Glucocorticoid receptor (GR) regulates various cellular functions. Given its broad influence on metabolic activities, it has been the target of drug discovery for decades. However, how drugs induce conformational changes in GR has remained elusive. Herein, we used five GR agonists  with different efficacies to investigate which aspect of the ligand induced the differences in efficacy. We performed molecular dynamics simulations on the five systems  and observed a distinct discrepancy in the conformation of the cofactor TIF2. Moreover, we discovered ligand-induced differences regarding the level of conformational changes posed by the binding of cofactor TIF2 and identified a pair of essential residues D590 and T39. We further found a positive correlation between the efficacies of ligands and the interaction of the two binding pockets’ domains, where D590 and T739 were involved, implying their significance in the participation of allosteric communication. Using community network analysis, two essential communities containing D590 and T739 were identified with their connectivity correlating to the efficacy of ligands. The potential communication pathways between these two residues were revealed. These results revealed the underlying mechanism of allosteric communication between the ligand-binding and cofactor-binding pockets and identified a pair of important residues in the allosteric communication pathway, which can serve as a guide for future drug discovery. Glucocorticoid receptor belongs to the nuclear receptor (NR) superfamily to transduce the signals triggered upon its ligand glucocorticoid (GC) binding . It is bDue to its critical implication in GR’s functions, LBD structural biology receives considerable research interest. Although intense time has been invested toward this aspect, relatively limited success has been achieved. The first crystal structure of LBD was not successfully obtained until 2002, which formed a complex with its coactivator nuclear receptor coactivator 2 (TIF2) and ligand dexamethasone . Since tGR executed an essential role in cells, bearing the responsibility of both transcriptional activation and non-genomic actions . In the in vitro allergen-driven activation of blood mononuclear cells and allergen-specific T-cell blasts   with difThree co-crystal structures of GR complexed with agonists  were selected from the Protein Data Bank (PDB) as initial structures for MD simulations. The mutated residues were mutated back, and the missing residues were added using the Discovery Studio.Due to the unavailability of co-crystal structures of GR−AZ938 and GR−pred complexes, molecular docking was performed to generate the 3D structure of these two complexes. The chemical structures of AZ938 and pred were built and pre-optimized using the ChemDraw software. The GR−NN7 complex (PBD ID: 4CSJ) and GR−dex complex (PBD ID: 4UDC) were used as templates for AZ938 and pred, respectively. The following docking procedures were accomplished using the Schrödinger program. The unnecessary water molecules beyond 5 Å and other cofactors were deleted from the template structure using the protein preparation module of Schrödinger. The H-bonds were optimized, and the system energy was minimized. The glide module was then used to generate boxes for docking. The target agonists were loaded into the software and processed by the ligPrep module. Finally, molecular docking was conducted using the Ligand Docking module in SP mode. All the above operations were carried out using default settings and parameters. The resulting docking poses were then analyzed with Pymol and Discovery Studio. Additional minimization of 10,000 steps using the steepest descent algorithm was performed by Discovery Studio to optimize the docking interface.reduce to add all the hydrogen to the systems. Then, we transformed the PDB files into Tripos Mol2 format. The AM1-BCC charge model was used to calculate the atomic charges. Utility parmchk was applied to create parameter files that can be loaded into LEaP. After loading the parameter files, we ran the LEaP and finally obtained the inpcrd and prmtop files . At the second time, the systems underwent 50,000 cycles of steepest descent and conjugate gradient minimization each free of restrictions. Then, we heated up the system from 300 ps to 300 K in a canonical ensemble (NVT) with a 700 ps equilibration step. Finally, a 1000 ns MD simulation was carried out in each system with random velocities in isothermal isobaric conditions (NPT) with periodic boundaries. The system was regulated by Langevin dynamics  using the AMBER18 software . First, op files . Second,op files  and geneop files  to approdynamics  with theCluster analysis was applied to MD trajectories to classify and make sense of information in trajectories. We used the k-means algorithm , which gMM/PBSA was performed using the MMPBSA.py to evaluate the most essential residues in the complex between ligands and the receptor or the cofactors and the receptor with a large contribution to the free binding energy . The binsolv), molecular mechanical energy (EMM), and the entropic compartments  of the CTo identify the potential region that could contribute to conformational dynamics, we extracted representative structures for each system using cluster analysis. As shown in To verify whether this discrepancy in the direction of TIF2 was observed in all three independent replicas of simulations, we measured two pair-wise distances throughout the trajectories . The disbinding) of TIF2 to GR, which was divided among each residue , which was 10 Å more than the increase in the cor-bound and dibC-bound systems (Cdown). This illustrated that the level of conformational changes induced by the binding of TIF2 was different in each system, probably by influencing the interaction between the two pockets, which might result in the different efficacies of agonists. Interestingly, the coexistence of Cup and Cdown was observed in the pred-bound system, which exhibited features of both agonists with high efficacy (dex-bound and AZ938-bound systems) and low efficacy (cor-bound and dibC-bound systems). These results further verified that these two features regarding the area of two pockets may sensitively reflect the efficacy of the agonists. After the binding of TIF2, the constriction of the ligand-binding pocket conformation was much stronger in the pred-bound system than that in the dibC- and cor-bound systems, implying a stronger response toward the binding of the cofactor in the pred-bound system. Altogether, the results indicated the pocket conformational changes induced by the TIF2 could reflect the efficacies of ligands.As shown in To further investigate the conformation of the chosen residues in the cofactor pocket, the representative structures were extracted from each two-dimensional landscape . ObviousGiven the unique expansion of D590 in dex-bound and AZ938-bound systems, the D590 was further investigated given that it might be a crucial residue in the allosteric communication between the ligand-binding pocket and cofactor-binding pocket. K579 and E755 were observed to have various conformations before and after the binding of TIF2 . No evidComparative analyses of the representative structure of the cofactor-binding pocket emphasized the importance of the special relationship between D590 and TIF2. Previous crystal structure analysis also revealed that D590 formed vital hydrogen bonds with the conserved residue R+2 on TIF2 . Thus, wWe next attempt to investigate other residues within the ligand-binding pocket which might also be important for allosteric communication between two pockets. MM/PBSA analysis for the binding of ligand to the GR was carried out, and the result was further decomposed into every residue forming the ligand-binding pocket. Consistent with previous studies, T739 was identified as one of the most important residues for the binding of ligands . Among tAfter identifying the critical T739 and D590 in the ligand-binding pocket and cofactor-binding pocket, we next tried to explore the potential allosteric pathways connecting them. Using dynamic cross-correlation matrix (DCCM) calculations, we provided an overview of the inter-residue correlations within the simulation systems . ResidueNext, community network analysis and allosteric pathway analysis were carried out for the five systems to systematically investigate the allosteric networks . During Additionally, by calculating the optimal and suboptimal pathways that link D590 in community 10 and T739 in community 4, we revealed the potential allosteric pathways between the chosen residues in the five systems. As shown in GR, as an essential nucleus receptor, controls a myriad of cellular functions and signal transduction . Upon thBy comparing the representative structures extracted from the three replicas of simulations, we revealed conformational dynamics in five systems bound to five different ligands . ConformTwo-dimensional landscapes of two parameters relative to the ligand-binding pocket and cofactor-binding pocket separately were projected in five GR-ligand-TIF2 and five GR-ligand systems . The parIn view of the crucial role played by GR in clinical treatments , the dev


We also find the increasing acceleration of epigenetic aging and telomere attrition in the sequential blood samples from healthy individuals and infected patients developing non-severe and severe COVID-19. In addition, the longitudinal DNA methylation profiling analysis find that the accumulation of epigenetic aging from COVID-19 syndrome could be partly reversed at late clinic phases in some patients. In conclusion, accelerated epigenetic aging is associated with the risk of SARS-CoV-2 infection and developing severe COVID-19. In addition, the accumulation of epigenetic aging from COVID-19 may contribute to the post-COVID-19 syndrome among survivors.Chronological age is a risk factor for SARS-CoV-2 infection and severe COVID-19. Previous findings indicate that epigenetic age could be altered in viral infection. However, the epigenetic aging in COVID-19 has not been well studied. In this study, DNA methylation of the blood samples from 232 healthy individuals and 413 COVID-19 patients is profiled using EPIC methylation array. Epigenetic ages of each individual are determined by applying epigenetic clocks and telomere length estimator to the methylation profile of the individual. Epigenetic age acceleration is calculated and compared between groups. We observe strong correlations between the epigenetic clocks and individual’s chronological age ( Age is a risk factor for SARS-CoV-2 infection and severe disease. Here the authors perform DNA methylation analyses in whole blood from COVID-19 patients using established epigenetic clocks and telomere length estimators, and describing correlations between epigenetic aging and the risk of SARS-CoV-2 infection and severe disease. The incidence of severity and death in COVID-19 patients has been reported to increase with age5. Chronological age has been proved to be one of the major risk factors for developing severe COVID-19 and death6, and this risk is independent of other age-related comorbidities like diabetes, cardiovascular diseases, or obesity7. Therefore, understanding the biological aging of COVID-19 in severe cases versus non-severe patients could be quite useful to model and predict the disease progression with other laboratory assays8.The ongoing pandemic of coronavirus disease 2019 (COVID-19) due to severe acute respiratory syndrome-corona virus 2 (SARS-CoV-2) infection is a rapidly developing global emergency which already claimed over 170 million cases and 3.8 million lives worldwide as of June 13rd, 2021 11. DNA methylation correlates with aging process and can be used to estimate epigenetic aging across tissues14. The deviation between DNA methylation age (DNAm age) and chronological age has been proposed as a biomarker for aging and has been related to risk and survival outcomes in age-related diseases16. Previous work showed that the epigenetic landscape of host cell is altered during HIV19 and coronavirus23 infection, including SARS-CoV-2. In addition, telomere attrition in leukocytes is another hallmark of aging and associated with increased risk of aging-related diseases and human life span26, and a DNAm-based telomere length estimator (DNAm TL) has been developed27. Interestingly, telomere length and the epigenetic clock do not correlate with one another, suggesting that DNAm age and TL measure different