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This document is an editorial for a special issue of the journal "Remote Sensing" that focuses on monitoring terrestrial water resources using satellite sensors. The editorial acknowledges the increasing demand for water resources and the importance of accurately evaluating and tracking them. It discusses the advantages of using satellite technologies for monitoring water resources and highlights studies in the special issue that cover topics such as water body extraction, flood mapping, and coastal wetland dynamics monitoring. The editorial also mentions the use of specific satellite sensors, like satellite altimeters and satellite imagery, for acquiring surface water information. It addresses the challenges of acquiring 3D information about surface water and emphasizes the need to combine satellite observation with model simulation to improve monitoring and understanding of the water cycle. The authors suggest incorporating newly released satellite data, such as SWOT, to enhance the acquisition of information on inland areas, coastal areas, and oceans. [Extracted from the article]

Brown carbon (BrC) exhibits a highly complex chemical composition with diverse light‐absorbing properties, which complicates our understanding of its climate impacts. This study examined the impact of molecular characteristics (including molecular mass, unsaturation, oxidation state, and polarity) and heteroatoms on the light‐absorbing properties (absorptivity and wavelength dependence) of BrC from a molecular perspective, based on the ultraviolet‐visible spectra of over 40,000 light‐absorbing substances in aerosol from different sources and ambience. Our findings reveal that the light‐absorptivity of BrC molecules increases with decreasing polarity and O/C ratio, while it rises with higher molecular mass and unsaturation. We developed predictive models for molecular absorptivity based on its double bond equivalent and O/C ratio. In addition, we observed an inverse correlation between absorptivity and wavelength dependence at the molecular level, as determined through mathematical analysis. This molecular‐level understanding provides valuable insights into BrC absorbing mechanisms, facilitating more accurate characterization in atmospheric models. Plain Language Summary: Brown carbon (BrC) plays a crucial role in global climate and air quality. However, extremely complex chemical composition with diverse optical properties in organic aerosols leads to a great variety of BrC in different atmospheric environments, which brings challenges for accurate representation in atmospheric models. This study investigates factors influencing light‐absorbing properties of BrC from a molecular perspective. Our study indicates that the diversity in BrC properties across different environment is an integrated result of variations in molecular mass, unsaturation and oxidation state, all of which should be taken into account. Additionally, it's not accurate to simply label organic aerosol molecules as either absorbing or non‐absorbing. Instead, this study proposes a method to continuously predict the absorption capacity of BrC molecules. Furthermore, we also noticed that as the ability of molecules to absorb light increases, their dependency on wavelength decreases, a relationship we identified and explained using mathematical equations at the molecular level. Key Points: The rising absorptivity of brown carbon (BrC) is an integrated result of lower polarity or O/C ratio, and higher molecular mass or unsaturationThe absorptivity of molecules in BrC can be predicted with double bond equivalent and O/C ratioAn inverse correlation between absorptivity and wavelength dependence is observed and mathematically derived at the molecular level [ABSTRACT FROM AUTHOR]

Background: N4-acetylcytidine (ac4C) is a conserved and abundant mRNA modification that controls protein expression by affecting translation efficiency and mRNA stability. Whether the ac4C modification of mRNA regulates hepatocellular carcinoma (HCC) development or affects the immunotherapy of HCC is unknown. Methods: By constructing an orthotopic transplantation mouse HCC model and isolating tumour-infiltrated immunocytes, we evaluated the ac4C modification intensity using flow cytometry. Remodelin hydrobromide (REM), an ac4C modification inhibitor, was systematically used to understand the extensive role of ac4C modification in immunocyte phenotypes. Single-cell RNA-seq was performed to comprehensively evaluate the changes in the tumour-infiltrating immunocytes and identify targeted cell clusters. RNA-seq and RIP-seq analyses were performed to elucidate the underlying molecular mechanisms. Tyramide Signal Amplification (TSA) analysis on the HCC tissue microarray was performed to explore the clinical relatedness of our findings. Results: Ac4C modification promoted M1 macrophage infiltration and reduced myeloid-derived suppressor cell MDSCs infiltration in HCC. The inhibition of ac4C modification induces PDL1 expression by stabilising mRNA in the myeloid cells, thereby attenuating the CTL-mediated tumour cell-killing ability. High infiltration of ac4C+CD11b+ cells is positively related to a better prognosis in patients with HCC. Conclusions: Ac4C modification of myeloid cells enhanced the HCC immunotherapy by suppressing PDL1 expression. [ABSTRACT FROM AUTHOR]

Diabetes mellitus (DM) is one of the most prevalent metabolic disorders that poses a global threat to human health. It can lead to complications in multiple organs and tissues, owing to its wide-ranging impact on the human body. Diabetic cardiomyopathy (DCM) is a specific cardiac manifestation of DM, which is characterized by heart failure in the absence of coronary heart disease, hypertension and valvular heart disease. Given that oxidative stress is a key factor in the pathogenesis of DCM, intervening to mitigate oxidative stress may serve as a therapeutic strategy for managing DCM. Naringenin is a natural product with anti-oxidative stress properties that can suppress oxidative damage by regulating various oxidative stress signaling pathways. In this review, we address the relationship between oxidative stress and its primary signaling pathways implicated in DCM, and explores the therapeutic potential of naringenin in DCM. [ABSTRACT FROM AUTHOR]

Microorganism-based methods have been widely applied for the treatment of phenol-polluted environments. The previously isolated Acinetobacter lwoffii NL1 strain could completely degrade 0.5 g/L phenol within 12 h, but not higher concentrations of phenol. In this study, we developed an evolutionary strain NL115, through adaptive laboratory evolution, which possessed improved degradation ability and was able to degrade 1.5 g/L phenol within 12 h. Compared with that of the starting strain NL1, the concentration of degradable phenol by the developed strain increased three-fold; its phenol tolerance was also enhanced. Furthermore, comparative genomics showed that sense mutations mainly occurred in genes encoding alkyl hydroperoxide reductase, phenol hydroxylase, 30S ribosomal protein, and mercury resistance operon. Comparative transcriptomics between A. lwoffii NL115 and NL1 revealed the enrichment of direct degradation, stress resistance, and vital activity processes among the metabolic responses of A. lwoffii adapted to phenol stress. Among these, all the upregulated genes (log2fold-change > 5) encoded peroxidases. A phenotypic comparison of A. lwoffii NL1 and NL115 found that the adapted strain NL115 exhibited strengthened antioxidant capacity. Furthermore, the increased enzymatic activities of phenol hydroxylase and alkyl hydroperoxide reductase in A. lwoffii NL115 validated their response to phenol. Overall, this study provides insight into the mechanism of efficient phenol degradation through adaptive microbial evolution and can help to drive improvements in phenol bioremediation. [ABSTRACT FROM AUTHOR]

In order to enhance the detection and parameter estimation capacity to the maneuvering target with complex motions, a low complexity coherent integration and parameter estimation method named SOKT-IAR-LVD is proposed in this paper. In SOKT-IAR-LVD, first, the second-order keystone transform (SOKT) is utilized to eliminate the range curvature induced by target acceleration. Second, improved axis rotation (IAR) is applied to regulate the linear range migration by rotating the fast time axis and the target envelope is aligned along the slow time axis with a quadratic phase characteristic. At last, the target signal is coherently integrated via the Lv's Distribution (LVD) transform. The target motion parameters, including range, velocity, and acceleration, are estimated by the IAR and LVD results. The integration gain and computational load of SOKT-IAR-LVD are analyzed. Without needing to estimate the Doppler ambiguity number and target acceleration, the computational burden of SOKT-IAR-LVD is three orders of magnitude lower than that of the Radon-Lv's Distribution (RLVD) method. Simulation results demonstrate that the detection performance of SOKT-IAR-LVD is almost the same as that of RLVD and that the required input SNR of SOKT-IAR-LVD is 17.4 dB lower than that of SOKT–Radon Fourier transform (SOKT-RFT) when the detection threshold is set to 12 dB. [ABSTRACT FROM AUTHOR]

One effective strategy to solve the existing limits of photocatalyst applications is to broaden the spectrum absorption range of catalysts for the degradation and conversion of microplastics. As a result, a brand-new composite system BN/PDA/MoS 2 (BPM) was developed in this work to form nanofluids for the degradation and reformation of fiber-based microplastics (FMPs) under the irradiation of near-infrared light (NIR) for the first time. The collaborative system BPM nanofluids/NIR could remove 94.7% and 95.2% of reactive blue KN-R (100 mg/L) and Cr (VI) (10 mg/L) within 60 min, along with the temperature of the system could reach 58°C within 30 min. The weight loss rates of FMPs like PET and PLA were 92% and 34%, respectively after undergoing molecular chain breakage to form a series of small molecules in the system. Moreover, the H 2 production maintained an improvement to 100 mmol g−1 (PET) as well as 160 mmol g−1 (PLA) compared to the past research. In conclusion, this work is an effective attempt to develop a new method for water treatment based on the photothermal degradation of microplastics by BPM nanofluids, which also bears new ideas and ways for industrial pollutant removal and waste utilization. [Display omitted] [ABSTRACT FROM AUTHOR]

