The role of light emitting diode in wound healing: A systematic review of experimental studies.

Wounds represent a growing global issue demanding increased attention. To expedite wound healing, technologies are under development, and light emitting diode (LED) devices of varying wavelengths are being explored for their stimulating influence on the healing process. This article presents a systematic literature review aiming to compile, organize, and analyze the impacts of LED devices on wound healing. This review is registered on the PROSPERO platform [CRD42023403870]. Two blinded authors conducted searches in the Pubmed, Web of Science, Scopus, Embase, and ScienceDirect databases. In vitro and in vivo experimental studies assessing LED utilization in the wound healing process were included. The search yielded 1010 studies, of which 27 were included in the review. It was identified that LED stimulates different healing pathways, promoting enhanced cell proliferation and migration, angiogenesis stimulation, increased collagen deposition, and modulation of the inflammatory response. Thus, it can be concluded that the LED stimulates cellular and molecular processes contingent on the utilized parameters. The effects depend on the standards used. Cell migration and proliferation were better influenced by green and red LED. The extracellular matrix components and angiogenesis were regulated by all wavelengths and the modulation of inflammation was mediated by green, red, and infrared LEDs.

Experimentation in cosmology: Intervening on the whole universe.

There are many arguments against the possibility of experimenting on the whole universe. This system seems to be too big to be manipulated, it exists in only one exemplar and its evolution is a non-repeatable process. In this paper, I claim that we can nonetheless talk about experimentation in cosmology if we use Woodward's non-anthropocentric notion of intervention. However, Woodward and other interventionists argued that an intervention was necessarily an exogenous causal process and thus that no intervention on a closed system such as the universe was possible. I discuss their argument and I determine the conditions under which a consistent notion of endogenous intervention on the universe can be defined. Then, I show that there is at least one cosmic phenomenon satisfying these conditions: the photon decoupling. Finally, I draw some conclusions from this analysis regarding a realist approach of cosmology.

A Novel Minimally Invasive Surgically Induced Skeletal Muscle Injury Model in Sheep.

Sports-related muscle injuries account for 10-55% of all injuries, which is a growing concern, especially given the aging world population. To evaluate the process of skeletal muscle injury and compare it with muscle lesions observed in humans, we developed a novel in vivo model in sheep. In this model, muscle injury was induced by an ultrasound-guided transverse biopsy at the myotendinous junction of the medial gastrocnemius muscle. Twelve male sheep were examined at 3, 7, 14, and 28 days post-injury. Histological, immunofluorescence, and MRI analyses indicate that our sheep model could resemble key human clinicopathological features. Statistically significant differences (p < 0.05) were observed in collagen I, dMHC, α-SMA, and CD68 immunohistochemical detection when comparing injured and healthy muscles. The injured gastrocnemius muscle exhibited elevated levels of type I collagen, infiltration of CD68(+) macrophages, angiogenesis, and the emergence of newly regenerated dMHC(+) myofibers, which persisted for up to 4 weeks post-injury. Similarly, the progression of muscle injury in the sheep model was assessed using advanced clinical 3 T MRI and compared with MRI scans from human patients. The data indicate that the sheep muscle injury model presents features similar to those observed in human skeletal muscle injuries. This makes it a valuable large animal model for studying muscle injuries and developing novel therapeutic strategies.

[From immersion to inclusion, a learning experience]. / De l'immersion à l'inclusion, une expérience apprenante.

As part of their training, volunteer nursing students from the Gers healthcare training institute were invited to take part in a sports exchange with a handibasket team. The main aim of the project was to change their perceptions of disability. Here, four of the students share their experiences and the benefits of the experience.

Accelerating the Discovery of Oxygen Reduction Electrocatalysts: High-Throughput Screening of Element Combinations in Pt-Based High-Entropy Alloys.

The vast number of element combinations and the explosive growth of composition space pose significant challenges to the development of high-entropy alloys (HEAs). Here, we propose a procedural research method aimed at accelerating the discovery of efficient electrocatalysts for oxygen reduction reaction (ORR) based on Pt-based quinary HEAs. The method begins with an element library provided by a large language model (LLM), combined with microscale precursor printing and pulse high-temperature synthesis techniques to prepare multi-element combination HEA array in one step. Through high-throughput measurement using scanning electrochemical cell microscopy (SECCM), precise identification of highly active HEA element combinations and exploration of composition space for a specific combination are achieved. Advantageous element combinations are further validated in practical electrocatalytic evaluations. The contributions of individual element sites and the synergistic effects among elements of such HEAs in enhancing reaction activity are elucidated via density functional theory (DFT) calculations. This method integrates high-throughput experiments, practical catalyst validation, and DFT calculations, providing a new pathway for accelerating the discovery of efficient multi-element materials in the field of energy catalysis.

