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Abstract Objective To assess the association between sleep patterns and sleep factors (sleep duration, trouble sleeping, sleep disorder) and the risk of depression in older adults. Methods A total of 5636 participants (2754 men and 2882 women) aged 60 years and older from the 2007–2014 waves of the National Health and Nutrition Examination Survey (NHANES) were included. Sleep duration, sleep problems, and sleep disorders were assessed in the home by trained interviewers using the Computer-Assisted Personal Interviewing (CAPI) system. The combined sleep behaviours were referred to as ‘sleep patterns (healthy, intermediate and poor)’, with a ‘healthy sleep pattern’ defined as sleeping 7–9 h per night with no self-reported trouble sleeping or sleep disorders. Intermediate and poor sleep patterns indicated 1 and 2–3 sleep problems, respectively. Baseline characteristics of participants analysed using one-way logistic regression. Logistic multiple linear regression was used to assess the association of sleep factors and sleep patterns with the risk of depressive symptoms.Conduct subgroup analyses to ensure robustness of findings. Results The overall prevalence of depression was 7.7% among the 5636 participants analysed, with the rate of depression in older women being 1.6 times higher than in older men. The prevalence of depression was higher in older adults with intermediate sleep pattern than in older adults with healthy sleep pattern (OR: 2.28, 95% CI: 1.71–3.03, p

Abstract Immune checkpoint blockade (ICB) has emerged as a promising therapeutic option for hepatocellular carcinoma (HCC), but resistance to ICB occurs and patient responses vary. Here, we uncover protein arginine methyltransferase 3 (PRMT3) as a driver for immunotherapy resistance in HCC. We show that PRMT3 expression is induced by ICB-activated T cells via an interferon-gamma (IFNγ)-STAT1 signaling pathway, and higher PRMT3 expression levels correlate with reduced numbers of tumor-infiltrating CD8+ T cells and poorer response to ICB. Genetic depletion or pharmacological inhibition of PRMT3 elicits an influx of T cells into tumors and reduces tumor size in HCC mouse models. Mechanistically, PRMT3 methylates HSP60 at R446 to induce HSP60 oligomerization and maintain mitochondrial homeostasis. Targeting PRMT3-dependent HSP60 methylation disrupts mitochondrial integrity and increases mitochondrial DNA (mtDNA) leakage, which results in cGAS/STING-mediated anti-tumor immunity. Lastly, blocking PRMT3 functions synergize with PD-1 blockade in HCC mouse models. Our study thus identifies PRMT3 as a potential biomarker and therapeutic target to overcome immunotherapy resistance in HCC.

Abstract Background The escalating prevalence of metabolic diseases has led to a rapid increase in non-alcoholic steatohepatitis (NASH)-related hepatocellular carcinoma (NASH-HCC). While oxaliplatin (OXA)-based hepatic arterial infusion chemotherapy (HAIC) has shown promise in advanced-stage HCC patients, its efficacy in NASH-HCC remains uncertain. This study aims to assess the effectiveness of OXA-based HAIC and elucidate the mechanisms underlying OXA resistance in NASH-HCC. Methods The key lncRNAs were screened through RNA-seq analysis of NASH/non-NASH and OXA-sensitive/OXA-resistant (OXA-S/R) HCC tissues. The biological functions of the lnc-OXAR (OXA resistance–related lncRNA in NASH-HCC) in NASH-HCC were verified through a series of in vitro and in vivo experiments. The molecular mechanism of lnc-OXAR was elucidated by fluorescence in situ hybridization, immunoprecipitation-mass spectrometry (FISH), Immunoprecipitation-Mass Spectrometry (IP-MS), RNA pulldown, RNA immunoprecipitation (RIP), methylated RNA immunoprecipitation sequencing (MeRIP-Seq) and a dual-luciferase reporter assay. Results NASH-HCC exhibited reduced responsiveness to OXA-based HAIC compared to non-NASH HCC. We identified and validated a novel transcript namedlnc-OXAR, which played a crucial role in conferring OXA resistance to NASH-HCC. Inhibition of lnc-OXAR suppressed HCC cell growth and restored OXA sensitivity both in NASH-HCC mouse models and in vitro. Mechanistically, lnc-OXAR recruited Ku70 and cystatin A (CSTA), preventing Ku70 degradation and facilitating DNA double-strand break (DSB) repair, thereby promoting OXA resistance in NASH-HCC. Additionally, WTAP-mediated m6A modification enhanced the stability of lnc-OXAR in an IGF2BP2-dependent manner. Notably, silencing lnc-OXAR significantly enhanced the response to OXA in patient-derived xenograft (PDX) models derived from NASH-HCC. Conclusions The reduced responsiveness of NASH-HCC to OXA treatment can be attributed to the upregulation of lnc-OXAR. Our findings provide a rationale for stratifying HCC patients undergoing OXA-based HAIC based on etiology. Lnc-OXAR holds promise as a novel target for overcoming OXA resistance in NASH-HCC and improving prognosis.

Abstract Amorphophallus is a perennial monocotyledonous herbaceous plant native to the southwestern region of China, widely used in various fields such as food processing, biomedicine and chemical agriculture. However, Amorphophallus is a typical thermolabile plant, and the continuous high temperature in summer have seriously affected the growth, development and economic yield of Amorphophallus in recent years. Calmodulin (CaM), a Ca2+ sensor ubiquitous in eukaryotes, is the most important multifunctional receptor protein in plant cells, which affects plant stress resistance by participating in the activities of a variety of signaling molecules. In this study, the key gene AaCaM3 for the Ca2+-CaM regulatory pathway was obtained from A. albus, the sequence analysis confirmed that it is a typical calmodulin. The qRT-PCR results demonstrated that with the passage of heat treatment time, the expression of AaCaM3 was significantly upregulated in A. albus leaves. Subcellular localization analysis revealed that AaCaM3 localized on the cytoplasm and nucleus. Meanwhile, heterologous transformation experiments have shown that AaCaM3 can significantly improve the heat tolerance of Arabidopsis under heat stress. The promoter region of AaCaM3 was sequenced 1,338 bp by FPNI-PCR and GUS staining assay showed that the promoter of AaCaM3 was a high-temperature inducible promoter. Yeast one-hybrid analysis and Luciferase activity reporting system analysis showed that the AaCaM3 promoter may interact with AaHSFA1, AaHSFA2c, AaHSP70, AaDREB2a and AaDREB2b. In conclusion, this study provides new ideas for further improving the signal transduction network of high-temperature stress in Amorphophallus.

ObjectiveOur aim was to assess the relationship between weight-adjusted waist circumference index (WWI) and the prevalence of depression in older adult hypertensive patients in the United States.MethodsWe selected individuals from the National Health and Nutrition Examination Survey (NHANES) database from 2007 to 2016 and used logistic regression analyses, subgroup analyses, and dose–response curves to assess the associations between the WWI index and the prevalence of depression in older hypertensive patients with age, sex, and BMI.ResultsA total of 4,228 participants aged ≥60 years with hypertension were included in our study; 364 patients were assessed for depression. After correction for confounders, each unit increase in WWI increased the risk of depression in older hypertensive patients by 19% (OR = 1.19, 95% CI: 0.99, 1.43). Dose–response curves showed that the WWI index was positively associated with the prevalence of depression in older hypertensive patients when the WWI index was ≥11.6. Based on subgroup analyses, this association was particularly pronounced in individuals ≥70 years of age, women, and individuals with a BMI of 25 or greater.ConclusionHigher WWI scores were positively associated with the prevalence of depression in older hypertensive patients and correlated with gender, age and BMI. This is notable, although a causal relationship cannot be established at this time.

