Pénfigo vulgar en un perro

Se describe un caso de pénfigo vulgar en un perro Pastor alemán, macho, de 8 años. El examen físico mostró lesiones eritematosas, vesiculares y ulcerativas en la cavidad oral, en diversas zonas de la piel y en las uniones cutáneomucosas de la nariz, del prepucio y del ano. A la vista del cuadro clínico, del estudio histopatológico y del test de inmunofluorescencia directa se estableció un diagnóstico de pénfigo vulgar. El tratamiento se basó en la administración oral de prednisona, azatioprina, amoxicilina-ácido clavulánico y vitamina E. Al cabo de tres meses las lesiones remitieron completamente. En la actualidad el animal se encuentra clínicamente controlado con prednisona a una dosis de mantenimiento de 0,5 mg/kg/2 días.A case of pemphigus vulgaris is described in an 8 year oId, male German Shepherd. Physical examination revealed erythematous, vesicular and ulcerative lesions in the mouth, in different areas of the skin and in the cutaneous-mucosal junctions of the nose, prepuce and anus. Based upon clinical findings, histopathological study, and dírect immunofluorescent test a diagnosis of pemphigus vulgaris was established. Treatment was based on oral administration of prednisone, azathioprine, amoxycillin-clavulanic acid and vitamin E. Complete remission was observed at three months. Presently the animal is clinically controlled with prednisone at a maintenance dose of 0,5 mg/kg on alternate days