High-throughput in silico workflow for optimization and characterization of multimodal chromatographic processes.

While high-throughput (HT) experimentation and mechanistic modeling have long been employed in chromatographic process development, it remains unclear how these techniques should be used in concert within development workflows. In this work, a process development workflow based on HT experiments and mechanistic modeling was constructed. The integration of HT and modeling approaches offers improved workflow efficiency and speed. This high-throughput in silico (HT-IS) workflow was employed to develop a Capto MMC polishing step for mAb aggregate removal. High-throughput batch isotherm data was first generated over a range of mobile phase conditions and a suite of analytics were employed. Parameters for the extended steric mass action (SMA) isotherm were regressed for the multicomponent system. Model validation was performed using the extended SMA isotherm in concert with the general rate model of chromatography using the CADET modeling software. Here, step elution profiles were predicted for eight RoboColumn runs across a range of ionic strength, pH, and load density. Optimized processes were generated through minimization of a complex objective function based on key process metrics. Processes were evaluated at lab-scale using two feedstocks, differing in composition. The results confirmed that both processes obtained high monomer yield (>85%) and removed ∼ 50 % $$ \sim 50\% $$ of aggregate species. Column simulations were then carried out to determine sensitivity to a wide range of process inputs. Elution buffer pH was found to be the most critical process parameter, followed by resin ionic capacity. Overall, this study demonstrated the utility of the HT-IS workflow for rapid process development and characterization.

Speech production and perception data collection in R: A tutorial for web-based methods using speechcollectr.

This tutorial is designed for speech scientists familiar with the R programming language who wish to construct experiment interfaces in R. We begin by discussing some of the benefits of building experiment interfaces in R-including R's existing tools for speech data analysis, platform independence, suitability for web-based testing, and the fact that R is open source. We explain basic concepts of reactive programming in R, and we apply these principles by detailing the development of two sample experiments. The first of these experiments comprises a speech production task in which participants are asked to read words with different emotions. The second sample experiment involves a speech perception task, in which participants listen to recorded speech and identify the emotion the talker expressed with forced-choice questions and confidence ratings. Throughout this tutorial, we introduce the new R package speechcollectr, which provides functions uniquely suited to web-based speech data collection. The package streamlines the code required for speech experiments by providing functions for common tasks like documenting participant consent, collecting participant demographic information, recording audio, checking the adequacy of a participant's microphone or headphones, and presenting audio stimuli. Finally, we describe some of the difficulties of remote speech data collection, along with the solutions we have incorporated into speechcollectr to meet these challenges.

Indignity of Nazi data: reflections on the utilization of illicit research.

Human rights may feel self-apparent to us, but less than 80 years ago, one of the most advanced countries at the time acted based on an utterly contrary ideology. The view of social Darwinism that abandoned the idea of the intrinsic value of human lives instead argued that oppression of the inferior is not only inevitable but desirable. One of the many catastrophic outcomes is the medical data obtained from inhuman experiments at concentration camps. Ethical uncertainty over whether the resulting insights should be a part of the medical literature provides a chance to consider the seemingly irreplaceable social construct of human dignity. Would any medical benefit justify the utilization of this illicit data? Would utilization even qualify as an insult to the dignity of the exploited subjects, or is this a question about intersubjective meaning? This work discusses the wisdom in blind adherence to human dignity, the possibility of retrospective insults, moral complicity, contrary viewpoints, and possible resolutions.

Prediction of Short- to Long-Term Cyclic Deformation Behavior and Fatigue Life of Polymers.

The prediction of mechanical behavior and fatigue life is of major importance for design and for replacing costly and time-consuming tests. The proposed approach for polymers is a combination of a fatigue model and a governing constitutive model, which is formulated using the Haward-Thackray viscoplastic model (1968) and is capable of capturing large deformations. The fatigue model integrates high- and low-cycle fatigue and is based on the concept of damage evolution and a moving endurance surface in the stress space, therefore memorizing the load history without requesting vague cycle-counting approaches. The proposed approach is applicable for materials in which the fatigue development is ductile, i.e., damage during the formation of microcracks controls most of the fatigue life (up to 90%). Moreover, damage evolution shows a certain asymptote at the ultimate of the low-cycle fatigue, a second asymptote at the ultimate of the high-cycle fatigue (which is near zero), and a curvature of how rapidly the transition between the asymptotes is reached. An interesting matter is that similar to metals, many polymers satisfy these constraints. Therefore, all the model parameters for fatigue can be given in terms of the Basquin and Coffin-Manson model parameters, i.e., satisfying well-defined parameters.

