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Background. Heart rhythm disorders, especially atrial fibrillation (AF), are increasing global health challenges. Conventional diagnostic tools for assessment of rhythm disorders suffer from limited availability, limited test duration time, and usability challenges. There is also a need for out-of-hospital investigation of arrhythmias. Therefore, the Norwegian ECG247 Smart Heart Sensor has been developed to simplify the assessment of heart rhythm disorders. The current study aimed to evaluate the diagnostic accuracy and usability of the ECG247 Smart Heart Sensor compared to conventional Holter monitors. Methods. Parallel tests with ECG247 Smart Heart Sensor and a Holter monitor were performed in 151 consecutive patients referred for out-of-hospital long-term ECG recording at Sorlandet Hospital Arendal, Norway. All ECG data were automatically analysed by both systems and evaluated by hospital physicians. Participants were asked to complete a questionnaire scoring usability parameters after the test. Results. A total of 150 patients (62% men, age 54 (±17) years) completed the study. The ECG quality from both monitors was considered satisfactory for rhythm analysis in all patients. AF was identified in 9 (6%) patients during the period with parallel tests. The diagnostic accuracy for automatic AF detection was 95% (95% CI 91–98) for the ECG247 Smart Heart Sensor and 81% (95% CI 74–87) for the Holter system. The proportion of false-positive AF was 4% in tests analysed by the ECG247 algorithm and 16% in tests analysed by the Holter algorithm. Other arrhythmias were absent/rare. The system usability score was significantly better for ECG247 Smart Heart Sensor compared to traditional Holter technology (score 87.4 vs. 67.5, p < 0.001 ). Conclusions. The ECG247 Smart Heart Sensor showed at least comparable diagnostic accuracy for AF and improved usability compared to conventional Holter technology. ECG247 allows for prolonged monitoring and may improve detection of AF. This trial is registered with https://clinicaltrials.gov/ct2/show/NCT04700865.

Every year, numerous environmental disasters and emergencies occur across the globe with far-reaching impacts on human health and the environment. The ability to rapidly assess an environmental emergency to mitigate potential risks and impacts is paramount. However, collating the necessary evidence in the early stages of an emergency to conduct a robust risk assessment is a major challenge. This article presents a methodology developed to help assess the risks and impacts during the early stages of such incidents, primarily to support the European Union Civil Protection Mechanism but also the wider global community in the response to environmental emergencies. An online rapid risk and impact assessment tool has also been developed to promote enhanced collaboration between experts who are working remotely, considering the impact of a disaster on the environment and public health in the short, medium, and long terms. The methodology developed can support the appropriate selection of experts and assets to be deployed to affected regions to ensure that potential public health and environmental risks and impacts are mitigated whenever possible. This methodology will aid defensible decision making, communication, planning, and risk management, and presents a harmonized understanding of the associated impacts of an environmental emergency.

For too long, problem solving has been studied as a solitary and isolated activity where individuals make progress based on personal resources acquired from knowledge, previous experiences or moments of illumination; however, in society, and indeed amongst mathematicians, problem solving can be highly collaborative and occurs in spaces where external resources (technology, the internet, social connections etc.) are abundant. In this paper, we present research into what problem solving looks like in classrooms when it is done collaboratively with access to resources that go beyond the knowledge and past experiences of the individual and even the group. Results indicate that in such choice-affluent environments, students will seek out new resources either when their collective or individual resources run low and will do so either by looking or discussing with others. This manuscript also offers a new methodological tool in the form of, what we call, gaze-dialogue transcripts for documenting such resource acquisition.

The utility of sheer volumes of very high spatial resolution (VHSR) commercial imagery in mapping the Arctic region is new and actively evolving. Commercial satellite sensors typically record image data in low-resolution multispectral (MS) and high-resolution panchromatic (PAN) mode. Spatial resolution is needed to accurately describe feature shapes and textural patterns, such as ice-wedge polygons (IWPs) that are rapidly transforming surface features due to degrading permafrost, while spectral resolution allows capturing of land-use and land-cover types. Data fusion, the process of combining PAN and MS images with complementary characteristics often serves as an integral component of remote sensing mapping workflows. The fusion process generates spectral and spatial artifacts that may affect the classification accuracies of subsequent automated image analysis algorithms, such as deep learning (DL) convolutional neural nets (CNN). We employed a detailed multidimensional assessment to understand the performances of an array of eight application-oriented data fusion algorithms when applied to VHSR image scenes for DLCNN-based mapping of ice-wedge polygons. Our findings revealed the scene dependency of data fusion algorithms and emphasized the need for careful selection of the proper algorithm. Results suggested that the fusion algorithms that preserve spatial character of original PAN imagery favor the DLCNN model performances. The choice of fusion approach needs to be considered of equal importance to the required training dataset for successful applications using DLCNN on VHRS imagery in order to enable an accurate mapping effort of permafrost thaw across the Arctic region.

Contains fulltext : 225351.pdf (Publisher’s version ) (Open Access) BACKGROUND: Fixed-dose combination of calcipotriol (50 μg/g; Cal) and betamethasone dipropionate (0.5 mg/g; BD) foam is approved for plaque psoriasis treatment in adults, with a paucity of data supporting use in adolescents. OBJECTIVES: To evaluate safety of 4 weeks' treatment with Cal/BD foam in adolescent patients with psoriasis, and additional safety outcomes in patients with more severe disease (HPA-axis cohort). Primary objectives included treatment-emergent adverse events (TEAEs) and systemic calcium levels in the overall population, and HPA-axis function, change in calcium excretion and the calcium:creatinine ratio in the HPA-axis cohort. Secondary objectives included exploratory efficacy endpoints [treatment success: change in Psoriasis Area and Severity Index (PASI)]. Systemic exposure to Cal/BD was also assessed. METHODS: A phase II, open-label, study (NCT02387853) in patients (12 to

