The gap between experts, farmers and non-farmers on perceived environmental vulnerability and the influence of values and beliefs.

Science has played a mixed role in guiding conservation and sustainability-oriented decision-making by individuals, policymakers, institutions, and governments. Not all science-based conservation and sustainability initiatives that address issues facing humanity and ecosystems and global problems have gained public support. Conservation decisions and policy prescriptions are and may be based on perceptions about and experiences with the environment, local land use, and ecosystems that may not align with or be grounded in science or evidence from experts in the field. Values, beliefs, and perceptions associated with nature play a critical role in how individuals view biodiversity conservation, sustainability, and natural resource management. This study first examines the gap between experts (scientists and other field experts) and the public (farmers and non-farmers) about the state of water and land resources, wildlife and associated habitats, and aquatic biodiversity in the Smoky Hill River Watershed in western Kansas. Second, the study examines the role that values and beliefs play in shaping environmental perceptions for farmers and non-farmers. Analysis confirms that a gap between experts and farmers/non-farmers does exist, especially with respect to the state of the Ogallala Aquifer, playas, rivers and streams, lakes and reservoirs, native grasslands, wildlife habitats, farmland, native fish populations, and wildlife species. Ordered-logistic regression analyses, meanwhile, indicate that farmer and non-farmer perceptions about the state of the local environment are influenced by traditional and self-interested values, as well as environmental values and beliefs, but less so by religiosity and political ideology. Despite broad takeaways, results exhibited heterogeneity across the farmer and non-farmer subpopulations. If environmental professionals cannot align ecological data, stakeholders' values/perceptions, and policies, then the existing body of technical research and management on sustainability in natural and social sciences may be of little value.

Local environment and individuals' beliefs: The dynamics shaping public support for sustainability policy in an agricultural landscape.

Agricultural landscapes are the leading edge in the advancement of sustainability and climate change adaptation. The purpose of this study is to endogenize culture as shaped by natural-cultural feedback into individuals' decision-making processes on sustainability policy support. We present an agent-based model in which an adaptive cultural decision-rule quantifies the probability of an agent deciding to support a wildlife area policy for the Smoky Hill River Watershed (SHRW) in Kansas, USA. By using an ABM to examine the watershed as a coupled natural and human system, we learned that agents would adopt a new behavior, voting for the policy, if the cultural conditions were right, with high levels of beliefs and norms for freshwater and its biota. Our results indicate that individuals in the SHRW are not engaged in caring for fish, plants, and bird richness in their rivers and playas with few individuals supporting the policy in the naïve cultural setting (8.9 % of simulated population). However, enough agents would support the policy under a lower cultural threshold (40.7 % of simulated population). Our results show that sustainability policies need to account for the local culture to gain support, and if a policy is culturally meaningful, it does not need to be cheap. For an agricultural landscape, such as those commonly found in the Central Great Plains, this study presents new levers for policymakers on the conditions needed to help assemble popular support for sustainability policies.

Spirometry quality predictors in a large multistate prospective study.

BACKGROUND: The Gulf Long-Term Follow-up (GuLF) Study is a prospective cohort study of health effects associated with oil spill response and clean-up following the 2010 Deepwater Horizon Disaster (DWH). As part of the study, spirometry testing of lung function was carried out in home visits across multiple states. Few studies have described factors associated with spirometry test failure in field-based settings. OBJECTIVE: Our objective was to identify what factors, if any, predict test failure among GuLF Study participants who completed spirometry testing in a non-traditional setting. METHODS: Trained examiners administered spirometry (May 2011-May 2013) to 10,019 participants living in US Gulf States (LA, MS, TX, AL, FL) using an Easy-on ultrasonic spirometer. We applied American Thoracic Society/European Respiratory Society quality criteria to determine quality test failure and identified factors predictive of failure using both a Stepwise and a LASSO model. We calculated odds ratios and 95% confidence intervals (CIs) for associations of selected factors with test failure. RESULTS: Among GuLF Study participants who conducted spirometry, self-reported African American/Black participants (OR: 1.39, 95% CI: 1.23,1.56); men (OR:1.61, 95% CI: 1.41,1.83); and those making less than $20,000 per year (OR: 1.45, 95% CI: 1.26,1.67) were more likely to fail quality testing, while those who were obese were less likely to fail (OR: 0.61, 95% CI: 0.42,0.89). CONCLUSION: Field-based studies involving spirometry should identify and account for participant factors that may influence test failure. Coaching that is tailored to those less likely to have experience with spirometry may help reduce test failure rates.

