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Abstract Backgrounds Hereditary hemochromatosis (HH) is mainly caused by homozygous p.C282Y mutations in HFE in the Caucasians. We recently reported non-HFE mutations constitute the major cause of HH in Chinese. However, there is still a relatively high proportion of cases with primary iron overload from unexplained causes. We aimed to explore novel non-HFE mutations in Chinese patients with primary iron overload. Methods Whole exome sequence was conducted to screen mutations in novel HH-related genes in the 9 cases with unexplained primary iron overload. Then the representative candidate genes were screened for mutations in another cohort of 18 HH cases. The biological function of the selected genes and variants were analyzed in vitro. Results Whole exome sequencing of 9 cases with unexplained primary iron overload identified 42 missense variants in 40 genes associated with iron metabolism pathway genes such as UBE2O p.K689R and PCSK7 p.R711W. Subsequent Sanger sequencing of the UBE2O and PCSK7 genes in the 27 cases with primary iron overload identified p.K689R in UBE2O, p.R711W and p.V143F in PCSK7 at frequency of 2/27,1/27 and 2/27 respectively. In vitro siRNA interference of UBE2O and PCSK7 resulted in down-regulated HAMP mRNA expression. Adenovirus generation of UBE2O p.K689R in cell lines resulted in increased expression of SMAD6 and SMAD7 and downregulation of p-SMAD1/5 and HAMP expression, and the reduction of hepcidin level. Conclusions Our study identified a series of novel candidate non-HFE mutations in Chinese patients with HH. These may provide insights into the genetic basis of unexplained primary iron overload.

Duchenne muscular dystrophy (DMD) is a lethal muscle disease caused by mutations in the dystrophin gene. CRISPR/Cas9 genome editing has been used to correct DMD mutations in animal models at young ages. However, the longevity and durability of CRISPR/Cas9 editing remained to be determined. To address these issues, we subjected ΔEx44 DMD mice to systemic delivery of AAV9-expressing CRISPR/Cas9 gene editing components to reframe exon 45 of the dystrophin gene, allowing robust dystrophin expression and maintenance of muscle structure and function. We found that genome correction by CRISPR/Cas9 confers lifelong expression of dystrophin in mice and that corrected skeletal muscle is highly durable and resistant to myofiber necrosis and fibrosis, even in response to chronic injury. In contrast, when muscle fibers were ablated by barium chloride injection, we observed a loss of gene edited dystrophin expression. Analysis of on- and off-target editing in aged mice confirmed the stability of gene correction and the lack of significant off-target editing at 18 months of age. These findings demonstrate the long-term durability of CRISPR/Cas9 genome editing as a therapy for maintaining the integrity and function of DMD muscle, even under conditions of stress.

Abstract Background Vacuolar protein sorting (VPS) plays a crucial role in intracellular molecular transport between organelles. However, studies have indicated a correlation between VPSs and tumorigenesis and the development of several cancers. Nevertheless, the association between VPSs and hepatocellular carcinoma (HCC) remains unclear. Methods By analyzing databases such as The Cancer Genome Atlas (TCGA) and The International Cancer Genome Consortium (ICGC), we investigated the differences in VPSs expression between normal tissue and HCC transcriptomes. Furthermore, we examined the relationship between VPSs expression and overall survival (OS) in patients with HCC. Univariate and multivariate Cox analyses were employed to assess the prognostic value of VPS72 as an independent factor, and the correlation between VPS72 and the tumor immune microenvironment was also analyzed. Results We observed significant overexpression of 28 VPSs in HCC tissues compared to normal tissues. The mRNA expression of VPSs displayed a negative correlation with OS, while exhibiting a positive correlation with tumor grade and stage. Additionally, both univariate and multivariate Cox analyses identified VPS72 as a potential independent risk factor for HCC prognosis. Overexpression of VPS72 demonstrated a positive correlation with various clinicopathological factors associated with poor prognosis, as well as the infiltration levels of immune cells. Conclusion Therefore, our research shows that VPSs participate in HCC occurrence and development, especially VPS72, which may act as a potential target for HCC treatment and prognosis biomarker.

Background: Increasing childhood obesity is a global issue requiring potentially local solutions to ensure it does not continue into adulthood. We systematically identified potentially modifiable targets of obesity at the onset and end of puberty in Hong Kong, the most economically developed major Chinese city. Methods: We conducted an environment-wide association study (EWAS) and an epigenome-wide association study of obesity to systematically assess associations with body mass index (BMI) and waist–hip ratio (WHR) in Hong Kong’s population-representative ‘Children of 1997’ birth cohort. Univariable linear regression was used to select exposures related to obesity at ~11.5 years (BMI and obesity risk n ≤ 7119, WHR n = 5691) and ~17.6 years (n = 3618) at Bonferroni-corrected significance, and multivariable regression to adjust for potential confounders followed by replicated multivariable regression (n = 308) and CpG by CpG analysis (n = 286) at ~23 years. Findings were compared with evidence from published randomized controlled trials (RCTs) and Mendelian randomization (MR) studies. Results: At ~11.5 and~17.6 years the EWAS identified 14 and 37 exposures associated with BMI, as well as 7 and 12 associated with WHR, respectively. Most exposures had directionally consistent associations at ~23 years. Maternal second-hand smoking, maternal weight, and birth weight were consistently associated with obesity. Diet (including dairy intake and artificially sweetened beverages), physical activity, snoring, binge eating, and earlier puberty were positively associated with BMI at ~17.6 years, while eating before sleep was inversely associated with BMI at ~17.6 years. Findings for birth weight, dairy intake, and binge eating are consistent with available evidence from RCTs or MR studies. We found 17 CpGs related to BMI and 17 to WHR. Conclusions: These novel insights into potentially modifiable factors associated with obesity at the outset and the end of puberty could, if causal, inform future interventions to improve population health in Hong Kong and similar Chinese settings. Funding: This study including the follow-up survey and epigenetics testing was supported by the Health and Medical Research Fund Research Fellowship, Food and Health Bureau, Hong Kong SAR Government (#04180097). The DNA extraction of the samples used for epigenetic testing was supported by CFS-HKU1.

BackgroundEarly diagnosis of esophageal squamous cell carcinoma (ESCC) is critical for effective treatment and optimal prognosis; however, less study on serum biomarkers for the early ESCC detection has been reported. The aim of this study was to identify and evaluate several serum autoantibody biomarkers in early ESCC.MethodsWe initially screened candidate tumor-associated autoantibodies (TAAbs) associated with ESCC by serological proteome analysis (SERPA) combined with nanoliter-liquid chromatography combined with quadrupole time of flight tandem mass spectrometry (nano-LC-Q-TOF-MS/MS), and the TAAbs were further subjected to analysis by Enzyme-linked immunosorbent assay (ELISA) in a clinical cohort (386 participants, including 161 patients with ESCC, 49 patients with high-grade intraepithelial neoplasia [HGIN] and 176 healthy controls [HC]). Receiver operating characteristic (ROC) curve was plotted to evaluate the diagnostic performance.ResultsThe serum levels of CETN2 and POFUT1 autoantibodies which were identified by SERPA were statistically different between ESCC or HGIN patients and HC in ELISA analysis with the area under the curve (AUC) values of 0.709 (95%CI: 0.654-0.764) and 0.741 (95%CI: 0.689-0.793), 0.717 (95%CI: 0.634-0.800) and 0.703 (95%CI: 0.627-0.779) for detection of ESCC and HGIN, respectively. Combining these two markers, the AUCs were 0.781 (95%CI: 0.733-0.829), 0.754 (95%CI: 0.694-0.814) and 0.756 (95%CI: 0.686-0.827) when distinguishing ESCC, early ESCC and HGIN from HC, respectively. Meanwhile, the expression of CETN2 and POFUT1 was found to be correlated with ESCC progression.ConclusionsOur data suggest that CETN2 and POFUT1 autoantibodies have potential diagnostic value for ESCC and HGIN, which may provide novel insights for early ESCC and precancerous lesions detection.

