An evaluation of machine learning techniques to predict the outcome of children treated for Hodgkin-Lymphoma on the AHOD0031 trial: A report from the Children's Oncology Group

In this manuscript we analyze a data set containing information on children with Hodgkin Lymphoma (HL) enrolled on a clinical trial. Treatments received and survival status were collected together with other covariates such as demographics and clinical measurements. Our main task is to explore the potential of machine learning (ML) algorithms in a survival analysis context in order to improve over the Cox Proportional Hazard (CoxPH) model. We discuss the weaknesses of the CoxPH model we would like to improve upon and then we introduce multiple algorithms, from well-established ones to state-of-the-art models, that solve these issues. We then compare every model according to the concordance index and the brier score. Finally, we produce a series of recommendations, based on our experience, for practitioners that would like to benefit from the recent advances in artificial intelligence

Chidamide and Decitabine in Combination with a HAG Priming Regimen for Acute Myeloid Leukemia with TP53 Mutation

We analyzed the treatment effects of chidamide and decitabine in combination with a HAG (homoharringtonine, cytarabine, G-CSF) priming regimen (CDHAG) in acute myeloid leukemia (AML) patients with TP53 mutation. Seven TP53 mutated AML patients were treated with CDHAG. The treatment effects were assessed using hemogram detection and bone marrow aspirate. The possible side effects were evaluated based on both hematological and non-hematological toxicity. Four of the seven patients were classified as having achieved complete remission after CDHAG treatment; one patient was considered to have achieved partial remission, and the remaining two patients were considered in non-remission. The overall response rate (ORR) to CDHAG was 71.4%. Regarding the side effects, the hematological toxicity level of the seven patients ranged from level III to level IV, and infections that occurred at lung, blood, and skin were recorded. Nausea, vomiting, liver injury, and kidney injury were also detected. However, all side effects were attenuated by proper management. The CDHAG regimen clearly improved the ORR (71.4%) of TP53-mutated AML patients, with no severe side effects

Variant histology, IgD and CD30 expression in low‐risk pediatric nodular lymphocyte predominant Hodgkin lymphoma: A report from the Children’s Oncology Group

BackgroundHistologic prognostic factors have been described for nodular lymphocyte predominant Hodgkin lymphoma (NLPHL). This study examines histologic and immunophenotypic variants in a clinical trial for pediatric NLPHL.ProcedureOne hundred sixty‐eight cases of localized NLPHL were examined for histologic variants, CD30 and immunoglobulin D (IgD) expression, and outcome. Histologic types were scored categorically as 0 = 0, 1 ≤ 25%, and 2 > 25% of the sample.ResultsFifty‐eight (35.1%) cases showed only typical nodular with or without serpiginous histology (types A and B). The remainder showed mixtures of histologies. The numbers of patients with score 2 are 85 (50.6%) type A, 21 (12.5%) type B, 46 (27.4%) with extranodular large B cells (type C), 3 with T‐cell‐rich nodular pattern (type D), 55 (32.7%) with diffuse T‐cell‐rich (type E) pattern, and 2 (1.2%) with diffuse B‐cell pattern (type F). Higher level of types C (P = 0.048) and D (P = 0.033) resulted in lower event‐free survival (EFS). Cytoplasmic IgD was found in 65 of 130 tested (50%), did not significantly associate with EFS but positively correlated with types C and E histology (P < 0.0001) and negatively correlated with types A (P = 0.0003) and B (P = 0.006). Seventeen (10%) expressed CD30, with no adverse effect.ConclusionsVariant histology is common in pediatric NLPHL, especially types C and E, which are associated with IgD expression. Type C variant histology and possibly type D are associated with decreased EFS, but neither IgD nor CD30 are adverse features. Variant histology may warrant increased surveillance, but did not affect overall survival.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/139999/1/pbc26753_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/139999/2/pbc26753.pd

Evaluating Disparities in Proton Radiation Therapy Use in AHOD1331, a Contemporary Children\u27s Oncology Group Trial for Advanced-Stage Hodgkin Lymphoma

