This paper presents a new approach for the automatic detection of galaxy morphology from datasets based on an image-retrieval approach. Currently, there are several classification methods proposed to detect galaxy types within an image. However, in some situations, the aim is not only to determine the type of galaxy within the queried image, but also to determine the most similar images for query image. Therefore, this paper proposes an image-retrieval method to detect the type of galaxies within an image and return with the most similar image. The proposed method consists of two stages, in the first stage, a set of features is extracted based on shape, color and texture descriptors, then a binary sine cosine algorithm selects the most relevant features. In the second stage, the similarity between the features of the queried galaxy image and the features of other galaxy images is computed. Our experiments were performed using the EFIGI catalogue, which contains about 5000 galaxies images with different types . We demonstrate that our proposed approach has better performance compared with the particle swarm optimization (PSO) and genetic algorithm (GA) methods. In turn, galaxy morphology can be used to provide an independent test of the two proposed scenarios for galaxy formation. Elliptical galaxies, for example, are believed to be formed through major mergers2, whereas disk-dominated galaxies cannot have undergone recent major mergers, as such mergers would have severely disrupted their shape3. Thus, the class of quenching models is sufficient to explain the full range of morphological types observed for quenched galaxies. For example, bars can be found in all types of disk galaxies, from the earliest to the latest stages of the Hubble sequence. Barred galaxies constitute a major fraction of all disk galaxies. A small number of galaxies that appear unbarred at visual wavelengths have actually been found to be barred when observed in the near infra-red. The three clearest cases are NGC 15664, NGC 10686 and NGC 3097. De Zeeuw and Franx8 surveyed the literature for the dynamics of these objects. We are still far from a complete understanding of the dynamical structure of galaxies. Here, we will be able to do no more than scratch the surface of the majority of these problems.Astronomy has become an immensely data-rich field. For example, the Sloan Digital Sky Survey (SDSS) will produce more than 50,000,000 images of galaxies in the near future10. In ref. HST/WFC3 image containing 1639 galaxies, which identified disturbed morphologies using multimode, intensity and deviation statistics. Additionally12, proposed a method that consists of two stages: first, feature extraction  of galaxy images from the SDSS DR7 spectroscopic sample, followed by the classification of these features using a support vector machine.The development of galaxy morphological schemes can be used to successfully determine galaxy morphology via classification or image-retrieval methods. For example, the Deep Neural Network (DNN) algorithm has been used to classify the Galaxy Zoo  approach is one of the most commonly used image retrieval methods15, which aims to avoid the use of textual descriptions and instead retrieves images based on similarities in their content. Relevant content can be information related to image patterns, colors, textures, shape and location16.The image-retrieval method is a computer system for browsing, searching, detecting and retrieving images from a large database of digital imagesSuch image content is obtained by using feature-extraction methods, which is then saved in a database. To answer a queried image, the similarity between stored features and the features of a queried image (extracted using the same method) is computed and used to determine the closest between the images. However, the CBIR approach is a challenging problem for galaxy images, because there is a large number of galaxy images and determining the most relevant images from a large database becomes a non-trivial task.18. Next, ref. Several methods have been applied to improve the quality of CBIR for galaxy images. Ref. K-NN classifier as measure of the quality of the features which selected by Sine Cosine algorithm (SCA).In general, the previous methods consider either the shape, the texture features or the color, or both of them , but not all of them. Moreover, not all of the extracted features are important: some may be redundant/irrelevant, which in turn reduce the quality of the classification or image-retrieval results. To address this, the aim of this paper is to introduce a new machine-learning approach for the retrieval of galaxy images. Our approach avoids the limitations of previous methods by extracting the shape, color and texture features from galaxy images, and then determining the most relevant features and ignoring other features by using the 20 that selects the most relevant features using the classification accuracy as a fitness function. In the second stage, similar images to the queried image are returned by using the Euclidean distance as a measure.The proposed approach consists of two stages: training and image retrieval. In the training stage there are two steps: the first is feature extraction, where the color, shape and texture features are extracted from a dataset of galaxy images. The second step is feature selection, which is performed based on the modified sine cosine algorithm15.In this section, visual features such as color, texture and shape are introduced21. Therefore, the aim of any color feature extraction method is to represent the main colors of the image content  and then use these color features to describe the image and distinguish it from other images. RGB colors used in this study were obtained by converting from the SDSS color system using the Maxim DL astronomical software22.The color of an image is one of the most widely used features in image retrieval and several other image-processing applications. It is a very important feature since it is invariant with respect to scaling, translation and rotation34, which denotes the joint probability of the intensity of an image. From probability theory, a probability distribution can be uniquely characterized by its moments. Thus, if we interpret the color distribution of an image as a probability distribution, moments can be used to characterize the color distribution. The moments of the color distribution are the features extracted from the images; if we denote the value of the ith color channel at the jth image pixel as Pij, then the color moments can be defined as refs The first-order moment (the mean):The second-order moment (the standard deviation):The third-order moment (skewedness):The color histogram is one of the most well-known color features used for image feature extraction25. Textures can be rough or smooth, vertical or horizontal. Generally, they capture patterns in the image data, such as repetitiveness and granularity.The texture descriptor is an important feature that provides properties such as smoothness, coarseness and regularity27. The Gray Level Co-Occurrence Matrix (GLCM) and Color Co-Occurrence Matrix (CCM) are the most commonly used statistical approaches used to extract the texture of an image28. These features include the contrast, correlation, entropy, energy and homogeneity, which are defined as:The contrast represents the amount of local variation in an image. This concept refers to pixel variance, and it is defined as:The correlation represents the relation between pixels in an image, which determines the linear dependency between two pixels and is defined as:En) represents the textural uniformity, where large values of En indicate a completely homogeneous image.The energy (ET) measures the randomness of the intensity distribution. It is inversely correlated to En, and is defined as:The entropy (H) is used to measure the closeness of the distribution, where large values H indicate that the image contrast is low. The definition of H is given in the following equation:The homogeneity , the discrete Fourier transform (DFT), discrete wavelet transform (DWT) and the Gabor filterz(i) be an ordered sequence that represents the Euclidean distance between the centroid and all N boundary pixels of the object. The rth contour sequence moment mr14 is defined as:Shape features were extracted by using the contour moments defined mathematically as follows. Let 20, this algorithms is a new meta-heuristic algorithm which used either the sine or cosine function to search about the best solution. Consider the current solution Xi, 20:20:r1, r2, r3 and r4 are random variables, P is the best solution, and |·| represents the absolute value20.In this section, the sine cosine algorithm (SCA) is illustratedr2 parameter defines the direction of Xi , while r3 gives random weights to P in order to stochastically emphasize (r3 > 1) or deemphasize (r3 < 1) its influence when defining the distance. Next, r4 is responsible for switching between the sine and cosine functions in equation , which could be either in the space between Xi and P or outside of this space, and it is also responsible for balancing between the exploration and exploitation to improve the convergence performance by updating its value as ref. t is the current iteration, tmax is the maximum number of iterations, and a is a constant. Figure Following ref. equation  20. Finaze r3 >  or deempmentclasspt{minimaIn this section, we investigate a new approach to galaxy image retrieval as illustrated in Algorithm 1. Our proposed approach consists of two stages: a training stage and the galaxy image retrieval stage.I, which are combined into a feature vector FVI, where I is the current image. The next step in the training stage is to reduce the size of FV through using the Binary SCA (BSCA) algorithm (see Algorithm 2) to select the most relevant features. This process is performed by maximizing the accuracy of the K-NN classifier, which is used as a fitness function.In the first stage, the input is the dataset of galaxy images. Then the shape, texture and color features are extracted for each galaxy image popsize, and the output is the best solution P that points to the selected features (SelFeat). The solution in the population of the BSCA algorithm is represented as a binary vector by using the sigmoid function which transforms a real number into a binary number as:Xi is the current solution .The BSCA starts by generating a random population of size NC is the number of correctly predicted samples, and NI represents the total number of images. The dataset is divided by using a 10-fold cross validation (CV), and then the K-NN algorithm predicts, using the label of the testing set, where the output from 10-fold CV is the average of accuracy through 10 runs.After the solutions are converted to binary vectors, the fitness function is computed for each solution. The fitness function is defined according to the classification accuracy rate as:Xi is updated using equations   Xi is uFQ, and then the same features corresponding to SelFeat are selected. Then the Euclidian distance is used to compute the similarity between FQ and FVThe second stage starts by extracting the features of a queried image 29. We also compared the performance of our method with the particle swarm optimization (PSO)30 and genetic algorithm (GA)31 methods. The parameters used in each algorithm is given in Table We tested our proposed approach using the EFIGI catalogue, which consists of 4458 galaxy images29 contains 16 morphological attributes that were measured by visual examination of the composite g, u, r color image of each galaxy, derived from the SDSS FITS images using29. The EFIGI catalogue merges data from standard surveys and catalogues . The bulge-to-disk ratio32 and the degree of azimuthal variation of the surface brightness were often used as discriminant parameters along the Hubble sequence. This is not surprising since the EFIGI classification scheme is very close to the RC3 system. The final EFIGI database is a large sub-sample of the local universe which densely samples. The EFIGI morphological sequence is based on the RC3 revised Hubble sequence (RHS), which we call the EFIGI morphological sequence (EMS).The EFIGI catalogue22, using the same intensity mapping for all RGB images.Finally, all colors of the original data were used to create composite, “true color”, RGB images in PNG format with the Maxim DL astronomical software28.The precision rate is defined as the ratio of the number of retrieved images similar to the queried image relative to the total number of retrieved images28.The recall rate is defined as the percentage of retrieved images similar to the query image among the total number of images similar to the queried image in the databasep, q and r are the number of relevant images retrieved, relevant images in the dataset which are not retrieved, and non-relevant images in the dataset which are retrieved, respectively.Two measurements were used to evaluate the performance of the proposed algorithm: the precision rate and the recall rate.33. As discussed previously, the 10-fold CV works by dividing the dataset into ten groups, and the experiment was performed ten times by selecting one group as the test set and the remaining groups were used as a training set during each run. The output is the average of accuracy of the ten runs.In order to assess the effectiveness of our approach, we used the leave-one-out cross-validation method, where each image in the dataset was considered as the queried image, and the process was repeated 4458 times. Also, we used the 1-NN method based on 10-fold cross-validation (CV), which was used to evaluate the subset of selected features. This classifier is a parameter-free feature and is easy to implementIn general, we used color, texture and shape feature vectors for galaxy image retrieval. The total number of extracted features was 30, where nine features were extracted from the three colors RGB (three moments for each color), 20 texture features (four rotations for each measure) and one shape feature. The extracted feature vectors were applied to the feature selection method  to determine the relevant features.The best selected features with their accuracy  are given in Table The comparison results of our proposed method with other methods are illustrated in Figs Moreover, from Table Figures In order to investigate the influence of the size of the training set when selecting the best features, the dataset was randomly divided into training and testing sets. The proposed method was then evaluated at three different sizes, i.e. 50%, 70% and 85% of dataset (the remaining is the test set). Our results are shown in Table Finally, from the previous results, we can conclude on two things: first is that the proposed approach for galaxy image retrieval is better than the PSO and GA algorithms in terms of recall, precision, accuracy and the time complexity. The second is that the most suitable method used to split the dataset (when selecting the best-fitting features) is the 10-fold CV, however, if the dataset is divided randomly then the most suitable size for the training set is in the range 85% to 90%.In this study, we proposed a machine learning approach for galaxy image retrieval used for the automatic detection of galaxy morphological types from datasets of galaxies images. The automated detection of galaxies types is very important to understand the physical properties of the past, present, and future of the universe, while also offering a means for identifying and analyzing peculiar galaxies that cannot be associated with a defined morphological stage on the Hubble sequence.Our analysis was performed such that our approach automatically detected specific morphology types from different morphological classes without human guidance. The proposed algorithm was compared with the PSO and GA algorithms, and its performance was evaluated based on recall and precision. The results indicate the superior performance of our proposed approach.Based on the promising results of the algorithm, our future work will attempt to further investigate its application to other complex problems in astronomy by modifying the proposed method.


