Step feature line extraction from large-scale point clouds of open-pit mine based on structural characteristics.

High-precision step feature lines play a crucial role in open-pit mine design, production scheduling, mining volume calculations, road network planning, and slope maintenance. Compared with the feature lines of the geometric model, step feature lines are more irregular, complex, higher in density, and richer in detail. In this study, a novel technique for extracting step feature line from large-scale point clouds of open-pit mine by leveraging structural attributes, that is, SFLE_OPM (Step Feature Line Extraction for Open-Pit Mine), is proposed. First, we adopt the k-dimensional tree (KD-tree) resampling method to reduce the point-cloud density while retaining point-cloud features and utilize bilateral filtering for denoising. Second, we use Point Cloud Properties Network (PCPNET) to estimate the normal, calculate the slope and aspect, and then filter them. We then apply morphological operations to the step surface and obtain more continuous and smoother slope lines. In addition, we construct an Open-Pit Mine Step Feature Line (OPMSFL) dataset and benchmarked SFLE_OPM, achieving an accuracy score of 89.31% and true positive rate score of 80.18%. The results demonstrate that our method yields a higher extraction accuracy and precision than most of the existing methods. Our dataset is available at https://github.com/OPMDataSets/OPMSFL .

Lamin A/C deficiency-mediated ROS elevation contributes to pathogenic phenotypes of dilated cardiomyopathy in iPSC model.

Mutations in the nuclear envelope (NE) protein lamin A/C (encoded by LMNA), cause a severe form of dilated cardiomyopathy (DCM) with early-onset life-threatening arrhythmias. However, molecular mechanisms underlying increased arrhythmogenesis in LMNA-related DCM (LMNA-DCM) remain largely unknown. Here we show that a frameshift mutation in LMNA causes abnormal Ca2+ handling, arrhythmias and disformed NE in LMNA-DCM patient-specific iPSC-derived cardiomyocytes (iPSC-CMs). Mechanistically, lamin A interacts with sirtuin 1 (SIRT1) where mutant lamin A/C accelerates degradation of SIRT1, leading to mitochondrial dysfunction and oxidative stress. Elevated reactive oxygen species (ROS) then activates the Ca2+/calmodulin-dependent protein kinase II (CaMKII)-ryanodine receptor 2 (RYR2) pathway and aggravates the accumulation of SUN1 in mutant iPSC-CMs, contributing to arrhythmias and NE deformation, respectively. Taken together, the lamin A/C deficiency-mediated ROS disorder is revealed as central to LMNA-DCM development. Manipulation of impaired SIRT1 activity and excessive oxidative stress is a potential future therapeutic strategy for LMNA-DCM.

Preparation of Quaternary Ammonium Separation Material based on Coupling Agent Chloromethyl Trimethoxysilane (KH-150) and Its Adsorption and Separation Properties in Studies of Th(IV).

In this research, the authors studied the synthesis of a silicon-based quaternary ammonium material based on the coupling agent chloromethyl trimethoxysilane (KH-150) as well as its adsorption and separation properties for Th(IV). Using FTIR and NMR methods, the silicon-based materials before and after grafting were characterized to determine the spatial structure of functional groups in the silicon-based quaternary ammonium material SG-CTSQ. Based on this, the functional group grafting amount (0.537 mmol·g-1) and quaternization rate (83.6%) of the material were accurately calculated using TGA weight loss and XPS. In the adsorption experiment, the four materials with different grafting amounts showed different degrees of variation in their adsorption of Th(IV) with changes in HNO3 concentration and NO3- concentration but all exhibited a tendency toward anion exchange. The thermodynamic and kinetic experimental results demonstrated that materials with low grafting amounts (SG-CTSQ1 and SG-CTSQ2) tended to physical adsorption of Th(IV), while the other two tended toward chemical adsorption. The adsorption mechanism experiment further proved that the functional groups achieve the adsorption of Th(IV) through an anion-exchange reaction. Chromatographic column separation experiments showed that SG-CTSQ has a good performance in U-Th separation, with a decontamination factor for uranium in Th(IV) of up to 385.1, and a uranium removal rate that can reach 99.75%.

TG-Net: Using text prompts for improved skin lesion segmentation.

