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To evaluate prospectively the feasibility of magnetic resonance neurography (MRN) in identifying the anatomical characteristics of thenar muscular branch (TMB) of the median nerve, also known as the “million dollar nerve,” in patients and controls. Thirteen patients affected by carpal tunnel syndrome (CTS) and four healthy controls had their hands scanned on a 3-T MR imaging scanner for TMB visualization. Median nerve anatomical variations were classified into four groups according to Poisel’s classification system modified by Lanz. TMB signal intensity and diameter were assessed for the diagnosis of neuropathy. TMB was successfully identified in all patients and subjects by using MRN. The most suitable pulse sequences to identify and measure nerve diameter were 3D DW-PSIF and T2-FS-TSE. The axial oblique and sagittal oblique planes are complementary in demonstrating its entire course. TMB had mostly an extraligamentous course with radial side origin (93.8%, each). All patients experienced increased T2 signal intensity (p < 0.001) and thickened nerves. Mean TMB diameters were 1.27 ± 0.21 mm (range, 1.02–1.74 mm) and 0.87 ± 0.16 mm (0.73–1.08 mm) (p = 0.008) in the patient and control groups, respectively. MRN is a reliable imaging technique for identification and anatomical characterization of TMB in patients affected by CTS. This innovative imaging workup may therefore be included in the preoperative evaluation of patients scheduled for carpal tunnel release, especially in CTS with TMB involvement or even in isolated TMB neuropathy. • Magnetic resonance neurography allows precise visualization of the thenar muscular branch of the median nerve. • Thenar muscular branch anatomical variations can be correctly identified. • Preoperative scanning can contribute to reducing the risk of iatrogenic injuries during carpal tunnel release, especially in carpal tunnel syndrome with thenar muscular branch involvement or even in isolated thenar muscular branch neuropathy.

Chikungunya fever is an arbovirus infection transmitted by the same mosquito vector of dengue and Zika virus. Besides high fever, common clinical symptoms include articular pain and general malaise. Neurological involvement is unusual, but some patients may develop peripheral and central nervous system involvement, including meningoencephalitis, myelitis, Guillain-Barre syndrome, and acute disseminated encephalomyelitis. We present three cases of Chikungunya fever complicated with extensive myelitis. The spinal cord magnetic resonance imaging (MRI) pattern is characterized by multiple dotted-like and longitudinal hyperintense lesions, with contrast enhancement, mostly distributed in the peripheral regions of the spinal cord. It seems that these lesions are mostly located in the perivascular spaces (PVS), related or not to virus attack. Involvement of brain PVS can also be demonstrated, as shown in two of the cases described. Considering the MRI pattern, extensive spinal cord lesion should include Chikungunya as a differential diagnosis, especially during an outbreak.

The complete features of the neurological complications of coronavirus disease 2019 (COVID-19) still need to be elucidated, including associated cranial nerve involvement. In the present study we describe cranial nerve lesions seen in magnetic resonance imaging (MRI) of six cases of confirmed COVID-19, involving the olfactory bulb, optic nerve, abducens nerve, and facial nerve. Cranial nerve involvement was associated with COVID-19, but whether by direct viral invasion or autoimmunity needs to be clarified. The development of neurological symptoms after initial respiratory symptoms and the absence of the virus in the cerebrospinal fluid (CSF) suggest the possibility of autoimmunity.

"Future Ready" es un marco desarrollado por WSP para ayudar a nuestros diseños en este mundo cambiante. "Future Ready" prepara nuestros proyectos para los nuevos retos globales, involucrando a los clientes e inspirando diseños para el futuro. Al comprender las tendencias y tecnologías futuras, puede mejorar los resultados de los proyectos a través de un buen diseño conceptual. Presentamos tres casos de estudio para explicar cómo consideramos las tendencias futuras, el proceso seguido y los beneficios del enfoque de "Future Ready". El proyecto del puente de Waterloo respondió a las tendencias de la tecnología ajustando el alcance del proyecto para probar técnicas avanzadas de monitorización por satélite aplicadas a los movimientos del puente. A la luz de las tendencias para un transporte saludable, el diseño conceptual de la renovación del viaducto de Bromley Heath mejoró el uso de una estructura existente para usuarios no motorizados. La solución desarrollada para el paso elevado de Hammersmith tuvo en cuenta las tendencias en materia de recursos y los nuevos criterios de compatibilidad al utilizar hormigón de ultra alto rendimiento.

In many real classification problems a monotone relation between some predictors and the classes may be assumed when higher (or lower) values of those predictors are related to higher levels of the response. In this paper, we propose new boosting algorithms, based on LogitBoost, that incorporate this isotonicity information, yielding more accurate and easily interpretable rules. These algorithms are based on theoretical developments that consider isotonic regression. We show the good performance of these procedures not only on simulations, but also on real data sets coming from two very different contexts, namely cancer diagnostic and failure of induction motors.

