OBJECTIVE: Verifying lumbar disc pain can present a clinical challenge. Low-pressure provocative discography (PD) has served as the gold standard, although it is invasive and often a challenge to interpret. We reported that magnetic resonance spectroscopy (MRS) biomarkers accurately predict PD results in lumbar discs and improved outcomes for patients with surgery at positive MRS levels versus nonsurgery. To further substantiate MRS for diagnosing painful discs, we report a prospective comparison of 2 MRS-derived measures: NOCISCORE (pain) and SI-SCORE (degeneration severity).
METHODS: Lumbar MRS and software-based postprocessing (NOCISCAN-LS, Aclarion Inc.) was performed in 44 discs in 14 patients (prospective cohort [PC]). PC data were compared to prior data used to establish the NOCISCORE (training cohort [TC]). The NOCISCORE was converted to an ordinal value (high/intermediate/low; NOCI+/mild/-) and compared against painful (P) versus nonpainful (NP) control diagnosis (PD) for 19 discs where PD was performed in the PC (12 NP; 7 P). Sensitivity, specificity, and positive and negative predictive values were calculated. The SI-SCORE was compared against MRI Pfirrmann Grades for 465 discs in 126 patients (PC plus TC).
RESULTS: For the PC, MRS (NOCI+/-) compared to PD (P/NP) with an accuracy of 87% and sensitivity and specificity of 100%. The positive and negative predictive values of MRS were 100%. NOCISCOREs were significantly higher for PD+ versus PD- discs for PC and TC (P < 0.05), and the NOCISCORE distributions for PD+/- group were not statistically different between the PC and TC (P > 0.05). SI-SCORES differed between Pfirrmann Grades 1 and 2 (less degenerated) versus Grades 3 and 4 (more degenerated; P < 0.05), with a progressively decreasing trend with Pfirrmann Grades 1-5.
CONCLUSIONS: These current data provide prospective confirmation of the predictive value of disc MRS for distinguishing painful discs and for assessing the disc structural integrity.
CONCLUSIONS: NOCISCAN is an adoptable, noninvasive, and objectively quantitative test to improve management of low back pain patients.
METHODS:

MRS was shown to reliably quantify relative levels of degenerative pain biomarkers, differentiating painful versus non-painful discs in patients with chronic discogenic low back pain (DLBP), and this correlates with surgical success rates. We now report results based on more patients and longer follow-up.
Disc MRS was performed in DLBP patients who subsequently received lumbar surgery. Custom post-processing (NOCISCAN-LS®; Aclarion Inc.) calculated disc-specific NOCISCORES® that reflect relative differences in degenerative pain biomarkers for diagnosing chemically painful discs. Outcomes in 78 patients were evaluated using Oswestry Disability Index (ODI) scores. Surgical success (≥ 15-point ODI improvement) was compared between surgeries that were \"Concordant\" (Group C) versus \"Discordant\" (Group D) with NOCISCORE-based diagnosis for painful discs.
Success rates were higher for Group C versus Group D: 6 months (88% vs. 62%; p = 0.01), 12 months (91% vs. 56%; p < 0.001), and 24 months (85% vs. 63%; p = 0.07). Success rates for Group C surgeries were also higher than Group D surgeries in a variety of sub-group comparisons. Group C had a greater reduction in ODI from pre-operative to follow-up than Group D [absolute change (% change), (p)]: 6 months: - 35 (- 61%) versus - 23 (- 39%), (p < 0.05); 12 months: - 39 (- 69%) versus - 22 (- 39%), (p < 0.01); and 24 months:  - 38 (- 66%) versus - 26 (- 48%), (p < 0.05).
More successful, sustained outcomes were obtained when surgically treating chemically painful discs identified by NOCISCAN-LS post-processed disc MRS exams. Results suggest that NOCISCAN-LS provides a valuable new diagnostic tool to help clinicians better select treatment levels.

The potential of Se to alleviate pain associated with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced neurotoxicity was investigated. Swiss mice were intraperitoneally injected with MPTP (20 mg/kg) 4 times with an interval of 2 h in 1 day. Seven days after MPTP injection, the mice (n = 5 mice per group) were randomly assigned to groups: MPTP-, DOPA (50 mg/kg)-, Se4 (0.4 mg/kg)-, Se6 (0.6 mg/kg)-, DOPA+Se4-, and DOPA+Se6-treated groups were compared with controls. MPTP mice were treated for seven days; thereafter, motor-coordination and nociceptive-motor reactions were assessed. Pro-inflammatory cytokines (IL-1β, IL-6 and TNFα), and selected pain biomarkers (substance P (SP), glutamate and β-endorphin) were assessed in the serum and the substantial nigra pars compacta (SNpc). Motor activity was increased slightly by Se (0.6 or 0.4 mg/kg) vs. MPTP (10.48 ± 2.71 or 11.81 ± 1.28 s vs. 3.53 ± 0.06 s respectively) but considerably increased by DOPA (50 mg/kg) vs. MPTP (50.47 ± 3.06 s vs. 3.53 ± 0.06 s respectively). Se and DOPA increased nociceptive threshold but Se alone reduced both serum and SN pro-inflammatory cytokines. Se modulates SP while DOPA modulates SP and glutamate in the SNpc of mice treated with MPTP. Se suppressed pro-inflammatory cytokines and restored the basal pain biomarkers in the SNpc of mice treated with MPTP. Se requires further study as analgesic adjuvant.

