Search

Abstract The inverse kinematics problem of exoskeleton rehabilitation robots is challenging due to the lack of a standard analytical model, resulting in a complex and varied solution process. This complexity is especially pronounced in redundant upper limb exoskeleton robots, where inefficient solutions hinder the robot’s ability to adapt to the kinematic shape of the upper limb. This paper proposes a modeling and solution method based on multi-objective optimization to address the inverse kinematics of upper limb exoskeleton robots. We analyzed and validated this method using a redundant upper limb exoskeleton rehabilitation robot system developed by ourselves. First, we established a multi-objective inverse kinematics solution model by defining the end-position function, joint motion comfort function, system energy consumption function, motion safety, and human-like constraints. Then, the solution was designed based on the Improved Equilibrium Optimization (IEO) algorithm and validated its computational performance in terms of optimization ability, accuracy, and robustness. Finally, we experimentally tested the inverse kinematics solution model with the IEO algorithm on discrete objectives and continuous training trajectories using a redundant upper limb exoskeleton rehabilitation robot system. The results show that by incorporating the joint comfort function, system energy consumption function, and human-like constraints into the inverse kinematics model, we can not only quickly solve the inverse kinematics of redundant upper limb exoskeleton robots but also significantly improve the robot’s motion shape. Furthermore, it has better solution accuracy and stronger robustness than other algorithms when solving this inverse kinematics model based on the IEO algorithm.

Abstract Periodontitis is a chronic inflammatory disease involving plaque biofilm as a pathogenic factor. Potassium ion plays an important role in cellular homeostasis; a large outflow of potassium may lead to local inflammation progression. In this work, the multifunctional short peptide molecule BmKTX-33 was designed by modifying the BmKTX, a Kv1.3 potassium channel inhibitor. This was to explore its antibacterial properties, capability of maintaining cell ion homeostasis, and bone-forming capacity. The results showed that BmKTX-33 had inhibitory effects on S. gordonii, F. nucleatum, and P. gingivalis. Moreover, BmKTX-33 also inhibited excessive potassium outflow in inflammatory environments. Finally, BmKTX-33 promoted MC3T3-E1 early osteogenesis while suppressing the NLRP3 inflammasome's production. In conclusion, BmKTX-33 not only has antibacterial properties, but also can inhibit the expression of NLRP3 inflammasome and play an anti-inflammatory role.

Abstract Glomus tumor (GT) is a neoplastic lesion of mesenchymal origin arising from the neuromyoarterial canal or glomus body. Although most GT occur in the peripheral soft tissue and extremities, these tumors can grow anywhere in the body. Here, we describe an uncommon case of GT involving the prostate.

Abstract Fault fracture zones are rock formations commonly encountered in submarine tunnels, and the diffusion mechanism of slurry in fault fracture zones has a crucial impact on submarine tunnel reinforcement. Based on the seepage equation of Bingham fluid, the tortuosity parameter, fractal theory, and variable viscosity equation are introduced to establish a spherical permeation grouting model of Bingham fluid considering the slurry diffusion path and viscosity time variability. The viscosity variation law with time of sulfur aluminate cement slurry under different seawater admixture conditions was tested, and the time-varying equation of viscosity of sulfur aluminate cement slurry was obtained by fitting. A set of fault fracture zone permeation grouting test system was developed, and a fault fracture zone grouting simulation test was carried out. The study shows that the diffusion distance calculated without considering the influence of slurry diffusion path and seawater is 1.63–1.91 times of the test value, which obviously overestimates the diffusion distance; the diffusion distance calculated with considering the influence of diffusion path and seawater is 1.06–1.35 times of the test value, which is in good agreement with the test value. The research results can provide some theoretical support for the design of grouting in seawater environment.

Abstract Purpose To investigate the value of multi-parametric MRI-based radiomics for preoperative prediction of lung metastases from soft tissue sarcoma (STS). Methods In total, 122 patients with clinicopathologically confirmed STS who underwent pretreatment T1-weighted contrast-enhanced (T1-CE) and T2-weighted fat-suppressed (T2FS) MRI scans were enrolled between Jul. 2017 and Mar. 2021. Radiomics signatures were established by calculating and selecting radiomics features from the two sequences. Clinical independent predictors were evaluated by statistical analysis. The radiomics nomogram was constructed from margin and radiomics features by multivariable logistic regression. Finally, the study used receiver operating characteristic (ROC) and calibration curves to evaluate performance of radiomics models. Decision curve analyses (DCA) were performed to evaluate clinical usefulness of the models. Results The margin was considered as an independent predictor (p

Abstract Studies have indicated that RAB17 expression levels are associated with tumor malignancy, and RAB17 is more highly expressed in endometrial cancer (EC) tissues than in peritumoral tissues. However, the roles and potential mechanisms of RAB17 in EC remain undefined. The present study confirmed that the expression of RAB17 facilitates EC progression by suppressing cellular ferroptosis-like alterations. Mechanistically, RAB17 attenuated ferroptosis in EC cells by inhibiting transferrin receptor (TFRC) protein expression in a ubiquitin proteasome-dependent manner. Because EC is a blood-deprived tumor with a poor energy supply, the relationship between RAB17 and hypoglycemia was investigated. RAB17 expression was increased in EC cells incubated in low-glucose medium. Moreover, low-glucose medium limited EC cell ferroptosis and promoted EC progression through the RAB17-TFRC axis. The in vitro results were corroborated by in vivo studies and clinical data. Overall, the present study revealed that increased RAB17 promotes the survival of EC cells during glucose deprivation by inhibiting the onset of TFRC-dependent ferroptosis.

Abstract Pulmonary Fibrosis (PF) is a fatal disease in the interstitial lung associated with high mortality, morbidity, and poor prognosis. Transforming growth factor-β1 (TGF-β1) is a fibroblast-activating protein that promotes fibrous diseases. Herein, an inhalable system was first developed using milk exosomes (M-Exos) encapsulating siRNA against TGF-β1 (MsiTGF-β1), and their therapeutic potential for bleomycin (BLM)-induced PF was investigated. M-siTGF-β1 was introduced into the lungs of mice with PF through nebulization. The collagen penetration effect and lysosomal escape ability were verified in vitro. Inhaled MsiTGF-β1 notably alleviated inflammatory infiltration, attenuated extracellular matrix (ECM) deposition, and increased the survival rate of PF mice by 4.7-fold. M-siTGF-β1 protected lung tissue from BLM toxicity by efficiently delivering specific siRNA to the lungs, leading to TGF-β1 mRNA silencing and epithelial mesenchymal transition pathway inhibition. Therefore, M-siTGF-β1 offers a promising avenue for therapeutic intervention in fibrosis-related disorders.

