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Objective: The aim of this study was to elucidate the effects of fermented hawthorn extract on high-fat diet (HFD)-induced non-alcoholic fatty liver disease (NAFLD) in rats, and explore the possible underlying mechanisms. Methods: A total of 42 male adult Sprague-Dawley rats were randomly divided into five groups: normal control group (given a normal feed diet and distilled water by gavage), NAFLD model (given HFD and distilled water by gavage), low-, medium-, and high-dose fermented hawthorn extract treatment groups (given HFD and different doses of fermented hawthorn extract by gavage). After 12 weeks of gavage administration, changes in body weight, liver/body weight ratio, serum liver enzymes, as well as triglyceride (TG) content and oxidative stress levels in rat liver tissueswere detected. Histological evaluation was performed to observe the degree of fat accumulation (steatosis). qRT-PCR and western blotting were performed to detect the mRNA and protein expression of cytochrome P4502E1 (CYP2E1, a key enzyme associated with lipid peroxidation), and lipogenic factors (sterol regulatory element-binding protein 1c (SREBP-1c) and fatty acid synthase (FAS)) in rat liver tissues. Results: Fermented hawthorn extract significantly reduced the body weight, decreased the levels of liver enzymes, improved hepatic steatosis, and exhibited obvious antioxidant effects. Fermented hawthorn extract also significantly down-regulated the mRNA and protein expression levels of CYP2E1, SREBP-1c and FAS. Conclusion: Our findings suggested that fermented hawthorn extract can markedly reduce body weight, ameliorate HFD-induced NAFLD in rats, and exhibits significant antioxidant effects. Its underlying mechanism may depend on the inhibition of CYP2E1, SREBP-1c, and FAS expression.

ObjectiveDespite several observational studies attempting to investigate the potential association between type 1 diabetes mellitus (T1DM) and the risk of digestive cancers, the results remain controversial. The purpose of this study is to examine whether there is a causal relationship between T1DM and the risk of digestive cancers.MethodsWe conducted a Mendelian randomisation (MR) study to systematically investigate the effect of T1DM on six most prevalent types of digestive cancers (oesophageal cancer, stomach cancer, hepatocellular carcinoma, biliary tract cancer, pancreatic cancer, and colorectal cancer). A total of 1,588,872 individuals were enrolled in this analysis, with 372,756 being the highest number for oesophageal cancer and 3,835 being the lowest for pancreatic cancer. Multiple MR methods were performed to evaluate the causal association of T1DM with the risk of six site-specific cancers using genome-wide association study summary data. Sensitivity analyses were also conducted to assess the robustness of the observed associations.ResultsWe selected 35 single nucleotide polymorphisms associated with T1DM as instrumental variables. Our findings indicate no significant effect of T1DM on the overall risk of oesophageal cancer (OR= 0.99992, 95% CI: 0.99979-1.00006, P= 0.2866), stomach cancer (OR=0.9298,95% CI: 0.92065-1.09466, P= 0.9298), hepatocellular carcinoma (OR= 0.99994,95% CI: 0.99987-1.00001, P= 0.1125), biliary tract cancer (OR=0.97348,95% CI: 0.8079-1.1729, P= 0.7775)), or pancreatic cancer (OR =1.01258, 95% CI: 0.96243-1.06533, P= 0.6294). However, we observed a causal association between T1DM and colorectal cancer (OR=1.000, 95% CI: 1.00045-1.0012, P

Summary: Background: Bone metastasis significantly impact the prognosis of non-small cell lung cancer (NSCLC) patients, reducing their quality of life and shortening their survival. Currently, there are no effective tools for the diagnosis and risk assessment of early bone metastasis in NSCLC patients. This study employed machine learning to analyze serum indicators that are closely associated with bone metastasis, aiming to construct a model for the timely detection and prognostic evaluation of bone metastasis in NSCLC patients. Methods: The derivation cohort consisted of 664 individuals with stage IV NSCLC, diagnosed between 2015 and 2018. The variables considered in this study included age, sex, and 18 specific serum indicators that have been linked to the occurrence of bone metastasis in NSCLC. Variable selection used multivariate logistic regression analysis and Lasso regression analysis. Six machine learning methods were utilized to develop a bone metastasis diagnostic model, assessed with Area Under the Curve (AUC), Decision Curve Analysis (DCA), sensitivity, specificity, and validation cohorts. External validation used 113 NSCLC patients from the Medical Alliance (2019–2020). Furthermore, a prospective validation study was conducted on a cohort of 316 patients (2019–2020) who were devoid of bone metastasis, and followed-up for at least two years to assess the predictive capabilities of this model. The model's prognostic value was evaluated using Kaplan–Meier survival curves. Findings: Through variable selection, 11 serum indictors were identified as independent predictive factors for NSCLC bone metastasis. Six machine learning models were developed using age, sex, and these serum indicators. A random forest (RF) model demonstrated strong performance during the training and internal validation cohorts, achieving an AUC of 0.98 (95% CI 0.95–0.99) for internal validation. External validation further confirmed the RF model’s effectiveness, yielding an AUC of 0.97 (95% CI 0.94–0.99). The calibration curves demonstrated a high level of concordance between the anticipated risk and the observed risk of the RF model. Prospective validation revealed that the RF model could predict the occurrence of bone metastasis approximately 10.27 ± 3.58 months in advance, according to the results of the SPECT. An online computing platform (https://bonemetastasis.shinyapps.io/shiny_cls_1model/) for this RF model is publicly available and free-to-use by doctors and patients. Interpretation: This study innovatively employs age, gender, and 11 serological markers closely related to the mechanism of bone metastasis to construct an RF model, providing a reliable tool for the early screening and prognostic assessment of bone metastasis in NSCLC patients. However, as an exploratory study, the findings require further validation through large-scale, multicenter prospective studies. Funding: This work is supported by the National Natural Science Foundation of China (NO.81974315); Shanghai Municipal Science and Technology Commission Medical Innovation Research Project (NO.20Y11903300); Shanghai Municipal Health Commission Health Industry Clinical Research Youth Program (NO.20204Y034).

