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Using carbon-based materials (CBMs) to facilitate phytoremediation shows great promise for simultaneously enhancing the restoration efficiency of contaminated soil and reducing carbon dioxide in the context of global warming, which is still in the exploring and attempting phase. In addition to direct degradation or alteration of pollutant bioavailability, CBMs can enhance phytoremediation by alleviating plant nutrient deprivation and oxidative stress, as well as by modulating soil microbial communities and root secretions. Photosynthetic carbon fixation predominantly affects both phytoremediation efficiency and carbon cycle turnover in terrestrial ecosystems. In this regard, CBMs have extremely positive properties in facilitating plant carbon capture, with intrinsic mechanisms including (1) promoting photosynthetic pigment synthesis and acting as artificial built-in antennae to improve photon capture efficiency, (2) accelerating the photosynthetic electron transport rate in photosystems, (3) improving the Calvin cycle, and (4) maintaining the structural integrity of chloroplasts. Besides, as an ultra-stable type of CBM derived from waste biomass, biochar can preserve the native biomass carbon in the soil environment for decades and attenuate the rhizosphere priming effect by influencing the structure of rhizosphere soil aggregates and microbial communities, thus retarding the native soil organic carbon efflux. This review critically elaborates on the mechanisms by which CBMs assist in improving the efficiency of phytoremediation and their positive effects on the plant-root soil carbon balance. Additionally, a simple full-life cycle analysis encompassing cost analysis as well as ecological, economic, and social benefits is concluded to evaluate the feasibility and sustainability of CBMs-phytoremediation systems. [ABSTRACT FROM AUTHOR]

High-speed rails with determined length and load run for long periods at almost uniform speeds along fixed routes, constituting a new stable and repeatable artificial seismic source. Studies have demonstrated the wide bands and discrete spectra of high-speed rail seismic signals. Exploring the abundant information contained in massive high-speed rail seismic signals has great application value in the safety monitoring of high-speed rail operation and subgrade. However, given the complex environment around the rail network system, field data contain not only high-speed rail seismic waves but also ambient noise and the noise generated by various human activities. The foundation and key to effectively using high-speed rail seismic signals is to extract them from field data. In this paper, we propose an adaptive variational mode decomposition (VMD)-based separation algorithm for high-speed rail seismic signals. The optimization algorithm is introduced to VMD, and sample entropy and energy difference are used to construct the fitness function for the optimal adjustment of the mode number and penalty factor. Furthermore, time–frequency analysis is performed on the extracted high-speed rail signals and field data using the synchrosqueezed wavelet transform (SSWT). After verifying the processing of simulated signals, the proposed method is applied to field data. Results show that the algorithm can effectively extract high-speed rail seismic signals and eliminate other ambient noises, providing a basis for the imaging and inversion of high-speed rail seismic waves. [ABSTRACT FROM AUTHOR]

For in situ detection via laser-induced breakdown spectroscopy (LIBS), the effect of the sample surface morphology matrix exacerbates spectral variations, leading to inaccurate and unstable analysis results, even under ideal laboratory conditions. Thus, it is essential to consider the influence of sample surface morphology on LIBS to obtain optimal detection results. Therefore, to reduce this influence, herein, we proposed spectral correction methods to correct LIBS spectra based on our previous research results on the relationship between LIBS characteristic spectral intensity and physical parameter of the sample surface morphology, where the parameter was the angle θ between the tangent of the sample surface and the horizontal direction. The results showed that the fluctuations in the corrected spectra were reduced and the relative standard deviation (RSD) was less than 10%, and the spectral intensities were close to that of the samples with a flat surface morphology. To assess the effectiveness of the proposed methods in improving the quantitative analysis accuracy, Cr, Ni, and Mn elements in standard stainless-steel samples were analyzed by partial least squares regression (PLSR). We established the model using the spectra of standard samples with a flat surface morphology as the training set, and the results showed that the accuracy was very low when the test set was the spectra of samples without a flat surface morphology, with R² of 0.781, 0.779, and 0.695 for Cr, Ni, and Mn elements, respectively. In contrast, when the test set was the corrected spectra, R2 increased to 0.950, 0.925, and 0.825 for Cr, Ni, and Mn elements, respectively, and the RMSE and MRE were reduced. When the corrected spectra of standard samples without a flat surface morphology were added to the training set, the accuracy was improved, with R² of 0.978, 0.939, and 0.929 for the three elements and their RMSE and MRE were minimum. [ABSTRACT FROM AUTHOR]

Background Purpose Methods Results Conclusion Stereotactic body radiotherapy (SBRT) is a well‐established treatment modality for liver metastases in patients unsuitable for surgery. Both CT and MRI are useful during treatment planning for accurate target delineation and to reduce potential organs‐at‐risk (OAR) toxicity from radiation. MRI‐CT deformable image registration (DIR) is required to propagate the contours defined on high‐contrast MRI to CT images. An accurate DIR method could lead to more precisely defined treatment volumes and superior OAR sparing on the treatment plan. Therefore, it is beneficial to develop an accurate MRI‐CT DIR for liver SBRT.To create a new deep learning model that can estimate the deformation vector field (DVF) for directly registering abdominal MRI‐CT images.The proposed method assumed a diffeomorphic deformation. By using topology‐preserved deformation features extracted from the probabilistic diffeomorphic registration model, abdominal motion can be accurately obtained and utilized for DVF estimation. The model integrated Swin transformers, which have demonstrated superior performance in motion tracking, into the convolutional neural network (CNN) for deformation feature extraction. The model was optimized using a cross‐modality image similarity loss and a surface matching loss. To compute the image loss, a modality‐independent neighborhood descriptor (MIND) was used between the deformed MRI and CT images. The surface matching loss was determined by measuring the distance between the warped coordinates of the surfaces of contoured structures on the MRI and CT images. To evaluate the performance of the model, a retrospective study was carried out on a group of 50 liver cases that underwent rigid registration of MRI and CT scans. The deformed MRI image was assessed against the CT image using the target registration error (TRE), Dice similarity coefficient (DSC), and mean surface distance (MSD) between the deformed contours of the MRI image and manual contours of the CT image.When compared to only rigid registration, DIR with the proposed method resulted in an increase of the mean DSC values of the liver and portal vein from 0.850 ± 0.102 and 0.628 ± 0.129 to 0.903 ± 0.044 and 0.763 ± 0.073, a decrease of the mean MSD of the liver from 7.216 ± 4.513 mm to 3.232 ± 1.483 mm, and a decrease of the TRE from 26.238 ± 2.769 mm to 8.492 ± 1.058 mm.The proposed DIR method based on a diffeomorphic transformer provides an effective and efficient way to generate an accurate DVF from an MRI‐CT image pair of the abdomen. It could be utilized in the current treatment planning workflow for liver SBRT. [ABSTRACT FROM AUTHOR]

Purpose: QT interval prolongation is one of the most common electrocardiographic (ECG) abnormalities in patients with aneurysmal subarachnoid hemorrhage (aSAH). Whether corrected QT interval (QTc) prolongation is associated with perioperative cardiac events and dismal neurological outcome in mid to long-term follow-up in patients after aSAH is insufficiently studied and remains controversial. Methods: We retrospectively studied the adult (≥ 18 years) patients admitted to our institution between Jan 2018 and Dec 2020 for aSAH who underwent intracranial aneurysm clipping or embolization. The patients were divided into 2 groups (normal and QTc prolongation groups) according to their QTc. To minimize the confounding bias, a propensity score matching (PSM) analysis was performed to compare the neurologic outcomes between patients with normal QTc and QTc prolongation. Results: After screening, 908 patients were finally included. The patients were divided into 2 groups: normal QTc groups (n = 714) and long QTc group (n = 194). Female sex, hypokalemia, posterior circulation aneurysm, and higher Hunt-Hess grade were associated with QTc prolongation. In multiple regression analysis, older age, higher hemoglobin level, posterior circulation aneurysm, and higher Hunt-Hess grade were identified to be associated with worse outcome during 1-year follow-up. Before PSM, patients with QTc prolongation had higher rate of perioperative cardiac arrest or ventricular arrhythmias. After PSM, there was no statistical difference between normal and QTc prolongation groups in perioperative cardiac events. However, patients in the QTc prolongation group still had worse neurologic outcome during 1-year follow-up. Conclusions: QTc prolongation is associated with worse outcome in patients following SAH, which is independent of perioperative cardiac events. [ABSTRACT FROM AUTHOR]

