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Erida Gjini

Researcher at Instituto Gulbenkian de Ciência

Publications -  40
Citations -  443

Erida Gjini is an academic researcher from Instituto Gulbenkian de Ciência. The author has contributed to research in topics: Population & Gene. The author has an hindex of 10, co-authored 38 publications receiving 338 citations. Previous affiliations of Erida Gjini include University of Glasgow & Instituto Superior Técnico.

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Integrating Antimicrobial Therapy with Host Immunity to Fight Drug-Resistant Infections: Classical vs. Adaptive Treatment.

TL;DR: This work compares aggressive and moderate antibiotic treatment, accounting for host immunity effects, and explains key parameters and dimensions, where an adaptive regime differs from classical treatment, bringing new insight into the ongoing debate of resistance management.
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Renal control of disease tolerance to malaria.

TL;DR: It is demonstrated that the establishment of disease tolerance to malaria relies on a tissue damage-control mechanism that operates specifically in renal proximal tubule epithelial cells (RPTEC), which relies on the induction of heme oxygenase-1 and ferritin H chain via a mechanism that involves the transcription-factor nuclear-factor E2-related factor-2 (NRF2).
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Critical interplay between parasite differentiation, host immunity, and antigenic variation in trypanosome infections.

TL;DR: A mechanistic framework for modeling within‐host infection dynamics of the sleeping sickness parasite, the African trypanosome, shows that the degree of synchronization in stochastic variant emergence determines the relative dominance of general over specific control within a single peak.
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How direct competition shapes coexistence and vaccine effects in multi-strain pathogen systems

TL;DR: An integrated modeling framework for understanding strain coexistence in polymorphic pathogen systems is described, conveying that direct competition for colonization mediates stable coexistence only when competitive abilities amongst pathogen clones satisfy certain pairwise asymmetries.
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Unveiling time in dose-response models to infer host susceptibility to pathogens.

TL;DR: A method is introduced to assess host susceptibility to pathogens, and applied to a detailed dataset generated by challenging groups of insect hosts with a range of pathogen doses and recording survival over time, which provides novel insights for study design and analyses to assess interventions.