Automatic supervision of gestures to guide novice surgeons during training

The final publication is available at Springer via http://dx.doi.org/10.1007/s00464-013-3285-9Background Virtual surgery simulators enable surgeons to learn by themselves, shortening their learning curves. Virtual simulators offer an objective evaluation of the surgeon’s skills at the end of each training session. The considered evaluation parameters are based on the analysis of the surgeon’s gestures performed throughout the training session. Currently, this information is usually known by surgeons only at the end of the training session, but very limited during the training performance. In this paper, we present a novel method for automatic and interactive evaluation of the surgeon’s skills that is able to supervise inexperienced surgeons during their training session with surgical simulators. Methods The method is based on the assumption that the sequence of gestures carried out by an expert surgeon in the simulator can be translated into a sequence (a character string) that should be reproduced by a novice surgeon during a training session. In this work, a string-matching algorithm has been modified to calculate the alignment and distance between the sequences of both expert and novice during the training performance. Results The results have shown that it is possible to distinguish between different skill levels at all times during the surgical training session. Conclusions The main contribution of this paper is a method where the difference between an expert’s sequence of gestures and a novice’s ongoing sequence is used to guide inexperienced surgeons. This is possible by indicating to novices the gesture corrections to be applied during surgical training as continuous expert supervision would do.Monserrat, C.; Lucas, A.; Hernández Orallo, J.; Rupérez Moreno, MJ. (2014). Automatic supervision of gestures to guide novice surgeons during training. Surgical Endoscopy. 28(4):1360-1370. doi:10.1007/s00464-013-3285-9S13601370284Ericsson KA (ed) (2009) Development of professional expertise: toward measurement of expert performance and design of optimal learning environments. Cambridge University Press, New YorkMcGaghie WC (2008) Research opportunities in simulation-based medical education using deliberate practice. Acad Emerg Med 15:995–1001Ericsson KA (2008) Deliberate practice and acquisition of expert performance: a general overview. Acad Emerg Med 15:988–994Issenberg SB, McGaghie WC, Petrusa ER et al (2005) Features and uses of high-fidelity medical simulations that lead to effective learning: a BEME systematic review. Med Teach 27:10–28Porte MC, Xeoulis G, Reznick RK, Dubrowski A (2007) Verbal feedback from an expert is more effective than self-accessed feedback about motion efficiency in learning new surgical skills. Am J Surg 193:105–110. doi: 10.1016/j.amjsurg.2006.03.016Hall PAV, Dowling GR (1980) Approximate string matching. ACM computing surveys (CSUR) 18(2):381–402. doi: 10.1145/356827.356830Stylopoulos N, Cotin S, Maithel SK et al (2004) Computer-enhanced laparoscopic training system (CELTS): bridging the gap. Surg Endosc 18(5):782–789. doi: 10.3233/978-1-60750-938-7-336Solis J, Oshima N, Ishii H, Matsuoka N et al (2009) Quantitative assessment of the surgical training methods with the suture/ligature training system WKS-2RII. In: IEEE international conference on robotics and automation, 2009 (ICRA ‘09), Kobe, pp 4219–4224. doi: 10.1109/ROBOT.2009.5152314Lin Z et al (2010) Objective evaluation of laparoscopic surgical skills using Waseda bioinstrumentation system WB-3. In: IEEE international conference on robotics and biomimetics (ROBIO), Tianjin, pp 247–252. doi: 10.1109/ROBIO.2010.5723335Chmarra MK, Klein S, Winter JCF, Jansen FW, Dankelman J (2010) Objective classification of residents based on their psychomotor laparoscopic skills. Surg Endosc 24(5):1031–1039. doi: 10.1007/s00464-009-0721-yLin HC, Shafran I, Yuh D, Hager GD (2006) Towards automatic skill evaluation: detection and segmentation of robot-assisted surgical motions. Comput Aided Surg 11(5):220–230. doi: 10.3109/10929080600989189Rosen J, Brown JD, Chang L, Sinanan MN, Hannaford B (2006) Generalized approach for modeling minimally invasive surgery as a stochastic process using a discrete Markov model. IEEE Trans Biomed Eng 53(3):399–413. doi: 10.1109/TBME.2005.869771Lahanas V, Loukas C, Nikiteas N, Dimitroulis D, Georgiou E (2011) Psychomotor skills assessment in laparoscopic surgery using augmented reality scenarios. In: 17th international conference on digital signal processing (DSP), Corfu. doi: 10.1109/ICDSP.2011.6004893Leong JJ et al (2006) HMM assessment of quality of movement trajectory in laparoscopic surgery. In: International conference on medical image computing and computer-assisted intervention (MICCAI’06), pp 752–759. doi: 10.3109/10929080701730979Megali G, Sinigaglia S, Tonet O, Dario P (2006) Modelling and evaluation of surgical performance using Hidden Markov models. IEEE Trans Biomed Eng 53(10):1911–1919. doi: 10.1109/TBME.2006.881784Huang J, Payandeh S, Doris P, Hajshirmohammadi I (2005) Fuzzy classification: towards evaluating performance on a surgical simulator. Stud Health Technol Inform 111:194–200Hajshirmohammadi I, Payandeh S (2007) Fuzzy set theory for performance evaluation in a surgical simulator. Presence 16(6):603–622. doi: 10.1162/pres.16.6.603Ukkonen E (1985) Algorithms for approximate string matching. Inf Control 64(1–3):100–118. doi: 10.1016/S0019-9958(85)80046-2Navarro G (2001) A guided tour to approximate string matching. ACM Comput Surv 33(1):31–88. doi: 10.1145/375360.375365Damerau FJ (1964) A technique for computer detection and correction of spelling errors. Commun ACM 7(3):171–176. doi: 10.1145/363958.363994Bergroth L, Hakonen H, Raita T (2000) A survey of longest common subsequence algorithms. In: Proceedings of the seventh international symposium on string processing information retrieval (SPIRE’00), A Coruña, p 39. doi: 10.1109/SPIRE.2000.878178Zhang Z (2000) A flexible new technique for camera calibration. IEEE Trans Pattern Anal Mach Intell 22(11):1330–1334. doi: 10.1109/34.888718Simbionix™, Lap Mentor™. simbionix.com. http://simbionix.com/simulators/lap-mentor/library-of-modules/basic-skills/ . Accessed 31 Jan 2013Wagner RA, Fischer MJ (1974) Algorithms for approximate string matching. J ACM 21(1):168–173. doi: 10.1016/S0019-9958(85)80046-2Hirschberg DS (1975) A linear space algorithm for computing maximal common subsequences. Commun ACM 18(6):341–343. doi: 10.1145/360825.36086