Background Transcutaneous vagus nerve stimulation (tVNS) has been suggested as a treatment method for depression. Methods A systematic review to systematically evaluate the efficacy of tVNS for the treatment of depression was conducted according to PRISMA guidelines. Primary outcomes were mortality, self-harm, depressive symptoms, and health-related quality of life (HRQoL). Secondary outcomes were anxiety symptoms, medication use, everyday functioning, complications, and patients’ experiences of treatment. Five databases were searched systematically. The included articles were critically appraised and certainty of evidence was assessed using GRADE. Results Two studies evaluating efficacy and a case series collecting data on complications were included. One randomized trial (n = 37) and one cohort study (n = 160) comparing tVNS with sham-tVNS reported significant reduction in the tVNS group of self-rated (SMD = -0.82, 95%-CI = -1.50, -0.15) but not clinician-rated depressive symptoms, after two weeks, and of both self-rated (SMD = -0.99, 95%-CI = -1.32, -0.66) and clinician-rated (SMD = -0.89, 95%-CI = -1.22, -0.57) depressive symptoms, after four weeks, respectively. Furthermore, the cohort study found reduction of both self-rated (SMD = -0.66, 95%-CI = -0.98, -0.34) and clinician-rated (SMD = -0.14, 95%-CI = -0.46, 0.17) anxiety symptoms. One case series (n = 12), collecting data on complications, reported mild to moderate transient side effects. Limitations Available studies are few and heterogeneous, have major study limitations, problems with directness and imprecision. Conclusions It is uncertain whether tVNS reduces depressive symptoms and anxiety. Although existing studies show promising results, further studies are needed to increase the certainty of evidence.

With the rapid advancement of sequencing technologies, next generation sequencing (NGS) analysis has been widely applied in cancer genomics research. More recently, NGS has been adopted in clinical oncology to advance personalized medicine. Clinical applications of precision oncology require accurate tests that can distinguish tumor-specific mutations from artifacts introduced during NGS processes or data analysis. Therefore, there is an urgent need to develop best practices in cancer mutation detection using NGS and the need for standard reference data sets for systematically measuring accuracy and reproducibility across platforms and methods. Within the SEQC2 consortium context, we established paired tumor-normal reference samples and generated whole-genome (WGS) and whole-exome sequencing (WES) data using sixteen library protocols, seven sequencing platforms at six different centers. We systematically interrogated somatic mutations in the reference samples to identify factors affecting detection reproducibility and accuracy in cancer genomes. These large cross-platform/site WGS and WES datasets using well-characterized reference samples will represent a powerful resource for benchmarking NGS technologies, bioinformatics pipelines, and for the cancer genomics studies., Measurement(s)Somatic Mutation AnalysisTechnology Type(s)whole genome sequencing • Whole Exome SequencingFactor Type(s)sequencing platform • sample prepration • library preparation • bioinformatics methodSample Characteristic - OrganismHomo sapiens Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.16713655

OBJECTIVE In PSO-LONG, long-term proactive management (PAM) of psoriasis with fixed-dose combination calcipotriol 50 µg/g and betamethasone dipropionate 0.5 mg/g (Cal/BD) aerosol foam was superior to conventional reactive management. This post-hoc analysis investigated long-term PAM with Cal/BD foam in PSO-LONG patients who could be more susceptible to corticosteroid-induced hypothalamic-pituitary-adrenal (HPA) axis suppression. METHODS Efficacy and safety of PAM with Cal/BD foam (twice-weekly) versus reactive management (twice-weekly vehicle foam), with once-daily rescue Cal/BD foam for four weeks following relapse, was assessed in the HPA subgroup (n = 66); patients had moderate-to-severe psoriasis (physician global assessment score ≥3; 10-30% body surface area affected). Primary endpoint was time to first relapse. RESULTS PAM with Cal/BD foam was associated with longer median time to first relapse (111 versus 31 days), reduced risk of first relapse (hazard ratio: 0.49; p = .029), greater proportion of days in remission (17%; p = .001) and reduced rate of relapse (60% reduction; p

People with severe self-harming behavior and histories of lengthy psychiatric inpatient admissions can represent a challenge to care providers. This interview-based study illuminates healthcare provider experiences (n = 12) of Brief Admission (BA) among self-harming individuals, with >180 days of psychiatric admission the previous year. Qualitative content analysis revealed that providers experienced benefits of increased predictability, and a shift from trigger and conflict to collaboration with individuals admitted to BA. Staff participants expressed an increased sense of safety and a strengthened link between inpatient and outpatient caregiving. Results indicated that BA is a promising intervention for self-harming individuals with extensive psychiatric histories.

Hairdressers are exposed to high levels of chemicals, including possible carcinogens. For dermal exposure, the skin protects against the uptake of chemicals and the protein filaggrin (encoded by FLG) has a key role in skin barrier function. This study investigated if variants of FLG previously linked to impaired skin barrier function, i.e. null mutations and copy number variation (CNV) alleles (CNV10), are associated with cancer-related DNA changes. Blood and questionnaire data were collected from hairdressers (n = 295) and controls (n = 92). Exposure to aromatic amines was measured as hemoglobin adducts by gas chromatography tandem mass spectrometry. DNA from peripheral blood was used to test for FLG null mutations and CNV (10, 11, or 12 repeats), telomere length, and methylation of selected cancer-related genes. Hairdressers had a lower frequency of FLG null mutations (4.1 vs. 7.6%, P = 0.18) and CNV10 (43.2 vs. 56%, P = 0.0032) than controls. In hairdressers, CNV10 carriers had a decreased risk of high ortho-toluidine adducts in blood compared with non-carriers (odds ratio, OR = 0.49, 95% CI = 0.30–0.81). Further, telomere length was shorter for carriers of any FLG null allele (β = −0.18, 95% CI = −0.31 to −0.044) and CNV10 carriers (β = −0.054, 95% CI = −0.11 to −0.00051, linear regression adjusted for age, passive smoking, residence, and education) compared to non-carriers. Carriers of any FLG null allele showed higher methylation of the cyclin-dependent kinase inhibitor 2A gene CDKN2A (OR = 6.26, CI = 1.13–34.7), but not of the other genes analyzed. These associations were not found among the controls. Our study showed that the frequency of FLG CNV10 was lower among hairdressers than controls, which may indicate a healthy worker selection. Moreover, FLG null and CNV10 were associated with cancer-related DNA changes in hairdressers, which may influence their risk of cancer. (Less)

This study described bicycling (C-classes) and tricycling (T-classes) performance in International Cycling Federation road race events between 2011 and 2019. A total of 3,243 race results from 33 events were analyzed. Race velocity was calculated for each result. Bicycling and tricycling data were separately modelled using a linear mixed-effects model. Bicycling velocity was statistically different between all adjacent men's classes (Cohen's d = 0.14 to 0.73), and between the women's C1 and C2 (d = 1.15), and C3 and C4 (d = 0.48) classes. The absence of statistical differences between some women's bicycling classes may be due to a limited number of observations in these classifications. As expected, velocity was statistically different between men's (d = 1.64) and women's (d = 1.38) T1 and T2 classes. Road race performance was hierarchical within the disciplines of bicycling and tricycling, although not all adjacent women's bicycling classes were statistically different. The existence of a performance hierarchy does not necessarily validate the classification system. The integration of information regarding athlete impairment type and severity, with performance data, would provide greater insight into the validity of the classification system, and should be prioritized as an area of future research.

