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Abstract Background Genome-wide association studies have enabled Mendelian randomization analyses to be performed at an industrial scale. Two-sample summary data Mendelian randomization analyses can be performed using publicly available data by anyone who has access to the internet. While this has led to many insightful papers, it has also fuelled an explosion of poor-quality Mendelian randomization publications, which threatens to undermine the credibility of the whole approach. Findings We detail five pitfalls in conducting a reliable Mendelian randomization investigation: (1) inappropriate research question, (2) inappropriate choice of variants as instruments, (3) insufficient interrogation of findings, (4) inappropriate interpretation of findings, and (5) lack of engagement with previous work. We have provided a brief checklist of key points to consider when performing a Mendelian randomization investigation; this does not replace previous guidance, but highlights critical analysis choices. Journal editors should be able to identify many low-quality submissions and reject papers without requiring peer review. Peer reviewers should focus initially on key indicators of validity; if a paper does not satisfy these, then the paper may be meaningless even if it is technically flawless. Conclusions Performing an informative Mendelian randomization investigation requires critical thought and collaboration between different specialties and fields of research.

Abstract Dissipation and the accompanying fluctuations are often seen as detrimental for quantum systems since they are associated with fast relaxation and loss of phase coherence. However, it has been proposed that a pure state can be prepared if external noise induces suitable downwards transitions, while exciting transitions are blocked. We demonstrate such a refrigeration mechanism in a cavity optomechanical system, where we prepare a mechanical oscillator in its ground state by injecting strong electromagnetic noise at frequencies around the red mechanical sideband of the cavity. The optimum cooling is reached with a noise bandwidth smaller than but on the order of the cavity decay rate. At higher bandwidths, cooling is less efficient as suitable transitions are not effectively activated. In the opposite regime where the noise bandwidth becomes comparable to the mechanical damping rate, damping follows the noise amplitude adiabatically, and the cooling is also suppressed.

Northern peatland vegetation exhibits fine-scale spatial and spectral heterogeneity that can potentially be captured with uncrewed aerial vehicle (UAV) data due to their ultra-high spatial resolution (

Abstract Plant biomass is a fundamental ecosystem attribute that is sensitive to rapid climatic changes occurring in the Arctic. Nevertheless, measuring plant biomass in the Arctic is logistically challenging and resource intensive. Lack of accessible field data hinders efforts to understand the amount, composition, distribution, and changes in plant biomass in these northern ecosystems. Here, we present The Arctic plant aboveground biomass synthesis dataset, which includes field measurements of lichen, bryophyte, herb, shrub, and/or tree aboveground biomass (g m−2) on 2,327 sample plots from 636 field sites in seven countries. We created the synthesis dataset by assembling and harmonizing 32 individual datasets. Aboveground biomass was primarily quantified by harvesting sample plots during mid- to late-summer, though tree and often tall shrub biomass were quantified using surveys and allometric models. Each biomass measurement is associated with metadata including sample date, location, method, data source, and other information. This unique dataset can be leveraged to monitor, map, and model plant biomass across the rapidly warming Arctic.

3D printing is a solid part of the health care environment, and in the future, it could assume a more innovative role in the work carried out by practical nurses. However, the educational context may not support the preparedness to face and adapt new and creative technologies on the part of practical nursing students. This study aimed to describe practical nursing students’ technological acceptance towards 3D printing before and after six hours of 3D printing instruction. The technological acceptance model was used as a framework of the study. The data was collected using focus group interviews that 14 practical nursing students participated in before and after their six-hour 3D teaching course. Along with the thematic analysis, the interview themes were created in accordance with the theoretical elements concerned. The results showed four narrative themes that described how a six-hour lesson series changed the students’ technological acceptance towards 3D printing, from: 1) professional meaningless to everyday usefulness, 2) resource dominance to a part of working life, 3) special competence to ease of use, and 4) assumptions to limitless possibilities. Every theme consisted of two subthemes. Despite having been a new thing for students, 3D printing could be conceived in terms of having professional significance. The students described 3D printing as being easy to adapt to and they highlighted the meaning of its educational usage, as it could prepare them to be better with respect to applying creative working life-based technological solutions. As a conclusion, it can be stated that even short educational sessions can promote practical nursing students’ technological acceptance towards 3D technology and the know-how to implement it in working life. This requires educational institutions to target resources to 3D printing and on teacher education.

Abstract Simulating the carbon-water fluxes at more widely distributed meteorological stations based on the sparsely and unevenly distributed eddy covariance flux stations is needed to accurately understand the carbon-water cycle of terrestrial ecosystems. We established a new framework consisting of machine learning, determination coefficient (R2), Euclidean distance, and remote sensing (RS), to simulate the daily net ecosystem carbon dioxide exchange (NEE) and water flux (WF) of the Eurasian meteorological stations using a random forest model or/and RS. The daily NEE and WF datasets with RS-based information (NEE-RS and WF-RS) for 3774 and 4427 meteorological stations during 2002–2020 were produced, respectively. And the daily NEE and WF datasets without RS-based information (NEE-WRS and WF-WRS) for 4667 and 6763 meteorological stations during 1983–2018 were generated, respectively. For each meteorological station, the carbon-water fluxes meet accuracy requirements and have quasi-observational properties. These four carbon-water flux datasets have great potential to improve the assessments of the ecosystem carbon-water dynamics.

