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Hepatocellular carcinoma (HCC) stands as the most prevalent and treatment‐resistant malignant tumour, characterized by a dismal prognosis. Croton acylation (CA) has recently gained attention as a critical factor in cancer pathogenesis. This study sought to rapidly identify prognostic features of HCC linked to CA. Differential analysis was conducted between tumour tissues and adjacent non‐tumour tissues in the TCGA‐LIHC and GSE76427 datasets to uncover differentially expressed genes (DEG1 and DEG2). The intersection of DEG1 and DEG2 highlighted DEGs with consistent expression patterns. Single‐sample gene set enrichment analysis scores were calculated for 18 lysine crotonylation‐related genes (LCRGs) identified in prior research, showing significant differences between tumour and normal groups. Subsequently, weighted gene co‐expression network analysis was employed to identify key module genes correlated with the LCRG score. Candidate genes were identified by overlapping consistently expressed DEGs with key module genes. Prognostic features were identified, and risk scores were determined via regression analysis. Patients were categorized into risk groups based on the optimal cutoff value. Gene set enrichment analysis (GSEA) and immunoassays were also performed. The prognostic features were further validated using reverse transcription‐quantitative polymerase chain reaction (RT‐qPCR). A total of 88 candidate genes were identified from 1179 consistently expressed DEGs and 4200 key module genes. Seven prognostic features were subsequently identified: TMCO3, RAP2A, ITGAV, ZFYVE26, CHST9, HMGN4, and KLHL21. GSEA revealed that DEGs between risk groups were primarily associated with chylomicron metabolism, among other pathways. Additionally, activated CD4+ T cells demonstrated the strongest positive correlation with risk scores, and most immune checkpoints showed significant differences between risk groups, with ASXL1 exhibiting the strongest correlation with risk scores. The Tumour Immune Dysfunction and Exclusion score was notably higher in the high‐risk group. Moreover, in both the TCGA‐LIHC and ICGC‐LIRI‐JP datasets, the expression of other prognostic features was elevated in tumour tissues, with the exception of CHST9. RT‐qPCR confirmed the increased expression of TMCO3, RAP2A, ITGAV, ZFYVE26, and HMGN4. This study establishes a risk model for HCC based on seven crotonylation‐associated prognostic features, offering a theoretical framework for the diagnosis and treatment of HCC. [ABSTRACT FROM AUTHOR]

Peripheral nerve defect are common clinical problem caused by trauma or other diseases, often leading to the loss of sensory and motor function in patients. Autologous nerve transplantation has been the gold standard for repairing peripheral nerve defects, but its clinical application is limited due to insufficient donor tissue. In recent years, the application of tissue engineering methods to synthesize nerve conduits for treating peripheral nerve defect has become a current research focus. This study introduces a novel approach for treating peripheral nerve defects using a tissue‐engineered PLCL/SF/NGF@TA‐PPy‐RGD conduit. The conduit was fabricated by combining electrospun PLCL/SF with an NGF‐loaded conductive TA‐PPy‐RGD gel. The gel, synthesized from RGD‐modified tannic acid (TA) and polypyrrole (PPy), provides growth anchor points for nerve cells. In vitro results showed that this hybrid conduit could enhance PC12 cell proliferation, migration, and reduce apoptosis under oxidative stress. Furthermore, the conduit activated the PI3K/AKT signalling pathway in PC12 cells. In a rat model of sciatic nerve defect, the PLCL/SF/NGF@TA‐PPy‐RGD conduit significantly improved motor function, gastrocnemius muscle function, and myelin sheath axon thickness, comparable to autologous nerve transplantation. It also promoted angiogenesis around the nerve defect. This study suggests that PLCL/SF/NGF@TA‐PPy‐RGD conduits provide a conducive environment for nerve regeneration, offering a new strategy for peripheral nerve defect treatment, this study provided theoretical basis and new strategies for the research and treatment of peripheral nerve defect. [ABSTRACT FROM AUTHOR]

Abstract. Understanding citywide transit patterns is important for transportation management, including city planning and route optimization. The wide deployment of automated fare collection (AFC) systems in public transit vehicles has [...]