Abstract N6-methyladenosine (m6A) is important in regulating mRNA stability, splicing, and translation, and it also contributes to tumor development. However, there is still limited understanding of the comprehensive effects of m6A modification patterns on the tumor immune microenvironment, metabolism, and drug resistance in hepatocellular carcinoma (HCC). In this study, we utilized unsupervised clustering based on the expression of 23 m6A regulators to identify m6A clusters. We identified differential m6A modification patterns and characterized m6A-gene-cluster A, which exhibited poorer survival rates, a higher abundance of Treg cells, and increased expression of TGFβ in the tumor microenvironment (TME). Additionally, m6A-gene-cluster A demonstrated higher levels of glycolysis activity, cholesterol metabolism, and fatty acid biosynthesis. We also found that the m6A score was associated with prognosis and drug resistance. Patients with a low m6A score experienced worse prognoses, which were linked to an abundance of Treg cells, upregulation of TGFβ, and increased metabolic activity. HCC patients with a higher m6A score showed improved prognosis following sorafenib treatment and immunotherapy. In conclusion, we reveals the association between m6A modification patterns and the tumor immune microenvironment, metabolism, and drug resistance in HCC. Furthermore, the m6A score holds potential as a predictive factor for the efficacy of targeted therapy and immunotherapy in HCC.

Hyperspectral video acquisition requires a precise balance between spectral and temporal resolution, often achieved through compressive sampling using two-dimensional detectors and spectral reconstruction algorithms. However, the reliance on spatial light modulators for coding reduces optical efficiency, while complex recovery algorithms hinder real-time reconstruction. To address these challenges, we propose a digital-micromirror-device-based complementary dual-channel hyperspectral (DMD-CDH) video imaging system. This system employs a DMD for simultaneous light splitting and spatial encoding, enabling one channel to perform non-aliasing spectral sampling at lower frame rates while the other provides complementary high-rate sampling for panchromatic video. Featuring high optical throughput and efficient complementary sampling, the system ensures reliable hyperspectral video reconstruction and serves as a robust ground-based validation platform for remote sensing applications. Additionally, we introduce tailored optical error calibration and fixation techniques alongside a lightweight hyperspectral fusion network for reconstruction, achieving hyperspectral frame rates exceeding 30 fps. Compared to the existing models, this system simplifies the calibration process and provides a practical high-performance solution for real-time hyperspectral video imaging.

Thermal barrier coatings (TBCs) applications of yttria-stabilized (YSZ) are widely utilized on turbine blades of aviation engines due to its low thermal conductivity and high electrical conductivity. Predicting the infrared emissivity aids in monitoring blade operating temperatures, ensuring safe engine operation. This paper innovatively introduces a novel three-dimensional columnar EB-PVD coating model and utilizes the FDTD method to predict emissivity. The model exhibits strong consistency with experimental results for predicted emissivity in the short-wave infrared band (1.4–3 μm). The unique microstructure of the EB-PVD thermal barrier coatings significantly influence the infrared emissivity. The results indicate that vertically uniform arranged feathers exhibit higher emissivity levels compared to feathers with varying densities. Additionally, increasing the thickness of the ceramic top coating and reducing spherical closed porosity also enhance the emissivity levels. This research provides guidance for controlling emissivity at the microscale in the preparation of thermal barrier coatings.

Summary: Monoacylglycerol acyltransferase-2 (MOGAT2), encodes MOGAT enzyme in the re-synthesis of triacylglycerol and protects from metabolism disorders. While, its precise involvement in colorectal cancer (CRC) progression remains inadequately understood. Our study demonstrated that knockout of Mogat2 in Apcmin/+ mice expedited intestinal tumor growth and progression, indicating that Mogat2 plays a tumor-suppressing role in CRC. Mechanically, Mogat2 deletion resulted in a significant alter the gut microbiota, while Fecal Microbiota Transplantation (FMT) experiments demonstrated that the gut microbiota in Mogat2 deleted mice promoted tumor growth. Furthermore, we identified Mogat2 as a functional regulator suppressing CRC cell proliferation and tumor growth by inhibiting the NF-κB signaling pathway in vivo. Collectively, these results provide novel insights into the protective double roles of Mogat2, inhibiting of NF-κB pathway and keeping gut microbiota homeostasis in colorectal cancer, which may help the development of novel cancer treatments for CRC.

Abstract Spectral emissivity is an essential and sensitive parameter to characterize the radiative capacity of the solid surface in scientific and engineering applications, which would be non-negligibly affected by surface morphology. However, there is a lack of assessment of the effect of roughness on emissivity and a straightforward method for estimating the emissivity of rough surfaces. This paper established an estimating method based on constructing random rough surfaces to predict rough surface (Geometric region) emissivity for metal solids. Based on this method, the emissivity of ideal gray and non-gray body surfaces was calculated and analyzed. The calculated and measured spectral emissivities of GH3044, K465, DD6, and TC4 alloys with different roughness were compared. The results show that the emissivity increases with the roughness degree, and the enhancement effect weakens with the increase of roughness or emissivity due to the existing limit (emissivity ε = 1.0). At the same time, the roughness would not change the overall spectral distribution characteristics but may attenuate the local features of the spectral emissivity. The estimated results are in good agreement with the experimental data for the above alloys’ rough surfaces. This study provides a new reliable approach to obtaining the spectral emissivity of rough surfaces. This approach is especially beneficial for measuring objects in extreme environments where emissivity is difficult to obtain. Meanwhile, this study promotes an understanding of surface morphology’s effect mechanism on emissivity.

Abstract Methytransferase-like proteins 9 (METTL9) has been characterized as an oncogene in several cancers, however, its role in hepatocellular carcinoma (HCC) remains unknown. Here, we investigated the function and molecular mechanism of METTL9 in HCC. We showed that METTL9 expression was elevated in HCC, and its high expression was associated with poor survival outcomes. Knockdown of METTL9 observed a significant inhibition of HCC cell viability, migration, and invasion both in vitro and in vivo. By contrast, METTL9 overexpression HCC cells obtained stronger abilities in cell proliferation and migration. Mechanistically, we discovered that METTL9 knockdown led to a reduction in the expression level of SLC7A11, a key suppressor of ferroptosis, in turn, promoted ferroptosis in HCC cells, impeding the progression of HCC. Moreover, we have proved that targeting METTL9 could significantly restrain the growth of HCC patient-derived xenograft (PDX). Our study established METTL9 as a critical role in promoting HCC development and provides a foundation for further investigation and potential therapeutic interventions targeting ferroptosis in HCC.