La competencia social y el desarrollo de comportamientos cívicos: la labor orientadora del profesor

En este artículo se analiza el concepto de competencia social desde una óptica positiva y promotora de una convivencia de calidad, así como estimuladora de la formación socioemocional de los alumnos. En un primer momento se realiza una aproximación histórica al término “competencia social”, describiendo los principales cambios terminológicos y conceptuales experimentados en los últimos años. Una vez establecido el marco, se describe a la escuela como un contexto privilegiado donde tienen lugar gran parte de los aprendizajes sociales y donde se sientan las bases para la posterior integración y participación de los alumnos como ciudadanos que conviven y se relacionan con otros. Dentro de este contexto se ha decidido centrar la atención en la figura del profesor

Estimating the Relative Stiffness between a Hepatic Lesion and the Liver Parenchyma through Biomechanical Simulations of the Breathing Process

[EN] In this paper, a method to in vivo estimate the relative stifness between a hepatic lesion and the liver parenchyma is presented. Tis method is based on the fnite element simulation of the deformation that the liver undergoes during the breathing process. Boundary conditions are obtained through a registration algorithm known as Coherent Point Drif (CPD), which compares the liver form in two phases of the breathing process. Finally, the relative stifness of the tumour with respect to the liver parenchyma is calculated by means of a Genetic Algorithm, which does a blind search of this parameter. Te relative stifness together with the clinical information of the patient can be used to establish the type of hepatic lesion. Te developed methodology was frst applied to a test case, i.e., to a control case where the parameters were known, in order to verify its validity. Afer that, the method was applied to two real cases and low errors were obtained.This work has been funded by the Spanish Ministry of Economy and Competitiveness (MINECO) through research projects DPI2013-40859-R and TIN2014-52033-R, both also supported by European FEDER funds.Martinez-Sanchis, S.; Rupérez Moreno, MJ.; Nadal, E.; Pareja, E.; Brugger, S.; Borzacchiello, D.; López, R.... (2018). Estimating the Relative Stiffness between a Hepatic Lesion and the Liver Parenchyma through Biomechanical Simulations of the Breathing Process. Mathematical Problems in Engineering. 1-10. https://doi.org/10.1155/2018/5317324S110Kmieć, Z. (2001). Introduction — Morphology of the Liver Lobule. Advances in Anatomy Embryology and Cell Biology, 1-6. doi:10.1007/978-3-642-56553-3_1Cequera, A., & García de León Méndez, M. C. (2014). Biomarkers for liver fibrosis: Advances, advantages and disadvantages. Revista de Gastroenterología de México (English Edition), 79(3), 187-199. doi:10.1016/j.rgmxen.2014.07.001Vilar-Gomez, E., & Chalasani, N. (2018). Non-invasive assessment of non-alcoholic fatty liver disease: Clinical prediction rules and blood-based biomarkers. Journal of Hepatology, 68(2), 305-315. doi:10.1016/j.jhep.2017.11.013Giannini, E. G. (2005). Liver enzyme alteration: a guide for clinicians. Canadian Medical Association Journal, 172(3), 367-379. doi:10.1503/cmaj.1040752Oliva, M. R. (2004). Liver cancer imaging: role of CT, MRI, US and PET. Cancer Imaging, 4(Special Issue A), S42-S46. doi:10.1102/1470-7330.2004.0011Mouw, J. K., Yui, Y., Damiano, L., Bainer, R. O., Lakins, J. N., Acerbi, I., … Weaver, V. M. (2014). Tissue mechanics modulate microRNA-dependent PTEN expression to regulate malignant progression. Nature Medicine, 20(4), 360-367. doi:10.1038/nm.3497Paszek, M. J., Zahir, N., Johnson, K. R., Lakins, J. N., Rozenberg, G. I., Gefen, A., … Weaver, V. M. (2005). Tensional homeostasis and the malignant phenotype. Cancer Cell, 8(3), 241-254. doi:10.1016/j.ccr.2005.08.010Kuo, Y.-H., Lu, S.-N., Hung, C.