Publications by authors named "S Vaehaemiko"

Lung cancer is the leading cause of mortality in both men and women due to genetic and epigenetic modifications. Our study focuses on fabricating phenmiazine ring leads by a functional group-based drug design to inhibit p53 -7A1W and MDM2-7AU9 proteins responsible for cancer cell growth. One hundred molecules are designed and allowed to bind inside the active site of 7A1W and 7AU9 protein using a glide dock platform and subjected to find MMGBSA.

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New methodologies have been evaluated for validating analytical characterization with artificial neural networks (ANNs). Compared to previous machine learning models, these provide more accurate and automated results with high testing accuracy. The Schiff base ruthenium complexes used in the proposed study were synthesized using 4-aminoantipyrine derivatives.

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PurposeChimeric antigen receptor (CAR) T-cell CD19 therapy has changed the treatment paradigm for patients with relapsed/refractory B-cell acute lymphoblastic leukemia. It is frequently associated with potentially severe toxicities: cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS), and admission to PICU is often required. Some biomarkers seem to correlate with CRS severity.

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Background: Centrifugal compressors are dynamic machines utilizing a rotating impeller, efficiently accelerate incoming gases, transforming kinetic energy into pressure energy for compression. They serve a wide range of industries, including air conditioning, refrigeration, gas turbines, industrial processes, and applications such as air compression, gas transportation, and petrochemicals, demonstrating their versatility. Designing a centrifugal compressor poses challenges related to achieving high aerodynamic efficiency, surge and choke control, material selection, rotor dynamics, cavitation, erosion, and addressing environmental considerations while balancing costs.

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Cross subject Electroencephalogram (EEG) emotion recognition refers to the process of utilizing electroencephalogram signals to recognize and classify emotions across different individuals. It tracks neural electrical patterns, and by analyzing these signals, it's possible to infer a person's emotional state. The objective of cross-subject recognition is to create models or algorithms that can reliably detect emotions in both the same person and several other people.

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