Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification and Management of High Risk Wilms Tumors

textabstractPediatric renal tumors comprise approximately 5% of malignancies in children under 15 years old and 3.6% of malignancies in children under 20 years old (1). Among 9731 patients registered with the National Wilms Tumor Study Group (NWTSG) (1969-2002), Wilms tumor composed the vast majority of childhood renal tumors (92%), followed by clear cell sarcoma of the kidney (3.4%), congenital mesoblastic nephroma (1.7%), malignant rhabdoid tumor (1.6%), and rare miscellaneous neoplasms including primitive neuroectodermal tumor (PNET), synovial sarcoma, neuroblastoma, and cystic nephroma (1.1%). Although not historically included on NWTSG studies, renal cell carcinoma accounts for 8% of renal tumors in children age 0-19 years according to data from the Surveillance, Epidemiology, and End Results (SEER) program (1). The study of Wilms tumor has had significant impact on the field of oncology. Tenets of cancer biology, such as Knudson’s two-hit model, tumor suppressor genes, and alteration of genomic imprinting as a cancer initiator, were pioneered in Wilms tumor. Wilms tumor also provided a paradigm for multidisciplinary treatment approaches and the conduct of cooperative group studies. Through the efforts of the NWTSG, International Society of Pediatric Oncology (SIOP), United Kingdom Children’s Cancer Study Group (UKCCSG) and others, the overall durable survival rate for Wilms tumor now approximates 90%. This remarkable feat has been achieved while reducing radiation and anthracycline exposure in most patients. Despite this success, it is premature to declare victory in the battle against Wilms tumor.
At Home with Users: A Comparative View of Living Labs

Living Labs provide a ‘human-centric’ research approach for the design of new ICT artefacts. In Living Labs users participate over several design stages, providing insights into unexpected ICT use, co-creation and evaluation of new IT solutions. Although this approach is becoming more popular, there is little comparative and reflective work on its practical dynamics, problems and possibilities. In this study, we analyse two 4-year Living Lab projects in Lancaster, UK and Siegen, Germany within the domain of Social TV, and compare experiences. We focus on documenting the purposes, methods and user dynamics that affect the trajectory of such long-term research initiatives, focusing inter alia on the dynamics of researcher/user interaction and the developing issues of trust and managing expectations; emphasizing some often neglected ethical issues and the impact of users' individual characteristics and their role in the community dynamics of Living Labs.
The Heuristic Quality Scale

This paper presents the Heuristic Quality Scale (HQS), an instrument designed to assess the quality of a published heuristic set. The purpose of this instrument is 2-fold: first, to aid the evaluator in selecting between prospective specialized heuristic sets for a given evaluation; second, to suggest considerations and guidelines for the creation and publication of new heuristic sets. The HQS was developed over a series of studies evaluating and refining iterations of the instrument while also polling the user experience community at large to identify which factors truly predict the quality of a particular set of heuristics. The contribution of the HQS is that it is a low-cost heuristic evaluation (HE) to apply to heuristic sets themselves. It produces a reliable subjective measure of the quality of a heuristic set and helps the usability professional rank and compare competing options for conducting HEs.
User Experience in the Work Domain: A Longitudinal Field Study

Of the many concepts of user experience (UX), only a few address UX in the work domain. In addition, while most underline the dynamic nature of UX, not many studies take an explicit longitudinal approach. This article presents data about how the UX of work-related interactive systems changed over the course of 13 weeks. Speci ﬁ cally, we studied the change in four groups of behaviors — execute, evolve, expand and engage — which we deem important for goal achievement. We examined the impact of user attributes (playfulness, computer expertise) as well as product attributes (pragmatic quality, hedonic quality). Multilevel analysis (MLA) provided the methodological frame for the statistical analysis. Since MLA is rather uncommon in human – computer interaction, we thoroughly discuss it and clarify its advantages over repeated-measures analysis of variance. Our study veri ﬁ ed that time is an important predictor, con ﬁ rming that UX (i.e. particular goal achievement-related behaviors and the perception of product attributes) changes over time. The pattern of change differed among participants in terms of rate and direction of change, and those differences even increased over the course of our study. Product attributes in ﬂ uenced change considerably, while playfulness had an impact on engaging behavior in the sense that more playful participants lost interest even faster.
Absolute and Relative User Perception of Classification Accuracy in an Affective Video Game

