Discussion on the Discreteness of the Attenuation Parameters of the Peak Particle Velocity Induced by Blasting.

The research on the attenuation law of blasting vibration has become the foundation and precondition of the effective control of blasting vibration damage. Aiming at the characteristics of low frequency, low velocity, and strong amplitude of the R wave, an improved wave component separation method based on R wave suppression is proposed. Combined with the measured vibration signals of a field test, the attenuation parameters of different types of waves in the propagation process of blasting seismic waves are studied. The analysis results show that, in the process of blasting seismic wave propagation, the attenuation parameters of different types of waves are significantly different. With an increase in propagation distance, the proportion of the different types of waves will also change. The study of attenuation law with only coupled particle peak vibration velocity often showed high discreteness. The fitting correlation coefficient and prediction accuracy of peak vibration velocity without distinguishing wave modes are lower than those induced by the P wave or R wave alone, which should be attributed to the conversion of dominant wave modes in blasting vibration at different distances.

Overview of Health-Monitoring Technology for Long-Distance Transportation Pipeline and Progress in DAS Technology Application.

There are various health issues associated with the different stages of long-distance pipeline transportation. These issues pose potential risks to environmental pollution, resource waste, and the safety of human life and property. It is essential to have real-time knowledge of the overall health status of pipelines throughout their entire lifecycle. This article investigates various health-monitoring technologies for long-distance pipelines, providing references for addressing potential safety issues that may arise during long-term transportation. This review summarizes the factors and characteristics that affect pipeline health from the perspective of pipeline structure health. It introduces the principles of major pipeline health-monitoring technologies and their respective advantages and disadvantages. The review also focuses on the application of Distributed Acoustic Sensing (DAS) technology, specifically time and space continuous monitoring technology, in the field of pipeline structure health monitoring. This paper discusses the process of commercialization development of DAS technology, the main research progress in the experimental field, and the open research issues. DAS technology has broad application prospects in the field of long-distance transportation pipeline health monitoring.

Insights into mechanism of peroxymonosufate activation by Mo single-atom catalysts: Singlet oxygen evolution and role of Mo-N coordination.

Recently, the Fenton-like reaction using peroxymonosulfate (PMS) has been acknowledged as a potential method for breaking down organic pollutants. In this study, we successfully synthesized a highly efficient and stable single atom molybdenum (Mo) catalyst dispersed on nitrogen-doped carbon (Mo-NC-0.1). This catalyst was then utilized for the first time to activate PMS and degrade bisphenol A (BPA). The Mo-NC-0.1/PMS system demonstrated the ability to completely degrade BPA within just 20 min. Scavenging tests and density functional theory (DFT) calculations have demonstrated that the primary reactive oxygen species was singlet oxygen (1O2) produced by Mo-N4 sites. The self-cycling of Mo facilitated PMS activation and the transition from a free radical activation pathway to a non-radical pathway mediated by 1O2. Simultaneously, the nearby pyridinic N served as adsorption sites to immobilize BPA and PMS molecules. The exceptionally high catalytic activity of Mo-NC-0.1 derived from its unique Mo-N coordination, which markedly reduced the distance for 1O2 to migrate to the BPA molecules. The Mo-NC-0.1/PMS system effectively reduced the acute toxicity of BPA and exhibited excellent cycling stability with minimal leaching. This study presented a new catalyst with high selectivity for 1O2 generation and provided valuable insights for the application of single atom catalysts in PMS-based AOPs.

Combination of sulfide-driven partial denitrification with anammox enhanced by zeolite powder for autotrophic nitrogen and sulfide removal from wastewater.

