Strategies for Measuring Non-Evoked Pain in Preclinical Models of Neuropathic Pain: Systematic Review.

The development of new analgesics for neuropathic pain treatment is crucial. The failure of promising drugs in clinical trials may be related to the over-reliance on reflex-based responses (evoked pain) in preclinical drug testing, which may not fully represent clinical neuropathic pain, characterized by spontaneous non-evoked pain (NEP). Hence, strategies for assessing NEP in preclinical studies emerged. This systematic review identified 443 articles evaluating NEP in neuropathic pain models (mainly traumatic nerve injuries in male rodents). An exponential growth in NEP evaluation was observed, which was assessed using 48 different tests classified in 12 NEP-related outcomes: anxiety, exploration/locomotion, paw lifting, depression, conditioned place preference, gait, autotomy, wellbeing, facial grooming, cognitive impairment, facial pain expressions and vocalizations. Although most of these outcomes showed clear limitations, our analysis suggests that conditioning-associated outcomes, pain-related comorbidities, and gait evaluation may be the most effective strategies. Moreover, a minimal part of the studies evaluated standard analgesics. The greater emphasis on evaluating NEP aligning with clinical pain symptoms may enhance analgesic drug development, improving clinical translation.

Adults with excess weight or obesity, but not with overweight, report greater pain intensities than individuals with normal weight: a systematic review and meta-analysis.

Context: Over 1.9 billion adult people have overweight or obesity. Considered as a chronic disease itself, obesity is associated with several comorbidities. Chronic pain affects approximately 60 million people and its connection with obesity has been displayed in several studies. However, controversial results showing both lower and higher pain thresholds in subjects with obesity compared to individuals with normal weight and the different parameters used to define such association (e.g., pain severity, frequency or duration) make it hard to draw straight forward conclusions in the matter. The objective of this article is to examine the relationship between overweight and obesity (classified with BMI as recommended by WHO) and self-perceived pain intensity in adults. Methods: A literature search was conducted following PRISMA guidelines using the databases CINAHL, Cochrane Library, EMBASE, PEDro, PubMed, Scopus and Web of Science to identify original studies that provide BMI values and their associated pain intensity assessed by self-report scales. Self-report pain scores were normalized and pooled within meta-analyses. The Cochrane's Q test and I2 index were used to clarify the amount of heterogeneity; meta-regression was performed to explore the relationship between each outcome and the risk of bias. Results: Of 2194 studies, 31 eligible studies were identified and appraised, 22 of which provided data for a quantitative analysis. The results herein suggested that adults with excess weight (BMI ≥ 25.0) or obesity (BMI ≥ 30.0) but not with overweight (pre-obesity) alone (BMI 25.0-29.9), are more likely to report greater intensities of pain than individuals of normal weight (BMI 18.5-24.9). Subgroup analyses regarding the pathology of the patients showed no statistically significant differences between groups. Also, influence of age in the effect size, evaluated by meta-regression, was only observed in one of the four analyses. Furthermore, the robustness of the findings was supported by two different sensitivity analyses. Conclusion: Subjects with obesity and excess weight, but not overweight, reported greater pain intensities than individuals with normal weight. This finding encourages treatment of obesity as a component of pain management. More research is required to better understand the mechanisms of these differences and the clinical utility of the findings. Systematic Review Registration: https://doi.org/10.17605/OSF.IO/RF2G3, identifier OSF.IO/RF2G3.

Sigma-1 receptor agonism exacerbates immune-driven nociception: Role of TRPV1 + nociceptors.

The analgesic effects of sigma-1 antagonists are undisputed, but the effects of sigma-1 agonists on pain are not well studied. Here, we used a mouse model to show that the administration of the sigma-1 agonists dextromethorphan (a widely used antitussive drug), PRE-084 (a standard sigma-1 ligand), and pridopidine (a selective drug being investigated in clinical trials for the treatment of neurodegenerative diseases) enhances PGE2-induced mechanical hyperalgesia. Superficial plantar incision induced transient weight-bearing asymmetry at early time points, but the mice appeared to recover at 24 h, despite noticeable edema and infiltration of neutrophils (a well-known cellular source of PGE2) at the injured site. Sigma-1 agonists induced a relapse of weight bearing asymmetry in a manner dependent on the presence of neutrophils. The effects of sigma-1 agonists were all reversed by administration of the sigma-1 antagonist BD-1063 in wild-type mice, and were absent in sigma-1 knockout mice, supporting the selectivity of the effects observed. The proalgesic effects of sigma-1 agonism were also abolished by the TRP antagonist ruthenium red and by in vivo resiniferatoxin ablation of TRPV1 + peripheral sensory neurons. Therefore, sigma-1 agonism exacerbates pain-like responses in mice with a mild inflammatory state through the action of TRPV1 + nociceptors. We also show that sigma-1 receptors are present in most (if not all) mouse and human DRG neurons. If our findings translate to humans, further studies will be needed to investigate potential proalgesic effects induced by sigma-1 agonism in patients treated with sigma-1 agonists.