With the widespread development of fifth-generation (5G) mobile communication technology, concerns regarding 5G network security have also increased.Blackbox fuzzing is a commonly used method for automated vulnerability discovery in software security.However, applying dynamic approaches like fuzzing to discover vulnerabilities in the complex design of 5G core network protocols poses challenges such as low efficiency, poor versatility, and lack of scalability.Therefore, a novel static method to examine the open-source solution of the 5G core network was proposed.Through this method, a series of memory leak security issues caused by improper variable life cycle management were identified, which can lead to denial-of-service attacks on the 5G core network.To summarize these weaknesses, a general vulnerability model and an automated vulnerability discovery method called HoI were presented, which utilized hybrid analysis based on control and data flow.By successfully discovering five zero-day bugs in Open5GS, an open-source solution for the 5G core network, vulnerabilities that cover practical application scenarios of multiple interface protocols in the 5G core network were identified.These vulnerabilities have wide-ranging impact, are highly detrimental, and can be easily exploited.They have been reported to the vendor and assigned four Common Vulnerabilities and Exposures (CVE) numbers, demonstrating the effectiveness of this automated vulnerability discovery method.

Abstract This research focuses on the evolution of mechanical behavior of bimodal mixtures undergoing compaction and diametrical compression. The clusters were built and discrete element method (DEM) was used to investigate the densification process and micromechanics of bimodal mixtures. Additionally, a more comprehensive investigate of the respective breakage of the bimodal mixtures has been carried out. On this basis, qualitative and quantitative analysis of the compressive force, force chain, contact bonds and density field evolution characteristics of the clusters are investigated during the compression process. The entire loading process of the clusters is divided into three stages: rearrangement, breakage and elastic–plastic deformation. Additionally, there are differences in the evolution of micromechanics behavior of different particles in the bimodal mixture, with pregelatinized starch breakage and deformation occurring before microcrystalline cellulose. With the tablet deformation, the fragmentation process of the tablet started at the point of contact and extended toward the center, and the curvature of the force chain increased. This approach may potentially hold a valuable new information relevant to important transformation forms batch manufacturing to advanced manufacturing for the oral solid dosage form.

Paddy rice cultivation is a vital food source but also a significant contributor to greenhouse gas (GHG) emissions, particularly methane. Management measures such as improved water management and fertilization are being pursued to sustain rice production while cutting down the emissions. However, climate change may pose further challenges for sustainable rice agriculture by either impacting rice production or GHG emissions. Based on a database consisting of 1216 observations across China, we established machine learning models predicting rice yield and GHG emissions, taking into account climate, soil, and management variables. We tested three machine learning methods including random forest, support vector machine and artificial neural networks. The models were trained on 70% of the dataset with the remaining 30% used to evaluate the model performance. Random forest performed best with R2 of 0.59 to 0.72 and modelling efficiency of 52% to 72%. Farmland management emerged as the most important variable to the model prediction, followed by climate and soil variables. Rice production and GHG emissions were estimated to be 245.36 Tg and 218.95 Tg CO2-eq in 2018, respectively. By the year 2050, rice yield was expected to experience a modest decrease ranging from 0.6% to 1.2% due to the combined effects of global change variables, but GHG emissions were projected to increase by 2.1% to 4.9% under different climate change scenarios (Representative Concentration Pathways) in China. A large spatial variability in the impact of climate change was observed, and climate change will have the most significant impact in the Northeast agricultural region of China due to the warming effect. Through the analysis of region-specific farmland management scenarios, this study underscores a “Code Red” situation, signifying that future climate change could pose unprecedented risks to the sustainability of rice production in China, despite ongoing management improvements.

Contemporary studies largely concentrate on the physical aspects of architecture, yet within the sphere of design, the gap between user experience and the designer’s intention is an undeniable fact. This gap, illustrating the contrast between the spatial perception and the actual physical space, to some degree, mirrors preferences in human spatial behavior. It accentuates the complex relationship between human cognitive functions and spatial layout, underlining the critical role of spatial perception in architectural design and planning. This prompts the question of whether perceptions of internal traffic flow within buildings also suffer from spatial distortions. Focusing on museums, and by examining circulation paths and spatial features, a virtual museum model is devised. The research employs a holistic and reductionist approach (complex systems theory) to forge a link between circulation components and the spatial experience of architecture. Utilizing agent-based modeling tools for simulating pedestrian movements, it investigates how different circulation patterns and spatial relationships influence pedestrian behavior. The study proposes a museum circulation optimization strategy, grounded in quantifying spatial experience through Anylogic software analysis. This strategy is aimed at enhancing the design of internal traffic flows in future museum projects, offering fresh insights into museum design research, and probing into new possibilities for using pedestrian simulation software.

Objective: Sorafenib and lenvatinib have been recommended as standard tyro sine kinase inhibitors (TKIs) for progressive radioiodine-refractory differentiated thyroid carcinoma (RR-DTC). However, their efficacy remains limited with unresolved drug resistance. Therefore, we conceived this open-label study based on real-world evidence to investigate the efficacy and safety of apatinib in patients wi th progressive RR-DTC. Methods: Off-label use of apatinib as either initial treatment or salvage treatment for sorafenib resistance was investigated. The primary endpoint was progression-free survival (PFS) and the secondary endpoints included objective r esponse rate (ORR), overall survival (OS), and safety. Results: For all 28 enrolled patients, the median PFS was 15.1 months, w ith an ORR of 69.6%. The median OS was not reached at the data cut-off. In det ail, the median PFS of 17.3 months and the ORR of 75% were determined in patients with TKI-naive RR-DTC (initial treatment group, n = 14). And, in patients with first-line sorafenib-resistant RR-DTC (salvage treatment group, n = 14), a median PFS of 12.0 months was reached, with an ORR of 45.5%. In the salvage treatment group, the media n OS from the start of apatinib administration was 20.6 months, reaching 89.1 month s from sorafenib treatment initiation. Adverse events at grade 3 or higher occur red in 64.3% of all subjects treated with apatinib. Conclusions: This study demonstrated that apatinib shows promise against RR- DTC with tolerable toxicity, representing a novel initial treatment for progressive RR-DTC and effective salvage treatment for RR-DTC resistant to sorafenib.

