It was found that the antimicrobial effectiveness of the silver-enriched red onion peel extract–gelatin films was higher at lower AgNO3 concentrations as compared to those usually used in the commercially available antimicrobial products. The enhancement of the antimicrobial effectiveness was analyzed and discussed, assuming the synergy between photoreducing agent (red onion peel extract) and silver nitrate (AgNO3) in the initial gel solutions leading to the intensification of Ag nanoparticles production. UV-initiated green synthesis of metal nanoparticles by using plant extracts as photoreducing agents is of particular interest since it is an environmentally friendly, easy-to-maintain, and cost-effective method. Plant molecules that act as reducing agents are assembled in a highly controlled way which makes them suitable for metal nanoparticle synthesis. Depending on the plant species, their application for green synthesis of metal nanoparticles for diverse applications may contribute to the mediation/reduction in organic waste amounts, thus enabling the implementation of the circular economy concept. In this work, UV-initiated green synthesis of Ag nanoparticles in hydrogels and hydrogel’s thin films containing gelatin (matrix), red onion peel extract of different concentrations, water, and a small amount of 1 M AgNO Allium cepa L.) is an important foodstuff consisting of phytomolecules such as phenolic acid, flavonoids, copaenes, thiosulfinate, organosulfur compounds, and anthocyanin [Onion  ,12,13,142O3 [It could be mentioned that stress conditions such as UV light, wounding, or infection induce the biosynthesis of phenolic compounds . Derivin2O3 , Au [20,2O3 ,22, Ag [2O3 ,24, and 2O3  nanopartHydrogels are three-dimensional cross-linked networks of hydrophilic polymer chains that have the ability to absorb and retain large amounts of water or biological fluids. Water serves as the medium for hydrogel swelling and for the diffusion of solutes. The amount of water or solvent absorbed by the hydrogel is an important parameter that influences its properties; however, the main component of hydrogel is polymer, which might be synthetic  and natural . The specific composition of a hydrogel can be tailored to achieve the desired properties and functionality for a particular application. The choice of polymers, cross-linkers (used to secure gelation and stability of hydrogels), additives (bioactive agents and/or nanoparticles), and other components. Depends on factors such as biocompatibility, mechanical strength, biodegradability, drug release kinetics, and the targeted environment or tissue. The use of biocompatible hydrogels ensures that the material is non-toxic and compatible with living tissues. This property is crucial for medical applications, as it minimizes adverse reactions and promotes tissue integration.When incorporating plant extracts and silver nanoparticles into biocompatible hydrogels, several potential benefits can be achieved: antimicrobial properties, which can help prevent the growth of bacteria and other microorganisms and reduce the risk of infection; and wound healing properties exhibited by certain plants, which can promote tissue regeneration and accelerate the healing process of wounds. However, it’s important to note that the development and utilization of such hydrogels require extensive research and testing to ensure their safety and efficacy. The choice of plant extracts, silver nanoparticle concentration, and formulation parameters must be carefully optimized to achieve the desired properties and therapeutic effects.The benefits of plant extract-gelatin-metal NPs composites have been approved for different plants by many authors. It is also known  that theThe aim of this work was to produce and characterize Ag NPs enriched antimicrobial and recyclable gel films containing red onion peel extract for possible medical and food packaging applications, implementing in parallel the principles of green policy in the circular economy.It is known ,29,30,31It was found that the red onion extract dilution with distilled water caused a blueshift of the absorbance band. The obtained UV-Vis spectra showed a broad peak with shoulder, indicating the presence of anthocyanins in red onion extract, which were responsible for a high absorbance at 240–280 nm and 465–560 nm ,33,34 anAnalysis of UV-Vis spectra and pH led to the suggestion that the most suitable concentrations of red onion peel extract might be between 2.4 wt.% and 7.00 wt.%. In order to explore this hypothesis, the contribution of each hydrogel’s component to UV-Vis absorbance spectra was examined by separately analyzing the UV-Vis absorbance spectra of the diluted red onion peel extract (4.75 wt.%), red onion extract-gelatin composition, and red onion extract-gelatin-silver nitrate hydrogel . It shou3 mixture also without application UV exposure. Synthesis of Ag NPs propagates via cationic silver (Ag+) interaction with flavonoids (at least quercetin) and polyphenols that are present in the red onion peel, as it was indicated in [It was possible to distinguish the absorbance peak at 488 nm, which corresponds to the position of the LSPR peak of Ag particles, thus indicating possible biosynthesis of Ag nano seeds in the initial gel-red onion peel extract-AgNOcated in . HoweverBased on the performed examination, the following composition of hydrogel was considered for further investigation: red onion extract (4.75 wt.%), gelatin (9.50 wt.%), silver nitrate (0.039 wt.%), and water.3 into silver nanoparticles. Therefore, the selection of the appropriate concentrations of red onion peel extract (unused bio-waste) and silver nitrate in the hydrogel’s composition combined with the UV exposure allows for controlling the size and quantity of the produced Ag-NPs. It is known ,36 that In order to produce the maximum amount of silver nanoparticles in red onion peel-extract-gelatin-silver nitrate hydrogels, experimental samples were additionally exposed to UV (36W), varying exposure time from 0 to 60 min. Significant color changes were observed in the exposed gel samples. These color changes were dependent on red onion peel extract concentration, the concentration of added silver nitrate (source of the produced nanoparticles), and UV exposure time .3 was very small (0.039 wt.%) in the hydrogel, it was suggested that some growth of NPs was present in experimental samples. This suggestion was experimentally approved when analyzing EDS results obtained for the hydrogel films.The UV-Vis spectra of the UV-exposed hydrogel samples  indicateAn example of experimentally prepared and 20-min-exposed red onion–gelatin film containing silver nanoparticles is presented in Performed investigation of the UV-exposed hydrogel films revealed that the corresponding absorbance peaks, which might indicate the presence of synthesized AgNPs (LSPR peaks of AgNPs), were clearly seen in the measured UV-Vis spectra at the wavelength of 457.6 nm, and the color of films was gradually changing with the increased exposure duration .As in the previous case with hydrogel solution, prolonged exposure of the hydrogel films was responsible for the absorbance band broadening; however, the absorbance bands of hydrogel films were narrower, and the LSPR peak of created Ag NPs was better expressed as compared to those measured for the hydrogel solutions. This was explained by the fact that prolonged exposure of hydrogel films having reduced amounts of water after drying may create a number of differently sized particles, but their mobility is restricted by the gelatin matrix. Stabilization of silver nanoparticles is realized by the amine pendant groups of the gelatin backbone. Long-term UV exposure of gels may also induce structural changes in the gelatin, which reduces the gelatin’s contribution to the absorbance spectrum of the exposed media ,39 and, Since the shape of UV-Vis spectra accounts for the presence of all hydrogel components, the formation and behavior of Ag NPs in the experimental films have been additionally approved by analyzing the results of XRD measurements and EDX measurements, and SEM images of the experimental samples. Supportive information could be obtained from FTIR measurements. 3 film after 20 min UV exposure is provided in 3, indicating that some amount of this material might not have been reduced and hence remained in the sample. XRD pattern of gelatin is usually seen in the range up to 30 degrees (2θ range) and does not overlap with metallic silver peaks; thus, this part of XRD spectra was omitted in this paper. It should be noted that the experimental XRD results were close to those obtained by other authors [An example of the XRD pattern of the red onion peel extract–gelatin–AgNO authors ,40. 3 in the experimental hydrogel films was very small (0.039 wt.%). It is known  that 3D It was not possible to draw conclusions regarding the amounts of silver nanoparticles in the hydrogel films from the obtained SEM images. A more detailed investigation of the elemental composition of UV-exposed samples performed using the EDX technique  revealedThe swelling ability of the films that are thought to the application as an antimicrobial wound dressing is of crucial importance. An ideal wound dressing should be able to absorb wound exudate and provide a wet environment for the wound. It should be noted  that theIt was found that the swelling ratio was higher than 60, which is sufficient for the application as hydrogel wound dressing was achieved 30 min after immersion of the hydrogel film in the distilled water. Staphylococcus aureus, Acinetobacter baumannii, Pseudomonas aeruginosa, and Pseudomonas aeruginosa bacteria. Significantly lower and very similar antimicrobial effect of experimental hydrogels was observed on Candida parapsilosis and Candida albicans yeasts, but there was no effect on Candida albicans observed in the case when hydrogel film containing Ag NPs was applied. The microscopic fungus, Aspergillus flavus, was completely unaffected by experimental hydrogels.Performed antimicrobial activity assessment in experimental hydrogels has shown  that redPseudomonas aeruginosa bacteria ATCC 15442 which are provided in The antimicrobial effect was slightly higher for hydrogel films, as could be seen from the results obtained for It was found that dried hydrogel films containing red onion peel extract, gelatin, and Ag NPs obtained via green photosynthesis were indicating higher ,44,45,46Nanosilver-gelatin-red-onion extract composite hydrogels were produced applying UV exposure supported green synthesis method and characterized using common analytical methods. The synthesized nanoparticles were differently sized and exhibited face-centered cubic crystalline structure, fixed inside of a gelatin matrix. 