The Apple Watch for monitoring mental health–related physiological symptoms : literature review

Background: An anticipated surge in mental health service demand related to COVID-19 has motivated the use of novel methods of care to meet demand, given workforce limitations. Digital health technologies in the form of self-tracking technology have been identified as a potential avenue, provided sufficient evidence exists to support their effectiveness in mental health contexts. Objective: This literature review aims to identify current and potential physiological or physiologically related monitoring capabilities of the Apple Watch relevant to mental health monitoring and examine the accuracy and validation status of these measures and their implications for mental health treatment. Methods: A literature review was conducted from June 2021 to July 2021 of both published and gray literature pertaining to the Apple Watch, mental health, and physiology. The literature review identified studies validating the sensor capabilities of the Apple Watch. Results: A total of 5583 paper titles were identified, with 115 (2.06%) reviewed in full. Of these 115 papers, 19 (16.5%) were related to Apple Watch validation or comparison studies. Most studies showed that the Apple Watch could measure heart rate acceptably with increased errors in case of movement. Accurate energy expenditure measurements are difficult for most wearables, with the Apple Watch generally providing the best results compared with peers, despite overestimation. Heart rate variability measurements were found to have gaps in data but were able to detect mild mental stress. Activity monitoring with step counting showed good agreement, although wheelchair use was found to be prone to overestimation and poor performance on overground tasks. Atrial fibrillation detection showed mixed results, in part because of a high inconclusive result rate, but may be useful for ongoing monitoring. No studies recorded validation of the Sleep app feature; however, accelerometer-based sleep monitoring showed high accuracy and sensitivity in detecting sleep. Conclusions: The results are encouraging regarding the application of the Apple Watch in mental health, particularly as heart rate variability is a key indicator of changes in both physical and emotional states. Particular benefits may be derived through avoidance of recall bias and collection of supporting ecological context data. However, a lack of methodologically robust and replicated evidence of user benefit, a supportive health economic analysis, and concerns about personal health information remain key factors that must be addressed to enable broader uptake

Rapid differentiation of cystic fibrosis-related bacteria via reagentless atmospheric pressure photoionisation mass spectrometry.

Breath analysis is an area of significant interest in medical research as it allows for non-invasive sampling with exceptional potential for disease monitoring and diagnosis. Volatile organic compounds (VOCs) found in breath can offer critical insight into a person's lifestyle and/or disease/health state. To this end, the development of a rapid, sensitive, cost-effective and potentially portable method for the detection of key compounds in breath would mark a significant advancement. Herein, we have designed, built and tested a novel reagent-less atmospheric pressure photoionisation (APPI) source, coupled with mass spectrometry (MS), utilising a bespoke bias electrode within a custom 3D printed sampling chamber for direct analysis of VOCs. Optimal APPI-MS conditions were identified, including bias voltage, cone voltage and vaporisation temperature. Calibration curves were produced for ethanol, acetone, 2-butanone, ethyl acetate and eucalyptol, yielding R2 > 0.99 and limits of detection < 10 pg. As a pre-clinical proof of concept, this method was applied to bacterial headspace samples of Escherichia coli (EC), Pseudomonas aeruginosa (PSA) and Staphylococcus aureus (SA) collected in 1 L Tedlar bags. In particular, PSA and SA are commonly associated with lung infection in cystic fibrosis patients. The headspace samples were classified using principal component analysis with 86.9% of the total variance across the first three components and yielding 100% classification in a blind-sample study. All experiments conducted with the novel APPI arrangement were carried out directly in real-time with low-resolution MS, which opens up exciting possibilities in the future for on-site (e.g., in the clinic) analysis with a portable system

Direct and Reagentless Atmospheric Pressure Photoionisation Mass Spectrometry: Rapid and Accurate Differentiation of Cystic Fibrosis Related Bacteria by Monitoring VOCs

Abstract Breath analysis is an area of significant interest in medical research as it allows for non-invasive sampling with exceptional potential for disease monitoring and diagnosis. Volatile organic compounds (VOCs) found in breath can offer critical insight into a person’s lifestyle and/or disease/health state. To this end, the development of a rapid, sensitive, cost-effective and potentially portable method for the detection of key compounds in breath would mark a significant advancement. Herein we have designed, built and tested a novel reagent-less atmospheric pressure photoionisation (APPI) source, coupled with mass spectrometry (MS), utilising a bespoke bias electrode within a custom 3D printed sampling chamber for direct analysis of VOCs. Optimal APPI-MS conditions were identified including bias voltage, cone voltage and vaporisation temperature. Calibration curves were produced for ethanol, acetone, 2-butanone, ethyl acetate and eucalyptol, yielding R2 &gt; 0.99 and limits of detection &lt; 10 pg. As a pre-clinical proof of concept, this method was applied to bacterial headspace samples of Escherichia coli (EC), Pseudomonas aeruginosa (PSA) and Staphylococcus aureus (SA) collected in 1 L Tedlar bags. In particular, PSA and SA are commonly associated with lung infection in cystic fibrosis patients. The headspace samples were classified using principal component analysis with 86.9% of the total variance across the first three components and yielding 100% classification in a blind-sample study. All experiments conducted with the novel APPI arrangement were carried out directly in real-time with low-resolution MS, which opens up exciting possibilities in the future for on-site (e.g., in the clinic) analysis with a portable system.</jats:p

