Identifying uncertainty in physical-chemical property estimation with IFSQSAR.

This study describes the development and evaluation of six new models for predicting physical-chemical (PC) properties that are highly relevant for chemical hazard, exposure, and risk estimation: solubility (in water SW and octanol SO), vapor pressure (VP), and the octanol-water (KOW), octanol-air (KOA), and air-water (KAW) partition ratios. The models are implemented in the Iterative Fragment Selection Quantitative Structure-Activity Relationship (IFSQSAR) python package, Version 1.1.0. These models are implemented as Poly-Parameter Linear Free Energy Relationship (PPLFER) equations which combine experimentally calibrated system parameters and solute descriptors predicted with QSPRs. Two other ancillary models have been developed and implemented, a QSPR for Molar Volume (MV) and a classifier for the physical state of chemicals at room temperature. The IFSQSAR methods for characterizing applicability domain (AD) and calculating uncertainty estimates expressed as 95% prediction intervals (PI) for predicted properties are described and tested on 9,000 measured partition ratios and 4,000 VP and SW values. The measured data are external to IFSQSAR training and validation datasets and are used to assess the predictivity of the models for "novel chemicals" in an unbiased manner. The 95% PI intervals calculated from validation datasets for partition ratios needed to be scaled by a factor of 1.25 to capture 95% of the external data. Predictions for VP and SW are more uncertain, primarily due to the challenges in differentiating their physical state (i.e., liquids or solids) at room temperature. The prediction accuracy of the models for log KOW, log KAW and log KOA of novel, data-poor chemicals is estimated to be in the range of 0.7 to 1.4 root mean squared error of prediction (RMSEP), with RMSEP in the range 1.7-1.8 for log VP and log SW. Scientific contributionNew partitioning models integrate empirical PPLFER equations and QSARs, allowing for seamless integration of experimental data and model predictions. This work tests the real predictivity of the models for novel chemicals which are not in the model training or external validation datasets.

Modeling sorption of environmental organic chemicals from water to soils.

Reliable estimation of chemical sorption from water to solid phases is an essential prerequisite for reasonable assessments of chemical hazards and risks. However, current fate and exposure models mostly rely on algorithms that lack the capability to quantify chemical sorption resulting from interactions with multiple soil constituents, including amorphous organic matter, carbonaceous organic matter, and mineral matter. Here, we introduce a novel, generic approach that explicitly combines the gravimetric composition of various solid constituents and poly-parameter linear free energy relationships to calculate the solid-water sorption coefficient (Kd) for non-ionizable or predominantly neutral organic chemicals with diverse properties in a neutral environment. Our approach demonstrates an overall statistical uncertainty of approximately 0.9 log units associated with predictions for different types of soil. By applying this approach to estimate the sorption of 70 diverse chemicals from water to two types of soils, we uncover that different chemicals predominantly exhibit sorption onto different soil constituents. Moreover, we provide mechanistic insights into the limitation of relying solely on organic carbon normalized sorption coefficient (KOC) in chemical hazard assessment, as the measured KOC can vary significantly across different soil types, and therefore, a universal cut-off threshold may not be appropriate. This research highlights the importance of considering chemical properties and multiple solid constituents in sorption modeling and offers a valuable theoretical approach for improved chemical hazard and exposure assessments.

Chemical Space Covered by Applicability Domains of Quantitative Structure-Property Relationships and Semiempirical Relationships in Chemical Assessments.

A significant number of chemicals registered in national and regional chemical inventories require assessments of their potential "hazard" concerns posed to humans and ecological receptors. This warrants knowledge of their partitioning and reactivity properties, which are often predicted by quantitative structure-property relationships (QSPRs) and other semiempirical relationships. It is imperative to evaluate the applicability domain (AD) of these tools to ensure their suitability for assessment purpose. Here, we investigate the extent to which the ADs of commonly used QSPRs and semiempirical relationships cover seven partitioning and reactivity properties of a chemical "space" comprising 81,000+ organic chemicals registered in regulatory and academic chemical inventories. Our findings show that around or more than half of the chemicals studied are covered by at least one of the commonly used QSPRs. The investigated QSPRs demonstrate adequate AD coverage for organochlorides and organobromines but limited AD coverage for chemicals containing fluorine and phosphorus. These QSPRs exhibit limited AD coverage for atmospheric reactivity, biodegradation, and octanol-air partitioning, particularly for ionizable organic chemicals compared to nonionizable ones, challenging assessments of environmental persistence, bioaccumulation capability, and long-range transport potential. We also find that a predictive tool's AD coverage of chemicals depends on how the AD is defined, for example, by the distance of a predicted chemical from the centroid of the training chemicals or by the presence or absence of structural features.

