Stepwise Strategy Research Articles

High furfural and levoglucosan selectivity from stepwise torrefaction and fast pyrolysis of sugarcane trash washed with citric acid

Converting agricultural waste biomass into value-added chemicals is attractive. However, a low selectivity for target chemicals hinders practical applications. This study presents a stepwise strategy to convert sugarcane trash (ST) into furfural and levoglucosan with high selectivity. The approach includes citric acid washing to reduce mineral content in ST, followed by torrefaction at different temperatures (210 °C, 250 °C and 290 °C) in a tube furnace and then fast pyrolysis at 500 °C in a micro-reactor. This study highlights the valorization potential of the torrefaction liquid, an often overlooked by-product from torrefaction, through significantly increasing furfural selectivity during the torrefaction of washed ST. Furthermore, the vapors from subsequent fast pyrolysis of washed-torrefied ST exhibited reduced acetic acid content compared to that of solely washed ST, which is advantageous for minimizing the acidity of the resulting bio-oil. Moreover, fast pyrolysis of ST, treated with washing and torrefaction at 250 °C, achieved a high levoglucosan yield while maintaining a high furfural yield obtained in the prior torrefaction step. The findings of this study provide valuable insights into future research and industrial applications in agricultural waste biomass utilization.

Cost-effectiveness of stepwise provisional versus systematic dual stenting strategies in patients with distal bifurcation left main stem lesions: economic analysis of the EBC MAIN trial

BackgroundIn patients with distal bifurcation left main stem lesions requiring intervention, the European Bifurcation Club Left Main Coronary Stent Study trial found a non-significant difference in major adverse cardiac events...

Comparison of Four Different Scoring Methods for Ki-67 Percentage in Breast Carcinoma: A Cross-sectional Study

Introduction: In breast cancer, the prognostic role of Ki-67 has been comprehensively studied, and its usefulness has been proven. Ki-67 expression has a prognostic and predictive value in both adjuvant therapy response and neoadjuvant settings. However, the inter and the intraobserver variability in manual counting limits the accuracy of scoring Ki-67 and consequently its application in treatment. Aim: To examine four different methods of Ki-67 estimation to find the most reliable, reproducible and time-efficient scoring methods for Ki-67. Materials and Methods: The present cross-sectional study was conducted in the Department of Pathology, Sree Mookambika Institute of Medical Sciences, Nagercoil, Tamil Nadu, India, from May 2023 to August 2023. Ki-67 immunostained slides of 30 trucut biopsies of invasive breast carcinoma were retrieved and analysed by two observers in a blinded manner. The four different methods of analysis of Ki-67 expression carried out were the global method, the hotspot method, the Eye-10 method and the stepwise counting strategy. The parameters included in the present study were the mean age of the study population, the pre/postmenopausal status, the histopathological type of invasive breast carcinoma, Estrogen receptor (ER), Progesterone Receptor (PR), and Human Epidermal growth factor Receptor 2 (HER2)/neu status, as well as, the interobserver agreement and the mean time taken by the four methods to analyse the Ki-67 expression. Data entry was performed using Microsoft Office Excel 2013, and statistical analysis was conducted using Statistical Package for the Social Sciences (SPSS) software version 20.0. Descriptive statistics for qualitative variables and mean and Standard Deviation (SD) for quantitative variables were used for data analysis. Chi-square tests were used for bivariate analysis with a determined statistical significance of 5% (p-value<0.05). Results: The mean age of the study population was 52.9±9.1 years. The highest interobserver concordance was observed among the observers using the weighted global scoring method, with an Interclass Correlation Coefficient (ICC) of 0.967. This method was time consuming, with the first observer taking a mean±SD time of 5.5±0.8 minutes and the second observer taking 4.6±0.9 minutes. The least time was consumed for performing the Eye-10 scoring, with mean±SD time was 1±0.87 minutes. The stepwise counting and hotspot method demonstrated excellent inter-rater agreement, with a kappa of 0.8304 (p-value<0.001) between both observers. Conclusion: Although the Eye-10 method and stepwise counting took the least time, they are limited by a gray/intermediate zone for scoring compared to the global scoring method and the hotspot method. As a result, the global and/or hotspot method after proper training is a robust and reliable method of assessing Ki-67, with the hotspot method being the most reliable, as the global method is limited by the use of an online tool.

