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BackgroundDeep learning has shown potential in various scientific domains but faces challenges when applied to complex, high-dimensional multi-omics data. Alzheimer's Disease (AD) is a neurodegenerative disorder that lacks targeted therapeutic options. This study introduces the Circular-Sliding Window Association Test (c-SWAT) to improve the classification accuracy in predicting AD using serum-based metabolomics data, specifically lipidomics.MethodsThe c-SWAT methodology builds upon the existing Sliding Window Association Test (SWAT) and utilizes a three-step approach: feature correlation analysis, feature selection, and classification. Data from 997 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) served as the basis for model training and validation. Feature correlations were analyzed using Weighted Gene Co-expression Network Analysis (WGCNA), and Convolutional Neural Networks (CNN) were employed for feature selection. Random Forest was used for the final classification.FindingsThe application of c-SWAT resulted in a classification accuracy of up to 80.8% and an AUC of 0.808 for distinguishing AD from cognitively normal older adults. This marks a 9.4% improvement in accuracy and a 0.169 increase in AUC compared to methods without c-SWAT. These results were statistically significant, with a p-value of 1.04 × 10ˆ-4. The approach also identified key lipids associated with AD, such as Cer(d16:1/22:0) and PI(37:6).InterpretationOur results indicate that c-SWAT is effective in improving classification accuracy and in identifying potential lipid biomarkers for AD. These identified lipids offer new avenues for understanding AD and warrant further investigation.FundingThe specific funding of this article is provided in the acknowledgements section.

Inflammation is an important factor in Alzheimer's disease (AD). An NMR measurement in plasma, glycoprotein acetyls (GlycA), captures the overall level of protein production and glycosylation implicated in systemic inflammation. With its additional advantage of reducing biological variability, GlycA might be useful in monitoring the relationship between peripheral inflammation and brain changes relevant to AD. However, the associations between GlycA and these brain changes have not been fully evaluated. Here, we performed Spearman's correlation analyses to evaluate these associations cross-sectionally and determined whether GlycA can inform AD-relevant longitudinal measurements among participants in the Alzheimer's Disease Neuroimaging Initiative (n = 1506), with additional linear models and stratification analyses to evaluate the influences of sex or diagnosis status and confirm findings from Spearman's correlation analyses. We found that GlycA was elevated in AD patients compared to cognitively normal participants. GlycA correlated negatively with multiple concurrent regional brain volumes in females diagnosed with late mild cognitive impairment (LMCI) or AD. Baseline GlycA level was associated with executive function decline at 3-9 year follow-up in participants diagnosed with LMCI at baseline, with similar but not identical trends observed in the future decline of memory and entorhinal cortex volume. Results here indicated that GlycA is an inflammatory biomarker relevant to AD pathogenesis and that the stage of LMCI might be relevant to inflammation-related intervention.

Alzheimers disease (AD) is influenced by a variety of modifiable risk factors, including a persons dietary habits. While the ketogenic diet (KD) holds promise in reducing metabolic risks and potentially affecting AD progression, only a few studies have explored KDs metabolic impact, especially on blood and cerebrospinal fluid (CSF). Our study involved participants at risk for AD, either cognitively normal or with mild cognitive impairment. The participants consumed both a modified Mediterranean Ketogenic Diet (MMKD) and the American Heart Association diet (AHAD) for 6 weeks each, separated by a 6-week washout period. We employed nuclear magnetic resonance (NMR)-based metabolomics to profile serum and CSF and metagenomics profiling on fecal samples. While the AHAD induced no notable metabolic changes, MMKD led to significant alterations in both serum and CSF. These changes included improved modifiable risk factors, like increased HDL-C and reduced BMI, reversed serum metabolic disturbances linked to AD such as a microbiome-mediated increase in valine levels, and a reduction in systemic inflammation. Additionally, the MMKD was linked to increased amino acid levels in the CSF, a breakdown of branched-chain amino acids (BCAAs), and decreased valine levels. Importantly, we observed a strong correlation between metabolic changes in the CSF and serum, suggesting a systemic regulation of metabolism. Our findings highlight that MMKD can improve AD-related risk factors, reverse some metabolic disturbances associated with AD, and align metabolic changes across the blood-CSF barrier.

Abstract In this community effort, we compare measurements between 34 laboratories from 19 countries, utilizing mixtures of labelled authentic synthetic standards, to quantify by mass spectrometry four clinically used ceramide species in the NIST (National Institute of Standards and Technology) human blood plasma Standard Reference Material (SRM) 1950, as well as a set of candidate plasma reference materials (RM 8231). Participants either utilized a provided validated method and/or their method of choice. Mean concentration values, and intra- and inter-laboratory coefficients of variation (CV) were calculated using single-point and multi-point calibrations, respectively. These results are the most precise (intra-laboratory CVs ≤ 4.2%) and concordant (inter-laboratory CVs < 14%) community-derived absolute concentration values reported to date for four clinically used ceramides in the commonly analyzed SRM 1950. We demonstrate that calibration using authentic labelled standards dramatically reduces data variability. Furthermore, we show how the use of shared RM can correct systematic quantitative biases and help in harmonizing lipidomics. Collectively, the results from the present study provide a significant knowledge base for translation of lipidomic technologies to future clinical applications that might require the determination of reference intervals (RIs) in various human populations or might need to estimate reference change values (RCV), when analytical variability is a key factor for recall during multiple testing of individuals.

