Innovative Diagnostic Tools for Ophthalmology in Low-Income Countries

Globally, there are almost 300 million people blind and visually impaired and over 90% live developing countries. The gross disparity in access to ophthalmologists limits the ability to accurately diagnose potentially blinding conditions like cataract, glaucoma, trachoma, uncorrected refractive error and limits timely initiation of medical and surgical treatment. Since 85% of blindness is preventable, bridging this chasm for care is even more critical in preventing needless blindness. Many low-income countries must rely on community health workers, physician assistants, and cataract surgeons for primary eye care. Ophthalmology in low-income countries (LIC) is further challenging due to complexities brought from tropical climates, frail electric grids, poor road and water infrastructure, limited diagnostic capability and limited treatment options. Vision 2020 set the goal of eliminating preventable blindness by 2020 despite formidable obstacles. Innovative technologies are emerging to test visual acuity, correct refractive error quickly and inexpensively, capture retinal images with portable tools, train cataract surgeons using simulators, capitalize on mHealth, access ophthalmic information remotely. These advancements are allowing nonspecialized ophthalmic practitioners to provide low-cost, high impact eye care in resource-limited regions around the world

A Brief Overview of Ophthalmic Ultrasound Imaging

Ultrasound is one of the oldest imaging modalities. Sound waves are emitted into the body, and the returning echoes can be interpreted. It has become widely used because it can easily be done at bedside with a relatively small apparatus and does not expose the patient to any ionizing radiation. While this technique has seen widespread acceptance in other fields such as cardiology or obstetrics and gynecology, the general use in ophthalmology has been somewhat limited. However, recent advancements in ultrasonic arrays can be a powerful tool in the evaluation of ophthalmic pathology. Such systems can quickly generate very high detail images and 3D reconstructions without the need for extensive manual scanning. The application of this technology includes evaluation of traumatic eye injuries; assessing presence and location of an intraocular foreign body; evaluation of intraocular tumors, including small tumors that have not yet caused visual distortion; evaluation of retinal detachment; and evaluation of vascular disease. The goal of this article is to briefly review the history and development of ultrasound and to provide an overview of the most current systems and applications of ultrasound use in ophthalmologic clinical evaluation

Differences in transcription between free-living and CO_2-activated third-stage larvae of Haemonchus contortus

Background: The disease caused by Haemonchus contortus, a blood-feeding nematode of small ruminants, is of major economic importance worldwide. The infective third-stage larva (L3) of this gastric nematode is enclosed in a cuticle (sheath) and, once ingested with herbage by the host, undergoes an exsheathment process that marks the transition from the free-living (L3) to the parasitic (xL3) stage. This study explored changes in gene transcription associated with this transition and predicted, based on comparative analysis, functional roles for key transcripts in the metabolic pathways linked to larval development. Results: Totals of 101,305 (L3) and 105,553 (xL3) expressed sequence tags (ESTs) were determined using 454 sequencing technology, and then assembled and annotated; the most abundant transcripts encoded transthyretin-like, calcium-binding EF-hand, NAD(P)-binding and nucleotide-binding proteins as well as homologues of Ancylostoma-secreted proteins (ASPs). Using an in silico-subtractive analysis, 560 and 685 sequences were shown to be uniquely represented in the L3 and xL3 stages, respectively; the transcripts encoded ribosomal proteins, collagens and elongation factors (in L3), and mainly peptidases and other enzymes of amino acid catabolism (in xL3). Caenorhabditis elegans orthologues of transcripts that were uniquely transcribed in each L3 and xL3 were predicted to interact with a total of 535 other genes, all of which were involved in embryonic development. Conclusion: The present study indicated that some key transcriptional alterations taking place during the transition from the L3 to the xL3 stage of H. contortus involve genes predicted to be linked to the development of neuronal tissue (L3 and xL3), formation of the cuticle (L3) and digestion of host haemoglobin (xL3). Future efforts using next-generation sequencing and bioinformatic technologies should provide the efficiency and depth of coverage required for the determination of the complete transcriptomes of different developmental stages and/or tissues of H. contortus as well as the genome of this important parasitic nematode. Such advances should lead to a significantly improved understanding of the molecular biology of H. contortus and, from an applied perspective, to novel methods of intervention

Mixed valency in cerium oxide crystallographic phases: Determination of valence of the different cerium sites by the bond valence method