Posterior dislocation of the shoulder joint is a rare condition. It is often misdiagnosed owing to a lack of evident clinical features compared with anterior shoulder dislocation, and inappropriate radiological examination. We present a case of chronic posterior fracture dislocation treated with greater tuberosity osteotomy. A 66-year-old man was injured in a fall while carrying a drone. He was referred to our hospital following 3 months of conservative treatment at a nearby clinic, without reduction of the posterior dislocation. Physical examination revealed a prominent reduction in shoulder joint range of motion and shoulder pain. Radiological examination revealed posterior shoulder dislocation associated with greater tuberosity malunion and a small bone fracture of the posterior portion of the glenoid. Open reduction and internal fixation, including greater tuberosity osteotomy, were performed. Although subluxation of the posterior dislocation persisted postoperatively, the humeral head gradually returned to its centric shoulder joint position owing to rotator cuff force coupling. At 24-month follow-up, the patient showed excellent shoulder results.

Cartilage conduction hearing aids (CC-HAs) are a novel type of hearing aid relying on cartilage conduction, the so-called third auditory conduction pathway. However, CC-HAs have only recently entered routine clinical use, and therefore data on their usefulness are lacking. The purpose of this study was to examine the possibility of assessing whether individual patients would show good adaptation to CC-HAs. Thirty-three subjects (41 ears in total) underwent a free trial of CC-HAs. Age, disease category, and the pure-tone threshold of air and bone conduction, unaided field sound threshold, aided field sound threshold, and functional gain (FG) at 0.25, 0.5, 1, 2, and 4 kHz were compared between patients who subsequently purchased and did not purchase the CC-HAs. Overall, 65.9% of the subjects purchased CC-HAs after the trial. In comparison to non-purchasers, those who decided to purchase CC-HAs showed better pure tone hearing thresholds at high frequencies for both air conduction (2 and 4 kHz) and bone conduction (1, 2, and 4 kHz), as well as for aided thresholds in the sound field (1, 2, and 4 kHz) when using CC-HAs. Therefore, the high-frequency hearing thresholds of subjects trialing CC-HAs might be helpful for identifying those who are likely to benefit from them.

Meat substitutes production using plant-derived materials is attracting attentions as a solution for sustainable protein supply. We have previously reported the fabrication of soy protein-based fibers by combination of wet spinning and ionic cross-linking of alginate. In this study, we focused on the calcium ion concentration in the coagulant solution and alginate concentration in the spinning solution, which are determinant factors for in the gelation of alginate. The fiber diameter was reduced by increasing calcium ion concentration, probably due to the dehydration from fiber induced by osmotic pressure difference with coagulant solution and the suppression of swelling of fiber by the rapid gelation. The hardness of fibers evaluated by texture analysis increased as the concentrations of alginate and calcium ion increased, while the springiness increased with increasing calcium ion concentration but decreased with alginate concentration. The controlling the structure and texture of fibers by the compositions of spinning and coagulant solutions would improve their applicability to meat substitutes.

Background and aimsIt is important to diagnose cerebral infarction at an early stage and select an appropriate treatment method. The number of stroke-trained physicians is unevenly distributed; thus, a shortage of specialists is a major problem in some regions. In this retrospective design study, we tested whether an artificial intelligence (AI) we built using computer-aided detection/diagnosis may help medical physicians to classify stroke for the appropriate treatment.MethodsTo build the Stroke Classification and Treatment Support System AI, the clinical data of 231 hospitalized patients with ischemic stroke from January 2016 to December 2017 were used for training the AI. To verify the diagnostic accuracy, 151 patients who were admitted for stroke between January 2018 and December 2018 were also enrolled.ResultsBy utilizing multimodal data, such as DWI and ADC map images, as well as patient examination data, we were able to construct an AI that can explain the analysis results with a small amount of training data. Furthermore, the AI was able to classify with high accuracy (Cohort 1, evaluation data 88.7%; Cohort 2, validation data 86.1%).ConclusionIn recent years, the treatment options for cerebral infarction have increased in number and complexity, making it even more important to provide appropriate treatment according to the initial diagnosis. This system could be used for initial treatment to automatically diagnose and classify strokes in hospitals where stroke-trained physicians are not available and improve the prognosis of cerebral infarction.

