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- Khatri, C, et al.
(författare)
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Outcomes after perioperative SARS-CoV-2 infection in patients with proximal femoral fractures: an international cohort study
- 2021
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Ingår i: BMJ open. - : BMJ. - 2044-6055. ; 11:11, s. e050830-
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Tidskriftsartikel (refereegranskat)abstract
- Studies have demonstrated high rates of mortality in people with proximal femoral fracture and SARS-CoV-2, but there is limited published data on the factors that influence mortality for clinicians to make informed treatment decisions. This study aims to report the 30-day mortality associated with perioperative infection of patients undergoing surgery for proximal femoral fractures and to examine the factors that influence mortality in a multivariate analysis.SettingProspective, international, multicentre, observational cohort study.ParticipantsPatients undergoing any operation for a proximal femoral fracture from 1 February to 30 April 2020 and with perioperative SARS-CoV-2 infection (either 7 days prior or 30-day postoperative).Primary outcome30-day mortality. Multivariate modelling was performed to identify factors associated with 30-day mortality.ResultsThis study reports included 1063 patients from 174 hospitals in 19 countries. Overall 30-day mortality was 29.4% (313/1063). In an adjusted model, 30-day mortality was associated with male gender (OR 2.29, 95% CI 1.68 to 3.13, p<0.001), age >80 years (OR 1.60, 95% CI 1.1 to 2.31, p=0.013), preoperative diagnosis of dementia (OR 1.57, 95% CI 1.15 to 2.16, p=0.005), kidney disease (OR 1.73, 95% CI 1.18 to 2.55, p=0.005) and congestive heart failure (OR 1.62, 95% CI 1.06 to 2.48, p=0.025). Mortality at 30 days was lower in patients with a preoperative diagnosis of SARS-CoV-2 (OR 0.6, 95% CI 0.6 (0.42 to 0.85), p=0.004). There was no difference in mortality in patients with an increase to delay in surgery (p=0.220) or type of anaesthetic given (p=0.787).ConclusionsPatients undergoing surgery for a proximal femoral fracture with a perioperative infection of SARS-CoV-2 have a high rate of mortality. This study would support the need for providing these patients with individualised medical and anaesthetic care, including medical optimisation before theatre. Careful preoperative counselling is needed for those with a proximal femoral fracture and SARS-CoV-2, especially those in the highest risk groups.Trial registration numberNCT04323644
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| 5. |
- Xie, Z., et al.
(författare)
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Physiological responses to salinity change and diel-cycling hypoxia in gills of Hong Kong oyster Crassostrea hongkongensis
- 2023
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Ingår i: Aquaculture. - : Elsevier BV. - 0044-8486. ; 570
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Tidskriftsartikel (refereegranskat)abstract
- Global climate change is a frequent cause of salinity fluctuation in seawater, especially in aquaculture sites. Moreover, anthropologic activities often cause seawater eutrophication with the consequence that hypoxia ap-pears often during nighttime. The Hong Kong oyster Crassostrea hongkongensis, as a species that inhabits estuarine and coastal waters, is faced with such challenges. In this study, oyster physiological changes were considered to be closely related to hypoxia and salinity changes. Physiological indices were examined in Hong Kong oysters by employing six treatments to shed light into the effects of diel-cycling hypoxia (periodical hypoxia) and salinity change. Three salinities (10%o, low salinity; 25%o, normal salinity; and 35%o, high salinity) and two types of dissolved oxygen (normoxia, 6 mg/L throughout the day) and periodical hypoxic condition (6 mg/L at daytime for 12 h and 2 mg/L at nighttime for 12 h) were set. After 14-and 28-day exposures, gill tissues were sampled to detect changes in gill ATP production, mitochondrial membrane potential (MMP), mitochondrial reactive oxygen species production (ROS), and gill respiratory metabolic enzymes. Results indicated that periodical hypoxia and salinity change led to increased hexokinase (HK) and pyruvate kinase (PK) (p < 0.05). By contrast, they had no significant effect on mitochondrial number (MN). Adenosine-triphosphate (ATP) production only increased in the early exposure. In addition, low salinity with periodical hypoxia resulted in decreased MMP, lactate dehy-drogenase (LDH), and succinate dehydrogenase (SDH, p < 0.05). On the contrary, periodical hypoxia with high salinity led to increases in ATP and ROS and decreases in SDH, MMP, and LDH (p < 0.05). These results revealed that when diel-cycling hypoxia occurs with salinity change, the gill metabolism of Hong Kong oysters are gradually dominated by glycolysis while aerobic respiration decreases. Moreover, gill functions could be affected although energy accumulation exists during early exposure. Therefore, long-term exposure to periodical hypoxia with salinity change poses risk to the health and growth of Hong Kong oysters, impairing oyster aquaculture and coastal ecosystem health.
