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Abstract Cross‐dataset object detection methods can adapt to the needs of rapid category expansion in object detection tasks. However, these methods are prone to generate dataset‐aware errors with false alarm objects. This study is aimed to address these issues. A box‐separated multiple‐head module and box‐separated loss function based on the YOLOv8 network are devised to achieve cross‐dataset object detection. Additionally, a sameclass‐aware fusion module to avoid gradient conflicts due to cross‐category conflicts is developed. A multiple‐head fusion module is devised to reduce the number of false alarm objects caused by dataset‐aware errors. A global class‐aware sampler is also designed to adapt to the impact of the imbalanced number of categories and training samples across datasets. The effectiveness of the box‐separated multiple‐head module is verified using cross‐datasets built using the COCO, WiderFace, WiderPerson, and OpenImages V4 datasets. Extensive experiments demonstrate the efficiency and precision of the proposed method.

Abstract Background Organoids are approved by the US FDA as an alternative to animal experiments to guide drug development and for sensitivity screening. Stable organoids models of gastric cancer are desirable for personalized medicine and drug screening. Methods Tumor tissues from a primary cancer of the stomach and metastatic cancer of the lymph node were collected for 3D culture. By long-term culture for over 50 generations in vitro, we obtained stably growing organoid lines. We analyzed short tandem repeats (STRs) and karyotypes of cancer cells, and tumorigenesis of the organoids in nude mice, as well as multi-omics profiles of the organoids. A CCK8 method was used to determine the drugs sensitivity to fluorouracil (5-Fu), platinum and paclitaxel. Results Paired organoid lines from primary cancer (SPDO1P) and metastatic lymph node (SPDO1LM) were established with unique STRs and karyotypes. The organoid lines resulted in tumorigenesis in vivo and had clear genetic profiles. Compared to SPDO1P from primary cancer, upregulated genes of SPDO1LM from the metastatic lymph node were enriched in pathways of epithelial-mesenchymal transition and angiogenesis with stronger abilities of cell migration, invasion, and pro-angiogenesis. Based on drug sensitivity analysis, the SOX regimen (5-Fu plus oxaliplatin) was used for chemotherapy with an optimal clinical outcome. Conclusions The organoid lines recapitulate the drug sensitivity of the parental tissues. The paired organoid lines present a step-change toward living biobanks for further translational usage.

Abstract Background Papillary thyroid carcinoma (PTC) is globally prevalent and associated with an increased risk of lymph node metastasis (LNM). The role of cancer-associated fibroblasts (CAFs) in PTC remains unclear. Methods We collected postoperative pathological hematoxylin–eosin (HE) slides from 984 included patients with PTC to analyze the density of CAF infiltration at the invasive front of the tumor using QuPath software. The relationship between CAF density and LNM was assessed. Single-cell RNA sequencing (scRNA-seq) data from GSE193581 and GSE184362 datasets were integrated to analyze CAF infiltration in PTC. A comprehensive suite of in vitro experiments, encompassing EdU labeling, wound scratch assays, Transwell assays, and flow cytometry, were conducted to elucidate the regulatory role of CD36+CAF in two PTC cell lines, TPC1 and K1. Results A significant correlation was observed between high fibrosis density at the invasive front of the tumor and LNM. Analysis of scRNA-seq data revealed metastasis-associated myoCAFs with robust intercellular interactions. A diagnostic model based on metastasis-associated myoCAF genes was established and refined through deep learning methods. CD36 positive expression in CAFs can significantly promote the proliferation, migration, and invasion abilities of PTC cells, while inhibiting the apoptosis of PTC cells. Conclusion This study addresses the significant issue of LNM risk in PTC. Analysis of postoperative HE pathological slides from a substantial patient cohort reveals a notable association between high fibrosis density at the invasive front of the tumor and LNM. Integration of scRNA-seq data comprehensively analyzes CAF infiltration in PTC, identifying metastasis-associated myoCAFs with strong intercellular interactions. In vitro experimental results indicate that CD36 positive expression in CAFs plays a promoting role in the progression of PTC. Overall, these findings provide crucial insights into the function of CAF subset in PTC metastasis.

