Higher-order accurate two-sample network inference and network hashing

Two-sample hypothesis testing for comparing two networks is an important yet difficult problem. Major challenges include: potentially different sizes and sparsity levels; non-repeated observations of adjacency matrices; computational scalability; and theoretical investigations, especially on finite-sample accuracy and minimax optimality. In this article, we propose the first provably higher-order accurate two-sample inference method by comparing network moments. Our method extends the classical two-sample t-test to the network setting. We make weak modeling assumptions and can effectively handle networks of different sizes and sparsity levels. We establish strong finite-sample theoretical guarantees, including rate-optimality properties. Our method is easy to implement and computes fast. We also devise a novel nonparametric framework of offline hashing and fast querying particularly effective for maintaining and querying very large network databases. We demonstrate the effectiveness of our method by comprehensive simulations. We apply our method to two real-world data sets and discover interesting novel structures

Geochemical Evidence for Hydration and Dehydration of Crustal Rocks During Continental Rifting

To understand the temporal sequence of geological processes such as magmatism, water‐rock interaction, and metamorphism in fossil continental rifts, a combined study of petrography, mineral geochemistry, in situ garnet O isotopes, in situ zircon U‐Pb ages and O isotopes, and pseudosection calculations was conducted for metagranites from a Neoproterozoic continental rift generated during the Rodinia breakup. The results provide insights into the operation of hydration and dehydration during continental rifting. In the metagranites from the northern margin of South China, three types of garnet (Garnet‐I to ‐III) are distinguished. They were sequentially produced by hydrothermal alteration, metamorphic dehydration, and fluid metasomatism. All of these garnets show negative δ18O values of −19.3‰ to −14.5‰, in contrast to mantle‐like δ18O values for magmatic zircon. The extremely negative δ18O values of hydrothermal Garnet‐I require infiltration of the continental deglacial meltwater during the continental rifting, and before that zircon crystallized from normal δ18O magmas. Once the rocks were hydrothermally altered, the extreme 18O depletion was retained in all later products such as metamorphic Garnet‐II and metasomatic Garnet‐III. Pseudosection calculations indicate that the metamorphic dehydration occurred at 1.0–3.0 kbar and 630–690 °C during a reheating stage, corresponding to high thermal gradients of >60 °C/km. The high‐temperature/low‐pressure metamorphic rocks produced by such high thermal gradients are indicative of the continental rift setting. The mineral geochemistry records not only the temporal sequence of rift magmatism, water‐rock interaction, and rift metamorphism but also the evolution of temperature and water action in the crust during the continental rifting

Inflammation and nerve injury induce expression of pancreatitis-associated protein-II in primary sensory neurons

Pancreatitis-associated protein (PAP)-I and -II, lectin-related secretory proteins, are members of the regenerating gene (Reg) family. Although expression of PAP-I was found in the dorsal root ganglion (DRG) neurons following peripheral nerve injury and cystitis, whether PAP-II could be expressed in DRG neurons in chronic pain models remains unclear. The present study shows an inflammation- and nerve injury-triggered expression of PAP-II in rat DRG neurons. In situ hybridization showed that only a few DRG neurons normally contained PAP-I and -II mRNAs. After peripheral inflammation, PAP-I and -II mRNAs were present in over half of small DRG neurons. Such an elevated expression of PAP-I and -II reached the peak level on the second day. Immunostaining showed that the expression of PAP-II was mostly increased in the isolectin B4-positive subset of small DRG neurons after inflammation. Furthermore, the expression of PAP-II was also induced in DRG neurons after peripheral nerve injury. Interestingly, PAP-II expression was shifted from small neurons on day 2 to large DRG neurons that expressed neuropeptide Y during the later post-injury days. These results suggest that PAP-II may play potential roles in the modulation of spinal sensory pathways in pathological pain states

Epstein-Barr virus encoded latent membrane protein 1 regulates mTOR signaling pathway genes which predict poor prognosis of nasopharyngeal carcinoma

