Cerebral organoids at the air-liquid interface generate diverse nerve tracts with functional output.

Neural organoids have the potential to improve our understanding of human brain development and neurological disorders. However, it remains to be seen whether these tissues can model circuit formation with functional neuronal output. Here we have adapted air-liquid interface culture to cerebral organoids, leading to improved neuronal survival and axon outgrowth. The resulting thick axon tracts display various morphologies, including long-range projection within and away from the organoid, growth-cone turning, and decussation. Single-cell RNA sequencing reveals various cortical neuronal identities, and retrograde tracing demonstrates tract morphologies that match proper molecular identities. These cultures exhibit active neuronal networks, and subcortical projecting tracts can innervate mouse spinal cord explants and evoke contractions of adjacent muscle in a manner dependent on intact organoid-derived innervating tracts. Overall, these results reveal a remarkable self-organization of corticofugal and callosal tracts with a functional output, providing new opportunities to examine relevant aspects of human CNS development and disease

Cetuximab in the treatment of metastatic mucoepidermoid carcinoma of the salivary glands: A case report and review of literature

<p>Abstract</p> <p>Introduction</p> <p>Patients with metastatic mucoepidermoid carcinoma of salivary glands have a poor outcome. The epidermal growth factor receptor protein is overexpressed in approximately 70% of mucoepidermoid carcinoma patients and may represent a therapeutic target. However, whether treatment with anti-epidermal growth factor receptor agents is effective is unclear and clinical trials are difficult due to the rarity of the disease. Here we assessed the activity of cetuximab in mucoepidermoid carcinoma on a molecular basis.</p> <p>Case presentation</p> <p>We present the case of a 40-year old Caucasian man with a mucoepidermoid carcinoma of the major salivary glands who developed distant bone and visceral metastases despite platinum-based chemotherapy. Epidermal growth factor receptor was overexpressed and fluorescence in situ hybridization analysis demonstrated a chromosome 7 polysomy. The patient was treated with the monoclonal antibody cetuximab in combination with cisplatin. After 11 doses of cetuximab, the patient developed brain metastases but evidence of response was documented at all extracranial metastatic sites.</p> <p>Conclusion</p> <p>This case report indicates that cetuximab can be active in mucoepidermoid carcinoma and may restore sensitivity to cisplatin in platinum-treated patients. Cetuximab does not cross the blood brain barrier and may select a metastatic clone to home the central nervous system while responding at other sites.</p

A 2017 Horizon Scan of Emerging Issues for Global Conservation and Biological Diversity

We present the results of our eighth annual horizon scan of emerging issues likely to affect global biological diversity, the environment, and conservation efforts in the future. The potential effects of these novel issues might not yet be fully recognized or understood by the global conservation community, and the issues can be regarded as both opportunities and risks. A diverse international team with collective expertise in horizon scanning, science communication, and conservation research, practice, and policy reviewed 100 potential issues and identified 15 that qualified as emerging, with potential substantial global effects. These issues include new developments in energy storage and fuel production, sand extraction, potential solutions to combat coral bleaching and invasive marine species, and blockchain technology.Cambridge Conservation Initiative, funded by the Natural Environment Research Council and the Royal Society for the Protection of Birds, Arcadia, Natural Environment Research Council (Grant ID: NE/N014472/1

NEAT: An efficient network enrichment analysis test

Background: Network enrichment analysis is a powerful method, which allows to integrate gene enrichment analysis with the information on relationships between genes that is provided by gene networks. Existing tests for network enrichment analysis deal only with undirected networks, they can be computationally slow and are based on normality assumptions. Results: We propose NEAT, a test for network enrichment analysis. The test is based on the hypergeometric distribution, which naturally arises as the null distribution in this context. NEAT can be applied not only to undirected, but to directed and partially directed networks as well. Our simulations indicate that NEAT is considerably faster than alternative resampling-based methods, and that its capacity to detect enrichments is at least as good as the one of alternative tests. We discuss applications of NEAT to network analyses in yeast by testing for enrichment of the Environmental Stress Response target gene set with GO Slim and KEGG functional gene sets, and also by inspecting associations between functional sets themselves. Conclusions: NEAT is a flexible and efficient test for network enrichment analysis that aims to overcome some limitations of existing resampling-based tests. The method is implemented in the R package neat, which can be freely downloaded from CRAN ( https://cran.r-project.org/package=neat )

Can We Really Prevent Suicide?