Investigational Drugs for the Treatment of Postherpetic Neuralgia: Systematic Review of Randomized Controlled Trials.

The pharmacological treatment of postherpetic neuralgia (PHN) is unsatisfactory, and there is a clinical need for new approaches. Several drugs under advanced clinical development are addressed in this review. A systematic literature search was conducted in three electronic databases (Medline, Web of Science, Scopus) and in the ClinicalTrials.gov register from 1 January 2016 to 1 June 2023 to identify Phase II, III and IV clinical trials evaluating drugs for the treatment of PHN. A total of 18 clinical trials were selected evaluating 15 molecules with pharmacological actions on nine different molecular targets: Angiotensin Type 2 Receptor (AT2R) antagonism (olodanrigan), Voltage-Gated Calcium Channel (VGCC) α2δ subunit inhibition (crisugabalin, mirogabalin and pregabalin), Voltage-Gated Sodium Channel (VGSC) blockade (funapide and lidocaine), Cyclooxygenase-1 (COX-1) inhibition (TRK-700), Adaptor-Associated Kinase 1 (AAK1) inhibition (LX9211), Lanthionine Synthetase C-Like Protein (LANCL) activation (LAT8881), N-Methyl-D-Aspartate (NMDA) receptor antagonism (esketamine), mu opioid receptor agonism (tramadol, oxycodone and hydromorphone) and Nerve Growth Factor (NGF) inhibition (fulranumab). In brief, there are several drugs in advanced clinical development for treating PHN with some of them reporting promising results. AT2R antagonism, AAK1 inhibition, LANCL activation and NGF inhibition are considered first-in-class analgesics. Hopefully, these trials will result in a better clinical management of PHN.

Efficacy and Security of Tetrodotoxin in the Treatment of Cancer-Related Pain: Systematic Review and Meta-Analysis.

The pharmacological treatment of cancer-related pain is unsatisfactory. Tetrodotoxin (TTX) has shown analgesia in preclinical models and clinical trials, but its clinical efficacy and safety have not been quantified. For this reason, our aim was to perform a systematic review and meta-analysis of the clinical evidence that was available. A systematic literature search was conducted in four electronic databases (Medline, Web of Science, Scopus, and ClinicalTrials.gov) up to 1 March 2023 in order to identify published clinical studies evaluating the efficacy and security of TTX in patients with cancer-related pain, including chemotherapy-induced neuropathic pain. Five articles were selected, three of which were randomized controlled trials (RCTs). The number of responders to the primary outcome (≥30% improvement in the mean pain intensity) and those suffering adverse events in the intervention and placebo groups were used to calculate effect sizes using the log odds ratio. The meta-analysis showed that TTX significantly increased the number of responders (mean = 0.68; 95% CI: 0.19-1.16, p = 0.0065) and the number of patients suffering non-severe adverse events (mean = 1.13; 95% CI: 0.31-1.95, p = 0.0068). However, TTX did not increase the risk of suffering serious adverse events (mean = 0.75; 95% CI: -0.43-1.93, p = 0.2154). In conclusion, TTX showed robust analgesic efficacy but also increased the risk of suffering non-severe adverse events. These results should be confirmed in further clinical trials with higher numbers of patients.

Validating distribution models for twelve endemic bird species of tropical dry forest in western Mexico.

