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Background: As patients interact with a healthcare service system, patterns of service utilization (PSUs) emerge. These PSUs are embedded in the sparse high-dimensional space of longitudinal cross-continuum health service encounter data. Once extracted, PSUs can provide quality assurance/quality improvement (QA/QI) efforts with the information required to optimize service system structures and functions. This may improve outcomes for complex patients with chronic diseases. Method: Working with longitudinal cross-continuum encounter data from a regional health service system, various pattern detection analyses were conducted, employing (1) graph community detection algorithms, (2) natural language processing (NLP) clustering, and (3) a hybrid NLP–graph method. Result: These approaches produced similar PSUs, as determined from a clinical perspective by clinical subject matter experts and service system operations experts. Conclusions: The similarity in the results provides validation for the methodologies. Moreover, the results stress the need to engage with clinical or service system operations experts, both in providing the taxonomies and ontologies of the service system, the cohort definitions, and determining the level of granularity that produces the most clinically meaningful results. Finally, the uniqueness of each approach provides an opportunity to take advantage of the various analytical capabilities that each approach brings, which will be further explored in our future research.

Abstract Global demand for food is expected to nearly double by 2050. Alternative proteins (AP) have been proposed as a sustainable solution to provide food security as natural resources become more depleted. However, the growth and consumer intake of AP remains limited. This review aims to better understand the challenges and environmental impacts of four main AP categories: plant-based, insect-based, microbe-derived, and cultured meat and seafood. The environmental benefits of plant-based and insect-based proteins have been documented but the impacts of microbe-derived proteins and cultured meat have not been fully assessed. The development of alternative products with nutritional and sensory profiles similar to their conventional counterparts remains highly challenging. Furthermore, incomplete safety assessments and a lack of clear regulatory guidelines confuse the food industry and hamper progress. Much still needs to be done to fully support AP utilization within the context of supporting the drive to make the global food system sustainable.

Abstract We have previously identified a network of higher-order brain regions particularly vulnerable to the ageing process, schizophrenia and Alzheimer’s disease. However, it remains unknown what the genetic influences on this fragile brain network are, and whether it can be altered by the most common modifiable risk factors for dementia. Here, in ~40,000 UK Biobank participants, we first show significant genome-wide associations between this brain network and seven genetic clusters implicated in cardiovascular deaths, schizophrenia, Alzheimer’s and Parkinson’s disease, and with the two antigens of the XG blood group located in the pseudoautosomal region of the sex chromosomes. We further reveal that the most deleterious modifiable risk factors for this vulnerable brain network are diabetes, nitrogen dioxide – a proxy for traffic-related air pollution – and alcohol intake frequency. The extent of these associations was uncovered by examining these modifiable risk factors in a single model to assess the unique contribution of each on the vulnerable brain network, above and beyond the dominating effects of age and sex. These results provide a comprehensive picture of the role played by genetic and modifiable risk factors on these fragile parts of the brain.

Harmful Algal Blooms (HABs) are outbreaks of aquatic toxic microalgae emerging as a global problem driven by nutrient enrichment, global climate change and invasive species. We uniquely describe a HAB of unprecedented duration, extent and magnitude during 2023 in Lough Neagh; the UK and Ireland’s largest freshwater lake, using an unparalleled combination of satellite imagery, nutrient analysis, 16S rRNA gene sequencing and cyanotoxin profiling. The causative agent Microcystis aeruginosa accounted for over a third of DNA in water samples though common bacterioplankton species also bloomed. Water phosphate levels were hypertrophic and drove local algal biomass. The HAB pervaded the entire ecosystem with algal mats accumulating around jetties, marinas and lock gates. Over 80 % of bacterial DNA isolated from algal mat samples consisted of species associated with wildfowl or livestock faeces and human-effluent wastewater including 13 potential pathogens that can cause serious human illness including: E. coli, Salmonella, Enterobacter and Clostridium among others. Ten microcystins, nodularin and two anabaenopeptin toxins were confirmed as present (with a further microcystin and four anabaenopeptins suspected), with MC-RR and -LR in high concentrations at some locations (1,137–18,493 μg/L) with MC-LR exceeding World Health Organisation (WHO) recreational exposure guidelines in all algal mats sampled. This is the first detection of anabaenopeptins in any waterbody on the island of Ireland. Notwithstanding the ecological impacts, this HAB represented an environmental and public health risk, curtailing recreational activities in-and-around the lake and damaging local businesses. Reducing agricultural runoff and discharge from human-effluent wastewater treatment to manage nutrient loading, and the public health risk, should be the top priority of stakeholders, especially government. Key recommendations include Nature-based Solutions that avoid conflict with the productivity and profitability of the farming sector enhancing sustainability. We hope this stimulates real-world action to resolve the problems besetting this internationally important ecosystem.

