Protein-protein interactions are a pivotal component of many biological processes and mediate a variety of functions. Knowing the tertiary structure of a protein complex is therefore essential for ...understanding the interaction mechanism. However, experimental techniques to solve the structure of the complex are often found to be difficult. To this end, computational protein-protein docking approaches can provide a useful alternative to address this issue. Prediction of docking conformations relies on methods that effectively capture shape features of the participating proteins while giving due consideration to conformational changes that may occur.
We present a novel protein docking algorithm based on the use of 3D Zernike descriptors as regional features of molecular shape. The key motivation of using these descriptors is their invariance to transformation, in addition to a compact representation of local surface shape characteristics. Docking decoys are generated using geometric hashing, which are then ranked by a scoring function that incorporates a buried surface area and a novel geometric complementarity term based on normals associated with the 3D Zernike shape description. Our docking algorithm was tested on both bound and unbound cases in the ZDOCK benchmark 2.0 dataset. In 74% of the bound docking predictions, our method was able to find a near-native solution (interface C-alphaRMSD < or = 2.5 A) within the top 1000 ranks. For unbound docking, among the 60 complexes for which our algorithm returned at least one hit, 60% of the cases were ranked within the top 2000. Comparison with existing shape-based docking algorithms shows that our method has a better performance than the others in unbound docking while remaining competitive for bound docking cases.
We show for the first time that the 3D Zernike descriptors are adept in capturing shape complementarity at the protein-protein interface and useful for protein docking prediction. Rigorous benchmark studies show that our docking approach has a superior performance compared to existing methods.
Tunnel boring machine (TBM) vibration induced by cutting complex ground contains essential information that can help engineers evaluate the interaction between a cutterhead and the ground itself. In ...this study, deep recurrent neural networks (RNNs) and convolutional neural networks (CNNs) were used for vibration-based working face ground identification. First, field monitoring was conducted to obtain the TBM vibration data when tunneling in changing geological conditions, including mixed-face, homogeneous, and transmission ground. Next, RNNs and CNNs were utilized to develop vibration-based prediction models, which were then validated using the testing dataset. The accuracy of the long short-term memory (LSTM) and bidirectional LSTM (Bi-LSTM) models was approximately 70% with raw data; however, with instantaneous frequency transmission, the accuracy increased to approximately 80%. Two types of deep CNNs, GoogLeNet and ResNet, were trained and tested with time-frequency scalar diagrams from continuous wavelet transformation. The CNN models, with an accuracy greater than 96%, performed significantly better than the RNN models. The ResNet-18, with an accuracy of 98.28%, performed the best. When the sample length was set as the cutterhead rotation period, the deep CNN and RNN models achieved the highest accuracy while the proposed deep CNN model simultaneously achieved high prediction accuracy and feedback efficiency. The proposed model could promptly identify the ground conditions at the working face without stopping the normal tunneling process, and the TBM working parameters could be adjusted and optimized in a timely manner based on the predicted results.
•A field monitoring was conducted to obtain the TBM vibration dataset in changing ground.•Deep RNN and CNN algorithms were applied to TBM vibration-based ground identification models.•The ResNet-18 model can achieve a high prediction accuracy and feedback efficiency.•The proposed deep learning-based framework can guide TBM tunneling in difficult ground.
Paclitaxel (PTX) is one of the widely used chemotherapy drugs in breast cancer (BC) treatment. Unfortunately, the survival rate of metastatic BC patients remains poor due to PTX resistance. ...Therefore, uncovering the underlying mechanism behind the PTX resistance of BC cells is crucial for BC therapy.
The enrichment of circular RNA ATP binding cassette subfamily B member 10 (circ-ABCB10), let-7a-5p and dual specificity phosphatase 7 (DUSP7) was measured by quantitative real time polymerase chain reaction (qRT-PCR) in PTX-resistant and PTX-sensitive BC tissues and cells. Chemoresistance, apoptosis, invasion and autophagy of BC cells were measured by 3-(4, 5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), flow cytometry, transwell invasion assay and Western blot assay, respectively. The binding sites between let-7a-5p and circ-ABCB10 or DUSP7 were predicted by Starbase bioinformatic software, and the combination was confirmed by dual-luciferase reporter assay. The protein expression of DUSP7 was examined by Western blot assay. Murine xenograft model was established to confirm the role of circ-ABCB10 in vivo.
Circ-ABCB10 depletion promoted the PTX sensitivity and apoptosis while suppressed the invasion and autophagy of PTX-resistant BC cells. Circ-ABCB10 could bind to let-7a-5p in BC cells, and circ-ABCB10 contributed to PTX resistance of BC cells via let-7a-5p. DUSP7 is a direct target of let-7a-5p in BC cells, and the accumulation of DUSP7 reversed the promoting effects of let-7a-5p overexpression on the PTX sensitivity and apoptosis and the inhibitory impact on the invasion and autophagy of PTX-resistant BC cells. Circ-ABCB10 interference suppressed the growth of BC tumors in vivo.
