Modelling disease activity in juvenile dermatomyositis: A Bayesian approach

Juvenile dermatomyositis is the most common form of the juvenile idiopathic inflammatory myopathies characterised by muscle and skin inflammation, leading to symmetric proximal muscle weakness and cutaneous symptoms. It has a fluctuating course and varying prognosis. In a Bayesian framework, we develop a joint model for four longitudinal outcomes, which accounts for within individual variability as well as inter-individual variability. Correlations among the outcome variables are introduced through a subject-specific random effect. Moreover, we exploit an approach similar to a hurdle model to account for excess of a specific outcome in the response. Clinical markers and symptoms are used as covariates in a regression set-up. Data from an ongoing observational cohort study are available, providing information on 340 subjects, who contributed 2725 clinical visits. The model shows good performance and yields efficient estimations of model parameters, as well as accurate predictions of the disease activity parameters, corresponding well to observed clinical patterns over time. The posterior distribution of the by-subject random intercepts shows a substantial correlation between two of the outcome variables. A subset of clinical markers and symptoms are identified as associated with disease activity. These findings have the potential to influence clinical practice as they can be used to stratify patients according to their prognosis and guide treatment decisions, as well as contribute to on-going research about the most relevant outcome markers for patients affected by juvenile dermatomyositis

Matrix metalloproteinase 13 modulates intestinal epithelial barrier integrity in inflammatory diseases by activating TNF

Several pathological processes, such as sepsis and inflammatory bowel disease (IBD), are associated with impairment of intestinal epithelial barrier. Here, we investigated the role of matrix metalloproteinase MMP13 in these diseases. We observed that MMP13(-/-) mice display a strong protection in LPS- and caecal ligation and puncture-induced sepsis. We could attribute this protection to reduced LPS-induced goblet cell depletion, endoplasmic reticulum stress, permeability and tight junction destabilization in the gut of MMP13(-/-) mice compared to MMP13(+/+) mice. Both in vitro and in vivo, we found that MMP13 is able to cleave pro-TNF into bioactive TNF. By LC-MS/MS, we identified three MMP13 cleavage sites, which proves that MMP13 is an alternative TNF sheddase next to the TNF converting enzyme TACE. Similarly, we found that the same mechanism was responsible for the observed protection of the MMP13(-/-) mice in a mouse model of DSS-induced colitis. We identified MMP13 as an important mediator in sepsis and IBD via the shedding of TNF. Hence, we propose MMP13 as a novel drug target for diseases in which damage to the gut is essential

ReaxFF parameter optimization with Monte-Carlo and evolutionary algorithms : guidelines and insights

ReaxFF is a computationally efficient force field to simulate complex reactive dynamics in extended molecular models with diverse chemistries, if reliable force-field parameters are available for the chemistry of interest. If not, they must be optimized by minimizing the error ReaxFF makes on a relevant training set. Because this optimization is far from trivial, many methods, in particular, genetic algorithms (GAs), have been developed to search for the global optimum in parameter space. Recently, two alternative parameter calibration techniques were proposed, that is, Monte-Carlo force field optimizer (MCFF) and covariance matrix adaptation evolutionary strategy (CMA-ES). In this work, CMA-ES, MCFF, and a GA method (OGOLEM) are systematically compared using three training sets from the literature. By repeating optimizations with different random seeds and initial parameter guesses, it is shown that a single optimization run with any of these methods should not be trusted blindly: nonreproducible, poor or premature convergence is a common deficiency. GA shows the smallest risk of getting trapped into a local minimum, whereas CMA-ES is capable of reaching the lowest errors for two-third of the cases, although not systematically. For each method, we provide reasonable default settings, and our analysis offers useful guidelines for their usage in future work. An important side effect impairing parameter optimization is numerical noise. A detailed analysis reveals that it can be reduced, for example, by using exclusively unambiguous geometry optimization in the training set. Even without this noise, many distinct near-optimal parameter vectors can be found, which opens new avenues for improving the training set and detecting overfitting artifacts

Thrombomodulin Ala455Val Polymorphism and the risk of cerebral infarction in a biracial population: the Stroke Prevention in Young Women Study

BACKGROUND: The genes encoding proteins in the thrombomodulin-protein C pathway are promising candidate genes for stroke susceptibility because of their importance in thrombosis regulation and inflammatory response. Several published studies have shown that the Ala455Val thrombomodulin polymorphism is associated with ischemic heart disease, but none has examined the association with stroke. Using data from the Stroke Prevention in Young Women Study, we sought to determine the association between the Ala455Val thrombomodulin polymorphism and the occurrence of ischemic stroke in young women. METHODS: All 59 hospitals in the greater Baltimore-Washington area participated in a population-based case-control study of stroke in young women. We compared 141 cases of first ischemic stroke (44% black) among women 15 to 44 years of age with 210 control subjects (35% black) who were identified by random digit dialing and frequency matched to the cases by age and geographical region of residence. Data on historical risk factors were collected by standardized interview. Genotyping of the thrombomodulin Ala455Val polymorphism was performed by pyrosequencing. RESULTS: The A allele (frequency = 0.85) was associated with stroke under the recessive model. After adjustment for age, race, cigarette smoking, hypertension, and diabetes, the AA genotype, compared with the AV and VV genotypes combined, was significantly associated with stroke (odds ratio 1.9, 95% CI 1.1–3.3). The AA genotype was more common among black than white control subjects (81% versus 68%) but there was no significant interaction between the risk genotype and race (adjusted odds ratio 2.7 for blacks and 1.6 for whites). A secondary analysis removing all probable (n = 16) and possible (n = 15) cardioembolic strokes demonstrated an increased association (odds ratio 2.2, 95% CI 1.2–4.2). CONCLUSIONS: Among women aged 15 to 44 years, the AA genotype is more prevalent among blacks than whites and is associated with increased risk of early onset ischemic stroke. Removing strokes potentially related to cardioembolic phenomena increased this association. Further studies are needed to determine whether this polymorphism is functionally related to thrombomodulin expression or whether the association is due to population stratification or linkage to a nearby functional polymorphism