Poorly differentiated thyroid carcinoma (PDTC) is a rare thyroid carcinoma originating from follicular epithelial cells. No explicit consensus can be achieved to date due to sparse clinical data, potentially compromising the outcomes of patients. In this comprehensive review from a clinician’s perspective, the epidemiology and prognosis are described, diagnosis based on manifestations, pathology, and medical imaging are discussed, and both traditional and emerging therapeutics are addressed as well. Turin consensus remains the mainstay diagnostic criteria for PDTC, and individualized assessments are decisive for treatment option. The prognosis is optimal if complete resection is performed at early stage but dismal in nearly half of patients with locally advanced and/or distant metastatic diseases, in which adjuvant therapies such as 131I therapy, external beam radiation therapy, and chemotherapy shou ld be incorporated. Emerging therapeutics including molecular targeted therapy, differentiation therapy, and immunotherapy deserve further investigations to improve the prognosis of PDTC patients with advanced disease.

The non-linearity and non-stationarity of wind power data have brought great challenges to the safe operation of the power system. It is particularly important to effectively improve the accuracy of ultra-short-term prediction of wind power. Therefore, we propose an ultra-short-term wind power prediction method that particle swarm optimization-variational mode decomposition (PVMD), enhanced slime mold algorithm (ESMA) for elite opposition-based learning strategy (EOBL) and deep extreme learning machine (DELM). First, the particle swarm optimization algorithm (PSO) is used to optimize the two core parameters of the variational mode decomposition (VMD) to obtain the PVMD algorithm. The PVMD is used to decompose the original wind power data into a series of stable sub-sequences, and the rolling time series is used to analyze the sub-sequences decomposed by PVMD. Then the DELM predictive model is established and the input weights (e) and thresholds (bc) in DELM are optimized through ESMA, and the EOBL is used to improve the diversity and population quality of the slime mold population, thereby improving the global optimization performance and convergence accuracy of the slime mold algorithm (SMA), and further improving the prediction accuracy of the DELM model. Finally, each subsequence is substituted into the DELM optimized by the elite opposition based learning-slime mold algorithm (ESMA-DELM), and the prediction components are superimposed to obtain the final prediction result. Comparing the effects of several different forecasting models with the evaluation of calculation examples proves the effectiveness of the PVMD-ESMA-DELM blended forecasting model proposed in this paper, and gives a new approach for ultra-short-term wind power prediction.

Abstract Background Laminins are high-molecular weight (400 ~ 900 kDa) proteins in extracellular matrix, which serve as major component of the basal lamina, and play a crucial role in promoting tumor cell migration. This study aimed at characterizing the role of laminin in promoting cancer development, and elucidating the mechanism of tumor progression driven by laminin-Notch signaling in bladder cancer. Methods 2D collagen/laminin culture system was established and CCK-8/transwell assay was conducted to evaluate the proliferation/migration ability of Biu-87 and MB49 cells cultured on 2D gels. Activation of integrins-Notch1 signaling was determined by western blotting. Orthotopic bladder cancer mice model was established to assess the therapeutic effects of Notch inhibitor. Results Our study demonstrated that extracellular laminin can trigger tumor cell proliferation/migration through integrin α6β4/Notch1 signaling in bladder cancer. Inhibition of Telomere repeat-binding factor 3 (TRB3)/Jagged Canonical Notch Ligand 1 (JAG1) signaling suppressed Notch signals activation induced by laminin-integrin axis. In MB49 orthotopic bladder cancer mice model, Notch inhibitor SAHM1 efficiently improved tumor suppressive effects of chemotherapy and prolonged survival time of tumor-bearing mice. Conclusion In conclusion, we show that, in bladder cancer, extracellular laminin induced the activation of Notch pathway through integrin α6β4/TRB3/JAG3, and disclosed a novel role of laminin in bladder cancer cells proliferation or migration.

Java deserialization vulnerabilities have become a common threat to Java application security nowadays.Finding out the gadget chain determines whether this type of vulnerability can be exploited.Due to the large code space of Java applications and dependent libraries and the polymorphism of Java itself, manual analysis of Java deserialization gadget chains consumes a lot of time and effort and it is highly dependent on the experienced knowledge.Therefore, it is crucial to study how to efficiently and accurately automate the discovery of gadget chains.Java deserialization gadget chain discovery method based on hybrid analysis was proposed.Call graph based on the variable declaration type was constructed, and then the deserialization entry functions that may reach the dangerous functions were screened using the call graph analysis.The screened entry functions were used as the entry point of the hybrid information flow analysis.The hybrid information flow analysis was carried out for both pointer and tainted variables.The tainted objects created implicitly were marked.The tainted information and the pointer information were propagated simultaneously to construct the hybrid information flow graph.The reachability of external taint data propagation to the dangerous function was judged based on the hybrid information flow graph.The corresponding deserialization gadget chain was constructed according to the taint propagation path.The hybrid analysis took into account the efficiency of call graph analysis and the accuracy of hybrid information flow analysis.The corresponding static analysis tool, namely GadgetSearch, was implemented based on the proposed hybrid analysis method.In the experimental evaluation, GadgetSearch had lower false positive and lower false negative than the existing tool GadgetInspector on four datasets of Ysoserial, Marshalsec, Jackson historical CVE, and XStream historical CVE.Additionally, GadgetSearch also found multiple undisclosed gadget chains.The experimental results show that the proposed method can efficiently and accurately discover the Java deserialization gadget chain in multiple practical Java applications.