The escalating evolution of aquaculture has wielded a profound and far-reaching impact on regional sustainable development, ecological equilibrium, and food security. Currently, most aquaculture mapping efforts mainly focus on coastal aquaculture ponds rather than diverse inland aquaculture areas. Recognizing all types of aquaculture areas and accurately classifying different types of aquaculture areas remains a challenge. Here, on the basis of the Google Earth Engine (GEE) and the time-series Sentinel-1 and -2 data, we developed a novel hierarchical framework extraction method for mapping fine inland aquaculture areas (aquaculture ponds + rice-crawfish fields) by employing distinct phenological disparities within two temporal windows (T1 and T2) in Qianjiang, so-called "Home of Chinese Crawfish". Simultaneously, we evaluated the classification performance of four distinct machine learning classifiers, namely Random Forest (RF), Support Vector Machine (SVM), Classification and Regression Trees (CART), and Gradient Boosting (GTB), as well as 11 feature combinations. Following an exhaustive comparative analysis, we selected the optimal machine learning classifier (i.e., the RF classifier) and the optimal feature combination (i.e., feature combination after an automated feature selection method) to classify the aquaculture areas with high accuracy. The results underscore the robustness of the proposed methodology, achieving an outstanding overall accuracy of 93.8%, with an F1 score of 0.94 for aquaculture. The result indicates that an area of 214.6 ± 10.5 km2 of rice-crawfish fields, constituting approximately 83% of the entire aquaculture area in Qianjiang, followed by aquaculture ponds (44.3 ± 10.7 km2, 17%). The proposed hierarchical framework, based on significant phenological characteristics of varied aquaculture types, provides a new approach to monitoring inland freshwater aquaculture in China and other regions of the world. [ABSTRACT FROM AUTHOR]

The fall armyworm (FAW) (Spodoptera frugiperda) (J. E. Smith) is a migratory pest that lacks diapause and has raised widespread concern in recent years due to its global dispersal and infestation. Seasonal environmental changes lead to its large-scale seasonal activities, and quantitative simulations of its dispersal patterns and spatiotemporal distribution facilitate integrated pest management. Based on remote sensing data and meteorological assimilation products, we constructed a mechanistic model of the dynamic distribution of FAW (FAW-DDM) by integrating weather-driven flight of FAW with host plant phenology and environmental suitability. The potential distribution of FAW in China from February to August 2020 was simulated. The results showed a significant linear relationship between the dates of the first simulated invasion and the first observed invasion of FAW in 125 cities (R2 = 0.623; p < 0.001). From February to April, FAW was distributed in the Southwestern and Southern Mountain maize regions mainly due to environmental influences. From May to June, FAW spread rapidly, and reached the Huanghuaihai and North China maize regions between June to August. Our results can help in developing pest prevention and control strategies with data on specific times and locations, reducing the impact of FAW on food security. [ABSTRACT FROM AUTHOR]

