The association of internet use and depression among spinal cord injury population

The purpose of this study was to exam the relationship between internet use and depression among a population of individuals who have sustained spinal cord injury. This was cross-sectional survey design conducted among spinal cord injury (SCI) patients in the Model Spinal Cord Injury System. We included a total of 1,011 SCI-patients who were interviewed face-to-face or by telephone interview over approximately a three year time period (2004–2006). All data were collected through a telephone survey which included the Patient Health Questionnaire-9 (PHQ-9) to assess depression. We examined various scales of this survey, included a reduced 3-item scale (items 1, 2 and 6) to avoid the presence of somatic symptoms among SCI patients from influencing classification of depression. The frequency of internet usage was grouped as daily/weekly/monthly/non user. Covariates examined as possible confounders included demographic characteristics, occupational status, educational level, injury type, daily function of living, pain level, self-perceived health status and satisfaction with life. We observed a negative association between the frequency of internet use and the level of depression. Daily use of internet was associated with lower PHQ-9 score and depression; however this association did not reach statistical significance after for the mentioned covariates. In conclusion, the factors related to lower depression in SCI patients who use the internet are complicated. Daily internet usage was associated with lower levels of depression. The accuracy of 3-item scale needs further validation and investigation. Further study of internet usage pattern in SCI patient is recommended. ^

A Su Salud Injury Prevention expansion: Analysis of injury prevention perceptions in a Hispanic community

Unintentional injury is the leading cause of death for American ages one to 44 and is ranked in the top ten causes of death for all age groups (CDC, 2006a). A Su Salud Injury Prevention was developed to address injury prevention awareness and education. The program is a mass media education campaign that uses role models, mass media, and community outreach to prevent injury. In 2009, University Health System (UHS) expanded the program. Baseline data were collected from 426 residents in targeted neighborhoods northwest of downtown San Antonio to support the expansion. The purpose of this study was to explore injury perceptions, knowledge, and behaviors of adults living in the expansion area, and define the predominant factors associated with these perceptions. A secondary aim was to assess community awareness and willingness to participate in the program.^ Survey results showed motor vehicle crashes (MVC), falls, drinking and driving, and guns and assaults were considered the most serious injures for adults. The most serious child injuries were MVC, abuse and neglect, falls, and head injuries. Residents were knowledgeable of state seatbelt policy, and over 90% responded as compliant for seatbelt and child car seat use. Most were knowledgeable about drinking and driving state policy and negative outcomes. However, 70% of those reporting driving under the influence of alcohol within the last year engaged in repeat high risk behavior. Men and residents under the age of 55 were more likely to engage in repeat drinking and driving (OR= 3.6, 7.0 respectively). Residents consider injury prevention an important issue, and have interest in a local injury prevention program. Younger women are the most likely to participate in a local program as potential role models and volunteers.^ Results from the study are summarized into an injury prevention and demographic profile of the community that will be used to develop tailored injury prevention messages to create a more effective program, and support program coordinators in effective community engagement. Results will also be used as a comparative basis for future evaluation of a behavioral injury prevention program focused on a predominantly Mexican-American community.^

A comparison of worker risk of injury while working on fully automated side loaders and other residential collection trucks at a large solid waste collection company

The study aim was to determine whether using automated side loader (ASL) trucks in higher proportions compared to other types of trucks for residential waste collection results in lower injury rates (from all causes). The primary hypothesis was that the risk of injury to workers was lower for those who work with ASL trucks than for workers who work with other types of trucks used in residential waste collection. To test this hypothesis, data were collected from one of the nation’s largest companies in the solid waste management industry. Different local operating units (i.e. facilities) in the company used different types of trucks to varying degrees, which created a special opportunity to examine refuse collection injuries and illnesses and the risk reduction potential of ASL trucks.^ The study design was ecological and analyzed end-of-year data provided by the company for calendar year 2007. During 2007, there were a total of 345 facilities which provided residential services. Each facility represented one observation.^ The dependent variable – injury and illness rate, was defined as a facility’s total case incidence rate (TCIR) recorded in accordance with federal OSHA requirements for the year 2007. The TCIR is the rate of total recordable injury and illness cases per 100 full-time workers. The independent variable, percent of ASL trucks, was calculated by dividing the number of ASL trucks by the total number of residential trucks at each facility.^ Multiple linear regression models were estimated for the impact of the percent of ASL trucks on TCIR per facility. Adjusted analyses included three covariates: median number of hours worked per week for residential workers; median number of months of work experience for residential workers; and median age of residential workers. All analyses were performed with the statistical software, Stata IC (version 11.0).^ The analyses included three approaches to classifying exposure, percent of ASL trucks. The first approach included two levels of exposure: (1) 0% and (2) >0 - <100%. The second approach included three levels of exposure: (1) 0%, (2) ≥ 1 - < 100%, and (3) 100%. The third approach included six levels of exposure to improve detection of a dose-response relationship: (1) 0%, (2) 1 to <25%, (3) 25 to <50%, (4) 50 to <75%, (5) 75 to <100%, and (6) 100%. None of the relationships between injury and illness rate and percent ASL trucks exposure levels was statistically significant (i.e., p<0.05), even after adjustment for all three covariates.^ In summary, the present study shows that there is some risk reduction impact of ASL trucks but not statistically significant. The covariates demonstrated a varied yet more modest impact on the injury and illness rate but again, none of the relationships between injury and illness rate and the covariates were statistically significant (i.e., p<0.05). However, as an ecological study, the present study also has the limitations inherent in such designs and warrants replication in an individual level cohort design. Any stronger conclusions are not suggested.^