Gene-expression profiling can be used to classify human tumors into molecular subtypes or risk groups, representing potential future clinical tools for treatment prediction and prognostication. However, it is less well-known how prognostic gene signatures derived in one malignancy perform in a pan-cancer context. In this study, a gene-rule-based single sample predictor (SSP) called classifier for lung adenocarcinoma molecular subtypes (CLAMS) associated with proliferation was tested in almost 15 000 samples from 32 cancer types to classify samples into better or worse prognosis. Of the 14 malignancies that presented both CLAMS classes in sufficient numbers, survival outcomes were significantly different for breast, brain, kidney and liver cancer. Patients with samples classified as better prognosis by CLAMS were generally of lower tumor grade and disease stage, and had improved prognosis according to other type-specific classifications (e.g. PAM50 for breast cancer). In all, 99.1% of non-lung cancer cases classified as better outcome by CLAMS were comprised within the range of proliferation scores of lung adenocarcinoma cases with a predicted better prognosis by CLAMS. This finding demonstrates the potential of tuning SSPs to identify specific levels of for instance tumor proliferation or other transcriptional programs through predictor training. Together, pan-cancer studies such as this may take us one step closer to understanding how gene-expression-based SSPs act, which gene-expression programs might be important in different malignancies, and how to derive tools useful for prognostication that are efficient across organs.

Purpose Improved early diagnosis and determination of aggressiveness of prostate cancer (PC) is important to select suitable treatment options and to decrease over-treatment. The conventional marker is total prostate specific antigen (PSA) levels in blood, but lacks specificity and ability to accurately discriminate indolent from aggressive disease. Experimental design In this study, we sought to identify a serum biomarker signature associated with metastatic PC. We measured 157 analytes in 363 serum samples from healthy subjects, patients with non-metastatic PC and patients with metastatic PC, using a recombinant antibody microarray. Results A signature consisting of 69 proteins differentiating metastatic PC patients from healthy controls was identified. Conclusions and clinical relevance The clinical value of this biomarker signature requires validation in larger independent patient cohorts before providing a new prospect for detection of metastatic PC. This article is protected by copyright. All rights reserved.

With the rapid advancement of sequencing technologies in the past decade, next generation sequencing (NGS) analysis has been widely applied in cancer genomics research. More recently, NGS has been adopted in clinical oncology to advance personalized medicine. Clinical applications of precision oncology require accurate tests that can distinguish tumor-specific mutations from errors or artifacts introduced during NGS processes or data analysis. Therefore, there is an urgent need to develop best practices in cancer mutation detection using NGS and the need for standard reference data sets for systematically benchmarking sequencing platforms, library protocols, bioinformatics pipelines and for measuring accuracy and reproducibility across platforms and methods. Within the SEQC2 consortium context, we established paired tumor-normal reference samples, a human triple-negative breast cancer cell line and a matched normal cell line derived from B lymphocytes. We generated whole-genome (WGS) and whole-exome sequencing (WES) data using 16 NGS library preparation protocols, seven sequencing platforms at six different centers. We systematically interrogated somatic mutations in the paired reference samples to identify factors affecting detection reproducibility and accuracy in cancer genomes. These large cross-platform/site WGS and WES datasets using well-characterized reference samples will represent a powerful resource for benchmarking NGS technologies, bioinformatics pipelines, and for the cancer genomics studies. Background & Summary The NGS technology has become a powerful tool for precision medicine. More researchers and clinicians are utilizing NGS to identify clinically actionable mutations in cancer patients and to establish targeted therapies for patients based on the patient’s genetic makeup or genetic variants of their tumor1, there is a critical need to have a full understanding of the many different variables affecting the NGS analysis output. The rapid growing number of sample processing protocols, library preparation methods, sequencing platforms, and bioinformatics pipelines to detect mutations in cancer genome, presents great technical challenges for the accuracy and reproducibility of utilizing NGS for cancer genome mutation detections. To investigate how these experimental and analytical elements may affect mutation detection accuracy, recently we carried out a comprehensive benchmarking study using both whole-genome (WGS) and whole-exome sequencing (WES) data sets generated from two well-characterized reference samples: a human breast cancer cell line (HCC1395) and a B lymphocytes cell line (HCC1395BL) derived from the same donor (NBT-RS47789). We generated WGS and WES data using various NGS library preparation protocols, seven NGS platforms at six centers (NBT-A46164B).

Disease recurrence in surgically treated lung adenocarcinoma (AC) remains high. New approaches for risk stratification beyond tumor stage are needed. Gene expression‐based AC subtypes such as the Cancer Genome Atlas Network (TCGA) terminal‐respiratory unit (TRU), proximal‐inflammatory (PI) and proximal‐proliferative (PP) subtypes have been associated with prognosis, but show methodological limitations for robust clinical use. We aimed to derive a platform independent single sample predictor (SSP) for molecular subtype assignment and risk stratification that could function in a clinical setting. Two‐class (TRU/nonTRU=SSP2) and three‐class (TRU/PP/PI=SSP3) SSPs using the AIMS algorithm were trained in 1655 ACs (n = 9659 genes) from public repositories vs TCGA centroid subtypes. Validation and survival analysis were performed in 977 patients using overall survival (OS) and distant metastasis‐free survival (DMFS) as endpoints. In the validation cohort, SSP2 and SSP3 showed accuracies of 0.85 and 0.81, respectively. SSPs captured relevant biology previously associated with the TCGA subtypes and were associated with prognosis. In survival analysis, OS and DMFS for cases discordantly classified between TCGA and SSP2 favored the SSP2 classification. In resected Stage I patients, SSP2 identified TRU‐cases with better OS (hazard ratio [HR] = 0.30; 95% confidence interval [CI] = 0.18‐0.49) and DMFS (TRU HR = 0.52; 95% CI = 0.33‐0.83) independent of age, Stage IA/IB and gender. SSP2 was transformed into a NanoString nCounter assay and tested in 44 Stage I patients using RNA from formalin‐fixed tissue, providing prognostic stratification (relapse‐free interval, HR = 3.2; 95% CI = 1.2‐8.8). In conclusion, gene expression‐based SSPs can provide molecular subtype and independent prognostic information in early‐stage lung ACs. SSPs may overcome critical limitations in the applicability of gene signatures in lung cancer., What's new? New tools are needed in order to improve risk stratification and therapy selection in early‐stage lung adenocarcinoma. Inherent differences in gene expression between adenocarcinoma subtypes could facilitate the development of such tools. The authors of this study derived platform‐independent, single‐sample predictors (SSP) of adenocarcinoma subtypes, based on gene expression. Derived SSPs successfully provided prognostic information in surgically treated stage I lung adenocarcinoma patients. The single‐sample classifier was readily translated into assays applicable to archival tissue, indicating clinical utility. The findings highlight the clinical relevance of transcriptional signatures and gene expression predictors in lung adenocarcinoma, warranting their further investigation and development.

