Hasil untuk "Microbial ecology"

Mingzhuang Wang, Yvyang Li, Xiyang Zhang et al.

Coral reefs, crucial for sustaining marine biodiversity and ecological processes (e.g., nutrient cycling, habitat provision), face escalating threats, underscoring the need for efficient monitoring. Coral reef ecological monitoring faces dual challenges of low efficiency in manual analysis and insufficient segmentation accuracy in complex underwater scenarios. This study develops the YH-MINER system, establishing an intelligent framework centered on the Multimodal Large Model (MLLM) for "object detection-semantic segmentation-prior input". The system uses the object detection module (mAP@0.5=0.78) to generate spatial prior boxes for coral instances, driving the segment module to complete pixel-level segmentation in low-light and densely occluded scenarios. The segmentation masks and finetuned classification instructions are fed into the Qwen2-VL-based multimodal model as prior inputs, achieving a genus-level classification accuracy of 88% and simultaneously extracting core ecological metrics. Meanwhile, the system retains the scalability of the multimodal model through standardized interfaces, laying a foundation for future integration into multimodal agent-based underwater robots and supporting the full-process automation of "image acquisition-prior generation-real-time analysis".

Eshta Bhardwaj, Rohan Alexander, Christoph Becker

The accelerating development and deployment of AI technologies depend on the continued ability to scale their infrastructure. This has implied increasing amounts of monetary investment and natural resources. Frontier AI applications have thus resulted in rising financial, environmental, and social costs. While the factors that AI scaling depends on reach its limits, the push for its accelerated advancement and entrenchment continues. In this paper, we provide a holistic review of AI scaling using four lenses (technical, economic, ecological, and social) and review the relationships between these lenses to explore the dynamics of AI growth. We do so by drawing on system dynamics concepts including archetypes such as "limits to growth" to model the dynamic complexity of AI scaling and synthesize several perspectives. Our work maps out the entangled relationships between the technical, economic, ecological and social perspectives and the apparent limits to growth. The analysis explains how industry's responses to external limits enables continued (but temporary) scaling and how this benefits Big Tech while externalizing social and environmental damages. To avoid an "overshoot and collapse" trajectory, we advocate for realigning priorities and norms around scaling to prioritize sustainable and mindful advancements.

Benjamin David Winter, William J. Teahan

When employing an evolutionary algorithm to optimize a neural networks architecture, developers face the added challenge of tuning the evolutionary algorithm's own hyperparameters - population size, mutation rate, cloning rate, and number of generations. This paper introduces Neuvo Ecological Neural Architecture Search (ENAS), a novel method that incorporates these evolutionary parameters directly into the candidate solutions' phenotypes, allowing them to evolve dynamically alongside architecture specifications. Experimental results across four binary classification datasets demonstrate that ENAS not only eliminates manual tuning of evolutionary parameters but also outperforms competitor NAS methodologies in convergence speed (reducing computational time by 18.3%) and accuracy (improving classification performance in 3 out of 4 datasets). By enabling "greedy individuals" to optimize resource allocation based on fitness, ENAS provides an efficient, self-regulating approach to neural architecture search.

Joseph Cummings, Kyle J. -M. Dahlin, Elizabeth Gross et al.

Changes in environmental or system parameters often drive major biological transitions, including ecosystem collapse, disease outbreaks, and tumor development. Analyzing the stability of steady states in dynamical systems provides critical insight into these transitions. This paper introduces an algebraic framework for analyzing the stability landscapes of ecological models defined by systems of first-order autonomous ordinary differential equations with polynomial or rational rate functions. Using tools from real algebraic geometry, we characterize parameter regions associated with steady-state feasibility and stability via three key boundaries: singular, stability (Routh-Hurwitz), and coordinate boundaries. With these boundaries in mind, we employ routing functions to compute the connected components of parameter space in which the number and type of stable steady states remain constant, revealing the stability landscape of these ecological models. As case studies, we revisit the classical Levins-Culver competition-colonization model and a recent model of coral-bacteria symbioses. In the latter, our method uncovers complex stability regimes, including regions supporting limit cycles, that are inaccessible via traditional techniques. These results demonstrate the potential of our approach to inform ecological theory and intervention strategies in systems with nonlinear interactions and multiple stable states.

Romain Lan, Romain Lan, Lucas De Paula Ramos et al.