Background: TFE3-rearranged renal cell carcinoma (TFE3-rearranged RCC) is a type of kidney cancer with a low incidence, with no consensus about whether it has a worse prognosis than clear cell renal cell carcinoma (ccRCC). This study attempted to elucidate the impact of TFE3-rearranged RCC by analyzing its clinical features and prognosis. Methods: Patients treated in Sun Yat-sen Memorial Hospital (SYSMH) who were suspected to be diagnosed with TFE3-rearranged RCC were divided into two groups, TFE3-rearranged RCC and ccRCC with positive TFE3 protein expression on immunohistochemistry [TFE3(+) ccRCC], by dual-color, break-apart fluorescence in situ hybridization (FISH). After balancing the baseline characteristics with TFE3(+) ccRCC using the propensity score matching (PSM) method in a ratio of 2, we selected patients diagnosed with ccRCC with negative TFE3 protein expression on immunohistochemistry [TFE3(−) ccRCC]. The impact of TFE3 gene rearrangement and protein expression on renal cell carcinoma was determined by feature comparison with a nonparametric test and survival analysis with the Kaplan‒Meier method. Results: Among 37 patients suspected of having TFE3-rearranged RCC, 13 patients were diagnosed with TFE3-rearranged RCC, and 24 patients had TFE3(+) ccRCC. The recurrence and new metastasis of TFE3-rearranged RCC was relatively common, even if the tumor stage was early at the first diagnosis. Through feature comparison and survival analysis, we found that TFE3-rearranged RCC was quite similar to TFE3(+) ccRCC. Compared with TFE3(−) ccRCC, TFE3(+) ccRCC tended to have a larger tumor diameter (P = 0.011), higher neutrophil/lymphocyte ratio (NLR) (P = 0.017) and metastatic potential (P = 0.022), and worse overall survival (OS) (P = 0.043) and PFS (P = 0.016). The survival analysis showed that TFE3-rearranged RCC had a worse PFS than ccRCC (P = 0.002), and TFE3(+) RCC had a worse PFS than TFE3(−) RCC (P = 0.001). According to the stratification system based on the combination of TFE3 and lymphovascular invasion (LVI), we further found that the prognosis from good to poor was TFE3(−) LVI(−), TFE3(+) LVI(−), TFE3(+) LVI(+) and TFE3(−) LVI(+), with statistically significant differences in both OS (P = 0.001) and PFS (P

BackgroundRetinal vein occlusion (RVO) is a common retinal vascular disease that can cause severe visual impairment. Many observational studies have shown that type 2 diabetes (T2DM) is associated with RVO, but it remains unknown if the association is causal. The present study aimed to perform Mendelian randomization (MR) analyses to evaluate the causal contribution of genetically predicted T2DM to RVO.MethodsWe obtained summary-level data from a genome-wide association study meta-analysis including 48,286 cases and 250,671 controls for T2DM and from a genome wide association study of 372 cases and 182,573 controls in the FinnGen project for RVO. To verify the robustness of the results, an independent validation dataset for T2DM (12,931 cases and 57,196 controls) was used. In addition to the main MR analysis using the inverse variance weighted (fixed effect) approach, sensitivity analyses and multivariable MR adjusting for common risk factors of RVO were conducted.ResultsGenetically predicted T2DM was found to be causally associated with RVO risk (odds ratio (OR)=2.823, 95% confidence interval (CI): 2.072-3.847, P=4.868×10-11). This association was supported by sensitivity analyses using the weighted median (OR=2.415, 95% CI: 1.411-4.132, P=1.294×10-3), weighted mode (OR=2.370, 95% CI: 1.321-4.252, P=5.159×10-3), maximum likelihood (OR=2.871, 95% CI: 2.100-3.924, P=3.719×10-11), MR-PRESSO (OR=2.823, 95% CI: 2.135-3.733, P=5.150×10-10), and MR-Egger (OR=2.441, 95% CI: 1.149-5.184, P=2.335×10-2) methods. In addition, this association persisted in multivariable MR after accounting for common RVO risk factors (OR=1.748, 95% CI: 1.238-2.467, P=1.490×10-3). The MR analyses using the validation dataset obtained consistent results.ConclusionThis study indicates that genetically predicted T2DM may have a causal contribution to RVO. Future studies are required to elucidate the underlying mechanisms.

As an emerging bandgap material, antimonene quantum dots (AQDs) have attracted much attention due to their unique structure and outstanding physical and chemical properties. However, the research on the optical properties of AQDs is still in the initial stage and needs further exploration. Herein, the fluorescent AQDs were synthesized by ultrasonic liquid-phase exfoliation, combined with a hydrothermal treatment process. The as-prepared AQDs exhibit good fluorescence characteristics and have a fluorescence quantum yield value of 7.56%. Besides, the AQDs show good stability under different salt concentrations. Especially, the AQDs show high selectivity and rapid detection of Fe3+, CrO42−, and Cr2O72− ions in an aqueous solution with good anti-interference ability. The relatively low limit of detection for Fe3+ based on AQDs was 6.85 µM, and the limits of detection for CrO42−, and Cr2O72− were 23.0 and 5.91 µM, respectively. The mechanism for the fluorescence quenching of the AQDs can be attributed to the synergistic effect of the internal filter effect and the oxidation–reduction reaction between the AQDs and analytes. This work provided a simple synthesis method to easily prepare the AQDs with a larger yield, which can be applied to rapidly detect Fe3+ cation, and CrO42−, and Cr2O72− anions.

BackgroundChest x-ray (CXR) is widely applied for the detection and diagnosis of children's lung diseases. Lung field segmentation in digital CXR images is a key section of many computer-aided diagnosis systems.ObjectiveIn this study, we propose a method based on deep learning to improve the lung segmentation quality and accuracy of children's multi-center CXR images.MethodsThe novelty of the proposed method is the combination of merits of TransUNet and ResUNet. The former can provide a self-attention module improving the feature learning ability of the model, while the latter can avoid the problem of network degradation.ResultsApplied on the test set containing multi-center data, our model achieved a Dice score of 0.9822.ConclusionsThis novel lung segmentation method proposed in this work based on TransResUNet is better than other existing medical image segmentation networks.

Many research results have emerged in the past decade regarding multi-agent reinforcement learning. These include the successful application of asynchronous advantage actor-critic, double deep Q-network and other algorithms in multi-agent environments, and the more representative multi-agent training method based on the classical centralized training distributed execution algorithm QMIX. However, in a large-scale multi-agent environment, training becomes a major challenge due to the exponential growth of the state-action space. In this article, we design a training scheme from small-scale multi-agent training to large-scale multi-agent training. We use the transfer learning method to enable the training of large-scale agents to use the knowledge accumulated by training small-scale agents. We achieve policy transfer between tasks with different numbers of agents by designing a new dynamic state representation network, which uses a self-attention mechanism to capture and represent the local observations of agents. The dynamic state representation network makes it possible to expand the policy model from a few agents (4 agents, 10 agents) task to large-scale agents (16 agents, 50 agents) task. Furthermore, we conducted experiments in the famous real-time strategy game Starcraft II and the multi-agent research platform MAgent. And also set unmanned aerial vehicles trajectory planning simulations. Experimental results show that our approach not only reduces the time consumption of a large number of agent training tasks but also improves the final training performance.

In bacteria, DegS protease functions as an activating factor of the σE envelope stress response system, which ultimately activates the transcription of stress response genes in the cytoplasm. On the basis of high-throughput RNA sequencing, we have previously found that degS knockout inhibits the expression of flagellum synthesis- and chemotaxis-related genes, thereby indicating that DegS may be involved in the regulation of V. cholerae motility. In this study, we examined the relationships between DegS and motility in V. cholerae. Swimming motility and chemotaxis assays revealed that degS or rpoE deletion promotes a substantial reduction in the motility and chemotaxis of V. cholerae, whereas these activities were restored in ΔdegS::degS and ΔdegSΔrseA strains, indicating that DegS is partially dependent on σE to positively regulate V. cholerae activity. Gene-act network analysis revealed that the cAMP–CRP–RpoS signaling pathway, which plays an important role in flagellar synthesis, is significantly inhibited in ΔdegS mutants, whereas in response to the overexpression of cyaA/crp and rpoS in the ΔdegS strain, the motility and chemotaxis of the ΔdegS + cyaA/crp and ΔdegS + rpoS strains were partially restored compared with the ΔdegS strain. We further demonstrated that transcription levels of the flagellar regulatory gene flhF are regulated by DegS via the cAMP–CRP–RpoS signaling pathway. Overexpression of the flhF gene in the ΔdegS strain partially restored motility and chemotaxis. In addition, suckling mouse intestinal colonization experiments indicated that the ΔdegS and ΔrpoE strains were characterized by the poor colonization of mouse intestines, whereas colonization efficacy was restored in the ΔdegSΔrseA, ΔdegS + cyaA/crp, ΔdegS + rpoS, and ΔdegS + flhF strains. Collectively, our findings indicate that DegS regulates the motility and chemotaxis of V. cholerae via the cAMP–CRP–RpoS–FlhF pathway, thereby influencing the colonization of suckling mouse intestines.

