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Probes for INS

ACD can configure probes for the various manual and automated assays for INS for RNAscope Assay, or for Basescope Assay compatible for your species of interest.

  • Probes for INS (11)
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Single‐Cell Transcriptomic Census of Endothelial Changes Induced by Matrix Stiffness and the Association with Atherosclerosis

Advanced Functional Materials

2022 Sep 12

Zamani, M;Cheng, Y;Charbonier, F;Gupta, V;Mayer, A;Trevino, A;Quertermous, T;Chaudhuri, O;Cahan, P;Huang, N;
| DOI: 10.1002/adfm.202203069

Vascular endothelial cell (EC) plasticity plays a critical role in the progression of atherosclerosis by giving rise to mesenchymal phenotypes in the plaque lesion. Despite the evidence for arterial stiffening as a major contributor to atherosclerosis, the complex interplay among atherogenic stimuli in vivo has hindered attempts to determine the effects of extracellular matrix (ECM) stiffness on endothelial-mesenchymal transition (EndMT). To study the regulatory effects of ECM stiffness on EndMT, an in vitro model is developed in which human coronary artery ECs are cultured on physiological or pathological stiffness substrates. Leveraging single-cell RNA sequencing, cell clusters with mesenchymal transcriptional features are identified to be more prevalent on pathological substrates than physiological substrates. Trajectory inference analyses reveal a novel mesenchymal-to-endothelial reverse transition, which is blocked by pathological stiffness substrates, in addition to the expected EndMT trajectory. ECs pushed to a mesenchymal character by pathological stiffness substrates are enriched in transcriptional signatures of atherosclerotic ECs from human and murine plaques. This study characterizes at single-cell resolution the transcriptional programs that underpin EC plasticity in both physiological or pathological milieus, and thus serves as a valuable resource for more precisely defining EndMT and the transcriptional programs contributing to atherosclerosis.
Multispectral LEDs Eliminate Lipofuscin-Associated Autofluorescence for Immunohistochemistry and CD44 Variant Detection by in Situ Hybridization in Aging Human, non-Human Primate, and Murine Brain

ASN neuro

2022 Sep 27

Adeniyi, PA;Fopiano, KA;Banine, F;Garcia, M;Gong, X;Keene, CD;Sherman, LS;Bagi, Z;Back, SA;
PMID: 36164936 | DOI: 10.1177/17590914221123138

A major limitation of mechanistic studies in aging brains is the lack of routine methods to robustly visualize and discriminate the cellular distribution of tissue antigens using fluorescent immunohistochemical multi-labeling techniques. Although such approaches are routine in non-aging brains, they are not consistently feasible in the aging brain due to the progressive accumulation of autofluorescent pigments, particularly lipofuscin, which strongly excite and emit over a broad spectral range. Consequently, aging research has relied upon colorimetric antibody techniques, where discrimination of tissue antigens is often challenging. We report the application of a simple, reproducible, and affordable protocol using multispectral light-emitting diodes (mLEDs) exposure for the reduction/elimination of lipofuscin autofluorescence (LAF) in aging brain tissue from humans, non-human primates, and mice. The mLEDs lamp has a broad spectral range that spans from the UV to infrared range and includes spectra in the violet/blue and orange/red. After photo quenching, the LAF level was markedly reduced when the tissue background fluorescence before and after mLEDs exposure was compared (p < 0.0001) across the spectral range. LAF elimination was estimated at 95 ± 1%. This approach permitted robust specific fluorescent immunohistochemical co-visualization of commonly studied antigens in aging brains. We also successfully applied this method to specifically visualize CD44 variant expression in aging human cerebral white matter using RNAscope fluorescent in-situ hybridization. Photo quenching provides an attractive means to accelerate progress in aging research by increasing the number of molecules that can be topologically discriminated by fluorescence detection in brain tissue from normative or pathological aging.
Human striatal glia differentially contribute to AD- and PD-specific neurodegeneration

Nature Aging

2023 Feb 09

Xu, J;Farsad, H;Hou, Y;Barclay, K;Lopez, B;Yamada, S;Saliu, I;Shi, Y;Knight, W;Bateman, R;Benzinger, T;Yi, J;Li, Q;Wang, T;Perlmutter, J;Morris, J;Zhao, G;
| DOI: 10.1038/s43587-023-00363-8

