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Abstract Background Persistent infection with high-risk human papillomavirus (HPV) is a significant risk factor for cervical cancer. HPV typing and cytology are conducted in women of appropriate age to assess the risk of cervical lesions and to guide the need for further diagnostic procedures such as colposcopy, cervical biopsy, or treatment. This article explores methods to predict the risks of high-grade precancerous cervical lesions based on high-risk HPV typing. Methods We conducted a retrospective analysis of HPV typing data from 158,565 women, including 19,707 who underwent ThinPrep cytologic testing (TCT), 7,539 who had colposcopy examinations, and 4,762 who had biopsies. We evaluated the sensitivity, specificity, and risk parameters of high-grade lesions associated with high-risk HPV types. Results (1) The overall prevalence of HPV infection was 17.89%, with the most prevalent types being HPV52 (4.44%), HPV58 (2.10%), HPV53 (1.96%), HPV81 (1.85%), HPV42 (1.75%), and HPV16 (1.44%). (2) The sensitivity and specificity of detecting high-grade lesions in TCT, colposcopy, and biopsy, based on high-risk HPV typing, demonstrated a strong linear correlation with the infection rate of each type. (3) HPV16 was confirmed to have a higher risk of CIN2 + in biopsies using a self-defined risk parameter. (4) The top five HPV types with the highest PPVs and pathogenicity risks in biopsies were HPV45, HPV16, HPV58, HPV33, and HPV18. Conclusion In Changsha, China, HPV52, HPV58, and HPV53 were the most prevalent and contributed significantly to high-grade lesions. After adjusting for infection rates, a self-defined risk parameter was proposed as a measure of the intrinsic risks of high-grade lesions associated with high-risk HPV types. Focused monitoring of prevalent high-risk HPV types such as HPV45, HPV16, HPV58, HPV33, and HPV18, which show the highest pathogenicity risks, is recommended in our region.

Abstract Acute kidney injury (AKI) is a clinical condition characterized by a rapid decline in kidney function, which is associated with local inflammation and programmed cell death in the kidney. The G protein-coupled receptors (GPCRs) represent the largest family of signaling transduction proteins in the body, and approximately 40% of drugs on the market target GPCRs. The expressions of various GPCRs, prostaglandin receptors and purinergic receptors, to name a few, are significantly altered in AKI models. And the role of GPCRs in AKI is catching the eyes of researchers due to their distinctive biological functions, such as regulation of hemodynamics, metabolic reprogramming, and inflammation. Therefore, in this review, we aim to discuss the role of GPCRs in the pathogenesis of AKI and summarize the relevant clinical trials involving GPCRs to assess the potential of GPCRs and their ligands as therapeutic targets in AKI and the transition to AKI-CKD.

Cyanopterus ninghais is an important gregarious ectoparasitoid during the larval stage of Monochamus alternatus, a key vector for pine wilt disease in Asia. In this study, the complete mitochondrial genome of C. ninghais was sequenced and analyzed. The mitochondrial genome of C. ninghais is 15,386 bp in length, comprising 13 protein-coding genes (PCGs), 22 transfer RNA genes (tRNAs), and 2 ribosomal RNA genes (rRNAs). The nucleotide composition is 41.32% A, 8.29% G, 6.06% C, and 44.33% T. Phylogenetic trees of Braconidae were constructed using 13 PCG sequences via Bayesian inference (BI) and maximum likelihood (ML) analyses to determine their phylogenetic position. Both ML and BI analyses revealed that C. ninghais is closely related to Euurobracon yokahamae, Virgulibracon endoxylaphagus, and Habrobracon hebetor.

Introduction: This study aimed to develop and validate machine learning (ML) models based on serum Klotho for predicting end-stage kidney disease (ESKD) and cardiovascular disease (CVD) in patients with chronic kidney disease (CKD). Methods: Five different ML models were trained to predict the risk of ESKD and CVD at three different time points (3, 5, and 8 years) using a cohort of 400 non-dialysis CKD patients. The dataset was divided into a training set (70%) and an internal validation set (30%). These models were informed by data comprising 47 clinical features, including serum Klotho. The best-performing model was selected and used to identify risk factors for each outcome. Model performance was assessed using various metrics. Results: The findings showed that the least absolute shrinkage and selection operator regression model had the highest accuracy (C-index = 0.71) in predicting ESKD. The features mainly included in this model were estimated glomerular filtration rate, 24-h urinary microalbumin, serum albumin, phosphate, parathyroid hormone, and serum Klotho, which achieved the highest area under the curve (AUC) of 0.930 (95% CI: 0.897–0.962). In addition, for the CVD risk prediction, the random survival forest model with the highest accuracy (C-index = 0.66) was selected and achieved the highest AUC of 0.782 (95% CI: 0.633–0.930). The features mainly included in this model were age, history of primary hypertension, calcium, tumor necrosis factor-alpha, and serum Klotho. Conclusion: We successfully developed and validated Klotho-based ML risk prediction models for CVD and ESKD in CKD patients with good performance, indicating their high clinical utility.

Experts and scholars from various nations have proposed studying low Earth orbit (LEO) satellite signals as the space-based signals of opportunity (SOPs) for navigation and positioning. This method serves as a robust alternative in environments where global navigation satellite systems (GNSS) are unavailable or compromised, providing users with high-precision, anti-interference, secure, and dependable backup navigation solutions. The rapid evolution of LEO communication constellations has spurred the development of SOPs positioning technology using LEO satellites. However, this has also led to a substantial increase in the number of LEO satellites, thereby reintroducing the traditional challenge of satellite selection. This research thoroughly examines three critical factors affecting positioning accuracy: satellite observable time, satellite elevation, and position dilution of precision (PDOP). It introduces a strategic approach for selecting satellites in LEO SOPs navigation and positioning. Simulation outcomes confirm that this satellite selection strategy effectively identifies visible satellites, ensuring precise positioning through LEO SOPs.

Monochamus alternatus is a serious wood borer of pine trees and is a widespread vector of pine wilt disease in Asia. Cyanopterus ninghais, as a biological control agent of M. alternatus found in China, is expected to be applied for management of M. alternatus in Asia through introduction or augmentative release. To examine the host range of C. ninghais and minimize potential risk to non-target hosts in the release areas, the parasitism of this wasp on 22 species of wood boring insects from pine and other forests was determined by non-choice tests. Cyanopterus ninghais parasitized Spondylis buprestoides and M. saltuarius which also infested trees in Pinaceae, but the parasitism rates on these two beetles were significantly lower than its natural host, M. alternatus. Cyanopterus ninghais always preferred to parasitize M. alternatus in the choice tests. In addition, host plant selection tests revealed that C. ninghais was only attracted to Pinaceae, especially Masson Pine, Pinus massoniana. Changing the host plant species did not affect the preference of this parasitoid to the test hosts. The results suggested that C. ninghais had high host specificity for M. alternatus, and the combination of M. alternatus larvae and Masson Pine branches was the best combination for rearing this parasitoid.

