The potential for ethanol production from sugarcane in Australia

The Australian sugar industry processes approximately 35 million tonnes of sugarcane per year from 400 000 hectares of land. Sugar remains the principal revenue stream from sugarcane in Australia with less than 60 ML/y of fuel ethanol produced from final molasses at present. Modelling has been undertaken to estimate the potential ethanol production from the Australian sugar industry for integrated facilities producing both sugar and ethanol from the entire sugarcane resource. Although research aimed at developing commercial processes is ongoing, the use of a proportion of the bagasse and trash for ethanol production, in addition to juice and molasses fermentation, would allow significant increases in the scale of ethanol production from sugarcane in Australia, increasing total industry revenues while maintaining energy self sufficiency.

Towards a commercial lignocellulosic ethanol industry in Australia : the Mackay Renewable Biocommodities Pilot Plant

In 2007, the Queensland University of Technology (QUT) received funding from the Australian Government through the NCRIS program and from the then Queensland Government Department of State Development to construct a pilot research and development facility for the production of bioethanol and other renewable biocommodities from biomass including sugar cane bagasse. This facility is being constructed adjacent to the Racecourse Sugar Mill in Mackay and is known as the Mackay Renewable Biocommodities Pilot Plant (MRBPP). The MRBPP will be capable of processing biomass through a pressurised pretreatment reactor and includes equipment for enzymatic saccharification, fermentation and distillation to produce ethanol. Lignin and fermentation co-products will also be produced at a pilot scale for product development and testing.

Combinatorial design of key distribution mechanisms for wireless sensor networks

Secure communications in wireless sensor networks operating under adversarial conditions require providing pairwise (symmetric) keys to sensor nodes. In large scale deployment scenarios, there is no prior knowledge of post deployment network configuration since nodes may be randomly scattered over a hostile territory. Thus, shared keys must be distributed before deployment to provide each node a key-chain. For large sensor networks it is infeasible to store a unique key for all other nodes in the key-chain of a sensor node. Consequently, for secure communication either two nodes have a key in common in their key-chains and they have a wireless link between them, or there is a path, called key-path, among these two nodes where each pair of neighboring nodes on this path have a key in common. Length of the key-path is the key factor for efficiency of the design. This paper presents novel deterministic and hybrid approaches based on Combinatorial Design for deciding how many and which keys to assign to each key-chain before the sensor network deployment. In particular, Balanced Incomplete Block Designs (BIBD) and Generalized Quadrangles (GQ) are mapped to obtain efficient key distribution schemes. Performance and security properties of the proposed schemes are studied both analytically and computationally. Comparison to related work shows that the combinatorial approach produces better connectivity with smaller key-chain sizes.

Structure of the immature retroviral capsid at 8 Å resolution by cryo-electron microscopy

The assembly of retroviruses such as HIV-1 is driven by oligomerization of their major structural protein, Gag. Gag is a multidomain polyprotein including three conserved folded domains: MA (matrix), CA (capsid) and NC (nucleocapsid)(1). Assembly of an infectious virion proceeds in two stages(2). In the first stage, Gag oligomerization into a hexameric protein lattice leads to the formation of an incomplete, roughly spherical protein shell that buds through the plasma membrane of the infected cell to release an enveloped immature virus particle. In the second stage, cleavage of Gag by the viral protease leads to rearrangement of the particle interior, converting the non-infectious immature virus particle into a mature infectious virion. The immature Gag shell acts as the pivotal intermediate in assembly and is a potential target for anti-retroviral drugs both in inhibiting virus assembly and in disrupting virus maturation(3). However, detailed structural information on the immature Gag shell has not previously been available. For this reason it is unclear what protein conformations and interfaces mediate the interactions between domains and therefore the assembly of retrovirus particles, and what structural transitions are associated with retrovirus maturation. Here we solve the structure of the immature retroviral Gag shell from Mason-Pfizer monkey virus by combining cryo-electron microscopy and tomography. The 8-angstrom resolution structure permits the derivation of a pseudo-atomic model of CA in the immature retrovirus, which defines the protein interfaces mediating retrovirus assembly. We show that transition of an immature retrovirus into its mature infectious form involves marked rotations and translations of CA domains, that the roles of the amino-terminal and carboxy-terminal domains of CA in assembling the immature and mature hexameric lattices are exchanged, and that the CA interactions that stabilize the immature and mature viruses are almost completely distinct.