A Pre-Clinical Assessment of Minocycline for Treatment of Chronic Neuropathic Pain after Spinal Cord Injury

Patients living with a spinal cord injury (SCI) often develop chronic neuropathic pain (CNP). Unfortunately, the clinically approved, current standard of treatment, gabapentin, only provides temporary pain relief. This treatment can cause numerous adverse side effects that negatively affect the daily lives of SCI patients. There is a great need for alternative, effective treatments for SCI-dependent CNP. Minocycline, an FDA-approved antibiotic, has been widely prescribed for the treatment of acne for several decades. However, recent studies demonstrate that minocycline has neuroprotective properties in several pre-clinical rodent models of CNS trauma and disease. Pre-clinical studies also show that short-term minocycline treatment can prevent the onset of CNP when delivered during the acute stage of SCI and can also transiently attenuate established CNP when delivered briefly during the chronic stage of SCI. However, the potential to abolish or attenuate CNP via long-term administration of minocycline after SCI is unknown. The purpose of this study was to investigate the potential efficacy and safety of long-term administration of minocycline to abolish or attenuate CNP following SCI. A severe spinal contusion injury was administered on adult, male, Sprague-Dawley rats. At day 29 post-injury, I initiated a three-week treatment regimen of daily administration with minocycline (50 mg/kg), gabapentin (50 mg/kg) or saline. The minocycline treatment group demonstrated a significant reduction in below-level mechanical allodynia and above- level hyperalgesia while on their treatment regimen. After a ten-day washout period of minocycline, the animals continued to demonstrate a significant reduction in below-level mechanical allodynia and above-level hyperalgesia. However, minocycline-treated animals exhibited abnormal weight gain and hepatotoxicity compared to gapabentin-treated or vehicle-treated subjects.The results support previous findings that minocycline can attenuate CNP after SCI and suggested that minocycline can also attenuate CNP via long-term delivery of minocycline after SCI (36). The data also suggested that minocycline had a lasting effect at reducing pain symptoms. However, the adverse side effects of long-term use of minocycline should not be ignored in the rodent model. Gabapentin treatment caused a significant decrease in below-level mechanical allodynia and below-level hyperalgesia during the treatment regimen. Because gabapentin treatment has an analgesic effect at the concentration I administered, the results were expected. However, I also found that gabapentin-treated animals demonstrated a sustained reduction in pain ten days after treatment withdrawal. This result was unexpected because gabapentin has a short half-life of 1.7 hours in rodents and previous studies have demonstrated that pre-drug pain levels return shortly after withdrawal of treatment. Additionally, the gabapentin-treated animals demonstrated a significant and sustained increase in rearing events compared with all other treatment groups which suggested that gabapentin treatment was not only capable of reducing pain long-term but may also significantly improve trunk stability or improve motor function recovery.

Epidemiology of Acute Lung Injury and Acute Respiratory Distress Syndrome in children in Vietnam

