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Background The clinical benefit of cusatuzumab, a CD70-directed monoclonal antibody with enhanced effector functions, was investigated in patients with relapsed/refractory (R/R) cutaneous T-cell lymphoma (CTCL). Methods In this cohort expansion of the ARGX-110-1201 study, 27 patients with R/R CTCL received cusatuzumab at 1 (n = 11) or 5 mg/kg (n = 16) once every 3 weeks to investigate its safety, dose, and exploratory efficacy. The pharmacokinetics, immunogenicity, CD70 expression, and CD70/CD27 biology were also assessed. Results The most common adverse events included infusion-related reactions, pyrexia, and asthenia. Eighteen serious adverse events (grade 1-3) were reported in 11 patients; 1 of these (vasculitis) was considered drug-related. For 8 of the 11 patients receiving 1 mg/kg, anti-drug antibodies (ADAs) affected the minimal concentration, and this resulted in undetectable cusatuzumab concentrations at the end of treatment and, in some cases, a loss of response. This effect was greatly reduced in the patients receiving 5 mg/kg. The overall response rate was 23%; this included 1 complete response and 5 partial responses (PRs) in 26 of the 27 evaluable patients. In addition, 9 patients achieved stable disease. The mean duration on cusatuzumab was 5.2 months, and the median duration was 2.5 months. Patients with Sezary syndrome (SS) achieved a 60% PR rate with a dosage of 5 mg/kg and a 33% PR rate with a dosage of 1 mg/kg; this resulted in an overall response rate of 50% for patients with SS at both doses. Conclusions Cusatuzumab was well tolerated, and antitumor activity was observed at both 1 and 5 mg/kg in highly pretreated patients with R/R CTCL. The observed dose-dependent effect on exposure supports the use of 5 mg/kg for future development.

Extreme weather events are expected to increase with climate change. Such events are detrimental for local economic activity but could also affect countries that are not directly exposed through global agricultural production shortfalls and price surges. Here, estimations for 75 countries show that increases in global agricultural commodity prices caused by harvest or weather disruptions in other regions of the world significantly curtail economic activity. The impact is considerably stronger in advanced countries, despite relatively lower shares of food in household expenditures. Effects are weaker when countries are net exporters of agricultural products, have large agricultural sectors and/or are less integrated in global markets for non-agricultural trade. Once we control for these characteristics, the relationship between the country’s income per capita and the economic repercussions becomes negative. Overall, these findings suggest that the consequences of climate change on advanced countries, particularly through food prices, may be larger than previously thought. Extreme weather events such as heatwaves and droughts are likely to occur more often under climate change. Such events can have an indirect effect on countries through global agricultural markets and food prices; this impact is stronger for higher-income than lower-income countries.

Objective:To compare actual patient presentation rates from Belgium’s largest public open-air cultural festival with predictions provided by existing models and the Belgian Plan Risk Manifestations model.Methods:Retrospectively, actual patient presentation rates gathered from the Ghent Festivities (Belgium) during 2013–2019 were compared to predicted patient presentation rates by the Arbon, Hartman, and PRIMA models.Results:During 7 editions, 8673000 people visited the Ghent Festivities; 9146 sought medical assistance resulting in a mean patient presentation rate (PPR) of 1.05. The PRIMA model overestimated the number of patient encounters for each occasion. The other models had a high rate of underprediction. When comparing deviations in predictions between the PRIMA model to the other models, there is a significant difference in the mean deviation (Arbon: T = 0.000, P < 0.0001, r = −0.8701; Hartman: T = 0.000, P < 0.0001, r = −0.869).Conclusion:Despite the differences between the predictions of all 3 models, our results suggest that the PRIMA model is a valid tool to predict patient presentations to IEHS during public cultural MG. However, to substantiate the PRIMA model even further, more research is needed to further validate the model for a broad range of MG.

Currently, researchers are more focusing on eco-friendly materials, sustainability, and low consumption of energy during the stage of handling, low initial cost, have appropriate mechanical properties and biodegradable and less susceptible to health hazards are the main challenge facing in the present day across the world especially to developing new materials that would improve the industrial supplies for making lightweight materials. Therefore; natural cellulosic fiber one, of effective strategies to substitute artificial fibers for its own benefits when compared and mainly concentrating to reinforce polymer matrices by natural cellulosic fiber due to their decomposable characteristic in nature. This an overview mainly discussed on commonly available natural fiber property such as physical property, chemical composition analysis, surface morphology analysis such as thermal stability analysis (TGA), Fourier Transform Infrared (FTIR) analysis and Scanning Electron Microscopy (SEM) to be adopted in order to characterized natural fiber and impact of treating natural fibers by appropriate chemical on certain properties was discussed by supporting literature. In addition to this the significance of characterization of natural fiber briefly discussed and this an overview will helps other researcher’s source for natural fiber composite studies in future studies.

Concrete crack is one of the main problems observed in concrete technology due to drying shrinkage. Incorporating fibers in concrete production is one of the mechanisms implemented to mitigate cracks. Nowadays, investigators concentrate on different techniques to replace human-made fiber with existing natural fibers for fiber-reinforced composite material. Utilization of natural fiber has an initiation for the development of eco-friendly materials by reducing damages caused by human-made materials and saving nonrenewable resources. Natural fibers are readily and abundantly available, sustainable, and biodegradable, with low cost and low density, and have superior specific properties. Nevertheless, there are some limitations of natural fiber compared to human-made fiber. Consequently, significant energy was applied to alter natural fiber’s surface and morphology using physical, chemical, and biological treatment techniques to overcome the limitation. The primary intention of surface treatment is to modify the bond between the fiber surface and the polymer matrix. However, based on this literature review, there were no specific treatment techniques to be followed to select the best one from the others as criteria. It should include all parameters to consider starting from the stage from the cradle to the grave, cost of chemicals, transportation, and labors, including energy consumption and effluent energy. Additionally, their environmental effect also investigated in detail to compare each other.

An advanced design classification system for bicycle paths, based on geometric features and force equilibrium, can pave the way for improved bicycle safety, accident prevention and the development of design guidelines. A design and classification system does exist for bicycle paths, but the number of accidents has led to ambivalence about its validity and effectiveness. In addition, a universally accepted classification system has not yet been approved or adopted. This paper presents a unique set of design parameters, analytically developed based on formulas that consider the physical characteristics and dimensions of individual bicycles. The proposed design system is based on theoretical trigonometric derivations. The model was validated with the real-world geometry of the transportation infrastructure of the city of Antwerp, Belgium. The conclusions of this study are useful for evaluating the effectiveness of bicycle paths during the design stage without the necessity for real-world experiments. The results will thus be valuable for stakeholders working on policy frameworks, bicycle safety and riding comfort.

