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Label noise causes deep neural networks to gradually memorize incorrect labels, leading to a decline in generalization. In this paper, based on three observations from learning behavior in textual noise scenarios, we propose a dynamic training method to enhance model robustness and generalization against textual label noise. This method corrects noisy labels by dynamically incorporating the model's predictions. The combination weight of the original labels is a decay function on training time, which relates to the learning dynamics. Additionally, our method introduces r-drop and prior regularization terms to ensure that the single-model backbone generates reliable predictions, thereby obtaining accurate corrected labels. This design removes the stage splitting and data segmentation required by existing SOTA methods and effectively mitigates the adverse impact of erroneous labels without introducing additional dependencies. Experimental results on four text classification datasets demonstrate that dynamic training outperforms strong baselines designed for class-conditional and instance-dependent noises within the common noise range. Our code is available at https://github.com/shaohuancheng/noisy_label_for_exp_decay. [ABSTRACT FROM AUTHOR]

Objective: To assess the efficacy and safety of Sanjie Analgesic Capsule (SAC) in Chinese patients with endometriosis-associated pain. Methods: This was a multicenter, randomized, double-blind, placebo-controlled trial conducted at 15 centers between November 2013 and July 2017 in China. Eligible 323 patients with endometriosis were randomized at a 3:1 ratio to the SAC group (241 cases) and placebo group (82 cases) by stratified block randomization. Patients in the SAC or placebo groups were given SAC or placebo 1.6 g 3 times per day, orally, respectively since the first day of menstruation for 3 consecutive menstrual cycles. The primary endpoint was clinical response to dysmenorrhea evaluated using a 10-point Visual Analogue Scale at 3 and 6 months. The secondary endpoint was the pain score evaluated by VAS (chronic pelvic pain, defecation pain, and dyspareunia) at 3 and 6 months, and the pain recurrence rate at 6 months. Adverse events (AEs) were recorded during the study. Results: A total of 241 women were included in the SAC group, and 82 were in the placebo group. Among these women, 217 (90.0%) and 71 (86.6%) completed the intervention, respectively. At 3 months, overall response rate (ORR) was significantly higher in women administered SAC (80.1%) compared with those who received a placebo (30.5%, P<0.01). Six months after treatment, the ORR for dysmenorrhea was 62.7% in the SAC group and 31.7% in the placebo group (P<0.01). Chronic pelvic pain and defecation pain were significantly improved by SAC compared with placebo (both P<0.05). The incidence rates of total AEs events in the SAC and placebo groups were 6.6% and 9.8%, respectively, and no significant difference was shown between the two groups (P=0.339). Conclusion: SAC is well-tolerated and may improve dysmenorrhea in women with endometriosis-associated pain. (Trial registration: ClinicalTrials.gov, No. NCT02031523) [ABSTRACT FROM AUTHOR]

Ferroptosis is a form of cell death and has great potential application in the treatment of many cancers, including clear cell renal cell carcinoma (ccRCC). Herein, we identified the essential roles of Krüppel-like factor 11 (KLF11) in suppressing the progression of ccRCC. By analyzing mRNA expression data from the Gene Expression Omnibus (GEO) database, we found that KLF11 was a significantly downregulated gene in ccRCC tissues. The results of subsequent functional assays verified that KLF11 played an antiproliferative role in ccRCC cells and xenograft tumors. Furthermore, gene set enrichment analysis indicated that ferroptosis was involved in ccRCC development, and correlation analysis revealed that KLF11 was positively related to ferroptosis drivers. We also found that KLF11 promoted ferroptosis in ccRCC by downregulating the protein expression of ferritin, system xc (−) cystine/glutamate antiporter (xCT), and glutathione peroxidase 4 (GPX4), acting as the inhibitory factors of ferroptosis and increasing the intracellular levels of lipid reactive oxygen species (ROS). As a transcriptional regulator, KLF11 significantly increased the promoter activity of nuclear receptor coactivator 4 (NCOA4), a gene significantly downregulated in ccRCC and whose low expression is associated with poor survival. The characteristics of ccRCC cells caused by KLF11 overexpression were reversed after NCOA4 silencing. In summary, the present study suggests that KLF11 suppresses the progression of ccRCC by increasing NCOA4 transcription. Therefore, the KLF11/NCOA4 axis may serve as a novel therapeutic target for human ccRCC. [ABSTRACT FROM AUTHOR]

Median filters are widely used to smooth data in image processing tasks and eliminate noise with extremely large or small magnitude. Thus, this paper proposes a median filtering method for quantum color images in the spatial domain, with the corresponding quantum circuit simulated on IBM the Quantum Experience (IBM Q) platform. In our technique, first, we improve the quantum color image storage module and adopt nine quantum color images to represent the core image (image to be processed) and its 8-neighborhoods. Then, a quantum comparator and a quantum control swap operation with low time complexity are employed to design the quantum median calculation module. Finally, we design the quantum circuit for color image median filtering, simulated on the IBM Q platform. Compared with existing methods, the proposed method's time complexity is significantly reduced from O (q 2) to O(q) and the auxiliary qubit is reduced from O(q) to O(1). The developed scheme provides the framework for encoding the neighborhood information of pixels in supplementary images and reduces the auxiliary qubits and time complexity, demonstrating the potential of quantum image processing for highly efficient image and video processing tasks in the big data era. [ABSTRACT FROM AUTHOR]