Background: The genetic predisposition to multiple sclerosis (MS) is associated with HLA alleles, especially HLA-DRB1*15:01. Objective: To identify associations between findings in magnetic resonance imaging (MRI) and genetic features in a Brazilian cohort of patients with MS. Methods: We retrospectively studied data from 95 consecutive patients with MS. Two independent observers who were blinded to the clinical data identified black holes and enhanced lesions on T1 MRI sequences, and counted and measured contrast-enhanced lesions on T2 and Flair (fluid attenuation inversion recovery) sequences. Cases were classified according to lesion size, number, and volume. The HLA-DRB1, HLA-DQB1, and HLA-DQA1 alleles, and the rs4774, rs3087456, rs6897932, rs731236, and rs1033182 single nucleotide polymorphisms were identified by polymerase chain reaction amplification with sequence-specific primers using the One Lambda Inc. Kit, Canoga Park, CA, USA. Results: Patients with the HLA-DQA1*04:01 allele had lesion load (adjusted for age, sex, and MS duration) above median compared with patients with other HLA-DQA1 alleles (p=0.02). There were no differences among all the other HLA alleles and single nucleotide polymorphisms and lesion load. Conclusions: The correlation of the HLA-DQA1*04:01 allele with a higher lesion load on T2/Flair MRI sequences suggests that the presence of this allele is associated with the risk of greater MS severity. RESUMO Antecedentes: A predisposição genética para a esclerose múltipla (EM) está associada a alelos HLA, principalmente o HLA-DRB1*15:01. Objetivo: Identificar associações entre lesões na ressonância magnética e características genéticas em uma coorte brasileira de pacientes com EM. Métodos: Estudamos retrospectivamente os dados de 95 pacientes consecutivos com EM. Dois observadores independentes que desconheciam os dados clínicos identificaram “black holes” e lesões realçadas pelo contraste nas sequências de ressonância magnética T1 e contaram e mediram as lesões nas sequências T2 e FLAIR (fluid attenuated inversion recovery). Os casos foram classificados de acordo com tamanho, número e volume da lesão. Os alelos HLA-DRB1, HLA-DQB1 e HLA-DQA1 e os polimorfismos de nucleotídeo único rs4774, rs3087456, rs6897932, rs731236 e rs1033182 foram identificados por amplificação de reação em cadeia da polimerase com iniciadores específicos de sequência usando o kit One Lambda Inc., Canoga Park, CA, EUA. Resultados: Os pacientes com alelo HLA-DQA1*04:01 apresentaram carga de lesão (ajustada para idade, sexo e duração da EM) acima da mediana em comparação com outros pacientes com demais alelos HLA-DQA1 (p=0,02). Não houve diferenças entre todos os outros alelos HLA e polimorfismos de nucleotídeo único e carga lesional. Conclusões: A correlação do alelo HLA-DQA1*04:01 com maior carga de lesão nas sequências de RM em T2 sugere que a presença desse alelo pode estar associada ao risco de maior gravidade da EM.

This paper analyses COVID-19 patients’ dynamics during the first wave in the region of Castilla y León (Spain) with around 2.4 million inhabitants using multi-state competing risk survival models. From the date registered as the start of the clinical process, it is assumed that a patient can progress through three intermediate states until reaching an absorbing state of recovery or death. Demographic characteristics, epidemiological factors such as the time of infection and previous vaccinations, clinical history, complications during the course of the disease and drug therapy for hospitalised patients are considered as candidate predictors. Regarding risk factors associated with mortality and severity, consistent results with many other studies have been found, such as older age, being male, and chronic diseases. Specifically, the hospitalisation (death) rate for those over 69 is 27.2% (19.8%) versus 5.3% (0.7%) for those under 70, and for males is 14.5%(7%) versus 8.3%(4.6%)for females. Among patients with chronic diseases the highest rates of hospitalisation are 26.1% for diabetes and 26.3% for kidney disease, while the highest death rate is 21.9% for cerebrovascular disease. Moreover, specific predictors for different transitions are given, and estimates of the probability of recovery and death for each patient are provided by the model. Some interesting results obtained are that for patients infected at the end of the period the hazard of transition from hospitalisation to ICU is significatively lower (p < 0.001) and the hazard of transition from hospitalisation to recovery is higher (p < 0.001). For patients previously vaccinated against pneumococcus the hazard of transition to recovery is higher (p < 0.001). Finally, internal validation and calibration of the model are also performed.

Background: Recent studies have demonstrated that women with early stage ER-positive (ER+) and HER2-negative (HER2-) breast cancer have a persistent risk of recurrence and cancer related death up to 20 years post diagnosis, highlighting the chronic nature of ER+ breast cancer and critical need to identify tumor characteristics that are more predictive of risk of recurrence than standard clinical covariates. However, progress in delineating the dynamics of breast cancer relapse and biomarkers of late recurrence has been hindered by the lack of large cohorts with long-term clinical follow-up and molecular information. Methods: We report the results of a cohort of 3,240 breast cancer patients from the United Kingdom and Canada with 20 years of follow-up (median 9.75 years), including 1,980 with accompanying molecular data from the primary breast tumor. Information for each patient on loco-regional recurrence (LR), distant recurrence (DR), and site(s) of metastases was collected. We developed a non-homogenous Markov chain model that accounted for different clinical endpoints and timescales, as well as competing risks of mortality and the distinct baseline hazards that characterize different molecular subgroups. This approach enabled robust analysis of the spatio-temporal dynamics of breast cancer recurrence across the clinical subgroups, PAM50 subgroups and the integrative clusters, while also enabling individual risk of relapse predictions. Results: We employed our multistate model to compute the probability of experiencing a LR or DR, as well as the baseline transition probabilities from surgery, LR or DR at various time intervals for average individuals in each of the clinical/molecular subgroups. These analyses reveal four late-recurring ER+ (predominantly HER2-) subgroups, together accounting for 26% of all ER+ tumors, with high (median 42-55%) risk of recurrence up to 20 years post-diagnosis. Each of these four subgroups maps to one of the Integrative Clusters, defined based on genomic copy number alterations and gene expression, and is enriched for a characteristic copy number amplification events: 11q13 (CCND1, RSF1), 8p12 (FGFR1, ZNF703), 17q23 (RPS6KB1) and 8q24 (MYC). These four molecular subgroups are superior in predicting late DR than standard clinical variables. Conclusions: A detailed understanding of the rates and routes of metastasis and their variability across the distinct molecular subtypes is essential for devising personalized approaches to breast cancer care. We describe a molecularly characterized breast cancer cohort with long-term clinical follow-up and a statistical modeling framework, enabling delineation of the dynamics of breast cancer recurrence at unprecedented resolution. These analyses reveal four late recurring ER+ subgroups and accompanying biomarkers that collectively define the quarter of ER+ cases at highest risk of recurrence. Our findings highlight opportunities for improved patient stratification and biomarker-driven clinical trials directed at the subset of breast cancer patients with persistent risk of recurrence. Citation Format: Curtis C, Rueda OM, Sammut S-J, Chin S-F, Caswell-Jin JL, Seoane JA, Callari M, Batra R, Pereira B, Bruna A, Ali HR, Provenzano E, Liu B, Parisien M, Gillett C, McKinney S, Green A, Murphy L, Purushotham A, Ellis I, Pharoah P, Rueda C, Aparicio S, Caldas C. Dynamics of breast cancer relapse reveal molecularly defined late recurring ER-positive subgroups: Results from the METABRIC study [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr GS3-06.

