A critical look at studies applying over-sampling on the TPEHGDB dataset

Preterm birth is the leading cause of death among young children and has a large prevalence globally. Machine learning models, based on features extracted from clinical sources such as electronic patient files, yield promising results. In this study, we review similar studies that constructed predictive models based on a publicly available dataset, called the Term-Preterm EHG Database (TPEHGDB), which contains electrohysterogram signals on top of clinical data. These studies often report near-perfect prediction results, by applying over-sampling as a means of data augmentation. We reconstruct these results to show that they can only be achieved when data augmentation is applied on the entire dataset prior to partitioning into training and testing set. This results in (i) samples that are highly correlated to data points from the test set are introduced and added to the training set, and (ii) artificial samples that are highly correlated to points from the training set being added to the test set. Many previously reported results therefore carry little meaning in terms of the actual effectiveness of the model in making predictions on unseen data in a real-world setting. After focusing on the danger of applying over-sampling strategies before data partitioning, we present a realistic baseline for the TPEHGDB dataset and show how the predictive performance and clinical use can be improved by incorporating features from electrohysterogram sensors and by applying over-sampling on the training set

Extremism Arabic Text Detection using Rough Set Theory: Designing a Novel Approach

The linguistics related research and particularly, sentiment analysis using data-driven approaches, has been growing in recent years. However, the large number of users and excessive amount of information available on social media, make it difficult to detect extremism text on these platforms. The literature revealed a plethora of research studies focusing the sentiment analysis primarily, for English texts, however, very limited studies are available concerning the Arabic language which is the 4th mostly spoken language in the world. We first time in this study, propose a text detection mechanism for extremism orientations distinction in Arabic language, to improve the comprehension of subjective phrases. The study introduces a novel method based on Rough Set theory to enhance the accuracy of selected models and recognize text orientation reliably. Experimental outcomes indicate that the proposed method outperforms existing algorithms by contributing towards feature discriminations. Our method achieved 90.853%, 81.707% and 71.951% accuracies for unigram, bigram, and trigram representations, respectively. This study significantly contributes to the limited research in the field of machine learning and linguistics in Arabic language

The conceptualisation and measurement of DSM-5 Internet Gaming Disorder: the development of the IGD-20 Test

Background: Over the last decade, there has been growing concern about ‘gaming addiction’ and its widely documented detrimental impacts on a minority of individuals that play excessively. The latest (fifth) edition of the American Psychiatric Association’s Diagnostic and Statistical Manual of Mental Disorders (DSM-5) included nine criteria for the potential diagnosis of Internet Gaming Disorder (IGD) and noted that it was a condition that warranted further empirical study. Aim: The main aim of this study was to develop a valid and reliable standardised psychometrically robust tool in addition to providing empirically supported cut-off points. Methods: A sample of 1003 gamers (85.2% males; mean age 26 years) from 57 different countries were recruited via online gaming forums. Validity was assessed by confirmatory factor analysis (CFA), criterion-related validity, and concurrent validity. Latent profile analysis was also carried to distinguish disordered gamers from non-disordered gamers. Sensitivity and specificity analyses were performed to determine an empirical cut-off for the test. Results: The CFA confirmed the viability of IGD-20 Test with a six-factor structure (salience, mood modification, tolerance, withdrawal, conflict and relapse) for the assessment of IGD according to the nine criteria from DSM-5. The IGD-20 Test proved to be valid and reliable. According to the latent profile analysis, 5.3% of the total participants were classed as disordered gamers. Additionally, an optimal empirical cut-off of 71 points (out of 100) seemed to be adequate according to the sensitivity and specificity analyses carried

Biomarker Changes Associated with Tuberculin Skin Test (TST) Conversion: A Two-Year Longitudinal Follow-Up Study in Exposed Household Contacts

