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Abstract Colorectal cancer (CRC) is one of the most common and fatal gastrointestinal cancers worldwide. Considering their diversity, the establishment of new continuous CRC cell lines with clear genetic backgrounds will provide useful tools for exploring molecular mechanisms, screening and evaluating antitumor drugs in CRC studies. Our de novo CRC cell line, PUMC-CRC1 (Peking Union Medical College Colorectal Cancer 1) was derived from a 47-year-old Chinese female patient diagnosed with moderately to poorly differentiated colon adenocarcinoma. Multiple experiments were used for full characterization. The new cell line was epithelial-like and was passaged for more than 40 times, with a population doubling time of 44 h in vitro, detected by cell counts. The cells exhibited complicated chromosomal abnormalities. The tumor formation rate in SCID mice was 100%. The xenograft tumor was adenocarcinoma with poor to moderate differentiation by Haematoxylin and Eosin staining (H&E) sections. Immunohistochemistry (IHC) analysis and next-generation sequencing (NGS) revealed microsatellite stable (MSS), APC (p.T1493fs) inactivation, KRAS (p.G12V) activation, and SMAD4 (p.V506A) mutation. Quality control of the cell line proved mycoplasma negative and identical STR profile with that of the original tissue, and no interspecific or intraspecific cross contamination was detected. In conclusion, PUMC-CRC1 was a newly established and well characterized human colon cancer cell line, which might be a good model for both in vitro and in vivo studies of the mechanism of colon cancer progression and the treatment strategies for MSS CRC.

The tumor immune microenvironment significantly affects tumor progression, metastasis, and clinical therapy. Its basic cell components include tumor-associated endothelial cells, fibroblasts, and macrophages, all of which constitute the tumor stroma and microvascular network. However, the functions of tumor stromal cells have not yet been fully elucidated. The three-dimensional (3D) model created by 3D bioprinting is an efficient way to illustrate cellular interactions in vitro. However, 3D bioprinted model has not been used to explore the effects of stromal cells on cholangiocarcinoma cells. In this study, we fabricated 3D bioprinted models with tumor cells and stromal cells. Compared with cells cultured in two-dimensional (2D) environment, cells in 3D bioprinted models exhibited better proliferation, higher expression of tumor-related genes, and drug resistance. The existence of stromal cells promoted tumor cell activity in 3D models. Our study shows that 3D bioprinting of an immune microenvironment is an effective way to study the effects of stromal cells on cholangiocarcinoma cells.

Purpose: 68Ga-labeled fibroblast activation protein inhibitors, such as [68Ga]Ga-DOTA-FAPI-04 and [68Ga]Ga-DOTA-FAPI-46, have been successfully applied in positron emission tomography imaging of various tumor types. To broaden the PET tracers of different positron nuclides for imaging studies of FAP-dependent diseases, we herein report the radiosynthesis and preclinical evaluation of two 11C-labeled FAP inhibitors, 11C-RJ1101 and 11C-RJ1102. Methods: Two phenolic hydroxyl precursors based on a quinoline amide core coupled with a 2-cyanopyrrolidine moiety were coupled with [11C]CH3I to synthesize 11C-RJ1101 and 11C-RJ1102. In vivo small-animal PET and biological distribution studies of 11C-RJ1101 and 11C-RJ1102 compared to [68Ga]Ga-DOTA-FAPI-04 were conducted in nude mice bearing U87MG tumor xenografts at 30, 60, and 90min, respectively. Results: 11C-RJ1101 and 11C-RJ1102 were synthesized in over 15% radiochemical yields, with specific activities of 67 GBq/μmol and 34 GBq/μmol, respectively, at the end of synthesis and radiochemical purities greater than 99%. In U87MG tumor xenograft PET studies, the three tracers experienced higher specific uptake at the tumor site. However, because of significant differences in metabolism and clearance, [68Ga]Ga-DOTA-FAPI-04 experienced high uptake in the kidney, whereas 11C-RJ1101 and 11C-RJ1102 showed high uptake in the liver and intestine. Biodistribution studies revealed significant hepatobiliary excretion of 11C-RJ1101 and 11C-RJ1102. 11C-RJ1102 showed higher specific tumor uptake in U87MG xenografts (1.71 ± 0.08% injected dose per Gram of tissue [ID/g]) than 11C-RJ1101 (1.34 ± 0.10%ID/g) and [68Ga]Ga-DOTA-FAPI-04 (1.29 ± 0.04%ID/g) after 30 min p. i. In orthotopic glioma models, the uptake values were 0.07 ± 0.03% ([68Ga]Ga-DOTA-FAPI-04) and 0.16 ± 0.03% (11C-RJ1102), respectively. Conclusion: 11C-RJ1101 and 11C-RJ1102 are interesting candidates for translation to the clinic, taking advantage of the shorter half-life and physical imaging properties of C-11.

Yield is an important indicator in evaluating rice planting, and it is the collective result of various factors over multiple growth stages. To achieve a large-scale accurate prediction of rice yield, based on yield estimation models using a single growth stage and conventional spectral transformation methods, this study introduced the continuous wavelet transform algorithm and constructed models under the premise of combined multiple growth stages. In this study, canopy reflectance spectra at four important stages of rice elongation, heading, flowering and milky were selected, and then, a rice yield estimation model was constructed by combining vegetation index, first derivative and wavelet transform based on random forest algorithm or multiple stepwise regression. This study found that the combination of multiple growth stages significantly improved the model accuracy. In addition, after two validations, the optimal model combination for rice yield estimation is first derivative-wavelet transform-vegetation index-random forest model based on four growth stages, with the coefficient of determination (R2) of 0.86, the root mean square error (RMSE) of 35.50 g·m−2 and the mean absolute percentage error (MAPE) of 4.6% for the training set, R2 of 0.85, RMSE of 33.40 g.m−2 and MAPE 4.30% for the validation set 1, and R2 of 0.80, RMSE of 37.40 g·m−2 and MAPE of 4.60% for the validation set 2. The research results demonstrated that the established model could accurately predict rice yield, providing technical support and a foundation for large-scale statistical estimating of rice yield.

Immunosuppressive cells accumulating in the tumor microenvironment constitute a formidable barrier that interferes with current immunotherapeutic approaches. A unifying feature of these tumor-associated immune and vascular endothelial cells appears to be the elevated expression of ectonucleotidase CD39, which in tandem with ecto-5′-nucleotidase CD73, catalyzes the conversion of extracellular ATP into adenosine. We glycoengineered an afucosylated anti-CD39 IgG2c and tested this reagent in mouse melanoma and colorectal tumor models. We identified major biological effects of this approach on cancer growth, associated with depletion of immunosuppressive cells, mediated through enhanced Fcγ receptor–directed (FcγR-directed), antibody-dependent cellular cytotoxicity (ADCC). Furthermore, regulatory/exhausted T cells lost CD39 expression, as a consequence of antibody-mediated trogocytosis. Most strikingly, tumor-associated macrophages and endothelial cells with high CD39 expression were effectively depleted following antibody treatment, thereby blocking angiogenesis. Tumor site–specific cellular modulation and lack of angiogenesis synergized with chemotherapy and anti–PD-L1 immunotherapy in experimental tumor models. We conclude that depleting suppressive cells and targeting tumor vasculature, through administration of afucosylated anti-CD39 antibody and the activation of ADCC, comprises an improved, purinergic system–modulating strategy for cancer therapy.

