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Associations between obesity and health are unequivocal and coupled with a substantial body of evidence suggesting that associations are likely causal. These associations and the supporting causal evidence are useful, but hide both the inadequacies of the measures used to qualify obesity and the mechanisms that are responsible for the observable relationships. A challenge therefore remains to determine both the intermediate factors associated with obesity and the mechanisms responsible for connecting excess adiposity (the defining feature of obesity) and health. A growing collection of detailed measures including examples in genomics, proteomics, metabolomics, and the microbiome are now available, allowing a broad approach to characterising obesity and analysing the associations between excess adiposity and health—but to what extent do these associations also provide insight into mechanism? In this specialist review, the problems facing the analysis of obesity (and related measures) both as a disease and as a risk factor for many downstream health outcomes are explored. This review looks to shift focus away from mechanisms of obesity and towards a useful interpretation of mechanisms associated with obesity in the context of promising developments in causal epidemiology.

Abstract Deep vein thrombosis (DVT) is the formation of a blood clot in a deep vein. DVT can lead to a venous thromboembolism (VTE), the combined term for DVT and pulmonary embolism, a leading cause of death and disability worldwide. Despite the prevalence and associated morbidity of DVT, the underlying causes are not well understood. Our aim was to leverage publicly available genetic summary association statistics to identify causal risk factors for DVT. We conducted a Mendelian randomization phenome-wide association study (MR-PheWAS) using genetic summary association statistics for 973 exposures and DVT (6,767 cases and 330,392 controls in UK Biobank). There was evidence for a causal effect of 57 exposures on DVT risk, including previously reported risk factors (e.g. body mass index—BMI and height) and novel risk factors (e.g. hyperthyroidism and varicose veins). As the majority of identified risk factors were adiposity-related, we explored the molecular link with DVT by undertaking a two-sample MR mediation analysis of BMI-associated circulating proteins on DVT risk. Our results indicate that circulating neurogenic locus notch homolog protein 1 (NOTCH1), inhibin beta C chain (INHBC) and plasminogen activator inhibitor 1 (PAI-1) influence DVT risk, with PAI-1 mediating the BMI-DVT relationship. Using a phenome-wide approach, we provide putative causal evidence that hyperthyroidism, varicose veins and BMI enhance the risk of DVT. Furthermore, the circulating protein PAI-1 has a causal role in DVT aetiology and is involved in mediating the BMI-DVT relationship.

Abstract Thousands of proteins circulate in the bloodstream; identifying those which associate with weight and intervention-induced weight loss may help explain mechanisms of diseases associated with adiposity. We aimed to identify consistent protein signatures of weight loss across independent studies capturing changes in body mass index (BMI). We analysed proteomic data from studies implementing caloric restriction (Diabetes Remission Clinical trial) and bariatric surgery (By-Band-Sleeve), using SomaLogic and Olink Explore1536 technologies, respectively. Linear mixed models were used to estimate the effect of the interventions on circulating proteins. Twenty-three proteins were altered in a consistent direction after both bariatric surgery and caloric restriction, suggesting that these proteins are modulated by weight change, independent of intervention type. We also integrated Mendelian randomisation (MR) estimates of the effect of BMI on proteins measured by SomaLogic from a UK blood donor cohort as a third line of causal evidence. These MR estimates provided further corroborative evidence for a role of BMI in regulating the levels of six proteins including alcohol dehydrogenase-4, nogo receptor and interleukin-1 receptor antagonist protein. These results indicate the importance of triangulation in interrogating causal relationships; further study into the role of proteins modulated by weight in disease is now warranted.

The IDEA Challenge 2022 prototyping dataset comprises a total of 240 prototype entries with 1049 edges (connections) and can provide valuable insights into prototyping practices, offering practical knowledge essential for developing prototyping strategies and generating hypotheses for future studies. Data were collected using Pro2booth - an online platform which captured comprehensive information about prototypes and participating teams’ development process, including details about the creators, purpose, timing, and methods of creation. It is particularly relevant to design researchers, engineering and design students, educators, and industry professionals seeking to enhance their prototyping skills and strategies. It serves as a robust foundation for subsequent studies, allowing for comparative analyses, hypothesis verification, and trend exploration. It also has the potential to inform meta-analyses across similar design scenarios, providing a comprehensive understanding of prototyping processes.