Abstract Background DNMT3L is a crucial DNA methylation regulatory factor, yet its function and mechanism in hepatocellular carcinoma (HCC) remain poorly understood. Bioinformatics-based big data analysis has increasingly gained significance in cancer research. Therefore, this study aims to elucidate the role of DNMT3L in HCC by integrating big data analysis with experimental validation. Methods Dozens of HCC datasets were collected to analyze the expression of DNMT3L and its relationship with prognostic indicators, and were used for molecular regulatory relationship evaluation. The effects of DNMT3L on the malignant phenotypes of hepatoma cells were confirmed in vitro and in vivo. The regulatory mechanisms of DNMT3L were explored through MSP, western blot, and dual-luciferase assays. Results DNMT3L was found to be downregulated in HCC tissues and associated with better prognosis. Overexpression of DNMT3L inhibits cell proliferation and metastasis. Additionally, CDO1 was identified as a target gene of DNMT3L and also exhibits anti-cancer effects. DNMT3L upregulates CDO1 expression by competitively inhibiting DNMT3A-mediated methylation of CDO1 promoter. Conclusions Our study revealed the role and epi-transcriptomic regulatory mechanism of DNMT3L in HCC, and underscored the essential role and applicability of big data analysis in elucidating complex biological processes.

The flow and diffusion of high-temperature smoke in mine fires is an important cause of safety accidents. In response to the unclear relationship between fire hazard zones and time in typical mine roadways, a safety zone classification method for T-shaped roadway fire in deep coal mines is proposed. A three-dimensional numerical model is established using Pyrosim software to simulate the high-temperature smoke flow in the T-shaped roadway during the fire development stage under high temperature and humidity conditions. The variation law of temperature field and CO, CO2 concentration field with time and spatial location in the T-shaped roadway during the fire development stage are revealed. Based on the simulated data of the height of the human mouth and nose (i.e. the height of 1.6 meters in the roadway), the relationship between the horizontal length of the roadway and temperature, CO concentration and CO2 concentration is obtained. The airflow mixes high-temperature smoke through the roadway and spreads downwards along the top of the roadway. As the distance from the fire source increases, the temprature gradually decreases, and the longitudinal distribution of CO and CO2 concentration contour lines becomes denser. On this basis, safety zones are classified based on the temperature of the smoke and the harm degree of CO and CO2 concentration to human health. The smoke diffusion area is divided into four categories: safety zone (hazard level 1), mild hazard zone (hazard level 2), moderate hazard zone (hazard level 3), and severe hazard zone (hazard level 4). The analysis results show that in the temperature classification results, the measurement points in roadwayⅠare mainly concentrated in the severe hazard zone. In the toxic gas classification results, the safety zone range of CO2 in roadway Ⅰ is larger than that of CO. The risk factors for CO are greater, mainly concentrated in mild and moderate hazard zones. In roadway Ⅱ, it is mainly concentrated in mild hazard zones. The range of hazard level 1 in roadway Ⅰ gradually decreases over time, while the range of hazard level 4 gradually increases over time, with the maximum change rate occurring at 40 seconds. The rates of change for hazard levels 2 and 3 are very small. The regional range changes of the two classification methods in roadway Ⅱ are similar, with the maximum change rate of hazard levels 2 and 3 occurring at 60 seconds.

As a highly regarded superconducting material with a concise layered structure, MgB2 has attracted significant scientific attention and holds vast potential for applications. However, its limited current-carrying capacity under high magnetic fields has greatly hindered its practical use. To address this issue, we have enhanced the superconducting performance of MgB2 by incorporating inhomogeneous phase nanostructures of p-n junctions with electroluminescent properties. Through temperature-dependent measurements of magnetization, electronic specific heat, and Hall coefficient under various magnetic fields, we have confirmed the crucial role of inhomogeneous phase electroluminescent nanostructures in improving the properties of MgB2. Experimental results demonstrate that the introduction of electroluminescent inhomogeneous phases effectively enhances the superconducting performance of MgB2. Moreover, by controlling the size of the electroluminescent inhomogeneous phases and optimizing grain connectivity, density, and microstructural uniformity, we can further improve the critical temperature (TC) and flux-pinning capability of MgB2 superconducting materials. Comprehensive studies on the physical properties of MgB2 superconducting structures added with p-n junction electroluminescent inhomogeneous phases also confirm the general effectiveness of electroluminescent inhomogeneous phases in enhancing the performance of superconducting materials.