In recent years, motion recognition has become a hot research topic in the field of computer vision and has great research worth. Scholars and research institutions at home and abroad have made a lot of research and achieved good results. However, the research results of applying motion recognition technology to dance video are relatively few, mainly because the complexity of human motion in dance video is relatively high. In article, an optimized design scheme for motion recognition research of dance video based on computer vision and image processing is proposed. The collected dance video is preprocessed, including grayscale, background subtraction and filter denoising, so as to extract the character features in the video image. Then, the method of self-organizing mapping neural network (SOM) in computer vision is used to realize the recognition of dance movements. Finally, the simulation test and analysis are carried out. The simulation results show that the proposed arithmetic has a certain accuracy, which is 9.34% higher than the traditional arithmetic. The research of motion recognition method based on dance video will also play a certain reference role for the research of human motion recognition in a large number of real and complex environments, and enrich the application field of motion recognition technology.

Abstract Background Hepatocellular carcinoma (HCC) cells undergo reprogramming of glucose metabolism to support uncontrolled proliferation, of which the intrinsic mechanism still merits further investigation. Although regulatory factor X6 (RFX6) is aberrantly expressed in different cancers, its precise role in cancer development remains ambiguous. Methods Microarrays of HCC tissues were employed to investigate the expression of RFX6 in tumour and adjacent non‐neoplastic tissues. Functional assays were employed to explore the role of RFX6 in HCC development. Chromatin immunoprecipitation, untargeted metabolome profiling and sequencing were performed to identify potential downstream genes and pathways regulated by RFX6. Metabolic assays were employed to investigate the effect of RFX6 on glycolysis in HCC cells. Bioinformatics databases were used to validate the above findings. Results HCC tissues exhibited elevated expression of RFX6. High RFX6 expression represented as an independent hazard factor correlated to poor prognosis in patients with HCC. RFX6 deficiency inhibited HCC development in vitro and in vivo, while its overexpression exerted opposite functions. Mechanistically, RFX6 bound to the promoter area of phosphoglycerate mutase 1 (PGAM1) and upregulated its expression. The increased PGAM1 protein levels enhanced glycolysis and further promoted the development of HCC. Conclusions RFX6 acted as a novel driver for HCC development by promoting aerobic glycolysis, disclosing the potential of the RFX6–PGAM1 axis for therapeutic targeting.

Mg3Sb1.5Bi0.5-based Zintl compounds have attracted extensive attention as potential thermoelectric materials due to their earth-abundant elements. However, pure and intrinsic Mg3Sb1.5Bi0.5 manifests a poor thermoelectric performance because of its low electrical conductivity of about 3 × 102 S/m at room temperature. In this work, In and Se co-doping was carried out to optimize the thermoelectric performance of n-type Mg3Sb1.5Bi0.5-based material. The experimental results revealed that the carrier concentration and mobility of Mg3Sb1.5Bi0.5 significantly increased after In and Se co-doping, leading to an improvement of power factor. Simultaneously, lattice thermal conductivity was significantly reduced due to the large mass difference between In and Mg. A maximum zT of 1.64 at 723 K was obtained for the Mg3.17In0.03Sb1.5Bi0.49Se0.01 sample. And an average zT value of about 1.1 between 300 and 723 K was achieved, which insures its possible application at medium temperature range as a non-toxic and low-cost TE material.

Despite being an effective treatment for hepatocellular carcinoma (HCC), resistance to oxaliplatin presents a major obstacle. Here, the authors identify PRMT3-induced methylation of IGF2BP1 resulting in HEG1 stabilisation as a mechanism of oxaliplatin resistance in HCC.

Abstract Background Non-homologous DNA end joining (NHEJ) is the predominant DNA double-strand break (DSB) repair pathway in human. However, the relationship between NHEJ pathway and hepatocellular carcinoma (HCC) is unclear. We aimed to explore the potential prognostic role of NHEJ genes and to develop an NHEJ-based prognosis signature for HCC. Methods Two cohorts from public database were incorporated into this study. The Kaplan–Meier curve, the Least absolute shrinkage and selection operator (LASSO) regression analysis, and Cox analyses were implemented to determine the prognostic genes. A NHEJ-related risk model was created and verified by independent cohorts. We derived enriched pathways between the high- and low-risk groups using Gene Set Enrichment Analysis (GSEA). CIBERSORT and microenvironment cell populations-counter algorithm were used to perform immune infiltration analysis. XRCC6 is a core NHEJ gene and immunohistochemistry (IHC) was further performed to elucidate the prognostic impact. In vitro proliferation assays were conducted to investigate the specific effect of XRCC6. Results A novel NHEJ-related risk model was developed based on 6 NHEJ genes and patients were divided into distinct risk groups according to the risk score. The high-risk group had a poorer survival than those in the low-risk group (P < 0.001). Meanwhile, an obvious discrepancy in the landscape of the immune microenvironment also indicated that distinct immune status might be a potential determinant affecting prognosis as well as immunotherapy reactiveness. High XRCC6 expression level associates with poor outcome in HCC. Moreover, XRCC6 could promote HCC cell proliferation in vitro. Conclusions In brief, this work reveals a novel NHEJ-related risk signature for prognostic evaluation of HCC patients, which may be a potential biomarker of HCC immunotherapy.

Object detection in UAV aerial images faces domain-adaptive challenges, such as changes in shooting height, viewing angle, and weather. These changes constitute a large number of fine-grained domains that place greater demands on the network’s generalizability. To tackle these challenges, we initially decompose image features into domain-invariant and domain-specific features using practical imaging condition parameters. The composite feature can improve domain generalization and single-domain accuracy compared to the conventional fine-grained domain-detection method. Then, to solve the problem of the overfitting of high-frequency imaging condition parameters, we mixed images from different imaging conditions in a balanced sampling manner as input for the training of the detection network. The data-augmentation method improves the robustness of training and reduces the overfitting of high-frequency imaging parameters. The proposed algorithm is compared with state-of-the-art fine-grained domain detectors on the UAVDT and VisDrone datasets. The results show that it achieves an average detection precision improvement of 5.7 and 2.4, respectively. The airborne experiments validate that the algorithm achieves a 20 Hz processing performance for 720P images on an onboard computer with Nvidia Jetson Xavier NX.

Abstract The poor prognosis of hepatocellular carcinoma (HCC) could be attributed to its high metastasis rate. Here, we report the role of nucleoredoxin (NXN), a multifunctional redox-active protein, in HCC metastasis. The expression of NXN in HCC tissues was measured by immunohistochemistry. The role of NXN on HCC proliferation was determined by CCK-8, EdU and colony formation assays in vitro and subcutaneous tumor formation model in vivo. Transwell and wound healing assays and tail vein injection model were performed to assess the function of NXN on HCC metastasis. Co-immunoprecipitation assay was performed to examine the interaction among NXN, Snail and DUB3. Our results showed that NXN was downregulated in HCC tissues compared to adjacent liver tissues. Patients with low NXN expression had shorter overall survival (OS) time (P

Abstract Background With the rapid development of high-throughput sequencing technology, the cost of whole genome sequencing drops rapidly, which leads to an exponential growth of genome data. How to efficiently compress the DNA data generated by large-scale genome projects has become an important factor restricting the further development of the DNA sequencing industry. Although the compression of DNA bases has achieved significant improvement in recent years, the compression of quality score is still challenging. Results In this paper, by reinvestigating the inherent correlations between the quality score and the sequencing process, we propose a novel lossless quality score compressor based on adaptive coding order (ACO). The main objective of ACO is to traverse the quality score adaptively in the most correlative trajectory according to the sequencing process. By cooperating with the adaptive arithmetic coding and an improved in-context strategy, ACO achieves the state-of-the-art quality score compression performances with moderate complexity for the next-generation sequencing (NGS) data. Conclusions The competence enables ACO to serve as a candidate tool for quality score compression, ACO has been employed by AVS(Audio Video coding Standard Workgroup of China) and is freely available at https://github.com/Yoniming/ACO.