Learner modeling systems so far formulated model learning in three main ways: a learner’s “position” within a lattice of declarative and procedural knowledge about highly structured disciplines such as geometry or physics, a learner’s path through curricular tasks compared to milestones, or profiles of a learner’s achievements on a set of tasks relative to mastery criteria or a peer group. Opening these models to learners identifies for them factors and relations among factors. Open learner models tacitly invite learners to regulate learning. However, contemporary learner models omit data about how learners have and should process information to learn, understand, consolidate and transfer new knowledge and skills. What to do with information opened to learners is opaque. I propose incorporating trace data about learning processes in learner models. Trace data allow generating learning analytics that inform self-regulating learners about potentially productive adaptations to processes they have used to learn. In a context of big data, such elaborated learner models are positioned to collaborate with self-regulating learners. Together, they can coordinate symbiotically, creating a platform for the system to improve its models of learners and for learners to more productively self-regulate learning.

Syphilis is a systemic, infectious disease caused byWe report a case of secondary syphilis with thyroid gland and ocular involvement in a human immunodeficiency virus (HIV) negative patient.We present the patient's history, clinical findings, laboratory test results, imaging and management.A 39-year-old Caucasian, HIV unaffected woman presented with acute midline neck swelling, dyspnea and difficulty to talk or swallow. Serologic tests for syphilis were positive. PCR performed on a thyroid fine needle aspiration cytology (FNAC) aspirate was positive forWe report an unusual case of thyroid swelling in a secondary syphilis infection. Awareness of syphilis as a differential diagnosis is important in a risk population.

Background: Although there are many interventions targeting childhood obesity prevention, only few have demonstrated positive results. The current review aimed to gather and evaluate available school-based intervention studies with family involvement targeting dietary, physical activity and sedentary behaviors among primary schoolchildren and their families, in order to identify the most effective strategies. Methods: Studies published between 2000 and January 2015 were retrieved from scientific electronic databases and grey literature. The databases used included MEDLINE/PubMed, Web-of-Science, CINAHL and Scopus. Included studies had to be experimental controlled studies and had duration over 1 school year, had family involvement, combined PA and dietary behaviors and were implemented in school setting. A complementary search was executed to update the review to cover the period from February 2015 to January 2019. Results: From the studies examined (n = 425), 27 intervention programs (33 publications) fulfilled the inclusion criteria. Among these, 15 presented significant effect on weight status and/ or overweight/ obesity or clinical indices, 3 presented significant effect on most energy balance-related behaviors (EBRBs) while 9 presented significant effect on some/few EBRBs or determinants. Strategies implemented in effective interventions were: teachers acting as role-models and being actively involved in the delivery of the intervention, school policies supporting the availability of healthy food and beverage choices and limiting unhealthy snacks, changes in the schoolyard, in the recess rules and in the physical education classes to increase physical activity, and involving parents in the intervention via assignments, meetings, informative material and encouraging them to improve the home environment. Use of incentives for children, social marketing techniques, collaboration with local stakeholders were found to increase effectiveness. Programs that focused only on educational sessions and material for parents, without promoting relevant environmental and policy changes, were found to be less effective. Cultural adaptations have been suggested to increase the intervention’s acceptance in specific or vulnerable population groups. Conclusions: Several effective strategies were identified in the reviewed programs. Outcomes of the current review were taken into account in developing the Feel4Diabetes-intervention and summed up as recommendations in the current work in order to facilitate other researchers designing similar childhood obesity prevention initiatives. Keywords: Obesity prevention, Type 2 diabetes prevention, Primary school children, Families, School based intervention., The Feel4Diabetes-study has received funding from the European Union's Horizon 2020 research and innovation programme [Grant Agreement: n degrees 643708]. The content of this article reflects only the authors' views and the European Community is not liable for any use that may be made of the information contained therein.

Background : Hamstring strain injuries (HSI) are prevalent in team sports and occur frequently in the latter phase of matches. In the search for interindividual factors that determine muscle fatigue and possibly injury risk, muscle fibre typology is a likely candidate. It was the aim of the study to determine whether muscle fibre typology is a risk factor for HSI. Methods : A prospective cohort study was conducted over 3 seasons in professional football players competing in the Belgian Jupiler Pro League (n=118) and in the English Premier League (n=47), and a total of 27 hamstring strain injuries were sustained during this period. The muscle fibre typology was non-invasively estimated using proton magnetic resonance spectroscopy, and was characterized as a fast, slow, or intermediate typology based on the carnosine concentration in the soleus. A multivariate cox model was used to identify risk factors for HSI. Results : Football players exhibit a wide variety of muscle typologies (slow typology=44.9%; intermediate typology=39.8%, fast typology=15.3%). In the combined cohort, players with a fast typology displayed a 5.3-fold (95% CI 1.92-14.8, P=0.001) higher risk than slow typology players to sustain an index HSI. This was also independently observed in both leagues separately as respectively a 6.7-fold (95% CI 1.3-34.1; P=0.023) and a 5.1-fold (95% CI 1.2-20.4; P=0.023) higher chance was found in fast typology players than slow typology players of the Jupiler Pro League and the Premier League cohort. Conclusion : We discovered muscle fibre typology as a novel and potent risk factor for HSI in team sports.

Introduction The potential of circulating cell-free DNA (cfDNA) analysis as a liquid biopsy has led to the development of several specialized measuring tools. Interest in the (pre-)analytical conditions of the liquid biopsy workflow has increased over the past few years. Methods In this study, we performed a systematic review of the cfDNA stabilizing efficacy in standard EDTA and specialized blood collection tubes (BCTs), namely CellSave, Norgen, PAXgene, Roche, and Streck tubes, and compared the efficacy of the latter three BCTs in a situation resembling the clinical setting. Blood samples were collected from ten KRAS-mutated metastatic cancer patients and stored for 72 h. During this time, samples were shaken and kept at either 6 degrees C or at room temperature for 24 h to mimic transport. Results We demonstrated that while cfDNA levels in EDTA tubes are only stable for a couple of (

Continuously reinforced concrete pavement (CRCP) is characterized by the absence of transverse contraction joints and the presence of longitudinal and transverse reinforcement. The continuous longitudinal reinforcement holds the transverse cracks, caused by the longitudinal shrinkage of concrete, tightly together and thus provides long term performance with minimal maintenance cost. Field investigations on recently constructed CRCP's in Flanders region of Belgium indicated horizontal cracking in the vicinity of the longitudinal reinforcement under the transverse cracks which eventually causes the punch-out distress at the edge of the pavement slab. This paper shows the results of a finite element (FE) study to investigate the effect of varying longitudinal reinforcement on the risk of horizontal cracking in CRCP under typical Flanders conditions. For this purpose, a (3D) FE model of CRCP is developed using a FE package Diana 10.2. The varying longitudinal reinforcement with a most narrow spacing of 125mm in the outer region of the pavement slab is applied while keeping the same CRCP reinforcement ratio. A comparison is made with the conventional longitudinal reinforcement spacing (170mm). Development of concrete stress in the vicinity of the longitudinal reinforcement is plotted against the different longitudinal steel spacing. Findings show that the stress in concrete near longitudinal reinforcement is significantly reduced up to maximum 17% when the narrow spacing is used. In addition, the steel stress in the longitudinal reinforcing is reduced up to maximum 31.75% in the outer region of the pavement slab.

