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.
J Comp Neurol.
2018 Jul 17
Patrick Card J, Johnson AL, Llewellyn-Smith IJ, Zheng H, Anand R, Brierley DI, Trapp S, Rinaman L.
PMID: 30019398 | DOI: 10.1002/cne.24482
Glutamatergic neurons that express pre-proglucagon (PPG) and are immunopositive (+) for glucagon-like peptide-1 (i.e., GLP-1+ neurons) are located within the caudal nucleus of the solitary tract (cNTS) and medullary reticular formation in rats and mice. GLP-1 neurons give rise to an extensive central network in which GLP-1 receptor (R) signaling suppresses food intake, attenuates rewarding, increases avoidance, and stimulates stress responses, partly via . GLP-1R signaling within the cNTS. In mice, noradrenergic (A2) cNTS neurons express GLP-1R, whereas PPG neurons do not. In the present study, confocal microscopy in rats confirmed that prolactin-releasing peptide (PrRP)+ A2 neurons are closely apposed by GLP-1+ axonal varicosities. Surprisingly, GLP-1+ appositions were also observed on dendrites of PPG/GLP-1+ neurons in both species, and electron microscopy in rats revealed that GLP-1+ boutons form asymmetric synaptic contacts with GLP-1+ dendrites. However, RNAscope confirmed that rat GLP-1 neurons do not express GLP-1R mRNA. Similarly, Ca2+ imaging of somatic and dendritic responses in mouse ex vivo slices confirmed that PPG neurons do not respond directly to GLP-1, and a mouse cross-breeding strategy revealed that fewer than 1% of PPG neurons co-express GLP-1R. Collectively, these data suggest that GLP-1R signaling pathways modulate the activity of PrRP+ A2 neurons, and also reveal a local "feed-forward" synaptic network among GLP-1 neurons that apparently does not utilize GLP-1R signaling. This local GLP-1 network may instead use glutamatergic signaling to facilitate dynamic and potentially selective recruitment of GLP-1 neural populations that shape behavioral and physiological responses to internal and external challenges.
Vaccine
2022 Jun 06
Shanmugaraj, B;Khorattanakulchai, N;Panapitakkul, C;Malla, A;Im-Erbsin, R;Inthawong, M;Sunyakumthorn, P;Hunsawong, T;Klungthong, C;Reed, MC;Kemthong, T;Suttisan, N;Malaivijitnond, S;Srimangkornkaew, P;Klinkhamhom, A;Manopwisedjaroen, S;Thitithanyanont, A;Taychakhoonavudh, S;Phoolcharoen, W;
PMID: 35697573 | DOI: 10.1016/j.vaccine.2022.05.087
Placenta
2022 Jul 01
Takada, K;Shimodai-Yamada, S;Suzuki, M;Trinh, Q;Takano, C;Kawakami, K;Asai-Sato, M;Komatsu, A;Okahashi, A;Nagano, N;Misawa, T;Yamaguchi, K;Suzuki, T;Kawana, K;Morioka, I;Yamada, H;Hayakawa, S;Hao, H;Komine-Aizawa, S;
| DOI: 10.1016/j.placenta.2022.07.010
Vectorology for Optogenetics and Chemogenetics
2023 Feb 07
Lin, J;Dimidschstein, J;
| DOI: 10.1007/978-1-0716-2918-5_9
Nat Neurosci.
2017 Dec 11
Hrvatin S, Hochbaum DR, Nagy MA, Cicconet M, Robertson K, Cheadle L, Zilionis R, Ratner A, Borges-Monroy R, Klein AM, Sabatini BL, Greenberg ME.
PMID: 29230054 | DOI: 10.1038/s41593-017-0029-5
Activity-dependent transcriptional responses shape cortical function. However, a comprehensive understanding of the diversity of these responses across the full range of cortical cell types, and how these changes contribute to neuronal plasticity and disease, is lacking. To investigate the breadth of transcriptional changes that occur across cell types in the mouse visual cortex after exposure to light, we applied high-throughput single-cell RNA sequencing. We identified significant and divergent transcriptional responses to stimulation in each of the 30 cell types characterized, thus revealing 611 stimulus-responsive genes. Excitatory pyramidal neurons exhibited inter- and intralaminar heterogeneity in the induction of stimulus-responsive genes. Non-neuronal cells showed clear transcriptional responses that may regulate experience-dependent changes in neurovascular coupling and myelination. Together, these results reveal the dynamic landscape of the stimulus-dependent transcriptional changes occurring across cell types in the visual cortex; these changes are probably critical for cortical function and may be sites of deregulation in developmental brain disorders.