The Hodgkin-Huxley model, decades after its first presentation, is still a reference model in neuroscience as it has successfully reproduced the electrophysiological activity of many organisms. The primary signal in the model represents the membrane potential of a neuron. A parametric and simple representation of this signal is presented in this paper.The new proposal is an adapted Frequency Modulated Möbius multicomponent model defined as a flexible decomposition in waves that describe the signal morphology. A specific feature of the new model is that the parameters are subject to interpretable restrictions.A broad simulation experiment is conducted to show the new model accurately represents the simulated Hodgkin-Huxley signal. Moreover, the model potential to predict the neuron’s relevant characteristics, described with parameters of the Hodgkin Huxley model, is shown using different Machine Learning methods. The proposed model is also validated with real data from Squid Giant Axons. The comparison of the parameter configuration between the simulated and real data demonstrated the flexibility of the model as well as interesting differences.Author summaryAlejandro Rodríguez-Collado. I received the double degree in Statistics and Computer Engineering and the Master’s degree in Business Intelligence and Big Data from the Universidad de Valladolid in 2019 and 2020, respectively. I work as researcher and Professor for the Department of Statistics and Operational Research at the Universidad de Valladolid. My main research interests include oscillatory signal processing, neuroscience, multivariate data analysis and supervised learning.Cristina Rueda. I received the BS degree in mathematics from the Universidad de Valladolid in 1987 and the PhD degree in statistical science from the Universidad de Valladolid in 1989. I am currently Professor in the Department of Statistics and Operational Research at the Universidad de Valladolid. My main research interests include statistical inference methods under restrictions, circular data, computational biology, and statistical methods for signal analysis.

Chikungunya virus (CHIKV) is a re-emergent arbovirus that causes a disease characterized primarily by fever, rash and severe persistent polyarthralgia, although

A novel approach for analysing cardiac rhythm data is presented in this paper. Heartbeats are decomposed into the five fundamental P, Q, R, S and T waves plus an error term to account for artifacts in the data which provides a meaningful, physical interpretation of the heart’s electric system. The morphology of each wave is concisely described using four parameters that allow all the different patterns in heartbeats to be characterized and thus differentiated This multi-purpose approach solves such questions as the extraction of interpretable features, the detection of the fiducial marks of the fundamental waves, or the generation of synthetic data and the denoising of signals. Yet the greatest benefit from this new discovery will be the automatic diagnosis of heart anomalies as well as other clinical uses with great advantages compared to the rigid, vulnerable and black box machine learning procedures, widely used in medical devices. The paper shows the enormous potential of the method in practice; specifically, the capability to discriminate subjects, characterize morphologies and detect the fiducial marks (reference points) are validated numerically using simulated and real data, thus proving that it outperforms its competitors.

Purpose Despite antiretroviral therapy, approximately half of individuals with human immunodeficiency virus (HIV) will develop HIV-associated neurocognitive disorder (HAND). Efficiency of brain networks is of great importance for cognitive functioning, since functional networks may reorganize or compensate to preserve normal cognition. This study aims to compare efficiency of the posterior cingulate cortex (PCC) between patients with and without HAND and controls. We hypothesize HAND negative (HAND–) patients will show higher PCC efficiency than HAND positive (HAND+) patients. Methods A total of 10 HAND + patients were compared with 9 HAND– patients and 17 gender-, age-, and education-matched controls. Resting-state functional MRI was acquired with a 3 Tesla scanner. Local efficiency, a measure of network functioning, was investigated for PCC. Network differences among HAND + , HAND– patients and controls were tested as well as correlations between network parameters and cognitive test performance in different domains. Results HAND– patients showed significantly increased PCC efficiency compared with healthy controls ( p = 0.015). No differences were observed between HAND + patients and either controls ( p = 0.327) or HAND– patients ( p = 0.152). In HAND– patients, PCC efficiency was positively related with cognitive performance in the attention/working memory domain ( p = 0.003). Conversely, in HAND + patients, PCC efficiency was negatively correlated with performance in the abstraction/executive domain ( p = 0.002). Conclusion HAND– patients showed a higher level of PCC efficiency compared with healthy subjects, and PCC efficiency was positively related to cognitive performance. These results support the functional reorganization hypothesis, that increased PCC efficiency is a compensation technique to maintain cognitive functioning.