Analytical model for fault section estimation and state identification of unobserved protective relays in power systems [电力系统故障诊断与不可观测保护状态识别的解析模型]

In recent years, some models have been proposed for the fault section estimation and state identification of unobserved protective relays (FSE-SIUPR) under the condition of incomplete state information of protective relays. In these models, the temporal alarm information from a faulted power system is not well explored although it is very helpful in compensating the incomplete state information of protective relays, quickly achieving definite fault diagnosis results and evaluating the operating status of protective relays and circuit breakers in complicated fault scenarios. In order to solve this problem, an integrated optimization mathematical model for the FSE-SIUPR, which takes full advantage of the temporal characteristics of alarm messages, is developed in the framework of the well-established temporal constraint network. With this model, the fault evolution procedure can be explained and some states of unobserved protective relays identified. The model is then solved by means of the Tabu search (TS) and finally verified by test results of fault scenarios in a practical power system.

Why stagnant? behind the scenes in Indonesia’s reformed state asset management policies

This study seeks to answer the question of “why is policy innovation in Indonesia, in particular reformed state asset management laws and regulations, stagnant?” through an empirical and qualitative approach, identifying and exploring potential impeding influences to the full and equal implementation of said laws and regulations. The policies and regulations governing the practice of state asset management has emerged as an urgent question among many countries worldwide (Conway, 2006; Dow, Gillies, Nichols, & Polen, 2006; Kaganova, McKellar, & Peterson, 2006; McKellar, 2006b) for there is heightened awareness of the complex and crucial role that state assets play in public service provision. Indonesia is an example of such country, introducing a ‘big-bang’ reform in state asset management laws, policies, regulations, and technical guidelines. Two main reasons propelled said policy innovation: a) world-wide common challenges in state asset management practices - such as incomplete information system, accountability, and governance adherence/conceptualisation (Kaganova, McKellar and Peterson 2006); and b) unfavourable state assets audit results in all regional governments across Indonesia. The latter reasoning is emphasised, as the Indonesian government admits to past neglect in ensuring efficiency and best practice in its state asset management practices. Prior to reform there was euphoria of building and developing state assets and public infrastructure to support government programs of the day. Although this euphoria resulted in high growth within Indonesia, there seems to be little attention paid to how state assets bought/built is managed. Up until 2003-2004 state asset management is considered to be minimal; inventory of assets is done manually, there is incomplete public sector accounting standards, and incomplete financial reporting standards (Hadiyanto 2009). During that time transparency, accountability, and maintenance state assets was not the main focus, be it by the government or the society itself (Hadiyanto 2009). Indonesia exemplified its enthusiasm in reforming state asset management policies and practices through the establishment of the Directorate General of State Assets in 2006. The Directorate General of State Assets have stressed the new direction that it is taking state asset management laws and policies through the introduction of Republic of Indonesia Law Number 38 Year 2008, which is an amended regulation overruling Republic of Indonesia Law Number 6 Year 2006 on Central/Regional Government State Asset Management (Hadiyanto, 2009c). Law number 38/2008 aims to further exemplify good governance principles and puts forward a ‘the highest and best use of assets’ principle in state asset management (Hadiyanto, 2009a). The methodology of this study is that of qualitative case study approach, with a triangulated data collection method of document analysis (all relevant state asset management laws, regulations, policies, technical guidelines, and external audit reports), semi-structured interviews, and on-site observation. Empirical data of this study involved a sample of four Indonesian regional governments and 70 interviews, performed during January-July 2010. The analytical approach of this study is that of thematic analysis, in an effort to identify common influences and/or challenges to policy innovation within Indonesia. Based on the empirical data of this study specific impeding influences to state asset management reform is explored, answering the question why innovative policy implementation is stagnant. An in-depth analysis of each influencing factors to state asset management reform, and the attached interviewee’s opinions for each factor, suggests the potential of an ‘excuse rhetoric’; whereby the influencing factors identified are a smoke-screen, or are myths that public policy makers and implementers believe in; as a means to explain innovative policy stagnancy. This study offers insights to Indonesian policy makers interested in ensuring the conceptualisation and full implementation of innovative policies, particularly, although not limited to, within the context of state asset management practices.

Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990–2010 : a systematic analysis for the Global Burden of Disease Study 2010

Background Non-fatal health outcomes from diseases and injuries are a crucial consideration in the promotion and monitoring of individual and population health. The Global Burden of Disease (GBD) studies done in 1990 and 2000 have been the only studies to quantify non-fatal health outcomes across an exhaustive set of disorders at the global and regional level. Neither effort quantified uncertainty in prevalence or years lived with disability (YLDs). Methods Of the 291 diseases and injuries in the GBD cause list, 289 cause disability. For 1160 sequelae of the 289 diseases and injuries, we undertook a systematic analysis of prevalence, incidence, remission, duration, and excess mortality. Sources included published studies, case notification, population-based cancer registries, other disease registries, antenatal clinic serosurveillance, hospital discharge data, ambulatory care data, household surveys, other surveys, and cohort studies. For most sequelae, we used a Bayesian meta-regression method, DisMod-MR, designed to address key limitations in descriptive epidemiological data, including missing data, inconsistency, and large methodological variation between data sources. For some disorders, we used natural history models, geospatial models, back-calculation models (models calculating incidence from population mortality rates and case fatality), or registration completeness models (models adjusting for incomplete registration with health-system access and other covariates). Disability weights for 220 unique health states were used to capture the severity of health loss. YLDs by cause at age, sex, country, and year levels were adjusted for comorbidity with simulation methods. We included uncertainty estimates at all stages of the analysis. Findings Global prevalence for all ages combined in 2010 across the 1160 sequelae ranged from fewer than one case per 1 million people to 350 000 cases per 1 million people. Prevalence and severity of health loss were weakly correlated (correlation coefficient −0·37). In 2010, there were 777 million YLDs from all causes, up from 583 million in 1990. The main contributors to global YLDs were mental and behavioural disorders, musculoskeletal disorders, and diabetes or endocrine diseases. The leading specific causes of YLDs were much the same in 2010 as they were in 1990: low back pain, major depressive disorder, iron-deficiency anaemia, neck pain, chronic obstructive pulmonary disease, anxiety disorders, migraine, diabetes, and falls. Age-specific prevalence of YLDs increased with age in all regions and has decreased slightly from 1990 to 2010. Regional patterns of the leading causes of YLDs were more similar compared with years of life lost due to premature mortality. Neglected tropical diseases, HIV/AIDS, tuberculosis, malaria, and anaemia were important causes of YLDs in sub-Saharan Africa. Interpretation Rates of YLDs per 100 000 people have remained largely constant over time but rise steadily with age. Population growth and ageing have increased YLD numbers and crude rates over the past two decades. Prevalences of the most common causes of YLDs, such as mental and behavioural disorders and musculoskeletal disorders, have not decreased. Health systems will need to address the needs of the rising numbers of individuals with a range of disorders that largely cause disability but not mortality. Quantification of the burden of non-fatal health outcomes will be crucial to understand how well health systems are responding to these challenges. Effective and affordable strategies to deal with this rising burden are an urgent priority for health systems in most parts of the world. Funding Bill & Melinda Gates Foundation.

Context-aware device self-configuration using self-organizing maps

Modern mobile computing devices are versatile, but bring the burden of constant settings adjustment according to the current conditions of the environment. While until today, this task has to be accomplished by the human user, the variety of sensors usually deployed in such a handset provides enough data for autonomous self-configuration by a learning, adaptive system. However, this data is not fully available at certain points in time, or can contain false values. Handling potentially incomplete sensor data to detect context changes without a semantic layer represents a scientific challenge which we address with our approach. A novel machine learning technique is presented - the Missing-Values-SOM - which solves this problem by predicting setting adjustments based on context information. Our method is centered around a self-organizing map, extending it to provide a means of handling missing values. We demonstrate the performance of our approach on mobile context snapshots, as well as on classical machine learning datasets.

