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This study aims to quantitatively analyze the three-dimensional microstructure of ultra-thin HDF paving boards and molding boards, in order to explore the modeling methods of HDF and attempt to predict its mechanical properties more accurately through theoretical and simulation analyses. In this study, non-destructive analysis of the internal microstructure was conducted using computed tomography (CT) imaging technology. The characteristics of microstructural evolution during the hot compression molding process were explored, and all analyzed data were utilized for 3D reconstruction and simulation model construction. Ultra-thin fiberboards with different fiber ratios were modeled through volume compression and experimentally simulated in tension. The results were compared with experimentally determined results for verification purposes. Additionally, differences in surface roughness, water absorption, and expansion of ultra-thin fiberboards with varying fiber ratios were analyzed. The findings indicate that different fiber ratios have a significant impact on the mechanical properties of ultra-thin fiberboards; tensile strength increases with an increase in medium-length fibers content when fibers are pulled or split, highlighting the key role played by the strength of the fibers themselves. Furthermore, it was observed that surface roughness and water-absorbing expansion rate are lower when a higher proportion of fine fibers is present. The results from this study hold great significance for gaining a deeper understanding of the composition, structure, and properties of ultra-thin fiberboards as well as exploring modeling methods for high-density fiberboards. They also provide guidance for optimizing material formulations and preparation processes while improving performance and quality standards for poplar-ultra-thin fiberboards. • We quantitatively analysed the three-dimensional microstructure of ultra-thin fibreboard paving slabs and moulded panels. • We explored the modelling method of high-density fibreboard and obtained a model of high-density fibreboard with a volume fraction of 90%. • We explored the effects of different fibre ratios on the mechanical properties of ultra-thin fibreboards. [ABSTRACT FROM AUTHOR]

Estrogen receptor (ER) is a major transcriptional regulator that plays an important role in the treatment of breast cancer. Herein, we rationally designed and synthesized a novel small-molecule near-infrared (NIR) fluorescent probe, 2-(4-(2-(2,5-bis(2-fluoro-4-hydroxyphenyl)thiophen-3-yl)vinyl)− 3-cyano-5,5-dimethylfuran-2(5 H)ylidene)malononitrile (TCFT) , which could enable prolonged live-cell imaging by three-dimensional (3D) confocal microscopy. Moreover, this bifunctional probe also exhibited photostability, selective estrogen receptor modulator activity, and potent antiproliferative activity for targeted breast cancer therapy, which would be a prominent NIR fluorescent probe for breast cancer study. [Display omitted] • A novel photostable NIR fluorescent probe TCFT was developed for estrogen receptor. • TCFT was successfully applied in prolong live-cell imaging of estrogen receptor by 3D confocal microscopy. • TCFT exhibited selective estrogen receptor modulator activity and potent antiproliferative activity for breast cancer therapy. • TCFT possessed the potential as a theranostic probe for estrogen receptor (+) breast cancer study. [ABSTRACT FROM AUTHOR]

The aim of this study was to evaluate diagnostic performance of radiomics models of MRI in the detection of differentiation degree (DD) and lymph node metastases (LNM) of extrahepatic cholangiocarcinoma (ECC). We retrospectively enrolled 100 patients with ECC confirmed by pathology from January 2011 to December 2018. Three hundred radiomics features were extracted from each region of interest using MaZda software. Next, the radiomics model was developed by incorporating the optimal radiomics signatures and ADC values of tumors to predict DD (model A) and LNM (model B) of ECC, respectively, through the random forest algorithm. After which, the performance of the radiomics models were further evaluated. The model A showed better performance in both training and testing cohorts to discriminate high and medium-low differentiation groups of ECC, with an average AUC of 0.78 and 0.80, respectively. The model B also yielded the good average AUC of 0.80 and 0.90 to predict the LNM of ECC in training and testing cohorts. The radiomics models based on MRI performed well in predicting DD and LNM of ECC and have significant potential in clinical noninvasive diagnosis and in the prediction of ECC. [ABSTRACT FROM AUTHOR]

Background: Most cases of extrahepatic cholangiocarcinoma (ECC) show various degrees of hyperintensity on diffusion-weighted imaging (DWI) and hypointensity on apparent diffusion coefficient (ADC). However, the factors influencing ADC values in ECC have not yet been explored extensively. Therefore, this study explored the independent factors influencing ADC values in ECC.Methods: A total of 88 patients with ECC confirmed by surgical pathology were retrospectively assessed. All patients underwent abdominal magnetic resonance imaging (MRI) at 3.0 T and ADC values of the tumor were measured. The correlation between ADC values and multiple clinicopathological features in ECC was analyzed, and independent factors influencing the ADC values in ECC were explored further.Results: The ADC value of the tumor showed a significant difference in different perineural invasion group (p = 0.048), microvascular invasion group (p = 0.001), vascular endothelial growth factor expression group (p < 0.001), lymphatic status group (p = 0.003), and differentiation degree (DD) group (p < 0.001). However, there were no significant differences in different sex (p = 0.715), tumor location (p = 0.659), and degree of T stage (p = 0.879). Moreover, ADC value was negatively correlated with microvascular density (r = -0.725, p < 0.001) and lesion size (r = -0.244, p = 0.023). Nevertheless, there was no correlation between ADC value and patient age (r = 0.026, p = 0.812). Further regression analysis indicated that ADC value was independently associated with pathological DD of ECC (R2 = 0.678, p < 0.001) but not with other clinicopathological factors (p > 0.05).Conclusion: ADC value of ECC is independently correlated with pathological DD of ECC, indicating that ADC value is a potential imaging biomarker for predicting the degree of ECC malignancy. [ABSTRACT FROM AUTHOR]

