N-phenyl pyrazoline derivative inhibits cell aggressiveness and enhances paclitaxel sensitivity of triple negative breast cancer cells.

Protein kinase dysregulation induces cancer cell aggressiveness leading to rapid tumor progression and poor prognosis in TNBC patients. Many small-molecule kinase inhibitors have been tested in clinical trials to treat TNBC patients. In the previous study, we found that N-phenylpyrazoline small molecule acts as a protein kinase inhibitor in cervical cancer cells. However, there remains unknown about N-phenyl pyrazoline potency as a kinase inhibitor and its anti-cancer activity in TNBC cells. In this study, we investigated the activity of N-phenyl pyrazoline against TNBC cells via tyrosine kinase inhibition. Based on the MTT assay, the IC50 values for the N-phenyl pyrazoline 2, 5, A, B, C, and D against Hs578T were 12.63 µM, 3.95 µM, not available, 18.62 µM, 30.13 µM, and 26.79 µM, respectively. While only P5 exhibited the IC50 against MDA MB 231 (21.55 µM). Further, N-phenyl pyrazoline 5 treatment significantly inhibited the cell proliferation rate of Hs578T and MDA MB 231 cells. The migration assay showed that treatment with the compound N-phenyl pyrazoline 5 with 4 µM concentration significantly reduced cell migration of Hs578T cells. N-phenyl pyrazoline 5 treatment at 1 µM and 2 µM was able to reduce the tumorsphere size of Hs578t cells. A combination treatment of P5 and paclitaxel showed a synergistic effect with a combination index score > 1 in both TNBC cells. Further, the P5 predictively targeted the protein kinases that significantly correlated to breast cancer prognosis. The GSEA analysis result shows that receptor tyrosine kinase, Notch3, Notch4, and Ephrin signaling pathways were targeted by P5. The P5 treatment reduced the EGFR expression level and activation in TNBC cells.

Higher-order nonequilibrium term: Effective power density quantifying evolution towards or away from local thermodynamic equilibrium.

A common approach to assess the nature of energy conversion in a classical fluid or plasma is to compare power densities of the various possible energy conversion mechanisms. A leading research area is quantifying energy conversion for systems that are not in local thermodynamic equilibrium (LTE), as is common in a number of fluid and plasma systems. Here we introduce the "higher-order nonequilibrium term" (HORNET) effective power density, which quantifies the rate of change of departure of a phase space density from LTE. It has dimensions of power density, which allows for quantitative comparisons with standard power densities. We employ particle-in-cell simulations to calculate HORNET during two processes, magnetic reconnection and decaying kinetic turbulence in collisionless magnetized plasmas, that inherently produce non-LTE effects. We investigate the spatial variation of HORNET and the time evolution of its spatial average. By comparing HORNET with power densities describing changes to the internal energy (pressure dilatation, Pi-D, and divergence of the vector heat flux density), we find that HORNET can be a significant fraction of these other measures (8% and 35% for electrons and ions, respectively, for reconnection; up to 67% for both electrons and ions for turbulence), meaning evolution of the system towards or away from LTE can be dynamically important. Applications to numerous plasma phenomena are discussed.

Deep-WET: a deep learning-based approach for predicting DNA-binding proteins using word embedding techniques with weighted features.

DNA-binding proteins (DBPs) play a significant role in all phases of genetic processes, including DNA recombination, repair, and modification. They are often utilized in drug discovery as fundamental elements of steroids, antibiotics, and anticancer drugs. Predicting them poses the most challenging task in proteomics research. Conventional experimental methods for DBP identification are costly and sometimes biased toward prediction. Therefore, developing powerful computational methods that can accurately and rapidly identify DBPs from sequence information is an urgent need. In this study, we propose a novel deep learning-based method called Deep-WET to accurately identify DBPs from primary sequence information. In Deep-WET, we employed three powerful feature encoding schemes containing Global Vectors, Word2Vec, and fastText to encode the protein sequence. Subsequently, these three features were sequentially combined and weighted using the weights obtained from the elements learned through the differential evolution (DE) algorithm. To enhance the predictive performance of Deep-WET, we applied the SHapley Additive exPlanations approach to remove irrelevant features. Finally, the optimal feature subset was input into convolutional neural networks to construct the Deep-WET predictor. Both cross-validation and independent tests indicated that Deep-WET achieved superior predictive performance compared to conventional machine learning classifiers. In addition, in extensive independent test, Deep-WET was effective and outperformed than several state-of-the-art methods for DBP prediction, with accuracy of 78.08%, MCC of 0.559, and AUC of 0.805. This superior performance shows that Deep-WET has a tremendous predictive capacity to predict DBPs. The web server of Deep-WET and curated datasets in this study are available at https://deepwet-dna.monarcatechnical.com/ . The proposed Deep-WET is anticipated to serve the community-wide effort for large-scale identification of potential DBPs.

