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Abstract This study comprehensively explores the clinical characteristics, diagnostic approaches, and treatment methods for liver mucinous cystic neoplasms (MCN). A retrospective analysis was conducted on seven individuals diagnosed with MCN, admitted to the Fifth Medical Center of the PLA General Hospital between October 2016 and May 2023. Preoperative AFP was negative, while CA19-9 was elevated in two cases. Surgical resection was performed for all patients. The patients showed favorable postoperative recovery. Follow-up revealed an excellent overall survival rate, except for one case of invasive carcinoma resulting in tumor recurrence and metastasis 6 months after surgery. MCN poses a diagnostic challenge due to the absence of distinct clinical and radiological features, leading to potential misdiagnosis and inappropriate treatment. Patients with suspected liver cystic diseases should consider the possibility of MCN. Surgical resection has proven to be a practical approach with satisfactory therapeutic outcomes.

Abstract This study investigates the craft of Tianche, an ancient towering timber structure used in well salt production in Sichuan Province, China. Originating in the Han Dynasty and maturing in the late Qing Dynasty, Tianches can reach heights of up to 110 m and represent a unique craft and structural system that is rare worldwide, yet remains largely unexplored in scholarly research. The Tianches are under threat due to a lack of maintenance and extinction of the craft. This study aims to document and elucidate the procedure and principles of the Tianche craft to help conserve this heritage. The key question is how to employ traditional craft to assemble over 100-m-tall structures from small-sized logs using pre-industrial technology. The study combines anthropological fieldwork and principles of mechanics to analyze the scientific validity and rationality of traditional crafts. The study reveals the principles of the Tianche craft, including mature craft procedure and reliable binding joints. Its advantages, namely self-locking structure, frictional force transmission, and hollow cylindrical columns, enhance the structure’s strength and stability and are fundamental for constructing 100-m-tall timber structures. Additionally, the study identifies two limitations of the craft: restricted column diameters and the tendency of the inverted dragon member’s tenon to break. This study investigated Tianche timber structures featuring hollow, bundle-like columns with frictional force transmission mechanism, presenting new possibilities beyond mainstream timber structural systems. The findings may contribute to enhancing research on the Tianche craft and could lay the foundation for future conservation practices related to Tianche heritage.

Hepatocellular carcinoma (HCC) is a common malignancy in China, with high recurrence rate and low resection rate among patients first diagnosed. Preoperative treatments including neoadjuvant and conversion therapy have the potential to overcome these challenges. In December 2021, Chinese expert consensus on neoadjuvant and conversion therapies for hepatocellular carcinoma was published. With the emersion of new evidence regarding the neoadjuvant and conversion therapies for HCC, the cooperative group brought together multidisciplinary researchers and scholars with experience in related fields to update the new edition (2023 Edition) for reference in China, including principle of the treatment strategies, the potential populations selection, treatment methods, multi-disciplinary team (MDT) and future research for preoperative treatments. The new consensus aims to provide guidance for clinical application. Through the use of neoadjuvant therapy and conversion therapy, we can enhance the resection rate and reduce the recurrence of intermediate-to-advanced HCC patients, thereby improving survival outcomes.

Semantic segmentation of high-resolution multispectral remote sensing image has been intensely studied. However, the shadow occlusions, or the similar color and textures, between the categories influence the segmentation accuracy. Concomitantly, the size of targets in the remote sensing images is diverse and the network cannot balance their segmentation. This paper introduces a network, Transformer-based Multi-modal Fusion Network (TMFNet), which fuses the multi-modal features and incorporates height features from the digital surface model (DSM) to supplement the extra different features between each category. Particularly, we introduce two parallel encoders to extract the features from different modalities, a Multi-Modal fusion model based on the Transformer (MMformer) to complete the multi-modal fusion, and a Border Region Attention based multi-level Fusion Module (BRAFM) to integrate the cross-level features and enhance the small target segmentation by utilizing the details around the border. The experiment results on the ISPRS Vaihingen and Potsdam benchmark datasets indicate that the proposed TMFNet outperforms the SOTA methods on the segmentation performance.

Supply chain disruptions caused by major public health crises will severely impact the economic growth. The main purpose of this paper is to examine the above proposition, taking the strict lockdown policy and supply chain disruption in Hubei Province at the beginning of the COVID-19 epidemic as a case, to provide decision-making reference for the government in supply chain management under major public health crisis. To achieve this goal, this paper firstly measures the supply chain network of Hubei province via the multi-region and multi-sector value-added model; then empirically studies the impact of lockdown policy and supply chain disruption on provincial economic growth, with the monthly data of 31 provinces covering January 2018 to December 2022, by the Difference in Difference method. The results show that: the lockdown policy and supply chain disruption under the Covid-19 epidemic negatively affected provincial economic growth; moreover, supply chain disruptions make provinces closer to Hubei more vulnerable to economic shocks. The results are significant in the placebo test, and are further supported in the robustness test of alternative variables and data. We further discussed the Business Cycle Co-movement between Hubei and other provinces, and the probable impact mechanism of supply chain interruption on economic growth in the Covid-19 epidemic. This study shows that supply chain network plays an important role in the transmission of interregional economic shocks, as well as its importance for economic growth, especially in major public health crises.

The Cambrian Terreneuvian Yuertusi Formation of the Tarim Basin, regarded as a potential hydrocarbon source rock (TOCmax = 29.8 wt%), preserves the record of the Ediacaran to Cambrian Series 2 transition. This study presents a high-resolution multi-proxy investigation of the Sugaitebulake and Yutixi sections of the NW Tarim Basin. Evidence of hydrothermal activity and euxinic conditions in the earliest Cambrian has been delineated by samples from the lower part of the Yuertusi Formation group A, featured by weakly positive Ce anomalies (Ce/Ce*avg. = 0.46), extremely positive Eu anomalies (Eu/Eu*avg. = 26.39), Y/Ho ratios (Y/Hoavg. = 40.48) and several barite layers. Mo and U covariation suggests that the Yuertusi Formation group A and Xiaoerbulake Formation were deposited under sulfidic conditions, whereas the Ediacaran Qigebulake Formation, and Yuertusi Formation groups B and C and D accumulated under suboxic to anoxic conditions. The basin has been weakly restricted and characterized by elevated productivity (Ba-excessavg. = 6,410.42 ppm) during Terreneuvian time. Suboxic conditions in late Ediacaran time (Qigebulake Formation) became euxinic conditions in association with increased sea level and productivity sustained by hydrothermal activity and upwelling, which have been preserved in the organic-rich lower part of the Yuertusi Formation. Suboxic conditions were reestablished during the Cambrian Terreneuvian time as reflected in the geochemistry of the upper part of the Yuertusi Formation. Euxinic conditions were once again established early in Cambrian Series 2 Xiaoerbulake Formation. Euxinic conditions were coincident with transgressions of the South Tianshan Ocean during that interval. The accumulation and preservation of organic matter of the Early Cambrian northern Tarim Platform reflect the interaction of hydrothermal activity, coastal upwelling, and sea level change.

