Visualising biological data: a semantic approach to tool and database integration

<p>Abstract</p> <p>Motivation</p> <p>In the biological sciences, the need to analyse vast amounts of information has become commonplace. Such large-scale analyses often involve drawing together data from a variety of different databases, held remotely on the internet or locally on in-house servers. Supporting these tasks are <it>ad hoc </it>collections of data-manipulation tools, scripting languages and visualisation software, which are often combined in arcane ways to create cumbersome systems that have been customised for a particular purpose, and are consequently not readily adaptable to other uses. For many day-to-day bioinformatics tasks, the sizes of current databases, and the scale of the analyses necessary, now demand increasing levels of automation; nevertheless, the unique experience and intuition of human researchers is still required to interpret the end results in any meaningful biological way. Putting humans in the loop requires tools to support real-time interaction with these vast and complex data-sets. Numerous tools do exist for this purpose, but many do not have optimal interfaces, most are effectively isolated from other tools and databases owing to incompatible data formats, and many have limited real-time performance when applied to realistically large data-sets: much of the user's cognitive capacity is therefore focused on controlling the software and manipulating esoteric file formats rather than on performing the research.</p> <p>Methods</p> <p>To confront these issues, harnessing expertise in human-computer interaction (HCI), high-performance rendering and distributed systems, and guided by bioinformaticians and end-user biologists, we are building reusable software components that, together, create a toolkit that is both architecturally sound from a computing point of view, and addresses both user and developer requirements. Key to the system's usability is its direct exploitation of semantics, which, crucially, gives individual components knowledge of their own functionality and allows them to interoperate seamlessly, removing many of the existing barriers and bottlenecks from standard bioinformatics tasks.</p> <p>Results</p> <p>The toolkit, named Utopia, is freely available from <url>http://utopia.cs.man.ac.uk/</url>.</p

Docetaxel-loaded liposomes: The effect of lipid composition and purification on drug encapsulation and in vitro toxicity

Docetaxel (DTX)-loaded liposomes have been formulated to overcome DTX solubility issue, improve its efficacy and reduce its toxicity. This study investigated the effect of steric stabilisation, varying liposome composition, and lipid:drug molar ratio on drug loading and on the physicochemical properties of the DTX-loaded liposomes. Size exclusion chromatography (SEC) was used to remove free DTX from the liposomal formulation, and its impact on drug loading and in vitro cytotoxicity was also evaluated. Liposomes composed of fluid, unsaturated lipid (DOPC:Chol:DSPE-PEG2000) showed the highest DTX loading compared to rigid, saturated lipids (DPPC:Chol:DSPE-PEG2000 and DSPC:Chol:DSPE-PEG2000). The inclusion of PEG showed a minimum effect on DTX encapsulation. Decreasing lipid:drug molar ratio from 40:1 to 5:1 led to an improvement in the loading capacities of DOPC-based liposomes only. Up to 3.6-fold decrease in drug loading was observed after liposome purification, likely due to the loss of adsorbed and loosely entrapped DTX in the SEC column. Our in vitro toxicity results in PC3 monolayer showed that non-purified, DTX-loaded DOPC:Chol liposomes were initially (24h) more potent than the purified ones, due to the fast action of the surface- adsorbed drug. However, we hypothesize that over time (48 and 72h) the purified, DTX-loaded DOPC:Chol liposomes became more toxic due to high intracellular release of encapsulated DTX. Finally, our cytotoxicity results in PC3 spheroids showed the superior activity of DTX-loaded liposomes compared to free DTX, which could overcome the DTX poor tissue penetration, drug resistance, and improve its therapeutic efficacy following systemic administration

Target Product Profile for a Machine Learning–Automated Retinal Imaging Analysis Software for Use in English Diabetic Eye Screening: Protocol for a Mixed Methods Study