Potential effects of the most prescribed drugs on the microbiota-gut-brain-axis: A review.

The link between drug-induced dysbiosis and its influence on brain diseases through gut-residing bacteria and their metabolites, named the microbiota-gut-brain axis (MGBA), remains largely unexplored. This review investigates the effects of commonly prescribed drugs (metformin, statins, proton-pump-inhibitors, NSAIDs, and anti-depressants) on the gut microbiota, comparing the findings with altered bacterial populations in major brain diseases (depression, multiple sclerosis, Parkinson's and Alzheimer's). The report aims to explore whether drugs can influence the development and progression of brain diseases via the MGBA. Central findings indicate that all explored drugs induce dysbiosis. These dysbiosis patterns were associated with brain disorders. The influence on brain diseases varied across different bacterial taxa, possibly mediated by direct effects or through bacterial metabolites. Each drug induced both positive and negative changes in the abundance of bacteria, indicating a counterbalancing effect. Moreover, the above-mentioned drugs exhibited similar effects, suggesting that they may counteract or enhance each other's effects on brain diseases when taken together by comorbid patients. In conclusion, the interplay of bacterial species and their abundances may have a greater impact on brain diseases than individual drugs or bacterial strains. Future research is needed to better understand drug-induced dysbiosis and the implications for brain disease pathogenesis, with the potential to develop more effective therapeutic options for patients with brain-related diseases.

Using Direct Laboratory Measurements of Electron Temperature Anisotropy to Identify the Heating Mechanism in Electron-Only Guide Field Magnetic Reconnection.

Anisotropic electron heating during electron-only magnetic reconnection with a large guide magnetic field is directly measured in a laboratory plasma through in situ measurements of electron velocity distribution functions. Electron heating preferentially parallel to the magnetic field is localized to one separatrix, and anisotropies of 1.5 are measured. The mechanism for electron energization is identified as the parallel reconnection electric field because of the anisotropic nature of the heating and spatial localization. These characteristics are reproduced in a 2D particle-in-cell simulation and are also consistent with numerous magnetosheath observations. A measured increase in the perpendicular temperature along both separatrices is not reproduced by our 2D simulations. This work has implications for energy partition studies in magnetosheath and laboratory reconnection.

Non-Healing Chronic Traumatic Ulcer, an Entity That Can Resemble Other Chronic Ulcers.

Introduction: Traumatic ulcer commonly occurs in the oral cavity, resulting in the loss of the entire epithelium. Traumatic ulcers often appear to mimic other lesions of the oral mucosa but the causative factors and other characteristic features rule out the differential diagnosis. It may have a similar appearance to some oral ulcer lesions such as traumatic ulcer granuloma with stromal eosinophilia (TUGSE) and oral squamous cell carcinoma (OSCC). Objective: To identify traumatic ulcers from other chronic lesions such as TUGSE and OSCC. Case: First case, a 63-year-old female complained of pain on the right side of the tongue for 4 months. Intraoral examination showed a painful single ulcer, mild keratosis white halo, and induration on the right lateral of the tongue. The second case, a 38-year-old male complained of pain on the left side of the tongue for 2 months. Intraoral examination showed a painful single ulcer, mild keratosis white halo, and induration on the left lateral of the tongue. In both cases, there were some retained roots where the ulcer was located, and due to its contact with lateral of the tongue and the appearance of the lesion, we got a provisional diagnosis of traumatic ulcer. Case Management: These ulcers had a visual appearance similar to OSCC and TUGSE, so eliminating etiological factors and a comprehensive treatment plan were needed. We planned to extract teeth close to the lesion that was suspected to be the etiology of traumatic ulcer. We also prescribed 0.1% triamcinolone acetonide in orabase to improve healing. One week later, the ulcer in both patients had healed. Conclusion: Recognition of traumatic ulcer characteristics is crucial in eliminating local factors to get rid of any differential diagnosis.

