Combining Past, Present and Future: A Self-Supervised Approach for Class Incremental Learning

Class Incremental Learning (CIL) aims to handle the scenario where data of novel classes occur continuously and sequentially. The model should recognize the sequential novel classes while alleviating the catastrophic forgetting. In the self-supervised manner, it becomes more challenging to avoid the conflict between the feature embedding spaces of novel classes and old ones without any class labels. To address the problem, we propose a self-supervised CIL framework CPPF, meaning Combining Past, Present and Future. In detail, CPPF consists of a prototype clustering module (PC), an embedding space reserving module (ESR) and a multi-teacher distillation module (MTD). 1) The PC and the ESR modules reserve embedding space for subsequent phases at the prototype level and the feature level respectively to prepare for knowledge learned in the future. 2) The MTD module maintains the representations of the current phase without the interference of past knowledge. One of the teacher networks retains the representations of the past phases, and the other teacher network distills relation information of the current phase to the student network. Extensive experiments on CIFAR100 and ImageNet100 datasets demonstrate that our proposed method boosts the performance of self-supervised class incremental learning. We will release code in the near future

Flooding Greatly Affects the Diversity of Arbuscular Mycorrhizal Fungi Communities in the Roots of Wetland Plants

The communities of arbuscular mycorrhizal fungi (AMF) colonizing the roots of three mangrove species were characterized along a tidal gradient in a mangrove swamp. A fragment, designated SSU-ITS-LSU, including part of the small subunit (SSU), the entire internal transcribed spacer (ITS) and part of the large subunit (LSU) of rDNA from samples of AMF-colonized roots was amplified, cloned and sequenced using AMF-specific primers. Similar levels of AMF diversity to those observed in terrestrial ecosystems were detected in the roots, indicating that the communities of AMF in wetland ecosystems are not necessarily low in diversity. In total, 761 Glomeromycota sequences were obtained, which grouped, according to phylogenetic analysis using the SSU-ITS-LSU fragment, into 23 phylotypes, 22 of which belonged to Glomeraceae and one to Acaulosporaceae. The results indicate that flooding plays an important role in AMF diversity, and its effects appear to depend on the degree (duration) of flooding. Both host species and tide level affected community structure of AMF, indicating the presence of habitat and host species preferences

Dynamic Evolution Analysis of Stock Price Fluctuation and Its Control

This paper studies a simple dynamical system of stock price fluctuation time series based on the rule of stock market. When the stock price fluctuation system is disturbed by external excitations, the system exhibits obviously chaotic phenomena, and its basic dynamic properties are analyzed. At the same time, a new fixed-time convergence theorem is proposed for achieving fixed-time control of stock price fluctuation system. Finally, the effectiveness of the method is verified by numerical simulation

Identification of potential diagnostic and prognostic biomarkers for sepsis based on machine learning

Background: To identify potential diagnostic and prognostic biomarkers of the early stage of sepsis. Methods: The differentially expressed genes (DEGs) between sepsis and control transcriptomes were screened from GSE65682 and GSE134347 datasets. The candidate biomarkers were identified by the least absolute shrinkage and selection operator (LASSO) regression and support vector machine recursive feature elimination (SVM-RFE) analyses. The diagnostic and prognostic abilities of the markers were evaluated by plotting receiver operating characteristic (ROC) curves and Kaplan–Meier survival curves. Gene Set Enrichment Analysis (GSEA) and single-sample GSEA (ssGSEA) were performed to further elucidate the molecular mechanisms and immune-related processes. Finally, the potential biomarkers were validated in a septic mouse model by qRT-PCR and western blotting. Results: Eleven DEGs were identified between the sepsis and control samples, including YOD1, GADD45A, BCL11B, IL1R2, UGCG, TLR5, S100A12, ITK, HP, CCR7 and C19orf59 (all AUC>0.9). Furthermore, the survival analysis identified YOD1, GADD45A, BCL11B and IL1R2 as the prognostic biomarkers of sepsis. According to GSEA, four DEGs were significantly associated with immune-related processes. In addition, ssGSEA demonstrated a significant difference in the enriched immune cell populations between the sepsis and control groups (all P < 0.05). Moreover, YOD1, GADD45A and IL1R2 were upregulated, and BCL11B was downregulated in the heart, liver, lungs, and kidneys of the septic mice model. Conclusions: We identified four potential immune-releated diagnostic and prognostic gene markers for sepsis that offer new insights into its underlying mechanisms

