Populus tree root systems. We show that in both studies the associations of OTUs can separate samples according to environmental or physiological characteristics of the studied systems.Studies of microbial communities by targeted sequencing of rRNA genes lead to recovering numerous rare low-abundance taxa with unknown biological roles. We propose to study associations of such rare organisms with their environments by a computational framework based on transformation of the data into qualitative variables. Namely, we analyze the sparse table of putative species or OTUs  and samples generated in such studies, also known as an OTU table, by collecting statistics on co-occurrences of the species and on shared species richness across samples. Based on the statistics we built two association networks, of the rare putative species and of the samples respectively, using a known computational technique, Association networks (Anets) developed for analysis of qualitative data. Clusters of samples and clusters of OTUs are then integrated and combined with metadata of the study to produce a map of associated putative species in their environments. We tested and validated the framework on two types of microbiomes, of human body sites and that of the  The rare low-abundance microbial species, which have been referred to as the “rare biosphere” , have atThe numerous rare OTUs are a typical output of 16S rRNA amplicon sequencing studies, especially those with many and diverse samples. The resultant sparse datasets present a challenge for common statistical tools. The data matrix produced by such studies are usually comprised of species-like groups (rows) and their abundances calculated as the number of sequencing reads representing each species across multiple samples (columns). The species-like groups are typically inferred by a conventional aggregation of sequences into OTUs based on a sequence identity threshold or, in more recent work, by amplicon sequence variants (ASVs) . In bothIn addition to sparsity, the 16S rRNA gene sequencing data have other challenges including their compositionality and dimensionality . The data compositionality means that we don’t know the real OTU abundances and have to deal with proportions of species relative to their sum in each sample. Several methods have been proposed to address the challenges . The mosPopulus Root Microbiome (PRM) dataset . Notably, the number of common abundant OTUs is extremely small in the datasets. Considering this observation we decided to treat the rare OTUs as qualitative data by replacing the putative species abundances with the presence/absence call . Although in this approach we lose information on abundances, at the same time, the resulting dataset will not be compositional. In addition, we get the chance to transform the data to collect additional statistics on co-occurrences of species with each other and to quantify interdependencies of the species. The quantification is based on an assumption that rare OTUs (putative species) are associated because they are dependent upon one another in each studied environment. They may be dependent metabolically, when metabolites produced by one species are consumed by another species. They also may have similar optimal growth conditions or offer complementary functions to support microbial community as a whole  to illustrate and explain computations underlying the proposed framework. In this study, we have two synthetic microbial communities with four associated species (circles) in the first community and four associated species (triangles) in the second community. Species in each community are co-dependent, and therefore more often co-occur in their parent environment. We made 12 random samples of species from the communities and organized the sampling results as an OTU table  with species/OTUs in rows and samples in columns. All species identified in the samples are rare; they are found only in 2–5 out of 12 samples. Thus, we replaced the species abundances with the presence/absence (1/0) values.We also used a simulated dataset . The transformed table, therefore, gives us the co-occurrence profiles for each OTU with the rest. We further use these profiles to infer pair-wise associations of the OTUs . Although the input of the approach is OTU table with 1/0 values instead of counts, the statistics collected in the transformed table produces continuous variables. The Anets program provides three options to quantify the pair-wise similarities of the profiles. The options include Spearman correlation (default), Pearson correlation, and cosine (Jaccard index). While alternative similarity metrics may be appropriate for particular datasets, in these studies we found that the Pearson correlation coefficient was most robust for identifying association networks. We calculate the Pearson correlation to measure similarity of the profiles for each pair of OTUs and consider the OTUs associated if the correlation coefficient R > = 0.30. The selected pairs of OTUs predict the network (Anets-OTUs) of seven species with seven associations separated into two clusters/communities . The species inferred by the Anets-OTUs in each cluster correspond to two communities provided in the mock study . The algorithm did not recover only one species from the Environment 1 of the study.To generate the Anets-OTUs we first transform the OTU table to produce a new table where rows and columns consist of OTUs and each cell shows the number of samples where two OTUs co-occur in the data . In this case we transform the OTU table to produce a new table where both rows and columns consist of samples and each cell represents the number of shared OTUs for each pair of samples. The ecological interpretation of the number is the shared species richness for a pair of samples. We consider two samples associated if they have a similar profile of the shared species richness values across all samples in the dataset. Such indirect similarity can establish an association between each pair of samples even if the majority of species in the samples are not common. Computationally, the algorithm generating the Anets-Samples  is similar to the algorithm of the Anets-OTUs . As before, the transposed table is used to compute profiles of shared species richness values for the samples  followed by estimation of pair-wise correlations  and clustering . As we can see in the Figure 3H, the clustering recovers associations among 9 out of 12 samples in the illustrative study. The final step of the framework is an integration of the results obtained by Anets-OTUs and Anets-Samples by building a presence/absence map of the associated species and samples .A similar algorithm was used to generate the associations of samples  trees at along two different rivers. The study also collected a set of soil properties and host characteristics for each of the 23 sampling locations; we used these metadata to examine their relationships with the associations of samples discovered by the Anets-Samples.The dataset  includesPopulus root are represented by only 61 OTUs, or 0.22% of total number of OTUs in the dataset. As expected, the majority of OTUs had low-abundance and was rare . After applying the Anets-OTUs algorithm to the OTU table we found six large associations of OTUs . A further enrichment analysis  attributed each association to a location, TN and NC, and to a sampling season, May or September . This analysis revealed that communities of low-abundance OTUs, were underlying groups of samples based on known environmental factors from the study. To further confirm the grouping we built a heat map of the associated OTUs  across all samples  organized by the geographical location and season and sampling . While, it can be appreciated that many rare Anets-OTUs are present across all samples, some of them often co-occur in samples from a particular location or a season. The largest microbial association includes OTUs found in Populus rhizosphere in any season and in any location. Some associations are more common for TN or NC, and some associations are more common in September or May. This pattern suggests a tight link between the identified associations of the rare OTUs and a particular environmental factor. We noticed, for example, that a fungal OTU representing the genus Inocybe was found only in the NC cluster. Indeed, species of the genera have been tied to their environments rather than their hosts more than other fungal species  or generalists in  species . Our resPopulus roots in both locations, TN and NC, include phylums Proteobacteria with less number of OTUs