Summary: Despite extensive global research into genetic predisposition for severe COVID-19, knowledge on the role of rare host genetic variants and their relation to other risk factors remains limited. Here, 52 genes with prior etiological evidence were sequenced in 1,772 severe COVID-19 cases and 5,347 population-based controls from Spain/Italy. Rare deleterious TLR7 variants were present in 2.4% of young (

Abstract Background Honey bees are the principal commercial pollinators. Along with other arthropods, they are increasingly under threat from anthropogenic factors such as the incursion of invasive honey bee subspecies, pathogens and parasites. Better tools are needed to identify bee subspecies. Genomic data for economic and ecologically important organisms is increasing, but in its basic form its practical application to address ecological problems is limited. Results We introduce HBeeID a means to identify honey bees. The tool utilizes a knowledge-based network and diagnostic SNPs identified by discriminant analysis of principle components and hierarchical agglomerative clustering. Tests of HBeeID showed that it identifies African, Americas-Africanized, Asian, and European honey bees with a high degree of certainty even when samples lack the full 272 SNPs of HBeeID. Its prediction capacity decreases with highly admixed samples. Conclusion HBeeID is a high-resolution genomic, SNP based tool, that can be used to identify honey bees and screen species that are invasive. Its flexible design allows for future improvements via sample data additions from other localities.

Abstract Inflammation is an important factor in Alzheimer’s disease (AD). An NMR measurement in plasma, glycoprotein acetyls (GlycA), captures the overall level of protein production and glycosylation implicated in systemic inflammation. With its additional advantage of reducing biological variability, GlycA might be useful in monitoring the relationship between peripheral inflammation and brain changes relevant to AD. However, the associations between GlycA and these brain changes have not been fully evaluated. Here, we performed Spearman’s correlation analyses to evaluate these associations cross-sectionally and determined whether GlycA can inform AD-relevant longitudinal measurements among participants in the Alzheimer’s Disease Neuroimaging Initiative (n = 1506), with additional linear models and stratification analyses to evaluate the influences of sex or diagnosis status and confirm findings from Spearman’s correlation analyses. We found that GlycA was elevated in AD patients compared to cognitively normal participants. GlycA correlated negatively with multiple concurrent regional brain volumes in females diagnosed with late mild cognitive impairment (LMCI) or AD. Baseline GlycA level was associated with executive function decline at 3–9 year follow-up in participants diagnosed with LMCI at baseline, with similar but not identical trends observed in the future decline of memory and entorhinal cortex volume. Results here indicated that GlycA is an inflammatory biomarker relevant to AD pathogenesis and that the stage of LMCI might be relevant to inflammation-related intervention.

The rapid increase in lipidomic studies has led to a collaborative effort within the community to establish standards and criteria for producing, documenting, and disseminating data. Creating a dynamic easy-to-use checklist that condenses key information about lipidomic experiments into common terminology will enhance the field's consistency, comparability, and repeatability. Here, we describe the structure and rationale of the established Lipidomics Minimal Reporting Checklist to increase transparency in lipidomics research.

Grazing management significantly contributes to low beef production in cow-calf systems within the Rio de la Plata native grasslands. An herbage allowance (HA) of 4 kg DM/kg BW increased the productive response of primiparous cows grazing shallow soils compared to 2.5. However, the impact of HA on metabolic changes and its association with productive response were not studied. We studied two levels of native grassland HA from −150 days relative to calving (DC) to weaning (195 DC) in spring-calving primiparous beef cows undergoing temporary weaning (TW) and flushing at 86 ± 12 DC on herbage intake (HI), body condition score (BCS), BW, milk yield, calf weight, concentrations of metabolic hormones, and the probability of ovulation and pregnancy. Thirty-one heifers were assigned to HA treatments that fluctuated throughout seasons: autumn (−150 to −90 DC) at 5 and 3 kg DM/kg BW, winter (−90 to 0 DC) at 3 and 3 kg DM/kg BW, and spring-summer (0 to 195 DC) at 4 and 2 kg DM/kg BW for High and Low HA, respectively. Data were analysed using linear models and generalised linear models for continuous and categorical variables, respectively. During the autumn period, HI, insulin, IGF-I, BCS, and BW were higher in High HA than Low, despite small differences in herbage mass between HA. Throughout the winter, spring, and summer, HI, insulin, leptin, and BCS changes did not differ between HA. However, IGF-I concentrations were greater at −65 and −40 DC (84 vs 55 ± 8.6 ng/mL; P