aspects of biological aging29. Recently, epigenetic age at the moment of the infection has been reported to be associated with COVID-1932. However, little is known about the epigenetic aging during SARS-CoV-2 infection and in COVID-19 survivors and whether this factor might help predict the risk of developing severe COVID-19.Aging is a biological process related to diseases and mortality. The biological process in aging is reflected by molecular hallmarks, which include epigenetic modifications and telomere attrition36 and telomere length estimator27. We defined epigenetic age acceleration for each case by comparing the individual’s epigenetic age with chronological age to assess whether the accelerated or dysfunctional epigenetic aging is associated with SARS-CoV-2 infection and the severity of COVID-19 syndrome.In this study, we estimated the epigenetic age of the whole blood in COVID-19 patients and healthy individuals using the previously established epigenetic clocks To study epigenetic aging in the whole blood and its correlation with non-severe and severe COVID-19, we conducted a genome-wide DNA methylation study on whole blood collected from 232 healthy individuals, 194 non-severe and 213 severe COVID-19 patients in the combined set to calculate their DNAm age and TL using five different epigenetic clocks and DNAm TL estimator. The COVID-19 patients were not significantly different from the healthy individuals in terms of age and sex , though the PhenoAge clock showed weaker correlations with chronological age in the severe COVID-19 group . In addition, all clocks were strongly correlated with one another in all groups . DNAm TL was negatively correlated with chronological and DNAm ages in the whole set and all groups 40, interferon-related pathways23, and immune response genes41. Considering the DNA methylation changes in SARS-CoV-2 infection that may affect the expression of metabolic process and epigenetic aging of COVID-1941, a further question could be whether the accelerated epigenetic aging exists before the first viral contact, worsening progressively up or coming back to normal during the convalescence phases and post-COVID-19 period. Our analysis of epigenetic clocks and telomere shortening indicates an increasing age acceleration at the initial phases of COVID-19 and this could be partly reversed at later phases. We speculated that COVID-19 syndrome might accelerate epigenetic aging in SARS-CoV-2-infected patients based on these findings. Our longitudinal DNA methylation profiling analysis indicates that the influence of COVID-19 syndrome on epigenetic aging in peripheral blood could be reversed in some patients. However, additional experiments are necessary to validate these findings and elucidate the underlying mechanism.Epigenetic changes have been reported to be associated with the SARS-CoV-2 infection and unfavorable COVID-19 outcomes, including the methylation regulation of Angiotensin Converting Enzyme 2  that interrogates almost 850,000 CpG sites of the human genome. The “minfi” R package12, the Hannum clock with 71 CpGs identified in blood DNA samples33, the PhenoAge clock based on 513 CpGs derived from whole blood34, the skinHorvath clock that integrated the dataset of whole blood with skin, endothelial cells, mouth mucosa and saliva35, and the GrimAge clock using 1030 CpGs associated with smoking packyears and physiological risk factors61.We determined the DNAm age with the blood-based epigenetic clocks, including the Horvath clock with 353 CpGs based on multiple tissue types62 or epithelial tissue in our previous work15. The deviation between epigenetic age and chronological age, also known as epigenetic age acceleration, was calculated for every sample based on the residuals from regressing the DNAm age or TL on chronological age, as described by McEwen et al.62.Although the EPIC array lacks some of the CpGs in the Hannum and Horvath clocks due to the difference of EPIC array with HM450 array that these clocks rely on, missing clock CpGs on the EPIC array was demonstrated to not substantially affect the accuracy of the DNAm age estimation using blood sample by McEwen et al.27. The deviation between DNAm TL and chronological age, defined as DNAm TL attrition acceleration, was calculated for every sample based on the residuals from regressing the DNAm TL on chronological age.To explore the dynamic change of telomere length in the COVID-19 disease process, we used a DNA methylation-based estimator for telomere length based on the Horvath’s Elastic Net regression model64 we estimated the cell counts with the ‘meffil’ tool65 and performed cell composition adjustment to control the impact on epigenetic age acceleration estimation.Based on the accumulating evidence reporting the change of immune cell composition in severe COVID-19 patients,P values < 0.05 were considered statistically significant.The correlation among DNAm age, DNAm TL and chronological age of the samples was calculated with the Pearson correlation coefficient. A linear regression model was applied to determine the relationship between the epigenetic age and chronological age at the time of sample collection. All statistical analysis was performed using R Statistical Software (version 3.6.1). Further information on research design is available in the Supplementary InformationReporting Summary


Among the players diagnosed with COVID-19, injury incidence increased on their return to play after the infection . Additionally, injury incidence during training  and matches  was ~two-fold higher on return to play after COVID-19 compared to controls . Conclusions: Injury incidence in professional football players who had been infected by the SARS-CoV-2 virus significantly increased compared to the injury rates that these same players had prior to the illness. Additionally, the injury incidence was higher when compared to players who were not infected by the SARS-CoV-2 virus during the season, especially during matches.Background: The SARS-CoV-2 virus disease has caused numerous changes in sports routines in the last two years, showing the influence on an increase in sports injuries. The aim of this study was to prospectively analyze the incidence and characteristics of injuries in male professional football players diagnosed with COVID-19 when they return to play after recovering from this illness. Methods: Injury characteristics of professional male football players were recorded for the 2020–2021 season following the international consensus statement from the International Olympic Committee (IOC). SARS-CoV-2 infection in the football players was certified by PCR analysis. Injury epidemiology was compared in players infected by the SARS-CoV-2 virus before and after being diagnosed with COVID-19. Results: 14 players (53.8%) were diagnosed with COVID-19 during 2020–2021 season and 12 (46.2%) were not infected (controls). Only three (21.4%) had suffered an injury before being diagnosed with COVID-19. Eleven players (78.6%) had injuries after being diagnosed with COVID-19 ( Coronavirus disease 2019 (COVID-19), caused by a severe acute respiratory syndrome produced by the SARS-CoV-2 virus, is an illness that can cause multi-system failure and some other life-threatening conditions in a relatively high proportion of infected individuals ,4. Due tIn the subsequent waves of COVID-19, the approach of health and football authorities to protect football players from contagion during training, competition and travelling has been different. First, although the fixture of the national football leagues in the 2020–2021 season was similar to previous seasons, some changes of in-game regulations were allowed, such as the five-substitutions option ,8. AdditSeveral investigations have been geared to determining the effect of the COVID-19 pandemic on injury incidence in professional football. Two of them analysed the effect of football suspension and home isolation in the 2019–2020 season in the German Bundesliga ,11 and tTherefore, the aim of this study was to prospectively analyse the incidence and characteristics of injuries in male professional football players diagnosed with COVID-19 when they return to play after recovering from this illness.Twenty-six professional football players, from a team competing in the LaLiga Smartbank , volunteered to participate in this investigation. The following inclusion criteria were established for participants: (a) football players with a first team contract; (b) regular exercise training of >1 h per day, >5 days per week for the prior six months; and (c) had to not be admitted to hospital due to COVID-19 infection. The following exclusion criteria were applied to potential participants: (a) several injuries within the prior two months; (b) injuries incapacitating football training or matches in the previous six months; (c) mechanical instability of the knee joint . An a prThe experimental procedure of this study was in accordance with the latest version of the Declaration of Helsinki and was approved by the Francisco de Vitoria University Research Ethics Committee (32/2020) and complied with the Declaration of Helsinki for Human Research of 1964 (last modified in 2013).Following the guidelines provided by Spanish football and medical authorities, all players were tested for SARS-CoV-2 infection using a rapid antigen test four times per week and by Polymerase Chain Reaction (PCR) analysis 48 h before any official match for the duration of the season. In those cases of a positive rapid antigen test, infection by SARS-CoV-2 was confirmed by a PCR analysis. Once a positive case of COVID-19 was reported in a football player, the medical staff of the team recorded the date of diagnosis, the symptoms suffered by the player during the infection, the quarantine time set and the duration of the illness, including the dates of return to training and competition. The medical staff considered that a player had overcome the infection once they had had two negative PCR tests over a 24-h period.No player was vaccinated when infected with COVID-19 in the 2020–2021 season.Injury data were obtained prospectively during the 2020–2021 competitive season. All injuries were diagnosed, classified and recorded by the medical staff of the football team using the classification system developed by the medical commission of the International Olympic Committee (IOC) . The medt-test for paired samples and χ2 test. Additionally, injury variables during the season were compared among players with a record of COVID-19 infection and the players who did not report COVID-19 infection during the season (between-subject comparison), who acted as controls, using a t-test for independent samples and χ2 test. For each variable, 95% confidence intervals (95% CI) were obtained using the Poisson model. The significance level was set at p < 0.05 for all statistical calculations.All statistical procedures were conducted using SPSS . The normality of each variable was initially tested with the Shapiro–Wilk test, and, consequently, parametric statistics tests were used to determine differences among groups. Baseline characteristics, measured as continuous variables, were calculated as mean values with corresponding standard deviations. Ordinal or categorical variables, such as number of players with an injury or injury severity, were presented as absolute numbers and percentages. In those players with a record of COVID-19 infection, all injury variables  were compared before (PreCOVID-19) and after infection (PostCOVID-19) for a within-subject comparison using a During the season, 14 players  were diagnosed with COVID-19 infection while the remaining 12 players never tested positive in any antigen or PCR test. From the sample of players with a recorded COVID-19 infection, five players (35.7%) did not report any symptoms while the remaining nine players reported one or several symptoms such as fatigue, asthenia, fever and headache . No playp < 0.001). There was only one nerve injury due to L4-L5 disc protrusion. Almost all muscle injuries occurred in noncontact situations , and only 37.5% occurred during matches.One of sixteen muscle and tendons injuries were traumatic with an acute onset. Overuse injuries with a gradual onset were more common among knee injuries than among injuries to the lower back, foot, and hand muscles  during the 2020–2021 season. The injury incidence for the whole season was similar in players who had had COVID-19 and in controls (p = 0.527). For the whole season, training injury