991 resultados para functional interpretation


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Despite several clinical tests that have been developed to qualitatively describe complex motor tasks by functional testing, these methods often depend on clinicians' interpretation, experience and training, which make the assessment results inconsistent, without the precision required to objectively assess the effect of the rehabilitative intervention. A more detailed characterization is required to fully capture the various aspects of motor control and performance during complex movements of lower and upper limbs. The need for cost-effective and clinically applicable instrumented tests would enable quantitative assessment of performance on a subject-specific basis, overcoming the limitations due to the lack of objectiveness related to individual judgment, and possibly disclosing subtle alterations that are not clearly visible to the observer. Postural motion measurements at additional locations, such as lower and upper limbs and trunk, may be necessary in order to obtain information about the inter-segmental coordination during different functional tests involved in clinical practice. With these considerations in mind, this Thesis aims: i) to suggest a novel quantitative assessment tool for the kinematics and dynamics evaluation of a multi-link kinematic chain during several functional motor tasks (i.e. squat, sit-to-stand, postural sway), using one single-axis accelerometer per segment, ii) to present a novel quantitative technique for the upper limb joint kinematics estimation, considering a 3-link kinematic chain during the Fugl-Meyer Motor Assessment and using one inertial measurement unit per segment. The suggested methods could have several positive feedbacks from clinical practice. The use of objective biomechanical measurements, provided by inertial sensor-based technique, may help clinicians to: i) objectively track changes in motor ability, ii) provide timely feedback about the effectiveness of administered rehabilitation interventions, iii) enable intervention strategies to be modified or changed if found to be ineffective, and iv) speed up the experimental sessions when several subjects are asked to perform different functional tests.

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This contribution investigates the evolution of diet in the Pan – Homo and hominin clades. It does this by focusing on 12 variables (nine dental and three mandibular) for which data are available about extant chimpanzees, modern humans and most extinct hominins. Previous analyses of this type have approached the interpretation of dental and gnathic function by focusing on the identification of the food consumed (i.e. fruits, leaves, etc.) rather than on the physical properties (i.e. hardness, toughness, etc.) of those foods, and they have not specifically addressed the role that the physical properties of foods play in determining dental adaptations. We take the available evidence for the 12 variables, and set out what the expression of each of those variables is in extant chimpanzees, the earliest hominins, archaic hominins, megadont archaic hominins, and an inclusive grouping made up of transitional hominins and pre-modern Homo . We then present hypotheses about what the states of these variables would be in the last common ancestor of the Pan – Homo clade and in the stem hominin. We review the physical properties of food and suggest how these physical properties can be used to investigate the functional morphology of the dentition. We show what aspects of anterior tooth morphology are critical for food preparation (e.g. peeling fruit) prior to its ingestion, which features of the postcanine dentition (e.g. overall and relative size of the crowns) are related to the reduction in the particle size of food, and how information about the macrostructure (e.g. enamel thickness) and microstructure (e.g. extent and location of enamel prism decussation) of the enamel cap might be used to make predictions about the types of foods consumed by extinct hominins. Specifically, we show how thick enamel can protect against the generation and propagation of cracks in the enamel that begin at the enamel– dentine junction and move towards the outer enamel surface.

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Research in autophagy continues to accelerate,(1) and as a result many new scientists are entering the field. Accordingly, it is important to establish a standard set of criteria for monitoring macroautophagy in different organisms. Recent reviews have described the range of assays that have been used for this purpose.(2,3) There are many useful and convenient methods that can be used to monitor macroautophagy in yeast, but relatively few in other model systems, and there is much confusion regarding acceptable methods to measure macroautophagy in higher eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers of autophagosomes versus those that measure flux through the autophagy pathway; thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from fully functional autophagy that includes delivery to, and degradation within, lysosomes (in most higher eukaryotes) or the vacuole (in plants and fungi). Here, we present a set of guidelines for the selection and interpretation of the methods that can be used by investigators who are attempting to examine macroautophagy and related processes, as well as by reviewers who need to provide realistic and reasonable critiques of papers that investigate these processes. This set of guidelines is not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to verify an autophagic response.