in NC (Supplementary Table Proteobacteria in NC had greater richness (10 orders) when compared with TN (seven orders), and included Rhodocyclales, Syntrophobacterales, Rhodobacterales, and Burkholderiales orders that were not observed in TN. Microbial communities in both locations, TN and NC, also included numerous species from phylum Acidobacteria. The microbial community in TN, however, was dominated by the order Solibacterales; this taxa, however, was not found in NC. This example clearly demonstrates that by analyzing the dataset at the level of OTUs and collapsing them after linking their associations to environments may be a better strategy for exploration of subtle difference among microbiomes in similar environments.The analysis confirms that clustering at low taxonomic levels may be crucial in discriminating different environments. We find that although OTUs in each of the associations often belong to the same phyla, they are more distinct at lower taxonomic levels, such as order . Within each cluster, all samples had similar profiles of the shared species richness across all samples (p < 0.01). Furthermore, there was a clear association with metadata of the study, with the first cluster representing a subset of samples from TN, and the second cluster representing a subset of samples from NC. Eight samples did not associate with either cluster. These results mirror the results of By applying the Anets-Samples algorithm to the OTU table we revealed two distinct clusters of samples in the PRM dataset , correspond to two distinct soil clusters inferred from the soil properties . This relationship was not found in the original study and again suggesting the importance of rare microbial species for differentiating subtle environmental conditions in addition to the traditional methods that more heavily weight species abundance and dominant taxa. In case of PRM we observe that a set of TN samples found as associated by Anets share relatively greater Zn, Mn, and Ca contents in the soil and a greater soil pH. A set of associated NC samples share relatively low values of these soil characteristics. Those samples, either from TN or NC, that are not identified by Anets-Samples as significantly associated, have a variable content of the soil properties as well as relatively greater sand content and lower clay and organic matter contents than the associated samples. The results point to the soil properties as a crucial factor underlying similarity of microbial communities in Populus deltoides rhizosphere.To examine the effect of soil on the separation of samples in more detail we hierarchically clustered 16 soil properties measured in the study and found that two associations discovered by the Anets-Samples in Figure 1A), the majority of OTUs in the dataset is rare and has low-abundance. Considering the large size of the OTU table produced in the study we started the analysis with the construction of the Anets-Samples  to find associations (clusters) of samples with similar profiles of the shared species richness and to discard samples-outliers. Most samples (74%) in the dataset were found to be associated  with at least one other sample in the network. Visualization and clustering of the network using the Markov clustering algorithm (MCL)  was comprised of male human subjects.The HMP dataset has been characterized in several publications  and inclhm (MCL)  revealedhm (MCL) . We nextFigure 5A. To reveal communities of microbial OTUs discriminating these clusters we built the Anets-OTUs using, as input, an OTU table comprised of these 314 samples in columns and 43140 OTUs in rows. The generated Anets-OTUs included 412 associated OTUs ; and subsequent clustering of the network revealed four major microbial communities . The enrichment analysis showed statistically significant links between the communities and the Anets-Samples clusters . Importantly, the three distinct clusters of samples, originated from skin of different human subjects, have significant differences in microbial communities at the OTU level, although most OTUs contributing to the difference belonged to the genus Propionibacterium. Indeed, microbial community 1 comprised of OTUs of the genus Propionibacterium  was significantly enriched in Anets-Samples clusters 2 and 10 , but not in Anets-Samples cluster 16 . Microbial community 2 comprised of a distinct set of OTUs from the same genus  was significantly enriched only in Anets-Samples cluster 2 . The third microbial community comprised of OTUs of the genera Propionibacterium and Actinomycetales  was enriched in Anets-Samples cluster 10 , and the fourth microbial community (OTUs from the genera Staphylococcus and Propionibacterium) was enriched in Anets-Samples cluster 16 comprised of male human subjects. The p-value 0.01 (Fisher exact test) was used as the significance threshold in the enrichment analysis. Thus, the OTU level clustering was important to discriminate microbial communities of the clustered samples.We further focused the analysis on 314 skin samples that represent three distinct, disconnected in the Anets-Samples, clusters labeled by black ovals in We use 1250 oral samples of HMP to investigate the robustness and limitations of the Anets algorithm, to compare it with other methods and to explore potential biases and confounding factors.The Library Size (LS) affects the number of identified rare species and, therefore, may introduce a technical bias in the OTU table if there are significant differences in LSs among studied environments. We explore this affect using known annotations of oral samples by subsites. Specifically, pair-wise comparisons were performed among all the subsites in terms of the library size and then in terms of the number of rare OTUs. We find that log-transformed values of the library size in the oral samples have a normal distribution  or with common and rare OTUs . In spite of the batch effect, the grouping of samples within the large batch . The PCoA plots generated for OTU tables by including or excluding the rare OTUs were rather similar  suggesting that we will not significantly effect the interpretation of the results by excluding rare species in the PCoA. However, by excluding the rare species when building Anets , we essentially decrease our chance to cluster samples according to subsides  and also decrease the number of associated samples (p > 0.05) from 1082 (87%) to 981 (78%). The results demonstrate high sensitivity of the Anets algorithm to signals from both, rare and more abundant, OTUs. The result is not surprising. To build Anets we have to collect additional statistics on co-occurrence of species with the rest and on the shared species richness to establish the pair-wise associations in Anets-Samples and in Anets-OTUs. By excluding some species, either less abundant or more abundant, we loose information important for the analysis and impair the results. Building Anets after filtering common species, however, may allow us to see biases obscured by the presence of common taxa.We further explore how important rare and common taxa for correct grouping of samples. We separated species identified in 1250 oral samples to two groups, rare (occupancy is between 0.5 and 25% samples) and common (occupancy > 25%). Then we generated three OTU tables; comprised of only rare OTUs, rare and common OTUs, and only common OTUs. We find that considering only rare OTUs we reduce the resolution of the Principal coordinates analysis (PCoA) plot . The generated clusters, however, were not as consistent with the annotation of subsites as in case of Anets-Samples network . Although in general all three networks showed the same trend of separation of subsites ‘keratinized gingiva’ and ‘bunccal mucosa’ from ‘saliva,’ ‘tongue dorsum,’ and ‘throat,’ it was easier to cluster the Anets-based network, and, importantly, many large clusters in the Anets network were enriched with samples originated from the same subsite . The comparison reveals a distinct topology of the Anets network if compared with UUF-based networks and a better association of the topological structure with oral subsites. The more centralized topology of the UUF-based network may be suitable for a global overview of the samples. The Anets-based network may perform better if we want a greater level of detail and more granularity in grouping the samples.UniFrac is widely used distance metric incorporating phylogenetic information to compare microbial communities. All taxa, common and rare, are included in calculation of the distance. The metric, therefore, may be an alternative way to construct