Plastic particle pollution poses an emerging threat to ecological and human health. Laboratory animal studies have illustrated that nano-sized plastics can accumulate in the testis and cause testosterone deficiency and spermatogenic impairment. In this study, TM3 mouse Leydig cells were in vitro exposed to polystyrene nanoparticles (PS-NPs, size 20 nm) at dosages of 50, 100 and 150 μg/mL to investigate their cytotoxicity. Our results demonstrated that PS-NPs can be internalized into TM3 Leydig cells and led to a concentration-dependent decline in cell viability. Furthermore, PS-NPs stimulation amplified ROS generation and initiated cellular oxidative stress and apoptosis. Moreover, PS-NPs treatment affected the mitochondrial DNA copy number and collapsed the mitochondrial membrane potential, accompanied by a disrupted energy metabolism. The cells exposed to PS-NPs also displayed a down-regulated expression of steroidogenesis-related genes StAR, P450scc and 17β-HSD, along with a decrease in testosterone secretion. In addition, treatment with PS-NPs destructed plasma membrane integrity, as presented by increase in lactate dehydrogenase release and depolarization of cell membrane potential. In summary, these data indicated that exposure to PS-NPs in vitro produced cytotoxic effect on Leydig cells by inducing oxidative injury, mitochondrial impairment, apoptosis, and cytomembrane destruction. Our results provide new insights into male reproductive toxicity caused by NPs.

BackgroundLow back pain is the leading cause of years lived with disability worldwide. The aim of this study was to evaluate whether dried fruit intake causally protects against low back pain using two-sample Mendelian randomization (MR).MethodsWe obtained summary-level data for dried fruit intake (N = 421,764) from the IEU Open GWAS Project. Forty-one independent genetic variants proxied dried fruit intake. The corresponding data for low back pain were derived from the FinnGen project (13,178 cases and 164,682 controls; discovery data) and the Neale lab (5,423 cases and 355,771 controls; replication data). We conducted univariable and multivariable MR analyses.ResultsIn the univariable MR analysis, the inverse variance weighted estimate showed that greater dried fruit intake was associated with decreased risk of low back pain [odds ratio (OR) = 0.435, 95% confidence interval (CI): 0.287–0.659, P = 8.657 × 10−5]. Sensitivity analyses using the MR-Egger (OR = 0.078, 95% CI: 0.013–0.479, P = 0.009), maximum likelihood (OR = 0.433, 95% CI: 0.295–0.635, P = 1.801 × 10−5), weighted median (OR = 0.561, 95% CI: 0.325–0.967, P = 0.038) and Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) (OR = 0.454, 95% CI: 0.302–0.683, P = 4.535 × 10−4) methods showed consistent results. No evidence of directional pleiotropy was identified according to the Egger intercept (intercept P-value = 0.065) or applying the MR-PRESSO method (global test P-value = 0.164). The replication analysis yielded similar results. The multivariable MR revealed that the inverse association between dried fruit intake and low back pain was consistent after adjustment for fresh fruit intake, body mass index, current tobacco smoking, alcohol intake frequency, total body bone mineral density, serum 25-hydroxyvitamin D levels, and vigorous physical activity.ConclusionThis MR study provides evidence to support that dried fruit intake causally protects against low back pain.

Pretension is regarded as an effective way to suppress the draping defects caused by the excessive shearing deformation of preforms during the manufacturing of woven composites. However, the research of shear-pretension coupling behavior on the 3D woven fabric uniform and variable thickness structures has not been carried out. In present study, the behavior of the two kinds of woven fabric structures is investigated. The picture frame shear test for fabrics are conducted with applied pre-tension for the work. The relationship between shear stress and shear angle under different pre-tension levels of the two kinds of fabrics is analyzed. Furthermore, the detailed comparison of shear-pretension coupling behavior between the two kinds of woven fabric structures is also analyzed. Finally, the effect of variable thickness condition on the in-plane shear properties for woven fabric variable thickness structure is investigated. The research provides experimental data support for the forming design of preforms of heterogeneous 3D composite structures.

Abstract Background Lymphatic metastasis has been associated with poor prognosis in bladder cancer patients with limited therapeutic options. Emerging evidence shows that heat shock factor 1 (HSF1) drives diversified transcriptome to promote tumor growth and serves as a promising therapeutic target. However, the roles of HSF1 in lymphatic metastasis remain largely unknown. Herein, we aimed to illustrate the clinical roles and mechanisms of HSF1 in the lymphatic metastasis of bladder cancer and explore its therapeutic potential. Methods We screened the most relevant gene to lymphatic metastasis among overexpressed heat shock factors (HSFs) and heat shock proteins (HSPs), and analyzed its clinical relevance in three cohorts. Functional in vitro and in vivo assays were performed in HSF1‐silenced and ‐regained models. We also used Co‐immunoprecipitation to identify the binding proteins of HSF1 and chromatin immunoprecipitation and dual‐luciferase reporter assays to investigate the transcriptional program directed by HSF1. The pharmacological inhibitor of HSF1, KRIBB11, was evaluated in popliteal lymph node metastasis models and patient‐derived xenograft models of bladder cancer. Results HSF1 expression was positively associated with lymphatic metastasis status, tumor stage, advanced grade, and poor prognosis of bladder cancer. Importantly, HSF1 enhanced the epithelial‐mesenchymal transition (EMT) of cancer cells in primary tumor to initiate metastasis, proliferation of cancer cells in lymph nodes, and macrophages infiltration to facilitate multistep lymphatic metastasis. Mechanistically, HSF1 interacted with protein arginine methyltransferase 5 (PRMT5) and jointly induced the monomethylation of histone H3 at arginine 2 (H3R2me1) and symmetric dimethylation of histone H3 at arginine 2 (H3R2me2s). This recruited the WD repeat domain 5 (WDR5)/mixed‐lineage leukemia (MLL) complex to increase the trimethylation of histone H3 at lysine 4 (H3K4me3); resulting in upregulation of lymphoid enhancer‐binding factor 1 (LEF1), matrix metallopeptidase 9 (MMP9), C‐C motif chemokine ligand 20 (CCL20), and E2F transcription factor 2 (E2F2). Application of KRIBB11 significantly inhibited the lymphatic metastasis of bladder cancer with no significant toxicity. Conclusion Our findings reveal a novel transcriptional program directed by the HSF1‐PRMT5‐WDR5 axis during the multistep process of lymphatic metastasis in bladder cancer. Targeting HSF1 could be a multipotent and promising therapeutic strategy for bladder cancer patients with lymphatic metastasis.

The traditional high-level remote landslide recognition efficiency which relies on the artificial discrimination of geological experts is low. In this paper, an automatic landslide terrain recognition model based on deep learning is developed to improve the efficiency of the screening of potential landslide hazard in a large area. The model takes remote sensing images, DEM data, geological zones, river system and other geological observation data of the target area as input. For the huge difference of different types of observation data, a feature branch network is designed and constructed to accurately extract the corresponding landslide features: Among them, deep network architecture is used to extract complex features from optical image data, and shallow network architecture is used to extract features from structured data such as altitude, geological composition, river and fault zone distribution. Subsequently, a feature fusion module was designed to fuse the extraction results of the two networks to obtain a comprehensive landslide hazard feature. The model performs semantic segmentation of the landslide area based on the extracted landslide features, and achieves accurate pixel-level landslide terrain classification and positioning. The experimental results show that the recognition accuracy(ACC) of the model reaches 0.85, which can provide technical support for automatic landslide identification.

Abstract Background The azygos lobe (AL) combined with partial anomalous pulmonary venous return (PAPVR) is comparatively uncommon as well as in radical surgery for right lung cancer. Case presentation We herein present an extremely rare case of lung cancer coexisting with AL and asymptomatic PAPVR, which was diagnosed with preoperative contrast three-dimensional reconstruction and received radical surgery by thoracoscopy. During the surgery, we preserved azygos vein successfully and found a split type of PAPVR in right upper pulmonary vein. Conclusions AL combined with PAPVR may cause confusion on the vascular separation and disconnection of the right pulmonary hilar. However, preoperative 3D reconstruction is more conducive to the correct performing of this type of surgery.

