A Semi-Automatic Environmental Monitoring Device for Mercury and Cobalt Ion Detection.

A syringe-based, semi-automatic environmental monitoring device is developed for on-site detection of harmful heavy metal ions in water. This portable device consists of a spring-embedded syringe and a polydimethylsiloxane (PDMS) membrane-based flow regulator for semi-automatic fix-and-release fluidic valve actuation, and a paper-based analytical device (PAD) with two kinds of gold nanoclusters (AuNCs) for sensitive Hg2+ and Co2+ ion detection, respectively. The thickness of the elastic PDMS membrane can be adjusted to stabilize and modulate the flow rates generated by the pushing force provided by the spring attached to the plunger. Also, different spring constants can drastically alter the response time. People of all ages can extract the fix-volume sample solutions and then release them to automatically complete the detection process, ensuring high reliability and repeatability. The PAD comprises two layers of modified paper, and each layer is immobilized with bovine serum albumin-capped gold nanoclusters (R-AuNCs) and glutathione-capped gold clusters (G-AuNCs), respectively. The ligands functionalized on the surface of the AuNCs not only can fine-tune the optical properties of the nanoclusters but also enable specific and simultaneous detection of Hg2+ and Co2+ ions via metallophilic Au+ -Hg2+ interaction and the Co2+ -thiol complexation effect, respectively. The feasibility of the device for detecting heavy metal ions at low concentrations in various environmental water samples is demonstrated. The Hg2+ and Co2+ ions can be seen simultaneously within 20 min with detection limits as low as 1.76 nm and 0.27 µm, respectively, lower than those of the regulatory restrictions on water by the US Environmental Protection Agency and the European Union. we expect this sensitive, selective, portable, and easy-to-use device to be valid for on-site multiple heavy metal ion pollution screenings in resource-constrained settings.

Bis(2-ethylhexyl)-tetrabromophthalate Poses a Higher Exposure Risk and Induces Gender-Specific Metabolic Disruptions in Zebrafish Liver.

Bis(2-ethylhexyl)-tetrabromophthalate (TBPH), a typical novel brominated flame retardant, has been ubiquitously identified in various environmental and biotic media. Consequently, there is an urgent need for precise risk assessment based on a comprehensive understanding of internal exposure and the corresponding toxic effects on specific tissues. In this study, we first investigated the toxicokinetic characteristics of TBPH in different tissues using the classical pseudo-first-order toxicokinetic model. We found that TBPH was prone to accumulate in the liver rather than in the gonad, brain, and muscle of both female and male zebrafish, highlighting a higher internal exposure risk for the liver. Furthermore, long-term exposure to TBPH at environmentally relevant concentrations led to increased visceral fat accumulation, signaling potential abnormal liver function. Hepatic transcriptome analysis predominantly implicated glycolipid metabolism pathways. However, alterations in the profile of associated genes and biochemical indicators revealed gender-specific responses following TBPH exposure. Besides, histopathological observations as well as the inflammatory response in the liver confirmed the development of nonalcoholic fatty liver disease, particularly in male zebrafish. Altogether, our findings highlight a higher internal exposure risk for the liver, enhancing our understanding of the gender-specific metabolic-disrupting potential associated with TBPH exposure.

Speech- and language-linked FOXP2 mutation targets protein motors in striatal neurons.

Human speech and language are among the most complex motor and cognitive abilities. The discovery of a mutation in the transcription factor FOXP2 in KE family members with speech disturbances has been a landmark example of the genetic control of vocal communication in humans. Cellular mechanisms underlying this control have remained unclear. By leveraging FOXP2 mutation/deletion mouse models, we found that the KE family FOXP2R553H mutation directly disables intracellular dynein-dynactin 'protein motors' in the striatum by induction of a disruptive high level of dynactin1 that impairs TrkB endosome trafficking, microtubule dynamics, dendritic outgrowth and electrophysiological activity in striatal neurons alongside vocalization deficits. Dynactin1 knockdown in mice carrying FOXP2R553H mutations rescued these cellular abnormalities and improved vocalization. We suggest that FOXP2 controls vocal circuit formation by regulating protein motor homeostasis in striatal neurons, and that its disruption could contribute to the pathophysiology of FOXP2 mutation/deletion-associated speech disorders.

