Journal: medRxiv

Article Title: Bio-Rad and QIAGEN digital PCR platforms provide equivalent quantification for wastewater-based SARS-CoV-2 surveillance

doi: 10.64898/2026.01.20.26344437

Figure Lengend Snippet: Quantitative comparison of SARS-CoV-2 targets between Bio-Rad QX200 ddPCR and QIAGEN QIAcuity dPCR platforms across all concentration ranges. Scatter plots showing hyperwelled (merged triplicate) concentrations for (A) N1 gene target and (B) N2 gene target. Each point represents a single wastewater sample (n = 95) plotted as log 10 copies L -1 on both axes. Samples are color-coded by concentration bin: high (red, 5×10 4 to 5×10 5 copies L -1 , n=31), medium (orange, 5×10 3 to 5×10 4 copies L -1 , n=32), and low (blue, 1×10 3 to 5×10 3 copies L -1 , n=31). Solid black line represents perfect 1:1 agreement; dashed line showed linear regression fit. Linear regression equations, R 2 values, and 95% confidence intervals (gray shading) are displayed for each target. Mean absolute differences between platforms: N1 = 0.10 log copies L -1 , N2 = 0.06 log copies L -1 . All correlations significant at p < 0.001.

Article Snippet: Total nucleic acids were eluted in 100μL of Buffer AE (19077, QIAGEN, Germantown, MD) and transferred into 96-Well ddPCR Plates (12001925, Bio-Rad Laboratories).

Techniques: Comparison, Concentration Assay

Journal: bioRxiv

Article Title: Ex vivo stem-like cell families model evolution of glioblastoma therapeutic resistance

doi: 10.64898/2026.04.02.716158

Figure Lengend Snippet: ( A ) Schematic of ex vivo treatment of whole GBM cell populations and generation of res-GSC families with chemo- or radiotherapy. Whole GBM cell suspensions are cultured in stem cell medium (EFPH20) supplemented with EGF, FGF2, PDGFBB, and HGF (20 ng/mL each) and exposed in parallel to temozolomide (TMZ) or ionizing radiation (IR) as indicated. Each res-GSC family includes TMZ-GSC, IR-GSC, and an untreated CTRL-GSC member. Families were considered established after passage 10. ( B ) Genetic profiling of original GBMs (n = 25) grouped by ability to generate res-GSC families under therapeutic pressure (columns). Top rows: res-GSC family members derived from each GBM (black squares). Bottom rows: altered genes and frequencies in original GBMs assessed by the NGS GBM-target panel. p TERT mutation was evaluated by ddPCR. Purple: GBMs yielding res-GSC families; light orange: GBMs yielding only CTRL-GSCs. ( C ) Associations between genetic alterations in original GBMs and res-GSC family derivation. Bars indicate the number of GBMs that are wild-type (wt) or altered (alt) for each gene and that did (dark gray) or did not (light grey) yield res-GSC families. Thicker dotted outline: tendency to anti-correlation between EGFR alterations and res-GSC family generation (p=0.40). PTEN loss and PIK3CA alterations showed gene-level trends (p = 0.06 and p > 0.99, respectively), while combined AKT-pathway alterations ( PTEN and PIK3CA ) were significantly associated with res-GSC family derivation (p = 0.03). TP53 mutations were also significantly associated (p = 0.0005) (Fisher’s exact test). Red: oncogenes. Blue: tumor suppressor genes. ( D-E ) Derivation times of TMZ-GSCs (D, upper) and IR-GSCs (E) from GBM processing (as in B ) to p5. Bars show the percentage increase in derivation time relative to the matched CTRL-GSC. Grey dotted bars: not derived GSCs. Absolute derivation times (days) are reported in . In ( D ), dots indicate the MGMT status of the original GBM (or of CTRL-GSC when the GBM status was unavailable). Lower panel: schematic of the functional relationship between MGMT promoter methylation and MGMT transcription (arrow).

Article Snippet: To detect possibly rare gene alterations in original UA, ddPCR was performed using probe–based assays with ddPCR Supermix for Probes (no dUTP) (Biorad), according to manufacturer’s instructions.

Techniques: Ex Vivo, Cell Culture, Derivative Assay, Mutagenesis, Functional Assay, Methylation

Journal: bioRxiv

Article Title: Ex vivo stem-like cell families model evolution of glioblastoma therapeutic resistance

doi: 10.64898/2026.04.02.716158

Figure Lengend Snippet: ( A ) Pathogenic alterations (variant allele frequency, VAF, and gene copy number variation, CNV) detected by the NGS GBM-target panel or ddPCR (p TERT ) in MGMT-neg whole GBMs and matched CTRL-GSCs and TMZ-GSCs. MSS: microsatellite stable; MSI: microsatellite instable, assessed at passage 10. ( B ) MMR activity measured by FM-HCR in matched CTRL-GSC and TMZ-GSC from GBM17 and GBM151 families, 24 hours after transfection. Data are z-values (mean ± SEM). n = 2 independent experiments for GM17 and n = 3 independent experiments for GBM151, Student’s paired t test. GBM17: *p=0.018734; GBM151: *p= 0.006080. ( C ) Ploidy (n) in MGMT-pos (orange square) and MGMT-neg (green square) TMZ-GSCs and CTRL-GSCs assessed by chromosome G-banding. ( D ) Cumulative chromosomal aberration number in all TMZ-GSCs vs. matched CTRL-GSCs, assessed by G-banding and multicolor fluorescent in situ hybridization (M-FISH). Data are shown as delta versus the corresponding CTRL-GSC; median is indicated. One sample Wilcoxon test. *p=0.0156.