Dario Leonardo Balacco, Ajoy Bardhan, Ajoy Bardhan et al.

IntroductionThe cutaneous microbiome plays an essential role in guarding against invasive pathogens and maintaining healthy skin homeostasis. Several studies have demonstrated the importance of a healthy skin microbiome through its alteration in several diseases. Differing skin characteristics across the body (temperature, pH, humidity) create distinct ecological niches inhabited by diverse microbial communities. The study of cutaneous microbiota is further complicated by numerous variables at all stages of investigation, including study design, skin sampling method, sample storage, sample processing, sequencing, and data analysis. Utilisation of standardised approaches is critical for reproducibility and comparison between skin microbiome studies. However, there is a notable lack of standardisation of sampling methodologies in the literature. Studies have employed differing sampling strategies and conditions which may affect microbiota characterisation. MethodsAntecubital fossa was sampled from sixteen individuals using sterile dry cotton swabs or eSwabs. Sterile phosphate buffered saline, or 0.9% sterile saline were used as moistening solutions. Samples were then either stored at room temperature for 30 minutes or stored at -80°C for at least 24 hours before processing. Cutaneous microbiome was identified using 16S sequencing.ResultsComparative analysis determined whether the type of swab (cotton/eSwab), moistening solution (saline solution/phosphate buffered saline), duration of swabbing (30 sec/1 min), and sample storage temperature (room temperature/-80°C) affect sampling and identification of skin microbial communities. Comparison of the total DNA yield extracted using different conditions showed that while moistening solution, duration of swabbing, and storage conditions did not affect the total DNA amount, using eSwabs yielded higher biomass.DiscussionSampling approaches are critical for the success of sequencing. The conditions investigated in this study did not influence microbiome profiling allowing consistent sampling of the microbiota. However, data clustering was affected more by individual subject than by the conditions investigated, suggesting the importance of recognizing inter-individual variability as an important factor in real-life skin microbiome studies.

Lia Oliver, Marta Malagón, Sara Ramió-Pujol et al.

BackgroundInterest in the intestinal microbiota has surged in recent years, leading to the development of various microbiota tests utilizing stool analysis. This study aimed to assess the clinical utility of the TestUrGut.ResultsThe abundances of different microbial markers analyzed correlated with various factors and symptoms. While no age differences were observed, an increase in A. muciniphila abundance was noted in women compared to men. Body mass index significantly influenced the abundance of A. muciniphila and M. smithii. Additionally, variations in the abundances of A. muciniphila and M. smithii, as well as a greater presence of Firmicutes or Bacteroidetes based on stool patterns, were linked to diarrhea or constipation. The dysbiosis index was validated, distinguishing between temporary and pathological dysbiosis.ConclusionsThis study revealed significant relationships between the intestinal microbiota and digestive tract symptoms. Microbial markers have emerged as robust indicators of the overall state of the intestinal microbiota, demonstrating that variations are closely associated with patients’ clinical symptoms.

Akshay K. Jagadish, Julian Coda-Forno, Mirko Thalmann et al.

Ecological rationality refers to the notion that humans are rational agents adapted to their environment. However, testing this theory remains challenging due to two reasons: the difficulty in defining what tasks are ecologically valid and building rational models for these tasks. In this work, we demonstrate that large language models can generate cognitive tasks, specifically category learning tasks, that match the statistics of real-world tasks, thereby addressing the first challenge. We tackle the second challenge by deriving rational agents adapted to these tasks using the framework of meta-learning, leading to a class of models called ecologically rational meta-learned inference (ERMI). ERMI quantitatively explains human data better than seven other cognitive models in two different experiments. It additionally matches human behavior on a qualitative level: (1) it finds the same tasks difficult that humans find difficult, (2) it becomes more reliant on an exemplar-based strategy for assigning categories with learning, and (3) it generalizes to unseen stimuli in a human-like way. Furthermore, we show that ERMI's ecologically valid priors allow it to achieve state-of-the-art performance on the OpenML-CC18 classification benchmark.

John S. McAlister, Michael J. Blum, Yana Bromberg et al.

The built environment provides an excellent setting for interdisciplinary research on the dynamics of microbial communities. The system is simplified compared to many natural settings, and to some extent the entire environment can be manipulated, from architectural design, to materials use, air flow, human traffic, and capacity to disrupt microbial communities through cleaning. Here we provide an overview of the ecology of the microbiome in the built environment. We address niche space and refugia, population and community (metagenomic) dynamics, spatial ecology within a building, including the major microbial transmission mechanisms, as well as evolution. We also address the landscape ecology connecting microbiomes between physically separated buildings. At each stage we pay particular attention to the actual and potential interface between disciplines, such as ecology, epidemiology, materials science, and human social behavior. We end by identifying some opportunities for future interdisciplinary research on the microbiome of the built environment.

Jiajie Sun, Fang Xie, Jing Wang et al.

Abstract Background Domesticated pigs serve as an ideal animal model for biomedical research and also provide the majority of meat for human consumption in China. Porcine intramuscular fat content associates with human health and diseases and is essential in pork quality. The molecular mechanisms controlling lipid metabolism and intramuscular fat accretion across tissues in pigs, and how these changes in response to pig breeds, remain largely unknown. Results We surveyed the tissue-resident cell types of the porcine jejunum, colon, liver, and longissimus dorsi muscle between Lantang and Landrace breeds by single-cell RNA sequencing. Combining lipidomics and metagenomics approaches, we also characterized gene signatures and determined key discriminating markers of lipid digestibility, absorption, conversion, and deposition across tissues in two pig breeds. In Landrace, lean-meat swine mainly exhibited breed-specific advantages in lipid absorption and oxidation for energy supply in small and large intestinal epitheliums, nascent high-density lipoprotein synthesis for reverse cholesterol transport in enterocytes and hepatocytes, bile acid formation, and secretion for fat emulsification in hepatocytes, as well as intestinal-microbiota gene expression involved in lipid accumulation product. In Lantang, obese-meat swine showed a higher synthesis capacity of chylomicrons responsible for high serum triacylglycerol levels in small intestinal epitheliums, the predominant characteristics of lipid absorption in muscle tissue, and greater intramuscular adipcytogenesis potentials from muscular fibro-adipogenic progenitor subpopulation. Conclusions The findings enhanced our understanding of the cellular biology of lipid metabolism and opened new avenues to improve animal production and human diseases. Video Abstract

Ziqi Ma, Tao Zuo, Norbert Frey et al.

Abstract The human microbiome is a complex and dynamic system that plays important roles in human health and disease. However, there remain limitations and theoretical gaps in our current understanding of the intricate relationship between microbes and humans. In this narrative review, we integrate the knowledge and insights from various fields, including anatomy, physiology, immunology, histology, genetics, and evolution, to propose a systematic framework. It introduces key concepts such as the ‘innate and adaptive genomes’, which enhance genetic and evolutionary comprehension of the human genome. The ‘germ-free syndrome’ challenges the traditional ‘microbes as pathogens’ view, advocating for the necessity of microbes for health. The ‘slave tissue’ concept underscores the symbiotic intricacies between human tissues and their microbial counterparts, highlighting the dynamic health implications of microbial interactions. ‘Acquired microbial immunity’ positions the microbiome as an adjunct to human immune systems, providing a rationale for probiotic therapies and prudent antibiotic use. The ‘homeostatic reprogramming hypothesis’ integrates the microbiome into the internal environment theory, potentially explaining the change in homeostatic indicators post-industrialization. The ‘cell-microbe co-ecology model’ elucidates the symbiotic regulation affecting cellular balance, while the ‘meta-host model’ broadens the host definition to include symbiotic microbes. The ‘health-illness conversion model’ encapsulates the innate and adaptive genomes’ interplay and dysbiosis patterns. The aim here is to provide a more focused and coherent understanding of microbiome and highlight future research avenues that could lead to a more effective and efficient healthcare system.

Khadijattou Taoufiq, Laila Aberchane, Oukacha Amri et al.