Abstract CD8+ T cells are critical for host antitumor responses, whereas persistent antigenic stimulation and excessive inflammatory signals lead to T cell dysfunction or exhaustion. Increasing early memory T cells can improve T cell persistence and empower T cell‐mediated tumor eradication, especially for adoptive cancer immunotherapy. Here, it is reported that tumor‐associated monocytes (TAMos) are highly correlated with the accumulation of CD8+ memory T cells in human cancers. Further analysis identifies that TAMos selectively reprogram CD8+ T cells into T central memory‐like (TCM‐like) cells with enhanced recall responses. L‐NMMA, a pan nitric oxide synthase inhibitor, can mitigate TAMo‐mediated inhibition of T cell proliferation without affecting TCM‐like cell generation. Moreover, the modified T cells by TAMo exposure and L‐NMMA treatment exhibit long‐term persistence and elicit superior antitumor effects in vivo. Mechanistically, the transmembrane protein CD300LG is involved in TAMo‐mediated TCM‐like cell polarization in a cell‐cell contact‐dependent manner. Thus, the terminally differentiated TAMo subset (CD300LGhighACElow) mainly contributes to TCM‐like cell development. Taken together, these findings establish the significance of TAMos in boosting T‐cell antitumor immunity.

Highlights The p–n segment thermoelectric aerogel fiber was fabricated through an alternating coaxial wet-spinning strategy. Resultant alternating p–n segment thermoelectric fiber was electrically connected in series (two p–n pairs with a length of 3 cm) with an outstanding electrical conductivity of 23.76 S m−1. Thermoelectric textile-based self-powered fire warning electronics exhibited sensitivity (trigger time within 1.43 s) and repeatable temperature sensing performance for firefighting clothing.

The influence of prefabricated dislocation features induced by rate dependent prestrain on the post-cyclic process in 7075 aluminum alloy exhibits significant variations, which are of great importance in terms of concerns, designs, and discoveries. Considering strain rate dependent prestrain provides diversified hardening stimuli for the subsequent cyclic process. The maximum cyclic stress in the post-cyclic stage was maintained at the same level as the prestress with strain rates ranging from 10-4s−1 to 10-1s−1. Subsequently, by adjusting post-cycling stress amplitude, research was conducted on quasi-plastic amplitude cycle (QPC) and low plasticity amplitude cycle (LPC) loading conditions. Through experimental mechanism analysis, as well as verification through molecular dynamics and crystal plasticity simulations, prestrain induced by rapid strain rates enhanced the hardening during QPC, stemming from the effects of matrix reconstruction strengthening and wavy structured grain boundaries. However, prestrain induced by slow strain rates promoted the hardening during LPC, primarily arising from the non-uniform crystal structures within individual grains, which was achieved through the complex sub-crystal clusters at grain boundaries, along with intracrystal orderly slipping lattice. These findings offer new insights for the optimization of microstructural design through dislocation engineering.

Endogenous peptides, particularly those with post-translational modifications, are increasingly being studied as biomarkers for diagnosing various diseases. However, they are weakly ionizable, have a low abundance in biological samples, and may be interfered with by high levels of proteins, peptides, and other macromolecular impurities, resulting in a high limit of detection and insufficient amounts of post-translationally modified peptides in real biological samples to be examined. Therefore, separation and enrichment are necessary before analyzing these biomarkers using mass spectrometry. Mesoporous materials have regular adjustable pores that can eliminate large proteins and impurities, and their large specific surface area can bind more target peptides, but this may result in the partial loss or destruction of target peptides during centrifugal separation. On the other hand, magnetic mesoporous materials can be used to separate the target using an external magnetic field, which improves the separation efficiency and yield. Core–shell magnetic mesoporous materials are widely utilized for peptide separation and enrichment due to their biocompatibility, efficient enrichment capability, and excellent recoverability. This paper provides a review of the latest progress in core–shell magnetic mesoporous materials for enriching glycopeptides and phosphopeptides and compares their enrichment performance with different types of functionalization methods.

Abstract Background Our previous study demonstrated that M1 macrophages could impair tight junctions (TJs) between vascular endothelial cells by secreting interleukin-6 (IL-6) after spinal cord injury (SCI). Tocilizumab, as a humanized IL-6 receptor (IL-6R) monoclonal antibody approved for the clinic, has been applied in the treatment of neurological diseases in recent years, but the treatment effect of Tocilizumab on the TJs restoration of the blood-spinal cord barrier (BSCB) after SCI remains unclear. This study aimed to explore the effect of Tocilizumab on the restoration of TJs between vascular endothelial cells and axon regeneration after SCI. Methods In this study, the mouse complete spinal cord crush injury model was used, and Tocilizumab was continuously injected intrathecally until the day of sample collection. A PBS injection in the same location was included as a control. At 14 days postinjury (dpi) and 28 dpi, spinal cord tissue sections were examined via tissue immunofluorescence. The Basso Mouse Scale (BMS) scores and footprint analysis were used to verify the effect of Tocilizumab on the recovery of motor function in mice after SCI. Results We demonstrated that depletion of macrophages has no effect on axon regeneration and motor functional recovery after SCI, but mice subjected to Tocilizumab showed a significant increase in axon regeneration and a better recovery in motor function during the chronic phase after SCI. Moreover, our study demonstrated that at 14 and 28 dpi, the expression of claudin-5 (CLDN5) and zonula occludens-1 (ZO-1) between vascular endothelial cells was significantly increased and the leakage of BSCB was significantly reduced in the injured core after daily intrathecal injection of Tocilizumab. Notably, the infiltration of CD68+ macrophages/microglia and the formation of fibrotic scar were decreased in the injured core after Tocilizumab treatment. Tocilizumab treatment could effectively reduce the IL-6 expression in macrophages in the injured core. Conclusion The application of Tocilizumab to antagonize IL-6R can effectively reduce the expression of IL-6 in macrophages and facilitate TJs restoration of the BSCB, which is beneficial for axon regeneration and motor functional recovery after SCI. Hence, Tocilizumab treatment is a potential therapeutic strategy for SCI.

Summary: Immune checkpoint blockade has become an effective approach to reverse the immune tolerance of tumor cells. Indoleamine 2,3-dioxygenase 1 (IDO1) is frequently upregulated in many types of cancers and contributes to the establishment of an immunosuppressive cancer microenvironment, which has been thought to be a potential target for cancer therapy. However, the development of IDO1 inhibitors for clinical application is still limited. Here, we isolated a DNA aptamer with a strong affinity and inhibitory activity against IDO1, designated as IDO-APT. By conjugating with nanoparticles, in situ injection of IDO-APT to CT26 tumor-bearing mice significantly suppresses the activity of regulatory T cells and promotes the function of CD8+ T cells, leading to tumor suppression and prolonged survival. Therefore, this functional IDO1-specific aptamer with potent anti-tumor effects may serve as a potential therapeutic strategy in cancer immunotherapy. Our data provide an alternative way to target IDO1 in addition to small molecule inhibitors.