A, Upset plot showing the overlap between putamen conserved marker genes of Ast-0, Ast-1 and Ast-2 astrocyte with marker genes of mouse DAA and Gfap-high astrocytes from Habib et al., 2020. B, Violin plots showing the expression level distributions of orthologous genes of murine DAA and Gfap-high astrocyte marker genes in the putamen astrocytes. C, PCA plot using murine DAA and Gfap-high astrocyte marker gene logFC of gene expression (comparing murine DAA and Gfap-high astrocyte with Gfap-low astrocytes, downloaded from Habib et al., 2020) and the logFC of the human orthologous genes (comparing putamen Ast-1 and Ast-2 with Ast-0 astrocytes). D,E, Violin plots showing the expression level distributions of reactive astrocyte marker genes in astrocytes from the (D) putamen and (E) prefrontal cortex. F, Violin plots showing the expression level distributions of A1-, A2-specific activated astrocyte markers and JAK-STAT3 pathway genes. G, Top 10 GO terms in the Biological Process category enriched in the astrocyte subpopulation signature genes (hypergeometric test, FDR-adjusted P value < 0.05, ≥ 5 query genes). Conserved marker genes plotted in panel (B), (D) and (E) were determined by FindConservedMarkers using Wilcoxon Rank Sum test and _metap_ R package with meta-analysis combined P value < 0.05 comparing gene expression in the given cluster with the other cell clusters for AD (n = 4), PD (n = 4) and the controls (n = 4). Genes plotted in (F) were not statistically significantly higher in any of the astrocyte subpopulations.
High-plex imaging of RNA and proteins at subcellular resolution in fixed tissue by spatial molecular imaging

Nature biotechnology

2022 Oct 06

He, S;Bhatt, R;Brown, C;Brown, EA;Buhr, DL;Chantranuvatana, K;Danaher, P;Dunaway, D;Garrison, RG;Geiss, G;Gregory, MT;Hoang, ML;Khafizov, R;Killingbeck, EE;Kim, D;Kim, TK;Kim, Y;Klock, A;Korukonda, M;Kutchma, A;Lewis, ZR;Liang, Y;Nelson, JS;Ong, GT;Perillo, EP;Phan, JC;Phan-Everson, T;Piazza, E;Rane, T;Reitz, Z;Rhodes, M;Rosenbloom, A;Ross, D;Sato, H;Wardhani, AW;Williams-Wietzikoski, CA;Wu, L;Beechem, JM;
PMID: 36203011 | DOI: 10.1038/s41587-022-01483-z

Resolving the spatial distribution of RNA and protein in tissues at subcellular resolution is a challenge in the field of spatial biology. We describe spatial molecular imaging, a system that measures RNAs and proteins in intact biological samples at subcellular resolution by performing multiple cycles of nucleic acid hybridization of fluorescent molecular barcodes. We demonstrate that spatial molecular imaging has high sensitivity (one or two copies per cell) and very low error rate (0.0092 false calls per cell) and background (~0.04 counts per cell). The imaging system generates three-dimensional, super-resolution localization of analytes at ~2 million cells per sample. Cell segmentation is morphology based using antibodies, compatible with formalin-fixed, paraffin-embedded samples. We measured multiomic data (980 RNAs and 108 proteins) at subcellular resolution in formalin-fixed, paraffin-embedded tissues (nonsmall cell lung and breast cancer) and identified >18 distinct cell types, ten unique tumor microenvironments and 100 pairwise ligand-receptor interactions. Data on >800,000 single cells and ~260 million transcripts can be accessed at http://nanostring.com/CosMx-dataset .
Non-thermal plasma promotes hair growth by improving the inter-follicular macroenvironment

RSC Advances

2021 Aug 17

Kim, H;Choi, E;Choi, E;Kim, H;Kim, J;Cho, G;Kim, H;Na, S;Shin, J;Do, S;Park, B;
| DOI: 10.1039/d1ra04625j

Non-thermal plasma (NTP) is widely used in the disinfection and surface modification of biomaterials.
Stress induced aging in mouse eye

Aging cell

2022 Nov 17

Xu, Q;Rydz, C;Nguyen Huu, VA;Rocha, L;Palomino La Torre, C;Lee, I;Cho, W;Jabari, M;Donello, J;Lyon, DC;Brooke, RT;Horvath, S;Weinreb, RN;Ju, WK;Foik, A;Skowronska-Krawczyk, D;
PMID: 36397653 | DOI: 10.1111/acel.13737

