EMBO/soda-nel huggingface dataset:
Comparative proteomics reveals a diagnostic signature for pulmonary head-and-neck cancer metastasis (2018)
Figure 4

Figure 4. Diagnostic proteomic signature for HNSCC metastasis in the lung.

A Schematic computational workflow: The SVM predictor was initially developed using a bootstrapping procedure on n=44 primary SQCLC and n=30 HNSCC cases. An independent set of n=38 tumours was used for validation, before we applied the classifier to n=51 lung tumours of unknown origin. Survival analysis was used to assess classification performance on this final data set.

B Classification accuracy of five different machine-learning methods used for classification of HNSCC vs. SQCLC. SVM, Support Vector Machine with a linear kernel; RPART, Classification and Regression Tree (CART); NB, naïve Bayes classifier; PAM, Partitioning Around Medoids / Nearest Shrunken Centroids; PLR, L1-Penalised Logistic Regression. All models were fitted by using the R/Bioconductor package 'caret'. Model hyperparameters were optimised by using caret's tuning option; accuracies were computed by bootstrapping with 25 repetitions, shown are mean accuracy ± standard deviation.

C Classification accuracy using a linear support vector machine. The figure shows the bootstrapped accuracy achieved over the number of proteins included in the computation. Feature selection was performed using recursive feature elimination.

D Boxplot showing the number of quantified proteins derived from 19 SQCLC, 19 HNSCC and 51 squamous-cell lung tumours of unknown origin derived from HNSCC patients. The central line in the boxes represents the median number of proteins over all samples, upper and lower borders of boxes correspond to 25% and 75% quantiles. Whiskers indicate minimum and maximum.

E Classification accuracy of the SVM-prediction model described, in an independent validation cohort of 19 SQCLC and 19 HNSCC cases.

F Representative H&E and immunohistochemical stainings of CK5/6 and p63 in squamous-cell lung tumours of unknown origin derived from HNSCC patients. Scale bar: 500 µm.

G Kaplan-Meier analysis of overall survival (OS) in which all patients with lung tumours were grouped according to the clinical classification (left, median survival SQCLC: 55 months; metHNSCC: 31 months) or proteomic classification (right, median survival SQCLC: 55 months; metHNSCC: 8 months) of the tumour as metHNSCC or SQCLC. The p value is from a log-rank test.

H Kaplan-Meier analysis of overall survival (OS) in which only the patients that were independent from the training cohort were grouped according to the clinical classification (left, median survival SQCLC: 84 months; metHNSCC: 35 months) or proteomic classification (right, median survival SQCLC: 84 months; metHNSCC: 5 months) of the tumour as metHNSCC or SQCLC. The p value is from a log-rank test.

Time HNSCC until lung tumour:

median (range) [months]

Squamous-cell lung carcinoma

(n = 19)

Time HNSCC until lung tumour:

median (range) [months]
A gene subset requires CTCF bookmarking during the fast post-mitotic reactivation of mouse ES cells (2022)
Figure 2

Figure 2. Examples of post-mitotic gene reactivation.

Y-axis, z-score; X-axis, timepoints. A indicates asynchronous cells, M mitotic cells and the numbers represent the minutes after release from the mitotic block). Dots show individual replicates and lines averages (n=3 for A and M; n=2 for each post-mitotic sample). Pre-mRNA levels are shown for pluripotency genes (Oct4, Klf4, Esrrb) and cell cycle regulators (E2f1, Cdk2, Rb); mRNA levels for individual histone genes (only averages are shown).
A gene subset requires CTCF bookmarking during the fast post-mitotic reactivation of mouse ES cells (2022)
Figure 5

Figure 5. CTCF does not influence global post-mitotic gene reactivation.

(A) Schematic describing the experimental layout for IAA-induced depletion of CTCF at the M/G1 transition.

(B) Heatmaps presented like in Figure 3A for untreated (-IAA; left) or CTCF-depleted (+IAA; right) CTCF-AID cells.

(C) PCA of post-mitotic gene reactivation in the presence (-IAA; blue) or absence of CTCF (+IAA; red).

