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Abstract Background Preeclampsia, especially early-onset preeclampsia (EO-PE), is a pregnancy complication that has serious consequences for the health of both the mother and the fetus. Although abnormal placentation due to mitochondrial dysfunction is speculated to contribute to the development of EO-PE, the underlying mechanisms have yet to be fully elucidated. Methods The expression and localization of Siglec-6 in the placenta from normal pregnancies, preterm birth and EO-PE patients were examined by RT-qPCR, Western blot and IHC. Transwell assays were performed to evaluate the effect of Siglec-6 on trophoblast cell migration and invasion. Seahorse experiments were conducted to assess the impact of disrupting Siglec-6 expression on mitochondrial function. Co-IP assay was used to examine the interaction of Siglec-6 with SHP1/SHP2. RNA-seq was employed to investigate the mechanism by which Siglec-6 inhibits mitochondrial function in trophoblast cells. Results The expression of Siglec-6 in extravillous trophoblasts is increased in placental tissues from EO-PE patients. Siglec-6 inhibits trophoblast cell migration and invasion and impairs mitochondrial function. Mechanismly, Siglec-6 inhibits the activation of NF-κB by recruiting SHP1/SHP2, leading to increased expression of GPR20. Notably, the importance of GPR20 function downstream of Siglec-6 in trophoblasts is supported by the observation that GPR20 downregulation rescues defects caused by Siglec-6 overexpression. Finally, overexpression of Siglec-6 in the placenta induces a preeclampsia-like phenotype in a pregnant mouse model. Conclusions This study indicates that the regulatory pathway Siglec-6/GPR20 has a crucial role in regulating trophoblast mitochondrial function, and we suggest that Siglec-6 and GPR20 could serve as potential markers and targets for the clinical diagnosis and therapy of EO-PE.

Hot tensile features in a Ni–Cr–Mo-based superalloy with different notched types are explored. Changes of microstructure and fracture mechanisms with stress triaxiality and tensile parameters are elucidated. Results manifest that the maximum load for the Ni–Cr–Mo-based superalloy in hot tensile ascends with increasing stress triaxiality. The development/interaction of dislocation clusters and subgrains is sensibly boosted, while the dynamic recrystallization (DRX) formation/coarsening behaviors is suppressed with ascending stress triaxiality or strain rate. Nevertheless, the intense generation/development in substructure and DRX grains appear at higher tensile temperature. The primary fracture mode is the ductile facture closely associated with dimples formation/coalescence and the progression of serpentine gliding. The primary fracture mechanism of Ni–Cr–Mo-based superalloy is the shear fracture characterized by the microporous polymerization. The coalescence/growing up in dimples becomes weaken with reducing stress triaxiality. Additionally, the dominant texture components are the E, F and Copper textures for the Ni–Cr–Mo-based superalloy with notched type in high-temperature tensile. With increasing stress triaxiality, the S texture sensibly increases.

BackgroundSpontaneous preterm birth (sPTB) is a global disease that is a leading cause of death in neonates and children younger than 5 years of age. However, the etiology of sPTB remains poorly understood. Recent evidence has shown a strong association between metabolic disorders and sPTB. To determine the metabolic alterations in sPTB patients, we used various bioinformatics methods to analyze the abnormal changes in metabolic pathways in the preterm placenta via existing datasets.MethodsIn this study, we integrated two datasets (GSE203507 and GSE174415) from the NCBI GEO database for the following analysis. We utilized the “Deseq2” R package and WGCNA for differentially expressed genes (DEGs) analysis; the identified DEGs were subsequently compared with metabolism-related genes. To identify the altered metabolism-related pathways and hub genes in sPTB patients, we performed multiple functional enrichment analysis and applied three machine learning algorithms, LASSO, SVM-RFE, and RF, with the hub genes that were verified by immunohistochemistry. Additionally, we conducted single-sample gene set enrichment analysis to assess immune infiltration in the placenta.ResultsWe identified 228 sPTB-related DEGs that were enriched in pathways such as arachidonic acid and glutathione metabolism. A total of 3 metabolism-related hub genes, namely, ANPEP, CKMT1B, and PLA2G4A, were identified and validated in external datasets and experiments. A nomogram model was developed and evaluated with 3 hub genes; the model could reliably distinguish sPTB patients and term labor patients with an area under the curve (AUC) > 0.75 for both the training and validation sets. Immune infiltration analysis revealed immune dysregulation in sPTB patients.ConclusionThree potential hub genes that influence the occurrence of sPTB through shadow participation in placental metabolism were identified; these results provide a new perspective for the development and targeting of treatments for sPTB.

Abstract Glioblastoma multiforme (GBM) is the most aggressive and lethal subtype of gliomas of the central nervous system. The efficacy of sonodynamic therapy (SDT) against GBM is significantly reduced by the expression of apoptosis‐inhibitory proteins in GBM cells. In this study, an intelligent nanoplatform (denoted as Aza‐BD@PC NPs) based on the aza‐boron‐dipyrromethene dye and phenyl chlorothionocarbonate‐modified DSPE‐PEG molecules is developed for synergistic ferroptosis‐enabled gas therapy (GT) and SDT of GBM. Once internalized by GBM cells, Aza‐BD@PC NPs showed effective cysteine (Cys) consumption and Cys‐triggered hydrogen sulfide (H2S) release for ferroptosis‐enabled GT, thereby disrupting homeostasis in the intracellular environment, affecting GBM cell metabolism, and inhibiting GBM cell proliferation. Additionally, the released Aza‐BD generated abundant singlet oxygen (1O2) under ultrasound irradiation for favorable SDT. In vivo and in vitro evaluations demonstrated that the combined functions of Cys consumption, H2S production, and 1O2 production induced significant death of GBM cells and markedly inhibited tumor growth, with an impressive inhibition rate of up to 97.5%. Collectively, this study constructed a cascade nanoreactor with satisfactory Cys depletion performance, excellent H2S release capability, and prominent reactive oxygen species production ability under ultrasound irradiation for the synergistic ferroptosis‐enabled GT and SDT of gliomas.

Abstract Introduction Nonsteroidal anti-inflammatory drugs (NSAIDs) are the primary treatment for osteoarthritis (OA), but prolonged use has adverse effects and varying efficacy. Among NSAIDs, imrecoxib, a selective cyclooxygenase-2 (COX-2) inhibitor, reduces side effects yet remains ineffective for half of the patient population. This study aims to identify biomarkers for early evaluation of imrecoxib efficacy in OA for personalized therapy optimization. Methods From September 2021 to January 2022, imrecoxib was administered to patients with OA at Nanjing Drum Tower Hospital. Plasma samples from these patients underwent proteomic analysis through the four-dimensional data-independent acquisition (4D-DIA) method, followed by bioinformatics analysis. Potential differentially expressed proteins (DEPs) were validated using enzyme-linked immunosorbent assays (ELISA). Results Sixty-six patients with knee OA were included and divided into responders (n = 35) and non-responders (n = 31). Proteomic analysis was conducted on 15 patients from each group, with ELISA validation for every patient. We found 140 DEPs between the two groups after imrecoxib treatment, characterized by 29 proteins showing upregulation and 111 displaying downregulation (P ± 1.2). Galectin-1 (LGALS1), galectin-3 (LGALS3), and cluster of differentiation 44 (CD44) were identified as potential markers for evaluating clinical response to imrecoxib in OA following ELISA validation. Conclusion This study successfully identified biomarkers for evaluating imrecoxib’s clinical response in patients with OA using 4D-DIA technology. These biomarkers may play a vital role in future personalized OA treatment strategies, pending further confirmation.

