Two-dimensional 1H NMR spectra of ferricytochrome c551 from Pseudomonas aeruginosa

AbstractThe full assignment of 1H NMR signals of heme proton resonances of ferricytochrome c551 from Pseudomonas aeruginosa has been performed by means of 2D NMR experiments. This technique allows the complete and unequivocal assignment of all heme resonances, including methylene resonances of the propionic groups, directly implicated in the pH dependence of the redox properties of cytochrome c551

Determination of Non-Invasive Biomarkers for the Assessment of Fibrosis, Steatosis and Hepatic Iron Overload by MR Image Analysis. A Pilot Study

[EN] The reference diagnostic test of fibrosis, steatosis, and hepatic iron overload is liver biopsy, a clear invasive procedure. The main objective of this work was to propose HSA, or human serum albumin, as a biomarker for the assessment of fibrosis and to study non-invasive biomarkers for the assessment of steatosis and hepatic iron overload by means of an MR image acquisition protocol. It was performed on a set of eight subjects to determine fibrosis, steatosis, and hepatic iron overload with four different MRI sequences. We calibrated longitudinal relaxation times (T1 [ms]) with seven human serum albumin (HSA [%]) phantoms, and we studied the relationship between them as this protein is synthesized by the liver, and its concentration decreases in advanced fibrosis. Steatosis was calculated by means of the fat fraction (FF [%]) between fat and water liver signals in "fat-only images" (the subtraction of in-phase [IP] images and out-of-phase [OOP] images) and in "water-only images" (the addition of IP and OOP images). Liver iron concentration (LIC [mu mol/g]) was obtained by the transverse relaxation time (T2* [ms]) using Gandon's method with multiple echo times (TE) in T2-weighted IP and OOP images. The preliminary results showed that there is an inverse relationship (r = -0.9662) between the T1 relaxation times (ms) and HSA concentrations (%). Steatosis was determined with FF > 6.4% and when the liver signal was greater than the paravertebral muscles signal, and thus, the liver appeared hyperintense in fat-only images. Hepatic iron overload was detected with LIC > 36 mu mol/g, and in these cases, the liver signal was smaller than the paravertebral muscles signal, and thus, the liver behaved as hypointense in IP images.This research was funded by "Conselleria d'Educacio, Investigacio, Cultura i Esport, Generalitat Valenciana" (grants AEST/2019/037 and AEST/2020/029), from the "Agencia Valenciana de la Innovacion, Generalitat Valenciana" (ref. INNCAD00/19/085 and INNCAD/2020/84), and from the "Centro para el Desarrollo Tecnologico Industrial" (Programa Eurostars-2, actuacion Interempresas Internacional), Spanish "Ministerio de Ciencia, Innovacion y Universidades" (ref. CIIP-20192020).Meneses, A.; Santabárbara, JM.; Romero, JA.; Aliaga, R.; Maceira, AM.; Moratal, D. (2021). Determination of Non-Invasive Biomarkers for the Assessment of Fibrosis, Steatosis and Hepatic Iron Overload by MR Image Analysis. A Pilot Study. Diagnostics. 11(7):1-12. https://doi.org/10.3390/diagnostics11071178S11211

End-systole and end-diastole detection in short axis cine MRI using a fully convolutional neural network with dilated convolutions

[EN] The correct assessment and characterization of heart anatomy and functionality is usually done through inspection of magnetic resonance image cine sequences. In the clinical setting it is especially important to determine the state of the left ventricle. This requires the measurement of its volume in the end-diastolic and end-systolic frames within the sequence trough segmentation methods. However, the first step required for this analysis before any segmentation is the detection of the end-systolic and end-diastolic frames within the image acquisition. In this work we present a fully convolutional neural network that makes use of dilated convolutions to encode and process the temporal information of the sequences in contrast to the more widespread use of recurrent networks that are usually employed for problems involving temporal information. We trained the network in two different settings employing different loss functions to train the network: the classical weighted cross-entropy, and the weighted Dice loss. We had access to a database comprising a total of 397 cases. Out of this dataset we used 98 cases as test set to validate our network performance. The final classification on the test set yielded a mean frame distance of 0 for the end-diastolic frame (i.e.: the selected frame was the correct one in all images of the test set) and 1.242 (relative frame distance of 0.036) for the end-systolic frame employing the optimum setting, which involved training the neural network with the Dice loss. Our neural network is capable of classifying each frame and enables the detection of the end-systolic and end-diastolic frames in short axis cine MRI sequences with high accuracy.Funding sources This work was partially supported by the Conselleria d'Innovació, Universitats, Ciència i Societat Digital, Generalitat Valenciana (grants AEST/2020/029 and AEST/2021/050) .Pérez-Pelegrí, M.; Monmeneu, JV.; López-Lereu, MP.; Maceira, AM.; Bodi, V.; Moratal, D. (2022). End-systole and end-diastole detection in short axis cine MRI using a fully convolutional neural network with dilated convolutions. Computerized Medical Imaging and Graphics. 99:1-8. https://doi.org/10.1016/j.compmedimag.2022.102085189