Pediatric Orthopaedic Venous Thromboembolism: A Systematic Review Investigating Incidence, Risk Factors, and Outcome.

There is growing evidence of increased venous thromboembolism (VTE) incidence in children with trauma or infection. The purpose of this study was to conduct a systematic review of existing literature related to VTE in the pediatric orthopaedic population, to estimate the overall incidence of VTE and identify risk factors associated with this condition. A systematic review of the available literature was performed to identify articles that described VTE in pediatric orthopaedic surgery or admission. Literature queries were performed to identify articles published from 1980 to 2021 that included patients ≤21 years of age. A stepwise search strategy of 5 electronic databases yielded 1,426 articles, which were filtered by 2 reviewers to identify 30 articles for full-text review. The primary aim was to determine the rate of VTE, and the secondary aim was to identify risk factors for VTE. The pooled incidence of VTE was estimated and reported in cases per 10,000. Studies were stratified by study size, by trauma versus elective surgery, and by orthopaedic subspecialty. The 30 articles reported 3,113 VTE events in 2,467,764 pediatric patients (including those with non-orthopaedic conditions), for a pooled VTE incidence of 20 events (95% confidence interval [CI] = 10.8 to 37.2) per 10,000. Four of the studies were excluded for incomplete data or high heterogeneity. The remaining 26 studies had 850,268 orthopaedic patients with 1,108 cases of VTE, for a pooled VTE incidence of 16.6 events (95% CI = 9.1 to 30.5) per 10,000. Studies with <10,000 patients and those involving a diagnosis of trauma had the highest VTE incidence when stratification was performed. The most frequently analyzed risk factors in 15 available studies included age, sex, obesity/body mass index, type of surgery, and use of a central venous catheter. This systematic review indicated that the risk of VTE associated with pediatric orthopaedic surgery or admission remains low, at <17 events per 10,000 cases. However, orthopaedic surgeons should be aware of the most common risk factors associated with pediatric orthopaedic VTE and should pay special attention to traumatic etiologies, as these yielded the highest incidence. Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

A highly efficient Li–Cu/MoOx catalyst constructed by a precursor dispersion and alkali metal-promotion stepwise regulation strategy for the CO2 hydrogenation to methanol reaction

The hydrogenation of CO2 enables the production of high-value fuels and chemicals, contributing to a sustainable and environment-friendly energy transition.

A Stepwise Discriminant Analysis and FBCSP Feature Selection Strategy for EEG MI Recognition

A Stepwise Discriminant Analysis and FBCSP Feature Selection Strategy for EEG MI Recognition

Analytic Deep Learning and Stepwise Integrated Gradients-Based Power System Transient Stability Preventive Control

Trajectory sensitivity (TS) is a powerful alternative to linearize strong-nonlinear transient stability patterns. However, due to its incomplete view of an intact power system operational space, it can be readily to drive preventive control to stuck in local stationary solution. To mitigate this issue, an integrated gradient (IG)-based stepwise control method is proposed. The key idea is to develop IG to enable a control sensitivity taking both merits of local and global sensitivity, further help preventive control escape from local stationary points. Particularly, deep belief network (DBN) is firstly utilized to parameterize pattern between transient stability index (TSI) and steady-state dispatches. It is then leveraged to infer IG to linearize transient stability constraints in real-time. Interior point method is employed to solve the linearized model. A stepwise control strategy is finally proposed to adaptively tune the integrated interval of the applied IG, such that the preventive control path can be ensured to follow the trend of improving transient stability. Case studies on two benchmarks show that the proposed method outperforms traditional TS method in terms of efficiency and economy, and provides a promising way to enhance engineering sensitivity methods.