The rates and routes of lethal systemic spread in breast cancer are poorly understood owing to a lack of molecularly characterized patient cohorts with long-term, detailed follow-up data. Long-term follow-up is especially important for those with oestrogen-receptor (ER)-positive breast cancers, which can recur up to two decades after initial diagnosis1–6. It is therefore essential to identify patients who have a high risk of late relapse7–9. Here we present a statistical framework that models distinct disease stages (locoregional recurrence, distant recurrence, breast-cancer-related death and death from other causes) and competing risks of mortality from breast cancer, while yielding individual risk-of-recurrence predictions. We apply this model to 3,240 patients with breast cancer, including 1,980 for whom molecular data are available, and delineate spatiotemporal patterns of relapse across different categories of molecular information (namely immunohistochemical subtypes; PAM50 subtypes, which are based on gene-expression patterns10,11; and integrative or IntClust subtypes, which are based on patterns of genomic copy-number alterations and gene expression12,13). We identify four late-recurring integrative subtypes, comprising about one quarter (26%) of tumours that are both positive for ER and negative for human epidermal growth factor receptor 2, each with characteristic tumour-driving alterations in genomic copy number and a high risk of recurrence (mean 47–62%) up to 20 years after diagnosis. We also define a subgroup of triple-negative breast cancers in which cancer rarely recurs after five years, and a separate subgroup in which patients remain at risk. Use of the integrative subtypes improves the prediction of late, distant relapse beyond what is possible with clinical covariates (nodal status, tumour size, tumour grade and immunohistochemical subtype). These findings highlight opportunities for improved patient stratification and biomarker-driven clinical trials. A statistical framework for breast-cancer recurrence uses long-term follow-up data and a knowledge of molecular subcategories to model distinct disease stages and to predict the risk of relapse.

Oscillatory systems arise in the different biological and medical fields. Mathematical and statistical approaches are fundamental to deal with these processes. The Frequency Modulated Mobiüs approach (FMM), reviewed in this paper, is one of these approaches. Little known as it has been recently developed, it solves a variety of exciting questions with real data; some of them, such as the decomposition of the signal into components and their multiple uses, are of general application, others are specific. Among the exciting specific applications is the automatic interpretation of the electrocardiogram signal. In this paper, a summary of the theoretical, statistical and computational properties of the FMM approach are revised. Additionally, as a novelty, the FMM approach’s usefulness for the analysis of blood pressure signals is shown. For the latter, a new robust estimation algorithm is proposed using FMM models with restrictions. The paper ends with a view about challenges for the future.

Data derived from microarray technologies are generally subject to various sources of noise and accordingly the raw data are pre-processed before formally analysed. Data normalization is a key pre-processing step when dealing with microarray experiments, such as circadian gene-expressions, since it removes systematic variations across arrays. A wide variety of normalization methods are available in the literature. However, from our experience in the study of rhythmic expression patterns in oscillatory systems (e.g. cell-cycle, circadian clock), the choice of the normalization method may substantially impair the identification of rhythmic genes. Hence, the identification of a gene as rhythmic could be just as an artefact of how the data were normalized. Yet, gene rhythmicity detection is crucial in modern toxicological and pharmacological studies, thus a procedure to truly identify rhythmic genes that are robust to the choice of a normalization method is required.To perform the task of detecting rhythmic features, we propose a rhythmicity measure based on bootstrap methodology to robustly identify rhythmic genes in oscillatory systems. Although our methodology can be extended to any high-throughput experiment, in this chapter, we illustrate how to apply it to a publicly available circadian clock microarray gene-expression data and give full details (both statistical and computational) so that the methodology can be used in an easy way. We will show that the choice of normalization method has very little effect on the proposed methodology since the results derived from the bootstrap-based rhythmicity measure are highly rank correlated for any pair of normalization methods considered. This suggests, on the one hand, that the rhythmicity measure proposed is robust to the choice of the normalization method, and on the other hand, that gene rhythmicity detected using this measure is potentially not a mere artefact of the normalization method used. In this way the researcher using this methodology will be protected against the possible effect of different normalizations, as the conclusions obtained will not depend so strongly on them. Additionally, the described bootstrap methodology can also be employed as a tool to simulate gene-expression participating in an oscillatory system from a reference data set.

Background: A range of different neurological manifestations has been reported in fetuses and adults after Zika virus (ZIKV) infection. Objective: We describe a detection of the ZIKV in the brain tissue from a multiple sclerosis (MS) patient with acute disseminated encephalomyelitis (ADEM)-like event in Rio de Janeiro, Brazil. Methods: Biological samples collected during the hospitalization were tested by serology and molecular diagnostic for various infectious agents. Histopathological analysis was performed using the anti-flavivirus group 4G2 monoclonal antibody, anti-ZIKV non-structural 1 (NS1) monoclonal antibody, and anti-CD4, CD8, and CD11b antibodies. Results: Anti-ZIKV IgM and IgG antibodies were positive in the serum and urine. A brain biopsy showed ZIKV protein in brain cells and T CD8 infiltration in brain tissue. Conclusion: Our data describe the coexistence of a recent central nervous system (CNS) ZIKV infection accompanied by a severe ADEM-like syndrome outcome in a patient with clinical history of MS. A de novo immune response concomitant with ZIKV infection might be involved in the mechanism of the ADEM-like syndrome and response to immunotherapy. The present report reinforces the importance of providing the differential diagnosis of acute episodes of MS exacerbation in an environment prone to ZIKV expression.

