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The theoretical capacity of pristine silicon as anodes for lithium-ion batteries (LIBs) can reach up to 4200 mAh g-1 , however, the low electrical conductivity and the huge volume expansion limit their practical application. To address this challenge, a precursor strategy has been explored to induce the curling of graphene oxide (GO) flakes and the enclosing of Si nanoparticles by selecting protonated chitosan as both assembly inducer and carbon precursor. The Si nanoparticles are dispersed first in a slurry of GO by ball milling, then the resulting dispersion is dried by a spray drying process to achieve instantaneous solution evaporation and compact encapsulation of silicon particles with GO. An Al2 O3 layer is constructed on the surface of Si@rGO@C-SD composites by the atomic layer deposition method to modify the solid electrolyte interface. This strategy enhances obviously the electrochemical performance of the Si as anode for LIBs, including excellent long-cycle stability of 930 mAh g-1 after 1000 cycles at 1000 mA g-1 , satisfied initial Coulomb efficiency of 76.7%, and high rate ability of 806 mAh g-1 at 5000 mA g-1 . This work shows a potential solution to the shortcomings of Si-based anodes and provides meaningful insights for constructing high-energy anodes for LIBs.
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Surface-textured polymer nanocomposite (PNC) films are utilized in many device applications, and therefore understanding the relaxation behavior of such films is important. By extending an in situ wrinkle relaxation method, we observed that the thermal stability of wrinkled PNC films, both above and below the glass transition temperature (Tg), is proportional to a film's nanoparticle (polymer grafted and bare) concentration, with a slope that changes sign at a compensation temperature (Tcomp) that is determined to be in the vicinity of the film's Tg. This provides unambiguous confirmation of entropy-enthalpy compensation (EEC) as a general feature of PNC films, implying that the stability of PNC films changes from being enhanced to becoming diminished by simply passing through this characteristic temperature, a phenomenon having evident practical ramifications. We suggest EEC will also arise in films where residual stresses are associated with the film fabrication process, which is relevant to nanotech device applications.
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Phthalocyanines (Pc)-derived materials represent an attractive category of porous organic scaffolds featured by extensive π-conjugated networks, but their construction is still limited to the solution-based pathways, producing materials with inferior conductivity and porosity. Herein, a mechanochemistry-driven approach was developed leveraging the on-surface polymerization of aromatic nitrile monomers with ortho-positioned dicyano groups in the presence of metal catalysts (magnesium, zinc, or aluminum) under neat and ambient conditions. Diverse Pc-functionalized conjugated porous networks (Pc-CPNs) were obtained featured by extensively and fully π-conjugated skeletons, high surface areas, and hierarchical porosities. The monomers in this mechanochemical approach could be extended to those difficult to be handled in solution-based procedures. The Pc-CPNs displayed attractive electrochemical performance as supercapacitor and anodes in batteries, together with superb long-term stability.
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Poly(ionic liquid) (PIL)-based block copolymers are of particular interest as they combine the specific properties of PILs with the self-assembling behaviors of block copolymers, broadening the range of potential applications for PIL-based materials. In this work, three particle brushes: SiO2-g-poly(methyl methacrylate) (PMMA), SiO2-g-PIL, and SiO2-g-PMMA-b-PIL were prepared through surface-initiated atom transfer radical polymerization. Unlike the homogeneous homopolymer particle brushes, the block copolymer particle brush SiO2-g-PMMA-b-PIL exhibited a bimodal chain architecture and unique phase-separated morphology, which were confirmed by size-exclusion chromatography and transmission electron microscopy. In addition, the influence of the introduction of the PMMA segment on the gas separation and mechanical performance of the PIL-containing block copolymer particle brushes were investigated. A significant improvement of Young's modulus was observed in the SiO2-g-PMMA-b-PIL compared to the SiO2-g-PIL bulk films; meanwhile, their gas separation performances (CO2 permeability and CO2/N2 selectivity) were the same, which demonstrates the possibility of improving the mechanical properties of PIL-based particle brushes without compromising their gas separation performance.