BackgroundDigital technologies can assist and optimize health care processes. This is increasingly the case in the musculoskeletal health domain, where digital platforms can be used to support the self-management of musculoskeletal conditions, as well as access to services. However, given a large proportion of the population with musculoskeletal conditions are older adults (aged ≥60 years), it is important to consider the acceptability of such platforms within this demographic. ObjectiveThis study aims to explore participants’ opinions and perceptions on the use of digital platforms for supporting the self-management of musculoskeletal conditions within older adult (aged ≥60 years) populations and to gather their opinions on real examples. MethodsA total of 2 focus groups (focus group 1: 6/15, 40%; focus group 2: 9/15, 60%) were conducted, in which participants answered questions about their thoughts on using digital health platforms to prevent or manage musculoskeletal conditions. Participants were further presented with 2 example scenarios, which were then discussed. Interviews were audio recorded, transcribed, and analyzed thematically. Participants were aged ≥60 years and with or without current musculoskeletal conditions. Prior experience of using smartphone apps or other digital health platforms for musculoskeletal conditions was not required. Focus groups took place virtually using the Teams (Microsoft Corp) platform. ResultsA total of 6 themes were identified across both focus groups: “experiences of digital health platforms,” “preference for human contact,” “barriers to accessing clinical services,” “individual differences and digital literacy,” “trust in technology,” and “features and benefits of digital health technologies.” Each theme is discussed in detail based on the interview responses. The findings revealed that most participants had some existing experience with digital health platforms for preventing or managing musculoskeletal conditions. Overall, there was a lack of trust in and low expectations of quality for digital platforms for musculoskeletal health within this age group. While there was some concern about the use of digital platforms in place of in-person health consultations, several benefits were also identified. ConclusionsResults highlighted the need for better communication on the benefits of using digital platforms to support the self-management of musculoskeletal conditions, without the platforms replacing the role of the health care professionals. The concerns about which apps are of suitable quality and trustworthiness lead us to recommend raising public awareness around the role of organizations that verify and assess the quality of digital health platforms.

Halloumi cheese has recently gained a Protected Designation of Origin (PDO) indicator, which is related to the place (Cyprus) in which halloumi cheese is made. The PDO label is linked with several requirements, e.g., milk species, quantities, etc.; thus, it is important to study this product regarding authenticity. The utility of using two spectroscopic techniques, hyperspectral imaging (HSI) (400–1000 nm) and conventional near-infrared spectroscopy (NIR) (800–2500 nm) were assessed for the discrimination of 17 Cypriot halloumi cheese types, which could be categorized as of cow or goat–sheep origin. The aim of this study was to obtain spectral information for halloumi cheese using other promising infrared and imaging spectroscopic techniques as a comparison to a previously acquired mid-infrared (MIR) spectroscopy dataset. NIR and HSI are both fast and easy techniques in application, both of which provide significant information in food analysis. Chemometric analysis was crucial for interpreting the spectroscopic data by applying the unsupervised methods: principal component analysis (PCA) and hierarchical cluster analysis (HCA). The HSI model was found to be based intuitively on the appearance of cheese samples after freeze-drying (e.g., color; yellow/white, and texture; oily/dry), while the NIR grouping of samples was determined to be based on composition, mainly fat, protein and lactose content of the cheese samples. The HSI model returned distinct clusters of the two halloumi cheese types, cow and goat–sheep origin, with one outlier (16/17 accuracy; 94%), while the NIR model proved less accurate (13/17; 76%).

Abstract Food consumption play a crucial role in human life, yet conventional food production and consumption patterns can be detrimental to the environment. Thus, research and development has been directed towards alternative proteins, with edible insects being promising sources. Edible insects have been recognised for their sustainable benefits providing protein, with less emission of greenhouse gas, land and water usage compared to sources, such as beef, chicken, and dairy products. Among the over 2000 known edible insect species, only four, namely yellow mealworm (Tenebrio molitor), migratory locust/grasshopper (Locusta migratoria), grain mould beetle, also known as lesser mealworm which is a larval form of Alphitobius diaperinus (from the family of Tenebrionidae of darkling beetles) and house cricket (Acheta domesticus), are currently authorised in specific products through specific producers in the EU. The expansion of such foods into Western diets face challenges such as consumer barriers, gaps in microbiological and chemical safety hazard data during production and processing, and the potential for fraudulent supply chain activity. The main aim of this study was to map the supply chain, through interviews with personnel along the supply chain, coupled with searches for relevant publications and governmental documents. Thus, the main potential points of food safety and fraud along the edible insect supply chain were identified. Feed substrate was identified as the main area of concern regarding microbiological and chemical food safety and novel processing techniques were forecast to be of most concern for future fraudulent activity. Despite the on-going authorisation of insect species in many countries there are substantial food safety and authenticity information gaps in this industry that need to be addressed before edible insects can be viewed as a safe and sustainable protein sources by Western consumers.

Objective The COVID-19 pandemic accelerated changes to clinical research methodology, with clinical studies being carried out via online/remote means. This mixed-methods study aimed to identify which digital tools are currently used across all stages of clinical research by stakeholders in clinical, health and social care research and investigate their experience using digital tools.Design Two online surveys followed by semistructured interviews were conducted. Interviews were audiorecorded, transcribed and analysed thematically.Setting, participants To explore the digital tools used since the pandemic, survey participants (researchers and related staff (n=41), research and development staff (n=25)), needed to have worked on clinical, health or social care research studies over the past 2 years (2020–2022) in an employing organisation based in the West Midlands region of England (due to funding from a regional clinical research network (CRN)). Survey participants had the opportunity to participate in an online qualitative interview to explore their experiences of digital tools in greater depth (n=8).Results Six themes were identified in the qualitative interviews: ‘definition of a digital tool in clinical research’; ‘impact of the COVID-19 pandemic’; ‘perceived benefits/drawbacks of digital tools’; ‘selection of a digital tool’; ‘barriers and overcoming barriers’ and ‘future digital tool use’. The context of each theme is discussed, based on the interview results.Conclusions Findings demonstrate how digital tools are becoming embedded in clinical research, as well as the breadth of tools used across different research stages. The majority of participants viewed the tools positively, noting their ability to enhance research efficiency. Several considerations were highlighted; concerns about digital exclusion; need for collaboration with digital expertise/clinical staff, research on tool effectiveness and recommendations to aid future tool selection. There is a need for the development of resources to help optimise the selection and use of appropriate digital tools for clinical research staff and participants.