The mechanical properties of concrete, such as compressive strength CS$$ \left(\mathrm{CS}\right) $$ and slump flow SL$$ \left(\mathrm{SL}\right) $$ rates, are very nonlinear. For academics, it is crucial to forecast these qualities while creating new building methods. Such capabilities should be developed to lower the cost of expensive tests and increase the precision of the measurements. The goal of this study is to create an radial basis function neural network RBFNN$$ \left(\mathrm{RBFNN}\right) $$ to describe the characteristics of hardness in high‐performance concrete (HPC) mix. Metaheuristic techniques were used to enhance the RBFNN's functionality. A dataset of 181 HPC mixes comprising ecologically beneficial ingredients, such as fly ash and silica fume, was used for training and evaluating the capabilities of the proposed hybrid models. According to the modeling process based on sensitivity analysis of input parameters and the results of hybrid models, the model combined with the multiverse optimization algorithm (MVO) had a higher correlation between the predicted and observed CS and slump values than the model combined with three optimization algorithms in terms of the R2 index being the maximum value of 0.984 in the tasting phase of CS and SL estimation. While evaluating two mechanical aspects of HPC samples, the RMSE$$ RMSE $$ of the model coupled with the MVO algorithm reconfirmed its accuracy being 3.59. [ABSTRACT FROM AUTHOR]

This study aimed to examine the antifungal effects of nine monoterpenes on Sclerotinia sclerotiorum via the mycelial growth rate method. The effects of carvacrol on the morphological structures of hyphae were investigated by scanning electron microscopy (SEM). The oxalic acid (OA), total protein contents, and the activity of cell wall- -degrading enzymes, including chitinase, cellulase and β-1,3-glucanase, were assessed. The results showed that the antifungal rates of carvacrol, thymol and eugenol reached 100% at a concentration of 400 mg/L, and the EC50 values of carvacrol, thymol, and eugenol were 43.40, 56.22, and 86.63 mg/L, respectively. The treatment of S. sclerotiorum with carvacrol had no significant effect on sclerotia formation, but the mycelial surface was shrivelled, uneven and broken, with cytoplasm flowing out. The OA content of S. sclerotiorum was significantly reduced to 133.78 μg/mL after treatment with carvacrol. Additionally, the total protein content of S. sclerotiorum mycelia in the carvacrol treatment group was significantly reduced to 15.67 μg/mL compared with that of the control group, and the activity of cellulase in the carvacrol treatment group was significantly higher than that in the control group. [ABSTRACT FROM AUTHOR]

Synapse is the fundamental structure for neurons to transmit information between cells. The proper synapse formation is crucial for developing neural circuits and cognitive functions of the brain. The aberrant synapse formation has been proved to cause many neurological disorders, including autism spectrum disorders and intellectual disability. Synaptic cell adhesion molecules (CAMs) are thought to play a major role in achieving mechanistic cell-cell recognition and initiating synapse formation via trans-synaptic interactions. Due to the diversity of synapses in different brain areas, circuits and neurons, although many synaptic CAMs, such as Neurexins (NRXNs), Neuroligins (NLGNs), Synaptic cell adhesion molecules (SynCAMs), Leucine-rich-repeat transmembrane neuronal proteins (LRRTMs), and SLIT and NTRK-like protein (SLITRKs) have been identified as synaptogenic molecules, how these molecules determine specific synapse formation and whether other molecules driving synapse formation remain undiscovered are unclear. Here, to provide a tool for synapse labeling and synaptic CAMs screening by artificial synapse formation (ASF) assay, we generated synaptotagmin-1-tdTomato (Syt1-tdTomato) transgenic mice by inserting the tdTomatofused synaptotagmin-1 coding sequence into the genome of C57BL/6J mice. In the brain of Syt1- tdTomato transgenic mice, the tdTomato-fused synaptotagmin-1 (SYT1-tdTomato) signals were widely observed in different areas and overlapped with synapsin-1, a widely-used synaptic marker. In the olfactory bulb, the SYT1-tdTomato signals are highly enriched in the glomerulus. In the cultured hippocampal neurons, the SYT1-tdTomato signals showed colocalization with several synaptic markers. Compared to the wild-type (WT) mouse neurons, cultured hippocampal neurons from Syt1- tdTomato transgenic mice presented normal synaptic neurotransmission. In ASF assays, neurons from Syt1-tdTomato transgenic mice could form synaptic connections with HEK293T cells expressing NLGN2, LRRTM2, and SLITRK2 without immunostaining. Therefore, our work suggested that the Syt1-tdTomato transgenic mice with the ability to label synapses by tdTomato, and it will be a convenient tool for screening synaptogenic molecules. [ABSTRACT FROM AUTHOR]

This article provides an overview of gastrointestinal (GI) cancer screening in China, focusing on the past 30 years. It discusses the prevalence of GI cancers in China and their impact on global new cases and deaths. The article emphasizes the importance of early screening and diagnosis in reducing incidence and mortality rates. It also highlights the national population-based cancer screening programs implemented in China and the progress made in reducing the burden of GI cancers. The article concludes by discussing future strategies for cancer screening in China and other developing countries. [Extracted from the article]

Background: An automated, accurate, and efficient lung four‐dimensional computed tomography (4DCT) image registration method is clinically important to quantify respiratory motion for optimal motion management. Purpose: The purpose of this work is to develop a weakly supervised deep learning method for 4DCT lung deformable image registration (DIR). Methods: The landmark‐driven cycle network is proposed as a deep learning platform that performs DIR of individual phase datasets in a simulation 4DCT. This proposed network comprises a generator and a discriminator. The generator accepts moving and target CTs as input and outputs the deformation vector fields (DVFs) to match the two CTs. It is optimized during both forward and backward paths to enhance the bi‐directionality of DVF generation. Further, the landmarks are used to weakly supervise the generator network. Landmark‐driven loss is used to guide the generator's training. The discriminator then judges the realism of the deformed CT to provide extra DVF regularization. Results: We performed four‐fold cross‐validation on 10 4DCT datasets from the public DIR‐Lab dataset and a hold‐out test on our clinic dataset, which included 50 4DCT datasets. The DIR‐Lab dataset was used to evaluate the performance of the proposed method against other methods in the literature by calculating the DIR‐Lab Target Registration Error (TRE). The proposed method outperformed other deep learning‐based methods on the DIR‐Lab datasets in terms of TRE. Bi‐directional and landmark‐driven loss were shown to be effective for obtaining high registration accuracy. The mean and standard deviation of TRE for the DIR‐Lab datasets was 1.20 ± 0.72 mm and the mean absolute error (MAE) and structural similarity index (SSIM) for our datasets were 32.1 ± 11.6 HU and 0.979 ± 0.011, respectively. Conclusion: The landmark‐driven cycle network has been validated and tested for automatic deformable image registration of patients' lung 4DCTs with results comparable to or better than competing methods. [ABSTRACT FROM AUTHOR]

We study the quasinormal modes (QNM) of the charged C-metric, which physically stands for a charged accelerating black hole, with the help of Nekrasov’s partition function of 4d N = 2 superconformal field theories (SCFTs). The QNM in the charged C-metric are classified into three types: the photon-surface modes, the accelerating modes and the near-extremal modes, and it is curious how the single quantization condition proposed in [1] can reproduce all the different families. We show that the connection formula encoded in terms of Nekrasov’s partition function captures all these families of QNM numerically and recovers the asymptotic behavior of the accelerating and the near-extremal modes analytically. Using the connection formulae of different 4d N = 2 SCFTs, one can solve both the radial and the angular parts of the scalar perturbation equation respectively. The same algorithm can be applied to the de Sitter (dS) black holes to calculate both the dS modes and the photon-sphere modes. [ABSTRACT FROM AUTHOR]

Stingrays genus Hypanus currently encompasses nine valid species from the Atlantic and Pacific oceans, though the phylogenetic relationships amongst some of them were based on a single mitochondrial gene and did not involve all putative Hypanus species. To address the monophyly of the genus and its relationship to other Dasyatinae genera, we sequenced the whole mitochondrial genomes of all species that supposedly belong to this genus and representatives of Dasyatinae, Neotrygoninae, and, as an outgroup, Fontitrygon (Urogymninae). Based on phylogenetic analyses, Hypanus is the sister-genus to all other Dasyatinae, and this subfamily is closely-related to Neotrygoninae within the family Dasyatidae. The species F. geijskesi is closely related to H. guttatus rather than to its congeners and should be allocated to Hypanus as H. geijskesi for the genus monophyly. After lineage delimitation analyses, we identified three species complexes composed of H. americanus, H. guttatus, and H. say, with two distinct evolutionary lineages within each, leaving the genus with 13 evolutionary units, of which six are currently under threat and only H. sabinus is of least concern. The urgency in identifying these new lineages lies in the fact they might already be under threat before being formally described. [ABSTRACT FROM AUTHOR]