Osteosarcoma, one of the most common primary malignancies in children and adolescents, has the primary characteristics of a poor prognosis and high rate of metastasis. This study used super-enhancer-related genes derived from two different cell lines to construct five novel super-enhancer-related gene prognostic models for patients with osteosarcoma. The training and testing datasets were used to confirm the prognostic models of the five super-enhancer-related genes, which resulted in an impartial predictive element for osteosarcoma. The immunotherapy and prediction of the response to anticancer drugs have shown that the risk signature of the five super-enhancer-related genes positively correlate with chemosensitivity. Furthermore, functional analysis of the risk signature genes revealed a significant relationship between gene groups and the malignant characteristics of tumours. TNF Receptor Superfamily Member 11b (TNFRSF11B) was selected for functional verification. Silencing of TNFRSF11B suppressed the proliferation, migration, and invasion of osteosarcoma cells in vitro and suppressed osteosarcoma growth in vivo. Moreover, transcriptome sequencing was performed on MG-63 cells to study the regulatory mechanism of TNFRSF11B in osteosarcoma cells, and it was discovered that TNFRSF11B is involved in the development of osteosarcoma via the phosphoinositide 3-kinase signalling pathway. Following the identification of TNFRSF11B as a key gene, we selected an inhibitor that specifically targeted this gene and performed molecular docking simulations. In addition, risedronic acid inhibited osteosarcoma growth at both cellular and molecular levels. In conclusion, the super-enhancer-related gene signature is a viable therapeutic tool for osteosarcoma prognosis and treatment.

Abstract Background The pathogenesis of intrahepatic cholestasis of pregnancy (ICP) remains unknown. The gut microbiome and its metabolites play important roles in bile acid metabolism, and previous studies have indicated the association of the gut microbiome with ICP. Methods We recruited a cohort of 5100 participants, and 20 participants were enrolled in the severe ICP group, matched with 20 participants in the mild ICP group and 20 controls. 16S rRNA sequencing and nontargeting metabolomics were adapted to explore the gut microbiome and fecal metabolites. Results An increase in richness and a dramatic deviation in composition were found in the gut microbiome in ICP. Decreased Firmicutes and Bacteroidetes abundances and increased Proteobacteria abundances were found in women with severe but not mild ICP compared to healthy pregnant women. Escherichia-Shigella and Lachnoclostridium abundances increased, whereas Ruminococcaceae abundance decreased in ICP group, especially in severe ICP group. The fecal metabolite composition and diversity presented typical variation in severe ICP. A significant increase in bile acid, formate and succinate levels and a decrease in butyrate and hypoxanthine levels were found in women with severe ICP. The MIMOSA model indicated that genera Ruminococcus gnavus group, Lachnospiraceae FCS020 group, and Lachnospiraceae NK4A136 group contributed significantly to the metabolism of hypoxanthine, which was significantly depleted in subjects with severe ICP. Genus Acinetobacter contributed significantly to formate metabolism, which was significantly enriched in subjects with severe ICP. Conclusions Women with severe but not mild ICP harbored a unique gut microbiome and fecal metabolites compared to healthy controls. Based on these profiles, we hypothesized that the gut microbiome was involved in bile acid metabolism through metabolites, affecting ICP pathogenesis and development, especially severe ICP.

Abstract Introduction The aim of this study was to determine the factors associated with the concentrations of hydroxychloroquine (HCQ) and its major metabolite, desethylhydroxychloroquine (DHCQ), in patients with systemic lupus erythematosus (SLE). Methods Patients with SLE taking oral HCQ for at least 3 months were recruited from the Department of Rheumatology and Immunology of Nanjing Drum Tower Hospital. Clinical characteristics and laboratory values were examined. The concentrations of HCQ and DHCQ were measured by high-performance liquid chromatography, and the effects of various factors on the concentrations were investigated. Results A total of 272 patients were included in this study. The average concentration of HCQ was 690.90 ng/ml and the average concentration of DHCQ was 431.84 ng/ml. Multivariate analysis indicated that gender (P = 0.015), age (year) (P

High-temperature flow features of the Al−Zn−Mg−Cu−Zr aluminum alloy was revealed by hot compression tests. The evolution mechanisms of dislocation clusters, subgrain, and dynamic recrystallization (DRX) grains, are thoroughly explored by EBSD and TEM analysis. Experimental results suggest that the high strain rate can exacerbate dislocation clusters formation, as well as subgrain nucleation/accumulation, inducing the increasing of flow stress. Nevertheless, the noticeable annihilation of substructures, as well as the growth of DRX grains, emerge at the higher temperature, causing the descending of flow stress. Three types of DRX nucleating mechanisms, i.e., discontinuous DRX (DDRX), geometric DRX (GDRX) and continuous DRX (CDRX) are activated in the Al−Zn−Mg−Cu−Zr aluminum alloy during hot compression. Simultaneously, the GDRX often appears at a high compressed temperature or a low strain rate. A physically-based (PB) model is proposed to collaboratively reconstruct true stresses and microstructure evolution features. The estimated values of true stress, DRX fractions and average grain size preferably fit the experimental data, indicating the proposed PB model can precisely catch the thermal compression behaviors and microstructure evolution characteristics of the Al−Zn−Mg−Cu−Zr aluminum alloy.

As one of the fundamental vehicular perception technologies, millimeter-wave radar’s accuracy in angle measurement affects the decision-making and control of vehicles. In order to enhance the accuracy and efficiency of the Direction of Arrival (DoA) estimation of radar systems, a super-resolution angle measurement strategy based on the Fast Deterministic Maximum Likelihood (FDML) algorithm is proposed in this paper. This strategy sequentially uses Digital Beamforming (DBF) and Deterministic Maximum Likelihood (DML) in the Field of View (FoV) to perform a rough search and precise search, respectively. In a simulation with a signal-to-noise ratio of 20 dB, FDML can accurately determine the target angle in just 16.8 ms, with a positioning error of less than 0.7010. DBF, the Iterative Adaptive Approach (IAA), DML, Fast Iterative Adaptive Approach (FIAA), and FDML are subjected to simulation with two targets, and their performance is compared in this paper. The results demonstrate that under the same angular resolution, FDML reduces computation time by 99.30% and angle measurement error by 87.17% compared with the angular measurement results of two targets. The FDML algorithm significantly improves computational efficiency while ensuring measurement performance. It provides more reliable technical support for autonomous vehicles and lays a solid foundation for the advancement of autonomous driving technology.

Abstract Super-enhancers (SEs) consist of multiple typical enhancers enriched at high density with transcription factors, histone-modifying enzymes and cofactors. Oncogenic SEs promote tumorigenesis and malignancy by altering protein-coding gene expression and noncoding regulatory element function. Therefore, they play central roles in the treatment of cancer. Here, we review the structural characteristics, organization, identification, and functions of SEs and the underlying molecular mechanism by which SEs drive oncogenic transcription in tumor cells. We then summarize abnormal SE complexes, SE-driven coding genes, and noncoding RNAs involved in tumor development. In summary, we believe that SEs show great potential as biomarkers and therapeutic targets.

Abstract Long non-coding RNAs (lncRNAs) are tissue-specific expression patterns and dysregulated in cancer. How they are regulated still needs to be determined. We aimed to investigate the functions of glioma-specific lncRNA LIMD1-AS1 activated by super-enhancer (SE) and identify the potential mechanisms. In this paper, we identified a SE-driven lncRNA, LIMD1-AS1, which is expressed at significantly higher levels in glioma than in normal brain tissue. High LIMD1-AS1 levels were significantly associated with a shorter survival time of glioma patients. LIMD1-AS1 overexpression significantly enhanced glioma cells proliferation, colony formation, migration, and invasion, whereas LIMD1-AS1 knockdown inhibited their proliferation, colony formation, migration, and invasion, and the xenograft tumor growth of glioma cells in vivo. Mechanically, inhibition of CDK7 significantly attenuates MED1 recruitment to the super-enhancer of LIMD1-AS1 and then decreases the expression of LIMD1-AS1. Most importantly, LIMD1-AS1 could directly bind to HSPA5, leading to the activation of interferon signaling. Our findings support the idea that CDK7 mediated-epigenetically activation of LIMD1-AS1 plays a crucial role in glioma progression and provides a promising therapeutic approach for patients with glioma.