Automatic skin segmentation is an efficient method for the early diagnosis of skin cancer, which can minimize the missed detection rate and treat early skin cancer in time. However, significant variations in texture, size, shape, the position of lesions, and obscure boundaries in dermoscopy images make it extremely challenging to accurately locate and segment lesions. To address these challenges, we propose a novel framework named TG-Net, which exploits textual diagnostic information to guide the segmentation of dermoscopic images. Specifically, TG-Net adopts a dual-stream encoder-decoder architecture. The dual-stream encoder comprises Res2Net for extracting image features and our proposed text attention (TA) block for extracting textual features. Through hierarchical guidance, textual features are embedded into the process of image feature extraction. Additionally, we devise a multi-level fusion (MLF) module to merge higher-level features and generate a global feature map as guidance for subsequent steps. In the decoding stage of the network, local features and the global feature map are utilized in three multi-scale reverse attention modules (MSRA) to produce the final segmentation results. We conduct extensive experiments on three publicly accessible datasets, namely ISIC 2017, HAM10000, and PH2. Experimental results demonstrate that TG-Net outperforms state-of-the-art methods, validating the reliability of our method. Source code is available at https://github.com/ukeLin/TG-Net.

Melt-electrowriting-enabled anisotropic scaffolds loaded with valve interstitial cells for heart valve tissue Engineering.

Tissue engineered heart valves (TEHVs) demonstrates the potential for tissue growth and remodel, offering particular benefit for pediatric patients. A significant challenge in designing functional TEHV lies in replicating the anisotropic mechanical properties of native valve leaflets. To establish a biomimetic TEHV model, we employed melt-electrowriting (MEW) technology to fabricate an anisotropic PCL scaffold. By integrating the anisotropic MEW-PCL scaffold with bioactive hydrogels (GelMA/ChsMA), we successfully crafted an elastic scaffold with tunable mechanical properties closely mirroring the structure and mechanical characteristics of natural heart valves. This scaffold not only supports the growth of valvular interstitial cells (VICs) within a 3D culture but also fosters the remodeling of extracellular matrix of VICs. The in vitro experiments demonstrated that the introduction of ChsMA improved the hemocompatibility and endothelialization of TEHV scaffold. The in vivo experiments revealed that, compared to their non-hydrogel counterparts, the PCL-GelMA/ChsMA scaffold, when implanted into SD rats, significantly suppressed immune reactions and calcification. In comparison with the PCL scaffold, the PCL-GelMA/ChsMA scaffold exhibited higher bioactivity and superior biocompatibility. The amalgamation of MEW technology and biomimetic design approaches provides a new paradigm for manufacturing scaffolds with highly controllable microstructures, biocompatibility, and anisotropic mechanical properties required for the fabrication of TEHVs.

Not exclusively the activity, but the sweet spot: a dehydrogenase point mutation synergistically boosts activity, substrate tolerance, thermal stability and yield.

Catalytic activity is undoubtedly a key focus in enzyme engineering. The complicated reaction conditions hinder some enzymes from industrialization even though they have relatively promising activity. This has occurred to some dehydrogenases. Hydroxysteroid dehydrogenases (HSDHs) specifically catalyze the conversion between hydroxyl and keto groups, and hold immense potential in the synthesis of steroid medicines. We underscored the importance of 7α-HSDH activity, and analyzed the overall robustness and underlying mechanisms. Employing a high-throughput screening approach, we comprehensively assessed a mutation library, and obtained a mutant with enhanced enzymatic activity and overall stability/tolerance. The superior mutant (I201M) was identified to harbor improved thermal stability, substrate susceptibility, cofactor affinity, as well as the yield. This mutant displayed a 1.88-fold increase in enzymatic activity, a 1.37-fold improvement in substrate tolerance, and a 1.45-fold increase in thermal stability when compared with the wild type (WT) enzyme. The I201M mutant showed a 2.25-fold increase in the kcat/KM ratio (indicative of a stronger binding affinity for the cofactor). This mutant did not exhibit the highest enzyme activity compared with all the tested mutants, but these improved characteristics contributed synergistically to the highest yield. When a substrate at 100 mM was present, the 24 h yield by I201M reached 89.7%, significantly higher than the 61.2% yield elicited by the WT enzyme. This is the first report revealing enhancement of the catalytic efficiency, cofactor affinity, substrate tolerance, and thermal stability of NAD(H)-dependent 7α-HSDH through a single-point mutation. The mutated enzyme reached the highest enzymatic activity of 7α-HSDH ever reported. High enzymatic activity is undoubtedly crucial for enabling the industrialization of an enzyme. Our findings demonstrated that, when compared with other mutants boasting even higher enzymatic activity, mutants with excellent overall robustness were superior for industrial applications. This principle was exemplified by highly active enzymes such as 7α-HSDH.

