MétaCan
Menu
Back to cohort
Record W4387743881 · doi:10.1097/gh9.0000000000000284

Role of Shankhpushpi (Convolvulus pluricaulis) in neurological disorders

2023· article· en· W4387743881 on OpenAlexaff
Mahesh Rachamalla, Ravinder K. Kaundal, Hitesh Chopra, Saikat Dewanjee, Saurabh Kumar Jha, Niraj Kumar Jha, Talha Bin Emran

Bibliographic record

VenueInternational Journal of Surgery Global Health · 2023
Typearticle
Languageen
FieldMedicine
TopicMedicinal Plants and Neuroprotection
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsNootropicPharmacologyMedicineCoumarinTraditional medicinePhytochemistryChemistry

Abstract

fetched live from OpenAlex

Shankhpushpi (Convolvulus pluricaulis) has emerged as a promising natural plant in the treatment of a variety of inflammatory and neurological disorders over the last two decades. Sharma et al.1 investigated and comprehensively reviewed the various health benefits of crude C. pluricaulis herb and its extracts, as well as metabolites, in alleviating inflammation, oxidative stress, stress, anxiety, and neurological disorders such as Alzheimer’s, memory impairment, and sleep disorders. Several preclinical and clinical studies suggested the potential benefits of Shankhpushpi for neurological complications. We agree with the author’s assessment and provide some new viewpoints on numerous areas relating to Shankhpushpi’s potential in this discussion. Lack of phytochemistry on active ingredients: Sharma et al. reviewed the currently available literature on various extracts from the plant and their role in various neurological models. C. pluricaulis contains several phytochemicals like alkaloids, anthocyanin, coumarin, flavonoid, phytosterol, and triterpenoid components. Interestingly, in silico ADME (absorption, distribution, metabolism, and excretion) screening identified only five active phytoconstituents viz. scopoletin, 4-hydroxycinnamic acid, kaempferol, quercetin, and ayapanin of C. pluricaulis that possess drug-likeness and blood–brain barrier permeability2. Considering the diverse pharmacological profile of these bioactive compounds, the beneficial effects of Shankhpushpi in a range of neurological ailments are not surprising. However, further investigations are warranted to explore the therapeutic potential and safety profile of individual phytoconstituents of Shankhpushpi, especially because of concerns about hepatotoxicity. Coumarin, a bioactive consistent of Shankhpushpi, has been reported to exhibit hepatoxicity in rodent models. As the authors mentioned, coumarin has been restricted by the United States Food and Drug Administration and is not permitted for use in human food. There is still a huge knowledge gap on phytochemistry and specific molecules that play a protective role in the various ailments mentioned above, but there is much more research to be done in this area to better understand the molecular mechanisms. Clear knowledge gap on molecular mechanisms: Sharma et al. thoroughly reviewed studies on the neurological benefits of several constituents of Shankhpushpi, but there is no clear understanding of the molecular mechanisms, which poses a lot of uncertainty on its potential benefits. Many of the studies, including the 166 in the review, can hardly explain the precise molecular mechanisms and which active phytoconstituent is responsible for the beneficial effects. A recent study utilizing integrated network pharmacology and in silico approach provided insight into the potential molecular mechanisms of phytoconstituents from Shankhpushpi. The five key bioactive metabolites of Shankhapushpi (scopoletin, 4-hydroxycinnamic acid, kaempferol, quercetin, and ayapanin) are predicted to modulate several molecular targets including PTGS1, PTGS2, NOS3, INSR, HMOX1, ACHE, PPARG, MAOA, MAOB, and TRKB. These molecular targets participate in many cellular pathways important for neuronal growth, survival, and functionality. The in-silico analysis predicted that PI3K/Akt signaling, neurotrophin signaling, and insulin signaling are the key pathways that are most likely to be modulated by Shankhapushpi. Another in-silico study looked at the relationships between Shankhapushpi metabolites and dopaminergic receptors, mitogen-activated protein kinases, 5-hydroxytryptamine receptors, and histone deacetylases. The hypothesized network of gene–gene interactions and its investigations have established the framework for understanding Shankhapushpi’s nootropic function. Furthermore, the network suggests unique insights into the future scope of investigation on Shankhapushpi’s nootropic action. The combined network pharmacology research from animal models and in-silico observations provides a scientific foundation for memory augmentation and the prevention of aging/pathological cognitive impairments. However, more studies are needed to explore the memory-enhancing and neuroprotective mechanisms of phytoconstituents and their metabolites before extrapolating the findings from preclinical and in silico models to clinical subjects2,3. Unknown toxicity might impact the potential of Shankhpushpi applications: Despite such extensive use of Shankhpushpi, data on the toxicity profile of its phytoconsitutents is lacking. Shankhpushpi has been reported to display mild hypotensive effects. It is also indicated to interact with phenytoin and decrease its antiepileptic activity. Furthermore, the hepatotoxicity of coumarin also raises serious safety concerns regarding Shankhpushpi use. Unfortunately, there is not enough literature to suggest that the critical evaluation of several bioactive compounds present in Shankhpushpi does not have toxicity data in various models. Therefore, it is essential to understand and critically evaluate the toxicity potential of all its phytoconstituents. Preliminary research using QSAR (quantitative structure–activity relationship) models and in silico approaches can provide some insight into the toxicity of these bioactive compounds for additional testing in animal models. Need for clinical validation: As the authors noted, multicentric trials involving diverse ethnic and regional populations are required to understand the clinical uses and commercial viability of bioactive compounds. Overall, the authors thoroughly investigated the Shankhpushpi literature (C. pluricaulis) and presented potential molecular targets such as the PI3K–Akt signaling pathway, cholinergic synapse, serotonergic synapse, MAPK (mitogen-activated protein kinase) signaling pathway, long-term depression, Alzheimer’s disease, and neurotrophin signaling pathway. Because these approaches have been taken by other researchers, as mentioned in the preceding sections, this type of study may not result in a concrete understanding of molecular mechanisms. However, pursuing the research of toxicity potential for the presented bioactive compounds might have revealed some unique perspectives. Nonetheless, more human clinical trials will be required to establish the safety, tolerability, and efficacy of each bioactive phytochemical in decreasing neuroinflammation in the brain, as well as highlight the implications for neurodegenerative disease treatment. Ethical approval This case report has been reported in line with the CAse REport (CARE) guidelines. Consent Not applicable. Source of funding None. Author contribution M.R.: conceptualization, data curation, and writing – original draft preparation, reviewing, and editing; R.K.K.: conceptualization, data curation, and writing – original draft preparation, reviewing, and editing; H.C.: data curation and writing – original draft preparation, reviewing, and editing; S.D.: data curation and writing – original draft preparation, reviewing, and editing; S.K.J.: data curation and writing – original draft preparation, reviewing, and editing; N.K.J.: writing – reviewing and editing, visualization, and supervision; T.B.E.: writing – reviewing and editing, visualization, and supervision. All authors critically revised the manuscript concerning intellectual content and approved the final manuscript. Conflicts of interest disclosure There are no conflicts of interest. Research registration unique identifying number (UIN) Not applicable. Provenance and peer review Not commissioned, externally peer-reviewed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.206
Threshold uncertainty score0.275

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.036
GPT teacher head0.352
Teacher spread0.316 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Surgery Global HealthSame topicMedicinal Plants and NeuroprotectionFrench-language works237,207