ABSTRACT
Tuojiang River Basin is a first-class tributary of the upper reaches of the Yangtze River-which is the longest river in China. As phytoplankton are sensitive indicators of trophic changes in water bodies, characterizing phytoplankton communities and their growth influencing factors in polluted urban rivers can provide new ideas for pollution control. Here, we used direct microscopic count and environmental DNA (eDNA) metabarcoding methods to investigate phytoplankton community structure in Tuojiang River Basin (Chengdu, Sichuan Province, China). The association between phytoplankton community structure and water environmental factors was evaluated by Mantel analysis. Additional environmental monitoring data were used to pinpoint major factors that influenced phytoplankton growth based on structural equation modeling. At the phylum level, the dominant phytoplankton taxa identified by the conventional microscopic method mainly belonged to Bacillariophyta, Chlorophyta, and Cyanophyta, in contrast with Chlorophyta, Dinophyceae, and Bacillariophyta identified by eDNA metabarcoding. In α-diversity analysis, eDNA metabarcoding detected greater species diversity and achieved higher precision than the microscopic method. Phytoplankton growth was largely limited by phosphorus based on the nitrogen-to-phosphorus ratios > 16:1 in all water samples. Redundancy analysis and structural equation modeling also confirmed that the nitrogen-to-phosphorus ratio was the principal factor influencing phytoplankton growth. The results could be useful for implementing comprehensive management of the river basin environment. It is recommended to control the discharge of point- and surface-source pollutants and the concentration of dissolved oxygen in areas with excessive nutrients (e.g., Jianyang-Ziyang). Algae monitoring techniques and removal strategies should be improved in 201 Hospital, Hongrihe Bridge and Colmar Town areas.
Subject(s)
Environmental Monitoring , Phytoplankton , Rivers , Rivers/chemistry , China , Water Pollutants, Chemical/analysis , Phosphorus/analysisABSTRACT
Bathymodioline mussels dominate deep-sea methane seep and hydrothermal vent habitats and obtain nutrients and energy primarily through chemosynthetic endosymbiotic bacteria in the bacteriocytes of their gill. However, the molecular mechanisms that orchestrate mussel host-symbiont interactions remain unclear. Here, we constructed a comprehensive cell atlas of the gill in the mussel Gigantidas platifrons from the South China Sea methane seeps (1100 m depth) using single-nucleus RNA-sequencing (snRNA-seq) and whole-mount in situ hybridisation. We identified 13 types of cells, including three previously unknown ones, and uncovered unknown tissue heterogeneity. Every cell type has a designated function in supporting the gill's structure and function, creating an optimal environment for chemosynthesis, and effectively acquiring nutrients from the endosymbiotic bacteria. Analysis of snRNA-seq of in situ transplanted mussels clearly showed the shifts in cell state in response to environmental oscillations. Our findings provide insight into the principles of host-symbiont interaction and the bivalves' environmental adaption mechanisms.
Subject(s)
Symbiosis , Animals , Gills/microbiology , Sequence Analysis, RNA/methods , Bivalvia/microbiology , Bivalvia/genetics , Mytilidae/genetics , Mytilidae/microbiology , Bacteria/geneticsABSTRACT
The prevalence of autism is increasing worldwide. The majority of autism research and development of autism assessments and interventions has been conducted in Western cultures. The prevalence of autism is reportedly lower in Asian versus Western cultures, but this is likely due to lack of personnel and uniform criteria for diagnosing autism. This article describes how two Asian cultures, Taiwan and Thailand, are dealing with the increasing identification of autistic children. National universal healthcare in both Taiwan and Thailand provides a mechanism for assessment and diagnosis of young children, but a lack of a sufficient number of trained professionals limits the availability of intervention services. A focus of research in these cultures has been on parents' experiences and coping with the stigma and stress of having an autistic child. Cultural values associated with Confucianism and Buddhism influence attitudes toward persons with disability and how parents of autistic children experience and cope with stigma and stress. Both areas have national laws that provide a range of educational opportunities for autistic children, including inclusion into general education classrooms. Special education and general education teachers, however, have little specific training in autism. Speech and language services are rarely offered in public school programs. Available speech and language services are limited to consultation with teachers a few times a year. In general, parents of autistic children are supportive of inclusion programs, but teachers and parents of both autistic and typically developing children express concerns about the ability to implement such programs in ways that are beneficial to all children.