Titanium nitride nanoparticles (TiN NPs) are proposed as a novel catalyst towards the V(II)/V(III) redox pair for the negative electrode in vanadium redox flow batteries (VRFB). Electrochemical properties of TiN NPs were characterized by cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). The results show that TiN NPs demonstrate better electrochemical activity and reversibility for the processes of V(II)/V(III) redox couples as compared with the graphite NPs. TiN NPs facilitate the charge transfer in the V(II)/V(III) redox reaction. Performance of a VRFB using a TiN NPs coated carbon paper as a negative electrode is much higher than that of a VRFB with a raw carbon paper electrode. The columbic efficiency (CE), the voltage efficiency (VE) and the energy efficiency (EE) of the VRFB single cell at charge-discharge current density of 30 mA/cm 2 are 91.74%, 89.11% and 81.74%, respectively. During a 50 charge-discharge cycles test, the CE values of VRFB with TiN NPs consistently remain higher than 90%. [ABSTRACT FROM AUTHOR]

[Display omitted] • Graphene induced conformation changes of SARS-CoV-2 spike RBD are studied by MD simulations. • Graphene significantly affects the secondary structure of the three key sites binding with ACE2. • Both π–π stacking and hydrophobic interactions orchestrate RBD adsorption. • To develop graphene-based protective equipments to defeat SARS-CoV-2 is possible. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been widely spread in the world, causing more than two million deaths and seriously threatening human life. Effective protection measures are important to prevent the infection and spreading of the virus. To explore the effects of graphene on the virus adsorption and its biological properties, the adsorption process of the receptor binding domain (RBD) of SARS-CoV-2 on graphene has been investigated by molecular dynamics simulations in this paper. The results show that RBD can be quickly adsorbed onto the surface of graphene due to π - π stacking and hydrophobic interactions. Residue PHE486 with benzene ring has stronger adsorption force and the maximum contact area with graphene. Graphene significantly affects the secondary structure of RBD area, especially on the three key sites of binding with human ACE2, GLY476, PHE486 and ASN487. The binding free energy of RBD and graphene shows that the adsorption is irreversible. Undoubtedly, these changes will inevitably affect the pathogenicity of the virus. Therefore, this study provides a theoretical basis for the application of graphene in the protection of SARS-CoV-2, and also provides a reference for the potential application of graphene in the biomedical field. [ABSTRACT FROM AUTHOR]

[Display omitted] • Fe 3 O 4 Fe 3 O 4 with small particles was compounded with BiOBr/BiOI(3:1) by solvothermal method. • The magnetism of Fe 3 O 4 /BiOBr/BiOI (1.1:3:1) is larger than that of previous studies. • Fe 3 O 4 /BiOBr/BiOI (1.1:3:1) exhibits good adsorption capacity and photocatalytic performance. • Fe 3 O 4 /BiOBr/BiOI (1.1:3:1) presents excellent recyclability and stability. Ternary magnetic Fe 3 O 4 /BiOBr/BiOI (1.1:3:1) with good magnetic separation performance and photocatalytic degradation performance was synthesized by two-step method. These properties remained good after repeated use for 10 times. Compared with Fe 3 O 4 /BiOBr/BiOI (0.5:2:2) prepared by other research group, the magnetism Fe 3 O 4 /BiOBr/BiOI (1.1:3:1) were 1.76 times that of it. Compared with the previous work, Fe 3 O 4 /BiOBr/BiOI (1.1:3:1) has advantages in magnetism, degradation activity and reusability. All results suggested that the Fe 3 O 4 /BiOBr/BiOI (1.1:3:1) with good photocatalytic performance, good magnetic separability, excellent recyclability, and stability has a good application prospect in photocatalytic degradation organic wastewater. [ABSTRACT FROM AUTHOR]

Abstract: Through structure-based virtual screening, some dozen of benzene sulfonamides with novel scaffolds are identified as potent inhibitors against carbonic anhydrase (CA) IX with IC50 values ranging from 2.86 to 588.34nM. Among them, compounds 1 and 9 show high selectivity against tumor-target CA IX over CA II (the selectivity ratios are 21.3 and 136.6, respectively). The possible binding poses of hit compounds are also explored and the selectivity is elucidated by molecular docking simulations. The hit compounds discovered in this work would provide novel scaffolds for further hit-to-lead optimization. [Copyright &y& Elsevier]

Clustering is one of the major exploratory techniques for gene expression data analysis. Only with suitable similarity metrics and when datasets are properly preprocessed, can results of high quality be obtained in cluster analysis. In this study, gene expression datasets with external evaluation criteria were preprocessed as normalization by line, normalization by column or logarithm transformation by base-2, and were subsequently clustered by hierarchical clustering, k-means clustering and self-organizing maps (SOMs) with Pearson correlation coefficient or Euclidean distance as similarity metric. Finally, the quality of clusters was evaluated by adjusted Rand index. The results illustrate that k-means clustering and SOMs have distinct advantages over hierarchical clustering in gene clustering, and SOMs are a bit better than k-means when randomly initialized. It also shows that hierarchical clustering prefers Pearson correlation coefficient as similarity metric and dataset normalized by line. Meanwhile, k-means clustering and SOMs can produce better clusters with Euclidean distance and logarithm transformed datasets. These results will afford valuable reference to the implementation of gene expression cluster analysis. [ABSTRACT FROM AUTHOR]

