind on the brain has been one of the challenging issues in the history of science and philosophy. In some recent mind-brain interaction models, the direct influence of mind on matter is either not accepted (as in Stapp’s model) or not clear, and there have not been any clear mechanism for it (as in Penrose-Hameroff’s model or in Eccles’s model). In this manuscript we propose a model and mechanism for mind’s effect on the matter using an extended Bohmian quantum mechanics and Avicenna’s ideas. We show that mind and mental states can affect brain’s activity without any violation of physical laws. This is a mathematical and descriptive model which shows the possibility of providing a causal model for mind’s effect on matter. It is shown that this model guarantees the realistic philosophical constraints and respects the laws of nature. In addition, it is shown that it is in agreement with the Libet style experimental results and parapsychological data. To propose this model, we obtained a modified (non-unitary) Schrödinger equation via second quantization method which affects the particle through a modified quantum potential and a new term in the continuity equation. At the second quantized level, which is equivalent to quantum field theory level (QFT), we can use the path integral formalism of Feynman. We show that there are three methods to extend Bohmian QM via path integral formalism, which has different interpretations. By numerical simulation of trajectories in the two-slits experiment, we show their differences and choose one of these methods for our mind-brain model which can be the basis for explaining some phenomena which are not possible to explain in the standard Bohmian QM.

We take what we see, hear, smell and feel for the reality. However, as neuroscientists, we know that this reality, that is, our perceptual world, is in fact made up by the brain from the processing of the nerve impulses coming from receptors. Ancient Greeks used to think that this perceptual world, sometimes called our 3D movie (Chalmers), is emitted and has its own physical nature. Given how real the 3D movie looks to us, it is still difficult today to consider that all we would be dealing with would be patterns of brain activity The present study thus aimed at testing whether the perceptual world could have some physical existence in addition to that of the neural patterns responsible for it. To achieve that goal, we tried to see whether brains could be sensitive to the 3D movie of others. This, admittedly unusual, operational hypothesis was based on two assumptions. First, brains are sensitive to the 3D movie, as our experience includes reactions to our perceptual world. Second, the physicality at stake does not differ across individuals. We recorded the event-related brain potentials (ERPs) evoked by stimuli of the international affective picture system in pairs of closely-related participants. Most importantly, they could neither see the stimuli simultaneously presented to their partners nor their reactions to them. As in Bouten et al. (2015), around 400 ms after the onset of the stimuli, ERPs started being more positive in inconsistent conditions. Namely, when the two subjects of each pair were presented with the same stimulus whereas they were told it would be a different one and vice-versa (i.e., different-stimuli expected to be same). ERPs were less positive when the two subjects of a pair were presented with the same stimuli and were told they were the same and conversely (i.e., different-stimuli expected to be different). The same experiment was then run in pairs of strangers. No significant effect of consistency on ERPs was observed even though participants could, this time, see, in the very periphery of their visual field, the reactions of their partner to the stimuli. We thus use the results of both studies to support a new version of the emission theory of consciousness and to suggest that the sensitivity to the perceptual world of others may depend on their prior familiarity with it.

Few prior works study self-driving cars by deep learning with IoT collaboration. SDC-Net, which is an end-to-end multitask self-driving car camera cocoon IoT-based system, is one of the research that tackles this direction. However, by design SDC-Net is not able to identify the accident locations, it only classifies if it is a crash scene or not. In this work, we introduce an enhanced design for the SDC-Net system by 1) replacing the classification network with a detection one, 2) adapting our benchmark dataset labels built on the CARLA simulator to include the vehicles bounding boxes while keeping the same training, validation, and testing samples, 3) modifying the shared information via IoT to include the accident location. We keep the same path planning and automatic emergency braking network, the digital automation platform, and the input representations to formulate the comparative study. SDC-Net++ system is proposed to 1) output the relevant control actions, especially in case of accidents: accelerate, decelerate, maneuver, and brake, and 2) share the most critical information to the connected vehicles via IoT, especially the accident locations. A comparative study is also conducted between SDC-Net and SDC-Net++ with the same input representations: front camera only, panorama and bird-eye views, and with single-task networks: crash avoidance only, and multitask networks. Multitask network with a BEV input representation outperforms the nearest representation in precision, recall, f1-score, and accuracy by more than 15.134%, 12.046%, 13.593%, and 5%, respectively. SDC-Net++ multitask network with BEV outperforms SDC-Net multitask with BEV in precision, recall, f1-score, accuracy, and average MSE by more than 2.201%, 2.8%, 2.505%, 2%, and 18.677% respectively.

A single paragraph of about 200 words maximum. For research articles, abstracts should give a pertinent overview of the work. We strongly encourage authors to use the following style of structured abstracts, but without headings: (1) Background: Place the question addressed in a broad context and highlight the purpose of the study; (2) Methods: briefly describe the main methods or treatments applied; (3) Results: summarize the article’s main findings; (4) Conclusions: indicate the main conclusions or interpretations. The abstract should be an objective representation of the article and it must not contain results that are not presented and substantiated in the main text and should not exaggerate the main conclusions.

Deep learning heavily relies on statistical correlations to drive artificial intelligence (AI) innovations, particularly in computer vision applications like autonomous driving and robotics. However, despite providing a solid foundation for deep learning, these statistical correlations can be vulnerable to unforeseen and uncontrolled factors. The lack of prior knowledge guidance can result in spurious correlations, introducing confounding factors and affecting the model's robustness. To address this challenge, recent research efforts have focused on integrating causal theory into deep learning methodologies. By modelling the inherent and unbiased causal structure, causal theory can potentially mitigate the impact of spurious correlations effectively. Hence, this paper explores the basics of causal methodologies in image classification.

Document deskewing is a fundamental problem in document image processing. While existing methods have limitations, such as Hough Line Transformation that can deskew images upside down, and Deep Learning models that require huge amounts of human labour and computational resources and still fail to deskew while taking care of orientation, OCR-based methods also struggle to read text when it is tilted. In this paper, we propose a novel, simple, cost-effective deep learning method for fixing the skew and orientation of documents. Our approach reduces the search space for the machine learning model to predict whether an image is upside down or not, avoiding the huge search space of predicting an angle between 0 and 360. We finetuned a MobileNetV2 model, which was pre-trained on imagenet, using only 200 images and achieve good results. This method is useful for automation-based tasks, such as data extraction using OCR technology, and can greatly reduce manual labour.

A machine learning method for classifying Lung UltraSound is here proposed to pro- vide a point of care tool for supporting a safe, fast and accurate diagnosis, that can also be useful during a pandemic like as SARS-CoV-2. Given the advantages (e.g. safety, rapidity, portability, cost-effectiveness) provided by the ultrasound technology over other methods (e.g. X-ray, computer tomography, magnetic resonance imaging), our method was validated on the largest LUS public dataset. Focusing on both accuracy and efficiency, our solution is based on an efficient adaptive ensembling of two EfficientNet-b0 models reaching 100% of accuracy, which, to our knowledge, outperforms the previous state-of-the-art. The complexity of this solution keeps the number of parameters in the same order as an EfficientNet-b0 by adopting specific design choices that are adaptive ensembling with a combination layer, ensembling performed on the deep features, minimal ensemble only two weak models. Moreover, a visual analysis of the saliency maps on sample images of all the classes of the dataset reveals where the focus is on an inaccurate weak model versus an accurate model.

Diffuse interstitial lung diseases (DILD) are a heterogeneous group of over 200 entities, some with dramatical evolution and poor prognostic. Because of their overlapping clinical, physiopathological and imagistic nature, successful management requires early detection and proper progression evaluation. This paper tests a complex networks (CN) algorithm for imagistic aided diagnosis fitness for the possibility of achieving relevant and novel DILD management data. 65 DILD and 31 normal high resolution computer tomography (HRCT) scans were selected and analyzed with the CN model. The algorithm is showcased in two case reports and then statistical analysis on the entire lot shows that a CN algorithm quantifies progression evaluation with a very fine accuracy, surpassing functional parameters’ variations. The CN algorithm can also be successfully used for early detection, mainly on the ground glass opacity Hounsfield Units band of the scan.

Chimeric antigen receptor T cells (CAR-Ts) have shown a remarkable efficacy in hematological malignancies, but limited responses in solid tumors. Among solid tumors, CAR-T cell therapy was particularly explored in brain tumors. CAR-T cells have shown a limited clinical efficacy in various types of brain tumors due to several factors that have hampered their activity, including tumor antigen heterogeneity (not all tumor cells express the target antigen), the limited access of CAR-T cells to brain tumor cells, limited CAR-T cell trafficking and in vivo persistence and the presence of a highly immunosuppressive tumor microenvironment. Despite these considerations, some recent studies have shown promising anti-tumor activity of GD2-CAR-T cells on diffuse midline gliomas and neuroblastomas and of CARv3-TEAM-E cells in glioblastomas. However, strategies are required to improve the effect of CAR-T cells in brain tumors, including advanced CAR-T cell design with multiple antigenic targeting and incorporation of combination therapies.