Abstract Background Till now, no study has focused on the functions of RNASEH1 antisense RNA 1 (RNASEH1‐AS1) in non‐small cell lung cancer (NSCLC). Accordingly, we measured the expression of RNASEH1‐AS1 in NSCLC and characterized its functions in detail. Finally, our research elucidated the mechanisms that occurred downstream of RNASEH1‐AS1. Methods RNASEH1‐AS1 expression was examined utilizing TCGA database and qRT‐PCR. Functional experiments were conducted to study the tumor‐associated functions of RNASEH1‐AS1. The targeting relationship among RNASEH1‐AS1, microRNA‐516a‐5p (miR‐516a‐5p), and forkhead box K1 (FOXK1) was revealed utilizing RNA immunoprecipitation and luciferase reporter assays. Results Utilizing TCGA database and our own cohort, we found a significantly increased level of RNASEH1‐AS1 in NSCLC. The high level of RNASEH1‐AS1 was markedly related with poor clinical outcomes. Knockdown of RNASEH1‐AS1 expression inhibited NSCLC cell growth, metastatic capacities, and epithelial‐mesenchymal transition and promoted the apoptosis in vitro, whereas RNASEH1‐AS1 overexpression exerted the opposite effects. Additionally, knocking down RNASEH1‐AS1 expression suppressed tumor growth in vivo. RNASEH1‐AS1 was confirmed to act as a miR‐516a‐5p sponge, consequently upregulating FOXK1 expression in NSCLC cells. As revealed by the subsequent rescue experiments, the miR‐516a‐5p/FOXK1 axis served as a downstream effector of RNASEH1‐AS1. In addition, by controlling the miR‐516a‐5p/FOXK1 axis, RNASEH1‐AS1 was capable of activating the Wnt/β‐catenin pathway. Conclusion RNASEH1‐AS1 exacerbated the oncogenicity of NSCLC by affecting the miR‐516a‐5p/FOXK1 axis and consequently promoting the activation of Wnt/β‐catenin pathway. Our newly identified RNASEH1‐AS1/miR‐516a‐5p/FOXK1/Wnt/β‐catenin network may offer an interesting foundation for NSCLC treatment in the clinic.

The riparian zone is a typical groundwater-surface water interaction zone, and there are few research reports on the behavior of arsenic in this interaction zone under different hydrodynamic conditions. In this study, the river sand samples from the riparian zone are collected to carry out indoor column experiments, the influence of different hydrodynamic factors (including flow velocity and particle size) on the migration of arsenic in the river sand are analyzed, and related models are established. The results show that (1) at a flow rate of 0.5 mL/min, the adsorption rate of the river sand on As(V) and the time required to reach an equilibrium state are both faster than those on As(III), and the smaller the particle size, the more obvious the phenomenon; at a flow rate of 1.0 mL/min, the adsorption rate of the river sand with different particle sizes on As(V) increases with the increasinng particle size, but there is no significant difference in the adsorption of As(III). (2) In a packed column filled with sand of the same particle size, the adsorption capacity of the river sand for As(III) and As(V) decreases with the increasing flow velocity. (3) Under the conditions of different flow rates and particle sizes, the migration processes of As(III) and As(V) in the sand column are more in line with the Thomas model, and the fitting R2 are higher than those of the Yoon-Nelson and Adams-Bohart models under the same conditions. Among them, at low flow rates, the Thomas model fitting R2 (≥0.94) to the migration processes of As(III) and As(V) in the particle size of 0.15−0.25 mm are significantly better than that of the larger particle size of 1.00−2.00 mm. At high flow rates, the model has little difference in fitting R2 to the migration process of arsenic in different particle sizes.

In this paper a time-fractional telegraph equation is considered. First the time-fractional telegraph equation is transformed into an integral-differential equation with a weakly singular kernel. Then an integral-difference discretization scheme on a graded mesh is developed to approximate the integral-differential equation. The possible singularity of the exact solution is taken into account in the convergence analysis. It is proved that the scheme is second-order convergent for both the spatial discretization and the time discretization. Numerical experiments confirm the validity of the theoretical results.

A new type dissimilar redundant actuation system (NT-DRAS), which is composed of an electro-hydrostatic actuator (EHA) and an electro-mechanical actuator (EMA), is applied in high value unmanned aerial vehicles such as the future near space vehicles to improve their reliability and performance index simultaneously. Further improvement in the flight safety is achieved with the fault-tolerant control (FTC) technique which deals with system faults. This paper proposes a novel convex optimization-based fault-tolerant control (CO-FTC) strategy for the NT-DRAS subject to gradual faults which are included in the state space representation of the system. A convex analysis-based treatment for system uncertainty caused by gradual faults is applied to determine the control gain matrix. The existence condition of the control gain matrix is optimized in the linear matrix inequality (LMI) form. Finally, the determined subsystems based on the novel technique is used to solve the modeled robust FTC problem. Case studies of NT-DRAS subject to different gradual faults have been accomplished to illustrate the FTC necessity for NT-DRAS. Furthermore, the effectiveness of the proposed CO-FTC strategy is validated by comparative analysis of the simulation results.

The requirements for drilling bentonites are tightening due to ever-increasing demands for petroleum resources, coupled with cost and reaction technology constraints. In addition to raising the risk of drilling, bentonite’s poor performance also raises the possibility of safety incidents and significant financial losses. Organically modified bentonites effectively reduce the consumption of drilling fluids, conserve resources, and lessen environmental effects. This paper aims to provide an overview of the several organic modification methods of bentonite for drilling fluids. It also evaluates the characteristics and application impacts of bentonite. We primarily describe the three popular modification methods represented by intercalation, coupling, and grafting. Also, this review provides the effect of molecular simulation on the investigation of structure in microconfined conditions. Through microlearning, organically modified bentonite with exceptional performance is to be further developed.

The foundation of a large river crossing bridge is often located on high and steep slopes in mountainous area, and the stability of the slope has a significant impact on the safety of the bridge. Not only the bridge load, but also the hydro-dynamical action in the reservoir area has a significant impact on the stability of the bank slope where the bridge foundation is located, especially for the toppling bank slope. This paper takes the stability of the toppling bank slope where the one major bridge foundation is located at on the Lancang River in China as an example. Through on-site exploration, drilling data and core conditions, and television images of the borehole, the geological structure of the on-site bank slope were conducted. Based on the development of the dumping body obtained from on-site exploration, corresponding indicators have been proposed from the perspectives of rock inclination, deformation, and rock quality to clarify the degree of dumping along the depth of the bank slope. The failure mechanism of the overturned bank slope under the action of a bridge was analyzed from a mechanical perspective. Numerical simulations were conducted using GeoStudio 2018:SEEP/W and FLAC3D 6.0 software to analyze the failure modes of bridge loads and hydrodynamic forces under different water levels and rainfall conditions. The seepage field characteristics, failure modes, and stability characteristics were analyzed from a two-dimensional perspective, while the displacement characteristics, plastic zone, and stress–strain characteristics were explored from a three-dimensional perspective, which revealed the evolution mode of overturned deformation under the action of bridge foundation loads. Finally, the stability of the wide slope was numerically calculated using the strength reduction method, and the stability calculation data was combined with the numerical simulation results to determine the optimal location of the bridge foundation.

Background: This paper aimed to appraise the diagnostic precision of assorted methodologies to identify left atrial/left atrial appendage (LA/LAA) thrombus through a network meta-assessment. Methods: Methodologically, we conducted a comprehensive literature search across multiple databases. Utilizing the risk of bias tool from the Cochrane Collaboration, methodological quality of included studies was critically assessed and potential publication bias was examined via funnel plots. The subsequent data analysis was executed using Stata software, with the most efficacious diagnostic modalities being determined based on cumulative ranking curve (SUCRA) values. Results: We scrutinized a sum of 18 papers, comprising 4102 subjects and utilizing 10 different diagnostic techniques. The hierarchical results derived from the network meta-analysis indicated that in regards to sensitivity, the dual-source cardiac computed tomography (DSCT) was superior (with a SUCRA value of 71.7%), it was succeeded by 3-minute delayed cardiac computed tomography (CCT) (scoring 66.8%), which surpassed the transesophageal echocardiography (TEE) (holding a SUCRA value of 57.5%). In terms of specificity, DSCT was the best (SUCRA value of 84.3%), followed by three dimensional (3D) cardiac magnetic resonance imaging (3D-CMRI) (SUCRA value of 78.0%), which was better than TEE (SUCRA value of 66.6%). In terms of positive likelihood ratio (PLR), 6-minute delayed CCT (SUCRA value of 85.6%) was superior to 3-minute delayed CCT (SUCRA value of 80.1%), both of which were superior to TEE (SUCRA value of 69.1%). DSCT (SUCRA value of 89.3%) had the best negative likelihood ratio (NLR), while DSCT (SUCRA value of 79.9%) had the highest accuracy. Conclusions: This study demonstrated that DSCT outperformed TEE in sensitivity, specificity, NLR, and accuracy in identifying thrombus of LA/LAA among patients suffering from atrial fibrillation. Our conclusion is that DSCT is the best in diagnosing LA/LAA. In addition, 3D-CMRI and 3-minute delayed CCT are expected to replace TEE.