Motivated by the hierarchical micro and nanoscale features in terms of porosity of diatomite, the production of ceramic-graded porous foams with tailored porosity, obtained by using it as raw material, has been proposed. The main challenge during the foam-production process has been the preservation of diatomite nanometric porosity and the addition of other levels of hierarchical porosity. The coupled use of two techniques of direct foaming , combined with the use of 3D printing inverse replica method, assured the achievement of porosity of, respectively, microscopic and macroscopic dimensions. Optical and scanning electron microscopies have been performed for an in-depth characterization of the final microstructure. XRD analysis has been carried out to check the influence of sacrificial templates on the matrix mineralogical composition. The porosity of the diatomite-based foams has been investigated by means of nitrogen-adsorption analysis and mercury-intrusion porosimetry. The experimental tests confirmed the presence of different porous architectures ranging over several orders of magnitudes, giving rise to complex systems, characterized by hierarchical levels of porosity. The presence of porosity of graded dimensions affects the final mechanical performances of the macroporous diatomite-based foams, while their mineralogical composition does not result to be affected by the addition of templates. For this reason, these materials find application in a broad range of high-tech fields such as energy, building, aerospace, filtration and bioengineering. In many of these applications, hierarchical structures with pores of distinct sizes are desired to achieve a proper balance between conflicting properties2. Generally, graded porous materials are materials in which the properties vary in a given direction 3 and this is the major advantage compared to other composite materials. Several processing routes have been explored to fabricate FGPMs  including templating, etching, freeze casting3, microwave sintering processes and compression-molding salt leaching4. In the last years, apart from the aforementioned conventional processes, the use of advanced techniques such as additive manufacturing, which permits the fabrication of complex geometries with high accuracy, to make graded porosity (with predicted distributed porosities) and compositions, still remains a challenge5. Furthermore, this is even more a challenge if the “starting material” itself contains an intrinsic gradient porosity, obtained through physical and chemical blowing reactions and in specific environmental conditions7.The fabrication of foam materials with a porosity gradient  is widely desired from scientists in order to achieve an enhanced performance , mainly due to their low density, high strength and specific functional properties. FGPMs are innovative materials suitable for specific and advanced functions, in which a spatial gradation in structure and/or composition leads to tailored properties8. Accordingly, combining a new fabrication method (3D printing) with foaming techniques can be considered an innovative approach in the production of graded porous ceramic foams11. For example, the additive manufacturing (AM) of ceramic foams has become an attractive field of research that has the potential to disruptively change the way complex-shaped bodies are fabricated12. An even more enticing feature that has only recently started to be explored is the use of AM technologies to create materials with locally-tuned chemical compositions and intricate microstructures that are not accessible by conventional processing routes13. However, the use of this kind of processing technologies for ceramic materials is challenging because they are not easy to process considering their processing requirements (in terms of feedstock and/or sintering)12. Consequently, an indirect inverse-replica approach where (macro-) porous structures (templates) are printed and the ceramic slurry is cast into the template cavity, can overcome some of the limitationsin the physical, functional, and geometrical characteristics of components produced of the other AM techniques14 especially of the direct printing. In this way, in fact, templates and molds can be produced with high levels of accuracy using common polymers, taking advantage of freedom and shape possibilities provided by this technique. Moreover, the use of an indirect inverse-replica approach allows to avoid limitations, in terms of homogeneity and microstructure control of the final ceramic part, typical of other AM techniques, by filling directly the templates with suitable slurries15. Finally, in this case, the rheological properties required to the slurry are much less stringent compared to those required in the case of the direct printing in which the rheology of the inks definitely plays a key role. In particular, in this paper, stereolithography has been selected as 3D-printing technique for the production of the polymeric sacrificial templates needed to add macropores to diatomite based foams.Improvements in conventional processing methods and the development of innovative fabrication approaches are required because of the increasing specific demands on properties and morphology  for these materials, which strictly depend on the application considered17. Recently, diatomite was proposed as active support to obtain hierarchically porous nanocomposites with interesting application in environmental field20. The addition of other levels of porosity, with varying sizes, to the nano porosity already present and typical of diatomite22, leads to a bio-inspired final product with hierarchical and graded porosity that can be properly tuned according to the final properties desired for the material.So, taking inspiration from these considerations, the aim of this paper is the design and synthesis of sustainable functionally-graded porous ceramic materials with hierarchical and tailored porosity. These are obtained by starting from a natural raw material, diatomite, which is similar to seashells, trying to fully exploit its intrinsic features. Diatomites, opokas, tripolis, spongiolites, and radiolarites form a group of sedimentary silica rock consisting predominantly of opal and cristobalite. The interest shown in the study of siliceous rock is largely due to their useful properties26. CBCs are produced through a chemical reaction, consisting of a polycondensation of silica phases dissolved in a strong alkaline environment at low temperature, in contrast to traditional ceramic materials that are usually produced using fusion or sintering processes at elevated temperature. The complete production process of the diatomite-based foams is well-known and is accurately described in our previous works7, where it has also been demonstrated that the chemical–physical properties and density of the resulted foams can be tailored using the proposed aproach. In this manner, the innovative manufacturing process proposed in the present paper guarantees the presence of both microscopic- and macroscopic-scale porosity, preserving at the same time the nanoscale porosity of the starting diatomite, leading to ceramic foams with graded and tunable porosity.For the design and the production of the solid ceramic matrix, starting from diatomite, the so-called alkali-bonded ceramics or chemically bonded ceramics (CBCs), have been selected as reference materials, considering their ever increasing number of possible applicationsThree different geometries of sacrificial templates have been selected and printed in order to investigate the influence of the template geometry on the final microstructure and porosity of the diatomite based foam Fig. .Figure 1The printed models replicate exactly the computationally designed desired macro-scale pore sizes and architectures; the solids struts in the polymeric scaffold will constitute the macropores in the inverse replica foam structure. In particular, the template reported in Fig. Each sacrificial template has been impregnated pouring the diatomite-based slurry in all their cavities Fig.  and thenIt is possible to notice that no shrinkage and no evidence of swelling are present after the curing time Fig. , indicatAll the lattices of the produced foams are effectively precise and accurate inverse replica of the 3D printed designed structures Fig. . Lookinget al.7. It is also possible to identify the presence of a significant porous structure at nanometric scale ranging from 100 to 400 nm. Moreover, looking at the highest magnifications .); at 38° and 56°, there are two peaks related to sodium fluoride, NaF (JCPDS card n. 36–1455) that is originated from the reaction between catalyst and sodium. Finally, the peak at 47° is related to the unreacted silicon (JCPDS card n. 75–0589).The XRD spectra of diatomite based foam without macroporosity addition and of the macroscopic foam sample STa_DHCF, are reported in Fig. Looking at the spectra, it appears evident that the mineralogical composition of the diatomite based foam does not result to be affected at all by the template addition and the following removal process. The main crystalline phases present, in fact, resulted to be the same in both spectra and, consequently, it is not possible to identify any other new peak related to potential mineralogical phases due to the possible interaction between the polymeric template and the ceramic matrix.2 adsorption analyses performed on the STa_DHCF samples produced are reported in Fig. The results obtained from the NAccording to the Brunauer classification of the adsorption isotherms, the foam sample showed isotherm belonging to the type II. Moreover, the STa_DHCF isotherm resulted to be characterized by the appearance of hysteresis, absent in the isotherm of the raw diatomite reported in Fig. xp) obtained is equal to 82.05%.In order to characterize also porosity of bigger dimensions, the pore size distribution resulted from the Hg intrusion is reported in Supporting Information. It is possible to deduce that diatomite-based foam showed a monomodal pore distribution located at around 60 μm. Moreover, the values of pores total volume fraction  within the diatomite-based matrix which was already characterized by the presence of nanoporosity due to the nanoporous nature of the same diatomite (2–5 nm). The last level of hierarchical porosity (macroporosity) has been added to the diatomite-based foams using the 3D printing inverse replica method and choosing the stereolithography as the additive manufacturing technology for the production of the polymeric sacrificial templates needed. The indirect inverse replica approach allowed to overcome some of the limitations of other AM techniques, especially of the direct printing. In fact, in this process, templates and molds can be produced with high accuracy with common polymers, taking advantage of freedom and shape possibilities provided by this technique and avoiding limitations, in terms of homogeneity and microstructure control of the final ceramic part, filling the templates with suitable slurries. Moreover, in this case, the rheological requirements of the slurry are much less stringent compared to the case of the direct printing. The optical microscopy and SEM analysis confirmed the presence of different porous architectures and confirmed the absence of negative effects of the template addition on the foam microstructure. XRD analysis provided a further confirmation of the stability of the ceramic matrix and its final properties also after the removal of the sacrificial templates. Morever, it has been found out that the presence of this porosity of graded dimensions affects the mechanical properties of the macroporous diatomite based foams causing a toughening effect. Finally, ranging from three orders of magnitudes macro, micro and nano, it is possible to properly tailor the foam porosity according to the final properties desired.Oligomer: Allnex Ebecryl 8210 39.776%, Sartomer SR 494 39.776%Photoinitiator: Esstech TPO +  0.400%Reactive diluent: Rahn Genomer 1122 19.888%UV blocker: Mayzo OB + bis(5-tertbutylbenzoxazole)) 0.160%.Stereolithography has been selected as AM technology for the production of sacrificial templates with a defined and precise geometry, which corresponds to the negative of the geometry desired in the foam sample. In particular, sacrificial templates were designed and converted into stereolitography data using AutoCAD as CAD/CAM software. The model was then imported into a software (Autodesk Print Studio) that sliced it into layers and converted to a code path for the direct 3D printing. The printer used is an Autodesk Ember 3D-Printer, in which the tray holds the liquid resin that the machine turns into 3D parts. It has a clear window made of glass coated with PDMS (a member of the silicone family), through which 405 nm ultraviolet light shines and cures each layer of the print that remains stuck on the printing head. The standard tray of the Ember printer needs at least 50–100 ml resin so that it can be used for printing. The window must allow oxygen permeation in order to form a layer that inhibits polymerization which prevents the print to stick to the window. The resin used to print templates was a standard resin  and it was supplied by the printer