Virology journal
2023 Jan 31
Zhang, C;Wei, B;Liu, Z;Yao, W;Li, Y;Lu, J;Ge, C;Yu, X;Li, D;Zhu, Y;Shang, C;Jin, N;Li, X;
PMID: 36721152 | DOI: 10.1186/s12985-023-01971-x
Cell reports
2022 Sep 20
Kim, S;Oh, H;Choi, SH;Yoo, YE;Noh, YW;Cho, Y;Im, GH;Lee, C;Oh, Y;Yang, E;Kim, G;Chung, WS;Kim, H;Kang, H;Bae, Y;Kim, SG;Kim, E;
PMID: 36130507 | DOI: 10.1016/j.celrep.2022.111398
Placenta
2021 Dec 02
Mao, Q;Chu, S;Shapiro, S;Young, L;Russo, M;De Paepe, ME;
PMID: 34929459 | DOI: 10.1016/j.placenta.2021.12.002
Cell reports
2021 Oct 19
McDonald, JT;Enguita, FJ;Taylor, D;Griffin, RJ;Priebe, W;Emmett, MR;Sajadi, MM;Harris, AD;Clement, J;Dybas, JM;Aykin-Burns, N;Guarnieri, JW;Singh, LN;Grabham, P;Baylin, SB;Yousey, A;Pearson, AN;Corry, PM;Saravia-Butler, A;Aunins, TR;Sharma, S;Nagpal, P;Meydan, C;Foox, J;Mozsary, C;Cerqueira, B;Zaksas, V;Singh, U;Wurtele, ES;Costes, SV;Davanzo, GG;Galeano, D;Paccanaro, A;Meinig, SL;Hagan, RS;Bowman, NM;UNC COVID-19 Pathobiology Consortium, ;Wolfgang, MC;Altinok, S;Sapoval, N;Treangen, TJ;Moraes-Vieira, PM;Vanderburg, C;Wallace, DC;Schisler, JC;Mason, CE;Chatterjee, A;Meller, R;Beheshti, A;
PMID: 34624208 | DOI: 10.1016/j.celrep.2021.109839
Neuroreport
2021 Jun 09
Lei, J;Liu, Y;Xie, T;Yao, G;Wang, G;Diao, B;Song, J;
PMID: 33994523 | DOI: 10.1097/WNR.0000000000001654
Curr Biol.
2017 Jul 01
Sharpe MJ, Marchant NJ, Whitaker LR, Richie CT, Zhang YJ, Campbell EJ, Koivula PP, Necarsulmer JC, Mejias-Aponte C, Morales M, Pickel J, Smith JC, Niv Y, Shaham Y, Harvey BK, Schoenbaum G.
PMID: 28690111 | DOI: 10.1016/j.cub.2017.06.024
Eating is a learned process. Our desires for specific foods arise through experience. Both electrical stimulation and optogenetic studies have shown that increased activity in the lateral hypothalamus (LH) promotes feeding. Current dogma is that these effects reflect a role for LH neurons in the control of the core motivation to feed, and their activity comes under control of forebrain regions to elicit learned food-motivated behaviors. However, these effects could also reflect the storage of associative information about the cues leading to food in LH itself. Here, we present data from several studies that are consistent with a role for LH in learning. In the first experiment, we use a novel GAD-Cre rat to show that optogenetic inhibition of LH γ-aminobutyric acid (GABA) neurons restricted to cue presentation disrupts the rats' ability to learn that a cue predicts food without affecting subsequent food consumption. In the second experiment, we show that this manipulation also disrupts the ability of a cue to promote food seeking after learning. Finally, we show that inhibition of the terminals of the LH GABA neurons in ventral-tegmental area (VTA) facilitates learning about reward-paired cues. These results suggest that the LH GABA neurons are critical for storing and later disseminating information about reward-predictive cues.
Nat Neurosci.
2018 Jan 15
Hochgerner H, Zeisel A, Lönnerberg P, Linnarsson S.
PMID: 29335606 | DOI: 10.1038/s41593-017-0056-2
The dentate gyrus of the hippocampus is a brain region in which neurogenesis persists into adulthood; however, the relationship between developmental and adult dentate gyrus neurogenesis has not been examined in detail. Here we used single-cell RNA sequencing to reveal the molecular dynamics and diversity of dentate gyrus cell types in perinatal, juvenile, and adult mice. We found distinct quiescent and proliferating progenitor cell types, linked by transient intermediate states to neuroblast stages and fully mature granule cells. We observed shifts in the molecular identity of quiescent and proliferating radial glia and granule cells during the postnatal period that were then maintained through adult stages. In contrast, intermediate progenitor cells, neuroblasts, and immature granule cells were nearly indistinguishable at all ages. These findings demonstrate the fundamental similarity of postnatal and adult neurogenesis in the hippocampus and pinpoint the early postnatal transformation of radial glia from embryonic progenitors to adult quiescent stem cells.
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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