Classification algorithms are used in affective computing to classify the state of the user and adapt the computer’s behaviour, but it is unclear how classification accuracy influences the overall user experience. We present a study in which classification accuracy is artificially pre-defined and used to adapt to the difficulty of a video game. Eighty subjects played the game and were told that difficulty would be adapted according to the measured brain activity. They played the game twice, with different classification accuracies, and then reported different aspects of their overall game experience using questionnaires. Classification accuracy was correlated with both in-game fun (r = 0.46) and satisfaction with the difficulty adaptation (r = 0.56). Most subjects could perceive a difference between two classification accuracies that differed by 16.7%. We tentatively posit that, for affective video games, an acceptable classification accuracy is 70–80%. Furthermore, studies that attempt to improve affect classification accuracy should aim for a practically meaningful improvement of 10%.
Tipping point in plant–fungal interactions under severe drought causes abrupt rise in peatland ecosystem respiration

Ecosystems are increasingly prone to climate extremes, such as drought, with long‐lasting effects on both plant and soil communities and, subsequently, on carbon (C) cycling. However, recent studies underlined the strong variability in ecosystem's response to droughts, raising the issue of nonlinear responses in plant and soil communities. The conundrum is what causes ecosystems to shift in response to drought. Here, we investigated the response of plant and soil fungi to drought of different intensities using a water table gradient in peatlands—a major C sink ecosystem. Using moving window structural equation models, we show that substantial changes in ecosystem respiration, plant and soil fungal communities occurred when the water level fell below a tipping point of −24 cm. As a corollary, ecosystem respiration was the greatest when graminoids and saprotrophic fungi became prevalent as a response to the extreme drought. Graminoids indirectly influenced fungal functional composition and soil enzyme activities through their direct effect on dissolved organic matter quality, while saprotrophic fungi directly influenced soil enzyme activities. In turn, increasing enzyme activities promoted ecosystem respiration. We show that functional transitions in ecosystem respiration critically depend on the degree of response of graminoids and saprotrophic fungi to drought. Our results represent a major advance in understanding the nonlinear nature of ecosystem properties to drought and pave the way towards a truly mechanistic understanding of the effects of drought on ecosystem processes.
Shifts of growing‐season precipitation peaks decrease soil respiration in a semiarid grassland

Changing precipitation regimes could have profound influences on carbon (C) cycle in the biosphere. However, how soil C release from terrestrial ecosystems responds to changing seasonal distribution of precipitation remains unclear. A field experiment was conducted for 4 years (2013–2016) to examine the effects of altered precipitation distributions in the growing season on soil respiration in a temperate steppe in the Mongolian Plateau. Over the 4 years, both advanced and delayed precipitation peaks suppressed soil respiration, and the reductions mainly occurred in August. The decreased soil respiration could be primarily attributable to water stress and subsequently limited plant growth (community cover and belowground net primary productivity) and soil microbial activities in the middle growing season, suggesting that precipitation amount in the middle growing season is more important than that in the early, late, or whole growing seasons in regulating soil C release in grasslands. The observations of the additive effects of advanced and delayed precipitation peaks indicate semiarid grasslands will release less C through soil respiratory processes under the projected seasonal redistribution of precipitation in the future. Our findings highlight the potential role of intra‐annual redistribution of precipitation in regulating ecosystem C cycling in arid and semiarid regions.
Simulating the recent impacts of multiple biotic disturbances on forest carbon cycling across the United States

