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Abstract Background The development of the human vermiform appendix at the cellular level, as well as its function, is not well understood. Appendicitis in preschool children, although uncommon, is associated with a high perforation rate and increased morbidity. Methods We performed single-cell RNA sequencing (scRNA-seq) on the human appendix during fetal and pediatric stages as well as preschool-age inflammatory appendices. Transcriptional features of each cell compartment were discussed in the developing appendix. Cellular interactions and differentiation trajectories were also investigated. We compared scRNA-seq profiles from preschool appendicitis to those of matched healthy controls to reveal disease-associated changes. Bulk transcriptomic data, immunohistochemistry, and real-time quantitative PCR were used to validate the findings. Results Our analysis identified 76 cell types in total and described the cellular atlas of the developing appendix. We discovered the potential role of the BMP signaling pathway in appendiceal epithelium development and identified HOXC8 and PITX2 as the specific regulons of appendix goblet cells. Higher pericyte coverage, endothelial angiogenesis, and goblet mucus scores together with lower epithelial and endothelial tight junction scores were found in the preschool appendix, which possibly contribute to the clinical features of preschool appendicitis. Preschool appendicitis scRNA-seq profiles revealed that the interleukin-17 signaling pathway may participate in the inflammation process. Conclusions Our study provides new insights into the development of the appendix and deepens the understanding of appendicitis in preschool children. Graphical Abstract

Abstract Metastasis is the major culprit of treatment failure in nasopharyngeal carcinoma (NPC). Aryl hydrocarbon receptor nuclear translocator like 2 (ARNTL2), a core circadian gene, plays a crucial role in the development of various tumors. Nevertheless, the biological role and mechanism of ARNTL2 are not fully elucidated in NPC. In this study, ARNTL2 expression was significantly upregulated in NPC tissues and cells. Overexpression of ARNTL2 facilitated NPC cell migration and invasion abilities, while inhibition of ARNTL2 in similarly treated cells blunted migration and invasion abilities in vitro. Consistently, in vivo xenograft tumor models revealed that ARNTL2 silencing reduced nude mice inguinal lymph node and lung metastases, as well as tumor growth. Mechanistically, ARNTL2 negatively regulated the transcription expression of AMOTL2 by directly binding to the AMOTL2 promoter, thus reducing the recruitment and stabilization of AMOTL2 to LATS1/2 kinases, which strengthened YAP nuclear translocation by suppressing LATS-dependent YAP phosphorylation. Inhibition of AMOTL2 counteracted the effects of ARNTL2 knockdown on NPC cell migration and invasion abilities. These findings suggest that ARNTL2 may be a promising therapeutic target to combat NPC metastasis and further supports the crucial roles of circadian genes in cancer development.

Abstract The interaction between programmed cell death ligand 1 (PD-L1), which is expressed on the surface of tumor cells, and programmed cell death 1 (PD-1), which is expressed on T cells, impedes the effective activation of tumor antigen-specific T cells, resulting in the evasion of tumor cells from immune-mediated killing. Blocking the PD-1/PD-L1 signaling pathway has been shown to be effective in preventing tumor immune evasion. PD-1/PD-L1 blocking antibodies have garnered significant attention in recent years within the field of tumor treatments, given the aforementioned mechanism. Furthermore, clinical research has substantiated the efficacy and safety of this immunotherapy across various tumors, offering renewed optimism for patients. However, challenges persist in anti-PD-1/PD-L1 therapies, marked by limited indications and the emergence of drug resistance. Consequently, identifying additional regulatory pathways and molecules associated with PD-1/PD-L1 and implementing judicious combined treatments are imperative for addressing the intricacies of tumor immune mechanisms. This review briefly outlines the structure of the PD-1/PD-L1 molecule, emphasizing the posttranslational modification regulatory mechanisms and related targets. Additionally, a comprehensive overview on the clinical research landscape concerning PD-1/PD-L1 post-translational modifications combined with PD-1/PD-L1 blocking antibodies to enhance outcomes for a broader spectrum of patients is presented based on foundational research.

To verify the predictive accuracy of existing strength criteria on true triaxial strength experimental data, understand the characteristics of different strength criteria, and provide a basis for selecting strength criteria for engineering applications, ten commonly used rock strength criteria were selected and divided into MC and HB types. The distribution characteristics of the yield surfaces and yield curves of different criteria were compared and analyzed in the principal stress space and the π plane. Afterwards, based on the least absolutely deviation method, these ten strength criteria were used to predict 32 sets of true triaxial rock strength experimental data. The results showed that the range of undetermined parameters for MC type strength criteria was small and easy to determine, while the range of undetermined parameter for HB type criteria was large and difficult to determine the search range, in addition, the fitting process may not converge. The fitting accuracy of strength criteria for true triaxial experimental data depends on the sensitivity of rock strength to the intermediate principal stress. PH and GP criteria are the most sensitive to changes of the intermediate principal stress, followed by MWC and ML criteria, MGC and ZZ criteria, MCJP and HBWW criteria. PH and GP criteria overestimate the effect of the intermediate principal stress, resulting in the largest prediction errors, while the other three-dimensional strength criteria have high prediction accuracy and no significant differences. The research results can provide scientific basis for engineering design, geological hazard prediction, and mineral resource development.

ObjectiveTo explore the association between circadian syndrome (CircS) and Metabolic Syndrome (MetS) with psoriasis. Compare the performance of MetS and CircS in predicting psoriasis.MethodsAn observational study used data from the NHANES surveys conducted in 2005–2006 and 2009–2014. We constructed three multiple logistic regression models to investigate the relationship between MetS, CircS, and their components with psoriasis. The performance of MetS and CircS in predicting psoriasis was compared using five machine-learning algorithms, and the best-performing model was explained via SHAP. Then, bidirectional Mendelian randomization analyses with the inverse variance weighted (IVW) as the primary method were employed to determine the causal effects of each component.ResultA total of 9,531 participants were eligible for the study. Both the MetS (OR = 1.53, 95%CI: 1.07–2.17, P = 0.02) and CircS (OR = 1.40, 95%CI: 1.02–1.91, P = 0.039) positively correlated with psoriasis. Each CircS algorithmic model performs better than MetS, with Categorical Features+Gradient Boosting for CircS (the area under the precision-recall curve = 0.969) having the best prediction effect on psoriasis. Among the components of CircS, elevated blood pressure, depression symptoms, elevated waist circumference (WC), and short sleep contributed more to predicting psoriasis. Under the IVW methods, there were significant causal relationships between WC (OR = 1.52, 95%CI: 1.34−1.73, P = 1.35e-10), hypertension (OR = 1.68, 95%CI: 1.19−2.37, P = 0.003), depression symptoms (OR = 1.39, 95%CI: 1.17−1.65, P = 1.51e-4), and short sleep (OR = 2.03, 95%CI: 1.21–3.39, p = 0.007) with psoriasis risk.ConclusionCircS demonstrated superior predictive ability for prevalent psoriasis compared to MetS, with elevated blood pressure, depression symptoms, and elevated WC contributing more to the prediction.

