Introducción a la genética en la enseñanza secundaria y bachillerato : II. ¿Resolución de problemas o realización de ejercicios?

In this paper we analize the level of knowledge students have at different educational levels (15-18 years), about some basic concepts related to genetic inheritance. The strategies developed by students when solving, successfully, genetic problems have also been studied. The results show the difficulties in learning through problem-solving activities. Consequently, very often, their posings (even those of cause-effect approach) allow them to find the right solution by applying the correspondent algorithm. As a conclusion, some suggestions to change the students' position on genetic problems are presented

Extraction of decision rules via imprecise probabilities

"This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of General Systems on 2017, available online: https://www.tandfonline.com/doi/full/10.1080/03081079.2017.1312359"Data analysis techniques can be applied to discover important relations among features. This is the main objective of the Information Root Node Variation (IRNV) technique, a new method to extract knowledge from data via decision trees. The decision trees used by the original method were built using classic split criteria. The performance of new split criteria based on imprecise probabilities and uncertainty measures, called credal split criteria, differs significantly from the performance obtained using the classic criteria. This paper extends the IRNV method using two credal split criteria: one based on a mathematical parametric model, and other one based on a non-parametric model. The performance of the method is analyzed using a case study of traffic accident data to identify patterns related to the severity of an accident. We found that a larger number of rules is generated, significantly supplementing the information obtained using the classic split criteria.This work has been supported by the Spanish "Ministerio de Economia y Competitividad" [Project number TEC2015-69496-R] and FEDER funds.Abellán, J.; López-Maldonado, G.; Garach, L.; Castellano, JG. (2017). Extraction of decision rules via imprecise probabilities. International Journal of General Systems. 46(4):313-331. https://doi.org/10.1080/03081079.2017.1312359S313331464Abellan, J., & Bosse, E. (2018). Drawbacks of Uncertainty Measures Based on the Pignistic Transformation. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 48(3), 382-388. doi:10.1109/tsmc.2016.2597267Abellán, J., & Klir, G. J. (2005). Additivity of uncertainty measures on credal sets. International Journal of General Systems, 34(6), 691-713. doi:10.1080/03081070500396915Abellán, J., & Masegosa, A. R. (2010). An ensemble method using credal decision trees. European Journal of Operational Research, 205(1), 218-226. doi:10.1016/j.ejor.2009.12.003(2003). International Journal of Intelligent Systems, 18(12). doi:10.1002/int.v18:12Abellán, J., Klir, G. J., & Moral, S. (2006). Disaggregated total uncertainty measure for credal sets. International Journal of General Systems, 35(1), 29-44. doi:10.1080/03081070500473490Abellán, J., Baker, R. M., & Coolen, F. P. A. (2011). Maximising entropy on the nonparametric predictive inference model for multinomial data. European Journal of Operational Research, 212(1), 112-122. doi:10.1016/j.ejor.2011.01.020Abellán, J., López, G., & de Oña, J. (2013). Analysis of traffic accident severity using Decision Rules via Decision Trees. Expert Systems with Applications, 40(15), 6047-6054. doi:10.1016/j.eswa.2013.05.027Abellán, J., Baker, R. M., Coolen, F. P. A., Crossman, R. J., & Masegosa, A. R. (2014). Classification with decision trees from a nonparametric predictive inference perspective. Computational Statistics & Data Analysis, 71, 789-802. doi:10.1016/j.csda.2013.02.009Alkhalid, A., Amin, T., Chikalov, I., Hussain, S., Moshkov, M., & Zielosko, B. (2013). Optimization and analysis of decision trees and rules: dynamic programming approach. International Journal of General Systems, 42(6), 614-634. doi:10.1080/03081079.2013.798902Chang, L.-Y., & Chien, J.-T. (2013). Analysis of driver injury severity in truck-involved accidents using a non-parametric classification tree model. Safety Science, 51(1), 17-22. doi:10.1016/j.ssci.2012.06.017Chang, L.-Y., & Wang, H.