Hazard vs. exposure: Does it make a difference in identifying chemicals with persistence and mobility concerns?

Persistent and mobile (PM) chemicals are considered emerging threats to the environment and drinking water because they can be transported over long distances, penetrate natural and artificial barriers, and resist removal by traditional water treatment procedures. Current chemical regulatory frameworks raise concerns over PM chemicals due to their potential to cause high human exposure through drinking water contamination. However, the criteria used to screen and identify these chemicals often rely on hazard properties related to stability and sorption, such as biodegradation half-lives and organic-carbon-normalized sorption coefficients as respective measures of P and M. Here, we conduct a model-based assessment to examine the consistency between hazard-based and exposure-based approaches in assessing PM chemicals, by evaluating whether chemicals identified as highly P and M are consistently associated with high drinking water exposure potential (DWEP). We discover that chemicals with the top DWEPs tend to be PM chemicals, but the reverse is not always true, because DWEPs are also impacted by volatilization for air-distributed chemicals and advective particle-bound transport for particle-bound chemicals. Our findings suggest that the hazard metrics are better suited for de-prioritizing, as opposed to prioritizing, chemicals that are unlikely to result in significant human exposure through drinking water, as unfavorable values of hazard metrics are a necessary but not sufficient condition for a high DWEP. We also find that distinct mechanisms determine the DWEP in different sources of drinking water: Sorption and stability are more influential on the DWEP of chemicals in groundwater and surface water, respectively, whereas both sorption and stability equally impact water undergoing riverbank filtration. Future studies should focus on optimizing the identification of persistent and mobile chemicals to ensure that exposure potential is taken into consideration.

Sequential extraction of labile and recalcitrant fractions of soil organic matter: A case study focusing on antimony (Sb) in humic acids, fulvic acids and humin fractions of long-term aged contaminated soils.

Soil organic matter (SOM) plays a key role in environmental chemistry of macro and micro nutrients as well as heavy metal (loids). In this research, a modified sequential extraction scheme was used to isolate labile and recalcitrant SOM from organic rich soils after 18 months of ageing with antimony. Humic substances were extracted with a mixture of 0.5 M sodium hydroxide +0.1 M sodium pyrophosphate solution from soils. Then soils deprived of humic substances were sequentially subjected to extraction with glycerol, citric acid, pre-treated with acid and extracted with boiling alkali mixture. The humic acids (HA) and fulvic acids (FA) of isolated SOM fractions were separated and HAs been characterized using FTIR, 1H NMR, and UV-VIS. Acid-alkali treatment of the most recalcitrant SOM fraction (A1-ROM) led to the extraction of sparingly soluble, highly aromatic compound with considerable amounts of N (44% of the extractable N), possibly due to the breakdown of bounds between aromatic rings and amine functional groups. Nevertheless, the highest content of C and TOC was associated with the glycerol extractable SOM. Substantial amounts of Fe and Al were extracted with glycerol, resulting in a dramatic rise of Sb in SOM extracts. The largest increase (60%) in Sb concentrations was observed after the removal of Fe with citric acid. The humic substances (HS) were responsible for 63% of extractable Sb, whereas even after exhaustive alkali extractions 22% of the total Sb remained in the residual humin fraction. Within the HS fraction, 95% of antimony was associated with the low molecular weight FAs. Antimony concentrations in organic fractions correlated significantly with TOC and N contents, possibly due to the role of amine functional groups in Sb complexation. The results of this research highlight the importance of Fe-Al-SOM bridging and humin fraction in sequestration of Sb in recalcitrant SOM pools.

Universal Langmuir and Fractal Analysis of High-Resolution Adsorption Isotherms of Argon and Nitrogen on Macroporous Silica.

