Coronavirus disease-19 (COVID-19) is caused by severe acute respiratory syndrome coronavirus-2 (SARSCoV-2). Specimen quality, and proper transportation is vital for accurate diagnosis. This standard operating procedure is designed to educate the clinicians, nurses, paramedics, and laboratory personnel regarding proper methods of sample collection, packaging, and transportation. Nasopharyngeal swabs and/or oropharyngeal swabs should be collected for real-time quantitative polymerase chain reaction to detect SARS-CoV-2. The sample should be collected wearing proper personal protective equipment, packed in a triple packaging system, and transported maintaining cold chain. These include structural proteins, including envelope glycoprotein spikes (S), envelope (E), transmembrane (M), helicase (Hel) and nucleocapsid (N). In addition to these genes that encode structural proteins, there are species-specific accessory genes that are required for viral replication. These include RNA-dependent RNA polymerase (RdRp), hemagglutinin-esterase (HE) and open reading frames ORF1a and ORD1b. Centre for disease control and prevention (CDC) recommends two nucleocapid protein targets (N1 and N2) while WHO recommends first line screening with E gene assay followed by a confirmatory assay using RdRp gene. Specimen quality, and maintenance of cold chain during transportation is vital for accurate result. False negative results occur due to improper timing of specimen collection and shortcoming in sampling proficiency, especially of nasopharyngeal swabs.6 Collecting the proper respiratory tract specimen at the right time from the right anatomic site is essential for a prompt and accurate molecular diagnosis of COVID-19. Appropriate measures are required to keep laboratory staff safe while producing reliable test results. Hence, this standard operating procedure (SOP) is designed to educate the clinicians, nurses, paramedics, and laboratory personnel regarding proper method for sample collection, packaging, and transportation.Coronavirus disease-19 (COVID-19) is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Upon sequencing, the genomics of this novel coronavirus was found to share 79.5% homology to the genetic sequence of the SARS-CoV and therefore, the International Committee of Taxonomy of Viruses, renamed it as SARS-CoV-2. Meanwhile, the disease caused by the virus was named COVID-19 (Coronavirus disease 2019) by World Health Organization (WHO). WHO declared that COVID-19 should be characterized as pandemic on March 11, 2020. The clinical manifestation of COVID-19 includes fever, dyspnea, fatigue, dry cough, myalgia, headache, and loss of taste or smell. For severe and critical cases, patients suffer from acute respiratory distress syndrome, respiratory failure, and other serious complications including death. Within 5-7 days of infection, patients with COVID-19 demonstrate high viral load in upper respiratory specimens.8 Collecting both NP and OP swab has shown to improve sensitivity by upto two-fold. Sputum, bronchoalveolar lavage, and endotracheal aspirate specimens have higher sensitivity, but not collected routinely due to invasiveness of procedure and inconvenience.8 In case of patients presenting with acute respiratory distress, and requiring intubation, lower respiratory sample should be collected during intubation.9 If personal protective equipment can't be utilized due to scarcity of such PPE, other means of collecting upper respiratory tract specimens will be needed. One alternative option for collecting an upper respiratory tract specimen to evaluate patients with suspected COVID-19 is a self-collected saliva specimen. Repeated testing may be particularly be important if a patient has a clinical picture of viral pneumonia, a potential exposure history, and/or radiographic findings consistent with COVID-19 pneumonia.The performance of PCR depends upon several factors such as sample type, different stage of infection in patient, the skill of the collection, and the quality and consistency of the PCR assays being used. A nasopharyngeal specimen is the preferred choice for swab-based SARS-CoV-2 testing, but oropharyngeal sample should also be collected whenever feasible.Viral transport medium (VTM), swab sticks, ice-box, ice-pads, tongue depressor, marker, requisition form, and personal protective equipment (PPE) are needed beforehand. VTM contains 3 ml fluid composed of gelatin and antimicrobial agents in a buffered salt solution. It helps to prevent the specimen from drying, maintains the viability of the virus, andavoids the growth of contaminants. Swabs should be made up of rayon or dacron with plastic shaft. Cotton or calcium alginate swabs should not be used since it may inhibit PCR reaction. Stick with wooden shaft may cause trauma during sample collection. Ice-box and ice-pads are required for maintaining cold-chain during sample transportation. The ice-pads should be filled with water and stored in the freezer (-20°C) after before and after use.11Before beginning the procedure, the requisition form should be filled properly with patient details, travel history, contact history, and contact number of patient and the doctor. A proper PPE comprising of N95 mask, face shield, gown, goggles, shoe cover, and cap should be worn since sample collection is an aerosol-generating procedure. It is essential that we follow the pertinent respiratory and contact precautions certified by the Centres for Disease Control and Prevention and by our own institution and that we put on the PPE correctly. If possible, we should put on and take off the PPE in the presence of an observer to make sure there are no breaks in technique that may pose a risk of contamination.12Firstly, we need to ask the patient to take off their mask and blow the nose into a tissue to clear the nasal passage. Then, slowly tilt the patient's head back slightly to access the nasal passage. We need to inform the patient to close their eyes to mitigate the displeasure of the procedure. After that, gently insert the swab along the nasal septum, parallel to the floor of the nasal passage, until resistance is felt. The swab should be left in place for few seconds to absorb secretions and then slowly remove while rotating it. In order to properly obtain an NP swab specimen, the swab must be inserted deeply into the nasal cavity and should elicit “tears”. Patients will likely flinch, but that means the swab has hit the target. Finally, the swab should be placed in the VTM and shaft should be broken.13For collecting oropharyngeal swabs, we need to ask the subject to open his or her mouth wide open. The tongue should be depressed using a tongue depressor and the posterior pharynx behind the tonsils should be swabbed, avoiding the tonsils. The OP swab should elicit a gag reflex, but there is much person to person variability in the gag response. Swabs should be kept in place for 10 seconds while twirling the swab three times. The collected swab should be placed into the same VTM and shaft needs to be broken. Swabs should have flocked non-toxic synthetic fibers such as polyester as well as synthetic nylon handles. Collecting a NP/OP swab specimen may carry a theoretical risk of transmitting theSARS-CoV-2 particularly if airborne transmission should be demonstrated as the investigation of the COVID-19 outbreak continues. After completing the procedure, the tongue depressor should be disposed properly in biohazard container. The swab should be placed immediately into the same VTM and shaft needs to be broken.14The sample should be safely packed in a triple-packing system which consists of three layers. For the first layer, the plastic pouch which the VTM came in, can be used. The labeled VTM should be placed inside the pouch and sealed with adhesive tape. If the cover is not available, a small-size zip-lock bag should be used. The packed VTM should be placed inside another zip-lock bag which acts as the second layer. Finally, the package should be inserted into a solid, unbreakable, leak-proof outer container which severs as the third layer. The VTM, zip-lock bag and the outer container should be labelled properly.13The specimen should be transferred to the laboratory maintaining cold chain (2-4°C) throughout. The packed specimen should be placed inside the ice-box; two ice-pads should be placed on both sides of the container. The ice-box should be cleaned thoroughly outside with 1 % sodium hypochlorite and transferred to the laboratory as soon as possible with prior communication. If there is delay of more than 72 hours, sample should be stored at -70°C. Specimen data forms, letters, and other types of information that identify or describe the specimen for testing of SARS-COV-2 should be carried separately.None.


