Test of a model of the effects of parental illness on youth and family functioning

Objective: Parental illness (PI) may have adverse impacts on youth and family functioning. Research in this area has suffered from the absence of a guiding comprehensive framework. This study tested a conceptual model of the effects of PI on youth and family functioning derived from the Family Ecology Framework (FEF; Pedersen & Revenson, 2005). Method. A total of 85 parents with multiple sclerosis and 127 youth completed questionnaires at Time 1 and 12 months later at Time 2. Results. Structural equation modeling results supported the FEF with regards to physical-illness disability. Specifically, the proposed mediators (role redistribution, stress, and stigma) were implicated in the processes that link parental disability to several domains of youth adjustment. The results suggest that the effects of parental depression (PD) are not mediated through these processes; rather, PD directly affects family functioning, which in turn mediates the effects onto youth adjustment. Family functioning further mediated between PD and youth well-being and behavioral-social difficulties. Conclusions. Although results support the effects of parental-illness disability on youth and family functioning via the proposed mediational mechanisms, the additive effects of PD on youth physical and mental health occur through direct and indirect (via family functioning) pathways, respectively.

Serum YKL-40 and Interleukin 6 Levels in Hodgkin Lymphoma

Purpose Serum levels of the inflammatory markers YKL-40 and IL-6 are increased in many conditions, including cancers. We examined serum YKL-40 and IL-6 levels in patients with Hodgkin lymphoma (HL), a tumor with strong immunologic reaction to relatively few tumor cells, especially in nodular sclerosis HL. Experimental Design We analyzed Danish and Swedish patients with incident HL (N=470) and population controls from Denmark (N= 245 for YKL-40; N= 348 for IL-6). Serum YKL-40 and IL-6 levels were determined by ELISA, and log-transformed data were analysed by linear regression, adjusting for age and sex. Results Serum levels of YKL-40 and IL-6 were increased in HL patients compared to controls (YKL-40: 3.6-fold, IL-6: 8.3-fold; both p<0.0001). In samples from pre-treatment HL patients (N=176), levels were correlated with more advanced stages (ptrend 0.0001 for YKL-40 and 0.013 for IL-6) and in those with B symptoms, but levels were similar in nodular sclerosis and mixed cellularity subtypes, by EBV status, and in younger (<45 years old) and older patients. Patients tested soon after treatment onset had significantly lower levels than pre-treatment patients, but even >6 months after treatment onset, serum YKL-40 and IL-6 levels remained significantly increased, compared to controls. In patients who died (N=12), pre-treatment levels for both YKL-40 and IL-6 were higher than in survivors, although not statistically significantly. Conclusions Serum YKL-40 and IL-6 levels were increased in untreated HL patients and those with more advanced stages but did not differ significantly by HL histology. Following treatment, serum levels were significantly lower.

Myoinositol Abnormalities in Temporal Lobe Epilepsy

Purpose: This study used magnetic resonance spectroscopy (MRS) to examine metabolite abnormalities in the temporal and frontal lobe of patients with temporal lobe epilepsy (TLE) of differing severity. Methods: We investigated myoinositol in TLE by using short-echo MRS in 34 TLE patients [26 late onset (LO-TLE), eight hippocampal sclerosis (HS-TLE)], and 16 controls. Single-voxel short-echo (35 ms) MR spectra of temporal and frontal lobes were acquired at 1.5 T and analyzed by using LCModel. Results: The temporal lobe ipsilateral to seizure origin in HS-TLE, but not LO-TLE, had reduced N-acetylaspartate (NA) and elevated myoinositol (MI; HS-TLE NA, 7.8 ± 1.9 mM, control NA, 9.2 ± 1.3 mM; p < 0.05; HS-TLE MI, 6.1 ± 1.6 mM, control mI 4.9 ± 0.8 mM, p< 0.05). Frontal lobe MI was low in both patient groups (LO-TLE, 4.3 ± 0.8 mM; p < 0.05; HS-TLE, 3.6 ±.05 mM; p < 0.001; controls, 4.8 ± 0.5 mM). Ipsilateral frontal lobes had lower MI (3.8 ± 0.7 mM; p < 0.01) than contralateral frontal lobes (4.3 ± 0.8 mM; p < 0.05). Conclusions: MI changes may distinguish between the seizure focus, where MI is increased, and areas of seizure spread where MI is decreased.