Sulfide-driven partial denitrification and anaerobic ammonia oxidizing (anammox) (SPDA) is a high-efficiency technology to achieve simultaneous nitrogen and sulfide removal. Nitrite accumulation from sulfide-driven partial denitrification is the key to achieve SPDA. Zeolite powder was added to strengthen the competition of anammox bacteria against nitrite. The nitrogen removal rate (NRR) and partial denitrification efficiency in reactor was 5.18 kg-N m-3d-1 and 92.3% during 180 days of operation, higher than those without zeolite powder, indicating an improving contribution of zeolite powder. Metabolomics analysis revealed zeolite powder addition enhanced the metabolisms of amino acids, nicotinate and porphyrin through increasing glutamate content, and improved EPS secretion, heme c content and particle size. Besides, high ammonia enriched by zeolite powder was conducive to improve anammox activity and NRR. This study provides the metabolic insights into the mechanism of zeolite powder enhancing SPDA, which is meaningful towards overcoming the limitations in practical application of SDPA.

Investigate the multipath erasure of nitrobenzene over nanoscale zero-valent-iron/N-doped biochar hybrid with extraordinary reduction performance.

In this study, the facile carbothermal reduction method was enforced using urea as dopant to modify the structure and chemical composition of nanoscale zero-valent-iron/biochar hybrid thereby boosting its reduction performance. Through fine-tuning the N-doped amount, the optimal nZVI/N-doped BC was obtained, which exhibited more active sites (nZVI, persistent free radicals (PFRs), pyrrolic-N) and superior electrochemical conductivity. With these blessings, the electrons originating from galvanic cell reaction could zip along the highway within the hybrid. Taking nitrobenzene (NB) as the target pollutant, the quantitative analysis revealed that the NB reduction and adsorption removal efficiency were dramatically improved by 2.42 and 2.78 times, respectively. What's more, combining the in-situ experimental detection and theoretical calculations, unexpected NB reductive multipath with respect to PFRs and pyrrolic-N accelerating the Fe3+/Fe2+ cycle within the nZVI/N-doped BC system was decoded. The enhancement of Fe3+/Fe2+ cycle improved the electron utilization efficiency and maintained the reduction reactivity of the hybrid. This work raised awareness of the mechanisms regarding the reduction performance of nZVI/N-doped BC elevated by N-doped and the pollutant reductive pathway within the system, uncovered the dusty roles of PFRs and N-species during the reduction process.

Structure-aware guided filtering for a ring artifact correction in synchrotron x-ray microtomography.

Synchrotron-based x-ray microtomography (S-µCT) is a powerful non-invasive three-dimensional (3D) imaging technique used for visualizing the internal structure of objects with micron-scale spatial resolution. However, in practical applications, ring artifacts often occur in S-µCT, which significantly degrades image quality and hinders interpretation. In this study, we propose a ring artifact correction method based on guided image filtering (GIF). The method first extracts structural prior from the input S-µCT images and then uses it as the guidance image to correct the ring artifacts. Finally, GIF with a self-guidance image is employed to further enhance image quality. Extensive comparisons and analyses on simulations and real data experiments demonstrate that the proposed method is capable of effectively correcting ring artifacts, accompanied by low-dose noise suppression and sparse-view artifact reduction. These findings suggest that the proposed method has great potential to promote the wider applications of S-µCT in the future.

Upregulation of INHBA mediated by the transcription factor BHLHE40 promotes colon cancer cell proliferation and migration.

BACKGROUND: Colon cancer is highly prevalent, and cell proliferation and migration are major reasons for its progression to malignancy. The upregulation of INHBA, a glycoprotein hormone that regulates the secretion of pituitary hormones, is documented to be oncogenic in numerous cancers, consisting of breast, gastric, and ovarian cancer. Herein, we assessed the role of INHBA in the proliferation along with the migration of colon cancer cells. METHODS: TCGA datasets were used to assess INHBA expression and its correlation with prognosis in colon cancer patients. Analyses on JASPAR, PROMO, and ENCODE databases, uncovered high correlation between INHBA and BHLHE40. Western blot and RT-qPCR analysis were used to determine protein and mRNA levels. Cell transfection inhibited the expression of INHBA and BHLHE40. Cell proliferation rates were determined using CCK8 analysis. Wound healing assays were adopted to explore cell migration. RESULTS: INHBA is markedly elevated in colon cancer tissues along with cells and is a predictive factor for patient's prognosis with colon cancer. INHBA silencing suppressed colon cancer cell proliferation and migration. Furthermore, we confirmed the association of INHBA with BHLHE40 in colon cancer cells. BHLHE40 could directly modulates INHBA expression. Here, we show that BHLHE40 modulates the expression of INHBA, which influences the proliferation, and migration of colon cancer cells. CONCLUSION: INHBA acts as an oncogene in colon cancer and it can be regulated by the transcription factor BHLHE40.