Summary: Background: Metabolic ageing biomarkers may capture the age-related shifts in metabolism, offering a precise representation of an individual’s overall metabolic health. Methods: Utilising comprehensive lipidomic datasets from two large independent population cohorts in Australia (n = 14,833, including 6630 males, 8203 females), we employed different machine learning models, to predict age, and calculated metabolic age scores (mAge). Furthermore, we defined the difference between mAge and age, termed mAgeΔ, which allow us to identify individuals sharing similar age but differing in their metabolic health status. Findings: Upon stratification of the population into quintiles by mAgeΔ, we observed that participants in the top quintile group (Q5) were more likely to have cardiovascular disease (OR = 2.13, 95% CI = 1.62–2.83), had a 2.01-fold increased risk of 12-year incident cardiovascular events (HR = 2.01, 95% CI = 1.45–2.57), and a 1.56-fold increased risk of 17-year all-cause mortality (HR = 1.56, 95% CI = 1.34–1.79), relative to the individuals in the bottom quintile group (Q1). Survival analysis further revealed that men in the Q5 group faced the challenge of reaching a median survival rate due to cardiovascular events more than six years earlier and reaching a median survival rate due to all-cause mortality more than four years earlier than men in the Q1 group. Interpretation: Our findings demonstrate that the mAge score captures age-related metabolic changes, predicts health outcomes, and has the potential to identify individuals at increased risk of metabolic diseases. Funding: The specific funding of this article is provided in the acknowledgements section.

Summary: Background: Decreased levels of circulating ethanolamine plasmalogens [PE(P)], and a concurrent increase in phosphatidylethanolamine (PE) are consistently reported in various cardiometabolic conditions. Here we devised, a plasmalogen score (Pls Score) that mirrors a metabolic signal that encompasses the levels of PE(P) and PE and captures the natural variation in circulating plasmalogens and perturbations in their metabolism associated with disease, diet, and lifestyle. Methods: We utilised, plasma lipidomes from the Australian Obesity, Diabetes and Lifestyle study (AusDiab; n = 10,339, 55% women) a nationwide cohort, to devise the Pls Score and validated this in the Busselton Health Study (BHS; n = 4,492, 56% women, serum lipidome) and in a placebo-controlled crossover trial involving Shark Liver Oil (SLO) supplementation (n = 10, 100% men). We examined the association of the Pls Score with cardiometabolic risk factors, type 2 diabetes mellitus (T2DM), cardiovascular disease and all-cause mortality (over 17 years). Findings: In a model, adjusted for age, sex and BMI, individuals in the top quintile of the Pls Score (Q5) relative to Q1 had an OR of 0.31 (95% CI 0.21–0.43), 0.39 (95% CI 0.25–0.61) and 0.42 (95% CI 0.30–0.57) for prevalent T2DM, incident T2DM and prevalent cardiovascular disease respectively, and a 34% lower mortality risk (HR = 0.66; 95% CI 0.56–0.78). Significant associations between diet and lifestyle habits and Pls Score exist and these were validated through dietary supplementation of SLO that resulted in a marked change in the Pls Score. Interpretation: The Pls Score as a measure that captures the natural variation in circulating plasmalogens, was not only inversely related to cardiometabolic risk and all-cause mortality but also associate with diet and lifestyle. Our results support the potential utility of the Pls Score as a biomarker for metabolic health and its responsiveness to dietary interventions. Further research is warranted to explore the underlying mechanisms and optimise the practical implementation of the Pls Score in clinical and population settings. Funding: National Health and Medical Research Council (NHMRC grant 233200), National Health and Medical Research Council of Australia (Project grant APP1101320), Health Promotion Foundation of Western Australia, and National Health and Medical Research Council of Australia Senior Research Fellowship (#1042095).

ABSTRACT Mounting evidence points towards inflammation as an important factor in Alzheimer’s disease (AD) pathogenesis. In this study, we investigated the relationship between a key marker of inflammation – glycoprotein acetyls (GlycA) – in blood and cognitive and brain structural changes in over 1500 participants enrolled into the Alzheimer’s Disease Neuroimaging Initiative. We evaluated those associations cross-sectionally at baseline, followed by an evaluation of whether baseline GlycA can inform about future disease progression. Our results support the following findings: 1) GlycA is elevated in participants diagnosed with AD compared to cognitively normal participants; 2) GlycA level correlates negatively with regional brain volumes in females diagnosed with late mild cognitive impairment (LMCI) or AD; 3) baseline GlycA level is associated with executive function decline at 3-9 year follow-up in both male and female participants diagnosed with LMCI at baseline; and 4) baseline GlycA is associated with decline in entorhinal cortex volume at years 2, 4 and 6-8 of follow-up in both male and female participants diagnosed with LMCI at baseline. In conclusion, peripheral inflammation was found to be positively associated with AD diagnosis and future decline in cognition and regional brain volumes. However, we note that the cross-sectional relationship between peripheral inflammation and AD-related brain atrophy is specific to sex and diagnostic status. Our findings point to peripheral inflammation as a risk factor in AD development, which enables the identification of potential markers and therapeutic intervention for participants who are at risk.

