AIMS65 scoring system is comparable to Glasgow-Blatchford score or Rockall score for prediction of clinical outcomes for non-variceal upper gastrointestinal bleeding

Background Risk stratification for patients with nonvariceal upper gastrointestinal (NVUGI) bleeding is crucial for successful prognosis and treatment. Recently, the AIMS65 score has been used to predict mortality risk and rebleeding. The purpose of this study was to compare the performance of the AIMS65 score with the Glasgow-Blatchford score (GBS), Rockall score, and pre-endoscopic Rockall score in Korea. Methods We retrospectively studied 512 patients with NVUGI bleeding who were treated at a university hospital between 2013 and 2016. The AIMS65, GBS, Rockall score, and pre-endoscopic Rockall score were used to stratify patients based on their bleeding risk. The primary outcome was in-hospital mortality. The secondary outcomes were composite clinical outcomes of mortality, rebleeding, and intensive care unit (ICU) admission. Each scoring system was compared using the receiver-operating curve (ROC). Results A total of 17 patients (3.3%) died and rebleeding developed in 65 patients (12.7%). Eighty-six patients (16.8%) required ICU admission. The AIMS65 (area under the curve (AUC) 0.84, 95% confidence interval, 0.81–0.88)) seemed to be superior to the GBS (AUC 0.72, 0.68–0.76), the Rockall score (AUC 0.75, 0.71–0.79), or the pre-endoscopic Rockall score (AUC 0.74, 0.70–0.78) in predicting in-hospital mortality, but there was not a statistically significant difference between the groups (P = 0.07). The AUC value of the AIMS65 was not significantly different from the other scoring systems in prediction of rebleeding, endoscopic intervention, or ICU admission. Conclusions The AIMS65 score in NVUGI bleeding patients was comparable to the GBS or Rockall scoring systems when predicting the mortality, rebleeding, or ICU admission. Because AIMS65 is a much easier, readily calculated scoring system compared to the others, we would recommend using the AIMS65 in daily practice.This work was supported by the 2018 Inje University research grant. Funding bodies were not involved in the study design, collection, analysis and interpretation of the data or in writing of the manuscript

BallGAN: 3D-aware Image Synthesis with a Spherical Background

3D-aware GANs aim to synthesize realistic 3D scenes such that they can be rendered in arbitrary perspectives to produce images. Although previous methods produce realistic images, they suffer from unstable training or degenerate solutions where the 3D geometry is unnatural. We hypothesize that the 3D geometry is underdetermined due to the insufficient constraint, i.e., being classified as real image to the discriminator is not enough. To solve this problem, we propose to approximate the background as a spherical surface and represent a scene as a union of the foreground placed in the sphere and the thin spherical background. It reduces the degree of freedom in the background field. Accordingly, we modify the volume rendering equation and incorporate dedicated constraints to design a novel 3D-aware GAN framework named BallGAN. BallGAN has multiple advantages as follows. 1) It produces more reasonable 3D geometry; the images of a scene across different viewpoints have better photometric consistency and fidelity than the state-of-the-art methods. 2) The training becomes much more stable. 3) The foreground can be separately rendered on top of different arbitrary backgrounds.Comment: Project Page: https://minjung-s.github.io/ballga

Resting-state prefrontal EEG biomarker in correlation with postoperative delirium in elderly patients

Postoperative delirium (POD) is associated with adverse outcomes in elderly patients after surgery. Electroencephalography (EEG) can be used to develop a potential biomarker for degenerative cerebral dysfunctions, including mild cognitive impairment and dementia. This study aimed to explore the relationship between preoperative EEG and POD. We included 257 patients aged >70 years who underwent spinal surgery. We measured the median dominant frequency (MDF), which is a resting-state EEG biomarker involving intrinsic alpha oscillations that reflect an idle cortical state, from the prefrontal regions. Additionally, the mini-mental state examination and Montreal cognitive assessment (MoCA) were performed before surgery as well as 5 days after surgery. For long-term cognitive function follow up, the telephone interview for cognitive status™ (TICS) was performed 1 month and 1 year after surgery. Fifty-two (20.2%) patients were diagnosed with POD. A multivariable logistic regression analysis that included age, MoCA score, Charlson comorbidity index score, Mini Nutritional Assessment, and the MDF as variables revealed that the MDF had a significant odds ratio of 0.48 (95% confidence interval 0.27–0.85). Among the patients with POD, the postoperative neurocognitive disorders could last up to 1 year. Low MDF on preoperative EEG was associated with POD in elderly patients undergoing surgery. EEG could be a novel potential tool for identifying patients at a high risk of POD

