Huopuxialing Decoction: A Promising Candidate for Precancerous Lesions of Gastric Cancer Treatment Based on Bioinformatics and Experimental Verification.

BACKGROUND: The Precancerous Lesion of Gastric Cancer (PLGC) is an early stage in the development of gastric cancer. The clinical application of HPXLD has been found to be effective in treating PLGC, but the mechanism of how HPXLD acts on PLGC is still unclear. OBJECTIVE: The objectives of this study were to reveal the molecular mechanism of how HPXLD can be used to treat PLGC and investigate this mechanism through bioinformatics and experimental validation. METHODS: PLGC-associated target genes were identified through bioinformatics analysis. A rat model of PLGC was induced using N-methyl-N'-nitro-N-nitrosoquanidine (MNNG) in combination with ranitidine, hot saline, ethanol, and intermittent fasting, with interventions by HPXLD. The pathological alterations in gastric mucosa were assessed through Hematoxylin-eosin staining (HE). Immunohistochemistry (IHC) and Western blot analyses were employed to evaluate the changes in expression levels of inflammation-related proteins. RESULTS: After conducting bioinformatics analysis, it was found that there were 23 HPXLDPLGC crossover genes, which were significantly enriched in the IL-17 signaling pathway, TNF signaling pathway, and NF-kappa B signaling pathway. The results of HE showed that HPXLD was effective in improving gastric mucosal histopathological changes. Additionally, the IHC results demonstrated that HPXLD was able to downregulate the expression of IL-6, COX-2, MCP- 1, and MMP-9. Furthermore, Western blot analysis revealed that HPXLD was able to downregulate the expressions of IL-6, IL-17RA, ACT1, NF-κB, and TNF-α. CONCLUSION: HPXLD has been shown to improve PLGC by reducing the expression of inflammation- related proteins. This suggests that HPXLD may potentially be a treatment option for PLGC.

Iterative-Weighted Thresholding Method for Group-Sparsity-Constrained Optimization With Applications.

Taking advantage of the natural grouping structure inside data, group sparse optimization can effectively improve the efficiency and stability of high-dimensional data analysis, and it has wide applications in a variety of fields such as machine learning, signal processing, and bioinformatics. Although there has been a lot of progress, it is still a challenge to construct a group sparse-inducing function with good properties and to identify significant groups. This article aims to address the group-sparsity-constrained minimization problem. We convert the problem to an equivalent weighted lp,q -norm ( , ) constrained optimization model, instead of its relaxation or approximation problem. Then, by applying the proximal gradient method, a solution method with theoretical convergence analysis is developed. Moreover, based on the properties proved in the Lagrangian dual framework, the homotopy technique is employed to cope with the parameter tuning task and to ensure that the output of the proposed homotopy algorithm is an L -stationary point of the original problem. The proposed weighted framework, with the central idea of identifying important groups, is compatible with a wide range of support set identification strategies, which can better meet the needs of different applications and improve the robustness of the model in practice. Both simulated and real data experiments demonstrate the superiority of the proposed method in terms of group feature selection accuracy and computational efficiency. Extensive experimental results in application areas such as compressed sensing, image recognition, and classifier design show that our method has great potential in a wide range of applications. Our codes will be available at https://github.com/jianglanfan/HIWT-GSC.

Orientin Promotes Antioxidant Capacity, Mitochondrial Biogenesis, and Fiber Transformation in Skeletal Muscles through the AMPK Pathway.