Since 1970, continuously reinforced concrete pavements have been used in Belgium. The standard design concept for CRCP has been modified through several changes made in the design parameters to eliminate the cluster of closely spaced crack patterns, since these crack patterns lead to the development of spalling and punch-out distresses in CRCPs. Despite adjusting the longitudinal reinforcement ratio, slab thickness, and addition of asphalt interlayer, the narrowly spaced cracks could not be effectively removed. The application of transverse partial surface saw-cuts significantly reduced the probability of randomly occurring cracks in the reconstruction project of the Motorway E313 in Herentals, Belgium. The field investigation has also indicated that the early-age crack induction in CRCP is quite susceptible to the saw-cut depth. Therefore, the present study aims to evaluate the effect of different depths and lengths of the partial surface saw-cut on the effectiveness of crack induction in CRCP under external varying temperature field. For this purpose, the FE software program DIANA 10.3 is used to develop the three dimensional finite element model of the active crack control CRCP segment. The characteristics of early-age crack induction in terms of crack initiation and crack propagation obtained from the FE model are compared and discussed concerning the field observations of the crack development on the active crack control E313 test sections. Findings indicate that the deeper saw-cut with longer cut-lengths could be a more effective attempt to induce the cracks in CRCP in desirable distributions to decrease the risk of spalling and punch-out distresses in the long-term performance of CRCP. These findings could be used as guidance to select the appropriate depth and length of saw-cut for active crack control sections of CRCP in Belgium.

Aim: The aim of the study was to assess patient preference for the fixed-dose combination of pertuzumab and trastuzumab for subcutaneous injection (PH FDC SC) in patients with HER2-positive early breast cancer in PHranceSCa (NCT03674112). Materials and methods: Patients who completed neoadjuvant P + H + chemotherapy + surgery were randomised 1:1 to three intravenous (IV) P + H cycles followed by three cycles of PH FDC SC or vice versa (crossover) and then chose subcutaneous (SC) injection or IV infusion to continue up to 18 cycles (continuation). Assessments were via patient and healthcare professional (HCP) questionnaires. Results: One hundred and sixty patients were randomised (cut-off: 24 February 2020); 136 (85.0%, 95% confidence interval: 78.5–90.2%) preferred SC; 22 (13.8%) preferred IV; 2 (1.3%) had no preference. The main reasons for SC preference were reduced clinic time (n = 119) and comfort during administration (n = 73). One hundred and forty-one patients (88.1%) were very satisfied/satisfied with SC injection versus 108 (67.5%) with IV infusion; 86.9% chose PH FDC SC continuation. HCP perceptions of median patient treatment room time ranged from 33.0–50.0 min with SC and 130.0–300.0 min with IV. Most adverse events (AEs) were grade 1/2 (no 4/5s); serious AE rates were low. AE rates before and after switching were similar (cycles 1–3 IV → cycles 4–6 SC: 77.5% → 72.5%; cycles 1–3 SC → cycles 4–6 IV: 77.5% → 63.8%). Conclusion: Most patients strongly preferred PH FDC SC over P + H IV. PH FDC SC was generally well tolerated, with no new safety signals (even when switching), and offers a quicker alternative to IV infusion.

INTRODUCTION: A significant proportion of the astronauts who spend extended periods in microgravity develop ophthalmic abnormalities, including optic disc edema, optic nerve sheath distention, globe flattening, chorioretinal folds, hyperopic refractive error shifts, and nerve fiber layer infarcts. A constellation of these neuro-ophthalmic findings has been termed spaceflight-associated neuro-ocular syndrome. An increased understanding of factors contributing to this syndrome is one of the top priorities for ESA and NASA because the length of missions is expected to increase substantially in the future. As discussed in the present article, the very recent discovery of an ocular glymphatic clearance system can potentially help to unlock mechanisms underlying microgravity-induced optic disc edema. Observations pertaining to the ocular glymphatic pathway provide supporting evidence for the hypothesis, originally proposed by our group, suggesting that the glymphatic outflow from the eye into the optic nerve may be impeded under prolonged microgravity conditions, leading to optic disc edema.Wostyn P, De Winne F, Stern C, Mader TH, Gibson CR, De Deyn PP. Potential involvement of the ocular glymphatic system in optic disc edema in astronauts. Aerosp Med Hum Perform. 2020; 91(12):975977. ispartof: AEROSPACE MEDICINE AND HUMAN PERFORMANCE vol:91 issue:12 pages:975-977 ispartof: location:United States status: published

International audience; Inspired by a pursuit of higher returns on human resource management (HRM) investments as well as a trend towards the individualization of HRM, several scholars have focused on the phenomenon of HR differentiation, that is, the differential allocation of resources across employees through the use of HRM practices. Yet, different definitions and angles to study HR differentiation have been used. As a result, ambiguities render it difficult to compare research findings and draw meaningful conclusions about HR differentiation and its consequences. Based on a systematic analysis of 164 articles from five different research streams (i.e., strategic HRM, talent management, i-deals, pay dispersion, and diversity management literatures), we identify four properties of HR differentiation (its basis, formalization, resource, and purpose) and propose a more fine-grained definition of the construct. Next, drawing from optimal distinctiveness–based inclusion theory, we develop an integrated multilevel model with propositions that helps explain the social psychological consequences of HR differentiation at three integrated levels of analysis (employee, workgroup, and organization). Subsequently, we derive an agenda for future research. In doing so, we contribute by developing a common language for scholars with different disciplinary backgrounds and inspire future research on HR differentiation.

Conventional dark chocolate production methods that are applied in the industry consist of several steps, which require equipment with big investment costs. There are however few cost-effective alternatives suggested for small-scale production. Meanwhile, knowledge on these alternative equipment/techniques are insufficient to promote miniature production of high quality chocolates, either for research purposes in an industrial context, or for producers in developing countries, where the cost of investing in conventional equipment seems to be an impediment. The aim of this study was two-fold; first, to assess the feasibility of utilizing the ECGC-12SLTA CocoaTown melanger as an alternative to the conventional 3-roll refiner at different settings and fat content. Thereafter, one optimal setting was selected for each equipment for further investigation on the impact of the refining on some quality attributes of the final dark chocolate (70% cocoa). Secondly, the Stephan mixer; being used to mimick a conching-like process, was assessed with respect to two processing factors; the dry conching temperature (60 °C, 80 °C) and the duration of vacuum pump connection (0, 30, 60 min). The latter was to facilitate adequate moisture removal. The melanger proved to be a suitable alternative to the 3-roll refiner, provided that refining was carried out at moderate/high (ca. 40%) fat content, as is often the case for “high-percentage-cocoa” chocolates. Refining for 180 min with the mini drum at 40% resulted in D (v,0.9) significantly (p

The use of alternative equipment for chocolate production is gaining attention in recent times in many countries. This is due to the lower cost of investment and maintenance, multi-functionality, and lower throughput. This study was conducted to investigate the applicability of two of such equipment; melanger and Stephan mixer. In the first set-up, the possibility of refining chocolate with the melanger in comparison with the conventional 3-roll refiner was explored. Whereas in the second set-up, the applicability of the Stephan mixer (aided with a vacuum pump) for a conching-like application was also investigated. From each set-up, 70% dark chocolates produced through various alternative means were then evaluated on the basis of their flavor profiles. Specific groups of volatiles such as aldehydes, ketones, terpenes and terpenoids, showed significant (p 0.05) preference for these representative chocolates from the clusters. These findings stimulate various practical application possibilities for tuning chocolate flavor through alternative processing for both industries and various artisans worldwide.