The COVID-19, novel coronavirus or SARS-Cov-2, has claimed hundreds of thousands of lives and affected millions of people all around the world with the number of deaths and infections growing exponentially. Deep convolutional neural network (DCNN) has been a huge milestone for image classification task including medical images. Transfer learning of state-of-the-art models have proven to be an efficient method of overcoming deficient data problem. In this paper, a thorough evaluation of eight pre-trained models is presented. Training, validating, and testing of these models were performed on chest X-ray (CXR) images belonging to five distinct classes, containing a total of 760 images. Fine-tuned models, pre-trained in ImageNet dataset, were computationally efficient and accurate. Fine-tuned DenseNet121 achieved a test accuracy of 98.69% and macro f1-score of 0.99 for four classes classification containing healthy, bacterial pneumonia, COVID-19, and viral pneumonia, and fine-tuned models achieved higher test accuracy for three-class classification containing healthy, COVID-19, and SARS images. The experimental results show that only 62% of total parameters were retrained to achieve such accuracy. COVID-19 , novel coronavirus or SARS-CoV-2, is a human coronavirus within the virus family Coronaviridae, order Nidovirales, which are multi-lipid, enveloped non-segmented, single-strained, positive-sense RNA viruses named after corona or crown-like surface projections [COVID-19 patients develop common symptoms like fever, dry cough, myalgia, fatigue, dyspnea, and anorexia at onset of illness. In due course of time, these symptoms progress to acute respiratory distress syndrome (ARDS), arrhythmia, and shock . X-rays AI researchers have contributed a lot in the field of data processing. Advances in AI have the potential in transforming the field of medicine since medical diagnostics and treatments are fundamentally a data problem. Deep learning, a sub-field of machine learning, automatically extracts detailed features from data which has proven to be highly efficient in various data processing task. Deep learning has become a prominent solution for a wide variety of natural language processing (NLP) or text processing, speech recognition and synthesis, signal analysis, and computer vision tasks. CNNs, multilayered neural networks, play a pivotal role in various digital image processing tasks such as feature extraction, pattern recognition, segmentation, object recognition, classification on various types of images including medical images. Deep learning demands plethora of data to achieve acceptable result and is resource hungry. To overcome this difficulty, a machine learning technique, transfer learning, was introduced. Transfer learning re-purposes a model trained on one task on a second related task. Pre-trained models are easily re-trained on smaller data with lesser trainable parameters to achieve higher accuracy. Depending upon the data and model selected, pre-trained models are fine-tuned to attain fine result.Several machine learning algorithms have been used for automatic classification of digitized medical images. Machine learning recognizes patterns to compute image features suitable for detection, diagnosis, or classification tasks. Machine learning algorithms can be classified on the basis of training styles: supervised, unsupervised, and reinforcement learning. Supervised learning involves gaining experience by using images that contain useful information and applying the gained expertise to predict on unseen new images (test data). Examples of supervised learning algorithms include support vector machine (SVM), decision tree, linear regression, logistic regression, naive Bayes, k-nearest neighbor (k-NN), random forest, AdaBoost, and neural network methods. In unsupervised learning, data are processed with a goal of separating the images into groups. Since the algorithm does not have information regarding the groups, it automatically determines the number of groups and a way to separate them. Examples of unsupervised learning algorithm systems include K-means, hierarchical clustering, density-based spatial clustering of applications with noise (DBSCAN), Markov random fields (MRF), iterative self-organizing data (ISODATA), and fuzzy C-means (FCM) systems. Like supervised learning, reinforcement learning begins with a classifier that was built by using labelled data. However, the system is then given unlabelled data, and it tries to further improve the classification by better characterizing these data similar to unsupervised learning. Examples of reinforcement learning algorithm systems include Monte Carlo methods and temporal difference (TD) algorithms . SeveralDeep learning is a new and powerful data oriented machine learning method, which utilizes a range of neural network architectures to perform various imaging tasks, like object  detection, segmentation and classification. Deep learning methods differ from the conventional machine learning methods , k-NN, naive Bayes, and random forest, etc.) in one major sense: The latter rely on feature extraction methods to train the algorithm, whereas deep learning methods extract feature automatically to learn the image. Evaluated on the 150 validation images from the ISIC 2017 classification challenge for skin lesion classification, a fusion of three pre-trained deep models, AlexNet, VGG16, and ResNet-18, as deep feature generators yielded an area under receiver operating characteristic (ROC) curve of 83.83% for melanoma classification and of 97.55% for seborrheic keratosis classification . RecurreA four convolutional layered CNN was employed for binary classification of presence of pneumonia based on a total of 5856 X-ray images of anterior–posterior chests from retrospective pediatric patients of which 3722 images were allocated to the training set and 2134 images to the validation set. The images were augmented using various techniques like rescale, rotation, shift, shear, zoom, horizontal ip, etc. The network achieved a validation accuracy of 93.73% on input data of size }200×200 . Classif}200×200 . Deep le}200×200 . COVID-N}200×200 . Covidx-}200×200 . A total}200×200 .In this work, we employ data-driven deep learning technique, convolutional neural network (CNN). Since its introduction by Lecun and due to its unrivalled performance in 2012 ImageNet challenge achieved by AlexNet, CNN has become a prominent technique in image processing tasks. Deep learning or data-driven approaches, in general, require abundance of data to generalize from training data and discover viable feature sets and decision criteria, and finally extract meaningful results. Various state-of-the-art deep learning models such as VGG-16, and VGG-19 , ResNet In 2014, Oxford’s Visual Geometry Group (VGG) developed and trained a 16 convolutional layered deep convolutional network for object recognition called VGGNet. Different versions of VGGNet were introduced like VGG11, VGG11 (LRN), VGG13, VGG16 (Conv1), VGG16,, and VGG19. VGG19 is 19 layers deep with each layer using a filter of size Szegedy et al.  proposedAt the ILSVRC 2015, Residual Neural Network (ResNet) by He et al.  introducResNet50 is a 50-layer deep neural network. Figure The need for smaller model size suitable for real-time analysis in resource constrained mobile devices led to the development of MobileNet , which uDense blocks were firstly proposed by Huang et al. in DenseNet  that intGoogle Brain designed a search space, called NASNet search space, which decouples the complexity of an architecture from the depth of the network, thus resulting in transferable and scalable network called Neural Architecture Search Network (NASNet). NASNet comprises of two types of cells: normal cell that returns a feature map of the same dimension and reduced cell that returns a feature map where the feature map height and width is reduced by a factor. NASNetMobile , also reTransfer learning is a machine learning technique that involves reusing an existing, trained neural network, developed for one task, as the foundation for another task. Transfer learning removes the necessity of large training data for a task as the basic features required to train a model are imported from previous task. In DNN, each layer generate a sequence of representations of the data. For an image recognition network, the early layers in the CNN capture the simplest features of the data that are universal such as the presence of edges, contours, or gradients in color and can be reused for similar tasks, while later layers capture more complicated which are highly data dependent and needs to be re-trained. The main challenge of transfer learning is to retain the existing knowledge in the model while adapting the model to new task which gives rise to the problem of the number of layers or parameters required to be re-trained to achieve optimal result.Transfer learning involves firstly finding the suitable pre-trained model, secondly, replacing the final layer of the model according to the number of output layers for the new task and finally, resume training the model with new data and fine-tuning the model till the accuracy converges towards higher value.Deep neural network is a stack of layers where each hidden layer extracts meaningful features automatically. This feature of DNNs is utilized in transfer learning. Transfer learning is employed whenever the amount of training data is smaller in number. Transfer learning is done either by training a model from scratch on a suitable huge dataset and retraining the model on desired smaller dataset or using a pre-trained state-of-the-art models. The former exploits lot of resources and time as designing a model, creating a huge dataset and then finally training them is tiresome. However, using state-of-the-art model pre-trained on standard dataset reduces lots of computational cost.Since collecting large amount of medical images is difficult due to data privacy concerns, transfer learning is opted as a suitable solution. Transfer learning makes use of reusable features by using the concept of layer freeze. Since each layer outputs some features in DNN, spotting the layer best suited for extracting the reusable feature is delicate. Freezing a certain portion of network that best provides the features which can be used in new domain is the basic principle of transfer learning. However, employing transfer learning on models pre-trained in ImageNet demands the replacement of final output layer with the new layer suited for the new task. The network can be either trained by freezing all the layers except the final layers which is termed as feature extractor or freezing a portion of network for best results which is termed as fine-tuning. We opted for fine-tuning instead of feature extractor for higher accuracy in expense of slightly higher computational cost . Fine-tuThe dataset used is a collection of two subsets from two different dataset, COVID-19 dataset  created The chest X-Ray contains images collected from various patients all around the world. A total of 744 images, equally split over four classes , were used for classification. The CXR C contains a total of 388 X-ray images from three different classes . Data are split similar to second scenario. While CXR A and B have balanced data, data in CXR C are highly imbalanced. The imageset contains AP (anterior–posterior) and PA (posterior–anterior) CXR images. L  X-ray images are discarded for the experiment. These x-rays were taken either erect (standing or sitting) or supine position. Few of the X-rays contain images from patients with chest port inserted in them. While most of the chest X-ray images were taken from different patients all around the world, COVID-19 dataset contain some X-rays from a single patient over a course of time, i.e., x-rays from day 1, day 8 and day 13.A detailed information about the images is shown in Table Transfer learned eight different state-of-the-art models pre-trained on ImageNet achieved 97.37% test accuracy on CXR A dataset. Fine-tuned DenseNet121 outperformed other models by achieving 98.69% test accuracy on CXR B dataset. Table Table In this work, various fine-tuned state-of-the-art deep learning models pre-trained on ImageNet, were compared for efficient classification of chest X-ray images. These models effectively classified healthy, bacterial, viral, COVID-19 and SARS diseases based on CXR images. Fine-tuned models achieved validation accuracy of 100% on all CXR dataset, 100% test accuracy on CXR C, 97.37% of test accuracy on CXR A dataset and 98.69% of test accuracy on CXR B dataset by fine-tuned DenseNet121. DenseNet121 outperforms all models in terms of precision, recall, f1-score, and accuracy, thus, it is proven to be the most effective model for the specific classification task, and the specific data sample.All the models were pre-trained on ImageNet dataset. ImageNet demonstrated to be a reliable source domain for transferring learned features on CXR disease classification. The models performed well for classification of healthy and disease X-ray images of COVID-19, SARS diseases. Dataset CXR A and CXR B had equal number of images per class while CXR C dataset had unbalanced data with one class sparse amount of data. This signifies that transfer learning method works well with unbalanced and small dataset.Using the concept of block freeze instead of layer, reduced the time required to pinpoint the layer that gives higher accuracy with less number of trainable parameters. Splitting the data into 80% for training and 20% for testing instead of 90% and 10% for training and testing respectively gives higher accuracy and f1 score. This study explored various deep learning models and transfer learning techniques by creating and comparing their efficacy on CXR images for COVID-19 classification, while keeping computational demands small. This model can be used as preliminary test for COVID-19 detection.