• This article first discovered that CAR can inhibit the growth of osteosarcoma. • In this article, while studying the effect of CAR on osteosarcoma, it also studies its toxic and side effects on normal cells. • This article also studies the role of CAR in vitro and in vivo. • This study confirmed the mechanism of CAR inhibiting osteosarcoma through P 38 and JNK signaling pathway inhibitors. Osteosarcoma (OS) is the most common type of bone malignant tumors. Clinical commonly used therapeutic drugs of OS treatment are prone to toxic and side effects, so it is very urgent to develop new drugs with low toxicity and low side effects. As a Chinese herbal medicine, Cardamonin (CAR) (C 16 H 14 O 4) has inhibitory effects in various tumors. In the present study, we investigated the effects of CAR on OS cells in vitro and in vivo. We found that CAR inhibited cell proliferation, reduced migration, decreased invasion, and induced G2 / M arrest of OS cells. Notably, we demonstrated that CAR had no obvious effect on proliferation and apoptosis of normal cells. Besides, CAR repressed tumor growth of OS cells in xenograft mouse model. Mechanically, we found that CAR increased the phosphorylation level of P38 and JNK. In summary, our research validates that CAR may inhibit the proliferation, migration, and invasion of OS and promote apoptosis possibly by activating P38 and JNK Mitogen-activated protein kinase (MAPK) signaling pathway. [ABSTRACT FROM AUTHOR]

Ulcerative colitis (UC) is regarded as a recurring inflammatory disorder of the gastrointestinal tract, for which treatment approaches remain notably limited. In this study, we demonstrated that ginseng polysaccharides (GPs) could alleviate the development of dextran sulfate sodium (DSS)-induced UC as reflected by the ameliorated pathological lesions in the colon. GPs strikingly suppressed the expression levels of multiple inflammatory cytokines, as well as significantly inhibited the infiltration of inflammatory cells. Microbiota-dependent investigations by virtue of 16S rRNA gene sequencing, antibiotic treatment and fecal microbiota transplantation illustrated that GPs treatment prominently restored intestinal microbial balance predominantly through modulating the relative abundance of Lactobacillus. Additionally, GPs remarkably influenced the levels of microbial tryptophan metabolites, diminished the intestinal permeability and strengthened intestinal barrier integrity via inhibiting the 5-HT/HTR3A signaling pathway. Taken together, the promising therapeutic potential of GPs on the development of UC predominantly hinges on the capacity to suppress the expression of inflammatory cytokines as well as to influence Lactobacillus and microbial tryptophan metabolites. [Display omitted] [ABSTRACT FROM AUTHOR]

• An automatic fundamental contour extraction of dugong chirps was presented. • Five categories of dugong chirps were identified. • A specific classification criterion was proposed for the automatic and effective identification of chirp types. • Our results enrich the known repertoire of dugong chirps, and may be useful in future passive acoustic monitoring studies. A steady decrease in the Dugong (Dugong dugon) population has been notices worldwide. Considering the social function and utilization rate, dugong chirp classification has become an important bioacoustics research topic, which may help marine biologists monitor the change of their population, study their behavioral context in different environments and optimise the protection policy. However, the objective classification of dugong chirps has not been adequately addressed in the literature. In this paper, an automatic fundamental contour extraction using the tempo-frequency variables to describe the contours of the fundamental frequency of the chirps is presented. With the automatic fundamental contour extraction, the time–frequency information of dugong chirps can be effectively represented, which gives a good classification performance. Following the principles used for the classification of dolphin whistles, three variables were chosen and performed with hierarchical cluster analysis. Based on these results and further visual examination, five categories of chirps were identified. A simple classification criterion was proposed which could be used in the automatic and effective identification of chirp types. Our findings enrich the known repertoire of dugong chirps, and may be useful in future passive acoustic monitoring studies. [ABSTRACT FROM AUTHOR]

[Display omitted] • The novel Ginkgo biloba extract (nGBE) improved long-term neurofunction after cerebral ischemia. • nGBE reduced microglia-related inflammation. • nGBE promoted white matter integrity. Ginkgo biloba L. leaf extract (GBE) has been added in many commercial herbal formulations such as EGb 761 and Shuxuening Injection to treat cardiovascular diseases and stroke worldwide. However, the comprehensive effects of GBE on cerebral ischemia remained unclear. Using a novel GBE (nGBE), which consists of all the compounds of traditional (t)GBE and one new compound, pinitol, we investigated its effect on inflammation, white matter integrity, and long-term neurological function in an experimental stroke model. Both transient middle cerebral artery occlusion (MCAO) and distal MCAO were conducted in male C57/BL6 mice. We found that nGBE significantly reduced infarct volume at 1, 3, and 14 days after ischemia. Sensorimotor and cognitive functions were superior in nGBE treated mice after MCAO. nGBE inhibited the release of IL-1β in the brain, promoted microglial ramification, and regulated the microglial M1 to M2 phenotype shift at 7 days post injury. In vitro analyses showed that nGBE treatment reduced the production of IL-1β and TNFα in primary microglia. Administration of nGBE also decreased the SMI-32/MBP ratio and enhanced myelin integrity, thus exhibiting improved white matter integrity at 28 days post stroke. These findings demonstrate that nGBE protects against cerebral ischemia by inhibiting microglia-related inflammation and promoting white matter repair, suggesting that nGBE is a promising therapeutic strategy for long-term recovery after stroke. [ABSTRACT FROM AUTHOR]