BeiDou Medium Earth Orbit moderate-energy electron detection data play an important role in space environment effect analysis including satellite anomaly diagnosis, satellite risk estimation, etc. However, the data contain outliers which cause obstacle for the subsequent usage significantly. To solve this problem, we propose an outlier detection method based on convolutional neural networks (CNNs) which can learn a rule from labeled historical data and detect outliers from the detection data. With this method, we can identify outliers and do some follow-up operations to improve the data quality. In comparison with general methods, this CNN method provides a more reliable and rapid way to build dataset for the follow-up work.

The detachment–transport coupling equation by Foster and Meyer is a classical equation that describes the relationship between detachment and transport. The equation quantifies the relationship between sediment loads and soil detachment rates, deepens the understanding of soil erosion and provides a reliable basis for the establishment of an erosion model. However, the applicability of this equation to slopes with gradients greater than 47% is limited. In this work, the detachment–transport coupling relationship is investigated using the colluvium material of Benggang. A nonerodible rill flume 4 m long and 0.12 m wide was adopted. The slope gradient ranged from 27% to 70%, the unit flow discharge ranged from 0.56 × 10−3 to 3.33 × 10−3 m2 s−1, and the sediment transport capacity (Tc) was measured under each slope and discharge combination. The sediment was inputted into the flume according to the predetermined sediment addition rate (from 0% to 100% of Tc), and the detachment rate (Dr) under each combination of the slope and discharge was measured. Dr linearly decreased with increasing sediment loads, which is consistent with the detachment–transport coupling equation by Foster and Meyer. The linear equations can predict the detachment capacity (Dc) and Tc well (Nash–Sutcliffe efficiency coefficient (NSE) = 0.98 for Dc, and NSE = 0.99 for Tc). The detachment–transport coupling equation can adequately predict the Dr (NSE = 0.89). However, its applicability to slopes of

Epidermal growth factor receptor 2 (ERBB2) is commonly over-expressed in advanced or metastatic tissues of papillary thyroid cancer (PTC) with poor prognosis, while it remains unknown whether ERBB2 plays a role in the progression of PTC. Thus, we analyzed the data derived from online repositories, including TCGA, KEGG, GO, GeneMANIA, and STRING, to explore the relationship between ERBB2 expression and prognosis, tumor phenotypes of interest, and immune infiltrates in PTC. Compared to normal thyroid tissue, ERBB2 was up-regulated in PTC samples (p < 0.001); In comparison with the group with low expression of ERBB2, the group with high expression of ERBB2 had poorer progression-free interval in stage III/IV patients (p = 0.008) and patients aged >45 years (p = 0.019). The up-regulated ERBB2 was associated with iodine metabolism dysfunction, proliferation, metastasis, angiogenesis, and drug resistance. The expression of ERBB2 negatively correlated with enrichment scores of B cells (r = −0.176, p < 0.001), CD8+ T cells (r = −0.160, p < 0.001), cytotoxic cells (r = −0.219, p < 0.001), NK CD56dim cells (r = −0.218, p < 0.001), plasmacytoid dendritic cells (r = −0.267, p < 0.001), T cells (r = −0.164, p < 0.001), T follicular helper cells (r = −0.111, p = 0.012), gamma delta T cells (r = −0.105, p = 0.017), and regulatory T cells (r = −0.125, p = 0.005). In conclusion, ERBB2 may serve as a prognostic biomarker and an immunotherapeutic target in PTC, deserving further exploration.

Abstract Background To investigate the heterogeneities of human umbilical cord mesenchymal stromal cells (HUCMSCs) derived from different donors and their therapeutic variations when applied to mouse liver fibrosis model. Methods The characteristics of HUCMSCs derived from multiple donors were comprehensively analyzed including expressions of surface markers, viability, growth curve, karyotype analysis, tumorigenicity, differentiation potentials, and immune regulation capability. Then, the HUCMSCs with distinct immunomodulatory effects were applied to treat mouse liver fibrosis and their therapeutic effects were observed. Results The HUCMSCs derived from multiple donors kept a high consistency in surface marker expressions, viability, growth curve, and tumorigenicity in nude mice but had robust heterogeneities in differentiation potentials and immune regulations. In addition, three HUCMSC lines applied to mice liver fibrosis model had different therapeutic outcomes, in line with individual immune regulation capability. Conclusion The HUCMSCs derived from different donors have individual heterogeneity, which potentially lead to distinct therapeutic outcomes in mouse liver fibrosis, indicating we could make use of the donor-variation of MSCs to screen out guaranteed general indicators of MSCs for specific diseases in further stromal cell therapy.

Although biologically targeted therapies based on key oncogenic mutations have made significant progress in the treatment of locally advanced or metastatic thyroid cancer, the challenges of drug resistance are urging us to explore other potentially effective targets. Herein, epigenetic modifications in thyroid cancer, including DNA methylation, histone modifications, non-coding RNAs, chromatin remodeling and RNA alterations, are reviewed and epigenetic therapeutic agents for the treatment of thyroid cancer, such as DNMT (DNA methyltransferase) inhibitors, HDAC (histone deacetylase) inhibitors, BRD4 (bromodomain-containing protein 4) inhibitors, KDM1A (lysine demethylase 1A) inhibitors and EZH2 (enhancer of zeste homolog 2) inhibitors, are updated. We conclude that epigenetics is promising as a therapeutic target in thyroid cancer and further clinical trials are warranted.