ABSTRACT
Endosomal membrane trafficking is mediated by specific protein coats and formation of actin-rich membrane domains. The Retromer complex coordinates with sorting nexin (SNX) cargo adaptors including SNX27, and the SNX27-Retromer assembly interacts with the Wiskott-Aldrich syndrome protein and SCAR homolog (WASH) complex which nucleates actin filaments establishing the endosomal recycling domain. Crystal structures, modeling, biochemical, and cellular validation reveal how the FAM21 subunit of WASH interacts with both Retromer and SNX27. FAM21 binds the FERM domain of SNX27 using acidic-Asp-Leu-Phe (aDLF) motifs similar to those found in the SNX1 and SNX2 subunits of the ESCPE-1 complex. Overlapping FAM21 repeats and a specific Pro-Leu containing motif bind three distinct sites on Retromer involving both the VPS35 and VPS29 subunits. Mutation of the major VPS35-binding site does not prevent cargo recycling; however, it partially reduces endosomal WASH association indicating that a network of redundant interactions promote endosomal activity of the WASH complex. These studies establish the molecular basis for how SNX27-Retromer is coupled to the WASH complex via overlapping and multiplexed motif-based interactions required for the dynamic assembly of endosomal membrane recycling domains.
Subject(s)
Endosomes , Sorting Nexins , Vesicular Transport Proteins , Humans , Endosomes/metabolism , Sorting Nexins/metabolism , Sorting Nexins/genetics , Sorting Nexins/chemistry , Vesicular Transport Proteins/metabolism , Vesicular Transport Proteins/genetics , Vesicular Transport Proteins/chemistry , Microfilament Proteins/metabolism , Microfilament Proteins/genetics , Microfilament Proteins/chemistry , Protein Binding , Crystallography, X-Ray , Binding Sites , Models, MolecularABSTRACT
Accurate identifications of protein-peptide binding residues are essential for protein-peptide interactions and advancing drug discovery. To address this problem, extensive research efforts have been made to design more discriminative feature representations. However, extracting these explicit features usually depend on third-party tools, resulting in low computational efficacy and suffering from low predictive performance. In this study, we design an end-to-end deep learning-based method, E2EPep, for protein-peptide binding residue prediction using protein sequence only. E2EPep first employs and fine-tunes two state-of-the-art pre-trained protein language models that can extract two different high-latent feature representations from protein sequences relevant for protein structures and functions. A novel feature fusion module is then designed in E2EPep to fuse and optimize the above two feature representations of binding residues. In addition, we have also design E2EPep+, which integrates E2EPep and PepBCL models, to improve the prediction performance. Experimental results on two independent testing data sets demonstrate that E2EPep and E2EPep+ could achieve the average AUC values of 0.846 and 0.842 while achieving an average Matthew's correlation coefficient value that is significantly higher than that of existing most of sequence-based methods and comparable to that of the state-of-the-art structure-based predictors. Detailed data analysis shows that the primary strength of E2EPep lies in the effectiveness of feature representation using cross-attention mechanism to fuse the embeddings generated by two fine-tuned protein language models. The standalone package of E2EPep and E2EPep+ can be obtained at https://github.com/ckx259/E2EPep.git for academic use only.
