| 1. |
- Beal, Jacob, et al.
(författare)
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Robust estimation of bacterial cell count from optical density
- 2020
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Ingår i: Communications Biology. - : Springer Science and Business Media LLC. - 2399-3642. ; 3:1
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Tidskriftsartikel (refereegranskat)abstract
- Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data.
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| 2. |
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| 3. |
- Campbell, PJ, et al.
(författare)
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Pan-cancer analysis of whole genomes
- 2020
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 578:7793, s. 82-
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Tidskriftsartikel (refereegranskat)abstract
- Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1–3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4–5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10–18.
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| 4. |
- Al-Rabadi, Laith Farah, et al.
(författare)
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Serine Protease HTRA1 as a Novel Target Antigen in Primary Membranous Nephropathy
- 2021
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Ingår i: Journal of the American Society of Nephrology. - : American Society of Nephrology (ASN). - 1046-6673 .- 1533-3450. ; 32:7, s. 1666-1681
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Tidskriftsartikel (refereegranskat)abstract
- Background Identification of target antigens PLA2R, THSD7A, NELL1, or Semaphorin-3B can explain the majority of cases of primary membranous nephropathy (MN). However, target antigens remain unidentified in 15%-20% of patients. Methods A multipronged approach, using traditional and modern technologies, converged on a novel target antigen, and capitalized on the temporal variation in autoantibody titer for biomarker discovery. Immunoblotting of human glomerular proteins followed by differential immunoprecipitation and mass spectrometric analysis was complemented by laser-capture microdissection followed by mass spectrometry, elution of immune complexes from renal biopsy specimen tissue, and autoimmune profiling on a protein fragment microarray. Results These approaches identified serine protease HTRA1 as a novel podocyte antigen in a subset of patients with primary MN. Sera from two patients reacted by immunoblotting with a 51-kD protein within glomerular extract and with recombinant human HTRA1, under reducing and nonreducing conditions. Longitudinal serum samples from these patients seemed to correlate with clinical disease activity. As in PLA2R- and THSD7A- associated MN, anti-HTRA1 antibodies were predominantly IgG4, suggesting a primary etiology. Analysis of sera collected during active disease versus remission on protein fragment microarrays detected significantly higher titers of anti-HTRA1 antibody in active disease. HTRA1 was specifically detected within immune deposits of HTRA1-associated MN in 14 patients identified among three cohorts. Screening of 118 "quadruple-negative" (PLA2R-, THSD7A-, NELL1-, EXT2-negative) patients in a large repository of MN biopsy specimens revealed a prevalence of 4.2%. Conclusions Conventional and more modern techniques converged to identify serine protease HTRA1 as a target antigen in MN.
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| 5. |
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| 6. |
- An, Rong, et al.
(författare)
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Ti–Si–Zr–Zn Nanometallic Glass Substrate with a Tunable Zinc Composition for Surface-Enhanced Raman Scattering of Cytochrome c
- 2023
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Ingår i: ACS Applied Materials and Interfaces. - : American Chemical Society (ACS). - 1944-8244 .- 1944-8252. ; 15:21, s. 25275-25284
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Tidskriftsartikel (refereegranskat)abstract
- As a remarkably powerful analytical technique, surface-enhanced Raman scattering (SERS) continues to find applications from molecular biology and chemistry to environmental and food sciences. In search of reliable and affordable SERS substrates, the development has moved from noble metals to other diverse types of structures, e.g., nano-engineered semiconductor materials, but the cost of the enhancement factors (EF) substantially decreasing. In this work, we employ biocompatible thin films of Ti–Si–Zr–Zn nanometallic glasses as the SERS substrates, while tuning the Zn composition. Aided by quartz crystal microbalance, we find that the composition of 4.3% Zn (Ti–Si–Zr–Zn4.3) gives an ultrasensitive detection of Cytochrome c (Cyt c) with an EF of 1.38 × 104, 10-fold higher than the previously reported EF in the semiconducting metal oxide nanomaterials, such as TiO2, and even comparable to the reported noble-metal-assisted semiconducting tungsten oxide hydrate. Ti–Si–Zr–Zn4.3 exhibits a stronger adhesion force toward Cyt c, which ensures the strong binding of Cyt c to the surface, facilitating the Cyt c adsorption onto the surface and thus enhancing the SERS signal. The high separation efficiency of photoinduced electrons and holes in Ti–Si–Zr–Zn4.3 is also acknowledged for promoting the SERS activity.
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| 7. |
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| 8. |
- Guo, Jinan, et al.
(författare)
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A non-invasive 25-Gene PLNM-Score urine test for detection of prostate cancer pelvic lymph node metastasis
- 2024
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Ingår i: Prostate Cancer and Prostatic Diseases. - : Nature Publishing Group. - 1365-7852 .- 1476-5608.