The objective of this study was to investigate the therapeutic wound healing potential and molecular mechanisms of shikonin as small molecules in vitro. A mouse burn model was used to explore the potential therapeutic effect of shikonin; we traced proliferating cells in vivo to locate the active area of skin cell proliferation. Through the results of conventional pathological staining, we found that shikonin has a good effect on the treatment of burned skin and promoted the normal distribution of skin keratin at the damaged site. At the same time, shikonin also promoted the proliferation of skin cells at the damaged site; importantly, we found a significant increase in the number of fibroblasts at the damaged site treated with shikonin. Most importantly, shikonin promotes fibroblasts to repair skin wounds by regulating the PI3K/AKT signaling pathway. This study shows that shikonin can effectively promote the proliferation of skin cell, and local injection of fibroblasts in burned skin can play a certain therapeutic role. [ABSTRACT FROM AUTHOR]

Transposable elements have created the majority of the sequence in many genomes. In mammals, LINE-1 retrotransposons have been expanding for more than 100 million years as distinct, consecutive lineages; however, the drivers of this recurrent lineage emergence and disappearance are unknown. Most human genome assemblies provide a record of this ancient evolution, but fail to resolve ongoing LINE-1 retrotranspositions. Utilizing the human CHM1 long-read-based haploid assembly, we identified and cloned all full-length, intact LINE-1s, and found 29 LINE-1s with measurable in vitro retrotransposition activity. Among individuals, these LINE- 1s varied in their presence, their allelic sequences, and their activity. We found that recently retrotransposed LINE-1s tend to be active in vitro and polymorphic in the population relative to more ancient LINE-1s. However, some rare allelic forms of old LINE-1s retain activity, suggesting older lineages can persist longer than expected. Finally, in LINE-1s with in vitro activity and in vivo fitness, we identified mutations that may have increased replication in ancient genomes and may prove promising candidates for mechanistic investigations of the drivers of LINE-1 evolution and which LINE-1 sequences contribute to human disease. [ABSTRACT FROM AUTHOR]

Objective: Non-small cell lung cancer (NSCLC) stands as a prominent contributor to cancer-related fatalities on a global scale, necessitating the search for novel therapeutic agents. SP-8356, a derivative of (1S)-(–)-verbenone, has shown promise as an anticancer agent in preclinical studies. However, specific mechanisms underlying its effects in NSCLC remain to be elucidated. The aim of this research was to explore the in vitro anti-NSCLC effects of SP-8356, elucidate its mechanisms of action, and assess its efficacy in inhibiting tumor formation in a murine model. Materials and Methods: In this experimental study, NSCLC cell lines were treated with various concentrations of SP-8356. Cell viability and proliferation were assessed using MTT and colony formation assays, respectively. Cell cycle distribution was analyzed by flow cytometry, and apoptosis was evaluated by determining apoptotic protein expression. Western blot analysis was conducted to assess protein expression levels of the both p53 and MDM2. Additionally, we evaluated efficacy of the SP-8356 in inhibiting tumor formation of the nude mouse model. Results: SP-8356 demonstrated a concentration-dependent inhibition of cell proliferation in the NSCLC cell lines. Flow cytometric analysis showed that SP-8356 led to cell cycle arrest at the G2/M phase, indicating its potential influence on regulating the cell cycle. SP-8356 treatment was associated with the downregulation of CDK1 and Cyclin B1. Additionally, SP-8356 significantly enhanced apoptosis in NSCLC cells. SP-8356 treatment was associated with the downregulation of Bcl-2, while Bax expression was upregulated. Mechanistically, SP-8356 led to accumulation of the p53 protein levels within the NSCLC cells. This accumulation was mediated through inhibition of its negative regulator, MDM2. Using a nude mouse model demonstrated that SP-8356 effectively inhibited tumor formation in vivo. Conclusion: Our findings shed light on the molecular mechanisms underlying anticancer activity of SP-8356 and highlight its potential as a promising therapeutic candidate for NSCLC treatment. [ABSTRACT FROM AUTHOR]

Porous nanocrystalline NiTi shape memory alloy (SMA) benefit from a combination of the smart responses of nanograined SMA and the characteristics of porous materials, showing great potential in the high-tech field. Porosity and grain size exert an influence on the microstructure evolution during phase transformations, thus possessing the ability to alter the transformation characteristics of NiTi SMA. To investigate the porosity and grain size-dependent superelastic behaviors of porous nanocrystalline NiTi, the constitutive model incorporating grain size effects and tensile–compressive asymmetry for dense nanocrystalline NiTi is first developed. Based on the dense SMA model, porous nanocrystalline NiTi SMA is regarded as a composite material consisting of the void phase and the SMA matrix phase. The voids are treated as inclusions embedded in the SMA matrix composed of grain core and grain boundary. Tensile–compressive asymmetry, transformation hardening modulus associated with intrinsic length scale and grain size are incorporated into the modified Gurson–Tvergaard–Needleman potential function, leading to the construction of constitutive model for porous nanocrystalline NiTi SMA. Simulated results demonstrate that the proposed model is capable to describe the characteristics of porous nanocrystalline NiTi SMA, such as grain size and porosity dependent superelasticity and tensile–compressive asymmetry. Using the developed model, the combined effects of porosity and grain size on the critical transformation stresses, strain hardening, peak stresses, tensile–compressive asymmetry behaviors and the superelastic stress–strain hysteresis loop are analyzed. [ABSTRACT FROM AUTHOR]

Grid-tied distributed generators (DGs) need to be equipped with anti-islanding protection to avoid the impact of unplanned islanding, which would affect system stability, auto-reclosing, and personal safety. Among the active anti-islanding protections, impedance measurements based on signal injection have the advantages of a low non-detection zone (NDZ) and are less prone to maloperation during grid disturbances; however, there are problems with signal interference in multi-DG systems. Hence, the impedance angle measurement method with signals injected synchronously is proposed. In this method, each DG injects phase-coherent signals to detect islanding using zero-cross points of the voltage (ZCPV) to avoid the protection failures caused by signal interference. An islanding identification criterion based on the measured impedance angle is proposed by analyzing the impedance characteristics of grid connection and islanding, which avoids the influence of variation of the DG operation state on islanding detection. Finally, we present a signal injection strategy and performance analysis in combination with an existing DG control platform, avoiding additional hardware investment. RTDS-based simulation verification shows that the proposed method can 100% avoid DG maloperation due to voltage and frequency disturbances during grid-connected operation and exit operation within 2 s when islanding occurs. [ABSTRACT FROM AUTHOR]

Allene oxide cyclase (AOC) is a key enzyme in the biosynthesis of jasmonic acid (JA), which is involved in plant growth and development as well as adaptation to environmental stresses. We identified the cold- and pathogen-responsive AOC2 gene from Medicago sativa subsp. falcata (MfAOC2) and its homolog MtAOC2 from Medicago truncatula. Heterologous expression of MfAOC2 in M. truncatula enhanced cold tolerance and resistance to the fungal pathogen Rhizoctonia solani, with greater accumulation of JA and higher transcript levels of JA downstream genes than in wild-type plants. In contrast, mutation of MtAOC2 reduced cold tolerance and pathogen resistance, with less accumulation of JA and lower transcript levels of JA downstream genes in the aoc2 mutant than in wild-type plants. The aoc2 phenotype and low levels of cold-responsive C-repeat-binding factor (CBF) transcripts could be rescued by expressing MfAOC2 in aoc2 plants or exogenous application of methyl jasmonate. Compared with wild-type plants, higher levels of CBF transcripts were observed in lines expressing MfAOC2 but lower levels of CBF transcripts were observed in the aoc2 mutant under cold conditions; superoxide dismutase, catalase, and ascorbate-peroxidase activities as well as proline concentrations were higher in MfAOC2-expressing lines but lower in the aoc2 mutant. These results suggest that expression of MfAOC2 or MtAOC2 promotes biosynthesis of JA, which positively regulates expression of CBF genes and antioxidant defense under cold conditions and expression of JA downstream genes after pathogen infection, leading to greater cold tolerance and pathogen resistance. [ABSTRACT FROM AUTHOR]

Superconformal indices of four-dimensional N = 1 gauge theories factorize into holomorphic blocks. We interpret this as a modular property resulting from the combined action of an SL(3, ℤ) and SL(2, ℤ) ⋉ ℤ2 transformation. The former corresponds to a gluing transformation and the latter to an overall large diffeomorphism, both associated with a Heegaard splitting of the underlying geometry. The extension to more general transformations leads us to argue that a given index can be factorized in terms of a family of holomorphic blocks parametrized by modular (congruence sub)groups. We find precise agreement between this proposal and new modular properties of the elliptic Γ function. This leads to our conjecture for the "modular factorization" of superconformal lens indices of general N = 1 gauge theories. We provide evidence for the conjecture in the context of the free chiral multiplet and SQED and sketch the extension of our arguments to more general gauge theories. Assuming the validity of the conjecture, we systematically prove that a normalized part of superconformal lens indices defines a non-trivial first cohomology class associated with SL(3, ℤ). Finally, we use this framework to propose a formula for the general lens space index. [ABSTRACT FROM AUTHOR]