Motivation: Gene-expression data obtained from high throughput technologies are subject to various sources of noise and accordingly the raw data are pre-processed before formally analyzed. Normalization of the data is a key pre-processing step, since it removes systematic variations across arrays. There are numerous normalization methods available in the literature. Based on our experience, in the context of oscillatory systems, such as cell-cycle, circadian clock, etc., the choice of the normalization method may substantially impact the determination of a gene to be rhythmic. Thus rhythmicity of a gene can purely be an artifact of how the data were normalized. Since the determination of rhythmic genes is an important component of modern toxicological and pharmacological studies, it is important to determine truly rhythmic genes that are robust to the choice of a normalization method. Results: In this paper we introduce a rhythmicity measure and a bootstrap methodology to detect rhythmic genes in an oscillatory system. Although the proposed methodology can be used for any high-throughput gene expression data, in this paper we illustrate the proposed methodology using several publicly available circadian clock microarray gene-expression datasets. We demonstrate that the choice of normalization method has very little effect on the proposed methodology. Specifically, for any pair of normalization methods considered in this paper, the resulting values of the rhythmicity measure are highly correlated. Thus it suggests that the proposed measure is robust to the choice of a normalization method. Consequently, the rhythmicity of a gene is potentially not a mere artifact of the normalization method used. Lastly, as demonstrated in the paper, the proposed bootstrap methodology can also be used for simulating data for genes participating in an oscillatory system using a reference dataset. Availability: A user friendly code implemented in R language can be downloaded from http://www.eio.uva.es/~miguel/robustdetectionprocedure.html.

OBJECTIVES: Since its development in the late 1990s, the European System for Cardiac Operative Risk Evaluation (EuroSCORE) has been the predictive model of choice for estimating mortality after cardiac surgery. As outcomes from cardiac surgery improved, the EuroSCORE showed a loss of calibration, and a revised version of the model was developed, EuroSCORE II. The objectives of this study were to examine the validity of both scores in the Spanish population, and to depict the performance of both models on a funnel plot. METHODS: A prospective multicentre study was performed, with requests to participate sent to all centres in Spain. Participating centres reported the EuroSCORE, EuroSCORE II and the actual mortality of each patient. Incomplete data were requested to get a zero incidence of lost data. Calibration of models was evaluated with the Hosmer–Lemeshow goodness-of-fit test, and discrimination with the areas under the receiver operating characteristic (ROC) curve. A funnel plot was constructed using mortality data from the 2010 European Registry, to represent risk-adjusted mortality. RESULTS: Twenty Spanish centres participated in the study; 4034 patients undergoing cardiac surgery between 1 October 2012 and 31 March 2013 were collected. Prevalence of risk factors was analysed. The observed mortality rate was 6.5%. The mean additive EuroSCORE was 6.5. The mean expected mortality rate was 9.8% for the logistic EuroSCORE, and 5.7% for EuroSCORE II. Areas under the ROC curves were EuroSCORE: 0.77 [95% confidence interval (CI): 0.75–0.80], EuroSCORE II: 0.79 (95% CI: 0.76–0.82). Results for the goodness-of-fit test were EuroSCORE: 33.02 (P< 0.001), EuroSCORE II: 38.98 (P< 0.001). Risk-adjusted mortality is far beyond the lower bound of the CI if EuroSCORE is used as the reference model, and is between the confidence limits, but near to the upper bound when EuroSCORE II is used. CONCLUSIONS: Spanish cardiac surgical patients have a high-risk profile. Areas under the ROC curve show good discrimination for both models. Predicted mortality using EuroSCORE II more closely matches actual mortality than that predicted by the original EuroSCORE. Both models show statistically significant differences from the actual mortality rate, with EuroSCORE overpredicting and EuroSCORE II underpredicting mortality. The funnel plot illustrates risk-adjusted mortality clearly out of boundaries when EuroSCORE is used, and near underprediction when the reference is EuroSCORE II.

BACKGROUND AND PURPOSE Optic neuritis (ON) is an acute episode of inflammation in the visual pathway (VP). It may occur as part of a demyelinating disease, which can affect white matter (WM) throughout the VP. Compensatory cortical adaptations may occur following WM damage to maintain visual integrity. Our aim was to investigate whether resting-state functional MRI (rsfMRI) can detect cortical adaptations following ON attacks and to correlate rsfMRI with diffusion tensor imaging (DTI) of WM within the VP. MATERIALS AND METHODS Neuromyelitis optica spectrum patients were compared to healthy controls at least 6 months after ON onset. DTI and rsfMRI were performed and post-processed using FSL tools (TBSS for DTI and MELODIC for fMRI). RESULTS Ptients had higher synchronization values than controls in the visual network (3.48 vs. 2.12, P < .05). A weak trend of correlation was revealed between fMRI and structural analysis by DTI using fractional anisotropy (right side: R = −.36, P < .08; left side: R = .075, P < .73). CONCLUSIONS The rsfMRI detected cortical reorganization following ON attack, but WM was considerably preserved in the posterior VP.