Background: Exploring the association of diet and indoor and outdoor environments on the gut microbiome of red-crowned cranes. We investigated the microbiome profile of the 24 fecal samples collected from nine cranes from day 1 to 35. Differences in the gut microbiome composition were compared across diet and environments. Results: A total of 2,883 operational taxonomic units (OTUs) were detected, with 438 species-specific OTUs and 106 OTUs common to the gut microbiomes of four groups. The abundance of Dietzia and Clostridium XI increased significantly when the red-crowned cranes were initially fed live mealworms. Skermanella and Deinococcus increased after the red-crowned cranes were fed fruits and vegetables and placed outdoors. Thirty-three level II pathway categories were predicted. Our study revealed the mechanism by which the gut microbiota of red-crowned cranes responds to dietary and environmental changes, laying a foundation for future breeding, nutritional and physiological studies of this species. Conclusions: The gut microbiome of red-crowned cranes could adapt to changes in diet and environment, but the proportion of live mealworms in captive red-crowned cranes can be appropriately reduced at the initial feeding stage, reducing the negative impact of high-protein and high-fat foods on the gut microbiome and growth and development. [ABSTRACT FROM AUTHOR]

[Display omitted] • A brand-new composite catalyst ZnFe 2 O 4 /Fe 3 O 4 @MWCNTs along with persulfate activation was established under near infrared radiation. • Temperature rising makes sure the synergistic system was of superior degradation and recycling performance for dyes (95%) and antibiotics (94.6%) in just 60 min than that of past research. • Persulfate adsorption on the surface and the theoretical kinetic constants calculated by DFT along with pathway analysis and toxicological properties of ampicillin degradation added to its industrial application. • This work bears certain efficacious research directions for water treatment technology. One of the most effective ways to address the problems of low solar spectrum utilization in photocatalysis and the high cost of persulfate activation technology is to create a cost-effective synergistic photothermal persulfate system. In this work, a brand-new composite catalyst called ZnFe 2 O 4 /Fe 3 O 4 @MWCNTs (ZFC) was developed to activate PDS (K 2 S 2 O 8) from the aforementioned basis. ZFC's surface temperature could unbelievably reach 120.6 °C in 150 s together with the degrading synergistic system solution temperature could reach 48 °C under near-infrared light (NIR) in 30 min, thus accelerating the ZFC/PDS decolorization rate for reactive blue KN-R (150 mg/L) to 95% in 60 min. Furthermore, the ZFC's ferromagnetism bore it with good cycling performance, allowing it to maintain an 85% decolorization rate even after 5 cycles with OH·, SO 4 -·, 1O 2 , and O 2 –· dominating the degrading process. In the meantime, the DFT calculations of the kinetic constants for the entire process of S 2 O 8 2- adsorption on Fe 3 O 4 in dye degradation solution were in agreement with the outcomes of the experimental pseudo-first-order kinetic fitting. By analyzing the particular degradation route of ampicillin (50 mg/L) and the possible environmental impact of the intermediate using LC-MS and the toxicological analysis software (T.E.S.T.), respectively, it was shown that this system might function as an environmentally friendly method for removing antibiotics. This work may provide some productive research lines for the creation of a photothermal persulfate synergistic system and suggest fresh approaches to water treatment technology. [ABSTRACT FROM AUTHOR]

Pavement skid resistance measurement is a fundamental component of roadway management and maintenance. Most traditional approaches rely on manual operations or heavy devices, which lead to a labor‐intensive, inefficient, and vulnerable testing environment. Precise laser scanning technology lays a solid foundation for effective and continuous pavement friction measurement. This paper proposed an automated pavement friction estimation model using 3D point cloud data and a deep neural network. The fine‐grained texture data of over 800 pavement sections with various anti‐skidding abilities were collected. The impact of the multi‐scale textures on pavement friction was separated and analyzed via two‐dimensional wavelet decomposition. A multi‐input fusion network with deep aggregation modules was designed to fuse the features of sub‐images generated by wavelet decomposition. The results show that the average prediction error is 0.0935, outperforming most state‐of‐the‐art models. The impact of different texture scales on friction estimation is then revealed. The proposed method provides a new tool for effective and large‐scale pavement friction evaluation. [ABSTRACT FROM AUTHOR]

Background: The objective of this study was to evaluate the association between red cell distribution width/platelet ratio (RPR) and 30-day and 1-year mortality in acute ischemic stroke (AIS). Methods: Data for the retrospective cohort study were collected from the Medical Information Mart for Intensive Care (MIMIC) III database. RPR was divided into two groups: RPR ≤ 0.11 and RPR > 0.11. The study outcomes were 30-day mortality and 1-year mortality from AIS. Cox proportional hazard models were utilized to assess the association between RPR and mortality. Subgroup analyses were applied based on age, tissue-type plasminogen activator (IV-tPA), endovascular treatment, and myocardial infarction. Results: A total of 1,358 patients were included in the study. Short- and long-term mortality occurred in 375 (27.61%) and 560 (41.24%) AIS patients, respectively. A high RPR was significantly associated with increased 30-day [hazard ratio (HR): 1.45, 95% confidence interval (CI): 1.10 to 1.92, P = 0.009] and 1-year mortality (HR: 1.54, 95%CI: 1.23 to 1.93, P < 0.001) in AIS patients. Meanwhile, RPR was found to be significantly related to 30-day mortality in AIS patients aged < 65 years (HR: 2.19, 95% CI: 1.17 to 4.10, P = 0.014), without IV-tPA use (HR: 1.42, 95% CI: 1.05 to 1.90, P = 0.021), without using endovascular treatment (HR: 1.45, 95% CI: 1.08 to 1.94, P = 0.012), and without myocardial infarction (HR: 1.54, 95% CI: 1.13 to 2.10, P = 0.006). Additionally, RPR was associated with 1-year mortality in AIS patients aged < 65 years (HR: 2.54, 95% CI: 1.56 to 4.14, P < 0.001), aged ≥ 65 years (HR: 1.38, 95% CI: 1.06 to 1.19, P = 0.015), with (HR: 1.46, 95% CI: 1.15 to 1.85, P = 0.002) and without using IV-tPA (HR: 2.30, 95% CI: 1.03 to 5.11, P = 0.041), without using endovascular treatment (HR: 1.56, 95% CI: 1.23 to 1.96, P < 0.001), and without myocardial infarction (HR: 1.68, 95% CI: 1.31 to 2.15, P < 0.001). Conclusion: Elevated RPR is associated with a high risk of short-term and long-term mortality in AIS. [ABSTRACT FROM AUTHOR]

(1) Objective: Traditional Chinese medicine (TCM) plays an important role in the treatment of numerous illnesses. As a classic Chinese medicine, Wendan Decoction (WDD) encompasses a marvelous impact on the remedy of hyperlipidemia. It is known that hyperlipidemia leads to cardiovascular injury, therefore anti-vascular endothelial cell injury (AVECI) may be an underlying molecular mechanism of WDD in the cure of hyperlipidemia. However, there is no relevant research on the effect of WDD on vascular endothelial cells and its pharmacodynamic substances. Therefore, the purpose of this study was to investigate the protective effect of WDD on vascular endothelial cells. (2) Methods: The chemical constituents of WDD were determined by LC-MS/MS technology. The protective effects of 16 batches of WDD on samples from human umbilical vein endothelial cells (HUVECs) were evaluated. Finally, gray relation analysis (GRA) and partial least squares regression (PLSR) were used to analyze the potential correlation between chemical ingredients and AVECI. (3) Results: The results indicated that WDD had apparent protective effect on endothelial cells, and pharmacological properties in 16 batches of WDD tests were apparently discrepant. The GRA and PLSR showed that trigonelline, liquiritin, hesperidin, hesperetin, scopoletin, morin, quercetin, isoliquiritigenin, liquiritigenin and formononetin may be the active ingredients of AVECI in WDD. (4) Conclusions: WDD has a protective effect on endothelial cell injury induced by palmitic acid, which may be related to its component content. This method was suitable for the search of active components in classical TCM. [ABSTRACT FROM AUTHOR]