Dysregulation of circular RNAs (circRNAs) executes important regulatory roles in carcinogenesis. Nonetheless, few studies focused on the mechanisms of circRNAs in cholangiocarcinoma (CCA). qRT‐PCR was applied to verify the dysregulated circRNAs in CCA. Fisher's exact test, Kaplan‐Meier analysis and Cox regression model were utilized to investigate the clinical implications of circ‐LAMP1 in the patients with CCA. The viability, apoptosis, migration and invasion of CCA cells were detected after silencing/overexpression of circ‐LAMP1. Xenograft and lung metastasis assays were performed to verify the in vitro results. The regulatory networks of circ‐LAMP1 were unveiled by bioinformatic analysis, RNA immunoprecipitation (RIP), RNA pulldown and luciferase reporter assays. Up‐regulation of circ‐LAMP1 was found in CCA tissue samples and cell lines. Enhanced level of circ‐LAMP1 was linked to clinical severity, high post‐operative recurrence and poor prognosis for the patients with CCA. Gain/loss‐of‐function assays confirmed the oncogenic role of circ‐LAMP1 in mediating cell growth, apoptosis, migration and invasion. Nevertheless, the level of circ‐LAMP1 had no effect on normal biliary epithelium proliferation and apoptosis. Animal study further verified the in vitro data. Mechanistically, circ‐LAMP1 directly sponged miR‐556‐5p and miR‐567, thereby releasing their suppression on YY1 at post‐transcriptional level. Rescue assay indicated that the oncogenic role of circ‐LAMP1 is partially dependent on its modulation of YY1 in CCA. In summary, this study suggested that circ‐LAMP1 might be used as a promising biomarker/therapeutic target for CCA. [ABSTRACT FROM AUTHOR]

Without the assistance of Global Positioning System (GPS), estimating the 3D position of indoor and outdoor pedestrians using a single wearable device is a daunting if not impossible task, especially if micro-sensors are used. Here, we present a novel 3D position estimation method using one integrated ankle sensing device, which consists of an accelerometer, a gyroscope, a magnetometer, and a barometer. Pedestrians’ vertical position is estimated by fusing the acceleration and angular velocity as well as the height derived from barometer data. To estimate pedestrians’ horizontal position, we proposed an adaptive multimodal stride length model and a multi-sensor-fusion-based heading angle estimation method, using the Pedestrian Dead Reckoning (PDR) mechanism. By introducing a vertical variable into the stride length model, this new model greatly improved the applicability and accuracy of PDR in horizontal position estimation. Based on this new model, PDR can be used not only for estimating the horizontal position of the pedestrian walking on flat areas but also for those walking up and down stairs. The effectiveness and applicability of our method in 3D position estimation have been demonstrated in several different experiments of indoor and outdoor scenes. The first is when a pedestrian walks on an indoor flat ground, following a spiral trajectory. The estimation accuracy of pedestrians’ height position is 1.5cm and the ratio of horizontal walking estimation error is 1.02m with a total walking distance of 53.1m. The second is when a pedestrian walks up staircases from Floor 4 to Floor 8 in a building. The cumulative error of the estimated height is 0.23m with a total height of 14.4m, and the root mean square error of the estimated horizontal 2D position is 15cm compared to a total horizontal walking distance of 38.4m. The third case involves a pedestrian walking on audience stands of an outdoor stadium and returns to the starting position for a total distance of 94.4m. The estimation error from the sensing device is 0.92m in this case, with mean error of the estimated height position of each step at 3.3cm. Having the capability to provide centimeter-level position estimation of pedestrians, this sensing device can be applied for 3D body tracking and indoor/outdoor pedestrian positioning and navigation. [ABSTRACT FROM AUTHOR]

Cystatin SN, a specific cysteine protease inhibitor, is thought to be involved in various malignant tumors. Therefore, we evaluated the role of cystatin SN in hepatocellular carcinoma (HCC). Notably, cystatin SN was elevated in tumorous samples and cells. Moreover, overexpression of cystatin SN was correlated with tumor diameter and TNM stage. Cox multivariate analysis displayed that cystatin SN was an independent prognosis indicator and that high cystatin SN level was associated with a dismal prognosis. Moreover, cystatin SN enhancement facilitated the proliferation, migratory, and invasive potential of Huh7 and HCCLM3 cells, whereas cystatin SN knockdown caused the opposite effect. Cystatin SN also modulated the epithelial‐mesenchymal transition progression through the PI3K/AKT pathway. In vivo cystatin SN promoted HCCLM3 cell growth and metastasis in xenograft mice model. Thus, cystatin SN was involved in HCC progression and could be a latent target for HCC treatment. [ABSTRACT FROM AUTHOR]

