GNE myopathy is an adult-onset degenerative muscle disease that leads to extreme disability in patients. Biallelic mutations in the rate-limiting enzyme UDP-N-acetylglucosamine-2-epimerase/N-acetylmannosamine-kinase (GNE) of sialic acid (SA) biosynthetic pathway, was shown to be the cause of this disease. Other genetic disorders with muscle pathology where defects in glycosylation are known. It is yet not clear why a defect in SA biosynthesis and glycosylation affect muscle cells selectively even though they are ubiquitously present in all tissues. Here we have comprehensively examined the complete SA metabolic pathway involving biosynthesis, sialylation, salvage, and catabolism. To understand the reason for tissue-specific phenotype caused by mutations in genes of this pathway, we analysed the expression of different SA pathway genes in various tissues, during the muscle tissue development and in muscle tissues from GNE myopathy patients (p.Met743Thr) using publicly available databases. We have also analysed gene co-expression networks with GNE in different tissues as well as gene interactions that are unique to muscle tissues only. The results do show a few muscle specific interactions involving ANLN, MYO16 and PRAMEF25 that could be involved in specific phenotype. Overall, our results suggest that SA biosynthetic and catabolic genes are expressed at a very low level in skeletal muscles that also display a unique gene interaction network.
  Ongoing advances in our understanding of neuroendocrine tumor (NET) biology, genetics, and immunology, will continue to expand the availability of targeted therapies, thus improving the outcomes of patients. Well-differentiated neuroendocrine tumors (NETs) are grouped into pancreatic and non-pancreatic NETs (includes GI and thoracic NETs) for treatment considerations (Fig.1). For panNETs, initial therapy is driven by the need of radiographic response, and targeted agents are typically reserved for second and third line based on the toxicity profile. Treatment options for non-pancreatic NETs are also expanding and while SSAs are the typical first-line option, everolimus and PRRT both remain approved therapies for future lines, and VEGF TKIs are showing promising results in research settings. Sequencing these agents and best time to incorporate peptide receptor radio therapy into the management algorithm remains an unmet need.
 Ongoing advances in our understanding of neuroendocrine tumor (NET) biology, genetics, and immunology, will continue to expand the availability of targeted therapies, thus improving the outcomes of patients. Well-differentiated neuroendocrine tumors (NETs) are grouped into pancreatic and non-pancreatic NETs (includes GI and thoracic NETs) for treatment considerations (Fig. 1). For panNETs, initial therapy is driven by the need of radiographic response, and targeted agents are typically reserved for second and third line based on the toxicity profile. Treatment options for non-pancreatic NETs are also expanding and while SSAs are the typical first-line option, everolimus and PRRT both remain approved therapies for future lines, and VEGF TKIs are showing promising results in research settings. Sequencing these agents and best time to incorporate peptide receptor radio therapy into the management algorithm remains an unmet need.
  The Severity Indices of Personality Problems 118 (SIPP-118) is a self-report questionnaire that aims to measure core components of (mal)adaptive personality functioning that can change over time. In this study, we aimed to assess the facet strength of the 16 facets across three large clinical samples.
 
  Data from Norwegian and Dutch psychiatric patients were analyzed in this international multi-center study (N
  = 2814, N
  = 4751, N
  = 2217). Bi-factor modeling was used to assess to what degree the SIPP items tap into an overall general factor. The incremental value (distinctiveness) of the facets was studied using proportional reduction in mean squared error (PRMSE) based statistics.
 
  The estimated model showed adequate fit. The explained common variance (ECV) attributable to the general factor equaled 50% for all three samples. All but two facets (stable self-image and frustration tolerance) showed sufficient levels of distinctiveness. The findings were observed to be comparable across the three samples.
 
  Our findings showed that the general factor was relatively weak, and the facets had a clear incremental value.
 Our findings showed that the general factor was relatively weak, and the facets had a clear incremental value.The COVID-19 pandemic has created a sense of threat, and stress that has surged globally at an alarming pace. University students were confronted with new challenges. This study examined university students' functional difficulties and concerns during COVID-19 pandemic in two countries Israel and Ukraine. Additionally, it examined the similarities and differences in prediction of COVID-related concerns in both countries. Two large samples of university students were drawn from both countries.  https://www.selleckchem.com/products/tasquinimod.html  Results showed that students' main functional difficulties in both countries were worries about their family health status and their learning assignments. In both countries, COVID-related functional difficulties and stress associated with exposure to the media added a significant amount of the explained variance of COVID-related concerns after controlling for background variables. In conclusion-while the level of exposure and difficulties may differ by country and context, their associations with students' concerns seem robust. Additionally, repeated exposure to media coverage about a community threat can lead to increased anxiety.
  Neurosurgeons can have a better understanding of surgical procedures by comparing ultrasound images obtained at different phases of the tumor resection. However, establishing a direct mapping between subsequent acquisitions is challenging due to the anatomical changes happening during surgery. We propose here a method to improve the registration of ultrasound volumes, by excluding the resection cavity from the registration process.
 
  The first step of our approach includes the automatic segmentation of the resection cavities in ultrasound volumes, acquired during and after resection. We used a convolution neural network inspired by the 3D U-Net. Then, subsequent ultrasound volumes are registered by excluding the contribution of resection cavity.
 
  Regarding the segmentation of the resection cavity, the proposed method achieved a mean DICE index of 0.84 on 27 volumes. Concerning the registration of the subsequent ultrasound acquisitions, we reduced the mTRE of the volumes acquired before and during resection from 3.