History and Memory: The Poetic Odyssey in Luo Fu’s ‘Driftwood’

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Exploring Robust Features for Improving Adversarial Robustness

While deep neural networks (DNNs) have revolutionized many fields, their fragility to carefully designed adversarial attacks impedes the usage of DNNs in safety-critical applications. In this paper, we strive to explore the robust features which are not affected by the adversarial perturbations, i.e., invariant to the clean image and its adversarial examples, to improve the model's adversarial robustness. Specifically, we propose a feature disentanglement model to segregate the robust features from non-robust features and domain specific features. The extensive experiments on four widely used datasets with different attacks demonstrate that robust features obtained from our model improve the model's adversarial robustness compared to the state-of-the-art approaches. Moreover, the trained domain discriminator is able to identify the domain specific features from the clean images and adversarial examples almost perfectly. This enables adversarial example detection without incurring additional computational costs. With that, we can also specify different classifiers for clean images and adversarial examples, thereby avoiding any drop in clean image accuracy.Comment: 12 pages, 8 figure

CASA: Category-agnostic Skeletal Animal Reconstruction

Recovering the skeletal shape of an animal from a monocular video is a longstanding challenge. Prevailing animal reconstruction methods often adopt a control-point driven animation model and optimize bone transforms individually without considering skeletal topology, yielding unsatisfactory shape and articulation. In contrast, humans can easily infer the articulation structure of an unknown animal by associating it with a seen articulated character in their memory. Inspired by this fact, we present CASA, a novel Category-Agnostic Skeletal Animal reconstruction method consisting of two major components: a video-to-shape retrieval process and a neural inverse graphics framework. During inference, CASA first retrieves an articulated shape from a 3D character assets bank so that the input video scores highly with the rendered image, according to a pretrained language-vision model. CASA then integrates the retrieved character into an inverse graphics framework and jointly infers the shape deformation, skeleton structure, and skinning weights through optimization. Experiments validate the efficacy of CASA regarding shape reconstruction and articulation. We further demonstrate that the resulting skeletal-animated characters can be used for re-animation.Comment: Accepted to NeurIPS 202

Research on data integration of bioinformatics database based on web services

ABSTRACT: With the development of human genome projects ( HGP) in the world, a mass of genetic information is generated. Now there are hundreds of different kinds of important bioinformatics databases in the world. How to unify the bioinformatics database from different countries has become an important issue in Bioinformatics. In this paper, we present a data integra-tion program based on Web Services of heterogeneous bioinformatics databases. The key technology of bioinformatics data integration has been researched and designed as well

Research Progress on Aroma-Enhancing Techniques for Fruit Wine Brewing: A Review

Aroma is one of the important indexes to measure the organoleptic quality of fruit wine. However, the weak aroma restricts the further improvement of fruit wine quality. The aroma enhancement of fruit wine is one of the focuses of attention for relevant practitioners. However, the complicated mechanism of aroma regulation is a bottleneck problem that restricts the creation of aroma-enhancing techniques for fruit wine fermentation. In this paper, we provide a systematic review of the mechanism of the influence of starter cultures, enzymes, and pretreatment before fermentation on the aroma of fruit wine with regard to the types of key aroma compounds and their formation pathways, and we discuss the application of modern biotechnology in the breeding of excellent aroma producing yeast. Finally, we discuss future directions in the research on fruit wine flavor

Conserved roles of C. elegans and human MANFs in sulfatide binding and cytoprotection.

Mesencephalic astrocyte-derived neurotrophic factor (MANF) is an endoplasmic reticulum (ER) protein that can be secreted and protects dopamine neurons and cardiomyocytes from ER stress and apoptosis. The mechanism of action of extracellular MANF has long been elusive. From a genetic screen for mutants with abnormal ER stress response, we identified the gene Y54G2A.23 as the evolutionarily conserved C. elegans MANF orthologue. We find that MANF binds to the lipid sulfatide, also known as 3-O-sulfogalactosylceramide present in serum and outer-cell membrane leaflets, directly in isolated forms and in reconstituted lipid micelles. Sulfatide binding promotes cellular MANF uptake and cytoprotection from hypoxia-induced cell death. Heightened ER stress responses of MANF-null C. elegans mutants and mammalian cells are alleviated by human MANF in a sulfatide-dependent manner. Our results demonstrate conserved roles of MANF in sulfatide binding and ER stress response, supporting sulfatide as a long-sought lipid mediator of MANF's cytoprotection