incidence was also similar in players with COVID-19 and in controls (p = 0.276), but the incidence of match injuries was ~two-fold higher in players who had COVID-19 than in controls (p < 0.001), not showing differences about inactivity and return to play (p = 0.632). The analysis of the subsample of players who had been infected with COVID-19 indicates that, when comparing injury rates before and after infection, the overall injury incidence and training and match injury incidence increased after COVID-19 infection when compared to the period prior to infection . Lastly, injury incidence after COVID-19 was higher than that reported by the control group for the whole season  had suffered a football-specific injury before being diagnosed, while 11 players (78.6%) had injuries after being diagnosed with COVID-19  but the incidence of muscle/tendon injuries during matches was ~two-fold higher in players who had had COVID-19 than the controls (p < 0.001). The analysis of the subsample of players who had had COVID-19 indicates that incidence of muscle/tendon injury overall and during training or competition increased after COVID-19 when compared to the period prior to infection  or when compared to the control group .The same pattern of injury incidences was present when analyzing only muscle/tendon injuries. Muscle/tendon injury incidence for the whole season was similar for the players diagnosed with COVID-19 and for the controls (p = 0.723). Additionally, the distribution of injury per type was similar in players diagnosed with COVID-19 before the infection and after their return to play (p = 0.621). Regarding severity, players diagnosed with COVID-19 needed a median of 22.0 days to return to play (interquartile range = 10.0–25.5 days) before infection and the return to play after the injury was similar after infection 29.0 days, (interquartile range = 16.0–33.5 days). In fact, the return to play after an injury in the players diagnosed with COVID-19 was similar to the controls who needed 21.0 days to return to play (interquartile range = 10.0–28.0 days). No player ended his career due to injury.For the whole team, most of the injuries were muscle/tendon injuries, with a lower percentage of joint/ligament injuries . The samIn the 2020–2021 season, football leagues were organised with strict measures to minimise the likelihood of contagion of SARS-CoV-2 during training and competition . This meIn the scenario of the 2020–2021 season, players infected with SARS-CoV-2 were rapidly quarantined in their homes while the football teams continued with their normal training and competition routines but with constant PCR and antigen testing to detect more potential cases within the team to prevent a possible outbreak early. While the player was at home, the medical staff of the team contacted him daily to certify the evolution of the illness while the player maintained an in-home training program tailored to the conditions of his place of residence and the evolution of the illness. Once it was certified that the player had no symptoms associated with COVID-19 by two negative results in PCR testing, the medical staff cleared him as free of COVID-19 and the return to training was determined. The strength and conditioning staff prepared a special “return to play” training program to aid the player to recover his physical condition. Again, the training program set for return to play was tailored to the characteristics of the time-out of each player, as the symptoms  and duraThe outcomes of the current investigation are different to the ones found in previous studies that analysed the effect of COVID-19 on injury rates in professional football ,11,12. SRecently, increased injury rates have been documented following COVID-19 sports suspension in American Major League Baseball ,22 and tOne of the most important findings of this research is that data from professional football players were collected and analysed during the COVID-19 pandemic despite the difficulty in taking these samples in professional athletes in all areas of sport due to their bubble of protection against SARS-CoV-2 infection . The autDespite the strength and novelty of this analysis, the study has some limitations. First, we have included the analysis of only 26 professional football players from a professional football team in the second division of the Spanish National League and from this sample, only 14 had COVID-19 during the 2020–2021 season. However, the data collected in this research were recorded prospectively and controlled by the club’s medical services, assuring the accuracy of injury epidemiological data and exposure times during both training and competition . FurtherIn summary, injury incidence in male professional football players who had been infected by the SARS-CoV-2 virus, and therefore had COVID-19, significantly increased with respect to the injury rates that these same players had prior to the illness. Additionally, the injury incidence was higher when compared to players who were not infected by the SARS-CoV-2 virus during the season, especially during matches.


The infectious coronavirus disease (COVID-19) has become a great threat to global human health. Timely and rapid detection of COVID-19 cases is very crucial to control its spreading through isolation measures as well as for proper treatment. Though the real-time reverse transcription-polymerase chain reaction (RT-PCR) test is a widely used technique for COVID-19 infection, recent researches suggest chest computed tomography (CT)-based screening as an effective substitute in cases of time and availability limitations of RT-PCR. In consequence, deep learning-based COVID-19 detection from chest CT images is gaining momentum. Furthermore, visual analysis of data has enhanced the opportunities of maximizing the prediction performance in this big data and deep learning realm. In this article, we have proposed two separate deformable deep networks converting from the conventional convolutional neural network (CNN) and the state-of-the-art ResNet-50, to detect COVID-19 cases from chest CT images. The impact of the deformable concept has been observed through performance comparative analysis among the designed deformable and normal models, and it is found that the deformable models show better prediction results than their normal form. Furthermore, the proposed deformable ResNet-50 model shows better performance than the proposed deformable CNN model. The gradient class activation mapping (Grad-CAM) technique has been used to visualize and check the targeted regions' localization effort at the final convolutional layer and has been found excellent. Total 2481 chest CT images have been used to evaluate the performance of the proposed models with a train-valid-test data splitting ratio of 80 : 10 : 10 in random fashion. The proposed deformable ResNet-50 model achieved training accuracy of 99.5% and test accuracy of 97.6% with specificity of 98.5% and sensitivity of 96.5% which are satisfactory compared with related works. The comprehensive discussion demonstrates that the proposed deformable ResNet-50 model-based COVID-19 detection technique can be useful for clinical applications. A massive outbreak of novel coronavirus disease COVID-19) occurred in Wuhan, China, in December 2019, and it is causing a pandemic situation worldwide. According to the World Health Organization (WHO), around 476 million confirmed cases of COVID-19 including 6.1 million deaths were reported worldwide as of March 25, 2022 9 occurre. The cheIn this study, chest CT scan images are used for COVID-19 detection due to its higher sensitivity than RT-PCR testing as demonstrated in . The expDesigning deformable convolutional neural network models in order to detect COVID-19 cases from chest CT images based on the conventional CNN and ResNet-50 architectures.Tuning the model to achieve superior performance and consequently training and validating it with a balanced dataset of COVID-19 chest CT images.Visual inspection of the localization capability of the convolution layers through Grad-CAM.Performance evaluation and inspection of the impact of deformable layers of the proposed models as well as comparative analysis with the related state-of-the-art techniques.There are lots of well-established deep convolutional neural network (CNN) architectures such as VGG16, ResNet-50, InceptionV3, and EfficientNet for object detection and classification tasks using images as input data. Last two years during the pandemic, various research works were conducted based on the DL method for COVID-19 classification, but to the best our knowledge the deformable CNN have not been used yet in this area. In this study, we have proposed two separate deformable deep convolutional networks considering the conventional CNN and the state-of-the-art ResNet-50 for COVID-19 detection from chest CT with a strategic emphasis on finding the impact of the deformable concept through a comparative performance analysis among the normal and deformable forms. The gradient class activation mapping (Grad-CAM) technique has been used to visualize and check the targeted regions' localizing effort at the final convolutional layer of the models. The main contributions of this work are as follows:The rest of this article is organized as follows: A literature review of recent work is given in the related works section. The methodology section explains the proposed methodology as well as the model evaluation process. The next subsection presents the dataset used in this work, and the experimental result analysis has been explained in the experimental results and discussions section. Finally, the conclusion section concludes the whole research work.Numerous research works have been performed to diagnose COVID-19 from chest CT scan and X-ray images using ML and DL techniques. This section presents some recent studies related to COVID-19 detection from CT images applying DL techniques. A nine-layer tailored deep CNN model is proposed in  for COVISingh et al.  designedF1-score ranges from 0.94 to 0.95. Gifani et al. [Ensemble learning is now becoming a popular technique because of its higher precision and accuracy instead of using a single model. Several studies implemented an ensemble of transfer learning using different pretrained deep neural network architectures such as VGG, Xception, and ResNet for screening COVID-19 cases. Aversano et al.  exploit i et al.  used 15 i et al.  also proi et al. . The expAfter reviewing the above research works, it is concluded that the deep learning method can be employed for COVID-19 screening purposes though there were some limitations such as imbalanced datasets and high rates of false prediction. So there is still a scope to improve the prediction accuracy more as well as the robustness of the methods that can minimize the false positive and false negative rates. In this work, we proposed a deep learning approach for COVID-19 detection using CT images. A deformable technique is implemented in the standard ResNet-50 architecture to make the model more robust by replacing a few layers of ResNet-50 with its deformable parts to achieve the good prediction performance.This section covers mainly three parts of the methodology for COVID-19 detection: (a) describing the idea of the deformable CNN, (b) explaining the proposed framework using the deformable concept, and (c) mentioning different evaluation criteria to validate the proposed framework. Description of the CT scan dataset used in this researh is provided at the end of this section. The standard CNNs are limited in their ability to model complex geometric transformations due to their fixed geometric composition of modules. The convolution kernel selects the samples at fixed spatial location, and the pooling layer reduces the spatial resolution at a constant ratio in regular CNN modules. As a consequence, it reduces the effectiveness of models for complex transformation. So the adaptive determination of sampling locations or deformed kernels based on the objects is required for exact visual recognition. In this regard, Dai et al.  introducS sampling locations, wi and li denote the weight and offset for the i-th location of the kernel, respectively. Then, y(l) denoting the output features from the input feature x(l) at location l is calculated as follows:Let a convolutional kernel of S sampling locations is augmented with offsets ∆li which is a learnable offset. As l + li + ∆li is now fractional, bilinear interpolation is used to calculate