Therapeutic drug monitoring (TDM) has played an important role in clinical medicine for precise dosing. Currently, chromatographic technology and immunoassay detection are widely used in TDM and have met most of the needs of clinical drug therapy. However, some problems still exist in practical applications, such as complicated operation and the influence of endogenous substances. Surface plasmon resonance (SPR) has been applied to detect the concentrations of small molecules, including pesticide residues in crops and antibiotics in milk, which indicates its potential for in vivo drug detection. In this study, a new SPR-based biosensor for detecting chloramphenicol (CAP) in blood samples was developed and validated using methodological verification, including precision, accuracy, matrix effect, and extraction recovery rate, and compared with the classic ultra-performance liquid chromatography-ultraviolet (UPLC-UV) method. The detection range of SPR was 0.1–50 ng/mL and the limit of detection was 0.099 ± 0.023 ng/mL, which was lower than that of UPLC-UV. The intra-day and inter-day accuracies of SPR were 98%–114% and 110%–122%, which met the analysis requirement. The results show that the SPR biosensor is identical to UPLC-UV in the detection of CAP in rat blood samples; moreover, the SPR biosensor has better sensitivity. Therefore, the present study shows that SPR technology can be used for the detection of small molecules in the blood samples and has the potential to become a method for therapeutic drug monitoring.

Abstract Background ASR (abscisic acid-, stress-, and ripening-induced) gene family plays a crucial role in responding to abiotic stresses in plants. However, the roles of ASR genes protecting plants against high salt and drought stresses remain unknown in Tamarix hispida. Results In this study, a salt and drought-induced ASR gene, ThASR3, was isolated from Tamarix hispida. Transgenic Arabidopsis overexpressing ThASR3 exhibited stimulating root growth and increasing fresh weight compared with wild-type (WT) plants under both salt and water deficit stresses. To further analyze the gain- and loss-of-function of ThASR3, the transgenic T. hispida plants overexpressing or RNA interference (RNAi)-silencing ThASR3 were generated using transient transformation. The overexpression of ThASR3 in Tamarix and Arabidopsis plants displayed enhanced reactive oxygen species (ROS) scavenging capability under high salt and osmotic stress conditions, including increasing the activities of antioxidant enzymes and the contents of proline and betaine, and reducing malondialdehyde (MDA) content and electrolyte leakage rates. Conclusion Our results indicate that ThASR3 functions as a positive regulator in Tamarix responses to salt and osmotic stresses and confers multiple abiotic stress tolerances in transgenic plants, which may have an important application value in the genetic improvement of forest tree resistance.

Amphotericin B (AmB) is a widely used antifungal agent especially for the therapy of systemic fungal infections. However, the severe side effects of AmB often leads to the premature termination of the treatment. So it is imperative to find the drugs that can both reduce the dosage and enhance the antifungal efficacy of AmB. Here we demonstrated that Nicotinamide (NAM), a cheap and safe vitamin, could enhance the antifungal activities of AmB. We demonstrated the synergistic interaction of NAM and AmB against Candida albicans as well as other Candida spp. and Cryptococcus neoformans. Moreover, NAM could enhance of the activity of AmB against biofilm. This enhancement was also observed in disseminated candidiasis in vivo. Our further study revealed that AmB could induce oxidative damage through the modification of histone acetylation. AmB could inhibit the expression of HST3, an H3K56 deacetylase in C. albicans. The immunoblotting test revealed excessive H3K56ac in AmB-treated fungal cells. Consistantly, the hst3Δ mutant displayed high sensitivity to AmB, while addition of NAM, an H3K56 deacetylation inhibitor, resulted in an even severe inhibition in the growth of this strain. These results indicated that AmB could execute antifungal activity via boosting H3K56ac which was mediated by HST3, and the mechanism for the synergistic interaction of NAM and AmB was based on exacerbating this process, which led to even excessive H3K56ac and oxidative damage. This finding provided theoretical basis for better understanding the antifungal mechanisms of AmB and clinical application of this drug.

Astragali Radix (AR) is a clinically used herbal medicine with multiple immunomodulatory activities that can strengthen the activity and cytotoxicity of natural killer (NK) cells. However, owing to the complexity of its composition, the specific active ingredients in AR that act on NK cells are not clear yet. Cell membrane chromatography (CMC) is mainly used to screen the active ingredients in a complex system of herbal medicines. In this study, a new comprehensive two-dimensional (2D) NK-92MI CMC/C18 column/time-of-flight mass spectrometry (TOFMS) system was established to screen for potential NK cell activators. To obtain a higher column efficiency, 3-mercaptopropyltrimethoxysilane-modified silica was synthesized to prepare the NK-92MI CMC column. In total, nine components in AR were screened from this system, which could be washed out from the NK-92MI/CMC column after 10 min, and they showed good affinity for NK-92MI/CMC column. Two representative active compounds of AR, isoastragaloside I and astragaloside IV, promoted the killing effect of NK cells on K562 cells in a dose-dependent manner. It can thus suggest that isoastragaloside I and astragaloside IV are the main immunomodulatory components of AR. This comprehensive 2D NK-92MI CMC analytical system is a practical method for screening immune cell activators from other herbal medicines with immunomodulatory effects.

Cell membrane affinity chromatography has been widely applied in membrane protein (MP)-targeted drug screening and interaction analysis. However, in current methods, the MP sources are derived from cell lines or recombinant protein expression, which are time-consuming for cell culture or purification, and also difficult to ensure the purity and consistent orientation of MPs in the chromatographic stationary phase. In this study, a novel in situ synthesis membrane protein affinity chromatography (iSMAC) method was developed utilizing cell-free protein expression (CFE) and covalent immobilized affinity chromatography, which achieved efficient in situ synthesis and unidirectional insertion of MPs into liposomes in the stationary phase. The advantages of iSMAC are: 1) There is no need to culture cells or prepare recombinant proteins; 2) Specific and purified MPs with stable and controllable content can be obtained within 2 h; 3) MPs maintain the transmembrane structure and a consistent orientation in the chromatographic stationary phase; 4) The flexible and personalized construction of cDNAs makes it possible to analyze drug binding sites. iSMAC was successfully applied to screen PDGFRβ inhibitors from Salvia miltiorrhiza and Schisandra chinensis. Micro columns prepared by in-situ synthesis maintain satisfactory analysis activity within 72 h. Two new PDGFRβ inhibitors, salvianolic acid B and gomisin D, were screened out with KD values of 13.44 and 7.39 μmol/L, respectively. In vitro experiments confirmed that the two compounds decreased α-SMA and collagen Ӏ mRNA levels raised by TGF-β in HSC-T6 cells through regulating the phosphorylation of p38, AKT and ERK. In vivo, Sal B could also attenuate CCl4-induced liver fibrosis by downregulating PDGFRβ downstream related protein levels. The iSMAC method can be applied to other general MPs, and provides a practical approach for the rapid preparation of MP-immobilized or other biological solid-phase materials.