Titanium oxo clusters are considered a model for nanotitanium dioxide and have gradually become a new field of functional materials in solar cells. In this work, the precise structural information of two types of tartrate-based titaniumoxo clusters was investigated by quantum chemical approaches. Density functional theory (DFT) and time-dependent density functional theory (TDDFT) calculations provided the precise structural parameters of Ti4(C4H2O6)(AS)2(OiPr)10 and Ti4(C4H2O6)(ATS)2(OiPr)10. Our work provided reliable results in agreement with the experimental results. In both molecules, the Ti-O bonds were mainly divided into three categories: the bonds in the first category were the coordination bonds between the central skeleton Ti atom and the tartaric acid group, whose bond lengths were 2.000 - 2.080 Å; the bonds in the second category were the coordination bond formed by the Ti atom and the oxygen on the AS ligand sulphonic acid group, whose bond lengths were 2.148 - 2.310 Å; the bonds in the third category were the Ti-O bonds with shorter bond lengths, which were the coordination bond formed by the Ti atom and the oxygen on the isopropylalkoxy group with their bond lengths in the value range from 1.777 Å to 1.795 Å. These kinds of Ti-O bonds also can be found in other Ti4 titanium-oxo clusters. Molecular orbitals showed that electron transfer from the AS/ATS ligand to the {Ti4} central skeleton was induced by sunlight with maximum UV-Vis absorption of 605/629 nm. Our calculation results provide strong guidance for the discovery of new efficient titanium oxo in solar cells. [ABSTRACT FROM AUTHOR]

Ion cyclotron waves (ICWs) are one kind of plasma waves whose frequency is close to the ion cyclotron frequency. They exist widely in the upstream of Mars, and the frequency observed by satellites is generally near the proton cyclotron frequency. ICWs are byproducts in the production processes of pick-up ions. The occurrence of ICWs constitutes, in principle, an indirect signature of the presence of newborn planetary protons. ICWs in the upstream of Mars have received much attention since they were first reported in 1990. In this review, we summarize the research progress of ICWs in the upstream of Mars, including the observation of ICWs, the wave generation mechanism, their statistical properties, and related future research trends. [ABSTRACT FROM AUTHOR]

Aerobic oxidative cross‐coupling represents one of the most straightforward and atom‐economic methods for construction of C−C and C−X (X=N, O, S, or P) bonds using air as a sustainable external oxidant. The oxidative coupling of C−H bonds in heterocyclic compounds can effectively increase their molecular complexity by introducing new functional groups through C−H bond activation, or by formation of new heterocyclic structures through cascade construction of two or more sequential chemical bonds. This is very useful as it can increase the potential applications of these structures in natural products, pharmaceuticals, agricultural chemicals, and functional materials. This is a representative overview of recent progress since 2010 on green oxidative coupling reactions of C−H bond using O2 or air as internal oxidant focus on Heterocycles. It aims to provide a platform for expanding the scope and utility of air as green oxidant, together with a brief discussion on research into the mechanisms behind it. [ABSTRACT FROM AUTHOR]

Purpose: Radiation damage on neurovascular bundles (NVBs) may be the cause of sexual dysfunction after radiotherapy for prostate cancer. However, it is challenging to delineate NVBs as organ‐at‐risks from planning CTs during radiotherapy. Recently, the integration of MR into radiotherapy made NVBs contour delineating possible. In this study, we aim to develop an MRI‐based deep learning method for automatic NVB segmentation. Methods: The proposed method, named topological modulated network, consists of three subnetworks, that is, a focal modulation, a hierarchical block and a topological fully convolutional network (FCN). The focal modulation is used to derive the location and bounds of left and right NVBs', namely the candidate volume‐of‐interests (VOIs). The hierarchical block aims to highlight the NVB boundaries information on derived feature map. The topological FCN then segments the NVBs inside the VOIs by considering the topological consistency nature of the vascular delineating. Based on the location information of candidate VOIs, the segmentations of NVBs can then be brought back to the input MRI's coordinate system. Results: A five‐fold cross‐validation study was performed on 60 patient cases to evaluate the performance of the proposed method. The segmented results were compared with manual contours. The Dice similarity coefficient (DSC) and 95th percentile Hausdorff distance (HD95) are (left NVB) 0.81 ± 0.10, 1.49 ± 0.88 mm, and (right NVB) 0.80 ± 0.15, 1.54 ± 1.22 mm, respectively. Conclusion: We proposed a novel deep learning‐based segmentation method for NVBs on pelvic MR images. The good segmentation agreement of our method with the manually drawn ground truth contours supports the feasibility of the proposed method, which can be potentially used to spare NVBs during proton and photon radiotherapy and thereby improve the quality of life for prostate cancer patients. [ABSTRACT FROM AUTHOR]

Purpose: The long acquisition time of CBCT discourages repeat verification imaging, therefore increasing treatment uncertainty. In this study, we present a fast volumetric imaging method for lung cancer radiation therapy using an orthogonal 2D kV/MV image pair. Methods: The proposed model is a combination of 2D and 3D networks. The proposed model consists of five major parts: (1) kV and MV feature extractors are used to extract deep features from the perpendicular kV and MV projections. (2) The feature‐matching step is used to re‐align the feature maps to their projection angle in a Cartesian coordinate system. By using a residual module, the feature map can focus more on the difference between the estimated and ground truth images. (3) In addition, the feature map is downsized to include more global semantic information for the 3D estimation, which is useful to reduce inhomogeneity. By using convolution‐based reweighting, the model is able to further increase the uniformity of image. (4) To reduce the blurry noise of generated 3D volume, the Laplacian latent space loss calculated via the feature map that is extracted via specifically‐learned Gaussian kernel is used to supervise the network. (5) Finally, the 3D volume is derived from the trained model. We conducted a proof‐of‐concept study using 50 patients with lung cancer. An orthogonal kV/MV pair was generated by ray tracing through CT of each phase in a 4D CT scan. Orthogonal kV/MV pairs from nine respiratory phases were used to train this patient‐specific model while the kV/MV pair of the remaining phase was held for model testing. Results: The results are based on simulation data and phantom results from a real Linac system. The mean absolute error (MAE) values achieved by our method were 57.5 HU and 77.4 HU within body and tumor region‐of‐interest (ROI), respectively. The mean achieved peak‐signal‐to‐noise ratios (PSNR) were 27.6 dB and 19.2 dB within the body and tumor ROI, respectively. The achieved mean normalized cross correlation (NCC) values were 0.97 and 0.94 within the body and tumor ROI, respectively. A phantom study demonstrated that the proposed method can accurately re‐position the phantom after shift. It is also shown that the proposed method using both kV and MV is superior to current method using kV or MV only in image quality. Conclusion: These results demonstrate the feasibility and accuracy of our proposed fast volumetric imaging method from an orthogonal kV/MV pair, which provides a potential solution for daily treatment setup and verification of patients receiving radiation therapy for lung cancer. [ABSTRACT FROM AUTHOR]

Background: Dietary therapy may potentially reduce inflammation and promote mucosal healing in patients with Crohn's disease and is associated with fewer side effects and lower cost compared to medical therapy. Recently the Crohn's disease exclusion diet (CDED) has been developed to reduce exposure to individualized dietary components which negatively affect the intestine in patients with Crohn's disease. Objectives: This systematic review aimed to explore the effectiveness of CDED in Crohn's disease patients. Design: A systematic review Data sources and methods: A systematic search was performed on the PubMed, EBSCOhost, Cochrane library, OVID, Embase, Scopus, and CINHAL to identify relevant clinical trials published from 1 January 2014 to 31 August 2022. Results: A total of 1120 studies were identified and 7 studies were finally included in the analysis. The study was reported according to Preferred Reporting Items for Systematic Reviews and Meta-analysis statement. Conclusion: Our findings suggested that the use of CDED seemed to be effective for induction and maintenance of remission in children and adults with mild to moderate Crohn's disease. However, heterogeneity and limitations existed among the studies included. Further investigation in the form of well-designed randomized clinical trials is needed to validate the present findings. Registration: PROSPERO registration number CRD42022335453. [ABSTRACT FROM AUTHOR]