Cardiometabolic diseases encompass a range of interrelated conditions that arise from underlying metabolic perturbations precipitated by genetic, environmental, and lifestyle factors. While obesity, dyslipidaemia, smoking, and insulin resistance are major risk factors for cardiometabolic diseases, individuals still present in the absence of such traditional risk factors, making it difficult to determine those at greatest risk of disease. Thus, it is crucial to elucidate the genetic, environmental, and molecular underpinnings to better understand, diagnose, and treat cardiometabolic diseases. Much of this information can be garnered using systems genetics, which takes population-based approaches to investigate how genetic variance contributes to complex traits. Despite the important advances made by human genome-wide association studies (GWAS) in this space, corroboration of these findings has been hampered by limitations including the inability to control environmental influence, limited access to pertinent metabolic tissues, and often, poor classification of diseases or phenotypes. A complementary approach to human GWAS is the utilisation of model systems such as genetically diverse mouse panels to study natural genetic and phenotypic variation in a controlled environment. Here, we review mouse genetic reference panels and the opportunities they provide for the study of cardiometabolic diseases and related traits. We discuss how the post-GWAS era has prompted a shift in focus from discovery of novel genetic variants to understanding gene function. Finally, we highlight key advantages and challenges of integrating complementary genetic and multi-omics data from human and mouse populations to advance biological discovery.

Background: Primary prevention programs utilising traditional risk scores fail to identify all individuals who suffer acute cardiovascular events. We aimed to model the impact and cost effectiveness of incorporating a Polygenic risk scores (PRS) into the cardiovascular disease CVD primary prevention program in Australia, using a whole-of-system model. Methods: System dynamics models, encompassing acute and chronic CVD care in the Australian healthcare setting, assessing the cost-effectiveness of incorporating a CAD-PRS in the primary prevention setting. The time horizon was 10-years. Results: Pragmatically incorporating a CAD-PRS in the Australian primary prevention setting in middle-aged individuals already attending a Heart Health Check (HHC) who are determined to be at low or moderate risk based on the 5-year Framingham risk score (FRS), with conservative assumptions regarding uptake of PRS, could have prevented 2, 052 deaths over 10-years, and resulted in 24, 085 QALYs gained at a cost of $19, 945 per QALY with a net benefit of $724 million. If all Australians overs the age of 35 years old had their FRS and PRS performed, and acted upon, 12, 374 deaths and 60, 284 acute coronary events would be prevented, with 183, 682 QALYs gained at a cost of $18, 531 per QALY, with a net benefit of $5, 780 million. Conclusions: Incorporating a CAD-PRS in a contemporary primary prevention setting in Australia would result in substantial health and societal benefits and is cost-effective. The broader the uptake of CAD-PRS in the primary prevention setting in middle-aged Australians, the greater the impact and the more cost-effective the strategy.

Dyslipidemia associates with and usually precedes the onset of chronic kidney disease (CKD), but a comprehensive assessment of molecular lipid species associated with risk of CKD is lacking. Here, we sought to identify fasting plasma lipids associated with risk of CKD among American Indians in the Strong Heart Family Study, a large-scale community-dwelling of individuals, followed by replication in Mexican Americans from the San Antonio Family Heart Study and Caucasians from the Australian Diabetes, Obesity and Lifestyle Study. We also performed repeated measurement analysis to examine the temporal relationship between the change in the lipidome and change in kidney function between baseline and follow-up of about five years apart. Network analysis was conducted to identify differential lipid classes associated with risk of CKD. In the discovery cohort, we found that higher baseline level of multiple lipid species, including glycerophospholipids, glycerolipids and sphingolipids, was significantly associated with increased risk of CKD, independent of age, sex, body mass index, diabetes and hypertension. Many lipid species were replicated in at least one external cohort at the individual lipid species and/or the class level. Longitudinal change in the plasma lipidome was significantly associated with change in the estimated glomerular filtration rate after adjusting for covariates, baseline lipids and the baseline rate. Network analysis identified distinct lipidomic signatures differentiating high from low-risk groups. Thus, our results demonstrated that disturbed lipid metabolism precedes the onset of CKD. These findings shed light on the mechanisms linking dyslipidemia to CKD and provide potential novel biomarkers for identifying individuals with early impaired kidney function at preclinical stages.

Dysregulation of sphingomyelin and ceramide metabolism have been implicated in Alzheimer's disease. Genome-wide and transcriptome-wide association studies have identified various genes and genetic variants in lipid metabolism that are associated with Alzheimer's disease. However, the molecular mechanisms of sphingomyelin and ceramide disruption remain to be determined. We focus on the sphingolipid pathway and carry out multi-omics analyses to identify central and peripheral metabolic changes in Alzheimer's patients, correlating them to imaging features. Our multi-omics approach is based on (a) 2114 human post-mortem brain transcriptomics to identify differentially expressed genes; (b) in silico metabolic flux analysis on context-specific metabolic networks identified differential reaction fluxes; (c) multimodal neuroimaging analysis on 1576 participants to associate genetic variants in sphingomyelin pathway with Alzheimer's disease pathogenesis; (d) plasma metabolomic and lipidomic analysis to identify associations of lipid species with dysregulation in Alzheimer's; and (e) metabolite genome-wide association studies to define receptors within the pathway as a potential drug target. We validate our hypothesis in amyloidogenic APP/PS1 mice and show prolonged exposure to fingolimod alleviated synaptic plasticity and cognitive impairment in mice. Our integrative multi-omics approach identifies potential targets in the sphingomyelin pathway and suggests modulators of S1P metabolism as possible candidates for Alzheimer's disease treatment.

