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Biology subjects

Ruiz, C.

Publications and source records attributed to Ruiz, C..

10 recordsLinked to original sources

FiberPro 1.0: Multiagent AI-Guided Design for High-Throughput Production and Conformal Deposition of Functional Protein Micro/Nanofibers

Functional protein micro/nanofibers integrate high specific surface areas with bioactive architectures but remain hampered low production throughput and severe processing instability. Focused rotary jet spinning (FRJS) shows promising to break these throughput constraints while enabling direct, conformal deposition onto complex, irregular substrates. However, navigating FRJS's narrow processing windows in proteins remains failure-prone without closed-loop experimental guidance. Here, we report FiberPro 1.0, a large language model driven multi agent framework that unites high-throughput spinning with real-time experimental feedback for autonomous design, execution, and optimization. Across three protein systems, FiberPro 1.0 converged on spinnable formulations within an average of two iterations. To demonstrate high-throughput conformal deposition in a translational setting, FiberPro designed a zein-based active packaging system applied directly onto diverse food matrices. The resulting conformal coating combined potent antibacterial activity with real-time freshness monitoring, markedly suppressing Escherichia coli and extending shelf life. This work connects autonomous AI reasoning with high-throughput processing, establishing a verifiable route for scalable manufacturing and conformal coating of functional protein micro/nanofibers.

bioengineering↗

Sexually Dimorphic Visual Processing in the Yellow-Fever Mosquito, Aedes aegypti

Flying insects process motion across the visual scene to regulate their ground speed, correct course deviations, and behaviorally relevant stimuli such as avoiding predators or finding hosts. The yellow-fever mosquito Aedes aegypti provides a useful model for studying these visually guided behaviors, as both sexes use vision to track moving features. Approaching a moving target presents mosquitoes with a demanding visual problem: they must extract target motion from the changing visual scene while simultaneously controlling their own flight and responding to potentially dangerous movements. To understand this, we first studied free-flight responses to static and moving vertical targets in a wind tunnel system capable of projecting dynamic visual stimuli, and found that males and females are sexually dimorphic with respect to their responses to target motion. When the feature was static, both males and females advanced toward it during flight; however, when it oscillated laterally at 2 Hz, only females continued to pursue it. In a subsequent yaw-unrestrained magnetic tethering paradigm, we showed that this divergence cannot be simply explained by sex-specific differences in visuomotor tuning dynamics, while micro-CT reconstructions revealed only modest sexual differences in eye morphology and broadly similar patterns of estimated spatial acuity. Together, these results indicate that males retain the biomechanical capacity to track oscillating targets but actively suppress approach behavior during free flight, whereas females pursue salient features independently of target motion. This pattern aligns with sex-divergent visual ecologies because the risk of approaching a large moving feature too closely likely outweighs the benefits for males seeking mates, whereas for host-seeking females the reproductive necessity of blood feeding overrides this avoidance.

neuroscience↗

Assessing pollinator community recovery in restored agroecosystems using the recovery debt framework

Recovery debt (RD) quantifies the interim deficit of biodiversity and function during the recovery process after disturbance. Unlike typical recovery indices derived from data on experimental-control comparisons, RD further considers the target (reference) biodiversity level, modelling the rate at which it is approached over time. However, the application of the RD approach to active restoration has not been explicitly implemented to date. Here, we extend the RD framework to evaluate active ecological restoration in agricultural systems, defining the onset of recovery as the shift from intensive to wildlife-friendly management. We applied this approach to assess short-term pollinator recovery in 14 olive groves across a gradient of farming intensification and landscape complexity in southern Spain. Restoration actions included adopting low-intensity ground cover management and actively restoring field margins. At one, three, and five years post-restoration, we assessed community responses by quantifying bee abundance, species richness, plant-bee network properties, and flower visitation rates. Reference systems were defined by olive groves in complex landscapes with low-intensity herb cover management and organic farming practices. Following restoration, the RD of bee abundance decreased from 71% to 55%. We found no significant effects of pre-intervention agricultural management on RD. Instead, across sites, the reduction of the RD (i.e., recovery) of bee abundance, richness, network connectance and flower visitation rate was strongly mediated by the availability of high-quality semi-natural areas in the surrounding landscape and by the ecological contrast created by restoration interventions at both the farm and floral patch levels. RD for other network metrics showed no significant pattern of variation. Our study demonstrates that wildlife-friendly management and targeted habitat restoration can rapidly reduce recovery debt for bee abundance and function in permanent agroecosystems. However, the recovery of more complex interaction-network properties likely requires longer timescales.

ecology↗

A bug's tale: revealing the history, biogeography and ecological patterns of 500 years of insect introductions