N6-methyladenosine (m6A) and lncRNAs have been implicated in the development of colon cancer, including tumorigenesis, migration, and invasion. However, the specific effect of m6A regulators on lncRNAs is not clear, and m6A-related lncRNAs may be new prognostic biomarkers and may help direct treatment and medication. We identified 29 prognostic m6A-related lncRNAs and constructed a risk model using 12 lncRNAs. The model was an independent prognostic factor and could accurately predict the prognosis. A stable and robust nomogram that combined the model and pathologic stage was constructed. A total of 2,424 differentially expressed genes (DEGs) were identified based on the model. Functional analysis of the DEGs showed that they were associated with tumor progression, helping investigate the underlying biological functions and signaling pathways of the risk model. In addition, the low-risk group based on the risk model had more sensitivity to afatinib, metformin, and GW.441756, and patients with low risk would more likely respond to immunotherapy. Moreover, patients with higher risk were more sensitive to olaparib, bexarotene, and doxorubicin.

The co-occurrence of multiple primary cancers with hematological malignancies is uncommon, and acute promyelocytic leukemia (APL) with MPC is even rarer, with only a few cases reported in the literature. Herein, we introduce the diagnosis and treatment of 2 cases of MPC complicated with APL in our hospital and review the relevant literature. Both patients were primary solid tumor patients and were treated with surgery and chemotherapy, and had stable disease (SD). However, more than 1 year after the primary tumor was diagnosed, clinical symptoms were found and APL was diagnosed. Both patients received standard remission-induction therapy, but unfortunately died in the short term due to hemorrhagic complications. In conclusion, treatment of hematological neoplasms, especially acute leukemia combined with multiple primary cancers, is challenging. The prognostic factors and survival analysis of MPC patients with combined APL still need further clinical research and analysis.

Background: Coronavirus disease 2019 (COVID-19) has triggered a global public health crisis. Proton pump inhibitors (PPIs) are one of the most commonly prescribed drugs. However, the effect of PPIs on the clinical outcomes of COVID-19 patients remains unclear. Methods: All COVID-19 patients admitted to the Wuhan Huoshenshan Hospital from February 2020 to April 2020 were retrospectively collected. Patients were divided into PPIs and non-PPIs groups. Logistic regression analyses were performed to explore the effects of PPIs on the outcomes of COVID-19 patients, including transfer to intensive care unit, mechanical ventilation, and death. Subgroup analyses were performed according to the presence of upper gastrointestinal symptoms potentially associated with acid and the routes, types, median total dosage, and duration of PPIs. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated. Results: Of the 3024 COVID-19 patients included, 694 and 2330 were in PPIs and non-PPIs groups, respectively. Univariate logistic regression analysis showed that PPIs significantly increased the risk of reaching the composite endpoint in COVID-19 patients (OR = 10.23, 95% CI = 6.90–15.16, p

Abstract Background Dynamic PET with kinetic modeling was reported to be potentially helpful in the assessment of hepatic malignancy. In this study, a kinetic modeling analysis was performed on hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) from dynamic FDG positron emission tomography/computer tomography (PET/CT) scans. Methods A reversible two-tissue compartment model with dual blood input function, which takes into consideration the blood supply from both hepatic artery and portal vein, was used for accurate kinetic modeling of liver dynamic 18F-FDG PET imaging. The blood input functions were directly measured as the mean values over the VOIs on descending aorta and portal vein respectively. And the contribution of hepatic artery to the blood input function was optimization-derived in the process of model fitting. The kinetic model was evaluated using dynamic PET data acquired on 24 patients with identified hepatobiliary malignancy. 38 HCC or ICC identified lesions and 24 healthy liver regions were analyzed. Results Results showed significant differences in kinetic parameters $${K}_{1}-{k}_{4}$$ K 1 - k 4 , blood supplying fraction $${f}_{A}$$ f A , and metabolic rate constant $${K}_{i}$$ K i between malignant lesions and healthy liver tissue. And significant differences were also observed in $${K}_{1}$$ K 1 , $${k}_{3}$$ k 3 , $${f}_{A}$$ f A and $${K}_{i}$$ K i between HCC and ICC lesions. Further investigations of the effect of SUV measurements on the derived kinetic parameters were conducted. And results showed comparable effectiveness of the kinetic modeling using either SUVmean or SUVmax measurements. Conclusions Dynamic 18F-FDG PET imaging with optimization-derived hepatic artery blood supply fraction dual-blood input function kinetic modeling can effectively distinguish malignant lesions from healthy liver tissue, as well as HCC and ICC lesions.

Abstract This paper proposes a data‐driven method of mmWave beam selection in multi‐cell systems to achieve a near‐optimal fast beam allocation with low complexity. In particular, an online learning algorithm based on support vector machine (SVM) equipped with the radial basis function kernel, namely SVM‐based online beam selection (SBOS) algorithm is proposed. The proposed algorithm starts with an adaptive beam selection process for certain traffic pattern that uses an SVM learning model to adaptively refine the beam selection strategy. Specifically, SVM‐based model labels the feedback (the average information rate) from the cellular system, then learns from samples, and makes the scheme space smaller by maximising samples' minimum distances to all labelled samples in the sample space constrained by newly learned boundaries. Then, according to the aggregated data about the traffic patterns and the performance of corresponding beam selection strategy, SBOS algorithm exploits beam selection schemes recorded in the database or explores new schemes for unknown situations, respectively, and how to tune the hyperparameters for the SBOS algorithm is discussed. Furthermore, the extensive simulation results show that the proposed algorithm achieves a better performance versus upper confidence bound and Random methods.

Introduction: Atezolizumab plus bevacizumab significantly improved overall survival (OS) and progression-free survival (PFS) versus sorafenib in patients with unresectable hepatocellular carcinoma (HCC) in IMbrave150. Efficacy and safety data from the Chinese subpopulation are reported. Methods: IMbrave150, a global, randomized, open-label, phase 3 study in patients with systemic treatment-naive unresectable HCC, included an extension phase that enrolled additional patients from mainland China. Patients were randomized (2:1) to receive intravenous atezolizumab 1,200 mg plus bevacizumab 15 mg/kg once every 3 weeks or sorafenib 400 mg twice a day until unacceptable toxicity or loss of clinical benefit. Co-primary endpoints were OS and independent review facility-assessed PFS per Response Evaluation Criteria in Solid Tumors version 1.1 in the intention-to-treat population. Results: Of 194 Chinese patients enrolled from April 16, 2018, to April 8, 2019 (137 in the global study and 57 in the China extension phase), 133 received atezolizumab plus bevacizumab and 61 received sorafenib. At the data cutoff (August 29, 2019), the stratified hazard ratio for OS was 0.44 (95% CI, 0.25–0.76) and for PFS was 0.60 (95% CI, 0.40–0.90). The respective median OS and PFS with atezolizumab plus bevacizumab were not reached (NR; 95% CI, 13.5 months to NR) and 5.7 months (95% CI, 4.2–8.3) versus 11.4 months (95% CI, 6.7 to NR) and 3.2 months (95% CI, 2.6–4.8) with sorafenib. Grade 3–4 adverse events (AEs) occurred in 78 of 132 (59.1%) atezolizumab plus bevacizumab-treated and 27 of 58 (46.6%) sorafenib-treated patients. The most common grade 3–4 AE with atezolizumab plus bevacizumab was hypertension, occurring in 15.2% of patients; however, other high-grade AEs were infrequent. Conclusion: Clinically meaningful improvements in OS and PFS observed with atezolizumab plus bevacizumab versus sorafenib suggest that atezolizumab plus bevacizumab may become a practice-changing treatment for Chinese patients with unresectable HCC.

