Generating actionable predictions regarding MOOC learners' engagement in peer reviews

Peer review is one approach to facilitate formative feedback exchange in MOOCs; however, it is often undermined by low participation. To support effective implementation of peer reviews in MOOCs, this research work proposes several predictive models to accurately classify learners according to their expected engagement levels in an upcoming peer-review activity, which offers various pedagogical utilities (e.g. improving peer reviews and collaborative learning activities). Two approaches were used for training the models: in situ learning (in which an engagement indicator available at the time of the predictions is used as a proxy label to train a model within the same course) and transfer across courses (in which a model is trained using labels obtained from past course data). These techniques allowed producing predictions that are actionable by the instructor while the course still continues, which is not possible with post-hoc approaches requiring the use of true labels. According to the results, both transfer across courses and in situ learning approaches have produced predictions that were actionable yet as accurate as those obtained with cross validation, suggesting that they deserve further attention to create impact in MOOCs with real-world interventions. Potential pedagogical uses of the predictions were illustrated with several examples

Extremity tourniquet training at high seas

Background Future navy officers require unique training for emergency medical response in the isolated maritime environment. The authors issued a workshop on extremity bleeding control, using four different commercial extremity tourniquets onboard a training sail ship. The purposes were to assess participants' perceptions of this educational experience and evaluate self-application simplicity while navigating on high seas. Methods A descriptive observational study was conducted as part of a workshop issued to volunteer training officers. A post-workshop survey collected their perceptions about the workshops' content usefulness and adequacy, tourniquet safety, self-application simplicity, and device preference. Tourniquet preference was measured by frequency count while the rest of the studied variables on a one-to-ten Likert scale. Frequencies and percentages were calculated for the studied variables, and application simplicity means compared using the ANOVA test (p < 0.05). Results Fifty-one Spanish training naval officers, aged 20 or 21, perceived high sea workshop content’s usefulness, adequacy, and safety level at 8.6/10, 8.7/10, and 7.5/10, respectively. As for application simplicity, CAT and SAM-XT were rated equally with a mean of 8.5, followed by SWAT (7.9) and RATS (6.9), this one statistically different from the rest (p < 0.01). Windlass types were preferred by 94%. Conclusions The training sail ship’s extremity bleeding control workshop was perceived as useful and its content adequate by the participating midshipmen. Windlass types were regarded as easier to apply than elastic counterparts. They were also preferred by nine out of every ten participants

Toward Multimodal Analytics in Ubiquitous Learning Environments

While Ubiquitous Learning Environments (ULEs) have shown several benefits for learning, they pose challenges for orchestration. Teachers need to be aware of the learning process, which is difficult to achieve when it occurs across a heterogeneous set of spaces, resources and devices. In addition, ULEs can benefit from multimodal analyses due to the heterogeneity of the data sources available (e.g., logs, geolocation, sensor information, learning artifacts). In previous works, we proposed an orchestration system with some analytics features that can gather multimodal datasets during the learning process. Based on this experience, in this paper we describe the technological support provided by the system to collect data from multiple spaces and sources as well as the structure of the generated dataset. We also reflect about the challenges of multimodal learning analytics (MMLA) in ULEs, and we pose some ideas about how the system could better support MMLA in the future to mitigate those challenges

Prognostic Gene Expression-Based Signature in Clear-Cell Renal Cell Carcinoma

The inaccuracy of the current prognostic algorithms and the potential changes in the therapeutic management of localized ccRCC demands the development of an improved prognostic model for these patients. To this end, we analyzed whole-transcriptome profiling of 26 tissue samples from progressive and non-progressive ccRCCs using Illumina Hi-seq 4000. Differentially expressed genes (DEG) were intersected with the RNA-sequencing data from the TCGA. The overlapping genes were used for further analysis. A total of 132 genes were found to be prognosis-related genes. LASSO regression enabled the development of the best prognostic six-gene panel. Cox regression analyses were performed to identify independent clinical prognostic parameters to construct a combined nomogram which includes the expression of CERCAM, MIA2, HS6ST2, ONECUT2, SOX12, TMEM132A, pT stage, tumor size and ISUP grade. A risk score generated using this model effectively stratified patients at higher risk of disease progression (HR 10.79; p < 0.001) and cancer-specific death (HR 19.27; p < 0.001). It correlated with the clinicopathological variables, enabling us to discriminate a subset of patients at higher risk of progression within the Stage, Size, Grade and Necrosis score (SSIGN) risk groups, pT and ISUP grade. In summary, a gene expression-based prognostic signature was successfully developed providing a more precise assessment of the individual risk of progression