Traumatic brain injury, a common cause of acquired epilepsy, is typical to find necrotic cell death within the injury core. The dynamic changes in astrocytes surrounding the injury core contribute to epileptic seizures associated with intense neuronal firing. However, little is known about the molecular mechanisms that activate astrocytes during traumatic brain injury or the effect of functional changes of astrocytes on seizures. In this comprehensive review, we present our cumulated understanding of the complex neurological affection in astrocytes after traumatic brain injury. We approached the problem through describing the changes of cell morphology, neurotransmitters, biochemistry, and cytokines in astrocytes during post-traumatic epilepsy. In addition, we also discussed the relationship between dynamic changes in astrocytes and seizures and the current pharmacologic agents used for treatment. Hopefully, this review will provide a more detailed knowledge from which better therapeutic strategies can be developed to treat post-traumatic epilepsy. [ABSTRACT FROM AUTHOR]

An in-fiber Bragg grating (FBG) sensor for refractive index (RI) measurement is proposed and experimentally demonstrated by using an optoelectronic oscillator (OEO). The index sensor device is an etched phase-shifted fiber Bragg grating (PS-FBG) with a radius of $27.5~\mu \text{m}$. In the OEO loop, the PS-FBG is exposed to different liquid samples via evanescent field interaction of the guided fiber mode. Since the RI change can introduce a shift to the center wavelength of the PS-FBG, the center frequency of the OEO will change. Therefore, the variation of the ambient RI can be estimated by measuring the oscillating frequency change. Since the oscillating microwave signal can be measured by a digital signal processor at a high resolution, the OEO-based sensor is able to provide RI measurement at an ultra-high resolution. The proposed measurement method is experimentally evaluated. The sensor has a sensitivity of 530 MHz/RIU and can detect an index variation of $1.9 \times 10^{-6}$ RIU. [ABSTRACT FROM AUTHOR]

In urban transportation systems, transfer stations refer to hubs connecting a variety of bus and subway lines and, thus, are the most important nodes in transportation networks. The pervasive availability of large-scale travel traces of passengers, collected from automated fare collection (AFC) systems, has provided unprecedented opportunities for understanding citywide transfer patterns, which can benefit smart transportation, such as smart route recommendation to avoid crowded lines, and dynamic bus scheduling to enhance transportation efficiency. To this end, in this article, we provide a systematic study of the measurement, patterns, and modeling of spatiotemporal dynamics of passenger transfers. Along this line, we develop a data-driven analytical system for modeling the transfer volumes of each transfer station. More specifically, we first identify and quantify the discriminative patterns of spatiotemporal dynamics of passenger transfers by utilizing heterogeneous sources of transfer related data for each station. Also, we develop a multi-task spatiotemporal learning model for predicting the transfer volumes of a specific station at a specific time period. Moreover, we further leverage the predictive model of passenger transfers to provide crowdedness-aware route recommendations. Finally, we conduct the extensive evaluations with a variety of real-world data. Experimental results demonstrate the effectiveness of our proposed modeling method and its applications for smart transportation. [ABSTRACT FROM AUTHOR]

In this study, a new fast algorithm for optimal design of block digital filters is proposed based on the skew circulant matrix, the Toeplitz and the skew shift cyclic matrices. The developed skew‐cyclic filter, compared with the cyclic filter, not only achieves the same computational complexity of the design process and the memory requirements, but is more efficient with only approximately half of the computational cost for the real signals. [ABSTRACT FROM AUTHOR]