The aim of our study was to detect functional changes in default-mode network of neuromyelitis optica (NMO) patients using resting-state functional magnetic resonance images and the evaluation of subcortical gray-matter structures volumes.NMO patients (n=28) and controls patients (n=19) were enrolled. We used the integrated registration and segmentation tool, part of FMRIB's Software Library (FSL) to segment subcortical structures including the thalamus, caudate nucleus, putamen, hippocampus and amygdalae. Resting-state functional magnetic resonance images were post-processed using the Multivariate Exploratory Linear Optimized Decomposition into Independent Components, also part of FSL. Average Z-values extracted from the default-mode network were compared between patients and controls using t-tests (P values0.05 were considered statistically significant).There were areas of increased synchronization in the default-mode network of patients compared to controls, notably in the precuneus and right hippocampus (corrected P0.01). The frontal area had decreased synchronization in patients compared to controls (corrected P0.01). There were no observed differences between patients and controls in subcortical volumes or average Z-values values for default-mode network.The hyperactivity of certain default-mode network areas may reflect cortical compensation for subtle structural damage in NMO patients.

Objective This study aims to evaluate “in vivo” the integrity of the normal-appearing spinal cord (NASC) in patients with multiple sclerosis (MS) compared to controls, using diffusion tensor MR imaging. Methods We studied 32 patients with MS and 17 without any neurologic disorder. Fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD) and mean diffusivity (MD) were calculated within regions of interest at C2 and C7 levels in the four columns of the spinal cord. Results At C2, FA value was decreased in MS patients. Besides, RD value was higher in MS than in controls. At C7, MD values were increased in MS. Conclusion The NASC in the right column of the cervical spinal cord showed abnormal FA, RD and MD values, which is possibly related to demyelination, since the FA abnormality was related to the RD and not to the AD.

We compared the ability of the EUCAST EDef 7.2 and the Etest to detect the susceptibility to micafungin of 160 Candida and non-Candida clinical isolates. Agreement was higher when Etest MICs were obtained after 24 h of incubation; essential agreement was 90%, and categorical agreement was >90%. False susceptibility was seen only for Candida krusei (10%), and false resistance was observed in 6% of the isolates, ranging from 2.6% (C. glabrata) to 13% (C. albicans).

Neuromyelitis optica (NMO) is considered a demyelinating disorder, predominantly affecting the optic nerve and the spinal cord. However the disease concept has undergone changes over the past decade. In the neurological field, NMO is no longer considered as being a multiple sclerosis (MS) subtype, being currently diagnosed as a disease itself, with a differentiated clinical course, besides different prognosis and treatment as compared with MS. In what regards the immunological aspect, the discovery of the central nervous system water channels (aquaporin) involvement by an autoantibody called anti-AQP4 was a key factor leading to the differentiation of the disease. The attack by autoimmune complexes to areas containing water channels, particularly those adjacent to ventricular regions, in the optic nerves and around the central channel of the spinal cord, causes necrosis in such regions, leading to more severe lesions which are more difficult to heal than MS lesions. All such discoveries were essential for the evolvement of radiological evaluation in NMO. The involvement of the brain in NMO has been increasingly investigated. Previously, the criteria for diagnosis of NMO established that cranial magnetic resonance imaging (MRI) should be normal. Currently, such criteria include the presence of lesions at cranial MRI which do not meet the imaging criteria for MS. At MRI, intracranial lesions are poorly specific, but are frequently found, affecting up to 90% of the cases. However, about 8–10% of the patients present more severe brain lesions, with typical images from affected regions which are rich in APQ4 channels, such as those around the third ventricle, the periaqueductal gray matter, hypothalamus and periventricular region(1).

Brain abnormalities in neuromyelitis optica (NMO) have been reported previously, but the pathophysiological mechanism and clinical relevance of these abnormalities are poorly understood. We assessed the prevalence and patterns of brain MRI abnormalities in a Brazilian cohort of patients with NMO. Conventional brain MRI and medical records from 24 Brazilian patients with NMO were retrospectively evaluated. Brain MRI were classified into four subgroups: normal, non-specific lesions, multiple sclerosis (MS)-like lesions, and typical lesions. Brain lesions were detected in 19 patients (79.2%). Fourteen patients (58.3%) had non-specific lesions, three (12.5%) had MS-like lesions, and two (8.3%) had typical lesions. Differences between these subgroups with respect to the Expanded Disability Status Scale (EDSS) scores (p = 0.86) were not significant. This study demonstrates a high prevalence of brain abnormalities in Brazilian patients with NMO; however, we did not find a significant relationship between these abnormalities and EDSS scores.

We propose and discuss improved Bayes rules to discriminate between two populations using ordered predictors. To address the problem we propose an alternative formulation using a latent space that allows to introduce the information about the order in the theoretical rules. The rules are first defined when the marginal densities are fully known and then under normality when the parameters are unknown and training samples are available. Several numerical examples and simulations in the paper illustrate the methodology and show that the new rules handle the information appropriately. We compare the new rules with the classical Bayes and Fisher rules in these examples and we show that the misclassification probability is smaller for the new rules. The method is also applied to data from a diabetes study where we again show that the new rules improve over the usual Fisher rule.

OBJECTIVE. The purpose of this article is to illustrate the feasibility of fused whole-body MRI and PET for the evaluation of patients with cancer.CONCLUSION. MRI has proven to be superior to CT for studying several regions of the body, and PET FDG has become an established diagnostic tool in oncology. Because FDG accumulates avidly in tumor tissue, fusing FDG PET to whole-body MRI allows good anatomy-based evaluation of disease.