the network of samples by incorporating the phylogenetic signals from rare species. We have compared the network of samples generated by Anets with those based on the Unweighted UniFrac (UUF) distances. The ‘phyloseq’ package  was usedFigure 8). The MOTHUR and QIIME networks, however, were surprisingly different in their ability to separate different subsites . The MOTHUR network performed well in separating tongue dorsum and throat from other subsites, but not as good in separating keratinized gingiva and buccal mucosa, while the QIIME v13 network performed better in separating keratinized gingiva and buccal mucosa from other subsites, and not as good for tongue dorsum and throat. The difference persists when we run Anets with different parameters. An interesting symmetrical structure, related to the batch effect, was revealed in the Anets-samples produced for OTU table HMPv35(Q) . The upper part of the network represents samples sequenced by J. Craig Venter Institute (JCVI) and the lower part representing samples sequenced by other sequencing centers. Importantly, each side of the network demonstrated similar grouping of samples into subtypes regardless of the batch affect. The network generated for a different subset of oral samples, HMPv35(Q) Validation, reveal a similar batch effect with separation of samples into subsites within each batch. Based on the results we conclude that the Anets algorithm recover similar groupings of samples from OTU tables produced by two commonly used 16S rRNA amplicon data processing pipelines regardless of the observed batch effects and type of sequencing (v13 or v35) as well as from an OTU table comprised of different samples from the same environments.Several different factors including sampling strategy and sample handling, the choice of universal 16S rRNA gene PCR primers, DNA extraction methods, amplification artifacts, such as chimeras, and computational methods employed to produce the OTU table from sequencing reads may contribute to different results in the 16S rRNA gene profiling studies. All of them can affect the number of rare species and the produced Anets. To evaluate the robustness of the algorithm we explore changes in the structure of Anets based on OTU tables constructed by different processing pipeline, by different 16S rRNA gene variable region for sequencing, and by a different subset of oral samples. Namely, we consider three different OTU tables produced for oral samples by two commonly used 16S rRNA amplicon data processing pipelines, MOTHUR  and QIIMPopulus roots and on Human body sites we were able to reproduce associations of samples in these complex environment and associations of species that were consistent with the existing metadata and the analyses described in the previous literature. In case of Human microbiomes we were able to identify associations of co-dependent rare OTUs and link them to sub-sides of the human body. Similar observations were reported by Ding and Schloss  and North Carolina (12 trees) taken in May (23 rhizosphere samples and 21 endosphere samples) and in September (23 rhizosphere samples and 17 endosphere samples). Bacterial (16S rRNA) and fungal (28S rRNA) genes from the samples were sequenced to estimate the abundance of fungal and bacterial OTUs and their association with plant phenotypic, genotypic, and environmental parameters. We initially explore abundance–occupancy relationships in the dataset using all rhizosphere and endosphere samples of the study  and then focused our further analysis on 46 rhizosphere samples. The OTU table for these samples was processed using the Anets tool in two ways: (1) to build the association network of OTUs, Anets-OTUs, and (2) to build the association network of samples, Anets-Samples. The Anets-Samples was generated using the Pearson correlation as the measure of association for each pair of samples and a p-value threshold equal 0.01. The Anets-OTUs was generated using OTUs that occurred in 10 or more samples. This threshold was necessary to reduce time and memory used by the Anets program for processing the data. The p-value threshold was set to 0.05. Markov clustering  and includes 2910 samples obtained from 18 different body sites of 180 healthy men and women. Each site was represented by 145–190 samples, except the vagina (87–89 samples). The data is described in more detail by the Human Microbiome consortia publications  spring embedded layout in Cytoscape . The OTUs table of the samples was used as input for the Anets-OTUs algorithm with the following parameters: the minimum number of samples per OTU is 15, and a p-value threshold is 0.001. The stringent thresholds were important to limit memory use and the processing time for the Anets program. Markov clustering  spring embedded layout was used for the network visualization.The downloaded OTU table was processed using the Anets-Samples algorithm to build the association network of samples. The network was generated using the Pearson correlation as the measure of association for each pair of samples and the d before . The netytoscape . The Aneustering  with theustering  was usedThe analysis was used to find samples enriched in each cluster of OTUs in the Anets-OTUs and to find phenotypic or environmental characteristics enriched in each clusters of samples in the Anets-Samples. In both cases the analysis was done using the Fisher’s exact test to examine independence of rows and columns in a two-dimensional contingency table generated by the following algorithms.p-value < 0.05) with at least one other OTU in the Anets-OTUs. We classified the associated OTUs in two ways: if the OTU belongs to the sample or not, and if the OTU belongs to the cluster or not. Using this classification we created the contingency table with the number of the sample’s OTUs in the cluster, the number of associated OTUs in the sample, the number of OTUs in the cluster that are not from the sample, and the number of associated OTUs that are not found in the sample. Because we performed several statistical tests simultaneously on the same data set, p-values calculated by the Fisher exact were adjusted using Bonferroni correction.We identified samples enriched in the cluster of OTUs (Anets-OTUs) by linking each clustered OTU to the sample and finding those samples that have the greatest representation by OTUs within the cluster. We used the fisher.test function in R to calculate probability that the number of OTUs representing a sample in the cluster is significantly greater than the number expected by randomly selecting OTUs in the cluster from a set of all associated OTUs, regardless of sample of origin. All associated OTUs were found as a set of unique OTUs associated significantly (Populus rhizosphere dataset or body subsites in the HMP dataset) enriched in the cluster of samples (Anets-Samples) were identified by linking each sample to the characteristics and revealing the characteristics represented by the greatest number of samples within the cluster. We used the Fisher’s exact test to calculate probabilities that number of samples representing a characteristic within the cluster is significantly greater than the number expected by randomly selecting samples into the cluster from a set of all associated samples. In this case the background of the comparison was a set of all associated samples; they were classified for each cluster and each characteristic to create the contingency table as (i) representing the environmental/phenotypic characteristic or not and (ii) belonging to the cluster or not.Specific characteristics (such as soil conditions in the https://www.hmpdacc.org/hmp/HMMCP/ for 16S rRNA amplicon datasets processed by QQIME and the link https://www.hmpdacc.org/hmp/HMQCP/ for datasets processed by MOTHUR software package using a high stringency approach (p-value threshold to 0.05. The networks were loaded into Cytoscape software, visualized using spring embedded layout without edge weighting and clustered using MCL algorithm by a Cytoscape plugin ‘clusterMaker2’3 by setting the inflation value to 2.0. Another Cytoscape plugin ‘Network Analyzer’4 was used to explore topology of the networks and to produce their statistics.All datasets for validation were downloaded from the HMP website from the link approach . The ‘phapproach  was usedTK conceived the study. CWS contributed to the preparation, collection, and analysis of the data. JW, AF, CWS, and JZ provided mentoring guidance and advices throughout the study. TK, VG, JW, AF, CWS, and JZ contributed to writing 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.


