Log In Sign up
The largest database of trusted experimental protocols
> Anatomy > Body Part > Prefrontal Cortex

Prefrontal Cortex

The Prefrontal Cortex is the anterior part of the frontal lobe of the brain, involved in a wide range of cognitive functions including decision-making, problem-solving, and emotional regulation.
This region plays a critical role in higher-order cognitive processes and has been extensively studied in the context of neuropsychiatric disorders.
PubCompare.ai can help optimzze your Prefrontal Cortex research by providing AI-driven access to a wealth of protocols, pre-prints, and patents, while offering insightful comparisons to identify the best methods and products.
Enhance the reproducibility and accuracy of your studies with the power of PubCompare.ai.

Most cited protocols related to «Prefrontal Cortex»

1
Integrating scRNA-seq and scATAC-seq Data

Protocol full text hidden due to copyright restrictions

Open the protocol to access the free full text link

Publication 2019
Cells dimesna Genes Mus Prefrontal Cortex RNA, Small Cytoplasmic Single-Cell RNA-Seq Transcriptome Visual Cortex XCL1 protein, human
2
Transcriptomic Analysis of Postmortem PFC Tissue
Post-mortem PFC grey matter tissue homogenates were obtained from all subjects. Total RNA was extracted, amplified and fluorescently labelled. Reference RNA was pooled from all samples and treated identically to sample RNAs. Labelled RNAs were hybridized to two-colour custom-spotted arrays from the NHGRI microarray core facility. After normalization21 (link), log2 intensity ratios were further adjusted to reduce the impact of known and unknown sources of systematic noise on gene expression measures using surrogate variable analysis22 (link) (SVA). Validation of microarray expression patterns was performed by Taqman qPCR (Supplementary Table 8). In this study of RNA derived from tissue homogenates, differential gene expression within a population of cells stable in cell type is indistinguishable from a change in the abundance of cell types that express different genes. There is no doubt that both phenomena contribute to signals measured here in the prefrontal cortex.
Colantuoni C., Lipska B.K., Ye T., Hyde T.M., Tao R., Leek J.T., Colantuoni E.A., Elkahloun A.G., Herman M.M., Weinberger D.R, & Kleinman J.E. (2011). Temporal dynamics and genetic control of transcription in the human prefrontal cortex. Nature, 478(7370), 519-523.
Publication 2011
Autopsy Cells Gene Expression Genes Gray Matter Microarray Analysis Prefrontal Cortex Tissues
3
Schizophrenia Gene Expression Associations
We used SMR37 as our primary method to identify SNPs which might mediate association with schizophrenia through effects on gene expression. The significance for SMR is set at the Bonferroni corrected threshold of 0.05/M where M is the number of genes with significant eQTLs tested for a given tissue. Significant SMR associations imply colocalization of the schizophrenia associations with eQTL. We applied the HEIDI test37 to filter out SMR associations (PHEIDI < 0.01) due to linkage disequilibrium between SCZ-associated variants and eQTLs. cis-eQTL summary data were from three studies: fetal brain (N=120)38 , adult brain (n = ~1,500)39 and blood (n = ~32,000)40 . Linkage disequilibrium (LD) data required for the HEIDI test37 were estimated from the Health and Retirement Study (HRS)41 (n = 8,557). We included only genes with at least one cis-eQTL at PeQTL < 5×10−8, excluding those in MHC regions due to the complexity of this region. For blood, we included only genes with eQTLs in brain. This left 7,803 genes in blood, 10,890 genes in prefrontal cortex and 754 genes in fetal brain for analysis (see Supplementary Note for further details). SMR was performed using data from the primary GWAS. The results were then filtered to exclude significant SMR implicated genes where the eQTLs did not map within our definition of an associated locus in the Extended GWAS meta-analysis of our primary GWAS dataset and the dataset provided by deCODE genetics.
For genomic regions where there were multiple genes showing significant SMR associations, we attempted to resolve these with conditional analysis using GCTA-COJO42 ,43 . We selected the top-associated cis-eQTL for one gene (or a set of genes sharing the same cis-eQTL) ran a COJO analysis in the schizophrenia GWAS data and the eQTL data for each of the other genes conditioning on the selected top cis-eQTL. We then re-ran the SMR and HEIDI analyses using these conditional GWAS and eQTL results.
We used FUSION44 and EpiXcan45 as tests of robustness of the SMR results. Details are supplied in the Supplementary Note as are our approaches to prioritising SMR associated genes.