x(l + li + ∆li) in equation , sensitivity (Sn), f1-score (Fs), and precision (Pr), respectively.tp) and true negative (tn) denote the value of correct predictions of actual COVID positive patients and non-COVID patients, respectively. False positive (fp) and false negative (fn) denote the value of incorrect predictions of COVID positive and negative patients, respectively. The confusion matrix is also utilized to show the value of true and false predictions in a comfortable way of visualization which is shown in The commonly used assessment metrics for DL classification models are utilized to assess the proposed methodology. The metrics are accuracy, specificity, sensitivity, quations –7) repr reprf1-sCT scan images have a detailed and clear view of the lungs as compared to CXR images. So it is a very convenient way to diagnose the COVID-19 disease using CT images. A chest CT scan dataset is collected from the kaggle dataset repository for this experiment of COVID-19 diagnosis. The CT images of this dataset have been collected from different real patients in hospitals from Sao Paulo, Brazil . It contThe collected CT dataset is almost a balanced dataset which is an important factor of the model learning phase in the deep CNN. An imbalanced dataset may mislead the output prediction in deep learning classification tasks. In this experiment, no preprocessing techniques are applied due to irregular opacification present in CT images of pulmonary diseases. So raw CT scans are used for COVID-19 detection purposes because preprocessing can cause the loss of actual sensitive information about the texture of the infected region.All the experiments were performed on the Google colaboratory platform using the Keras and Tensor Flow libraries. The programs were run on GPU with 12.69 GB RAM and 107.72 GB Disk provided by Python-3 Google compute engine backend. In total, four experiments were performed in this study, consisting of a fifteen-layered CNN with its normal as well as deformable form and a ResNet-50 model with its normal as well as deformable form for COVID-19 screening.Both the normal and deformable fifteen-layered CNN models are trained and validated using the collected COVID-19 CT dataset with input shapes of 150 × 150 × 3. The dropout rate of 0.4 is used in the dropout layer of both configurations. The Adam optimizer with the learning rate of 0.001 and the categorical cross-entropy loss function are employed to compile the models. The number of epochs and other hyperparameters are tuned for the best learning process. Finally, the number of epochs is selected as 60. The train-valid-test splitting ratio is used as 80 : 10 : 10, and The erratic nature is seen from the model accuracy curve due to the raw CT images of random passing to the models shown in Then, the state-of-the-art CNN model, ResNet-50, has been selected for this experiment of COVID-19 screening. Primarily, the whole model has been developed from scratch, according to its original architecture. Then, its deformable form is created as mentioned in the proposed model subsection. All the parameters of both models  are trained through the collected CT dataset; no transfer learning technique is employed here. The training dataset has been selected for learning the model with input shapes of 64 × 64 × 3. The hyperparameters are selected to the standard value after various tuning processes addressing overfitting and underfitting problems. The Adam optimizer and categorical cross entropy loss function are used to compile the normal ResNet-50 and deformable ResNet-50 models. The learning curves for both normal and deformable ResNet-50 models are shown in The confusion matrixes for both regular ResNet-50 and proposed deformable ResNet-50 models are shown in Computation time is an important factor for model performance analysis and for any diagnosis system. In this regard, we have calculated the CPU times required for a single CT image prediction in all our experiments. CPU times depend on the input image shape. For the first two experiments , input image shapes were 150 × 150 × 3 and then the regular and proposed deformable ResNet-50 took input shapes of 64 × 64 × 3. The normal and deformable fifteen-layered CNN take CPU times of 46.7 ms and 71.6 ms, respectively, for the prediction of a single CT image. This time includes image loading and resizing according to the model's input shape and then prediction. Then, the normal ResNet-50 model and the proposed deformable ResNet-50 model take CPU times of 55.2 ms and 68.1 ms, respectively, for a single image. Hence, the deformable part takes little more time than its original form due to the extra parameters contains in deformable parts.The receiver operating characteristics (ROC) curve is a widely used graphical representation of classifier performance. The Grad-CAM visualization is a useful tool for differentiating the model learning capability in positive and negative cases using the heatmap view in the images . It usesIn this study, we have also discussed comparative analysis with the related deep learning-based state-of-the-art works. Most of the time, the performance metrics of deep learning models depend on the size of the dataset used for training. So the articles that used the same dataset or one that was close to our employed dataset size as well as related deep CNN models were selected for appropriate comparison of performances. The deployment of DL techniques in the various medical diagnosis systems is now growing worldwide, and it speeds up the early diagnosis system in healthcare environments. In this article, we have proposed a COVID-19 disease detection technique from chest CT using the deformable deep CNN. Different experiments were performed for better model selection. The impact of the deformable concept has been examined through performance comparative analysis among the designed deformable and normal models, and it is found that the deformable models show better prediction results than their normal form. Extensive analysis shows that the proposed deformable ResNet-50 model performs satisfactorily with an accuracy of 97.6% compared with the state-of-the-art techniques. The Grad-CAM visualization evidences of the targeted regions' localizing tendency at the final convolutional layer is also found noteworthy. In the future, more diverse and critical CT datasets will be utilized for training to boost the robustness of the model. Finally, this study showed that the proposed method can be useful for effective COVID-19 detection as a substitute for RT-PCR with time and availability limitations.


Several studies have shown that neutralizing antibody levels correlate with immune protection from COVID-19 and have estimated the relationship between neutralizing antibodies and protection. However, results of these studies vary in terms of estimates of the level of neutralizing antibodies required for protection. By normalizing antibody titers, we found that study results converge on a consistent relationship between antibody levels and protection from COVID-19. This finding can be useful for planning future vaccine use, determining population immunity, and reducing the global effects of the COVID-19 pandemic Determining the relationship between immune response and protection from symptomatic SARS-CoV-2 infection  is useful for predicting the future effectiveness of vaccines. That relationship should enable immunobridging  that can help with approval of new or updated vaccines based on immunogenicity data, without the need for large phase 3 trials  or ChAdOx1  with or without symptomatic breakthrough infection .The study of immune correlates by Khoury et al. used a vaccine-comparison approach, which estimated the relationship between mean neutralizing antibody levels  and vaccine efficacy  across 7 vaccines and convalescing persons  . TA major limitation for reconciling thresholds of protection  is lack An alternative approach for normalizing neutralization titers between studies is to assume that similar groups of vaccinees should have similar titers. For example, rather than relying on conversion to the WHO international units, we can assume that the mean neutralization for the mRNA-1273 vaccinees is similar in the phase 1/2 trials .The broad CIs and divergence of the models for which neutralization data are sparse suggests the need for caution when extrapolating the relationship between neutralization and protection beyond the ranges of data available in each study. The vaccine comparison approach has the advantage of fitting to a large span of neutralization titers (a 20-fold range in GMT between the 7 vaccines) (https://www.pfizer.com) vaccinees . Using ChAdOx1 (with 4-week spacing of doses) as a comparator, we found that a superiority margin of 2.6-fold of GMT compared with ChAdOx1 vaccinees would provide similarly high confidence of >80% vaccine efficacy. Of note, those margins are in strong agreement with the lower 95% CIs predicted in the breakthrough-infection studies  and that a margin of 2.6-fold of the mean ChAdOx1 titer would predict an efficacy of >76%  associated with a given level of protection, which regulators and vaccine developers could use as a target when assessing and approving vaccines . However, the lack of assay standardization means that no such threshold in international units can be determined that is broadly applicable across different neutralizing antibody assays. Alternatively, regulators have signaled that immunobridging studies, which compare the immunogenicity of new vaccines with that of existing vaccines (for which efficacy has previously been determined) should be conducted , panel Cal virus . If mRNA studies , which wll cases  . TA second goal for the study of protective thresholds is to identify a protective titer for clinical use, that is, a simple blood test for clinically relevant antibody level to indicate if a person is likely to have good protection from COVID-19. The studies that have defined the relationship between neutralization titer and vaccine efficacy have not been designed for, and are not primarily concerned with, defining such a threshold because they deal only with estimates of vaccine efficacy at a population level. Furthermore, individual predictions from population statistics can be fraught with difficulty. Unfortunately, the term “threshold” gives the impression that there might be an antibody level above which one is fully protected (and below which one is susceptible). However, the shapes of the protection curves  make it –Predicting vaccine efficacy or a clinically useful threshold of protection against COVID-19 would be a major advance. The in vitro neutralization titer has been demonstrated by multiple studies to be well correlated with vaccine efficacy and with a person’s protection from symptomatic SARS-CoV-2 infection (https://www.medrxiv.org/content/10.1101/2022.06.09.22275942v1), although a recent study has begun to explore this question by using a breakthrough-infection approach  to deal with neutralization of current and future SARS-CoV-2 variants. The studies discussed in this analysis primarily deal with neutralization of and protection from the ancestral SARS-CoV-2 strain because the breakthrough-infection data and vaccine efficacy data in most studies was from phase 3 clinical trials (https://www.medrxiv.org/content/10.1101/2022.03.21.22272672v2). Neutralizing antibody levels are also correlated with protection from severe SARS-CoV-2 infection (In vitro neutralizing antibody titers against SARS-CoV-2 present a clear correlate of protection from symptomatic SARS-CoV-2 infection. Studies of passive administration of neutralizing monoclonal antibodies in animals and humans support that neutralizing antibody titers are a mechanistic correlate of protection (In conclusion, our findings show that the different COVID-19 correlate of protection studies, which seemingly report different thresholds of protection, have strong agreement. However, other immune responses may also play a substantial role in protection against progression from symptomatic to severe SARS-CoV-2 infection. The agreement across multiple studies of the relationship between neutralizing antibodies and efficacy against COVID-19 can be useful for planning future vaccine use, determining population immunity, and reducing the global effects of the COVID-19 pandemic..Supplementary methods and analyses for study of correlates of protection for SARS-CoV-2 infection