Climate change is destabilizing permafrost landscapes, affecting infrastructure, ecosystems, and human livelihoods. The rate of permafrost thaw is controlled by surface and subsurface properties and processes, all of which are potentially linked with each other. However, no standardized protocol exists for measuring permafrost thaw and related processes and properties in a linked manner. The permafrost thaw action group of the Terrestrial Multidisciplinary distributed Observatories for the Study of the Arctic Connections (T-MOSAiC) project has developed a protocol, for use by non-specialist scientists and technicians, citizen scientists, and indigenous groups, to collect standardized metadata and data on permafrost thaw. The protocol introduced here addresses the need to jointly measure permafrost thaw and the associated surface and subsurface environmental conditions. The parameters measured along transects include: snow depth, thaw depth, vegetation height, soil texture, and water level. The metadata collection includes data on timing of data collection, geographical coordinates, land surface characteristics (vegetation, ground surface, water conditions), as well as photographs. Our hope is that this openly available dataset will also be highly valuable for validation and parameterization of numerical and conceptual models, and thus to the broad community represented by the T-MOSAiC project.

We developed a high-throughput mapping workflow, which centers on deep learning (DL) convolutional neural network (CNN) algorithms on high-performance distributed computing resources, to automatically characterize ice-wedge polygons (IWPs) from sub-meter resolution commercial satellite imagery. We applied a region-based CNN object instance segmentation algorithm, namely the Mask R-CNN, to automatically detect and classify IWPs in North Slope of Alaska. The central goal of our study was to systematically expound the DLCNN model interoperability across varying tundra types (sedge, tussock sedge, and non-tussock sedge) and image scene complexities to refine the understanding of opportunities and challenges for regional-scale mapping applications. We corroborated quantitative error statistics along with detailed visual inspections to gauge the IWP detection accuracies. We found promising model performances (detection accuracies: 89% to 96% and classification accuracies: 94% to 97%) for all candidate image scenes with varying tundra types. The mapping workflow discerned the IWPs by exhibiting low absolute mean relative error (AMRE) values (0.17&ndash, 0.23). Results further suggest the importance of increasing the variability of training samples when practicing transfer-learning strategy to map IWPs across heterogeneous tundra cover types. Overall, our findings demonstrate the robust performances of IWPs mapping workflow in multiple tundra landscapes.

Background: Diagnosis of skin diseases is often challenging and computer-aided diagnostic tools are urgently needed to underpin decision making. Objective: To develop a convolutional neural network model to classify clinically relevant selected multiple-lesion skin diseases, this in accordance to the STARD guidelines. Methods: This was an image-based retrospective study using multi-task learning for binary classification. A VGG-16 model was trained on 16,543 non-standardized images. Image data was distributed in training set (80%), validation set (10%), and test set (10%). All images were collected from a clinical database of a Danish population attending one dermatological department. Included was patients categorized with ICD-10 codes related to acne, rosacea, psoriasis, eczema, and cutaneous t-cell lymphoma. Results: Acne was distinguished from rosacea with a sensitivity of 85.42% CI 72.24–93.93% and a specificity of 89.53% CI 83.97–93.68%, cutaneous t-cell lymphoma was distinguished from eczema with a sensitivity of 74.29% CI 67.82–80.05% and a specificity of 84.09% CI 80.83–86.99%, and psoriasis from eczema with a sensitivity of 81.79% CI 78.51–84.76% and a specificity of 73.57% CI 69.76–77.13%. All results were based on the test set. Conclusion: The performance rates reported were equal or superior to those reported for general practitioners with dermatological training, indicating that computer-aided diagnostic models based on convolutional neural network may potentially be employed for diagnosing multiple-lesion skin diseases.

Metals in solid propellants are used to improve specific impulse and increment the energy density. Their combustion generates condensed products that move along the motor chamber and are expelled through the nozzle. The discharge of liquid or solid particles across the gas dynamic nozzle of large boosters is not only a matter of specific impulse loss. Recent climatological studies are addressing possible short and long term environmental effects that may be attributed to space launch activity by large launchers. In this respect, the knowledge of plume content and, specifically, of physical, chemical, and morphological properties of the exhausted particulate is needed. In the frame of the EMAP (Experimental Modelling of Alumina Particulate in Solid Booster) project, an activity financed by the European Space Agency, the Space Propulsion Laboratory (SPLab) of Politecnico di Milano developed a collection method and an analysis protocol for the characterization of the particles contained in the rocket plume. The collection is performed by an intrusive probe capable of capturing the particles directly from the nozzle exit and quenching them. The post-collection protocol enables size measurement, chemical characterization, and morphology observation. In this paper an overview of the collection and analysis activity is presented, along with the final results that were achieved by analyzing the plume of different rocket motors.

Background Glioblastoma is the most common primary malignant brain tumor in adults. Previous studies have suggested that CRP (C-reactive protein) could serve as a biomarker candidate as well as a prognostic factor in glioblastoma patients, and we here further investigate its potential role. Materials and methods Publicly available datasets were used to compare gene expression between brain samples from glioblastoma patients and non-tumor tissue. The structure of CRP was compared between humans and rats. Glioblastoma cells from humans and rats were stained with anti-CRP. Fischer 344 rats were inoculated with syngeneic glioblastoma cells pre-coated with anti-CRP, and survival was monitored. CRP concentration in rats carrying glioblastoma was followed. Results CRP was upregulated on one locus on gene level in glioblastoma tissue as compared to non-tumor brain tissue, but not in glioma stem cells as compared to neural stem cells. The structure of the CRP protein was a characteristic pentamer in both humans and rats. Both human and rat glioblastoma cells were clearly positive for anti-CRP staining. Pre-coating of glioblastoma cells with anti-CRP antibodies did not affect survival in rats with intracranial tumors. Serum levels of CRP increased during tumor progression but did not reach significantly different levels. Conclusions Both human and rat glioblastoma cells could be stained with anti-CRP antibodies in vitro. In a syngeneic glioblastoma rat model we could see an increase in serum CRP during tumor progression, but coating glioblastoma cells with anti-CRP antibodies did not provide any survival change for the animals.

