Aeromonas hydrophila infection in acute myeloid leukemia: A case report

Rationale:Aeromonas hydrophila,a bacterium commonly found in a variety of soils,aquatic habitats,and other natural environments,is known for causing infections and hemorrhagic diseases in both aquatic and terrestrial animals.Patients with leukemia,when infected by Aeromonas hydrophila following chemotherapy,face an increased risk of developing necrotizing fasciitis.Patient concerns:A 48-year-old male with a history of acute myeloid leukemia presented with swelling and pain in his right hand after being stabbed by a grass carp two days ago.The injury occurred on the fifth day after his last chemotherapy session when he was accidentally punctured in the right thumb and ring finger by a carp while fishing.Two days following the injury,the skin isurrounding the wound turned black immediately,while the rest of his hand was reddened,swollen,and bleeding.Diagnosis:Aeromonas hydrophila infection in the soft tissue of the right hand.Interventions:Intravenous antibiotics and local debridement.Outcomes:The patient experienced an alleviation of systemic poisoning symptoms,effective control of the local wound infection.Lessons:It is important for physicians to appreciate the potential for highly unusual and life-threatening infections in patients with acute myeloid leukemia.Early diagnosis and prompt treatment can prevent the development of necrotizing fasciitis and save patients’lives.

A Storage Optimization Scheme for Blockchain Transaction Databases

As the typical peer-to-peer distributed networks, blockchain systemsrequire each node to copy a complete transaction database, so as to ensure newtransactions can by verified independently. In a blockchain system (e.g., bitcoinsystem), the node does not rely on any central organization, and every node keepsan entire copy of the transaction database. However, this feature determines thatthe size of blockchain transaction database is growing rapidly. Therefore, with thecontinuous system operations, the node memory also needs to be expanded tosupport the system running. Especially in the big data era, the increasing networktraffic will lead to faster transaction growth rate. This paper analyzes blockchaintransaction databases and proposes a storage optimization scheme. The proposedscheme divides blockchain transaction database into cold zone and hot zone usingexpiration recognition method based on Least Recently Used (LRU) algorithm. Itcan achieve storage optimization by moving unspent transaction outputs outsidethe in-memory transaction databases. We present the theoretical analysis on theoptimization method to validate the effectiveness. Extensive experiments showour proposed method outperforms the current mechanism for the blockchaintransaction databases.