sion of risk) is not associated with high-PPT (another dimension of risk). This finding has important clinical and theoretical implications.
 The study suggests both higher level of PC and pressure sensitivity have a cumulative impact on risk screening for pain-related outcomes, considering gender in functional avoidance (task-related outcome). A clinical presentation with high-PC (one dimension of risk) is not associated with high-PPT (another dimension of risk). This finding has important clinical and theoretical implications.The evidence-based medicine allows the physician to evaluate the risk-benefit ratio of a treatment through setting and data. Risk-based choices can be done by the doctor using different information. With the emergence of new technologies, a large amount of data is recorded offering interesting perspectives with machine learning for predictive data analytics. Machine learning is an ensemble of methods that process data to model a learning problem. Supervised machine learning algorithms consist in using annotated data to construct the model. This category allows to solve prediction data analytics problems. In this paper, we detail the use of supervised machine learning algorithms for predictive data analytics problems in medicine. In the medical field, data can be split into two categories medical images and other data. For brevity, our review deals with any kind of medical data excluding images. In this article, we offer a discussion around four supervised machine learning approaches information-based, similarity-based, probability-based and error-based approaches. Each method is illustrated with detailed cardiovascular and nuclear medicine examples. Our review shows that model ensemble (ME) and support vector machine (SVM) methods are the most popular. SVM, ME and artificial neural networks often lead to better results than those given by other algorithms. In the coming years, more studies, more data, more tools and more methods will, for sure, be proposed.Like many institutions around the world, the COVID-19 pandemic prompted us to shift our summer 2020 in-person undergraduate experiential learning program to a remote, virtual format. Here, we present our observations, summarized in 10 best practices, for moving a STEM-focused research experience for undergraduates, experiential learning program or research-based course online. We will also discuss how our program was originally designed and implemented, and how we adapted our activities to deliver an at-home research experience that maintained student engagement, mentorship, and a shared sense of community.Clinical presentation of Wilson disease (WD) includes hepatic and neurologic manifestations. This study compares subcortical brain regions by magnetic resonance imaging (MRI) in WD patients with and without neurological symptoms. Distinct atrophy affecting the basal ganglia, accumbens and hippocampus were present in neurological WD. Cerebellar atrophy was observed in hepatic WD without neurological symptoms.Extreme drought events have negative effects on forest diversity and functioning. At the species level, however, these effects are still unclear, as species vary in their response to drought through specific functional trait combinations. We used long-term demographic records of 21,821 trees and extensive databases of traits to understand the responses of 338 tropical dry forests tree species to ENSO2015 , the driest event in decades in Northern South America. Functional differences between species were related to the hydraulic safety-efficiency trade-off, but unexpectedly, dominant species were characterised by high investment in leaf and wood tissues regardless of their leaf phenological habit. Despite broad functional trait combinations, tree mortality was more widespread in the functional space than tree growth, where less adapted species showed more negative net biomass balances. Our results suggest that if dry conditions increase in this ecosystem, ecological functionality and biomass gain would be reduced.
  This study aimed to evaluate the relationship between p62 expression status and tumour regression grade in advanced rectal cancer.
 
  We enrolled 47 consecutive patients with advanced rectal cancer who underwent chemoradiation therapy (CRT) before surgery. p62 expression in the biopsy specimens was immunohistochemically evaluated, and p62 expression score (staining intensity × positive tumour cells, %) was calculated (range 0-300). The relationship between p62 expression score and CRT effect was analysed.
 
  The staining intensity was +2 and +3 in 29 and 18 patients, respectively. The median proportion of positive neoplastic cells was 87.8%, and that of the p62 expression score was 200. Stronger staining intensity and a higher proportion of p62-positive neoplastic cells were significantly associated with CRT non-effectiveness (P=0.0002 and P=0.0116, respectively), and a higher p62 expression score was significantly associated with CRT non-effectiveness (P<0.0001). The optimal cut-off value for predicting the CRT effect was 240.
 
  A higher p62 expression score was significantly associated with less CRT effectiveness in patients with advanced rectal cancer. Analysis of p62 expression score using biopsy specimens is a useful and easily assessable prediction marker for CRT effect and might help select patients who can undergo a 'watch-and-wait' strategy after CRT.
 A higher p62 expression score was significantly associated with less CRT effectiveness in patients with advanced rectal cancer. Analysis of p62 expression score using biopsy specimens is a useful and easily assessable prediction marker for CRT effect and might help select patients who can undergo a 'watch-and-wait' strategy after CRT.Cross-presentation was first observed serendipitously in the 1970s. The importance of it was quickly realized and subsequently attracted great attention from immunologists. Since then, our knowledge of the ability of certain antigen presenting cells to internalize, process, and load exogenous antigens onto MHC-I molecules to cross-prime CD8+ T cells has increased significantly. Dendritic cells (DCs) are exceptional cross-presenters, thus making them a great tool to study cross-presentation but the relative rarity of DCs in circulation and in tissues makes it challenging to isolate sufficient numbers of cells to study this process in vitro. In this paper, we describe in detail two methods to culture DCs from bone-marrow progenitors and a method to expand the numbers of DCs present in vivo as a source of endogenous bona-fide cross-presenting DCs. We also describe methods to assess cross-presentation by DCs using the activation of primary CD8+ T cells as a readout. © 2020 Wiley Periodicals LLC.  https://www.selleckchem.com/btk.html  Basic Protocol 1 Isolation of bone marrow progenitor cells Basic Protocol 2 In vitro differentiation of dendritic cells with GM-CSF Support Protocol 1 Preparation of conditioned medium from GM-CSF producing J558L cells Basic Protocol 3 In vitro differentiation of dendritic cells with Flt3L Support Protocol 2 Preparation of Flt3L containing medium from B16-Flt3L cells Basic Protocol 4 Expansion of cDC1s in vivo for use in ex vivo experiments Basic Protocol 5 Characterizing resting and activated dendritic cells Basic Protocol 6 Dendritic cell stimulation, antigenic cargo, and fixation Support Protocol 3 Preparation of model antigen coated microbeads Support Protocol 4 Preparation of apoptotic cells Support Protocol 5 Preparation of recombinant bacteria Basic Protocol 7 Immunocytochemistry immunofluorescence (ICC/IF) Support Protocol 6 Preparation of Alcian blue-coated coverslips Basic Protocol 8 CD8+ T cell activation to assess cross-presentation Support Protocol 7 Isolation and labeling of CD8+ T cells with CFSE.