Schwartz–Jampel syndrome: comprehensive diagnostics and orthopedic treatment

Schwartz–Jampel syndrome (chondrodystrophic myotonia) is a monogenic genetic disorder, demonstrating unique coincidence of the features of skeletal dysplasia and neuromuscular disease. We present four clinical cases of Schwartz–Jampel syndrome. Principles of diagnostic and results of surgical treatment of the lower limbs deformities are discussed. Importance of this study comprises unique description of rare cases. Surgical treatment for orthopaedic conditions is important and can lead to functional improvement, prevent progression of deformities and enhance daily activity

Синдром Шварца–Джампела: опыт диагностики и ортопедического лечения

Schwartz–Jampel syndrome (chondrodystrophic myotonia) is a monogenic genetic disorder, demonstrating unique coincidence of the features of skeletal dysplasia and neuromuscular disease. We present four clinical cases of Schwartz–Jampel syndrome. Principles of diagnostic and results of surgical treatment of the lower limbs deformities are discussed. Importance of this study comprises unique description of rare cases. Surgical treatment for orthopaedic conditions is important and can lead to functional improvement, prevent progression of deformities and enhance daily activity.Синдром Шварца–Джампела (хондродистрофическая миотония) – моногенное наследственное заболевание, характеризующееся уникальным сочетанием признаков скелетной дисплазии и нейромышечного заболевания. Представлены 4 клинических случая синдрома Шварца–Джампела. Рассмотрены принципы диагностики и опыт хирургического лечения деформаций нижних конечностей. Ввиду того, что в современной научной отечественной литературе имеются единичные описания клинических примеров данного синдрома, настоящие наблюдения имеют большую значимость. Хирургическое лечение деформаций опорно-двигательного аппарата патогенетически обоснованно, так как позволяет добиться функциональных улучшений и опороспособности, предотвратить прогрессирование деформаций и контрактур, увеличивая двигательную активность пациентов

The landscape of long noncoding RNAs in the human transcriptome

Long non-coding RNAs (lncRNAs) are emerging as important regulators of tissue physiology and disease processes including cancer. In order to delineate genome-wide lncRNA expression, we curated 7,256 RNA-Seq libraries from tumors, normal tissues, and cell lines comprising over 43 terabases of sequence from 25 independent studies. We applied ab initio assembly methodology to this dataset, yielding a consensus human transcriptome of 91,013 expressed genes. Over 68% (58,648) of genes were classified as lncRNAs, of which 79% (48,952) were previously unannotated. About 1% (597) of the lncRNAs harbored ultraconserved elements and 7% (3,900) overlapped disease-associated single nucleotide polymorphisms (SNPs). To prioritize lineage-specific, disease-associated lncRNA expression we employed non-parametric differential expression testing and nominated 7,942 lineage- or cancer-associated lncRNA genes. The lncRNA landscape characterized here may shed light into normal biology and cancer pathogenesis, and be valuable for future biomarker development

Critical assessment of automated flow cytometry data analysis techniques

Traditional methods for flow cytometry (FCM) data processing rely on subjective manual gating. Recently, several groups have developed computational methods for identifying cell populations in multidimensional FCM data. The Flow Cytometry: Critical Assessment of Population Identification Methods (FlowCAP) challenges were established to compare the performance of these methods on two tasks: (i) mammalian cell population identification, to determine whether automated algorithms can reproduce expert manual gating and (ii) sample classification, to determine whether analysis pipelines can identify characteristics that correlate with external variables (such as clinical outcome). This analysis presents the results of the first FlowCAP challenges. Several methods performed well as compared to manual gating or external variables using statistical performance measures, which suggests that automated methods have reached a sufficient level of maturity and accuracy for reliable use in FCM data analysis.