The detection of early biomarkers and molecular mechanisms in Parkinson’s disease (PD) remains a challenge. Recent research has pointed to potential roles for peptidylarginine deiminases (PADs), a family of calcium activated enzymes, and associated post-translational protein citrul-lination/deimination in early stages of the disease, with a focus on hippocampal and cortex re-gions of the brain. Further analysis of brain region specific changes in PAD isozymes and identi-fication of brain-region specific citrullinomes, therefore remain to be studied. This study assessed brain-region specific PAD isozyme expression (PADs 1-4; PAD6) and associated citrullinated protein targets in the 6-hydroxydopamine (6-OHDA) induced rat model of pre-motor PD. Cortex, hippocampus, striatum, midbrain, cerebellum and olfactory bulb were compared between con-trols/shams and the PD model. In cortex, a significant increase of PAD2 and PAD3 was observed in the PD model. In hippocampus, PAD3, PAD4 and PAD6 showed strongest levels, but with no significant changes observed between PD and controls. In striatum, a significant reduction in all PAD isozymes was observed in the PD model. In the olfactory bulb, PAD3 was significantly el-evated in PD. In midbrain, PAD2, PAD4 and PAD6 showed strongest signal but with no signifi-cant changes between PD and controls. In cerebellum, a significant increase was seen in PAD3, PAD4 and PAD6 in the PD model. Citrullinated protein hits were most abundant in cortex and hippocampus, while for the PD model an increase in citrullinated hits was particularly observed in cortex and cerebellum, compared to controls. For all brain regions there was a considerable difference in citrullinated protein IDs between the PD model and the controls. Citrullinome as-sociated KEGG pathways differed in the six brain regions; some were overlapping for controls and PD, some were identified for the PD model only, and some were identified in control brains only. KEGG pathways identified in PD brains onlywere: “Axon guidance”; “Spinocerebellar ataxia”; “Hippo signalling pathway”; “NOD-like receptor signalling pathway”; “Phosphatidyl-inositol signalling system”; “Rap1 signalling pathway”; “Platelet activation”; “Yersinia infection”; “Fc gamma R-mediated phagocytosis”; “Human cytomegalovirus infection”; “Inositol phosphate metabolism”; “Thyroid hormone signalling pathway”; “Progesterone-mediated oocyte matura-tion”; “Oocyte meiosis”; and “Choline metabolism in cancer”. Our findings highlight differences in PAD isozymes, citrullinated proteins and associated KEGG pathways between brain regions, in pre-motor PD.

Objective: To investigate whether the relationships between acute care occupational therapy (OT) and physical therapy (PT) utilization and community discharge are moderated by functional or physical performance at discharge among individuals hospitalized with traumatic brain injury (TBI). Setting: 14 acute care hospitals in the state of Colorado. Participants: We studied 5,599 adults hospitalized with TBI between June 2018 and April 2021. Design: In a secondary analysis of de-identified electronic health record (EHR) data, multivariable moderation logistic regression models were performed to calculate odds ratios (ORs) for the likelihood of community discharge among patients who utilized OT/PT services. Main Measures: Functional (activities of daily living [ADL]) and physical (mobility) performance at discharge, OT and PT utilization, and community discharge status. Results: Overall, 67% of patients discharged to the community. The mean age of the sample was 55 years (SD = 20 years). Most participants were male (64%) and non-Hispanic white (72%). Mean hospital length of stay was 6 days (SD = 6 days). Both OT and PT utilization (OT: OR= 1.21, 95% CI [1.11, 1.33]; PT: OR= 1.22, 95% CI [1.14, 1.30]) and discharge ADL and mobility scores (ADL: OR= 1.34, 95% CI [1.30, 1.39]; mobility: OR= 1.38, 95% CI [1.33, 1.42]) were significantly and positively associated with community discharge. The OT and PT utilization-by-discharge ADL and mobility interaction terms yielded slightly negative, but statistically significant moderation effects in both models (ORs= 0.99, 95% CIs [0.98, 1.00]); indicating the magnitude of the OT and PT utilization effect diminished as ADL and mobility scores increased. Several sociodemographic characteristics and clinical factors were also independently associated with community discharge in both models (p-values

Brain tumors are frequently classified with high accuracy using convolutional neural networks (CNNs) and better comprehend the spatial connections among pixels in complex pictures. Due to their tiny receptive fields, the majority of deep convolutional neural network (DCNN)-based techniques overfit and are unable to extract global context information from more significant regions. While dilated convolution retains data resolution at the output layer and increases the receptive field without adding computation, stacking several dilated convolutions has the drawback of producing a grid effect. To handle gridding artifacts and extract both coarse and fine features from the images, this research suggests using a dilated parallel deep convolutional neural network (PDCNN) architecture that preserves a wide receptive field. To reduce complexity, initially, input images are resized and then grayscale transformed. Data augmentation has since been used to expand the number of datasets. Dilated PDCNN makes use of the lower computational overhead and contributes to the reduction of gridding artifacts. By contrasting various dilation rates, the global path uses a low dilation rate (2,1,1), while the local path uses a high dilation rate (4,2,1) for decremental even numbers to tackle gridding artifacts and extract both coarse and fine features from the two parallel paths. Using three different types of MRI datasets, the suggested dilated PDCNN with the average ensemble method performs better. The accuracy provided by the Multiclass Kaggle dataset-III, Figshare dataset-II, and Binary tumor identification dataset-I is 98.35%, 98.13%, and 98.67%, respectively. In comparison to state-of-the-art techniques, the suggested structure improves results by extracting both fine and coarse features, making it efficient.

Health-Related Quality of Life (HRQoL) encompasses the comprehensive evaluation of an indi-vidual's health and well-being across multiple dimensions. Mindfulness, recognized as a scientifi-cally supported strategy for anxiety management, plays a role in enhancing both physical and mental health. The Gut-Brain Axis (GBA) serves as the bidirectional communication link between the gastrointestinal system and the central nervous system. This study aims to explore the associa-tion between Mindfulness and factors influencing the GBA in both healthy individuals and those with Inflammatory Bowel Diseases (IBD). A cross-sectional investigation involved 338 adults, in-cluding 50 IBD patients, utilizing validated Greek scales for Mindfulness (MAAS-15), Mediterra-nean Diet (14-MEDAS), and HRQoL (EQ-5D-5L). The questionnaire gathered demographic, an-thropometric, and lifestyle data. Among healthy participants, EQ-5D-5L showed a moderate cor-relation with the MAAS-15 scale (r=0.389, p

Objective: The COVID-19 pandemic inferred on neuro-oncological patients (PTS) and the caregivers regarding tumor care and emotional functioning. This study aimed to understand how COVID-19 affects their psychological state and relations between PTS and health personnel in neuro-oncology. Methods: A cross-sectional study on neuro-oncological PTS and their caregivers. Results: A total of 162 PTS and 66 caregivers completed the questionnaire. The 37.5% of PTS perceived greater risk of contracting the COVID-19 compared to the general population. On the 0-10 scale, PTS tumor-related anxiety score was 5.8 and COVID-related 4.6. The caregivers reported 7.7 and 5.5 respectively. The QoL was described at least as good in 75% of both PTS and caregivers; the caregivers’ care burden increased in 22.7% during the pandemic, with no correlation with QoL. Future perception often changed both in PTS and in the caregivers. Cancer treatment schedule was changed in 18.5%, including for PTS decision. However, the 93.5% of PTS was satisfied with the overall care. Conclusion: A considerable proportion of PTS and caregivers still perceived the tumor disease as more burdensome than the pandemic, and perceived their future as more uncertain. Such data rinforce the need to build a proficient alliance between PTS and health personnel.

Iron deficiency in the fetal and neonatal period (perinatal iron deficiency) bodes poorly to neuro-development. Given its common occurrence and the negative impact on brain development, a screening and treatment strategy that is focused on optimizing brain development in perinatal iron deficiency is necessary. Pediatric societies currently recommend a universal iron supple-mentation strategy for full-term and preterm infants that does not consider individual variation in the body iron status and could lead to under-treatment or over-treatment. Moreover, the focus is on hematological normalcy and not optimal brain development. Several serum iron indices and hematological parameters in the perinatal period are associated with risk of abnormal neurodevelopment, suggesting their potential use as biomarkers for screening and monitoring treatment in infants at risk for perinatal iron deficiency. A biomarker-based screening and treatment strategy that is focused on optimizing brain development will likely improve outcome in perinatal iron deficiency.

