Glucose signaling in the brain and periphery to memory

Enhancement of response learning in male rats with intrastriatal infusions of a BDNF - TrkB agonist, 7,8-dihydroxyflavone

Enhancement of learning and memory by cognitive and physical exercise may be mediated by brain-derived neurotrophic factor (BDNF) acting at tropomyosin receptor kinase B (TrkB). Upregulation of BDNF and systemic administration of a TrkB agonist, 7,8-dihydroxyflavone (7,8-DHF), enhance learning of several hippocampus-sensitive tasks in rodents. Although BDNF and 7,8-DHF enhance functions of other brain areas too, these effects have mainly targeted non-cognitive functions. One goal of the present study was to determine whether 7,8-DHF would act beyond the hippocampus to enhance cognitive functions sensitive to manipulations of the striatum. Here, we examined the effects of intrastriatal infusions of 7,8-DHF on learning a striatum-sensitive response maze and on phosphorylation of TrkB receptors in 3-month-old male Sprague Dawley rats. Most prior studies of BDNF and 7,8-DHF effects on learning and memory have administered the drugs for days to months before assessing effects on cognition. A second goal of the present study was to determine whether a single drug treatment near the time of training would effectively enhance learning. Moreover, 7,8-DHF is often tested for its ability to reverse impairments in learning and memory rather than to enhance these functions in the absence of impairments. Thus, a third goal of this experiment was to evaluate the efficacy of 7,8-DHF in enhancing learning in unimpaired rats. In untrained rats, intrastriatal infusions of 7,8-DHF resulted in phosphorylation of TrkB receptors, suggesting that 7,8-DHF acted as a TrkB agonist and BDNF mimic. The findings that a single, intra-striatal infusion of 7,8-DHF 20 min before training enhanced response learning in rats suggest that, in addition to its trophic effects, BDNF modulates learning and memory through receptor mediated cell signaling events.

Benchtop Fabricated Nano-Roughened Microstructured Electrodes for Electrochemical and Surface-Enhanced Raman Scattering Sensing

Tailoring a material's surface with hierarchical structures from the micro- to the nanoscale is key for fabricating highly sensitive detection platforms. To achieve this, the fabrication method should be simple, inexpensive, and yield materials with a high density of surface features. Here, using benchtop fabrication techniques, gold surfaces with hierarchically structured roughness are generated for sensing applications. Hierarchical gold electrodes are prepared on pre-stressed polystyrene substrates via electroless deposition and amperometric pulsing. Electrodes fabricated using 1 mm H[AuCl₄] and roughened with 80 pulses revealed the highest electroactive surface area. These electrodes are used for enzyme-free detection of glucose in the presence of bovine serum albumin and achieved a limit of detection of 0.36 mm, below glucose concentrations in human blood. The surfaces nanoroughened with 100 pulses also showed excellent surface-enhanced Raman scattering (SERS) response for the detection of rhodamine 6G, with an enhancement factor of ≈2 × 106 compared to detection in solution, and for the detection of a self-assembled monolayer of thiophenol, with an enhancement factor of ≈30 compared to the response from microstructured gold surfaces. It is envisioned that the simplicity and low fabrication cost of these gold-roughened structures will expedite the development of electrochemical and SERS sensing devices.

Acute severe hypoglycemia alters mouse brain microvascular proteome

Hypoglycemia increases the risk related to stroke and neurodegenerative diseases, however, the underlying mechanisms are unclear. For the first time, we studied the effect of a single episode (acute) of severe (ASH) and mild (AMH) hypoglycemia on mouse brain microvascular proteome. After four-hour fasting, insulin was administered (i.p) to lower mean blood glucose in mice and induce ∼30 minutes of ASH (∼30 mg/dL) or AMH (∼75 mg/dL), whereas a similar volume of saline was given to control mice (∼130 mg/dL). Blood glucose was allowed to recover over 60 minutes either spontaneously or by 20% dextrose administration (i.p). Twenty-four hours later, the brain microvessels (BMVs) were isolated, and tandem mass tag (TMT)-based quantitative proteomics was performed using liquid chromatography-mass spectrometry (LC/MS). When compared to control, ASH significantly downregulated 13 proteins (p ≤ 0.05) whereas 23 proteins showed a strong trend toward decrease (p ≤ 0.10). When compared to AMH, ASH significantly induced the expression of 35 proteins with 13 proteins showing an increasing trend. AMH downregulated only 3 proteins. ASH-induced downregulated proteins are involved in actin cytoskeleton maintenance needed for cell shape and migration which are critical for blood-brain barrier maintenance and angiogenesis. In contrast, ASH-induced upregulated proteins are RNA-binding proteins involved in RNA splicing, transport, and stability. Thus, ASH alters BMV proteomics to impair cytoskeletal integrity and RNA processing which are critical for cerebrovascular function.