The activin/BMP-2 chimera AB204 promotes periodontal tissue regeneration in a buccal dehiscence model: a pilot study.

PURPOSE: A combination of activin and bone morphogenetic protein-2 (BMP-2), termed AB204, has been shown to improve osteogenic potential with fewer side effects than BMP-2 alone. This study was performed to evaluate the effect of AB204 on periodontal tissue regeneration in a dog buccal dehiscence model. METHODS: Buccal dehiscence defects were created on the maxillary premolars (P1, P2, and P3) of 6 mongrel dogs. After 5 weeks, the dogs were randomly assigned to 1 of 3 groups: the control, collagen matrix (CM), and CM/AB204 groups. Grafting procedures were then performed. The dogs were sacrificed 8 weeks after the grafting procedure, and volumetric and histological analyses were conducted. RESULTS: The thickness of the buccal gingiva in the CM/AB204 group was greater than those in the other groups at 2 weeks (P<0.05). The ridge width in the AB204/CM group exceeded the width in the other groups at 4 and 8 weeks; however, the difference was not statistically significant. Histological analysis revealed that the CM/AB204 group demonstrated the formation of new bone surrounded by newly formed periodontal ligament and cementum (P=0.035). CONCLUSIONS: The combined application of CM and AB204 shows promise in facilitating the regeneration of periodontal attachment, including the formation of new bone, cementum, and periodontal ligament.

Assessing two methods of webcam-based eye-tracking for child language research.

We assess the feasibility of conducting web-based eye-tracking experiments with children using two methods of webcam-based eye-tracking: automatic gaze estimation with the WebGazer.js algorithm and hand annotation of gaze direction from recorded webcam videos. Experiment 1 directly compares the two methods in a visual-world language task with five to six year-old children. Experiment 2 more precisely investigates WebGazer.js' spatiotemporal resolution with four to twelve year-old children in a visual-fixation task. We find that it is possible to conduct web-based eye-tracking experiments with children in both supervised (Experiment 1) and unsupervised (Experiment 2) settings - however, the webcam eye-tracking methods differ in their sensitivity and accuracy. Webcam video annotation is well-suited to detecting fine-grained looking effects relevant to child language researchers. In contrast, WebGazer.js gaze estimates appear noisier and less temporally precise. We discuss the advantages and disadvantages of each method and provide recommendations for researchers conducting child eye-tracking studies online.

Predicting drug solubility in organic solvents mixtures: A machine-learning approach supported by high-throughput experimentation.

A novel approach based on supervised machine-learning is proposed to predict the solubility of drugs and drug-like molecules in mixtures of organic solvents. Similar to quantitative structure-property relationship (QSPR) models, different solvent types are identified by molecular descriptors, which, in this study, are considered as UNIFAC subgroups. To overcome the potential lack of UNIFAC subgroups for the complex Active Pharmaceutical Ingredients (APIs) currently developed in the pharmaceutical industry, the API molecule is considered as a unique entity in the proposed modelling approach. Therefore, API solubility is predicted as a function of temperature, functional subgroups of the solvents and composition of the solvent mixture; in turn, regressors' correlation is handled through Partial Least-Squares (PLS) regression. The method is developed and tested with experimental data of a real API and 14 organic solvents that are industrially employed for crystallisation. Solubility predictions are accurate and precise for single solvents, binary mixtures and ternary mixtures of organic solvents at different compositions and temperatures, with a determination coefficient R2 ≥ 0.90. To further test the applicability of the model, the proposed approach is applied to 9 literature organic solubility datasets of drugs and drug-like compounds and compared to benchmark solubility models in the literature. Results show that the proposed approach provides satisfactory predictions: the majority of validation and calibration data have R2 = 0.95-0.99; the ratio between RMSE (root mean squared error) of the proposed method and the range of measured solubility values is from 1 to 3 orders of magnitude smaller than the RMSE ratio obtained by the benchmark models.

The advancement of artificial intelligence in biomedical research and health innovation: challenges and opportunities in emerging economies.