Abstract Background Populus davidiana × P. bollena is a species of poplar from northeastern China that is characterized by cold resistance and fast growth but now suffers from pathogen infections. Leaf blight caused by Alternaria alternata has become a common poplar disease that causes serious economic impacts, but the molecular mechanisms of resistance to A. alternata in P. davidiana × P. bollena are still unclear. Results In this study, the transcriptomic response of P. davidiana × P. bollena to A. alternata infection was determined via RNA-Seq. Twelve cDNA libraries were generated from RNA isolated from three biological replicates at four time points (0, 2, 3, and 4 d post inoculation), and a total of 5,930 differentially expressed genes (DEGs) were detected (| log2 fold change |≥ 1 and FDR values

P-glycoprotein (P-gp) highly expressed in cancer cells can lead to multidrug resistance (MDR) and the combination of anti-cancer drugs with P-gp inhibitor has been a promising strategy to reverse MDR in cancer treatment. In this study, we established a label-free and detergent-free system combining surface plasmon resonance (SPR) biosensor with styrene maleic acid (SMA) polymer membrane proteins (MPs) stabilization technology to screen potential P-gp inhibitors. First, P-gp was extracted from MCF-7/ADR cells using SMA polymer to form SMA liposomes (SMALPs). Following that, SMALPs were immobilized on an SPR biosensor chip to establish a P-gp inhibitor screening system, and the affinity between P-gp and small molecule ligand was determined. The methodological investigation proved that the screening system had good specificity and stability. Nine P-gp ligands were screened out from 50 natural products, and their affinity constants with P-gp were also determined. The in vitro cell verification experiments demonstrated that tetrandrine, fangchinoline, praeruptorin B, neobaicalein, and icariin could significantly increase the sensitivity of MCF-7/ADR cells to Adriamycin (Adr). Moreover, tetrandrine, praeruptorin B, and neobaicalein could reverse MDR in MCF-7/ADR cells by inhibiting the function of P-gp. This is the first time that SMALPs-based stabilization strategy was applied to SPR analysis system. SMA polymer can retain P-gp in the environment of natural lipid bilayer and thus maintain the correct conformation and physiological functions of P-gp. The developed system can quickly and accurately screen small molecule ligands of complex MPs and obtain affinity between complex MPs and small molecule ligands without protein purification.

The application of machine learning (ML)-based methods to the study of thermoelectric (TE) materials is promising. Although conventional ML algorithms can achieve high prediction performance, their lack of interpretability severely obstructs researchers from extracting material-oriented insights from ML models. In this work, high ML-based prediction performance was achieved with respect to TE power factors (PFs), and the results were well understood by the SHapley Additive exPlanations (SHAP), a method to identify the correlations between targets and descriptors. We designed a robust PF prediction model for diamond-like compounds via a stacking technique, and the model achieved a coefficient of determination value above 0.95 on the test set. From the SHAP analysis, the PFs were negatively correlated with electronegativity and positively correlated with the descriptor “volume per atom” based on the previously reported dataset. TE domain knowledge was adopted to understand these correlations. This work shows that ML models can achieve high accuracy while exhibiting good interpretability, making them useful for materials scientists.

For accelerating the technology development and facilitating the reliable operation of lithium-ion batteries, accurate prediction for battery remaining useful life (RUL) are both critical. In this paper, a 1D CNN-BiLSTM method is proposed to extract the RUL prediction of lithium-ion battery of Electric Vehicles (EVs). By using one dimensional convolutional neural network (1D CNN) and bidirectional long short-term memory (BiLSTM) neural network simultaneously, selecting the ELU activation function to apply to the convolutional layer, a hybrid neural network is proposed to improve the accuracy and stability of lithium-ion battery RUL prediction. The 1D CNN is used to fully mine the deep features of lithium-ion SOH data, while the BiLSTM is adopted to study the deep features in two directions, and the RUL prediction of lithium-ion battery is output through dense layer. To verify the effectiveness of the proposed method, the battery data of the National Aeronautics and Space Administration (NASA) are utilized to make some comparisons among the RNN model, LSTM model, BiLSTM model and hybrid neural network model. The results show that the hybrid one has higher generalization ability and prediction accuracy than the others.

Gas hydrate is greatly developed in the Qiongdongnan Basin which is one of the key exploration targets in the South China Sea, but the geological study of gas hydrate is insufficient. With 3D seismic data interpretation, geochemical data analysis and a large number of investigations, a related research work of H zone in the Qiongdongnan Basin was carried out in this paper, with accumulation system as the main line and focused on migration and transportation system. According to the analysis of 48 sets of geochemical data, the hydrate decomposition gas in H zone has a methane carbon isotope value (δ13C1) of -48.2‰ and a higher content of ethane and propane (C2+=21%), indicating that the gas is mainly thermogenic, and some are mixed gas. Seismic interpretation showed that the Quaternary tectonic activity in H zone was weak, and the NNE-trending gas chimney structure group, polygonal fault-silt complex and submarine slump body constituted the main migrating system and high-quality reservoir in the study area. Based on the gas source characteristics and migrating system of natural gas hydrate in H zone, three accumulation types were proposed, including the gas chimney type hydrate rich in thermogenic gas, the polygonal fracture-silt composite hydrate rich in thermogenic gas, and the submarine slump hydrate rich in thermogenic gas and mixed genetic gas.

Abstract Background This study intends to establish a combined prediction model that integrates the clinical symptoms,the lung lesion volume, and the radiomics features of patients with COVID-19, resulting in a new model to predict the severity of COVID-19. Methods The clinical data of 386 patients with COVID-19 at several hospitals, as well as images of certain patients during their hospitalization, were collected retrospectively to create a database of patients with COVID-19 pneumonia. The contour of lungs and lesion locations may be retrieved from CT scans using a CT-image-based quantitative discrimination and trend analysis method for COVID-19 and the Mask R-CNN deep neural network model to create 3D data of lung lesions. The quantitative COVID-19 factors were then determined, on which the diagnosis of the development of the patients' symptoms could be established. Then, using an artificial neural network, a prediction model of the severity of COVID-19 was constructed by combining characteristic imaging features on CT slices with clinical factors. ANN neural network was used for training, and tenfold cross-validation was used to verify the prediction model. The diagnostic performance of this model is verified by the receiver operating characteristic (ROC) curve. Results CT radiomics features extraction and analysis based on a deep neural network can detect COVID-19 patients with an 86% sensitivity and an 85% specificity. According to the ROC curve, the constructed severity prediction model indicates that the AUC of patients with severe COVID-19 is 0.761, with sensitivity and specificity of 79.1% and 73.1%, respectively. Conclusions The combined prediction model for severe COVID-19 pneumonia, which is based on deep learning and integrates clinical aspects, pulmonary lesion volume, and radiomics features of patients, has a remarkable differential ability for predicting the course of disease in COVID-19 patients. This may assist in the early prevention of severe COVID-19 symptoms.

