Calcium/calcimimetic via calcium-sensing receptor ameliorates cholera toxin-induced secretory diarrhea in mice.

BACKGROUND: Enterotoxins produce diarrhea through direct epithelial action and indirectly by activating the enteric nervous system. Calcium-sensing receptor (CaSR) inhibits both actions. The latter has been well documented in vitro but not in vivo. The hypothesis to be tested was that activating CaSR inhibits diarrhea in vivo. AIM: To determine whether CaSR agonists ameliorate secretory diarrhea evoked by cholera toxin (CTX) in mice. METHODS: CTX was given orally to C57BL/6 mice to induce diarrhea. Calcium and calcimimetic R568 were used to activate CaSR. To maximize their local intestinal actions, calcium was administered luminally via oral rehydration solution (ORS), whereas R568 was applied serosally using an intraperitoneal route. To verify that their actions resulted from the intestine, effects were also examined on Cre-lox intestine-specific CaSR knockouts. Diarrhea outcome was measured biochemically by monitoring changes in fecal Cl- or clinically by assessing stool consistency and weight loss. RESULTS: CTX induced secretory diarrhea, as evidenced by increases in fecal Cl-, stool consistency, and weight loss following CTX exposure, but did not alter CaSR, neither in content nor in function. Accordingly, calcium and R568 were each able to ameliorate diarrhea when applied to diseased intestines. Intestinal CaSR involvement is suggested by gene knockout experiments where the anti-diarrheal actions of R568 were lost in intestinal epithelial CaSR knockouts (villinCre/Casrflox/flox) and neuronal CaSR knockouts (nestinCre/Casrflox/flox). CONCLUSION: Treatment of acute secretory diarrheas remains a global challenge. Despite advances in diarrhea research, few have been made in the realm of diarrhea therapeutics. ORS therapy has remained the standard of care, although it does not halt the losses of intestinal fluid and ions caused by pathogens. There is no cost-effective therapeutic for diarrhea. This and other studies suggest that adding calcium to ORS or using calcimimetics to activate intestinal CaSR might represent a novel approach for treating secretory diarrheal diseases.

Dynamic UAV Phenotyping for Rice Disease Resistance Analysis Based on Multisource Data.

Bacterial blight poses a threat to rice production and food security, which can be controlled through large-scale breeding efforts toward resistant cultivars. Unmanned aerial vehicle (UAV) remote sensing provides an alternative means for the infield phenotype evaluation of crop disease resistance to relatively time-consuming and laborious traditional methods. However, the quality of data acquired by UAV can be affected by several factors such as weather, crop growth period, and geographical location, which can limit their utility for the detection of crop disease and resistant phenotypes. Therefore, a more effective use of UAV data for crop disease phenotype analysis is required. In this paper, we used time series UAV remote sensing data together with accumulated temperature data to train the rice bacterial blight severity evaluation model. The best results obtained with the predictive model showed an R p 2 of 0.86 with an RMSEp of 0.65. Moreover, model updating strategy was used to explore the scalability of the established model in different geographical locations. Twenty percent of transferred data for model training was useful for the evaluation of disease severity over different sites. In addition, the method for phenotypic analysis of rice disease we built here was combined with quantitative trait loci (QTL) analysis to identify resistance QTL in genetic populations at different growth stages. Three new QTLs were identified, and QTLs identified at different growth stages were inconsistent. QTL analysis combined with UAV high-throughput phenotyping provides new ideas for accelerating disease resistance breeding.

Robotic Assay for Drought (RoAD): an automated phenotyping system for brassinosteroid and drought responses.