Proteomics is the identification, detection and quantification of proteins within a biological sample. The complete set of proteins expressed by an organism is known as the proteome. The availability of new high-throughput proteomic technologies, such as Olink Proteomic Proximity Extension Assay (PEA) technology has enabled detailed investigation of the circulating proteome in large-scale epidemiological studies. In particular, the Olink® Target 96 inflammatory panel allows the measurement of 92 circulating inflammatory proteins. The Avon Longitudinal Study of Parents and Children (ALSPAC) is a prospective population-based cohort study which recruited pregnant women in 1991-1992 and has followed these women, their partners, and their offspring ever since. In this data note, we describe the newly-released proteomic data available in ALSPAC. Ninety-two proteins were analysed in 9000 blood plasma samples using the Olink® Target 96 inflammatory panel. Samples were derived from 2968 fasted mothers (mean age 47.5; Focus on Mothers 1 (FOM1)), 3005 non-fasted offspring at age 9 (Focus@9) and 3027 fasted offspring at age 24 (Focus@24). Post sample filtering, 1834 offspring have data at both timepoints and 1119 of those have data from their mother available. We performed quality control analyses using a standardised data processing workflow (metaboprep) to produce a filtered dataset of 8983 samples for researchers to use in future analyses. Initial validation analyses indicate that IL-6 measured using the Olink® Target 96 inflammatory panel is highly correlated with IL-6 previously measured by clinical chemistry (Pearson’s correlation = 0.77) and we are able to reproduce the reported positive correlation between body mass index (BMI) and IL-6. The pre-processing and validation analyses indicate a rich proteomic dataset to further characterise the role of inflammation in health and disease.

This paper demonstrates the unpredictability of outcomes that result from compounding variabilities when using generative design (GD) coupled with additive manufacturing (AM). AM technologies offer the greatest design freedom and hence are most able to leverage the full capability of generative design (GD) tools and thus maximize potential improvements, such as weight, waste and cost reduction, strength, and part consolidation. Implicit in all studies reported in the literature is the fundamental assumption that the use of GD, irrespective of user experience or approach followed, yields high-performing and/or comparable design outputs. This work demonstrates the contrary and shows that achieving high performance with GD tools requires careful consideration of study setup and initial conditions. It is further shown that, when coupled with the inherent variability of AM parts, the potential variation in the performance of the design output can be significant, with poorer designs achieving only a fraction of that of higher-performing designs. This investigation shows how AM by Material Extrusion (MEX), which is used to manufacture components with polylactic acid (PLA), varies through different design pathways, bridging MEX and GD. Through a practical study across nine independently generated designs, the breadth of performance—due to initial GD conditions and MEX part strength unpredictability—is shown to reach 592%. This result suggest that current GD tools, including their underlying workflows and algorithms, are not sufficiently understood for users to be able to generate consistent solutions for an input case. Further, the study purports that training and consideration on GD setup are necessary to apply GD toolsets to achieve high-performing designs, particularly when applied in the context of MEX.

The COVID-19 pandemic profoundly affected various aspects of daily life, particularly the supply and demand of essential goods, resulting in critical shortages. This included personal protective equipment for medical professionals and the general public. To address these shortages, online ‘maker communities’ emerged, aiming to develop and locally manufacture critical products. While some organized efforts existed, the majority of initiatives originated from individuals and groups on platforms like Thingiverse. This paper presents a longitudinal analysis of Thingiverse, one of the largest maker community websites, to examine the pandemic’s effects. Our findings reveal a surge in community output during the initial lockdown periods in major contributing nations (primarily those in the Western Hemisphere), followed by a subsequent decline. Additionally, throughout 2020, pandemic-related products dominated uploads and interactions during this period. Based on these observations, we propose recommendations to expedite the community’s ability to support local, national and international responses to future disasters.