Sex-dependent endozepinergic regulation of ventromedial hypothalamic nucleus glucose counter-regulatory neuron aromatase protein expression in the adult rat.

The hypothalamic brain cell types that produce estradiol from testosterone remain unclear. Aromatase inhibition affects ventromedial hypothalamic nucleus (VMN) glucose-stimulatory nitric oxide (NO) and glucose-inhibitory γ-aminobutyric acid (GABA) transmission during insulin (INS)-induced hypoglycemia (IIH). Pure GABA and NO nerve cell samples acquired by laser-catapult-microdissection from consecutive rostro-caudal segments of the VMN were analyzed by Western blot to investigate whether regional subpopulations of each cell type contain machinery for neuro-estradiol synthesis. Astrocyte endozepinergic signaling governs brain steroidogenesis. Pharmacological tools were used here to determine if the glio-peptide octadecaneuropeptide (ODN) controls aromatase expression in GABA and NO neurons during eu- and/or hypoglycemia. Intracerebroventricular administration of the ODN G-protein coupled-receptor antagonist cyclo(1-8)[DLeu5]OP (LV-1075) decreased (male) or enhanced (female) VMN GABAergic neuron aromatase expression, but increased or reduced this profile in nitrergic neurons in a region-specific manner in each sex. IIH suppressed aromatase levels in GABA neurons located in the middle segment of the male VMN or distributed throughout this nucleus in the female. This inhibitory response was altered by the ODN isoactive surrogate octapeptide (OP) in female, but was refractory to OP in male. NO neuron aromatase protein in hypoglycemic male (middle and caudal VMN) and female (rostral and caudal VMN) rats, but was normalized in OP- plus INS-treated rats of both sexes. Results provide novel evidence that VMN glucose-regulatory neurons may produce neuro-estradiol, and that the astrocyte endozepine transmitter ODN may impose sex-specific control of baseline and/or hypoglycemic patterns of aromatase expression in distinct subsets of nitrergic and GABAergic neurons in this neural structure.

Quantitative analysis of serum cell-free DNA as a predictive and prognostic marker in breast cancer patients.

Introduction: According to the GLOBOCAN (Global Cancer Observatory) 2020 report, 13,028 new cases of breast cancer (19%) were diagnosed in the United States, and 6,783 of them succumbed to the disease, making it the most common cancer among women. The clinical stage at the time of diagnosis is one of the most significant survival predictors in breast cancer. With delayed illness detection comes a lower survival rate. The prognosis of breast cancer may be predicted using circulating cell-free DNA (cfDNA), a non-invasive diagnosis technique. Objective: This study aimed to determine the most sensitive and effective method for detecting changes in cfDNA levels and for using cfDNA as a diagnostic and prognostic marker of breast cancer. Methods: The potential function of serum cfDNA levels as a marker for early breast cancer diagnosis was investigated using UV spectrophotometric, fluorometric, and real-time qPCR assays. Results: This research suggests that the most successful way to measure the amount of cfDNA described decades ago could be used as a "liquid biopsy" to track cancer in real time. The RT-qPCR (ALU115) method produced the most statistically significant results (p=0.000). At the threshold concentration of 395.65 ng/ml of cfDNA, the ROC curve reflects the maximum AUC= 0.7607, with a sensitivity of 0.65 and specificity of 0.80. Conclusion: For a preliminary assessment of total circulating cfDNA, a combination of all of the above techniques will be most efficacious. Based on our results, we conclude that the RT-qPCR technique combined with fluorometric measurement can identify a statistically significant difference in cfDNA levels between cohorts of breast cancer patients and healthy controls.

Dietary and Non-Dietary Modulators of Cognitive Function.

Manifold internal and external factors may influence brain function in the long run, including genetic predispositions as well as epigenetic and environmental factors [...].

Study of kaempferol in the treatment of COVID-19 combined with Chikungunya co-infection by network pharmacology and molecular docking technology.