<p>Abstract</p> <p>Background</p> <p>The oncoprotein Epstain-Barr Virus (EBV)-encoded latent membrane protein1 (LMP1) modulates the pathological effects of the NF-κB, AP-1 and JAK/STAT pathways in nasopharyngeal carcinoma (NPC).</p> <p>Methods</p> <p>Microarray analysis was performed on the NPC cell line HONE1 stably transfected with a LMP1-expression plasmid or an empty vector. Based on assigned pathways analyzed using the KEGG database, the mTOR signaling pathway was selected for verification by quantitative RT-PCR. Western blot, RNA interference and immunofluorescence were used to determine the relationship between LMP1 and mTOR signing pathway genes, and their clinical significance to NPC.</p> <p>Results</p> <p>Our studies revealed that overexpression of LMP1 upregulated the mTOR signaling pathway, possibly through phosphorylation of AKT/mTOR/P70S6K/4EBP1 in the NPC cell lines HONE1 and 6-10B. Knockdown of LMP1 reduced expression of p-mTOR and p-4EBP1 in EBV-positive NPC cell line C666-1. In addition, LMP1 expression closely correlated with expression of p-mTOR, p-P70S6K and p-4EBP1 in NPC tumors. Expression of p-P70S6K, p-4EBP1 and LMP1, but not p-mTOR, significantly correlated with overall survival of NPC patients. However, only LMP1 was an independent prognostic factor.</p> <p>Conclusions</p> <p>These results suggest that the mTOR signaling pathway is regulated by LMP1 expression in NPC. LMP1 and the genes in the mTOR pathway such as p-P70S6K and p-4EBP1 may be potential prognostic biomarkers.</p

Secreted protein acidic and rich in cysteine (SPARC) is associated with nasopharyngeal carcinoma metastasis and poor prognosis

<p>Abstract</p> <p>Background</p> <p>The aim of the present study was to analyse the expression of Secreted protein acidic and rich in cysteine (SPARC) in nasopharyngeal carcinoma (NPC) specimens, and to evaluate its correlation with clinicopathologic features, including survival of patients with NPC</p> <p>Methods</p> <p>NPC tissue microarrays (TMAs) were constructed from Sun Yat-sen University Cancer Center (SYSUCC), another three centers on mainland China, Singapore and Hong Kong. Using quantitative RT-PCR and Western-blotting techniques, we detected mRNA and protein expression of SPARC in NPC cell lines and immortalized nasopharyngeal epithelial cells (NPECs) induced by Bmi-1 (NPEC2 Bmi-1). The difference of SPARC expression in the cell lines was tested using a <it>t</it>-test method. The relationship between the SPARC expression and clinicopathological data was assessed by chi-square. Survival analysis was estimated using the Kaplan-Meier approach with log-rank test. Univariate and multivariate analyses of clinical variables were performed using Cox proportional hazards regression models.</p> <p>Results</p> <p>The expression levels of SPARC mRNA and protein were markedly higher in NPC cell lines than in NPEC2 Bmi-1. Especially, the expression levels of SPARC mRNA and protein were much lower in the 6-10B than in the 5-8 F (<it>P </it>= 0.002, <it>P </it>= 0.001). SPARC immunostaining revealed cytoplasmic localization in NPC cells and no staining in the stroma and epithelium.</p> <p>In addition, high level of SPARC positively correlated with the status of distant metastasis (<it>P </it>= 0.001) and WHO histological classification (<it>P </it>= 0.023). NPC patients with high SPARC expression also had a significantly poorer prognosis than patients with low SPARC expression (log-rank test, <it>P </it>< 0.001), especially patients with advanced stage disease (log-rank, <it>P </it>< 0.001). Multivariate analysis suggested that the level of SPARC expression was an independent prognostic indicator for the overall survival of patients with NPC (<it>P </it>< 0.001).</p> <p>Conclusions</p> <p>SPARC expression is common in NPC patients. Our data shows that elevated SPARC expression is a potential unfavorable prognostic factor for patients with NPC.</p