Purposes: To provide abdominal contrast-enhanced MR image synthesis, we developed an gradient regularized multi-modal multi-discrimination sparse attention fusion generative adversarial network (GRMM-GAN) to avoid repeated contrast injections to patients and facilitate adaptive monitoring. Methods: With IRB approval, 165 abdominal MR studies from 61 liver cancer patients were retrospectively solicited from our institutional database. Each study included T2, T1 pre-contrast (T1pre), and T1 contrast-enhanced (T1ce) images. The GRMM-GAN synthesis pipeline consists of a sparse attention fusion network, an image gradient regularizer (GR), and a generative adversarial network with multi-discrimination. The studies were randomly divided into 115 for training, 20 for validation, and 30 for testing. The two pre-contrast MR modalities, T2 and T1pre images, were adopted as inputs in the training phase. The T1ce image at the portal venous phase was used as an output. The synthesized T1ce images were compared with the ground truth T1ce images. The evaluation metrics include peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and mean squared error (MSE). A Turing test and experts’ contours evaluated the image synthesis quality. Results: The proposed GRMM-GAN model achieved a PSNR of 28.56, an SSIM of 0.869, and an MSE of 83.27. The proposed model showed statistically significant improvements in all metrics tested with p-values < 0.05 over the state-of-the-art model comparisons. The average Turing test score was 52.33%, which is close to random guessing, supporting the model’s effectiveness for clinical application. In the tumor-specific region analysis, the average tumor contrast-to-noise ratio (CNR) of the synthesized MR images was not statistically significant from the real MR images. The average DICE from real vs. synthetic images was 0.90 compared to the inter-operator DICE of 0.91. Conclusion: We demonstrated the function of a novel multi-modal MR image synthesis neural network GRMM-GAN for T1ce MR synthesis based on pre-contrast T1 and T2 MR images. GRMM-GAN shows promise for avoiding repeated contrast injections during radiation therapy treatment.

The incidence of fungal infections has increased continuously in recent years. Caspofungin (CAS) is one of the first-line drugs for the treatment of systemic fungal infection. However, the emerging CAS-resistant clinical isolates and high economic cost for CAS administration hamper the wide application of this drug. Thus, the combined administration of CAS with other compounds that can enhance the antifungal activity and reduce the dose of CAS has gained more and more attention. In this study, we investigated the effect of mangiferin (MG) on the antifungal activities of CAS. Our results showed that MG acted synergistically with CAS against various Candida spp., including CAS-resistant C. albicans. Moreover, MG could enhance the activity of CAS against biofilm. The in vivo synergism of MG and CAS was further confirmed in a mouse model of disseminated candidiasis. To explore the mechanisms, we found that SPE1-mediated polyamine biosynthesis pathway was involved in the fungal cell stress to caspofungin. Treatment of CAS alone could stimulate SPE1 expression and accumulation of polyamines, while combined treatment of MG and CAS inhibited SPE1 expression and destroyed polyamine accumulation, which might contribute to increased oxidative damage and cell death. These results provided a promising strategy for high efficient antifungal therapies and revealed novel mechanisms for CAS resistance.

Summary: Owing to the impact of the western development of China, there have been signs of air pollution over the Qinghai-Tibet Plateau in recent years. However, monitoring data on atmospheric volatile organic compounds (VOCs) are lacking in plateau areas. Here, VOCs concentrations in urban and background areas in North China and the Qinghai-Tibet Plateau were observed from 2012 to 2014 and 2020 to 2022, respectively. Compared to 2012–2014, the concentration of VOCs increased to 2.5 times in urban areas on the Qinghai-Tibet Plateau, which was equivalent to that in North China. Oil, gas, and solvent evaporation caused by a low atmospheric pressure is the primary factor for the increase in VOCs in plateau areas, and weak VOCs degradation is the secondary factor. Hence, we put forward the VOCs control strategies in plateau areas and point out the defects in the current research.

Abstract Background Transketolase (TKT), a key rate‐limiting enzyme in the non‐oxidative branch of the pentose phosphate pathway (PPP), provides more than 85% of the ribose required for de novo nucleotide biosynthesis and promotes the development of hepatocellular carcinoma (HCC). Pharmacologic inhibition of TKT could impede HCC development and enhance treatment efficacy. However, no safe and effective TKT inhibitor has been approved. Methods An online two‐dimensional TKT protein immobilised biochromatographic system was established for high‐throughput screening of TKT ligands. Oroxylin A was found to specifically bind TKT. Drug affinity responsive target stability, cellular thermal shift assay, surface plasmon resonance, molecular docking, competitive displacement assay, and site mutation were performed to identify the binding of oroxylin A with TKT. Antitumour effects of oroxylin A were evaluated in vitro, in human xenograft mice, diethylnitrosamine (DEN)‐induced HCC mice, and patient‐derived organoids (PDOs). Metabolomic analysis was applied to detect the enzyme activity. Transcriptome profiling was conducted to illustrate the anti‐HCC mechanism of oroxylin A. TKT knocking‐down HCC cell lines and PDOs were established to evaluate the role of TKT in oroxylin A‐induced HCC suppression. Results By targeting TKT, oroxylin A stabilised the protein to proteases and temperature extremes, decreased its activity and expression, resulted in accumulation of non‐oxidative PPP substrates, and activated p53 signalling. In addition, oroxylin A suppressed cell proliferation, induced apoptosis and cell‐cycle arrest, and inhibited the growth of human xenograft tumours and DEN‐induced HCC in mice. Crucially, TKT depletion exerted identical effects to oroxylin A, and the promising inhibitor also exhibited excellent therapeutic efficacy against clinically relevant HCC PDOs. Conclusions These results uncover a unique role for oroxylin A in TKT inhibition, which directly targets TKT and suppresses the non‐oxidative PPP. Our findings will facilitate the development of small‐molecule inhibitors of TKT and novel therapeutics for HCC.

The state of health (SOH) and remaining useful life (RUL) of lithium-ion batteries describe the current aging degree of the batteries from different perspectives, and accurate and efficient battery health estimation is essential for their safe use. To improve the effectiveness and accuracy of the batteries’ health assessment models, this paper proposes a new method for SOH and RUL estimation of lithium-ion batteries. Convolutional neural networks (CNNs), bi-directional long short-term memory (BiLSTM), and attention mechanism (AM) to build a hybrid network model for capacity estimation of lithium-ion batteries, and further calculate the SOH and RUL estimation results. By using Center for Advanced Life Cycle Engineering (CALCE) lithium-ion battery capacity degradation data, we extracted the battery health indicator (HI) and verified the reasonableness of HI selection by using Gray Relational Analysis (GRA) and compared it with other network models to calculate the prediction accuracy by various evaluation indexes. The experimental results show that the method has higher estimation accuracy while avoiding the construction of complex battery mechanism degradation models and is highly generalized.

