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Background: Currently, intensity-modulated radiation therapy (IMRT) is commonly used in radiotherapy clinics. However, designing a treatment plan with multiple beam angles depends on the experience of human planners, and is mostly achieved using a trial-and-error approach. It is preferrable but challenging to solve this issue automatically and mathematically using an optimization approach. The goal of this study is to develop a mixed-integer linear programming (MILP) approach for the beam angle optimization (BAO) of non-coplanar IMRT for liver cancer. Methods: MILP models for the BAO of both coplanar and non-coplanar IMRT treatment plans were developed. The beam angles of the IMRT plans were first selected by the MILP model built using mathematical optimization software. Next, the IMRT plans with the selected beam angles was created in a commercial treatment planning system. Finally, the fluence map and dose distribution of the IMRT plans were generated under pre-defined dose-volume constraints. The IMRT plans of 10 liver cancer patients previously treated at our institute were used to assessed the proposed MILP models. For each patient, both coplanar and non-coplanar IMRT plans with beam angles optimized by the MILP models were compared with the IMRT plan clinically approved by physicians. Results: The MILP model-guided IMRT plans showed reduced doses for most of the organs at risk (OARs). Compared with the IMRT plans clinically approved by physicians, the doses for the spinal cord (28.5 vs. 36.1, P=0.001<0.05) and liver (27.6 vs. 29.1, P=0.005<0.05) decreased significantly in the IMRT plans with non-coplanar beams selected by the MILP models. Conclusions: The MILP model is an effective tool for the BAO in coplanar and non-coplanar IMRT treatment planning. It facilitates the automation of IMRT treatment planning for current high-precision radiotherapy.
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Herbal polysaccharides are extensively studied as vaccine adjuvants due to their safety and potent immunoenhancing activity. This study aimed to analyze the structure of Lagenaria siceraria (Molina) Standl polysaccharide (LSP50) and investigate its adjuvant activity for the H9N2 vaccine in broiler chickens. Structural analysis revealed that LSP50 primarily consisted of rhamnose, arabinose, xylose, mannose, glucose, and galactose with molar ratios of 23.12: 12.28: 10.87: 8.26: 2.64: 22.82 respectively. The adjuvant activity of LSP50 was evaluated, which showing significant enhancements compared to the H9N2 group. Parameters including the immune organ index, H9N2 specific IgG level, cytokines contents (IFN-γ, IL-2, IL-4, and IL-5), and the proportion of CD3e+CD8aT+cells were significantly increased in the LSP50 group (P < 0.05). Additionally, sequencing results showed that LSP50 modulates the immune response by regulating PLA2G12B and PTGDS genes involved in the arachidonic acid pathway. These findings were further validated through qPCR analysis to affirm the reliability of the sequencing data. In conclusion, our results demonstrate that LSP50 exhibits potent adjuvant activity, enhancing both cellular and humoral immunity.
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BACKGROUND AND AIMS: Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death all over the world, and brings a heavy social economic burden especially in China. Several immuno-combination therapies have shown promising efficacy in the first-line treatment of unresectable HCC and are widely used in clinical practice. Nevertheless, which combination is the most affordable one is unknown. Our study assessed the cost-effectiveness of the immuno-combinations as first-line treatment for patients with unresectable HCC from the perspective of Chinese payers. METHODS: A Markov model was built according to five multicenter, phase III, open-label, randomized trials (Himalaya, IMbrave150, ORIENT-32, CARES-310, LEAP-002) to investigate the cost-effectiveness of tremelimumab plus durvalumab (STRIDE), atezolizumab plus bevacizumab (A + B), sintilimab plus bevacizumab biosimilar (IBI305) (S + B), camrelizumab plus rivoceranib (C + R), and pembrolizumab plus lenvatinib (P + L). Three disease states were included: progression free survival (PFS), progressive disease (PD) as well as death. Medical costs were searched from West China Hospital, published literatures or the Red Book. Cost-effectiveness ratios (CERs) and incremental cost-effectiveness ratios (ICERs) were evaluated to compare costs among different combinations. Sensitivity analyses were performed to assess the robust of the model. RESULTS: The total cost and quality-adjusted life years (QALYs) of C + R, S + B, P + L, A + B and STRIDE were $12,109.27 and 0.91, $26,961.60 and 1.12, $55,382.53 and 0.83, $70,985.06 and 0.90, $84,589.01 and 0.73, respectively, resulting in the most cost-effective strategy of C + R with CER of $13,306.89 per QALY followed by S + B with CER of $24,072.86 per QALY. Compared with C + R, the ICER of S + B strategy was $70,725.38 per QALY, which would become the most cost-effective when the willing-to-pay threshold exceeded $73,500/QALY. In the subgroup analysis, with the application of Asia results in Leap-002 trial, the model results were the same as global data. In the sensitivity analysis, with the variation of parameters, the results were robust. CONCLUSION: As one of the promising immuno-combination therapies in the first-line systemic treatment of HCC, camrelizumab plus rivoceranib demonstrated the potential to be the most cost-effective strategy, which warranted further studies to best inform the real-world clinical practices.