Tropomyosin receptor kinase (TK) is encoded by the neurotrophic tyrosine receptor kinase genes (NTRK) 1, 2, and 3, whose activation plays an important role in cell cycle proliferation and survival. Fusions of one of these genes can lead to constitutive activation of TRK, which can potentially be oncogenic. NTRK fusions are commonly present in rare histologic tumor types. Among sarcomas, infantile fibrosarcoma shows NTRK fusion in more than 90% of the cases. Many other sarcoma types are also investigated for NTRK fusions. These fusions are druggable alteration of the agnostic type, meaning that all NTRK fused tumors can be treated with NTRK-inhibitors regardless of tumor type or tissue of origin. TRK-inhibitors have shown good response rates, with durable effects and limited side effects. Resistance to therapy will eventually occur in some cases, wherefore the next-generation TRK-inhibitors are introduced. The diagnosis of NTRK fused tumors, among them sarcomas, remains an issue, as many algorithms but no guidelines exist to date. Given the importance of this diagnosis, in this paper we aim to (1) analyze the histopathological features of sarcomas that correlate more often with NTRK fusions, (2) give an overview of the TRK-inhibitors and the problems that arise from resistance to the therapy, and (3) discuss the diagnostic algorithms of NTRK fused tumors with emphasis on sarcomas.

The technological innovation of continuously reinforced concrete pavement (CRCP) that contains a significantly reduced amount of reinforcement and the same fundamental behavior as CRCP is called advanced reinforced concrete pavement (ARCP). This new concept of a rigid pavement structure is developed to eliminate unnecessary continuous longitudinal steel bars of CRCP by using partial length steel bars at predetermined crack locations. In Belgium, partial surface saw-cuts are used as the most effective crack induction method to eliminate the randomness in early-age crack patterns by inducing cracks at the predetermined locations of CRCP. The reinforcement layout of ARCP is designed based on the distribution of steel stress in continuous longitudinal steel bar in CRCP and the effectiveness of partial surface saw-cuts as a crack induction method. The 3D finite element (FE) model is developed to evaluate the behavior of ARCP with partial surface saw-cuts. The early-age crack characteristics in terms of crack initiation and crack propagation obtained from the FE simulation are validated with the field observations of cracking characteristics of the CRCP sections in Belgium. The finding indicates that there is fundamentally no difference in the steel stress distribution in the partial length steel bar of ARCP and continuous steel bar of CRCP. Moreover, ARCP exhibits the same cracking characteristics as CRCP even with a significantly reduced amount of continuous reinforcement.

Background Low back pain (LBP) is the leading cause of worldwide years lost because of disability, with a tremendous economic burden for health care systems. Digital therapeutic care (DTC) programs provide a scalable, universally accessible, and low-cost approach to the multidisciplinary treatment of LBP. Moreover, novel decision support interventions such as personalized feedback messages, push notifications, and data-driven activity recommendations amplify DTC by guiding the user through the program while aiming to increase overall engagement and sustainable behavior change. Objective This systematic review aims to synthesize recent scientific literature on the impact of DTC apps for people with LBP and outline the implementation of add-on decision support interventions, including their effect on user retention and attrition rates. Methods We searched bibliographic databases, including MEDLINE, Cochrane Library, Web of Science, and the Physiotherapy Evidence Database, from March 1, 2016, to October 15, 2020, in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and conducted this review based on related previously published systematic reviews. Besides randomized controlled trials (RCTs), we also included study designs with the evidence level of at least a retrospective comparative study. This enables the consideration of real-world user-generated data and provides information regarding the adoption and effectiveness of DTC apps in a real-life setting. For the appraisal of the risk of bias, we used the Risk of Bias 2 Tool and the Risk of Bias in Non-Randomized Studies of Interventions Tool for the RCTs and nonrandomized trials, respectively. The included studies were narratively synthesized regarding primary and secondary outcome measures, DTC components, applied decision support interventions, user retention, and attrition rates. Results We retrieved 1388 citations, of which 12 studies are included in this review. Of the 12 studies, 6 (50%) were RCTs and 6 (50%) were nonrandomized trials. In all included studies, lower pain levels and increased functionality compared with baseline values were observed in the DTC intervention group. A between-group comparison revealed significant improvements in pain and functionality levels in 67% (4/6) of the RCTs. The study population was mostly homogeneous, with predominantly female, young to middle-aged participants of normal to moderate weight. The methodological quality assessment revealed moderate to high risks of biases, especially in the nonrandomized trials. Conclusions This systematic review demonstrates the benefits of DTC for people with LBP. There is also evidence that decision support interventions benefit overall engagement with the app and increase participants’ ability to self-manage their recovery process. Finally, including retrospective evaluation studies of real-world user-generated data in future systematic reviews of digital health intervention trials can reveal new insights into the benefits, challenges, and real-life adoption of DTC programs.

The technological innovation of continuously reinforced concrete pavement (CRCP) that contains a significantly reduced amount of reinforcement and the same fundamental behaviour as CRCP is called advanced reinforced concrete pavement (ARCP). This new concept of a rigid pavement structure is developed to eliminate unnecessary continuous longitudinal steel bars of CRCP by using partial length steel bars at predetermined crack locations. In Belgium, partial surface saw-cuts are used as the most effective crack induction method to eliminate the randomness in early-age crack patterns by inducing cracks at the predetermined locations of CRCP. The reinforcement layout of ARCP is designed based on the distribution of steel stress in continuous longitudinal steel bar in CRCP and the effectiveness of partial surface saw-cuts as a crack induction method. The 3D finite element (FE) model is developed to evaluate the behaviour of ARCP with partial surface saw-cuts. The early-age crack characteristics in terms of crack initiation and crack propagation obtained from the FE simulation are validated with the field observations of cracking characteristics of the CRCP sections in Belgium. The finding indicates that ARCP exhibits the same cracking characteristics as CRCP even with a significantly reduced amount of continuous reinforcement.