Intelligent unmanned vending machines (UVMs) based on machine vision have attracted great attention in the unmanned retail industry. However, due to the complexity of practical application scenarios and environments, the existing vision-based intelligent UVMs face challenges related to missed-detection and mis-detection of product, and require costly physical components such as the infrared radio frequency sensors to capture shopping behaviors. In this study, we propose a BP-YOLO, the real-time model that integrates optimized YOLOv7 and BlazePose for product detection and shopping behaviors recognition. BP-YOLO can accurately detect the products purchased by consumers and their shopping behaviors in complex scenarios. To address the problems of missed-detection and mis-detection, we introduce the 3D attention mechanism SimAM and the deformable ConvNets v2 (DCNv2) to recombine and optimize the one-stage object detection model YOLOv7. This method reduces the interference of the invalid information in complex scenarios by adaptively weighting each channel and 3D spatial features, focuses on feature information in a sparse space, and minimizes the loss of feature information during the transmission process based on multi-scale feature extraction and fusion. To recognize and judge the shopping behaviors of consumers, we track the hand and arm key points of consumers using the pose estimation model BlazePose. Using the mAP@[0.5:0.95] as the evaluation metric for product detection, the experimental results on a customized product dataset show that BP-YOLO achieves an average accuracy of 96.17% for all product categories detection; the average success rate of consumer shopping recognition reaches 92%, 98%, and 94.7% under three light and noise intensity, respectively. Therefore, our BP-YOLO model for intelligent UVMs has effectiveness in commercial deployment.

Abstract With the emergence of new information and communication technology, mobile‐based ridesharing services have received more attention and have improved. They offer timely and convenient service and exert an enormous influence on pollution and congestion by allowing passengers to share overlapping routes. However, ridesharing services have also been discussed and called into question by people with respect to their attractiveness, their comfort, and passenger safety. This paper proposes a ridesharing algorithm with a perceived mechanism by introducing multiple dimensions of perceived value to overall assess passengers’ perceptions. The approach involved can continuously track the psychological changes in passengers during travel, capture the dynamic and comprehensive perceptions of passengers, and make real‐time adjustments on this basis. Furthermore, the proposed partition‐based parallel strategy can ensure high‐quality services and further enhance computational efficiency. Finally, numerical experiments are conducted based on the urban transportation network and the actual trip data from Manhattan to evaluate the performance of the proposed algorithm. The results show that it is important to effectively capture the passengers’ perception of ridesharing services and apply them to optimization mechanisms, which will contribute to improving the perception of ride experiences and attracting potential passengers.

Abstract To optimize railway car routing based on balanced station‐line capacities, thereby improving railway freight traffic organization efficiency, and reducing transportation costs, a railway car routing optimization model based on the coordinated utilization of station‐line capacities was developed. Based on the theory of the membership function in fuzzy mathematics, the level of railway station‐line coordination based on capacity utilization was presented. The occupancy of a railway line by each car was taken as a binary decision variable. Using a set of deviation constraints, the deviation between the station‐line flow of the railway network and the utilization of a certain level was expressed in the form of decision variables that were then penalized to different degrees in the objective function. The total transportation cost and the penalty cost were taken as the objective function for minimization. Based on the characteristics of the fuzzy membership degree, the relationship between the penalty for capacity deviation and the membership function in the optimization model was analyzed, and the calculation method of the penalty for the capacity deviation considering the membership function was presented. An adaptive large‐scale neighbourhood search (ALNS) algorithm was designed to solve the model, and its effectiveness was verified. An actual 36‐station railway network was used to validate the proposed railway car routing optimization model through comparison with existing models. The optimization results showed that, at the expense of increasing the transportation cost by 1.05%, the coordination penalty cost was reduced by 11.24%, the overall cost was reduced by 3.21%, and most of the situation with 90% utilization rate of stations and lines in the railway network was eliminated. The model proposed in this paper can help reduce the pressure on lines and stations with tight capacity in the network, improve the utilization of virtual lines and stations and coordination of station‐line capacities.

A thin-walled structure of high-strength aluminum alloy 2024 (AA2024) was fabricated using novel laser and cold metal transfer and pulse (CMT-P) arc hybrid additive manufacturing (LCAHAM) technology. The influence of the wire feeding speed, scanning speed, and laser power on the forming quality was systematically studied by the response surface methodology, probability statistical theory, and multi-objective optimization algorithm. The result showed that the forming accuracy was significantly more affected by the laser power than by the wire feeding speed and scanning speed. Specifically, there was an obvious correlation between the interaction of the laser power and wire feeding speed and the resulting formation accuracy of LCAHAM AA2024. Moreover, the laser power, wire feeding speed, and scanning speed all had noticeable effects on the spattering degree during the LCAHAM AA2024 process, with the influence of the laser power surpassing that of the other two factors. Importantly, these three factors demonstrated minimal mutual interaction on spattering. Furthermore, the scanning speed emerged as the most significant factor influencing porosity compared to the wire feeding speed and laser power. It was crucial to highlight that the combined effects of the wire feed speed and laser power played an obvious role in reducing porosity. Considering the forming accuracy, spattering degree, and porosity collectively, the recommended process parameters were as follows: a wire feeding speed ranging from 4.2 to 4.3 m/min, a scanning speed between 15 and 17 mm/s, and a laser power set at approximately 2000 W, where the forming accuracy was 84–85%, the spattering degree fell within 1.0–1.2%, and the porosity was 0.7–0.9%.