3 water solution were suitable for the formation of free-standing gel films that may produce a sufficient amount of silver nanoparticles upon UV exposure which is needed to secure antimicrobial efficiency of films. It was found that hydrogels containing 4.75 wt.% of red onion peel extract, 9.5 wt.%, and 0.039 wt.% of 1 M AgNOExperimental hydrogel films indicated relatively high swelling behavior achieving a swelling ratio > 60, which is sufficient for wound dressing 30 min after their immersion in distilled water.Staphylococcus aureus, Acinetobacter baumannii, and Pseudomonas aeruginosa bacteria; however, the antibacterial efficiency of red onion hydrogel films enriched with Ag NPs was higher, as compared to hydrogel solution of the same composition due lower mobility of silver ions in the media with reduced amount of water and fixation of synthesized Ag NPS in gelatin matrix.Both hydrogels and free-standing gel films were most effective against Allium cape var. cepa ‘Red Karmen’) were removed from the bulbs and dried. A total of 2.65 g of dried red onion peel was immersed in 53 g of distilled water and heated for 20 min at 62.5 °C. The prepared extract was filtered twice using a white-band filter  and was ready to use. For the hydrogel preparation, a certain amount of 1M AgNO3 water solution was dropped into red onion extract and then admixed to the dissolved gelatin under continuous stirring. Silver nitrate powder  and gelatin from porcine skin  were used for the formation of hydrogels. In order to decide the optimal concentration of the red onion peel extract in silver nitrate–red onion-gelatin hydrogel, different read onion extract concentrations , which were obtained diluting onion extract in the corresponding amount of water, were used for gel production. This was absolutely necessary, taking into account that the absorbance peak of the red onion peel extract appears in the wavelength region [The peels of fresh red onion  and then dried in the open air in a dark box at room temperature (22 ± 2 °C) for 24 h to form the films. It was found that the average mass loss in onion peel extract-gelatin films containing Ag nanoparticles was 8.6–10.13 wt.% of during the drying process. The thickness of the dried films prepared from 5 g of gels was (142.6 ± 11.3) µm. Photoreduction of silver ions in hydrogels and in gel films was performed under UV exposure using UV lamps . The exposure time of samples varied from 0 to 60 min. ® . Optical properties of experimental samples were evaluated by Jasco V 650 spectrometer  working in absorbance photometric mode with a measurement range from 200 nm to 800 nm, UV-Vis bandwidth 0.1 nm; and UV-Vis photospectrometer Ocean Optics USB 4000 UV-Vis  with a measurement range from 200 nm to 1100 nm, UV-Vis bandwidth 1.5 nm. The thickness of the gel films was measured with a digital micrometer . Active acidity of primary extracts (control solutions) and extracts with synthesized silver nanoparticles was measured by HI 98103CheckerThe surface morphologies of red-onion-gelatin films without and with silver nanoparticles were investigated by scanning electron microscope  using a secondary electron detector. Elemental mapping of red onion gelatin films without and with silver nanoparticles was performed using energy-dispersive X-ray spectroscopy .The structure of synthesized Ag NPS was investigated using a D8 Discover X-ray diffractometer  operating at 40 kV and 40 mA with Cu Kα source (λ = 1.5418 Å) and parallel beam geometry with 60 mm Göbel mirror. Diffraction patterns were recorded using a fast-counting LynxEye detector with an opening angle of 2.475 deg. Additionally, it had a slit opening of 6 mm .Swelling studies of the dried films were carried out in distilled water. The weighed amount of the dried film was immersed in 10 mL of the swelling solution at room (20 °C) temperature. At predefined time intervals, the film was separated from the swelling solution, gently wiped with filter paper, and weighed. The swelling capacity (tion (1) ,48:(1)StBacteria–Staphylococcus aureus ATCC 29213, Acinetobacter baumannii BAA 747, Pseudomonas aeruginosa ATCC 15442, yeasts–Candida parapsilosis CBS 8836, Candida albicans ATCC 90028 and microscopic fungi–Aspergillus flavus BTL G-33, Aspergillus fumigatus BTL G-38 were used in assays. Microorganisms were stored in a −70 °C freezer at the Laboratory of Biodeterioration Research of the Nature Research Centre . Bacteria for antimicrobial tests were grown on nutrient agar , and yeasts and fungi were grown on Sabouraud dextrose agar . Inoculums were obtained from overnight bacterial cultures grown on nutrient agar at 37 °C. Yeasts were cultured for 3 days, and fungi were cultured for 7 days at 28 °C. The optical density of the microorganism cell suspensions was measured with a spectrophotometer  at a wavelength of 610 nm. The resulting microorganism suspensions were vortexed for 15 s.The antimicrobial activity of red onion skin extract gels and films containing silver nanoparticles was tested using the agar diffusion method. For the agar diffusion assay, 100 µL of each microorganism suspension was uniformly spread on Mueller–Hinton agar (bacteria) or on Sabouraud dextrose agar (yeasts and microscopic fungi) in 90 mm Petri dishes. The red onion gels (10 µL) and films (5 × 5 mm) containing silver nanoparticles were placed on the surface of each media as the microbial suspension absorbed into it. The plates were incubated at 28 ± 1 °C for 3 (yeasts) or 5 days (microscopic fungi), while the plates with bacteria were incubated at 37 ± 1 °C for 2 days. All tests were triplicated for all strains. The red onion skin extract, gel, and film were used as negative controls. The diameters of the inhibition zones were measured in millimeters after the incubation period. Data were collected and processed with the corresponding program package. Mean, standard errors, and confidence intervals were calculated.


Background: This review aims to identify the current indications and gaps in the management of fat-soluble vitamins in pediatric patients with cholestasis. Methods: A comprehensive review of the literature using PubMed, Scopus, Web of Science and Embase was performed. Two authors independently identified the most relevant studies published over the past 20 years up to February 2022, including original papers, narrative reviews, observational studies, clinical trials, systematic reviews and meta-analyses. The literature was screened, and preclinical studies about pathogenetic mechanisms were also included. Keywords searched for each fat-soluble vitamin , alone or in combination, were “cholestasis”, “chronic liver disease”, “biliary atresia”, “malnutrition” and “nutritional needs”. Studies published prior to the selected time range were searched manually and, when considered relevant, included within the list of references. Results: Eight hundred twenty-six articles were initially screened. From these, 48 studies were selected. A comparison of the recommended methods of supplementation for fat-soluble vitamins was then carried out. The causes of malabsorption were explained and current methods for defining deficiency and monitoring complications were summarized. Conclusions: According to the literature, children with cholestasis are at a higher risk of fat-soluble vitamin deficiency. Although there are general recommendations, the treatment for vitamin deficiency is not uniformly validated. In the pediatric population, cholestasis predominantly affects newborns and infants. It affects approximately 1 in 2500 full-term births, with a substantial percentage having a chronic course. It has been defined as “chronic cholestatic liver disease” (CCLD), which can lead to end-stage liver disease, hence requiring liver transplantation.In the cholestatic diseases, impaired secretion of bile acids into the intestinal lumen and fat malabsorption induce a deficiency of fat-soluble vitamins . Absorption of these micronutrients requires the formation of micelles that solubilize liposoluble components in the intestine and facilitate their passive diffusion through the enterocyte. If the bile acid level in the intestinal lumen is below a critical micellar concentration, absorption of fat-soluble vitamins is impaired, thus leading to major complications, such as rickets, xerophthalmia and bleeding . When cholestasis begins in childhood, it is crucial to ensure an adequate intake of vitamins, adjusting the dosages to the specific needs of the patient and avoiding the onset of side effects. In the literature, the indications for supplementation have not been standardized, although different routes of administration and wide dosage ranges have been published. The aim of this review is to summarize and compare the data about deficiency of fat-soluble vitamins in cholestatic pediatric patients (CPP) to understand the real incidence of the problem and to conduct a comparison on the current indications.Fat-soluble vitamin (FSV) deficiency is one of major nutritional problems of chronic cholestatic liver disease. Several studies report different vitamin A, E and D deficiencies in patients with chronic liver disease (CLD) and cholestasis ,3 Table. p < 0.001), whereas vitamin D deficiency was similar between CPP and non-cholestatic patients  ..69].p < 0.001).At the moment of biliary atresia’s diagnosis, the absolute and relative risk of severe VKD and cerebral bleeding were examined. Blood loss due to vitamin K deficiency was noted in 25 of 30 breastfed infants (83%) receiving 25 μg of daily oral prophylaxis, 1 out of 13 receiving 1 mg of weekly oral prophylaxis (7%), 1 out of 10 (10%) receiving 2 mg of intramuscular prophylaxis at birth and 1 out of 98 infants receiving formula (1%) (The relative risk of bleeding was higher (RR = 77.5) in the 25 μg daily oral prophylaxis’ group, suggesting that this regimen is not able to prevent bleeding in infants who had been misdiagnosed with cholestasis but appeared healthy .These results indicate that breastfed infants with biliary atresia are not preserved by the Dutch prophylactic vitamin K regimen. At the time of cholestasis diagnosis, more than 80% of these kids had already had VKDB, and 43% of breastfed infants with biliary atresia experienced cerebral bleeding. Among Dutch breastfed infants with biliary atresia, the risk of VKDB was 8–10 times higher than in infants who had weekly oral prophylaxis or IM prophylaxis at birth; it was roughly 80 times higher than in infants who were formula-fed.The oral 1 mg weekly regimen appears to be more efficient than the 25 μg daily regimen and is comparable to IM treatment . This isp < 0.001)  .p = 0.43). The 2 mg IM group did not experience intracranial bleeding . In breastfed infants with undiagnosed