Recommendations for the management of secondary hypogammaglobulinaemia due to B cell targeted therapies in autoimmune rheumatic diseases

OBJECTIVES: The association of B cell targeted therapies with development of hypogammaglobulinaemia and infection is increasingly recognized. Our aim was to develop consensus recommendations for immunoglobulin replacement therapy for management of hypogammaglobulinaemia following B cell targeted therapies in autoimmune rheumatic diseases. // METHODS: A modified Delphi exercise involved a 17-member Taskforce committee, consisting of immunologists, rheumatologists, nephrologists, haematologists, a gastroenterologist, an immunology specialist nurse and a patient representative. The first round identified the most pertinent topics to address in the recommendations. A search string was agreed upon for the identification of publications in PubMed focusing on these areas, for a systematic literature review. Original data was presented from this review to the Taskforce committee. Recommendations from the British Society for Rheumatology, the UK Department of Health, EULAR, the ACR, and the American Academy of Allergy, Asthma, and Immunology were also reviewed. The evidence was discussed in a face-to-face meeting to formulate recommendation statements. The levels of evidence and statements were graded according to Scottish Intercollegiate Guidelines Network methodology. // RESULTS: Three overarching principles, eight recommendation statements and a research agenda were formulated. The Taskforce committee voted on these statements, achieving 82–100% agreement for each recommendation. The strength of the recommendations was restricted by the low quality of the available evidence, with no randomized controlled trial data. The recommendations cover risk factors, monitoring, referral for hypogammaglobulinaemia; indications, dosage and discontinuation of immunoglobulin replacement therapy. // CONCLUSION: These are the first recommendations specifically formulated for B cell targeted therapies related to hypogammaglobulinaemia in autoimmune rheumatic diseases. The recommendations are to aid health-care professionals with clinical decision making for patients with hypogammaglobulinaemia

Prevalence of HCV and HIV infections in 2005-Earthquake-affected areas of Pakistan

<p>Abstract</p> <p>Background</p> <p>On October 8, 2005, an earthquake of magnitude 7.6 hit the Northern parts of Pakistan. In the post-earthquake scenario, overcrowding, improper sewage disposal, contamination of food and drinking water, hasty surgical procedures, and unscreened blood transfusions to earthquake victims most likely promotes the spread of infections already prevalent in the area.</p> <p>Objective</p> <p>The objective of the study reported here was to determine the prevalence of Human Immunodeficiency and Hepatitis C viruses (respectively, HIV and HCV) in the earthquake-affected communities of Pakistan. The samples were analyzed 2 months and then again 11 months after the earthquake to estimate the burden of HIV and HCV in these areas, and to determine any rise in the prevalence of these viral infections as a result of the earthquake.</p> <p>Methods</p> <p>Blood samples were initially collected during December, 2005 to March 2006, from 245 inhabitants of the earthquake-affected areas. These samples were screened for HCV and HIV, using immunochromatography and Enzyme-Linked Immuno-Sorbent Assay (ELISA).</p> <p>Results</p> <p>Out of 245 samples tested, 8 (3.26%) were found positive for HCV, and 0 (0.0%) for HIV, indicating the existence of HCV infection in the earthquake-stricken areas. The same methods were used to analyze the samples collected in the second round of screening in the same area, in September, 2006 – 11 months after the earthquake. This time 290 blood samples were collected, out of which 16 (5.51%) samples were positive for HCV, and 0 for HIV.</p> <p>Conclusion</p> <p>A slightly higher prevalence of HCV was recorded 11 months after the earthquake; this increase, however, was not statistically significant. None of the study participants was found HIV-infected.</p

Hand gesture-based interactive puppetry system to assist storytelling for children