The advancement of artificial intelligence (AI), algorithm optimization and high-throughput experiments has enabled scientists to accelerate the discovery of new chemicals and materials with unprecedented efficiency, resilience and precision. Over the recent years, the so-called autonomous experimentation (AE) systems are featured as key AI innovation to enhance and accelerate research and development (R&D). Also known as self-driving laboratories or materials acceleration platforms, AE systems are digital platforms capable of running a large number of experiments autonomously. Those systems are rapidly impacting biomedical research and clinical innovation, in areas such as drug discovery, nanomedicine, precision oncology, and others. As it is expected that AE will impact healthcare innovation from local to global levels, its implications for science and technology in emerging economies should be examined. By examining the increasing relevance of AE in contemporary R&D activities, this article aims to explore the advancement of artificial intelligence in biomedical research and health innovation, highlighting its implications, challenges and opportunities in emerging economies. AE presents an opportunity for stakeholders from emerging economies to co-produce the global knowledge landscape of AI in health. However, asymmetries in R&D capabilities should be acknowledged since emerging economies suffers from inadequacies and discontinuities in resources and funding. The establishment of decentralized AE infrastructures could support stakeholders to overcome local restrictions and opens venues for more culturally diverse, equitable, and trustworthy development of AI in health-related R&D through meaningful partnerships and engagement. Collaborations with innovators from emerging economies could facilitate anticipation of fiscal pressures in science and technology policies, obsolescence of knowledge infrastructures, ethical and regulatory policy lag, and other issues present in the Global South. Also, improving cultural and geographical representativeness of AE contributes to foster the diffusion and acceptance of AI in health-related R&D worldwide. Institutional preparedness is critical and could enable stakeholders to navigate opportunities of AI in biomedical research and health innovation in the coming years.

Tacit social experimentation with digital technologies during the Covid-19 crisis.

In the management of the Covid 19 crisis, digital technologies were used in a major way. This article defends the hypothesis that these technologies took the form of a "tacit social experimentation". This article justifies this concept in three levels. The first part uses this concept to qualify the form of biopolitics that was implemented to manage the crisis. Digital technologies were used to discipline the population and, literally speaking, as instruments of knowledge of the population. Uncertainty forced experts to make preliminary observations and act to produce knowledge. Second, this article shows that the use of digital technologies during the crisis was experimental in a second sense. By promoting telemedicine within a more flexible legal framework, the authorities authorised an experimental use of telemedicine without knowledge or control of its side effects. Finally, the article defends the use of the concept of "tacit social experimentation" for ethical and political purposes. For indeed, understanding the experiments carried out during the crisis begs the question of the involvement of the participants and their democratic steering.

Utility of pemafibrate in nonalcoholic steatohepatitis model mice induced by a choline-deficient, high-fat diet and dextran sulfate sodium.

Aim: The purpose of this study was to examine the effect of pemafibrate in a murine model of non-alcoholic steatohepatitis (NASH). Methods: Forty-two, 19-week-old, male, C57BL/6J mice were divided into three groups: a Control group (n = 14), a dextran sulfate sodium (DSS) group (n = 14), and a DSS + PEM group (n = 14). All mice were given a standard rodent diet for the first week, followed by a choline-deficient, high-fat diet (CDHF) for the next 12 weeks. The 22nd day after the animals arrived was taken as Day 1 of the experiment. The Control group continued the CDHF diet and MilliQ water. The DSS group continued the CDHF diet, but starting on Day 1, the group received 0.8 % DSS to drink for 7 consecutive days, followed by MilliQ water for 10 days; this was taken as one course, and it was repeated on the same schedule until autopsy. The DSS + PEM group received the CDHF diet with PEM 0.1 mg/kg/day. Their drinking water was the same as that of the DSS group. On Seven animals from each group were autopsied on each of Day 50 and Day 120, and histopathological and immunohistochemical examinations, as well as quantitative RNA and cytokine measurements, of autopsied mice were performed. Results: Pemafibrate improved hepatic steatosis (decreased steatosis area), improved liver inflammation enhanced by DSS (decreased aspartate transaminase and alanine aminotransferase), improved hepatic fibrosis promoted by DSS (decreased fibrotic areas and a marker of fibrosis), inhibited tumorigenesis, and decreased intestinal inflammation in the NASH model mice. Conclusions: In a murine model of NASH, mixing PEM 0.1 mg/kg/day into the diet inhibited disease progression and tumor formation.

Direct Fabrication of Atomically Defined Pores in MXenes Using Feedback-Driven STEM.