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| 6. |
- Bruin, WB, et al.
(författare)
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Structural neuroimaging biomarkers for obsessive-compulsive disorder in the ENIGMA-OCD consortium: medication matters
- 2020
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Ingår i: Translational psychiatry. - : Springer Science and Business Media LLC. - 2158-3188. ; 10:1, s. 342-
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Tidskriftsartikel (refereegranskat)abstract
- No diagnostic biomarkers are available for obsessive-compulsive disorder (OCD). Here, we aimed to identify magnetic resonance imaging (MRI) biomarkers for OCD, using 46 data sets with 2304 OCD patients and 2068 healthy controls from the ENIGMA consortium. We performed machine learning analysis of regional measures of cortical thickness, surface area and subcortical volume and tested classification performance using cross-validation. Classification performance for OCD vs. controls using the complete sample with different classifiers and cross-validation strategies was poor. When models were validated on data from other sites, model performance did not exceed chance-level. In contrast, fair classification performance was achieved when patients were grouped according to their medication status. These results indicate that medication use is associated with substantial differences in brain anatomy that are widely distributed, and indicate that clinical heterogeneity contributes to the poor performance of structural MRI as a disease marker.
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| 7. |
- Guo, Y., et al.
(författare)
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Hypercomplex Low Rank Reconstruction for NMR Spectroscopy
- 2023
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Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684. ; 203
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Tidskriftsartikel (refereegranskat)abstract
- Nuclear magnetic resonance (NMR) spectroscopy serves as an important tool to analyze chemicals and proteins in bioengineering. Multi-dimensional NMR offers a major improvement in resolution with multi-dimensional spectrum, but significantly increases data acquisition time and produces hypercomplex data that is difficult to be handled. To reduce this time, non-uniformly sampling can be applied to obtain undersampled data and using a reconstruction approach, such as the state-of-the-art low rank method, to remove the spectral artifacts introduced by undersampling. However, only complex format of signal, including the real and imaginary parts, is considered in previous low rank approach, which is less efficient when dealing with hypercomplex data that has multiple components. To solve this problem, a hypercomplex low rank model is proposed by introducing an adjoint matrix operation and then solved with a fast matrix factorization algorithm. This method explores redundant information among all the components of hypercomplex signal. Using simulated data and real protein data, we demonstrate that the proposed method provides a fast and high-fidelity reconstruction of hypercomplex spectroscopy in fast NMR. © 2022 Elsevier B.V.
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- Wang, Z., et al.
(författare)
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A Sparse Model-Inspired Deep Thresholding Network for Exponential Signal Reconstruction--Application in Fast Biological Spectroscopy
- 2022
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Ingår i: IEEE Transactions on Neural Networks and Learning Systems. - : Institute of Electrical and Electronics Engineers (IEEE). - 2162-237X .- 2162-2388. ; 34:10, s. 7578-92
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Tidskriftsartikel (refereegranskat)abstract
- The nonuniform sampling (NUS) is a powerful approach to enable fast acquisition but requires sophisticated reconstruction algorithms. Faithful reconstruction from partially sampled exponentials is highly expected in general signal processing and many applications. Deep learning (DL) has shown astonishing potential in this field, but many existing problems, such as lack of robustness and explainability, greatly limit its applications. In this work, by combining the merits of the sparse model-based optimization method and data-driven DL, we propose a DL architecture for spectra reconstruction from undersampled data, called MoDern. It follows the iterative reconstruction in solving a sparse model to build the neural network, and we elaborately design a learnable soft-thresholding to adaptively eliminate the spectrum artifacts introduced by undersampling. Extensive results on both synthetic and biological data show that MoDern enables more robust, high-fidelity, and ultrafast reconstruction than the state-of-the-art methods. Remarkably, MoDern has a small number of network parameters and is trained on solely synthetic data while generalizing well to biological data in various scenarios. Furthermore, we extend it to an open-access and easy-to-use cloud computing platform (XCloud-MoDern), contributing a promising strategy for further development of biological applications.
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