AbstractBackground Studies have demonstrated the diagnostic efficiency of antibody testing in COVID-19 infection. There is limited data on the IgM/IgG changes in asymptomatic and discharged patients with reoccurring positive nucleic acid test (RPNAT). This study aims to investigate these IgM/IgG changes.Methods There were 111 patients with positive nucleic acid test (NAT) and 40 suspected patients enrolled in the study. The serum SARS-CoV-2 specific IgM/IgG antibody levels were retrospectively analysed with the disease progress in asymptomatic and RPNAT patients.Results The best overall performance was found by combining the IgM, IgG, and CT; 95.1% sensitivity and 75% specificity. This was tested in 111 RT-PCR positive cases. The median IgM and IgG levels were lower in the asymptomatic group compared to the symptomatic group (p

Abstract Background To evaluate the feasibility, safety, applied value and efficacy of enhanced recovery after surgery (ERAS) for PCNL for the treatment of renal calculi. Although the ERAS is applied for many urological diseases, its application in percutaneous nephrolithotripsy (PCNL) is still limited. Methods This was a prospective study of patients admitted to hospital January and December 2018 and who were only diagnosed with renal calculi and excepted for serious or uncontrollable basic diseases and patients with multiple operation history and medication history. Patients were randomized 1:1 to the ERAS and traditional operation groups starting on the day before operation and end on the day of discharge. Each group was 118 cases. The stone clearance rate, visual analogue scale (VAS) pain score, the occurrence of perirenal hematoma and effusion, the incidence of extravasation of urine, the incidence of fever, bleeding and blood transfusion, and postoperative hospital stay were observed. Results The stone clearance rates were similar between the two groups (ERAS: 93.2% (109/117) vs. traditional: 89.8% (106/118), P = 0.800). The operation time was similar in the two groups (ERAS: 54 ± 12 vs. traditional: 58 ± 11 min, P = 0.656). VAS pain score that was 0.79 ± 0.76 in the ERAS group at 4 h after surgery and was significantly lower than 2.79 ± 0.98 in the traditional group (P

Integrating device-to-device (D2D) communication into cellular networks is considered as a promising technology to support high data rate and improve spectrum utilization. However, the severe interference issue in D2D and cellular coexisting networks might erode the benefits brought by D2D communications. To address this critical issue, we first propose two exclusion-based D2D activation schemes with hybrid spectrum allocation (named EDAH) and spectrum sharing (named EDAS), where D2D users (DUs) outside the exclusion regions of base stations are active. Based on the activation scheme, cellular users can be classified into central users (CUs) within the exclusion regions and the remaining edge users (EUs). Secondly, we establish a stochastic geometry-based framework to characterize the performance of D2D and cellular coexisting networks, where the distribution of the active D2D pairs follow a bipolar Poisson hole process. Specifically, we provide tight bounds and accurate approximations for the success probabilities of CUs and DUs. Due to the different spectrum allocation, we provide an exact analytical expression for the success probability of EUs in EDAH and a tight bound in EDAS. With these results, we further analyze the area spectral efficiency (ASE) for network-level performance evaluations. The results show that both schemes are effective in suppressing interference. In particular, the EDAH scheme can significantly improve the transmission reliabilities of users anywhere, while the EDAS scheme generally gains higher ASE at the expense of the transmission reliability of EUs.

Background: Ambient air pollution is leading risk factor for health burden in China. Few studies in China have investigated the economic loss related to short-term exposure to ambient PM2.5, which could trigger acute onset of cardiorespiratory diseases within a few days. Methods: Daily ambient air pollutants data are obtained for each city from the National Air Quality Monitoring System and daily hospitalization data are obtained from the urban employee-based basic medical insurance scheme database in 74 Chinese cities with an average coverage of 88.5 million urban employees during 2016-2017. A three-stage time-series analytic approach is used in this study to investigate the impact of short-term exposure to ambient fine particulate (PM2.5) air pollution on hospital admissions, expenses and hospital stays of three cause-specific cardiorespiratory diseases, including lower respiratory infections (LRI), coronary heart disease (CHD) and stroke in the included cities. Findings: Based on the time-series analysis using daily hospitalization data, 28,560 LRI cases, 54,600 CHD cases, and 23,989 stroke cases are attributable to ambient PM2.5 in the 74 cities during the study period, and the related attributable expenses are 220 million CNY (US$ 32.9 million) for LRI, 458 million CNY (US$ 68.5 million) for CHD, and 410 million CNY (US$ 65.8 million) for stroke, respectively. These attributable numbers account for 1.45% to 2.05% of total hospital admissions and 1.10% to 1.51% of total expenses for the three diseases during 2016-2017, respectively. The attributable numbers for the three cause-specific cardiorespiratory diseases would increase to 362,007 hospital admission cases and 3.68 billion CNY expenses ($US550 million) in the entire urban employee population (299 million) in China during 2016-2017, and the related direct economic loss of absence from work would be 798 million CNY (US$ 119.3 million). Interpretation: Our results support that short-term exposure to ambient PM2.5 pollution could lead to significant health and economic impacts in China. Reducing levels of ambient PM2.5 can avoid substantial health damage and expenditures, and generate appreciable economic benefits from decreasing absence from work. Funding: Natural Science Foundation of China (82073509, 71903010, 71903011), and the National Key Research and Development Program of China (2017YFC0211600, 2017YFC0211601).

Radioiodine remnant ablation (RRA) was previously demonstrated to be a safe and effective alternative to completion thyroidectomy for patients with differentiated thyroid cancer (DTC). However, its side effects have not been fully investigated, particularly in patients with lobectomy. We reported a young euthyroidal female who underwent RRA post lobectomy and lymph node dissection for papillary thyroid cancer, whose post-ablation 131I-whole-body scan accidentally showed diffuse radioiodine distribution on chest-mimicking pulmonary metastases. Immediately-added single-photon emission computed tomography/computed tomography (SPECT/CT), nevertheless, revealed a 131I-accumulating swollen left thyroid lobe and emerging pleural effusion, which relieved after short-term treatment with prednisone. In summary, acute pleural effusion ascribed to RRA-induced thoracic duct compression was reported for the first time. 131I-lobectomy-induced pleural effusion could be precisely diagnosed by SPECT/CT and efficiently manipulated via treating radiation thyroiditis with the short-term administration of corticosteroid.