Brassinosteroids (BRs) are a group of plant steroid hormones involved in regulating growth, development, and stress responses. Many components of the BR pathway have previously been identified and characterized. However, BR phenotyping experiments are typically performed in a low-throughput manner, such as on Petri plates. Additionally, the BR pathway affects drought responses, but drought experiments are time consuming and difficult to control. To mitigate these issues and increase throughput, we developed the Robotic Assay for Drought (RoAD) system to perform BR and drought response experiments in soil-grown Arabidopsis plants. RoAD is equipped with a robotic arm, a rover, a bench scale, a precisely controlled watering system, an RGB camera, and a laser profilometer. It performs daily weighing, watering, and imaging tasks and is capable of administering BR response assays by watering plants with Propiconazole (PCZ), a BR biosynthesis inhibitor. We developed image processing algorithms for both plant segmentation and phenotypic trait extraction to accurately measure traits including plant area, plant volume, leaf length, and leaf width. We then applied machine learning algorithms that utilize the extracted phenotypic parameters to identify image-derived traits that can distinguish control, drought-treated, and PCZ-treated plants. We carried out PCZ and drought experiments on a set of BR mutants and Arabidopsis accessions with altered BR responses. Finally, we extended the RoAD assays to perform BR response assays using PCZ in Zea mays (maize) plants. This study establishes an automated and non-invasive robotic imaging system as a tool to accurately measure morphological and growth-related traits of Arabidopsis and maize plants in 3D, providing insights into the BR-mediated control of plant growth and stress responses.

Proposal for reunification of the genus Raoultella with the genus Klebsiella and reclassification of Raoultella electrica as Klebsiella electrica comb. nov.

The order Enterobacterales was divided into seven families including the family Enterobacteriaceae in 2016. The genus Klebsiella within the family Enterobacteriaceae was divided into two genera Klebsiella and Raoultella in 2001. Here, our phylogenomic analysis shows that the genus Raoultella is nested within the genus Klebsiella. Klebsiella and Raoultella together are monophyletic and share average amino acid identities (AAIs) of 86.9-89.6% above the AAI threshold (86%) for genus delimitation within the family Enterobacteriaceae. Klebsiella and Raoultella share AAIs of 79.9%-85.0% with the other genera within the subfamily "Klebsiella clade", which are in the range of inter-genus AAIs (74-85%) within the family Enterobacteriaceae. Klebsiella and Raoultella also share six known conserved signature indels. Therefore, we propose to reunify Klebsiella and Raoultella to the single genus Klebsiella and reclassify Raoultella electrica as Klebsiella electrica comb. nov. Our genome-based taxonomic analyses also identified seven potential novel species within the unified genus Klebsiella.

A Convolutional Neural Network-Based Method for Corn Stand Counting in the Field.

Accurate corn stand count in the field at early season is of great interest to corn breeders and plant geneticists. However, the commonly used manual counting method is time consuming, laborious, and prone to error. Nowadays, unmanned aerial vehicles (UAV) tend to be a popular base for plant-image-collecting platforms. However, detecting corn stands in the field is a challenging task, primarily because of camera motion, leaf fluttering caused by wind, shadows of plants caused by direct sunlight, and the complex soil background. As for the UAV system, there are mainly two limitations for early seedling detection and counting. First, flying height cannot ensure a high resolution for small objects. It is especially difficult to detect early corn seedlings at around one week after planting, because the plants are small and difficult to differentiate from the background. Second, the battery life and payload of UAV systems cannot support long-duration online counting work. In this research project, we developed an automated, robust, and high-throughput method for corn stand counting based on color images extracted from video clips. A pipeline developed based on the YoloV3 network and Kalman filter was used to count corn seedlings online. The results demonstrate that our method is accurate and reliable for stand counting, achieving an accuracy of over 98% at growth stages V2 and V3 (vegetative stages with two and three visible collars) with an average frame rate of 47 frames per second (FPS). This pipeline can also be mounted easily on manned cart, tractor, or field robotic systems for online corn counting.

Toward "Smart Canopy" Sorghum: Discovery of the Genetic Control of Leaf Angle Across Layers.