(D) Smoothed (loess) median reactivation kinetics in the presence (-IAA; blue) or absence of CTCF (+IAA; red). The shadow areas represent 95% confidence intervals of the regression.
A gene subset requires CTCF bookmarking during the fast post-mitotic reactivation of mouse ES cells (2022)
Figure 6

Figure 6. Mitotic bookmarking effects mediated by CTCF.

(A) Gene expression changes (z-score) in asynchronous cells and during post-mitotic release of CTCF-AID cells treated or not with IAA to deplete CTCF (blue, presence of CTCF; red, absence). Samples are indicated on the X-axis (A: asynchronous cells; M: mitotic cells; numbers: minutes since release from mitotic block). Six gene groups are shown, based on the time of their response to CTCF depletion (asy, late, early) and the direction of the transcriptional change (up, down). The number of genes of each group is indicated. The yellow shadow areas indicate times showing expression changes. The boxplots show the median (bar), 25-75% percentiles (box) and 1.5-fold inter-quartile range (whiskers).

(B) Statistical enrichment (Y-axis, -log10(Fisher p-value)) of CTCF binding sites at increasing distances (log10(kb)) of the TSS of genes responding to CTCF depletion exclusively in asynchronous cells (asy; left) or either late (middle) or early (right) after mitotic release. Two categories of CTCF sites are separately analysed: those that are present in interphase and mitosis (Book, in red) and those that are exclusive of interphase (Lost, in black). The direction of gene responses is also considered (down and up, see (A), as solid and dashed lines respectively).

(C) Average binding profile (X-axis, reads per million) of CTCF (top) and the Cohesin subunit SMC1 (bottom), across 8kb centred on the TSS of genes responding to CTCF depletion exclusively in asynchronous cells (left) or either late or early upon mitotic release (middle and right, respectively). Interphase is shown in blue and mitosis in red.
Low-dose TNF augments fracture healing in normal and osteoporotic bone by up-regulating the innate immune response. (2015)
Figure 1

Role of TNF in fracture healing in vivo

Addition of rhTNF at the fracture site on days 0 and 1 led to augmented healing, indicated by increased % callus mineralization, at day 28 after operation in a dose-dependent manner. Data are presented as mean ± SEM. Treatment with 1 ng TNF versus PBS control, ****P < 0.0001 by one-way ANOVA with Dunnett's multiple comparisons test.

Addition of rhTNF at the fracture site must be given within the first 24 h to augment healing, indicated by % callus mineralization. Data are presented as mean ± SEM. 1 ng TNF versus PBS control treatment on days 0 and 1, ***P = 0.0009 by one-way ANOVA with Dunnett's multiple comparisons test.

Treatment with systemic anti-TNF or local rmIL-10 led to impaired fracture repair at day 28, indicated by % callus mineralization. Data are presented as mean ± SEM. Treatment with PBS control versus anti-TNF, *P = 0.037, PBS control versus rmIL-10, *P = 0.037, by unpaired two-sided t-tests.

Representative micro-CT images at the fracture site showing (from left to right): lateral view of tibia, cross-section, and cross and longitudinal sections with color overlay and 3D reconstruction. In the color overlays, the shade of blue corresponds to percentage mineralization: light blue denotes soft immature callus, whereas dark blue denotes hard mineralized callus. Scale bar, 2 mm.

Representative ISH image (light field) showing TNF expression at the murine fracture site at 24 h after fracture. Scale bar, 250 μm. Red box indicates region of interest.

High-power micrographs of region of interest from (E): at 24 h after fracture, mTNF expression (white signal on dark field, above) co-localized with polymorphonuclear cells found on the adjacent H&E section (below). Scale bar, 25 μm. Neutrophils were identified by their polymorphonuclear morphology as well as positive dark brown staining with anti-neutrophil elastase.