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Technologies for removal of mercury from produced water and hydrocarbon phases are desired by oil and gas production facilities, oil refineries, and petrochemical plants. Herein, we synthesize and demonstrate the efficacy of an amphiphilic, thiol-abundant (11.8 wt % S, as thiol) polymer nanogel that can remove environmentally relevant mercury species from both produced water and the liquid hydrocarbon. The nanogel disperses in both aqueous and hydrocarbon phases. It has a high sorption affinity for dissolved Hg(II) complexes and Hg-dissolved organic matter complexes found in produced water and elemental (Hg0) and soluble Hg-alkyl thiol species found in hydrocarbons. X-ray absorption spectroscopy analysis indicates that the sorbed mercury is transformed to a surface-bound Hg(SR)2 species in both water and hydrocarbon regardless of its initial speciation. The nanogel had high affinity to native mercury species present in real produced water (>99.5% removal) and in natural gas condensate (>85% removal) samples, removing majority of the mercury species using only a 50 mg L-1 applied dose. This thiolated amphiphilic polymeric nanogel has significant potential to remove environmentally relevant mercury species from both water and hydrocarbon at low applied doses, outperforming reported sorbents like sulfur-impregnated activated carbons because of the mass of accessible thiol groups in the nanogel.
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Mercúrio , Hidrocarbonetos , Nanogéis , Polímeros , Compostos de Sulfidrila , ÁguaRESUMO
BACKGROUND: Septic shock comprises a heterogeneous population, and individualized resuscitation strategy is of vital importance. The study aimed to identify subclasses of septic shock with non-supervised learning algorithms, so as to tailor resuscitation strategy for each class. METHODS: Patients with septic shock in 25 tertiary care teaching hospitals in China from January 2016 to December 2017 were enrolled in the study. Clinical and laboratory variables were collected on days 0, 1, 2, 3 and 7 after ICU admission. Subclasses of septic shock were identified by both finite mixture modeling and K-means clustering. Individualized fluid volume and norepinephrine dose were estimated using dynamic treatment regime (DTR) model to optimize the final mortality outcome. DTR models were validated in the eICU Collaborative Research Database (eICU-CRD) dataset. RESULTS: A total of 1437 patients with a mortality rate of 29% were included for analysis. The finite mixture modeling and K-means clustering robustly identified five classes of septic shock. Class 1 (baseline class) accounted for the majority of patients over all days; class 2 (critical class) had the highest severity of illness; class 3 (renal dysfunction) was characterized by renal dysfunction; class 4 (respiratory failure class) was characterized by respiratory failure; and class 5 (mild class) was characterized by the lowest mortality rate (21%). The optimal fluid infusion followed the resuscitation/de-resuscitation phases with initial large volume infusion and late restricted volume infusion. While class 1 transitioned to de-resuscitation phase on day 3, class 3 transitioned on day 1. Classes 1 and 3 might benefit from early use of norepinephrine, and class 2 can benefit from delayed use of norepinephrine while waiting for adequate fluid infusion. CONCLUSIONS: Septic shock comprises a heterogeneous population that can be robustly classified into five phenotypes. These classes can be easily identified with routine clinical variables and can help to tailor resuscitation strategy in the context of precise medicine.