Soil nutrients, including soil available potassium (SAK), soil available phosphorous (SAP), and soil organic matter (SOM), play an important role in farmland soil productivity, food security, and agricultural management. Spectroscopic analysis has proven to be a rapid, nondestructive, and effective technique for predicting soil properties in general and potassium, phosphorous, and organic matter in particular. However, the successful estimation of soil nutrient content by visible and near-infrared (Vis-NIR) reflectance spectroscopy depends on proper calibration methods (including preprocessing transformation methods and multivariate methods for regression analysis) and the selection of appropriate variable selection techniques. In this study, raw spectrum and 13 preprocessing transformations combined with 2 variable selection methods (competitive adaptive reweighted sampling (CARS) and the successive projections algorithm (SPA)) and 2 regression algorithms (support vector machine (SVM) and partial least squares regression (PLSR)), for a total of 56 calibration methods, were investigated for modeling and predicting the above three soil nutrients using hyperspectral Vis-NIR data (400–2450 nm). The results show that first-order derivatives based on logarithmic and inverse transformations (FD-LGRs) can provide better predictions of soil available potassium and phosphorous, and the best form of soil organic matter transformation is SG+MSC. CARS was superior to the SPA in selecting effective variables, and the PLSR model outperformed the SVM models. The best estimation accuracies (R2, RMSE) for soil available potassium, phosphorous, and organic matter were 0.7532, 32.3090 mg/kg; 0.7440, 6.6910 mg/kg; and 0.9009, 3.2103 g/kg, respectively, and their corresponding calibration methods were (FD-LGR)/SPA/PLSR, (FD-LGR)/SPA/PLSR, and SG+MSC/CARS/SVM, respectively. Overall, for the prediction of the soil nutrient content, organic matter was superior to available phosphorous, followed by available potassium. It was concluded that the application of hyperspectral images (Vis-NIR data) was an efficient method for mapping and monitoring soil nutrients at the regional scale, thus contributing to the development of precision agriculture. [ABSTRACT FROM AUTHOR]

Background: Abnormal metabolism, including abnormal lipid metabolism, is a hallmark of cancer cells. Some studies have demonstrated that the lipogenic pathway might promote the development of hepatocellular carcinoma (HCC). However, the role of the lipolytic pathway in HCC has not been elucidated. Methods: We compared levels of adipose triglyceride lipase (ATGL) in human HCC and healthy liver tissues by real time PCR, western blot and immunohistochemistry. We measured diacylglycerol(DAG) and free fatty acid (FFA) levels in HCC cells driven by the NEAT1-ATGL axis and in HCC tissues. We also assessed the effects of ATGL, DAG, FFA, and NEAT1 on HCC cells proliferation in vitro and in an orthotopic xenograft HCC mouse model. We also performed a luciferase reporter assay to investigate the interaction between NEAT1/ATGL and miR-124-3p. Results: We found that the lipolytic enzyme, ATGL is highly expressed in human HCC tissues and predicts poor prognosis. We also found that high levels of DAG and FFA are present in HCC tissues. Furthermore, the lncRNA-NEAT1 was found to modulate ATGL expression and disrupt lipolysis in HCC cells via ATGL. Notably, ATGL and its products, DAG and FFA, were shown to be responsible for NEAT1-mediated HCC cell growth. NEAT1 regulated ATGL expression by binding miR-124-3p. Additionally, NEAT1 knockdown attenuated HCC cell growth through miR-124-3p/ATGL/DAG+FFA/PPARα signaling. Conclusion: Our results reveal that NEAT1-modulates abnormal lipolysis via ATGL to drive HCC proliferation. [ABSTRACT FROM AUTHOR]

GPUs provide impressive computing power, but GPU programming can be challenging. Here, an experience in porting real-world earthquake code to Nvidia GPUs is described. Specifically, an annotation-based programming model, called Mint, and its accompanying source-to-source translator are used to automatically generate CUDA source code and simplify the exploration of performance tradeoffs. [ABSTRACT FROM PUBLISHER]