Decentralized detector generation in cooperative intrusion detection system

We consider Cooperative Intrusion Detection System (CIDS) which is a distributed AIS-based (Artificial Immune System) IDS where nodes collaborate over a peer-to-peer overlay network. The AIS uses the negative selection algorithm for the selection of detectors (e.g., vectors of features such as CPU utilization, memory usage and network activity). For better detection performance, selection of all possible detectors for a node is desirable but it may not be feasible due to storage and computational overheads. Limiting the number of detectors on the other hand comes with the danger of missing attacks. We present a scheme for the controlled and decentralized division of detector sets where each IDS is assigned to a region of the feature space. We investigate the trade-off between scalability and robustness of detector sets. We address the problem of self-organization in CIDS so that each node generates a distinct set of the detectors to maximize the coverage of the feature space while pairs of nodes exchange their detector sets to provide a controlled level of redundancy. Our contribution is twofold. First, we use Symmetric Balanced Incomplete Block Design, Generalized Quadrangles and Ramanujan Expander Graph based deterministic techniques from combinatorial design theory and graph theory to decide how many and which detectors are exchanged between which pair of IDS nodes. Second, we use a classical epidemic model (SIR model) to show how properties from deterministic techniques can help us to reduce the attack spread rate.

Utilization and optimization of a waste stream cellulose culture medium for pigment production by Penicillium spp

Aims This research sought to determine optimal corn waste stream–based fermentation medium C and N sources and incubation time to maximize pigment production by an indigenous Indonesian Penicillium spp., as well as to assess pigment pH stability. Methods and Results A Penicillium spp. was isolated from Indonesian soil, identified as Penicillium resticulosum, and used to test the effects of carbon and nitrogen type and concentrations, medium pH, incubation period and furfural on biomass and pigment yield (PY) in a waste corncob hydrolysate basal medium. Maximum red PY (497·03 ± 55·13 mg l−1) was obtained with a 21 : 1 C : N ratio, pH 5·5–6·0; yeast extract-, NH4NO3-, NaNO3-, MgSO4·7H2O-, xylose- or carboxymethylcellulose (CMC)-supplemented medium and 12 days (25°C, 60–70% relative humidity, dark) incubation. C source, C, N and furfural concentration, medium pH and incubation period all influenced biomass and PY. Pigment was pH 2–9 stable. Conclusions Penicillium resticulosum demonstrated microbial pH-stable-pigment production potential using a xylose or CMC and N source, supplemented waste stream cellulose culture medium. Significance and Impact of the Study Corn derived, waste stream cellulose can be used as a culture medium for fungal pigment production. Such application provides a process for agricultural waste stream resource reuse for production of compounds in increasing demand.

A vibrational spectroscopic study of the so-called ‘healing’ mineral papagoite CaCuAlSi2O6(OH)3

Papagoite is a silicate mineral named after an American Indian tribe and was used as a healing mineral. Papagoite CaCuAlSi2O6(OH)3 is a hydroxy mixed anion compound with both silicate and hydroxyl anions in the formula. The structural characterization of the mineral papagoite remains incomplete. Papagoite is a four-membered ring silicate with Cu2+ in square planar coordination. The intense sharp Raman band at 1053 cm−1 is assigned to the ν1 (A 1g) symmetric stretching vibration of the SiO4 units. The splitting of the ν3 vibrational mode offers support to the concept that the SiO4 tetrahedron in papagoite is strongly distorted. A very intense Raman band observed at 630 cm−1 with a shoulder at 644 cm−1 is assigned to the ν4 vibrational modes. Intense Raman bands at 419 and 460 cm−1 are attributed to the ν2 bending modes. Intense Raman bands at 3545 and 3573 cm−1 are assigned to the stretching vibrations of the OH units. Low-intensity Raman bands at 3368 and 3453 cm−1 are assigned to water stretching modes. It is suggested that the formula of papagoite is more likely to be CaCuAlSi2O6(OH)3 · xH2O. Hence, vibrational spectroscopy has been used to characterize the molecular structure of papagoite.

Thermogravimetric analysis of selected layered double hydroxides

Thermogravimetric analysis (TG) and powder X-ray diffraction (PXRD) were used to study some selected Mg/Al and Zn/Al layered double hydroxides (LDHs) prepared by co-precipitation. A Mg/Al hydrotalcite was investigated before and after reformation in fluoride and nitrate solutions. Little change in the TG or PXRD patterns was observed. It was proposed that successful intercalation of nitrate anions has occurred. However, the absence of any change in the d(003) interlayer spacing suggests that fluoride anions were not intercalated between the LDH layers. Any fluoride anions that were removed from solution are most likely adsorbed onto the outer surfaces of the hydrotalcite. As fluoride removal was not quantified it is not possible to confirm that this has happened without further experimentation. Carbonate is probably intercalated into the interlayer of these hydrotalcites, as well as fluoride or nitrate. The carbonate most likely originates from either incomplete decarbonation during thermal activation or adsorption from the atmosphere or dissolved in the deionised water. Small and large scale co-precipitation syntheses of a Zn/Al LDH were also investigated to determine if there was any change in the product. While the small scale experiment produced a good quality LDH of reasonable purity; the large scale synthesis resulted in several additional phases. Imprecise measurement and difficulty in handling the large quantities of reagents appeared to be sufficient to alter the reaction conditions causing a mixture of phases to be formed.