In recent years, mass spectrometry techniques have helped proteomics to become a powerful tool for the early diagnosis of cancer, as they help to discover protein profiles specific to each pathological state. One of the questions where proteomics is giving useful practical results is that of classifying patients into one of the possible severity levels of an illness, based on some features measured on the patient. This classification is usually made using one of the many discrimination procedures available in statistical literature. We present in this chapter recently developed restricted discriminant rules that use additional information in terms of orderings on the means, and we illustrate how to apply them to mass spectrometry data using R package dawai. Specifically, we use proteomic prostate cancer data, and we describe all steps needed, including data preprocessing and feature extraction, to build a discriminant rule that classifies samples in one of several disease stages, thus helping diagnosis. The restricted discriminant rules are compared with some standard classifiers that do not take into account the additional information, showing better performance in terms of error rates.

The most useful and broadly known rule in the classical two-group linear normal discriminant analysis is Anderson's rule. In this article we propose some alternative procedures that prove useful wh...

This is an Open Access article distributed under the terms of the Creative Commons Attribution License., The fruitfly compound eye has been broadly used as a model for neurodegenerative diseases. Classical quantitative techniques to estimate the degeneration level of an eye under certain experimental conditions rely either on time consuming histological techniques to measure retinal thickness, or pseudopupil visualization and manual counting. Alternatively, visual examination of the eye surface appearance gives only a qualitative approximation provided the observer is well-trained. Therefore, there is a need for a simplified and standardized analysis of fruitfly eye degeneration extent for both routine laboratory use and for automated high-throughput analysis. We have designed the freely available ImageJ plugin FLEYE, a novel and user-friendly method for quantitative unbiased evaluation of neurodegeneration levels based on the acquisition of fly eye surface pictures. The incorporation of automated image analysis tools and a classification algorithm sustained on a built-in statistical model allow the user to quickly analyze large sample size data with reliability and robustness. Pharmacological screenings or genetic studies using the Drosophila retina as a model system may benefit from our method, because it can be easily implemented in a fully automated environment. In addition, FLEYE can be trained to optimize the image detection capabilities, resulting in a versatile approach to evaluate the pattern regularity of other biological or non-biological samples and their experimental or pathological disruption., We acknowledge the support of the publication fee by the CSIC Open Access Publication Support Initiative through its Unit of Information Resources for Research (URICI).

Many biological processes, such as cell cycle, circadian clock, menstrual cycles, are governed by oscillatory systems consisting of numerous components that exhibit rhythmic patterns over time. It is not always easy to identify such rhythmic components. For example, it is a challenging problem to identify circadian genes in a given tissue using time-course gene expression data. There is a great potential for misclassifying non-rhythmic as rhythmic genes and vice versa. This has been a problem of considerable interest in recent years. In this article we develop a constrained inference based methodology called Order Restricted Inference for Oscillatory Systems (ORIOS) to detect rhythmic signals. Instead of using mathematical functions (e.g. sinusoidal) to describe shape of rhythmic signals, ORIOS uses mathematical inequalities. Consequently, it is robust and not limited by the biologist’s choice of the mathematical model. We studied the performance of ORIOS using simulated as well as real data obtained from mouse liver, pituitary gland and data from NIH3T3, U2OS cell lines. Our results suggest that, for a broad collection of patterns of gene expression, ORIOS has substantially higher power to detect true rhythmic genes in comparison to some popular methods, while also declaring substantially fewer non-rhythmic genes as rhythmic., Spanish Ministerio de Ciencia e Innovación [MTM2015-71217-R], Spanish Ministerio de Educación, Cultura y Deporte [FPU14/04534], Intramural Research Program of the National Institute of Environmental Health Sciences (NIEHS) [Z01 ES101744-04]

A total of 116 samples (44 clinical specimens and 72 environmental samples) have been analyzed for the presence of Acanthamoeba. The environmental samples (ESs) were collected from four drinking water treatment plants (DWTP, n = 32), seven wastewater treatment plants (n = 28), and six locations of influence (n = 12) on four river basins from the central area of Spain (winter–spring 2008). Water samples were concentrated by using the IDEXX Filta-Max® system. Acanthamoeba was identified in 65 of the 72 ESs by culture isolation (90.3%) and 63 by real-time PCR (87.5%), resulting in all sampling points (100%) positive for Acanthamoeba when considering both techniques and all the time period analyzed. Nine of the 44 clinical specimens were positive for Acanthamoeba. Seventeen Acanthamoeba strains (eight from four DWTP and nine from clinical samples) were also established in axenic-PYG medium. Twenty-four of the ESs and the 17 Acanthamoeba sp. strains were genotyped as T4/1, T4/8, and T4/9. The eight strains isolated from the DWTP samples were inoculated in nude mouse to ascertain their potential pathogenicity in this model. Animals that were inoculated died or showed central nervous system symptoms 9 days post-inoculation. Examination of immunofluorescence-stained brain and lung tissue sections showed multiple organisms invading both tissues, and re-isolation of throphozoites was successful in these tissues of all infected animals. For the first time, potentially pathogenic Acanthamoeba T4 has been detected in 100% of different types of water samples including tap water and sewage effluents in the central area of Spain suggesting a potential health threat for humans especially for the contact lens wearers.

Introduction This study aims to evaluate “in vivo” the integrity of the normal-appearing spinal cord in patients with neuromyelitis optica (NMO), using diffusion tensor MR imaging, comparing to controls and patients with multiple sclerosis (MS). Materials and methods We studied 8 patients with NMO and 17 without any neurologic disorder. Also, 32 MS patients were selected. Fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD) and mean diffusivity (MD) were calculated within regions of interest at C2 and C7 levels in the four columns of the spinal cord. Results At C2, the FA value was decreased in NMO patients compared to MS and controls in the anterior column. Also in this column, RD value showed increase in NMO compared to MS and to controls. The FA value of the posterior column was decreased in NMO in comparison to controls. At C7, AD value was higher in NMO than in MS in the right column. At the same column, MD values were increased in NMO compared to MS and to controls. Conclusions There is extensive NASC damage in NMO patients, including peripheral areas of the cervical spinal cord, affecting the white matter, mainly caused by demyelination. This suggests a new spinal cord lesion pattern in NMO in comparison to MS.