The synergistic effect and mechanism of the spherical CoSn(OH)6 (T-CHS) and ammonium polyphosphate (APP) on epoxy resin (EP) were investigated by limiting oxygen index (LOI), vertical combustion test (UL-94), cone calorimeter, tensile machine, thermogravimetric analysis-coupled with a Fourier transform infrared spectrometer (TGA/FTIR), scanning electron microscopy (SEM), X-ray photoelectron spectroscopy, and Raman spectrometer. The results indicate that when the mass ratio of APP and T-CHS is 5.9:0.1 and 5.5:0.5, respectively, there is a synergistic effect between APP and T-CHS, and the flame retardant EP samples could pass the V-0 level of UL-94 test and their tensile properties have little difference to that of the blank EP. Compared with the blank EP, the total heat release and total smoke production of EP/5.9APP/0.1 T-CHS are decreased by 25% and 26%, respectively. TGA/FTIR results of the EP samples under N2 atmosphere indicate the NH3 production of EP/5.9APP/0.1 T-CHS is decreased by 47% and the CO2 and H2O production is increased by 991% and 210%, respectively, when compared with that of the blank EP. APP and T-CHS show a good synergistic effect on promoting the retention of C, Co, Sn, and N elements in the char residues. The char residues of EP/5.9APP/0.1 T-CHS and EP/5.5APP/0.5 T-CHS samples contain Co3O4, CoO, SnO, SnO2, oxides of phosphorus, and Sn element, which form a more compact physical barrier. [ABSTRACT FROM AUTHOR]

Efficient quantum circuits of algebraic operations are vital for quantum algorithms. In this paper, we propose a novel fault-tolerant quantum divider based on long division algorithm using Clifford+T gates. Firstly, two efficient quantum subtractors are designed which we call them equal-bit subtractor and unequal-bit subtractor. The advantage of these quantum subtractors is that the number of the constant inputs is 2, which will dramatically reduce the qubit cost. Then, based on the quantum comparator and the quantum subtractors, we propose a novel fault-tolerant quantum divider. Compared with existing work, the proposed quantum divider has better performances in quantum cost, T-depth, T-count, qubit cost, constant inputs and garbage outputs. Finally, we simulate these algorithms on IBM Quantum Experience (IBM Q Experience) platform, and the probability histograms show that these algorithms are feasible and efficient. [ABSTRACT FROM AUTHOR]

Periodontal ligament stem cells (PDLSCs) are a key cell type for restoring/regenerating lost/damaged periodontal tissues, including alveolar bone, periodontal ligament and root cementum, the latter of which is important for regaining tooth function. However, PDLSCs residing in an inflammatory environment generally exhibit compromised functions, as demonstrated by an impaired ability to differentiate into cementoblasts, which are responsible for regrowing the cementum. This study investigated the role of mitochondrial function and downstream long noncoding RNAs (lncRNAs) in regulating inflammation-induced changes in the cementogenesis of PDLSCs. We found that the inflammatory cytokine-induced impairment of the cementogenesis of PDLSCs was closely correlated with their mitochondrial function, and lncRNA microarray analysis and gain/loss-of-function studies identified GACAT2 as a regulator of the cellular events involved in inflammation-mediated mitochondrial function and cementogenesis. Subsequently, a comprehensive identification of RNA-binding proteins by mass spectrometry (ChIRP-MS) and parallel reaction monitoring (PRM) assays revealed that GACAT2 could directly bind to pyruvate kinase M1/2 (PKM1/2), a protein correlated with mitochondrial function. Further functional studies demonstrated that GACAT2 overexpression increased the cellular protein expression of PKM1/2, the PKM2 tetramer and phosphorylated PKM2, which led to enhanced pyruvate kinase (PK) activity and increased translocation of PKM2 into mitochondria. We then found that GACAT2 overexpression could reverse the damage to mitochondrial function and cementoblastic differentiation of PDLSCs induced by inflammation and that this effect could be abolished by PKM1/2 knockdown. Our data indicated that by binding to PKM1/2 proteins, the lncRNA GACAT2 plays a critical role in regulating mitochondrial function and cementogenesis in an inflammatory environment. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Central South University is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The seismic design of gravity retaining walls is based mostly on the pseudo static method. The seismic earth pressure is assumed to be a constant without considering the wave traveling effect when the seismic wave propagates through the slope. However, under continuous ground motion, the actual earth pressure on the retaining wall varies with time. The present seismic earth pressure calculation method yields results that differ significantly from the actual scenario. Considering this, a slip surface curve was assumed in this study. It is more suitable for engineering practice. In addition, a theoretical calculation model based on energy dissipation was established. The time history of seismic earth pressure response under continuous ground motion was calculated using the equilibrium equation between the external power and the internal energy dissipation power of the sliding soil wedge. It can more effectively reflect the stress scenario of a retaining wall under seismic conditions. To verify the applicability of the proposed approach, a large-scale shaking table test was conducted, and the time history of the seismic earth pressure response obtained from the experiment was compared with the calculation results. The results show that the proposed approach is applicable to the calculation of the time history of seismic earth pressure response of gravity retaining walls. This lays the foundation for the seismic design of retaining structures by using dynamic time history. [ABSTRACT FROM AUTHOR]