Abstract Ultra‐dense networking is considered an effective solution to achieve high capacity in 5G networks. However, the densely distributed base stations (BSs) in ultra‐dense networks (UDNs) make the inter‐cell interference much more serious than that in traditional cellular networks. Therefore, it is important to mitigate inter‐cell interference in the UDNs to improve network performance. To tackle this problem, we propose a novel virtual resource mapping algorithm that includes a resource reservation (RR) algorithm and a real‐time resource embedding (RE) algorithm. Specifically, according to the number of services predicted by a dynamic service model, the RR algorithm is proposed to determine the sets of multiplexing BSs in the next time cycle and reserve channel resource required by each BS. Then, to further reduce inter‐cell interference, the real‐time RE algorithm is proposed to allocate the channel resource in real time. Finally, simulation results show that the proposed algorithm has better performance in terms of signal‐to‐interference‐plus‐noise ratio and acceptance ratio, compared to the existing algorithms, such as the frequency reuse channel allocation algorithm and inter‐cell interference coordination algorithm.

Chemical fertilizers are commonly used to meet the nutritional demands of crops and boost their yields. However, their high costs and excessive application in soils increase the cost of production and have negative effects on the soil and environmental health. Vermicompost is an organic amendment that can potentially lessen the dependence on chemical fertilizers, with the additional advantages of sustainable nutrient supply to crops and maintaining soil health. To evaluate the potential of the two diverse vermicompost, the sole and combined applications of these vermicompost with reduced rates of chemical fertilizers were used for tomato cultivation in a field study. The results indicated that vermicompost produced from cattle manure combined with chemical fertilizers was more effective in improving tomato growth, physiology, yield, and nutritional attributes. Compared to the control treatment (NP applied), the combined application of vermicompost and chemical fertilizer significantly improved the root length (21.6%), plant height (167%), SPAD value (13.5%), chlorophyll ‘a’ (96%), chlorophyll ‘b’ (161%), relative water content (16%), membrane stability index (18%), carotenoid (87%), yield (82%), photosynthetic rate (148%), fruit diameter (83%), protein (89%), fat (27.5%), fiber (12%), vitamin C (52%), calcium (54%), magnesium (117%), phosphorus (38%) and potassium (128%). In addition, significant improvements in different soil physicochemical properties were also pragmatic. The results suggest that vermicompost application with reduced doses of chemical fertilizers can be used to improve crop yield and soil physico-chemical properties.

Pipeline steel is a special type of steel used for transporting, for example, oil and natural gas. This study focuses on X80-grade pipeline steel modified with the addition of Nb and Nb-V at different cooling rates (air cooling or quenching) after hot rolling and subjecting it to quenching and tempering heat treatment. Based on multiscale characterization techniques, the effects of microalloying and the cooling rate after hot rolling on the microstructure, precipitation behavior, and strengthening mechanisms were studied. The results showed that the strengths of quenched steels were higher than those of air-cooled steels, and the increase in strength was more pronounced with the addition of Nb-V than with the addition of Nb alone in the steels. Under the same cooling condition, the strengths of Nb-V-added steels were larger than those of Nb-added steels. Additionally, the Nb-V addition promotes the formation of lath structures. The yield stress of the steels, calculated by using measured microstructural parameters following the linear addition of strengthening, is in good agreement with the measured values.

Introduction: Over the past 4 decades, the management of hepatocellular carcinoma (HCC) has changed dramatically. The publications that have had the most significant impact on HCC management have not been quantitatively analyzed. In this article, we analyzed the 100 most influential articles over the past 4 decades using bibliometric citation analysis to characterize the evolution in HCC treatment. Methods: The top-cited publications were identified and analyzed from the Clarivate Analytics Web of Science Core Collection database. Results: The 100 most cited articles were identified with an average of 738 citations (range: 349–6,799). There was an increase in the number of influential articles in the late 1990s, which was paralleled by an increase in reports focused on locoregional treatment of HCC. Most top 100 articles came from the USA (n = 35), followed by Italy (n = 28), mainland China (n = 26), and Japan (n = 24). The surgical management was the most studied topic (n = 33). The Annals of Surgery published the highest number of papers (n = 26) with 13,978 citations. While other 3 topics (surgical management, locoregional treatment, and outcome prediction) declined among publications beginning in the 2000s, there was an emergence of highly cited papers on targeted drugs and immune checkpoint inhibitors with a concomitant increase in the number of publications on systemic therapy. Conclusions: Based on bibliometric analysis of the literature over the last 40 years, a comprehensive analysis of the most historically significant HCC management articles highlighted the key contributions made to the evolution and advancement of this specialist field. The data should provide clinicians and researchers insight into future directions relative to the advancement of HCC management.

Abstract Background Although immunotherapy has revolutionized treatment strategies for some types of cancers, most patients failed to respond or obtain long-term benefit. Tumor-infiltrating CD8+ T lymphocytes are closely related to the treatment outcome and prognosis of patients. Therefore, noninvasive elucidation of both systemic and tumor-infiltrating CD8+ T lymphocytes is of extraordinary significance for patients during cancer immunotherapy. Herein, a panel of 68Ga-labeled Nanobodies were designed and investigated to track human CD8+ T cells in vivo through immuno-positron emission tomography (immunoPET). Results Among the screened Nanobodies, SNA006a showed the highest binding affinity and specificity to both human CD8 protein and CD8+ cells in vitro, with the equilibrium dissociation constant (K D ) of 6.4 × 10−10 M and 4.6 × 10−10 M, respectively. 68Ga-NOTA-SNA006 was obtained with high radiochemical yield and purity, and stayed stable for at least 1 h both in vitro and in vivo. Biodistribution and Micro-PET/CT imaging studies revealed that all tracers specifically concentrated in the CD8+ tumors with low accumulation in CD8− tumors and normal organs except the kidneys, where the tracer was excreted and reabsorbed. Notably, the high uptake of 68Ga-NOTA-SNA006a in CD8+ tumors was rapid and persistent, which reached 24.41 ± 1.00% ID/g at 1.5 h after intravenous injection, resulting in excellent target-to-background ratios (TBRs). More specifically, the tumor-to-muscle, tumor-to-liver, and CD8+ to CD8− tumor was 28.10 ± 3.68, 5.26 ± 0.86, and 19.58 ± 2.70 at 1.5 h, respectively. Furthermore, in the humanized PBMC-NSG and HSC-NPG mouse models, 68Ga-NOTA-SNA006a accumulated in both CD8+ tumors and specific tissues such as liver, spleen and lung where human CD8 antigen was overexpressed or CD8+ T cells located during immunoPET imaging. Conclusions 68Ga-NOTA-SNA006a, a novel Nanobody tracer targeting human CD8 antigen, was developed with high radiochemical purity and high affinity. Compared with other candidates, the long retention time, low background, excellent TBRs of 68Ga-NOTA-SNA006a make it precisely track the human CD8+ T cells in mice models, showing great potential for immunotherapy monitoring and efficacy evaluation.