The microalgae Phaeodactylum tricornutum (PT) is distinguished by its rich nutrient profile, characterized by well-documented neuroprotective activities, including fucoxanthin (FX), a major carotenoid, and polyunsaturated omega-3 fatty acids (n-3 PUFA). The current study aims to evaluate the protective effects of a standardized extract of PT (Mi136) containing 2% FX on cognitive function, oxidative stress, and inflammation parameters in a mouse model of accelerated aging. Seventy-two (72) male mice were randomly assigned to the blank control group (BC), negative control group (NC), and four similar microalgae extract of PT groups (branded as BrainPhytTM) with different human equivalent doses. From day 01 to day 51, mice in the BC group were injected with a 0.9% normal saline solution, while mice in all other groups were subcutaneously injected with D-galactose (D-Gal) at a dose of 150 mg/kg once per day, five days per week. Results indicated that, for the three higher microalgae extract of PT dose groups, spatial cognitive function, swim latency, and step-through latency impairments induced by chronic D-Gal intoxication were significantly and fully inhibited, with mean values similar to those in the BC group during each day of testing. Similar benefits were observed in biochemical analysis, specifically regarding brain and plasma levels of lipid peroxidation, TNF-α, and IL-6 markers. These data underscore the positive effects of a standardized extract of PT containing 2% FX on cognitive function parameters such as spatial working memory, long-term memory, and short-term memory through the regulation of oxidative stress and inflammation pathways.

The orbitofrontal cortex (OFC) area plays a critical role in human brain functions. However, susceptibility differences between paranasal sinuses and nasal cavity tissues often cause local field variations in the OFC during MRI, resulting in image distortions and signal loss. In this paper, we introduce a subject-friendly neck passive shim solution aimed at enhancing field homogeneity in the brain, specifically in the OFC region. Utilizing 3D gradient-echo pulse sequences, main magnetic field (B0) maps of four subjects’ brains were acquired at 4T MRI. Subsequently, these maps were decomposed into spherical harmonic coefficients and averaged. Optimal positions for placing shim elements on a semi-cylindrical surface, positioned slightly above the neck and below the chin, were computed. The findings indicate a substantial enhancement in B0 homogeneity, particularly within the OFC region, through the integration of this semi-cylindrical passive shim system in conjunction with first and second-order active shimming.

Background: Increase of collagen I (COL I)/COL III ratio enhances vessel wall stiffness and renders vessels less resistant to blood flow and pressure changes. We hypothesized that COL I/COL III ratio is increased in the brain arteriovenous malformations (bAVMs), which is associated with bAVM hemorrhage. Method: Surgically resected human bAVM samples and mouse bAVMs induced in three transgenic mouse lines with activin receptor-like kinase 1 or endoglin deletion in the endothelial cells or in the brain focally. Colony-stimulating factor receptor inhibitor was used to transiently deplete microglia. COL I and COL III levels, hemorrhage, and gene expression in bAVMs were analyzed. Results: The COL I and COL III levels and the COL I/COL III ratio were higher on human and mouse bAVMs than controls, which was associated with bAVM hemorrhage. Col I and Col III mRNAs were also increased in mouse bAVMs. The degree of microhemorrhage in mouse bAVMs was positively correlated with Col I/Col III ratios. Transient depletion of microglia reduced Col I/Col III ratio and microhemorrhage in mouse bAVMs. Conclusion: COL I/COL III ratio are increased in bAVM vessels, which is associated with bAVM hemorrhage. Depletion of microglia reduces Col I/Col III ratio and hemorrhage in mice bAVMs.

Background: Aging rate is affected by genetic changes, epigenetic modifications, oxidative stress, inflammation, lifestyle and environmental factors. In accelerated aging (AA), biological age exceeds the chronological one. Objective: To undertake a critical reappraisal of the AA concept and to reveal its weaknesses and limitations. Methods: We reviewed over 300 recent articles dealing with physiology of brain aging and pathophysiology of neurodegeneration. Results: (1) Organ systems age at different rates, which interferes with application of the AA concept to individual organs. (2) Aging rate can be decelerated due to individual structure–functional reserves built with cognitive, physical training or pharmacological interventions. (3) The AA concept lacks standardised terminology and methodology. (4) Specific molecular biomarkers (MBM) reflect aging. To consolidate the AA theory, researchers should validate numerous MBM candidates. (5) Aging factors, mechanisms and the exact nature of their biological outcomes are not well understood. Conclusion: Although considered as a perspective theory, the AA concept has serious limitations and it requires an update.

Device-mediated, non-invasive drug delivery across the blood-brain barrier (BBB) represents a significant advancement in treating neurological diseases. The BBB is a tightly packed layer of endothelial cells that shields the brain from harmful substances in the blood, allowing necessary nutrients to pass through. It is a highly selective barrier, which poses a challenge to delivering therapeutic agents into the brain. Several non-invasive techniques and devices have been proposed or investigated to enhance drug delivery across the BBB. This paper presents the current state of the art and case studies that address the pharmacology, technology, delivery systems, regulatory approval, ethical concerns, and future possibilities.

Alzheimer’s disease (AD) and vascular dementia (VaD) together contribute to almost 90% of all dementia cases leading to major health challenges of our time with a substantial global socioeconomic burden. While in Alzheimer’s disease, the improved understanding of Amyloid beta (Aß) mismetabolism and tau hyperphosphorylation as pathophysiological hallmarks has led to significant clinical breakthroughs, similar advances in VaD are lacking. We thus highlight here the importance of shared pathomechanisms found in AD and VaD: Endothelial damage, blood brain barrier (BBB) breakdown and hypoperfusion inducing oxidative stress, inflammation and demyelination and thus trophic uncoupling in the neurovascular unit. A dysfunctional endothelium and BBB lead to the accumulation of neurotoxic molecules and Aß through impaired clearance, which in turn leads to neurodegeneration. In this context we discuss possible neuropathological parameters, which might serve as biomarkers and thus improve diagnostic accuracy or reveal targets for novel therapeutic strategies for both forms of dementia.

Eutherians have 11 retrotransposon Gag-like (RTL)/sushi-ichi retrotransposon homolog (SIRH) genes presumably derived from a certain retrovirus. Accumulating evidence indicates that the RTL/SIRH genes play a variety of roles in the current mammalian developmental system, such as in the placenta, brain and innate immune system in a eutherian-specific manner. It has been shown that the functional role of Paternally Expressed 10 (PEG10) in placental formation is unique to the therian mammals, as are the eutherian-specific roles of PEG10 and PEG11/RTL1 in maintaining the fetal capillary network and the endocrine regulation of RTL7/SIRH7 (aka Leucine Zipper Down-Regulated in Cancer 1 (LDOCK1)) in the placenta. In the brain, PEG11/RTL1 is expressed in the corticospinal tract and hippocampal commissure, mammalian-specific structures, and in the corpus callosum, a eutherian-specific structure. Unexpectedly, at least three RTL/SIRH genes, RTL5/SIRH8, RTL6/SIRH3 and RTL9/SIRH10, play important roles in combating a variety of pathogens, viruses, bacteria and fungi, respectively, suggesting that the innate immunity system of the brain in eutherians has been enhanced by the emergence of these new components. In this review, we will summarize the function of 10 out of the 11 RTL/SIRH genes and discuss their roles in eutherian development and evolution.

Postural instability (PI) in Parkinson’s disease (PD) exposes patients to increased risk of falls (RF). Although dopaminergic therapy and deep brain stimulation (DBS) improve motor performance in advanced PD patients, their effects on PI and RF are not clear. PI and RF were assessed by a stabilometric platform in 6 advanced PD patients. Patients were evaluated on and off dopaminergic medication and four DBS conditions: bilateral-DBS, DBS of the more- or less-affected side and DBS-off. Dopaminergic medication alone worsened PI and RF, DBS alone worsened RF, and no medication/DBS combination produced an improvement in postural control with respect to the OFF-medication/DBS-off condition. When ON-medication, PI and RF significantly improved after turning the DBS on, regardless of medication condition. Among DBS conditions, bilateral-DBS provided the maximal improvement of PI and RF when ON medication, and minimal worsening of PI and RF when OFF medication, whereas patients performed worse when in most-affected side DBS condition. These results can help in developing the best therapeutic strategy for postural disorders in patients with advanced PD.

Neurodegenerative diseases encompass a broad spectrum of profoundly disabling disorders that impact millions of individuals globally. While their underlying causes and pathophysiol-ogy display considerable diversity and remain incompletely understood, a mounting body of evidence indicates that the disruption of blood-brain barrier (BBB) permeability, resulting in brain damage and neuroinflammation, constitutes a shared characteristic among them. Con-sequently, targeting the BBB has emerged as an innovative therapeutic strategy for address-ing neurological diseases. Within this review, we not only explore the neuroprotective, neu-rotrophic, and immunomodulatory benefits of mesenchymal stem cells (MSCs) in combating neurodegeneration but also delve into their recent role in modulating the BBB. We will delve into the cellular and molecular mechanisms through which MSC treatment impacts primary age-related neurological disorders like Alzheimer’s disease, Parkinson’s disease, and stroke as well as immune-mediated conditions such as multiple sclerosis. Our focus will center on how MSCs participate in the modulation of cell transporters, matrix remodeling, stabilization of cell-junction components, and restoration of BBB network integrity in these pathological con-texts.