A Novel Mitragynine Analog with Low-Efficacy Mu Opioid Receptor Agonism Displays Antinociception with Attenuated Adverse Effects.

Mitragynine and 7-hydroxymitragynine (7OH) are the major alkaloids mediating the biological actions of the psychoactive plant kratom. To investigate the structure-activity relationships of mitragynine/7OH templates, we diversified the aromatic ring of the indole at the C9, C10, and C12 positions and investigated their G-protein and arrestin signaling mediated by mu opioid receptors (MOR). Three synthesized lead C9 analogs replacing the 9-OCH3 group with phenyl (4), methyl (5), or 3'-furanyl [6 (SC13)] substituents demonstrated partial agonism with a lower efficacy than DAMGO or morphine in heterologous G-protein assays and synaptic physiology. In assays limiting MOR reserve, the G-protein efficacy of all three was comparable to buprenorphine. 6 (SC13) showed MOR-dependent analgesia with potency similar to morphine without respiratory depression, hyperlocomotion, constipation, or place conditioning in mice. These results suggest the possibility of activating MOR minimally (G-protein Emax ≈ 10%) in cell lines while yet attaining maximal antinociception in vivo with reduced opioid liabilities.

Predicted Mode of Binding to and Allosteric Modulation of the µ-Opioid Receptor by Kratom's Alkaloids with Reported Antinociception In Vivo.

Pain management devoid of serious opioid adverse effects is still far from reach despite vigorous research and development efforts. Alternatives to classical opioids have been sought for years, and mounting reports of individuals finding pain relief with kratom have recently intensified research on this natural product. Although the composition of kratom is complex, the pharmacological characterization of its most abundant alkaloids has drawn attention to three molecules in particular, owing to their demonstrated antinociceptive activity and limited side effects in vivo. These three molecules are mitragynine (MG), its oxidized active metabolite, 7-hydroxymitragynine (7OH), and the indole-to-spiropseudoindoxy rearrangement product of MG known as mitragynine pseudoindoxyl (MP). Although these three alkaloids have been shown to preferentially activate the G protein signaling pathway by binding and allosterically modulating the µ-opioid receptor (MOP), a molecular level understanding of this process is lacking and yet important for the design of improved therapeutics. The molecular dynamics study and experimental validation reported here provide an atomic level description of how MG, 7OH, and MP bind and allosterically modulate the MOP, which can eventually guide structure-based drug design of improved therapeutics.

High-resolution structures of multiple 5-HT3AR-setron complexes reveal a novel mechanism of competitive inhibition.

Serotonin receptors (5-HT3AR) play a crucial role in regulating gut movement, and are the principal target of setrons, a class of high-affinity competitive antagonists, used in the management of nausea and vomiting associated with radiation and chemotherapies. Structural insights into setron-binding poses and their inhibitory mechanisms are just beginning to emerge. Here, we present high-resolution cryo-EM structures of full-length 5-HT3AR in complex with palonosetron, ondansetron, and alosetron. Molecular dynamic simulations of these structures embedded in a fully-hydrated lipid environment assessed the stability of ligand-binding poses and drug-target interactions over time. Together with simulation results of apo- and serotonin-bound 5-HT3AR, the study reveals a distinct interaction fingerprint between the various setrons and binding-pocket residues that may underlie their diverse affinities. In addition, varying degrees of conformational change in the setron-5-HT3AR structures, throughout the channel and particularly along the channel activation pathway, suggests a novel mechanism of competitive inhibition.

