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Image anomaly detection and localization perform not only image-level anomaly classification but also locate pixel-level anomaly regions. Recently, it has received much research attention due to its wide application in various fields. This paper proposes ProtoAD, a prototype-based neural network for image anomaly detection and localization. First, the patch features of normal images are extracted by a deep network pre-trained on nature images. Then, the prototypes of the normal patch features are learned by non-parametric clustering. Finally, we construct an image anomaly localization network (ProtoAD) by appending the feature extraction network with L2 feature normalization, a 1 × 1 convolutional layer, a channel max-pooling, and a subtraction operation. We use the prototypes as the kernels of the 1 × 1 convolutional layer; therefore, our neural network does not need a training phase and can conduct anomaly detection and localization in an end-to-end manner. Extensive experiments on two challenging industrial anomaly detection datasets, MVTec AD and BTAD, demonstrate that ProtoAD achieves competitive performance compared to the state-of-the-art methods with a higher inference speed. The code and pre-trained models are publicly available at . [ABSTRACT FROM AUTHOR]

The buffer zones between urban protected areas (UPAs) and their cities play a significant role in managing and protecting UPAs. However, they are also the frontier of conflicts due to complex functionality and a large number of stakeholders. Besides ensuring the buffer zone's function of protecting the UPA, it is also vital to understand how it can fulfill the diverse needs of multiple interest groups residing in or utilizing this area. To address the significant social science research gap in UPA buffer zone management, we establish a conceptual framework and explore how the public's overall satisfaction with the buffer depends on five essential buffer zone qualities, namely environmental quality, connectivity, infrastructure, cultural, and visual quality. We focus on China's Urban Scenic and Historic Areas (USHA), a major type of UPA with high cultural, social, and esthetic values. Using the buffer of Shugang-Slender West Lake Scenic and Historic Area in Yangzhou City as the case study, we conducted intercept and online surveys (n = 499), investigating the perceptions of three user groups—residents, businesses, and tourists. The results indicate high overall satisfaction for all three groups. Environmental, visual, and cultural qualities were rated higher than connectivity and infrastructure quality. Residents generally showed the highest satisfaction and tourists the lowest. For all three groups, environmental quality, connectivity, and infrastructure quality significantly influenced overall satisfaction, while cultural and visual quality did not. This suggests that the public expects the buffer zone to serve as high-quality multi-functional open spaces that enhance the quality of life while providing recreation, service, and transportation functions. Besides direct planning and management advice to China's UPAs and other countries with similar contexts, our study offers a transferable framework for incorporating social perceptions and highlights their significance in informing the functional planning of UPA buffer zones for public welfare. [ABSTRACT FROM AUTHOR]

In this methodology, a nanomagnetic copper catalyst prepared via the immobilization of CuCl2 on the surface of Fe3O4@SiO2-APA-Amide/Imid ligand and its structure identified by several spectroscopic techniques including XRD, FT-IR, VSM, SEM, TEM, ICP-OES, TGA, EDX and elemental mapping analysis. This Fe3O4@SiO2-APA-Amide/Imid-CuCl2 nanomaterial can catalyze the preparation of 1,2,3-triazole derivatives through reactions of alkyne derivatives with NaN3 and aryl halides under ecofriendly conditions. It is noteworthy that the 1,2,3-triazole products were obtained with high yields when 2-phenylthiirane was used instead of aryl halides. In this research, one-pot three-component reactions were successfully performed in water, and the corresponding triazole products were obtained with high to excellent yields. After the end of the reaction, the Fe3O4@SiO2-APA-Amide/Imid-CuCl2 catalyst was recovered by magnetic separation and reused for 8 runs with a constant efficiency. [ABSTRACT FROM AUTHOR]

Human activity recognition (HAR) with wearable inertial sensors is a burgeoning field, propelled by advances in sensor technology. Deep learning methods for HAR have notably enhanced recognition accuracy in recent years. Nonetheless, the complexity of previous models often impedes their use in real-life scenarios, particularly in online applications. Addressing this gap, we introduce SenseMLP, a novel approach employing a multi-layer perceptron (MLP) neural network architecture. SenseMLP features three parallel MLP branches that independently process and integrate features across the time, channel, and frequency dimensions. This structure not only simplifies the model but also significantly reduces the number of required parameters compared to previous deep learning HAR frameworks. We conducted comprehensive evaluations of SenseMLP against benchmark HAR datasets, including PAMAP2, OPPORTUNITY, USC-HAD, and SKODA. Our findings demonstrate that SenseMLP not only achieves state-of-the-art performance in terms of accuracy but also boasts fewer parameters and lower floating-point operations per second. For further research and application in the field, the source code of SenseMLP is available at [ABSTRACT FROM AUTHOR]

Background: This study aimed to investigate the relationship between signal regulatory protein gamma (SIRPG) and tumor immune microenvironment phenotypes or T cell mediated-adaptive antitumor immunity, and its predictive value for response to PD-1 blockade in cancers. Methods: Pan-cancer analysis of SIRPG expression and immune deconvolution was performed using transcriptomic data across 33 tumor types. Transcriptomic and clinical data from 157 patients with non-small-cell lung cancer (NSCLC) and melanoma received PD-1 blockade were analyzed. Expression characteristics of SIRPG were investigated using single-cell RNA sequencing (scRNA-seq) data of 103,599 cells. The effect of SIRPG expression was evaluated via SIRPG knockdown or overexpression in Jurkat T cells. Results: The results showed that most cancers with high SIRPG expression had significantly higher abundance of T cells, B cells, NK cells, M1 macrophages and cytotoxic lymphocytes and increased expression level of immunomodulatory factors regulating immune cell recruitment, antigen presentation, T cell activation and cytotoxicity, but markedly lower abundance of neutrophils, M2 macrophages, and myeloid-derived suppressor cells. High SIRPG expression was associated with favorable response to PD-1 blockade in both NSCLC and melanoma. scRNA-seq data suggested SIRPG was mainly expressed in CD8+ exhausted T and CD4+ regulatory T cells, and positively associated with immune checkpoint expression including PDCD1 and CTLA4. In vitro test showed SIRPG expression in T cells could facilitate expression of PDCD1 and CTLA4. Conclusion: High SIRPG expression is associated with an inflamed immune phenotype in cancers and favorable response to PD-1 blockade, suggesting it would be a promising predictive biomarker for PD-1 blockade and novel immunotherapeutic target. [ABSTRACT FROM AUTHOR]