Abstract Background Super-enhancers (SEs), driving high-level expression of genes with tumor-promoting functions, have been investigated recently. However, the roles of super-enhancer-associated lncRNAs (SE-lncRNAs) in tumors remain undetermined, especially in gliomas. We here established a SE-lncRNAs expression-based prognostic signature to choose the effective treatment of glioma and identify a novel therapeutic target. Methods Combined analysis of RNA sequencing (RNA-seq) data and ChIP sequencing (ChIP-seq) data of glioma patient-derived glioma stem cells (GSCs) screened SE-lncRNAs. Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) datasets served to construct and validate SE-lncRNA prognostic signature. The immune profiles and potential immuno- and chemotherapies response prediction value of the signature were also explored. Moreover, we verified the epigenetic activation mechanism of LINC00945 via the ChIP assay, and its effect on glioma was determined by performing the functional assay and a mouse xenograft model. Results 6 SE-lncRNAs were obtained and identified three subgroups of glioma patients with different prognostic and clinical features. A risk signature was further constructed and demonstrated to be an independent prognostic factor. The high-risk group exhibited an immunosuppressive microenvironment and was higher enrichment of M2 macrophage, regulatory T cells (Tregs), and Cancer-associated fibroblasts (CAFs). Patients in the high-risk group were better candidates for immunotherapy and chemotherapeutics. The SE of LINC00945 was further verified via ChIP assay. Mechanistically, BRD4 may mediate epigenetic activation of LINC00945. Additionally, overexpression of LINC00945 promoted glioma cell proliferation, EMT, migration, and invasion in vitro and xenograft tumor formation in vivo. Conclusion Our study constructed the first prognostic SE-lncRNA signature with the ability to optimize the choice of patients receiving immuno- and chemotherapies and provided a potential therapeutic target for glioma.

Abstract Background Idiopathic pulmonary fibrosis (IPF) is a condition that may cause persistent pulmonary damage. The transformation of pericytes into myofibroblasts has been recognized as a key player during IPF progression. This study aimed to investigate the functions of lncRNA growth arrest-specific transcript 5 (GAS5) in myofibroblast transformation during IPF progression. Methods We created a mouse model of pulmonary fibrosis (PF) via intratracheal administration of bleomycin. Pericytes were challenged with exogenous transforming growth factor-β1 (TGF-β1). To determine the expression of target molecules, we employed quantitative reverse transcription-polymerase chain reaction, Western blotting, and immunohistochemical and immunofluorescence staining. The pathological changes in the lungs were evaluated via H&E and Masson staining. Furthermore, the subcellular distribution of GAS5 was examined using FISH. Dual-luciferase reporter assay, ChIP, RNA pull-down, and RIP experiments were conducted to determine the molecular interaction. Results GAS5 expression decreased whereas PDGFRα/β expression increased in the lungs of IPF patients and mice with bleomycin-induced PF. The in vitro overexpression of GAS5 or silencing of PDGFRα/β inhibited the TGF-β1-induced differentiation of pericytes to myofibroblasts, as evidenced by the upregulation of pericyte markers NG2 and desmin as well as downregulation of myofibroblast markers α-SMA and collagen I. Further mechanistic analysis revealed that GAS5 recruited KDM5B to promote H3K4me2/3 demethylation, thereby suppressing PDGFRα/β expression. In addition, KDM5B overexpression inhibited pericyte–myofibroblast transformation and counteracted the promotional effect of GAS5 knockdown on pericyte–myofibroblast transformation. Lung fibrosis in mice was attenuated by GAS5 overexpression but promoted by GAS5 deficiency. Conclusion GAS5 represses pericyte–myofibroblast transformation by inhibiting PDGFRα/β expression via KDM5B-mediated H3K4me2/3 demethylation in IPF, identifying GAS5 as an intervention target for IPF.

Objectives: This study aimed to provide guidance for clinical treatment and increase public confidence in COVID-19 vaccines. Methods: The Cochrane Library, Embase, PubMed, Web of Science, ClinicalKey, and other COVID-19 datasets were searched from December 2019 to May 2022. Case-control studies and prospective cohort studies of COVID-19 vaccine effectiveness and safety in pregnant women were included. Results: From day 11 to day 13, after the first dose of the COVID-19 messenger RNA vaccine, the effectiveness was 54% (95% confidence interval: 0.33-0.69). On days 14 to 27, the effectiveness was 59%. There was a 14% increase in vaccine effectiveness 28 days after the first dose was given. The inactivated vaccines showed similar effectiveness. The proportions of placental abruptions, postpartum hemorrhages, miscarriages, stillbirths, premature births, and small for gestational age infants were not significantly different between vaccinated and nonvaccinated pregnant women. Fatigue and fever were also not associated with pregnancy. Conclusion: Our findings affirm that the effectiveness varies for different types of vaccines and is significantly and positively correlated with time in the pregnant population. COVID-19 vaccines have also been deemed safe for pregnant women. Thus, we developed a comprehensive understanding of the role of vaccines in pregnant women.

Objective: Pain is one of the most common symptoms of cancer patients. Patients with advanced stages of cancer are always transferred to primary medical institutions or treated with home medication due to their specific pathophysiological characteristics. Studies have shown that continuous pharmaceutical care can improve the effectiveness and safety of drug therapy for cancer pain patients in primary care, but no relevant research has been conducted in China. Based on the Delphi method, this study aims to construct a pharmaceutical care mode for cancer pain patients and analyze its effect in drug therapy treatment in primary care in China.Methods: A pharmaceutical care mode for cancer pain patients in primary care was developed through two rounds of expert consensus. A total of 200 cancer pain patients from January 2022 to January 2023 in Nanjing Drum Tower Hospital were recruited and divided into an intervention group and control group. The self-developed pharmaceutical care mode in primary care was conducted in the intervention group, while the traditional pharmaceutical care mode was conducted in the control group. Comparisons between the groups were performed in terms of pain assessment rate, reasonable rate of pain assessment, pain score, and incidence of adverse reactions.Results: The initiative of experts in the two rounds of consultation was 100%, with an authority coefficient of 0.83. The coordination coefficient of the second round was higher than that of the first round, indicating that the consistency of expert opinions was enhanced. There were 100 cases in each group, and 12 and 8 were lost to follow-up in the intervention group and control group, respectively. Compared with the control group, the intervention group had a significantly higher pain assessment rate, a reasonable rate of pain assessment, and a significantly lower pain score and incidence of adverse reactions.Conclusion: Under the scientific and reasonable mode of pharmaceutical care for cancer pain patients at the primary level, standardized drug therapy could significantly enhance the efficacy of treatment, thereby improving the quality of life of patients.

Objectives The study aims to investigate the impact of gene polymorphisms on blood hydroxychloroquine (HCQ) concentrations in patients with SLE and provide guidelines for individualised care.Methods 489 Chinese patients with SLE taking HCQ for more than 3 months were collected in this study. The blood HCQ, desethylhydroxychloroquine (DHCQ) and desethylchloroquine concentrations were measured. The optimal blood concentration of HCQ was determined by receiver operating characteristic curve analysis. Single nucleotide polymorphisms of metabolic enzymes involved in HCQ metabolism were genotyped and the associations with treatment effects were investigated.Results The cut-off value of HCQ was 559.67 ng/mL, with sensitivity and specificity values of 0.51 and 0.89, respectively. The TC and CC genotypes of CYP2C8 (rs7910936) were significantly related to the increase in blood HCQ concentrations, and the CYP2C8 (rs10882521) TT genotype was associated with lower blood HCQ concentrations. The DHCQ:HCQ ratio was highest in patients with the GG genotype of the CYP2D6*10 (rs1065852) polymorphism and lowest in those with the AA genotype. Patients with the CYP2C8 (rs7910936) CC genotype were more likely to achieve the optimal blood concentration (p=0.030) in HCQ 200 mg/day group and patients with the CYP2D6*10 (rs1065852) GG genotype were more likely to reach the optimal blood concentration (p=0.049) in 400 mg/day group.Conclusions Our results suggest that the optimal blood concentration of HCQ measured approximately 12–18 hours after the last dosage may be between 500 and 600 ng/mL in Chinese patients with SLE. The observed variations in HCQ concentrations between individuals can potentially be attributed to genetic polymorphisms in CYP2D6*10 (rs1065852) and CYP2C8 (rs7910936 and rs10882521). Genotypical testing of patients and regular monitoring of blood levels are recommended for optimising HCQ dosage management in Chinese patients with SLE.Trial registration number ChiCTR2300070628.