Abstract Background Significant intertumoral heterogeneity exists as antitumor treatment is introduced. Heterogeneous therapeutic responses are conventionally evaluated by imaging examinations based on Response Evaluation Criteria in Solid Tumors (RECIST); nevertheless, there are increasing recognitions that they do not fully capture patient clinical benefits. Currently, there is a paucity of data regarding the clinical implication of biological responses assessed by liquid biopsy of on-treatment circulating tumor DNA (ctDNA). Here, we investigated whether biological response evaluated by ctDNA kinetics added critical information to the RECIST, and whether integrating on-treatment biological response information refined risk stratification of cancer patients. Methods In this population-based cohort study, we included 821 patients with Epstein-Barr virus (EBV)-associated nasopharynx of head and neck cancer (NPC) receiving sequential neoadjuvant chemotherapy (NAC) and chemoradiotherapy (CRT), who had pretreatment and on-treatment cfEBV DNA and magnetic resonance imaging (MRI) surveillance. Biological responses evaluated by cfEBV DNA were profiled and compared with conventional MRI-based RECIST evaluation. The inverse probability weighting (IPW)-adjusted survival analysis was performed for major survival endpoints. The Cox proportional hazard regression [CpH]-based model was developed to predict the on-treatment ctDNA-based individualized survival. Results Of 821 patients, 71.4% achieved complete biological response (cBR) upon NAC completion. RECIST-based response evaluations had 25.3% discordance with ctDNA-based evaluations. IPW-adjusted survival analysis revealed that cfEBV DNApost-NAC was a preferential prognosticator for all endpoints, especially for distant metastasis. In contrast, radiological response was more preferentially associated with locoregional recurrence. Intriguingly, cfEBV DNApost-NAC further stratified RECIST-responsive and non-responsive patients; RECIST-based non-responsive patients with cBR still derived substantial clinical benefits. Moreover, detectable cfEBV DNApost-NAC had 83.6% prediction sensitivity for detectable post-treatment ctDNA, which conferred early determination of treatment benefits. Finally, we established individualized risk prediction models and demonstrated that introducing on-treatment ctDNA significantly refined risk stratification. Conclusions Our study helps advance the implementation of ctDNA-based testing in therapeutic response evaluation for a refined risk stratification. The dynamic and refined risk profiling would tailor future liquid biopsy-based risk-adapted personalized therapy.

Radiotherapy is the mainstay treatment for nasopharyngeal carcinoma (NPC). Here the authors show that the deubiquitinase, USP44, increases radiosensitivity of NPC cells by promoting the degradation of Ku80, and thus enhancing the levels of DNA damage.

As the intersection of multiple high-speed railway lines, the multi-station high-speed railway hub is the key to improve the transport efficiency of the high-speed railway network. This paper focuses on the optimization of the multi-station high-speed railway hub and models it as a train routing problem (TRP). Considering the capacity of railway infrastructures and the demand of passengers, a mixed integer linear programming model is proposed to minimize the total cost of train routes and passenger routes. The optimized train routes include the macroscopic routes between stations and the microscopic track allocation inside stations and Electric Multiple Units (EMUs) depots. A Lagrangian relaxation (LR) approach is developed to dualize the hard constraints and decompose the origin model into train and passenger subproblems, then a shortest path algorithm is designed to solve the subproblems independently. Numerical experiments based on an illustrative railway hub network and a real-world network are implemented to demonstrate the effectiveness of the model and algorithm. The solution results prove that the LR approach can obtain high-quality solutions within an acceptable computational time. Compared with the existing fixed scheme, the optimization scheme can reduce the total cost by 37.18% and utilize the railway lines and tracks more reasonably.

Abstract Background Hirschsprung's disease (HSCR) is a relatively common congenital disability. Accumulating extracellular matrix (ECM) prompts intestinal fibrosis remodelling in the aganglionic segments of HSCR. The contributions of various cellular subsets in the fibrogenesis of HSCR segments are poorly understood. Methods Single‐cell transcriptomics from 8 aganglionic segments and 5 normal segments of 7 HSCR subjects and 26 healthy segments of seven healthy donors were analysed. Fibrotic phenotype and alterations were explored using differential expression analysis and single‐cell trajectory analysis. Fibrosis‐related transcription factors were inferred through single‐cell regulatory network inference. Bulk transcriptomic data, proteomic data, immunohistochemistry (IHC) and real‐time polymerase chain reaction were used to validate the alterations in the HSCR intestine. Results Various collagen, fibronectin and laminin protein‐coding genes expression were up‐regulated in the stromal and glial cells of the HSCR intestine. The number of fibroblasts and myofibroblasts in the aganglionic segments increased, and more myofibroblasts were activated at an earlier stage in HSCR segments, which infers that there is an intestinal fibrosis phenotype in HSCR segments. The fibrotic regulators POSTN, ANXA1 and HSP70 were highly expressed in the ECM‐related cellular subsets in the transitional segments and aganglionic segments. The transcription factor regulatory network revealed that fibrosis‐related and megacolon‐related NR2F1 in the fibroblasts and glial subsets was up‐regulated in the aganglionic segment. Conclusions This work identifies intestinal fibrosis and related regulators in aganglionic segments of HSCR; hence, anti‐fibrotic therapy may be considered to prevent HSCR‐associated enterocolitis (HAEC), relieve intestinal stricture and improve cell therapy.

Whether N6-methyladenosine (m6A) is involved in biliary atresia (BA) remains undefined. Herein, we comprehensively evaluated the m6A profile in BA. When compared with normal controls, BA had an elevated m6A level with upregulated m6A writers. The m6A level was correlated with liver function, stage of fibrosis and jaundice clearance in BA. Methylated RNA immunoprecipitation sequencing (MeRIP-seq) demonstrated an altered m6A topology in BA. MeRIP-seq and RNA sequencing filtered out 130 m6A-modified genes, which were enriched in fibrogenetic pathways. MeRIP-qPCR in vivo and interventions of LX-2 and primary HSCs in vitro validated the regulatory role of m6A on COL1A1 and THY1. THY1+ myofibroblasts expanded in portal area of BA, and highly expressed profibrogenic genes (COL1A1, MMP2, PDGFRA, and DCN). THY1 was correlated with liver fibrosis and jaundice clearance in BA. Bulk array (GSE46960, GSE15235), single-cell RNA sequencing (GSE136103), primary HSC interventions, and co-immunoprecipitation revealed that THY1 was correlated with extracellular matrix organization, promoted HSC activation, showed higher interactions with integrins on myeloid cells in cholestatic fibrosis, and was correlated with native liver survival in BA. Our study highlights the significance of m6A in BA-induced liver fibrogenesis by regulating THY1, shedding new light on the novel therapies to alleviate liver fibrosis by targeting m6A/THY1 axis in BA.