Serious concerns have been raised about the negative effects of the COVID-19 pandemic on population psychological well-being. However, limited data exist on the long-term effects of the pandemic on incident psychiatric morbidities among individuals with varying exposure to the pandemic. Leveraging prospective data from the community-based UK Biobank cohort, we included 308,400 participants free of diagnosis of anxiety or depression, as well as 213,757 participants free of anxiolytics or antidepressants prescriptions, to explore the trends in incident diagnoses and drug prescriptions for anxiety and depression from 16 March 2020 to 31 August 2021, compared to the pre-pandemic period  and across populations with different exposure statuses . The age- and sex-standardized incidence ratios (SIRs) were calculated by month which indicated an increase in incident diagnoses of anxiety or depression among individuals who were tested for COVID-19 , especially during the first six months of the pandemic . Similar increases were also observed for incident prescriptions of anxiolytics or antidepressants . In contrast, individuals not tested for COVID-19 had consistently lower incidence rates of both diagnoses of anxiety or depression (0.70 [0.67–0.72]) and prescriptions of respective psychotropic medications (0.70 [0.68–0.72]) during the pandemic period. These data suggest a distinct rise in health care needs for anxiety and depression among individuals tested for COVID-19, regardless of the test result, in contrast to a reduction in health care consumption for these disorders among individuals not tested for and, presumably, not directly exposed to the disease. The coronavirus disease COVID-19) pandemic continues to be a world-wide public health threat 9 pandemi. SeriousNotably, previous studies have also suggested varying effects of the pandemic on population mental health across time  and degrYet, limited data exist on the long-term effects of the pandemic on incident psychiatric disorders among individuals with varying exposure to the pandemic , with careful control of potential confounding including seasonal effects. To this end, we leveraged routinely collected administrative data from the UK Biobank to assess trends in incident diagnoses of common psychiatric disorders – anxiety and depression – and prescriptions of respective psychotropic medications  during the first 18 months of the pandemic, by history of COVID-19 testing  as an indicator of pandemic exposure.The UK Biobank is a population-based cohort study that recruited 502,507 men and women aged 40–69 years from England, Scotland, and Wales between 2006 and 2010, accounting for 5.5% of the UK population. Health-related outcomes of the participants are obtained regularly through linkage to multiple datasets . Specifin = 94), had no available primary care data , or died before 16 March 2020 , we included 401,180 participants registered in England in the study  declared the COVID-19 as a pandemic on 11 March 2020 and given the availability of COVID-19 related data in the UK Biobank, we defined the pandemic exposure period from 16 March 2020 to 31 August 2021. After excluding participants who withdrew from the UK Biobank . This present study was also approved by the biomedical research ethics committee of West China Hospital (2020.661).Diagnoses of anxiety and depression were retrieved from the UK Biobank hospital inpatient data (according to ICD-10 codes)  and primAccounting for the reported variations in psychological implications of COVID-19 pandemic among populations with different exposure level, we categorized the participants into three pandemic exposure groups, using the history COVID-19 testig as an indicator . As the testing status could change over time, the categorization was done in a time-varying manner, namely that all participants were in the “not tested” group on 16 March 2020, while those with a record of negative test result in PHE were moved to the “tested negative” group on the date of the corresponding COVID-19 test. Further, individuals not tested or tested negative could move to “tested positive” group on the date of a positive test result as recorded in PHE, or the date of a COVID-19 diagnosis  as documented in the UK Biobank inpatient hospital data, if any. Although the UK Biobank population is not representative of the entire UK population, we found largely similar trend in the daily number of COVID-19 cases in the study cohort as that in the whole England  of the incident diagnoses of anxiety or depression as well as prescriptions of psychotropic medications during the pandemic period, respectively. We then calculated the IRs by history of COVID-19 testing . The comparison between the pandemic and pre-pandemic periods was achieved by applying indirect standardization method to calculate the standardized incidence ratios  and their 95% confidence intervals (95%CIs). As psychological well-being may be influenced by seasonal variation, we further calculated the monthly SIRs during the 18-month pandemic period, using the average month-, sex-, and age-specific incidence rate of the studied outcomes from the pre-pandemic period as reference.Moreover, we performed separate analyses for anxiety and depression as well as for anxiolytics and antidepressants. In addition, to test the robustness of our results to severe somatic conditions, we repeated all analyses after excluding participants with severe somatic diseases  Table , 4 439 rThe analysis of seasonal variation showed a lower overall risk for incident diagnoses of anxiety or depression during the pandemic period when compared to the pre-pandemic period, except in June 2021 (1.30 [1.17–1.45]) and July 2021 (1.34 [1.20–1.49]) . However, the impact of such a concern, if any, should be constant throughout the whole study period, whilst the change in incident diagnoses and drug prescriptions for anxiety and depression was indeed time-varying, suggesting potential contribution of other causes, such as temporary psychological burden caused by COVID-19-related exposures or reduced social contacts. In addition, considering the overloaded healthcare system during the pandemic period, our outcome identification strategy  is likely to only capture patients with more severe psychiatric symptoms. Conditions for individuals with less severe symptoms who did not seek medical care need to be studied in future studies. Likewise, as our identification of COVID-19 cases relies solely on RT-PCR testing (but not self-tests which became available in UK since January 2021 ), indiviIn conclusion, the findings of this study suggest differential population mental health care utilization during the COVID-19 pandemic by level of pandemic exposure indicated by history of COVID-19 testing. Compared to the pre-pandemic period, we observed a decrease in incident diagnoses of anxiety and depression as well as prescriptions of respective psychotropic medications among individuals not tested for COVID-19, but an increase in incident psychiatric morbidity among those tested for COVID-19, irrespective of the test result, particularly at the beginning of COVID-19 pandemic.Supplementary


Type 2 diabetes mellitus (T2DM) has caused a huge clinical and economic burden worldwide. The management strategy of T2DM has been mentioned in many guidelines. However, controversy still exists in the recommendation of anti-hyperglycemic agents. To this end, this protocol has been written according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P). We will make an overview of systematic reviews based-on network meta-analysis firstly that report on safety and efficacy of different category of anti-hyperglycemic agents for T2DM patients. We will identify network meta-analysis by applying a robust and standardized search strategy within Embase, PubMed, Web of Science, and Cochrane Database of Systematic Reviews. Hemoglobin A1c (HbA1c) and fasting plasma glucose (FPG) will be defined as the primary outcomes. We will assess the methodological quality of included reviews by applying the A MeaSurement Tool to Assess Systematic Reviews (AMSTAR-2) tool, and quality of evidence for all outcomes will be judged by using the Grading of Recommendations Assessment, Development and Evaluation (GRADE). This will provide an accessible narrative synthesis to clinicians, patients, policy makers, and developers of clinical guidelines based on published high-quality network meta-analysis. We will submit our results for peer-review publication and presentation at domestic and international conferences. We will also disseminate our results through established clinical networks and consumer networks, using pamphlet where appropriate. Ethics approval is not required for this overview as we will analysis published network meta-analysis only.Trial registration number:INPLASY202070118. Diabetes is a chronic and progressive disease featured by the deterioration in blood glucose control over time. It has caused significant clinical and economic burdens worldwide . Twenty Type 2 diabetes mellitus (T2DM) is the most common type of diabetes, accounting for approximately 90% of diabetes worldwide. Globally, the prevalence of T2DM is estimated at 9% in the adult population, and it is rising across all regions ,6. This Ann Intern Med published the first network meta-analysis [In 2011, the analysis  on the canalysis –18. ThisSpecifically, the objectives we aim to access include: 1) make a narrative synthesis of the evidence to get an insight for different agent therapy strategy for T2DM, and 2) make an evidence map based on Grading of Recommendations Assessment, Development and Evaluation (GRADE) to guide the use of anti-hyperglycemic agents. To this end, the proposed overview of systematic reviews will answer the following questions: 1) What is the methodological quality of published network analysis in this field? 2) What are the efficacy and safety of various anti-hyperglycemic agents verified by systematic review based on network meta-analysis and which agents are suitable for patients with different risk stratification? 3) Based on GRADE hierarchy of evidence, what are the strength of evidence and recommendation level of the various agents included in the network meta-analysis?https://doi.org/10.37766/inplasy2020.7.0118).In accordance with the guidelines, the protocol for this overview of systematic reviews was reported with the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) 2015 checklist ,20. It wStudies will be selected based on the criteria listed below to identify multiple systematic reviews on related research questions in the same topic area . If the We will include peer-reviewed and published network meta-analysis of anti-hyperglycemic agents for T2DM which provide meta-estimates for outcomes. Both direct comparison and indirect comparison of network meta-analysis will be included. The network meta-analysis that is ongoing or published in the form of conference abstracts will not be included.We will limit our overview of systematic reviews to studies of adults with T2DM, regardless of gender, race, or the presence of insulin resistance. The pregnant women with gestational diabetes will be excluded.Comparisons among the following interventions were included: insulin, metformin, sulfonylureas, thiazolidinediones (TZDs), active comparator drugs (ACDs), dipeptidyl peptidase-4 (DPP-4) inhibitors, Glucagon-like peptide-1 (GLP-1) analogues or agonists, sodium/glucose cotransporter 2 (SGLT-2) inhibitors, α-glucosidase inhibitors, meglitinides, or placebo. There are no restrictions on the combination formula such as whether to plus other agents to metformin or sulfonylureas. There are also no restrictions on different doses or frequency of the same agent. We classify all eligible drugs according to the above drug categories and because different drugs in the same category may have a variable effect, we include studies that compare drugs in a same category either. If a network meta-analysis included drugs of interest but also included drugs that were not of interest, or if multiple interventions included glycemic control by non-pharmacological methods, such studies would also be included. Interventions includes some drugs but not any drugs of interest within the list except for comparator drugs will not be included.The primary outcomes are HbA1c and fasting plasma glucose (FPG). The second outcomes are body mass index (BMI), 2 h postprandial blood glucose (2HPPG), body weight and adverse events, including hypoglycemia, diarrhea, upper respiratory tract infection (URTI), hypersensitivity reaction (HR), cardiovascular outcomes, renal and hepatic toxicity ,24. The No restrictions will be placed on the original languages to which the literature will be included. Languages other than English and Chinese will be processed with the help of translation software tools or by seeking native speakers.diabetes and network meta-analysis. A researcher from evidence-based medicine center will create and run a search string to identify relevant articles. Take electronic databases PubMed which planned to be searched as an example, the pre-search strategy is presented in Table 1. The search strategy will undergo internal peer review. The research is expected to officially start in December 2022.Our overview will search for systematic reviews including network meta-analysis from the following databases: PubMed, Embase, Web of Science, and Cochrane Database of Systematic Reviews. Search terms include The retrieved articles from the databases were exported to EndNote X9 for duplicate removal and further categorization. The full text of eligible reviews will also be attached to EndNote X9.We will follow the recommendations in the Cochrane handbook for quality control and transparency of independent screening . Two autThe reviewers will extract the following data items from each included systematic review: 1) Bibliographic details . 