Considering the high biodiversity and conservation concerns of the tropical dry forest, this study aim is to predict and evaluate the potential and current distributions of twelve species of endemic birds which distribute along the western slope of Mexico. The main goal is to evaluate altogether different methods for predicting actual species distribution models (ADMs) of the twelve species including the identification of key environmental potential limiting factors. ADMs for twelve endemic Mexican birds were generated and validated by means of applying: (1) three widely used species niche modeling approaches (ENFA, Garp, and Maxent); (2) two thresholding methods, based on ROC curves and Kappa Index, for transforming continuous models to presence/absence (binary) models; (3) documented habitat-species associations for reducing species potential distribution models (PDMs); and (4) field occurrence data for validating final ADMs. Binary PDMs' predicted areas seemed overestimated, while ADMs looked drastically reduced and fragmented because of the approach taken for eliminating those predicted areas which were documented as unsuitable habitat types for individual species. Results indicated that both thresholding methods generated similar threshold values for species modeled by each of the three species distribution modeling algorithms (SDMAs). A Wilcoxon signed-rank test, however, showed that Kappa values were generally higher than ROC curve for species modeled by ENFA and Maxent, while for Garp models there were no significant differences. Prediction success (e.g., true presences percentage) obtained from field occurrence data revealed a range of 50%-82% among the 12 species. The three modeling approaches applied enabled to test the application of two thresholding methods for transforming continuous to binary (presence/absence) models. The use of documented habitat preferences resulted in drastic reductions and fragmentation of PDMs. However, ADMs predictive success rate, tested using field species occurrence data, varied between 50 and 82%.

An analysis of the radioactive contamination due to radon in a granite processing plant and its decontamination by ventilation.

This work focuses on studying concentration distribution of 222Rn radioisotope in a granite processing plant. Using Computational Fluid Dynamic Techniques (CFD), the exposure of the workers to radiation was assessed and, in order to minimise this exposure, different decontamination scenarios using ventilation were analysed. Natural ventilation showed not sufficient to maintain radon concentration below acceptable limits, so a forced ventilation was used instead. Position of the granite blocks also revealed as a determining factor in the radioactive level distribution. Thus, a correct layout of the stored material and an adequate ventilation system can guarantee free of exposure to radiation zones within the studied workshop. This leads to a drastic fall in the exposure of the workers and consequently minimises their risk of developing aggressive illness like lung cancer.

Extinction risk from climate change.

Climate change over the past approximately 30 years has produced numerous shifts in the distributions and abundances of species and has been implicated in one species-level extinction. Using projections of species' distributions for future climate scenarios, we assess extinction risks for sample regions that cover some 20% of the Earth's terrestrial surface. Exploring three approaches in which the estimated probability of extinction shows a power-law relationship with geographical range size, we predict, on the basis of mid-range climate-warming scenarios for 2050, that 15-37% of species in our sample of regions and taxa will be 'committed to extinction'. When the average of the three methods and two dispersal scenarios is taken, minimal climate-warming scenarios produce lower projections of species committed to extinction ( approximately 18%) than mid-range ( approximately 24%) and maximum-change ( approximately 35%) scenarios. These estimates show the importance of rapid implementation of technologies to decrease greenhouse gas emissions and strategies for carbon sequestration.

Predicting distributions of known and unknown reptile species in Madagascar.

Despite the importance of tropical biodiversity, informative species distributional data are seldom available for biogeographical study or setting conservation priorities. Modelling ecological niche distributions of species offers a potential solution; however, the utility of old locality data from museums, and of more recent remotely sensed satellite data, remains poorly explored, especially for rapidly changing tropical landscapes. Using 29 modern data sets of environmental land coverage and 621 chameleon occurrence localities from Madagascar (historical and recent), here we demonstrate a significant ability of our niche models in predicting species distribution. At 11 recently inventoried sites, highest predictive success (85.1%) was obtained for models based only on modern occurrence data (74.7% and 82.8% predictive success, respectively, for pre-1978 and all data combined). Notably, these models also identified three intersecting areas of over-prediction that recently yielded seven chameleon species new to science. We conclude that ecological niche modelling using recent locality records and readily available environmental coverage data provides informative biogeographical data for poorly known tropical landscapes, and offers innovative potential for the discovery of unknown distributional areas and unknown species.

Future projections for Mexican faunas under global climate change scenarios.

Global climates are changing rapidly, with unexpected consequences. Because elements of biodiversity respond intimately to climate as an important driving force of distributional limitation, distributional shifts and biodiversity losses are expected. Nevertheless, in spite of modelling efforts focused on single species or entire ecosystems, a few preliminary surveys of fauna-wide effects, and evidence of climate change-mediated shifts in several species, the likely effects of climate change on species' distributions remain little known, and fauna-wide or community-level effects are almost completely unexplored. Here, using a genetic algorithm and museum specimen occurrence data, we develop ecological niche models for 1,870 species occurring in Mexico and project them onto two climate surfaces modelled for 2055. Although extinctions and drastic range reductions are predicted to be relatively few, species turnover in some local communities is predicted to be high (>40% of species), suggesting that severe ecological perturbations may result.