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.
Investigative Ophthalmology & Visual Science
2022 Jan 01
Yang, H;Yuan, M;Gaurang, P;Sun, A;
Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology
2022 Sep 08
McNulty, CJ;Fallon, IP;Amat, J;Sanchez, RJ;Leslie, NR;Root, DH;Maier, SF;Baratta, MV;
PMID: 36076018 | DOI: 10.1038/s41386-022-01443-w
Immunology
2022 Apr 11
Fan, W;Huang, W;Chen, J;Li, N;Mao, L;Hou, S;
PMID: 35403700 | DOI: 10.1111/imm.13479
Cell reports
2022 Nov 15
Lysko, DE;Talbot, WS;
PMID: 36384112 | DOI: 10.1016/j.celrep.2022.111669
Acta pharmacologica Sinica
2022 Dec 02
Chen, ZJ;Su, CW;Xiong, S;Li, T;Liang, HY;Lin, YH;Chang, L;Wu, HY;Li, F;Zhu, DY;Luo, CX;
PMID: 36460834 | DOI: 10.1038/s41401-022-01024-z
British journal of pharmacology
2023 Apr 19
Bode, M;Diemer, JN;Luu, TV;Ehnert, N;Teigeler, T;Wiech, T;Lindenmeyer, MT;Herrnstadt, GR;Bülow, J;Huber, TB;Tomas, NM;Wenzel, UO;
PMID: 37076314 | DOI: 10.1111/bph.16097
Acta Neuropathol Commun.
2020 Feb 14
McKinnon C, De Snoo ML, Gondard E, Neudorfer C, Chau H, Ngana SG, O'Hara DM, Brotchie JM, Koprich JB, Lozano AM, Kalia LV, Kalia SK
PMID: 32059750 | DOI: 10.1186/s40478-020-0894-0
Communications biology
2022 Aug 18
Noh, YW;Yook, C;Kang, J;Lee, S;Kim, Y;Yang, E;Kim, H;Kim, E;
PMID: 35982261 | DOI: 10.1038/s42003-022-03813-y
EMBO J.
2019 Feb 08
Anderson R, Lagnado A, Maggiorani D, Walaszczyk A, Dookun E, Chapman J, Birch J, Salmonowicz H, Ogrodnik M, Jurk D, Proctor C, Correia-Melo C, Victorelli S, Fielder E, Berlinguer-Palmini R, Owens A, Greaves LC, Kolsky KL, Parini A, Douin-Echinard V, LeBrasseur NK, Arthur HM, Tual-Chalot S, Schafer MJ, Roos CM, Miller JD, Robertson N, Mann J, Adams PD, Tchkonia T, Kirkland JL, Mialet-Perez J, Richardson GD, Passos JF.
PMID: 30737259 | DOI: 10.15252/embj.2018100492
Ageing is the biggest risk factor for cardiovascular disease. Cellular senescence, a process driven in part by telomere shortening, has been implicated in age-related tissue dysfunction. Here, we address the question of how senescence is induced in rarely dividing/post-mitotic cardiomyocytes and investigate whether clearance of senescent cells attenuates age-related cardiac dysfunction. During ageing, human and murine cardiomyocytes acquire a senescent-like phenotype characterised by persistent DNA damage at telomere regions that can be driven by mitochondrial dysfunction and crucially can occur independently of cell division and telomere length. Length-independent telomere damage in cardiomyocytes activates the classical senescence-inducing pathways, p21CIP and p16INK4a, and results in a non-canonical senescence-associated secretory phenotype, which is pro-fibrotic and pro-hypertrophic. Pharmacological or genetic clearance of senescent cells in mice alleviates detrimental features of cardiac ageing, including myocardial hypertrophy and fibrosis. Our data describe a mechanism by which senescence can occur and contribute to age-related myocardial dysfunction and in the wider setting to ageing in post-mitotic tissues.
Neurobiology of disease
2021 Oct 19
Bourel, J;Planche, V;Dubourdieu, N;Oliveira, A;Séré, A;Ducourneau, EG;Tible, M;Maitre, M;Lesté-Lasserre, T;Nadjar, A;Desmedt, A;Ciofi, P;Oliet, SH;Panatier, A;Tourdias, T;
PMID: 34673149 | DOI: 10.1016/j.nbd.2021.105533
PNAS 2018
2018 Feb 07
Clarke LE, Liddelow SA, Chakraborty C, Münch AE, Heiman M, Barres BA.