Abstract Wetlands are responsible for 20%–31% of global methane (CH4) emissions and account for a large source of uncertainty in the global CH4 budget. Data‐driven upscaling of CH4 fluxes from eddy covariance measurements can provide new and independent bottom‐up estimates of wetland CH4 emissions. Here, we develop a six‐predictor random forest upscaling model (UpCH4), trained on 119 site‐years of eddy covariance CH4 flux data from 43 freshwater wetland sites in the FLUXNET‐CH4 Community Product. Network patterns in site‐level annual means and mean seasonal cycles of CH4 fluxes were reproduced accurately in tundra, boreal, and temperate regions (Nash‐Sutcliffe Efficiency ∼0.52–0.63 and 0.53). UpCH4 estimated annual global wetland CH4 emissions of 146 ± 43 TgCH4 y−1 for 2001–2018 which agrees closely with current bottom‐up land surface models (102–181 TgCH4 y−1) and overlaps with top‐down atmospheric inversion models (155–200 TgCH4 y−1). However, UpCH4 diverged from both types of models in the spatial pattern and seasonal dynamics of tropical wetland emissions. We conclude that upscaling of eddy covariance CH4 fluxes has the potential to produce realistic extra‐tropical wetland CH4 emissions estimates which will improve with more flux data. To reduce uncertainty in upscaled estimates, researchers could prioritize new wetland flux sites along humid‐to‐arid tropical climate gradients, from major rainforest basins (Congo, Amazon, and SE Asia), into monsoon (Bangladesh and India) and savannah regions (African Sahel) and be paired with improved knowledge of wetland extent seasonal dynamics in these regions. The monthly wetland methane products gridded at 0.25° from UpCH4 are available via ORNL DAAC (https://doi.org/10.3334/ORNLDAAC/2253).

Abstract Climate change mitigation requires, besides reductions in greenhouse gas emissions, actions to increase carbon sinks in terrestrial ecosystems. A key measurement method for quantifying such sinks and calibrating models is the eddy covariance technique, but it requires imputation, or gap-filling, of missing data for determination of annual carbon balances of ecosystems. Previous comparisons of gap-filling methods have concluded that commonly used methods, such as marginal distribution sampling (MDS), do not have a significant impact on the carbon balance estimate. By analyzing an extensive, global data set, we show that MDS causes significant carbon balance errors for northern (latitude $$>60^\circ$$ > 60 ∘ ) sites. MDS systematically overestimates the carbon dioxide (CO $$_2$$ 2 ) emissions of carbon sources and underestimates the CO $$_2$$ 2 sequestration of carbon sinks. We also reveal reasons for these biases and show how a machine learning method called extreme gradient boosting or a modified implementation of MDS can be used to substantially reduce the northern site bias.

Peatlands are one of the most significant terrestrial carbon pools, and the processes behind the carbon cycle in peatlands are strongly associated with different vegetation patterns. Handheld spectroradiometer data has been widely applied in ecological research, but there is a lack of studies on peatlands assessing how the temporal and spectral resolution affect the detectability of vegetation patterns. We collected field spectroscopy and vegetation inventory data at two northern boreal peatlands, Lompolojänkkä and Halssiaapa, between late May and August 2019. We conducted multivariate random forest regressions to examine the appropriate periods, benefits of multi-temporal data, and optimal spectral bandwidth and sampling interval for detecting plant communities and the two-dimensional (2D) %-cover, above-ground biomass (AGB) and leaf area index (LAI) of seven plant functional types (PFTs). In the best cross-site regression models for detecting plant community clusters (PCCs), R2 was 42.6–48.0% (root mean square error (RMSE) 0.153–0.193), and for PFT 2D %-cover 53.9–69.8% (RMSE 8.2–17.6%), AGB 43.1–61.5% (RMSE 86.2–165.5 g/m2) and LAI 46.3–51.3% (RMSE 0.220–0.464 m2/m2). The multi-temporal data of the whole season increased R2 by 13.7–24.6%-points and 10.2–33.0%-points for the PCC and PFT regressions, respectively. There was no single optimal temporal window for vegetation pattern detection for the two sites; in Lompolojänkkä the early growing season between late May and mid-June had the highest regression performance, while in Halssiaapa, the optimal period was during the peak season, from July to early August. In general, the spectral sampling interval between 1 to 10 nm yielded the best regression performance for most of the vegetation characteristics in Lompolojänkkä, whereas the optimal range extended to 20 nm in Halssiaapa. Our findings underscore the importance of fieldwork timing and the use of multi-temporal and hyperspectral data in detecting vegetation in spatially heterogeneous landscapes.