Serotonin is perhaps best known as a chemical messenger in the brain, where it regulates mood, appetite and sleep. But as a hormone, serotonin works in other parts of the body too. Serotonin is predominantly made in the gut, where it binds receptor proteins that help to regulate the movement of substances through the gastrointestinal tract, aiding digestion. However, a surge in serotonin release in the gut induces vomiting and nausea, which commonly happens as a side effect of treating cancer with radiotherapy and chemotherapy. Anti-nausea drugs used to manage and prevent the severe nausea and vomiting experienced by cancer patients are therefore designed to target serotonin receptors in the gut. These drugs, called setrons, work by binding to serotonin receptors before serotonin does, essentially neutralising the effect of any surplus serotonin. Although they generally target serotonin receptors in the same way, some setrons are more efficient than others and can provide longer lasting relief. Clarifying exactly how each drug interacts with its target receptor might help to explain their differential effects. Basak et al. used a technique called cryo-electron microscopy to examine the interactions between three common anti-nausea drugs (palonosetron, ondansetron and alosetron) and one type of serotonin receptor, 5-HT3AR. The experiments showed that each drug changed the shape of 5-HT3AR, thereby inhibiting its activity to varying degrees. Further analysis identified a distinct 'interaction fingerprint' for the three setron drugs studied, showing which of the receptors' subunits each drug binds to. Simulations of their interactions also showed that water molecules play a crucial role in the process, exposing the binding pocket on the receptor's surface where the drugs attach. This work provides a structural blueprint of the interactions between anti-nausea drugs and serotonin receptors. The structures could guide the development of new and improved therapies to treat nausea and vomiting brought on by cancer treatments.

Developing an Environmental Health Sciences COVID-19 Research Agenda: Results from the NIEHS Disaster Research Response (DR2) Work Group's Modified Delphi Method.

Leveraging the community of practice recently established through the U.S. National Institute of Environmental Health Sciences (NIEHS) Disaster Research Response (DR2) working group, we used a modified Delphi method to identify and prioritize environmental health sciences Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and associated Coronavirus Disease 2019 (COVID-19) research questions. Twenty-six individuals with broad expertise across a variety of environmental health sciences subdisciplines were selected to participate among 45 self-nominees. In Round 1, panelists submitted research questions and brief justifications. In Round 2, panelists rated the priority of each question on a nine-point Likert scale. Responses were trichotomized into priority categories (low priority; medium priority; and high priority). A research question was determined to meet consensus if at least 69.2% of panelists rated it within the same priority category. Research needs that did not meet consensus in round 2 were redistributed for re-rating. Fourteen questions met consensus as high priority in round 2, and an additional 14 questions met consensus as high priority in round 3. We discuss the impact and limitations of using this approach to identify and prioritize research questions in the context of a disaster response.

Mechanism of µ-Opioid Receptor-Magnesium Interaction and Positive Allosteric Modulation.

In the era of opioid abuse epidemics, there is an increased demand for understanding how opioid receptors can be allosterically modulated to guide the development of more effective and safer opioid therapies. Among the modulators of the µ-opioid (MOP) receptor, which is the pharmacological target for the majority of clinically used opioid drugs, are monovalent and divalent cations. Specifically, the monovalent sodium cation (Na+) has been known for decades to affect MOP receptor signaling by reducing agonist binding, whereas the divalent magnesium cation (Mg2+) has been shown to have the opposite effect, notwithstanding the presence of sodium chloride. Although ultra-high-resolution opioid receptor crystal structures have revealed a specific Na+ binding site and molecular dynamics (MD) simulation studies have supported the idea that this monovalent ion reduces agonist binding by stabilizing the receptor inactive state, the putative binding site of Mg2+ on the MOP receptor, as well as the molecular determinants responsible for its positive allosteric modulation of the receptor, are unknown. In this work, we carried out tens of microseconds of all-atom MD simulations to investigate the simultaneous binding of Mg2+ and Na+ cations to inactive and active crystal structures of the MOP receptor embedded in an explicit lipid-water environment and confirmed adequate sampling of Mg2+ ion binding with a grand canonical Monte Carlo MD method. Analyses of these simulations shed light on 1) the preferred binding sites of Mg2+ on the MOP receptor, 2) details of the competition between Mg2+ and Na+ cations for specific sites, 3) estimates of binding affinities, and 4) testable hypotheses of the molecular mechanism underlying the positive allosteric modulation of the MOP receptor by the Mg2+ cation.

Inclusion of enclosed hydration effects in the binding free energy estimation of dopamine D3 receptor complexes.

Confined hydration and conformational flexibility are some of the challenges encountered for the rational design of selective antagonists of G-protein coupled receptors. We present a set of C3-substituted (-)-stepholidine derivatives as potent binders of the dopamine D3 receptor. The compounds are characterized biochemically, as well as by computer modeling using a novel molecular dynamics-based alchemical binding free energy approach which incorporates the effect of the displacement of enclosed water molecules from the binding site. The free energy of displacement of specific hydration sites is obtained using the Hydration Site Analysis method with explicit solvation. This work underscores the critical role of confined hydration and conformational reorganization in the molecular recognition mechanism of dopamine receptors and illustrates the potential of binding free energy models to represent these key phenomena.