Intact fibroblast growth factor 23 (iFGF23) is a phosphaturic hormone that is cleaved by furin into N-terminal and C-terminal fragments. Several studies have implicated vitamin D in regulating furin in infections. Thus, we investigated the effect of 1,25-dihydroxyvitamin D3 [1,25(OH)2D] and the vitamin D receptor (VDR) on furin-mediated iFGF23 cleavage. Mice lacking VDR (Vdr–/–) had a 25-fold increase in iFGF23 cleavage, with increased furin levels and activity compared with wild-type (WT) littermates. Inhibition of furin activity blocked the increase in iFGF23 cleavage in Vdr–/– animals and in a Vdr-knockdown osteocyte OCY454 cell line. Chromatin immunoprecipitation revealed VDR binding to DNA upstream of the Furin gene, with more transcription in the absence of VDR. In WT mice, furin inhibition reduced iFGF23 cleavage, increased iFGF23, and reduced serum phosphate levels. Similarly, 1,25(OH)2D reduced furin activity, decreased iFGF23 cleavage, and increased total FGF23. In a post hoc analysis of a randomized clinical trial, we found that ergocalciferol treatment, which increased serum 1,25(OH)2D, significantly decreased serum furin activity and iFGF23 cleavage, compared with placebo. Thus, 1,25(OH)2D inhibits iFGF23 cleavage via VDR-mediated suppression of Furin expression, thereby providing a mechanism by which vitamin D can augment phosphaturic iFGF23 levels.

Systemic lupus erythematosus (SLE) is an autoimmune disease in which the immune system attacks its own tissues and organs. However, the causes of SLE remain unknown. Dyslipidemia is a common symptom observed in SLE patients and animal models and is closely correlated to disease activity. Lipid metabolic reprogramming has been considered as a hallmark of the dysfunction of T cells in patients with SLE, therefore, manipulating lipid metabolism provides a potential therapeutic target for treating SLE. A better understanding of the underlying mechanisms for the metabolic events of immune cells under pathological conditions is crucial for tuning immunometabolism to manage autoimmune diseases such as SLE. In this review, we aim to summarize the cross-link between lipid metabolism and the function of T cells as well as the underlying mechanisms, and provide light on the novel therapeutic strategies of active compounds from herbals for the treatment of SLE by targeting lipid metabolism in immune cells.

The maternal-fetal interface is defined as the interface between maternal tissue and sections of the fetus in close contact. RNA methylation modifications are the most frequent kind of RNA alterations. It is effective throughout both normal and pathological implantation and placentation during pregnancy. By influencing early embryo development, embryo implantation, endometrium receptivity, immune microenvironment, as well as some implantation and placentation-related disorders like miscarriage and preeclampsia, it is essential for the establishment of the maternal-fetal interface. Our review focuses on the role of dynamic RNA methylation at the maternal-fetal interface, which has received little attention thus far. It has given the mechanistic underpinnings for both normal and abnormal implantation and placentation and could eventually provide an entirely novel approach to treating related complications.

ABSTRACTGliomas are the most common type of primary brain tumor. Despite advances in treatment, it remains one of the most aggressive and deadly tumor of the central nervous system (CNS). Gliomas are characterized by high malignancy, heterogeneity, invasiveness, and high resistance to radiotherapy and chemotherapy. It is urgent to find potential new molecular targets for glioma. The TRPM channels consist of TRPM1-TPRM8 and play a role in many cellular functions, including proliferation, migration, invasion, angiogenesis, etc. More and more studies have shown that TRPM channels can be used as new therapeutic targets for glioma. In this review, we first introduce the structure, activation patterns, and physiological functions of TRPM channels. Additionally, the pathological mechanism of glioma mediated by TRPM2, 3, 7, and 8 and the related signaling pathways are described. Finally, we discuss the therapeutic potential of targeting TRPM for glioma.

Curcumenol, an effective ingredient of Wenyujin, has been reported that exerted its antitumor potential in a few cancer types. However, the effect and molecular mechanism of curcumenol in lung cancer are largely unknown. Here, we found that curcumenol induced cell death and suppressed cell proliferation in lung cancer cells. Next, we demonstrated that ferroptosis was the predominant method that contributed to curcumenol-induced cell death of lung cancer in vitro and vivo for the first time. Subsequently, using RNA sequencing, we found that the long non-coding RNA H19 (lncRNA H19) was significantly downregulated in lung cancer cells treated with curcumenol, when compared to untreated controls. Overexpression of lncRNA H19 eliminated the anticancer effect of curcumenol, while lncRNA H19 knockdown promoted ferroptosis induced by curcumenol treatment. Mechanistically, we showed that lncRNA H19 functioned as a competing endogenous RNA to bind to miR-19b-3p, thereby enhanced the transcription activity of its endogenous target, ferritin heavy chain 1 (FTH1), a marker of ferroptosis. In conclusion, our data show that the natural product curcumenol exerted its antitumor effects on lung cancer by triggering ferroptosis, and the lncRNA H19/miR-19b-3p/FTH1 axis plays an essential role in curcumenol-induced ferroptotic cell death. Therefore, our findings will hopefully provide a valuable drug for treating lung cancer patients.

Introduction: Dimethyl phthalate (DMP) which has been widely detected in water is neurotoxic to humans and should be effectively eliminated. Persulfate-based advanced oxidation processes are considered to be reliable methods aiming at emerging contaminants degradation, while an efficient catalyst is urgently needed for the activation of the reaction. As a typical 2D material, 1T-MoS2 is expected to be applied to the activation of persulfate owing to its abundant active sites and excellent electrical conductivity. In practical applications, 1T-MoS2 has the phenomenon of reunion which affects the exposure of its catalytic sites.Methods: Therefore, in this study, we used waste cow manure as a raw material to prepare biochar and achieved high exposure of 1T-MoS2 activation sites by loading 1T-MoS2 onto the surface of cow manure biochar through hydrothermal synthesis. The prepared composite catalytic material CMB@1T-MoS2 was used to activate PMS for the degradation of DMP.Results: It was found that CMB@1T-MoS2 has better effect than CMB or 1T-MoS2 alone for the degradation of DMP, reaching 77.65% at pH = 3. Under alkaline conditions, the degradation rate of DMP was reduced due to the inhibition of the catalytic process. Among the different coexisting anions, HCO-3 interfered and inhibited the degradation process the most, leading to the lowest degradation rate of DMP with 42.45%.Discussion: The quenching experiments and EPR analysis showed that SO-4• and •OH were the main ROS in the CMB@1T-MoS2/PMS process. This study promotes the resourceful use of cow manure and is expected to provide a novel persulfate-based advanced oxidation process catalyzed by CMB@1T-MoS2 for the elimination of DMP in an aqueous environment.

This study aims to propose and evaluate DR-CycleGAN, a disentangled unsupervised network by introducing a novel content-consistency loss, for removing arterial-phase motion artifacts in gadoxetic acid-enhanced liver MRI examinations. From June 2020 to July 2021, gadoxetic acid-enhanced liver MRI data were retrospectively collected in this center to establish training and testing datasets. Motion artifacts were semi-quantitatively assessed using a five-point Likert scale (1 = no artifact, 2 = mild, 3 = moderate, 4 = severe, and 5 = non-diagnostic) and quantitatively evaluated using the structural similarity index (SSIM) and peak signal-to-noise ratio (PSNR). The datasets comprised a training dataset (308 examinations, including 58 examinations with artifact grade = 1 and 250 examinations with artifact grade ≥ 2), a paired test dataset (320 examinations, including 160 examinations with artifact grade = 1 and paired 160 examinations with simulated motion artifacts of grade ≥ 2), and an unpaired test dataset (474 examinations with artifact grade ranging from 1 to 5). The performance of DR-CycleGAN was evaluated and compared with a state-of-the-art network, Cycle-MedGAN V2.0. As a result, in the paired test dataset, DR-CycleGAN demonstrated significantly higher SSIM and PSNR values and lower motion artifact grades compared to Cycle-MedGAN V2.0 (0.89 ± 0.07 vs. 0.84 ± 0.09, 32.88 ± 2.11 vs. 30.81 ± 2.64, and 2.7 ± 0.7 vs. 3.0 ± 0.9, respectively; p < 0.001 each). In the unpaired test dataset, DR-CycleGAN also exhibited a superior motion artifact correction performance, resulting in a significant decrease in motion artifact grades from 2.9 ± 1.3 to 2.0 ± 0.6 compared to Cycle-MedGAN V2.0 (to 2.4 ± 0.9, p < 0.001). In conclusion, DR-CycleGAN effectively reduces motion artifacts in the arterial phase images of gadoxetic acid-enhanced liver MRI examinations, offering the potential to enhance image quality.