A boron and iron co-doped biochar (B-Fe/biochar) from Masson pine bark was fabricated and used to activate peroxydisulfate (PDS) for the degradation of guaiacol (GL). The roles of the dopants and the contribution of the radical and non-radical oxidations were investigated. The results showed that the doping of boron and iron significantly improved the catalytic activity of the biochar catalyst with a GL removal efficiency of 98.30% within 30 min. The degradation of the GL mainly occurred through the generation of hydroxyl radicals (·OHs) and electron transfer on the biochar surface, and a non-radical degradation pathway dominated by direct electron transfer was proposed. Recycling the B-Fe/biochar showed low metal leaching from the catalyst and satisfactory long-term stability and reusability, providing potential insights into the use of metal and non-metal co-doped biochar catalysts for PDS activation.

In complex systems constrained by multiple factors, it is very important to identify the key influencing factors for mastering the evolution and development law of a system and for obtaining scientific decision-making suggestions or schemes. At present, the method based on experimental simulation is limited by the difficulty of system model construction; DEMATEL (Factual Decision Trial and Evaluation Laboratory) is inevitably influenced by subjective factors. In view of this, we propose a novel model based on heuristic causal inference. By combining the network analysis in complex network science, the model defines the global/local causal pathway and the causal pathway’s length in the causal network and takes the causal pathway contribution degree as an indicator to measure the approximate causal effects. The model includes steps such as causal network learning, causal pathway contribution degree calculation, and key influencing factor identification. The model uses the Fast Causal Inference (FCI) algorithm with prior knowledge to learn the global causal network of the complex system and uses the heuristic causal inference to calculate the causal pathway contribution degree. The heuristic method draws on the idea of complex network topology analysis and measures the influence degree between variables by the number and distance of causal pathways. The key influencing factors are finally identified according to the causal pathway contribution degree. Based on the SECOM dataset, we carried out simulation experiments and demonstrated the feasibility and effectiveness of the proposed method.

Community detection is an important task in the analysis of complex networks, which is significant for mining and analyzing the organization and function of networks. As an unsupervised learning algorithm based on the particle competition mechanism, stochastic competitive learning has been applied in the field of community detection in complex networks, but still has several limitations. In order to improve the stability and accuracy of stochastic competitive learning and solve the problem of community detection, we propose an unsupervised community detection algorithm LNSSCL (Local Node Similarity-Integrated Stochastic Competitive Learning). The algorithm calculates node degree as well as Salton similarity metrics to determine the starting position of particle walk; local node similarity is incorporated into the particle preferential walk rule; the particle is dynamically adjusted to control capability increments according to the control range; particles select the node with the strongest control capability within the node to be resurrected; and the LNSSCL algorithm introduces a node affiliation selection step to adjust the node community labels. Experimental comparisons with 12 representative community detection algorithms on real network datasets and synthetic networks show that the LNSSCL algorithm is overall better than other compared algorithms in terms of standardized mutual information (NMI) and modularity (Q). The improvement effect for the stochastic competition learning algorithm is evident, and it can effectively accomplish the community detection task in complex networks.

Polygonatum sibiricum Polysaccharide (PsP) with antioxidant function is the main active component of Polygonatum sibiricum (P.sibiricum). The currently poor extraction yield and extraction methods of PsP cannot meet the application of that in food industrial production. In this research, an ultrasound-assisted extraction-deep eutectic solvents (UAE-DESs) method, which has never been used in the PsP industry, was first used to extract PsP. The extraction conditions were optimized by the response surface method (RSM). Both the extraction yield and antioxidant function were simultaneously considered during the optimization process. The indicators of PsP’s level and antioxidant activity in vitro were used to present the extraction yield of the UAE-DESs method, the purity, and the antioxidant effect of PsP. Under the optimal conditions, which included a liquid–solid ratio of 26:1 (mL:g), extraction temperature of 80 °C, ultrasonic time of 51 min, and ultrasonic power of 82 W, the PsP extraction yield could reach (43.61 ± 0.09)%, which was obviously higher than single DESs (33.81%) and UAE (5.83%), respectively, and the PsP appeared favorably antioxidant function. This research proposed an efficient extraction method for PsP, filled the basic research gap, and further improved the development of PsP as a dietary supplement with antioxidant function in the food industry.

Abstract Blood pressure variability (BPV) is significantly associated with cardiovascular diseases (CVD) and mortality in hemodialysis patients. However, the relationship between blood pressure and CVD in hemodialysis patients is complex and affected by many factors. The present study aimed to assess the association of long‐term predialysis BPV with all‐cause mortality and major adverse cardiovascular events (MACE). One thousand seven hundred twenty‐seven patients receiving maintenance hemodialysis were recruited in nine hemodialysis centers. Predialysis BPV was assessed over 1‐year intervals. Outcomes included all‐cause mortality and MACE during follow‐up periods. The mean age of the final cohort was 59 years, of which 57% were males. Greater predialysis systolic BPV was associated with an increased risk of all‐cause mortality (adjusted hazard ratio, 1.101; 95% confidence intervals 1.064–1.140) and MACE (adjusted hazard ratio, 1.091; 95% confidence intervals 1.059–1.125). Results were similar when systolic BPV was stratified by baseline systolic blood pressure. In conclusion, greater predialysis BPV among hemodialysis patients was associated with all‐cause mortality and MACE. Strategies to reduce blood pressure variability might be beneficial for hemodialysis patients.

Bauxite-type vanadium deposit in north sichuan is a newly discovered type of vanadium deposit. Through the study of process mineralogy and selectivity of vanadium, it is found that vanadium has two kinds of occurrence states: The main is an independent mineral in the form of vanadite, and the other is in the form of isomorphism in sericite and illite. The experimental study on the washability of vanadium ore shows that the bauxite type vanadium ore is economic. The valuable element vanadium and molybdenum in ore can be recovered effectively by the combined flowsheet of “ Recovery of sulfide by heavy separation- recovery of vanadium and molybdenum from tailings by roasting in air and alkaline leaching-Recovery of clay ore by leaching residue”. The associated pyrite and clay minerals in ore are utilized synthetically. After the test, the slag leaching rate of vanadium is 74.42%, the liquid leaching rate of vanadium is 75.97%, the slag leaching rate of molybdenum is 88.77%, the liquid leaching rate of molybdenum is 91.00%.

Abstract Background Myocarditis is a cardiomyopathy associated with the inflammatory response. Rosuvastatin (RS) demonstrates cardioprotective effect in the clinical setting, although its cellular and molecular mechanisms in ameliorating myocarditis are largely unknown. MG53 (muscle-specific E3 ligase Mitsugumin 53), a newly identified striated muscle-specific protein, is involved in skeletal muscle membrane repair. We aimed to explore whether RS mediated the repair of cardiomyocytes in an MG53-dependent manner. Methods The RS-induced upregulation of MG53 was determined using RT-qPCR and western blotting. A lipopolysaccharide (LPS)-induced cell inflammatory model was constructed using rat cardiac muscle cell H9C2. Inflammatory injury was evaluated according to the alterations of cell viability, mitochondrial membrane potential, cell apoptosis, and expression of pro-inflammatory cytokines (interleukin-1β, interleukin-6, tumor necrosis factor-α, and monocyte chemoattractant protein-1). Small interfering RNAs (siRNAs) were used to silence MG53. The cardioprotective effect of RS and the inhibition of this protection by MG53 silence were evaluated in the forementioned in vitro model. The underlying mechanism was finally investigated using western blotting to detected the expressions of apoptotic markers (Bcl-2, Bax, Cleaved caspase-9, Cleaved caspase-3), cell cycle regulatory factors (Cyclin A, Cyclin E1, Cyclin D1, CDK2), and components involved in NF-κB signaling pathway (p-IκBa, Iκba, p-p65, p65). Results RS ameliorated LPS-induced inflammatory injury. RS upregulated the expression of MG53. MG53 was crucial for the RS-mediated repair response in vitro. Ablation of MG53 inhibited the RS-mediated protective effect. Furthermore, RS and MG53 interact in multiple signaling pathways to modulate recovery. Conclusion RS exerts cardioprotective effect in an MG53-dependent manner. MG53 may serve as a novel drug target for myocarditis treatment.