Bahasa Inggris berperan terhadap perkembangan teknologi yang terus mengalami kemajuan. Oleh karena itu perlu adanya inovasi yang dapat membantu siswa dalam hal penguasaan bahasa inggris. Dalam penguasaan bahasa inggris terutama kemampuan speaking ada beberapa kendala yang dihadapi siswa yakni, kurangnya kosakata, tata bahasa, kurangnya rasa kepercayaan diri dikarenakan pengucapan yang tidak jelas serta media ajar yang tidak menarik. Oleh karena itu tujuan penulisan ini untuk menyadarkan siswa maupun guru akan manfaat dari media sosial youtube sebagai media untuk melatih kemampuan speaking sehingga pembelajaran dikelas lebih menyenangkan. Penulisan ini menggunakan metode studi kepustakaan dengan mengkaji beberapa artikel hasil penelitian yang sudah terpublikasi serta di dukung oleh beberapa buku untuk dianalisis serta dibuat kesimpulan. Hasil pengkajian menunjukkan bahwa media Youtube terhadap motivasi belajar siswa pada kemampuan speaking dapat menjadi solusi dari beberapa kendala yang ditemui dalam proses pembelajaran. Pembelajaran menggunakan media youtube dapat memotivasi siswa dalam penguasaan bahasa serta video pembelajarannya dapat di akses di mana saja dan kapan saja. Dengan demikian, perlunya kesiapan guru serta siswa dalam menghadapi era perkembangan teknologi serta mampu memanfaatkannya.

Abstract We assigned 329,908 UK Biobank participants into six subgroups based on a self-organizing map of 51 biochemical measures (blinded for clinical outcomes). The subgroup with the most favorable metabolic traits was chosen as the reference. Hazard ratios (HR) for incident disease were modeled by Cox regression. Enrichment ratios (ER) of incident multi-morbidity versus randomly expected co-occurrence were evaluated by permutation tests; ER is like HR but captures co-occurrence rather than event frequency. The subgroup with high urinary excretion without kidney stress (HR = 1.24) and the subgroup with the highest apolipoprotein B and blood pressure (HR = 1.52) were associated with ischemic heart disease (IHD). The subgroup with kidney stress, high adiposity and inflammation was associated with IHD (HR = 2.11), cancer (HR = 1.29), dementia (HR = 1.70) and mortality (HR = 2.12). The subgroup with high liver enzymes and triglycerides was at risk of diabetes (HR = 15.6). Multimorbidity was enriched in metabolically favorable subgroups (3.4 ≤ ER ≤ 4.0) despite lower disease burden overall; the relative risk of co-occurring disease was higher in the absence of obvious metabolic dysfunction. These results provide synergistic insight into metabolic health and its associations with cardiovascular disease in a large population sample.

The use of adhesives and metal connectors is vital in engineered wood product (EWP) composition. However, the utilization of adhesives poses sustainability and recyclability challenges due to the emission of toxic gases. Similarly, metal fasteners negatively impact the disposal, reusability, and recyclability of EWPs. An alternative solution that exclusively employs pure wood, known as dovetail massive wooden board elements (DMWBEs), eliminates the need for adhesives and metal fasteners. This paper presents an experimental comparative assessment of the fire/charring performance of DMWBEs and cross-laminated timber (CLT). Model-scale test specimens measuring 200 mm in thickness, 950 mm in width, and 950 mm in length were vertically tested according to EN 1363-1. The charring behavior of DMWBEs closely resembled that of solid timber, with only a slight increase in the charring rate. Charring primarily occurred in the third lamella layer out of five, with no observable flames or hot gases on the unexposed side. The dovetail detail effectively prevented char fall-off with the tested lamella thickness. CLT specimens exhibited a notable rise in the charring rate due to the fall-off of the first lamellae layer.

It has long been known that oncolytic viruses wield their therapeutic capability by priming an inflammatory state within the tumor and activating the tumor immune microenvironment, resulting in a multifaceted antitumor immune response. Vaccine-derived viruses, such as measles and mumps, have demonstrated promising potential for treating human cancer in animal models and clinical trials. However, the extensive cost of manufacturing current oncolytic viral products makes them far out of reach for most patients. Here by analyzing the impact of intratumoral (IT) administrations of the trivalent live attenuated measles, mumps, and rubella viruses (MMR) vaccine, we unveil the cellular and molecular basis of MMR-induced anti-cancer activity. Strikingly, we found that IT delivery of low doses of MMR correlates with tumor control and improved survival in murine hepatocellular cancer and colorectal cancer models via increased tumor infiltration of CD8+ granzyme B+ T-cells and decreased macrophages. Moreover, our data indicate that MMR activates key cellular effectors of the host’s innate and adaptive antitumor immunity, culminating in an immunologically coordinated cancer cell death. These findings warrant further work on the potential for MMR to be repurposed as safe and cost-effective cancer immunotherapy to impact cancer patients globally.