The relationship between Bayesian motor unit number estimation and histological measurements of motor neurons in wild-type and SOD1 G93A mice

Objective: To assess the relationship between Bayesian MUNE and histological motor neuron counts in wild-type mice and in an animal model of ALS. Methods: We performed Bayesian MUNE paired with histological counts of motor neurons in the lumbar spinal cord of wild-type mice and transgenic SOD1 G93A mice that show progressive weakness over time. We evaluated the number of acetylcholine endplates that were innervated by a presynaptic nerve. Results: In wild-type mice, the motor unit number in the gastrocnemius muscle estimated by Bayesian MUNE was approximately half the number of motor neurons in the region of the spinal cord that contains the cell bodies of the motor neurons supplying the hindlimb crural flexor muscles. In SOD1 G93A mice, motor neuron numbers declined over time. This was associated with motor endplate denervation at the end-stage of disease. Conclusion: The number of motor neurons in the spinal cord of wild-type mice is proportional to the number of motor units estimated by Bayesian MUNE. In SOD1 G93A mice, there is a lower number of estimated motor units compared to the number of spinal cord motor neurons at the end-stage of disease, and this is associated with disruption of the neuromuscular junction. Significance: Our finding that the Bayesian MUNE method gives estimates of motor unit numbers that are proportional to the numbers of motor neurons in the spinal cord supports the clinical use of Bayesian MUNE in monitoring motor unit loss in ALS patients. © 2012 International Federation of Clinical Neurophysiology.

Marginal reversible jump Markov chain Monte Carlo with application to motor unit number estimation

Motor unit number estimation (MUNE) is a method which aims to provide a quantitative indicator of progression of diseases that lead to loss of motor units, such as motor neurone disease. However the development of a reliable, repeatable and fast real-time MUNE method has proved elusive hitherto. Ridall et al. (2007) implement a reversible jump Markov chain Monte Carlo (RJMCMC) algorithm to produce a posterior distribution for the number of motor units using a Bayesian hierarchical model that takes into account biological information about motor unit activation. However we find that the approach can be unreliable for some datasets since it can suffer from poor cross-dimensional mixing. Here we focus on improved inference by marginalising over latent variables to create the likelihood. In particular we explore how this can improve the RJMCMC mixing and investigate alternative approaches that utilise the likelihood (e.g. DIC (Spiegelhalter et al., 2002)). For this model the marginalisation is over latent variables which, for a larger number of motor units, is an intractable summation over all combinations of a set of latent binary variables whose joint sample space increases exponentially with the number of motor units. We provide a tractable and accurate approximation for this quantity and also investigate simulation approaches incorporated into RJMCMC using results of Andrieu and Roberts (2009).

Neurological drugs and opioids for pain management

20.1 Epilepsy and an introduction to drugs used to treat 20.1.1 Introduction to epilepsy 20.1.2 Treatment of partial seizures 20.1.3 Treatment of generalised seizures 20.1.4 Treatment of status epilepticus 20.2 Neurodegenerative disorders; principles of treatment 20.2.1 Introduction to neurodegenerative disorders 20.2.2 Parkinson’s disease 20.2.2.1 Introduction to Parkinson’s disease 20.2.2.2 Dopaminergic system 20.2.2.3 Treatment to enhance the dopaminergic system 20.2.2.4 Treatment to inhibit the cholinergic system 20.2.3 Dementia/Alzheimer’s disease 20.2.3.1 Introduction to Alzheimer’s disease 20.2.3.2 Treatment of Alzheimer’s disease 20.2.4 Amyotrophic lateral sclerosis 43.4.1 Introduction 43.4.2 Treatment 20.3. Pain and opioid analgesics 20.3.1 Introduction to pain and analgesia 20.3.2 Introduction to opioids 20.3.3 Tolerance and physical dependence 20.3.4 Effects of opioids 20.3.5 Agonists at opioid μ receptors 20.3.6 Toxicity to opioids This section deals with the neurologic drugs. The neurologic drugs are used to treat epilepsy and neurodegenerative diseases such as Parkinson’s disease and Alzheimer’s disease. The opioids for pain management are also discussed in this section.

