CD43 signals induce Type One lineage commitment of human CD4+ T cells

<p>Abstract</p> <p>Background</p> <p>The activation and effector phenotype of T cells depend on the strength of the interaction of the TcR with its cognate antigen and additional signals provided by cytokines and by co-receptors. Lymphocytes sense both the presence of an antigen and also clues from antigen-presenting cells, which dictate the requisite response. CD43 is one of the most abundant molecules on the surface of T cells; it mediates its own signalling events and cooperates with those mediated by the T cell receptor in T cell priming. We have examined the role of CD43 signals on the effector phenotype of adult CD4⁺and CD8⁺human T cells, both alone and in the presence of signals from the TcR.</p> <p>Results</p> <p>CD43 signals direct the expression of IFNγ in human T cells. In freshly isolated CD4⁺T cells, CD43 signals potentiated expression of the IFNγ gene induced by TcR activation; this was not seen in CD8⁺T cells. In effector cells, CD43 signals alone induced the expression of the IFNγ gene in CD4⁺T cells and to a lesser extent in CD8⁺cells. The combined signals from CD43 and the TcR increased the transcription of the T-bet gene in CD4⁺T cells and inhibited the transcription of the GATA-3 gene in both populations of T cells, thus predisposing CD4⁺T cells to commitment to the T1 lineage. In support of this, CD43 signals induced a transient membrane expression of the high-affinity chains of the receptors for IL-12 and IFNγ in CD4⁺T cells. CD43 and TcR signals also cooperated with those of IL-12 in the induction of IFNγ expression. Moreover, CD43 signals induced the co-clustering of IFNγR and the TcR and cooperated with TcR and IL-12 signals, triggering a co-capping of both receptors in CD4⁺populations, a phenomenon that has been associated with a T1 commitment.</p> <p>Conclusion</p> <p>Our results suggest a key role for CD43 signals in the differentiation of human CD4⁺T cells into a T1 pattern.</p

Automatic analysis of facilitated taste-liking

This paper focuses on: (i) Automatic recognition of taste-liking from facial videos by comparatively training and evaluating models with engineered features and state-of-the-art deep learning architectures, and (ii) analysing the classification results along the aspects of facilitator type, and the gender, ethnicity, and personality of the participants. To this aim, a new beverage tasting dataset acquired under different conditions (human vs. robot facilitator and priming vs. non-priming facilitation) is utilised. The experimental results show that: (i) The deep spatiotemporal architectures provide better classification results than the engineered feature models; (ii) the classification results for all three classes of liking, neutral and disliking reach F1 scores in the range of 71%-91%; (iii) the personality-aware network that fuses participants’ personality information with that of facial reaction features provides improved classification performance; and (iv) classification results vary across participant gender, but not across facilitator type and participant ethnicity.EPSR

Vaccine Preventability of Meningococcal Clone, Greater Aachen Region, Germany

An emerging serogroup B clone can be prevented by vaccines

Development and Optimization of a Machine-Learning Prediction Model for Acute Desquamation After Breast Radiation Therapy in the Multicenter REQUITE Cohort.

Some patients with breast cancer treated by surgery and radiation therapy experience clinically significant toxicity, which may adversely affect cosmesis and quality of life. There is a paucity of validated clinical prediction models for radiation toxicity. We used machine learning (ML) algorithms to develop and optimise a clinical prediction model for acute breast desquamation after whole breast external beam radiation therapy in the prospective multicenter REQUITE cohort study. Using demographic and treatment-related features (m = 122) from patients (n = 2058) at 26 centers, we trained 8 ML algorithms with 10-fold cross-validation in a 50:50 random-split data set with class stratification to predict acute breast desquamation. Based on performance in the validation data set, the logistic model tree, random forest, and naïve Bayes models were taken forward to cost-sensitive learning optimisation. One hundred and ninety-two patients experienced acute desquamation. Resampling and cost-sensitive learning optimisation facilitated an improvement in classification performance. Based on maximising sensitivity (true positives), the "hero" model was the cost-sensitive random forest algorithm with a false-negative: false-positive misclassification penalty of 90:1 containing m = 114 predictive features. Model sensitivity and specificity were 0.77 and 0.66, respectively, with an area under the curve of 0.77 in the validation cohort. ML algorithms with resampling and cost-sensitive learning generated clinically valid prediction models for acute desquamation using patient demographic and treatment features. Further external validation and inclusion of genomic markers in ML prediction models are worthwhile, to identify patients at increased risk of toxicity who may benefit from supportive intervention or even a change in treatment plan. [Abstract copyright: © 2022 The Authors.

