Journal: Genome Medicine

Article Title: Tumor-naïve ctDNA detection with deep learning-enhanced error suppression for sensitive mutation calling

doi: 10.1186/s13073-026-01694-y

Figure Lengend Snippet: Limitations of ultra deep sequencing for UMI based sequencing error correction on a custom CRC capture panel. A Shown is the average number of mutations covered by each panel according to respective panel size in kb as observed in the test subset of CRC patients ( n = 108), not used for TRON CRC panel design. Other panel include Agilent Custom Comprehensive Cancer Panel v2 (AGL), Burning Rock DX OncoScreen Plus (BRP), Integrated DNA Technologies xGen Pan-Cancer Panel (IDT), iGeneTech AIOnco-seq (IGT), Illumina TruSight Tumor 170 (ILM), QIAGEN Comprehensive cancer panel (QGN), Roche SeqCap EZ Choice custom PHC Panel (ROC), and Thermo Fisher Oncomine Comprehensive Assay v3 (TFS). B Histogram showing how patients of the CRC test dataset ( n = 108) distribute across different coverage levels ranging from not covered = 0 mutations to > = 10 mutations. C Estimated mean error rate by raw sequencing depths via down-sampling of sequencing reads for the three cell lines CL34, MOLT4, and PF382

Article Snippet: Synthetic cfDNA Pan-cancer Reference Standards were purchased from Twist Bioscience (WT and 5% VAF; 3.0 μg per tube [San Francisco, CA, US]).

Techniques: Sequencing, Sampling

Journal: Genome Medicine

Article Title: Tumor-naïve ctDNA detection with deep learning-enhanced error suppression for sensitive mutation calling

doi: 10.1186/s13073-026-01694-y

Figure Lengend Snippet: DeepES and RF classifier synergize for TWIST artificial ctDNA mutation detection. A Observed VAF in plasma cfDNA and matched PBMC DNA for tumor confirmed (blue) and not confirmed (green) mutations predicted in plasma cfDNA. B A schematic showing the steps of DEEPctMUT computational pipeline which includes: mapping to reference genome, UMI collapsing, candidate mutation generation, and three steps of error polishing. C The counts of true positive mutations (blue) and true negative positions (green) are shown for different observed VAF ranges in Twist spiked-in samples . D Recall, precision, and f1- score are shown for UMI (green), UMI + DeepES (blue), UMI + RF (red), UMI + DeepES + RF (grey), and UMI + DeepES + RF + matched PBMC (pink) across different VAF ranges

Article Snippet: Synthetic cfDNA Pan-cancer Reference Standards were purchased from Twist Bioscience (WT and 5% VAF; 3.0 μg per tube [San Francisco, CA, US]).

Techniques: Mutagenesis, Clinical Proteomics

Journal: Genome Medicine

Article Title: Tumor-naïve ctDNA detection with deep learning-enhanced error suppression for sensitive mutation calling

doi: 10.1186/s13073-026-01694-y

Figure Lengend Snippet: Our combined approach can accurately predict ctDNA in CRC patients. A Characteristics of 32 preoperative plasma samples derived from 31 CRC patients. For more details, see Additional file 1: Table S3. B cfDNA levels in ng/ml blood for healthy and CRC preoperative samples from primary and metastasized patients. C Comparison of mutation calls when applying different stages of the pipeline across 32 CRC patients. The left plot shows the number tumor- confirmed mutations, and the right plot shows tumor- unconfirmed mutations (a proxy for false positive) D Fragment length distribution of tumor confirmed, tumor unconfirmed, and healthy control mutations in plasma. E Called mutations of DEEPctMUT and DEEPctMUT without PBMC on a cohort of 22 CRC patients and 27 healthy controls. F Called mutations of DEEPctMUT, DEEPctMUT without PBMC, Avenio, and Avenio BAM files analyzed by PI DeepES and RF on an independent cohort of 10 CRC patients and 10 healthy controls according to two VAF ranges. G Patient-level performance of the DEEPctMUT, DEEPctMUT without PBMC, Avenio, and Avenio analyzed by PI DeepES and RF on 10 CRC patients and 10 healthy controls. For Avenio (with iDES), a VAF threshold of > 0.5% was applied. For all other pipelines, VAF > 0.03% was applied. H VAF with DEEPctMUT of mutations in metastatic and localized tumor samples

Article Snippet: Synthetic cfDNA Pan-cancer Reference Standards were purchased from Twist Bioscience (WT and 5% VAF; 3.0 μg per tube [San Francisco, CA, US]).

Techniques: Clinical Proteomics, Derivative Assay, Comparison, Mutagenesis, Control

Journal: ACS Omega

Article Title: Matrix-Aware LC–MS/MS Quantification of Cyhexatin in Chemically Complex Herbal Matrices Using DOE-Assisted Extraction Optimization

doi: 10.1021/acsomega.6c05657

Figure Lengend Snippet: Overview of the analytical workflow developed for LC–MS/MS determination of cyhexatin in herbal matrices. DOE-guided multivariate optimization (FFD followed by BBD) was applied to improve extraction recovery and quantitative performance. Matrix-matched calibration and surrogate IS normalization were subsequently used to reduce matrix-dependent bias and within-matrix signal variability during quantitative analysis.

Article Snippet: Cyhexatin reference standard (purity ≥99.7%) and triphenyl phosphate (TPP, purity ≥99.9%; Figure S1 ) were obtained from LGC Standards (Teddington, UK).