High-temperature forming behaviors of a 7046-aluminum alloy were investigated by hot compression experiments. The microstructural evolution features with the changes in deformation parameters were dissected. Results indicated the formation of massive dislocation clusters/cells and subgrains through the intense DRV mechanism at low compression temperature. With an increase in deformation temperature, the annihilation of dislocations and the coarsening of subgrains/DRX grains became prominent, due to the collaborative effects of the DRV and DRX mechanisms. However, the growth of subgrains and DRX grains displayed the weakening trend at high strain rates. Moreover, two constitutive models involving a physically based (PB) model and a gate recurrent unit (GRU) model were proposed for predicting the hot compression features. By validation analysis, the predicted values of true stress perfectly fit with the experimental data, indicating that both the proposed PB model and the GRU model can accurately predict the hot compression behaviors of 7046-aluminum alloys.

Background: Recent studies demonstrate that N6-methyladenosine (m6A) methylation plays a crucial role in colorectal cancer (CRC). Therefore, we conducted a comprehensive analysis to assess the m6A modification patterns and identify m6A-modified genes in patients with CRC recurrence.Methods: The m6A modification patterns were comprehensively evaluated by the NMF algorithm based on the levels of 27 m6A regulators, and tumor microenvironment (TME) cell-infiltrating characteristics of these modification patterns were systematically assessed by ssGSEA and CIBERSORT algorithms. The principal component analysis algorithm based on the m6A scoring scheme was used to explore the m6A modification patterns of individual tumors with immune responses. The weighted correlation network analysis and univariable and multivariable Cox regression analyses were applied to identify m6A-modified gene signatures. The single-cell expression dataset of CRC samples was used to explore the tumor microenvironment affected by these signatures.Results: Three distinct m6A modification patterns with significant recurrence-free survival (RFS) were identified in 804 CRC patients. The TME characterization revealed that the m6A modification pattern with longer RFS exhibited robust immune responses. CRC patients were divided into high- and low-score subgroups according to the m6A score individually, which was obtained from the m6A-related signature genes. The patients with low m6A scores had both longer RFS and overall survival (OS) with altered immune cell infiltration. Notably, m6A-modified genes showed significant differences related to the prognosis of CRC patients in the meta-GEO cohort and TCGA cohort. Single-cell expression indicated that ALVRL1 was centrally distributed in endothelial tip cells and stromal cells.Conclusion: The m6A modification plays an indispensable role in the formation of TME diversity and complexity. Importantly, the signatures (TOP2A, LRRC58, HAUS6, SMC4, ACVRL1, and KPNB1) were identified as m6A-modified genes associated with CRC recurrence, thereby serving as a promising predictive biomarker or therapeutic target for patients with CRC recurrence.

Vagus nerve stimulation (VNS) is an effective treatment for drug-resistant epilepsy (DRE). The present study evaluated the efficacy of VNS in pediatric patients with DRE of monogenic etiology. A total of 20 patients who received VNS treatment at our center were followed up every 3 months through outpatient visits or a remote programming platform. The median follow-up time was 1.4 years (range: 1.0–2.9). The rate of response to VNS at 12 months of follow-up was 55.0% (11/20) and the seizure-free rate was 10.0% (2/20). We found that 75.0% (3/4) of patients with an SCN1A variant had a >50% reduction in seizure frequency. Patients with pathogenic mutations in the SLC35A2, CIC, DNM1, MBD5, TUBGCP6, EEF1A2, and CHD2 genes or duplication of X q28 (MECP2 gene) had a >50% reduction in seizure frequency. Compared with the preoperative electroencephalography (EEG), at 6, 12, 18, and 24 months after stimulator implantation, the percentage of the patients whose background frequency increased >1.5 Hz was respectively, 15.0% (3/20), 50.0% (10/20), 58.3% (7/12) and 62.5% (5/8); the percentage of the patients whose interictal EEG showed a >50% decrease in spike number was respectively 10% (2/20), 40.0% (8/20), 41.6% (5/12) and 50.0% (4/8). In the 9 patients with no response to VNS treatment, there was no difference in terms of spike number and background frequency between preoperative and postoperative EEG. Five of the 20 children (25.0%) reached new developmental milestones or acquired new skills after VNS compared to the preoperative evaluation. The efficacy of VNS in pediatric patients with DRE of monogenic etiology is consistent with that in the overall population of pediatric DRE patients. Patients with Dravet syndrome (DS), tuberous sclerosis complex (TSC), or Rett syndrome/MECP2 duplication syndrome may have a satisfactory response to VNS, but it is unclear whether patients with rare variants of epilepsy-related genes can benefit from the treatment.

Abstract Background Oral Function, Orofacial Pain, Orofacial Appearance, and Psychosocial Impact are the four oral health-related quality of life (OHRQoL) dimensions (4D) or areas in which oral disorders impact pediatric patients. Using their dentists' assessment, the study aimed to evaluate whether pediatric dental patients' oral health concerns fit into the 4D of the Oral Health-Related Quality of Life (OHRQoL) construct. Methods Dentists who treat children from 32 countries and all WHO regions were selected from a web-based survey of 1580 international dentists. Dentists were asked if their pediatric patients with current or future oral health concerns fit into the 4D of the Oral Health-Related Quality of Life (OHRQoL) construct. Proportions of all pediatric patients’ oral health problems and prevention needs were computed. Findings Data from 101 dentists treating children only and 523 dentists treating children and adults were included. For 90% of pediatric patients, their current oral health problems fit well in the four OHRQoL dimensions. For 91% of oral health problems they intended to prevent in the future were related to these dimensions as well. Both numbers increased to at least 96% when experts analyzed dentists´ explanations of why some oral health problems would not fit these four categories. Conclusions The study revealed the four fundamental components of dental patients, i.e., the four OHRQoL dimensions (Oral Function, Orofacial Pain, Orofacial Appearance, and Psychosocial Impact) are also applicable for pediatric patients, regardless of whether they have current or future oral health concerns, and should be considered when measuring OHRQoL in the pediatric dental patient population.

Generation of reactive oxygen species (ROS) are possibly induced by the crosstalk between mitochondria and endoplasmic reticula, which is physiologically important in apoptosis. Cytochrome c (Cyt c) is believed to play a crucial role in such signaling pathway by interrupting the coupling within microsomal monooxygenase (MMO). In this study, the correlation of ROS production with the electron transfer between Cyt c and the MMO system is investigated by resonance Raman (RR) spectroscopy. Binding of Cyt c to MMO is found to induce the production of ROS, which is quantitatively determined by the in-situ RR spectroscopy reflecting the interactions of Cyt c with generated ROS. The amount of ROS that is produced from isolated endoplasmic reticulum depends on the redox state of the Cyt c, indicating the important role of oxidized Cyt c in accelerating apoptosis. The role of electron transfer from MMO to Cyt c in the apoptotic mitochondria-endoplasmic reticulum pathway is accordingly proposed. This study is of significance for a deeper understanding of how Cyt c regulates apoptotic pathways through the endoplasmic reticulum, and thus may provide a rational basis for the design of antitumor drugs for cancer therapy.

BackgroundPain has become an important factor in evaluating patients' quality of life and clinical treatment. For gastric cancer (GC) patients, open radical gastrectomy (OG) causes significant trauma to the body, increases patients' pain after operation, and delays early recovery. The aim of this study was to investigate the predictive factors of acute pain after OG within postoperative 72 h.MethodsFrom March 2020 to September 2021, 307 patients who underwent OG were included in the study in Nanjing Drum Tower Hospital. The predictors included demographic predictors, pathological data, surgical predictors, and intraoperative predictors. The pain scores at 12, 24, 48, and 72 h after operation were evaluated by numeric rating scale (NRS). The predictors of acute pain were determined by univariate and multivariate analysis.ResultsThe average pain score (NRS) of patients showed a downward trend over time within 72 h after OG. Multivariate analysis indicated that total gastrectomy (OR 1.823, 95% CI 1.094–3.040, P < 0.05), AJCC TNM stage (II) (OR.232, 95% CI 0.062–0.872, P < 0.05), AJCC TNM stage(III) (OR.185, 95% CI 0.049–0.698, P < 0.05), BMI (kg/m2) (OR 1.75, 95% CI 1.029–2.976, P < 0.05), distant metastasis (OR 3.054, 95% CI 1.019–9.155, P < 0.05), intraoperative transfusion (OR 2.246, 95% CI 1.267–3.982, P < 0.01) were significant predictive factors for acute pain after OG.ConclusionReasonable postoperative acute pain control was the prerequisite for accelerating the postoperative rehabilitation of patients. In order to reduce the occurrence of excessive or insufficient analgesia, it was necessary for patients who underwent OG to formulate appropriate analgesics according to risk factors.

