BackgroundThe diagnosis of neuromuscular diseases is strongly based on the histological characterization of muscle biopsies. However, this morphological analysis is mostly a subjective process and difficult to quantify. We have tested if network science can provide a novel framework to extract useful information from muscle biopsies, developing a novel method that analyzes muscle samples in an objective, automated, fast and precise manner.MethodsOur database consisted of 102 muscle biopsy images from 70 individuals (including controls, patients with neurogenic atrophies and patients with muscular dystrophies). We used this to develop a new method, Neuromuscular DIseases Computerized Image Analysis (NDICIA), that uses network science analysis to capture the defining signature of muscle biopsy images. NDICIA characterizes muscle tissues by representing each image as a network, with fibers serving as nodes and fiber contacts as links.ResultsAfter a ‘training’ phase with control and pathological biopsies, NDICIA was able to quantify the degree of pathology of each sample. We validated our method by comparing NDICIA quantification of the severity of muscular dystrophies with a pathologist’s evaluation of the degree of pathology, resulting in a strong correlation (R = 0.900, P <0.00001). Importantly, our approach can be used to quantify new images without the need for prior ‘training’. Therefore, we show that network science analysis captures the useful information contained in muscle biopsies, helping the diagnosis of muscular dystrophies and neurogenic atrophies.ConclusionsOur novel network analysis approach will serve as a valuable tool for assessing the etiology of muscular dystrophies or neurogenic atrophies, and has the potential to quantify treatment outcomes in preclinical and clinical trials.

BackgroundMutations in pre-mRNA splicing factor PRPF31 can lead to retinitis pigmentosa (RP). Although the exact disease mechanism remains unknown, it has been hypothesized that haploinsufficiency might be involved in the pathophysiology of the disease.MethodsIn this study, we have analyzed a mouse model containing the p.A216P mutation in Prpf31 gene.ResultsWe found that mutant Prpf31 protein produces cytoplasmic aggregates in the retinal pigment epithelium and decreasing the protein levels of this splicing factor in the nucleus. Additionally, normal protein was recruited in insoluble aggregates when the mutant protein was overexpressed in vitro. In response to protein aggregation, Hspa4l is overexpressed. This member of the HSP70 family of chaperones might contribute to the correct folding and solubilization of the mutant protein, allowing its translocation to the nucleus.ConclusionsOur data suggests that a mechanism haploinsufficiency and dominant-negative is involved in retinal degeneration due to mutations in PRPF31. HSP70 over-expression might be a new therapeutic target for the treatment of retinal degeneration due to PRPF31 mutations.

The striatum integrates motor behavior using a well‐defined microcircuit whose individual components are independently affected in several neurological diseases. The glial cell line‐derived neurotrophic factor (GDNF), synthesized by striatal interneurons, and Sonic hedgehog (Shh), produced by the dopaminergic neurons of the substantia nigra (DA SNpc), are both involved in the nigrostriatal maintenance but the reciprocal neurotrophic relationships among these neurons are only partially understood. To define the postnatal neurotrophic connections among fast‐spiking GABAergic interneurons (FS), cholinergic interneurons (ACh), and DA SNpc, we used a genetically induced mouse model of postnatal DA SNpc neurodegeneration and separately eliminated Smoothened (Smo), the obligatory transducer of Shh signaling, in striatal interneurons. We show that FS postnatal survival relies on DA SNpc and is independent of Shh signaling. On the contrary, Shh signaling but not dopaminergic striatal innervation is required to maintain ACh in the postnatal striatum. ACh are required for DA SNpc survival in a GDNF‐independent manner. These data demonstrate the existence of three parallel but interdependent neurotrophic relationships between SN and striatal interneurons, partially defined by Shh and GDNF. The definition of these new neurotrophic interactions opens the search for new molecules involved in the striatal modulatory circuit maintenance with potential therapeutic value.

Abstract. Diagnosis of neuromuscular diseases is based on subjective visual assessment of biopsies from patients by the pathologist specialist. A system for objective analysis and classification of muscular dystrophies and neurogenic atrophies through muscle biopsy images of fluorescence microscopy is presented. The procedure starts with an accurate segmentation of the muscle fibers using mathematical morphology and a watershed transform. A feature extraction step is carried out in two parts: 24 features that pathologists take into account to diagnose the diseases and 58 structural features that the human eye cannot see, based on the assumption that the biopsy is considered as a graph, where the nodes are represented by each fiber, and two nodes are connected if two fibers are adjacent. A feature selection using sequential forward selection and sequential backward selection methods, a classification using a Fuzzy ARTMAP neural network, and a study of grading the severity are performed on these two sets of features. A database consisting of 91 images was used: 71 images for the training step and 20 as the test. A classification error of 0% was obtained. It is concluded that the addition of features undetectable by the human visual inspection improves the categorization of atrophic patterns.

Background: Gene therapy is a therapeutic possibility for retinitis pigmentosa (RP), in which therapeutic transgenes are currently delivered to the retina by adeno-associated viral vectors (AAVs). Although their safety and efficacy have been demonstrated in both clinical and preclinical settings, AAVs present some technical handicaps, such as limited cargo capacity and possible immunogenicity in repetitive doses. The development of alternative, non-viral delivery platforms like nanoparticles is of great interest to extend the application of gene therapy for RP. Methods: Amino-functionalized mesoporous silica-based nanoparticles (N-MSiNPs) were synthesized, physico-chemically characterized, and evaluated as gene delivery systems for human cells in vitro and for retinal cells in vivo. Transgene expression was evaluated by WB and immunofluorescence. The safety evaluation of mice subjected to subretinal injection was assessed by ophthalmological tests (electroretinogram, funduscopy, tomography, and optokinetic test). Results: N-MSiNPs delivered transgenes to human cells in vitro and to retinal cells in vivo. No adverse effects were detected for the integrity of the retinal tissue or the visual function of treated eyes. N-MSiNPs were able to deliver a therapeutic transgene candidate for RP, PRPF31, both in vitro and in vivo. Conclusions: N-MSiNPs are safe for retinal delivery and thus a potential alternative to viral vectors.

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