B cells do not take up bacterial DNA: An essential role for antigen in exposure of DNA to toll-like receptor-9

Murine dendritic cells (DC) and macrophages respond to bacterial CpG DNA through toll-like receptor 9 (TLR9). Although it is frequently assumed that bacterial DNA is a direct stimulus for B cells, published work does not reliably show responses of purified B cells. Here we show that purified splenic B cells did not respond to Escherichia coli DNA with induction of CD86, despite readily responding to single-stranded (ss) phosphodiester CpG oligodeoxynucleotides (ODN). This was due to a combination of weak responses to both long and double-stranded (ds) DNA. B-cell DNA uptake was greatly reduced with increasing DNA length. This contrasts with macrophages where DNA uptake and subsequent responses were enhanced with increasing DNA length. However, when DNA was physically linked to hen egg lysozyme (HEL), HEL-specific B cells showed efficient uptake of DNA, and limited proliferation in response to the HEL-DNA complex. We propose that, in the absence of other signals, B cells have poor uptake and responses to long dsDNA to prevent polyclonal activation. Conversely, when DNA is physically linked to a B-cell receptor (BCR) ligand, its uptake is increased, allowing TLR9-dependent B-cell activation in an antigen-specific manner. We could not generate fragments of E. coli DNA by limited DNaseI digestion that could mimic the stimulatory effect of ss CpG ODN on naive B cells. We suggest that the frequently studied polyclonal B-cell responses to CpG ODN are relevant to therapeutic applications of phosphorothioate-modified CpG-containing ODN, but not to natural responses to foreign or host dsDNA. Immunology and Cell Biology (2011) 89, 517-525; doi:10.1038/icb.2010.112; published online 5 October 201

Voxel-wise comparisons of cellular microstructure and diffusion-MRI in mouse hippocampus using 3D Bridging of Optically-clear histology with Neuroimaging Data (3D-BOND)

A key challenge in medical imaging is determining a precise correspondence between image properties and tissue microstructure. This comparison is hindered by disparate scales and resolutions between medical imaging and histology. We present a new technique, 3D Bridging of Optically-clear histology with Neuroimaging Data (3D-BOND), for registering medical images with 3D histology to overcome these limitations. Ex vivo 120 × 120 × 200 μm resolution diffusion-MRI (dMRI) data was acquired at 7 T from adult C57Bl/6 mouse hippocampus. Tissue was then optically cleared using CLARITY and stained with cellular markers and confocal microscopy used to produce high-resolution images of the 3D-tissue microstructure. For each sample, a dense array of hippocampal landmarks was used to drive registration between upsampled dMRI data and the corresponding confocal images. The cell population in each MRI voxel was determined within hippocampal subregions and compared to MRI-derived metrics. 3D-BOND provided robust voxel-wise, cellular correlates of dMRI data. CA1 pyramidal and dentate gyrus granular layers had significantly different mean diffusivity (p > 0.001), which was related to microstructural features. Overall, mean and radial diffusivity correlated with cell and axon density and fractional anisotropy with astrocyte density, while apparent fibre density correlated negatively with axon density. Astrocytes, axons and blood vessels correlated to tensor orientation

Society for Immunotherapy of Cancer clinical and biomarkers data sharing resource document: Volume I—conceptual challenges

The sharing of clinical trial data and biomarker data sets among the scientific community, whether the data originates from pharmaceutical companies or academic institutions, is of critical importance to enable the development of new and improved cancer immunotherapy modalities. Through data sharing, a better understanding of current therapies in terms of their efficacy, safety and biomarker data profiles can be achieved. However, the sharing of these data sets involves a number of stakeholder groups including patients, researchers, private industry, scientific journals and professional societies. Each of these stakeholder groups has differing interests in the use and sharing of clinical trial and biomarker data, and the conflicts caused by these differing interests represent significant obstacles to effective, widespread sharing of data. Thus, the Society for Immunotherapy of Cancer (SITC) Biomarkers Committee convened to identify the current barriers to biomarker data sharing in immuno-oncology (IO) and to help in establishing professional standards for the responsible sharing of clinical trial data. The conclusions of the committee are described in two position papers: Volume I-conceptual challenges and Volume II-practical challenges, the first of which is presented in this manuscript. Additionally, the committee suggests actions by key stakeholders in the field (including organizations and professional societies) as the best path forward, encouraging the cultural shift needed to ensure responsible data sharing in the IO research setting