On-Surface Bottom-Up Construction of COF Nanoshells towards Photocatalytic H2 Production

The rational design of an outer shell is of great significance to promote the photocatalytic efficiency of core-shell structured photocatalysts. Herein, a covalent organic framework (COF) nanoshell was designed and deposited on the cadmium sulfide (CdS) core surface. A typical COF material, TPPA, featuring exceptional stability, was synthesized through interfacial polymerization using 1, 3, 5-triformylphloroglucinol (TP) and p-phenylenediamine (PA) as monomers. The nanoshell endows the CdS@TPPA nanosphere with ordered channels for unimpeded light-harvesting and fast diffusion of reactants/products and well-defined modular building blocks for spatially charge separation. Moreover, the heterojunction formed between CdS and TPPA can further facilitate the effective charge separation at the interface via lower exciton binding energy compared with that of pristine TPPA. By modulating the thickness of TPPA nanoshell, the CdS@TPPA nanosphere photocatalyst with the nanoshell thickness of about 8±1 nm exhibits the highest photocatalytic H2 evolution of 194.1 μmol h-1 (24.3 mmol g-1 h-1, 8 mg), which is superior to most of the reported COF-based photocatalysts. The framework nanoshell in this work may stimulate the thinking about how to design advanced shell architecture in the core-shell structured photocatalysts to achieve coordinated charge and molecule transport

Electrostatic-modulated interfacial polymerization toward ultra-permselective nanofiltration membranes

10.1016/j.isci.2021.102369iScience24410236

An Immune Signature for Risk Stratification and Therapeutic Prediction in Helicobacter pylori-Infected Gastric Cancer

Helicobacter pylori (HP) infection is the greatest risk factor for gastric cancer (GC). Increasing evidence has clarified that tumor immune microenvironment (TIME) is closely related to the prognosis and therapeutic efficacy of HP-positive (HP+) GC patients. In this study, we aimed to construct a novel immune-related signature for predicting the prognosis and immunotherapy efficacy of HP+ GC patients. A total of 153 HP+ GC from three different cohorts were included in this study. An Immune-Related prognostic Signature for HP+ GC patients (IRSHG) was established using Univariate Cox regression, the LASSO algorithm, and Multivariate Cox regression. Univariate and Multivariate analyses proved IRSHG was an independent prognostic predictor for HP+ GC patients, and an IRSHG-integrated nomogram was established to quantitatively assessthe prognostic risk. The low-IRSHG group exhibited higher copy number load and distinct mutation profiles compared with the high-IRSHG group. In addition, the difference of hallmark pathways and immune cells infiltration between the two groups was investigated. Notably, tumor immune dysfunction and exclusion (TIDE) analysis indicated that the low-IRSHG group had a higher sensitivity to anti-PD-1 immunotherapy, which was validated by an external pabolizumab treatment cohort. Moreover, 98 chemotherapeutic drugs and corresponding potential biomarkers were identified for two groups, and several drugs with potential ability to reverse IRSHG score were identified using CMap analysis. Collectively, IRSHG may serve as a promising biomarker for survival outcome as well as immunotherapy efficacy. Furthermore, it can also help to prioritize potential therapeutics for HP+ GC patients, providing new insight for the personalized treatment of HP-infected GC

The First Identification of Lysine Malonylation Substrates and Its Regulatory Enzyme

Protein post-translational modifications (PTMs) at the lysine residue, such as lysine methylation, acetylation, and ubiquitination, are diverse, abundant, and dynamic. They play a key role in the regulation of diverse cellular physiology. Here we report discovery of a new type of lysine PTM, lysine malonylation (Kmal). Kmal was initially detected by mass spectrometry and protein sequence-database searching. The modification was comprehensively validated by Western blot, tandem MS, and high-performance liquid chromatography of synthetic peptides, isotopic labeling, and identification of multiple Kmal substrate proteins. Kmal is a dynamic and evolutionarily conserved PTM observed in mammalian cells and bacterial cells. In addition, we demonstrate that Sirt5, a member of the class III lysine deacetylases, can catalyze lysine demalonylation and lysine desuccinylation reactions both in vitro and in vivo . This result suggests the possibility of nondeacetylation activity of other class III lysine deacetylases, especially those without obvious acetylation protein substrates. Our results therefore reveal a new type of PTM pathway and identify the first enzyme that can regulate lysine malonylation and lysine succinylation status