| 1. |
- Ismail, M, et al.
(författare)
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Levels and Potential Health Hazards of Chlorinated Pesticidesin Surface Water Samples of Charsadda Area of Pakistan Using SPME-GC-ECD Technique
- 2021
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Ingår i: Water S.A.. - : MDPI. - 0378-4738 .- 1816-7950. ; 13, s. 1-14
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Tidskriftsartikel (refereegranskat)abstract
- In the present study, we determined the levels of chlorinated pesticide residues in surfacewater samples collected from the Charsadda district (KPK, Pakistan). SPME-GC-ECD with COMBIPAL CTC autosampler was used for extraction and analysis of 20 organochlorine pesticides in thecollected water samples. For maximum efficiency of the SPME procedure, several parameters werestudied, including the extraction and desorption time of the fiber, solution pH, agitation of samples,and stirring speed, etc. This method showed good liner response, with R2 values in the range of0.9887 to 0.9999 for all pesticides. This method also provided good percent recoveries at 1 µg L−1(87.5to 106.0%) and at 2 µg L−1(88.5 to 109.2%). Lower limits of detection for all 20 chlorinated pesticideswere found to be lower than their maximum permissible contamination levels. Approximately 50%of the surface water samples collected from the Charsadda district were found to be contaminatedwith the pesticides γ-BHC, heptachlor, aldrin and dieldrin, with maximum concentrations of 0.023,0.108, 0.014 and 0.013 µg L−1, respectively. For adults and children, the cancer risk from water dueto contamination by various pesticides ranged from 0 to 33.29 × 10−6. The non-carcinogenic riskfrom each pollutant in the water samples of the Charsadda district was found to be in the order ofheptachlor > aldrin > dieldrin > γ-BHC. However, the pesticides α-BHC, β-BHC, heptachlor epoxide,chlordane, endrin, 4,40-DDD, endrin ketone, 4,40-DDT, endosulfan sulfate and methoxychlor werenot detected in any of the surface water samples of investigated in the present study.
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| 2. |
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| 3. |
- Micheletti, Chiara, et al.
(författare)
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Multimodal and Multiscale Characterization of the Bone-Bacteria Interface in a Case of Medication-Related Osteonecrosis of the Jaw
- 2022
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Ingår i: JBMR Plus. - : Wiley. - 2473-4039. ; 6:12
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Tidskriftsartikel (refereegranskat)abstract
- Medication-related osteonecrosis of the jaw (MRONJ) is a known side effect of bisphosphonates (BPs). Although bacterial infection is usually present, the etiology of MRONJ remains unknown. Here we apply a multimodal and multiscale (micro-to-nano) characterization approach to investigate the interface between necrotic bone and bacteria in MRONJ. A non-necrotic bone sample was used as control. Both necrotic and non-necrotic bone samples were collected from the jaw of a female individual affected by MRONJ after using BPs for 23 years. For the first time, resin cast etching was used to expose bacteria at the necrotic site. The bone-bacteria interface was also resolved at the nanoscale by scanning transmission electron microscopy (STEM). Nanosized particulates, likely corresponding to degraded bone mineral, were often noted in close proximity to or enclosed by the bacteria. STEM also revealed that the bone-bacteria interface is composed of a hypermineralized front fading into a highly disordered region, with decreasing content of calcium and phosphorus, as assessed by electron energy loss spectroscopy (EELS). This, combined with the variation in calcium, phosphorus, and carbon across the necrotic bone-bacteria interface evaluated by scanning electron microscopy (SEM)-energy dispersive X-ray spectroscopy (EDX) and the lower mineral-to-matrix ratio measured by micro-Raman spectroscopy in necrotic bone, indicates the absence of a mineralization front in MRONJ. It appears that the bone-bacteria interface originates not only from uncontrolled mineralization but also from the direct action of bacteria degrading the bone matrix. (c) 2022 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.
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| 4. |
- Tsang, Kevin CH, et al.