High-resolution isotherms of argon and nitrogen adsorption on macroporous silica have been simulated with universal Langmuir and fractal models. A four-parameter, fractal universal Langmuir equation is a good fit to the data at low pressures. Standard Gibbs energy changes calculated from equilibrium adsorption coefficients show a series of broad peaks that indicate adsorbate structural transformations as a function of pressure and coverage. The Freundlich equation or mean fractal model is also a good fit to isotherms at low pressures. Pressure-varying fractals are accurate fits to the data. Fractal exponents provide information on adsorbate coverage and surface access. Broad peaks in pressure-varying exponents are indicators of adsorbate structure. From adsorptive gas amounts, mean and pressure-varying fractal exponents provide details of adsorbate fractal dimensions and surface roughness. Both Ar and N2 adsorption cause increases in mean surface roughness when compared with pure silica. Surface roughness fluctuations from pressure-dependent adsorptive gas fractal dimensions are associated with adsorbate structure. At one trough, the surface is smooth and is linked to close-packed Ar or N2. For Ar adsorption at 87 K, this structure is a complete monolayer (1.00(4)), while for Ar (77 K), 1.15(4) layers and for N2 (87 K), 2.02(10) layers. The universal Langmuir specific area of the silica is 10.1(4) m2 g-1. Pressure- and coverage-dependent adsorbate structures range from filling defects and holes on the surface to cluster formation to adsorbed Ar or N2 evenly distributed or packed across the surface. The Ar (87 K) isotherm is most sensitive to adsorbate structural transformations.

Developing an internal threshold of toxicological concern (iTTC).

BACKGROUND: Threshold of Toxicological Concern (TTC) approaches are used for chemical safety assessment and risk-based priority setting for data poor chemicals. TTCs are derived from in vivo No Observed Effect Level (NOEL) datasets involving an external administered dose from a single exposure route, e.g., oral intake rate. Thus, a route-specific TTC can only be compared to a route-specific exposure estimate and such TTCs cannot be used for other exposure scenarios such as aggregate exposures. OBJECTIVE: Develop and apply a method for deriving internal TTCs (iTTCs) that can be used in chemical assessments for multiple route-specific exposures (e.g., oral, inhalation or dermal) or aggregate exposures. METHODS: Chemical-specific toxicokinetics (TK) data and models are applied to calculate internal concentrations (whole-body and blood) from the reported administered oral dose NOELs used to derive the Munro TTCs. The new iTTCs are calculated from the 5th percentile of cumulative distributions of internal NOELs and the commonly applied uncertainty factor of 100 to extrapolate animal testing data for applications in human health assessment. RESULTS: The new iTTCs for whole-body and blood are 0.5 nmol/kg and 0.1 nmol/L, respectively. Because the iTTCs are expressed on a molar basis they are readily converted to chemical mass iTTCs using the molar mass of the chemical of interest. For example, the median molar mass in the dataset is 220 g/mol corresponding to an iTTC of 22 ng/L-blood (22 pg/mL-blood). The iTTCs are considered broadly applicable for many organic chemicals except those that are genotoxic or acetylcholinesterase inhibitors. The new iTTCs can be compared with measured or estimated whole-body or blood exposure concentrations for chemical safety screening and priority-setting. SIGNIFICANCE: Existing Threshold of Toxicological Concern (TTC) approaches are limited in their applications for route-specific exposure scenarios only and are not suitable for chemical risk and safety assessments under conditions of aggregate exposure. New internal Threshold of Toxicological Concern (iTTC) values are developed to address data gaps in chemical safety estimation for multi-route and aggregate exposures.

Treatment Efficacy and Clinical Effectiveness of EEG Neurofeedback as a Personalized and Multimodal Treatment in ADHD: A Critical Review.

PURPOSE: Recent reviews have proposed that scientifically validated standard EEG neurofeedback (NF) protocols are an efficacious and specific treatment for attention-deficit hyperactivity disorder (ADHD). Here, we review the current evidence for the treatment efficacy and clinical effectiveness of NF in ADHD to investigate whether NF treatment personalization (standard protocols matched to the electrophysiological features of ADHD) and combination with other interventions (psychosocial, sleep hygiene and nutritional advice) might yield superior long-term treatment outcomes relative to non-personalized NF and medication monotreatments. METHODS: The electronic databases PubMed and PsycINFO were systematically searched using our key terms. Of the 38 resulting studies, 11 randomized controlled trials (RCTs) and open-label studies were eligible for inclusion. Studies were analyzed for effect sizes and remission rates at the end of treatment and at follow-up. The effects of personalized and multimodal NF treatments were compared to non-personalized NF monotreatments and with two benchmark medication studies. RESULTS: The analysis of RCTs indicated that the long-term effects of personalized NF interventions were superior to non-personalized NF and comparable to those of medication alone or in combination with behavioral intervention. The analysis of open-label trials further indicates that the interaction of NF with parental interventions, sleep and nutritional advice might yield superior clinical effectiveness relative to NF and medication monotreatments. CONCLUSION: Personalized and multimodal NF interventions seem to yield superior treatment efficacy relative to NF alone and superior clinical effectiveness relative to medication. We propose that treatment outcomes may be further enhanced by adjusting NF non-specific factors (eg, reinforcement contingencies) to specific ADHD characteristics (eg, reward sensitivity). Future NF research should focus on the systematic evaluation of the treatment outcomes of personalized and multimodal treatments.

