A Comparison of Automatic Labelling Approaches for Sentiment Analysis

Labelling a large quantity of social media data for the task of supervised machine learning is not only time-consuming but also difficult and expensive. On the other hand, the accuracy of supervised machine learning models is strongly related to the quality of the labelled data on which they train, and automatic sentiment labelling techniques could reduce the time and cost of human labelling. We have compared three automatic sentiment labelling techniques: TextBlob, Vader, and Afinn to assign sentiments to tweets without any human assistance. We compare three scenarios: one uses training and testing datasets with existing ground truth labels; the second experiment uses automatic labels as training and testing datasets; and the third experiment uses three automatic labelling techniques to label the training dataset and uses the ground truth labels for testing. The experiments were evaluated on two Twitter datasets: SemEval-2013 (DS-1) and SemEval-2016 (DS-2). Results show that the Afinn labelling technique obtains the highest accuracy of 80.17% (DS-1) and 80.05% (DS-2) using a BiLSTM deep learning model. These findings imply that automatic text labelling could provide significant benefits, and suggest a feasible alternative to the time and cost of human labelling efforts.Comment: 12 pages 3 figure, 11th International Conference on Data Science, Technology and Applications, ISBN 978-989-758-583-8, ISSN 2184-285X, pages 312-31

Impact of Chromogranin A deficiency on catecholamine storage, catecholamine granule morphology and chromaffin cell energy metabolism in vivo

Chromogranin A (CgA) is a prohormone and granulogenic factor in neuroendocrine tissues with a regulated secretory pathway. The impact of CgA depletion on secretory granule formation has been previously demonstrated in cell culture. However, studies linking the structural effects of CgA deficiency with secretory performance and cell metabolism in the adrenomedullary chromaffin cells in vivo have not previously been reported. Adrenomedullary content of the secreted adrenal catecholamines norepinephrine (NE) and epinephrine (EPI) was decreased 30–40 % in Chga-KO mice. Quantification of NE and EPI-storing dense core (DC) vesicles (DCV) revealed decreased DCV numbers in chromaffin cells in Chga-KO mice. For both cell types, the DCV diameter in Chga-KO mice was less (100–200 nm) than in WT mice (200–350 nm). The volume density of the vesicle and vesicle number was also lower in Chga-KO mice. Chga-KO mice showed an ~47 % increase in DCV/DC ratio, implying vesicle swelling due to increased osmotically active free catecholamines. Upon challenge with 2 U/kg insulin, there was a diminution in adrenomedullary EPI, no change in NE and a very large increase in the EPI and NE precursor dopamine (DA), consistent with increased catecholamine biosynthesis during prolonged secretion. We found dilated mitochondrial cristae, endoplasmic reticulum and Golgi complex, as well as increased synaptic mitochondria, synaptic vesicles and glycogen granules in Chga-KO mice compared to WT mice, suggesting that decreased granulogenesis and catecholamine storage in CgA-deficient mouse adrenal medulla is compensated by increased VMAT-dependent catecholamine update into storage vesicles, at the expense of enhanced energy expenditure by the chromaffin cell

Salivary Metabolomics for Oral Precancerous Lesions: A Comprehensive Narrative Review

Oral submucous fibrosis (OSMF) is a chronic, potentially malignant disorder of the oral cavity, primarily associated with the consumption of areca nut products and other risk factors. Early and accurate diagnosis of OSMF is crucial to prevent its progression to oral cancer. In recent years, the field of metabolomics has gained momentum as a promising approach for disease detection and monitoring. Salivary metabolomics, a non-invasive and easily accessible diagnostic tool, has shown potential in identifying biomarkers associated with various oral diseases, including OSMF. This review synthesizes current literature on the application of salivary metabolomics in the context of OSMF detection. The review encompasses a comprehensive analysis of studies conducted over the past decade, highlighting advancements in analytical techniques, metabolomic profiling, and identified biomarkers linked to OSMF progression. The primary objective of this review is to provide a critical assessment of the feasibility and reliability of salivary metabolomics as a diagnostic tool for OSMF, along with its potential to differentiate OSMF from other oral disorders. In conclusion, salivary metabolomics holds great promise in revolutionizing OSMF detection through the identification of reliable biomarkers and the development of robust diagnostic models. However, challenges such as sample variability, validation of biomarkers, and standardization need to be addressed before its widespread clinical implementation. This review contributes to a comprehensive understanding of the current status, challenges, and future directions of salivary metabolomics in the realm of OSMF detection, emphasizing its potential impact on early intervention and improved patient outcomes

