Biology subjects

Kiani, A.

Publications and source records attributed to Kiani, A..

3 recordsLinked to original sources

bioRxiv2026

MycorrhizaFinder: an efficient machine learning tool to quantify endomycorrhizal colonisation of real-world roots

AbstractO_ST_ABSBackground and aimsC_ST_ABSRoot colonisation by endomycorrhizal fungi has long been one of the most widely used metrics in mycorrhizal studies. However, due to the significant time required to assess colonisation using traditional microscope techniques, studies of colonisation at large scales are impractical. AI-powered approaches may increase output and facilitate ecosystem assessments. MethodsWe trained an AI-powered tool (MycorrhizaFinder) on field roots from diverse grasslands and heathlands hosting common Northern European plants with a range of arbuscular (AM) and ericoid mycorrhizal (ErM) fungal structures, and dark septate endophytes (DSE), also common in field-sourced roots. We incorporated a user-customized confidence threshold to encourage the user to engage with inevitable morphological ambiguities, in e.g. ErM and DSE. A Macro F1 statistic was used to assess the tools development. ResultsWe provide a sample workflow from root processing and microscope slide scanning to semi-automated model training and performance evaluation. Without human supervision, our automated baseline Macro F1 is 66% for arbuscular and at 57% for ericoid mycorrhizal colonisation assessment. ConclusionMycorrhizaFinder is user friendly, requires no programming skills and offers flexibility for advanced agronomists or ecologists who wish to train the tool using their own labelled mycorrhizal root datasets, including images acquired from different instruments or staining protocols. This adaptability allows users to customize the model for specific ecosystems or experimental designs. Leveraged with molecular identification and/or functional assessment of fungi, MycorrhizaFinder could support scalable and repeatable monitoring across ecosystems to assess mycorrhizal status and track land-use changes over time.

ecology↗

bioRxiv2025

Controlling TCR and CAR activation by targeting LCK recruitment with a first-in-class small-molecule inhibitor

T-cell activation is driven by the recruitment of lymphocyte-specific protein tyrosine kinase (LCK) to the T-cell receptor (TCR), a critical step in initiating immune responses. Existing LCK inhibitors lack specificity because they target the conserved kinase domain shared by Src family kinases, resulting in off-target effects. Here, we introduce a novel strategy to selectively modulate T-cell activation by disrupting the interaction between the SH3 domain of LCK and the receptor kinase (RK) motif of CD3{varepsilon}. Using computational modeling and high-throughput virtual screening, we identified candidate compounds targeting the SH3(LCK) domain. Functional validation revealed that one compound, C10, selectively disrupted the SH3-RK interaction, leading to reduced TCR-driven activation and proliferation, while sparing activation via alternative receptors and B-cell responses. Moreover, C10 modulated the activity of CD3{varepsilon}-containing CAR and TRuC T cells, attenuating cytokine production and promoting a central-memory-like phenotype associated with enhanced persistence. These findings establish targeted disruption of LCK recruitment as a viable strategy for fine-tuning T-cell responses and propose SH3(LCK) as a druggable domain with therapeutic potential for autoimmune diseases, graft-versus-host disease, and optimizing CAR T-cell therapies.

immunology↗

bioRxiv2025

Enhanced epigenetic modulation via mRNA-encapsulated lipid nanoparticles enables targeted anti-inflammatory control

Temporal transcriptional modulation of immune-related genes offers powerful therapeutic potential for treating inflammatory diseases. Here, we introduce an enhanced zinc finger (ZF)-based transcriptional repressor delivered via lipid nanoparticles for controlling immune signaling pathways in vivo. By targeting Myd88, an essential adaptor molecule involved in immunity, our system demonstrates therapeutic efficacy against septicemia in C57BL/6J mice and improves repeated AAV administration by reducing antibody responses. This epigenetic engineering approach provides a platform for safe and efficient immunomodulation applicable across diseases caused by imbalanced inflammatory responses.

immunology↗