Globally, anthropogenic disturbance and climate change caused a rapid decline of submerged macrophytes in lake ecosystems. Potamogeton crispus (P. crispus), a species that germinates in winter, explosively expanded throughout many Chinese lakes, yet the underlying mechanism remained unclear. Here, this study examined the long-term changes in the distribution patterns of P. crispus in Lake Gaoyou by combining remote sensing images and hydrometeorological data from 1984 to 2022 and water quality data from 2009 to 2022. It aims to unravel the relationships between the distribution patterns of P. crispus and hydrometeorological and water quality factors. The results showed that the area of P. crispus in Lake Gaoyou showed a slight increase from 1984 to 2009, a marked increase from 2010 to 2019, followed by a decline after 2020. Spatially, P. crispus was primarily distributed in the western and northern parts of Lake Gaoyou, with less distribution in the central and southeastern parts of the lake. Wind speed (WS), temperature (Temp), water level (WL), ammonia nitrogen (NH3-N), and Secchi depth (SD) were identified as the key factors regulating the variation in the P. crispus area in Lake Gaoyou. We found that the P. crispus area showed an increasing trend with increasing Temp, WL, and SD and decreasing WS and NH3-N. The influence of environmental factors on the area of P. crispus in Lake Gaoyou varied among seasons. The results indicated that hydrometeorology (WS, Temp, and WL) may override water quality (NH3-N and SD) in driving the succession of P. crispus distribution. The findings of this study offer valuable insights into the recent widespread expansion of P. crispus in shallow lakes across Eastern China.

Background: BMSC-secreted exosomes (BMSC-Exos) have shown potential for promoting behavioral recovery following spinal cord injury (SCI). However, its role in blocking astrocyte activation remains unclear. Thus, this study aimed to determine whether BMSC-Exos impair the function of astrocytes following SCI in mice and to seek the mechanism. Methods: BMSC-Exos were collected by ultracentrifugation and identified. The SCI mice were developed by laminectomy combined with spinal cord shock, followed by BMSC-Exos or nerve growth factor (positive control) treatment. HE staining, Nissl staining, and TUNEL were conducted to analyze the pathological structural damage and neuronal damage in the mouse spinal cord. Bioinformatics was used to screen altered molecules under the BMSC-Exos treatment. Effects of BMSC-Exos and changes in ZBTB4 and ITIH3 expression on neuronal damage induced by activated astrocytes in the co-culture system were analyzed by CCK-8 and flow cytometry. Results: Nerve growth factor and BMSC-Exos promoted motor function recovery, alleviated nerve injury, and reduced apoptosis in mice with SCI. ZBTB4 was enriched in BMSC-Exos and lowly expressed in SCI. Downregulation of ZBTB4 diminished the therapeutic effects of BMSC-Exos against SCI. ITIH3 was a downstream target of ZBTB4. Neurotoxic activation of astrocytes induced neuronal injury, which was alleviated by BMSC-Exos. However, ZBTB4 knockdown overturned the effects of BMSC-Exos in vitro and combined ITIH3 knockdown alleviated the accentuating effects of ZBTB4 knockdown on neuronal injury. Conclusion: BMSC-Exos protected against astrocyte-induced neuronal injury by delivering ZBTB4 to repress ITIH3, ultimately improving motor function in mice with SCI.

Abstract Background The endoplasmic reticulum plays an important role in glucose metabolism and has not been explored in the kinetic estimation of hepatocellular carcinoma (HCC) via 18F-fluoro-2-deoxy-d-glucose PET/CT. Methods A dual-input four-compartment (4C) model, regarding endoplasmic reticulum was preliminarily used for kinetic estimation to differentiate 28 tumours from background liver tissue from 24 patients with HCC. Moreover, parameter images of the 4C model were generated from one patient with negative findings on conventional metabolic PET/CT. Results Compared to the dual-input three-compartment (3C) model, the 4C model has better fitting quality, a close transport rate constant (K 1) and a dephosphorylation rate constant (k 6/k 4), and a different removal rate constant (k 2) and phosphorylation rate constant (k 3) in HCC and background liver tissue. The K 1, k 2, k 3, and hepatic arterial perfusion index (HPI) from the 4C model and k 3, HPI, and volume fraction of blood (V b ) from the 3C model were significantly different between HCC and background liver tissues (all P

Abstract Esophageal cancer is a highly incidence and deadly disease with a poor prognosis, especially in developing countries. Owing to the lack of specific symptoms and early diagnostic biomarkers, most patients are diagnosed with advanced disease, leading to a 5-year survival rate of less than 15%. Early (n = 50) and middle-advanced (n = 50) esophageal squamous cell carcinoma (ESCC) patients, as well as 71 healthy individuals, underwent 5-hydroxymethylcytosine (5hmC) sequencing on their plasma cell-free DNA (cfDNA). A Northern Chinese cohort of cfDNA 5hmC dataset of 150 ESCC patients and 183 healthy individuals were downloaded for validation. A diagnostic model was developed using cfDNA 5hmC signatures and then improved by low-pass whole genome sequencing (WGS) features of cfDNA. Conserved cfDNA 5hmC modification motifs were observed in the two independent ESCC cohorts. The diagnostic model with 5hmC features achieved an AUC of 0.810 and 0.862 in the Southern and Northern cohorts, respectively, with sensitivities of 69.3–74.3% and specificities of 82.4–90.7%. The performance was well maintained in Stage I to Stage IV, with accuracy of 70–100%, but low in Stage 0, 33.3%. Low-pass WGS of cfDNA improved the AUC to 0.934 with a sensitivity of 82.4%, a specificity of 88.2%, and an accuracy of 84.3%, particularly significantly in Stage 0, with an accuracy up to 80%. 5hmC and WGS could efficiently differentiate very early ESCC from healthy individuals. These findings imply a non-invasive and convenient method for ESCC detection when clinical treatments are available and may eventually prolong survival.

Potential multi-ship conflict situations in coastal or near-shore port areas have always been one of the important factors affecting ship navigation safety and a key target of maritime traffic regulatory authorities. In recent years, with the continuous development and integration of various emerging technologies in the maritime field, maritime traffic supervision has also shown a trend of intelligent and autonomous development. The traditional supervision method dominated by human experience is evolving towards data and model-driven practices. In order to solve the problem of ship navigation safety supervision under multi-ship conflict scenarios, it is urgent to build an intelligent conflict mitigation decision-making model. Therefore, this paper designs a novel risk mitigation decision-making model for multi-ship conflict scenarios from the perspective of maritime supervision. The model proposed in this paper first extracts high-density ship clusters based on AIS (Automatic Identification System) data and uses the MCD (Mean Core Density) and PRM (Proportion of Relative Motion) as feature indicators to further mine potential multi-ship conflict scenarios. Finally, a global optimization decision-making model is constructed to effectively mitigate conflict risks. Experimental verification shows that the intelligent decision-making model for the mitigation of maritime traffic conflict proposed in this paper can autonomously identify conflict scenarios and make reasonable decisions in real time. It can effectively ensure the navigation safety of ships in multi-ship conflict scenarios and further improve the supervision level of maritime departments.

Abstract Background The immunosuppressive microenvironment in glioma induces immunotherapy resistance and is associated with poor prognosis. Glioma-associated mesenchymal stem cells (GA-MSCs) play an important role in the formation of the immunosuppressive microenvironment, but the mechanism is still not clear. Results We found that GA-MSCs promoted the expression of CD73, an ectonucleotidase that drives immunosuppressive microenvironment maintenance by generating adenosine, on myeloid-derived suppressor cells (MDSCs) through immunosuppressive exosomal miR-21 signaling. This process was similar to the immunosuppressive signaling mediated by glioma exosomal miR-21 but more intense. Further study showed that the miR-21/SP1/DNMT1 positive feedback loop in MSCs triggered by glioma exosomal CD44 upregulated MSC exosomal miR-21 expression, amplifying the glioma exosomal immunosuppressive signal. Modified dendritic cell-derived exosomes (Dex) carrying miR-21 inhibitors could target GA-MSCs and reduce CD73 expression on MDSCs, synergizing with anti-PD-1 monoclonal antibody (mAb). Conclusions Overall, this work reveals the critical role of MSCs in the glioma microenvironment as signal multipliers to enhance immunosuppressive signaling of glioma exosomes, and disrupting the positive feedback loop in MSCs with modified Dex could improve PD-1 blockade therapy. Graphical abstract

This paper reviews the research progress and development of aluminate long afterglow luminescent materials in the field of road marking, especially the study of rare earth ion-activated strontium aluminate (SrAl2O4: Eu2+, Dy3+)-based long afterglow powders. This article begins by describing the importance of road markings and the need to improve their visibility and durability at night and in adverse weather conditions. Subsequently, the current passive and active methods for improving the visibility of marking materials are discussed in detail, focusing on the advantages of aluminate long afterglow materials and challenges related to their hydrolysis and thermal stability. Through the application of organic–inorganic composite coating technology, the water resistance and thermal stability of the materials can be improved, thus enhancing the performance of road markings. This article also summarizes the current research status of different types of long afterglow road marking coatings. It analyzes the luminescence mechanism of aluminate long afterglow materials. Additionally, this article discusses future research directions and application prospects. The aim is to provide technical references and support for the wide application of long afterglow self-luminous road marking coatings.

