Raising the spectra of T-cell profiling

Murphy, William J.

doi:10.1182/blood-2008-07-165795

Cited by 2 publications

(3 citation statements)

References 7 publications

(3 reference statements)

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“…A required normalization parameter for this model is the radio flux at 1 GHz. We use a value of 1.24 Jy, which has been derived by starting with the value from Reynolds et al (2009), 1.17 GHz, and accounting for for the observed increase of the radio flux of roughly 1.2% per year (Murphy et al 2008). Figure 5 shows that the srcut model gives an excellent fit (reduced χ 2 of 1.06) over the whole energy band from 0.5 to 30 keV.…”

Section: Discussionmentioning

confidence: 99%

The Hard X-Ray View of the Young Supernova Remnant G1.9+0.3

Zoglauer

Reynolds

et al. 2014

ApJ

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NuSTAR observed G1.9+0.3, the youngest known supernova remnant in the Milky Way, for 350 ks and detected emission up to ∼30 keV. The remnant's X-ray morphology does not change significantly across the energy range from 3 to 20 keV. A combined fit between NuSTAR and Chandra shows that the spectrum steepens with energy. The spectral shape can be well fitted with synchrotron emission from a power-law electron energy distribution with an exponential cutoff with no additional features. It can also be described by a purely phenomenological model such as a broken powerlaw or a power-law with an exponential cutoff, though these descriptions lack physical motivation. Using a fixed radio flux at 1 GHz of 1.17 Jy for the synchrotron model, we get a column density of N H = (7.23 ± 0.07) × 10 22 cm −2 , a spectral index of α = 0.633 ± 0.003, and a roll-off frequency of ν rolloff = (3.07 ± 0.18) × 10 17 Hz. This can be explained by particle acceleration, to a maximum energy set by the finite remnant age, in a magnetic field of about 10 µG, for which our roll-off implies a maximum energy of about 100 TeV for both electrons and ions. Much higher magnetic-field strengths would produce an electron spectrum that was cut off by radiative losses, giving a much higher roll-off frequency that is independent of magnetic-field strength. In this case, ions could be accelerated to much higher energies. A search for 44 Ti emission in the 67.9 keV line results in an upper limit of 1.5 × 10 −5 ph cm −2 s −1 assuming a line width of 4.0 keV (1 sigma). Subject headings: supernova remnants -X-rays: individual (G1.9+0.3)

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Section: Discussionmentioning

confidence: 99%

The Hard X-Ray View of the Young Supernova Remnant G1.9+0.3

Zoglauer

Reynolds

et al. 2014

ApJ

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“…There has been much historical interest in these factors, and although efforts have been made to profile patient T-cell repertoires after HSCT using spectratyping, they have always yielded an incomplete view [33]. Now, using TCR-seq, investigators can examine more comprehensively the repertoires of HSCT patients, yielding much more incisive and reliable insights into post-HSCT repertoire reconstitution.…”

Section: New Insights From T-cell Repertoire Analysis By Tcr-seqmentioning

confidence: 99%

“…Numerous T-cell repertoire considerations are relevant to this procedure, including: (i) the source of the HSCs - bone marrow, peripheral blood or umbilical cord, autologous or allogeneic; (ii) the risk for, incidence of, and potential methods for mitigation and treatment of ‘graft versus host disease’ (GVHD) post-transplant (wherein donor T cells are reactive against host antigens); (iii) the prevention and treatment of post-transplant infection and malignancy resulting from lymphopenia and immunosuppression; and (iv) the timescale and nature of the post-transplant reconstitution of the TCR repertoire. There has been much historical interest in these factors, and although efforts have been made to profile patient T-cell repertoires after HSCT using spectratyping, they have always yielded an incomplete view [ 33 ]. Now, using TCR-seq, investigators can examine more comprehensively the repertoires of HSCT patients, yielding much more incisive and reliable insights into post-HSCT repertoire reconstitution.…”

Section: New Insights From T-cell Repertoire Analysis By Tcr-seqmentioning

confidence: 99%

Sequence analysis of T-cell repertoires in health and disease

2013

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T-cell antigen receptor (TCR) variability enables the cellular immune system to discriminate between self and non-self. High-throughput TCR sequencing (TCR-seq) involves the use of next generation sequencing platforms to generate large numbers of short DNA sequences covering key regions of the TCR coding sequence, which enables quantification of T-cell diversity at unprecedented resolution. TCR-seq studies have provided new insights into the healthy human T-cell repertoire, such as revised estimates of repertoire size and the understanding that TCR specificities are shared among individuals more frequently than previously anticipated. In the context of disease, TCR-seq has been instrumental in characterizing the recovery of the immune repertoire after hematopoietic stem cell transplantation, and the method has been used to develop biomarkers and diagnostics for various infectious and neoplastic diseases. However, T-cell repertoire sequencing is still in its infancy. It is expected that maturation of the field will involve the introduction of improved, standardized tools for data handling, deposition and statistical analysis, as well as the emergence of new and equivalently large-scale technologies for T-cell functional analysis and antigen discovery. In this review, we introduce this nascent field and TCR-seq methodology, we discuss recent insights into healthy and diseased TCR repertoires, and we examine the applications and challenges for TCR-seq in the clinic.

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Raising the spectra of T-cell profiling

Cited by 2 publications

References 7 publications

The Hard X-Ray View of the Young Supernova Remnant G1.9+0.3

The Hard X-Ray View of the Young Supernova Remnant G1.9+0.3

Sequence analysis of T-cell repertoires in health and disease

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