Objective: Long-term use of olanzapine can induce various side effects such as lipid metabolic disorders, but the mechanism remains to be elucidated. The gut microbiota-brain axis plays an important role in lipid metabolism, and may be related to the metabolic side effects of olanzapine. Therefore, we explored the mechanism by which olanzapine-induced lipid disturbances through the gut microbiota-brain axis.Methods: Sprague Dawley rats were randomly divided into two groups, which underwent subphrenic vagotomy and sham surgery. Then the two groups were further randomly divided into two subgroups, one was administered olanzapine (10 mg/kg/day) by intragastric administration, and the other was administered normal saline by intragastric administration (4 ml/kg/day) for 2 weeks. The final changes in lipid parameters, gut microbes and their metabolites, and orexin-related neuropeptides in the hypothalamus were investigated among the different groups.Results: Olanzapine induced lipid disturbances as indicated by increased weight gain, elevated ratio of white adipose tissue to brown adipose tissue, as well as increased triglyceride and total cholesterol. Olanzapine also increased the Firmicutes/Bacteroides (F/B) ratio in the gut, which was even aggravated by subphrenic vagotomy. In addition, olanzapine reduced the abundance of short-chain fatty acids (SCFAs) metabolism related microbiome and 5-hydroxytryptamine (5-HT) levels in the rat cecum, and increased the gene and protein expression of the appetite-related neuropeptide Y/agouti-related peptide (NPY/AgRP) in the hypothalamus.Conclusion: The abnormal lipid metabolism caused by olanzapine may be closely related to the vagus nerve-mediated gut microbiota-brain axis.

Background: Hepatocellular carcinoma (HCC) is one of the most common malignancies in China. Most HCC patients are firstly diagnosed at an advanced stage, and systemic treatments are the mainstay of treatment. Summary: In recent years, immune checkpoint inhibitors have made a breakthrough in the systemic treatment of middle-advanced HCC, breaking the single therapeutic pattern of molecular targeted agents. To better guide the clinical treatment for effective and safe use of immunotherapeutic drugs, the Chinese Association of Liver Cancer and Chinese Medical Doctor Association has gathered multidisciplinary experts and scholars in relevant fields to formulate the “Chinese Clinical Expert Consensus on Immunotherapy for Hepatocellular Carcinoma (2021)” based on current clinical studies and clinical medication experience for reference in China. Key messages: The consensus contained 17 recommendations, including the preferred regimen for first- and second-line immunotherapy, evaluation and monitoring before/during/after treatment, management of complications, precautions for special patients and potential population for immunotherapy.

Liver fibrosis is currently a global health challenge with no approved therapy, with the activation of hepatic stellate cells being a principal factor. Lipophilic constituents in Salvia miltiorrhiza (LS) have been reported to improve liver function and reduce the indicators of liver fibrosis for patients with chronic hepatitis B induced hepatic fibrosis. However, the pharmacological mechanisms of LS on liver fibrosis have not been clarified. In this study, 71 active compounds, 342 potential target proteins and 22 signaling pathways of LS were identified through a network pharmacology strategy. Through text mining and data analysis, the JAK1/STAT3 signaling pathway was representatively selected for further experimental validation. We firstly confirmed the protective effect of LS on liver fibrosis in vivo by animal experiments. Hepatic stellate cells, which proliferated and displayed a fibroblast-like morphology similar to activated primary stellate cells, were applied to evaluate its underlying mechanisms. The results showed that LS could inhibit the cell viability, promote the cell apoptosis, decrease the expression of liver fibrosis markers, and downregulate the JAK1/STAT3 signaling pathway. These results demonstrated that LS could exert anti-liver-fibrosis effects by inhibiting the activation of HSCs and regulating the JAK1/STAT3 signaling pathway, which is expected to benefit its clinical application.

The Qiongdongnan Basin is an important gas hydrate exploration area in the South China Sea, but the gas hydrate accumulation process is poorly understood. By selecting an Lingshui (LS) target area and using first-hand geochemical data, three-dimensional seismic data, and an independent thermal insulation and pressure maintaining shipborne core analysis system, in this study, comprehensive geological evaluation was carefully conducted around the gas source and reservoir of the gas chimney hydrates, and the accumulation process was investigated. Geochemical data for a total of 47 sets of gas samples revealed that the gas source of the hydrates in the study area was mainly thermogenic gas supplemented by mixed gas. It was predicted that the contribution of the thermogenic gas to the hydrate accumulation was up to 70%. Using the independent shipborne core analysis system, the characteristics of the low-temperature combustible gas hydrates were determined, and the reservoir in the study area was characterized as non-diagenetic to weakly diagenetic, rich in clay and silt (D50 = 15.1–34.1 μm), weakly self-sustaining, and strongly heterogeneous. Based on the differentiated seismic response of the hydrate layer-gas bearing hydrate layer-shallow gas layer at the top of the gas chimney, the accumulation process in the target area was determined to be as follows: remote thermogenic gas transportation, local microbial genetic gas accumulation, episodic dynamic gas chimney reservoir formation, and source-reservoir control. In addition, the exploration ideas of an effective supply from a gas source and a shallow large-scale sand body are emphasized. The results of this study provide an important reference for the trial production of natural gas hydrates in the South China Sea.

Machine learning is a major means to realize artificial intelligence (AI), which can provide support for decision making through exploration of data law and establishment of prediction model. Since the oil and gas pipeline system has the characteristics of numerous equipment, complicated structure and complex technology, machine learning is introduced to solve the problems that are hard to solve with pure mathematical models with AI technology and to replace personnel to complete some boring, tedious and dangerous tasks. Here, the application of 3 types of machine leaning, such as deep learning, reinforcement learning and transfer learning, were reviewed with reference to the production process of oil and gas pipeline system, covering the application scenarios like pipeline leakage, recognition of multi-phase flow pattern, equipment fault diagnosis and tank target detection. The application framework of AI technology in oil and gas pipeline systems was established, and it was also pointed out that the application of deep learning, reinforcement learning and transfer learning in this field was prospective. Finally, the application of machine learning in oil and gas pipelines was prospected, so as to provide references for the intelligent research and development of oil and gas pipeline systems.

This paper designs a sampled-data controller to exponentially stabilize a kind of chaotic systems (CSs) which are represented by T-S fuzzy model with nonuniform sampling. By employing a switched technology and Lyapunov functional dependent on fuzzy membership-functions (FMFs), a new control criterion for chaotic systems was established. Compared with the existing methods, less conservatism and a large sampling period can be obtained by above approaches. Consequently, the amount of transmitted information is greatly reduced and the efficiency of bandwidth is much improved. Finally, the proposed T-S fuzzy sampled-data (TSFSD) controller is applied to Lorenz system to prove the effectiveness of those methods.

As an important part of demand side, residential users have the characteristics of imperfect rationality and strong randomness, which are rarely considered in the existing study. Moreover, to effectively improve the energy efficiency, integrated demand response (IDR) is proposed as an effective measure to reduce the local energy supply pressure. This paper focuses on a scenario for IDR programs, in which the intelligent building aggregator (IBA) wants to encourage residential users to participate in IDR according to a proper contract price policy. To analyze how the participation degree tendency evolves over time, an evolutionary game approach is proposed considering residential users' bounded-rationality. A symmetric evolutionary game model and an asymmetric evolutionary game model are established, and the stability of equilibrium points in the above models is proven. Simulation results show that different contract price policies will obviously influence residential users' strategy, and affect the stable equilibrium points of the evolutionary game. The simulation results provide an effective reference for IBA to set proper and effective price incentives.