Gait analysis and evaluation are vital for disease diagnosis and rehabilitation. Current gait analysis technologies require wearable devices or high-resolution vision systems within a limited usage space. To facilitate gait analysis and quantitative walking-ability evaluation in daily environments without using wearable devices, a mobile gait analysis and evaluation system is proposed based on a cane robot. Two laser range finders (LRFs) are mounted to obtain the leg motion data. An effective high-dimensional Takagi-Sugeno-Kang (HTSK) fuzzy system, which is suitable for high-dimensional data by solving the saturation problem caused by softmax function in defuzzification, is proposed to recognize the walking states using only the motion data acquired from LRFs. The gait spatial-temporal parameters are then extracted based on the gait cycle segmented by different walking states. Besides, a quantitative walking-ability evaluation index is proposed in terms of the conventional Tinetti scale. The plantar pressure sensing system records the walking states to label training data sets. Experiments were conducted with seven healthy subjects and four patients. Compared with five classical classification algorithms, the proposed method achieves the average accuracy rate of 96.57%, which is improved more than 10%, compared with conventional Takagi-Sugeno-Kang (TSK) fuzzy system. Compared with the gait parameters extracted by the motion capture system OptiTrack, the average errors of step length and gait cycle are only 0.02 m and 1.23 s, respectively. The comparison between the evaluation results of the robot system and the scores given by the physician also validates that the proposed method can effectively evaluate the walking ability.

Text classification is one of the most fundamental tasks in text data analysis. Generally, textual data are extensive in scale and complex in the inherent relationship, leading to low accuracy in traditional classification models. This paper proposes a multi-label classification model based on multi-layer neural network architecture. We first construct a dual-attention mechanism graph neural network (named DGAT for short) to fuse the typological and informational features of the target node and the connected nodes. Secondly, we also build a multi-layer network architecture with multiple DGATs to expand the range of neighborhood nodes participating in the feature fusion to meet the needs of classifying different datasets. To ensure the learning ability of the model, we also use the residual network to solve the problem of error rise and gradient descent caused by multi-layer network architecture. Finally, we conducted a large number of experiments on five benchmark datasets. The results show that the accuracy of the proposed model is significantly better than that of the traditional models, and that there is a noticeable improvement when compared with other deep learning methods.

Abstract Background Preoperative diagnosis of pheochromocytoma (PHEO) accurately impacts preoperative preparation and surgical outcome in PHEO patients. Highly reliable model to diagnose PHEO is lacking. We aimed to develop a magnetic resonance imaging (MRI)-based radiomic-clinical model to distinguish PHEO from adrenal lesions. Methods In total, 305 patients with 309 adrenal lesions were included and divided into different sets. The least absolute shrinkage and selection operator (LASSO) regression model was used for data dimension reduction, feature selection, and radiomics signature building. In addition, a nomogram incorporating the obtained radiomics signature and selected clinical predictors was developed by using multivariable logistic regression analysis. The performance of the radiomic-clinical model was assessed with respect to its discrimination, calibration, and clinical usefulness. Results Seven radiomics features were selected among the 1301 features obtained as they could differentiate PHEOs from other adrenal lesions in the training (area under the curve [AUC], 0.887), internal validation (AUC, 0.880), and external validation cohorts (AUC, 0.807). Predictors contained in the individualized prediction nomogram included the radiomics signature and symptom number (symptoms include headache, palpitation, and diaphoresis). The training set yielded an AUC of 0.893 for the nomogram, which was confirmed in the internal and external validation sets with AUCs of 0.906 and 0.844, respectively. Decision curve analyses indicated the nomogram was clinically useful. In addition, 25 patients with 25 lesions were recruited for prospective validation, which yielded an AUC of 0.917 for the nomogram. Conclusion We propose a radiomic-based nomogram incorporating clinically useful signatures as an easy-to-use, predictive and individualized tool for PHEO diagnosis.

Abstract Background Epidemiological and experimental evidence has linked chronic inflammation to cancer aetiology. It is unclear whether associations for specific inflammatory biomarkers are causal or due to bias. In order to examine whether altered genetically predicted concentration of circulating cytokines are associated with cancer development, we performed a two-sample Mendelian randomisation (MR) analysis. Methods Up to 31,112 individuals of European descent were included in genome-wide association study (GWAS) meta-analyses of 47 circulating cytokines. Single nucleotide polymorphisms (SNPs) robustly associated with the cytokines, located in or close to their coding gene (cis), were used as instrumental variables. Inverse-variance weighted MR was used as the primary analysis, and the MR assumptions were evaluated in sensitivity and colocalization analyses and a false discovery rate (FDR) correction for multiple comparisons was applied. Corresponding germline GWAS summary data for five cancer outcomes (breast, endometrial, lung, ovarian, and prostate), and their subtypes were selected from the largest cancer-specific GWASs available (cases ranging from 12,906 for endometrial to 133,384 for breast cancer). Results There was evidence of inverse associations of macrophage migration inhibitory factor with breast cancer (OR per SD = 0.88, 95% CI 0.83 to 0.94), interleukin-1 receptor antagonist with endometrial cancer (0.86, 0.80 to 0.93), interleukin-18 with lung cancer (0.87, 0.81 to 0.93), and beta-chemokine-RANTES with ovarian cancer (0.70, 0.57 to 0.85) and positive associations of monokine induced by gamma interferon with endometrial cancer (3.73, 1.86 to 7.47) and cutaneous T-cell attracting chemokine with lung cancer (1.51, 1.22 to 1.87). These associations were similar in sensitivity analyses and supported in colocalization analyses. Conclusions Our study adds to current knowledge on the role of specific inflammatory biomarker pathways in cancer aetiology. Further validation is needed to assess the potential of these cytokines as pharmacological or lifestyle targets for cancer prevention.

Abstract Osteosarcoma accounts for a frequently occurring cancer of the primary skeletal system. In osteosarcoma cells, a hypoxic microenvironment is commonly observed that drives tumor growth, progression, and heterogeneity. Hypoxia and tumor-infiltrating immune cells might be closely related to the prognosis of osteosarcoma. In this study, we aimed to determine the biomarkers and therapeutic targets related to hypoxia and immunity through bioinformatics methods to improve the clinical prognosis of patients. We downloaded the gene expression data of osteosarcoma samples and normal samples in the UCSC Xena database and GTEx database, respectively, and downloaded the validation dataset (GSE21257) in the GEO database. Subsequently, we performed GO enrichment analysis and KEGG pathway enrichment analysis on the data of the extracted osteosarcoma hypoxia-related genes. Through univariate COX regression analysis, lasso regression analysis, multivariate COX regression analysis, etc., we established a predictive model for the prognosis of osteosarcoma. Five genes, including ST3GAL4, TRIM8, STC2, TRPS1, and FAM207A, were found by screening. In particular, we analyzed the immune cell composition of each gene based on the five genes through the CIBERSORT algorithm and verified each gene at the cell and tissue level. Our findings are valuable for the clinical diagnosis and treatment of this disease.

Objective: Single-stranded DNA-binding protein 1 (SSBP1) plays an important role in DNA repair processes and the maintenance of genomic stability. The aim of this study was to evaluate the expression of SSBP1 and its prognostic value in lung adenocarcinoma (LUAD) using bioinformatics approaches. Methods: We applied databases including UALCAN, Kaplan-Meier plotter, LinkedOmics, Webgestalt, cBioPortal and TIMER2.0 in this study. Results: We found that SSBP1 expression was up-regulated in LUAD samples and was correlated with clinicopathological features including age, cancer stage, and nodal metastasis status by the UALCAN analysis. Multivariate Cox regression analysis by the Kaplan-Meier plotter showed that high SSBP1 expression was independently correlated with poor overall survival (hazard ratio = 1.63, 95% confidence interval: 1.08−2.46, logrank P = 0.02). The LinkedOmics analysis showed that 5078 genes were positively correlated with SSBP1 expression, whereas 7905 genes were negatively correlated with SSBP1 in LUAD. Functional enrichment analysis using the Webgestalt tool showed that for SSBP1 and the genes positively correlating with it, the significantly enriched biological process was ribosomal large subunit biogenesis, and the significantly enriched pathway was proteasome. According to the cBioPortal database, the frequency of SSBP1 alterations was 1.7% in LUAD patients, and patients with SSBP1 alterations had worse prognosis (logrank P = 4.26e-05) compared with those unaltered for SSBP1. Finally, SSBP1 expression was negatively correlated with B cell infiltration level (Rho = −0.193, P = 1.54e-05) and the expression of B cell biomarkers including CD79A and CD19. Conclusion: Our results suggest that SSBP1 may be a prognostic marker for human LUAD.