AbstractBackground Anti-CD19 chimeric antigen receptors (CARs) T-cell therapy has been shown to have excellent efficacy in patients with relapsed/refractory (R/R) B-cell acute lymphoblastic leukemia (ALL). But many patients are refractory to anti-CD19-CAR T-cell therapy or relapse again.Methods Five patients with R/R B-ALL did not respond to anti-CD19-CAR T-cell therapy or had a disease progression again after CAR-T cell therapy. They received a salvage therapy of Blinatumomab. The clinical response, CD19 expression on ALL cells, the proportion of CD3+ T cells, level of cytokine levels of interleukin-6 (IL-6), hematological toxicity, grade of cytokine release syndrome (CRS), and immune effector cell-associated neurotoxic syndrome (ICANS) were observed in salvage therapy of Blinatumomab.Results Four patients obtained CR/CRi, even in patients without high expression of CD19 in B-ALL cells, while the other patient received NR after Blinatumomab therapy. The CD19 expression on ALL cells, the proportion of CD3+ T cells, and CD3+CD8+ T cells were deficient in Pt 5, who obtained PR in Blinatumomab therapy. One patient (Pt 3) was diagnosed with grade 0 hematological toxicity. The other four patients were diagnosed with grades 2–3 of hematological toxicity. The CRS was grade 0/one patient, grade 1/three, and grade 2/one. The ICANS was grade 0/four patients, grade 1/one. Rhizopus microsporus pneumonia and cryptococcal encephalopathy in two patients were controlled during Blinatumomab therapy.Conclusions Blinatumomab could be an effective and safe salvage therapy in patients with R/R B-ALL who failed/progressed after anti-CD19-CAR T therapy, even in R/R B-ALL patients without high expression of CD19 in B-ALL cells, patients with CNS leukemia or co-infection.Key messagesSome R/R B-ALL patients did not respond to anti-CD19 CAR T-cell therapy or had a disease progression again. Effective and safe salvage therapy for such patients remains to be explored.Blinatumomab could be an effective and safe salvage therapy in patients with R/R B-ALL who failed/progressed after anti-CD19-CAR T therapy, even in patients without high expression of CD19 in B-ALL cells.Blinatumomab could be an effective and safe salvage therapy in patients with R/R B-ALL who failed/progressed after anti-CD19-CAR T therapy, even in patients with CNS leukemia or co-infection.

This paper explores solitary wave solutions arising in the deformations of a hyperelastic compressible plate. Explicit traveling wave solution expressions with various parameters for the hyperelastic compressible plate are obtained and visualized. To analyze the perturbed equation, we employ geometric singular perturbation theory, Melnikov methods, and invariant manifold theory. The solitary wave solutions of the hyperelastic compressible plate do not persist under small perturbations for wave speed c>−βk2. Further exploration of nonlinear models that accurately depict the persistence of solitary wave solution on the significant physical processes under the K-S perturbation is recommended.

How to effectively transform the pro-oncogenic tumor microenvironments (TME) surrounding a tumor into an anti-tumoral never fails to attract people to study. Small interfering RNA (siRNA) is considered one of the most noteworthy research directions that can regulate gene expression following a process known as RNA interference (RNAi). The research about siRNA delivery targeting tumor cells and TME has been on the rise in recent years. Using siRNA drugs to silence critical proteins in TME was one of the most efficient solutions. However, the manufacture of a siRNA delivery system faces three major obstacles, i.e., appropriate cargo protection, accurately targeted delivery, and site-specific cargo release. In the following review, we summarized the pharmacological actions of siRNA drugs in remolding TME. In addition, the delivery strategies of siRNA drugs and combination therapy with siRNA drugs to remodel TME are thoroughly discussed. In the meanwhile, the most recent advancements in the development of all clinically investigated and commercialized siRNA delivery technologies are also presented. Ultimately, we propose that nanoparticle drug delivery siRNA may be the future research focus of oncogene therapy. This summary offers a thorough analysis and roadmap for general readers working in the field.

