Search Results (984)

Objectives: This study aimed to identify the incidence and risk factors for contrast-associated acute kidney injury nephropathy (CA-AKI) in patients undergoing contrast-enhanced computed tomography (CCT) in the emergency department. Materials and Methods: In this retrospective single-center study, patients aged 18 and older who visited the emergency department and underwent CCT between January and February 2022 were included. The Mehran score, calculated from patient data, was used to assess risk. CA-AKI development was determined by measuring serum creatinine (SCr) levels 48–72 h post-contrast administration. Results: The study included 532 patients, with a mean age of 57 ± 19 years; 53.2% were male. CA-AKI developed in 16% of cases, 5.82% required hemodialysis, and 7.9% died. The Mehran score was the only significant predictor of CA-AKI development. Patients with a Mehran score of 16 or higher had a 161-fold increased risk of developing CA-AKI compared to those with a score of 5 or lower. The model achieved a 91.3% correct classification rate. Logistic regression analysis showed that CA-AKI significantly increased mortality risk by 15.7 times. Conclusion: The Mehran score, originally developed for predicting CA-AKI risk post-coronary intervention, is also effective for predicting CA-AKI risk after CCT. While CA-AKI is a significant factor affecting mortality, it is not the sole cause of death (Nagelkerke R2 value 0.310). Full article

This study aimed to evaluate the potential of pre-treatment CT-based radiomics features (RFs) derived from single and multiple tumor sites, and state-of-the-art machine-learning survival algorithms, in predicting progression-free survival (PFS) for patients with metastatic lung adenocarcinoma (MLUAD) receiving first-line treatment including immune checkpoint inhibitors (CPIs). To do so, all adults with newly diagnosed MLUAD, pre-treatment contrast-enhanced CT scan, and performance status ≤ 2 who were treated at our cancer center with first-line CPI between November 2016 and November 2022 were included. RFs were extracted from all measurable lesions with a volume ≥ 1 cm³ on the CT scan. To capture intra- and inter-tumor heterogeneity, RFs from the largest tumor of each patient, as well as lowest, highest, and average RF values over all lesions per patient were collected. Intra-patient inter-tumor heterogeneity metrics were calculated to measure the similarity between each patient lesions. After filtering predictors with univariable Cox p < 0.100 and analyzing their correlations, five survival machine-learning algorithms (stepwise Cox regression [SCR], LASSO Cox regression, random survival forests, gradient boosted machine [GBM], and deep learning [Deepsurv]) were trained in 100-times repeated 5-fold cross-validation (rCV) to predict PFS on three inputs: (i) clinicopathological variables, (ii) all radiomics-based and clinicopathological (full input), and (iii) uncorrelated radiomics-based and clinicopathological variables (uncorrelated input). The Models’ performances were evaluated using the concordance index (c-index). Overall, 140 patients were included (median age: 62.5 years, 36.4% women). In rCV, the highest c-index was reached with Deepsurv (c-index = 0.631, 95%CI = 0.625–0.647), followed by GBM (c-index = 0.603, 95%CI = 0.557–0.646), significantly outperforming standard SCR whatever its input (c-index range: 0.560–0.570, all p < 0.0001). Thus, single- and multi-site pre-treatment radiomics data provide valuable prognostic information for predicting PFS in MLUAD patients undergoing first-line CPI treatment when analyzed with advanced machine-learning survival algorithms. Full article

Mitigating air pollutants such as SO_x and PM emitted from ships is an important task for marine environmental protection and improving air quality. To address this, exhaust gas after-treatment devices have been introduced, but treating pollutants like SO_x and PM individually poses challenges due to spatial constraints on ships. Consequently, a Total Gas Cleaning System (TGCS) capable of simultaneously reducing sulfur oxides and particulate matter has been developed. The TGCS combines a cyclone dust collector and a wet scrubber system. The cyclone dust collector is designed to maintain a certain distance from the bottom of the wet scrubber, allowing exhaust gases entering from the bottom to rise as sulfur oxides are adsorbed. Additionally, the exhaust gases descending through the space between the cyclone dust collector and the wet scrubber collide with the scrubbing solution before entering the bottom of the wet scrubber, facilitating the absorption of SO_x. In this study, the efficiency of the developed TGCS was evaluated, and the reduction effects based on design parameters were investigated. Furthermore, the impact of this device on ship engines was analyzed to assess its practical applicability. Experimental results showed that increasing the volume flow rate of the cleaning solution enhanced the PM reduction effect. Particularly, when the height of the Pall ring was 1000 mm and the volume flow rate was 35 L/min, the sulfur oxide reduction effect met the standards for Sulfur Emission Control Areas (SECA). Based on these findings, suggestions for effectively controlling atmospheric pollutants from ships were made, with the expectation of contributing to the development of systems combining various after-treatment devices. Full article