BA, a preventive regimen of 1 mg of oral vitamin K at birth followed by daily oral doses of 25 or 150 μg failed to prevent VKDB. The data therefore confirmed the effectiveness of the prophylaxis against VKDB at birth with a 2 mg IM of vitamin K [Cerebral bleeding was a presenting symptom in 27% of infants in the 150 μg group in comparison with the 40% of all infants in the 25 μg group (itamin K . In concitamin K .Although the pharmacokinetics of intravenous (IV) vitamin K are unknown, they are probably comparable to those of vitamin K taken orally. To prevent the late type of VKDB, intravenous delivery does not appear to be as effective as the IM route, particularly if the injection is not repeated .1 mg vitamin K1 by intramuscular (IM) injection at birth;3 × 2 mg of vitamin K1 orally at birth, at 4–6 days and at 4–6 weeks;2 mg of vitamin K 1 orally at birth and a weekly dose of 1 mg orally for 3 months.According to the 2016 ESPGHAN Guidelines , healthyIn terms of effectiveness and dependability, IM administration is the most popular approach globally. Oral supplementation has been proposed, but it is not indicated in premature infants, infants with cholestasis or intestinal disorders and infants whose mothers have taken medications that may interfere with vitamin K metabolism. Thus, the best VKDB prophylaxis for this group of infants is currently thought to be a rapid postnatal IM vitamin K treatment . We repoOur review shows that the treatment of fat-soluble vitamin deficiency in children with cholestasis is complex, and each patient requires a tailored approach. Meanwhile, in clinical practice, it is often necessary to start from an empirical treatment, considering that serum levels of fat-soluble vitamins are not always immediately available, and laboratory results often require prolonged technical times. For this reason, in Most of these reviews have been focused on the nutritional indications for cholestasis and do not analyze exclusively the treatment of vitamin deficiencies. Considering data from the literature and the comparison of clinical studies and reviews, we propose an adapted summary of the treatment strategies for each vitamin .Our scoping review shows that pediatric patients with cholestasis have a high risk of fat-soluble vitamin deficiency. However, although there are general guidelines on management of these patients, there are still evidence gaps about dosages and supplementation strategies. The indications provided in the literature are not currently validated or clearly homogeneous, neither in terms of dosages nor in terms of routes of administration. Our study compared the different indications that can be used initially in the supplementation of patients, but it remains necessary to individually adjust the treatment according to plasma vitamin values. The complex management of these patients requires new studies to validate the efficacy of commercially available formulations and to improve new effective formulas.


Using explainable machine learningto interpret the outputs of a predictive model, we show that the degreeto which NO2 pollution was reduced in an area was correlatedwith spatial features (including road freight traffic and proximityto a major airport and the city center), and that existing inequalitiesin air pollution exposure were exacerbated: pollution reductions weregreater in places with more affluent residents and better access topublic transport services.Activity changes during the COVID-19 lockdown presentan opportunityto understand the effects that prospective emission control and airquality management policies might have on reducing air pollution.Using a regression discontinuity design for causal analysis, we showthat the first UK national lockdown led to unprecedented decreasesin road traffic, by up to 65%, yet incommensurate and heterogeneousresponses in air pollution in London. At different locations, changesin air pollution attributable to the lockdown ranged from −50%to 0% for nitrogen dioxide (NO We use causalinference and explainable machine learningto identify, quantify, and interpret heterogeneous changes to airpollution in response to the first COVID-19 lockdown in London. However, as a city is a complex network, the impactpathways from intervention to air quality can incorporate variousfactors (such as land use and demographics) and complicated interactions,3 which present challenges to isolating the interventioneffect and quantifying the contribution of factors to the net effect.The recent development of interpretation methods for machine learning(ML) models provides an opportunity to gain insights into complicatedrelationships among high-dimensional variables. Unlike “black-box”ML, explainable ML seeks to make the processes and outputs of themodel more interpretable and understandable to humans.4 These methods have been used to support decision-makingin various fields, including healthcare,5 transport safety,6 and epidemiology.7Air pollution exposure is the second leadingcause of noncommunicablediseases worldwide.11 Specifically, the UK’s first compulsory national lockdownon 23 March 2020 led to an immediate decrease in transport demandand public transport provision in London: by up to 65% for road traffic,15% for bus service provision, and 59% for London Underground serviceprovision.8 Meanwhile, both residentialactivities and home delivery services in London increased: the shareof workers working from home full-time increased from 4% prepandemicto 54% in March and April 2020, and the proportion of retail salescompleted online increased from 20% in 2019 to 33% by May 2020.8 While overall trends in activities were evident,heterogeneous responses were observed across vehicle type, spatiallocation, and population group.8 Societaltrends such as remote working and e-commerce are expected to persisteven after the pandemic.14Coronavirus disease 19 (COVID-19) has rapidlyspread worldwidesince it was initially identified in late 2019. In response, severalcountries implemented lockdown measures to limit nonessential activitiesand restrict close contacts to varying degrees. The lockdown requirements,ongoing pandemic, and global economic recession caused activity changesin various sectors.2, due to the stringent travel restrictions duringthe lockdown; however, for other pollutants such as PM2.5 and O3, the results are less significant and more mixed.20 For example, Venter et al.19 analyzedthe air quality levels across 34 countries worldwide and found thatlockdowns reduced NO2 and PM2.5 concentrationsby 60% and 31% on average, with a mixed effect on O3, rangingfrom −2% to 10%. Furthermore, several studies found lockdownshad heterogeneous effects on air quality across industrial structure,population size, transport demand, and geographical location.26 However, most of these studies focused on depicting the variationin effects across subsamples of cities or countries; few comparedeffects within a city or further evaluated the contribution of differentfactors to the heterogeneity of effects.Activity changes during the COVID-19 lockdown provide an unprecedentedopportunity to understand the likely effectiveness of prospectiveemission control policies and mobility patterns (such as higher levelsof fleet electrification and more remote working) in improving airquality. A growing number of studies have focused on evaluating theair quality impacts of COVID-19 lockdowns. Most results show a significantreduction in pollutants that are largely affected by transport activities,such as NO29 However, the impact estimatesfrom this approach are typically influenced by several factors, suchas weather conditions, seasonality effects, and a long-term trendin air quality, which has been improving in London.30 Some other studies quantified the impacts using a bottom-upsimulation.32 However, simulation typically requires detailedactivity/emission data, and the results are highly dependent on inputscenarios, emission factors, and substantial assumptions in variables.Additionally, several studies evaluated the impacts with predictionsof business-as-usual concentrations from statistical or ML models.34 However, this approach is subject to the generalization performanceof the predictive model.Several studies reportedthe lockdown impacts by comparing airquality before and after the lockdown.Causality goesbeyond statistical association by measuring the neteffect of an intervention on an outcome through all pathways.35 Causal inference methods have already been appliedto quantify the effect of COVID-19 lockdowns on air pollution.37 In these studies, sharp regression discontinuitydesign (RDD) is one of the main methods applied, and some importantconfounders  werecommonly controlled for by parametrically incorporating relevant variablesinto the model. However, due to the complexity of atmospheric processes,using a parametric confounding control for weather conditions in anair quality appraisal can be difficult.38 An alternative is to first use a nonparametric model to “de-weather”the pollution data.39Causal inference methods generallyhave advantages for interventionevaluation, in terms of data requirements, model building, and theinterpretation of effect estimates. 41 Various factors are considered,such as demographics, economy, transport demand, public transportsupply, and geographical location. The identification of key factorsaffecting the level of pollution reduction within a city can providefurther guidance in improving air quality and help shape our citywith better and more equitable urban design, planning, and management.In this paper, we provide a causal analysis of the first UKnationallockdown with a sharp RDD model to evaluate its causal impacts onLondon’s air quality. The meteorological normalization techniqueis applied to provide a nonparametric confounding control for weatherconditions and seasonality effects. To further understand the spatialheterogeneity shown in the lockdown impacts, we additionally evaluatethe contribution of different factors to the magnitude of lockdownimpacts by interpreting a ML model with Shapley Additive exPlanations(SHAP) values.2, O3, PM2.5, and PM10, and a nonregulatedpollutant, nitrogen oxides (NOx = NO +NO2).To quantifythe causal effects of the first UK national lockdown on London’sair quality, a sharp RDD model is applied at individual air qualitymonitoring sites within the geographical extent of the Greater LondonAuthority (GLA), for regulated air pollutants including NO43 Hourly meteorological observations for the same period are fromthe U.S. National Oceanic and Atmospheric Administration (NOAA).45 Details on data description, data merging, and data quality controlare provided in SI §S1. Roadside andbackground monitoring sites are distinguished in the analysis. A roadsidesite is generally installed close to a busy road to represent roadsidepublic exposure. A background site is located away from major emissionsources to represent general public exposure at the city level.46 After data merging and quality reviewing, 42background sites  and 50 roadside sites  are included in the study. The spatial distribution ofthese sites is illustrated in SI §S1.Hourly air pollutant concentrations from 2016-01-01to 2020-12-31 at monitoring sites are downloaded from the London AirQuality Network (LAQN) and the Air Quality England Network (AQE).SI §S1. 