Superconducting materials exhibit unique physical properties and have great scientific value and vast industrial application prospects. However, due to limitations, such as the critical temperature (TC) and critical current density (JC), the large-scale application of superconducting materials remains challenging. Chemical doping has been a commonly used method to enhance the superconductivity of B(P)SCCO. However, satisfactory enhancement results have been difficult to achieve. In this study, we introduce green-light GaN p-n junction particles as inhomogeneous phases into B(P)SCCO polycrystalline particles to form a smart meta-superconductor (SMSC) structure. Based on the electroluminescence properties of the p-n junction, the Cooper pairs were stimulated and strengthened to enhance the superconductivity of B(P)SCCO. The experimental results demonstrate that the introduction of inhomogeneous phases can indeed enhance the critical temperature TC, critical current density JC, and complete diamagnetism (Meissner effect) of B(P)SCCO superconductors. Moreover, when the particle size of the raw material of B(P)SCCO is reduced from 30 to 5 μm, the grain size of the sintered samples also decreases, and the optimal doping concentration of the inhomogeneous phases increases from 0.15 wt.% to 0.2 wt.%, further improving the superconductivity.

With the development of communication and computer technology, the application of big data technology has become increasingly widespread. Reasonable, effective, and fast retrieval methods for querying information from massive data have become an important content of current research. This article provides an image retrieval method based on the weighted nearest neighbor label prediction for the problem of automatic image annotation and keyword image retrieval. In order to improve the performance of the test method, scientific experimental verification was implemented. The nearest neighbor weights are determined by maximizing the training image annotation, and experiments are carried out from multiple angles based on the Mahalanobis metric learning integration model. The experimental results show that the proposed tag correlation prediction propagation model has obvious improvements in accuracy, recall rate, break-even point, and overall average accuracy performance compared with other widely used algorithm models.

Abstract Background The exchange of mitochondria reportedly plays an important role in cell–cell communication in the central nervous system (CNS). The transfer of fragmented and dysfunctional astrocytic mitochondria into neurons and subsequent mitochondrial fusion often cause serious neuronal damage and cerebral ischaemic injury. Methods In this study, we prepared macrophage-derived exosomes laden with heptapeptide (Hep) as a dynamin-related protein-1 (Drp1)–fission 1 (Fis1) peptide inhibitor P110 to alleviate cerebral ischemia–reperfusion injury by reducing mitochondrial Drp1/Fis1 interaction-mediated astrocytic mitochondrial disorder and promoting the transfer of astrocyte-derived healthy mitochondria into neurons. Results The results demonstrated that Hep-loaded macrophage-derived exosomes (EXO-Hep) reduced mitochondrial damage in astrocytes by inhibiting the Drp1/Fis1 interaction after ischemia–reperfusion, ensuring the release of heathy astrocytic mitochondria and their subsequent transmission to neurons, alleviating mitochondria-mediated neuronal damage. Conclusion EXO-Hep significantly mitigated ischemic injury in a model of transient middle cerebral artery occlusion (tMCAO) by reducing the infarct area and improving neurological performance during the process of cerebral ischemia–reperfusion. Graphical Abstract

Abstract Background As recovery time of diabetic wound injury is prolonged by the production of detrimental factors, including reactive oxygen species (ROS) and inflammatory cytokines, attenuating the oxidative stress and inflammatory reactions in the microenvironment of the diabetic wound site would be significant. Experimental design In our study, we prepared thermoreversible, antibacterial zeolite-based nanoparticles loaded hydrogel to promote diabetic wound healing via the neutralization of detrimental factors such as inflammatory cytokines and ROS. Results The cerium (Ce)-doped biotype Linde type A (LTA) zeolite nanoparticles synergistically eliminated mitochondrial ROS and neutralized free inflammatory factors, thus remodeling the anti-inflammatory microenvironment of the wound and enhancing angiogenesis. Moreover, the thermoreversible hydrogel composed of Pluronic F127 and chitosan demonstrated strong haemostatic and bactericidal behavior. Conclusions In conclusion, the obtained thermoreversible, antibacterial, zeolite-based nanoparticles loaded hydrogels represent a multi-targeted combination therapy for diabetic wound healing. Graphical Abstract

