Role of nitric oxide in Salmonella typhimurium-mediated cancer cell killing

Background: Bacterial targeting of tumours is an important anti-cancer strategy. We previously showed that strain SL7838 of Salmonella typhimurium targets and kills cancer cells. Whether NO generation by the bacteria has a role in SL7838 lethality to cancer cells is explored. This bacterium has the mechanism for generating NO, but also for decomposing it. Methods: Mechanism underlying Salmonella typhimurium tumour therapy was investigated through in vitro and in vivo studies. NO measurements were conducted either by chemical assays (in vitro) or using Biosensors (in vivo). Cancer cells cytotoxic assay were done by using MTS. Bacterial cell survival and tumour burden were determined using molecular imaging techniques. Results: SL7838 generated nitric oxide (NO) in anaerobic cell suspensions, inside infected cancer cells in vitro and in implanted 4T1 tumours in live mice, the last, as measured using microsensors. Thus, under these conditions, the NO generating pathway is more active than the decomposition pathway. The latter was eliminated, in strain SL7842, by the deletion of hmp- and norV genes, making SL7842 more proficient at generating NO than SL7838. SL7842 killed cancer cells more effectively than SL7838 in vitro, and this was dependent on nitrate availability. This strain was also ca. 100% more effective in treating implanted 4T1 mouse tumours than SL7838

Analysing cyclist behaviour at cycling facility discontinuities using video data

RÉSUMÉ: The primary purpose of any transportation network is to provide connectivity between the origin and travel destination. However, given the vehicle oriented structure of the road network in many countries, there are connectivity issues in the cycling network, which has been implemented later. Discontinuities are physical interruptions in the cycling network where cyclists are faced with unexpected situations such as the end of a cycling facility or the change from one facility type to another that are perceived as inconvenient and less safe. The microscopic behaviour of cyclists and the risks they face at these points of discontinuity has not been extensively investigated in the literature. This study aims to evaluate the challenges faced by cyclists at discontinuities by observing cyclist behaviour at these locations and comparing them to control sites using automated video analysis techniques. Our methodology allows the extraction of valuable microscopic data for evaluation of cyclist behaviour at any location. The methodology is applied to a case study of four sites in Montreal, Canada. Using a set of discontinuity measures proposed in a previous work and applied to Montreal’s cycling network, video data was collected from a pole-mounted camera at locations with discontinuity and control sites. After extracting road user trajectories from the video data, a trajectory clustering algorithm was applied to find cyclists’ motion patterns and the various maneuver strategies adopted by cyclists. Speeds and acceleration statistics are extracted and compared between different motion patterns and between discontinuity and control sites. Results show that cyclists undertake a larger number of maneuvers at points of discontinuity compared to their control sites, and that both cyclist accelerations and speeds exhibit larger variations at discontinuities compared to larger and more stable speeds at control sites

Effect of Amino Acids on the Corrosion and Metal Release from Copper and Stainless Steel

Copper (Cu) and stainless steel 316 L are widely used for biomedical applications, such as intrauterine devices and orthopedic/dental implants. Amino acids are abundantly present in biological environments. We investigated the influence of select amino acids on the corrosion of Cu under naturally aerated and deaerated conditions using a phosphate-free buffer. Amino acids increased the corrosion of Cu under both aeration conditions at pH 7.4. Cu release was also significantly (up to 18-fold) increased in the presence of amino acids, investigated at pH 7.4 and 37 °C for 24 h under naturally aerated conditions. Speciation modelling predicted a generally increased solubility of Cu in the presence of amino acids at pH 7.4. 316 L, investigated for metal release under similar conditions for comparison, released about 1,000-fold lower amounts of metals than did Cu and remained passive with no change in surface oxide composition or thickness. However, amino acids also increased the chromium release (up to 52-fold), significantly for lysine, and the iron release for cysteine, while nickel and molybdenum release remained unaffected. This was not predicted by solution speciation modelling. The surface analysis confirmed the adsorption of amino acids on 316 L and, to a lower extent, Cu coupons

Artificial intelligence and machine learning algorithms for early detection of skin cancer in community and primary care settings : a systematic review

Acknowledgments This systematic review was funded by the National Institute for Health Research Policy Research Programme, conducted through the Policy Research Unit in Cancer Awareness, Screening, and Early Diagnosis (PR-PRU-1217–21601). The views expressed in this publication are those of the authors and not necessarily those of the National Health Service, the NIHR or the Department of Health and Social Care. The first author (OTJ) was also supported by the CanTest Collaborative funded by Cancer Research UK (C8640/A23385), of which FMW is Director, JE is an Associate Director, and NC is Research Fellow. During protocol development, this Review benefited from the advice of an international expert panel from the CanTest collaborative, including Willie Hamilton (University of Exeter, Exeter, UK), Greg Rubin (University of Newcastle, Newcastle, UK), Hardeep Singh (Baylor College of Medicine, Houston, TX, USA), and Niek de Wit (University Medical Center Utrecht, Utrecht, Netherlands). The research was also supported by a Cancer Research UK Cambridge Centre Clinical Research Fellowship for OTJ, and a National Health and Medical Research Council Investigator Fellowship (APP1195302) for JE. The funding sources had no role in the study design, data collection, data analysis, data interpretation, writing of the report, or in the decision to submit for publication. The authors would like to thank Isla Kuhn (Reader Services Librarian, University of Cambridge Medical Library, Cambridge, UK) for her help in developing the search strategy. We also thank Smiji Saji, who assisted with the early stages of the Review, Haruyuki Yanaoka, who assisted with the translation and assessment of papers that were written in Korean, and Steve Morris who assisted with the analysis of the data.Peer reviewedPublisher PD

Crowd guilds: Worker-led reputation and feedback on crowdsourcing platforms

Crowd workers are distributed and decentralized. While decentralization is designed to utilize independent judgment to promote high-quality results, it paradoxically undercuts behaviors and institutions that are critical to high-quality work. Reputation is one central example: crowdsourcing systems depend on reputation scores from decentralized workers and requesters, but these scores are notoriously inflated and uninformative. In this paper, we draw inspiration from historical worker guilds (e.g., in the silk trade) to design and implement crowd guilds: centralized groups of crowd workers who collectively certify each other’s quality through double-blind peer assessment. A two-week field experiment compared crowd guilds to a traditional decentralized crowd work model. Crowd guilds produced reputation signals more strongly correlated with ground-truth worker quality than signals available on current crowd working platforms, and more accurate than in the traditional model