Subject(s)
Antibodies, Monoclonal, Humanized , Antineoplastic Combined Chemotherapy Protocols , Carcinoma, Hepatocellular , Cost-Effectiveness Analysis , Immune Checkpoint Inhibitors , Liver Neoplasms , Humans , Antibodies, Monoclonal, Humanized/economics , Antibodies, Monoclonal, Humanized/therapeutic use , Antibodies, Monoclonal, Humanized/administration & dosage , Antineoplastic Combined Chemotherapy Protocols/therapeutic use , Antineoplastic Combined Chemotherapy Protocols/economics , Bevacizumab/economics , Bevacizumab/therapeutic use , Bevacizumab/administration & dosage , Carcinoma, Hepatocellular/drug therapy , Carcinoma, Hepatocellular/economics , Carcinoma, Hepatocellular/mortality , Carcinoma, Hepatocellular/therapy , China/epidemiology , Clinical Trials, Phase III as Topic , Immune Checkpoint Inhibitors/therapeutic use , Immune Checkpoint Inhibitors/economics , Liver Neoplasms/drug therapy , Liver Neoplasms/economics , Liver Neoplasms/mortality , Liver Neoplasms/therapy , Markov Chains , Phenylurea Compounds/therapeutic use , Phenylurea Compounds/economics , Progression-Free Survival , Quality-Adjusted Life Years , Quinolines/therapeutic use , Quinolines/economics , Quinolines/administration & dosage , Randomized Controlled Trials as TopicABSTRACT
Background: Pulmonary vein stenosis (PVS) continues to be a major complication after surgical repair of total anomalous pulmonary venous connection (TAPVC). Recent studies suggest that the morphology of pulmonary venous confluence and the left atrium (LA) is associated with PVS. However, there are limited data on the prognostic value of integrating quantitative confluence-atrial morphology into risk stratification. Objectives: This study sought to evaluate the prognostic impact of novel imaging metrics derived from 3-dimensional (3D) computed tomography angiography (CTA) modeling on postsurgical PVS (PPVS) in the supracardiac TAPVC (sTAPVC) setting. Methods: Patients undergoing sTAPVC repair in 2017 to 2022 from 3 centers were retrospectively reviewed. Study investigators developed 3D CTA modeled geometric features to quantify confluence-atrial morphology that were analyzed with regard to PPVS. Results: Of the 162 patients (median age 61 days; 55% having preoperative pulmonary venous obstruction [prePVO]) included, 47 (29%) with PPVS at a median of 1.5 months ([quartile 1-quartile 3: 1.5-3.0 months]). In the univariable analysis, the indexed total volume of the LA and confluence (iTVLC) and the ratio of the corresponding confluence length to the mean distance between the LA and confluence (CCL/mDBLC ratio) were significantly associated with PPVS. In a multivariable model adjusting for prePVO and age, the iTVLC and CCL/mDBLC ratio independently predicted PPVS (HR: 1.15; 95% CI: 1.06-1.25; and HR: 1.20; 95% CI: 1.08-1.35, respectively, all P < 0.01). Specifically, an iTVLC ≥20 cm3/m2 and a CCL/mDBLC ratio ≥7.7 were significantly associated with a reduced risk of PPVS. Conclusions: Quantification of 3D confluence-atrial morphology appears to offer a deeper and better metric to predict PPVS in patients with sTAPVC.
