Data (attached) for a focused review and meta-analysis of cerebral levels of glutamate, Glx, and GABA levels assessed with H-MRS in high-risk of psychosis states was collected and stored at covidence.org and extracted to The Cochrane Collaboration Review Manager software package (RevMan Version 5.3) for meta-analytical purposes. Meta-analyses were performed with a random-effects, inverse-variance weighted model to calculate the pooled effect size. Heterogeneity was measured using the I value. Significance was assessed using two-sided 95% confidence intervals. Potential publication bias was assessed by visual inspection of funnel plots. Supplementary to the co-submitted article are comprehensive meta-analyses of glutamate, Glx, and GABA, as well as the PRISMA flow diagram of included studies and a list of studies included in the review along with available measures and methodological variables. The attached data offers an insight into the included studies and the specified metabolite values for each study and offers possible further investigation for other researchers, as well as an insight into the review and meta-analyses performed. The supplementary material also serves to support findings and interpretations in the main article.
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http://dx.doi.org/10.1016/j.dib.2019.104920 | DOI Listing |
Environ Sci Pollut Res Int
December 2024
Department of Mechanical Engineering, K. Ramakrishnan College of Engineering, Samayapuram, Trichy, India.
Lubricants are pivotal in mitigating friction and wear between surfaces, ensuring seamless movement of solid objects. However, the predominant use of petroleum-based lubricants in the automotive and industrial ssectors raises substantial concerns for future energy security. The exploration of vegetable oils as an alternative lubricant in the automotive industry was motivated by the depletion of fossil fuels and escalating environmental concerns.
View Article and Find Full Text PDFCancer Cell Int
December 2024
Department of Plastic and Aesthetic Surgery, the Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, China.
Background: Cutaneous melanoma is one of the most invasive and lethal skin malignant tumors. Compared to primary melanoma, metastatic melanoma (MM) presents poorer treatment outcomes and a higher mortality rate. The tumor microenvironment (TME) plays a critical role in MM progression and immunotherapy resistance.
View Article and Find Full Text PDFRespir Res
December 2024
Department of Mechanical and Product Design Engineering, Swinburne University of Technology, Hawthorn, VIC, Australia.
By virtue of applying small tidal volumes, high-frequency ventilation is advocated as a method of minimizing ventilator-induced lung injury. Lung protective benefits are established in infants, but not in other patient cohorts. Efforts to improve and extend the lung protection potential should consider how fundamental modes of gas transport can be exploited to minimize harmful tidal volumes while maintaining or improving ventilation.
View Article and Find Full Text PDFBMC Health Serv Res
December 2024
Centre for Safety in Healthcare, at the Faculty of Technology, Policy and Management, Delft University of Technology, Jaffalaan 5, Delft, 2628 BX, the Netherlands.
Background: Speaking up among healthcare professionals plays an essential role in improving patient safety and quality of care, yet it remains complex and multifaceted behaviour. Despite awareness of potential risks and adverse outcomes for patients, professionals often hesitate to voice concerns due to various influencing factors. This complexity has encouraged research into the determinants of speaking-up behaviour in hospital settings.
View Article and Find Full Text PDFBMC Public Health
December 2024
Upstream Lab, MAP Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, Unity Health Toronto, 30 Bond Street, Toronto, ON, M5B 1W8, Canada.
Background: Machine learning (ML) is increasingly used in population and public health to support epidemiological studies, surveillance, and evaluation. Our objective was to conduct a scoping review to identify studies that use ML in population health, with a focus on its use in non-communicable diseases (NCDs). We also examine potential algorithmic biases in model design, training, and implementation, as well as efforts to mitigate these biases.
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