Mozarab Perseverance of Identity and Faith amid Islam

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Localization of zinc transporter-3 (ZnT-3) in mouse retina

AbstractStudies of the central nervous system have localized the zinc-transporter-3 (ZnT-3) protein to synaptic vesicles containing glutamate and zinc. We have examined the distribution of the ZnT-3 protein in the light-adapted mouse retina using immunohistochemical techniques. Light microscopic analysis of 15–30-μm retinal sections revealed a rich band of ZnT-3 protein in the region of the outer limiting membrane and photoreceptor inner segments. ZnT-3 reactivity was also present in the outer plexiform, inner nuclear, inner plexiform, and ganglion cell layers. The outer nuclear layer and photoreceptor outer segments did not exhibit ZnT-3 immunoreactivity. In the light-adapted murine retina, ZnT-3 appears localized in regions which have been found reactive for ionic zinc

Potassium currents distinguish the two subtypes of morphologically distinct skate bipolar cells

Author Posting. © Marine Biological Laboratory, 2004. This article is posted here by permission of Marine Biological Laboratory for personal use, not for redistribution. The definitive version was published in Biological Bulletin 207 (2004): 191-194.Bipolar cells in the vertebrate retina are second-order neurons that convey visual information from photoreceptors to ganglion cells, the neurons that relay the message to the brain. Bipolar cells consist typically of multiple subtypes that differ in their morphology, synaptic connections, and response properties. The individual subtypes are thought to carry different aspects of the visual signal through the retina, and they often exhibit unique membrane properties and neurotransmitter receptors. In the all-rod skate retina, only two morphologically and pharmacologically distinct subtypes of bipolar cell have been identified thus far. The large-field bipolar cells, with extensive dendritic arbors, are glycine-insensitive, whereas the small-field bipolar cells, which have only one or two dendritic branches, are sensitive to glycine. In the present study, we explored further the membrane properties of these two subtypes of skate bipolar cell with emphasis on the voltage-sensitive potassium currents. Our results show that the cells exhibit different voltage-activated current profiles, suggesting that the signals they transmit contain different features of the visual scene.This study was supported in part by NIH Grant EY-12028 (HQ); Fight for Sight, PSC/CUNY Grant 66257-0035, and NCRR/NIH RCMI Award RR-03037 (RLC); NIH Grant EY-06516 and a Senior Research Investigator Award from Research to Prevent Blindness (HR)

Reprint of “Pharmacokinetic modelling of the anti-malarial drug artesunate and its active metabolite dihydroartemisinin”

A four compartment mechanistic mathematical model is developed for the pharmacokinetics of the commonly used anti-malarial drug artesunate and its principle metabolite dihydroartemisinin following oral administration of artesunate. The model is structurally unidentifiable unless additional constraints are imposed. Combinations of mechanistically derived constraints are considered to assess their effects on structural identifiability and on model fits. Certain combinations of the constraints give rise to locally or globally identifiable model structures. Initial validation of the model under various combinations of the constraints leading to identifiable model structures was performed against a dataset of artesunate and dihydroartemisinin concentration–time profiles of 19 malaria patients. When all the discussed constraints were imposed on the model, the resulting globally identifiable model structure was found to fit reasonably well to those patients with normal drug absorption profiles. However, there is wide variability in the fitted parameters and further investigation is warranted

Modelling of pH dynamics in brain cells after stroke

The identification of salvageable brain tissue is a major challenge at stroke presentation. Standard techniques used in this context, such as the perfusion–diffusion mismatch, remain controversial. There is thus a need for new methods to help guide treatment. The potential role of pH imaging in this context is currently being investigated. Intracellular pH varies as a function of local perfusion, intracellular energy stores and time. Low pH triggers the production of free radicals and affects the calcium balance of the cells, which may lead to apoptosis and cell death. Thus, the characterization of pH dynamics may have predictive value for cell death after stroke, particularly when combined with novel imaging techniques. Therefore, we have extended an existing model of brain cellular metabolism to simulate the pH response of cells to ischaemia. Simulation results for conditions of reduced cerebral blood flow show good agreement for the evolution of intracellular pH with previously reported measurements and encourage the development of quantitative pH imaging to validate the predictive value of pH

Association between Striatal Brain Iron Deposition, Microbleeds and Cognition 1 Year After a Minor Ischaemic Stroke

Brain iron deposits (IDs) are inversely associated with cognitive function in community-dwelling older people, but their association with cognition after ischemic stroke, and whether that differs from microbleeds, is unknown. We quantified basal ganglia IDs (BGID) and microbleeds (BMBs) semi-automatically on brain magnetic resonance images from patients with minor stroke (NIHSS < 7), at presentation and 12 months after stroke. We administered the National Adult Reading Test (NART, estimates premorbid or peak adult cognition) and the Revised Addenbrooke’s Cognitive Examination (ACE-R; current cognition) at 1 and 12 months after stroke. We adjusted analyses for baseline cognition, age, gender, white matter hyperintensity (WMH) volume and vascular risk factors. In 200 patients, mean age 65 years, striatal IDs and BMBs volumes did not change over the 12 months. Baseline BGID volumes correlated positively with NART scores at both times (ρ = 0.19, p < 0.01). Baseline and follow-up BGID volumes correlated positively with age (ρ = 0.248, p < 0.001 and ρ = 0.271, p < 0.001 respectively), but only baseline (and not follow-up) BMB volume correlated with age (ρ = 0.129, p < 0.05). Both smoking and baseline WMH burden predicted verbal fluency and visuospatial abilities scores (B = −1.13, p < 0.02 and B = −0.22, p = 0.001 respectively) at 12 months after stroke. BGIDs and BMBs are associated differently with cognition post-stroke; studies of imaging and post-stroke cognition should adjust for premorbid cognition. The positive correlation of BGID with NART may reflect the lower premorbid cognition in patients with stroke at younger vs older ages