© 2016 The Author(s)Digital techniques have been used to assist narrative and storytelling, especially in many pedagogical practices. With the rapid development of HCI techniques, saturated with digital media in their daily lives, young children, demands more interactive learning methods and meaningful immersive learning experiences. In this paper, we propose a novel hand gesture-based puppetry storytelling system which provides a more intuitive and natural human computer interaction method for young children to develop narrative ability in virtual story world. Depth motion sensing and hand gestures control technology is utilized in the implementation of user-friendly interaction. Young players could intuitively use hand gestures to manipulate virtual puppet to perform story and interact with different items in virtual environment to assist narration. Based on the result of the evaluation, this novel digital storytelling system shows positive pedagogical functions on children’s narrating ability as well as the competencies of cognitive and motor coordination. The usability of the system is preliminary examined in our test, and the results which showed that young children can benefit from playing with Puppet Narrator

An integrated workflow for robust alignment and simplified quantitative analysis of NMR spectrometry data

<p>Abstract</p> <p>Background</p> <p>Nuclear magnetic resonance spectroscopy (NMR) is a powerful technique to reveal and compare quantitative metabolic profiles of biological tissues. However, chemical and physical sample variations make the analysis of the data challenging, and typically require the application of a number of preprocessing steps prior to data interpretation. For example, noise reduction, normalization, baseline correction, peak picking, spectrum alignment and statistical analysis are indispensable components in any NMR analysis pipeline.</p> <p>Results</p> <p>We introduce a novel suite of informatics tools for the quantitative analysis of NMR metabolomic profile data. The core of the processing cascade is a novel peak alignment algorithm, called hierarchical Cluster-based Peak Alignment (CluPA). The algorithm aligns a target spectrum to the reference spectrum in a top-down fashion by building a hierarchical cluster tree from peak lists of reference and target spectra and then dividing the spectra into smaller segments based on the most distant clusters of the tree. To reduce the computational time to estimate the spectral misalignment, the method makes use of Fast Fourier Transformation (FFT) cross-correlation. Since the method returns a high-quality alignment, we can propose a simple methodology to study the variability of the NMR spectra. For each aligned NMR data point the ratio of the between-group and within-group sum of squares (BW-ratio) is calculated to quantify the difference in variability between and within predefined groups of NMR spectra. This differential analysis is related to the calculation of the F-statistic or a one-way ANOVA, but without distributional assumptions. Statistical inference based on the BW-ratio is achieved by bootstrapping the null distribution from the experimental data.</p> <p>Conclusions</p> <p>The workflow performance was evaluated using a previously published dataset. Correlation maps, spectral and grey scale plots show clear improvements in comparison to other methods, and the down-to-earth quantitative analysis works well for the CluPA-aligned spectra. The whole workflow is embedded into a modular and statistically sound framework that is implemented as an R package called "speaq" ("spectrum alignment and quantitation"), which is freely available from <url>http://code.google.com/p/speaq/</url>.</p

A simpler method of preprocessing MALDI-TOF MS data for differential biomarker analysis: stem cell and melanoma cancer studies

<p>Abstract</p> <p>Introduction</p> <p>Raw spectral data from matrix-assisted laser desorption/ionisation time-of-flight (MALDI-TOF) with MS profiling techniques usually contains complex information not readily providing biological insight into disease. The association of identified features within raw data to a known peptide is extremely difficult. Data preprocessing to remove uncertainty characteristics in the data is normally required before performing any further analysis. This study proposes an alternative yet simple solution to preprocess raw MALDI-TOF-MS data for identification of candidate marker ions. Two in-house MALDI-TOF-MS data sets from two different sample sources (melanoma serum and cord blood plasma) are used in our study.</p> <p>Method</p> <p>Raw MS spectral profiles were preprocessed using the proposed approach to identify peak regions in the spectra. The preprocessed data was then analysed using bespoke machine learning algorithms for data reduction and ion selection. Using the selected ions, an ANN-based predictive model was constructed to examine the predictive power of these ions for classification.</p> <p>Results</p> <p>Our model identified 10 candidate marker ions for both data sets. These ion panels achieved over 90% classification accuracy on blind validation data. Receiver operating characteristics analysis was performed and the area under the curve for melanoma and cord blood classifiers was 0.991 and 0.986, respectively.</p> <p>Conclusion</p> <p>The results suggest that our data preprocessing technique removes unwanted characteristics of the raw data, while preserving the predictive components of the data. Ion identification analysis can be carried out using MALDI-TOF-MS data with the proposed data preprocessing technique coupled with bespoke algorithms for data reduction and ion selection.</p