A Belgian ring trial for pan-TRK immunohistochemistry (IHC) staining was organised to harmonise pan-TRK IHC staining protocols and interpretation. As a reference method, the VENTANA pan-TRK Assay (clone EPR17341) on the Benchmark Ultra platform was selected. Six samples were selected: 2 negative, 2 fusion positive and 2 samples with wild-type endogenous TRK expression. Each participating laboratory stained the slides using their routine pan-TRK IHC and reported their results. In addition, they were asked to return one TRK-stained slide from each case. The coordinating lab evaluated these slides, compared them with the reference method and scored them. Two clones were used during the ring trial: A7H6R (Cell Signaling) and EPR17341 (Abcam/Ventana). Seven protocols achieved a sufficient performance mark, and three labs were advised to further optimise the protocol. Interpretation of pan-TRK IHC proved to be challenging in cases with physiological TRK expression. In addition, depending on the NTRK fusion partner, the staining can vary strongly in both intensity and staining pattern. Labs using the Ventana ready-to-use system based on the EPR17341 clone and using the recommended protocol settings scored best. However, given some small optimisation, all labs scored well on the technical staining and the succeeding evaluation., SCOPUS: ar.j, info:eu-repo/semantics/published

Introduction:A Belgian predictive medical resource tool, Plan Risk Manifestations (PRIMA), for the prediction of the number of patient encounters at mass gatherings (MGs) has recently been developed, in addition to the existing models of Arbon and Hartman. This study presents the results of the validation process for the PRIMA model for music MGs.Methods:A retrospective study was conducted using data gathered from music MGs in the province of Antwerp (Belgium) during the period of 2012-2016. Data from 87 music MGs were used for the study. The forecast of medical resources for these events was determined by entering the characteristics of individual events into the Arbon, Hartman, and PRIMA models. In order to determine if the PRIMA model is under- or over-predictive, the data gathered were retrospectively compared to the predicted number of resources needed using the aforementioned models. Statistical analysis included means, medians, and interquartile ranges (IQRs). Nonparametric related samples test (Wilcoxon Samples Signed Rank Test) for comparison of the median in deviations in predictions of patient presentation rates (PPRs) was performed using SPSS version 23 (IBM Corp.; Armonk, New York USA). Confidence interval levels were set at 95% and results were deemed statistically significant at P Results:All three models had an acceptable rate of over-prediction of number of patient encounters ([Arbon 25.29%; 95% CI, 30.91-43.74]; [Hartman 29.89%; 95% CI, 57.10-68.90]; and [PRIMA 19.54%; 95% CI, 57.80-76.20]). But all models also had a high rate of under-prediction of number of patient encounters ([Arbon 74.71%; 95% CI, 453.31-752.52]; [Hartman 70.11%; 95% CI, 546.90-873.77]; and [PRIMA 78.16%; 95% CI, 288.91-464.89]). Only the PRIMA model succeeded in the correct prediction of the number of patient encounters on two occasions (2.3%).Conclusion:Results of this study are in-line with existing literature. When comparing the predicted patient encounters, all three models had high rates of under-prediction and moderate rates of over-prediction. When comparing mean deviations, the PRIMA model had the lowest mean deviation of all predicted PPRs. Belgian events of the types included in the presented data may use the PRIMA model with confidence to predict PPRs and estimate the in-event health services (IEHS) requirements.

The advancement of wearable technologies provides opportunities to continuously track individuals’ daily activity levels and sleep patterns over extended periods of time. These data are useful in examining the reciprocal relationships between physical activity and sleep at the intrapersonal level. The purpose of this study is to test the bidirectional relationships between daily activity levels and sleep duration. The current study analyzed activity and sleep data collected from a Fitbit device as part of a 6 month employer-sponsored weight loss program. A total of 105 overweight/obese adults were included (92% female, 70% obese, and 44% Hispanic). Multilevel models were used to examine (a) whether daily active and sedentary minutes predicted that night’s sleep duration and (b) whether sleep duration predicted active and sedentary minutes the following day. Potential extended effects were explored by using a 2 day average of the activity minutes/sleep duration as the predictor. No significant relationships between active minutes and sleep duration were found on a daily basis. However, having less sleep over two nights than one’s usual level was associated with an increased likelihood of engaging in some physical activity the following day. There was a significant bidirectional negative association between sedentary minutes and sleep duration for both the daily and 2 day models. Data from wearable trackers, such as Fitbit, can be used to investigate the daily within-person relationship between activity levels and sleep duration. Future studies should investigate other sleep metrics that may be obtained from wearable trackers, as well as potential moderators and mediators of daily activity levels and sleep.

Currently, there is a strong interest in barrel ageing of finished, conventionally fermented beers, as a novel way to produce sour beers with a rich and complex flavour profile. The production process, however, remains largely a process of trial and error, often resulting in profit losses and inconsistency in quality. To improve product quality and consistency, a better understanding of the interactions between microorganisms, wood and maturing beer is needed. The aim of this study was to describe the temporal dynamics in microbial community composition, beer chemistry and sensory characteristics during barrel ageing of three conventionally fermented beers that differed in parameters like alcohol content and bitterness. Beers were matured for 38 weeks in new (two types of wood) and used (one type of wood) oak barrels. Beer samples were taken at the start of the maturation and after 2, 12 and 38 weeks. Microbial community composition, determined using amplicon sequencing of the V4 region of the bacterial 16S rRNA gene and the fungal ITS1 region, beer chemistry and sensory characteristics substantially changed throughout the maturation process. Likewise, total bacterial and fungal population densities generally increased during maturation. PerMANOVA revealed significant differences in the bacterial and fungal community composition of the three beers and across time points, but not between the different wood types. By contrast, significant differences in beer chemistry were found across the different beers, wood types and sampling points. Results also indicated that the outcome of the maturation process likely depends on the initial beer properties. Specifically, results suggested that beer bitterness may restrain the bacterial community composition, thereby having an impact on beer souring. While the bacterial community composition of moderately-hopped beers shifted to a dominance of lactic acid bacteria, the bacterial community of the high-bitterness beer remained fairly constant, with low population densities. Bacterial community composition of the moderate-bitterness beers also resembled those of traditional sours like lambic beers, hosting typical lambic brewing species like Pediococcus damnosus, Lactobacillus brevis and Acetobacter sp. Furthermore, results suggested that alcohol level may have affected the fungal community composition and extraction of wood compounds. More specifically, the concentration of wood compounds like cis-3-methyl-4-octanolide, trans-3-methyl-4-octanolide, eugenol and total polyphenols was higher in beers with a high alcohol content. Altogether, our results provide novel insights into the barrel ageing process of beer, and may pave the way for a new generation of sour beers. ispartof: International Journal Of Food Microbiology vol:339 ispartof: location:Netherlands status: Published online

