Madhusudan, M. | Search bioRxiv

bioRxiv2025

Real-Time Wide-Field Fluorescence Lifetime Imaging via Single-Snapshot Acquisition for Biomedical Applications

Fluorescence lifetime imaging (FLI) is a powerful tool for investigating molecular processes, microenvironmental parameters, and molecular interactions across tissue to (sub-)cellular levels. Despite its established value in numerous biomedical applications, conventional FLI techniques are hindered by long acquisition times. This limitation restricts their use in real-time scenarios, such as monitoring fast biological processes, studying live organisms, and in environments that require rapid imaging and immediate inference, such as clinical image-guided interventions. Here, we present a novel FLI approach that combines a large-format time-gated SPAD array with dual-gate acquisition capability, alongside a rapid lifetime determination algorithm. This integration allows for real-time fluorescence lifetime estimation through single-snapshot acquisitions, eliminating the need for traditional, time-consuming time-resolved data collection. We demonstrate the scalability and versatility of this method by achieving real-time FLI across challenging biomedical applications, ranging from capturing fast neural dynamics at the microscopic scale, performing multimodal 3D volumetric FLI of tumor organoids at the mesoscopic scale, to macroscale FLI in both direct and highly scattering regimes. Furthermore, we validate its utility in fluorescence lifetime-guided surgical procedures using tissue-mimicking phantoms. Overall, this new methodology significantly enhances the temporal and spatial capabilities of FLI, opening the door to the assessment of fast dynamic biomedical signals. It also enables the seamless integration of FLI into clinical workflows, particularly in applications like fluorescence-guided surgery.

bioengineering↗

bioRxiv2024

State of India's Birds 2023: A framework to leverage semi-structured citizen science for bird conservation

Birds and their habitats are threatened with extinction around the world. Regional assessments of the State of Birds are a vital means to prioritize data-driven conservation action by informing national and global policy. Such evaluations have traditionally relied on data derived from extensive, long-term, systematic surveys that require significant resources, limiting their feasibility to a few regions in the world. In the absence of such structured long-term datasets, semi-structured datasets have recently emerged as a promising alternative in other regions around the world. Semi-structured data are generated and uploaded by birdwatchers to citizen science platforms like eBird. Such data contain inherent biases because birdwatchers are not required to adhere to a fixed protocol. An evaluation of the status of birds from semi-structured data is therefore a difficult task that requires careful curation of data and the use of robust statistical methods to reduce errors and biases. In this paper, we present a methodology that was developed for this purpose, and was applied to produce the comprehensive State of Indias Birds (SoIB) 2023 report. SoIB 2023 assessed the status of 942 bird species in India by evaluating each species based on three metrics: 1) long-term change: change in abundance between the year 2022 and the year-interval pre-2000; 2) current annual trend: mean annual change in abundance from 2015 to 2022; and 3) distribution range size. We found evidence that 204 species have declined in the long term, and 142 species are currently declining. We present and discuss important insights about Indias birds that can guide research and conservation action in the region. We hope that the detailed methodology described here can act as a blueprint to produce State of Birds assessments from semi-structured citizen science datasets and springboard conservation action in many other regions where structured data is lacking but strong communities of birders exist. Open Research StatementThe primary data are already publicly available on eBird (Sullivan et al. 2014), and other data are already published in a GitHub repository (stateofindiasbirds 2024).

ecology↗