Ethnicity might be associated with treatment outcomes in advanced prostate cancer. This study aimed to evaluate the efficacy and safety of androgen deprivation therapy (ADT) combined with apalutamide in East Asians with metastatic castration-sensitive prostate cancer (mCSPC). The original phase 3 Targeted Investigational Treatment Analysis of Novel Anti-androgen (TITAN) trial was conducted at 260 sites in 23 countries. This subgroup analysis included patients enrolled in 62 participating centers in China, Japan, and Korea. Radiographic progression-free survival (PFS), time to prostate-specific antigen (PSA) progression, and PSA changes from baseline were compared between groups in the East Asian population. The intent-to-treat East Asian population included 111 and 110 participants in the apalutamide and placebo groups, respectively. The 24-month radiographic PFS rates were 76.1% and 52.3% in the apalutamide and placebo groups, respectively (apalutamide vs placebo: hazard ratio [HR] = 0.506; 95% confidence interval [CI], 0.302–0.849; P = 0.009). Median time to PSA progression was more favorable with apalutamide than placebo (HR = 0.210; 95% CI, 0.124–0.357; P < 0.001). Median maximum percentages of PSA decline from baseline were 99.0% and 73.9% in the apalutamide and placebo groups, respectively. The most common adverse event (AE) was rash in the apalutamide group, with a higher rate than that in the placebo group (37.3% vs 9.1%). The most common grade 3 or 4 AEs were rash (12 [10.9%]) and hypertension (12 [10.9%]) for apalutamide. The efficacy and safety of apalutamide in the East Asian subgroup of the TITAN trial are consistent with the global results.

This paper presents the development of autonomy capability for an unmanned surface vehicle (USV). The development mainly focuses on the high-level autonomy on perception, path planning, guidance and control to achieve real sea applications of the USV. First, visual recognition and point cloud data processing techniques are utilized to achieve a real-time perception of the object in the sea environment. Second, detailed path planning strategies are illustrated to plan the easily reachable path for different missions, and the classic guidance and heading controller are adopted to implement the path following algorithm. Subsequently, these autonomy algorithms run in the high-level computer and render the actuator commands for the low-level embedded control system. Finally, sea trials of the USV are conducted by attending the 2020 Zhuhai Wanshan International Intelligent Vessel Competition (IIVC) in Dong Ao Island of South China Sea. The USV accomplish three missions: 1) path following, 2) navigating around the obstacle, and 3) rescuing the drowning. Sea trial results verify the autonomy of the USV in terms of the achieved performances.

Docetaxel (DTX) is a highly effective anti-tumor drug frequently used in clinical practice. Previous reports indicated that complications after DTX therapy could be related to retinal pigment epithelial (RPE) cell dysfunction, although no direct reports of this relationship have been published. In this study, human embryonic stem cell–derived RPE (hESC-RPE) cells were used to explore the effects of DTX on their morphology, viability, apoptosis, proliferation, and cell cycle. We also searched for DTX residue in these cells. DTX had a time- and concentration-dependent inhibitory effect on hESC-RPE cell viability, and the cells only survived after 24 h of stimulation with 0.1 mg/mL of DTX. Following drug withdrawal, the cell morphology continued to change, and hESC-RPE cell damage was observed. High-performance liquid chromatography/mass spectrometry showed that some unmetabolized DTX remained in hESC-RPE cells after the 48 and 120 h DTX treatments. Flow cytometry and immunofluorescence revealed that DTX significantly enhanced apoptosis, and the Cell Counting Kit-8 assay and flow cytometry indicated that DTX inhibited cell proliferation and blocked the cell cycle. These results suggest that DTX has a direct cytotoxic effect on hESC-RPE cells. Thus, RPE cell damage after DTX treatment may present an important safety problem that could potentially limit the application of this drug in clinical practice. The findings of this study suggest that clinicians should weigh the benefits of DTX versus the risks of ocular adverse reactions rationally. Timely diagnostic evaluation and drug withdrawal will be conducive to the recovery of patients' visual acuity.

Objective To evaluate whether transcatheter or surgical aortic valve replacement (TAVR or SAVR) affects clinical and haemodynamic outcomes in symptomatic patients with moderately-severe aortic stenosis (AS).Methods Echocardiographic evidence of severe AS for enrolment in the Evolut Low Risk trial was based on site-reported measurements. For this post hoc analysis, core laboratory measurements identified patients with symptomatic moderately-severe AS (1.0

Abstract Recent advances in flexible wearable devices have boosted the remarkable development of devices for human–machine interfaces, which are of great value to emerging cybernetics, robotics, and Metaverse systems. However, the effectiveness of existing approaches is limited by the quality of sensor data and classification models with high computational costs. Here, a novel gesture recognition system with triboelectric smart wristbands and an adaptive accelerated learning (AAL) model is proposed. The sensor array is well deployed according to the wrist anatomy and retrieves hand motions from a distance, exhibiting highly sensitive and high‐quality sensing capabilities beyond existing methods. Importantly, the anatomical design leads to the close correspondence between the actions of dominant muscle/tendon groups and gestures, and the resulting distinctive features in sensor signals are very valuable for differentiating gestures with data from 7 sensors. The AAL model realizes a 97.56% identification accuracy in training 21 classes with only one‐third operands of the original neural network. The applications of the system are further exploited in real‐time somatosensory teleoperations with a low latency of

Aims To screen abnormal lncRNAs and diagnostic biomarkers in the progression of hepatocellular carcinoma through high-throughput sequencing and explore the underlying mechanisms of abnormal lncRNAs in the progression of hepatocellular carcinoma. Methods The transcriptome sequencing was used to analyze the RNA expression profile and identify differentially expressed RNAs. Hub lncRNAs were screened by combining (WGCNA, ceRNA regulatory network, PPI, GO and KEGG analyses, Kaplan-Meier curve analysis, Cox analysis, risk model construction and qPCR). Thereafter, the correlation between the expression of hub lncRNAs and tumor clinicopathological parameters was analyzed, and the hub lncRNAs were analyzed by GSEA. Finally, the effects of hub RNAs on the proliferation, migration and invasion of HepG2 cells were investigated in vitro. Results Compared with the control group, a total of 610 lncRNAs, 2,593 mRNAs and 26 miRNAs were screened in patients with hepatocellular carcinoma. Through miRNA target prediction and WGCNA, a ceRNA was constructed, comprising 324 nodes and 621 edges. Enrichment analysis showed that mRNAs in ceRNA were involved mainly in cancer development progression. Then, the ZFAS1/miR-150-5p interaction pair was screened out by Kaplan Meier curve analysis, Cox analysis and qPCR analysis. Its expression was related to tumor stage, TNM stage and patient age. ROC curve analysis showed that it has a good predictive value for the risk of hepatocellular carcinoma. GSEA showed that ZFAS1 was also enriched in the regulation of immune response, cell differentiation and proliferation. Loss-of-function experiments revealed that ZFAS1 inhibition could remarkably suppress HepG2 cell proliferation, migration and invasion in vitro. Bioinformatic analysis and luciferase reporter assays revealed that ZFAS1 directly interacted with miR-150-5p. Rescue experiments showed that a miR-150-5p inhibitor reversed the cell proliferation, migration and invasion functions of ZFAS1 knockdown in vitro. Conclusion ZFAS1 is associated with the malignant status and prognosis of patients with hepatocellular carcinoma, and the ZFAS1/miR-150-5p axis is involved in hepatocellular carcinoma progression.

ObjectiveTo investigate the diagnostic value of quantitative parameters of spectral computed tomography (CT) in ischaemic stroke areas.MethodsThe medical records of 57 patients with acute ischaemic stroke (AIS) who underwent plain computed tomography (CT) head scans, CT angiography (CTA), and CT perfusion (CTP) were retrospectively reviewed. The ischaemic areas (including the core infarct area and penumbra) and non-ischaemic areas in each patient were quantitatively analyzed using F-STROKE software. Two independent readers measured the corresponding values of the spectroscopic quantitative parameters (effective atomic number [Zeff value], iodine density value, and iodine–no-water value) in the ischaemic area and contralateral normal area alone. The differences in spectroscopic quantitative parameters between the two groups were compared, and their diagnostic efficacy was obtained.ResultsThe Zeff, iodine–no-water value, and iodine density value of the ischaemic area all showed significant lower than those of non-ischaemic tissue (P < 0.001). For differentiating the ischaemic area from non-ischaemic tissue, the area under the curve (AUC) of the Zeff value reached 0.869 (cut-off value: 7.385; sensitivity: 93.0%; specificity: 70.2%), the AUC of the iodine density value reached 0.932 (cut-off value: 0.235; sensitivity: 91.2%; specificity: 82.5%), and the AUC of the iodine–no-water value reached 0.922 (cut-off value: 0.205; sensitivity: 96.5%; specificity: 78.9%).ConclusionThe study showed the spectral CT would be a potential novel rapid method for identifying AIS. The spectral CT quantitative parameters (Zeff, iodine density values, and iodine–no-water values) can effectively differentiate the ischaemic area from non-ischaemic tissue in stroke patients.