Abstract Background The study aimed to establish a 68Ga-FAPI-04 kinetic model in hepatic lesions, to determine the potential role of kinetic parameters in the differentiation of hepatocellular carcinoma (HCC) from non-HCC lesions. Material and methods Time activity curves (TACs) were extracted from seven HCC lesions and five non-HCC lesions obtained from 68Ga-FAPI-04 dynamic positron emission tomography (PET) scans of eight patients. Three kinetic models were applied to the TACs, using image-derived hepatic artery and/or portal vein as input functions. The maximum standardized uptake value (SUVmax) was taken for the lesions, the hepatic artery, and for the portal veins—the mean SUV for all healthy regions. The optimum model was chosen after applying the Schwartz information criteria to the TACs, differences in model parameters between HCC, non-HCC lesions, and healthy tissue were evaluated with the ANOVA test. Results A reversible two-tissue compartment model using both the arterial as well as venous input function was most preferred and showed significant differences in the kinetic parameters V ND, V T, and BPND between HCC, non-HCC lesions, and healthy regions (p

Imaging with different spectrums often leads to significant nonlinear differences in the intensity, which brings a great challenge to the automatic matching of multispectral images. Considering that there are often limitations to only using intensity information, this article studies multispectral image matching based on the structure consistency. First, an extended log-Gabor filter is constructed to build phase congruency maps, which encodes the structure information and provides rich and robust features. Then, a nonlinear diffusion-based algorithm is developed to detect the salient feature points on the phase congruency map, which are expected to be illumination and contrast invariant. Finally, the structure descriptors are built according to the orientation of the maximum log-Gabor filter responses, and the image matching is achieved by computing the correspondence. Extensive experiments are carried out on various multispectral image datasets. The results show that the proposed method holds a stable performance over the nonlinear intensity variance across spectrums, and outperforms the comparison methods in terms of the number of correct matches and the matching precision.

Flight line planning is the first step in an aerial photography campaign. Its two key parameters, ground sampling distance (GSD), and overlap should be designed carefully as they will impact subsequent flying workload and even the final mapping accuracy. For a flat terrain region, flight line planning is easy using a traditional method with fixed baseline, flight spacing, and flight altitude. But for a steep terrain region, photo overlap and GSD will change greatly with topography, and thus a flight line planning using the traditional method is not sufficient. This article presents a novel adaptable flight line planning method for frame camera with four application modes. The flight line planning procedure is implemented through rigorous imaging geometry model using digital elevation data, where actual overlap and GSD can be calculated precisely. Using the desired overlap and GSD as constraint conditions, the flight spacing, baseline, and flight altitude can be adjusted adaptively according to ground topography. To assess the effect, a hypothetical test in a rugged terrain region was conducted to compare the project workload, GSD, and overlap of the four modes. The results show that Mode 2, Mode 3, and Mode 4 can realize better overlap with lower workload than the traditional method Mode 1. Mode 3 and Mode 4 have better GSD distribution than Mode 1 and Mode 2. The Mode 3 method was also validated in an actual project, showing a favorable performance in final reality 3D model result.

Power Internet of Things (PIoT) is a promising solution to meet the increasing electricity demand of modern cities, but real-time processing and analysis of huge data collected by the devices is challengeable due to limited computing capability of devices and long distance from the cloud center. In this paper, we consider the edge computing assisted PIoT where the computing tasks of the devices can be either processed locally by the devices, or offloaded to edge servers. Aiming to maximize the long-term system utility which is defined as a weighted sum of reduction in latency and energy consumption, we propose a novel task offloading algorithm based on deep reinforcement learning, which jointly optimizes task scheduling, transmit power of the PIoT devices, and computing resource allocation of the edge servers. Specifically, the task execution on each edge server is modeled as a queuing system, in which the current queue state may affect the waiting time for the next tasks. The transmit power and computing resource allocation is first optimized, respectively, and then a deep Q-learning algorithm is adopted to make task scheduling decisions. Numerical results show that the proposed method can improve the system utility.

Abstract DNA repair gene aberrations (GAs) occur in several cancers, may be prognostic and are actionable. We investigated the frequency of DNA repair GAs in gallbladder cancer (GBC), association with tumor mutational burden (TMB), microsatellite instability (MSI), programmed cell death protein 1 (PD-1), and its ligand (PD-L1) expression. Comprehensive genomic profiling (CGP) of 760 GBC was performed. We investigated GAs in 19 DNA repair genes including direct DNA repair genes (ATM, ATR, BRCA1, BRCA2, FANCA, FANCD2, MLH1, MSH2, MSH6, PALB2, POLD1, POLE, PRKDC, and RAD50) and caretaker genes (BAP1, CDK12, MLL3, TP53, and BLM) and classified patients into 3 groups based on TMB level: low (

Ti3C2Tx MXenes are normally fabricated by removal of main group element from the corresponding transition metal carbides, and they have been actively studied due to their superior energy storage performance. However, the low efficiency in removal of main group element (named as chemical etching) has significantly limited the application of MXene or MXene-related materials. Herein, we demonstrated an ultrasound-assisted approach to synthesize Ti3C2Tx MXene material by using Ti3AlC2 as the precursor. The experimental results indicate that the efficiency of chemical etching of Ti3AlC2 was dramatically promoted by ultrasound. The etching time was greatly shortened to 8 h while typically 24 h is sufficient in dilute hydrofluoric acid. Particularly, the high etching efficiency was achieved by using 2% hydrofluoric acid under the aid of ultrasound, which is lower in concentration than those reported in the previous literature. The specific capacitance of the 8 h sonicated sample is 155F/g, which is much higher than that of the un-sonicated sample prepared under the same experimental conditions. Additionally, the specific capacitance retention of the prepared 8 h sonicated sample was 97.5% after 20,000 cycles of charging/discharging, exhibiting an outstanding energy storage stability compared with the materials reported in previous literatures. It was proposed that removal of AlF3 from the surface of the etched particles was significantly promoted and the hydrogen bonds between the terminations of two different adjacent layers were broken by the acoustic cavitation effect of ultrasound.