The arrival of Europeans to the Americas triggered a massive exchange of organisms on a continental scale. This exchange was accelerated by the amazing increase in the movement of people and goods during the 20th century. In Chile, scientific and technical literature contains hundreds of records of exotic insect species in different parts of the territory, from the hyperarid Atacama Desert to the Magallanes Region. Here, we analyze the biological patterns obtained from the database of introductions of exotic insects to Chile from the European arrival to the present. Our task includes a review of old records in museums, libraries, collections, expedition records and catalogs. Almost 600 species of exotic insects have been reported in Chile. Introductions started at the very arrival of Europeans to the central valley of Chile and underwent a huge acceleration in the second half of the 20th century. The order Hemiptera was the most prevalent among introduced insects. Most species are linked to agriculture and forestry. Species are of Palearctic origin in more than 50% of the records. In terms of temporal trends, the rate of introduced species shows an abrupt increase at the beginning of the 1950s. This change may be associated with the strong development in agriculture and forestry in Chile after World War II and the increase in intercontinental air traffic. We believe that the understanding of past patterns of introductions is an important component in the design of current policies to minimize the impact of invasive insects.

ecology↗

An inexpensive setup for robust activity tracking in small animals: Portable Locomotion Activity Monitor (pLAM)

O_LIAdvances in computer vision and deep learning have automated animal behaviour studies that previously required tedious manual input. However, tracking activity of small and fast flying animals remains a hurdle, especially in a field setting with variable light conditions. Commercial locomotor activity monitors (LAMs) can be expensive, closed source, and generally limited to laboratory settings. C_LIO_LIHere, we present a portable locomotion activity monitor (pLAM), a mobile activity detector to quantify small animal circadian activity. Our setup uses inexpensive components, is based on open-source motion tracking software, and is easy to assemble and use in the field. It runs off-grid, supports low-light tracking with infrared lights, and can implement arbitrary light cycle colours and brightnesses with programmable LEDs. We provide a user-friendly guide to assembling pLAM hardware and accessing its pre-configured software and guidelines for using it in other systems. C_LIO_LIWe benchmarked pLAM for insects under various lab and field conditions, then compared results to a commercial activity detector. They offer broadly similar activity measures, but our setup captures flight and bouts of motion that are often missed by beam-breaking activity detection. C_LIO_LIpLAM will enable high-throughput quantification of small animal location and activity in a low-cost and accessible manner, crucial to studying behaviour that can help inform conservation and management decisions. C_LI

animal behavior and cognition↗

Comparison of heat-inactivated and infectious SARS-CoV-2 across indoor surface materials shows comparable RT-qPCR viral signal intensity and persistence

Environmental monitoring in public spaces can be used to identify surfaces contaminated by persons with COVID-19 and inform appropriate infection mitigation responses. Research groups have reported detection of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) on surfaces days or weeks after the virus has been deposited, making it difficult to estimate when an infected individual may have shed virus onto a SARS-CoV-2 positive surface, which in turn complicates the process of establishing effective quarantine measures. In this study, we determined that reverse transcription-quantitative polymerase chain reaction (RT-qPCR) detection of viral RNA from heat-inactivated particles experiences minimal decay over seven days of monitoring on eight out of nine surfaces tested. The properties of the studied surfaces result in RT-qPCR signatures that can be segregated into two material categories, rough and smooth, where smooth surfaces have a lower limit of detection. RT-qPCR signal intensity (average quantification cycle (Cq)) can be correlated to surface viral load using only one linear regression model per material category. The same experiment was performed with infectious viral particles on one surface from each category, with essentially identical results. The stability of RT-qPCR viral signal demonstrates the need to clean monitored surfaces after sampling to establish temporal resolution. Additionally, these findings can be used to minimize the number of materials and time points tested and allow for the use of heat-inactivated viral particles when optimizing environmental monitoring methods. ImportanceEnvironmental monitoring is an important tool for public health surveillance, particularly in settings with low rates of diagnostic testing. Time between sampling public environments, such as hospitals or schools, and notifying stakeholders of the results should be minimal, allowing decisions to be made towards containing outbreaks of coronavirus disease 2019 (COVID-19). The Safer At School Early Alert program (SASEA) [1], a large-scale environmental monitoring effort in elementary school and child care settings, has processed > 13,000 surface samples for SARS-CoV-2, detecting viral signals from 574 samples. However, consecutive detection events necessitated the present study to establish appropriate response practices around persistent viral signals on classroom surfaces. Other research groups and clinical labs developing environmental monitoring methods may need to establish their own correlation between RT - qPCR results and viral load, but this work provides evidence justifying simplified experimental designs, like reduced testing materials and the use of heat-inactivated viral particles.