Abstract Preterm birth (PTB) is associated with increased risk of type 2 diabetes and neurocognitive impairment later in life. We analyzed for the first time the associations of PTB with blood miRNA levels in adulthood. We also investigated the relationship of PTB associated miRNAs and adulthood phenotypes previously linked with premature birth. Blood MicroRNA profiling, genome-wide gene expression analysis, computer-based cognitive testing battery (CANTAB) and serum NMR metabolomics were performed for Young Finns Study subjects (aged 34–49 years, full-term n = 682, preterm n = 84). Preterm birth (vs. full-term) was associated with adulthood levels of hsa-miR-29b-3p in a fully adjusted regression model (p = 1.90 × 10–4, FDR = 0.046). The levels of hsa-miR-29b-3p were down-regulated in subjects with PTB with appropriate birthweight for gestational age (p = 0.002, fold change [FC] = − 1.20) and specifically in PTB subjects with small birthweight for gestational age (p = 0.095, FC = − 1.39) in comparison to individuals born full term. Hsa-miR-29b-3p levels correlated with the expressions of its target-mRNAs BCL11A and CS and the gene set analysis results indicated a target-mRNA driven association between hsa-miR-29b-3p levels and Alzheimer's disease, Parkinson's disease, Insulin signaling and Regulation of Actin Cytoskeleton pathway expression. The level of hsa-miR-29b-3p was directly associated with visual processing and sustained attention in CANTAB test and inversely associated with serum levels of VLDL subclass component and triglyceride levels. In conlcusion, adult blood levels of hsa-miR-29b-3p were lower in subjects born preterm. Hsa-miR-29b-3p associated with cognitive function and may be linked with adulthood morbidities in subjects born preterm, possibly through regulation of gene sets related to neurodegenerative diseases and insulin signaling as well as VLDL and triglyceride metabolism.

Summary Fungal laccases are attracting enzymes for sustainable valorization of biorefinery lignins. To improve the lignin oxidation capacity of two previously characterized laccase isoenzymes from the white‐rot fungus Obba rivulosa, we mutated their substrate‐binding site at T1. As a result, the pH optimum of the recombinantly produced laccase variant rOrLcc2‐D206N shifted by three units towards neutral pH. O. rivulosa laccase variants with redox mediators oxidized both the dimeric lignin model compound and biorefinery poplar lignin. Significant structural changes, such as selective benzylic α‐oxidation, were detected by nuclear magnetic resonance analysis, although no polymerization of lignin was observed by gel permeation chromatography. This suggests that especially rOrLcc2‐D206N is a promising candidate for lignin‐related applications.

Abstract Background Exercise electrocardiography is a widely used diagnostic modality for diagnosing coronary artery disease. This method has been used for both sexes; however, its diagnostic accuracy in women is limited. Methods The study analyzed 332 women participating in the Finnish Cardiovascular Study. Among 332 women, 125 with angiographically proven coronary artery disease (mean age 62.1 ± 9.5 years), 91 with a low likelihood of coronary artery disease (mean age 47.3 ± 13.5 years), and 116 without angiographically proven coronary artery disease (mean age 56.3 ± 9.9 years) were analyzed. The Q, R, S, and ST‐segment changes and QRS score were determined by subtracting the Q, R, S, and ST‐segment amplitudes immediately after the maximal exercise changes from their rest values (Δ). Receiver operating characteristic curve analysis was performed to evaluate the overall diagnostic performance of the parameters for predicting coronary artery disease. Results The areas under the receiver operating characteristic curve between coronary artery disease and low likelihood of coronary artery disease groups for the QRS score and ΔSTV5, ΔQaVF, and ΔRaVF were 0.75, 0.73, 0.71, and 0.71, respectively. These areas were lower (0.62, 0.57, 0.60, and 0.60, respectively) between the groups with and without angiographically proven coronary artery disease. QRS score demonstrated the highest sensitivity at 80% specificity (61.5%) and the highest specificity at 80% sensitivity (57.6%). Conclusions This study suggests that the QRS and ST‐segment depression have a moderate diagnostic ability to predict coronary artery disease in women. Q and R waves in lead aVF showed good diagnostic ability.

Abstract In peroneal nerve palsy with closed knee injury, most of the case improves by follow‐up. We present a case of peroneal nerve rupture with closed multiple ligament knee injury, requiring nerve transplantation. In multiple ligament knee injury, it is necessary to consider the possibility of peroneal nerve rupture.

Abstract Background Elevated level of plasma uric acid (PUA) has been associated with cardiovascular disease, but whether uric acid is an independent risk factor or merely a marker remains controversial. Methods We investigated in a cross-sectional setting the association of PUA with hemodynamics in 606 normotensive and never-medicated hypertensive subjects (295 men, 311 women, age range 19–73 years) without cardiovascular disease or gout. In all except 15 individuals, PUA was within the normal range. Supine hemodynamics were recorded using whole-body impedance cardiography and radial tonometric pulse wave analysis. Results The mean concentrations of PUA in age, sex and body mass index adjusted quartiles were 234, 278, 314, and 373 µmol/l, respectively. The highest PUA quartile presented with higher aortic to popliteal pulse wave velocity (PWV) than the lowest quartile (8.7 vs. 8.2 m/s, p = 0.026) in analyses additionally adjusted for plasma concentrations of C-reactive protein, low density lipoprotein cholesterol, triglycerides, and mean aortic blood pressure. No differences in radial and aortic blood pressure, wave reflections, heart rate, cardiac output, and systemic vascular resistance were observed between the quartiles. In linear regression analysis, PUA was an independent explanatory factor for PWV (β = 0.168, p

Wetland methane emissions contribute to global warming, and are oversimplified in climate models. Here the authors use eddy covariance measurements from 48 global sites to demonstrate seasonal hysteresis in methane-temperature relationships and suggest the importance of microbial processes.