(författare)
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Compliance and Usability of an Asthma Home Monitoring System
- 2023
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Ingår i: Pervasive Computing Technologies for Healthcare. - : Springer. - 9783031345852 - 9783031345869 ; , s. 116-126
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Konferensbidrag (refereegranskat)abstract
- Asthma monitoring is an important aspect of patient self-management. However, due to its repetitive nature, patients can find long-term monitoring tedious. Mobile health can provide an avenue to monitor asthma without needing high levels of active engagement, and instead rely on passive monitoring. In our recent AAMOS-00 study, we collected mobile health data over six months from 22 asthma patients using passive and active monitoring technology, including smartwatch, peak flow measurements, and daily asthma diaries.Compliance to smartwatch monitoring was found to lie between the compliance to complete daily asthma diaries and measuring daily peak flow. However, some study participants faced technical issues with the devices which could have affected the relative compliance of the monitoring tasks.Moreover, as evidenced by standard usability questionnaires, we found that the AAMOS-00 study’s data collection system was similar in quality to other studies and published apps.
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| 5. |
- Tsang, Kevin C H, et al.
(författare)
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Home monitoring with connected mobile devices for asthma attack prediction with machine learning
- 2023
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Ingår i: Scientific Data. - : Nature Publishing Group. - 2052-4463. ; 10:1
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Tidskriftsartikel (refereegranskat)abstract
- Monitoring asthma is essential for self-management. However, traditional monitoring methods require high levels of active engagement, and some patients may find this tedious. Passive monitoring with mobile-health devices, especially when combined with machine-learning, provides an avenue to reduce management burden. Data for developing machine-learning algorithms are scarce, and gathering new data is expensive. A few datasets, such as the Asthma Mobile Health Study, are publicly available, but they only consist of self-reported diaries and lack any objective and passively collected data. To fill this gap, we carried out a 2-phase, 7-month AAMOS-00 observational study to monitor asthma using three smart-monitoring devices (smart-peak-flow-meter/smart-inhaler/smartwatch), and daily symptom questionnaires. Combined with localised weather, pollen, and air-quality reports, we collected a rich longitudinal dataset to explore the feasibility of passive monitoring and asthma attack prediction. This valuable anonymised dataset for phase-2 of the study (device monitoring) has been made publicly available. Between June-2021 and June-2022, in the midst of UK's COVID-19 lockdowns, 22 participants across the UK provided 2,054 unique patient-days of data.
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| 6. |
- Tsang, Kevin Cheuk Him, et al.
(författare)
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Predicting asthma attacks using connected mobile devices and machine learning : the AAMOS-00 observational study protocol
- 2022
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Ingår i: BMJ Open. - : BMJ Publishing Group Ltd. - 2044-6055. ; 12:10
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Tidskriftsartikel (refereegranskat)abstract
- INTRODUCTION: Supported self-management empowering people with asthma to detect early deterioration and take timely action reduces the risk of asthma attacks. Smartphones and smart monitoring devices coupled with machine learning could enhance self-management by predicting asthma attacks and providing tailored feedback.We aim to develop and assess the feasibility of an asthma attack predictor system based on data collected from a range of smart devices.METHODS AND ANALYSIS: A two-phase, 7-month observational study to collect data about asthma status using three smart monitoring devices, and daily symptom questionnaires. We will recruit up to 100 people via social media and from a severe asthma clinic, who are at risk of attacks and who use a pressurised metered dose relief inhaler (that fits the smart inhaler device).Following a preliminary month of daily symptom questionnaires, 30 participants able to comply with regular monitoring will complete 6 months of using smart devices (smart peak flow meter, smart inhaler and smartwatch) and daily questionnaires to monitor asthma status. The feasibility of this monitoring will be measured by the percentage of task completion. The occurrence of asthma attacks (definition: American Thoracic Society/European Respiratory Society Task Force 2009) will be detected by self-reported use (or increased use) of oral corticosteroids. Monitoring data will be analysed to identify predictors of asthma attacks. At the end of the monitoring, we will assess users' perspectives on acceptability and utility of the system with an exit questionnaire.ETHICS AND DISSEMINATION: Ethics approval was provided by the East of England - Cambridge Central Research Ethics Committee. IRAS project ID: 285 505 with governance approval from ACCORD (Academic and Clinical Central Office for Research and Development), project number: AC20145. The study sponsor is ACCORD, the University of Edinburgh.Results will be reported through peer-reviewed publications, abstracts and conference posters. Public dissemination will be centred around blogs and social media from the Asthma UK network and shared with study participants.
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