Predicting resistive wall mode stability in NSTX through balanced random forests and counterfactual explanations

Recent progress in the disruption event characterization and forecasting framework has shown that machine learning guided by physics theory can be easily implemented as a supporting tool for fast computations of ideal stability properties of spherical tokamak plasmas. In order to extend that idea, a customized random forest (RF) classifier that takes into account imbalances in the training data is hereby employed to predict resistive wall mode (RWM) stability for a set of high beta discharges from the NSTX spherical tokamak. More specifically, with this approach each tree in the forest is trained on samples that are balanced via a user-defined over/under-sampler. The proposed approach outperforms classical cost-sensitive methods for the problem at hand, in particular when used in conjunction with a random under-sampler, while also resulting in a threefold reduction in the training time. In order to further understand the model’s decisions, a diverse set of counterfactual explanations based on determinantal point processes (DPP) is generated and evaluated. Via the use of DPP, the underlying RF model infers that the presence of hypothetical magnetohydrodynamic activity would have prevented the RWM from concurrently going unstable, which is a counterfactual that is indeed expected by prior physics knowledge. Given that this result emerges from the data-driven RF classifier and the use of counterfactuals without hand-crafted embedding of prior physics intuition, it motivates the usage of counterfactuals to simulate real-time control by generating the β N levels that would have kept the RWM stable for a set of unstable discharges

Physics-guided machine learning approaches to predict the ideal stability properties of fusion plasmas

One of the biggest challenges to achieve the goal of producing fusion energy in tokamak devices is the necessity of avoiding disruptions of the plasma current due to instabilities. The disruption event characterization and forecasting (DECAF) framework has been developed in this purpose, integrating physics models of many causal events that can lead to a disruption. Two different machine learning approaches are proposed to improve the ideal magnetohydrodynamic (MHD) no-wall limit component of the kinetic stability model included in DECAF. First, a random forest regressor (RFR), was adopted to reproduce the DCON computed change in plasma potential energy without wall effects, , for a large database of equilibria from the national spherical torus experiment (NSTX). This tree-based method provides an analysis of the importance of each input feature, giving an insight into the underlying physics phenomena. Secondly, a fully-connected neural network has been trained on sets of calculations with the DCON code, to get an improved closed form equation of the no-wall limit as a function of the relevant plasma parameters indicated by the RFR. The neural network has been guided by physics theory of ideal MHD in its extension outside the domain of the NSTX experimental data. The estimated value of has been incorporated into the DECAF kinetic stability model and tested against a set of experimentally stable and unstable discharges. Moreover, the neural network results were used to simulate a real-time stability assessment using only quantities available in real-time. Finally, the portability of the model was investigated, showing encouraging results by testing the NSTX-trained algorithm on the mega ampere spherical tokamak (MAST)

Is there still a need for prophylactic intra-abdominal drainage in elective major gastro-intestinal surgery?

SummaryProphylactic drainage of the abdominal cavity after gastro-intestinal surgery is widely used. The rationale is that intra-abdominal drainage enhances early detection of complications (gastro-intestinal leakage, hemorrhage, bile leak), prevents collection of fluid or pus, reduces morbidity and mortality, and decreases the duration of hospital stay. However, dogmatic attitudes favoring systematic drain placement should be questioned. The aim of this review was to evaluate the evidence supporting systematic use of prophylactic abdominal drainage following gastrectomy, pancreatectomy, liver resection, and rectal resection. Based on this review of the literature: (i) there was no evidence in favor of intra-peritoneal drainage following total or sub-total gastrectomy with respect to morbidity-mortality, nor was it helpful in the diagnosis or management of leakage, however the level of evidence is low, (ii) following pancreatic resection, data are conflicting but, overall, suggest that the absence of drainage is prejudicial, and support the notion that short-term drainage is better than long-term drainage, (iii) after liver resection without hepatico-intestinal anastomosis, high level evidence supports that there is no need for abdominal drainage, and (iv) following rectal resection, data are insufficient to establish recommendations. However, results from the French multicenter randomized controlled trial GRECCAR5 (NCT01269567) should provide new evidence this coming year. Accumulating data support that systematic drainage of the abdominal cavity in digestive surgery is a non-beneficial and obsolete practice, except following pancreatectomy where the consensus appears to indicate the usefulness of short-term drainage. While the level of evidence is high for liver resections, new randomized controlled trials are awaited regarding gastric, pancreatic and rectal surgery