Gliomas are a group of the most aggressive primary central nervous system tumors with limited treatment options. The abnormal expression of long non-coding RNA (lncRNA) is related to the prognosis of glioma. However, the role of endoplasmic reticulum (ER) stress-associated lncRNAs in glioma prognosis has not been reported. In this paper, we obtained ER stress-related lncRNAs by co-expression analysis, and then a risk signature composed of 6 ER stress-related lncRNAs was constructed using Cox regression analysis. Glioma samples in The Cancer Genome Atlas (TCGA) were separated into high- and low-risk groups based on the median risk score. Compared with the low-risk group, patients in the high-risk group had shorter survival times. Additionally, we verified the predictive ability of these candidate lncRNAs in the testing set. Three glioma patient subgroups (cluster 1/2/3) were identified by consensus clustering. We further analysed the abundance of immune-infiltrating cells and the expression levels of immune checkpoint molecules in both three subgroups and two risk groups, respectively. Immunotherapy and anticancer drug response prediction showed that ER stress-related lncRNA risk signature positively correlates with responding to immune checkpoints and chemosensitivity. Functional analysis showed that these gene sets are enriched in the malignant process of tumors. Finally, LINC00519 was chosen for functional experiments. The silence of LINC00519 restrained the migration and invasion of glioma cells. Hence, those results indicated that ER stress-related lncRNA risk signature could be a potential treatment target and a prognosis biomarker for glioma patients.

Introduction: Our objective was to explore the clinical features, pregnancy complications, and outcomes of subchorionic hematomas (SCHs) in the third trimester. Material and methods: This was a retrospective analysis and evaluation of 1112 cases diagnosed with SCHs from January 2014 to December 2020. Comparisons were performed according to the clinical features (e.g., number of pregnancies, parity, gestational weeks, and age), pregnancy complications, and outcomes associated with SCHs. Results: In total, 71.85% (799/1112) of the patients were diagnosed with different pregnancy complications. The overall rates of gestational diabetes mellitus (GDM), hypertensive disorder complicating pregnancy (HDCP), premature rupture of membranes (PROM), and IVF were 12.14%, 7.55%, 17.27%, and 10.34%, respectively. The positive rates for newborn outcomes such as premature birth and low birth weight (LBW) were 9.35% and 6.47%, respectively. There was a significant relationship between repeated pregnancies and the incidence of GDM (p < 0.05), but not HDCP, PROM, or IVF. The proportion of SCH patients who conceived through IVF was significantly higher among primiparas than among multiparas (p < 0.05), but was not significantly different in terms of GDM, HDCP, or PROM. Premature birth was not a high-risk factor for most SCH patients with HDCP, IVF, or PROM (p < 0.05), most of whom delivered at term. The rate of cesarean sections for SCH patients with GDM, HDCP, or IVF was significantly higher than that for vaginal deliveries (p < 0.05), but this was not affected by age. Conclusions: The coexistence of SCHs with HDCP, IVF, or PROM lacked an effective predictive value for premature birth, but increased the rate of a cesarean section.

Some studies have shown that the cognitive state in Alzheimer's disease (AD) patients is related to the changes of the temporal characteristics of dynamic functional connection. Persistent homology index analysis method provides a deeper insight into the property of dynamic brain networks. However, current research mainly focused on spatial evolution, while there is little research on time-varying brain network evolution. Based on resting state-functional magnetic resonance imaging (rs-fMRI) data, this paper analyzed the static functional connectivity network in AD patients and normal controls (NC), as well as the dynamic brain networks constructed by sliding windows. The analysis method based on persistent homology was compared with the ones based on graph theory, and the temporal characteristics were analyzed with k-means clustering. The results demonstrated that there were more significant differences between the AD patients and NC subjects, when the index based on persistent homology was used. Compared with the analysis of static brain networks, the dynamic brain network evolution analysis based on persistent homology provides new ideas for the detection of functional brain network biomarkers.

Diamagnetically levitated oscillators of millimeter and submillimeter size are emerging ultrasensitive sensors for gravitylike force and acceleration measurements. However, improving the levitation capability while keeping mechanical dissipation low remains an open challenge. Here, we propose and experimentally demonstrate an engineering conductive geometry scheme to efficiently reduce the mechanical dissipation of a diamagnetically levitated oscillator made of pyrolytic graphite. We show that with a specially designed conductive geometry, the eddy current damping is reduced, and the reduction factor increases as the engraving pattern being denser. Under high vacuum and room temperature, eddy current damping is the dominant contribution to mechanical dissipation, and we reduce it by a factor of 50 in the experiment. Our work opens up a new way to achieve diamagnetically levitated oscillator with ultralow mechanical dissipation and strong levitation capability, a candidate platform for studying a broad range of fundamental physics.

Robust optimal design of circulation systems (e.g., roads for vehicles or corridors for pedestrians) relies on an accurate steady-state traffic flow model that considers the effect of randomly changing environmental factors (e.g., daily periodicity and weather). Most analytical models assume that the customer interarrival time and service time of circulation facilities follow the exponential distribution with fixed rate parameters, which is unrealistic in most cases. In this paper, we develop a stationary PH i/PH i,n/C/C state-dependent queuing model in a randomly changing environment (RE), which is represented by a Markov chain. The model simultaneously considers the general randomness of arrival and service, the randomly varying rate parameters, and the state-dependent service (the travel time increases with the number of customers). The existing matrix analytic scheme (MAS) algorithm is extended to solve the proposed model because it avoids the explicit calculation of probability distributions. The space complexity of the algorithm is only linear in the number of RE states and is independent of the enormous (four-dimensional) state space of the Markov process. Its time complexity is a linear function of the product of the queue capacity and the number of RE states. Our model is validated versus simulation estimates. The obtained conditional performance measures can accurately capture the queue accumulation and dissipation and reveal the effect of randomly changing environments. Numerical experiments provide some interesting findings. (1) The proposed stationary model coincides with the transient M(t)/Gx/C/C fluid queuing model under special conditions. (2) Under high traffic intensities, increasing the randomness in the duration time of the RE state leads to an obvious growth in the conditional queue length. (3) An increase in the facility length leads to an increase or a decrease in the average output rate, depending on whether the congestion dissipates effectively in one cycle. (4) A larger width is required to obtain the maximum average output rate for traffic demand with a greater nonuniformity.

The lane-changing behavior is one of the important causes in traffic accident in congest traffic, and many behaviors of change lane affect volume of traffic. When autonomous driving vehicles are running on road with human-driven vehicles, the effects of change lane on traffic are different. In all human-driven vehicles traffic, the vehicle behaviors of changing lane are more competent. When autonomous driving vehicles are running in mixed traffic, the behaviors of changing lane decrease and the volume of traffic increases. However, a few studies have involved the relationship between traffic volume and lane-change behavior. In a sense, the study of this relationship is good for understanding the operation mechanism of mixed traffic. In this paper, we proposed the linear regression model to describe the relationship between traffic volume and lane-change behavior. The model can be used to establish the basic graph model. Here, we used empirical, simulation, and data-driven methods to obtain data and established a multiple linear regression model. First, we empirically study the continuous traffic with all human-driven vehicles. Then, the corresponding simulation model is established, and the availability of the simulation model is proved by data comparison with empirical study. Finally, 9 rounds of simulation experiments are carried out with the established simulation model. The number of autonomous driving vehicles in each round of simulation experiment increases by 10%. Then, we analyze the data of the behaviors of changing lane and the volume of traffic from simulation experiments. The following was found: (1) an increase in autonomous driving vehicle leads to an increase in traffic volume and a slight decrease in lane changing behaviors; (2) the influence of different proportions of autonomous vehicles on the traffic volume of lanes at different locations is slightly different; and (3) the relationships among the rate of vehicles entering lane, the rate of vehicles exiting lane together, and the volume of traffic show obvious linear relationships with the increase in autonomous driving vehicles. We used multiple linear regression models to carry out description, and the obtained parameter value intervals are close under different operating ratios of autonomous vehicles. To sum up, on multilane roads, especially 4-lane urban expressways, autonomous driving vehicles join in the traffic, which can effectively increase the volume of traffic of each lane while reducing vehicle behaviors of changing lane. The relationships between vehicle behaviors of changing lane and the traffic volume in mixed traffic show linear relationships with the increase in autonomous driving vehicles. In the future, we will further study whether this relationship model can be used in discrete traffic flow.