Identification of a SARS-CoV-2 virus-derived vmiRNA in COVID-19 patients holding potential as a diagnostic biomarker

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a lasting threat to public health. To minimize the viral spread, it is essential to develop more reliable approaches for early diagnosis of the infection and immediate suppression of the viral replication. Herein, through computational prediction of SARS-CoV-2 genome and screening analysis of specimens from covid-19 patients, we predicted 15 precursors for SARS-CoV-2-encoded miRNAs (CvmiRNAs) containing 20 mature CvmiRNAs, in which CvmiR-2 was successfully detected by quantitative analysis in both serum and nasal swab samples of patients. CvmiR-2 showed high specificity in distinguishing covid-19 patients from normal controls, and high conservation between SARS-CoV-2 and its mutants. A positive correlation was observed between the CvmiR-2 expression level and the severity of patients. The biogenesis and expression of CvmiR-2 were validated in the pre-CvmiR-2-transfected A549 cells, showing a dose-dependent pattern. The sequence of CvmiR-2 was validated by sequencing analysis of human cells infected by either SARS-CoV-2 or pre-CvmiR-2. Target gene prediction analysis suggested CvmiR-2 may be involved in the regulation of the immune response, muscle pain and/or neurological disorders in covid-19 patients. In conclusion, the current study identified a novel v-miRNA encoded by SARS-CoV-2 upon infection of human cells, which holds the potential to serve as a diagnostic biomarker or a therapeutic target in clinic

Regulatory controls of duplicated gene expression during fiber development in allotetraploid cotton.

Polyploidy complicates transcriptional regulation and increases phenotypic diversity in organisms. The dynamics of genetic regulation of gene expression between coresident subgenomes in polyploids remains to be understood. Here we document the genetic regulation of fiber development in allotetraploid cotton Gossypium hirsutum by sequencing 376 genomes and 2,215 time-series transcriptomes. We characterize 1,258 genes comprising 36 genetic modules that control staged fiber development and uncover genetic components governing their partitioned expression relative to subgenomic duplicated genes (homoeologs). Only about 30% of fiber quality-related homoeologs show phenotypically favorable allele aggregation in cultivars, highlighting the potential for subgenome additivity in fiber improvement. We envision a genome-enabled breeding strategy, with particular attention to 48 favorable alleles related to fiber phenotypes that have been subjected to purifying selection during domestication. Our work delineates the dynamics of gene regulation during fiber development and highlights the potential of subgenomic coordination underpinning phenotypes in polyploid plants. [Abstract copyright: © 2023. The Author(s).

Frozen tissue coring and layered histological analysis improves cell type-specific proteogenomic characterization of pancreatic adenocarcinoma

Abstract Background Omics characterization of pancreatic adenocarcinoma tissue is complicated by the highly heterogeneous and mixed populations of cells. We evaluate the feasibility and potential benefit of using a coring method to enrich specific regions from bulk tissue and then perform proteogenomic analyses. Methods We used the Biopsy Trifecta Extraction (BioTExt) technique to isolate cores of epithelial-enriched and stroma-enriched tissue from pancreatic tumor and adjacent tissue blocks. Histology was assessed at multiple depths throughout each core. DNA sequencing, RNA sequencing, and proteomics were performed on the cored and bulk tissue samples. Supervised and unsupervised analyses were performed based on integrated molecular and histology data. Results Tissue cores had mixed cell composition at varying depths throughout. Average cell type percentages assessed by histology throughout the core were better associated with KRAS variant allele frequencies than standard histology assessment of the cut surface. Clustering based on serial histology data separated the cores into three groups with enrichment of neoplastic epithelium, stroma, and acinar cells, respectively. Using this classification, tumor overexpressed proteins identified in bulk tissue analysis were assigned into epithelial- or stroma-specific categories, which revealed novel epithelial-specific tumor overexpressed proteins. Conclusions Our study demonstrates the feasibility of multi-omics data generation from tissue cores, the necessity of interval H&E stains in serial histology sections, and the utility of coring to improve analysis over bulk tissue data