The currently predominant token-to-token attention mechanism has demonstrated its ability to capture word dependencies in neural machine translation. This mechanism treats a sequence as bag-of-words tokens and compute the similarity between tokens without considering their intrinsic interactions. In this paper, we argue that this attention mechanism may miss opportunity of take advantage of the state information through multiple time steps. Thus, we propose a Gated State Network which manipulates the state information flow with sequential characteristics. We also incorporate a Focal Adaptive Attention Network which utilizes a Gaussian distribution to concentrate the attention distribution to a predicted focal position and its neighborhood. Experimental results on WMT'14 English–German and WMT'17 Chinese–English translation tasks demonstrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Diagnosing Alzheimer's Disease (AD) in older people using magnetic resonance imaging (MRI) is quite hard since it requires the extraction of highly discriminative feature representation from similar brain patterns and pixel intensities. However, deep learning techniques possess the capability of extracting relevant representations from data. In this work, we designed a novel spiking deep convolutional neural network-based pipeline to classify AD using MRI scans. We considered three MRI scan groups (patients with AD dementia, Mild Cognitive Impairment (MCI), and healthy controls (NC)). We developed a three-binary classification task (AD vs. NC, AD vs. MCI, and NC vs. MCI) for the AD classification tasks. Specifically, an unsupervised convolutional Spiking Neural Networks (SNN) is pre-trained on the MRI scans. Finally, a supervised deep Convolution Neural Network (CNN) is trained on the output of the SNN for the classification tasks. Experiments are performed using the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, and promising results are obtained for the AD classification tasks. We present our proposed model results for both the unsupervised spike pre-training technique and the case where the pre-training technique was not considered, thus serving as a baseline. The accuracy of the proposed model with spike pre-training techniques for the three-binary classification are 90.15%, 87.30%, and 83.90%, respectively, and the accuracy of the model without the spike are 86.90%, 83.25%, and 76.70%, respectively, with a noticeable increase in accuracy and thus, reveals the effectiveness of the proposed method. We also evaluated the robustness of our proposed approach by running experiment on six baseline methods using our preprocessed MRI scans. Our model outperformed almost all the comparable methods due to the robust discriminative capability of the SNN in extracting relevant AD features for the AD classification task. [ABSTRACT FROM AUTHOR]

With only global image-level annotations, weakly supervised learning of deep convolutional neural networks has shown enough capacity in classification and localization but lack of ability to present the detection explicitly. In this work, we propose a novel spatial division network, which is applied to detect bounding boxes only with weak supervision. The essence of our model is two innovative differentiable modules, determination network and parameterized division, which perform the spatial division in feature maps of classification networks. After training, the learned parameters of the spatial division would correspond to a set of predicted bounding box coordinates. To demonstrate the effectiveness of our model for multi-label classification and weakly supervised detection, we conduct extensive experiments on the multi-MNIST dataset. Experimental results show our spatial division networks can (1) help improve the accuracy of multi-label classification, (2) implement in an end-to-end way only with the image-level annotations, and (3) output accurate bounding box coordinate, thereby achieving multi-digits detection. [ABSTRACT FROM AUTHOR]

Purpose: We detected the DNA of herpes simplex virus type 1 (HSV-1), herpes simplex virus type 2 (HSV-2), varicella-zoster virus (VZV), cytomegalovirus (CMV), and Epstein-Barr virus (EBV) in donor corneas and assessed the clinical outcomes of recipients who received virus-positive grafts. Method: All donor corneas were analyzed for the presence of HSV-1, HSV-2, VZV, CMV, and EBV by real-time PCR from April 2017 to July 2019. The medical records of the transplant patients who received virus-positive grafts were reviewed. Result: Twenty-three (2.44%) donor cornea buttons tested positive for herpesviridae DNA. The positivity rates of HSV-1, CMV, VZV, and EBV were 0.74%, 0.85%, 0.64%, and 0.21%, respectively. Conclusion: We suggest that the corneas from donors who had cancer, donors who were inpatients, and donors who had immunodeficiency or who were on immunosuppressive therapy should be tested for herpesviridae DNA before transplantation. Finally, HSV-1 can be transmitted from graft to recipient, but that CMV cannot be transmitted according to our observations. The donor corneas found to be HSV-1-positive have to be discarded and not used for keratoplasty. [ABSTRACT FROM AUTHOR]