MicroRNAs and long non-coding RNAs in liver surgery: Diagnostic and therapeutic merits.

BACKGROUND: Hepatectomy and liver transplantation (LT) are the two most commonly performed surgical procedures for various hepatic lesions. microRNA (miRNA) and long non-coding RNA (lncRNA) have been gradually unveiled their roles as either biomarkers for early diagnosis or potentially therapeutic tools to manipulate gene expression in many disease entities. This review aimed to discuss the effects of miRNA or lncRNA in the hepatectomy and LT fields. DATA SOURCES: We did a literature search from 1990 through January 2018 to summarize the currently available evidence with respect to the effects of miRNA and lncRNA in liver regeneration after partial hepatectomy, as well as their involvement in several key issues related to LT, including ischemia-reperfusion injury, allograft rejection, tolerance, recurrence of original hepatic malignancies, etc. RESULTS: Certain miRNAs and lncRNAs are actively involved in the regulation of various aspects of liver resection and transplantation. During the process of liver regeneration after hepatectomy, the expression of miRNAs and lncRNAs shows dynamic changes. CONCLUSIONS: It is now clear that miRNAs and lncRNAs orchestrate in various aspects of the pathophysiological process of LT and hepatectomy. Better understanding of the underlying mechanism and future clinical trials may strengthen their positions as either biomarkers or potential therapeutic targets in the management of complications after liver surgery.

Nitrogen-associated niche characteristics and bacterial community estimated by 15N-DNA-stable isotope probing in one-stage partial nitritation/anammox process with different ammonium loading.

Anaerobic ammonium oxidation coupled with partial nitritation is critical for cleaner production in sewage treatment. The long-term effects of high- and low-strength influent ammonium (NH4+-N) on the anammox activity, ecological niche characteristics and active microbial community were investigated in a one-stage partial nitritation/anammox (PN/A) process. The total nitrogen (TN) removal efficiency was up to 90% with influent NH4+-N of 192 mg/L. The 15N-isotope pairing technique illustrated that the potential anammox rate could reach to 3507.8 nmoL/g-sludge/h, accounting for 73.2% of dinitrogen production. As the influent NH4+-N decreased to 63 mg/L, the anammox population significantly decreased and the Nitrospira became the dominant specialized species in the PN/A system. The Nitrobacter had the smallest niche overlap value and the furthest ecological distance to the anammox bacteria among the seven investigated nitrogen conversion-related genes along the influent NH4+-N concentration gradient, indicating different ecological similarities. The redundancy analysis showed that the rise of dissolved oxygen caused by low NH4+-N might be the main cause of the excessive proliferation of the Nitrospira. The 15N-DNA-stable isotope probing illustrated that both the class Anaerolineae and Proteobacteria had closely symbiotic relations with the Planctomycetacia in this in situ surveys. This study provides a deep understanding of PN/A process treating low-ammonium mainstream wastewater from the viewpoint of microecology.

Predictors of Treatment Failure After 2-Stage Reimplantation for Infected Total Knee Arthroplasty: A 2- to 10-Year Follow-Up.