microbiology↗

Discovery of disease treatment mechanisms through the multiscale interactome

Most diseases disrupt multiple proteins, and drugs treat such diseases by restoring the functions of the disrupted proteins. How drugs restore these functions, however, is often unknown as a drugs therapeutic effects are not limited only to the proteins that the drug directly targets. Here, we develop the multiscale interactome, a powerful approach to explain disease treatment. We integrate disease-perturbed proteins, drug targets, and biological functions into a multiscale interactome network, which contains 478,728 interactions between 1,661 drugs, 840 diseases, 17,660 human proteins, and 9,798 biological functions. We find that a drugs effectiveness can often be attributed to targeting proteins that are distinct from disease-associated proteins but that affect the same biological functions. We develop a random walk-based method that captures how drug effects propagate through a hierarchy of biological functions and are coordinated by the protein-protein interaction network in which drugs act. On three key pharmacological tasks, we find that the multiscale interactome predicts what drugs will treat a given disease more effectively than prior approaches, identifies proteins and biological functions related to treatment, and predicts genes that interfere with treatment to alter drug efficacy and cause serious adverse reactions. Our results indicate that physical interactions between proteins alone are unable to explain the therapeutic effects of drugs as many drugs treat diseases by affecting the same biological functions disrupted by the disease rather than directly targeting disease proteins or their regulators. We provide a general framework for identifying proteins and biological functions relevant in treatment, even when drugs seem unrelated to the diseases they are recommended for.

bioinformatics↗

Early-Career Coordinated Distributed Experiments: Empowerment Through Collaboration

Coordinated distributed experiments (CDEs) enable the study of large-scale ecological patterns in geographically dispersed areas, while simultaneously providing broad academic and personal benefits for the participants. However, the effective involvement of early-career researchers (ECRs) presents major challenges. Here, we analyze the benefits and challenges of the first CDE exclusively led and conducted by ECRs (i.e. ECR-CDE), which sets a baseline for similar CDEs, and we provide recommendations for successful CDE execution. ECR-CDEs achieve most of the outcomes identified in conventional CDEs as well as extensive benefits for the young cohort of researchers, including: (i) receiving scientific credit, (ii) peer-training in new concepts and methods, (iii) developing leadership and communication skills, (iv) promoting a peer network among ECRs, and (v) building on individual engagement and independence. We also discuss the challenges of ECR-CDEs, which are mainly derived from the lack of independence and instability of the participants, and we suggest mechanisms to address them, such as resource re-allocation and communication strategies.

scientific communication and education↗

Phase space characterization for gene circuit design

Genetic circuit design requires characterization of the dynamics of synthetic gene expression. This is a difficult problem since gene expression varies in complex ways over time and across different contexts. Here we present a novel method for characterizing the dynamics of gene expression with a few parameters that account for changes in cellular context (host cell physiology) and compositional context (adjacent genes). The dynamics of gene circuits were characterized by a trajectory through a multi-dimensional phase space parameterized by the expression levels of each of their constituent transcriptional units (TU). These trajectories followed piecewise linear dynamics, with each dynamical regime corresponding to different growth regimes, or cellular contexts. Thus relative expression rates were changed by transitions between growth regimes, but were constant in each regime. We present a plausible two-factor mathematical model for this behavior based on resource consumption. By analyzing different combinations of TUs, we then showed that relative expression rates were significantly affected by the neighboring TU (compositional context), but maintained piecewise linear dynamics across cellular and compositional contexts. Taken together these results show that TU expression dynamics could be predicted by a reference TU up to a context dependent scaling factor. This model provides a framework for design of genetic circuits composed of TUs. A common sharable reference TU may be chosen and measured in the cellular contexts of interest. The output of each TU in the circuit may then be predicted from a simple function of the output of the reference TU in the given cellular context. This will aid in genetic circuit design by providing simple models for the dynamics of gene circuits and their constituent TUs.

synthetic biology↗

Chemogenetic ligands for translational neurotheranostics

Designer Receptors Exclusively Activated by Designer Drugs (DREADDs) are a popular chemogenetic technology for manipulation of neuronal activity in uninstrumented awake animals with potential for precision medicine-based clinical theranostics. DREADD ligands developed to date are not appropriate for such translational applications. The prototypical DREADD agonist clozapine N-oxide (CNO) lacks brain entry and converts to clozapine. The second-generation DREADD agonist, Compound 21 (C21), was developed to overcome these limitations. We found that C21 has low brain penetrance, weak affinity, and low in vivo DREADD occupancy. To address these drawbacks, we developed two new DREADD agonists, JHU37152 and JHU37160, and the first dedicated positron emission tomography (PET) DREADD radiotracer, [18F]JHU37107. JHU37152 and JHU37160 exhibit high in vivo DREADD potency. [18F]JHU37107 combined with PET allows for DREADD detection in locally-targeted neurons and at their long-range projections, enabling for the first time, noninvasive and longitudinal neuronal projection mapping and potential for neurotheranostic applications.

neuroscience↗