Case Report: Giant cystic schwannoma of the middle mediastinum with cervical extension

Schwannomas (neurilemmomas) are benign tumors arising from the Schwann cells of the neural sheath. They are typically, well-encapsulated lesions which rarely adhere to the adjacent structures. In the chest, schwannomas are often seen within the posterior mediastinum and commonly originating along intercostal nerves. Several operative approaches have previously been described for the resection of these tumors, including thoracoscopic techniques and posterolateral thoracotomy. We report in this case a giant cystic mediastinal schwannoma of the left recurrent laryngeal nerve with cervical extension, unresectable by the usual described approaches, which was completely removed through a cervical approach.Keywords: mediastinal tumor; schwannoma; thoracotomy; cervicotom

QT Prolongation Complicated with Torsades de Pointes in Prosthetic Mitral Valve Endocarditis: A Case Report

We present the case of a 49-year-old male patient with prosthetic mitral valve endocarditis associated with QT prolongation and torsades de pointes. He was asymptomatic until the end of January 2012, when he was admitted to our hospital emergency unit because of syncope, fever, and suspicion of endocarditis. Cardiologic evaluation was requested and the transthoracic (TTE) and transesophageal (TEE) echocardiograms revealed vegetations on the prosthetic mitral valve. All cultures were positive for methicillin-sensitive Staphylococcus aureus. The corrected QT (QTc) interval was markedly prolonged upon admission (QTc 540 ms). He experienced torsades de pointes (TdP) several times and he was recovered after bystander cardiopulmonary resuscitation. The clinical course and the long QTc interval with deep inverted T wave were completely normalized 4 weeks after. He continued on triple antibiotic therapy for 45 days with a good revolution. The clinical features and the possible mechanisms of QT prolongation (inflammation, infection) of this patient are discussed

Biodiversity Studies for Sustainable Lagoon: Thermophilic and Tropical Fish Species vs. Endemic Commercial Species at Mellah Lagoon (Mediterranean, Algeria)

Lagoons play an important socio-economic role and represent a precious natural heritage at risk from fishing pressure and chemical and biological pollution. Our research focused on better understanding the discrimination of fish biodiversity, the detection of non-indigenous species, and the valorization of commercial indigenous species at Mellah lagoon (Algeria). Taxonomic characterization and barcoding for all fish species and Inkscape schematic drawings for the most common species are provided. A total of 20 families and 37 species were recorded. The thermophilic species Coris julis, Thalassoma pavo, and Aphanius fasciatus and tropical species such as Gambusia holbrooki and Parablennius pilicornis were identified. Numerous Mediterranean species of socio-economic importance are highlighted, and detailed information is summarized for the lagoon’s sustainability. This short-term evaluation goes hand in hand with long-term programs documenting the interaction between indigenous and non-indigenous species in the lagoon and will allow the development of a provisional relationship model for future studies. Thermophilic and tropical species patterns in the Mellah lagoon are presented. Taken together, we provide useful data that can guide future investigations and may become a potential management tool for achieving the Sustainable Development Goals and protecting species with large socio-economic roles from potential thermal stress impact

Seabird surveillance: combining CCTV and artificial intelligence for monitoring and research

Ecological research and monitoring need to be able to rapidly convey information that can form the basis of scientifically sound management. Automated sensor systems, especially if combined with artificial intelligence, can contribute to such rapid high-resolution data retrieval. Here, we explore the prospects of automated methods to generate insights for seabirds, which are often monitored for their high conservation value and for being sentinels for marine ecosystem changes. We have developed a system of video surveillance combined with automated image processing, which we apply to common murres Uria aalge. The system uses a deep learning algorithm for object detection (YOLOv5) that has been trained on annotated images of adult birds, chicks and eggs, and outputs time, location, size and confidence level of all detections, frame-by-frame, in the supplied video material. A total of 144 million bird detections were generated from a breeding cliff over three complete breeding seasons (2019–2021). We demonstrate how object detection can be used to accurately monitor breeding phenology and chick growth. Our automated monitoring approach can also identify and quantify rare events that are easily missed in traditional monitoring, such as disturbances from predators. Further, combining automated video analysis with continuous measurements from a temperature logger allows us to study impacts of heat waves on nest attendance in high detail. Our automated system thus produces comparable, and in several cases significantly more detailed, data than those generated from observational field studies. By running in real time on the camera streams, it has the potential to supply researchers and managers with high-resolution up-to-date information on seabird population status. We describe how the system can be modified to fit various types of ecological research and monitoring goals and thereby provide up-to-date support for conservation and ecosystem management

Novel homozygous missense mutation in GAN associated with Charcot-Marie-Tooth disease type 2 in a large consanguineous family from Israel.