Inferring kangaroo phylogeny from incongruent nuclear and mitochondrial genes

The marsupial genus Macropus includes three subgenera, the familiar large grazing kangaroos and wallaroos of M. (Macropus) and M. (Osphranter), as well as the smaller mixed grazing/browsing wallabies of M. (Notamacropus). A recent study of five concatenated nuclear genes recommended subsuming the predominantly browsing Wallabia bicolor (swamp wallaby) into Macropus. To further examine this proposal we sequenced partial mitochondrial genomes for kangaroos and wallabies. These sequences strongly favour the morphological placement of W. bicolor as sister to Macropus, although place M. irma (black-gloved wallaby) within M. (Osphranter) rather than as expected, with M. (Notamacropus). Species tree estimation from separately analysed mitochondrial and nuclear genes favours retaining Macropus and Wallabia as separate genera. A simulation study finds that incomplete lineage sorting among nuclear genes is a plausible explanation for incongruence with the mitochondrial placement of W. bicolor, while mitochondrial introgression from a wallaroo into M. irma is the deepest such event identified in marsupials. Similar such coalescent simulations for interpreting gene tree conflicts will increase in both relevance and statistical power as species-level phylogenetics enters the genomic age. Ecological considerations in turn, hint at a role for selection in accelerating the fixation of introgressed or incompletely sorted loci. More generally the inclusion of the mitochondrial sequences substantially enhanced phylogenetic resolution. However, we caution that the evolutionary dynamics that enhance mitochondria as speciation indicators in the presence of incomplete lineage sorting may also render them especially susceptible to introgression.

Metabolic and ecological study of environmental pentose utilizing bacteria (E-PUB)