Hidden bias in the DUD-E dataset leads to misleading performance of deep learning in structure-based virtual screening.

Recently much effort has been invested in using convolutional neural network (CNN) models trained on 3D structural images of protein-ligand complexes to distinguish binding from non-binding ligands for virtual screening. However, the dearth of reliable protein-ligand x-ray structures and binding affinity data has required the use of constructed datasets for the training and evaluation of CNN molecular recognition models. Here, we outline various sources of bias in one such widely-used dataset, the Directory of Useful Decoys: Enhanced (DUD-E). We have constructed and performed tests to investigate whether CNN models developed using DUD-E are properly learning the underlying physics of molecular recognition, as intended, or are instead learning biases inherent in the dataset itself. We find that superior enrichment efficiency in CNN models can be attributed to the analogue and decoy bias hidden in the DUD-E dataset rather than successful generalization of the pattern of protein-ligand interactions. Comparing additional deep learning models trained on PDBbind datasets, we found that their enrichment performances using DUD-E are not superior to the performance of the docking program AutoDock Vina. Together, these results suggest that biases that could be present in constructed datasets should be thoroughly evaluated before applying them to machine learning based methodology development.

Developing Large-Scale Research in Response to an Oil Spill Disaster: a Case Study.

Research conducted in the wake of a disaster can provide information to help mitigate health consequences, support future recovery efforts, and improve resilience. However, a number of barriers have prevented time-sensitive research responses following previous disasters. Furthermore, large-scale disasters present their own special challenges due to the number of people exposed to disaster conditions, the number of groups engaged in disaster response, and the logistical challenges of rapidly planning and implementing a large study. In this case study, we illustrate the challenges in planning and conducting a large-scale post-disaster research study by drawing on our experience in establishing the Gulf Long-term Follow-up (GuLF) Study following the 2010 Deepwater Horizon disaster. We describe considerations in identifying at-risk populations and appropriate comparison groups, garnering support for the study from different stakeholders, obtaining timely scientific and ethics review, measuring and characterizing complex exposures, and addressing evolving community health concerns and unmet medical needs. We also describe the NIH Disaster Research Response (DR2) Program, which provides a suite of resources, including data collection tools, research protocols, institutional review board guidance, and training materials to enable the development and implementation of time-critical studies following disasters and public health emergencies. In describing our experiences related to the GuLF Study and the ongoing efforts through the NIH DR2 Program, we aim to help improve the timeliness, quality, and value of future disaster-related data collection and research studies.

Evaluating environmental change and behavioral decision-making for sustainability policy using an agent-based model: A case study for the Smoky Hill River Watershed, Kansas.

Sustainability has been at the forefront of the environmental research agenda of the integrated anthroposphere, hydrosphere, and biosphere since the last century and will continue to be critically important for future environmental science. However, linking humans and the environment through effective policy remains a major challenge for sustainability research and practice. Here we address this gap using an agent-based model (ABM) for a coupled natural and human systems in the Smoky Hill River Watershed (SHRW), Kansas, USA. For this freshwater-dependent agricultural watershed with a highly variable flow regime influenced by human-induced land-use and climate change, we tested the support for an environmental policy designed to conserve and protect fish biodiversity in the SHRW. We develop a proof of concept interdisciplinary ABM that integrates field data on hydrology, ecology (fish richness), social-psychology (value-belief-norm) and economics, to simulate human agents' decisions to support environmental policy. The mechanism to link human behaviors to environmental changes is the social-psychological sequence identified by the value-belief-norm framework and is informed by hydrological and fish ecology models. Our results indicate that (1) cultural factors influence the decision to support the policy; (2) a mechanism modifying social-psychological factors can influence the decision-making process; (3) there is resistance to environmental policy in the SHRW, even under potentially extreme climate conditions; and (4) the best opportunities for policy acceptance were found immediately after extreme environmental events. The modeling approach presented herein explicitly links biophysical and social science has broad generality for sustainability problems.

New Dopamine D3-Selective Receptor Ligands Containing a 6-Methoxy-1,2,3,4-tetrahydroisoquinolin-7-ol Motif.