Exploration of the Equilibrium and Stability Properties of Spherical Tokamaks and Projection for MAST-U

In preparation for high fusion plasma performance operation of the newly operating spherical tokamak MAST-U, the equilibrium and stability properties of plasmas in the MAST database, as well as projections for MAST-U, are explored. The disruption event characterization and forecasting (DECAF) code is utilized to map disruptions in MAST, particularly with regard to vertical displacement events. Loss of vertical stability control was not found to be common in MAST, providing reassurance for MAST-U operation. MAST equilibria were reconstructed with magnetic diagnostics, adding kinetic diagnostics, or finally also adding magnetic pitch angle data. The reconstructions work well for MAST and the procedures are set up for MAST-U, including determination of the plasma current in the first MAST-U discharges. A 3D wall model of MAST-U has been constructed in the VALEN code, indicating that significant toroidal currents may be induced in the conducting structure. Rotation measurements may also be included in the reconstructions, and a test with the FLOW code of a rotating MAST plasma indicates a modest shift of the pressure contours off of the magnetic flux surfaces may be expected. Unstable resistive wall modes (RWMs) may constrain the performance of high pressure MAST-U plasmas. A machine learning (ML) assisted algorithm for stability calculation developed for the NSTX spherical tokamak has been applied to MAST plasmas. Improvements and expansion of the ML techniques continue, including semi-supervised learning techniques and a detection algorithm for unstable RWMs. Finally, projections of MAST-U plasma stability have been performed, indicating that a region of high pressure operational space exists in which the new passive stabilization plates act to stabilize ideal kink modes and RWMs may be stabilized by kinetic effects or active control

Leukocyte-specific protein 1 regulates T-cell migration in rheumatoid arthritis

Copy number variations (CNVs) have been implicated in human diseases. However, it remains unclear how they affect immune dysfunction and autoimmune diseases, including rheumatoid arthritis (RA). Here, we identified a novel leukocyte-specific protein 1 (LSP1) deletion variant for RA susceptibility located in 11p15.5. We replicated that the copy number of LSP1 gene is significantly lower in patients with RA, which correlates positively with LSP1 protein expression levels. Differentially expressed genes in Lsp1-deficient primary T cells represent cell motility and immune and cytokine responses. Functional assays demonstrated that LSP1, induced by T-cell receptor activation, negatively regulates T-cell migration by reducing ERK activation in vitro. In mice with T-cell-dependent chronic inflammation, loss of Lsp1 promotes migration of T cells into the target tissues as well as draining lymph nodes, exacerbating disease severity. Moreover, patients with RA show diminished expression of LSP1 in peripheral T cells with increased migratory capacity, suggesting that the defect in LSP1 signaling lowers the threshold for T-cell activation. To our knowledge, our work is the first to demonstrate how CNVs result in immune dysfunction and a disease phenotype. Particularly, our data highlight the importance of LSP1 CNVs and LSP1 insufficiency in the pathogenesis of RA and provide previously unidentified insights into the mechanisms underlying T-cell migration toward the inflamed synovium in RA.1187Ysciescopu

Informant-reported cognitive symptoms that predict amnestic mild cognitive impairment

