| 51. |
- Petzold, Martin, et al.
(författare)
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Towards an Ambient Assisted Living User Interaction Taxonomy
- 2013
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Ingår i: CHI '13 Extended Abstracts of the ACM International Conference on Human Factors in Computing Systems. - New York : ACM Press. - 9781450318990 ; , s. 49-54
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Konferensbidrag (refereegranskat)abstract
- Extensive research in the field of ambient assisted living (AAL) provides profound knowledge about the design of AAL systems. However, more generic design characteristics for user interaction have not been formalized for this domain yet. Thus, we propose to develop a domain specific taxonomy for the design of user interaction in AAL systems. We adopted a systematic taxonomy development approach that combines an empirical and a pseudo-conceptual strategy. Six co-researchers from different disciplines conduct the iterative research process. Next to AAL systems existing taxonomies in the field of human-computer interaction are analyzed following the Delphi method. In this paper we present our research process and preliminary results from the first iteration. The final taxonomy allows classification and should support the analysis of user interaction utilized in AAL systems. Furthermore, it can deal as a practical design guideline.
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| 52. |
- Andersson, Sören, 1957-, et al.
(författare)
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Chimeric MOMP antigen
- 2014
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Patent (populärvet., debatt m.m.)abstract
- The present invention regards polypeptides capable of eliciting an immunological response that is protective against Chlamydia trachomatis. The polypeptide comprises a first amino acid sequence which has at least 90% homology with the amino acid sequence according to SEQ ID NO: 1 and a second amino acid sequence which has at least 90% homology with the amino acid sequence according to SEQ ID NO: 2. Furthermore, production of these polypeptides and pharmaceutical compositions comprising them are also provided.
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| 53. |
- Klingström, Tomas, et al.
(författare)
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Supporting the Development of Biobanks in Low and Medium Income Countries
- 2016
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Ingår i: 2016 IST-AFRICA WEEK CONFERENCE. - 9781905824557
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Konferensbidrag (refereegranskat)abstract
- Biobanks are an organized collection of biological material and associated data. They are a fundamental resource for life science research and contribute to the development of pharmaceutical drugs, diagnostic markers and to a deeper understanding of the genetics that regulate the development of all life on earth. Biobanks are well established in High Income Countries (HIC) and are rapidly emerging in Low and Middle Income Countries (LMIC). Surveys among biobanks operating in a LMIC setting indicate that limited resources and short term funding tied to specific projects threaten the sustainability of the biobanks. Fit-for-purpose biobanks targeting major societal challenges such as HIV and Malaria provide an excellent basis for integrating biobanks with the available research communities in LMIC regions. But to become sustainable for the future it is important that biobanks become an integrated part of local research communities. To achieve this, the cost of operating biobanks must be lowered, templates must be developed to support local ethics committees and researchers must be given the opportunity to build experience in successfully operating biobank based research projects. The B3Africa consortium is based on these conclusions and set up to support biobank based research by creating a cost efficient Laboratory Information Management System (LIMS) for developing biobanks and also contribute to the training and capacity building in the local research community. The technical platform called the eB3Kit is open source and consists of a LIMS and a bioinformatics module based on the eBiokit that allow researchers to take control over the analysis of their own data. Along with the technical platform the consortium will also contribute training and support for the associated infrastructures necessary to regulate the ethical and legal implications of biobank based research.
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| 54. |
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| 55. |
- Javeed, Ashir, 1989-, et al.
(författare)
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Predictive Power of XGBoost_BiLSTM Model : A Machine-Learning Approach for Accurate Sleep Apnea Detection Using Electronic Health Data
- 2023
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Ingår i: International Journal of Computational Intelligence Systems. - : Springer Nature. - 1875-6891 .- 1875-6883. ; 16:1
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Tidskriftsartikel (refereegranskat)abstract
- Sleep apnea is a common disorder that can cause pauses in breathing and can last from a few seconds to several minutes, as well as shallow breathing or complete cessation of breathing. Obstructive sleep apnea is strongly associated with the risk of developing several heart diseases, including coronary heart disease, heart attack, heart failure, and stroke. In addition, obstructive sleep apnea increases the risk of developing irregular heartbeats (arrhythmias), which can lead to low blood pressure. To prevent these conditions, this study presents a novel machine-learning (ML) model for predicting sleep apnea based on electronic health data that provides accurate predictions and helps in identifying the risk factors that contribute to the development of sleep apnea. The dataset used in the study includes 75 features and 10,765 samples from the Swedish National Study on Aging and Care (SNAC). The proposed model is based on two modules: the XGBoost module assesses the most important features from feature space, while the Bidirectional Long Short-Term Memory Networks (BiLSTM) module classifies the probability of sleep apnea. Using a cross-validation scheme, the proposed XGBoost_BiLSTM algorithm achieves an accuracy of 97% while using only the six most significant features from the dataset. The model’s performance is also compared with conventional long-short-term memory networks (LSTM) and other state-of-the-art ML models. The results of the study suggest that the proposed model improved the diagnosis and treatment of sleep apnea by identifying the risk factors.
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| 56. |
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| 57. |
- Orre, Lukas Minus, et al.