Acute Lung Injury (ALI) and Acute Respiratory Distress Syndrome (ARDS) are life- threatening disorders that can result from many severe conditions and diseases. Since the American European Consensus Conference established the internationally accepted definition of ALI and ARDS, the epidemiology of pediatric ALI/ARDS has been described in some developed countries. In the developing world, however, there are very few data available regarding the burden, etiologies, management, outcome, and factors associated with outcomes of ALI/ARDS in children. ^ Therefore, we conducted this observational, clinical study to estimate the prevalence and case mortality rate of ALI/ARDS among a cohort of patients admitted to the pediatric intensive care unit (PICU) of the National Hospital of Pediatrics in Hanoi, the largest children's hospital in Vietnam. Etiologies and predisposing factors, and management strategies for pediatric ALI/ARDS were described. In addition, we determined the prevalence of HIV infection among children with ALI/ARDS in Vietnam. We also identified the causes of mortality and predictors of mortality and prolonged mechanical ventilation of children with ALI/ARDS. ^ A total of 1,051 patients consecutively admitted to the pediatric intensive care unit from January 2011 to January 2012 were screened daily for development of ALI/ARDS using the American-European Consensus Conference Guidelines. All identified patients with ALI/ARDS were followed until hospital discharge or death in the hospital. Patients' demographic and clinical data were collected. Multivariable logistic regression models were developed to identify independent predictors of mortality and other adverse outcome of ALI/ARDS. ^ Prevalence of ALI and ARDS was 9.6% (95% confidence interval, 7.8% to 11.4%) and 8.8% (95% confidence interval, 7.0% to 10.5%) of total PICU admissions, respectively. Infectious pneumonia and sepsis were the most common causes of ALI/ARDS accounting for 60.4% and 26.7% of cases, respectively. Prevalence of HIV infection among children with ALI/ARDS was 3.0%. The case fatality rate of ALI/ARDS was 63.4% (95% confidence interval, 53.8% to 72.9%). Multiple organ failure and refractory hypoxemia were the main causes of death. Independent predictors of mortality and prolonged mechanical ventilation were male gender, duration of intensive care stay prior to ALI/ARDS diagnosis, level of oxygenation defect measured by PaO2/FiO2 ratio at ALI/ARDS diagnosis, presence of non-pulmonary organ dysfunction at day one and day three after ALI/ARDS diagnosis, and presence of hospital acquired infection. ^ The results of this study demonstrated that ALI/ARDS was a common and severe condition in children in Vietnam. The level of both pulmonary and non-pulmonary organ damage influenced survival of patients with ALI/ARDS. Strategies for preventing ALI/ARDS and for clinical management of the disease are necessary to reduce the associated risks.^

TRPV1 Channels Contribute to Behavioral Hypersensitivity and Spontaneous Activity in Nociceptors After Spinal Cord Injury

A majority of persons who have sustained spinal cord injury (SCI) develop chronic pain. While most investigators have assumed that the critical mechanisms underlying neuropathic pain after SCI are restricted to the central nervous system (CNS), recent studies showed that contusive SCI results in a large increase in spontaneous activity in primary nociceptors, which is correlated significantly with mechanical allodynia and thermal hyperalgesia. Upregulation of ion channel transient receptor vanilloid 1 (TRPV1) has been observed in the dorsal horn of the spinal cord after SCI, and reduction of SCI-induced hyperalgesia by a TRPV1 antagonist has been claimed. However, the possibility that SCI enhances TRPV1 expression and function in nociceptors has not been tested. I produced contusive SCI at thoracic level T10 in adult, male rats and harvested lumbar (L4/L5) dorsal root ganglia (DRG) from sham-treated and SCI rats 3 days and 1 month after injury, as well as from age-matched naive control rats. Whole-cell patch clamp recordings were made from small (soma diameter <30 >μm) DRG neurons 18 hours after dissociation. Capsaicin-induced currents were significantly increased 1 month, but not 3 days, after SCI compared to neurons from control animals. In addition, Ca2+ transients imaged during capsaicin application were significantly greater 1 month after SCI. Western blot experiments indicated that expression of TRPV1 protein in DRG is also increased 1 month after SCI. A major role for TRPV1 channels in pain-related behavior was indicated by the ability of a specific TRPV1 antagonist, AMG9810, to reverse SCI-induced hypersensitivity of hindlimb withdrawal responses to heat and mechanical stimuli. Similar reversal of behavioral hypersensitivity was induced by intrathecal delivery of oligodeoxynucleotides antisense to TRPV1, which knocked down TRPV1 protein and reduced capsaicin-evoked currents. TRPV1 knockdown also decreased the incidence of spontaneous activity in dissociated nociceptors after SCI. Limited activation of TRPV1 was found to induce prolonged repetitive firing without accommodation or desensitization, and this effect was enhanced by SCI. These data suggest that SCI enhances TRPV1 expression and function in primary nociceptors, increasing the excitability and spontaneous activity of these neurons, thus contributing to chronic pain after SCI.

Proteolytic mechanisms of cell injury following glucose -oxygen deprivation in primary neuronal cultures