Background Low‐grade inflammation in the young may contribute to the early development of cardiovascular disease. We assessed whether circulating levels of glycoprotein acetyls (GlycA) were better able to predict the development of adverse cardiovascular disease risk profiles compared with the more commonly used biomarker high‐sensitivity CRP (C‐reactive protein). Methods and Results A total of 3306 adolescents and young adults from the Avon Longitudinal Study of Parents and Children (mean age, 15.4±0.3; n=1750) and Cardiovascular Risk in Young Finns Study (mean age, 32.1±5.0; n=1556) were included. Baseline associations between inflammatory biomarkers, body composition, cardiovascular risk factors, and subclinical measures of vascular dysfunction were assessed cross‐sectionally in both cohorts. Prospective risk of developing hypertension and metabolic syndrome during 9‐to‐10‐year follow‐up were also assessed as surrogate markers for future cardiovascular risk. GlycA showed greater within‐subject correlation over 9‐to‐10‐year follow‐up in both cohorts compared with CRP, particularly in the younger adolescent group (r=0.36 versus 0.07). In multivariable analyses, GlycA was found to associate with multiple lifestyle‐related cardiovascular disease risk factors, cardiometabolic risk factor burden, and vascular dysfunction (eg, mean difference in flow‐mediated dilation=−1.2 [−1.8, −0.7]% per z‐score increase). In contrast, CRP levels appeared predominantly driven by body mass index and showed little relationship to any measured cardiovascular risk factors or phenotypes. In both cohorts, only GlycA predicted future risk of both hypertension (risk ratio [RR], ≈1.1 per z‐score increase for both cohorts) and metabolic syndrome (RR, ≈1.2–1.3 per z‐score increase for both cohorts) in 9‐to‐10‐year follow‐up. Conclusions Low‐grade inflammation captured by the novel biomarker GlycA is associated with adverse cardiovascular risk profiles from as early as adolescence and predicts future risk of hypertension and metabolic syndrome in up to 10‐year follow‐up. GlycA is a stable inflammatory biomarker which may capture distinct sources of inflammation in the young and may provide a more sensitive measure than CRP for detecting early cardiovascular risk.

Total joint arthroplasty is one of the surgical option for thumb carpometacarpal (CMC) joint arthritis, however the optimal position the center of rotation (COR) has not been quantified. The purpose of this study is to identify ideal ball-and-socket thumb carpometacarpal joint implants and the optimal position of the COR. We obtained eight right thumb computed tomography images each from ten healthy men, comprising four images each of thumbs at various angles of flexion-extension and abduction-adduction. We reconstructed 3D bone models on 3D CAD, created virtual ball-and-socket implants with three variables (neck offset, implant height, neck rotation), and found the optimal COR where the position change in the COR was smallest across various thumb positions. When the offset was 4.5 mm, neck rotation angle was 130.6° from the radial side to the palmar side of the first metacarpal, and implant height from the distal end of the metacarpal was 43.6 mm, we could restore almost normal kinematics. This study could serve as a reference for implant development and surgical technique guidelines.

Background: Tailored sexuality education for adolescents with intellectual and developmental disabilities is a crucial, yet unmet, need as this population is particularly at risk for sexual abuse and victimisation. However, there are no evidence-based interventions to specifically address this need. This paper presents the development of an intervention framework to address equity in sexuality education and support adolescents with intellectual and developmental disabilities to understand and provide sexual consent, a foundational aspect of sexuality education and sexual health. Methods: The Sexual Health Equity Project team used a Community-Based Participatory Research approach to develop a four-module sexual consent intervention for adolescents with intellectual and developmental disabilities. We leveraged a diverse, interdisciplinary team in a suburban Midwestern school district, and used Backward Design to create objectives and assessments which were rooted in findings from qualitative data by special education teachers. Results: The resulting sexual consent intervention, "Ask Me First--Choices," is comprised of four modules covering topics including definition of sexual consent; decision-making strategies and practice; communicating consent and refusal, identifying situations of consent and non-consent; and legal issues surrounding consent. Each module is divided into five components for content delivery: (1) introduction, (2) lecture, (3) supplemental activity, (4) assessment, and (5) conclusion. We detail the intervention's unique aspects, emphasising areas where we used Universal Design for Learning principles to support teachers' instruction and students' learning. Conclusion: Our efforts to create a sexual consent intervention directly address sexuality education equity issues. We offer commentary on our design process and decisions, as well as recommendations for future groups who want to develop sexual health interventions in similar contexts for students with intellectual and developmental disabilities. Next steps include further testing and validation of the sexual consent intervention to build the evidence-base of sexuality education for adolescents with intellectual and developmental disabilities.