In response to cytosolic DNA, stimulator of interferon gene (STING) initiates and orchestrates host's innate immunity by inducing type I interferon. Since endometriosis is a chronic inflammatory disorder, we sought to determine whether STING pathway is activated in ectopic endometrium in comparison to eutopic endometrium. Immunohistochemistry was employed in evaluating the expression levels of STING in normal endometrium, endometriosis, and adenomyosis. The density of CD45+ intraepithelial lymphocytes was correlated with STING expression levels. A total of 39 cases of endometriosis and/or adenomyosis with normal endometrium were analyzed. Among them, 32 had adenomyosis, 26 had endometriosis, and 19 have both lesions. STING protein expression is mainly evident in the cytoplasm of epithelial cells but much less in stromal cells. Based on H-score, we found that the STING expression levels were significantly higher in the epithelial cells of adenomyosis and endometriosis than in eutopic endometrium (132.7 ± 12.20, 119.6 ± 12.57 vs. 19.74 ± 5.96, p < 0.0001). There was no significant difference in STING expression level between endometriosis and adenomyosis. More intraepithelial lymphocytes were detected in endometriosis and adenomyosis lesions than endometrium (5.60 ± 0.70%, 4.95 ± 0.54% vs. 1.25 ± 0.12%, p < 0.0001). A positive correlation between STING expression and intraepithelial lymphocytic infiltrate was observed (p < 0.0001). In summary, STING was upregulated in the epithelium of ectopic endometrium as compared to eutopic endometrium. Its expression levels correlate with the degree of intraepithelial lymphocyte infiltration, suggesting a role in promoting chronic inflammation of ectopic endometrium. [ABSTRACT FROM AUTHOR]

Tight sandstone gas (hereafter "tight gas") has become a subject of unconventional gas exploration globally. The large-scale development and use of tight gas resources in the USA, in particular, facilitated the rapid rebound of natural gas production in the USA, in addition to driving the rapid development of tight gas worldwide. In the eastern Ordos Basin, the Upper Paleozoic feature includes multiple layers of gas, a shallow depth, and notable potential for exploration and development. However, the reservoirs in the area are relatively tight, exhibit strong heterogeneity, and possess a complex micropore structure, thus restricting the effective economic development of oil and gas. Thus, research on the primary parameters controlling pore throat structure and the seepage capability of low-permeability reservoirs will be beneficial for the efficient exploration and development of natural gas in the eastern Ordos Basin. The parameters of reservoir porosity and percolation ability, as well as permeability, were analyzed using systematic sampling of the of the Upper Paleozoic Benxi, Taiyuan, and Shanxi Formations in the eastern Ordos Basin, constant-rate mercury injection experiments, nuclear magnetic resonance analysis, and gas–water-phase experimental studies. The results indicate that reservoir porosity is controlled by the effective pore volume and number, whereas permeability is controlled by the largest throat radius, rather than the average. The effective pore volume controls the movable fluid saturation, while reservoir percolation capability is controlled by the effective pore volume, irreducible water saturation, and size of the gas–water two-phase seepage zone. [ABSTRACT FROM AUTHOR]

As the third generation of neural networks, Spiking Neural Networks (SNNs) have made great success in pattern recognition fields. However, the existing training methods for SNNs are not efficient enough because of the temporal encoding mechanism. To improve the training efficiency of the supervised SNNs and keep the useful temporal information, the Maximum Points-based Supervised Learning Rule (MPSLR) is proposed in this paper. Three training strategies are adopted in MPSLR to improve the learning performance. Firstly, only the target points and maximum voltage points are trained. By theoretical analyses, we find that the maximum points are effective for the voltage controlling of the non-target points, and the analytic solutions for all maximum voltage points are parallelly obtainable. This improves the training efficiency significantly by avoiding the successive voltage detecting. Secondly, the weight modification for each presynaptic neuron is normalized by a rate function to resizing the output scale. Thirdly, the spiking rates accumulated in a time window are utilized to involve more useful knowledge. Extensive experiments on both synthetic data and four real-world UCI datasets demonstrate that our algorithm achieves significantly better performance and higher efficiency than traditional methods in various situations, including different multi-spike rates and time lengths. Besides, it is more stable to hyper-parameter variations. [ABSTRACT FROM AUTHOR]

Two kinds of activated carbon spheres (ACS)-supported metal oxides, ACS-supported Fe3O4 (ACS@Fe3O4) and ACS-supported NiO (ACS@NiO), were synthesized and used as flame retardants for reducing smoke release volume and fire hazard in flexible poly(vinyl chloride) (PVC). Scanning electron microscope measurement, Fourier transform infrared spectrum, X-ray diffraction and thermogravimetric analysis (TGA) were utilized to investigate the morphology, chemical structure and stability of the flame retardants. The TGA coupled with mass spectrometry (TG-MS) results of PVC composites showed that ACS could retard the heat and oxygen transfer between gas and polymers. Under the same condition, ACS@Fe3O4 could promote the dehydrochlorination reaction of PVC in lower temperature, while the ACS@NiO could make the dehydrochlorination reaction faster. Therefore, both ACS@Fe3O4 and ACS@NiO effectively promoted the cross-linked carbonization reaction of PVC and then generated a large amount of stable char residues. Limiting oxygen index (LOI) and cone calorimeter test results of the PVC composites showed that ACS@Fe3O4 and ACS@NiO were much more efficient than ACS alone to improve the flame retardancy and smoke suppression of PVC. The incorporation of ACS@Fe3O4 and ACS@NiO increased the LOI from 24.9 to 27.4% and 26.9% and reduced the peak of heat release rate by 47.2 and 30.8%, respectively, compared with pure PVC. [ABSTRACT FROM AUTHOR]