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Ressuscitação/métodos , Choque Séptico/terapia , Idoso , Análise de Variância , China , Feminino , Análise de Elementos Finitos , Hidratação/métodos , Hidratação/normas , Hidratação/estatística & dados numéricos , Humanos , Unidades de Terapia Intensiva/organização & administração , Unidades de Terapia Intensiva/estatística & dados numéricos , Masculino , Pessoa de Meia-Idade , Escores de Disfunção Orgânica , Ressuscitação/normas , Ressuscitação/estatística & dados numéricos , Fatores de Risco , Choque Séptico/classificação , Estatísticas não ParamétricasRESUMO
Perfluorinated covalent triazine frameworks (F-CTFs) have shown unique features and attractive performance in separation and catalysis. However, state-of-the-art F-CTFs synthesized via the ZnCl2 -promoted procedure have quite low fluorine contents due to C-F bond cleavage induced by chloride (a Lewis base) and the harsh conditions deployed (400-700 °C). Fabricating F-CTFs with high fluorine contents (>30â wt %) remains challenging. Herein, we present a low-temperature ionothermal approach (275 °C) to prepare F-CTFs, which is achieved via polymerization of tetrafluoroterephthalonitrile (TFPN) over the Lewis superacids, e.g., zinc triflimide [Zn(NTf2 )2 ] without side reactions. With low catalyst loading (equimolar), F-CTFs are afforded with high fluorine content (31â wt %), surface area up to 367â m2 g-1 , and micropores around 1.1â nm. The highly hydrophobic F-CTF-1 exhibits good capability to boost electroreduction of CO2 to CO, with faradaic efficiency of 95.7 % at -0.8â V and high current density (-141â mA cm-2 ) surpassing most of the metal-free electrocatalysts.
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Acute respiratory distress syndrome (ARDS) is a severe condition with high morbidity and mortality and few interventions. The role of sympathetic stress in the pathogenesis of ARDS has attracted recent research attention. Blockade of α-2 or α2A-adrenoceptor (α2A-AR) has been shown to attenuate lung injury induced by lipopolysaccharide (LPS) in rats. However, the mechanism is unclear. We confirmed the role of α2A-AR in ARDS using knockout mice and alveolar macrophages following LPS stimulation to assess the underlying mechanisms. We found that α2A-AR deficiency decreased the permeability of the alveolar capillary barrier in ARDS mice and suppressed lung inflammation by reducing inflammatory cell infiltration and the production of TNF-α, interleukin (IL)-6, and CXCL2/MIP-2. LPS stimulation decreased NF-κB activation in lung tissues of α2A-AR deficient mice and increased norepinephrine concentrations. In vitro, we found that norepinephrine inhibited the production of TNF-α, IL-6, and CXCL2/MIP-2 and promoted the secretion of IL-10 from LPS-stimulated murine alveolar macrophages. Blockade of α2A-AR by a specific antagonist further inhibited the production of TNF-α, IL-6, and IL-10. Furthermore, norepinephrine down-regulated NF-κB activation in stimulated alveolar macrophages. Altogether, these results suggest that α2A-AR deficiency ameliorates lung injury by increasing norepinephrine concentrations in lung tissues and inhibiting the activation of alveolar macrophages.
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Pulmão/metabolismo , Macrófagos Alveolares/fisiologia , Norepinefrina/metabolismo , Receptores Adrenérgicos alfa 2/fisiologia , Síndrome do Desconforto Respiratório/imunologia , Animais , Permeabilidade Capilar , Linhagem Celular , Modelos Animais de Doenças , Lipopolissacarídeos , Pulmão/imunologia , Ativação de Macrófagos , Masculino , Camundongos Knockout , Infiltração de Neutrófilos , Síndrome do Desconforto Respiratório/metabolismoRESUMO
Transcription factors (TFs) play a crucial role in controlling key cellular processes and responding to the environment. Yeast is a single-cell fungal organism that is a vital biological model organism for studying transcription and translation in basic biology. The transcriptional control process of yeast cells has been extensively calculated and studied using traditional methods and high-throughput technologies. However, the identities of transcription factors that regulate major functional categories of genes remain unknown. Due to the avalanche of biological data in the post-genomic era, it is an urgent need to develop automated computational methods to enable accurate identification of efficient transcription factor binding sites from the large number of candidates. In this paper, we analyzed high-resolution DNA-binding profiles and motifs for TFs, covering all possible contiguous 8-mers. First, we divided all 8-mer motifs into 16 various categories and selected all sorts of samples from each category by setting the threshold of E-score. Then, we employed five feature representation methods. Also, we adopted a total of four feature selection methods to filter out useless features. Finally, we used Extreme Gradient Boosting (XGBoost) as our base classifier and then utilized the one-vs-rest tactics to build 16 binary classifiers to solve this multiclassification problem. In the experiment, our method achieved the best performance with an overall accuracy of 79.72% and Mathew's correlation coefficient of 0.77. We found the similarity relationship among each category from different TF families and obtained sequence motif schematic diagrams via multiple sequence alignment. The complexity of DNA recognition may act as an important role in the evolution of gene regulation. Source codes are available at https://github.com/guofei-tju/tfbs.