Abstract Obesity is a risk factor for type 2 diabetes and cardiovascular disease. However, a substantial proportion of patients with these conditions have a seemingly normal body mass index (BMI). Conversely, not all obese individuals present with metabolic disorders giving rise to the concept of “metabolically healthy obese”. We use lipidomic-based models for BMI to calculate a metabolic BMI score (mBMI) as a measure of metabolic dysregulation associated with obesity. Using the difference between mBMI and BMI (mBMIΔ), we identify individuals with a similar BMI but differing in their metabolic health and disease risk profiles. Exercise and diet associate with mBMIΔ suggesting the ability to modify mBMI with lifestyle intervention. Our findings show that, the mBMI score captures information on metabolic dysregulation that is independent of the measured BMI and so provides an opportunity to assess metabolic health to identify “at risk” individuals for targeted intervention and monitoring.

Abstract Recent advancements in plasma lipidomic profiling methodology have significantly increased specificity and accuracy of lipid measurements. This evolution, driven by improved chromatographic and mass spectrometric resolution of newer platforms, has made it challenging to align datasets created at different times, or on different platforms. Here we present a framework for harmonising such plasma lipidomic datasets with different levels of granularity in their lipid measurements. Our method utilises elastic-net prediction models, constructed from high-resolution lipidomics reference datasets, to predict unmeasured lipid species in lower-resolution studies. The approach involves (1) constructing composite lipid measures in the reference dataset that map to less resolved lipids in the target dataset, (2) addressing discrepancies between aligned lipid species, (3) generating prediction models, (4) assessing their transferability into the targe dataset, and (5) evaluating their prediction accuracy. To demonstrate our approach, we used the AusDiab population-based cohort (747 lipid species) as the reference to impute unmeasured lipid species into the LIPID study (342 lipid species). Furthermore, we compared measured and imputed lipids in terms of parameter estimation and predictive performance, and validated imputations in an independent study. Our method for harmonising plasma lipidomic datasets will facilitate model validation and data integration efforts.

Abstract Lipotoxicity, the accumulation of lipids in non-adipose tissues, alters the metabolic transcriptome and mitochondrial metabolism in skeletal muscle. The mechanisms involved remain poorly understood. Here we show that lipotoxicity increased histone deacetylase 4 (HDAC4) and histone deacetylase 5 (HDAC5), which reduced the expression of metabolic genes and oxidative metabolism in skeletal muscle, resulting in increased non-oxidative glucose metabolism. This metabolic reprogramming was also associated with impaired apoptosis and ferroptosis responses, and preserved muscle cell viability in response to lipotoxicity. Mechanistically, increased HDAC4 and 5 decreased acetylation of p53 at K120, a modification required for transcriptional activation of apoptosis. Redox drivers of ferroptosis derived from oxidative metabolism were also reduced. The relevance of this pathway was demonstrated by overexpression of loss-of-function HDAC4 and HDAC5 mutants in skeletal muscle of obese db/db mice, which enhanced oxidative metabolic capacity, increased apoptosis and ferroptosis and reduced muscle mass. This study identifies HDAC4 and HDAC5 as repressors of skeletal muscle oxidative metabolism, which is linked to inhibition of cell death pathways and preservation of muscle integrity in response to lipotoxicity.

From June to October, 2022, we recorded the weight, the internal temperature, and the hive entrance video traffic of ten managed honey bee (Apis mellifera) colonies at a research apiary of the Carl Hayden Bee Research Center in Tucson, AZ, USA. The weight and temperature were recorded every five minutes around the clock. The 30 s videos were recorded every five minutes daily from 7:00 to 20:55. We curated the collected data into a dataset of 758,703 records (280,760–weight; 322,570–temperature; 155,373–video). A principal objective of Part I of our investigation was to use the curated dataset to investigate the discrete univariate time series forecasting of hive weight, in-hive temperature, and hive entrance traffic with shallow artificial, convolutional, and long short-term memory networks and to compare their predictive performance with traditional autoregressive integrated moving average models. We trained and tested all models with a 70/30 train/test split. We varied the intake and the predicted horizon of each model from 6 to 24 hourly means. Each artificial, convolutional, and long short-term memory network was trained for 500 epochs. We evaluated 24,840 trained models on the test data with the mean squared error. The autoregressive integrated moving average models performed on par with their machine learning counterparts, and all model types were able to predict falling, rising, and unchanging trends over all predicted horizons. We made the curated dataset public for replication.