Modelling the mixed traffic flows of autonomous vehicles (AVs) and human-driven vehicles (HVs) on highways is challenging. Randomness, fluctuations, and congestion exist in the mixed traffic flows. This paper extends the current literature by proposing an M/G(n)/c/c state-dependent queuing model operating in a random environment. The fluctuating traffic demand is addressed by arrival rates modulated by the random environment. Meanwhile, a Markovian arrival process (MAP) is incorporated to describe the platoons. We investigate the performance of the mixed traffic flow under the I policy (AVs and HVs travel together in all lanes) and the D policy (one lane is designated to AVs). Numerical experiments reveal the following interesting findings: (1) the fluctuation degree of traffic demand, the traffic intensity, and the penetration rate of AVs play essential roles in determining the performance of mixed traffic flows. (2) The I policy should always be adopted if the travel time is more valuable. In terms of output rate, the choice between the I and the D policies depends on the traffic intensity, SCV of arrival rates and penetration rate. (3) A larger penetration rate is required to completely eliminate congestion on a longer highway segment.

Teacher's emotions have been shown to be highly important in the quality and effectiveness of teaching and learning. There is a recognized need to examine the essential role of teacher's emotions in students' academic achievement. However, the influence of teacher's displays of emotions on students' outcomes in small-group interaction activities, especially in the online environment, has received little attention in prior research. The aim of the present study was to explore the relationship between teacher's different emotional displays and students' perceptions of the teacher's competence, as well as students' collaborative feelings and productivity in online small-group discussions. Using a three-level between-subjects design, 74 participants were randomly divided into four-member groups comprising a teacher and three other participants. All the groups were asked to discuss an open-ended realistic problem using online software, during which the teacher's display of emotions varied (positive vs. negative vs. neutral). The participants' self-reported questionnaire data (perception of the teacher's competence, students' feeling of pleasure, collaborative satisfaction, and willingness to continue collaborating) and productivity (number of effective ideas expressed within a given time) were measured to compare the participants who were exposed to different emotional displays. As expected, the results showed that the participants who received the teacher's positive emotional display reported that they experienced higher levels of pleasure during the task. However, in contrast to our expectations, those under the negative emotional display condition showed a significantly higher level of productivity in the group task. In addition, compared to emotional display, the participants' perceptions of the teacher's competence were rated significantly higher under the neutral condition, and they reported higher levels of collaborative satisfaction and greater willingness to continue collaborating with their group. The findings have the potential benefit of informing educational practice on whether teachers should display their emotions in a small-group discussion or how they should display emotions following adjustment for the relative aim of the teaching activities.

The behavior of changing lanes has a great impact on road traffic with heavy traffic. Traffic flow density is one of the important parameters that characterize the characteristics of traffic flow, and it will also be affected by the behavior of changing lanes, especially in the case of each lane. The penetration of autonomous vehicles can effectively reduce lane-changing behavior. Studying the relationship between traffic flow density and lane-changing behavior under different autonomous vehicle penetration rates is of great significance for describing the operation mechanism of mixed traffic flow and the control of mixed traffic. In this article, we use empirical, simulation, and data-driven methods to analyze the urban expressway of autonomous vehicles with penetration rates of 10%, 20%, 30%, 40%, 50%, 60%, 70%, and 80%, respectively. A simulation experiment was carried out on the road, and data related to density, the rate of changing into the lanes, and the rate of changing out lanes were collected. The analysis of the experimental results found the following: (1) The increase in penetration of autonomous vehicles leads to a certain degree of downward trend in density, the rate of changing into the lanes, and the rate of changing out lanes. (2) Different lanes have different effects on the penetration of autonomous vehicles. In a 4-lane road, the two lanes farther from the entrance and exit are closer in appearance, while the two lanes closer to the entrance and exit are similar. (3) The relationship between density and the rate of changing into the lanes and the rate of changing out lanes shows a linear relationship with the penetration of autonomous vehicles. Although the performance of each lane is slightly different, in general, it can be carried out by a multiple regression model. The given parameter value range is relatively close under different permeability. In summary, autonomous vehicles effectively reduce the traffic density and lane-changing behavior of each lane. There is a linear relationship between traffic flow density and lane-changing behavior with the penetration of autonomous vehicles. The density-lane-changing behavior model proposed in this paper can better describe the relationship between the density of the circular multilane urban expressway and the lane-changing behavior in the case of a large traffic flow in mixed traffic.

In mixed traffic with autonomous vehicles, the relationship between speed and lane-changing behavior is an important basis for mixed traffic control. In this study, we use empirical, simulation, and data-driven methods to study the relationship between speed and lane change rates in mixed traffic under different autonomous vehicle penetration rates. We use the empirical data to establish the corresponding road simulation models. Based on the simulation model, the traffic flow simulation experiments under the conditions of 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, and 90% penetration rate of autonomous vehicles were carried out. The analysis of the simulation results found that: (1) the penetration of autonomous vehicles into the road has a positive impact on the lanes far away from the entrance and exit, while the impact on the lanes closer to the entrance and exit is not obvious. (2) Lane-changing behavior has effectively decreased with the penetration of autonomous vehicles, but it is not obvious when the penetration rate exceeds 10%, and there is no significant drop in the lane connecting the entrance and exit. (3) There is a linear relationship between speed and lane-changing rate. Under different penetration rates, the data-driven analysis is used to perform multiple linear regressions, and the regression formula fits are all above 0.7. Based on the above findings, the linear formula of the fitting is proposed, and the value interval of the parameters in different states is given as well. Due to the small changes in the parameter values under different permeability conditions, the model has a certain degree of stability. The speed-lane change rate model proposed in this study can better describe the relationship between the speed of the ring-shaped urban expressway and the lane-changing behavior in the mixed traffic environment with the larger traffic flow.

Abstract Background Transcriptomic structural variants (TSVs)—large-scale transcriptome sequence change due to structural variation - are common in cancer. TSV detection from high-throughput sequencing data is a computationally challenging problem. Among all the confounding factors, sample heterogeneity, where each sample contains multiple distinct alleles, poses a critical obstacle to accurate TSV prediction. Results To improve TSV detection in heterogeneous RNA-seq samples, we introduce the Multiple Compatible Arrangements Problem (MCAP), which seeks k genome arrangements that maximize the number of reads that are concordant with at least one arrangement. This models a heterogeneous or diploid sample. We prove that MCAP is NP-complete and provide a $$\frac{1}{4}$$ 1 4 -approximation algorithm for $$k=1$$ k = 1 and a $$\frac{3}{4}$$ 3 4 -approximation algorithm for the diploid case ( $$k=2$$ k = 2 ) assuming an oracle for $$k=1$$ k = 1 . Combining these, we obtain a $$\frac{3}{16}$$ 3 16 -approximation algorithm for MCAP when $$k=2$$ k = 2 (without an oracle). We also present an integer linear programming formulation for general k. We characterize the conflict structures in the graph that require $$k>1$$ k > 1 alleles to satisfy read concordancy and show that such structures are prevalent. Conclusions We show that the solution to MCAP accurately addresses sample heterogeneity during TSV detection. Our algorithms have improved performance on TCGA cancer samples and cancer cell line samples compared to a TSV calling tool, SQUID. The software is available at https://github.com/Kingsford-Group/diploidsquid .