Trubetskoy V., Panagiotaropoulou G., Awasthi S., Braun A., Kraft J., Skarabis N., Walter H., Ripke S., Pardiñas A.F., Dennison C.A., Hall L.S., Harwood J.C., Richards A.L., Legge S.E., Lynham A., Williams N.M., Bray N.J., Escott-Price V., Kirov G., Holmans P.A., Pocklington A.J., Owen M.J., Walters J.T., O’Donovan M.C., Qi T., Sidorenko J., Wu Y., Zeng J., Gratten J., Visscher P.M., Yang J., Wray N.R., Qi T., Yang J., Bigdeli T.B., Fanous A.H., Bryois J., Bergen S.E., Kähler A.K., Magnusson P.K., Hultman C.M., Sullivan P.F., Chen C.Y., Atkinson E.G., Goldstein J.I., Howrigan D.P., Martin A.R., Daly M.J., Huang H., Neale B.M., Ripke S., Ge T., Lam M., Ge T., Atkinson E.G., Belliveau R.A., Chambert K.D., Genovese G., Lee P.H., Martin A.R., Pietiläinen O., McCarroll S.A., Moran J.L., Smoller J.W., Brown T.C., Feng G., Hyman S.E., Sheng M., Hyman S.E., Huang H., Neale B.M., Lam M., Chong S.A., Subramaniam M., Lam M., Lencz T., Malhotra A.K., Watanabe K., Frei O., Agartz I., Athanasiu L., Melle I., Andreassen O.A., Frei O., Athanasiu L., Melle I., Steen N.E., Andreassen O.A., Frei O., Ge T., DeLisi L.E., Mesholam-Gately R.I., Seidman L.J., Koopmans F., Magnusson S., Stefánsson H., Stefansson K., Grove J., Agerbo E., Als T.D., Bybjerg-Grauholm J., Demontis D., Hougaard D.M., Mors O., Mortensen P.B., Nordentoft M., Børglum A.D., Grove J., Als T.D., Demontis D., Mattheisen M., Børglum A.D., Grove J., Als T.D., Demontis D., Børglum A.D., Kim M., Gandal M.J., Li Z., Shi Y., Shi Y., Li Z., Zhou W., Qin S., Shi Y., Shi Y., Voloudakis G., Zhang W., Roussos P., Zhang W., Adams M., McIntosh A., Agartz I., Agartz I., Söderman E., Jönsson E.G., McGrath J.J., Al Eissa M., Bass N.J., Fiorentino A., O’Brien N.L., Pimm J., Sharp S.I., McQuillin A., Albus M., Alexander M., Alizadeh B.Z., Bruggeman R., Alizadeh B.Z., Alptekin K., Alptekin K., Amin F., Arolt V., Lencer R., Rothermundt M., Baune B.T., Arrojo M., Azevedo M.H., Bacanu S.A., Webb B.T., Wormley B.K., Riley B.P., Kendler K.S., Begemann M., Mitjans M., Steixner-Kumar A.A., Ehrenreich H., Bene J., Benyamin B., Benyamin B., Benyamin B., Blasi G., Rampino A., Torretta S., Bertolino A., Bobes J., Bobes J., Bobes J., Bonassi S., Bressan R.A., Gadelha A., Noto C., Bressan R.A., Gadelha A., Noto C., Ota V.K., Santoro M.L., Belangero S.I., Bromet E.J., Bruggeman R., Buckley P.F., Buckner R.L., Bybjerg-Grauholm J., Hougaard D.M., Cahn W., Kahn R.S., Cahn W., Cairns M.J., Scott R.J., Tooney P.A., Cairns M.J., Schall U., Scott R.J., Tooney P.A., Cairns M.J., Tooney P.A., Calkins M.E., Gur R.E., Gur R.C., Turetsky B.I., Carr V.J., Carr V.J., Carr V.J., Castle D., Harvey C., Castle D., Catts S.V., Catts S.V., Chan R.C., Chan R.C., Chaumette B., Kebir O., Krebs M.O., Chaumette B., Cheng W., Cheung E.F., Chong S.A., Subramaniam M., Cohen D., Consoli A., Giannitelli M., Laurent-Levinson C., Cohen D., Consoli A., Giannitelli M., Laurent-Levinson C., Cohen D., Cordeiro Q., Costas J., Curtis C., Quattrone D., Breen G., Collier D.A., Di Forti M., Vassos E., Curtis C., Mondelli V., Quattrone D., van Amelsvoort T., Di Forti M., Murray R.M., Vassos E., van Amelsvoort T., Davidson M., Davis K.L., Haroutunian V., Malaspina D., Reichenberg A., Siever L.J., Silverman J.M., Buxbaum J.D., Kahn R.S., de Haan L., de Haan L., de Haan L., de Haan L., Degenhardt F., Forstner A., Nöthen M.M., DeLisi L.E., Dickerson F., Dikeos D., Papadimitriou G.N., Dinan T., Dinan T., Djurovic S., Djurovic S., Duan J., Gejman P.V., Sanders A.R., Duan J., Gejman P.V., Sanders A.R., Ducci G., Dudbridge F., Eriksson J.G., Eriksson J.G., Eriksson J.G., Fañanás L., Fañanás L., Peñas