55 research outputs found

    Automated bow shock and magnetopause boundary detection with Cassini using threshold and deep learning methods

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    Two algorithms set for automatic detection of bow shock (BS) and magnetopause (MP) boundaries at Saturn using in situ magnetic field and plasma data acquired by the Cassini spacecraft are presented. Traditional threshold-based and modern deep learning algorithms were investigated for the task of boundary detection. Sections of Cassini’s orbits were pre-selected based on empirical BS and MP boundary models, and from outlier detection in magnetic field data using an autoencoder neural network. The threshold method was applied to pre-selected magnetic field and plasma data independently to compute parameters to which a threshold was applied to determine the presence of a boundary. The deep learning method used a type of convolutional neural network (CNN) called ResNet on images of magnetic field time series data and electron energy-time spectrograms to classify the presence of boundaries. 2012 data were held out of the training data to test and compare the algorithms on unseen data. The comparison showed that the CNN method applied to plasma data outperformed the threshold method. A final multiclass CNN classifier trained on plasma data obtained F1 scores of 92.1% ± 1.4% for BS crossings and 84.7% ± 1.9% for MP crossings on a corrected test dataset (from use of a bootstrap method). Reliable automated detection of boundary crossings could enable future spacecraft experiments like the PEP instrument on the upcoming JUICE spacecraft mission to dynamically adapt the best observing mode based on rapid classification of the boundary crossings as soon as it appears, thus yielding higher quality data and improved potential for scientific discovery

    High-Density Transcriptional Initiation Signals Underline Genomic Islands in Bacteria

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    Genomic islands (GIs), frequently associated with the pathogenicity of bacteria and having a substantial influence on bacterial evolution, are groups of “alien” elements which probably undergo special temporal–spatial regulation in the host genome. Are there particular hallmark transcriptional signals for these “exotic” regions? We here explore the potential transcriptional signals that underline the GIs beyond the conventional views on basic sequence composition, such as codon usage and GC property bias. It showed that there is a significant enrichment of the transcription start positions (TSPs) in the GI regions compared to the whole genome of Salmonella enterica and Escherichia coli. There was up to a four-fold increase for the 70% GIs, implying high-density TSPs profile can potentially differentiate the GI regions. Based on this feature, we developed a new sliding window method GIST, Genomic-island Identification by Signals of Transcription, to identify these regions. Subsequently, we compared the known GI-associated features of the GIs detected by GIST and by the existing method Islandviewer to those of the whole genome. Our method demonstrates high sensitivity in detecting GIs harboring genes with biased GI-like function, preferred subcellular localization, skewed GC property, shorter gene length and biased “non-optimal” codon usage. The special transcriptional signals discovered here may contribute to the coordinate expression regulation of foreign genes. Finally, by using GIST, we detected many interesting GIs in the 2011 German E. coli O104:H4 outbreak strain TY-2482, including the microcin H47 system and gene cluster ycgXEFZ-ymgABC that activates the production of biofilm matrix. The aforesaid findings highlight the power of GIST to predict GIs with distinct intrinsic features to the genome. The heterogeneity of cumulative TSPs profiles may not only be a better identity for “alien” regions, but also provide hints to the special evolutionary course and transcriptional regulation of GI regions

    Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

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    Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat

    Data-driven decarbonisation pathways for reducing life cycle GHG emissions from food waste in the hospitality and food service sectors

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    Abstract The Hospitality and Food Service (HaFS) sectors are notoriously known for their contribution to the food waste problem. Hence, there is an urgent need to devise strategies to reduce food waste in the HaFS sectors and to decarbonise their operation to help fight hunger, achieve food security, improve nutrition and mitigate climate change. This study proposes three streams to decarbonise the staff cafeteria operation in an integrated resort in Macau. These include upstream optimisation to reduce unserved food waste, midstream education to raise awareness amongst staff about the impact of food choices on the climate and health, and finally downstream recognition to reduce edible plate waste using a state-of-the-art computer vision system. Technology can be an effective medium to facilitate desired behavioural change through nudging, much like how speed cameras can cause people to slow down and help save lives. The holistic and data-driven approach taken revealed great potential for organisations or institutions that offer catering services to reduce their food waste and associated carbon footprint whilst educating individuals about the intricate link between food, climate and well-being

    Unfolded Protein Response (UPR) in Survival, Dormancy, Immunosuppression, Metastasis, and Treatments of Cancer Cells

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    The endoplasmic reticulum (ER) has diverse functions, and especially misfolded protein modification is in the focus of this review paper. With a highly regulatory mechanism, called unfolded protein response (UPR), it protects cells from the accumulation of misfolded proteins. Nevertheless, not only does UPR modify improper proteins, but it also degrades proteins that are unable to recover. Three pathways of UPR, namely PERK, IRE-1, and ATF6, have a significant role in regulating stress-induced physiological responses in cells. The dysregulated UPR may be involved in diseases, such as atherosclerosis, heart diseases, amyotrophic lateral sclerosis (ALS), and cancer. Here, we discuss the relation between UPR and cancer, considering several aspects including survival, dormancy, immunosuppression, angiogenesis, and metastasis of cancer cells. Although several moderate adversities can subject cancer cells to a hostile environment, UPR can ensure their survival. Excessive unfavorable conditions, such as overloading with misfolded proteins and nutrient deprivation, tend to trigger cancer cell death signaling. Regarding dormancy and immunosuppression, cancer cells can survive chemotherapies and acquire drug resistance through dormancy and immunosuppression. Cancer cells can also regulate the downstream of UPR to modulate angiogenesis and promote metastasis. In the end, regulating UPR through different molecular mechanisms may provide promising anticancer treatment options by suppressing cancer proliferation and progression
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