Correction to: Clin Epigenet 12, 64 (2020)https://doi.org/10.1186/s13148-020-00857-xAfter the publication of the original article , an erroThe sentence currently reads:Data generated during this study are included in this published article, and its supplementary information files or available from the corresponding author on reasonable request.The sentence should read:Data generated during this study are included in this published article and its supplementary information files and have been deposited on GEO, accession number GSE143850.


Extending the public knowledge base of activity cliffs (ACs) with new categories of ACs having special structural characteristics.Dual-site ACs, isomer ACs and ACs with privileged substructures are described and their systematic identification is detailed.More than 7400 new ACs belonging to different categories with activity against more than 200 targets were identified and are made publicly available.For dual-site ACs, limited numbers of isomers are available as structural analogs for rationalizing contributions to AC formation. The search for such analogs will continue. In addition, the target distribution of ACs containing privileged substructures will be further analyzed. Activity cliffs (ACs) are formed by small molecules that have very similar structures, are active against the same biological target, but have a large difference in potency against their target. Accordingly, ACs are of interest in medicinal chemistry because they reveal small structural changes that greatly influence the potency of active compounds. This information can be used for compound optimization. Computational methods are applied to search for ACs in large compound databases. Here, we further extend the public AC knowledge base with new categories of ACs having special structural characteristics. i) values are reported.Shown are an exemplary dual-site activity cliff (AC) (top), isomer AC (middle) and an AC containing a privileged substructure (bottom). Structural differences between AC compounds are highlighted in blue and the privileged substructure is colored pink. Compound targets and potency (pK Activity cliffs (ACs) are defined as pairs or groups of structurally similar  compounds that are active against the same target but have a large difference in potency . ACs havFor formally defining ACs, molecular similarity and potency difference criteria must be specified . Similari values) as potency measurements is generally preferred over assay-dependent measurements such as IC50 values. The use of Ki values makes it possible to compare ACs for a given target and across different targets in a meaningful way.Furthermore, for defining ACs, constant potency difference thresholds can be applied across different compound activity classes  ,3. AlterConsidering the evolution of the AC concept in medicinal chemistry , we haveSimilarity criterion: numerical or substructure-based similarity.Potency difference criterion: constant potency difference threshold across all activity classes.Similarity criterion: MMP formation .Potency difference criterion: variable activity class-dependent potency difference thresholds.Similarity criterion: structural analogs originating from the same AS (with single or multiple substitution sites).Potency difference criterion: variable activity class-dependent potency difference thresholds.Previously, we have generated a large collection of second generation ACs ,17 and mFor nearly 100 different activity classes, each representing a unique target protein, more than 20,000 activity class-dependent ACs were identified, also taking structural analogs of potent compounds into account that were confirmed inactive against the same target ,17. CompHerein, we further increase the public AC knowledge base through addition of three recently introduced categories of ACs including dual-site ACs (ds-ACs) , isomer et al. [The PS concept was originally introduced in medicinal chemistry by Evans et al.  and has et al. ,25. PSs et al. . Studyinet al. .In the following, we report a systematic search for ds-ACs, iso-ACs and PS-ACs, resulting in a new collection of ACs that further extends our knowledge base of ACs and is made available as an open access deposition. Importantly, ds-ACs, iso-ACs and PS-ACs were originally introduced in independent studies. Herein, we report a new unified search strategy that has made it possible to identify these ACs in bioactive compounds in concert applying consistent criteria, determine the overlap between different AC categories and study ACs belonging to these categories. This strategy is related to, yet distinct from the one applied in the original assessment of PS-ACs, which were most recently introduced , and hasi values) with specified numerical values (‘=’ relationship) were accepted as potency measurements for given targets.Bioactive compounds were extracted from the latest version of the ChEMBL  databaseet al. [PSs were defined according to Welsch et al. . A systeTo ensure consistent generation of ACs belonging to different categories, a recently introduced compound fragmentation scheme was applied . Using aStructural isomers: the same substituent occurred at two different sites (core positions).Dual-site analogs: two different substituents occurred at different sites. The size difference between these exchanged substituents was restricted to at most eight non-hydrogen atoms.Following fragmentation, compounds having the same activity and sharing the same core were organized into individual sets of analogs. Then, analog pairs (APs) differing at two substitution sites were systematically enumerated and categorized as follows:For each AP, it was determined whether the participating compounds had an at least 100-fold difference in potency, which qualified the pair as an iso-AC or ds-AC. We note that iso-ACs are confined to structural isomers and hence distinct from chirality or chiral cliffs ,9 where For ds-AC compounds, a further systematic search for structural isomers (from the same activity class) with the same substituent at the other substitution site was carried out. If such isomers were identified, it was possible to generate an extended data structure for a ds-AC, revealing the contributions of substituent positions to AC formation, as further discussed below.Originally, ds-ACs, iso-ACs and PS-ACs were separately studied. Here, we have implemented a unified search strategy to identify ACs belonging to these categories in parallel and determine their overlap. The search strategy is summarized in For SAR exploration, ds-ACs can be extended to generate a data structure comprising four analogs, as illustrated in Our systematic search identified a total of 3696 ACs without PSs that were formed by 2757 unique compounds with activity against 191 targets. These ACs included 3401 ds- and 295 iso-ACs. Thus, only a limited number of iso-ACs were available. In addition, the search identified 3769 PS-ACs formed by 2559 unique compounds with activity against 131 targets. These PS-ACs included 3544 ds- and 225 iso-ACs. ACs with and without PSs shared 84 targets.Our analysis revealed that approximately half of the newly identified ACs contained one of 24 predefined PSs that were detected in at least 100 unique bioactive compounds. The high frequency with which a predefined set of PSs occurred in ds- and iso-ACs, thus combining different AC categories, indicated that PSs yielded SAR-informative compounds with potential for further optimization. Hence, on the basis of AC analysis, these PSs deserve further consideration in medicinal chemistry. The PS-ACs provided as a part of our study should aid in further exploring these PSs.All ACs identified herein are provided in a text file. For each AC, category membership(s) are specified. For AC compounds, the ChEMBL ID, canonical SMILES representation and potency value are reported. For PS-ACs identified herein (forming a subset of iso-ACs and ds-ACs), the SMILES string of the PS is also provided. The data are made freely available as a deposition on the ZENODO open access platform .The extended ds-AC data structure enables the analysis of substitution site-specific contributions to AC formation. However, among structural analogs, structural isomers are under-represented and only limited numbers of isomers are currently available for ds-AC analysis. This is essentially the only data-dependent limitation associated with exploring the new AC categories introduced here. Hence, the search for isomers as structural analogs for ds-AC analysis will continue. Furthermore, the large number of PS-ACs we identified makes it possible to investigate the target distribution and SAR information content of PS-containing compounds and their analogs in greater detail. For this purpose, PS-ACs provide immediate focal points.The activity cliffs (AC) concept is rationalized.Different generations of ACs are defined.Procedures for AC identification are detailed.Recently introduced AC categories are described.Search routines are implemented.A unified search strategy for identifying different ACs is detailed.Search results are summarized.An extended data structure based upon dual-site ACs is introduced.A collection of ACs is generated.Details of its open access deposition are provided.Limited availability of isomers of dual-site AC compounds is discussed.Further analysis of privileged substructure-containing ACs is proposed.