Subgraph Isomorphic Decision Tree to Predict Radical Thermochemistry with Bounded Uncertainty Estimation.

Detailed chemical kinetic models offer valuable mechanistic insights into industrial applications. Automatic generation of reliable kinetic models requires fast and accurate radical thermochemistry estimation. Kineticists often prefer hydrogen bond increment (HBI) corrections from a closed-shell molecule to the corresponding radical for their interpretability, physical meaning, and facilitation of error cancellation as a relative quantity. Tree estimators, used due to limited data, currently rely on expert knowledge and manual construction, posing challenges in maintenance and improvement. In this work, we extend the subgraph isomorphic decision tree (SIDT) algorithm originally developed for rate estimation to estimate HBI corrections. We introduce a physics-aware splitting criterion, explore a bounded weighted uncertainty estimation method, and evaluate aleatoric uncertainty-based and model variance reduction-based prepruning methods. Moreover, we compile a data set of thermochemical parameters for 2210 radicals involving C, O, N, and H based on quantum chemical calculations from recently published works. We leverage the collected data set to train the SIDT model. Compared to existing empirical tree estimators, the SIDT model (1) offers an automatic approach to generating and extending the tree estimator for thermochemistry, (2) has better accuracy and R2, (3) provides significantly more realistic uncertainty estimates, and (4) has a tree structure much more advantageous in descent speed. Overall, the SIDT estimator marks a great leap in kinetic modeling, offering more precise, reliable, and scalable predictions for radical thermochemistry.

Toward Accurate Quantum Mechanical Thermochemistry: (1) Extensible Implementation and Comparison of Bond Additivity Corrections and Isodesmic Reactions.

Obtaining accurate enthalpies of formation of chemical species, ΔHf, often requires empirical corrections that connect the results of quantum mechanical (QM) calculations with the experimental enthalpies of elements in their standard state. One approach is to use atomization energy corrections followed by bond additivity corrections (BACs), such as those defined by Petersson et al. or Anantharaman and Melius. Another approach is to utilize isodesmic reactions (IDRs) as shown by Buerger et al. We implement both approaches in Arkane, an open-source software that can calculate species thermochemistry using results from various QM software packages. In this work, we collect 421 reference species from the literature to derive ΔHf corrections and fit atomization energy corrections and BACs for 15 commonly used model chemistries. We find that both types of BACs yield similar accuracy, although Anantharaman- and Melius-type BACs appear to generalize better. Furthermore, BACs tend to achieve better accuracy than IDRs for commonly used model chemistries, and IDRs can be less robust because of the sensitivity to the chosen reference species and reactions. Overall, Anantharaman- and Melius-type BACs are our recommended approach for achieving accurate QM corrections for enthalpies.

Dosimetric comparison of helical tomotherapy and volumetric modulated arc therapy in hippocampal avoidance whole-brain radiotherapy.