The sleep-breathing condition obstructive sleep apnea (OSA) is characterized by repetitive upper airway collapse, which can exacerbate oxidative stress and free radical generation, thereby detrimentally impacting both motor and sensory nerve function and inducing muscular damage. OSA development is promoted by increasing proportions of fast-twitch muscle fibers in the genioglossus. Orientin, a water-soluble dietary C-glycosyl flavonoid with antioxidant properties, increased the expression of slow myosin heavy chain (MyHC) and signaling factors associated with AMP-activated protein kinase (AMPK) activation both in vivo and in vitro. Inhibiting AMPK signaling diminished the effects of orientin on slow MyHC, fast MyHC, and Sirt1 expression. Overall, orientin enhanced type I muscle fibers in the genioglossus, enhanced antioxidant capacity, increased mitochondrial biogenesis through AMPK signaling, and ultimately improved fatigue resistance in C2C12 myotubes and mouse genioglossus. These findings suggest that orientin may contribute to upper airway stability in patients with OSA, potentially preventing airway collapse.

Hepatic arterial infusion chemotherapy with anti-angiogenesis agents and immune checkpoint inhibitors for unresectable hepatocellular carcinoma and meta-analysis.

BACKGROUND: Hepatic arterial infusion chemotherapy (HAIC) has been proven to be an ideal choice for treating unresectable hepatocellular carcinoma (uHCC). HAIC-based treatment showed great potential for treating uHCC. However, large-scale studies on HAIC-based treatments and meta-analyses of first-line treatments for uHCC are lacking. AIM: To investigate better first-line treatment options for uHCC and to assess the safety and efficacy of HAIC combined with angiogenesis inhibitors, programmed cell death of protein 1 (PD-1) and its ligand (PD-L1) blockers (triple therapy) under real-world conditions. METHODS: Several electronic databases were searched to identify eligible randomized controlled trials for this meta-analysis. Study-level pooled analyses of hazard ratios (HRs) and odds ratios (ORs) were performed. This was a retrospective single-center study involving 442 patients with uHCC who received triple therapy or angiogenesis inhibitors plus PD-1/PD-L1 blockades (AIPB) at Sun Yat-sen University Cancer Center from January 2018 to April 2023. Propensity score matching (PSM) was performed to balance the bias between the groups. The Kaplan-Meier method and cox regression were used to analyse the survival data, and the log-rank test was used to compare the suvival time between the groups. RESULTS: A total of 13 randomized controlled trials were included. HAIC alone and in combination with sorafenib were found to be effective treatments (P values for ORs: HAIC, 0.95; for HRs: HAIC + sorafenib, 0.04). After PSM, 176 HCC patients were included in the analysis. The triple therapy group (n = 88) had a longer median overall survival than the AIPB group (n = 88) (31.6 months vs 14.6 months, P < 0.001) and a greater incidence of adverse events (94.3% vs 75.4%, P < 0.001). CONCLUSION: This meta-analysis suggests that HAIC-based treatments are likely to be the best choice for uHCC. Our findings confirm that triple therapy is more effective for uHCC patients than AIPB.

2D Ordered Mesoporous Lamellar Hetero-Nanochannels with Asymmetric Wettability for Controllable Ion Transport.

Heterogeneous membranes play a crucial role in osmotic energy conversion by effectively reducing concentration polarization. However, most heterogeneous membranes mitigate concentration polarization through an asymmetric charge distribution, resulting in compromised ion selectivity. Herein, hetero-nanochannels with asymmetric wettability composed of 2D mesoporous carbon and graphene oxide are constructed. The asymmetric wettability of the membrane endows it with the ability to suppress the concentration polarization without degrading the ion selectivity, as well as achieving a diode-like ion transport feature. As a result, enhanced osmotic energy harvesting is achieved with a power density of 6.41 W m-2 . This represents a substantial enhancement of 102.80-137.85% when compared to homogeneous 2D membranes, surpassing the performance of the majority of reported 2D membranes. Importantly, the membrane can be further used for high-performance ionic power harvesting by regulating ion transport, exceeding previously reported data by 89.1%.

Camrelizumab (a PD-1 inhibitor) plus apatinib (an VEGFR-2 inhibitor) and hepatic artery infusion chemotherapy for hepatocellular carcinoma in Barcelona Clinic Liver Cancer stage C (TRIPLET): a phase II study.