Bone marrow mononuclear cells (BMMNCs) have emerged as a potential therapeutic strategy for various incurable conditions including autism spectrum disorder (ASD). To study its safety and efficacy, we analyzed 1011 patients who underwent intrathecal administration of autologous BMMNCs along with neurorehabilitation. At mean follow-up of 19.3 months after intervention, 90.6% patients showed overall improvement. Improvements were observed in attention concentration, command following, eye contact, sitting tolerance, social interaction, hyperactivity, communication, speech, aggressiveness, stereotypical and self-injurious behavior. Statistically significant changes were observed in scores of Indian Scale of Autism Assessment and Childhood Autism Rating Scale (p<0.05). On subgroup analysis, improvements were recorded irrespective of age and disease severity and better outcome was observed in patients who took multiple doses of cell therapy compared to single dose. Comparative Brain PET-CT scan of 401 patients showed improved brain metabolism after the intervention. No major adverse events were reported. Only 9 out of 1011 patients experienced seizures which were managed using medications. 4 out of 9 had history of seizures while 5 had normal EEG with no history. However, improvements were still observed in these 9 patients. Thus, intrathecal transplantation of autologous BMMNCs along with neurorehabilitation is safe and efficacious in patients with ASD.

Background: This study investigated the incidence, characteristics and functional outcomes associated with unplanned Acute Care Unit Readmissions (ACUR) during inpatient traumatic brain injury (TBI) rehabilitation in an Asian cohort. Methods: Retrospective review of electronic medical records from single rehabilitation unit was conducted from 1 Jan 2012 to 31 Dec 2014. Inclusion criteria were first TBI, aged &gt;18 years, admitted &lt; 6 months of TBI. ACUR were characterized into either of neurological, medical or neurosurgical subtypes. The main outcome measure was discharge Functional Independence Measure (FIM). Secondary outcomes included rehabilitation length of stay (RLOS). Results: Of 121 eligible TBI records, the incidence of ACUR was 14% (n=17), comprising neurologic (76.5%) and medical (23.5%) subtypes, occurring at median of 13 days (IQR 6, 28.5) after rehabilitation admission. Patients without ACUR had significantly higher admission mean (SD) FIM score compared to those with ACUR (FIM ACUR-negative 63.4 (21.1) vs FIM ACUR-positive 50.53(25.4), P =0.026). Significantly lower discharge FIM was noted in those with ACUR compared to those without. (FIM ACUR-positive 65.8(31.4) vs FIM ACUR-negative 85.4 (21.1), P = 0.023) Furthermore, a significant near-doubling of RLOS was noted in ACUR patients compared to non-ACUR counterparts [ACUR-positive median 55 days (IQR 34.50, 87.50) vs ACUR-negative median 28 days (IQR 16.25, 40.00), P = 0.002]. Conclusion: This study highlights the significant negative functional impact and lengthening of rehabilitation duration of ACUR on inpatient rehabilitation outcome for TBI.

Judo is a popular Japanese martial art and an Olympic sport. Recently, an increasing interest has been observed in the application of judo as a multicomponent exercise, with a growing body of evidence showing that multicomponent exercise improves physical and cognitive performance in older adults. Therefore, this review highlights the benefits of judo training in preventing physical and cognitive decline in older adults. Specifically, first, this review outlines the basic characteristics of judo (philosophy, match, and training). Next, previous studies investigating the effects of judo training on physical and cognitive aspects of older adults are reviewed. Thereafter, the brain mechanisms underlying the effects of judo training in improving physical and cognitive performance are discussed. Throughout this review, judo training demonstrated some positive effects on physical (gait and balance, among others) and cognitive (memory and executive function) function in older adults. These positive effects are attributed to a variety of changes in the brain (e.g., increased neurotrophic factor expression and increased cerebral blood flow, among others), that affect different brain regions and networks both functionally and structurally. From these findings, this review concludes that judo training can be an effective way to maintain and prevent physical and cognitive decline in older adults.

In this work, we developed a highly sensitive multiplexed immunosensor for direct simultaneous detection of both N-terminal Natriuretic Peptide (NT-proBNP) and Cortisol in human artificial saliva (AS). The developed biosensor platform based on silicon nitride was composed from four gold working microelectrodes (WEs) and an integrated counter and reference electrode. Gold WEs were biofunctionalized through carboxyl diazonium (4-APA) to immobilize both anti- NT-proBNP and anti-Cortisol antibodies for simultaneous detection. The electroaddressing of the 4-APA onto the gold WE surfaces was realized by cyclic voltammetry (CV), while the interaction between antibodies and antigens in PBS was monitored by electrochemical impedance spectroscopy (EIS). The antigen detection in human AS was realized by EIS combined with the standard addition method. The immunesensor was highly sensitive and selective toward the corresponding biomarkers in both PBS and artificial human saliva as well as in the presence of other potential interfering biomarkers such as tumor necrosis factor alpha (TNF-α) and interleukin-10 (IL-10). The limit of detection (LOD) was at 0.2pg/mL for NT-proBNP within the range 0.03 to 0.9pg/mL, while the LOD for Cortisol was 0.06 ng/mL within the range 0.02 to 0.6 ng/mL for Cortisol in artificial saliva. The developed immunosensor is very promising for significant detection time reducing as it allows the simultaneous detection of various biomarkers.

Amphetamine is a psychostimulant drug with a high risk of toxicity and death when misused. Abuse of amphetamines is associated with an altered organic profile, which includes omega fatty acids. Low omega fatty acid levels are linked to mental disorders. Using the Comparative Toxicogenomic Database (CTD), we investigated the chemical profile of the brain in amphetamine-related fatalities and the possibility of neurotoxicity. We classified amphetamine cases as low (0-0.5 g/ml), medium (&gt;0.5 to 1.5 g/ml), and high (&gt;1.5 g/ml) based on amphetamine levels in brain samples. All three groups shared 1-octadecene, 1-tridecene, 2,4-di-tert-butylphenol, arachidonic acid, docosahexaenoic acid (DHA), eicosane, and oleylamide. We identified chemical-disease associations using the CTD tools and predict an association between docosahexaenoic and arachidonic acids and curated conditions like autistic disorder, disorders related to cocaine, Alzheimer's disease, and cognitive dysfunction. An amphetamine challenge may cause neurotoxicity in the human brain due to a decrease in omega-3 fatty acids and an increase in oxidative products. Therefore, in cases of amphetamine toxicity, supplement therapy may necessitate preventing omega-3 fatty acid deficiency.

Background: Anemia is one of the most frequent diseases worldwide, affecting a third of the general population. Anemia in general and in particular, iron-deficient anemia (IDA), has been associated to a higher risk of thrombotic manifestations, including ischemic stroke and cerebral venous thrombosis (CVT), as well as systemic extra cerebral arterial and venous thrombosis. Despite these data, anemia is seldom considered as an etiological factor of stroke. Methods: An individual case encompassing all known neurovascular and systemic arterial and venous thrombotic manifestations related to IDA is presented with the focus on clinical reasoning issues in the diagnostic pathways, starting from the neuroradiological signs. The main questions have been identified and addressed in a narrative review of the most relevant data in the literature from a pragmatic and clinical viewpoint. Results and Discussion: The presented case concerns a 46 years old man admitted to the Stroke Unit because of acute is-chemic stroke with multiple thrombi in large intracranial and extracranial vessels, multifocal ischemic lesions in several arterial territories and the concurrent finding of asymptomatic CVT, pulmonary embolism with lung infarction and aortic thrombosis. An extended diagnostic work-up excluded the main etiologies (arterial dissection, cardiac embolism, genetic and acquired prothrombotic disorders, as cancer and antiphospholipid syndrome), except for a severe IDA, such as to require blood transfusions followed by anticoagulant therapy for the several thrombotic manifestations. Neuroimaging and systemic vascular findings have been analyzed and the main issues proposed by the case in the diagnostic pathway have been identified and discussed in a pragmatic clinical road map reviewing the data provided by the literature. Conclusions: IDA is a common but treatable condition that, independently or synergically, may increase the risk of thrombotic events. The diagnostic and therapeutic approach has not yet defined and each case should be individually addressed in a pragmatic clinical road map.

‘Dysbiosis’ of the adult gut microbiota, in response to challenges such as infection, altered diet, stress, and antibiotics treatment has been recently linked to pathological alteration of brain func-tion and behavior. Moreover, gut microbiota composition constantly controls microglia matura-tion as revealed by morphological observations and gene expression analysis. However, it is un-clear whether gut microbiota influences microglia functional properties and crosstalk with neu-rons, known to shape and modulate synaptic development and function. Here, we investigated how antibiotic mediated alteration of the gut microbiota influences microglial and neuronal functions in adult mice hippocampus. Hippocampal microglia from adult mice treated with oral antibiotics exhibited increased microglia density, altered basal patrolling activity, and impaired process rearrangement in response to damage. Patch clamp recordings at CA3-CA1 synapses revealed that antibiotics treatment alters neuronal functions, reducing spontaneous postsynaptic glutamatergic currents and decreasing synaptic connectivity, without reducing dendritic spines density. The effect of dysbiosis on neuronal functions are mediated by microglia-neuron cross-talk through the CX3CL1-CX3CR1 axis, as antibiotics treatment of CX3CR1 deficient mice, mod-ulates microglia density and processes rearrangement leaving unaltered synaptic function. To-gether, our findings show that the antibiotics alteration of gut microbiota impairs synaptic effi-cacy, probably through CX3CL1-CX3CR1 signaling supporting microglia as a major player in in the gut-brain axis, and in particular in the gut microbiota-to-neuron communication pathway.

