Noxious heat threshold measured with slowly increasing temperatures: novel rat thermal hyperalgesia models

The triple function of the capsaicin-sensitive sensory neurons: In memoriam János Szolcsányi

This paper is dedicated to the memory of János Szolcsányi (1938-2018), an outstanding Hungarian scientist. Among analgesics that act on pain receptors, he identified capsaicin as a selective lead molecule. He studied the application of capsaicin and revealed several physiological (pain, thermoregulation) and pathophysiological (inflammation, gastric ulcer) mechanisms. He discovered a new neuroregulatory system without sensory efferent reflex and investigated its pharmacology. The authors of this review are his former Ph.D. students who carried out their doctoral work in Szolcsányi's laboratory between 1985 and 2010 and report on the scientific results obtained under his guidance. His research group provided evidence for the triple function of the peptidergic capsaicin-sensitive sensory neurons including classical afferent function, local efferent responses, and remote, hormone-like anti-inflammatory, and antinociceptive actions. They also proposed somatostatin receptor type 4 as a promising drug target for the treatment of pain and inflammation. They revealed that neonatal capsaicin treatment caused no acute neuronal death but instead long-lasting selective ultrastructural and functional changes in B-type sensory neurons, similar to adult treatment. They described that lipid raft disruption diminished the agonist-induced channel opening of the TRPV1, TRPA1, and TRPM8 receptors in native sensory neurons. Szolcsányi's group has developed new devices for noxious heat threshold measurement: an increasing temperature hot plate and water bath. This novel approach proved suitable for assessing the thermal antinociceptive effects of analgesics as well as for analyzing peripheral mechanisms of thermonociception.

Neuropathic pain modeling: Focus on synaptic and ion channel mechanisms

Animal models of pain consist of modeling a pain-like state and measuring the consequent behavior. The first animal models of neuropathic pain (NP) were developed in rodents with a total lesion of the sciatic nerve. Later, other models targeting central or peripheral branches of nerves were developed to identify novel mechanisms that contribute to persistent pain conditions in NP. Objective assessment of pain in these different animal models represents a significant challenge for pre-clinical research. Multiple behavioral approaches are used to investigate and to validate pain phenotypes including withdrawal reflex to evoked stimuli, vocalizations, spontaneous pain, but also emotional and affective behaviors. Furthermore, animal models were very useful in investigating the mechanisms of NP. This review will focus on a detailed description of rodent models of NP and provide an overview of the assessment of the sensory and emotional components of pain. A detailed inventory will be made to examine spinal mechanisms involved in NP-induced hyperexcitability and underlying the current pharmacological approaches used in clinics with the possibility to present new avenues for future treatment. The success of pre-clinical studies in this area of research depends on the choice of the relevant model and the appropriate test based on the objectives of the study.

Evaluation of ameliorative effect of sodium nitrate in experimental model of streptozotocin-induced diabetic neuropathy in male rats

OBJECTIVE

Diabetes induces sensory symptoms of neuropathy as positive (hyperalgesia), negative (hypoalgesia), or both.

METHODS

In the present study, fifty male Wistar rats were allocated to five groups: control, control+nitrate, diabetes, diabetes+insulin, and diabetes+nitrate. Thirty days after diabetes confirmation, insulin (2-4 U/day) was injected subcutaneously in diabetes+insulin group and nitrate (100 mg/l) was added into drinking water of the control+nitrate and diabetes+nitrate groups for a period of 2 months. In order to assess the mechanical and thermal algesia, tail immersion, hot plate, and von Frey tests were performed. The serum insulin levels were determined with insulin ELISA Kit. Serum level of NOx was determined by the Griess method.

RESULTS

Both thermal and mechanical nociceptive thresholds showed a significant decrease (p<0.05) which was followed by a significant increase (p<0.01) in the thermal nociceptive threshold in the diabetes group. Chronic nitrate or insulin treatment led to a significant decrease (p<0.01) in blood glucose levels, as well as a significant (p<0.05) increase in the body weight and serum NOx. Moreover, nitrate treatment significantly increased serum insulin levels (p<0.001) compared to the other groups.

CONCLUSION

Chronic nitrate treatment modified the thermal and mechanical sensitivities in diabetic animals.

Intrastriatal Chromospheres' Transplant Reduces Nociception in Hemiparkinsonian Rats

The present study evaluates the possible antinociceptive effect of chromosphere transplants in rats injected with 6-hydroxydopamine (6-OHDA), a model of Parkinson's disease. Male adult Wistar rats received 40μg/0.5μl of 6-OHDA or 0.5μl of vehicle into the left substantia nigra (SNc). Rats were evaluated for mechanical allodynia, cold allodynia, thermal hyperalgesia and formalin. Rats with altered nociceptive threshold were transplanted with chromospheres. After transplant, rats were evaluated every week. Our results confirm that 6-OHDA injection into rat's SNc reduces mechanical, thermal, and chemical thresholds. Interestingly, chromospheres' transplant reverted 6-OHDA-induced allodynia and hyperalgesia. The antinociceptive effect induced by chromospheres was dopamine D2- and opioid-receptor dependent since sulpiride or naltrexone reverted its effect.