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Saccharomyces cerevisiae , Fatores de Transcrição , Sítios de Ligação , Biologia Computacional , Regulação da Expressão Gênica , Ligação Proteica , Saccharomyces cerevisiae/genética , Saccharomyces cerevisiae/metabolismo , Fatores de Transcrição/genética , Fatores de Transcrição/metabolismoRESUMO
BACKGROUND: To develop a machine learning model for predicting acute respiratory distress syndrome (ARDS) events through commonly available parameters, including baseline characteristics and clinical and laboratory parameters. METHODS: A secondary analysis of a multi-centre prospective observational cohort study from five hospitals in Beijing, China, was conducted from January 1, 2011, to August 31, 2014. A total of 296 patients at risk for developing ARDS admitted to medical intensive care units (ICUs) were included. We applied a random forest approach to identify the best set of predictors out of 42 variables measured on day 1 of admission. RESULTS: All patients were randomly divided into training (80%) and testing (20%) sets. Additionally, these patients were followed daily and assessed according to the Berlin definition. The model obtained an average area under the receiver operating characteristic (ROC) curve (AUC) of 0.82 and yielded a predictive accuracy of 83%. For the first time, four new biomarkers were included in the model: decreased minimum haematocrit, glucose, and sodium and increased minimum white blood cell (WBC) count. CONCLUSIONS: This newly established machine learning-based model shows good predictive ability in Chinese patients with ARDS. External validation studies are necessary to confirm the generalisability of our approach across populations and treatment practices.
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Algoritmos , Unidades de Terapia Intensiva , Aprendizado de Máquina , Modelos Teóricos , Síndrome do Desconforto Respiratório/diagnóstico , Idoso , China , Estudos de Coortes , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Curva ROCRESUMO
The evolution of particle morphology occurring during polymerization-induced self-assembly (PISA) of a block copolymer poly(oligo(ethylene glycol) methacrylate)-b-poly(benzyl methacrylate) (POEGMA-b-PBzMA) is studied. A well-controlled reversible addition-fragmentation chain transfer (RAFT) polymerization yields nano-objects with various morphologies: spheres, aggregates, worm-like structures, and vesicles. A comparison of the morphology of the nano-objects formed from two different chain-length stabilizers established that the unreacted monomer played an important role during the morphology transitions, which is contrary to previous observations. In addition, morphology evolution to higher-order structures could be attained simply by extending the reaction time, after reaching full monomer conversion.
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Técnicas de Química Sintética/métodos , Nanopartículas/química , Polimerização , Ácidos Polimetacrílicos/química , Microscopia Eletrônica de Transmissão , Nanopartículas/ultraestrutura , Ácidos Polimetacrílicos/síntese químicaRESUMO
An aqueous-based approach for the scalable synthesis of nitrogen-doped porous carbons with high specific surface area (SSA) and high nitrogen content is presented. Low molecular weight polyacrylonitrile (PAN) is solubilized in water in the presence of ZnCl2 that also acts as a volatile porogen during PAN pyrolysis to form mesoporous structures with significantly increased SSA. By templating with commercial SiO2 nanoparticles, nanocellulose fillers or filter paper, nanocarbons with SSA = 1776, 1366, and 1501 m2/g, respectively and 10 wt % N content were prepared. The materials formed by this benign process showed excellent catalytic activity in oxygen reduction reaction via the four-electron mechanism.