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Electrochemical water splitting is regarded as an emerging green and sustainable hydrogen production technology because of its zero-carbon process. However, the overall cost of anode materials in a proton exchange membrane water electrolyzer (PEMWE) is high due to the use of noble metal Ir. It has been proved that introducing carrier materials to reduce the content of Ir element is a feasible cost-reduction program. Here, the Ir/TiO2 composite material was prepared by the polyol method and used to catalyze the oxygen evolution reaction, which could effectively reduce the load amount of Ir in the membrane electrode assembly (MEA). In addition, the theoretical load of Ir was obtained by model calculation and the polarization curve test and electrochemical impedance spectroscopy (EIS) were used to discuss the relationship between Ir load in MEA and voltage loss and conductivity. The results show that MEA has lower voltage loss and better conductivity as the Ir load is in the range of 0.204-0.304 mgIr/cm2. Altogether, an effective method to reduce the Ir load of PEMWE anode was proposed under the premise comprehensive consideration of both catalyst design and MEA preparation in this work.
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Background: Linezolid (LZD) is a cornerstone medication in the treatment of drug-resistant tuberculosis (DR-TB). However, it frequently triggers adverse effects such as bone marrow suppression, optic neuropathy, and peripheral neuropathy, all of which can impact treatment outcomes and prognosis. Contezolid (CZD), a novel oxazolidinone antibiotic, exhibits comparable antimicrobial efficacy against Mycobacterium tuberculosis as LZD, but with potentially enhanced safety profiles. Case Presentation: This report presents five cases (Cases 1-5) of LZD intolerance, wherein CZD served as an effective alternative treatment. In Cases 1-3, LZD administration resulted in bone marrow suppression, primarily manifested as anemia. Transitioning to CZD therapy led to a rise and stabilization of hemoglobin (HGB) levels in Cases 1-2, and a return to baseline values in Case 3. In Case 4, CZD treatment alleviated symptoms of LZD-induced peripheral neuritis, although complete resolution was not achieved, hinting at potential irreversibility of this type of peripheral neuropathy. In Case 5, direct CZD anti-TB therapy was initiated for recurrent leukopenia and neutropenia, resulting in no further severe myelosuppression and successful recovery. Conclusion: These case studies suggest that CZD could represent an effective and safe option for anti-TB therapy, especially for patients intolerant to LZD.
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Untargeted metabolomic analysis using mass spectrometry provides comprehensive metabolic profiling, but its medical application faces challenges of complex data processing, high inter-batch variability, and unidentified metabolites. Here, we present DeepMSProfiler, an explainable deep-learning-based method, enabling end-to-end analysis on raw metabolic signals with output of high accuracy and reliability. Using cross-hospital 859 human serum samples from lung adenocarcinoma, benign lung nodules, and healthy individuals, DeepMSProfiler successfully differentiates the metabolomic profiles of different groups (AUC 0.99) and detects early-stage lung adenocarcinoma (accuracy 0.961). Model flow and ablation experiments demonstrate that DeepMSProfiler overcomes inter-hospital variability and effects of unknown metabolites signals. Our ensemble strategy removes background-category phenomena in multi-classification deep-learning models, and the novel interpretability enables direct access to disease-related metabolite-protein networks. Further applying to lipid metabolomic data unveils correlations of important metabolites and proteins. Overall, DeepMSProfiler offers a straightforward and reliable method for disease diagnosis and mechanism discovery, enhancing its broad applicability.