The fibroblast growth factor system in cognitive disorders and dementia

Cognitive impairment is the core precursor to dementia and other cognitive disorders. Current hypotheses suggest that they share a common pathological basis, such as inflammation, restricted neurogenesis, neuroendocrine disorders, and the destruction of neurovascular units. Fibroblast growth factors (FGFs) are cell growth factors that play essential roles in various pathophysiological processes via paracrine or autocrine pathways. This system consists of FGFs and their receptors (FGFRs), which may hold tremendous potential to become a new biological marker in the diagnosis of dementia and other cognitive disorders, and serve as a potential target for drug development against dementia and cognitive function impairment. Here, we review the available evidence detailing the relevant pathways mediated by multiple FGFs and FGFRs, and recent studies examining their role in the pathogenesis and treatment of cognitive disorders and dementia.

Machine Learning-Based Routine Laboratory Tests Predict One-Year Cognitive and Functional Decline in a Population Aged 75+ Years

BACKGROUND

Cognitive and functional decline are common problems in older adults, especially in those 75+ years old. Currently, there is no specific plasma biomarker able to predict this decline in healthy old-age people. Machine learning (ML) is a subarea of artificial intelligence (AI), which can be used to predict outcomes Aim: This study aimed to evaluate routine laboratory variables able to predict cognitive and functional impairment, using ML algorithms, in a cohort aged 75+ years, in a one-year follow-up study.

METHOD

One hundred and thirty-two older adults aged 75+ years were selected through a community-health public program or from long-term-care institutions. Their functional and cognitive performances were evaluated at baseline and one year later using a functional activities questionnaire, Mini-Mental State Examination, and the Brief Cognitive Screening Battery. Routine laboratory tests were performed at baseline. ML algorithms-random forest, support vector machine (SVM), and XGBoost-were applied in order to describe the best model able to predict cognitive and functional decline using routine tests as features.

RESULTS

The random forest model showed better accuracy than other algorithms and included triglycerides, glucose, hematocrit, red cell distribution width (RDW), albumin, hemoglobin, globulin, high-density lipoprotein cholesterol (HDL-c), thyroid-stimulating hormone (TSH), creatinine, lymphocyte, erythrocyte, platelet/leucocyte (PLR), and neutrophil/leucocyte (NLR) ratios, and alanine transaminase (ALT), leukocyte, low-density lipoprotein cholesterol (LDL-c), cortisol, gamma-glutamyl transferase (GGT), and eosinophil as features to predict cognitive decline (accuracy = 0.79). For functional decline, the most important features were platelet, PLR and NLR, hemoglobin, globulin, cortisol, RDW, glucose, basophil, B12 vitamin, creatinine, GGT, ALT, aspartate transferase (AST), eosinophil, hematocrit, erythrocyte, triglycerides, HDL-c, and monocyte (accuracy = 0.92).

CONCLUSIONS

Routine laboratory variables could be applied to predict cognitive and functional decline in oldest-old populations using ML algorithms.

Antioxidant and anti-inflammatory effect of olive leaf extract treatment in diabetic rat brain

OBJECTIVES

Olive (Olea europaea L.) plays a promising role in pharmaceutical, nutraceutical, and cosmetic production. On the other hand, olive leaf is widely used in folk medicine due to its antihyperglycemic activity. For this aim, possible effects of olive leaf extract (OLE) in the brain tissue of streptozotocin-induced diabetic rats were investigated.

METHODS

A total of 28 male rats were divided into four equal groups as control, diabetic (single dose of 45 mg/kg streptozotocin, i.p.), OLE (500 mg/kg/day), and diabetic + OLE groups. The study was terminated 21 days after the diabetes model was formed. At the end of the study, all the animals were sacrificed and blood and brain tissues were isolated. Relative brain weights, complete blood count, blood glycated hemoglobin, serum glucose, total protein, total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglycerides, insulin, gonadal hormone levels, production and messenger ribonucleic acid (mRNA) levels of proinflammatory cytokines and mediators, total thiol, total oxidative stress, and total antioxidant status levels and fatty acid composition in brain tissue were measured in all study groups.

RESULTS

In diabetic rats, relative brain weight and serum insulin level decreased, glycated hemoglobin, oxidative stress, production and mRNA level of proinflammatory cytokines and mediators increased, hyperglycemia, hypercholesterolemia and hypertriglyceridemia, degraded fatty acid composition, anemia, leukopenia, and thrombocytopenia occurred. After OLE treatment, a remarkable improvement in most of these parameters, except gonadal hormones, has been observed in diabetic rats.