Polyvinyl alcohol/chitosan based nanocomposite organohydrogel flexible wearable strain sensors for sports monitoring and underwater communication rescue

Hydrogel-based flexible wearable sensors have garnered significant attention in recent years. However, the use of hydrogel, a biomaterial known for its high toughness, environmental friendliness, and frost resistance, poses a considerable challenge. In this study, we propose a stepwise construction and multiple non-covalent interaction matching strategy to successfully prepare dynamically physically crosslinked multifunctional conductive hydrogels. These hydrogels self-assembled to form a rigid crosslinked network through intermolecular hydrogen bonding and metal ion coordination chelation. Furthermore, the freeze-thawing process promoted the formation of poly(vinyl alcohol) microcrystalline domains within the amorphous hydrogel network system, resulting in exceptional mechanical properties, including a tensile strength (2.09 ± 0.01 MPa) and elongation at break of 562 ± 12 %. It can lift 10,000 times its own weight. Additionally, these hydrogels exhibit excellent resistance to swelling and maintain good toughness even at temperatures as low as −60 °C. As a wearable strain sensor with remarkable sensing ability (GF = 1.46), it can be effectively utilized in water and underwater environments. Moreover, it demonstrates excellent antimicrobial properties against Escherichia coli (Gram-negative bacteria). Leveraging its impressive sensing ability, we combine signal recognition with a deep learning model by incorporating Morse code for encryption and decryption, enabling information transmission.

Efficient Mycoprotein Production with Low CO2 Emissions through Metabolic Engineering and Fermentation Optimization of Fusarium venenatum.

The global protein shortage is intensifying, and promising means to ensure daily protein supply are desperately needed. The mycoprotein produced by Fusarium venenatum is a good alternative to animal/plant-derived protein. To comprehensively improve the mycoprotein synthesis, a stepwise strategy by blocking the byproduct ethanol synthesis and the gluconeogenesis pathway and by optimizing the fermentation medium was herein employed. Ultimately, compared to the wild-type strain, the synthesis rate, carbon conversion ratio, and protein content of mycoprotein produced from the engineered strain were increased by 57% (0.212 vs 0.135 g/L·h), 62% (0.351 vs 0.217 g/g), and 57% (61.9 vs 39.4%), respectively, accompanied by significant reductions in CO2 emissions. These results provide a referential strategy that could be useful for improving mycoprotein synthesis in other fungi; more importantly, the obtained high-mycoprotein-producing strain has the potential to promote the development of the edible protein industry and compensate for the gap in protein resources.

Engineering a synthetic energy-efficient formaldehyde assimilation cycle in Escherichia coli

One-carbon (C1) substrates, such as methanol or formate, are attractive feedstocks for circular bioeconomy. These substrates are typically converted into formaldehyde, serving as the entry point into metabolism. Here, we design an erythrulose monophosphate (EuMP) cycle for formaldehyde assimilation, leveraging a promiscuous dihydroxyacetone phosphate dependent aldolase as key enzyme. In silico modeling reveals that the cycle is highly energy-efficient, holding the potential for high bioproduct yields. Dissecting the EuMP into four modules, we use a stepwise strategy to demonstrate in vivo feasibility of the modules in E. coli sensor strains with sarcosine as formaldehyde source. From adaptive laboratory evolution for module integration, we identify key mutations enabling the accommodation of the EuMP reactions with endogenous metabolism. Overall, our study demonstrates the proof-of-concept for a highly efficient, new-to-nature formaldehyde assimilation pathway, opening a way for the development of a methylotrophic platform for a C1-fueled bioeconomy in the future.