MutLα heterodimers modify the molecular phenotype of Friedreich ataxia

This article has been made available through the Brunel Open Access Publishing Fund.Background: Friedreich ataxia (FRDA), the most common autosomal recessive ataxia disorder, is caused by a dynamic GAA repeat expansion mutation within intron 1 of FXN gene, resulting in down-regulation of frataxin expression. Studies of cell and mouse models have revealed a role for the mismatch repair (MMR) MutS-heterodimer complexes and the PMS2 component of the MutLα complex in the dynamics of intergenerational and somatic GAA repeat expansions: MSH2, MSH3 and MSH6 promote GAA repeat expansions, while PMS2 inhibits GAA repeat expansions. Methodology/Principal Findings: To determine the potential role of the other component of the MutLα complex, MLH1, in GAA repeat instability in FRDA, we have analyzed intergenerational and somatic GAA repeat expansions from FXN transgenic mice that have been crossed with Mlh1 deficient mice. We find that loss of Mlh1 activity reduces both intergenerational and somatic GAA repeat expansions. However, we also find that loss of either Mlh1 or Pms2 reduces FXN transcription, suggesting different mechanisms of action for Mlh1 and Pms2 on GAA repeat expansion dynamics and regulation of FXN transcription. Conclusions/Significance: Both MutLα components, PMS2 and MLH1, have now been shown to modify the molecular phenotype of FRDA. We propose that upregulation of MLH1 or PMS2 could be potential FRDA therapeutic approaches to increase FXN transcription. © 2014 Ezzatizadeh et al.This article has been made available through the Brunel Open Access Publishing Fund

The value of ischemia-modified albumin compared with d-dimer in the diagnosis of pulmonary embolism

<p>Abstract</p> <p>Study objective</p> <p>The primary aim of this study was to investigate whether IMA levels are helpful in the diagnosis of pulmonary embolism (PE). The secondary aim was to determine whether IMA was more effective alone or in combination with clinical probability scores in the diagnosis of PE. Thirdly, the sensitivity and specificity of IMA is compared with D-dimer both with and without clinical probability scores in patients with suspected PE.</p> <p>Methods</p> <p>Consecutive patients presenting to the emergency department with suspected PE were prospectively recruited, and healthy volunteers were also enrolled as controls. D-dimer and IMA levels were measured for the entire study group. Wells and Geneva scores were calculated and s-CTPA was performed on all suspected PE patients.</p> <p>Results</p> <p>The study population consisted of 130 patients with suspected PE and 59 healthy controls. Mean IMA levels were 0.362 ± 0.11 ABSU for Group A, the PE group (n = 75); 0.265 ± 0.07 ABSU for Group B, the non-PE group (n = 55); and 0.175 ± 0.05 ABSU for Group C, the healthy control group (p < 0.0001). At a cut-off point of 0.25 ABSU, IMA was 93% sensitive and 75% specific in the diagnosis of PE. PPV was 79.4% and NPV was 78.6%. Mean D-dimer levels were 12.48 ± 10.88 μg/ml for Group A; 5.36 ± 7.80 μg/ml for Group B and 0.36 ± 0.16 μg/ml for Group C (p < 0.0001). The D-dimer cut-off point was 0.81 μg/ml with a sensitivity of 98.9% and a specificity of 62.7%, PPV of 69.4% and NPV of 83.3%. The use of IMA in combination with Wells and Geneva clinical probability scores was determined to have a positive impact on these scores' sensitivity and negative predictive values.</p> <p>Conclusion</p> <p>IMA is a good alternative to D-dimer in PE diagnosis in terms of both cost and efficiency. Used in combination with clinical probability scores, it has a similar positive effect on NPV and sensitivity to that of D-dimer. The PPV of IMA is better than D-dimer, but it is still unable to confirm a diagnosis of PE without additional investigation.</p

Mindfulness-Based Cognitive Therapy (MBCT) For Health Anxiety (Hypochondriasis): Rationale, Implementation and Case Illustration.

Recent research has shown that mindfulness-based cognitive therapy (MBCT) could be a useful alternative approach to the treatment of health anxiety and deserves further investigation. In this paper, we outline the rationale for using MBCT in the treatment of this condition, namely its hypothesised impact on the underlying mechanisms which maintain health anxiety, such as rumination and avoidance, hypervigilance to body sensations and misinterpretation of such sensations. We also describe some of the adaptations which were made to the MBCT protocol for recurrent depression in this trial and discuss the rationale for these adaptations. We use a case example from the trial to illustrate how MBCT was implemented and outline the experience of one of the participants who took part in an 8-week MBCT course. Finally, we detail some of the more general experiences of participants and discuss the advantages and possible limitations of this approach for this population, as well as considering what might be useful avenues to explore in future research

A taxonomy for vocal learning

Funding: ONR grant no. N00014-18-1-2062 and the MASTS pooling initiative (The Marine Alliance for Science and Technology for Scotland). MASTS is funded by the Scottish Funding Council (grant no. HR09011) and contributing institutions.Humans and songbirds learn to sing or speak by listening to acoustic models, forming auditory templates, and then learning to produce vocalizations that match the templates. These taxa have evolved specialized telencephalic pathways to accomplish this complex form of vocal learning, which has been reported for very few other taxa. By contrast, the acoustic structure of most animal vocalizations is produced by species-specific vocal motor programmes in the brainstem that do not require auditory feedback. However, many mammals and birds can learn to fine-tune the acoustic features of inherited vocal motor patterns based upon listening to conspecifics or noise. These limited forms of vocal learning range from rapid alteration based on real-time auditory feedback to long-term changes of vocal repertoire and they may involve different mechanisms than complex vocal learning. Limited vocal learning can involve the brainstem, mid-brain and/or telencephalic networks. Understanding complex vocal learning, which underpins human speech, requires careful analysis of which species are capable of which forms of vocal learning. Selecting multiple animal models for comparing the neural pathways that generate these different forms of learning will provide a richer view of the evolution of complex vocal learning and the neural mechanisms that make it possible. This article is part of the theme issue 'What can animal communication teach us about human language?'Publisher PDFPeer reviewe