Metabolic dysfunctions are among the best documented hallmarks of ageing. Cardiovascular disease, Alzheimer’s disease, cancer, type 2 diabetes mellitus, metabolic-dysfunction-associated steatosis liver disease, and fragility fractures are diseases of hyperinsulinaemia that reduce life and healthspan. We studied the effect of suppressing ketosis in 10 lean (BMI 20.5 kg/m2 ± 1.4), metabolically healthy, pre-menopausal women (age 32.3 ± 8.9 years) maintaining nutritional ketosis (NK) for an average of 3.9 years (± 2.3) who underwent three 21-day phases: nutritional ketosis (NK; P1), suppressed ketosis (SuK; P2), and returned to NK (P3). Ketosis suppression significantly increased insulin, 1.83-fold (p = 0.0006); glucose, 1.17-fold (p = 0.0088); homeostasis model assessment for insulin resistance (HOMA-IR), 2.13-fold (p = 0.0008); leptin, 3.35-fold (p = 0.0010); total osteocalcin, 1.63-fold (p = 0.0138); and uncarboxylated osteocalcin, 1.98-fold (p = 0.0417) and significantly decreased beta-hydroxybutyrate, 13.50-fold (p = 0.0012) and glucagon-like peptide-1 (GLP-1), 2.40-fold (p = 0.0209). Sustained NK showed no adverse health effects and may mitigate hyperinsulinemia. All biomarkers returned to basal P1 levels after removing the intervention for SuK, indicating that metabolic flexibility was maintained with long-term euketonaemia.

Abstract Risk communication is defined as the interactive exchange of information and opinions concerning risk, risk-related factors and risk perceptions amongst all the stakeholders of food safety throughout the risk analysis process. The interactive exchange of information occurs at three different levels i.e. informed level, dialogue level and engagement level. For an effective food safety risk communication (FSRC), it is important that the information should adhere to the core principles of risk communication which are transparency, openness, responsiveness and timeliness. Communication of a food safety risk within all the components of risk communication strategy constitutes a complex network of information flow that can be better understood with the help of a framework. Therefore, a model framework to communicate the risks associated with aflatoxins (AFs) dietary intake has been developed with the aim of (a) creating general awareness amongst public and (b) involving industry stakeholders in the prevention and control of risk. The framework has been motivated by the learnings and best practices outlined in the identified technical guidance documents for risk communication. Risk assessors, risk managers, industry stakeholders and general public have been identified as the major stakeholders for the present framework. Amongst them, industry stakeholders and general public has been selected as the major target audience for risk managers. Moreover, population residing in low- and middle-income countries (LMIC) has been identified as the main target group to reach.

Abstract Objective: The school food environment (SFE) is an ideal setting for encouraging healthy dietary behaviour. We aimed to develop an instrument to assess whole-SFE, test the instrument in the school setting and demonstrate its use to make food environment recommendations. Design: SFE literature and UK school food guidance were searched to inform instrument items. The instrument consisted of (i) an observation proforma capturing canteen areas systems, food presentation and monitoring of food intake and (ii) a questionnaire assessing food policies, provision and activities. The instrument was tested in schools and used to develop SFE recommendations. Descriptive analyses enabled narrative discussion. Setting: Primary schools. Participants: An observation was undertaken at schools in urban and rural geographical regions of Northern Ireland of varying socio-economic status (n 18). School senior management completed the questionnaire with input from school caterers (n 16). Results: The instrument captured desired detail and potential instrument modifications were identified. SFE varied. Differences existed between food policies and how policies were implemented and monitored. At many schools, there was scope to enhance physical eating environments (n 12, 67 %) and food presentation (n 15, 83 %); emphasise healthy eating through food activities (n 7, 78 %) and increase parental engagement in school food (n 9, 56 %). Conclusions: The developed instrument can measure whole-SFE in primary schools and also enabled identification of recommendations to enhance SFE. Further assessment and adaptation of the instrument are required to enable future use as a research tool or for self-assessment use by schools.

Abstract A mid-level data fusion coupled with multivariate analysis approach is applied to dual-platform mass spectrometry data sets using Rapid Evaporative Ionization Mass Spectrometry and Inductively Coupled Plasma Mass Spectrometry to determine the correct classification of salmon origin and production methods. Salmon (n = 522) from five different regions and two production methods are used in the study. The method achieves a cross-validation classification accuracy of 100% and all test samples (n = 17) have their origins correctly determined, which is not possible with single-platform methods. Eighteen robust lipid markers and nine elemental markers are found, which provide robust evidence of the provenance of the salmon. Thus, we demonstrate that our mid-level data fusion - multivariate analysis strategy greatly improves the ability to correctly identify the geographical origin and production method of salmon, and this innovative approach can be applied to many other food authenticity applications.