Aging, a universal process that affects all cells in an organism, is a major risk factor for a group of neuropathies called glaucoma, where elevated intraocular pressure is one of the known stresses affecting the tissue. Our understanding of molecular impact of aging on response to stress in retina is very limited; therefore, we developed a new mouse model to approach this question experimentally. Here we show that susceptibility to response to stress increases with age and is primed on chromatin level. We demonstrate that ocular hypertension activates a stress response that is similar to natural aging and involves activation of inflammation and senescence. We show that multiple instances of pressure elevation cause aging of young retina as measured on transcriptional and DNA methylation level and are accompanied by local histone modification changes. Our data show that repeated stress accelerates appearance of aging features in tissues and suggest chromatin modifications as the key molecular components of aging. Lastly, our work further emphasizes the importance of early diagnosis and prevention as well as age-specific management of age-related diseases, including glaucoma.
Myeloid cell interferon secretion restricts Zika flavivirus infection of developing and malignant human neural progenitor cells

Neuron

2022 Sep 26

Bulstrode, H;Girdler, GC;Gracia, T;Aivazidis, A;Moutsopoulos, I;Young, AMH;Hancock, J;He, X;Ridley, K;Xu, Z;Stockley, JH;Finlay, J;Hallou, C;Fajardo, T;Fountain, DM;van Dongen, S;Joannides, A;Morris, R;Mair, R;Watts, C;Santarius, T;Price, SJ;Hutchinson, PJA;Hodson, EJ;Pollard, SM;Mohorianu, I;Barker, RA;Sweeney, TR;Bayraktar, O;Gergely, F;Rowitch, DH;
PMID: 36174572 | DOI: 10.1016/j.neuron.2022.09.002

Zika virus (ZIKV) can infect human developing brain (HDB) progenitors resulting in epidemic microcephaly, whereas analogous cellular tropism offers treatment potential for the adult brain cancer, glioblastoma (GBM). We compared productive ZIKV infection in HDB and GBM primary tissue explants that both contain SOX2+ neural progenitors. Strikingly, although the HDB proved uniformly vulnerable to ZIKV infection, GBM was more refractory, and this correlated with an innate immune expression signature. Indeed, GBM-derived CD11b+ microglia/macrophages were necessary and sufficient to protect progenitors against ZIKV infection in a non-cell autonomous manner. Using SOX2+ GBM cell lines, we found that CD11b+-conditioned medium containing type 1 interferon beta (IFNβ) promoted progenitor resistance to ZIKV, whereas inhibition of JAK1/2 signaling restored productive infection. Additionally, CD11b+ conditioned medium, and IFNβ treatment rendered HDB progenitor lines and explants refractory to ZIKV. These findings provide insight into neuroprotection for HDB progenitors as well as enhanced GBM oncolytic therapies.
X
Description
sense
Example: Hs-LAG3-sense
Standard probes for RNA detection are in antisense. Sense probe is reverse complent to the corresponding antisense probe.
Intron#
Example: Mm-Htt-intron2
Probe targets the indicated intron in the target gene, commonly used for pre-mRNA detection
Pool/Pan
Example: Hs-CD3-pool (Hs-CD3D, Hs-CD3E, Hs-CD3G)
A mixture of multiple probe sets targeting multiple genes or transcripts
No-XSp
Example: Hs-PDGFB-No-XMm
Does not cross detect with the species (Sp)
XSp
Example: Rn-Pde9a-XMm
designed to cross detect with the species (Sp)
O#
Example: Mm-Islr-O1
Alternative design targeting different regions of the same transcript or isoforms
CDS
Example: Hs-SLC31A-CDS
Probe targets the protein-coding sequence only
EnEmProbe targets exons n and m
En-EmProbe targets region from exon n to exon m
Retired Nomenclature
tvn
Example: Hs-LEPR-tv1
Designed to target transcript variant n
ORF
Example: Hs-ACVRL1-ORF
Probe targets open reading frame
UTR
Example: Hs-HTT-UTR-C3
Probe targets the untranslated region (non-protein-coding region) only
5UTR
Example: Hs-GNRHR-5UTR
Probe targets the 5' untranslated region only
3UTR
Example: Rn-Npy1r-3UTR
Probe targets the 3' untranslated region only
Pan
Example: Pool
A mixture of multiple probe sets targeting multiple genes or transcripts

Enabling research, drug development (CDx) and diagnostics

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