Observations of optical and near-infrared counterparts of binary neutron star mergers not only enrich our knowledge about the abundance of heavy elements in the universe and help reveal the remnant object just after the merger, which is generally known, but can also effectively constrain the dense properties of the nuclear matter and the equation of state (EOS) in the interior of the merging stars. Following the relativistic mean-field description of nuclear matter, we perform a Bayesian inference of the EOS and the properties of the nuclear matter using the first multi-messenger event GW170817/AT2017gfo, together with the NICER mass–radius measurements of pulsars. The kilonova is described by a radiation-transfer model with the dynamical ejecta, and light curves connect with the EOS through the quasi-universal relations between the properties of the ejecta (the ejected mass, velocity, opacity, or electron fraction) and binary parameters (the mass ratio and reduced tidal deformability). It is found that the posterior distributions of the reduced tidal deformability from the AT2017gfo analysis display a bimodal structure, with the first peak enhanced by the GW170817 data, leading to slightly softened posterior EOSs, while the second peak cannot be achieved by a nuclear EOS with saturation properties in their empirical ranges. The inclusion of NICER data results in a stiffened EOS posterior because of the massive pulsar PSR J0740+6620. We provide the results at nuclear saturation density for the nuclear incompressibility, the symmetry energy, and its slope, as well as the nucleon effective mass, from our analysis of the observational data.

Aim: Interpersonal sensitivity and mistrust are the main characteristics of cluster A personality disorders (CAPD) which might be due to the high accessibility to negative suggestions from environments. Yet the exact associations between hypnotic suggestibility and their personality disorder functioning styles remain unclear. Methods: We invited 36 patients with CAPD and 115 healthy volunteers to undergo the Stanford Hypnotic Susceptibility Scale: Form C (SHSS:C) and Parker Personality Measure (PERM). Results: Compared to controls; patients scored higher on PERM paranoid; schizoid; schizotypal; borderline; avoidant; and dependent styles; on the SHSS:C total and “challenge suggestions”, and the passing rates of “hand lowering”, “arm rigidity”, “dream”, and “arm immobilization”. In patients, “dream” negatively predicted the schizoid; “hallucinated voice” negatively the schizotypal; “mosquito hallucination” positively the histrionic and dependent; and “arm immobilization” negatively the avoidant style. Conclusions: Our results suggested that the insusceptibility to perceptual suggestions from others and the high control over body contribute to the paranoid attitude and interpersonal avoidance in CAPD. These findings help to understand the cause of interpersonal problems in these patients and suggest the trial of hypnotherapy for them.

ObjectiveTo investigate the MRI features and clinical significance of hepatic epithelioid hemangioendothelioma (HEHE).MethodsClinical records and MRI findings were retrospectively evaluated in nine HEHE patients from May 2010 to January 2020.ResultThere were 121 lesions in nine patients with a predominantly peripheral distribution. Five lesions (4.13%) in two patients (22.22%) had evidence of capsular retraction, and three patients had lung metastasis (33.33%). Dynamic contrast-enhanced MRI showed progressive enhancement, mainly in two ways: ring enhancement with hypovascularity in four patients (44.44%) and ring enhancement with hypervascularity in five patients (55.56%). Imaging demonstrated a multilayer ring appearance, which was typically observed on T2-weighted imaging (T2WI). The most common appearance consisted of two layers of varying signal, with some images displaying up to four layers. There were significant differences in the size of lesions between different layers of multilayer ring appearance (p < 0.001). All lesions exhibited a two-layer appearance on diffusion-weighted imaging (DWI), with hyperintensity at the periphery and a slightly high signal at the center (except for those with a single layer on T2WI). The “vascular penetration sign” was observed in most lesions, and the blood vessels of 112 lesions (92.56%) were portal vein branches, and five (4.13%) were hepatic vein branches. Pulmonary metastasis was found in three patients with the “vascular penetration sign” of hepatic vein branches.ConclusionThe multilayer ring appearance on T2WI, the “vascular penetration sign”, and the two enhancement patterns may be of great significance in the diagnosis and treatment of HEHE. The “vascular penetration sign” of hepatic vein branches may indicate extrahepatic metastasis.

Brillouin optical time domain analyzer (BOTDA) assisted by optimized support vector machine (SVM) algorithm for accurate temperature extraction is presented and experimentally demonstrated. Three typical intelligent optimization algorithms, particle swarm optimization algorithm, genetic algorithm and firefly algorithm are explored to optimize the SVM parameters. The performances of optimized SVM algorithms for temperature extraction are investigated in both simulation and experiment under different conditions for Brillouin gain spectrum collection, resulting in the significant enhancement of sensing accuracy. In particular, the extraction accuracy (i.e., smaller root mean square error value) of temperature information is improved about 4 °C compared with the conventional SVM when the signal-to-noise ratio (SNR) as low as 2.5 dB and 40-ns pump pulse width are adopted in the experiment. In addition to the enhanced accuracy with good robustness, the optimized algorithms have faster processing speed than the curve fitting method, over 20-times improvement. That makes the optimized algorithms become a very promising candidate for high performance BOTDA sensors in the future.

Recent research indicates that after spinal cord injury (SCI), microglia accumulate at the borders of lesions between astrocytic and fibrotic scars and perform inflammation-limiting and neuroprotective functions, however, the mechanism of microglial migration remains unclear. Fascin-1 is a key actin-bundling protein that regulates cell migration, invasion and adhesion, but its role during SCI has not been reported. Here, we found that at 7–14 days after SCI in mice, Fascin-1 is significantly upregulated, mainly distributed around the lesion, and specifically expressed in CX3CR1-positive microglia. However, Fascin-1 is not expressed in GFAP-positive astrocytes, NeuN-positive neurons, NG2-positive cells, PDGFRβ-positive cells, or blood-derived Mac2-positive macrophages infiltrating into the lesion core. The expression of Fascin-1 is correspondingly decreased after microglia are specifically depleted in the injured spinal cord by the colony-stimulating factor 1 receptor (CSF1R) inhibitor PLX5622. The upregulation of Fascin-1 expression is observed when microglia are activated by myelin debris in vitro, and microglial migration is prominently increased. The inhibition of Fascin-1 expression using small interfering RNA (siRNA) markedly suppresses the migration of microglia, but this effect can be reversed by treatment with myelin. The M1/M2-like polarization of microglia does not affect the expression of Fascin-1. Together, our results suggest that Fascin-1 is highly expressed specifically in microglia after SCI and can play an important role in the migration of microglia and the formation of microglial scars. Hence, the elucidation of this mechanism will provide novel therapeutic targets for the treatment of SCI.

During the charging process of the electric vehicle (EV), a spontaneous combustion accident may occur due to overheating of the battery, causing personal danger and property damage. To address the charging safety of EVs, this paper proposes a new hybrid EV charging process early warning protection method by combining Convolutional Long-Short Term Memory (ConvLSTM), the sliding window method, and the residual analysis method. The method is fully trained by extracting the deep features of EV charging data through ConvLSTM, eliminating the influence of erroneous transmission data through the sliding window method, and setting a reasonable warning threshold through the residual analysis method. The cross-validation results showed that among the four training sets, the ConvLSTM model of training, set three, had the highest prediction accuracy compared with the CNN, LSTM, BiLSTM and CNN-LSTM models, with RMSE reaching 0.029, MAPE reaching 11.37, and r2 reaching 0.89. Training set one had the worst prediction in the four training sets, and after using it to set the warning threshold, the alarm task was completed five sampling points earlier. Therefore, the hybrid model can quickly complete the safety warning task, thereby ensuring the safety of EV charging.