IntroductionLenvatinib, a multiple receptor tyrosine kinase inhibitors that target vascular endothelial growth factor receptors and fibroblast growth factor receptors, recently demonstrated a treatment effect in various tumors. This study evaluated the efficacy and safety of lenvatinib for patients with biliary tract cancers (BTCs) who had received ≥1 line of prior systemic anti-BTC therapy.MethodsThis open-label, single-arm study included adult (≥18 years) patients with histologically confirmed BTC. Efficacy and safety were evaluated based on the Response Evaluation Criteria in Solid Tumors RECIST Version 1.1 (RECIST 1.1) and the National Cancer Institute Common Terminology Criteria for Adverse Events (CTCAE version 4.0). Changes in tumor biomarkers throughout the treatment period were recorded.Results41 patients received lenvatinib treatment. The ORR was 12% (95% CI: 1.7–22.7), with a median PFS of 3.8 months (95% CI: 1.3–6.3) and an OS of 11.4 months (95% CI: 6.6–16.2). Thirty-nine (95.1%) patients experienced ≥1 treatment-related adverse event. Decreasing carbohydrate antigen 19-9 (CA19-9) level predicted tumor size reduction in intrahepatic cholangiocarcinoma with a sensitivity of 77.7% and a specificity of 73.9%.ConclusionsLenvatinib which was individualized based on the patient’s weight has promising clinical activity against advanced BTC and had an acceptable safety profile. Additionally, serum biomarkers and gene sequencing may hold the potential to guide our treatment.

The Bronze Age in China is characterized by the appearance of bronze ritual vessels, such as gui and he pitchers and jue cups, which were symbols of high social status and likely used in ritual feasting events. Their forms imitate similar ceramic vessels made of white clay. This transformation of such ceramic vessels into their bronze counterparts took place at the Erlitou site in the Yiluo basin, North China (ca. 1,800–1,500 BC). Such white pottery types are commonly regarded as alcohol-related vessels, but there is a lack of scientific analysis of organic remains on vessels’ interior surfaces to understand their functions. In this study, we analyzed microfossil remains on 16 ceramic vessels unearthed from Erlitou and discovered direct evidence of the production and consumption of fermented beverages that were prepared using qu starter as a saccharification agent. Dakouzun wide-orifice vats may have been used for fermentation, likely in semi-solid-state fermentation conditions; narrow-orifice jars zun for storage; gui and he pitchers for heating and/or pouring the beverages; and jue cups for drinking. Monascus mold and herbs were probably used to make qu starter. Fermentation ingredients were primarily rice and wheat, sometimes mixed with broomcorn millet, Job’s tears, roots of snake gourd, among other plants. Rice and wheat were minor crops in the region, probably cultivated for special uses and received by the Erlitou elites as tributary items for making alcoholic beverages. This research demonstrates that Erlitou feasting activities involved serving luxury drinks with prestige utensils in socially exclusive spaces, which emphasized social status, wealth, and power. The development of such drinking materiality and social values coincided with increased social differentiation at the time of early state formation.

In order to solve the problem that the data packets were out of order at the receiving end in the multipath transmission,which greatly reduced the transmission performance,an optimization algorithm was proposed for multipath transmission path scheduling based on forward delay in the vehicle heterogeneous network.The main idea of the proposed algorithm was to schedule data packets through a concurrent path according to the forward delay and throughput difference estimated by the sender.A simulation experiment was carried out on NS-3.The simulation results show that compared with the previous algorithm,the proposed algorithm has better performance than other algorithms in reorder-buffer-occupancy density (RBD) and throughput.The problem of out-of-order data packets at the receiving end is significantly reduced,and the total system throughput and network utilization have been improved.

For heat-transfer-controlled or diffusion-controlled phase transformation simulations, the movement of the interface between different phases needs to be determined, which is commonly called the Stefan problem. Various numerical methods have been developed for this and the movement of the interface is conventionally calculated by a flux balance equation, which is usually called the Stefan condition equation. However, mass conservation errors have been reported in the literature for some of the numerical methods. In this research, a control volume method based interface movement equation was proposed to achieve mass conservation during calculation. The obtained maximum relative mass conservation error for the new interface movement equation is less than 10−13 and the total mass is constant to the machine precision. This is much smaller than that of the Stefan condition discrete equation, which is in the order of 10−2. It was also found that the mass conservation accuracy of the numerical methods partly depends on the choice of the interface movement equation. The mass change term in the Stefan condition discrete equation is only a part of the whole mass change during interface movement, leading to the mass non-conservation found in the literature. In contrast, the piecewise integration treatment in the proposed interface movement equation in this research gives a more accurate mass change description during the interface movement. The correctness of the proposed interface movement equation was also proved by a comparison with the analytical solutions.

In order to achieve the best balance between latency,computational rate and energy consumption,for a edge access network of IoV,a distribution offloading algorithm based on deep Q network (DQN) was considered.Firstly,these tasks of different vehicles were prioritized according to the analytic hierarchy process (AHP),so as to give different weights to the task processing rate to establish a relationship model.Secondly,by introducing edge computing based on DQN,the task offloading model was established by making weighted sum of task processing rate as optimization goal,which realized the long-term utility of strategies for offloading decisions.The performance evaluation results show that,compared with the Q-learning algorithm,the average task processing delay of the proposed method can effectively improve the task offload efficiency.

Abstract Background Serum lipids were reported to be the prognostic factors of various cancers, but their prognostic value in malignant biliary tumor (MBT) patients remains unclear. Thus we aim to assess and compare prognosis values of different serum lipids, and construct a novel prognostic nomogram based on serum lipids. Methods Patients with a confirmed diagnosis of MBT at our institute from 2003 to 2017 were retrospectively reviewed. Prognosis-related factors were identified via univariate and multivariate Cox regression analyses. Then the novel prognostic nomogram and a 3-tier staging system were constructed based on these factors and further compared to the TNM staging system. Results A total of 368 patients were included in this study. Seven optimal survival-related factors—TC/HDL > 10.08, apolipoprotein B > 0.9 g/L, lipoprotein> 72 mg/L, lymph node metastasis, radical cure, CA199 > 37 U/mL, and tumor differentiation —were included to construct the prognostic nomogram. The C-indexes in training and validation sets were 0.738 and 0.721, respectively. Besides, ROC curves, calibration plots, and decision curve analysis all suggested favorable discrimination and predictive ability. The nomogram also performed better predictive ability than the TNM system and nomogram without lipid parameters. And the staging system based on nomogram also presented better discriminative ability than TNM system (P

Abstract Background This study aimed to investigate the incidence of surgical site infection (SSI) in elective foot and ankle surgeries and identify the associated risk factors. Methods This was designed as a retrospective study, including patients who underwent elective surgery of foot and ankle between July 2015 and June 2018. Data on demographics, comorbidities, and perioperative parameters were collected from the medical records, the laboratory report, the operation report, and the outpatient follow-up registration database. SSI was defined in accordance with the Center for Disease Control criteria. Univariate and multivariate logistic regression analyses were used to identify the independent risk factors for SSI. Results A total of 1201 patients undergoing 1259 elective foot/ankle surgeries were included, of whom 26 (2.1%) had an SSI, representing an incidence rate of 1.3% for superficial SSI and 0.8% for deep SSI, respectively. The results for organism culture showed Pseudomonas aeruginosa in 7 cases, methicillin-resistant Staphylococcus aureus (MRSA) in 6, methicillin-susceptible Staphylococcus aureus (MSSA) in 5, methicillin-resistant coagulase-negative Staphylococci (MRCNS) in 2, Escherichia coli in 2, and Proteus mirabilis in 1 case. Five factors were identified to be independently associated with SSI, including prolonged preoperative stay (OR, 1.21; 95% CI, 1.09 to 1.30), allograft or bone substitute (OR, 3.76; 95% CI, 1.51 to 5.30), elevated FBG level (OR, 1.17; 95% CI, 1.04 to 1.26), lower ALB level (OR, 2.33; 95% CI, 1.19 to 3.05), and abnormal NEUT count (OR, 1.72; 95% CI, 1.27 to 2.12). Conclusions SSI following elective foot and ankle surgeries is low, but relatively high in forefoot surgeries, requiring particular attention in clinical practice. Although most not modifiable, these identified factors aid in risk assessment of SSI and accordingly stratifying patients and therefore should be kept in mind.