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Tidskriftsartikel (refereegranskat)abstract
- Background: Prostate cancer patients with pelvic lymph node metastasis (PLNM) have poor prognosis. Based on EAU guidelines, patients with >5% risk of PLNM by nomograms often receive pelvic lymph node dissection (PLND) during prostatectomy. However, nomograms have limited accuracy, so large numbers of false positive patients receive unnecessary surgery with potentially serious side effects. It is important to accurately identify PLNM, yet current tests, including imaging tools are inaccurate. Therefore, we intended to develop a gene expression-based algorithm for detecting PLNM. Methods: An advanced random forest machine learning algorithm screening was conducted to develop a classifier for identifying PLNM using urine samples collected from a multi-center retrospective cohort (n = 413) as training set and validated in an independent multi-center prospective cohort (n = 243). Univariate and multivariate discriminant analyses were performed to measure the ability of the algorithm classifier to detect PLNM and compare it with the Memorial Sloan Kettering Cancer Center (MSKCC) nomogram score. Results: An algorithm named 25 G PLNM-Score was developed and found to accurately distinguish PLNM and non-PLNM with AUC of 0.93 (95% CI: 0.85-1.01) and 0.93 (95% CI: 0.87-0.99) in the retrospective and prospective urine cohorts respectively. Kaplan-Meier plots showed large and significant difference in biochemical recurrence-free survival and distant metastasis-free survival in the patients stratified by the 25 G PLNM-Score (log rank P < 0.001 and P < 0.0001, respectively). It spared 96% and 80% of unnecessary PLND with only 0.51% and 1% of PLNM missing in the retrospective and prospective cohorts respectively. In contrast, the MSKCC score only spared 15% of PLND with 0% of PLNM missing. Conclusions: The novel 25 G PLNM-Score is the first highly accurate and non-invasive machine learning algorithm-based urine test to identify PLNM before PLND, with potential clinical benefits of avoiding unnecessary PLND and improving treatment decision-making.
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| 9. |
- Guo, Jinan, et al.
(författare)
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Establishing a Urine-Based Biomarker Assay for Prostate Cancer Risk Stratification
- 2020
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Ingår i: Frontiers in Cell and Developmental Biology. - Swiss : Frontiers Media S.A.. - 2296-634X. ; 8
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Tidskriftsartikel (refereegranskat)abstract
- One of the major features of prostate cancer (PCa) is its heterogeneity, which often leads to uncertainty in cancer diagnostics and unnecessary biopsies as well as overtreatment of the disease. Novel non-invasive tests using multiple biomarkers that can identify clinically high-risk cancer patients for immediate treatment and monitor patients with low-risk cancer for active surveillance are urgently needed to improve treatment decision and cancer management. In this study, we identified 14 promising biomarkers associated with PCa and tested the performance of these biomarkers on tissue specimens and pre-biopsy urinary sediments. These biomarkers showed differential gene expression in higher- and lower-risk PCa. The 14-Gene Panel urine test (PMP22, GOLM1, LMTK2, EZH2, GSTP1, PCA3, VEGFA, CST3, PTEN, PIP5K1A, CDK1, TMPRSS2, ANXA3, and CCND1) was assessed in two independent prospective and retrospective urine study cohorts and showed high diagnostic accuracy to identify higher-risk PCa patients with the need for treatment and lower-risk patients for surveillance. The AUC was 0.897 (95% CI 0.939–0.855) in the prospective cohort (n = 202), and AUC was 0.899 (95% CI 0.964–0.834) in the retrospective cohort (n = 97). In contrast, serum PSA and Gleason score had much lower accuracy in the same 202 patient cohorts [AUC was 0.821 (95% CI 0.879–0.763) for PSA and 0.860 (95% CI 0.910–0.810) for Gleason score]. In addition, the 14-Gene Panel was more accurate at risk stratification in a subgroup of patients with Gleason scores 6 and 7 in the prospective cohort (n = 132) with AUC of 0.923 (95% CI 0.968–0.878) than PSA [AUC of 0.773 (95% CI 0.852–0.794)] and Gleason score [AUC of 0.776 (95% CI 0.854–0.698)]. Furthermore, the 14-Gene Panel was found to be able to accurately distinguish PCa from benign prostate with AUC of 0.854 (95% CI 0.892–0.816) in a prospective urine study cohort (n = 393), while PSA had lower accuracy with AUC of 0.652 (95% CI 0.706–0.598). Taken together, the 14-Gene Panel urine test represents a promising non-invasive tool for detection of higher-risk PCa to aid treatment decision and lower-risk PCa for active surveillance.
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| 10. |
- Guo, Jinan, et al.
(författare)
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Non-invasive Urine Test for Molecular Classification of Clinical Significance in Newly Diagnosed Prostate Cancer Patients
- 2021
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Ingår i: Frontiers in Medicine. - : Frontiers Media S.A.. - 2296-858X. ; 8
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Tidskriftsartikel (refereegranskat)abstract
- Objective: To avoid over-treatment of low-risk prostate cancer patients, it is important to identify clinically significant and insignificant cancer for treatment decision-making. However, no accurate test is currently available.Methods: To address this unmet medical need, we developed a novel gene classifier to distinguish clinically significant and insignificant cancer, which were classified based on the National Comprehensive Cancer Network risk stratification guidelines. A non-invasive urine test was developed using quantitative mRNA expression data of 24 genes in the classifier with an algorithm to stratify the clinical significance of the cancer. Two independent, multicenter, retrospective and prospective studies were conducted to assess the diagnostic performance of the 24-Gene Classifier and the current clinicopathological measures by univariate and multivariate logistic regression and discriminant analysis. In addition, assessments were performed in various Gleason grades/ISUP Grade Groups.Results: The results showed high diagnostic accuracy of the 24-Gene Classifier with an AUC of 0.917 (95% CI 0.892-0.942) in the retrospective cohort (n = 520), AUC of 0.959 (95% CI 0.935-0.983) in the prospective cohort (n = 207), and AUC of 0.930 (95% 0.912-CI 0.947) in the combination cohort (n = 727). Univariate and multivariate analysis showed that the 24-Gene Classifier was more accurate than cancer stage, Gleason score, and PSA, especially in the low/intermediate-grade/ISUP Grade Group 1-3 cancer subgroups.Conclusions: The 24-Gene Classifier urine test is an accurate and non-invasive liquid biopsy method for identifying clinically significant prostate cancer in newly diagnosed cancer patients. It has the potential to improve prostate cancer treatment decisions and active surveillance.
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