J.G., González-Pinto A., Molto M.D., Moreno C., Parellada M., Sanjuan J., Crepo-Facorro B., Mata I., Arango C., Faraone S.V., Forstner A., Frank J., Streit F., Witt S.H., Rietschel M., Freimer N.B., Ophoff R.A., Freimer N.B., Fromer M., Stahl E.A., Frustaci A., Gershon E.S., Giegling I., Hartmann A.M., Konte B., Rujescu D., Giusti-Rodríguez P., Szatkiewicz J.P., Sullivan P.F., Godard S., González Peñas J., Moreno C., Parellada M., Arango C., González-Pinto A., Gopal S., Savitz A., Li Q.S., Gratten J., Green M.F., Nuechterlein K.H., Sugar C.A., Green M.F., Greenwood T.A., Light G.A., Swerdlow N.R., Braff D., Guillin O., Campion D., Guillin O., Campion D., Guillin O., Gülöksüz S., Luykx J.J., Rutten B.P., van Amelsvoort T., van Winkel R., van Amelsvoort T., van Winkel R., Gülöksüz S., Gutiérrez B., Hahn E., Hakonarson H., Pellegrino R., Haroutunian V., Haroutunian V., Harvey C., Pantelis C., Hayward C., Henskens F.A., Kelly B.J., Herms S., Hoffmann P., Howrigan D.P., Fromer M., Daly M.J., Ikeda M., Iwata N., Iyegbe C., van Os J., Joa I., Julià A., Marsal S., Kam-Thong T., Rautanen A., Kamatani Y., Kamatani Y., Karachanak-Yankova S., Toncheva D., Karachanak-Yankova S., Keller M.C., Khrunin A., Limborska S., Slominsky P., Kim S.W., Klovins J., Nikitina-Zake L., Kondratiev N., Golimbet V., Kraft J., Kubo M., Kučinskas V., Kučinskiene Z.A., Kusumawardhani A., Kuzelova-Ptackova H., Landi S., Lazzeroni L.C., Levinson D.F., Lazzeroni L.C., Lee P.H., Petryshen T.L., Smoller J.W., Lehrer D.S., Lerer B., Li M., Lieberman J., Stroup T.S., Light G.A., Braff D., Liu C.M., Liu C.M., Hwu H.G., Lönnqvist J., Lönnqvist J., Loughland C.M., Lubinski J., Luykx J.J., Bakker S., Kahn R., Luykx J.J., Luykx J.J., Macek M J.r., Mackinnon A., Mackinnon A., Maher B.S., Maier W., Malaspina D., Atbaşoğlu E.C., Mallet J., Marder S.R., Martin A.R., Huang H., Martorell L., Muntané G., Vilella E., Mattheisen M., Meier S., Mattheisen M., Mattheisen M., Schulze T.G., McCarley R.W., McDonald C., Donohoe G., Morris D.W., McGrath J.J., Periyasamy S., Mowry B.J., Wray N.R., McGrath J.J., Medeiros H., Sobell J.L., Medeiros H., Meier S., Melegh B., Mesholam-Gately R.I., Seidman L.J., Metspalu A., Milani L., Esko T., Michie P.T., Milanova V., Molden E., Molden E., Molina E., Molto M.D., Molto M.D., Sanjuan J., Mondelli V., Morley C.P., Muntané G., Murphy K.C., Myin-Germeys I., Nenadić I., Nenadić I., Nestadt G., Pulver A.E., O’Neill F.A., Oh S.Y., Oh S.Y., Olincy A., Freedman R., Ota V.K., Santoro M.L., Belangero S.I., Pantelis C., Pantelis C., Baune B.T., Pantelis C., Baune B.T., Paunio T., Paunio T., Periyasamy S., Mowry B.J., Perkins D.O., Sullivan P.F., Pfuhlmann B., Pietiläinen O., Hyman S.E., Pietiläinen O., Benner C., Pirinen M., Palotie A., Daly M.J., Porteous D., Powell J., Quattrone D., Di Forti M., Quested D., Quested D., Radant A.D., Tsuang D.W., Radant A.D., Tsuang D.W., Rapaport M.H., Roe C., Liu C., Roffman J.L., Moran J.L., Roth J., Gawlik M., Saker-Delye S., Salomaa V., Suvisaari J., Sanjuan J., Schall U., Scott R.J., Shi J., Siever L.J., Silverman J.M., Sigurdsson E., Sigurdsson E., Sim K., Sim K., Sim K., So H.C., So H.C., Stain H.J., Stain H.J., Steen N.E., Jönsson E.G., Stögmann E., Zimprich F., Stone W.S., Stone W.S., Straub R.E., Hyde T., Jaffe A., Weinberger D.R., Strengman E., Sugar C.A., Svrakic D.M., Cloninger C.R., Ta T.M., Ta T.M., Takahashi A., Terao C., Thibaut F., Thibaut F., Toncheva D., Tosato S., Tura G.B., Üçok A., Vaaler A., Vaaler A., van Winkel R., Veijola J., van Winkel R., Veijola J., Waddington J., Waterreus A., Morgan V.A., Waterreus A., Jablensky A.V., Morgan V.A., Weiser M., Wu