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The aim was to investigate the effect of mechanical pain stimulation at the lower back on hemodynamic and oxygenation changes in the prefrontal cortex (PFC) assessed by functional near-infrared spectroscopy (fNIRS) and on the partial pressure of end-tidal carbon dioxide ( PetCO 2) measured by capnography. 13 healthy subjects underwent three measurements (M) during pain stimulation using pressure pain threshold (PPT) at three locations, i.e., the processus spinosus at the level of L4 (M1) and the lumbar paravertebral muscles at the level of L1 on the left (M2) and the right (M3) side. Results showed that only in the M2 condition the pain stimulation elicited characteristic patterns consisting of (1) a fNIRS-derived decrease in oxy- and total hemoglobin concentration and tissue oxygen saturation, an increase in deoxy-hemoglobin concentration, (2) a decrease in the PetCO 2 response and (3) a decrease in coherence between fNIRS parameters and PetCO 2 responses in the respiratory frequency band (0.2-0.5 Hz). We discuss the comparison between M2 vs. M1 and M3, suggesting that the non-significant findings in the two latter measurements were most likely subject to effects of the different stimulated tissues, the stimulated locations and the stimulation order. We highlight that PetCO 2 is a crucial parameter for proper interpretation of fNIRS data in experimental protocols involving pain stimulation. Together, our data suggest that the combined fNIRS-capnography approach has potential for further development as pain monitoring method, such as for evaluating clinical pain treatment.

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Introduction In several studies, we found that during guided rhythmic speech exercises, a decrease in cerebral hemodynamics and oxygenation occurred as the result of a decrease in the partial pressure of carbon dioxide in the arterial blood (PaCO2) during speaking. To further explore the effect of PaCO2 variations on cerebral hemodynamics and oxygenation, the aim of the present study was to investigate the impact of spoken, inner and heard speech tasks on these parameters. Material and Methods Speech tasks included recitation or inner recitation or listening to hexameter, alliteration, prose, or performing mental arithmetic. The following physiological parameters were measured: tissue oxygen saturation (StO2) and absolute concentrations of oxyhemoglobin, deoxyhemoglobin, total hemoglobin (over the left and right anterior prefrontal cortex, using an ISS OxiplexTS frequency domain near-infrared spectrometer) and end-tidal CO2 (PETCO2; using Nellcor N1000 and Datex NORMOCAP capnographs). Statistical analysis was applied to the differences between baseline, 2 tasks, and 3 post-baseline periods. Data of 3 studies with 24, 7 and 29 healthy subjects, respectively, were combined, and linear regression analyses were calculated. Results Linear regression analyses revealed significant relations between changes in oxyhemoglobin, deoxyhemoglobin, total hemoglobin or StO2 and the participants’ age, the baseline PETCO2 or certain speech tasks. While hexameter verses affected changes during the tasks, alliteration verses only affected changes during the recovery phase. Discussion and Conclusion The observed effects in hemodynamics and oxygenation indicate a combination of neurovascular coupling (increased neuronal activity leading to an increase in the cerebral metabolic rate of oxygen resulting in an increase in cerebral flood flow/volume) and CO2 reactivity (increased breathing during speech tasks causing a decrease in PaCO2 leading to vasoconstriction and decrease in cerebral blood flow). The neurovascular coupling characteristics are task-dependent. References Scholkmann F, Gerber U, Wolf M, Wolf U. End-tidal CO2: An important parameter for a correct interpretation in functional brain studies using speech tasks. Neuroimage 2013;66:71-79. Scholkmann F, Wolf M, Wolf U. The effect of inner speech on arterial CO2, cerebral hemodynamics and oxygenation – A functional NIRS study. Adv Exp Med Biol 2013;789:81-87.

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Non-failure analysis aims at inferring that predicate calis in a program will never fail. This type of information has many applications in functional/logic programming. It is essential for determining lower bounds on the computational cost of calis, useful in the context of program parallelization, instrumental in partial evaluation and other program transformations, and has also been used in query optimization. In this paper, we re-cast the non-failure analysis proposed by Debray et al. as an abstract interpretation, which not only allows to investígate it from a standard and well understood theoretical framework, but has also several practical advantages. It allows us to incorpórate non-failure analysis into a standard, generic abstract interpretation engine. The analysis thus benefits from the fixpoint propagation algorithm, which leads to improved information propagation. Also, the analysis takes advantage of the multi-variance of the generic engine, so that it is now able to infer sepárate non-failure information for different cali patterns. Moreover, the implementation is simpler, and allows to perform non-failure and covering analyses alongside other analyses, such as those for modes and types, in the same framework. Finally, besides the precisión improvements and the additional simplicity, our implementation (in the Ciao/CiaoPP multiparadigm programming system) also shows better efRciency.