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3D bioprinting with cell-laden materials is an emerging technique for fabricating functional tissue constructs. However, current cell-laden bioinks often lack sufficient cytocompatibility with commonly used UV-light sources. In this study, green to red photoinduced hydrogel crosslinking was obtained by introducing synthesized biosafety photoinitiators and used in light-based direct ink writing (DIW) 3D printing for enabling cell encapsulation successfully. The novel type II photointiators contain iodonium (ONI) and synthesized cyanine dyes CZBIN, TDPABIN, Col-SH-CZ, and Col-SH-TD with strong absorption in the range of 400-600â¯nm. Collagen-based macromolecule dyes Col-SH-CZ and Col-SH-TD showed excellent cytocompatibility. The photochemistry of these photoinitiators revealed an efficient photoinduced electron transfer (PET) process from the singlet excited states of the dyes to iodonium (ONI), facilitating the crosslinking of the biogels. L929 cells were encapsulated in Gel-MA hydrogels containing various photoinitiating systems and exposed to near-ultraviolet, green, or red LED irradiation. DIW-type 3D printing of Gel-MA bioink with L929 cells was also evaluated. The cell viability achieved with green light encapsulation reached 90â¯%. This novel approach offers promising prospects for bioprinting functional tissues with enhanced cytocompatibility under visible light conditions.
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Conjugated polymers (CPs), which emit in the second near-infrared window (NIR-II, 1000-1700 nm), are used as biomaterials for NIR-II fluorescence imaging because of their adjustable photophysical properties and high optical stability. However, the fluorescence signal of conventional CPs is quenched in an aggregated state due to strong π-π stacking, which results in the closure of the radiation attenuation pathway. To solve this problem, the aggregation-induced emission effect is considered a reasonable strategy for enhancing the aggregative fluorescence of IR-II emitters. We herein report NIR-II conjugated polymers with typical AIE characteristics (αAIE > 3) by changing the side chain structure of receptor units and the conjugation degree of donors. Conjugated polymer nanoparticles (PoBVT NPs) exhibit outstanding performance in NIR-II fluorescence imaging (QY = 1.94%) and highly effective photothermal therapy (η = 45%). In vivo studies have shown that the location of tumors can be accurately obtained by NIR-II FL/NIR-II PA imaging, and there is a significant anti-tumor effect after laser irradiation. This work offers prospects for the design of multifunctional conjugated polymers for NIR-II FL/PA imaging to guide NIR-II PTT applications.
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The introduction of heterogeneous components within one single coordination network leads to the multifunctionality of the final material. However, it is hard to precisely control the local distribution of these different components in such a coordination network, especially for different components with identical topological connectivity. In this study, we successfully achieved the ordered assembly of [Mn3(µ3-O)] nodes and [Mn6(µ3-O)2(CH3COO)3] nodes within one pacs coordination network. The resulting new structure (NPU-6) with heterogeneous metal nodes simultaneously inherits the advantages of both parent networks (good thermal stability and high pore volume). The significant effect of the reaction concentration of competing ligand CH3COO- on the mixed assembly of these two nodes in NPU-6 is revealed by a series of control experiments. This method is anticipated to offer a valuable reference for orderly assembling heterogeneous components in coordination networks.
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In situ polymerized 1,3-dioxolane (PDOL) is widely utilized to construct solid polymer electrolytes because of its high room-temperature ionic conductivity and good compatibility with lithium metal. However, the current polymerization additives used in PDOL do not effectively contribute to the formation of a robust solid electrolyte interphase (SEI), leading to decreased cycle life. Herein, a film-forming Lewis acid, tris(hexafluoroisopropyl) borate (THB), is demonstrated not only to be a catalyst for the ring-opening polymerization of DOL, but also an additive for the formation of a stable fluorine- and boron-rich SEI to improve the interfacial stability and suppress the Li dendrite growth. Moreover, molecular dynamics simulations and experimental results demonstrate that the introduction of THB can promote the dissociation of lithium salt and release more Li+ while the boron site can effectively restrict the free movement of TFSI- anion, thus increasing Li+ transference numbers (0.76) and ensuring the long-term cycling stability of cells. By using THB-PDOL, a stable cycling of LiâLi symmetric cell for 600 h at a capacity of 0.5 mA h cm-2 can be achieved. Furthermore, employing THB-PDOL in LiâLiFePO4 full cell enables a capacity retention of 98.64% after 300 cycles at 1C and a capacity retention of 95.39% after 200 cycles at a high temperature (60 °C). At the same time, this electrolyte is also suitable for the LiâNCM523 full cell, which also achieves excellent stability of more than 180 cycles. This film-forming Lewis acid additive provides ideas for designing low-cost, high-performance PDOL-based lithium metal batteries.