CONCLUSIONS

This study suggests that olive leaf can be a precious neuroprotective agent in diabetes.

Plasmalogens inhibit neuroinflammation and promote cognitive function

Neuroinflammation (NF) is defined as the activation of brain glial cells that are found in neurodegenerative diseases including Alzheimer's disease (AD). It has been known that an increase in NF could reduce the memory process in the brain but the key factors, associated with NF, behind the dysregulation of memory remained elusive. We previously reported that the NF and aging processes reduced the special phospholipids, plasmalogens (Pls), in the murine brain by a mechanism dependent on the activation of transcription factors, NF-kB and c-MYC. A similar mechanism has also been found in postmortem human brain tissues with AD pathologies and in the AD model mice. Recent evidence showed that these phospholipids enhanced memory and reduced neuro-inflammation in the murine brain. Pls can stimulate the cellular signaling molecules, ERK and Akt, by activating the membrane-bound G protein-coupled receptors (GPCRs). Therefore, recent findings suggest that plasmalogens could be one of the key phospholipids in the brain to enhance memory and inhibit NF.

Vagus Nerve and Underlying Impact on the Gut Microbiota-Brain Axis in Behavior and Neurodegenerative Diseases

The gut microbiota is the most abundant and diverse microbiota in the human body and the vagus nerve is the most widely distributed and complex nerve in the body, both of them are essential in maintaining homeostasis. The most important phenomenon is how they coordinate to regulate functions, which has attracted the great attention of scientists. The academic literature on the correlation with a host of intestinal diseases and even systemic diseases has revealed the bidirectional communication between the gut microbiota and the brain, which can be carried out via multiple patterns. In the review, firstly, we have a general overview of the gut microbiota and the gut microbiota-brain axis. Secondly, according to the distribution characteristics of the vagus nerve, we analyzed and summarized its function in the intestinal tract. At the same time, we have summarized the underlying mechanism of some behavior changes such as depressive and anxiety-like behaviors and related neurodegenerative diseases caused by the vagus nerve and intestinal microecological environment disorders, and then we also analyzed inconsistency of the experimental evidence in order to propose novel strategies for the clinical practice.

Prediction value of the genetic risk of type 2 diabetes on the amnestic mild cognitive impairment conversion to Alzheimer’s disease

Amnestic mild cognitive impairment (aMCI) and Type 2 diabetes mellitus (T2DM) are both important risk factors for Alzheimer’s disease (AD). We aimed to investigate whether a T2DM-specific polygenic risk score (PRS_sT2DM) can predict the conversion of aMCI to AD and further explore the underlying neurological mechanism. All aMCI patients were from the Alzheimer’s disease Neuroimaging Initiative (ADNI) database and were divided into conversion (aMCI-C, n = 164) and stable (aMCI-S, n = 222) groups. PRS_sT2DM was calculated by PRSice-2 software to explore the predictive efficacy of the aMCI conversion to AD. We found that PRS_sT2DM could independently predict the aMCI conversion to AD after removing the common variants of these two diseases. PRS_sT2DM was significantly negatively correlated with gray matter volume (GMV) of the right superior frontal gyrus in the aMCI-C group. In all aMCI patients, PRS_sT2DM was significantly negatively correlated with the cortical volume of the right superior occipital gyrus. The cortical volume of the right superior occipital gyrus could significantly mediate the association between PRS_sT2DM and aMCI conversion. Gene-based analysis showed that T2DM-specific genes are highly expressed in cortical neurons and involved in ion and protein binding, neural development and generation, cell junction and projection, and PI3K-Akt and MAPK signaling pathway, which might increase the aMCI conversion by affecting the Tau phosphorylation and amyloid-beta (Aβ) accumulation. Therefore, the PRS_sT2DM could be used as a measure to predict the conversion of aMCI to AD.

ROLE OF GUT MICROBIOTA IN DEPRESSION: UNDERSTANDING MOLECULAR PATHWAYS, RECENT RESEARCH, AND FUTURE DIRECTION

Gut microbiota, also known as the "second brain" in humans because of the regulatory role it has on the central nervous system via neuronal, chemical and immune pathways. It has been proven that there exists a bidirectional communication between the gut and the brain. Increasing evidence supports that this crosstalk is linked to the etiology and treatment of depression. Reports suggest that the gut microbiota control the host epigenetic machinery in depression and gut dysbiosis causes negative epigenetic modifications via mechanisms like histone acetylation, DNA methylation and non-coding RNA mediated gene inhibition. The gut microbiome can be a promising approach for the management of depression. The diet and dietary metabolites like kynurenine, tryptophan, and propionic acid also greatly influence the microbiome composition and thereby, the physiological activities. This review gives a bird-eye view on the pathological updates and currently used treatment approaches targeting the gut microbiota in depression.

