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Biology subjects

Fernandes, K. A.

Publications and source records attributed to Fernandes, K. A..

3 recordsLinked to original sources

Modelling sterilisation strategies to maximise population impact and cost-efficiency in free-roaming dog populations

Free-roaming dog populations pose challenges to public health and animal welfare, and their management and protection is legally mandated in many countries to control zoonotic diseases such as rabies, reduce bites, mitigate fear of aggressive dogs, and preserve animal welfare. Although international organisations recommend holistic dog population management with surgical sterilisation as a key component, stakeholders report a lack of evidence-based guidance on effective and cost-efficient strategies. To address this, we developed a deterministic model of a closed free-roaming dog (FRD) population, including dogs dependent on and independent of humans, parameterised using data from southern India. We evaluated a wide range of sterilisation strategies varying duration, interval, frequency, intensity, targeting different population subsets, and fixed or responsive approaches. Strategies were assessed based on their effects on independent FRD population size and implementation costs. Female sterilisation coverage (FSC) strongly determined population reduction and cost-effectiveness. Repeated, short sterilisation periods with appropriately timed intervals and high early intensity best balanced population reduction and cost-efficiency. Excluding dependent dogs (cared for by humans) severely constrained population reduction, while male sterilisation enhanced impact at little extra cost, assuming direct effects on pregnancy rates. Costs and population impacts can be visualised on an interactive web application (https://field.shinyapps.io/DogPopSimApp), allowing practitioners and policymakers to explore sterilisation strategy outcomes. Overall, cost-effective population reduction required sustained commitment and coverage-driven strategies that balance welfare, population reduction and the operational needs of dog-mediated rabies control. Author SummaryFree-roaming street dogs live closely with people. While these animals are often valued members of the community, they can raise public health and safety concerns, including disease transmission, bites, and traffic accidents. To protect both human and animal health, many regions use surgical sterilisation to humanely manage street dog populations. However, running these programmes is complex and expensive, and community managers often lack clear guidance on how to maximise their limited resources. To address this, we used data from southern India to create a mathematical model of a street dog population. We simulated thousands of different sterilisation strategies to see how factors like campaign length, frequency, and targeted sub-groups impacted population size and total costs. We found that short, repeated sterilisation campaigns offer the best balance of population reduction and cost-efficiency. Crucially, these programmes must include dogs that are partially cared for by humans; otherwise, their puppies will continually replenish the street population. Although sterilisation of females drives population reduction, sterilising males alongside females enhanced the overall impact. Ultimately, our study provides practical, evidence-based guidance to help communities design effective and financially sustainable dog management programmes that improve public health and animal welfare.

ecology↗

Deep Learning of Functional Perturbations from Condensate Morphology

Biomolecular condensates compartmentalize the interior of living cells to spatiotemporally organize complex functions, yet linking molecular interactions within condensates to their mesoscale organization remains a major challenge. To bridge this gap, we developed a neural network-based framework - Deep-Phase - that uses microscopy images to quantitatively classify condensate morphology changes resulting from pharmacological alterations in associated biochemical processes. We use Deep-Phase to precisely quantify time- and concentration-dependent structural perturbations to the multiphase nucleolus and show that they are tightly coupled to potencies of drugs inhibiting rRNA transcription and processing. Applying Deep-Phase in a chemical screen, we identify a unique nucleolar morphology and discover a role for a DNA topoisomerase in rRNA processing. Mechanistic studies of this morphology provide insights into how interfaces between nucleolar subcompartments are maintained. We demonstrate Deep-Phases adaptability to diverse cell lines, labels, and condensates, offering a powerful platform for uncovering cellular organizing principles and therapeutic targets. HighlightsO_LIA deep learning framework, Deep-Phase, classifies and quantifies drug-induced changes in morphologies of nucleoli, nucleolar speckles, and viral cytoplasmic condensates, directly from images. C_LIO_LITime- and concentration-dependent morphological responses to perturbation predict associated disruptions in RNA transcription and processing. C_LIO_LIUsing Deep-Phase in a high-content small molecule screen reveals a unique nucleolar morphology induced by TOP1 inhibition. C_LIO_LITOP1 inhibition leads to reduced levels and processing of large ribosomal subunit precursors and provides a mechanism for maintenance of nucleolar phase boundaries. C_LI

molecular biology↗

Mkk4 and Mkk7 are important for retinal development and axonal injury-induced retinal ganglion cell death

The mitogen activated protein kinase (MAPK) pathway has been shown to be involved in both neurodevelopment and neurodegeneration. c-Jun N-terminal kinase (JNK), a MAPK shown to be important in retinal development and after optic nerve crush injury, is regulated by two upstream kinases: MKK4 and MKK7. The specific requirements of MKK4 and MKK7 in retinal development and retinal ganglion cell (RGC) death after axonal injury, however, are currently undefined. Optic nerve injury is an important insult in many neurologic conditions including traumatic, ischemic, inflammatory, and glaucomatous optic neuropathies. Mice deficient in Mkk4, Mkk7, and both Mkk4 and Mkk7 were generated. Immunohistochemistry was used to study the distribution and structure of retinal cell types and to assess RGC survival after optic nerve injury (mechanical controlled optic nerve crush; CONC). Adult Mkk4 and Mkk7 deficient retinas had all retinal cell types. With the exception of small areas of lamination defects with photoreceptors in Mkk4 deficient mice, the retinas of both mutants were grossly normal. Deficiency of Mkk4 or Mkk7 reduced JNK signaling after axonal injury in RGCs. Mkk4 and Mkk7 deficient retinas had a significantly greater percentage of surviving RGCs 35 days after CONC as compared to wildtype controls (Mkk4: 51.5%, Mkk7: 29.1% WT: 15.2%; p<0.001). Combined deficiency of Mkk4 and Mkk7 caused failure of optic nerve formation, irregular retinal axonal trajectories, disruption of retinal lamination, clumping of RGC cell bodies, and dendritic fasciculation of dopaminergic amacrine cells. These results suggest that MKK4 and MKK7 may serve redundant and unique roles in molecular signaling important for retinal development and injury response following axonal insult.

neuroscience↗