Application of machine learning algorithms in thermal images for an automatic classification of lumbar sympathetic blocks

Purpose There are no previous studies developing machine learning algorithms in the classification of lumbar sympathetic blocks (LSBs) performance using infrared thermography data. The objective was to assess the performance of different machine learning algorithms to classify LSBs carried out in patients diagnosed with lower limbs Complex Regional Pain Syndrome as successful or failed based on the evaluation of thermal predictors. Methods 66 LSBs previously performed and classified by the medical team were evaluated in 24 patients. 11 regions of interest on each plantar foot were selected within the thermal images acquired in the clinical setting. From every region of interest, different thermal predictors were extracted and analysed in three different moments (minutes 4, 5, and 6) along with the baseline time (just after the injection of a local anaesthetic around the sympathetic ganglia). Among them, the thermal variation of the ipsilateral foot and the thermal asymmetry variation between feet at each minute assessed and the starting time for each region of interest, were fed into 4 different machine learning classifiers: an Artificial Neuronal Network, K-Nearest Neighbours, Random Forest, and a Support Vector Machine. Results All classifiers presented an accuracy and specificity higher than 70%, sensitivity higher than 67%, and AUC higher than 0.73, and the Artificial Neuronal Network classifier performed the best with a maximum accuracy of 88%, sensitivity of 100%, specificity of 84% and AUC of 0.92, using 3 predictors. Conclusion These results suggest thermal data retrieved from plantar feet combined with a machine learning-based methodology can be an effective tool to automatically classify LSBs performance

Prognostic value of cardiac magnetic resonance early after ST-segment elevation myocardial infarction in older patients

[EN] Background older patients with ST-segment elevation myocardial infarction (STEMI) represent a very high-risk population. Data on the prognostic value of cardiac magnetic resonance (CMR) in this scenario are scarce. Methods the registry comprised 247 STEMI patients over 70 years of age treated with percutaneous intervention and included in a multicenter registry. Baseline characteristics, echocardiographic parameters and CMR-derived left ventricular ejection fraction (LVEF, %), infarct size (% of left ventricular mass) and microvascular obstruction (MVO, number of segments) were prospectively collected. The additional prognostic power of CMR was assessed using adjusted C-statistic, net reclassification index (NRI) and integrated discrimination improvement index (IDI). Results during a 4.8-year mean follow-up, the number of first major adverse cardiac events (MACE) was 66 (26.7%): 27 all-cause deaths and 39 re-admissions for acute heart failure. Predictors of MACE were GRACE score (HR 1.03 [1.02-1.04], P 155, LVEF = 2 segments. A simple score (0, 1, 2, 3) based on the number of altered factors accurately predicted the MACE per 100 person-years: 0.78, 5.53, 11.51 and 78.79, respectively (P < 0.001). Conclusions CMR data contribute valuable prognostic information in older patients submitted to undergo CMR soon after STEMI. The Older-STEMI-CMR score should be externally validated.This work was supported by Instituto de Salud Carlos III and Fondos Europeos de Desarrollo Regional FEDER (grant numbers PI20/00637, PI15/00531, and CIBERCV16/11/00486,CIBERCV16/11/00420, CIBERCV16/11/00479), apostgraduate contract FI18/00320 to C.R.-N., CM21/00175 to V.M.-G. and JR21/00041 to C.B., Fundacio La MaratoTV3 (grant 20153030-31-32), La Caixa Banking Foundation (HR17-00527), by Conselleria de Educacion-Generalitat Valenciana (PROMETEO/2021/008) and by Sociedad Espanola de Cardiologia (grant SEC/FEC-INV-CLI 21/024). J.G. acknowledges financial support from the Agencia Estatal de Investigacion (grant FJC2020-043981-I/AEI/10.13039/501100011033). D.M. acknowledges financial support from the Conselleria d'Educacio,Investigacio, Cultura i Esport, Generalitat Valenciana (grants AEST/2019/037, AEST/2020/029).Gabaldón-Pérez A; Marcos-Garcés, V.; Gavara-Doñate, J.; López-Lereu, MP.; Monmeneu, JV.; Pérez, N.; Ríos-Navarro, C.... (2022). Prognostic value of cardiac magnetic resonance early after ST-segment elevation myocardial infarction in older patients. Age and Ageing. 51(11):1-11. https://doi.org/10.1093/ageing/afac248111511

The Argentinean Connection (2008)

El título de la presente editorial es cinematográfico, remeda la obra de William Friedkin, The French Connection (1971), y expresivo, en cuanto a que es un indicio de que el presente número de la Revista de Medicina y Cine está básicamente realizado en Argentina, pues argentinos son la mayor parte de los autores de los artículos que recoge