Prenatal Vitamin D deficiency induces an early and more severe experimental autoimmune encephalomyelitis in the second generation

In a previous study, we demonstrated that mouse adult F(1) offspring, exposed to a vitamin d deficiency during pregnancy, developed a less severe and delayed Experimental Autoimmune Encephalomyelitis (EAE), when compared with control offspring. We then wondered whether a similar response was observed in the subsequent generation. To answer this question, we assessed F(2) females whose F(1) parents (males or females) were vitamin d-deprived when developing in the uterus of F(0) females. Unexpectedly, we observed that the vitamin d deficiency affecting the F(0) pregnant mice induced a precocious and more severe EAE in the F(2) generation. This paradoxical finding led us to assess its implications for the epidemiology of Multiple Sclerosis (MS) in humans. Using the REFGENSEP database for MS trios (the patient and his/her parents), we collected the parents' dates of birth and assessed a potential season of birth effect that could potentially be indicative of the vitamin d status of the pregnant grandmothers. A trend for a reduced number of births in the Fall for the parents of MS patients was observed but statistical significance was not reached. Further well powered studies are warranted to validate the latter finding.

Bayesian algorithms with applications

Advances in algorithms for approximate sampling from a multivariable target function have led to solutions to challenging statistical inference problems that would otherwise not be considered by the applied scientist. Such sampling algorithms are particularly relevant to Bayesian statistics, since the target function is the posterior distribution of the unobservables given the observables. In this thesis we develop, adapt and apply Bayesian algorithms, whilst addressing substantive applied problems in biology and medicine as well as other applications. For an increasing number of high-impact research problems, the primary models of interest are often sufficiently complex that the likelihood function is computationally intractable. Rather than discard these models in favour of inferior alternatives, a class of Bayesian "likelihoodfree" techniques (often termed approximate Bayesian computation (ABC)) has emerged in the last few years, which avoids direct likelihood computation through repeated sampling of data from the model and comparing observed and simulated summary statistics. In Part I of this thesis we utilise sequential Monte Carlo (SMC) methodology to develop new algorithms for ABC that are more efficient in terms of the number of model simulations required and are almost black-box since very little algorithmic tuning is required. In addition, we address the issue of deriving appropriate summary statistics to use within ABC via a goodness-of-fit statistic and indirect inference. Another important problem in statistics is the design of experiments. That is, how one should select the values of the controllable variables in order to achieve some design goal. The presences of parameter and/or model uncertainty are computational obstacles when designing experiments but can lead to inefficient designs if not accounted for correctly. The Bayesian framework accommodates such uncertainties in a coherent way. If the amount of uncertainty is substantial, it can be of interest to perform adaptive designs in order to accrue information to make better decisions about future design points. This is of particular interest if the data can be collected sequentially. In a sense, the current posterior distribution becomes the new prior distribution for the next design decision. Part II of this thesis creates new algorithms for Bayesian sequential design to accommodate parameter and model uncertainty using SMC. The algorithms are substantially faster than previous approaches allowing the simulation properties of various design utilities to be investigated in a more timely manner. Furthermore the approach offers convenient estimation of Bayesian utilities and other quantities that are particularly relevant in the presence of model uncertainty. Finally, Part III of this thesis tackles a substantive medical problem. A neurological disorder known as motor neuron disease (MND) progressively causes motor neurons to no longer have the ability to innervate the muscle fibres, causing the muscles to eventually waste away. When this occurs the motor unit effectively ‘dies’. There is no cure for MND, and fatality often results from a lack of muscle strength to breathe. The prognosis for many forms of MND (particularly amyotrophic lateral sclerosis (ALS)) is particularly poor, with patients usually only surviving a small number of years after the initial onset of disease. Measuring the progress of diseases of the motor units, such as ALS, is a challenge for clinical neurologists. Motor unit number estimation (MUNE) is an attempt to directly assess underlying motor unit loss rather than indirect techniques such as muscle strength assessment, which generally is unable to detect progressions due to the body’s natural attempts at compensation. Part III of this thesis builds upon a previous Bayesian technique, which develops a sophisticated statistical model that takes into account physiological information about motor unit activation and various sources of uncertainties. More specifically, we develop a more reliable MUNE method by applying marginalisation over latent variables in order to improve the performance of a previously developed reversible jump Markov chain Monte Carlo sampler. We make other subtle changes to the model and algorithm to improve the robustness of the approach.