A new adaptive multi-kernel relevance vector regression for structural reliability analysis

Surrogate models have been widely used in structural reliability analysis to improve the computational efficiency and the accuracy of failure probability. Recently, several multi-kernel relevance vector regression (MKRVR) models have been studied to evaluate the failure probability. However, existing multiple kernel functions for relevance vector regression models are fixed choices, which increases the number of calls to the limit state function (LSF) and leads to inaccurate results. To address the problem, this paper presents a new adaptive MKRVR model combined with Monte Carlo simulation (MCS). Firstly, a stepwise kernel selection strategy is developed to adaptively select better-performing kernel functions and eliminate redundant kernel functions for constructing the MKRVR model. Secondly, a new active learning function is proposed by considering the probability of mis-prediction and spatial locations of the existing sampling point to identify the new training sample points. Thirdly, a hybrid efficient stopping criterion is adopted to terminate the learning process automatically. Three benchmark examples and one practical engineering example are introduced to demonstrate the effectiveness of the proposed method. Results show that the proposed method can provide accurate failure probability by less number of calls to the LSF than existing fixed kernel-based methods.

Weak fault feature extraction of rolling bearing based on multi-system coupled cascaded stochastic resonance system

The accurate extraction of weak signal features under strong noise background plays a crucial role in the fault detection of rolling bearings. In order to promote the ability of stochastic resonance (SR) system to detect weak signals and improve the output performance of the system, a multi-system coupled cascaded SR (MCCSR) system is investigated and applied to the fault detection of rolling bearings. Firstly, a MCCSR system is constructed by exploiting the positive synergistic effect between multiple systems, which consists of a triangular-topology coupled system composed of three SR subsystems and a cascaded SR system with topology output as input. This system makes full use of the advantages of coupled system and cascaded system in weak signal detection. In terms of parameter optimization, a stepwise multi-parameter optimization strategy is proposed, which adopts different optimization methods for different parameters, and avoids the inconsistency between error and step factor by improving the least mean square algorithm. Finally, through the comparative analysis of numerical simulation and experimental signals, it is verified that the proposed method can effectively enhance the weak signal features and improve the system output signal-to-noise ratio, which can better serve for rolling bearing fault detection.

Multilevel Gradient-Ordered Silicon Anode with Unprecedented Sodium Storage.

While cost-effective sodium-ion batteries (SIBs) with crystalline silicon anodes promise high theoretical capacities, they perform poorly because silicon stores sodium ineffectively (capacity <40 mAh g-1 ). To address this issue, herein an atomic-order structural-design tactic is adopted for obtaining unique multilevel gradient-ordered silicon (MGO-Si) by simple electrochemical reconstruction. In situ-formed short-range-, medium-range-, and long-range-ordered structures construct a stable MGO-Si, which contributes to favorable Na-Si interaction and fast ion diffusion channels. These characteristics afford a high reversible capacity (352.7 mAh g-1 at 50mA g-1 ) and stable cycling performance (95.2% capacity retention after 4000 cycles), exhibiting record values among those reported for pure silicon electrodes. Sodium storage of MGO-Si involves an adsorption-intercalation mechanism, and a stepwise construction strategy of gradient-ordered structure further improves the specific capacity (339.5 mAh g-1 at 100mA g-1 ). Reconstructed Si/C composites show a high reversible capacity of 449.5 mAh g-1 , significantly better than most carbonaceous anodes. The universality of this design principle is demonstrated for other inert or low-capacity materials (micro-Si, SiO2 , SiC, graphite, and TiO2 ), boosting their capacities by 1.5-6 times that of pristine materials, thereby providing new solutions to facilitate sodium storage capability for better-performing battery designs.