Chikungunya (CHIK) patients may be vulnerable to coronavirus disease (COVID-19). However, presently there are no anti-COVID-19/CHIK therapeutic alternatives available. The purpose of this research was to determine the pharmacological mechanism through which kaempferol functions in the treatment of COVID-19-associated CHIK co-infection. We have used a series of network pharmacology and computational analysis-based techniques to decipher and define the binding capacity, biological functions, pharmacological targets, and treatment processes in COVID-19-mediated CHIK co-infection. We identified key therapeutic targets for COVID-19/CHIK, including TP53, MAPK1, MAPK3, MAPK8, TNF, IL6 and NFKB1. Gene ontology, molecular and upstream pathway analysis of kaempferol against COVID-19 and CHIK showed that DEGs were confined mainly to the cytokine-mediated signalling pathway, MAP kinase activity, negative regulation of the apoptotic process, lipid and atherosclerosis, TNF signalling pathway, hepatitis B, toll-like receptor signaling, IL-17 and IL-18 signaling pathways. The study of the gene regulatory network revealed several significant TFs including KLF16, GATA2, YY1 and FOXC1 and miRNAs such as let-7b-5p, mir-16-5p, mir-34a-5p, and mir-155-5p that target differential-expressed genes (DEG). According to the molecular coupling results, kaempferol exhibited a high affinity for 5 receptor proteins (TP53, MAPK1, MAPK3, MAPK8, and TNF) compared to control inhibitors. In combination, our results identified significant targets and pharmacological mechanisms of kaempferol in the treatment of COVID-19/CHIK and recommended that core targets be used as potential biomarkers against COVID-19/CHIK viruses. Before conducting clinical studies for the intervention of COVID-19 and CHIK, kaempferol might be evaluated in wet lab tests at the molecular level.

Nutrition and Aging.

This Special Issue focuses on the importance of nutritional interventions for the delay of age-related conditions [...].

A Novel Hybrid Approach for Classifying Osteosarcoma Using Deep Feature Extraction and Multilayer Perceptron.

Osteosarcoma is the most common type of bone cancer that tends to occur in teenagers and young adults. Due to crowded context, inter-class similarity, inter-class variation, and noise in H&E-stained (hematoxylin and eosin stain) histology tissue, pathologists frequently face difficulty in osteosarcoma tumor classification. In this paper, we introduced a hybrid framework for improving the efficiency of three types of osteosarcoma tumor (nontumor, necrosis, and viable tumor) classification by merging different types of CNN-based architectures with a multilayer perceptron (MLP) algorithm on the WSI (whole slide images) dataset. We performed various kinds of preprocessing on the WSI images. Then, five pre-trained CNN models were trained with multiple parameter settings to extract insightful features via transfer learning, where convolution combined with pooling was utilized as a feature extractor. For feature selection, a decision tree-based RFE was designed to recursively eliminate less significant features to improve the model generalization performance for accurate prediction. Here, a decision tree was used as an estimator to select the different features. Finally, a modified MLP classifier was employed to classify binary and multiclass types of osteosarcoma under the five-fold CV to assess the robustness of our proposed hybrid model. Moreover, the feature selection criteria were analyzed to select the optimal one based on their execution time and accuracy. The proposed model achieved an accuracy of 95.2% for multiclass classification and 99.4% for binary classification. Experimental findings indicate that our proposed model significantly outperforms existing methods; therefore, this model could be applicable to support doctors in osteosarcoma diagnosis in clinics. In addition, our proposed model is integrated into a web application using the FastAPI web framework to provide a real-time prediction.

In Vitro Biofouling Performance of Boron-Doped Diamond Microelectrodes for Serotonin Detection Using Fast-Scan Cyclic Voltammetry.