OBJECTIVE: This study aimed to discuss the dosimetric advantages of helical tomotherapy (HT) and volumetric modulated arc therapy (VMAT) technology in hippocampal avoidance whole-brain radiotherapy and provide references for clinical selection of ideal radiotherapy technology. METHODS: A total of 20 patients with hippocampal avoidance whole-brain radiotherapy were chosen randomly. Computed tomography (CT) and MRI scanning images were input into the treatment planning system (TPS). After the CT and enhanced magnetic resonance T1 weighted images were fused and registered, the same radiation therapy physician was invited to outline the tumor target volume. PTV-HS refers to the whole brain subtracted by 5 mm outward expansion of the hippocampus (HP). The prescribed dose was 30 Gy/10 fractions. HT and VMAT plans were designed for each patient in accordance with PTV. Under the premise that the 95% isodose curve covers the PTV, dose-volume histogram was applied to evaluate the PTV, conformal index (CI), heterogeneity index (HI), maximum dose (Dmax), mean dose (Dmean), minimum dose (Dmin) and absorbed doses of organs at risk (OARs) in HT and VMAT plans. Paired t-test was performed to compare the differences between two radiation therapy plans, and p  <  0.05 was considered statistically significant. RESULTS: These two plans had no significant difference in PTV-HS (max, min, and mean). However, the HI and CI of the HT plan were significantly better than those of the VMAT plan, showing statistically significant difference (p < 0.05). The HT plan was significantly superior to the VMAT plan in terms of the Dmax, Dmin, and Dmean of HP, left and right eye lens, left and right eye, and spinal cord, showing statistically significant difference (p < 0.05). The HT plan was also better than the VMAT plan in terms of the Dmax of the left optic nerve. However, the two plans showed no obvious differences in terms of the absorbed doses of the right optic nerve and brainstem, without statistical significance. CONCLUSIONS: Compared with the VMAT plan of hippocampal avoidance, HT technology has significant dosimetric advantages. HT plans significantly decreased the radiation dose and radiation volume of OARs surrounding the target area (e.g., surrounding eye lens and eye, especially hippocampal avoidance area) while increasing the CI and HI of PTV dose in whole brain radiotherapy (WBRT) greatly, thus enabling the decrease in the incidence rate of radioactive nerve function impairment.

Degradation and inhibition of epigenetic regulatory protein BRD4 exacerbate Alzheimer's disease-related neuropathology in cell models.

Epigenetic regulation plays substantial roles in human pathophysiology, which provides opportunities for intervention in human disorders through the targeting of epigenetic pathways. Recently, emerging evidence from preclinical studies suggested the potential in developing therapeutics of Alzheimer's disease (AD) by targeting bromodomain containing protein 4 (BRD4), an epigenetic regulatory protein. However, further characterization of AD-related pathological events is urgently required. Here, we investigated the effects of pharmacological degradation or inhibition of BRD4 on AD cell models. Interestingly, we found that both degradation and inhibition of BRD4 by ARV-825 and JQ1, respectively, robustly increased the levels of amyloid-beta (Aß), which has been associated with the neuropathology of AD. Subsequently, we characterized the mechanisms by which downregulation of BRD4 increases Aß levels. We found that both degradation and inhibition of BRD4 increased the levels of BACE1, the enzyme responsible for cleavage of the amyloid-beta protein precursor (APP) to generate Aß. Consistent with Aß increase, we also found that downregulation of BRD4 increased AD-related phosphorylated Tau (pTau) protein in our 3D-AD human neural cell culture model. Therefore, our results suggest that downregulation of BRD4 would not be a viable strategy for AD intervention. Collectively, our study not only shows that BRD4 is a novel epigenetic component that regulates BACE1 and Aß levels, but also provides novel and translational insights into the targeting of BRD4 for potential clinical applications.

Dose prediction of organs at risk in patients with cervical cancer receiving brachytherapy using needle insertion based on a neural network method.

OBJECTIVE: A neural network method was employed to establish a dose prediction model for organs at risk (OAR) in patients with cervical cancer receiving brachytherapy using needle insertion. METHODS: A total of 218 CT-based needle-insertion brachytherapy fraction plans for loco-regionally advanced cervical cancer treatment were analyzed in 59 patients. The sub-organ of OAR was automatically generated by self-written MATLAB, and the volume of the sub-organ was read. Correlations between D2cm3 of each OAR and volume of each sub-organ-as well as high-risk clinical target volume for bladder, rectum, and sigmoid colon-were analyzed. We then established a neural network predictive model of D2cm3 of OAR using the matrix laboratory neural net. Of these plans, 70% were selected as the training set, 15% as the validation set, and 15% as the test set. The regression R value and mean squared error were subsequently used to evaluate the predictive model. RESULTS: The D2cm3/D90 of each OAR was related to volume of each respective sub-organ. The R values for bladder, rectum, and sigmoid colon in the training set for the predictive model were 0.80513, 0.93421, and 0.95978, respectively. The ∆D2cm3/D90 for bladder, rectum, and sigmoid colon in all sets was 0.052 ± 0.044, 0.040 ± 0.032, and 0.041 ± 0.037, respectively. The MSE for bladder, rectum, and sigmoid colon in the training set for the predictive model was 4.779 × 10-3, 1.967 × 10-3 and 1.574 × 10-3, respectively. CONCLUSION: The neural network method based on a dose-prediction model of OAR in brachytherapy using needle insertion was simple and reliable. In addition, it only addressed volumes of sub-organs to predict the dose of OAR, which we believe is worthy of further promotion and application.