Subject(s)
Deep Learning , Lung Neoplasms , Mass Spectrometry , Metabolome , Metabolomics , Humans , Metabolomics/methods , Mass Spectrometry/methods , Lung Neoplasms/metabolism , Lung Neoplasms/blood , Lung Neoplasms/diagnosis , Adenocarcinoma of Lung/metabolism , Adenocarcinoma of Lung/blood , Adenocarcinoma of Lung/diagnosis , Male , Female , Data Analysis , Reproducibility of Results , Middle AgedABSTRACT
The integration of sensing and communication can achieve ubiquitous sensing while enabling ubiquitous communication. Within the gradually improving global communication, the integrated sensing and communication system based on optical fibers can accomplish various functionalities, such as urban structure imaging, seismic wave detection, and pipeline safety monitoring. With the development of quantum communication, quantum networks based on optical fiber are gradually being established. In this paper, we propose an integrated sensing and quantum network (ISAQN) scheme, which can achieve secure key distribution among multiple nodes and distributed sensing under the standard quantum limit. The continuous variables quantum key distribution protocol and the round-trip multiband structure are adopted to achieve the multinode secure key distribution. Meanwhile, the spectrum phase monitoring protocol is proposed to realize distributed sensing. It determines which node is vibrating by monitoring the frequency spectrum and restores the vibration waveform by monitoring the phase change. The scheme is experimentally demonstrated by simulating the vibration in a star structure network. Experimental results indicate that this multiuser quantum network can achieve a secret key rate of approximately 0.7 Mbits/s for each user under 10-km standard fiber transmission, and its network capacity is 8. In terms of distributed sensing, it can achieve a vibration response bandwidth ranging from 1 Hz to 2 kHz, a strain resolution of 0.50 n ε / Hz , and a spatial resolution of 0.20 m under shot-noise-limited detection. The proposed ISAQN scheme enables simultaneous quantum communication and distributed sensing in a multipoint network, laying a foundation for future large-scale quantum networks and high-precision sensing networks.
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Eggs are recognized for their rich nutrient profile, providing essential proteins and lipids with notable functional properties. This study examines the effects of incorporating Water Extract of Ampelopsis grossedentata (WEA) into poultry feed on egg quality, focusing on lipid content, choline, L-carnitine levels, and flavonoid compound deposition. Our results show significant increases in essential amino acids, flavonoids, and other bioactive compounds in eggs from WEA-treated hens, suggesting enhanced cardiovascular, antioxidant, and anti-inflammatory benefits. Additionally, we observed elevated levels of choline and betaine in egg yolks, alongside increased L-carnitine content, which may contribute to improved lipid metabolism and reduced cardiovascular disease risk. KEGG pathway analysis revealed upregulation of metabolites involved in critical metabolic pathways, enhancing the nutritional profile of eggs. Flavonoid compounds, traditionally associated with plant-based foods, were also significantly increased, with notable levels of 7, 4'-dihydroxyflavone, daidzein, and glycitein identified in WEA-treated eggs, indicating potential health benefits. These findings suggest that WEA supplementation can produce functional eggs with improved nutritional quality, offering a novel approach to enhancing egg production and meeting the growing demand for functional foods. Further research is needed to fully understand the bioavailability and health impacts of these enriched compounds.