Researchers have historically emphasized the contribution of caspase-3 to apoptotic but not necrotic cell death, while calpain has been implicated primarily in necrosis and, to a lesser extent, in apoptosis. Activation of these proteases occurs in vivo following various CNS insults including ischemia. In addition, both necrotic and apoptotic cell death phenotypes are detected following ischemia. However, the contributions of calpain and caspase-3 to apoptotic and necrotic cell death phenotypes following CNS insults are relatively unexplored. To date, no study has examined the concurrent activation of calpain and caspase-3 in necrotic and apoptotic cell death phenotypes following any CNS insult. The present study employed oxygen-glucose deprivation (OGD) to determine the relative contributions of caspase-3 and calpain to apoptotic and necrotic cell death following OGD. Experiments characterized a model of OGD by evaluating cell viability and characterizing the cell death phenotypes following OGD in primary septo-hippocampal co-cultures. Furthermore, cell markers (NeuN and MAP2 or GFAP) assessed the effects of OGD on neuronal and astroglial viability, respectively. In addition, calpain and caspase-3 mediated proteolysis of α-spectrin was examined using Western blot techniques. Activation of these proteases in individual cells phenotypically characterized as apoptotic and necrotic was also evaluated by using antibodies specific for calpain or caspase-3 mediated breakdown products to α-spectrin. Administration of appropriate caspase-3 and calpain inhibitors also examined the effects of protease inhibition on cell death. OGD produced prominent expression of apoptotic cell death phenotypes primarily in neurons, with relatively little damage to astroglia. Although Western blot data suggested greater proteolysis of α-spectrin by calpain than caspase-3, co-activation of both proteases was usually detected in cells exhibiting apoptotic or necrotic cell death phenotypes. While inhibition of calpain and caspase-3 activity decreased LDH release following OGD, it was not clear whether this effect was also associated with a decrease in cell death and the appearance of apoptotic cell death phenotypes. These data demonstrate that both calpain and caspase-3 contribute to the expression of apoptotic cell death phenotypes following OGD, and that calpain could potentially have a larger role in the expression of apoptotic cell death than previously thought. ^

Transcriptional response to cardiac injury in the zebrafish: systematic identification of genes with highly concordant activity across in vivo models

BACKGROUND Zebrafish is a clinically-relevant model of heart regeneration. Unlike mammals, it has a remarkable heart repair capacity after injury, and promises novel translational applications. Amputation and cryoinjury models are key research tools for understanding injury response and regeneration in vivo. An understanding of the transcriptional responses following injury is needed to identify key players of heart tissue repair, as well as potential targets for boosting this property in humans. RESULTS We investigated amputation and cryoinjury in vivo models of heart damage in the zebrafish through unbiased, integrative analyses of independent molecular datasets. To detect genes with potential biological roles, we derived computational prediction models with microarray data from heart amputation experiments. We focused on a top-ranked set of genes highly activated in the early post-injury stage, whose activity was further verified in independent microarray datasets. Next, we performed independent validations of expression responses with qPCR in a cryoinjury model. Across in vivo models, the top candidates showed highly concordant responses at 1 and 3 days post-injury, which highlights the predictive power of our analysis strategies and the possible biological relevance of these genes. Top candidates are significantly involved in cell fate specification and differentiation, and include heart failure markers such as periostin, as well as potential new targets for heart regeneration. For example, ptgis and ca2 were overexpressed, while usp2a, a regulator of the p53 pathway, was down-regulated in our in vivo models. Interestingly, a high activity of ptgis and ca2 has been previously observed in failing hearts from rats and humans. CONCLUSIONS We identified genes with potential critical roles in the response to cardiac damage in the zebrafish. Their transcriptional activities are reproducible in different in vivo models of cardiac injury.

Artificial metaplasticity prediction model for cognitive rehabilitation outcome in acquired brain injury patients

Objective The main purpose of this research is the novel use of artificial metaplasticity on multilayer perceptron (AMMLP) as a data mining tool for prediction the outcome of patients with acquired brain injury (ABI) after cognitive rehabilitation. The final goal aims at increasing knowledge in the field of rehabilitation theory based on cognitive affectation. Methods and materials The data set used in this study contains records belonging to 123 ABI patients with moderate to severe cognitive affectation (according to Glasgow Coma Scale) that underwent rehabilitation at Institut Guttmann Neurorehabilitation Hospital (IG) using the tele-rehabilitation platform PREVIRNEC©. The variables included in the analysis comprise the neuropsychological initial evaluation of the patient (cognitive affectation profile), the results of the rehabilitation tasks performed by the patient in PREVIRNEC© and the outcome of the patient after a 3–5 months treatment. To achieve the treatment outcome prediction, we apply and compare three different data mining techniques: the AMMLP model, a backpropagation neural network (BPNN) and a C4.5 decision tree. Results The prediction performance of the models was measured by ten-fold cross validation and several architectures were tested. The results obtained by the AMMLP model are clearly superior, with an average predictive performance of 91.56%. BPNN and C4.5 models have a prediction average accuracy of 80.18% and 89.91% respectively. The best single AMMLP model provided a specificity of 92.38%, a sensitivity of 91.76% and a prediction accuracy of 92.07%. Conclusions The proposed prediction model presented in this study allows to increase the knowledge about the contributing factors of an ABI patient recovery and to estimate treatment efficacy in individual patients. The ability to predict treatment outcomes may provide new insights toward improving effectiveness and creating personalized therapeutic interventions based on clinical evidence.