A wide-field imaging system uses birefringence to efficiently permit quantitative fluorophore concentration mapping, with clear relevance for neurosurgery.

Mitochondria are key tumor drivers, but their suitability as a therapeutic target is unknown. Here, we report on the preclinical characterization of Gamitrinib (GA mitochondrial matrix inhibitor), a first-in-class anticancer agent that couples the Heat Shock Protein-90 (Hsp90) inhibitor 17-allylamino-geldanamycin (17-AAG) to the mitochondrial-targeting moiety, triphenylphosphonium. Formulated as a stable (≥24 weeks at −20°C) injectable suspension produced by microfluidization (99.5% purity) is heavily bound to plasma proteins (>99%), has intrinsic clearance from liver microsomes of 3.30 mL/min/g and minimally penetrates a Caco-2 intestinal monolayer. Compared to 17-AAG, Gamitrinib has slower clearance (85.6 ± 5.8 mL/min/kg), longer t1/2 (12.2 ± 1.55 h), mean AUC0-t of 783.1 ± 71.3 h∙ng/mL, and unique metabolism without generation of 17-AG. Concentrations of Gamitrinib that trigger tumor cell killing (IC50 ~1-4 µM) do not affect cytochrome P450 isoforms CYP1A2, CYP2A6, CYP2B6, CYP2C8 or ion channel conductance (Nav1.5, Kv4.3/KChIP2, Cav1.2, Kv1.5, KCNQ1/mink, HCN4, Kir2). Twice weekly IV administration of Gamitrinib to Sprague-Dawley rats or beagle dogs for up to 36 d is feasible. At dose levels of up to 5 (rats)- and 12 (dogs)-fold higher than therapeutically effective doses in mice (10 mg/kg), Gamitrinib treatment is unremarkable in dogs with no alterations in clinical-chemistry parameters, heart function, or tissue histology, and causes occasional inflammation at the infusion site and mild elevation of serum urea nitrogen in rats (≥10 mg/kg/dose). Therefore, targeting mitochondria for cancer therapy is feasible and well tolerated. A publicly funded, first-in-human phase I clinical trial of Gamitrinib in patients with advanced cancer is ongoing (ClinicalTrials.gov NCT04827810)

Abstract Colorectal cancer (CRC) is the second most prevelant malignancy in Europe and diet is an important modifiable risk factor. Processed meat consumption, including meats with preservative salts such as sodium nitrite, have been implicated in CRC pathogenesis. This study investigated how the CRC pathology and metabolic status of adenomatous polyposis coli (APC) multiple intestinal neoplasia (min) mice was perturbed following 8 weeks of pork meat consumption. Dietary inclusions (15%) of either nitrite-free pork, nitrite-free sausage, or nitrite-containing sausage (frankfurter) were compared against a parallel control group (100% chow). Comprehensive studies investigated: gastrointestinal tract histology (tumours), aberrant crypt foci (ACF), mucin deplin foci (MDF), lipid peroxidation (urine and serum), faecal microbiota, and serum metabolomics (599 metabolites). After 8 weeks mice consuming the frankfurter diet had 53% more (P = 0.014) gastrointestinal tumours than control, although ACF and MDF did not differ. Urine and serum lipid peroxidation markers were 59% (P = 0.001) and 108% (P = 0.001) higher, respectively in the frankfurter group. Gut dysbiosis was evident in these mice with comparably fewer Bacteriodes and more Firmicutes. Fasting serum levels of trimethylamine N-oxide (TMAO) and numerous triglycerides were elevated. Various serum phosphotidylcholine species were decreased. These results demonstrate that nitrite-containing sausages may exaccerbate the development of CRC pathology in APCMin mice to a greater extent than nitrite-free sausages, and this is associated with greater lipid peroxidation, wide-ranging metabolic alternation and gut dysbiosis.

Abstract As an important spice, ginger has been widely distributed in the Chinese and the European Union (EU) markets, the two largest trading areas, in various forms. The ginger supply chain between China and the EU is long and complex, providing opportunities for fraudsters to deceive consumers. However, limited attention has been given to food fraud in ginger, and there is a lack of research on this topic. In this review, ginger was used as an example for interpreting the fraud issues within low-priced and high-trade volume spice products. This review aims to summarize the open access information from food and food fraud databases, literature, and stakeholders about ginger fraud, and to map, deconstruct and analyse the food fraud vulnerability in the supply chain. In addition, potential testing strategies to detect ginger fraud were also discussed. The investigation of food fraud databases, a semi-structured literature review and online interviews with stakeholders revealed that adulteration is the major fraud type in ginger products. And the most vulnerable ginger products are ground ginger and finely processed ginger. The ginger supply chain from China to the EU comprises nine stages and is medium vulnerable to food fraud, both in regard to opportunities and motivational drivers. To ensure the integrity of the ginger supply chain, there is a need to apply fraud vulnerability tools in the companies of the industry. In addition, screening and confirmatory techniques based on the characteristics of ginger should be utilised for monitoring fraud issues in the supply chain.