Article Snippet: To detect possibly rare gene alterations in original UA, ddPCR was performed using probe–based assays with ddPCR Supermix for Probes (no dUTP) (Biorad), according to manufacturer’s instructions.

Techniques: Variant Assay, Activity Assay, Transfection, In Situ Hybridization

Journal: bioRxiv

Article Title: Ex vivo stem-like cell families model evolution of glioblastoma therapeutic resistance

doi: 10.64898/2026.04.02.716158

Figure Lengend Snippet: ( A ) BRAF (top panel) and TP53 (bottom panel) mutations evaluated by ddPCR in GBM149 parental GBM, CTRL-GSC and TMZ-GSC. Data are shown as fractional abundance of the indicated mutant (black) and wild type (grey) alleles. ( B ) Representative metaphase images showing chromosome number and aberrations in all res-GSC families evaluated by G-banding and M-FISH.

Article Snippet: To detect possibly rare gene alterations in original UA, ddPCR was performed using probe–based assays with ddPCR Supermix for Probes (no dUTP) (Biorad), according to manufacturer’s instructions.

Techniques: Mutagenesis

Journal: bioRxiv

Article Title: Ex vivo stem-like cell families model evolution of glioblastoma therapeutic resistance

doi: 10.64898/2026.04.02.716158

Figure Lengend Snippet: ( A ) Genetic profiling of matched CTRL-GSCs and IR-GSCs using the NGS GBM-target panel; p TERT mutations were assessed by ddPCR. Samples are ordered by primary and secondary radioresistance. *Significant increase in MYCN copy number; see also A Table EV4. ( B ) Ploidy (n) of matched CTRL-GSCs e IR-GSCs assessed by chromosome G-banding. ( C ) Cumulative chromosomal aberration number in all IR-GSCs vs. matched CTRL-GSCs, assessed by G-banding and M-FISH. Median number is indicated. Data are shown as delta relative to the corresponding CTRL-GSC; median is indicated. One-sample Wilcoxon test. *p = 0.0313. ( D ) Western blots showing phospho-H2AX (γH2AX), phospho-CHK2 (pCHK2; Tyr68), total CHK2 and p21 in GBM95 CTRL-GSC and IR-GSC in a representative time-course experiment after a single 5 Gy dose. Calnexin: loading control. ( E-F ) Immunofluorescence for phospho-H2AX (γH2AX) in GBM95 CTRL-GSC and IR-GSC in a time-course experiment after a single 5 Gy dose. ( E ) Quantification of γH2AX-positive cell nuclei. n = 4 technical replicates, Student’s paired t test. * p<0.000001. ( F ) Representative images. Scale bar, 25 μm. ( G ) Fraction of GBM95 CTRL-GSC and IR-GSC cells in G2 and M phases, measured by flow cytometry using phospho-Histone 3 (pH3; Ser10) staining at 6 and 24 h after a single 5 Gy dose, shown as fold change vs. mock. Mock: no IR. n = 2 independent experiments, Student’s paired t test. ( H ) Schematic of adaptive mechanisms of secondary radioresistance in GBM95 GSC family. In (E, G), data are presented as mean ± SEM.

Article Snippet: To detect possibly rare gene alterations in original UA, ddPCR was performed using probe–based assays with ddPCR Supermix for Probes (no dUTP) (Biorad), according to manufacturer’s instructions.

Techniques: Western Blot, Control, Immunofluorescence, Flow Cytometry, Staining

Journal: Methods (San Diego, Calif.)

Article Title: In pursuit of sensitivity: Lessons learned from viral nucleic acid detection and quantification on the Raindance ddPCR platform

doi: 10.1016/j.ymeth.2021.04.008

Figure Lengend Snippet: DNA input upper limit test on the Raindance ddPCR platform. Each 50 μL, SIV and CCR5 duplex ddPCR reaction was loaded with 1 million to 8 million cell equivalent genomic DNA extracted from the duodenum of an SIVmac239-infected rhesus macaque (animal 313–08) that was treated with combination antiretrovirals. Note that as the input DNA amount was progressively increased, the separation between clusters was less distinct, and when the total DNA input in each reaction was 5 million cell equivalent or more, there were no distinct signal clusters. SIV+, target cluster containing SIV signal. SIV+ CCR5+, dual occupancy cluster.

Article Snippet: Most of the discussion uses a human HIV infection model and the Raindance ddPCR platform as an example, but the technical considerations presented herein are applicable and can be adapted to a broad range of applications where highly sensitive nucleic acid detection is required.

Techniques: Infection

Journal: Methods (San Diego, Calif.)

Article Title: In pursuit of sensitivity: Lessons learned from viral nucleic acid detection and quantification on the Raindance ddPCR platform

doi: 10.1016/j.ymeth.2021.04.008

Figure Lengend Snippet: The effect of high occupancy setting on cluster separation. The high occupancy (HO) setting during the “sense” step was used to alleviate the “cluster-squeeze” issue caused by large template DNA input in Raindance ddPCR reactions (A-D, no HO setting; E-H, HO setting). Note that in the 1 million cell to 3 million cell equivalent DNA input range tested, the HO setting did not lead to appreciably improved cluster separation.

Article Snippet: Most of the discussion uses a human HIV infection model and the Raindance ddPCR platform as an example, but the technical considerations presented herein are applicable and can be adapted to a broad range of applications where highly sensitive nucleic acid detection is required.

Techniques: