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Figure 2 in Gastroesophageal tube of the Iguana iguana (Iguanidae): histological description, histochemical and immunohistochemical analysis of 5-HT and SS cells

Figure 2. Histological sections of the (a,b) oesophagus, (c) cranial, (d) middle and (e-f) caudal regions of stomach of I. iguana. (a) After Periodic Acid Schiff (PAS) staining the glycoconjugates are identified in magenta in the goblet cells (arrow) in oesophagus; (b) The ephitelium (EP) of oesophagus has positive histochemical reaction to Alcian Blue (AB, pH 2.5); (c-f) The epithelium lining of stomach is simple columnar mucous with positive histochemical reactions to PAS (c,e) and AB (d,f). (c) Note the mucous cells PAS-positive along the glands (arrowhead) in cranial region of stomach; (e) In caudal region gastric glands (G) are positive only for PAS reaction.

FedscGen: privacy-aware federated batch effect correction of single-cell RNA sequencing data -- Preprocessed datasets

<div> <div> <div> <div> <p>This dataset accompanies the publication "FedscGen: Privacy-Aware Federated Batch Effect Correction of Single-Cell RNA Sequencing Data" and includes eight single-cell RNA sequencing (scRNA-seq) datasets used to benchmark the FedscGen and scGen methods. The datasets are provided in <code>.h5ad</code> format and include comprehensive metadata necessary for replication and further analysis.</p> <h3>Datasets</h3> <p>We analyze various datasets to compare FedscGen against scGen (centralized) in terms of batch correction. For simplicity, we refer to the dataset by abbreviations:</p> <ol> <li> <p><strong>Cell Line (CL)</strong>:</p> <ul> <li>Derived from the 293t_jurkat experiment with three batches: Zheng et al., 2017.</li> </ul> </li> <li> <p><strong>Human Dendritic Cells (HDC)</strong>:</p> <ul> <li>scRNA-seq data of human dendritic cells across two batches: Villani et al., 2017.</li> </ul> </li> <li> <p><strong>Human Pancreas (HP)</strong>:</p> <ul> <li>Consolidated data from five sources with 14,767 cells each: Baron et al., 2016; Muraro et al., 2016; Segerstolpe et al., 2016; Wang et al., 2016; Xin et al., 2016.</li> </ul> </li> <li> <p><strong>Mouse Brain (MB)</strong>:</p> <ul> <li>Merged datasets with 691,600 and 141,606 cells: Saunders et al., 2018; Rosenberg et al., 2018.</li> </ul> </li> <li> <p><strong>Mouse Cell Atlas (MCA)</strong>:</p> <ul> <li>Data focusing on 11 cell types from various organs: Han et al., 2018; The Tabula Muris Consortium, 2018.</li> </ul> </li> <li> <p><strong>Mouse Hematopoietic Stem and Progenitor Cells (MHSPC)</strong>:</p> <ul> <li>Data from SMART-seq2 and MARS-seq protocols: Nestorowa et al., 2016; Paul et al., 2015.</li> </ul> </li> <li> <p><strong>Mouse Retina (MR)</strong>:</p> <ul> <li>Data from two unassociated laboratories with 26,830 and 44,808 cells: Macosko et al., 2015; Shekhar et al., 2016.</li> </ul> </li> <li> <p><strong>PBMC (human Peripheral Blood Mononuclear Cell)</strong>:</p> <ul> <li>scRNA-seq data with two batches: Zheng et al., 2017.</li> </ul> </li> </ol> <p><strong>Usage Notes</strong>: Each dataset is provided in <code>.h5ad</code> format, compatible with common single-cell analysis tools such as Scanpy. Detailed metadata is included within each file.</p> <p><strong>Keywords</strong>: Single-cell RNA sequencing, scRNA-seq, Batch effect correction, Privacy-aware, Federated learning, scGen, FedscGen, Clinical multi-center studies, Genomics, Bioinformatics</p> <p><strong>Contact</strong>: For questions or further information, please contact Mohammad Bakhtiari at <a href="mailto:mohammad.bakhtiari@uni-hamburg.de.">mohammad.bakhtiari@uni-hamburg.de.</a></p> <p><strong>License</strong>: Creative Commons Attribution 4.0 International (CC BY 4.0)</p> </div> </div> </div> </div> <div> <div> <div> </div> </div> </div>

Real-world comprehensive genomic and immune profiling reveals distinct age- and sex-based genomic and immune landscapes in tumors of patients with non-small cell lung cancer