Shared heritability and functional enrichment across six solid cancers

Correction: Nature Communications 10 (2019): art. 4386 DOI: 10.1038/s41467-019-12095-8Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (r(g) = 0.57, p = 4.6 x 10(-8)), breast and ovarian cancer (r(g) = 0.24, p = 7 x 10(-5)), breast and lung cancer (r(g) = 0.18, p = 1.5 x 10(-6)) and breast and colorectal cancer (r(g) = 0.15, p = 1.1 x 10(-4)). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.Peer reviewe

Модель професійної культури юриста: критерії та підходи

В статті визначається модель професійної культури

Shared heritability and functional enrichment across six solid cancers

Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (r(g) = 0.57, p = 4.6 x 10(-8)), breast and ovarian cancer (r(g) = 0.24, p = 7 x 10(-5)), breast and lung cancer (r(g) = 0.18, p = 1.5 x 10(-6)) and breast and colorectal cancer (r(g) = 0.15, p = 1.1 x 10(-4)). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis

Attachment, personality and psychopathology in adolescence

The relationships among attachment classification, psychopathology and personality traits were examined in a group of psychiatrically hospitalized adolescents. In addition, the concordance between the adolescents\u27 and their mothers\u27 attachment classification was examined. The attachment organization of 60 adolescents admitted to a private psychiatric hospital for serious psychopathology and 27 of their mothers was assessed with the Adult Attachment Interview. Psychiatric diagnoses and symptomatology of the adolescents were evaluated with standardized clinical interviews, projective psychological tests, self-report and observer measures of symptomatology, and a self-report measure of personality traits. Consistent and predicted relationships emerged between the adolescents\u27 attachment organization and psychopathology, symptomatology and personality traits. A high degree of concordance was found between maternal and adolescent attachment classification. The Autonomous adolescent group was highly coherent in its discussion of childhood experience but showed no association with psychopathology or personality. The adolescent group Dismissing of attachment was associated with Conduct and Substance Abuse Disorders, denial of psychiatric symptomatology, and narcissistic, antisocial and histrionic personality traits. The adolescent group Preoccupied by attachment was associated with Affective Disorders, overt disclosure of symptomatic distress and avoidant, dependent, schizotypal and dysthymic personality traits. Sex differences in both diagnosis and attachment classification were found, with males more likely to be Dismissing and Conduct Disordered or Substance Abusing and females more likely to be Preoccupied. These findings were interpreted in terms of differing styles of affect regulation and defensive bias resulting from the internalization of relational histories with parents

Comparative and Prospective Study of Different Immune Parameters in Healthy Subjects at Risk for Tuberculosis and in Tuberculosis Patients

It has not been fully elucidated which of the components of the immune response against Mycobacterium tuberculosis is indicative of resistance or susceptibility. The aim of this study was to identify an immune parameter that could be indicative of either resistance or susceptibility to M. tuberculosis infection. We prospectively studied (three determinations, at months 0, 8, and 12) 15 patients with chronic pulmonary tuberculosis and 42 healthy individuals with a recent and frequent contact with tuberculosis patients. Peripheral blood mononuclear cells were stimulated with a whole-protein extract or the 30-kDa antigen of M. tuberculosis for 6 days, and several immune parameters were determined. No consistent differences between tuberculosis patients and healthy controls were detected in most immune parameters studied, including the expression of different activation antigens, cytokine secretion, lymphocyte proliferation, and nitric oxide production. However, the synthesis of tumor necrosis factor alpha, the intracellular detection of gamma interferon, and the apoptosis of monocytes under certain culture conditions tended to show clear-cut differences in cells from patients and controls (P < 0.05 in all cases for most determinations). Nevertheless, when results were analyzed on an individual basis, it was evident that a significant degree of overlapping of values from patients and controls occurred for all parameters studied. We conclude that although the immune parameters tested do not allow the identification of individuals susceptible to M. tuberculosis, the specificity and sensitivity of some of them could be improved through future studies