Experimental and Numerical Investigation of One-Dimensional Electroosmotic Consolidation Based on Segment Inheritance Strategy

The attenuation of effective potential is a significant factor leading to the low postdrainage efficiency in the electroosmotic consolidation and drainage methods. In this study, the influence of the attenuation of effective potential on the electroosmotic consolidation process and the problem of solving the governing equations were investigated. A 102.5-hr one-dimensional electroosmotic consolidation test was performed to monitor the changes in the properties of the soil interior and the soil–electrode interface, and the variation curve of the effective potential in the test model was measured. The time-dependent nature of the potential distribution due to the attenuation of effective potential contradicts the assumption of introducing intermediate variables. To address this key issue, the variation curve of the effective potential was linearly segmented, ensuring the validity of introducing intermediate variables within each local state segment. Based on the continuity between state segments, the initial conditions of the governing equations in different state segments were updated, thereby extending the differential iteration within local state segments to the entire electroosmotic time domain. A finite-difference program for this method was developed using the Python language. Calculations and analyses based on the measured potential data were performed, revealing that a decrease in potential leads to a reduction in the effectiveness of electroosmotic drainage and consolidation in terms of the instantaneous distribution of pore pressure and the overall average degree of consolidation. This method can reflect the influence of the attenuation of effective potential on the pore water pressure during the electroosmotic consolidation process. The research findings of this paper can provide theoretical and numerical support for the improvement and engineering application of the electroosmotic consolidation and drainage method

Identification of potential antigenic peptides of Brucella through proteome and peptidome

Abstract Background Brucellosis, caused by Brucella spp., is a major zoonotic public health threat. Although several Brucella vaccines have been demonstrated for use in animals, Brucella spp. can cause human infection and to date, there are no human‐use vaccines licensed by any agency. Recently, methods in vaccine informatics have made major breakthroughs in peptide‐based epitopes, opening up a new avenue of vaccine development. Objectives The purpose of this article was to identify potential antigenic peptides in Brucella by proteome and peptidome analyses. Methods Mouse infection models were first established by injection with Brucella and spleen protein profiles were then analysed. Subsequently, the major histocompatibility complex class I or II (major histocompatibility complex [MHC]‐I/II)‐binding peptides in blood samples were collected by immunoprecipitation and peptides derived from Brucella proteins were identified through liquid chromatography–mass spectrometry (LC‐MS/MS). These peptides were then evaluated in a variety of ways, such as in terms of conservation in Brucella and synchronicity in predicted peptides (similarity and coverage), which allowed us to more effectively measure their antigenic potential. Results The expression of the inflammatory cytokines IL1B and IFN‐γ was significantly altered in the spleen of infected mice and some Brucella proteins, such as Muri, AcpP and GroES, were also detected. Meanwhile, in blood, 35 peptides were identified and most showed high conservation, highlighting their potential as antigen epitopes for vaccine development. In particular, we identified four proteins containing both MHC‐I‐ and MHC‐II‐binding peptides including AtpA, AtpD, DnaK and BAbS19_II02030. They were also compared with the predicted peptides to estimate their reliability. Conclusions The peptides we screened could bind to MHC molecules. After being stimulated with antigen T epitopes, Memory T cells can stimulate T cell activation and promote immune responses. Our results indicated that the peptides we identified may be good candidate targets for the design of subunit vaccines and these results pave the way for the study of safer vaccines against Brucella

Clinical and analytical validation of FoundationOne Liquid CDx, a novel 324-Gene cfDNA-based comprehensive genomic profiling assay for cancers of solid tumor origin.

As availability of precision therapies expands, a well-validated circulating cell-free DNA (cfDNA)-based comprehensive genomic profiling assay has the potential to provide considerable value as a complement to tissue-based testing to ensure potentially life-extending therapies are administered to patients most likely to benefit. Additional data supporting the clinical validity of cfDNA-based testing is necessary to inform optimal use of these assays in the clinic. The FoundationOne®Liquid CDx assay is a pan-cancer cfDNA-based comprehensive genomic profiling assay that was recently approved by FDA. Validation studies included >7,500 tests and >30,000 unique variants across >300 genes and >30 cancer types. Clinical validity results across multiple tumor types are presented. Additionally, results demonstrated a 95% limit of detection of 0.40% variant allele fraction for select substitutions and insertions/deletions, 0.37% variant allele fraction for select rearrangements, 21.7% tumor fraction for copy number amplifications, and 30.4% TF for copy number losses. The limit of detection for microsatellite instability and blood tumor mutational burden were also determined. The false positive variant rate was 0.013% (approximately 1 in 8,000). Reproducibility of variant calling was 99.59%. In comparison with an orthogonal method, an overall positive percent agreement of 96.3% and negative percent agreement of >99.9% was observed. These study results demonstrate that FoundationOne Liquid CDx accurately and reproducibly detects the major types of genomic alterations in addition to complex biomarkers such as microsatellite instability, blood tumor mutational burden, and tumor fraction. Critically, clinical validity data is presented across multiple cancer types