A series of analogues featuring a 6-methoxy-1,2,3,4-tetrahydroisoquinolin-7-ol unit as the arylamine "head" group of a classical D3 antagonist core structure were synthesized and evaluated for affinity at dopamine D1, D2, and D3 receptors (D1R, D2R, D3R). The compounds generally displayed strong affinity for D3R with very good D3R selectivity. Docking studies at D2R and D3R crystal structures revealed that the molecules are oriented such that their arylamine units are positioned in the orthosteric binding pocket of D3R, with the arylamide "tail" units residing in the secondary binding pocket. Hydrogen bonding between Ser 182 and Tyr 365 at D3R stabilize extracellular loop 2 (ECL2), which in turn contributes to ligand binding by interacting with the "tail" units of the ligands in the secondary binding pocket. Similar interactions between ECL2 and the "tail" units were absent at D2R due to different positioning of the D2R loop region. The presence of multiple H-bonds with the phenol moiety of the headgroup of 7 and Ser192 accounts for its stronger D3R affinity as compared to the 6,7-dimethoxy-1,2,3,4-tetrahydroisoquinoline-containing analogue 8.

Water Pharmacophore: Designing Ligands using Molecular Dynamics Simulations with Water.

In this study, we demonstrate a method to construct a water-based pharmacophore model which can be utilized in the absence of known ligands. This method utilizes waters found in the binding pocket, sampled through molecular dynamics. Screening of compound databases against this water-based pharmacophore model reveals that this approach can successfully identify known binders to a target protein. The method was tested by enrichment studies of 7 therapeutically important targets and compared favourably to screening-by-docking with Glide. Our results suggest that even without experimentally known binders, pharmacophore models can be generated using molecular dynamics with waters and used for virtual screening.

Solvation Structure and Thermodynamic Mapping (SSTMap): An Open-Source, Flexible Package for the Analysis of Water in Molecular Dynamics Trajectories.

We have developed SSTMap, a software package for mapping structural and thermodynamic water properties in molecular dynamics trajectories. The package introduces automated analysis and mapping of local measures of frustration and enhancement of water structure. The thermodynamic calculations are based on Inhomogeneous Fluid Solvation Theory (IST), which is implemented using both site-based and grid-based approaches. The package also extends the applicability of solvation analysis calculations to multiple molecular dynamics (MD) simulation programs by using existing cross-platform tools for parsing MD parameter and trajectory files. SSTMap is implemented in Python and contains both command-line tools and a Python module to facilitate flexibility in setting up calculations and for automated generation of large data sets involving analysis of multiple solutes. Output is generated in formats compatible with popular Python data science packages. This tool will be used by the molecular modeling community for computational analysis of water in problems of biophysical interest such as ligand binding and protein function.

Synthesis and evaluation of C9 alkoxy analogues of (-)-stepholidine as dopamine receptor ligands.

Tetrahydroprotoberberine alkaloids have shown interesting polypharmacological actions at dopamine receptors and are a unique template from which to mine novel molecules with dual selective actions at D1 and D3 receptors. Such compounds will be valuable to evaluate as anti-cocaine therapeutics. Towards that eventual goal, we engaged an SAR study in which a series of C9 alkoxy analogues of the D1/D2/D3 ligand (-)-stepholidine that possessed or lacked a C12 bromo functionality, were synthesized and evaluated for affinity at dopamine D1, D2 and D3 receptors. We found that the analogues are generally selective for the D1 receptor. Small n-alkoxy substituents (up to 4 carbons in length) were generally well tolerated for high D1 affinity but such groups reduced D3 affinity. In the case of C12 brominated analogues, C9 alkoxylation also had little effect on D1 affinity for the smaller alkoxy groups, but reduced D2 and D3 affinities significantly. C12 bromination tends to increase D1 receptor selectivity. A number of compounds were identified that retain affinity for D1 and D3 receptors but lack D2 receptor affinity. Among them, compound 22a was found to be a selective D1/D3 dual antagonist (Ki = 5.3 and 106 nM at D1 and D3 receptors). Docking studies performed on the analogues at the D3 receptor revealed a number of interactions that are important for affinity including a critical N - Asp110 salt bridge motif, H-bonds to Ser192 and Cys181 and hydrophobic interactions between the aryl rings and Phe106 and Phe345. The analogues adopt an orientation in which ring A is located in the orthosteric binding site while the C9 alkoxy substituents attached to ring D project into the secondary binding pocket of the D3 receptor.

Solvation thermodynamic mapping of molecular surfaces in AmberTools: GIST.