Seed weight is a component of seed yield in rapeseed (Brassica napus L.). Although quantitative trait loci (QTL) for seed weight have been reported in rapeseed, only a few causal quantitative trait genes (QTGs) have been identified, resulting in a limitation in understanding of seed weight regulation. We constructed a gene coexpression network at the early seed developmental stage using transcripts of 20,408 genes in QTL intervals and 1017 rapeseed homologs of known genes from other species. Among the 10 modules in this gene coexpression network, modules 1 and 2 were core modules and contained genes involved in source–flow–sink processes such as synthesis and transportation of fatty acid and protein, and photosynthesis. A hub gene SERINE CARBOXYPEPTIDASE-LIKE 19 (SCPL19) was identified by candidate gene association analysis in rapeseed and functionally investigated using Arabidopsis T-DNA mutant and overexpression lines. Our study demonstrates the power of gene coexpression analysis to prioritize candidate genes from large candidate QTG sets and enhances the understanding of molecular mechanism for seed weight at the early developmental stage in rapeseed. [ABSTRACT FROM AUTHOR]

Polyimide-bearing retainer has been successfully used in space environment. However, the structural damage of polyimide induced by space irradiation limits its wide use. In order to further improve the atomic oxygen resistance of polyimide and comprehensively investigate the tribological mechanism of polyimide composites exposed in simulate space environment, 3-amino-polyhedral oligomeric silsesquioxane (NH2-POSS) was incorporated into a polyimide molecular chain and silica (SiO2) nanoparticles were in situ added into polyimide matrix and the combined effect of vacuum environment, and atomic oxygen (AO) on the tribological performance of polyimide was studied using bearing steel as the counterpart by a ball on disk tribometer. XPS analysis demonstrated the formation of protective layer induced by AO. The wear resistance of polyimide after modification was enhanced under AO attack. FIB-TEM confirmed that the inert protective layer of Si was formed on the counterpart during the sliding process. Mechanisms behind this are discussed based on the systematic characterization of worn surfaces of the samples and the tribofilms formed on the counterbody. [ABSTRACT FROM AUTHOR]

Objective. CBCTs in image-guided radiotherapy provide crucial anatomy information for patient setup and plan evaluation. Longitudinal CBCT image registration could quantify the inter-fractional anatomic changes, e.g. tumor shrinkage, and daily OAR variation throughout the course of treatment. The purpose of this study is to propose an unsupervised deep learning-based CBCT-CBCT deformable image registration which enables quantitative anatomic variation analysis. Approach. The proposed deformable registration workflow consists of training and inference stages that share the same feed-forward path through a spatial transformation-based network (STN). The STN consists of a global generative adversarial network (GlobalGAN) and a local GAN (LocalGAN) to predict the coarse- and fine-scale motions, respectively. The network was trained by minimizing the image similarity loss and the deformable vector field (DVF) regularization loss without the supervision of ground truth DVFs. During the inference stage, patches of local DVF were predicted by the trained LocalGAN and fused to form a whole-image DVF. The local whole-image DVF was subsequently combined with the GlobalGAN generated DVF to obtain the final DVF. The proposed method was evaluated using 100 fractional CBCTs from 20 abdominal cancer patients in the experiments and 105 fractional CBCTs from a cohort of 21 different abdominal cancer patients in a holdout test. Main Results. Qualitatively, the registration results show good alignment between the deformed CBCT images and the target CBCT image. Quantitatively, the average target registration error calculated on the fiducial markers and manually identified landmarks was 1.91 ± 1.18 mm. The average mean absolute error, normalized cross correlation between the deformed CBCT and target CBCT were 33.42 ± 7.48 HU, 0.94 ± 0.04, respectively. Significance. In summary, an unsupervised deep learning-based CBCT-CBCT registration method is proposed and its feasibility and performance in fractionated image-guided radiotherapy is investigated. This promising registration method could provide fast and accurate longitudinal CBCT alignment to facilitate inter-fractional anatomic changes analysis and prediction. [ABSTRACT FROM AUTHOR]

Objectives: To verify the effects of self‐care programs among adults with prediabetes, to identify the preferable structure components and to summarise the core content components of self‐care programs. Design: A systematic review and meta‐analysis of randomised controlled trials. Methods: PubMed, Embase, Cochrane, CINAHL, PsycINFO, Wanfang, CNKI, Chinese Biomedical Database and Open Grey were searched for studies published from January 2002 to December, 2021. Meta‐analysis was conducted to verify the effects of self‐care programs on diabetes incidence. Subgroup analyses based on structure components were performed to contrast the effects. We made a critical analysis to generalise the core elements of content components. The study was reported according to PRISMA statement. Results: Totally, 15 studies were included in systematic review, of which 14 studies were eligible for meta‐analysis. The results of meta‐analysis showed the incidence of diabetes for prediabetic adults receiving self‐care programs was significantly lower than those who received usual care (OR 0.58; 95% CI 0.46 to 0.73). The results of subgroup analyses based on delivery mode, intervention implementer, health education brochures provided, and follow‐up duration showed statistically significant reduction in incidence compared with control group (p <.05). However, the differences of these pair‐wise comparisons (face‐to‐face or remote, individual or interdisciplinary team, with or without brochures provided, ≤1 year or >1 year) were not statistically significant (p >.05). Three core content elements were generalised: cognitive education, behaviour guidance and psychological support. Conclusions: Self‐care programs can effectively delay the progression of prediabetes to diabetes. Regardless of the diversified structure components, self‐care programs can achieve better effects on the diabetes incidence than usual care, while the optimal structure components still remain unknown. Cognitive education, behaviour guidance and psychological support are core elements for these programs. Relevance to clinical practice: More clinical trials with rigorous study design are needed to provide further evidence. [ABSTRACT FROM AUTHOR]

As the number and length of high-speed railway tunnels increase in China, implicit defects such as insufficient lining thicknesses, voids, and poor compaction have become increasingly common, posing a serious threat to train operation safety. It is, therefore, imperative to conduct a comprehensive census of the defects within the tunnel linings. In response to this problem, this study proposes a high-speed railway tunnel detection method based on vehicle-mounted air-coupled GPR. Building on a forward simulation of air-coupled GPR, the study proposes the F-K filtering and BP migration algorithms based on the practical considerations of random noise and imaging interference from the inherent equipment. Through multi-dimensional quantitative comparisons, these algorithms are shown to improve the spectrum entropy values and instantaneous amplitude ratios by 4.6% and 11.6%; and 120% and 180%, respectively, over the mean and bandpass filtering algorithms, demonstrating their ability to suppress clutter and enhance the internal signal prominence of the lining. The experimental results are consistent with the forward simulation trends, and the verification using the ground-coupled GPR detection confirms that air-coupled GPR can meet the requirements of high-speed railway tunnel lining inspections. A comprehensive GPR detection model is proposed to lay the foundation for a subsequent defect census of high-speed railway tunnels. [ABSTRACT FROM AUTHOR]

Tartrate-resistant acid phosphatase type 5 (TRAP5) is an enzyme that is highly expressed in activated macrophages and osteoclasts and plays important biological functions in mammalian immune defense systems. In the study, we investigated the functions of tartrate-resistant acid phosphatase type 5b from Oreochromis niloticus (OnTRAP5b). The OnTRAP5b gene has an open reading frame of 975 bp, which encodes a mature peptide consisting of 302 amino acids with a molecular weight of 33.448 kDa. The OnTRAP5b protein contains a metallophosphatase domain with metal binding and active sites. Phylogenetic analysis revealed that OnTRAP5b is clustered with TRAP5b of teleost fish and shares a high amino acid sequence similarity with other TRAP5b in teleost fish (61.73–98.15%). Tissues expression analysis showed that OnTRAP5b was most abundant in the liver and was also widely expressed in other tissues. Upon challenge with Streptococcus agalactiae and Aeromonas hydrophila in vivo and in vitro, the expression of OnTRAP5b was significantly up-regulated. Additionally, the purified recombinant OnTRAP5b ((r)OnTRAP5) protein exhibited optimal phosphatase activity at pH 5.0 and an ideal temperature of 50 °C. The Vmax, Km, and kcat of purified (r)OnTRAP5b were found to be 0.484 μmol × min−1 × mg−1, 2.112 mM, and 0.27 s−1 with respect to pNPP as a substrate, respectively. Its phosphatase activity was differentially affected by metal ions (K+, Na+, Mg2+, Ca2+, Mn2+, Cu2+, Zn2+, and Fe3+) and inhibitors (sodium tartrate, sodium fluoride, and EDTA). Furthermore, (r)OnTRAP5b was found to promote the expression of inflammatory-related genes in head kidney macrophages and induce reactive oxygen expression and phagocytosis. Moreover, OnTRAP5b overexpression and knockdown had a significant effect on bacterial proliferation in vivo. When taken together, our findings suggest that OnTRAP5b plays a significant role in the immune response against bacterial infection in Nile tilapia. [ABSTRACT FROM AUTHOR]

