| 1. |
- Falk Erhag, Hanna, et al.
(författare)
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Concluding Remarks
- 2022
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Ingår i: A Multidisciplinary Approach to Capability in Age and Ageing. - Chem : Springer. - 9783030780654 ; 18:2, s. 143-144
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Bokkapitel (övrigt vetenskapligt/konstnärligt)
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| 2. |
- Berglund, Fanny, et al.
(författare)
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Evidence for wastewaters as environments where mobile antibiotic resistance genes emerge
- 2023
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Ingår i: Communications Biology. - : Springer Science and Business Media LLC. - 2399-3642. ; 6
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Tidskriftsartikel (refereegranskat)abstract
- The emergence and spread of mobile antibiotic resistance genes (ARGs) in pathogens have become a serious threat to global health. Still little is known about where ARGs gain mobility in the first place. Here, we aimed to collect evidence indicating where suchinitial mobilizationevents of clinically relevant ARGs may have occurred. We found that the majority of previously identified origin species did not carry the mobilizing elements that likely enabled intracellular mobility of the ARGs, suggesting a necessary interplay between different bacteria. Analyses of a broad range of metagenomes revealed that wastewaters and wastewater-impacted environments had by far the highest abundance of both origin species and corresponding mobilizing elements. Most origin species were only occasionally detected in other environments. Co-occurrence of origin species and corresponding mobilizing elements were rare in human microbiota. Our results identify wastewaters and wastewater-impacted environments as plausible arenas for the initial mobilization of resistance genes.
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| 3. |
- Palmquist, Anders, 1977, et al.
(författare)
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Complex geometry and integrated macro-porosity: Clinical applications of electron beam melting to fabricate bespoke bone-anchored implants
- 2023
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Ingår i: Acta Biomaterialia. - : Elsevier BV. - 1742-7061 .- 1878-7568. ; 156, s. 125-145
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Forskningsöversikt (refereegranskat)abstract
- The last decade has witnessed rapid advancements in manufacturing technologies for biomedical implants. Additive manufacturing (or 3D printing) has broken down major barriers in the way of producing complex 3D geometries. Electron beam melting (EBM) is one such 3D printing process applicable to metals and alloys. EBM offers build rates up to two orders of magnitude greater than comparable laser-based technologies and a high vacuum environment to prevent accumulation of trace elements. These features make EBM particularly advantageous for materials susceptible to spontaneous oxidation and nitrogen pick-up when exposed to air (e.g., titanium and titanium-based alloys). For skeletal reconstruction(s), anatomical mimickry and integrated macro-porous architecture to facilitate bone ingrowth are undoubtedly the key features of EBM manufactured implants. Using finite element modelling of physiological loading conditions, the design of a prosthesis may be further personalised. This review looks at the many unique clinical applications of EBM in skeletal repair and the ground-breaking innovations in prosthetic rehabilitation. From a simple acetabular cup to the fifth toe, from the hand-wrist complex to the shoulder, and from vertebral replacement to cranio-maxillofacial reconstruction, EBM has experienced it all. While sternocostal reconstructions might be rare, the repair of long bones using EBM manufactured implants is becoming exceedingly frequent. Despite the various merits, several challenges remain yet untackled. Nevertheless, with the capability to produce osseointegrating implants of any conceivable shape/size, and permissive of bone ingrowth and functional loading, EBM can pave the way for numerous fascinating and novel applications in skeletal repair, regeneration, and rehabilitation. Statement of significance: Electron beam melting (EBM) offers unparalleled possibilities in producing contaminant-free, complex and intricate geometries from alloys of biomedical interest, including Ti6Al4V and CoCr. We review the diverse range of clinical applications of EBM in skeletal repair, both as mass produced off-the-shelf implants and personalised, patient-specific prostheses. From replacing large volumes of disease-affected bone to complex, multi-material reconstructions, almost every part of the human skeleton has been replaced with an EBM manufactured analog to achieve macroscopic anatomical-mimickry. However, various questions regarding long-term performance of patient-specific implants remain unaddressed. Directions for further development include designing personalised implants and prostheses based on simulated loading conditions and accounting for trabecular bone microstructure with respect to physiological factors such as patient's age and disease status.
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| 4. |
- Trigo, João Pedro, 1995, et al.