Hepatic arterial infusion chemotherapy (HAIC) using a combination of oxaliplatin, fluorouracil, and leucovorin (FOLFOX) has shown promise for hepatocellular carcinoma (HCC) patients classified under Barcelona Clinic Liver Cancer (BCLC) stage C. In China, the combined therapy of camrelizumab and apatinib is now an approved first-line approach for inoperable HCC. This study (NCT04191889) evaluated the benefit of combining camrelizumab and apatinib with HAIC-FOLFOX for HCC patients in BCLC stage C. Eligible patients were given a maximum of six cycles of HAIC-FOLFOX, along with camrelizumab and apatinib, until either disease progression or intolerable toxicities emerged. The primary outcome measured was the objective response rate (ORR) based on the Response Evaluation Criteria in Solid Tumors (RECIST) v1.1. Thirty-five patients were enrolled. Based on RECIST v1.1 criteria, the confirmed ORR stood at 77.1% (95% CI: 59.9% to 89.6%), with a disease control rate of 97.1% (95% CI: 85.1% to 99.9%). The median progression-free survival was 10.38 months (95% CI: 7.79 to 12.45). Patient quality of life had a transient deterioration within four cycles of treatment, and generally recovered thereafter. The most frequent grade ≥3 or above treatment-related adverse events included reduced lymphocyte count (37.1%) and diminished neutrophil count (34.3%). The combination of camrelizumab, apatinib, and HAIC demonstrated encouraging results and manageable safety concerns for HCC at BCLC stage C.

Cost-effectiveness and prognostic model of hepatic arterial infusion chemotherapy for hepatocellular carcinoma with high tumor burden and/or Vp4 tumor thrombus compared with sorafenib: a post-hoc analysis of the FOHAIC-1 trial.

OBJECTIVES: The phase III FOHAIC-1 trial revealed that hepatic arterial infusion of chemotherapy (HAIC) improved overall survival compared to sorafenib in the high-risk hepatocellular carcinoma (HCC). This study therefore set out to evaluate the cost-effectiveness and establish a prognostic clinico-radiological score of HAIC. MATERIALS AND METHODS: A total of 409 patients with high-risk HCC who received HAIC between 2014 and 2020 were included. A Markov model was applied in the cost-effectiveness analysis using data from the FOHAIC-1 trial. In prognosis analysis, a clinico-radiological score was developed using a Cox-regression model and subsequently confirmed in the internal validation and test cohorts. The area under the curve from receiver operator characteristic analysis was used to assess the performance of the clinico-radiological score. RESULTS: HAIC resulted in an incremental cost-effectiveness ratio of $10190.41/quality-adjusted life years compared to sorafenib, which was lower than the willingness-to-pay threshold. Probabilistic sensitivity analysis predicted a ≥99.9% probability that the incremental cost-effectiveness ratio was below the willingness-to-pay. The Cox analysis identified five factors, namely extrahepatic metastasis (m), arterial enhancing type (a), tumor number (nu), albumin-bilirubin index (a), and involved lobe (l), which together comprise the clinico-radiological score (HAIC-manual). Patients were classified into three groups based on the number of factors present, with cutoffs at 2 and 4 factors. The stratified median overall survival for these groups were 21.6, 10.0, and 5.9 months, respectively ( P <0.001). These findings were verified through internal validation and test cohorts with a significance level of P ≤0.01. The time-dependent area under the curve from receiver operator characteristic for the ability of the HAIC-manual to predict survival in 1, 2, and 3 years were 0.71, 0.76, and 0.78, which significantly outperformed existing staging systems. CONCLUSION: HAIC is a promising and cost-effective strategy for patients with high-risk HCC. The clinico-radiological score may be a simple prognostic tool for predicting HAIC treatment.

Ultrasound enhanced destruction of tetracycline hydrochloride with peroxydisulfate oxidation over FeS/NBC catalyst: Governing factors, strengthening mechanism and degradation pathway.