A "smart canopy" ideotype has been proposed with leaves being upright at the top and more horizontal toward the bottom of the plant to maximize light interception and conversion efficiencies, and thus increasing yield. The genetic control of leaf angle has, to date, been studied on one or two leaves, or data have been merged from multiple leaves to generate average values. This approach has limited our understanding of the diversity of leaf angles across layers and their genetic control. Genome-wide association studies and quantitative trait loci mapping studies in sorghum (Sorghum bicolor) were performed using layer-specific angle data collected manually and via high-throughput phenotyping strategies. The observed distribution of angles in indoor and field settings is opposite to the ideotype. Several genomic regions were associated with leaf angle within layers or across the canopy. The expression of the brassinosteroid-related transcription factor BZR1/BES1 and the auxin-transporter Dwarf3 were found to be highly correlated with the distribution of angles at different layers. The application of a brassinosteroid biosynthesis inhibitor could not revert the undesirable overall angle distribution. These discoveries demonstrate that the exploitation of layer-specific quantitative trait loci/genes will be instrumental to reversing the natural angle distribution in sorghum according to the "smart canopy" ideotype.

Assessing plant performance in the Enviratron.

BACKGROUND: Assessing the impact of the environment on plant performance requires growing plants under controlled environmental conditions. Plant phenotypes are a product of genotype × environment (G × E), and the Enviratron at Iowa State University is a facility for testing under controlled conditions the effects of the environment on plant growth and development. Crop plants (including maize) can be grown to maturity in the Enviratron, and the performance of plants under different environmental conditions can be monitored 24 h per day, 7 days per week throughout the growth cycle. RESULTS: The Enviratron is an array of custom-designed plant growth chambers that simulate different environmental conditions coupled with precise sensor-based phenotypic measurements carried out by a robotic rover. The rover has workflow instructions to periodically visit plants growing in the different chambers where it measures various growth and physiological parameters. The rover consists of an unmanned ground vehicle, an industrial robotic arm and an array of sensors including RGB, visible and near infrared (VNIR) hyperspectral, thermal, and time-of-flight (ToF) cameras, laser profilometer and pulse-amplitude modulated (PAM) fluorometer. The sensors are autonomously positioned for detecting leaves in the plant canopy, collecting various physiological measurements based on computer vision algorithms and planning motion via "eye-in-hand" movement control of the robotic arm. In particular, the automated leaf probing function that allows the precise placement of sensor probes on leaf surfaces presents a unique advantage of the Enviratron system over other types of plant phenotyping systems. CONCLUSIONS: The Enviratron offers a new level of control over plant growth parameters and optimizes positioning and timing of sensor-based phenotypic measurements. Plant phenotypes in the Enviratron are measured in situ-in that the rover takes sensors to the plants rather than moving plants to the sensors.

A Robotic Platform for Corn Seedling Morphological Traits Characterization.

Crop breeding plays an important role in modern agriculture, improving plant performance, and increasing yield. Identifying the genes that are responsible for beneficial traits greatly facilitates plant breeding efforts for increasing crop production. However, associating genes and their functions with agronomic traits requires researchers to observe, measure, record, and analyze phenotypes of large numbers of plants, a repetitive and error-prone job if performed manually. An automated seedling phenotyping system aimed at replacing manual measurement, reducing sampling time, and increasing the allowable work time is thus highly valuable. Toward this goal, we developed an automated corn seedling phenotyping platform based on a time-of-flight of light (ToF) camera and an industrial robot arm. A ToF camera is mounted on the end effector of the robot arm. The arm positions the ToF camera at different viewpoints for acquiring 3D point cloud data. A camera-to-arm transformation matrix was calculated using a hand-eye calibration procedure and applied to transfer different viewpoints into an arm-based coordinate frame. Point cloud data filters were developed to remove the noise in the background and in the merged seedling point clouds. A 3D-to-2D projection and an x-axis pixel density distribution method were used to segment the stem and leaves. Finally, separated leaves were fitted with 3D curves for morphological traits characterization. This platform was tested on a sample of 60 corn plants at their early growth stages with between two to five leaves. The error ratios of the stem height and leave length measurements are 13.7% and 13.1%, respectively, demonstrating the feasibility of this robotic system for automated corn seedling phenotyping.