ObjectivesThis paper seeks to obtain the wheel load distribution characteristics of a truck tire on a stiffener plate. Methods First, stiffener plate experiments are carried out under wheel pressure with different axle load cases; the contact area and contact pressure changes between the tire and aluminum alloy stiffened plate are obtained; and the basic distribution law of wheel load is summarized in combination with the relevant literature. Second, based on the experimental results, a second-order polynomial hypothesis for wheel load distribution characteristics is given, and the parameters in the polynomial under different axle load cases are determined according to the experimental data. Finally, the stress response of the aluminum alloy stiffener plate is compared with a combination of numerical simulation and experimental results. Results The load distribution characteristics of a truck tire on a stiffener plate and the expressional method are obtained, and the rationality of the proposed wheel load distribution characteristics is proven.ConclusionThe study of wheel load in this article is helpful for understanding the characteristics of wheel load distribution on stiffener plates, and provides certain references for engineering applications.

The construction of transition metal alloys with 3D structure facilitates their catalytic activity towards hydrogen evolution reaction. Although this can be achieved by the wet chemical and template strategies, the uncertainty of reaction process inevitably results in the difficulty of the repeatability of product synthesis. Herein, we present the rationally designed 3D Ni-Mo with a typical hierarchical structure on Ni foam by combing ‘hydrogen bubble template’ and ‘tip effect’ via one-step electrodeposition. This 3D Ni-Mo/NF has both regular columnar structures of micron level and widespread pyramidal-like nanoparticles, which only needs an overpotential of 53 mV and 161 mV to afford 10 mA cm−2 and 100 mA cm−2 for HER in 1 M KOH, respectively. In addition, a small Tafel slope (42.6 mV dec-1), and long-term operational stability are achieved on the catalyst. The excellent performance can be traced to the amorphous and hierarchical structure with favorable active sites. Furthermore, the network structure of the nickel foam substrate can promote the diffusion and infiltration of electrolyte. Impressively, this electrode exhibits super hydrophilic, which facilitates the detachment of bubbles. The free-standing 3D catalysts in this study can be synthesized in a facile and viable way, indicating their promising tactic for scaled-up water electrolysis.

Abstract Background Biliary atresia (BA) is a devastating inflammatory and fibrosing cholangiopathy of neonates with unknown aetiology. We aim to investigate the relationship between these two main characteristics. Methods Single‐cell RNA sequencing and spatial transcriptomics were performed on liver samples from a cohort of 14 objects (BA: n = 6; control: n = 8). We conducted data integration and cell‐type annotation based on gene expression profiling. Furthermore, we identified fibrosis‐related immune cells according to their spatial locations, GO and KEGG analysis. Finally, SPOTlight and CIBERSORTx were used to deconvolute ST data and microarray data of the GSE46960 cohorts, respectively. Results Immune subpopulations inhabiting the ‘fibrotic niche’ (areas of scarring), comprising ‘intermediate’ CD14++CD16+ monocytes, scar‐associated macrophages, natural killer T cells, transitional B cells and FCN3+ neutrophils were identified. GO and KEGG analyses showed that pathways including ‘positive regulation of smooth muscle cell/fibroblast proliferation’ and ‘positive regulation of/response to VEGFR/VEGF/EGFR/FGF’ were enriched in these cell types. Interactions analysis showed that communication among ‘FGF_FGFR’, ‘RPS19‐C5AR1’, ‘CD74_COPA/MIF/APP’ and ‘TNFRSF1A/B_GRN’ was extensive. Finally, the results of deconvolution for ST data and microarray data validated that the proportions of certain identified fibrosis‐related cell types we identified were increased in BA. Discussion Fibrosis is an important feature of BA, in which the immune system plays an important role. Our work reveals the subpopulations of immune cells enriched in the fibrotic niche of BA liver, as well as key related pathways and molecules; some are highlighted for the first time in liver fibrosis. These newly identified interactions might partly explain why the rate of liver fibrosis occurs much faster in BA than in other liver diseases. Conclusion Our study revealed the molecular, cellular and spatial immune microenvironment of the fibrotic niche of BA.

ObjectiveThis study was designed to compare the safety and efficacy of unilateral hemilaminectomy conducted under complete neuroendoscopic visualization (UHNV) relative to unilateral hemilaminectomy under total microscopic visualization (UHMV) for the treatment of patients diagnosed with intraspinal tumors.MethodsIn total, 41 patients undergoing intraspinal tumor resection at Northern Jiangsu People's Hospital were included in this study, including 20 and 21 patients in the UHNV and UHMV groups, respectively. Intraoperative parameters including incision length, operative duration, number of vertebral laminae removed and intraoperative blood loss, as well as indicators of curative efficacy such as total tumor resection rates and postoperative symptom improvement rates, and safety indicators including complication rates, recurrence rates, spinal deformity rates, spinal instability incidence, and length of stay (LOS), were compared between the two groups.ResultsIn contrast to the UHMV group, patients in the UHNV group had a significantly shorter incision length and decreased intraoperative blood loss (P < 0.05), while the operative duration (P > 0.05) showed no statistical difference. Although the postoperative improvement and total tumor resection rates were enhanced, the difference was not statistically significant (P > 0.05). In comparison, the bedridden time and length of stay (LOS) were significantly shortened (P < 0.05) in the UHNV group. However, there were no significant differences in recurrence, incidence of complications, spinal deformity, and spinal instability (P > 0.05).ConclusionCollectively, our findings indicate that UHNV is not inferior to the UHMV approach. Moreover, due to its safe and minimally invasive nature, UHNV represents a promising alternative to UHMV as a treatment for patients with intradural extramedullary tumors.