<p>Wallen ZD, Ko H, Nesline MK, Hastings SB, Strickland KC, Previs RA, Zhang S, Pabla S, Conroy J, Jackson JB, Saini KS, Jensen TJ, Eisenberg M, Caveney B, Sathyan P, Severson EA, Ramkissoon SH. <strong>Real-world comprehensive genomic and immune profiling reveals distinct age- and sex-based genomic and immune landscapes in tumors of patients with non-small cell lung cancer.</strong> <em>Front Immunol.</em> 2024 Jun 21;15:1413956. doi: <a href="https://doi.org/10.3389/fimmu.2024.1413956">10.3389/fimmu.2024.1413956</a>. PMID: <a href="https://pubmed.ncbi.nlm.nih.gov/38975340/">38975340</a>; PMCID: <a href="https://pmc.ncbi.nlm.nih.gov/articles/PMC11224431/">PMC11224431</a>.</p> <p><strong>ABSTRACT</strong></p> <p>Younger patients with non-small cell lung cancer (NSCLC) (<50 years) represent a significant patient population with distinct clinicopathological features and enriched targetable genomic alterations compared to older patients. However, previous studies of younger NSCLC suffer from inconsistent findings, few studies have incorporated sex into their analyses, and studies targeting age-related differences in the tumor immune microenvironment are lacking. We performed a retrospective analysis of 8,230 patients with NSCLC, comparing genomic alterations and immunogenic markers of younger and older patients while also considering differences between male and female patients. We defined older patients as those ≥65 years and used a 5-year sliding threshold from <45 to <65 years to define various groups of younger patients. Additionally, in an independent cohort of patients with NSCLC, we use our observations to inform testing of the combinatorial effect of age and sex on survival of patients given immunotherapy with or without chemotherapy. We observed distinct genomic and immune microenvironment profiles for tumors of younger patients compared to tumors of older patients. Younger patient tumors were enriched in clinically relevant genomic alterations and had gene expression patterns indicative of reduced immune system activation, which was most evident when analyzing male patients. Further, we found younger male patients treated with immunotherapy alone had significantly worse survival compared to male patients ≥65 years, while the addition of chemotherapy reduced this disparity. Contrarily, we found younger female patients had significantly better survival compared to female patients ≥65 years when treated with immunotherapy plus chemotherapy, while treatment with immunotherapy alone resulted in similar outcomes. These results show the value of comprehensive genomic and immune profiling (CGIP) for informing clinical treatment of younger patients with NSCLC and provides support for broader coverage of CGIP for younger patients with advanced NSCLC.</p> <p><strong>DATA AVAILABILITY: </strong></p> <p>De-identified, individual-level patient data, genomic variants, and individual immune gene expression data used in the manuscript can be found in this repository (https://zenodo.org/record/11396552). An R markdown file with R code used to perform the analyses and generate figures is also provided in the repository along with the data. All versions of software used are provided in the Methods section of the manuscript. Raw sequencing data were derived from routine clinical testing of real-world patients and cannot be shared publicly. Data for immune gene expression signatures are not publicly available due to a non‑provisional patent filing covering the methods used to generate and analyze these data but are available from the corresponding author on reasonable request.</p>

Figure 4 in Investigation the effects of vitreous humor on proliferation and dedifferentiation of differentiated NTERA2 cells

Figure 4. Western blot analysis show that the NT2 cells are known as perfectly positive cells for OCT4 protein expression.

Figure 7. T in Bioinformatics and expression analysis of the Xeroderma Pigmentosum complementation group C (XPC) of Trypanosoma evansi in Trypanosoma cruzi cells

Figure 7. T. cruzi growth assessment after cisplatin treatment (300 ΜM). (a) Wild type (WT). (b) TcXPC superexpressor (Tc-TcXPC). (c) TevXPC expressor (Tc-TevXPC). The solid lines represent the untreated cells, while the dotted lines represent the cells treated with cisplatin. Statistical student's t test: (*) On that point, cells treated with cisplatin presented a statistically significant lower growth in relation to untreated cells (p <0.05). Representative results of three independent experiments.