Objectives To identify the ultrasound methods used in the literature to measure traumatic scar thickness, and map gaps in the translation of these methods using evidence across the research-to-practice pipeline.Design Scoping review.Data sources Electronic database searches of Ovid MEDLINE, Embase, Cumulative Index of Nursing and Allied Health Literature and Web of Science. Grey literature searches were conducted in Google. Searches were conducted from inception (date last searched 27 May 2022).Data extraction Records using brightness mode (B-mode) ultrasound to measure scar and skin thickness across the research-to-practice pipeline of evidence were included. Data were extracted from included records pertaining to: methods used; reliability and measurement error; clinical, health service, implementation and feasibility outcomes; factors influencing measurement methods; strengths and limitations; and use of measurement guidelines and/or frameworks.Results Of the 9309 records identified, 118 were analysed (n=82 articles, n=36 abstracts) encompassing 5213 participants. Reporting of methods used was poor. B-mode, including high-frequency (ie, >20 MHz) ultrasound was the most common type of ultrasound used (n=72 records; 61% of records), and measurement of the combined epidermal and dermal thickness (n=28; 24%) was more commonly measured than the epidermis or dermis alone (n=7, 6%). Reliability of ultrasound measurement was poorly reported (n=14; 12%). The scar characteristics most commonly reported to be measured were epidermal oedema, dermal fibrosis and hair follicle density. Most records analysed (n=115; 97%) pertained to the early stages of the research-to-practice pipeline, as part of research initiatives.Conclusions The lack of evaluation of measurement initiatives in routine clinical practice was identified as an evidence gap. Diverse methods used in the literature identified the need for greater standardisation of ultrasound thickness measurements. Findings have been used to develop nine methodological considerations for practitioners to guide methods and reporting.

Fraud uses deception to obtain a financial reward from its victim. There are strong negative stereotypes and victim blaming discourses towards fraud victims, with research indicating that fraud victims are unlikely to report incidents for many reasons, including a high degree of shame and stigmatisation. In this way, it can be assumed that fraud victims are averse to seeking help in the aftermath of an incident. Drawing from romance fraud reports lodged with Scamwatch (an Australian online reporting portal for fraud) between 1 July 2018 and 31 July 2019, this article examines the help-seeking behaviours of those targeted by romance fraud. The analysis found a variety of explicit and implicit help-seeking behaviours, encompassing both personal justice and altruistic reasons. The analysis demonstrates that despite the victim blaming that exists, this did not always act as a barrier to reporting or requesting help. Overall, this article challenges some of the perceived aversity to help-seeking behaviour of fraud victims. It also provides a foundation for improving responses and support to those who actively engage in help-seeking behaviour.

Provitamin D3 is the biological precursor to naturally formed vitamin D3 in humans, and its conversion is initiated via photoexcitation by near ultraviolet light. Following an initial photolysis, the primary intermediate, known as previtamin D3, is prone to light-induced isomerization or recyclization, which creates byproducts that limit the desired final thermal conversion to vitamin D3. The branching of the photochemical reaction is highly wavelength-dependent, whereby excitation toward the blue edge of the provitamin D3 absorption spectrum tends to terminate the reaction with the most undesired tachysterol byproduct and the lowest previtamin D3 concentration. In this work, the influence of introducing the natural amino acid phenyalanine as an excitation energy donor to the photochemical reaction is investigated. We find that the incorporation of phenylalanine into provitamin D3 solution results in greater intermediate concentrations and prolonged lifetimes of the desired previtamin D3 while simultaneously reducing the final concentration of tachysterol when exposing the solution to wavelengths at the blue edge of the provitamin D3 spectrum. The results, coupled with quantum chemical analysis, suggest that phenylalanine indeed helps to funnel energy from shorter wavelengths more effectively into the provitamin D3 precursor, while simultaneously screening those wavelengths from direct excitation, which otherwise leads to enhanced concentrations of tachysterol byproduct at the expense of previtamin D3.

Abstract Recently developed Long (≥100 cm) axial field of view (AFOV) PET/CT scanners are capable of producing images with higher signal‐to‐noise ratio, or performing faster whole‐body acquisitions, or scanning with lower radiation dose to the patient, compared with conventional PET/CT scanners. These benefits, which arise due to their substantially higher, by more than an order of magnitude, geometric efficiency, have been well described in the recent literature. The introduction of Long AFOV PET/CT technology into the clinic also has important implications for the design and workflow of PET/CT facilities and their effects on radiation exposure to staff and patients. Maximising the considerable benefits of this technology requires a thorough understanding of the relationships between these factors to optimise workflows while appropriately managing radiation exposure. This article reviews current knowledge on PET/CT facility design, workflows and their effects on radiation exposure, identifies gaps in the literature and discusses the challenges that need to be considered with the introduction of Long AFOV PET/CT into the clinic.