producers, who provided the following chemical formulation :2SiF6) has been added in order to promote the gelification of the entire system. Then, two different techniques of direct foaming have been coupled, one based on chemical reactions with gas and the other one based on a mechanical foaming6. The Sodium Silicate water solution (SS)  was provided by Prochin Italia Srl and has the following chemical composition: Na2O 8.15%, SiO2 27.40%. Si metal powder  and Na2SiF6 were supplied by Merck and Sigma-Aldrich respectively. Vegetable surfactant  in water solution (pH = 7) was supplied by Isoltech s.r.l. Italia and used as received after mechanical whipping. Taking into consideration the experimental results already obtained in our previous works7 the diatomite-based foam has been produced using the following mixture (wt%): 70% of SS, 8.65% of Na2SiF6, 21.3% of diatomite and 0.05% of silicon powder. Based on 100 parts of the above mixture 12 part of a “meringue” type foam was added. The diatomite-based foam was prepared using simultaneously the silicon powder and the whipped protein as foaming agents, adding both of them to the starting mixture obtained homogeneously dry mixing first the powdered materials (diatomite and Na2SiF6) and then adding the SS solution.The produced slurry was poured inside the 3D printed sacrificial template and then the so obtained system, namely ST_DHCF, was cured at 40 °C and at room humidity for 24 hours. After curing, the consolidated foam, was thermally treated in order to burn out the polymeric template. The samples were slowly (0.5 °C/min) heated in a furnace (Nabertherm HTC 03/15) at 500 °C for 6 hours, in order to avoid the formation of cracks and fractures inside the foam matrix, caused by the polymer burning out.An aqueous sodium silicate solution has been used as alkali activator for the consolidation process of the starting diatomite , flux-calcined diatomaceous earth, was provided by Celite France) and a catalyst  to evaluate macroporosity. Furthermore, the evaluation of pores total volume fraction (xp) was determined as follows:0 is the real density and ρ was the bulk density of the foam, calculated as the mass of the foam divided by its apparent volume. The apparent volume has been geometrically calculated using a caliper (accuracy ± 0.05 mm), while the real density has been obtained performing a He picnometry .In order to investigate the morphology and microstructure and to verify the presence of all the different levels of porosity, optical microscopy  and SEM analysis  have been performed on all the produced samples. Also XRD analysis has been carried out to check if the template addition, especially the thermal treatment performed because of the template removal process, affected the mineralogical composition of the starting diatomite based foam. Porosity and specific surface were also evaluated by nitrogen adsorption analysis using a Nova 1000 machine . Density functional theory (DFT) method was used for determining pore size distribution in the range from micropores to mesopores3) using a universal testing machine  equipped with a 1 kN load cell. Measurements were performed in displacement control mode at a rate of 2 mm min−1 until the sample fracture was detected in the force–displacement plot. Three cubic samples have been produced and tested.Finally, compressive strength measurements were conducted on cubic ceramic foam samples (10 × 10 × 10 mmSupplementary Information


In comparison to WPT smokers, a larger increase in POX activity  and a smaller decline in DPPH activity  were found in non-smokers compared with WPT smokers. While these changes were slowly compensated within 1 hour after exhaustion, the activity of both markers was different from the pre-exercise values (p < 0.001). There was also a trend for UA concentration in non-smokers to be higher during the recovery period, with no significant difference between the groups (p > 0.05). It seems that WPT smoking is associated with negative effects on important human antioxidants and a diminished antioxidative response following acute exercise.Waterpipe tobacco (WPT) smoking is a public health problem with similar or even stronger effects than cigarette smoking. Although it appears to be associated with extensive oxidative stress, there is a limited number of studies on the oxidative effects of WPT smoking in stressful conditions. We, therefore, compared the responses of salivary flow rate (SFR), uric acid (UA) concentration, and peroxidase (POX) and 2,2-diphenyl-1-picryl-hydrazyl-hydrate (DPPH) activities between WPT smokers and non-smokers following a bout of exhaustive aerobic exercise (AE). Twenty-three sedentary young women (age: 22.95 ± 2.83 years) participated in this study, including 11 smokers (7.00 ± 1.41 uses/week) and 12 non-smokers. All participants were required to perform the Bruce protocol treadmill test at an initial gradient of 10% at 1.7 mph, with increases of these parameters every 3 min until exhaustion. Unstimulated saliva samples were collected before, immediately after, and 1 hour after AE. WPT smokers showed lower SFR compared with non-smokers at all time points ( Tobacco smoking is one of the most common leading causes of death in the world because it is associated with many types of non-communicable chronic disease such as cancers, cardiovascular diseases, and respiratory problems ,2. It haCigarette smoking and waterpipe tobacco (WPT) or hookah smoking are two major forms of tobacco consumption by the adult population , with IrOn the other hand, although regular exercise training increases the activity of DNA repair enzymes involved in ROS-mediated damage , acute pTwenty-three young women, including 11 WPT users (5 to 9 uses per week) and 12 non-users, were selected from a total of 27 volunteers according to the entry criteria, i.e., no regular exercise training in the last 3 months, no current pregnancy, lack of any oral infection and acute disease, and no signs, symptoms, or history of cardiovascular, respiratory, and musculoskeletal diseases. All participants did not use drugs in the past month and supplements known to affect the results  in the past six months. WPT smokers also did not smoke tobacco products other than hookah . The demographic characteristics of participants are shown in A familiarization session was considered one week before the test day to familiarize participants with the AE protocol and collection of saliva samples. Descriptive characteristics of each participant including height, weight, and body fat percentage were also measured at the end of this session. Participants were instructed to maintain their current dietary routines during the following week. However, to control energy intake, each participant received both written and verbal instructions to record the type and portion sizes of her daily food (two working days and one weekend day). Participants were instructed to eat their last meal at 11 am along with 500 mL of water to reach the same hydration level and refer to the gym at 2 pm. After arriving, they brushed their teeth and rinsed their mouth with distilled water. A list of foods with high antioxidant properties  was provided to all participants, and they were not permitted to use any of these foods at least 24 h before the exercise test. Pretest saliva samples were collected before the exercise during the final 5 min of a 15 min rest on a comfortable chair. The second and third whole saliva samples were also obtained immediately and 1 h after the exercise, respectively. Participants did not eat or drink between the samplings. WPT smokers were also instructed to avoid smoking on the day before the testing. It should be noted that all the study procedures including data collection and familiarization were time-matched between the groups and performed in a temperature-controlled room (22–24 °C) to avoid circadian variations in salivary antioxidant status and exercise performance.Initially, all participants completed a 10 min warm-up period including 5 min walking on a treadmill with no gradient followed by lower limb stretching exercises. The graded AE protocol was according to the Bruce protocol treadmill test. The test started by walking at 1.7 mph (2.74 km/h) at a gradient of 10% for the first 3 min. Because the exercise workload was increased gradually, the AE protocol proceeded with running during next stages. The gradient of the treadmill was increased by 2% every 3 min, and the speed was 2.5, 3.4, 4.2, 5, 5.5, and 6 mph in the subsequent six stages . The proSaliva is the first biological fluid containing different antioxidant molecules and enzymes that protect the body cells against free radical oxidation . Therefo−4 mg/mL in 0.3 M phosphate buffer, pH 7.4) was then added, and alterations in absorption were recorded at 510 nm (ΔA/min). One unit of enzyme activity was defined as an absorbance change of 0.001 per min under standard conditions . In WPT smokers, the flow rate immediately after AE was significantly lower than before exercise . However, the changes in non-smokers did not indicate a time effect (p = 0.068). Between-group comparisons revealed that the pre-exercise differences between WPT smokers and non-smokers (p = 0.013) as well as the differences immediately (p = 0.028) and 1 h (p = 0.014) after exercise were significant statistically. The changes in salivary flow rate during the 1 h recovery period after exhaustive AE are shown in p < 0.001; η2 = 0.79]. On the basis of pairwise comparisons using the Bonferroni test, POX activity immediately after exercise was higher than before exercise in both WPT smokers  and non-smokers . These values then decreased near to pre-exercise levels, as POX activity 1 h after exercise was lower than immediately after exercise in both WPT smokers  and non-smokers . Moreover, in between-group comparisons, no statistically significant differences were found before exercise (p = 0.142) and 1 h after that (p = 0.085), whereas a significant difference was only observed immediately after exercise (p = 0.009). Alterations in salivary POX activity following exhaustive AE are shown in p < 0.001; η2 = 0.51]. However, no significant differences were found between WPT smokers and non-smokers before exercise (p = 0.854), immediately after exercise (p = 0.615), or 1 h after exercise (p = 0.771). Although the mean concentration of UA was higher immediately and 1 h after AE in both groups compared to pre-exercise levels, these changes were only significant in non-smokers .In relation to salivary UA changes indicated in p < 0.001; η2 = 0.76]. DPPH activity was decreased significantly in both WPT smokers  and non-smokers . However, the observed differences between the groups were found to be statistically significant only immediately after exercise (p = 0.004). As shown in As it has been well documented in previous research ,15,19,21We observed that saliva FR in WPT smokers before exercise and immediately and 1 h after an exhaustive AE was lower than in non-smoker women. These findings confirm that the presence of various toxic chemicals in hookah smoke may decrease saliva FR in smokers . As obseThe results obtained in the present study revealed that the responses of salivary POX activity and DPPH radical scavenging activity in WPT smokers were weaker than in non-smokers, particularly immediately after exercise. It was also observed that the responses of salivary UA could differ between WPT smokers and non-smokers during the recovery period after an exhaustive AE. In comparison to WPT smokers, non-smokers experienced a larger increase in POX activity (around 23% vs. 14%) and a smaller reduction in DPPH activity (around −8% vs. −15%) immediately after exercise. Moreover, UA concentrations in non-smokers tended to be higher than in WPT smokers following exhaustive AE, but the differences were not significant. 2O2 that are produced after acute physical exercise [Enzymatic and non-enzymatic antioxidants protect the body against the adverse effects of OS. Overall, the antioxidant capacity is determined by these antioxidative compounds . The salexercise ,28. Thusexercise . Likewisexercise . The imp2O2 and ROS) as a result of increasing exercise intensity to exhaustion may induce a vigorous stress on the salivary antioxidant defense system, specifically in WPT smokers, because UA concentrations were significantly increased only in non-smokers, and POX activity in non-smokers after exercise were significantly higher than in WPT smokers. These findings are in line with those of our previous experimental study [It is well established that extreme physical exercise is associated with high free radicals production, including that of superoxide, hydrogen peroxide, and hydroxyl radical, as a result of high oxygen consumption . In the al study  that revIn our experiment, DPPH analysis was used to assess peroxy radical clearance based on available studies ,31. DPPHIn conclusion, the present results allow us to assert that a bout of exhaustive AE on a treadmill induces OS in both non-smoker and WPT smoker young women. However, it seems that the responses of salivary antioxidative markers including POX activity and the percent of scavenging activity against DPPH radical after the exercise were weaker in WPT smokers. Therefore, contrary to popular belief, these findings provide experimental evidence that WPT smoking presents health risks similar to those of cigarette smoking. Further research in this field is needed to compare the effects of different forms of tobacco smoking on the responses of human antioxidants following acute exercise.