Unexpected removal of the most neutral cationic pharmaceutical in river waters

Contamination of surface waters by pharmaceuticals is now widespread. There are few data on their environmental behaviour, particularly for those which are cationic at typical surface water pH. As the external surfaces of bacterio-plankton cells are hydrophilic with a net negative charge, it was anticipated that bacterio-plankton in surface-waters would preferentially remove the most extensively-ionised cation at a given pH. To test this hypothesis, the persistence of four, widely-used, cationic pharmaceuticals, chloroquine, quinine, fluphenazine and levamisole, was assessed in batch microcosms, comprising water and bacterio-plankton, to which pharmaceuticals were added and incubated for 21 days. Results show that levamisole concentrations decreased by 19 % in microcosms containing bacterio-plankton, and by 13 % in a parallel microcosm containing tripeptide as a priming agent. In contrast to levamisole, concentrations of quinine, chloroquine and fluphenazine were unchanged over 21 days in microcosms containing bacterio-plankton. At the river-water pH, levamisole is 28 % cationic, while quinine is 91–98 % cationic, chloroquine 99 % cationic and fluphenazine 72–86 % cationic. Thus, the most neutral compound, levamisole, showed greatest removal, contradicting the expected bacterio-plankton preference for ionised molecules. However, levamisole was the most hydrophilic molecule, based on its octanol–water solubility coefficient (K ow). Overall, the pattern of pharmaceutical behaviour within the incubations did not reflect the relative hydrophilicity of the pharmaceuticals predicted by the octanol–water distribution coefficient, D ow, suggesting that improved predictive power, with respect to modelling bioaccumulation, may be needed to develop robust environmental risk assessments for cationic pharmaceuticals

The cost of lost productivity due to premature mortality associated with COVID-19: a Pan-European study

Background Economic cost estimates have the potential to provide a valuable alternative perspective on the COVID-19 burden. We estimate the premature mortality productivity costs associated with COVID-19 across Europe. Methods We calculated excess deaths between the date the cumulative total of COVID-19 deaths reached 10 in a country to 15th May 2020 for nine countries (Belgium, France, Germany, Italy, The Netherlands, Portugal, Spain, Sweden and Switzerland). Gender- and age-specific excess deaths and Years of Potential Productive Life Lost (YPPLL) between 30 and 74 years were calculated and converted into premature mortality productivity costs €2020 for paid and unpaid work using the Human Capital and the Proxy Good Approaches. Costs were discounted at 3.5%. Results Total estimated excess deaths across the nine countries were 18,614 (77% in men) and YPPLL were 134,190 (77% male). Total paid premature mortality costs were €1.07 billion (87% male) with Spain (€0.35 billion, 33.0% of total), Italy (€0.22 billion; 20.6%) and The Netherlands (€0.19 billion; 17.5%) ranking highest. Total paid and unpaid premature mortality costs were €2.89 billion (77% male). Premature mortality costs per death ranged between €40,382 (France) and €350,325 (Switzerland). Spain experienced the highest premature mortality cost as a proportion of Gross Domestic Product (0.11%). Conclusion Even in the initial period of the pandemic in Europe, COVID-19-related premature mortality costs were significant across Europe. We provide policy makers and researchers with a valuable alternative perspective on the burden of the virus and highlight potential economic savings that may be accrued by applying timely public health measures

Effects of soil improvement treatments on bacterial community structure and soil processes in an upland grassland soil

Temporal temperature gradient electrophoresis (TTGE) analysis of 16S rRNA gene fragments amplified with primers selective for eubacteria and β-proteobacterial ammonia-oxidising bacteria (AOB) was used to analyse changes in bacterial and AOB community profiles of an upland pasture following soil improvement treatments (addition of sewage sludge and/or lime). Community structure was compared with changes in activity assessed by laboratory measurements of basal respiration and ammonia oxidation potentials, and with measurements of treatment- and time-related changes in soil characteristics. The predominant bacterial populations had a high degree of similarity under all treatment regimens, which was most pronounced early in the growing season. Most of the differences that occurred between soil samples with time could be accounted for by spatial and temporal variation; however, analysis of variance and cluster analysis of similarities between 16S rDNA TTGE profiles indicated that soil improvement treatments exerted some effect on community structure. Lime application had the greatest influence. The impact of soil improvement treatments on autotrophic ammonia oxidation was significant and sustained, especially in soils which had received sewage sludge and lime treatments in combination. However, despite obvious changes in soil characteristics, e.g. pH and soil nitrogen, increasing heterogeneity in the AOB community structure over time obscured the treatment effects observed at the beginning of the experiment. Nevertheless, time series analysis of AOB TTGE profiles indicated that the AOB community in improved soils was more dynamic than in control soils where populations were found to be relatively stable. These observations suggest that the AOB populations exhibited a degree of functional redundancy

Anoxic biodegradation of isosaccharinic acids at alkaline pH by natural microbial communities

10.1371/journal.pone.0137682PLoS ONE109e013768