Macrophage-sensory neuronal interaction in HIV-1 gp120-induced neurotoxicity

Acknowledgements We thank Dr Jim Perkins of University College London for his help with the statistical analysis of our gene array data. We thank Prof. Maria Papathanasopoulos from the University of the Witwatersrand, Johannesburg, for the gift of gp120Bal.Peer reviewedPublisher PD

Axonal swellings are related to type 2 diabetes, but not to distal diabetic sensorimotor polyneuropathy

Aims/hypothesis Distal diabetic sensorimotor polyneuropathy (DSP) is a common complication of diabetes with many patients showing a reduction of intraepidermal nerve fibre density (IENFD) from skin biopsy, a validated and sensitive diagnostic tool for the assessment of DSP. Axonal swelling ratio is a morphological quantification altered in DSP. It is, however, unclear if axonal swellings are related to diabetes or DSP. The aim of this study was to investigate how axonal swellings in cutaneous nerve fibres are related to type 2 diabetes mellitus, DSP and neuropathic pain in a well-defined cohort of patients diagnosed with type 2 diabetes. Methods A total of 249 participants, from the Pain in Neuropathy Study (UK) and the International Diabetic Neuropathy Consortium (Denmark), underwent a structured neurological examination, nerve conduction studies, quantitative sensory testing and skin biopsy. The study included four groups: healthy control study participants without diabetes (n = 45); participants with type 2 diabetes without DSP (DSP−; n = 31); and participants with evidence of DSP (DSP+; n = 173); the last were further separated into painless DSP+ (n = 74) and painful DSP+ (n = 99). Axonal swellings were defined as enlargements on epidermal-penetrating fibres exceeding 1.5 μm in diameter. Axonal swelling ratio is calculated by dividing the number of axonal swellings by the number of intraepidermal nerve fibres. Results Median (IQR) IENFD (fibres/mm) was: 6.7 (5.2–9.2) for healthy control participants; 6.2 (4.4–7.3) for DSP−; 1.3 (0.5–2.2) for painless DSP+; and 0.84 (0.4–1.6) for painful DSP+. Swelling ratios were calculated for all participants and those with IENFD > 1.0 fibre/mm. When only those participants with IENFD > 1.0 fibre/mm were included, the axonal swelling ratio was higher in participants with type 2 diabetes when compared with healthy control participants (p < 0.001); however, there was no difference between DSP− and painless DSP+ participants, or between painless DSP+ and painful DSP+ participants. The axonal swelling ratio correlated weakly with HbA1c (r = 0.16, p = 0.04), but did not correlate with the Toronto Clinical Scoring System (surrogate measure of DSP severity), BMI or type 2 diabetes duration. Conclusions/interpretation In individuals with type 2 diabetes where IENFD is >1.0 fibre/mm, axonal swelling ratio is related to type 2 diabetes but is not related to DSP or painful DSP. Axonal swellings may be an early marker of sensory nerve injury in type 2 diabetes

Comparison of psychological and physical function in neuropathic pain and nociceptive pain: implications for cognitive behavioral pain management programs

Research has increased our understanding of the psychological and physical functioning associated with persistent pain and has facilitated the development of cognitive behavioral pain management programs to help improve people’s physical function and decrease their distress in the presence of persistent pain. The majority of this research has focused on nociceptive pain or pain of mixed etiology. There has been less focus on these aspects of neuropathic pain. It is possible that differences exist in the function and difficulties associated with nociceptive and neuropathic pain. These differences may be associated with our clinical observation that some people with neuropathic pain have difficulty applying some aspects of the theory and practice of cognitive behavioral pain management. The purpose of this study was to compare a single neuropathic pain condition (post-herpetic neuralgia) with a persistent pain of nociceptive origin (low back pain) and determine whether differences exist in: (1) physical and psychological function; (2) factors that increase difficulties; (3) responses to pain; (4) beliefs about pain and (5) problems experienced. The results suggest that the differences between the two groups were not on the major variables of pain, mood, cognition and physical function. The main differences were in factors that increase pain, people’s responses to pain, their beliefs about diagnosis and the cause of pain and the problems they reported as a result of experiencing pain. The implications of our findings for the development of cognitive behavioral pain management programs for people with neuropathic pain are discussed

Cytokine q-RT-PCR, c-Fos immunoreactivity and open field behaviour data in rats following bladder inflammation

<p>Dataset 1: Cytokine Up-regulation following Acute Bladder Inflammation<br>Legend: .csv file containing q-RT-PCR cycle time (CT) for each of the 92 inflammatory mediators and 4 housekeeping genes. Delta CT (dCT) and fold change (FC) values are shown for each. Exclusions are denoted by * by the sample or transcript ID.</p> <p>Dataset 2: Cytokine Up-regulation following Repeated Bladder Inflammation<br>Legend: .csv file containing q-RT-PCR cycle time (CT) for each of the 92 inflammatory mediators and 4 housekeeping genes. Delta CT (dCT) and fold change (FC) values are shown for each. Exclusions are denoted by * by the sample or transcript ID.</p> <p>Dataset 3: Open Field activity following Acute Bladder Inflammation<br>Legend: .zip file containing 15 minute videos of open field behaviour in rats 24hrs after acute bladder inflammation (36). File naming reflects individual animal IDs to maintain blinding. Group allocation data available on request from F1000Research.<br>Each file was edited using Adobe Premiere (Creative Cloud) as follows: • A 10 second ‘lead-in’ period prior to introduction of the animal was edited in, either by trimming from the start of the video to a point 10 seconds before introduction of the animal, or by stretching the footage prior to introduction of the animal to a 10 second duration<br>• The arena was straightened, making it easier for others analysing the dataset as only a single arena template is required during automated analysis e.g. using Ethovision, Noldus Software, The Netherlands<br>• File formats were converted from .mpg to .mp4 to reduce the file size (from ~200MB to ~50MB)</p> <p>Dataset 4: Open Field activity following Repeated Bladder Inflammation<br>Legend: .zip file containing 15 minute videos of open field behaviour in rats 24hrs after (38). File naming reflects individual animal IDs to maintain blinding. Group allocation data available on request from F1000Research.<br>Each file has been edited using Adobe Premiere (Creative Cloud) as follows: • A 10 second ‘lead-in’ period prior to introduction of the animal was edited in, either by trimming from the start of the video to a point 10 seconds before introduction of the animal, or by stretching the footage prior to introduction of the animal to a 10 second duration<br>• The arena was straightened, making it easier for others analysing the dataset as only a single arena template is required during automated analysis e.g. using Ethovision, Noldus Software, The Netherlands<br>• File formats were converted from .mpg to .mp4 to reduce the file size (from ~200MB to ~50MB)</p> <p> </p> <p>Dataset 5: c-Fos Immunoreactivity in the Central Amygdala following Acute Bladder Inflammation<br>Legend: .csv file containing area, count, and density data for c-Fos immunoreactivity in the central amygdala. This data underwent extensive manipulation prior to analysis: density values for each subnuclei were pooled for each rostro-caudal level, and used in combination with individual subnuclei data to calculate overall density values.</p> <p>Dataset 6: c-Fos Immunoreactivity in the Central Amygdala following Repeated Bladder Inflammation<br>Legend: .csv file containing area, count, and density data for c-Fos immunoreactivity in the central amygdala.<br>This data underwent extensive manipulation prior to analysis: density values for each subnuclei were pooled for each rostro-caudal level, and used in combination with individual subnuclei data to calculate overall density values.</p> <p> </p