Kinematic analysis of a novel 2-d.o.f. orientation device

This paper presents the development of a new parallel robot designed for helping with bone milling surgeries. The robot is a small modular wrist with 2 active degrees of freedom, and it is proposed to be used as an orientation device located at the end of a robotic arm designed for bone milling processes. A generic kinematic geometry is proposed for this device. This first article shows the developments on the workspace optimization and the analysis of the force field required to complete a reconstruction of the inferior jawbone. The singularities of the mechanism are analyzed, and the actuator selection is justified with the torque requirements and the study of the force space. The results obtained by the simulations allow building a first prototype using linear motors. Bone milling experiment video is shown as additional material

Mathematical modeling of food intake and insulin infusion in a patient with type 1 Ddabetes in closed loop

[EN] Diabetes mellitus type 1 is a condition in which the pancreas loses its ability to produce enough insulin, increasing the levels of blood glucose. This work presents the design of a mathematical model of the glucose - insulin dynamics of a type 1 diabetes patient, contemplating the contribution to the concentration of blood glucose by the intake of carbohydrates, fats and proteins. The model also includes the absorption dynamics of 5 insulin types, different administration methods of exogenous insulin, and the variation of insulin sensitivity during the day. The model was integrated into a closed-loop insulin regulation algorithm, in order to evaluate the performance of the model and the efficiency of closed-loop treatments, compared to open-loop therapies. The results show the response of the model to different situations of a real patient, and tests of the controller’s performance.[ES] La diabetes tipo 1 es una afección en la cual el páncreas pierde su capacidad de producir suficiente insulina, incrementando significativamente la concentración de glucosa en la sangre. En el presente trabajo se presenta el diseño de un modelo matemático de las dinámicas glucosa-insulina de un paciente con diabetes tipo 1, el cual contempla el aporte a la concentración de glucosa en la sangre por parte de la ingesta de carbohidratos, grasas y proteínas. El modelo incluye las dinámicas de absorción de 5 tipos de insulina, diferentes métodos de administración de la misma, y la variación de la sensibilidad a la insulina durante el día. Se integró el modelo a un algoritmo de regulación de insulina en lazo cerrado, con el fin de evaluar el desempeño del modelo y la eficacia de los tratamientos en lazo cerrado, en comparación con las terapias en lazo abierto. Los resultados muestran la respuesta del modelo ante distintas situaciones de un paciente real, y pruebas de funcionamiento del controlador.Manrique-Córdoba, J.; Romero-Ante, JD.; Vivas, A.; Vicente, J.; Sabater-Navarro, JM. (2020). Modelado matemático de ingestas de alimento e infusión de insulina en un paciente con diabetes tipo 1 en lazo cerrado. Revista Iberoamericana de Automática e Informática industrial. 17(2):156-168. https://doi.org/10.4995/riai.2019.11161OJS156168172Ackerman, E., Rosevear, J. W., McGuckin, W. F., 1964. A mathematical model of the glucose-tolerance test. Physics in medicine & Biology 9 (2), 203. https://doi.org/10.1088/0031-9155/9/2/307American Diabetes Association, 2017. [Online; accessed October 2018]. URL: http://www.diabetes.org/Apablaza, P., Soto, N., Codner, E., 2017. De la bomba de insulina y el monitoreo continuo de glucosa al páncreas artificial. Revista Médica de Chile,145 (5), 630-640. https://doi.org/10.4067/S0034-98872017000500011Barrio, R., Andia, V., Vazquez, F., Salgado, Y., Valverde, M., Jansa, M., Flores, M., 2012. Guía de educación terapéutica, al inicio de tratamiento con infusión subcutánea continua de insulina (ISCI). PardeDós. URL: https://diabetesmadrid.org/Beneyto, A., Bertachi, A., Bondia, J., Vehi, J., 2018. A new blood glucose control scheme for unannounced exercise in type 1 diabetic subjects. IEEE Transactions on Control Systems Technology, 1-8.Bergenstal, R. M., Garg, S., Weinzimer, S. A., Buckingham, B. A., Bode, B. W., Tamborlane, W. V., Kaufman, F. R., 2016. Safety of a hybrid closed-loop insulin delivery system in patients with type 1 diabetes. Jama 316 (13), 1407- 1408. https://doi.org/10.1001/jama.2016.11708Berger, M., Rodbard, D., 1989. Computer simulation of plasma insulin and glucose dynamics after subcutaneous insulin injection. Diabetes Care 12 (10), 725-736. https://doi.org/10.2337/diacare.12.10.725Binder, C., 1969. Absorption of injected insulin: A clinical-pharmacological study. Acta Pharmacologica et Toxicologica 27 (S2), 1-83. https://doi.org/10.1111/j.1600-0773.1969.tb03069.xBolie, V. W., 1961. Coefficients of normal blood glucose regulation. Journal of Applied Physiology 16 (5), 783-788. https://doi.org/10.1152/jappl.1961.16.5.783Breda, E., Cavaghan, M. K., Toffolo, G., Polonsky, K. S., Cobelli, C., 2001. Oral glucose tolerance test minimal model indexes of β-cell function and insulin sensitivity. Diabetes 50 (1), 150-158. https://doi.org/10.2337/diabetes.50.1.150Breton, M., Farret, A., Bruttomesso, D., Anderson, S., Magni, L., Patek, S., Dalla Man, C., Place, J., Demartini, S., Del Favero, S., 2012. Fully integrated artificial pancreas in type 1 diabetes: modular closed-loop glucose control maintains near normoglycemia. Diabetes 61, 2230-2237. https://doi.org/10.2337/db11-1445Bruttomesso, D., Farret, A., Costa, S., Marescotti, M. C., Vettore, M., Avogaro, A., Tiengo, A., Dalla Man, C., Place, J., Facchinetti, A., 2009. Closed-loop artificial pancreas using subcutaneous glucose sensing and insulin delivery and a model predictive control algorithm: preliminary studies in Padova and Montpellier. Journal of Diabetes Science and Technology 3, 1014-1021. https://doi.org/10.1177/193229680900300504Clarke, W. L., Anderson, S., Breton, M., Patek, S., Kashmer, L., Kovatchev, B., 2009. Closed-loop artificial pancreas using subcutaneous glucose sensing and insulin delivery and a model predictive control algorithm: the Virginia experience. Journal of Diabetes Science and Technology 3, 1031-1038. https://doi.org/10.1177/193229680900300506Clemens, A., Chang, P., Myers, R., 1977. The development of biostator, a glucose controlled insulin infusion system (GCIIS). Hormone and metabolic research 7, 23-33.Cobelli, C., Nucci, G., Del Prato, S., 1999. A physiological simulation model of the glucose-insulin system. Vol. 2.Colino, E., 2018. Fundación para la Diabetes. [Online; October 2018]. URL: http://www.fundaciondiabetes.org/Craig, T. P., 2010. Dietary Carnitine Supplementation as a potential modulator of insulin sensitivity. Master's Thesis, University of Stirling. URL: https://dspace.stir.ac.uk/Dalla Man, C., Breton, M. D., Cobelli, C., 2009. Physical activity into the meal glucose-insulin model of type 1 diabetes: in silico studies 3, 56-67. https://doi.org/10.1177/193229680900300107Dalla Man, C., Camilleri, M., Cobelli, C., 2006. A system model of oral glucose absorption: validation on gold standard data. IEEE Transactions on Biomedical Engineering 53 (12), 2472-2478. https://doi.org/10.1109/TBME.2006.883792Dalla Man, C., Micheletto, F., Lv, D., Breton, M., Kovatchev, B., Cobelli, C., 2014. The uva/padova type 1 diabetes simulator: new features. Journal of Diabetes Science and Technology 8 (1), 26-34. https://doi.org/10.1177/1932296813514502Dalla Man, C., Raimondo, D. M., Rizza, R. A., Cobelli, C., 2007a. GIM, simulation software of meal glucose insulin model. Journal of Diabetes Science and Technology 1, 323-330. https://doi.org/10.1177/193229680700100303Dalla Man, C., Rizza, R. A., Cobelli, C., 2007b. Meal simulation model of the glucose-insulin system. IEEE Transactions on Biomedical Engineering 54 (10), 