Abstract Background Circular RNAs (circRNAs), a new type of noncoding RNA (ncRNA), have been identified as significant gene expression regulators and are involved in cancer progression. However, the roles of circRNAs in nasopharyngeal carcinoma (NPC) remain largely unknown. Methods Here, the expression profile of circRNAs in a pair of NPC cell lines with different metastatic abilities (S18 and S26 cells) was analyzed by RNA-sequencing. Quantitative reverse transcription PCR was used to detect the expression level of circCRIM1 in NPC cells and tissues. Then, function experiments in vitro and in vivo were performed to evaluate the effects of circCRIM1 on NPC metastasis and EMT. Mechanistically, RNA immunoprecipitation, luciferase reporter assay, pull-down assay with biotinylated miRNA, fluorescent in situ hybridization were performed to confirm the interaction between circCRIM1 and miR-422a in NPC. The clinical value of circCRIM1 was evaluated in NPC metastasis and chemosensitivity. Results We identified that circCRIM1 was upregulated in highly metastatic NPC cells. CircCRIM1 was also overexpressed in NPC tissues with distant metastasis, and its overexpression promoted NPC cell metastasis and EMT. Mechanistically, circCRIM1 competitively bound to miR-422a and prevented the suppressive effects of miR-422a on its target gene FOXQ1, which finally led to NPC metastasis, EMT and docetaxel chemoresistance. Furthermore, high circCRIM1 expression was associated with unfavorable survival in NPC patients. We established a prognostic model based on circCRIM1 expression and N stage that effectively predicted the risk of distant metastasis and treatment response to docetaxel-containing induction chemotherapy in NPC patients. Conclusions Our findings reveal the critical role of circCRIM1 specifically in promoting NPC metastasis and chemoresistance via a ceRNA mechanism and provide an exploitable biomarker and therapeutic target for prognosis and treatment resistance in NPC patients.

In order to tackle the congestion and environmental issues, customized bus services are proposed and deployed in metropolitan areas. As emerging public transportation services, customized bus services bring passengers more convenience and accessibility. Besides, conventional customized bus services generally organize homogeneous fleet and single location selection to passengers. In this paper, to enhance the mobility and flexibility of customized buses and increase companies’ profit, we propose a new form of customized bus service with heterogeneous fleets and multiple candidate locations. First, a mixed-integer programming model (MIP) is developed to describe the customized bus problem. Compared with the conventional model, the proposed MIP is involved in the case of one passenger with multiple candidate pickup or delivery locations and can be solved by GUROBI on small scale, quickly and efficiently. Second, an improved adaptive large neighborhood search algorithm (ALNSip) is utilized to address the large-scale problem more efficiently. Time slack calculation method is then designed to optimize vehicle timetables, which provides stable and excellent performance for searching feasible solutions. In addition, we propose two inserting operators to deal with the problem with multiple candidate locations and analyse its influence on the results. Finally, we test the performance of the proposed model and algorithm on the numerical experiments. And they are verified the effectiveness and implication in a small-scale case on a simplified Sioux waterfall network and a large-scale problem in Beijing, China. The result shows that ALNSip outperforms other algorithms in searching for more satisfying solutions with higher efficiency. However, the GUROBI solver can obtain the solution to small-scale problems within a shorter time than ALNSip. Furthermore, it can be suggested that the heterogeneous fleets service with multiple candidate locations is helpful to facilitate collaboration among vehicles and optimize pickup and delivery routes in consequence.

Objective To investigate the association between DNA methylation and the stable warfarin dose through genome-wide DNA methylation analysis and pyrosequencing assay. Method This study included 161 patients and genome-wide DNA methylation analysis was used to screen potential warfarin dose-associated CpGs through Illumina Infinium HumanMethylation 450 K BeadChip; then, the pyrosequencing assay was used to further validate the association between the stable warfarin dose and alterations in the methylation of the screened CpGs. GenomeStudio Software and R were used to analyze the differentially methylated CpGs. Results The methylation levels of CpGs surrounding the xenobiotic response element (XRE) within the CYP1A1 promoter, differed significantly between the different dose groups (P 0, P

Abstract Background Premature ovarian insufficiency (POI) is a common disease in reproductive women. The pathogenesis of POI is not clear, although it is known that it involves the disorder of oocyte differentiation and development. The introduction of reprogramming human somatic cells into induced pluripotent stem cells (iPSCs) offers a unique opportunity to study many aspects of POI from cell differentiation in vitro that could ultimately lead to novel drug development and testing to help treat the disorder. Methods The fibroblasts from POI patients, including fragile X syndrome, abnormal karyotype (45, X; 45, X/46, XX; 45, XO and 47, XXX), and the gene mutation (FIGLA and GDF9) were reprogrammed to pluripotency status by retroviral transduction using defined factors. The morphology, growth characteristics, gene expression profiles, epigenetic status, and in vitro and in vivo differentiation potential of the POI-1-iPSCs (from fragile X syndrome) were analyzed. Then, POI-1-iPSCs were induced to differentiation into primordial germ cells (PGCs) with DNA methyltransferase inhibitors. Results The iPSCs were successfully generated from POI patients’ fibroblasts. The formed iPS clones have the same characteristics of human ESCs. POI-1-iPSCs were successfully generated with germline competence. The POI-1-iPSCs, with genotypes of fragile X syndrome, can be induced to differentiation into PGCs with high efficiency under our culture system by DNA demethylation. This study proved that disease-specific iPSC lines derived from POI patients could be generated and successfully differentiated into PGCs. Conclusions We established some novel, systemic cell models for the studying of the pathogenesis of POI patients. Second, DNA demethylation may accelerate the induction of human PGCs from iPSCs in vitro and the conclusion needs further exploration. This represents an important step in the novel approach for the study of the pathophysiology and potential egg resource for POI patients.

This paper considers a fresh produce three-layer e-commerce supply chain consisting of a producer, a third-party logistics service provider, and a fresh produce e-commerce enterprise in a new framework. The market demand for the fresh produce is affected by the safety traceability system availability, the freshness level, the unit online selling price, and the random factor. We develop the game models under different supply chain decision scenarios. Two different types of contracts, namely, unilateral cost-sharing and revenue-sharing contract, and consolidated rebate and revenue-sharing contract are proposed to facilitate coordination of the supply chain. The impact of the changes of market preferences on the supply chain decisions, the supply chain profits, and the contract policies implementation is examined. The theoretical derivations and results are illustrated with numerical examples. While enriching the relevant literature, this paper also provides a practical guidance for the production, operation, and sales of the fresh produce e-commerce supply chain.