The dynamic characteristics of pipe piles are of considerable importance for the dynamic foundation design of offshore wind turbines. In this study, we develop an analytical model for the lateral vibration of offshore pipe piles with consideration of the inertia effect and axial loading from the superstructure. A coupled dynamic saturated soil–pile interaction model is established based on Biot’s poroelastic theory and Euler–Bernoulli theory. The potential function, operator decomposition method, variable separation method and matrix transfer method are introduced herein to obtain the lateral force of the inner and outer soil acting on the pile shaft. Then, the analytical solution of the pile dynamic impedance in the frequency domain is derived by employing the soil–pile continuous deformation conditions and the boundary conditions of the pile. The rationality and accuracy of the presented solution have were by comparing its results with those predicted by existing solutions. The influence of superstructure, pile geometry and soil plug height on the lateral dynamic impedance and natural frequency of pipe piles was thoroughly investigated based on the theoretical model. The main findings can be summarized as: (1) The dynamic stiffness of piles will be remarkably underestimated if the inertia effect of the superstructure is not accounted for. (2) The vertical load of the superstructure is main factor affecting the natural frequency, whereas the inertia effect of the superstructure will enlarge the resonance amplitude. (3) The overall lateral dynamic impedance and first-order natural frequency of the pile increase significantly with the soil plug height.

Clinical efficacy of redifferentiation therapy with histone deacetylase inhibitor (HDACi) for lethal radioiodine-refractory papillary thyroid cancer (RR-PTC) is urgently needed to be improved. Given that the impairment of histone acetylation is a mechanism in BRAFV600E-mitogen-activated protein kinase (MAPK)-induced aberrant silencing of thyroid iodine-metabolizing genes, dual inhibition of HDAC and MAPK may produce a more favorable effect. In this study, we treated BRAFV600E-mutant (BCPAP and K1) and BRAF-wild-type (BHP 2-7) cells with HDACi (panobinostat) and MAPK inhibitor (dabrafenib or selumetinib), alone or in combination, and we tested the expression of iodine- and glucose-metabolizing genes, radioiodine uptake and efflux, and toxicity. We found that panobinostat alone increased iodine-metabolizing gene expression, promoted radioiodine uptake and toxicity, and suppressed GLUT1 expression in all the cells. However, MAPKi (dabrafenib or selumetinib) induced these effects only in BRAFV600E-mutant cells. Combined treatment with panobinostat and MAPKi (dabrafenib or selumetinib) displayed a more robust BRAFV600E-dependent redifferentiation effect than panobinostat alone via further improving the acetylation level of histone at the sodium-iodide symporter (NIS) promoter. In conclusion, MAPK inhibitors enhance HDACi-induced redifferentiation in PTC cells harboring BRAFV600E, warranting animal and clinical trials. Keywords: thyroid cancer, redifferentiation therapy, histone deacetylase inhibitor, MAPK inhibitor, sodium-iodide symporter

BackgroundRepeated radioiodine (131I) treatment (RT) are commonly performed in patients with 131I-avid distant metastatic differentiated thyroid cancer (DM-DTC), but more precise indications remain indeterminate. This prospective study was conducted to explore predictors for biochemical response (BR) to next RT.MethodsTotally thyroidectomized patients with 131I-avid DM-DTC demonstrated by initial post-therapeutic whole body scan (Rx-WBS) were consecutively recruited. Repeated RTs were performed at a fixed dose and a fixed interval, which was terminated once a decline in thyroid stimulating hormone-suppressed thyroglobulin (Tgon) could not be achieved or Rx-WBS was negative. BR was evaluated by change rate of Tgon level (ΔTgon%).ResultsAfter exclusion of 27 ineligible courses, a total of 166 neighboring course pairs from 77 patients were established and utilized. Univariate and multivariate analyses showed that the maximum target/background ratio (T/Bmax) on the whole body scan and ΔTgon% derived from the former RT were independently associated to the latter one. In predicting biochemical remission, the positive predictive value (PPV) and negative predictive value (NPV) of T/Bmax at the cut-off value of 8.1 were 79.1% and 84.0%, respectively; whereas the PPV and NPV of ΔTgon% at the cut-off value of 25.3% were 70.8% and 77.1%, respectively. Notably, the PPV of combined T/Bmax ≥ 8.1 and ΔTgon% ≥ 25.3% increased to 87.7%; while the NPV of T/Bmax ≥ 8.1 or ΔTgon% ≥ 25.3% reached as high as 97.7%.ConclusionsThis study revealed that combined use of the latest RT-derived T/Bmax and ΔTgon% may efficiently identify biochemical responders/non-responders to next RT, warranting management optimization of patients with 131I-avid DM-DTC.

Opa-interacting protein 5 (OIP5) is a member of the cancer-testis antigen (CTA) family that elicits a spontaneous antitumor immune response. The failure of current immunotherapies for glioma has prompted the search for novel biomarkers that may be utilized as therapeutic targets. This study aimed to investigate whether OIP5 serves as a target for malignant glioma immunotherapy. Glioma specimens from 53 adult patients were evaluated for OIP5 expression by immunohistochemical (IHC) staining, and the correlation of OIP5 expression with World Health Organization (WHO) tumor grade was analyzed. Endogenous expression of OIP5 in glioma cell lines was determined via real-time polymerase chain reaction (RT-PCR). Using lentiviral siOIP5, the effect of OIP5 gene knockdown on proliferation, cell cycle, and apoptosis in U251 glioma cells was studied. The results show that OIP5 is overexpressed in glioma tissues and is correlated with WHO tumor grade ( P < 0.001). However, OIP5 protein expression is barely detectable in normal adult brain tissues. MTT assays and analysis using the Celigo Imaging Cytometry System reveal that the silencing of OIP5 inhibits U251 cell growth. Cell cycle assays and Annexin V staining show that OIP5 silencing disrupts the balance of the cell cycle and increases U251 cell death. These results indicate that OIP5 is upregulated in malignant glioma specimens but barely detected in normal brain tissues. OIP5 knockdown inhibits the biological function of glioma cells, reinforcing that OIP5 may serve as an immunotherapeutic target for malignant glioma.