The expulsion of water from surfaces upon molecular recognition and nonspecific association makes a major contribution to the free energy changes of these processes. In order to facilitate the characterization of water structure and thermodynamics on surfaces, we have incorporated Grid Inhomogeneous Solvation Theory (GIST) into the CPPTRAJ toolset of AmberTools. GIST is a grid-based implementation of Inhomogeneous Fluid Solvation Theory, which analyzes the output from molecular dynamics simulations to map out solvation thermodynamic and structural properties on a high-resolution, three-dimensional grid. The CPPTRAJ implementation, called GIST-cpptraj, has a simple, easy-to-use command line interface, and is open source and freely distributed. We have also developed a set of open-source tools, called GISTPP, which facilitate the analysis of GIST output grids. Tutorials for both GIST-cpptraj and GISTPP can be found at ambermd.org. © 2016 Wiley Periodicals, Inc.

Enthalpic Breakdown of Water Structure on Protein Active-Site Surfaces.

The principles underlying water reorganization around simple nonpolar solutes are well understood and provide the framework for the classical hydrophobic effect, whereby water molecules structure themselves around solutes so that they maintain favorable energetic contacts with both the solute and the other water molecules. However, for certain solute surface topographies, water molecules, due to their geometry and size, are unable to simultaneously maintain favorable energetic contacts with both the surface and neighboring water molecules. In this study, we analyze the solvation of ligand-binding sites for six structurally diverse proteins using hydration site analysis and measures of local water structure, in order to identify surfaces at which water molecules are unable to structure themselves in a way that maintains favorable enthalpy relative to bulk water. These surfaces are characterized by a high degree of enclosure, weak solute-water interactions, and surface constraints that induce unfavorable pair interactions between neighboring water molecules. Additionally, we find that the solvation of charged side chains in an active site generally results in favorable enthalpy but can also lead to pair interactions between neighboring water molecules that are significantly unfavorable relative to bulk water. We find that frustrated local structure can occur not only in apolar and weakly polar pockets, where overall enthalpy tends to be unfavorable, but also in charged pockets, where overall water enthalpy tends to be favorable. The characterization of local water structure in these terms may prove useful for evaluating the displacement of water from diverse protein active-site environments.

Tetrahydroprotoberberine alkaloids with dopamine and σ receptor affinity.

Two series of analogues of the tetrahydroprotoberberine (THPB) alkaloid (±)-stepholidine that (a) contain various alkoxy substituents at the C10 position and, (b) were de-rigidified with respect to (±)-stepholidine, were synthesized and evaluated for affinity at dopamine and σ receptors in order to evaluate effects on D3 and σ2 receptor affinity and selectivity. Small n-alkoxy groups are best tolerated by D3 and σ2 receptors. Among all compounds tested, C10 methoxy and ethoxy analogues (10 and 11 respectively) displayed the highest affinity for σ2 receptors as well as σ2 versus σ1 selectivity and also showed the highest D3 receptor affinity. De-rigidification of stepholidine resulted in decreased affinity at all receptors evaluated; thus the tetracyclic THPB framework is advantageous for affinity at dopamine and σ receptors. Docking of the C10 analogues at the D3 receptor, suggest that an ionic interaction between the protonated nitrogen atom and Asp110, a H-bond interaction between the C2 phenol and Ser192, a H-bond interaction between the C10 phenol and Cys181 as well as hydrophobic interactions of the aryl rings to Phe106 and Phe345, are critical for high affinity of the compounds.

Evaluation of a model training program for respiratory-protection preparedness at local health departments.

Respiratory-protection programs have had limited application in local health departments and have mostly focused on protecting employees against exposure to tuberculosis (TB). The need to provide the public health workforce with effective respiratory protection has, however, been underscored by recent concerns about emerging infectious diseases, bioterrorism attacks, drug-resistant microbes, and environmental exposures to microbial allergens (as in recent hurricane flood waters). Furthermore, OSHA has revoked the TB standard traditionally followed by local health departments, replacing it with a more stringent regulation. The additional OSHA requirements may place increased burdens on health departments with limited resources and time. For these reasons, the North Carolina Office of Public Health Preparedness and Response and industrial hygienists of the Public Health Regional Surveillance Teams have developed a training program to facilitate implementation of respiratory protection programs at local health departments. To date, more than 1,400 North Carolina health department employees have been properly fit-tested for respirator use and have received training in all aspects of respiratory protection. This article gives an overview of the development and evaluation of the program. The training approach presented here can serve as a model that other health departments and organizations can use in implementing similar respiratory-protection programs.