Abstract Aim This research explores and examines the differentiated mediation roles of multi‐foci commitment in the relationship between HPWS and knowledge exchange and combination among Chinese hospital nurses. Design This study employs a quantitative research approach and survey design. Methods Individual‐level time‐lagged data were collected from 845 nurses in public hospitals in China using online questionnaires. Aside from personal information, the items in the questionnaires were adopted from mature scales in previous research. Results The results of multiple regression analysis demonstrate that nurses’ professional and affective commitments partially mediate the relationship between HPWS and KEC. Nurses’ continuance commitment does not play a mediation role in HPWS‐KEC relationship, although HPWS positively influences nurse continuance commitment, which then weakly and positively impacts KEC.

Abstract Transarterial chemoembolization (TACE) is the major treatment for advanced hepatocellular carcinoma (HCC), but it may cause hypoxic environment, leading to rapid progression after treatment. Here, using high‐throughput sequencing on different models, S100 calcium binding protein A9 (S100A9) is identified as a key oncogene involved in post‐TACE progression. Depletion or pharmacologic inhibition of S100A9 significantly dampens the growth and metastatic ability of HCC. Mechanistically, TACE induces S100A9 via hypoxia‐inducible factor 1α (HIF1A)‐mediated pathway. S100A9 acts as a scaffold recruiting ubiquitin specific peptidase 10 and phosphoglycerate mutase family member 5 (PGAM5) to form a tripolymer, causing the deubiquitination and stabilization of PGAM5, leading to mitochondrial fission and reactive oxygen species production, thereby promoting the growth and metastasis of HCC. Higher S100A9 level in HCC tissue or in serum predicts a worse outcome for HCC patients. Collectively, this study identifies S100A9 as a key driver for post‐TACE HCC progression. Targeting S100A9 may be a promising therapeutic strategy for HCC patients.

Background and objective Anaplastic lymphoma kinase (ALK) is an important therapeutic target for advanced non-small cell lung cancer (NSCLC). In recent years, with the emergence of several ALK tyrosine kinase inhibitors (TKI), the overall survival (OS) of ALK fusion positive patients is gradually extended. This paper reports the treatment of a late stage non-small cell lung cancer (NSCLC) patient with ALK fusion positive for more than 5 years, and analyzes the treatment process and effect evaluation, so as to provide experience for the follow-up treatment of patients. Methods The diagnosis and treatment process of a patient with advanced ALK fusion mutation positive lung cancer admitted to the third ward of Department of oncology, Chifeng hospital, Inner Mongolia on July 3, 2015 was retrospectively analyzed. Results A 42 years old male patient was admitted to our department on July 3, 2015 for "intermittent cough, chest tightness for 2 months, diagnosed with lung adenocarcinoma for 1 day". Imaging examination showed a space occupying lesion in the left lower lobe of the lung, accompanied by mediastinal lymphadenopathy and left encapsulated pleural effusion. Bronchoscopic pathology showed non-small cell carcinoma, and adenocarcinoma was tentatively suggested. Diagnosis: left lower lobe adenocarcinoma T1bN2M1a stage IV. Fluorescence in situ hybridization (FISH) indicated the translocation of ALK (2p23) chromosome. After 2 cycles of docetaxel+cisplatin (DP) regimens chemotherapy, disease progression occurred, so we used 6 cycles of pemetrexed+carboplatin to apply combination chemotherapy, 4 cycles of pemetrexed monotherapy were used after that. The efficacy evaluation: PR. On April 9, 2016, the patient was treated with crizotinib. In August 2019, multiple intracranial metastases were found and whole brain radiotherapy was given. Since September 4, 2019, oral administration of nsatinib has been carried out. As of March 1, 2021, the patients were followed up well. Conclusion The advanced ALK fusion positive lung adenocarcinoma patients, though the first-line and the second-line chemotherapy, and the follwing application of ALK-TKI treatment, has procured a total OS has reached 68 months, and the current follow-up is good.

Fruit and vegetable picking robots are affected by the complex orchard environment, resulting in poor recognition and segmentation of target fruits by the vision system. The orchard environment is complex and changeable. For example, the change of light intensity will lead to the unclear surface characteristics of the target fruit; the target fruits are easy to overlap with each other and blocked by branches and leaves, which makes the shape of the fruits incomplete and difficult to accurately identify and segment one by one. Aiming at various difficulties in complex orchard environment, a two-stage instance segmentation method based on the optimized mask region convolutional neural network (mask RCNN) was proposed. The new model proposed to apply the lightweight backbone network MobileNetv3, which not only speeds up the model but also greatly improves the accuracy of the model and meets the storage resource requirements of the mobile robot. To further improve the segmentation quality of the model, the boundary patch refinement (BPR) post-processing module is added to the new model to optimize the rough mask boundaries of the model output to reduce the error pixels. The new model has a high-precision recognition rate and an efficient segmentation strategy, which improves the robustness and stability of the model. This study validates the effect of the new model using the persimmon dataset. The optimized mask RCNN achieved mean average precision (mAP) and mean average recall (mAR) of 76.3 and 81.1%, respectively, which are 3.1 and 3.7% improvement over the baseline mask RCNN, respectively. The new model is experimentally proven to bring higher accuracy and segmentation quality and can be widely deployed in smart agriculture.

ObjectiveTo conduct a large cross-sectional survey of the mental health of college students during the recovery period of the COVID-19 epidemic.MethodsSymptom Checklist 90 (SCL-90) and COVID-19 questionnaire were used to investigate the overall mental health level and cognition of epidemic situation of college students in seven colleges and universities in Shaanxi Province.Results(1) In the recovery period of COVID-19 epidemic, college students still had psychological and somatic symptoms such as obsessive-compulsive disorder, interpersonal sensitivity, anxiety, hostility, and poor appetite or insomnia; (2) female college students, science and engineering college students, freshmen and senior graduates, and some ethnic minority college students were all groups with psychological symptoms; (3) the psychological status of college students was related to their perception of COVID-19 epidemic, and the more knowledge about epidemic prevention and control, the more confident they were in overcoming the epidemic, and the milder the psychological symptoms.ConclusionCollege students still have some mental health problems in the recovery period of COVID-19 epidemic, which should be paid attention to by education authorities and colleges and universities.

Tumor mutation burden (TMB) is an important biomarker for tumor immunotherapy. It plays an important role in the clinical treatment process, but the gold standard measurement of TMB is based on whole exome sequencing (WES). WES cannot be done in most hospitals due to its high cost, long turnaround times and operational complexity. To seek out a better method to evaluate TMB, we divided the patients with lung adenocarcinoma (LUAD) in TCGA into two groups according to the TMB value, then analyzed the differences of clinical characteristics and gene expression between the two groups. We further explored the possibility of using histopathological images to predict TMB status, and developed a deep learning model to predict TMB based on histopathological images of LUAD. In the 5-fold cross-validation, the area under the receiver operating characteristic (ROC) curve (AUC) of the model was 0.64. This study showed that it is possible to use deep learning to predict genomic features from histopathological images, though the prediction accuracy was relatively low. The study opens up a new way to explore the relationship between genes and phenotypes.