-W. (2006). Analysis of traffic injury severity: An application of non-parametric classification tree techniques. Accident Analysis & Prevention, 38(5), 1019-1027. doi:10.1016/j.aap.2006.04.009DE CAMPOS, L. M., HUETE, J. F., & MORAL, S. (1994). PROBABILITY INTERVALS: A TOOL FOR UNCERTAIN REASONING. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 02(02), 167-196. doi:10.1142/s0218488594000146DGT. 2011b.Spanish Road Safety Strategy 2011–2020, 222 p. Madrid: Traffic General Directorate.Dolques, X., Le Ber, F., Huchard, M., & Grac, C. (2016). Performance-friendly rule extraction in large water data-sets with AOC posets and relational concept analysis. International Journal of General Systems, 45(2), 187-210. doi:10.1080/03081079.2015.1072927Gray, R. C., Quddus, M. A., & Evans, A. (2008). Injury severity analysis of accidents involving young male drivers in Great Britain. Journal of Safety Research, 39(5), 483-495. doi:10.1016/j.jsr.2008.07.003Guo, J., & Chankong, V. (2002). Rough set-based approach to rule generation and rule induction. International Journal of General Systems, 31(6), 601-617. doi:10.1080/0308107021000034353Huang, H., Chin, H. C., & Haque, M. M. (2008). Severity of driver injury and vehicle damage in traffic crashes at intersections: A Bayesian hierarchical analysis. Accident Analysis & Prevention, 40(1), 45-54. doi:10.1016/j.aap.2007.04.002Kashani, A. T., & Mohaymany, A. S. (2011). Analysis of the traffic injury severity on two-lane, two-way rural roads based on classification tree models. Safety Science, 49(10), 1314-1320. doi:10.1016/j.ssci.2011.04.019Li, X., & Yu, L. (2016). Decision making under various types of uncertainty. International Journal of General Systems, 45(3), 251-252. doi:10.1080/03081079.2015.1086574Mantas, C. J., & Abellán, J. (2014). Analysis and extension of decision trees based on imprecise probabilities: Application on noisy data. Expert Systems with Applications, 41(5), 2514-2525. doi:10.1016/j.eswa.2013.09.050Mayhew, D. R., Simpson, H. M., & Pak, A. (2003). Changes in collision rates among novice drivers during the first months of driving. Accident Analysis & Prevention, 35(5), 683-691. doi:10.1016/s0001-4575(02)00047-7McCartt, A. T., Mayhew, D. R., Braitman, K. A., Ferguson, S. A., & Simpson, H. M. (2009). Effects of Age and Experience on Young Driver Crashes: Review of Recent Literature. Traffic Injury Prevention, 10(3), 209-219. doi:10.1080/15389580802677807Montella, A., Aria, M., D’Ambrosio, A., & Mauriello, F. (2011). Data-Mining Techniques for Exploratory Analysis of Pedestrian Crashes. Transportation Research Record: Journal of the Transportation Research Board, 2237(1), 107-116. doi:10.3141/2237-12Montella, A., Aria, M., D’Ambrosio, A., & Mauriello, F. (2012). Analysis of powered two-wheeler crashes in Italy by classification trees and rules discovery. Accident Analysis & Prevention, 49, 58-72. doi:10.1016/j.aap.2011.04.025De Oña, J., López, G., & Abellán, J. (2013). Extracting decision rules from police accident reports through decision trees. Accident Analysis & Prevention, 50, 1151-1160. doi:10.1016/j.aap.2012.09.006De Oña, J., López, G., Mujalli, R., & Calvo, F. J. (2013). Analysis of traffic accidents on rural highways using Latent Class Clustering and Bayesian Networks. Accident Analysis & Prevention, 51, 1-10. doi:10.1016/j.aap.2012.10.016Pande, A., & Abdel-Aty, M. (2009). Market basket analysis of crash data from large jurisdictions and its potential as a decision support tool. Safety Science, 47(1), 145-154. doi:10.1016/j.ssci.2007.12.001Peek-Asa, C., Britton, C., Young, T., Pawlovich, M., & Falb, S. (2010). Teenage driver crash incidence and factors influencing crash injury by rurality. Journal of Safety Research, 41(6), 487-492. doi:10.1016/j.jsr.2010.10.002Sikora, M., & Wróbel, Ł. (2013). Data-driven adaptive selection of rule quality measures for improving rule induction and filtration algorithms. International Journal of General Systems, 42(6), 594-613. doi:10.1080/03081079.2013.798901Walley, P. (1996). Inferences from Multinomial Data: Learning About a Bag of Marbles. Journal of the Royal Statistical Society: Series B (Methodological), 58(1), 3-34. doi:10.1111/j.2517-6161.1996.tb02065.xWang, Z., & Klir, G. J. (1992). Fuzzy Measure Theory. doi:10.1007/978-1-4757-5303-5Webb, G. I. (2007). Discovering Significant Patterns. Machine Learning, 68(1), 1-33. doi:10.1007/s10994-007-5006-xWitten, I. H., & Frank, E. (2002). Data mining. ACM SIGMOD Record, 31(1), 76-77. doi:10.1145/507338.50735