Appropriate biomimetic scaffolds created via 3D bioprinting are promising methods for treating damaged menisci. However, given the unique anatomical structure and complex stress environment of the meniscus, many studies have adopted various techniques to take full advantage of different materials, such as the printing combined with infusion, or electrospining, to chase the biomimetic meniscus, which makes the process complicated to some extent. Some researchers have tried to tackle the challenges only by 3D biopringting, while its alternative materials and models have been constrained. In this study, based on a multilayer biomimetic strategy, we optimized the preparation of meniscus-derived bioink, gelatin methacrylate (GelMA)/meniscal extracellular matrix (MECM), to take printability and cytocompatibility into account together. Subsequently, a customized 3D bioprinting system featuring a dual nozzle + multitemperature printing was used to integrate the advantages of polycaprolactone (PCL) and meniscal fibrocartilage chondrocytes (MFCs)-laden GelMA/MECM bioink to complete the biomimetic meniscal scaffold, which had the best biomimetic features in terms of morphology and components. Furthermore, cell viability, mechanics, biodegradation and tissue formation in vivo were performed to ensure that the scaffold had sufficient feasibility and functionality, thereby providing a reliable basis for its application in tissue engineering.

Abstract Background The majority of the human genome is transcribed in the form of long non-coding (lnc) RNAs. While these transcripts have attracted considerable interest, their molecular mechanisms of function and biological significance remain controversial. One of the main reasons behind this lies in the significant challenges posed by lncRNAs requiring the development of novel methods and concepts to unravel their functionality. Existing methods often lack cross-validation and independent confirmation by different methodologies and therefore leave significant ambiguity as to the authenticity of the outcomes. Nonetheless, despite all the caveats, it appears that lncRNAs may function, at least in part, by regulating other genes via chromatin interactions. Therefore, the function of a lncRNA could be inferred from the function of genes it regulates. In this work, we present a genome-wide functional annotation strategy for lncRNAs based on identification of their regulatory networks via the integration of three distinct types of approaches: co-expression analysis, mapping of lncRNA-chromatin interactions, and assaying molecular effects of lncRNA knockdowns obtained using an inducible and highly specific CRISPR/Cas13 system. Results We applied the strategy to annotate 407 very long intergenic non-coding (vlinc) RNAs belonging to a novel widespread subclass of lncRNAs. We show that vlincRNAs indeed appear to regulate multiple genes encoding proteins predominantly involved in RNA- and development-related functions, cell cycle, and cellular adhesion via a mechanism involving proximity between vlincRNAs and their targets in the nucleus. A typical vlincRNAs can be both a positive and negative regulator and regulate multiple genes both in trans and cis. Finally, we show vlincRNAs and their regulatory networks potentially represent novel components of DNA damage response and are functionally important for the ability of cancer cells to survive genotoxic stress. Conclusions This study provides strong evidence for the regulatory role of the vlincRNA class of lncRNAs and a potentially important role played by these transcripts in the hidden layer of RNA-based regulation in complex biological systems.

With the technological evolutionary advent, a vision-based approach presents the remote measuring approach for the analysis of vibration. The structure vibration test and model parameter identification in the detection of the structure of the bridge evaluation occupies the important position. The bridge structure to operate safely and reliably is ensured, according to the geological data of qixiashan lead-zinc mine and engineering actual situation, with the aid of international mining software Surpac. To build the 3D visualization model of the application of visualization in mine production are discussed. The results show that the final solid model of -425 stope can accurately display the spatial form of each layer of stope through rotation, amplification and movement. The proposed system is effectually able to perform cutting, volume calculation and roaming in any direction, which has certain guiding significance for mine production management. An accuracy value of 98.75%, the sensitivity of 99%, specificity of 99.64% and PPV of 99.89% are achieved using the proposed 3D modelling and visualization algorithm for vibration signal processing and management.

