Light-emitting diodes as a light source for intraoperative photodynamic therapy

Journal ArticleTHE DEVELOPMENT OF more cost-effective light sources for photodynamic therapy of brain tumors would be of benefit for both research and clinical applications. In this study, the use of light-emitting diode arrays for photodynamic therapy of brain tumors with Pholofrin porfimer sodium was investigated. An inflatable balloon device with a light-emitting diode (LED) tip was constructed. These LEDs are based on the new semiconductor aluminum gallium arsenide. They can emit broad-spectrum red light at high power levels with a peak wavelength of 677 nm and a bandwidth of 25 nm. The balloon was inflated with 0.1 % intralipid, which served as a light-scattering medium. Measurements of light flux at several points showed a high degree of light dispersion. The spectral emission of this probe was then compared with the absorption spectrum of Photofrin, This analysis showed that the light absorbed by Photofrin with the use of the LED source was 27.5% of that absorbed with the use of the monochromatic 630-nm light. Thus, to achieve an energy light dose equivalent to that of a laser light source, the LED light output must be increased by a factor of 3.63. This need for additional energy is the difference between a 630 - and 677-nm absorption of Photofrin. Using the LED probe and the laser balloon adapter, a comparison of brain stem toxicity in canines was conducted. LED and laser light showed the same signs of toxicity at equivalent light energy and Photofrin doses. The maximal tolerated dose of Photofrin was 1.6 mg/kg, using 100J / cm 2 of light energy administered by laseror LED. This study concludes that LEDs are a suitable light source for photodynamic therapy of brain tumors with Photofrin. In addition, LEDs have the potential to be highly efficient light sources for second-generation photosensitizers with absorption wavelengths closer to the LED peak emission

Proactive Approach in Detecting Elderly Subjects with Cognitive Decline in General Practitioners’ Practices

Background: Although cognitive decline is a common finding among the elderly and is considered a risk factor for developing dementia, it is rarely diagnosed by general practitioners (GPs). Aim: To evaluate cognitive function with the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) in asymptomatic subjects in daily GP practice and compare subjects who confirmed having cognitive problems with subjects who did not. Methods: 388 consecutive subjects >65 years of age who consulted their GP were interviewed and tested with MMSE and MoCA. Results: None of the study subjects spontaneously complained of cognitive or memory problems. 155 subjects (39.94%) confirmed having cognitive problems and 233 (60.05%) did not even when asked. The prevalence of mild cognitive impairment (MCI) was 18.30% (95% CI 14.36–22.04) and the prevalence of cognitive impairment/no dementia (CIND) was 17.27% (95% CI 13.50–21.04). Delayed memory recall as a separate cognitive domain in MoCA was significantly worse in subjects with MCI (p = 0.00958) and in those with CIND (p = 0.0208). Conclusion: There is a significant number of patients in daily GP practices with unrecognized, but objectively verifiable, cognitive deficits who do not report having cognitive problems. They can be identified by assessment with MMSE and MoCA already in the GP practice

PLAN2L: a web tool for integrated text mining and literature-based bioentity relation extraction

There is an increasing interest in using literature mining techniques to complement information extracted from annotation databases or generated by bioinformatics applications. Here we present PLAN2L, a web-based online search system that integrates text mining and information extraction techniques to access systematically information useful for analyzing genetic, cellular and molecular aspects of the plant model organism Arabidopsis thaliana. Our system facilitates a more efficient retrieval of information relevant to heterogeneous biological topics, from implications in biological relationships at the level of protein interactions and gene regulation, to sub-cellular locations of gene products and associations to cellular and developmental processes, i.e. cell cycle, flowering, root, leaf and seed development. Beyond single entities, also predefined pairs of entities can be provided as queries for which literature-derived relations together with textual evidences are returned. PLAN2L does not require registration and is freely accessible at http://zope.bioinfo.cnio.es/plan2l

Characterization of an enzymatic packed-bed microreactor: Experiments and modeling