• Voltage-detection active power filters (VDAPFs), SVGs and multi-function grid-connected inverters (MFGCIs) are used to mitigate harmonic and voltage deviation simultaneously. • Remaining capacity of MFGCIs is utilized to mitigate PQ disturbances, and the remaining disturbances are mitigated by allocating VDAPFs and SVGs. • After VDAPF meets harmonic requirements, its remaining capacity is used for reactive power compensation. • Compensation coefficients of harmonic and reactive power for MFGCIs are optimized in each operation. • Minimization of total cost and optimization of annual average PQ level. A novel strategy for collaborative optimization allocation of voltage-detecting active power filters (VDAPFs) and static var generators (SVGs) considering multi-functional grid-connected inverters (MFGCIs) contribution is proposed to mitigate voltage harmonic (VH) and voltage deviation (VD) in distribution networks. Based on the defined integrated voltage sensitivity, two partitioning schemes for the VDAPFs and SVGs to be installed and the MFGCIs already installed are studied. Two methods based on single and integrated sensitivity are adopted to coordinately determine dominant nodes as candidates of VDAPFs and SVGs in each region. The mitigation regions of the non-dominant nodes with MFGCIs are determined. With the limitation of MFGCI capacity, a comprehensive evaluation model of PQ level is established to get the compensation coefficients of harmonic and reactive power for MFGCIs. Multiple objectives model including the total cost and the annual average PQ level is presented to optimize the sites and sizes of VDAPFs and SVGs. Pareto optimal solutions with uniform distribution are obtained by the normalized normal constraint (NNC) algorithm. The proposed strategy is implemented on IEEE 33-bus system and PG&E 69-bus system. The results verify the effectiveness and applicability of the proposed strategy by comparing the two allocations with and without MFGCIs and the traditional allocation. [ABSTRACT FROM AUTHOR]

As a novel and promising technology for 5G networks, device-to-device (D2D) communication has garnered a significant amount of research interest because of the advantages of rapid sharing and high accuracy on deliveries as well as its variety of applications and services. Big data technology offers unprecedented opportunities and poses a daunting challenge to D2D communication and sharing, where the data often contain private information concerning users or organizations and thus are at risk of being leaked. Privacy preservation is necessary for D2D services but has not been extensively studied. In this paper, we propose an (a, k)-anonymity privacy-preserving framework for D2D big data deployed on MapReduce. Firstly, we provide a framework for the D2D big data sharing and analyze the threat model. Then, we propose an (a, k)-anonymity privacy-preserving framework for D2D big data deployed on MapReduce. In our privacy-preserving framework, we adopt (a, k)-anonymity as privacy-preserving model for D2D big data and use the distributed MapReduce to classify and group data for massive datasets. The results of experiments and theoretical analysis show that our privacy-preserving algorithm deployed on MapReduce is effective for D2D big data privacy protection with less information loss and computing time. [ABSTRACT FROM AUTHOR]

Background and Aims: Microvascular invasion (MVI) is a crucial pathological hallmark of HCC that is closely associated with poor outcomes, early recurrence, and intrahepatic metastasis following surgical resection and transplantation. However, the intricate tumor microenvironment and transcriptional programs underlying MVI in HCC remain poorly understood., Approach and Results: We performed single-cell RNA sequencing of 46,789 individual cells from 10 samples of MVI+ (MVI present) and MVI- (MVI absent) patients with HCC. We conducted comprehensive and comparative analyses to characterize cellular and molecular features associated with MVI and validated key findings using external bulk, single-cell, and spatial transcriptomic datasets coupled with multiplex immunofluorescence assays. The comparison identified specific subtypes of immune and stromal cells critical to the formation of the immunosuppressive and pro-metastatic microenvironment in MVI+ tumors, including cycling T cells, lysosomal associated membrane protein 3+ dendritic cells, triggering receptor expressed on myeloid cells 2+ macrophages, myofibroblasts, and arterial i endothelial cells. MVI+ malignant cells are characterized by high proliferation rates, whereas MVI- malignant cells exhibit an inflammatory milieu. Additionally, we identified the midkine-dominated interaction between triggering receptor expressed on myeloid cells 2+ macrophages and malignant cells as a contributor to MVI formation and tumor progression. Notably, we unveiled a spatially co-located multicellular community exerting a dominant role in shaping the immunosuppressive microenvironment of MVI and correlating with unfavorable prognosis., Conclusions: This study provides a comprehensive single-cell atlas of MVI in HCC, shedding light on the complex multicellular ecosystem and molecular features associated with MVI. These findings deepen our understanding of the underlying mechanisms driving MVI and provide valuable insights for improving clinical diagnosis and developing more effective treatment strategies., (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc.)