Every year, suicide is among the top 20 leading causes of death globally for all ages. Unfortunately, suicide is difficult to prevent, in large part because the prevalence of risk factors is high among the general population. In this review, clinical and psychological risk factors are examined and methods for suicide prevention are discussed. Prevention strategies found to be effective in suicide prevention include means restriction, responsible media coverage, and general public education, as well identification methods such as screening, gatekeeper training, and primary care physician education. Although the treatment for preventing suicide is difficult, follow-up that includes pharmacotherapy, psychotherapy, or both may be useful. However, prevention methods cannot be restricted to the individual. Community, social, and policy interventions will also be essentia

The role of dobutamine stress cardiovascular magnetic resonance in the clinical management of patients with suspected and known coronary artery disease

BACKGROUND: Recent studies have demonstrated the consistently high diagnostic and prognostic value of dobutamine stress cardiovascular magnetic resonance (DCMR). The value of DCMR for clinical decision making still needs to be defined. Hence, the purpose of this study was to assess the utility of DCMR regarding clinical management of patients with suspected and known coronary artery disease (CAD) in a routine setting. METHODS AND RESULTS: We prospectively performed a standard DCMR examination in 1532 consecutive patients with suspected and known CAD. Patients were stratified according to the results of DCMR: DCMR-positive patients were recommended to undergo invasive coronary angiography and DCMR-negative patients received optimal medical treatment. Of 609 (40%) DCMR-positive patients coronary angiography was performed in 478 (78%) within 90 days. In 409 of these patients significant coronary stenoses ≥ 50% were present (positive predictive value 86%). Of 923 (60%) DCMR-negative patients 833 (90%) received optimal medical therapy. During a mean follow-up period of 2.1 ± 0.8 years (median: 2.1 years, interquartile range 1.5 to 2.7 years) 8 DCMR-negative patients (0.96%) sustained a cardiac event.In 131 DCMR-positive patients who did not undergo invasive angiography, 20 patients (15%) suffered cardiac events. In 90 DCMR-negative patients (10%) invasive angiography was performed within 2 years (range 0.01 to 2.0 years) with 56 patients having coronary stenoses ≥ 50%. CONCLUSION: In a routine setting DCMR proved a useful arbiter for clinical decision making and exhibited high utility for stratification and clinical management of patients with suspected and known CAD

Late gadolinium uptake demonstrated with magnetic resonance in patients where automated PERFIT analysis of myocardial SPECT suggests irreversible perfusion defect

<p>Abstract</p> <p>Background</p> <p>Myocardial perfusion single photon emission computed tomography (MPS) is frequently used as the reference method for the determination of myocardial infarct size. PERFIT^®is a software utilizing a three-dimensional gender specific, averaged heart model for the automatic evaluation of myocardial perfusion. The purpose of this study was to compare the perfusion defect size on MPS, assessed with PERFIT, with the hyperenhanced volume assessed by late gadolinium enhancement magnetic resonance imaging (LGE) and to relate their effect on the wall motion score index (WMSI) assessed with cine magnetic resonance imaging (cine-MRI) and echocardiography (echo).</p> <p>Methods</p> <p>LGE was performed in 40 patients where clinical MPS showed an irreversible uptake reduction suggesting a myocardial scar. Infarct volume, extent and major coronary supply were compared between MPS and LGE as well as the relationship between infarct size from both methods and WMSI.</p> <p>Results</p> <p>MPS showed a slightly larger infarct volume than LGE (MPS 29.6 ± 23.2 ml, LGE 22.1 ± 16.9 ml, p = 0.01), while no significant difference was found in infarct extent (MPS 11.7 ± 9.4%, LGE 13.0 ± 9.6%). The correlation coefficients between methods in respect to infarct size and infarct extent were 0.71 and 0.63 respectively. WMSI determined with cine-MRI correlated moderately with infarct volume and infarct extent (cine-MRI vs MPS volume r = 0.71, extent r = 0.71, cine-MRI vs LGE volume r = 0.62, extent r = 0.60). Similar results were achieved when wall motion was determined with echo. Both MPS and LGE showed the same major coronary supply to the infarct area in a majority of patients, Kappa = 0.84.</p> <p>Conclusion</p> <p>MPS and LGE agree moderately in the determination of infarct size in both absolute and relative terms, although infarct volume is slightly larger with MPS. The correlation between WMSI and infarct size is moderate.</p