Neurotransmitter release is important to study in order to better understand neurological diseases and treatment approaches. Serotonin is a neurotransmitter known to play key roles in the etiology of neuropsychiatric disorders. Fast-scan cyclic voltammetry (FSCV) has enabled the detection of neurochemicals, including serotonin, on a sub-second timescale via the well-established carbon fiber microelectrode (CFME). However, poor chronic stability and biofouling, i.e., the adsorption of interferent proteins to the electrode surface upon implantation, pose challenges in the natural physiological environment. We have recently developed a uniquely designed, freestanding, all-diamond boron-doped diamond microelectrode (BDDME) for electrochemical measurements. Key potential advantages of the device include customizable electrode site layouts, a wider working potential window, improved stability, and resistance to biofouling. Here, we present a first report on the electrochemical behavior of the BDDME in comparison with CFME by investigating in vitro serotonin (5-HT) responses with varying FSCV waveform parameters and biofouling conditions. While the CFME delivered lower limits of detection, we also found that BDDMEs showed more sustained 5-HT responses to increasing or changing FSCV waveform-switching potential and frequency, as well as to higher analyte concentrations. Biofouling-induced current reductions were significantly less pronounced at the BDDME when using a "Jackson" waveform compared to CFMEs. These findings are important steps towards the development and optimization of the BDDME as a chronically implanted biosensor for in vivo neurotransmitter detection.

Evaluation of instrumental variable method using Cox proportional hazard model in epidemiological studies.

The instrumental variable (IV) method with a Cox proportional hazard (PH) model has been used to evaluate treatment effects in epidemiological studies involving survival data. The effectiveness of the IV methods in these circumstances has yet to be fully understood, though. The study aimed to evaluate the performance of IV methods using a Cox model. We evaluated the validity of treatment effects estimated by two-stage IV models using simulated scenarios with varying confounder strengths and baseline hazards. Our simulation demonstrated that when observed confounders were not taken into account in the IV models, and the confounder strength was moderate, the treatment effects based on the two-stage IV models were similar to the true value. However, the effect estimates diverged from the true value when observed confounders were taken into account in the IV models. In the case of a null treatment effect (i.e., hazard ratio=1), the estimates from the unadjusted and adjusted IV models (only two-stage) were close to the true value. The implication of our study findings is that the treatment effects obtained through IV analyses using the Cox PH model remain valid if the estimates are reported from unadjusted IV models with moderate confounding effects or if the treatment does not impact the outcome.•For every simulation, we utilized a sample size of 10,000 and performed 1,000 replications.•The true treatment effects (HR) of 3, 2, and 1 (null effect) were evaluated.•The 95% confidence intervals (CI) were calculated as the range between the 2.5 and 97.5 percentiles of the 1000 estimates.

COVID-19 Infection as an Exacerbated Factor of Oral Candidiasis in HIV/AIDS Patient.

Introduction: Oral candidiasis is an oral mucosal infection caused by Candida sp. This infection can appear in patients with HIV/AIDS associated with immunodeficiency. Another factor that can aggravate the occurrence of oral candidiasis is the COVID-19 infection caused by the SARS-CoV-2 virus as a current pandemic condition. This case report aims to explain the mechanism of COVID-19 infection as a factor that can aggravate the condition of oral candidiasis in HIV/AIDS patients. Case: A 56-year-old male patient was consulted from the COVID-19 isolation unit to the Department of Oral Medicine with complaints of sore and uncomfortable mouth related to white plaque covering the surface of the tongue. The patient was diagnosed with HIV/AIDS and had a COVID-19 infection. The management instructions were to maintain oral hygiene, administration of antifungal drugs such as nystatin oral suspension and fluconazole, chlorhexidine gluconate 0.2% mouthwash, and vaseline album. Discussion: Generally, HIV/AIDS patient has dysregulation of the immune system which can suppress host immunity to fight pathogens, making it easy for opportunistic infections such as oral candidiasis. The COVID-19 infection can cause lymphopenia conditions that further reduce the host's ability to fight pathogens. The SARS-CoV-2 virus can also directly attack various tissues in the oral mucosa which can contribute to exacerbating the severity of oral candidiasis in HIV/AIDS patients. Conclusion: The COVID-19 infection is a factor that can exacerbate the condition of oral candidiasis in HIV/AIDS patients by further decreasing the host's immunity and damaging various tissues in the oral mucosa.

Sex-Dimorphic Octadecaneuropeptide (ODN) Regulation of Ventromedial Hypothalamic Nucleus Glucoregulatory Neuron Function and Counterregulatory Hormone Secretion.