J.Q., Xu Z., Yolken R., Zai C.C., Kennedy J.L., Zai C.C., Kennedy J.L., Zhu F., Zhu F., Atbaşoğlu E.C., Saka M.C., Ayub M., Black D.W., Buccola N.G., Byerley W.F., Chen W.J., Chen W.J., Crespo-Facorro B., Crespo-Facorro B., Galletly C., Galletly C., Galletly C., Gennarelli M., Gennarelli M., Hwu H.G., Mors O., Müller-Myhsok B., Müller-Myhsok B., Müller-Myhsok B., Neil A.L., Nordentoft M., Pato M.T., Pato C.N., Pato M.T., Pato C.N., Pirinen M., Pirinen M., Schulze T.G., Schulze T.G., Schulze T.G., Stahl E.A., Esko T., Stahl E.A., Wang S.H., Xu S., Xu S., Xu S., Adolfsson R., Bramon E., Cervilla J.A., Cichon S., Cichon S., Cichon S., Collier D.A., Collier D.A., Corvin A., Gill M., Curtis D., Curtis D., Domenici E., Escott-Price V., Fanous A.H., Fanous A.H., Gareeva A., Khusnutdinova E., Gareeva A., Gareeva A., Khusnutdinova E., Gareeva A., Glatt S.J., Hong K.S., Knowles J.A., Knowles J.A., Lee J., Lee J., Lencz T., Malhotra A.K., Lencz T., Malhotra A.K., Liu J., Liu J., Malhotra D., Menezes P.R., Nimgaonkar V., Ophoff R.A., Ophoff R.A., Paciga S.A., Palotie A., Palotie A., Ripke S., Qin S., Rivera M., Rivera M., Schwab S.G., Schwab S.G., Serretti A., Sham P.C., Sham P.C., Sham P.C., Sham P.C., Sham P.C., Sham P.C., Clair D.S., Tsuang M.T., Tsuang M.T., van Os J., Vawter M.P., Werge T., Werge T., Clair D.S., Werge T., Werge T., van Os J., Wildenauer D.B., van Os J., Yu X., Yue W., Yu X., Yue W., Yue W., Roussos P., Vassos E., Verhage M., Koopmans F., Sahasrabudhe D., Toonen R.F., Verhage M., Verhage M., Posthuma D., Yang J., Dai N., Wenwen Q., Wildenauer D.B., Dai N., Wenwen Q., Wildenauer D.B., Agiananda F., Amir N., Antoni R., Arsianti T., Asmarahadi A., Diatri H., Djatmiko P., Irmansyah I., Khalimah S., Kusumadewi I., Kusumaningrum P., Lukman P.R., Nasrun M.W., Safyuni N.S., Prasetyawan P., Semen G., Siste K., Tobing H., Widiasih N., Wiguna T., Wulandari D., Evalina N., Hananto A.J., Ismoyo J.H., Marini T.M., Henuhili S., Reza M., Yusnadewi S., Abyzov A., Akbarian S., van Bakel H., Breen M., Charney A., Dracheva S., Girdhar K., Hoffman G., Jiang Y., Pinto D., Purcell S., Roussos P., Wiseman J., Ashley-Koch A., Crawford G., Reddy T., Brown M., Grennan K., Bryois J., Carlyle B., Emani P., Galeev T., Gerstein M., Gu M., Guerra B., Gursoy G., Kitchen R., Lee D., Li M., Liu S., Navarro F., Pan X., Pochareddy S., Rozowsky J., Sestan N., Sethi A., Shi X., Szekely A., Wang D., Warrell J., Weissman S., Wu F., Xu X., Coetzee G., Farnham P., Lay F., Rhie S., Witt H., Wood S., Yao L., Gandal M., Polioudakis D., Swarup V., Won H., Giase G., Jiang S., Kefi A., Shieh A., Goes F., Zandi P., Kim Y., Knowles J.A., Mattei E., Purcaro M., Pratt H., Peters M.A., Sanders S., Weng Z., White K., Arranz M.J., Bramon E., Iyegbe C., Lewis C., Lin K., Murray R.M., Powell J., Walshe M., Arranz M.J., Bender S., Bender S., Weisbrod M., Bramon E., Crepo-Facorro B., Mata I., Hall J., Lawrie S., McIntosh A., Linszen D.H., Ophoff R.A., van Os J., van Os J., Rujescu D., Rujescu D., Achsel T., Bagni C., Andres-Alonso M., Kreutz M.R., Bayés À., Biederer T., Brose N., Chua J.J., Coba M.P., Cornelisse L.N., van Weering J.R., de Jong A.P., MacGillavry H.D., de Juan-Sanz J., Dieterich D.C., Pielot R., Smalla K.H., Dieterich D.C., Gundelfinger E.D., Pielot R., Smalla K.H., Feng G., Goldschmidt H.L., Huganir R.L., Hoogenraad C., Hyman S.E., Imig C., Jahn R., Jung H., Kim E., Kaeser P.S., Lipstein N., Malenka R., McPherson P.S., O’Connor V., Ryan T.A., Sala C., Verpelli C., Smit A.B., Südhof T.C, & Thomas P.D. (2022). Mapping genomic loci implicates genes and synaptic biology in schizophrenia. Nature, 604(7906), 502-508.