This paper studied the train stop planning problem with variable train length and stop time under stochastic demand (TSPPWVTLSTSD). As we know, stop time and train length were often considered in a fixed manner in train stop planning for high-speed rail (HSR). One obvious disadvantage was that it often resulted in insufficient time for passengers to get on or get off a train. In addition, fixed train length may cause a waste of train capacity. And travel demand was usually assumed to be deterministic, although travel demand usually was stochastic. In this paper, we presented an optimization model that simultaneously optimized the stop-schedule, the stop time schedule and the train length schedule for each train trip under stochastic demand. By formulating deterministic equivalents to the chance constraints, we obtained a deterministic mixed integer model. To solve the problem, a novel column generation-based heuristic solution technique based on Dantzig-Wolfe decomposition principle and column generation procedure was proposed. Some numerical experiments and a case study based on real-world data were used to demonstrate that the proposed solution method can yield a service plan within a reasonable time compared with ILOG Cplex. Besides, the variable train length and stop time model needed fewer carriages and also gave rise to less total time loss compared with the fixed scenario.

As the core of the rail freight flow organization process, train formation problem (TFP) has attracted much attention. In Chinese practice, car flow routing, TFP, and train routing are usually optimized sequentially to reduce the complexity of computation, which may result in a local optimum, and even no feasible solution. To address this issue, this paper studies the integrated optimization of the three sub problems with aims to minimize the total cost of transportation cost, accumulation cost, and classification cost. An integer linear arc-based model incorporating the unitary and in-tree rules of a shipment is first formulated and solved by the state-of-the-art solver GUROBI. Since GUROBI can't deal with the large test cases, a path-based model is built and solved by a bespoken two-phase algorithm. The first phase of the algorithm is Benders-and-Price approach that combines Benders decomposition and column generation, and the second phase is to solve the arc-based model with some variables fixed as the corresponding values fetched from the first phase. The results show that the proposed algorithm outperforms GUROBI, and the acceleration techniques, i.e., trust region and Pareto-optimal cuts, can improve the convergence efficiency of Benders decomposition significantly.

Background We used bioinformatic analysis and quantitative reverse transcription polymerase chain reaction (RT-qPCR) assays to investigate the association between plasma microRNAs (miRNAs) and stable warfarin dosage in a Chinese Han population. Methods Bioinformatics analysis was used to screen out potential warfarin dose-associated miRNAs. Three plasma miRNAs were validated in 99 samples by RT-qPCR. Kruskal–Wallis test and multivariate logistic regression were used to compare differences in plasma miRNAs expression levels between three warfarin dosage groups. Results There were significant between-group differences among the three dose groups for hsa-miR-133b expression (p = 0.005), but we observed an “n-shaped” dose-dependent curve rather than a linear relationship. Expression levels of hsa-miR-24-3p (p = 0.475) and hsa-miR-1276 (p = 0.558) were not significantly different in the multivariate logistic regression. Conclusion miRNAs have received extensive attention as ideal biomarkers and possible therapeutic targets for various diseases. However, they are not yet widely used in precision medicine. Our results indicate that hsa-miR-133b may be a possible reference factor for the warfarin dosage algorithm. These findings emphasize the importance of a comprehensive evaluation of complex relationships in warfarin dose prediction models and provide new avenues for future pharmacogenomics studies.

IntroductionPregnancy in patients with mechanical heart valves (MHVs) is associated with high maternal complications and fetal complications.Anticoagulation treatments serve to decrease their venous clotting risk. Although some anticoagulation regimens have been used for patients during pregnancy with MHVs, no one is definitively superior among different regimens in recent studies. For a better understanding of the clinical treatment which anticoagulation regimen is more effective and safer during the pregnancy in patients with MHVs, a Bayesian network meta-analysis is necessary.Methods and analysisThis protocol has been reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols. Related studies until April 2019 will be searched in the following databases: PubMed, Embase,SinoMed and the using the OVID interface to search for evidence-based medicine reviews. A clinical trial registry (www.ClinicalTrials.gov) was also searched for unpublished trials. Both experimental studies (randomised clinical trials) and observational studies (cohort studies, case–control studies and case series studies) will be included in this study. Quality assessment will be conducted using Cochrane Collaboration’s tool or Newcastle-Ottawa Scale based on their study designs. The primary outcomes of interest will be the frequencies of serious maternal and fetal events. The additional outcomes of interest will be adverse maternal events, mode of delivery and adverse fetal events. Pairwise and network meta-analysis will be conducted using R (V.3.4.4, R Foundation for Statistical Computing, Vienna, Austria) and Stata (V.14, StataCorp). The ranking probabilities will be estimated at each possible rank for each anticoagulation regimen using the surface under the cumulative ranking curve. Statistical inconsistency assessment, subgroup analysis, sensitivity analysis and publication bias assessment will be performed.Ethics and disseminationEither ethics approval or patient consent is not necessary, because this study will be based on literature. The results of this study will be published in a peer-reviewed journal.PROSPERO registration numberCRD42019130659

This paper proposes a product-based framework that exploits cloud computing resources to improve the logistics of transporting door-to-door railway freight products. First, cluster analysis is used to determine the demand points on branch highway service networks and at stations on main railway service networks, enabling the establishment of a transfer service network between the two. Then, we develop a mathematical optimization model for door-to-door railway freight transportation products, in which the service time of arcs in the network is calculated based on railway freight car trajectory data. Finally, we examine the real-world case of the Wuhan-Dalang section of the Beijing-Guangzhou railway trunk line, demonstrating the practical value of big data and cloud computing technology for calculating the relevant parameters, as well as the adaptability of a framework that highlights product considerations.

In practice, vehicle scheduling is planned on a variable timetable so that the departure times of trips can be shifted in tolerable ranges, rather than on a fixed timetable, to decrease the required fleet size. This paper investigates the vehicle scheduling problem on a variable timetable with the constraint that each vehicle can perform limited trips. Since the connection-based model is difficult to solve by optimization software for a medium-scale or large-scale instance, a designed path-based model is developed. A Benders-and-Price algorithm by combining the Benders decomposition and column generation is proposed to solve the LP-relaxation of the path-based model, and a bespoke Branch-and-Price is used to obtain the integer solution. Numerical experiments indicate that a variable timetable approach can reduce the required fleet size with a tolerable timetable deviation in comparison with a fixed timetable approach. Moreover, the proposed algorithm is greatly superior to GUROBI in terms of computational efficiency and guarantees the quality of the solution.