A micro packed-bed reactor (µPBR) based on two-parallel-plates configuration with immobilized Candida antarctica lipase B in the form of porous particles (Novozym® 435) was theoretically and experimentally characterized. A residence time distribution (RTD) within µPBRs comprising various random distributions of particles placed in one layer was computationally predicted by a mesoscopic lattice Boltzmann (LB) method. Numerical simulations were compared with measurements of RTD, obtained by stimulus-response experiment with a pulse input using glucose as a tracer, monitored by an electrochemical glucose oxidase microbiosensor integrated with the reactor. The model was validated by a good agreement between the experimental data and predictions of LB model at different conditions. The developed µPBR was scaled-up in length and width comprising either a single or two layers of Novozym® 435 particles and compared regarding the selected enzyme-catalyzed transesterification. A linear increase in the productivity with the increase in all dimensions of the µPBR between two-plates demonstrated very efficient and simple approach for the capacity rise. Further characterization of µPBRs of various sizes using the piezoresistive pressure sensor revealed very low pressure drops as compared to their conventional counterparts and thereby great applicability for production systems based on numbering-up approach

Road Roughness Estimation Using Machine Learning

Road roughness is a very important road condition for the infrastructure, as the roughness affects both the safety and ride comfort of passengers. The roads deteriorate over time which means the road roughness must be continuously monitored in order to have an accurate understand of the condition of the road infrastructure. In this paper, we propose a machine learning pipeline for road roughness prediction using the vertical acceleration of the car and the car speed. We compared well-known supervised machine learning models such as linear regression, naive Bayes, k-nearest neighbor, random forest, support vector machine, and the multi-layer perceptron neural network. The models are trained on an optimally selected set of features computed in the temporal and statistical domain. The results demonstrate that machine learning methods can accurately predict road roughness, using the recordings of the cost approachable in-vehicle sensors installed in conventional passenger cars. Our findings demonstrate that the technology is well suited to meet future pavement condition monitoring, by enabling continuous monitoring of a wide road network

Database for exploration of functional context of genes implicated in ovarian cancer

Ovarian cancer (OC) is becoming the most common gynecological cancer in developed countries and the most lethal gynecological malignancy. It is also the fifth leading cause of all cancer-related deaths in women. The identification of diagnostic biomarkers and development of early detection techniques for OC largely depends on the understanding of the complex functionality and regulation of genes involved in this disease. Unfortunately, information about these OC genes is scattered throughout the literature and various databases making extraction of relevant functional information a complex task. To reduce this problem, we have developed a database dedicated to OC genes to support exploration of functional characterization and analysis of biological processes related to OC. The database contains general information about OC genes, enriched with the results of transcription regulation sequence analysis and with relevant text mining to provide insights into associations of the OC genes with other genes, metabolites, pathways and nuclear proteins. Overall, it enables exploration of relevant information for OC genes from multiple angles, making it a unique resource for OC and will serve as a useful complement to the existing public resources for those interested in OC genetics. Access is free for academic and non-profit users and database can be accessed at http://apps.sanbi.ac.za/ddoc/

Structure-Guided Molecular Grafting Of A Complex Broadly Neutralizing Viral Epitope

Antigenic variation and viral evolution have thwarted traditional influenza vaccination strategies. The broad protection afforded by a “universal” influenza vaccine may come from immunogens that elicit humoral immune responses targeting conserved epitopes on the viral hemagglutinin (HA), such as the receptor-binding site (RBS). Here, we engineered candidate immunogens that use noncirculating, avian influenza HAs as molecular scaffolds to present the broadly neutralizing RBS epitope from historical, circulating H1 influenzas. These “resurfaced” HAs (rsHAs) remove epitopes potentially targeted by strain-specific responses in immune-experienced individuals. Through structure-guided optimization, we improved two antigenically different scaffolds to bind a diverse panel of pan-H1 and H1/H3 cross-reactive bnAbs with high affinity. Subsequent serological and single germinal center B cell analyses from murine prime-boost immunizations show that the rsHAs are both immunogenic and can augment the quality of elicited RBS-directed antibodies. Our structure-guided, RBS grafting approach provides candidate immunogens for selectively presenting a conserved viral epitope