BACKGROUND: Although the understanding of hypobaric hypoxia is increasing, it remains a hazard in aviation medicine. This study examined the feasibility of detecting voice markers sensitive to acute hypobaric hypoxia in an early presymptomatic (PRE-SYMP) stage.METHOD: Eight subjects qualified with hypobaric training completed a series of standardized speech tests in a hypobaric chamber at 20,000 ft and 25,000 ft (6096 and 7620 m) of altitude. Voice response patterns were analyzed in terms of fundamental frequency (F0), F0 range, and voice onset time (VOT). We hypothesized a PRE-SYMP compensatory stage in voice reactivity.RESULTS: There was a different dose-response reactivity course at 20,000 ft vs. 25,000 ft, nonlinear to altitude. At 20,000 ft, our hypothesis was confirmed. In comparison to sea level, a PRE-SYMP compensatory stage could be distinguished, characterized by a decreased F0 range, decreased VOT, and increased F0. During a transitional (TRANS) stage, in comparison with sea level, the F0-range reset, VOT decreased, and F0 increased. During a symptomatic (SYMP) stage, F0 increased, F0 range increased, and VOT decreased. At 25,000 ft, in comparison to sea level, voice reactivity showed increased F0 and F0 range and decreased VOT in a PRE-SYMP stage and increased F0 and F0 range in the SYMP stage.DISCUSSION: The compensatory PRE-SYMP stage is suggested to be the expression of ongoing bottom-up and top-down regulatory mechanisms, whereas the 25,000-ft results are interpreted as a combination of tonic and phasic voice reactivity. This tonic component needs to be foreseen in sea level baseline measures.Van Puyvelde M, Neyt X, Vanderlinden W, Van den Bossche M, Bucovaz T, De Winne T, Pattyn N. Voice reactivity as a response to acute hypobaric hypoxia at high altitude. Aerosp Med Hum Perform. 2020; 91(6):471–478.

Advances in machine learning (ML) and artificial intelligence (AI) present an opportunity to build better tools and solutions to help address some of the world’s most pressing challenges, and deliver positive social impact in accordance with the priorities outlined in the United Nations’ 17 Sustainable Development Goals (SDGs). The AI for Social Good (AI4SG) movement aims to establish interdisciplinary partnerships centred around AI applications towards SDGs. We provide a set of guidelines for establishing successful long-term collaborations between AI researchers and application-domain experts, relate them to existing AI4SG projects and identify key opportunities for future AI applications targeted towards social good., The AI for Social Good movement aims to apply AI/ML tools to help in delivering on the United Nations’ sustainable development goals (SDGs). Here, the authors identify the challenges and propose guidelines for designing and implementing successful partnerships between AI researchers and application - domain experts.

Learning strategies populate a large and multidimensional conceptual space. Features of experimental designs strongly affect the validly of inferences about whether and how learning strategies affect achievement. Successes in helping learners build learning strategies typically yield quite localized and short-lived benefits. Tamping down excessive optimism about learning strategies needs constant attention not only by Internet surfers but also by researchers and teachers. Taking another perspective, a learning strategy refers to how a learner engaged in any task proceeds in a context-sensitive way to stepwise traverse a lattice of cognitive engagements with information in a context where information is updated at each step the strategy is applied. Future research should investigate how learners’ decisions unfold and how learners can be supported to evolve more productive decision making about learning strategies. Throughout the timeline of work on a task, learners choose among tactics and learning strategies in the context of current and successively updated conditions.

We use a unique data set covering brokerage accounts for a large cross-section of investors over a sample from January 2003 to March 2012, which includes the 2008 financial crisis, to assess the potential benefits of robo-investing. We explore robo-investing strategies commonly used in the industry, including some involving advanced machine learning methods. We shadow each of our investors with a robo-advisor to shed light on possible benefits the emerging robo-advising industry may provide to certain segments of the population, such as low income and/or low education investors.

Background Feel4Diabetes was a school and community based intervention aiming to promote healthy lifestyle and tackle obesity for the prevention of type 2 diabetes among families in 6 European countries. We conducted this literature review in order to guide the development of evidence-based implementation of the Feel4Diabetes intervention. We focused on type 2 diabetes prevention strategies, including all the phases from risk identification to implementation and maintenance. Special focus was given to prevention among vulnerable groups and people under 45 years. Methods Scientific and grey literature published between January 2000 and January 2015 was searched for relevant studies using electronic databases. To present the literature review findings in a systematic way, we used the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. A complementary literature search from February 2015 to December 2018 was also conducted. Results The initial review included 27 studies with a follow-up ≥12 months and 9 studies with a follow-up ≥6 months and with a participant mean age Conclusion This narrative review highlighted several important aspects that subsequently guided the development of the Feel4Diabetes high-risk intervention. Research on diabetes prevention interventions targeted at younger adults or vulnerable population groups is still relatively scarce. Feel4Diabetes is a good example of a project aiming to fill this research gap. Trial registration clinicaltrials.gov NCT02393872, registered 20th March 2015.

From 2005 until early 2015, as many as 52 companies perform delisting. Meanwhile, the practice of earnings management will be found on all companies including the delisted companies. Previously earnings management are found on discretionary accruals, but because it is often used and can be detected easily managers began to switch to manipulate earnings through operating activities or real activities manipulation. The purpose of this study is to analyze the practices of earnings management through real activities manipulation in companies that perform forced and voluntary delisting. Obtained each of 14 companies forced and voluntary delisting during observation from 2005 to 2014 who meet the criteria of purposive sampling. The results using independent t-test found there were no difference in the average earnings management in forced and voluntary delisting companies, which in both earnings management done to lower profits. It is analyzed as the company's goals for the restructuring of debt, save on tax payments as well as the distribution of dividends and employee bonuses. Thus, earnings management to do more to efficient contracting perspective.

Indonesia has the perpetrators of Micro, Small and Medium Enterprises or SMEs which sums are growing. In the city of Bandung there Zoraya Community consisting of small and medium entrepreneurs, which aims to share the products and exchange experiences in marketing their products. Zoraya Community members belong to the cottage industry entrepreneurs, who have problems in marketing their products. Marketing through social media and direct marketing or direct selling them often become a bottleneck. This occurs at the time of product exhibition,they are hampered in communicating to consumers in promoting their products. The right solution to the problem is the public speaking training, capacity building through presentation skills, facilitation process of direct selling products during the exhibition. The method used in the form of training activities as part of the presentation skill of public speaking, presentations skills training benef its, training of basic techniques for presentation public speaking skills, and training make the script about a superior product. The results of this activity is that participants increased understanding of how effective product presentation and systematic. Besides increasing the confidence member Zoraya Community after being given training.

A stereoselective synthetic method is reported for the molecular framework found in common daucane and isodaucane sesquiterpenoid natural products. The synthetic method constitutes a scalable, modular, and also asymmetric access to a complex natural product scaffold, wherein the substitution pattern and the stereochemistry can be adjusted simply by choosing different starting materials. The method allows the rapid introduction of diverse heterocyclic substructures such as (benzo)furans, (benzo)thiophenes, dithiins, thiazoles, and indoles, which actually also facilitate and direct the key intramolecular annulation step.

A bottleneck in gathering big data about learning is instrumentation designed to record data about processes students use to learn and information on which those processes operate. The software system nStudy fills this gap. nStudy is an extension to the Chrome web browser plus a server side database for logged trace data plus peripheral modules that analyze trace data and assemble web pages as learning analytics. Students can use nStudy anywhere they connect to the internet. Every event related to creating, modifying, reviewing, linking and organizing information artifacts is logged in fine grain with a time stamp. These data fully trace information students operate on and how they operate on it. Ambient big data about studying gathered au naturel can be tailored by configuring several of nStudy’s features. Thus the system can be used to gather data across a wide range lab studies and field trials designed to test a range of models and theories.