To address the need for multivalent vaccines against Coronaviridae that can be rapidly developed and manufactured, we compared antibody responses against SARS-CoV, SARS-CoV-2, and several variants of concern in mice immunized with mRNA-lipid nanoparticle vaccines encoding homodimers or heterodimers of SARS-CoV/SARS-CoV-2 receptor-binding domains. All vaccine constructs induced robust anti-RBD antibody responses, and the heterodimeric vaccine elicited an IgG response capable of cross-neutralizing SARS-CoV, SARS-CoV-2 Wuhan-Hu-1, B.1.351 (beta), and B.1.617.2 (delta) variants.

Abstract Background Kinetic estimation provides fitted parameters related to blood flow perfusion and fluorine-18-fluorodeoxyglucose (18F-FDG) transport and intracellular metabolism to characterize hepatocellular carcinoma (HCC) but usually requires 60 min or more for dynamic PET, which is time-consuming and impractical in a busy clinical setting and has poor patient tolerance. Methods This study preliminarily evaluated the equivalence of liver kinetic estimation between short-term (5-min dynamic data supplemented with 1-min static data at 60 min postinjection) and fully 60-min dynamic protocols and whether short-term 18F-FDG PET-derived kinetic parameters using a three-compartment model can be used to discriminate HCC from the background liver tissue. Then, we proposed a combined model, a combination of the maximum-slope method and a three-compartment model, to improve kinetic estimation. Results There is a strong correlation between the kinetic parameters K 1 ~ k 3, HPI and $${{\varvec{V}}}_{{\varvec{b}}}$$ V b in the short-term and fully dynamic protocols. With the three-compartment model, HCCs were found to have higher k 2, HPI and k 3 values than background liver tissues, while K 1, k 4 and $${{\varvec{V}}}_{{\varvec{b}}}$$ V b values were not significantly different between HCCs and background liver tissues. With the combined model, HCCs were found to have higher HPI, K 1 and k 2, k 3 and $${{\varvec{V}}}_{{\varvec{b}}}$$ V b values than background liver tissues; however, the k 4 value was not significantly different between HCCs and the background liver tissues. Conclusions Short-term PET is closely equivalent to fully dynamic PET for liver kinetic estimation. Short-term PET-derived kinetic parameters can be used to distinguish HCC from background liver tissue, and the combined model improves the kinetic estimation. Clinical relevance statement Short-term PET could be used for hepatic kinetic parameter estimation. The combined model could improve the estimation of liver kinetic parameters. Graphical Abstract

Abstract The PandaX-III experiment uses a high-pressure xenon gaseous time projection chamber (TPC) to search for the neutrinoless double beta decay (0νββ) of 136Xe. The absence of the vertex position in the electron drift direction at which the event takes place in the detector limits the PandaX-III TPC’s performance. The charged particle tracks recorded by the TPC provide a possibility for vertex reconstruction. In this paper, a convolution neural network (CNN) model VGGZ0net is proposed for the reconstruction of vertex position. An 11 cm precision is achieved with the Monte Carlo simulation events uniformly distributed along a maximum drift distance of 120 cm. The electron loss during the drift under the different gas conditions is studied, and after the distance-based correction, the detector energy resolution is significantly improved. The CNN model is also verified successfully using the experimental data of the PandaX-III prototype detector.

Abstract Glioma is the most common malignant tumor of the central nervous system in adults. The tumor microenvironment (TME) is related to poor prognosis in glioma patients. Glioma cells could sort miRNA into exosomes to modify TME. And hypoxia played an important role in this sorting process, but the mechanism is not clear yet. Our study was to find miRNAs sorted into glioma exosomes and reveal the sorting process. Sequencing analysis of glioma patients cerebrospinal fluid (CSF) and tissue showed that miR-204-3p tends to be sorted into exosomes. miR-204-3p suppressed glioma proliferation through the CACNA1C/MAPK pathway. hnRNP A2/B1 can accelerate exosome sorting of miR-204-3p by binding a specific sequence. Hypoxia plays an important role in exosome sorting of miR-204-3p. Hypoxia can upregulate miR-204-3p by upregulating the translation factor SOX9. Hypoxia promotes the transfer of hnRNP A2/B1 to the cytoplasm by upregulating SUMOylation of hnRNP A2/B1 to eliminate miR-204-3p. Exosomal miR-204-3p promoted tube formation of vascular endothelial cells through the ATXN1/STAT3 pathway. The SUMOylation inhibitor TAK-981 can inhibit the exosome-sorting process of miR-204-3p to inhibit tumor growth and angiogenesis. This study revealed that glioma cells can eliminate the suppressor miR-204-3p to accelerate angiogenesis under hypoxia by upregulating SUMOylation. The SUMOylation inhibitor TAK-981 could be a potential drug for glioma. This study revealed that glioma cells can eliminate the suppressor miR-204-3p to accelerate angiogenesis under hypoxia by upregulating SUMOylation. The SUMOylation inhibitor TAK-981 could be a potential drug for glioma.

Craniotomy is an invasive operation with great trauma and many complications, and patients undergoing craniotomy should enter the ICU for monitoring and treatment. Based on electronic medical records (EMR), the discovery of high-risk multi-biomarkers rather than a single biomarker that may affect the length of ICU stay (LoICUS) can provide better decision-making or intervention suggestions for clinicians in ICU to reduce the high medical expenses of these patients and the medical burden as much as possible. The multi-biomarkers or medical decision rules can be discovered according to some interpretable predictive models, such as tree-based methods. Our study aimed to develop an interpretable framework based on real-world EMRs to predict the LoICUS and discover some high-risk medical rules of patients undergoing craniotomy. The EMR datasets of patients undergoing craniotomy in ICU were separated into preoperative and postoperative features. The paper proposes a framework called Rules-TabNet (RTN) based on the datasets. RTN is a rule-based classification model. High-risk medical rules can be discovered from RTN, and a risk analysis process is implemented to validate the rules discovered by RTN. The performance of the postoperative model was considerably better than that of the preoperative model. The postoperative RTN model had a better performance compared with the baseline model and achieved an accuracy of 0.76 and an AUC of 0.85 for the task. Twenty-four key decision rules that may have impact on the LoICUS of patients undergoing craniotomy are discovered and validated by our framework. The proposed postoperative RTN model in our framework can precisely predict whether the patients undergoing craniotomy are hospitalized for too long (more than 15 days) in the ICU. We also discovered and validated some key medical decision rules from our framework.