BACKGROUND: The aim of this study is to identify risk factors which may lead to treatment failure following 2-stage reimplantation for chronic infected total knee arthroplasty (TKA). METHODS: We retrospectively reviewed 106 patients (108 knees) who underwent consecutive 2-stage revision for chronic PJI of the knee at our institution between January 2005 and December 2015. A total of 31 risk factors, including patient characteristics, comorbidities, surgical variables, and microbiology data, were collected. Kaplan-Meier survival and Cox regression analyses were used to calculate survival rates and adjusted hazard ratios (HRs) of treatment failure. RESULTS: Within the cohort, 16 of the 108 2-stage reimplantations (14.8%) had treatment failure. The treatment success for 2-stage reimplantation was 91% (95% confidence interval [CI] 0.8-1.0) at 2 years and 84% (95% CI 0.8-0.9) at 5 and 10 years. Multivariate analysis provided the strongest predictors of treatment failure, including body mass index ≥30 kg/m2 (adjusted HR 9.3, 95% CI 2.7-31.8, P < .001), operative time >4 hours (adjusted HR 11.3, 95% CI 3.9-33.1, P < .001), gout (adjusted HR 13.8, 95% CI 2.9-66.1, P = .001), and the presence of Enterococcus species during resection arthroplasty (adjusted HR 14.1, 95% CI 2.6-76.3, P = .002). CONCLUSION: Our study identified 4 potential risk factors that may predict treatment failure following 2-stage revision for chronic knee PJI. This finding may be useful when counseling patients regarding the treatment success and prognosis of 2-stage reimplantation for infected TKA.

TFCNet: A texture-aware and fine-grained feature compensated polyp detection network.

PURPOSE: Abnormal tissue detection is a prerequisite for medical image analysis and computer-aided diagnosis and treatment. The use of neural networks (CNN) to achieve accurate detection of intestinal polyps is beneficial to the early diagnosis and treatment of colorectal cancer. Currently, image detection models using multi-scale feature processing perform well in polyp detection. However, these methods do not fully consider the misalignment of information in the process of feature scale change, resulting in the loss of fine-grained features, and eventually cause the missed and false detection of targets. METHOD: To solve this problem, a texture-aware and fine-grained feature compensated polyp detection network (TFCNet) is proposed in this paper. Firstly, design Texture Awareness Module (TAM) to excavate the rich texture information from the low-level layers and utilize high-level semantic information for background suppression, thereby capturing purer fine-grained features. Secondly, the Texture Feature Enhancement Module (TFEM) is designed to enhance the low-level texture information in TAM, and the enhanced texture features were fused with the high-level features. By making full use of the low-level texture features and multi-scale context information, the semantic consistency and integrity of the features were ensured. Finally, the Residual Pyramid Splittable Attention Module (RPSA) is designed to balance the loss of channel information caused by skip connections, and further improve the detection performance of the network. RESULTS: Experimental results on 4 datasets demonstrate that the TFCNet network outperforms existing methods. Particularly, on the large dataset PolypSets, the mAP@0.5-0.95 has been improved to 88.9%. On the small datasets CVC-ClinicDB and Kvasir, the mAP@0.5-0.95 is increased by 2% and 1.6%, respectively, compared to the baseline, showcasing a significant superiority over competing methods.

DBH-YOLO: a surgical instrument detection method based on feature separation in laparoscopic surgery.

PURPOSE: Accurately locating and analysing surgical instruments in laparoscopic surgical videos can assist doctors in postoperative quality assessment. This can provide patients with more scientific and rational solutions for healing surgical complications. Therefore, we propose an end-to-end algorithm for the detection of surgical instruments. METHODS: Dual-Branched Head (DBH) and Overall Intersection over Union Loss (OIoU Loss) are introduced to solve the problem of inaccurate surgical instrument detection, both in terms of localization and classification. An effective method (DBHYOLO) for the detection for laparoscopic surgery in complex scenarios is proposed. This study manually annotates a new laparoscopic gastric cancer resection surgical instrument location dataset LGIL, which provides a better validation platform for surgical instrument detection methods. RESULTS: The proposed method's performance was tested using the m2cai16-tool-locations, LGIL, and Onyeogulu datasets. The mean Average Precision (mAP) values obtained were 96.8%, 95.6%, and 98.4%, respectively, which were higher than the other classical models compared. The improved model is more effective than the benchmark network in distinguishing between surgical instrument classes with high similarity and avoiding too many missed detection cases. CONCLUSIONS: In this paper, the problem of inaccurate detection of surgical instruments is addressed from two different perspectives: classification and localization. And the experimental results on three representative datasets verify the performance of DBH-YOLO. It is shown that this method has a good generalization capability.

