Network diffusion modeling predicts neurodegeneration in traumatic brain injury

Objective Traumatic brain injury (TBI) is a heterogeneous disease with multiple neurological deficits that evolve over time. It is also associated with an increased incidence of neurodegenerative diseases. Accordingly, clinicians need better tools to predict a patient’s long‐term prognosis. Methods Diffusion‐weighted and anatomical MRI data were collected from 17 adolescents (mean age = 15y8mo) with moderate‐to‐severe TBI and 19 healthy controls. Using a network diffusion model (NDM), we examined the effect of progressive deafferentation and gray matter thinning in young TBI patients. Moreover, using a novel automated inference method, we identified several injury epicenters in order to determine the neural degenerative patterns in each TBI patient. Results We were able to identify the subject‐specific patterns of degeneration in each patient. In particular, the hippocampus, temporal cortices, and striatum were frequently found to be the epicenters of degeneration across the TBI patients. Orthogonal transformation of the predicted degeneration, using principal component analysis, identified distinct spatial components in the temporal–hippocampal network and the cortico‐striatal network, confirming the vulnerability of these networks to injury. The NDM model, best predictive of the degeneration, was significantly correlated with time since injury, indicating that NDM can potentially capture the pathological progression in the chronic phase of TBI. Interpretation These findings suggest that network spread may help explain patterns of distant gray matter thinning, which would be consistent with Wallerian degeneration of the white matter connections (i.e., “diaschisis”) from diffuse axonal injuries and multifocal contusive injuries, and the neurodegenerative patterns of abnormal protein aggregation and transmission, which are hallmarks of brain changes in TBI. NDM approaches could provide highly subject‐specific biomarkers relevant for disease monitoring and personalized therapies in TBI

Individualised profiling of white matter organisation in moderate-to-severe traumatic brain injury patients

Background and purpose Approximately 65% of moderate-to-severe traumatic brain injury (m-sTBI) patients present with poor long-term behavioural outcomes, which can significantly impair activities of daily living. Numerous diffusion-weighted MRI studies have linked these poor outcomes to decreased white matter integrity of several commissural tracts, association fibres and projection fibres in the brain. However, most studies have focused on group-based analyses, which are unable to deal with the substantial between-patient heterogeneity in m-sTBI. As a result, there is increasing interest and need in conducting individualised neuroimaging analyses. Materials and methods Here, we generated a detailed subject-specific characterisation of microstructural organisation of white matter tracts in 5 chronic patients with m-sTBI (29 – 49y, 2 females), presented as a proof-of-concept. We developed an imaging analysis framework using fixel-based analysis and TractLearn to determine whether the values of fibre density of white matter tracts at the individual patient level deviate from the healthy control group (n = 12, 8F, Mage = 35.7y, age range 25 – 64y). Results Our individualised analysis revealed unique white matter profiles, confirming the heterogenous nature of m-sTBI and the need of individualised profiles to properly characterise the extent of injury. Future studies incorporating clinical data, as well as utilising larger reference samples and examining the test–retest reliability of the fixel-wise metrics are warranted. Conclusions Individualised profiles may assist clinicians in tracking recovery and planning personalised training programs for chronic m-sTBI patients, which is necessary to achieve optimal behavioural outcomes and improved quality of life

Machine Fault Detection Based on Filter Bank Similarity Features Using Acoustic and Vibration Analysis

Vibration and acoustic analysis actively support the nondestructive and noninvasive fault diagnostics of rotating machines at early stages. Nonetheless, the acoustic signal is less used because of its vulnerability to external interferences, hindering an efficient and robust analysis for condition monitoring (CM). This paper presents a novel methodology to characterize different failure signatures from rotating machines using either acoustic or vibration signals. Firstly, the signal is decomposed into several narrow-band spectral components applying different filter bank methods such as empirical mode decomposition, wavelet packet transform, and Fourier-based filtering. Secondly, a feature set is built using a proposed similarity measure termed cumulative spectral density index and used to estimate the mutual statistical dependence between each bandwidth-limited component and the raw signal. Finally, a classification scheme is carried out to distinguish the different types of faults. The methodology is tested in two laboratory experiments, including turbine blade degradation and rolling element bearing faults. The robustness of our approach is validated contaminating the signal with several levels of additive white Gaussian noise, obtaining high-performance outcomes that make the usage of vibration, acoustic, and vibroacoustic measurements in different applications comparable. As a result, the proposed fault detection based on filter bank similarity features is a promising methodology to implement in CM of rotating machinery, even using measurements with low signal-to-noise ratio

Multidisciplinary rehabilitation reduces hypothalamic grey matter volume loss in individuals with preclinical Huntington's disease: A nine-month pilot study

Background: Hypothalamic pathology is a well-documented feature of Huntington's disease (HD) and is believed to contribute to circadian rhythm and habitual sleep disturbances. Currently, no therapies exist to combat hypothalamic changes, nor circadian rhythm and habitual sleep disturbances in HD. Objective: To evaluate the effects of multidisciplinary rehabilitation on hypothalamic volume, brain-derived neurotrophic factor (BDNF), circadian rhythm and habitual sleep in individuals with preclinical HD. Methods: Eighteen individuals with HD (ten premanifest and eight prodromal) undertook a nine-month multidisciplinary rehabilitation intervention (intervention group), which included exercise, cognitive and dual task training and social events, and were compared to a community sample of eleven individuals with premanifest HD receiving no intervention (control group). Hypothalamic volume, serum BDNF, salivary cortisol and melatonin concentrations, subjective sleep quality, daytime somnolence, habitual sleep-wake patterns, stress and anxiety and depression symptomatology were evaluated. Results: Hypothalamus grey matter volume loss was significantly attenuated in the intervention group compared to the control group after controlling for age, gender, Unified Huntington's Disease Rating Scale-Total Motor Score and number of cytosine-adenine-guanine repeats. Serum BDNF levels were maintained in the intervention group, but decreased in the control group following the study period. Both groups exhibited decreases in cortisol and melatonin concentrations. No changes were observed in sleep or mood outcomes. Conclusions: This exploratory study provides evidence that multidisciplinary rehabilitation can reduce hypothalamic volume loss and maintain peripheral BDNF levels in individuals with preclinical HD but may not impact on circadian rhythm. Larger, randomised controlled trials are required to confirm these findings