Copyright of Rare Metals is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Image inpainting is a fundamental task in the field of computer vision. However, there are three major challenges associated with this technique: (1) maintaining neighborhood texture consistency; (2) ensuring the rationality of visual structure; and (3) the limitation of existing inpainting models based on deep neural networks due to a large number of parameters. In order to tackle these challenges, we propose a novel generative adversarial network based on tensor ring decomposition to inpaint images with varying degrees of damage. First, we design a dual-path block that captures features at different scales without significant memory consumption. Every pair of dual-path blocks is incorporated into an enhanced residual module to integrate local and global features. Additionally, we propose the tensor ring layer to compress the convolution, reducing the number of model parameters and computational complexity. We then use a more accurate U-Net based discriminator to optimize the network by minimizing reconstruction loss, adversarial loss, perceptual loss and style loss. Extensive experiments demonstrate that, when compared with other state-of-the-art algorithms, our model shows superior performance in compression. The repaired images also exhibit reasonable texture structure and contextual semantic information. [ABSTRACT FROM AUTHOR]

We address the problem of resource allocation with multi-attribute demand considering heterogeneous servers in mobile edge computing (MEC). A mobile device (MD) may be within the coverage area of multiple access points and can get resources from any server that can establish direct communication. However, the configurations of heterogeneous servers are different, so the demand for each MEC server is different. We tackle this problem and consider multi-attribute demand, where each MD is assigned exactly one of multiple demands. We formulate the allocation problem in an auction-based setting to provide server scalability. We propose a family of greedy mechanisms to solve the resource allocation problem. However, each MD is self-interested and may try to manipulate the system to maximize its utility. We show our mechanisms are truthful, and they drive the system into an equilibrium where no MD can declare an untrue value to obtain higher utility. We also analyze the approximation ratios of our greedy mechanisms. Experimental results demonstrate that the greedy mechanisms obtain the near-optimal allocation in a short period while benefiting MDs and edge cloud providers. [ABSTRACT FROM AUTHOR]

Copyright of Rare Metals is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this study, we analyzed the morphological structure of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in human cells. We identified the two types of viral particles present within the vacuoles of infected cells. Using transmission electron microscopy, we observed that SARS-CoV-2 particles exhibited both low- and high-electron-density structures, which was further confirmed through three-dimensional reconstruction using electron tomography. The budding of these particles was exclusively observed within these vacuoles. Intriguingly, viral particles with low-electron-density structures were confined to vacuoles, whereas those with high-electron-density structures were found in vacuoles and on the cell membrane surface of infected cells. Notably, high-electron-density particles found within vacuoles exhibited the same morphology as those outside the infected cells. This observation suggests that the two types of viral particles identified in this study had different maturation status. Our findings provide valuable insights into the molecular details of SARS-CoV-2 particles, contributing to our understanding of the virus. [ABSTRACT FROM AUTHOR]

Main conclusion: The identification of a functional cinnamoyl-CoA reductase enzyme from Cinnamomum cassia involved in trans-cinnamaldehyde biosynthesis offers the potential for enhancing trans-cinnamaldehyde production through genetic engineering. A significant accumulation of trans-cinnamaldehyde has been found in the bark tissues of C. cassia, used in traditional Chinese medicine. trans-Cinnamaldehyde exhibits various pharmacological properties such as anti-inflammatory, analgesic, and protection of the stomach and the digestive tract. However, further elucidation and characterization of the biosynthetic pathway for trans-cinnamaldehyde is required. In this study, we conducted an integrated analysis of trans-cinnamaldehyde accumulation profiles and transcriptomic data from five different C. cassia tissues to identify the genes involved in its biosynthesis. The transcriptome data we obtained included nearly all genes associated with the trans-cinnamaldehyde pathway, with the majority demonstrating high abundance in branch barks and trunk barks. We successfully cloned four C. cassia cinnamoyl-CoA reductases (CcCCRs), a key gene in trans-cinnamaldehyde biosynthesis. We found that the recombinant CcCCR1 protein was the only one that more efficiently converted cinnamoyl-CoA into trans-cinnamaldehyde. CcCCR1 exhibited approximately 14.7-fold higher catalytic efficiency (kcat/Km) compared to the Arabidopsis thaliana cinnamoyl-CoA reductase 1 (AtCCR1); therefore, it can be utilized for engineering higher trans-cinnamaldehyde production as previously reported. Molecular docking studies and mutagenesis experiments also validated the superior catalytic activity of CcCCR1 compared to AtCCR1. These findings provide valuable insights for the functional characterization of enzyme-coding genes and hold potential for future engineering of trans-cinnamaldehyde biosynthetic pathways. [ABSTRACT FROM AUTHOR]

Copyright of Rare Metals is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Citrus reticulata cv. Chachiensis (CRC) is an important medicinal plant, its dried mature peels named "Guangchenpi", has been used as a traditional Chinese medicine to treat cough, indigestion, and lung diseases for several hundred years. However, the biosynthesis of the crucial natural products polymethoxylated flavonoids (PMFs) in CRC remains unclear. Here, we report a chromosome-scale genome assembly of CRC with the size of 314.96 Mb and a contig N50 of 16.22 Mb. Using multi-omics resources, we discover a putative caffeic acid O-methyltransferase (CcOMT1) that can transfer a methyl group to the 3-hydroxyl of natsudaidain to form 3,5,6,7,8,3',4'-heptamethoxyflavone (HPMF). Based on transient overexpression and virus-induced gene silencing experiments, we propose that CcOMT1 is a candidate enzyme in HPMF biosynthesis. In addition, a potential gene regulatory network associated with PMF biosynthesis is identified. This study provides insights into PMF biosynthesis and may assist future research on mining genes for the biosynthesis of plant-based medicines. Citrus reticulata cv. Chachiensis (CRC) is used in traditional Chinese medicine to treat various ailments. Here Wen et al. provide genomic, transcriptomic and metabolomic resources for CRC and propose a possible biosynthetic pathway for bioactive components. [ABSTRACT FROM AUTHOR]