Background: The protein-coding gene RAB22A , a member of the RAS oncogene family, is amplified or overexpressed in certain cancers. However, its action mechanism in hepatocellular carcinoma (HCC) remains unclear. Here, we aimed to examine the connection between RAB22A and survival prognosis in HCC and explore the biological significance of RAB22A., Methods: A database-based pan-cancer expression analysis of RAB22A was performed. Kaplan-Meier analysis and Cox regression were performed to evaluate the association between RAB22A expression and survival prognosis in HCC. Using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA), various potential biological functions and regulatory pathways of RAB22A in HCC were discovered. Tumor immune infiltration was studied using the single sample gene set enrichment analysis (ssGSEA) method. N6-methyladenosine modifications and the regulatory network of competitive endogenous RNA (ceRNA) were verified in the TCGA cohort., Results: RAB22A was upregulated in HCC samples and cell lines. A high RAB22A expression in HCC was strongly correlated with sex, race, age, weight, TNM stage, pathological stage, tumor status, histologic grade, TP53 mutation status, and alpha fetal protein (AFP) levels. Overexpression of RAB22A indicated a poor prognosis was related to overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI). GO and KEGG analyses revealed that the differentially expressed genes related to RAB22A might be involved in the proteasomal protein catabolic process, ncRNA processing, ribosome ribosomal subunit, protein serine/threonine kinase activity, protein serine kinase activity, Endocytosis, and non-alcoholic fatty liver disease. GSEA analyses revealed that the differentially expressed genes related to RAB22A might be involved in the T cell receptor, a co-translational protein, that binds to the membrane, axon guidance, ribosome, phagocytosis, and Eukaryotic translation initiation. RAB22A was correlated with N6-methyladenosine expression in HCC and established RAB22A -related ceRNA regulatory networks. Finally, RAB22A expression was positively connected the levels of infiltrating with T helper cells, Tcm cells, and Th2 cells,In contrast, we observed negatively correlations with cytotoxic cells, DCs, and pDCs cells.Moreover, RAB22A expression showed a strong correlation with various immunomarkergroups in HCC., Conclusions: RAB22A is a potential therapeutic target for improving HCC prognosis and is closely related to immune cell infiltration., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Wen, Meng, Li, Li, Liu, Zhang, Zhao, Zhang, Wang, Ju, Cui and Lu.)

As a member of the phospholipase family, phospholipase C beta 1 ( PLCB1 ) is involved in phospholipid hydrolysis and is frequently upregulated in human cancer. However, little is known about the role of PLCB1 in cholangiocarcinoma (CCA). In this study, we uncover a role for PLCB1 in CCA progression and identify the underlying mechanisms. Both human CCA tissues and CCA cell lines expressed high levels of PLCB1. PLCB1 promoted tumor development and growth in various CCA mouse models, including transposon-based tumorigenesis models. PLCB1 activated PI3K/AKT signaling to induce CCA cells to undergo epithelial-to-mesenchymal transition (EMT). Mechanistically, PABPC1 interacted with PLCB1 and PI3K to amplify PLCB1-mediated EMT via PI3K/AKT/GSK3β/Snail signaling. Ectopic PLCB1 induced resistance to treatment with gemcitabine combined with cisplatin, which could be reversed by the AKT inhibitor MK2206. PLCB1 expression was regulated by miR-26b-5p through direct interaction with PLCB1 3'UTR. Collectively, these data identify a PLCB1-PI3K-AKT signaling axis vital for CCA development and EMT, suggesting that AKT can be used as a therapeutic target to overcome chemotherapy resistance in CCA patients with high PLCB1 expression. SIGNIFICANCE: PLCB1 functions as an oncogenic driver in cholangiocarcinoma development that confers an actionable therapeutic vulnerability to AKT inhibition., (©2021 The Authors; Published by the American Association for Cancer Research.)

