Prospective phase II clinical trial of autologous haematopoietic stem cell transplant for treatment refractory multiple sclerosis

Background Autologous haematopoietic stem cell transplantation (AHSCT) has been explored as a therapeutic intervention in multiple sclerosis (MS) over the last two decades; however, prospective clinical trials of the most common myeloablative conditioning regimen, BEAM, are limited. Furthermore, patient selection, optimal chemotherapeutic regimen and immunological changes associated with disease response require ongoing exploration. We present the outcomes, safety and immune reconstitution (IR) of patients with active, treatment refractory MS. Methods This study was a single-centre, phase II clinical trial of AHSCT for patients with active relapsing remitting (RRMS) and secondary progressive MS (SPMS). Patients underwent AHSCT using BEAM (carmustine, etoposide, cytarabine, melphalan)+antithymocyte globulin chemotherapeutic regimen. Outcomes The primary outcome was event-free survival (EFS); defined as no clinical or radiological relapses and no disability progression. Multiparameter flow cytometry was performed for evaluation of post-transplant IR in both MS and lymphoma patients receiving the same chemotherapy regimen. Results Thirty-five patients (20 RRMS, 15 SPMS) completed AHSCT, with a median follow-up of 36 months (range 12-66). The median Expanded Disability Status Scores (EDSS) was 6 (2-7) and patients had failed a median of 4 (2-7) disease modifying therapies. 66% failed treatment with natalizumab. EFS at 3 years was 60%, (70% RRMS). Sustained improvement in EDSS was seen in 15 (44%) of patients. There was no treatment-related mortality. A sustained rise in CD39 + T regulatory cells, immunosuppressive CD56 hi natural killer cells and ablation of proinflammatory mucosal-associated invariant T cells was seen for 12 months following AHSCT in patients with MS. These changes did not occur in patients with lymphoma receiving the same chemotherapy for AHSCT. Conclusions The EFS in our MS cohort is significantly greater than other high-efficacy immunosuppressive therapies and similar to other AHSCT studies despite a more heavily pretreated cohort. Trial registration number ACTRN12613000339752

Scalable and Interpretable One-class SVMs with Deep Learning and Random Fourier features

One-class support vector machine (OC-SVM) for a long time has been one of the most effective anomaly detection methods and extensively adopted in both research as well as industrial applications. The biggest issue for OC-SVM is yet the capability to operate with large and high-dimensional datasets due to optimization complexity. Those problems might be mitigated via dimensionality reduction techniques such as manifold learning or autoencoder. However, previous work often treats representation learning and anomaly prediction separately. In this paper, we propose autoencoder based one-class support vector machine (AE-1SVM) that brings OC-SVM, with the aid of random Fourier features to approximate the radial basis kernel, into deep learning context by combining it with a representation learning architecture and jointly exploit stochastic gradient descent to obtain end-to-end training. Interestingly, this also opens up the possible use of gradient-based attribution methods to explain the decision making for anomaly detection, which has ever been challenging as a result of the implicit mappings between the input space and the kernel space. To the best of our knowledge, this is the first work to study the interpretability of deep learning in anomaly detection. We evaluate our method on a wide range of unsupervised anomaly detection tasks in which our end-to-end training architecture achieves a performance significantly better than the previous work using separate training.Comment: Accepted at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) 201

Pre-launch calibration of the HIRDLS instrument

Report about the aims for the calibration of the HIRDLS instrument

Effective Feedback to Improve Primary Care Prescribing Safety (EFIPPS) a pragmatic three-arm cluster randomised trial:designing the intervention (ClinicalTrials.gov registration NCT01602705)

Peer reviewedPublisher PD

Fungal microbiota from rain water and pathogenicity of Fusarium species isolated from atmospheric dust and rainfall dust