Topical psoriasis treatment relies on a reactive rather than a long-term proactive approach to disease relapse.Assess long-term efficacy and safety of proactive psoriasis management with twice-weekly calcipotriene 0.005%/betamethasone dipropionate 0.064% (Cal/BD) foam.Phase III trial (NCT02899962) included a 4-week open-label lead-in phase (Cal/BD foam once daily) and a 52-week, randomized, double-blind, maintenance phase. A total of 545 patients achieved treatment success (physician's global assessment "clear"/"almost clear," ≥2-grade improvement from baseline) and were randomized to proactive management (Cal/BD foam; n = 272) or reactive management (vehicle foam; n = 273) twice-weekly, with rescue treatment of Cal/BD foam once daily for 4 weeks upon relapse. Primary endpoint was time to first relapse (physician's global assessment "mild" or higher).A total of 251 randomized patients (46.1%) completed the trial. Median time to first relapse was 56 days (proactive) and 30 days (reactive). Patients in the proactive group had an additional 41 days in remission compared with the reactive group over 1 year (P .001). Number of relapses per year of exposure was 3.1 (proactive) and 4.8 (reactive). Cal/BD foam was well tolerated.Maintenance phase dropout rate (53.9%) was within the expected range but provides challenges in statistical analysis.Long-term proactive management with Cal/BD foam demonstrated superior efficacy vs reactive management.

Vast mosaics of lakes, wetlands, and rivers on the Arctic Coastal Plain give the impression of water surplus. Yet long winters lock freshwater resources in ice, limiting freshwater habitats and water supply for human uses. Increasingly the petroleum industry relies on lakes to build temporary ice roads for winter oil exploration. Permitting water withdrawal for ice roads in Arctic Alaska is dependent on lake depth, ice thickness, and the fish species present. Recent winter warming suggests that more winter water will be available for ice- road construction, yet high interannual variability in ice thickness and summer precipitation complicates habitat impact assessments. To address these concerns, multidisciplinary researchers are working to understand how Arctic freshwater habitats are responding to changes in both climate and water use in northern Alaska. The dynamics of habitat availability and connectivity are being linked to how food webs support fish and waterbirds across diverse freshwater habitats. Moving toward watershed-scale habitat classification coupled with scenario analysis of climate extremes and water withdrawal is increasingly relevant to future resource management decisions in this region. Such progressive refinement in understanding responses to change provides an example of adaptive management focused on ensuring responsible resource development in the Arctic.

State-of-the-art deep learning technology has been successfully applied to relatively small selected areas of very high spatial resolution (0.15 and 0.25 m) optical aerial imagery acquired by a fixed-wing aircraft to automatically characterize ice-wedge polygons (IWPs) in the Arctic tundra. However, any mapping of IWPs at regional to continental scales requires images acquired on different sensor platforms (particularly satellite) and a refined understanding of the performance stability of the method across sensor platforms through reliable evaluation assessments. In this study, we examined the transferability of a deep learning Mask Region-Based Convolutional Neural Network (R-CNN) model for mapping IWPs in satellite remote sensing imagery (~0.5 m) covering 272 km2 and unmanned aerial vehicle (UAV) (0.02 m) imagery covering 0.32 km2. Multi-spectral images were obtained from the WorldView-2 satellite sensor and pan-sharpened to ~0.5 m, and a 20 mp CMOS sensor camera onboard a UAV, respectively. The training dataset included 25,489 and 6022 manually delineated IWPs from satellite and fixed-wing aircraft aerial imagery near the Arctic Coastal Plain, northern Alaska. Quantitative assessments showed that individual IWPs were correctly detected at up to 72% and 70%, and delineated at up to 73% and 68% F1 score accuracy levels for satellite and UAV images, respectively. Expert-based qualitative assessments showed that IWPs were correctly detected at good (40–60%) and excellent (80–100%) accuracy levels for satellite and UAV images, respectively, and delineated at excellent (80–100%) level for both images. We found that (1) regardless of spatial resolution and spectral bands, the deep learning Mask R-CNN model effectively mapped IWPs in both remote sensing satellite and UAV images; (2) the model achieved a better accuracy in detection with finer image resolution, such as UAV imagery, yet a better accuracy in delineation with coarser image resolution, such as satellite imagery; (3) increasing the number of training data with different resolutions between the training and actual application imagery does not necessarily result in better performance of the Mask R-CNN in IWPs mapping; (4) and overall, the model underestimates the total number of IWPs particularly in terms of disjoint/incomplete IWPs.