Levodopa remains the primary drug for controlling motor symptoms in Parkinson's disease through the whole course, but over time complications develop in the form of dyskinesias, which gradually become more frequent and severe. These abnormal, involuntary, hyperkinetic movements are mostly characteristic of the ON phase and reflect an excess of exogenous levodopa. They may also occur during OFF phase, or in both phases. Over the past 10 years, the issue of levodopa-induced dyskinesia has been the subject of research into both the substrate of this pathology and potential remedial strategies. The purpose of the present study was to review the results of recent research on the background and treatment of dyskinesia. To this end, databases were reviewed using a search strategy that included both relevant keywords related to the topic and appropriate filters to limit results to English-language literature published since 2010. Based on the selected papers, the current state of knowledge on morphological, functional, genetic, and clinical features of levodopa-induced dyskinesia, as well as pharmacological, genetic treatment and other therapies such as deep brain stimulation are described.

Pervasive and wide-ranging cognitive deficits are a core feature of schizophrenia and an important determinant of long-term functional outcome. The lack of sufficiently effective treatments for cognitive impairment associated with schizophrenia (CIAS) represents a major unmet need and a central roadblock towards recovery. This is partly due to the current therapeutic focus on clinical symptoms, and the relative neglect of cognitive impairments despite their functionally disabling effects. Furthermore, effective treatment is impeded by our limited knowledge of the complex pathophysiology, which gives rise to perturbed information processing. Here, we review mechanisms and effectiveness of available pharmacological and non-pharmacological treatments for CIAS. Current evidence indicates, that while techniques which broadly enhance neural plasticity show the greatest therapeutic potential, effect sizes are at best moderate. Among other reasons, this is due to a considerable heterogeneity of responses to individual interventions. Furthermore, we discuss how recent conceptual advances in operationalizing cognitive impairments based on cognitive neuroscience have the potential to address these issues and facilitate the development of novel treatment strategies for CIAS. This includes more clearly elucidating pathophysiological mechanisms in both humans and animal models, identifying new treatment targets as well as establishing biomarkers for a better prediction of treatment responses.

Cancer is the second biggest cause of death in children. With the development of chemotherapy, there is a substantial increase in overall survival rate over recent 30 years. However, the overall mortality rate in children with cancer still remains 25%, and many survivors experience a decline in overall quality of life and long-term adverse effects caused by treatments. Although cancer cells share common characteristics, pediatric cancers are different from adult cancers in their prevalence, mutation load, and drug response. Therefore, there is an urgent unmet need to develop therapeutic approaches specifically designed for children with cancer. Nanotechnology can potentially overcome the deficiencies of conventional methods of administering chemotherapy and ultimately improve clinical outcomes. The nanoparticle-based drug delivery systems can decrease the toxicity of therapy, provide a sustained or controlled drug release, improve pharmacokinetic properties of loading contents, and achieve a targeted drug delivery with achievable modifications. Further, therapeutic approaches based on combining nanoformulated drugs with novel immunotherapeutic agents are emerging. In this review, we discuss the recently developed nanotechnology-based strategies for treating blood and solid pediatric cancers.

A case report of the diagnosis of Long Term Sequelae of West Nile Neuroinvasive Disease in a patient with 9 years history. Empirical data of symptoms and test reports has been presented and based on the available data likely pathogenesis of the disease has been discussed. The empirical data has been compared to the published literature to reach a highly confident diagnosis.

Studies in animal models have suggested that the ketogenic diet may be effective in the treatment of cancer. However, human cohort studies on the ketogenic diet have, thus far, failed to show benefits in cancer survival or in any other hard clinical endpoints of the disease. This paper presents a case report of a patient with glioblastoma multiforme. The patient had initially been treated with standard oncotherapy including surgery, radiotherapy and chemotherapy. Despite standard treatment, the patient experienced a recurrence of the glioblastoma seven months later. Subsequently, the patient refused radiotherapy and chemotherapy and opted to use the paleolithic ketogenic diet (PKD) as a stand-alone therapy. Following the adoption of the PKD, progression of the disease has been completely halted. At the time of writing, the patient has remained in remission for 48 months, is without side-effects and experiences an excellent quality of life without the use of any drugs.

Noninvasive and portable diagnoses via angle-resolved coherent spectral data are presented. ACTIRS (Angle- resolved coherent tomographic IR spectroscopy) through angle-coherent return spectra from photonic quantum ring laser of whispering gallery modes, which is not photocurrent-converted after the cortical, vascular or muscular diffuse paths, can be a new method for brain/heart studies. Also it will be eligible for frequent do-it-yourself diagnoses of breast cancer before hospital visits. The unique angle-coherent multi-spectra will eventually lead to study ionic or protein contents of cranial, arterial or lactiferous ducts that have been obtained only from uncomfortable biopsy, NMR, CT or mammography. The spectral data can be spatially or temporally improved and correlated for extracting more meaningful diagnostic conclusions

The New Zealand brushtail possum (Trichosurus vulpecula), introduced from Australia in the 1850s, is an invasive species that is widespread throughout New Zealand and forms the largest self-sustained reservoir of bovine tuberculosis (Mycobacterium bovis) in the wild. Conservation and agricultural authorities regularly apply a series of population control measures to suppress brushtail possum populations. The evolutionary consequence of more than half a century of intensive population control operations on the species genomic diversity and population structure is hindered by a paucity of available genomic resources for the species. This study is the first to characterise the functional content and diversity of brushtail possum liver and brain cerebral cortex transcriptomes. Raw sequences from hepatic cells and cerebral cortex were assembled into 58,001 and 64,735 transcripts in hepatic cells and cerebral cortex, respectively. Functional annotation and polymorphism assignment of the assembled transcripts demonstrated a considerable level of variation in the core metabolic pathways that represent potential targets for selection pressure exerted by chemical toxicants. This study suggests that the brushtail possum population in New Zealand harbours considerable levels of variation in metabolic pathways that could potentially promote the development of tolerance against chemical toxicants.

Natural killer (NK) cell therapy is one of the most promising treatments for Glioblastoma Multiforme (GBM). However, this emerging technology is limited by the availability of sufficient numbers of fully functional cells. Here, we investigated the efficacy of NK cells that were expanded and treated by interleukin-2 (IL-2) and heat shock protein70 (HSP70), both in vitro and in vivo. Proliferation and cytotoxicity assays were used to assess the functionality of NK cells in vitro, after which treated and naïve NK cells were administrated intra-cranially and systemically to compare the potential antitumor activities in our in vivo rat GBM models. In vitro assays provided strong evidence of NK cell efficacy against C6 tumor cells. In vivo tracking of NK cells showed efficient homing around and within the tumor site. Furthermore, significant amelioration of the tumor in rats treated with HSP70/Il-2 treated NK cells as compared to those subjected to non-treated NK cells, as confirmed by MRI, proved the efficacy of adoptive NK cell therapy. Moreover, results obtained with systemic injection confirmed migration of activated NK cells over the blood brain barrier and subsequent targeting of GBM tumor cells. Our data suggest that administration of HSP70/Il-2 treated NK cells may be a promising therapeutic approach to be considered in the treatment of GBM.

Glioblastoma (GBM) is the most lethal form of brain tumor, characterized by rapid growth and surrounding tissue invasion. The current standard treatment is surgery followed by radiotherapy, and concurrent chemotherapy, typically with temozolomide. Although extensive research has been performed over the past years to develop an effective therapeutic strategy for the treatment of GBM, efforts have not provided major improvements in the overall survival of patients with GBM. Thus, new therapeutic approaches are urgently needed. A major challenge in the development of therapies for central nervous system (CNS) disorders is overcoming the blood–brain barrier (BBB). In this context, the intranasal (IN) route of drug administration has been proposed as a non-invasive alternative route to directly targeting the CNS. In fact, this route of drug administration may bypass the blood-brain barrier and reduce systemic side effects. Recently, formulations have been developed to further enhance nose-to-brain transport, mainly with the use of nano-sized and nanostructured drug delivery systems. The focus of this review will be on the strategies developed to deliver a number of anticancer compounds for the treatment of GBM using the nasal administration. In particular, the specific properties of nanomedicines proposed for the nose-to-brain delivery will be critically evaluated. The number of preclinical and clinical data reviewed support the idea that nasal delivery of anticancer drugs might represent a breakthrough advancement in the fight against GBM.

Perception and motor interaction with physical surroundings can be analyzed by the changes in probability laws governing two possible outcomes of neuronal activity, namely the presence or absence of spikes (binary states). Perception and motor interaction with physical environment are accounted partly by the reduction in entropy within the probability distributions of binary states of neurons in distributed neural circuits, given the knowledge about the characteristics of stimuli in physical surroundings. This reduction in the total entropy of multiple pairs of circuits in networks, by an amount equal to the increase of mutual information among them, occurs as sensory information is processed successively from lower to higher cortical areas or between different areas at the same hierarchical level but belonging to different networks. The increase in mutual information is partly accounted by temporal coupling as well as synaptic connections as proposed by Bahmer and Gupta [1]. We propose that robust increases in mutual information, measuring the association between the characteristics of sensory inputs and neural circuits connectivity patterns, are partly responsible for perception and successful motor interactions with physical surroundings. It is also argued that perception from a sensory input is the result of networking of many circuits to a common circuit that primarily processes the given sensory input.