Scientific Reports 10.1038/s41598-018-37017-4, published online 10 January 2019Correction to: This Article contains an error in Figure 4, where the key was omitted. The correct Figure 4 appears below as Fig.


Scientific Reports 10.1038/s41598-018-25967-8, published online 15 May 2018Correction to: This Article contains an error in Figure 9, where Figure 9b is a duplication of Figure 9a. The correct Figure 9 appears below as Figure


Scientific Reports 10.1038/s41598-018-29865-x, published online 20 August 2018Correction to: In Figure 1C, Sites 1 and 2 are incorrectly labelled. The correct Figure


Scientific Reports 10.1038/s41598-018-22504-5, published online 09 March 2018Correction to: 18O (blue) curves. The correct Figure 4 appears below as Figure In Figure 4 the Ostracod curve does not align with δD (orange) and δ


Scientific Reports 10.1038/s41598-018-19421-y, published online 05 February 2018Correction to: In Figure 4c, the heading “Autophagic ac”vity analysis” should read “Autophagic activity analysis”.Additionally, the “+” and “−” symbols are reversed in the displayed Western blots and graphs.The correct Figure 4 appears below as Figure


Anxiety disorders are common among children and adolescents; almost one-third of this population has an anxiety disorder. The most common anxiety disorders in this population are specific phobia (19.3%), social anxiety disorder/ social phobia (9.1 %), and separation anxiety disorder (7.6 %). Pediatric anxiety disorders are often associated with poor psychosocial functioning, academic underachievement, learning difficulties, substance abuse, relationship problems, and suicide behaviors. Psychotherapy, particularly cognitive behavioral therapy as a stand-alone treatment or in combination with medication, is found to be efficacious in the treatment of various anxiety disorders. The early recognition and treatment of anxiety disorders result in better long-term outcomes in children and adolescents. This article summarizes the evidence-based pharmacologic treatments for anxiety disorders in youth, including social anxiety disorder generalized anxiety disorder, separation anxiety disorder, and panic disorder. Anxiety disorders are the most common psychiatric disorders in adolescents and young adults with a lifetime prevalence of up to 30%. In a national survey, lifetime prevalence rates for adolescents were 31.9 % for any anxiety disorder, 19.3 % for specific phobia, 9.1 % for social anxiety disorder (SAD), 7.6 % for separation anxiety disorder, 2.3 % for panic disorder, 2.4 % for agoraphobia, and 2.2 % for generalized anxiety disorder (GAD). In adolescents, anxiety disorders are more prevalent among girls than boys, with an estimated ratio of 2:1 [Anxiety disorders usually have a chronic and persistent course as suggested by the prevalence rates throughout the life span . The perAnxiety disorders are associated with significant functional impairment and the development of the co-morbid psychiatric disorder in adulthood. They also result in a higher risk of cognitive impairment, academic under-achievement, and social dysfunction . MoreoveIn this review article, we have included the pharmacological treatment for the disorders that are currently recognized under the umbrella of anxiety disorder in the current Diagnostic and Statistical Manual of Mental Disorders (DSM)- 5. The existing literature has been assessed for the efficacy and safety of existing treatment options for SAD, GAD, panic disorder, and separation anxiety disorder. Selective serotonin reuptake inhibitors (SSRIs) are frequently prescribed for the treatment of anxiety disorders in youth. Only a few medications are approved by the Food and Drug Administration (FDA) to treat anxiety disorders in children and adolescents. Table A combination of treatments is often more efficacious. The results of the Child/ Adolescent Multimodal Study (CAMS) show that a combination of CBT and sertraline (80.7%) was better than CBT alone (59.7%) or sertraline alone ( 54.9%) to treat non-OCD anxiety disorder  . MethodsIn August 2018, the PubMed and Scopus were systematically searched for relevant publications focused on pharmacological treatments of SAD, GAD, panic disorder and separation anxiety disorder in humans. Two independent reviewers performed the manual search of references and relevant articles for included studies. Search results from these databases were imported to Endnote ×7  to remove any duplicates. Two independent reviewers performed title and abstract screening (when available) followed by the full-text screening of the articles by selecting case reports, case series, open-label trials, and randomized controlled trials (RCTs). The abstract-only articles, conference papers without original data, reviews, theses, posters, book chapters, editorials, letters, and commentaries were excluded. No restrictions on language, country, publication year, age, gender, or ethnicity of patients were applied. This article provides a summary of the evidence-based pharmacologic treatments for different anxiety disorders in children and adolescents based on the available data. Social anxiety disorder1. SertralineIn an open-label trial of 8 weeks, the efficacy and safety of sertraline were assessed among 14 participants, ages 10-17 (eight boys and six girls), with SAD. Sertraline was initiated at 50 mg/day with dinner, and it was titrated at 50-mg increments every other week to reach a maximum dose of 200 mg/day by week 6, depending on the clinical response and tolerability. At the end of the study, the doses were 200 mg/day in one, 150 mg/day in five, 125 mg/day in one, and 100 mg/day in four participants. The average daily dose of sertraline was 123.21 ± 37.29 mg/day at the end of the study. The Clinical Global Impression-Improvement scale (CGI-I) was used to measure improvement relative to baseline and the Clinical Global Impression - Severity scale (CGI-S) was used to measure severity. The Social Phobia and Anxiety Inventory for Children and a standardized behavioral avoidance test were used to assess for anxiety. By the end of the eight weeks, the independent evaluator reported that 5/14 (36%) subjects were classified as treatment responders or partial responders 4/14 (29%). However, psychiatrists rated 3/14 (21%) subjects as treatment responders and 7/14 (50%) as partial responders. The most common side effects were drowsiness, nausea, diarrhea, jitteriness, restlessness, headache, trouble sleeping, aggression, and skin rash in descending order of frequency. Most of these side effects were transient and resolved with a reduction in the dose of sertraline. Sertraline was discontinued in one patient due to severe gastrointestinal side effects [2. EscitalopramThe efficacy and safety of escitalopram were assessed in a 12-week open-label trial among 20 youth (10-17 years old) with SAD. Escitalopram was started at 5 mg/day in the first week, and then it was increased to 10 mg/day in the second week. The dose was maximized to 20 mg/day at 5-mg increments depending on the clinical response and tolerability. At the end of the study, 12 (60%) patients were taking 10 mg/day of escitalopram, four (20%) were taking 15 mg/day, and another four (20%) were taking 20 mg/day. The clinical efficacy was assessed by a change in CGI-I scores indicating that 13 of 20 (65%) patients achieved a score of 2 indicating a response to treatment. All secondary outcomes and quality of life measures showed improvements from baseline to week twelve, with effect sizes ranging from 0.9 to 1.9. The average daily dose of escitalopram over the 12-week open-label was 12.65 ± 2.08 and at the endpoint was 13 ± 4.1 mg. Somnolence, insomnia, flu symptoms, and appetite change were frequent, but transient side effects. Tremors were reported in one patient and were resolved on discontinuation [3. ParoxetineIn a 16-week long, double-blind RCT, the efficacy and tolerability of paroxetine were evaluated for SAD among 322 children and adolescents (ages 8-17 years old). Participants were randomized to receive paroxetine (10-50 mg/day) or placebo. Paroxetine was started at 10 mg/day and was titrated to a maximum dose of 50 mg/day at 10 mg-increments per week. The average dose for paroxetine was 32.6 mg/day for all patients (26.5 mg/day for children and 35.0 mg/day for adolescents) at the end of the study. The CGI-I was used to assess for efficacy at the endpoint, a score of ≤ 2 indicating a response. Safety was evaluated at each visit by monitoring vital signs and adverse effects. About 95.6% of participants were categorized as high risk. Further breakdown yielded 45.1% were “moderately ill”, another 38.5% were “markedly ill”, and 12% were “severely ill” by using CGI-S with higher comorbidity among the paroxetine group. About 77.6% of participants receiving paroxetine were defined as responders compared to 38.3% receiving a placebo. The clinical benefits of paroxetine were noticeable within the first four weeks of treatment. At the endpoint, participants receiving paroxetine (47.2%) were more likely to achieve remission compared to placebo (13.3%). The most common adverse effects were insomnia, decreased appetite, and vomiting. These side effects were mild and transient. Behavioral side effects included nervousness, hyperkinesia, asthenia, hostility, somnolence, insomnia, agitation, manic reaction, and emotional liability. Four patients receiving paroxetine reported suicidal ideations with one patient displaying self-harm behaviors .4. Tandospirone1A receptor with anxiolytic properties. Tandospirone was started at a fixed dose of 10 mg twice daily for the first week with a gradual increase to three times/day. The maintenance dose was between 20 to 60 mg/day depending on the efficacy and safety. Sertraline was initiated at 25 mg/day during the first week and was titrated to 50 mg/day in the second week. The mean dose was 35.14±7.75 mg for tandospirone and 89.58±30.47 mg for sertraline at the end of the study with a maintenance dose of 25-200 mg/day. The efficacy was assessed by Hamilton Anxiety (HAM)-A scores and change from baseline in CGI-I scores. Vital signs and adverse events were assessed at baseline and at weeks two, four, six, and eight by using the Treatment-Emergent Scale. The response rates were 48.6% for tandospirone and 55.6% for sertraline on the CGI-I scale. By using the HAM-A scale, the rate of response was 37.1% for tandospirone and 41.7% for sertraline. The most common side effect was drowsiness (11.4%), fatigue, and decreased appetite (8.6%) for tandospirone and decreased appetite (13.9%) followed by nausea (11.1%) for sertraline. The study demonstrates the efficacy and safety of tandospirone for adolescents, showing it to be as effective as sertraline for treating SAD [Huang and colleagues examined the efficacy and safety of tandospirone compared to sertraline in an open-label trial of eight weeks among 71 adolescents (ages 14-21 years) with SAD. Tandospirone is a partial agonist of serotonin ting SAD .5. CitalopramChavira and colleague assessed the efficacy of citalopram in a 12-week long, open-label trial along with psychoeducational treatment. All 12 participants (ages 8-17 years old) received 12 weeks of citalopram treatment and eight brief CBT-oriented counseling sessions (15 minutes each). Of these 12 participants, two participants dropped out due to nausea, lightheadedness, or concentration problems. Citalopram was started at 10 mg/day, and it was increased at 10-mg increments with a maximum dose of 40 mg/day over 12 weeks. About 83% of the participants were reported as being very much improved (41.7%) and much improved (41.7%) on the CGI-I scale. The treatment was well-tolerated without any side effects during the course of study .6. CannabidiolA double-blind randomized trial tracked the effects of a simulation public speaking test (SPST) among 12 healthy control participants and 24 patients with SAD who received a single dose of Cannabidiol (CBD) or placebo before the test. After careful screening, a total of 24 SAD subjects who never received any treatment for SAD were randomized to either CBD 600 mg (n=12) and placebo (n=12). The control subjects were assigned to perform the SPST without any medical intervention. CBD was given before the test. Psychological assessment was conducted by using the Visual Analogue Mood Scale (VAMS) and Negative Self-Statement scale (SSPS-N), and physiological measures including blood pressure, heart rate, and skin conductance. This study reported that pretreatment with CBD resulted in improvement in anxiety, cognitive impairment, and discomfort in their speech performance. It also resulted in a significant reduction of alertness in their anticipatory speech, compared to the placebo group. There was no significant difference observed among the healthy control participants .7. Several Serotonergic AgentsMancini and colleagues reported the efficacy of different serotonergic agents for social phobia among seven participants. The