In this study, FeS/N-doped biochar (NBC) derived from the co-pyrolysis of birch sawdust and Mohr's salt was applied to evaluate the efficiency of catalyzed peroxydisulfate (PDS) oxidation for tetracycline (TC) degradation. It is found that the combination of ultrasonic irradiation can distinctly enhance the removal of TC. This study investigated the effects of control factors such as PDS dose, solution pH, ultrasonic power, and frequency on TC degradation. Within the applied ultrasound intensity range, TC degradation increases with increasing frequency and power. However, excessive power can lead to a reduced efficiency. Under the optimized experimental conditions, the observed reaction kinetic constant of TC degradation increased from 0.0251 to 0.0474 min-1, with an increase of 89%. The removal ratio of TC also increased from ∼85% to ∼99% and the mineralization level from 45% to 64% within 90 min. Through the decomposition testing of PDS, reaction stoichiometric efficiency calculation, and electron paramagnetic resonance experiments, it is shown that the increase in TC degradation of the ultrasound-assisted FeS/NBC-PDS system was attributed to the increase in PDS decomposition and utilization, as well as the increase in SO4•- concentration. The radical quenching experiments showed that SO4•-, •OH, and O2•- radicals were the dominant active species in TC degradation. TC degradation pathways were speculated according to intermediates from HPLC-MS analysis. The test of simulated actual samples showed that dissolved organic matter, metal ions, and anions in waters can undercut the TC degradation in FeS/NBC-PDS system, but ultrasound can significantly reduce the negative impact of these factors.

CT texture analysis in predicting treatment response and survival in patients with hepatocellular carcinoma treated with transarterial chemoembolization using random forest models.

BACKGROUND: Using texture features derived from contrast-enhanced computed tomography (CT) combined with general imaging features as well as clinical information to predict treatment response and survival in patients with hepatocellular carcinoma (HCC) who received transarterial chemoembolization (TACE) treatment. METHODS: From January 2014 to November 2022, 289 patients with HCC who underwent TACE were retrospectively reviewed. Their clinical information was documented. Their treatment-naïve contrast-enhanced CTs were retrieved and reviewed by two independent radiologists. Four general imaging features were evaluated. Texture features were extracted based on the regions of interest (ROIs) drawn on the slice with the largest axial diameter of all lesions using Pyradiomics v3.0.1. After excluding features with low reproducibility and low predictive value, the remaining features were selected for further analyses. The data were randomly divided in a ratio of 8:2 for model training and testing. Random forest classifiers were built to predict patient response to TACE treatment. Random survival forest models were constructed to predict overall survival (OS) and progress-free survival (PFS). RESULTS: We retrospectively evaluated 289 patients (55.4 ± 12.4 years old) with HCC treated with TACE. Twenty features, including 2 clinical features (ALT and AFP levels), 1 general imaging feature (presence or absence of portal vein thrombus) and 17 texture features, were included in model construction. The random forest classifier achieved an area under the curve (AUC) of 0.947 with an accuracy of 89.5% for predicting treatment response. The random survival forest showed good predictive performance with out-of-bag error rate of 0.347 (0.374) and a continuous ranked probability score (CRPS) of 0.170 (0.067) for the prediction of OS (PFS). CONCLUSIONS: Random forest algorithm based on texture features combined with general imaging features and clinical information is a robust method for predicting prognosis in patients with HCC treated with TACE, which may help avoid additional examinations and assist in treatment planning.

Phenolic compounds in walnut pellicle improve walnut (Juglans regia L.) protein solubility under pH-shifting condition.