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An increasing number of neuroimaging studies are concerned with the identification of interactions or statistical dependencies between brain areas. Dependencies between the activities of different brain regions can be quantified with functional connectivity measures such as the cross-correlation coefficient. An important factor limiting the accuracy of such measures is the amount of empirical data available. For event-related protocols, the amount of data also affects the temporal resolution of the analysis. We use analytical expressions to calculate the amount of empirical data needed to establish whether a certain level of dependency is significant when the time series are autocorrelated, as is the case for biological signals. These analytical results are then contrasted with estimates from simulations based on real data recorded with magnetoencephalography during a resting-state paradigm and during the presentation of visual stimuli. Results indicate that, for broadband signals, 50–100 s of data is required to detect a true underlying cross-correlations coefficient of 0.05. This corresponds to a resolution of a few hundred milliseconds for typical event-related recordings. The required time window increases for narrow band signals as frequency decreases. For instance, approximately 3 times as much data is necessary for signals in the alpha band. Important implications can be derived for the design and interpretation of experiments to characterize weak interactions, which are potentially important for brain processing.

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In 10-30% of hypertrophic cardiomyopathy kindreds, the disease is caused by > 29 missense mutations in the cardiac beta-myosin heavy chain (MYH7) gene. The amino acid sequence similarity between chicken skeletal muscle and human beta-cardiac myosin and the three-dimensional structure of the chicken skeletal muscle myosin head have provided the opportunity to examine the structural consequences of these naturally occurring mutations in human beta-cardiac myosin. This study demonstrates that the mutations are related to distinct structural and functional domains. Twenty-four are clustered around four specific locations in the myosin head that are (i) associated with the actin binding interface, (ii) around the nucleotide binding site, (iii) adjacent to the region that connects the two reactive cysteine residues, and (iv) in close proximity to the interface of the heavy chain with the essential light chain. The remaining five mutations are in the myosin rod. The locations of these mutations provide insight into the way they impair the functioning of this molecular motor and also into the mechanism of energy transduction.

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An increasing number of neuroimaging studies are concerned with the identification of interactions or statistical dependencies between brain areas. Dependencies between the activities of different brain regions can be quantified with functional connectivity measures such as the cross-correlation coefficient. An important factor limiting the accuracy of such measures is the amount of empirical data available. For event-related protocols, the amount of data also affects the temporal resolution of the analysis. We use analytical expressions to calculate the amount of empirical data needed to establish whether a certain level of dependency is significant when the time series are autocorrelated, as is the case for biological signals. These analytical results are then contrasted with estimates from simulations based on real data recorded with magnetoencephalography during a resting-state paradigm and during the presentation of visual stimuli. Results indicate that, for broadband signals, 50-100 s of data is required to detect a true underlying cross-correlations coefficient of 0.05. This corresponds to a resolution of a few hundred milliseconds for typical event-related recordings. The required time window increases for narrow band signals as frequency decreases. For instance, approximately 3 times as much data is necessary for signals in the alpha band. Important implications can be derived for the design and interpretation of experiments to characterize weak interactions, which are potentially important for brain processing.

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Advances in the generation and interpretation of proteomics data have spurred a transition from focusing on protein identification to functional analysis. Here we review recent proteomics results that have elucidated new aspects of the roles and regulation of signal transduction pathways in cancer using the epidermal growth factor receptor (EGFR), ERK and breakpoint cluster region (BCR)-ABL1 networks as examples. The emerging theme is to understand cancer signalling as networks of multiprotein machines which process information in a highly dynamic environment that is shaped by changing protein interactions and post-translational modifications (PTMs). Cancerous genetic mutations derange these protein networks in complex ways that are tractable by proteomics.