Relying on the express freight network, the dispatching of empty pallets based on the pallet pool mode is studied to reuse pallets with the minimum transport cost, enhance the pallet utilization rate, reduce the waste of resources, and save the cost of logistics. Considering the influence of transport efficiency for different modes in transportation process, differences of transportation cost, carbon emissions, and transportation timeliness of demand points required, an optimization model is constructed. The objective of the model is to minimize the total cost including transportation cost, inventory cost, lease cost, and loss cost. According to the structural characteristics of the model, genetic algorithm and improved cloud clonal selection operation is used to solve the model. Finally, the validity and rationality of the optimization model are verified by a case study. The result shows that the total dispatching cost of considering time requirement is 1.8 times the cost without considering the time requirement, respectively, both less than the total cost of pallets leasing. Moreover, when there are 3 supply points and 2 demand points and the number of iterations is 100, after the algorithms are run for 30 times, the worst values are 9305 and 8317 for genetic algorithm and the improved cloud clonal selection operation, respectively. Therefore, the efficiency of the improved cloud clonal selection operation is higher than genetic algorithm.

In China, based on the mobile Internet technology and global positioning system (GPS), innovative bike-sharing is different from traditional bike-sharing system with docking station, for its flexibility and convenience. However, innovative bike-sharing system faces operational challenges, especially in faulty bike-sharing recycling (FBSR) problem. In this paper, a framework is designed based on the optimization method to solve the FBSR problem so that it can minimize the total recycling costs by taking the route optimization and loading capacity ratio as constraints. The FBSR method combines the K-means method for clustering faulty bike-sharing with planning recycling route for operational decisions. Moreover, CPLEX solver is used to obtain the desired result of the FBSR model. Finally, a case study based on a certain area in Beijing, China, is used to verify the validity and applicability of the model. The results show that the value of loading capacity ratio and the number of clustering points greatly affect the results of FBSR problem. Four vehicles are designated to execute FBSR tasks required by different clustering points. This study is of considerable significance for the bike-sharing promotion in the last-mile situation to the real problems arising in the initial period.

With the rapid development of multiyards railway intermodal terminal (MYRIT) construction in China, performance evaluation has become an important issue for terminal design and management departments. Due to the complexity of the multiyards terminal and the associated rail network, the train moving process and related terminal operations have become more complicated compared with the traditional intermodal container terminal. However, in general simulation platforms, the train moving process is simplified and train route scheduling rules are not considered in existing simulation models. In order to provide an accurate and comprehensive quantitative evaluation tool for MYRIT, a simulation platform based on the Timed Petri Net model has been developed, which can offer decision support for terminal design and management departments. In this platform, a yards and facilities layout module has been created to give simulation users access to designing the railway network on this platform. And a train route dispatching simulation method has been integrated to provide an accurate simulation of the train moving process. Based on a real case of Qianchang railway intermodal terminal that is located in Fujian Province, China, the platform is thoroughly validated against historical data. And the test scenarios show that train routes arrangement and handling equipment configuration both have a significant influence on overall terminal performance, which need to be carefully considered during terminal design and management.

An operational process at train marshaling yard is considered in this study. The inbound trains are decoupled and disassembled into individual railcars, which are then moved to a series of classification tracks, forming outbound trains after being assembled and coupled. We focus on the allocation plan of the classification tracks. Given are the disassembling and assembling sequence, the railcars connection plan, and a number of classification tracks. Output is the assignment of the railcars to the classification tracks. An integer programming model is proposed, aimed at reducing the number of coupling operations, as well as the number of dirty tracks which is related to the rehumping operation, and the order of the railcars on the outbound train must satisfy the block sequence. Tabu algorithm is designed to solve the problem, and the model is also tested by CPLEX in comparison. A numerical experiment based on a real-world case is analyzed, and the result can be reached within a reasonable amount of time. We also discussed a number of factors that may affect the track assignment and gave suggestions for the real-world case.

Bone regeneration is very important for the recovery of some diseases including osteoporosis and bone fracture trauma. It is a multiple-step- and multiple-gene-involved complex process, including the matrix secretion and calcium mineralization by osteoblasts differentiated from mesenchymal stem cells (MSCs) and the absorption of calcium and phosphorus by osteoclasts differentiated from hematopoietic stem cells. Long noncoding RNAs (lncRNAs) are a family of transcripts longer than 200 nt without or with very low protein-coding potential. Recent studies have demonstrated that lncRNAs are widely involved in the regulation of lineage commitment and differentiation of stem cells through multiple mechanisms. In this review, we will summarize the roles and molecular mechanism of lncRNAs including H19, MALAT1, MODR, HOTAIR, DANCR, MEG3, HoxA-AS3, and MIAT in osteogenesis ossification; lncRNA ZBED3-AS1 and CTA-941F9.9, DANCR, and HIT in chondrogenic differentiation; and lncRNA DANCR in osteoclast differentiation. These findings will facilitate the development and application of novel molecular drugs which regulate the balance of bone formation and absorption.

Custom bus routes need to be optimized to meet the needs of a customized bus for personalized trips of different passengers. This paper introduced a customized bus routing problem in which trips for each depot are given, and each bus stop has a fixed time window within which trips should be completed. Treating a trip as a virtual stop was the first consideration in solving the school bus routing problem (SBRP). Then, the mixed load custom bus routing model was established with a time window that satisfies its requirement and the result were solved by Cplex software. Finally, a simple network diagram with three depots, four pickup stops, and five delivery stops was structured to verify the correctness of the model, and based on the actual example, the result is that all the buses ran 124.42 kilometers, the sum of kilometers was 10.35 kilometers less than before. The paths and departure times of the different busses that were provided by the model were evaluated to meet the needs of the given conditions, thus providing valuable information for actual work.