NOx selective catalytic reduction at high temperatures with mixed oxides derived from layered double hydroxides

[EN] Mixed oxides derived from layered double hydroxides (LDHs) have been investigated as potential catalysts for the NOx removal at high temperatures. The best results were obtained with Co–Al mixed oxides derived from LDHs that are active at 750 ◦C in the presence of oxygen and water. These catalysts could reduce or/and decompose the NOx formed in the dense phase of the FCC regenerator, being deactivated at oxygen concentrations higher than 1.5%. Nevertheless this deactivation is not permanent and they would be regenerated after reduction with hydrogen at 530 ◦C. The influence of the layered double hydroxides (LDHs) preparation method on the catalyst activity was studied, observing that the activity of the catalyst depends on its chemical composition but it does not depend on the initial LDHs crystallinity, obtaining similar results independently of the synthesis method.A.E. Palomares and C. Franch thank the Spanish Government (projects MAT2009-14528-C02-01 and CONSOLIDER INGENIO 2010) and the European Union (European Community's Seventh Framework Programme FP7/2007-2013 under Grant Agreement No. 226347 Project) for financial support. A. Ribera and G. Abellan acknowledge financial support from the Spanish Ministerio de Ciencia e Innovacion with FEDER co-financing (CTQ-2011-26507) and the Generalitat Valenciana (Prometeo Program).Palomares Gimeno, AE.; Franch Martí, C.; Ribera, A.; Abellán, G. (2012). NOx selective catalytic reduction at high temperatures with mixed oxides derived from layered double hydroxides. Catalysis Today. 191(1):47-51. https://doi.org/10.1016/j.cattod.2012.01.023S4751191

Interception of a corner kick in football: A task analysis

Debido a la inexistencia de estudios previos, la presente investigación tiene como objetivo realizar un análisis de la tarea, que es atrapar un balón procedente de un lanzamiento de córner. Para ello se analizó el rendimiento, el comportamiento motor y los movimientos oculares de jóvenes porteros cuando realizaban esta tarea. Además se compararon las variables en función de los aciertos o fallos durante el blocaje. Los resultados muestran que los fallos en el blocaje se deben a que los porteros iniciaron su carrera demasiado pronto y además utilizaron un patrón inadecuado del movimiento de sus manos y salto. El análisis de los movimientos oculares muestra que el balón es la zona informativa más importante, pero no se obtienen diferencias entre los aciertos y los fallos en el blocajeDue to the inexistence of previous studies, the present research is aimed at performing an analysis of the task of intercepting a ball coming from a corner kick. With that objective in mind, the motor behaviour and eye movements of young goalkeepers were analysed when performing the aforementioned task. Also, variables dependent on the number of right and wrong movements during the interception were compared. Results show that errors in blocking are due to the fact that goalkeepers began their run too early and also used an inadequate pattern of hand movement and jump. The analysis of eye movements shows that the ball is the most important informational zone, but no differences were found between hits and misses in the interception.La presente investigación se llevo a cabo mientras el primer autor disfrutaba de una beca FPU (Formación del Profesorado Universitario) otorgada por el Ministerio de Educación, Cultura y Deporte del Gobierno de Españ