Background:A high prevalence (50-80%) of Tuberculin Skin Test Positivity (TST+ \u3eor=10 mm indurations) has been reported in TB endemic countries. This pool forms a huge reservoir for new incident TB cases. However, immune biomarkers associated with TST conversion are largely unknown. The objective of this study was to identify immune biomarkers associated with TST conversion after acute Mycobacterium tuberculosis (MTB) Methodology/Principal Findings:A 24 month longitudinal study was carried out in a recently MTB exposed cohort of household contacts (HC = 93, 75% TST+). Control group consisted of unexposed community controls (EC = 59, 46%TST+). Cytokine secretion was assessed in whole blood cultures in response to either mycobacterial culture filtrate (CF) antigens or mitogens (PHA or LPS) using Elisa methodology. Compared to the EC group, the HC group at recruitment (Kruskal-Wallis Test) showed significantly suppressed IFN gamma (p = 0.0001), raised IL-10 (p = 0.0005) and raised TNF alpha (p = 0.001) in response to CF irrespective of their TST status. Seventeen TST-HC, showed TST conversion when retested at 6 months. Post TST conversion (paired t tests) significant increases were observed for CF induced IFN gamma (p = 0.038), IL-10 (p = 0.001) and IL-6 (p = 0.006). Cytokine responses were also compared in the exposed HC group with either recent infection [(TST converters (N = 17)] or previous infection [TST+ HC (N = 54)] at 0, 6, 12 and 24 months using ANOVA on repeated measures. Significant differences between the exposed HC groups were noted only at 6 months. CF induced IFN gamma was higher in previously infected HC group (p = 0.038) while IL-10 was higher in recently infected HC group (p = 0.041). Mitogen induced cytokine secretion showed similar differences for different group.Conclusions/Significance:Our results suggest that TST conversion is associated with early increases in IFN gamma and IL-10 responses and precedes latency by several months post exposure

Predicting Physical Time Series Using Dynamic Ridge Polynomial Neural Networks

Forecasting naturally occurring phenomena is a common problem in many domains of science, and this has been addressed and investigated by many scientists. The importance of time series prediction stems from the fact that it has wide range of applications, including control systems, engineering processes, environmental systems and economics. From the knowledge of some aspects of the previous behaviour of the system, the aim of the prediction process is to determine or predict its future behaviour. In this paper, we consider a novel application of a higher order polynomial neural network architecture called Dynamic Ridge Polynomial Neural Network that combines the properties of higher order and recurrent neural networks for the prediction of physical time series. In this study, four types of signals have been used, which are; The Lorenz attractor, mean value of the AE index, sunspot number, and heat wave temperature. The simulation results showed good improvements in terms of the signal to noise ratio in comparison to a number of higher order and feedforward neural networks in comparison to the benchmarked techniques

Is there a role for melatonin in fibromyalgia?

Fibromyalgia, characterised by persistent pain, fatigue, sleep disturbance and cognitive dysfunction, is a central sensitivity syndrome that also involves abnormality in peripheral generators and in the hypothalamic pituitary adrenal axis. Heterogeneity of clinical expression of fibromyalgia with a multifactorial aetiology has made the development of effective therapeutic strategies challenging. Physiological properties of the neurohormone melatonin appear related to the symptom profile exhibited by patients with fibromyalgia and thus disturbance of it’s production would be compatible with the pathophysiology. Altered levels of melatonin have been observed in patients with fibromyalgia which are associated with lower secretion during dark hours and higher secretion during daytime. However, inconsistencies of available clinical evidence limit conclusion of a relationship between levels of melatonin and symptom profiles in patients with fibromyalgia. Administration of melatonin to patients with fibromyalgia has demonstrated suppression of many symptoms and an improved quality of life consistent with benefit as a therapy for the management of this condition. Further studies with larger samples, however, are required to explore the potential role of melatonin in the pathophysiology of fibromyalgia and determine the optimal dosing regimen of melatonin for the management of fibromyalgia

DNA damage by lipid peroxidation products: implications in cancer, inflammation and autoimmunity

Oxidative stress and lipid peroxidation (LPO) induced by inflammation, excess metal storage and excess caloric intake cause generalized DNA damage, producing genotoxic and mutagenic effects. The consequent deregulation of cell homeostasis is implicated in the pathogenesis of a number of malignancies and degenerative diseases. Reactive aldehydes produced by LPO, such as malondialdehyde, acrolein, crotonaldehyde and 4-hydroxy-2-nonenal, react with DNA bases, generating promutagenic exocyclic DNA adducts, which likely contribute to the mutagenic and carcinogenic effects associated with oxidative stress-induced LPO. However, reactive aldehydes, when added to tumor cells, can exert an anticancerous effect. They act, analogously to other chemotherapeutic drugs, by forming DNA adducts and, in this way, they drive the tumor cells toward apoptosis. The aldehyde-DNA adducts, which can be observed during inflammation, play an important role by inducing epigenetic changes which, in turn, can modulate the inflammatory process. The pathogenic role of the adducts formed by the products of LPO with biological macromolecules in the breaking of immunological tolerance to self antigens and in the development of autoimmunity has been supported by a wealth of evidence. The instrumental role of the adducts of reactive LPO products with self protein antigens in the sensitization of autoreactive cells to the respective unmodified proteins and in the intermolecular spreading of the autoimmune responses to aldehyde-modified and native DNA is well documented. In contrast, further investigation is required in order to establish whether the formation of adducts of LPO products with DNA might incite substantial immune responsivity and might be instrumental for the spreading of the immunological responses from aldehyde-modified DNA to native DNA and similarly modified, unmodified and/or structurally analogous self protein antigens, thus leading to autoimmunity