Carbon is an essential element in steel, but there are still discrepancies regarding its effect on steel hot deformation behaviours. In this research, isothermal compression tests were carried out for a low-carbon (0.05 C) and a medium-carbon (0.38 C) vanadium microalloyed steel with deformation temperatures of 900−1050 °C and strain rates of 0.01−30 s−1. It was found that carbon causes a softening effect at low strain rates (0.01−1.0 s−1), while a hardening effect at high strain rates (10.0−30 s−1). Through constitutive analysis, the hot deformation activation energy for 0.05 C steel is 305.9 kJ/mol in the whole strain rate range, while for 0.38 C steel, the activation energy is 292.3 kJ/mol in the low strain rate range (0.01−1 s−1) and 475.0 kJ/mol in the high strain rate range (10−30 s−1). It was proposed that the addition of carbon decreases the deformation activation energy at low strain rates (0.01−1 s−1), due to its positive influence on the self-diffusion coefficient of iron, which increases the rates of dislocation climb and recovery. On the other hand, carbon lowers the stacking fault energy of austenite, which could make partial dislocation collapse more difficult than dislocation climb and thus becomes the rate-controlling mechanism for 0.38 C steel at high strain rates (10−30 s−1). This gives rise to the higher activation energy and work hardening rate of 0.38C steel at high strain rates. Comparing the power-dissipation-efficiency maps, two peak domains were found in those of 0.38 C steel, while only one peak domain exists in those of 0.05 C steel.

In order to accurately evaluate the autonomous communication and networking capability of these unmanned system which was instructive to the intelligent collaboration of UAV (unmanned aerial vehicle) system,the research of the UAV system which was adapted to the complex environment with countermeasure possibilities was focused on.The autonomous communication and networking capability of UAV system and their relationship from multiple perspectives was analyzed and modeled,including self-adaptation,self-decision,man-UAV interaction,cyber-physical integration and evolution,and an example was provided to illustrate the detailed evaluation process.The example results show that the proposed method comprehensively consider all the key aspects of the performance evaluation,which can be used to quantitatively evaluate the autonomous communication and networking capability of different UAVs or other unmanned systems.

40CrNi steel is a low alloy steel with medium hardenability and has been widely used in the manufacturing of crankshafts, wind turbine forgings, etc. As forging is usually involved in the manufacturing of these components, optimization of the hot deformation process of 40CrNi steel is quite critical. Towards this, the prediction of flow stress and the determination of optimal processing parameter windows are of great importance. In this research, isothermal uniaxial hot compression tests were carried out for 40CrNi steel with true strain rates of 0.01, 0.1, 1, 10 and 30 s−1 and temperatures of 850–1200 °C. Both the strain compensated hyperbolic sine constitutive equation and the modified Johnson-Cook model were adopted to predict the flow stress curves, with average absolute relative errors of 0.034 and 0.061, respectively. Processing maps of the tested steel were constructed to determine the optimal deformation parameter windows, and the characteristics of the prior austenite microstructure generally correspond very well to the processing map established. Furthermore, different processing map construction methods were compared and it was found that power-dissipation efficiency maps strongly rely on the σ- ε˙ relationship. Assuming a certain type of constitutive equations leads to monotonic efficiency value patterns. Calculation methods based on experimental results are helpful to reflect the meaningful information carried by the experimental σ- ε˙ relationships.

Vehicular networks are regarded as an effective solution for the traffic management and road safety. In this paper, the performance of the vehicular networks is investigated under Nakagami-m fading channels. The vehicular communication is considered to reuse the same time-frequency with another vehicular communication link, so that both interference and noise produce an effect on each vehicle and infrastructure. Firstly, we derive the closed-form expressions for the outage probability of vehicular links and particularly examine two special cases, that is, high SNR case and weak interference case. For both cases, approximate expressions for outage probability are provided in closed form. Then, we derive lower and upper bounds of ergoidic achievable rate, which are evident to be sufficiently tight to the Monte-Carlo simulated results. Based on these results, we further analyze the high SNR and weak interference scenarios and the asymptotic expressions of ergoidic achievable rate are also presented. All the analytical results are applicable for arbitrary locations, transmit power, as well as channel parameters. Finally, we propose the power optimization which aims at maximizing the ergodic achievable rate and guaranteeing the outage performance. Numerical results validate our analytical results via Monte Carlo simulations.

In this paper, a face spoofing detection method called the Fully Convolutional Network with Domain Adaptation and Lossless Size Adaptation (FCN-DA-LSA) is proposed. As its name suggests, the FCN-DA-LSA includes a lossless size adaptation preprocessor followed by an FCN based pixel-level classifier embedded with a domain adaptation layer. The FCN local classifier makes full use of the basic properties of face spoof distortion namely ubiquitous and repetitive. The domain adaptation (DA) layer improves generalization across different domains. The lossless size adaptation (LSA) preserves the high-frequent spoof clues caused by the face recapture process. The ablation study shows that both DA and the LSA are necessary for high-accuracy face spoofing detection. The FCN-LSA obtains competitive performance among the state-of-the-art methods. With the help of small-sample external data in the target domain (2/50, 2/50, and 1/20 subjects for CASIA-FASD, Replay-Attack, and OULU-NPU respectively), the FCN-DA-LSA further improves the performance and outperforms the existing methods.

Inkjet printing-based 2D materials for flexible electronics have aroused much interest due to their highly low-cost customization and manufacturing resolution. However, there is a lack of investigation and essential understanding of the surface adhesion affected by the printing parameters at the atomic scale. Herein, we conducted a systematic molecular dynamics simulation investigating the inkjet printing of graphitic inks on polyimide substrates under various conditions. Simulations under different temperatures, inkjet velocities, and mechanical loadings such as pressure and deformation are performed. The results show that the best adhesion is achieved in the plasma-modified polyimide/graphene-oxide (mPI/GO) interfacial system (the interaction energy (Ein) between mPI and GO is ca. 1.2 times than with graphene). The adhesion strength decreases with increasing temperature, and higher inkjet velocities lead to both larger impact force as well as interfacial fluctuation, while the latter may result in greater interfacial instability. When loaded with pressure, the adhesion strength reaches a threshold without further improvement as continuing compacting of polymer slabs can hardly be achieved. The detachment of the interfaces was also explored and mPI/GO shows better resistance against delamination. Hopefully, our simulation study paves the way for future inkjet printing-based manufacturing of graphene-based flexible electronics.