Objective To explore and practice“rain classroom” in basic medical teaching. Methods Take the undergraduates majoring in Imaging Technology and Biotechnology in the class of 2018 of Dalian Medical University as the research objects Through questionnaire, the teachers and students' feedback on the wisdom teaching of “rain classroom” was investigated, so as to reflect and summarize the auxiliary teaching of “rain classroom”. Results Students believe that “rain classroom” is helpful to their physiology learning and hope to extend this method to use other courses. The teachers impressed on the “rain classroom” exercise answering system,data collection and analysis function which are helpful to understand the learning outcomes of students quantitatively, evaluate the teaching process and adjust the teaching strategy. Conclusions Under the guideline of “Internet +”, “rain classroom” can improve the quality and efficiency of education , encourage students' autonomous learning, promote students' personalized talents training, and thus support the reform of medical education and teaching methodology.

Psoriasis is chronic skin disease and an important health concern. Traditional Chinese Medicine (TCM) has shown great promise in the treatment of psoriasis. However, the correlation between TCM Syndromes and genomics of psoriasis has not been evaluated. Here, we analyzed gene expression profiling of monocytes from psoriasis vulgaris patients with different TCM syndrome types to reveal the molecular basis of different psoriasis syndromes. Of the 62 cases of psoriasis vulgaris recruited, 16, 23, and 23 cases were of blood-heat syndrome, blood stasis syndrome, and blood-dryness syndrome, respectively; 10 healthy controls were recruited as controls. Affymertix’s Gene Chip ®clariom D gene chip was used to detect the gene expression profile of peripheral blood monocytes collected from recruited individuals. Compared with the healthy control group, 1570 genes were up-regulated and 977 genes were down-regulated in the psoriasis vulgaris patients group; 798 genes and 108 genes were up- and down-regulated in the blood-heat syndrome group respectively; 319 and 433 genes were up- and down-regulated in the blood-dryness syndrome group, respectively; and 502 and 179 genes were up-and down-regulated in the blood-stasis syndrome group. Our analyses indicated not only common differential genes and pathways between psoriasis syndrome groups and healthy controls, but also syndrome-specific genes and pathways. The results of this study link the three syndromes at the gene level and will be useful for clarifying the molecular basis of TCM syndromes of psoriasis.Clinical Trial Registration: (http://www.chictr.org.cn/showproj.aspx?proj=4390), identifier (ChiCTR-TRC-14005185).

Abstract Background To analyze the expression of miRNA (microRNA) in peripheral blood mononuclear cells in patients with Psoriasis vulgaris with different TCM syndromes by miRNA chip. It further revealed the micromaterial basis of different syndrome types of psoriasis at the miRNA level. Methods Peripheral blood monocytes were collected and prepared from 30 patients with Psoriasis vulgaris (including 9 patients of blood heat syndrome, 8 patients of blood stasis syndrome, and 13 patients of blood dry syndrome) and 9 healthy controls. The miRNA expression profile of peripheral blood monocytes was detected by Agilent Hum miRNA chip. Results Compared to the healthy control group, 156 upregulated and 242 downregulated miRNAs were detected in all psoriasis patients. Compared to the healthy control group, 40 miRNAs were upregulated and 44 were downregulated in the blood heat syndrome group. Furthermore, there were 49 upregulated miRNAs and 44 downregulated miRNAs in the dry syndrome group as compared to the healthy control group. Also, 67 miRNAs were upregulated and 154 miRNAs were downregulated in the blood stasis syndrome group as compared to the healthy control group. Conclusions There are common different miRNAs and pathways, as well as specific miRNAs between the psoriasis and the healthy control groups. Trial registration ChiCTR-TRC-14005185 registered on August 8, 2014.