Figure 6 in Bioinformatics and expression analysis of the Xeroderma Pigmentosum complementation group C (XPC) of Trypanosoma evansi in Trypanosoma cruzi cells

Figure 6. Growth assessment of T. cruzi: wild type (WT), TcXPC superexpressor (Tc-TcXPC) and TevXPC expressor (Tc-TevXPC). Statistical student's t test: (*) On that point, only Tc-TevXPC presented a statistically significant lower growth in relation to WT (p <0.05); (**) On that point, both Tc-TcXPC and Tc-TevXPC presented a significant lower growth in relation to WT (p <0.05). All parasites were at same initial concentration, grown on LIT medium and were counted daily. Representative results of three independent experiments.

Figure 5 in Bioinformatics and expression analysis of the Xeroderma Pigmentosum complementation group C (XPC) of Trypanosoma evansi in Trypanosoma cruzi cells

Figure 5. TevXPC amplification by RT-PCR with the cDNA from cell cultures. Lanes: (1) 1Kb DNA Ladder; (2) WT; (3) Tc-TcXPC; (4 and 5) Tc-TevXPC; (6) positive control (DNA from T. evansi); (7) negative control.

Figure 4 in Bioinformatics and expression analysis of the Xeroderma Pigmentosum complementation group C (XPC) of Trypanosoma evansi in Trypanosoma cruzi cells

Figure 4. (a) TcXPB-R protein model. (b) TevXPB-R protein model. (c) TcXPB-R (blue) and TevXPB-R (orange) models overlay.

Figure 2 in Bioinformatics and expression analysis of the Xeroderma Pigmentosum complementation group C (XPC) of Trypanosoma evansi in Trypanosoma cruzi cells

Figure 2. (a) Alignment between TcXPC and TevXPC proteins (mismatches highlighted) and its domains. Green: RAD4/PNGase transglutaminase-like fold. Blue: RAD4 beta-hairpin domain 1. Red: RAD4 beta-hairpin domain 2. Yellow: RAD4 beta-hairpin domain 3. (b) Candidate sequence motif involved in p62 interaction (highlighted by brown rectangle) found in TcXPC and TevXPC. This sequence is suggested based on the sequence motif described for Human XPC and yeast RAD4: D/E-F/W-E-D/E-V.

Figure 1 in Bioinformatics and expression analysis of the Xeroderma Pigmentosum complementation group C (XPC) of Trypanosoma evansi in Trypanosoma cruzi cells

Figure 1. (a) TcXPC protein model. (b) TevXPC protein model. (c) TbXPC protein model (d) Model of TevXPC protein bound to a mismatch DNA. (e) TcXPC (red), TevXPC (blue) and TbXPC (green) models overlay. (f) Crystal structure of Rad4-Rad23 bound to a mismatched DNA performed by Min and Pavletich (2007).

Figure 2 in Investigation the effects of vitreous humor on proliferation and dedifferentiation of differentiated NTERA2 cells

Figure 2. Cell cycle analysis of NT2-RA cells after treatment with different amounts of VH at (A) 3 days and (B) 6 days post-treatment. After treatment with RA the number of cells at S phase decreased. These numbers were recovered after three and six days treatment with different amounts of VH.

Figure 3 in Bioinformatics and expression analysis of the Xeroderma Pigmentosum complementation group C (XPC) of Trypanosoma evansi in Trypanosoma cruzi cells

Figure 3. (a) TcXPB protein model. (b) TevXPB protein model. (c) TcXPB (green) and TevXPB (red) models overlay.

opencc-by-4.0Sep 2017View details →

Fig. 2 in Trypanosoma brucei: trypanocidal and cell swelling activities of lasalocid acid

Fig. 2 Effect of lasalocid acid and salinomycin on the growth of bloodstream forms of T. brucei and human myeloid leukaemia HL-60 cell. Trypanosomes (circles) and HL-60 cells (squares) were incubated with varying concentration of lasalocid acid (closed symbols) or salinomycin (open symbols). After 72 h of culture, cell viability and proliferation were determined with the colorimetric dye resazurin. The experiment was repeated three times and mean values ± SD of three experiments are shown

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Fig. 3 in Trypanosoma brucei: trypanocidal and cell swelling activities of lasalocid acid