-H., Kee, K.-M., Chen, C.-H., Hu, T.-H., … Wang, J.-H. (2010). Liver stiffness measurement in the risk assessment of hepatocellular carcinoma for patients with chronic hepatitis. Hepatology International, 4(4), 700-706. doi:10.1007/s12072-010-9223-1Heide, R., Strobel, D., Bernatik, T., & Goertz, R. (2010). Characterization of Focal Liver Lesions (FLL) with Acoustic Radiation Force Impulse (ARFI) Elastometry. Ultraschall in der Medizin - European Journal of Ultrasound, 31(04), 405-409. doi:10.1055/s-0029-1245565Frulio, N., Laumonier, H., Carteret, T., Laurent, C., Maire, F., Balabaud, C., … Trillaud, H. (2013). Evaluation of Liver Tumors Using Acoustic Radiation Force Impulse Elastography and Correlation With Histologic Data. Journal of Ultrasound in Medicine, 32(1), 121-130. doi:10.7863/jum.2013.32.1.121Ma, X., Zhan, W., Zhang, B., Wei, B., Wu, X., Zhou, M., … Li, P. (2014). Elastography for the differentiation of benign and malignant liver lesions: a meta-analysis. Tumor Biology, 35(5), 4489-4497. doi:10.1007/s13277-013-1591-4Guo, L.-H., Wang, S.-J., Xu, H.-X., Sun, L.-P., Zhang, Y.-F., Xu, J.-M., … Xu, X.-H. (2015). Differentiation of benign and malignant focal liver lesions: value of virtual touch tissue quantification of acoustic radiation force impulse elastography. Medical Oncology, 32(3). doi:10.1007/s12032-015-0543-9Dietrich, C., Bamber, J., Berzigotti, A., Bota, S., Cantisani, V., Castera, L., … Thiele, M. (2017). EFSUMB Guidelines and Recommendations on the Clinical Use of Liver Ultrasound Elastography, Update 2017 (Long Version). Ultraschall in der Medizin - European Journal of Ultrasound, 38(04), e16-e47. doi:10.1055/s-0043-103952Ferraioli, G., Filice, C., Castera, L., Choi, B. I., Sporea, I., Wilson, S. R., … Kudo, M. (2015). WFUMB Guidelines and Recommendations for Clinical Use of Ultrasound Elastography: Part 3: Liver. Ultrasound in Medicine & Biology, 41(5), 1161-1179. doi:10.1016/j.ultrasmedbio.2015.03.007Sigrist, R. M. S., Liau, J., Kaffas, A. E., Chammas, M. C., & Willmann, J. K. (2017). Ultrasound Elastography: Review of Techniques and Clinical Applications. Theranostics, 7(5), 1303-1329. doi:10.7150/thno.18650Cosgrove, D., Piscaglia, F., Bamber, J., Bojunga, J., Correas, J.-M., Gilja, O., … Dietrich, C. (2013). EFSUMB Guidelines and Recommendations on the Clinical Use of Ultrasound Elastography.Part 2: Clinical Applications. Ultraschall in der Medizin - European Journal of Ultrasound, 34(03), 238-253. doi:10.1055/s-0033-1335375Palmeri, M. L., & Nightingale, K. R. (2011). What challenges must be overcome before ultrasound elasticity imaging is ready for the clinic? Imaging in Medicine, 3(4), 433-444. doi:10.2217/iim.11.41Samir, A. E., Dhyani, M., Vij, A., Bhan, A. K., Halpern, E. F., Méndez-Navarro, J., … Chung, R. T. (2015). Shear-Wave Elastography for the Estimation of Liver Fibrosis in Chronic Liver Disease: Determining Accuracy and Ideal Site for Measurement. Radiology, 274(3), 888-896. doi:10.1148/radiol.14140839Toshima, T., Shirabe, K., Takeishi, K., Motomura, T., Mano, Y., Uchiyama, H., … Maehara, Y. (2011). New method for assessing liver fibrosis based on acoustic radiation force impulse: a special reference to the difference between right and left liver. Journal of Gastroenterology, 46(5), 705-711. doi:10.1007/s00535-010-0365-7Barr, R. G., Ferraioli, G., Palmeri, M. L., Goodman, Z. D., Garcia-Tsao, G., Rubin, J., … Levine, D. (2015). Elastography Assessment of Liver Fibrosis: Society of Radiologists in Ultrasound Consensus Conference Statement. Radiology, 276(3), 845-861. doi:10.1148/radiol.2015150619Venkatesh, S. K., Yin, M., & Ehman, R. L. (2013). Magnetic resonance elastography of liver: Technique, analysis, and clinical applications. Journal of Magnetic Resonance Imaging, 37(3), 544-555. doi:10.1002/jmri.23731Low, G. (2016). General review of magnetic resonance elastography. World Journal of Radiology, 8(1), 