This study aimed to characterize endophytic bacteria isolated from legume nodules and roots in the rhizosphere soils of Acacia trees in Morocco’s arid regions. The focus was on identifying bacterial strains with plant growth-promoting rhizobacteria (PGPR) traits and antibiotic resistance, which could enhance legume productivity under various abiotic stresses. Autochthonous legumes were used to harbor the endophytic bacteria, including chickpea (<i>Cicer arietinum</i>), faba bean (<i>Vicia faba</i>), lentil (<i>Lens culinaris</i>), and common bean (<i>Phaseolus vulgaris</i>). In a previous study, seventy-two isolates were obtained, and molecular characterization grouped them into twenty-two bacterial isolates. These twenty-two bacterial isolates were then further analyzed for their antibiotic resistance and key PGPR traits, such as phosphate solubilization, indole-3-acetic acid (IAA) production, and siderophore production. The results revealed that 86.36% of the isolates were resistant to erythromycin, 45.45% to ciprofloxacin, 22.73% to ampicillin-sulbactam, and 9.09% to tetracycline, with ciprofloxacin and tetracycline being the most effective. All isolates produced IAA, with HN51 and PN105 exhibiting the highest production at 6 µg of IAA per mg of protein. The other isolates showed varying levels of IAA production, ranging from moderate to low. Siderophore production, assessed using CAS medium, indicated that the strains PN121, LR142, LNR146, and HR26 exhibited high production, while the rest demonstrated moderate to low capacities. Additionally, 18.2% of the isolates demonstrated phosphate solubilization on YED-P medium, with PR135 and LNR135 being the most efficient, achieving solubilization indices of 2.14 and 2.13 cm, respectively. LR142 and LNR146 showed a moderate solubilization efficiency. Overall, these findings indicate that these isolated endophytic bacteria possess significant potential as biofertilizers, owing to their antibiotic resistance, IAA production, siderophore production, and phosphate solubilization abilities. These characteristics position them as promising candidates for enhancing legume growth under abiotic stress and contributing to sustainable agriculture in arid regions.

Jeffrey W. Doser, Marc Kéry, Sarah P. Saunders et al.

Species distribution models (SDMs) are increasingly applied across macroscales. Such models typically assume that a single set of regression coefficients can adequately describe species-environment relationships and/or population trends. However, such relationships often show nonlinear and/or spatially-varying patterns that arise from complex interactions with abiotic and biotic processes that operate at different scales. Spatially-varying coefficient (SVC) models can readily account for variability in the effects of environmental covariates. Yet, their use in ecology is relatively scarce due to gaps in understanding the inferential benefits that SVC models can provide compared to simpler frameworks. Here we demonstrate the inferential benefits of SVC SDMs, with a particular focus on how this approach can be used to generate and test ecological hypotheses regarding the drivers of spatial variability in population trends and species-environment relationships. We illustrate the inferential benefits of SVC SDMs with simulations and two case studies: one that assesses spatially-varying trends of 51 forest bird species in the eastern US over two decades and a second that evaluates spatial variability in the effects of five decades of land cover change on Grasshopper Sparrow occurrence across the continental US. We found strong support for SVC SDMs compared to simpler alternatives in both empirical case studies. These applications display the utility of SVC SDMs to help reveal the environmental factors that drive species distributions across both local and broad scales. We conclude by discussing the potential applications of SVC SDMs in ecology and conservation.

Kyle M. Meyer, Peter Deines, Zhong Wei et al.

Elijah G. Kiarie, Samantha Steelman, Marco Martinez

The provision of adequate and balanced nutrients is critical for efficient and profitable animal protein production. However, non-nutritive components in feedstuffs can elicit responses that can negatively impact nutrient utilization efficiency. For example, dietary β-mannans are recognizable by cell surface mannose receptors are pivotal for diverse cellular functions. This review will evaluate the physiological implications of dietary native β-mannans, the utility of supplemental feed β-mannanase in hydrolyzing β-mannans, and subsequent metabolic responses. Dietary native β-mannans have been implicated in inadvertent stimulation of immune response through a phenomenon called the feed-induced immune response (FIIR), that has been associated with intestinal inflammation and depression in animal performance. Supplemental β-mannanase blunted the FIIR by hydrolyzing native β-mannans to smaller fragments with a reduced ability to stimulate the innate immune system as indicated by the modulation of oxidative stress, mucosal permeability, and blood concentration of acute phase proteins and immunoglobulins in broilers and piglet models. Moreover, β-mannanase hydrolysis of native β-mannans to mannooligosaccharides (MOS) impacted gastrointestinal microbial ecology. Indeed, β-mannanase-derived MOS reduced the concentration of pathogenic bacteria such as Escherichia coli and Salmonella and increased the production of short-chain fatty acids in gastrointestinal tracts of various animal models. Consequently, by hydrolyzing native β-mannans, supplemental β-mannanase may have nutritional, metabolic, and microbial ecology benefits. In summary, integrating multi-functional feed additives such as β-mannanase into feeding programs for monogastric animals will be critical for efficient and sustainable animal protein production in the context of evolving challenges such as the mandated elimination of use of antibiotics for growth promotion.