Van der Hoeve's syndrome, also known as osteogenesis imperfecta (OI), is a genetic connective tissue disorder characterized by fragile, fracture-prone bone and hearing loss. The disease is caused by a gene mutation in one of the two type I collagen genes COL1A1 or COL1A2. In this study, we identified a novel frameshift mutation of the COL1A1 gene (c.1607delG) in a family with OI using whole-exome sequencing, bioinformatics analysis and Sanger sequencing. This mutation may lead to the deletion of a portion of exon 23 and the generation of a premature stop codon in the COL1A1 gene. To further investigate the impact of this mutation, we established two induced pluripotent stem cell (iPSC) lines from peripheral blood mononuclear cells of OI patients carrying a novel mutation in the COL1A1 gene. Osteoblasts (OB) derived from OI-iPSCs exhibited reduced production of type I collagen and diminished ability to differentiate into osteoblasts. Using a CRISPR-based homology-directed repair strategy, we corrected the OI disease-causing COL1A1 novel mutations in iPSCs generated from an affected individual. Our results demonstrated that the diminished expression of type I collagen and osteogenic potential were enhanced in OB induced from corrected OI-iPSCs compared to those from OI-iPSCs. Overall, our results provide new insights into the genetic basis of Van der Hoeve's syndrome and highlight the potential of iPSC technology for disease modeling and therapeutic development. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to assess the margin for the planning target volume (PTV) using the Van Herk formula. We then validated the proposed margin by real-time magnetic resonance imaging (MRI). Methods: An analysis of cone-beam computed tomography (CBCT) data from early glottic cancer patients was performed to evaluate organ motion. Deformed clinical target volumes (CTV) after rigid registration were acquired using the Velocity program (Varian Medical Systems, Palo Alto, CA, USA). Systematic (Σ) and random errors (σ) were evaluated. The margin for the PTV was defined as 2.5 Σ + 0.7 σ according to the Van Herk formula. To validate this margin, we accrued healthy volunteers. Sagittal real-time cine MRI was conducted using the ViewRay system (ViewRay Inc., Oakwood Village, OH, USA). Within the obtained sagittal images, the vocal cord was delineated. The movement of the vocal cord was summed up and considered as the internal target volume (ITV). We then assessed the degree of overlap between the ITV and the PTV (vocal cord plus margins) by calculating the volume overlap ratio, represented as (ITV∩PTV)/ITV. Results: CBCTs of 17 early glottic patients were analyzed. Σ and σ were 0.55 and 0.57 for left–right (LR), 0.70 and 0.60 for anterior–posterior (AP), and 1.84 and 1.04 for superior–inferior (SI), respectively. The calculated margin was 1.8 mm (LR), 2.2 mm (AP), and 5.3 mm (SI). Four healthy volunteers participated for validation. A margin of 3 mm (AP) and 5 mm (SI) was applied to the vocal cord as the PTV. The average volume overlap ratio between ITV and PTV was 0.92 (range 0.85–0.99) without swallowing and 0.77 (range 0.70–0.88) with swallowing. Conclusion: By evaluating organ motion by using CBCT, the margin was 1.8 (LR), 2.2 (AP), and 5.3 mm (SI). The margin acquired using CBCT fitted well in real-time cine MRI. Given that swallowing during radiotherapy can result in a substantial displacement, it is crucial to consider strategies aimed at minimizing swallowing and related motion. [ABSTRACT FROM AUTHOR]

Inflammation and immunity play important roles in the pathogenesis of ischemic stroke. This study aimed to explore key regulatory genes in acute ischemic stroke (AIS) and their underlying mechanisms to provide new research targets for the diagnosis and treatment of ischemic stroke. We searched for differentially expressed mRNAs and miRNAs in patients with AIS and healthy populations in GEO databases, constructed a miRNA–mRNA network, and screened key miRNAs using least absolute shrinkage and selection operator regression and the support vector machine-recursive feature elimination model. Correlations between key miRNAs and infiltrating immune cells and inflammatory factors were analyzed using CIBERSORT and immunoassays and verified using clinical experiments. Bioinformatics analysis identified hsa-miR-877-5p as a key regulatory miRNA in AIS that can modulate immune and inflammatory responses. In clinical studies, it was verified by quantitative PCR analysis that the expression of hsa-miR-877-5p in the blood of AIS patients was higher than that of the healthy group. Then, enzyme-linked immunosorbent assay revealed that the expression of IL-23 and TNF-α related to inflammation in AIS patients was higher than that of the healthy. Quantitative PCR further found that the relative mRNA expression of IL-23, CXCR3, and TNF-α in AIS group was higher than that of the healthy group. This study may provide a basis for a more comprehensive understanding of the potential mechanism of the occurrence and development of AIS, and hsa-miR-877-5p and its downstream effectors IL-23, CXCR3, and TNF-α may be potential intervention targets in AIS. [ABSTRACT FROM AUTHOR]

Dragon's Blood (DB) serves as a precious Chinese medicine facilitating blood circulation and stasis dispersion. Daemonorops draco (D. draco; Qi-Lin-Jie) and Dracaena cochinchinensis (D. cochinchinenesis; Long-Xue-Jie) are two reputable plant sources for preparing DB. This work was designed to comprehensively characterize and compare the metabolome differences between D. draco and D. cochinchinenesis, by integrating liquid chromatography/mass spectrometry and untargeted metabolomics analysis. Offline two-dimensional liquid chromatography/ion mobility-quadrupole time-of-flight mass spectrometry (2D-LC/IM-QTOF-MS), by utilizing a powerful hybrid scan approach, was elaborated for multicomponent characterization. Configuration of an XBridge Amide column and an HSS T3 column in offline mode exhibited high orthogonality (A0 0.80) in separating the complex components in DB. Particularly, the hybrid high-definition MSE-high definition data-dependent acquisition (HDMSE-HDDDA) in both positive and negative ion modes was applied for data acquisition. Streamlined intelligent data processing facilitated by the UNIFI™ (Waters) bioinformatics platform and searching against an in-house chemical library (recording 223 known compounds) enabled efficient structural elucidation. We could characterize 285 components, including 143 from D. draco and 174 from D. cochinchinensis. Holistic comparison of the metabolomes among 21 batches of DB samples by the untargeted metabolomics workflows unveiled 43 significantly differential components. Separately, four and three components were considered as the marker compounds for identifying D. draco and D. cochinchinenesis, respectively. Conclusively, the chemical composition and metabolomic differences of two DB resources were investigated by a dimension-enhanced analytical approach, with the results being beneficial to quality control and the differentiated clinical application of DB. [ABSTRACT FROM AUTHOR]