59. doi:10.4329/wjr.v8.i1.59Thompson, S. M., Wang, J., Chandan, V. S., Glaser, K. J., Roberts, L. R., Ehman, R. L., & Venkatesh, S. K. (2017). MR elastography of hepatocellular carcinoma: Correlation of tumor stiffness with histopathology features—Preliminary findings. Magnetic Resonance Imaging, 37, 41-45. doi:10.1016/j.mri.2016.11.005Myronenko, A., & Xubo Song. (2010). Point Set Registration: Coherent Point Drift. IEEE Transactions on Pattern Analysis and Machine Intelligence, 32(12), 2262-2275. doi:10.1109/tpami.2010.46Martínez-Martínez, F., Lago, M. A., Rupérez, M. J., & Monserrat, C. (2013). Analysis of several biomechanical models for the simulation of lamb liver behaviour using similarity coefficients from medical image. Computer Methods in Biomechanics and Biomedical Engineering, 16(7), 747-757. doi:10.1080/10255842.2011.637492Untaroiu, C. D., & Lu, Y.-C. (2013). Material characterization of liver parenchyma using specimen-specific finite element models. Journal of the Mechanical Behavior of Biomedical Materials, 26, 11-22. doi:10.1016/j.jmbbm.2013.05.013Large deformation isotropic elasticity – on the correlation of theory and experiment for incompressible rubberlike solids. (1972). Proceedings of the Royal Society of London. A. Mathematical and Physical Sciences, 326(1567), 565-584. doi:10.1098/rspa.1972.0026Chui, C., Kobayashi, E., Chen, X., Hisada, T., & Sakuma, I. (2006). Transversely isotropic properties of porcine liver tissue: experiments and constitutive modelling. Medical & Biological Engineering & Computing, 45(1), 99-106. doi:10.1007/s11517-006-0137-yHostettler, A., George, D., Rémond, Y., Nicolau, S. A., Soler, L., & Marescaux, J. (2010). Bulk modulus and volume variation measurement of the liver and the kidneys in vivo using abdominal kinetics during free breathing. Computer Methods and Programs in Biomedicine, 100(2), 149-157. doi:10.1016/j.cmpb.2010.03.003Chatterjee, S., Laudato, M., & Lynch, L. A. (1996). Genetic algorithms and their statistical applications: an introduction. Computational Statistics & Data Analysis, 22(6), 633-651. doi:10.1016/0167-9473(96)00011-4Martínez-Martínez, F., Rupérez, M. J., Martín-Guerrero, J. D., Monserrat, C., Lago, M. A., Pareja, E., … López-Andújar, R. (2013). Estimation of the elastic parameters of human liver biomechanical models by means of medical images and evolutionary computation. Computer Methods and Programs in Biomedicine, 111(3), 537-549. doi:10.1016/j.cmpb.2013.05.005Lago, M. A., Rupérez, M. J., Martínez-Martínez, F., Monserrat, C., Larra, E., Güell, J. L., & Peris-Martínez, C. (2015). A new methodology for the in vivo estimation of the elastic constants that characterize the patient-specific biomechanical behavior of the human cornea. Journal of Biomechanics, 48(1), 38-43. doi:10.1016/j.jbiomech.2014.11.009Lago, M. A., Rupérez, M. J., Martínez-Martínez, F., Martínez-Sanchis, S., Bakic, P. R., & Monserrat, C. (2015). Methodology based on genetic heuristics for in-vivo characterizing the patient-specific biomechanical behavior of the breast tissues. Expert Systems with Applications, 42(21), 7942-7950. doi:10.1016/j.eswa.2015.05.058Hoyt, K., Castaneda, B., Zhang, M., Nigwekar, P., di Sant’Agnese, P. A., Joseph, J. V., … Parker, K. J. (2008). Tissue elasticity properties as biomarkers for prostate cancer. Cancer Biomarkers, 4(4-5), 213-225. doi:10.3233/cbm-2008-44-505Xu, W., Mezencev, R., Kim, B., Wang, L., McDonald, J., & Sulchek, T. (2012). Cell Stiffness Is a Biomarker of the Metastatic Potential of Ovarian Cancer Cells. PLoS ONE, 7(10), e46609. doi:10.1371/journal.pone.0046609Martinez-Sanchis, S., Rupérez, M. J., Nadal, E., Borzacchiello, D., Monserrat, C., Pareja, E., … López-Andújar, R. (2017). Estimating the Patient-Specific Relative Stiffness Between a Hepatic Lesion and the Liver Parenchyma. Lecture Notes in Computational Vision and Biomechanics, 485-494. doi:10.1007/978-3-319-68195-5_5