Highly efficient bioconversion of icariin to icaritin by whole-cell catalysis.

BACKGROUND: Icaritin is an aglycone of flavonoid glycosides from Herba Epimedii. It has good performance in the treatment of hepatocellular carcinoma in clinical trials. However, the natural icaritin content of Herba Epimedii is very low. At present, the icaritin is mainly prepared from flavonoid glycosides by α-L-rhamnosidases and ß-glucosidases in two-step catalysis process. However, one-pot icaritin production required reported enzymes to be immobilized or bifunctional enzymes to hydrolyze substrate with long reaction time, which caused complicated operations and high costs. To improve the production efficiency and reduce costs, we explored α-L-rhamnosidase SPRHA2 and ß-glucosidase PBGL to directly hydrolyze icariin to icaritin in one-pot, and developed the whole-cell catalytic method for efficient icaritin production. RESULTS: The SPRHA2 and PBGL were expressed in Escherichia coli, respectively. One-pot production of icaritin was achieved by co-catalysis of SPRHA2 and PBGL. Moreover, whole-cell catalysis was developed for icariin hydrolysis. The mixture of SPRHA2 cells and PBGL cells transformed 200 g/L icariin into 103.69 g/L icaritin (yield 95.23%) in 4 h in whole-cell catalysis under the optimized reaction conditions. In order to further increase the production efficiency and simplify operations, we also constructed recombinant E. coli strains that co-expressed SPRHA2 and PBGL. Crude icariin extracts were also efficiently hydrolyzed by the whole-cell catalytic system. CONCLUSIONS: Compared to previous reports on icaritin production, in this study, whole-cell catalysis showed higher production efficiency of icaritin. This study provides promising approach for industrial production of icaritin in the future.

Sodium citrate increases the aggregation capacity of calcium ions during microbial mineralization to accelerate the formation of calcium carbonate.

The microbially induced carbonate precipitation (MICP) technique is widely used in soil heavy metal pollution control. Microbial mineralization involves extended mineralization times and slow crystallization rates. Thus, it is important to discover a method to accelerate mineralization. In this study, we selected six nucleating agents to screen and investigated the mineralization mechanism using polarized light microscopy, scanning electron microscopy, X-ray diffraction and Fourier-transform infrared spectroscopy. The results showed that sodium citrate removed 90.1% Pb better than traditional MICP and generated the highest amount of precipitation. Interestingly, due to the addition of sodium citrate (NaCit), the rate of crystallization increased and vaterite was stabilized. Moreover, we constructed a possible model to explain that NaCit increases the aggregation capacity of calcium ions during microbial mineralization to accelerate the formation of calcium carbonate (CaCO3). Thus, sodium citrate can increase the rate of MICP bioremediation, which is important for improving MICP efficiency.

Modeling optical emission from a highly multi-mode step-index fiber via ray tracing and the limitations: publisher's note.

This publisher's note amends the author listing of Appl. Opt.60, 10885 (2021)APOPAI0003-693510.1364/AO.434229.

Quantitative risk assessment-epidemic curve prediction model for leafy green outbreak investigation.

