Editorial Volume 18 Issue 4

Editorial Volume 18 Issue

The lingering symptoms of post-COVID-19 condition (long-COVID): a prospective cohort study

Background: Longer-term symptoms (long COVID) may be present in seemingly recovered patients for several months and can be debilitating. Aim: To investigate the prevalence and type of symptoms in those with a prior COVID-19 diagnosis. Methods: This prospective, longitudinal observational study commenced in July 2020 investigating the longer-term health impacts of COVID-19. Participants were recruited via public health units and media publicity. Surveys were completed upon enrolment, and at 1, 3, 6 and 12 months. Outcome measures included incidence of activity limitations and symptoms against health and vaccination status, age and gender. Results: Overall, 339 participants were recruited. At 3 months after COVID-19, 66.8% reported symptoms, and 44.8% were still experiencing symptoms at 12 months. Fatigue was most common at every point (between 53.1% and 33.1%). Pain symptoms increased in relative prevalence over time, whereas respiratory/pulmonary-type symptoms decreased substantially after 3 months. Females and younger people were more likely to experience symptoms in the early stages of long COVID (P \u3c 0.01) and those with more comorbidities in the latter stages (P \u3c 0.001). Vaccination showed a statistically significant protective effect against symptoms (P \u3c 0.01–0.001). Conclusion: Long-term COVID-19 symptoms exist among recovered patients up to 12 months after contracting the virus. Fatigue is a primary contributor, while chronic pain became more problematic after 6 months. Vaccination was a factor in preventing long-term symptoms and aiding faster recovery from symptoms. Further work exploring additional contributors to symptom prevalence would assist in developing appropriate follow-up care

Fast and random charging of electric vehicles and its impacts: State-of-the-art technologies and case studies

The era of the electrified transportation system is fast approaching. Although the socioeconomic and environmental benefits of electric vehicles (EVs) have contributed to their large-scale utilization, it has also created a huge load demand on the existing power grids throughout the world. Moreover, fast, super-fast, and ultra-super-fast charging stations are under development, some of which are now in the markets. These have the potential to cause power quality issues such as charging transients, rapid voltage fluctuations, and harmonics in the power grids. Moreover, EVs can participate as mobile storage to provide vehicle-to-grid (V2G) support and ancillary services. There are still some barriers to the wide implementation of V2G systems. This paper addresses these issues and provides a review of the state-of-the-art EV technologies and their impacts on power grids. This paper also investigates the impacts of random and fluctuating EV fast-charging loads on the electric power grids, mainly considering the random connection of EVs to the power grids through DC fast-charging stations as the principal source of fluctuating EV loads. A practical electrical grid of Wollongong, New South Wales, Australia has been considered in this work to separately analyze the impacts of constant current (CC) and constant voltage (CV) charging modes upon the grid. Furthermore, design and modeling of three different commercial DC fast charger connections (CHAdeMO, SAE CCS, and ChargePoint Express 200), with separate CC-CV charging modes of the DC fast chargers have been incorporated. To quantify the impacts, two separate scenarios were examined using a simulation platform, with case studies conducted to determine the impacts on the power grid. The first scenario involved three fast charging stations, while the second scenario featured ten stations that were able to charge six and twenty electric vehicles respectively, with various load combinations considered. Each of these scenarios was analyzed under different conditions to evaluate their impact on the grid, using factors such as voltage drops, maximum power demand, current, and voltage total harmonic distortion (THD) for the transformer that was connected to the charging stations. The study results indicated that the power systems were affected more significantly by random and fluctuating EV fast-charging loads, compared to normal EV slow-charging loads

What do people with inflammatory bowel disease want to know about diet? The dietary information needs of people with inflammatory bowel disease and perceptions of healthcare providers