age range for these participants was 7 to 18 years  with a mean age of 14.4 years. Of the seven patients, four had comorbid anxiety and mood disorder. The mean age of onset for social phobia was six years. These patients were treated with paroxetine (n=5), sertraline (n=1), and nefazodone (n=1). The response to treatment was assessed by retrospective chart review performed by treating physicians. All patients responded to serotonergic agents, and their anxiety improved with minimal side effects. The most common side effects reported by three participants were transient diarrhea, minor visual accommodation difficulty, and mild somnolence. The dose range was 5-80 mg for paroxetine, 175 mg for sertraline, and 400 mg for nefazodone [8. FluoxetineIn an RCT, the effectiveness of fluoxetine, placebo, and social effectiveness therapy (SET-C) was studied among children and adolescents (age 7-17 years) with social phobias . In this9. Venlafaxine Extended-Release (ER)A 16-week placebo-controlled RCT evaluated the efficacy, safety, and tolerability of venlafaxine ER in 293 youth aged 8-17 years with SAD. Participants were randomized at baseline visit to venlafaxine ER or placebo in a double-blind manner. Venlafaxine ER was started at 37.5 mg /day and titrated up to 75 mg/day depending upon weight and clinical symptoms. The efficacy was assessed by Social Anxiety Scale-child or adolescent version (SAS-CA), and responder assessment was performed by CGI-I scores at each visit. Safety was assessed by measuring weight, heart rate, temperature, and electrocardiogram (EKG) during the visits. About 35% of participants dropped out of the study due to lack of efficacy and 4% due to the adverse effects. The average daily dose of venlafaxine ER during the active treatment phase was 141.5±47.5 mg for > 0 days of treatment among 140 participants and 155±39.0 mg for > 112 days of treatment among 54 participants. The average daily dose was given at 2.6 mg/kg to 3 mg/kg.A statistically significant benefit was observed for venlafaxine ER on the SAS-CA compared to placebo with a number needed to treat of five. About 56 % of venlafaxine ER was scored 1 (very much improved) or 2 (much improved) on the CGI-I scale compared to 37% among the placebo group. About 90% of participants reported treatment-emergent adverse effects which were mild-to-moderate in severity. These side effects resolve over the course of study with continued treatment. The most common side effects were anorexia, nausea, weight loss, dizziness, and nervousness. Three patients developed suicidality with no completed suicide and one patient developed an episode of hypomania with venlafaxine .10. BuspironeIn an open-label study of treatment of 25 subjects with pediatric social phobia, buspirone  showed some efficacy in the treatment of the phobia. Only three children improved enough to continue the medication after study completion (nine weeks) .Generalized anxiety disorder1. SertralineRyan et al. evaluated the efficacy of sertraline (n=11) compared to placebo (n=11) in children and adolescents (ages 5-17 years with mean age 11.7+3.9 years) with GAD in a 9-week long, double-blind RCT. Primary outcome measures were evaluated by the HAM, and the CGI-I and -S scales. Sertraline was started at 25 mg/day, and then it was titrated to 50 mg/day from week two to nine. The HAM total, psychic and somatic factor scores showed a significant benefit for sertraline from week four to the end of the study. About 90% of patients taking sertraline improved on the CGI scale compared to 10% in placebo. However, only two patients taking sertraline markedly improved. Dry mouth, drowsiness, leg spasm, and restlessness were the adverse effects common in the sertraline group while dizziness, nausea, and stomach pain were observed in the placebo group .2. DuloxetineThis 10-week long double-blind RCT of duloxetine  and placebo (n=137) was followed by an 18-week open-label phase (dose 30-120 mg). This study included children and adolescents (ages 7-17 years) with GAD who received duloxetine or placebo in a flexible-dose manner depending on the tolerability and response. The mean daily dose was 53.6 mg during the initial phase, followed by 66 mg (continued on duloxetine) and 60.4 mg (transition from placebo) during the open-label phase. Efficacy measures included the Pediatric Anxiety Rating Scale (PARS), CGI-S, and Children’s Global Assessment Scale (CGAS), while safety was assessed by the Columbia Suicide Severity Rating Scale (C-SSRS). The duloxetine group showed significant improvement in PARS, CGI-Severity, and CGAS in terms of symptomatic response, remission and functional remission (CGAS >70% improvement). The mean improvement was statistically significant in the duloxetine group, while the placebo group showed significant mean improvement in adolescents. During the second phase, there was a significant mean improvement in GAD symptoms in the group of duloxetine who transitioned from placebo.Severe adverse events in the acute phase included suicidal ideation and self-injurious behaviors in one subject with a history of depression and suicidal ideations. In the open-label phase, the duloxetine group manifested acute psychosis, bipolar disorder, suicidal ideations, tonsillitis, and adenoiditis. A patient who suffered from apathy and later developed suicidal in the tapering phase was eliminated from the study. In the acute phase, seven patients in duloxetine and six in placebo discontinued due to the adverse events which include nausea. Duloxetine group exhibited side effects in a 28-week period resulting in discontinuation of the treatment included nausea, suicidal ideation, vomiting, abdominal pain, upper dyspepsia, self-harming thoughts, bipolar disorder, abnormal behavior, irritability, fatigue, initial insomnia, somnolence, apathy, vaginal bleeding, blepharospasm, pharyngeal inflammation, and severe adenoiditis. When duloxetine was tapered, headache and upper abdominal pain were observed. Duloxetine caused a three-fold increase in alanine transaminase which became normal after discontinuing it.During the open-label phase, suicidal ideations with uncompleted suicidal attempts were reported seen in two patients. In comparison to baseline , three patients in each group (receiving duloxetine from the start and one switched from placebo to duloxetine) manifested treatment-emergent suicidal ideations. Duloxetine group exhibited more adverse events like nausea, vomiting, decreased appetite, oropharyngeal pain, cough, dizziness, and palpitations. In the acute phase, duloxetine showed a greater increase in pulse rate than the placebo group; also weight loss was seen in the duloxetine group, while weight gain was observed in the placebo group. In the second phase, the duloxetine group (receiving duloxetine from the beginning) showed a decrease in systolic and diastolic blood pressure, pulse, and increase in weight. The other group, which shifted from placebo to duloxetine, showed a mild increase in pulse, blood pressure, and weight .3. Venlafaxine ERRynn et al. reported the results of two RCTs of eight weeks (each and tapering period of 14 days) evaluating the efficacy of venlafaxine ER (n=157) compared placebo (n=163) in children and adolescents of age 6-17 years with GAD . The priAsthenia, anorexia, pain, and somnolence were common adverse effects in the venlafaxine group, twice as high as for placebo. Somnolence was common among adolescents. Changes in height, weight, pulse rate, blood pressure, and cholesterol level were significant with venlafaxine. Initially, 25% of placebo and 24% of the venlafaxine group dropped prematurely. Two subjects in the venlafaxine group discontinued treatment due to aggressive behaviors. On subgroup analysis, primary outcome measure improvement from baseline was observed both in children and adolescents. No gender difference in baseline severity existed. Tapering-related adverse events were 32% in the venlafaxine group and 16.5 % in the placebo group with dizziness more common with venlafaxine. Serious adverse events were observed in the first study with two participants dropping out of the study: one boy had suicidal ideation 48 hours after the last full dose, and one girl in the placebo group attempted suicide. In the second study, a girl showed agitation, and confusion resulted after venlafaxine taper. EKG changes like abnormal right atrial rhythm with short PR interval; and left atrial rhythm, rightward axis, and non-specific ST abnormality were observed in the venlafaxine group. These EKG changes were not significant enough to cause the withdrawal of participants.4. AlprazolamIn an RCT of 30 children with the overanxious disorder (n=21) and avoidant disorder (n=9) one week of placebo administration was followed by either placebo or alprazolam. The medication was tapered with placebo substitution in week five, and all the subjects received placebo on week six. There was a strong treatment effect in both the alprazolam and placebo group. Alprazolam was superior to placebo only on clinical global ratings, and the difference was not statistically significant .Panic disorder1. ParoxetineIn a retrospective chart review of 18 participants ages 7-14 years , Masi et al. reviewed the efficacy and safety of paroxetine for panic disorder. Participants with medical causes of panic disorder were excluded from the study. Paroxetine was started with an initial minimal dose of 8.9± 2.1 mg/day and was gradually titrated up to 40 mg/day depending upon clinical response and tolerability. CGI-I scale was used to assess clinical response among participants and adverse effects were monitored retrospectively at each follow-up visit. These patients were followed for a period of 11.7± 8.3 months (range 2-24 months). About 83.3% (15 out of 18 patients) reported an improvement in symptoms of panic disorder on the CGI scale (scores of ≤ 2). It took 21.87± 7.1 days (range 10-30 days) for these participants to respond, with the average dose at the initial response of 22.00± 7.75 mg/day. The average dose for participants with a response was 22.67± 9.61 mg/day (range 10-40 mg) at the end of the study. Paroxetine was well-tolerated with mild and transient side effects. The most common adverse effects were nausea, tension, agitation, sedation, insomnia, palpitations, and headache .2. ClonazepamBiederman investigated the efficacy of clonazepam for anxiety disorder with panic-like symptoms among three pre-pubertal children . Two of Separation anxiety disorder1. ImipramineIn the second phase of a six-week-long double-blind RCT, children (n=21) with age range of 6-11 years (mean age 9.5±0.8 years) were assigned to either imipramine (n=11) or placebo (n=10) group. The participants were diagnosed with a separation anxiety disorder who failed to respond to an initial psychotherapeutic intervention. Of these, only half of the subjects improved. The imipramine was started at 25 mg/ day for three days, after which it was increased to 50 mg for next four days, and subsequently increased gradually with the maximum dose of 5 mg/kg/day. By the end of the study, the dose of imipramine was 75-275 mg /day with a mean dose of 153 mg/ day (4.67 mg/kg). EKG was obtained at the initial visit, and then with each dose increment after the first increase to 50 mg, and no significant changes were observed. Pre-study assessments included the Wechsler Intelligence Scale for Children-Revised, Diagnostic Interview Schedule, problem list, Conner’s Questionnaire by parents and teachers, and Children’s Manifest Anxiety Scale for parents and youth. The global rating of improvement, which was rated by the child psychiatrists, parents, and teachers, was also performed. The assessment measures performed by parents, teachers and children self-rating failed to show any significant differences between the two groups. About 40-60 % of subjects improved overall without any difference between the two groups. Side effects were reported by 8/11 subjects in the imipramine group and 2/9 in the placebo group. Imipramine group had 12 moderate to severe complaints out of 18 total complaints, with the irritability and anger most frequent side effect. None of the side effects were serious enough to warrant a dropout .2. ClonazepamIn a double-blind cross-over study of 15 patients with separation anxiety disorder, subjects were treated with clonazepam (up to 2 mg /day ) and placebo. There were no significant treatment differences between the two groups. The authors did not support the use of clonazepam for separation anxiety disorder .DiscussionCurrent literature suggests a role of pharmacotherapy in the management of moderate to severe anxiety. An SSRI is considered as the first-line of treatment with an option of switching to another SSRI or Serotonin and norepinephrine reuptake inhibitors (SNRIs) in patients with persistent anxiety . HoweverA complete bio-psycho-social assessment, a working diagnosis, physical examination, and a comprehensive treatment plan that includes tangible goals is necessary before starting medications for anxiety disorders. SSRIs are the most common and efficacious treatment for anxiety disorders in youth. A combination of psychotherapy and medications usually results in better treatment outcomes in several anxiety disorders.