The interception of a corner kick from the contraints-led perspective

El comportamiento motor surge de la continua interacción entre tres limitadores (organismo, entorno y tarea), que nunca actúan de forma aislada. Este artículo estudia su efecto en el rendimiento, comportamiento motor y comportamiento visual de porteros de fútbol durante el lanzamiento de córner. 31 participantes, divididos en tres grupos en función del nivel de juego, intentaron atrapar el balón procedente del lanzamiento de córner en dos situaciones (estática y dinámica), mientras que se registraron sus movimientos oculares. Entre los resultados se observa que los expertos tienen un rendimiento más estable, mientras que los otros grupos rinden peor en la situación más difícil; que los expertos realizan un inicio más tardío de la carrera hacia el balón y un patrón motor más rápido para atraparlo; y que la información contenida en los jugadores implicados no es relevante, ya que los porteros dedican valores cercanos al 0% del tiempo total a su fijaciónMotor behavior arises from the continuous interaction between three constraints (organism, environment and task), which never act in isolation. This paper studies the effect of the constraints on the performance, motor behavior and visual search behavior of soccer goalkeepers during the corner kick. 31 participants, divided into three groups depending on the level of play, tried to catch the ball out of a corner kick in two situations (static and dynamic), while their eye movements were recorded. Among the results it is observed that the experts have a more stable performance, while the other groups perform worse in the most difficult situation; that the experts make a later start of their run up towards the ball and a faster motor pattern to catch it; and that the that the information of the players involved is not relevant, goalkeepers dedicate values close to 0% of their visual total time to themLa presente investigación se llevó a cabo mientras el primer autor y la segunda autora disfrutaban de una beca FPU (Formación del Profesorado Universitario) otorgada por el Ministerio de Educación, Cultura y Deporte del Gobierno de España

Exercise increases the dynamics of diurnal cortisol secretion and executive functionin people wiht MCI

Summary: Regular physical activity is protective against and beneficial for Mild Cognitive Impairment (MCI), dementia, and Alzheimer´s disease. The mechanisms underlying these benefits remain unknown although it has been suggested that exercise-induced changes in the circadian pattern of cortisol secretion may be implicated. Fitness, salivary cortisol levels (0 and 30 mins post awakening, midday, 5pm and 9pm) and cognitive function were determined in a group of amnestic MCI patients (n=39) before and after a three-month exercise program (n=19) or usual care (n=20). At base fitness measures were positively correlated with peak levels of cortisol and a greater fall in cortisol concentration from peak levels to midday. The exercise intervention successfully increased fitness and resulted in a greater fall in cortisol concentration from peak to midday, compared to the control group. The exercise intervention enhanced indices of executive function, although memory, mood, and functionality were not affected