The substitution of ethyl acetate for ammonia in NH₃-SCR provides a novel strategy for the simultaneous removal of VOCs and NO. In this study, three distinct types of biochar were fabricated through pyrolysis at 700 °C. MnO_x and TiO₂ were sequentially loaded onto these biochar substrates via a hydrothermal process, yielding a family of biochar-based catalysts with optimized dosages. Upon exposure to xenon lamp irradiation at 240 °C, the biochar catalyst designated as 700-12-3GN, derived from Ginkgo shells, demonstrated the highest catalytic activity when contrasted with its counterparts prepared from moso bamboo and loofah. The conversion efficiencies for NO and ethyl acetate (EA) peaked at 73.66% and 62.09%, respectively, at a catalyst loading of 300 mg. The characterization results indicate that the 700-12-3GN catalyst exhibits superior activity, which can be attributed to the higher concentration of Mn⁴⁺ and Ti⁴⁺ species, along with its superior redox properties and suitable elemental distribution. Notably, the 700-12-3GN catalyst has the smallest specific surface area but the largest pore volume and average BJH pore size, indicating that the specific surface area is not the predominant factor affecting catalyst performance. Instead, pore volume and average BJH pore diameter appear to be the more influential parameters. This research provides a reference and prospect for the resource utilization of biochar and the development of photothermal co-catalytic ethyl acetate and NO at low cost. Full article

GAI-RGA-and-SCR (GRAS) transcription factors can regulate many biological processes such as plant growth and development and stress defense, but there are few related studies in sugar beet. Salt stress can seriously affect the yield and quality of sugar beet (Beta vulgaris). Therefore, this study used bioinformatics methods to identify GRAS transcription factors in sugar beet and analyzed their structural characteristics, evolutionary relationships, regulatory networks and salt stress response patterns. A total of 28 BvGRAS genes were identified in the whole genome of sugar beet, and the sequence composition was relatively conservative. According to the topology of the phylogenetic tree, BvGRAS can be divided into nine subfamilies: LISCL, SHR, PAT1, SCR, SCL3, LAS, SCL4/7, HAM and DELLA. Synteny analysis showed that there were two pairs of fragment replication genes in the BvGRAS gene, indicating that gene replication was not the main source of BvGRAS family members. Regulatory network analysis showed that BvGRAS could participate in the regulation of protein interaction, material transport, redox balance, ion homeostasis, osmotic substance accumulation and plant morphological structure to affect the tolerance of sugar beet to salt stress. Under salt stress, BvGRAS and its target genes showed an up-regulated expression trend. Among them, BvGRAS-15, BvGRAS-19, BvGRAS-20, BvGRAS-21, LOC104892636 and LOC104893770 may be the key genes for sugar beet’s salt stress response. In this study, the structural characteristics and biological functions of BvGRAS transcription factors were analyzed, which provided data for the further study of the molecular mechanisms of salt stress and molecular breeding of sugar beet. Full article

With the rapid development of industrialization, the emission of nitrogen oxides (NO_x) has become a global environmental issue. Uranium is the primary fuel used in nuclear power generation. However, the production of uranium, typically based on the uranyl nitrate method, usually generates large amounts of nitrogen oxides, particularly NO₂, with concentrations in the exhaust gas exceeding 10,000 ppm. High concentrations of nitrogen dioxide are also produced during silver electrolysis processing and the treatment of waste electrolyte solutions. Traditional V-W/TiO₂ NH₃-SCR catalysts typically exhibit high catalytic activity at temperatures ranging from 300 to 400 °C, under conditions of low NO_x concentrations and high gas hourly space velocity. However, their performance is not satisfying when reducing high concentrations of NO₂. This study aims to optimize the traditional V-W/TiO₂ catalysts to enhance their catalytic activity under conditions of high NO₂ concentrations (10,000 ppm) and a wide temperature range (200–400 °C). On the basis of 3 wt% Mo/TiO₂, various loadings of V₂O₅ were selected, and their catalytic activities were tested. Subsequently, the optimal ratios of active component vanadium and additive molybdenum were explored. Simultaneously, doping with WO₃ for modification was selected in the V-Mo/TiO₂ catalyst, followed by activity testing under the same conditions. The results show that: the NO_x conversion rates of all five catalysts increase with temperature at range of 200–400 °C. Excessive loading of MoO₃ decreased the catalytic performance, with 5 wt% being the optimal loading. The addition of WO₃ significantly enhanced the low-temperature activity of the catalysts. When the loadings of WO₃ and MoO₃ were both 3 wt%, the catalyst exhibited the best denitrification performance, achieving a NO_x conversion rate of 98.8% at 250 °C. This catalyst demonstrates excellent catalytic activity in reducing very high concentration (10,000 ppm) NO₂, at a wider temperature range, expanding the temperature range by 50% compared to conventional SCR catalysts. Characterization techniques including BET, XRD, XPS, H₂-TPR, and NH₃-TPD were employed to further study the evolution of the catalyst, and the promotional mechanisms are explored. The results revealed that the proportion of chemisorbed oxygen (O_α) increased in the WO₃-modified catalyst, exhibiting lower V reduction temperatures, which are favorable for low-temperature denitrification activity. NH₃-TPD experiments showed that compared to MoO_x species, surface WO_x species could provide more acidic sites, resulting in stronger surface acidity of the catalyst. Full article