1740-1749. https://doi.org/10.1109/TBME.2007.893506Haidar, A., 2016. The artificial pancreas: How close-loop control is revolutionizing diabetes. IEEE Condtrol Systems 36 (5), 28-47. https://doi.org/10.1109/MCS.2016.2584318International Diabetes Federation, 2017. IDF diabetes atlas, 8th Edition. URL: http://www.diabetesatlas.org/IRICOM, 2018. Sociedad Española de Diabetes. [Online; October 2018]. URL: http://www.sediabetes.org/Kadish, A. H., 1963. Automation control of blood sugar a servomechanism for glucose monitoring and control. ASAIO Journal 9 (1), 363-367.Manrique, J., Romero, J. D., Sabater, J. M., Vivas, O. A., Vicente, J. M., 2018. Simulador de paciente T1D en tiempo real. Actas de las XXXIX Jornadas de Automática, Badajoz, 64-71. 'Mauseth, R., Hirsch, I. B., Bollyky, J., Kircher, R., Matheson, D., Sanda, S., Greenbaum, C., 2013. Use of a "fuzzy logic" controller in a closed-loop artificial pancreas. Diabetes Technology & Therapeutics 15 (8), 628-633. https://doi.org/10.1089/dia.2013.0036Murillo, M. D., Fernandez, F., Tuneu, L., 2004. Guía de seguimiento farmacoterapéutico sobre diabetes. Grupo de Investigación en Atención Farmacéutica (GIAF). URL: http://www.ugr.es/National Center for Biotechnology Information, 2018. Insulin aspart. Pub Chem Compound Database, [Online; October 2018]. URL: https://pubchem.ncbi.nlm.nih.gov/compound/16132418Nimri, R., Atlas, E., Ajzensztejn, M., Miller, S., Oron, T., Phillip, M., 2012. Feasibility study of automated overnight closed-loop glucose control under md-logic artificial pancreas in patients with type 1 diabetes: the dream project. Diabetes Technology & Therapeutics 14 (8), 728-735. https://doi.org/10.1089/dia.2012.0004Nucci, G., Cobelli, C., 2000. Models of subcutaneous insulin kinetics. a critical review. Computer Methods and Programs in Biomedicine 62 (3), 249-257. https://doi.org/10.1016/S0169-2607(00)00071-7OpenAPS Community, 2015. Openaps. OpenAPS.org, [Online; October 2018]. URL: https://openaps.org/Renard, E., Place, J., Cantwell, M., Chevassus, H., Palerm, C. C., 2010. Closedloop insulin delivery using a subcutaneous glucose sensor and intraperitoneal insulin delivery: feasibility study testing a new model for the artificial pancreas. Diabetes Care 33 (1), 121-127. https://doi.org/10.2337/dc09-1080Segre, G., Turco, G., Vercellone, G., 1973. Modeling blood glucose and insulin kinetics in normal, diabetic and obese subjects. Diabetes 22 (2), 94-103. https://doi.org/10.2337/diab.22.2.94Steil, G. M., Palerm, C. C., Kurtz, N., Voskanyan, G., Roy, A., Paz, S., Kandeel, F. R., 2011. The effect of insulin feedback on closed loop glucose control. The Journal of Clinical Endocrinology & Metabolism 96 (5), 1402-1408. https://doi.org/10.1210/jc.2010-2578Toffolo, G., Bergman, R. N., Finegood, D. T., Bowden, C. R., Cobelli, C., 1980. Quantitative estimation of beta cell sensitivity to glucose in the intact organism: a minimal model of insulin kinetics in the dog. Diabetes 29 (12), 979-990. https://doi.org/10.2337/diab.29.12.979Trajanoski, Z., Wach, P., Kotanko, P., Ott, A., Skraba, F., 1993. Pharmacokinetic model for the absorption of subcutaneously injected soluble insulin and monomeric insulin-analogues. Biomedizinische Technik Biomedical Engineering 38 (9), 224-231. https://doi.org/10.1515/bmte.1993.38.9.224Turksoy, K., Cinar, A., 2014. Adaptive control of artificial pancreas systems-a review. Journal of Healthcare Engineering 5 (1), 1-22. https://doi.org/10.1260/2040-2295.5.1.1Weinzimer, S. A., Sherr, J. L., Cengiz, E., Kim, G., Ruiz, J. L., Carria, L., Voskanyan, G., Roy, A., Tamborlane, W. V., 2012. Effect of pramlintide on prandial glycemic excursions during closed-loop control in adolescents and young adults with type 1 diabetes. Diabetes Care. URL: http://care.diabetesjournals.org https://doi.org/10.2337/dc12-0330Yoldi, C., Mayo 2018. Las grasas y las proteínas también cuentan. Guía Diabetes tipo 1, [Online; October 2018]. URL: https://www.diabetes-cidi.org