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PURPOSE: To investigate the dose rate dependence of MapCHECK3 and its influence on measurement accuracy, as well as the effect of dose rate correction. MATERIALS AND METHODS: The average and instantaneous dose rate dependence of MapCHECK2 and MapCHECK3 were studied. The accuracy of measurements was investigated where the dose rate differed significantly between dose calibration of the MapCHECK and the measurement. Measurements investigated include: the central axis dose for different fields at different depths, off-axis doses outside the field, and off-axis doses along the wedge direction. Measurements using an ion chamber were taken as the reference. Exponential functions were fit to account for average and instantaneous dose rate dependence for MapCHECK3 and used for dose rate correction. The effect of the dose rate correction was studied by comparing the differences between the measurements for MapCHECK (with and without the correction) and the reference. RESULTS: The maximum dose rate dependence of MapCHECK3 is greater than 2.5%. If the dose calibration factor derived from a 10 × 10 cm2 open field at 10 cm depth was used for measurements, the average differences in central diode dose were 0.8% ± 1.0% and 1.0% ± 0.8% for the studied field sizes and measurement depths, respectively. The introduction of wedge would not only induce -1.8% ± 1.3% difference in central diode dose, but also overestimate the effective wedge angle. After the instantaneous dose rate correction, above differences can be changed to 1.9% ± 8.1%, 0.2% ± 0.1%, and 0.0% ± 0.9%. The pass rate can be improved from 98.4% to 98.8%, 98.3%-100.0%, and 96.3%-100.0%, respectively. CONCLUSION: Compared with MapCHECK2 (SunPoint1 diodes), the more pronounced dose rate dependence of MapCHECK3 (SunPoint2 diodes) should be carefully considered. To ensure highly accurate measurement, it is suggested to perform the dose calibration at the same condition where measurement will be performed. Otherwise, the dose rate correction should be applied.
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With the increasing age of the population worldwide, the incidence rate of Parkinson's disease (PD) is increasing annually. Currently, the treatment strategy for PD only improves clinical symptoms. No effective treatment strategy can slow down the progression of the disease. In the present study, whole transcriptome sequencing was used to obtain the mRNA and miRNA expression profiles in a PD mouse model, which revealed the pathogenesis of PD. The transcription factor RUNX3 upregulated the miR-186-3p expression in the PD model. Furthermore, the high miR-186-3p expression in PD can be targeted to inhibit the DAT expression, resulting in a decrease in the dopamine content of dopaminergic neurons. Moreover, miR-186-3p can be targeted to inhibit the IGF1R expression and prevent the activation of the IGF1R-P-PI3K-P-AKT pathway, thus increasing the apoptosis of dopaminergic neurons by regulating the cytochrome c-Bax-cleaved caspase-3 pathway. Our research showed that the RUNX3-miR-186-3p-DAT-IGF1R axis plays a key role in the pathogenesis of PD, and miR-186-3p is a potential target for the treatment of PD.
Subject(s)
Core Binding Factor Alpha 3 Subunit , Disease Models, Animal , MicroRNAs , Parkinson Disease , Receptor, IGF Type 1 , MicroRNAs/genetics , MicroRNAs/metabolism , Animals , Receptor, IGF Type 1/metabolism , Receptor, IGF Type 1/genetics , Parkinson Disease/genetics , Parkinson Disease/metabolism , Parkinson Disease/pathology , Core Binding Factor Alpha 3 Subunit/metabolism , Core Binding Factor Alpha 3 Subunit/genetics , Mice, Inbred C57BL , Male , Apoptosis/genetics , Signal Transduction , Dopaminergic Neurons/metabolism , Dopaminergic Neurons/pathology , Mice , Base SequenceABSTRACT
Ultrahigh-temperature Joule-heating of carbon nanostructures opens up unique opportunities for property enhancements and expanded applications. This study employs rapid electrical Joule-heating at ultrahigh temperatures (up to 3000 K within 60 s) to induce a transformation in nanocarbon aerogels, resulting in highly graphitic structures. These aerogels function as versatile platforms for synthesizing customizable metal oxide nanoparticles while significantly reducing carbon emissions compared to conventional furnace heating methods. The thermal conductivity of the aerogel, characterized by Umklapp scattering, can be precisely adjusted by tuning the heating temperature. Utilizing the aerogel's superhydrophobic properties enables its practical application in filtration systems for efficiently separating toxic halogenated solvents from water. The hierarchically porous aerogel, featuring a high surface area of 607 m2 g-1, ensures the uniform distribution and spacing of embedded metal oxide nanoparticles, offering considerable advantages for catalytic applications. These findings demonstrate exceptional catalytic performance in oxidative desulfurization, achieving a 98.9% conversion of dibenzothiophene in the model fuel. These results are corroborated by theoretical calculations, surpassing many high-performance catalysts. This work highlights the pragmatic and highly efficient use of nanocarbon structures in nanoparticle synthesis under ultrahigh temperatures, with short heating durations. Its broad implications extend to the fields of electrochemistry, energy storage, and high-temperature sensing.