A frequent co-morbidity of cerebrovascular pathology and Alzheimer's disease pathology has been observed over past decades. Accordingly, much evidence has been reported which indicates that microvascular endothelial dysfunction, due to cerebrovascular risk factors (e.g., atherosclerosis, obesity, diabetes, smoking, hypertension, aging), precedes cognitive decline in Alzheimer's disease and contributes to its pathogenesis. By incorporating appropriate drug(s) into biomimetic (lipid cubic phase) nanocarriers, one obtains a multitasking combination therapeutic which targets certain cell-surface scavenger receptors, mainly class B type I (i.e., SR-BI), and crosses the blood-brain barrier (BBB). Such targeting allows for various Alzheimer's-related cell types to be simultaneously searched out, in vivo, for localized drug treatment. This in vivo targeting advantage may be particularly important for repurposing an FDA-approved drug, especially one which has shown the added ability to restore some cognitive functions in certain animal models of Alzheimer's disease (e.g., the anticancer drug bexarotene); this (candidate repurposing) drug up to now, by itself (i.e, without nanocarrier), displayed poor CNS penetration in human subjects.

Celiac disease is a gluten-sensitive immune-mediated enteropathy of the small intestine that occurs in genetically predisposed individuals. Abnormal immune response results in mucosal inflammation, villous atrophy, and crypt hyperplasia. This study was a proof-of-concept exercise that used a convolutional neural network to classify hematoxylin and eosin (H&E) histological images of celiac disease, normal small intestine control, and non-specified duodenal inflammation; 7294, 11,642, and 5966 images, respectively. The trained network classified celiac disease images with high performance (accuracy 99.7%, precision 99.6%, recall 99.3%, F1-score 99.5%, and specificity 99.8%). Interestingly, when the same network (already trained for the 3 class images), analyzed duodenal adenocarcinoma (3723 images), the new images were classified as duodenal inflammation in 63.65%, small intestine control in 34.73%, and celiac disease in 1.61% of the cases. Finally, when the network was retrained using the 4 histological subtypes of images, all performance parameters were above 99% for celiac disease. In conclusion, the convolutional neural network (CNN)-based deep neural system was able to classify medical histological images with high performance. Narrow artificial intelligence (AI) is designed to perform tasks that typically require human intelligence, but it operates within limited constraints and is task specific.

Visualization of volumetric data holds great importance, particularly in medical and biomedical applications. Various imaging techniques, such as FMRI and 3D microscopy, are employed to generate volumetric data, used in medical practice, research, and teaching. Commonly utilized tools like 3D Slicer, Fiji, and MATLAB ® aid in rendering and analyzing 3D images. However, these tools may lack comprehensive rendering functionality and face challenges in handling computational demands as data sizes grow. To address these limitations, this work introduces a GPU-supported renderer with a MATLAB ® interface. This solution gives the user flexible control over rendering parameters and optimizes data transfer through a memory management system. By leveraging the computational power of NVIDIA GPUs, the renderer enables complex and high-quality renderings, enhancing speed and efficiency. It therefore facilitates the analysis and visualization of volumetric data within an integrated environment, namely MATLAB ®, streamlining their workflows. This advancement provides valuable opportunities for researchers and medical professionals to explore and comprehend volumetric data effectively.

The human mandible's cancellous bone, which is characterized by its unique porosity and directional sensitivity to external forces, is crucial for sustaining biting stress. Traditional CAD models fail to fully represent bone's anisotropic structure and thus depend on simple isotropic assumptions. For our research, we use the latest versions of nTopology and Creo Parametric software to make biomimetic Voronoi lattice models that accurately reflect the complex geometry and mechanical properties of trabecular bone. The porosity of human cancellous bone is accurately modeled in this work using biomimetic Voronoi lattice models. The porosities range from 70% to 95%, which can be achieved by changing the pore sizes to 1.0 mm, 1.5 mm, 2.0 mm, and 2.5 mm. Finite element analysis (FEA) was used to examine the displacements, stresses, and strains acting on dental implants with a buttress thread, abutment, retaining screw, and biting load surface. The results show that the Voronoi model accurately depicts the complex anatomy of the trabecular bone in the human jaw, compared to standard solid block models. The ideal pore size for biomimetic Voronoi lattice trabecular bone models is 2 mm, taking into account both the von Mises stress distribution over the dental implant, screw retention, cortical bone, cancellous bone, and micromotions. This pore size displayed balanced performance by successfully matching natural bone's mechanical characteristics. Advanced finite element analysis (FEA) improves biomechanical understanding of how bones and implants interact by creating more accurate models of biological problems and dynamic loading situations. This makes biomechanical engineering better.

How crucial is big data in contemporary molecular design? In this publication we elucidate fundamental concepts and terminology in this field, critically addressing overlooked issues. We thoroughly examine the size, accessibility, quality, and structural aspects of big data alongside the primary methodologies employed for their analysis. Within chemical compounds, properties and descriptors represent two distinct data types, forming the basis for categorizing molecular big data. The primary objective of chemistry is property production, which means we are searching for novel drugs or materials rather than chemical compounds, and big data is the central issue of this philosophy. The increasing availability of data in computer-aided technology propels advancements in artificial intelligence (AI), machine learning (ML), and deep learning (DL). Accordingly, a broad chemical audience must comprehend these methods to understand data-centered chemistry. Thus, we aim to systemize big data issues through a simple illustrative framework with fundamental descriptor categories: coding, computer-generated descriptors, and property correlates. Although we employ computer-generated descriptors as big data for predictions, the measured data are irreplaceable for achieving high-quality and reliable outcomes and controlling molecular effects. The scarcity of property data remains a significant hurdle limiting comprehensive studies on the structure-property relationships within big data. Accordingly, guided by pragmatics not-so-big data is an option for drug design. We presented also a brief review of the recent big data literature.

In the dynamic landscape of drug discovery, Computer-rAided Drug Design (CADD) emerges as a transformative force, bridging the realms of biology and technology. This paper overviews CADD's historical evolution, categorization into structure-based and ligand-based approaches, and its crucial role in rationalizing and expediting drug discovery. As CADD advances, incorporating diverse biological data and ensuring data privacy become paramount. Challenges persist, demanding the optimization of algorithms and robust ethical frameworks. Integrating Machine Learning and Artificial Intelligence amplifies CADD's predictive capabilities, yet ethical considerations and scalability challenges linger. Collaborative efforts and global initiatives, exemplified by platforms like Open Source Malaria, underscore the democratization of drug discovery. The convergence of CADD with personalized medicine offers tailored therapeutic solutions, though ethical dilemmas and accessibility concerns must be navigated. Emerging technologies like quantum computing, immersive technologies, and green chemistry promise to redefine the future of CADD. The trajectory of CADD, marked by rapid advancements, anticipates challenges in ensuring accuracy, addressing biases in AI, and incorporating sustainability metrics. The paper concludes by highlighting the need for proactive measures in navigating the ethical, technological, and educational frontiers of CADD to shape a healthier, brighter future in drug discovery.

Thanks to the continued development of experimental structural biology and the half-a-century old Protein Data Bank, 2021 saw a big step forward in the development of protein structure prediction with deep learning algorithms. Recently, DeepMinds AlphaFold has determined the structures of ∼ 200 million proteins from 1 million species. The speed of this progress raise the question of what becomes possible for computational drug discovery and design when we have a systems-wide account of the structures and motions of most proteins. Therefore, this article puts forward the concept of a general intermolecular binding affinity calculator (GIBAC): Kd = f(molA, molB, envPara), towards the acceleration of traditional computer-aided drug design (CADD) and artificial intelligence-integrated drug discovery (AIDD), for both small molecules and biologics such as therapeutic proteins.

Pure orbital blowout fractures occur within the confines of the internal orbital wall. Restoration of orbital form and volume is paramount to prevent functional and esthetic impairment. The anatomical peculiarity of the orbit has encouraged surgeons to develop implants with customized features to restore its architecture. This has resulted in worldwide clinical demand for patient-specific implants (PSIs) designed to fit precisely in the patient's unique anatomy. Fused filament fabrication (FFF) three-dimensional (3D) printing technology has enabled the fabrication of implant-grade polymers such as Polyetheretherketone (PEEK), paving the way for a more sophisticated generation of biomaterials. This study evaluates the FFF 3D printed PEEK orbital mesh customized implants with a metric considering the relevant design, biomechanical, and morphological parameters. The performance of the implants is studied as a function of varying thicknesses and porous design constructs through a finite element (FE) based computational model and a decision matrix based statistical approach. The maximum stress values achieved in our results predict the high durability of the implants, and the maximum deformation values were under one-tenth of a millimeter (mm) domain in all the implant profile configurations. The circular patterned implant (0.9 mm) had the best performance score. The study demonstrates that compounding multi-design computational analysis with 3D printing can be beneficial for the optimal restoration of the orbital floor.