• An advanced detection neural network, the improved Faster R-CNN, is presented to realize the localization and classification of axillary lymph nodes (ALNs) simultaneously, which not only classifies lymph node metastasis, but also provides doctors with the position of ALNs in the image for reference. • As ALN usually appears on the left and right sides of CECT images, an attention model, which has the ability of extracting spatial information, was added into the network, aiming to further improve the performance of the algorithm in positioning ALN. • A novel model constructed by channel fusion and bottle neck architecture is proposed and placed before the flatten operation to better fuse and transmit spatial information with less computational cost. Background and objective: Preoperative imaging diagnosis of axillary lymph node (ALN) metastasis is particularly important for breast cancer patients. This paper focuses on developing non-invasive and automatic schemes for accurate localization and classification (metastasis prediction) of ALN via contrast-enhanced computed tomography (CECT) image and deep learning models. Methods: Based on a two-stage strategy, a novel detection neural network is proposed, where the convolutional block attention module is utilized to extract spacial information and the bottleneck feature fusion module is designed for feature fusion in different scales. Results: Owing to the two embedded modules, the proposed convolutional neural network (CNN) model outperforms Faster R-CNN, YOLOv3, and EfficientDet in the sense that the achieved mAP is 0.454, higher than 0.247, 0.335, and 0.329, respectively. In particular, considering the function of classification only, the proposed model reaches the best performance on most indices (accuracy of 0.968, positive predictive value of 0.972, negative predictive value of 0.966, specificity of 0.983), compared with the methods that have been frequently adopted to predict ALN. In addition, the proposed CNN model has the function of locating ALN, which is lacking in existing models. Conclusions: In this paper, a supervised deep learning method is proposed to detect ALN in CECT images. The positive effect of new added modules are verified, and the benefits of spatial information in ALN detection are confirmed. Further, the two subtasks called localization and classification are evaluated separately, where the proposed model achieves the best performance on most indices. The source code mentioned in this article will be released later. [ABSTRACT FROM AUTHOR]

• Successfully joined magnesium and aluminum dissimilar metals by nanosecond pulsed laser welding technology. • The laser power has a significant effect on the weld appearance, interface organization, fracture morphology and mechanical properties. • The heat transfer mechanism of the molten pool is described, and two paths of heat transfer are proposed. • At a laser power of 25 W, the maximum tensile force of the joint is the largest, which is 76.5 N. • The temperature field during the welding process was simulated. AZ31B magnesium alloy and 6061 aluminum alloy of 0.2 mm thickness were joined by nanosecond pulsed laser welding technology, and the effects of nanosecond pulsed laser power on the formation of weld seam, interface microstructure and mechanical properties were investigated, and numerical simulation of the temperature field during the welding process was carried out. The results show that when the laser power is 50 W, more defects such as cracks, pores and sags appeared in the joints due to the high heat input, and these defects resulted in a smaller effective joint area between the metals, which is very unfavorable to the strength of the joints. As the laser power decreases, at a laser power of 25 W, fewer defects are exhibited and the effective joint area becomes larger. As the laser power continues to decrease, the low heat input makes metal melting and joining very difficult. At low laser power, the Mg element intrudes backwards into the aluminum, causing the joint boundary interface to take on a reverse "V" shape. According to the results of the tensile shear experiments, the maximum tensile force of the joint was the highest at a laser power of 25 W, which reached 76.5 N. In addition, it was observed that the effective joint area, the number of oxides and their inclusions, and the degree of angular deformation had a very important effect on the mechanical properties of the joints. The results of temperature field numerical simulation experiments show that the heat is accumulated from outside to inside during the laser scanning process, and whether the temperature in the center of the molten pool reaches the melting point of the alloy can be used as an important basis for analyzing the degree of welding. [ABSTRACT FROM AUTHOR]

The resurrection plant Selaginella pulvinata possesses an extraordinary ability to survive longterm desiccation, with the capacity to recover to normal growth after four years in a desiccated state. To understand the phenomenon, we investigated morphology, cytology, physiology, and performed PacBio single-molecule, real-time (SMRT) sequencing and Illumina RNA-sequencing of S. pulvinata during dehydration and rehydration. The full-length transcriptome dataset of S. puvinata consisted of 78,914 isoforms, and 75,819 isoforms (96.07%) were functionally annotated. The mapping rate of RNA-seq was 86.83–93.46% when utilizing the full-length transcriptome dataset as a reference. A total of 17,934 differentially expressed genes (DEGs) were identified during dehydration and rehydration. During dehydration, swollen chloroplasts and mitochondria, as well as vacuolation occupied space in desiccated cells, which cooperated with dense cytoplasm to inhibit the collapse and folding of desiccated cells. Accumulation and up-regulated gene expressions of osmotic agent and protective proteins contributed to the formation of vacuolation and dense cytoplasm. To reduce ROS damage during dehydration, two strategies were employed in S. pulvinata , i.e., reducing ROS production and scavenging ROS. Reducing exposure area, inactive PSII and down-regulated gene expression in photosynthesis decreased ROS production caused by excessive light absorption. Increased activities and up-regulated gene expressions in antioxidant enzyme system promoted ROS scavenging. ABA signaling pathway was hypothesized to play an important regulatory role in the desiccation tolerance of S. pulvinata due to significant ABA accumulation and up-regulated expressions of related genes during dehydration. Moreover, the comparative transcriptome analysis revealed that the pathways involved in dehydration and rehydration of the resurrection species S. pulvinata , S. lepidophylla and S. sellowii were consistent, indicating the similar desiccation tolerance mechanisms existing in the different resurrection species of Selaginella. Our study preliminarily revealed the desiccation tolerance mechanisms of S. pulvinata , which holds significant potential for inspiring biotechnological strategies aimed at enhancing drought tolerance in crops. • Changes of morphology, physiology, cytology and transcriptome level were observed in S. pulvinata during dehydration and rehydration. • Desiccation tolerance of S. pulvinata was an intricate process orchestrated by many genes and metabolic pathways. • The different resurrection species of Selaginella possessed the similar desiccation tolerance mechanism. [ABSTRACT FROM AUTHOR]