Techniques: Liquid Chromatography with Mass Spectroscopy, Extraction

Journal: ACS Omega

Article Title: Matrix-Aware LC–MS/MS Quantification of Cyhexatin in Chemically Complex Herbal Matrices Using DOE-Assisted Extraction Optimization

doi: 10.1021/acsomega.6c05657

Figure Lengend Snippet: Comparison of cyhexatin (100 ppb) recovery obtained under a representative empirical extraction condition for Angelicae Gigantis Radix and Paeoniae Radix. Bars represent mean recovery values and error bars indicate standard deviations ( n = 3). Individual points correspond to replicate measurements. The shaded region indicates the Codex acceptance range for pesticide residue recovery (70–120%). A statistically significant difference between the two matrices was observed (two-tailed Welch’s t -test, p = 0.00064). The pronounced divergence in recovery under identical extraction conditions illustrates the limitation of empirical optimization for chemically complex herbal matrices and supports the use of multivariate DOE optimization in the subsequent method development.

Article Snippet: Cyhexatin reference standard (purity ≥99.7%) and triphenyl phosphate (TPP, purity ≥99.9%; Figure S1 ) were obtained from LGC Standards (Teddington, UK).

Techniques: Comparison, Extraction, Residue, Two Tailed Test

Journal: ACS Omega

Article Title: Matrix-Aware LC–MS/MS Quantification of Cyhexatin in Chemically Complex Herbal Matrices Using DOE-Assisted Extraction Optimization

doi: 10.1021/acsomega.6c05657

Figure Lengend Snippet: Workflow of the modified QuEChERS-based sample preparation procedure used for the determination of cyhexatin in herbal medicines. The scheme illustrates sequential sample hydration, extraction using formic acid-modified hexane/MTBE, dispersive solid phase extraction cleanup, solvent evaporation, reconstitution in methanol, and final clarification prior to LC–MS/MS analysis.

Article Snippet: Cyhexatin reference standard (purity ≥99.7%) and triphenyl phosphate (TPP, purity ≥99.9%; Figure S1 ) were obtained from LGC Standards (Teddington, UK).

Techniques: Modification, Sample Prep, Extraction, Solvent, Evaporation, Clarification Assay, Liquid Chromatography with Mass Spectroscopy

Journal: ACS Omega

Article Title: Matrix-Aware LC–MS/MS Quantification of Cyhexatin in Chemically Complex Herbal Matrices Using DOE-Assisted Extraction Optimization

doi: 10.1021/acsomega.6c05657

Figure Lengend Snippet: Representative MRM chromatograms obtained under optimized LC–MS/MS conditions demonstrating method selectivity. Panels (A–C) correspond to (A) standard solution at the LLOQ level, (B) blank matrix extract, and (C) pre-extraction spiked sample at the LLOQ level. Screening (m/z 369.2 → 205.1) and confirmatory (m/z 369.2 → 287.3) transitions are shown for both Angelicae Gigantis Radix and Paeoniae Radix. The orange box indicates the expected retention time window of cyhexatin. A minor background signal was observed in the screening transition of the Angelicae Gigantis Radix blank extract within this window; however, no corresponding signal was detected in the confirmatory transition. The absence of a consistent screening-to-confirmatory transition ratio in the blank sample indicates that the observed signal originates from matrix-derived interference rather than residual analyte. In contrast, the characteristic screening-to-confirmatory transition ratio was consistently observed in both the standard and pre-extraction spiked samples. All chromatograms are displayed using identical intensity and time scales to allow direct comparison.

Article Snippet: Cyhexatin reference standard (purity ≥99.7%) and triphenyl phosphate (TPP, purity ≥99.9%; Figure S1 ) were obtained from LGC Standards (Teddington, UK).

Techniques: Liquid Chromatography with Mass Spectroscopy, Extraction, Derivative Assay, Comparison

Journal: bioRxiv

Article Title: Performance Evaluation of a Quantitative Metabolomics Workflow Incorporating Microchip Capillary Electrophoresis, Indexed Migration Time, and Single-Point External Calibration

doi: 10.64898/2026.07.10.737294

Figure Lengend Snippet: Performance of the end-to-end mCE-HRMS workflow across multiple biological matrices. (A) Principal components analysis (PCA) using 126 analytes with ≤50% CV in SPQC and ≤50% missing data across all measurements. Samples cluster by matrix type with no apparent inter-batch clustering; the SPQC (gray) plots at the centroid of all samples (PC1: 59.8%, PC2: 11.2%). (B) Metabolite coverage by sample type and metabolite class; the Library bar represents the full 325-compound target list. SPQC shows the broadest coverage due to contributions from all matrices. (C)Quantitative comparison of NIST SRM-1950 concentrations measured by the mCE-HRMS single-point calibration workflow versus published reference values from Mandal et al. (2025) for 64 metabolites in common (Deming slope = 0.862, pseudo-R 2 = 0.994). Cysteine (excluded from regression, asterisk) is elevated in the CE-MS data due to the addition of a reducing agent during sample preparation, which converts disulfide-bound cysteine to the free form.

Article Snippet: Metabolite reference standards for library construction were purchased from IROA Technologies (Ann Arbor, MI) and Cerilliant Corporation (Round Rock, TX).

Techniques: Comparison, Sample Prep