Through the long development processes of reservoir sedimentation and diagenesis, acidic and alkaline fluids play key roles in controlling deep reservoir development. However, the ways in which deep fluids control and transform the reservoir under complex fault conditions remain unclear. In this study, a 2D model was established based on a typical sub-salt to intra-salt vertical profile in the Qaidam Basin, China. Based on measured data, multiphase flow reaction and solute transport simulation technology were used to analyze fluids flow and migration in the intra-salt and sub-salt reservoirs, determine the mineral dissolution, precipitation, and transformation in the reservoir caused by the deep fluids, and calculate the changes in reservoir porosity. Results show that deep fluid migrates preferentially along dominant channels and triggers a series of fluiderock chemical reactions. In the first stage, a large amount of anhydrite precipitated in the fault as a result of upward migration of deep saline fluid, resulting in the formation of anhydrite veins and blockage at the base of the fault. In the second stage, organic acids caused minerals dissolution and a vertical channel was opened in previously blocked area, which promoted continuous upward migration of organic acids and the formation of secondary pores. This study clarifies the transformative effects of deep alkaline and acidic fluids on the reservoir. Moreover, the important fluid transport role of faults and their effect on reservoir development were determined. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) proves decisive in today's rapidly developing society and is a motive force for the evolution of financial technology. As a subdivision of artificial intelligence research, machine learning (ML) algorithm is extensively used in all aspects of the daily operation and development of the supply chain. Using data mining, deductive reasoning, and other characteristics of machine learning algorithms can effectively help decision-makers of enterprises to make more scientific and reasonable decisions by using the existing financial index data. At present, globalization uncertainties such as COVID-19 are intensifying, and supply chain enterprises are facing bankruptcy risk. In the operation process, practical tools are needed to identify and opportunely respond to the threat in the supply chain operation promptly, predict the probability of business failure of enterprises, and take scientific and feasible measures to prevent a financial crisis in good season. Artificial intelligence decision-making technology can help traditional supply chains to transform into intelligent supply chains, realize smart management, and promote supply chain transformation and upgrading. By applying machine learning algorithms, the supply chain can not only identify potential risks in time and adopt scientific and feasible measures to deal with the crisis but also strengthen the connection and cooperation between different enterprises with the advantage of advanced technology to provide overall operation efficiency. On account of this, the paper puts forward an artificial intelligence-based corporate financial-risk-prevention (FRP) model, which includes four stages: data preprocessing, feature selection, feature classification, and parameter adjustment. Firstly, relevant financial index data are collected, and the quality of the selected data is raised through preprocessing; secondly, the chaotic grasshopper optimization algorithm (CGOA) is used to simulate the behavior of grasshoppers in nature to build a mathematical model, and the selected data sets are selected and optimized for features. Then, the support vector machine (SVM) performs classification processing on the quantitative data with reduced features. Empirical risk is calculated using the hinge loss function, and a regular operation is added to optimize the risk structure. Finally, slime mould algorithm (SMA) can optimize the process to improve the efficiency of SVM, making the algorithm more accurate and effective. In this study, Python is used to simulate the function of the corporate business finance risk prevention model. The experimental results show that the CGOA-SVM-SMA algorithm proposed in this paper achieves good results. After calculation, it is found that the prediction and decision-making capabilities are good and better than other comparative models, which can effectively help supply chain enterprises to prevent financial risks. [ABSTRACT FROM AUTHOR]

An adaptive denoising method based on 2D empirical mode decomposition (EMD) is proposed to improve the infrared image quality of inspection UNMANNED aerial vehicles (UAVs) and provide guarantee for improving the inspection level of distribution network. Through rapid adaptive two-dimensional empirical mode decomposition algorithm decomposition of a UAV collected for distribution network inspection original noise of infrared image, get more than the IMF component and the residual amount, a forecast noise dominated the IMF component parameters such as threshold value and the variance of noise, using the estimated parameters in combination with the optimal linear interpolation algorithm of noise threshold function of leading the IMF component implementation of threshold denoising. After the denoised IMF component is obtained, the denoised infrared image is obtained after reconstruction with the signal-dominated IMF component, and the adaptive denoising of the infrared image of the distribution network inspection UAV is realized. The experimental results show that the method in this paper can maintain the details of the image, improve the definition, significantly improve the visual effect, the overall denoising performance is stable and feasible, and ensure the quality inspection UAV to collect infrared images. [ABSTRACT FROM AUTHOR]

Direct oxidative coupling of inert C(sp3)−H bond has been a great challenge. Herein, an environmentally friendly aerobic oxidative coupling of α‐methyl substituted N‐heteroarenes with indoles is reported. A variety of diheteroaryl ketones were prepared in good yields (up to 72 %). This protocol features simple operation and broad substrates scope (26 examples). Significantly, a plausible mechanism about catalytic cycle was proposed, and two key intermediates were confirmed by high resolution mass spectrometry. [ABSTRACT FROM AUTHOR]

The extracellular matrix (ECM) is a complex molecular network distributed throughout the extracellular space of different tissues as well as the neuronal system. Previous studies have identified various ECM components that play important roles in neuronal maturation and signal transduction. ECM components are reported to be involved in neurogenesis, neuronal migration, and axonal growth by interacting or binding to specific receptors. In addition, the ECM is found to regulate synapse formation, the stability of the synaptic structure, and synaptic plasticity. Here, we mainly reviewed the effects of various ECM components on synapse formation and briefly described the related diseases caused by the abnormality of several ECM components. [ABSTRACT FROM AUTHOR]

Background: Multimodality positron emission tomography/computed tomography (PET/CT) imaging combines the anatomical information of CT with the functional information of PET. In the diagnosis and treatment of many cancers, such as non‐small cell lung cancer (NSCLC), PET/CT imaging allows more accurate delineation of tumor or involved lymph nodes for radiation planning. Purpose: In this paper, we propose a hybrid regional network method of automatically segmenting lung tumors from PET/CT images. Methods: The hybrid regional network architecture synthesizes the functional and anatomical information from the two image modalities, whereas the mask regional convolutional neural network (R‐CNN) and scoring fine‐tune the regional location and quality of the output segmentation. This model consists of five major subnetworks, that is, a dual feature representation network (DFRN), a regional proposal network (RPN), a specific tumor‐wise R‐CNN, a mask‐Net, and a score head. Given a PET/CT image as inputs, the DFRN extracts feature maps from the PET and CT images. Then, the RPN and R‐CNN work together to localize lung tumors and reduce the image size and feature map size by removing irrelevant regions. The mask‐Net is used to segment tumor within a volume‐of‐interest (VOI) with a score head evaluating the segmentation performed by the mask‐Net. Finally, the segmented tumor within the VOI was mapped back to the volumetric coordinate system based on the location information derived via the RPN and R‐CNN. We trained, validated, and tested the proposed neural network using 100 PET/CT images of patients with NSCLC. A fivefold cross‐validation study was performed. The segmentation was evaluated with two indicators: (1) multiple metrics, including the Dice similarity coefficient, Jacard, 95th percentile Hausdorff distance, mean surface distance (MSD), residual mean square distance, and center‐of‐mass distance; (2) Bland–Altman analysis and volumetric Pearson correlation analysis. Results: In fivefold cross‐validation, this method achieved Dice and MSD of 0.84 ± 0.15 and 1.38 ± 2.2 mm, respectively. A new PET/CT can be segmented in 1 s by this model. External validation on The Cancer Imaging Archive dataset (63 PET/CT images) indicates that the proposed model has superior performance compared to other methods. Conclusion: The proposed method shows great promise to automatically delineate NSCLC tumors on PET/CT images, thereby allowing for a more streamlined clinical workflow that is faster and reduces physician effort. [ABSTRACT FROM AUTHOR]

Coal and gas outbursts in underground mines are the result of dynamic rupture propagation along coal seams, starting from localized instability caused by the sudden release of gas and strain energies. Although physical simulations have facilitated quantitative studies of outbursts, and rupture processes have been investigated both experimentally and theoretically, the underlying mechanisms responsible for triggering outbursts remain poorly understood. This lack of understanding seriously limits our ability to prevent gas hazards. Here we systematically analyze the essential characteristics and energy principles of outburst experiments over the past 70 years and explore the onset of natural outbursts. The results show that although laboratory experiments and natural events are dynamically similar, their triggering mechanisms are fundamentally different. Specifically, actual outbursts depend highly on stress conditions and gas desorption; in contrast, experiments can be performed under stress-free conditions or even entirely dominated by free gas, often with low threshold pressures (< 0.7 MPa). Energy analysis indicated that the high porosity of the experimental briquette resulted in much higher free gas energy than in the actual coal seam (up to ~ 40 times), enabling the simulated outbursts to overcome mechanical barriers easily and, in turn, to be stress independent. Furthermore, our findings suggest that the triggering process of a natural outburst is unlikely to be transient. Instead, the development of fractures and the consequent enlargement of free gas energy are essential processes for initiating ruptures and generating potential precursors. Our results highlight that understanding the role of gas and stress is crucial for accurately interpreting outburst mechanisms. Highlights: The essential characteristics and energy principles of outburst experiments were systematically analyzed. Outburst experiments are fundamentally different from natural events in triggering mechanisms. Outburst simulations are essentially free gas-driven dynamics. Fracture development and increased free gas energy are necessary processes to initiate ruptures. [ABSTRACT FROM AUTHOR]