ObjectiveThe Omicron BA.5.2 variant of SARS-CoV-2 has undergone several evolutionary adaptations, leading to multiple subvariants. Rapid and accurate characterization of these subvariants is essential for effective treatment, particularly in critically ill patients. This study leverages Next-Generation Sequencing (NGS) to elucidate the clinical and immunological features across different Omicron BA.5.2 subvariants.MethodsWe enrolled 28 patients infected with the Omicron variant, hospitalized in Zhangjiajie People’s Hospital, Hunan, China, between January 20, 2023, and March 31, 2023. Throat swabs were collected upon admission for NGS-based identification of Omicron subvariants. Clinical data, including qSOFA scores and key laboratory tests, were collated. A detailed analysis of lymphocyte subsets was conducted to ascertain the extent of immune cell damage and disease severity.ResultsPatients were infected with various Omicron subvariants, including BA.5.2.48, BA.5.2.49, BA.5.2.6, BF.7.14, DY.1, DY.2, DY.3, and DY.4. Despite having 43 identical mutation sites, each subvariant exhibited unique marker mutations. Critically ill patients demonstrated significant depletion in total lymphocyte count, T cells, CD4, CD8, B cells, and NK cells (P < 0.05). However, there were no significant differences in clinical and immunological markers across the subvariants.ConclusionThis study reveals that critically ill patients infected with different Omicron BA.5.2 subvariants experience similar levels of cellular immune dysfunction and inflammatory response. Four mutations - ORF1a:K3353R, ORF1a:L3667F, ORF1b:S997P, S:T883I showed correlation with immunological responses although this conclusion suffers from the small sample size. Our findings underscore the utility of NGS in the comprehensive assessment of infectious diseases, contributing to more effective clinical decision-making.

Abstract Background Thymosin family genes (TMSs), biologically important peptides with diverse intracellular and extracellular functions, have been shown to promote the progression of multiple cancers. However, multiomics characterization of TMSs and their role in human cancer prognosis has not been systematically performed. Methods We performed a comprehensive analysis of TMSs and thymosin β10 (TMSB10) using multiomics data from more than 10,000 tumor samples of 33 cancer types from The Cancer Genome Atlas (TCGA). We used single-sample gene set enrichment analysis (ssGSEA) and the gene set variation analysis (GSVA) algorithm to investigate the differences in tumor microenvironment (TME) cell infiltration and functional annotation for individual tumor samples, respectively. The role of TMSB10 in the malignant progression of glioma, the promotion of macrophage infiltration,and immunosuppressive polarization, and the combination drug efficacy were assessed via biological function assays. Results We comprehensively assessed genomic mutations, expression dysregulation, prognosis and immunotherapeutic response across 33 human cancer samples and showed that TMSB10 is specifically overexpressed in almost all types of cancer tissues. Further pan-cancer analysis showed that TMSB10 is closely related to the biological function, immune regulation and prognosis of glioma. Similar results were also found in several public glioma cohorts and our Qilu local cohort. Further integration with other biological experiments revealed the key roles of TMSB10 in the malignant progression of glioma, the promotion of macrophage infiltration and immunosuppressive polarization. We also identified multiple drugs targeting cells with high TMSB10 expression and validated that knockdown of TMSB10 improved the efficacy of selumetinib (a MEK1/2 inhibitor approved by the FDA for the treatment of neurofibromatosis-associated tumors) and anti-PD1 treatment in glioma. Conclusion These results indicate that TMSB10 holds promise as a novel prognostic marker and therapeutic target, providing a theoretical basis for the development of more effective and targeted clinical treatment strategies for glioma patients.

The effluent discharge produced in the textile printing and dyeing, leather and other fields, will cause the irreversible environmental pollution and extremely threatening safety of living organisms. The appropriate and efficient disposal method of dyestuff originated wastewater has been widely concerned in the past decades. In this study, the recrystallization of 1,3,5-benzene tricarboxylic acid (RCTMA) was put forward via a hydrothermal method to form the supramolecular RCTMA-based hexamer and thereafter assembled into the porous nano-bacterial cellulose (NBC) to construct the RCTMA@NBC composite. The morphology and surface properties of RCTMA@NBC were examined by scanning electron microscope, X-ray diffraction, and Fourier transform infrared spectroscopy. This RCTMA@NBC was employed to adsorb methylene blue (MB) adjusting the pH, temperature, and dosage of adsorbent. The result showed the maximal absorption capacity of RCTMA@NBC appeared under pH = 7.1 and higher temperature will hinder the adsorption of dyes. Moreover, the adsorption isotherms and kinetics were evaluated which was more confirmed to Langmuir model and quasi-second-order kinetic equation, and the simulated maximum adsorption capacities of MB was 1162.12 mg/g. Moreover, cationic golden XGL and anionic brilliant crocein were selected to further verify the distinct adsorptive behavior. The excellent affinity towards cationic dyes proved the easy combination was based on the chemical force originated from mutual attraction between opposite charges, π–π interactions, and H-bonding, whereas the poor attraction for brilliant crocein was due to the electrostatic repulsion between sulfonic and carboxyl groups. The synthesized RCTMA@NBC possesses higher efficiency and selective adsorption, which exhibits the promising potential in the field of precise treatment of organic dye wastewater.

Abstract Background Resistance to temozolomide (TMZ) is a major obstacle to preventing glioblastoma (GBM) recurrence after surgery. Although long noncoding RNAs (lncRNAs) play a variety of roles in GBM, the lncRNAs that regulate TMZ resistance have not yet been clearly elucidated. This study aims to identify lncRNAs that may affect TMZ treatment sensitivity and to explore novel therapeutic strategies to overcome TMZ resistance in GBM. Methods LncRNAs associated with TMZ resistance were identified using the Cancer Cell Line Encyclopedia (CCLE) and Genomics of Drug Sensitivity in Cancer (GDSC) datasets. Quantitative real-time PCR (qRT–PCR) was used to determine the expression of PDIA3P1 in TMZ-resistant and TMZ-sensitive GBM cell lines. Both gain-of-function and loss-of-function studies were used to assess the effects of PDIA3P1 on TMZ resistance using in vitro and in vivo assays. Glioma stem cells (GSCs) were used to determine the effect of PDIA3P1 on the GBM subtype. The hypothesis that PDIA3P1 promotes proneural-to-mesenchymal transition (PMT) was established using bioinformatics analysis and functional experiments. RNA pull-down and RNA immunoprecipitation (RIP) assays were performed to examine the interaction between PDIA3P1 and C/EBPβ. The posttranslational modification mechanism of C/EBPβ was verified using ubiquitination and coimmunoprecipitation (co-IP) experiments. CompuSyn was leveraged to calculate the combination index (CI), and the antitumor effect of TMZ combined with nefllamapimod (NEF) was validated both in vitro and in vivo. Results We identified a lncRNA, PDIA3P1, which was upregulated in TMZ-resistant GBM cell lines. Overexpression of PDIA3P1 promoted the acquisition of TMZ resistance, whereas knockdown of PDIA3P1 restored TMZ sensitivity. PDIA3P1 was upregulated in MES-GBM, promoted PMT progression in GSCs, and caused GBMs to be more resistant to TMZ treatment. Mechanistically, PDIA3P1 disrupted the C/EBPβ-MDM2 complex and stabilized the C/EBPβ protein by preventing MDM2-mediated ubiquitination. Expression of PDIA3P1 was upregulated in a time- and concentration-dependent manner in response to TMZ treatment, and TMZ-induced upregulation of PDIA3P1 was mediated by the p38α-MAPK signaling pathway. NEF is a small molecule drug that specifically targets p38α with excellent blood–brain barrier (BBB) permeability. NEF blocked TMZ-responsive PDIA3P1 upregulation and produced synergistic effects when combined with TMZ at specific concentrations. The combination of TMZ and NEF exhibited excellent synergistic antitumor effects both in vitro and in vivo. Conclusion PDIA3P1 promotes PMT by stabilizing C/EBPβ, reducing the sensitivity of GBM cells to TMZ treatment. NEF inhibits TMZ-responsive PDIA3P1 upregulation, and NEF combined with TMZ provides better antitumor effects.

