•The mRNA expression of the bitter taste receptor T2R38 is differentially regulated by SNPs.•Genotype- and bacteria-specific reduction of antimicrobial peptide hBD-2 secretion is observed in the ...absence of T2R38.•IL-1a and IL-8 secretion is also genotype-specific for T2R38.•T2R38 modulates innate oral immunity in a genotype-specific manner.•Modulation of hBD-2 secretion via T2R38 may be the mechanism by which the PAV haplotype confers caries protection.
The bitter taste receptor T2R38 has been shown to regulate mucosal innate immune responses in the upper airway epithelium. Furthermore, SNPs in T2R38 influence the sensitivity to 6-n-propylthiouracil (PROP) and are associated with caries risk/protection. However, no study has been reported on the role of T2R38 in the innate immune responses to oral bacteria. We hypothesize that T2R38 regulates oral innate immunity and that this regulation is genotype-specific. Primary gingival epithelial cells carrying three common genotypes, PAV/PAV (PROP super-taster), AVI/PAV (intermediate) and AVI/AVI (non-taster) were stimulated with cariogenic bacteria Streptococcus mutans, periodontal pathogen Porphyromonas gingivalis or non-pathogen Fusobacterium nucleatum. QRT-PCR analyzed T2R38 mRNA, and T2R38-specific siRNA and ELISA were utilized to evaluate induction of hBD-2 (antimicrobial peptide), IL-1α and IL-8 in various donor-lines. Experiments were set up in duplicate and repeated three times. T2R38 mRNA induction in response to S. mutans was highest in PAV/PAV (4.3-fold above the unstimulated controls; p<0.05), while lowest in AVI/AVI (1.2-fold). In PAV/PAV, hBD-2 secretion in response to S. mutans was decreased by 77% when T2R38 was silenced. IL-1α secretion was higher in PAV/PAV compared to AVI/PAV or AVI/AVI with S. mutans stimulation, but it was reduced by half when T2R38 was silenced (p<0.05). In response to P. gingivalis, AVI/AVI showed 4.4-fold increase (p<0.05) in T2R38 expression, whereas the levels in PAV/PAV and AVI/PAV remained close to that of the controls. Secretion levels of IL-1α and IL-8 decreased in AVI/AVI in response to P. gingivalis when T2R38 was silenced (p<0.05), while the changes were not significant in PAV/PAV. Our data suggest that the regulation of gingival innate immunity by T2R38 is genotype-dependent and that the ability to induce a high level of hBD-2 by PAV/PAV carriers may be a reason for protection against caries in this group.
The prevalence of obesity has increased dramatically worldwide. The obesity epidemic begs for novel concepts and therapeutic targets that cohesively address "food-abuse" disorders. We demonstrate a ...molecular link between impairment of a central kinase (Akt) involved in insulin signaling induced by exposure to a high-fat (HF) diet and dysregulation of higher order circuitry involved in feeding. Dopamine (DA) rich brain structures, such as striatum, provide motivation stimuli for feeding. In these central circuitries, DA dysfunction is posited to contribute to obesity pathogenesis. We identified a mechanistic link between metabolic dysregulation and the maladaptive behaviors that potentiate weight gain. Insulin, a hormone in the periphery, also acts centrally to regulate both homeostatic and reward-based HF feeding. It regulates DA homeostasis, in part, by controlling a key element in DA clearance, the DA transporter (DAT). Upon HF feeding, nigro-striatal neurons rapidly develop insulin signaling deficiencies, causing increased HF calorie intake.
We show that consumption of fat-rich food impairs striatal activation of the insulin-activated signaling kinase, Akt. HF-induced Akt impairment, in turn, reduces DAT cell surface expression and function, thereby decreasing DA homeostasis and amphetamine (AMPH)-induced DA efflux. In addition, HF-mediated dysregulation of Akt signaling impairs DA-related behaviors such as (AMPH)-induced locomotion and increased caloric intake. We restored nigro-striatal Akt phosphorylation using recombinant viral vector expression technology. We observed a rescue of DAT expression in HF fed rats, which was associated with a return of locomotor responses to AMPH and normalization of HF diet-induced hyperphagia.