Enhancing graphitization with desirable porosity for CO2 adsorption through a one-step strategy and a novel stepwise pyrolysis method from Terminalia boivinii tul tree dead leaves

The rising level of greenhouse gases in the atmosphere has led to concerns about climate change, making carbon dioxide (CO2) adsorption an increasingly important issue. Activated carbon-based materials with high surface area and porous structure have shown great potential for capturing CO2 from gas mixtures. In this study, we investigated the use of Terminalia boivinii tul tree dead leaves to synthesize activated carbon using a one-step strategy with KMnO4 and a novel stepwise pyrolysis strategy. We examined the effects of the stepwise pyrolysis strategy on carbon structure and CO2 adsorption and used X-ray diffraction (XRD) to analyze the degree of crystallinity and structural orientation of the synthesized activated carbon samples. The results of the XRD analysis showed that the HAC_850S sample exhibited higher intensity in the (002) plane than the HAC_850 sample, indicating a higher degree of crystallinity and suggesting that the sample treated with the step-wise pyrolysis strategy exhibited a more ordered carbon structure. This finding suggests that the use of waste biomass as feedstock to produce activated carbon using one-step KMnO4-assisted synthesis and step-wise pyrolysis can lead to the production of high-quality graphitized materials with desirable porosity and surface area suitable for CO2 adsorption. The study's results revealed that the sample treated by the HAC_850S process exhibited the highest CO2 adsorption capacity of approximately 41 mg/g, while the HAC_850 and PP_350 pyrolysis samples had adsorption capacities of around 36 mg/g and 30 mg/g, respectively. The findings suggest that the development of cost-effective and scalable methods to produce activated carbon for CO2 capture is possible, and the study's results contribute to the development of new technology and solutions capable of addressing the challenges associated with climate change.

Multi-view feature fusion and density-based minority over-sampling technique for amyloid protein prediction under imbalanced data

Amyloid fibers formed by the aggregation of amyloid proteins can lead to various neurological diseases. Accurate prediction of amyloid proteins can provide scientific basis for exploring the pathogenesis of related neurological diseases, and developing targeted treatment plans. In view of the limitations of the synthetic minority over-sampling technique (SMOTE), an improved SMOTE method based on density clustering is proposed in this paper, and combined with multi-view features to construct an amyloid protein prediction model. The benefits of this enhanced SMOTE method include eliminating problematic samples, accomplishing an evenly distributed minority sample pool, and utilizing all available boundary sample information. Compared with other over-sampling methods, this method can effectively improve the authenticity and representativeness of the synthesized samples, and has a strong ability to process imbalanced data. After the dataset is over-sampling, different prediction algorithms are trained respectively to construct the baseline models. To fully characterize proteins, the probability and category features are extracted from the baseline models and combined with the sequence features selected by CFS-GSSS (Correlation-based Feature Selection Combined with Greedy Stepwise Search Strategy) to generate the multi-view features. Experimental results demonstrate the complementarity and feasibility of the multi-view features. On the independent test set, compared with the existing best model (ECAmyloid), the proposed amyloid protein prediction model improved the sensitivity and geometric mean by 0.0706 and 0.0129, respectively, far superior to other existing methods.

Stepwise Synthesis of Cl-Decorated Trinuclear-Cu Cluster-Based Frameworks for C2H2/C2H4 and C2H2/CO2 Separation.

A novel Cl-decorated trinuclear-Cu cluster-based MOF (NbU-7-Cl, NbU denotes Ningbo University) was synthesized by a stepwise synthesis strategy. Compared to one-step reactions, the strategy of combining cationic templates with single-crystal-to-single-crystal transformation provides more possibilities for the design and postsynthetic modification of multifunctional materials. Note that the chloride ions are attached to the copper ions of the planar trinuclear cluster nodes in a fully symmetric or partially asymmetric manner. The insertion of the chloride ion can alter the overall symmetry and adsorption energy in addition to occupying the appropriate asymmetric orbit and reducing the effective active sites of metal. The activated NbU-7-Cl displays improved C2H2 uptake capacity and C2H2/C2H4 and C2H2/CO2 separation performance, which is proved by breakthrough experiments.