[Screening of immune related gene and survival prediction of lung adenocarcinoma patients based on LightGBM model].

Lung cancer is one of the malignant tumors with the greatest threat to human health, and studies have shown that some genes play an important regulatory role in the occurrence and development of lung cancer. In this paper, a LightGBM ensemble learning method is proposed to construct a prognostic model based on immune relate gene (IRG) profile data and clinical data to predict the prognostic survival rate of lung adenocarcinoma patients. First, this method used the Limma package for differential gene expression, used CoxPH regression analysis to screen the IRG to prognosis, and then used XGBoost algorithm to score the importance of the IRG features. Finally, the LASSO regression analysis was used to select IRG that could be used to construct a prognostic model, and a total of 17 IRG features were obtained that could be used to construct model. LightGBM was trained according to the IRG screened. The K-means algorithm was used to divide the patients into three groups, and the area under curve (AUC) of receiver operating characteristic (ROC) of the model output showed that the accuracy of the model in predicting the survival rates of the three groups of patients was 96%, 98% and 96%, respectively. The experimental results show that the model proposed in this paper can divide patients with lung adenocarcinoma into three groups [5-year survival rate higher than 65% (group 1), lower than 65% but higher than 30% (group 2) and lower than 30% (group 3)] and can accurately predict the 5-year survival rate of lung adenocarcinoma patients.

[Multi-classification prediction model of lung cancer tumor mutation burden based on residual network].

Medical studies have found that tumor mutation burden (TMB) is positively correlated with the efficacy of immunotherapy for non-small cell lung cancer (NSCLC), and TMB value can be used to predict the efficacy of targeted therapy and chemotherapy. However, the calculation of TMB value mainly depends on the whole exon sequencing (WES) technology, which usually costs too much time and expenses. To deal with above problem, this paper studies the correlation between TMB and slice images by taking advantage of digital pathological slices commonly used in clinic and then predicts the patient TMB level accordingly. This paper proposes a deep learning model (RCA-MSAG) based on residual coordinate attention (RCA) structure and combined with multi-scale attention guidance (MSAG) module. The model takes ResNet-50 as the basic model and integrates coordinate attention (CA) into bottleneck module to capture the direction-aware and position-sensitive information, which makes the model able to locate and identify the interesting positions more accurately. And then, MSAG module is embedded into the network, which makes the model able to extract the deep features of lung cancer pathological sections and the interactive information between channels. The cancer genome map (TCGA) open dataset is adopted in the experiment, which consists of 200 pathological sections of lung adenocarcinoma, including 80 data samples with high TMB value, 77 data samples with medium TMB value and 43 data samples with low TMB value. Experimental results demonstrate that the accuracy, precision, recall and F1 score of the proposed model are 96.2%, 96.4%, 96.2% and 96.3%, respectively, which are superior to the existing mainstream deep learning models. The model proposed in this paper can promote clinical auxiliary diagnosis and has certain theoretical guiding significance for TMB prediction.

Carbon-Encapsulated Magnetite Nanodoughnut as a NIR-II Responsive Nanozyme for Synergistic Chemodynamic-Photothermal Therapy.