Magnetic resonance microscopy and correlative histopathology of the infarcted heart

Altres ajuts:The present study was supported by the EU Joint Programming Initiative 'A Healthy Diet for a Healthy Life' (JPI HDHL INTIMIC-085), Generalitat Valenciana (GV/2018/116), INCLIVA and Universitat de Valencia (program VLC-BIOCLINIC 20-nanomIRM-2016A).Delayed enhancement cardiovascular magnetic resonance (MR) is the gold-standard for non-invasive assessment after myocardial infarction (MI). MR microscopy (MRM) provides a level of detail comparable to the macro objective of light microscopy. We used MRM and correlative histopathology to identify infarct and remote tissue in contrast agent-free multi-sequence MRM in swine MI hearts. One control group (n = 3 swine) and two experimental MI groups were formed: 90 min of ischemia followed by 1 week (acute MI = 6 swine) or 1 month (chronic MI = 5 swine) reperfusion. Representative samples of each heart were analysed by contrast agent-free multi-sequence (T1-weighting, T2-weighting, T2*-weighting, T2-mapping, and T2*-mapping). MRM was performed in a 14-Tesla vertical axis imager (Bruker-AVANCE 600 system). Images from MRM and the corresponding histopathological stained samples revealed differences in signal intensities between infarct and remote areas in both MI groups (p-value < 0.001). The multivariable models allowed us to precisely classify regions of interest (acute MI: specificity 92% and sensitivity 80%; chronic MI: specificity 100% and sensitivity 98%). Probabilistic maps based on MRM images clearly delineated the infarcted regions. As a proof of concept, these results illustrate the potential of MRM with correlative histopathology as a platform for exploring novel contrast agent-free MR biomarkers after MI

The Spanish Pancreatic Club recommendations for the diagnosis and treatment of chronic pancreatitis: Part 1 (diagnosis)

Chronic pancreatitis (CP) is a relatively uncommon, complex and heterogeneous disease. The absence of a gold standard applicable to the initial phases of CP makes its early diagnosis difficult. Some of its complications, particularly chronic pain, can be difficult to manage. There is much variability in the diagnosis and treatment of CP and its complications amongst centers and professionals. The Spanish Pancreatic Club has developed a consensus on the management of CP. Two coordinators chose a multidisciplinary panel of 24 experts on this disease. A list of questions was drafted, and two experts reviewed each question. Then, a draft was produced and shared with the entire panel of experts and discussed in a face-to-fac

Seguimiento de las guías españolas para el manejo del asma por el médico de atención primaria: un estudio observacional ambispectivo

Objetivo Evaluar el grado de seguimiento de las recomendaciones de las versiones de la Guía española para el manejo del asma (GEMA 2009 y 2015) y su repercusión en el control de la enfermedad. Material y métodos Estudio observacional y ambispectivo realizado entre septiembre del 2015 y abril del 2016, en el que participaron 314 médicos de atención primaria y 2.864 pacientes. Resultados Utilizando datos retrospectivos, 81 de los 314 médicos (25, 8% [IC del 95%, 21, 3 a 30, 9]) comunicaron seguir las recomendaciones de la GEMA 2009. Al inicio del estudio, 88 de los 314 médicos (28, 0% [IC del 95%, 23, 4 a 33, 2]) seguían las recomendaciones de la GEMA 2015. El tener un asma mal controlada (OR 0, 19, IC del 95%, 0, 13 a 0, 28) y presentar un asma persistente grave al inicio del estudio (OR 0, 20, IC del 95%, 0, 12 a 0, 34) se asociaron negativamente con tener un asma bien controlada al final del seguimiento. Por el contrario, el seguimiento de las recomendaciones de la GEMA 2015 se asoció de manera positiva con una mayor posibilidad de que el paciente tuviera un asma bien controlada al final del periodo de seguimiento (OR 1, 70, IC del 95%, 1, 40 a 2, 06). Conclusiones El escaso seguimiento de las guías clínicas para el manejo del asma constituye un problema común entre los médicos de atención primaria. Un seguimiento de estas guías se asocia con un control mejor del asma. Existe la necesidad de actuaciones que puedan mejorar el seguimiento por parte de los médicos de atención primaria de las guías para el manejo del asma. Objective: To assess the degree of compliance with the recommendations of the 2009 and 2015 versions of the Spanish guidelines for managing asthma (Guía Española para el Manejo del Asma [GEMA]) and the effect of this compliance on controlling the disease. Material and methods: We conducted an observational ambispective study between September 2015 and April 2016 in which 314 primary care physicians and 2864 patients participated. Results: Using retrospective data, we found that 81 of the 314 physicians (25.8%; 95% CI 21.3–30.9) stated that they complied with the GEMA2009 recommendations. At the start of the study, 88 of the 314 physicians (28.0%; 95% CI 23.4–33.2) complied with the GEMA2015 recommendations. Poorly controlled asthma (OR, 0.19; 95% CI 0.13–0.28) and persistent severe asthma at the start of the study (OR, 0.20; 95% CI 0.12–0.34) were negatively associated with having well-controlled asthma by the end of the follow-up. In contrast, compliance with the GEMA2015 recommendations was positively associated with a greater likelihood that the patient would have well-controlled asthma by the end of the follow-up (OR, 1.70; 95% CI 1.40–2.06). Conclusions: Low compliance with the clinical guidelines for managing asthma is a common problem among primary care physicians. Compliance with these guidelines is associated with better asthma control. Actions need to be taken to improve primary care physician compliance with the asthma management guidelines

