Recognition of Multiomics-Based Molecule-Pattern Biomarker for Precise Prediction, Diagnosis, and Prognostic Assessment in Cancer

Cancer is a complex whole-body chronic disease, is involved in multiple causes, multiple processes, and multiple consequences, which are associated with a series of molecular alterations in the different levels of genome, transcriptome, proteome, metabolome, and radiome, with between-molecule mutual interactions. Those molecule-panels are the important resources to recognize the reliable molecular pattern biomarkers for precise prediction, diagnosis, and prognostic assessment in cancer. Pattern recognition is an effective methodology to identify those molecule-panels. The rapid development of computation biology, systems biology, and multiomics is driving the development of pattern recognition to discover reliable molecular pattern biomarkers for cancer treatment. This book chapter addresses the concept of pattern recognition and pattern biomarkers, status of multiomics-based molecular patterns, and future perspective in prediction, diagnosis, and prognostic assessment of a cancer

Fine-Grained Knowledge Selection and Restoration for Non-Exemplar Class Incremental Learning

Non-exemplar class incremental learning aims to learn both the new and old tasks without accessing any training data from the past. This strict restriction enlarges the difficulty of alleviating catastrophic forgetting since all techniques can only be applied to current task data. Considering this challenge, we propose a novel framework of fine-grained knowledge selection and restoration. The conventional knowledge distillation-based methods place too strict constraints on the network parameters and features to prevent forgetting, which limits the training of new tasks. To loose this constraint, we proposed a novel fine-grained selective patch-level distillation to adaptively balance plasticity and stability. Some task-agnostic patches can be used to preserve the decision boundary of the old task. While some patches containing the important foreground are favorable for learning the new task. Moreover, we employ a task-agnostic mechanism to generate more realistic prototypes of old tasks with the current task sample for reducing classifier bias for fine-grained knowledge restoration. Extensive experiments on CIFAR100, TinyImageNet and ImageNet-Subset demonstrate the effectiveness of our method. Code is available at https://github.com/scok30/vit-cil.Comment: to appear at AAAI 202

A biophysical elucidation for less toxicity of Agglutinin than Abrin-a from the Seeds of Abrus Precatorius in consequence of crystal structure

X-ray crystal structure determination of agglutinin from abrus precatorius in Taiwan is presented. The crystal structure of agglutinin, a type II ribosome-inactivating protein (RIP) from the seeds of Abrus precatorius in Taiwan, has been determined from a novel crystalline form by the molecular replacement method using the coordinates of abrin-a as the template. The structure has space group P41212 with Z = 8, and been refined at 2.6 Å to R-factor of 20.4%. The root-mean-square deviations of bond lengths and angles from the standard values are 0.009 Å and 1.3°. Primary, secondary, tertiary and quaternary structures of agglutinin have been described and compared with those of abrin-a to a certain extent. In subsequent docking research, we found that Asn200 of abrin-a may form a critical hydrogen bond with G4323 of 28SRNA, while corresponding Pro199 of agglutinin is a kink hydrophobic residue bound with the cleft in a more compact complementary relationship. This may explain the lower toxicity of agglutinin than abrin-a, despite of similarity in secondary structure and the activity cleft of two RIPs

Page Curve and Phase Transition in deformed Jackiw-Teitelboim Gravity

We consider the entanglement island in a deformed Jackiw-Teitelboim black hole in the presence of the phase transition. This black hole has the van der Waals-Maxwell-like phase structure as it is coupled with a Maxwell field. We study the behavior of the Page curve of this black hole by using the island paradigm. In the fixed charge ensemble, we discuss different situations with different charges that influence the system's phase structure. There is only a Hawking-Page phase transition in the absence of charges, which leads to an unstable small black hole. Hence, the related Page curve does not exist. However, a van der Waals-Maxwell-like phase transition occurs in the presence of charges. This yields three black hole solutions. The Page curve of the middle size black hole does not exist. For the extremal black hole, the Page time approaches zero in the phase transition situation but becomes divergent without the phase transition. In a word, we study the Page curve and the island paradigm for different black hole phases and in different phase transition situations.Comment: 28 pages, 13 figures, references added, published versio

Reverse strain-induced snake states in graphene nanoribbons

Strain can tailor the band structures and properties of graphene nanoribbons (GNRs) with the well-known emergent pseudo-magnetic fields and the corresponding pseudo-Landau levels (pLLs). We design one type of the zigzag GNR (ZGNR) with reverse strains, producing pseudo-magnetic fields with opposite signs in the lower and upper half planes. Therefore, electrons propagate along the interface as "snake states", experiencing opposite Lorentz forces as they cross the zero field border line. By using the Landauer-Buttiker formalism combined with the nonequilibrium Green's function method, the existence and robustness of the reverse strain-induced snake states are further studied. Furthermore, the realization of long-thought pure valley currents in monolayer graphene systems is also proposed in our device.Comment: 6 figure

Establish real-time monitoring models of cotton aphid quantity based on different leaf positions in cotton seedlings

Cotton aphids, Aphis gossypii glover, are major pest threats to cotton plants, leading to quality and yield loss of cotton. Rapid and accurate evaluation on the occurrence and quantity of cotton aphids can help precision management and treatment of cotton aphids. The occurrence rules of cotton aphids on different leaf positions in cotton seedling stage for two cultivars of cotton were studied. The quantity of cotton aphids in the whole cotton seedlings were predicted based on the single leaf cotton aphid quantity. The correlation analysis results showed that cotton aphids of single leaf were significantly and positively correlated with the infected time, the all leaves of the whole plant, the whole plant contained all leaves and branches. The variance analysis results showed that cotton aphids of single leaf were significant difference with the extension of infected time. Based on different leaf positions, monitoring models were constructed respectively. The modelling set’s determination coefficient of ‘Xinluzao-45’ was greater than 0.8, while ‘Lumainyan-24’ was greater than 0.6. The best monitoring leaf position was the third for ‘Xinluzao-45’, the sixth for ‘Lumianyan-24’. From the data analysis, we can realize that it is feasible to construct a monitoring model based on the occurrence of cotton aphid in one leaf in cotton seedling, and different cotton varieties have different leaf positions. This will greatly reduce the investment of manpower and time