Publication 2022
Adult BLOOD Brain Care, Prenatal Gene Expression Genes Genes, vif Genome Genome-Wide Association Study Multiple Birth Offspring Prefrontal Cortex Schizophrenia Single Nucleotide Polymorphism Tissues
4
Mapping Genetic Variants to Brain Traits
Parameters were set as described above and eQTLs in 10 brain tissues from GTEx. Chromatin interaction mapping was performed using Hi-C data of two brain regions; hippocampus and prefrontal cortex. The extended MHC region (25–34 Mb), Chromosome X and indels were excluded from this analysis. The input GWAS summary statistics are based on the discovery phase and not all reported lead SNPs from the combined results of discovery and replication phases reached genome-wide significance. To include all reported lead SNPs, 111 non-indel lead SNPs were provided to FUMA and additional independent lead SNPs were identified at P < 5e-8 (Supplementary Data 14). Only protein-coding genes were used in mappings and enrichment of DEG in 53 tissue types, Canonical Pathways and GO terms were tested.
Watanabe K., Taskesen E., van Bochoven A, & Posthuma D. (2017). Functional mapping and annotation of genetic associations with FUMA. Nature Communications, 8, 1826.
Full text: Click here
Publication 2017
Brain Chromatin DNA Replication Gene Products, Protein Genome Genome-Wide Association Study Histocompatibility Testing INDEL Mutation Prefrontal Cortex Seahorses Single Nucleotide Polymorphism Tissues X Chromosome
5
Behavioural and Molecular Neuroscience Protocols
Behavioural studies were performed using adult male wild type C57BL/6 or mutant strains maintained as previously described10 (link),15 (link). All drugs utilized were administered via intraperitonteal injection. Antidepressant-like behaviour was assessed using the forced swim test as previously described4 (link). Briefly, animals were placed in a cylinder of water (22-24° C) for 6 minutes and immobility was measured during the last 4 minutes of the test. Molecular studies consisted of Western blotting analysis or QPCR performed on whole cell lysates from medial prefrontal cortex or anterior HC. Electrophysiological studies were performed as previously described in cultured neurons (whole cell recordings23 (link)) or hippocampal slices (field recordings10 (link)).
Autry A.E., Adachi M., Nosyreva E., Na E.S., Los M.F., Cheng P.F., Kavalali E.T, & Monteggia L.M. (2011). NMDA Receptor Blockade at Rest Triggers Rapid Behavioural Antidepressant Responses. Nature, 475(7354), 91-95.
Publication 2011
Adult Animals Antidepressive Agents Cells Electrophysiologic Study, Cardiac Males Neurons Pharmaceutical Preparations Prefrontal Cortex Strains Western Blot

Most recents protocols related to «Prefrontal Cortex»

1
Western Blot Analysis of Brain Proteins
After the mice were euthanized, the prefrontal cortex (PFC) and hippocampus (HIP) of each mouse were separated and collected immediately on ice. Then, the total proteins were extracted by homogenization using lysis buffer (RIPA, P0013K, Beyotime, Shanghai, China). Protein extracts were separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and then transferred onto a polyvinylidene fluoride (PVDF) membrane. Then, the PVDF membranes were incubated with the corresponding specific antibodies for NF-κB, COX-2, NLRP3, nuclear factor erythroid 2-related factor (Nrf2), heme oxygenase-1 (HO-1), GAPDH, and β-actin overnight at 4°C, followed by incubation with either HRP-labeled Goat Anti-Rabbit IgG (H + L) or HRP-labeled Goat Anti-Mouse IgG (H + L) for 2 h at room temperature. Images of the resulting bands were obtained after ECL (P0018S, Beyotime, Shanghai, China) and developed by the Amersham imager 680 (General Electric Company, Boston, United States). The band intensities were normalized to β-actin or GAPDH. Information on the antibodies utilized in this study is provided in Supplementary Table S3.
Hou L., Yang L., Zhu C., Miao J., Zhou W., Tang Y., Meng H, & Liu S. (2023). Cuscutae semen alleviates CUS-induced depression-like behaviors in mice via the gut microbiota-neuroinflammation axis. Frontiers in Pharmacology, 14, 1107781.