Complicated crown-root fractures account for a small percentage of traumatic dental injuries seen in children; however, management of these injuries can be very challenging to clinicians. Factors such as complexity of the injury, patient's age and dentition stage, patient's cooperation, and parental demands may have some bearing on the type of treatment undertaken and its outcomes. In some children, these injuries may have significant impact on their quality of life. The purpose of this article is to describe two cases of complicated crown-root fracture which were successfully managed through orthodontic extrusion using a sectional fixed orthodontic technique. The basis for the treatment technique and its favourable outcomes were highlighted with its advantages and drawbacks. Dentoalveolar trauma accounts for 76% of cases seen among children with maxillofacial injuries . In the Of the different types of dental injuries, the crown fracture which accounts for a third of the injuries is the commonest type reported. In contrast, crown-root fracture only represents 0.3–5% of the injuries stated . Both thCrown-root fracture especially the complicated type with pulp involvement is one of the most difficult types of dental injury to treat. Factors such as the complexity and direction of fracture, size and mobility of the fractured tooth fragment, subgingival extension of the fracture line, stage root development, alveolar fracture, soft tissue injuries, and the pulp status of the affected tooth at the time of presentation may contribute toward the outcomes of the treatment . BesidesThis case report highlighted two clinical cases of complicated crown-root fracture of permanent central incisors in growing children with complex fracture lines. The challenges and possible treatment options with the basis of treatment selection were discussed. In addition, the preparation of the affected teeth prior to the root canal treatment and the use of sectional fixed orthodontic extrusion technique were also explained.An eight-year-old girl was referred by her general dental practitioner (GDP) to the National University of Malaysia (UKM) Paediatric Dental Clinic for management of an upper anterior tooth with a complicated crown-root fracture. The tooth fractured two days earlier due to a fall at a poolside. The patient was medical fit and healthy.Clinical examination revealed an oblique fracture from the labial surface of the upper left permanent central incisor tooth 21) extending palatally 3.5 mm beneath the gingival margin  plug. The following week, the canal was obturated with thermoplasticised GP, and the access cavity was restored with the self-cured GIC  archwire . The patA ten-year-old was brought to the to the National University of Malaysia (UKM) Paediatric Dental Clinic a month after an alleged fall at school by his mother. The patient had some discomfort during eating and felt there is something loose behind his front tooth. He was medically fit and well.Clinical examination showed a crown-root fracture of the upper right permanent central incisor (tooth 11) . The oblTM, Brasseler, USA) plug. The following week, the canal was obturated with thermoplasticised GP, and four orthodontic brackets were placed on the labial surfaces of tooth 12 to tooth 22  after chemomechanical debridement of the canals. The Endo Sequence Root Repair Material is a calcium silicate-based cement which exhibits high biocompatibility and has antibacterial and osteogenic properties. It can be used as an alternative to mineral trioxide aggregate [In the cases presented, both the teeth had complicated crown-root fracture and required RCT. One of the main challenges in carrying out RCT on crown-root fractured teeth is bleeding and crevicular fluid contamination from the gums which usually occurs after removal of the mobile coronal fragment. Two different approaches were undertaken to minimise the degree of contamination: in Case 1, the fractured crown was repositioned and held together in the reduced position with composite resin. The RCT was carried through the fractured crown. In Case 2, the coronal fragment was too loose for reattachment and had to be removed. GIC was placed on the palatal defect up to the supragingival level after control of gum bleeding. The GIC forms a continues rim with the tooth and allowed the gums to heal without any ingrowth into the defective area prior to the commencement of the RCT. Conventional GIC was used because it has better biocompatibility to gingivae than resin-modified GIC . Since bggregate , 15.Another treatment issue that required much attention was the subgingival fracture margins. In order to provide good and self-cleansing restoration, the restorative margin should be either equigingival or supragingival. As both the traumatic teeth had fractures extending subgingivally and had encroached into the biologic width, extrusion of the apical portion of the teeth was decided to bring the fractured margins close to the desired gum level. In order to achieve this, two options were considered, either the use of orthodontic extrusion or surgical extrusion. Although both methods have proven clinical successes to extrude teeth with minimal complications –18, orthWith regard to restoration of teeth with crown-root facture, factors such as the extent of the fracture, availability of tooth structure, presence of the tooth fragment, occlusion, aesthetic, and patient's age and cooperation may dictate the type of restoration needed. If the fractured coronal fragment is large and available, it could be reused to restore the tooth as demonstrated in Case 1. Another option is to do a composite build-up or composite crown with or without a postcore. Often in a growing child, a ceramic extracoronal crown is not considered as the restorative margins become visible with growth. On the other hand, composite-based restorations allow easy repair and adjustment.The current cases demonstrated the application of multidisciplinary approach in the management of teeth with crown-root fractures. The management displayed three main areas of expertise: the endodontics, orthodontics, and restorative. Each tooth with complicated crown-root fracture has its uniqueness and challenges that need to be taken into consideration during the treatment planning stage. The sectional fixed orthodontics used produced a favourable extrusion of the crown-root fractured teeth and may offer a better alternative to be used than other forms of modified removal appliances.


Stress can significantly impact brain function and increase the risk for developing various psychiatric disorders. Many of the brain regions that are implicated in psychiatric disorders and are vulnerable to the effects of stress are also involved in mediating emotional learning. Emotional learning has been a subject of intense investigation for the past 30 years, with the vast majority of studies focusing on the amygdala and its role in associative fear learning. However, the mechanisms by which stress affects the amygdala and amygdala-dependent fear memories remain unclear. Here we review the literature on the enhancing effects of acute and chronic stress on the acquisition and/or consolidation of a fear memory, as measured by auditory Pavlovian fear conditioning, and discuss potential mechanisms by which these changes occur in the amygdala. We hypothesize that stress-mediated activation of glucocorticoid receptors (GR) and norepinephrine release within the amygdala leads to the mobilization of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors to the synapse, which underlies stress-induced increases in fear memory. We discuss the implications of this hypothesis for evaluating the effects of stress on extinction and for developing treatments for anxiety disorders. Understanding how stress-induced changes in glucocorticoid and norepinephrine signaling might converge to affect emotional learning by increasing the trafficking of AMPA receptors and enhancing amygdala excitability is a promising area for future research. Stress is defined as any threat or perceived threat that disturbs an organism’s ability to maintain homeostasis. Although activation of the stress response is initially adaptive, long-term exposure to stress poses a significant risk for the development of numerous psychiatric disorders  is paired with an aversive stimulus, such as a foot shock . After the animal learns to associate the CS with the US, presentation of the tone alone elicits defensive responses that are characteristic of fear, such as freezing , which modulates AMPA receptors by increasing their conductance , which is the main input nucleus and a key site of plasticity underlying associative learning , from the adrenal medulla. The release of adrenaline acts directly on the cardiovascular system triggering peripheral responses, such as an increase in heart rate, respiration and blood pressure McEwen, . Stress Converging lines of evidence indicate that acute stress affects auditory fear conditioning by stimulating the local release of norepinephrine and activating GRs in the lateral and basal nuclei (BLA) of the amygdala. The most commonly reported effect of stress on auditory fear conditioning is an enhancement in memory consolidation. For example, acute stress or a single systemic injection of the glucocorticoid hormone corticosterone administered immediately after fear conditioning improves long-term memory  but not inhibitory neurons within the BLA ; National Institutes of Health (NIH) 5R24DA012136-13 and 1R21 MH109779-01 to PAS and by the National Institute on Minority Health and Health Disparities of the NIH under award number G12MD007599 to NSB.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. The reviewer AK and handling Editor declared their shared affiliation, and the handling Editor states that the process nevertheless met the standards of a fair and objective review.