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The surface quality of milled blade-root grooves in industrial turbine blades significantly influences their mechanical properties. The surface texture reveals the interaction between the tool and the workpiece during the machining process, which plays a key role in determining the surface quality. In addition, there is a significant correlation between acoustic vibration signals and surface texture features. However, current research on surface quality is still relatively limited, and most considers only a single signal. In this paper, 160 sets of industrial field data were collected by multiple sensors to study the surface quality of a blade-root groove. A surface texture feature prediction method based on acoustic vibration signal fusion is proposed to evaluate the surface quality. Fast Fourier transform (FFT) is used to process the signal, and the clean and smooth features are extracted by combining wavelet denoising and multivariate smoothing denoising. At the same time, based on the gray-level co-occurrence matrix, the surface texture image features of different angles of the blade-root groove are extracted to describe the texture features. The fused acoustic vibration signal features are input, and the texture features are output to establish a texture feature prediction model. After predicting the texture features, the surface quality is evaluated by setting a threshold value. The threshold is selected based on all sample data, and the final judgment accuracy is 90%.
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Background: The long-term survival and perioperative outcomes of robotic-assisted lobectomy (RAL) and video-assisted lobectomy (VAL) in resectable non-small-cell lung cancer (NSCLC) were found to be comparable in retrospective studies, but they have not been investigated in a randomized trial setting. We conducted the RVlob trial to investigate if RAL was non-inferior to VAL in patients with resectable NSCLC. Methods: In this single-center, open-label, and parallel-arm randomized controlled trial conducted in Ruijin Hospital (Shanghai, China) between May 2017 and May 2020, we randomly assigned patients with resectable NSCLC in a 1:1 ratio to receive either RAL or VAL. One of the primary endpoints was 3-year overall survival. Secondary endpoints included 3-year disease-free survival. The Kaplan-Meier approach was used to calculate overall survival and disease-free survival at 3 years. This study was registered with ClinicalTrials.gov, NCT03134534. Findings: A total of 320 patients were randomized to receive RAL (n = 157) or VAL (n = 163). The baseline characteristics of patients were well balanced between the two groups. After a median follow-up of 58.0 months, the 3-year overall survival was 94.6% (95% confidence interval [CI], 91.0-98.3) in the RAL group and 91.5% (95% CI, 87.2-96.0) in the VAL group (hazard ratio [HR] for death, 0.65; 95% CI, 0.33-1.28; P = 0.21); noninferiority of RAL was confirmed according to the predefined margin of -5% (absolute difference, 2.96%; a one-sided 90% CI, -1.39% to ∞; P = 0.0029 for noninferiority). The 3-year disease-free survival was 88.7% (95% CI, 83.6-94.1) in the RAL group and 85.4% (95% CI, 80.0-91.2) in the VAL group (HR for disease recurrence or death, 0.87; 95% CI, 0.50-1.52; P = 0.62). Interpretation: This study is the first randomized trial to show that RAL resulted in non-inferior overall survival compared with VAL in patients with resectable NSCLC. Based on our results, RAL is an equally oncologically effective treatment and can be considered as an alternative to VAL for resectable NSCLC. Funding: National Natural Science Foundation of China (82072557), National Key Research and Development Program of China (2021YFC2500900), Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant (20172005, the 2nd round of disbursement), program of Shanghai Academic Research Leader from Science and Technology Commission of Shanghai Municipality (20XD1402300), Novel Interdisciplinary Research Project from Shanghai Municipal Health Commission (2022JC023), and Interdisciplinary Program of Shanghai Jiao Tong University (YG2023ZD04).