Abstract Background Ovarian cancer (OC) has the highest fatality rate among all gynecological malignancies, necessitating the exploration of novel, efficient, and low-toxicity therapeutic strategies. Ferroptosis is a type of programmed cell death induced by iron-dependent lipid peroxidation and can potentially activate antitumor immunity. Developing highly effective ferroptosis inducers may improve OC prognosis. Results In this study, we developed an ultrasonically controllable two-dimensional (2D) piezoelectric nanoagonist (Bi2MoO6-MXene) to induce ferroptosis. A Schottky heterojunction between Bi2MoO6 (BMO) and MXene reduced the bandgap width by 0.44 eV, increased the carrier-separation efficiency, and decreased the recombination rate of electron–hole pairs under ultrasound stimulation. Therefore, the reactive oxygen species yield was enhanced. Under spatiotemporal ultrasound excitation, BMO-MXene effectively inhibited OC proliferation by more than 90%, induced lipid peroxidation, decreased mitochondrial-membrane potential, and inactivated the glutathione peroxidase and cystathionine transporter protein system, thereby causing ferroptosis in tumor cells. Ferroptosis in OC cells further activated immunogenic cell death, facilitating dendritic cell maturation and stimulating antitumor immunity. Conclusion We have succeeded in developing a highly potent ferroptosis inducer (BMO-MXene), capable of inhibiting OC progression through the sonodynamic-ferroptosis-immunogenic cell death pathway. Graphical Abstract

Abstract The diagnostic value of contrast-enhanced ultrasound combined with ultrasound elastography for benign and malignant thyroid nodules is still controversial, so we used meta-analysis to seek controversial answers. The PubMed, OVID, and CNKI databases were searched according to the inclusion and exclusion criteria. The literature was selected from the establishment of each database to February 2024. The QUADAS-2 tool assessed diagnostic test accuracy. SROC curves and Spearman's correlation coefficient were made by Review Manager 5.4 software to assess the presence of threshold effects in the literature. Meta-Disc1.4 software was used for Cochrane-Q and χ 2 tests, which be used to evaluate heterogeneity, with P-values and I 2 indicating heterogeneity levels. The appropriate effect model was selected based on the results of the heterogeneity test. Stata18.0 software was used to evaluate publication bias. The diagnostic accuracy of contrast-enhanced ultrasound combined with ultrasound elastography for benign and malignant thyroid nodules was evaluated by calculating the combined sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, DOR, and area under the SROC curve. A total of 31 studies included 3811 patients with 4718 nodules were analyzed. There is no heterogeneity caused by the threshold effect, but there is significant non-threshold heterogeneity. Combined diagnostic metrics were: sensitivity = 0.93, specificity = 0.91, DOR = 168.41, positive likelihood ratio = 10.60, and negative likelihood ratio = 0.07. The SROC curve area was 0.97. Contrast-enhanced ultrasound and elastography show high diagnostic accuracy for thyroid nodules, offering a solid foundation for early diagnosis and treatment. Trial registration. CRD42024509462.

Abstract Artificial ears with intelligence, which can sensitively detect sound—a variant of pressure—and generate consciousness and logical decision‐making abilities, hold great promise to transform life. However, despite the emerging flexible sensors for sound detection, most success is limited to very simple phonemes, such as a couple of letters or words, probably due to the lack of device sensitivity and capability. Herein, the construction of ultrasensitive artificial eardrums enabling intelligent song recognition is reported. This strategy employs novel geometric engineering of sensing units in the soft microstructure array (to significantly reduce effective modulus) along with complex song recognition exploration leveraging machine learning algorithms. Unprecedented pressure sensitivity (6.9 × 103 kPa−1) is demonstrated in a sensor with a hollow pyramid architecture with porous slants. The integrated device exhibits unparalleled (exceeding by 1–2 orders of magnitude compared with reported benchmark samples) sound detection sensitivity, and can accurately identify 100% (for training set) and 97.7% (for test set) of a database of the segments from 77 songs varying in language, style, and singer. Overall, the results highlight the outstanding performance of the hollow‐microstructure‐based sensor, indicating its potential applications in human–machine interaction and wearable acoustical technologies.

Health is important to human capital and national sustainable development. Based on the latest Chinese Family Panel Studies (CFPS), this paper uses the IVprobit model to test the impact of import trade liberalization on residents’ health from the micro-individual perspective and further explores its mechanism. The results indicate that import trade liberalization brings hidden health costs, and that the negative effects on the health of people in eastern China or rural areas, people with a low education background, people under 60 years of age, and women are more significant. In areas with more serious environmental pollution, the health deterioration effect of expanding imports is more obvious. Increasing green coverage and optimizing the quality of public services can effectively alleviate this negative impact. Import trade liberalization does not affect residents’ health through income gap, therefore when carrying out import trade liberalization the government should pay greater attention to the health status of the specified groups, adopt various means to improve the ecological and living environments, reduce pollution emissions, optimize the supply of public services, and ultimately improve residents’ overall health level.

The role of mitochondria in the pathogenesis of osteoarthritis (OA) is significant. In this study, we aimed to identify diagnostic signature genes associated with OA from a set of mitochondria-related genes (MRGs). First, the gene expression profiles of OA cartilage GSE114007 and GSE57218 were obtained from the Gene Expression Omnibus. And the limma method was used to detect differentially expressed genes (DEGs). Second, the biological functions of the DEGs in OA were investigated using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Wayne plots were employed to visualize the differentially expressed mitochondrial genes (MDEGs) in OA. Subsequently, the LASSO and SVM-RFE algorithms were employed to elucidate potential OA signature genes within the set of MDEGs. As a result, GRPEL and MTFP1 were identified as signature genes. Notably, GRPEL1 exhibited low expression levels in OA samples from both experimental and test group datasets, demonstrating high diagnostic efficacy. Furthermore, RT-qPCR analysis confirmed the reduced expression of Grpel1 in an in vitro OA model. Lastly, ssGSEA analysis revealed alterations in the infiltration abundance of several immune cells in OA cartilage tissue, which exhibited correlation with GRPEL1 expression. Altogether, this study has revealed that GRPEL1 functions as a novel and significant diagnostic indicator for OA by employing two machine learning methodologies. Furthermore, these findings provide fresh perspectives on potential targeted therapeutic interventions in the future.

Abstract Although long-read sequencing enables the generation of complete genomes for unculturable microbes, its high cost limits the widespread adoption of long-read sequencing in large-scale metagenomic studies. An alternative method is to assemble short-reads with long-range connectivity, which can be a cost-effective way to generate high-quality microbial genomes. Here, we develop Pangaea, a bioinformatic approach designed to enhance metagenome assembly using short-reads with long-range connectivity. Pangaea leverages connectivity derived from physical barcodes of linked-reads or virtual barcodes by aligning short-reads to long-reads. Pangaea utilizes a deep learning-based read binning algorithm to assemble co-barcoded reads exhibiting similar sequence contexts and abundances, thereby improving the assembly of high- and medium-abundance microbial genomes. Pangaea also leverages a multi-thresholding algorithm strategy to refine assembly for low-abundance microbes. We benchmark Pangaea on linked-reads and a combination of short- and long-reads from simulation data, mock communities and human gut metagenomes. Pangaea achieves significantly higher contig continuity as well as more near-complete metagenome-assembled genomes (NCMAGs) than the existing assemblers. Pangaea also generates three complete and circular NCMAGs on the human gut microbiomes.