Differential gene expression profile between progressive and de novo muscle invasive bladder cancer and its prognostic implication

This study aimed to ascertain gene expression profle diferences between progressive muscle-invasive bladder cancer (MIBC) and de novo MIBC, and to identify prognostic biomarkers to improve patients' treatment. Retrospective multicenter study in which 212 MIBC patients who underwent radical cystectomy between 2000 and 2019 were included. Gene expression profles were determined in 26 samples using Illumina microarrays. The expression levels of 94 genes were studied by quantitative PCR in an independent set of 186 MIBC patients. In a median follow-up of 16 months, 46.7% patients developed tumor progression after cystectomy. In our series, progressive MIBC patients show a worse tumor progression (p= 0.024) and cancer-specifc survival (CSS) (p= 0.049) than the de novo group. A total of 480 genes were found to be diferently expressed between both groups. Diferential expression of 24 out of the 94 selected genes was found in an independent cohort. RBPMC2 and DSC3 were found as independent prognostic biomarkers of tumor progression and CALD1 and LCOR were identifed as prognostic biomarkers of CSS between both groups. In conclusion, progressive and de novo MIBC patients show diferent clinical outcome and gene expression profles. Gene expression patterns may contribute to predict high-risk of progression to distant metastasis or CSS

Prevalence of orthostatic hypotension in a series of elderly Mexican institutionalized patients

Background: Orthostatic hypotension (OH) is a common problem among the elderly. It is associated with an increase in morbidity and mortality, but its prevalence in Mexico is unknown. Methods: We conducted a cross-sectional prospective study of intern patients at several Mexican elderly assistance institutions. We carried out a history and took blood pressure readings in a seated position, immediately after standing up, and again after 3 min of standing up. Results: We evaluated 132 patients, mean age 82.3 &#177; 9.5 years, 74.1% of them female. Thirty-nine (29.3%) subjects had OH. They had a higher prevalence of hypothyroidism, Parkinson&#8217;s disease, depression and alcoholism. Their Minimental result was 15.45 &#177; 7.2 vs 16.12 &#177; 7.9 (p = 0.6) among those without OH, and their quality of life (Minnesota scale) was 12.1 &#177; 7.3 vs 9.15 &#177; 7.05 (p = 0.03). They used more ACEI, digoxin and levothyroxin. Hypertension and alcoholism showed respectively a RR of 2.6 (95% CI 0.9&#8211;7.6, p = 0.06) and 3.18 (95% CI 0.96&#8211;10.48, p = 0.05) to develop OH. Conclusions: OH was present in 29.3% of the studied population. A third of them had hypertension. The use of different medications does not solely explain OH, so it is necessary to look for different associations. Among those, chronic alcoholism stands out. OH is associated with a poorer quality of life and cognitive performance. OH is asymptomatic in most cases. (Cardiol J 2011; 18, 3: 282&#8211;288

The use of fluoroproline in MUC1 antigen enables efficient detection of antibodies in patients with prostate cancer

A structure-based design of a new generation of tumor-associated glycopeptides with improved affinity against two anti-MUC1 antibodies is described. These unique antigens feature a fluorinated proline residue, such as a (4S)-4-fluoro-l-proline or 4,4-difluoro-l-proline, at the most immunogenic domain. Binding assays using biolayer interferometry reveal 3-fold to 10-fold affinity improvement with respect to the natural (glyco)peptides. According to X-ray crystallography and MD simulations, the fluorinated residues stabilize the antigen-antibody complex by enhancing key CH/π interactions. Interestingly, a notable improvement in detection of cancer-associated anti-MUC1 antibodies from serum of patients with prostate cancer is achieved with the non-natural antigens, which proves that these derivatives can be considered better diagnostic tools than the natural antigen for prostate cancer.We thank the Ministerio de Economía y Competitividad (projects CTQ2015-67727-R, UNLR13-4E-1931, CTQ2013-44367-C2-2-P, CTQ2015-64597-C2-1P, and BFU2016-75633-P). I.A.B. thanks the Asociación Española Contra el Cancer en La Rioja for a grant. I.S.A. and G.J.L.B. thank FCT Portugal (Ph.D. studentship and FCT Investigator, respectively) and EPSRC. G.J.L.B. holds a Royal Society URF and an ERC StG (TagIt). F.C. and G.J.L.B thank the EU (Marie-Sklodowska Curie ITN, Protein Conjugates). R.H-G. thanks Agencia Aragonesa para la Investigación y Desarrollo (ARAID) and the Diputación General de Aragón (DGA, B89) for financial support. The research leading to these results has also received funding from the FP7 (2007-2013) under BioStruct-X (grant agreement no. 283570 and BIOSTRUCTX_5186). We thank synchrotron radiation source DIAMOND (Oxford) and beamline I04 (number of experiment mx10121-19). The Hokkaido University group acknowledges JSPS KAKENHI grant no. 25220206 and JSPS Wakate B KAKENHI grant no. 24710242. We also thank CESGA (Santiago de Compostela) for computer support.Peer reviewedPeer Reviewe