N-hydroxy, oxazine, isoxazolidine, nitro, nitrone, oxime, C-, S-, or N-nitroso, and azoxy units. To this end, molecular oxygen is activated by flavin, heme, or metal cofactor-containing enzymes and transferred to initially obtain N-hydroxy compounds, which can be further functionalized. In this review, we focus on flavin-dependent N-hydroxylating enzymes, which play a major role in the production of secondary metabolites, such as siderophores or antimicrobial agents. Flavoprotein monooxygenases of higher organisms  can interact with nitrogen-bearing secondary metabolites or are relevant with respect to detoxification metabolism and are thus of importance to understand potential medical applications. Many enzymes that catalyze N-hydroxylation reactions have specific substrate scopes and others are rather relaxed. The subsequent conversion towards various N-O or N-N comprising molecules is also described. Overall, flavin-dependent N-hydroxylating enzymes can accept amines, diamines, amino acids, amino sugars, and amino aromatic compounds and thus provide access to versatile families of compounds containing the N-O motif. Natural roles as well as synthetic applications are highlighted.Amino groups derived from naturally abundant amino acids or (di)amines can be used as “shuttles” in nature for oxygen transfer to provide intermediates or products comprising N-O functional groups such as  N-hydroxy; others are oxime, azoxy, oxazine, nitrone, C-nitroso, N-nitroso, S-nitroso, nitro, isoxazolidine), which are often found in secondary metabolites. Those natural products are interesting for many reasons, as they comprise antibiotics, bioactive agents, flavor and fragrance molecules, food additives, pharmaceutical precursors or products, siderophores and metallophores, enzyme inhibitors, and toxins, among others.Nature provides access to numerous complex molecules with a variety of activities. The respective function is based on the molecular character of individual compounds and often shaped by their functional groups  and present recent findings about these enzymes since the last reviews six and more years ago  at the beginning of biosynthetic pathways. Here, structural diversification typically happens in variable downstream conversions. Furthermore, we highlight NMOs that accept more complex substrates, as late diversification stages of complex molecules or involved in the metabolization of bioactive compounds. Lastly, we describe NMOs involved in the formation of N-N and N=N bonds and reveal which common biological pathways are used by microorganisms to produce this great structural diversity. Few NMOs are currently exploited for biotechnological applications, leaving the vast majority of known—but hitherto uncharacterized in terms of enzymatic performance—enzymes as potential research target aiming at the production of complex chemical compounds.We first depict the catalytic mechanism and structural properties of NMOs, followed by recent advances and results from in-depth enzymology studies especially in the context of siderophore synthesis, where NMOs catalyze the N-hydroxylations. Those enzymes are typically designated as FMOs, a term which has been introduced for flavin-containing monooxygenases being involved in mammalian detoxification processes (EC 1.14.13.8) (Ziegler Flavin-dependent NMOs (EC 1.14.13.x) produce numerous important products, but only a few family members have been thoroughly characterized to date. NMOs belong to the single-component group B flavoprotein monooxygenases  and nicotinamide adenine dinucleotide (NAD(P)H) cofactors and keep the pyridine nucleotide bound during the oxidative half-reaction. In general, the mechanism of NMOs is similar to that of group B Baeyer-Villiger monooxygenases (BVMOs) , as determined for SidA from Aspergillus fumigatus   Fig. . For boted) Fig. . Furthered) Fig. , whereased) Fig. .red-NADP+ complex allows binding and activation of molecular oxygen to form the stable, long-lived C4a-hydroperoxflavin  is dependent on substrate binding  is formed, which decays to FADox and H2O. Finally, after the release of N6-hydroxyornithine and NADP+, FADox is ready for the next cycle.Formation of the ternary complex between FADHate Fig. . In the N5-hydroxylation of l-ornithine, uncoupling occurs with a range of substrate analogs, including among others d-ornithine, l-arginine, and l-lysine. Structural studies of PvdA indicated that an optimal orientation of the amino group of the substrate is required to prevent uncoupling  and wasting the reducing equivalents of NADPH. In the case of SidA and PvdA, which are both highly specific for the Mycobacterium smegmatis features a somewhat different kinetic mechanism  revealed that the active site is located at the interface of three domains. Next to the FAD- and NADPH-binding domains, the enzyme contains a small helical domain for binding the ornithine substrate. The PvdA structure also revealed that Arg240 and Ser286 were in H-bond distance of the 2′-phosphate group of the adenosine ribose in NADPH, thereby determining the coenzyme specificity.The crystal structure of PvdA (PDB code 3S5W) was the first NMO structure solved  are secondary metabolites produced by many organisms  to sequester iron in a physiological context  acetyltransferases to prevent overoxidation towards nitro functions, or directly used in the assembly line of siderophores, as presented for DFOB in Fig. We focus here on routes involving flavoproteins as one of the first biosynthetic steps. Enzymes studied so far are listed in Table The enzymes mentioned in Table N-hydroxylases  form small subgroups in the phylogenetic tree.Among the lysine es Table , seems cMany enzymes share a similar pattern of activity, and the final product of metabolic pathways they are part of is typically defined by the subsequent enzymatic steps and respective substrates. Functional groups that connect NMO-based routes, often N-O bonds, are crucial for biological function. This is true for all the siderophores produced via such a route since the N-O bond is usually part of a hydroxamate functional unit that allows metal chelation. This hydroxamate unit can be located terminally as an open or ring-like structure or simply in the middle of a siderophore molecule, and several such units can be present in one single molecule.Amycolatopsis alba under iron starvation. The involved NMO is designated AMO and prefers ornithine as substrate and NADPH as an electron donor. NADH does bind and allows conversion but yields only unproductive hydrogen peroxide formation. The same is true for lysine, which is only an effector and increases uncoupling as reported for other ornithine converting NMOs, such as VbsO (vide supra).Recently, the biosynthesis of albachelin was described Fig.  Kodani . This siN-hydroxy, C-nitroso, nitro, and azoxy  from a XMA Fig. . The groThe human family of FMOs includes five known enzymes, hFMO1–5. As already introduced above, these FMOs belong to the same group of flavoprotein monooxygenases and are able to oxygenate carbon-linked heteroatoms , it adversely affects Gram-positive and Gram-negative bacteria and has antifungal and even antitumor activities      =N- unit, different mechanisms have initially been proposed for a reaction of isobutylhydroxylamine with serine  binding protein from Salinispora pacifica  and Tri26 being homologous to N-hydroxylase MbtG in Streptomyces ipomoeae  . Interestingly, a second N-hydroxylation step is discussed within the biosynthesis pathway involving enzymes denoted as AlnG and AlnL. The former was described as a putative flavin-dependent acyl-CoA dehydrogenase, which operates in the oxidative direction to activate oxygen for N4-hydroxylation of a diaminopropane unit . Overall, 14 gene clusters with relation to the l-alanosine gene cluster were identified in Streptomyces and Saccharothrix sp., all containing genes similar to alnG but none with genes for the alnM/N pair (Wang et al. Another important intermediate in the biosynthesis of more complex structures is the non-proteinogenic amino acid alanosine, itself discussed to have antibiotic, antiviral and anticancer activities Fig.  Ng et a. Its bioIn this review, we focused on the remarkable ability of flavin-dependent enzymes to hydroxylate nitrogen-containing compounds, leading to a myriad of possible functional groups which play a major role in the bioactivity of secondary metabolites. The detailed understanding of ornithine-converting NMOs and their mode of action has set the basis for focused research efforts to include this enzyme class in biocatalytic processes. These efforts have especially stimulated processes employing NMOs from the siderophore biosynthetic pathways.Here, we highlighted the versatility in substrate scope some recently divulged NMOs can have and showcased their broad occurrence in different biosynthetic surroundings. It is especially noteworthy that many of these NMOs have just been discovered from genomics and/or proteomics studies and that they have not been characterized in an enzymological or biocatalytic context. We thus see great potential in these recent developments: From substrate scope to applications, flavin-dependent NMOs are key enzymes that we expect to play an even more prominent role in biotechnology in the near future.


There was a significant difference in time to all-cause hospitalization during acute-phase treatment (p = 0.018), with median times of 530 (95% CI: 499–587) and 425 (95% CI: 364–492) days for adherent and non-adherent groups, respectively. Conclusions: Acute-phase adherence to HEDIS AMM was associated with reductions in all-cause hospitalization risk among older adults with dementia and MDD.Objectives: To examine health outcomes associated with adherence to Healthcare Effectiveness Data and Information Set (HEDIS) antidepressant medication management (AMM) during acute and continuation phases of depression treatment among older adults with dementia and major depressive disorder (MDD). Design: Retrospective cohort study. Setting: Medicare 5% sample data (2011–2013). Participants: Older adults (aged 65 years or older) with dementia and MDD. Measurements: The first antidepressant prescription claim from 1 May 2011 through 30 April 2012 was considered the index prescription start date (IPSD). Adherence during acute- and continuation-phase AMM was based on HEDIS guidelines. Study outcomes included all-cause mortality, all-cause hospitalization, and falls/factures  during follow-up from end of acute-/continuation-phase AMM adherence. Due to the proportionality assumption violation of Cox models, fully non-parametric approaches (Kaplan–Meier and modified Gray’s test) were used for time-to-event analysis adjusting for the inverse probability of treatment weights. Results: Final study samples consisted of 4330 (adherent (N) = 3114 (71.92%)) and 3941 (adherent (N) = 2407 (61.08%)) older adults with dementia and MDD during acute- and continuation-phase treatments, respectively. No significant difference ( Dementia is a public health priority with a substantial economic burden (costs amounted to $290 billion in 2019) and is associated with several neuropsychiatric comorbidities, depression being the most common .While treatment guidelines for depression in adults are well established, studies exploring the outcomes of antidepressant use among older adults with dementia have yielded conflicting findings. A number of studies have shown that antidepressant use in patients with dementia led to improvements in functional status ,5,6. AddIn the present study, we examined the association of real-world outcomes  with adherence to antidepressant therapy during acute and continuation phases of depression treatment using a nationally representative sample of United States (U.S.) older adults with dementia and newly diagnosed major depressive disorder (MDD). Currently, Healthcare Effectiveness Data and Information Set (HEDIS) recommendations for antidepressant medication management (AMM) are used to guide treatment for depression across all populations . HoweverWe conducted a retrospective, cohort study. The primary data source used in this study was the Medicare 5% sample claims data from 2011 to 2013, including claims from the inpatient, outpatient, skilled nursing facility, carrier, hospice care, home health agency, durable medical equipment, and Part D event (PDE) Standard Analytic Files. Demographic information  as well as information on eligibility, residence (state and county), and date of death, were obtained from the Medicare Beneficiary Summary File (MBSF). A 5% random sample of the Medicare beneficiaries in the U.S. is included in the Medicare 5% sample claims data making it a nationally representative sample of the Medicare beneficiaries in the U.S. The current study utilized de-identified Medicare data that were obtained from the Centers for Medicare and Medicaid Services (CMS). A strict data use agreement (DUA) was set up between CMS and The University of Arizona to properly use the Medicare data. According to the CMS policy, the Medicare data we used for the current study cannot be shared with other individuals/groups/organizations without proper DUA approval. Hence, we will not be able to publicly share the Medicare claims data with any individuals/groups/organizations