(författare)
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In vitro digestibility and Caco-2 cell bioavailability of sea lettuce (Ulva fenestrata) proteins extracted using pH-shift processing
- 2021
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Ingår i: Food Chemistry. - : Elsevier BV. - 0308-8146 .- 1873-7072. ; 356
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Tidskriftsartikel (refereegranskat)abstract
- Seaweed is a promising sustainable source of vegan protein as its farming does not require arable land, pesticides/insecticides, nor freshwater supply. However, to be explored as a novel protein source the content and nutritional quality of protein in seaweed need to be improved. We assessed the influence of pH-shift processing on protein degree of hydrolysis (%DH), protein/peptide size distribution, accessibility, and cell bioavailability of Ulva fenestrata proteins after in vitro gastrointestinal digestion. pH-shift processing of Ulva, which concentrated its proteins 3.5-times, significantly improved the %DH from 27.7±2.6% to 35.7±2.1% and the amino acid accessibility from 56.9±4.1% to 72.7±0.6%. Due to the higher amino acid accessibility, the amount of most amino acids transported across the cell monolayers was higher in the protein extracts. Regarding bioavailability, both Ulva and protein extracts were as bioavailable as casein. The protein/peptide molecular size distribution after digestion did not disclose a clear association with bioavailability.
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| 5. |
- Trigo, João Pedro, 1995, et al.
(författare)
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Mild blanching prior to pH-shift processing of Saccharina latissima retains protein extraction yields and amino acid levels of extracts while minimizing iodine content
- 2023
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Ingår i: Food Chemistry. - : Elsevier BV. - 0308-8146 .- 1873-7072. ; 404
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Tidskriftsartikel (refereegranskat)abstract
- The seaweed Saccharina latissima is often blanched to lower iodine levels, however, it is not known how blanching affects protein extraction. We assessed the effect of blanching or soaking (80/45/12 °C, 2 min) on protein yield and protein extract characteristics after pH-shift processing of S. latissima. Average protein yields and extract amino acid levels ranked treatments as follows: blanching-45 °C ∼ control > soaking ∼ blanching-80 °C. Although blanching-45 °C decreased protein solubilization yield at pH 12, it increased isoelectric protein precipitation yield at pH 2 (p < 0.05). The former could be explained by a higher ratio of large peptides/proteins in the blanched biomass as shown by HP-SEC, whereas the latter by blanching-induced lowering of ionic strength, as verified by a dialysis model. Moreover, blanching-45 °C yielded a protein extract with 49 % less iodine compared with the control extract. We recommend blanching-45 °C since it is effective at removing iodine and does not compromise total protein extraction yield.
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| 6. |
- Bakidou, Anna, 1996, et al.
(författare)
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On Scene Injury Severity Prediction (OSISP) model for trauma developed using the Swedish Trauma Registry
- 2023
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Ingår i: BMC Medical Informatics and Decision Making. - 1472-6947. ; 23:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Providing optimal care for trauma, the leading cause of death for young adults, remains a challenge e.g., due to field triage limitations in assessing a patient’s condition and deciding on transport destination. Data-driven On Scene Injury Severity Prediction (OSISP) models for motor vehicle crashes have shown potential for providing real-time decision support. The objective of this study is therefore to evaluate if an Artificial Intelligence (AI) based clinical decision support system can identify severely injured trauma patients in the prehospital setting. Methods: The Swedish Trauma Registry was used to train and validate five models – Logistic Regression, Random Forest, XGBoost, Support Vector Machine and Artificial Neural Network – in a stratified 10-fold cross validation setting and hold-out analysis. The models performed binary classification of the New Injury Severity Score and were evaluated using accuracy metrics, area under the receiver operating characteristic curve (AUC) and Precision-Recall curve (AUCPR), and under- and overtriage rates. Results: There were 75,602 registrations between 2013–2020 and 47,357 (62.6%) remained after eligibility criteria were applied. Models were based on 21 predictors, including injury location. From the clinical outcome, about 40% of patientswere undertriaged and 46% were overtriaged. Models demonstrated potential for improved triaging and yielded AUC between 0.80–0.89 and AUCPR between 0.43–0.62. Conclusions: AI based OSISP models have potential to provide support during assessment of injury severity. The findings may be used for developing tools to complement field triage protocols, with potential to improve prehospital trauma care and thereby reduce morbidity and mortality for a large patient population.
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| 7. |
- Wiszmeg, Andréa, et al.
