73 research outputs found

    Transplantation of Specific Human Astrocytes Promotes Functional Recovery after Spinal Cord Injury

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    Repairing trauma to the central nervous system by replacement of glial support cells is an increasingly attractive therapeutic strategy. We have focused on the less-studied replacement of astrocytes, the major support cell in the central nervous system, by generating astrocytes from embryonic human glial precursor cells using two different astrocyte differentiation inducing factors. The resulting astrocytes differed in expression of multiple proteins thought to either promote or inhibit central nervous system homeostasis and regeneration. When transplanted into acute transection injuries of the adult rat spinal cord, astrocytes generated by exposing human glial precursor cells to bone morphogenetic protein promoted significant recovery of volitional foot placement, axonal growth and notably robust increases in neuronal survival in multiple spinal cord laminae. In marked contrast, human glial precursor cells and astrocytes generated from these cells by exposure to ciliary neurotrophic factor both failed to promote significant behavioral recovery or similarly robust neuronal survival and support of axon growth at sites of injury. Our studies thus demonstrate functional differences between human astrocyte populations and suggest that pre-differentiation of precursor cells into a specific astrocyte subtype is required to optimize astrocyte replacement therapies. To our knowledge, this study is the first to show functional differences in ability to promote repair of the injured adult central nervous system between two distinct subtypes of human astrocytes derived from a common fetal glial precursor population. These findings are consistent with our previous studies of transplanting specific subtypes of rodent glial precursor derived astrocytes into sites of spinal cord injury, and indicate a remarkable conservation from rat to human of functional differences between astrocyte subtypes. In addition, our studies provide a specific population of human astrocytes that appears to be particularly suitable for further development towards clinical application in treating the traumatically injured or diseased human central nervous system

    Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

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    Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified
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