Timely predicting and controlling the traffic congestion in a station caused by an emergency is an important task in railway emergency management. However, traffic forecasting in an emergency is subject to a dynamic service network, with uncertainty surrounding elements such as the capacity of the transport network, schedules, and plans. Accurate traffic forecasting is difficult. This paper proposes a practical time-space network model based on a train diagram for predicting and controlling the traffic congestion in a station caused by an emergency. Based on the train diagram, we constructed a symmetric time-space network for the first time by considering the transition of the railcar state. On this basis, an improved A* algorithm based on the railcar flow route was proposed to generate feasible path sets and a dynamic railcar flow distribution model was built to simulate the railcar flow distribution process in an emergency. In our numerical studies, these output results of our proposed model can be used to control traffic congestion.

Studying the interaction between demand forecasting and train stop planning is important, as it ensures the sustainable development of high-speed rail (HSR). Forecasting the demand for high-speed rail (HSR), which refers to modal choice or modal split in this paper, is the first step in high-speed rail (HSR) planning. Given the travel demand and the number of train trips on each route, the train stop planning problem (TSPP) of line planning involves determining the stations at which each train trip stops, i.e., the stop-schedule of each train trip, so that the demand can be satisfied. To integrate and formulate the two problems, i.e., the modal choice problem (MCP) and train stop planning problem (TSPP), a nonlinear model is presented with the objective of maximizing the total demand captured by a high-speed rail system. To solve the model, a heuristic iterative algorithm is developed. To study the relationship between the demand and the service, the Beijing−Shanghai high-speed rail (HSR) corridor in China is selected. The empirical analysis indicates that combining modal choice and train stop planning should be considered for the sustainable design of high-speed rail (HSR) train services. Furthermore, the model simulates the impact of the number of stops on its mode share by reflecting changes in travelers’ behaviors according to HSR train stop planning, and it also provides a theoretical basis for the evaluation of the adaptability of the service network to travel demand.

The quality of route design can greatly affect the operational efficiency of feeder bus service for high-speed rail stations. A bi-objective optimization formulation is established to consider the trade-off between two conflicting optimization objectives, namely maximizing the travel demand that can be served and minimizing the feeder bus route length. The Pareto optimal solutions of the discrete mathematical formulation are generated by the exact ε-constraint method. We test the proposed approach with a numerical example on an actual size scale. The results indicate that the computational efficiency of the solution approach is encouraging, and a series of route design plans and location stop plans are generated simultaneously in a short time. A numerical example also shows that as the passengers’ maximum acceptable walking distance increases, more travel demand can be served when the route length does not change much. Benefits brought by increasing feeder bus route length are analyzed and the robustness of obtained solutions is verified. The comparison of our approach and an existing approach is also presented to demonstrate that our approach can generate better solutions.

Rescheduling is often needed when trains stay in segments or stations longer than specified in the timetable due to disturbances. Under crowded situations, it is more challenging to return to normal with heavy passenger flow. Considering making a trade-off between passenger loss and operating costs, we present a train regulation combined with a passenger control model by analyzing the interactive relationship between passenger behaviors and train operation. In this paper, we convert the problem into a Markov decision process and then propose the management strategy of regulating the running time and controlling the number of boarding passengers. Owing to the high dimensions of the large-scale problem, we applied the Approximate Dynamic Programming (ADP) approach, which approximates the value function with state features to improve computational efficiency. Finally, we designed three experimental scenarios to verify the effectiveness of our proposed model and approach. The results show that both the proposed model and the approach have a good performance in the cases with different passenger flows and different disturbances.

The community shuttle system plays an important role in serving communities with a heavy travel demand for the metro service. Stop location and route design are the two main decisions of planning a community shuttle service. Those two decisions are interrelated and interact, and are strongly related to the user cost and operating cost. The optimal stop location and route can help to reduce the walking distance of passengers and the route length. To make a trade-off between the walking distance of passengers and route length, we propose a discrete optimization problem. A single integrated formulation is established to optimize stop location and route design. Planners can decide the stop location and route design of the community shuttle system simultaneously based on this formulation. Then, we present a non-dominated sorting genetic (NSGA-II) based algorithm to obtain the non-dominated solutions of the discrete optimization formulation. The numerical experiments and a case study based on real-world data are used to demonstrate that the proposed solution method can yield a set of plans of stop location and route in a reasonable time. We also find that when the maximum tolerable walking distance is set to 418 m, the trade-off between the total walking distance of passengers and route length can be obtained.

This paper investigated, for the first time, the game and coordination of a dual-channel, three-layered, green fresh produce supply chain, with regard to its economic, social, and environmental performance. Considering that the market demand is dual-channel priced and sensitive to the degree of greenness and the freshness-level, four game models, under different scenarios have been established. These included a centralized scenario, a decentralized scenario, and two contractual scenarios. The equilibrium solutions under the four scenarios were characterized. From the perspective of a sustainable development, the economic, social, and environmental performance of the supply chain was analyzed. To enhance the supply chain performance, two contract mechanisms were designed and the conditions for a multi-win outcome were obtained. Accordingly, many propositions and management implications were provided. The results showed that, (1) compared to the centralized supply chain case, the performance of the decentralized supply chain case is inferior; (2) in addition to increasing the concentration of the supply chain decisions, the two contracts proposed can effectively coordinate the green supply chain and improve its sustainable performance; and (3) the performance of the supply chain is positively driven by the consumers’ sensitivity to greenness degree and the freshness level of fresh produce. This paper fills a research gap and helps the participants of the channel recognize the operational decision principle of a complex green supply chain, in order to achieve a higher and a long-term sustainable-development performance.

Although forsterite (Mg2SiO4) possesses good biocompatibility and suitable mechanical properties, the insufficient bioactivity and degradability hinders its further application. In this study, a novel MgO-CaO-SiO2 system was developed by adding wollastonite (CaSiO3) into Mg2SiO4 to fabricate bone scaffolds via selective laser sintering (SLS). The apatite-forming ability and degradability of the scaffolds were enhanced because the degradation of CaSiO3 could form silanol groups, which could offer nucleation sites for apatite. Meanwhile, the mechanical properties of the scaffolds grew with increasing CaSiO3 to 20 wt %. It was explained that the liquid phase of CaSiO3 promoted the densification during sintering due to its low melting point. With the further increase in CaSiO3, the mechanical properties decreased due to the formation of the continuous filling phase. Furthermore, the scaffolds possessed a well-interconnected porous structure and exhibited an ability to support cell adhesion and proliferation.