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.
Sci Rep.
2017 Oct 05
Wang L, Huang J, Moore DC, Zuo C, Wu Q, Xie L, von der Mark K, Yuan X, Chen D, Warman ML, Ehrlich MG, Yang W.
PMID: 28983104 | DOI: 10.1038/s41598-017-12767-9
Transdifferentiation of hypertrophic chondrocytes into bone-forming osteoblasts has been reported, yet the underlying molecular mechanism remains incompletely understood. SHP2 is an ubiquitously expressed cytoplasmic protein tyrosine phosphatase. SHP2 loss-of-function mutations in chondroid cells are linked to metachondromatosis in humans and mice, suggesting a crucial role for SHP2 in the skeleton. However, the specific role of SHP2 in skeletal cells has not been elucidated. To approach this question, we ablated SHP2 in collagen 2α1(Col2α1)-Cre- and collagen 10α1(Col10α1)-Cre-expressing cells, predominantly proliferating and hypertrophic chondrocytes, using "Cre-loxP"-mediated gene excision. Mice lacking SHP2 in Col2α1-Cre-expressing cells die at mid-gestation. Postnatal SHP2 ablation in the same cell population caused dwarfism, chondrodysplasia and exostoses. In contrast, mice in which SHP2 was ablated in the Col10α1-Cre-expressing cells appeared normal but were osteopenic. Further mechanistic studies revealed that SHP2 exerted its influence partly by regulating the abundance of SOX9 in chondrocytes. Elevated and sustained SOX9 in SHP2-deficient hypertrophic chondrocytes impaired their differentiation to osteoblasts and impaired endochondral ossification. Our study uncovered an important role of SHP2 in bone development and cartilage homeostasis by influencing the osteogenic differentiation of hypertrophic chondrocytes and provided insight into the pathogenesis and potential treatment of skeletal diseases, such as osteopenia and osteoporosis.
The Journal of clinical investigation
2021 Dec 14
Yadav, VK;Berger, JM;Singh, P;Nagarajan, P;Karsenty, G;
PMID: 34905510 | DOI: 10.1172/JCI153752
Journal of developmental biology
2022 Feb 10
Vonk, AC;Hasel-Kolossa, SC;Lopez, GA;Hudnall, ML;Gamble, DJ;Lozito, TP;
PMID: 35225965 | DOI: 10.3390/jdb10010012
Cell Tissue Res.
2016 Apr 05
Brenna Ø, Furnes MW, Munkvold B, Kidd M, Sandvik AK, Gustafsson BI.
PMID: 27044258 | DOI: -
Guanylin (GUCA2A/Guca2a/GN) and uroguanylin (GUCA2B/Guca2b/UGN) are expressed in the gastrointestinal tract and have been implicated in ion and fluid homeostasis, satiety, abdominal pain, growth and intestinal barrier integrity. Their cellular sources are debated and include goblet cells, entero-/colonocytes, enteroendocrine (EE) cells and tuft cells. We therefore investigated the cellular sources of GN and UGN mRNAs in human and rat duodenal and colonic epithelium with in situ hybridization (ISH) to determine co-expression with Chromogranin A (CHGA/Chga/CgA; enterochromaffin [EC] cells), defensin alpha 6 (DEFA6/Defa6; Paneth cells), mucin 2 (MUC2/Muc2; goblet cells) and selected tuft cell markers. GUCA2A/Guca2a expression was localized to goblet cells and colonocytes in human and rat colon. In human duodenum, GUCA2A was expressed in Paneth cells and was scarce in villous epithelial cells. In rat duodenum, Guca2a was only localized to goblet cells. Guca2b was focally expressed in rat colon. In human and rat duodenum and in human colon, GUCA2B/Guca2b was expressed in dispersed solitary epithelial cells, some with a tuft cell-like appearance. Neither GUCA2A nor GUCA2B were co-expressed with CHGA in human duodenal cells. Consequently, EC cells are probably not the major source of human GN or UGN but other EE cells as a source of GN or UGN are not entirely excluded. No convincing overlap with tuft cell markers was found. For the first time, we demonstrate the cellular expression of GUCA2B in human duodenum. The specific cellular distribution of both GN and UGN differs between duodenum and colon and between human and rat intestines.