Aiming to problems in the pairwise registration of point clouds, such as keypoints are difficult to describe accurately, corresponding points are difficult to match accurately and convergence speed is slow due to uncertainty of initial transformation matrix, we propose a novel feature descriptor based on ratio of rotational volume to describe effectively keypoints, and on the basis of the feature descriptor, we proposed an improved coarse-to-fine registration pipeline of point clouds, in which we use coarse registration to obtain a good initial transformation matrix and then use fine registration based on a modified ICP algorithm to obtain an accurate transformation matrix. Experimental results show that our proposed feature descriptor has a good robustness to rotation, noise, scale and varying mesh resolution, less storage space and faster running speed than PFH, FPFH, SHOT and RoPS descriptors, and our improved pairwise registration pipeline is very effective to solve the problems in the pairwise registration of point clouds.

Cancer progression and metastases are the leading causes of poor outcomes in patients with colon cancer. Colon cancer metastasis is a multigene, multistep, multistage complex process in which target genes, microRNAs, epithelial-stromal transformation, tumour stem cells, the tumour microenvironment, and various cell signalling pathways are implicated in the progression and metastasis of colon cancer. Although conventional therapies have made significant advances in treating the progression and metastasis of colorectal cancer, they have failed to improve survival outcomes. Natural compounds may have more significant potential in preventing and treating colon cancer. Active natural compounds exert their antitumor effects by inducing tumour cell differentiation, promoting tumour cell apoptosis, inhibiting tumour vascular growth, and regulating immunity. Natural compounds, combined with conventional therapies, can target mutant genes and various cellular signalling pathways, inhibit epithelial-stromal transformation, and improve the tumour microenvironment to inhibit tumour progression and metastasis. The synergism of natural compounds and conventional therapeutics has the potential to become a promising therapy for treating colorectal cancer progression and metastases.

Objective: Accumulating evidence suggested that resveratrol (RES) could protect against adverse cardiac remodeling induced by several cardiovascular diseases. However, the role of RES in the setting of heart failure with preserved ejection fraction (HFpEF) and the underlying mechanisms of its action remain understood. This study was to determine whether RES could ameliorate HFpEF-induced cardiac remodeling and its mechanisms.Methods:In vivo, C57BL/6 mice served as either the sham or the HFpEF model. The HFpEF mice model was induced by uninephrectomy surgery and d-aldosterone infusion. RES (10 mg/kg/day, ig) or saline was administered to the mice for four weeks. In vitro, transforming growth factor β1 (TGF-β1) was used to stimulate neonatal rat cardiac fibroblasts (CFs) and Ex-527 was used to inhibit sirtuin 1 (Sirt1) in CFs. Echocardiography, hemodynamics, western blotting, quantitative real-time PCR, histological analysis, immunofluorescence, and ELISA kits were used to evaluate cardiac remodeling induced by HFpEF. Sirt1 and Smad3 expressions were measured to explore the underlying mechanisms of RES.Results: HFpEF mice developed left ventricular hypertrophy, preserved ejection fraction, diastolic dysfunction, and pulmonary congestion. Moreover, HFpEF mice showed increased infiltration of neutrophils and macrophages into the heart, including increased interleukin (IL)-1β, IL-6, and TNF-α. We also observed elevated M1 macrophages and decreased M2 macrophages, which were exhibited by increased mRNA expression of M1 markers (iNOS, CD86, and CD80) and decreased mRNA expression of M2 markers (Arg1, CD163, and CD206) in HFpEF hearts. Moreover, HFpEF hearts showed increased levels of intracellular reactive oxygen species (ROS). Importantly, HFpEF mice depicted increased collagen-I and -III and TGF-β mRNA expressions and decreased protein expression of phosphorylated endothelial nitric-oxide synthase (p-eNOS). Results of western blot revealed that the activated TGF-β/Smad3 signaling pathway mediated HFpEF-induced cardiac remodeling. As expected, this HFpEF-induced cardiac remodeling was reversed when treated with RES. RES significantly decreased Smad3 acetylation and inhibited Smad3 transcriptional activity induced by HFpEF via activating Sirt1. Inhibited Sirt1 with Ex-527 increased Smad3 acetylation, enhanced Smad3 transcriptional activity, and offset the protective effect of RES on TGF-β–induced cardiac fibroblast–myofibroblast transformation in CFs.Conclusion: Our results suggested that RES exerts a protective action against HFpEF-induced adverse cardiac remodeling by decreasing Smad3 acetylation and transcriptional activity via activating Sirt1. RES is expected to be a novel therapy option for HFpEF patients.

Owing to the excellent mechanical properties of the Ti3Al alloy, the study of its microstructure has attracted the extensive attention of researchers. In this study, a Ti3Al alloy was grown based on molecular dynamics using a decahedral precursor. Face centered cubic nanocrystals with tetrahedral shapes were formed and connected by twin boundaries (TBs) to form penta twins. To understand the shear response of the Ti3Al alloy with multiple and penta twins, a shear load perpendicular to the Z-axis was applied to the quenched sample. The TBs slipped as Shockley dislocations commenced and propagated under shear loading, causing the detwinning of the penta twins and the failure of the system, indicating that the plastic deformation had been due to Shockley dislocations. The slip mechanism of multi-twinned structures in the Ti3Al alloy is discussed in detail. This study would serve as a useful guide for the design and development of advanced alloy materials.

Pulmonary fibrosis: Moving signals down a notch might help A cell membrane protein called Notch1, which binds to signaling molecules outside cells and then alters the activity of genes inside the cells, might be a promising target for drugs to treat the lung damage of pulmonary fibrosis. This condition, generally of unknown cause, involves thickening, stiffening and scarring of lung tissue. It can lead to serious breathing difficulties and eventually death, especially in people aged over 70. Hui Wang and colleagues at Central South University, Changsha, investigated the significance of the Notch1 signaling pathway by examining lung tissue from patients and manipulating the activity of the pathway in mouse cells. They conclude that Notch1 signaling is activated in pulmonary fibrosis. Drugs that could inhibit the pathway, for example by binding to the Notch1 protein, might open a promising new avenue toward treatment.

Owing to its wide range of applications, 3D object detection has attracted increasing attention in computer vision tasks. Most existing 3D object detection methods are based on Lidar point cloud data. However, these methods have some limitations in localization consistency and classification confidence, due to the irregularity and sparsity of Light Detection and Ranging (LiDAR) point cloud data. Inspired by the complementary characteristics of Lidar and camera sensors, we propose a new end-to-end learnable framework named Point-Image Fusion Network (PIFNet) to integrate the LiDAR point cloud and camera images. To resolve the problem of inconsistency in the localization and classification, we designed an Encoder-Decoder Fusion (EDF) module to extract the image features effectively, while maintaining the fine-grained localization information of objects. Furthermore, a new effective fusion module is proposed to integrate the color and texture features from images and the depth information from the point cloud. This module can enhance the irregularity and sparsity problem of the point cloud features by capitalizing the fine-grained information from camera images. In PIFNet, each intermediate feature map is fed into the fusion module to be integrated with its corresponding point-wise features. Furthermore, point-wise features are used instead of voxel-wise features to reduce information loss. Extensive experiments using the KITTI dataset demonstrate the superiority of PIFNet over other state-of-the-art methods. Compared with several state-of-the-art methods, our approach outperformed by 1.97% in mean Average Precision (mAP) and by 2.86% in Average Precision (AP) for the hard cases on the KITTI 3D object detection benchmark.

In this study, a novel multi‐layer fused convolution neural network (MLF‐CNN) is proposed for detecting pedestrians under adverse illumination conditions. Currently, most existing pedestrian detectors are very likely to be stuck under adverse illumination circumstances such as shadows, overexposure, or nighttime. To detect pedestrians under such conditions, the authors apply deep learning for effective fusion of the visible and thermal information in multispectral images. The MLF‐CNN consists of a proposal generation stage and a detection stage. In the first stage, they design an MLF region proposal network and propose to use summation fusion method for integration of the two convolutional layers. This combination can detect pedestrians in different scales, even in adverse illumination. Furthermore, instead of extracting features from a single layer, they extract features from three feature maps and match the scale using the fused ROI pooling layers. This new multiple‐layer fusion technique can significantly reduce the detection miss rate. Extensive evaluations of several challenging datasets well demonstrate that their approach achieves state‐of‐the‐art performance. For example, their method performs 28.62% better than the baseline method and 11.35% better than the well‐known faster R‐CNN halfway fusion method in detection accuracy on KAIST multispectral pedestrian dataset.