Controlled fabrication of nanopores in 2D materials offer the means to create robust membranes needed for ion transport and nanofiltration. Techniques for creating nanopores have relied upon either plasma etching or direct irradiation; however, aberration-corrected scanning transmission electron microscopy (STEM) offers the advantage of combining a sub-Å sized electron beam for atomic manipulation along with atomic resolution imaging. Here, a method for automated nanopore fabrication is utilized with real-time atomic visualization to enhance the mechanistic understanding of beam-induced transformations. Additionally, an electron beam simulation technique, Electron-Beam Simulator (E-BeamSim) is developed to observe the atomic movements and interactions resulting from electron beam irradiation. Using the MXene Ti3C2Tx, the influence of temperature on nanopore fabrication is explored by tracking atomic transformations and find that at room temperature the electron beam irradiation induces random displacement and results in titanium pileups at the nanopore edge, which is confirmed by E-BeamSim. At elevated temperatures, after removal of the surface functional groups and with the increased mobility of atoms results in atomic transformations that lead to the selective removal of atoms layer by layer. This work can lead to the development of defect engineering techniques within functionalized MXene layers and other 2D materials.

[Exavir: Implementation and evaluation of experimental pharmacology skills acquisition by pharmacy students]. / Exavir : mise en place et évaluation de l'acquisition de compétences en pharmacologie expérimentale par des étudiants en pharmacie.

With the evolution of European and French regulations on animal experimentation in higher education, taking greater account of animal welfare, the University of Angers has developed a virtual animal experimentation software named Exavir. Used for practical work (PW) in physiology, pharmacology and toxicology in the Health, Sciences, and engineering curricula, Exavir can be used to simulate various experiments for teaching purposes, in vivo or ex vivo. Thanks to an original approach integrating serious games with different scenarios, students gain autonomy and become directly involved in their learning. In addition, Exavir's collaborative and participative development approach fosters inter-university partnerships and the emergence of innovative teaching methods. A hybrid pilot study carried out on a sample of 22 students in the Pharmacy Department of the Faculty of Health showed that Exavir improved students' acquisition of teaching skills in both physiology and pharmacology, compared with practical work only based on animal organs. These encouraging results demonstrate for the first time the pedagogical advantages of Exavir and confirm the interest in developing such a platform. In this context, it appears that Exavir also opens up the possibility of adapting the practical work offered within universities, and thus responding to the changing ethical issues of the coming decades.

Neural correlates of metacognition: Disentangling the brain circuits underlying prospective and retrospective second-order judgments through noninvasive brain stimulation.

Metacognition encompasses the capability to monitor and control one's cognitive processes, with metamemory and metadecision configuring among the most studied higher order functions. Although imaging experiments evaluated the role of disparate brain regions, neural substrates of metacognitive judgments remain undetermined. The aim of this systematic review is to summarize and discuss the available evidence concerning the neural bases of metacognition which has been collected by assessing the effects of noninvasive brain stimulation (NIBS) on human subjects' metacognitive capacities. Based on such literature analysis, our goal is, at first, to verify whether prospective and retrospective second-order judgments are localized within separate brain circuits and, subsequently, to provide compelling clues useful for identifying new targets for future NIBS studies. The search was conducted following the preferred reporting items for systematic reviews and meta-analyses guidelines among PubMed, PsycINFO, PsycARTICLES, PSYNDEX, MEDLINE, and ERIC databases. Overall, 25 studies met the eligibility criteria, yielding a total of 36 experiments employing transcranial magnetic stimulation and 16 ones making use of transcranial electrical stimulation techniques, including transcranial direct current stimulation and transcranial alternating current stimulation. Importantly, we found that both perspective and retrospective judgments about both memory and perceptual decision-making performances depend on the activation of the anterior and lateral portions of the prefrontal cortex, as well as on the activity of more caudal regions such as the premotor cortex and the precuneus. Combining this evidence with results from previous imaging and lesion studies, we advance ventromedial prefrontal cortex as a promising target for future NIBS studies.

Experimental necrotizing enterocolitis using oral lipopolysaccharide and protective role of breastmilk. / Enterocolitis necrotizante experimental con lipopolisacárido oral y función protectora de la leche materna.