The Lancet Breast Cancer Commission: tackling a global health, gender, and equity challenge

Breast cancer is an increasing global health, gender, socioeconomic, and equity challenge. In 2020, 2·3 million women were diagnosed with breast cancer and there were 685 000 deaths worldwide.1 Not only is breast cancer the highest incident cancer globally, but it is also the most prevalent, causing more disability-adjusted life-years lost than any other malignancy. Tackling breast cancer is a formidable task for health-care systems, policy makers, and other stakeholders. The numbers of people with metastatic breast cancer who go uncounted are concerning. Cancer registries record patients initially presenting with de-novo metastatic breast cancer, but data on those who develop metastases after a diagnosis of early breast cancer are scarce. In a world focused on breast cancer cure, these uncounted people living with metastatic disease face abandonment and stigma

Inactivation of DltA Modulates Virulence Factor Expression in Streptococcus pyogenes

D-alanylated lipoteichoic acid is a virtually ubiquitous component of gram-positive cell walls. Mutations in the dltABCD operon of numerous species exhibit pleiotropic effects, including reduced virulence, which has been attributed to increased binding of cationic antimicrobial peptides to the more negatively charged cell surface. In this study, we have further investigated the effects that mutating dltA has on virulence factor expression in Streptococcus pyogenes.Isogenic Delta dltA mutants had previously been created in two distinct M1T1 isolates of S. pyogenes. Immunoblots, flow cytometry, and immunofluorescence were used to quantitate M protein levels in these strains, as well as to assess their ability to bind complement. Bacteria were tested for their ability to interact with human PMN and to grow in whole human blood. Message levels for emm, sic, and various regulatory elements were assessed by quantitative RT-PCR. Cell walls of Delta dltA mutants contained much less M protein than cell walls of parent strains and this correlated with reduced levels of emm transcripts, increased deposition of complement, increased association of bacteria with polymorphonuclear leukocytes, and reduced bacterial growth in whole human blood. Transcription of at least one other gene of the mga regulon, sic, which encodes a protein that inactivates antimicrobial peptides, was also dramatically reduced in Delta dltA mutants. Concomitantly, ccpA and rofA were unaffected, while rgg and arcA were up-regulated.This study has identified a novel mechanism for the reduced virulence of dltA mutants of Streptococcus pyogenes in which gene regulatory networks somehow sense and respond to the loss of DltA and lack of D-alanine esterification of lipoteichoic acid. The mechanism remains to be determined, but the data indicate that the status of D-alanine-lipoteichoic acid can significantly influence the expression of at least some streptococcal virulence factors and provide further impetus to targeting the dlt operon of gram-positive pathogens in the search for novel antimicrobial compounds

Germline selection shapes human mitochondrial DNA diversity.

Approximately 2.4% of the human mitochondrial DNA (mtDNA) genome exhibits common homoplasmic genetic variation. We analyzed 12,975 whole-genome sequences to show that 45.1% of individuals from 1526 mother-offspring pairs harbor a mixed population of mtDNA (heteroplasmy), but the propensity for maternal transmission differs across the mitochondrial genome. Over one generation, we observed selection both for and against variants in specific genomic regions; known variants were more likely to be transmitted than previously unknown variants. However, new heteroplasmies were more likely to match the nuclear genetic ancestry as opposed to the ancestry of the mitochondrial genome on which the mutations occurred, validating our findings in 40,325 individuals. Thus, human mtDNA at the population level is shaped by selective forces within the female germ line under nuclear genetic control, which ensures consistency between the two independent genetic lineages.NIHR, Wellcome Trust, MRC, Genomics Englan