Short hairpin RNA (shRNA)-mediated gene silencing is an important technology to achieve RNA interference, in which the design of potent and reliable shRNA molecules plays a crucial role. However, efficient shRNA target selection through biological technology is expensive and time consuming. Hence, it is crucial to develop a more precise and efficient computational method to design potent and reliable shRNA molecules. In this work, we present an interpretable classification model for the shRNA target prediction using the Light Gradient Boosting Machine algorithm called ILGBMSH. Rather than utilizing only the shRNA sequence feature, we extracted 554 biological and deep learning features, which were not considered in previous shRNA prediction research. We evaluated the performance of our model compared with the state-of-the-art shRNA target prediction models. Besides, we investigated the feature explanation from the model's parameters and interpretable method called Shapley Additive Explanations, which provided us with biological insights from the model. We used independent shRNA experiment data from other resources to prove the predictive ability and robustness of our model. Finally, we used our model to design the miR30-shRNA sequences and conducted a gene knockdown experiment. The experimental result was perfectly in correspondence with our expectation with a Pearson's coefficient correlation of 0.985. In summary, the ILGBMSH model can achieve state-of-the-art shRNA prediction performance and give biological insights from the machine learning model parameters. [ABSTRACT FROM AUTHOR]

Understanding the dynamic behavior of tires and their interactions with roads plays an important role in designing integrated vehicle control strategies. Accordingly, having access to reliable information about tire–road interactions through tire-embedded sensors is desirable for developing enhanced vehicle control systems. Thus, the main objectives of this research are: 1) to analyze data from an experimental accelerometer-based intelligent tire acquired over a wide range of maneuvers, with different vertical loads, velocities, and high slip angles and 2) to develop a lateral force predictor based on a machine learning tool, more specifically, the Gaussian process regression (GPR) technique. It is determined that the proposed intelligent tire system can provide reliable information about the tire–road interactions even in the case of high slip angles. In addition, lateral force models based on GPR can predict forces very well, outperforming other machine learning models and providing levels of uncertainty that can be useful for designing vehicle control strategies. [ABSTRACT FROM AUTHOR]

In the era of big data, using big data to realize the online estimation of battery SOH has become possible. Traditional solutions based on theoretical models cannot take into account driving behavior and complicated environmental factors. In this paper, an approximate SOH degradation model based on real operating data and environmental temperature data of electric vehicles (EVs) collected with a big data platform is proposed. Firstly, the health indicators are extracted from the historical operating data, and the equivalent capacity at 25 °C is obtained based on the capacity–temperature empirical formula and the capacity offset. Then, the attenuation rate during each charging and discharging process is calculated by combining the operating data and the environmental temperature. Finally, the long short-term memory (LSTM) neural network is used to learn the degradation trend of the battery and predict the future decline trend. The test results show that the proposed method has better performance. [ABSTRACT FROM AUTHOR]

• Using deep learning method to predict siRNA efficacy rather than extensive hand-crafted features extraction. • Transferring gene sequence information from large DNA corpus for siRNA prediction task with the BERT style. • Providing model explainability by visualization of attention scores and hidden layers. Silencing mRNA through siRNA is vital for RNA interference (RNAi), necessitating accurate computational methods for siRNA selection. Current approaches, relying on machine learning, often face challenges with large data requirements and intricate data preprocessing, leading to reduced accuracy. To address this challenge, we propose a BERT model-based siRNA target gene knockdown efficiency prediction method called BERT-siRNA, which consists of a pre-trained DNA-BERT module and Multilayer Perceptron module. It applies the concept of transfer learning to avoid the limitation of a small sample size and the need for extensive preprocessing processes. By fine-tuning on various siRNA datasets after pretraining on extensive genomic data using DNA-BERT to enhance predictive capabilities. Our model clearly outperforms all existing siRNA prediction models through testing on the independent public siRNA dataset. Furthermore, the model's consistent predictions of high-efficiency siRNA knockdown for SARS-CoV-2, as well as its alignment with experimental results for PDCD1 , CD38 , and IL6 , demonstrate the reliability and stability of the model. In addition, the attention scores for all 19-nt positions in the dataset indicate that the model's attention is predominantly focused on the 5′ end of the siRNA. The step-by-step visualization of the hidden layer's classification progressively clarified and explained the effective feature extraction of the MLP layer. The explainability of model by analysis the attention scores and hidden layers is also our main purpose in this work, making it more explainable and reliable for biological researchers. [ABSTRACT FROM AUTHOR]

Our recent multi-omics studies have revealed rich sources of novel bioactive proteins and polypeptides from marine organisms including cnidarians. In the present study, we initially conducted a transcriptomic analysis to review the composition profile of polypeptides from Zoanthus sociatus. Then, a newly discovered NPY-like polypeptide-ZoaNPY was selected for further in silico structural, binding and virtually pharmacological studies. To evaluate the pro-angiogenic effects of ZoaNPY, we employed an in vitro HUVECs model and an in vivo zebrafish model. Our results indicate that ZoaNPY, at 1–100 pmol, enhances cell survival, migration and tube formation in the endothelial cells. Besides, treatment with ZoaNPY could restore a chemically-induced vascular insufficiency in zebrafish embryos. Western blot results demonstrated the application of ZoaNPY could increase the phosphorylation of proteins related to angiogenesis signaling including PKC, PLC, FAK, Src, Akt, mTOR, MEK, and ERK1/2. Furthermore, through molecular docking and surface plasmon resonance (SPR) verification, ZoaNPY was shown to directly and physically interact with NPY Y2 receptor. In view of this, all evidence showed that the pro-angiogenic effects of ZoaNPY involve the activation of NPY Y2 receptor, thereby activating the Akt/mTOR, PLC/PKC, ERK/MEK and Src- FAK-dependent signaling pathways. Furthermore, in an excision wound model, the treatment with ZoaNPY was shown to accelerate the wound healing process in mice. Our findings provide new insights into the discovery and development of novel pro-angiogenic drugs derived from NPY-like polypeptides in the future. [Display omitted] [ABSTRACT FROM AUTHOR]

Background: Non-steroidal anti-inflammatory drugs (NSAIDs) are among the most widely prescribed drugs worldwide. However, the effect of NSAIDS on postoperative renal function is still unclear. Few studies have assessed the effects of parecoxib on renal function. Our aim is to investigate a correlation between parecoxib and the presence or absence of AKI postoperatively after a breast cancer surgery operation. Methods: This was a retrospective cohort study that we performed on our hospitalized database. From January 2012 to August 2021, 3542 female patients undergoing radical mastectomy were enrolled, all data including the patients' information and laboratory results were obtained from electronic medical system. The main outcome was the incidence of AKI postoperatively. AKI was defined in accordance with the KDIGO criteria. Study groups were treated with or without parecoxib. Univariable and multivariable logistic regression analyses were performed. Results: In our study, about 5.76% experienced AKI. The incidence rate of postoperative AKI (3.49%) within 7 days in the parecoxib group was lower than that in the control group (6.00%, P = 0.05). Compared to the control group, the AKI's incidence was reduced by 49% (OR = 0.46; 95%CI 0.27–0.97) in parecoxib group in multivariable logistic regression analysis. There was a reduction in the incidence of postoperative AKI in other three subgroups: preoperative eGFR < 90 mL/min·1.73/m2 (OR = 0.52; 95%CI 0.27–0.97), blood loss < 1000 ml (OR = 0.48; 95%CI 0.24–0.96) and non-diabetes (OR = 0.51; 95%CI 0.26–0.98). Conclusions: Parecoxib was associated with incidence of postoperative acute kidney injury. [ABSTRACT FROM AUTHOR]

The heart and brain are the core organs of the circulation and central nervous system, respectively, and play an important role in maintaining normal physiological functions. Early neuronal and cardiac damage affects organ function. The relationship between the heart and brain is being continuously investigated. Evidence-based medicine has revealed the concept of the "heart- brain axis," which may provide new therapeutic strategies for certain diseases. Takeda protein-coupled receptor 5 (TGR5) is a metabolic regulator involved in energy homeostasis, bile acid homeostasis, and glucose and lipid metabolism. Inflammation is critical for the development and regeneration of the heart and brain during metabolic diseases. Herein, we discuss the role of TGR5 as a metabolic regulator of heart and brain development and injury to facilitate new therapeutic strategies for metabolic and ischemic diseases of the heart and brain. • There is a brain-heart axis and organ damage may be reduced by intervening fluid changes in brain and heart injury. • TGR5 is widely distributed in various types of cells, and is closely related to the metabolism and injury of brain and heart. • TGR5 may play a key role in brain and heart diseases, which become a potential treatment for diseases related to the brain and heart. [ABSTRACT FROM AUTHOR]