In order to suppress complex mixing noise in low-illumination images for wide-area search of nighttime sea surface, a model based on total variation (TV) and split Bregman is proposed in this paper. A fidelity term based on L1 norm and a fidelity term based on L2 norm are designed considering the difference between various noise types, and the regularization mixed first-order TV and second-order TV are designed to balance the influence of details information such as texture and edge for sea surface image. The final detection result is obtained by using the high-frequency component solved from L1 norm and the low-frequency component solved from L2 norm through wavelet transform. The experimental results show that the proposed denoising model has perfect denoising performance for artificially degraded and low-illumination images, and the result of image quality assessment index for the denoising image is superior to that of the contrastive models. [ABSTRACT FROM AUTHOR]

In order to achieve high quality images with time-delayed integration (TDI) charge-coupled device (CCD) imaging system, an improved adaptive preprocessing method is proposed with functions of both denoising and edge enhancement. It is a weighted average filter integrating the average filter and the improved range filter. The weighted factors are deduced in terms of a cost function, which are adjustable to different images. To validate the proposed method, extensive tests are carried out on a developed TDI CCD imaging system. The experimental results confirm that this preprocessing method can fulfill the noise removal and edge sharpening simultaneously, which can play an important role in remote sensing field. [ABSTRACT FROM AUTHOR]

During the new product development process, reusing the existing CAD models could avoid designing from scratch and decrease human cost. With the advent of big data, how to rapidly and efficiently find out suitable 3D CAD models for design reuse is taken more attention. Currently the sketch-based retrieval approach makes search more convenient, but its accuracy is not high enough; on the other hand, the semantic-based retrieval approach fully utilizes high level semantic information, and makes search much closer to engineers' intent. However, effectively extracting and representing semantic information from data sets is difficult. Aiming at these problems, we proposed a sketch-based semantic retrieval approach for reusing 3D CAD models. Firstly a fine granularity semantic descriptor is designed for representing 3D CAD models; Secondly, several heuristic rules are adopted to recognize 3D features from 2D sketch, and the correspondences between 3D feature and 2D loops are built; Finally, semantic and shape similarity measurements are combined together to match the input sketch to 3D CAD models. Hence the retrieval accuracy is improved. A sketch-based prototype system is developed. Experimental results validate the feasibility and effectiveness of our proposed approach. [ABSTRACT FROM AUTHOR]

Many biological conservationists take actions to conserve plant species with extremely small populations (PSESP) in China; however, there have been few studies on the spatial distribution of threats to PSESP. Hence, we selected distribution data of PSESP and made a map of the spatial distribution of threats to PSESP in China. First, we used the weight assignment method to evaluate the threat risk to PSESP at both country and county scales. Second, we used a geographic information system to map the spatial distribution of threats to PSESP, and explored the threat factors based on linear regression analysis. Finally, we suggested some effective conservation options. We found that the PSESP with high values of protection, such as the plants with high scientific research values and ornamental plants, were threatened by over-exploitation and utilization, habitat fragmentation, and a small sized wild population in broad-leaved forests and bush fallows. We also identified some risk hotspots for PSESP in China. Regions with low elevation should be given priority for ex- and in-situ conservation. Moreover, climate change should be considered for conservation of PSESP. To avoid intensive over-exploitation or utilization and habitat fragmentation, in-situ conservation should be practiced in regions with high temperatures and low temperature seasonality, particularly in the high risk hotspots for PSESP that we proposed. Ex-situ conservation should be applied in these same regions, and over-exploitation and utilization of natural resources should be prevented. It is our goal to apply the concept of PSESP to the global scale in the future. [ABSTRACT FROM AUTHOR]

Background: Colon cancer nomogram designed by Memorial Sloan-Kettering Cancer Center (MSKCC) is an online prediction tool to predict overall survival for individual patient after curative resection. However, this model was never externally validated. We evaluated the accuracy of this nomogram in an independent external Chinese cohort. Methods: Clinical data from 1005 patients who underwent primary curative-intent surgery at Peking University Cancer Hospital & Institute between 1996 and 2008 were used for external validation. Clinicopathologic characteristics and the performance of the MSKCC nomogram for prediction of overall survival were evaluated for 985 patients with complete data by using concordance index (C-index) and calibration plot. Results: The C-index for the MSKCC nomogram was 0.71 in the Chinese cohort, compared with 0.67 for American Joint Committee on Cancer (AJCC) stage ( P < .0001). This suggests that the nomogram discriminates overall survival better than AJCC staging system. Calibration plot showed a good calibration of the nomogram in the validation cohort. Furthermore, the MSKCC nomogram prediction illustrated the heterogeneity for survival of Chinese patients within each AJCC stage. Conclusions: The MSKCC nomogram for colon cancer provides more accurate survival predictions than the AJCC staging system when applied to an external Chinese cohort. The MSKCC nomogram improved individualized prediction of survival and may aid in more accurate patient counseling, selection of various treatment options, and follow-up scheduling. [ABSTRACT FROM AUTHOR]