The aim of this study is to develop and test radiomics models based on magnetic resonance imaging (MRI) to preoperatively and respectively predict the T stage, perineural invasion, and microvascular invasion of extrahepatic cholangiocarcinoma (eCCA) through a non-invasive approach. This research included 101 eCCA patients (29–83 years; 45 females and 56 males) between August 2011 and December 2019. Radiomics features were retrospectively extracted from T1-weighted imaging, T2-weighted imaging, diffusion-weighted imaging, and apparent diffusion coefficient map using MaZda software. The region of interest was manually delineated in the largest section on four MRI images as ground truth while keeping 1–2 mm margin to tumor border, respectively. Pretreatment, dimension reduction method, and classifiers were used to establish radiomics signatures for assessing three pathological characteristics of eCCA. Finally, independent training and testing datasets were used to assess radiomics signature performance based on receiver operating characteristic curve analysis, accuracy, precision, sensitivity, and specificity. This study extracted 1208 radiomics features from four MRI images of each patient. The best performing radiomics signatures for assessing the T stage, perineural invasion, and microvascular invasion were respectively produced by L1_normalization + linear discriminant analysis (LDA) + logistic regression, Box_Cox transformer + LDA + K-nearest neighbor, and L2_normalization + LDA + AdaBoost. The area under the curve values of the radiomics signatures for predicting the training and testing cohorts in each subgroup were respectively 1 and 0.962 (T stage), 1 and 1 (both perineural invasion and microvascular invasion). These proposed radiomic models based on MR images had powerful performance and high potential in predicting T stage, perineural, and microvascular invasion of eCCA. Prognostic study. [Display omitted] • MRI radiomics models were built to predict T stage, perineural, and microvascular invasion. • MRI-based radiomics model achieved AUC 1 and 0.962 (train and test) for predicting T stage. • The AUCs were 1 and 1 (train, test) in perineural and microvascular invasion models, respectively. [ABSTRACT FROM AUTHOR]

• The magnesium alloy and 304 stainless steel were successfully joined via nanosecond pulsed laser welding. • Highest tensile shear force of 298.7 N was obtained at the speed of 30 mm/s. • Three fracture modes produced at various welding speeds were clarified. • The welding temperature field of magnesium/steel joint was simulated. Nanosecond pulse laser welding was performed on AZ31B magnesium alloy and 304 stainless steel to investigate the impact of welding speed on the joining process. The temperature field of the magnesium/steel laser welding process was simulated using COMSOL software. The findings revealed that a welding speed of 10 mm/s resulted in significant spattering and larger porosity defects in the joint due to excessive heat input. However, when the welding speed was increased to 30 mm/s, these defects disappeared, and the porosity decreased to a minimum, leading to an increased bonding area at the interface. As the speed increased, the heat input decreased, making it more challenging for the porosity to escape from the molten pool and resulting in the formation of larger pores. The shear force test results indicated that the highest shear force was 298.7 N at a welding speed of 30 mm/s. The reduction in porosity and greater penetration depth of the magnesium alloy contributed to the desired mechanical performance. Additionally, the fracture modes were classified as button pullout failure (BPF), base material tearing failure (BTF), and interface failure (IF). The outermost weld seam served as the initial fracture path for both BPF and BTF modes, with BTF ultimately fracturing in the steel base material during tearing. Oxide inclusions, porosity, and the angle of distortion contributed to the fracture path of IF. [ABSTRACT FROM AUTHOR]

The albumin-bilirubin (ALBI) grade has exhibited an equal excellence with the Child-Pugh (C-P) grade in predicting overall survival (OS) of patients with hepatocellular carcinoma (HCC). However, available published results of the ALBI grade in predicting the prognosis of HCC are still limited. The goal of this study is to perform a systematic review and meta-analysis of the available data to comprehensively evaluate the ALBI grade in predicting OS of patients with HCC. Multiple databases were systematically searched for eligible studies. Studies analyzing the relationship between the ALBI grade and survival outcome were identified. Hazard ratio (HR) with 95% confidence interval (CI) was calculated to assess the risk. All statistical analyses were conducted by R version 3.3.1 (The R Foundation for Statistical Computing, Vienna, Austria). A total of 8 studies were enrolled in the meta-analysis. The pooled estimates demonstrated a significant relationship between elevated ALBI grade and inferior OS in patients with HCC (grade 1 vs 2: HR = 1.71, 95% CI: 1.52-1.92; grade 1 vs 3: HR = 3.81, 95% CI: 2.75-5.29.). In addition, the same tendency was observed when performing subgroup analysis, including treatment strategies (surgical resection, transcatheter arterial chemoembolization, radiofrequency ablation, and sorafenib) and study regions (Japan, Europe, China, and the USA). Moreover, the ALBI grade was able to classify patients with C-P grade A into 2 distinct prognostic cohorts—ALBI grade 1 and ALBI grade 2—with distinguishing survival outcomes (surgical resection: grade 1 vs 2: HR = 1.74, 95% CI: 1.55-2.06, P <. 001; sorafenib: grade 1 vs 2: HR = 1.54, 95% CI: 1.30-1.82, P <. 001). The ALBI grade has the potency of becoming an independent prognostic factor in patients with HCC. More well-designed studies should be performed to evaluate the ALBI grade as a complementary prognostic tool to current staging systems in routine clinical practice. [ABSTRACT FROM AUTHOR]