Abstract Electrochemical hydrogenation of acetonitrile based on well-developed proton exchange membrane electrolyzers holds great promise for practical production of ethylamine. However, the local acidic condition of proton exchange membrane results in severe competitive proton reduction reaction and poor selection toward acetonitrile hydrogenation. Herein, we conduct a systematic study to screen various metallic catalysts and discover Pd/C exhibits a 43.8% ethylamine Faradaic efficiency at the current density of 200 mA cm−2 with a specific production rate of 2912.5 mmol g−1 h−1, which is about an order of magnitude higher than the other screened metal catalysts. Operando characterizations indicate the in-situ formed PdHx is the active centers for catalytic reaction and the adsorption strength of the *MeCH2NH2 intermediate dictates the catalytic selectivity. More importantly, the theoretical analysis reveals a classic d-band mediated volcano curve to describe the relation between the electronic structures of catalysts and activity, which could provide valuable insights for designing more effective catalysts for electrochemical hydrogenation reactions and beyond.

Abstract Typically, user behaviour occurs continuously, and considering this dynamic sequence correlation can lead to more accurate recommendations. Sequential recommendation systems have, therefore, become an important means of solving the problem of network information overload. However, existing attention mechanisms are still insufficient for modelling users’ dynamic and diverse preferences. This paper presents a recommendation model based on a multiheaded self-attention mechanism and multitemporal embeddings of long- and short-term interests (MSMT-LSI). MSMT-LSI balances users’ long- and short-term benefits through two multihead self-attention networks and finally forms a hybrid representation for recommendation. After finding the most suitable parameter combinations for the MSMT-LSI model through parameter sensitivity analysis and verifying the advantages of the long- and short-term fusion strategy, related experiments on five well-known datasets and their analysis shows that the performance of MSMT-LSI is better than that of the classical model on the same benchmark dataset.

Abstract Background The evasion of the immune response by tumor cells through programmed death-ligand 1 (PD-L1) has been identified as a factor contributing to resistance to radioimmunotherapy in lung cancer patients. However, the precise molecular mechanisms underlying the regulation of PD-L1 remain incompletely understood. This study aimed to investigate the role of cyclin-dependent kinase-like 1 (CDKL1) in the modulation of PD-L1 expression and the response to radioimmunotherapy in lung cancer. Methods The tumorigenic roles of CDKL1 were assessed via cell growth, colony formation, and EdU assays and an in vivo nude mouse xenograft model. The in vitro radiosensitization effect of CDKL1 was evaluated using a neutral comet assay, γH2AX foci formation analysis, and a clonogenic cell survival assay. The protein‒protein interactions were confirmed via coimmunoprecipitation and GST pulldown assays. The regulation of PD-L1 by CDKL1 was evaluated via chromatin immunoprecipitation (ChIP), real-time quantitative PCR, and flow cytometry analysis. An in vitro conditioned culture model and an in vivo C57BL/6J mouse xenograft model were developed to detect the activation markers of CD8+ T cells and evaluate the efficacy of CDKL1 overexpression combined with radiotherapy (RT) and an anti-PD-L1 antibody in treating lung cancer. Results CDKL1 was downregulated and suppressed the growth and proliferation of lung cancer cells and increased radiosensitivity in vitro and in vivo. Mechanistically, CDKL1 interacted with the transcription factor YBX1 and decreased the binding affinity of YBX1 for the PD-L1 gene promoter, which consequently inhibits the expression of PD-L1, ultimately leading to the activation of CD8+ T cells and the inhibition of immune evasion in lung cancer. Moreover, the combination of CDKL1 overexpression, RT, and anti-PD-L1 antibody therapy exhibited the most potent antitumor efficacy against lung cancer. Conclusions Our findings demonstrate that CDKL1 plays a crucial role in regulating PD-L1 expression, thereby enhancing the antitumor effects of radioimmunotherapy. These results suggest that CDKL1 may be a promising therapeutic target for the treatment of lung cancer.

Abstract Histone lactylation has been reported to involve in tumorigenesis and development. However, its biological regulatory mechanism in endometrial carcinoma (EC) is yet to be reported in detail. In the present study, we evaluated the modification levels of global lactylation in EC tissues by immunohistochemistry and western blot, and it was elevated. The non-metabolizable glucose analog 2-deoxy-d-glucose (2-DG) and oxamate treatment could decrease the level of lactylation so as to inhibit the proliferation and migration ability, induce apoptosis significantly, and arrest the cell cycle of EC cells. Mechanically, histone lactylation stimulated USP39 expression to promote tumor progression. Moreover, USP39 activated PI3K/AKT/HIF-1α signaling pathway via interacting with and stabilizing PGK1 to stimulate glycolysis. The results of present study suggest that histone lactylation plays an important role in the progression of EC by promoting the malignant biological behavior of EC cells, thus providing insights into potential therapeutic strategies for endometrial cancer.

Abstract Heterogeneous cancer-associated fibroblasts (CAFs) play important roles in cancer progression. However, the specific biological functions and regulatory mechanisms involved in endometrial cancer have yet to be elucidated. We aimed to explore the potential mechanisms of heterogeneous CAFs in promoting endometrial cancer progression. The presence of melanoma cell adhesion molecule (MCAM; CD146) positive CAFs was confirmed by tissue multi-immunofluorescence (mIF), and fluorescence activated cell sorting (FACS). The biological functions were determined by wound healing assays, tuber formation assays and cord formation assays. The effects of CD146+CAFs on endometrial cancer cells were studied in vitro and in vivo. The expression level of interleukin 10 (IL-10) was measured by quantitative real time polymerase chain reaction (qRT-PCR), western boltting and enzyme linked immunosorbent assays (ELISAs). In addition, the transcription factor STAT3 was identified by bioinformatics methods and chromatin immunoprecipitation (ChIP). A subtype of CAFs marked with CD146 was found in endometrial cancer and correlated with poor prognosis. CD146+CAFs promoted angiogenesis and vasculogenic mimicry (VM) in vitro. A xenograft tumour model also showed that CD146+CAFs can facilitate tumour progression. The expression of IL-10 was elevated in CD146+CAFs. IL-10 promoted epithelial-endothelial transformation (EET) and further VM formation in endometrial cancer cells via the janus kinase 1/signal transducer and activator of transcription 3 (JAK1/STAT3) signalling pathway. This process could be blocked by the JAK1/STAT3 inhibitor niclosamide. Mechanically, STAT3 can bind to the promoter of cadherin5 (CDH5) to promote its transcription which may be stimulated by IL-10. We concluded that CD146+CAFs could promote angiogenesis and VM formation via the IL-10/JAK1/STAT3 signalling pathway. These findings may lead to the identification of potential targets for antiangiogenic therapeutic strategies for endometrial cancers.

Background Short tandem repeat (STR) markers are widely used in forensic DNA analysis due to their ability to provide automated and standardised typing. However, incorrect STR typing can have a significant impact on forensic outcomes.Aim In this study, we detected drop-out alleles at the SE33 locus in a putative father-son pair using the Microreader™ 28 A ID System. This result could lead to a false conclusion of non-paternity.Subjects and methods To investigate the cause of the drop-out alleles, we developed a nest and touch-down PCR program for Sanger sequencing of the SE33 locus. Subsequently, we investigated the mutation frequency in 300 unrelated individuals and reviewed the results of 429 paternity tests.Results The results showed that the frequency of the G > T mutation at this locus was less than 0.01, which is a novel and rare mutation. Our analysis revealed a novel G > T mutation in the primer-binding region of both samples, which was a rare single-nucleotide mutation site in the Chinese population. This variation was found to be responsible for the drop-out alleles observed in the samples.Conclusion Our findings have important implications for optimising primer design and constructing DNA databases for forensic analysis.