High-power micrographs: at 7 days, TNF expression (white signal on dark field, above) co-localized with F4/80-positive cells (stained dark brown) extravasating from a blood vessel on the adjacent H&E section (below). Scale bar, 25 μm.
Low-dose TNF augments fracture healing in normal and osteoporotic bone by up-regulating the innate immune response. (2015)
Figure 2

Role of neutrophils in fracture healing

Neutrophils were mobilized into the murine systemic circulation within 30 min of injury in our murine fracture model. Compared to control and number of blood neutrophils at 3 h ***P = 0.0006 and at 6 h *P = 0.042, by one-way ANOVA with Dunnett correction.

Depletion of neutrophils using anti-Ly6G. Intravenous anti-Ly6G treatment led to depletion of neutrophils in the systemic circulation (left) as well the local peri-fracture soft tissues (right). Left: counts of neutrophils in the blood harvested by cardiac puncture at 3 h post-injury. Data are presented as mean ± SEM (**P = 0.0074 using unpaired one-tailed t-test). Right: counts of positively stained infiltrative neutrophils in the adjacent muscle to the fracture site comparing neutrophil depletion with anti-Ly6G antibody versus IgG control at day 1 and day 7 post-fracture. At day 1, number of neutrophils in control group as detected by Ly6G and NE in control versus treatment: ****P = 0.0001 for both Ly6G and NE, by unpaired two-tailed t-test. At day 7, number of neutrophils in control group as detected by Ly6G and NE in control versus treatment groups: ****P = 0.0001 for Ly6G and *P = 0.020 for NE, by unpaired two-tailed t-test. Number of neutrophils at day 1 versus day 7 in control groups, *P = 0.037 for Ly6G and ***P = 0.0006 for NE, by unpaired two-tailed t-test.

Representative sections showing local infiltration of neutrophils in the adjacent muscle stained using anti-Ly6G and anti-neutrophil elastase primary antibodies at day 1 post-fracture following treatment with anti-Ly6G antibody or IgG control. Scale bar, 100 μm.

Depletion of neutrophils using anti-Ly6G led to impaired fracture healing. Representative section stained with Masson's trichrome at day 14 comparing fracture healing in mouse treated with isotype control (top) versus anti-Ly6G (bottom). Black and white images in the right column are identical to the color images in the left column; they have been labeled to clearly demonstrate the anatomical structures. Control section shows advanced mineralized callus, while treatment section shows a large immature unmineralized callus. Muscle fibers: red; collagen, bone, and mineralized callus: green. Scale bar, 1 mm.

Anti-Ly6G treatment led to impaired fracture healing as shown by the reduced % callus mineralization at day 28 after surgery and representative micro-CT images. Anti-Ly6G treatment led to delayed mineralization and remodeling of the fracture callus compared to control. Data are presented as mean ± SEM. ***P = 0.0006 by unpaired two-sided t-test. Scale Bar, 2 mm.
Low-dose TNF augments fracture healing in normal and osteoporotic bone by up-regulating the innate immune response. (2015)
Figure 3

TNF promotes recruitment of innate immune cells and CCL2 expression

Anti-Ly6G treatment depletes local monocytes/macrophages at the fracture site. Counts of positively stained infiltrative F4/80+ cells in the adjacent muscle to the fracture site following treatment with control or anti-Ly6G at day 1 and day 7. Data are presented as mean ± SEM. **P = 0.005 at day 1 and **P = 0.002 at day 7, and *P = 0.013 for control at day 1 versus control at day 7, by unpaired two-sided t-test.

Addition of 1 ng rhTNF to fracture supernatant in the air pouch model led to increased numbers of neutrophils (Ly6G+, CD11b+ cells) and monocytes/macrophages (Ly6G−, CD11b+, CD115+ cells) in the cellular infiltrate. These effects were abrogated by the addition of anti-CCL2. Neutrophils: FS versus FS + TNF *P = 0.015, FS + TNF versus FS + TNF + anti-CCL2 *P = 0.028, and FS + TNF + anti-CCL2 versus FS + TNF + IgG *P = 0.042 by one-way ANOVA followed by Bonferroni's multiple comparison test. Monocytes/macrophages: FS versus FS + TNF **P = 0.0063, FS + TNF versus FS + TNF + anti-CCL2 ****P < 0.0001, and FS + TNF + anti-CCL2 v FS + TNF + IgG *P = 0.015 by one-way ANOVA followed by Bonferroni's multiple comparisons test.

