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Impaired linear growth is a known complication of pediatric inflammatory bowel disease (IBD), but the use of growth hormone (GH) in this population is not well-described. The primary aim of this study is to determine whether growth hormone use in pediatric IBD leads to improved height outcomes. This was a retrospective chart review of patients with IBD aged 0–21 years followed at a single center between 2018 and 2021 treated with at least 1 year of GH. Records collected included demographics, IBD phenotype, IBD disease activity scores, medications, weight z-score, height z-score, bone age, and details of GH therapy including testing for GH deficiency. The primary outcome measure was change in height z-score after 1 year of GH treatment. Forty-six patients were identified and 18 were excluded. Of the 28 patients included (7 female; 25.0 %), 26 (92.9 %) had a diagnosis of Crohn's disease (CD) and 2 (7.1 %) had ulcerative colitis (UC). The mean (SD) age at GH initiation was 9.6 (3.4) years. Among all participants, there was a significant mean difference in height z-score from baseline to 1 year on therapy (−2.25 vs. −1.50, respectively; difference, 0.75; 95 % CI, 0.56 to 0.94; p<0.001). Among the 19 subjects that completed GH therapy there was a significant mean difference between baseline and final height z-scores (−2.41 vs. −0.77, respectively; difference, 1.64; 95 % CI, 1.30 to 1.98; p<0.001). GH use was associated with improved height outcomes. The pediatric IBD patients in this cohort had significant improvements in height z-scores both after one year on therapy and at completion of GH therapy. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease and related dementias (AD/ADRD) are chronic neurodegenerative pathology and bring a growing public health concern worldwide; particularly, treatments for AD/ADRD remain limited. Drug repositioning has alternate potential to provide an opportunity to accelerate newly identified treatments for individuals with AD/ADRD. Like, some studies have investigated effects of antihypertensive medications on dementia risk, but inconsistent results are reported. In this study, we aim to determine whether existing or approved drugs, including antihypertensive drugs and hormone replacement therapy, enable to reduce the risk of dementia or cognitive impairment. Method: We searched PubMed, MEDLINE and EMBASE for published trials up to December 31, 2020. The primary outcome of interest was incident dementia or incident cognitive decline. We examined the following candidate repurposed drugs, including hormone replacement therapy and antihypertensive drug classes: diuretics, beta blockers (BB), angiotensin‐converting enzyme inhibitors (ACE‐I), angiotensin II receptor blockers (ARB), calcium channel blockers (CCB), alpha blockers, central agonists, vasodilators, and aldosterone blockers. We conducted a random‐effects network meta‐analysis using individual participant data to identify both direct and indirect evidence from the include trials. Result: Four trials, including 19,632 participants and 10 candidate repurposed drugs, met the eligibility criteria, as shown in Figure 1. The results of network meta‐analysis were presented as a league table in Figure 2. We found that aldosterone blockers (OR = 2.32; 95% CI: 1.41 to 3.81), ARB (OR = 1.31; 95% CI: 1.07 to 1.60) and hormone therapy (OR = 1.36; 95% CI: 1.08 to 1.71) were less effective in reducing dementia risk when compared with ACE‐I. Moreover, all the other drugs reduced dementia risk statistically significantly compared with aldosterone blockers (ORs ranging from 0.46 (95% CI: 0.27 to 0.79) for alpha blockers to 0.59 (95% CI: 0.35 to 0.99) for hormone replacement therapy). Conclusion: Our findings showed some classes of antihypertensive drugs may have more potential to prevent the incidence of dementia or cognitive decline than the other classes. However, further research for validation of our results is needed. [ABSTRACT FROM AUTHOR]

• Investment Recovery practices positively affect customers' intention to participate in sharing economy. • Corporate Social Responsibility of sharing economy platforms encourages consumers to use sharing economy products/services. • Green-related sustainable supply chain practices cannot motivate consumers to participate in the sharing economy. • Promote green-related sustainable supply chain practices through critical advertising can attract more consumers. The notion of the sharing economy has been introduced in many sectors and provided significant benefits to consumers and asset owners. Despite the remarkable improvement of the sharing economy in recent years, its relationship with sustainability remains insufficiently researched. This study adopts a sustainable supply chain management (SSCM) perspective. A large-scale survey with 420 participants showed that investment recovery (IR) practices and corporate social responsibility (CSR) conducted by sharing economy platforms significantly and positively affect customers' intention to use sharing economy-based services/products, whereas internal green management (IGM), supplier green management (SGM), eco-design (ECD) and customer green management (CGM) practices do not. A follow-up qualitative study with ten participants provided further explanations and supported the findings of the survey. This study links the sharing economy and sustainability by testing the effectiveness of sharing economy platforms' sustainable practices and proposes the best practices for sharing economy platforms to maintain a long-term sustainable marketplace. [ABSTRACT FROM AUTHOR]

Objectives Falling is a major health risk facing the elderly. The prevalence of falls is 20.5% among adults older than 65 years in Taiwan. Our study used a geriatric screening tool to identify elderly people at high risk of falls. Materials and Methods Our study used a 10-minute geriatric screening tool developed by the World Health Organization to survey geriatric health problems and evaluated its effectiveness in a population of elderly Taiwanese. There were 186 participants who were ≥ 65 years old. All participants were interviewed by trained volunteers using the screening tool. Results The prevalence of falls was 28.3%, depression 13.4%, and urinary incontinence 29.9% in the previous year. Health issues in the elderly associated with a history of falls included depression ( p < 0.001), urinary incontinence in the previous year ( p = 0.004), and urinary incontinence in the previous week ( p = 0.007). Protective factors against falls included the ability to walk fast ( p < 0.001), get to places out of walking distance ( p < 0.001), and perform heavy work ( p < 0.001). The logistic regression analysis revealed that depression was positively correlated with a history of falling ( p = 0.023), whereas the ability to walk fast presented a negative correlation ( p = 0.015). Conclusion The World Health Organization 10-minute screening tool can be rapidly and easily implemented in a primary care clinical setting. It can also improve the identification of elderly persons living in the community at high risk of falling. [ABSTRACT FROM AUTHOR]

Summary: Background: Avian influenza A H6N1 virus is one of the most common viruses isolated from wild and domestic avian species, but human infection with this virus has not been previously reported. We report the clinical presentation, contact, and environmental investigations of a patient infected with this virus, and assess the origin and genetic characteristics of the isolated virus. Methods: A 20-year-old woman with an influenza-like illness presented to a hospital with shortness of breath in May, 2013. An unsubtyped influenza A virus was isolated from her throat-swab specimen and was transferred to the Taiwan Centres for Disease Control (CDC) for identification. The medical records were reviewed to assess the clinical presentation. We did a contact and environmental investigation and collected clinical specimens from the case and symptomatic contacts to test for influenza virus. The genomic sequences of the isolated virus were determined and characterised. Findings: The unsubtyped influenza A virus was identified as the H6N1 subtype, based on sequences of the genes encoding haemagglutinin and neuraminidase. The source of infection was not established. Sequence analyses showed that this human isolate was highly homologous to chicken H6N1 viruses in Taiwan and had been generated through interclade reassortment. Notably, the virus had a G228S substitution in the haemagglutinin protein that might increase its affinity for the human α2-6 linked sialic acid receptor. Interpretation: This is the first report of human infection with a wild avian influenza A H6N1 virus. A unique clade of H6N1 viruses with a G228S substitution of haemagglutinin have circulated persistently in poultry in Taiwan. These viruses continue to evolve and accumulate changes, increasing the potential risk of human-to-human transmission. Our report highlights the continuous need for preparedness for a pandemic of unpredictable and complex avian influenza. Funding: Taiwan Centres for Disease Control. [ABSTRACT FROM AUTHOR]