Abstract PandaX-4T is a ton-scale dark matter direct detection experiment using a dual-phase TPC technique at the China Jinping Underground Laboratory. Various ultra-low background technologies have been developed and applied to material screening for PandaX-4T, including HPGe gamma spectroscopy, ICP-MS, NAA, radon emanation measurement system, krypton assay station, and alpha detection system. Low background materials were selected to assemble the detector. Surface treatment procedures were investigated to further suppress radioactive background. Combining measured results and Monte Carlo simulation, the total material background rates of PandaX-4T in the energy region of 1–25 keVee are estimated to be (9.9 ± 1.9) × 10 −3 mDRU for electron recoil and (2.8 ± 0.6) × 10 −4 mDRU for nuclear recoil. In addition, natKr in the detector is estimated to be < 8 ppt.

Abstract Clear evidence shows that tumors could secrete microRNAs (miRNAs) via exosomes to modulate the tumor microenvironment (TME). However, the mechanisms sorting specific miRNAs into exosomes are still unclear. In order to study the biological function and characterization of exosomal miRNAs, we performed whole-transcriptome sequencing in 59 patients’ whole-course cerebrospinal fluid (CSF) small extracellular vesicles (sEV) and matched glioma tissue samples. The results demonstrate that miRNAs could be divided into exosome-enriched miRNAs (ExomiRNAs) and intracellular-retained miRNAs (CLmiRNAs), and exosome-enriched miRNAs generally play a dual role. Among them, miR-1298-5p was enriched in CSF exosomes and suppressed glioma progression in vitro and vivo experiments. Interestingly, exosomal miR-1298-5p could promote the immunosuppressive effects of myeloid-derived suppressor cells (MDSCs) to facilitate glioma. Therefore, we found miR-1298-5p had different effects on glioma cells and MDSCs. Mechanically, downstream signaling pathway analyses showed that miR-1298-5p plays distinct roles in glioma cells and MDSCs via targeting SETD7 and MSH2, respectively. Moreover, reverse verification was performed on the intracellular-retained miRNA miR-9-5p. Thus, we confirmed that tumor-suppressive miRNAs in glioma cells could be eliminated through exosomes and target tumor-associated immune cells to induce tumor-promoting phenotypes. Glioma could get double benefit from it. These findings uncover the mechanisms that glioma selectively sorts miRNAs into exosomes and modulates tumor immunity.

As one of the most common post-transcriptional modifications of mRNAs and noncoding RNAs, N6-methyladenosine (m6A) modification regulates almost every aspect of RNA metabolism. Evidence indicates that dysregulation of m6A modification and associated proteins contributes to glioblastoma (GBM) progression. However, the function of fat mass and obesity-associated protein (FTO), an m6A demethylase, has not been systematically and comprehensively explored in GBM. Here, we found that decreased FTO expression in clinical specimens correlated with higher glioma grades and poorer clinical outcomes. Functionally, FTO inhibited growth and invasion in GBM cells in vitro and in vivo. Mechanistically, FTO regulated the m6A modification of primary microRNA-10a (pri-miR-10a), which could be recognized by reader HNRNPA2B1, recruiting the microRNA microprocessor complex protein DGCR8 and mediating pri-miR-10a processing. Furthermore, the transcriptional activity of FTO was inhibited by the transcription factor SPI1, which could be specifically disrupted by the SPI1 inhibitor DB2313. Treatment with this inhibitor restored endogenous FTO expression and decreased GBM tumor burden, suggesting that FTO may serve as a novel prognostic indicator and therapeutic molecular target of GBM.

Abstract Background Kinetic parameters estimated with dynamic 18F-FDG PET/CT can help to characterize hepatocellular carcinoma (HCC). We aim to evaluate the feasibility of the gravitational search algorithm (GSA) for kinetic parameter estimation and to propose a dynamic chaotic gravitational search algorithm (DCGSA) to enhance parameter estimation. Methods Five-minute dynamic PET/CT data of 20 HCCs were prospectively enrolled, and the kinetic parameters k 1 ~ k 4 and the hepatic arterial perfusion index (HPI) were estimated with a dual-input three-compartment model based on nonlinear least squares (NLLS), GSA and DCGSA. Results The results showed that there were significant differences between the HCCs and background liver tissues for k 1, k 4 and the HPI of NLLS; k 1, k 3, k 4 and the HPI of GSA; and k 1, k 2, k 3, k 4 and the HPI of DCGSA. DCGSA had a higher diagnostic performance for k 3 than NLLS and GSA. Conclusions GSA enables accurate estimation of the kinetic parameters of dynamic PET/CT in the diagnosis of HCC, and DCGSA can enhance the diagnostic performance.

Abstract Background Gliomas are the most common malignant primary brain tumours with a highly immunosuppressive tumour microenvironment (TME) and poor prognosis. Circular RNAs (circRNA), a newly found type of endogenous noncoding RNA, characterized by high stability, abundance, conservation, have been shown to play an important role in the pathophysiological processes and TME remodelling of various tumours. Methods CircRNA sequencing analysis was performed to explore circRNA expression profiles in normal and glioma tissues. The biological function of a novel circRNA, namely, circNEIL3, in glioma development was confirmed both in vitro and in vivo. Mechanistically, RNA pull-down, mass spectrum, RNA immunoprecipitation (RIP), luciferase reporter, and co-immunoprecipitation assays were conducted. Results We identified circNEIL3, which could be cyclized by EWS RNA-binding protein 1(EWSR1), to be upregulated in glioma tissues and to correlate positively with glioma malignant progression. Functionally, we confirmed that circNEIL3 promotes tumorigenesis and carcinogenic progression of glioma in vitro and in vivo. Mechanistically, circNEIL3 stabilizes IGF2BP3 (insulin-like growth factor 2 mRNA binding protein 3) protein, a known oncogenic protein, by preventing HECTD4-mediated ubiquitination. Moreover, circNEIL3 overexpression glioma cells drives macrophage infiltration into the tumour microenvironment (TME). Finally, circNEIL3 is packaged into exosomes by hnRNPA2B1 and transmitted to infiltrated tumour associated macrophages (TAMs), enabling them to acquire immunosuppressive properties by stabilizing IGF2BP3 and in turn promoting glioma progression. Conclusions This work reveals that circNEIL3 plays a nonnegligible multifaceted role in promoting gliomagenesis, malignant progression and macrophage tumour-promoting phenotypes polarization, highlighting that circNEIL3 is a potential prognostic biomarker and therapeutic target in glioma.

m6Am is a modification of the 5′ end of mRNAs catalyzed by PCIF1. Here, Zhang et al. show that HIV infection induces a decrease in m6Am of cellular mRNAs through Vpr-mediated PCIF1 ubiquitination and degradation, resulting in increased HIV replication through regulation of host transcription factors.

We present the constraints on the axial-vector and pseudo-scalar mediated WIMP-nucleus interactions from the PandaX-4T experiment, using the data set corresponding to a total exposure of 0.63 tonne⋅year. No significant signal excess is observed, and the most stringent constraints to date on the mediator mass are set for the axial-vector and pseudo-scalar simplified models. The maximum excluded mass of an axial-vector mediator is 825 GeV/c2 and that of a pseudo-scalar mediator is 106 GeV/c2. In addition, the upper limits on the spin-dependent WIMP-nucleon scattering cross-section for conventional neutron-only and proton-only interactions are derived.

In the two-component Majorana dark matter model, one dark matter particle can scatter off the target nuclei, and turn into a slightly heavier component. In the framework of a simplified model with a vector boson mediator, both the tree-level and loop-level processes contribute to the signal in direct detection experiment. In this paper, we report the search results for such dark matter from PandaX-II experiment, using total data of the full 100.7 tonne⋅day exposure. No significant excess is observed, so strong constraints on the combined parameter space of mediator mass and dark matter mass are derived. With the complementary search results from collider experiments, a large range of parameter space can be excluded.