A High-Throughput, Field-Based Phenotyping Technology for Tall Biomass Crops.

Recent advances in omics technologies have not been accompanied by equally efficient, cost-effective, and accurate phenotyping methods required to dissect the genetic architecture of complex traits. Even though high-throughput phenotyping platforms have been developed for controlled environments, field-based aerial and ground technologies have only been designed and deployed for short-stature crops. Therefore, we developed and tested Phenobot 1.0, an auto-steered and self-propelled field-based high-throughput phenotyping platform for tall dense canopy crops, such as sorghum (Sorghum bicolor). Phenobot 1.0 was equipped with laterally positioned and vertically stacked stereo RGB cameras. Images collected from 307 diverse sorghum lines were reconstructed in 3D for feature extraction. User interfaces were developed, and multiple algorithms were evaluated for their accuracy in estimating plant height and stem diameter. Tested feature extraction methods included the following: (1) User-interactive Individual Plant Height Extraction (UsIn-PHe) based on dense stereo three-dimensional reconstruction; (2) Automatic Hedge-based Plant Height Extraction (Auto-PHe) based on dense stereo 3D reconstruction; (3) User-interactive Dense Stereo Matching Stem Diameter Extraction; and (4) User-interactive Image Patch Stereo Matching Stem Diameter Extraction (IPaS-Di). Comparative genome-wide association analysis and ground-truth validation demonstrated that both UsIn-PHe and Auto-PHe were accurate methods to estimate plant height, while Auto-PHe had the additional advantage of being a completely automated process. For stem diameter, IPaS-Di generated the most accurate estimates of this biomass-related architectural trait. In summary, our technology was proven robust to obtain ground-based high-throughput plant architecture parameters of sorghum, a tall and densely planted crop species.

Dietary contribution of foods and beverages sold within a university campus and its effect on diet quality of young adults.

OBJECTIVE: Tertiary education institutions have been linked with excessive weight in young adults. However, few data are available on the effect of foods from the university food environment on the diet quality of young adults. The aim of this study was to describe the association of a number of foods and beverages consumed at university food outlets with the diet quality of young adults. METHODS: This was a cross-sectional survey in which the 103 university student participants, aged 19 to 24 y, contributed 5 d of dietary data. A purposely designed, validated smartphone application was used to collect the data. Diet quality was assessed by adherence to the 2013 dietary guidelines for food groups and nutrients, and the validated Healthy Eating Index for Australians (HEIFA-2013) was applied. Individual HEIFA-2013 scores were compared with the frequency of food purchase and consumption from university outlets to assess a dose-response effect of the food environment. Comparisons by tertiles of diet quality for body mass index, waist circumference, and takeaway food consumption (university and other) were computed using a one-way analysis of variance and post hoc Tukey test. RESULTS: There was a statistically significant difference between the number of university foods and beverages consumed in 5 d and the HEIFA-2013 scores: More on-campus purchases resulted in a poor-quality diet (P = 0.001). As the HEIFA-2013 tertile scores increased, there was a significant decrease in the number of university campus and other takeaway foods consumed; body mass index and waist circumference showed a decrease in trend. CONCLUSIONS: Efforts to improve the diet quality of young adults attending university may benefit from approaches to improve the campus food environment.

Electronic Dietary Intake Assessment (e-DIA): relative validity of a mobile phone application to measure intake of food groups.