A new methodology for the in vivo estimation of the elastic constants that characterize the patient-specific biomechanical behavior of the human cornea

This work presents a methodology for the in vivo characterization of the complete biomechanical behavior of the human cornea of each patient. Specifically, the elastic constants of a hyperelastic, second-order Ogden model were estimated for 24 corneas corresponding to 12 patients. The finite element method was applied to simulate the deformation of human corneas due to non-contact tonometry, and an iterative search controlled by a genetic heuristic was used to estimate the elastic parameters that most closely approximates the simulated deformation to the real one. The results from a synthetic experiment showed that these parameters can be estimated with an error of about 5%. The results of 24 in vivo corneas showed an overlap of about 90% between simulation and real deformed cornea and a modified Hausdorff distance of 25 mu m, which indicates the great accuracy of the proposed methodology. (C) 2014 Elsevier Ltd. All rights reserved.This project has been partially funded by MECD (reference AP2009-2414) and MINECO (INNPACTO, IPT-2012-0495-300000).Lago, MA.; Rupérez Moreno, MJ.; Martínez Martínez, F.; Monserrat Aranda, C.; Larra, E.; Gueell, JL.; Peris-Martinez, C. (2015). A new methodology for the in vivo estimation of the elastic constants that characterize the patient-specific biomechanical behavior of the human cornea. Journal of Biomechanics. 48(1):38-43. https://doi.org/10.1016/j.jbiomech.2014.11.009S384348

Implications of zoonotic and vector-borne parasites to free-roaming cats in central Spain

Cats are definitive hosts and reservoirs for several parasites, some of which are responsible for serious zoonotic diseases. We conducted a case-control study of data from a trap-neuter-return (TNR) programme (years 2014-2017) designed to examine the prevalence of zoonotic parasites in free-roaming cats living in urban areas of central Spain. In the animal population tested (n = 263), we detected a 29.2% prevalence of endoparasites, including high rates of cestodes (12.9%) and Toxocara cati (11.7%). While faecal samples showed no Toxoplasma gondii oocysts, the seroprevalence of T. gondii infection was 24.2%. Antibodies to Leishmania infantum were detected in 4.8% of the animals, though all skin and blood samples analyzed were PCR negative for this parasite. Ectoparasites (ticks and fleas) were found in 4.6% of the cat population, and 10.6% of the cats were detected with Otodectes cynotis. Finally, 6.3% and 7.9% cats tested positive for feline leukaemia virus and feline immunodeficiency virus, respectively. Our study provides useful information for animal-welfare and public-health, as the parasites detected can affect native wild animals through predation, competition and disease transmission. Our detection of zoonotic parasites such as L. infantum, T. gondii, T. cati, Giardia duodenalis and several ectoparasites prompts an urgent need for health control measures in stray cats.S