Silicone rubber (SR) composites are most widely used as thermal interface materials (TIMs) for electronics heat dissipation. Thermal impedance as the main bottleneck limiting the performance of TIMs is usually neglected. Herein, the thermal impedance of SR composites loaded with different levels of hexagonal boron nitride (h-BN) as TIMs was elaborated for the first time by the ASTM D 5470 standard test and finite element analysis. It was found that elastic modulus and surface roughness of SR composites increased with the increase of h-BN content, indicating that the conformity was reduced. When the assembly pressure was 0.69 MPa, there existed an optimal h-BN content at which the contact resistance was minimum (0.39 K·cm2·W−1). Although the decreased bond line thickness (BLT) by increasing the assembly pressure was beneficial to reduce the thermal impedance, the proper assembly pressure should be selected to prevent the warpage of the contact surfaces and the increase in contact resistance, according to the compression properties of the SR composites. This study provides valuable insights into fabrication of high-performance TIMs for modern electronic device applications. [ABSTRACT FROM AUTHOR]

In the past decades, ontology-based query expansion has been studied to improve health and biomedical information retrieval by many researchers, but the results of previous works are inconsistent. Query expansion with domain ontologies could introduce noise that degrades the retrieval performance, therefore noise control is the key to its success. In this paper, we explore three noise control strategies for UMLS-based query expansion. The first strategy is the adoption of a word-phrase hybrid retrieval model, and the other two strategies explored are expansion term weighting and term filtering. All the three strategies are implemented based on the Indri search engine and evaluated on two standard datasets, OHSUMED and TREC Genomic Track 2006. The experimental results indicate that the word-phrase hybrid retrieval model is superior to the word-based model and the pure phrase-based model, and beneficial to not only baseline retrieval but also query expansion. Expansion term weighting is an effective strategy to suppress term noise and improve retrieval performance. And expansion term filtering can also give some positive effects in most cases but is not as effective as the other two strategies. By combining the three strategies together, the best retrieval performances can be achieved on both datasets. [ABSTRACT FROM AUTHOR]

Preservation of executive function, like inhibition, closely links to the quality of life in senior adults. Although neuroimaging literature has shown enhanced inhibitory function followed by aerobic exercise, current evidence implies inconsistent neuroplasticity patterns along different time durations of exercise. Hence, we conducted a 12-week exercise intervention on 12 young and 14 senior volunteers and repeatedly measured the inhibitory functionality of distinct aspects (facilitation and interference effects) using the numerical Stroop task and functional Magnetic Resonance Imaging. Results showcased improved accuracy and reduced reaction times (RT) after 12-week exercise, attributed to frontoparietal and default mode network effects. In young adults, the first phase (0 to six weeks) exercise increased the activation of the right superior medial frontal gyrus, associated with reduced RT in interference, but in the second intervention phase (six to twelve weeks), the decreased activation of the left superior medial frontal gyrus positively correlated with reduced RT in facilitation. In senior adults, the first six-week intervention led to reduced activations of the inferior frontal gyrus, inferior parietal gyrus, and default mode network regions, associated with the reduced RT in interference. Still, in the second intervention phase, only the visual area exhibited increased activity, associated with reduced RT in interference. Except for the distinctive brain plasticity between the two phases of exercise intervention, the between-group comparison also presented that the old group gained more cognitive benefits within the first six weeks of exercise intervention; however, the cognitive improvements in the young group occurred after six weeks of intervention. Limited by the sample size, these preliminary findings corroborated the benefits of aerobic exercise on the inhibitory functions, implying an age × exercise interaction on the brain plasticity for both facilitation and interference. [ABSTRACT FROM AUTHOR]

Membrane technology has become one of the most promising separation technologies for its energy saving, high separation efficiency, environmental friendliness, and economic feasibility. Covalent organic frameworks (COFs) with intrinsically high porosity, controllable pore size, uniform pore size distribution and long-range ordered channel structure, have emerged as next-generation materials to fabricate advanced separation membranes. This feature article summarizes some latest studies in the development of pure COF membranes in our lab, including their fabrication and applications in chemical separations. Finally, current challenges facing high-performance COF separation membranes are discussed. [ABSTRACT FROM AUTHOR]

In the actual monitoring of deep hole displacement, the identification of slip surfaces is primarily based on abrupt changes observed in the inclinometric curve. In conventional identification methods, inclinometric curves exhibiting indications of sliding can be categorized into three types: B-type, D-type, and r-type. The position of the slip surface is typically determined by identifying the depth corresponding to the point of maximum displacement mutation. However, this method is sensitive to the interval of measurement points and the observation scale of the coordinate axes and suffers from unclear sliding surfaces and uncertain values. Based on the variation characteristics of these diagonal curves, we classified the landslide into three components: the sliding body, the sliding interval, and the immobile body. Moreover, three different generalization models were established to analyze the relationships between the curve form and the slip surface location based on different physical indicators such as displacement rate, relative displacement, and acceleration. The results show that the displacement rate curves of an r-type slope exhibit a clustering feature in the sliding interval, and by solving for the depth of discrete points within the step phase, it is possible to determine the location of the slip surface. On the other hand, D-type slopes have inflection points in the relative displacement curve located at the slip surface. The acceleration curves of B-type slopes exhibit clustering characteristics during the sliding interval, while the scattered acceleration data demonstrate wandering characteristics. Consequently, the slip surface location can be revealed by solving the depth corresponding to the maximum acceleration with cubic spline interpolation. The approach proposed in this paper was applied to the monitoring data of a landslide in Yunnan Province, China. The results indicate that our approach can accurately identify the slip surface location and enable computability of its position, thereby enhancing applicability and reliability of the deep-hole displacement monitoring data. [ABSTRACT FROM AUTHOR]

Time series classification (TSC) is one of the most challenging research topics in data mining, and can finds its wide applications in biomedical engineering and clinical prediction. In recent years, deep learning (DL) has shown impressive performance in TSC research due to its end-to-end capabilities. In contrast to univariate TSC (UTSC), multivariable TSC (MTSC) is more prevalent and its effectiveness depends on long and short-term dependencies to a certain degree. However, mainstream DL models mainly construct various complex frameworks to extract features, and with the over-fitting problem. This paper proposes a comprehensive DL structure, namely the Multivariable Multi-Scale Attention Gated Cycle Unit Fully Convolutional Network (MMAGRU-FCN), which can effectively address the long and short-term dependence in MTSC by integrating memory and attention mechanisms at multiple scales. The proposed model can achieve adaptive characteristic calibration and capture significant features simultaneously. Extensive experiments demonstrate the superior performance of our model over state-of-the-art DL networks in terms of faster convergence, better stability, and in the case that parameters are close to the minimum threshold of comparison. Moreover, the proposed model consistently achieves the highest classification accuracy across different time series lengths. Finally, we verify the performance of the proposed model for various classification scenarios. [ABSTRACT FROM AUTHOR]