124 of the136 features are included in the analysis after applying the dataquality criteria (see SI §S1). Thefeature evaluation is conducted at the Middle Layer Super Output Area(MSOA) level. The GLA covers 983 MSOAs. MSOAs are small enough toindicate the spatial variation of features, and the total number islarge enough to build a predictive model using ML methods.To further interpret the spatial heterogeneity of lockdownimpacts,various spatial features are evaluated based on their contributionin predicting the pollution reduction caused by the lockdown, includingthe distance to town centers and London Heathrow Airport (LHR), population,employment, median earnings, business count, business turnover, publictransport accessibility level, annual average daily flow (AADF), andmotor vehicle traffic. Complete information for the features, relevantdata, and methods to assign feature values to different spatial locationscan be found in 30 and sequentiallycombines meteorological normalization, change point detection (CPD),and a sharp RDD model. The research framework and a pseudo code outliningthis method are shown in SI §S2. Thesharp RDD is a causal inference approach for nonrandomized interventions,which assumes that the intervention is assigned by the value of aforcing variable on either side of a threshold.47 The core of the methodology in Ma et al.30 is a sharp RDD with time as the forcing variable and thestart of the intervention, T0, as thethreshold.The methodology to quantifythe causal air quality impacts of an intervention with an explicitstart time follows Ma et al.48 A normalized air pollutant concentration time series is derivedby removing the variation in the observed concentrations that canbe explained by these factors. Meteorological variables included inthe model include temperature, wind speed, wind direction, atmosphericpressure, relative humidity, rainfall, and Monin–Obukhov length.Seasonality variables include the hours of the day, days of the week,and days of the year. A time variable is additionally included torepresent the long-term concentration trend. A nonparametric modelis used to consider the complex relationship between air pollutionand model variables. Further details on model training and normalizingare provided in SI §S3. We additionallyutilize a bootstrapping approach to evaluate the uncertainty in airquality effect estimates on meteorological normalization; see SI §S3. For most of the randomly selectedtest cases, the baseline effect estimate is generally similar to thosefrom bootstrapping, indicating the robustness of our effect estimates.First, meteorological normalization is applied tocontrol for variables that may violate the continuity assumption of a valid RDD.T0 (threshold), justifyingthe use of sharp RDD. Particularly, a normalized concentration timeseries is considered to have responded to the lockdown if it has detectedchange point(s) that lie within a short period around T0, referred to as the “margin period” (MP).The MP is specified based on an analysis of the timing of responsefor different air pollutants (SI §S7). Moreover, CPD results are also used to support the research periodspecification of the RDD models. To mitigate influences from unobservableconfounders and unrelated interventions, the normalized concentrationtime series are segmented by the detected change points, and onlythe data in the segments near T0 are usedto estimate the RDD model. Detailed discussions on the CPD methodand research period of RDD models are in SI §S4 and §S6, respectively.Second, CPD is conducted to detect structural changes in the normalizedconcentration time series. Structural changes are identified as achange in the slope of the linear trend or an abrupt discontinuityin normalized concentrations. The detected change points are usedto test the discontinuity in the normalized concentration (outcome)time series around 30 withfurther details in SI §S5. The modelis based on a trend function approximation and quantifies the causaleffect at the discontinuity of a trendline either side of T0, making it less vulnerable to random noiseand unrelated events.30 Moreover, to accountfor any anticipation, adaptation, or delay in response around T0, the model is specified as a “donut”RDD, where the data within a short period around T0 (“donut hole”) are excluded from the RDDmodel estimation. For simplicity, the donut hole is specified as thesame as MP. A summary of the key dates used in our study is providedin SI §S2. The interaction among differentsteps of this method is also illustrated in SI §S2.Finally, a sharp RDD modelis specified on the daily average normalizedconcentrations where a monitoring site showed a response. The modelspecification follows Ma et al.SI §S5. By using the natural logarithm transformation of the outcome variableas the dependent variable, τ can be interpreted as the percentagechange in daily average concentration caused by the lockdown.39 The interval estimates of τ are providedwith a Monte Carlo simulation in Ma et al.39 to account for the uncertainty in estimating model coefficients.The statistical significance of τ at the 10%, 5%, and 1% levelsis, respectively, determined if the corresponding confidence interval(CI) does not contain zero. This paper mainly discusses the statisticalsignificance of τ at the 10% level.The derivation of the lockdown effect, τ,is based on theestimated coefficients of the RDD model, which incorporates the impactfrom the current daily period and those from previous daily periods; see 39 to aggregate the effect estimates for each airpollutant across different monitoring sites to assess the overallair quality effects of the lockdown in London. We distinguish betweenroadside and background sites during the aggregation and further presentresults for the aggregation of only those sites that showed a responseto the lockdown.Furthermore, we usea bootstrapping approach in Ma et al.To provide insight forfuture public policies, we identify the important contributing factorsto the magnitude of lockdown impact at different locations with anexplainable ML.2 in2020 that can be attributed to the lockdown. We particularly focuson the reductions in background concentrations, as they are more representativeof general public exposure compared to roadside concentrations.46 The European Union has established a limit valuefor annual average NO2 concentrations, which the memberstates should not exceed, and this limit value has been transposedinto UK legislation.49 Although substantiallyreduced, the number of people in London living in areas exceedingthe annual average legal limit for NO2 was still 119,000in 2019.50 We note that ground-level O3 and PM2.5 also have noticeable adverse effectson human health.51 However, the sites thathad measurements for these pollutants are relatively limited and spatiallysparse compared with NO2, making it difficult to conducta robust feature evaluation using a ML approach. Therefore, thesepollutants are not included in further analysis. Moreover, our resultsshow that concentrations of O3 and PM2.5 wereless affected by the lockdown compared with NO2.In this paper, we focus on the changes in long-termaverage  background concentrations of NO2 concentrations in 2020 at individual monitoringsites are estimated using observed concentrations for the with-lockdownscenario and counterfactual concentrations for the without-lockdownscenario. The counterfactual concentrations after T0 are scaled from the observed concentrations with theeffect estimate τ̂. For the sites that showed a responseto the lockdown, τ̂ uses the central estimate of the intervalestimate of τ with the statistically insignificant τ̂(at the 10% level) adjusted to zero; for the sites that showed noresponse, set τ̂ = 0. We denote Y̅sobs and Y̅scounter as the annualaverage NO2 concentration at site s withand without the lockdown, respectively. We denote φs = Y̅sobs − Y̅scounter and φs%, = (Y̅sobs – Y̅scounter)/Y̅scounter as the corresponding lockdown impact in absolute and relative terms,respectively.The annualaverage NOφs} and {φs%,} to the 1 × 1 km grids, which arethen averaged to the MSOA level. The mapping method mainly followsHorálek et al.53 Ultimately, it combines a linearregression and ordinary kriging of the residuals from the linear regression. Further discussions on the mappingmethod and mapping results are listed in SI §S8 and §S9, respectively.To estimate the lockdown impactsat individual MSOAs, a mapping method is applied to separately interpolate{38 In this paper, we build a gradient boostingdecision trees (GBDT) model on the estimated pollution reductionsin annual average NO2 concentrations attributable to thelockdown at different MSOAs, separately for absolute and relativereductions. Each GBDT model includes 124 features, covering variousaspects of specific MSOAs . The GBDT model training and hyperparameter tuning are discussedin SI §S10.Tree-based ML modelsare typical ensemble methods for feature importance evaluation andhave been applied in air quality analysis.54 However, the value of feature importance providedby these metrics does not directly indicate how the magnitude of themodel output variable is affected, which is also of great interestto policymakers. To address this question, we use the SHAP values to interpret our GBDT models.For comparison, we also provide the results for measuring featureimportance with the total gains of splits that use the feature. Thetop features selected by using total gains are generally consistentwith those identified by using SHAP values (see SI §S10).Some widely usedfeature importance metrics for a tree-based model, such as total gainsand total splits, either rely on the frequency of usage in the modelor focus on the contribution of a particular feature to error reduction.55 This method can also be classified as an additive feature attribution method for a local explanationof complex predictive models,40 where theinput features act as the players and the output prediction as thetotal payoff. Specifically, an additive feature attribution methodis characterized by assigning a contribution ϕi to each feature, with the sum of {ϕi} approximating theoriginal model