11 research outputs found
Retinal Ganglion Cells With a Glaucoma OPTN(E50K) Mutation Exhibit Neurodegenerative Phenotypes when Derived from Three-Dimensional Retinal Organoids
Retinal ganglion cells (RGCs) serve as the connection between the eye and the brain, with this connection disrupted in glaucoma. Numerous cellular mechanisms have been associated with glaucomatous neurodegeneration, and useful cellular models of glaucoma allow for the precise analysis of degenerative phenotypes. Human pluripotent stem cells (hPSCs) serve as powerful tools for studying human disease, particularly cellular mechanisms underlying neurodegeneration. Thus, efforts focused upon hPSCs with an E50K mutation in the Optineurin (OPTN) gene, a leading cause of inherited forms of glaucoma. CRISPR/Cas9 gene editing introduced the OPTN(E50K) mutation into existing lines of hPSCs, as well as generating isogenic controls from patient-derived lines. RGCs differentiated from OPTN(E50K) hPSCs exhibited numerous neurodegenerative deficits, including neurite retraction, autophagy dysfunction, apoptosis, and increased excitability. These results demonstrate the utility of OPTN(E50K) RGCs as an in vitro model of neurodegeneration, with the opportunity to develop novel therapeutic approaches for glaucoma
Transcriptomic analysis of the temporal host response to skin infestation with the ectoparasitic mite Psoroptes ovis
<p>Abstract</p> <p>Background</p> <p>Infestation of ovine skin with the ectoparasitic mite <it>Psoroptes ovis </it>results in a rapid cutaneous immune response, leading to the crusted skin lesions characteristic of sheep scab. Little is known regarding the mechanisms by which such a profound inflammatory response is instigated and to identify novel vaccine and drug targets a better understanding of the host-parasite relationship is essential. The main objective of this study was to perform a combined network and pathway analysis of the <it>in vivo </it>skin response to infestation with <it>P. ovis </it>to gain a clearer understanding of the mechanisms and signalling pathways involved.</p> <p>Results</p> <p>Infestation with <it>P. </it>ovis resulted in differential expression of 1,552 genes over a 24 hour time course. Clustering by peak gene expression enabled classification of genes into temporally related groupings. Network and pathway analysis of clusters identified key signalling pathways involved in the host response to infestation. The analysis implicated a number of genes with roles in allergy and inflammation, including pro-inflammatory cytokines (<it>IL1A, IL1B, IL6, IL8 </it>and <it>TNF</it>) and factors involved in immune cell activation and recruitment (<it>SELE, SELL, SELP, ICAM1, CSF2, CSF3, CCL2 </it>and <it>CXCL2</it>). The analysis also highlighted the influence of the transcription factors NF-kB and AP-1 in the early pro-inflammatory response, and demonstrated a bias towards a Th2 type immune response.</p> <p>Conclusions</p> <p>This study has provided novel insights into the signalling mechanisms leading to the development of a pro-inflammatory response in sheep scab, whilst providing crucial information regarding the nature of mite factors that may trigger this response. It has enabled the elucidation of the temporal patterns by which the immune system is regulated following exposure to <it>P. ovis</it>, providing novel insights into the mechanisms underlying lesion development. This study has improved our existing knowledge of the host response to <it>P. ovis</it>, including the identification of key parallels between sheep scab and other inflammatory skin disorders and the identification of potential targets for disease control.</p
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A Clinical Perspective on the Automated Analysis of Reflectance Confocal Microscopy in Dermatology.
Background and objectivesNon-invasive optical imaging has the potential to provide a diagnosis without the need for biopsy. One such technology is reflectance confocal microscopy (RCM), which uses low power, near-infrared laser light to enable real-time in vivo visualization of superficial human skin from the epidermis down to the papillary dermis. Although RCM has great potential as a diagnostic tool, there is a need for the development of reliable image analysis programs, as acquired grayscale images can be difficult and time-consuming to visually assess. The purpose of this review is to provide a clinical perspective on the current state of artificial intelligence (AI) for the analysis and diagnostic utility of RCM imaging.Study design/materials and methodsA systematic PubMed search was conducted with additional relevant literature obtained from reference lists.ResultsAlgorithms used for skin stratification, classification of pigmented lesions, and the quantification of photoaging were reviewed. Image segmentation, statistical methods, and machine learning techniques are among the most common methods used to analyze RCM image stacks. The poor visual contrast within RCM images and difficulty navigating image stacks were mediated by machine learning algorithms, which allowed the identification of specific skin layers.ConclusionsAI analysis of RCM images has the potential to increase the clinical utility of this emerging technology. A number of different techniques have been utilized but further refinements are necessary to allow consistent accurate assessments for diagnosis. The automated detection of skin cancers requires more development, but future applications are truly boundless, and it is compelling to envision the role that AI will have in the practice of dermatology. Lasers Surg. Med. © 2020 Wiley Periodicals LLC
Anti-Inflammatory Effect of Pre-Elafin in Lipopolysaccharide-Induced Acute Lung Inflammation
Preinjury alcohol exposure attenuates the neuroinflammatory response to traumatic brain injury
Evaluation of diacetyl mediated pulmonary effects in physiologically relevant air-liquid interface models of human primary bronchial epithelial cells
Chemokines: novel targets for breast cancer metastasis.
Recent studies have highlighted the possible involvement of chemokines and their receptors in breast cancer progression and metastasis. Chemokines and their receptors constitute a superfamily of signalling factors whose prognosis value in breast cancer progression remains unclear. We will examine here the expression pattern of chemokines and their receptors in mammary gland physiology and carcinogenesis. The nature of the cells producing chemokines or harboring chemokine receptors appears to be crucial in certain conditions for example, the infiltration of the primary tumor by leukocytes and angiogenesis. In addition, chemokines, their receptors and the interaction with glycosaminoglycan (GAGs) are key players in the homing of cancer cells to distant metastasis sites. Several lines of evidence, including in vitro and in vivo models, suggest that the mechanism of action of chemokines in cancer development involves the modulation of proliferation, apoptosis, invasion, leukocyte recruitment or angiogenesis. Furthermore, we will discuss the regulation of chemokine network in tumor neovascularity by decoy receptors. The reasons accounting for the deregulation of chemokines and chemokine receptors expression in breast cancer are certainly crucial for the comprehension of chemokine role in breast cancer and are in several cases linked to estrogen receptor status. The targeting of chemokines and chemokine receptors by antibodies, small molecule antagonists, viral chemokine binding proteins and heparins appears as promising tracks to develop therapeutic strategies. Thus there is significant interest in developing strategies to antagonize the chemokine function, and an opportunity to interfere with metastasis, the leading cause of death in most patients