Clustering techniques for patients suffering acquired brain injury inneuro personal trainer

The study of the effectiveness of the cognitive rehabilitation processes and the identification of cognitive profiles, in order to define comparable populations, is a controversial area, but concurrently it is strongly needed in order to improve therapies. There is limited evidence about cognitive rehabilitation efficacy. Many of the trials conclude that in spite of an apparent clinical good response, differences do not show statistical significance. The common feature in all these trials is heterogeneity among populations. In this situation, observational studies on very well controlled cohort of studies, together with innovative methods in knowledge extraction, could provide methodological insights for the design of more accurate comparative trials. Some correlation studies between neuropsychological tests and patients capacities have been carried out -1---2- and also correlation between tests and morphological changes in the brain -3-. The procedures efficacy depends on three main factors: the affectation profile, the scheduled tasks and the execution results. The relationship between them makes up the cognitive rehabilitation as a discipline, but its structure is not properly defined. In this work we present a clustering method used in Neuro Personal Trainer (NPT) to group patients into cognitive profiles using data mining techniques. The system uses these clusters to personalize treatments, using the patients assigned cluster to select which tasks are more suitable for its concrete needs, by comparing the results obtained in the past by patients with the same profile.

1RM prediction: a data mining case study

In the last few years there has been a heightened interest in data treatment and analysis with the aim of discovering hidden knowledge and eliciting relationships and patterns within this data. Data mining techniques (also known as Knowledge Discovery in Databases) have been applied over a wide range of fields such as marketing, investment, fraud detection, manufacturing, telecommunications and health. In this study, well-known data mining techniques such as artificial neural networks (ANN), genetic programming (GP), forward selection linear regression (LR) and k-means clustering techniques, are proposed to the health and sports community in order to aid with resistance training prescription. Appropriate resistance training prescription is effective for developing fitness, health and for enhancing general quality of life. Resistance exercise intensity is commonly prescribed as a percent of the one repetition maximum. 1RM, dynamic muscular strength, one repetition maximum or one execution maximum, is operationally defined as the heaviest load that can be moved over a specific range of motion, one time and with correct performance. The safety of the 1RM assessment has been questioned as such an enormous effort may lead to muscular injury. Prediction equations could help to tackle the problem of predicting the 1RM from submaximal loads, in order to avoid or at least, reduce the associated risks. We built different models from data on 30 men who performed up to 5 sets to exhaustion at different percentages of the 1RM in the bench press action, until reaching their actual 1RM. Also, a comparison of different existing prediction equations is carried out. The LR model seems to outperform the ANN and GP models for the 1RM prediction in the range between 1 and 10 repetitions. At 75% of the 1RM some subjects (n = 5) could perform 13 repetitions with proper technique in the bench press action, whilst other subjects (n = 20) performed statistically significant (p < 0:05) more repetitions at 70% than at 75% of their actual 1RM in the bench press action. Rate of perceived exertion (RPE) seems not to be a good predictor for 1RM when all the sets are performed until exhaustion, as no significant differences (p < 0:05) were found in the RPE at 75%, 80% and 90% of the 1RM. Also, years of experience and weekly hours of strength training are better correlated to 1RM (p < 0:05) than body weight. O'Connor et al. 1RM prediction equation seems to arise from the data gathered and seems to be the most accurate 1RM prediction equation from those proposed in literature and used in this study. Epley's 1RM prediction equation is reproduced by means of data simulation from 1RM literature equations. Finally, future lines of research are proposed related to the problem of the 1RM prediction by means of genetic algorithms, neural networks and clustering techniques. RESUMEN En los últimos años ha habido un creciente interés en el tratamiento y análisis de datos con el propósito de descubrir relaciones, patrones y conocimiento oculto en los mismos. Las técnicas de data mining (también llamadas de \Descubrimiento de conocimiento en bases de datos\) se han aplicado consistentemente a lo gran de un gran espectro de áreas como el marketing, inversiones, detección de fraude, producción industrial, telecomunicaciones y salud. En este estudio, técnicas bien conocidas de data mining como las redes neuronales artificiales (ANN), programación genética (GP), regresión lineal con selección hacia adelante (LR) y la técnica de clustering k-means, se proponen a la comunidad del deporte y la salud con el objetivo de ayudar con la prescripción del entrenamiento de fuerza. Una apropiada prescripción de entrenamiento de fuerza es efectiva no solo para mejorar el estado de forma general, sino para mejorar la salud e incrementar la calidad de vida. La intensidad en un ejercicio de fuerza se prescribe generalmente como un porcentaje de la repetición máxima. 1RM, fuerza muscular dinámica, una repetición máxima o una ejecución máxima, se define operacionalmente como la carga máxima que puede ser movida en un rango de movimiento específico, una vez y con una técnica correcta. La seguridad de las pruebas de 1RM ha sido cuestionada debido a que el gran esfuerzo requerido para llevarlas a cabo puede derivar en serias lesiones musculares. Las ecuaciones predictivas pueden ayudar a atajar el problema de la predicción de la 1RM con cargas sub-máximas y son empleadas con el propósito de eliminar o al menos, reducir los riesgos asociados. En este estudio, se construyeron distintos modelos a partir de los datos recogidos de 30 hombres que realizaron hasta 5 series al fallo en el ejercicio press de banca a distintos porcentajes de la 1RM, hasta llegar a su 1RM real. También se muestra una comparación de algunas de las distintas ecuaciones de predicción propuestas con anterioridad. El modelo LR parece superar a los modelos ANN y GP para la predicción de la 1RM entre 1 y 10 repeticiones. Al 75% de la 1RM algunos sujetos (n = 5) pudieron realizar 13 repeticiones con una técnica apropiada en el ejercicio press de banca, mientras que otros (n = 20) realizaron significativamente (p < 0:05) más repeticiones al 70% que al 75% de su 1RM en el press de banca. El ínndice de esfuerzo percibido (RPE) parece no ser un buen predictor del 1RM cuando todas las series se realizan al fallo, puesto que no existen diferencias signifiativas (p < 0:05) en el RPE al 75%, 80% y el 90% de la 1RM. Además, los años de experiencia y las horas semanales dedicadas al entrenamiento de fuerza están más correlacionadas con la 1RM (p < 0:05) que el peso corporal. La ecuación de O'Connor et al. parece surgir de los datos recogidos y parece ser la ecuación de predicción de 1RM más precisa de aquellas propuestas en la literatura y empleadas en este estudio. La ecuación de predicción de la 1RM de Epley es reproducida mediante simulación de datos a partir de algunas ecuaciones de predicción de la 1RM propuestas con anterioridad. Finalmente, se proponen futuras líneas de investigación relacionadas con el problema de la predicción de la 1RM mediante algoritmos genéticos, redes neuronales y técnicas de clustering.