Plasmalogens, the Vinyl Ether-Linked Glycerophospholipids, Enhance Learning and Memory by Regulating Brain-Derived Neurotrophic Factor

Plasmalogens (Pls), a kind of glycerophospholipids, have shown potent biological effects but their role in hippocampus-dependent memory remained mostly elusive. Here, we first report Pls can enhance endogenous expression of brain-derived neurotrophic factor (Bdnf) in the hippocampus and promotes neurogenesis associated with improvement of learning and memory in mice. Genomic and proteomic studies revealed that Pls enhanced recruitment of CREB transcription factor onto the murine Bdnf promoter region via upregulating ERK-Akt signaling pathways in neuronal cells. Reduction of endogenous Pls in murine hippocampus significantly reduced learning and memory associated with the reduction of memory-related protein expression, suggesting that Pls can regulate memory-related gene expression in the hippocampus.

Sesquiterpene glycoside isolated from loquat leaf targets gut microbiota to prevent type 2 diabetes mellitus in db/db mice

• SG1 prevents obesity, ameliorates insulin resistance, and reduces systemic inflammation. • SG1 keeps the gut microbial diversity. •The efficacy of SG1 in the treatment of T2DM is strongly linked with the enhancement of several gut genera.

Type 2 Diabetes Mellitus Easily Develops into Alzheimer's Disease via Hyperglycemia and Insulin Resistance

With the acceleration of population aging, the incidence of type 2 diabetes mellitus (T2DM) and Alzheimer's disease (AD) is progressively increasing due to the age-relatedness of these two diseases. The association between T2DM and AD-like dementia is receiving much attention, and T2DM is reported to be a significant risk factor for AD. The aims of this review were to reveal the brain changes caused by T2DM as well as to explore the roles of hyperglycemia and insulin resistance in the development of AD.

A study of microbially fabricated bio-conjugated quantum dots for pico-molar sensing of H2O2 and glucose

Quantum dots (QDs) as bio-detectors have been intensively explored owing to their size dependent optical properties and are still envisioned to be used in a plethora of biomedical and healthcare areas. However, the medical application of the biosensors demands the ultrasensitive detection of the analytes, which is usually limited for the conventional methods of colorimetric and fluorescence detection. The Fluorescence Resonance Energy Transfer (FRET) process, exploited by QDs, translates the close association between the analyte and the detector into optical properties and thus promises the effective detection of biomolecules. FRET based detection systems for biomolecules utilize surface-functionalized QDs which are usually modified post production using different organic groups. In this work, a novel protocol was formulated to produce bio-functionalized QDs with controlled chemical and optical characteristics. Here, we demonstrate the first-ever biological green synthesis of MoS2 QDs using Pseudomonas aeruginosa. The bio-functionalized QDs show green luminescence with a quantum yield of 42%, supporting their application as an optical sensor. These QDs are utilized to detect the pico-molar concentration of glucose, which makes them ideal for early diabetes detection and many biomedical applications. Also, the ability to sense pico-molar levels of H2O2 opens the path for its utilization in apprehending the plant signaling pathways under stress conditions.

Gut microbiome-mediated epigenetic regulation of brain disorder and application of machine learning for multi-omics data analysis

The gut-brain axis (GBA) is a biochemical link that connects the central nervous system (CNS) and enteric nervous system (ENS). Clinical and experimental evidence suggests gut microbiota as a key regulator of the GBA. Microbes living in the gut not only interact locally with intestinal cells and the ENS but have also been found to modulate the CNS through neuroendocrine and metabolic pathways. Studies have also explored the involvement of gut microbiota dysbiosis in depression, anxiety, autism, stroke, and pathophysiology of other neurodegenerative diseases. Recent reports suggest that microbe-derived metabolites can influence host metabolism by acting as epigenetic regulators. Butyrate, an intestinal bacterial metabolite, is a known histone deacetylase inhibitor that has shown to improve learning and memory in animal models. Due to high disease variability amongst the population, a multi-omics approach that utilizes artificial intelligence and machine learning to analyze and integrate omics data is necessary to better understand the role of the GBA in pathogenesis of neurological disorders, to generate predictive models, and to develop precise and personalized therapeutics. This review examines our current understanding of epigenetic regulation of the GBA and proposes a framework to integrate multi-omics data for prediction, prevention, and development of precision health approaches to treat brain disorders.