Novel therapies tailored to the molecular composition mechanism of esophageal squamous cell carcinoma (ESCC) are needed to improve patient survival. miR-20b-5p expression was significantly upregulated in cancerous tissues and associated with lymph node metastasis, clinical stage, and overall survival (OS). An analysis of the methylation status of the miR-20b-5p gene indicated that the hypomethylation of the CpG sites located upstream of the miR-20b-5p gene in the ESCC tissues was more frequent than in the adjacent normal tissues, and the methylation status of miR-20b-5p correlated inversely with its expression levels. Notably, a series of gain- and loss-of-function assays elucidated that miR-20b-5p promoted ESCC cell proliferation, migration, and invasion both in vitro and in vivo. Luciferase reporter assays, western blot, and qRT-PCR revealed that RB1 and TP53INP1 were the direct targets of miR-20b-5p. Moreover, the effects of ectopic miR-20b-5p expression were abrogated by RB1 and TP53INP1 overexpression. In contrast, the effects of miR-20b-5p depletion were impaired by RB1 and TP53INP1 knockdown. Treatment with a miR-20b-5p antagomir dramatically increased tumor growth and inhibited RB1 and TP53INP1 protein expression in nude mice. This work provided novel insights on the molecular mechanism of ESCC and further provided suggestions for therapy development.

The n-type filled and doped skutterudites GaxCo4Sb12.3 and Ga0.2Co4Sb11.3Te composites with the well-distributed GaSb nanoinclusions are synthesized through the manipulating of metastable Ga fillers and enrichment of Sb by an in-situ method with a proper annealing procedure. Ga atoms can fill the icosahedron cages of skutterudite at high temperature, but at low temperature, they are driven out from the lattice voids and form the second phase of GaSb at grain boundaries. The presence of GaSb second phases reduces the thermal conductivity effectively. Te doping leads to a significant increase in carrier concentration of Ga0.2Co4Sb11.3Te, thus largely suppresses the bipolar effect of GaxCo4Sb12.3, resulting in a great enhancement in power factor. Moreover, Te doping induces mass and strain fluctuation, which decreases the lattice thermal conductivity further. Consequently, the maximum ZT is increased from 0.56 for Ga0.2Co4Sb12.3 at 573 K to 1.48 for Ga0.2Co4Sb11.3Te at 873 K, which is advantageous to improve the thermoelectric conversion efficiency for commercial application. Keywords: Thermoelectric, Skutterudite, Second phase, Bipolar effect

The rapid development of digitalization has brought disruptive changes to the economy and life. The effect of digitalization on energy efficiency is explored using a time series dataset from 2003–2019 in Zhejiang Province and is discussed in four aspects: physical foundation, participant, medium, and pathway. The ridge regression estimation results show that digitalization has a positive effect on energy efficiency. Network infrastructure, communication service development, information technology industry development, and digital technology innovation have various degrees of positive contribution to energy efficiency. This study provides valuable insights for improving energy efficiency. Enhancing the physical foundation, participant, medium, and pathway of digitalization are confirmed as ways to improve energy efficiency. This study enriches the theory of energy efficiency in the context of digitalization and has practical implications for improving regional energy efficiency in the digital era.

In order to save the time and cost of friction and wear experiments, the coating composition (different contents of Al, Ti, and Cu elements), ratio of hardness and elastic modulus (H3/E2), vacuum heat treatment (VHT) temperature, and wear form were used as input variables, and the wear rates of high-entropy alloy (HEA) coatings were used as output variables. The dataset was entirely obtained by experiment. Four machine learning algorithms (classification and regression tree (CART), random forest (RF), gradient boosting decision tree (GBDT), and adaptive boosting (AdaBoost)) were used to predict the wear resistance of HEA coatings based on a small amount of data. The results show that except for the GBDT model, the other three models had good performance. Because of the small amount of data, the CART model demonstrated the best prediction performance and can provide guidance for predicting the wear resistance of AlCoCrFeNi-X (Ti, Cu) HEA coatings for drilling equipment. Furthermore, the contribution of different factors to the wear rate of AlCoCrFeNi-X (Ti, Cu) HEA coatings was obtained. Al content had the greatest influence on wear rate, followed by H3/E2, wear form, and VHT temperature.

BackgroundAcute respiratory distress syndrome (ARDS) is a common critical respiratory illness. Hypoxia at high altitude is a factor that influences the progression of ARDS. Currently, we lack clear diagnostic criteria for high-altitude ARDS. The purpose of this study was to determine the value of the application of the Berlin Definition altitude-PaO2/FiO2-corrected criteria for ARDS in Xining, Qinghai (2,261 m).MethodsWe retrospectively analyzed the clinical data of patients with ARDS admitted to the Department of Critical Care Medicine of the Affiliated Hospital of Qinghai University from January 2018 to December 2018. The severity of ARDS was categorized according to the Berlin Definition, Berlin Definition altitude-PaO2/FiO2-corrected criteria, and the diagnostic criteria for acute lung injury (ALI)/ARDS at high altitudes in Western China (Zhang criteria). In addition, the differences between the three criteria were compared.ResultsAmong 1,221 patients, 512 were treated with mechanical ventilation. In addition, 253 met the Berlin Definition, including 49 (19.77%) with mild ARDS, 148 (58.50%) with moderate ARDS, and 56 (22.13%) with severe ARDS. A total of 229 patients met the altitude-PaO2/FiO2-corrected criteria, including 107 with mild ARDS (46.72%), 84 with moderate ARDS (36.68%), and 38 (16.59%) with severe ARDS. Intensive care unit (ICU) mortality increased with the severity of ARDS (mild, 17.76%; moderate, 21.43%; and severe, 47.37%). Twenty-eight-day mortality increased with worsening ARDS (mild 23.36% vs. moderate 44.05% vs. severe 63.16%) (p < 0.001). There were 204 patients who met the Zhang criteria, including 87 (42.65%) with acute lung injury and 117 (57.35%) with ARDS. The area under receiver operating characteristics (AUROCs) of the Berlin Definition, the altitude-P/F-corrected criteria, and the Zhang criteria were 0.6675 (95% CI 0.5866–0.7484), 0.6216 (95% CI 0.5317–0.7116), and 0.6050 (95% CI 0.5084–0.7016), respectively. There were no statistically significant differences between the three diagnostic criteria.ConclusionFor Xining, Qinghai, the altitude-PaO2/FiO2-corrected criteria for ARDS can distinguish the severity of ARDS, but these results need to be confirmed in a larger sample and in multicenter clinical studies.Clinical Trial RegistrationClinicalTrials.gov, identifier: NCT04199650.