It is reported that quercetin (Que) can prevent tau pathology and induce neuroprotection by improving cognitive and functional symptoms in the treatment of Alzheimer’s disease (AD). However, its clinical application has been limited due to its poor brain targeting and bioavailability. Exosomes are considered as cargo carriers for intercellular communication and especially serve as a natural and important drug brain delivery platform for achieving better treatment of central neurological diseases. Here, we developed plasma exosomes (Exo) loaded with Que (Exo-Que) to improve the drug bioavailability, enhance the brain targeting of Que and potently ameliorate cognitive dysfunction in okadaic acid (OA)-induced AD mice. Our results showed that Exo-Que improved brain targeting of Que as well as significantly enhanced bioavailability of Que. Furthermore, compared with free Que, Exo-Que better relieved the symptoms of AD by inhibiting cyclin-dependent kinase 5 (CDK5)-mediated phosphorylation of Tau and reducing formation of insoluble neurofibrillary tangles (NFTs), suggesting its therapeutic potential for better treatment of AD.

Early cancer detection is the key to a positive clinical outcome. While a number of early diagnostics methods exist in clinics today, they tend to be invasive and limited to a few cancer types. Thus, a clear need exists for non-invasive diagnostics methods that can be used to detect the presence of cancer of any type. Liquid biopsy based on analysis of molecular components of peripheral blood has shown significant promise in such pan-cancer diagnostics; however, existing methods based on this approach require improvements, especially in sensitivity of early-stage cancer detection. The improvement would likely require diagnostics assays based on multiple different types of biomarkers and, thus, calls for identification of novel types of cancer-related biomarkers that can be used in liquid biopsy. Whole-blood transcriptome, especially its non-coding component, represents an obvious yet under-explored biomarker for pan-cancer detection. In this study, we show that whole transcriptome analysis using RNA-seq could indeed serve as a viable biomarker for pan-cancer detection. Furthermore, a class of long non-coding (lnc) RNAs, very long intergenic non-coding (vlinc) RNAs, demonstrated superior performance compared with protein-coding mRNAs. Finally, we show that age and presence of non-blood cancers change transcriptome in similar, yet not identical, directions and explore implications of this observation for pan-cancer diagnostics.

Topological maps generated in complex and irregular unknown environments are meaningful for autonomous robots’ navigation. To obtain the skeleton of the environment without obstacle polygon extraction and clustering, we propose a method to obtain high-quality topological maps using only pure Voronoi diagrams in three steps. Supported by Voronoi vertex’s property of the largest empty circle, the method updates the global topological map incrementally in both dynamic and static environments online. The incremental method can be adapted to any fundamental Voronoi diagram generator. We maintain the entire space by two graphs, the pruned Voronoi graph for incremental updates and the reduced approximated generalized Voronoi graph for routing planning requests. We present an extensive benchmark and real-world experiment, and our method completes the environment representation in both indoor and outdoor areas. The proposed method generates a compact topological map in both small- and large-scale scenarios, which is defined as the total length and vertices of topological maps. Additionally, our method has been shortened by several orders of magnitude in terms of the total length and consumes less than 30% of the average time cost compared to state-of-the-art methods.

Increasing and improving the critical transition temperature (TC), current density (JC) and the Meissner effect (HC) of conventional superconductors are the most important problems in superconductivity research, but progress has been slow for many years. In this study, by introducing the p-n junction nanostructured electroluminescent inhomogeneous phase with a red wavelength to realize energy injection, we found the improved property of smart meta-superconductors MgB2, the critical transition temperature TC increases by 0.8 K, the current density JC increases by 37%, and the diamagnetism of the Meissner effect HC also significantly improved, compared with pure MgB2. Compared with the previous yttrium oxide inhomogeneous phase, the p-n junction has a higher luminescence intensity, a longer stable life and simpler external field requirements. The coupling between superconducting electrons and surface plasmon polaritons may be explained by this phenomenon. The realization of smart meta-superconductor by the electroluminescent inhomogeneous phase provides a new way to improve the performance of superconductors.