Mobility assessment in people with Alzheimer disease using smartphone sensors

[EN] Background Understanding the functional status of people with Alzheimer Disease (AD), both in a single (ST) and cognitive dual task (DT) activities is essential for identifying signs of early-stage neurodegeneration. This study aims to compare the performance quality of several tasks using sensors embedded in an Android device, among people at different stages of Alzheimer and people without dementia. The secondary aim is to analyze the effect of cognitive task performance on mobility tasks. Methods This is a cross-sectional study including 22 participants in the control group (CG), 18 in the group with mild AD and 22 in the group with moderate AD. They performed two mobility tests, under ST and DT conditions, which were registered using an Android device. Postural control was measured by medial-lateral and anterior-posterior displacements of the COM (MLDisp and APDisp, respectively) and gait, with the vertical and medial-lateral range of the COM (Vrange and MLrange). Further, the sit-to-stand (PStand) and turning and sit power (PTurnSit), the total time required to complete the test and the reaction time were measured. Results There were no differences between the two AD stages either for ST or DT in any of the variables (p > 0.05). Nevertheless, people at both stages showed significantly lower values of PStand and PTurnSit and larger Total time and Reaction time compared to CG (p < 0.05). Further, Vrange is also lower in CDR1G than in CG (p < 0.05). The DT had a significant deleterious effect on MLDisp in all groups (p < 0.05) and on APDisp only in moderate AD for DT. Conclusions Our findings indicate that AD patients present impairments in some key functional abilities, such as gait, turning and sitting, sit to stand, and reaction time, both in mild and moderate AD. Nevertheless, an exclusively cognitive task only influences the postural control in people with AD.This work was funded by the Spanish Government, Secretaria de Estado de Investigacion, Desarrollo e Innovacion, and co-financed by EU FEDER funds (Grant DPI2013-44227-R). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Serra-Añó, P.; Pedrero, J.; Hurtado-Abellán, J.; Inglés, M.; Espí-López, G.; Lopez Pascual, J. (2019). Mobility assessment in people with Alzheimer disease using smartphone sensors. Journal of NeuroEngineering and Rehabilitation. 16(1). https://doi.org/10.1186/s12984-019-0576-yS161Association A. 2017 Alzheimer’s disease facts and figures. Alzheimers Dement. 2017;13(4):325–73.Harrington MG, Chiang J, Pogoda JM, Gomez M, Thomas K, Marion SD, et al. Executive function changes before memory in preclinical Alzheimer’s pathology: a prospective, cross-sectional, case control study. PLoS One. 2013;8(11):e79378.Buckner RL. Memory and executive function in aging and AD: multiple factors that cause decline and reserve factors that compensate. Neuron. 2004;44(1):195–208.Beauchet O, Launay CP, Barden J, Liu-Ambrose T, Chester VL, Szturm T, et al. Association between falls and brain subvolumes: results from a cross-sectional analysis in healthy older adults. Brain Topogr. 2017;30(2):272–80.Yogev-Seligmann G, Hausdorff JM, Giladi N. The role of executive function and attention in gait. Mov Disord Off J Mov Disord Soc. 2008;23(3):329–42.Verghese J, Wang C, Holtzer R, Lipton R, Xue X. Quantitative gait dysfunction and risk of cognitive decline and dementia. J Neurol Neurosurg Psychiatry. 2007;78(9):929–35.Beauchet O, Annweiler C, Callisaya ML, De Cock A-M, Helbostad JL, Kressig RW, et al. Poor gait performance and prediction of dementia: results from a meta-analysis. J Am Med Dir Assoc. 2016;17(6):482–90.Rucco R, Agosti V, Jacini F, Sorrentino P, Varriale P, De Stefano M, et al. Spatio-temporal and kinematic gait analysis in patients with frontotemporal dementia and Alzheimer’s disease through 3D motion capture. Gait Posture. 