Pulmonary extra-nodal marginal zone B-cell lymphoma, also known as extra-nodal mucosa-associated lymphoid tissue (MALT) lymphoma, is rare among all non-Hodgkin lymphomas and generally among all pulmonary malignancies. We present a 46-year-old lady with persistent right lower lung consolidation despite earlier treatment efforts with intravenous antibiotics for community acquired pneumonia. Apart from initial presentation with a short 3-day history of fever, cough and shortness of breath, she had remained largely asymptomatic throughout the follow-up period. Flexible bronchoscopy done ruled out infectious aetiologies but transbronchial lung biopsies showed atypical lymphocytes. A computed tomography guided core biopsy of her right lung consolidation was subsequently performed, confirming a diagnosis of pulmonary MALT lymphoma. She was promptly referred to the haematology team for further management and commencement of chemotherapy. Pulmonary MALT lymphoma, albeit uncommon and often follows a relatively indolent cause, should be considered as a differential diagnosis among patients with persistent lung consolidation.
Artificial electronic synapses are commonly used to simulate biological synapses to realize various learning functions, regarded as one of the key technologies in the next generation of neurological computation. This work used a simple spin coating technique to fabricate polyimide (PI):graphene quantum dots(GQDs) memristor structure. As a result, the devices exhibit remarkably stable exponentially decaying postsynaptic suppression current over time, as interpreted in the spike-timing-dependent plasticity phenomenon. Furthermore, with the increase of the applied electrical signal over time, the conductance of the electrical synapse gradually changes, and the electronic synapse also shows plasticity dependence on the amplitude and frequency of the pulse applied. In particular, the devices with the structure of Ag/PI:GQDs/ITO prepared in this study can produce a stable response to the stimulation of electrical signals between millivolt to volt, showing not only high sensitivity but also a wide range of "feelings", which makes the electronic synapses take a step forwards to emulate biological synapses. Meanwhile, the electronic conduction mechanisms of the device are also studied and expounded in detail. The findings in this work lay a foundation for developing brain-like neuromorphic modeling in artificial intelligence.