There are two kinds of methods for uncertain random multi-objective programming (URMOP) problem now. One is to convert the URMOP problem into deterministic multi-objective programming (DMOP) problem directly, and then solves the DMOP problem, which neglects the nature of the uncertainty and randomness. The other is to use the linear weighting method (LVM) to convert the URMOP problem into the uncertain random single-objective programming (URSOP) problem, and then convert it into the deterministic single-objective programming (DSOP) problem, which can be solved directly. However, the LVM has limited application range and low reliability. In this paper, we propose a new method named ideal point method (IPM) for solving the URMOP problem. First, we define the ideal point of URMOP. Based on different modules, we propose three different IPMs named SD-IPM, SWS-IPM, and WMM-IPM. It is then proved that under the PE criterion, the three IPMs can transform the URMOP problem into its equivalent URSOP problem, that is, the optimal solution of the transformed URSOP problem is proved to be the Pareto efficient solution of the original URMOP problem. Then, the URSOP problem can be transformed into its equivalent DSOP problem, which can be solved directly. The example discusses the differences and application range of the IPMs and other methods. The influences of weights are discussed simultaneously.

The smart meta-superconductor MgB2 and Bi(Pb)SrCaCuO increase the superconducting transition temperature (TC), but the changes in the transport critical current density (JC) and Meissner effect are still unknown. Here, we investigated the JC and Meissner effect of smart meta-superconductor MgB2 and Bi(Pb)SrCaCuO. The use of the standard four-probe method shows that Y2O3:Eu3+ and Y2O3:Eu3++Ag inhomogeneous phase significantly increase the JC, and JC decreases to a minimum value at a higher temperature. The Meissner effect was measured by direct current magnetization. The doping of Y2O3:Eu3+ and Y2O3:Eu3++Ag luminescent inhomogeneous phase causes a Meissner effect of MgB2 and Bi(Pb)SrCaCuO at a higher temperature, while the non-luminescent dopant reduces the temperature at which samples have Meissner effect. The introduction of luminescent inhomogeneous phase in conventional MgB2 and copper oxide high-temperature Bi(Pb)SrCaCuO superconductor increases the TC and JC, and Meissner effect is exerted at higher temperature. Therefore, smart meta-superconductivity is suitable for conventional and copper oxide high-temperature superconductors.

A smart meta-superconductor Bi(Pb)SrCaCuO (B(P)SCCO) may increase the critical transition temperature (TC) of B(P)SCCO by electroluminescence (EL) energy injection of inhomogeneous phases. However, the increase amplitude ΔTC (ΔTC=TC−TC,pure) of TC is relatively small. In this study, a smart meta-superconductor B(P)SCCO with different matrix sizes was designed. Three kinds of raw materials with different particle sizes were used, and different series of Y2O3:Sm3+, Y2O3, Y2O3:Eu3+, and Y2O3:Eu3++Ag-doped samples and pure B(P)SCCO were prepared. Results indicated that the TC of the Y2O3 or Y2O3:Sm3+ non-luminescent dopant doping sample is lower than that of pure B(P)SCCO. However, the TC of the Y2O3:Eu3++Ag or Y2O3:Eu3+ luminescent inhomogeneous phase doping sample is higher than that of pure B(P)SCCO. With the decrease of the raw material particle size from 30 to 5 μm, the particle size of the B(P)SCCO superconducting matrix in the prepared samples decreases, and the doping content of the Y2O3:Eu3++Ag or Y2O3:Eu3+ increases from 0.2% to 0.4%. Meanwhile, the increase of the inhomogeneous phase content enhances the ΔTC. When the particle size of raw material is 5 μm, the doping concentration of the luminescent inhomogeneous phase can be increased to 0.4%. At this time, the zero-resistance temperature and onset transition temperature of the Y2O3:Eu3++Ag doped sample are 4 and 6.3 K higher than those of pure B(P)SCCO, respectively.

An identification algorithm based on an isoparametric graded finite element model is developed to identify the material parameters of the plane structure of functionally graded materials (FGMs). The material parameter identification problem is formulated as the problem of minimizing the objective function, which is defined as a square sum of differences between measured displacement and calculated displacement by the isoparametric graded finite element approach. The minimization problem is solved by using the Levenberg-Marquardt method, in which the sensitivity calculation is based on the differentiation of the governing equations of the isoparametric graded finite element model. The validity of this algorithm is illustrated by some numerical experiments. The numerical results reveal that the proposed algorithm not only has high accuracy and stable convergence, but is also robust to the effects of measured displacement noise.