Automation of dietary assessment can reduce limitations of established methodologies, by alleviating participant and researcher burden. Designed as a research tool, the electronic Dietary Intake Assessment (e-DIA) is a food record in mobile phone application format. The present study aimed to examine the relative validity of the e-DIA with the 24-h recall method to estimate intake of food groups. A sample of eighty university students aged 19-24 years recorded 5 d of e-DIA and 3 d of recall within this 5-d period. The three matching days of dietary data were used for analysis. Food intake data were disaggregated and apportioned to one of eight food groups. Median intakes of food groups were similar between the methods, and strong correlations were found (mean: 0·79, range: 0·69-0·88). Cross-classification by tertiles produced a high level of exact agreement (mean: 71 %, range: 65-75 %), and weighted κ values were moderate to good (range: 0·54-0·71). Although mean differences (e-DIA-recall) were small (range: -13 to 23 g), limits of agreement (LOA) were relatively large (e.g. for vegetables, mean difference: -4 g, LOA: -159 to 151 g). The Bland-Altman plots showed robust agreement, with minimum bias. This analysis supports the use of e-DIA as an alternative to the repeated 24-h recall method for ranking individuals' food group intake.

Genomic identification of nitrogen-fixing Klebsiella variicola, K. pneumoniae and K. quasipneumoniae.

It was difficult to differentiate Klebsiella pneumoniae, K. quasipneumoniae and K. variicola by biochemical and phenotypic tests. Genomics increase the resolution and credibility of taxonomy for closely-related species. Here, we obtained the complete genome sequence of the K. variicola type strain DSM 15968(T) (=F2R9(T)). The genome of the type strain is a circular chromosome of 5,521,203 bp with 57.56% GC content. From 540 Klebsiella strains whose genomes had been publicly available as at 3 March 2015, we identified 21 strains belonging to K. variicola and 8 strains belonging to K. quasipneumoniae based on the genome average nucleotide identities (ANI). All the K. variicola strains, one K. pneumoniae strain and five K. quasipneumoniae strains contained nitrogen-fixing genes. A phylogenomic analysis showed clear species demarcations for these nitrogen-fixing bacteria. In accordance with the key biochemical characteristics of K. variicola, the idnO gene encoding 5-keto-D-gluconate 5-reductase for utilization of 5-keto-D-gluconate and the sorCDFBAME operon for catabolism of L-sorbose were present whereas the rbtRDKT operon for catabolism of adonitol was absent in the genomes of K. variicola strains. Therefore, the genomic analyses supported the ANI-based species delineation; the genome sequence of the K. variicola type strain provides the reference genome for genomic identification of K. variicola, which is a nitrogen-fixing species.

Electronic Dietary Intake Assessment (e-DIA): Comparison of a Mobile Phone Digital Entry App for Dietary Data Collection With 24-Hour Dietary Recalls.

BACKGROUND: The electronic Dietary Intake Assessment (e-DIA), a digital entry food record mobile phone app, was developed to measure energy and nutrient intake prospectively. This can be used in monitoring population intakes or intervention studies in young adults. OBJECTIVE: The objective was to assess the relative validity of e-DIA as a dietary assessment tool for energy and nutrient intakes using the 24-hour dietary recall as a reference method. METHODS: University students aged 19 to 24 years recorded their food and drink intake on the e-DIA for five days consecutively and completed 24-hour dietary recalls on three random days during this 5-day study period. Mean differences in energy, macro-, and micronutrient intakes were evaluated between the methods using paired t tests or Wilcoxon signed-rank tests, and correlation coefficients were calculated on unadjusted, energy-adjusted, and deattenuated values. Bland-Altman plots and cross-classification into quartiles were used to assess agreement between the two methods. RESULTS: Eighty participants completed the study (38% male). No significant differences were found between the two methods for mean intakes of energy or nutrients. Deattenuated correlation coefficients ranged from 0.55 to 0.79 (mean 0.68). Bland-Altman plots showed wide limits of agreement between the methods but without obvious bias. Cross-classification into same or adjacent quartiles ranged from 75% to 93% (mean 85%). CONCLUSIONS: The e-DIA shows potential as a dietary intake assessment tool at a group level with good ranking agreement for energy and all nutrients.