Background: Inflammatory bowel disease (IBD) is an incurable illness of the gastrointestinal tract. Its relapsing–remitting nature negatively impacts physical health and quality of life. Food and eating are key concerns for people with this illness. To provide holistic person-centred care, healthcare providers (HCPs) need to meet patients’ dietary information needs. However, there is a paucity of literature describing these in any meaningful detail. The present study aimed to explore the perceived dietary information needs of individuals with IBD, the perceptions of HCPs and enablers and barriers to communication. Methods: Online and face-to-face semi-structured interviews with 13 HCPs and 29 people with IBD were conducted. The framework method aided thematic analysis of de-identified interview recordings. Results: The cyclical nature of IBD contextualised the five themes. Both individuals with IBD and HCPs articulated similar ideas viewed from different perspectives: (1) living with IBD is exasperating and unique to the individual; (2) individuals with IBD desire dietary information; (3) diet manipulation is used to exert control on a disease with unpredictable nature; (4) people with IBD and HCPs have different views on the role of diet; and (5) doctors are perceived as gatekeepers to accessing dietetics care. Conclusions: A lack of dietary guidance at diagnosis negatively impacts the patient\u27s journey with food and eating. The present study supports a paradigm shift towards holistic person-centred care for consistent access to dietetics services to meet the needs of people with IBD

Highly selective gas sensors for formaldehyde detection based on ZnO@ZIF‑8 core-shell heterostructures

Formaldehyde is a hazardous volatile organic pollutant commonly found indoors, making selective and accurate detection of formaldehyde crucial. To achieve this, ZnO@ZIF-8 core-shell heterostructures were fabricated using the sacrificial template method, where the 3D ZnO flower-like structures served as the core material. This innovative approach utilizing the ZIF-8 shell as a “selective gas filter” offers a novel pathway for enhancing the selectivity of formaldehyde sensors. Subsequent investigations revealed that the thickness of the ZIF-8 shell significantly influences the material\u27s performance. Among various configurations tested, the 2-ZnO@ZIF-8 sensor demonstrates the best formaldehyde detection properties, including high response (5 ppm, 5.03), excellent selectivity, short response and recovery times (29/40 s), excellent long-term stability, and a low theoretical detection limit (12.86 ppb) at 175 °C. The enhanced sensing properties can be attributed to the ZIF-8 surface\u27s high adsorption energy for formaldehyde molecules and the selective screening of gas molecules by ZIF-8. Overall, our study presents a promising strategy for developing highly selective gas sensors for formaldehyde detection, with the potential to contribute to improved indoor air quality monitoring and safety measures

Time is brain, so we must BEFAST: Improving stroke identification and triage in a rural emergency department

Objective: Shoalhaven District Memorial Hospital is a rural (MM3) secondary hospital which is over an hour travel time from the nearest tertiary centre. The objective of the present study was to pilot the implementation of the BEFAST (Balance, Eyes, Face, Arms, Speech and Time) stroke screening tool at the ED, and determine whether its usage improved timely stroke detection. Methods: During initial implementation and training (October–December 2019), triage nurses consulted with senior medical officers before activating stroke calls. Data were collected for the subsequent 24 months (January 2020–2022), and retrospective records for confirmed strokes during a 24-month period prior to BEFAST implementation (October 2017–2019) were also collected. The main outcome measures were triage category, CT scan result time, discharge destination, length of stay (LOS) and Modified Rankin Score (MRS). Results: After BEFAST implementation, patients (n = 268) were three times more likely to be triaged at category 1 or 2, and door-to-CT scan time was reduced by 20.7 min on average. More patients were discharged to their usual residence and more quickly (LOS 7.9 vs 11.1 days). MRS 90 days after stroke was less, and patients were nearly twice as likely to experience an improvement in neurological symptoms. Conclusions: Patient outcomes were improved after implementation of the BEFAST stroke triage tool. More stroke patients were identified upon presentation to the ED, and in a timely fashion. For those with a stroke diagnosis, time-critical interventions can take place earlier, allowing patients to return home sooner, and with less disability

Developing an ontology of non-pharmacological treatment for emotional and mood disturbances in dementia