PMID: - | DOI: 10.1073/pnas.1800165115
The decline of cognitive function occurs with aging, but the mechanisms responsible are unknown. Astrocytes instruct the formation, maturation, and elimination of synapses, and impairment of these functions has been implicated in many diseases. These findings raise the question of whether astrocyte dysfunction could contribute to cognitive decline in aging. We used the Bac-Trap method to perform RNA sequencing of astrocytes from different brain regions across the lifespan of the mouse. We found that astrocytes have region-specific transcriptional identities that change with age in a region-dependent manner. We validated our findings using fluorescence in situ hybridization and quantitative PCR. Detailed analysis of the differentially expressed genes in aging revealed that aged astrocytes take on a reactive phenotype of neuroinflammatory A1-like reactive astrocytes. Hippocampal and striatal astrocytes up-regulated a greater number of reactive astrocyte genes compared with cortical astrocytes. Moreover, aged brains formed many more A1 reactive astrocytes in response to the neuroinflammation inducer lipopolysaccharide. We found that the aging-induced up-regulation of reactive astrocyte genes was significantly reduced in mice lacking the microglial-secreted cytokines (IL-1α, TNF, and C1q) known to induce A1 reactive astrocyte formation, indicating that microglia promote astrocyte activation in aging. Since A1 reactive astrocytes lose the ability to carry out their normal functions, produce complement components, and release a toxic factor which kills neurons and oligodendrocytes, the aging-induced up-regulation of reactive genes by astrocytes could contribute to the cognitive decline in vulnerable brain regions in normal aging and contribute to the greater vulnerability of the aged brain to injury.
Molecular Metabolism
2018 Nov 27
López-Ferreras L, Eerola K, Mishra D, Shevchouk OT, Richard JE, Nilsson FH, Hayes MR, Skibicka KP.
PMID: - | DOI: 10.1016/j.molmet.2018.11.005
Objective
The supramammillary nucleus (SuM) is nestled between the lateral hypothalamus (LH) and the ventral tegmental area (VTA). This neuroanatomical position is consistent with a potential role of this nucleus to regulate ingestive and motivated behavior. Here neuroanatomical, molecular, and behavior approaches are utilized to determine whether SuM contributes to ingestive and food-motivated behavior control.
Methods
Through the application of anterograde and retrograde neural tract tracing with novel designer viral vectors, the current findings show that SuM neurons densely innervate the LH in a sex dimorphic fashion. Glucagon-like peptide-1 (GLP-1) is a clinically targeted neuro-intestinal hormone with a well-established role in regulating energy balance and reward behaviors. Here we determine that GLP-1 receptors (GLP-1R) are expressed throughout the SuM of both sexes, and also directly on SuM LH-projecting neurons and investigate the role of SuM GLP-1R in the regulation of ingestive and motivated behavior in male and female rats.
Results
SuM microinjections of the GLP-1 analogue, exendin-4, reduced ad libitum intake of chow, fat, or sugar solution in both male and female rats, while food-motivated behaviors, measured using the sucrose motivated operant conditioning test, was only reduced in male rats. These data contrasted with the results obtained from a neighboring structure well known for its role in motivation and reward, the VTA, where females displayed a more potent response to GLP-1R activation by exendin-4. In order to determine the physiological role of SuM GLP-1R signaling regulation of energy balance, we utilized an adeno-associated viral vector to site-specifically deliver shRNA for the GLP-1R to the SuM. Surprisingly, and in contrast to previous results for the two SuM neighboring sites, LH and VTA, SuM GLP-1R knockdown increased food seeking and adiposity in obese male rats without altering food intake, body weight or food motivation in lean or obese, female or male rats.
Conclusion
Taken together, these results indicate that SuM potently contributes to ingestive and motivated behavior control; an effect contingent on sex, diet/homeostatic energy balance state and behavior of interest. These data also extend the map of brain sites directly responsive to GLP-1 agonists, and highlight key differences in the role that GLP-1R play in interconnected and neighboring nuclei.
Description | ||
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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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