BackgroundProlapse recurrence after transvaginal surgical repair is common; however, its mechanisms are ill-defined. A thorough understanding of how and why prolapse repairs fail is needed to address their high rate of anatomic recurrence and to develop novel therapies to overcome defined deficiencies.ObjectiveThis study aimed to identify mechanisms and contributors of anatomic recurrence after vaginal hysterectomy with uterosacral ligament suspension (native tissue repair) vs transvaginal mesh (VM) hysteropexy surgery for uterovaginal prolapse.Study designThis multicenter study was conducted in a subset of participants in a randomized clinical trial by the Eunice Kennedy Shriver National Institute of Child Health and Human Development Pelvic Floor Disorders Network. Overall, 94 women with uterovaginal prolapse treated via native tissue repair (n=48) or VM hysteropexy (n=46) underwent pelvic magnetic resonance imaging at rest, maximal strain, and poststrain rest (recovery) 30 to 42 months after surgery. Participants who desired reoperation before 30 to 42 months were imaged earlier to assess the impact of the index surgery. Using a novel 3-dimensional pelvic coordinate system, coregistered midsagittal images were obtained to assess study outcomes. Magnetic resonance imaging-based anatomic recurrence (failure) was defined as prolapse beyond the hymen. The primary outcome was the mechanism of failure (apical descent vs anterior vaginal wall elongation), including the frequency and site of failure. Secondary outcomes included displacement of the vaginal apex and perineal body and change in the length of the anterior wall, posterior wall, vaginal perimeter, and introitus of the vagina from rest to strain and rest to recovery. Group differences in the mechanism, frequency, and site of failure were assessed using the Fisher exact tests, and secondary outcomes were compared using Wilcoxon rank-sum tests.ResultsOf the 88 participants analyzed, 37 (42%) had recurrent prolapse (VM hysteropexy, 13 of 45 [29%]; native tissue repair, 24 of 43 [56%]). The most common site of failure was the anterior compartment (VM hysteropexy, 38%; native tissue repair, 92%). The primary mechanism of recurrence was apical descent (VM hysteropexy, 85%; native tissue repair, 67%). From rest to strain, failures (vs successes) had greater inferior displacement of the vaginal apex (difference, -12 mm; 95% confidence interval, -19 to -6) and perineal body (difference, -7 mm; 95% confidence interval, -11 to -4) and elongation of the anterior vaginal wall (difference, 12 mm; 95% confidence interval, 8-16) and vaginal introitus (difference, 11 mm; 95% confidence interval, 7-15).ConclusionThe primary mechanism of prolapse recurrence following vaginal hysterectomy with uterosacral ligament suspension or VM hysteropexy was apical descent. In addition, greater inferior descent of the vaginal apex and perineal body, lengthening of the anterior vaginal wall, and increased size of the vaginal introitus with strain were associated with anatomic failure. Further studies are needed to provide additional insight into the mechanism by which these factors contribute to anatomic failure.

ObjectiveLow HDL-C (high-density lipoprotein cholesterol) is the most frequent dyslipidemia in Mexicans, but few studies have examined the underlying genetic basis. Our purpose was to identify genetic variants associated with HDL-C levels and cardiovascular risk in the Mexican population.Approach and resultsA genome-wide association studies for HDL-C levels in 2335 Mexicans, identified four loci associated with genome-wide significance: CETP, ABCA1, LIPC, and SIDT2. The SIDT2 missense Val636Ile variant was associated with HDL-C levels and was replicated in 3 independent cohorts (P=5.9×10−18 in the conjoint analysis). The SIDT2/Val636Ile variant is more frequent in Native American and derived populations than in other ethnic groups. This variant was also associated with increased ApoA1 and glycerophospholipid serum levels, decreased LDL-C (low-density lipoprotein cholesterol) and ApoB levels, and a lower risk of premature CAD. Because SIDT2 was previously identified as a protein involved in sterol transport, we tested whether the SIDT2/Ile636 protein affected this function using an in vitro site-directed mutagenesis approach. The SIDT2/Ile636 protein showed increased uptake of the cholesterol analog dehydroergosterol, suggesting this variant affects function. Finally, liver transcriptome data from humans and the Hybrid Mouse Diversity Panel are consistent with the involvement of SIDT2 in lipid and lipoprotein metabolism.ConclusionsThis is the first genome-wide association study for HDL-C levels seeking associations with coronary artery disease in the Mexican population. Our findings provide new insight into the genetic architecture of HDL-C and highlight SIDT2 as a new player in cholesterol and lipoprotein metabolism in humans.

Abstract Placing honey bee colonies in cold storage has been proposed as a way to induce a pause in brood production as part of a Varroa mite treatment plan. Here, we exposed colonies to combinations of with or without an October cold storage period and with or without a subsequent miticide application. We then measured the effects of those treatments on colony-level variables (i.e. colony size, Varroa infestation level, survivorship and hive weight and temperature) and pooled individual-level variables that are associated with nutritional and stress responses. Colonies were assessed before and after cold storage, and again post winter, for a total duration of about 5 months, and the experiment was repeated. Brood levels were significantly lower after cold storage, and hive temperatures indicated that most or all brood had emerged after about two weeks in cold storage. However, Varroa levels at the end of the experiments in February were not significantly different among treatment groups. Colonies kept outside (not subjected to cold storage) and treated with a miticide had higher survivorship on average than any other treatment group, but no other group comparisons were significant, and long-term impact of cold storage on adult bee populations and on colony thermoregulation was low. The bee forage environment was also very different between the 2 years of the study, as rainfall and bee forage availability were much higher the second year. Colonies were over 2.5 times larger on average the second year compared to the first, both in terms of adult bee mass and brood area, and expression levels of nutrition and stress response genes were also significantly higher the second year. The results indicate that limited cold storage would likely have little long-term impact on most colony and individual measures of health, but for such a strategy to succeed levels of stressors, such as Varroa, may also need to be low.