Full text: Click here
Publication 2023
Actins anti-IgG Antibodies Buffers Electricity GAPDH protein, human Goat HMOX1 protein, human Mus NFE2L2 protein, human polyvinylidene fluoride Prefrontal Cortex Proteins PTGS2 protein, human Rabbits Radioimmunoprecipitation Assay RELA protein, human SDS-PAGE Seahorses Tissue, Membrane
2
Quantification of PLP/DM20 and MBP Levels
Prefrontal cortex (frontal to bregma 5.22) and cerebellum were dissected from mice and homogenized in 1× TBS with protease inhibitor (Complete Mini, Roche). Protein concentration was measured using the DC protein assay (Bio-Rad). Immunoblotting displayed in Figure 1C and D was essentially as described (Kusch et al., 2017 (link); Schardt et al., 2009 (link)). Briefly, lysates from prefrontal cortex (3.2 µg for PLP/DM20 and 1 µg for actin) and cerebellum (0.8 µg for PLP/DM20 and 1 µg for actin) were separated on 15% SDS-polyacrylamide gels and blotted onto PVDF membranes (Hybond, Amersham) using the Novex Semi-Dry Blotter (Invitrogen). Primary antibodies were incubated in 5% milk powder in TBST over night at 4°C. Primary antibodies were specific for PLP/DM20 (A431; 1:5000; Jung et al., 1996 (link)), MBP (1:500; DAKO), and actin (1:1000 for cerebellum, 1:5000 for prefrontal cortex; Sigma). Secondary HRP-coupled antibodies (dianova) were detected using the ChemoCam system (Intas).
Arinrad S., Depp C., Siems S.B., Sasmita A.O., Eichel M.A., Ronnenberg A., Hammerschmidt K., Lüders K.A., Werner H.B., Ehrenreich H, & Nave K.A. (2023). Isolated catatonia-like executive dysfunction in mice with forebrain-specific loss of myelin integrity. eLife, 12, e70792.
Full text: Click here
Publication 2023
Actins Antibodies Biological Assay Cerebellum Milk, Cow's Mus polyacrylamide gels polyvinylidene fluoride Powder Prefrontal Cortex Protease Inhibitors Proteins Tissue, Membrane
3
Pain-related Brain Regions Analysis
Data from ten pain-related brain regions of interest were selected for analysis. These included the left and right frontal, insula, cingulum anterior, postcentral, and thalamus (see Figure 1A), which are involved in the processing of sensory-discriminative (e.g., location and intensity), cognitive-evaluative, and affective-emotional aspects of nociception and pain (Bushnell et al., 2013 (link); Kuner and Kuner, 2021 (link); Mercer Lindsay et al., 2021 (link)). These ROIs were selected because metabolite alterations in these regions have been consistently observed in chronic pain conditions (Ito et al., 2017 (link); Levins et al., 2019 (link); Peek et al., 2020 (link); Cruz-Almeida and Porges, 2021 (link)), including neuropathic pain (Chang et al., 2013 (link); Widerström-Noga et al., 2015 (link)). The frontal region, which includes the prefrontal cortex, has been implicated in attentional and evaluative processes of pain (Bushnell et al., 2013 (link); Kuner and Kuner, 2021 (link); Tan and Kuner, 2021 (link)). The insula has been implicated in coding pain intensity (Garcia-Larrea et al., 2010 (link); Garcia-Larrea and Peyron, 2013 (link)). The anterior cingulate cortex (ACC) and cingulum are components of the limbic system, thought to be involved in the affective-emotional components of the pain experience (Bushnell et al., 2013 (link); Kuner and Kuner, 2021 (link); Tan and Kuner, 2021 (link)). The postcentral gyrus or primary somatosensory cortex is commonly activated during induced pain and implicated in the sensory-discriminative (e.g., location and intensity) components of pain (Apkarian et al., 2005 (link); Kuner and Kuner, 2021 (link); Tan and Kuner, 2021 (link)). Lastly, the thalamus is the primary relay station for sensory information, communicates with the cortex and is also be involved in pain modulation (Apkarian et al., 2005 (link)).
Robayo L.E., Govind V., Salan T., Cherup N.P., Sheriff S., Maudsley A.A, & Widerström-Noga E. (2023). Neurometabolite alterations in traumatic brain injury and associations with chronic pain. Frontiers in Neuroscience, 17, 1125128.
Full text: Click here
Publication 2023
Attention Brain Cognition Cortex, Cerebral Discrimination, Psychology Emotions Gyrus, Anterior Cingulate Insula of Reil Larrea Limbic System Lobe, Frontal Neuralgia Nociception Pain Pain Disorder polyetheretherketone Postcentral Gyrus Prefrontal Cortex Process Assessment, Health Care Severity, Pain Somatosensory Cortex, Primary Thalamus
4
DBS-Mediated Hippocampal and Amygdalar Modulation
All surgical procedures were performed under urethane (1.5 g/kg; Sigma-Aldrich/Merck, Barcelona, Spain) anesthesia. To record the local field potentials, custom-made Teflon-coated stainless steel recording electrodes (AM Systems, Sequim, WA, USA) were implanted, according to the stereotactic coordinates from Bregma (Paxinos and Watson, 2007 ), in the dorsal hippocampus (HPCd) (AP −3.4 mm; L 2.5 mm; DV 2.4 mm), intermediate hippocampus (HPCi) (AP −5.8 mm; L 5.8 mm; DV 5 mm), ventral hippocampus (HPCv) (AP −4.7 mm; L 5 mm; DV 8.7 mm), and basolateral amygdala (BLA) (AP −2.3 mm; L 5 mm; DV 8.5 mm). For DBS, we used in-house custom-made bipolar twisted electrodes made of Teflon-coated stainless-steel wire, with 1 mm between both tips. Stimulating electrodes were bilaterally implanted into the infralimbic (IL) region of the medial prefrontal cortex (coordinates: AP +3.2 mm; L 0.5 mm; DV 5.4 mm).