The single-pair K shortest path (KSP) problem can be described as finding $$k$$ least cost paths through a graph between two given nodes in a non-decreasing order, while single-source KSP algorithms aim to find KSPs from a given node to each other node. However, little effort has been devoted to the single-source KSP approaches. This paper proposes a novel single-source KSP algorithm in a given directed weighted graph where loops are allowed. The proposed method is designed to compute a set of shortest paths with exactly $$k$$ distinctive lengths in a non-decreasing order. Meanwhile, it can also find all shortest paths with the length less than a given threshold. Inspired by water flowing principle, we imagine that there are waters flowing from a source node to each other node along edges at a constant speed. When the water reaches a node, the node will generate new waters flowing along its outgoing edges. By stepping back the traces of the water, the ordered shortest paths can be obtained. We also address the correctness and effectiveness of the method. Simulations are carried out using synthetic data and practical graph data, which demonstrate the considerable performance of the proposed approach especially for single-source KSP problems. [ABSTRACT FROM AUTHOR]

The discovery of functional cannabinoid receptors 2 (CB2Rs) in brain suggests a potential new therapeutic target for neurological and psychiatric disorders. However, recent findings in experimental animals appear controversial. Here we report that there are significant species differences in CB2R mRNA splicing and expression, protein sequences, and receptor responses to CB2R ligands in mice and rats. Systemic administration of JWH133, a highly selective CB2R agonist, significantly and dose-dependently inhibited intravenous cocaine self-administration under a fixed ratio (FR) schedule of reinforcement in mice, but not in rats. However, under a progressive ratio (PR) schedule of reinforcement, JWH133 significantly increased breakpoint for cocaine self-administration in rats, but decreased it in mice. To explore the possible reasons for these conflicting findings, we examined CB2R gene expression and receptor structure in the brain. We found novel rat-specific CB2C and CB2D mRNA isoforms in addition to CB2A and CB2B mRNA isoforms. In situ hybridization RNAscope assays found higher levels of CB2R mRNA in different brain regions and cell types in mice than in rats. By comparing CB2R-encoding regions, we observed a premature stop codon in the mouse CB2R gene that truncated 13 amino-acid residues including a functional autophosphorylation site in the intracellular C-terminus. These findings suggest that species differences in the splicing and expression of CB2R genes and receptor structures may in part explain the different effects of CB2R-selective ligands on cocaine self-administration in mice and rats. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Acupuncture & Tuina Science is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objective: To observe the clinical effect of tuina reduction manipulation on leg length discrepancy and lumbosacral pain due to sacroiliac joint subluxation. Methods: A total of 60 eligible cases were randomly allocated into an observation group and a control group, 30 in each group. Cases in the observation group were treated with conventional tuina plus reduction manipulation of sacroiliac joint subluxation; whereas cases in the control group were treated with conventional tuina plus acupuncture. The clinical effects were observed after 10 times of treatment. In addition, the relapse rates were observed 2 months after treatment. Results: The total effective rate in the observation group was 80.0%, versus 50.0% in the control group, showing a statistically significant difference ( P<0.05). The relapse rate of lumbosacral pain in the observation group was 12.5%, versus 66.7% in the control group, showing a statistically significant difference ( P<0.01). The relapse rate of leg length discrepancy in the observation group was 16.7%, versus 80.0% in the control group, showing a statistically significant difference ( P<0.01). Conclusion: Tuina reduction manipulation can obtain substantial therapeutic effect for leg length discrepancy and lumbosacral pain due to sacroiliac joint subluxation, coupled with a low relapse rate. [ABSTRACT FROM AUTHOR]

The relationship between tyrosine phosphorylation (TP) and protein expression of insulin receptor (InsR) and insulin resistance (IR) in patients with gestational diabetes mellitus (GDM) was investigated. The InsR expression and TP in skeleton muscle tissue were determined by Western blotting and immunoprecipitation in women with GDM (GDM group, n=22), normal pregnant women (normal pregnancy group, n=22) and normal non-pregnant women (normal non-pregnant group, n=13). Fasting plasma glucose (FPG) and fasting insulin (FINS) were measured by oxidase assay and immunoradioassay. The results showed that the levels of FPG (5.61±0.78 mmol/L), FINS (15.42±5.13 mU/L) and Homeostasis model assessment-IR (HOMA-IR) (1.21±0.52) in GDM group were significantly higher than those in normal pregnancy group (4.43±0.46 mmol/L, 10.56±3.07 mU/L and 0.80±0.31 respectively) ( P<0.01). The levels of FINS and HOMA-IR in normal pregnancy group were significantly higher than those in normal non-pregnant group (7.56±2.31 mU/L and 0.47±0.26 respectively) ( P<0.01). There was no significant difference in the InsR expression level among the three groups ( P>0.05). TP of InsR with insulin stimulation was significantly decreased in GDM group (0.20±0.05) as compared with normal pregnancy group (0.26±0.06) ( P<0.01). TP of InsR with insulin stimulation in normal pregnancy group was lower than that in normal non-pregnant group (0.31±0.06) ( P<0.01). TP of InsR with insulin stimulation was negatively related with HOMA-IR in GDM group ( r=−0.525, P<0.01). There was no correlation between the protein expression of InsR and HOMA-IR in GDM group ( r=−0.236, P>0.05). It was suggested that there is no significant correlation between the protein expression of InsR in skeletal muscle and IR in GDM, but changes in TP of InsR are associated with IR in GDM. [ABSTRACT FROM AUTHOR]