without CMS approval. However, interested parties can feel free to contact the first/corresponding author of this study (S.B.) via email to obtain information regarding the DUA process for acquisition of the Medicare data.Characteristics of the subjects’ county of residence  were obtained from the Area Health Resource File, a publicly available, county-specific database. The specialty of healthcare providers was obtained from the National Plan and Provider Enumeration System (NPPES); this file contains the National Provider Identifier (NPI), a unique identification number issued to healthcare providers by CMS, which we used to link with the NPIs in the PDE file.The study sample consisted of older adults aged 65 years and older with a diagnosis of dementia based on the Chronic Condition Data Warehouse (CCW) algorithm . Based oMDD was ascertained by HEDIS recommendations of using primary or secondary International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes  from inpatient/outpatient claims ,17,18,19The key independent variables were adherence during acute-phase treatment and adherence during continuation-phase treatment. Based on HEDIS guidelines , adherenSubjects who were considered “adherent” for the acute period may not have been adherent during the continuation period. Whether or not a subject was covered by their antidepressant prescription for a given day was calculated based on the date and days of supply of antidepressants from prescription claims in the PDE file .Outcomes of interest included time to all-cause mortality, time to first all-cause hospitalization, and time to first fall or fracture, with time measured from the end of the respective adherence period (acute or continuation). For hospitalization and fall/fracture outcomes, death was treated as a competing event. Mortality was identified from the MBSF files. Hospitalization was identified from the inpatient claims data. Falls and fractures were identified using validated ICD-9-CM and current procedural terminology codes based on the Tseng et al. study .To account for baseline differences in characteristics between adherent and non-adherent groups that might affect the outcomes, we used IPTW for all analyses. Propensity scores for each individual were calculated via logistic regression with the following predictor variables: gender ; age (65–74 or ≥75 years old); race (White or non-White); receipt of public assistance (indicated by Medicare premiums and deductibles that were subsidized for the enrollee by the state); census region ; metropolitan residency status (yes or no); whether or not there was a diagnosis of Parkinson’s disease during baseline (indicated by the presence of ICD-9-CM code 332.x); psychotherapy during baseline (yes or no); the specialty of the provider associated with the index prescription ; the per-capita density by county of each of neurologists and psychologists ; Elixhauser Index based on diagnoses present during baseline (truncated at 3); and the presence or absence of prescriptions for each of the following medication types during baseline: angiotensin-converting-enzyme (ACE) inhibitors, angiotensin II receptor blockers (ARBs), anticoagulants, antidiabetics, anti-Parkinsonian, antipsychotics, anxiolytics, beta-blockers (BBs), calcium-channel blockers (CCBs), diuretics, proton pump inhibitors (PPIs), and statins.As the analyses for acute-phase adherence and for continuation-phase adherence involved different sets of subjects, propensity scores (and the respective IPT weights) were calculated separately for each subset. We calculated standardized mean differences (SMDs) for each of the variables used in propensity score calculation before and after IPTW adjustment and considered an SMD of <0.20  as indicDue to violation of the proportionality assumption inherent in Cox models, we opted to employ fully non-parametric analyses. For all-cause mortality, survival was estimated using the Kaplan–Meier model and the weighted log-rank test was used to test of differences in survival curves between adherent and non-adherent groups. For hospitalization and falls/fractures outcomes, cumulative incidence functions (CIF) were plotted, and the modified Grey’s test  was usedPoint estimates and 95% CIs for survival and cumulative incidence of hospitalization and falls/fractures were calculated at 90, 180, 270, 365, 455, and 545 days. We also calculated point estimate and 95% CIs of the first quartile and median (where possible) of time to each outcome. For hospitalization and falls/fractures data, confidence intervals were calculated via bootstrap sampling. Analyses for all-cause mortality were conducted in SAS  and analyses for hospitalization and falls/fractures were conducted in R  . StatistDuring sensitivity analysis, we excluded subjects with physician specialty unknown; propensity scores and the respective IPTWs were recalculated for these subsets (acute- and continuation-phase treatment groups).p-values after IPT-weighting between adherent and non-adherent groups in the acute- and continuation-phase depression treatment groups, respectively. For the study sample included in the acute-phase depression treatment cohort, significant differences for baseline characteristics were observed for race/ethnicity, density of neurologists, Elixhauser comorbidity score, and antipsychotic use. For example, White older adults with dementia and newly diagnosed MDD were more adherent compared to the non-White race/ethnic group   (< 0.001) . However< 0.001) . After ap = 0.168, p = 0.518, p = 0.018), with median times of 530 (95% CI: 499–587) and 425 (95% CI: 364–492) days for the adherent and non-adherent groups during acute phase, respectively , and we observed consistent findings to our base case analysis (details not provided in Tables but available upon request).Using a U.S. nationally representative study sample, we demonstrated an association between adherence to antidepressants by older adults with dementia and significantly prolonged time to all-cause hospitalization during the acute phase, however, there was no statistically significant association with all-cause mortality or falls/fractures. Findings from this study address the existing knowledge gap regarding the effectiveness of antidepressant treatment among older adults with dementia and MDD by employing a rigorous study design.The eventual need for hospitalization in older adults with co-existing dementia and depression has been reported in previous studies ,27,28,29p < 0.0001) [Another variable explored in our study was the effect of antidepressant adherence on all-cause mortality. A cohort study using a nationwide population sample of individuals (age ≥ 60 years) with dementia and depression in Taiwan comparing 18,226 antidepressant users and 7664 non-users of antidepressant found that most antidepressant treatments showed significant protective effects on all-cause mortality, particularly when dosages were optimized   that obs 0.0001)  conducteWe also assessed the relationship between acute- and continuous-phase AMM and the risk of falls/fractures in our study, which did not show significant associations. While previous studies have independently established causality between falls and medications for depression ,35,36,37Our study has a number of strengths, including our use of a large nationally representative sample of older Medicare beneficiaries with dementia and depression and the use of the Index Prescription Start Date (IPSD) and Medicare prescription drug information, which allowed us to accurately estimate adherence to medications without being subjected to recall bias. We also utilized a robust study design and multilevel modeling statistical analysis to establish relationships amongst diverse variables. However, some limitations of our study include lack of dementia and depression severity measures within claims data, lack of generalizability to populations outside the U.S., and possible coding errors in the dataset. Due to data limitations, we do not have depression-specific outcomes such as Cornell Scale for Depression in Dementia in this study.Acute-phase adherence to HEDIS AMM was associated with significantly prolonging the time to all-cause hospitalization among older adults with dementia and MDD compared to non-adherence; however, no other differences were observed with the other study outcomes between adherent and non-adherent groups. Future large-scale studies are needed to determine optimal adherence thresholds and identify whether this is associated with better outcomes.


The standard of care for differentiated thyroid carcinoma (DTC) includes surgery, risk-adapted postoperative radioiodine therapy (RaIT), individualized thyroid hormone therapy, and follow-up for detection of patients with persistent or recurrent disease. In 2019, the nine Martinique Principles for managing thyroid cancer were developed by the American Thyroid Association, European Association of Nuclear Medicine, Society of Nuclear Medicine and Molecular Imaging, and European Thyroid Association. In this review, we present our clinical practice recommendations with regard to implementing these principles in the diagnosis, treatment, and long-term follow-up of patients with DTC.A multidisciplinary panel of five thyroid cancer experts addressed the implementation of the Martinique Principles in routine clinical practice based on clinical experience and evidence from the literature.123/131I radioiodine diagnostic whole-body scans and 18F-fluoro-2-deoxyglucose positron emission tomography/computed tomography suggested in selected patients. Management of metastatic DTC should involve a multidisciplinary team.We provide a suggested approach for the assessment and diagnosis of DTC in routine clinical practice, including the use of neck ultrasound, measurement of serum thyroid-stimulating hormone and calcitonin, fine-needle aspiration, cytology, and molecular imaging. Recommendations for the use of surgery  and postoperative RaIT are also provided. Long-term follow-up with neck ultrasound and measurement of serum anti-thyroglobulin antibody and basal/stimulated thyroglobulin is standard, with In routine clinical practice, the Martinique Principles should be implemented in order to optimize clinical management/outcomes of patients with DTC. Differentiated thyroid cancer (DTC), most commonly the papillary histotype, accounts for the majority of thyroid cancer cases . The staThyroid nodules are frequently detected in the general population and usually have a low risk of malignancy. When a thyroid nodule is detected , medical history and physical examination, measurement of thyroid-stimulating hormone (TSH) levels and neck ultrasonography are advised. In addition, measurement of serum calcitonin should be considered to further delineate the possibility of medullary thyroid carcinoma, despite there being a lack of general consensus with regard to routine serum calcitonin measurement . In the 99mTc-methoxy-isobutyl-isonitrile (MIBI) scintigraphy and 18F-fluoro-2-deoxyglucose positron emission tomography/computed tomography (18F-FDG-PET/CT)  , 11. Des-PET/CT) –17 may bFigure Primary diagnostic assessments include neck ultrasound, serum TSH, FNA cytology, and  calcitonin measurement.99mTc pertechnetate or 123I) is recommended when TSH levels are reduced (<0.3–0.4 mIU/L) and can be considered for TSH levels up to 1.0–1.5 mIU/L depending on local iodine supply.Thyroid scintigraphy ; or nodule that is taller than it is wide.In the absence of clearly suspicious ultrasound features, FNA cytology should be considered based on diameter , clinical history, and physical examination.99mTc-MIBI scintigraphy and 18F-FDG-PET/CT may help in refining the diagnosis in selected cases of nodules with indeterminate cytology.Molecular testing and molecular imaging based on BRAFV600E and TERT mutation status, should also be considered to refine surgical planning , 9072, 9Management of metastatic DTC should involve a multidisciplinary team and should be based on both local therapy  and systemic treatment .In patients with RAI-avid metastatic disease, RaIT may improve overall and disease-free survival and remains the treatment of choice.RAI activity to be administered can be determined empirically (3.7–11.1 GBq) or based on a dosimetric  approach; individualized dosimetry is preferable in selected cases .THW is recommended to prepare patients with metastatic DTC for RaIT; however, rhTSH is mandatory when endogenous stimulation is precluded  or clinically contraindicated.The definition of RaIT-refractory patients Table  is evolvThe Martinique Principles should be implemented in routine clinical practice in order to optimize clinical management/outcomes in patients with DTC. Based on the clinical experience of five thyroid cancer experts, we provide a suggested approach for assessing and diagnosing thyroid nodules in clinical practice, as well as our recommendations for the use of surgery and postoperative RaIT, and long-term follow-up of patients with DTC. The multidisciplinary approach is particularly important in the management of patients with metastatic DTC, which should be individualized according to disease status and comorbidities. Comprehensive assessment of patients with suspected RaIT-refractory disease is recommended before stopping RaIT.