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Skeleton-based action recognition, renowned for its computational efficiency and indifference to lighting variations, has become a focal point in the realm of motion analysis. However, most current methods typically only extract global skeleton features, overlooking the potential semantic relationships among various partial limb motions. For instance, the subtle differences between actions such as "brush teeth" and "brush hair" are mainly distinguished by specific elements. Although combining limb movements provides a more holistic representation of an action, relying solely on skeleton points proves inadequate for capturing these nuances. Therefore, integrating detailed linguistic descriptions into the learning process of skeleton features is essential. This motivates us to explore integrating fine-grained language descriptions into the learning process of skeleton features to capture more discriminative skeleton behavior representations. To this end, we introduce a new Linguistic-Driven Partial Semantic Relevance Learning framework (LPSR) in this work. While using state-of-the-art large language models to generate linguistic descriptions of local limb motions and further constrain the learning of local motions, we also aggregate global skeleton point representations and textual representations (which generated from an LLM) to obtain a more generalized cross-modal behavioral representation. On this basis, we propose a cyclic attentional interaction module to model the implicit correlations between partial limb motions. Numerous ablation experiments demonstrate the effectiveness of the method proposed in this paper, and our method also obtains state-of-the-art results.
Subject(s)
Semantics , Humans , Linguistics , Movement/physiology , Pattern Recognition, Automated/methods , Algorithms , Learning/physiologyABSTRACT
Long noncoding RNAs (lncRNAs) constitute a distinctive subset of RNA molecules with limited protein-coding potential, which exert crucial impacts on various biological activities. In the context of cancer, dysregulated lncRNAs function as essential regulators that affect tumor initiation and malignant progression. These lncRNAs serve as competitive endogenous RNAs (ceRNAs) through sponging microRNAs and regulating the expression of targeted genes. Moreover, they also directly bind to RNA-binding proteins, which can be integrated into a complex mechanistic network. E2F1, an extensively studied transcription factor, mediates multiple malignant behaviors by regulating cell cycle progression, tumor metastasis, and therapeutic response. Emerging evidence suggests that lncRNAs play a pivotal role in regulating the E2F1 pathway. This review aims to elucidate the intricate gene regulatory programs between lncRNAs and E2F1 in cancer progression. We elaborate on distinct mechanistic networks involved in cancer progression, emphasizing the potential of the lncRNAs/E2F1 axes as promising targets for cancer therapy. Additionally, we provide novel perspectives on current evidence, limitations, and future directions for targeting lncRNAs in human cancers. Fully deciphering the intricate network of lncRNA/E2F1-mediated regulatory mechanisms in cancer could facilitate the translation of current findings into clinical course, such efforts ultimately significantly improve the clinical prognosis of cancer patients.
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BACKGROUND: In various disease contexts, magnesium abnormalities are associated with acute kidney injury (AKI) incidence. However, this association remains unclear and has not been systematically investigated in patients with cirrhosis. Hence, we aimed to elucidate the association between admission serum magnesium levels and AKI incidence in intensive care unit (ICU)-admitted cirrhotic patients. METHODS: A retrospective cohort study was conducted using MIMIC-IV2.2 data, focusing on critically ill patients with cirrhosis. We employed univariable and multivariable logistic regression and restricted cubic spline analyses to robustly address our research objectives. To further substantiate the findings, subgroup and sensitivity analyses were also conducted. RESULTS: Among the 3,228 enrolled ICU-admitted cirrhotic patients, 34.4% were female, and the overall AKI incidence was 68.6% (2,213/3,228). Multivariable logistic regression analysis revealed an independent relationship between elevated serum magnesium levels and increased AKI risk (OR = 1.55 [95% CI = 1.15-2.09], p = 0.004). Compared with individuals with serum magnesium levels < 1.6 mg/dL, individuals with serum magnesium levels in Q2 (1.6-2.6 mg/dL) and Q3 (≥2.6 mg/dL) had adjusted ORs for AKI of 1.89 (95% CI = 1.34-2.65, p < 0.001) and 2.19 (95% CI = 1.27-3.75, p = 0.005), respectively. The restricted cubic spline analysis revealed that AKI risk increased linearly with increasing serum magnesium levels. Subgroup analysis revealed that the association between serum magnesium levels and AKI incidence was remarkably stable in subgroup analysis (all Pinteraction >0.05). CONCLUSIONS: High serum magnesium concentrations were significantly associated with an increased AKI risk in ICU-admitted patients with cirrhosis. Further randomized trials are needed to confirm this association.