MXene nanosheets have been identified as promising building blocks for high-performance nanofiltration (NF) membranes in water purification. Herein, we report a series of amino acid-bonded Ti 3 C 2 T x MXene membranes with enhanced NF performance and antifouling properties via glycine (Gly), l -glutamic acid (L-Glu), l -lysine (L-Lys) or l -cysteine (L-Cys) modification. The physicochemical properties, separation performances and anti-fouling behaviors of the pure Ti 3 C 2 T x MXene membrane, Gly-, L-Glu-, L-Lys- and L-Cys-bonded Ti 3 C 2 T x MXene membranes were comparatively investigated. The stable Ti–N bonds were found between the amino acids and the MXene nanosheets and different amino acids lead to different properties of the corresponding membranes. While maintaining ultra-high rejections to various organic dyes, all the amino acid functionalized membranes exhibited enhanced water permeability (7.17–13.11 L·m−2·h−1·bar−1) compared with that of the pure MXene membrane. Importantly, the Gly-bonded membrane showed the optimal separation performance with high salt rejections of 86.28%, 81.36%, 72.88% and 66.82% to MgSO 4 , MgCl 2 , Na 2 SO 4 and NaCl, respectively, and the membrane also exhibited superior anti-fouling property with a flux recovery rate of 80.59% to bovine serum albumin (BSA). The separation mechanism was further revealed which may offer a simple yet efficient way for enhancing 2D MXene-based NF membranes. [Display omitted] • Amino acid-bonded Ti 3 C 2 T x MXene nanofiltration membranes were prepared. • Four amino acids were used to functionalize the MXene laminates. • The prepared membranes exhibited enhanced water purification performance. • The glycine-bonded membrane demonstrates superior antifouling behavior. [ABSTRACT FROM AUTHOR]

Acquiring accurate and timely datasets on tidal flat topography is fundamental for studies, management, and policy‐making in coastal zones. In this study, we report a fusion method of freely accessed and global‐scale Sentinel‐2 (imagery) and Ice,Cloud, and Land Elevation Satellite‐2 (ICESat‐2) (laser altimetry) datasets for deriving tidal flat topography. The basic idea is to construct a model on characterizing the specific relationship between the elevations of the tidal flat (from ICESat‐2 data) and corresponding inundation frequencies (from Sentinel‐2 time‐series). The proposed method was validated for the largest tidal flat on the Chinese continental shelf with a root mean square error of 0.23 m. We highlight that this method solely relies on satellite data and does not require any in‐situ data because ICESat‐2 provides dense and accurate along‐track points as valuable prior elevation information, which enhance the ability to obtain tidal flat topography in many coastal regions even in the absence of local in‐situ data. Plain Language Summary: Global tidal flat topography is still unavailable at present, although it is the foundation of many global‐scale coastal‐related issues, such as coastal vulnerability estimation to sea level rise and flooding, coastal wetland monitoring, habitat conservation, site selection of offshore wind farms and ports, and land use planning. To generate tidal flat topography, accurate vertical and horizontal information is simultaneously acquired. The Ice, Cloud, and Land Elevation Satellite‐2 (ICESat‐2) satellite provides dense three‐dimensional points with high vertical accuracy, which can replace field surveying (e.g., by handheld/airborne/shipborne devices) for obtaining these three‐dimensional points. The time‐series imagery of the Sentinel‐2 satellite can map accurate inundation frequencies of tidal flats (i.e., the frequency of a location heaves out or is covered by water due to ocean tides) with high horizontal resolution. Integrating the advantages of ICESat‐2 and Sentinel‐2 makes it possible to obtain global topography for tidal flats with only satellite remotely sensed data. With freely accessed and global‐scale ICESat‐2 and Sentinel‐2 data, it can be expanded to obtain tidal flat topography in many specific coastal regions or even globally. Key Points: A method to generate tidal flat topography in coastal zones was proposed using satellite remotely sensed dataIce,Cloud, and Land Elevation Satellite‐2 provides accurate along‐track profiles as prior elevation information; therefore, in‐situ data are no longer neededGoogle Earth Engine was used to speed up implementation and can expand this method for large scale applications [ABSTRACT FROM AUTHOR]

[Display omitted] Recent advances in artificial intelligence, computer science, communication, sensing and actuation technologies have resulted in the development of several novel intelligent systems. At the same time, the emergence of nanogenerators has opened a new research avenue with the overarching goal of developing self-powered sensing systems. The concepts of self-powered sensing, based on nanogenerators and intelligent systems can be fused together to open a new area of interdisciplinary research. In this article, we aim to show how these two emerging technologies have been combined to develop self-powered intelligent sensing systems. We first focus on the main keywords in the area of nanogenerators. Keyword co-occurrence network graphs are generated based on the most used keywords in the area of nanogenerators to select key concepts that are directly connected to the concept of intelligent systems. Thus, a detailed review is provided on different intelligent self-powered sensing systems based on nanogenerators. We also discuss the challenges presented by combining intelligent systems and self-powered sensing. As most of intelligent devices rely on machine learning techniques, a comprehensive section is allocated to this topic to focus on its applications in nanogenerator-based devices. [ABSTRACT FROM AUTHOR]

Background: Current intra-tumoral heterogeneous feature extraction in radiology is limited to the use of a single slice or the region of interest within a few context-associated slices, and the decoding of intra-tumoral spatial heterogeneity using whole tumor samples is rare. We aim to propose a mathematical model of space-filling curve-based spatial correspondence mapping to interpret intra-tumoral spatial locality and heterogeneity. Methods: A Hilbert curve-based approach was employed to decode and visualize intra-tumoral spatial heterogeneity by expanding the tumor volume to a two-dimensional (2D) matrix in voxels while preserving the spatial locality of the neighboring voxels. The proposed method was validated using three-dimensional (3D) volumes constructed from lung nodules from the LIDC-IDRI dataset, regular axial plane images, and 3D blocks. Results: Dimensionality reduction of the Hilbert volume with a single regular axial plane image showed a sparse and scattered pixel distribution on the corresponding 2D matrix. However, for 3D blocks and lung tumor inside the volume, the dimensionality reduction to the 2D matrix indicated regular and concentrated squares and rectangles. For classification into benign and malignant masses using lung nodules from the LIDC-IDRI dataset, the Inception-V4 indicated that the Hilbert matrix images improved accuracy (85.54% vs. 73.22%, p < 0.001) compared to the original CT images of the test dataset. Conclusions: Our study indicates that Hilbert curve-based spatial correspondence mapping is promising for decoding intra-tumoral spatial heterogeneity of partial or whole tumor samples on radiological images. This spatial-locality-preserving approach for voxel expansion enables existing radiomics and convolution neural networks to filter structured and spatially correlated high-dimensional intra-tumoral heterogeneity. [ABSTRACT FROM AUTHOR]

Our aim was to explore the effects of dietary and behavior interventions on lipometabolism caused by an unhealthy high-fat diet and the best method to rebuild lipid homeostasis of this lifestyle. Apart from normal diet rats, 34 rats were fed with high-fat emulsion for 4 weeks and then intervened for another 4 weeks. Eight of them were classified into high-fat control group, and 9 were sorted into high-fat diet with rice vinegar group. Meanwhile, 10 were put into high-fat diet in swimming group, and 7 were just for refeeding normal diet group. Then, the data of body weight was recorded and analyzed. Indexes of serum samples were tested by kits. AMPKα, HNF1α, and CTRP6 in pancreas, liver, cardiac, and epididymis adipose tissues were detected by western blot. According to our experiments, swimming and refeeding groups reflected a better regulation on lipid homeostasis mainly by upregulating the expression of pancreas AMPKα. To be more specific, the refeeding rats showed lower T-CHO (P < 0.001) and LDL-C (P < 0.05), but higher weight gain (P < 0.001), insulin level (P < 0.01), and pancreas AMPKα (P < 0.01) than high-fat control rats. Compared with rats intervened by swimming or rice vinegar, they showed higher weight gain (P < 0.001), insulin level (P < 0.01), and HNF1α, but lower of CTRP6. In summary, refeeding diet functioned better in regulating the lipometabolic level after high-fat diet. Whatever approach mentioned above we adopted to intervene, the best policy to keep the balance of lipid homeostasis is to maintain a healthy diet. [ABSTRACT FROM AUTHOR]