Background: Patients with coronavirus disease 2019 (COVID-19) can present with gastrointestinal (GI) symptoms. However, the prevalence of GI symptoms and their association with outcomes remain controversial in COVID-19 patients.Methods: All COVID-19 patients consecutively admitted to the Wuhan Huoshenshan hospital from February 2020 to April 2020 were collected. Disease severity and outcomes were compared between COVID-19 patients with and without GI symptoms. Logistic regression analyses were performed to evaluate the association of GI symptoms with the composite endpoint and death in COVID-19 patients. A composite endpoint was defined as transfer to intensive care unit, requirement of mechanical ventilation, and death. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated.Results: Overall, 2,552 COVID-19 patients were included. The prevalence of GI symptoms was 21.0% (537/2,552). Diarrhea (8.9%, 226/2,552) was the most common GI symptom. Patients with GI symptoms had significantly higher proportions of severe COVID-19 and worse outcomes than those without. Univariate logistic regression analyses demonstrated that GI symptoms were significantly associated with the composite endpoint (OR = 2.426, 95% CI = 1.608–3.661; P < 0.001) and death (OR = 2.137, 95% CI = 1.209–3.778; P = 0.009). After adjusting for age, sex, and severe/critical COVID-19, GI symptoms were still independently associated with the composite endpoint (OR = 2.029, 95% CI = 1.294–3.182; P = 0.002), but not death (OR = 1.726, 95% CI = 0.946–3.150; P = 0.075). According to the type of GI symptoms, GI bleeding was an independent predictor of the composite endpoint (OR = 8.416, 95% CI = 3.465–20.438, P < 0.001) and death (OR = 6.640, 95% CI = 2.567–17.179, P < 0.001), but not other GI symptoms (i.e., diarrhea, abdominal discomfort, nausea and/or vomiting, constipation, acid reflux and/or heartburn, or abdominal pain).Conclusion: GI symptoms are common in COVID-19 patients and may be associated with their worse outcomes. Notably, such a negative impact of GI symptoms on the outcomes should be attributed to GI bleeding.

In this paper, a blockchain-enabled energy trading method is proposed to deal with the inefficiency and security issues in energy trading for electric vehicles in smart grids. It includes the design of a smart contract and the excitation mechanism of energy sharing. The credit points of each vehicle as a node are considered in the design of the smart contract, which is used to supervise the process of energy trading. A strategy to estimate the credit points of each node and describe the excitation mechanism is illustrated. The connection between the credit points and the probability that a node would be accepted for energy trading has been established. To control the energy trading access, a double auction method is used to choose the part of the nodes participating in energy trading. Only selected nodes with winning bids can supply or request energy from the blockchain-based platform. Then it reaches the conclusion that the higher the credit points they have, the more trading initiative they would have during the energy transaction and transmission. The smart contract design and the excitation mechanism proposed in this paper would reward the vehicles that perform well and punish the beguiling vehicles for regulating the trading process.

Radioiodination of oligonucleotides provides an extra modality for nucleic acid-based theranostics with potential applications. Herein, we report the design and synthesis of a phosphoramidite embedded with a phenolic moiety and demonstrate that oligonucleotides can be readily functionalized with phenol as a precursor by general DNA synthesis. It was identified that the introduction of the precursor does not block the specificity of an aptamer, and the radioiodination is applicable to both DNA and RNA oligonucleotides in a site-specific approach with a commercial kit.

Technological advancements in recent decades have greatly transformed the field of material chemistry. Juxtaposing the accentuating energy demand with the pollution associated, urgent measures are required to ensure energy maximization, while reducing the extended experimental time cycle involved in energy production. In lieu of this, the prominence of catalysts in chemical reactions, particularly energy related reactions cannot be undermined, and thus it is critical to discover and design catalyst, towards the optimization of chemical processes and generation of sustainable energy. Most recently, artificial intelligence (AI) has been incorporated into several fields, particularly in advancing catalytic processes. The integration of intensive data set, machine learning models and robotics, provides a very powerful tool in modifying material synthesis and optimization by generating multifarious dataset amenable with machine learning techniques. The employment of robots automates the process of dataset and machine learning models integration in screening intermetallic surfaces of catalyst, with extreme accuracy and swiftness comparable to a number of human researchers. Although, the utilization of robots in catalyst discovery is still in its infancy, in this review we summarize current sway of artificial intelligence in catalyst discovery, briefly describe the application of databases, machine learning models and robots in this field, with emphasis on the consolidation of these monomeric units into a tripartite flow process. We point out current trends of machine learning and hybrid models of first principle calculations (DFT) for generating dataset, which is integrable into autonomous flow process of catalyst discovery. Also, we discuss catalyst discovery for renewable energy related reactions using this tripartite flow process with predetermined descriptors.

Background: The COVID-19 has grown into a global pandemic. This study investigated the public psychosocial and behavioral responses through different time periods of the pandemic, and assessed whether these changes are different in age, gender, and region.Methods: A three-phase survey was conducted through the DaDui Social Q&A Software for COVID-19. A total of 13,214 effective responses of COVID-19 were collected. Statistical analysis was performed based on their basic information and psychosocial responses.Results: The degree of attention, understanding, and cooperation with preventive and control measures of the disease increased and then decreased. The panic level gradually increased with the epidemic process. The degree of satisfaction with management measures and of confidence in defeating COVID-19 increased throughout the survey. Compared with residents in other areas, respondents from the COVID-19 epicenter (Wuhan) reported a higher degree of self-protection during the outbreak and a significantly lower degree of satisfaction with respect to government prevention and control measures during all phases. Shortages of medical supplies and low testing capacity were reported as the biggest shortcoming in the prevention and control strategies during COVID-19, and an abundance of disorderly and inaccurate information from different sources was the primary cause of panic.Conclusions and Relevance: Major public health events elicit psychosocial and behavioral changes that reflect the different phases of the biologic curve. Sufficient medical supplies and improved organization and accurate information during epidemics may reduce panic and improve compliance with requested changes in behavior. We need to recognize this natural phenomenon and our public policy preparedness should attempt to move the social/psychological curve to the left in order to minimize and flatten the biologic curve.

BackgroundHepatocellular carcinoma (HCC) has a high risk of recurrence after surgical resection, particularly among patients with multifocal HCC. Genomic heterogeneity contributes to the early recurrence. Few studies focus on targeted next-generation sequencing (tNGS) to depict mutational footprints of heterogeneous multifocal HCC.MethodsWe conducted tNGS with an ultra-deep depth on 31 spatially distinct regions from 11 resected multifocal HCC samples. Matched preoperative peripheral circulating-free DNA (cfDNA) were simultaneously collected. Genomic alterations were identified and compared to depict the heterogeneity of multifocal HCC.ResultsWidespread intertumoral heterogeneity of driver mutations was observed in different subfoci of multifocal HCC. The identified somatic mutations were defined as truncal drivers or branchy drivers according to the phylogenetic reconstruction. TP53 and TERT were the most commonly altered truncal drivers in multifocal HCC, while the most frequently mutated branchy driver was TSC2. HCC patients with a higher level of intertumoral heterogeneity, defined by the ratio of truncal drivers less than 50%, had a shorter RFS after surgical resection (HR=0.17, p=0.028). Genome profiling of cfDNA could effectively capture tumor-derived driver mutations, suggesting cfDNA was a non-invasive strategy to gain insights of genomic alterations in patients with resected multifocal HCC.ConclusionsTruncal mutations and the level of genomic heterogeneity could be identified by tNGS panel in patients with resected multifocal HCC. cfDNA could serve as a non-invasive and real-time auxiliary method to decipher the intertumoral heterogeneity and identify oncodrivers of multifocal HCC.