Metabolomic pathway regulation to achieve optimal control of inorganic carbon in anammox process.

The significance of inorganic carbon (IC) for anaerobic ammonium oxidation (anammox) bacteria has been verified. However, the regulation of metabolic pathways under IC stress is not clear, limiting the optimization of IC supply. In this study, the regulatory pathways at IC concentration of 5-150 mg/L were explored to achieve optimal control of IC. The results show that the changes of metabolic pathway under IC stress determined anammox characteristics. At IC concentration of 5 mg/L, the anammox activity distinctly decreased due to the guanosine tetraphosphate (ppGpp) -mediated regulation under IC limitation. With less than 15 mg/L of IC, the decrease of carbon fixation limited the biosynthesis of gluconeogenesis and amino acids, causing the decline of extracellular polymeric substance synthesis. With more than 50 mg/L of IC, the improvement of purine and pyrimidine metabolism enhanced the electron transport capacity and growth potential of anammox bacteria. This study provides metabolic insights into IC influence on anammox consortia and a novel method of IC concentration optimization using metabolomics analysis.

Metabolomics uncovers adaptation discrepancy among anammox granular sludge with different granule size: Metabolic pathway regulation by consortia cooperation.

The relationship between granular size and anaerobic ammonium oxidation (anammox) performance in the anammox granular sludge (AnGS) system has been extensively observed. However, the metabolic pathways regulated by communication and cross-feedings among anammox consortia remain unclear. The reactor operation and metabolomics analyses were combined to explore the influence of microbiota cooperation on metabolic pathways and granule properties under low temperature (18 °C) and nitrite inhibition. Anammox activity was sustained under challenging circumstances by active quorum sensing among anammox consortia in AnGS with diameters larger than 1.4 mm, which promoted nucleotide metabolism. Cross-feedings among anammox consortia increased the levels of molybdopterin cofactor and folate meanwhile decreasing the cost of carbon fixation metabolism, which supported anabolism and maintained the content of heme c and extracellular polymeric substance. These metabolic insights into the AnGS system provide a new view for anammox process overcoming the low temperature and nitrite stress.

Metabolomic pathway regulation for prevention and control of granule sludge bulking in thiosulfate-driven denitrification.

The performance of thiosulfate-driven denitrification (TDD) granule reactor and the mechanism of granule sludge bulking were investigated in this study. The results showed that TDD granule bulking occurred under 12 kgNm-3d-1 of nitrogen loading rate (NLR). The higher NLR promoted accumulation of intermediates in the carbon fixation pathway, including citrate, oxaloacetate, oxoglutarate and fumarate. The carbon fixation improved amino acids biosynthesis, which increased proteins (PN) in extracellular polymers (EPS) to 134.6 ± 11.8 mg/gVSS. The excessive PN altered the content, components and chemical groups of EPS, leading to change of granule structure and decline in settling property, permeability and nitrogen removal. By adopting the strategy of intermittently reducing NLR, excess amino acids in sulfur-oxidizing bacteria was consumed through microbial growth-related metabolism instead of EPS synthesis. Therefore, the nitrogen removal rate increased to 10.23 kg-Nm-3d-1 and maintained stable in the long term. The EPS contents decreased from 168.8 ± 13.5 mg/gVSS to 93 ± 11.5 mg/gVSS and the SVI5 decreased from 66 ± 3.5 ml/g to 25 ± 1.5 ml/g. These findings provide an effective strategy to prevent granule bulking and guide practical application of TDD process.

Research on recognition and intervention of behavior sequences in virtual museum learning.