The surgical procedures used in the study of the electrophysiological activity are the same as for the analysis of c-Fos expression. However, in the case of the immunoreactivity study, only the DBS stimulation electrode in IL was implanted to preserve an optimal state in the other regions of interest. Figure 1 illustrates the experimental setup and the stimulation sites.
Vila-Merkle H., González-Martínez A., Campos-Jiménez R., Martínez-Ricós J., Teruel-Martí V., Lloret A., Blasco-Serra A, & Cervera-Ferri A. (2023). Sex differences in amygdalohippocampal oscillations and neuronal activation in a rodent anxiety model and in response to infralimbic deep brain stimulation. Frontiers in Behavioral Neuroscience, 17, 1122163.
Full text: Click here
Publication 2023
Anesthesia Electrophysiologic Study, Cardiac Nuclear Groups, Basolateral Operative Surgical Procedures Prefrontal Cortex Seahorses Stainless Steel Teflon Urethane
5
Mapping Melanocortin Receptor Neurons
Subjects were injected with a lethal dose of sodium pentobarbital (Beuthanasia-D, 0.25 ml i.p., Schering, Union, NJ, United States) and sacrificed by rapid decapitation. Brains were extracted, frozen in optimum cutting temperature compound (VWR Scientific Products) and stored at −80°C. Brains were later sliced coronally on a cryostat at 14 μm thickness and sections were mounted on Colorfrost Plus slides (Fisher Scientific, Waltham, MA, United States). Some studies in rats and mice have provided an extensive analysis of range of the distribution of melanocortin receptor expressing neurons. Here, we limited our focus to the forebrain and midbrain with tissue collected from slices containing the prefrontal cortex through to slices containing the dorsal raphe nucleus. Slides were stored at −80°C until RNAscope procedure treatment.
Hall M.A., Kohut-Jackson A.L., Peyla A.C., Friedman G.D., Simco N.J., Borland J.M, & Meisel R.L. (2023). Melanocortin receptor 3 and 4 mRNA expression in the adult female Syrian hamster brain. Frontiers in Molecular Neuroscience, 16, 1038341.
Full text: Click here
Publication 2023
Beuthanasia Brain Decapitation Freezing Melanocortin Receptor Mesencephalon Mice, Laboratory Neurons Pentobarbital Sodium Prefrontal Cortex Prosencephalon Raphe, Dorsal Nucleus Rattus Tissues

Top products related to «Prefrontal Cortex»

1
Trizol reagent by Thermo Fisher Scientific
Sourced in United States, China, Japan, Germany, United Kingdom, Canada, France, Italy, Australia, Spain, Switzerland, Netherlands, Belgium, Lithuania, Denmark, Singapore, New Zealand, India, Brazil, Argentina, Sweden, Norway, Austria, Poland, Finland, Israel, Hong Kong, Cameroon, Sao Tome and Principe, Macao, Taiwan, Province of China, Thailand
TRIzol reagent is a monophasic solution of phenol, guanidine isothiocyanate, and other proprietary components designed for the isolation of total RNA, DNA, and proteins from a variety of biological samples. The reagent maintains the integrity of the RNA while disrupting cells and dissolving cell components.
2
Rneasy mini kit by Qiagen
Sourced in Germany, United States, United Kingdom, Netherlands, Spain, Japan, Canada, France, China, Australia, Italy, Switzerland, Sweden, Belgium, Denmark, India, Jamaica, Singapore, Poland, Lithuania, Brazil, New Zealand, Austria, Hong Kong, Portugal, Romania, Cameroon, Norway
The RNeasy Mini Kit is a laboratory equipment designed for the purification of total RNA from a variety of sample types, including animal cells, tissues, and other biological materials. The kit utilizes a silica-based membrane technology to selectively bind and isolate RNA molecules, allowing for efficient extraction and recovery of high-quality RNA.
3
Trizol by Thermo Fisher Scientific
Sourced in United States, Germany, China, Japan, United Kingdom, Canada, France, Italy, Australia, Spain, Switzerland, Belgium, Denmark, Netherlands, India, Ireland, Lithuania, Singapore, Sweden, Norway, Austria, Brazil, Argentina, Hungary, Sao Tome and Principe, New Zealand, Hong Kong, Cameroon, Philippines
TRIzol is a monophasic solution of phenol and guanidine isothiocyanate that is used for the isolation of total RNA from various biological samples. It is a reagent designed to facilitate the disruption of cells and the subsequent isolation of RNA.
4
High capacity cdna reverse transcription kit by Thermo Fisher Scientific
Sourced in United States, Germany, United Kingdom, Japan, Lithuania, France, Italy, China, Spain, Canada, Switzerland, Poland, Australia, Belgium, Denmark, Sweden, Hungary, Austria, Ireland, Netherlands, Brazil, Macao, Israel, Singapore, Egypt, Morocco, Palestine, State of, Slovakia
The High-Capacity cDNA Reverse Transcription Kit is a laboratory tool used to convert RNA into complementary DNA (cDNA) molecules. It provides a reliable and efficient method for performing reverse transcription, a fundamental step in various molecular biology applications.