Early-Time Energy Loss in a Strongly-Coupled SYM Plasma

We carry out an analytic study of the early-time motion of a quark in a strongly-coupled maximally-supersymmetric Yang-Mills plasma, using the AdS/CFT correspondence. Our approach extracts the first thermal effects as a small perturbation of the known quark dynamics in vacuum, using a double expansion that is valid for early times and for (moderately) ultrarelativistic quark velocities. The quark is found to lose energy at a rate that differs significantly from the previously derived stationary/late-time result: it scales like T^4 instead of T^2, and is associated with a friction coefficient that is not independent of the quark momentum. Under conditions representative of the quark-gluon plasma as obtained at RHIC, the early energy loss rate is a few times smaller than its late-time counterpart. Our analysis additionally leads to thermally-corrected expressions for the intrinsic energy and momentum of the quark, in which the previously discovered limiting velocity of the quark is found to appear naturally.Comment: 39 pages, no figures. v2: Minor corrections and clarifications. References added. Version to be published in JHE

Measurement of the Lifetime Difference Between B_s Mass Eigenstates

We present measurements of the lifetimes and polarization amplitudes for B_s --> J/psi phi and B_d --> J/psi K*0 decays. Lifetimes of the heavy (H) and light (L) mass eigenstates in the B_s system are separately measured for the first time by determining the relative contributions of amplitudes with definite CP as a function of the decay time. Using 203 +/- 15 B_s decays, we obtain tau_L = (1.05 +{0.16}/-{0.13} +/- 0.02) ps and tau_H = (2.07 +{0.58}/-{0.46} +/- 0.03) ps. Expressed in terms of the difference DeltaGamma_s and average Gamma_s, of the decay rates of the two eigenstates, the results are DeltaGamma_s/Gamma_s = (65 +{25}/-{33} +/- 1)%, and DeltaGamma_s = (0.47 +{0.19}/-{0.24} +/- 0.01) inverse ps.Comment: 8 pages, 3 figures, 2 tables; as published in Physical Review Letters on 16 March 2005; revisions are for length and typesetting only, no changes in results or conclusion

Biotechnological production and application of fructooligosaccharides

Currently, prebiotics are all carbohydrates of relatively short chain length. An important group is the fructooligosaccharides, which are a special kind of prebiotics associated to their selective stimulation of the activity of certain groups of colonic bacteria that have a positive and beneficial effect on intestinal microbiota, reducing incidence of gastrointestinal infections, respiratory and also possessing a recognized bifidogenic effect. Traditionally, these prebiotic compounds have been obtained through extraction processes from some plants, as well as through enzymatic hydrolysis of sucrose. However, different fermentative methods have also been proposed for the production of fructooligosaccharides, such as solid-state fermentation utilizing various agroindustrial by-products. By optimizing the culture parameters, fructooligosaccharides yields and productivity can be improved. The use of immobilized enzymes and cells has also been proposed as being an effective and economic method for large-scale production of fructooligosaccharides. This paper is an overview on the results of recent studies on fructooligosacharides biosynthesis, physicochemical properties, sources, biotechnological production and applications.The authors thank the National Council of Science and Technology of Mexico (CONACYT) for funding this study. D. A. Flores-Maltos thank the CONACYT for the financial support provided for her postgraduate studies in the Food Science and Technology Program, Universidad Autonoma de Coahuila, Mexico

Experimental Characterisation of the Fire Behaviour of Thermal Insulation Materials for a Performance-Based Design Methodology

A novel performance-based methodology for the quantitative fire safe design of building assemblies including insulation materials has recently been proposed. This approach is based on the definition of suitable thermal barriers in order to control the fire hazards imposed by the insulation. Under this framework, the concept of “critical temperature” has been used to define an initiating failure criterion for the insulation, so as to ensure there will be no significant contribution to the fire nor generation of hazardous gas effluents. This paper proposes a methodology to evaluate this “critical temperature” using as examples some of the most common insulation materials used for buildings in the EU market, i.e. rigid polyisocyanurate foam, rigid phenolic foam, rigid expanded polystyrene foam and low density flexible stone wool. A characterisation of these materials, based on a series of ad-hoc Cone Calorimeter and thermo-gravimetric experiments, serves to establish the rationale behind the quantification of the critical temperature. The temperature of the main peak of pyrolysis, obtained from differential thermo-gravimetric analysis under a nitrogen atmosphere at low heating rates, is proposed as the “critical temperature” for materials that do not significantly shrink and melt, i.e. charring insulation materials. For materials with shrinking and melting behaviour it is suggested that the melting point could be used as “critical temperature”. Conservative values of “critical temperature” proposed are 300°C for polyisocyanurate, 425°C for phenolic foam and 240°C for expanded polystyrene. The concept of a “critical temperature” for the low density stone wool is examined in the same manner and found to be non-applicable due to the inability to promote a flammable mixture. Additionally, thermal inertia values required for the performance-based methodology are obtained for PIR and PF using a novel approach, providing thermal inertia values within the range 4.5 to 6.5\ua0×\ua010\ua0W\ua0s\ua0K\ua0m