prediction.40 Therefore, ϕi is in the same unitas the model’s output and, consequently, can provide a betterinterpretation compared with the use of total gains. Moreover, severalmethods for interpreting complex ML models have been recently developed,58 and many of them also fall into the class of additive feature attributionmethods.40 Previous studies have shownthat Shapley values have advantages over the other methods of thisclass, as they can provide a single unique solution to the problemof assigning contributions with desirable properties.41The Shapley value is a key solution methodin cooperative gametheory to allocate the total payoff generated by a coalition of playersto individual players according to their contributions.41 we use an efficient algorithm in the SHAP library41 in python to approximate theShapley values, and the results are called “SHAP values”hereafter. Notably, {ϕi} is a local explanation of the GBDT model, meaning that itis unique to a single instance x in the model .41 Therefore, we additionally estimate theglobal importance of a particular feature by the mean absolute SHAPvalue across all MSOAs.54 Further discussionson the Shapley values, the algorithm for computing SHAP values, andan illustrative interpretation of SHAP values are included in SI §S10.As estimating Shapley values is computationally expensive,2 pollution in London comes from road transport.50 Following a dramatic decrease in road trafficled by travel restrictions, an abrupt decrease in NO2 concentrationswas clearly observable in London around the start of the lockdown,at both the roadside and background monitoring sites (SI §S11), we find that the median of the concentrationchanges that occurred around the start of the lockdown was greaterthan the 90th percentile of changes observed at other times since2016.Around 50%of NOng sites 1. ExaminSI §S12. Our results indicate that 92% ofthe monitoring sites  within Londonshowed a response in NO2 concentrations to the lockdown.The lockdown changed the daily average background NO2 concentrationsby −7%  on average, rangingfrom −23% to 0% at different sites, and roadside NO2 concentrations by −12%  on average,ranging from −50% to −2%.To further isolate the changes in air pollutionattributable tothe lockdown, we specify a sharp RDD model at individual monitoringsites, and the results are summarized across London in 2, at theroadside, the lockdown caused a higher average reduction (12%) andaffected a higher proportion of monitoring sites (100%) . The difference in response between monitoring locationslikely reflects how lockdown affected different activities: whileroadside concentrations are mainly affected by transport emissions,background concentrations can be affected by various sectors, suchas domestic heating, transport, industry, and energy supply.46 During the first UK national lockdown, mobilityrestrictions dramatically reduced London’s road traffic; however,activities in some other sectors in London were less affected (suchas power generation) or even increased .59Compared with backgroundconcentrations of NO2 concentrations at all roadside sites, yet the magnitudeofthe reduction was spatially heterogeneous  was observed in centralLondon, and all of the roadside sites within central London showeda pollution decrease of greater than 10%. However, across the restof London, 50% of the roadside sites showed a smaller pollution reductionof less than 10%. The spatial heterogeneity shown in the impact estimatesfor the roadside sites is generally consistent with the variationin road traffic reduction among different regions in London. Comparedwith inner and outer London, road traffic in central London experienceda higher initial reduction (64%) in the first week following the lockdown(inner and outer London: ∼50%) and showed a slower subsequentrecovery.8The lockdown consistently caused a significant reduction inNOogeneous 2. The hi2 concentrations was in outer London, yet road traffic in outerLondon was generally less affected during the lockdown compared tocentral London;8 this reemphasizes thatreductions in background concentrations of NO2 were notsolely driven by changes in road traffic. Further discussions on theresults for NO2 in central, inner, and outer London areprovided in SI §S12.The response at background locations was similarlyspatially heterogeneous.While the lockdown caused a large pollution reduction at some locations,the majority (∼70%) of background sites in London showed onlya small pollution reduction (<10%) or null response. Moreover,the highest reduction in background NOx and 22% for particulate matter (PM) in 2020 compared with2019.60 However, our results show thatthe relative change in London’s air pollution caused by thelockdown ranged from −62% to 0% for NOx, from 0% to 4% for O3, and from −5% to +0%for PM10, and there was no response for PM2.5. The negative correlation in the direction of changes in O3 (increase) and NO2 and NOx (decrease) is consistent with theory and observations;61 effect estimates where these three pollutantsare simultaneously measured are summarized in SI §S14. Aggregating the effects across London, the lockdownreduced NOx concentrations by 11% at roadsidesites and 6% at background sites on average and had an insignificanteffect on the concentrations of O3, PM10, andPM2.5 concentrations. Unlike NO2 and NOx, the regional contribution to PM and O3 is substantial;61 more than half of thePM2.5 concentrations in London are from regional sourcesoutside London.63 Our results imply that reducing transport activities and restrictingexhaust emissions are not sufficient to tackle the challenges in reducingconcentrations of air pollutants that are largely affected by regionalemission sources. Further analysis of the changes in mean concentrationsof NOx, O3, and PM at differentperiods since 2016 is provided in SI §S11, and further discussions on the estimated causal effects for thesepollutants at different locations are in SI §S13, §S14, and §S15, respectively.Followingthe changes in road traffic, the UK reported an overallemission reduction in road transport of 25% for NO2 concentrations yet less significant changes in otherregulated pollutants . However, our impact estimates are not as large as those of Jephcoteet al.,15 who reported average reductionsof 38% and 17% respectively in NO2 and PM2.5 concentrations and an average increase in O3 concentrationsof 8% across 129 monitoring sites in the UK during the first nationallockdown. The impact estimates from Jephcote et al.15 were derived by comparing the air quality observationsbetween the lockdown period and the same period in previous years.However, this approach may be biased by differing meteorological conditionsand long-term trends in air quality. In particular, air quality inthe UK (both NO2 and PM) has improved year on year in mostmajor cities, including London.49 Therefore, the approachused in several studies to estimate the lockdown impacts in the UKby comparing air pollution levels across different years64 is likely to overestimate theair quality impacts attributable to the lockdown.Our estimatedair quality impacts of the lockdown are generallyconsistent with previous studies in that we find more marked reductionsin NO65 reportedabrupt but smaller than expected changes in air quality attributableto the COVID-19 lockdown in 11 cities globally. This is in agreementwith our results. For London, they found that the lockdown changedbackground concentrations of NO2, O3, and PM2.5 by −8 ± 8%, −2 ± 8%, and +11 ±17%, respectively. While our results for NO2 and O3 are similar, the results for PM2.5 differ: wefind no response for PM2.5. Shi et al.65 estimated the lockdown impact by the relative change inair pollution before and after the lockdown in 2020 after subtractingthe relative change over the same period in the average concentrationsacross the previous 4 years. However, their estimated impacts forPM could be biased by PM episodes during their research period, betweenMarch and April in 2016–2020. PM episodes are a regular featurein springtime in Western Europe, when pollution from continental Europeis transported by southeasterly winds.66 Particularly, two PM episodes due to regional pollution transportwere recorded in London in their specified postlockdown period.67 Although Shi et al.65 applied a meteorological normalization to control for weather conditions,this technique does not always sufficiently account for abrupt naturalevents or regional pollution transport.65 Consequently, the pollution increase estimated in Shi et al.65 for PM2.5 may incorporate the influenceof these recorded episodes. In contrast, our study focuses on thetime around the start of the lockdown; particularly, we use changepoint detection to identify the response and subsequently apply asharp RDD to normalized concentrations near the start of the lockdownto estimate the effect, which in combination makes our method lesssusceptible to the influence of pollution episodes.Another studyby Shi et al.23 Both DID and SC require defining treatmentand control groups and pre- and postintervention periods, assumingonly the treatment group in the postintervention period is exposedto the treatment.68 A crucial assumption in bothmethods is the parallel trend assumption, assuming the outcome ofinterest would follow the same trend in the treatment and controlgroups in the absence of the intervention.70 However, due to spatial correlations amongdifferent regions and pollution dispersion, changes in activitiesand pollution may extend beyond the area where the transport interventionis actually implemented.72 Therefore, selecting an appropriate control group for air qualityappraisals using DID or SC can be challenging in practice, particularlyin the case of nationwide COVID-19 lockdowns. In contrast, our researchframework strengthens the justification of the key model assumptionsof sharp RDD through the use of meteorological normalization and changepoint detection. These additional steps improve the validity of ourmethod, resulting in a more reliable estimate of the causal effect.In additionto sharp RDD, difference-in-differences (DID) and syntheticcontrol (SC) are commonly used causal inference approaches to estimatethe air quality effects of COVID-19 lockdowns.Our methodology was designed to overcome existing limitations byenhancingthe confounding control, improving the validity of causal effect estimates,and ensuring internal consistency within the research framework. However,it should be noted that this research framework is intrinsically astochastic process; each component within the research framework mayintroduce uncertainties in the effect estimates. Sources of uncertaintycan include air quality and weather observations, model fitting atdifferent