Background Today's gold standard for identifying what works, the randomized controlled trial, poorly serves each and any individual learner. Elements of my argument provide grounds for proposed remedies in cases where software can log extensive data about operations each learner applies to learn and each bit of information to which a learner applies those operations. Purpose of Study Analyses of such big data can produce learning analytics that provide raw material for self-regulating learners, for instructors to productively adapt instructional designs, and for learning scientists to advance learning science. I describe an example of such a software system, nStudy. Research Design I describe and analyze features of nStudy, including bookmarks, quotes, notes, and note artifacts that can be used to generate trace data. Results By using software like nStudy as they study, learners can partner with instructors and learning scientists in a symbiotic and progressive ecology of authentic experimentation. Conclusion I argue that software technologies like nStudy offer significant value in supporting learners and advancing learning science. A rationale and recommendations for this approach arise from my critique of pseudo-random controlled trials.

Objective: Little is known about why PwD leave traditional pathways and turn to DIY technology. This study aims to examine the motivations of Do-it-Yourself Artificial Pancreas System (DIYAPS) users and caregivers to build and maintain these systems. Methods: An online survey with 34 items was distributed to DIYAPS users and caregivers of children with DIYAPS through Facebook (“Looped” and regional subgroups) and Twitter (Diabetes Online Community). Results: 1058 participants from 34 countries responded to the survey. The majority were adult users (80.2%; 43% female; median age 41 years) with T1D (98.9%) for 25.2 years ±13.3. 19.8% were caregivers of children (47.4% female; median age 10 years) with T1D (99.4%) for 5.1 years ±3.9. With 10.1m ±17.6 on DIYAPS, HbA1c improved from 7.07% ±1.07 to 6.24% ±0.68 %. Time in Range improved from 63.21% ±16.27 to 83.07% ±10.11. Additional out-of-pocket costs of 712 USD/year were spent. Motivations to build a DIYAPS are shown in Fig.1. Conclusions: Improved glycemic control, need for an ‘autopilot’ and less acute and long-term complications were key motivations in both groups; as well as better sleep for caregivers. Users were also able to access and afford the required tools. These results may provide a better understanding of unmet needs of PwD and current challenges to uptake, in order to facilitate the involvement of patient-led and open source approaches in healthcare. Disclosure K. Braune: Advisory Panel; Self; Medtronic MiniMed, Inc. Speaker’s Bureau; Self; Dexcom, Inc. S. O’Donnell: None. B. Cleal: None. D.M. Lewis: Consultant; Self; Diabeloop SA, Roche Diabetes Care. A. Tappe: Consultant; Self; IME-DC GmbH. Employee; Self; Hi.health, Gruber-Debong GmbH. Speaker’s Bureau; Self; Dexcom, Inc., Roche Diabetes Care, Ypsomed AG. Other Relationship; Self; SOOIL Developments Co., Ltd. B. Hauck: Consultant; Self; Bayer AG, Eli Lilly and Company, LifeScan, Inc., Novo Nordisk A/S, Roche Diabetes Care, Roche Pharma. I. Willaing: None. R. Scibilia: Speaker’s Bureau; Self; Roche Diabetes Care. E. Rowley: None. W. Ko: None. G. Doyle: None. T.C. Skinner: None. K. Raile: Advisory Panel; Self; Abbott, Lilly Diabetes. Funding European Union

In this study, the clinical performance of the Idylla MSI test (investigational use only) was evaluated in 330 colorectal carcinoma samples (all stages). This test is fully automated, from formalin-fixed, paraffin-embedded slide to result, and gives a result in

Volumes of detailed information are now unobtrusively collected as students use learning management systems and digital learning environments in their studies. This significantly elevates opportunities to better understand how students learn. The learning analytics community is exploring these data to describe learning processes [117] and ground recommendations for improved learning environments [8, 102, 139]. One challenge in this work is need for more and more detailed information about each student’s learning processes to mine for developing useful and timely feedback for students and teachers [150]. Student engagement is a strong focus in this work. Research consistently shows positive relationships between engagement and academic success (e.g., [68, 111]). However, to construct learning analytics describing student engagement and recommending more productive forms of engagement, the field needs to better understand what student engagement means, how it can be observed online and quantified, and how it relates to learning processes and achievement. We review literatures describing student engagement and its relations to learning focusing on engagement in online and distance learning in postsecondary education. We catalog conceptualizations, measurement approaches and benefits of student engagement for learning and academic achievement. Through lenses of learning analytics and learning science, we map the evolution of analytics about student engagement and propose future research to bridge the learning analytics—learning science gap. We note challenges of tracking and supporting student engagement and recommend strategies that are predicted to facilitate positive long-term change.

Revision is important but challenging for novice writers, particularly in post-secondary education where opportunities for personalized feedback are limited. Inexperienced writers typically overlook revision; when they do revise, they focus on surface errors rather than global revisions that enhance meaning and coherence. Writing analytics can automate personalized prompts to guide revision. We use topic modelling LDA as grounds for an analytic to scaffold holistic revision at paragraph and essay levels. The analytic visualizes topic distribution and generates three types of prompts: Introduction, Paragraph and Conclusion. Feedback encourages revisions focusing on sequencing topics, expanding underdeveloped ideas, and making holistic revisions to improve clarity and coherence of paragraphs. Model feedback was evaluated using undergraduate student essays on various topics scored by human evaluators. Model accuracy was strong for all types of feedback. This opens new branches of research to explore generating personalized feedback at paragraph and essay levels.

Artificial intelligence, or AI, enhancements are increasingly shaping our daily lives. Financial decision-making is no exception to this. We introduce the notion of AI Alter Egos, which are shadow robo-investors, and use a unique data set covering brokerage accounts for a large cross-section of investors over a sample from January 2003 to March 2012, which includes the 2008 financial crisis, to assess the benefits of robo-investing. We have detailed investor characteristics and records of all trades. Our data set consists of investors typically targeted for robo-advising. We explore robo-investing strategies commonly used in the industry, including some involving advanced machine learning methods. The man versus machine comparison allows us to shed light on potential benefits the emerging robo-advising industry may provide to certain segments of the population, such as low income and/or high risk averse investors.

Learning projects are major academic assignments. They benefit from productive self-regulated learning to improve skills for solving information problems of searching for, analyzing, mining and organizing unfamiliar content. Findings from randomized controlled trials (RCTs), the “gold standard” for research, are recommended to meet these needs but RCTs poorly serve this purpose. A state-of-the-art learning technology, nStudy, is proposed to support a new approach to learning science and help fill gaps RCTs cannot. In the course of learners’ everyday studying activities, nStudy gathers ambient, fine-grained, trace data fully cataloging information learners operate on and operations they apply to information. Big ambient trace data are raw material for developing learning analytics that support self-regulated learning for improving information problem solving.