Metastasis is the spread of cancer cells from a primary tumor to distant sites within the body to establish secondary tumors. Although this is an inefficient process, the consequences are devastating as metastatic disease accounts for >90% of cancer-related deaths. The formation of metastases is the result of a series of events that allow cancer cells to escape from the primary site, survive in the lymphatic system or blood vessels, extravasate and grow at distant sites. The metastatic capacity of a tumor is determined by genetic and epigenetic changes within the cancer cells as well as contributions from cells in the tumor microenvironment. Mouse models have proven to be an important tool for unraveling the complex interactions involved in the metastatic cascade and delineating its many stages. Here, we critically appraise the strengths and weaknesses of the current mouse models and highlight the recent advances that have been made using these models in our understanding of metastasis. We also discuss the use of these models for testing potential therapies and the challenges associated with the translation of these findings into the provision of new and effective treatments for cancer patients. Summary: This Review describes the currently available mouse models of metastasis, focusing on the mechanistic and therapeutic insights that have been gained by their application, strengths and weaknesses of different models and key technological advances that are generating more refined models. Metastasis, the process of tumor cell migration from the primary site to distant organs, remains the major cause of cancer-related deaths, despite therapeutic advances in recent years . This hiMetastasis is a multistep process, as illustrated in Allograft: The transplant of cells or organs from one individual to another individual of the same species.Cancer-associated fibroblast (CAF): Fibroblasts found within or in close proximity to a tumor. Usually derived from normal fibroblasts but can also be formed from pericytes (contractile cells that line capillaries) and smooth muscle cells, among other cell types.Circulating tumor cell (CTC): Tumor cells that have left the primary tumor and entered the circulatory system.Colonization: The processes  which allow disseminated tumor cells to form large macrometastases.loxPCre recombinase/: Cre recombinase enzymatically removes sequences that are flanked (floxed) by inserted loxP sequences.CRISPR/Cas9: Gene-editing technology that enables precise genomic modifications. This technology can be used to generate gene modifications, deletions and insertions, by using a synthetic guide RNA to introduce a double-strand break at specific sites in DNA, mediated by Cas9 endonuclease.Disseminated tumor cell (DTC): Tumor cells that have settled in distant organs away from the primary tumor site after exiting the circulatory system.Ectopic: The transplantation of a cell type to a location in which it is not found under normal physiological circumstances.Epithelial-to-mesenchymal transition (EMT): Loss of cell-cell adhesion complexes and cell polarity by an epithelial cell, and the gain of an invasive, migratory, mesenchymal phenotype.Exosome: Extracellular vesicles that are released from cells after the fusion of multivesicular bodies with the plasma membrane.Extracellular matrix (ECM): The acellular support surrounding tissues.Extravasation: The process by which a tumor cell leaves the circulatory system and enters a secondary site away from the primary tumor.Genetically engineered mouse model (GEMM): A mouse with a genome altered by genetic engineering techniques, including gene deletion, mutation or addition. This can be performed in a tissue- or cell-specific manner and may also be inducible.Immunocompromised mice: Mice in which specific elements of the immune system have been removed to allow engraftment of human material.Integrin: Transmembrane receptor protein that cells use to adhere and respond to the extracellular matrix.Intravasation: The process by which a tumor cell leaves the primary tumor and enters the circulation.Invadopodium: Actin-rich protrusion present at the membrane of invasive cancer cells that extends and degrades the extracellular matrix.Micrometastasis: Small clusters of cancer cells in secondary organs that are too small to detect through screening.Organoids (tumor): three-dimensional cultures of tumor cells.Orthotopic: The transplantation of a cell type or organ to a location in which it would be found under normal physiological circumstances.Patient-derived xenograft (PDX): A model in which human patient tumor material is implanted into an immunocompromised host, most commonly the mouse.Seeding: In the context of metastasis, seeding refers to the process whereby tumor cells ‘seed’ new tumors in distant organs. Originally described in Stephen Paget's ‘seed and soil’ hypothesis of cancer metastasis  or transcellularly .Tumor-associated macrophage (TAM): A macrophage found within or in close proximity to a tumor that actively promotes tumor growth through the secretion of cytokines and chemokines.Tumor microenvironment: All elements that make up the surroundings of the tumor, including other cell types, vasculature and the extracellular matrix.Xenograft: The transplant of cells or organs from one species into an individual of a different species.Pre-metastatic niches are organ-specific supportive biological environments that support survival of CTCs in distal organs and promote metastatic outgrowth. The formation of the pre-metastatic niche is governed by secreted factors from the primary tumor, including growth factors and inflammatory cytokines and chemokines. Recent studies found that tumor-derived exosomes can also promote niche establishment and determine organ specificity in some types of cancer; however, whether it is a common feature for pre-metastatic niche formation remains unclear. These tumor-derived secreted factors induce changes in distant pre-metastatic sites while also mobilizing bone marrow-derived cells, the recruitment of which – along with a number of other types of immune cell – to the niche leads to remodeling of the local environment and formation of the pre-metastatic niche. This involves interactions with local resident stromal cells, such as endothelial cells, macrophages and fibroblasts, and also the extracellular matrix, which all cooperate to form a permissive environment for tumor outgrowth. For example, activated fibroblasts remodel the ECM by secreting matrix components such as fibronectin and metalloproteinases that break down existing ECM. Increased fibronectin in the niche enhances adhesion of recruited bone marrow-derived cells. Lysyl oxidase, an enzyme that cross-links collagen and elastins in the ECM, is also important in the formation of the pre-metastatic niche; by remodeling the ECM, this enzyme enhances myeloid cell infiltration. For further information, readers are directed to two reviews on the formation and role of the pre-metastatic niche .After entry into the circulation, tumor cells can disseminate widely throughout the body and are known as circulating tumor cells (CTCs)   , which overcome the problem of limited metastatic potential   that have a predisposition to tumor formation  is fused to Cre recombinase: treatment of mice with the estrogen analogue tamoxifen leads to activation of Cre recombinase in a temporal manner . The tetppressor . These mAn important limitation of GEMMs is the low incidence of metastatic spread that often does not reflect the organ tropism seen in the human disease . AlthougDespite the limitations discussed above, mouse models have made important contributions to our understanding of cancer progression and metastasis. Here, we highlight some recent advances in which mouse models have been instrumental in defining the key drivers and features of metastatic cancer. We also outline the usefulness of these models as preclinical drug development tools.In vivo metastasis models are important tools to investigate the interaction of tumor cells with tumor-associated stromal components. Within this complex microenvironment, several immune cell populations have been shown to promote tumor invasion and metastasis  GEMM of pancreatic cancer, where mutations in Kras and Trp53 drive the development of spontaneous pancreatic ductal adenocarcinomas  derived from UV-damaged keratinocytes. This neutrophil recruitment led to enhanced tumor migration and invasion resulting in distal metastasis . More rercinomas , neutroprcinomas .