6 research outputs found
TCR-Signaling Events in Cellular Metabolism and Specialization
Engaging the T cell receptor (TCR) with peptide:MHC complexes initiates a cascade of signaling events that activates T cells in an antigen specific manner. It is now clear that multiple inputs, including the strength of TCR signaling, co-stimulation, and the cytokine environment, impact T cell specialization decisions in the context of specific pathogenic encounters. Additionally, it is now appreciated that these same stimuli direct cellular metabolism programs. In this review, we will discuss how TCR-signaling events coordinate cellular metabolism and specialization gene programs in T cells
Translating JAKs to Jakinibs
The discovery of JAKs and STATs and their roles in cytokine and IFN action represented a significant basic advance and a new paradigm in cell signaling. This was quickly followed by discoveries pointing to their essential functions, including identification of mutations as a cause of SCID. This and other findings predicted the use of therapeutically targeting JAKs as a new strategy for treating immune and inflammatory diseases. This now is a reality with seven approved jakinibs being used to treat multiple forms of arthritis, inflammatory bowel disease and myeloproliferative neoplasms, and numerous ongoing clinical trials in other settings. This story provides interesting insights into the process of translating basic discoveries and also reveals the need to return to basic work to fill gaps that now become apparent
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Inhibition of IL-2 responsiveness by IL-6 is required for the generation of GC-T FH cells
IL-6–mediated inhibition of CD122 allows T
FH
cells to receive TCR signaling without initiating an inhibitory TCR/IL-2 loop (see the related Focus by
Zhou and Yu
)..
Unraveling a paradox
Germinal center T follicular helper (GC-T
FH
) cells are maintained through sustained TCR stimulation, but TCR activation induces IL-2 production and IL-2 receptor expression, which can inhibit T
FH
cells. Papillion
et al.
now explore this paradox using an influenza infection model, where they observe that GC-T
FH
cells can produce large amounts of IL-2 but are relatively unresponsive to this cytokine. Intrinsic IL-6 signaling is required to maintain this state of hyporesponsiveness, which involves a mechanism by which IL-6 prevents STAT5 from associating with Il2rb locus and thereby prevents up-regulation of IL-2Rβ (CD122). This allows GC-T
FH
cells to tolerate sustained TCR activation without triggering inhibitory IL-2 responses, thus revealing a regulatory mechanism that modulates GC-T
FH
cell generation (see the related Focus by
Zhou and Yu
).
Sustained T cell receptor (TCR) stimulation is required for maintaining germinal center T follicular helper (GC-T
FH
) cells. Paradoxically, TCR activation induces interleukin-2 receptor (IL-2R) expression and IL-2 production, thereby initiating a feedback loop of IL-2 signaling that normally inhibits T
FH
cells. It is unclear how GC-T
FH
cells can receive prolonged TCR signaling without succumbing to the detrimental effects of IL-2. Using an influenza infection model, we show here that GC-T
FH
cells secreted large amounts of IL-2 but responded poorly to it. To maintain their IL-2 hyporesponsiveness, GC-T
FH
cells required intrinsic IL-6 signaling. Mechanistically, we found that IL-6 inhibited up-regulation of IL-2Rβ (CD122) by preventing association of STAT5 with the
Il2rb
locus, thus allowing GC-T
FH
cells to receive sustained TCR signaling and produce IL-2 without initiating a TCR/IL-2 inhibitory feedback loop. Collectively, our results identify a regulatory mechanism that controls the generation of GC-T
FH
cells
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Clinical prediction rule for SARS-CoV-2 infection from 116 U.S. emergency departments 2-22-2021
Objectives: Accurate and reliable criteria to rapidly estimate the probability of infection with the novel coronavirus-2 that causes the severe acute respiratory syndrome (SARS-CoV-2) and associated disease (COVID-19) remain an urgent unmet need, especially in emergency care. The objective was to derive and validate a clinical prediction score for SARS-CoV-2 infection that uses simple criteria widely available at the point of care. Methods: Data came from the registry data from the national REgistry of suspected COVID-19 in EmeRgency care (RECOVER network) comprising 116 hospitals from 25 states in the US. Clinical variables and 30-day outcomes were abstracted from medical records of 19,850 emergency department (ED) patients tested for SARS-CoV-2. The criterion standard for diagnosis of SARS-CoV-2 required a positive molecular test from a swabbed sample or positive antibody testing within 30 days. The prediction score was derived from a 50% random sample (n = 9,925) using unadjusted analysis of 107 candidate variables as a screening step, followed by stepwise forward logistic regression on 72 variables. Results: Multivariable regression yielded a 13-variable score, which was simplified to a 13-point score: +1 point each for age>50 years, measured temperature>37.5°C, oxygen saturation75% probability with +5 or more points). Conclusion: Criteria that are available at the point of care can accurately predict the probability of SARS-CoV-2 infection. These criteria could assist with decisions about isolation and testing at high throughput checkpoints.</p
Clinical prediction rule for SARS-CoV-2 infection from 116 U.S. emergency departments 2-22-2021.
Objectives
Accurate and reliable criteria to rapidly estimate the probability of infection with the novel coronavirus-2 that causes the severe acute respiratory syndrome (SARS-CoV-2) and associated disease (COVID-19) remain an urgent unmet need, especially in emergency care. The objective was to derive and validate a clinical prediction score for SARS-CoV-2 infection that uses simple criteria widely available at the point of care.
Methods
Data came from the registry data from the national REgistry of suspected COVID-19 in EmeRgency care (RECOVER network) comprising 116 hospitals from 25 states in the US. Clinical variables and 30-day outcomes were abstracted from medical records of 19,850 emergency department (ED) patients tested for SARS-CoV-2. The criterion standard for diagnosis of SARS-CoV-2 required a positive molecular test from a swabbed sample or positive antibody testing within 30 days. The prediction score was derived from a 50% random sample (n = 9,925) using unadjusted analysis of 107 candidate variables as a screening step, followed by stepwise forward logistic regression on 72 variables.
Results
Multivariable regression yielded a 13-variable score, which was simplified to a 13-point score: +1 point each for age>50 years, measured temperature>37.5°C, oxygen saturation75% probability with +5 or more points).
Conclusion
Criteria that are available at the point of care can accurately predict the probability of SARS-CoV-2 infection. These criteria could assist with decisions about isolation and testing at high throughput checkpoints