Deep learning has increasingly been applied to supervised learning tasks in astronomy, such as classifying images of galaxies based on their apparent shape (i.e., galaxy morphology classification) to gain insight regarding the evolution of galaxies. In this work, we examine the effect of pretraining on the performance of the classical AlexNet convolutional neural network (CNN) in classifying images of 14,034 galaxies from the Sloan Digital Sky Survey Data Release 4. Pretraining involves designing and training CNNs on large labeled image datasets unrelated to astronomy, which takes advantage of the vast amounts of such data available compared to the relatively small amount of labeled galaxy images. We show a statistically significant benefit of using pretraining, both in terms of improved overall classification success and reduced computational cost to achieve such performance.

There is a growing demand from consumers for more assurance in premium food products such as beef and especially steak. The quality of beef steak is primarily dictated by the maturation which ultimately influences its taste and flavor. These enhanced qualities have resulted in steak becoming a premium product that consumers are willing to pay a premium price for. A challenge, however, is analyzing the maturity of beef by traditional analytical techniques. Hyperspectral imaging (HSI) is a methodology that is gaining traction mainly due to miniaturization, improved optics, and software. In this study, HSI was applied to wet aged beef supplied at various stages of maturity, with spectral data generated using a portable hyperspectral camera. Two trials were conducted over a five-month period: (i) proof of principle and (ii) a bespoke sampling trial for the industry. With the support of industry participation, all samples were sourced from a highly reputable UK/Ireland supplier. To enhance data interpretation, the spectral data collected were combined with multivariate analysis. A range of chemometric models were generated using unsupervised and supervised methods to determine the maturity of the beef, and external validation was performed. The external validation showed good accuracy for “unknown samples” tested against the model set and ranged from 74 to 100% for the different stages of maturity (20, 30, and 40 days old). This study demonstrated that HSI can detect different maturity timepoints for beef samples, which could play an important role in solving some of the challenges that the industry faces with ensuring the authenticity of their products. This is the first time that portable HSI has been coupled with chemometric modeling for assessing the maturity of beef, and it can serve as a model for other food authenticity and quality applications.

Progress in the management of rare diseases, including rare cancers, is dependent upon clinical trials; however, as many as 32% of rare-disease trials go uncompleted or unpublished due to insufficient accrual. Monitoring practices may differ between institutions. We sought to survey the regulatory standards for various trial types among major U.S. cancer centers. A 10-question survey was designed using Qualtrics assessment software. The survey was sent via email to an internal server of member institutions of the Association of American Cancer Institutes (AACI). Of 103 AACI centers, 31% completed the survey (n = 32). Respondents differed in their definitions of a rare disease, minimum expectations for rare tumor studies, and frequency of accrual monitoring by their institutional Protocol Review and Monitoring Committee. Seventy-three percent of respondents did not close trials based on low accrual. Strategies to optimize accrual included investigator incentives for high accrual and penalties for low accrual in 37% and 13% of respondents, respectively.

Abstract Fermented foods (ffs) and beverages are widely consumed in Southeast Asia (SEA) for their nutritional balance, flavor, and food security. They serve as vehicles for beneficial microorganisms performing a significant role in human health. However, there are still major challenges concerning the safety of ffs and beverages due to the presence of natural toxins. In this review, the common toxins found in traditional ffs in SEA are discussed with special reference to mycotoxins and plant toxins. Also, mitigation measures for preventing risks associated with their consumption are outlined. Ochratoxin, citrinin, aflatoxins were reported to be major mycotoxins present in SEA ffs. In addition, soybean-based ff food products were more vulnerable to mycotoxin contaminations. Common plant toxins recorded in ffs include cyanogenic glycosides, oxalates, phytates and saponins. Combined management strategies such as pre-harvest, harvest and post-harvest control and decontamination, through the integration of different control methods such as the use of clean seeds, biological control methods, fermentation, appropriate packaging systems, and controlled processing conditions are needed for the safe consumption of indigenous ffs in SEA.

Neuroinflammation driven primarily by microglia directly contributes to neuronal death in many neurodegenerative diseases. Classical anti-inflammatory approaches aim to suppress pro-inflammatory mediator production, but exploitation of inflammatory resolution may also be of benefit. A key driver of peripheral inflammatory resolution, formyl peptide receptor 2 (Fpr2), is expressed by microglia, but its therapeutic potential in neurodegeneration remains unclear. Here, we studied whether targeting of Fpr2 could reverse inflammatory microglial activation induced by the potent bacterial inflammogen lipopolysaccharide (LPS). Exposure of murine primary or immortalised BV2 microglia to LPS triggered pro-inflammatory phenotypic change and activation of ROS production, effects significantly attenuated by subsequent treatment with the Fpr2 agonist C43. Mechanistic studies showed C43 to act through p38 MAPK phosphorylation and reduction of LPS-induced NFκB nuclear translocation via prevention of IκBα degradation. Here, we provide proof-of-concept data highlighting Fpr2 as a potential target for control of microglial pro-inflammatory activity, suggesting that it may be a promising therapeutic target for the treatment of neuroinflammatory disease.