Nephroblastoma, an overexpressed gene (NOV) protein, plays an important role in proliferation, differentiation, angiogenesis, adhesion, invasion and tumorigenesis, but the function of amino-truncated NOV is different. This study is to investigate the role of amino-truncated NOV in the progression of bladder cancer. Using immunohistochemistry and Western blot analysis, we detected the amino-truncated NOV in bladder cancer, and statistical analysis was performed to estimate the association between the expression of amino-truncated NOV and the patient’s prognosis by SPSS 19.0. With transduction of amino-truncated NOV, we evaluated alteration for proliferation, migration, invasion and chemoresistance in bladder cancer cells, as well as some proteins related to Wnt/β-catenin pathway and epithelial–mesenchymal transition. The truncated variant of the NOV protein was located in a nucleus other than the cytoplasm and highly expressed in bladder cancer, which was also linked to higher pathological grade and positive lymph node metastasis as well as recurrence. The exact sequence of this truncated protein was confirmed, and it was a 26-kDa splicing. The truncated NOV protein found in bladder cancer was cut at the 187th amino acid of the full-length protein. It was also involved in bladder cancer progression and chemoresistance through a mechanism involving epithelial–mesenchymal transition (EMT) and the Wnt/β-catenin signaling pathway. Our findings provide experimental evidence that the nuclear NOV protein expression is a potential biomarker in the prognostic evaluation of bladder cancer and enhanced amino-truncated NOV expression is potentially important for bladder cancer cell invasion, metastasis and chemoresistance during progression.

Background: Butein, a natural chalcone found in plants, exhibits promising anti-tumor effects across cancers, yet its role in Colorectal cancer (CRC) remain largely unclear. Methods: We utilized pharmacological, molecular, and in vivo models to assess its impact on CRC cell proliferation, apoptosis, migration, and invasion. Molecular docking and network pharmacology analyses predicted potential target proteins and pathways regulated by Butein. Experimental validations included western blotting, immunohistochemistry, and functional assays. Results: Butein significantly inhibited CRC cell proliferation, induced apoptosis, and disrupted the epithelial-mesenchymal transition (EMT). Its repression of cell migration and invasion capabilities, suggesting potential anti-metastatic properties. The activation of the p38 signaling pathway emerged as a key mechanism mediating Butein’s anti-tumor effects, supported by network pharmacology predictions and experimental evidence. Conclusion: This study highlights the multifaceted anti-cancer potential of Butein in CRC, emphasizing its promising application and the novel role of the p38 pathway.

Real time recognition and detection of tomato fruit maturity is a key function of tomato picking robots. Existing recognition and detection algorithms have slow speed and low recognition accuracy for small tomatoes. Here, a tomato fruit maturity detection model YOLOv5s3 based on improved YOLOv5s was proposed and its accuracy was verified through comparative experiments. On the basis of YOLOv5s, an SC module was proposed based on channel shuffle packet convolution. Then, A C3S module is constructed, which replaced the original C3 module with this C3S module to reduce the number of parameters while maintaining the feature expression ability of the original network. And a 3-feature fusion FF module was put forward, which accepted inputs from three feature layers. The FF module fused two feature maps from the backbone network. The C2 layer of the backbone was integrated, and the large target detection head was removed to use dual head detection to enhance the detection ability of small targets. The experimental results showed that the improved model has a detection accuracy of 94.8%, a recall rate of 96%, a parameter quantity of 3.02M, and an average accuracy (mAP0.5) of 93.3% for an intersection over union (IoU) of 0.5. The detection speed reaches 9.4ms. It can quickly and accurately identify the maturity of tomato fruits, and the detection speed is 22.95%, 33.33%, 48.91%, 68.35%, 15%, and 25.98% higher than the original YOLOv5s, YOLOv5m, YOLOv5l, YOLOv5x, YOLOv5n, and YOLOv4, respectively. The real-time testing visualization results of different models indicated that the improved model can effectively improve detection speed and solve the problem of low recognition rate for small tomatoes, which can provide reference for the development of picking robots.

Irrigation and fertilization are the main measures used by farmers to maintain crop yield and quality, especially in arid and semi-arid regions. To investigate the compensation of cotton yield loss due to deficit drip irrigation in non-mulched fields by increasing nitrogen (N) fertilizer application, a split-plot experiment with irrigation amount as the main plot and N application as the subplot was carried out in southern Xinjiang, China. The experiment included two irrigation amounts of 450 mm (deficit irrigation, W1) and 540 mm (full irrigation, W2) and three N application rates of 150 kg ha−1 (F1), 225 kg ha−1 (F2), and 300 kg ha−1 (F3). From the cotton seedling stage, ET0 (reference evapotranspiration) was calculated from daily meteorological data and irrigation was applied when the cumulative ET0-P reached 45 ± 3 mm. The results showed that irrigation and fertilization significantly affected soil moisture and total N, which in turn affected cotton growth, biomass formation, and yield (P

Medullary thyroid carcinoma (MTC) accounts for only 3% of all thyroid carcinomas: 75% as sporadic MTC (sMTC) and 25% as hereditary MTC (hMTC) in the context of multiple endocrine neoplasia type 2 (MEN2). Early diagnosis is possible by determining the tumour marker calcitonin (Ctn) when clarifying nodular goitre and by detecting the mutation in the proto-oncogene RET in the MEN2 families. If the Ctn level is only slightly elevated, up to 30 pg/ml in women and up to 60 pg/ml in men, follow-up checks are advisable. At higher levels, surgery should be considered; at a level of > 100 pg/ml, surgery is always advisable. The treatment of choice is total thyroidectomy, possibly with central lymphadenectomy. In the early stage, cure is possible with adequate surgery; in the late stage, treatment with tyrosine kinase inhibitors is an option. RET A mutation analysis should be performed on all patients with MTC. During follow-up, a biochemical distinction is made between: healed (Ctn not measurably low), biochemically incomplete (Ctn increased without tumour detection) and structural tumour detection (metastases on imaging). After MTC surgery, the following results should be available for classification in follow-up care: (i) histology, Ctn immunohistology if necessary, (ii) classification according to the pTNM scheme, (iii) the result of the RET analysis for categorisation into the hereditary or sporadic variant and (iiii) the postoperative Ctn value. Tumour progression is determined by assessing the Ctn doubling time and the RECIST criteria on imaging. In most cases, “active surveillance” is possible. In the case of progression and symptoms, the following applies: local (palliative surgery, radiotherapy) before systemic (tyrosine kinase inhibitors).