Automated detection and classification of brain injury lesions on structural magnetic resonance imaging

El daño cerebral adquirido (DCA) es un problema social y sanitario grave, de magnitud creciente y de una gran complejidad diagnóstica y terapéutica. Su elevada incidencia, junto con el aumento de la supervivencia de los pacientes, una vez superada la fase aguda, lo convierten también en un problema de alta prevalencia. En concreto, según la Organización Mundial de la Salud (OMS) el DCA estará entre las 10 causas más comunes de discapacidad en el año 2020. La neurorrehabilitación permite mejorar el déficit tanto cognitivo como funcional y aumentar la autonomía de las personas con DCA. Con la incorporación de nuevas soluciones tecnológicas al proceso de neurorrehabilitación se pretende alcanzar un nuevo paradigma donde se puedan diseñar tratamientos que sean intensivos, personalizados, monitorizados y basados en la evidencia. Ya que son estas cuatro características las que aseguran que los tratamientos son eficaces. A diferencia de la mayor parte de las disciplinas médicas, no existen asociaciones de síntomas y signos de la alteración cognitiva que faciliten la orientación terapéutica. Actualmente, los tratamientos de neurorrehabilitación se diseñan en base a los resultados obtenidos en una batería de evaluación neuropsicológica que evalúa el nivel de afectación de cada una de las funciones cognitivas (memoria, atención, funciones ejecutivas, etc.). La línea de investigación en la que se enmarca este trabajo de investigación pretende diseñar y desarrollar un perfil cognitivo basado no sólo en el resultado obtenido en esa batería de test, sino también en información teórica que engloba tanto estructuras anatómicas como relaciones funcionales e información anatómica obtenida de los estudios de imagen. De esta forma, el perfil cognitivo utilizado para diseñar los tratamientos integra información personalizada y basada en la evidencia. Las técnicas de neuroimagen representan una herramienta fundamental en la identificación de lesiones para la generación de estos perfiles cognitivos. La aproximación clásica utilizada en la identificación de lesiones consiste en delinear manualmente regiones anatómicas cerebrales. Esta aproximación presenta diversos problemas relacionados con inconsistencias de criterio entre distintos clínicos, reproducibilidad y tiempo. Por tanto, la automatización de este procedimiento es fundamental para asegurar una extracción objetiva de información. La delineación automática de regiones anatómicas se realiza mediante el registro tanto contra atlas como contra otros estudios de imagen de distintos sujetos. Sin embargo, los cambios patológicos asociados al DCA están siempre asociados a anormalidades de intensidad y/o cambios en la localización de las estructuras. Este hecho provoca que los algoritmos de registro tradicionales basados en intensidad no funcionen correctamente y requieran la intervención del clínico para seleccionar ciertos puntos (que en esta tesis hemos denominado puntos singulares). Además estos algoritmos tampoco permiten que se produzcan deformaciones grandes deslocalizadas. Hecho que también puede ocurrir ante la presencia de lesiones provocadas por un accidente cerebrovascular (ACV) o un traumatismo craneoencefálico (TCE). Esta tesis se centra en el diseño, desarrollo e implementación de una metodología para la detección automática de estructuras lesionadas que integra algoritmos cuyo objetivo principal es generar resultados que puedan ser reproducibles y objetivos. Esta metodología se divide en cuatro etapas: pre-procesado, identificación de puntos singulares, registro y detección de lesiones. Los trabajos y resultados alcanzados en esta tesis son los siguientes: Pre-procesado. En esta primera etapa el objetivo es homogeneizar todos los datos de entrada con el objetivo de poder extraer conclusiones válidas de los resultados obtenidos. Esta etapa, por tanto, tiene un gran impacto en los resultados finales. Se compone de tres operaciones: eliminación del cráneo, normalización en intensidad y normalización espacial. Identificación de puntos singulares. El objetivo de esta etapa es automatizar la identificación de puntos anatómicos (puntos singulares). Esta etapa equivale a la identificación manual de puntos anatómicos por parte del clínico, permitiendo: identificar un mayor número de puntos lo que se traduce en mayor información; eliminar el factor asociado a la variabilidad inter-sujeto, por tanto, los resultados son reproducibles y objetivos; y elimina el tiempo invertido en el marcado manual de puntos. Este trabajo de investigación propone un algoritmo de identificación de puntos singulares (descriptor) basado en una solución multi-detector y que contiene información multi-paramétrica: espacial y asociada a la intensidad. Este algoritmo ha sido contrastado con otros algoritmos similares encontrados en el estado del arte. Registro. En esta etapa se pretenden poner en concordancia espacial dos estudios de imagen de sujetos/pacientes distintos. El algoritmo propuesto en este trabajo de investigación está basado en descriptores y su principal objetivo es el cálculo de un campo vectorial que permita introducir deformaciones deslocalizadas en la imagen (en distintas regiones de la imagen) y tan grandes como indique el vector de deformación asociado. El algoritmo propuesto ha sido comparado con otros algoritmos de registro utilizados en aplicaciones de neuroimagen que se utilizan con estudios de sujetos control. Los resultados obtenidos son prometedores y representan un nuevo contexto para la identificación automática de estructuras. Identificación de lesiones. En esta última etapa se identifican aquellas estructuras cuyas características asociadas a la localización espacial y al área o volumen han sido modificadas con respecto a una situación de normalidad. Para ello se realiza un estudio estadístico del atlas que se vaya a utilizar y se establecen los parámetros estadísticos de normalidad asociados a la localización y al área. En función de las estructuras delineadas en el atlas, se podrán identificar