Environmental policy stringency (EPS) is widely adopted as the most practical option to tackle the menace of environmental degradation. Therefore, this study investigates the dynamic linkage between EPS and carbon dioxide (CO2) emissions in the most polluted countries of the Asia Pacific Region for the period 1991–2021. For empirical analysis, we have relied on nonlinear panel ARDL methods. In the NARDL analysis, a positive shock in EPS has a significant negative effect on CO2, while a negative shock in EPS has a significant positive impact on CO2 in both the short and long run. Moreover, the growth of human capital and the rise in renewable energy consumption are crucial in improving environmental quality; however, the rise in the region's economic prosperity makes the region more polluted in the long run. In light of these findings, our study emphasizes the critical role of policymakers in the Asia Pacific region in implementing and maintaining strict environmental policies to effectively control carbon emissions. These policies can complement other mitigation strategies, such as raising environmental awareness and promoting renewable energy consumption. [ABSTRACT FROM AUTHOR]

With the rapid development of the electronics, communication, and energy industries, there is an increasing demand for flexible materials with high thermal conductivity and electrical insulation properties. Silicone rubber (SR) is widely used in various fields due to its excellent mechanical properties. However, its intrinsic low thermal conductivity requires the addition of thermally conductive fillers to enhance its thermal conductivity. Insulating thermally conductive composites are prepared by adding thermally conductive fillers such as boron nitride (BN) and graphite into a silicone rubber matrix. When BN is added as a single filler up to 20 wt%, the thermal conductivity of BN/SR reaches 0.526 W m−1 K−1, which is a 126% improvement compared to the SR matrix. When the total filler content is 20 wt%, and the ratio of BN to graphite is 1:1, the thermal conductivity of BN/graphite/SR composite is 0.685 W m−1 K−1. This represents a 194% and 30% increase in thermal conductivity compared to the SR matrix and BN/SR composite with the same filler content, respectively. On the cured silicone rubber substrate, the incremental cured BN/SR acts as an insulation coating. This allows for a significant reduction in the electrical conductivity of the composite without the use of adhesives, while preserving the thermal conductivity. Moreover, the interface formed through incremental curing retains high tensile and compressive strength. [ABSTRACT FROM AUTHOR]

Hair loss disorders such as androgenetic alopecia have caused serious disturbances to normal human life. Animal models play an important role in exploring pathogenesis of disease and evaluating new therapies. NIH hairless mice are a spontaneous hairless mouse discovered and bred in our laboratory. In this study, we resequenced the genomes of NIH normal mice and NIH hairless mice and obtained 3,575,560 high-quality, plausible SNP loci and 995,475 InDels. The Euclidean distance algorithm was used to assess the association of SNP loci with the hairless phenotype, at a threshold of 0.62. Two regions of chromosome 18 having the highest association with the phenotype contained 345 genes with a total length of 13.98 Mb. The same algorithm was used to assess the association of InDels with the hairless phenotype at a threshold of 0.54 and revealed a region of 25.45 Mb in length, containing 518 genes. The mutation candidate gene Lama3 (NM_010680.2: c.652C>T; NP_034810.1: p. Arg217Cys) was selected based on the results of functional gene analysis and mutation prediction screening. Lama3 (R217C) mutant mice were further constructed using CRISPR/Cas9 technology, and the relationship between Lama3 point mutations and the hairless phenotype were clarified by phenotypic observation. The results showed that male Lama3 point mutation mice started to lose hair on the 80th day after birth, and the hair loss area gradually expanded over time. H&E staining of skin sections showed that the point mutation mice had increased sebaceous glands in the dermis and missing hair follicle structure (i.e., typical symptoms of androgenetic alopecia). This study is a good extension of the current body of knowledge about the function of Lama3, and the constructed Lama3 (R217C) mutant mice may be a good animal model for studying androgenetic alopecia. [ABSTRACT FROM AUTHOR]

Intrahepatic cholangiocarcinoma (ICC) accounts for 20% of liver malignancies with a 5-year survival rate of 35% at best with limited prognostic predictors. Lung Immune Prognostic Index (LIPI) is a novel prognostic factor in pulmonary cancers. In this study, we developed a modified prognostic model from LIPI called intrahepatic immune prognostic index (IIPI) for ICC. A retrospectively study was conducted at Liver Transplant Center of West China Hospital between January 2015 and January 2023. Hematological factors and clinical features of ICC patients were collected and analyzed. The area under curve (AUC) and optimal cuff-off of each single hematological factor was calculated. In this study, derived neurtrophil to lymphocyte ratio (dNLR), arbohydrate antigen199 (CA199) and carcinoembryonic antigen (CEA) have higher AUC values. LIPI was composed of dNLR and was further modified by combing CA199 and CEA, forming the IIPI. The IIPI consists of four grades which are None, Light, Moderate and Severe. Compared to other prognostic factors, IIPI exhibited better ability to predict overall survival. The multivariate analysis indicated that cirrhosis, differentiation, hilar invasion and IIPI were independent prognostic factors for ICC patients. An IIPI-based nomogram was also established and could predict the overall survival. In addition, the subgroup analyses based on clinical prognostic factors showed that the IIPI exhibited excellent prognostic influence. IIPI model is suitable for predicting the prognosis of postoperative ICC patients. Further research is needed to explore the relationship between postoperative recurrence and metastasis of ICC patients and IIPI. [ABSTRACT FROM AUTHOR]

As a result of chloride ion erosion, corrosion of steel bars in coastal or deicing salt environments deteriorates reinforced concrete’s (RC) structural performance. At present, there were few studies involving both chloride ion erosion and shear walls with flange, which made it difficult to evaluate the performance of corroded shear wall structures in coastal environments. Consequently, seven high-rise RC shear walls with flange were tested by electrochemical chloride erosion (ECE) and low cyclic loading in this paper, and the influences of key parameters such as corrosion degree, axial compression ratio and reinforcement ratio of longitudinal reinforcement on the hysteretic characteristics of corroded shear walls with flange were investigated. This article assesses the seismic behavior of specimens by analyzing corrosion morphology and damage processes of concrete and rebars. In addition, scrutiny is placed on failure modes, bearing capability, deformability, and energy-dissipating capacity. Subsequently, according to the failure characteristics and test data, a numerical modeling analysis method based on fiber elements was proposed and validated to obtain the seismic response prediction of corroded shear walls with flange. Finally, based on the built numerical model, the effects of other parameters on the seismic property of corroded shear walls with flange were discussed. [ABSTRACT FROM AUTHOR]