Lignocellulosic materials, such as sugar cane bagasse, a waste product of the sugarcane processing industry, agricultural residues and herbaceous crops, may serve as an abundant and comparatively cheap feedstock for largescale industrial fermentation, resulting in the production of marketable end-products. However, the complex structure of lignocellulosic materials, the presence of various hexose and pentose sugars in the hemicellulose component, and the presence of various compounds that inhibit the organisms selected for the fermentation process, all constitute barriers that add to the production costs and make full scale industrial production economically less feasible. The work presented in this thesis was conducted in order to screen microorganisms for ability to utilize pentose sugars derived from the sugar mill industrial waste. A large number of individual bacterial strains were investigated from hemi-cellulose rich material collected at the Proserpine and Maryborough sugar mills, notably soil samples from the mill sites. The research conducted to isolation of six pentose-capable Gram-positive organisms from the actinomycetes group by using pentose as a sole carbon source in the cultivation process. The isolates were identified as Corynebacterium glutamicum, Actinomyces odontolyticus, Nocardia elegans, and Propionibacterium freudenreichii all of which were isolated from the hemicellulose-enriched soil. Pentose degrading microbes are very rare in the environment, so this was a significant discovery. Previous research indicated that microbes could degrade pentose after genetic modification but the microbes discovered in this research were able to naturally utilize pentose. Six isolates, identified as four different genera, were investigated for their ability to utilize single sugars as substrates (glucose, xylose, arabinose or ribose), and also dual sugars as substrates (a hexose plus a pentose). The results demonstrated that C. glutamicum, A. odontolyticus, N. elegans, and P. freudenreichii were pentose-capable (able to grow using xylose or other pentose sugar), and also showed diauxie growth characteristics during the dual-sugar (glucose, in combination with xylose, arabinose or ribose) carbon source tests. In addition, it was shown that the isolates displayed very small differences in growth rates when grown on dual sugars as compared to single sugars, whether pentose or hexose in nature. The anabolic characteristics of C. glutamicum, A. odontolyticus, N. elegans and P. freudenreichii were subsequently investigated by qualitative analysis of their end-products, using high performance liquid chromatography (HPLC). All of the organisms produced arginine and cysteine after utilization of the pentose substrates alone. In addition, P. freudenreichii produced alanine and glycine. The end-product profile arising from culture with dual carbon sources was also tested. Interestingly, this time the product was different. All of them produced the amino acid glycine, when grown on a combination substrate-mix of glucose with xylose, and also glucose with arabinose. Only N. elegans was able to break down ribose, either singly or in combination with glucose, and the end-product of metabolism of the glucose plus ribose substrate combination was glutamic acid. The ecological analysis of microbial abundance in sugar mill waste was performed using denaturing gradient gel electrophoresis (DGGE) and also the metagenomic microarray PhyloChip method. Eleven solid samples and seven liquid samples were investigated. A very complex bacterial ecosystem was demonstrated in the seven liquid samples after testing with the PhyloChip method. It was also shown that bagasse leachate was the most different, compared to all of the other samples, by virtue of its richness in variety of taxa and the complexity of its bacterial community. The bacterial community in solid samples from Proserpine, Mackay and Maryborough sugar mills showed huge diversity. The information found from 16S rDNA sequencing results was that the bacterial genera Brevibacillus, Rhodospirillaceae, Bacillus, Vibrio and Pseudomonas were present in greatest abundance. In addition, Corynebacterium was also found in the soil samples. The metagenomic studies of the sugar mill samples demonstrate two important outcomes: firstly that the bagasse leachate, as potentially the most pentose-rich sample tested, had the most complex and diverse bacterial community; and secondly that the pentose-capable isolates that were initially discovered at the beginning of this study, were not amongst the most abundant taxonomic groups discovered in the sugar mill samples, and in fact were, as suspected, very rare. As a bioprospecting exercise, therefore, the study has discovered organisms that are naturally present, but in very small numbers, in the appropriate natural environment. This has implications for the industrial application of E-PUB, in that a seeding process using a starter culture will be necessary for industrial purposes, rather than simply assuming that natural fermentation might occur.

Modeling the cumulative genetic risk for multiple sclerosis from genome-wide association data

Background: Multiple sclerosis (MS) is the most common cause of chronic neurologic disability beginning in early to middle adult life. Results from recent genome-wide association studies (GWAS) have substantially lengthened the list of disease loci and provide convincing evidence supporting a multifactorial and polygenic model of inheritance. Nevertheless, the knowledge of MS genetics remains incomplete, with many risk alleles still to be revealed. Methods: We used a discovery GWAS dataset (8,844 samples, 2,124 cases and 6,720 controls) and a multi-step logistic regression protocol to identify novel genetic associations. The emerging genetic profile included 350 independent markers and was used to calculate and estimate the cumulative genetic risk in an independent validation dataset (3,606 samples). Analysis of covariance (ANCOVA) was implemented to compare clinical characteristics of individuals with various degrees of genetic risk. Gene ontology and pathway enrichment analysis was done using the DAVID functional annotation tool, the GO Tree Machine, and the Pathway-Express profiling tool. Results: In the discovery dataset, the median cumulative genetic risk (P-Hat) was 0.903 and 0.007 in the case and control groups, respectively, together with 79.9% classification sensitivity and 95.8% specificity. The identified profile shows a significant enrichment of genes involved in the immune response, cell adhesion, cell communication/ signaling, nervous system development, and neuronal signaling, including ionotropic glutamate receptors, which have been implicated in the pathological mechanism driving neurodegeneration. In the validation dataset, the median cumulative genetic risk was 0.59 and 0.32 in the case and control groups, respectively, with classification sensitivity 62.3% and specificity 75.9%. No differences in disease progression or T2-lesion volumes were observed among four levels of predicted genetic risk groups (high, medium, low, misclassified). On the other hand, a significant difference (F = 2.75, P = 0.04) was detected for age of disease onset between the affected misclassified as controls (mean = 36 years) and the other three groups (high, 33.5 years; medium, 33.4 years; low, 33.1 years). Conclusions: The results are consistent with the polygenic model of inheritance. The cumulative genetic risk established using currently available genome-wide association data provides important insights into disease heterogeneity and completeness of current knowledge in MS genetics.