Biotic disturbances (BDs, for example, insects, pathogens, and wildlife herbivory) substantially affect boreal and temperate forest ecosystems globally. However, accurate impact assessments comprising larger spatial scales are lacking to date although these are critically needed given the expected disturbance intensification under a warming climate. Hence, our quantitative knowledge on current and future BD impacts, for example, on forest carbon (C) cycling, is strongly limited. We extended a dynamic global vegetation model to simulate ecosystem response to prescribed tree mortality and defoliation due to multiple biotic agents across United States forests during the period 1997–2015, and quantified the BD‐induced vegetation C loss, that is, C fluxes from live vegetation to dead organic matter pools. Annual disturbance fractions separated by BD type (tree mortality and defoliation) and agent (bark beetles, defoliator insects, other insects, pathogens, and other biotic agents) were calculated at 0.5° resolution from aerial‐surveyed data and applied within the model. Simulated BD‐induced C fluxes totaled 251.6 Mt C (annual mean: 13.2 Mt C year−1, SD ±7.3 Mt C year−1 between years) across the study domain, to which tree mortality contributed 95% and defoliation 5%. Among BD agents, bark beetles caused most C fluxes (61%), and total insect‐induced C fluxes were about five times larger compared to non‐insect agents, for example, pathogens and wildlife. Our findings further demonstrate that BD‐induced C cycle impacts (i) displayed high spatio‐temporal variability, (ii) were dominated by different agents across BD types and regions, and (iii) were comparable in magnitude to fire‐induced impacts. This study provides the first ecosystem model‐based assessment of BD‐induced impacts on forest C cycling at the continental scale and going beyond single agent‐host systems, thus allowing for comparisons across regions, BD types, and agents. Ultimately, a perspective on the potential and limitations of a more process‐based incorporation of multiple BDs in ecosystem models is offered.
Lags in the response of mountain plant communities to climate change

Rapid climatic changes and increasing human influence at high elevations around the world will have profound impacts on mountain biodiversity. However, forecasts from statistical models (e.g. species distribution models) rarely consider that plant community changes could substantially lag behind climatic changes, hindering our ability to make temporally realistic projections for the coming century. Indeed, the magnitudes of lags, and the relative importance of the different factors giving rise to them, remain poorly understood. We review evidence for three types of lag: “dispersal lags” affecting plant species’ spread along elevational gradients, “establishment lags” following their arrival in recipient communities, and “extinction lags” of resident species. Variation in lags is explained by variation among species in physiological and demographic responses, by effects of altered biotic interactions, and by aspects of the physical environment. Of these, altered biotic interactions could contribute substantially to establishment and extinction lags, yet impacts of biotic interactions on range dynamics are poorly understood. We develop a mechanistic community model to illustrate how species turnover in future communities might lag behind simple expectations based on species’ range shifts with unlimited dispersal. The model shows a combined contribution of altered biotic interactions and dispersal lags to plant community turnover along an elevational gradient following climate warming. Our review and simulation support the view that accounting for disequilibrium range dynamics will be essential for realistic forecasts of patterns of biodiversity under climate change, with implications for the conservation of mountain species and the ecosystem functions they provide.
Climate change impacts on selected global rangeland ecosystem services