The influence of different antimony (Sb) compounds and ageing on bioavailability and fractionation of antimony in two dissimilar soils.

Assessing the bioavailability of various Sb substances plays a crucial role in human health and the ecological risk assessment of contaminated soils. However, fate, behaviour and bioavailability of different Sb compounds in soils are insufficiently known. Therefore, in this present study, the effects of soil properties and ageing on bioavailability of four different Sb compounds (C8H4K2O12Sb2, Sb2S3, Sb2O3 and Sb2O3 nanoparticles) were evaluated during 120 days ageing time. A black soil (BS) with approximately 12% organic matter (OM) and a red soil (RS) with less than 1% OM were amended with 1000 mg Sb kg-1 of different Sb compounds and subjected to single extractions with distilled (DI) water, 2M HNO3, Simplified Bioaccessibility Extraction Test (SBET) and a modified Community Bureau of Reference (BCR) sequential extraction method. The results revealed that there are substantial variations in dissolution rate of various Sb sources, depending upon soil type and Sb compound. The amounts of DI water extractability of Sb during the incubation time varied between <1% and 2%, whereas HNO3 extractable fractions and Sb bioaccessibility at the end of ageing time ranged between about 1%-3% and <1%-9% of the total Sb, with maximum bioaccessibility observed in BS contaminated with C8H4K2O12Sb2. The residual and labile fractions accounted for 77-93% and 0.1-4% of the total Sb, respectively, indicating that Sb is mostly associated with recalcitrant fractions of the soils. The results of single and sequential extraction studies revealed that source of Sb, ageing time and soil properties can greatly affect the bioavailability of Sb in soils. The findings of this research provide a deeper understanding of the potential risks associated with Sb compounds and highlights the role of site-specific considerations for improving the robustness of toxicity guidelines and long-term management of Sb contaminated sites.

An update to the Milk Allergy in Primary Care guideline.

The Milk Allergy in Primary (MAP) Care guideline was first published in 2013 in this journal. MAP aimed to provide simple and accessible algorithms for UK clinicians in primary care, detailing all the steps between initial presentation, through diagnosis, management and tolerance development. Despite its UK focus, it soon became clear that MAP was being accessed internationally and thus an updated International Milk Allergy in Primary Care (iMAP) guideline was published in 2017. Both guidelines used existing international consensus guidelines to develop accessible algorithms accompanied by patient information leaflets. In 2018, the guidelines were criticised for 3 distinct reasons: promoting the overdiagnosis of cow's milk allergy (CMA), negatively impacting breastfeeding and the possibility of industry influence on the guidelines. The authors address these criticisms using available evidence and, in the context of this and in consultation with patient groups, members of the General Practice Infant Feeding Network and other infant feeding healthcare leads, have collaboratively produced updated algorithms and an information leaflet to support breastfeeding. We believe iMAP is now closer to its original aim of facilitating early and accurate diagnosis of CMA, whilst minimising, as far as possible, any concerns around overdiagnosis or a risk to breastfeeding rates. We continue to welcome open and constructive engagement about how best to achieve these aims to provide evidence-based, practical guidelines for the primary care practitioner.

Application of an Iterative Fragment Selection (IFS) Method to Estimate Entropies of Fusion and Melting Points of Organic Chemicals.

The main objective of this study is to develop and evaluate novel Quantitative Structure-Property Relationships (QSPRs) for predicting entropy of fusion (ΔSM ) and melting point (TM ) of organic chemicals from chemical structure. The QSPRs are developed using the Iterative Fragment Selection (IFS) method that requires only 2D structural information from the user (SMILES codes) for property prediction. The QSPRs also provide information on the applicability domain for each calculation and uncertainty estimates for the predictions. The root mean square error (RMSE) for the external validation sets are 11.8 J mol-1 K-1 and 46.9 K for the ΔSM and TM QSPRs, respectively. The performance of the new QSPRs is comparable to other predictive methods but has advantages with respect to availability and ease of use as well as the guidance on applicability domain for each prediction. Limitations of the new QSPRs are discussed. The QSPRs are coded as a user-friendly, freely available tool.