A single insulin receptor (InR) gene has been identified and extensively studied in model species ranging from nematodes to mice. However, most insects possess additional copies of InR, yet the functional significance, if any, of alternate InRs is unknown. Here, we used the wing-dimorphic brown planthopper (BPH) as a model system to query the role of a second InR copy in insects. NlInR2 resembled the BPH InR homologue (NlInR1) in terms of nymph development and reproduction, but revealed distinct regulatory roles in fuel metabolism, lifespan, and starvation tolerance. Unlike a lethal phenotype derived from NlInR1 null, homozygous NlInR2 null mutants were viable and accelerated DNA replication and cell proliferation in wing cells, thus redirecting short-winged–destined BPHs to develop into long-winged morphs. Additionally, the proper expression of NlInR2 was needed to maintain symmetric vein patterning in wings. Our findings provide the first direct evidence for the regulatory complexity of the two InR paralogues in insects, implying the functionally independent evolution of multiple InRs in invertebrates. Author summary: The highly conserved insulin/insulin-like growth factor signaling pathway plays a pivotal role in growth, development, and various physiological processes across a wide phylogeny of organisms. Unlike a single InR in the model species such as the fruit fly Drosophila melanogaster and the nematode Caenorhabditis elegans, most insect lineages have two or even three InR copies. However, the function of the alternative InRs remains elusive. Here, we created a homozygous mutation for a second insulin receptor (InR2) in the wing-dimorphic brown planthopper (BPH), Nilaparvata lugens, using the clustered regularly interspaced palindromic repeats/CRISPR-associated (CRISPR/Cas9) system. Our findings revealed that InR2 possesses functions distinct from the BPH InR homologue (NlInR1), indicating that multiple InR paralogues may have evolved independently and may have functionally diversified in ways more complex than previously expected in invertebrates. [ABSTRACT FROM AUTHOR]

Objective. To prepare the cell-penetrating peptide Penetratin-modified liposome (Pen-Lip) for ophthalmic application and evaluate its applicability to treat fundus neovascularization diseases through topical instillation. Methods. The copolymer DSPE-PEG2000-Pen was synthesized by the addition reaction of DSPE-PEG2000-Mal and Penetratin, and Pen-Lip was then prepared by the thin film dispersion method. The cellular uptake experiment was used to determine the optimal ratio of Penetratin to modify liposomes. The average particle size, Zeta potential and polydispersity index (PDI) of Pen- Lip were characterized by the nano particle size potentiometer, and the morphology of Pen-Lip was observed by using transmission electron microscope (TEM). The encapsulation efficiency and the drug loading of Pen-Lip with conbercept were determined by centrifugation. Pen-lip was incubated in the PBS or the PBS containing 50% fetal bovine serum for 48 h and the stability of Pen-Lip was investigated by the change of particle size and the morphology under TEM. The CCK-8 assay was conducted to detect the cytotoxicity of Pen-Lip to human corneal epithelial cell (HCEC) and human retinal pigment epithelium (ARPE-19), and the uptake of Pen-Lip by ARPE-19 was observed by using laser confocal microscope. The diffusion cell device was used to detect the permeability of Pen-Lip through the isolated rabbit cornea, and the apparent permeability coefficient (Papp) was calculated. The toxicity of Pen-Lip with conbercept to the corneal tissue was evaluated by the hydration value. Results. The optimal ratio of Penetratin to modify liposomes was 3%. The average particle size of Pen-Lip was (148.07±3.51) nm, the Zeta potential was (5.66±0.91) mV, and the PDI was 0.227±0.045. TEM results showed that Pen-Lip had a smooth spherical structure. The encapsulation efficiency of Pen-Lip was (44.06±3.70) %, and the drug loading was (2.84±0.24) %. The particle size of Pen-Lip did not change significantly and TEM showed uniform dispersion after dispersing in the PBS or the PBS containing 50% fetal bovine serum for 48 h, exhibiting the good stability of Pen-Lip. When Pen-Lip was at the concentration of 15-500 μg/mL, Pen-Lip had no cytotoxicity to HCEC and ARPE-19. Compared with unmodified liposomes, ARPE-19 cells had significantly higher uptake of Pen-Lip (P=0.000). In the experiment of rabbit cornea penetration in vitro, the Papp of Pen-Lip was significantly higher than that of unmodified liposomes (P=0.000). There was no statistically significant difference in the hydration value of the rabbit cornea treated with drug-loaded Pen-Lip compared to the untreatd group (P> 0.05). Conclusion. Pen-Lip has good stability, biocompatibility and corneal permeability in vitro and can be taken up by retinal cells, which is a potential ocular drug delivery system to treat fundus neovascularization diseases through topical instillation. [ABSTRACT FROM AUTHOR]

Tire slip angle is a vital parameter in tire/vehicle dynamics and control. This paper proposes an accurate estimation method by the fusion of intelligent tire technology and machine-learning techniques. The intelligent tire is equipped by MEMS accelerometers attached to its inner liner. First, we describe the intelligent tire system along with the implemented testing apparatus. Second, experimental results under different loading and velocity conditions are provided. Then, we show the procedure of data processing, which will be used for training five different machine learning techniques to estimate tire slip angles. The results show that the machine learning techniques, especially in frequency domain, can accurately estimate tire slip angles up to 10 degrees. More importantly, with the accurate tire slip angle estimation, all other states and parameters can be easily and precisely obtained, which is significant to vehicle advanced control, and thus this study has a high potential to obviously improve the vehicle safety especially in extreme maneuvers. [ABSTRACT FROM AUTHOR]

The plant pathogen Agrobacterium tumefaciens causes crown gall disease and is a widely used tool for generating transgenic plants owing to its virulence. The pathogenic process involves a shift from an independent to a living form within a host plant. However, comprehensive analyses of metabolites, genes, and reactions contributing to this complex process are lacking. To gain new insights about the pathogenicity from the viewpoints of physiology and cellular metabolism, a genome‐scale metabolic model (GSMM) was reconstructed for A. tumefaciens. The model, referred to as iNX1344, contained 1,344 genes, 1,441 reactions, and 1,106 metabolites. It was validated by analyses of in silico cell growth on 39 unique carbon or nitrogen sources and the flux distribution of carbon metabolism. A. tumefaciens metabolic characteristics under three ecological niches were modelled. A high capacity to access and metabolize nutrients is more important for rhizosphere colonization than in the soil, and substantial metabolic changes were detected during the shift from the rhizosphere to tumour environments. Furthermore, by integrating transcriptome data for tumour conditions, significant alterations in central metabolic pathways and secondary metabolite metabolism were identified. Overall, the GSMM and constraint‐based analysis could decode the physiological and metabolic features of A. tumefaciens as well as interspecific interactions with hosts, thereby improving our understanding of host adaptation and infection mechanisms. [ABSTRACT FROM AUTHOR]

Energy efficiency is extremely important for electric vehicles to improve their driving range. As the motor output energy directly acts on the tire, the tire slip energy generated by tire excessive slip will reduce the effective utilization of motor output energy, resulting in the reduction of energy efficiency, especially in the case of low friction coefficient, or even vehicle instability in some changes, such as slalom change, etc. Therefore, this paper designs an integrated chassis control and verifies the energy utilization. First, based on model predictive control (MPC), an integrated chassis controller is proposed by explicitly incorporating both motor energy and tire slip energy in the main objective function. Second, the reference control actions of the torque distribution method optimized for the motor energy, which facilitates solution-search process of MPC. Then, a semi-empirical UniTire tire slip energy model is proposed for derivation of the tire dissipation energy. Acceleration and stability tests are conducted by four in-wheel independent motor-drive electric vehicles (4WIMD-EVs) on winter proving ground, respectively. The acceleration change results show that both tire dissipation energy and motor output energy are well suppressed to achieve energy-efficient, and the energy utilization ratio of tire dissipation energy to motor output energy is only 35% to achieve stable acceleration. The slalom change verifies vehicle stability, and the results show that the slip ratio of four wheels only reaches to 0.04, and the motor output energy of four wheels is effectively utilized to generate differential yaw moment. [ABSTRACT FROM AUTHOR]

Here, the complete mitochondrial genome (mitogenome) of Drawida gisti was sequenced and compared with the mitogenomes of other Metagynophora species. The circular mitogenome was 14,648 bp in length and contained two ribosomal RNA genes (rRNAs), 13 protein-coding genes (PCGs), and 22 transfer RNA genes (tRNAs). The types of constitutive genes and the direction of the coding strand that appeared in Drawida mitogenome were identical to those observed in other Metagynophora species, except for a missing lengthy non-coding region. The conservative relationships between Drawida species were supported by the overall analyses of 13 PCGs, two rRNAs, and 22 tRNAs. A comparison of the Metagynophora mitogenomes revealed that the ATP8 gene possessed the highest polymorphism among the 13 PCGs and two rRNAs. Phylogenetic analysis suggested that the Moniligastridae contained Drawida , which is a primitive Metagynophora group. Our study provides a step forward toward elucidating the evolutionary linkages within Drawida and even Metagynophora. • Extremely small mitogenome size of Drawida gisti • Absence of lengthy non-coding regions in Drawida mitogenomes • Significant difference in codon usage of mitochondrial genes between Drawida and other earthworms • Conservative relationships of Metagynophora supported by mitogenomes [ABSTRACT FROM AUTHOR]