Quantum and classical correlations in the one-dimensional XY model with Dzyaloshinskii-Moriya interaction

We study the effect of Dzyaloshinskii-Moriya (DM) interaction on pairwise quantum discord, entanglement, and classical correlation in the anisotropic XY spin-half chain. Analytical expressions for both quantum and classical correlations are obtained from the spin-spin correlation functions. We show that these pairwise quantities exhibit various behaviors in relation to the relative strengths of the DM interaction, the anisotropy and the magnetic intensity. We observe non-analyticities of the derivatives of both quantum and classical correlations with respect to the magnetic intensity at the critical point, with consideration of the DM interaction.Comment: 18pages, 6figure

General-Purpose Multi-Modal OOD Detection Framework

Out-of-distribution (OOD) detection identifies test samples that differ from the training data, which is critical to ensuring the safety and reliability of machine learning (ML) systems. While a plethora of methods have been developed to detect uni-modal OOD samples, only a few have focused on multi-modal OOD detection. Current contrastive learning-based methods primarily study multi-modal OOD detection in a scenario where both a given image and its corresponding textual description come from a new domain. However, real-world deployments of ML systems may face more anomaly scenarios caused by multiple factors like sensor faults, bad weather, and environmental changes. Hence, the goal of this work is to simultaneously detect from multiple different OOD scenarios in a fine-grained manner. To reach this goal, we propose a general-purpose weakly-supervised OOD detection framework, called WOOD, that combines a binary classifier and a contrastive learning component to reap the benefits of both. In order to better distinguish the latent representations of in-distribution (ID) and OOD samples, we adopt the Hinge loss to constrain their similarity. Furthermore, we develop a new scoring metric to integrate the prediction results from both the binary classifier and contrastive learning for identifying OOD samples. We evaluate the proposed WOOD model on multiple real-world datasets, and the experimental results demonstrate that the WOOD model outperforms the state-of-the-art methods for multi-modal OOD detection. Importantly, our approach is able to achieve high accuracy in OOD detection in three different OOD scenarios simultaneously. The source code will be made publicly available upon publication

Antitumor Efficacy and Mechanism in Hepatoma H22-Bearing Mice of Brucea javanica

Brucea javanica is a traditional herbal medicine in China, and its antitumor activities are of research interest. Brucea javanica oil, extracted with ether and refined with 10% ethyl alcohol from Brucea javanica seed, was used to treat hepatoma H22-bearing mice in this study. The antitumor effect and probable mechanisms of the extracted Brucea javanica oil were studied in H22-bearing mice by WBC count, GOT, GPT levels, and western blotting. The H22 tumor inhibition ratio of 0.5, 1, and 1.5 g/kg bw Brucea javanica oil were 15.64%, 23.87%, and 38.27%. Brucea javanica oil could inhibit the involution of thymus induced by H22 tumor-bearing, but it could not inhibit the augmentation of spleen and liver. Brucea javanica oil could decrease the levels of WBC count and GOT and GPT in H22-bearing mice. The protein levels of GAPDH, Akt, TGF-β1, and α-SMA in tumor tissues decreased after being treated with Brucea javanica oil. Disturbing energy metabolism and neoplastic hyperplasia controlled by Akt and immunoregulation activity were its probable antitumor mechanisms in hepatoma H22-bearing mice

First Efficacy Results of Capecitabine with Anthracycline- and Taxane-Based Adjuvant Therapy in High-Risk Early Breast Cancer: A Meta-Analysis

Background: Capecitabine is effective and indicated for the salvage treatment of metastatic breast cancer. Therefore, it is essential to evaluate the efficacy of capecitabine in the adjuvant setting. There have been two large randomized studies to determine whether patients with high-risk early breast cancer benefit from the addition of capecitabine to standard chemotherapy, but they have yielded inconsistent results. We first undertook a meta-analysis to evaluate the efficacy of the addition of capecitabine over standard treatment