Recognizing a person in a crowded environment is a challenging, yet critical, visual-search task for both humans and machine-vision algorithms. This paper explores the possibility of combining a residual neural network (ResNet), brain-computer interfaces (BCIs) and human participants to create “cyborgs” that improve decision making. Human participants and a ResNet undertook the same face-recognition experiment. BCIs were used to decode the decision confidence of humans from their EEG signals. Different types of cyborg groups were created, including either only humans (with or without the BCI) or groups of humans and the ResNet. Cyborg groups decisions were obtained weighing individual decisions by confidence estimates. Results show that groups of cyborgs are significantly more accurate (up to 35%) than the ResNet, the average participant, and equally-sized groups of humans not assisted by technology. These results suggest that melding humans, BCI, and machine-vision technology could significantly improve decision-making in realistic scenarios. Visual search is the process of looking for an item of interest in a scene. Everyone engages in visual search many times every day . For exaThese difficulties are present also when searching for a target face in pictures of crowded environments, a critical task in security and surveillance . This chface detection) [face identification) [Searching for a target face in a crowded environment is a challenging task also for fully-automated computer-vision systems , albeit tection) . Secondlication) . If the ication) . In prinication) , especiaication) , 15.worse than individual ones. For example, when the opinions of group members are too correlated [To partially address the limitations of the human visual system, people can work together to search a scene. When making perceptual decisions, groups are generally more accurate than their members . This “wrrelated , when a rrelated , or whenrrelated , 23.The strategy used to aggregate individual opinions critically influences performance in group decision making. In the case of binary judgements, standard majority is the most straightforward strategy to use. However, in many circumstances it is suboptimal . A well-In principle, decision confidence could be more objectively assessed via means other than self-reporting. There is ample evidence that physiological correlates of decision confidence exist. For instance, several brain-activity patterns as recorded via electroencephalography (EEG) are known to provide information about decision confidence  and the error related negativity , 32), anhybrid Brain-Computer Interfaces (hBCIs) to test whether it is indeed possible to decode the decision confidence of single users from their EEG signals, RTs and other physiological measurements. In all cases, the hBCI relies heavily on machine-learning technology, which is used to specialise the interface to each particular user and to learn to predict the probability that, in a certain trial, the user made a correct decision. The confidence estimates provided by the hBCI were then used to weigh individual opinions and obtain group decisions. That is, our hBCI did not make automated decisions, it only produced weights for integrating behavioural decisions provided by the operators. These hBCI-assisted group decisions were then compared to decisions obtained by other forms of opinion aggregation. After initial tests of our system with a simple visual-matching task [In recent research, we developed a series of ing task , which sing task , 40, wheing task , which iing task . While tcombine these together. At least in principle, within such “cyborgs”, automated algorithms could compensate for the weaknesses of humans and vice versa, thereby producing more reliable and accurate decisions. For example, in a situation where most users in a group missed a target face , both traditional and hBCI-assisted groups would likely make a wrong decision. Conversely, a machine-vision algorithm might still identify the target with confidence. So, if it was included as a member in a group of humans, the machine-vision algorithm could potentially swing the group decision towards a correct decision.Given advantages and limitations of both humans  and computer-vision systems, one may wonder whether we could usefully search an image of a crowded, indoor environment and decide whether or not it contained a target face, a more challenging task than the face identification task used in [This study explores the benefits and drawbacks of this idea. Prior research has shown that aggregating decisions from a superrecognizer and a deep convolutional neural network in a face identification task led to significant more accurate decisions than two superrecognizers . We used used in .This research received UK Ministry of Defence Research Ethics Committee  and University of Essex ethical approval in July 2014. All participants signed an informed consent form before taking part in the experiment.Ten healthy participants  with normal or corrected-to-normal vision and no reported history of epilepsy took part in the experiment. Each participant was paid GBP 16 for taking part in the experiment plus an additional amount of up to GBP 4 proportional to the participant’s percentage of correct decisions. The latter was used to encourage participants to focus on the task and achieve maximum performance.Participants were comfortably seated at about 80 cm from a LCD screen (refresh rate 60 Hz) in an experimental room with normal white illumination .The experiment consisted of six blocks of 48 trials. At the beginning of each block, participants were shown a cropped face image of the person to be considered as a target for that block and were asked to memorise it before starting the presentation of the trials in the block. Each trial  started The images used as stimuli were obtained from the sequences P2L_S5 and P2E_S5 of the ChokePoint video dataset . The twoIn each block of the experiment, the images selected from a given sequence (1 or 2) and viewpoint  were presented. All six possible combinations of sequences and viewpoints have been tested. The order of presentation of the images in a particular block was the same for all participants. However, the order of presentation of the blocks was pseudo-randomly chosen for each participant, for counterbalancing reasons. In each block 25% of the images contained the target.Briefing, preparation and task familiarisation  took about 45 minutes, while the experiment took roughly 25 minutes. The images used as stimuli during familiarisation were pseudo-randomly selected for each participant from the dataset used in the experiment.Neural data were recorded at 2048 Hz from 64 electrode locations with a BioSemi ActiveTwo EEG system. Each channel was referenced to the average voltage recorded from the electrodes placed on each earlobe and band-pass filtered between 0.15 and 40 Hz. Artefacts caused by ocular movements were removed with a standard correlation-based subtraction algorithm. From each trial, response-locked epochs starting 1 s before the user’s response and lasting 1.5 s were extracted from the EEG data, baseline corrected with the average voltage recorded in the 200 ms before the stimulus onset, and downsampled to 32 Hz. Each epoch was then associated to the class “correct” (confident) or “incorrect” (not confident) depending on whether the decision made by the participant in that trial was correct or not, respectively.Common Spatial Pattern (CSP)  filterinp, we trained a logistic regression classifier with L2 penalty to predict the decision confidence wp, i.e., the probability of a particular decision being correct. Hence, each participant had his/her own BCI able to assess the objective decision confidence of the decision maker. We used 8-fold cross-validation to ensure that the results were not unfairly affected by overfitting. In each fold, 252 trials were used as training set and the remaining 36 as test set, to evaluate the groups’ performance.For each participant face_recognition Python library v1.2.3 available at https://github.com/ageitgey/face_recognition) to decide whether or not the target person was present in each image used as a stimulus in our experiment. The ResNet was formed of 29 convolutional layers  , and hae et al. , where iface_recognition library. The image of each face was then mapped to a 128-dimensional vector space where images of the same person are likely to be near to each other . Then, the ResNet computed the difference between the encoding of each face and the encoding of the target face, normalised using the Frobenius norm. If any extracted face had a difference smaller than a threshold, t, the stimulus was labelled as “target”, otherwise it was labelled as “nontarget”. The threshold was set to the value that maximised the accuracy on the training set using 8-fold cross-validation .In each trial of our experiment, the ResNet firstly scanned the input image to identify and extract individual faces using a pre-trained face-detection model integrated in the wResNet, was computed as follows:d is the difference between the encodings of the face extracted from the image and the target face . If more than one face was extracted from an image, only the face with the minimum d was considered. t. This formula ensures that the ResNet has substantially bigger confidence weights when the difference between the target face and the stimulus is very small or very big (confident decisions) than when it is close to the threshold (not confident decisions).In each trial, the confidence weight of the ResNet, wResNet were set to 0, so that, in cyborg groups, the ResNet vote would be ignored and only the humans influenced the decision.Trials where the ResNet did not identify any face in the image were labelled as “nontarget”, given the prevalence of nontarget stimuli in the training set . In such trials, the corresponding weights m = 2, …, 10 were formed off-line by combining the N = 10 participants in all possible Groups of size m in a trial was given by:dp = −1 if user p decided the trial represented a “target” and dp = + 1 for a “nontarget”, wp is the corresponding weight, and rsign