Learning Bayesian network structure with immune algorithm

Finding out reasonable structures from bulky data is one of the difficulties in modeling of Bayesian network （BN）, which is also necessary in promoting the application of BN. This pa- per proposes an immune algorithm based method （BN-IA） for the learning of the BN structure with the idea of vaccination. Further- more, the methods on how to extract the effective vaccines from local optimal structure and root nodes are also described in details. Finally, the simulation studies are implemented with the helicopter convertor BN model and the car start BN model. The comparison results show that the proposed vaccines and the BN-IA can learn the BN structure effectively and efficiently.

Nasopharyngeal Local Transcriptional Profile upon SARS-CoV-2 Omicron BA.2.2 Breakthrough Infection

The Omicron variants have continued to cause severe acute respiratory syndrome coronavirus 2 infections.To better understand the anti-viral effects of vaccination on host-virus interactions during the outbreak of BA.2.2 Omicron,we conducted RNA-seq transcriptome analysis on nasopharyngeal swabs from COVID-19 patients in Shanghai.This study was performed on selected cases from unvaccinated,fully vaccinated,and booster groups with the same founder virus infection background.We observed predominant immune cell chemotaxis and interleukin-1 production,as well as mucosal keratinization and epidermis development,in unvaccinated patients.In contrast,fully vaccinated subjects exhibited an obvious T-cell activation in the local immune response,whereas B-cell activation was higher in booster-vaccinated cases.In conclusion,our findings suggest that full or booster vaccination provides better adaptive immunity and relieve inflammation at the nasopharyngeal site,thereby reducing the risk of cytokine storm during breakthrough infection.

Intratumoral heterogeneity of hepatocellular carcinoma: From singlecell to population-based studies

Hepatocellular carcinoma(HCC)is characterized by high heterogeneity in both intratumoral and interpatient manners.While interpatient heterogeneity is related to personalized therapy,intratumoral heterogeneity(ITH)largely influences the efficacy of therapies in individuals.ITH contributes to tumor growth,metastasis,recurrence,and drug resistance and consequently limits the prognosis of patients with HCC.There is an urgent need to understand the causes,characteristics,and consequences of tumor heterogeneity in HCC for the purposes of guiding clinical practice and improving survival.Here,we summarize the studies and technologies that describe ITH in HCC to gain insight into the origin and evolutionary process of heterogeneity.In parallel,evidence is collected to delineate the dynamic relationship between ITH and the tumor ecosystem.We suggest that conducting comprehensive studies of ITH using single-cell approaches in temporal and spatial dimensions,combined with population-based clinical trials,will help to clarify the clinical implications of ITH,develop novel intervention strategies,and improve patient prognosis.

Targeted Local Immunization in Scale-Free Peer-to-Peer Networks

The power-law node degree distributions of peer-to-peer overlay networks make them extremely robust to random failures whereas highly vulnerable under intentional targeted attacks. To enhance attack survivability of these networks, DeepCure, a novel heuristic immunization strategy, is proposed to conduct decentralized but targeted immunization. Different from existing strategies, DeepCure identifies immunization targets as not only the highly-connected nodes but also the nodes with high availability and/or high link load, with the aim of injecting immunization information into just right targets to cure. To better trade off the cost and the efficiency, DeepCure deliberately select these targets from 2-local neighborhood, as well as topologically-remote but semantically-close friends if needed. To remedy the weakness of existing strategies in case of sudden epidemic outbreak, DeepCure is also coupled with a local-hub oriented rate throttling mechanism to enforce proactive rate control. Extensive simulation results show that DeepCure outperforms its competitors, producing an arresting increase of the network attack tolerance, at a lower price of eliminating viruses or malicious attacks.