This study focused on the interaction of walnut protein with phenolic extracts of walnut pellicle (PEWP) under alkaline condition, leading to enhancement of protein solubility under neutral condition. First, the change of PEWP under alkaline condition was determined by RP-HPLC and mass spectrometry, and the results showed that most ellagitannins in PEWP could be retained under alkaline condition within 3 h. Interaction between PEWP and walnut protein under pH-shifting condition resulted in the remarkable increase of protein solubility (above 90%) at neutral pH. The results from SDS-PAGE and SEC showed that the improved solubility lied in the formation of large and soluble protein aggregates due to the covalent interaction among walnut protein and polyphenols. A significant change in tertiary structure of protein-phenolic complex was witnessed by fluorescence spectrum and near-UV circular dichroism. Meanwhile, walnut protein-polyphenol interaction led to a slight increase in ß-turn while a slight decrease in ß-sheet. Combined with amino acid composition, it could be illustrated that the covalent bonding for walnut protein with polyphenol mainly occurred at Lysine residues.

ST-CRMF: Compensated Residual Matrix Factorization with Spatial-Temporal Regularization for Graph-Based Time Series Forecasting.

Despite the extensive efforts, accurate traffic time series forecasting remains challenging. By taking into account the non-linear nature of traffic in-depth, we propose a novel ST-CRMF model consisting of the Compensated Residual Matrix Factorization with Spatial-Temporal regularization for graph-based traffic time series forecasting. Our model inherits the benefits of MF and regularizer optimization and further carries out the compensatory modeling of the spatial-temporal correlations through a well-designed bi-directional residual structure. Of particular concern is that MF modeling and later residual learning share and synchronize iterative updates as equal training parameters, which considerably alleviates the error propagation problem that associates with rolling forecasting. Besides, most of the existing prediction models have neglected the difficult-to-avoid issue of missing traffic data; the ST-CRMF model can repair the possible missing value while fulfilling the forecasting tasks. After testing the effects of key parameters on model performance, the numerous experimental results confirm that our ST-CRMF model can efficiently capture the comprehensive spatial-temporal dependencies and significantly outperform those state-of-the-art models in the short-to-long terms (5-/15-/30-/60-min) traffic forecasting tasks on the open Seattle-Loop and METR-LA traffic datasets.

Elsholtzia splendens promotes phenanthrene and polychlorinated biphenyl degradation under Cu stress through enrichment of microbial degraders.

Co-contamination of heavy metals and organic pollutants is widespread in the environment. Metal-tolerant/hyperaccumulating plants have the advantage of enhancing co-operation between plants and rhizospheric microbes under heavy metal stress, but the underlying mechanism remains unclear. In the present study, the effects of Elsholtzia splendens and Lolium perenne on the rhizospheric microbial community and degraders of phenanthrene (PHE) and polychlorinated biphenyls (PCBs) were investigated. The results showed E. splendens could tolerate high Cu concentrations, while L. perenne was sensitive to Cu toxicity. Although Cu played the most important role in microbial community construction, both E. splendens and L. perenne caused shifts in the rhizospheric microbial community. For PHE and PCB degradation, L. perenne was more efficient under low Cu concentrations, whereas E. splendens performed better under high Cu concentrations. This difference can be attributed to shifts in the degrader community and key degradation genes identified by stable isotope probing. Moreover, higher abundances of various genes for organic pollutant degradation were observed in the rhizosphere of E. splendens than L. perenne based on gene prediction under high Cu stress. Our study reveals underlying mechanism of the advantages of heavy metal-tolerant plants for organic pollutant removal in soils co-contaminated with heavy metals.

Kinetics-Regulated Interfacial Selective Superassembly of Asymmetric Smart Nanovehicles with Tailored Topological Hollow Architectures.

Hollow nanoparticles featuring tunable structures with spatial and chemical specificity are of fundamental interest. However, it remains a significant challenge to design and synthesize asymmetric nanoparticles with controllable topological hollow architecture. Here, a versatile kinetics-regulated cooperative polymerization induced interfacial selective superassembly strategy is demonstrated to construct a series of asymmetric hollow porous composites (AHPCs) with tunable diameters, architectures and components. The size and number of patches on Janus nanoparticles can be precisely manipulated by the precursor and catalyst content. Notably, AHPCs exhibit excellent photothermal conversion performance under the irradiation of a near infrared (NIR) laser. Thus, AHPCs are utilized as NIR light-triggered nanovehicles and cargos can be controllably released. In brief, this versatile superassembly approach offers a streamlined and powerful toolset to design diverse asymmetric hollow porous composites.