Learning in virtual museum can transcend the limits of time and space. The virtual museum that combines expertise in different disciplines provides a virtual learning environment for college students, but how to intervene in museum learning has been unclear. Targeted at this question, this study selected 2030 majors in clinical medicine from a certain university and the final results exhibited four types of learners who are of high, medium, low and absent museum immersion, respectively. When the learners visited the virtual museum, their behavior data were collected backstage and later used as data source. The method of fuzzy c clustering analysis was utilized to test the behavior recognition results of virtual museum learning, and lag sequential analysis (LSA) was used to carry out sequential transformation of learning behaviors in virtual museum. In this study, the four types of learners were subsumed under two broad categories of middle & high museum immersion and low & absent museum immersion. The importance of behavior was identified with random forest algorithm, and the intervention mechanism of museum teaching was designed according to the analysis results. Specifically, such strategies as museum support, voice guidance, video guidance, sub-museum ordering, rewards points on the list, etc. were used to study the museum learners in need of intervention. The results showed that the learning state of some learners was significantly improved.

Design and validation of a multi-objective waypoint planning algorithm for UAV spraying in orchards based on improved ant colony algorithm.

Introduction: Current aerial plant protection with Unmanned Aerial Vehicles (UAV) usually applies full coverage route planning, which is challenging for plant protection operations in the orchards in South China. Because the fruit planting has the characteristics of dispersal and irregularity, full-coverage route spraying causes re-application as well as missed application, resulting in environmental pollution. Therefore, it is of great significance to plan an efficient, low-consumption and accurate plant protection route considering the flight characteristics of UAVs and orchard planting characteristics. Methods: This study proposes a plant protection route planning algorithm to solve the waypoint planning problem of UAV multi-objective tasks in orchard scenes. By improving the heuristic function in Ant Colony Optimization (ACO), the algorithm combines corner cost and distance cost for multi-objective node optimization. At the same time, a sorting optimization mechanism was introduced to speed up the iteration speed of the algorithm and avoid the influence of inferior paths on the optimal results. Finally, Multi-source Ant Colony Optimization (MS-ACO) was proposed after cleaning the nodes of the solution path. Results: The simulation results of the three test fields show that compared with ACO, the path length optimization rate of MS-ACO are 3.89%, 4.6% and 2.86%, respectively, the optimization rate of total path angles are 21.94%, 45.06% and 55.94%, respectively, and the optimization rate of node numbers are 61.05%, 74.84% and 75.47%, respectively. MS-ACO can effectively reduce the corner cost and the number of nodes. The results of field experiments show that for each test field, MS-ACO has a significant optimization effect compared with ACO, with an optimization rate of energy consumption per meter of more than 30%, the optimization rate of flight time are 46.67%, 56% and 59.01%, respectively, and the optimization rate of corner angle are 50.76%, 61.78% and 71.1%, respectively. Discussion: The feasibility and effectiveness of the algorithm were further verified. The algorithm proposed in this study can optimize the spraying path according to the position of each fruit tree and the flight characteristics of UAV, effectively reduce the energy consumption of UAV flight, improve the operating efficiency, and provide technical reference for the waypoint planning of plant protection UAV in the orchard scene.

Immunogenic chemotherapy: great potential for improving response rates.

The activation of anti-tumor immunity is critical in treating cancers. Recent studies indicate that several chemotherapy agents can stimulate anti-tumor immunity by inducing immunogenic cell death and durably eradicate tumors. This suggests that immunogenic chemotherapy holds great potential for improving response rates. However, chemotherapy in practice has only had limited success in inducing long-term survival or cure of cancers when used either alone or in combination with immunotherapy. We think that this is because the importance of dose, schedule, and tumor model dependence of chemotherapy-activated anti-tumor immunity is under-appreciated. Here, we review immune modulation function of representative chemotherapy agents and propose a model of immunogenic chemotherapy-induced long-lasting responses that rely on synergetic interaction between killing tumor cells and inducing anti-tumor immunity. We comb through several chemotherapy treatment schedules, and identify the needs for chemotherapy dose and schedule optimization and combination therapy with immunotherapy when chemotherapy dosage or immune responsiveness is too low. We further review tumor cell intrinsic factors that affect the optimal chemotherapy dose and schedule. Lastly, we review the biomarkers indicating responsiveness to chemotherapy and/or immunotherapy treatments. A deep understanding of how chemotherapy activates anti-tumor immunity and how to monitor its responsiveness can lead to the development of more effective chemotherapy or chemo-immunotherapy, thereby improving the efficacy of cancer treatment.

