Sensory phenotypes in complex regional pain syndrome and chronic low back pain-indication of common underlying pathomechanisms.

INTRODUCTION First-line pain treatment is unsatisfactory in more than 50% of chronic pain patients, likely because of the heterogeneity of mechanisms underlying pain chronification. OBJECTIVES This cross-sectional study aimed to better understand pathomechanisms across different chronic pain cohorts, regardless of their diagnoses, by identifying distinct sensory phenotypes through a cluster analysis. METHODS We recruited 81 chronic pain patients and 63 age-matched and sex-matched healthy controls (HC). Two distinct chronic pain cohorts were recruited, ie, complex regional pain syndrome (N = 20) and low back pain (N = 61). Quantitative sensory testing (QST) was performed in the most painful body area to investigate somatosensory changes related to clinical pain. Furthermore, QST was conducted in a pain-free area to identify remote sensory alterations, indicating more widespread changes in somatosensory processing. RESULTS Two clusters were identified based on the QST measures in the painful area, which did not represent the 2 distinct pain diagnoses but contained patients from both cohorts. Cluster 1 showed increased pain sensitivities in the painful and control area, indicating central sensitization as a potential pathomechanism. Cluster 2 showed a similar sensory profile as HC in both tested areas. Hence, either QST was not sensitive enough and more objective measures are needed to detect sensitization within the nociceptive neuraxis or cluster 2 may not have pain primarily because of sensitization, but other factors such as psychosocial ones are involved. CONCLUSION These findings support the notion of shared pathomechanisms irrespective of the pain diagnosis. Conversely, different mechanisms might contribute to the pain of patients with the same diagnosis

The evaluation of exposure risks for natural transmission of scrapie within an infected flock

Background: Although the epidemiology of scrapie has been broadly understood for many years, attempts to introduce voluntary or compulsory controls to eradicate the disease have frequently failed. Lack of precision in defining the risk factors on farm has been one of the challenges to designing control strategies. This study attempted to define which parts of the annual flock management cycle represented the greatest risk of infection to naive lambs exposed to the farm environment at different times.Results: In VRQ/VRQ lambs exposed to infected sheep at pasture or during lambing, and exposed to the buildings in which lambing took place, the attack rate was high and survival times were short. Where exposure was to pasture alone the number of sheep affected in each experimental group was reduced, and survival times were longer and related to length of exposure.Conclusion: At the flock level, eradication and control strategies for scrapie must take into account the need to decontaminate buildings used for lambing, and to reduce (or prevent) the exposure of lambs to infected sheep, especially in the later stages of incubation, and at lambing. The potential for environmental contamination from pasture should also be considered. Genotype selection may still prove to be the only viable tool to prevent infection from contaminated pasture, reduce environmental contamination and limit direct transmission from sheep to sheep

Three decades of post-logging tree community recovery in naturally regenerating and actively restored dipterocarp forest in Borneo

