Definition and research guide
This page combines a MeSH definition, publication statistics and selected research abstracts. It is a starting point for reading the literature, not a medical textbook or a systematic evidence review.
Content available: 3 complete abstracts (559 words), 9 references. Full article text is not stored or reproduced here; follow the PMID, DOI or PMC links to read the original sources and their access terms.
Definition
The main information-processing organs of the nervous system, consisting of the brain, spinal cord, and meninges.
Definition: NLM Medical Subject Headings (MeSH) scope note (Public domain (U.S. National Library of Medicine); attribution requested). View the MeSH record.
Also known as: Central Nervous Systems; Nervous System, Central; Nervous Systems, Central; Systems, Central Nervous; Cerebrospinal Axis; Axi, Cerebrospinal; Axis, Cerebrospinal; Cerebrospinal Axi.
Where it fits in the MeSH classification
- Broader topics
- Nervous System
- Narrower topics
- Brain; Meninges; Spinal Cord
Research landscape
PubMed indexes 1,576,449 records tagged with the MeSH heading “Central Nervous System” (counts retrieved 2026-10-29). 253,021 of them (16.1%) were published from 2020 onward, and the busiest period so far is through 1999 with 615,859 records.
Reviews account for 166,117 records (10.5%) and meta-analyses for 5,050. Randomized controlled trials number 14,184 (0.9%) as a share of all records on the topic. Randomized trials make up only a small share of this literature, so much of what is known comes from laboratory, observational or descriptive work.
Show the data
| Period | Records |
|---|---|
| through 1999 | 615,859 |
| 2000-2009 | 312,380 |
| 2010-2019 | 395,189 |
| 2020 onward | 253,021 |
Publication-type chart data
| Type | Records | Share |
|---|---|---|
| Reviews | 166,117 | 10.5% |
| Meta-analyses | 5,050 | 0.3% |
| Randomized controlled trials | 14,184 | 0.9% |
Method: PubMed query "Central Nervous System"[MeSH Terms] with publication-type and date filters, retrieved 2026-10-29.
Reading the evidence in neuroscience
Neuroscience draws on tools with different strengths: cellular and animal work can manipulate circuits directly, while human imaging and electrophysiology observe the living brain at lower resolution. Small imaging studies are prone to false positives, and findings in animals do not always carry over to people. Clinical neurology and psychiatry rely on trials and cohort studies whose outcomes are often symptom scales. Check the species, the sample size, how the outcome was measured and whether results were replicated.
Evidence from open-access studies
These open-access studies come from PubMed’s best-match results for this heading (papers whose main topic it is), ranked here by citation count, with one recent addition. Each abstract is reproduced in full under its recorded open licence so that you can read the authors’ own words. They illustrate the literature; they are not a systematic summary of it. Citation counts measure attention, not reliability or clinical benefit.
| Study / authors | Year | Source label / design | Europe PMC citations | Licence / source |
|---|---|---|---|---|
| Osteoporosis and Alzheimer's Disease: The Role of Sclerostin | 2026 | Review article Design not recorded in structured metadata | 0 | cc by PMID 42905237 · DOI · PMC13687117 |
| Central Nervous System Reservoirs and HIV Cure: Therapeutic Opportunities and Challenges | 2026 | Review article Design not recorded in structured metadata | 0 | cc by PMID 42891909 · DOI · PMC13676512 |
| Insulin resistance and brain sulcal morphology in non-diabetic adults | 2026 | Research article Design not recorded in structured metadata | 0 | cc by PMID 42903296 · DOI · PMC13681054 |
Osteoporosis and Alzheimer's Disease: The Role of Sclerostin [1]
Abstract reading summary — source excerpts
- Opening excerpt
- Purpose of reviewLittle is known about the underlying cause contributing to the association between Osteoporosis (OP) and Alzheimer's disease (AD).