ABSTRACTDevelopment of antifungal agents with novel mechanism and low toxicity are essential due to the prevalence of the infectious diseases caused by Candida albicans. The current study employed a new research method, which combined the ultra-high performance liquid chromatography with quadrupole time-of-flight mass spectrometry and gas chromatography-mass spectrometry, to investigate the intrinsic mechanism of Shikonin (SK) against C. albicans. The levels of 27 metabolites, which mainly involved in histone deacetylation, amino acid synthesis, lipid synthesis, nitrogen metabolism, tricarboxylic acid cycle, oxidative stress and glycolysis, were remarkably changed upon SK treatment. Specially, the down-regulation of nicotinamide (NAM) upon SK treatment indicated the suppression of the deacetylation of the histone H3 on lysine 56 residue (H3K56). Further experiment confirmed that the level of H3K56 acetylation (H3K56ac) was dramatically increased upon SK treatment which was mediated by HST3, the gene encoding the H3K56 deacetylase (Hst3p). Our results demonstrated that SK is the first natural compound reported to execute antifungal activity directly via boosting H3K56ac mediated by HST3. Importantly, this finding shed new light on the mechanisms to relieve the side effects or reverse the drug tolerance, as well as the development of agents for antifungal therapies.

The time-frequency analysis (TFA) by wavelet transform is adopted for the laser ultrasonic signal processing, and the effective features extraction of the material defect is obtained. The TFA is adopted here to analyze the laser-generated surface acoustic wave (SAW) signal which contains the defect features, the echo wave features are extracted significantly, especially under the condition of low signal-to-noise rate (SNR). The simulation model by using finite element method (FEM) is set up in an aluminum plate with different surface defect depths in detail, and the defect depths prediction with TFA is also considered. It shows that, without extra denoising process, the echo SAW is extracted significantly in case of defect depths ranging from 0.1mm to 0.9mm at SNR of -3dB by TFA. The TFA for processing the laser ultrasonic signal provides a promising way to get the defect information, with the accuracy increased by 7.9dB in this work, which is extremely meaningful for the ultrasonic signal processing and material evaluation.

This paper investigates the problem of fuzzy state feedback control for a category of fuzzy-model-based coronary artery system(FMBCAS) with state time-delay. T-S fuzzy model is employed to close in coronary artery system(CAS) which exists unknown nonlinear characteristics. Through the use of linear matrix inequality technique, the synchronization controller for CAS are obtained. By utilizing the delay-partitioning method, we can get a less conservative results. The Bessel-Legendre inequality and the Moon's et al. inequality with convex analysis are used to further reduce the conservatism of the system. Finally, a simulation of CAS proves the effectiveness of our strategy.

Wave velocity under different pressure and temperature (PT) conditions plays an important role in the exploration of oil and gas reservoirs. We obtained the mineral composition and porosity of 20 underground sandstone and mudstone samples in Yinggehai Basin via X-ray diffraction and porosity measurements. Using high-frequency ultrasound, the P- and S-wave velocities of four samples under high temperature and overpressure conditions were found to vary significantly, owing to the material composition and porosity. According to the comparison between the experimental conclusion and the well-logging data, the genesis of false bright spot and dark spot gas reservoirs in the study area was analyzed. The variation in P-wave velocity under different temperature and pressure conditions was explained with the PT coefficient. The traditional pressure–velocity and temperature–velocity prediction methods were improved and applied to well-logging data. Herein, the velocity of P- or S-waves of sand and mudstone under high temperature and overpressure via rock physics experiments and the genesis of false bright spot and dark spot gas reservoirs in the Yinggehai Basin was observed. Overall, the results serve as a theoretical basis for seismic exploration in the study area.

Deformable image registration is of essential important for clinical diagnosis, treatment planning, and surgical navigation. However, most existing registration solutions require separate rigid alignment before deformable registration, and may not well handle the large deformation circumstances. We propose a novel edge-aware pyramidal deformable network (referred as EPReg) for unsupervised volumetric registration. Specifically, we propose to fully exploit the useful complementary information from the multi-level feature pyramids to predict multi-scale displacement fields. Such coarse-to-fine estimation facilitates the progressive refinement of the predicted registration field, which enables our network to handle large deformations between volumetric data. In addition, we integrate edge information with the original images as dual-inputs, which enhances the texture structures of image content, to impel the proposed network pay extra attention to the edge-aware information for structure alignment. The efficacy of our EPReg was extensively evaluated on three public brain MRI datasets including Mindboggle101, LPBA40, and IXI30. Experiments demonstrate our EPReg consistently outperformed several cutting-edge methods with respect to the metrics of Dice index (DSC), Hausdorff distance (HD), and average symmetric surface distance (ASSD). The proposed EPReg is a general solution for the problem of deformable volumetric registration.

With the continuous increase of railway transportation volume, the aging problem of railway tunnel bottom structure is becoming more and more serious, which seriously threatens the safe operation of trains. Based on the cause analysis and field detection of the defects at the railway tunnel bottom structure, the “Anchor-Grouting-Drainage” treatment technology of the railway tunnel bottom structure is summarized. The research shows that (1) the technology is simple and can effectively repair the defects of railway tunnel bottom structure under the conditions of the narrow site, short time of maintenance skylight, strict requirements of track size variation, and no interference with the normal operation of the train, which has great significance and broad application prospect. (2) The drainage system of the existing railway tunnel bottom structure can be applied to the reconstruction of the railway tunnel bottom structure. The high-strength transverse diversion structure at the bottom of the tunnel has the advantages of strong bearing capacity, large drainage capacity, and corrosion resistance, which can provide a reference for the subsequent implementation of the reconstruction project at the railway tunnel bottom structure.

In this paper, 25-ton and 27-ton axle heavy trucks are used to carry out moving loading and dynamic real vehicle test on the cracked section, the intact section, and the repaired section of a railway tunnel foundation to test the dynamic performance of the tunnel basement structure with the change of axle loads and health conditions. By analyzing the influence law of dynamic response and fatigue life of heavy haul train under different basement conditions (intact, damaged, and repaired), the adaptability of railway tunnel equipment to freight trucks axle load is clarified. The results show that (1) the intact section of the tunnel can meet the normal operation of 25-ton and 27-ton axle load freight trains in good condition. (2) The normal operation of 25-ton and 27-ton axle load freight trucks is seriously affected by the cracked section of the tunnel. When the cracks in the tunnel basement are gradually hollowed out by groundwater, serious traffic accidents such as vehicle shaking and derailment are likely to occur. (3) The repaired section of the tunnel can meet the normal operation of 25-ton and 27-ton axle load freight trains after adopting the integrated comprehensive treatment of “Anchor-Injection-Drainage”. The research results will have reference significance for the condition assessment and disease treatment of the basement structure of the heavy haul railway tunnel.