Background and objectives: Mechanistic research suggests synergistic effects of cardiovascular disease (CVD) and dementia pathologies on cognitive decline. Interventions targeting proteins relevant to shared mechanisms underlying CVD and dementia could also be used for the prevention of cognitive impairment.Methods: We applied Mendelian randomisation (MR) and colocalization analysis to investigate the causal relationships of 90 CVD-related proteins measured by the Olink CVD I panel with cognitive traits. Genetic instruments for circulatory protein concentrations were obtained using a meta-analysis of genome-wide association studies (GWAS) from the SCALLOP consortium (N = 17,747) based on three sets of criteria: 1) protein quantitative trait loci (pQTL); 2) cis-pQTL (pQTL within ±500 kb from the coding gene); and 3) brain-specific cis-expression QTL (cis-eQTL) which accounts for coding gene expression based on GTEx8. Genetic associations of cognitive performance were obtained from GWAS for either: 1) general cognitive function constructed using Principal Component Analysis (N = 300,486); or, 2) g Factor constructed using genomic structural equation modelling (N = 11,263–331,679). Findings for candidate causal proteins were replicated using a separate protein GWAS in Icelanders (N = 35,559).Results: A higher concentration of genetically predicted circulatory myeloperoxidase (MPO) was nominally associated with better cognitive performance (p < 0.05) using different selection criteria for genetic instruments. Particularly, brain-specific cis-eQTL predicted MPO, which accounts for protein-coding gene expression in brain tissues, was associated with general cognitive function (βWald = 0.22, PWald = 2.4 × 10−4). The posterior probability for colocalization (PP.H4) of MPO pQTL with the g Factor was 0.577. Findings for MPO were replicated using the Icelandic GWAS. Although we did not find evidence for colocalization, we found that higher genetically predicted concentrations of cathepsin D and CD40 were associated with better cognitive performance and a higher genetically predicted concentration of CSF-1 was associated with poorer cognitive performance.Conclusion: We conclude that these proteins are involved in shared pathways between CVD and those for cognitive reserve or affecting cognitive decline, suggesting therapeutic targets able to reduce genetic risks conferred by cardiovascular disease.

ABSTRACT Oropharyngeal candidiasis (OPC), which has a high incidence in immunocompromised and denture stomatitis patients, is commonly caused by Candida albicans infection and in some cases develops into disseminated candidiasis throughout the throat and esophagus, resulting in high mortality. New drugs are needed to combat OPC because of the limited treatment options currently available and increasing resistance to existing drugs. Here, we confirmed that riboflavin (RF), a cofactor of flavin adenine mononucleotide and flavin adenine dinucleotide, has broad-spectrum anti-Candida activity. The formation of C. albicans hyphae and biofilm was inhibited by RF. Mechanistically, RF disrupted membrane and cell wall integrity, as well as promoting reactive oxygen species and pyruvate accumulation. Furthermore, RF targeted multiple essential pathways via functional disruption of thiamine and RF metabolic pathways, central carbon metabolism, and ribosome metabolism. Similar to the results in vitro, the inhibitory effect of RF on C. albicans hyphae was confirmed in a mouse model of OPC. Moreover, after 5 consecutive days of intraperitoneal injection, RF exhibited therapeutic efficacy, as demonstrated by phenotype investigation, the fungal burden, and histopathological analysis. These findings revealed that RF exerts a multifaceted anti-Candida effect and has potential benefits in the treatment of OPC. IMPORTANCE Candida species are common pathogens in fungal infections, causing mucosal infection and invasive infection in immunodeficient patients. Given the limited classes of drugs and resistance to these drugs, new antifungal agents need to be developed. Drug repurposing is a potential method for antifungal drug development. This study demonstrated that riboflavin (RF) exhibited broad-spectrum anti-Candida activity. RF affected multiple targets involving the membrane and cell wall integrity, the accumulation of reactive oxygen species and pyruvate, and the altered metabolic pathways in C. albicans. Moreover, RF exhibited efficacy in the treatment of C. albicans in an oropharyngeal candidiasis mouse model. Taken together, the antifungal activity and the promising clinical application of RF were highlighted.

Acute lung injury (ALI) is a common respiratory disease in clinics, which is characterized by alveolar-capillary membrane loss, plasma protein leakage, pulmonary edema, massive neutrophil infiltration, and the release of proinflammatory cytokines and mediators. Rhodiola rosea L. an adaptogenic plant rich in phenylethanoloids, phenylpropanoids, monoterpenes, has anti-inflammatory and antioxidant effects. We hope to verify the relieving effect of total glycosides of Rhodiola rosea L. (RTG) on ALI in mice and clarify its mechanism through this study. In this study, we identified the effect and mechanism of RTG on ALI through LPS-induced ALI mice. After RTG treatment, the pathological structure of lung tissue in ALI mice induced by LPS was significantly improved, and the infiltration of inflammatory cells was reduced. In addition, RTG reduced the production of IL-6, IL-1β, and TNF-α in the serum of ALI mice and reduced the content or activity of MPO, T-SOD, GSH, and MDA in lung tissue. RNAseq analysis showed that RTG ameliorated LPS-induced ALI through anti-inflammatory, reduced immune response, and anti-apoptotic activities. The western blotting analysis confirmed that RTG could down-regulate the expression levels of TLR4, MyD88, NF-κB p65, and p-IκBα/IκBα. These results suggest that RTG can attenuate LPS-induced ALI through antioxidants and inhibition of the TLR4/NF-κB pathway.

BackgroundVirtual reality (VR) can be used to build many different scenes aimed at reducing study-related stress. However, only few academic experiments on university students for preference testing have been performed. ObjectiveThis study aims to assess the preference of VR games for stress and depression treatment using a discrete choice experiment (DCE). MethodsA total of 5 different attributes were selected based on the depression therapy parameters and attributes related to VR: (1) treatment modality; (2) therapy duration; (3) perceived remission rate; (4) probability of adverse events; and the (5) monthly cost of adding treatment to a discrete choice experiment. By comparing different attributes and levels, we could draw some conclusions about the depression therapy testing preference for university students; 1 university student was responsible for VR scene development and 1 for participant recruitment. ResultsThe utility value of different attributes for “0% Probability of adverse events” was higher than others (99.22), and the utility value of VR treatment as the most popular treatment method compared with counseling and medicine treatment was 80.95. Three parameter aspects (different treatments for depression) were statistically significant (P

BackgroundRisk stratification of elderly patients with ischemic stroke (IS) who are admitted to the intensive care unit (ICU) remains a challenging task. This study aims to establish and validate predictive models that are based on novel machine learning (ML) algorithms for 28-day in-hospital mortality in elderly patients with IS who were admitted to the ICU.MethodsData of elderly patients with IS were extracted from the electronic intensive care unit (eICU) Collaborative Research Database (eICU-CRD) records of those elderly patients admitted between 2014 and 2015. All selected participants were randomly divided into two sets: a training set and a validation set in the ratio of 8:2. ML algorithms, such as Naïve Bayes (NB), eXtreme Gradient Boosting (xgboost), and logistic regression (LR), were applied for model construction utilizing 10-fold cross-validation. The performance of models was measured by the area under the receiver operating characteristic curve (AUC) analysis and accuracy. The present study uses interpretable ML methods to provide insight into the model's prediction and outcome using the SHapley Additive exPlanations (SHAP) method.ResultsAs regards the population demographics and clinical characteristics, the analysis in the present study included 1,236 elderly patients with IS in the ICU, of whom 164 (13.3%) died during hospitalization. As regards feature selection, a total of eight features were selected for model construction. In the training set, both the xgboost and NB models showed specificity values of 0.989 and 0.767, respectively. In the internal validation set, the xgboost model identified patients who died with an AUC value of 0.733 better than the LR model which identified patients who died with an AUC value of 0.627 or the NB model 0.672.ConclusionThe xgboost model shows the best predictive performance that predicts mortality in elderly patients with IS in the ICU. By making the ML model explainable, physicians would be able to understand better the reasoning behind the outcome.