Muscle injury and impaired function, and insulin resistance in Chromogranin A knockout mice

Chromogranin A (CgA) is widely expressed in endocrine and neuroendocrine tissues as well as in the central nervous system. We observed CgA expression (mRNA and protein) in the gastrocnemius (GAS) muscle and found that performance of CgA-deficient Chga-KO mice in treadmill exercise was impaired. Supplementation with CgA in Chga-KO mice restored exercise ability suggesting a novel role for endogenous CgA in skeletal muscle function. Chga-KO mice display (i) lack of exercise-induced stimulation of pAKT, pTBC1D1 and phospho-p38 kinase signaling, (ii) loss of GAS muscle mass, (iii) extensive formation of tubular aggregates (TA), (iv) disorganized cristae architecture in mitochondria, (v) increased expression of the inflammatory cytokines Tnfα, Il6 and Ifnɣ, and fibrosis. The impaired maximum running speed and endurance in the treadmill exercise in Chga-KO mice correlated with decreased glucose uptake and glycolysis, defects in glucose oxidation and decreased mitochondrial cytochrome C oxidase activity. The lack of adaptation to endurance training correlated with the lack of stimulation of p38MAPK that is known to mediate the response to tissue damage. Since CgA sorts proteins to the regulated secretory pathway, we speculate that lack of CgA could cause misfolding of membrane proteins inducing aggregation of sarcoplasmic reticulum (SR) membranes and formation of tubular aggregates that is observed in Chga-KO mice. In conclusion, CgA deficiency renders the muscle energy deficient, impairs performance in treadmill exercise and prevents regeneration after exercise-induced tissue damage

Muscle injury and impaired function, and insulin resistance in Chromogranin A knockout mice

Chromogranin A (CgA) is widely expressed in endocrine and neuroendocrine tissues as well as in the central nervous system. We observed CgA expression (mRNA and protein) in the gastrocnemius (GAS) muscle and found that performance of CgA-deficient Chga-KO mice in treadmill exercise was impaired. Supplementation with CgA in Chga-KO mice restored exercise ability suggesting a novel role for endogenous CgA in skeletal muscle function. Chga-KO mice display (i) lack of exercise-induced stimulation of pAKT, pTBC1D1 and phospho-p38 kinase signaling, (ii) loss of GAS muscle mass, (iii) extensive formation of tubular aggregates (TA), (iv) disorganized cristae architecture in mitochondria, (v) increased expression of the inflammatory cytokines Tnfα, Il6 and Ifnɣ, and fibrosis. The impaired maximum running speed and endurance in the treadmill exercise in Chga-KO mice correlated with decreased glucose uptake and glycolysis, defects in glucose oxidation and decreased mitochondrial cytochrome C oxidase activity. The lack of adaptation to endurance training correlated with the lack of stimulation of p38MAPK that is known to mediate the response to tissue damage. Since CgA sorts proteins to the regulated secretory pathway, we speculate that lack of CgA could cause misfolding of membrane proteins inducing aggregation of sarcoplasmic reticulum (SR) membranes and formation of tubular aggregates that is observed in Chga-KO mice. In conclusion, CgA deficiency renders the muscle energy deficient, impairs performance in treadmill exercise and prevents regeneration after exercise-induced tissue damage