Ari Kauppinen, Sallamaari Siponen, Tarja Pitkänen et al.

Bacteriophage control of harmful or pathogenic bacteria has aroused growing interest, largely due to the rise of antibiotic resistance. The objective of this study was to test phages as potential agents for the biocontrol of an opportunistic pathogen <i>Pseudomonas aeruginosa</i> in water. Two <i>P. aeruginosa</i> bacteriophages (vB_PaeM_V523 and vB_PaeM_V524) were isolated from wastewater and characterized physically and functionally. Genomic and morphological characterization showed that both were myoviruses within the <i>Pbunavirus</i> genus. Both had a similar latent period (50–55 min) and burst size (124–134 PFU/infected cell), whereas there was variation in the host range. In addition to these environmental phages, a commercial <i>Pseudomonas</i> phage, JG003 (DSM 19870), was also used in the biocontrol experiments. The biocontrol potential of the three phages in water was tested separately and together as a cocktail against two <i>P. aeruginosa</i> strains; PAO1 and the environmental strain 17V1507. With PAO1, all phages initially reduced the numbers of the bacterial host, with phage V523 being the most efficient (>2.4 log₁₀ reduction). For the environmental <i>P. aeruginosa</i> strain (17V1507), only the phage JG003 caused a reduction (1.2 log₁₀) compared to the control. The cocktail of three phages showed a slightly higher decrease in the level of the hosts compared to the use of individual phages. Although no synergistic effect was observed in the host reduction with the use of the phage cocktail, the cocktail-treated hosts did not appear to acquire resistance as rapidly as hosts treated with a single phage. The results of this study provide a significant step in the development of bacteriophage preparations for the control of pathogens and harmful microbes in water environments.

Olivia N. Choi, Ammon Corl, Andrew Wolfenden et al.

Studies in both humans and model organisms suggest that the microbiome may play a significant role in host health, including digestion and immune function. Microbiota can offer protection from exogenous pathogens through colonization resistance, but microbial dysbiosis in the gastrointestinal tract can decrease resistance and is associated with pathogenesis. Little is known about the effects of potential pathogens, such as Salmonella, on the microbiome in wildlife, which are known to play an important role in disease transmission to humans. Culturing techniques have traditionally been used to detect pathogens, but recent studies have utilized high throughput sequencing of the 16S rRNA gene to characterize host-associated microbial communities (i.e., the microbiome) and to detect specific bacteria. Building upon this work, we evaluated the utility of high throughput 16S rRNA gene sequencing for potential bacterial pathogen detection in barn swallows (Hirundo rustica) and used these data to explore relationships between potential pathogens and microbiota. To accomplish this, we first compared the detection of Salmonella spp. in swallows using 16S rRNA data with standard culture techniques. Second, we examined the prevalence of Salmonella using 16S rRNA data and examined the relationship between Salmonella-presence or -absence and individual host factors. Lastly, we evaluated host-associated bacterial diversity and community composition in Salmonella-present vs. -absent birds. Out of 108 samples, we detected Salmonella in six (5.6%) samples based on culture, 25 (23.1%) samples with unrarefied 16S rRNA gene sequencing data, and three (2.8%) samples with both techniques. We found that sex, migratory status, and weight were correlated with Salmonella presence in swallows. In addition, bacterial community composition and diversity differed between birds based on Salmonella status. This study highlights the value of 16S rRNA gene sequencing data for monitoring pathogens in wild birds and investigating the ecology of host microbe-pathogen relationships, data which are important for prediction and mitigation of disease spillover into domestic animals and humans.

Frederiek-Maarten Kerckhof, Frederiek-Maarten Kerckhof, Myrsini Sakarika et al.