BACKGROUND: CMT-2 is a clinically and genetically heterogeneous group of peripheral axonal neuropathies characterized by slowly progressive weakness and atrophy of distal limb muscles resulting from length-dependent motor and sensory neurodegeneration. Classical giant axonal neuropathy (GAN) is an autosomal recessively inherited progressive neurodegenerative disorder of the peripheral and central nervous systems, typically diagnosed in early childhood and resulting in death by the end of the third decade. Distinctive phenotypic features are the presence of "kinky" hair and long eyelashes. The genetic basis of the disease has been well established, with over 40 associated mutations identified in the gene GAN, encoding the BTB-KELCH protein gigaxonin, involved in intermediate filament regulation. METHODS: An Illumina Human CytoSNP-12 array followed by whole exome sequence analysis was used to identify the disease associated gene mutation in a large consanguineous family diagnosed with Charcot-Marie-Tooth disease type 2 (CMT-2) from which all but one affected member had straight hair. RESULTS: Here we report the identification of a novel GAN missense mutation underlying the CMT-2 phenotype observed in this family. Although milder forms of GAN, with and without the presence of kinky hair have been reported previously, a phenotype distinct from that was investigated in this study. All family members lacked common features of GAN, including ataxia, nystagmus, intellectual disability, seizures, and central nervous system involvement. CONCLUSIONS: Our findings broaden the spectrum of phenotypes associated with GAN mutations and emphasize a need to proceed with caution when providing families with diagnostic or prognostic information based on either clinical or genetic findings alone

A multi-biometric iris recognition system based on a deep learning approach

YesMultimodal biometric systems have been widely applied in many real-world applications due to its ability to deal with a number of significant limitations of unimodal biometric systems, including sensitivity to noise, population coverage, intra-class variability, non-universality, and vulnerability to spoofing. In this paper, an efficient and real-time multimodal biometric system is proposed based on building deep learning representations for images of both the right and left irises of a person, and fusing the results obtained using a ranking-level fusion method. The trained deep learning system proposed is called IrisConvNet whose architecture is based on a combination of Convolutional Neural Network (CNN) and Softmax classifier to extract discriminative features from the input image without any domain knowledge where the input image represents the localized iris region and then classify it into one of N classes. In this work, a discriminative CNN training scheme based on a combination of back-propagation algorithm and mini-batch AdaGrad optimization method is proposed for weights updating and learning rate adaptation, respectively. In addition, other training strategies (e.g., dropout method, data augmentation) are also proposed in order to evaluate different CNN architectures. The performance of the proposed system is tested on three public datasets collected under different conditions: SDUMLA-HMT, CASIA-Iris- V3 Interval and IITD iris databases. The results obtained from the proposed system outperform other state-of-the-art of approaches (e.g., Wavelet transform, Scattering transform, Local Binary Pattern and PCA) by achieving a Rank-1 identification rate of 100% on all the employed databases and a recognition time less than one second per person

Stability of domain structures in multi-domain proteins

Multi-domain proteins have many advantages with respect to stability and folding inside cells. Here we attempt to understand the intricate relationship between the domain-domain interactions and the stability of domains in isolation. We provide quantitative treatment and proof for prevailing intuitive ideas on the strategies employed by nature to stabilize otherwise unstable domains. We find that domains incapable of independent stability are stabilized by favourable interactions with tethered domains in the multi-domain context. Stability of such folds to exist independently is optimized by evolution. Specific residue mutations in the sites equivalent to inter-domain interface enhance the overall solvation, thereby stabilizing these domain folds independently. A few naturally occurring variants at these sites alter communication between domains and affect stability leading to disease manifestation. Our analysis provides safe guidelines for mutagenesis which have attractive applications in obtaining stable fragments and domain constructs essential for structural studies by crystallography and NMR

Embracing Monogenic Parkinson's Disease: The MJFF Global Genetic PD Cohort

Background: As gene-targeted therapies are increasingly being developed for Parkinson's disease (PD), identifying and characterizing carriers of specific genetic pathogenic variants is imperative. Only a small fraction of the estimated number of subjects with monogenic PD worldwide are currently represented in the literature and availability of clinical data and clinical trial-ready cohorts is limited. Objective: The objectives are to (1) establish an international cohort of affected and unaffected individuals with PD-linked variants; (2) provide harmonized and quality-controlled clinical characterization data for each included individual; and (3) further promote collaboration of researchers in the field of monogenic PD. Methods: We conducted a worldwide, systematic online survey to collect individual-level data on individuals with PD-linked variants in SNCA, LRRK2, VPS35, PRKN, PINK1, DJ-1, as well as selected pathogenic and risk variants in GBA and corresponding demographic, clinical, and genetic data. All registered cases underwent thorough quality checks, and pathogenicity scoring of the variants and genotype–phenotype relationships were analyzed. Results: We collected 3888 variant carriers for our analyses, reported by 92 centers (42 countries) worldwide. Of the included individuals, 3185 had a diagnosis of PD (ie, 1306 LRRK2, 115 SNCA, 23 VPS35, 429 PRKN, 75 PINK1, 13 DJ-1, and 1224 GBA) and 703 were unaffected (ie, 328 LRRK2, 32 SNCA, 3 VPS35, 1 PRKN, 1 PINK1, and 338 GBA). In total, we identified 269 different pathogenic variants; 1322 individuals in our cohort (34%) were indicated as not previously published. Conclusions: Within the MJFF Global Genetic PD Study Group, we (1) established the largest international cohort of affected and unaffected individuals carrying PD-linked variants; (2) provide harmonized and quality-controlled clinical and genetic data for each included individual; (3) promote collaboration in the field of genetic PD with a view toward clinical and genetic stratification of patients for gene-targeted clinical trials. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

Using global team science to identify genetic parkinson's disease worldwide.

No abstract available