The objective of this study was to leverage quantitative risk assessment to investigate possible root cause(s) of foodborne illness outbreaks related to Shiga toxin-producing Escherichia coli O157:H7 (STEC O157) infections in leafy greens in the United States. To this end, we developed the FDA leafy green quantitative risk assessment epidemic curve prediction model (FDA-LG QRA-EC) that simulated the lettuce supply chain. The model was used to predict the number of reported illnesses and the epidemic curve associated with lettuce contaminated with STEC O157 for a wide range of scenarios representing various contamination conditions and facility processing/sanitation practices. Model predictions were generated for fresh-cut and whole lettuce, quantifying the differing impacts of facility processing and home preparation on predicted illnesses. Our model revealed that the timespan (i.e., number of days with at least one reported illness) and the peak (i.e., day with the most predicted number of reported illnesses) of the epidemic curve of a STEC O157-lettuce outbreak were not strongly influenced by facility processing/sanitation practices and were indications of contamination pattern among incoming lettuce batches received by the facility or distribution center. Through comparisons with observed number of illnesses from recent STEC O157-lettuce outbreaks, the model identified contamination conditions on incoming lettuce heads that could result in an outbreak of similar size, which can be used to narrow down potential root cause hypotheses.

Leveraging risk assessment for foodborne outbreak investigations: The Quantitative Risk Assessment-Epidemic Curve Prediction Model.

Root cause analysis can be used in foodborne illness outbreak investigations to determine the underlying causes of an outbreak and to help identify actions that could be taken to prevent future outbreaks. We developed a new tool, the Quantitative Risk Assessment-Epidemic Curve Prediction Model (QRA-EC), to assist with these goals and applied it to a case study to investigate and illustrate the utility of leveraging quantitative risk assessment to provide unique insights for foodborne illness outbreak root cause analysis. We used a 2019 Salmonella outbreak linked to melons as a case study to demonstrate the utility of this model (Centers for Disease Control and Prevention [CDC], 2019). The model was used to evaluate the impact of various root cause hypotheses (representing different contamination sources and food safety system failures in the melon supply chain) on the predicted number and timeline of illnesses. The predicted number of illnesses varied by contamination source and was strongly impacted by the prevalence and level of Salmonella contamination on the surface/inside of whole melons and inside contamination niches on equipment surfaces. The timeline of illnesses was most strongly impacted by equipment sanitation efficacy for contamination niches. Evaluations of a wide range of scenarios representing various potential root causes enabled us to identify which hypotheses, were likely to result in an outbreak of similar size and illness timeline to the 2019 Salmonella melon outbreak. The QRA-EC framework can be adapted to accommodate any food-pathogen pairs to provide insights for foodborne outbreak investigations.

Polysaccharides from Paecilomyces hepiali Prevent Acute Colitis in Association with Modulating Gut Microbiota and Treg/Th17 Immune Balance in Mice.

Cordyceps exopolysaccharide (CEP) has shown emerging potential in adjustment of gut microbiota and immune cell function. In this study, a water-soluble CEP with a molecular weight of 58.14 kDa was extracted from the fermentation broth of Paecilomyces hepiali, an endophytic fungus of Cordyceps sinensis. Our results indicated that Paecilomyces hepiali polysaccharide (PHP) showed significantly preventive potential on dextran sulfate sodium (DSS)-induced colitis in mice, which can prevent colon shortening, reduce intestinal epithelial cell (IEC) destruction, suppress inflammatory cell infiltration, and regulate the balance between regulatory T (Treg) cells and T helper type 17 (Th17) cells. Meanwhile, the disturbed gut microbiota was partially restored after PHP treatment. Further Pearson correlation coefficient analyses exhibited that the alteration of the gut microbiota was significantly related to adjustment of the IEC barrier and Treg/Th17 balance. In conclusion, all findings proposed that purified PHP has the potential to develop into a promising agent for colitis prevention and adjuvant therapy via maintaining intestinal homeostasis of gut microbiota and immune system.

RMG Database for Chemical Property Prediction.