steps, and the meteorological normalization process. Futurework should include a comprehensive quantification of uncertaintiesacross different components within the research framework, in particularthose associated with the meteorological normalization, as its outputis specified as the outcome variable in the sharp RDD model and, consequently,directly influences the magnitude of effect estimates.2 concentrations in Londoncompared with other regulated pollutants included in our study . We now discuss thefactors that contributed to the heterogeneous reductions in NO2 concentrations at different locations. All the factors referto the spatial characteristics before the lockdown, as behavioralresponses to the lockdown are more likely to be constrained by pre-existingconditions of the urban environment.The first UK nationallockdown is estimated to have caused more significant, yet spatiallyheterogeneous, impacts on NOSI §S10 for the absolute pollution reductioncaused by the lockdown. In these figures, feature importance and featureeffect are combined in the local SHAP values: a positive SHAP valueof a feature at an MSOA indicates that this feature contributed toincreasing the pollution reduction at this location, while a negativevalue implies a decrease in pollution reduction associated with thisfeature; the magnitude of SHAP values indicates how much the contributionwas, and they are in the same units as the model output. For example,a value of −2 in decreased the relative pollution reduction by two percentagepoints (pp).The estimated SHAP valuesare summarized in 2 was reducedin an area was mostly correlated with the proportion of heavy goodsvehicles (HGVs) in road traffic before the lockdown, the distanceto LHR, and the distance to the Central Activities Zone (city center)(SI §S10). This finding is generally consistentwith Yang et al.,34 who found the NO2 reduction in Los Angeles during the lockdown was primarilydue to the changes in HGVs’ activities; they also found thedistance to major airports was an important predictor of NO2 concentrations in the city. In addition to feature ranking, ouruse of explainable ML enables us to find that a lower proportion ofHGVs in road traffic and closer proximity to LHR are associated withgreater pollution reductions in most MSOAs; however, different MSOAscan have opposite effects from a short distance to the city center in HGVs and light goods vehiclesin the first week following the lockdown (60% in cars) and a quickersubsequent recovery.8 Our results showthat where HGVs comprised less than 1.6% of vehicle traffic, the relativepollution reduction increased by up to 4.6 pp  for all motor vehicles is also highlightedin our study (SI §S10), which implies thenecessity of managing overall traffic demand in addition to reducingemission factors.HGVs accounted for 3% of London’s on-roadvehicle fleetyet disproportionately contributed 13% of road transport NOo 4.6 pp 4a. Moreoo 4.6 pp 4b, indicSI §S10. Additionally, our results reveal that the existing health inequalitieswithin the city were exacerbated during the lockdown: areas with lower-incomeresidents, which have also been exposed to higher levels of air pollutionbefore the pandemic,76 typically experiencedsmaller NO2 pollution reductions during the lockdown. Areaswith median incomes below the 10th percentile experienced a mean decreasein pollution reduction of 0.6 pp, while those with median incomesabove the 90th percentile experienced a mean increase in pollutionreduction of 0.3 pp . Sites closer to the LHR experienced larger pollutionreductions; a distance less than 5.9 km to the LHR is estimated tohave increased the relative pollution reduction by up to 4.1 pp (79 However, LHR reported asignificant decrease in passenger demand after the lockdown; by ∼97%in April 2020 compared with the same month in 2019.80 Our impact estimates at individual monitoring sites aroundLHR are generally consistent with several previous studies, whichestimated LHR contributed to 4%–31% of NOx concentrations81 and 4%–36%of NO2 concentrations83 in nearbyareas. Notably, our impact estimates are likely a combined effectof emission reductions from both airside activities and on-road trafficassociated with passengers, freight, and supporting services.The COVID-19 pandemic and subsequent lockdownshave also seen adramatic decrease in the global air traffic. Some large improvementsin NOo 4.1 pp 4. As the8 While close proximity to London’s CentralActivities Zone is estimated to enhance the reduction in NO2 in several cases (84 These resultsimply the potential of alleviating air pollution in the city centerby shifting activity to metropolitan centers, however, policymakersshould be mindful of the potential deterioration of air quality withinand around metropolitan centers following the development. We notethat continued remote or hybrid working post-pandemic may13 persisently change mobility patternscompared to pre-pandemic, thereby contributing to a shift in activityaway from the city center.8Furthermore, as most residents were forced to stay close to home,people tended to make shorter and more local trips during the lockdown.al cases 4, the aral cases 3. As shoOur study shows that the unprecedenteddecrease in transport activitiesfollowing the COVID-19 lockdown did not lead to a commensurate reductionin air pollution. The heterogeneous effects observed across air pollutantsand spatial locations suggest that reducing transport activities andrestricting exhaust emissions, such as through remote working andfleet electrification, alone are not sufficient to address the complexitiesof improving air quality, particularly for pollution at backgroundlocations and pollutants that are largely affected by regional emissionsources. Therefore, improving air quality across the city requiresa multifaceted set of policies to control emissions across sectors,with coordination among governments and consideration of existinginequalities. Within the transport sector, sustained efforts are necessarysuch as reducing emissions for freight transport, facilitating andencouraging public transport, and integrating transport planning withland use planning. Meanwhile, proactive actions are necessary to respondto long-term societal trends and to consistently guide cities forhealth and equality.


Morphologically, the left single ventricle showed a higher peakVO2% predicted value . The factors associated with low peakVO2 values were an early flattened or descending O2 pulse at maximal exertion  and chronotropic insufficiency . The OUES was found to be a useful parameter to assess the FC in FPs in maximal and submaximal exercise testing. A strong positive correlation was observed between the %OUES and peakVO2%predicted . The lung function was impaired in the FPs, mostly with a mild restrictive pattern (56.8%). The FPs showed lower inspiratory muscle strength compared to the HCs but it was not statistically associated with either the peakVO2 or VE/VCO2 slope. Regular intense physical activity improves one’s FC. Although FPs have inspiratory muscle weakness, its impact on their FC is unclear. The peakVO2% predicted grew progressively higher as the level of physical activity increased .At rest, a good Fontan circulation can provide a normal cardiac output (CO). However, as a consequence of its unique hemodynamic nature, the limitations of the Fontan circuit are exposed during exercise. We aimed to provide a comprehensive assessment of the pathophysiology of exercise in adult Fontan patients (FPs) and identify factors limiting their functional capacity (FC). In a single-center study conducted in 37 FPs aged ≥16 years and 19 healthy-controls (HCs) who underwent CPET on a cycle ergometer in February and March 2022, the mean peakVO Since the introduction of the Fontan operation 50 years ago, the life expectancy of infants born with complex and functionally univentricular congenital heart disease (CHD) has increased significantly, and most children will survive to adult life . The FonMany other factors might contribute to the impaired exercise capacity in patients with Fontan circulation. Thus, in adults with CHD, the lung volumes are commonly reduced, and the forced vital capacity (FVC) correlates with exercise capacity ,6,7,8 an2), carbon dioxide production (VCO2), and ventilation during a symptom-limited exercise test. CPET provides clinicians and researchers in an integrative and comprehensive assessment of the physiological responses to exercise and cardiorespiratory fitness in this patient population [2 measured by CPET is broadly used to classify functional capacity. In different studies, this parameter is strongly related to the outcome and prognosis [2, it does not rely on the last segment of exercise. However, it has only been used in a small number of studies with young Fontan patients [Cardiopulmonary exercise testing (CPET) is a valuable tool for assessing the exercise capacity and fitness of individuals with Fontan circulation. It involves measurements of oxygen uptake ; (b) arrhythmias in the preceding 6 months prior to inclusion; (c) unstable angina; (d) recent surgery (<12 months) or changes in medication (<6 months), neurological sequelae, cognitive disability, or musculoskeletal problems that prevented us from performing the exercise testing. The presence of valve dysfunction was not considered as an exclusion criterion.All patients aged >16 years who had undergone Fontan palliation and were being followed up at the Adult Congenital Heart Disease Unit in the University Hospital Virgen del Rocio in Seville were identified. Their demographic data, cardiac anatomy, prior therapeutic interventions, complications, diagnostic techniques, and medical treatments were collected from electronic health records and served as the primary data source for this study. Patients with both atriopulmonary and total cavopulmonary connection Fontan circulations, either fenestrated and non-fenestrated, were included. The exclusion criteria were: (a) clinical instability . The HC participants were non-smokers, were not under drug treatment, and did not have a history of cardiovascular or pulmonary disease. All participants were informed about the details of the procedures, including the potential risks, before signing the written informed consent. The local Ethics Committee on Human Research approved the study.All patients and controls completed the International Physical Activity Questionnaire—Short Form. The IPAQ-SF is a well-developed 7-question instrument that addresses the number of days and time spent on physical activity of moderate intensity, vigorous intensity, and walking for at least 10 min duration over the last 7 days, and includes the time spent sitting on weekdays over the last 7 days .The forced vital