Search for the Zγ decay mode of new high-mass resonances in pp collisions at √s = 13 TeV with the ATLAS detector

This letter presents a search for narrow, high-mass resonances in the Zγ final state with the Z boson decaying into a pair of electrons or muons. The √s = 13 TeV pp collision data were recorded by the ATLAS detector at the CERN Large Hadron Collider and have an integrated luminosity of 140 fb−1. The data are found to be in agreement with the Standard Model background expectation. Upper limits are set on the resonance production cross section times the decay branching ratio into Zγ. For spin-0 resonances produced via gluon–gluon fusion, the observed limits at 95% confidence level vary between 65.5 fb and 0.6 fb, while for spin-2 resonances produced via gluon–gluon fusion (or quark–antiquark initial states) limits vary between 77.4 (76.1) fb and 0.6 (0.5) fb, for the mass range from 220 GeV to 3400 GeV

Search for lepton-favour violation in high-mass dilepton final states using 139 fb−1 of pp collisions at √s = 13 TeV with the ATLAS detector

A search is performed for a heavy particle decaying into different-flavour, dilepton final states, using 139 fb−1 of proton-proton collision data at √s = 13 TeV collected in 2015–2018 by the ATLAS detector at the Large Hadron Collider. Final states with electrons, muons and hadronically decaying tau leptons are considered (eμ, eτ or μτ). No significant excess over the Standard Model predictions is observed. Upper limits on the production cross-section are set as a function of the mass of a Z′ boson, a supersymmetric τ-sneutrino, and a quantum black-hole. The observed 95% CL lower mass limits obtained on a typical benchmark model Z′ boson are 5.0 TeV (eμ), 4.0 TeV (eτ), and 3.9 TeV (μτ), respectively

Search for heavy Higgs bosons with flavour-violating couplings in multi-lepton plus b-jets final states in pp collisions at 13 TeV with the ATLAS detector

A search for new heavy scalars with flavour-violating decays in final states with multiple leptons and b-tagged jets is presented. The results are interpreted in terms of a general two-Higgs-doublet model involving an additional scalar with couplings to the top-quark and the three up-type quarks (ρtt, ρtc, and ρtu). The targeted signals lead to final states with either a same-sign top-quark pair, three top-quarks, or four top-quarks. The search is based on a data sample of proton-proton collisions at √s = 13 TeV recorded with the ATLAS detector during Run 2 of the Large Hadron Collider, corresponding to an integrated luminosity of 139 fb−1. Events are categorised depending on the multiplicity of light charged leptons (electrons or muons), total lepton charge, and a deep-neural-network output to enhance the purity of each of the signals. Masses of an additional scalar boson mH between 200 − 630 GeV with couplings ρtt = 0.4, ρtc = 0.2, and ρtu = 0.2 are excluded at 95% confidence level. Additional interpretations are provided in models of R-parity violating supersymmetry, motivated by the recent flavour and (g − 2)μ anomalies

Search for a new heavy scalar particle decaying into a Higgs boson and a new scalar singlet in final states with one or two light leptons and a pair of τ-leptons with the ATLAS detector

A search for a new heavy scalar particle X decaying into a Standard Model (SM) Higgs boson and a new singlet scalar particle S is presented. The search uses a proton-proton (pp) collision data sample with an integrated luminosity of 140 fb−1 recorded at a centre-of-mass energy of s√ = 13 TeV with the ATLAS detector at the Large Hadron Collider. The most sensitive mass parameter space is explored in X mass ranging from 500 to 1500 GeV, with the corresponding S mass in the range 200–500 GeV. The search selects events with two hadronically decaying τ-lepton candidates from H → τ+τ− decays and one or two light leptons (ℓ = e, μ) from S → VV (V = W, Z) decays while the remaining V boson decays hadronically or to neutrinos. A multivariate discriminant based on event kinematics is used to separate the signal from the background. No excess is observed beyond the expected SM background and 95% confidence level upper limits between 72 fb and 542 fb are derived on the cross-section σ(pp → X → SH) assuming the same SM-Higgs boson-like decay branching ratios for the S → VV decay. Upper limits on the visible cross-sections σ(pp → X → SH → WWττ) and σ(pp → X → SH → ZZττ) are also set in the ranges 3–26 fb and 6–33 fb, respectively