Eating disorder is a group of physiological and psychological disorders affecting approximately 1% of the female population worldwide. Although the genetic epidemiology of eating disorder is becoming increasingly clear with accumulated studies, the underlying molecular mechanisms are still unclear. Recently, integration of various high-throughput data expanded the range of candidate genes and started to generate hypotheses for understanding potential pathogenesis in complex diseases. This article presents EDdb (Eating Disorder database), the first evidence-based gene resource for eating disorder. Fifty-nine experimentally validated genes from the literature in relation to eating disorder were collected as the core dataset. Another four datasets with 2824 candidate genes across 601 genome regions were expanded based on the core dataset using different criteria (e.g., protein-protein interactions, shared cytobands, and related complex diseases). Based on human protein-protein interaction data, we reconstructed a potential molecular sub-network related to eating disorder. Furthermore, with an integrative pathway enrichment analysis of genes in EDdb, we identified an extended adipocytokine signaling pathway in eating disorder. Three genes in EDdb ( ADIPO (adiponectin), TNF (tumor necrosis factor) and NR3C1 (nuclear receptor subfamily 3, group C, member 1)) link the KEGG (Kyoto Encyclopedia of Genes and Genomes) “adipocytokine signaling pathway” with the BioCarta “visceral fat deposits and the metabolic syndrome” pathway to form a joint pathway. In total, the joint pathway contains 43 genes, among which 39 genes are related to eating disorder. As the first comprehensive gene resource for eating disorder, EDdb ( http://eddb.cbi.pku.edu.cn ) enables the exploration of gene-disease relationships and cross-talk mechanisms between related disorders. Through pathway statistical studies, we revealed that abnormal body weight caused by eating disorder and obesity may both be related to dysregulation of the novel joint pathway of adipocytokine signaling. In addition, this joint pathway may be the common pathway for body weight regulation in complex human diseases related to unhealthy lifestyle. [ABSTRACT FROM AUTHOR]

Rodent models of Huntington disease (HD) are valuable tools for investigating HD pathophysiology and evaluating new therapeutic approaches. Non-invasive characterization of HD-related phenotype changes is important for monitoring progression of pathological processes and possible effects of interventions. The first transgenic rat model for HD exhibits progressive late-onset affective, cognitive, and motor impairments, as well as neuropathological features reflecting observations from HD patients. In this report, we contribute to the anatomical phenotyping of this model by comparing high-resolution ex vivo DTI measurements obtained in aged transgenic HD rats and wild-type controls. By region of interest analysis supplemented by voxel-based statistics, we find little evidence of atrophy in basal ganglia regions, but demonstrate altered DTI measurements in the dorsal and ventral striatum, globus pallidus, entopeduncular nucleus, substantia nigra, and hippocampus. These changes are largely compatible with DTI findings in preclinical and clinical HD patients. We confirm earlier reports that HD rats express a moderate neuropathological phenotype, and provide evidence of altered DTI measures in specific HD-related brain regions, in the absence of pronounced morphometric changes. [ABSTRACT FROM AUTHOR]

A high speed steel (HSS) was studied for rollers in this work. The steel was quenched at 1150°C and tempered at 520°C. The phase structures of the steel were determined by X-ray diffraction (XRD), and the hardness of specimens was measured. The volume fraction of carbides was counted by Image-Pro Plus software. The typical microstructures were observed by field emission scanning electron microscope (FESEM). Stable and meta-stable carbides were deduced by removing the existing phases one by one in the Fe-C equilibrium calculation. It is found that the precipitated carbides are bulk-like MC, long stripe-like MC, fishbone-like MC, and daisy-like MC during the tempering process. The stable carbides are MC and MC, but the meta-stable ones are MC, MC, and MC. [ABSTRACT FROM AUTHOR]

In order to obtain the additional benefit of anti-diabetic activity and protective effects of liver injury for diabetes, the anti-diabetic effect and acute oral toxicity of a combination of chromium(III) malate complex (Cr(LMA)) and propolis were assessed. The anti-diabetic activity of the combination of the CrLMA and propolis was compared with Cr(LMA) and propolis alone in alloxan-induced diabetic mice by daily oral gavage for a period of 2 weeks. Acute oral toxicity of the combination of the CrLMA and propolis was tested using ICR mice at the dose of 1.0-5.0 g/kg body mass by a single oral gavage and observed for a period of 2 weeks. The results of the anti-diabetic activity of the combination from the aspects of blood glucose level, liver glycogen level, and the activities of aspartate transaminase, alanine transaminase, and alkaline phosphatase indicated that the increased anti-diabetic activity and the protective efficacy of liver injury for diabetes were observed. In acute toxicity study, LD (median lethal dose) value for the combination was greater than 5.0 g/kg body mass. The combination of CrLMA and propolis might represent the nutritional supplement with potential therapeutic value to control blood glucose and exhibit protective efficacy of liver injury for diabetes and non-toxicity in acute toxicity. [ABSTRACT FROM AUTHOR]