Because of the unstructured characteristics of natural orchards, the efficient detection and segmentation applications of green fruits remain an essential challenge for intelligent agriculture. Therefore, an innovative fruit segmentation method based on deep learning, termed SE-COTR (segmentation based on coordinate transformer), is proposed to achieve accurate and real-time segmentation of green apples. The lightweight network MobileNetV2 is used as the backbone, combined with the constructed coordinate attention-based coordinate transformer module to enhance the focus on effective features. In addition, joint pyramid upsampling module is optimized for integrating multiscale features, making the model suitable for the detection and segmentation of target fruits with different sizes. Finally, in combination with the outputs of the function heads, the dynamic convolution operation is applied to predict the instance mask. In complex orchard environment with variable conditions, SE-COTR achieves a mean average precision of 61.6% with low complexity for green apple fruit segmentation at severe occlusion and different fruit scales. Especially, the segmentation accuracy for small target fruits reaches 43.3%, which is obviously better than other advanced segmentation models and realizes good recognition results. The proposed method effectively solves the problem of low accuracy and overly complex fruit segmentation models with the same color as the background and can be built in portable mobile devices to undertake accurate and efficient agricultural works in complex orchard.

This paper proposes a 16-bit 6-channel high-voltage successive approximation register (SAR) ADC with an optimized 5 + 5 + 6 segmented capacitor array. The lower 10 bits of the capacitor array are all composed of unit capacitors without any calibration unit. Without calibration, the lower 10 bits of the capacitor array can ensure 10-bit conversion accuracy. Every of the upper 6 bits of the capacitor array contains a linearity calibration unit. The linearity error of the upper 6 bits is calibrated by the linearity calibration unit. The 16-bit is manufactured by a $0.6~\mu m$ standard COMS process, and the total chip area of 6-channel ADC including pads is 6.6mm $\times6.6$ mm. As for single channel SAR ADC, the area is 0.9mm $\times2.0$ mm. The measurement results show that the effective conversion accuracy of the SAR ADC reaches 13 bits by using novel differential nonlinearity (DNL) and integral nonlinearity (INL) calibration methods. The power is 80mW, corresponding to a Figure of Merit (FOM) of 48 pJ/conv.-step.

Abstract Background N6-methyladenosine (m6A) modification is the most pervasive modification in mRNA, and has been considered as a new layer of epigenetic regulation on mRNA processing, stability and translation. Despite its functional significance in various physiological processes, the role of the m6A modification involved in breast cancer is yet fully understood. Methods We used the m6A-RNA immunoprecipitation sequencing to identify the potential targets in breast cancer. To determine the underlying mechanism for the axis of FTO-BNIP3, we performed a series of in vitro and in vivo assays in 3 breast cancer cell lines and 36 primary breast tumor tissues and 12 adjunct tissues. Results We showed that FTO, a key m6A demethylase, was up-regulated in human breast cancer. High level of FTO was significantly associated with lower survival rates in patients with breast cancer. FTO promoted breast cancer cell proliferation, colony formation and metastasis in vitro and in vivo. We identified BNIP3, a pro-apoptosis gene, as a downstream target of FTO-mediated m6A modification. Epigenetically, FTO mediated m6A demethylation in the 3’UTR of BNIP3 mRNA and induced its degradation via an YTHDF2 independent mechanism. BNIP3 acts as a tumor suppressor and is negatively correlated with FTO expression in clinical breast cancer patients. BNIP3 dramatically alleviated FTO-dependent tumor growth retardation and metastasis. Conclusions Our findings demonstrate the functional significance of the m6A modification in breast cancer, and suggest that FTO may serve as a novel potential therapeutic target for breast cancer.

The process of fusing the rich spectral information of a low spatial resolution hyperspectral image (LR-HSI) with the spatial information of a high spatial resolution multispectral image (HR-MSI) to obtain an HSI with the spatial resolution of an MSI image is called hyperspectral image fusion (HIF). To reconstruct hyperspectral images at video frame rate, we propose a lightweight multi-level information network (MINet) for multispectral and hyperspectral image fusion. Specifically, we develop a novel lightweight feature fusion model, namely residual constraint block based on global variance fine-tuning (GVF-RCB), to complete the feature extraction and fusion of hyperspectral images. Further, we define a residual activity factor to judge the learning ability of the residual module, thereby verifying the effectiveness of GVF-RCB. In addition, we use cascade cross-level fusion to embed the different spectral bands of the upsampled LR-HSI in a progressive manner to compensate for lost spectral information at different levels and to maintain spatial high frequency information at all times. Experiments on different datasets show that our MINet outperforms the state-of-the-art methods in terms of objective metrics, in particular by requiring only 30% of the running time and 20% of the number of parameters.

Breast cancer is a heterogeneous malignant disease with different prognoses and has been divided into four molecular subtypes. It is believed that molecular events occurring in breast stem/progenitor cells contribute to the carcinogenesis and development of different breast cancer subtypes. However, these subtype-specific molecular characteristics are largely unknown. In this study, we employed 1217 breast cancer samples from The Cancer Genome Atlas (TCGA) database for a multiomics analysis of the molecular characteristics of different breast cancer subtypes based on PAM50 algorithms. We detected the expression changes of subtype-specific genes and revealed that the expression of particular subtype-specific genes significantly affected prognosis. We also investigated the mutations and copy number variations (CNVs) of breast cancer driver genes and the representative genes of ten signaling pathways in different subtypes and revealed several subtype-specifically altered genes. Moreover, we detected the infiltration of various immune cells in different subtypes of breast cancer and showed that the infiltration levels of major immune cell types are different among these subtypes. Additionally, we investigated the factors affecting the immune infiltration level and the immune cytolytic activity in different breast cancer subtypes, namely, the mutation burden, genome instability and cancer-associated fibroblast (CAF) infiltration. This study may shed light on the molecular events contributing to carcinogenesis and development and provide potential markers and targets for the clinical diagnosis and treatment of different breast cancer subtypes.

Anther indehiscence is an important form of functional male sterility that can facilitate the production of hybrid seeds. However, the molecular mechanisms of anther indehiscence-based male sterility in eggplant (Solanum melongena L.) have not been thoroughly explored. We performed transcriptome sequencing and real-time quantitative reverse transcription-PCR (qRT-PCR) assays to compare the fertile line (F142) and male sterile line (S12) eggplant. We identified 2,670 differentially expressed genes (DEGs) between lines. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses identified 31 DEGs related to hormone biosynthesis. We, therefore, measured phytohormone contents, such as jasmonic acid (JA), auxin (IAA), gibberellin (GA), and abscisic acid (ABA) in S12 and F142. There were differences in IAA, GA3, and ABA levels between S12 and F142, while JA levels were significantly lower in S12 than in F142. Five key genes in the JA signaling pathway were differentially expressed in S12 vs. F142. Of these, SmJAZ1 and SmJAR1 were significantly upregulated and SmDAD1, SmLOX, and SmCOI1 were downregulated in S12 vs. F142. Protein–protein interaction studies identified a direct interaction between SmDAD1 and SmLOX, while SmDAD1 failed to interact with SmJAR1, SmCOI1, and SmJAZ1. The data represent a valuable resource for further exploration of regulatory mechanisms underlying anther dehiscence in eggplant.