Significant efforts on construction of smart drug delivery for developing minimally invasive gelling system to prolong local delivery of bisphosphonates are considered as promising perspectives for the bone-related diseases, which provide the hydrogels with unique bioactivities for bone repair in clinic. Herein, we have constructed an alendronate (ALN)-conjoined injectable tetra-PEG hydrogel with excellent biocompatibility, uniform network, and favorable mechanical properties in one-pot strategy. In views of the quick ammonolysis reaction between N-hydroxysuccinimide (NHS)-ester of tetra-PEG-SG and amine groups of tetra-PEG-NH2 polymer and ALN molecules, the uniform networks were formed within seconds along with the easy injection, favorable biocompatibility and mechanical properties for hydrogel scaffolds. On account of the simultaneous physical encapsulation and chemical linkage of the ALN within the hydrogels, the ALN-conjoined tetra-PEG hydrogel exhibited a sustained drug release delivery that could persistently and effectively facilitate viability, growth, proliferation, and osteogenesis differentiation of stem cells, thereby allowing the consequent adaptation of hydrogels into the bone defects with irregular shapes, which endowed the ALN-conjoined tetra-PEG hydrogel with depot formulation capacity for governing the on-demand release of ALN drugs. Consequently, the findings imply that these drug-based tetra-PEG hydrogels mediate optimal release of therapeutic cargoes and effective promotion of in situ bone regeneration, which will be broadly utilized as therapeutic scaffolds in tissue engineering and regenerative medicine.

Abstract With the application of advanced composite materials in High-Aspect-Ratio wings (HARW), the randomness of structural parameters, such as elastic modulus and Poisson's ratio, is enhanced. Hence, in order to explore the whole picture of aeroelastic problems, it is of great significance to study the role of random structural parameters in aeroelastic problems. In this paper, the dynamic response of flexible HARW considering random structural parameters is analyzed. An aeroelastic model of a one-dimensional cantilevered Euler–Bernoulli beam considering aerodynamic forces acting on the wing is established based on Hamilton's principle. Adopted the idea of simplifying calculation, the effect of random structural parameters is analyzed. Then, considering the elastic modulus and torsional stiffness as continuously one-dimensional random field functions, and discretized by local method. The first and second order recursive stochastic nonlinear finite element equations of wing are derived by using perturbation method. Based on it, statistical expression of aeroelastic effects of the wing is derived. Monte Carlo method is adopted to verify the effectiveness of the method. Numerical simulations indicate that the method proposed can well mirror the statistical characteristics of aeroelastic response.

Abstract Particle tracks and differential energy loss measured in high pressure gaseous detectors can be exploited for event identification in neutrinoless double beta decay (0νββ) searches. We develop a new method based on Kalman Filter in a Bayesian formalism (KFB) to reconstruct meandering tracks of MeV-scale electrons. With simulation data, we compare the signal and background discrimination power of the KFB method assuming different detector granularities and energy resolutions. Typical background from 232Th and 238U decay chains can be suppressed by another order of magnitude than that in published literatures, approaching the background-free regime. For the proposed PandaX-III experiment, the 0νββ search half-life sensitivity at the 90% confidence level would reach 2.7× 1026 yr with 5-year live time, a factor of 2.7 improvement over the initial design target.

Eye lens cells are highly enriched in cholesterol that sustains lens transparency, and disruption of cholesterol biosynthesis leads to cataracts. The authors show that cholesterol biosynthesis regulated by Qki is essential for maintenance of membrane integrity of lens cells and proper protein folding.

Abstract Exosomes participate in intercellular communication and glioma microenvironment modulation, but the exact mechanisms by which glioma-derived exosomes (GDEs) promote the generation of the immunosuppressive microenvironment are still unclear. Here, we investigated the effects of GDEs on autophagy, the polarization of tumor-associated macrophages (TAMs), and glioma progression. Compared with normoxic glioma-derived exosomes (N-GDEs), hypoxic glioma-derived exosomes (H-GDEs) markedly facilitated autophagy and M2-like macrophage polarization, which subsequently promoted glioma proliferation and migration in vitro and in vivo. Western blot and qRT-PCR analyses indicated that interleukin 6 (IL-6) and miR-155-3p were highly expressed in H-GDEs. Further experiments showed that IL-6 and miR-155-3p induced M2-like macrophage polarization via the IL-6-pSTAT3-miR-155-3p-autophagy-pSTAT3 positive feedback loop, which promotes glioma progression. Our study clarifies a mechanism by which hypoxia and glioma influence autophagy and M2-like macrophage polarization via exosomes, which could advance the formation of the immunosuppressive microenvironment. Our findings suggest that IL-6 and miR-155-3p may be novel biomarkers for diagnosing glioma and that treatments targeting autophagy and the STAT3 pathway may contribute to antitumor immunotherapy.

Abstract Transplanting trees with rhizospheric soil is an important way to facilitate tree survival in the process of landscaping and reforestation. Traditional way to prevent looseness of rhizospheric soil is forming soil balls around the roots with bags, boxes or rope wrapping, which is cumbersome, laborious and easy to break. This study is aimed to develop a new type of degradable environment-friendly polymer as soil consolidation agent to facilitate tree transplanting. In this paper, the KGM/CA/PVA ternary blending soil consolidation agent was prepared by using Konjac glucomannan (KGM), chitosan (CA) and polyvinyl alcohol (PVA) as raw materials. Through the verification and evaluation, the clay and sandy soil can be consolidated and formed into soil balls by the ternary blend adhesive, which was convenient for transportation. The preliminary application of the ternary blend adhesive in the transplanting process of sierra salvia, Japanese Spindle (Euonymus japonicus) and Juniperus sabina ‘Tamaricifolia’ confirmed that the application of soil consolidation agent can effectively solve the problem that the root ball of seedling is easily broken in the process of transplant. And the application of soil consolidation agent has no adverse effect on the growth of transplanted seedlings. The research and development of ternary blending soil consolidation agent and its preliminary application in seedling transplanting will provide a new solution to solve the problem of soil ball breakage in the process of seedling transplanting. This is an important stage in the development of new seedling transplanting technology. Therefore, the research and development of soil consolidation agent is of great significance.

ObjectivesShip collision is one of the main factors threatening the navigation safety of intelligent ships. A calculation model of ship collision risk should identify potential collision risks in time and provide the basic information for the intelligent ship's autonomous collision avoidance decision-making.MethodsThis paper first analyzes the domain-based collision risk parameter calculation model according to the degree of domain violation and other parameters. The navigation scene is divided into a single-ship encounter situation and an encounter between a ship and target ship group, and a new collision risk parameter calculation model for multi-ship encounters is given. Second, based on the Wiener process, the uncertainty of ship position prediction is modeled and obtained according to the Chi-squared distribution. Finally, a calculation method for collision risk parameters which considers the uncertainty of ship position prediction is given.ResultsOn this basis, the influence of ship position prediction uncertainty on ship collision risk is considered. ConclusionsThis method can further guarantee the safety of intelligent ships at sea.