In many applications, especially in cancer treatment and diagnosis, investigators are interested in classifying patients into various diagnosis groups on the basis of molecular data such as gene expression or proteomic data. Often, some of the diagnosis groups are known to be related to higher or lower values of some of the predictors. The standard methods of classifying patients into various groups do not take into account the underlying order. This could potentially result in high misclasiffication rates, especially when the number of groups is larger than two. In this article, we develop classification procedures that exploit the underlying order among the mean values of the predictor variables and the diagnostic groups by using ideas from order-restricted inference. We generalize the existing methodology on discrimination under restrictions and provide empirical evidence to demonstrate that the proposed methodology improves over the existing unrestricted methodology. The proposed methodology is applied to a bladder cancer data set where the researchers are interested in classifying patients into various groups. Copyright © 2012 John Wiley & Sons, Ltd.

Traumatic brain injury is a common cause of death worldwide, affecting mostly young people. The most feasible examination to be performed in the emergency room is computed tomography. Magnetic resonance (MR) imaging is becoming a significant tool in the evaluation of severe brain trauma. Diffusion-weighted imaging is an advanced MR imaging sequence that has been used to detect areas of ischemia and tumor malignancy. This article describes the recent advances in trauma based on diffusion-weighted MR imaging findings and in brain injury from head trauma based on diffusion-weighted MR imaging and diffusion tensor MR imaging findings. Current and potential clinical applications are discussed.

We propose and discuss improved classification rules when a subset of the predictors is known to be ordered. We compare the performance of the new rules with other standard rules in a restricted normal setting using simulation experiments and real data exposing their good performance.

Plasma cell granuloma (PCG) are uncommon non-neoplastic masses of unknown etiology, characterized histologically by proliferation of connective tissue with an inflammatory infiltrate of mononuclear elements1,2. They occur more commonly in the lung and conducting airways, but can also be seen in other tissues, such as the meninges3 […] Intracranial cell plasma granuloma

Background: Endovascular repair of the thoracic aorta has shown reduced morbidity and mortality compared with open surgery. We describe our experience with endovascular stent grafting in the treatment of acute thoracic aortic pathology. Methods: From October 2003 to January 2008, 25 patients underwent endovascular stent graft repair of the thoracic aorta. The underlying pathology was a complicated Stanford type B dissection (n = 13), a symptomatic or ruptured thoracic aorta aneurysm (n = 6), a symptomatic penetrating atherosclerotic ulcer (n = 5), or a traumatic aortic injury (n = 1). There were 21 males and four female patients with a mean age of 61.3 years (30–91 years). Routine surveillance included clinical evaluation and contrast-enhanced spiral computed tomography scans before discharge and at 3, 6, and 12 months after the procedure and yearly thereafter. Results: Stent graft placement was technically successful in all patients. There was no intraoperative mortality. Hospital mortality was of two patients (8%). Paraparesis occurred in one patient (4%). Average intensive care unit and hospital stay was 1 and 10 days, respectively. The mean follow-up was 30 months (range, 7–53). Late mortality was in one patient (4%), due to a type A dissection. During the follow-up, four patients (16%) required a second procedure for type I endoleak. Conclusions: Mortality and morbidity in our small series were low. Close follow-up is mandatory and long-term results have to be awaited.

A literatura sobre formação de professores de ciências não tem tratado suficientemente a situação do mundo quanto a uma percepção global de seus graves problemas atuais. O presente artigo consiste essencialmente de um programa de atividades a ser desenvolvido com professores em formação e em exercício, que visa favorecer uma reflexão coletiva e conscientização sobre essa problemática. Nesta perspectiva é apontado um conjunto de referências e questões para um debate fundamentado sobre vários dos fatores associados à degradação da vida e sobre possíveis medidas para o enfrentamento da emergência planetária. Investigações preliminares sobre a utilização do programa proposto têm revelado resultados favoráveis quanto à percepção de que a educação científica tem a contribuir para pensar e construir o futuro na direção de uma melhoria da qualidade de vida. The literature about science teachers' training program hasn't properly explored the world's situation regarded to a global perception of its serious present problems. This article consists basically of a program of activities to be developed in partnership with graduated and graduating teachers, which aims to stimulate a group reflection over those matters. Under this perspective, a group of references and questions is indicated for a debate based on many factors connected to life's degradation and possible decisions to be taken in order to face the planetary emergency. Primary studies about the use of the proposed program have shown auspicious results regarding the perception that the scientific education can contribute to the thinking and building the future towards a better life quality.

ResumenEl abordaje quirúrgico adecuado es un aspecto esencial en la cirugía de aorta. Tras realizar múltiples accesos quirúrgicos en cadáveres en fresco para un curso de formación de residentes y revisar la literatura, se desarrolla de forma didáctica y práctica una visión anatómica y quirúrgica de las diferentes vías de acceso a la aorta.AbstractAppropriate surgical access is an essential aspect in aortic surgery. After performing multiple surgical approaches in fresh frozen human cadavers for a training course, and reviewing the literature, an anatomical and surgical review of the different approaches to aorta was developed for didactic and practical purposes.