CD160 serves as a negative regulator of NKT cells in acute hepatic injury

[EN] CD160 and BTLA both bind to herpes virus entry mediator. Although a negative regulatory function of BTLA in natural killer T (NKT) cell activation has been reported, whether CD160 is also involved is unclear. By analyzing CD160−/− mice and mixed bone marrow chimeras, we show that CD160 is not essential for NKT cell development. However, CD160−/− mice exhibit severe liver injury after in vivo challenge with α-galactosylceramide (α-GalCer). Moreover, CD160−/− mice are more susceptible to Concanavalin A challenge, and display elevated serum AST and ALT levels, hyperactivation of NKT cells, and enhanced IFN-γ, TNF, and IL-4 production. Lastly, inhibition of BTLA by anti-BTLA mAb aggravates α-GalCer-induced hepatic injury in CD160−/− mice, suggesting that both CD160 and BTLA serve as non-overlapping negative regulators of NKT cells. Our data thus implicate CD160 as a co-inhibitory receptor that delivers antigen-dependent signals in NKT cells to dampen cytokine production during early innate immune activationSIWe thank the NIH Tetramer Core Facility for providing PBS 57 ligand loaded CD1d Tetramers. Further, we thank the staffs of Gyerim Experimental Animal Resource Center for animal care and technical assistance. K.-M. Lee was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT, and Future planning (NRF-2016M3A9B6948342, NRF- 2017R1A2B3004828, and NRF-2018M3A9D3079288). S.-J. Kim was supported by the Korea Health Industry Development Institute (KHIDI-HI14C2640) grant funded by Korea Government. S.-J. Ha was supported by a grant from the NRF (NRF- 2018R1A2A1A05076997). T.-J. Kim was additionally supported by a grant from the NRF (NRF-2016R1A6A3A04009698

Implementing a Sepsis Resuscitation Bundle Improved Clinical Outcome: A Before-and-After Study

BACKGROUND: Unlike other diseases, the management of sepsis has not been fully integrated in our daily practice. The aim of this study was to determine whether repeated training could improve compliance with a 6-h resuscitation bundle in patients with severe sepsis and septic shock. METHODS: Repeated education regarding a sepsis bundle was provided to the intensive care unit and emergency department residents, nurses, and faculties in a single university hospital. The educational program was led by a multidisciplinary team. A total of 175 adult patients with severe sepsis or septic shock were identified (88 before and 87 after the educational program). Hemodynamic resuscitation bundle and timely antibiotics administration were measured for all cases and mortality at 28 days after sepsis diagnosis was evaluated. RESULTS: The compliance rate for the sepsis resuscitation bundle before the educational program was poor (0%), and repeated training improved it to 80% (p < 0.001). The 28-day mortality was significantly lower in the intervention group (16% vs. 32%, p = 0.040). Within the intervention group, patients for whom the resuscitation bundle was successfully completed had a significantly lower 28-day mortality than other patients (11% vs. 41%, p = 0.004). CONCLUSIONS: Repeated education led by a multidisciplinary team and interdisciplinary communication improved the compliance rate of the 6-h resuscitation bundle in severe sepsis and septic shock patients. Compliance with the sepsis resuscitation bundle was associated with improved 28-day mortality in the study population

INSANet: INtra-INter Spectral Attention Network for Effective Feature Fusion of Multispectral Pedestrian Detection

Pedestrian detection is a critical task for safety-critical systems, but detecting pedestrians is challenging in low-light and adverse weather conditions. Thermal images can be used to improve robustness by providing complementary information to RGB images. Previous studies have shown that multi-modal feature fusion using convolution operation can be effective, but such methods rely solely on local feature correlations, which can degrade the performance capabilities. To address this issue, we propose an attention-based novel fusion network, referred to as INSANet (INtra-INter Spectral Attention Network), that captures global intra- and inter-information. It consists of intra- and inter-spectral attention blocks that allow the model to learn mutual spectral relationships. Additionally, we identified an imbalance in the multispectral dataset caused by several factors and designed an augmentation strategy that mitigates concentrated distributions and enables the model to learn the diverse locations of pedestrians. Extensive experiments demonstrate the effectiveness of the proposed methods, which achieve state-of-the-art performance on the KAIST dataset and LLVIP dataset. Finally, we conduct a regional performance evaluation to demonstrate the effectiveness of our proposed network in various regions