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The diagnosis and monitoring of ocular disease presents considerable clinical difficulties for two main reasons i) the substantial physiological variation of anatomical structure of the visual pathway and ii) constraints due to technical limitations of diagnostic hardware. These are further confounded by difficulties in detecting early loss or change in visual function due to the masking of disease effects, for example, due to a high degree of redundancy in terms of nerve fibre number along the visual pathway. This thesis addresses these issues across three areas of study: 1. Factors influencing retinal thickness measures and their clinical interpretation As the retina is the principal anatomical site for damage associated with visual loss, objective measures of retinal thickness and retinal nerve fibre layer thickness are key to the detection of pathology. In this thesis the ability of optical coherence tomography (OCT) to provide repeatable and reproducible measures of retinal structure at the macula and optic nerve head is investigated. In addition, the normal physiological variations in retinal thickness and retinal nerve fibre layer thickness are explored. Principal findings were: • Macular retinal thickness and optic nerve head measurements are repeatable and reproducible for normal subjects and diseased eyes • Macular and retinal nerve fibre layer thickness around the optic nerve correlate negatively with axial length, suggesting that larger eyes have thinner retinae, potentially making them more susceptible to damage or disease • Foveola retinal thickness increases with age while retinal nerve fibre layer thickness around the optic nerve head decreases with age. Such findings should be considered during examination of the eye with suspect pathology or in long-term disease monitoring 2. Impact of glucose control on retinal anatomy and function in diabetes Diabetes is a major health concern in the UK and worldwide and diabetic retinopathy is a major cause of blindness in the working population. Objective, quantitative measurements of retinal thickness. particularly at the macula provide essential information regarding disease progression and the efficacy of treatment. Functional vision loss in diabetic patients is commonly observed in clinical and experimental studies and is thought to be affected by blood glucose levels. In the first study of its kind, the short term impact of fluctuations in blood glucose levels on retinal structure and function over a 12 hour period in patients with diabetes are investigated. Principal findings were: • Acute fluctuations in blood glucose levels are greater in diabetic patients than normal subjects • The fluctuations in blood glucose levels impact contrast sensitivity scores. SWAP visual fields, intraocular pressure and diastolic pressure. This effect is similar for type 1 and type 2 diabetic patients despite the differences in their physiological status. • Long-term metabolic control in the diabetic patient is a useful predictor in the fluctuation of contrast sensitivity scores. • Large fluctuations in blood glucose levels and/or visual function and structure may be indicative of an increased risk of development or progression of retinopathy 3. Structural and functional damage of the visual pathway in glaucomatous optic neuropathy The glaucomatous eye undergoes a number of well documented pathological changes including retinal nerve fibre loss and optic nerve head damage which is correlated with loss of functional vision. In experimental glaucoma there is evidence that glaucomatous damage extends from retinal ganglion cells in the eye, along the visual pathway, to vision centres in the brain. This thesis explores the effects of glaucoma on retinal nerve fibre layer thickness, ocular anterior anatomy and cortical structure, and its correlates with visual function in humans. Principal findings were: • In the retina, glaucomatous retinal nerve fibre layer loss is less marked with increasing distance from the optic nerve head, suggesting that RNFL examination at a greater distance than traditionally employed may provide invaluable early indicators of glaucomatous damage • Neuroretinal rim area and retrobulbar optic nerve diameter are strong indicators of visual field loss • Grey matter density decreases at a rate of 3.85% per decade. There was no clear evidence of a disease effect • Cortical activation as measured by fMRI was a strong indicator of functional damage in patients with significant neuroretinal rim loss despite relatively modest visual field defects These investigations have shown that the effects of senescence are evident in both the anterior and posterior visual pathway. A variety of anatomical and functional diagnostic protocols for the investigation of damage to the visual pathway in ocular disease are required to maximise understanding of the disease processes and thereby optimising patient care.

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This study investigates the Spanish indefinite pronoun uno (“one”). After a detailed analysis of its occurrences in authentic language, we find that its interpretation varies depending on the linguistic context. Therefore, we examine which elements of the context - we focus on the broader context, beyond the sentence – have an impact on its interpretation and develop a typology of the indefinite pronoun as to its interpretation. The pronoun may be interpreted as completely generic or specific (referring to the speaker, the listener or a third person). Its interpretation can also be located in an intermediate position between these interpretive extremes.In addition, we compare its use in various discursive genres - spontaneous conversations, academic essays and web forum - which are distinguished by the presence or absence of interactivity and of more or less subjectivity / intersubjectivity. The comparison shows that pronoun use depends on these characteristics.

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Objective: Real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback (NF) uses feedback of the patient’s own brain activity to self-regulate brain networks which in turn could lead to a change in behaviour and clinical symptoms. The objective was to determine the effect of neurofeedback and motor training and motor training (MOT) alone on motor and non-motor functions in Parkinson’s disease (PD) in a 10-week small Phase I randomised controlled trial. Methods: 30 patients with PD (Hoehn & Yahr I-III) and no significant comorbidity took part in the trial with random allocation to two groups. Group 1 (NF: 15 patients) received rt-fMRI-NF with motor training. Group 2 (MOT: 15 patients) received motor training alone. The primary outcome measure was the Movement Disorder Society – Unified Parkinson’s Disease Rating Scale-Motor scale (MDS-UPDRS-MS), administered pre- and post-intervention ‘off-medication’. The secondary outcome measures were the ‘on-medication’ MDS-UPDRS, the Parkinson’s disease Questionnaire-39, and quantitative motor assessments after 4 and 10 weeks. Results: Patients in the NF group were able to upregulate activity in the supplementary motor area by using motor imagery. They improved by an average of 4.5 points on the MDS-UPDRS-MS in the ‘off-medication’ state (95% confidence interval: -2.5 to -6.6), whereas the MOT group improved only by 1.9 points (95% confidence interval +3.2 to -6.8). However, the improvement did not differ significantly between the groups. No adverse events were reported in either group. Interpretation: This Phase I study suggests that NF combined with motor training is safe and improves motor symptoms immediately after treatment, but larger trials are needed to explore its superiority over active control conditions. Clinical Trial website : Unique Identifier: NCT01867827 URL: https://clinicaltrials.gov/ct2/show/NCT01867827?term=NCT01867827&rank=1

