Evidence map›Paper›PMID 34561609›Full record

ReviewMolecular psychiatry2022

Emerging strategies for the genetic dissection of gene functions, cell types, and neural circuits in the mammalian brain.

Ling Gong, Xue Liu, Jinyun Wu, Miao He

Abstract readReview
PubMed Publisher
In one paragraph

Review in Molecular psychiatry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Ling Gong *Department of Neurology, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science and Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Xue Liu *Department of Neurology, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science and Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Jinyun WuDepartment of Neurology, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science and Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Miao HeDepartment of Neurology, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science and Zhongshan Hospital, Fudan University, Shanghai, 200032, China. hem@fudan.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The mammalian brain is composed of a large number of highly diverse cell types with different molecular, anatomical, and functional features. Distinct cellular identities are generated during development under the regulation of intricate genetic programs and manifested through unique combinations of gene expression. Recent advancements in our understanding of the molecular and cellular mechanisms underlying the assembly, function, and pathology of the brain circuitry depend on the invention and application of genetic strategies that engage intrinsic gene regulatory mechanisms. Here we review the strategies for gene regulation on DNA, RNA, and protein levels and their applications in cell type targeting and neural circuit dissection. We highlight newly emerged strategies and emphasize the importance of combinatorial approaches. We also discuss the potential caveats and pitfalls in current methods and suggest future prospects to improve their comprehensiveness and versatility.

Indexed as

BrainNeuronsAnimalsGene Expression RegulationMammals

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.