5
Matlab by MathWorks
Sourced in United States, United Kingdom, Germany, Canada, Japan, Sweden, Austria, Morocco, Switzerland, Australia, Belgium, Italy, Netherlands, China, France, Denmark, Norway, Hungary, Malaysia, Israel, Finland, Spain
MATLAB is a high-performance programming language and numerical computing environment used for scientific and engineering calculations, data analysis, and visualization. It provides a comprehensive set of tools for solving complex mathematical and computational problems.
6
Nanodrop by Thermo Fisher Scientific
Sourced in United States, Germany, United Kingdom, China, France, Japan, Canada, Italy, Belgium, Australia, Denmark, Spain, Sweden, India, Finland, Switzerland, Poland, Austria, Brazil, Singapore, Portugal, Macao, Netherlands, Taiwan, Province of China, Ireland, Lithuania
The NanoDrop is a spectrophotometer designed for the quantification and analysis of small volume samples. It measures the absorbance of a sample and provides accurate results for DNA, RNA, and protein concentration measurements.
7
Agilent 2100 bioanalyzer by Agilent Technologies
Sourced in United States, Germany, Canada, China, France, United Kingdom, Japan, Netherlands, Italy, Spain, Australia, Belgium, Denmark, Switzerland, Singapore, Sweden, Ireland, Lithuania, Austria, Poland, Morocco, Hong Kong, India
The Agilent 2100 Bioanalyzer is a lab instrument that provides automated analysis of DNA, RNA, and protein samples. It uses microfluidic technology to separate and detect these biomolecules with high sensitivity and resolution.
8
Rnalater by Thermo Fisher Scientific
Sourced in United States, United Kingdom, Germany, Japan, Lithuania, Italy, Australia, Canada, Denmark, China, New Zealand, Spain, Belgium, France, Sweden, Switzerland, Brazil, Austria, Ireland, India, Netherlands, Portugal, Jamaica
RNAlater is a RNA stabilization solution developed by Thermo Fisher Scientific. It is designed to protect RNA from degradation during sample collection, storage, and transportation. RNAlater stabilizes the RNA in tissues and cells, allowing for efficient RNA extraction and analysis.
9
Cryostat by Leica
Sourced in Germany, United States, Japan, United Kingdom, France, Australia, Canada, Denmark, Italy, Singapore, Switzerland, Israel
The Cryostat is a specialized piece of laboratory equipment used for the sectioning of frozen tissue samples. It maintains a controlled low-temperature environment, enabling the precise and consistent cutting of delicate specimens for microscopic analysis and examination.
10
Protease inhibitor cocktail by Merck Group
Sourced in United States, Germany, China, United Kingdom, Italy, Japan, Sao Tome and Principe, France, Canada, Macao, Switzerland, Spain, Australia, Israel, Hungary, Ireland, Denmark, Brazil, Poland, India, Mexico, Senegal, Netherlands, Singapore
The Protease Inhibitor Cocktail is a laboratory product designed to inhibit the activity of proteases, which are enzymes that can degrade proteins. It is a combination of various chemical compounds that work to prevent the breakdown of proteins in biological samples, allowing for more accurate analysis and preservation of protein integrity.

More about "Prefrontal Cortex"

The Prefrontal Cortex (PFC) is a crucial region of the brain, known for its involvement in a wide range of cognitive functions.
Situated in the anterior part of the frontal lobe, the PFC plays a critical role in decision-making, problem-solving, and emotional regulation, making it a key area of study in the field of neuropsychiatry.
Researchers investigating the PFC often utilize a variety of techniques and tools to gain a deeper understanding of its structure, function, and clinical relevance.
For example, TRIzol reagent and the RNeasy Mini Kit are commonly used for RNA extraction and purification, while the High-Capacity cDNA Reverse Transcription Kit is employed for complementary DNA (cDNA) synthesis.
Additionally, MATLAB, a powerful software for data analysis and visualization, is frequently utilized in PFC research.
The NanoDrop and Agilent 2100 Bioanalyzer are valuable instruments for assessing the quantity and quality of RNA samples, respectively.
RNAlater, a RNA stabilization solution, helps preserve the integrity of RNA samples, while cryostats are used for sectioning brain tissue for subsequent analysis.
To ensure the accuracy and reproducibility of their studies, researchers may also employ protease inhibitor cocktails to prevent the degradation of proteins during sample preparation.
By leveraging these advanced techniques and tools, scientists can enhance our understanding of the PFC's role in cognitive processes and its involvement in neuropsychiatric disorders.
PubCompare.ai, an AI-driven platform, can further optimize PFC research by providing access to a wealth of protocols, pre-prints, and patents, while offering insightful comparisons to identify the best methods and products.