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The ability to recover tissue deformation from visual features is fundamental for many robotic surgery applications. This has been a long-standing research topic in computer vision, however, is still unsolved due to complex dynamics of soft tissues when being manipulated by surgical instruments. The ambiguous pixel correspondence caused by homogeneous texture makes achieving dense and accurate tissue tracking even more challenging. In this paper, we propose a novel self-supervised framework to recover tissue deformations from stereo surgical videos. Our approach integrates semantics, cross-frame motion flow, and long-range temporal dependencies to enable the recovered deformations to represent actual tissue dynamics. Moreover, we incorporate diffeomorphic mapping to regularize the warping field to be physically realistic. To comprehensively evaluate our method, we collected stereo surgical video clips containing three types of tissue manipulation (i.e., pushing, dissection and retraction) from two different types of surgeries (i.e., hemicolectomy and mesorectal excision). Our method has achieved impressive results in capturing deformation in 3D mesh, and generalized well across manipulations and surgeries. It also outperforms current state-of-the-art methods on non-rigid registration and optical flow estimation. To the best of our knowledge, this is the first work on self-supervised learning for dense tissue deformation modeling from stereo surgical videos. Our code will be released.
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Nearly four decades have passed since IBM scientists pioneered atomic force microscopy (AFM) by merging the principles of a scanning tunneling microscope with the features of a stylus profilometer. Today, electrical AFM modes are an indispensable asset within the semiconductor and nanotechnology industries, enabling the characterization and manipulation of electrical properties at the nanoscale. However, electrical AFM measurements suffer from reproducibility issues caused, for example, by surface contaminations, Joule heating, and hard-to-minimize tip drift and tilt. Using as experimental system nanoscale Schottky diodes assembled on oxide-free silicon crystals of precisely defined surface chemistry, it is revealed that voltage-dependent adhesion forces lead to significant rotation of the AFM platinum tip. The electrostatics-driven tip rotation causes a strain gradient on the silicon surface, which induces a flexoelectric reverse bias term. This directional flexoelectric internal-bias term adds to the external (instrumental) bias, causing both an increased diode leakage as well as a shift of the diode knee voltage to larger forward biases. These findings will aid the design and characterization of silicon-based devices, especially those that are deliberately operated under large strain or shear, such as in emerging energy harvesting technologies including Schottky-based triboelectric nanogenerators (TENGs).
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SHP2 plays a critical role in modulating tumor growth and PD-1-related signaling pathway, thereby serving as an attractive antitumor target. To date, no antitumor drugs targeting SHP2 have been approved, and hence, the search of SHP2 inhibitors with new chemical scaffolds is urgently needed. Herein, we developed a novel SHP2 allosteric inhibitor SDUY038 with a furanyl amide scaffold, demonstrating potent binding affinity (KD = 0.29 µM), enzymatic activity (IC50 = 1.2 µM) and similar binding interactions to SHP099. At the cellular level, SDUY038 exhibited pan-antitumor activity (IC50 = 7-24 µM) by suppressing pERK expression. Furthermore, SDUY038 significantly inhibited tumor growth in both xenograft and organoid models. Additionally, SDUY038 displayed acceptable bioavailability (F = 14%) and half-life time (t1/2 = 3.95 h). Conclusively, this study introduces the furanyl amide scaffold as a novel class of SHP2 allosteric inhibitors, offering promising lead compounds for further development of new antitumor therapies targeting SHP2.