Collaborative discussions should engage all students, not just a few who dominate (“leaders”) while others participate as “followers” (Zhu, 2006). Cunningham (1991) noted that collaborating learners bring, discuss and debate multiple perspectives to develop their own position while acknowledging others' views. Higher levels of knowledge construction emerged when posts stimulated frequent reply by multiple participants (Aviv, Erlich, Ravid, & Geva, 2003) and were strongly content- and task-oriented (Rovai, 2007). So, to help students more actively and productively engage in knowledge-constructing discussions, an instructor needs to detect students' posts that do not stimulate replies, identify content those posts introduce, and guide students to revise posts to encourage peers' responses. However, such monitoring would be very time- and energy-consuming, especially in large-enrolment courses (Hura, 2010). To set a stage for developing a classifier to automate these tasks, we proposed 10 rhetorical moves characteristic of the interactive mode of Chi and Wylie's ICAP framework (2014) and categorized fine-grained content in discussion posts using these moves. We then identified attributes of posts that triggered a greater number of responses. Rhetorical moves of “asking questions,” “requesting justification,” “building-on,” “giving a reason” and “making a claim” triggered more peer responses. Posts with moves of “disagreeing,” “comparing” and “making claims” predicted students' achievement on a test and an argumentative writing task. We propose analytics for learners and instructors about forming and revising posts to promote constructive discussions and subsequent achievements.

Information and communication technology (ICT) infrastructure plays a critical role in many aspects of the society. While ICTs contribute to climate-related responses and adaptive practices, much less is known about the impacts that climate change may have on ICT itself. Drawing on knowledge in the literature and findings elicited from industrial workshop conversations and case studies, this paper attempts to provide a review of available evidence of climate impacts on the UK’s ICT infrastructure. This research shows that, although ICTs are resilient to climate impacts, in part due to the rapid refresh rate of equipment, ICTs are vulnerable to a number of future climate risks. The criticality of ICTs to other infrastructure sectors implies that any disruption to ICTs could result in multisectoral cascade failures. This paper also explores the potential for strategies to adapt ICTs to be more resilient to extreme weather and changes in climate, discusses some of the opportunities that climate change may offer and identifies some areas for further research.

Articles in this special issue on regulation of learning in computer-supported collaborative learning apply tools across the spectrum of qualitative and quantitative methods to investigate self-, co- and socially shared regulation of learning. As well, a careful consideration of each of these constructs is provided. I briefly review these contributions to identify unique and forward-looking approaches to research in this vibrant area of research. A particular opportunity is recommended for future research regarding the use of process mining, sequence mining, social network analysis and an as-yet to be invented amalgam of these methods in constructing intelligent software agents that could guide participants in CSCL to assemble an optimum mix of self-, co- and socially shared regulation of learning.

We present a case regarding a 32-year old African male with penoscrotal hypospadias, left cryptorchidism and a left inguinal hernia. There were moderate masculinization characteristics. He underwent a Lichtenstein hernia repair with perioperative biopsies of the left inguinal testis and epididymis. Microscopic examination showed a Sertoli-only left testis with Leydig-cell hyperplasia and the left epididymis consisted of ovarian tissue with corpora albicantia and maturing follicles. Endocrinological evaluation showed a sex-determining region Y (SRY) negative 46,XX karyotype. We successfully performed a two-stage urethroplasty with buccal mucosa graft to reconstruct his penoscrotal hypospadias.

BACKGROUND: Mass gathering manifestations attended by large crowds are an increasingly common feature of society. In parallel, an increased number of studies have been conducted that developed and/or validated a model to predict medical usage rates at these manifestations. AIMS: To conduct a systematic review to screen, analyse and critically appraise those studies that developed or validated a multivariable statistical model to predict medical usage rates at mass gatherings. To identify those biomedical, psychosocial and environmental predictors that are associated with increased medical usage rates and to summarise the predictive performance of the models. METHOD: We searched for relevant prediction modelling studies in six databases. The predictors from multivariable regression models were listed for each medical usage rate outcome (i.e. patient presentation rate (PPR), transfer to hospital rate (TTHR) and the incidence of new injuries). The GRADE methodology (Grades of Recommendation, Assessment, Development and Evaluation) was used to assess the certainty of evidence. RESULTS: We identified 7,036 references and finally included 16 prediction models which were developed (n = 13) or validated (n = 3) in the USA (n = 8), Australia (n = 4), Japan (n = 1), Singapore (n = 1), South Africa (n = 1) and The Netherlands (n = 1), with a combined audience of >48 million people in >1700 mass gatherings. Variables to predict medical usage rates were biomedical (i.e. age, gender, level of competition, training characteristics and type of injury) and environmental predictors (i.e. crowd size, accommodation, weather, free water availability, time of the manifestation and type of the manifestation) (low-certainty evidence). Evidence from 3 studies indicated that using Arbon's or Zeitz' model in other contexts significantly over- or underestimated medical usage rates (from 22% overestimation to 81% underestimation). CONCLUSIONS: This systematic review identified multivariable models with biomedical and environmental predictors for medical usage rates at mass gatherings. Since the overall certainty of the evidence is low and the predictive performance is generally poor, proper development and validation of a context-specific model is recommended. ispartof: PLOS ONE vol:15 issue:6 ispartof: location:United States status: published

Background Because of the limited experience with tyrosine kinase receptor (TRK) gene fusion, a Belgian ring trial for TRK immunohistochemistry (IHC) staining was organised by the pathology department of Antwerp University Hospital. The trial was conducted between January and July 2019 with a total of 9 participating laboratories and aimed to harmonize pan-TRK IHC staining protocols and pan-TRK IHC interpretation. Methods The first and last slides of six selected cases were stained for TRK using the VENTANA pan-TRK Assay (clone EPR17341) on the Benchmark Ultra platform. Each participating laboratory received two unstained slides and was asked to return one TRK–stained slide per case and to report the protocol used and their interpretation. One site participated with two different protocols. The stained slides were evaluated by two designated pathologists. The results of a comparative study evaluating the IHC interpretations from the in-house pathologists of the different laboratories and those obtained from the trial-designated pathologists were communicated to the participating laboratories. Results Two different clones were used during the ring trial: A7H6R (Cell Signaling) and EPR17341 (Abcam/Ventana). The VENTANA pan-TRK Assay (clone EPR17341) on the Benchmark Ultra platform was most popular and used by 40% of the labs. The remaining in-house protocols used EPR17341 in its concentrated form (abcam) or A7H6R (Cell Signaling). Overall, 7 protocols achieved a sufficient performance mark and 3 labs were advised to further optimise the protocol. Interpretation of panTRK IHC proofed to be challenging in cases with physiological TRK expression. In addition, depending on the NTRK fusion partner, the staining can vary strongly in both intensity and staining pattern. Conclusions To our knowledge, this is the first panTRK IHC ring trial. According to our results, the EPR17341 and A7H6R clones are both highly recommendable antibodies for panTRK IHC. Labs using the Ventana ready-to-use system based on the EPR17341 clone and using the recommended protocol settings scored best. However, given some small optimisation, all labs scored well on the technical staining and the succeeding evaluation. Legal entity responsible for the study Antwerp University Hospital. Funding Bayer. Disclosure All authors have declared no conflicts of interest.