Hand-held echocardiography-based heart failure screening in hypertensive or diabetic patients in community: a pilot study

Abstract Background There is lack of solid data on screening methods for preclinical heart failure (HF) in primary care settings. Standard echocardiography is not regarded as a routine test due to high cost and need of operation by specialists. Hand-held echocardiography (HHE) has been used in various clinical settings with easier access and lower price but has never been integrated into HF screening programme. Purpose This study aimed to explore the feasibility and cost-effectiveness of hand HHE-based HF screening strategies in patients with risk factors in community. Methods The registered patients with hypertension or diabetes at two Chinese community health service centres (CHSCs) who had not been diagnosed previously as HF were recruited. Every patient received symptom assessment (dyspnea and/or lower limb edema), blood test for N-terminal-probrain natriuretic peptide (NT-proBNP ≥ 125 pg/ml regarded as positive), and HHE for any indexed abnormality in the dedicated protocol with focused and semiquantitative scanning [i.e. left ventricular (LV) dilation, left atrial (LA) dilation, interventricular septum (IVS) thickening, LV systolic dysfunction by calipers, as well as region wall motion abnormality, valvular stenosis, ≥moderate valvular regurgitation, significant pericardial effusion by eyeballing). By using the results of all the three modalities for screening compared to the concurrent guidelines, the patients were categorized into HF stages A, B, or C as the "gold standard". Three screening strategies were proposed (Figure 1), of which Strategy I was designed as a single test, Strategy II as a combined test, and Strategy III as a stratified stepwise test. Diagnostic accuracy and cost-effectiveness of each strategy was calculated in comparison with the "gold standard". Results A total of 423 patients (70 ± 9 years; 46.6% males) were enrolled. There were 166 (39.2%) symptomatic patients, while 106 (25.1%) patients had elevated NT-proBNP. HHE abnormalities were found in 286 (67.0%) patients, of which IVS thickening was the most common finding (47.0%), followed by LA enlargement (30.0%). LV systolic dysfunction was identified in 18 (4.3%) patients. 232 (54.8%) and 59 (13.9%) patients were reclassified as HF stage B and C, respectively. As shown in Figure 2, the stepwise Strategy III of using symptoms for the first stratification, followed by choosing HHE or NT-proBNP test led to a 100% accuracy and a 35.6% reduction in cost. Conclusions HHE-based focused screening detects HF earlier in high-risk populations. The screening strategy combined with symptoms, NT-proBNP, and HHE is feasible for identifying underdiagnosed HF stage B or C that may be considered in primary care.Scheme of HF stage screening strategiesHF Screening and cost-effectiveness

The effect of implementing a guideline-based approach to achieve target LDL-C levels in very high risk patients. The PENELOPE study one year follow-up results

Abstract Background/introduction Hyperlipidemia is a major modifiable risk factor for developing cardiovascular disease. Lowering LDL-C reduces the risk for coronary heart disease (1,2). The PENELOPE study implemented an ESC-guideline-based, stepwise strategy of lipid-lowering therapy (LLT) to achieve target LDL-C levels in very high-risk patients, with a mean duration of 61 days. Purpose This paper demonstrates the legacy effect after one year. Methods Nine hundred and ninety-nine (999) patients with a myocardial infarction and a history of atherosclerotic cardiovascular disease and/or diabetes mellitus were included in PENELOPE for stepwise intensified LLT (high intensity statin (HIST) monotherapy, HIST + ezetimibe, HIST + ezetimibe + PCSK9i) until reaching target LDL-C level (≤1.8mmol/L). The primary objective was to assess the prevalence of maintained LDL-C ≤1.8 mmol/L and therapy-adherence after one year. Results For the one year follow up visit, 738 patients (73%) were available. Thirty patients had died, 45 were lost to follow up and from 178 patients no signed informed reconsent was obtained. The per protocol cohort included six hundred and seventy-one (671) patients. In this cohort, a non-participation bias cannot be excluded. After one year, in four-hundred forty-nine (449) patients target LDL-C level (66,9%) was maintained. Mean LDL-C level after one year was 1.67 mmol/L and the adherence rate to LLT was 94,5%. The major treatment regimens were statin monotherapy (61,7%), statin + ezetimibe (28,3%) and PCK9i + ezetimibe (+ statin) (5,8%). Maintained target (LDL-C ≤1.8mmol/L) was 64%, 77% and 82%, respectively. The large percentage loss of patients on target after one year could be explained by the cut-off at 1.8 mmol/L (only 0.28 mmol/L increase in mean LDL-C level), the short-term effect of heart rehabilitation and a treatment change in 20,4% of patients. Therapy adherence was high and did not differ between treatment regimen. Conclusion Using an ESC-guideline-based flowchart with quick, stepwise intensification of LLT leads to a 99% success rate (LDL-C ≤1.8mmol/L) within 3 months and 67% after one year. The mean LDL-C level increases with 0.28 mmol/L.