Human molecular genetics
2022 Aug 11
Bando, H;Brinkmeier, ML;Castinetti, F;Fang, Q;Lee, MS;Saveanu, A;Albarel, F;Dupuis, C;Brue, T;Camper, SA;
PMID: 35951005 | DOI: 10.1093/hmg/ddac192
Developmental cell
2023 Mar 27
Chen, HJ;Barske, L;Talbot, JC;Dinwoodie, OM;Roberts, RR;Farmer, DT;Jimenez, C;Merrill, AE;Tucker, AS;Crump, JG;
PMID: 36905926 | DOI: 10.1016/j.devcel.2023.02.011
Nature communications
2021 Nov 03
Jarmas, AE;Brunskill, EW;Chaturvedi, P;Salomonis, N;Kopan, R;
PMID: 34732708 | DOI: 10.1038/s41467-021-26626-9
JBMR Plus (2018)
2018 Dec 07
Miura Y, Ota S, Peterlin M, McDevitt G, Kanazawa S.
| DOI: 10.1002/jbm4.10132
Cellular and molecular gastroenterology and hepatology
2021 Dec 29
Kim, TY;Kim, S;Kim, Y;Lee, YS;Lee, S;Lee, SH;Kweon, MN;
PMID: 34971821 | DOI: 10.1016/j.jcmgh.2021.12.015
Clin Cancer Res.
2019 Apr 19
Piskol R, Huw LY, Sergin I, Klijn C, Modrusan Z, Kim D, Kljavin NM, Tam R, Patel R, Burton J, Penuel E, Qu X, Koeppen H, Sumiyoshi T, de Sauvage FJ, Lackner MR, de Sousa E Melo F, Kabbarah O.
PMID: 31004000 | DOI: 10.1158/1078-0432.CCR-18-3032
Abstract
PURPOSE:
Four consensus molecular subtypes (CMS1-4) of colorectal cancer (CRC) were identified in primary tumors and found to be associated with distinctive biological features and clinical outcomes. Given that distant metastasis largely accounts for CRC-related mortality, we examined the molecular and clinical attributes of CMS in metastatic CRC (mCRC).
EXPERIMENTAL DESIGN:
We developed a CRC-focused Nanostring based CMS classifier that is ideally suited to interrogate archival tissues. We successfully employ this panel in the CMS classification of FFPE tissues from mCRC cohorts, one of which is comprised of paired primary tumors and metastases. Finally, we developed novel mouse implantation models to enable modelling of CRC in vivo at relevant sites.
RESULTS:
Using our classifier we find that the biological hallmarks of mCRC, including CMS, are in general highly similar to those observed in non-metastatic early stage disease. Importantly, our data demonstrate that CMS1 has the worst outcome in relapsed disease, compared to other CMS. Assigning CMS to primary tumors and their matched metastases revealed mostly concordant subtypes between primary and metastasis. Molecular analysis of matched discordant pairs revealed differences in stromal composition at each site. The development of two novel in vivo orthotopic implantation models further reinforces the notion that extrinsic factors may impact on CMS identification in matched primary and metastatic CRC.
CONCLUSION:
We describe the utility of a Nanostring panel for CMS classification of FFPE clinical samples. Our work reveals the impact of intrinsic and extrinsic factors on CRC heterogeneity during disease progression.
Sci Rep
2020 Jan 16
Yoshida T, Takizawa N, Matsuda T, Yamada H, Kitada M, Tanaka S
PMID: 31949236 | DOI: 10.1038/s41598-019-57351-5
Emerg Infect Dis.
2016 Dec 15
Vergara-Alert J, van den Brand JM, Widagdo W, Muñoz M 5th, Raj S, Schipper D, Solanes D, Cordón I, Bensaid A, Haagmans BL, Segalés J.
PMID: 27901465 | DOI: 10.3201/eid2302.161239
Middle East respiratory syndrome (MERS) cases continue to be reported, predominantly in Saudi Arabia and occasionally other countries. Although dromedaries are the main reservoir, other animal species might be susceptible to MERS coronavirus (MERS-CoV) infection and potentially serve as reservoirs. To determine whether other animals are potential reservoirs, we inoculated MERS-CoV into llamas, pigs, sheep, and horses and collected nasal and rectal swab samples at various times. The presence of MERS-CoV in the nose of pigs and llamas was confirmed by PCR, titration of infectious virus, immunohistochemistry, and in situ hybridization; seroconversion was detected in animals of both species. Conversely, in sheep and horses, virus-specific antibodies did not develop and no evidence of viral replication in the upper respiratory tract was found. These results prove the susceptibility of llamas and pigs to MERS-CoV infection. Thus, the possibility of MERS-CoV circulation in animals other than dromedaries, such as llamas and pigs, is not negligible.
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 | |
EnEm | Probe targets exons n and m | |
En-Em | Probe 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 |
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