- Closing excerpt
- Future longitudinal and interventional studies are essential to confirm the association between sclerostin and risk of AD, and to clarify whether targeting sclerostin can delay the onset of the disease or modify its trajectory.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (172 words)
Purpose of reviewLittle is known about the underlying cause contributing to the association between Osteoporosis (OP) and Alzheimer's disease (AD). This review highlights the emerging role of sclerostin, a protein mainly produced by osteocytes, in the newly discovered crosstalk between bone and brain, with a focus on its potential contribution to the relationship between OP and AD.Recent findingsCirculating sclerostin levels increase with aging and are positively associated with brain amyloid-β burden in older adults. Studies demonstrate that elevated sclerostin can cross the blood-brain barrier, promote amyloid-β peptide deposition, and impair synaptic plasticity by suppressing Wnt/β-catenin signalling, whereas sclerostin inhibition restores neuronal plasticity and attenuates AD pathology. Sclerostin represents a promising target in the bone-brain interaction pathway. Its dual role as a measurable circulating biomarker and a modifiable component offers new opportunities for early risk assessment and therapeutic repurposing. Future longitudinal and interventional studies are essential to confirm the association between sclerostin and risk of AD, and to clarify whether targeting sclerostin can delay the onset of the disease or modify its trajectory.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 42905237 · DOI · PMC13687117
Central Nervous System Reservoirs and HIV Cure: Therapeutic Opportunities and Challenges [2]
Abstract reading summary — source excerpts
- Opening excerpt
- Purpose of reviewDespite viral suppression with antiretroviral therapy, people with HIV (PWH) remain at increased risk of neurocognitive impairment, neuroinflammation, and potential viral rebound following therapy interruption.
- Closing excerpt
- Developing CNS-inclusive strategies that minimise adverse neurological effects may be an important step in achieving HIV cure.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (143 words)
Purpose of reviewDespite viral suppression with antiretroviral therapy, people with HIV (PWH) remain at increased risk of neurocognitive impairment, neuroinflammation, and potential viral rebound following therapy interruption. Although the central nervous system (CNS) is a recognised HIV reservoir, it is often not fully considered in cure approaches.Recent findingsHIV DNA and ongoing viral transcription persist in the CNS of ART-suppressed PWH, potentially contributing to neuroinflammation and neurocognitive dysfunction. HIV cure strategies, including latency-reversing/promoting agents, broadly neutralising antibodies and other approaches have varying degrees of CNS penetration, efficacy and potential neurotoxicity. Therefore, interventions aimed at silencing or eradicating HIV reservoirs require monitoring of both reservoir-targeting efficacy and neurological adverse effects. Greater consideration of CNS penetration, efficacy in targeting CNS reservoirs, and neurotoxicity is required in HIV cure studies. Developing CNS-inclusive strategies that minimise adverse neurological effects may be an important step in achieving HIV cure.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 42891909 · DOI · PMC13676512
Insulin resistance and brain sulcal morphology in non-diabetic adults [3]
Abstract reading summary — source excerpts
- Opening excerpt
- Insulin resistance exerts direct effects on brain structure, yet most neuroimaging evidence comes from populations with established diabetes, and conventional gray matter volumetry may lack sensitivity to detect early structural changes.
- Closing excerpt
- These findings suggest that sulcal morphology can detect metabolic effects on brain structure at a pre-diabetic stage, changes that were not apparent through frontal gray matter volumetry in the same sample, and identify insulin resistance as a potential modifiable target for preserving brain health.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (244 words)
Insulin resistance exerts direct effects on brain structure, yet most neuroimaging evidence comes from populations with established diabetes, and conventional gray matter volumetry may lack sensitivity to detect early structural changes. Here, we examined associations between insulin resistance and sulcal morphology, a measure that integrates cortical thinning, subcortical atrophy, and white matter degeneration into a single outcome, in 728 non-diabetic adults (518 men, 210 women; mean age 61.4 ± 11.6 years). Brain volumes were quantified using OpenMAP-T1, an automated deep learning-based parcellation tool, and associations between HOMA-IR and 30 cerebrospinal fluid-related regional volumes were examined using multiple linear regression adjusted for age, sex, and estimated total intracranial volume, with FDR correction for multiple comparisons. Higher HOMA-IR was significantly associated with greater frontal sulcal volumes (left: β = 596 mm³, right: β = 344 mm³; both FDR-corrected p < 0.001), with a dose-response relationship across insulin resistance categories. This association was observed only in men (sex × HOMA-IR interaction p = 0.019) and was strongest in participants younger than 70 years. Mediation analysis revealed that the relationship between BMI and frontal sulcal enlargement was largely accounted for by the indirect pathway through insulin resistance, with no significant direct effect of BMI. These findings suggest that sulcal morphology can detect metabolic effects on brain structure at a pre-diabetic stage, changes that were not apparent through frontal gray matter volumetry in the same sample, and identify insulin resistance as a potential modifiable target for preserving brain health.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 42903296 · DOI · PMC13681054
Key reviews and meta-analyses
The most cited review-type papers among PubMed’s best-match results for this heading, listed with bibliographic details only. Follow the links for the full text and access terms.