Addition of 1 ng rhTNF to fracture supernatant increased CCL2 protein levels in the air pouch. “Neat” indicates level of CCL2 in fracture supernatant before injection into air pouch. Data are presented as mean ± SEM. FS versus FS + TNF **P = 0.0020 by one-way ANOVA with Bonferroni's multiple comparisons test.

Addition of rhTNF to enriched bone marrow-derived murine neutrophils pre-exposed to fracture supernatant in vitro led to up-regulation of CCL2 production at 1 h. Data are presented as mean ± SEM. No TNF versus TNF 0.01 ng/ml *P = 0.012, TNF 0.1 ng/ml ***P < 0.0001, TNF 1.0 ng ***P = 0.0001, TNF 10 ng/ml ***P < 0.0001, and TNF 100 ng/ml *P = 0.023 by one-way ANOVA with Dunnett's multiple comparisons test.
Low-dose TNF augments fracture healing in normal and osteoporotic bone by up-regulating the innate immune response. (2015)
Figure 4

Effects of inhibiting inflammatory cell recruitment on fracture healing

Treatment with CCR2 antagonist, INCB3344, led to impaired fracture healing compared to vehicle control as shown by the reduced % callus mineralization at day 28 after operation. Data are presented as mean ± SEM. *P = 0.011 unpaired two-sided t-test. Representative micro-CT images are shown. Scale bar, 2 mm.
Low-dose TNF augments fracture healing in normal and osteoporotic bone by up-regulating the innate immune response. (2015)
Figure 5

TNF promotes fracture healing in osteoporotic bone

rhTNF treatment augmented early phase fracture healing in osteoporotic mice. Treatment with 1 ng rhTNF at the fracture site on days 0 and 1 led to increased % callus mineralization at day 14 but no difference at day 28 indicating accelerated early healing but the same final result at day 28. Data are presented as mean ± SEM. At day 14, PBS control versus TNF, **P = 0.0099; at day 28, PBS control versus TNF, nsP = 0.37, by unpaired two-sided t-test. Representative micro-CT images at day 14 are shown. rhTNF treatment led to mature callus bridging across the fracture which was absent in the PBS-treated control group. Scale bar, 2 mm.
miR-AB, a miRNA-based shRNA viral toolkit for multicolor-barcoded multiplex RNAi at a single-cell level (2022)
Figure 2

Figure 2. Comparison of RNAi efficiency mediated by miR-E vs. miR-AB in vitro and in vivo.

Two top-ranked SplashRNA-designed shRNAmirs targeting human Nurd complex components and a control shRNAmir targeting human CD4 were cloned into both miR-AB and miR-E lentiviral vectors with Venus as reporter. The lentiviruses packaged by these constructs were used for transduction of multiple human cell lines. RNAi efficiency was determined by western blot (WB) analysis of target protein levels in the lysates of the transduced cells. -actin served as loading control.

A shERWOOD-designed shRNAmir targeting mouse transcriptional factor Tbx21 and a control shRNAmir targeting mouse CD4 were cloned into both miR-AB and miR-E retroviral vectors with Venus or Ametrine as reporter. The packaged viruses were used for transduction of primary mouse P14 TCR transgenic CD8+ T cells, which were used for evaluation of CD8+ T cells differentiation in vivo as described previously(Wang et al., 2018) (see details in the Materials and Methods section).

Representative FACS plots of differentiation marker CD127/KLRG1 staining of the gated P14 CD8+ T cells and the statistical summary of SLEC subsets were shown to indicate CD8+ T cell differentiation. Data are shown as mean ± s.d. and n=5. * indicates significant difference (P<0.01, two-tailed unpaired Student's t-test). Data are from one representative experiment of two biological replicates.