In order to determine the presence of Fusarium spp. in atmospheric dust and rainfall dust, samples were collected during September 2007, and July, August, and October 2008. The results reveal the prevalence of airborne Fusarium species coming from the atmosphere of the South East coast of Spain. Five different Fusarium species were isolated from the settling dust: Fusarium oxysporum, F. solani, F. equiseti, F. dimerum, and F. proliferatum. Moreover, rainwater samples were obtained during significant rainfall events in January and February 2009. Using the dilution-plate method, 12 fungal genera were identified from these rainwater samples. Specific analyses of the rainwater revealed the presence of three species of Fusarium: F. oxysporum, F. proliferatum and F. equiseti. A total of 57 isolates of Fusarium spp. obtained from both rainwater and atmospheric rainfall dust sampling were inoculated onto melon (Cucumis melo L.) cv. Piñonet and tomato (Lycopersicon esculentum Mill.) cv. San Pedro. These species were chosen because they are the main herbaceous crops in Almeria province. The results presented in this work indicate strongly that spores or propagules of Fusarium are able to cross the continental barrier carried by winds from the Sahara (Africa) to crop or coastal lands in Europe. Results show differences in the pathogenicity of the isolates tested. Both hosts showed root rot when inoculated with different species of Fusarium, although fresh weight measurements did not bring any information about the pathogenicity. The findings presented above are strong indications that long-distance transmission of Fusarium propagules may occur. Diseases caused by species of Fusarium are common in these areas. They were in the past, and are still today, a problem for greenhouses crops in Almería, and many species have been listed as pathogens on agricultural crops in this region. Saharan air masses dominate the Mediterranean regions. The evidence of long distance dispersal of Fusarium spp. by atmospheric dust and rainwater together with their proved pathogenicity must be taken into account in epidemiological studies

The impact of nonlinear exposure-risk relationships on seasonal time-series data: modelling Danish neonatal birth anthropometric data

Background Birth weight and length have seasonal fluctuations. Previous analyses of birth weight by latitude effects identified seemingly contradictory results, showing both 6 and 12 monthly periodicities in weight. The aims of this paper are twofold: (a) to explore seasonal patterns in a large, Danish Medical Birth Register, and (b) to explore models based on seasonal exposures and a non-linear exposure-risk relationship. Methods Birth weight and birth lengths on over 1.5 million Danish singleton, live births were examined for seasonality. We modelled seasonal patterns based on linear, U- and J-shaped exposure-risk relationships. We then added an extra layer of complexity by modelling weighted population-based exposure patterns. Results The Danish data showed clear seasonal fluctuations for both birth weight and birth length. A bimodal model best fits the data, however the amplitude of the 6 and 12 month peaks changed over time. In the modelling exercises, U- and J-shaped exposure-risk relationships generate time series with both 6 and 12 month periodicities. Changing the weightings of the population exposure risks result in unexpected properties. A J-shaped exposure-risk relationship with a diminishing population exposure over time fitted the observed seasonal pattern in the Danish birth weight data. Conclusion In keeping with many other studies, Danish birth anthropometric data show complex and shifting seasonal patterns. We speculate that annual periodicities with non-linear exposure-risk models may underlie these findings. Understanding the nature of seasonal fluctuations can help generate candidate exposures

Metabolomics demonstrates divergent responses of two Eucalyptus species to water stress

Past studies of water stress in Eucalyptus spp. generally highlighted the role of fewer than five “important” metabolites, whereas recent metabolomic studies on other genera have shown tens of compounds are affected. There are currently no metabolite profiling data for responses of stress-tolerant species to water stress. We used GC–MS metabolite profiling to examine the response of leaf metabolites to a long (2 month) and severe (Ψpredawn < −2 MPa) water stress in two species of the perennial tree genus Eucalyptus (the mesic Eucalyptus pauciflora and the semi-arid Eucalyptus dumosa). Polar metabolites in leaves were analysed by GC–MS and inorganic ions by capillary electrophoresis. Pressure–volume curves and metabolite measurements showed that water stress led to more negative osmotic potential and increased total osmotically active solutes in leaves of both species. Water stress affected around 30–40% of measured metabolites in E. dumosa and 10–15% in E. pauciflora. There were many metabolites that were affected in E. dumosa but not E. pauciflora, and some that had opposite responses in the two species. For example, in E. dumosa there were increases in five acyclic sugar alcohols and four low-abundance carbohydrates that were unaffected by water stress in E. pauciflora. Re-watering increased osmotic potential and decreased total osmotically active solutes in E. pauciflora, whereas in E. dumosa re-watering led to further decreases in osmotic potential and increases in total osmotically active solutes. This experiment has added several extra dimensions to previous targeted analyses of water stress responses in Eucalyptus, and highlights that even species that are closely related (e.g. congeners) may respond differently to water stress and re-waterin