Mechanism of salicylic acid in promoting the rhizosphere benzo[a]pyrene biodegradation as revealed by DNA-stable isotope probing.

Benzo[a]pyrene (BaP) is a typical high-molecular-weight PAH with carcinogenicity. Rhizoremediation is commonly applied to remove soil BaP, but its mechanism remains unclear. The role of inducers in root exudates in BaP rhizoremediation is rarely studied. Here, to address this problem, we firstly investigated the effect of the inducer salicylic acid on BaP rhizoremediation, rhizosphere BaP degraders, and PAH degradation-related genes by combining DNA-stable-isotope-probing, high-throughput sequencing, and gene function prediction. BaP removal in the rhizosphere was significantly increased by stimulation with salicylic acid, and the rhizosphere BaP-degrading microbial community structure was significantly changed. Fourteen microbes were responsible for the BaP metabolism, and most degraders, e.g. Aeromicrobium and Myceligenerans, were firstly linked with BaP biodegradation. The enrichment of the PAH-ring hydroxylating dioxygenase (PAH-RHD) gene in the heavy fractions of all 13C-treatments further indicated their involvement in the BaP biodegradation, which was also confirmed by the enrichment of dominant PAH degradation-related genes (e.g. PAH dioxygenase and protocatechuate 3,4-dioxygenase genes) based on gene function prediction. Overall, our study demonstrates that salicylic acid can enhance the rhizosphere BaP biodegradation by altering the community structure of rhizosphere BaP-degrading bacteria and the abundance of PAH degradation-related genes, which provides new insights into BaP rhizoremediation mechanisms in petroleum-contaminated sites.

Promising Applications of Nanoparticles in the Treatment of Hearing Loss.

Hearing loss is one of the most common disabilities affecting both children and adults worldwide. However, traditional treatment of hearing loss has some limitations, particularly in terms of drug delivery system as well as diagnosis of ear imaging. The blood-labyrinth barrier (BLB), the barrier between the vasculature and fluids of the inner ear, restricts entry of most blood-borne compounds into inner ear tissues. Nanoparticles (NPs) have been demonstrated to have high biocompatibility, good degradation, and simple synthesis in the process of diagnosis and treatment, which are promising for medical applications in hearing loss. Although previous studies have shown that NPs have promising applications in the field of inner ear diseases, there is still a gap between biological research and clinical application. In this paper, we aim to summarize developments and challenges of NPs in diagnostics and treatment of hearing loss in recent years. This review may be useful to raise otology researchers' awareness of effect of NPs on hearing diagnosis and treatment.

Surveillance Strategy for Barcelona Clinic Liver Cancer B Hepatocellular Carcinoma Achieving Complete Response: An Individualized Risk-Based Machine Learning Study.

Background: For patients with complete response (CR) of Barcelona Clinical Liver Cancer (BCLC) stage B hepatocellular carcinoma (HCC), there is no consensus regarding the monitoring strategy. Optimal surveillance strategies that can detect early progression of HCC within a limited visit after treatment have not yet been investigated. A retrospective, real-world study was conducted to investigate surveillance strategies for BCLC stage B HCC (BBHCC) patients with CR after curative treatment to support clinical decision making. Methods: From January 2007 to December 2019, 546 BBHCC patients with CR after radical treatment were collected at Sun Yat-sen University Cancer Center. Seventy percent of patients were subjected to the train cohort randomly; the remaining patients comprised the validation cohort to verify the proposed arrangements. The random survival forest method was applied to calculate the disease progression hazard per month, and follow-up schedules were arranged to maximize the capability of progression detection at each visit. The primary endpoint of the study was the delayed-detection months for disease progression. Results: The cumulative 1, 2, and 3-years risk-adjusted probabilities for the train/validation cohorts were 32.8%/33.7%, 54.0%/56.3%, and 64.0%/67.4%, respectively, with peaks around approximately the 9th month. The surveillance regime was primarily concentrated in the first year posttreatment. The delayed-detection months gradually decreased when the total follow-up times increased from 6 to 11. Compared with controls, our schedule reduced delayed detection. Typically, the benefits of our surveillance regimes were obvious when the patients were followed seven times according to our schedule. The optional schedules were 5, 7, 9, 11, 17, 23, and 30 months. Conclusion: The proposed new surveillance schedule may provide a new perspective concerning follow-up for BBHCC patients with CR.