Programa Infantes y Salud Ambiental Programa ISA ISA Infants' Environmental Health Study Infants' Environmental Health Program ISA birth cohort Background:Pesticides and metals may disrupt thyroid function, which is key to fetal brain development.Objectives:To evaluate if current-use pesticide exposures, lead and excess manganese alter free thyroxine (FT4),freetriiodothyronine(FT3), and thyroidstimulatinghormone (TSH) concentrationsinpregnant women fromtheInfants' Environmental Health Study (ISA).Methods:At enrollment, we determined women's (n=400)specific-gravity corrected urinary pesticide (μg/L)metabolite concentrations of mancozeb (ethylene thiourea (ETU)), pyrimethanil, thiabendazole, chlorpyrifos,synthetic pyrethroids, and 2,4-D. We also measured manganese hair (MnH) (μg/g) and blood (MnB) (μg/L),and blood lead (PbB) (μg/L) concentrations. To detect an immediate and late effect on thyroid homeostasis, wedetermined TSH, FT4 and FT3 in serum obtained at the same visit (n= 400), and about ten weeks afterwards (n= 245). We assessed associations between exposures and outcomes with linear regression and general addi-tive models, Bayesian multivariate linear regression, and Bayesian kernel machine regression.Results:About 80%, 94%, and 100% of the women had TSH, FT4, and FT3 within clinical reference ranges, respec-tively. Women with higher urinary ETU, and pyrimethanil-metabolites, had lower FT4:β=−0.79 (95%CI =−1.51,−0.08) andβ=−0.29 (95%CI =−0.62,−0.03), respectively, for each tenfold increase in exposure.MnB was positively associated with FT4 (β= 0.04 (95%CI = 0.00, 0.07 per 1μg/L increase), and women withhigh urinary pyrethroid-metabolite concentrations had decreased TSH (non-linear effects). For the late-effectanalysis, metabolites of pyrethroids and chlorpyrifos, as well as MnH, and PbB were associated decreased TSH,or increased FT4 and/or FT3.Discussion:Mancozeb (ETU) and pyrimethanil may inhibit FT4 secretion (hypothyroidism-like effect), whilechlorpyrifos, pyrethroids, MnB, MnH, PbB and Mn showed hyperthyroidism-like effects. Some effects on thyroidhomeostasis seemed to be immediate (mancozeb (ETU), pyrimethanil, MnB), others delayed (chlorpyrifos, MnH,PbB), or both (pyrethroids), possibly reflecting different mechanisms of action. Antecedentes: los pesticidas y los metales pueden alterar la función tiroidea, que es clave para el desarrollo del cerebro fetal.Objetivos: Evaluar si la exposición a pesticidas de uso actual, el plomo y el exceso de manganeso alteran la tiroxina libre (FT4), la triyodotironina libre (FT3) y la hormona estimulante de la tiroides (TSH) Métodos: En el momento de la inscripción, determinamos las concentraciones urinarias de plaguicidas (μg / L) de plaguicida corregido por gravedad específica (μg / L) de mujeres (n = 400) de mancozeb (etilen tiourea (ETU)), pirimetanil, tiabendazol en mujeres embarazadas. , clorpirifos, piretroides sintéticos y 2,4-D. También medimos las concentraciones de manganeso en cabello (MnH) (μg / g) y sangre (MnB) (μg / L), y de plomo en sangre (PbB) (μg / L). Para detectar un efecto inmediato y tardío sobre la homeostasis tiroidea, determinamos TSH, FT4 y FT3 en el suero obtenido en la misma visita (n = 400) y aproximadamente diez semanas después (n = 245). Evaluamos las asociaciones entre las exposiciones y los resultados con regresión lineal y modelos aditivos generales, regresión lineal multivariante bayesiana y regresión de máquina de kernel bayesiana. Resultados: Aproximadamente el 80%, 94% y 100% de las mujeres tenían TSH, FT4 y FT3 dentro de los rangos de referencia clínica, respectivamente. Las mujeres con mayor ETU urinaria y metabolitos de pirimetanilo tenían menor FT4: β = −0,79 (IC del 95% = −1,51, −0,08) y β = −0,29 (IC del 95% = −0,62, −0,03), respectivamente, para cada El MnB se asoció positivamente con FT4 (β = 0,04 (IC del 95% = 0,00, 0,07 por aumento de 1 μg / L), y las mujeres con concentraciones altas de metabolitos piretroides en orina tenían TSH disminuida (efectos no lineales). análisis de efectos tardíos, metabolitos de piretroides y clorpirifos, así como MnH y PbB se asociaron con disminución de TSH o aumento de FT4 y / o FT3. Discusión: Mancozeb (ETU) y pirimetanilo pueden inhibir la secreción de FT4 (efecto similar al hipotiroidismo), mientras que el clorpirifos , piretroides, MnB, MnH, PbB y Mn mostraron efectos similares al hipertiroidismo. Algunos efectos sobre la homeostasis tiroidea parecían ser inmediatos (mancozeb (ETU), pirimetanil, MnB), otros retardados (clorpirifos, MnH, PbB) o ambos (piretroides) , posiblemente reflejando diferentes mecanismos de acción. Universidad Nacional, Costa Rica Lund University, Sweden University of California at Berkeley, United States Federal University of Bahia, Brasil University of California, United States Université du Québec à Montréal, Canada North Carolina State University, United States Instituto Regional de Estudios en Sustancias Tóxicas

Background To investigate the outcome of an integrated individual and family therapy (Intensive Contextual Treatment: ICT) in terms of reducing suffering and increasing functional adjustment among self-harming and/or suicidal adolescents with high symptom loads and their families. Methods Forty-nine self-harming and/or suicidal adolescents, Mage = 14.6, of predominantly Swedish origin and female gender (85.7%) participated with their parents. The study had a within group design with repeated measures at pre- and post-treatment, as well as six- and twelve-months follow-ups. Self-reports were used for the main outcomes; self-harm rates, suicide attempts, parent-reported days of inpatient/institutional care, internalized and externalized symptoms, perceived stress, emotion regulation, school hours and adjustment. Secondary outcomes were levels of reported expressed emotions within family dyads, as well as parental anxiety, depression and stress. Results From pre- to post-assessment, the adolescents reported significant reductions of self-harm (p = .001, d = 0.54) and suicide attempts (p

Introduction The clinical environment has been increasingly acknowledged as an important setting for learning within healthcare professional education. In particular, researchers have highlighted the need to advance the knowledge on the social nature of learning in the workplace setting. The aim of the thesis was to explore workplace learning among undergraduate medical and nursing students. Method The thesis adopted a socio-cultural perspective on learning and employed a qualitative approach embedded in an interpretative tradition of inquiry. Four consecutive studies were included in the thesis, the first one designed according to qualitative description whereas the other three had an ethnographic approach. Data were collected through individual interviews and field observations. Content analysis and thematic analysis were employed. Results For the medical students, workplace learning entailed access to a variety of activities in the role of a marginal member of the healthcare team. Medical students demonstrated an adaptive approach to workplace learning. For the nursing students, workplace learning involved being entrusted to hold responsibility for patient care and the need to negotiate their basic values with those of the workplaces. Nursing students showed a hesitant approach to workplace learning. Discussion Workplace learning was built upon varying theoretical perspectives of learning in the medical and nursing contexts respectively. The main message in the thesis argued for an upgrading of students as a powerful and active stakeholder in workplace learning, so as not to view students as passive consumers of clinical education.