Increasing efforts are directed towards the development of sustainable alternative protein sources among which microbial protein (MP) is one of the most promising. Especially when waste streams are used as substrates, the case for MP could become environmentally favorable. The risks of using organic waste streams for MP production–the presence of pathogens or toxicants–can be mitigated by their anaerobic digestion and subsequent aerobic assimilation of the (filter-sterilized) biogas. Even though methane and hydrogen oxidizing bacteria (MOB and HOB) have been intensively studied for MP production, the potential benefits of their co-cultivation remain elusive. Here, we isolated a diverse group of novel HOB (that were capable of autotrophic metabolism), and co-cultured them with a defined set of MOB, which could be grown on a mixture of biogas and H2/O2. The combination of MOB and HOB, apart from the CH4 and CO2 contained in biogas, can also enable the valorization of the CO2 that results from the oxidation of methane by the MOB. Different MOB and HOB combinations were grown in serum vials to identify the best-performing ones. We observed synergistic effects on growth for several combinations, and in all combinations a co-culture consisting out of both HOB and MOB could be maintained during five days of cultivation. Relative to the axenic growth, five out of the ten co-cultures exhibited 1.1–3.8 times higher protein concentration and two combinations presented 2.4–6.1 times higher essential amino acid content. The MP produced in this study generally contained lower amounts of the essential amino acids histidine, lysine and threonine, compared to tofu and fishmeal. The most promising combination in terms of protein concentration and essential amino acid profile was Methyloparacoccus murrelli LMG 27482 with Cupriavidus necator LMG 1201. Microbial protein from M. murrelli and C. necator requires 27–67% less quantity than chicken, whole egg and tofu, while it only requires 15% more quantity than the amino acid-dense soybean to cover the needs of an average adult. In conclusion, while limitations still exist, the co-cultivation of MOB and HOB creates an alternative route for MP production leveraging safe and sustainably-produced gaseous substrates.

Harm de Vries, Dzmitry Bahdanau, Christopher Manning

Language User Interfaces (LUIs) could improve human-machine interaction for a wide variety of tasks, such as playing music, getting insights from databases, or instructing domestic robots. In contrast to traditional hand-crafted approaches, recent work attempts to build LUIs in a data-driven way using modern deep learning methods. To satisfy the data needs of such learning algorithms, researchers have constructed benchmarks that emphasize the quantity of collected data at the cost of its naturalness and relevance to real-world LUI use cases. As a consequence, research findings on such benchmarks might not be relevant for developing practical LUIs. The goal of this paper is to bootstrap the discussion around this issue, which we refer to as the benchmarks' low ecological validity. To this end, we describe what we deem an ideal methodology for machine learning research on LUIs and categorize five common ways in which recent benchmarks deviate from it. We give concrete examples of the five kinds of deviations and their consequences. Lastly, we offer a number of recommendations as to how to increase the ecological validity of machine learning research on LUIs.

Marco Hartl, Diego F. Bedoya-Ríos, Marta Fernández-Gatell et al.

Microbial fuel cells implemented in constructed wetlands (CW-MFCs), albeit a relatively new technology still under study, have shown to improve treatment efficiency of urban wastewater. So far the vast majority of CW-MFC systems investigated were designed as lab-scale systems working under rather unrealistic hydraulic conditions using synthetic wastewater. The main objective of this work was to quantify CW-MFCs performance operated under different conditions in a more realistic setup using meso-scale systems with horizontal flow fed with real urban wastewater. Operational conditions tested were organic loading rate (4.9+-1.6, 6.7+-1.4 and 13.6+-3.2 g COD/m2.day) and hydraulic regime (continuous vs intermittent feeding) as well as different electrical connections: CW control (conventional CW without electrodes), open-circuit CW-MFC (external circuit between anode and cathode not connected) and closed-circuit CW-MFC (external circuit connected). Eight horizontal subsurface flow CWs were operated for about four months. Each wetland consisted of a PVC reservoir of 0.193 m2 filled with 4/8 mm granitic riverine gravel. All wetlands had intermediate sampling points for gravel and interstitial liquid sampling. The CW-MFCs were designed as three MFCs incorporated one after the other along the flow path of the CWs. Results showed no significant differences between tested organic loading rates, hydraulic regimes or electrical connections, however, on average, systems operated in closed-circuit CW-MFC mode under continuous flow outperformed the other experimental conditions. Closed-circuit CW-MFC compared to conventional CW control systems showed around 5% and 22% higher COD and ammonium removal, respectively. Correspondingly, overall bacteria activity, as measured by the fluorescein diacetate technique, was higher (4% to 34%) in closed-circuit systems when compared to CW control systems.