Background: The remarkable regenerative capacity of the liver enables recovery after radical Hepatocellular carcinoma (HCC) resection. After resection, macrophages secrete interleukin 6 and hepatocyte growth factors to promote liver regeneration. Ten-eleven translocation-2 (Tet2) DNA dioxygenase regulates pro-inflammatory factor secretion in macrophages. In this study, we explored the role of Tet2 in macrophages and its function independent of its enzymatic activity in liver regeneration. Methods: The model of liver regeneration after 70% partial hepatectomy (PHx) is a classic universal model for studying reparative processes in the liver. Mice were euthanized at 0, 24, and 48 h after PHx. Enzyme-linked immunosorbent assays, quantitative reverse transcription-polymerase chain reaction, western blotting, immunofluorescence analysis, and flow cytometry were performed to explore immune cell infiltration and liver regenerative capability. Molecular dynamics simulations were performed to study the interaction between Tet2 and signal transducer and activator of transcription 1 (Stat1). Results: Tet2 in macrophages negatively regulated liver regeneration in the partial hepatectomy mice model. Tet2 interacted with Stat1, inhibiting the expression of proinflammatory factors and suppressing liver regeneration. The Tet2 inhibitor attenuated the interaction between Stat1 and Tet2, enhanced Stat1 phosphorylation, and promoted hepatocyte proliferation. The proliferative function of the Tet2 inhibitor relied on macrophages and did not affect hepatocytes directly. Conclusion: Our findings underscore that Tet2 in macrophages negatively regulates liver regeneration by interacting with Stat1. Targeting Tet2 in macrophages promotes liver regeneration and function after a hepatectomy, presenting a novel target to promote liver regeneration and function. Tet2 interacts with Stat1 in the cytoplasm and suppresses IFN-γ-induced macrophage activation. Tet2 inhibitor decreases the combination of Stat1 and Tet2, activating the macrophages through the Jak-Stat pathway. The activation of macrophages increases the transcription and translation of the IL-6 and promotes liver regeneration. BnQa2gdaXkcfesAu78GqfX Video Abstract [ABSTRACT FROM AUTHOR]

Background: The remarkable regenerative capacity of the liver enables recovery after radical Hepatocellular carcinoma (HCC) resection. After resection, macrophages secrete interleukin 6 and hepatocyte growth factors to promote liver regeneration. Ten-eleven translocation-2 (Tet2) DNA dioxygenase regulates pro-inflammatory factor secretion in macrophages. In this study, we explored the role of Tet2 in macrophages and its function independent of its enzymatic activity in liver regeneration. Methods: The model of liver regeneration after 70% partial hepatectomy (PHx) is a classic universal model for studying reparative processes in the liver. Mice were euthanized at 0, 24, and 48 h after PHx. Enzyme-linked immunosorbent assays, quantitative reverse transcription-polymerase chain reaction, western blotting, immunofluorescence analysis, and flow cytometry were performed to explore immune cell infiltration and liver regenerative capability. Molecular dynamics simulations were performed to study the interaction between Tet2 and signal transducer and activator of transcription 1 (Stat1). Results: Tet2 in macrophages negatively regulated liver regeneration in the partial hepatectomy mice model. Tet2 interacted with Stat1, inhibiting the expression of proinflammatory factors and suppressing liver regeneration. The Tet2 inhibitor attenuated the interaction between Stat1 and Tet2, enhanced Stat1 phosphorylation, and promoted hepatocyte proliferation. The proliferative function of the Tet2 inhibitor relied on macrophages and did not affect hepatocytes directly. Conclusion: Our findings underscore that Tet2 in macrophages negatively regulates liver regeneration by interacting with Stat1. Targeting Tet2 in macrophages promotes liver regeneration and function after a hepatectomy, presenting a novel target to promote liver regeneration and function. Tet2 interacts with Stat1 in the cytoplasm and suppresses IFN-γ-induced macrophage activation. Tet2 inhibitor decreases the combination of Stat1 and Tet2, activating the macrophages through the Jak-Stat pathway. The activation of macrophages increases the transcription and translation of the IL-6 and promotes liver regeneration. BnQa2gdaXkcfesAu78GqfX Video Abstract [ABSTRACT FROM AUTHOR]

• Totally 155 patients from three medical centers in East China were recruited, including 108 patients in standard-dose group and 47 patients in high-dose group. • This study was a retrospective study, and established strict inclusion criteria. Furthermore, two experienced infectious experts reviewed the cases which met the cSSTIs diagnosis, and excluded the doubtful cases. • The results of multivariate analysis indicated that high-dose daptomycin was an independent effector for early clinical stabilization. • Compared with standard-dose daptomycin, high-dose daptomycin increased the rate of early clinical stabilization in Asian patients with cSSTIs, whereas the incidence of adverse events did not increase. To compare the efficacy and safety of standard-dose (SD) daptomycin with those of high-dose (HD) daptomycin in complicated skin and soft tissue infections (cSSTIs) in an Asian population. Patients from three medical centers diagnosed with cSSTIs were screened in the clinical information system. Patients included in the analysis were divided into two groups: those who received daptomycin at doses ≥ 6 mg/kg (HD group) and those receiving 4 mg/kg (SD group). The demographics and clinical treatment information were analyzed. Overall, 155 patients were recruited, including 108 patients in the SD group and 47 patients in the HD group. The rate of healthcare-associated infections was higher in the HD group (61.70% vs. 37.04%), demonstrating a statistically significant difference (P = 0.005). Compared with the SD group, the HD group had statistically significant early clinical stabilization (72.34% vs 52.78%, P = 0.023). The results of the multivariate analysis indicated that HD daptomycin was an independent effector for early clinical stabilization (HR=0.394, P < 0.001). The rate of drug-related adverse events was equally distributed in the HD and SD groups (36.17% vs. 26.85%, P = 0.243). Compared with SD daptomycin, HD daptomycin increased the rate of early clinical stabilization in Asian patients with cSSTIs, whereas the incidence of adverse events did not increase. [ABSTRACT FROM AUTHOR]

The low to intermediate temperature (850–1050 K) auto-ignition characteristics of furan, 2,3-dihydrofurn and tetrahydrofuran have been investigated both experimentally and kinetically. The pressure (18 and 33 bar) and equivalence ratio (0.5, 1.0 and 2.0) effects on the auto-ignition of furan were experimentally examined using a rapid compression machine. Compared with alkylated furans, the ignition delay times of furan show notably insensitivity to equivalence ratio. Comparison on the low to intermediate temperature reactivity of furan, alkylated furans, 2, 3-dihydrofuran, and tetrahydrofuran indicates that saturation degree plays a more dominant role in enhancing reactivity than alkyl substitution. Literature mechanisms were validated against present data. Kinetic analyses revealed the major fuel consuming routes and the causes for the deviation between simulation and experimental results. Furthermore, a modified model of furan, 2, 3-dihydrofuran, and tetrahydrofuran was proposed and validated against the ignition delay times in this study as well as experimental data in literatures. [ABSTRACT FROM AUTHOR]

Mesozoic magmatism and lithospheric destruction in East China exerted significant control on gold metallogeny. Here, we investigate the mineralogy, geochemistry, geochronology, and isotopic systematics of the Dongyang gold deposit in southeast China to constrain its origin and geodynamics. This is a newly discovered epithermal gold deposit along the Circum–Pacific metallogenic belt and is characterized by intense silicification and sericitization. The C–H–O isotope data suggest deep magmatic sources of the ores and indicate that the ore‐forming fluids comprised a mixture of magmatic water and meteoric water. The S–Pb values of the pyrite indicate magmatic origin for the sulfur, and deposit was derived mostly from crustal sources, mixed with mantle materials. The Rb–Sr dating of the pyrite from the ore deposit shows an age of 164.2 ± 9.9 Ma, whereas the zircon U–Pb SHRIMP ages of the rhyolite porphyry is 160.9 ± 0.5 Ma, suggesting that the timing of mineralization is close to that of the crystallization of the dykes. In conjunction with previous studies on similar deposits, we suggest that the gold mineralization was the response of continental lithospheric thinning in southeast China triggered by the subduction of the Palaeo‐Pacific Ocean Plate. [ABSTRACT FROM AUTHOR]

Drought stress led to a decrease in PSII photochemical activity in tobacco leaves and the blockage of electron transfer, especially from QA to QB on PSII acceptor side. In addition, drought stress caused a dramatic increase in H2O2 and MDA contents. However, the overexpression of 2-Cys Prx significantly reduced the H2O2 accumulation in tobacco seedlings and alleviated the degree of oxidative damage under drought stress. It also improved stomatal limitation and net photosynthetic rate of tobacco seedlings and reduced its PSII photoinhibition under drought stress which promoted the ability of PSII electron transfer. [ABSTRACT FROM AUTHOR]