Central endozepinergic signaling is implicated in glucose homeostasis. Ventromedial hypothalamic nucleus (VMN) metabolic monitoring governs glucose counter-regulation. VMN glucose-stimulatory nitric oxide (NO) and glucose-inhibitory γ-aminobutyric acid (GABA) neurons express the energy gauge 5'-AMP-activated protein kinase (AMPK). Current research addresses the premise that the astrocyte glio-peptide octadecaneuropeptide (ODN) imposes sex-dimorphic control of metabolic sensor activity and neurotransmitter signaling in these neurons. The ODN G-protein coupled-receptor antagonist cyclo(1-8)[DLeu5]OP (LV-1075) was administered intracerebroventricularly (icv) to euglycemic rats of each sex; additional groups were pretreated icv with the ODN isoactive surrogate ODN11-18 (OP) before insulin-induced hypoglycemia. Western blotting of laser-catapult-microdissected VMN NO and GABA neurons showed that hypoglycemia caused OP-reversible augmentation of phospho-, e.g., activated AMPK and nitric oxide synthase (nNOS) expression in rostral (female) or middle (male) VMN segments or ODN-dependent suppression of nNOS in male caudal VMN. OP prevented hypoglycemic down-regulation of glutamate decarboxylase profiles in female rat rostral VMN, without affecting AMPK activity. LV-1075 treatment of male, not female rats elevated plasma glucagon and corticosterone concentrations. Moreover, OP attenuated hypoglycemia-associated augmentation of these hormones in males only. Results identify, for each sex, regional VMN metabolic transmitter signals that are subject to endozepinergic regulation. Directional shifts and gain-or-loss of ODN control during eu- versus hypoglycemia infer that VMN neuron receptivity to or post-receptor processing of this stimulus may be modulated by energy state. In male, counter-regulatory hormone secretion may be governed principally by ODN-sensitive neural pathways, whereas this endocrine outflow may be controlled by parallel, redundant ODN-dependent and -independent mechanisms in female.

An integrated complete-genome sequencing and systems biology approach to predict antimicrobial resistance genes in the virulent bacterial strains of Moraxella catarrhalis.

Moraxella catarrhalis is a symbiotic as well as mucosal infection-causing bacterium unique to humans. Currently, it is considered as one of the leading factors of acute middle ear infection in children. As M. catarrhalis is resistant to multiple drugs, the treatment is unsuccessful; therefore, innovative and forward-thinking approaches are required to combat the problem of antimicrobial resistance (AMR). To better comprehend the numerous processes that lead to antibiotic resistance in M. catarrhalis, we have adopted a computational method in this study. From the NCBI-Genome database, we investigated 12 strains of M. catarrhalis. We explored the interaction network comprising 74 antimicrobial-resistant genes found by analyzing M. catarrhalis bacterial strains. Moreover, to elucidate the molecular mechanism of the AMR system, clustering and the functional enrichment analysis were assessed employing AMR gene interactions networks. According to the findings of our assessment, the majority of the genes in the network were involved in antibiotic inactivation; antibiotic target replacement, alteration and antibiotic efflux pump processes. They exhibit resistance to several antibiotics, such as isoniazid, ethionamide, cycloserine, fosfomycin, triclosan, etc. Additionally, rpoB, atpA, fusA, groEL and rpoL have the highest frequency of relevant interactors in the interaction network and are therefore regarded as the hub nodes. These genes can be exploited to create novel medications by serving as possible therapeutic targets. Finally, we believe that our findings could be useful to advance knowledge of the AMR system present in M. catarrhalis.

Quantifying Energy Conversion in Higher-Order Phase Space Density Moments in Plasmas.

Weakly collisional and collisionless plasmas are typically far from local thermodynamic equilibrium (LTE), and understanding energy conversion in such systems is a forefront research problem. The standard approach is to investigate changes in internal (thermal) energy and density, but this omits energy conversion that changes any higher-order moments of the phase space density. In this Letter, we calculate from first principles the energy conversion associated with all higher moments of the phase space density for systems not in LTE. Particle-in-cell simulations of collisionless magnetic reconnection reveal that energy conversion associated with higher-order moments can be locally significant. The results may be useful in numerous plasma settings, such as reconnection, turbulence, shocks, and wave-particle interactions in heliospheric, planetary, and astrophysical plasmas.

Sex-dimorphic hindbrain lactate regulation of ventromedial hypothalamic nucleus glucoregulatory neuron 5'-AMP-activated protein kinase activity and transmitter marker protein expression.