Most studies on ketosis have focused on short-term effects, male athletes, or weight loss. Hereby, we studied the effects of short-term ketosis suppression in healthy women on long-standing ketosis. Ten lean (BMI 20.5 ± 1.4), metabolically healthy, pre-menopausal women (age 32.3 ± 8.9) maintaining nutritional ketosis (NK) for > 1 year (3.9 years ± 2.3) underwent three 21-day phases: nutritional ketosis (NK; P1), suppressed ketosis (SuK; P2), and returned to NK (P3). Adherence to each phase was confirmed with daily capillary D-beta-hydroxybutyrate (BHB) tests (P1 = 1.9 ± 0.7; P2 = 0.1 ± 0.1; and P3 = 1.9 ± 0.6 pmol/L). Ageing biomarkers and anthropometrics were evaluated at the end of each phase. Ketosis suppression significantly increased: insulin, 1.78-fold from 33.60 (± 8.63) to 59.80 (± 14.69) pmol/L (p = 0.0002); IGF1, 1.83-fold from 149.30 (± 32.96) to 273.40 (± 85.66) µg/L (p = 0.0045); glucose, 1.17-fold from 78.6 (± 9.5) to 92.2 (± 10.6) mg/dL (p = 0.0088); respiratory quotient (RQ), 1.09-fold 0.66 (± 0.05) to 0.72 (± 0.06; p = 0.0427); and PAI-1, 13.34 (± 6.85) to 16.69 (± 6.26) ng/mL (p = 0.0428). VEGF, EGF, and monocyte chemotactic protein also significantly increased, indicating a pro-inflammatory shift. Sustained ketosis showed no adverse health effects, and may mitigate hyperinsulinemia without impairing metabolic flexibility in metabolically healthy women.

In the pursuit of longevity and healthspan, we are challenged with first overcoming chronic diseases of ageing: cardiovascular disease, hypertension, cancer, dementias, type 2 diabetes mellitus. These are hyperinsulinaemia diseases presented in different tissue types. Hyperinsulinaemia reduces endogenous antioxidants, via increased consumption and reduced synthesis. Hyperinsulinaemia enforces glucose fuelling, consuming 4 NAD+ to produce 2 acetyl moieties; beta-oxidation, ketolysis and acetoacetate consume 2, 1 and 0, respectively. This decreases sirtuin, PARPs and oxidative management capacity, leaving reactive oxygen species to diffuse to the cytosol, upregulating aerobic glycolysis, NF-kB and cell division signalling. Also, oxidising cardiolipin, reducing oxidative phosphorylation (OXPHOS) and apoptosis ability; driving a tumourigenic phenotype. Over time, increasing senescent/pathological cell populations occurs, increasing morbidity and mortality. Beta-hydroxybutyrate, an antioxidant, metabolite and signalling molecule, increases synthesis of antioxidants via preserving NAD+ availability and enhancing OXPHOS capacity. Fasting and ketogenic diets increase ketogenesis concurrently decreasing insulin secretion and demand; hyperinsulinaemia inhibits ketogenesis. Lifestyles that maintain lower insulin levels decrease antioxidant catabolism, additionally increasing their synthesis, improving oxidative stress management and mitochondrial function and, subsequently, producing healthier cells. This supports tissue and organ health, leading to a better healthspan, the first challenge that must be overcome in the pursuit of youthful longevity.

Abstract This study used desorption electrospray ionisation mass spectrometry (DESI-MS) to analyse and detect and classify biomarkers in five different animal and plant sources of milk for the first time. A range of differences in terms of features was observed in the spectra of cow milk, goat milk, camel milk, soya milk, and oat milk. Chemometric modelling was then used to classify the mass spectra data, enabling unique or significant markers for each milk source to be identified. The classification of different milk sources was achieved with a cross-validation percentage rate of 100% through linear discriminate analysis (LDA) with high sensitivity to adulteration (0.1–5% v/v). The DESI-MS results from the milk samples analysed show the methodology to have high classification accuracy, and in the absence of complex sample clean-up which is often associated with authenticity testing, to be a rapid and efficient approach for milk fraud control.

Abstract Pesticides are a safety issue globally and cause serious concerns for the environment, wildlife and human health. The handheld detection of four pesticide residues widely used in Basmati rice production using surface-enhanced Raman spectroscopy (SERS) is reported. Different SERS substrates were synthesised and their plasmonic and Raman scattering properties evaluated. Using this approach, detection limits for pesticide residues were achieved within the range of 5 ppb-75 ppb, in solvent. Various extraction techniques were assessed to recover pesticide residues from spiked Basmati rice. Quick, Easy, Cheap, Effective, Rugged and Safe (QuEChERs) acetate extraction was applied and characteristic spectral data for each pesticide was obtained from the spiked matrix and analysed using handheld-SERS. This approach allowed detection limits within the matrix conditions to be markedly improved, due to the rapid aggregation of nanogold caused by the extraction medium. Thus, detection limits for three out of four pesticides were detectable below the Maximum Residue Limits (MRLs) of 10 ppb in Basmati rice. Furthermore, the multiplexing performance of handheld-SERS was assessed in solvent and matrix conditions. This study highlights the great potential of handheld-SERS for the rapid on-site detection of pesticide residues in rice and other commodities.