2) Methodological characteristics . 3) Method of pooling and bias assessment . 4) Patient characteristics . 5) Results .Two reviewers will independently assess the methodological quality of included network meta-analysis using A MeaSurement Tool to Assess Systematic Reviews (AMSTAR-2) tool . The AMSThe quality of evidence for all outcomes will be judged using GRADE systems ,29. ThisThe strict criteria on which we will base our synthesis will ensure that only those systematic reviews based on network meta-analysis with a high quality contribute to the evidence . DisagreWe will consider the issue of overlapping primary studies prior to preparing our evidence synthesis. If there are multiple network meta-analysis that include the same agents in the same patient, and measure the same outcome, we will deal with overlapping primary documents by the following methods: 1) If the primary research completely overlaps (repetition rate ≥ 80% of any one of the article), then we will choose the highest quality review.2) If the primary studies partially overlap, and the repetition rate is between 50% and 80%, then we will retain both reviews if the lower-quality review consists of more than 30% new studies. 3) If the primary studies do not overlap (repetition rate ≤ 50%), then we will retain both reviews .We will present the findings as a narrative synthesis, and will take tabulated summaries and visualized evidenced map to display the data . The preThis study will be the first overview of systematic reviews based on network meta-analysis. We will use rigorous methodology to seriously and systematically appraise and synthesis published systematic reviews with network meta-analysis evidence. The results of the many network meta-analysis overwhelm readers, and we hope to be able to summarise and sort them out further for users of the evidence. It is a great ambition to perform a secondary combined analysis of the data from the numerous network meta-analyses, and our team did not consider a combined analysis of the data in this work. Based on the published network meta-analysis, the efficacy and safety of various anti-hyperglycemic agents will be systematically reviewed and validated, and used GRADE to validate the quality of evidence from different studies to identify the most suitable treatment options for T2DM patients in different risk strata. We will provide new commentary and higher levels of evidence for the harm and benefits associated with diabetes medications . The oveS1 Checklist(DOC)Click here for additional data file.


Over the last years, multidisciplinary pulmonary embolism response teams (PERTs) have emerged to encounter the increasing variety and complexity in the management of acute pulmonary embolism (PE). We aimed to systematically investigate the composition and added clinical value of PERTs.We searched PubMed, CENTRAL and Web of Science until January 2022 for articles designed to describe the structure and function of PERTs. We performed a random-effects meta-analysis of controlled studies (PERT vs. pre-PERT era) to investigate the impact of PERTs on clinical outcomes and advanced therapies use.We included 22 original studies and four surveys. Overall, 31.5% of patients with PE were evaluated by PERT referred mostly by emergency departments (59.4%). In 11 single-arm studies  mortality rate was 10%, bleeding rate 9% and length of stay 7.3 days [95% confidence interval (CI) 5.7–8.9]. In nine controlled studies there was no difference in mortality  by comparing pre-PERT with PERT era. When analysing patients with intermediate or high-risk class only, the effect estimate for mortality tended to be lower for patients treated in the PERT era compared to those treated in the pre-PERT era . The use of advanced therapies was higher  and the in-hospital stay shorter (mean difference − 1.6 days) in PERT era compared to pre-PERT era.PERT implementation led to greater use of advanced therapies and shorter in-hospital stay. Our meta-analysis did not show a survival benefit in patients with PE since PERT implementation. Large prospective studies are needed to further explore the impact of PERTs on clinical outcomes.Open Science Framework 10.17605/OSF.IO/SBFK9.The online version contains supplementary material available at 10.1007/s00392-022-02077-0. Acute pulmonary embolism (PE) is one of the most frequent cardiovascular emergencies and is of particular clinical relevance due to its life-threatening potential in case of cardiorespiratory decompensation . PatientThe “heart team” concept for multidisciplinary management of patients with challenging cardiovascular diseases is meanwhile established and is gaining increasing acceptance worldwide . OriginaThe objectives of the present scoping review and meta-analysis were: (1) to identify the published evidence regarding the implementation of PERTs in acute PE treatment, (2) to clarify the key characteristics in the structure, function and operating procedures of PERTs worldwide, and (3) to identify knowledge gaps concerning PERTs. The present review was performed according to the PRISMA extension guidelines for scoping reviews . The proA systematic search of MEDLINE (via PubMed), the Cochrane Central Register of Controlled Trials (CENTRAL) and Web of Science was performed up to 10 January 2022. A search string was created for PubMed and modified accordingly for the other databases (Supplement 1). To complement our search, all references from selected studies were retrieved and manually reviewed according to the snowball effect. No language restrictions were set.We considered full-text, prospective and retrospective observational studies, which included patients with acute PE evaluated by a PERT. Both controlled and uncontrolled (single-group) studies were eligible. In controlled studies, the  control group consisted of patients with acute PE who were treated before the implementation of a PERT. Eligible articles were designed to either describe the structure and function of PERTs and/or to investigate outcomes related to the implementation of a PERT. The main outcome was all-cause mortality . Additional outcomes were the occurrence of bleeding , 30-day rehospitalisation rates, length of hospitalisation, use of intensive care unit (ICU), length of stay in the ICU, use of advanced therapies ; the insertion of a vena cava [IVC] filter was also evaluated. We excluded case reports and non-peer-reviewed articles.Retrieved studies were imported into a reference management software (Mendeley version 1.19). After the removal of duplicated studies, two independent authors  at a first stage screened the titles and abstracts and at a second stage perused the full texts for eligible studies. A third author (LH) was consulted to resolve any discordance regarding eligibility of studies. All reasons for exclusion at the full-text study selection phase were reported.We created a predefined excel spreadsheet into which two authors  independently extracted data from eligible studies. A pilot test was performed before the formal initiation of data extraction to ensure coherence. Any disagreement was resolved by consensus. We extracted data regarding the study design of each study , site-specific characteristics of the PERT , baseline characteristics of the population  and outcomes (as described above). We performed a quality assessment of the eligible controlled studies using the ROBINS-I risk-of-bias tool for non-randomised studies of interventions .We performed a random effects model meta-analysis of controlled studies (DerSimonian and Laird method). The effect estimate was the risk ratio (RR) for binary outcomes and the mean difference for continuous outcomes, with corresponding 95% confidence intervals (CIs). Heterogeneity was assessed with the Cochran chi-square test and the I  statistiThe search strategy resulted in the retrieval of 292 studies after removal of duplicates. Among them, we identified 26 (8.9%) reviews, 17 (5.8%) letters or editorials and 39 13.4%) conference abstracts related to PERT implementation. After the complete study selection process, 26 studies were included in the final review and meta-analysis  , 33, 34.n = 1532 patients) reported outcomes for the subgroup of intermediate- and high-risk patients who were evaluated by a PERT  and CDT , but not for surgical thrombectomy , or ECMO . Use of IVC filters was less frequent in the PERT compared to the pre-PERT era .Use of advanced therapies (pooled rate) was more frequent in the PERT era compared to the pre-PERT era  [severe PE, comparison of outcomes in low-risk patients is of limited clinical relevance in this context [The direct impact of PERTs on patient outcomes remains uncertain to date, since no direct prospective comparisons have been performed. In a retrospective singe-centre study, in which 769 patients with acute PE were divided in two groups corresponding to PE management in the pre-PERT and PERT era, all-cause 30-day mortality rate was significantly lower in patients treated in the PERT compared to the pre-PERT era  . In the  context . Even if context , we focu context . In fact context , 44; theRegardless of the risk class, length of the general and the ICU in-hospital stay was lower in the PERT era as compared to the pre-PERT era. Although the length of hospital stay may be considered a rather subjective outcome as the criteria for discharge were likely different across sites, our results suggest that the implementation of PERT in an institution may provide confidence for earlier discharge in stabilised patients with acute PE. Besides, among patients with intermediate risk PE, patients who undergo invasive therapies have been shown to have a shorter length of stay in the hospital . The cosTreatment options for patients with acute PE have expanded ; thus a Our study has some limitations. First, several of the included studies were post-hoc analyses of existing cohorts, hence the results are purely observational and no cause-and-effect relationship can be established. Second, conclusions regarding clinical outcomes cannot be made due to the fact that the numerical analysis was only explorative. Third, not all controlled studies reported the outcomes of subgroups with intermediate- and high-risk PE separately, which reduced the power of the numerical analysis. Finally, the definition of intermediate- and high-risk PE was not standardised across studies, contributing to heterogeneity in the analysis.In conclusion, in our study we were able to analyse the association between PERT-based management and clinical outcomes in 9823 patients with acute PE. Our meta-analysis did not demonstrate an effect estimate on mortality in patients with intermediate- or high-risk PE of PERT implementation compared to the pre-PERT era. However, PERT implementation was associated with increasing use of advanced therapies and lower length of in-hospital stay. Our study should be considered hypothesis generating; large prospective observational studies are needed to further explore the impact of PERT teams on clinical outcomes and mortality in patients with acute PE.Supplementary file1 (DOCX 319 KB)Below is the link to the electronic supplementary material.