Underground natural gas storage (UNGS) is an important part of the natural gas supply system to ensure a balanced energy supply. The surface system, as an important part of the gas storage, undertakes the functions of gas injection and gas production of the gas storage, and its investment economy is of vital importance. In fact, the UNGS surface pipeline network has two-way injection and production characteristics, which is different from the one-way production characteristics of conventional oil&gas gathering and transportation systems. This paper takes the minimum investment of the pipeline network as the objective function, considers the gas injection and gas withdrawal flow conditions and esablishes a mixed integer non-linear programming model (MINLP) for the surface pipeline network of the UNGS to optimize its pipeline layout and diameter parameters. Constraints including the well affiliation, the number of stations, the gathering radius, the processing capacity and the flow/pressure equilibrium equations, are also taken into consideration. Taking an UNGS in China as an example, the results of the optimal structure and diameter of the pipeline network, as well as the pipe flow, node pressure, and maximum/minimum flowrate during gas injection and gas withdrawal are obtained. Finally, the effects of constraints such as processing capacity and radius on the structure layout and investment of the UNGS are analyzed, verifying the reliability and effectiveness of the model.

Abstract This study aimed to develop and validate a novel rabbit fixator made from a thermoplastic mask for awake imaging experiments. When heated in a hot-water bath at 65–70 °C for 2–5 min, the thermoplastic mask became soft and could be molded to fit over the entire body of an anesthetized rabbit (4 ml of 3% pentobarbital sodium solution by intramuscular injection). Twenty rabbits were randomly divided into fixator (n = 10) and anesthesia (n = 10) groups. The animals’ vital signs, stress hormones (cortisol and adrenaline), and subjective image quality scores for the computed tomography (CT), positron emission tomography (PET), and magnetic resonance imaging (MRI) scanning were measured and compared. Phantom CT, MRI and PET studies were performed to assess the performance with and without the thermoplastic mask by using image agents at different concentrations or with different radioactivity. The respiration rate (RR), systolic blood pressure (SBP), diastolic blood pressure (DBP), peripheral capillary oxygen saturation (SpO2) and body temperature (T) decreased after anesthesia (all P 0.05). The heart rate (HR), cortisol and adrenaline did not significantly decrease after either anesthesia or fixation (all P > 0.05). The subjective image quality scores for the CT and MRI images of the head, thorax, liver, kidney, intestines and pelvis and the subjective image quality scores for the PET images did not significantly differ between the two groups (all P > 0.05). For all examined organs except the muscle, 18F-FDG metabolism was lower after fixation than after anesthesia, and was almost identical of liver between two groups. The phantom study showed that the CT values, standard uptake values and MR T2 signal values did not differ significantly with or without the mask (all P > 0.05). A novel rabbit fixator created using a thermoplastic mask could be used to obtain high-quality images for different imaging modalities in an awake and near-physiological state.

Recently, building an efficient and robust model for object detection has attracted the attention of the vision community. Although binary networks have a fast inference speed, they cannot be used directly on mobile devices such as unmanned aerial vehicles (UAVs) because of their low detection accuracy. Different from improving the detection accuracy of a binary network by adjusting the network structure or adjusting the update gradient, we propose an improved binary neural network based on the block scaling factor XNOR (BSF-XNOR) convolutional layer. In addition, we propose a two-level densely connected network structure, which further enhances the network layer’s feature representation capabilities. Experiments using the TensorFlow framework prove the effectiveness of our algorithm in improving accuracy. Compared with the original standard XNOR network, the mean average precision (mAP) detected by our algorithm on the PASCAL VOC dataset was improved. The experimental results on the VisDrone2019 UAV dataset confirm that our method achieves a better balance between speed and accuracy than previous methods. Our algorithm aims to guide and deploy high-precision binary networks on the embedded device and solves the problem of low-precision binary networks.

Collision risk identification is necessary for autonomous ships to recognize the risk when facing different encounter situations and make the proper collision avoidance decision. For achieving quantitative assessment of collision risk, this paper proposed a collision risk identification method based on field theory. Specifically, the method first combines the uncertainty model of ship position prediction to improve the quaternion ship domain (QSD). Then, based on the field theory and the situation of encounters, the ship risk field is constructed, which transform the ship domain overlapping index into the field energy superposition problem. The validation and superiority of this approach is examined by simulation studies. The results demonstrate that the proposed method can overcome some deficiencies of the conventional risk assessment methods. Moreover, the approach can effectively identify the collision risk in real time and provide a reference on furthering enhance the navigational safety for the autonomous ships. Therefore, the approach gives it a significant potential for use in collision risk identification in the future.

Abstract Background Glioma stem cells (GSCs) are considered the initial cells of gliomas, contributing to therapeutic resistance. Patient-derived GSCs well recapitulate the heterogeneity of their parent glioma tissues, which can be classified into different subtypes. Likewise, previous works identified GSCs as two distinct subtypes, mesenchymal (MES) and proneural (PN) subtypes, and with general recognition, the MES subtype is considered a more malignant phenotype characterized by high invasion and radioresistance. Therefore, understanding the mechanisms involved in the MES phenotype is necessary for glioblastoma treatment. Methods Data for bioinformatic analysis were obtained from The Cancer Genome Atlas (TCGA) and The Gene Expression Omnibus (GEO) database. An antibody was used to block cell surface glucose-regulated protein 78 (csGRP78). Apoptosis and cell cycle analyses were performed to evaluate radiation damage. Immunofluorescence staining was applied to assess protein expression and distribution. Mass spectrometry combined with bioinformatic analysis was used to screen downstream molecules. Intracranial GSC-derived xenografts were established for in vivo experiments. Results Total GRP78 expression was associated with MES GSC stemness, and csGRP78 was highly expressed in MES GSCs. Targeting csGRP78 suppressed the self-renewal and radioresistance of MES GSCs in vitro and in vivo, accompanied by downregulation of the STAT3, NF-κB and C/EBPβ pathways. Mass spectrometry revealed the potential downstream β-site APP-cleaving enzyme 2 (BACE2), which was regulated by csGRP78 via lysosomal degradation. Knockdown of BACE2 inactivated NF-κB and C/EBPβ and significantly suppressed the tumorigenesis and radioresistance of MES GSCs in vitro and in vivo. Conclusions Cell surface GRP78 was preferentially expressed in MES GSCs and played a pivotal role in MES phenotype maintenance. Thus, blocking csGRP78 in MES GSCs with a high-specificity antibody might be a promising novel therapeutic strategy.

The pathogenic mechanisms of cardiorenal syndrome type 4 (CRS4) remain unclear. Here, the authors identify IRF1-PGC1α axis-mediated myocardial energy metabolism remodeling as a contributor to CRS4 pathogenesis, thus providing potential new targets for reducing cardiovascular events in CKD patients.

Abstract Background Cullin-7 (CUL7) is a member of the DOC domain-containing cullin family and is involved in the regulation of cell transformation. However, the clinical significance, potential mechanism and upstream regulators of CUL7 in malignant gliomas remain to be determined. Methods Expression level data and clinical information were obtained via the Cancer Genome Atlas (TCGA) database, the Chinese Glioma Genome Atlas (CGGA) database, immunohistochemistry (IHC) and western blot analysis. Gene set enrichment analysis (GSEA) was used to explore the potential molecular mechanisms of CUL7. RNA silencing was performed using siRNA or lentiviral constructs in U87MG and U251 glioma cell lines and GSC267 glioma stem cells. CUL7 overexpression was performed using the GV141-CUL7 plasmid construct. In addition, overexpression of miR-3940-5p was performed and validated by quantitative real-time PCR (qRT-PCR). Cells were characterized in vitro or in vivo to evaluate their molecular status, cell proliferation, invasion, and migration by Cell Counting Kit (CCK)-8, EdU, flow cytometry, colony formation, Transwell and 3D tumour spheroid invasion assays. Coimmunoprecipitation (co-IP) and western blotting were performed to test the mechanisms of activation of the NF-κB signalling pathway. Results High CUL7 expression was associated with a high tumour grade, a mesenchymal molecular glioma subtype and a poor prognosis in patients. Gene silencing of CUL7 in U87MG and U251 cells significantly inhibited tumour growth, invasion and migration in vitro and in vivo. Western blot analysis revealed that cyclin-dependent kinase inhibitors and epithelial-mesenchymal transition (EMT) molecular markers changed under CUL7 silencing conditions. In contrast, CUL7 overexpression promoted tumour growth, invasion and migration. Gene set enrichment analysis (GSEA) and western blot analysis revealed that CUL7 was positively associated with the NF-κB pathway. Moreover, with coimmunoprecipitation assays, we discovered that CUL7 physically associated with MST1, which further led to ubiquitin-mediated MST1 protein degradation, which promoted activation of the NF-κB signalling pathway. Finally, CUL7 was found to be downregulated by miR-3940-5p, which suppressed the development of gliomas. Conclusions Our findings indicate that CUL7 plays a significant role in promoting tumorigenesis via NF-κB activation and that it can be negatively regulated by miR-3940-5p in human gliomas. Furthermore, CUL7 might be a candidate molecular target for the treatment of glioma.

