Dynamic Transfer Learning across Graphs

Transferring knowledge across graphs plays a pivotal role in many high-stake domains, ranging from transportation networks to e-commerce networks, from neuroscience to finance. To date, the vast majority of existing works assume both source and target domains are sampled from a universal and stationary distribution. However, many real-world systems are intrinsically dynamic, where the underlying domains are evolving over time. To bridge the gap, we propose to shift the problem to the dynamic setting and ask: given the label-rich source graphs and the label-scarce target graphs observed in previous T timestamps, how can we effectively characterize the evolving domain discrepancy and optimize the generalization performance of the target domain at the incoming T+1 timestamp? To answer the question, for the first time, we propose a generalization bound under the setting of dynamic transfer learning across graphs, which implies the generalization performance is dominated by domain evolution and domain discrepancy between source and target domains. Inspired by the theoretical results, we propose a novel generic framework DyTrans to improve knowledge transferability across dynamic graphs. In particular, we start with a transformer-based temporal encoding module to model temporal information of the evolving domains; then, we further design a dynamic domain unification module to efficiently learn domain-invariant representations across the source and target domains. Finally, extensive experiments on various real-world datasets demonstrate the effectiveness of DyTrans in transferring knowledge from dynamic source domains to dynamic target domains

Aromatic Glucosinolate Biosynthesis Pathway in Barbarea vulgaris and its Response to Plutella xylostella Infestation

The inducibility of the glucosinolate resistance mechanism is an energy-saving strategy for plants, but whether induction would still be triggered by glucosinolate-tolerant Plutella xylostella (diamondback moth, DBM) after a plant had evolved a new resistance mechanism (e.g. saponins in Barbara vulgaris) was unknown. In B. vulgaris, aromatic glucosinolates derived from homo-phenylalanine are the dominate glucosinolates, but their biosynthesis pathway are unclear in this plant. In this study, we used G-type (pest-resistant) and P-type (pest-susceptible) B. vulgaris to compare glucosinolate levels and the expression profiles of their biosynthesis genes before and after infestation by DBM larvae. Two different stereoisomers of hydroxylated aromatic glucosinolates are dominant in G- and P-type B. vulgaris, respectively, and are induced by DBM. The transcripts of genes in the glucosinolate biosynthesis pathway and their corresponding transcription factors were identified from an Illumina dataset of G- and P-type B. vulgaris. Many genes involved or potentially involved in glucosinolate biosynthesis were induced in both plant types. The expression patterns of six DBM induced genes were validated by quantitative PCR (qPCR), while six long-fragment genes were validated by molecular cloning. The core structure biosynthetic genes showed high sequence similarities between the two genotypes. In contrast, the sequence identity of two apparent side chain modification genes, the SHO gene in the G-type and the RHO in P-type plants, showed only 77.50% identity in coding DNA sequences and 65.48% identity in deduced amino acid sequences. The homology to GS-OH in Arabidopsis, DBM induction of the transcript and a series of qPCR and glucosinolate analyses of G-type, P-type and F1 plants indicated that these genes control the production of S and R isomers of 2-hydroxy-2-phenylethyl glucosinolate. These glucosinolates were significantly induced by P. xylostella larvae in both the susceptiple P-type and the resistant G-type, even though saponins are the main DBM-resistance causing metabolites in G-type plants. Indol-3-ylmethylglucosinolate was induced in the G-type only. These data will aid our understanding of the biosynthesis and induction of aromatic glucosinolates at the molecular level and also increase our knowledge of the complex mechanisms underpinning defense induction in plants

A multi-view latent variable model reveals cellular heterogeneity in complex tissues for paired multimodal single-cell data

Motivation Single-cell multimodal assays allow us to simultaneously measure two different molecular features of the same cell, enabling new insights into cellular heterogeneity, cell development and diseases. However, most existing methods suffer from inaccurate dimensionality reduction for the joint-modality data, hindering their discovery of novel or rare cell subpopulations. Results Here, we present VIMCCA, a computational framework based on variational-assisted multi-view canonical correlation analysis to integrate paired multimodal single-cell data. Our statistical model uses a common latent variable to interpret the common source of variances in two different data modalities. Our approach jointly learns an inference model and two modality-specific non-linear models by leveraging variational inference and deep learning. We perform VIMCCA and compare it with 10 existing state-of-the-art algorithms on four paired multi-modal datasets sequenced by different protocols. Results demonstrate that VIMCCA facilitates integrating various types of joint-modality data, thus leading to more reliable and accurate downstream analysis. VIMCCA improves our ability to identify novel or rare cell subtypes compared to existing widely used methods. Besides, it can also facilitate inferring cell lineage based on joint-modality profiles

Research progress on the fanconi anemia signaling pathway in non-obstructive azoospermia

Non-obstructive azoospermia (NOA) is a disease characterized by spermatogenesis failure and comprises phenotypes such as hypospermatogenesis, mature arrest, and Sertoli cell-only syndrome. Studies have shown that FA cross-linked anemia (FA) pathway is closely related to the occurrence of NOA. There are FA gene mutations in male NOA patients, which cause significant damage to male germ cells. The FA pathway is activated in the presence of DNA interstrand cross-links; the key step in activating this pathway is the mono-ubiquitination of the FANCD2-FANCI complex, and the activation of the FA pathway can repair DNA damage such as DNA double-strand breaks. Therefore, we believe that the FA pathway affects germ cells during DNA damage repair, resulting in minimal or even disappearance of mature sperm in males. This review summarizes the regulatory mechanisms of FA-related genes in male azoospermia, with the aim of providing a theoretical reference for clinical research and exploration of related genes