Analysis of the PD-1 Ligands Among Gastrointestinal Cancer Patients: Focus on Cancer Immunity.

Many types of gastrointestinal cancer have shown promising outcomes after checkpoint blockade immunotherapy; however, it remains largely unclear about the expression profiles of programmed death 1 (PD-1) ligands (CD274 and PDCD1LG2) in the context of human pan-cancer. This work comprehensively analyzed the expression pattern of the PD-1 ligands and the clinical significance in the prognosis prediction among the seven types of gastrointestinal malignancies collected from The Cancer Genome Atlas (TCGA) and the Cancer Cell Line Encyclopedia (CCLE) database. Furthermore, the correlation of CD274/PDCD1LG2 with cancer immunity was also explored. The patients with liver hepatocellular carcinoma (LIHC) receiving cytokine-induced killer (CIK) cell immunotherapy at our cancer center were enrolled. CD274 and PDCD1LG2 displayed inconsistent gene expression levels among the diverse cancer cell lines. Typically, the abnormal expression level of CD274 and PDCD1LG2 was detected in both esophageal carcinoma (ESCA) and stomach adenocarcinoma (STAD), where PDCD1LG2 was related to the overall survival (OS) of the patients in ESCA (p = 0.015) and STAD (p = 0.025). High-serum CD274 and PDCD1LG2 levels predicted a worse survival in the patients with LIHC receiving CIK therapy. More importantly, the expression level of CD274 and PDCD1LG2 was significantly correlated with the degree of Estimation of STromal and Immune cells in MAlignant Tumor tissues using the Expression data (ESTIMATE). In addition, we found that CD274 and PDCD1LG2 were correlated with gene markers in tumor-infiltrating immune cells. Furthermore, the expression of CD274 and PDCD1LG2 was correlated with tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repair (MMR), and DNA methyltransferase (DNMT) of different types of cancers. The present work comprehensively analyzed a RNA sequencing of the PD-1 ligands across the seven distinct types of gastrointestinal cancers, which provided clues for further studies in cancer immunity and development.

Uptake, Acropetal Translocation, and Enantioselectivity of Perfluorooctane Sulfonate in Maize Coexisting with Copper.

Plant uptake and translocation of perfluorooctane sulfonate (PFOS) are critical for food safety and raise major concerns. However, those processes are associated with many undisclosed mechanisms, especially when PFOS coexist with heavy metals. In this study, we investigated the effect of copper (Cu) on PFOS distribution in maize tissues by assessing the PFOS concentration and enantioselectivity. The presence of <100 µmol/L Cu exerted a limited effect on PFOS bioaccumulation, while >100 µmol/L Cu damaged the root cell membrane and increased root permeability, resulting in a higher PFOS concentration in roots. The suppression of acropetal translocation might be attributed to Cu inhibition of carrier proteins. The enantiomer fraction (EF) of 1m-PFOS at <100 µmol/L Cu was higher than that in a commercial product (0.5). Racemic PFOS was detected at >100 µmol/L Cu in roots and the EF variation changed from positive to negative in shoots. These EF results evidenced the existence of a protein-mediated uptake pathway. Besides, this study indicated the challenge of chiral signature application in PFOS source identification, given the effects of heavy metals and plants on PFOS enantioselectivity. The findings provide insight into PFOS bioaccumulation in plants cocontaminated with Cu and will facilitate environmental risk assessment.

