Publications by authors named "N P Medvedev"

Article Synopsis
  • Rheumatic paraneoplastic syndromes are uncommon but can indicate hidden cancers, often appearing within two years before a cancer diagnosis.
  • An 18-year-old female with no prior health issues developed morning stiffness and a rash, leading to a diagnosis of systemic lupus erythematosus (SLE) and later the discovery of a dysgerminoma tumor.
  • After surgery and chemotherapy for the tumor, her SLE symptoms went into remission, highlighting the need for doctors to consider cancer when patients show unexplained lupus symptoms.
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Ultrafast laser radiation or beams of fast charged particles primarily excite the electronic system of a solid driving the target transiently out of thermal equilibrium. Apart from the nonequilibrium between the electrons and atoms, each subsystem may be far from equilibrium. From first principles, we derive the definition of various atomic temperatures applicable to electronically excited ensembles.

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Although polymers are widely used in laser-irradiation research, their microscopic response to high-intensity ultrafast XUV and X-ray irradiation is still largely unknown. Here, we comparatively study a homologous series of alkenes. The XTANT-3 hybrid simulation toolkit is used to determine their damage kinetics and irradiation threshold doses.

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Electron-phonon coupling is an important energy transfer mechanism in solids after ultrafast laser excitation. In this study, we present an extreme ultraviolet (EUV) and infrared (IR) pump-probe photoemission experiment to investigate the electron-phonon coupling in nonequilibrium gold. The energy of IR-laser-emitted photoelectrons is shifted due to the EUV photoemission and oscillates with a ∼4THz frequency.

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Multiparameter flow cytometry is widely used for acute myeloid leukemia minimal residual disease testing (AML MRD) but is time consuming and demands substantial expertise. Machine learning offers potential advancements in accuracy and efficiency, but has yet to be widely adopted for this application. To explore this, we trained single cell XGBoost classifiers from 98 diagnostic AML cell populations and 30 MRD negative samples.

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