Brief admission (BA) is an adjunctive treatment option for individuals with self-harming behavior, having traits of borderline personality disorder (BPD). It is offered alongside outpatient psychotherapy for the purpose of strengthening autonomy, self-reflection and self-care and to increase the likelihood of being able to stay in therapy by avoiding lengthy inpatient hospitalizations.To investigate participants' experiences with BA during the pilot phase of the Brief Admission Skåne Randomized Controlled Trial (BASRCT), in order to detect possible strengths and limitations of the intervention and gain knowledge to facilitate implementation of BA at other treatment centers.Eight participants randomized to BA were interviewed to obtain their experience of BA, or alternatively their reasons for choosing not to use BA. Thematic analysis was conducted upon their transcribed interviews.Reported as most helpful by the participants was the structure/routines at the ward and the positive attitudes from the staff. However, some individuals reported problems with perceived negative attitudes from the staff administering BA and negative rumination about themselves. The reported reasons to request BA were: preventing urges to self-harm from escalating; ending isolation; preventing longer admissions and forced admission; feelings of emotional exhaustion, and the need for rest and support in re-creating a daily routine. Reasons for not requesting BA were fear of rejection, questioning the method; presumed room shortage; difficulties in deciding whether one's problems are serious enough; experiencing the situation to be too clinically acute.The results from this study indicated the importance of repeated staff education on all aspects of BA when it is being newly implemented, as well as the importance of working with attitudes of staff delivering BA. These were the key ingredients in making BA implementation successful. Our findings may be of value to other treatment centers implementing BA for the first time.NCT02985047.

Epithelial ovarian cancer (OC) is a disease with high mortality due to vague early clinical symptoms. Benign ovarian cysts are common and accurate diagnosis remains a challenge because of the molecular heterogeneity of OC. We set out to investigate whether the disease diversity seen in ovarian cyst fluids and tumor tissue could be detected in plasma. Using existing mass spectrometry (MS)-based proteomics data, we constructed a selected reaction monitoring (SRM) assay targeting peptides from 177 cancer-related and classical proteins associated with OC. Plasma from benign, borderline, and malignant ovarian tumors were used to verify expression (n = 74). Unsupervised and supervised multivariate analyses were used for comparisons. The peptide signatures revealed by the supervised multivariate analysis contained 55 to 77 peptides each. The predictive (Q2) values were higher for benign vs. low-grade serous Q2 = 0.615, mucinous Q2 = 0.611, endometrioid Q2 = 0.428 and high-grade serous Q2 = 0.375 (stage I–II Q2 = 0.515, stage III Q2 = 0.43) OC compared to benign vs. all malignant Q2 = 0.226. With targeted SRM MS we constructed a multiplexed assay for simultaneous detection and relative quantification of 185 peptides from 177 proteins in only 20 µL of plasma. With the approach of histology-specific peptide patterns, derived from pre-selected proteins, we may be able to detect not only high-grade serous OC but also the less common OC subtypes.

Through an exploration of the interdependence between workplace affordances and individual engagement, this study addressed how medical students interact with clinical learning environments (CLEs). Building on the workplace participatory practices approach outlined by Billett, CLEs can be viewed as constructed through a negotiation of meaning between the workplace and the student. Inspired by ethnography, an observational study using field observations and follow-up interviews was performed. Workplace affordances included being given a marginal status in the healthcare team which students adapted to through striving to fit into the workplace. Further, there were many potential activities available to students; however, students seemed selective in terms of what activities they elected to engage in. As such, interacting with CLEs entailed students navigating complexity without the immediate access to any explicit ‘map’ of workplace learning. This study indicates that workplaces increasingly need to...

Author(s): Eichenfield, LF; Marcoux, D; Kurvits, M; Liljedahl, M | Abstract: BackgroundPsoriasis is a disease that commonly manifests in adolescence. Up to half of adults with psoriasis develop it before the age of 20. Topical formulations containing corticosteroids and/or vitamin D3 analogs are recommended for treatment.ObjectiveThis phase II study aimed to evaluate the safety, including any potential effect on the hypothalamic-pituitary-adrenal axis and calcium metabolism, and efficacy of fixed-dose combination calcipotriene (0.005%) and betamethasone (0.064% as dipropionate) (Cal/BD) gel in adolescents with psoriasis.MethodsPatients aged 12 to l17nyears, with at least mild psoriasis on the body and scalp, received topical Cal/BD gel once daily for ≤8nweeks. Safety response criteria included adverse drug reactions [ADRs; any adverse event (AE) possibly or probably related to treatment as determined by the investigator; a primary response criterion] and AEs (a secondary response criterion). Only treatment-emergent AEs (events that occurred after the first application of Cal/BD gel or events which started before this and increased in intensity after the first application of Cal/BD gel) are presented here. Efficacy response criteria included controlled disease, by physician's global assessment of disease severity (PGA), following Cal/BD gel treatment.ResultsA total of 107 patients (median age 14nyears; range 12-16) were enrolled and treated. Eight ADRs were observed in 7 (7%) patients and 38 (36%) patients experienced ≥1 AE. The most common AEs were headache [6 (6%) patients], nasopharyngitis [6 (6%) patients] and blood parathyroid hormone increased [4 (4%) patients]. One severe AE was reported (attempted suicide) but was considered unrelated to treatment. At the end of treatment, 58% of patients had controlled disease on the body and 69% on the scalp according to PGA.ConclusionIn this uncontrolled phase II study, Cal/BD gel was well tolerated and effective for treating scalp and body psoriasis in adolescents.

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The microtopography associated with ice-wedge polygons governs many aspects of Arctic ecosystem, permafrost, and hydrologic dynamics from local to regional scales owing to the linkages between microtopography and the flow and storage of water, vegetation succession, and permafrost dynamics. Wide-spread ice-wedge degradation is transforming low-centered polygons into high-centered polygons at an alarming rate. Accurate data on spatial distribution of ice-wedge polygons at a pan-Arctic scale are not yet available, despite the availability of sub-meter-scale remote sensing imagery. This is because the necessary spatial detail quickly produces data volumes that hamper both manual and semi-automated mapping approaches across large geographical extents. Accordingly, transforming big imagery into ‘science-ready’ insightful analytics demands novel image-to-assessment pipelines that are fueled by advanced machine learning techniques and high-performance computational resources. In this exploratory study, we tasked a deep-learning driven object instance segmentation method (i.e., the Mask R-CNN) with delineating and classifying ice-wedge polygons in very high spatial resolution aerial orthoimagery. We conducted a systematic experiment to gauge the performances and interoperability of the Mask R-CNN across spatial resolutions (0.15 m to 1 m) and image scene contents (a total of 134 km2) near Nuiqsut, Northern Alaska. The trained Mask R-CNN reported mean average precisions of 0.70 and 0.60 at thresholds of 0.50 and 0.75, respectively. Manual validations showed that approximately 95% of individual ice-wedge polygons were correctly delineated and classified, with an overall classification accuracy of 79%. Our findings show that the Mask R-CNN is a robust method to automatically identify ice-wedge polygons from fine-resolution optical imagery. Overall, this automated imagery-enabled intense mapping approach can provide a foundational framework that may propel future pan-Arctic studies of permafrost thaw, tundra landscape evolution, and the role of high latitudes in the global climate system.

