Ocular Biomarkers of Disease: Employing Routine Eye Exams to Promote Better Health Surveillance

America’s burden of vision impairment, Alzheimer’s disease and related dementias (ADRD), and cardiovascular disease will continue to rise over the next 40 years. The burden of these diseases will be greater for women, Hispanics, African-Americans, and those from lower socio-economic regions. A key challenge is to develop strategies to deny the organization of the pathologies that eventually lead to the manifestation of the disease. An important feature within this battle is the development of appropriate tools and biomarkers for early reconnaissance of the enemy. Recent advances in Optical Coherence Tomography Angiography (OCTA) present a unique opportunity to examine physiological features of the eyes that overlap with structures within the brain and heart. Specifically, tracking of the vessel density and thickness of the nerve fiber layers of the eye may provide valuable information regarding an individual’s path towards visual impairment, ADRD, and cardiovascular disease. Thus, OCTA can extend eye care beyond capturing those who are at risk for vision loss, and include examination of biomarkers which provide information concerning trajectories of cognitive and cardiovascular health. Given loss of vision is perceived as ‘the worst ailment that could happen to person’ across all ethnic and racial groups, Ophthalmologists and Optometrists can not only provide a path toward improved eye health, but also serve as an innovative access point for early detection of individuals at risk for ADRD and Cardiovascular disease

Cancer gene prioritization by integrative analysis of mRNA expression and DNA copy number data: a comparative review

A variety of genome-wide profiling techniques are available to probe complementary aspects of genome structure and function. Integrative analysis of heterogeneous data sources can reveal higher-level interactions that cannot be detected based on individual observations. A standard integration task in cancer studies is to identify altered genomic regions that induce changes in the expression of the associated genes based on joint analysis of genome-wide gene expression and copy number profiling measurements. In this review, we provide a comparison among various modeling procedures for integrating genome-wide profiling data of gene copy number and transcriptional alterations and highlight common approaches to genomic data integration. A transparent benchmarking procedure is introduced to quantitatively compare the cancer gene prioritization performance of the alternative methods. The benchmarking algorithms and data sets are available at http://intcomp.r-forge.r-project.orgComment: PDF file including supplementary material. 9 pages. Preprin

Comparative Genomic Hybridization Analysis of Astrocytomas: Prognostic and Diagnostic Implications.

Astrocytoma is comprised of a group of common intracranial neoplasms that are classified into four grades based on the World Health Organization histological criteria and patient survival. To date, histological grade, patient age, and clinical performance, as reflected in the Karnofsky score, are the most reliable prognostic predictors. Recently, there has been a significant effort to identify additional prognostic markers using objective molecular genetic techniques. We believe that the identification of such markers will characterize new chromosomal loci important in astrocytoma progression and aid clinical diagnosis and prognosis. To this end, our laboratory used comparative genomic hybridization to identify DNA sequence copy number changes in 102 astrocytomas. Novel losses of 19p loci were detected in low-grade pilocytic astrocytomas and losses of loci on 9p, 10, and 22 along with gains on 7, 19, and 20 were detected in a significant proportion of high-grade astrocytomas. The Cox proportional hazards statistical modeling showed that the presence of +7q and -10q comparative genomic hybridization alterations significantly increased a patient\u27s risk of dying, independent of histological grade. This investigation demonstrates the efficacy of comparative genomic hybridization for identifying tumor suppressor and oncogene loci in different astrocytic grades. The cumulative effect of these loci is an important consideration in their diagnostic and prognostic implications

Reducing unscheduled hospital care for adults with diabetes following a hypoglycaemic event: which community-based interventions are most effective? A systematic review

AIM: To determine which community-based interventions are most effective at reducing unscheduled hospital care for hypoglycaemic events in adults with diabetes. METHODS: Medline Ovid, CINAHL Plus and ProQuest Health and Medical Collection were searched using both key search terms and medical subject heading terms (MeSH) to identify potentially relevant studies. Eligible studies were those that involved a community-based intervention to reduce unscheduled admissions in adults with diabetes. Papers were initially screened by the primary researcher and then a secondary reviewer. Relevant data were then extracted from papers that met the inclusion criteria. RESULTS: The search produced 2226 results, with 1360 duplicates. Of the remaining 866 papers, 198 were deemed appropriate based on titles, 90 were excluded following abstract review. A total of 108 full papers were screened with 19 full papers included in the review. The sample size of the 19 papers ranged from n = 25 to n = 104,000. The average ages within the studies ranged from 41 to 74 years with females comprising 57% of the participants. The following community-based interventions were identified that explored reducing unscheduled hospital care in people with diabetes; telemedicine, education, integrated care pathways, enhanced primary care and care management teams. CONCLUSIONS: This systematic review shows that a range of community-based interventions, requiring different levels of infrastructure, are effective in reducing unscheduled hospital care for hypoglycaemia in people with diabetes. Investment in effective community-based interventions such as integrated care and patient education must be a priority to shift the balance of care from secondary to primary care, thereby reducing hospital admissions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40200-021-00817-z

Distributed Branching Bisimulation Minimization by Inductive Signatures

We present a new distributed algorithm for state space minimization modulo branching bisimulation. Like its predecessor it uses signatures for refinement, but the refinement process and the signatures have been optimized to exploit the fact that the input graph contains no tau-loops. The optimization in the refinement process is meant to reduce both the number of iterations needed and the memory requirements. In the former case we cannot prove that there is an improvement, but our experiments show that in many cases the number of iterations is smaller. In the latter case, we can prove that the worst case memory use of the new algorithm is linear in the size of the state space, whereas the old algorithm has a quadratic upper bound. The paper includes a proof of correctness of the new algorithm and the results of a number of experiments that compare the performance of the old and the new algorithms