The visualisation of fingermarks on Pangolin scales using gelatine lifters

Recent media reports document the plight of the Pangolin and its current position as “the most trafficked mammal in the world”. They are described by some as scaly anteaters as all species are covered in hard keratinous tissue in the form of overlapping scales acting as a “flexible dermal armour”. It is estimated that between 2011 and 2013, 117,000–234,000 pangolins were slaughtered, but the seizures may only represent as little as 10% of the true volume of pangolins being illegally traded. In this paper, methods to visualise fingermarks on Pangolin scales using gelatine lifters is presented. The gelatine lifters provide an easy to use, inexpensive but effective method to help wildlife crime rangers across Africa and Asia to disrupt the trafficking. The gelatine lifting process visualised marks producing clear ridge detail on 52% of the Pangolin scales examined, with a further 30% showing the impression of a finger with limited ridge detail. The paper builds on an initial sociotechnical approach to establishing requirement, then it focuses on the methods and outcomes relating to lifting fingermarks off Pangolin scales using gelatine lifters, providing an evaluation of its use in practice

Co-producing Justice : International Social Economy Network Programme Report

While the significance of employment to desistance (giving up crime) is well established, there are multifarious obstacles to people with convictions accessing and sustaining work. Social enterprises are businesses that trade for a social purpose, rather than for the enrichment of shareholders or owners. It has been shown that social enterprise and cooperative structures of employment can circumnavigate some of the systemic obstacles to employment, such as criminal records and employer discrimination that people routinely encounter. Yet, one in six people in the UK have a criminal conviction; a large proportion of people are, therefore, affected by the impacts that contact with the justice system has on access to employment and, relatedly, opportunities to move on from offending. The House of Commons Work and Pensions Committee (2016) recognise that employment significantly reduces reoffending and can lead to other outcomes that can reduce reoffending (e.g. financial security and stable accommodation). The Scottish Government (2016) has recently co-produced, with the social enterprise sector, a ten-year Strategy to encourage the further development of the sector and contribute to an overarching ‘inclusive growth’ agenda, demonstrating considerable appetite for an evidence-informed approach for this demographic. Despite this, not only are such structures providing paid work a rarity in the UK justice system, the potential of social enterprises and co-operatives in this context has hardly been explored. Recent research (Roy et al., 2017; Weaver 2016; forthcoming) provides important evidence to suggest their potential to support desistance, recovery and integration; this project sought to build on this by exploring approaches to their implementation, connecting a range of multi-disciplinary international and local experts who can differently contribute towards their realisation. By combining these largely disconnected strands of research, siloed within specific disciplines, our aim has been to advance a more coherent interdisciplinary theorizing and exploration of the interactions, synergies and distinctions in these disciplinary fields and to influence the direction of future research, policy and practice in justice contexts

Reliability of an automatic classifier for brain enlarged perivascular spaces burden and comparison with human performance

pp. 1465-1481En el cerebro, los espacios perivasculares agrandados (PVS) se relacionan con la enfermedad de los vasos pequeños (SVD), mala cognición, inflamación e hipertensión. Proponemos un esquema totalmente automático que utiliza una máquina de vectores de soporte (SVM) para clasificar la carga de PVS en los ganglios basales (BG) como baja o alta. Evaluamos el rendimiento de tres tipos diferentes de descriptores extraídos de la región BG en imágenes de RMN ponderadas en T2: (I) estadísticas obtenidas de los coeficientes de la transformada de Wavelet, (II) patrones binarios locales y (III) bolsa de palabras visuales (BoW), descriptores basados en la caracterización de claves locales obtenidas de una rejilla densa con las características de transformación de la función de escala-invariante (SIFT). Cuando se utilizaron estos últimos, el SVM clasificador alcanzó la mejor precisión (81,16%). Lo obtenido del clasificador utilizando los descriptores del BoW se comparó con las calificaciones visuales realizadas por un neurorradiólogo experimentado (observador 1) y por un analista de imágenes entrenado (observador 2). El acuerdo y la correlación cruzada entre el clasificador y el observador 2 (κ = 0,67 (0,58 – 0,76)) fueron ligeramente más altos que entre el clasificador y el observador 1 (κ = 0,62 (0,53 – 0,72)) y entre ambos observadores (κ = 0,68 (0,61 – 0,75)). Por último, se construyeron tres modelos de regresión logística que utilizan variables clínicas como variable independiente y cada una de las clasificaciones de PVS como variable dependiente, para evaluar clínicamente lo significativas que resultan las predicciones del clasificador. El ajuste del modelo para el clasificador era bueno (área bajo la curva (AUC) valores: 0,93 (modelo 1), 0,90 (modelo 2) y 0,92 (modelo 3)) y un poco mejor (es decir, valores de AUC: 0,02 unidades superiores) que las del modelo para el observador 2. Estos resultados sugieren que, aunque se puede mejorar, un clasificador automático para evaluar la carga de PVS de la resonancia magnética del cerebro puede proporcionar resultados clínicamente significativos cercanos a los de un observador entrenado.S