más o menos estructuras anatómicas, siendo nuestra metodología independiente del atlas seleccionado. En general, esta tesis doctoral corrobora las hipótesis de investigación postuladas relativas a la identificación automática de lesiones utilizando estudios de imagen médica estructural, concretamente estudios de resonancia magnética. Basándose en estos cimientos, se han abrir nuevos campos de investigación que contribuyan a la mejora en la detección de lesiones. ABSTRACT Brain injury constitutes a serious social and health problem of increasing magnitude and of great diagnostic and therapeutic complexity. Its high incidence and survival rate, after the initial critical phases, makes it a prevalent problem that needs to be addressed. In particular, according to the World Health Organization (WHO), brain injury will be among the 10 most common causes of disability by 2020. Neurorehabilitation improves both cognitive and functional deficits and increases the autonomy of brain injury patients. The incorporation of new technologies to the neurorehabilitation tries to reach a new paradigm focused on designing intensive, personalized, monitored and evidence-based treatments. Since these four characteristics ensure the effectivity of treatments. Contrary to most medical disciplines, it is not possible to link symptoms and cognitive disorder syndromes, to assist the therapist. Currently, neurorehabilitation treatments are planned considering the results obtained from a neuropsychological assessment battery, which evaluates the functional impairment of each cognitive function (memory, attention, executive functions, etc.). The research line, on which this PhD falls under, aims to design and develop a cognitive profile based not only on the results obtained in the assessment battery, but also on theoretical information that includes both anatomical structures and functional relationships and anatomical information obtained from medical imaging studies, such as magnetic resonance. Therefore, the cognitive profile used to design these treatments integrates information personalized and evidence-based. Neuroimaging techniques represent an essential tool to identify lesions and generate this type of cognitive dysfunctional profiles. Manual delineation of brain anatomical regions is the classical approach to identify brain anatomical regions. Manual approaches present several problems related to inconsistencies across different clinicians, time and repeatability. Automated delineation is done by registering brains to one another or to a template. However, when imaging studies contain lesions, there are several intensity abnormalities and location alterations that reduce the performance of most of the registration algorithms based on intensity parameters. Thus, specialists may have to manually interact with imaging studies to select landmarks (called singular points in this PhD) or identify regions of interest. These two solutions have the same inconvenient than manual approaches, mentioned before. Moreover, these registration algorithms do not allow large and distributed deformations. This type of deformations may also appear when a stroke or a traumatic brain injury (TBI) occur. This PhD is focused on the design, development and implementation of a new methodology to automatically identify lesions in anatomical structures. This methodology integrates algorithms whose main objective is to generate objective and reproducible results. It is divided into four stages: pre-processing, singular points identification, registration and lesion detection. Pre-processing stage. In this first stage, the aim is to standardize all input data in order to be able to draw valid conclusions from the results. Therefore, this stage has a direct impact on the final results. It consists of three steps: skull-stripping, spatial and intensity normalization. Singular points identification. This stage aims to automatize the identification of anatomical points (singular points). It involves the manual identification of anatomical points by the clinician. This automatic identification allows to identify a greater number of points which results in more information; to remove the factor associated to inter-subject variability and thus, the results are reproducible and objective; and to eliminate the time spent on manual marking. This PhD proposed an algorithm to automatically identify singular points (descriptor) based on a multi-detector approach. This algorithm contains multi-parametric (spatial and intensity) information. This algorithm has been compared with other similar algorithms found on the state of the art. Registration. The goal of this stage is to put in spatial correspondence two imaging studies of different subjects/patients. The algorithm proposed in this PhD is based on descriptors. Its main objective is to compute a vector field to introduce distributed deformations (changes in different imaging regions), as large as the deformation vector indicates. The proposed algorithm has been compared with other registration algorithms used on different neuroimaging applications which are used with control subjects. The obtained results are promising and they represent a new context for the automatic identification of anatomical structures. Lesion identification. This final stage aims to identify those anatomical structures whose characteristics associated to spatial location and area or volume has been modified with respect to a normal state. A statistical study of the atlas to be used is performed to establish which are the statistical parameters associated to the normal state. The anatomical structures that may be identified depend on the selected anatomical structures identified on the atlas. The proposed methodology is independent from the selected atlas. Overall, this PhD corroborates the investigated research hypotheses regarding the automatic identification of lesions based on structural medical imaging studies (resonance magnetic studies). Based on these foundations, new research fields to improve the automatic identification of lesions in brain injury can be proposed.

