Publications by authors named "T Salminen"

The role of mitochondria in immunity is increasingly recognized, but it is unclear how variation in mitochondrial DNA (mtDNA) contributes to variable infection outcomes. To quantify the effect of mtDNA variation on humoral and cell-mediated innate immune responses, we utilized a panel of fruit fly Drosophila melanogaster cytoplasmic hybrids (cybrids), where unique mtDNAs (mitotypes) were introgressed into a controlled isogenic nuclear background. We observed substantial heterogeneity in infection outcomes within the cybrid panel upon bacterial, viral and parasitoid infections, driven by the mitotype.

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Background: In modern emergency medical services (EMS), ambulances increasingly focus on examining and treating the patient at the scene. This has led to increased levels of non-conveyance. In Finland, for instance, approximately 40% of EMS dispatches end up in non-conveyance.

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Invertebrates lack the immune machinery underlying vertebrate-like acquired immunity. However, in many insects past infection by the same pathogen can 'prime' the immune response, resulting in improved survival upon reinfection. Here, we investigated the mechanistic basis and epidemiological consequences of innate immune priming in the fruit fly Drosophila melanogaster when infected with the gram-negative bacterial pathogen Providencia rettgeri.

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Background And Purpose: The CardioSwitch-study demonstrated that patients with solid tumors who develop cardiotoxicity on capecitabine or 5-fluorouracil (5-FU) treatment can be safely switched to S-1, an alternative fluoropyrimidine (FP). In light of the European Medicines Agency approval of S-1 in metastatic colorectal cancer (mCRC), this analysis provides more detailed safety and efficacy information, and data regarding metastasectomy and/or local ablative therapy (LAT), on the mCRC patients from the original study.

Materials And Methods: This retrospective cohort study was conducted at 12 European centers.

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The three-dimensional structure of proteins determines their function in vital biological processes. Thus, when the structure is known, the molecular mechanism of protein function can be understood in more detail and obtained information utilized in biotechnological, diagnostics, and therapeutic applications. Over the past five years, machine learning (ML)-based modeling has pushed protein structure prediction to the next level with AlphaFold in the front line, predicting the structure for hundreds of millions of proteins.

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