Summary: We report on an outbreak caused by Salmonella enteritidis phage type 4 (PT4) among 143 participants at a soccer camp in Austria in August 2010. The outbreak affected 34 persons, including 24 epidemiologically related cases and 10 laboratory-confirmed cases. Food-specific cohort analyses revealed spaetzle (homemade noodles) (relative risks (RR): 2.68; 95% CI: 1.13–6.45), hamburger (RR: 2.70; 95% CI: 1.13–6.45) and potato salad (RR: 2.91; 95% CI: 1.69–5.02) as the most biologically plausible infection sources. Eggs used as ingredients were considered to be the vehicle of infection for the outbreak strain. The sole egg producer supplying the hotel that housed the soccer camp participants with table eggs operated two flocks. One flock had been epidemiologically and microbiologically related to a previous S. enteritidis PT4 outbreak affecting the same Austrian province in the four months preceding the August outbreak. We hypothesize that eggs from this flock, already condemned for industrial use only, were falsely declared table eggs and sold among eggs from the non-banned flock causing the subsequent outbreak. In Austria, the illegal distribution of eggs designated for industrial use (i.e., false declaration of these eggs as table eggs) has been previously documented. Our findings underscore the potential of proper epidemiological outbreak investigation to identify the pitfalls of regulatory responses in risk management. [ABSTRACT FROM AUTHOR]

• This research analyses the South African carbon capture and storage (CCS) project using a technological innovation system (TIS) framework. • It complements this approach with a political economy framework and explores the relevance of political dynamics related to the successful implementation of TIS. • Through a systematic review of relevant contextual factors and the relationships between key actors, this study identifies important shortcomings in the management of the CCS project in an emerging market. This research investigates the technological innovation system (TIS) approach in emerging markets, focusing on South Africa's deployment of the carbon capture and storage (CCS) project and explaining its underlying structures and functions. In identifying the shortcomings of the TIS, this study further considers relevant contextual factors that affect the successful employment of the system, particularly the political economy of the energy sector. As a result, it develops an integrated framework that offers a more comprehensive understanding of the factors relevant to TIS implementation. Utilising a qualitative thematic analysis to analyse secondary data, the findings of our study reveal the pertinence of the power of incumbents and the lack of a legal framework. The results not only theoretically contribute to the innovation system field but also offer practical suggestions for the execution and management of technological projects in South Africa. [ABSTRACT FROM AUTHOR]

Background: Changeful seasonal influenza activity in subtropical areas such as Taiwan causes problems in epidemic preparedness. The Taiwan Centers for Disease Control has maintained real-time national influenza surveillance systems since 2004. Except for timely monitoring, epidemic forecasting using the national influenza surveillance data can provide pivotal information for public health response.Objective: We aimed to develop predictive models using machine learning to provide real-time influenza-like illness forecasts.Methods: Using surveillance data of influenza-like illness visits from emergency departments (from the Real-Time Outbreak and Disease Surveillance System), outpatient departments (from the National Health Insurance database), and the records of patients with severe influenza with complications (from the National Notifiable Disease Surveillance System), we developed 4 machine learning models (autoregressive integrated moving average, random forest, support vector regression, and extreme gradient boosting) to produce weekly influenza-like illness predictions for a given week and 3 subsequent weeks. We established a framework of the machine learning models and used an ensemble approach called stacking to integrate these predictions. We trained the models using historical data from 2008-2014. We evaluated their predictive ability during 2015-2017 for each of the 4-week time periods using Pearson correlation, mean absolute percentage error (MAPE), and hit rate of trend prediction. A dashboard website was built to visualize the forecasts, and the results of real-world implementation of this forecasting framework in 2018 were evaluated using the same metrics.Results: All models could accurately predict the timing and magnitudes of the seasonal peaks in the then-current week (nowcast) (ρ=0.802-0.965; MAPE: 5.2%-9.2%; hit rate: 0.577-0.756), 1-week (ρ=0.803-0.918; MAPE: 8.3%-11.8%; hit rate: 0.643-0.747), 2-week (ρ=0.783-0.867; MAPE: 10.1%-15.3%; hit rate: 0.669-0.734), and 3-week forecasts (ρ=0.676-0.801; MAPE: 12.0%-18.9%; hit rate: 0.643-0.786), especially the ensemble model. In real-world implementation in 2018, the forecasting performance was still accurate in nowcasts (ρ=0.875-0.969; MAPE: 5.3%-8.0%; hit rate: 0.582-0.782) and remained satisfactory in 3-week forecasts (ρ=0.721-0.908; MAPE: 7.6%-13.5%; hit rate: 0.596-0.904).Conclusions: This machine learning and ensemble approach can make accurate, real-time influenza-like illness forecasts for a 4-week period, and thus, facilitate decision making. [ABSTRACT FROM AUTHOR]