Most cases of hepatocellular carcinoma (HCC) are already advanced at the time of diagnosis, which limits treatment options. Challenges in early‐stage diagnosis may be due to the genetic complexity of HCC. Gene fusion plays a critical function in tumorigenesis and cancer progression in multiple cancers, yet the identities of fusion genes as potential diagnostic markers in HCC have not been investigated. Here, we employed STAR‐Fusion and identified 43 recurrent fusion events in our own and four public RNA‐seq datasets. We identified 2354 different gene fusions in two hepatitis B virus (HBV)‐HCC patients. Validation analysis against the four RNA‐seq datasets revealed that only 1.8% (43/2354) were recurrent fusions. Comparison with the four fusion databases demonstrated that 19 recurrent fusions were not previously annotated to diseases and three were annotated as disease‐related fusion events. Finally, we validated six of the novel fusion events, including RP11‐476K15.1‐CTD‐2015H3.2, by RT‐PCR and Sanger sequencing of 14 pairs of HBV‐related HCC samples. In summary, our study provides new insights into gene fusions in HCC and may contribute to the development of anti‐HCC therapy.

Abstract Gastrointestinal (GI) malignant neoplasms have a high global incidence and treatment prospects for patients with advanced GI tumors are dismal. PD-1/PD-L1 inhibitors emerged as a frontline treatment for several types of cancer. However, the shortcomings of PD-1/PD-L1 inhibitors have been observed, including low objective response rates and acquired tumor resistance, especially in patients receiving PD-1/PD-L1 inhibitors as a single treatment. Accumulating evidence from clinical trials increasingly suggests that combined immunotherapies enhance therapeutic responses in patients with malignances, especially for GI tumors which have a complex matrix, and significant molecular and immunological differences. Preclinical and clinical studies suggest there are advantages to combined immunological regimens, which represents the next logical step in this field, although further research is necessary. This literature review explores the current limitations of monotherapies, before critically discussing the rationale behind combination regimens. Then, we provide a summary of the clinical applications for gastrointestinal cancers.

Abstract Background Long noncoding RNAs (lncRNAs) can act as microRNA (miRNA) sponges to regulate protein-coding gene expression; therefore, lncRNAs are considered a major part of the competitive endogenous RNA (ceRNA) network and have attracted growing attention. The present study explored the regulatory mechanisms and functional roles of lncRNAs as ceRNAs in hepatocellular carcinoma (HCC) and their potential impact on HCC patient prognosis. Methods In this study, we systematically studied the expression profiles and prognostic value of lncRNA, miRNA, and mRNA from a total of 838 HCC patients from five HCC cohorts (TCGA, GSE54236, GSE76427, GSE64041 and GSE14520). The TCGA, GSE54236 and GSE76427 HCC cohorts were utilized to establish a prognosis-related network of dysregulated ceRNAs by bioinformatics methods. The GSE64041 and GSE14520 HCC cohorts were utilized to verify the expression of candidate genes. Results In total, 721 lncRNAs, 73 miRNAs, and 1563 mRNAs were aberrantly expressed in HCC samples. A ceRNA network including 26 lncRNAs, four miRNAs, and six mRNAs specific to HCC was established. The survival analysis showed that four lncRNAs (MYCNOS, DLX6-AS1, LINC00221, and CRNDE) and two mRNAs (CCNB1 and SHCBP1) were prognostic biomarkers for patients with HCC in both the TCGA and GEO databases. Conclusion The proposed ceRNA network may help elucidate the regulatory mechanism by which lncRNAs function as ceRNAs and contribute to the pathogenesis of HCC. Importantly, the candidate lncRNAs, miRNAs, and mRNAs involved in the ceRNA network can be further evaluated as potential therapeutic targets and prognostic biomarkers for HCC.

Background: TP53 mutation is the most common mutation in hepatocellular carcinoma (HCC), and it affects the progression and prognosis of HCC. We investigated how TP53 mutation regulates the HCC immunophenotype and thus affects the prognosis of HCC. Methods: We investigated TP53 mutation status and RNA expression in different populations and platforms and developed an immune prognostic model (IPM) based on immune-related genes that were differentially expressed between TP53WT and TP53MUT HCC samples. Then, the influence of the IPM on the immune microenvironment in HCC was comprehensively analysed. Findings: TP53 mutation resulted in the downregulation of the immune response in HCC. Thirty-seven of the 312 immune response-related genes were differentially expressed based on TP53 mutation status. An IPM was established and validated based on 865 patients with HCC to differentiate patients with a low or high risk of poor survival. A nomogram was also established for clinical application. Functional enrichment analysis showed that the humoral immune response and immune system diseases pathway represented the major function and pathway, respectively, related to the IPM genes. Moreover, we found that the patients in the high-risk group had higher fractions of T cells follicular helper, T cells regulatory (Tregs) and macrophages M0 and presented higher expression of CTLA-4, PD-1 and TIM-3 than the low-risk group. Interpretation: TP53 mutation is strongly related to the immune microenvironment in HCC. Our IPM, which is sensitive to TP53 mutation status, may have important implications for identifying subgroups of HCC patients with low or high risk of unfavourable survival. Fund: This work was supported by the International Science and Technology Cooperation Projects (2016YFE0107100), the Capital Special Research Project for Health Development (2014-2-4012), the Beijing Natural Science Foundation (L172055 and 7192158), the National Ten Thousand Talent Program, the Fundamental Research Funds for the Central Universities (3332018032), and the CAMS Innovation Fund for Medical Science (CIFMS) (2017-I2M-4-003 and 2018-I2M-3-001). Keywords: TP53, Mutation, Immune prognostic model, Immune profile, Hepatocellular carcinoma

The trend of energy transformation is to integrate smart grid into comprehensive energy.The research method is to establish the framework of energy information,physics and social system research.The active support of power transformation is the guarantee of the success of energy transformation.The proposed scheme emphasized the importance of social factors in practical engineering and research.As a new research methodology,it was compatible with mixed simulation of data,model and behavior.The widely used method in engineering was extended to economics and sociology,and the decision-making method based on subjective experience was made more scientific.In addition,in the definition of the Internet of things,the idea of removing the limitations of the Internet was proposed,and a unified framework was used to reflect the impact of the combination of the Internet/private network and other technologies.

Detecting Alzheimer’s disease from blood samples is challenging because amyloid β blood levels are lower than the ELISA detection limit. Here the authors capture amyloid β bound to circulating exosomes on a plasmonic nanosensor, followed by enzymatic amplification to improve detection sensitivity.