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Record W2059753261 · doi:10.4103/1673-5374.150728

Hypersensitivity of vascular alpha-adrenoceptor responsiveness: a possible inducer of pain in neuropathic states

2015· article· en· W2059753261 on OpenAlexaff
RobertW. Teasell, Qingping Feng

Bibliographic record

VenueNeural Regeneration Research · 2015
Typearticle
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsParkwood InstituteLawson Health Research InstituteWestern University
Fundersnot available
KeywordsMedicineNeuropathic painNociceptionVasoconstrictionAnesthesiaAllodyniaNerve injuryPeripheral nerve injuryPeripheralAnalgesicNorepinephrineInternal medicineHyperalgesiaEndocrinologyReceptorSciatic nerve

Abstract

fetched live from OpenAlex

Dear editor, Dr. Peter Drummond's article noted that peripheral nerve and tissue injury in neuropathic pain syndromes releases cytokines which in turn lead to an increase in alpha1-adrenoceptor upregulation, resulting in a heightened sensitivity to noradrenaline. In these circumstances, noradrenaline acting on upregulated alpha1 a-adrenoceptors increases the release of cytokine interleukin-6. Hence, nociceptive afferent neurons exposed to injury induced cytokines become more hypersensitive to noradrenaline, which in turn promotes the release of more inflammatory cytokines. Dr. Drummond noted that this mechanism may contribute to the pain of post-herpetic neuralgia or complex regional pain syndrome (Drummond, 2014). Using a technique that allowed us to monitor vasoconstriction in peripheral veins of affected limbs in response to increasing concentrations of noradrenaline in local intravenous infusions, we were able to determine the responsiveness of alpha-adrenoceptors in a number of painful conditions. We found significant venous alpha-adrenoceptor hyperresponsiveness in complex regional pain syndrome (Arnold et al., 1993), spinal cord injuries (Arnold et al., 1995; Teasell et al., 2000) and diabetic peripheral nerve injuries (Capes et al., 1997) to local intravenous infusions of noradrenaline. A similar technique in insulin dependent diabetic mellitus patients found vascular (venous) responsiveness to noradrenaline directly correlated with nerve conduction velocity, a measure of the severity of the nerve injury (Eichler et al., 1992; Bodmer et al., 1999). Notably, the ED50 (defined as the concentration of noradrenaline required to cause a 50% reduction of the resting vein diameter) of the dorsal veins of insulin dependent diabetic mellitus patients with symptomatic autonomic dysfunction was lower than in asymptomatic diabetics. The exaggerated vascular reactivity to noradrenaline can be blocked by an alpha 1-adrenoceptor blocker doxazosin, suggesting the vascular response is mediated by alpha-1 adrenoceptors. One hypothesis which may account for these findings is a dysfunctional sympathetic nervous system with diminished ability of alpha-2 adrenoceptors to presympathetically reuptake noradrenaline resulting in excessive stimulation of the alpha-1 adrenoceptor. Support for this comes from observations of higher noradrenaline levels in patients with a clinical diabetic peripheral neuropathy (Capes et al., 1997) and the fact that transdermal clonidine (an alpha-2-adrenoceptor agonist) is more effective than controls in reducing the pain of peripheral diabetic neuropathies (Zeigler et al., 1992). This additional evidence, which demonstrates alpha-adrenoceptor hyperresponsiveness of peripheral veins in three painful neuropathic states, insulin dependent diabetic mellitus, spinal cord injuries and diabetic peripheral neuropathies, raises the intriguing possibility that sympathetic nervous system dysfunction may be an important factor in the generation of pain in a number of neuropathic states (Teasell and Arnold, 2004). This is also supported by the fact that alpha-adrenoceptor blockers relieve pain in diabetic neuropathy in rodents (Lee et al., 2000; Bujalska et al., 2008) and in patients with chronic prostatitis/chronic pelvic pain syndrome (Thakkinstian et al., 2012).

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)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.342

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.127
GPT teacher head0.382
Teacher spread0.255 · 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 designBench or experimental
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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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