Junction tuning by ferroelectric switching in silicon nanowire Schottky-barrier field effect transistors

We report on a novel silicon nanowire-based field effect transistor with integrated ferroelectric gate oxide. The concept allows tuning the carrier transport in a non-volatile approach by switching the polarization in the ferroelectric layer close to the source Schottky-junction. We interpret the results in terms of tuning the transmissibility of the Schottky-junction for charge carriers. The experimental results provide a first step towards the integration of memory-in-logic concepts with reconfigurable nanowire transistors

Physical and circuit modeling of HfO2 based ferroelectric memories and devices

The discovery of ferroelectric properties in polycrystalline HfO2 has revived the interest in ferroelectric (FE) memories, which shows scaling feasibility allowing targeting high-density storage applications. In order to provide engineering guidelines for FE memory devices it is crucial to establish a correlation between the electrical device performances and the underlying physical mechanisms. In this work, we will discuss physical and circuit modeling approaches for FE memories connecting the FE HfO2 materials properties to the electrical performances of memory cells, artificial synapse for neuromorphic and in memory computing applications

2016 classification criteria for macrophage activation syndrome complicating systemic juvenile idiopathic arthritis: a European League Against Rheumatism/American College of Rheumatology/Paediatric Rheumatology International Trials Organisation collaborative initiative

OBJECTIVE: To develop criteria for the classification of macrophage activation syndrome (MAS) in patients with systemic juvenile idiopathic arthritis (JIA). METHODS: A multistep process, based on a combination of expert consensus and analysis of real patient data, was conducted. A panel of 28 experts was first asked to classify 428 patient profiles as having or not having MAS, based on clinical and laboratory features at the time of disease onset. The 428 profiles comprised 161 patients with systemic JIA-associated MAS and 267 patients with a condition that could potentially be confused with MAS (active systemic JIA without evidence of MAS, or systemic infection). Next, the ability of candidate criteria to classify individual patients as having MAS or not having MAS was assessed by evaluating the agreement between the classification yielded using the criteria and the consensus classification of the experts. The final criteria were selected in a consensus conference. RESULTS: Experts achieved consensus on the classification of 391 of the 428 patient profiles (91.4%). A total of 982 candidate criteria were tested statistically. The 37 best-performing criteria and 8 criteria obtained from the literature were evaluated at the consensus conference. During the conference, 82% consensus among experts was reached on the final MAS classification criteria. In validation analyses, these criteria had a sensitivity of 0.73 and a specificity of 0.99. Agreement between the classification (MAS or not MAS) obtained using the criteria and the original diagnosis made by the treating physician was high (κ = 0.76). CONCLUSION: We have developed a set of classification criteria for MAS complicating systemic JIA and provided preliminary evidence of its validity. Use of these criteria will potentially improve understanding of MAS in systemic JIA and enhance efforts to discover effective therapies, by ensuring appropriate patient enrollment in studies

Development and initial validation of the macrophage activation syndrome/primary hemophagocytic lymphohistiocytosis score, a diagnostic tool that differentiates primary hemophagocytic lymphohistiocytosis from macrophage activation syndrome

OBJECTIVE: To develop and validate a diagnostic score that assists in discriminating primary hemophagocytic lymphohistiocytosis (pHLH) from macrophage activation syndrome (MAS) related to systemic juvenile idiopathic arthritis. STUDY DESIGN: The clinical, laboratory, and histopathologic features of 362 patients with MAS and 258 patients with pHLH were collected in a multinational collaborative study. Eighty percent of the population was assessed to develop the score and the remaining 20% constituted the validation sample. Variables that entered the best fitted model of logistic regression were assigned a score, based on their statistical weight. The MAS/HLH (MH) score was made up with the individual scores of selected variables. The cutoff in the MH score that discriminated pHLH from MAS best was calculated by means of receiver operating characteristic curve analysis. Score performance was examined in both developmental and validation samples. RESULTS: Six variables composed the MH score: age at onset, neutrophil count, fibrinogen, splenomegaly, platelet count, and hemoglobin. The MH score ranged from 0 to 123, and its median value was 97 (1st-3rd quartile 75-123) and 12 (1st-3rd quartile 11-34) in pHLH and MAS, respectively. The probability of a diagnosis of pHLH ranged from <1% for a score of <11 to >99% for a score of  ≥123. A cutoff value of ≥60 revealed the best performance in discriminating pHLH from MAS. CONCLUSION: The MH score is a powerful tool that may aid practitioners to identify patients who are more likely to have pHLH and, thus, could be prioritized for functional and genetic testing

Development and Initial Validation of the Macrophage Activation Syndrome/Primary Hemophagocytic Lymphohistiocytosis Score, a Diagnostic Tool that Differentiates Primary Hemophagocytic Lymphohistiocytosis from Macrophage Activation Syndrome

Objective To develop and validate a diagnostic score that assists in discriminating primary hemophagocytic lymphohistiocytosis (pHLH) from macrophage activation syndrome (MAS) related to systemic juvenile idiopathic arthritis. Study design The clinical, laboratory, and histopathologic features of 362 patients with MAS and 258 patients with pHLH were collected in a multinational collaborative study. Eighty percent of the population was assessed to develop the score and the remaining 20% constituted the validation sample. Variables that entered the best fitted model of logistic regression were assigned a score, based on their statistical weight. The MAS/HLH (MH) score was made up with the individual scores of selected variables. The cutoff in the MH score that discriminated pHLH from MAS best was calculated by means of receiver operating characteristic curve analysis. Score performance was examined in both developmental and validation samples. Results Six variables composed the MH score: age at onset, neutrophil count, fibrinogen, splenomegaly, platelet count, and hemoglobin. The MH score ranged from 0 to 123, and its median value was 97 (1st-3rd quartile 75-123) and 12 (1st-3rd quartile 11-34) in pHLH and MAS, respectively. The probability of a diagnosis of pHLH ranged from 99% for a score of ≥123. A cutoff value of ≥60 revealed the best performance in discriminating pHLH from MAS. Conclusion The MH score is a powerful tool that may aid practitioners to identify patients who are more likely to have pHLH and, thus, could be prioritized for functional and genetic testing

Expert Consensus On Dynamics Of Laboratory Tests For Diagnosis Of Macrophage Activation Syndrome Complicating Systemic Juvenile Idiopathic Arthritis

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