Summary: Background: Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are neurodevelopmental conditions with early life origins. Alterations in blood lipids have been linked to ADHD and ASD; however, prospective early life data are limited. This study examined (i) associations between the cord blood lipidome and ADHD/ASD symptoms at 2 years of age, (ii) associations between prenatal and perinatal predictors of ADHD/ASD symptoms and cord blood lipidome, and (iii) mediation by the cord blood lipidome. Methods: From the Barwon Infant Study cohort (1074 mother-child pairs, 52.3% male children), child circulating lipid levels at birth were analysed using ultra-high-performance liquid chromatography-tandem mass spectrometry. These were clustered into lipid network modules via Weighted Gene Correlation Network Analysis. Associations between lipid modules and ADHD/ASD symptoms at 2 years, assessed with the Child Behavior Checklist, were explored via linear regression analyses. Mediation analysis identified indirect effects of prenatal and perinatal risk factors on ADHD/ASD symptoms through lipid modules. Findings: The acylcarnitine lipid module is associated with both ADHD and ASD symptoms at 2 years of age. Risk factors of these outcomes such as low income, Apgar score, and maternal inflammation were partly mediated by higher birth acylcarnitine levels. Other cord blood lipid profiles were also associated with ADHD and ASD symptoms. Interpretation: This study highlights that elevated cord blood birth acylcarnitine levels, either directly or as a possible marker of disrupted cell energy metabolism, are on the causal pathway of prenatal and perinatal risk factors for ADHD and ASD symptoms in early life. Funding: The foundational work and infrastructure for the BIS was sponsored by the Murdoch Children's Research Institute, Deakin University, and Barwon Health. Subsequent funding was secured from the Minderoo Foundation, the European Union's Horizon 2020 research and innovation programme (ENDpoiNTs: No 825759), National Health and Medical Research Council of Australia (NHMRC) and Agency for Science, Technology and Research Singapore [APP1149047], The William and Vera Ellen Houston Memorial Trust Fund (via HOMER Hack), The Shepherd Foundation, The Jack Brockhoff Foundation, the Scobie & Claire McKinnon Trust, the Shane O'Brien Memorial Asthma Foundation, the Our Women Our Children's Fund Raising Committee Barwon Health, the Rotary Club of Geelong, the Ilhan Food Allergy Foundation, Geelong Medical and Hospital Benefits Association, Vanguard Investments Australia Ltd, the Percy Baxter Charitable Trust, and Perpetual Trustees.

HDL particles vary in lipidome and proteome, which dictate their individual physicochemical properties, metabolism, and biological activities. HDL dysmetabolism in nondiabetic hypertriglyceridemia (HTG) involves subnormal HDL-cholesterol and apoAI levels. Metabolic anomalies may impact the qualitative features of both the HDL lipidome and proteome. Whether particle content of bioactive lipids and proteins may differentiate HDL subclasses (HDL2b, 2a, 3a, 3b, and 3c) in HTG is unknown. Moreover, little is known of the effect of statin treatment on the proteolipidome of hypertriglyceridemic HDL and its subclasses. Nondiabetic, obese, HTG males (n = 12) received pitavastatin calcium (4 mg/day) for 180 days in a single-phase, unblinded study. ApoB-containing lipoproteins were normalized poststatin. Individual proteolipidomes of density-defined HDL subclasses were characterized prestatin and poststatin. At baseline, dense HDL3c was distinguished by marked protein diversity and peak abundance of surface lysophospholipids, amphipathic diacylglycerol and dihydroceramide, and core cholesteryl ester and triacylglycerol, (normalized to mol phosphatidylcholine), whereas light HDL2b showed peak abundance of free cholesterol, sphingomyelin, glycosphingolipids (monohexosylceramide, dihexosylceramide, trihexosylceramide, and anionic GM3), thereby arguing for differential lipid transport and metabolism between subclasses. Poststatin, bioactive lysophospholipid (lysophosphatidylcholine, lysoalkylphosphatidylcholine, lysophosphatidylethanolamine, and lysophosphatidylinositol) cargo was preferentially depleted in HDL3c. By contrast, baseline lipidomic profiles of ceramide, dihydroceramide and related glycosphingolipids, and GM3/phosphatidylcholine were maintained across particle subclasses. All subclasses were depleted in triacylglycerol and diacylglycerol/phosphatidylcholine. The abundance of apolipoproteins CI, CII, CIV, and M diminished in the HDL proteome. Statin treatment principally impacts metabolic remodeling of the abnormal lipidome of HDL particle subclasses in nondiabetic HTG, with lesser effects on the proteome.