<p>Abstract</p> <p>Background</p> <p>Differentiating amnestic mild cognitive impairment (aMCI) from normal cognition is difficult in clinical settings. Self-reported and informant-reported memory complaints occur often in both clinical groups, which then necessitates the use of a comprehensive neuropsychological examination to make a differential diagnosis. However, the ability to identify cognitive symptoms that are predictive of aMCI through informant-based information may provide some clinical utility in accurately identifying individuals who are at risk for developing Alzheimer's disease (AD).</p> <p>Methods</p> <p>The current study utilized a case-control design using data from an ongoing validation study of the Alzheimer's Questionnaire (AQ), an informant-based dementia assessment. Data from 51 cognitively normal (CN) individuals participating in a brain donation program and 47 aMCI individuals seen in a neurology practice at the same institute were analyzed to determine which AQ items differentiated aMCI from CN individuals.</p> <p>Results</p> <p>Forward stepwise multiple logistic regression analysis which controlled for age and education showed that 4 AQ items were strong indicators of aMCI which included: repetition of statements and/or questions [OR 13.20 (3.02, 57.66)]; trouble knowing the day, date, month, year, and time [OR 17.97 (2.63, 122.77)]; difficulty managing finances [OR 11.60 (2.10, 63.99)]; and decreased sense of direction [OR 5.84 (1.09, 31.30)].</p> <p>Conclusions</p> <p>Overall, these data indicate that certain informant-reported cognitive symptoms may help clinicians differentiate individuals with aMCI from those with normal cognition. Items pertaining to repetition of statements, orientation, ability to manage finances, and visuospatial disorientation had high discriminatory power.</p

Contribution of copy number variants (CNVs) to congenital, unexplained intellectual and developmental disabilities in Lebanese patients

International audienceBackground: Chromosomal microarray analysis (CMA) is currently the most widely adopted clinical test for patients with unexplained intellectual disability (ID), developmental delay (DD), and congenital anomalies. Its use has revealed the capacity to detect copy number variants (CNVs), as well as regions of homozygosity, that, based on their distribution on chromosomes, indicate uniparental disomy or parental consanguinity that is suggestive of an increased probability of recessive disease. Results: We screened 149 Lebanese probands with ID/DD and 99 healthy controls using the Affymetrix Cyto 2.7 M and SNP6.0 arrays. We report all identified CNVs, which we divided into groups. Pathogenic CNVs were identified in 12.1% of the patients. We review the genotype/phenotype correlation in a patient with a 1q44 microdeletion and refine the minimal critical regions responsible for the 10q26 and 16q monosomy syndromes. Several likely causative CNVs were also detected, including new homozygous microdeletions (9p23p24.1, 10q25.2, and 8p23.1) in 3 patients born to consanguineous parents, involving potential candidate genes. However, the clinical interpretation of several other CNVs remains uncertain, including a microdeletion affecting ATRNL1. This CNV of unknown significance was inherited from the patient's unaffected-mother; therefore, additional ethnically matched controls must be screened to obtain enough evidence for classification of this CNV. Conclusion: This study has provided supporting evidence that whole-genome analysis is a powerful method for uncovering chromosomal imbalances, regardless of consanguinity in the parents of patients and despite the challenge presented by analyzing some CNVs

Impact of Selection and Demography on the Diffusion of Lactase Persistence

BACKGROUND: The lactase enzyme allows lactose digestion in fresh milk. Its activity strongly decreases after the weaning phase in most humans, but persists at a high frequency in Europe and some nomadic populations. Two hypotheses are usually proposed to explain the particular distribution of the lactase persistence phenotype. The gene-culture coevolution hypothesis supposes a nutritional advantage of lactose digestion in pastoral populations. The calcium assimilation hypothesis suggests that carriers of the lactase persistence allele(s) (LCT*P) are favoured in high-latitude regions, where sunshine is insufficient to allow accurate vitamin-D synthesis. In this work, we test the validity of these two hypotheses on a large worldwide dataset of lactase persistence frequencies by using several complementary approaches. METHODOLOGY: We first analyse the distribution of lactase persistence in various continents in relation to geographic variation, pastoralism levels, and the genetic patterns observed for other independent polymorphisms. Then we use computer simulations and a large database of archaeological dates for the introduction of domestication to explore the evolution of these frequencies in Europe according to different demographic scenarios and selection intensities. CONCLUSIONS: Our results show that gene-culture coevolution is a likely hypothesis in Africa as high LCT*P frequencies are preferentially found in pastoral populations. In Europe, we show that population history played an important role in the diffusion of lactase persistence over the continent. Moreover, selection pressure on lactase persistence has been very high in the North-western part of the continent, by contrast to the South-eastern part where genetic drift alone can explain the observed frequencies. This selection pressure increasing with latitude is highly compatible with the calcium assimilation hypothesis while the gene-culture coevolution hypothesis cannot be ruled out if a positively selected lactase gene was carried at the front of the expansion wave during the Neolithic transition in Europe