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Severe water pollution issues present an important contemporary challenge that drives the development and advancement of efficient and environmentally benign photocatalysts that enable the degradation of pollutants upon visible light irradiation. One example is zinc oxide/carbon (ZnO/C) hybrid materials that have been shown to be effective photocatalysts. To maximize the effectiveness of ZnO/C hybrids, materials with high accessible surface area of ZnO are required. Here, a novel strategy is presented to enable the synthesis of fine dispersions of ZnO nanoparticles within a porous carbon matrix. The synthesis entails the grafting of ZnO nanparticles with polystyrene-b-poly(styrene-co-acrylonitrile) (PS-b-PSAN) block copolymer and subsequent pyrolysis of the material under inert gas (N2) atmosphere. During the pyrolysis process, the PS block effectively prevents agglomeration of ZnO particles, thus resulting in a fine dispersion of ZnO nanocrystals within a prorous C matrix. Materials are found to exhibit a dye adsorption capacity of 125 mg g-1 (from a methylene blue aqueous solution with a concentration of 305 mg L-1) and dye degradation rate constant of 0.021 min-1. The significant increase of effective surface area and degradation efficacy (as compared to ZnO/C synthesized by the pyrolysis of binary PSAN/ZnO blends) is rationalized as a consequence of the increased porosity that promotes dye adsorption and transport within the hybrid material.
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The synthesis of a sulfoxide-based water-soluble polymer, poly(2-(methylsulfinyl)ethyl acrylate) (polyMSEA), a polymeric analogue of DMSO, by atom transfer radical polymerization (ATRP) is reported. Well-defined linear polymers were synthesized using relatively low amounts of copper catalyst (1000 or 100 ppm). Two types of star polymers were synthesized by either an "arm-first" approach or a "core-first" approach using a biodegradable ß-cyclodextrin core. The glass transition temperatures of both the linear polymer (16 °C) and star polymer (32 °C) were determined by differential scanning calorimetry (DSC). The lower critical solution temperature (LCST) of poly(MSEA) was estimated to be ca. 140 °C by extrapolating the LCST of a series of copolymers with NIPAM. Cytotoxicity tests revealed that both the linear and star polymers have low toxicity, even at concentrations up to 3 mg/mL.
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Materiais Biocompatíveis/administração & dosagem , Dimetil Sulfóxido/química , Polímeros/administração & dosagem , Materiais Biocompatíveis/química , Varredura Diferencial de Calorimetria , Catálise , Sobrevivência Celular/efeitos dos fármacos , Células HEK293 , Humanos , Polimerização , Polímeros/química , Temperatura de Transição , Água/químicaRESUMO
Poly(styrene-co-acrylonitrile) (PSAN)-capped ZnO nanoparticles (NPs) were synthesized by a "ligand exchange" method. First, octylamine (OA)-capped ZnO NPs were prepared by reaction of OA and zinc 2-ethylhexanoate (Zn(EH)2). Then PSAN polymer ligands were synthesized by activators regenerated by electron transfer (ARGET) atom transfer radical polymerization (ATRP) and were efficiently exchanged with OA ligands on the ZnO particle surface benefiting from the relatively low boiling point of OA (175 °C). The morphology, content of ZnO, and grafting density of the nanocomposite were well controlled by altering the ratio between OA and polymer ligands as well as the molecular weight of PSAN-NH2 used in the exchange reaction. The resulting ZnO/polymer nanocomposites were stable in THF with narrow size distributions and varying grafting densities from 0.9 to 2.5 nm-2. With excess amount of polymer ligands, individual dispersed ZnO NPs were observed. However, with a limited amount of ligands, NPs clusters were formed, as confirmed by TEM and DLS.