(författare)
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Transforming trash to treasure Cultural ambiguity in foetal cell research
- 2021
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Ingår i: Philosophy Ethics and Humanities in Medicine. - : Springer Science and Business Media LLC. - 1747-5341. ; 16:1
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Tidskriftsartikel (refereegranskat)abstract
- Background Rich in different kind of potent cells, embryos are used in modern regenerative medicine and research. Neurobiologists today are pushing the boundaries for what can be done with embryos existing in the transitory margins of medicine. Therefore, there is a growing need to develop conceptual frameworks for interpreting the transformative cultural, biological and technical processes involving these aborted, donated and marginal embryos. This article is a contribution to this development of frameworks. Methods This article examines different emotional, cognitive and discursive strategies used by neurobiologists in a foetal cell transplantation trial in Parkinson's disease research, using cells harvested from aborted embryos. Two interviews were analysed in the light of former observations in the processing laboratories, using the anthropologist Mary Douglas's concept of pollution behaviour and the linguist, philosopher, psychoanalyst and feminist Julia Kristeva's concept of the abjective to explain and make sense of the findings. Results The findings indicate that the labour performed by the researchers in the trial work involves transforming the foetal material practically, as well as culturally, from trash to treasure. The transformation process contains different phases, and in the interview material we observed that the foetal material or cells were considered objects, subjects or rejected as abject by the researchers handling them, depending on what phase of process or practice they referred to or had experience of. As demonstrated in the analysis, it is the human origin of the cell that makes it abjective and activates pollution discourse, when the researchers talk of their practice. Conclusions The marginal and ambiguous status of the embryo that emerges in the accounts turns the scientists handling foetal cells into liminal characters in modern medicine. Focusing on how practical as well as emotional and cultural strategies and rationalizations of the researchers emerge in interview accounts, this study adds insights on the rationale of practically procuring, transforming and utilizing the foetal material to the already existing studies focused on the donations. We also discuss why the use and refinement of a tissue, around which there is practical consensus but cultural ambiguity, deserves further investigation.
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| 8. |
- Yewale, Priti, et al.
(författare)
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Studies on Biosmotrap : A multipurpose biological air purifier to minimize indoor and outdoor air pollution
- 2022
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Ingår i: Journal of Cleaner Production. - : Elsevier. - 0959-6526 .- 1879-1786. ; 357
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Tidskriftsartikel (refereegranskat)abstract
- Air pollution is a serious health concern that affects many people across the globe. The major air pollutants are particulate matter, carbon oxides, nitrogen oxides, sulphur oxides, volatile organic compounds, polycyclic aromatics and free radicals which cause severe respiratory distress and infections. The existing air cleaning systems suffer from drawbacks of high cost and generation of secondary pollutants. A novel biological air filter “Biosmotrap” which is a laminate composite of sponge gourd and algae was developed. Biosmotrap placed in a carrier assembly on exhaust of vehicles, could remove carbon monoxide, nitric oxide, nitrogen dioxide, and fine particulate matter (PM2.5) from the vehicular emissions resulting in cleaner emissions. Biosmotrap decreased carbon monoxide from 1,423,992 μg/m3 to 76,756 μg/m3, nitric oxide from 71,128 μg/m3 to 9982 μg/m3, nitrogen dioxide from 565 μg/m3 to 188 μg/m3 and PM2.5 from 3200 μg/m3 to 60 μg/m3 from a polluting vehicle. Biosmotrap removed 60–80% of indoor pollutants from cigarette smoke and incense-stick smoke. Biosmotrap could protect the human cells from oxidative DNA damage induced by indoor air pollutants. Hibiscus rosa-sinensis plants exposed to air filtered through Biosmotrap were healthy as compared to the plants directly exposed to polluted air. Biosmotrap is an economic, efficient, eco-friendly filter that is superior to existing air filtration methods.
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| 9. |
- Ahluwalia, Bani, et al.
(författare)
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Differences in Metabolite Composition of Aloe barbadensis Mill. Extracts Lead to Differential Effects on Human Blood T Cell Activity In Vitro
- 2022
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Ingår i: Molecules. - : MDPI AG. - 1420-3049 .- 1420-3049. ; 27:19
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Tidskriftsartikel (refereegranskat)abstract
- Aloe barbadensis Mill. (Aloe) is used for diverse therapeutic properties including immunomodulation. However, owing to the compositionally complex nature of Aloe, bioactive component(s) responsible for its beneficial properties, though thought to be attributed to polysaccharides (acemannan), remain unknown. We therefore aimed to determine the metabolite composition of various commercial Aloe extracts and assess their effects on human blood T cell activity in vitro. Peripheral blood mononuclear cells (PBMC) from healthy donors were stimulated polyclonally in presence or absence of various Aloe extracts. T cell phenotype and proliferation were investigated by flow cytometry. Aloe extracts were analyzed using targeted 1H-NMR spectroscopy for standard phytochemical quality characterization and untargeted gas chromatography mass spectrometry (GC-MS) for metabolite profiling. Aloe extracts differing in their standard phytochemical composition had varying effects on T cell activation, proliferation, apoptosis, and cell-death in vitro, although this was not related to the acemannan content. Furthermore, each Aloe extract had its own distinct metabolite profile, where extracts rich in diverse sugar and sugar-derivatives were associated with reduced T cell activity. Our results demonstrate that all commercial Aloe extracts are unique with distinct metabolite profiles, which lead to differential effects on T cell activity in vitro, independent of the acemannan content.
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| 10. |
- 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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