BACKGROUND: The oxidizable glycolytic end-product L-lactate is a gauge of nerve cell metabolic fuel stability that metabolic-sensory hindbrain A2 noradrenergic neurons impart to the brain glucose-regulatory network. Current research investigated the premise that hindbrain lactate deficiency exerts sex-specific control of energy sensor and transmitter marker protein responses to hypoglycemia in ventromedial hypothalamic nucleus (VMN) glucose-regulatory nitrergic and γ-aminobutyric acid (GABA) neurons. METHODS: Nitric oxide synthase (nNOS)- or glutamate decarboxylase65/67 (GAD)-immunoreactive neurons were laser-catapult-microdissected from male and female rat VMN after subcutaneous insulin injection and caudal fourth ventricular L-lactate or vehicle infusion for Western blot protein analysis. RESULTS: Hindbrain lactate repletion reversed hypoglycemia-associated augmentation (males) or inhibition (females) of nitrergic neuron nNOS expression, and prevented up-regulation of phosphorylated AMPK 5'-AMP-activated protein kinase (pAMPK) expression in those neurons. Hypoglycemic suppression of GABAergic neuron GAD protein was averted by exogenous lactate over the rostro-caudal length of the male VMN and in the middle region of the female VMN. Lactate normalized GABA neuron pAMPK profiles in hypoglycemic male (caudal VMN) and female (all VMN segments) rats. Hypoglycemic patterns of norepinephrine (NE) signaling were lactate-dependent throughout the male VMN, but confined to the rostral and middle female VMN. CONCLUSIONS: Results document, in each sex, regional VMN glucose-regulatory transmitter responses to hypoglycemia that are controlled by hindbrain lactate status. Hindbrain metabolic-sensory regulation of hypoglycemia-correlated nitric oxide or GABA release may entail AMPK-dependent mechanisms in specific VMN rostro-caudal segments in each sex. Additional effort is required to examine the role of hindbrain lactoprivic-sensitive VMN neurotransmitters in lactate-mediated attenuation of hypoglycemic hyperglucagonemia and hypercorticosteronemia in male and female rats.

Effects of Ventromedial Hypothalamic Nucleus (VMN) Aromatase Gene Knockdown on VMN Glycogen Metabolism and Glucoregulatory Neurotransmission.

The enzyme aromatase is expressed at high levels in the ventromedial hypothalamic nucleus (VMN), a principal component of the brain gluco-regulatory network. Current research utilized selective gene knockdown tools to investigate the premise that VMN neuroestradiol controls glucostasis. Intra-VMN aromatase siRNA administration decreased baseline aromatase protein expression and tissue estradiol concentrations and either reversed or attenuated the hypoglycemic regulation of these profiles in a VMN segment-specific manner. Aromatase gene repression down-regulated protein biomarkers for gluco-stimulatory (nitric oxide; NO) and -inhibitory (gamma-aminobutyric acid; GABA) neurochemical transmitters. Insulin-induced hypoglycemia (IIH) up- or down-regulated neuronal nitric oxide synthase (nNOS) and glutamate decarboxylase65/67 (GAD), respectively, throughout the VMN. Interestingly, IIH caused divergent changes in tissue aromatase and estradiol levels in rostral (diminished) versus middle and caudal (elevated) VMN. Aromatase knockdown prevented hypoglycemic nNOS augmentation in VMN middle and caudal segments, but abolished the GAD inhibitory response to IIH throughout this nucleus. VMN nitrergic and GABAergic neurons monitor stimulus-specific glycogen breakdown. Here, glycogen synthase (GS) and phosphorylase brain- (GPbb; AMP-sensitive) and muscle- (GPmm; noradrenergic -responsive) type isoform responses to aromatase siRNA were evaluated. Aromatase repression reduced GPbb and GPmm content in euglycemic controls and prevented hypoglycemic regulation of GPmm but not GPbb expression while reversing glycogen accumulation. Aromatase siRNA elevated baseline glucagon and corticosterone secretion and abolished hypoglycemic hyperglucagonemia and hypercorticosteronemia. Outcomes document the involvement of VMN neuroestradiol signaling in brain control of glucose homeostasis. Aromatase regulation of VMN gluco-regulatory signaling of hypoglycemia-associated energy imbalance may entail, in part, control of GP variant-mediated glycogen disassembly.