Subject(s)
Acute Kidney Injury , Intensive Care Units , Liver Cirrhosis , Magnesium , Humans , Acute Kidney Injury/blood , Acute Kidney Injury/epidemiology , Acute Kidney Injury/etiology , Female , Magnesium/blood , Retrospective Studies , Male , Middle Aged , Liver Cirrhosis/blood , Liver Cirrhosis/complications , Intensive Care Units/statistics & numerical data , Incidence , Aged , Risk Factors , Critical Illness , Logistic Models , Databases, Factual , AdultABSTRACT
The bottom contact in perovskite solar cells (PSCs) is easy to cause deep trap states and severe instability issues, especially under maximum power point tracking (MPPT). In this study, sodium gluconate (SG) is employed to disperse tin oxide (SnO2) nanoparticles (NPs) and regulate the interface contact at the buried interface. The SG-SnO2 electron transfer layer (ETL) enabled the deposition of pinhole-free perovskite films in ambient air and improved interface contact by bridging effect. SG-SnO2 PSCs achieved an impressive power conversion efficiency (PCE) of 25.34% (certified as 25.17%) with a high open-circuit voltage (VOC) exceeding 1.19 V. The VOC loss is less than 0.34 V relative to the 1.53 eV bandgap, and the fill factor (FF) loss is only 2.02% due to the improved contact. The SG-SnO2 PSCs retained around 90% of their initial PCEs after 1000 h operation (T90 = 1000 h), higher than T80 = 1000 h for the control SnO2 PSC. Microstructure analysis revealed that light-induced degradation primarily occurred at the buried holes and grain boundaries and highlighted the importance of bottom-contact engineering.
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Biological materials relying on hierarchically ordered architectures inspire the emergence of advanced composites with mutually exclusive mechanical properties, but the efficient topology optimization and large-scale manufacturing remain challenging. Herein, this work proposes a scalable bottom-up approach to fabricate a novel nacre-like cement-resin composite with gradient brick-and-mortar (BM) structure, and demonstrates a machine learning-assisted method to optimize the gradient structure. The fabricated gradient composite exhibits an extraordinary combination of high flexural strength, toughness, and impact resistance. Particularly, the toughness and impact resistance of such composite attractively surpass the cement counterparts by factors of approximately 700 and 600 times, and even outperform natural rocks, fiber-reinforced cement-based materials and even some alloys. The strengthening and toughening mechanisms are clarified as the regional-matrix densifying and crack-tip shielding effects caused by the gradient BM structure. The developed gradient composite not only endows a promising structural material for protective applications in harsh scenarios, but also paves a new way for biomimetic metamaterials designing.
