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Metabolomics : Official Journal of the... Mar 2024Untargeted direct mass spectrometric analysis of volatile organic compounds has many potential applications across fields such as healthcare and food safety. However,...
INTRODUCTION
Untargeted direct mass spectrometric analysis of volatile organic compounds has many potential applications across fields such as healthcare and food safety. However, robust data processing protocols must be employed to ensure that research is replicable and practical applications can be realised. User-friendly data processing and statistical tools are becoming increasingly available; however, the use of these tools have neither been analysed, nor are they necessarily suited for every data type.
OBJECTIVES
This review aims to analyse data processing and analytic workflows currently in use and examine whether methodological reporting is sufficient to enable replication.
METHODS
Studies identified from Web of Science and Scopus databases were systematically examined against the inclusion criteria. The experimental, data processing, and data analysis workflows were reviewed for the relevant studies.
RESULTS
From 459 studies identified from the databases, a total of 110 met the inclusion criteria. Very few papers provided enough detail to allow all aspects of the methodology to be replicated accurately, with only three meeting previous guidelines for reporting experimental methods. A wide range of data processing methods were used, with only eight papers (7.3%) employing a largely similar workflow where direct comparability was achievable.
CONCLUSIONS
Standardised workflows and reporting systems need to be developed to ensure research in this area is replicable, comparable, and held to a high standard. Thus, allowing the wide-ranging potential applications to be realised.
Topics: Metabolomics; Volatile Organic Compounds; Mass Spectrometry; Reference Standards; Workflow
PubMed: 38491298
DOI: 10.1007/s11306-024-02104-3 -
Journal of Neurochemistry Dec 2023The aim of this study was to systematically review prior research investigating the effects of contact/collision sport participation on neurometabolite levels in the... (Meta-Analysis)
Meta-Analysis Review
The effect of contact/collision sport participation without concussion on neurometabolites: A systematic review and meta-analysis of magnetic resonance spectroscopy studies.
The aim of this study was to systematically review prior research investigating the effects of contact/collision sport participation on neurometabolite levels in the absence of concussion. Four online databases were searched to identify studies that measured neurometabolite levels in contact/collision sport athletes (without concussion) using proton ( H) or phosphorus ( P) magnetic resonance spectroscopy (MRS). All study designs were acceptable for inclusion. Meta-analytic procedures were used to quantify the effect of contact/collision sport participation on neurometabolite levels and explore the impact of specific moderating factors (where sufficient data were available). Narrative synthesis was used to describe outcomes that could not be meta-analysed. Nine observational studies involving 300 contact/collision sport athletes were identified. Six studies (providing 112 effect estimates) employed longitudinal (cohort) designs and three (that could not be meta-analysed) employed case-control designs. N-acetylaspartate (NAA; g = -0.331, p = 0.013) and total creatine (tCr; creatine + phosphocreatine; g = -0.524, p = 0.029), but not glutamate-glutamine (Glx), myo-inositol (mI) or total choline (tCho; choline-containing compounds; p's > 0.05), decreased between the pre-season and mid-/post-season period. Several moderators were statistically significant, including: sex (Glx: 6 female/23 male, g = -0.549, p = 0.013), sport played (Glx: 22 American football/4 association football [soccer], g = 0.724, p = 0.031), brain region (mI: 2 corpus callosum/9 motor cortex, g = -0.804, p = 0.015), and the MRS quantification approach (mI: 18 absolute/3 tCr-referenced, g = 0.619, p = 0.003; and tCho: 18 absolute/3 tCr-referenced, g = 0.554, p = 0.005). In case-control studies, contact/collision sport athletes had higher levels of mI, but not NAA or tCr compared to non-contact sport athletes and non-athlete controls. Overall, this review suggests that contact/collision sport participation has the potential to alter neurometabolites measured via H MRS in the absence of concussion. However, further research employing more rigorous and consistent methodologies (e.g. interventional studies with consistent H MRS pulse sequences and quantifications) is required to confirm and better understand the clinical relevance of observed effects.
Topics: Humans; Male; Female; Creatine; Brain Concussion; Magnetic Resonance Spectroscopy; Choline; Receptors, Antigen, T-Cell; Aspartic Acid; Inositol
PubMed: 37908148
DOI: 10.1111/jnc.16000 -
International Journal of Psychiatry in... Mar 2024Resilience measures are typically based on subjective self-assessment, which is prone to bias. Objective biological/physiological measures of resilience are therefore... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Resilience measures are typically based on subjective self-assessment, which is prone to bias. Objective biological/physiological measures of resilience are therefore needed. Hair cortisol concentration is a particularly promising candidate as a biomarker for resilience.
METHODS
We conducted a meta-analytic review from inception to April 2023 in PubMed, EMBASE, Cochrane Library, and Psych Info databases. All data were analyzed using a random-effects model.
RESULTS
Eight studies were identified that included a total of 1,064 adults. The random effects model demonstrated that resilience and hair cortisol concentration were inversely correlated (r = -0.18, 95% confidence interval [CI] = -0.27 to -0.09) with substantial heterogeneity ( = 54.2%, = 0.03). The inverse association was stronger in those who were age 40 years or younger compared to those who were over 40 years. The correlation coefficients between psychological resilience and hair cortisol concentration among adults assessed by different resilience measures were r = -0.29 (95% CI = -0.49 to -0.08) for the CD-RISC-10; r = -0.21 (95% CI = -0.31 to -0.11) for the CDRISC- 25, and r = -0.08 (95% CI = -0.22 to 0.06) for the BRS. Six of eight studies examined the connection between resilience and perceived stress, where the weighted mean correlation coefficient was r = -0.45 (95% CI = -0.56 to -0.33), with considerable heterogeneity ( = 76.2%, = 0.001).
CONCLUSIONS
There is a negative association between psychological resilience and hair cortisol concentration based on these eight studies. Additional research, particularly prospective studies, is needed to determine whether hair cortisol concentration can be used as a biomarker for psychological resilience.
Topics: Adult; Humans; Resilience, Psychological; Hydrocortisone; Prospective Studies; Hair; Stress, Psychological; Biomarkers; Psychological Tests
PubMed: 37222570
DOI: 10.1177/00912174231178108 -
Critical Reviews in Food Science and... 2024Neural network (i.e. deep learning, NN)-based data analysis techniques have been listed as a pivotal opportunity to protect the integrity and safety of the global food... (Review)
Review
Neural network (i.e. deep learning, NN)-based data analysis techniques have been listed as a pivotal opportunity to protect the integrity and safety of the global food supply chain and forecast $11.2 billion in agriculture markets. As a general-purpose data analytic tool, NN has been applied in several areas of food science, such as food recognition, food supply chain security and omics analysis, and so on. Therefore, given the rapid emergence of NN applications in food safety, this review aims to provide a comprehensive overview of the NN application in food analysis for the first time, focusing on domain-specific applications in food analysis by introducing fundamental methodology, reviewing recent and notable progress, and discussing challenges and potential pitfalls. NN demonstrated that it has a bright future through effective collaboration between food specialist and the broader community in the food field, for example, superiority in food recognition, sensory evaluation, pattern recognition of spectroscopy and chromatography. However, major challenges impeded NN extension including void in the food scientist-friendly interface software package, incomprehensible model behavior, multi-source heterogeneous data, and so on. The breakthrough from other fields proved NN has the potential to offer a revolution in the immediate future.
Topics: Neural Networks, Computer; Humans; Food Analysis; Food Safety; Food Technology; Food Supply; Deep Learning
PubMed: 36322538
DOI: 10.1080/10408398.2022.2139217