Sentinel-2 satellites are one of the major instruments in remote sensing (RS) technology that has revolutionized Earth observation research, as its main goal is to offer high-resolution satellite data for dynamic monitoring of Earth’s surface and climate change detection amongst others. However, visual observation of Sentinel-2 satellite data has revealed that most images obtained during the winter season contain snow noise, posing a major challenge and impediment to satellite RS analysis of land surface. This singular effect hampers satellite signals from capturing important surface features within the geographical area of interest. Consequently, it leads to information loss, image processing problems due to contamination, and masking effects, all of which can reduce the accuracy of image analysis. In this study, we developed a snow-cover removal (SCR) model based on the Cycle-Consistent Adversarial Networks (CycleGANs) architecture. Data augmentation procedures were carried out to salvage the effect of the limited availability of Sentinel-2 image data. Sentinel-2 satellite images were used for model training and the development of a novel SCR model. The SCR model captures snow and other prominent features in the Sentinel-2 satellite image and then generates a new snow-free synthetic optical image that shares the same characteristics as the source satellite image. The snow-free synthetic images generated are evaluated to quantify their visual and semantic similarity with original snow-free Sentinel-2 satellite images by using different image qualitative metrics (IQMs) such as Structural Similarity Index Measure (SSIM), Universal image quality index (Q), and peak signal-to-noise ratio (PSNR). The estimated metric data shows that Q delivers more metric values, nearly 95%, than SSIM and PRSN. The methodology presented in this study could be beneficial for RS research in DL model development for environmental mapping and time series modeling. The results also confirm the DL technique’s applicability in RS studies. Full article

Background: Various supply chain response frameworks (SCRFs) have been proposed in the supply chain (SC) literature, but there is no in-depth analysis. This study analyzes the applicability of SCRFs in scenarios that require SC responses by examining the frameworks’ design and use in response situations. Methods: A qualitative analysis of 38 studies revealed weaknesses in SCRFs, which include the entity proposing the framework, the stimulus being responded to, the adaptation of activities to the stimulus that is responded to, objectives, and response evaluation criteria. Results: The analysis reveals that while these frameworks have been designed for specific situations involving single SC processes, they demonstrate weaknesses by failing to meet two requirements: (1) the stimulus being responded to is different from changes in demand, and (2) the response is generated by a process distinct from manufacturing. Conclusions: Further, SCRF research that incorporates these weaknesses will promote the fragmented development of the SCR concept. Conversely, a robust SCRF can be successfully utilized in various SCRs, facilitating the comparison and evaluation of responses of different SCs to the same stimulus. Full article

The initial adoption of penicillin as an antibiotic marked the start of exploring other compounds essential for pharmaceuticals, yet resistance to penicillins and their side effects has compromised their efficacy. The N-terminal nucleophile (Ntn) amide-hydrolases S45 family plays a key role in catalyzing amide bond hydrolysis in various compounds, including antibiotics like penicillin and cephalosporin. This study comprehensively analyzes the structural and functional traits of the bacterial N-terminal nucleophile (Ntn) amide-hydrolases S45 family, covering penicillin G acylases, cephalosporin acylases, and D-succinylase. Utilizing structural bioinformatics tools and sequence analysis, the investigation delineates structurally conserved regions (SCRs) and substrate binding site variations among these enzymes. Notably, sixteen SCRs crucial for substrate interaction are identified solely through sequence analysis, emphasizing the significance of sequence data in characterizing functionally relevant regions. These findings introduce a novel approach for identifying targets to enhance the biocatalytic properties of N-terminal nucleophile (Ntn) amide-hydrolases, while facilitating the development of more accurate three-dimensional models, particularly for enzymes lacking structural data. Overall, this research advances our understanding of structure–function relationships in bacterial N-terminal nucleophile (Ntn) amide-hydrolases, providing insights into strategies for optimizing their enzymatic capabilities. Full article