The Tbx21 RNAi efficiency mediated by miR-AB vs. miR-E in the transduced in vitro-expanded P14 CD8+ T cells was determined by western blot analysis of T-bet protein level. β-actin served as loading control.

The RNAi efficiency of Pten.1524 and Pten.932 shRNAmir mediated by miR-AB vs. miR-E was tested in NIH-3T3 cells in the context of <30% transduction efficiency (GFP as reporter). Representative western blots of Pten protein expression of the FACS-sorted GFP+ cells from two biological replicates were shown. β-actin served as loading control.

Three shRNAmirs targeting the GFP reporter of a lentiviral vector in miR-AB or miR-E backbone were transduced into MC38 or 293T cells. The RNAi efficiency was determined by FACS analysis of GFP in the context of <30% transduction efficiency. Data are shown as mean ± s.d. and n=3. * indicates significant difference (P<0.05). NS indicates no significant difference (P>0.05, two-tailed unpaired Student's t-test).
miR-AB, a miRNA-based shRNA viral toolkit for multicolor-barcoded multiplex RNAi at a single-cell level (2022)
Figure 3

Figure 3. RNAi via miR-AB driven by multiple eukaryotic promoters in different cell types. Two top-ranked SplashRNA-designed shRNAmirs targeting human or mouse surface protein FAS were cloned into Venus-expressing miR-AB lentiviral vectors which harbor different promoters to drive the shRNAmir expression. The packaged lentiviruses were used to infect the indicated human or mouse cell lines. A shRNAmir targeting human or mouse CD4 driven under hCMV promoter was used as control. After >96h of infection, FAS protein levels in the transduced Venus-positive cells were determined by surface staining and shown in histograms (top panels) and quantified by MFI of APC (bottom panels).
miR-AB, a miRNA-based shRNA viral toolkit for multicolor-barcoded multiplex RNAi at a single-cell level (2022)
Figure 4

Figure 4. miR-AB-based multi-promoter and multicolor viral toolkit.

Schematic diagram of miR-AB-based lentiviral (LV) and retroviral (RV) vectors. miR-AB shRNAmir expression is driven by a composite promoter composed of the endogenous 5' LTR of HIV and a eukaryotic promoter in lentiviral vectors, or by the endogenous 5' LTR of MSCV in retroviral vectors. Eight fluorescent proteins with emission peaks across whole visible spectrum are controlled by mouse PGK promoter. A woodchuck hepatitis post-transcriptional regulatory element (WPRE) is used to enhance transgene expression.

The excitation and emission spectra of these fluorescent proteins are shown in FPbase Spectra Viewer (https://www.fpbase.org/spectra/). The five commonly-used lasers are indicated in the spectrum. The excitation spectrum of Azurite is shown as that of its parental protein EBFP due to lack of information in the database.

Nomenclature of fifty-six miR-AB-based lentiviral and retroviral vectors with different promoters and different fluorescent protein reporters. AH promoter (human beta actin promoter(Ng et al, 1989)/human leukaemia viruses RU5 region)-based miR-AB lentiviral vectors, the most recently developed one, also exhibited strong RNAi efficiency. Puromycin was also engineered into this toolkit for antibiotic-based screening of transformants.

Lentiviral vectors with GFP reporter that are controlled by the promoters used in miR-AB lentiviral vectors were constructed for easy assessment of the promoters activity on microscope or flow cytometer.

CD8+ T cells were activated and then co-transduced with miR-AB retroviruses targeting CD4 with Azurite, GFP, Ametrine, mOrange, mCherry2 or E2-Crimson as fluorescent reporters. The fluorescences of all fluorescent proteins were plotted on contour plots showing the fluorescent separation of each pair of the fluorescent proteins. The data was a representative of at least three biologically independent experiments.

