ß-Adrenergic signaling induces Notch-mediated salivary gland progenitor cell control.

ß-Adrenergic signaling blockade is a mainstay of hypertension management. One percent of patients taking ß-blockers develop reduced salivary gland (SG) function. Here we investigate the role of SG progenitor cells in ß-blocker-induced hyposalivation, using human SG organoid cultures (SGOs). Compared with control SGs, initial low SG progenitor cell yield from patients taking ß-blockers was observed. When passaged, these SGOs recovered self-renewal and upregulated Notch pathway expression. Notch signaling was downregulated in situ in ß-adrenergic receptor-expressing luminal intercalated duct (ID) cells of patients taking ß-blockers. Control SGOs treated with ß-adrenergic agonist isoproterenol demonstrated increased proportion of luminal ID SGO cells with active Notch signaling. Control SGOs exposed to isoproterenol differentiated into more mature SGOs (mSGOs) expressing markers of acinar cells. We propose that ß-blocker-induced Notch signaling reduction in luminal ID cells hampers their ability to proliferate and differentiate into acinar cells, inducing a persistent hyposalivation in some patients taking ß-blocking medication.

Disease-Induced Changes in Salivary Gland Function and the Composition of Saliva.

Although the physiological control of salivary secretion has been well studied, the impact of disease on salivary gland function and how this changes the composition and function of saliva is less well understood and is considered in this review. Secretion of saliva is dependent upon nerve-mediated stimuli, which activate glandular fluid and protein secretory mechanisms. The volume of saliva secreted by salivary glands depends upon the frequency and intensity of nerve-mediated stimuli, which increase dramatically with food intake and are subject to facilitatory or inhibitory influences within the central nervous system. Longer-term changes in saliva secretion have been found to occur in response to dietary change and aging, and these physiological influences can alter the composition and function of saliva in the mouth. Salivary gland dysfunction is associated with different diseases, including Sjögren syndrome, sialadenitis, and iatrogenic disease, due to radiotherapy and medications and is usually reported as a loss of secretory volume, which can range in severity. Defining salivary gland dysfunction by measuring salivary flow rates can be difficult since these vary widely in the healthy population. However, saliva can be sampled noninvasively and repeatedly, which facilitates longitudinal studies of subjects, providing a clearer picture of altered function. The application of omics technologies has revealed changes in saliva composition in many systemic diseases, offering disease biomarkers, but these compositional changes may not be related to salivary gland dysfunction. In Sjögren syndrome, there appears to be a change in the rheology of saliva due to altered mucin glycosylation. Analysis of glandular saliva in diseases or therapeutic interventions causing salivary gland inflammation frequently shows increased electrolyte concentrations and increased presence of innate immune proteins, most notably lactoferrin. Altering nerve-mediated signaling of salivary gland secretion contributes to medication-induced dysfunction and may also contribute to altered saliva composition in neurodegenerative disease.

Evaluation of computational techniques for predicting non-synonymous single nucleotide variants pathogenicity.

The human genetic diseases associated with many factors, one of these factors is the non-synonymous Single Nucleotide Variants (nsSNVs) cause single amino acid change with another resulting in protein function change leading to disease. Many computational techniques have been released to expect the impacts of amino acid alteration on protein function and classify mutations as pathogenic or neutral. Here in this article, we assessed the performance of eight techniques; FATHMM, SIFT, Provean, iFish, Mutation Assessor, PANTHER, SNAP2, and PON- P2 using a VaribenchSelectedPure dataset of 2144 pathogenic variants and 3777 neutral variants extracted from the free standard database "Varibench." The first five techniques achieve (45.60-83.75) % specificity, (52.64-94.13) % sensitivity, (51.00-88.90) % AUC, and (49.76-88.24) % ACC on whole dataset, while all eight techniques achieve (36.54-77.88) % specificity, (50.00-75.00) % sensitivity, (51.00-76.40) % AUC, and (25.00-77.78) % ACC on random sample dataset. We also created a Meta classifier (CSTJ48) that combines FATHMM, iFish, and Mutation Assessor. It registers 96.33% specificity, 86.07% sensitivity, 91.20% AUC, and 91.89 ACC. By comparing the results, it's clear that FATHMM gives the highest performance over the seven individual techniques, where it achieves 83.75% and 77.88% specificity, 94.13%, and 75.00% sensitivity, 88.90% and 76.40% AUC, and 88.24% and 77.78% ACC on whole and random sample dataset, respectively. Also, the launched Meta classifier (CSTJ48) is outperforming over all the eight individual tools that compared here.