Although titanium implants account for a large proportion of the commercial dental market, their bioactivity are inadequate in many applications. A micro- and nano- scale hierarchical surface topography of the implant is suggested for rapid osseointegration from the biomimetic perspective. Moreover, Zinc (Zn) is an essential element in the skeletal system. Thus, a micro/nanostructured TiO2/ZnO coating, produced by micro-arc oxidation, and hydrothermal treatment, and heat treatment, was designed to endow the implant surface with enhanced osteogenic capacity. Physiochemical properties and biological effects of this coating were investigated in our study. The annealed micro/nanostructured TiO2/ZnO coating exhibited higher hydrophilicity and fibronectin adsorption ability compared to the micro-arc oxidation modified TiO2 coating. SaOS-2 cells grown on the annealed micro/nanostructured TiO2/ZnO coating showed increased alkaline phosphatase activity and collagen secretion, and immunofluorescence labeling revealed an upregulation of osteopontin, collagen type ι and osteocalcin. The micro/nanostructure and incorporation of Zn were considered to perform positive effect on the enhanced osteogenic activity of SaOS-2 cells. In conclusion, the micro/nanostructured TiO2/ZnO structure is simple, stable, and easy to produce and scale up, has promising applications in the surface modification of titanium implants. [ABSTRACT FROM AUTHOR]

Cryo-electron microscopy provides 2D projection images of the 3D electron scattering intensity of many instances of the particle under study (e.g., a virus). Both symmetry (rotational point groups) and heterogeneity are important aspects of biological particles and both aspects can be combined by describing the electron scattering intensity of the particle as a stochastic process with a symmetric probability law and, therefore, symmetric moments. A maximum likelihood estimator implemented by an expectation–maximization algorithm is described, which estimates the unknown statistics of the electron scattering intensity stochastic process from the images of instances of the particle. The algorithm is demonstrated on the bacteriophage HK97 and the virus $\text{N}\omega \text{V}$. The results are contrasted with the existing algorithms, which assume that each instance of the particle has the symmetry rather than the less restrictive assumption that the probability law has the symmetry. [ABSTRACT FROM AUTHOR]

This article has been withdrawn at the request of the author(s) and/or editor. The Publisher apologizes for any inconvenience this may cause. The full Elsevier Policy on Article Withdrawal can be found at http://www.elsevier.com/locate/withdrawalpolicy. [ABSTRACT FROM AUTHOR]

Candida glabrata is a major cause of candidiasis and the second most frequent opportunistic yeast pathogen. Its infectious and antifungal mechanisms are globally regulated by the transcription systems of pathogenic fungi. In this study, we reconstructed the genome-scale transcriptional regulatory network (TRN) of C. glabrata, consisting of 6634 interactive relationships between 145 transcription factors and 3230 target genes, based on genomic and transcriptomic data. The C. glabrata TRN was found to have a typical topological structure and significant network cohesiveness. Moreover, this network could be functionally divided into several sub-networks, including networks involving carbon, nitrogen, growth-associated metabolic profiles, stress response to acidity, hyperosmosis, peroxidation, hypoxia and virulence. Furthermore, by integrating the genome-scale metabolic model of C. glabrata, six essential metabolites and eight related enzymes were systematically selected as drug targets. Overall, elucidation of the genome-scale TRN of C. glabrata has expanded our knowledge of the contents and structures of microbial regulatory networks and improved our understanding of the regulatory behaviors of growth, metabolism and gene expression programs in response to environmental stimuli. Reconstruction of genome-scale transcriptional regulatory network for non-model microbe Candida glabrata and integration with metabolic model for the in silico drug targets. [ABSTRACT FROM AUTHOR]

Abstract Systemic lupus erythematosus (SLE) constitutes an autoimmune disease characterized by the breakdown of tolerance to self-antigens, sustained production of pathogenic autoantibodies, and damage to multiple organs and tissues. Nanoparticle (NP)-based therapeutics have demonstrated efficacy in attenuating the progression of SLE. However, investigations of nano-drugs that address the crucial initiating factor in the pathogenesis of SLE; e.g., inefficient clearance of apoptotic cells by phagocytes and consequent accumulation of self-antigens, have seldom been reported. Here, an apoptotic cell-mimicking gold nanocage (AuNC)-based nano drug carrier capable of correcting the impaired clearance of apoptotic cells in SLE was rationally designed and generated by conjugating phosphatidylserine (PS) on the surface of liposome-coated AuNCs for liver X receptor (LXR) agonist T0901317 delivery. Notably, PS-lipos-AuNC@T0901317 could efficiently enhance apoptotic cell clearance by elevating the expression of Mer, one of the pivotal phagocytosis-associated receptors on macrophages, resulting in decreased production of anti-dsDNA autoantibodies, reduced inflammatory response, and alleviation of kidney damage in lupus model mice. Additionally, PS-lipos-AuNC could be tracked by photoacoustic imaging for nano drug carrier biodistribution. By addressing the crucial pathogenic factor of SLE, the NP-based delivery system in this study is envisioned to provide a promising strategy to treat this complex and challenging disease. [ABSTRACT FROM AUTHOR]

Pacific White Shrimps (Litopenaeus vannamei) are an aquaculture species with global importance. For the purpose of this paper, the quality shelling process of Pacific White Shrimps, freshly harvested from farms and stored in a mixture ice water up to 24 hr, was investigated. Both the differences and correlations between the indexes such as peeling time, shrimp yield, chromatic aberration, texture, K value, TBA value, and microstructure were compared and analyzed. The optimal shell peeling time of Pacific White Shrimps was determined by ice water treatment for 8 hr. The shell peeling time was 1.77 min, the elasticity of the shrimp was 0.51 mm, the hardness was 2,124.58 g, K value was 1.33%, and TBA value was 0.004 mg/100 g. Both the smell and color of the shelled shrimp were normal. This study aims to endorse the mechanical shelling of Pacific White Shrimps. For the purpose of this paper, the quality shelling process of Pacific White Shrimps, freshly harvested from farms and stored in an ice water mixture for up to 24 hr, was investigated. Both the differences and correlations between the indexes such as peeling time, shrimp yield, chromatic aberration, texture, K value, TBA value, and microstructure were compared and analyzed. This study aims to endorse the mechanical shelling of Pacific White Shrimps. [ABSTRACT FROM AUTHOR]

Sorghum variety Longza 17 was used as the experimental organism in a study of the effects of different types of sodium salt (two neutral salts, NaCl and Na2SO4; and two alkaline salts, NaHCO3 and Na2CO3), at an equivalent Na+ concentration (100 mmol·L−1) on leaf growth parameters and PSII and PSI function by using the Fast Chlorophyll Fluorescence Induction Dynamics technique and 820 nm light reflectance curves. The results showed that at Na+ concentration of 100 mmol·L−1, different types of sodium salt stress significantly inhibited the growth of sorghum plants. Different types of sodium salt stress showed significant inhibition on the activities of PSII and PSI in sorghum leaves, the impact of different types of sodium salt on the activities of PSII and PSI in sorghum leaves was consistent, listed from greatest to least impact as Na2CO3 > NaHCO3 > Na2SO4 > NaCl. The effects of alkaline salt stress on the growth and photosynthetic properties of sorghum were greater than those under the neutral salt stress, therefore, in addition to considering the impact of Na+ concentration in the sorghum planting area, emphasis should also be given to the influence of the degree of alkalization, especially the higher alkalinity of Na2CO3. [ABSTRACT FROM AUTHOR]

Crop soil is inevitably contaminated by the excess of phosphate (P) fertilizers. A large amount of nanoparticle titanium dioxide (nTiO 2 ) entered soils as well due to the wide use of engineered nanomaterials. It is of great urgency and a high priority to investigate the mechanisms of nTiO 2 deposition with the presence of P in crop soils. This study investigated the transport behavior of (1.0 g L −1 ) rutile nTiO 2 with two representative clay particles (montmorillonite or diatomite) in the presence of P through the saturated quartz sand. In 10 mM NaCl electrolyte solution at pH 6.0, the recovery percentage of nTiO 2 was 36.3% from sand column. Nevertheless, it was reduced to 18.6% and 11.1% while montmorillonite and diatomite present in suspensions, respectively. Obviously, the improvement of nTiO 2 retention in sand was more pronounced by diatomite than montmorillonite. The likely mechanism for this result was that large aggregates were formed due to the attachment of nTiO 2 to montmorillonite and diatomite. Moreover, the surface of diatomite with the larger hydrodynamic radius was less negatively charged by comparison with montmorillonite. However, this phenomenon disappeared with the addition of P. P adsorption increases the repulsive force between particles and sand and the fast release of attached nTiO 2 -montmorillonite and diatomite from sand. The two-site kinetic retention model and the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory suggested that the combination of k 1/ k 1d , k 2 and secondary minimum energy can be used to accurately describe the attachment of nTiO 2 -montmorillonite and diatomite to sand in the presence of P. [ABSTRACT FROM AUTHOR]