The Reaction Mechanism Generator (RMG) database for chemical property prediction is presented. The RMG database consists of curated datasets and estimators for accurately predicting the parameters necessary for constructing a wide variety of chemical kinetic mechanisms. These datasets and estimators are mostly published and enable prediction of thermodynamics, kinetics, solvation effects, and transport properties. For thermochemistry prediction, the RMG database contains 45 libraries of thermochemical parameters with a combination of 4564 entries and a group additivity scheme with 9 types of corrections including radical, polycyclic, and surface absorption corrections with 1580 total curated groups and parameters for a graph convolutional neural network trained using transfer learning from a set of >130 000 DFT calculations to 10 000 high-quality values. Correction schemes for solvent-solute effects, important for thermochemistry in the liquid phase, are available. They include tabulated values for 195 pure solvents and 152 common solutes and a group additivity scheme for predicting the properties of arbitrary solutes. For kinetics estimation, the database contains 92 libraries of kinetic parameters containing a combined 21 000 reactions and contains rate rule schemes for 87 reaction classes trained on 8655 curated training reactions. Additional libraries and estimators are available for transport properties. All of this information is easily accessible through the graphical user interface at https://rmg.mit.edu. Bulk or on-the-fly use can be facilitated by interfacing directly with the RMG Python package which can be installed from Anaconda. The RMG database provides kineticists with easy access to estimates of the many parameters they need to model and analyze kinetic systems. This helps to speed up and facilitate kinetic analysis by enabling easy hypothesis testing on pathways, by providing parameters for model construction, and by providing checks on kinetic parameters from other sources.

Multi-nanocavities and multi-defects synergetic enhancement for the electromagnetic absorption of the rGO-NG film.

Dielectric loss is an important way to eliminate electromagnetic pollution. In order to achieve high dielectric loss, a graphene film reduced graphene oxide-N doped graphene (rGO-NG) was constructed from graphene oxide-Ni@polydopamine (GO-Ni@PDA) via thein situsynthesis of hollow graphene spheres between graphene sheets. Thisin situwas achieved by means of electrostatic self-assembly and metal-catalyzed crystallization. Owing to the synergetic effect of multi-nanocavities and multi-defects, the prepared rGO-NG film shows an average shielding effectiveness (SE) of 50.0 dB in the range of 8.2-12.4 GHz with a thickness of 12.2µm, and the SE reflection is only 7.3 dB on average. It also exhibits an average dielectric loss tangent (tanδ) of 23.1, which is 26 and 105 times higher than those of rGO and rGO-Ni, respectively. This work provides a simple but effective route to develop high performance graphene-based materials for application as an electromagnetic interference shielding film in today's electronic devices.

Evaluation of Potential Impacts of Free Chlorine during Washing of Fresh-Cut Leafy Greens on Escherichia coli O157:H7 Cross-Contamination and Risk of Illness.

Addition of chlorine-based antimicrobial substances to fresh-cut leafy green wash water is done to minimize microbial cross-contamination during processing. We developed the FDA Leafy Green Risk Assessment Model (FDA-LGRAM) to quantify the impact of free chlorine concentration in wash water during fresh-cut lettuce processing on the extent of water-mediated cross-contamination between shredded lettuce and the associated risk of illness due to exposure to Escherichia coli O157:H7. At different contamination prevalence and levels of E. coli O157:H7 on incoming lettuce heads, the model compared the predicted prevalence of contaminated fresh-cut lettuce packages and the risk of illness per serving between: (1) a scenario where fresh-cut lettuce was packaged without washing; and (2) scenarios involving washing fresh-cut lettuce with different levels of free chlorine (0 ppm, 5 ppm, 10 ppm, 15 ppm, and 20 ppm) prior to packaging. Our results indicate that the free chlorine level in wash water has a substantial impact on the predicted prevalence of contaminated fresh-cut lettuce packages and the risk of illness associated with E. coli O157:H7 in fresh-cut lettuce. Results showed that the required level of free chlorine that can minimize water-mediated cross-contamination and reduce the corresponding risk of illness depended on contamination prevalence and levels of E. coli O157:H7 on incoming lettuce heads. Our model also indicated that the pathogen inactivation rate in wash water via free chlorine was a key model parameter that had a significant impact on the extent of cross-contamination during washing and the predicted associated risk of illness.