OBJECTIVE: Chronic pancreatitis (CP) is associated with debilitating refractory pain. Distinct subtypes of CP pain have been previously characterized based on severity (none, mild-moderate, severe) and temporal (none, intermittent, constant) nature of pain, but no mechanism-based tools are available to guide pain management. This exploratory study was designed to determine if potential pain biomarkers could be detected in patient serum and whether they associate with specific pain patterns.
METHODS: Cytokines, chemokines, and peptides associated with nociception and pain were measured in legacy serum samples from CP patients (N = 99) enrolled in the North American Pancreatitis Studies. The unsupervised hierarchical cluster analysis was applied to cluster CP patients based on their biomarker profile. Classification and regression tree was used to assess whether these biomarkers can predict pain outcomes.
RESULTS: The hierarchical cluster analysis revealed a subset of patients with predominantly constant, mild-moderate pain exhibited elevated interleukin-1β (IL-1β), interleukin-6 (IL-6), interleukin-2 (IL-2), tumor necrosis factor alpha (TNFα), and monocyte chemoattractant protein-1 (MCP1) whereas patients with higher interleukin-4 (IL-4), interleukin-8 (IL-8) and calcitonin gene related peptide (CGRP) were more likely to have severe pain. Interestingly, analyses of each individual biomarker revealed that patients with constant pain had reduced circulating TNFα and fractalkine. Patients with severe pain exhibited a significant reduction in TNFα as well as trends towards lower levels of IL-6 and substance P.
CONCLUSIONS: The observations from this study indicate that unique pain experiences within the chronic pancreatitis population can be associated with distinct biochemical signatures. These data indicate that further hypothesis-driven analyses combining biochemical measurements and detailed pain phenotyping could be used to develop precision approaches for pain management in patients with chronic pancreatitis.

The worlds of chronic pain and addiction continue to intersect too often in many ways. Chronic pain significantly impairs and disrupts the quality of life of millions of people worldwide. Opioids remain the most prescribed pharmacotherapy offered to patients to alleviate chronic pain. The extensive and often unnecessary prescription of opioids has created a surge in the prevalence of opioid use disorders and opioid overdose-related deaths. In this brief review, we aim to provide a bench-to-bedside overview of promising biomarkers, therapeutic targets, and challenges related to treating patients with chronic pain. We hope this review will inspire new opportunities and insights into the development of novel, nonaddictive treatments for chronic pain that will be available to patients in the near future.

This review was focused on understanding which substances inside the human body increase and decrease with increasing neuropathic pain. We reviewed various studies, and saw correlations between neuropathic pain and components of the immune system (this system defends the body against diseases and infections). Our findings will especially be useful for understanding ways to reduce or eliminate the discomfort, chronic neuropathic pain brings with it. Spinal cord stimulation (SCS) procedure is one of the few fairly efficient remedial treatments for pain. A follow-up study will apply our findings from this review to SCS, in order to understand the mechanism, and further optimize efficaciousness.

Recent studies have posited that machine learning (ML) techniques accurately classify individuals with and without pain solely based on neuroimaging data. These studies claim that self-report is unreliable, making \"objective\" neuroimaging classification methods imperative. However, the relative performance of ML on neuroimaging and self-report data have not been compared. This study used commonly reported ML algorithms to measure differences between \"objective\" neuroimaging data and \"subjective\" self-report (ie, mood and pain intensity) in their ability to discriminate between individuals with and without chronic pain. Structural magnetic resonance imaging data from 26 individuals (14 individuals with fibromyalgia and 12 healthy controls) were processed to derive volumes from 56 brain regions per person. Self-report data included visual analog scale ratings for pain intensity and mood (ie, anger, anxiety, depression, frustration, and fear). Separate models representing brain volumes, mood ratings, and pain intensity ratings were estimated across several ML algorithms. Classification accuracy of brain volumes ranged from 53 to 76%, whereas mood and pain intensity ratings ranged from 79 to 96% and 83 to 96%, respectively. Overall, models derived from self-report data outperformed neuroimaging models by an average of 22%. Although neuroimaging clearly provides useful insights for understanding neural mechanisms underlying pain processing, self-report is reliable and accurate and continues to be clinically vital.
CONCLUSIONS: The present study compares neuroimaging, self-reported mood, and self-reported pain intensity data in their ability to classify individuals with and without fibromyalgia using ML algorithms. Overall, models derived from self-reported mood and pain intensity data outperformed structural neuroimaging models.

Animals of both sexes are slaughtered for meat and meat products at the abattoirs. It has been found in few countries that one-out-of-every-three ewe and one-out-of-every-four doe with single, twin or multiple foetuses are slaughtered in registered slaughterhouses. In quest for meat, numerous viable embryos and foetuses are wasted unnoticed since the productive pregnant animals are not spared in the process. The trend in the slaughter of pregnant animals for meat (ranging from 54.5% to 70.1%) therefore calls for a review to reminisce issues on slaughter reforms, emphasize its implication on losses of genetic materials and sustainability of meat production. As a way of ensuring that welfare quality® assessment is not compromised and cruelty is prevented during animal slaughter, the quantitation of housekeeping genes and naturally occurring microRNAs (miRNAs) are recommended for identifying candidate pain biomarkers. In order to respect consumers\' right however, the manuscript suggests meat branding where the consumption of meat from pregnant animals is ethical.