Emotional and mood disturbances are common in people with dementia. Non-pharmacological interventions are beneficial for managing these disturbances. However, effectively applying these interventions, particularly in the person-centred approach, is a complex and knowledge-intensive task. Healthcare professionals need the assistance of tools to obtain all relevant information that is often buried in a vast amount of clinical data to form a holistic understanding of the person for successfully applying non-pharmacological interventions. A machine-readable knowledge model, e.g., ontology, can codify the research evidence to underpin these tools. For the first time, this study aims to develop an ontology entitled Dementia-Related Emotional And Mood Disturbance Non-Pharmacological Treatment Ontology (DREAMDNPTO). DREAMDNPTO consists of 1258 unique classes (concepts) and 70 object properties that represent relationships between these classes. It meets the requirements and quality standards for biomedical ontology. As DREAMDNPTO provides a computerisable semantic representation of knowledge specific to non-pharmacological treatment for emotional and mood disturbances in dementia, it will facilitate the application of machine learning to this particular and important health domain of emotional and mood disturbance management for people with dementia

Glucagon-like peptide-1 receptor agonists reverse nerve morphological abnormalities in diabetic peripheral neuropathy

Aims/hypothesis: Diabetic peripheral neuropathy (DPN) is a highly prevalent cause of physical disability. Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are used to treat type 2 diabetes and animal studies have shown that glucagon-like peptide-1 (GLP-1) receptors are present in the central and peripheral nervous systems. This study investigated whether GLP-1 RAs can improve nerve structure. Methods: Nerve structure was assessed using peripheral nerve ultrasonography and measurement of tibial nerve cross-sectional area, in conjunction with validated neuropathy symptom scores and nerve conduction studies. A total of 22 consecutively recruited participants with type 2 diabetes were assessed before and 1 month after commencing GLP-1 RA therapy (semaglutide or dulaglutide). Results: There was a pathological increase in nerve size before treatment in 81.8% of the cohort (n=22). At 1 month of follow-up, there was an improvement in nerve size in 86% of participants (p\u3c0.05), with 32% returning to normal nerve morphology. A 3 month follow-up study (n=14) demonstrated further improvement in nerve size in 93% of participants, accompanied by reduced severity of neuropathy (p\u3c0.05) and improved sural sensory nerve conduction amplitude (p\u3c0.05). Conclusions/interpretation: This study demonstrates the efficacy of GLP-1 RAs in improving neuropathy outcomes, evidenced by improvements in mainly structural and morphological measures and supported by electrophysiological and clinical endpoints. Future studies, incorporating quantitative sensory testing and measurement of intraepidermal nerve fibre density, are needed to investigate the benefits for small fibre function and structure. Graphical Abstract: [Figure not available: see fulltext.]

Energy recovery potential in Bangladesh from elevated temperature textile processing wastewater: an analysis of energy recovery, energy economics and reduction in carbon dioxide emission

The textile and readymade garments sector is the main engine of economic growth and the main source of foreign currency and employment. It significantly contributes to the national Gross Domestic Product (GDP). The textile industry is resource-intensive, with heavy reliance on water and energy. Groundwater temperature at 27.33 ± 1.46 oC is the source of the process water and is heated for process use in the textile industry for washing, texturing, and dyeing. Energy is required to achieve the desired elevated temperature for process water. The subsequently generated wastewater released at a high temperature of 40.4 ± 8.7 oC, and its thermal energy is not recovered. Recovered thermal energy is an excellent alternative renewable energy source to natural gas and coal used in the industry to fire its boilers to heat the required process water. In this research program, we did an energy recovery analysis from generated wastewater based on groundwater temperature, discharge wastewater temperature, and discharge flow rate (wastewater treatment plant capacities). We also modeled the potential energy recovery. The results of the model were correlated to fuel consumption, economic savings, and reduction in CO2 emission based on published databases, industrial surveys, and stakeholder input from international retail companies. The analysis shows that 102 T kWh of energy per annum can be recovered with the savings of 8.6 billion cubic meters of natural gas and 6,87,794 tons of coal, producing a total savings of 1.35 billion USD in energy cost per annum. Reducing the consumption of coal and natural gas will reduce CO2 emissions by 24.8 million tons per annum, more than 20% of annual CO2 emissions in Bangladesh and 2.00% of total greenhouse gas emissions attributed to the global textile and apparel industry. Hence, this will contribute immensely to a sustainable transition of textile industries towards a green circular economy