Few large multicity studies have assessed acute effect of tropospheric ozone pollution on pneumonia risk. We aimed to examine the relation between day-to-day changes in ozone concentrations and hospital admissions for pneumonia in China. We conducted a national time-series study in 184 major Chinese cities from 2014 to 2017. City-specific relation between ozone concentrations and pneumonia admissions was evaluated using an over-dispersed generalized additive model. Random-effects meta-analysis was conducted to pool the city-specific estimates. Two-pollutant models were fitted to test the robustness of the relations. We also investigated potential effect modifiers. Overall, we observed increased admissions for pneumonia associated with ozone exposure. The national-average estimates per 10-μg/m3 increase in ozone were 0.14% (95% CI: 0.03%–0.25%) at lag 0 day in the whole year, 0.30% (95% CI: 0.17%–0.43%) at lag 0 day in the warm season, and 0.20% (95% CI: 0.05%–0.34%) at lag 1 day in the cool season. Two-pollutant models indicated that the ozone effects were not confounded by PM2.5, SO2, NO2 or CO. The association between ozone and pneumonia was stronger in the elderly. Ozone levels and gross domestic product per capita reduced the effects of ozone, and smoking enhanced the effects of ozone. In conclusion, we estimated an increase in daily pneumonia admissions associated with ozone exposure in China. As the first national study in China to report acute effect of ozone on pneumonia hospitalizations, our findings are incredibly meaningful in terms of both ozone pollution related policy development and pneumonia prevention. Keywords: Air pollution, Pneumonia, Ozone, Time-series study

BACKGROUND:The effects of ambient particulate matter (PM) pollution on pneumonia in adults are inconclusive, and few scientific data on a national scale have been generated in low- or middle-income countries, despite their much higher PM concentrations. We aimed to examine the association between PM levels and hospital admissions for pneumonia in Chinese adults. METHODS AND FINDINGS:A nationwide time series study was conducted in China between 2014 and 2017. Information on daily hospital admissions for pneumonia for 2014-2017 was collected from the database of Urban Employee Basic Medical Insurance (UEBMI), which covers 282.93 million adults. Associations of PM concentrations and hospital admissions for pneumonia were estimated for each city using a quasi-Poisson regression model controlling for time trend, temperature, relative humidity, day of the week, and public holiday and then pooled by random-effects meta-analysis. Meta-regression models were used to investigate potential effect modifiers, including cities' annual-average air pollutants concentrations, temperature, relative humidity, gross domestic product (GDP) per capita, and coverage rates by the UEBMI. More than 4.2 million pneumonia admissions were identified in 184 Chinese cities during the study period. Short-term elevations in PM concentrations were associated with increased pneumonia admissions. At the national level, a 10-μg/m3 increase in 3-day moving average (lag 0-2) concentrations of PM2.5 (PM ≤2.5 μm in aerodynamic diameter) and PM10 (PM ≤10 μm in aerodynamic diameter) was associated with 0.31% (95% confidence interval [CI] 0.15%-0.46%, P < 0.001) and 0.19% (0.11%-0.30%, P < 0.001) increases in hospital admissions for pneumonia, respectively. The effects of PM10 were stronger in cities with higher temperatures (percentage increase, 0.031%; 95% CI 0.003%-0.058%; P = 0.026) and relative humidity (percentage increase, 0.011%; 95% CI 0%-0.022%; P = 0.045), as well as in the elderly (percentage increase, 0.10% [95% CI 0.02%-0.19%] for people aged 18-64 years versus 0.32% [95% CI 0.22%-0.39%] for people aged ≥75 years; P < 0.001). The main limitation of the present study was the unavailability of data on individual exposure to PM pollution. CONCLUSIONS:Our findings suggest that there are significant short-term associations between ambient PM levels and increased hospital admissions for pneumonia in Chinese adults. These findings support the rationale that further limiting PM concentrations in China may be an effective strategy to reduce pneumonia-related hospital admissions.

Background/Aims: In the treatment of serious and symptomatic coronary heart disease (CHD), coronary artery bypass grafting (CABG) is a frequently utilized intervention. In addition, the risk of CHD is strongly associated with the low activity of paraoxonase-1 (PON1), whose 3’-UTR harbors an rs3735590 polymorphism. The aim of this study was to investigate whether the rs3735590 polymorphism could be used as a prognosis marker in chronic obstructive pulmonary disease (COPD) patients undergoing CABG. In addition, the hypothesis, i.e., the rs3735590 polymorphism may be involved in the regulation of PON1 gene expression via modulating its interaction with miRNAs, was tested in this study. Methods: 292 patients diagnosed with COPD and treated with CABG were recruited for this study. Genomic DNA was extracted from clinical samples, and real-time quantitative PCR and Western-blot were used to measure the expression of miR-616 and PON1 in liver cells of different genotypes. Results: 292 COPD patients were divided into three groups according to their genotypes, i.e., rs3735590: CC (212), TC (75), and TT (5), respectively (TC and TT were merged in one group of T carriers for statistical analyses). Patients with the CC genotype were associated with a shorter event-free survival time as compared to patients with the T genotypes. In addition, PON1 was confirmed as a direct target gene of miR-616, while experiments with primary cells of different genotypes showed that miR-616 inhibited the expression of PON1 in CC cells. On the contrary, rs3735590 impaired such inhibitory effect of miR-616 in TT cells. Conclusion: The rs3735590 polymorphism of PON1 acts as a prognostic biomarker in COPD patients treated by CABG.