+ T helper cells expressing Type 2 cytokines , have been shown to promote tumor progression via activation of humoral immunity and inflammation  model, and transplanted tumor fragments from this KEP model into recipient mice. Metastatic development was monitored following resection of the primary tumor, and the authors observed that systemic expansion of neutrophils significantly promoted spontaneous metastasis to the lungs and lymph nodes by suppressing a CD8+ T cell-mediated anti-tumor immune response  and cancer-associated fibroblasts (CAFs)  can be significantly promoted by distal tumors in an insulin growth factor (IGF)-II-dependent manner . Using aogenesis . Howeverogenesis . Thus, mImmune rejection is a key factor that limits the efficiency of tumor engraftment in immune-competent preclinical models, even when the tumor and host are both from the same syngeneic background . It is pin vitro studies were lacking.Epithelial-to-mesenchymal transition (EMT)  oncogenes, Fischer and colleagues also established that EMT and metastasis might not be as intricately linked as first thought . By usinin vivo without experimental modulation of genes commonly thought to regulate EMT. Models that are able to accurately recapitulate the metastatic cascade without experimental gene modulation are key tools in uncovering the events involved, but in a way that reflects in situ processes as closely as possible. The use of lineage tracing to assess the contribution of EMT to metastasis has the potential to help uncover the gene signature of cells that are able to colonize secondary sites.The use of intra-vital imaging has helped unravel the complexities associated with tumor cell plasticity and metastatic spread. In the MMTV-PyMT mammary tumor model, Beerling and colleagues used a fluorescent epithelial marker (E-cadherin-CFP) combined with intra-vital imaging to show that EMT is a reversible, plastic process and that mesenchymal cells that reach secondary sites can rapidly regain an epithelial phenotype . In contmT/mG; MMTV-PyMTROSA, from which organoids  that can be used to model prostate cancer  cells, interaction of platelet integrins with collagen at specific regions of the endothelium may help tumor cell adherence at secondary organs and determine the site of metastatic tumor cell extravasation . A recenex vivo intact lung imaging in the same model revealed that macrophages (and not monocytes) directly contact the extravasating tumor cells, and depletion of these macrophages significantly reduces the number of tumor cells that complete extravasation  has been characterized in the target organ (lung). Depletion of these MAMs using transgenic CD11b-diphtheria toxin receptor (DTR) mice significantly reduces metastatic seeding and persistent growth of breast cancer cells . One cavvasation .Adhesion signaling also plays an important role in the survival of tumor cells within the metastatic niche. Using an innovative method of experimental bone metastasis in which breast cancer cells were injected into the iliac artery of mice , in vitro experiments demonstrated that distinct endothelial niches can induce dormancy through the secretion of thrombospondin-1  in immune competent hosts has led to their adoption for preclinical assessment of drug response and mechanisms of resistance . GEMMs aPDX models are also predicted to be a major advance in preclinical testing platforms as they recapitulate the tumor heterogeneity that plays such an important role in tumor biology, including response to therapy. A number of therapeutic studies have demonstrated their value in linking response with genetic alterations and identifying mechanisms of resistance and biomarkers, while use of humanized mice recipients will further enhance their value as we look at the potential for testing immunotherapies . HoweverThe increasing use of imaging modalities that allow noninvasive longitudinal monitoring of metastases will help more accurate detection and quantification of metastatic disease in deep tissue sites. This technology is thus likely to enhance the usability of GEMMs and PDXs. Recent advances in preclinical magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET) and single-photon emission computed tomography (SPECT) are showing promise .A greater understanding of the pathways that drive metastatic spread and what is achievable in the clinical setting gives hope that anti-metastatic therapies will be viable in the future. For example, targeting metastatic colonization, which is often the rate-limiting step in the metastatic cascade holds great potential, but it will be important to provide robust preclinical evidence of activity in appropriate animal models that accurately reflect the clinical scenario in which the therapy will ultimately be tested in. Careful thought to clinical trial design with appropriate primary endpoints is also essential.Mouse models have been essential in advancing our understanding of the biological processes that drive tumor progression. However, metastatic cancer remains the main cause of cancer-related deaths, with new treatments desperately needed. Increasing our understanding of what drives metastatic spread is key to achieving this goal. This will require the further development and refinement of mouse models to more faithfully mimic human disease and progression.loxP and Flp-FRT systems (in vivo transplantation models (A number of technological advances have allowed the further development of GEMMs. These include combined use of the Cre- systems  that all systems  has been systems . It is h systems . For exa systems . RNA intn models ; the valin vitro models that try to recapitulate the complexity of the tumor microenvironment is a major area of ongoing research. Models include co-culture of tumor cells with different stromal cell types and 3D engineered matrixes, with developments in 3D bioprinting and microfluidics platforms having the potential to significantly impact on the design and reconstruction of the complex tumor microenvironment (in vitro models have the potential to be used as drug screening platforms and could guide the preclinical testing of new agents in mouse models.The design of more biologically relevant ironment . Coupledironment . The desAdvances in intra-vital imaging have shown great potential for elucidation of the close interplay between tumor and host cells , and funAlthough much is known about the biological pathways that control the individual steps in the metastatic cascade, a number of important questions remain. Uncovering the underlying mechanisms that govern the enormous diversity in the onset and target organs affected in patients and identifying whether there are common mechanisms at play will be important. In addition, understanding the fundamental differences between primary and secondary tumors and the drivers of metastatic colonization is essential to identifying strategies for targeting metastatic disease, and would have a major impact on the survival of cancer patients. The technological advances in the generation of mouse models that better mimic human disease, combined with advances in imaging, will allow for the translation of such research into meaningful treatments.