The ReaxFF reactive force-field : development, applications and future directions

The reactive force-field (ReaxFF) interatomic potential is a powerful computational tool for exploring, developing and optimizing material properties. Methods based on the principles of quantum mechanics (QM), while offering valuable theoretical guidance at the electronic level, are often too computationally intense for simulations that consider the full dynamic evolution of a system. Alternatively, empirical interatomic potentials that are based on classical principles require significantly fewer computational resources, which enables simulations to better describe dynamic processes over longer timeframes and on larger scales. Such methods, however, typically require a predefined connectivity between atoms, precluding simulations that involve reactive events. The ReaxFF method was developed to help bridge this gap. Approaching the gap from the classical side, ReaxFF casts the empirical interatomic potential within a bond-order formalism, thus implicitly describing chemical bonding without expensive QM calculations. This article provides an overview of the development, application, and future directions of the ReaxFF method

A semi-quantitative survey of macroinvertebrates at selected sites to evaluate the ecosystem health of the Olifants River

This study was conducted to evaluate the ecosystem health of the Olifants River by means of semi-quantitative surveys of the macroinvertebrates at 7 selected sites in the catchment. These surveys were performed during the high- and low-flow seasons for 2 consecutive years. Macroinvertebrates were collected by using a net consisting of a 30 cm square steel frame with a sturdy handle, to which a Perlon gauze net with a mesh of 1 mm was attached. Semi-quantitative surveys were done by sampling the vegetation, as well as the substratum, with the net at each site for approximately 15 min. The pH, water temperature and conductivity were measured in situ at each site during the different surveys. Samples were fixed and preserved in 90% ethanol and thereafter sorted, identified up to family level and counted. The specimens were categorised as tolerant, moderately sensitive or highly sensitive, according to the guidelines set by the South African Scoring System Version 5 (SASS5). Although a total of 95 taxa were recovered during this study, only 7 of these taxa were categorised as highly sensitive, it can be concluded that the water of the Olifants River is in a poor state of health as revealed by the macroinvertebrate assemblages.Keywords: Olifants River, macroinvertebrates, river healt

A new distribution record of Chambardia wahlbergi (Krauss, 1848) (Bivalvia: Iridinidae) and Unio caffer (Krauss, 1848) (Bivalvia: Unionidae) in South Africa

Little is known with regard to the conservation status of invertebrates of South Africa; however, in the revised edition of the IUCN Red Data List (2011) the conservation status of both Unio caffer and Chambardia wahlbergi is considered as ‘of least concern’. In recent reports on the geographical distribution and habitat preferences of these two species in South Africa, concern was expressed regarding their conservation status. However, specimens of C. wahlbergi collected at several sites on several occasions in the Vaal River were the first evidence that the geographical distribution of this bivalve was wider and not restricted to water bodies located in east-flowing catchments in the warmer areas of South Africa. The fact that populations of C. wahlbergi can become established in habitats on the Highveld was further supported by a number of valves collected on the dry bed of the Schoonspruit (26° 37’ 55.2”S, 26° 35’ 32.3”E), near Klerksdorp in the North West Province, on 16 February 2016. A number of valves of U. caffer which were collected on the same occasion at the same locality are also the first record of this species from this water body

Classical and reactive molecular dynamics: Principles and applications in combustion and energy systems

Molecular dynamics (MD) has evolved into a ubiquitous, versatile and powerful computational method for fundamental research in science branches such as biology, chemistry, biomedicine and physics over the past 60 years. Powered by rapidly advanced supercomputing technologies in recent decades, MD has entered the engineering domain as a first-principle predictive method for material properties, physicochemical processes, and even as a design tool. Such developments have far-reaching consequences, and are covered for the first time in the present paper, with a focus on MD for combustion and energy systems encompassing topics like gas/liquid/solid fuel oxidation, pyrolysis, catalytic combustion, heterogeneous combustion, electrochemistry, nanoparticle synthesis, heat transfer, phase change, and fluid mechanics. First, the theoretical framework of the MD methodology is described systemically, covering both classical and reactive MD. The emphasis is on the development of the reactive force field (ReaxFF) MD, which enables chemical reactions to be simulated within the MD framework, utilizing quantum chemistry calculations and/or experimental data for the force field training. Second, details of the numerical methods, boundary conditions, post-processing and computational costs of MD simulations are provided. This is followed by a critical review of selected applications of classical and reactive MD methods in combustion and energy systems. It is demonstrated that the ReaxFF MD has been successfully deployed to gain fundamental insights into pyrolysis and/or oxidation of gas/liquid/solid fuels, revealing detailed energy changes and chemical pathways. Moreover, the complex physico-chemical dynamic processes in catalytic reactions, soot formation, and flame synthesis of nanoparticles are made plainly visible from an atomistic perspective. Flow, heat transfer and phase change phenomena are also scrutinized by MD simulations. Unprecedented details of nanoscale processes such as droplet collision, fuel droplet evaporation, and CO2 capture and storage under subcritical and supercritical conditions are examined at the atomic level. Finally, the outlook for atomistic simulations of combustion and energy systems is discussed in the context of emerging computing platforms, machine learning and multiscale modelling