Objective: There has been increasing scholarly interest in the role of environments in health care professional education, and the value of these has been widely acknowledged as an influential factor in educational quality. However, little is known about how teachers experience the environment, and there is a recognizable absence of a perspective from chiropractic and physiotherapy faculties. The aim of this study was to explore and contrast chiropractic and physiotherapy teachers' experiences and conceptualizations of the meaning of the educational environment. Methods: In this qualitative study, we performed semistructured interviews with 14 teachers, purposefully selected to obtain richness, variation, and breadth in the data. The data were analyzed using inductive qualitative content analysis. Results: The most noteworthy findings were, first, that chiropractic teachers experienced the meaning of the environment as motivating a vocational practice and modeling ideal, supporting and managing stressed students, and including students in the community of chiropractors. Physiotherapy teachers experienced the meaning of the environment as putting the pedagogical vision into practice, balancing students' expectations, and providing the prerequisites to grow within the profession. Second, both groups of teachers held common conceptualizations of the constituents of the environment as physical, organizational, relational, communicational, and pedagogical; however, they attached different connotations to these dimensions. Conclusion: The findings conveyed a variance in the experience of the meaning of the educational environment that can be attributed to contextual and cultural differences.

The field of fault detection and diagnosis has been the subject of considerable interest in industry. Fault detection may increase the availability of products, thereby improving their quality. Fau ...

Homoepitaxial layers of fluorescent 4H-SiC were grown on 4 degree off-axis substrates by sublimation epitaxy. Luminescence in the green spectral range was obtained by co-doping with nitrogen and boron utilizing donor-acceptor pair luminescence. This concept opens possibilities to explore green light emitting diodes using a new materials platform.

In this paper we present a concept on the defect generation and annihilation during the homoepitaxial growth step of cubic silicon carbide by sublimation epitaxy on templates grown by chemical vapor deposition on silicon substrates. Several structural defects like stacking faults, twins and star defects show opposite evolution from the template layer into the sublimation grown material. While single planar defects tend to annihilate with increasing layer thickness, the defect clusters assigned to the star defects are enlarging. These issues contribute to a balance of how to achieve the best possible quality on thick layers.

Background Belongingness has been argued to be a prerequisite for students’ learning in the clinical setting but making students feel like they belong to the workplace is a challenge. From a sociocultural perspective, workplace participatory practices is a framework that views clinical learning environments to be created in interaction between students and the workplace and hence, are dependent on them both. The aim of this study was to explore the interdependence between affordances and engagement in clinical learning environments. The research question was: How are nursing students influenced in their interactions with clinical learning environments? Methods An observational study with field observations and follow-up interviews was performed. The study setting comprised three academic teaching hospitals. Field observations included shadowing undergraduate nursing students during entire shifts. Fifty-five hours of field observations and ten follow-up interviews with students, supervisors and clinical managers formed the study data. A thematic approach to the analysis was taken and performed iteratively with the data collection. Results The results revealed that students strived to fill out the role they were offered in an aspirational way but that they became overwhelmed when given the responsibility of care. When students’ basic values did not align with those enacted by the workplace, they were not willing to compromise their own values. Workplaces succeeded in inviting students into the community of nurses and the practice of care. Students demonstrated hesitance regarding their desire to belong to the workplace community. Conclusion The results imply that the challenge for clinical education is not to increase the experience of belongingness but to maintain students’ critical and reflective approach to health care practice. Additionally, results suggest students to be included as an important stakeholder in creating clinical learning environments rather than being viewed as consumer of clinical education. Electronic supplementary material The online version of this article (doi:10.1186/s12909-016-0721-2) contains supplementary material, which is available to authorized users.

In this work a new approach for the production of freestanding cubic silicon carbide (3C SiC) in (001) orientation is presented which is based on the combination of chemical vapor deposition (CVD) and the fast sublimation growth process (FSGP). Fast homoepitaxial growth of 3C SiC using sublimation epitaxy on a template created by CVD growth on silicon substrates allows to obtain thick freestanding material with low defect densities. Using standard silicon wafers as substrate material permits a cost efficient process and the applying of wafers with different orientations. The (001) orientation used in this work will potentially allow further heteroepitaxial growth of other cubic semiconductors, like e.g. gallium nitride (GaN).

The aim of the study was to describe, using qualitative phenomenographic interviews, how physiotherapists experience client participation in physiotherapy interventions. The objective of phenomenographic research is to identify and describe various ways of experiencing the investigated phenomenon. Eleven respondents were strategically selected according to the maximum variation strategy with variations in: gender, seniority and areas of physiotherapy. Three qualitatively different descriptive categories were indentified with critical variations in paradigms of health and goal-setting procedures – A: Collaboration, i.e. an experience of client participation from a biopsychosocial collaborative view of intervention in which the client enter into equal partnership with the physiotherapist and thereby are jointly responsible for intervention, goal-setting and outcome; B: Guidance, i.e. an experience of client participation from a guided biomedical view of intervention, in which the client is guided by...

The application of bonded 'straps' has been proposed for extending the fatigue life of aircraft structures, particularly for integral structures with low inherent crack-retarding capability. A potential disadvantage in the use of bonded crack retarders is the difference between the coefficients of thermal expansion between the strap and substrate materials, which causes residual stresses when the temperature deviates from the curing or assembly temperature. The evolution of these stresses in flight is important to take into account to accurately assess the fatigue crack growth behaviour of the structure. In this work, the residual strains in an aluminium compact-tension sample adhesively reinforced with a titanium strap have been measured with neutron diffraction and modelled with a finite element approach at room temperature and at −50 °C. It was found that a linear elastic approach could accurately be used to predict the residual stresses. The residual stresses were found to be about twice as large at −50 °C as at room temperature.

In this work the evolution of the residual stresses in a MIG-welded 2024-T3 aluminium alloy M(T) specimen during in situ fatigue crack growth at constant load amplitude has been measured with neutron diffraction. The plastic relaxation and plasticity-induced residual stresses associated with the fatigue loading were found to be small compared with the stresses arising due to elastic re-distribution of the initial residual stress field. The elastic re-distribution was modelled with a finite element simulation and a good correlation between the experimentally-determined and the modelled stresses was found. A significant mean stress effect on the fatigue crack growth rate was seen and this was also accurately predicted using the measured initial residual stresses.