BACKGROUND:Epidemiological studies have provided compelling evidence of associations between ambient temperature and cardiovascular disease. However, evidence of effects of daily temperature variability on cardiovascular disease is scarce and mixed. We aimed to examine short-term associations between temperature variability and hospital admissions for cause-specific cardiovascular disease in urban China. METHODS AND FINDINGS:We conducted a national time-series analysis in 184 cities in China between 2014 and 2017. Data on daily hospital admissions for ischemic heart disease, heart failure, heart rhythm disturbances, and ischemic stroke were obtained from the database of Urban Employee Basic Medical Insurance (UEBMI) including 0.28 billion enrollees. Temperature data were acquired from the China Meteorological Data Sharing Service Center. Temperature variability was calculated from the standard deviation (SD) of daily minimum and maximum temperatures over exposure days. City-specific associations between temperature variability and cardiovascular disease were examined with overdispersed Poisson models controlling for calendar time, day of the week, public holiday, and daily mean temperature and relative humidity. Random-effects meta-analyses were performed to obtain national and regional average associations. We also plotted exposure-response relationship curve using a natural cubic spline of temperature variability. There were 8.0 million hospital admissions for cardiovascular disease during the study period. At the national-average level, a 1-°C increase in temperature variability at 0-1 days (TV0-1) was associated with a 0.44% (0.32%-0.55%), 0.31% (0.20%-0.43%), 0.48% (0.01%-0.96%), 0.34% (0.01%-0.67%), and 0.82% (0.59%-1.05%) increase in hospital admissions for cardiovascular disease, ischemic heart disease, heart failure, heart rhythm disturbances, and ischemic stroke, respectively. The estimates decreased but remained significant when controlling for ambient fine particulate matter (PM2.5), NO2, and SO2 pollution. The main limitation of the present study was the unavailability of data on individual exposure to temperature variability. CONCLUSIONS:Our findings suggested that short-term temperature variability exposure could increase the risk of cardiovascular disease, which may provide new insights into the health effects of climate change.

This study aimed to compare the prevalence of hypertension between the island and rural residents in Dalian, China, and to explore associated risk factors of hypertension in order to provide evidence for the establishment of targeted strategy of hypertension prevention and treatment for island and rural residents. The modified MONICA questionnaire survey was performed on 7764 island and rural residents aged ≥40 years (including 2652 island residents and 5112 rural residents). Our data showed that totally weighted prevalence of hypertension was significantly higher in rural residents than in island residents (61.9% vs. 55.2%, P

The research on the deformation mechanism of monopile foundation supporting offshore wind turbines is significant to optimize the design of a monopile foundation under wave and current load. In this paper, a three-dimensional wave-pile-soil coupling finite element model is proposed to investigate the deformation mechanism of monopile undercurrent and fifth-order Stokes wave. Different from the conventional assumption that there is no slip at the pile-soil interface, Frictional contact is set to simulate the relative movement between monopile and soil. Numerical results indicate that under extreme environmental conditions, the monopile foundation sways within a certain range and the maximum displacement in the loading direction is 1.3 times the displacement in the reverse direction. A further investigation has been made for a large-diameter pipe pile with various design parameters. The finite element analyses reveal that the most efficient way to reduce the deflection of the pile head is by increasing the embedment depth of the monopile. When the embedment depth is limited, increasing the pile diameter is a more effective way to strengthen the foundation than increasing the wall thickness.

Abstract Background Pregnancy is an unquantifiable risk to accelerate tumor growth of papillary thyroid carcinoma (PTC), and whether pregnancy induces an unfavorable prognosis of radioiodine refractory papillary thyroid carcinoma (RR-PTC) remains unknown. Case presentation We investigated the impact of pregnancy on the prognosis of pulmonary metastases in an RR-PTC woman via a long-term clinical follow-up and consecutive computed tomography examinations and serum tests. After a successful pregnancy, the metastatic lesions shrank with serum thyroglobulin slightly fluctuated under sustained thyroid stimulating hormone (TSH) suppression, demonstrating a favorable outcome. Conclusions This case study indicates that metastatic RR-PTC may not be aggravated by pregnancy under TSH suppression, and pregnancy should not be contraindicated in RR-PTC patients with stable disease.

This study aims to establish a probabilistic capacity model of a wall pier under various damage states, and the seismic vulnerability of a typical wall pier bridge is studied. The finite element analysis of the wall pier is carried out by using the layered shell element, and its accuracy is verified through the comparison with the experimental results. A series of wall pier samples are generated based on the survey data, and the corresponding finite element models are established. The hysteresis analysis is implemented to obtain the displacement drift ratio of each seismic performance point. A candidate capacity model with various factors is proposed, and the unknown parameters are estimated and filtered by the Bayesian method. One hundred and twenty bridge samples of a benchmark bridge are generated by considering the uncertainty of parameters, and the finite element models are established. The bridge samples and ground motions were matched by one-to-one correspondence for the nonlinear time history analysis, and seismic vulnerability models of bridge components and system are obtained. The results showed that the in-plane capacity of wall piers is mainly affected by axial compression ratio, shear span ratio, and vertical reinforcement ratio. The wall pier shows excellent behavior in the earthquakes. The capacity models of wall piers can be used for evaluating the damage states of wall piers, and obtaining the seismic vulnerability model of wall piers bridges to be used for future seismic risk assessment and retrofit prioritization.

BACKGROUND:Evidence of the short-term effects of ambient air pollution on the risk of ischemic stroke in low- and middle-income countries is limited and inconsistent. We aimed to examine the associations between air pollution and daily hospital admissions for ischemic stroke in China. METHODS AND FINDINGS:We identified hospital admissions for ischemic stroke in 2014-2016 from the national database covering up to 0.28 billion people who received Urban Employee Basic Medical Insurance (UEBMI) in China. We examined the associations between air pollution and daily ischemic stroke admission using a two-stage method. Poisson time-series regression models were firstly fitted to estimate the effects of air pollution in each city. Random-effects meta-analyses were then conducted to combine the estimates. Meta-regression models were applied to explore potential effect modifiers. More than 2 million hospital admissions for ischemic stroke were identified in 172 cities in China. In single-pollutant models, increases of 10 μg/m3 in particulate matter with aerodynamic diameter

The With the development of new applications and technologies, software defined networking is getting more attention from application providers, carriers, and IT system and network devices vendors. In SDN, the control and data planes are decoupled, which supports programmable network control and service provision. The definition and framework of SDN were discussed; the demands of IP RAN in SDN in current telecommunication network were analyzed. The target network structure and network models based SDN in IP RAN network were described and the application strategy of SDN in IP RAN network was also discussed.