A Philosophically Plausible Formal Interpretation of Intuitionistic Logic

This study addresses the mediating role of settlement patterns in the relationship between urbanization and start-up activity. Places do not operate in a vacuum and to understand the effect of 'own' density on start-up patterns, we need to account for the urban spillovers or borrowed size that they may experience from other places nearby. The results can explain the empirical ambiguity in the relationship between urbanization and start-up patterns: the relationship between urbanization and start-up rates becomes more similar between countries when controlling for country-specific settlement patterns by including a spatially lagged urbanization variable and variables measuring the distance to urban centers. Accounting for the relative location of places and relevant sorting effects, we find that 'own' density has a consistently negative effect on start-up activity. Yet, access to other places has a generally positive effect. This implies that nearby regions profit from the advantages offered by urban environments without having to deal with the costs involved

Methods for evaluating clustering algorithms for gene expression data using a reference set of functional classes

BACKGROUND: A cluster analysis is the most commonly performed procedure (often regarded as a first step) on a set of gene expression profiles. In most cases, a post hoc analysis is done to see if the genes in the same clusters can be functionally correlated. While past successes of such analyses have often been reported in a number of microarray studies (most of which used the standard hierarchical clustering, UPGMA, with one minus the Pearson's correlation coefficient as a measure of dissimilarity), often times such groupings could be misleading. More importantly, a systematic evaluation of the entire set of clusters produced by such unsupervised procedures is necessary since they also contain genes that are seemingly unrelated or may have more than one common function. Here we quantify the performance of a given unsupervised clustering algorithm applied to a given microarray study in terms of its ability to produce biologically meaningful clusters using a reference set of functional classes. Such a reference set may come from prior biological knowledge specific to a microarray study or may be formed using the growing databases of gene ontologies (GO) for the annotated genes of the relevant species. RESULTS: In this paper, we introduce two performance measures for evaluating the results of a clustering algorithm in its ability to produce biologically meaningful clusters. The first measure is a biological homogeneity index (BHI). As the name suggests, it is a measure of how biologically homogeneous the clusters are. This can be used to quantify the performance of a given clustering algorithm such as UPGMA in grouping genes for a particular data set and also for comparing the performance of a number of competing clustering algorithms applied to the same data set. The second performance measure is called a biological stability index (BSI). For a given clustering algorithm and an expression data set, it measures the consistency of the clustering algorithm's ability to produce biologically meaningful clusters when applied repeatedly to similar data sets. A good clustering algorithm should have high BHI and moderate to high BSI. We evaluated the performance of ten well known clustering algorithms on two gene expression data sets and identified the optimal algorithm in each case. The first data set deals with SAGE profiles of differentially expressed tags between normal and ductal carcinoma in situ samples of breast cancer patients. The second data set contains the expression profiles over time of positively expressed genes (ORF's) during sporulation of budding yeast. Two separate choices of the functional classes were used for this data set and the results were compared for consistency. CONCLUSION: Functional information of annotated genes available from various GO databases mined using ontology tools can be used to systematically judge the results of an unsupervised clustering algorithm as applied to a gene expression data set in clustering genes. This information could be used to select the right algorithm from a class of clustering algorithms for the given data set