Circ-ABCB10 mediated PTX resistance, apoptosis, invasion and autophagy of BC cells via let-7a-5p/DUSP7 axis.
Published emission factors (EFs) often vary significantly, leading to high uncertainties in emission estimations. There are few reliable EFs from field measurements of residential wood combustion in ...China. In this study, 17 wood fuels and one bamboo were combusted in a typical residential stove in rural China to measure realistic EFs of particulate matter (PM), organic carbon (OC), and elemental carbon (EC), as well as to investigate the influence of fuel properties and combustion conditions on the EFs. Measured EFs of PM, OC, and EC (EFPM, EFOC, and EFEC, respectively) were in the range of 0.38–6.4, 0.024–3.0, and 0.039–3.9 g/kg (dry basis), with means and standard derivation of 2.2 ± 1.2, 0.62 ± 0.64, and 0.83 ± 0.69 g/kg, respectively. Shrubby biomass combustion produced higher EFs than tree woods, and both species had lower EFs than those of indoor crop residue burning (p < 0.05). Significant correlations between EFPM, EFOC, and EFEC were expected. By using a nine-stage cascade impactor, it was shown that size distributions of PM emitted from tree biomass combustions were unimodal with peaks at a diameter less than 0.4 μm (PM0.4), much finer than the PM from indoor crop residue burning. Approximately 79.4% of the total PM from tree wood combustion was PM with a diameter less than 2.1 μm (PM2.1). PM size distributions for shrubby biomasses were slightly different from those for tree fuels. On the basis of the measured EFs, total emissions of PM, OC, and EC from residential wood combustion in rural China in 2007 were estimated at about 303, 75.7, and 92.0 Gg.
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SH-MCM-41 was examined in adsorption and desorption experiments to investigate the adsorption capacities of La3+, Gd3+ and Yb3+ and the reusability.
Sulfhydryl MCM-41 (SH-MCM-41) ...mesoporous materials were prepared via a hydrothermal method, and -SH was successfully imported by a post-grafting method. The structure and surface properties of the materials were characterized using Fourier Transform infrared spectroscopy, X-ray diffraction and Transmission Electron Microscopy analysis. The low concentrations of La3+, Gd3+ and Yb3+ adsorption on the material were investigated. This paper discusses the effects of system factors, such as pH and the solid-liquid ratio, on the performance of the adsorption process. The adsorption thermodynamics and kinetics were also explored. Experimental results indicated that the materials were in good order and had high specific surface area (956 m2/g) with an average pore diameter of 2.1 nm; the mercapto groups were successfully grafted onto a molecular sieve, and the best grafted amount was 1.46 × 10−3 mol/g. The materials showed preferable adsorption of La3+, Gd3+ and Yb3+ with maximum adsorption capacities of 560.56 mg/g, 467.60 mg/g and 540.68 mg/g, respectively. The adsorption process can be described by the Freundlich isotherm model, and the adsorption data fits pseudo-second-order kinetics. After repeating the elution-regeneration cycle four times, the adsorption capacity of rare earth ions was mostly maintained, indicating that the adsorbent can be regenerated well and recycled to save costs. It has potential in practical application.
Targeted nucleases, including zinc-finger nucleases (ZFNs), transcription activator-like (TAL) effector nucleases (TALENs) and clustered regularly interspaced short palindromic repeat ...(CRISPR)/CRISPR-associated protein 9 (Cas9), have provided researchers with the ability to manipulate nearly any genomic sequence in human cells and model organisms. However, realizing the full potential of these genome-modifying technologies requires their safe and efficient delivery into relevant cell types. Unlike methods that rely on expression from nucleic acids, the direct delivery of nuclease proteins to cells provides rapid action and fast turnover, leading to fewer off-target effects while maintaining high rates of targeted modification. These features make nuclease protein delivery particularly well suited for precision genome engineering. Here we describe procedures for implementing protein-based genome editing in human embryonic stem cells and primary cells. Protocols for the expression, purification and delivery of ZFN proteins, which are intrinsically cell-permeable; TALEN proteins, which can be internalized via conjugation with cell-penetrating peptide moieties; and Cas9 ribonucleoprotein, whose nucleofection into cells facilitates rapid induction of multiplexed modifications, are described, along with procedures for evaluating nuclease protein activity. Once they are constructed, nuclease proteins can be expressed and purified within 6 d, and they can be used to induce genomic modifications in human cells within 2 d.
Abstract
With the continuous advancement and upgrading of human space exploration, the complexity and difficulty of space missions are increasing. Space manipulation, rendezvous and docking, and ...situation awareness of non cooperative targets have become important components of space missions. Relative position and attitude navigation system is an important part of space rendezvous and docking and space manipulation system. At present, the method of matching with cooperative target is mainly used for high-precision relative position and attitude measurement.
This paper introduces a method of matching solid-state lidar with high-precision cooperative target for attitude determination. First, a design method of three-dimensional cooperative target is carried out, and then a mathematical model of target recognition is constructed. Three criteria for recognition and matching are proposed. In the third part of the article, the specific process of this method is introduced, and experimental verification is carried out. The experiment shows that the method can achieve the position measurement accuracy of 0.006m and the attitude measurement accuracy of 0.15 ° , and has important application value in various high-precision space missions.