Melanoma is the leading cause of cancer-related death among skin tumors, with an increasing incidence worldwide. Few studies have effectively investigated the significance of an immune-related gene (IRG) signature for melanoma prognosis. Here, we constructed an IRGs prognostic signature using bioinformatics methods and evaluated and validated its predictive capability. Then, immune cell infiltration and tumor mutation burden (TMB) landscapes associated with this signature in melanoma were analyzed comprehensively. With the 10-IRG prognostic signature, melanoma patients in the low-risk group showed better survival with distinct features of high immune cell infiltration and TMB. Importantly, melanoma patients in this subgroup were significantly responsive to MAGE-A3 in the validation cohort. This immune-related prognostic signature is thus a reliable tool to predict melanoma prognosis; as the underlying mechanism of this signature is associated with immune infiltration and mutation burden, it might reflect the benefit of immunotherapy to patients.

Multi-spectral imaging (MSI) is a novel non-invasive tool for visualizing the entire span of the eye, from the internal limiting membrane to the choroid. However, spatial misalignments can be frequently observed in sequential MSI images because the eye saccade movement is usually faster than the MSI image acquisition speed. Therefore, registering MSI images is necessary for computer-based analysis of retinal degeneration via MSI. In this paper, we propose an early deep learning framework for achieving an accurate registration of MSI images in a group-wise fashion. The framework contains three parts: a template construction based on principal component analysis, a deformation field calculation, and a spatial transformation. The framework is uniquely capable of resolving two key challenges, i.e., the “multi-modal” characteristics in MSI images for the acquisition with different spectra and the requirement of joint registration of the sequential images. Our experimental results demonstrate the superior performance of our framework compared to several representative state-of-the-art techniques in both speed and accuracy.

Exosomal microRNAs (miRNAs) have been recently shown to play vital regulatory and communication roles in cancers. In this study, we showed that the expression levels of miR-652-5p in tumour tissues and serum samples of oesophageal squamous cell carcinoma (OSCC) patients were lower compared to non-tumorous tissues and serum samples from healthy subjects, respectively. Decreased expression of miR-652-5p was correlated with TNM stages, lymph node metastasis, and short overall survival (OS). More frequent CpG sites hypermethylation in the upstream of miR-652-5p was found in OSCC tissues compared to adjacent normal tissues. Subsequently, miR-652-5p downregulation promoted the proliferation and metastasis of OSCC, and regulated cell cycle both in cells and in vivo. The dual-luciferase reporter assay confirmed that poly (ADP-ribose) glycohydrolase (PARG) and vascular endothelial growth factor A (VEGFA) were the direct targets of miR-652-5p. Moreover, the delivery of miR-652-5p agomir suppressed tumour growth and metastasis, and inhibited the protein expressions of PARG and VEGFA in nude mice. Taken together, our findings provide novel insight into the molecular mechanism underlying OSCC pathogenesis.

Abstract Background Esophageal cancer is a high incident cancer worldwide with poor survival and limited therapeutic options. Alterations of microRNAs are common in cancers, and many of these micro RNAs are potential therapeutic and diagnostic targets to treat these cancers. miR-10b-3p located in chromosome region 2q31.1, and its expression is frequently increased in esophageal squamous cell carcinoma (ESCC). However, the biological functions, clinical significance and therapeutic implications of miR-10b-3p in ESCC remain unclear. Methods The expression levels of miR-10b-3p in ESCC specimens were analyzed by in situ hybridization (ISH) and quantitative reverse transcription polymerase chain reaction (qRT-PCR) assays. Ectopic overexpression of miR-10b-3p in ESCC cells, mouse xenograft model, and metastasis model were used to evaluate the effects of miR-10b-3p on proliferation, and migration of cancer cells. Luciferase reporter assay and Western blot were performed to validate the potential targets of miR-10b-3p after the preliminary screening by computer-aided microarray analysis. Results We found that miR-10b-3p expression levels were significantly upregulated in the tumor tissues and serum samples of patients with ESCC. The expression levels of miR-10b-3p in both tumor tissues and serum samples were inversely associated with lymph node metastasis and clinical stages. We identified the expression level of miR-10b-3p in ESCC cancer samples as an independent prognostic marker of the overall survival rates of ESCC patients. We found more frequent hypomethylation of the CpG sites located upstream of the miR-10b-3p gene in the ESCC tissues compared with in the adjacent normal tissues, and the DNA methylation status of miR-10b-3p promoter region inversely correlated with the expression levels of miR-10b-3p. Ectopic overexpression of miR-10b-3p promoted cell proliferation, colony formation, migration and invasion in ESCC. While knockdown of miR-10b-3p had the opposite effects, particularly in promoting apoptosis. Mouse xenograft model confirmed that miR-10b-3p functions as a potent oncogenic miRNA in ESCC, which also promoting ESCC metastasis. Mechanistically, we found miR-10b-3p regulated FOXO3 expression by directly binding to the 3′-untranslated region. And systemic delivery of miR-10b-3p antagomir reduced tumor growth and inhibit FOXO3 protein expression in nude mice. Conclusions Collectively, our findings suggested upregulated expression of miR-10b-3p caused by promoter hypomethylation contributed to the progression of ESCC; Thus, miR-10b-3p is a potentially effective biomarker for ESCC that could have further therapeutic implications.

N6-Methyladenosine (m6A) modification is the most pervasive modification of human mRNA molecules. It is reversible via regulation of m6A modification methyltransferase, demethylase and proteins that preferentially recognize m6A modification as “writers”, “erasers” and “readers”, respectively. Altered expression levels of the m6A modification key regulators substantially affect their function, leading to significant phenotype changes in the cell and organism. Recent studies have proved that the m6A modification plays significant roles in regulation of metabolism, stem cell self-renewal, and metastasis in a variety of human cancers. In this review, we describe the potential roles of m6A modification in human cancers and summarize their underlying molecular mechanisms. Moreover, we will highlight potential therapeutic approaches by targeting the key m6A modification regulators for cancer drug development. Key words: N6-Methyladenosine, Human cancer, Pharmacological target, m6A modification regulator, Drug development

Abstract Background Non-small cell lung cancer (NSCLC) is a leading cause of death worldwide. MicroRNAs (miRNAs) have been indicated as crucial actors in cancer biology. Accumulating evidence suggests that miRNAs can be used as diagnostic and prognostic markers for NSCLC. Methods The purpose of this study was to characterize and identify the novel biomarker miR-4317 and its targets in NSCLC. The expression of miR-4317 was analyzed by in situ hybridization (ISH) and quantitative reverse transcription polymerase chain reaction (qRT-PCR). The effect of miR-4317 on proliferation was evaluated through 3–4,5-dimethylthiazol-2-yl-5-3–carboxymethoxyphenyl-2-4-sulfophenyl-2H-tetrazolium (MTS) and colony formation assays, and cell migration and invasion were evaluated through transwell assays. The expression of target proteins and downstream molecules was analyzed by qRT-PCR and western blot. Dual-luciferase reporter assay was used to assess the target genes of miR4317 in NSCLC cells. Results Our results demonstrated that miR-4317 was downregulated in NSCLC tissues and serum, particularly in lymph node metastasis and advanced clinical stage tissues. Kaplan-Meier survival analysis showed that NSCLC patients with high expression of miR-4317 exhibited better overall survival (OS). Enhanced expression of miR-4317 significantly inhibited proliferation, colony formation, migration and invasion, and hampered cycles of NSCLC cell lines in vitro. Our results suggested that miR-4317 functions by directly targeting fibroblast growth factor 9 (FGF9) and cyclin D2 (CCND2). In concordance with in vitro studies, mouse xenograft, lung, and brain metastatic studies validated that miR-4317 functions as a potent suppressor miRNA of NSCLC in vivo. Systemically delivered agomiR-4317 reduced tumor growth and inhibited FGF9 and CCND2 protein expression. Reintroduction of FGF9 and CCND2 attenuated miR-4317-mediated suppression of migration and invasion in NSCLC. Conclusions Our results indicate that miR-4317 can reduce NSCLC cell growth and metastasis by targeting FGF9 and CCND2. These findings provide new evidence of miR-4317 as a potential non-invasive biomarker and therapeutic target for NSCLC.