The contribution of epigenetic mechanisms as a potential treatment model has been observed in cancer and autoimmune/inflammatory diseases. This review aims to put forward the epigenetic mechanisms as a promising strategy in implant surface functionalization and modification of biomaterials, to promote better osseointegration and bone regeneration, and could be applicable for alveolar bone regeneration and osseointegration in the future. Materials and Methods: Electronic and manual searches of the literature in PubMed, MEDLINE, and EMBASE were conducted, using a specific search strategy limited to publications in the last 5 years to identify preclinical studies in order to address the following focused questions: (i) Which, if any, are the epigenetic mechanisms used to functionalize implant surfaces to achieve better osseointegration? (ii) Which, if any, are the epigenetic mechanisms used to functionalize biomaterials to achieve better bone regeneration? Results: Findings from several studies have emphasized the role of miRNAs in functionalizing implants surfaces and biomaterials to promote osseointegration and bone regeneration, respectively. However, there are scarce data on the role of DNA methylation and histone modifications for these specific applications, despite being commonly applied in cancer research. Conclusions: Studies over the past few years have demonstrated that biomaterials are immunomodulatory rather than inert materials. In this context, epigenetics can act as next generation of advanced treatment tools for future regenerative techniques. Yet, there is a need to evaluate the efficacy/cost effectiveness of these techniques in comparison to current standards of care. Bulk me TiO2 ~4– nm, and itecture ,12,13,14Rapidly developing 3D printing technologies for metals, e.g., selective laser sintering  and elecThe biological response to metal/alloy implant surfaces, however, remains strongly governed by the initial events—and particularly by the adsorption of proteins and other constituents of tissue fluid , which iIn addition to naturally occurring polymers such as collagen, various synthetic polymers have also been developed and investigated in applications such as guided bone regeneration (GBR) and guided tissue regeneration (GTR). Collagen-based membranes typically demonstrate rapid degradation in vivo . In compThe term epigenetics was first coined in 1942 by Waddington and relates to changes in gene expression that are not encoded in the DNA sequence ,36. EpigIn contrast to the human genome, the epigenome is dynamic and changes in response to environmental factors and during a person’s lifetime. Interestingly, some epigenetic modifications are reversible and can be induced and/or altered by environmental factors, therefore presenting a link between the inherited genome and the environment . In addiModifications of the DNA do not change the base pairing but affect the DNA–protein interaction while being in the major groove of the double helix  DNA methIn the classic DNA methylation model, there is a covalent addition of methyl groups to the 5th carbon on cytosine bases (5-methyl cytosine “5mC”), which are situated next to guanine bases at specific sites in the DNA sequence, so-called CpG islands or CpG sites. The addition of methyl groups is regulated by DNA methyltransferases (DNMTs) . To add another level to the concept of DNA methylation, it was discovered that 5mC could be further oxidized into 5-hydroxymethylcytosine (5hmC) by the ten-eleven translocation (TET) family of enzymes ,45. The 6-methyldeoxyadenosine (6mA), was confirmed in DNA [In 2015, the presence of DNA methylation of adenine, Nd in DNA ,49,50. INucleosomes are the building blocks of chromatin , and oneHistone methylation, in turn, is regulated by histone methyltransferases and demethylases . HistoneDNA methylation and histone modifications  are not MicroRNAs (miRNAs) are a group of small noncoding RNAs of about 22 bp in length that regulate gene expression through post-transcriptional modifications of a target messenger RNA (mRNA) . This re(i)Which, if any, are the epigenetic mechanisms used to functionalize implant surfaces to achieve better osseointegration?(ii)Which, if any, are the epigenetic mechanisms used to functionalize biomaterials to achieve better tissue regeneration?This narrative review examines recently published preclinical studies to address the following focused questions: Electronic and manual searches of the literature in PubMed, MEDLINE, and EMBASE were conducted by two independent reviewers (F.A. and L.L.) for articles published in the last 5 years up to August 2020. The following  search term(s) were used: “(epigenetic OR histone modification OR DNA methylation OR miRNA or microRNA) AND (bone) AND  NOT (review) NOT (modular scaffold) NOT (cancer) NOT (CRISPR) NOT (exosome)”.This search resulted in a total of 185 articles. The exclusion criteria were review papers and papers not in the English language. Two reviewers (F.A. and L.L.) independently extracted the data from studies identified as relevant in the database search. In the following sections, the overall findings are summarized in a narrative manner according to the epigenetically functionalized implant/biomaterial described in the literature retrieved. The need for dental implants continues to increase alongside a rapidly growing population . As a reIn line with this, Meng et al.  developeAnother tested miRNA for implant surface coating is miRNA-21, due to its well-documented role in the regulation of cellular functions ,76,77,78COLI, COLIII, RUNX-2, OPN, and OCN, suggesting that this coating might have a clinical potential in promoting osseointegration [In another investigation on the use of miRNA-21 for implant surface coating, Wang et al.  developeegration . It seems that MAO-treated implants are ideal candidates for surface functionalization with miRNAs. Recently, Shao et al.  construcWith the same purpose of modifying the titanium surface, implant surface modification with anti-miRNAs, also known as antago-miRNA, has been explored as well. 2+), in an in vitro model, to deliver siRNA/miRNA to promote osteogenic differentiation of human mesenchymal stem cells (hMSCs) and, thus, improve osseointegration. Since miRNA-138 was previously shown to suppress the focal adhesion kinase signaling, which is essential for osteoblast differentiation, inhibition of miRNA-138 with anti-miRNA-138 might promote the osteogenic differentiation of mesenchymal stem cells [2+/anti-miRNA-138-functionalized implant was able to significantly enhance mineralization compared to the control groups, both on and around the implant. This finding may be of value for in vivo bone regeneration due to enhanced osteogenesis of hMSCs, both locally and around the functionalized titanium surface [In a recent study, Song et al.  used calem cells ,85. Ther surface .Functionalized titanium surfaces with anti-miRNA-138 were further assessed in vitro and in vivo by Yan et al. . In vivoIn an earlier study, Wu et al.  evaluateIn a different investigation, Liu et al.  conjugatTaken all the previous findings together, it can be proposed that functionalizing dental implant surfaces with miRNAs or anti-miRNAs might be of importance in promoting osseointegration in healthy and systemically compromised patients . SummaryControlling the behavior of drug release into the site of injury is important and a challenge in tissue engineering. Thus, the potential to use scaffolds or microspheres as vehicles for site-specific and controlled delivery over time is a major research focus.co-glycolic) acid (PLGA); and bioceramics (hydroxyapatite (HAp), tricalcium phosphate (α-TCP and β-TCP), biphasic calcium phosphate (BCP), and metals  [Biomaterials for fabrication of scaffolds for bone regeneration can be divided into biodegradable natural polymers including proteins and polysaccharides ; biodegradable synthetic polymers (polycaprolactone (PCL), polylactic acid (PLA), polyglycolic acid (PGA), and poly(lactic-gnesium) . For morgnesium) ,90. For complex tissues, such as the periodontal tissue with its connection to alveolar bone, composite scaffolds may be used. These composite scaffolds can, e.g., be a polymer combined with ceramics, ceramics/metal, and polymer/metal . Regardless of using recombinant protein or genetic material to obtain bone regeneration, these molecules need to be delivered into the healing site. Incorporating growth factors or signaling molecules into a scaffold presents a promising therapy for providing a localized delivery into the healing site. Methods for transfecting a gene into cells include nonviral vectors, viral vectors, and microRNAs ,92. In aIt has been found that both surface structure and material energy of biomaterials influence cells epigenetic pattern and hence has the ability to further influence gene expression in cells in contact with the material. A recent review summarizing the current knowledge on biomaterials and epigenetics showed that titanium, silica, PLGA, bioglass, and ceramics are potential materials in tissue engineering that influence epigenetic mechanisms . Below, Biodegradable natural polymers such as chitosan and collagen have so far been used together with other materials for the delivery of epigenetic drugs or miRNAs for bone regeneration.A combination of chitosan, hydroxyapatite, and zirconium dioxide scaffold containing miRNAs for bone tissue regeneration was recently established and shown to have an osteoinductive effect on cells, in fact, the addition of miRNAs further induced the osteogenic differentiation of mouse mesenchymal stem cells . In a stInstead of functionalizing natural polymers solely with miRNAs, the incorporation of 3D-printed technologies to fabricate scaffolds, later to be seeded with miRNA-transfected cells could represent a more advanced