Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

The Impact of Exercise on Cardiotoxicity in Pediatric and Adolescent Cancer Survivors: A Scoping Review

Childhood and adolescent cancer survivors are disproportionately more likely to develop cardiovascular diseases from the late effects of cardiotoxic therapies (e.g., anthracycline-based chemotherapy and chest-directed radiotherapy). Currently, dexrazoxane is the only approved drug for preventing cancer treatment-related cardiac damage. While animal models highlight the beneficial effects of exercise cancer treatment-related cardiac dysfunction, few clinical studies have been conducted. Thus, the objective of this scoping review was to explore the designs and impact of exercise-based interventions for managing cancer treatment-related cardiac dysfunction in childhood and adolescent cancer survivors. Reviewers used Joanna Briggs Institute’s methodology to identify relevant literature. Then, 4616 studies were screened, and three reviewers extracted relevant data from six reports. Reviewers found that exercise interventions to prevent cancer treatment-related cardiac dysfunction in childhood and adolescent cancer survivors vary regarding frequency, intensity, time, and type of exercise intervention. Further, the review suggests that exercise promotes positive effects on managing cancer treatment-related cardiac dysfunction across numerous indices of heart health. However, the few clinical studies employing exercise interventions for childhood and adolescent cancer survivors highlight the necessity for more research in this area

The Prognostic Effect of Immune Cell Infiltration Depends on Molecular Subtype in Endometrioid Ovarian Carcinomas.

PURPOSE: Endometrioid ovarian carcinoma (ENOC) is the second most-common type of ovarian carcinoma, comprising 10%-20% of cases. Recently, the study of ENOC has benefitted from comparisons to endometrial carcinomas including defining ENOC with four prognostic molecular subtypes. Each subtype suggests differential mechanisms of progression, although tumor-initiating events remain elusive. There is evidence that the ovarian microenvironment may be critical to early lesion establishment and progression. However, while immune infiltrates have been well studied in high-grade serous ovarian carcinoma, studies in ENOC are limited. EXPERIMENTAL DESIGN: We report on 210 ENOC, with clinical follow-up and molecular subtype annotation. Using multiplex IHC and immunofluorescence, we examine the prevalence of T-cell lineage, B-cell lineage, macrophages, and populations with programmed cell death protein 1 or programmed death-ligand 1 across subtypes of ENOC. RESULTS: Immune cell infiltrates in tumor epithelium and stroma showed higher densities in ENOC subtypes with known high mutation burden (POLEmut and MMRd). While molecular subtypes were prognostically significant, immune infiltrates were not (overall survival P > 0.2). Analysis by molecular subtype revealed that immune cell density was prognostically significant in only the no specific molecular profile (NSMP) subtype, where immune infiltrates lacking B cells (TILB minus) had inferior outcome (disease-specific survival: HR, 4.0; 95% confidence interval, 1.1-14.7; P < 0.05). Similar to endometrial carcinomas, molecular subtype stratification was generally superior to immune response in predicting outcomes. CONCLUSIONS: Subtype stratification is critical for better understanding of ENOC, in particular the distribution and prognostic significance of immune cell infiltrates. The role of B cells in the immune response within NSMP tumors warrants further study

Emotional processing in Parkinson's disease and anxiety: an EEG study of visual affective word processing

A general problem in the design of an EEG-BCI system is the poor quality and low robustness of the extracted features, affecting overall performance. However, BCI systems that are applicable in real-time and outside clinical settings require high performance. Therefore, we have to improve the current methods for feature extraction. In this work, we investigated EEG source reconstruction techniques to enhance the extracted features based on a linearly constrained minimum variance (LCMV) beamformer. Beamformers allow for easy incorporation of anatomical data and are applicable in real-time. A 32-channel EEG-BCI system was designed for a two-class motor imagery (MI) paradigm. We optimized a synchronous system for two untrained subjects and investigated two aspects. First, we investigated the effect of using beamformers calculated on the basis of three different head models: a template 3-layered boundary element method (BEM) head model, a 3-layered personalized BEM head model and a personalized 5-layered finite difference method (FDM) head model including white and gray matter, CSF, scalp and skull tissue. Second, we investigated the influence of how the regions of interest, areas of expected MI activity, were constructed. On the one hand, they were chosen around electrodes C3 and C4, as hand MI activity theoretically is expected here. On the other hand, they were constructed based on the actual activated regions identified by an fMRI scan. Subsequently, an asynchronous system was derived for one of the subjects and an optimal balance between speed and accuracy was found. Lastly, a real-time application was made. These systems were evaluated by their accuracy, defined as the percentage of correct left and right classifications. From the real-time application, the information transfer rate (ITR) was also determined. An accuracy of 86.60 ± 4.40% was achieved for subject 1 and 78.71 ± 0.73% for subject 2. This gives an average accuracy of 82.66 ± 2.57%. We found that the use of a personalized FDM model improved the accuracy of the system, on average 24.22% with respect to the template BEM model and on average 5.15% with respect to the personalized BEM model. Including fMRI spatial priors did not improve accuracy. Personal fine- tuning largely resolved the robustness problems arising due to the differences in head geometry and neurophysiology between subjects. A real-time average accuracy of 64.26% was reached and the maximum ITR was 6.71 bits/min. We conclude that beamformers calculated with a personalized FDM model have great potential to ameliorate feature extraction and, as a consequence, to improve the performance of real-time BCI systems