Construction and analysis of microRNA-transcription factor regulation network in Arabidopsis.

Transcription factors (TFs) and microRNAs (miRNAs) are two major types of regulators of gene expression, at transcriptional and post-transcriptional levels, respectively. By gathering their gene regulatory relationships, gene regulatory networks (GRNs) could be formed. A network motif is a type of connection pattern among a set of nodes which appears significantly more frequently than in random networks. Investigations of the network motifs often yield biological insights into the nature of the network. The previous study on miRNA-TF regulation networks concentrated on animals, and relied heavily on computational predictions. The authors collected data concerning miRNA regulation and transcriptional regulation relationships in Arabidopsis from publicly available databases, and further incorporated them with the protein-protein interaction data. All the data in the author's collection are supported by experiments. They screened the network motifs, whose size ranges between 1 and 4. The biological implications of the motifs were further analysed, and a flower development related network was constructed as an example. In this example, they illustrated the relevance of the network with the given process, and proposed the association of several genes with flowers by a network cluster identification. In this study, they analysed the properties of the GRN in Arabidopsis, and discussed their biological implications, as well as their potential applications.

Effects of nutritional supplementation during pregnancy on early adult disease risk: follow up of offspring of participants in a randomised controlled trial investigating effects of supplementation on infant birth weight.

BACKGROUND: Observational evidence suggests that improving fetal growth may improve adult health. Experimental evidence from nutritional supplementation trials undertaken amongst pregnant women in the less developed world does not show strong or consistent effects on adult disease risk and no trials from the more developed world have previously been reported. OBJECTIVE: To test the hypothesis that nutritional supplementation during pregnancy influences offspring disease risk in adulthood. DESIGN: Clinical assessment of a range of established diseases risk markers in young adult offspring of 283 South Asian mothers who participated in two trials of nutritional supplementation during pregnancy (protein/energy/vitamins; energy/vitamins or vitamins only) at Sorrento Maternity Hospital in Birmingham UK either unselected or selected on the basis of nutritional status. RESULTS: 236 (83%) offspring were traced and 118 (50%) of these were assessed in clinic. Protein/energy/vitamins supplementation amongst undernourished mothers was associated with increased infant birthweight. Nutritional supplementation showed no strong association with any one of a comprehensive range of markers of adult disease risk and no consistent pattern of association with risk across markers in offspring of either unselected or undernourished mothers. CONCLUSIONS: We found no evidence that nutritional supplements given to pregnant women are an important influence on adult disease risk however our study lacked power to estimate small effects. Our findings do not provide support for a policy of nutritional supplementation for pregnant women as an effective means to improve adult health in more developed societies.

The calcium-sensing receptor acts as a modulator of gastric acid secretion in freshly isolated human gastric glands.