2017;52:312–7.de Melo Coelho FG, Stella F, de Andrade LP, Barbieri FA, Santos-Galduróz RF, Gobbi S, et al. Gait and risk of falls associated with frontal cognitive functions at different stages of Alzheimer’s disease. Aging Neuropsychol Cogn. 2012;19(5):644–56.Beauchet O, Allali G, Launay C, Herrmann FR, Annweiler C. Gait variability at fast-pace walking speed: a biomarker of mild cognitive impairment? J Nutr Health Aging. 2013;17(3):235–9.Ganz DA, Bao Y, Shekelle PG, Rubenstein LZ. Will my patient fall? JAMA. 2007;297(1):77–86.Egerton T, Danoudis M, Huxham F, Iansek R. Central gait control mechanisms and the stride length - cadence relationship. Gait Posture. 2011;34(2):178–82.Baddeley AD, Baddeley HA, Bucks RS, Wilcock GK. Attentional control in Alzheimer’s disease. Brain. 2001;124(8):1492–508.Dubois B, Feldman HH, Jacova C, DeKosky ST, Barberger-Gateau P, Cummings J, et al. Research criteria for the diagnosis of Alzheimer’s disease: revising the NINCDS–ADRDA criteria. Lancet Neurol. 2007;6(8):734–46.Coubard OA, Ferrufino L, Boura M, Gripon A, Renaud M, Bherer L. Attentional control in normal aging and Alzheimer’s disease. Neuropsychology. 2011;25(3):353–67.Ries JD, Echternach JL, Nof L, Gagnon BM. Test-retest reliability and minimal detectable change scores for the timed “up & go” test, the six-minute walk test, and gait speed in people with Alzheimer disease. Phys Ther. 2009;89(6):569–79.Tamura K, Kocher M, Finer L, Murata N, Stickley C. Reliability of clinically feasible dual-task tests: expanded timed get up and go test as a motor task on young healthy individuals. Gait Posture. 2018;60:22–7.Muir SW, Speechley M, Wells J, Borrie M, Gopaul K, Montero-Odasso M. Gait assessment in mild cognitive impairment and Alzheimer’s disease: the effect of dual-task challenges across the cognitive spectrum. Gait Posture. 2012;35(1):96–100.Morris JC. The clinical dementia rating (CDR): current version and scoring rules. Neurology. 1993;43(11):2412–4.Ansai JH, Andrade LP, Rossi PG, Takahashi AC, Vale FA, Rebelatto JR. Gait, dual task and history of falls in elderly with preserved cognition, mild cognitive impairment, and mild Alzheimer’s disease. Braz J Phys Ther. 2017;21(2):144–51.Herrero MJ, Blanch J, Peri JM, De Pablo J, Pintor L, Bulbena A. A validation study of the hospital anxiety and depression scale (HADS) in a Spanish population. Gen Hosp Psychiatry. 2003;25(4):277–83.Bower ES, Wetherell JL, Merz CC, Petkus AJ, Malcarne VL, Lenze EJ. A new measure of fear of falling: psychometric properties of the fear of falling questionnaire revised (FFQ-R). Int Psychogeriatr. 2015;27(7):1121–33.López-Pascual J, Hurtado AJ, Inglés M, Espí-López G, Serra-Añó P. P 151-reliability of variables measured with an android device during a modified timed up and go test in patients with Alzheimer’s disease. Gait Posture. 2018;65:484.Nishiguchi S, Yamada M, Nagai K, Mori S, Kajiwara Y, Sonoda T, et al. Reliability and validity of gait analysis by android-based smartphone. Telemed J E Health. 2012;18(4):292–6.Zijlstra W, Hof AL. Assessment of spatio-temporal gait parameters from trunk accelerations during human walking. Gait Posture. 2003;18(2):1–10.Ribeiro JG, De Castro JT, Freire JL. Using the FFT-DDI method to measure displacements with piezoelectric, resistive and ICP accelerometers. In: Conference and exposition on structural dynamics. Rio de Janeiro: Citeseer; 2003.Prieto TE, Myklebust JB, Hoffmann RG, Lovett EG, Myklebust BM. Measures of postural steadiness: differences between healthy young and elderly adults. Biomed Eng IEEE Trans On. 1996;43(9):956–66.Esser P, Dawes H, Collett J, Howells K. IMU: inertial sensing of vertical CoM movement. J Biomech. 2009;42(10):1578–81.Gordon KE, Ferris DP, Kuo AD. Metabolic and mechanical energy costs of reducing vertical center of mass movement during gait. Arch Phys Med Rehabil. 