Utilisation of an operative difficulty grading scale for laparoscopic cholecystectomy

Background A reliable system for grading operative difficulty of laparoscopic cholecystectomy would standardise description of findings and reporting of outcomes. The aim of this study was to validate a difficulty grading system (Nassar scale), testing its applicability and consistency in two large prospective datasets. Methods Patient and disease-related variables and 30-day outcomes were identified in two prospective cholecystectomy databases: the multi-centre prospective cohort of 8820 patients from the recent CholeS Study and the single-surgeon series containing 4089 patients. Operative data and patient outcomes were correlated with Nassar operative difficultly scale, using Kendall’s tau for dichotomous variables, or Jonckheere–Terpstra tests for continuous variables. A ROC curve analysis was performed, to quantify the predictive accuracy of the scale for each outcome, with continuous outcomes dichotomised, prior to analysis. Results A higher operative difficulty grade was consistently associated with worse outcomes for the patients in both the reference and CholeS cohorts. The median length of stay increased from 0 to 4 days, and the 30-day complication rate from 7.6 to 24.4% as the difficulty grade increased from 1 to 4/5 (both p < 0.001). In the CholeS cohort, a higher difficulty grade was found to be most strongly associated with conversion to open and 30-day mortality (AUROC = 0.903, 0.822, respectively). On multivariable analysis, the Nassar operative difficultly scale was found to be a significant independent predictor of operative duration, conversion to open surgery, 30-day complications and 30-day reintervention (all p < 0.001). Conclusion We have shown that an operative difficulty scale can standardise the description of operative findings by multiple grades of surgeons to facilitate audit, training assessment and research. It provides a tool for reporting operative findings, disease severity and technical difficulty and can be utilised in future research to reliably compare outcomes according to case mix and intra-operative difficulty

In Vivo and In Vitro Effects of Antituberculosis Treatment on Mycobacterial Interferon-γ T Cell Response

Background: In recent years, the impact of antituberculous treatment on interferon (IFN)-c response to Mycobacterium tuberculosis antigens has been widely investigated, but the results have been controversial. The objective of the present study was: i) to evaluate longitudinal changes of IFN-c response to M. tuberculosis-specific antigens in TB patients during antituberculous treatment by using the QuantiFERON-TB Gold (QFT-G) assay; ii) to compare the differences in T-cell response after a short or prolonged period of stimulation with mycobacterial antigens; iii) to assess the CD4+ and CD8+ T cells with effector/memory and central/memory phenotype; iv) to investigate the direct in vitro effects of antituberculous drugs on the secretion of IFN-c. Principal Findings: 38 TB patients was evaluated at baseline and at month 2 and 4 of treatment and at month 6 (treatment completion). 27 (71%) patients had a QFT-G reversion (positive to negative) at the end of therapy, while 11 (29%) TB patients remained QFT-G positive at the end of therapy. Among the 11 patients with persistent positive QFT-G results, six had a complete response to the treatment, while the remaining 5 patients did not have a resolution of the disease. All 27 patients who became QFT-G negative had a complete clinical and microbiological recovery of the TB disease. In these patients the release of IFN-c is absent even after a prolonged 6-day incubation with both ESAT-6 and CFP-10 antigens and the percentage of effector/memory T-cells phenotype was markedly lower than subjects with persistent positive QFT-G results. The in vitro study showed that antituberculous drugs did not exert any inhibitory effect on IFN-c production within the range of therapeutically achievable concentrations. Conclusions: The present study suggests that the decrease in the M. tuberculosis-specific T cells responses following successful anti-TB therapy may have a clinical value as a supplemental tool for the monitoring of the efficacy of pharmacologic intervention for active TB. In addition, the antituberculous drugs do not have any direct down-regulatory effect on the specific IFN-c response