Objectives : To investigate the brain functional alterations in dysthyroid optic neuropathy (DON) by evaluating spontaneous neural activity, using functional magnetic resonance imaging (fMRI) with regional homogeneity (ReHo), and its relationship with ophthalmologic performance. Methods: Forty-seven patients with thyroid-associated ophthalmopathy (TAO; 20 with DON, 27 with non-DON) and 33 age-, sex-, and education-matched healthy controls (HCs) underwent fMRI. ReHo values were compared using one-way analysis of variance (ANOVA) with post hoc pairwise comparisons (voxel-level p < 0.01, Gaussian random field correction, cluster-level p < 0.05). Correlations between ReHo values and ophthalmological metrics were assessed for DONs, with Bonferroni correction for multiple comparisons (p < 0.004). ROC curves were applied to evaluate the diagnostic performance of ReHo metrics. Results: ReHo values were significantly lower in the left insula and right superior temporal gyrus, and higher in the left posterior cingulate cortex (LPCC), of DON than of non-DON patients. ReHo values were also significantly lower in the right middle temporal, left insula, and left precentral gyrus in DON than in HCs. Meanwhile, ReHo values were higher in LPCC in non-DON than in HCs. ReHo values correlated with ophthalmic examinations to varying degrees in DON. For distinguishing DON, the ReHo values in LPCC showed optimal individually (AUC = 0.843), the combination of the ReHo in both the left insula and LPCC performed better (AUC = 0.915). Conclusion: Spontaneous brain activity differed between TAO with and without DON, which may reflect the underlying pathological mechanism of DON. The ReHo index can be considered a diagnostic biomarker. Clinical relevance statement: Spontaneous brain activity in DON differed from that in TAO without DON, which may reflect the underlying pathological mechanism of DON. The ReHo index can be considered a diagnostic biomarker for early detection of DON. Key Points: • Dysthyroid optic neuropathy (DON) affects brain activity, which contributes in the understanding of its visual dysfunction. • Regional homogeneity values differ between thyroid-associated ophthalmopathy with and without DON in various brain regions. • Regional homogeneity values can be used as a biomarker in the differential diagnosis of DON. [ABSTRACT FROM AUTHOR]

Highlights: The process of machine learning is introduced in detail. Recent developments in machine learning for low-dimensional electrocatalysts are briefly reviewed. Future directions and perspectives for machine learning in hydrogen evolution reaction are critically discussed. Efficient electrocatalysts are crucial for hydrogen generation from electrolyzing water. Nevertheless, the conventional "trial and error" method for producing advanced electrocatalysts is not only cost-ineffective but also time-consuming and labor-intensive. Fortunately, the advancement of machine learning brings new opportunities for electrocatalysts discovery and design. By analyzing experimental and theoretical data, machine learning can effectively predict their hydrogen evolution reaction (HER) performance. This review summarizes recent developments in machine learning for low-dimensional electrocatalysts, including zero-dimension nanoparticles and nanoclusters, one-dimensional nanotubes and nanowires, two-dimensional nanosheets, as well as other electrocatalysts. In particular, the effects of descriptors and algorithms on screening low-dimensional electrocatalysts and investigating their HER performance are highlighted. Finally, the future directions and perspectives for machine learning in electrocatalysis are discussed, emphasizing the potential for machine learning to accelerate electrocatalyst discovery, optimize their performance, and provide new insights into electrocatalytic mechanisms. Overall, this work offers an in-depth understanding of the current state of machine learning in electrocatalysis and its potential for future research. [ABSTRACT FROM AUTHOR]

Neoadjuvant therapy (NAT) for pancreatic cancer (PC) has achieved certain results. This article was aimed to analyze the trends in NAT in PC over the past 20 years using bibliometric analysis and visualization tools to guide researchers in exploring future research hotspots. Articles related to NAT for PC were retrieved from the Web of Science Core Collection for the period 2002–2021. The information was analyzed and visualized using VOSviewer, Citespace, Microsoft Excel and R software. The number of articles per year has continued to increase over the past 20 years. Of the 1,598 eligible articles, the highest number was from the United States (760), and an analysis of institutions indicated that the University of Texas System (150) had the highest number of articles. Matthew H. G. Katz had the highest number of citations and the highest H-index. "Pancreatic cancer" (981), "Resection" (623), "Cancer" (553), "Neoadjuvant therapy" (509) and "Survival" (484) were the top five ranked keywords. Combined with the keywords-cluster analysis and citation burst analysis, current research hotspots were the optimal NAT regimen, NAT response assessment, NAT for resectable PC and management of complications. NAT has received increasing attention in the field of PC over the past 20 years, but greater collaboration between countries and additional multicenter randomized clinical trials are needed. Overall, we have revealed current research hotspots and provided valuable information for the choice of future research directions. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to investigate alterations in the topological organization of whole-brain functional networks in patients with chronic low back pain (CLBP) and characterize the relationship of these alterations with pain characteristics. Methods: Thirty-three CLBP patients and 34 matched healthy controls (HCs) underwent fMRI scans. A graph-theoretical approach was applied to identify brain network changes in patients suffering from chronic low back pain given its nonspecific etiology and complexity. Graph theory-based analysis was used to construct functional connectivity matrices and extract the features of small-world networks of the brain in both groups. Then, the whole-brain functional connectivity differences were characterized by network-based statistics (NBS) analysis, and the relationship between the altered brain features and clinical measures was explored. Results: At the global level, patients with CLBP showed significantly decreased gamma, sigma, global efficiency, and local efficiency and increased lambda and shortest path length compared with HCs. At the regional level, there were deficits in nodal efficiency within the default mode network and salience network. NBS analysis demonstrated that decreased functional connectivity was present in the CLBP patients, mainly in the frontolimbic circuit and temporal regions. Furthermore, aspects of topological dysfunctions in CLBP were correlated with pain severity. Conclusion: This study highlighted the aberrant topological organization of functional brain networks in CLBP, which may shed light on the pathophysiology of CLBP and support the development of pain management approaches. [ABSTRACT FROM AUTHOR]