The AusD Study: A population-based study of the determinants of serum 25-hydroxyvitamin D concentration across a broad latitude range

Observational studies suggest that people with a high serum 25-hydroxyvitamin D (25(OH)D) concentration may have reduced risk of chronic diseases such as osteoporosis, multiple sclerosis, type 1 diabetes, cardiovascular disease, and some cancers. The AusD Study (A Quantitative Assessment of Solar UV Exposure for Vitamin D Synthesis in Australian Adults) was conducted to clarify the relationships between ultraviolet (UV) radiation exposure, dietary intake of vitamin D, and serum 25(OH)D concentration among Australian adults residing in Townsville (19.3°S), Brisbane (27.5°S), Canberra (35.3°S), and Hobart (42.8°S). Participants aged 18-75 years were recruited from the Australian Electoral Roll between 2009 and 2010. Measurements were made of height, weight, waist:hip ratio, skin, hair, and eye color, blood pressure, and grip strength. Participants completed a questionnaire on sun exposure and vitamin D intake, together with 10 days of personal UV dosimetry and an associated sun-exposure and physical-activity diary that was temporally linked to a blood test for measurement of 25(OH)D concentration. Ambient solar UV radiation was also monitored at all study sites. We collected comprehensive, high-quality data from 1,002 participants (459 males, 543 females) assessed simultaneously across a range of latitudes and through all seasons. Here we describe the scientific and methodological issues considered in designing the AusD Study.

No association between MTHFR A1298C and MTRR A66G polymorphisms, and MS in an Australian cohort

Multiple sclerosis (MS) is a complex neurological disease that affects the central nervous system (CNS) resulting in debilitating neuropathology. Pathogenesis is primarily defined by CNS inflammation and demyelination of nerve axons. Methionine synthase reductase (MTRR) is an enzyme that catalyzes the remethylation of homocysteine (Hcy) to methionine via cobalamin and folate dependant reactions. Cobalamin acts as an intermediate methyl carrier between methylenetetrahydrofolate reductase (MTHFR) and Hcy. MTRR plays a critical role in maintaining cobalamin in an active form and is consequently an important determinant of total plasma Hcy (pHcy) concentrations. Elevated intracellular pHcy levels have been suggested to play a role in CNS dysfunction, neurodegenerative, and cerebrovascular diseases. Our investigation entailed the genotyping of a cohort of 140 cases and matched controls for MTRR and MTHFR, by restriction length polymorphism (RFLP) techniques. Two polymorphisms: MTRR A66G and MTHFR A1298C were investigated in an Australian age and gender matched case-control study. No significant allelic frequency difference was observed between cases and controls at the α = 0.05 level (MTRR χ2 = 0.005, P = 0.95, MTHFR χ2 = 1.15, P = 0.28). Our preliminary findings suggest no association between the MTRR A66G and MTHFR A1298C polymorphisms and MS

Saliva-derived DNA performs well in large-scale, high-density single-nucleotide polymorphism microarray studies

