Evidence map›Paper›PMID 26508863›Full record

ReviewNeuropsychiatric disease and treatment2015

Neurobehavioral burden of multiple sclerosis with nanotheranostics.

Bhasker Sriramoju, Rupinder K Kanwar, Jagat R Kanwar

Open access · goldAbstract readReview
In one paragraph

Review in Neuropsychiatric disease and treatment, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.9field-weighted citation impact, top 26% of its field
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

0 citing papers in PubMed, 6 citations in OpenAlex.

No citing paper in PubMed yet.

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

3 authors at 1 institution in 1 country.

Bhasker SriramojuNanomedicine-Laboratory of Immunology and Molecular Biomedical Research (NLIMBR), School of Medicine, Molecular and Medical Research, Faculty of Health, Deakin University, VIC, Australia.
Rupinder K KanwarNanomedicine-Laboratory of Immunology and Molecular Biomedical Research (NLIMBR), School of Medicine, Molecular and Medical Research, Faculty of Health, Deakin University, VIC, Australia.
Jagat R KanwarNanomedicine-Laboratory of Immunology and Molecular Biomedical Research (NLIMBR), School of Medicine, Molecular and Medical Research, Faculty of Health, Deakin University, VIC, Australia.
Deakin University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multiple sclerosis (MS) is a chronic demyelinating neurological disorder affecting people worldwide; women are affected more than men. MS results in serious neurological deficits along with behavioral compromise, the mechanisms of which still remain unclear. Behavioral disturbances such as depression, anxiety, cognitive impairment, psychosis, euphoria, sleep disturbances, and fatigue affect the quality of life in MS patients. Among these, depression and psychosis are more common than any other neurological disorders. In addition, depression is associated with other comorbidities. Although anxiety is often misdiagnosed in MS patients, it can induce suicidal ideation if it coexists with depression. An interrelation between sleep abnormalities and fatigue is also reported among MS patients. In addition, therapeutics for MS is always a challenge because of the presence of the blood-brain barrier, adding to the lack of detailed understanding of the disease pathology. In this review, we tried to summarize various behavioral pathologies and their association with MS, followed by its conventional treatment and nanotheranostics.

Indexed as

behavioral disordersbehavioral testsdemyelination

Identifiers

PMID26508863
PMCPMC4610886
OpenAlexW2126012988

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.