Transient stability control of power systems is based on actions that are taken automatically following a disturbance to ensure that the system remains in synchronism. Examples of such measures include generator rejection and the insertion of dynamic braking resistors. Methods like these are designed to rapidly absorb excess energy or otherwise alter the generation-demand balance at key points in the system. While these methods are often effective, they lack the ability to inject real power to compensate for a deficit. Utility-scale inverter-based resources, particularly energy storage systems, enable bidirectional modulation of real power with the bandwidth necessary to provide synchronizing torque. These resources, and the control strategies they enable, have garnered substantial research interest. This paper provides a critical review of research on real power modulation strategies for transient stability control. The design of these control strategies is heavily informed by the methods used to assess changes in the transient stability margins. Rigorously assessing these changes is difficult because the dynamics of large-scale power systems are inherently nonlinear. The well-known equal-area criterion is physically intuitive, but conceptual extensions are necessary for multi-machine systems. So-called direct methods of transient stability analysis offer a more general alternative; however, these methods require many simplifying assumptions and have difficulty incorporating detailed system dynamics. In this paper, we discuss data-driven methods for offline stability assessment based on Koopman operator theory.

Abstract HSD10 disease is a rare X‐linked mitochondrial disorder caused by pathogenic variants in the HSD17B10 gene. The phenotype results from impaired 17β‐hydroxysteroid dehydrogenase 10 (17β‐HSD10) protein structure and function. HSD10 is a multifunctional protein involved in enzymatic degradation of isoleucine and branched‐chain fatty acids, the metabolism of sex hormones and neurosteroids, as well as in regulating mitochondrial RNA maturation. HSD10 disease is characterised by progressive neurologic impairment. Disease onset is varied and includes neonatal‐onset, infantile‐onset and late‐onset in males. Females can also be affected. Our index case is a 45‐month‐old female, who initially presented at 11 months of age with global developmental delay. She subsequently began to lose previously acquired cognitive and motor skills starting around 29 months of age. Brain MRI showed abnormalities in the basal ganglia indicative of possible mitochondrial disease. Urine organic acid analysis revealed elevations of 2‐methyl‐3‐hydroxybutyric acid and tiglyglycine. HSD17B10 gene sequencing revealed a likely pathogenic variant, NM_001037811.2:c.439C>T (p.Arg147Cys) inherited from her mother, expected to be causative of HSD10 disease. Her X‐chromosome inactivation study is consistent with a skewed X‐inactivation pattern. We report a female patient with HSD10 disease caused by a missense pathogenic variant, Arg147Cys in the HSD17B10 gene. The patient is the fifth severely affected female with this disease. This case adds to the small number of known affected families with this highly variable disease in the literature. These findings support the possibility of X‐inactivation patterns influencing the penetrance of HSD10 disease in females.

COVID-19 is an ongoing, global pandemic caused by the novel, highly infectious SARS-CoV-2 virus. Efforts to mitigate the effects of SARS-CoV-2, such as mass vaccination and development of monoclonal therapeutics, require precise measurements of correlative, functional neutralizing antibodies that block virus infection. The development of rapid, safe, and easy-to-use neutralization assays is essential for faster diagnosis and treatment. Here, we developed a vesicular stomatitis virus (VSV)-based neutralization assay with two readout methods, imaging and flow cytometry, that were capable of quantifying varying degrees of neutralization in patient serum samples. We tested two different spike-pseudoviruses and conducted a time-course assay at multiple multiplicities of infection (MOIs) to optimize the assay workflow. The results of this assay correlate with the results of previously developed serology and surrogate neutralization assays. The two pseudovirus readout methods produced similar values of 50% neutralization titer values. Harvest-free in situ readouts for live-cell imaging and high-throughput analysis results for flow cytometry can provide unique capabilities for fast evaluation of neutralization, which is critical for the mitigation of future pandemics.

The presence of antibiotic residues in water is linked to the emergence of antibiotic resistance globally and necessitates novel decontamination strategies to minimize antibiotic residue exposure in both the environment and food. A holistic assessment of cold atmospheric pressure plasma technology (CAPP) for β-lactam antibiotic residue removal is described in this study. CAPP operating parameters including plasma jet voltage, gas composition and treatment time were optimized, with highest β-lactam degradation efficiencies obtained for a helium jet operated at 6 kV. Main by-products detected indicate pH-driven peroxidation as a main mechanism of CAPP-induced decomposition of β-lactams. No in vitro hepatocytotoxicity was observed in HepG2 cells following exposure to treated samples, and E. coli exposed to CAPP-degraded β-lactams did not exhibit resistance development. In surface water, over 50% decrease in antibiotic levels was achieved after only 5 min of treatment. However, high dependence of treatment efficiency on residue concentration, pH and presence of polar macromolecules was observed.

Abstract Background This study examined the impact of a ‘rewards-for-exercise’ mobile application on physical activity, subjective well-being and sleep quality among 148 employees in a UK university with low to moderate physical activity levels. Methods A three-month open-label single-arm trial with a one-year follow-up after the end of the trial. Participants used the Sweatcoin application which converted their outdoor steps into a virtual currency used for the purchase of products available at the university campus’ outlets, using an in-app marketplace. The primary outcome measure was self-reported physical activity. Secondary measures included device-measured physical activity, subjective well-being (i.e., life satisfaction, positive affect, negative affect), and self-reported sleep quality. Results The findings show an increase in self-reported physical activity (d = 0.34), life satisfaction (d = 0.31), positive affect (d = 0.29), and sleep quality (d = 0.22) during the three-month trial period. Conclusion The study suggests that mobile incentives-for-exercise applications might increase physical activity levels, positive affect, and sleep quality, at least in the short term. The observed changes were not sustained 12 months after the end of the trial.