Multi-Stage Pedestrian Positioning Using Filtered WiFi Scanner Data in an Urban Road Environment.

Since widespread applications of wireless sensors networks, low-speed traffic positioning based on the received signal strength indicator (RSSI) from personal devices with WiFi broadcasts has attracted considerable attention. This study presents a new range-based localization method for outdoor pedestrian positioning by using the combination of offline RSSI distance estimation and real-time continuous position fitting, which can achieve high-position accuracy in the urban road environment. At the offline stage, the piecewise polynomial regression model (PPRM) is proposed to formulate the Euclidean distance between the targets and WiFi scanners by replacing the common propagation model (PM). The online stage includes three procedures. Firstly, a constant velocity Kalman filter (CVKF) is developed to smooth the real-time RSSI time series and estimate the target-detector distance. Then, a least squares Taylor series expansion (LS-TSE) is developed to calculate the actual 2-dimensional coordinate with the replacement of existing trilateral localization. Thirdly, a trajectory-based technique of the unscented Kalman filter (UKF) is introduced to smooth estimated positioning points. In tests that used field scenarios from Guangzhou, China, the experiments demonstrate that the combined CVKF and PPRM can achieve the highly accurate distance estimator of <1.98 m error with the probability of 90% or larger, which outperforms the existing propagation model. In addition, the online method can achieve average positioning error of 1.67 m with the much better than classical methods.

Identification and Validation of a Prognostic lncRNA Signature for Hepatocellular Carcinoma.

Background: An accumulating body of evidence suggests that long non-coding RNAs (lncRNAs) can serve as potential cancer prognostic factors. However, the utility of lncRNA combinations in estimating overall survival (OS) for hepatocellular carcinoma (HCC) remains to be elucidated. This study aimed to construct a powerful lncRNA signature related to the OS for HCC to enhance prognostic accuracy. Methods: The expression patterns of lncRNAs and related clinical data of 371 HCC patients were obtained based on The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs (DElncRNAs) were acquired by comparing tumors with adjacent normal samples. lncRNAs displaying significant association with OS were screened through univariate Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) algorithm. All cases were classified into the validation or training group at the ratio of 3:7 to validate the constructed lncRNA signature. Data from the Gene Expression Omnibus (GEO) were used for external validation. We conducted real-time polymerase chain reaction (PCR) and assays for Transwell invasion, migration, CCK-8, and colony formation to determine the biological roles of lncRNA. Gene set enrichment analysis (GSEA) of the lncRNA model risk score was also conducted. Results: We identified 1292 DElncRNAs, among which 172 were significant in univariate Cox regression analysis. In the training group (n = 263), LASSO regression analysis confirmed 11 DElncRNAs including AC010547.1, AC010280.2, AC015712.7, GACAT3 (gastric cancer associated transcript 3), AC079466.1, AC089983.1, AC051618.1, AL121721.1, LINC01747, LINC01517, and AC008750.3. The prognostic risk score was calculated, and the constructed risk model showed significant correlation with HCC OS (log-rank P-value of 8.489e-9, hazard ratio of 3.648, 95% confidence interval: 2.238-5.945). The area under the curve (AUC) for this lncRNA model was up to 0.846. This risk model was confirmed in the validation group (n = 108), the entire cohort, and the external GEO dataset (n = 203). GACAT3 was highly expressed in HCC tissues and cell lines. Based on online databases, GACAT3 expression independently affects both OS and disease-free survival in HCC patients. Silencing GACAT3 in vitro significantly suppressed HCC cell proliferation, invasion, and migration. Moreover, pathways related to the lncRNA model risk score were confirmed by GSEA. Conclusion: The lncRNA signature established in this study can be used to predict HCC prognosis, which could provide novel clinical evidence to guide targeted HCC treatment.