- Research article Is criticality a unified setpoint of brain function? [4]
- Research article The 'reading' brain: Meta-analytic insight into functional activation during reading in adults [5]
- Research article Peri-ictal imaging abnormalities in non-convulsive status epilepticus: A systematic review and meta-analysis comparing magnetic resonance imaging and computed tomography perfusion [6]
- Research article Linguistic and emotional prosody: A systematic review and ALE meta-analysis [7]
- Research article Joint and distinct neural structure and function deficits in major depressive disorder with suicidality: a multimodal meta-analysis of MRI studies [8]
- Research article Shared and Distinct Alterations in Brain Structure of Youth With Internalizing or Externalizing Disorders: Findings From the ENIGMA Antisocial Behavior, ADHD, Major Depressive Disorder, and Anxiety Working Groups [9]
References
- Gagiano L, Chen Z, Blakeney WG, Jones C, Mastaglia F, Zheng M, et al.. Osteoporosis and Alzheimer's Disease: The Role of Sclerostin. . 2026. PMID 42905237 · DOI · PMC13687117
- Angelovich TA, Roche M, Gorry PR, Churchill MJ. Central Nervous System Reservoirs and HIV Cure: Therapeutic Opportunities and Challenges. . 2026. PMID 42891909 · DOI · PMC13676512
- Yoshimaru D, Yuzawa A, Ozawa M, Hirabayashi M, Matsushita Y, Tsurugizawa T, et al.. Insulin resistance and brain sulcal morphology in non-diabetic adults. . 2026. PMID 42903296 · DOI · PMC13681054
- Hengen KB, Shew WL. Is criticality a unified setpoint of brain function?. Neuron. 2025. PMID 40555236 · DOI · PMC12374783
- Turker S, Fumagalli B, Kuhnke P, Hartwigsen G. The 'reading' brain: Meta-analytic insight into functional activation during reading in adults. Neurosci Biobehav Rev. 2025. PMID 40254114 · DOI
- Bosque-Varela P, Kuchukhidze G, Hahn W, Jünemann C, Machegger L, Möller L, et al.. Peri-ictal imaging abnormalities in non-convulsive status epilepticus: A systematic review and meta-analysis comparing magnetic resonance imaging and computed tomography perfusion. Epilepsia. 2025. PMID 40827398 · DOI · PMC12779322
- Themistocleous C. Linguistic and emotional prosody: A systematic review and ALE meta-analysis. Neurosci Biobehav Rev. 2025. PMID 40379231 · DOI
- Lin S, Chen Z, Zhao Y, Gong Q. Joint and distinct neural structure and function deficits in major depressive disorder with suicidality: a multimodal meta-analysis of MRI studies. J Psychiatry Neurosci. 2025. PMID 40268326 · DOI · PMC12029312
- Sophie Townend, Staginnus M, Gao Y, Alexander N, Arolt V, Banaschewski T, et al.. Shared and Distinct Alterations in Brain Structure of Youth With Internalizing or Externalizing Disorders: Findings From the ENIGMA Antisocial Behavior, ADHD, Major Depressive Disorder, and Anxiety Working Groups. Biol Psychiatry. 2026. PMID 40812743 · DOI
About this article
- Sources
- NLM Medical Subject Headings (definition, synonyms); NCBI PubMed (counts, identifiers); Europe PMC (open-access abstracts and citation counts).
- Verification
- Every reference was resolved against PubMed on 2026-10-31; title, year and DOI matched.
- Review state
- automated source verified; no human expert review has been recorded yet.
- Version
- 1, last updated 2026-10-29.
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Evidence strength
EvidenceHelix's computed view of the study designs behind this topic: how common meta-analyses, randomized trials and reviews are, how recent the literature is, and a plain-language reading. It describes the design mix of the literature. It is not a quality appraisal of any study, and it is not medical advice.