Rangelands are Earth's dominant land cover and are important providers of ecosystem services. Reliance on rangelands is projected to grow, thus understanding the sensitivity of rangelands to future climates is essential. We used a new ecosystem model of moderate complexity that allows, for the first time, to quantify global changes expected in rangelands under future climates. The mean global annual net primary production (NPP) may decline by 10 g C m−2 year−1 in 2050 under Representative Concentration Pathway (RCP) 8.5, but herbaceous NPP is projected to increase slightly (i.e., average of 3 g C m−2 year−1). Responses vary substantially from place‐to‐place, with large increases in annual productivity projected in northern regions (e.g., a 21% increase in productivity in the US and Canada) and large declines in western Africa (−46% in sub‐Saharan western Africa) and Australia (−17%). Soil organic carbon is projected to increase in Australia (9%), the Middle East (14%), and central Asia (16%) and decline in many African savannas (e.g., −18% in sub‐Saharan western Africa). Livestock are projected to decline 7.5 to 9.6%, an economic loss of from $9.7 to $12.6 billion. Our results suggest that forage production in Africa is sensitive to changes in climate, which will have substantial impacts on the livelihoods of the more than 180 million people who raise livestock on those rangelands. Our approach and the simulation tool presented here offer considerable potential for forecasting future conditions, highlight regions of concern, and support analyses where costs and benefits of adaptations and policies may be quantified. Otherwise, the technical options and policy and enabling environment that are needed to facilitate widespread adaptation may be very difficult to elucidate.
Increase in beta-lactam-resistant Proteus mirabilis strains due to CTX-M- and CMY-type as well as new VEB- and inhibitor-resistant TEM-type beta-lactamases.

OBJECTIVES The aim of this study was to characterize the different inhibitor-resistant TEM beta-lactamases, extended-spectrum beta-lactamases (ESBLs) and plasmid-mediated AmpC beta-lactamases implicated in beta-lactam resistance in Proteus mirabilis, which has increased over recent years. METHODS From February 2000 to December 2005, 1423 clinical isolates of P. mirabilis were collected. The AmpC phenotype was checked by means of a double-disc synergy test using cloxacillin as an inhibitor of AmpC enzymes. The production of ESBL was assessed by the double-disc synergy method and by Etest ESBL. Analytical isoelectric focusing, determination of kinetic constants, conjugation, PCR and a sequencing strategy were used to characterize the enzymes. The possible relationships between isolates were analysed by PFGE. RESULTS AND CONCLUSIONS Twenty-five of 1423 isolates were found to display intermediate or full resistance to co-amoxiclav, cefotaxime or ceftazidime. Seventeen isolates had reduced susceptibility to co-amoxiclav; of these, seven produced TEM-110, eight produced the new TEM-159, one the new TEM-160 and one TEM-1. Five isolates producing TEM-110, TEM-159 or TEM-160 enzymes shared the same PFGE profile. Three isolates produced an ESBL, CTX-M-1, CTX-M-32 and the new variant, VEB-4. Finally, five isolates with an AmpC phenotype produced CMY-2, two with the same PFGE profile. Our data emphasize the diversity of beta-lactamases found in this species.
Superiority of frailty over age in predicting outcomes among geriatric trauma patients: a prospective analysis.

IMPORTANCE The Frailty Index (FI) is a known predictor of adverse outcomes in geriatric patients. The usefulness of the FI as an outcome measure in geriatric trauma patients is unknown. OBJECTIVE To assess the usefulness of the FI as an effective assessment tool in predicting adverse outcomes in geriatric trauma patients. DESIGN, SETTING, AND PARTICIPANTS A 2-year (June 2011 to February 2013) prospective cohort study at a level I trauma center at the University of Arizona. We prospectively measured frailty in all geriatric trauma patients. Geriatric patients were defined as those 65 years or older. The FI was calculated using 50 preadmission frailty variables. Frailty in patients was defined by an FI of 0.25 or higher. MAIN OUTCOMES AND MEASURES The primary outcome measure was in-hospital complications. The secondary outcome measure was adverse discharge disposition. In-hospital complications were defined as cardiac, pulmonary, infectious, hematologic, renal, and reoperation. Adverse discharge disposition was defined as discharge to a skilled nursing facility or in-hospital mortality. Multivariate logistic regression was used to assess the relationship between the FI and outcomes. RESULTS In total, 250 patients were enrolled, with a mean (SD) age of 77.9 (8.1) years, median Injury Severity Score of 15 (range, 9-18), median Glasgow Coma Scale score of 15 (range, 12-15), and mean (SD) FI of 0.21 (0.10). Forty-four percent (n = 110) of patients had frailty. Patients with frailty were more likely to have in-hospital complications (odds ratio, 2.5; 95% CI, 1.5-6.0; P = .001) and adverse discharge disposition (odds ratio, 1.6; 95% CI, 1.1-2.4; P = .001). The mortality rate was 2.0% (n = 5), and all patients who died had frailty. CONCLUSIONS AND RELEVANCE The FI is an independent predictor of in-hospital complications and adverse discharge disposition in geriatric trauma patients. This index should be used as a clinical tool for risk stratification in this patient group.
Tamanho da amostra em estudos clínicos e experimentais