Abstract Aims There are only a few studies on novel biomarkers for incident heart failure (HF). We investigated the association of multiple circulating biomarkers with incident HF in a large prospective population‐based study. Methods and results Conventional risk factors and inflammatory biomarkers were measured, and systemic metabolic measures determined by a high‐throughput serum nuclear magnetic resonance platform in a population‐based Metabolic Syndrome in Men study including 10 106 Finnish men without HF at baseline. During an 8.8 year follow‐up, 172 (1.7%) participants developed HF. Adiponectin, high‐sensitivity C‐reactive protein (hs‐CRP), glycoprotein acetyls, alanine, phenylalanine, glycerol, and pyruvate were associated with incident HF in unadjusted Cox regression analyses, in addition to age, systolic blood pressure, body mass index (BMI), waist circumference, fasting plasma glucose and insulin, haemoglobin A1c (HbA1c), and urinary albumin excretion rate (UAER). After adjustment for age, BMI, diabetes, and statin medication, only adiponectin [hazard ratio (HR) 1.18 (1.10–1.26, P = 4.1E‐08)], pyruvate [HR 1.38 (1.28–1.50, P = 8.2E‐05)], and UAER [HR 1.15 (1.11—1.18, P = 7.8E‐06)] remained statistically significant. In principal component analysis of biomarkers associated with HF in univariate Cox regression analysis, we identified six components, explaining 61.7% of total variance. Four principal components, one with significant loadings on waist, BMI, fasting plasma insulin, interleukin 1 receptor antagonist, and hs‐CRP; another on pyruvate, glycoprotein acetyls, alanine, glycerol and HbA1c; third on age and glomerular filtration rate; and fourth on systolic blood pressure, UAER, and adiponectin, significantly associated with incident HF. Conclusions Several novel metabolic and inflammatory biomarkers were associated with incident HF, suggesting early activation of respective pathways in the pathogenesis of HF.

Animals cannot produce β-carotene, and therefore they exclusively depend on its dietary availability. We previously showed that a 9-cis β-carotene-enriched diet, provided as Dunaliella powder, has a beneficial effect on atherosclerosis and diabetes mellitus in animal models and on lipid profiles, retinitis pigmentosa, and psoriasis in human trials. Therefore, the current study aimed to investigate the bioavailability of 9-cis β-carotene from super-critical CO2-extracted Dunaliella oil in mice. In total, ten 12-week old mice were allocated into two groups: (1) a control-received unfortified diet; (2) a Dunaliella oil diet enriched with Dunaliella oil. Four-week dietary supplementation with Dunaliella oil led to a substantial accumulation of both all-trans and 9-cis β-carotene in the plasma, liver and white adipose tissue. β-carotene was stable in oil preparation, and the 9-cis to all-trans β-carotene ratio was constant (60:40, g/g) after two years of storage at 4°C. These results suggest that supercritically extracted Dunaliella oil can potentially be used as a food supplement.

The supply logistics of energy biomasses generally involves a complex system of supply chains, which aim to achieve timely and cost-efficient feedstock deliveries to biomass demand points. The performance of supply chains is often examined in case studies where spatial data about biomass sources and transportation networks are deployed in varying resolutions and to different geographical extents. In this paper, we have reviewed 94 publications, in which spatial data were used in case studies that focused on analysing and optimising energy biomass supply chains. The reviewed publications were classified into 16 categories, according to the publication year, study methods and objectives, biomass types, supply system complexity and the spatial features of each study area. This review found that the use of geographical information systems in this context has increased in popularity in recent years, and that and the multiformity of the applied methods, study objectives and data sources have increased simultaneously. Another finding was that most of the studies that we reviewed focused on countries in which spatial biomass and transport network data of high quality were unrestrictedly available. Nevertheless, case studies, including spatial data from multiple countries, were represented marginally in the papers that we reviewed. In this paper we also argue that a standard way of reporting geographical contents in biomass case studies should be developed to improve the comprehension and reproducibility of the publications in this field of research.

There is fine-scale spatial heterogeneity in key vegetation properties including leaf-area index (LAI) and biomass in treeless northern peatlands, and hyperspectral drone data with high spatial and spectral resolution could detect the spatial patterns with high accuracy. However, the advantage of hyperspectral drone data has not been tested in a multi-source remote sensing approach (i.e. inclusion of multiple different remote sensing datatypes); and overall, sub-meter-level leaf-area index (LAI) and biomass maps have largely been absent. We evaluated the detectability of LAI and biomass patterns at a northern boreal fen (Halssiaapa) in northern Finland with multi-temporal and multi-source remote sensing data and assessed the benefit of hyperspectral drone data. We measured vascular plant percentage cover and height as well as moss cover in 140 field plots and connected the structural information to measured aboveground vascular LAI and biomass and moss biomass with linear regressions. We predicted both total and plant functional type (PFT) specific LAI and biomass patterns with random forests regressions with predictors including RGB and hyperspectral drone (28 bands in a spectral range of 500–900 nm), aerial and satellite imagery as well as topography and vegetation height information derived from structure-from-motion drone photogrammetry and aerial lidar data. The modeling performance was between moderate and good for total LAI and biomass (mean explained variance between 49.8 and 66.5%) and variable for PFTs (0.3–61.6%). Hyperspectral data increased model performance in most of the regressions, usually relatively little, but in some of the regressions, the inclusion of hyperspectral data even decreased model performance (change in mean explained variance between −14.5 and 9.1%-points). The most important features in regressions included drone topography, vegetation height, hyperspectral and RGB features. The spatial patterns and landscape estimates of LAI and biomass were quite similar in regressions with or without hyperspectral data, in particular for moss and total biomass. The results suggest that the fine-scale spatial patterns of peatland LAI and biomass can be detected with multi-source remote sensing data, vegetation mapping should include both spectral and topographic predictors at sub-meter-level spatial resolution and that hyperspectral imagery gives only slight benefits.