A finite element-based machine learning approach for modeling the mechanical behavior of the breast tissues under compression in real-time

[EN] This work presents a data-driven method to simulate, in real-time, the biomechanical behavior of the breast tissues in some image-guided interventions such as biopsies or radiotherapy dose delivery as well as to speed up multimodal registration algorithms. Ten real breasts were used for this work. Their deformation due to the displacement of two compression plates was simulated off-line using the finite element (FE) method. Three machine learning models were trained with the data from those simulations. Then, they were used to predict in real-time the deformation of the breast tissues during the compression. The models were a decision tree and two tree-based ensemble methods (extremely randomized trees and random forest). Two different experimental setups were designed to validate and study the performance of these models under different conditions. The mean 3D Euclidean distance between nodes predicted by the models and those extracted from the FE simulations was calculated to assess the performance of the models in the validation set. The experiments proved that extremely randomized trees performed better than the other two models. The mean error committed by the three models in the prediction of the nodal displacements was under 2 man, a threshold usually set for clinical applications. The time needed for breast compression prediction is sufficiently short to allow its use in real-time (< 0.2 s).This work has been funded by the Spanish Ministry of Economy and Competitiveness (MINECO) through research projects TIN2014-52033-R and DPI2013-40859-R with the support of European FEDER funds.Martínez Martínez, F.; Rupérez Moreno, MJ.; Martínez-Sober, M.; Solves Llorens, JA.; Lorente, D.; Serrano-Lopez, A.; Martinez-Sanchis, S.... (2017). A finite element-based machine learning approach for modeling the mechanical behavior of the breast tissues under compression in real-time. Computers in Biology and Medicine. 90:116-124. https://doi.org/10.1016/j.compbiomed.2017.09.019S1161249

Prepubertal Children With Metabolically Healthy Obesity or Overweight Are More Active Than Their Metabolically Unhealthy Peers Irrespective of Weight Status: GENOBOX Study

Background and Aim: The association of a metabolically healthy status with the practice of physical activity (PA) remains unclear. Sedentarism and low PA have been linked to increased cardiometabolic risk. The aim of this study was to evaluate the PA levels in metabolically healthy (MH) or unhealthy (MU) prepubertal children with or without overweight/obesity. Methods: A total 275 children (144 boys) with 9 ± 2 years old were selected for the GENOBOX study. PA times and intensities were evaluated by accelerometry, and anthropometry, blood pressure, and blood biochemical markers were analyzed. Children were considered to have normal weight or obesity, and further classified as MH or MU upon fulfillment of the considered metabolic criteria. Results: Classification resulted in 119 MH children (21% with overweight/obesity, referred to as MHO) and 156 MU children (47% with overweight/obesity, referred to as MUO). Regarding metabolic profile, MHO showed lower blood pressure levels, both systolic and diastolic and biochemical markers levels, such as glucose, Homeostatic Model Assessment of Insulin Resistance, triglycerides and higher HDL-c levels than MUO (P < 0.001). In addition, MHO children spent more time in PA of moderate intensity compared with MUO children. In relation to vigorous PA, MH normal weight (MHN) children showed higher levels than MUO children. Considering sex, boys spent more time engaged in moderate, vigorous, and moderate–vigorous (MV) PA than girls, and the number of boys in the MH group was also higher. Conclusion: Prepubertal MHO children are less sedentary, more active, and have better metabolic profiles than their MUO peers. However, all children, especially girls, should increase their PA engagement, both in terms of time and intensity because PA appears to be beneficial for metabolic health status itself. Copyright © 2022 Llorente-Cantarero, Leis, Rupérez, Anguita-Ruiz, Vázquez-Cobela, Flores-Rojas, González-Gil, Aguilera, Moreno, Gil-Campos and Bueno