Magnetite-based nanozymes have attracted great interest for catalytic cancer therapy enabled by catalyzing hydrogen peroxide (H2 O2 ) to produce highly toxic hydroxyl radicals (•OH) to kill tumor cells. However, their therapeutic efficacies remain low due to insufficient •OH. Here, a light-responsive carbon-encapsulated magnetite nanodoughnuts (CEMNDs) with dual-catalytic activities for photothermal-enhanced chemodynamic therapy (CDT) is reported. The CEMNDs can accumulate in tumor and get into tumor cells and effectively act as peroxidase to convert H2 O2 to •OH that causes tumor cell death. The CEMNDs also possess intrinsic glutathione oxidase-like activity that which catalyzes the oxidation of reduced glutathione and produce lipid peroxidase for enhanced catalytic therapy. Furthermore, the CEMNDs can absorb 1064 nm light to elevate local temperature and increase release of Fe ions for photothermal therapy and enhanced CDT respectively. The in vivo experiments in an aggressive and drug-resistant metastatic mouse model of triple negative breast cancer model demonstrate excellent synergistic anti-tumor function and no measurable systemic toxicity of CEMNDs.

Characteristic analysis of epileptic brain network based on attention mechanism.

Constructing an efficient and accurate epilepsy detection system is an urgent research task. In this paper, we developed an EEG-based multi-frequency multilayer brain network (MMBN) and an attentional mechanism based convolutional neural network (AM-CNN) model to study epilepsy detection. Specifically, based on the multi-frequency characteristics of the brain, we first use wavelet packet decomposition and reconstruction methods to divide the original EEG signals into eight frequency bands, and then construct MMBN through correlation analysis between brain regions, where each layer corresponds to a specific frequency band. The time, frequency and channel related information of EEG signals are mapped into the multilayer network topology. On this basis, a multi-branch AM-CNN model is designed, which completely matches the multilayer structure of the proposed brain network. The experimental results on public CHB-MIT datasets show that eight frequency bands divided in this work are all helpful for epilepsy detection, and the fusion of multi-frequency information can effectively decode the epileptic brain state, achieving accurate detection of epilepsy with an average accuracy of 99.75%, sensitivity of 99.43%, and specificity of 99.83%. All of these provide reliable technical solutions for EEG-based neurological disease detection, especially for epilepsy detection.

Hydrophobic Carbon Dots Derived from Organic Pollutants and Applications in NIR Anticounterfeiting and Bioimaging.

In an effort to fulfill the strategy of sustainable development, Rhodamine B, a common and toxic organic pollutant in the textile industry, was reported for the first time as a single precursor to develop a kind of novel hydrophobic nitrogen-doped carbon dot (HNCD) through a green and facile one-pot solvothermal method. The HNCDs with an average size of 3.6 nm possess left and right water contact angles of 109.56° and 110.34°, respectively. The HNCDs manifest excitation wavelength-tunable and upconverted fluorescence from the ultraviolet (UV) to the near-infrared (NIR) range. Furthermore, the PEGylation of HNCDs enables them to be used as an optical marker for cell and in vivo imaging. Notably, the HNCDs with solvent-dependent fluorescence can be used for invisible inks with a wide range of light responses from UV-vis-NIR spectra. This work not only provides an innovative way to recycle chemical waste but also expands the potential application of HNCDs in NIR security printing and bioimaging.

Octahedral/Tetrahedral Vacancies in Fe3 O4 as K-Storage Sites: A Case of Anti-Spinel Structure Material Serving as High-Performance Anodes for PIBs.

Potassium-ion batteries (PIBs) have attracted more and more attention as viable alternatives to lithium-ion batteries (LIBs) due to the deficiency and uneven distribution of lithium resources. However, it is shown that potassium storage in some compounds through reaction or intercalation mechanisms cannot effectively improve the capacity and stability of anodes for PIBs. The unique anti-spinel structure of magnetite (Fe3 O4 ) is densely packed with thirty-two O atoms to form a face-centered cubic (fcc) unit cell with tetrahedral/octahedral vacancies in the O-closed packing structure, which can serve as K+ storage sites according to the density functional theory (DFT) calculation results. In this work, carbon-coated Fe3 O4 @C nanoparticles are prepared as high-performance anodes for PIBs, which exhibit high reversible capacity (638 mAh g-1 at 0.05 A g-1 ) and hyper stable cycling performance at ultrahigh current density (150 mAh g-1 after 9000 cycles at 10 A g-1 ). In situ XRD, ex-situ Fe K-edge XAFS, and DFT calculations confirm the storage of K+ in tetrahedral/octahedral vacancies.