Short-Term Event Prediction in the Operating Room (STEP-OP) of Five-Minute Intraoperative Hypotension Using Hybrid Deep Learning: Retrospective Observational Study and Model Development

BackgroundIntraoperative hypotension has an adverse impact on postoperative outcomes. However, it is difficult to predict and treat intraoperative hypotension in advance according to individual clinical parameters. ObjectiveThe aim of this study was to develop a prediction model to forecast 5-minute intraoperative hypotension based on the weighted average ensemble of individual neural networks, utilizing the biosignals recorded during noncardiac surgery. MethodsIn this retrospective observational study, arterial waveforms were recorded during noncardiac operations performed between August 2016 and December 2019, at Seoul National University Hospital, Seoul, South Korea. We analyzed the arterial waveforms from the big data in the VitalDB repository of electronic health records. We defined 2s hypotension as the moving average of arterial pressure under 65 mmHg for 2 seconds, and intraoperative hypotensive events were defined when the 2s hypotension lasted for at least 60 seconds. We developed an artificial intelligence–enabled process, named short-term event prediction in the operating room (STEP-OP), for predicting short-term intraoperative hypotension. ResultsThe study was performed on 18,813 subjects undergoing noncardiac surgeries. Deep-learning algorithms (convolutional neural network [CNN] and recurrent neural network [RNN]) using raw waveforms as input showed greater area under the precision-recall curve (AUPRC) scores (0.698, 95% CI 0.690-0.705 and 0.706, 95% CI 0.698-0.715, respectively) than that of the logistic regression algorithm (0.673, 95% CI 0.665-0.682). STEP-OP performed better and had greater AUPRC values than those of the RNN and CNN algorithms (0.716, 95% CI 0.708-0.723). ConclusionsWe developed STEP-OP as a weighted average of deep-learning models. STEP-OP predicts intraoperative hypotension more accurately than the CNN, RNN, and logistic regression models. Trial RegistrationClinicalTrials.gov NCT02914444; https://clinicaltrials.gov/ct2/show/NCT02914444

Strong enhancement of room-temperature thermoelectric properties of Cu-doped Bi2Te2.7Se0.3

We investigate thermoelectric properties of Cu-doped Bi2Te2.7Se0.3 fabricated using a simple doping process and spark plasma sintering. Through precise control of Cu doping, it is found that Cu atoms preferentially occupied Bi sites and then intercalated into the van der Waals gap with an increasing Cu content. Electrical transport properties of Cu-doped samples were systemically controlled using this mechanism. At the same time, thermal conductivities of the Cu-doped samples were reduced by the enhancement of point defect phonon scattering due to the Cu atoms. Compared to that of pristine samples, the dimensionless thermoelectric figure of merit ("ZT") of 0.98 at 323 K for the Cu-doped sample was increased by more than 92% owing to these synergetic effects. Furthermore, the shift of maximum ZT to room temperature provides advantages for enlarging the applications of thermoelectric effects at room temperature. © 2022 Author(s).1

Quantitative analysis on the depletion rate of \u3b2-NiAl phases in MCrAlY coating

In this study, a disk-shaped thermal barrier coating system for a gas turbine blade was isothermally aged at 1100\ub0C for various times up to 800 h. The microstructures of the bond coat were observed by using an optical microscope for each aging condition. Diffusion of primary elements consisting of the bond coat was characterized by using electron probe microanalyzer mapping. Semi-quantitative analysis by using scanning electron microscopy energy-dispersive X-ray was insufficient to sense variations in the Al content within the bond coat according to exposure time. An area fraction of \u3b2-NiAl phases within the bond coat was calculated by image analysis, and a reasonable approach to estimate time for complete depletion of the Al-rich \u3b2-NiAl phase within the bond coat was suggested.Peer reviewed: YesNRC publication: Ye