The primary imaging markers for idiopathic Normal Pressure Hydrocephalus (iNPH) emphasize morphological measurements within the ventricular system, with no attention given to alterations in brain ...parenchyma. This study aimed to investigate the potential effectiveness of combining ventricular morphometry and cortical structural measurements as diagnostic biomarkers for iNPH.
A total of 57 iNPH patients and 55 age-matched healthy controls (HC) were recruited in this study. Firstly, manual measurements of ventricular morphology, including Evans Index (EI), z-Evans Index (z-EI), Cella Media Width (CMW), Callosal Angle (CA), and Callosal Height (CH), were conducted based on MRI scans. Cortical thickness measurements were obtained, and statistical analyses were performed using surface-based morphometric analysis. Secondly, three distinct models were developed using machine learning algorithms, each based on a different input feature: a ventricular morphology model (LVM), a cortical thickness model (CT), and a fusion model (All) incorporating both features. Model performances were assessed using 10-fold cross validation and tested on an independent dataset. Model interpretation utilized Shapley Additive Interpretation (SHAP), providing a visualization of the contribution of each variable in the predictive model. Finally, Spearman correlation coefficients were calculated to evaluate the relationship between imaging biomarkers and clinical symptoms.
iNPH patients exhibited notable differences in cortical thickness compared to HC. This included reduced thickness in the frontal, temporal, and cingulate cortices, along with increased thickness in the supracentral gyrus. The diagnostic performance of the fusion model (All) for iNPH surpassed that of the single-feature models, achieving an average accuracy of 90.43%, sensitivity of 90.00%, specificity of 90.91%, and Matthews correlation coefficient (MCC) of 81.03%. This improvement in accuracy (6.09%), sensitivity (11.67%), and MCC (11.25%) compared to the LVM strategy was significant. Shap analysis revealed the crucial role of cortical thickness in the right isthmus cingulate cortex, emerging as the most influential factor in distinguishing iNPH from HC. Additionally, significant correlations were observed between the typical triad symptoms of iNPH patients and cortical structural alterations.
This study emphasizes the significant role of cortical structure changes in the diagnosis of iNPH, providing a novel insights for assisting clinicians in improving the identification and detection of iNPH.
Indoor combustion of crop residues for cooking or heating is one of the most important emission sources of polycyclic aromatic hydrocarbons (PAHs) in developing countries. However, data on PAH ...emission factors (EFs) for burning crop residues indoor, particularly those measured in the field, were scarce, leading to large uncertainties in the emission inventories. In this study, EFs of PAHs for nine commonly used crop residues burned in a typical Chinese rural cooking stove were measured in a simulated kitchen. The measured EFs of total PAHs averaged at 63 ± 37 mg/kg, ranging from 27 to 142 mg/kg, which were higher than those measured in chamber experiments, implying that the laboratory experiment-based emission and risk assessment should be carefully reviewed. EFs of gaseous and particulate phase PAHs were 27 ± 13 and 35 ± 23 mg/kg, respectively. Composition profiles and isomer ratios of emitted PAHs were characterized. Stepwise regressions found that modified combustion efficiency and fuel moisture were the most important factors affecting the emissions. There was 80 ± 6% of PAHs associated with PM2.5, and the mass percentage of PAHs in fine particles increased as the molecular weight increased. For freshly emitted PAHs, absorption into organic carbon, rather than adsorption, dominated the gas−particle partitioning.
Both particulate matter (PM) and black carbon (BC) impact climate change and human health. Uncertainties in emission inventories of PM and BC are partially due to large variation of measured emission ...factors (EFs) and lack of EFs from developing countries. Although there is a debate whether thermal-optically measured elemental carbon (EC) may be referred to as BC, EC is often treated as the same mass of BC. In this study, EFs of PM (EFPM) and EC (EFEC) for 9 crop residues and 5 coals were measured in actual rural cooking and coal stoves using the carbon mass balance method. The dependence of the EFs on fuel properties and combustion conditions was investigated. It was found that the mean EFPM were 8.19 ± 4.27 and 3.17 ± 4.67 g/kg and the mean EFEC were 1.38 ± 0.70 and 0.23 ± 0.36 g/kg for crop residues and coals, respectively. PM with size less than 10 μm (PM10) from crop residues were dominated by particles of aerodynamic size ranging from 0.7 to 2.1 μm, while the most abundant size ranges of PM10 from coals were either from 0.7 to 2.1 μm or less than 0.7 μm. Of various fuel properties and combustion conditions tested, fuel moisture and modified combustion efficiency (MCE) were the most critical factors affecting EFPM and EFEC for crop residues. For coal combustion, EFPM were primarily affected by MCE and volatile matter, whereas EFEC were significantly influenced by ash content, volatile matter, heat value, and MCE. It was also found that EC emissions were significantly correlated with emissions of PM with size less than 0.4 μm.
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