capacity (FVC), forced expiratory volume in one second (FEV1), and FEV1/FVC ratio were assessed according to the recommendations of the American Thoracic Society and European Respiratory Society  and the Maximal static inspiratory pressure (MIP): During testing, the participants were sitting upright. Both the patients and controls were instructed to exhale slowly and completely, seal their lips firmly around the mouthpiece, and then inhale through the mouth as hard and fast as possible, with the nostrils occluded with a clamp. Ideally, the inspiratory pressure was held for 1.5 s so that the maximum pressure sustained for 1 s was recorded. The maximum value of three inspiratory maneuvers that varied by less than 10% were recorded . The refMaximal sniff nasal inspiratory pressure (SNIP): The inspiratory pressure was recorded by a pressure transducer connected to a catheter inserted into the nostril. This maneuver consists of sniffing quickly and deeply, generally from the functional residual capacity, then measuring the pressure generated. The duration of the sniff should be <500 ms. The maneuver was repeated 10 times, taking the highest value reached . ReferenMaximal exercise testing was performed using a standardized ramp protocol on an electronically braked cycle ergometer. The participants were submitted to individualized ramp protocols with increments of 5 or 10 watts per minute in Fontan patients and 15 or 20 W/min in healthy controls.The participants pedaled in an unloaded state for three minutes and the workload was then increased continuously with a slope chosen to achieve each participant’s predicted maximal work rate after 10 to 12 min of cycling. Metabolic measurements were assessed on a breath-by-breath basis throughout the exercise . A 12-lead electrocardiogram was recorded throughout the exercise test. The blood pressure was measured at rest, every 2 min during exercise, and every minute throughout recovery.2) was determined by the mean of the last 20–30 s of maximal effort. The predicted maximal VO2 was calculated by using the Hansen–Wasserman equation [2 production (VCO2) and O2 consumption (VO2) disappears. The VE/VCO2 slope was determined until the onset of the respiratory compensation point. The predicted maximum heart rate (HR) was obtained from the 220-age difference. The chronotropic index was calculated by maximal HR-rest HR/(220-age)-rest HR. The oxygen pulse is the VO2/HR ratio. The oxygen uptake efficiency slope (OUES) is the slope between the VO2 and the logarithmic transformation of ventilation: (VO2/log10 VE) − k. The predicted OUES values were obtained using the equation used by Buys et al. [The maximal effort was defined as achieving a respiratory exchange ratio (RER) equal to or greater than 1.10. The CPET was terminated by the patient in cases of discomfort or by the supervising physician in cases of ECG changes, an excessive breathing pattern, or for other reasons. However, the maximal exercise test parameters were calculated only in patients who achieved RER > 1.1. The peak oxygen uptake  with a mean age of 26.5 ± 6.25 years (range 16–41 years) and 19 healthy controls (68.5% men) with a mean age of 26.1 ± 6.8 years were recruited. There were no differences in age, gender, or body mass index (BMI) between the groups. The baseline characteristics of the Fontan patients are displayed in The FVC and FEV1 were significantly lower in Fontan patients compared to their healthy peers. No differences were observed in the FEV1/FVC ratio between both groups. Twenty-one Fontan patients (56.8%) showed a mildly restrictive pattern, six (16.2%) showed a moderate restrictive pattern, and ten (27%) had normal lung function. None of the patients had a severe restrictive or obstructive pattern .p = 0.047). We did not find a statistically significant association between a reduced FVC and lower peakVO2 (p = 0.598) or ventilatory efficiency parameters (p = 0.545).The patients with a history of lateral thoracotomy showed a lower FVC , up to 8% of the Fontan patients did not achieve a maximal exercise effort (RER < 1.10). 2 was 21 ± 5.4 mL/kg/min, an average of 55% of the predicted peakVO2 (peakVO2% predicted). The anaerobic threshold (AT) occurred at 32 ± 8% of the predicted peakVO2 (early AT). Although there were no differences between healthy subjects and Fontan patients with regard to age, weight, and height, an examination of the peakVO2 results revealed 36.6% lower values for the patients than controls, with a mean peakVO2% predicted difference of 32 ± 3.8 (p < 0.001). The patients with a morphologically left single ventricle showed higher peakVO2% predicted values compared to those with a morphologically right ventricle . We found no statistically significant differences in either peak oxygen uptake or VO2 at the anaerobic threshold between the different degrees of AV valve insufficiency.The mean peakVO2 pulse was low, with a mean of 65.7 ± 13.8% of the predicted O2 pulse. As for the oxygen pulse kinetics, 51.4% showed an ascending slope and 48.6% showed early flattening after reaching the AT. Furthermore, in 24.3% of the total cohort (9 patients), we observed a descending O2 pulse slope at maximal exertion. The patients with an early flattened O2 pulse or a descending pulse at maximal exertion had a lower peakVO2% predicted values .The O2% predicted values . The chronotropic index , % of maximum predicted HR , and HR reserve  showed statistically significant correlations with the peakVO2% predicted values. Finally, the Fontan patients had higher values for ventilatory efficiency parameters compared to their healthy peers . A strong positive correlation was observed between the %OUES and peakVO2% predicted values  and between the indexed OUES/kg and indexed peakVO2 (mL/kg/min) . The OUES also correlated with submaximal parameters: OUES-VO2 at the anaerobic threshold (AT) r = 0.608, p = 0.000. A negative correlation was seen between the OUES and VE/VCO2 slope .The mean OUES was 1600 ± 351, a mean of 54% of the predicted OUES (%OUES). A moderate positive correlation was observed between the absolute OUES and absolute peakVOn = 22), while 27% of the cohort (n = 10) had a sedentary life and only 13.5% (5 patients) had a high level of physical activity. Among the healthy controls, the physical activity levels according to the IPAQ questionnaire were as follows: low in 7 subjects (37%), moderate in 8 subjects (42%), and high in 4 subjects (21%). No differences were observed between the groups . Although there were differences between the three levels of physical activity, the sample size only allowed us to obtain statistically significant differences between low- and high-intensity activity , low-moderate physical activity = 5.5 ± 5.2%, (p = 0.545), and moderate-intense = 13.8 ± 6.8% (p = 0.121)). We observed the same pattern of increasing peak oxygen uptake within the different physical activity levels in both the FPs and HCs, as displayed in The peakVO2 greater than 80% of the predicted value, which has been previously dubbed as the “super Fontan”, with the following characteristics: VO2 at AT = 49.8 ± 3%, %OUES = 77.8 ± 7%, O2 pulse = 91.5 ± 0.7%, peak predicted load = 120 ± 4%, %FCMP = 98 ± 1.2%, chronotropic index = 0.9 ± 0.04, with statistically significant differences from the rest of the cohort. Both patients had a morphologically left single ventricle and performed regular intense physical activity.Two patients from the total cohort showed a peakVO2 or VO2 at AT. No significant correlation was observed between the MIP (p = 0.482) or SNIP (p = 0.570) and VE/VCO2 slope or lung function parameters.The SNIP and MIP characteristics are displayed in In this study, we provide insights into the exercise physiology response, aerobic functional capacity, and factors limiting physical effort in adult patients with Fontan circulation using CPET. Importantly, we demonstrate that the OUES is a submaximal parameter that can be used in Fontan patients, whether or not they achieve a maximal exercise effort. This cohort of patients may also present abnormal lung volumes and inspiratory muscle weakness. Lastly, we demonstrate a correlation between physical activity and exercise capacity in Fontan patients.2 is an established and reliable measure widely used to assess the exercise intolerance of patients with CHD. As our group has previously published [2 is higher on a treadmill than on a cycle ergometer in patients with Fontan circulation (up to 23.8% higher on the treadmill), and this difference in exercise modality should also be taken into account in the assessment of the functional capacity of this population group. Since exercise on a cycle ergometer is less prone to induce noise artifacts in ECG and blood pressure monitoring, with better quantification of the load achieved and more accurate calculation of the parameters derived from it, and as it is less intimidating for people unaccustomed with a moving treadmill, in this study we chose a cycle ergometer as the testing modality. Consistent with previous studies [2 of 21 mL/kg/min, which on average was 55% of what would be predicted for the general population according to the Hansen–Wasserman equation. Importantly, the distribution of the levels of physical activity was similar in the Fontan patients and controls. Given the significance of the differences between CPET variables in Fontan patients and healthy controls, this needs to be highlighted, especially since inactivity in the general population means that many healthy controls might not perform at the predicted levels either. Furthermore, while a reduced peakVO2 is commonly observed, there is a subset of Fontan patients who exhibit normal or even supranormal peakVO2. Lastly, our study shows that the Fontan patients with a morphologically left single ventricle performed better under CPET. Although it could be hypothesized that the right ventricle is not intended to withstand the physiological pressure and workload required of the systemic ventricle, and conflicting evidence exists on the prognostic significance of the SRV versus SLV after a Fontan operation, a recently published single-center retrospective study suggested that a dominant single ventricle morphology may not be associated with an appreciable difference in exercise performance in adult survivors with a Fontan palliation [To maintain cardiac output (CO), the Fontan circulation relies on venous pressure to passively drive systemic venous blood through the pulmonary vascular bed to the pulmonary venous atrium, given the absence of a subpulmonary ventricular pump. This intrinsically limits the ability to boost systemic ventricular preload, which leads to a very high prevalence of impaired maximal aerobic exercise capacity ,33,34. Aublished , the pea