Abstract Electrochemical carbon dioxide reduction reaction using sustainable energy is a promising approach of synthesizing chemicals and fuels, yet is highly energy intensive. The oxygen evolution reaction is particularly problematic, which is kinetically sluggish and causes anodic carbon loss. In this context, we couple CO2 electrolysis with hydrogen oxidation reaction in a single electrochemical cell. A Ni(OH)2/NiOOH mediator is used to fully suppress the anodic carbon loss and hydrogen oxidation catalyst poisoning by migrated reaction products. This cell is highly flexible in producing either gaseous (CO) or soluble (formate) products with high selectivity (up to 95.3%) and stability (>100 h) at voltages below 0.9 V (50 mA cm−2). Importantly, thanks to the “transferred” oxygen evolution reaction to a water electrolyzer with thermodynamically and kinetically favored reaction conditions, the total polarization loss and energy consumption of our H2-integrated CO2 reduction reaction, including those for hydrogen generation, are reduced up to 22% and 42%, respectively. This work demonstrates the opportunity of combining CO2 electrolysis with the hydrogen economy, paving the way to the possible integration of various emerging energy conversion and storage approaches for improved energy/cost effectiveness.

Synthetic aperture radar (SAR) has the advantage of providing imaging capabilities throughout the day and under all-weather conditions, which makes it particularly important for Earth observation applications. Recently, the utilization of deep learning for SAR image recognition has become a crucial discipline in radar image interpretation since the deepened networks can generate the high-dimensional features and make the function fit accurately when with a large amount of training samples. However, for SAR images, the accurate annotation demands significant effort, expert knowledge, and is prone to errors due to the effect of noise. The lack of SAR-labeled data limits the application of deep neural networks, which usually need a large number of training samples. Consequently, the task of recognizing SAR targets in the scenario with a few training samples has emerged as a significant research interest and, accordingly, the few-shot target recognition technique was introduced and has shown great potential. This article provides a summary of recent advancements in few-shot SAR image target recognition. First, this article outlines the concept of few-shot learning and discusses the dataset specific to the SAR recognition field. Subsequently, it delves into a detailed categorization of methods for recognizing few-shot SAR targets, which include approaches based on the transfer learning, data augmentation, metalearning, and model-based strategies. Finally, it examines both qualitative and quantitative aspects of SAR automatic target recognition technology utilizing few-shot learning, highlights certain challenges and crucial issues that require great attention, and offers a perspective on future research opportunities.

Point cloud-based place recognition plays a crucial role in robotics and unmanned vehicle tasks, particularly in relocalization and loop detection modules of LiDAR-based simultaneous localization and mapping systems. It’s also essential for global localization in scenarios where prior pose information is unavailable. However, three-dimensional point cloud data are characterized by sparsity and disorder, making it challenging to extract robust features. This study proposes an end-to-end deep learning network to compress the point cloud into a global descriptor for point cloud retrieval tasks. The proposed network implements two self-attention modules, i.e., the local point cloud-based self-attention and global point cloud-based self-attention mechanisms. Due to this two-stage self-attention mechanism, the proposed PointAttentionVLAD network achieved a higher average recall @ top 1 on the Benchmark datasets than the SOE-Net and LPD-Net algorithms by 0.39% and 3.41%, respectively. Furthermore, experiments were conducted on KAIST dataset to assess the generalization ability of the proposed PointAttentionVLAD, and the proposed network demonstrated impressive performance on KAIST dataset. The code and the pre-trained model of the proposed PointAttentionVLAD are available at https://github.com/leo6862/pointattentionvlad.

Abstract Electrocardiogram (ECG) prediction is highly important for detecting and storing heart signals and identifying potential health hazards. To improve the duration and accuracy of ECG prediction on the basis of noise filtering, a new algorithm based on variational mode decomposition (VMD) and a convolutional gated recurrent unit (ConvGRU) was proposed, named VMD-ConvGRU. VMD can directly remove noise, such as baseline drift noise, without manual intervention, greatly improving the model usability, and its combination with ConvGRU improves the prediction time and accuracy. The proposed algorithm was compared with three related algorithms (PSR-NN, VMD-NN and TS fuzzy) on MIT-BIH, an internationally recognized arrhythmia database. The experiments showed that the VMD-ConvGRU algorithm not only achieves better prediction accuracy than that of the other three algorithms but also has a considerable advantage in terms of prediction time. In addition, prediction experiments on both the MIT-BIH and European ST-T databases have shown that the VMD-ConvGRU algorithm has better generalizability than the other methods.

BackgroundPrinters can release particles, which is harmful to human health. However, there is insufficient research on how printing conditions affect the level of particles released by printers.ObjectiveTo explore the effects of different printing conditions on the level of printer-emitted particles.MethodsThe experiment was carried out in a closed experimental chamber, and the changes in the number concentration of particles (size range: 0.25-32 μm) and ozone concentration in the experimental chamber during designed printing process were monitored with a portable aerosol particle size spectrometer and an ozone detector respectively. The monitoring included three parts: 2 min before printing as the background number concentration, printing 72 sheets with a designed printing task sets, and then 10 min after printing. A set of printing tasks with predetermined conditions included font, font size, single/double-sided printing mode, page layout, paper size, paper brand, and paper moisture content. The association between printing conditions and level of printer-emitted particles was evaluated by Spearman correlation analysis.ResultsWhen printing in different fonts (Song and Kai) and different font sizes (14 points and 10.5 points), the number concentration peaks of particles in the experimental chamber were 14.71-59.35 P·cm−3, and there was no significant difference (P>0.05). There was no difference in the peak concentrations of printer-emitted particles between single-sided printing and double-sided printing (P>0.05), but there was a significant difference in the time of peak occurrence (P middle 1/ 3> lower 1/3). No increase in the concentration of printer-emitted particles was detected when printing with B5 paper. The peak concentration of printer-emitted particles in printing paper with varying degrees of paper moisture showed differences (P0.05).ConclusionBy changing printing conditions, the levels of printer-emitted particles are affected. Among them, page layout, paper size, and degree of paper moisture have a significant impact on the results; however, single/double-sided printing, font, font size, and paper brand have no significant impact on the results.

Abstract Bioelectronic medicine is a rapidly growing field where targeted electrical signals can act as an adjunct or alternative to drugs to treat neurological disorders and diseases via stimulating the peripheral nervous system on demand. However, current existing strategies are limited by external battery requirements, and the injury and inflammation caused by the mechanical mismatch between rigid electrodes and soft nerves. Here we report a wireless, leadless, and battery-free ferroelectret implant, termed NeuroRing, that wraps around the target peripheral nerve and demonstrates high mechanical conformability to dynamic motion nerve tissue. As-fabricated NeuroRing can act as an ultrasound receiver that converts ultrasound vibrations into electrostimulation pulses, thus stimulating the targeted peripheral nerve on demand. This capability is demonstrated by the precise modulation of the sacral splanchnic nerve to treat colitis, providing a framework for future bioelectronic medicines that offer an alternative to non-specific pharmacological approaches.