The synthesis and antileukemia evaluation of a series of dual HDAC/COX-2 inhibitors are reported. [Display omitted] • A series of dual HDAC/COX-2 inhibitors were designed and synthesized. • Compound 11 was identified as an effective agent to reduce the viability of different leukemia cell lines, particularly NALM6 cells (acute lymphoblastic leukemia cells). • Compound 11 inhibited the growth of NALM6 via cell cycle arrest and induction of apoptosis. • Compound 11 induced apoptotic cell death by activating PARP cleavage. • Compound 11 had the potential as a promising chemotherapeutic agent for acute lymphoblastic leukemia. Acute lymphoblastic leukemia (ALL) is the most common malignancy in children. Here, we exploited the synergy between histone deacetylase inhibitors (HDACi) and cyclooxygenase 2 (COX-2) inhibitors by generating and testing a series of hybrid Celecoxib-HDAC inhibitors (selenium-containing analogues of Celecoxib) on ALL cells, of which compound 11 exhibited significant inducement to kill NALM6 cells with an average IC 50 of 9.95 ± 0.44 μM compared with control Celecoxib at 28.58 ± 1.44 μM and inhibited NALM6 cells growth via the inhibition of the cell cycle in G2 phase. Furthermore, compound 11 induced apoptosis by activating PARP cleavage. Taken together, compound 11 possessed the potential to be developed further as a chemotherapeutic agent for ALL. [ABSTRACT FROM AUTHOR]

• Four types of defects in rubber timber are performed by improved YOLOX. • Improve the feature fusion module of YOLOX by adding ECA attention mechanism and ASSF multi-feature adaptive fusion. • Improve the confidence loss function and change BCE loss to Focal loss. • The regression of the target box was performed using EIOU loss. Deep learning has achieved certain results in the field of wood surface defect detection. To address the problems of low accuracy of the detection results of surface defects on boards, slow detection speed and large number of model parameters, this article take advantage of computer vision to improve the feature fusion module of YOLOX target detection algorithm, by adding efficient channel attention (ECA) mechanism, adaptive spatial feature fusion mechanism (ASFF) and improve the confidence loss and localization loss functions as Focal loss and Efficient Intersection over Union (EIoU) loss, to enhance the feature extraction ability and detection accuracy of the algorithm. Considering the depth and width of the model, the depth-separable convolution and optional multi-version algorithm are used to reduce the model parameters and computational effort to seek the optimal model. Experiments show that the improved model detects four types of defects in rubber timber with a considerable improvement and has significant advantages over other target detection algorithms. [ABSTRACT FROM AUTHOR]

Infrared spectroscopy has been widely used in quantitative analysis due to its advantages of rapidity, high efficiency and no pollution. With the development of deep learning, Convolutional Neural Network (CNN) promotes the further development of quantitative analysis methods. Spectral pretreatment is a key part to remove noise before the network training, which is able to improve the accuracy of the CNN model. However, the parameters adjustment and the signal information loss always exist in the preprocessing, which limits the application scope of CNN model. In this paper, a combined Time-Frequency Analysis and CNN (TFA-CNN) method for quantitative analysis in infrared spectroscopy is proposed. The pretreatment process of infrared spectra is integrated with CNN to avoid the loss of information, guaranteeing a high accuracy quantitative analysis without parameter adjustment. The experiment results show that the proposed TFA-CNN method has better accuracy in quantitative analysis of infrared spectroscopy, compared with traditional quantitative analysis methods. Furthermore, the TFA-CNN method has proved to be effective in a relatively small dataset. The proposed method is simple and universal, which has a broader application prospect. [ABSTRACT FROM AUTHOR]

Osteosarcoma (OS) is an aggressive malignant skeletal tumor characterized by an extremely poor prognosis and a high tendency to recur. The frequently used anti-OS chemotherapy regents are often limited by drug resistance and severe adverse events. It is urgent to develop more effective, tolerable and safe drugs for the treatment of OS. Andrographolide (AG), a diterpenoid lactone isolated from Andrographis paniculata, has been proved to possess anti-tumor activity against several human cancer types. In this current study, we evaluated the inhibitory effect of AG on human OS cells and probed the possible mechanism. We found that AG inhibited the proliferation of human OS cells and blocked cell cycle at G2/M phase. Furthermore, AG impeded the migration and invasion, while promoted the apoptosis of human OS cells. Moreover, we found that AG inhibited OS growth and lung metastasis in orthotopic transplantation model. Mechanistically, we demonstrated that AG suppressed the activity of Wnt/β-catenin, PI3K/AKT and NF-κB signaling pathways. Notably, we validated that AG synergized with the inhibitors of Wnt/β-catenin, PI3K/AKT and NF-κB to suppress the proliferation, migration and invasion of human OS cells. Collectively, our study conclusively demonstrates that AG inhibits the growth of human OS cells, thus, may be a promising candidate for the treatment of OS. • Andrographolide effectively inhibited osteosarcoma cell growth in vitro and in vivo. • Andrographolide had relative lower toxicity against normal cells. • Andrographolide suppressed Wnt/β-catenin, PI3K/AKT and NF-κB signaling pathway. [ABSTRACT FROM AUTHOR]