The indications for proton radiation therapy carry the strongest evidence in pediatric cancers. In a recently published letter, Bitterman et al reviewed factors associated with receipt of proton radiation therapy in patients enrolled in Children\u27s Oncology Group (COG) solid tumor and CNS tumor trials. They demonstrated that Black children were less likely to receive this treatment than non-Hispanic white patients, a disparity that persisted when controlling for other demographic and clinical variables. We strongly commend them for their work, as addressing racism and infrastructural barriers to care requires its identification

Wet-air co-electrolysis in high-temperature solid oxide electrolysis cell for production of ammonia feedstock

To significantly abate the carbon footprint in the conventional Haber-Bosch process, a novel approach based on wet air co-electrolysis in solid oxide electrolysis cell (SOEC) was proposed and evaluated in this study for sustainable single-step production of ammonia feedstock (i.e., H2/N2 mixture). An electrolyte-supported SOEC composed of LSCM-GDC cathode, SSZ electrolyte and LSCF-GDC anode was prepared and tested under various operation conditions. The current-voltage responses measured for wet air co-electrolysis were featured with three different regions which could be attributed to competitive and combinative effects of oxygen splitting reaction and water splitting reaction under wet air co-electrolysis operation. Gas chromatography (GC) analysis of the exit gas from the cathode chamber proved that high purity H2/N2 mixture had been produced successfully through the novel wet air co-electrolysis process. However, the obtained H2:N2 ratios were still much lower than the desired 3:1 ratio in the ammonia feedstock for the Haber-Bosch process. Further explorations will be made to increase the H2:N2 ratio in the produced gas mixture.Ministry of Education (MOE)This research project is funded by Academic Research Fund Tier 1 (ID 2021-T1-001-091) under Ministry of Education, Singapore

Estimation of Leaf Nitrogen Content of Winter Wheat Based on Akaike’s Information Criterion

International audienceNitrogen is one of the important indices for evaluation of crop growth and output quality. At present, there are a lot of researches on the estimation of crop nitrogen content, but most of the studies do not consider whether the model established by vegetation index and crop nitrogen content is the best. The purpose of this study was to estimate the nitrogen content of wheat leaves and to establish a method and the optimal model for monitoring nitrogen content in wheat leaves. Spectral reflectance of leaves and concurrent leaf nitrogen content parameters of samples were acquired in during 2013 and 2014 wheat growth season, in Beijing Academy of Agriculture and Forestry Sciences. 17 vegetation indices related to nitrogen content were chosen, and the relationship between related vegetation indices and leaf nitrogen content were built for screening vegetation indices with variable importance projection (VIP). Choosing first 10 different vegetation indices after ranking with VIP value as the independent variable for estimating nitrogen content of leaf in wheat. And the number of vegetation indices was gradually increased from top 4 to 10. The leaf nitrogen content estimation model with different vegetation indices can be built using the integrated model of variable importance projection (VIP) - partial least squares (PLS). At the same time, Akaike’s Information Criterion (AIC) value was calculated in different estimation model, and the AIC value of 7 different estimation model was compared. Then the optimal model with 5 vegetation indices was selected, which AIC value is the lowest. The optimal model was validated by leave one out cross-validation method. The result, (1) the comprehensive interpretation ability of the first 10 spectral indices on the nitrogen content of winter wheat leaves was PSSRc, GMI-2, SR705, RI-half, ZM, GMI-1, PSSRb, RI-3 dB, VOGc and CIred edge. (2) The optimal model with 5 vegetation indices was selected from 7 models. (3) The decision coefficient (R2) and root-mean-square error (RMSE) of the optimal model respectively were 0.73 and 0.33. The R2 and RMSE of wheat by validating were 0.73 and 0.33, respectively. The study showed: (1) The VIP-PLS model has higher ability to estimate the nitrogen content of leaf in wheat, which laying an important foundation for improving the precision of forecasting winter wheat leaf nitrogen content with remote sensing. (2) The AIC method can be used to select the optimal model, and the selected model has the higher predictive ability. And the optimal estimation model of wheat LNC can be obtained based on AIC

Experimental Study on the Bonding Performance between Shaped Steel and High-Strength Concrete