BackgroundVirtual Health and Wellbeing Living Lab Infrastructure is a Horizon 2020 project that aims to harmonize Living Lab procedures and facilitate access to European health and well-being research infrastructures. In this context, this study presents a joint research activity that will be conducted within Virtual Health and Wellbeing Living Lab Infrastructure in the transitional care domain to test and validate the harmonized Living Lab procedures and infrastructures. The collection of data from various sources (information and communications technology and clinical and patient-reported outcome measures) demonstrated the capacity to assess risk and support decisions during care transitions, but there is no harmonized way of combining this information. ObjectiveThis study primarily aims to evaluate the feasibility and benefit of collecting multichannel data across Living Labs on the topic of transitional care and to harmonize data processes and collection. In addition, the authors aim to investigate the collection and use of digital biomarkers and explore initial patterns in the data that demonstrate the potential to predict transition outcomes, such as readmissions and adverse events. MethodsThe current research protocol presents a multicenter, prospective, observational cohort study that will consist of three phases, running consecutively in multiple sites: a cocreation phase, a testing and simulation phase, and a transnational pilot phase. The cocreation phase aims to build a common understanding among different sites, investigate the differences in hospitalization discharge management among countries, and the willingness of different stakeholders to use technological solutions in the transitional care process. The testing and simulation phase aims to explore ways of integrating observation of a patient’s clinical condition, patient involvement, and discharge education in transitional care. The objective of the simulation phase is to evaluate the feasibility and the barriers faced by health care professionals in assessing transition readiness. ResultsThe cocreation phase will be completed by April 2022. The testing and simulation phase will begin in September 2022 and will partially overlap with the deployment of the transnational pilot phase that will start in the same month. The data collection of the transnational pilots will be finalized by the end of June 2023. Data processing is expected to be completed by March 2024. The results will consist of guidelines and implementation pathways for large-scale studies and an analysis for identifying initial patterns in the acquired data. ConclusionsThe knowledge acquired through this research will lead to harmonized procedures and data collection for Living Labs that support transitions in care. International Registered Report Identifier (IRRID)PRR1-10.2196/34573

Decolorization assays allow to assess the ability of white rot fungi to degrade persistent organic molecules such as textile dyes and can contribute to discover microorganisms that can be used for bioremediation. The decolorization can be overlayed by the absorption from metabolites that are produced by fungi during screening, which interfere with the results. To compensate for this interference a method was developed by using different controls to subtract interfering signals.The method was designed for simple screening in multiwell plates that can be operated with a plate reader. It was applied to four different textile dyes (Reactive Black 5, Reactive Blue 4, Reactive Green 19, and Reactive Orange 16) that were degraded by the white rot fungus Phanerochaete velutina. The four textile dyes showed different results with a different degree of interference. The controls allow to compensate for interfering signals and to calculate kinetic parameters for the decolorization reaction and the enzymatic degradation. • Determine the non-enzymatic degradation of the dyes in experiments without fungi. • Determine the absorbance of metabolites and subtract it from the decolorization data to obtain the degradation of the dye. • Determine kinetic parameters of the degradation to compare the efficiency of the enzymes towards dyes.

Patients with bone metastases are treated with long-term bone resorption inhibitors such as bisphosphonates and denosumab. However, resorption inhibitors have been known to cause fractures, such as atypical femoral fractures (AFFs). In recent years, there have been an increasing number of reports of atypical ulna fractures (AUFs) caused by bone resorption inhibitor usage. Treatment of AUFs is complicated, especially when they occur in patients with bone metastases, because it is difficult to discontinue bone resorption inhibitor treatment without the risk of aggravating metastatic lesions. Prophylactic surgery is recommended in AFFs when fractures are predicted, but there are few reports of prophylactic surgery for AUFs. Here, we report a case of incomplete AUF in a 74-year-old woman which was surgically treated with prophylactic plate fixation. The patient had been using denosumab for 6 years to treat bone metastases due to thyroid cancer. After surgery, no fractures were observed for 2 years without discontinuing denosumab, and her forearm function was adequate. AUFs are rare and difficult to treat, so oncologists who treat bone metastases need to pay special attention to diagnose this incomplete AUF before the fracture worsens. We believe that detection of a possible fracture and prophylactic surgery can improve prognosis.