dimension and also the sampling technique (collection/selection) of the elements of the study. It is essential in the elaboration of the project, and problems with such planning may compromise the final data analysis and interpretation of its results. A proper sample planning depends on basic knowledge of the study statistics and deep knowledge of the problem under investigation, in order to combine the statistical significance of the tests with the clinical meaning of the results 1,3,4 . Most biostatistical tests assume that the study sample is probabilistically representative of the population. Some samples of convenience, e.g. like choosing consecutive patients of a specific outpatient clinic, may not properly rep resent all the study population. The investigator should be alert to possible selection biases resulting from the availability of patients in consecutive sampling, because increasing sample size would not correct the effect of biased samples. In addition, strategies of non-probability stratified sampling, by using sample quotas, complex sampling (conglomerates, multi-levels), voluntary response, saturation of variables,
Malignant Transformation and Stromal Invasion from Normal Appearing Prostate Tissues: True or False?

The human prostate epithelium, which is the histological origin of most prostate malignancies, is physically separated from the stroma by a layer of basal cells and the basement membrane. Basal cells are inter-connected by intercellular junctions and adhesion molecules, constituting a continuous sheet encircling luminal cells [1-2]. The basement membrane is composed of type IV collagen, laminins, and other molecules, forming a continuous lining surrounding and attaching to the basal cell layer [3-4] (Fig 1). The basement membrane and the basal cell layer are intermixed to form a dense fibrous capsule surrounding all epithelial cells. Due to these relationships, disruption of the basal cell layer and the basement membrane is a pre-requisite for tumor invasion or metastasis. It is a commonly held belief that prostate carcinogenesis progresses sequentially from normal to hyperplasia, to prostatic intraepithelial neoplasia (PIN), and to invasive or metastatic lesions [5-8]. Progression from PIN to invasion is believed to be triggered by overproduction of proteolytic enzymes primarily by cancer cells, which cause degradation of the tumor capsule [9-10]. These theories are consistent with laboratory findings from cell cultures and animal models, whereas are hard to reconcile with a number of critical facts. First, previous studies revealed that some healthy men between 19 and 29 years old had a spectrum of proliferative lesions, including hyperplasia, PIN, and incipient adenocarcinoma [11-13]. Second, recent studies have detected a DNA phenotype identical to that of invasive prostate cancer in some “healthy” men, and also in normal prostate tissues adjacent to prostate cancer [14-17]. Third, a majority of PIN express high levels of proteolytic enzymes, but only 10-30% of untreated PIN progress to invasive lesions during patients’ lifetime [1821]. Fourth, cancer of unknown primary site is one of the 10 most frequent cancers worldwide and the 4th most common cause of cancer deaths [22-24]. Together, these facts argue that the linear model of carcinogenesis [5-8] and enzyme theory of tumor invasion [9-10] are not universally applicable to all prostate cancer cases. These facts also suggest that the past efforts to classify tumor progression and invasion purely based on the profiles of epithelial cells may have overlooked some essential factors. As over 90% of prostate cancer related mortality result from invasion related diseases, and the incidence of PIN could be up to 16.5%-25% in prostate biopsies [25-27], there is an urgent