Pressure-varying Langmuir parameters and stepped nitrogen adsorption on alumina and silica.

Insights into surface structures and thermodynamics are provided for nitrogen adsorption on two nonporous alumina adsorbents and two macroporous silica adsorbents by modelling high-resolution data using the simple Langmuir isotherm equation combined with pressure-varying flexible least squares. The fitted parameters, maximum adsorption capacity and standard Gibbs energy change for each adsorbent show multiple steps that are assumed to be indicative of transitions to different complete monolayer and multilayer structures. Pressure-varying N2 cross-sectional areas for three of the adsorbents are calculated by assuming that one of the steps is the Brunauer-Emmett-Teller monolayer with molecular area 16.2 Å2. The silica with added octyldimethylsilyl groups has pressure-varying parameter profiles that differ from the other adsorbents and here the N2 cross-sectional area is assumed to be 21.3 Å2 to ensure consistency with the literature surface area. Seven monolayers and multilayers are identified across the four adsorbents, and corresponding molecular areas compare favourably with reported values. At low pressures, adsorption occurs at the strongest sites, and is localised and dependent on surface heterogeneity and topography. Up to five complete, two-dimensional lattice structures are apparent in the mid-pressure ranges. At high pressures, multilayers and liquefaction points are observed and are independent of surface composition and heterogeneity.

Correction to: Better recognition, diagnosis and management of non-IgE-mediated cow's milk allergy in infancy: iMAP-an international interpretation of the MAP (Milk Allergy in Primary Care) guideline.

[This corrects the article DOI: 10.1186/s13601-017-0162-y.].

Better recognition, diagnosis and management of non-IgE-mediated cow's milk allergy in infancy: iMAP-an international interpretation of the MAP (Milk Allergy in Primary Care) guideline.

Cow's milk allergy (CMA) is one of the most common presentations of food allergy seen in early childhood. It is also one of the most complex food allergies, being implicated in IgE-mediated food allergy as well as diverse manifestations of non-IgE-mediated food allergy. For example, gastrointestinal CMA may present as food protein induced enteropathy, enterocolitis or proctocolitis. Concerns regarding the early and timely diagnosis of CMA have been highlighted over the years. In response to these, guideline papers from the United Kingdom (UK), Australia, Europe, the Americas and the World Allergy Organisation have been published. The UK guideline, 'Diagnosis and management of non-IgE-mediated cow's milk allergy in infancy-a UK primary care practical guide' was published in this journal in 2013. This Milk Allergy in Primary Care (MAP) guideline outlines in simple algorithmic form, both the varying presentations of cow's milk allergy and also focuses on the practical management of the most common presentation, namely mild-to-moderate non-IgE-mediated allergy. Based on the international uptake of the MAP guideline, it became clear that there was a need for practical guidance beyond the UK. Consequently, this paper presents an international interpretation of the MAP guideline to help practitioners in primary care settings around the world. It incorporates further published UK guidance, feedback from UK healthcare professionals and affected families and, importantly, also international guidance and expertise.

A toxicokinetic model for fish including multiphase sorption features.

In the scientific field of physiologically based toxicokinetic modeling the complexity of the model used depends on the complexity of the problem to be handled, leading to a broad range of existing models from simple 1-box models to complex multicompartment models. Most of these models work with lumped parameters, for example, an uptake efficiency parameter that can only be obtained with a fit of experimental data. The authors' goal was a model that is completely based on well-defined physiological and physicochemical parameters. Lumped parameters fitted on training data sets would limit the model's applicability. This would enable a new view on process understanding for uptake, distribution, and elimination procedures. Eventual goals are a better localization of chemicals within the organism itself, and to set the stage for future extensions toward ionic compounds and active transport across membranes. The model evaluation reported in the present study has shown that uptake, clearance, and bioaccumulation data for nonpolar chemicals are well predicted. Environ Toxicol Chem 2017;36:1538-1546. © 2016 SETAC.

Which Molecular Features Affect the Intrinsic Hepatic Clearance Rate of Ionizable Organic Chemicals in Fish?