Gastric acid secretion is activated by two distinct pathways: a neuronal pathway via the vagus nerve and release of acetylcholine and an endocrine pathway involving gastrin and histamine. Recently, we demonstrated that activation of H(+)-K(+)-ATPase activity in parietal cells in freshly isolated rat gastric glands is modulated by the calcium-sensing receptor (CaSR). Here, we investigated if the CaSR is functionally expressed in freshly isolated gastric glands from human patients undergoing surgery and if the CaSR is influencing histamine-induced activation of H(+)-K(+)-ATPase activity. In tissue samples obtained from patients, immunohistochemistry demonstrated the expression in parietal cells of both subunits of gastric H(+)-K(+)-ATPase and the CaSR. Functional experiments using the pH-sensitive dye 2',7'-bis-(2-carboxyethyl)-5-(and 6)-carboxyfluorescein and measurement of intracellular pH changes allowed us to estimate the activity of H(+)-K(+)-ATPase in single freshly isolated human gastric glands. Under control conditions, H(+)-K(+)-ATPase activity was stimulated by histamine (100 microM) and inhibited by omeprazole (100 microM). Reduction of the extracellular divalent cation concentration (0 Mg(2+), 100 microM Ca(2+)) inactivated the CaSR and reduced histamine-induced activation of H(+)-K(+)-ATPase activity. In contrast, activation of the CaSR with the trivalent cation Gd(3+) caused activation of omeprazole-sensitive H(+)-K(+)-ATPase activity even in the absence of histamine and under conditions of low extracellular divalent cations. This stimulation was not due to release of histamine from neighbouring enterochromaffin-like cells as the stimulation persisted in the presence of the H(2) receptor antagonist cimetidine (100 microM). Furthermore, intracellular calcium measurements with fura-2 and fluo-4 showed that activation of the CaSR by Gd(3+) led to a sustained increase in intracellular Ca(2+) even under conditions of low extracellular divalent cations. These experiments demonstrate the presence of a functional CaSR in the human stomach and show that this receptor may modulate the activity of acid-secreting H(+)-K(+)-ATPase in parietal cells. Furthermore, our results show the viability of freshly isolated human gastric glands and may allow the use of this preparation for experiments investigating the physiological regulation and properties of human gastric glands in vitro.

Novel nucleotide-binding sites in ATP-sensitive potassium channels formed at gating interfaces.

The coupling of cell metabolism to membrane electrical activity is a vital process that regulates insulin secretion, cardiac and neuronal excitability and the responses of cells to ischemia. ATP-sensitive potassium channels (K(ATP); Kir6.x) are a major part of this metabolic-electrical coupling system and translate metabolic signals such as the ATP:ADP ratio to changes in the open or closed state (gate) of the channel. The localization of the nucleotide-binding site (NBS) on Kir6.x channels and how nucleotide binding gates these K(ATP) channels remain unclear. Here, we use fluorescent nucleotide binding to purified Kir6.x proteins to define the peptide segments forming the NBS on Kir6.x channels and show that unique N- and C-terminal interactions from adjacent subunits are required for high-affinity nucleotide binding. The short N- and C-terminal segments comprising the novel intermolecular NBS are next to helices that likely move with channel opening/closing, suggesting a lock-and-key model for ligand gating.

Perinatal respiratory control and its modulation by adenosine and caffeine in the rat.

The perinatal development of respiratory rhythm generation and its modulation by adenosinergic drugs have been examined in rats from embryonic d 18 (E18) to postnatal d 3 using an in vitro brain stem-spinal cord preparation. Generation of rhythmic respiratory activity in the medulla oblongata and inhibition of this activity by pontine structures were evident on E18. The adenosine A(1)-receptor agonist, N(6)-(2-phenylisopropyl) adenosine, R (-) isomer (R-PIA) (1 microM), induced an age-dependent reduction of respiratory frequency that could be reversed by the adenosine antagonist theophylline (55 microM). The effect of R-PIA was reduced 24 h after birth compared with E21 and 2 h postnatal age. In preparations from pups that had been exposed to a low dose of caffeine (0.3 g/L in drinking water to dams), pontine inhibition of respiratory rhythm generation in the medulla was more pronounced. When the pons was removed, the respiratory frequency was higher than in the control group. Adenosine A(1)-mRNA and A(1)-receptor development in pons and medulla were studied, and by E18, mRNA, receptor protein, and functional coupling to G-proteins were confirmed using guanylyl-5'-O-(gamma-[(35)S]thio)-triphosphate binding. There were no major changes in receptor numbers or distribution of A(1) receptors or mRNA in rat pups subjected to caffeine exposure. We conclude that respiration is already modulated by adenosine A(1) receptors at the level of the medulla oblongata in the fetal period in an age-dependent manner. Furthermore, long-term maternal caffeine intake during gestation seems to increase the pontine inhibition of, and the activity of, respiratory rhythm-generating neuronal networks in medulla oblongata without detectable changes in expression of A(1)-receptor number or A(1)-receptor mRNA.