Higher body mass index (BMI) is a risk factor for thrombosis. Platelets are essential for hemostasis but contribute to thrombosis when activated pathologically. We hypothesized that higher BMI leads to changes in platelet characteristics, thereby increasing thrombotic risk. The effect of BMI on platelet traits (measured by Sysmex) was explored in 33 388 UK blood donors (INTERVAL study). Linear regression showed that higher BMI was positively associated with greater plateletcrit (PCT), platelet count (PLT), immature platelet count (IPC), and side fluorescence (SFL, a measure of mRNA content used to derive IPC). Mendelian randomization (MR), applied to estimate a causal effect with BMI proxied by a genetic risk score, provided causal estimates for a positive effect of BMI on both SFL and IPC, but there was little evidence for a causal effect of BMI on PCT or PLT. Follow-up analyses explored the functional relevance of platelet characteristics in a pre-operative cardiac cohort (COPTIC). Linear regression provided observational evidence for a positive association between IPC and agonist-induced whole blood platelet aggregation. Results indicate that higher BMI raises the number of immature platelets, which is associated with greater whole blood platelet aggregation in a cardiac cohort. Higher IPC could therefore contribute to obesity-related thrombosis.

Background Adiposity is an established risk factor for colorectal cancer (CRC). The pathways underlying this relationship, and specifically the role of circulating proteins, are unclear. Methods Utilizing two-sample univariable Mendelian randomization (UVMR), multivariable Mendelian randomization (MVMR), and colocalization, based on summary data from large sex-combined and sex-specific genetic studies, we estimated the univariable associations between: (i) body mass index (BMI) and waist–hip ratio (WHR) and overall and site-specific (colon, proximal colon, distal colon, and rectal) CRC risk, (ii) BMI and WHR and circulating proteins, and (iii) adiposity-associated circulating proteins and CRC risk. We used MVMR to investigate the potential mediating role of adiposity- and CRC-related circulating proteins in the adiposity–CRC association. Results BMI and WHR were positively associated with CRC risk, with similar associations by anatomical tumor site. In total, 6591 adiposity–protein (2628 unique circulating proteins) and 33 protein–CRC (7 unique circulating proteins) associations were identified using UVMR and colocalization. One circulating protein, GREM1, was associated with BMI (only) and CRC outcomes in a manner that was consistent with a potential mediating role in sex-combined and female-specific analyses. In MVMR, adjusting the BMI–CRC association for GREM1, effect estimates were attenuated—suggestive of a potential mediating role—most strongly for the BMI–overall CRC association in women. Conclusion Results highlight the impact of adiposity on the plasma proteome and of adiposity-associated circulating proteins on the risk of CRC. Supported by evidence from UVMR and colocalization analyses using cis -single-nucleotide polymorphisms, GREM1 was identified as a potential mediator of the BMI–CRC association, particularly in women. [ABSTRACT FROM AUTHOR]

Increased deployment of solar photovoltaic (PV) enables the transition to decarbonized energy systems, capable of tempering the dire consequences of global warming. Even though backsheets are very important regarding lifetime energy yield of the PV module, the environmental impacts of their production, use, and end‐of‐life (EoL) processing are largely neglected. As part of a recently finalized Dutch national project EXTENSIBLE (Energy yield assessment of neXT gENeration and SustaInaBLE backsheets), the environmental impacts for 7 different polymeric backsheets have been evaluated via a life cycle assessment (LCA). The selected backsheets include 3 traditional polyethylene terephthalate (PET)‐based backsheets with a fluorine containing outer layer (two white pigmented and one fully transparent). The other 4 backsheets are novel high‐performance polyolefin (PO)‐based backsheets, manufactured by Endurans Solar™, also including one transparent version. From results of the LCA, it is concluded that in comparison with PET‐based backsheets and fluoropolymer containing backsheets, PO‐based backsheets perform best in terms of energy yield, reliability, and environmental impacts. The production of fluoropolymer‐ and PET‐based backsheets cause substantial environmental impacts, especially regarding climate change and ozone depletion. This conclusion is corroborated by recent literature data. Regarding the EoL phase, it was shown from a theoretical assessment that pyrolysis of the spent backsheets potentially leads to much lower global warming potential (GWP) when compared to incineration, especially for the PO‐based backsheets. Incineration of the shredded and solid backsheet material causes direct emissions of CO2 with a limited heat recovery potential only. Deploying pyrolysis for spent PO‐based backsheets significantly improves their life‐time GWP per kWh produced. Pyrolysis offers the possibility to recover a large part of the PO as an usable pyrolysis oil that might serve as feedstock for chemicals or as transportable liquid fuel for the generation of process heat in recovery boilers, thereby avoiding the use of new fossil resources. EoL pyrolysis (or incineration) of fluoropolymer‐based backsheets is problematic due to the presence of fluorinated hydrocarbons, leading to corrosive and/or toxic products. [ABSTRACT FROM AUTHOR]