Efficacy of immunotherapy is limited in patients with colorectal cancer (CRC) because high expression of tumor-derived transforming growth factor (TGF)-β pathway molecules and interferon (IFN)-stimulated genes (ISGs) promotes tumor immune evasion. Here, we identified a long noncoding RNA (lncRNA), VPS9D1-AS1, which was located in ribosomes and amplified TGF-β signaling and ISG expression. We show that high expression of VPS9D1-AS1 was negatively associated with T lymphocyte infiltration in two independent cohorts of CRC. VPS9D1-AS1 served as a scaffolding lncRNA by binding with ribosome protein S3 (RPS3) to increase the translation of TGF-β, TGFBR1, and SMAD1/5/9. VPS9D1-AS1 knockout downregulated OAS1, an ISG gene, which further reduced IFNAR1 levels in tumor cells. Conversely, tumor cells overexpressing VPS9D1-AS1 were resistant to CD8+ T cell killing and lowered IFNAR1 expression in CD8+ T cells. In a conditional overexpression mouse model, VPS9D1-AS1 enhanced tumorigenesis and suppressed the infiltration of CD8+ T cells. Treating tumor-bearing mice with antisense oligonucleotide drugs targeting VPS9D1-AS1 significantly suppressed tumor growth. Our findings indicate that the tumor-derived VPS9D1-AS1/TGF-β/ISG signaling cascade promotes tumor growth and enhances immune evasion and may thus serve as a potential therapeutic target for CRC. [ABSTRACT FROM AUTHOR]

Purpose: A quality assurance (QA) CT scans are usually acquired during cancer radiotherapy to assess for any anatomical changes, which may cause an unacceptable dose deviation and therefore warrant a replan. Accurate and rapid deformable image registration (DIR) is needed to support contour propagation from the planning CT (pCT) to the QA CT to facilitate dose volume histogram (DVH) review. Further, the generated deformation maps are used to track the anatomical variations throughout the treatment course and calculate the corresponding accumulated dose from one or more treatment plans. Methods: In this study, we aim to develop a deep learning (DL)‐based method for automatic deformable registration to align the pCT and the QA CT. Our proposed method, named dual‐feasible framework, was implemented by a mutual network that functions as both a forward module and a backward module. The mutual network was trained to predict two deformation vector fields (DVFs) simultaneously, which were then used to register the pCT and QA CT in both directions. A novel dual feasible loss was proposed to train the mutual network. The dual‐feasible framework was able to provide additional DVF regularization during network training, which preserves the topology and reduces folding problems. We conducted experiments on 65 head‐and‐neck cancer patients (228 CTs in total), each with 1 pCT and 2–6 QA CTs. For evaluations, we calculated the mean absolute error (MAE), peak‐signal‐to‐noise ratio (PSNR), structural similarity index (SSIM), target registration error (TRE) between the deformed and target images and the Jacobian determinant of the predicted DVFs. Results: Within the body contour, the mean MAE, PSNR, SSIM, and TRE are 122.7 HU, 21.8 dB, 0.62 and 4.1 mm before registration and are 40.6 HU, 30.8 dB, 0.94, and 2.0 mm after registration using the proposed method. These results demonstrate the feasibility and efficacy of our proposed method for pCT and QA CT DIR. Conclusion: In summary, we proposed a DL‐based method for automatic DIR to match the pCT to the QA CT. Such DIR method would not only benefit current workflow of evaluating DVHs on QA CTs but may also facilitate studies of treatment response assessment and radiomics that depend heavily on the accurate localization of tissues across longitudinal images. [ABSTRACT FROM AUTHOR]

Objective: With the advancement of minimally invasive spine surgery, endoscopic discectomy (ED) has become a common technique for degenerative disease of the spine. The present study aimed to explore the knowledge structure, emerging trends, and future research hotspots in this field. Methods: All relevant publications on ED from 2002 to 2021 were extracted from the Web of Science databases. Key bibliometric indicators, including countries/regions, institutions, authors, journals, references, and keywords were calculated and evaluated using VOSviewer and CiteSpace software. Results: A total of 1,196 articles and reviews were included for analysis. The number of publications regarding ED increased yearly. From the quality and quantity viewpoint, China, South Korea, and the United States were the major contributors in this field. The most influential institution in the field of ED was Wooridul Spine Hospital. We identified 3,488 authors, among which Lee SH had the most significant number of papers, and Ruetten S was cocited most often. World Neurosurgery was the journal with the most papers, and Spine was the most commonly cocited journal. Keywords were stratified into 4 clusters by VOSviewer software: cluster 1 (clinical outcomes of ED in the treatment of lumbar disc herniation); cluster 2 (surgical technique of percutaneous endoscopic lumbar discectomy); cluster 3 (clinical outcomes of ED in the treatment of lumbar spinal stenosis); and cluster 4 (clinical outcomes of percutaneous endoscopic cervical discectomy). Several topics including lateral recess stenosis, spinal stenosis, and reoperation were considered as the next hotspot in ED research. Conclusion: ED research has gained considerable attention over the last 2 decades. Our bibliometric findings illuminate the publication trends and research hotspots of the ED field, which may provide useful references for scholars and decision-makers interested in this field. [ABSTRACT FROM AUTHOR]

In this study, a typical three-dimensional model of single channel mono-block-layer build solid oxide fuel cell (MOLB-type SOFC) was developed. The effects of rib width and cathode thickness on the species concentration distribution, electrochemical performance, and temperature distribution of MOLB-type SOFC were investigated. The results show that adapting a smaller rib width can improve the uniformity of gas distribution, decrease the concentration polarization, and improve the output performance of SOFC. The performance of the cell can be significantly improved by thickening the cathode electrode. When the cathode thickness is 0.45 mm, the maximum output power density is improved by 53.69% compared with that at 0.15 mm. With the increase of the cathode thickness, the enhancement of the cell performance by increasing the cathode thickness gradually decreases. In addition, as the cathode thickness increases, the concentration polarization and temperature gradient of the cell gradually rise, while the activation polarization gradually decreases. [ABSTRACT FROM AUTHOR]

The Journey to the West, based on the story of Chen Xuanzang's learning from the scriptures in the Tang Dynasty, was finally written by Wu Cheng'en in the Ming Dynasty, which deeply reflected the social reality at that time. It was not only the first romantic novel about ghosts and gods in ancient China, but also a masterpiece of romanticism in the history of world literature. The hero of the story, Monkey King, has been constantly mythologized in the process of China's folk communication, becoming a household name hero and a cultural sign. Taking the Monkey King as the research object, this paper discusses its cross-media transformation from the perspective of semiotics, in order to provide some reference for China's excellent traditional literature to go out. [ABSTRACT FROM AUTHOR]

The NASA MEaSUREs Inter-mission Time Series of Land Ice Velocity and Elevation (ITS_LIVE) project seeks to accelerate understanding of critical glaciers and ice sheet processes by providing researchers with global, low-latency, comprehensive and state of the art records of surface velocities and elevations as observed from space. Here we describe the image-pair ice velocity product and processing methodology for ESA Sentinel-1 radar data. We demonstrate improvements to the core processing algorithm for dense offset tracking, "autoRIFT", that provide finer resolution (120 m instead of the previous 240 m used for version 1) and higher accuracy (20 % to 50 % improvement) data products with significantly enhanced computational efficiency (>2 orders of magnitude) when compared to earlier versions and the state of the art "dense ampcor" routine in the JPL ISCE software. In particular, the disparity filter is upgraded for handling finer grid resolution with overlapping search chip sizes, and the oversampling ratio in the subpixel cross-correlation estimation is adaptively determined for Sentinel-1 data by matching the precision of the measured displacement based on the search chip size used. A novel calibration is applied to the data to correct for Sentinel-1A/B subswath and full-swath dependent geolocation biases caused by systematic issues with the instruments. Sentinel-1 C-band images are affected by variations in the total electron content of the ionosphere that results in large velocity errors in the azimuth (along-track) direction. To reduce these effects, slant range (line of sight or LOS) velocities are used and accompanied by LOS parameters that support map coordinate (x / y) velocity inversion from ascending and descending slant range offset measurements, as derived from two image pairs. After the proposed correction of ionosphere errors, the uncertainties in velocities are reduced by 9 %–61 %. We further validate the ITS_LIVE Version 2 Sentinel-1 image-pair products, with 6-year time series composed of thousands of epochs, over three typical test sites covering the globe: the Jakobshavn Isbræ Glacier of Greenland, Pine Island Glacier of the Antarctic, and Malaspina Glacier of Alaska. By comparing with other similar products (PROMICE, FAU, and MEaSUREs Annual Antarctic Ice Velocity Map products), as well as other ITS_LIVE version 2 products from Landsat-8 and Sentinel-2 data, we find an overall variation between products around 100 m yr -1 over fast-flowing glacier outlets, where both mean velocity and variation are on the order of km yr -1 , and increases up to 300–500 m yr -1 (3 %–6 %) for the fastest Jakobshavn Isbræ Glacier. The velocity magnitude uncertainty of the ITS_LIVE Sentinel-1 products is calculated to be uniformly distributed around 60 m yr -1 for the three test regions investigated. The described product and methods comprise the MEaSUREs ITS_LIVE Sentinel-1 Image-Pair Glacier and Ice Sheet Surface Velocities: version 2 (DOI: 10.5067/0506KQLS6512, Lei et al., 2022). [ABSTRACT FROM AUTHOR]