Acquired disruption of brain insulin action may confer risk for and/or underlie "food-abuse" disorders and the recalcitrance of obesity. This molecular model, thus, explains how even short-term exposure to "the fast food lifestyle" creates a cycle of disordered eating that cements pathological changes in DA signaling leading to weight gain and obesity.
Elevated plasma triglyceride (TG) levels contribute to an atherogenic dyslipidemia that is associated with obesity, diabetes, and metabolic syndrome. Numerous models of obesity are characterized by ...increased central nervous system (CNS) neuropeptide Y (NPY) tone that contributes to excess food intake and obesity. Previously, we demonstrated that intracerebroventricular (icv) administration of NPY in lean fasted rats also elevates hepatic production of very low-density lipoprotein (VLDL)-TG. Thus, we hypothesize that elevated CNS NPY action contributes to not only the pathogenesis of obesity but also dyslipidemia. Here, we sought to determine whether the effects of NPY on feeding and/or obesity are dissociable from effects on hepatic VLDL-TG secretion. Pair-fed, icv NPY-treated, chow-fed Long-Evans rats develop hypertriglyceridemia in the absence of increased food intake and body fat accumulation compared with vehicle-treated controls. We then modulated CNS NPY signaling by icv injection of selective NPY receptor agonists and found that Y1, Y2, Y4, and Y5 receptor agonists all induced hyperphagia in lean, ad libitum chow-fed Long-Evans rats, with the Y2 receptor agonist having the most pronounced effect. Next, we found that at equipotent doses for food intake NPY Y1 receptor agonist had the most robust effect on VLDL-TG secretion, a Y2 receptor agonist had a modest effect, and no effect was observed for Y4 and Y5 receptor agonists. These findings, using selective agonists, suggest the possibility that the effect of CNS NPY signaling on hepatic VLDL-TG secretion may be relatively dissociable from effects on feeding behavior via the Y1 receptor.
•Seismic performance-based design of steel structures.•Seismic loss estimation considering direct economic and social losses.•Multi-objective optimization.•Comparison of evaluated seismic losses in ...different geographic locations.
Seismic performance-based design of a steel structure is performed using a multi-objective optimization that considers both direct economic and social losses. Specified performance objectives are considered as constraints and their variance over the obtained Pareto front is investigated. Optimization objectives are selected as the lifetime cost calculated from the initial construction cost and expected annual loss associated with seismic direct economic losses, and direct social loss parameter defined as expected annual social loss. Inelastic time history analysis is used to evaluate structural response under different levels of earthquake hazard to obtain engineering demand parameters. To illustrate the seismic performance-based design procedure, calculations are presented and compared for a sample steel structure located in Los Angeles, CA and Memphis, TN.
An optimized seismic performance-based design (PBD) methodology considering structural and nonstructural system performance and seismic losses is considered to optimize the design of a steel ...structure. Optimization objectives are to minimize the initial construction cost associated with the weight of the structural system and the expected annual loss (EAL), considering direct economic losses. A non-dominated sorting genetic algorithm method is implemented for the multi-objective optimization. Achieving the desired confidence levels in meeting performance objectives of interest are set as constraints of the optimization problem. Inelastic time history analysis is used to evaluate structural response under different levels of earthquake hazard to obtain engineering demand parameters. Hazus fragility functions are employed for obtaining the damage probabilities for the structural system and nonstructural components. The optimized designs and losses are compared for the structure located in two geographic locations: one in the central United States and another in the western United States.
A novel hybrid evolutionary neural network method to generate multiple spectrum-compatible artificial earthquake accelerograms (SCAEAs) is presented. Genetic algorithm is employed to optimize the ...weight values of networks. In order to improve the training efficiency, principal component analysis along with some other reduction techniques are used. The proposed evolutionary neural network develops an inverse mapping from compacted and reduced spectrum coefficients to the metamorphosed accelerogram's wavelet packet coefficients. As compared to the traditional methods, our algorithm is capable of generating an ensemble of dissimilar 10, 20, 30, and 40 s SCAEAs with better spectrum-compatibility and diversity, and proper computational efforts.