Comparison of air displacement plethysmography to hydrostatic weighing for estimating total body density in children

BACKGROUND: The purpose of this study was to examine the accuracy of total body density and percent body fat (% fat) using air displacement plethysmography (ADP) and hydrostatic weighing (HW) in children. METHODS: Sixty-six male and female subjects (40 males: 12.4 ± 1.3 yrs, 47.4 ± 14.8 kg, 155.4 ± 11.9 cm, 19.3 ± 4.1 kg/m(2); 26 females: 12.0 ± 1.9 yrs, 41.4 ± 7.7 kg, 152.1 ± 8.9 cm, 17.7 ± 1.7 kg/m(2)) were tested using ADP and HW with ADP always preceding HW. Accuracy, precision, and bias were examined in ADP with HW serving as the criterion method. Lohman's equations that are child specific for age and gender were used to convert body density to % fat. Regression analysis determined the accuracy of ADP and potential bias between ADP and HW using Bland-Altman analysis. RESULTS: For the entire group (Y = 0.835x + 0.171, R(2 )= 0.84, SEE = 0.007 g/cm(3)) and for the males (Y = 0.837x + 0.174, R(2 )= 0.90, SEE = 0.006 g/cm(3)) the regression between total body density by HW and by ADP significantly deviated from the line of identity. However in females, the regression between total body density by HW and ADP did not significantly deviate from the line of identity (Y = 0.750x + 0.258, R(2 )= 0.55, SEE = 0.008 g/cm(3)). The regression between % fat by HW and ADP for the group (Y = 0.84x + 3.81, R(2 )= 0.83, SEE = 3.35 % fat) and for the males (Y = 0.84x + 3.25, R(2 )= 0.90, SEE = 3.00 % fat) significantly deviated from the line of identity. However, in females the regression between % fat by HW and ADP did not significantly deviate from the line of identity (Y = 0.81x + 5.17, R(2 )= 0.56, SEE = 3.80 % fat). Bland-Altman analysis revealed no bias between HW total body density and ADP total body density for the entire group (R = 0.-22; P = 0.08) or for females (R = 0.02; P = 0.92), however bias existed in males (R = -0.37; P ≤ 0.05). Bland-Altman analysis revealed no bias between HW and ADP % fat for the entire group (R = 0.21; P = 0.10) or in females (R = 0.10; P = 0.57), however bias was indicated for males by a significant correlation (R = 0.36; P ≤ 0.05), with ADP underestimating % fat at lower fat values and overestimating at the higher % fat values. CONCLUSION: A significant difference in total body density and % fat was observed between ADP and HW in children 10–15 years old with a potential gender difference being detected. Upon further investigation it was revealed that the study was inadequately powered, thus we recommend that larger studies that are appropriately powered be conducted to better understand this potential gender difference

Comprehensive Brain MRI Segmentation in High Risk Preterm Newborns

Most extremely preterm newborns exhibit cerebral atrophy/growth disturbances and white matter signal abnormalities on MRI at term-equivalent age. MRI brain volumes could serve as biomarkers for evaluating the effects of neonatal intensive care and predicting neurodevelopmental outcomes. This requires detailed, accurate, and reliable brain MRI segmentation methods. We describe our efforts to develop such methods in high risk newborns using a combination of manual and automated segmentation tools. After intensive efforts to accurately define structural boundaries, two trained raters independently performed manual segmentation of nine subcortical structures using axial T2-weighted MRI scans from 20 randomly selected extremely preterm infants. All scans were re-segmented by both raters to assess reliability. High intra-rater reliability was achieved, as assessed by repeatability and intra-class correlation coefficients (ICC range: 0.97 to 0.99) for all manually segmented regions. Inter-rater reliability was slightly lower (ICC range: 0.93 to 0.99). A semi-automated segmentation approach was developed that combined the parametric strengths of the Hidden Markov Random Field Expectation Maximization algorithm with non-parametric Parzen window classifier resulting in accurate white matter, gray matter, and CSF segmentation. Final manual correction of misclassification errors improved accuracy (similarity index range: 0.87 to 0.89) and facilitated objective quantification of white matter signal abnormalities. The semi-automated and manual methods were seamlessly integrated to generate full brain segmentation within two hours. This comprehensive approach can facilitate the evaluation of large cohorts to rigorously evaluate the utility of regional brain volumes as biomarkers of neonatal care and surrogate endpoints for neurodevelopmental outcomes