\ua9 2024 JMIR Publications Inc.. All rights reserved.Background: Diabetic eye screening (DES) represents a significant opportunity for the application of machine learning (ML) technologies, which may improve clinical and service outcomes. However, successful integration of ML into DES requires careful product development, evaluation, and implementation. Target product profiles (TPPs) summarize the requirements necessary for successful implementation so these can guide product development and evaluation. Objective: This study aims to produce a TPP for an ML-automated retinal imaging analysis software (ML-ARIAS) system for use in DES in England. Methods: This work will consist of 3 phases. Phase 1 will establish the characteristics to be addressed in the TPP. A list of candidate characteristics will be generated from the following sources: an overview of systematic reviews of diagnostic test TPPs; a systematic review of digital health TPPs; and the National Institute for Health and Care Excellence’s Evidence Standards Framework for Digital Health Technologies. The list of characteristics will be refined and validated by a study advisory group (SAG) made up of representatives from key stakeholders in DES. This includes people with diabetes; health care professionals; health care managers and leaders; and regulators and policy makers. In phase 2, specifications for these characteristics will be drafted following a series of semistructured interviews with participants from these stakeholder groups. Data collected from these interviews will be analyzed using the shortlist of characteristics as a framework, after which specifications will be drafted to create a draft TPP. Following approval by the SAG, in phase 3, the draft will enter an internet-based Delphi consensus study with participants sought from the groups previously identified, as well as ML-ARIAS developers, to ensure feasibility. Participants will be invited to score characteristic and specification pairs on a scale from “definitely exclude” to “definitely include,” and suggest edits. The document will be iterated between rounds based on participants’ feedback. Feedback on the draft document will be sought from a group of ML-ARIAS developers before its final contents are agreed upon in an in-person consensus meeting. At this meeting, representatives from the stakeholder groups previously identified (minus ML-ARIAS developers, to avoid bias) will be presented with the Delphi results and feedback of the user group and asked to agree on the final contents by vote. Results: Phase 1 was completed in November 2023. Phase 2 is underway and expected to finish in March 2024. Phase 3 is expected to be complete in July 2024. Conclusions: The multistakeholder development of a TPP for an ML-ARIAS for use in DES in England will help developers produce tools that serve the needs of patients, health care providers, and their staff. The TPP development process will also provide methods and a template to produce similar documents in other disease areas

Obesity related methylation changes in DNA of peripheral blood leukocytes

<p>Abstract</p> <p>Background</p> <p>Despite evidence linking obesity to impaired immune function, little is known about the specific mechanisms. Because of emerging evidence that immune responses are epigenetically regulated, we hypothesized that DNA methylation changes are involved in obesity induced immune dysfunction and aimed to identify these changes.</p> <p>Method</p> <p>We conducted a genome wide methylation analysis on seven obese cases and seven lean controls aged 14 to 18 years from extreme ends of the obesity distribution and performed further validation of six CpG sites from six genes in 46 obese cases and 46 lean controls aged 14 to 30 years.</p> <p>Results</p> <p>In comparison with the lean controls, we observed one CpG site in the UBASH3A gene showing higher methylation levels and one CpG site in the TRIM3 gene showing lower methylation levels in the obese cases in both the genome wide step (<it>P </it>= 5 × 10^-6and <it>P </it>= 2 × 10^-5for the UBASH3A and the TRIM3 gene respectively) and the validation step (<it>P </it>= 0.008 and <it>P </it>= 0.001 for the UBASH3A and the TRIM3 gene respectively).</p> <p>Conclusions</p> <p>Our results provide evidence that obesity is associated with methylation changes in blood leukocyte DNA. Further studies are warranted to determine the causal direction of this relationship as well as whether such methylation changes can lead to immune dysfunction.</p> <p>See commentary: <url>http://www.biomedcentral.com/1741-7015/8/88/abstract</url></p

Factors associated with dental attendance among adolescents in Santiago, Chile

BACKGROUND: Dental treatment needs are commonly unmet among adolescents. It is therefore important to clarify the determinants of poor utilization of dental services among adolescents. METHODS: A total of 9,203 Chilean students aged 12–21 years provided information on dental visits, oral health related behavior, perceived oral health status, and socio-demographic determinants. School headmasters provided information on monthly tuition and annual fees. Based on the answers provided, three outcome variables were generated to reflect whether the respondent had visited the dentist during the past year or not; whether the last dental visit was due to symptoms; and whether the responded had ever been to a dentist. Aged adjusted multivariable logistic regression models were used to assess the influence of the covariates gender; oral health related behaviors (self-reported tooth brushing frequency & smoking habits); and measures of social position (annual education expenses; paternal income; and achieved parental education) on each outcome. RESULTS: Analyses showed that students who had not attended a dentist within the past year were more likely to be male (OR = 1.3); to report infrequent tooth brushing (OR = 1.3); to have a father without income (OR = 1.8); a mother with only primary school education (OR = 1.5); and were also more likely to report a poor oral health status (OR = 2.0), just as they were more likely to attend schools with lower tuition and fees (OR = 1.4). Students who consulted a dentist because of symptoms were more likely to have a father without income (OR = 1.4); to attend schools with low economic entry barriers (OR = 1.4); and they were more likely to report a poor oral health status (OR = 2.9). Students who had never visited a dentist were more likely to report infrequent tooth brushing (OR = 1.9) and to have lower socioeconomic positions independently of the indicator used. CONCLUSION: The results demonstrate that socioeconomic and behavioral factors are independently associated with the frequency of and reasons for dental visits in this adolescent population and that self-perceived poor oral health status is strongly associated with infrequent dental visits and symptoms