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Single-cell functional proteomics assays can connect genomic information to biological function through quantitative and multiplex protein measurements. Tools for single-cell proteomics have developed rapidly over the past 5 years and are providing unique opportunities. This thesis describes an emerging microfluidics-based toolkit for single cell functional proteomics, focusing on the development of the single cell barcode chips (SCBCs) with applications in fundamental and translational cancer research.

The microchip designed to simultaneously quantify a panel of secreted, cytoplasmic and membrane proteins from single cells will be discussed at the beginning, which is the prototype for subsequent proteomic microchips with more sophisticated design in preclinical cancer research or clinical applications. The SCBCs are a highly versatile and information rich tool for single-cell functional proteomics. They are based upon isolating individual cells, or defined number of cells, within microchambers, each of which is equipped with a large antibody microarray (the barcode), with between a few hundred to ten thousand microchambers included within a single microchip. Functional proteomics assays at single-cell resolution yield unique pieces of information that significantly shape the way of thinking on cancer research. An in-depth discussion about analysis and interpretation of the unique information such as functional protein fluctuations and protein-protein correlative interactions will follow.

The SCBC is a powerful tool to resolve the functional heterogeneity of cancer cells. It has the capacity to extract a comprehensive picture of the signal transduction network from single tumor cells and thus provides insight into the effect of targeted therapies on protein signaling networks. We will demonstrate this point through applying the SCBCs to investigate three isogenic cell lines of glioblastoma multiforme (GBM).

The cancer cell population is highly heterogeneous with high-amplitude fluctuation at the single cell level, which in turn grants the robustness of the entire population. The concept that a stable population existing in the presence of random fluctuations is reminiscent of many physical systems that are successfully understood using statistical physics. Thus, tools derived from that field can probably be applied to using fluctuations to determine the nature of signaling networks. In the second part of the thesis, we will focus on such a case to use thermodynamics-motivated principles to understand cancer cell hypoxia, where single cell proteomics assays coupled with a quantitative version of Le Chatelier's principle derived from statistical mechanics yield detailed and surprising predictions, which were found to be correct in both cell line and primary tumor model.

The third part of the thesis demonstrates the application of this technology in the preclinical cancer research to study the GBM cancer cell resistance to molecular targeted therapy. Physical approaches to anticipate therapy resistance and to identify effective therapy combinations will be discussed in detail. Our approach is based upon elucidating the signaling coordination within the phosphoprotein signaling pathways that are hyperactivated in human GBMs, and interrogating how that coordination responds to the perturbation of targeted inhibitor. Strongly coupled protein-protein interactions constitute most signaling cascades. A physical analogy of such a system is the strongly coupled atom-atom interactions in a crystal lattice. Similar to decomposing the atomic interactions into a series of independent normal vibrational modes, a simplified picture of signaling network coordination can also be achieved by diagonalizing protein-protein correlation or covariance matrices to decompose the pairwise correlative interactions into a set of distinct linear combinations of signaling proteins (i.e. independent signaling modes). By doing so, two independent signaling modes – one associated with mTOR signaling and a second associated with ERK/Src signaling have been resolved, which in turn allow us to anticipate resistance, and to design combination therapies that are effective, as well as identify those therapies and therapy combinations that will be ineffective. We validated our predictions in mouse tumor models and all predictions were borne out.

In the last part, some preliminary results about the clinical translation of single-cell proteomics chips will be presented. The successful demonstration of our work on human-derived xenografts provides the rationale to extend our current work into the clinic. It will enable us to interrogate GBM tumor samples in a way that could potentially yield a straightforward, rapid interpretation so that we can give therapeutic guidance to the attending physicians within a clinical relevant time scale. The technical challenges of the clinical translation will be presented and our solutions to address the challenges will be discussed as well. A clinical case study will then follow, where some preliminary data collected from a pediatric GBM patient bearing an EGFR amplified tumor will be presented to demonstrate the general protocol and the workflow of the proposed clinical studies.