Abstract 17378: A Novel Strategy in the Sequencing of HFrEF Therapy: An Upfront and Prompt Approach

Introduction: The latest HF European guidelines recommend the use of four different classes of drugs for HFrEF. Despite advances in treatment, some gaps remain to be filled. In particular, sequencing and timing of HF therapy administration are not clarified and different strategies have been proposed. Hypothesis: An early, upfront novel approach, based on prompt administration of BB, SGLT2i, ACEi/ARNI, and MRAs may prove beneficial in terms of HF rehospitalization and CV death risk reduction. Aims: To compare early sequencing of HFrEF GDMT with the conventional, stepwise strategy. The primary endpoint was a composite of HF rehospitalization and CV death. Secondary endpoints were the single events of the primary endpoint. Methods: This prospective, observational study included consecutive patients with a HFrEF diagnosis from the Cardiology department. They were divided based on treatment strategy. Group 1 (G1) was treated with a novel GDMT sequencing (in-hospital start of BB and SGLT2i, ACE-i/ARNI, and lastly adding MRAs within 30 days from discharge). Group 2 (G2) was treated with the conventional, stepwise GDMT sequencing. Comparison between the two groups has been performed at 6-month follow up. Results: The study included a total of 302 patients. 278 patients underwent follow up: 139 in G1 group and 139 in G2 group. The two groups did not show significant differences at baseline. No significant differences have been observed for the primary composite outcome (p= 0.135) and for CV mortality (p=0.642) between the two groups. HF rehospitalization risk was significantly lower in G1 group compared to G2 group (p&lt;0.001). Conclusions: HFrEF patients treated with a novel GDMT sequencing, promptly initiated and completed within 30 days from discharge, have shown reduced risk of HF rehospitalization compared with the conventional strategy.

Hybrid Integration of Au Nanoplates and Ag Nanoparticles with Controlled Nanogaps via Cu2O‐mediated Galvanic Replacement Reaction: Plasmonic Catalysis and Photothermal Conversion

AbstractRational assembling of different noble metal nanocrystals with controlled nanogaps in one entity allows the efficient coupling of electromagnetic fields of each component and versatile manipulation over the overall physiochemical properties. In the present study, we report a stepwise synthetic strategy to hybridlike assemble Au nanoplate and Ag nanoparticles without direct physical contact. Particularly, the success of current work relies on the conformal coating of Cu2O over the Au nanoplate as an intermediate layer, followed by the in situ formation of Ag nanoparticles via the galvanic replacement reaction between Cu2O and Ag+. With the anchoring of Ag nanoparticles over the Cu2O‐wrapped Au nanoplate, the resulting hybrid nanostructures exhibit noticeable multiple plasmonic absorptions across the UV‐vis‐NIR region. The potential use as the plasmonic catalyst for current Au@Cu2O‐Ag hybrid products is validated using reduction of 4‐nitrophenol as the model reaction, where the catalytic performance is greatly improved by the UV‐vis light irradiation. They also exhibit satisfactory photothermal conversion performance under the irradiation of Xe lamp. The current work provides a niche strategy to create noble‐metal hybrid nanostructures with controlled interparticle distance and tunable plasmonic properties, could be extended to other noble metal or alloys.