Abstract The fringe pattern can realize high-resolution and dense depth sensing. However, the phase ambiguity is a challenge in the fringe pattern. In this paper, one period-code pattern is embedded to the fringe pattern by the frequency-division-multiplexing (FDM) framework. The nonparametric skew and De Bruijn sequence are utilized to determine the label of the period. For a more reliable phase unwrapping, three criteria are utilized to rectify the period numbers further. Quantitative and qualitative experiments show that the proposed method can achieve more reliable depth sensing compared with the counterparts. Even the measured scene contains discontinuous surfaces or sharp edges, the proposed algorithm can attain reliable depth.

With the rise of crowdsourcing economies, the home delivery business is now undergoing rapid development. The authentication schemes that are currently used in the home delivery business remain unanalyzed from the provable authenticity perspective. In this paper, we generalize the “cross-realm authentication path”of the Kerberos protocol and apply it to the online ordering and offline delivery business. We design a Kerberos-based scheme for the crowdsourcing delivery model to establish authenticity for principals, including customers, suppliers, and deliverymen. Then we extend it to some more complex models, such as the receiving agent model, the unified service of franchised chain model, and the relay delivery model. The authentication schemes can also be incorporated into the door access and guard system to enhance the physical security in smart cities.

ObjectiveElectroencephalogram (EEG) based brain–computer interfaces (BCI) in motor imagery (MI) have developed rapidly in recent years. A reliable feature extraction method is essential because of a low signal-to-noise ratio (SNR) and time-dependent covariates of EEG signals. Because of efficient application in various fields, deep learning has been adopted in EEG signal processing and has obtained competitive results compared with the traditional methods. However, designing and training an end-to-end network to fully extract potential features from EEG signals remains a challenge in MI.ApproachIn this study, we propose a parallel multiscale filter bank convolutional neural network (MSFBCNN) for MI classification. We introduce a layered end-to-end network structure, in which a feature-extraction network is used to extract temporal and spatial features. To enhance the transfer learning ability, we propose a network initialization and fine-tuning strategy to train an individual model for inter-subject classification on small datasets. We compare our MSFBCNN with the state-of-the-art approaches on open datasets.ResultsThe proposed method has a higher accuracy than the baselines in intra-subject classification. In addition, the transfer learning experiments indicate that our network can build an individual model and obtain acceptable results in inter-subject classification. The results suggest that the proposed network has superior performance, robustness, and transfer learning ability.

The space application task is to carry out various scientific experiments and applied research by using the ability of space experiment of spacecraft. In the past 20 years, >50 space application studies have been carried out in Chinese manned space flight application system, >500 units have been involved in the previous flight missions, and fruitful results have been achieved. The white paper ‘Chinese spaceflight in 2016’ pointed out that in the next 5 years, Chinese satellite system will enhance the level and basic ability to construct the satellite system. Chinese manned space station project is scheduled to be completed ∼2022 and it will plan to operate >10 years. The space station, based on the world-wide integrated information network, has a large number of payloads and will become a national space laboratory. Space activities are full of risks and challenges. On the basis of a great deal of literatures, the method of avoiding space risk in the field of spaceflight is discussed. Aiming at the fault diagnosis task for space utilisation, the intelligent methods of deep learning including deep belief network, convolutional neural network and generative adversarial network are discussed.

In an electrical safe microenvironment, all kinds of electrical appliances can be operated safely to ensure the safety of life and property. The significance of safety hazard factors detection is to detect safety hazards in advance, to remind the administrators to exclude risk, to reduce the unnecessary loss, and to ensure that the electrical operation is healthy and orderly before the occurrence of accidents. In this paper, batteries are selected as the primary research subject of safety detection because batteries are used more and more in the Internet of Things (IOT), and they often cause fire in the process of discharging and charging. The existing algorithms need to be embedded into the specialized sensor for each important electrical appliance. However, they are limited by the actual deployment, so it is extremely difficult to spread widely. According to the opinions above, an improved load disaggregation algorithm based on dictionary learning and sparse coding with optimal dictionary matrix period is proposed to detect potential safety hazards of battery loads. For safety-related electrical applications, doing so can increase interpretability. Through experiments, we test this algorithm on the REDD dataset, and compare it with the baseline algorithms (combinatorial optimization, factorial hidden Markov model, basic discriminative dictionary sparse coding algorithm) to achieve a degree of trust. The Mean Absolute Error (MAE) value is 8.26, which drops by 70%. The Root Mean Square Error (RMSE) value is 97.75, which is also better than those baseline algorithms.

In this study, the feasibility of using Lamb waves in functionally graded (FG) nano copper layered wafers in nondestructive evaluation is evaluated. The elastic parameters and mass densities of these wafers vary with thickness due to the variation in grain size. The power series technique is used to solve the governing equations with variable coefficients. To analyze multilayered structures, of which the material parameters are continuous but underivable, a modified transfer matrix method is proposed and combined with the power series method. Results show that multiple modes of Lamb waves exist in FG nano copper wafers. Moreover, the gradient property leads to a decrease in phase velocity, and the absolute value of the phase velocity variation is positively correlated with the gradient coefficient. The phase velocity variation and variation rate in Mode 2 are smaller than those in other modes. The findings indicate that Mode 4 is recommended for nondestructive evaluation. However, if the number of layers is greater than four, the dispersion curves of the Lamb waves in the multilayer structures tend to coincide with those in the equivalent uniform structures. The results of this study provide theoretical guidance for the nondestructive evaluation of FG nanomaterial layered structures.

Electrification of transportation has drawn increasing attention for the sake of low-pollution emission and high-fuel economy. Scientific scale forecasting of electric vehicles (EVs) is fundamental to promote EVs' integration for transportation and electric power industries. To capture the evolution pattern, a system dynamics (SD) approach is proposed to simulate and forecast the scale of the EVs. The proposed SD model can integrate various factors and quantify their relationship by comprehensive reasoning. Causal loop diagrams are designed to describe the relationship between factors and variables, and their quantifications are formulated by different business models and surveys. The main procedure for simulation includes survey, problem analysis, variable definition, feedback analysis, and model building. The effectiveness of the SD approach is verified by case studies. Furthermore, sensitivity analysis of the key factors, such as fuel price, subsidy policy, and so on, is also conducted.

In the original publication of this manuscript [1], Fig. 6 contains a repeated image in error (the left image of ‘Migration’ and the left image of ‘Invasion’).