We have applied the bond valence method to cerium oxides to determine the oxidation states of the Ce ion at the various site symmetries of the crystals. The crystals studied include cerium dioxide and the two sesquioxides along with some selected intermediate phases which are crystallographically well characterized. Our results indicate that cerium dioxide has a mixed-valence ground state with an f-electron population on the Ce site of 0.27 while both the A- and C-sesquioxides have a nearly pure f^1 configuration. The Ce sites in most of the intermediate oxides have non-integral valences. Furthermore, many of these valences are different from the values predicted from a naive consideration of the stoichiometric valence of the compound

Deep insights into Dictyocaulus viviparus transcriptomes provides unique prospects for new drug targets and disease intervention

The lungworm, Dictyocaulus viviparus, causes parasitic bronchitis in cattle, and is responsible for substantial economic losses in temperate regions of the world. Here, we undertake the first large-scale exploration of available transcriptomic data for this lungworm, examine differences in transcription between different stages/both genders and identify and prioritize essential molecules linked to fundamental metabolic pathways, which could represent novel drug targets. Approximately 3 million expressed sequence tags (ESTs), generated by 454 sequencing from third-stage larvae (L3s) as well as adult females and males of D. viviparus, were assembled and annotated. The assembly of these sequences yielded ~61,000 contigs, of which relatively large proportions encoded collagens (4.3%), ubiquitins (2.1%) and serine/threonine protein kinases (1.9%). Subtractive analysis in silico identified 6928 nucleotide sequences as being uniquely transcribed in L3, and 5203 and 7889 transcripts as being exclusive to the adult female and male, respectively. Most peptides predicted from the conceptual translations were nucleoplasmins (L3), serine/threonine protein kinases (female) and major sperm proteins (male). Additional analyses allowed the prediction of three drug target candidates, whose Caenorhabditis elegans homologues were linked to a lethal RNA interference phenotype. This detailed exploration, combined with future transcriptomic sequencing of all developmental stages of D. viviparus, will facilitate future investigations of the molecular biology of this parasitic nematode as well as genomic sequencing. These advances will underpin the discovery of new drug and/or vaccine targets, focused on biotechnological outcomes

Structure–activity relationship study of acridine analogs as haspin and DYRK2 kinase inhibitors

Haspin is a serine/threonine kinase required for completion of normal mitosis that is highly expressed during cell proliferation, including in a number of neoplasms. Consequently, it has emerged as a potential therapeutic target in oncology. A high throughput screen of approximately 140,000 compounds identified an acridine analog as a potent haspin kinase inhibitor. Profiling against a panel of 270 kinases revealed that the compound also exhibited potent inhibitory activity for DYRK2, another serine/threonine kinase. An optimization study of the acridine series revealed that the structure–activity relationship (SAR) of the acridine series for haspin and DYRK2 inhibition had many similarities. However, several structural differences were noted that allowed generation of a potent haspin kinase inhibitor (33, IC50 <60 nM) with 180-fold selectivity over DYRK2. In addition, a moderately potent DYRK2 inhibitor (41, IC50 <400 nM) with a 5.4-fold selectivity over haspin was also identified

Bulinus truncatus transcriptome – a resource to enable molecular studies of snail and schistosome biology

Despite advances in high-throughput sequencing and bioinformatics, molecular investigations of snail intermediate hosts that transmit parasitic trematodes are scant. Here, we report the first transcriptome for Bulinus truncatus – a key intermediate host of Schistosoma haematobium – a blood fluke that causes urogenital schistosomiasis in humans. We assembled this transcriptome from short- and long-read RNA-sequence data. From this transcriptome, we predicted 12,998 proteins, 58% of which had orthologs in Biomphalaria glabrata – an intermediate host of Schistosoma mansoni – a blood fluke that causes hepato-intestinal schistosomiasis. We predicted that select protein groups are involved in signal transduction, cell growth and death, the immune system, environmental adaptation and/or the excretory/secretory system, suggesting roles in immune responses, pathogen defence and/or parasite-host interactions. The transcriptome of Bu. truncatus provides a useful resource to underpin future molecular investigations of this and related snail species, and its interactions with pathogens including S. haematobium. The present resource should enable comparative investigations of other molluscan hosts of socioeconomically important parasites in the future

A practical, bioinformatic workflow system for large data sets generated by next-generation sequencing