a randomising sign operator which returns +1 (“nontarget”) if its argument is positive, −1 (“target”) if it is negative, and randomly chooses between +1 and −1 if its argument is 0. Traditional group decisions were obtained using standard majority, i.e., wp = 1 for all trials and users, while BCI-assisted group decisions used the decision confidence estimated by the BCI from the brain signals as weight wp.Traditional and BCI-assisted groups were composed only by human participants  of 12.0%. We have also looked at the ability of each participant of identifying nontargets and targets by computing their specificity and sensitivity as:The participants’ average specificity was 77.4% (SD = 15.8%) and their average sensitivity was 56.9% (SD = 10.9%). Hence, they recognised nontarget stimuli much better than target ones.t , but quite weak in detecting targets  compared to the average participant. Since target stimuli appeared only in 25% of the trials, the ResNet could still achieve high accuracy, which was the metrics used to choose the threshold t see . In two t see . Hence, t could achieve better sensitivity. When choosing t in order to maximise the F1 score in cross-validation instead of the accuracy, the ResNet reduced its accuracy (82.6%) and specificity (94.0%), and increased its sensitivity (48.6%). The average value of the threshold t over the eight folds was 0.559, while it was 0.526 when maximising accuracy. Similar results were obtained when maximising Cohen’s kappa to optimise t . In all cases, the sensitivity of the ResNet was worse than that of the average participant.One may wonder whether a ResNet using a different metrics to optimise the choice of the threshold To exhibit error-correction capability, groups require their members to make errors in different trials . In factParticipants had performance better than random and, therefore, their decisions were the same in the majority of the trials. However, the Hamming loss between two participants ranged from 12.5% and 47.2% . This suggests that the pairs exhibited error-correction capability in a large percentage of trials.p = 0.646). Given its high performance, of course the ResNet had minimum Hamming loss with the participants with the highest accuracy . Yet, even when paired with them, the pair still exhibited error-correction capability in more than 12% of the trials.When looking at the Hamming loss between the ResNet and each participant, we found similar results. In this case, the Hamming loss ranged between 12.2% and 48.3% . A Wilcoxon signed-rank test showed no differences between the Hamming loss of humans and ResNet  between corresponding nodes. Then, utilising a graph layout algorithm one can flattened the graph to obtain an intuition of similarities and differences in decision-making behaviour. This diagram as well as the previous analyses show how the ResNet behaves differently from virtually all other participants.m) using the five different methods for making group decisions analysed in this study . Since ResNet-assisted groups are based on standard majority, the smaller the group, the bigger the influence of the ResNet on the group decision. Indeed, the biggest improvement brought by ResNet-assisted groups over traditional groups occurs for m = 2, where the addition of the ResNet allows us to turn most of the ties generated by the two humans into correct decisions. This results in a boost in accuracy of more than 10% over traditional pairs. For bigger group sizes, the difference in average performance between ResNet-assisted and traditional groups gradually diminishes. We should expect the performance of ResNet-assisted groups to eventually converge to that of traditional groups. Yet, even for the larger group sizes considered in our study, ResNet-assisted groups were still better that traditional groups by 2–3%.Of course, one may expect methods which use some form of confidence estimation on a decision-by-decision basis to break ties, such as the BCI-assisted groups , but less accurate than BCI-and-ResNet-assisted groups. This indicates that, contrary to what is suggested in the literature for human groups [Interestingly, when using groups of BCI-and-ResNet-assisted humans . Conversely, BCI-assisted groups are significantly better than ResNet-assisted groups for large group sizes (m = 8–9). The two methods were on par for groups of size 7. For all group sizes m, BCI-and-ResNet-assisted groups  vs (e)” column in As expected, BCI-assisted groups are significantly more accurate than equally-sized traditional groups based on standard majority for all group sizes—see “(a) vs (b)” column in m = 3 − 10, while the opposite happened for accuracy. On the other hand, the sensitivity of groups of different sizes . The median BCI confidence values for incorrect and correct trials are 0.747 and 0.850, respectively. The ResNet is also able to assess its degree of confidence via p = 0.191).p = 2.9 × 10−7 and p = 2.0 × 10−3, respectively). Once again, the difference in standard deviations between correct and incorrect confidence values is bigger for the ResNet.From Taken together, these statistical differences suggest that both the BCI and the ResNet are able to assess the decision confidence, albeit not perfectly. Of course, this is not entirely unexpected. The BCI bases its confidence estimates on the brain signals of the users, hence facing two major challenges that affect its certainty. Firstly, EEG signals are generally affected by a high level of noise caused by various sources . Secondly, humans participants may be overconfident or underconfident, two behaviours which might in turn also impact their brain patterns, thereby making it potentially difficult for our algorithms to reliably infer the probability of a decision being correct. The ResNet decisions and confidence are also affected by noise from different sources .Irrespective of the reasons for the differences in confidence distributions between ResNet and BCI-assisted humans reported in A cyborg is typically defined as the combination of a human and a machine, which is either invasively embedded inside the human or replaces/extends a body part, with the aim of restoring some function or augmenting human capabilities. These types of cyborgs were once only the domain of science fiction, but are nowadays becoming a reality thanks to the advancements in neural engineering and prosthetics. However, we believe that the terms cyborg and cyborg group are also appropriate to describe non-invasive combinations of one or more humans and one or more machines, such as the systems described in this paper to augment performance in face recognition.shared-control systems, where the artificial component of the HMI generally takes care of all low-level decisions [Of course, such systems can also be considered as forms of Human-Machine Interaction (HMI), consisting of a machine analysing information, and humans using this analysis to make informed decisions. In this area fall hybrid BCIs  that allecisions . For exaecisions  or contrecisions  with a hecisions . HoweverA more recent and promising avenue of research has been looking at Human-Machine Cooperation (HMC), which further extend HMI to allow the human and the machine to cooperate on a more equal footing and at a higher (cognitive) level . This noThe cyborgs and cyborg groups proposed in this study represent operational solutions to the problem of how HMC could be implemented in an uncentralised and self-organising manner in the domain of decision making. The simplest solution would be creating groups where humans and machines have an equal weight in the decision making (majority-based groups). In our face-recognition task, the ResNet achieved significantly better performance than the average participant, hence allowing ResNet-assisted groups to significantly improve performance over traditional groups of humans. However, this approach is situation-independent, i.e., it is not able to discriminate in which cases the machine or the human should be trusted more.Cyborg group performance could be significantly boosted by assessing the decision confidence of team members (computers or humans) in each decision and weighing their decisions accordingly. We have shown that machine-vision algorithms could be designed that also estimate their degree of confidence, while BCIs could be used to decode the decision confidence of humans from their brain activity. These BCI-and-ResNet-assisted groups fully implement the HMC strategy, allowing to decide the contribution to the group decision of each team member (human or machine) on a decision-by-decision basis, depending on the degree of confidence of each actor. Moreover, contrary to what has been suggested in the literature for human groups , cyborg The cyborgs proposed in this study also take into account ethical and liability issues concerning automated decision making. We have shown that the confidence values provided by the BCI for humans are higher than the confidence of the ResNet, leading to humans counting often more than the ResNet in uncertain decisions. When cyborg groups are used at an operational level, it is ethically simpler  to let humans decide in cases where there is no clear majority of opinions between humans and ResNet. However, when humans in a group cannot agree on a decision, it is more reasonable to trust fully-automated systems than flipping a coin to break ties.Overall, all strategies explored in this study on how to integrate humans and machines have shown significant advantages in face-recognition performance over traditional groups of only humans. When fully-automated machine-vision algorithms are not reliable enough, BCIs could be used to significantly boost the performance of groups of human operators. In other situations, pairing machines and BCI-assisted humans may provide the best performance. Future work will verify these findings with other tasks where automated algorithms could be developed. Furthermore, ensemble of ResNets or similar artificial agents could be created and their performance compared with that of groups of humans or humans and machines, to further verify the need of humans in the loop to achieve maximum accuracy.