Surface Site-Specific Replacement for Catalysis Selectivity Switching.

Surface atom replacement in materials without other composition/structure changes is challenging but is important for fundamental scientific research and for practical applications. In particular, for nanoparticles including nanoclusters, surface metal site-specific replacement with atomic precision has not yet been achieved. In this study, we for the first time achieved surface site-specific antigalvanic replacement with the remaining composition/structure and surface replacement-dependent selectivity in the electrocatalytic reduction of CO2. Density functional theory (DFT) calculations describe the catalysis selectivity switch induced by replacing Ag with Cu and explain why Cu replacement facilitates C2 production. Also, CO2 electroreduction to C2 on well-defined metal nanoclusters is first reported in this study.

Spike-based adenovirus vectored COVID-19 vaccine does not aggravate heart damage after ischemic injury in mice.

An unprecedented number of COVID-19 vaccination campaign are under way worldwide. The spike protein of SARS-CoV-2, which majorly binds to the host receptor angiotensin converting enzyme 2 (ACE2) for cell entry, is used by most of the vaccine as antigen. ACE2 is highly expressed in the heart and has been reported to be protective in multiple organs. Interaction of spike with ACE2 is known to reduce ACE2 expression and affect ACE2-mediated signal transduction. However, whether a spike-encoding vaccine will aggravate myocardial damage after a heart attack via affecting ACE2 remains unclear. Here, we demonstrate that cardiac ACE2 is up-regulated and protective after myocardial ischemia/reperfusion (I/R). Infecting human cardiac cells or engineered heart tissues with a spike-based adenovirus type-5 vectored COVID-19 vaccine (AdSpike) does not affect their survival and function, whether subjected to hypoxia-reoxygenation injury or not. Furthermore, AdSpike vaccination does not aggravate heart damage in wild-type or humanized ACE2 mice after I/R injury, even at a dose that is ten-fold higher as used in human. This study represents the first systematic evaluation of the safety of a leading COVID-19 vaccine under a disease context and may provide important information to ensure maximal protection from COVID-19 in patients with or at risk of heart diseases.

NIR-II responsive PEGylated nickel nanoclusters for photothermal enhanced chemodynamic synergistic oncotherapy.

Rationale: All kinds of non-metal and metal-based nanozymes have been extensively explored as Fenton agents for Chemodynamic therapy (CDT). However, the low catalytic efficiency of non-metallic nanozymes and the susceptibility to oxidation and long-term toxicity of metallo-nanozymes limit their potential in CDT. Methods: In this study, we report a magneto-solvothermal method to tune the crystallinity and shape of polyethylene glycol (PEG)-ylated urchin-like nickel nanoclusters (named as 9T-PUNNC) at a high magnetic field with an intensity of 9 T for enhanced combined photothermal-chemodynamic therapy. Results: The needle-like protrusions on the surface of 9T-PUNNC can effectively increase the reception of NIR light in second NIR window (NIR-II) and transform it into local hyperthermia, achieving effective photothermal treatment. The light and heat generated by NIR-II further promotes the release of Ni2+ and improves the ability of Ni2+-mediated chemodynamic therapy (CDT). In addition, the surface coating of PEG on the surface of 9T-PUNNC improves its stability and biocompatibility of nanocrystals. In vitro and in vivo results indicate that the 9T-PUNNC could efficiently kill tumor cells (nearly 12 times more than control group) and inhibit tumor growth (nearly 9 times smaller than control group) under NIR-II irradiation through the synergistic effect of combined treatments. Conclusions: we developed a novel synthetic strategy to tune crystallinity and shape of PUNNC for enhanced NIR-II responsive photothermal conversion efficiency and accelerated acid-induced dissolution for improved ·OH generation. Such 9T-PUNNC enable a combined chemodynamic-photothermal treatment to provide superior therapeutic efficacy due to their highly synergistic effect.

Ultrasmall Cu Nanocrystals Dispersed in Nitrogen-Doped Carbon as Highly Efficient Catalysts for CO2 Electroreduction.