The DEAD-box RNA helicase Ded1 is an essential yeast protein involved in translation initiation that belongs to the DDX3 subfamily. The purified Ded1 protein is an ATP-dependent RNA-binding protein and an RNA-dependent ATPase, but it was previously found to lack substrate specificity and enzymatic regulation. Here we demonstrate through yeast genetics, yeast extract pull-down experiments, in situ localization, and in vitro biochemical approaches that Ded1 is associated with, and regulated by, the signal recognition particle (SRP), which is a universally conserved ribonucleoprotein complex required for the co-translational translocation of polypeptides into the endoplasmic reticulum lumen and membrane. Ded1 is physically associated with SRP components in vivo and in vitro. Ded1 is genetically linked with SRP proteins. Finally, the enzymatic activity of Ded1 is inhibited by SRP21 in the presence of SCR1 RNA. We propose a model where Ded1 actively participates in the translocation of proteins during translation. Our results provide a new understanding of the role of Ded1 during translation. Full article

High-efficiency and low-emissions heavy-duty (HD) internal combustion engines (ICEs) offer significant GHG reduction potential. Mild hybridization via regenerative braking and enabling the use of an electric heater component (EHC) for the aftertreatment system (ATS) warm-up extends these benefits, which can mitigate tailpipe GHG and NOx emissions simultaneously. Understanding such integrated hybrid powertrains is essential for the system optimization of real-world driving conditions. In the present work, the potential of a low engine-out NOx (1.5–2.5 g/kWh range) ‘Low-NOx’ HD diesel engine and EHCs were analyzed in a 48V P1 mild-hybrid system for a class 8 commercial vehicle concept and compared with those in an EPA-2010-certified HD diesel truck as a baseline under real-world driving cycles, including those from the US, Europe, India, China, as well as the world harmonized vehicle cycle (WHVC). For analysis, an integrated 1-D vehicle model was utilized that consisted of models of the ‘Low-NOx’ HD engine, the stock ATS, and a production EHC. For the real driving cycles, ‘GT-RealDrive’-based vehicle speed profiles were generated for busy trucking routes for different markets. For each cycle, the effects of the Low-NOx and EHC performances were quantified in terms of the ATS warm-up time, engine-out NOx emissions, and net fuel consumption. Depending on the driving route, the regenerative braking fully or partly neutralized the EHC power penalty without a significant impact on the ATS thermal performance. For a two-EHC system, the fueling penalty associated with every second reduction in the warm-up time ${FC}_{EHC}$ (g/s) was several-fold higher for the real driving routes compared with the WHVC. Overall, while a multi-EHC setup accelerated the ATS warm-up, a single EHC integrated at the SCR inlet showed minimized EHC heating power, leading to a minimized fueling penalty. Finally, for the India and China routes, being highly transient, the P1 hybridization proved inadequate for GHG reduction due to the limited energy recuperation. A stronger hybridization was desirable for such driving cycles. Full article

This study explored the role of sensorimotor simulation in modulating the stress response in individuals exposed to stressful digital simulated interviews. Participants were assigned to two different versions of a Digital Social Stress Test: a simulated version with a dynamic–realistic examining committee (Dyn-DSST) and a version with a static examining committee (Stat-DSST). During interview preparation, behavioral indices reflecting stress regulation and resistance, response times, and electroencephalographic (EEG) and autonomic indices were collected. Higher regulation scores were found for the Stat-DSST group compared to the Dyn-DSST group, probably induced by the presence of limited external sensory input in time and space, perceived as less stressful. The EEG results revealed a distinct contribution of the low- and high-frequency bands for both groups. Dyn-DSST required greater cognitive regulation effort due to the presence of a continuous flow of information, which can enhance sensory and motor activation in the brain. The SCR increased in the Dyn-DSST group compared to the Stat-DSST group, reflecting greater emotional involvement in the Dyn-DSST group and reduced sensory stimulation in the static version. In conclusion, the results suggest that sensorimotor simulation impacts the stress response differently in dynamic interviews compared to static ones, with distinct profiles based on behavioral, EEG, and autonomic measures. Full article