INTRODUCTION: Necrotizing enterocolitis (NEC) is a life-threatening condition that afflicts neonates. Breastfeeding has demonstrated to play a protective role against it. By administering lipopolysaccharides (LPS) orally in newborn rats (NBR), we have developed an experimental model to induce NEC-like gut damage. Our aim was to assess the macroscopic and microscopic appearance of the gut, to evaluate the presence of NEC and study the role of breast milk (BM). MATERIALS AND METHODS: NBR were divided into 3 groups: Group A (control, n= 10) remained with the mother, group B (LPS, n= 25) was isolated after birth, gavage-fed with special rat formula and oral LPS, then submitted to stress (hypoxia after gavage) and group c (BM, n= 12) was breastfed once after birth, then isolated, and submitted to stress like group B. On day 4, NBR were sacrificed, and intestine was harvested and assessed. RESULTS: In the control group NEC was not present either macroscopically or histologically. Both groups submitted to stress (B and C) presented a global incidence of NEC of 73%. Most of group B developed histologic signs of NEC (85%) and group C showed a statistically lower incidence of NEC (50%, p= 0.04), playing the BM a protective role against NEC (OR= 0.19; 95% CI: 0.40-0.904). CONCLUSION: Our model showed a significant incidence of NEC in NBR (73%) with the same protective role of BM as in newborn humans, achieving a reliable and reproducible experimental NEC model. This will allow us to investigate new potential therapeutic targets for a devastating disease that currently lacks treatment.

INTRODUCCION: La enterocolitis necrotizante (ECN) es una enfermedad potencialmente mortal que afecta a los neonatos, y frente a la que la leche materna ha demostrado tener un papel protector. Administrando lipopolisacáridos (LPS) por vía oral en ratas recién nacidas (RRN), hemos desarrollado un modelo experimental para inducir un daño intestinal similar al que provoca la ECN con objeto de evaluar el aspecto macroscópico y microscópico del intestino, y de ese modo, analizar la presencia de ECN y estudiar el papel que desempeña la leche materna (LM). MATERIAL Y METODOS: Las RRN se dividieron en tres grupos: el grupo A (control, n= 10) permaneció con su madre; el grupo B (LPS, n= 25) fue aislado tras el nacimiento, alimentado por sonda con una fórmula especial para ratas y LPS oral, y sometido a estrés (hipoxia tras sonda); y el grupo C (LM, n= 12) fue alimentado con leche materna tras el nacimiento y posteriormente aislado y sometido a estrés al igual que el grupo B. El día 4 se sacrificó a las RRN y se recuperaron sus intestinos para su posterior evaluación. RESULTADOS: En el grupo de control, no se observó ECN ni macroscópica ni histológicamente, mientras que los dos grupos sometidos a estrés (B y C) presentaron una incidencia global de la ECN del 73%. La mayoría de los sujetos del grupo B desarrollaron signos histológicos de ECN (85%), y los del grupo C registraron una incidencia de la ECN estadísticamente menor (50%, p= 0,04), lo que significa que la LM desempeña una función protectora frente a la ECN (OR= 0,19; IC 95%: 0,40-0,904). CONCLUSION: Nuestro modelo reveló una incidencia significativa de la ECN en RRN (73%), desempeñando la LM la misma función protectora que en el caso de los humanos recién nacidos, lo que significa que este modelo experimental de ECN es fiable y reproducible. Gracias a dicho logro, podremos investigar nuevos y potenciales objetivos terapéuticos para una peligrosa enfermedad que, a día de hoy, carece de tratamiento.

Sequential Treatment Application Robot (STAR) for high-replication marine experimentation.

Marine organisms are often subject to numerous anthropogenic stressors, resulting in widespread ecosystem degradation. Physiological responses to these stressors, however, are complicated by high biological variability, species-specific sensitivities, nonlinear relationships, and countless permutations of stressor combinations. Nevertheless, quantification of these relationships is paramount for parameterizing predictive tools and ultimately for effective management of marine resources. Multi-level, multi-stressor experimentation is therefore key, yet the high replication required has remained a logistical challenge and a financial barrier. To overcome these issues, we created an automated system for experimentation on marine organisms, the Sequential Treatment Application Robot (STAR). The system consists of a track-mounted robotic arm that sequentially applies precision treatments to independent aquaria via syringe and peristaltic pumps. The accuracy and precision were validated with dye and spectrophotometry, and stability was demonstrated by maintaining corals under treatment conditions for more than a month. The system is open source and scalable in that additional treatments and replicates may be added without incurring multiplicative costs. While STAR was designed for investigating the combined impacts of nutrients, warming, and disease on reef-building corals, it is highly customizable and may be used for experimentation involving a diverse array of treatments and species.