Transcriptomics (at the level of single cells, tissues and/or whole organisms) underpins many fields of biomedical science, from understanding the basic cellular function in model organisms, to the elucidation of the biological events that govern the development and progression of human diseases, and the exploration of the mechanisms of survival, drug-resistance and virulence of pathogens. Next-generation sequencing (NGS) technologies are contributing to a massive expansion of transcriptomics in all fields and are reducing the cost, time and performance barriers presented by conventional approaches. However, bioinformatic tools for the analysis of the sequence data sets produced by these technologies can be daunting to researchers with limited or no expertise in bioinformatics. Here, we constructed a semi-automated, bioinformatic workflow system, and critically evaluated it for the analysis and annotation of large-scale sequence data sets generated by NGS. We demonstrated its utility for the exploration of differences in the transcriptomes among various stages and both sexes of an economically important parasitic worm (Oesophagostomum dentatum) as well as the prediction and prioritization of essential molecules (including GTPases, protein kinases and phosphatases) as novel drug target candidates. This workflow system provides a practical tool for the assembly, annotation and analysis of NGS data sets, also to researchers with a limited bioinformatic expertise. The custom-written Perl, Python and Unix shell computer scripts used can be readily modified or adapted to suit many different applications. This system is now utilized routinely for the analysis of data sets from pathogens of major socio-economic importance and can, in principle, be applied to transcriptomics data sets from any organism

A practical, bioinformatic workflow system for large data sets generated by next-generation sequencing

Transcriptomics (at the level of single cells, tissues and/or whole organisms) underpins many fields of biomedical science, from understanding the basic cellular function in model organisms, to the elucidation of the biological events that govern the development and progression of human diseases, and the exploration of the mechanisms of survival, drug-resistance and virulence of pathogens. Next-generation sequencing (NGS) technologies are contributing to a massive expansion of transcriptomics in all fields and are reducing the cost, time and performance barriers presented by conventional approaches. However, bioinformatic tools for the analysis of the sequence data sets produced by these technologies can be daunting to researchers with limited or no expertise in bioinformatics. Here, we constructed a semi-automated, bioinformatic workflow system, and critically evaluated it for the analysis and annotation of large-scale sequence data sets generated by NGS. We demonstrated its utility for the exploration of differences in the transcriptomes among various stages and both sexes of an economically important parasitic worm (Oesophagostomum dentatum) as well as the prediction and prioritization of essential molecules (including GTPases, protein kinases and phosphatases) as novel drug target candidates. This workflow system provides a practical tool for the assembly, annotation and analysis of NGS data sets, also to researchers with a limited bioinformatic expertise. The custom-written Perl, Python and Unix shell computer scripts used can be readily modified or adapted to suit many different applications. This system is now utilized routinely for the analysis of data sets from pathogens of major socio-economic importance and can, in principle, be applied to transcriptomics data sets from any organism

The State of Altmetrics: A Tenth Anniversary Celebration

Altmetric’s mission is to help others understand the influence of research online.We collate what people are saying about published research in sources such as the mainstream media, policy documents, social networks, blogs, and other scholarly and non-scholarly forums to provide a more robust picture of the influence and reach of scholarly work. Altmetric works with some of the biggest publishers, funders, businesses and institutions around the world to deliver this data in an accessible and reliable format. Contents Altmetrics, Ten Years Later, Euan Adie (Altmetric (founder) & Overton) Reflections on Altmetrics, Gemma Derrick (University of Lancaster), Fereshteh Didegah (Karolinska Institutet & Simon Fraser University), Paul Groth (University of Amsterdam), Cameron Neylon (Curtin University), Jason Priem (Our Research), Shenmeng Xu (University of North Carolina at Chapel Hill), Zohreh Zahedi (Leiden University) Worldwide Awareness and Use of Altmetrics, Yin-Leng Theng (Nanyang Technological University) Leveraging Machine Learning on Altmetrics Big Data, Saeed-Ul Hassan (Information Technology University), Naif R. Aljohani (King Abdulaziz University), Timothy D. Bowman (Wayne State University) Altmetrics as Social-Spatial Sensors, Vanash M. Patel (West Hertfordshire Hospitals NHS Trust), Robin Haunschild (Max Planck Institute for Solid State Research), Lutz Bornmann (Administrative Headquarters of the Max Planck Society) Altmetric’s Fable of the Hare and the Tortoise, Mike Taylor (Digital Science) The Future of Altmetrics: A Community Vision, Liesa Ross (Altmetric), Stacy Konkiel (Altmetric