Subject(s)
Amides , Antineoplastic Agents , Drug Design , Protein Tyrosine Phosphatase, Non-Receptor Type 11 , Protein Tyrosine Phosphatase, Non-Receptor Type 11/antagonists & inhibitors , Protein Tyrosine Phosphatase, Non-Receptor Type 11/metabolism , Humans , Antineoplastic Agents/pharmacology , Antineoplastic Agents/chemical synthesis , Antineoplastic Agents/chemistry , Animals , Allosteric Regulation/drug effects , Amides/pharmacology , Amides/chemistry , Amides/chemical synthesis , Mice , Cell Line, Tumor , Structure-Activity Relationship , Furans/pharmacology , Furans/chemistry , Furans/chemical synthesis , Xenograft Model Antitumor Assays , Enzyme Inhibitors/pharmacology , Enzyme Inhibitors/chemical synthesis , Enzyme Inhibitors/chemistry , Cell Proliferation/drug effects , Mice, NudeABSTRACT
In recent decades, there has been a growing interest in fully automated methods for tackling complex optimization problems across various fields. Active learning (AL) and its variant, assisted active learning (AAL), incorporating guidance or assistance from external sources into the learning process, play key roles in this automation by enabling the autonomous selection of optimal experimental conditions to efficiently explore the problem space. These approaches are particularly valuable in situations wherein experimentation is costly or time-consuming. This study explores the application of AAL in model-based method development (MD) for liquid chromatography (LC) by using Bayesian statistics to incorporate historical data and analyte information for the generation of initial retention models. The process involves updating the model parameters based on new experiments, coupled with an active data selection method to choose the most informative experiment to run in a subsequent step. This iterative process balances model exploitation and experimental exploration until a satisfactory separation is achieved. The effectiveness of this approach is demonstrated via two practical examples, resulting in optimized separations in a limited number of experiments by optimizing the gradient slope. It is shown that the ability of AAL to leverage past knowledge and compound information to improve accuracy and reduce experimental runs offers a flexible alternative approach to fixed design methods.
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Immune checkpoint blockade (ICB) immunotherapy remains hampered by insufficient immunogenicity and a high-lactate immunosuppressive tumor microenvironment (TME). Herein, a nanobody-engineered NIR-II nanoadjuvant with targeting metabolic reprogramming capability is constructed for potentiating NIR-II photothermal-ferroptosis immunotherapy. Specifically, the nanoadjuvant (2DG@FS-Nb) is prepared by metallic iron ion-mediated coordination self-assembly of D-A-D type NIR-II molecules and loading of glycolysis inhibitor, 2-deoxy-D-glucose (2DG), followed by modification with aPD-L1 nanobody (Nb), which can effectively target the immunosuppressive TME and trigger in situ immune checkpoint blockade. The nanoadjuvants responsively release therapeutic components in the acidic TME, enabling the precise tumor location by NIR-II fluorescence/photoacoustic imaging while initiating NIR-II photothermal-ferroptosis therapy. The remarkable NIR-II photothermal efficiency and elevated glutathione (GSH) depletion further sensitize ferroptosis to induce severe lipid peroxidation, provoking robust immunogenic cell death (ICD) to trigger anti-tumor immune response. Importantly, the released 2DG markedly inhibits lactate generation through glycolysis obstruction. Decreased lactate efflux remodels the immunosuppressive TME by suppressing M2 macrophage proliferation and downregulating regulatory T cell levels. This work provides a new paradigm for the integration of NIR-II phototheranostics and lactate metabolism regulation into a single nanoplatform for amplified anti-tumor immunotherapy combined with ICB therapy.
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Asthma is a common chronic lung disease, and COVID-19 pandemic as a respiratory viral disease led to lung infection and resulted in millions of deaths. So, the impact of COVID-19 on asthma outcomes and the risk of being infected or hospitalized should be clarified. Systematic review and meta-analysis on the outcomes and risk of asthma for people with COVID-19 was done by searching electronic databases between 1 December 2019 and 31 July 2023. A total of 48 studies from 27 countries spread across all continents were included in the review. The prevalence of asthma among COVID-19 patients was 7.9%, and the analysis demonstrated a 16.5% reduction in the risk ratio for acquiring COVID-19 among subjects with asthma compared to those without asthma. There was no statistically significant difference in hospitalization risk, ICU admission risk, and death risk for COVID-19 patients with no asthma compared to those with asthma. The risk of death from COVID-19 was similar between nonasthmatics and asthmatics. The findings indicated that subjects with asthma may be at a lower risk of having infection with COVID-19 compared to those without asthma, but they have a similar risk of hospitalization and mortality.