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To clarify the regulating effect of vegetation and soil factors on microbial communities in the alpine steppe under degradation on the Qinghai-Xizang Plateau, the alpine steppe in the Sanjiangyuan area of the Qinghai-Tibet Plateau was chosen. We analyzed the differences in vegetation and soil factors in different stages of degradation ï¼non-degradation, moderate degradation, and severe degradationï¼ and detected the variations in microbial community characteristics in the alpine steppe under different degradation stages using high-throughput sequencing technology. Eventually, redundancy analysis ï¼RDAï¼ and multiple regression matrixes ï¼MRMï¼ based on the similarity or dissimilarity matrix were used to identify key environmental factors regulating microbial ï¼bacterial and fungalï¼ community changes under degradation. The results showed that the degradation of the alpine steppe significantly changed the community coverage, height, biomass, and important value of graminaeï¼ significantly reduced the contents of soil organic matter, total nitrogen, total phosphorus, and siltï¼ and increased the soil bulk density and sand content. Degradation did not change the composition of bacteria and fungi, but their composition proportions changed and also resulted in the loss of microbial richness ï¼Chao1 index and Richness indexï¼ but did not significantly change the microbial diversity ï¼Shannon indexï¼. With the occurrence of degradation, the vegetation characteristics, soil physicochemical properties, and microbial diversity showed a consistent change trend. Combined with the characteristics of the network topology changes ï¼the number of nodes and clustering coefficient significantly decreasedï¼, it was found that degradation of the alpine steppe led to the decline of interspecies interactions, decentralization of network, and homogenization of microorganisms, but the cooperation relations among the species were maintained ï¼positive correlation connections accounted for more than 90% in all degradation stagesï¼. Under the alpine steppe degradation, the vegetation-soil interaction had the greatest effect on soil bacterial community, whereas soil physicochemical properties had the greatest influence on soil fungal community. Specifically, vegetation community height, biomass, and soil bulk density were the mutual factors regulating soil microorganisms, whereas the vegetation Simpson index, important value of graminae, soil total phosphorus, total potassium, and silt content were the unique factors affecting the soil bacterial community, and soil pH and total nitrogen content were the particular factors affecting the soil fungal community.
Subject(s)
Grassland , Microbiota , Soil Microbiology , Soil , Soil/chemistry , Bacteria/classification , Bacteria/isolation & purification , Bacteria/growth & development , Phosphorus/analysis , China , Nitrogen/analysis , Fungi/classification , Fungi/isolation & purification , Tibet , EcosystemABSTRACT
A novel method for synthesizing substituted 4-chloroquinolines has been devised, utilizing a cascade reaction of N-aryl enaminones promoted by bis(trichloromethyl) carbonate (BTC) and triphenylphosphine oxide (TPPO). This approach features accessible starting materials, a broad substrate range, extensive functional group compatibility, gentle reaction conditions, and straightforward operation. Its versatility is evidenced by its facile scalability and suitability for late-stage derivatization. A plausible mechanism involving α-carbonylation, 6π-azaelectrocyclization, and dehydroxychlorination sequence is proposed.
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BACKGROUND: To identify the sensitivity, specificity, and overall diagnostic accuracy of infrared thermography in diagnosing lumbosacral radicular pain. METHODS: Patients sequentially presenting with lower extremity pain were enrolled. A clinical certainty score ranging from 0 to 10 was used to assess the likelihood of lumbosacral radicular pain, with higher scores indicating higher likelihood. Infrared Thermography scans were performed and the temperature difference (ΔT) was calculated as ΔT = T1 - T2, where T2 represents the skin temperature of the most painful area on the affected limb and T1 represents the skin temperature of the same area on the unaffected limb. Upon discharge from the hospital, two independent doctors diagnosed lumbosacral radicular pain based on intraoperative findings, surgical effectiveness, and medical records. RESULTS: A total of 162 patients were included in the study, with the adjudicated golden standard diagnosis revealing that 101 (62%) patients had lumbosacral radicular pain, while the lower extremity pain in 61 patients was attributed to other diseases. The optimal diagnostic value for ΔT was identified to fall between 0.8â and 2.2â, with a corresponding diagnostic accuracy, sensitivity, and specificity of 80%, 89%, and 66% respectively. The diagnostic accuracy, sensitivity, and specificity for the clinical certainty score were reported as 69%, 62%, and 79% respectively. Combining the clinical certainty score with ΔT yielded a diagnostic accuracy, sensitivity, and specificity of 84%, 77%, and 88% respectively. CONCLUSION: Infrared thermography proves to be a highly sensitive tool for diagnosing lumbosacral radicular pain. It offers additional diagnostic value in cases where general clinical evaluation may not provide conclusive results. TRIAL REGISTRATION: ChiCTR2300078786, 19/22/2023.