Fig. 3 Effect of polyether ionophore antibiotics on the cell volume of bloodstream forms of T. brucei. a Trypanosomes (5 × 107 cell/ml) were incubated with 100 μM lasalocid acid (triangles) or salinomycin (squares) in Baltz medium in the presence of 1% DMSO. Controls (circles) were incubated with 1% DMSO. Every 10 min, the absorbance at 490 nm was measured. Mean values ± SD of three experiments are shown. Except for the time point 0 min at all other time points, the absorbance values were statistically significantly different from each other (One-way ANOVA test, p <0.01). b Trypanosomes (5 × 107 cell/ml) were incubated with 100 μM lasalocid acid in the absence (closed circles, solid line) or presence of 6 mM EDTA (open squares, dashed line) in Baltz medium containing 1% DMSO. Every 10 min, the absorbance at 490 nm was measured. Mean values of three experiments are shown. For clarity, the standard deviations were omitted. The standard deviations ranged between 17.5–25.1% of the mean values. At each time point, the data points of the two curves were statistically not significantly different (p = 0.465–0.977, Student's t test)

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Fig. 1 in Trypanosoma brucei: trypanocidal and cell swelling activities of lasalocid acid

Fig. 1 Structure of lasalocid acid. The PubChem compound identifier (CID) for the compound is shown in parentheses

Fig. 3 in SjTat-TPI facilitates adaptive T-cell responses and reduces hepatic pathology during Schistosoma japonicum infection in BALB/c mice

Fig. 3 Th1 immune response acter CD8+T cells blockage in sitro. a. CD3+CD8+T cells were successcullv blocked. The blocking ecciciencv was more than 99.6 %. b, c. Percentages oc CD4+IFN-γ+ (Th1) in Tat-TPI (T-TPI), TPI stimulated splenocvtes with or without CD8+T-cell blockage. Data are presented as the means ± SEM crom cour independent experiments. (*P <0.05; **P <0.01)

Fig. 2 in SjTat-TPI facilitates adaptive T-cell responses and reduces hepatic pathology during Schistosoma japonicum infection in BALB/c mice

Fig. 2 Immune responses in the draining popliteal lvmph nodes oc mice induced bv Tat-TPI (T-TPI) and TPI proteins. a and c. Percentages oc CD4+IFN-γ+ cells (Th1), CD8+IFN-γ+ cells (Tc1) analvsed bv FACS. b. The ratio oc CD4+ T cells to CD8+ T cells (CD4/CD8) in the draining popliteal lvmph nodes. Data are presented as the means ± SEM crom six mice in each group. (*P <0.05; **P <0.01)

Fig. 1 in SjTat-TPI facilitates adaptive T-cell responses and reduces hepatic pathology during Schistosoma japonicum infection in BALB/c mice

Fig. 1 Expression, puricication and identicication oc the cusion proteins Tat-TPI and TPI. a. Puricication oc two cusion proteins detected bv Protein Gel Electrophoresis. M: molecular weight marker, Lane 1: recombinant SjTat-TPI, Lane 2: recombinant SjTPI, Lane 3: the recombinant plasmid without puricication. b. Fusion proteins recognised bv His-Ab with Western blotting. Lane 1: recombinant SjTat-TPI, Lane 2: recombinant SjTPI. c. Fusion proteins recognised bv S. japonicum incected-mice serum with Western blotting. Lane 1: recombinant SjTat-TPI, Lane 2: recombinant SjTPI

Fig. 5 in SjTat-TPI facilitates adaptive T-cell responses and reduces hepatic pathology during Schistosoma japonicum infection in BALB/c mice

Fig. 5 Parasite burden and immune response were obsersed at 6 weeks acter S. japonicum incection in mice saccinated with T-TPI + IFA, TPI + IFA, IFA and PBS. a. Aserage number oc worms recosered. b. Aserage number oc eggs per gram (EPG) in the liser. c. Representatise granulomas with a single egg crom each group (100×). d. Aserage area oc single egg granulomas crom each group. e, f. Percentages oc CD3+CD4+IFN-γ+(Th1) and CD3+CD8+IFN-γ+(Tc1) gated crom CD3+ T cells analvsed bv FACS. Each bar represents the means ± SEM crom twelse mice per group. (*P <0.05; **P <0.01)

Fig. 4 T cell and antibodies responses acter three immunisations with T in SjTat-TPI facilitates adaptive T-cell responses and reduces hepatic pathology during Schistosoma japonicum infection in BALB/c mice

Fig. 4 T cell and antibodies responses acter three immunisations with T-TPI + IFA, TPI + IFA, IFA and PBS. a and b: Percentages oc CD3+CD4+IFN-γ+ (Th1) and CD3+CD8+IFN-γ+ (Tc1) gated crom CD3+ cells analvsed bv FACS. c. IgG, IgG1 and IgG2a lesels in mice sera were detected. Data are presented as the means ± SEM crom eight mice in each group. (*P <0.05; **P <0.01)