As of June 2009, 361 genome-wide association studies (GWAS) had been referenced by the HuGE database. GWAS require DNA from many thousands of individuals, relying on suitable DNA collections. We recently performed a multiple sclerosis (MS) GWAS where a substantial component of the cases (24%) had DNA derived from saliva. Genotyping was done on the Illumina genotyping platform using the Infinium Hap370CNV DUO microarray. Additionally, we genotyped 10 individuals in duplicate using both saliva- and blood-derived DNA. The performance of blood- versus saliva-derived DNA was compared using genotyping call rate, which reflects both the quantity and quality of genotyping per sample and the “GCScore,” an Illumina genotyping quality score, which is a measure of DNA quality. We also compared genotype calls and GCScores for the 10 sample pairs. Call rates were assessed for each sample individually. For the GWAS samples, we compared data according to source of DNA and center of origin. We observed high concordance in genotyping quality and quantity between the paired samples and minimal loss of quality and quantity of DNA in the saliva samples in the large GWAS sample, with the blood samples showing greater variation between centers of origin. This large data set highlights the usefulness of saliva DNA for genotyping, especially in high-density single-nucleotide polymorphism microarray studies such as GWAS.

Understanding chronic pain complicating disability: Finding meaning through focus group methodology

Over the past few decades a major paradigm shift has occurred in the conceptualisation of chronic pain as a complex multidimensional phenomenon. Yet, pain experienced by individuals with a primary disability continues to be understood largely from a traditional biomedical model, despite its inherent limitations. This is reflected in the body of literature on the topic that is primarily driven by positivist assumptions and the search for etiologic pain mechanisms. Conversely, little is known about the experiences of and meanings attributed to, disability-related pain. Thus the purpose of this paper is to discuss the use of focus group methodology in elucidating the meanings and experiences of this population. Here, a distinction is made between the method of the focus group and focus group research as methodology. Typically, the focus group is presented as a seemingly atheoretical method of research. Drawing on research undertaken on the impact of chronic pain in people with multiple sclerosis, this paper seeks to theorise the focus group in arguing the methodological congruence of focus group research and the study of pain experience. It is argued that the contributions of group interaction and shared experiences in focus group discussions produce data and insights less accessible through more structured research methods. It is concluded that a biopsychosocial perspective of chronic pain may only ever be appreciated when the person-in-context is the unit of investigation.

Targeting histone deacetylases for the treatment of immune, endocrine and metabolic disorders

The 'histone code' is a well-established hypothesis describing the idea that specific patterns of post-translational modifications to histones act like a molecular "code" recognised and used by non-histone proteins to regulate specific chromatin functions. One modification which has received significant attention is that of histone acetylation. The enzymes which regulate this modification are described as histone acetyltransferases or HATs, and histone deacetylases or HDACs. Due to their conserved catalytic domain HDACs have been actively targeted as a therapeutic target. The proinflammatory environment is increasingly being recognised as a critical element for both degenerative diseases and cancer. The present review will discuss the current knowledge surrounding the clinical potential & current development of histone deacetylases for the treatment of diseases for which a proinflammatory environment plays important roles, and the molecular mechanisms by which such inhibitors may play important functions in modulating the proinflammatory environment. © 2009 Bentham Science Publishers Ltd.

Disentangling the cognitive components supporting Austin Maze performance in left versus right temporal lobe epilepsy

Neuropsychological tests requiring patients to find a path through a maze can be used to assess visuospatial memory performance in temporal lobe pathology, particularly in the hippocampus. Alternatively, they have been used as a task sensitive to executive function in patients with frontal lobe damage. We measured performance on the Austin Maze in patients with unilateral left and right temporal lobe epilepsy (TLE), with and without hippocampal sclerosis, compared to healthy controls. Performance was correlated with a number of other neuropsychological tests to identify the cognitive components that may be associated with poor Austin Maze performance. Patients with right TLE were significantly impaired on the Austin Maze task relative to patients with left TLE and controls, and error scores correlated with their performance on the Block Design task. The performance of patients with left TLE was also impaired relative to controls; however, errors correlated with performance on tests of executive function and delayed recall. The presence of hippocampal sclerosis did not have an impact on maze performance. A discriminant function analysis indicated that the Austin Maze alone correctly classified 73.5% of patients as having right TLE. In summary, impaired performance on the Austin Maze task is more suggestive of right than left TLE; however, impaired performance on this visuospatial task does not necessarily involve the hippocampus. The relationship of the Austin Maze task with other neuropsychological tests suggests that differential cognitive components may underlie performance decrements in right versus left TLE.