The combination of body mass index and fasting plasma glucose is associated with type 2 diabetes mellitus in Japan: a secondary retrospective analysis

BackgroundBody mass index (BMI) and fasting plasma glucose (FPG) are known risk factors for type 2 diabetes mellitus (T2DM), but data on the prospective association of the combination of BMI and FPG with T2DM are limited. This study sought to characterize the association of the combination of BMI and FPG (ByG) with T2DM.MethodsThe current study used the NAGALA database. We categorized participants by tertiles of ByG. The association of ByG with T2DM was expressed with hazard ratios (HRs) with 95% confidence intervals (CIs) after adjustment for potential risk factors.ResultsDuring a median follow-up of 6.19 years in the normoglycemia cohort and 5.58 years in the prediabetes cohort, the incidence of T2DM was 0.75% and 7.79%, respectively. Following multivariable adjustments, there were stepwise increases in T2DM with increasing tertiles of ByG. After a similar multivariable adjustment, the risk of T2DM was 2.57 (95% CI 2.26 - 2.92), 1.97 (95% CI 1.53 - 2.54) and 1.50 (95% CI 1.30 - 1.74) for a per-SD change in ByG in all populations, the normoglycemia cohort and the prediabetes cohort, respectively.ConclusionByG was associated with an increased risk of T2DM in Japan. The result reinforced the importance of the combination of BMI and FPG in assessing T2DM risk

Advanced NSCLC Patients With EGFR T790M Harboring TP53 R273C or KRAS G12V Cannot Benefit From Osimertinib Based on a Clinical Multicentre Study by Tissue and Liquid Biopsy

BackgroundNon-small cell lung cancer (NSCLC) patients treated with first-generation epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI) almost always acquire resistance, and the development of novel techniques analyzing circulating tumor DNA (ctDNA) have made it possible for liquid biopsy to detect genetic alterations from limited amount of DNA with less invasiveness. While a large amount of patients with EGFR exon 21 p.Thr790 Met (T790M) benefited from osimertinib treatment, acquired resistance to osimertinb has subsequently become a growing challenge.MethodsWe performed tissue and liquid rebiopsy on 50 patients with EGFR-mutant NSCLC who acquired resistance to first-generation EGFR-TKIs. Plasma samples underwent droplet digital PCR (ddPCR) and next-generation sequencing (NGS) examinations. Corresponding tissue samples underwent NGS and Cobas® EGFR Mutation Test v2 (Cobas) examinations.ResultsOf the 50 patients evaluated, the mutation detection rates of liquid biopsy group and tissue biopsy group demonstrated no significant differences (41/48, 85.4% vs. 44/48, 91.7%; OR=0.53, 95% CI=0.15 to 1.95). Overall concordance, defined as the proportion of patients for whom at least one identical genomic alteration was identified in both tissue and plasma, was 78.3% (36/46, 95% CI=0.39 to 2.69). Moreover, our results showed that almost half of the patients (46%, 23/50) resistant to first-generation EGFR-TKI harbored p.Thr790 Met (T790M) mutation. 82.6% (19/23) of the T790M positive patients were analyzed by liquid biopsy and 60.9% (14/23) by tumor tissue sequencing. Meanwhile, a wide range of uncommon mutations was detected, and novel mechanisms of osimertinib resistance were discovered. In addition, 16.7% (2/12) of the T790M positive patients with either TP53 R237C or KRAS G12V failed to benefit from the subsequent osimertinib treatment.ConclusionOur results emphasized that liquid biopsy is applicable to analyze the drug resistance mechanisms of NSCLC patients treated with EGFR-TKIs. Moreover, we discovered two uncommon mutations, TP53 R273C and KRAS G12V, which attenuates the effectiveness of osimertinib

Influence of Matrix Strength on Bridging Performance of Fiber-Reinforced Cementitious Composite with Bundled Aramid Fiber

The bundled aramid fiber has good bond properties in the cementitious matrix, and is expected to have high bridging performance in the fiber-reinforced cementitious composite (FRCC). To investigate the influence of matrix strength on the bridging performance of FRCC with the bundled aramid fiber, the uniaxial tension test of FRCC, the pullout test for an individual fiber, and the calculation of bridging law are conducted with the main parameters of matrix strength and fiber volume fraction. From the test results, the maximum tensile load of FRCC and the maximum pullout load of an individual fiber increase as the matrix strength also increases. The calculation result of the bridging law considering the effect of matrix strength expresses the bridging performance of the bundled aramid fiber well. The calculation result also shows that the bridging strength has a linear relationship up to a compressive strength of around 50 MPa

Influence of Matrix Strength on Bridging Performance of Fiber-Reinforced Cementitious Composite with Bundled Aramid Fiber

The bundled aramid fiber has good bond properties in the cementitious matrix, and is expected to have high bridging performance in the fiber-reinforced cementitious composite (FRCC). To investigate the influence of matrix strength on the bridging performance of FRCC with the bundled aramid fiber, the uniaxial tension test of FRCC, the pullout test for an individual fiber, and the calculation of bridging law are conducted with the main parameters of matrix strength and fiber volume fraction. From the test results, the maximum tensile load of FRCC and the maximum pullout load of an individual fiber increase as the matrix strength also increases. The calculation result of the bridging law considering the effect of matrix strength expresses the bridging performance of the bundled aramid fiber well. The calculation result also shows that the bridging strength has a linear relationship up to a compressive strength of around 50 MPa