2009;90(1):136–44.Gard SA, Miff SC, Kuo AD. Comparison of kinematic and kinetic methods for computing the vertical motion of the body center of mass during walking. Hum Mov Sci. 2004;22(6):597–610.Weinert-Aplin RA, Twiste M, Jarvis HL, Bennett AN, Baker RJ. Medial-lateral centre of mass displacement and base of support are equally good predictors of metabolic cost in amputee walking. Gait Posture. 2017;51:41–6.Chen S-H, Lo O-Y, Kay T, Chou L-S. Concurrent phone texting alters crossing behavior and induces gait imbalance during obstacle crossing. Gait Posture. 2018;62:422–5.Lindemann U, Claus H, Stuber M, Augat P, Muche R, Nikolaus T, et al. Measuring power during the sit-to-stand transfer. Eur J Appl Physiol. 2003;89(5):466–70.Manckoundia P, Mourey F, Pfitzenmeyer P, Papaxanthis C. Comparison of motor strategies in sit-to-stand and back-to-sit motions between healthy and Alzheimer’s disease elderly subjects. Neuroscience. 2006;137(2):385–92.Christ BU, Combrinck MI, Thomas KG. Both reaction time and accuracy measures of Intraindividual variability predict cognitive performance in Alzheimer’s disease. Front Hum Neurosci. 2018;12:124–35.Vienne A, Barrois RP, Buffat S, Ricard D, Vidal P-P. Inertial sensors to assess gait quality in patients with neurological disorders: a systematic review of technical and analytical challenges. Front Psychol. 2017;8:817.Wang W-H, Chung P-C, Yang G-L, Lin C-W, Hsu Y-L, Pai M-C. An inertial sensor based balance and gait analysis system. In: 2015 IEEE International Symposium on Circuits and Systems (ISCAS): Rio de Janeiro: IEEE; 2015. p. 2636–9.Wüest S, Masse F, Aminian K, Gonzenbach R, De Bruin ED. Reliability and validity of the inertial sensor-based timed “up and go” test in individuals affected by stroke. J Rehabil Res Dev. 2016;53(5):599–610.Nguyen H, Lebel K, Boissy P, Bogard S, Goubault E, Duval C. Auto detection and segmentation of daily living activities during a timed up and go task in people with Parkinson’s disease using multiple inertial sensors. J Neuroengineering Rehabil. 2017;14(1):26.Ansai JH, de Andrade LP, Rossi PG, Nakagawa TH, Vale FAC, Rebelatto JR. Differences in timed up and go subtasks between older people with mild cognitive impairment and mild Alzheimer’s disease. Mot Control. 2018;27:1–12.Eggermont LH, Gavett BE, Volkers KM, Blankevoort CG, Scherder EJ, Jefferson AL, et al. Lower-extremity function in cognitively healthy aging, mild cognitive impairment, and Alzheimer’s disease. Arch Phys Med Rehabil. 2010;91(4):584–8.Leandri M, Cammisuli S, Cammarata S, Baratto L, Campbell J, Simonini M, et al. Balance features in Alzheimer’s disease and amnestic mild cognitive impairment. J Alzheimers Dis. 2009;16(1):113–20.Nakamura T, Meguro K, Yamazaki H, Okuzumi H, Tanaka A, Horikawa A, et al. Postural and gait disturbance correlated with decreased frontal cerebral blood flow in Alzheimer disease. Alzheimer Dis Assoc Disord. 1997;11(3):132–9.Cavagna GA, Margaria R. Mechanics of walking. J Appl Physiol. 1966;21(1):271–8.Ganea R, Paraschiv-Ionescu A, Büla C, Rochat S, Aminian K. Multi-parametric evaluation of sit-to-stand and stand-to-sit transitions in elderly people. Med Eng Phys. 2011;33(9):1086–93.Cameron DM, Bohannon RW, Garrett GE, Owen SV, Cameron DA. Physical impairments related to kinetic energy during sit-to-stand and curb-climbing following stroke. Clin Biomech. 2003;18(4):332–40.McGuinness B, Barrett SL, Craig D, Lawson J, Passmore AP. Attention deficits in Alzheimer’s disease and vascular dementia. J Neurol Neurosurg Psychiatry. 2010;81(2):157–9.Phillips M, Rogers P, Haworth J, Bayer A, Tales A. Intra-individual reaction time variability in mild cognitive impairment and Alzheimer’s disease: gender, processing load and speed factors. PLoS One. 2013;8(6):e65712