studies ,20,21,36lliation ,38. The 2, O2 pulse, chronotropic incompetence) are helpful in the evaluation of Fontan patients. However, one of its major strengths is that it focuses on the OUES as a surrogate marker for the peakVO2 obtained at an RER of 1.1.Our cross-sectional study reinforces the notion that several CPET parameters . This makes the OUES a dimensionless and submaximal parameter of the functional capacity. In addition, the OUES can also be normalized by body weight or body surface area to correct for differences in anthropometrics between patients. In our Fontan cohort, the mean OUES was 1600 ± 351, about 54% of the predicted OUES. Although higher %OUES results of up to 79% of the predicted values have been reported in a pediatric age group [2% predicted and between the OUES/kg and indexed peakVO2 (mL/kg/min), as previously demonstrated by Terol et al. in a pediatric Fontan cohort at a median age of 11 years [2 at AT). Typically, clinical trials and observational studies often use the peakVO2 as the primary outcome measure. However, some investigators have proposed using submaximal parameters such as the VO2 at AT in Fontan patients as outcome measures instead. Submaximal exertion may be more representative of daily activities, and by the time they have reached peak exercise, the central venous pressure in Fontan patients has hit a physiological limit and may not be amenable to improvement. Moreover, in Fontan patients who are unable to perform a maximal effort, a lower VO2 at anaerobic threshold (AT) has been associated with a greater risk of death or transplant, and one study identified a cutoff value of <9 mL/kg/min as being associated with increased mortality. Although in other studies higher percentages of submaximal effort have been described (up to 20% do not reach the maximum effort) [2 should be interpreted with caution, and the VO2 at AT needs to be used to assess the functional capacity and prognosis. Unfortunately, identifying the anaerobic threshold may be associated with substantial error and uncertainty. In this study, the OUES was used as a submaximal and effort-independent parameter as it is easier to determine than the anaerobic threshold and unlike the peakVO2 does not rely on the last segment of the exercise. Instead, it uses all of the exercise data, even if they are submaximal, which can be an advantage in patients who do not tolerate maximal exertion, particularly Fontan patients with a worse functional class, PLE, or low motivation to finish the test.When the minute ventilation (VE) over the entire exercise duration is logarithmically transformed and plotted against the VOge group , the meage group . The str11 years , althoug effort) , in our 2 are not necessarily interchangeable parameters. However, the OUES is not meant to predict the maximal exercise parameters; it provides an objective and independent measure of the cardiorespiratory function and it seems to be a useful submaximal alternative in Fontan patients unable to perform maximal exercise.In certain patient groups, however, the OUES values must be interpreted with caution. Firstly, Giardini et al.  observedIn our series, the patients with Fontan circulation had a lower oxygen pulse, with a mean of 66% of the predicted value, suggesting a stroke volume limitation. Furthermore, in half of the cohort, the rise in the oxygen pulse reached a plateau much earlier at the AT and then flattened.2 pulse curve in the CPET reflects a cardiac limitation to increase the stroke volume during exercise or a peripheral limitation of the O2 extraction in the skeletal muscles. It is noteworthy that the stroke volume also represents the amount of ventricular filling during diastole and may, therefore, be limited by diastolic factors.The oxygen pulse is the product of the stroke volume and arteriovenous oxygen difference during exercise. It represents the oxygen consumption per heartbeat and is considered a surrogate of the stroke volume in the absence of anemia or severe hypoxemia. During the initial and intermediate phases of exercise, the stroke volume has a higher relative contribution to the cardiac output, although at a certain point it stops increasing and reaches a plateau. At low exercise loads, the cardiac output increases due to an increase in stroke volume and HR. At higher loads, the stroke volume no longer increases and the rise in cardiac output is due to an increase in heart rate. Thus, the early flattening or decreasing O2 pulse slope or a downward displacement at peak exercise in our series was associated with lower O2 consumption. This was likely due to the Fontan circulation’s inability to increase the pulmonary blood flow and ventricle preload during exercise, and as a consequence a limited capacity to increase the stroke volume with exertion [In line with the study by Bansal et al. , early fexertion ,44,45,46Chronotropic insufficiency is common in patients with Fontan circulation (up to 85% in our study) and has been associated with exercise limitations . However2 than in the healthy subjects. They also showed that the stroke volume (SV) decreased during exercise in the Fontan patients, whereas the controls showed an increase in SV during exercise. The clinical implications of these findings would be that medications resulting in relative bradycardia during exercise may lead to improved exercise capacity because of enhanced diastolic filling, whereas chronotropic medications or pacing would be expected to have negative effects.In Fontan patients, it has been shown that the sinus node may be dysfunctional, either congenitally or by damage caused by multiple surgeries . Thus, sinus node dysfunction is common and chronotropic incompetence has been associated with exercise limitations in this patient population. However, since there is no optimal definition for chronotropic incompetence, identifying patients in whom exercise limitations are causally related to chronotropic incompetence and who would, therefore, benefit from pacing remains a challenge. Previous studies have used the term “chronotropic incompetence” when the peak exercise HR failed to reach a lower arbitrary percentage  of the age-predicted maximal HR. Nevertheless, it does not necessarily mean that a reduced peak heart rate during exercise is directly responsible for exercise intolerance. Other parameters such as inadequate effort, residual cardiac shunting, inadequate systemic ventricular filling, or inappropriate ventricular contraction also modulate the exercise capacity and peak heart rate. Consistent with this, in our series the HR reserve (HRR) was lower in Fontan patients as compared with controls, even though up to 92% of the patients did achieve a maximal effort. Thus, Claessen et al.  demonstr2 predicted as the physical activity level (as determined by the IPAQ questionnaire) increased in both the FPs and HCs. Although there were differences in peakVO2 between the three levels of physical activity, a statistically significant difference was only observed between the low and high intensity levels  and 0.409 for FVC (p = 0.022) and Callegari et al. [2% predicted . Moreover, Alonso-Gonzalez et al. [Overall, the Fontan patients in our series showed smaller lung volumes compared to the healthy controls. Seventy-three percent of the patients presented with a restrictive pattern during spirometry and having a previous lateral thoracotomy was significantly associated with impaired lung function. However, in contrast to prior studies, we did not observe an association between a reduced FVC and lower peakVOs et al.  observedi et al.  found th2 ; FEV1 ) in a cohort of Fontan patients, with prevalence rates of moderate restriction of up to 44%. Although an insufficient sample size to demonstrate significant differences may be the cause, since in our series the majority of patients had only a mild restrictive pattern, the low prevalence of moderate restrictive disease (only 16.2%) can also explain this discrepancy.In line with this, Turquetto et al.  found a 2, it appears that the skeletal muscle and ventilatory pumps account importantly for the increase in cardiac output during submaximal exercise in patients with Fontan circulation. It has been previously reported that patients with CHD often have an abnormal body composition [2  in a subgroup of 11 Fontan patients, we found no correlation between the MIP and peakVO2, nor could it be demonstrated by Turquetto et al. [Having abnormal lung mechanics also impairs the negative intrathoracic pressure required to “pull” blood through the Fontan circulation . In thisposition ,11. Compposition  found a o et al. . FurtherWe must acknowledge several limitations. The small sample size of the population study reduces the robustness of the results. However, the sample was homogeneous in terms of age, and despite the small number there was a significant difference between the patients and healthy controls. It is noteworthy that in patients with congenital heart disease, the IPAQ tends to overestimate and physical activity level . Limitat2. However, our study did not specifically address the ventricular function or hemodynamic abnormalities and their potential contributions to exercise intolerance. Finally, a follow-up study may allow for us to identify the prognostic value of the CPET parameters and inspiratory muscle function in the outcome of Fontan patients.Data on static lung volumes measured by plethysmography were not available for the scope of this study. However, forced expiratory and inspiratory lung flows in ACHD patients were recorded by trained physicians following the American Thoracic Society guidelines. Another potential limitation is the much higher proportion of patients with left single ventricle morphology included in our study. Together with the small sample size, this limits the ability to account for confounding variables such as age, the ejection fraction, or the atrioventricular valvular function. The assessment of cardiac function during exercise may have shown stronger correlations with peakVO2. Chronotropic insufficiency and an early flattened or descending oxygen pulse slope is associated with lower peakVO2, whereas left ventricular morphology associates with better functional capacity. Those patients who perform regular intense physical activity are associated higher exercise capacity, highlighting the importance of regular exercise training. Although patients with Fontan circulation have inspiratory muscle weakness, its impact on their functional capacity is unclear.Patients with Fontan circulation have an impaired exercise capacity. The OUES is a useful parameter of functional capacity in both patients who fail or not to reach maximal exertion, showing a strong positive correlation with the peakVO