Mycobacterium bovis and the potential for transmission of infection to humans is often the fundamental driver for surveillance of disease in livestock and wild animals. However, with such a vast array of species susceptible to infection, it is often extremely difficult to gain a detailed understanding of the pathogenesis of infection––a key component of the epidemiology in all affected species. This is important because the development of disease control strategies in animals is determined chiefly by an understanding of the epidemiology of the disease. The most revealing data from which to formulate theories on pathogenesis are that observed in susceptible hosts infected by natural transmission. These data are gathered from detailed studies of the distribution of gross and histological lesions, and the presence and distribution of infection as determined by highly sensitive bacteriology procedures. The information can also be used to establish the baseline for evaluating experimental model systems. The European badger (Meles meles) is one of a very small number of wild animal hosts where detailed knowledge of the pathogenesis of M. bovis infection has been generated from observations in natural-infected animals. By drawing parallels from other animal species, an experimental badger infection model has also been established where infection of the lower respiratory tract mimics infection and the disease observed in natural-infected badgers. This has facilitated the development of diagnostic tests and testing of vaccines that have the potential to control the disease in badgers. In this review, we highlight the fundamental principles of how detailed knowledge of pathogenesis can be used to evaluate specific intervention strategies, and how the badger model may be a paradigm for understanding pathogenesis of tuberculosis in any affected wild animal species.Tuberculosis in animals is caused principally by infection with  Meles meles) is the principal wild animal species involved (Sus scrofa) (Capra hircus) (Cervus elaphus), fallow (Dama dama), and roe deer (Capreolus capreolus) are affected in continental Europe (Trichosurus vulpecula) is the key species affected (Odocoileus virginianus) (Cervus canadensis) (Bison bison)  , goats ( hircus)  and specl Europe . In New affected . In Nortinianus)  elk (Ceradensis)  and bison bison)  are amonn bison) . With liThere has been much written about the value of laboratory animals as surrogates in studying tuberculosis . This isM. bovis) are all subject to the same constraints when applying the interpretation of the results across species , leading to proliferation of T lymphocytes, secretion of interleukin-2 (IL-2) and release of pro-inflammatory cytokines including interferon-γ (IFN-γ)  –43. The nfection . Serolognfection . The immnfection , 47. Therculosis  and M. bovis BCG . Nitric arginine  in a reaarginine . Howeverrophages . This inM. bovis infection. In developing the badger infection model for tuberculosis in Ireland, the key factors that were considered to achieve this end were the choice of M. bovis strain, route of infection, the infective dose, and the kinetics of infection. The strain of M. bovis used for experimental infection was first isolated from a lesion in a clinically diseased badger , to gross lesions in the lungs, draining and extrathoracic lymph nodes, and pleura. The experimental infections appeared to mimic the more severe end of the spectrum of lung disease found in natural-infected badgers in that pulmonary lesions ranged from 1- to 2-mm diameter discrete tubercles, to extensive miliary lesions, with consolidation and pervading caseation of lobes  with bovine purified protein derivative tuberculin (PPD-B), increased to levels associated with the infective dose and pathology recorded postmortem . The badThe aim of the follow-up study was to describe pathological, bacteriological, and immunological changes over a 24-week infection period using only the high-dose rate , 53. InoA key feature of the badger experimental model has been the dose-dependent recreation of different states of infection, ranging from latency to clinical disease, all characteristic of natural infection. This is unique among natural hosts of infection in that each state in the badger can be defined by a combination of pathological and immunological parameters. In human tuberculosis, latency  is significant in the epidemiology of disease , 55. Lat5 CFU) and application to mucosal membranes . This latter route of immunization facilitated the delivery of BCG directly to an available mucosal surface, as a proxy route for delivery of an oral vaccine. With this protocol, the BCG was likely to be presented to the immune system via lymphoid tissues of the nasal cavity and/or conjunctiva. Inhaled aerosol particles may also have been exposed to the lymphoid tissues of the lower respiratory tract.Having established an experimental infection model that mimics the characteristics of moderate-to-severe natural disease, the studies progressed to evaluating BCG vaccine protection using the endobronchial experimental infection model , 58. A s4 CFU M. bovis) infection was established in all vaccinates and in all of the control group. Compared with the controls, vaccinates had fewer sites of infection, sites of extrathoracic infection, and sites with gross lesions. In the group vaccinated by the subcutaneous routes, all these measures were lower than for those vaccinated by the mucosal route. Vaccination also altered the distribution of gross lesions following challenge with no extrathoracic gross lesions in the vaccinates. These effects were more pronounced for the subcutaneous group. It was 2 weeks after M. bovis challenge that the subcutaneous vaccinated group responded to PPD-B, whereas the remaining groups responded from 4 weeks postchallenge. Over the period of infection, the highest immune responses were recorded in the non-vaccinated/infected control group. The immune profiles observed also associated with lesion severity scores measured at postmortem in all groups. Vaccination was also expressed by a significant delay in seroconversion to MPB83, which correlated with the levels of severity of the disease in all groups. From an immunological perspective, an intriguing finding was the lack of CMI activity in response to vaccination, as measured by IFN-γ production. This has been found in other captive badger studies and there is evidence that it correlates positively with the dose of vaccine delivered  on protective effect and the distribution of infection after experimental challenge  by intratracheal/endobronchial inoculation or by aerosol-generating systems has resulted in lesions similar to those detected in the lungs and associated lymph nodes of natural-infected animals (M. caprae) or aerosol delivery (M. bovis) have been carried out in goats  revealed different clinical outcomes with lesion scores ranking highest with M. bovis, then M. caprae and M. tuberculosis  are susceptible to infection with M. bovis and are considered as part of the epidemiology of M. bovis transmission in New Zealand  is considered as a key maintenance host for tuberculosis in Spain with prevalence rates >50% in areas with high-density populations (M. bovis was delivered to boar by the oropharyngeal route using a range of infective doses between 102 and 106 CFU (The wild boar (ulations . Vaccina 106 CFU . All fouM. bovis via conjunctival instillation resulted in established infection in a dose-dependent manner (M. bovis suspension into the paws resulted in gross lesions in superficial lymph nodes as is observed in natural-infected possums (M. bovis transmission was lowest when animals were mixed at random; however, transmission increased significantly with mixing of more sociable possums. This indicated that transmission was influenced by the proximity of susceptible and infected possums leading to increased frequency and duration of social interactions.Routes of infection not observed in natural-infected wild animals have been used in experimental infections to achieve particular outcomes. Such alternative inoculation routes have been used to experimentally infect New Zealand brushtail possums to counter the high susceptibility of these animals to experimental infection and the rapid progression of disease. Delivery of t manner . The inf possums . As with possums . Natural possums . The ratThough the presence of visible lesions, whether in experimentally infected or in natural-infected animals, can point toward the likely route of natural infection, caution must be taken in interpreting such data when only a limited number of infection parameters are measured. This highlights one of the difficulties when working with relatively large animal species to understand pathogenesis. The sensitivity of detection of infection can be severely compromised in large animals, such as cattle and deer, simply because of the difficulty of detecting small lesions or infection in large organs and lymph nodes . This caEven when using natural-infected animals across a broad spectrum of disease, the interpretation can be subjected to bias if insensitive protocols for bacteriology and histology are employed. In studying the disease in natural-infected badgers, we tried to minimize these biases by randomly sampling from the infected population and by using sensitive bacteriological and histological procedures on a predetermined set of 36 tissues covering a wide range of anatomically diverse tissue samples in each animal. In addition, the tissues for bacteriology were collected aseptically so that the bacteriological detection of infection was maximized and tissues were individually cultured for the same reason . This inM. bovis infection is naturally endemic in a diverse range of domestic and wild animals, as well as in humans. Experimentally, at least, it seems that most animal species are susceptible to infection. With the continuous threat of infection spreading from wild animals to livestock and the risk of onward transmission to humans, the continued improvement in knowledge of pathogenesis and epidemiology will serve to lessen the transmission risks into the future.The pathological and bacteriological examination of natural-infected badgers with tuberculosis when using sensitive postmortem examination procedures has provided an important and essential baseline for understanding the pathogenesis and epidemiology of tuberculosis in this species. It has also provided the framework for developing experimental infection studies, which has allowed the evaluation of diagnostic assays and the measurement of vaccine efficacy. There is a growing awareness that EG and LC contributed equally to this review including critical analysis of published data and preparation of 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.


