Energy Content of Colliding Plane Waves using Approximate Noether Symmetries

This paper is devoted to study the energy content of colliding plane waves using approximate Noether symmetries. For this purpose, we use approximate Lie symmetry method of Lagrangian for differential equations. We formulate the first-order perturbed Lagrangian for colliding plane electromagnetic and gravitational waves. It is shown that in both cases, there does not existComment: 18 pages, accepted for publication in Brazilian J Physic

Mobile Applications and Wearables for Chronic Respiratory Disease Monitoring

Mobile health (mHealth) has tremendous potential to benefit patients, providers, and the entire healthcare system. Benefits for patients to adopt mHealth include more effective access to health providers, reduced costs of care, and better health control. For physicians and the healthcare system, reasons to embrace mHealth are enhanced health outcomes, facilitated access to patients for care, and decreased time required for administrative tasks. Currently, some mobile apps and wearables dedicated to respiratory health provide medical education and messaging services, enable diary logs, aid with disease self-management, and include educational games. Major challenges for mHealth to be widely adopted include lack of studies demonstrating effectiveness, limited access to technology by all patients, decreased adoption over time, high costs, and data privacy concerns

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

On-line immunoaffinity solid-phase extraction capillary electrophoresis-mass spectrometry for the analysis of serum transthyretin

The analysis of low abundant proteins in biological fluids by capillary electrophoresis (CE) is particularly problematic due to the typically poor concentration limits of detection of microscale separation techniques. Another important issue is sample matrix complexity that requires an appropriate cleanup. Here, we describe an on-line immunoaffinity solid-phase extraction capillary electrophoresis-mass spectrometry (IA-SPE-CE-MS) method for the immunoextraction, preconcentration, separation, detection, and characterization of serum transthyretin (TTR). TTR is a protein biomarker related to diverse types of amyloidosis, such as familial amyloidotic polyneuropathy type I (FAP-I), which is the most common hereditary systemic amyloidosis