Construction workers’ unsafe behavior is a major cause of safety accidents and injuries, therefore, a profound understanding of the formation process and evolution laws about construction workers’ unsafe behavior is conducive to taking measures to prevent incidents. At present, the new generation of construction workers (NGCWs) born after 1980 are gradually becoming the main force at construction sites in China. Given that generational differences of construction workers can cause the discrepancies in their thoughts and attitudes when engaging in safety-related activities, this study aims to investigate the formation mechanism and dynamic evolution laws about NGCWs’ unsafe behavior based on the context of China’s construction industry. From the perspective of behavior motivation, in-depth semi-structured interviews with 18 NGCWs and 7 grassroots managers were conducted, and data analysis followed a three-step coding process based on grounded theory. Through continuous comparison, abstraction and analysis, the stimulus-organism-response theory was introduced and expanded to construct a three-stage formation mechanism model. On this basis, the causal diagram and stock flow diagram were developed based on system dynamics principles to reflect the dynamic feedback relationships of the factors in the static formation mechanism model, and simulation was carried out using Vensim PLE software. The results show that three types of internal needs and three types of external incentives stimulate corresponding motivations for NGCWs’ unsafe behavior. Two types of individual factors, five types of situational factors and behavior result play an influencing role in the decision-making process of externalizing motivation into behavior. Under the synergistic effect of multiple factors, the level of unsafe behavior displays a downward trend, and the rate of decrease is slow first and then fast. Furthermore, among individual factors and situational factors, safety awareness and safety management system have the most significant effect on the level of unsafe behavior, while situational factors play a more obvious role. The findings can provide theoretical support and practical references to China’s construction companies and government departments for the purpose of improving NGCWs’ unsafe behavior.

BackgroundGlioblastoma (GBM) is a fatal brain tumor with no effective treatment. The specific GBM tumor immune microenvironment (TIME) may contribute to resistance to immunotherapy, a tumor therapy with great potential. Thus, an in-depth understanding of the characteristics of tumor-infiltrating immune cells is essential for exploring biomarkers in GBM pathogenesis and immunotherapy.MethodsWe estimated the relative abundances of 25 immune cell types in 796 GBM samples using single sample gene set enrichment analysis (ssGSEA). Unsupervised clustering was used to identify different GBM-associated TIME immune cell infiltration (GTMEI) patterns. The GTMEIscore system was constructed with principal component analysis (PCA) to determine the immune infiltration pattern of individual tumors.ResultsWe revealed three distinct GTMEI patterns with different clinical outcomes and modulated biological pathways. We developed a scoring system (GTMEIscore) to determine the immune infiltration pattern of individual tumors. We comprehensively analyzed the genomic characteristics, molecular subtypes and clinicopathological features as well as proteomic, phosphoproteomic, acetylomic, lipidomic and metabolomic properties associated with the GTMEIscore and revealed many novel dysregulated pathways and precise targets in GBM. Moreover, the GTMEIscore accurately quantified the immune status of many other cancer types. Clinically, the GTMEIscore was found to have significant potential therapeutic value for chemotherapy/radiotherapy, immune checkpoint inhibitor (ICI) therapy and targeted therapy.ConclusionsFor the first time, we employed a multilevel and multiplatform strategy to construct a multidimensional molecular map of tumors with different immune infiltration patterns. These results may provide theoretical basises for identifying more effective predictive biomarkers and developing more effective drug combination strategies or novel immunotherapeutic agents for GBM.

BackgroundPrevious studies have reported the effect of N7-methylguanosine (m7G) regulator methyltransferase like-1 protein (METTL1) in tumor initiation, metastasis, and chemosensitivity. However, the relationship between METTL1 and cancer immune infiltration is not validated and the prognostic significance of METTL1 in pan-cancer remains unclear.MethodsClinical parameters, including gender, age, lifetime, stage, and treatment response were analyzed to evaluate the prognostic significance of METTL1. To evaluate protein level of METTL1, the METTL1 activity was generated by single sample gene set enrichment analysis. The one-class logistic regression algorithm was used to calculate the stemness indices based on transcriptomics and methylation data of pan-cancer and pluripotent stem cells. The relationship between METTL1 expression or activity and tumor immune infiltration were analyzed to explore the significance of METTL1 in tumor immunotherapy. Meanwhile, the correlation between three immunotherapeutic biomarkers and METTL1 was investigated. Finally, to calculate the association between drug sensitivity and METTL1 expression, spearman correlation analysis was performed.ResultsMETTL1 was not intimately related to gender, age, tumor stage, or treatment outcome of the various cancers, but it displayed potential prognostic significance for evaluating patient survival. High METTL1 expression was related to tumor progression-relevant pathways. Moreover, METTL1 exhibited a distinct correlation with tumor immune microenvironment infiltration and stemness indices. In the anti-PD-L1 cohort, patients in treatment response group exhibited significantly higher METTL1 expression than those in the no/limited response group. Further analysis showed that tumor cell lines with higher METTL1 expression were more sensitive to drugs targeting chromatin histone methylation, ERK-MAPK and WNT signaling pathways.ConclusionThis study provides insight into the correlation of METTL1 with tumor immune infiltration and stemness in pan-cancer, revealing the significance of METTL1 for cancer progression and guiding more effective and generalized therapy strategies.

Merchant ships sometimes fail to detect small ships at night and in poor visibility, leading to urgent situations and even collisions. Infrared (IR) cameras have inherent advantages in small target detection and become essential environmental awareness equipment on unmanned ships. The existing target detection models are complex and difficult to deploy on small devices. Lightweight detection algorithms are needed with the increase in the number of shipborne cameras. Therefore, herein, a lightweight model for small IR ship detection was selected as the research object. IR videos were collected in the Bohai Strait, the image sampling interval was calculated, and an IR dataset of small ships was constructed. Based on the analysis of the characteristics of the IR ship images, gamma transform was used to preprocess the images, which increased the gray difference between the target and background. The backbone of YOLOv5 was replaced with that of Mobilev3 to improve the computing efficiency. Finally, the results showed that the parameters of the proposed model were reduced by 83% compared with those of the YOLOv5m model, while the detection performance was almost the same.

To solve the multi-ship interaction problem under the scenario of multi-modal ships, this paper designed a ship Mobile Ad hoc Network (MANET) dominated by an autonomous ship. Foremost, we discussed the development and status of autonomous ships, proposed the inevitability of multi-modal ship scenarios, and analyzed the applicability of ad hoc networks in maritime communication. After that, a ship MANET under the guidance of an autonomous ship was designed, including the system composition, network mode, and network management method. We built the ship MANET connectivity model and analyzed its attributes. In addition, the transmission capacity of the ship as a network node is also analyzed. In conclusion, we believe that the ship MANET is feasible and effective in the scenario of multi-modal ships.