The automotive augmented reality head-up-display (AR-HUD) system relies on multiple free-form surfaces to project the virtual image into human eyes. A wide range of views and the extensive display area result in extraordinarily complex distortions. Providing a way to correct such distortions is a major leap forward. Methods widely used for calibration, such as lookup tables and interpolation, require considerable memory capacity, complicated calibration procedures, etc. Additionally, when attempting to meet the high-accuracy requirements for such systems, computational memory grow rapidly. In this context, we propose a fully connected neural network (HUDNet) for an automotive AR-HUD to correct dynamic distortion. Here, we propose a parallel prediction framework for the center and the edge of the image, and separate the distortion information from the disparity information in order to balance the unstable central field of view error. Ultimately, we introduce the transfer learning method to improve accuracy and its effect on accuracy is assessed. The present study provides a reference for us to apply deep learning methods to predict dynamic image distortion of various complex multi-freeform surface reflection systems in the future. [Display omitted] • It is effective to decouple disparity and distortion in calibrating AR-HUD. • Positional coding and proper data processing improve the accuracy of the network. • Deep learning improves the mobility of calibration data among different products. [ABSTRACT FROM AUTHOR]

There are an estimated 800,000 small reservoirs globally with a range of uses. Given the collective importance of these reservoirs to water resource management and wider society, it is essential that we can monitor and understand the hydrological dynamics of ungauged reservoirs, particularly in a changing climate. However, unlike large reservoirs, continuous and systematic hydrological observations of small reservoirs are often unavailable. In response, this study has developed a retrieval framework for water levels of small reservoirs using a deep learning algorithm and remotely sensed satellite data. Demonstrated at four reservoirs in California, satellite imagery from both Sentinel-1 and Sentinel-2 along with corresponding water level field measurements was collected. Post-processed images were fed into a water level inversion convolutional neural network model for water level inversion, while different combinations of these satellite images, sampling approaches for training/testing data, and attention modules were used to train the model and evaluated for accuracy. The results show that random sampling of training data coupled with Sentinel-2 satellite imagery was generally the most accurate initially. Performance is improved by incorporating a channel attention mechanism, with the average R2 increasing by 8.6% and the average RMSE and MAE decreasing by 15.5% and 36.4%, respectively. The proposed framework was further validated on three additional reservoirs in different regions. In conclusion, the retrieval framework proposed in this study provides a stable and accurate methodology for water level estimation of small reservoirs and can be a powerful tool for small reservoir monitoring over large spatial scales. [ABSTRACT FROM AUTHOR]

In this paper, a low-cost and portable plasma device is developed to generate atmospheric pressure nonthermal air plasma jet for safe and effective biomedical applications. The device mainly consists of a pen electrode, a high-frequency ac power supply, an ac/dc module, and a dc air pump, and it totally costs only U.S. $63 and has a small size of 280 mm $\times190$ mm $\times180$ mm. The appearance of two-mode discharge of half-wave and full-wave breakdown with the changing of applied voltage is identified, and the length of the plasma jet is optimized through studying on the influences of distance between two electrodes, gas flow rates, and hole diameters of the gas outflow in ground electrode. Stronger plasma with a longer jet length of 12 mm can be obtained in the full-wave breakdown discharge mode, while moderate plasma with a length of 8 mm can be obtained in the half-wave breakdown discharge mode. The discharge characteristics of the device such as the main generated active particle, voltage and current, discharge power, and operation temperature are obtained. It is shown that rich active species for biomedical application can be generated at low power of approximate 2 W and low operation temperature of approximate 40 °C. The developed device is tested for biomedical application, and the results of effective sterilization of C. albicans and blood coagulation are obtained. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) have advantages in the aspect of energy, environment, and vehicle motion control. However, it is still not competitive enough to conventional vehicles because of the limited driving range and the high cost of the battery. Therefore, the energy efficiency is of the most importance for the control of EVs. Existing range extension control systems on EVs mostly focus on longitudinal front and rear axle torque distribution or lower-level yaw moment allocation. It is a challenge to maintain the vehicle’s stability at the cost of the minimum energy when the vehicle is cornering, this paper proposes a phase plane-based controller for EVs, focusing on the energy-efficient upper-level yaw stability control. The phase plane-based controller is automatically adaptive to driving situations through the optimization of weights on the performance of the vehicle handling and stability. Firstly, a friction constrained desired model is presented for the model-following control. Secondly, β - β ̇ phase plane analysis is conducted based on a nonlinear vehicle model to graphically identify the vehicle lateral stability in real time. The self-stable region can be determined by the vehicle velocity, the road friction coefficient, and the wheel steering angle. Then, energy optimizing (i.e. gain scheduling of LQR controllers) rules are designed based on the vehicle lateral stability identification. Finally, the proposed phase plane-based controller is evaluated and the yaw moment costs are compared to other controllers’ in a realistic 7-DOF vehicle model. The results demonstrate that the proposed controller presents an excellent yaw stability control capability, and compared to the widely used Shino’s controller, the proposed controller reduces the energy consumption by 9.68% and 3% at the ‘light’ and ‘severe’ maneuver, respectively. [ABSTRACT FROM AUTHOR]

Coastline change often results from social and natural factors, such as human activities in the coastal zone, long-term and short-term sea level change, hurricane occurrences, subsequent recovery, and so on. Tracking coastline change is essential to deepen our understanding of coastal responses to these factors. Such information is also required for land use planning and sustainable development of coastal zones. In this context, we aimed to collect all available Landsat data (TM: Thematic Mapper, ETM+: Enhanced Thematic Mapper Plus and OLI: Operational Land Imager) over 1986-2015 for tracking the coastline dynamic and estimating its change rate in the State of Texas, USA. First, the land vs. water maps at an annual scale were derived from the satellite images. The border between land and water represents the coastline in this study. Second, the annual land area was obtained to characterize the coastline dynamic and a linear regression model was used for estimating the change rate. We also analyzed the potential driving factors of the observed coastline change. The results reveal that the coastline in the State of Texas changed at a rate of -0.154 ± 0.063 km2/year from 1986 to 2015, which indicates that the coastline has mainly experienced an erosion over the past three decades. Specifically, 52.58% of the entire coastline retreated to the land while a 47.42% portion advanced to the ocean. Long-term sea level rise can result in the erosion of coastline. Hurricane occurrences can explain the relatively strong coastline erosion. Besides, significant difference between the coastline change rate with a higher curvature and a lower curvature was observed. This study establishes a general method for detecting coastline change at large spatial and long-term temporal scales, by using remote sensing that can give fundamental information on coastline change. This is important for making scientific and reasonable policies of sustainable development of coastal zones. [ABSTRACT FROM AUTHOR]

The widespread tectonic and magmatic events in Southeast China during the Mesozoic were accompanied by large‐scale metallogenesis. Here, we investigate the petrology, geochemistry, and zircon U–Pb age of the porphyry dykes in relation to the gold mineralization at Dongyang deposit in the Fujian Province. The geochemical data show silica‐rich and Mg‐ and Ca‐poor A‐type granite affinity for the dykes. The rocks have high concentrations of Light Rare Earth Elements (LREE) and Large Ion Lithophile Elements (LILE) and relatively low contents of Heavy Rare Earth Elements (HREE) and High Field Strength Element (HFSE). They display (La/Yb)N and (La/Sm)N values in the range of 5.7 to 31.4 and 6.0 to 8.3, respectively, with negative anomalies of Ba, Nb, Ta, Sr, Zr, Eu, and Ti and positive Ce anomaly. The source magma for the dykes was derived from a mixture of partially melted Al‐rich crustal material, with an input of mantle components. We present sensitive high‐resolution ion microprobe zircon U–Pb data from the dykes, which show emplacement ages in the range of 158 to 162 Ma, coinciding with the onset of the Yanshanian magmatism in Southeast China. Integrating the data obtained from studies on geology, geochronology and petro‐geochemistry, we suggest that the dykes played role in controlling the gold mineralization, and the magmatism and gold mineralization are the response of continental lithosphere thinning in Southeast China triggered by the subduction of the ancient Pacific Ocean Plate. [ABSTRACT FROM AUTHOR]