The integration of steel fibers into high-strength concrete (HSC) offers a solution to address the brittleness and limited ductility typically associated with conventional HSC structures. To investigate the bonding properties between shaped steel and high-strength concrete with steel fiber (SFRC), thirteen tests of the shaped steel/SFRC specimens are conducted to explore the effects of various factors such as steel fiber volume ratio, concrete strength grade, reinforcement ratio, steel embedment depth, and cover thickness on bond–slip behavior. Three distinct failure modes, such as pushout failure, bond splitting, and yielding failure of steel, are identified during the pushout tests. Three different types of bond strength, such as the initial bond strength, the ultimate bond strength, and the residual bond strength, are observed from the load–slip curves between the shaped steel and concrete. By incorporating nonlinear spring elements, a numerical model for accurately simulating the bond performance between the shaped steel and SFRC specimens is developed. The bond strength between the shaped steel and concrete increase as the concrete strength, cover thickness, steel fiber volume ratio, and stirrup ratio increase, while it decreases as the steel embedment depth increases. A model for the bond strength between shaped steel and SFRC is developed, and it agrees well with the test data

Estimation of Leaf Nitrogen Concentration of Winter Wheat Using UAV-Based RGB Imagery

International audienceLeaf nitrogen concentration (LNC) of winter wheat can reflect its nitrogen (N) status. Rapid, non-destructive and accurate monitoring of LNC of winter wheat has important practical applications in monitoring N nutrition and fertilizing management. The experimental site of winter wheat was located at Xiaotangshan National Demonstration Base of Precision Agricultural Research located in Changping District, Beijing, China. High spatial resolution digital images of the winter wheat were acquired using a low-cost unmanned aerial vehicle (UAV) with digital camera system at three key growth stages of booting, flowering and filling during April to June in 2015. Firstly, the acquired UAV digital images were mosaicked to generate a Digital Orthophoto Map (DOM) of the entire experimental site and 15 digital image variables were constructed. Then, based on the ground measured data onto LNC and digital image variables derived from the DOM for 48 sampling plots of winter wheat, linear and stepwise regression models were constructed for estimating LNC. Finally, the optimum model for estimating LNC was screened out by comprehensively considering the coefficient of determination (R2), the root mean square error (RMSE), the normalized root mean square error (nRMSE) and the simplicity of model calibrating and validating. The experimental results showed that the linear regression model of r/b that was one of the digital image variables for estimating LNC had the best accuracy with the model’s calibration and validation of R2, RMSE and nRMSE were 0.76, 0.40, 11.97% and 0.69, 0.43, 13.02%, respectively. The results suggest that it is feasible to estimate LNC of winter wheat based on the DOM acquired by UAV remote sensing platform carrying a low-cost, high-resolution digital camera, which can rapidly and non-destructively obtains the LNC of winter wheat experiment site and provide a quick and low-cost method for monitoring N nutrition and fertilizing management

A systematic investigation on the minimum tensile strengths and size effects of 3D printing polymers

Unlike isotropic homogenous materials, 3D printing polymers are anisotropic in terms of their strength and fracture toughness properties, according to previous research. Therefore, the lowest strength must be accurately measured before the extensive application of any 3D printing materials. Certain 3D printing materials have been increasingly employed in large structures; therefore, the size effect of their strengths has become very important. In this work, we performed a systematic experimental investigation on the minimum strengths and size effects of four common 3D printing polymers made by fusion deposition modeling and injection molding. Three types of tensile specimens with very different cross-sectional areas were selected. For each material system, two types of specimens with different printing surface angles were employed. The results from 200 specimens demonstrated that the minimum tensile strengths in the build direction of some specimens were only 25% that of the other directions in the same specimens, and 59% of the injection-molded specimens composed of the same material. No general conclusion on the size effects of the tensile strengths could be made for most specimens. Only the strengths along the build direction decreased up to 72% in two types of specific specimens if their cross-sectional areas increased by 60 times. Although their strengths were anisotropic, the stiffness properties of the 3D printing polymers were isotropic. Digital image correlation measurements showed that the Young's moduli of all specimens composed of the same material were similar. A dual-notch mechanics model was employed to explain the anisotropic strengths, and a fractography analysis supported the size effect