Aims: Emerging evidence is demonstrating that rapid regeneration of remnant liver elicited by associating liver partition and portal vein ligation for staged hepatectomy (ALPPS) may be attenuated in fibrotic livers. However, the molecular mechanisms responsible for this process are largely unknown. It is widely acknowledged that the TGFβ1 signaling axis plays a major role in liver fibrosis. Therefore, the aims of this study were to elucidate the underlying mechanism of liver regeneration during ALPPS with or without fibrosis, specifically focusing on TGFβ1 signaling. Approach: ALPPS was performed in rat models with N -diethylnitrosamine-induced liver fibrosis and no fibrosis. Functional liver remnant regeneration and expression of TGFβ1 were analyzed during the ALPPS procedures. Adeno-associated virus-shTGFβ1 and the small molecule inhibitor LY2157299 (galunisertib) were used separately or in combination to inhibit TGFβ1 signaling in fibrotic rats. Results: Liver regeneration following ALPPS was lower in fibrotic rats than non-fibrotic rats. TGFβ1 was a key mediator of postoperative regeneration in fibrotic liver. Interestingly, AAV-shTGFβ1 accelerated the regeneration of fibrotic functional liver remnant and improved fibrosis, while LY2157299 only enhanced liver regeneration. Moreover, combination treatment elicited a stronger effect. Conclusions: Inhibition of TGFβ1 accelerated regeneration of fibrotic liver, ameliorated liver fibrosis, and improved liver function following ALPPS. Therefore, TGFβ1 is a promising therapeutic target in ALPPS to improve fibrotic liver reserve function and prognosis., Competing Interests: Competing Interests: The authors have declared that no competing interest exists., (© The author(s).)

Purpose: As a main rate-limiting subunit of the 2-oxoglutarate dehydrogenase multienzyme complex, oxoglutarate dehydrogenase like (OGDHL) is involved in the tricarboxylic acid cycle, and frequently downregulated in human carcinoma and suppresses tumor growth. However, little is known about the role of OGDHL in human cancer, especially pancreatic cancer. Our goal is to study the underlying mechanism and define a novel signaling pathway controlled by OGDHL modulating pancreatic cancer progression., Experimental Design: The expression and functional analysis of OGDHL, miR-214, and TWIST1 in human pancreatic cancer tissues, cell lines, and xenograft tumor model were investigated. The correlations between OGDHL and those markers were analyzed., Results: OGDHL was downregulated in human pancreatic cancer and predicted poor prognosis. OGDHL overexpression inhibited migration and invasion of pancreatic cancer cells and suppressed pancreatic cancer tumor growth. OGDHL was shown to be negatively regulated by miR-214. TWIST1 upregulation induced miR-214 expression in pancreatic cancer. OGDHL suppressed TWIST1 expression through promoting ubiquitin-mediated proteasomal degradation of HIF1α and regulating AKT pathways. A combination of OGDHL downregulation and TWIST1 and miR-214 overexpression predicted worse prognosis in patients with pancreatic cancer., Conclusions: We demonstrated the prognostic value of OGDHL, miR-214, and TWIST1 in pancreatic cancer, and elucidated a novel pathway in OGDHL-regulated inhibition of pancreatic cancer tumorigenesis and metastasis. These findings may lead to new targeted therapy for pancreatic cancer through regulating OGDHL, miR-214, and TWIST1., (©2019 American Association for Cancer Research.)