Acute kidney injury (AKI) is associated with long-term consequences and poor outcomes in the neonatal intensive care unit. Its precocious diagnosis represents one of the hardest challenges in clinical practice due to the lack of sensitive and specific biomarkers. Currently, neonatal AKI is defined with urinary markers and serum creatinine (sCr), with limitations in early detection and individual treatment. Biomarkers and risk factor scores were studied to predict neonatal AKI, to early identify the stage of injury and not the damage and to anticipate late increases in sCr levels, which occurred when the renal function already began to decline. Sepsis is the leading cause of AKI, and sepsis-related AKI is one of the main causes of high mortality. Moreover, preterm neonates, as well as patients with post-neonatal asphyxia or after cardiac surgery, are at a high risk for AKI. Critical patients are frequently exposed to nephrotoxic medications, representing a potentially preventable cause of AKI. This review highlights the definition of neonatal AKI, its diagnosis and new biomarkers available in clinical practice and in the near future. We analyze the risk factors involving patients with AKI, their outcomes and the risk for the transition from acute damage to chronic kidney disease. Full article

Artificial corner reflectors are widely used in the vegetated landslide for time series InSAR monitoring due to their permanent scattering features. This paper investigated the RCS features of a novel dihedral CR under multi-resource SAR datasets. An RCS reduction model for the novel dihedral corner reflector has been proposed to evaluate the energy loss caused by the deviation between the SAR incident angle and the CR’s axis. On the Huangtupo slope, Badong county, Hubei province, tens of dihedral CRs had been installed and the TSX–spotlight and Sentinel-TOPS data had been collected. Based on the observation results of CRs with more than ten deviation angles, the proposed reduction model was tested with preferable consistency under a real dataset, while 2 dBsm of systematic bias was verified in those datasets. The maximum incident angle deviation in the Sentinel data overlapping area is over 12°, which leads to a 2.4 dBsm RCS decrease for horizontally placed dihedral CRs estimated by the proposed model, which has also been testified by the observed results. The testing results from the Sentinel data show that in high, vegetation-covered mountain areas like the Huangtupo slope, the dihedral CRs with a 0.4 m slide length can be achieve 1 mm precision accuracy, while a side length of 0.2 m can achieve the same accuracy under TSX–spotlight data. Full article

Studying the effects of maize and soybean intercropping for improving the maize yield and sustaining stability of the maize yield under different phosphate (P) application rates in red soil is crucial for promoting maize productivity, improving soil fertility and optimizing P nutrient management in southwest China. The objective of this study was to evaluate the dynamic changes in maize yield, yield stability and soil fertility under monoculture and intercropping maize with different P application rates. A six-year field experiment was conducted from 2017 to 2022 to investigate the effects of maize intercropping with soybean on the yield stability and sustainability of maize according to the changes in the maize yield, biomass, partial land equivalent ratio of yield (pLERY), actual yield loss index (AYL), contribution rate of soil capacity and fertilizer (SCR, SFCR) over time, as well as the differences in the coefficient of variation (CV) and sustainable yield index (SYI) at four P application rates (0 kg P₂O₅ ha⁻¹, P0; 60 kg P₂O₅ ha⁻¹, P1; 90 kg P₂O₅ ha⁻¹, P2; and 120 kg P₂O₅ ha⁻¹, P3) based on the two-factor randomized block design. The linear-platform model was utilized to simulate the relationship between the grain yield, the SYI and the amount of P fertilizer under different P application rates. The maize yield in intercropping was significantly superior to the maize yield in monoculture throughout the entire six-year experiment. For all planting years, the yield and biomass of the intercropping were higher than those of the matched monoculture average by 56.0% and 56.1%, respectively. Intercropping had an advantage of pLERY and AYL for maize. Otherwise, intercropping reduced the CV by 30.8% and 39.1% and increased the SYI by 39.4% and 23.0% in P0 and P3 compared with the matched monoculture, respectively. For all planting years, the average SFCR in intercropping treatment was higher than that in monoculture treatment. The linear-plateau model fitted showed that intercropping increased the yield and SYI by 19.8% and 40.7% on the platform and reduced the P application rate by 37.8% and 11.9% at the inflection point, respectively. These results demonstrate that maize and soybean intercropping could achieve a higher yield, a higher yield stability and an SYI with a lower P input than monoculture. Maize and soybean intercropping could be a sustainable practice for promoting the maize productivity and the yield sustainability in the red soil of southwest China. Full article