(författare)
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SubCellBarCode : Proteome-wide Mapping of Protein Localization and Relocalization
- 2019
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Ingår i: Molecular Cell. - : Elsevier BV. - 1097-2765 .- 1097-4164. ; 73:1, s. 166-182.e7
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Tidskriftsartikel (refereegranskat)abstract
- Subcellular localization is a main determinant of protein function; however, a global view of cellular proteome organization remains relatively unexplored. We have developed a robust mass spectrometry-based analysis pipeline to generate a proteome-wide view of subcellular localization for proteins mapping to 12,418 individual genes across five cell lines. Based on more than 83,000 unique classifications and correlation profiling, we investigate the effect of alternative splicing and protein domains on localization, complex member co-localization, cell-type-specific localization, as well as protein relocalization after growth factor inhibition. Our analysis provides information about the cellular architecture and complexity of the spatial organization of the proteome; we show that the majority of proteins have a single main subcellular location, that alternative splicing rarely affects subcellular location, and that cell types are best distinguished by expression of proteins exposed to the surrounding environment. The resource is freely accessible via www.subcellbarcode.org.
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| 58. |
- Yewale, Priti Prabhakar, et al.
(författare)
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Molecular profiling of multidrug-resistant river water isolates : insights into resistance mechanism and potential inhibitors
- 2020
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Ingår i: Environmental Science and Pollution Research. - : Springer. - 0944-1344 .- 1614-7499. ; 27:22, s. 27279-27292
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Tidskriftsartikel (refereegranskat)abstract
- Polluted waters are an important reservoir for antibiotic resistance genes and multidrug-resistant bacteria. This report describes the microbial community, antibiotic resistance genes, and the genetic profile of extended spectrum β-lactamase strains isolated from rivers at, Pune, India. ESBL-producing bacteria isolated from diverse river water catchments running through Pune City were characterized for their antibiotic resistance. The microbial community and types of genes which confer antibiotic resistance were identified followed by the isolation of antibiotic-resistant bacteria on selective media and their genome analysis. Four representative isolates were sequenced using next generation sequencing for genomic analysis. They were identified as Pseudomonas aeruginosa, Escherichia coli, and two isolates were Enterobacter cloacae. The genes associated with the multidrug efflux pumps, such as tolC, macA, macB, adeL, and rosB, were detected in the isolates. As MacAB-TolC is an ABC type efflux pump responsible for conferring resistance in bacteria to several antibiotics, potential efflux pump inhibitors were identified by molecular docking. The homology model of their MacB protein with that from Escherichia coli K12 demonstrated structural changes in different motifs of MacB. Molecular docking of reported efflux pump inhibitors revealed the highest binding affinity of compound MC207-110 against MacB. It also details the potential efflux pump inhibitors that can serve as possible drug targets in drug development and discovery.
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| 59. |
- Palsdottir, Vilborg, 1979, et al.
(författare)
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Postnatal deficiency of essential fatty acids in mice results in resistance to diet-induced obesity and low plasma insulin during adulthood
- 2011
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Ingår i: Prostaglandins, Leukotrienes and Essential Fatty Acids. - : Elsevier BV. - 1532-2823 .- 0952-3278. ; 84:3-4, s. 85-92
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Tidskriftsartikel (refereegranskat)abstract
- Our objective was to investigate the long-term metabolic effects of postnatal essential fatty acid deficiency (EFAD). Mouse dams were fed an EFAD diet or an isoenergetic control diet 4 days before delivery and throughout lactation. The pups were weaned to standard diet (STD) and were later subdivided into two groups: receiving high fat diet (HFD) or STD. Body composition, energy expenditure, food intake and leptin levels were analyzed in adult offspring. Blood glucose and plasma insulin concentrations were measured before and during a glucose tolerance test. EFAD offspring fed STD were leaner with lower plasma leptin and insulin concentrations compared to controls. EFAD offspring fed HFD were resistant to diet-induced obesity, had higher energy expenditure and lower levels of plasma leptin and insulin compared to controls. These results indicate that the fatty acid composition during lactation is important for body composition and glucose tolerance in the adult offspring.
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| 60. |
- Gomariz, Alvaro, et al.
(författare)
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Modality attention and sampling enables deep learning with heterogeneous marker combinations in fluorescence microscopy
- 2021
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Ingår i: Nature Machine Intelligence. - : Springer Nature. - 2522-5839. ; 3:9, s. 799-811
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Tidskriftsartikel (refereegranskat)abstract
- Fluorescence microscopy allows for a detailed inspection of cells, cellular networks and anatomical landmarks by staining with a variety of carefully selected markers visualized as colour channels. Quantitative characterization of structures in acquired images often relies on automatic image analysis methods. Despite the success of deep learning methods in other vision applications, their potential for fluorescence image analysis remains underexploited. One reason lies in the considerable workload required to train accurate models, which are normally specific for a given combination of markers and therefore applicable to a very restricted number of experimental settings. We herein propose ‘marker sampling and excite’—a neural network approach with a modality sampling strategy and a novel attention module that together enable (1) flexible training with heterogeneous datasets with combinations of markers and (2) successful utility of learned models on arbitrary subsets of markers prospectively. We show that our single neural network solution performs comparably to an upper bound scenario in which an ensemble of many networks is naively trained for each possible marker combination separately. We also demonstrate the feasibility of this framework in high-throughput biological analysis by revising a recent quantitative characterization of bone-marrow vasculature in three-dimensional confocal microscopy datasets and further confirm the validity of our approach on another substantially different dataset of microvessels in foetal liver tissues. Not only can our work substantially ameliorate the use of deep learning in fluorescence microscopy analysis, but it can also be utilized in other fields with incomplete data acquisitions and missing modalities.
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