approach in this paradigm. In this context, functionalized 3D-printed collagen scaffold with miRNA-148b-transfected bone marrow stem cells were shown to improve clavarial bone regeneration in rats . This inInterestingly, another epigenetic mechanism was investigated in collagen functionalization; collagen sponges and macroporous biphasic calcium phosphate scaffolds mixed with HDAC inhibitor (HDACi) induced woven bone formation and newly formed bone at the contact with the scaffold .Silk is another natural polymer that has been functionalized with epigenetics. James et al. (2019)  assessedMicrospheres of PLGA have been used for the delivery of proteins and drugs; by altering its porosity and structure, delivery of drugs and proteins can be released in a controlled way. The microspheres can be porous, nonporous, or covered-porous, with covered microsphere shown to have a sustained release of drug and protein over time compared to open and porous microspheres ,102. In PLGA microspheres coupled with miRNA-124 coloaded with ketoprofen showed a synergistic effect reducing inflammation as well as bone damage in a rat rheumatoid arthritis (RA) model . FurtherGsk-3β to activate the osteoblastic activity of endogenous stem cells. This system can be important in overcoming the limitations of using cell free scaffolds for bone regeneration. This 3D scaffold-defined controlled miRNA delivery technology enables the prolonged expression of multiple osteogenic genes at their therapeutic levels, leading to repair of critical-sized bone defect without adding cells [Zhang et al.  reportedng cells .l-lactic acid) (PLLA) nanofibrous spongy microspheres, as an injectable scaffold for the adhesion and proliferation of Tregs, (b) PLLA/polyethylene glycol (PEG) cofunctionalized mesoporous silica nanoparticles, and c) PLGA microspheres, both utilized to distinctly release IL-2/TGF-β and miR-10a to locally recruit T cells and stimulate their differentiation into Tregs. In a mouse model of periodontitis, the injectable and biomolecule-delivery system resulted in Treg enrichment, expansion, and Treg-mediated immune therapy against bone loss [In an attempt to counteract periodontal bone loss, Liu et al.  created one loss .l-lactic acid)/POSS  scaffold. MicroRNA-19b-3p-modified BMSCs were seeded on the scaffold, which was then implanted in a critical-sized calvarial defect in rats. The functionalized scaffold promoted efficient healing in the bone defects [Xiong et al.  used pha defects . co-ethyl ethylene phosphate) (PCLEEP) fiber scaffold containing miRNAs has been developed [In order to investigate the use of miRNA as a means to regulate foreign body reaction towards implants, electrospun poly(caprolactone-eveloped . The PCLeveloped . A sustaeveloped . As a cob-poly(l-lactide-co-ε-caprolactone) (PELCL) forming the inner layer and electrospinning of poly(ε-caprolactone) (PCL) and gelatin forming the outer layer to incorporate miRNA-22 and miRNA-126 to induce osteogenic differentiation of pluripotent stem cells grown on the scaffold [Other various biodegradable synthetic polymers have been functionalized with miRNAs to enhance bone regeneration. Tahmasebi and coworkers (2019)  used a bscaffold . The resscaffold . In a cascaffold  tested pscaffold . RUNX2, OPN, OCN, and ALP) [Pan et al.  utilizedand ALP) . Bioceramic scaffolds are often combined with different polymers in order to improve molecules/drug release from such scaffolds. Menciá Castanõ and coworkers  designedSilica has been used for miRNA delivery as well for bone regeneration purposes, especially mesoporous silica nanoparticles, which are ideal for drug delivery and are promising in gene transfection . Recentlb-poly(lactic-co-glycolic acid)-b-poly(N-isopropylacrylamide) (PEG-PLGA-PNIPAM) hydrogel for localized and long-term codelivery of microRNA-222 and aspirin, in local mandibular rat defects. The injection of this hydrogel system into the defects resulted in neurogenesis and enhanced bone formation, suggesting that this system could be promising in innervated bone tissue engineering, since adequate innervation is required for an optimal bone healing outcome [In an earlier investigation, Lei et al.  develope outcome . 2+ signaling pathway. This is indeed a very interesting finding, since Yan et al. [In the repair of rat femoral defects, Yuan et al.  seeded an et al.  reportedn et al.  reportedn et al.  and the To further improve delivery of miRNAs to site of tissue damage and to reduce the risk of degradation of miRNA, Ou and coworkers  loaded mIn another attempt to enhance miRNA delivery and reduce its degradation, Xue et al.  developeFunctionalization of implant surfaces have been done with miRNAs or anti-miRNAs, directly coated on the surface or coated on a biomaterial then attached to the implant surface or by seeding miRNA/anti-miRNA-transfected cells on the implant.Unlike cancer studies, which heavily reported on DNA methylation and histone modifications, functionalization of biomaterials and scaffolds for bone regeneration have been done with miRNAs or anti-miRNAs, except for one study that reported on the use HDACis.For bone regeneration, the functionalized scaffolds of different biomaterials were either cell free, or were loaded with miRNA or anti-miRNA-transfected stem cells.Modulating the inflammatory and immune reaction with these functionalized scaffolds to enhance bone regeneration is possible, either by influencing macrophage polarization or the recruitment of Tregs.Microspheres, nanoparticles, and PEI-based nanoparticles are heavily applied for miRNA or anti-miRNA delivery.Findings of this review demonstrate the potential of functionalized implant surfaces and epigenetic modifications of biomaterials to better achieve osseointegration and bone formation. Nevertheless, most of these studies explored functionalization of these surfaces through miRNAs. Scarce data are available on the modifications using DNA methylation and histone modification for bone regeneration, despite being commonly used in cancer research. MiRNA and anti-miRNA delivery has been carried out either by directly immobilizing them to the implant surface or by transfecting them in cells and then immobilizing the transfected cells on the surfaces. The composite scaffolds  have been commonly used in these studies. Further conclusions can be drawn from this review:Historically, it has been stated that successful osseointegration of dental implants and biomaterials for bone regeneration is dependent on a direct bone apposition onto the surface of the implanted materials. Recent findings propose that the genetic basis of individuals plays a more critical role than previously described . PreviouAn interesting hypothesis presented regarding tissue reactions towards various biomaterials is the impact of the basement membrane to which unfavorable transformations could be related. This may lead to alterations in fibroblasts, keratinocytes, collagen, laminin, integrin, and other factors with specific inflammatory and immunologic roles, which eventually lead to foreign body reactions . Hence,


Objective: Dazhu hongjingtian  preparation as an add-on therapy has been applied to the treatment of angina pectoris. We aimed to evaluate the efficacy and safety of DZHJT as adjuvant therapy for the treatment of unstable angina pectoris (UAP).Methods: An extensive literature search was conducted on PubMed, Emase, Cochrane Library, Wanfang, CNKI, and VIP databases from inception to January 2019. Randomized controlled trials (RCTs) comparing DZHJT in combination with Western medicine with Western medicine alone were included. Two authors independently performed the literature search, data extraction and risk of bias assessment of included studies, and conducted the statistical analysis.Results: A total of 18 RCTs involving 1,679 patients were included in the meta-analysis. Adjuvant treatment with DZHJT significantly decreased ≥80% reduction in the frequency of angina attacks , weekly frequency of angina attacks , marked improved abnormal electrocardiogram . In addition, DZHJT significantly reduced the whole-blood viscosity , plasma viscosity , serum level of fibrinogen , thromboxanes B2 , and C-reactive protein . No significant differences in headache/dizziness  were observed between two groups.Conclusion: Adjuvant treatment with DZHJT has an add-on effect in reducing angina pectoris attacks in patients with UAP. The beneficial effect may be correlated with regulating whole-blood viscosity, plasma viscosity, fibrinogen, thromboxanes B2, and CRP level. However, future well-designed prospective, randomized, double-blind placebo-controlled trials with large sample sizes are required to evaluate the evidence. Angina pectoris is a symptomatic condition characterized by chest pain attacks. It is clinically classified into stable angina pectoris (SAP) and unstable angina pectoris (UAP). UAP is a type of acute coronary syndrome characterized by an attack at rest and severe, prolonged, and frequent or newly developed angina pectoris  has been frequently introduced to patients with angina pectoris in China /We conducted this meta-analysis following the checklists of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Guidelines  study design was RCT; (2) patients diagnosed with UAP according to the guideline of the American College of Cardiology Foundation/American Heart Association (ACCF/AHA) , outcome measures, and methodological information. We evaluated the methodological quality of the included trials according to the Cochrane risk of bias tool, which included selection bias, performance bias, detection bias, attrition bias, reporting bias, and other sources of bias. Each trial was categorized by “high,” “unclear,” or “low” risk of bias.I2 index were applied to the analysis of heterogeneity across the studies. A random effect