Adenoviral expression of vascular endothelial growth factor splice variants differentially regulate bone marrow-derived mesenchymal stem cells

Bone marrow-derived mesenchymal stem cells (MSCs) are being explored for clinical applications, and genetic engineering represents a useful strategy for boosting the therapeutic potency of MSCs. Vascular endothelial growth factor (VEGF)-based gene therapy protocols have been used to treat tissue ischemia, and a combined VEGF/MSC therapeutics is appealing due to their synergistic paracrine actions. However, multiple VEGF splice variants exhibit differences in their mitogenicity, chemotactic efficacy, receptor interaction, and tissue distribution, and the differential regulatory effects of multiple VEGF isoforms on the function of MSCs have not been characterized. We expressed three rat VEGF-A splice variants VEGF120, 164, and 188 in MSCs using adenoviral vectors, and analyzed their effects on MSC proliferation, differentiation, survival, and trophic factor production. The three VEGF splice variants exert common and differential effects on MSCs. All three expressed VEGFs are potent in promoting MSC proliferation. VEGF120 and 188 are more effective in amplifying expression of multiple growth factor and cytokine genes. VEGF164 on the other hand is more potent in promoting expression of genes associated with MSC remodeling and endothelial differentiation. The longer isoform VEGF188, which is preferentially retained by proteoglycans, facilitates bone morphogenetic protein-7 (BMP7)-mediated MSC osteogenesis. Under serum starvation condition, virally expressed VEGF188 preferentially enhances serum withdrawal-mediated cell death involving nitric oxide production. This work indicates that seeking the best possible match of an optimal VEGF isoform to a given disease setting can generate maximum therapeutic benefits and minimize unwanted side effects in combined stem cell and gene therapy.     

Potential regulatory sequences in the untranslated regions of the baboon MHC class Ib gene, <Emphasis Type="Italic">Paan-AG</Emphasis>, more closely resemble those in the human MHC class Ia genes than those in the class Ib gene, <Emphasis Type="Italic">HLA-G</Emphasis>

The baboon major histocompatibility complex (MHC) class Ib gene, Paan-AG, is structurally similar to the human MHC class Ia gene, HLA-A, but exhibits characteristics similar to those of the class Ib gene HLA-G. These include limited polymorphism, alternative splicing of a single message, and restricted tissue distribution, with high expression in the placenta. In order to determine whether regulatory elements controlling expression of Paan-AG resemble those of HLA-A or HLA-G, we cloned the 5 and 3 untranslated regions of Paan-AG. Unexpectedly, sequence comparisons showed that potential regulatory elements in Paan-AG strikingly resembled those in HLA-A and differed in major respects from those in HLA-G. Unlike HLA-G, Paan-AG contained an intact interferon- stimulated response element (ISRE) in the promoter. Studies using luciferase reporter assays showed that the Paan-AG ISRE was functional. The basal activity of the Paan-AG ISRE and its response to interferon- was similar to that of class Ia MHC genes. Further, we identified an ISRE in the 3 untranslated region of Paan-AG that is known to be functional in HLA-A2 but is deleted in HLA-G. These experiments predict that functional studies may demonstrate differences in regulation of expression of Paan-AG and HLA-G genes, which could restrict the use of the baboon as a primate model for studying HLA-G expression and function.The nucleotide sequence data reported in this paper are available in the DDBJ/EMBL/GenBank databases under accession numbers AY434095, AY434096, AY434097 and AY434103.     

A peroxidase-dependent apoplastic oxidative burst in cultured Arabidopsis cells functions in MAMP-elicited defense

Perception by plants of so-called microbe-associated molecular patterns (MAMPs) such as bacterial flagellin, referred to as pattern-triggered immunity, triggers a rapid transient accumulation of reactive oxygen species (ROS). We previously identified two cell wall peroxidases, PRX33 and PRX34, involved in apoplastic hydrogen peroxide (H2O2) production in Arabidopsis (Arabidopsis thaliana). Here, we describe the generation of Arabidopsis tissue culture lines in which the expression of PRX33 and PRX34 is knocked down by antisense expression of a heterologous French bean (Phaseolus vulgaris) peroxidase cDNA construct. Using these tissue culture lines and two inhibitors of ROS generation, azide and diphenylene iodonium, we found that perxoxidases generate about half of the H2O2 that accumulated in response to MAMP treatment and that NADPH oxidases and other sources such as mitochondria account for the remainder of the ROS. Knockdown of PRX33/PRX34 resulted in decreased expression of several MAMP-elicited genes, including MYB51, CYP79B2, and CYP81F2. Similarly, proteomic analysis showed that knockdown of PRX33/PRX34 led to the depletion of various MAMP-elicited defense-related proteins, including the two cysteine-rich peptides PDF2.2 and PDF2.3. Knockdown of PRX33/PRX34 also led to changes in the cell wall proteome, including increases in enzymes involved in cell wall remodeling, which may reflect enhanced cell wall expansion as a consequence of reduced H2O2-mediated cell wall cross-linking. Comparative metabolite profiling of a CaCl2 extract of the PRX33/PRX34 knockdown lines showed significant changes in amino acids, aldehydes, and keto acids but not fatty acids and sugars. Overall, these data suggest that PRX33/PRX34-generated ROS production is involved in the orchestration of pattern-triggered immunity in tissue culture cells.     