Abstract Warming across the globe is expected to alter the strength and amount of regional precipitation, but there is uncertainty associated with the magnitude of these expected changes, and also how these changes in temperature and the hydrologic cycle will affect humans. For example, the climate in central-south Chile is projected to become significantly warmer and drier over the next several decades in response to anthropogenically driven warming, but these anthropogenic changes are superimposed on natural climate variability. The stable isotope composition of meteoric water provides significant information regarding the moisture source, pathways, and rain-out history of an air mass, but precipitation samples suitable for stable isotope measurements require long-term placement of field equipment making them difficult to obtain. The International Atomic Energy Agency (IAEA) Global Network of Isotopes in Precipitation (GNIP) stations generate isotopic and ancillary data of precipitation from many locations around the world, but remote areas of developing countries like Chile typically have sparse networks of meteorological stations, which inhibit our ability to accurately model regional precipitation. Central-south Chile, in particular, has a sparse network of GNIP stations and, as a result, the isotopic composition of meteoric water is underrepresented in the global database complicating efforts to constrain modern day hydroclimate variability as well as paleohydrologic reconstruction for southern South America. In this study, we measured the stable isotope compositions of hydrogen (δ2H) and oxygen (δ18O) in surface lacustrine waters of central-south Chile to determine what physical and/or climatic features are the dominant controls on lacustrine δ18O and δ2H composition, assess whether or not the isotopic composition of the lakes record time-averaged isotope composition of meteoric water, and determine whether an isoscape map based on lake surface waters could predict the H and O isotope compositions of precipitation at the few GNIP stations in the region.

This study is directed towards developing a fast, non-destructive, and easy-to-use handheld multimode spectroscopic system for fish quality assessment. We apply data fusion of visible near infra-red (VIS-NIR) and short wave infra-red (SWIR) reflectance and fluorescence (FL) spectroscopy data features to classify fish from fresh to spoiled condition. Farmed Atlantic and wild coho and chinook salmon and sablefish fillets were measured. Three hundred measurement points on each of four fillets were taken every two days over 14 days for a total of 8400 measurements for each spectral mode. Multiple machine learning techniques including principal component analysis, self-organized maps, linear and quadratic discriminant analyses, k-nearest neighbors, random forest, support vector machine, and linear regression, as well as ensemble and majority voting methods, were used to explore spectroscopy data measured on fillets and to train classification models to predict freshness. Our results show that multi-mode spectroscopy achieves 95% accuracy, improving the accuracies of the FL, VIS-NIR and SWIR single-mode spectroscopies by 26, 10 and 9%, respectively. We conclude that multi-mode spectroscopy and data fusion analysis has the potential to accurately assess freshness and predict shelf life for fish fillets and recommend this study be expanded to a larger number of species in the future.

Abstract Background Evidence suggests that dietary intake of UK children is suboptimal. As schools provide an ideal natural environment for public health interventions, effective and sustainable methods of improving food knowledge and dietary habits in this population must be identified. Project Daire aimed to improve children’s health-related quality of life, wellbeing, food knowledge and dietary habits via two multi-component interventions. Methods Daire was a randomised-controlled, factorial design trial evaluating two interventions across four arms. Primary schools in Northern Ireland were randomised to one of four 6-month intervention arms: i) ‘Nourish’, ii) ‘Engage’, iii) ‘Nourish’ and ‘Engage’ and iv) Control (Delayed). ‘Nourish’ was an intervention aiming to alter the whole-school food environment, provide food-related experiences and exposure to locally produced foods. ‘Engage’ was an age-appropriate, cross-curricular educational intervention on food, agriculture, nutrition science and related careers. Primary outcomes were emotional and behavioural wellbeing and health-related quality of life. A number of secondary outcomes, including dietary intake, cooking competence and food-related knowledge, were also measured. Results Fifteen schools from areas of varying socio-economic status participated in the randomised trial. A total of 903 (n = 445 aged 6–7 years and n = 458 aged 10–11 years) primary school pupils took part. Total Difficulties Score improved in all pupils (6–7 and 10–11 year old pupils) who received the ‘Nourish’ intervention compared with those that did not (adjusted difference in mean = − 0.82; 95% CI -1.46, − 0.17; P

Background: Osteoarthritis is a heterogeneous condition characterised by a wide variety of factors and represents a worldwide healthcare challenge. There are multiple clinical and research specialisms involved in the diagnosis, prognosis and treatment of osteoarthritis, and there may be opportunities to share or pool data which are currently not being utilised. However, there are challenges to doing so which require carefully structured solutions and partnership working. Methods: Interviews were conducted with nine experts from various fields within osteoarthritis research. A semi-structured approach was used, and thematic analysis applied to the results. Results: Generally, osteoarthritis researchers were supportive of data sharing, provided it is done responsibly and without impacting data integrity. Benefits identified included increasing typically low-powered data, the potential for machine learning opportunities, and the potential for improved patient outcomes. However, a number of challenges were identified, relating to: data security, data harmonisation, storage costs, ethical considerations and governance. Conclusions: There is clear support for increased data sharing and partnership working in osteoarthritis research. Further investigation will be required to navigate the complex issues identified; however, it is clear that collaborative opportunities should be better facilitated and there may be innovative ways to do this. It is also clear that nomenclature within different disciplines could be better streamlined, to improve existing opportunities to harmonise data.