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Most individuals affected with DYT1 dystonia have a heterozygous 3-bp deletion in the TOR1A gene (c.907_909delGAG). The mutation appears to act through a dominant-negative mechanism compromising normal torsinA function, and it is proposed that reducing mutant torsinA may normalize torsinA activity. In this study, we used an engineered Cas9 variant from Streptococcus pyogenes (SpCas9-VRQR) to target the mutation in the TOR1A gene in order to disrupt mutant torsinA in DYT1 patient fibroblasts. Selective targeting of the DYT1 allele was highly efficient with most common non-homologous end joining (NHEJ) edits, leading to a predicted premature stop codon with loss of the torsinA C terminus (delta 302-332 aa). Structural analysis predicted a functionally inactive status of this truncated torsinA due to the loss of residues associated with ATPase activity and binding to LULL1. Immunoblotting showed a reduction of the torsinA protein level in Cas9-edited DYT1 fibroblasts, and a functional assay using HSV infection indicated a phenotypic recovery toward that observed in control fibroblasts. These findings suggest that the selective disruption of the mutant TOR1A allele using CRISPR-Cas9 inactivates mutant torsinA, allowing the remaining wild-type torsinA to exert normal function.Decidual mechanistic target of rapamycin (mTOR) is inhibited, amino acid response (AAR) and protein kinase CK2 are activated, and IGF (insulin-like growth factor) binding protein (IGFBP)-1 is hyperphosphorylated in human intrauterine growth restriction (IUGR). Using decidualized human immortalized endometrial stromal cells (HIESC), we hypothesized that hypoxia and leucine deprivation causing inhibition of decidual IGF-1 signaling is mediated by mTOR, AAR, CK2 and IGFBP-1 phosphorylation. Mass spectrometry demonstrated that hypoxia (1% O2) or rapamycin increased IGFBP-1 phosphorylation singly at Ser101/119/169 (confirmed using immunoblotting) and dually at pSer169 + 174. Hypoxia resulted in mTOR inhibition, AAR and CK2 activation, and decreased IGF-1 bioactivity, with no additional changes with rapamycin + hypoxia. Rapamycin and/or hypoxia promoted colocalization of IGFBP-1 and CK2 (dual-immunofluorescence and proximity ligation assay). Leucine deprivation showed similar outcomes. Changes in IGFBP-1 phosphorylation regulated by mTOR/AAR signaling and CK2 may represent a novel mechanism linking oxygen and nutrient availability to IGF-1 signaling in the decidua.Accumulating studies have indicated that long non-coding RNAs (lncRNAs) play crucial roles in large amount of biological processes. Predicting lncRNA-disease associations can help biologist to understand the molecular mechanism of human disease and benefit for disease diagnosis, treatment and prevention. In this paper, we introduce a computational framework based on graph autoencoder matrix completion (GAMCLDA) to identify lncRNA-disease associations. In our method, the graph convolutional network is utilized to encode local graph structure and features of nodes for learning latent factor vectors of lncRNA and disease. Further, the inner product of lncRNA factor vector and disease factor vector is used as decoder to reconstruct the lncRNA-disease association matrix. In addition, the cost-sensitive neural network is utilized to deal with the imbalance between positive and negative samples. The experimental results show GAMLDA outperforms other state-of-the-art methods in prediction performance which is evaluated by AUC value, AUPR value, PPV and F1-score. Moreover, the case study shows our method is the effectively tool for potential lncRNA-disease prediction.Background and objective Liver segmentation from abdominal CT volumes is a primary step for computer-aided surgery and liver disease diagnosis. However, accurate liver segmentation remains a challenging task for intensity inhomogeneity and serious pathologies occurring in liver CT volume. This paper presents a novel framework for accurate liver segmentation from CT images. Methods Firstly, a novel level set integrated with intensity bias and position constraint is applied, and for normal liver, the generated liver regions are regarded as the final results. Then, for pathological liver, a sparse shape composition (SSC)-based method is presented to refine liver shapes, followed by an improved graph cut to further optimize segmentation results. The level set-based method is capable of overcoming intensity inhomogeneity in object regions, and the SSC- and graph cut-based strategy has outstanding power to address under-segmentation appearing in pathological livers. Results The experiments conducted on public databases SLIVER07 and 3Dircadb show that the proposed method can segment both healthy and pathological liver effectively. The segmentation performance in terms of mean ASD, RMSD, MSD, VOE and RVD on SLIVER07 are 0.9mm, 1.8mm, 19.4mm, 5.1% and 0.1%, respectively, and on 3Dircadb are 1.6mm, 3.1mm, 27.2mm, 9.2% and 0.5%, respectively, which outperforms many existing methods. Conclusions The proposed method does not require complex training procedure on numerous liver samples, and has satisfying and robust segmentation performance on both normal and pathological liver in various shapes.Objectives Several studies have focused on the benefits of physical activity to prevent and treat preeclampsia, given that preeclampsia and cardiovascular disease share several risk factors. However, none of these studies have been conducted in Africa. Moreover, it has been demonstrated that exercise training has preventive effects on the development of preeclampsia in mouse models. Therefore, we evaluated the association between the practice of physical activity and the development of this pathology