Serum levels of IL-32 in patients with coronary artery disease and its relationship with the serum levels of IL-6 and TNF-α

Molecular Biology Reports - The coronary artery disease (CAD) is a chronic inflammatory disease caused by atherosclerosis, in which arteries become clogged due to plaque formation, fat...     

Isolation of alkaliphilic calcifying bacteria and their feasibility for enhanced CaCO3 precipitation in bio-based cementitious composites

Microbially induced calcite precipitation (MICP), secreted through biological metabolic activity, secured an imperative position in remedial measures within the construction industry subsequent to ecological, environmental and economical returns. However, this contemporary recurrent healing system is susceptible to microbial depletion in the highly alkaline cementitious environment. Therefore, researchers are probing for alkali resistant calcifying microbes. In the present study, alkaliphilic microbes were isolated from different soil sources and screened for probable CaCO₃ precipitation. Non-ureolytic pathway (oxidation of organic carbon) was adopted for calcite precipitation to eliminate the production of toxic ammonia. For this purpose, calcium lactate Ca(C₃H₅O₃)₂ and calcium acetate Ca(CH₃COO)₂ were used as CaCO₃ precipitation precursors. The quantification protocol for precipitated CaCO₃ was established to select potent microbial species for implementation in the alkaline cementitious systems as more than 50% of isolates were able to precipitate CaCO₃. Results suggested 80% of potent calcifying strains isolated in this study, portrayed higher calcite precipitation at pH 10 when compared to pH 7. Ten superlative morphologically distinct isolates capable of CaCO₃ production were identified by 16SrRNA sequencing. Sequenced microbes were identified as species of Bacillus, Arthrobacter, Planococcus, Chryseomicrobium and Corynebacterium. Further, microstructure of precipitated CaCO₃ was inspected through scanning electron microscopy (SEM), X-ray diffraction (XRD) and thermal gravimetric (TG) analysis. Then, the selected microbes were investigated in the cementitious mortar to rule out any detrimental effects on mechanical properties. These strains showed maximum of 36% increase in compressive strength and 96% increase in flexural strength. Bacillus, Arthrobacter, Corynebacterium and Planococcus genera have been reported as CaCO₃ producers but isolated strains have not yet been investigated in conjunction with cementitious mortar. Moreover, species of Chryseomicrobium and Glutamicibacter were reported first time as calcifying strains.     

Clinicopathological and immunohistochemical study of 29 cases of solid-pseudopapillary neoplasms of the pancreas in patients under 20 years of age along with detailed review of literature

Background

Multiplex immunohistochemistry (mIHC) permits the labeling of six or more distinct cell types within a single histologic tissue section. The classification of each cell type requires detection of uniquely colored chromogens localized to cells expressing biomarkers of interest. The most comprehensive and reproducible method to evaluate such slides is to employ digital pathology and image analysis pipelines to whole-slide images (WSIs). Our suite of deep learning tools quantitatively evaluates the expression of six biomarkers in mIHC WSIs. These methods address the current lack of readily available methods to evaluate more than four biomarkers and circumvent the need for specialized instrumentation to spectrally separate different colors. The use case application for our methods is a study that investigates tumor immune interactions in pancreatic ductal adenocarcinoma (PDAC) with a customized mIHC panel.

Methods

Six different colored chromogens were utilized to label T-cells (CD3, CD4, CD8), B-cells (CD20), macrophages (CD16), and tumor cells (K17) in formalin-fixed paraffin-embedded (FFPE) PDAC tissue sections. We leveraged pathologist annotations to develop complementary deep learning-based methods: (1) ColorAE is a deep autoencoder which segments stained objects based on color; (2) U-Net is a convolutional neural network (CNN) trained to segment cells based on color, texture and shape; and (3) ensemble methods that employ both ColorAE and U-Net, collectively referred to as ColorAE:U-Net. We assessed the performance of our methods using: structural similarity and DICE score to evaluate segmentation results of ColorAE against traditional color deconvolution; F1 score, sensitivity, positive predictive value, and DICE score to evaluate the predictions from ColorAE, U-Net, and ColorAE:U-Net ensemble methods against pathologist-generated ground truth. We then used prediction results for spatial analysis (nearest neighbor).

Results

We observed that (1) the performance of ColorAE is comparable to traditional color deconvolution for single-stain IHC images (note: traditional color deconvolution cannot be used for mIHC); (2) ColorAE and U-Net are complementary methods that detect six different classes of cells with comparable performance; (3) combinations of ColorAE and U-Net in ensemble methods outperform ColorAE and U-Net alone; and (4) ColorAE:U-Net ensemble methods can be employed for detailed analysis of the tumor microenvironment (TME).

Summary

We developed a suite of scalable deep learning methods to analyze 6 distinctly labeled cell populations in mIHC WSIs. We evaluated our methods and found that they reliably detected and classified cells in the PDAC tumor microenvironment. We also utilized the ColorAE:U-Net ensemble method to analyze 3 mIHC WSIs with nearest neighbor spatial analysis. We demonstrate a proof of concept that these methods can be employed to quantitatively describe the spatial distribution of immune cells within the tumor microenvironment. These complementary deep learning methods are readily deployable for use in clinical research studies.