Cyperus rotundus L. has been widely used in the treatment and prevention of numerous diseases in traditional systems of medicine around the world, such as nervous, gastrointestinal systems diseases and inflammation. In traditional Chinese medicine (TCM), its rhizomes are frequently used to treat liver disease, stomach pain, breast tenderness, dysmenorrheal and menstrual irregularities. The review is conducted to summarize comprehensively the plant's vernacular names, distribution, phytochemistry, pharmacology, toxicology and analytical methods, along with the data mining for TCM prescriptions containing C. rotundus. Herein, 552 compounds isolated or identified from C. rotundus were systematically collated and classified, concerning monoterpenoids, sesquiterpenoids, flavonoids, phenylpropanoids, phenolics and phenolic glycosides, triterpenoids and steroids, diterpenoids, quinonoids, alkaloids, saccharides and others. Their pharmacological effects on the digestive system, nervous system, gynecological diseases, and other bioactivities like antioxidant, anti-inflammatory, anti-cancer, insect repellent, anti-microbial activity, etc. were summarized accordingly. Moreover, except for the data mining on the compatibility of C. rotundus in TCM, the separation, identification and analytical methods of C. rotundus compositions were also systematically summarized, and constituents of the essential oils from different regions were re-analyzed using multivariate statistical analysis. In addition, the toxicological study progresses on C. rotundus revealed the safety property of this herb. This review is designed to serve as a scientific basis and theoretical reference for further exploration into the clinical use and scientific research of C. rotundus. [ABSTRACT FROM AUTHOR]

The aim of the current research was to explore the influence of bismuth (Bi) nanoparticles on the single-crystal iron (Fe) nano-cutting process using molecular dynamics (MD) simulations. The existence of Bi nanoparticles in the workpiece affected the variation of cutting force, Von_mises stress distribution and dislocation generation during nano-cutting process. Thus, based on the study of one nanoparticle presence in this paper, the influences of different cutting depths and nanoparticle distribution were also considered separately. The results demonstrated that when the tool cut through Bi nanoparticles, the cutting force and Von_mises stress in the cutting zone were both decreased owing to the smaller hardness of Bi nanoparticles than Fe substrate and the nanoparticles undergo deformation. Dislocation Analysis (DXA) analysis revealed that the presence of Bi soft nanoparticles hindered the dislocation generation, which is unlike the presence of hard nanoparticles, and the BCC Defect Analysis (BDA) analysis showed dislocations, twins and vacancy defects in the workpiece. In addition, the cutting force, workpiece temperature and Von_mises stress increased with the cutting depth, yet the cutting force still decreased when the tool cut through the upper surface of the Bi nanoparticles without contacting the Bi nanoparticles, which was caused by the deformation of Bi nanoparticles under the stress of the shear deformation zone. When two Bi nanoparticles were present in the Fe matrix, the second Bi nanoparticle impedes the movements of the generated dislocations and the cutting force would be reduced when the tool cut over two nanoparticles. This research contributes to understanding the role of Bi nanoparticles in free-cutting steels from the nano perspective. [ABSTRACT FROM AUTHOR]

Objective: To assess the effect and safety of Reyanning Mixture (RYN) in treating asymptomatic or mild severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in children and adolescents. Methods: This is a prospective, open-label, randomized controlled trial. Patients aged 1–17 years and diagnosed with asymptomatic or mild coronavirus disease-2019 (COVID-19) were assigned to an intervention group (RYN plus standard care) and a control group (standard care) according to a randomization list. The primary outcomes were SARS-CoV-2 negative conversion time. Secondary outcomes included negative conversion rate on days 3 and 7, hospital length of stay, symptom relief rate, new-onset symptoms of asymptomatic infected patients, and progressive disease rate. The cycle threshold (Ct) values of ORF1ab or N genes were also tested. Results: A total of 214 patients in the intervention group and 217 in the control group were analyzed. The SARS-CoV-2 negative conversion time was significantly shortened in the intervention group [5 days (interquartile range (IQR): 5–6) vs. 7 days (IQR: 6–7), P<0.01]. By days 3 and 7, the negative conversion rates were significantly higher in the intervention group (day 3: 32.7% vs. 21.2%, P=0.007; day 7: 75.2% vs. 60.8%, P=0.001). Ct values significantly increase on day 2 [ORF1ab gene: 35.62 (IQR: 29.17–45.00) vs. 34.22 (IQR: 28.41–39.41), P=0.03; N gene: 34.97 (IQR: 28.50–45.00) vs. 33.51 (IQR: 27.70–38.25), P=0.024] and day 3 [ORF1ab gene: 38.00 (IQR: 32.72–45.00) vs. 35.81 (IQR: 29.96–45.00), P=0.003; N gene: 37.16 (IQR: 32.01–45.00) vs. 35.26 (IQR: 29.09–45.00), P=0.01]. No significant difference was found in hospital length of stay between the two groups (P>0.05). Symptoms of cough were significantly improved (82.2% vs. 70.0%, P=0.02) and wheezing was significantly reduced (0.7% vs. 12.9%, P<0.01) in the intervention group compared with the control group. During the trial, no disease progression or serious adverse events were reported. Conclusion: Adding RYN to standard care may be a safe and effective treatment for children with asymptomatic and mild SARS-CoV-2 infection. (Registration No. ChiCTR2200060292) [ABSTRACT FROM AUTHOR]

By the q-to-Q relationship between the 3D coupled nonautonomous nonlinear Schrödinger system and Manakov model, with the help of the Darboux transform technique, vector fundamental bright–bright and bright–dark freak wave solutions with two different forms of coupled components are found. Analyzing the physical quantities of solution formation hints that diffraction parameters and phase chirps strongly affect the properties of freak waves including amplitude, width, center and phase. By selecting suitable parameters, we can realize three different cases to find the excitation controllability of vector bright–bright and bright–dark freak waves, including shape delayed excitation, shape maximum excitation and shape initial excitation. [ABSTRACT FROM AUTHOR]

Introduction: Lymph node metastasis is a cause of poor prognosis in breast cancer. Mass spectrometry-based proteomics aims to map the protein landscapes of biological samples and profile tumors more comprehensively. Here, proteomics was employed to identify differentially expressed proteins (DEPs) that were associated with lymph node metastasis. Methods: Tandem mass tag (TMT) quantitative proteomic approaches were applied for extensive profiling of conditioned medium of MDA-MB-231 and MCF7 cell lines and serums of patients who did or did not have lymph node metastasis, and DEPs were analyzed by bioinformatics. Furthermore, potential secreted or membrane proteins MUC5AC, ITGB4, CTGF, EphA2, S100A4, PRDX2, and PRDX6 were selected for verification in 114 tissue microarray samples of breast cancer using the immunohistochemical method. The relevant data was analyzed and processed by independent sample t test, chi-square test, or Fisher's exact test using SPSS 22.0 software. Results: In the conditioned medium of MDA-MB-231 cell lines, 154 proteins were upregulated, while 136 were downregulated compared to those of MCF7. In the serum of patients with breast cancer and lymph node metastasis, 17 proteins were upregulated, and 5 proteins were downregulated compared to those without lymph node metastasis. Furthermore, according to tissue verification, CTGF, EphA2, S100A4, and PRDX2 were associated with breast cancer lymph node metastasis. Conclusion: Our study provides a new perspective for the understanding of the role of DEPs (especially CTGF, EphA2, S100A4, and PRDX2) in the development and metastasis of breast cancer. They could become potential diagnostic and prognostic biomarkers and therapeutic targets. [ABSTRACT FROM AUTHOR]