Greater knowledge of biotransformation rates for ionizable organic compounds (IOCs) in fish is required to properly assess the bioaccumulation potential of many environmentally relevant contaminants. In this study, we measured in vitro hepatic clearance rates for 50 IOCs using a pooled batch of liver S9 fractions isolated from rainbow trout (Oncorhynchus mykiss). The IOCs included four types of strongly ionized acids (carboxylates, phenolates, sulfonates, and sulfates), three types of strongly ionized bases (primary, secondary, tertiary amines), and a pair of quaternary ammonium compounds (QACs). Included in this test set were several surfactants and a series of beta-blockers. For linear alkyl chain IOC analogues, biotransformation enzymes appeared to act directly on the charged terminal group, with the highest clearance rates for tertiary amines and sulfates and no clearance of QACs. Clearance rates for C12-IOCs were higher than those for C8-IOC analogues. Several analogue series with multiple alkyl chains, branched alkyl chains, aromatic rings, and nonaromatic rings were evaluated. The likelihood of multiple reaction pathways made it difficult to relate all differences in clearance to specific molecular features the tested IOCs. Future analysis of primary metabolites in the S9 assay is recommended to further elucidate biotransformation pathways for IOCs in fish.

Dermal permeation data and models for the prioritization and screening-level exposure assessment of organic chemicals.

High-throughput screening (HTS) models are being developed and applied to prioritize chemicals for more comprehensive exposure and risk assessment. Dermal pathways are possible exposure routes to humans for thousands of chemicals found in personal care products and the indoor environment. HTS exposure models rely on skin permeability coefficient (KP; cm/h) models for exposure predictions. An initial database of approximately 1000 entries for empirically-based KP data was compiled from the literature and a subset of 480 data points for 245 organic chemicals derived from testing with human skin only and using only water as a vehicle was selected. The selected dataset includes chemicals with log octanol-water partition coefficients (KOW) ranging from -6.8 to 7.6 (median=1.8; 95% of the data range from -2.5 to 4.6) and molecular weight (MW) ranging from 18 to 765g/mol (median=180); only 3% >500g/mol. Approximately 53% of the chemicals in the database have functional groups which are ionizable in the pH range of 6 to 7.4, with 31% being appreciably ionized. The compiled log KP values ranged from -5.8 to 0.1cm/h (median=-2.6). The selected subset of the KP data was then used to evaluate eight representative KP models that can be readily applied for HTS assessments, i.e., parameterized with KOW and MW. The analysis indicates that a version of the SKINPERM model performs the best against the selected dataset. Comparisons of representative KP models against model input parameter property ranges (sensitivity analysis) and against chemical datasets requiring human health assessment were conducted to identify regions of chemical properties that should be tested to address uncertainty in KP models and HTS exposure assessments.

Cow's Milk Allergy Prescribing Is Influenced by Regional and National Guidance.

OBJECTIVES: Cow's milk allergy (CMA) is the most common food allergy in children with many clinical manifestations, leading to misdiagnoses such as gastro-oesophageal reflux, infantile colic, and lactose intolerance with inappropriate prescribing. We aimed to determine the impact of infant feeding guidelines on CMA prescribing in UK primary care using a simple and inexpensive training package. METHODS: Prospectively collected data of infant feeding prescriptions in Northern Ireland from June 2012 to March 2014 were analysed with the intervention period between November 2012 and March 2013. A comparison was made between hypoallergenic formulae, appropriate for CMA, versus alternative prescriptions including antiregurgitation and colic products, lactose-free and partially hydrolysed milks, or infant Gaviscon. RESULTS: Comparing pre- and postintervention period, the total quantity of hypoallergenic formulae increased by 63.2% and alternative prescriptions decreased by 44.6% (P < 0.001). The total amount of all prescribed products decreased by 41.0% (P < 0.001). During the study period, the proportion of recommended CMA treatment increased from 3.4% before training to 9.8% in the short- and long-term follow-up (P < 0.001). The overall increase was £33,508 per year or £95.5 per general practitioner's surgery. CONCLUSIONS: We present the first study evaluating the impact of infant feeding guidelines on CMA prescribing in UK primary care. Practical advice and teaching of health professionals allowed for effective implementation of regional and national guidelines, with a significant impact on prescription patterns. This study shows promising results for prospective research on a national scale, including socioeconomical impact and cost-effectiveness.