meta-analysis was conducted when the p-value of Cochrane Q statistic test is <0.10 and I2 >50%. Otherwise, we pooled the data by using a fixed-effect model. We used a funnel plot to examine the possible publication bias when the number of trials was sufficient. Leave-one-out sensitivity analysis was conducted to test the stability of the pooling results.The RevMan 5.2 software was used for the meta-analysis. We summarized as the risk ratio (RR) with 95% confidence intervals (CI) for dichotomous outcomes or mean difference (MD) with 95% CI for continuous outcomes. The Cochrane Q statistic and In brief, our initial literature search yielded 615 potentially relevant articles. After screening the titles and abstracts, we retrieved 54 full-text articles for detailed evaluation. We further removed 36 articles on the basis of our predefined inclusion criteria. Thus, 18 articles . Meta-analysis showed that adjuvant treatment with DZHJT significantly reduced the ≥80% reduction in frequency of angina attacks . When we removed one trial . No evidence of publication bias was observed based on the visual inspection of the funnel plot . As shown in I2 = 76%, p = 0.006); four trials ; four trials ; 3 trials ; three trials  between two groups. When we excluded one trial  is a holistic system of medicine. However, most of the included trials did not consider syndrome differentiation in patient selection. TCM syndrome differentiation must be incorporated into the diagnostic process and DZHJT is suitable for blood stagnation syndrome. Thirdly, generalizing the current findings to patients with SAP must be with caution. Finally, the included trials did not report the long-term follow-up results, and whether adjuvant treatment with DZHJT can reduce the risk of future cardiovascular events is unknown.This meta-analysis suggests that adjuvant treatment with DZHJT has an add-on effect in reducing the frequency of angina pectoris attacks among patients with UAP. The beneficial effect of DZHJT may be correlated with its function to regulate whole-blood viscosity, plasma viscosity, fibrinogen, thromboxanes B2 and CRP level. However, based on the existing evidence, no conclusion about the therapeutic benefits, limitations of use and potential risks can be drawn. Future well-designed prospective, randomized, double-blind placebo-controlled trials with large sample sizes are required to evaluate the evidence.CM and ZD made the literature search, extracted data, evaluated the study quality, and performed the statistical analysis. CM drafted the manuscript. YF designed the study, interpreted the results, and revised the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Hermansky-Pudlak syndrome (HPS) is an extremely rare disease with pulmonary fibrosis (PF), oculocutaneous albinism, induced platelet dysfunction, and granulomatous colitis. Although patients with HPS-associated PF (HPS-PF) often receive treatment with anti-fibrotic agents, including pirfenidone, many HPS-PF cases are progressive. The development of pneumothorax is known to be rare in HPS-PF. Pneumothorax development is generally important for prognosis in patients with interstitial pneumonia. However, there are few reports regarding the development of pneumothorax in patients with HPS-PF.HPS-1 gene. After diagnosis with HPS-PF, he initiated home oxygen therapy due to gradually progressive hypoxemia.A 50-year-old Japanese man with chestnut hair, white skin, and light brown squint eyes visited our hospital for interstitial pneumonia examination. Chest high-resolution computed tomography (HRCT) demonstrated diffuse bilateral reticular opacities along the bronchovascular bundles and traction bronchiectasis predominantly in the upper lung fields. He was definitively diagnosed with HPS because genetic analysis showed that he had a homozygous mutation, c.398 + 5G > A, in the Three months after the HPS-PF diagnosis, the patient suddenly developed severe chest pain and dyspnea and was admitted to our hospital on emergency. He was diagnosed with pneumothorax by chest radiological findings. He immediately received chest drainage; however, his pneumothorax did not improve. Therefore, he underwent video-assisted surgery by thoracic surgeons. The leak point was not detected, but multiple bullae were found, mainly in the upper lung lobes. Thus, the surgeons did not perform bullectomy and only covered the apical areas. Fifteen days after the surgery, the patient developed high fever and dyspnea with a new diffuse reticular shadow found through HRCT. We first initiated the patient on broad-spectrum antibiotics; however, the symptoms and radiological findings worsened. Therefore, we started treatment with pirfenidone for inhibition of PF progression. The patient re-developed pneumothorax with severe respiratory failure. Although he re-underwent chest drainage, he died of progressive respiratory failure.We herein report the case of a rare HPS patient who developed pneumothorax with progressive PF. Pneumothorax may cause rapid progressive respiratory failure and may be associated with PF progression in HPS-PF. Hermansky-Pudlak syndrome (HPS)  is an exThe development of pneumothorax is rare in patients with HPS-PF. In general, the development of pneumothorax leads to a decrease in patient quality of life and worsens any respiratory symptoms in patients with interstitial pneumonia.We herein report the development of severe refractory pneumothorax in a patient with HPS-PF and review the previously published case reports associated with the development of pneumothorax in patients with HPS-PF.HPS-1 gene; thus, he was definitively diagnosed with HPS. Further, his interstitial change on HRCT was considered to be associated with HPS-PF. After the diagnosis with HPS-PF, hypoxemia gradually progressed; thus, he started home oxygen therapy (HOT).A 50-year-old Japanese man, with natural white skin, chestnut hair, and light brown squint eyes, visited our hospital with a suspicion of interstitial pneumonia based on a chest X-ray Fig. a. He hadThree months after the diagnosis with HPS, the patient was admitted to our hospital on emergency due to a sudden development of chest pain and acutely worsening dyspnea. Chest X-ray showed a collapsed right lung Fig. a, and thHPS-1 genetic analysis. Many gene subtypes are reported to be associated with HPS. Patients with HPS-1, HPS-2, and HPS-4 often show PF complications [HPS-1 have a high incidence of PF [HPS-1 mutation; thus, the findings from our patient are consistent with those from previous cases. Our patient showed complications of oculocutaneous albinism, platelet dysfunction, and a history of granulomatous colitis; hence, our patient had almost all features associated with HPS. This patient developed pneumothorax; however, this manifestation is rare in HPS. During the observation period, PF and the respiratory condition worsened rather rapidly. In general, survival time has been reported to be approximately 30 years in HPS [Our patient was diagnosed with HPS based on ications . Particuce of PF  and morece of PF . Our patThere have been only two cases reported on the development of pneumothorax in patients with HPS-PF , 11, Tab1, Tab1. For the treatment of HPS-PF, due to HPS-PF progression, our patient received pirfenidone. However, lung fibrosis sub-acutely worsened when the patient received the anti-fibrotic agent. We judged that pirfenidone was not effective against PF in our patient. We also considered treatment with other anti-fibrotic agents such as nintedanib. However, the patient had a prolonged bleeding time and pneumothorax; thus, we did not choose this agent due to the possibility of the condition worsening, as well as other adverse effects. Corticosteroids are used for treating any interstitial pneumonia; however, we cannot administer corticosteroids for IPF . HRCT scIn conclusion, we report here a rare HPS case of pneumothorax development with progressive PF. The development of pneumothorax may cause the rapid progression of respiratory failure and PF. Clinicians should be made aware that pneumothorax development indicates a poor prognosis in patients with HPS-PF.


Balance and mobility function worsen with age, and more so for those with underlying diseases. Our research has demonstrated that asymptomatic carotid artery stenosis (ACAS) is associated with worse balance and mobility, and a higher fall risk, compared to older adults with similar comorbidities, but without ACAS. Thus, ACAS, with attendant blood flow-restriction to the brain is a potentially modifiable risk factor for balance and mobility dysfunction. The purpose of this study was to evaluate the impact of restoring blood flow to the brain by carotid revascularization, on balance and mobility in patients with high-grade ACAS (≥70% diameter-reducing stenosis). Twenty adults (67.0±9.4 years) undergoing carotid revascularization for high-grade stenosis were enrolled. A balance and mobility assessment was performed before- and six weeks- after carotid revascularization and included: Short Physical Performance Battery (SPPB), Berg Balance Scale (BBS), Four Square Step Test (FSST), Dynamic Gait Index (DGI) Timed Up and Go (TUG), gait speed, MiniBESTest, and Walk While Talk (WWT) test. Paired t-tests assessed changes in outcome measures between the two-time points. Significant improvements were observed in measures that combined walking with dynamic movements, DGI (P=0.003), and MiniBESTest (P=0.021). Pearson’s correlations examined the relationship between balance and mobility before surgery and change score after surgery. Patients with lower baseline DGI and MiniBest scores demonstrated the most improvement on follow-up testing . In conclusion, revascularization of a carotid artery stenosis improves balance and mobility; the greatest improvements are observed in those patients that are the most impaired.