A Fungal Versatile GH10 Endoxylanase and Its Glycosynthase Variant: Synthesis of Xylooligosaccharides and Glycosides of Bioactive Phenolic Compounds

The study of endoxylanases as catalysts to valorize hemicellulosic residues and to obtain glycosides with improved properties is a topic of great industrial interest. In this work, a GH10 β-1,4-endoxylanase (XynSOS), from the ascomycetous fungus Talaromyces amestolkiae, has been het- erologously produced in Pichia pastoris, purified, and characterized. rXynSOS is a highly glycosylated monomeric enzyme of 53 kDa that contains a functional CBM1 domain and shows its optimal activity on azurine cross-linked (AZCL)–beechwood xylan at 70 ◦C and pH 5. Substrate specificity and kinetic studies confirmed its versatility and high affinity for beechwood xylan and wheat arabi- noxylan. Moreover, rXynSOS was capable of transglycosylating phenolic compounds, although with low efficiencies. For expanding its synthetic capacity, a glycosynthase variant of rXynSOS was developed by directed mutagenesis, replacing its nucleophile catalytic residue E236 by a glycine (rXynSOS-E236G). This novel glycosynthase was able to synthesize β-1,4-xylooligosaccharides (XOS) of different lengths (four, six, eight, and ten xylose units), which are known to be emerging prebiotics. rXynSOS-E236G was also much more active than the native enzyme in the glycosylation of a broad range of phenolic compounds with antioxidant properties. The interesting capabilities of rXynSOS and its glycosynthase variant make them promising tools for biotechnological application.This research was funded by the MICIU/AEI/FEDER [RTI2018-093683-B-I00, RTI2018- 094751-B-C22, PID2019-107476GB-I00], Comunidad de Madrid [RETOPROSOST-2-CM P2018/EMT- 4459], and CIBERES (an initiative from the Spanish Institute of Health Carlos IPeer reviewe

Urine cell-based DNA methylation classifier for monitoring bladder cancer

Background: Current standard methods used to detect and monitor bladder cancer (BC) are invasive or have low sensitivity. This study aimed to develop a urine methylation biomarker classifier for BC monitoring and validate this classifier in patients in follow-up for bladder cancer (PFBC). Methods: Voided urine samples (N = 725) from BC patients, controls, and PFBC were prospectively collected in four centers. Finally, 626 urine samples were available for analysis. DNA was extracted from the urinary cells and bisulfite modificated, and methylation status was analyzed using pyrosequencing. Cytology was available from a subset of patients (N = 399). In the discovery phase, seven selected genes from the literature (CDH13, CFTR, NID2, SALL3, TMEFF2, TWIST1, and VIM2) were studied in 111 BC and 57 control samples. This training set was used to develop a gene classifier by logistic regression and was validated in 458 PFBC samples (173 with recurrence). Results: A three-gene methylation classifier containing CFTR, SALL3, and TWIST1 was developed in the training set (AUC 0.874). The classifier achieved an AUC of 0.741 in the validation series. Cytology results were available for 308 samples from the validation set. Cytology achieved AUC 0.696 whereas the classifier in this subset of patients reached an AUC 0.768. Combining the methylation classifier with cytology results achieved an AUC 0.86 in the validation set, with a sensitivity of 96%, a specificity of 40%, and a positive and negative predictive value of 56 and 92%, respectively. Conclusions: The combination of the three-gene methylation classifier and cytology results has high sensitivity and high negative predictive value in a real clinical scenario (PFBC). The proposed classifier is a useful test for predicting BC recurrence and decrease the number of cystoscopies in the follow-up of BC patients. If only patients with a positive combined classifier result would be cystoscopied, 36% of all cystoscopies can be prevented