Inland waterway transport is an important mode of transportation for many countries and regions. Route planning optimization can reduce navigation time, avoid traffic congestion, and improve transportation efficiency. In actual operations, many vessels determine their navigation routes based on the experience of their shipowners. When the captain fails to obtain accurate information, experience-based routes may pose significant navigation risks and may not consider the overall economic efficiency. This study proposes a comprehensive method for optimizing inland waterway vessel routes using automatic identification system (AIS) data, considering the geographical characteristics of inland waterways and navigation constraints. First, AIS data from vessels in inland waters are collected, and the multi-objective Peak Douglas–Peucker (MPDP) algorithm is applied to compress the trajectory data. Compared to the traditional DP algorithm, the MPDP algorithm reduces the average compression rate by 5.27%, decreases length loss by 0.04%, optimizes Euclidean distance by 50.16%, and improves the mean deviations in heading and speed by 23.53% and 10.86%, respectively. Next, the Ordering Points to Identify the Clustering Structure (OPTICS) algorithm is used to perform cluster analysis on the compressed route points. Compared to the traditional DBSCAN algorithm, the OPTICS algorithm identifies more clusters that are both detailed and hierarchically structured, including some critical waypoints that DBSCAN may overlook. Based on the clustering results, the A* algorithm is used to determine the connectivity between clusters. Finally, the nondominated sorting genetic algorithm II is used to select suitable route points within the connected clusters, optimizing objectives, including path length and route congestion, to form an optimized complete route. Experiments using vessel data from the waters near Shuangshan Island indicate that, when compared to three classic original routes, the proposed method achieves path length optimizations of 4.28%, 1.67%, and 0.24%, respectively, and reduces congestion by 24.15%. These improvements significantly enhance the planning efficiency of inland waterway vessel routes. These findings provide a scientific basis and technical support for inland waterway transport.

Isorhamnetin (ISO) is an active flavonoid compound mainly isolated from the fruits of Hippophae rhamnoides L. and the leaves of Ginkgo biloba L. Previous studies have revealed the antifibrotic action of ISO in the liver and lungs, although its potential protective effects against renal fibrosis and the underlying mechanisms are still poorly understood. Given that many actions of ISO could be similarly attained by hydrogen sulfide (H2S), we speculated that ISO may work through the induction of endogenous H2S. To test the hypothesis, we established the unilateral ureteral obstruction (UUO) renal fibrosis rat model and transforming growth factor-β1(TGF-β1)-induced fibrosis in cultured renal tubular cells. ISO treatment inhibited epithelial–mesenchymal transition (EMT) formation, decreased extracellular matrix (ECM) deposition, and relieved renal fibrosis. Further analysis revealed that ISO stimulated the expression of the H2S-synthesizing enzyme cystathionine lyase (CSE) and cystathionine beta-synthase (CBS), and promoted H2S production in vivo and in vitro. The elevated H2S attenuated oxidative stress and elevated the thiol level. It induced Keap1 sulfhydration, disrupted Keap1-Nrf2 interaction, and promoted the entry of Nrf2 into the nucleus. Finally, we found that circulating H2S mainly derived from the liver, and not the kidney. Collectively, our study revealed that ISO alleviated renal fibrosis by inducing endogenous H2S and regulating Keap1-Nrf2 interaction through sulfhydration of Keap1. Endogenous H2S could be an important mediator underlying the pharmacological actions of ISO. Due to the multifunctional properties of H2S, the H2S-inducing nature of ISO could be exploited to treat various diseases.

In order to ensure national grain and oil security, it is imperative to expand the soybean planting area in the Xinjiang region. However, the scarcity of water resources in southern Xinjiang, the relatively backward soybean planting technology, and the lack of a supporting irrigation system have negatively impacted soybean planting and yield. In 2022 and 2023, we conducted an experiment which included three irrigation amounts of 27 mm, 36 mm, and 45 mm and analyzed the changes in dry mass and yield. Additionally, we simulated the potential yield using the corrected DSSAT-CROPGRO-Soybean model and biomass based on the meteorological data from 1994 to 2023. The results demonstrated that the model was capable of accurately predicting soybean emergence (the relative root mean square error (nRMSE) = 0, the absolute relative error (ARE) = 0), flowering (nRMSE = 0, ARE = 2.78%), maturity (nRMSE = 0, ARE = 3.21%). The model demonstrated high levels of accuracy in predicting soybean biomass (R2 = 0.98, nRMSE = 20.50%, ARE = 20.63%), 0–80 cm soil water storage (R2 = 0.64, nRMSE = 7.78%, ARE = 3.24%), and yield (R2 = 0.81, nRMSE = 10.83%, ARE = 8.79%). The biomass of soybean plants increases with the increase in irrigation amount. The highest biomass of 63 mm is 9379.19 kg·hm−2. When the irrigation yield is 36–45 mm (p < 0.05), the maximum yield can reach 4984.73 kg·hm−2; the maximum efficiency of soybean irrigation water was 33–36 mm. In light of the impact of soybean yield and irrigation water use efficiency, the optimal irrigation amount for soybean cultivation in southern Xinjiang is estimated to be between 36 and 42 mm. The simulation results provide a theoretical foundation for soybean cultivation in southern Xinjiang.

In traditional cardiac ultrasound diagnostics, the process of planning scanning paths and adjusting the ultrasound window relies solely on the experience and intuition of the physician, a method that not only affects the efficiency and quality of cardiac imaging but also increases the workload for physicians. To overcome these challenges, this study introduces a robotic system designed for autonomous cardiac ultrasound scanning, with the goal of advancing both the degree of automation and the quality of imaging in cardiac ultrasound examinations. The system achieves autonomous functionality through two key stages: initially, in the autonomous path planning stage, it utilizes a camera posture adjustment method based on the human body’s central region and its planar normal vectors to achieve automatic adjustment of the camera’s positioning angle; precise segmentation of the human body point cloud is accomplished through efficient point cloud processing techniques, and precise localization of the region of interest (ROI) based on keypoints of the human body. Furthermore, by applying isometric path slicing and B-spline curve fitting techniques, it independently plans the scanning path and the initial position of the probe. Subsequently, in the autonomous scanning stage, an innovative servo control strategy based on cardiac image edge correction is introduced to optimize the quality of the cardiac ultrasound window, integrating position compensation through admittance control to enhance the stability of autonomous cardiac ultrasound imaging, thereby obtaining a detailed view of the heart’s structure and function. A series of experimental validations on human and cardiac models have assessed the system’s effectiveness and precision in the correction of camera pose, planning of scanning paths, and control of cardiac ultrasound imaging quality, demonstrating its significant potential for clinical ultrasound scanning applications.

The ceRNA network, consisting of both noncoding RNA and protein-coding RNA, governs the occurrence, progression, metastasis, and infiltration of lung adenocarcinoma. Signatures comprising multiple genes can effectively determine survival stratification and prognosis of patients with lung adenocarcinoma. To explore the mechanisms of lung adenocarcinoma progression and identify potential biological targets, we carried out systematic bioinformatics analyses of the genetic profiles of lung adenocarcinoma, such as weighted gene co-expression network analysis (WGCNA), differential expression (DE) assessment, univariate and multivariate Cox proportional hazard regression models, ceRNA modulatory networks generated using the ENCORI and miRcode databases, nomogram models, ROC curve assessment, and Kaplan-Meier survival curve analysis. The ceRNA network encompassed 37 nodes, comprising 12 mRNAs, 22 lncRNAs, and three miRNAs. Simultaneously, we performed integration analysis using the 12 genes from the ceRNA network. Our findings revealed that the signature established by these 12 genes serves as an adverse element in lung adenocarcinoma, contributing to unfavorable patient prognosis. To ensure the credibility of our results, we used in vitro experiments for further verification. In conclusion, our study delved into the potential mechanisms underlying lung adenocarcinoma via the ceRNA regulatory network, specifically focusing on the PIF1 and has-miR-125a-5p axis. Additionally, a signature comprising 12 genes was identified as a biomarker related to the prognosis of lung adenocarcinoma.