3D printing technologies, such as material extrusion (MEX), hold the potential to revolutionise manufacturing by providing individuals without traditional manufacturing capabilities with powerful and affordable resources. However, widespread adoption is impeded by the lack of user-friendly design tools due to the necessity of domain-specific expertise in computer-aided design (CAD) software and the overwhelming level of design freedom afforded by the MEX process. To overcome these barriers and facilitate the democratisation of design (DoD), this article introduces an innovative, generative-based design (GBD) methodology aimed at enabling non-technical users to create functional components independently. The novelty of this methodology lies in its capacity to simplify complex design tasks, making them more accessible to non-designers. The proposed methodology was tested in the design of a load-bearing part, yielding a functional component within two design iterations. A comparative analysis with the conventional CAD-based process revealed that the GBD methodology enables the DoD, reflected in a 68% reduction in design activities and a decrease in design difficulty of 62% in requisite know-how and a 55% in understanding. Through the creation and implementation of this methodology, the article demonstrates a pioneering integration of state-of-the-art techniques of generative design with design repositories enabling effective co-design with non-designers.

Prototyping is a knowledge generation activity facilitating improved understanding of problem and solution spaces. This knowledge can be generated across a range of dimensions, termed knowledge dimensions (KDs), via a range of methods and media, each with their own inherent properties. This article investigates and characterises the relationships between prototypes and knowledge generated from prototyping activities during the design process, by establishing how different methods and media contribute across KDs. In so doing, it provides insights into prototyping activity, as well as affording a means by which prototyping knowledge generation may be studied in detail. The investigation considers sets of prototypes from eight parallel 16-week design projects, with subsequent investigation of the knowledge contributions that each prototype provides and at what stage of the design process. Results showed statistical significance supporting three inferences: i) teams undertaking the same design brief create similar knowledge profiles; ii) prototyping fidelity impacts KD contribution and iii) KDs align with the different phases of the project. This article demonstrates a means to describe and potentially prescribe knowledge generation activities through prototyping. Correspondingly, the article contends that consideration of KDs offers potential to improve aspects of the design process through better prototyping method selection and sequencing.

Abstract Sphingosine 1-phosphate (S1P) is a bioactive signalling sphingolipid that is increased in diseases such as obesity and diabetes. S1P can modulate platelet function, however the direction of effect and S1P receptors (S1PRs) involved are controversial. Here we describe the role of S1P in regulating human platelet function and identify the receptor subtypes responsible for S1P priming. Human platelets were treated with protease-activated receptor 1 (PAR-1)-activating peptide in the presence or absence of S1P, S1PR agonists or antagonists, and sphingosine kinases inhibitors. S1P alone did not induce platelet aggregation but at low concentrations S1P enhanced PAR1-mediated platelet responses, whereas PAR1 responses were inhibited by high concentrations of S1P. This biphasic effect was mimicked by pan-S1PR agonists. Specific agonists revealed that S1PR1 receptor activation has a positive priming effect, S1PR2 and S1PR3 have no effect on platelet function, whereas S1PR4 and S1PR5 receptor activation have an inhibitory effect on PAR-1 mediated platelet function. Although platelets express both sphingosine kinase 1/2, enzymes which phosphorylate sphingosine to produce S1P, only dual and SphK2 inhibition reduced platelet function. These results support a role for SphK2-mediated S1P generation in concentration-dependent positive and negative priming of platelet function, through S1PR1 and S1PR4/5 receptors, respectively.