Ontologies in Quantitative Biology: A Basis for Comparison, Integration, and Discovery

As biology is becoming a data-driven discipline, ontologies become increasingly important for systematically capturing the existing knowledge. This essay discusses current trends and how ontologies can also be used for discovery

Keeping Pace with Your Eating: Visual Feedback Affects Eating Rate in Humans

Deliberately eating at a slower pace promotes satiation and eating quickly has been associated with a higher body mass index. Therefore, understanding factors that affect eating rate should be given high priority. Eating rate is affected by the physical/textural properties of a food, by motivational state, and by portion size and palatability. This study explored the prospect that eating rate is also influenced by a hitherto unexplored cognitive process that uses ongoing perceptual estimates of the volume of food remaining in a container to adjust intake during a meal. A 2 (amount seen; 300ml or 500ml) x 2 (amount eaten; 300ml or 500ml) between-subjects design was employed (10 participants in each condition). In two ‘congruent’ conditions, the same amount was seen at the outset and then subsequently consumed (300ml or 500ml). To dissociate visual feedback of portion size and actual amount consumed, food was covertly added or removed from a bowl using a peristaltic pump. This created two additional ‘incongruent’ conditions, in which 300ml was seen but 500ml was eaten or vice versa. We repeated these conditions using a savoury soup and a sweet dessert. Eating rate (ml per second) was assessed during lunch. After lunch we assessed fullness over a 60-minute period. In the congruent conditions, eating rate was unaffected by the actual volume of food that was consumed (300ml or 500ml). By contrast, we observed a marked difference across the incongruent conditions. Specifically, participants who saw 300ml but actually consumed 500ml ate at a faster rate than participants who saw 500ml but actually consumed 300ml. Participants were unaware that their portion size had been manipulated. Nevertheless, when it disappeared faster or slower than anticipated they adjusted their rate of eating accordingly. This suggests that the control of eating rate involves visual feedback and is not a simple reflexive response to orosensory stimulatio

PhenoFam-gene set enrichment analysis through protein structural information

<p>Abstract</p> <p>Background</p> <p>With the current technological advances in high-throughput biology, the necessity to develop tools that help to analyse the massive amount of data being generated is evident. A powerful method of inspecting large-scale data sets is gene set enrichment analysis (GSEA) and investigation of protein structural features can guide determining the function of individual genes. However, a convenient tool that combines these two features to aid in high-throughput data analysis has not been developed yet. In order to fill this niche, we developed the user-friendly, web-based application, PhenoFam.</p> <p>Results</p> <p>PhenoFam performs gene set enrichment analysis by employing structural and functional information on families of protein domains as annotation terms. Our tool is designed to analyse complete sets of results from quantitative high-throughput studies (gene expression microarrays, functional RNAi screens, <it>etc</it>.) without prior pre-filtering or hits-selection steps. PhenoFam utilizes Ensembl databases to link a list of user-provided identifiers with protein features from the InterPro database, and assesses whether results associated with individual domains differ significantly from the overall population. To demonstrate the utility of PhenoFam we analysed a genome-wide RNA interference screen and discovered a novel function of plexins containing the cytoplasmic RasGAP domain. Furthermore, a PhenoFam analysis of breast cancer gene expression profiles revealed a link between breast carcinoma and altered expression of PX domain containing proteins.</p> <p>Conclusions</p> <p>PhenoFam provides a user-friendly, easily accessible web interface to perform GSEA based on high-throughput data sets and structural-functional protein information, and therefore aids in functional annotation of genes.</p

InterPro in 2017-beyond protein family and domain annotations

InterPro (http://www.ebi.ac.uk/interpro/) is a freely available database used to classify protein sequences into families and to predict the presence of important domains and sites. InterProScan is the underlying software that allows both protein and nucleic acid sequences to be searched against InterPro's predictive models, which are provided by its member databases. Here, we report recent developments with InterPro and its associated software, including the addition of two new databases (SFLD and CDD), and the functionality to include residue-level annotation and prediction of intrinsic disorder. These developments enrich the annotations provided by InterPro, increase the overall number of residues annotated and allow more specific functional inferences