Hand gestures may play an important role in medical applications for health care of elderly people, where providing a natural interaction for different requests can be executed by making specific gestures. In this study we explored three different scenarios using a Microsoft Kinect V2 depth sensor then evaluated the effectiveness of the outcomes. The first scenario utilized the default system embedded in the Kinect V2 sensor, which depth metadata gives 11 parameters related to the tracked body with five gestures for each hand. The second scenario used joint tracking provided by Kinect depth metadata and depth threshold together to enhance hand segmentation and efficiently recognize the number of fingers extended. The third scenario used a simple convolutional neural network with joint tracking by depth metadata to recognize five categories of gestures. In this study, deaf-mute elderly people execute five different hand gestures to indicate a specific request, such as needing water, meal, toilet, help and medicine. Then, the requests were sent to the care provider’s smartphone because elderly people could not execute any activity independently. The system transferred these requests as a message through the global system for mobile communication (GSM) using a microcontroller.

Objectives: Studies evaluating machine learning (ML) algorithms on cross-lingual RadLex® mappings for developing context-sensitive radiological reporting tools are lacking. Therefore, we investigated whether ML-based approaches can be utilized to assist radiologists in providing key imaging biomarkers – such as The Alberta stroke programme early CT score (APECTS). Material and Methods: A stratified random sample (age, gender, year) of CT reports (n=206) with suspected ischemic stroke was generated out of 3997 reports signed off between 2015-2019. Three independent, blinded readers assessed these reports and manually annotated clinico-radiologically relevant key features. The primary outcome was whether ASPECTS should have been provided (yes/no: 154/52). For all reports, both the findings and impressions underwent cross-lingual (German to English) RadLex®-mappings using natural language processing. Well-established ML-algorithms including classification trees, random forests, elastic net, support vector machines (SVMs) and boosted trees were evaluated in a 5 x 5-fold nested cross-validation framework. Further, a linear classifier (fastText) was directly fitted on the German reports. Ensemble learning was used to provide robust importance rankings of these ML-algorithms. Performance was evaluated using derivates of the confusion matrix and metrics of calibration including AUC, brier score and log loss as well as visually by calibration plots. Results: On this imbalanced classification task SVMs showed the highest accuracies both on human-extracted- (87%) and fully automated RadLex® features (findings: 82.5%; impressions: 85.4%). FastText without pre-trained language model showed the highest accuracy (89.3%) and AUC (92%) on the impressions. Ensemble learner revealed that boosted trees, fastText and SVMs are the most important ML-classifiers. Boosted trees fitted on the findings showed the best overall calibration curve. Conclusions: Contextual ML-based assistance suggesting ASPECTS while reporting neuroradiological emergencies is feasible, even if ML-models are restricted to be developed on limited and highly imbalanced data sets.

White adipose tissue (WAT) and gut are involved as inducers of neuroinflammation when they detect injury and trigger inflammation. The autonomous nervous system innervates both tissues, although the roles of the sympathetic, parasympathetic and enteric nervous systems have not been fully elucidated. Here, we revisited the participation of both types of inflamed peripheral tissue in neuroinflammation. We first analyzed how inflamed peripheral WAT plays a key role in neuroinflammation once metainflammation is installed. Second, we described the impact of insulin resistance (IR) on hypothalamic dysfunction, T2DM and neurodegenerative diseases. Finally, we analyzed the gut-brain axis, examining cell interactions, soluble factors, the sensing of microbes and the role of the intestinal microbiota and mucosal barriers in neuroinflammation. Since intestinal mucosa and secondary lymphoid organs are densely innervated by the sympathetic, parasympathetic, and enteric nervous systems, we analyzed bidirectional crosstalk between different tissues, neurons, and immune systems in healthy and pathological circumstances to restore normal tissues functions, and consequently homeostasis.

Traumatic brain injury (TBI) is an important global clinical issue, requiring not only prevention but also effective treatment. Following TBI, diverse parallel and intertwined pathological mechanisms affecting biochemical, neurochemical, and inflammatory pathways can have severe impact on the patient’s quality of life. The current review summarizes evidence for utility of amantadine in TBI in connection to its mechanism of action. Amantadine combining multiple mechanisms of action may offer both neuroprotective and neuroactivating effects in TBI patients. Indeed, use of amantadine in TBI has been encouraged by several clinical practice guidelines/recommendations. Amantadine is also available as infusion which may be of particular benefit in unconscious patients with TBI, due to immediate delivery to the central nervous system and the possibility of precise dosing. In other situations, orally administered amantadine may be used. There are several questions that remain to be addressed: Can amantadine be effective in disorders of consciousness requiring long-term treatment and in combination with drugs approved for treatment of TBI? Do the observed beneficial effects of amantadine extend to disorders of consciousness due to factors other than TBI? Well controlled clinical studies are warranted to ultimately confirm its utility in the TBI and provide answers these questions.

Alzheimer’s disease (AD) is a progressive irreversible neurodegenerative disorder that represents a major global public health concern. Traditionally, AD is diagnosed using cerebrospinal fluid biomarker analysis or brain imaging modalities. Recently, less burdensome, more widely available blood biomarker (BBM) assays for amyloid-beta (Aβ42/40) and phosphorylated-tau concentrations have been found to accurately identify the presence/absence of brain amyloid plaques and tau tangles and have helped to streamline AD diagnosis. However, few BBMs have been rigorously analytically validated. Herein, we report the analytical validation of a novel liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for quantifying plasma phosphorylated-tau217 (p-tau217) and non-phosphorylated-tau217 (np-tau217) peptide concentrations. We combined the p-tau217/np-tau217 concentrations ratio (%p-tau217) and the previously validated LC-MS/MS assay for plasma Ab42/40 into a new multiple analyte blood test and algorithm (PrecivityAD2™) that identifies brain amyloid status based on brain amyloid positron emission tomography. We found: (a) the %p-tau217 assay is precise, accurate, sensitive, linear over a wide analytical measurement range, and free from carryover and interference; (b) the pre-analytical specimen collection, processing, storage and shipping conditions that maintain plasma tau peptide stability; and (c) using the measured analytical imprecision for plasma Aβ42/40 and p-tau217/np-tau217 levels in a worst-case scenario model, the PrecivityAD2 test algorithm for amyloid pathology classification changed for only 3.5% of participants from brain amyloid positive to negative, or negative to positive. The plasma sample preparation and LC-MS/MS methods underlying the PrecivityAD2 test are suitable for use in the clinical laboratory and valid for the test’s intended purpose: to aid in the diagnostic evaluation of individuals aged 55 and older with signs or symptoms of mild cognitive impairment or dementia.

The central nervous system (CNS) is the final frontier in drug delivery because of the blood-brain barrier (BBB), which poses significant barriers to the access of most drugs to their targets. Kynurenic acid (KYNA), a tryptophan (Trp) metabolite, plays an important role in behavioral functions and abnormal KYNA levels have been observed in neuropsychiatric conditions. The current challenge lies in delivering KYNA to the CNS owing to its polar side chain. Recently, C-3 side chain modified KYNA analogs have been shown to cross the BBB; however, it is unclear whether they retain the biological functions of the parent molecule. This study examined the impact of KYNA analogs, specifically SZR-72, SZR-104, and the newly developed SZRG-21, on behavior. The analogs were administered intracerebroventricularly (i.c.v.), and their effects on the motor domain were compared with those of KYNA. Specifically, open field (OF) and rotarod (RR) tests were employed to assess motor activity and skills. SZR-104 increased horizontal exploratory activity in the OF test at a dose of 0.04 μmol/4 μL, while SZR-72 decreased vertical activity at doses of 0.04 and 0.1 μmol/4 μL. In the RR test, however, neither KYNA nor its analogs showed any significant differences in motor skills at either dose. Side chain modification affects affective motor performance and exploratory behavior, as the results show for the first time. In this study, we showed that KYNA analogs alter emotional components such as motor-associated curiosity and emotions. Consequently, drug design necessitates the development of precise strategies to traverse the BBB while paying close attention to modifications in their effects on behavior.

One of the hallmarks of Alzheimer’s disease (AD) is the accumulation of beta-amyloid peptide (Aβ) leading to formation of soluble neurotoxic Aβ oligomers and insoluble amyloid plaques in various parts of the brain. Aβ undergoes post-translational modifications that alter its pathogenic properties. Aβ is produced not only in brain, but also in the peripheral tissues. Such Aβ, including its post-translationally modified forms, can enter the brain from circulation by binding to RAGE and contribute to the pathology of AD. However, the transport of modified forms of Aβ across the blood–brain barrier (BBB) has not been investigated. Here, we used a transwell BBB model as a controlled environment for permeability studies. We found that Aβ42 containing isomerized Asp7 residue (iso-Aβ42) and Aβ42 containing phosphorylated Ser8 residue crossed the BBB better than unmodified Aβ42, which correlated with different contribution of endocytosis mechanisms to the transport of these isoforms. Using microscale thermophoresis, we observed that RAGE binds to iso-Aβ42 an order of magnitude weaker than to Aβ42. Thus, post-translational modifications of Aβ increase the rate of its transport across the BBB and modify the mechanisms of the transport, which may be important for AD pathology and treatment.