Data on the relationship between the triglyceride glucose (TyG) index and coronary artery calcification (CAC) progression is limited. This longitudinal study evaluated the association of TyG index with CAC progression in asymptomatic adults.We enrolled 12,326 asymptomatic Korean adults who had at least two CAC evaluations. The TyG index was determined using ln (fasting triglycerides [mg/dL] × fasting glucose [mg/dL]/2). CAC progression was defined as a difference ≥ 2.5 between the square roots (√) of the baseline and follow-up coronary artery calcium score (CACS) (Δ√transformed CACS). Annualized Δ√transformed CACS was defined as Δ√transformed CACS divided by the inter-scan period.During a mean 3.3 years, the overall incidence of CAC progression was 30.6%. The incidence of CAC progression  and annualized Δ√transformed CACS  were markedly elevated with increasing TyG index tertiles. Multivariate linear regression analysis showed that TyG index was associated with annualized Δ√transformed CACS . In multivariate logistic regression analysis, the TyG index was significantly associated with CAC progression in baseline CACS ≤ 100.The TyG index is an independent predictor of CAC progression, especially in adults without heavy baseline CAC. Recent epidemiologic study revealed that the number of people who died from cardiovascular (CV) disease in 2013 was more than 17.3 million, representing an increase from 1990 of 40.8% .The triglyceride glucose (TyG) index has been suggested as a reliable surrogate marker of insulin resistance (IR), which is a substantial risk factor for ASCVD –9. PreviData from the Korea Initiatives on Coronary Artery Calcification (KOICA) registry were analysed in the present study. Briefly, the KOICA is a retrospective, multicentre, and observational registry with single ethnicity in the setting of self-referral for asymptomatic subjects who underwent general health examination at six healthcare centres in South Korea . Overall2). Blood pressure of the right arm was measured using an automatic manometer after resting for at least more than 5 min. All blood samples including total cholesterol, triglyceride, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), creatinine, glucose, and glycated haemoglobin A1C (HbA1C) levels were obtained after at least 8 h of fasting and analysed. All methods were performed in accordance with the relevant guidelines and regulations.Information on history of hypertension, diabetes, hyperlipidaemia, and smoking status for each subject was systematically collected. Weight, height, and blood pressure were measured during the healthcare centre visits. Weight and height were measured during the subjects wore light clothing without shoes. The body mass index was calculated as weight (kg)/height  and SAS version 9.1.3 . A P-value < 0.05 was considered significant in all analyses.Continuous variables are expressed as the mean ± standard deviation. Categorical variables are presented as absolute values and proportions. After checking the distribution status of variables, the one-way analysis of variance test was used to analyse continuous variables and the χThe mean age of the 12,326 participants  was 51.7 ± 8.5 years. The prevalence of hypertension, diabetes, hyperlipidaemia, and current smoking was 33.5%, 13.8%, 28.0%, and 28.5%, respectively. The ranges of the TyG index in stratified groups of I (lowest), II, and III (highest) were 6.77–8.40, 8.41–8.91, and 8.92–11.62, respectively. Systolic and diastolic blood pressure; body mass index (BMI); the levels of total cholesterol, triglyceride, LDL-C, glucose, HbA1C, and creatinine; and the prevalence of male sex, hypertension, diabetes, hyperlipidaemia, and current smoking significantly increased with increasing TyG index tertiles. In contrast, the mean age and HDL-C levels significantly decreased with increasing tertiles . Annualised Δ√transformed CACS was elevated with increasing TyG index tertiles in categorical CACSs of 0 , 1–10 , and 11–100 , not in CACS > 100   Table . The resWith regards to the relation of TyG index with CAC progression according to the baseline CACS, the TyG index (per 1-unit increase) was associated with an increased risk of CAC progression in baseline CACSs of 0, 1–10, and 11–100 after adjusting for age, male sex, BMI, hypertension, diabetes, hyperlipidaemia, current smoking, and serum creatinine level. However, this association of the TyG index and CAC progression was not observed in the condition with baseline CACS > 100 Table . After aThe present study aimed to evaluate longitudinal change of CAC related to TyG index after considering baseline CAC status in asymptomatic adults. A number of studies reported that the TyG index was related to the risk of developing traditional CV disease and adverse clinical events. Recent cross-sectional data from Brazilian Cardioprotective Nutritional Program Trial showed the positive association of TyG index with metabolic and behavioral risk factors . In the The homeostatic model assessment of IR (HOMA-IR) has been traditionally used to measure IR , 29. HowAlthough several cross-sectional studies previously reported a significant relationship between the TyG index and CAC prevalence, longitudinal data have been limited in clinical practice. Recently, Park et al. observed that an elevated TyG index was related to an increased risk of CAC progression in 1175 subjects ; howeverIn the current study, CAC progression was observed in 13.0% of participants without CAC at baseline. Importantly, we found that a high TyG index has a strong association with an increased risk of CAC progression in this population after adjusting for confounding clinical factors. This relation of the TyG index with CAC progression was consistent in the baseline conditions of CACS of 1–10 and 11–100. However, there was no significant impact of the TyG index on CAC progression in participants with baseline CACS > 100. This result might be affected by the relatively small sample size of participants with CACS > 100, which was about 10.6% in our study. Thus, the significance of the TyG index for predicting CAC progression is still uncertain in individuals with heavy calcification at baseline. Further prospective studies with a large sample size are necessary to confirm this issue.The mechanism underlying the relationship of the TyG index with atherosclerosis is unclear. However, previous studies revealed the pivotal role of IR in atherosclerosis progression via promoting apoptosis of macrophages, endothelial cells, and vascular smooth muscle cells –38. ReceThere are some limitations to the present study. First, the KOICA registry was based on a relatively healthy population who underwent health check-ups in healthcare centres. The present study only included subjects who experienced at least two CAC scan examinations with available data on the TyG index and diabetic status from the KOICA registry. Thus, this study could not represent the characteristics of overall participants of KOICA registry and a potential selection bias might be present. Second, this was a retrospective study, which may be affected by unidentified confounders. Third, we only evaluated the association between the baseline TyG index and CAC progression; however, the mean change of the TyG index was very small: − 0.02 ± 0.48. Longitudinal consecutive changes of the TyG index during follow-up could not be confirmed. Fourth, the homeostatic model assessment of IR was not analysed because insulin levels were not measured in the KOICA registry. Fifth, some important data including physical activity, alcohol consumption, family history of disease were unavailable. Sixth, we could not control the effect of medications for hypertension, diabetes, and hyperlipidaemia on CAC progression because of the observational study design. Finally, the present study included only the Korean population. However, this study is unique in that we identified the predictive value of the TyG index for CAC progression according to the baseline CAC status in a large sample of asymptomatic adults.The TyG index is strongly associated with CAC progression after adjusting for confounding clinical variables, especially in adults without heavy CAC at baseline.Additional file 1: Table S1. Association between clinical variables and CAC progression.Additional file 2: Table S2. TyG index (per 1-unit increase) and the risk of CAC progression according to baseline CACS 100.