Application of ß-Glucosidase in a Biphasic System for the Efficient Conversion of Polydatin to Resveratrol.

Resveratrol, an ingredient of traditional Chinese medicine, has beneficial effects on human health and huge potential for application in modern medicine. Polydatin is extracted from plants and then deglycosylated into resveratrol; enzymatic methods are preferred for this reaction. In this study, a ß-D-glucosidase from Sphingomonas showed high efficiency in transforming polydatin into resveratrol and was tolerant toward organic solvents. Applying this enzyme in a biphasic transformation system resulted in 95.3% conversion of 20% concentration crude polydatin to resveratrol in 4 h. We thus report a new method for high-efficiency, clean production of resveratrol.

Modeling optical emission from a highly multi-mode step-index fiber via ray tracing and the limitations.

Geometric optics is widely applied for diverse optical simulations. In this work, we introduce an incoherent ray model to describe the laser beam radiation emitted from a highly multi-mode step-index fiber, which is frequently applied for industrial laser material processing. First the mathematical validation and the limitation of this model are demonstrated. Then we determine the ray density and the angular spectrum according to measured intensity profiles along the caustic. Furthermore, based on the determined information, we demonstrate the simulation and measurement of the laser beam shaped by an axicon telescope. Not only the reconstruction itself, but also the simulation with free form optics present significant agreements to the measurements. The reasonable modeling of a laser source via geometric optics enables the precise determination of laser radiation and propagation properties with refractive beam shaping technologies.

ß2-Adrenoceptor Activation Stimulates IL-6 Production via PKA, ERK1/2, Src, and Beta-Arrestin2 Signaling Pathways in Human Bronchial Epithelia.

OBJECTIVE: ß2-Adrenoceptor agonists are widely used to treat asthma because of their bronchial-dilation effects. We previously reported that isoprenaline, via the apical and basolateral ß2-adrenoceptor, induced Cl- secretion by activating cyclic AMP (cAMP)-dependent pathways in human bronchial epithelia. Despite these results, whether and how the ß2-adrenoceptor-mediated cAMP-dependent pathway contributes to pro-inflammatory cytokine release in human bronchial epithelia remains poorly understood. METHODS: We investigated ß2-adrenoceptor-mediated signaling pathways involved in the production of two pro-inflammatory cytokines, interleukin (IL)-6 and IL-8, in 16HBE14o- human bronchial epithelia. The effects of isoprenaline or formoterol were assessed in the presence of protein kinase A (PKA), exchange protein directly activated by cAMP (EPAC), Src, and extracellular signal-regulated protein kinase (ERK)1/2 inhibitors. The involvement of ß-arrestin2 was examined using siRNA knockdown. RESULTS: Isoprenaline and formoterol (both ß2 agonists) induced IL-6, but not IL-8, release, which could be inhibited by ICI 118,551 (ß2 antagonist). The PKA-specific inhibitor, H89, partially inhibited IL-6 release. Another intracellular cAMP receptor, EPAC, was not involved in IL-6 release. Isoprenaline-mediated IL-6 secretion was attenuated by dasatinib, a Src inhibitor, and PD98059, an ERK1/2 inhibitor. Isoprenaline treatment also led to ERK1/2 phosphorylation. In addition, knockdown of ß-arrestin2 by siRNA specifically suppressed cytokine release when a high concentration of isoprenaline (1 mM) was used. CONCLUSION: Our results suggest that activation of the ß2-adrenoceptor in 16HBE14o- cells stimulated the PKA/Src/ERK1/2 and/or ß-arrestin2 signaling pathways, leading to IL-6 release. Therefore, our data reveal that ß2-adrenoceptor signaling plays a role in the immune regulation of human airway epithelia.