Every gigantic Coal and Gas Outburst begins as a tiny, localized coal failure. This point of failure leads to a rupture of the coal seam, resulting in a violent ejection of enormous amounts of gas and pulverized coal. Whether the size of an outburst is predictable and whether a large-scale outburst requires unique conditions different from smaller events are fundamental questions associated with the potential for disaster probabilistic forecasting. In this study, we conducted a series of outburst simulations using carbon dioxide (CO2) and He and recorded acoustic signals in the frequency band 0.5–50 Hz during each outburst. We established that the cross-correlation coefficients of initial waveforms between Different-Sized Outbursts are generally high, which provides evidence for identical onsets of large and small events. Therefore, we focused on the self-similar properties of rupture growth and developed a viable model to explain the outburst mechanism. In our model, every outburst is essentially a trigger sequence. A large outburst results from a cascading sequence from a small rupture whose propagation proceeded along a route at which each step of the sequence had a sufficient energy supply to continue the cascade to a larger area. However, the route to the rupture of outbursts is sensitive to coal properties and the energy supply from the surrounding area. Hence, large-scale events are highly variable and almost independent of their initial state. If this is true for the actual outbursts, it would be quite difficult to predict the scale for any forthcoming outburst event. Highlights: A large outburst results from a cascading sequence from a small rupture. Outburst rupture are highly variable and difficult to predict. Similar initial low-frequency acoustic waves generally exist between different-sized outbursts. The size of an outburst cannot be distinguished solely from its initial features. [ABSTRACT FROM AUTHOR]

To observe the effects of propofol and dexmedetomidine on the expression of cytochrome c oxidase in primary hippocampal neurons isolated from neonatal mice. C57 neonatal mice were sacrificed within 24 h of birth and hippocampal tissue was collected. Primary hippocampal neurons were cultured in vitro and then randomly divided into a control group (0 µM propofol and 0 µM dexmedetomidine), propofol group (20 µM propofol and 0 µM dexmedetomidine) and propofol+dexmedetomidine group (20 µM propofol and 10 µM dexmedetomidine). The neurons were incubated for 1 h. Neuron morphology was observed under a light microscope. The expression of cytochrome c protein was detected semiquantitatively by Western blot and immunofluorescence staining. Compared with those in the control group, the primary hippocampal neurons in the propofol group were morphologically degenerated, with sparse axons and dendrites; the expression of cytochrome c protein was significantly higher in the propofol group (p<0.0001). The morphology of primary hippocampal neurons in the propofol+dexmedetomidine group was similar to that of primary hippocampal neurons in the control group, with plump and bright cell bodies and thickened neurites intertwined in a neuron network; additionally, cytochrome c protein expression was significantly lower in the hippocampal neurons in the propofol+dexmedetomidine group than in the hippocampal neurons in propofol group (p<0.0001). Dexmedetomidine reversed propofol induced injury and morphological abnormalities of primary hippocampal neurons. The mechanism may be related to the downregulation of cytochrome c protein expression. [ABSTRACT FROM AUTHOR]

The article presents a case study of a 20-year-old male patient with pulmonary artery dissection secondary to a ventricular septal defect and pulmonary valve stenosis. Topics discussed include diagnostic imaging techniques, the pathological features of pulmonary artery dissection, and the importance of early surgical intervention.

We searched PVS-related literature in the Web of Science Core Collection database, extracted and analyzed the data using the Science Citation Index Extended Edition, and included two types of literature: review and monograph. The search terms were subject = persistent vegetative state and publication year (2001-2021) and language = English. Statistical analysis of literature overview, countries and regions, institutions, authors, literature source publications, literature research direction, citation frequency, impact factor, H-index and keywords, etc. are carried out. Use VOS viewer 1.6.17 software to visually cluster the keywords in the titles and abstracts of the included literature and analyze the research direction and development trend. A total of 772 PVS-related documents published in the core collection database of Web of Science from 2001 to 2021 were included. The country with the largest number of publications was the United States (261 papers, 33.80%), and the institution with the largest number of publications was the University of Liège, Belgium (40 papers, 5.18%). The author with the largest number of published papers is Laureys S of the University of Liège, Belgium (39 papers, 5.05%). The research directions of PVS are mainly neuroscience (350 articles, 45.33%), rehabilitation (98 articles, 12.69%), and internal medicine (9 articles, 11.79%). The literature is mainly from Brain Injury. The annual average impact factor of the top 10 journals in 2020 was 4.55, and their publication volume accounted for 17.35% (134/772) of the total literature. The 772 articles were cited 23,503 times (21,400 self-citations were excluded), with an average of 30.44 citations per article. The H-index of the United States, the United Kingdom and Belgium are 48, 27 and 27, which are significantly higher than other countries, and the citation frequencies are 8609, 3451 and 3270, accounting for 36.60%, 14.68% and 13.90% of the total citations, respectively. China's publication volume is in the middle, but only 8th in citation frequency and H-index (818 citations, H-index 16). We used the VOS viewer software to analyze and found that the keywords were mainly concentrated in four groups: "diagnosis-related","treatmentrelated"," prognosis-related"and"disease-related". From 2001 to 2021, the United States, Italy and the United Kingdom have the largest number of PVS related literature publications. There is still a certain gap between China and western countries in terms of the number and quality of literature publications. [ABSTRACT FROM AUTHOR]

In the past three decades, rare-earth metal triflates including scandium triflate, yttrium triflate, and the lanthanide (La−Lu) triflate, were widely employed in the organic chemistry, such as cyclization, C-H bond functionalization and types of reactions. Recently, the approaches using rare-earth metal triflates as catalysts have been mainly focusing on (1) achieving the high regioselectivity and stereoselectivity with effective ligands and (2) further extending the reaction scope by cooperation with other transition metal catalysts. This review mainly focuses on recent advances in the rare-earth metal triflates-catalyzed organic reactions from 2017 to 2019. This review also emphasis on reaction transformations and related mechanisms to show the general readership about capabilities, challenges as well as potential applications. [ABSTRACT FROM AUTHOR]

Aims • This study was conducted to establish the potential competing endogeneous RNA (ceRNA) network for predicting prognoses in kidney papillary renal cell carcinoma (KIRP) and explore novel therapeutic targets. Methods • The edgeR package in R was used to determine differentially expressed messenger RNAs (mRNAs), long non-coding RNAs (lncRNAs) and microRNAs (miRNAs), based on data from The Cancer Gene Atlas Program (TCGA) and the Genotype Expression (GTEx) databases. Weighted gene co-expression network analysis (WGCNA) was performed to filter out the mRNAs or lncRNAs that were strongly related to KIRP. The miRNAs that possibly sponged by differentially expressed RNAs lncRNAs (DElncRNAs) were screened using miRcode. Starbase, miRDB, and TargetScan sets were utilized to predict target mRNAs to corresponding miRNAs. LASSO and multivariate Cox regression analyses were applied for the determination of potential prognostic significance. Finally, the lncRNAmiRNA-mRNA ceRNA network was constructed. Results • A total of 1739 DEmRNAs and 1599 DElncRNAs were identified in KIRP. WGCNA analysis suggested that DEmRNAs in the blue module and DElncRNAs in the turquoise module were closely correlated with KIRP. An 8-gene signature was constructed, which had prognostic significance and predictive value in KIRP. Of note, a lncRNA-miRNA-mRNA ceRNA network (including 18 lncRNAs, 5 miRNAs, and 7 mRNAs) was established. Conclusion • This investigation constructed a new lncRNA-miRNA-mRNA ceRNA network, and proposed some genes that may be novel targets, as well as a theoretical basis for the treatment of patients with KIRP. (Altern Ther Health Med. [ABSTRACT FROM AUTHOR]