A review study: Computational techniques for expecting the impact of non-synonymous single nucleotide variants in human diseases.

Non-Synonymous Single-Nucleotide Variants (nsSNVs) and mutations can create a diversity effect on proteins as changing genotype and phenotype, which interrupts its stability. The alterations in the protein stability may cause diseases like cancer. Discovering of nsSNVs and mutations can be a useful tool for diagnosing the disease at a beginning stage. Many studies introduced the various predicting singular and consensus tools that based on different Machine Learning Techniques (MLTs) using diverse datasets. Therefore, we introduce the current comprehensive review of the most popular and recent unique tools that predict pathogenic variations and Meta-tool that merge some of them for enhancing their predictive power. Also, we scanned the several types computational techniques in the state-of-the-art and methods for predicting the effect both of coding and noncoding variants. We then displayed, the protein stability predictors. We offer the details of the most common benchmark database for variations including the main predictive features used by the different methods. Finally, we address the most common fundamental criteria for performance assessment of predictive tools. This review is targeted at bioinformaticians attentive in the characterization of regulatory variants, geneticists, molecular biologists attentive in understanding more about the nature and effective role of such variants from a functional point of views, and clinicians who may hope to learn about variants in human associated with a specific disease and find out what to do next to uncover how they impact on the underlying mechanisms.

Post-operative nausea and vomiting in patients undergoing day-case surgery: an international, observational study.

Post-operative nausea and vomiting (PONV) are complications of surgical procedures, and are of particular relevance in the day-case setting. The aim of this study was to examine the incidence and impact of PONV before and after discharge from day surgery units. Patients recorded the incidence, severity and impact of PONV for 5 days following surgery. The incidence of PONV in the 561 eligible patients was 17% upon waking, 14% travelling home and 3% by the 5th day post-surgery. PONV was most common in gastrointestinal, obstetric and gynaecological surgery. Although freedom from pain and PONV are requirements for discharge after ambulatory surgery, PONV is still a problem post-discharge.

"Effects of Enterobius vermicularis infection on intelligence quotient (I.Q) and anthropometric measurements of Egyptian rural children".

Two hundred and thirty nine children (114 boys and 125 girls, aged 6-12 years, infected with Enterobius vermicularis worm (E.v.) were selected from 637 originally examined children (329 boys and 308 girls)., derived from El-Katta village, Giza Governorate. The diagnosis was made according to history, physical examination, urine and stools examination, as well as peri-anal swab. The physical growth of these children was investigated by taking some anthropometric measurements which included body weight, standing height, head circumference, upper arm circumf., and triceps skinfold thickness. I.Q. was determined by using Goodenough "draw-a-ma" test. Blood hemoglobin concentration was also determined using a spectrophotometric method. The prevalence of Enterobius vermicularis among our original sample was 43.8%. Mean I.Q. of Enterobius vermicularis infected children was statistically lower than that of their non-infected peers (t = 2.02, P = 0.04), while the non-infected peers (t = 2.42, P = 0.02). Infected male children showed significantly lower I.Q. than infected females (t = 2.02, P = 0.04) while the non infected children showed no sex difference. However physical growth and hemoglobin concentration of Enterobius vermicularis infected children were not statistically different from those of the non-infected control peers, in all age and sex subgroups.