Background: Idiopathic granulomatous mastitis (IGM) is a rare inflammatory disease of the breast with unknown etiology. Clinico-radiologic findings can mimic breast cancer. Further pathologic ...evaluation to rule out malignancy is mandatory. Recognizing the severity of the disease is crucial to choosing the most effective therapeutic modality. The aim of this study is to evaluate clinical and radio-pathologic features of IGM, and the treatment outcome in a large series of IGM patients in Iran.Methods: The retrospective charts of 243 patients suspicious of IGM, between December 2007 and September 2017 were reviewed. Patients with confirmed diagnosis of IGM were classified into four grades of severity. Demographic information, clinical and radio-pathologic findings, severity and treatment outcomes were collected.Results: Overall, 224 patients were confirmed to have IGM. Breast mass and erythema were the most common clinical findings. Mammographic findings mimicked malignancy in 34%. Lobulo-centric non-caseating granulomas were the most common pathologic finding. Also, 61.5% of the patients had mild to moderate symptoms and 49.5% of them recovered completely by observation. In addition, 53 (25.9%) patients had severe symptoms and 30.8% of them were resistant to treatment. Conclusion: IGM is a diagnostic challenge. Its diagnosis is based on exclusion and a close cooperation between the clinician, the radiologist and the pathologist. Mild to moderate cases can be managed conservatively; however, severe cases may need further aggressive medical or surgical treatments.
This study pioneers the integration of echocardiography and pathology data with advanced machine learning (ML) techniques to significantly enhance the diagnostic accuracy of cardiac tumours, a ...critical yet challenging aspect of cardiology. Despite advancements in diagnostic methods, cardiac tumours' nuanced complexity and rarity necessitate more precise, non-invasive, and efficient diagnostic solutions. Our research aims to bridge this gap by developing and validating ML models—Support Vector Machines (SVM), Random Forest (RF), and Gradient Boosting Machines (GBM)—optimized for limited datasets prevalent in specialized medical fields. Utilizing a dataset comprising clinical features from 399 patients at the Heart Hospital, our study meticulously evaluated the performance of these models against traditional diagnostic metrics. The RF model emerged superior, achieving a groundbreaking accuracy of 96.25% and a perfect ROC AUC score of 0.99, significantly outperforming existing diagnostic approaches. Key predictors identified include age, echo malignancy, and echo position, underscoring the value of integrating diverse data types. Clinical validation conducted at the Heart Hospital further confirmed the models' applicability and reliability, with the RF model demonstrating a diagnostic accuracy of 94% in a real-world setting. These findings advocate for the potential of ML in revolutionizing cardiac tumour diagnostics, offering pathways to more accurate, non-invasive, and patient-centric diagnostic processes. This research not only highlights the capabilities of ML to enhance diagnostic precision in the realm of cardiac tumours but also sets a foundation for future explorations into its broader applicability across various domains of medical diagnostics, emphasizing the need for expanded datasets and external validation.
Background. Epilepsy is caused by frequent generation of excitatory impulses in different part of the brain and it would affect different aspects of quality of life in these patients.The present ...study was conducted to evaluate the quality of life and diverse Confounding Factors in epileptic patients. Methods. This Descriptive-analytical study was performed in 2017 with a simple random sampling method on 150 patients with epilepsy who admitted to the neurology department of Rouhani hospital of Babol. We used Patient Weighted Quality Of Life In Epilepsy (QOLIE-31-P) questionnaire. All statistics were carried out using SPSS v21.0 and P<0.05 was accepted as statistically significant. Results. Of the 150 participant. The mean overall quality of life score in the patients was 54.07 (11.63%). The quality of life of patients with epilepsy in females (54.19±11.52) was higher than males (53.89±11.88, p=0.979). The overall quality of life score of married patients with epilepsy 54.12 (11.12) was higher than single patients 54.04 (11.90, p=0.65). In the extent of energy (tiredness), quality of life score decreased significantly with increasing age (p=0.028). In the field of medication effects the quality of life score decreased significantly with increasing level of education (p=0.030). Conclusion. The mean overall quality of life score was intermediate which is expected required policies will be adopted to improve the status quo. It is also necessary to consider the marital status and aging in these patients.
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