Recombinant Adeno-Associated Virus Utilizes Cell-Specific Infectious Entry Mechanisms

Understanding the entry and trafficking mechanism(s) of recombinant adeno-associated virus (rAAV) into host cells can lead to evolution in capsid and vector design and delivery methods, resulting in enhanced transduction and therapeutic gene expression. Variability of findings regarding the early entry pathway of rAAV supports the possibility that rAAV, like other viruses, can utilize more than one infectious entry pathway. We tested whether inhibition of macropinocytosis impacted rAAV transduction of HeLa cells compared to hepatocellular carcinoma cell lines. We found that macropinocytosis inhibitor cytochalasin D blocked rAAV transduction of HeLa cells (>2-fold) but enhanced (10-fold) transduction in HepG2 and Huh7 lines. Similar results were obtained with another macropinocytosis inhibitor, 5-(N-ethyl-N-isopropyl) amiloride (EIPA). The augmented transduction was due to neither viral binding nor promoter activity, affected multiple rAAV serotypes (rAAV2, rAAV2-R585E, and rAAV8), and influenced single-stranded and self-complementary virions to comparable extents. Follow-up studies using CDC42 inhibitor ML141 and p21-activated kinase 1 (PAK1) siRNA knockdown also resulted in enhanced HepG2 transduction. Microscopy revealed that macropinocytosis inhibition correlated with expedited nuclear entry of the rAAV virions into HepG2 cells. Enhancement of hepatocellular rAAV transduction extended to the mouse liver in vivo (4-fold enhancement) but inversely blocked heart tissue transduction (13-fold). This evidence of host cell-specific rAAV entry pathways confers a potent means for controlling and enhancing vector delivery and could help unify the divergent accounts of rAAV cellular entry mechanisms

COSMIC: mining complete cancer genomes in the Catalogue of Somatic Mutations in Cancer

COSMIC (http://www.sanger.ac.uk/cosmic) curates comprehensive information on somatic mutations in human cancer. Release v48 (July 2010) describes over 136 000 coding mutations in almost 542 000 tumour samples; of the 18 490 genes documented, 4803 (26%) have one or more mutations. Full scientific literature curations are available on 83 major cancer genes and 49 fusion gene pairs (19 new cancer genes and 30 new fusion pairs this year) and this number is continually increasing. Key amongst these is TP53, now available through a collaboration with the IARC p53 database. In addition to data from the Cancer Genome Project (CGP) at the Sanger Institute, UK, and The Cancer Genome Atlas project (TCGA), large systematic screens are also now curated. Major website upgrades now make these data much more mineable, with many new selection filters and graphics. A Biomart is now available allowing more automated data mining and integration with other biological databases. Annotation of genomic features has become a significant focus; COSMIC has begun curating full-genome resequencing experiments, developing new web pages, export formats and graphics styles. With all genomic information recently updated to GRCh37, COSMIC integrates many diverse types of mutation information and is making much closer links with Ensembl and other data resources

Network of Cancer Genes (NCG 3.0): integration and analysis of genetic and network properties of cancer genes

The identification of a constantly increasing number of genes whose mutations are causally implicated in tumor initiation and progression (cancer genes) requires the development of tools to store and analyze them. The Network of Cancer Genes (NCG 3.0) collects information on 1494 cancer genes that have been found mutated in 16 different cancer types. These genes were collected from the Cancer Gene Census as well as from 18 whole exome and 11 whole-genome screenings of cancer samples. For each cancer gene, NCG 3.0 provides a summary of the gene features and the cross-reference to other databases. In addition, it describes duplicability, evolutionary origin, orthology, network properties, interaction partners, microRNA regulation and functional roles of cancer genes and of all genes that are related to them. This integrated network of information can be used to better characterize cancer genes in the context of the system in which they act. The data can also be used to identify novel candidates that share the same properties of known cancer genes and may therefore play a similar role in cancer. NCG 3.0 is freely available at http://bio.ifom-ieo-campus.it/ncg

Millisecond-Timescale Optical Control of Neural Dynamics in the Nonhuman Primate Brain

To understand how brain states and behaviors are generated by neural circuits, it would be useful to be able to perturb precisely the activity of specific cell types and pathways in the nonhuman primate nervous system. We used lentivirus to target the light-activated cation channel channelrhodopsin-2 (ChR2) specifically to excitatory neurons of the macaque frontal cortex. Using a laser-coupled optical fiber in conjunction with a recording microelectrode, we showed that activation of excitatory neurons resulted in well-timed excitatory and suppressive influences on neocortical neural networks. ChR2 was safely expressed, and could mediate optical neuromodulation, in primate neocortex over many months. These findings highlight a methodology for investigating the causal role of specific cell types in nonhuman primate neural computation, cognition, and behavior, and open up the possibility of a new generation of ultraprecise neurological and psychiatric therapeutics via cell-type-specific optical neural control prosthetics.Helen Hay Whitney Foundation (Fellowship)National Institutes of Health (U.S.) (NIH-EY002621-31)McGovern Institute for Brain Research at MIT (Neurotechnology Award)National Institutes of Health (U.S.) (Grant NIH-EY12848)National Institutes of Health (U.S.) (Grant NIH-EY017292)National Institutes of Health (U.S.) (NIH Director's New Innovator Award (DP2 OD002002-01))Brain & Behavior Research FoundationUnited States. Dept. of DefenseNational Science Foundation (U.S.)Alfred P. Sloan FoundationDr. Gerald Burnett and Marjorie BurnettSFN Research Award for Innovation in NeuroscienceMassachusetts Institute of Technology. Media LaboratoryBenesse FoundationWallace H. Coulter Foundatio

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types