Selective logging has affected large areas of tropical forests and there is increasing interest in how to manage selectively logged forests to enhance recovery. However, the impacts of logging and active restoration, by liberation cutting and enrichment planting, on tree community composition are poorly understood compared to trajectories of biomass recovery. Here, we assess the long-term impacts of selective logging and active restoration for biomass recovery on tree species diversity, community composition, and forest structure. We censused all stems ≥2 cm diameter at breast height (DBH) on 46 permanent plots in unlogged, primary forest in the Danum Valley Conservation Area (DVCA; 12 plots, totalling 0.6 ha) and in sites logged 23–35 years prior to the census in the Ulu Segama Forest Reserve adjacent to DVCA (34 plots, totalling 1.7 ha) in Sabah, Malaysian Borneo. Active restoration treatments, including enrichment planting and climber cutting, were implemented on 17 of the logged forest plots 12–24 years prior to the census. Total plot-level basal area and pole (5–10 cm DBH) stem density were lower in logged than unlogged forests, however no difference was found in stem density amongst saplings (2–5 cm DBH) or established trees (≥10 cm DBH). Neither basal area, nor plot-level stem density varied with time since logging at any size class, although sapling and pole stem densities were lower in actively restored than naturally regenerating logged forest. Sapling species diversity was lower in logged than unlogged forest, however there were no other significant effects of logging on tree species richness or diversity indices. Tree species composition, however, differed between logged and unlogged forests across all stem size classes (PERMANOVA), reflected by 23 significant indicator species that were only present in unlogged forest. PERMANOVA tests revealed no evidence that overall species composition changed with time since logging or with active restoration treatments at any size class. However, when naturally regenerating and actively restored communities were compared, two indicator species were identified in naturally regenerating forest and three in actively restored forests. Together our results suggest that selective logging has a lasting effect on tree community composition regardless of active restoration treatments and, even when species richness and diversity are stable, species composition remains distinct from unlogged forest for more than two decades post-harvest. Active restoration efforts should be targeted, monitored, and refined to try to ensure positive outcomes for multiple metrics of forest recovery

Self-collecting a cervico-vaginal specimen for cervical cancer screening: An exploratory study of acceptability among medically underserved women in rural Appalachia

Innovative screening methods such as self-testing for human papillomavirus (HPV) may alleviate barriers to cervical cancer screening. The purpose of this exploratory study was to determine whether Appalachian Kentucky women would be amenable to self-collecting a cervico-vaginal specimen for HPV testing

CD11c+ Cells Are Gatekeepers for Lymphocyte Trafficking to Infiltrated Islets During Type 1 Diabetes.

Type 1 diabetes (T1D) is a T cell mediated autoimmune disease that affects more than 19 million people with incidence increasing rapidly worldwide. For T cells to effectively drive T1D, they must first traffic to the islets and extravasate through the islet vasculature. Understanding the cues that lead to T cell entry into inflamed islets is important because diagnosed T1D patients already have established immune infiltration of their islets. Here we show that CD11

CD11c+ Cells Are Gatekeepers for Lymphocyte Trafficking to Infiltrated Islets During Type 1 Diabetes

Type 1 diabetes (T1D) is a T cell mediated autoimmune disease that affects more than 19 million people with incidence increasing rapidly worldwide. For T cells to effectively drive T1D, they must first traffic to the islets and extravasate through the islet vasculature. Understanding the cues that lead to T cell entry into inflamed islets is important because diagnosed T1D patients already have established immune infiltration of their islets. Here we show that CD11c+ cells are a key mediator of T cell trafficking to infiltrated islets in non-obese diabetic (NOD) mice. Using intravital 2-photon islet imaging we show that T cell extravasation into the islets is an extended process, with T cells arresting in the islet vasculature in close proximity to perivascular CD11c+ cells. Antigen is not required for T cell trafficking to infiltrated islets, but T cell chemokine receptor signaling is necessary. Using RNAseq, we show that islet CD11c+ cells express over 20 different chemokines that bind chemokine receptors expressed on islet T cells. One highly expressed chemokine-receptor pair is CXCL16-CXCR6. However, NOD. CXCR6−/− mice progressed normally to T1D and CXCR6 deficient T cells trafficked normally to the islets. Even with CXCR3 and CXCR6 dual deficiency, T cells trafficked to infiltrated islets. These data reinforce that chemokine receptor signaling is highly redundant for T cell trafficking to inflamed islets. Importantly, depletion of CD11c+ cells strongly inhibited T cell trafficking to infiltrated islets of NOD mice. We suggest that targeted depletion of CD11c+ cells associated with the islet vasculature may yield a therapeutic target to inhibit T cell trafficking to inflamed islets to prevent progression of T1D

Initiating Evaluation of Composite Outcome Measures for Psoriatic Arthritis:2022 Updates From the GRAPPA-OMERACT Working Group

The Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA)-Outcome Measures in Rheumatology (OMERACT) Psoriatic Arthritis (PsA) working group-comprising rheumatologists, dermatologists, methodologists, and patient research partners-provided updates at the GRAPPA 2022 annual meeting on its work to evaluate composite outcome measures for PsA. Ten composite outcome measures were considered. Initial steps were to define the population, the purpose of use, and the proposed pros and cons of the 10 candidate composite instruments for PsA. Preliminary Delphi exercises within the working group and GRAPPA stakeholders confirmed high priority for evaluating minimal disease activity (MDA); moderate priority for Disease Activity in PsA (DAPSA), American College of Rheumatology (ACR) response criteria, Psoriatic Arthritis Disease Activity Score (PASDAS), Composite Psoriatic Disease Activity Index (CPDAI), 3 visual analog scale (VAS), and 4VAS; and low priority for Disease Activity Score in 28 joints (DAS28), Psoriatic Arthritis Responder Criteria (PsARC), and Routine Assessment of Patient Index Data 3 (RAPID3). Further appraisal of candidate composite instruments is ongoing.</p

GA4GH Phenopackets: A Practical Introduction.

The Global Alliance for Genomics and Health (GA4GH) is developing a suite of coordinated standards for genomics for healthcare. The Phenopacket is a new GA4GH standard for sharing disease and phenotype information that characterizes an individual person, linking that individual to detailed phenotypic descriptions, genetic information, diagnoses, and treatments. A detailed example is presented that illustrates how to use the schema to represent the clinical course of a patient with retinoblastoma, including demographic information, the clinical diagnosis, phenotypic features and clinical measurements, an examination of the extirpated tumor, therapies, and the results of genomic analysis. The Phenopacket Schema, together with other GA4GH data and technical standards, will enable data exchange and provide a foundation for the computational analysis of disease and phenotype information to improve our ability to diagnose and conduct research on all types of disorders, including cancer and rare diseases

GA4GH Phenopackets: A Practical Introduction

The Global Alliance for Genomics and Health (GA4GH) is developing a suite of coordinated standards for genomics for healthcare. The Phenopacket is a new GA4GH standard for sharing disease and phenotype information that characterizes an individual person, linking that individual to detailed phenotypic descriptions, genetic information, diagnoses, and treatments. A detailed example is presented that illustrates how to use the schema to represent the clinical course of a patient with retinoblastoma, including demographic information, the clinical diagnosis, phenotypic features and clinical measurements, an examination of the extirpated tumor, therapies, and the results of genomic analysis. The Phenopacket Schema, together with other GA4GH data and technical standards, will enable data exchange and provide a foundation for the computational analysis of disease and phenotype information to improve our ability to diagnose and conduct research on all types of disorders, including cancer and rare diseases

Fifteen new risk loci for coronary artery disease highlight arterial-wall-specific mechanisms

Coronary artery disease (CAD) is a leading cause of morbidity and mortality worldwide. Although 58 genomic regions have been associated with CAD thus far, most of the heritability is unexplained, indicating that additional susceptibility loci await identification. An efficient discovery strategy may be larger-scale evaluation of promising associations suggested by genome-wide association studies (GWAS). Hence, we genotyped 56,309 participants using a targeted gene array derived from earlier GWAS results and performed meta-analysis of results with 194,427 participants previously genotyped, totaling 88,192 CAD cases and 162,544 controls. We identified 25 new SNP-CAD associations (P &lt; 5 × 10(-8), in fixed-effects meta-analysis) from 15 genomic regions, including SNPs in or near genes involved in cellular adhesion, leukocyte migration and atherosclerosis (PECAM1, rs1867624), coagulation and inflammation (PROCR, rs867186 (p.Ser219Gly)) and vascular smooth muscle cell differentiation (LMOD1, rs2820315). Correlation of these regions with cell-type-specific gene expression and plasma protein levels sheds light on potential disease mechanisms