Myocarditis has been recognized as a rare complication of coronavirus disease 2019 (COVID-19) mRNA vaccinations. Young adult and adolescent males < 30 years of age are the most commonly affected group, with decreased incidence with older age. This is a case of a 48-year-old male who presented with chest pain and EKG findings of STEMI shortly after receiving the second dose of the Moderna COVID-19 mRNA vaccine. Emergent left heart catheterization revealed normal coronaries. Subsequently, the patient had rapid resolution of his symptoms and improvement in serum markers. The exact etiology factors to this new and rare phenomenon are yet to be fully understood. This patient did have a history of previous viral myocarditis 7 years ago; however, it remains unclear if this could be a predisposing factor to the development of mRNA vaccine-associated myocarditis. The coronavirus disease 2019 (COVID-19) messenger RNA- (mRNA-) based vaccines (BNT162b2 mRNA-Pfizer-BioNTech and the mRNA-1273-Moderna) have a relatively benign side effect profile; usually associated with local reactions, fatigue, and headache. A more severe adverse effect, myocarditis, has recently been recognized as a rare complication with higher incidence than expected, usually after the second dose of the 2-dose series. Young adult and adolescent males < 30 years of age are the most commonly affected group, with decreased incidence with older age [A 48-year-old male presented to the emergency department with acute-onset typical chest pain. He reported having fevers, fatigue, and chills for the past 3 days which began shortly after receiving the second dose of the Moderna COVID-19 mRNA vaccine. Vital signs were within normal limits, his weight was 83 kg with a BMI of 30.5, and the rest of his general and cardiorespiratory physical exam were largely unremarkable. His medical history was one of health; however, 7 years prior, the patient was diagnosed with viral myocarditis after a flulike illness which resolved with supportive management and the patient had no sequelae. That episode was characterized by acute-onset chest pain consistent after having severe flulike symptoms for 1 to 2 weeks, elevated troponins, and no ischemic changes on EKG. A left heart catheterization with coronary angiography was done revealing normal and patent coronary arteries, and the specific offending virus was not identified. He was of Hispanic ethnicity and a lifelong nonsmoker and reported only rare alcohol consumption on social occasions. He worked in construction management, exercised one to two times per week, and had a family history positive for coronary artery disease.Upon his current presentation, the patient was found to have ST elevations in the lateral leads  and was The next day, he had resolution of the chest pain along with resolution of his flulike symptoms. Troponins and CRP were trending down. He denied any dyspnea on exertion and subjectively felt that he was back in his usual state of health. Left ventricular biplane function ejection fraction on echocardiogram was similar to that estimated by ventriculography, and no pericardial effusion or thickening was noted. He was started on guideline-directed medical therapy with metoprolol succinate 25 mg, ramipril 2.5 mg, and atorvastatin 40 mg daily and was discharged after extensive counselling. At 3-month follow-up, the patient was feeling well with no symptoms of chest pain or shortness of breath including with exertion.In the current literature, patients with mRNA vaccine-associated myocarditis invariably presented with chest pain, usually 2 to 3 days after second-dose mRNA vaccine and had elevated cardiac troponin levels. Data from the largest study to date from Israel found that the estimated incidence of myocarditis was 2.13 cases per 100,000 persons, with the highest incidence among male patients between the ages of 16 and 29 years. Most cases of myocarditis were mild or moderate in severity. STEMI was the most common electrocardiographic presentation [In this case, the presentation and clinical course are compatible with those of majority of COVID-19 mRNA vaccine-associated myocarditis. Endomyocardial biopsy was not indicated due to the absence of acute-onset heart failure, hemodynamic compromise, ventricular arrhythmias, high-degree AV block, or failure to respond to medical therapy . CardiacOnly a few reports of acute thrombotic events post-mRNA COVID-19 vaccines exist and Kounis syndrome has been suggested as the pathophysiology. This along with temporally coincidental acute plaque rupture is an important differential diagnosis with life-threatening consequences if not promptly diagnosed and treated –6. More As mRNA vaccine-associated myocarditis is a new phenomenon in clinical practice, there are many gaps in our understanding of the disease. Future research studies are needed to investigate the mechanism of development of mRNA vaccine-associated myocarditis, to explore predisposing factors for the development of myocarditis related to COVID-19 vaccines, and to provide guidance to those who have suffered this myocarditis on the safest future vaccination/booster strategy. This case also highlights the need to investigate if prior viral myocarditis is a predisposing factor to development of mRNA vaccine-related myocarditis.