• The Markov, FLUS, and InVEST models were combined for their respective strengths. • The cultivated land occupation by construction land leads to the reduction of carbon storage. • 200 m is the optimal grid scale in carbon storage prediction. • The NTS, FSS, HUS, and ESS were used to predict future changes in carbon storage. • ESS increases carbon storage by 1.51 Tg between 2020 and 2035. Carbon storage services play an important role in maintaining ecosystem stability. Land use/cover change (LUCC) is the dominant factor generating changes in the ecosystem carbon storage. Demonstrating the impact of LUCC on regional carbon storage changes and predicting future carbon storage under different land use scenarios is of great significance for promoting regional carbon peak and carbon neutrality goals. Taking the main urban area of Chongqing as an example, this study analyzes carbon storage changes from 2000 to 2020 and the response to LUCC. The Markov-FLUS model is employed to predict the land use pattern of the main urban area in 2035 under four scenarios, and the InVEST model is used to assess carbon storage in 2035 under different scenarios. The results can be summarized as follows: 1) In the past 20 years, the area of cultivated land in the main urban areas of Chongqing decreased by 743.29 km2, and the area of construction land increased by 773.48 km2. About 18.8 % of the main urban area of Chongqing was transferred, the conversion of cultivated land to construction land being the most important type of transfer. 2) In 2000, 2005, 2010, 2015, and 2020, the carbon storage in the main urban area was 59.85, 59.29, 57.90, 56.95, and 54.07 Tg, respectively, showing an annually decreasing trend with a cumulative decrease of 5.78 Tg. The cultivated land occupation by construction land is the leading factor for the rapid decrease of carbon storage. The spatial distribution of carbon storage in the main urban area differs significantly, exhibiting a low in the middle and high in the surrounding areas. 3) In 2035, the carbon storage in the main urban area shows different degrees of decline in the Natural Trend Scenario (NTS), the Food Security Scenario (FSS) and the High Urbanization Scenario (HUS), decreasing by 3.37, 0.59, and 5.25 Tg, respectively. The only increase by 1.51 Tg is found in the Ecological Security Scenario (ESS). Therefore, under the background of the "Dual Carbon" targets and the important positioning of Chongqing as an important ecological barrier in the Yangtze River Basin, the ESS can be considered in the future development planning of the main urban area of Chongqing, which can both increase carbon sink and ensure ecological security. [ABSTRACT FROM AUTHOR]

Erysipelothrix rhusiopathiae is a Gram-positive bacillus that causes erysipelas in swine. In recent years, erysipelas infection among swine in China has been increasing. A combined resistance phenotype to pleuromutilins, lincosamides, and streptogramin A (PLS A phenotype) was found in some E. rhusiopathiae isolates. The aim of this study was to identify the resistance genes responsible for the PLS A phenotype in E. rhusiopathiae strains and to map the genetic environment of the identified resistance gene. A total of 46 E. rhusiopathiae isolates from 31 pig farms in China were studied. Minimum inhibitory concentrations (MICs) of 11 antimicrobial agents were determined by broth microdilution method. Seven were highly resistant to tiamulin (MICs 32 μg/ml) and clindamycin (MICs 64 μg/ml). Resistance genes responsible for the PLS A phenotype were screened by PCR. The lsa (E), spw , lnu (B), aadE and aphA 3 genes were detected in strains had the PLS A phenotype, whereas none was detected in susceptible strains. The genetic environment of lsa (E) gene was determined by whole-genome sequencing and overlapping PCR assays. A novel multiresistance gene cluster, orf 1- aadE - apt - spw - lsa (E)- lnu (B)- rec - orf 2- orf 1- aadE - sat 4- aphA 3, was found. Horizontal gene transfer experiments and whole-genome sequencing suggested that the lsa (E)-carrying multiresistance gene cluster was located in the chromosome. This is the first molecular characterization of PLS A resistance in E. rhusiopathiae . The lsa (E), spw and lnu (B) genes were found in E. rhusiopathiae for the first time. A novel lsa (E)-carrying multiresistance gene cluster was found. The location of lsa (E) in different gene cluster facilitates its persistence and dissemination. [ABSTRACT FROM AUTHOR]

• A method that can accomplish both detection and classification tasks of three marine mammal calls in one-step with Convolutional neural networks is proposed. • The proposed method can reach high identification precise and recall rate. • The identification process is fast and can be done in real-time. • The proposed method shows the potential to be applied in passive acoustic monitoring systems in the future. Animal vocalization is one of the most important ways to identify the existence and occurrence of marine mammals. Accurately detecting and identifying marine mammal species in real time is significant in the field of marine mammal research. In this study, we developed a novel method based on convolutional neural networks (CNNs) to precisely identify the calls of bottlenose dolphins (Tursiops), dugongs (Dugong dugong), and the Indo-Pacific humpback dolphin (Sousa chinensis). Compared with traditional detection and classification techniques, the proposed method is a one-step algorithm that combines detection and classification. It can automatically learn the features of different marine mammal calls and position the target calls with bounding boxes in a spectrogram. Furthermore, the whole process can be conducted in real time. With this method, the raw data are cut into fixed lengths and spectrograms are created. Next, the annotated sound data are sent to the CNNs to train an identification model. Experimental results showed that the proposed method achieved >91% precision and >84% recall of test data with real-time speed. In the future, this method can be applied to passive acoustic observation equipment for quick, accurate pre-detection of marine mammal calls. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, a method of utilizing the carbonized micron wood fiber (CMWF) as the filter material is presented and a corresponding numerical simulation method is applied. Furthermore, a kind of detachable diesel particulate filters (DPF) is developed, a diesel engine bench test is conducted and the influence elements upon Δp/H are researched. Theory and test show that the smaller the average micro pore diameter is, the larger the focal length of parabola is, which means that the numerical simulation method can be consistent with the test very well. Meanwhile, a lot of tests prove that the DPF filters with bigger pore diameter and longer length should take priority over the others, together with the increase of the filter length, the PM arresting efficiency will be improved and Δp/H also climbs up rapidly and a kind of modified CMWF DPF, of which the micro pore diameter reduces gradually from entry to exit end, possesses high filtration efficiency and low pressure drop and be suited to filter the exhaust gases of diesel. [Copyright &y& Elsevier]