Animal models of chronic pain: Advances and challenges for clinical translation

Chronic pain is a global problem that has reached epidemic proportions. An estimated 20% of adults suffer from pain, and another 10% are diagnosed with chronic pain each year (Goldberg and McGee, ). Despite the high prevalence of chronic pain (an estimated 1.5 billion people are afflicted worldwide), much remains to be understood about the underlying causes of this condition, and there is an urgent requirement for better pain therapies. The discovery of novel targets and the development of better analgesics rely on an assortment of preclinical animal models; however, there are major challenges to translating discoveries made in animal models to realized pain therapies in humans. This review discusses common animal models used to recapitulate clinical chronic pain conditions (such as neuropathic, inflammatory, and visceral pain) and the methods for assessing the sensory and affective components of pain in animals. We also discuss the advantages and limitations of modeling chronic pain in animals as well as highlighting strategies for improving the predictive validity of preclinical pain studies. © 2016 Wiley Periodicals, Inc.

Neuropathic pain: role of inflammation, immune response, and ion channel activity in central injury mechanisms

Neuropathic pain (NP) is a significant and disabling clinical problem with very few therapeutic treatment options available. A major priority is to identify the molecular mechanisms responsible for NP. Although many seemingly relevant pathways have been identified, more research is needed before effective clinical interventions can be produced. Initial insults to the nervous system, such as spinal cord injury (SCI), are often compounded by secondary mechanisms such as inflammation, the immune response, and the changing expression of receptors and ion channels. The consequences of these secondary effects myriad and compound those elicited by the primary injury. Chronic NP syndromes following SCI can greatly complicate the clinical treatment of the primary injury and result in high comorbidity. In this review, we will describe physiological outcomes associated with SCI along with some of the mechanisms known to contribute to chronic NP development.

Rapid determination of the thermal nociceptive threshold in diabetic rats

Painful diabetic neuropathy (PDN) is characterized by hyperalgesia i.e., increased sensitivity to noxious stimulus, and allodynia i.e., hypersensitivity to normally innocuous stimuli. Hyperalgesia and allodynia have been studied in many different rodent models of diabetes mellitus. However, as stated by Bölcskei et al, determination of "pain" in animal models is challenging due to its subjective nature. Moreover, the traditional methods used to determine behavioral responses to noxious thermal stimuli usually lack reproducibility and pharmacological sensitivity. For instance, by using the hot-plate method of Ankier, flinch, withdrawal and/or licking of either hind- and/or fore-paws is quantified as reflex latencies at constant high thermal stimuli (52-55 °C). However, animals that are hyperalgesic to thermal stimulus do not reproducibly show differences in reflex latencies using those supra-threshold temperatures. As the recently described method of Bölcskei et al., the procedures described here allows for the rapid, sensitive and reproducible determination of thermal nociceptive thresholds (TNTs) in mice and rats. The method uses slowly increasing thermal stimulus applied mostly to the skin of mouse/rat plantar surface. The method is particularly sensitive to study anti-nociception during hyperalgesic states such as PDN. The procedures described bellow are based on the ones published in detail by Almási et al and Bölcskei et al. The procedures described here have been approved the Laboratory Animal Care and Use Committee (LACUC), Wright State University.

Meta-analysis of untargeted metabolomic data from multiple profiling experiments

metaXCMS is a software program for the analysis of liquid chromatography/mass spectrometry-based untargeted metabolomic data. It is designed to identify the differences between metabolic profiles across multiple sample groups (e.g., 'healthy' versus 'active disease' versus 'inactive disease'). Although performing pairwise comparisons alone can provide physiologically relevant data, these experiments often result in hundreds of differences, and comparison with additional biologically meaningful sample groups can allow for substantial data reduction. By performing second-order (meta-) analysis, metaXCMS facilitates the prioritization of interesting metabolite features from large untargeted metabolomic data sets before the rate-limiting step of structural identification. Here we provide a detailed step-by-step protocol for going from raw mass spectrometry data to metaXCMS results, visualized as Venn diagrams and exported Microsoft Excel spreadsheets. There is no upper limit to the number of sample groups or individual samples that can be compared with the software, and data from most commercial mass spectrometers are supported. The speed of the analysis depends on computational resources and data volume, but will generally be less than 1 d for most users. metaXCMS is freely available at http://metlin.scripps.edu/metaxcms/.

metaXCMS: second-order analysis of untargeted metabolomics data

Mass spectrometry-based untargeted metabolomics often results in the observation of hundreds to thousands of features that are differentially regulated between sample classes. A major challenge in interpreting the data is distinguishing metabolites that are causally associated with the phenotype of interest from those that are unrelated but altered in downstream pathways as an effect. To facilitate this distinction, here we describe new software called metaXCMS for performing second-order ("meta") analysis of untargeted metabolomics data from multiple sample groups representing different models of the same phenotype. While the original version of XCMS was designed for the direct comparison of two sample groups, metaXCMS enables meta-analysis of an unlimited number of sample classes to facilitate prioritization of the data and increase the probability of identifying metabolites causally related to the phenotype of interest. metaXCMS is used to import XCMS results that are subsequently filtered, realigned, and ultimately compared to identify shared metabolites that are up- or down-regulated across all sample groups. We demonstrate the software's utility by identifying histamine as a metabolite that is commonly altered in three different models of pain. metaXCMS is freely available at http://metlin.scripps.edu/metaxcms/.