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Photoinduced ATRP was successfully performed in aqueous media. Polymerization of oligo(ethylene oxide) methyl ether methacrylate (OEOMA) in the presence of CuBr2 catalyst and tris(2-pyridylmethyl)amine ligand when irradiated with visible light of 392 nm wavelength at 0.9 mW/cm(2) intensity was well controlled. Linear semi-logarithmic kinetic plots and molecular weights increasing with conversion were observed. Polymers of OEOMA were synthesized with low dispersity (Mw/Mn = 1.12) using only 22 ppm of copper catalyst in the presence of excess bromide anions in highly diluted (90% v/v) aqueous media. The effects of copper concentration, salt, and targeted degrees of polymerization were investigated. The polymerization could be directly regulated by external stimulation, i.e., switching the irradiation on/off, with a good retention of chain-end functionality, as proved by clean chain extension of the OEOMA polymers. This new system could enable applications for controlled aqueous radical polymerization due to its low catalyst loading in the absence of any other chemicals.
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BACKGROUND: In recent years, microcirculatory blood flow alterations have been recognized to be stronger predictors of septic shock treatment outcomes than global hemodynamic variables. METHODS: In our self-controlled, interventional pilot clinical trial study, we investigated the effects of a single papaverine injection on the microcirculation in sepsis patients undergoing fluid resuscitation combined with vasopressor treatments. Fourteen septic shock patients admitted to the Peking University Third Hospital were included in the study, and each patient received 30 mg papaverine, which is the approximate dosage used to treat a conventional arterial spasm. Papaverine was administered as an intravenous bolus injection after systemic hemodynamic stabilization had been achieved by means of fluid resuscitation combined with dopamine and/or norepinephrine vasopressor medication. Baseline characteristics, as well as global hemodynamic and blood gas parameters, before and 60 min after papaverine injection were recorded and sublingual microcirculatory data at baseline and 15, 30, and 60 min after papaverine administration obtained using sidestream dark-field video microscopy. RESULTS: The perfused vessel density of small vessels was significantly increased 30 and 60 min after papaverine administration (P < 0.01), and the proportion of perfused small vessels (PPV), as well as the microvascular flow index, was significantly increased 30 min after papaverine (P < 0.05). There were no visible systemic effects, arrhythmia, or hypotension during the observation period in each patient. CONCLUSIONS: In our pilot study, papaverine transiently improved sublingual microcirculatory blood flow without influencing systemic hemodynamics in patients with septic shock, who required vasoconstrictors to maintain blood pressure during fluid resuscitation.
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Microcirculação/efeitos dos fármacos , Papaverina/uso terapêutico , Fitoterapia , Choque Séptico/tratamento farmacológico , Vasodilatadores/uso terapêutico , Idoso , Idoso de 80 Anos ou mais , Feminino , Hemodinâmica/efeitos dos fármacos , Humanos , Masculino , Mucosa Bucal/irrigação sanguínea , Papaverina/farmacologia , Projetos Piloto , Extratos Vegetais/farmacologia , Extratos Vegetais/uso terapêutico , Vasodilatadores/farmacologiaRESUMO
PURPOSE: This study aimed to investigate whether CYP3A4*1G genetic polymorphism influences the metabolism of fentanyl in human liver microsomes in Chinese patients. METHODS: The human liver microsomes were obtained from 88 hepatobiliary surgery patients who accepted liver resection surgery in this study. A normal liver sample (confirmed by the Department of Pathology) was taken from the outer edge of the resected tissue. The metabolism of fentanyl in human liver microsomes was studied. The concentration of fentanyl was measured by high performance liquid chromatography. The CYP3A4*1G variant allele was genotyped using the PCR restriction fragment length polymorphism method. RESULTS: The frequency of the CYP3A4*1G variant allele was 0.188 in the 88 Chinese patients who had received hepatobiliary surgery. The metabolic rate of fentanyl in patients homozygous for the *1G/*1G variant (0.85 ± 0.37) was significantly lower than that in patients bearing the wild-type allele *1/*1 (1.89 ± 0.58) or in patients heterozygous for the *1/*1G variant (1.82 ± 0.65; p < 0.05). There were no gender-related differences in the metabolic rate of fentanyl (p > 0.05) nor was there any correlation between age and metabolic rate of fentanyl (p > 0.05). Results from different hepatobiliary diseases showed no significant difference in the metabolic rate of fentanyl (p > 0.05). The difference of CYP3A4 mRNA among different CYP3A4*1G variant alleles was significant (p < 0.05). There was positive correlation between CYP3A4 mRNA and metabolic rate of fentanyl (p < 0.01). CONCLUSIONS: CYP3A4*1G genetic polymorphism decreases the metabolism of fentanyl. There is a positive correlation between CYP3A4 mRNA level and metabolism of fentanyl.