Diabetic nephropathy (DN) is a common disease, and patients often do not have satisfactory treatments. We investigated therapeutic effects of Fuxin Granules(FX) on DN and potential molecular mechanisms. We orally administered doses of FX to db/db mice for 10 weeks and measured total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol. H&E, PAS, Masson, and Oil Red O staining were used to observe the structure of kidneys and calculate indices of kidney function. We used pharmacological analysis to investigate potential mechanisms of FX. Relative mRNA and protein levels in the TGF-β1/Smad, TGF-β1/Smad, and VEGF/VEGFR2 pathways were examined. TC, TG, and LDL-C were markedly reduced, lipid accumulation was low, fibrosis reduced, kidney atrophy improved, kidney lipid droplet number significantly reduced, and glomerular filtration function improved by FX treatment. Multi-channel therapeutic effects in DN through the TGF-β1/Smad and VEGF/VEGFR2 signaling pathways occurred, and FX substantially reduced expression of TGF-β1 in the glomeruli. FX significantly inhibited TGF-β1, Smad2/3 total protein levels, Smad2/3 phosphorylation mRNA levels of TGF-β1, Smad2, and Smad3. eNOS, VEGFA, and VEGFR2 expression was regulated, levels of VEGFA and VEGFR2 were decreased, and FX increased eNOS. FX ameliorated symptoms of DN, resulting in marked improvement in hyperglycemia and hyperlipidemia and optimized structure and function of kidneys in db/db mice. FX efficacy was associated with the TGF-β1/Smad and VEGF/VEGFR2 signaling pathways. We verified this potential mechanism and hope that this study will provide benefits for the clinical treatment of DN. [Display omitted] • Fuxin Granules attenuate symptoms of hyperglycemia and hyperlipidemia in db/db mice. • Fuxin Granules aid kidney lipid droplet deposition and renal function in db/db mice. • Fuxin Granules play a multi-channel regulatory and therapeutic role. • Fuxin Granules inhibit ECM storage in db/db mice by TGF-β1/Smad pathway activation. • Fuxin Granules protect renal function in db/db mice through the VEGF/VEGFR2 pathway. [ABSTRACT FROM AUTHOR]

Abstract: Neuroligins are postsynaptic membrane cell-adhesion molecules which bind to β-neurexins, a family of proteins that act as neuronal cell surface receptors. To explore the possibility that structural variants in the β-neurexin genes predispose to autism, the coding regions and associated splice junctions of three β-neurexin genes were scanned with detection of virtually all mutations-SSCP (DOVAM-S) in 72 Caucasian patients with autism. In addition, segments of the neurexin 1β gene were sequenced in 131 additional Caucasian and 61 Afro-American patients with autism from South Carolina and the Midwest. Two putative missense structural variants were identified in the neurexin 1β gene in four Caucasian patients with autism and not in 535 healthy Caucasian controls (4/203 vs. 0/535, P =0.0056). Initial family data suggest that incomplete penetrance may occur. In addition, no structural variant was found in the neurexin 2β gene and the neurexin 3β gene. In the context of all available data, we conclude that mutations of the neurexin 1β gene may contribute to autism susceptibility. [Copyright &y& Elsevier]

• Dual fluorescence channels high contrast imaging strategy to resolve attachment. • Stronger attachment between targeted microbubbles and cell membrane on rigid ECM. • Total six different attachment configurations were observed. • More violent bubble oscillation driven by ultrasound for cells on rigid ECM. • Smaller pore with slower resealing process was generated to cells on rigid ECM. In this study, we investigated the effects of extracellular matrix rigidity, an important physical property of microenvironments regulating cell morphology and functions, on sonoporation facilitated by targeted microbubbles, highlighting the role of microbubbles. We conducted mechanistic studies at the cellular level on physiologically relevant soft and rigid substrates. By developing a unique imaging strategy, we first resolved details of the 3D attachment configurations between targeted microbubbles and cell membrane. High-speed video microscopy then unveiled bubble dynamics driven by a single ultrasound pulse. Finally, we evaluated the cell membrane permeabilization using a small molecule model drug. Our results demonstrate that: (1) stronger targeted microbubble attachment was formed for cells cultured on the rigid substrate, while six different attachment configurations were revealed in total; (2) more violent bubble oscillation was observed for cells cultured on the rigid substrate, while one third of bubbles attached to cells on the soft substrate exhibited deformation shortly after ultrasound was turned off; (3) higher acoustic pressure was needed to permeabilize the cell membrane for cells on the soft substrate, while under the same ultrasound condition, acoustically-activated microbubbles generated larger pores as compared to cells cultured on the soft substrate. The current findings provide new insights to understand the underlying mechanisms of sonoporation in a physiologically relevant context and may be useful for the clinical translation of sonoporation. [ABSTRACT FROM AUTHOR]

• Based on image feature extraction technology to build aggregate feature data set. • A fusion feature importance analysis method is proposed. • Establish a random forest and XGBoost aggregate shape classification model. • The ability to recognize the 3D features of aggregates in 2D images are improved. Aggregate plays the role of skeleton filling in asphalt pavements. The shape of the aggregate affects the embedded structure between the aggregates, thus affecting the performance of asphalt concrete. In this study, extreme gradient boosting (XGBoost) classification is used to study the automatic shape classification of aggregates. The expression of main and microscopic features of aggregate was improved by transforming aggregate images into data, and a feature importance analysis method based on method fusion is proposed to select the feature parameters of aggregate morphology. Based on cross-validation, the XGBoost classification model was trained by optimizing the super parameter combination to complete the classification of aggregate shapes. Compared with the random forest model, the results show that the proposed method can effectively classify aggregate shapes. It is also proved that the two-dimensional images can reflect the three-dimensional features of the aggregate to some extent. This method provides a certain theoretical basis for the automatic classification of aggregate, and simultaneously it has important practical significance to promote the intelligent production of asphalt mixtures. [ABSTRACT FROM AUTHOR]