Serum cholinesterase as a new nutritional indicator for predicting weaning failure in patients.

Aim: The objective of this study is to examine the correlation between patient serum cholinesterase (SCHE) concentration and weaning failure in the context of invasive mechanical ventilation (IMV), as well as to identify predictors of ventilator weaning failure. Additionally, this study investigates the potential relationship between SCHE and nutritional risk for developing more effective weaning strategies. Method: A retrospective observational study was conducted. The sample was collected from 227 patients with IMV over 48 h who underwent SBT before weaning. Relevant experimental samples and data collection were analyzed at the time of patient admission and before the initiation of the SBT. The correlation between SCHE and weaning failure was determined by multifactorial logistic regression and propensity matching scores. Results: Weaning was successful in 127 patients and failed in 100 patients. Depending on the difficulty of weaning, 55 of these patients had difficulty in weaning and 45 had long-term weaning. In the crude cohort, experimental data collected on the day of SBT showed that SCHE concentrations were higher in patients with successful weaning than in those with failed weaning (4,514 u/l vs. 3,190 u/l p < 0.01). The critical value for predicting weaning failure was SCHE 3,228 u/l (p < 0.01). Ventilator weaning failure was predicted by multifactorial logistic regression analysis of SCHE, heart rate, and PaO2 before SBT, with SCHE predicting ventilator weaning failure (AUC 0.714; 95% CI 0.647-0.782) better than heart rate (AUC 0.618; 95% CI 0.545-0.690), PaO2 (AUC 0.59; 95% CI 0.515-0.664). After propensity-matched scores, SCHE remained an independent predictor of weaning failure (p = 0.05). And the SCHE concentration was strongly correlated with the patient's weaning difficulties (p < 0.01). The Nutrition Risk in Critically Ill (NUTRIC) score was also significantly correlated with SCHE according to Spearman's correlation analysis (p < 0.01). Conclusion: Our study revealed that the patients who experienced weaning failure exhibited lower SCHE values compared to those who successfully underwent weaning. Before spontaneous breathing trial (SBT), SCHE, heart rate, and PaO2 were identified as independent predictors of weaning failure. Following propensity score matching (PSM), SCHE and heart rate remained independent predictors. Patients with SCHE levels below 3,228 u/l should undergo careful evaluation before weaning. Our findings suggest that malnutrition may be a contributing factor to weaning failure in patients.

The Characteristic Aroma Compounds of GABA Sun-Dried Green Tea and Raw Pu-Erh Tea Determined by Headspace Solid-Phase Microextraction Gas Chromatography-Mass Spectrometry and Relative Odor Activity Value.

We aim to improve the product quality of GABA raw Pu-erh tea during development and processing. In this study, headspace solid-phase microextraction gas chromatography-mass spectrometry technology combined with relative odor activity evaluations was used to compare the volatile compounds of GABA sun-dried green tea and GABA raw Pu-erh tea. Sensory evaluation showed a higher aroma score of GABA raw Pu-erh tea than that of GABA sun-dried green tea, with significant differences in aroma type and purity. A total of 147 volatile compounds of 13 categories were detected, which differed in composition and quantity between the two teas. 2-Buten-1-one,1-(2,6,6-trimethyl-1,3-cyclohexadien-1-yl)-,(E)- and beta.-myrcene largely contributed to the aroma formation of both teas. Five volatile compounds were screened as potential markers for tea aroma. Metabolic pathway analysis showed that monoterpenoid biosynthesis may be beneficial to the formation of flowery and fruity aromas in the teas. We suggest that the findings of this study may provide important guidance for the processing and optimization of GABA tea.