When a human strokes the surface of an object with his/her finger, the surface shape influences the perceived softness of the object. This study introduced a curved surface softness illusion, which alters the perception of material softness. When a surface with curvature is felt by sliding a finger over it, it feels softer than a flat surface made of the same material. In contrast, a rugged surface is perceived as harder. This illusion indicates that, in addition to mechanical hardness, humans judge an object’s softness based on its surface shape.

Stroke is the second leading cause of death worldwide, with ischemic stroke accounting for a significant proportion of morbidity and mortality among stroke patients. Ischemic stroke often causes disability and cognitive impairment in patients, which seriously affects the quality of life of patients. Therefore, how to predict the recovery of patients can provide support for clinical intervention in advance and improve the enthusiasm of patients for rehabilitation treatment. With the popularization of imaging technology, the diagnosis and treatment of ischemic stroke patients are often accompanied by a large number of imaging data. Through machine learning and Deep Learning, information from imaging data can be used more effectively. In this review, we discuss recent advances in neuroimaging, machine learning, and Deep Learning in the rehabilitation of ischemic stroke.

Prostate cancer (PCa) is a common malignant tumor, whose morbidity and mortality keep the top three in the male-related tumors in developed countries. Abnormal ion channels, such as transient receptor potential canonical 6 (TRPC6), are reported to be involved in the carcinogenesis and progress of prostate cancer and have become potential drug targets against prostate cancer. Here, we report a novel small molecule inhibitor of TRPC6, designated as PCC0208057, which can suppress the proliferation and migration of prostate cancer cells in vitro, and inhibit the formation of Human umbilical vein endothelial cells cell lumen. PCC0208057 can effectively inhibit the growth of xenograft tumor in vivo. Molecular mechanism studies revealed that PCC0208057 could directly bind and inhibit the activity of TRPC6, which then induces the prostate cancer cells arrested in G2/M phase via enhancing the phosphorylation of Nuclear Factor of Activated T Cells (NFAT) and Cdc2. Taken together, our study describes for the first time that PCC0208057, a novel TRPC6 inhibitor, might be a promising lead compound for treatment of prostate cancer.

To simulate the creep characteristics of corn straw particles under uniaxial compression, a 6-level 2D model was created using PFC 2D software according to the actual uniaxial creep test, the grain size, and shape of corn straw particles. Five groups of controlled tests were designed by the control variable method to study the influence of Maxwell body parameters Em, ηm; Kelvin body parameters Ek, ηk; and friction coefficient f on the creep curve of Burgers model. Results revealed that the creep characteristics of corn straw are affected by these 5 parameters. After multiple debugging by trial-and-error method, simulation parameters suitable for describing the creep characteristics of corn straw particles were obtained. The creep curves obtained by simulation under these parameters are consistent with those obtained by physical tests. It was shown that PFC software can not only study the creep characteristics of geotechnical materials, but also study the creep characteristics of agricultural fiber materials, which provides a reference for the subsequent rheological characteristics of biomass materials.

Abstract Background The roles of low molecular mass polypeptide 2 (LMP2) and transporter-associated with antigen processing (TAP2) in tumorigenesis are controversial. Here we aimed to explore the effect of LMP2 and TAP2 on the oncogenesis and metastasis of cervical cancer cells. Methods The expressions of LMP2 and TAP2 in cervical cancer and normal tissues were determined by qPCR. Plate colony formation, cell counting kit-8 analysis and in vivo tumor xenograft assays were used to detect the tumor growth. Wound healing and transwell assays were used to detect the metastasis of cervical cancer. Gelatin zymography and western blotting assays were used to detect the effect of LMP2 and TAP2 on the EMT and Wnt/β-catenin pathway in cervical cancer cells. Results In the present study, we reported that LMP2 and TAP2 levels were overexpressed in cervical cancer. Overexpression of LMP2 and TAP2 impaired the proliferation of Hela cells. In vivo studies substantiated that LMP2 and TAP2 antagonized tumor growth. Likewise, LMP2 and TAP2 overexpression decreased the migration and invasion ability of Hela cells by regulating the process of epithelial-mesenchymal transition (EMT). Mechanically, LMP2 and TAP2 subverted the protein abundance of Wnt1 and β-catenin, thereby downregulating their downstream targets Cyclin D1 and c-Myc. In addition, Wnt1 overexpression partially rescued the observed consequences of ectopic expression of LMP2 and TAP2 in cervical cancer cells. Taken together, our study revealed that LMP2 and TAP2 suppress the oncogenesis and metastasis of cervical cancer cells by Wnt/β-catenin pathway and altering EMT. Conclusion LMP2 and TAP2 may inhibit the oncogenesis and metastasis of cervical cancer cells by inhibiting the process of EMT and the Wnt/β-catenin signaling pathway, which may provide important insight into prospective targets for the treatment of cervical cancer.

In recent years, more and more metal oxides have been finding critical tribo-catalytic applications. Presently, we have explored the tribo-catalytic conversion of H2O and CO2 using Co3O4 nanoparticles and obtained some surprising results. In an as-received 150 mL glass reactor enclosed with 10 mL of H2O, 0.10 g of Co3O4 nanoparticles, 1 atm of CO2, and a Teflon magnetic rotary disk, we observed the production of as much as 57.41 µmol/L of H2, 0.15 µmol/L of CH4, and 0.21 µmol/L of CO after 5 h of magnetic stirring. Metallic coatings of Cu, Ni, SUS316, Ti, Nb, Mo, and W were further introduced on reactor bottoms separately. For those coatings of Ni, SUS316, Ti, and Nb, the reduction of CO2 was dramatically enhanced, and C2+ products of C2H6 and C2H4 were observed. Especially for the Ti coating, the amounts of H2 and CH4 were increased by 2 and 26 times from those for the glass bottom, respectively, and the amounts of C2H6 and C2H4 were very impressive. The Co3O4 nanoparticles were proven chemically stable under magnetic stirring in water, and hydroxyl radicals and superoxide radicals have been detected for the Co3O4 nanoparticles under magnetic stirring through fluorescence spectroscopy and electron paramagnetic resonance spectroscopy analyses. These findings not only reveal outstanding capability of Co3O4 to generate multicarbon products from H2O and CO2 through tribo-catalysis but also highlight a promising potential of tribo-catalysis as a whole to harness mechanical energy for addressing energy shortages and environmental pollution.