: The primary objective of this study was to investigate the association of certain genetic alterations and intraoperative fluorescent activity of 5-aminolevulinic acid (ALA) in brain metastasis (BM) of lung adenocarcinoma. A retrospective cohort study was conducted among 72 patients who underwent surgical resection of BM from lung adenocarcinoma at our institute for 5 years. Cancer cell infiltration was estimated by the intraoperative fluorescent activity of 5-ALA, and genetic alterations were analyzed by next-generation sequencing (NGS). The sensitivity and specificity for detecting cancer cell infiltration using 5-ALA were 87.5% and 96.4%, respectively. Genes associated with cell cycle regulation (p = 0.003) and cell proliferation (p = 0.044) were significantly associated with positive fluorescence activity of 5-ALA in the adjacent brain tissue. Genetic alterations in cell cycle regulation and cell proliferation were also associated with shorter recurrence-free survival (p = 0.013 and p = 0.042, respectively) and overall survival (p = 0.026 and p = 0.042, respectively) in the multivariate analysis. The results suggest that genetic alterations in cell cycle regulation and cell proliferation are associated with positive fluorescence activity of 5-ALA in the adjacent infiltrative brain tissue and influence the clinical outcome of BM of lung adenocarcinoma.

The introduction of anti-amyloid monoclonal antibodies against Alzheimer’s disease (AD) is of high importance. However, even though treated patients show very little amyloid pathology, there is only a modest effect on the rate of cognitive decline. Although this effect possibly can increase over time, there is still a need for alternative treatments that will improve the cognitive function in patients with AD. Therefore, the purpose of this study was to characterize the triazinetrione ACD856, a novel pan-Trk positive allosteric modulator, in multiple models to address its neuroprotective and potential disease modifying effects. The pharmacological effect of ACD856 was tested in recombinant cell lines, primary cortical neurons or animals. We demonstrate that ACD856 enhanced NGF-induced neurite outgrowth, increased the levels of the pre-synaptic protein SNAP25 in PC12 cells and increased the degree of phosphorylated TrkB in SH-SY5Y cells. In primary cortical neurons, ACD856 led to increased levels of phospho-ERK1/2, showed neuroprotective effect against amyloid-beta or energy-deprivation induced neurotoxicity, and increased the levels of brain derived neurotrophic factor (BDNF). Consequently, administration of ACD856 resulted in a significant increase of BDNF in the brains of 21-months old mice. Furthermore, repeated administration of ACD856 resulted in a sustained anti-depressant effect which lasted up to seven days, suggesting effects that go beyond merely symptomatic effects. In conclusion, the results confirm ACD856 as a cognitive enhancer, but more importantly, they provide substantial in vitro and in vivo evidence of neuroprotective and long-term effects that contribute to neurotrophic support and increased neuroplasticity. Presumably, the described effects of ACD856 may improve cognition, increase resilience, and promote neurorestorative processes, thereby leading to a healthier brain in patients with AD.

Diabetes mellitus is one of the most common metabolic diseases worldwide, and its long-term complications include neuropathy, referring both to the peripheral and to the central nervous system. Detrimental effects of dysglycemia, especially hyperglycemia, on the structure and function of blood-brain barrier (BBB) seem to be a significant backgrounds of diabetic neuropathy pertaining to the central nervous system (CNS). Effects of hyperglycemia, including excessive glucose influx to insulin independent cells, may induce oxidative stress and secondary innate immunity dependent inflammatory response which can damage cells within the CNS, thus promoting neurodegeneration and dementia. Advanced glycation end products (AGE) may exert similar, pro-inflammatory effects through activating receptors for advanced glycation end products (RAGE), as well as some pattern-recognition receptors (PRR). Moreover, long-term hyperglycemia can promote brain insulin resistance, which may in turn promote Aβ aggregate accumulation and tau hyperphosphorylation. This review is focused on a detailed analysis of the effects mentioned above towards the CNS, with special regard to mechanisms taking part in the pathogenesis of central long-term complications of diabetes mellitus initiated by the loss of BBB integrity.

Keywords: Hypertensive emergency; diagnosis; lactate dehydrogenase; high sensitivity cardiac troponin T; brain natriuretic peptide; area under the curve.

Unwanted proteins and metabolic waste in cerebral spinal fluid are cleared from the brain by meningeal and nasal lymphatics, and perineural sheath of cranial nerves; however, the distribution and clearance of CSF along the subarachnoid space of the entire spinal cord is not fully understood. It was hypothesized that the anatomical resolution of Cryo-Fluorescence Tomography (CFT) could provide the visual evidence of clearance across the spinal cord at each level of the vertebral column. To that end, isoflurane anesthetized mice were infused into the lateral cerebroventricle with 5.0 µl of quantum dots [QdotR 605 ITKTM amino (PEG)] over two mins. Mice were allowed to recover (ca 2-3 min) and remained awake and ambulatory for 5, 15, 30, 60 and 120 minutes after which they were euthanized, and the entire intact body frozen at -800. The entire mouse was sectioned and imaged to produce an isotropic voxel resolution of 35 µm. Both white light and fluorescent images were captured after each slice to produce high resolution three-dimensional volumes for each mouse. CFT highlighted the circulation of tracer throughout the ventricular system and central canal of the spinal cord and the entire subarachnoid space of the CNS. Signal could be visualized in the nasal cavity, deep cervical lymph nodes, thoracic lymph nodes and more superficial submandibular lymph nodes as early as 15 min post infusion. Fluorescent signal could be visualized along the dorsal root ganglia and down the proximal extension of the spinal nerves of the thoracic and lumbar segments at 30 min. There was significant accumulation of tracer in the lumbar and sacral lymph nodes between 15- 60 min. The dense fluorescent signal in the thoracic vertebrae noted at 5- and 15-mins post infusion was significantly reduced by 30 min. Indeed, all signal in the spinal cord was ostensibly absent by 120 min except for trace amounts in the coccyx. The brain still had some residual signal at 120 min. These data show that Qdots with a hydrodynamic diameter of 16-20 nm rapidly clear from the brain of awake mice. These data also clearly demonstrate the rapid distribution and efflux of trace along a major length of the vertebral column and the potential contribution of the spinal cord in the clearance of brain waste.

Concussion, also known as mild traumatic brain injury (mTBI), commonly causes transient neurocognitive symptoms, but in some cases, it causes cognitive impairment, including working memory (WM) deficit, which can be long-lasting and impede a patient’s return to work. The predictors of long-term cognitive outcomes following mTBI remain unclear because abnormality is often absent in structural imaging findings. The purpose of the study was to determine whether machine learning-based models using functional magnetic resonance imaging (fMRI) biomarkers and demographic or neuropsychological measures at baseline could effectively predict 1-year cognitive outcomes of concussion. We conducted a prospective, observational study of patients with mTBI who were compared with demographically-matched healthy controls enrolled between September 2015 to August 2020. Baseline assessments were collected within the first week of injury, and follow-ups were conducted at 6 weeks, 3 months, 6 months, and 1 year. Potential demographic, neuropsychological, and fMRI features were selected according to the significance of correlation with the estimated changes in WM ability. The support vector machine classifier was trained using these potential features and estimated changes in WM between the predefined time periods. Patients demonstrated significant cognitive recovery at the third month, followed by worsened performance after 6 months, which persisted until 1 year after concussion. Approximately half of the patients experienced prolonged cognitive impairment at 1-year follow up. Satisfactory predictions were achieved for patients whose WM function did not recover at 3 months (accuracy=87.5%), 6 months (accuracy=83.3%), 1 year (accuracy=83.3%), and performed worse at 1-year follow-up compared to baseline assessment (accuracy=83.3%). This study demonstrated the feasibility of personalized prediction for long-term postconcussive WM outcomes based on baseline fMRI and demographic features, opening a new avenue for early rehabilitation intervention in selected individuals with possible poor long-term cognitive outcomes.

Survivors of severe brain injury may require care in a neurointensive care unit (neuro-ICU), where the brain is vulnerable to secondary brain injury. Thus, there is a need for noninvasive, bedside, continuous cerebral blood flow monitoring approaches in the neuro-ICU. Our goal is to address this need through combined measurements of EEG and functional optical spectroscopy (EEG-Optical) instrumentation and analysis to provide a complementary fusion of data about brain activity and function. The present case demonstrates in a patient with traumatic brain injury, noninvasive cerebral blood flow transients can be recorded that correlate with gold-standard invasive measurements and with the frequency content changes in the EEG data during clinical care.

We constructed a novel design integrating the administration of a clinical self-assessment scale with simultaneous acquisition of functional Magnetic Resonance Imaging (fMRI), aiming at cross-validation between psychopathology evaluation and neuroimaging techniques. We hypothesized that areas demonstrating differential activation in two groups of patients (paranoid and depressive) will have distinct connectivity patterns and structural differences.