Subject(s)
Asthma , COVID-19 , Hospitalization , Humans , COVID-19/epidemiology , COVID-19/mortality , COVID-19/complications , Asthma/epidemiology , Hospitalization/statistics & numerical data , Prevalence , SARS-CoV-2ABSTRACT
Chiral spin textures, as exotic phases in magnetic materials, hold immense promise for revolutionizing logic, and memory applications. Recently, chiral spin textures have been observed in centrosymmetric magnetic insulators (FMI), due to an interfacial Dzyaloshinskii-Moriya interaction (iDMI). However, the source and origin of this iDMI remain enigmatic in magnetic insulator systems. Here, the source and origin of the iDMI in Pt/Y3Fe5O12 (YIG)/substrate structures are deeply delved by examining the spin-Hall topological Hall effect (SH-THE), an indication of chiral spin textures formed due to an iDMI. Through carefully modifying the interfacial chemical composition of Pt/YIG/substrate with a nonmagnetic Al3+ doping, the obvious dependence of SH-THE on the interfacial chemical composition for both the heavy metal (HM)/FMI and FMI/substrate interfaces is observed. The results reveal that both interfaces contribute to the strength of the iDMI, and the iDMI arises due to strong spin-orbit coupling and inversion symmetry breaking at both interfaces in HM/FMI/substrate. Importantly, it is shown that nonmagnetic substitution and interface engineering can significantly tune the SH-THE and iDMI in ferrimagnetic iron garnets. The approach offers a viable route to tailor the iDMI and associated chiral spin textures in low-damping insulating magnetic oxides, thus advancing the field of spintronics.
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Interfacial solar evaporation (ISE) holds considerable promise to solve fresh water shortage, but it is challenging to achieve high evaporation rate (Reva) and fresh water yield in close system. Here, we report design and preparation of MOF-based solar evaporators with hierarchical microporous/nanobridged/nanogranular structures for rapid ISE and fresh water collection in close system. The evaporators are fabricated by growing silicone nanofilaments with variable length as nanobridges on a microporous silicone sponge followed by grafting with polydopamine nanoparticles and Cu-MOF nanocrystals. Integration of the unique structure and excellent photothermal composites endows the evaporators with high Reva of 3.5-20 wt% brines (3.60-2.90 kg m-2 h-1 in open system and 2.38-1.44 kg m-2 h-1 in close system) under simulated 1 sun, high Reva under natural sunlight, excellent salt resistance and high fresh water yield, which surpass most state-of-the-art evaporators. Moreover, when combined with a superhydrophilic cover, the evaporators show much higher average Reva of real seawater, remarkable fresh water yield and excellent long-term stability over one month continuous ISE under natural sunlight. The findings here will promote the development of advanced evaporators via microstructure engineering and their real-world ISE applications.
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OBJECTIVES: To evaluate the predictive value of fasting plasma glucose (FPG) for in-hospital mortality in patients with acute myocardial infarction (AMI) with different glucose metabolism status. METHODS: We selected 5,308 participants with AMI from the prospective, nationwide, multicenter CAMI registry, of which 2,081 were diabetic and 3,227 were nondiabetic. Patients were divided into high FPG and low FPG groups according to the optimal cutoff values of FPG to predict in-hospital mortality for diabetic and nondiabetic cohorts, respectively. The primary endpoint was in-hospital mortality. RESULTS: Overall, 94 diabetic patients (4.5%) and 131 nondiabetic patients (4.1%) died during hospitalization, and the optimal FPG thresholds for predicting in-hospital death of the two cohorts were 13.2 mmol/L and 6.4 mmol/L, respectively. Compared with individuals who had low FPG, those with high FPG were significantly associated with higher in-hospital mortality in diabetic cohort (10.1% vs. 2.8%; odds ratio [OR] = 3.862, 95% confidence interval [CI]: 2.542-5.869) and nondiabetic cohort (7.4% vs. 1.7%; HR = 4.542, 95%CI: 3.041-6.782). After adjusting the potential confounders, this significant association was not changed. Furthermore, FPG as a continuous variable was positively associated with in-hospital mortality in single-variable and multivariable models regardless of diabetic status. Adding FPG to the original model showed a significant improvement in C-statistic and net reclassification in diabetic and nondiabetic cohorts. CONCLUSIONS: This large-scale registry indicated that there is a strong positive association between FPG and in-hospital mortality in AMI patients with and without diabetes. FPG might be useful to stratify patients with AMI.