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Povo Asiático/genética , Citocromo P-450 CYP3A/genética , Fentanila/metabolismo , Microssomos Hepáticos/metabolismo , Polimorfismo Genético/genética , Alelos , China , Feminino , Fentanila/farmacocinética , Genótipo , Humanos , Masculino , Pessoa de Meia-IdadeRESUMO
The effect of a novel hollow annular micro-hole electrode on the DBD de-NOx performance was investigated. The experimental results show that the hollow electrode allows the feed gas to take full advantage of the redundant heat of the electrode, thus reducing the energy consumption of the system. Subsequently, the micro-hole structure can improve the uniformity of feed gas in the plasma channel and prolong the residence time of the feed gas in the plasma channel. The reactor can also raise the temperature of the feed gas and enhance the plasma electric field. The optimum NOx removal efficiency of about 82.6% is achieved at 16 annular micro-holes. Compared to the rod electrode reactor, the novel electrode reactor shows 19.7% reduction in energy consumption and 13.2% enhancement in de-NOx efficiency. The calculations of de-NOx mechanism show that the NO2 concentration decays significantly as the feed gas residence time increases, accompanied by a slight increase in N2O concentration. The NO2 concentration marginally increases while N2O concentration slightly decreases as the increase of feed gas temperature. DBD de-NOx presents the mode of accelerated reduction of NO, essential removal of NO2, and gradual consumption of N2O with the reduced electric field increases.
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OBJECTIVE: Trauma is a leading cause of death worldwide, with many incidents resulting in hemorrhage before the patient reaches the hospital. Despite advances in trauma care, the majority of deaths occur within the first three hours of hospital admission, offering a very limited window for effective intervention. Unfortunately, a significant increase in mortality from hemorrhagic trauma is primarily due to delays in hemorrhage control. Therefore, we propose a machine learning model to predict the need for urgent hemorrhage intervention. METHODS: This study developed and validated an XGBoost-based machine learning model using data from the National Trauma Data Bank (NTDB) from 2017 to 2019. It focuses on demographic and clinical data from the initial hours following trauma for model training and validation, aiming to predict whether trauma patients require urgent hemorrhage intervention. RESULTS: The XGBoost model demonstrated superior performance across multiple datasets, achieving an AUROC of 0.872 on the training set, 0.869 on the internal validation set, and 0.875 on the external validation set. The model also showed high sensitivity (77.8% on the external validation set) and specificity (82.1% on the external validation set), with an accuracy exceeding 81% across all datasets, highlighting its high reliability for clinical applications. CONCLUSIONS: Our study shows that the XGBoost model effectively predicts urgent hemorrhage interventions using data from the National Trauma Data Bank (NTDB). It outperforms other machine learning algorithms in accuracy and robustness across various datasets. These results highlight machine learning's potential to improve emergency responses and decision-making in trauma care.