From the bottom-up: chemotherapy and gut-brain axis dysregulation

The central nervous system and gastrointestinal tract form the primary targets of chemotherapy-induced toxicities. Symptoms associated with damage to these regions have been clinically termed chemotherapy-induced cognitive impairment and mucositis. Whilst extensive literature outlines the complex etiology of each pathology, to date neither chemotherapy-induced side-effect has considered the potential impact of one on the pathogenesis of the other disorder. This is surprising considering the close bidirectional relationship shared between each organ; the gut-brain axis. There are complex multiple pathways linking the gut to the brain and vice versa in both normal physiological function and disease. For instance, psychological and social factors influence motility and digestive function, symptom perception, and behaviors associated with illness and pathological outcomes. On the other hand, visceral pain affects central nociception pathways, mood and behavior. Recent interest highlights the influence of functional gut disorders, such as inflammatory bowel diseases and irritable bowel syndrome in the development of central comorbidities. Gut-brain axis dysfunction and microbiota dysbiosis have served as key portals in understanding the potential mechanisms associated with these functional gut disorders and their effects on cognition. In this review we will present the role gut-brain axis dysregulation plays in the chemotherapy setting, highlighting peripheral-to-central immune signaling mechanisms and their contribution to neuroimmunological changes associated with chemotherapy exposure. Here, we hypothesize that dysregulation of the gut-brain axis plays a major role in the intestinal, psychological and neurological complications following chemotherapy. We pay particular attention to evidence surrounding microbiota dysbiosis, the role of intestinal permeability, damage to nerves of the enteric and peripheral nervous systems and vagal and humoral mediated changes.Juliana E. Bajic, Ian N. Johnston, Gordon S. Howarth and Mark R. Hutchinso

Mining biosynthetic gene clusters in Virgibacillus genomes

BACKGROUND: Biosynthetic gene clusters produce a wide range of metabolites with activities that are of interest to the pharmaceutical industry. Specific interest is shown towards those metabolites that exhibit antimicrobial activities against multidrug-resistant bacteria that have become a global health threat. Genera of the phylum Firmicutes are frequently identified as sources of such metabolites, but the biosynthetic potential of its Virgibacillus genus is not known. Here, we used comparative genomic analysis to determine whether Virgibacillus strains isolated from the Red Sea mangrove mud in Rabigh Harbor Lagoon, Saudi Arabia, may be an attractive source of such novel antimicrobial agents. RESULTS: A comparative genomics analysis based on Virgibacillus dokdonensis Bac330, Virgibacillus sp. Bac332 and Virgibacillus halodenitrificans Bac324 (isolated from the Red Sea) and six other previously reported Virgibacillus strains was performed. Orthology analysis was used to determine the core genomes as well as the accessory genome of the nine Virgibacillus strains. The analysis shows that the Red Sea strain Virgibacillus sp. Bac332 has the highest number of unique genes and genomic islands compared to other genomes included in this study. Focusing on biosynthetic gene clusters, we show how marine isolates, including those from the Red Sea, are more enriched with nonribosomal peptides compared to the other Virgibacillus species. We also found that most nonribosomal peptide synthases identified in the Virgibacillus strains are part of genomic regions that are potentially horizontally transferred. CONCLUSIONS: The Red Sea Virgibacillus strains have a large number of biosynthetic genes in clusters that are not assigned to known products, indicating significant potential for the discovery of novel bioactive compounds. Also, having more modular synthetase units suggests that these strains are good candidates for experimental characterization of previously identified bioactive compounds as well. Future efforts will be directed towards establishing the properties of the potentially novel compounds encoded by the Red Sea specific trans-AT PKS/NRPS cluster and the type III PKS/NRPS cluster

Effect of welding regime and filler content on structure of microalloyed Nb/Ti steel weldments

In this paper changes in the proportions of certain microconstituents in the structure of weld metal and the heat affected zone are described and the mechanical and technological properties of welded joints of high-strength microalloyed Nb/Ti steel performed by E-process and MAG-process of welding with modification of the filler composition and welding parameters were analysed. The influence of different structures of filler material and welding parameters on the microstructure of HAZ and weld metal is studied with the aim to explain changes of mechanical and technological properties of welded microalloyed Nb/Ti steel joints.Описано зміни в пропорціях між певними складниками мікроструктури металу зварного шва і зони термічного впливу; проаналізовано механічні та технологічні параметри зварних з’єднань високоміцної мікролегованої Nb/Ti сталі, виконаних за різних технологій зварювання з модифікацією складу наповнювача і параметрів зварювання. Вивчено вплив структури матеріалу наповнювача і параметрів зварювання на мікроструктуру зварних з’єднань для пояснення їх механічних і технологічних властивостей.Описаны изменения в пропорциях между некоторыми составляющими микроструктуры металла сварного шва и зоны термического влияния; проанализированы механические и технологические параметры сварных соединений высокопрочной микролегированной Nb/Ti стали, выполненных в условиях разных технологий сварки с модификацией состава наполнителя и параметров сварки. Изучено влияние структуры материала наполнителя и параметров сварки на микроструктуру сварных соединений для объяснения их механических и технологических свойств