A high-throughput screening identifies microRNA inhibitors that influence neuronal maintenance and/or response to oxidative stress

Oxidative stress; Small RNA sequencing; NeurodegenerationEstrés oxidativo; Secuenciación de ARN pequeño; NeurodegeneraciónEstrès oxidatiu; Seqüenciació d'ARN petit; NeurodegeneracióSmall non-coding RNAs (sncRNAs), including microRNAs (miRNAs) are important post-transcriptional gene expression regulators relevant in physiological and pathological processes. Here, we combined a high-throughput functional screening (HTFS) platform with a library of antisense oligonucleotides (ASOs) to systematically identify sncRNAs that affect neuronal cell survival in basal conditions and in response to oxidative stress (OS), a major hallmark in neurodegenerative diseases. We considered hits commonly detected by two statistical methods in three biological replicates. Forty-seven ASOs targeting miRNAs (miRNA-ASOs) consistently decreased cell viability under basal conditions. A total of 60 miRNA-ASOs worsened cell viability impairment mediated by OS, with 36.6% commonly affecting cell viability under basal conditions. In addition, 40 miRNA-ASOs significantly protected neuronal cells from OS. In agreement with cell viability impairment, damaging miRNA-ASOs specifically induced increased free radical biogenesis. miRNAs targeted by the detrimental ASOs are enriched in the fraction of miRNAs downregulated by OS, suggesting that the miRNA expression pattern after OS contributes to neuronal damage. The present HTFS highlighted potentially druggable sncRNAs. However, future studies are needed to define the pathways by which the identified ASOs regulate cell survival and OS response and to explore the potential of translating the current findings into clinical applications.This work was supported by the Spanish Ministry of Economy and Competitiveness and FEDER funds (SAF2014-60551-R and SAF2017-88452-R). We acknowledge the support of the Spanish Ministry of Economy, Industry and Competitiveness (MEIC) to the EMBL partnership and the Centro de Excelencia Severo Ochoa 2013-2017 (SEV-2012-0208). We acknowledge the support of the Spanish Ministry of Science Innovation and Universities, Maria Maeztu Unit of Excellence Programme. We thank the staff of the Genomics Unit for the preparation of sRNA libraries and sequencing and the staff of the Biomolecular Screening and Protein Technologies Unit for their help in the setting up the high-throughput screening

Regional asymmetry of metabolic and antioxidant profile in the sciaenid fish shi drum (Umbrina cirrosa) white muscle. Response to starvation and refeeding.

The objective of the present study is to characterize the metabolic and antioxidant profile of white muscle of shi drum in two sites of the body, anterior dorsal (AM) and posterior dorsal (PM) portions. In addition, it will be analyzed the possible effect of starvation and a subsequent refeeding, with two different protocols, pair feeding and ad libitum. Activities of key enzymes of intermediary metabolism and of antioxidant enzymes, as well as lipid peroxidation, as an index of oxidative stress, were evaluated. The results indicate the existence of a regional asymmetry of the metabolic capacities of the white muscle of shi drum, which is likely related to the different contribution to swimming of the body regions examined. Starvation induces a metabolic depression that is more marked in those activities that support burst swimming in PM, while those activities supporting maintenance requirements are conserved. The greatest energy demands during starvation appear to lie in AM, which showed the highest oxidative metabolism rate. The increased use of fatty acids as energy source for AM leads to oxidative stress. A period of more than four weeks of refeeding for full restoration of metabolic capacities in AM is needed, probably related to the higher muscle mass located in this region. On the contrary, all enzyme activities in PM returned to control levels in both refeeding protocols, but pair feeding seems to be advantageous since compensatory growth has been taking place without signs of oxidative stress. This work was addressed to gain knowledge on the physiology of a promising fish species in aquaculture like shi drum. The results displayed here show how the starving and further re-feeding events could generate oxidative stress situations characterized by high lipid peroxidation levels which may influence negatively on the quality of the edible part of the fish. This study opens an interesting field on this fish species which deserves being investigated in the future.Versión del edito