Clarification of wear behaviors would be attractive for selecting and designing wear-resistant materials. In this study, the wear behaviors of bainitic and martensitic wear-resistant steels (FB and H400) were investigated under different wear conditions. Comparing the wear resistance of FB with that of H400 specimen, the former was inferior to the latter under three-body abrasive wear, but the opposite was true based on the impact wear results. FB, composed of bainite, martensite, and retained austenite (RA), exhibited lower resistance against abrasive cutting because of its lower hardness and yield strength. The H400, composed of high-hardness martensite, displayed great three-body abrasive resistance, but the wear behavior changed when impact wear was introduced. In addition, the fatigue triggered by the impact of the wear surface played a greater role. The FB with RA had higher plasticity because of the transformation-induced plasticity (TRIP) effect, which could delay fatigue crack growth. Therefore, the FB demonstrated better wear resistance under impact wear. [ABSTRACT FROM AUTHOR]

Main conclusion: CgPG21 is mainly located in the cell wall, participates in the intercellular layer degradation of the cell wall during the formation of secretory cavity in the intercellular space-forming and lumen-expanding stages. The secretory cavity is a common structure in Citrus plants and is the main site for synthesis and accumulation of medicinal ingredients. The secretory cavity is formed in lysogenesis, when epithelial cells enter a process of programmed cell death. Pectinases are known to be involved in degradation of the cell wall during the cytolysis of secretory cavity cells, but the changes in cell structure, the dynamic characteristics of cell wall polysaccharides and the related genes regulating cell wall degradation are unclear. In this study, electron microscopy and cell wall polysaccharide-labeling techniques were used to study the main characteristics of cell wall degradation of the secreting cavity of Citrus grandis 'Tomentosa' fruits. At the same time, the full CDS length of the pectinase gene CgPG21 was cloned, encoding a protein composed of 480 amino acids. CgPG21 is mainly located in the cell wall, participates in the degradation of the intercellular layer of the cell wall during the development of the secretory cavity, and plays an important role in the formation of the secretory cavity in the intercellular space-forming and lumen-expanding stages. With the development of secretory cavity, the cell wall polysaccharides of epithelial cells gradually degrade. CgPG21 is mainly involved in the intercellular layer degradation. [ABSTRACT FROM AUTHOR]

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Highlights: Carbon fiber (CF) scaffolds with horizontally aligned, diagonally aligned and vertically aligned structure were fabricated via magnetic field-assisted Tetris-style stacking and carbonization process. The obtained CF scaffolds/ polydimethylsiloxane composites showed ultrahigh thermal conductivity (above 40 W m−1 K−1) in the fiber alignment direction. Fibers with different alignment direction can be combined by multiple stacking and carbonization process, allowing for the efficient heat transfer along customized paths. As the miniaturization of electronic devices and complication of electronic packaging, there are growing demands for thermal interfacial materials with enhanced thermal conductivity and the capability to direct the heat toward heat sink for highly efficient heat dissipation. Pitch-based carbon fiber (CF) with ultrahigh axial thermal conductivity and aspect ratios exhibits great potential for developing thermally conductive composites as TIMs. However, it is still hard to fabricate composites with aligned carbon fiber in a general approach to fully utilize its excellent axial thermal conductivity in specific direction. Here, three types of CF scaffolds with different oriented structure were developed via magnetic field-assisted Tetris-style stacking and carbonization process. By regulating the magnetic field direction and initial stacking density, the self-supporting CF scaffolds with horizontally aligned (HCS), diagonally aligned and vertically aligned (VCS) fibers were constructed. After embedding the polydimethylsiloxane (PDMS), the three composites exhibited unique heat transfer properties, and the HCS/PDMS and VCS/PDMS composites presented a high thermal conductivity of 42.18 and 45.01 W m−1 K−1 in fiber alignment direction, respectively, which were about 209 and 224 times higher than that of PDMS. The excellent thermal conductivity is mainly ascribed that the oriented CF scaffolds construct effective phonon transport pathway in the matrix. In addition, fishbone-shaped CF scaffold was also produced by multiple stacking and carbonization process, and the prepared composites exhibited a controlled heat transfer path, which can allow more versatility in the design of thermal management system. [ABSTRACT FROM AUTHOR]

Background: Toripalimab is an immune checkpoint inhibitor (ICI) against programmed death ligand 1 (PD-L1). It has been approved for advanced esophageal squamous cell carcinoma (ESCC) as the first-line treatment due to significantly improved progression-free survival (PFS) and overall survival (OS) in the JUPITER-06 trial. Aim: This study aimed to compare the cost-effectiveness between toripalimab plus chemotherapy and placebo plus chemotherapy from the perspective of the Chinese health system. Method: The study developed a 3-year partitioned survival model to assess costs and outcomes in two treatment groups with or without toripalimab. The critical indicator was the incremental cost-effectiveness ratio (ICER). Scenario and sensitivity analyses were performed to evaluate the robustness of the findings and identify the parameters with the greatest impact on cost-effectiveness. Results: In the base case analysis, the incremental effectiveness and cost of toripalimab plus chemotherapy versus placebo plus chemotherapy were 0.26 quality-adjusted life year (QALYs) and $11,254.84, respectively, resulting in an ICER of $43,405.09/QALY, higher than the 2021 willingness-to-pay threshold in China ($37,658.70/QALY). The results were sensitive to the utility of PFS, the incidence of neutropenia in the toripalimab group, and the cost of toripalimab. The toripalimab plus chemotherapy group was cost-effective only if the price of toripalimab decreased by more than 40%. Conclusion: Adding toripalimab to chemotherapy was not cost-effective in patients with advanced ESCC in China. [ABSTRACT FROM AUTHOR]