Abstract Background Endometrial cancer (EC) is one of the worldwide gynecological malignancies. Endoplasmic reticulum (ER) stress is the cellular homeostasis disturbance that participates in cancer progression. However, the mechanisms of ER Stress on EC have not been fully elucidated. Method The ER Stress-related genes were obtained from Gene Set Enrichment Analysis (GSEA) and GeneCards, and the RNA-seq and clinical data were downloaded from The Cancer Genome Atlas (TCGA). The risk signature was constructed by the Cox regression and the least absolute shrinkage and selection operator (LASSO) analysis. The significance of the risk signature and clinical factors were tested by time-dependent receiver operating characteristic (ROC) curves, and the selected were to build a nomogram. The immunity correlation was particularly analyzed, including the related immune cells, pathways, and immune checkpoints. Functional enrichment, potential chemotherapies, and in vitro validation were also conducted. Result An ER Stress-based risk signature, consisting of TRIB3, CREB3L3, XBP1, and PPP1R15A was established. Patients were randomly divided into training and testing groups with 1:1 ratio for subsequent calculation and validation. Based on risk scores, high- and low-risk subgroups were classified, and low-risk subgroup demonstrated better prognosis. The Area Under Curve (AUC) demonstrated a reliable predictive capability of the risk signature. The majority of significantly different immune cells and pathways were enriched more in low-risk subgroup. Similarly, several typical immune checkpoints, expressed higher in low-risk subgroup. Patients of the two subgroups responded differently to chemotherapies. Conclusion We established an ER Stress-based risk signature that could effectively predict EC patients’ prognosis and their immune correlation.

Abstract Background Mitofusin 2 (MFN2) plays an important role in many tumors, but how its role in renal clear cell carcinoma needs further research. Methods In this study, we analyzed the expression of MFN2 in renal clear cell carcinoma tissues and normal kidney tissues through the Cancer Genome Atlas (TCGA) database and our clinical samples.Enrichment analysis was performed to determine MFN2-related pathways and biological functions. The correlation of MFN2 expression with immune cells was analyzed.The correlation of the expression of methylation and the methylation sites of MFN2 were analyzed by UALCAN and TCGA databases. Univariate / multivariate COX risk regression and Kaplan-Meier methods were used to determine the prognostic value of MFN2.Nomograms were drawn to predict overall survival (OS) at 1,3, and 5 years. We investigated the role of MFN2 in renal cancer cells using CCK 8, clone formation, wound healing assay, and methylase qPCR experiments. Results MFN2 is poorly expressed in renal clear cell carcinoma compared to normal kidney tissue,and is significantly negatively associated with TNM stage, histological grade and pathological stage.MFN2 was directly associated with OS after multivariate Cox regression analysis.MFN2 shows a hypomethylation state and shows a positive correlation with multiple methylation sites.Signaling pathways through functional enrichment to B-cell receptors and oxidative stress-induced senescence.Moreover, the low expression of MFN2 was positively correlated with the degree of immune cell infiltration in a variety of immune cells.In vitro experiments showed that overexpression of MFN2 significantly inhibited the proliferation and migration of renal clear cells and promoted methylation. Conclusions In conclusion, MFN2 can be used as a novel prognostic marker for renal clear cell carcinoma and requires further investigation of its role in tumor development.

This study analyzed the flavor compounds in the meat of four indigenous breeds of Chinese sheep through the use of gas chromatography–ion mobility spectrometry (GC-IMS). GC-IMS provided information on the characteristics and strength of 71 volatile flavor compounds (monomers and dimers), with aldehydes, alcohols and ketones being the most abundant in all types of sheep meat. The compounds with higher intensity peaks in the sheep meat were aldehydes (n-nonanal, octanal, heptanal, 3-methylbutanal, and hexanal), alcohols (1-octen-3-ol, hexanol, and pentanol), ketones (3-hydroxy-2-butanon, 2-butanone, and 2-propanone), esters (methyl benzoate), and thiazole (trimethylthiazole). The volatile flavor components in the meat of the different breeds of sheep obtained via GC-IMS were further differentiated using principal component analysis. In addition, orthogonal partial least squares discriminant analysis (OPLS-DA) and variable importance on projection (VIP) were used to determine the characteristic flavor compounds in the meats of different breeds of sheep, and 21 differentially volatile components were screened out based on having a VIP above 1. These results indicate that GC-IMS combined with multivariate analysis is a convenient and powerful method for characterizing and discriminating sheep meat.

Object detection is applied extensively in various domains, including industrial manufacturing, road traffic management, warehousing and logistics, and healthcare. In ship object detection tasks, detection networks are frequently deployed on devices with limited computational resources, e.g., unmanned surface vessels. This creates a need to balance accuracy with a low parameter count and low computational load. This paper proposes an improved object detection network based on YOLOv5. To reduce the model parameter count and computational load, we utilize an enhanced ShuffleNetV2 network as the backbone. In addition, a split-DLKA module is devised and implemented in the small object detection layer to improve detection accuracy. Finally, we introduce the WIOUv3 loss function to minimize the impact of low-quality samples on the model. Experiments conducted on the SeaShips dataset demonstrate that the proposed method reduces parameters by 71% and computational load by 58% compared to YOLOv5s. In addition, the proposed method increases the mAP@0.5 and mAP@0.5:0.95 values by 3.9% and 3.3%, respectively. Thus, the proposed method exhibits excellent performance in both real-time processing and accuracy.

Aerodynamic investigation of a bionic coaxial-rotors unmanned aerial vehicle (UAV) is performed. According to Chinese parasol seed features and flight requirements, the bionic conceptual design of a coaxial-rotors UAV is described. A solution procedure for the numerical simulation method, based on a multi-reference frame (MRF) model, is expressed, and a verification study is presented using the typical case. The aerodynamic design is conducted for airfoil, blade, and coaxial-rotors interference. The aerodynamic performance of the coaxial rotors is investigated by numerical simulation analysis. The rotor/motor integrated experiment verification is conducted to assess the performance of the coaxial-rotors UAV. The results indicate that the UAV has excellent aerodynamic performance and bionic configuration, allowing it to adapt to task requirements. The bionic UAV has a good cruise power load reach of 8.36 kg/kw, and the cruise flying thrust force is not less than 78 N at coaxial-rotor and rotor-balloon distance ratios of 0.39 and 1.12, respectively. It has the “blocks stability phenomenon” formed by the rotor downwash speed decreases and the balloon’s additional negative pressure. The present method and the bionic configuration provide a feasible design and analysis strategy for coaxial-rotors UAVs.

Phosphorus (P) recovery from wastewater is considered to be a positive human intervention towards sustainable P use in the global P cycle. This study investigated the feasibility of synthesizing a superparamagnetic nano-sorbent that was functionalized by lanthanum silicate nanorods (NRLa-Si) using drinking water treatment sludge (DWTS), evaluating both its P adsorption capacity and fertilization effect. The DWTS-based La-modified P nano-sorbent (P-sorbent D) exhibited complicated but single-layer-dominant adsorption for phosphate, with a maximum adsorption capacity up to 26.8 mg/g, which was superior to that of most of the similar sludge-based P-sorbent. The NRLa-Si-modified P-sorbent D was identified with several characterization techniques and the leaching metal elements from the nano-sorbent were tested, which were below the limits proposed by the Food and Agriculture Organization of the United Nations. In addition, the growth and vigorousness of Arabidopsis thaliana indicated that the exhausted P-sorbent D could be used as a potential water-soluble moderate-release P fertilizer, which was also confirmed by the well-fitted P uptake model and the P desorption pattern from the sorbent–fertilizer. The doped lanthanum silicate nanorods could play the dual role of P complexation enhancement and health/growth promotion. In light of this, this study proposed a new way of reclaiming DWTS as a P-sorbent for fertilization, offering new insights into the path toward “closing the P loop”.