The electroreduction of carbon dioxide (CO2) to a liquid product is a viable method for establishing an artificial carbon cycle. Unfortunately, most electrocatalysts' low efficiency and instability prevent them from being used in practical applications. In the current study, we developed ultrasmall Cu nanocrystals embedded in nitrogen-doped carbon nanosheets (Cu/NC-NSs) for selective CO2 electroreduction by adjusting the potential. Cu/NC-NSs had 43.7 and 63.5% Faradaic efficiencies for the synthesis of ethanol and formate with applied potentials of -0.37 and -0.77 V vs reversible hydrogen electrode (RHE) using a flow cell architecture, respectively. Moreover, these Cu/NC-NSs show a steady catalytic performance up to 16 h. Density functional theory (DFT) calculations were performed to investigate the reaction mechanism. Furthermore, the synergistic effect formed by nitrogen-doped carbon and highly dispersed copper atoms led to their excellent performance in CO2 electroreduction.

Hollow Cuprous Oxide@Nitrogen-Doped Carbon Nanocapsules for Cascade Chemodynamic Therapy.

Cuprous-based nanozymes have demonstrated great potential for cascade chemodynamic therapy (CDT) due to their higher catalytic efficiency and simple reaction conditions. Here, hollow cuprous oxide@nitrogen-doped carbon (HCONC) dual-shell structures are designed as nanozymes for CDT oncotherapy. This HCONC with a size distribution of 130 nm is synthesized by a one-step hydrothermal method using cupric nitrate and dimethyl formamide as precursors. The thin-layer carbon (1.88 nm) of HCONC enhances the water-stability and reduces the systemic toxicity of cuprous oxide nanocrystals. The dissolved Cu+ of HCONC in acid solution induces a Fenton-like reaction and exhibits a fast reaction rate for catalyzing H2 O2 into highly toxic hydroxyl radicals (·OH). Meanwhile, the formed Cu+ consumes oversaturated glutathione (GSH) to avoid its destruction of ROS at the intracellular level. In general, both cellular and animal experiments show that HCONC demonstrates excellent antitumor ability without causing significant systemic toxicity, which may present tremendous potential for clinical cancer therapy.

In situ immobilization of silver nanocrystals in carbon nanoparticles for intracellular fluorescence imaging and hydroxyl radicals detection.

Silver nanoparticles (Ag NPs) have attracted extensive research interest in bioimaging and biosensing due to their unique surface plasmon resonance. However, the potential aggregation and security anxiety of Ag NPs hinder their further application in biomedical field due to their high surface energy and the possible ionization. Here, binary heterogeneous nanocomplexes constructed from silver nanoparticles and carbon nanomaterials (termed as C-Ag NPs) were reported. The C-Ag NPs with multiple yolk structure were synthesized via a one-step solvothermal route using toluene as carbon precursor and dispersant. The hydrophilic functional groups on the carbon layer endowed the C-Ag NPs excellent chemical stability and water-dispersity. Results showed that C-Ag NPs demonstrated excellent safety profile and excellent biocompatibility, which could be used as an intracellular imaging agent. Moreover, the C-Ag NPs responded specifically to hydroxyl radicals and were expected to serve as a flexible sensor to efficiently detect diseases related to the expression of hydroxyl radicals in the future.

NIR-II Responsive Hollow Magnetite Nanoclusters for Targeted Magnetic Resonance Imaging-Guided Photothermal/Chemo-Therapy and Chemodynamic Therapy.

Phototherapy in the second near-IR (1000-1700 nm, NIR-II) window has achieved much progress because of its high efficiency and relatively minor side effects. In this paper, a new NIR-II responsive hollow magnetite nanocluster (HMNC) for targeted and imaging-guided cancer therapy is reported. The HMNC not only provides a hollow cavity for drug loading but also serves as a contrast agent for tumor-targeted magnetic resonance imaging. The acid-induced dissolution of the HMNCs can trigger a pH-responsive drug release for chemotherapy and catalyze the hydroxyl radical (·OH) formation from the decomposition of hydrogen peroxide for chemodynamic therapy. Moreover, the HMNCs can adsorb and convert NIR-II light into local heat (photothermal conversion efficacy: 36.3%), which can accelerate drug release and enhance the synergistic effect of chemo-photothermal therapy. The HMNCs show great potential as a versatile nanoplatform for targeted imaging-guided trimodal cancer therapy.