Modeling and Simulation of Upper Brachial Plexus Injury

This article presents the first musculoskeletal model and simulation of upper plexus brachial injury. From this model is possible to analyse forces and movement ranges in order to develop a robotic exoskeleton to improve rehabilitation. The software that currently exists for musculoskeletal modeling is varied and most have advanced features for proper analysis and study of motion simulations. Whilst more powerful computer packages are usually expensive, there are other free and open source packages available which offer different tools to perform animations and simulations and which obtain forces and moments of inertia. Among them, Musculoskeletal Modeling Software was selected to construct a model of the upper limb, which has 7 degrees of freedom and 10 muscles. These muscles are important for two of the movements simulated in this article that are part of the post-surgery rehabilitation protocol. We performed different movement animations which are made using the inertial measurement unit to capture real data from movements made by a human being. We also performed the simulation of forces produced in elbow flexion-extension and arm abduction-adduction of a healthy subject and one with upper brachial plexus injury in a postoperative state to compare the force that is capable of being produced in both cases.

Nerve growth factor inhibits sympathetic neurons’ response to an injury cytokine

Axonal damage to adult peripheral neurons causes changes in neuronal gene expression. For example, axotomized sympathetic, sensory, and motor neurons begin to express galanin mRNA and protein, and recent evidence suggests that galanin plays a role in peripheral nerve regeneration. Previous studies in sympathetic and sensory neurons have established that galanin expression is triggered by two consequences of nerve transection: the induction of leukemia inhibitory factor (LIF) and the reduction in the availability of the target-derived factor, nerve growth factor. It is shown in the present study that no stimulation of galanin expression occurs following direct application of LIF to intact neurons in the superior cervical sympathetic ganglion. Injection of animals with an antiserum to nerve growth factor concomitant with the application of LIF, on the other hand, does stimulate galanin expression. The data suggest that the response of neurons to an injury factor, LIF, is affected by whether the neurons still receive trophic signals from their targets.

KDIGO-based acute kidney injury criteria operate differently in hospitals and the community—findings from a large population cohort

ACKNOWLEDGEMENTS We acknowledge the data management support of Grampian Data Safe Haven (DaSH) and the associated financial support of NHS Research Scotland, through NHS Grampian investment in the Grampian DaSH. S.S. is supported by a Clinical Research Training Fellowship from the Wellcome Trust (Ref 102729/Z/13/Z). We also acknowledge the support from The Farr Institute of Health Informatics Research. The Farr Institute is supported by a 10-funder consortium: Arthritis Research UK, the British Heart Foundation, Cancer Research UK, the Economic and Social Research Council, the Engineering and Physical Sciences Research Council, the Medical Research Council, the National Institute of Health Research, the National Institute for Social Care and Health Research (Welsh Assembly Government), the Chief Scientist Office (Scottish Government Health Directorates) and the Wellcome Trust (MRC Grant Nos: Scotland MR/K007017/1).