293T cells were co-transduced with four miR-AB lentiviruses at 1:1 ratio, which carries a neutral shRNAmir targeting CD4 or CD19, with Azurite, GFP, Ametrine or mOrange as reporter respectively. Cells were cultured for 22 days and fluorescence positive cells were quantified at the time points as indicated. Representative contour FACS plots cells on day 4 and day 22 shown (top panels). Cell numbers of untransduced, single fluorescence positive cells and quadruple positive cells were quantified and normalized to untransduced cells on day 4, and plotted over time (bottom panel). Data are shown as mean ± s.d. and n=4. NS indicates no significant difference (P>0.05, two-tailed unpaired Student's t-test).
miR-AB, a miRNA-based shRNA viral toolkit for multicolor-barcoded multiplex RNAi at a single-cell level (2022)
Figure 5

Figure 5. miR-AB-based multicolor-barcoded multiplex RNAi.

CD8+ T cells were activated for 16h and then co-transduced with miR-AB retroviruses at 1:1 ratio, which carries a SplashRNA-designed shRNAmir, targeting surface protein CD127, CD90, CD44 or CD8, with Azurite, GFP, Ametrine or mCherry2 as fluorescent reporters respectively for 4h. miR-AB retroviruses expressing CD19-specific shRNAmirs with same fluorescent reporters were used as controls. Surface staining was performed 72h after transduction. FACS data were shown as overlaid histograms of control shRNAmirs (shCD19s) and target shRNAmirs (shCD127, shCD90, shCD44 or shCD8). Cells were categorized as sixteen populations expressing single, double, triple or quadruple fluorescent proteins or not (none) and fluorescent reporter-positive plots were highlighted with thick frames and white background. Each population's surface staining profile was shown on the right. The data was representative of two biologically independent experiments.
Pten controls B cell responsiveness and germinal center reaction by regulating expression of IgD BCR (2019)
Figure 1

Figure 1 | Pten is required for receptor editing

A | Representative analysis of B220 and IgM surface expression in bone marrow (left) and spleen cells (right) of mice from the indicated genotypes.

B | Representative flow cytometric analysis of splenocytes from mice of the indicated genotypes (pre-gated on B cells: B220+/CD19+) for surface expression of IgM and the 3-83 idiotype (54.1). Shown data are representative 11 - 35 individual mice per genotype.

C | PCR fragments amplified with specific primers for Vκ and Jκ5 from genomic DNA of purified splenic B cells from Ptenf/f x 3-83ki and Ptenf/f x mb1-cre x 3-83ki mice on the respective backgrounds. Genomic tail DNA from a 3-83ki mouse and DNA from purified splenic B cells of a control (ctrl) mouse were used as controls. PCR for the splicing factor Srp20 served as a loading control. Kb and Kd indicate the respective background of the mice, (H2-Kb: +Ag).
Pten controls B cell responsiveness and germinal center reaction by regulating expression of IgD BCR (2019)
Figure 2

Figure 2 | Pten-deficient B cells are capable of acquiring an anergic phenotype

A | Intracellular expression of IgM (Ig-μHC ic) in bone marrow (left) and spleen cells (right) was determined by flow cytometry and compared between the populations of B cells (green, identified by B220 and CD19 expression) and non-B cells (gray). Numbers in the histograms indicate the percentages of the positive populations. Figures are representative of 11 - 35 individual mice per genotype.

B | Intracellular Ca2+ influx was measured in CD90.2/Thy1.2- splenocytes derived from mice of the indicated genotypes following stimulation with 10 μg/ml α-κLC antibody. Figures are representative of at least 3 individual mice per genotype.

C | Serum IgM concentrations measured in mice of the indicated genotypes. Mean ±SD, symbols represent IgM concentrations from individual mice (n). Statistical significance was calculated by using the Kruskal-Wallis test (see also Table S1), n. s. = not significant; **** p ≤ 0.0001.

D, E | Absolute numbers of B cells in bone marrow (D) and spleens (E) from mice of the respective genotypes, determined by B220/CD19 surface expression. Mean ±SD, symbols indicate the numbers of B cells in individual mice (n). Statistical significance was calculated by using the Kruskal-Wallis test (see also Tables S2-3), n. s. = not significant; * p ≤ 0.05; *** p ≤ 0.001; **** p ≤ 0.0001.