The fall in non-coronavirus disease 2019 (non-COVID-19) respiratory viruses, including seasonal influenza, during the pandemic is well reported [1–4]. It is thought to be a result of a combination of social distancing, lockdowns, improved hand hygiene and potentially virus–virus interactions and cross-protection affecting population dynamics. However, as vaccines weaken the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), clinicians remain vigilant for a potential resurgence of other respiratory pathogens and the implications of an ongoing rise in new SARS-CoV-2 variants. There was a significant reduction in pleural infection incidence, by almost a third, in the year following the start of the #COVID19 pandemic. Public health measures enforced during this period are likely to have played a significant role.https://bit.ly/3QAPPR9 To the Editor:The fall in non-coronavirus disease 2019 (non-COVID-19) respiratory viruses, including seasonal influenza, during the pandemic is well reported . It is trnoldet al. [A huge rise in pleural infection cases is well documented following the influenza pandemic in 1918  and a redet al.  also fouPleural effusions have been noted in only a minority of severe COVID-19 cases (up to 5%) . To dateThe study was conducted through a network of geographically diverse specialist pleural units across the UK actively recruiting to a prospective multicentre randomised controlled trial (RCT), the third Multicentre Intrapleural Sepsis Trial . The five centres were continuously screening for cases of pleural infection within their services and had dedicated pleural multidisciplinary team (MDT) meetings that captured and recorded all pleural infections across their services as standard practice.Two comparative periods were chosen as March 2020 to February 2021 (post-COVID), to represent the study cohort, against the same period before the COVID-19 pandemic  as a control cohort. A retrospective review of screening logs and case notes was conducted.The primary outcome measure was the difference in incidence (number of confirmed cases) of pleural infection admissions between the two time periods. Secondary outcome measures included the following: comparison of patient demographics; interval between symptoms onset and presentation; incidence of pleural infection during the influenza season; the effect of immunosuppression ; radiological evidence of pneumonic consolidation and/or COVID-19 infection (according to the reporting radiologist); and microbiological profile. As clinical outcomes would be skewed by involvement of the study cohort in the MIST-3 study, which involves early randomisation to one of three study intervention arms , these were not evaluated. In the study cohort, data on COVID-19 PCR positivity was also collected. As this was a retrospective analysis, patient consent and research ethics committee approval were not required.To be included, the patients had to be adults aged ≥18 years) with a diagnosis of pleural infection based on standard, internationally agreed criteria  years wi). These Statistical analyses were conducted using simple descriptive statistics. Continuous variables were reported as mean and standard deviation. Comparisons of proportions were conducted using the Pearson's Chi-squared test (p<0.05). The analyses were conducted using SPSS .versus 124 new cases in the 1-year period following the start of the pandemic. This equated to a decrease of 32.61% in admissions between the two years , immunosuppression and median RAPID score ) were similar in both groups with no statistically significant differences in the two time periods studied. The median interval between symptoms onset and hospital attendance was slightly longer in the post-COVID cohort (14 versus 10 days) but did not reach statistical significance (p=0.16). All patients had computed tomography scans and none of these showed evidence of co-existent COVID-19 pneumonia.Patient demographics  showed 46 out of 184 (25%) in the pre-COVID period, and 15 out of 124 (12.1%) cases during those 3 months in the post-COVID period. This difference was statistically significant , p=0.005).versus 50 out of 184 (27.2%); p=0.04) and culture-positive infections (48 out of 124 (38.7%) versus 49 out of 184 (26.6%); p=0.03) were observed in the post-COVID period. The species of microorganisms isolated on pleural fluid culture were similar in both cohorts.Greater proportions of pleural fluid purulence (49 out of 124 (39.5%) SARS-CoV-2 PCR positivity was seen in nine out of 124 (7.25%) patients in the post-COVID cohort.We present, to our knowledge, the first study examining the impact of COVID-19 on the incidence and profile of pleural infection. Epidemiological studies have suggested that the incidence has steadily increased year-on-year in the last decade –12. In tThe low rate of co-existent COVID-19 PCR positivity 7.25%) and the absence of radiological evidence of COVID-19 pneumonia in any of the pleural infection cases are in keeping with the literature, which suggests that empyema does not appear to be frequently associated with COVID-19 pneumonia [.25% and Compared to previous influenza pandemics, it is noteworthy that during the COVID-19 peaks, antibiotics were used sparingly to cover secondary bacterial infections, and this may have helped prevent empyema complications.The potential role of public health measures in reducing pleural infection incidence is intriguing and one that has not been specifically explored in the existing literature. It is highly likely that decreased social mixing, shielding of older, more vulnerable patients with additional comorbidity, often at increased risk of pleural infection, as well as social distancing measures have had, in combination, a beneficial impact.There were some limitations to this study. Being retrospective, it is bound by the validity and bias limitations of such a study design. However, the regular prospective screening procedures in place as part of recruitment to the MIST-3 study and the prospective documentation of pleural infection cases through the weekly specialist MDT meetings at the participating centres are likely to have been more robust methods of capturing cases compared to hospital episode statistics or administrative databases. These data only capture patients admitted to hospital and therefore cannot exclude that a proportion of patients chose to be treated in the community to avoid catching COVID-19 in hospital. The impact of vaccinations remains unclear. It also remains to be seen whether pleural infection incidence will return to pre-pandemic levels as enforcement of public health measures is relaxed.This study demonstrates a reduction in pleural infection incidence, by almost a third, following the start of the COVID-19 pandemic. Potential causes for lower rates of pleural infection may be secondary to reduced community transmission of viruses due to social distancing and use of personal protective equipment in both community and healthcare settings.


COVID-19 pandemic is one of the factors that can increase anxiety and stress levels in pregnant women. Anxiety reduces the maternal-infant attachment. Mother-infant attachment can play an important role in maternal competency. The aim of this study was to predict effect of COVID-19 anxiety during pregnancy and the postpartum period on the maternal competency with mediating role of maternal-infant attachment.A prospective longitudinal study was conducted on 253 pregnant women in the third trimester of pregnancy that referred to the health centers of Iran University of Medical Sciences and met the study inclusion criteria. Demographic questionnaire and the COVID-19 anxiety scale completed during the third trimester of pregnancy and after the delivery and Müller's mother-infant attachment and maternal competency questionnaire completed at 48 h and 6 weeks after delivery by self-report method. Smart partial lease square version 3 was used to assess the validity and reliability of the model and the relationship between the variables.The findings of this study demonstrated that the COVID-19 anxiety during postpartum had a significant negative effect on the maternal-infant attachment (β = −0.183). Also, the maternal-infant attachment had a significant positive effect on the maternal competency (β = 0.48). Moreover, the conceptual model had good validity, reliability, quality and fit. And also the two variables of anxiety and mother-infant attachment together explained 25% of maternal competency.Mothers experience higher levels of the COVID-19 anxiety during pregnancy and postpartum; therefore, it is recommended that particular attention should be given to the psychological support of pregnant women during the COVID-19 pandemic and quarantine. Also, the COVID-19 anxiety during the postpartum period had a negative effect on the maternal-infant attachment and competency, which necessitates the need for the support of mother-infant relationship and providing the online training to promote the maternal-infant attachment patterns and maternal competency during the COVID-19 pandemic. Competence, Maternal-infant attachment, Anxiety, COVID-19. Recent studies show that pregnant women appear to be more susceptible to severe COVID-19 illness compared to non-pregnant women , 4. COVIAnxiety causes the mother's inappropriate responses to the fetus during pregnancy and reduces the maternal-infant attachment. Mothers who were less attached to their fetus have higher levels of anxiety and depression, which can result in pregnancy complications . PsycholThe first hour after birth is a sensitive period for the development of the maternal-infant attachment. There is evidence that postpartum anxiety is associated with poor maternal compromise and low self-esteem and affects the maternal attachment . Severe Stress during pregnancy reduces the maternal attachment and is associated with impaired parenting behaviors . MaternaCOVID-19 has led to significant changes in almost every aspect of daily life. These changes may expose pregnant women, maternal –infant attachment and mother hood. And also there is not enough study about COVID-19 anxiety and maternal –infant attachment and maternal competency, aim of this study was to explore the effects of COVID-19 anxiety during pregnancy and the postpartum period on the maternal competency with mediating role of maternal-infant attachment using the structural equation modeling (SEM).H1COVID-19 anxiety during pregnancy has effect on the maternal competency.H2COVID-19 anxiety during the postpartum has effect on the maternal competency.H3COVID-19 anxiety during pregnancy has effect on the maternal-infant attachment.H4COVID-19 anxiety during the postpartum has effect on the maternal-infant attachment.H5maternal-infant attachment has effect on the maternal competency.The conceptual model was used to test the following hypotheses .H1COVID-2This study was prospective longitudinal study that approved by the Ethics Committee of Alborz University of Medical Sciences with code (IR.ABZUMS.REC.1399.235). Participants were selected from the health centers of Iran University of medical sciences that had the most clients and were the middle class. Participants were received written and oral information about the study, and written informed consent was obtained from them. They were free to decline participation or to withdraw at any time of study. All methods were performed in accordance with the relevant guidelines and regulations.2.1This study was conducted on 253 pregnant women in the third trimester of pregnancy who were referred to the health centers of Iran University of medical Sciences from January to July 2021 and met the study inclusion criteria include: Pregnant women during the COVID-19 pandemic and the third trimester of pregnancy (weeks 28–40), having no history of disabilities. The Mothers with a history of psychiatric disease. Mothers with high-risk pregnancies , mothers with infants with congenital anomalies and mothers with COVID-19 are excluded from study.The participants were selected using the multi-stage sampling. In the first stage, the health centers of Iran University of medical sciences from each region as districts (clustered sampling) were selected then we consider health centers that had the most clients and were the middle class based on zoning of the municipality (simple random sampling). In the third stage, the eligible pregnant women through integrated health system were selected using the convenience sampling. Given the association between COVID-19 anxiety and maternal competency, the Pearson's correlation coefficient is at least (r = 0.2) . With a First, a list of pregnant women was prepared, and then the researcher contacted the eligible women. The study objectives were explained to them. The demographic questionnaire and the COVID-19 anxiety scale were completed in third trimester of pregnancy. The pregnant women were followed up until the delivery to assess the pregnancy and labor complications. After that, the COVID-19 anxiety scale, Müller's mother-infant attachment questionnaire were completed at 48-hour and maternal competency questionnaire were completed at 6-week after delivery. The questionnaires in the Google form format were completed by the social media platform, and also in case the mothers did not have access to social networks, they were asked to present to complete the questionnaires by the coordination by phone.2.22.2.1Corona disease anxiety is defined as a feeling of worry, anger, or dissatisfaction with Covid 19 with an uncertain outcome, this questionnaire was used during pregnancy and post -partum. Corona-related anxiety is an 18-item tool on a Likert scale from zero to 3. Each participant receives a score from 0 to 54. it measure corona-related anxiety in two dimensions, psychological and physical symptoms. The validity and reliability of this questionnaire have been assessed in Iran by Alipour et al. Moreover Cronbach's alpha coefficient for psychological symptoms as (α = 0. 879), physical symptoms as (α = 0. 861), and for the whole questionnaire as (α = 0. 919) . In this2.2.2The MAI measures of maternal affectionate attachment. Müller Maternal Attachment index (MAI) was developed by Müller in 1994. It is contains 26 items that are scored from almost never . Its val2.2.3PSOC in this study measures new mothers' beliefs, values, and perceived skills regarding being a mother. Gibaud-Wallston .The study was approved by the Data will be made available on request.The authors declare no conflict of interest.No additional information is available for this paper.