Purpose: Changes in cerebral glucose metabolism may be an early prognostic indicator of perinatal hypoxic-ischaemic injury. In this study dynamic F-FDG PET was used to evaluate cerebral glucose metabolism in piglets after global perinatal hypoxia and the impact of the resuscitation strategy using room air or hyperoxia. Methods: New-born piglets ( n = 16) underwent 60 min of global hypoxia followed by 30 min of resuscitation with a fraction of inspired oxygen (FiO) of 0.21 or 1.0. Dynamic FDG PET, using a microPET system, was performed at baseline and repeated at the end of resuscitation under stabilized haemodynamic conditions. MRI at 3 T was performed for anatomic correlation. Global and regional cerebral metabolic rates of glucose (CMR) were assessed by Patlak analysis for the two time-points and resuscitation groups. Results: Global hypoxia was found to cause an immediate decrease in cerebral glucose metabolism from a baseline level (mean ± SD) of 21.2 ± 7.9 to 12.6 ± 4.7 μmol/min/100 g ( p <0.01). The basal ganglia, cerebellum and cortex showed the greatest decrease in CMR but no significant differences in global or regional CMR between the resuscitation groups were found. Conclusion: Dynamic FDG PET detected decreased cerebral glucose metabolism early after perinatal hypoxia in piglets. The decrease in CMR may indicate early changes of mild cerebral hypoxia-ischaemia. No significant effect of hyperoxic resuscitation on the degree of hypometabolism was found in this early phase after hypoxia. Cerebral FDG PET can provide new insights into mechanisms of perinatal hypoxic-ischaemic injury where early detection plays an important role in instituting therapy. [ABSTRACT FROM AUTHOR]

We analyzed past and future trends in river export of dissolved nitrogen (N) and phosphorus (P) to the coastal waters of China, for a selection of rivers, as calculated by the Global NEWS models (Nutrient Export from WaterSheds). Over the period 1970-2000, river export of dissolved nutrients increased considerably, especially of dissolved inorganic N and P. Anthropogenic sources of N and P in rivers have become increasingly important, in particular N and P losses from agriculture. We tested the sensitivity of calculated nutrient export by rivers to changes in selected controlling factors. The calculated export of dissolved N and P is sensitive to changes in hydrology, synthetic fertilizer use and manure excretion in river basins. Changes in sewage inputs have large effects on dissolved inorganic P export. We analyzed future trends up to 2050 for several scenarios to illustrate the combined effects of selected management options. In the Base Scenario, the N and P export by the selected rivers increases considerably between 2000 and 2030. The increase continues from 2030 to 2050 except for DIP. Strategies to reduce N and P export by rivers include changes in agriculture, sewage and energy use. Changes in agriculture have the largest impact on future dissolved N and P river export to the coastal waters of China. The effectiveness of reduction strategies differs between nutrient forms and basins. [ABSTRACT FROM AUTHOR]

TSdb () is the first manually curated central repository that stores formatted information on the substrates of transporters. In total, 37608 transporters with 15075 substrates from 884 organisms were curated from UniProt functional annotation. A unique feature of TSdb is that all the substrates are mapped to identifiers from the KEGG Ligand compound database. Thus, TSdb links current metabolic pathway schema with compound transporter systems via the shared compounds in the pathways. Furthermore, all the transporter substrates in TSdb are classified according to their biochemical properties, biological roles and subcellular localizations. In addition to the functional annotation of transporters, extensive compound annotation that includes inhibitor information from the KEGG Ligand and BRENDA databases has been integrated, making TSdb a useful source for the discovery of potential inhibitory mechanisms linking transporter substrates and metabolic enzymes. User-friendly web interfaces are designed for easy access, query and download of the data. Text and BLAST searches against all transporters in the database are provided. We will regularly update the substrate data with evidence from new publications. [ABSTRACT FROM AUTHOR]

Urea combustion method was adopted to prepare precursor powder, MCeO3 doped with Zr (M is alkaline earth element, such as barium, strontium, and calcium). The precursor powder has typically perovskite structure after being calcined at 873 K. In 773 K∼1,273 K, BaCe0.425Zr0.475Y0.1O3 has the highest conductivity above 10−2 S cm−1 and good chemical stability, while the phase transition may exist in H2S atmosphere for the proton conductors. In the single fuel cell composed of MoS2-BaCe0.425Zr0.475Y0.1O3-σ-Ag with BaCe0.425Zr0.475Y0.1O3-σ as electrolyte, the best performance is obtained. The open circuit voltage of fuel cell is all about 0.72 V, the max power density, 1.55 mW cm−2. The performance drop is attributed to ohmic loss resulting from the separation of electrolyte and electrode, and improvement is required to bring out new anode materials compatible to the proton conductor, BaCe0.425Zr0.475Y0.1O3-σ, as electrolyte. [ABSTRACT FROM AUTHOR]