in a Tunisian cohort. Study design Sixty-one healthy pregnant Tunisian women and 45 women with preeclampsia were recruited and completed the Pregnancy Physical Activity Questionnaire to determine their level and type of physical activity during the entire pregnancy. Main outcome measure Continuous variables were compared using the Mann-Whitney U test, while categorical variables were compared using the Chi-square test. The correlation between preeclampsia features and energy expenditure were assessed using the Pearson's correlation test. Results Energy expenditure analysis revealed that women with preeclampsia engaged in more sedentary activities than controls, while controls practiced more physical activities. Interestingly, we found a positive correlation between the total amount of energy spent and the duration of pregnancy in controls and women with preeclampsia. Conclusions Increasing physical activity is correlated with increasing pregnancy duration which is an index of maternal and fetal health. The practice of physical activities during pregnancy is associated with a healthier pregnancy, while sedentary activities is associated with the development of preeclampsia.Many seizure-free patients who consider withdrawing from antiepileptic drugs (AEDs) hope to discontinue treatment to avoid adverse effects. However, withdrawal has certain risks that are difficult to predict. In this study, we performed a literature review, summarized the causes of significant variability in the risk of postwithdrawal recurrent seizures, and reviewed study data on the age at onset, cause, types of seizures, epilepsy syndrome, magnetic resonance imaging (MRI) abnormalities, epilepsy surgery, and withdrawal outcomes of patients with epilepsy. Many factors are associated with recurrent seizures after AED withdrawal. For patients who are seizure-free after treatment, the role of an electroencephalogram (EEG) alone in ensuring safe withdrawal is limited. A series of prediction models for the postwithdrawal recurrence risk have incorporated various potentially important factors in a comprehensive analysis. We focused on the populations of studies investigating five risk prediction models and analyzed the predictive variables and recommended applications of each model, aiming to provide a reference for personalized withdrawal for patients with epilepsy in clinical practice.This work reports for the first time a significantly improved and simplified electrochemical immunoassay to detect antibodies to tick-borne encephalitis virus (TBEV) using a 96-well microtiter plate as a platform for immobilization and silver nanoparticles (AgNPs) as electrochemical labels. The electrochemical assay is performed by detecting the elemental silver oxidation signal where the electroactive signalling silver species are released from the bioconjugates (Ab@AgNP, AbS@AgNP, and ProteinA@AgNP). For this purpose, AgNPs were synthesized and further tagged with biomolecules (antibodies to TBEV, cleaved antibodies to TBEV, and protein A). Signal is read by linear sweep anodic stripping voltammetry (LSASV) of silver ions (through the electrochemical stripping of accumulated elemental silver) on a graphite electrode (GE). AbS@AgNP was chosen as the best option for the new electrochemical immunoassay. The results of electrochemical measurements demonstrated that voltammetric signal increased with the increasing concentration of target antibodies to TBEV within the range from 100 to 1600 IU mL-1, with a detection limit of 90 IU mL-1. To verify the practical application of the novel electrochemical immunosensor, the quantity of immunoglobulins against TBEV in human serum was checked. The results may contribute to the development of alternative methods for monitoring TBEV in biological fluids.High relapse rate of acute myeloid leukemia (AML) is still a crucial problem despite considerable advances in anti-cancer therapies. One crucial cause of relapse is the existence of leukemia stem cells (LSCs) with self-renewal ability, which contribute to repeated treatment resistance and recurrence. Treatments targeting LSCs, especially in combination with existing chemotherapy regimens or hematopoietic stem cell transplantation might help achieve a higher complete remission rate and improve overall survival. Many novel agents of different therapeutic strategies that aim to modulate LSCs self-renewal, proliferation, apoptosis, and differentiation are under investigation. Selleckchem MGCD0103 In this review, we summarize the latest advances of different therapies in development based on the biological characteristics of LSCs, with particular attention on natural products, synthetic compounds, antibody therapies, and adoptive cell therapies that promote the LSC eradication. We also explore the causes of AML recurrence and proposed potential strategies with new dimensions for targeting LSCs in the future.The production of fuels and other valuable chemicals via biological routes has gained significant attention during last decades. Cyanobacteria are prokaryotes that convert solar energy to chemical compounds in vivo in direct processes. Intensive studies have been carried out with the aim of engineering cyanobacteria as microfactories for solar fuel and chemical production. Engineered strains of photosynthetic cyanobacteria can produce different compounds on a proof-of-concept level, but few products show titers comparable with those achieved in heterotrophic organisms. Efficient genetic engineering tools and metabolic modeling can accelerate the development of solar fuel and chemical production in cyanobacteria. This review addresses the most recent approaches to produce solar fuels and chemicals in engineered cyanobacteria with a focus on acetyl-CoA-dependent products.