A group of 240-day-old Ross cockerels were used in a 4-week experiment to assess the effect of the fat type on the intestinal digestibility of fatty acids (FAs), the FA profiles of breast meat and abdominal fat, and the mRNA expression of six hepatic lipid-related genes. Experimental diets were supplemented with rapeseed oil, pork lard or palm oil at 60 g/kg. In the control diet, wheat starch was substituted for the fat source. The highest ileal digestibility of the fat and all FAs (except stearic acid) was observed in chickens fed lard. The content of fat in the breast meat of chickens was not significantly influenced by the fat supplements. The FA profiles of breast meat and abdominal fat reflected the FA composition of the diet. In the meat of chickens fed rapeseed oil, oleic acid was the predominant FA. Palmitic acid was the most abundant FA in the meat of chickens fed lard or palm oil. Oleic acid was the most abundant FA in the abdominal fat of all chickens. The highest mRNA expression of desaturases  was observed in chickens fed palm oil. The mRNA expression of hepatic FA synthase was higher in chickens fed palm oil or lard than in chickens fed rapeseed oil. The expression of HMG-CoA reductase was higher in chickens fed palm oil than in those fed rapeseed oil or lard. It can be concluded that rapeseed oil and lard are better sources of lipids than palm oil. These former two sources contain more digestible fatty acids and provide a lower concentration of SFAs in the meat and fat of chickens. The FA profile in breast meat was primarily affected by the FA profile of the feed. In abdominal fat, MUFAs dominated in all groups of chickens. This dominance may be related to the difference between structural and depot lipids .r = 0.908; P < 0.001), suggesting a significant conversion of linoleic acid by Δ6-desaturase. This result also suggests a significant activity of FA elongase because the addition of two carbons was also necessary.Both breast meat and abdominal fat are edible parts of the chicken body. Information on the effects of FAs on human health is extensive , 20, 21.de novo synthesis.In chickens fed lard or palm oil, the relative proportions of PUFAs were 15–16% of the total FAs, which was less than that in the respective diets (24 and 22%). Oleic acid dominated the lipids deposited in the bodies of all chickens. This dominance may be related to the fact that the oleic acid content in tissue lipids depends not only on the oleic acid intake but also on Evaluating the relationship between biochemical parameters and mRNA levels is one way to evaluate the relevance of gene expression data. Musa et al. (2007)  noticed de novo FA synthesis. This is consistent with the results obtained in our experiment. The expression of FA synthase mRNA was higher in chickens fed palm oil or lard than in those fed rapeseed oil. HMG-CoA reductase is the rate-limiting enzyme of cholesterol synthesis. Its expression was higher in chickens fed a diet supplemented with palm oil or lard. This observation is consistent with the finding that the substitution of rapeseed oil for lard significantly decreased the cholesterol concentration in chicken breast muscle [Sanz et al. (2000)  reportedt muscle .Carnitine palmitoyltransferase is a mitochondrial enzyme responsible for the transfer of activated FAs inside the mitochondria for β-oxidation. Literature data regarding the dietary effects on carnitine palmitoyltransferase activity are ambiguous. Smink et al. (2010)  reportedIn this study, three fat supplements with different fatty acid profiles were compared in the diets of broiler chickens. The digestibilities of the fatty acids in rapeseed oil and lard were higher than that in palm oil. The use of rapeseed oil in the diets of broiler chickens provided the optimum composition of fatty acids in the breast meat and fat. The mRNA expression of genes associated with lipid metabolism is consistent with this opinion.


Breast cancer is the most prevalent cancer that affects women all over the world. Early detection and treatment of breast cancer could decline the mortality rate. Some issues such as technical reasons, which related to imaging quality and human error, increase misdiagnosis of breast cancer by radiologists. Computer-aided detection systems (CADs) are developed to overcome these restrictions and have been studied in many imaging modalities for breast cancer detection in recent years. The CAD systems improve radiologists' performance in finding and discriminating between the normal and abnormal tissues. These procedures are performed only as a double reader but the absolute decisions are still made by the radiologist. In this study, the recent CAD systems for breast cancer detection on different modalities such as mammography, ultrasound, MRI, and biopsy histopathological images are introduced. The foundation of CAD systems generally consist of four stages: Pre-processing, Segmentation, Feature extraction, and Classification. The approaches which applied to design different stages of CAD system are summarised. Advantages and disadvantages of different segmentation, feature extraction and classification techniques are listed. In addition, the impact of imbalanced datasets in classification outcomes and appropriate methods to solve these issues are discussed. As well as, performance evaluation metrics for various stages of breast cancer detection CAD systems are reviewed.  Breast cancer is the most common cause of death after lung cancer in the world. Early detection and efficient treatment of breast cancer could increase the treatment options and decline the mortality rate. Different modalities such as mammography, ultrasound, and Magnetic Resonance Imaging (MRI) are the most effective tools in the early detection of breast cancer. Issues such as technical reasons, which are related to imaging quality and human error have increased the misdiagnosis of breast cancer in radiologists' interpretation. In the effort to overcome such restrictions, CAD systems are developed to automated breast cancer detections and classify benign and malignant lesions. The CAD systems improve radiologists' performance in finding and discriminating between the normal and abnormal tissues. These procedures are performed only as a double reader but the absolute decisions are still made by the radiologist.Recent advances in the resolution of medical imaging modality have revolutionised the diagnostic accuracy. Efficient usage of imaging data to improve the diagnosis is very important. In recent years, computer-aided diagnosis systems (CADs) have developed a new context in radiology to take advantage of the data to be applied to different imaging modality and the diagnosis of different diseases. The efficiency of radiologists' interpretation can be improved in terms of accuracy and consistency in detection or diagnosis while productivity can be improved by reducing the time required to read the images . The ouIn relation to breast cancer, the main objective of CAD system is to design accurate and reliable approach, to decrease observational oversights and assist in discriminating benign and malignant lesions. In the following, we present some of the recent proposed CAD systems for breast cancer detection or diagnosis on various modalities such as mammography, ultrasound, MRI, and biopsy histopathological images. Mammography is a dedicated imaging modality for breast screening that uses low-dose X-ray during breast examination. Mammography is currently the most effective tool for early detection of breast cancer; however, it has some restrictions. Breast density is a variety of confounding factors that make diagnosis of breast cancer more difficult in women with dense breasts . The coDouble reading is one of the solutions that can significantly contribute to achieving high sensitivity and specificity . DetectAnother lesion in the breast is mass, which; is a circumscribed lump in the breast and might be categorised to be benign or malignant. Masses are characterised by various attributes such as shape , margin , size, location, and their contrast. Mass detection is more difficult compared to micro-calcification because of the similarity and ambiguity of their characteristics with the normal tissue  provides additional information of anatomical and vascular flow related, which assists the differential diagnosis of breast lesions .The studies indicate that ultrasound is able to detect and discriminate benign and malignant masses with high accuracy and also reduce the number of unnecessary biopsies . Chabi Since nearly three decades, MRI screening has been employed for detection and diagnosis of breast cancer lesions . BreastBiopsy is the final stage when a mammogram or other imaging modalities found any type of abnormality. During a biopsy, a sample is taken from suspicious lesion in order to conduct microscopic observation. There are several types of biopsies such as fine needle aspiration biopsy (FNAB), core biopsy, or surgical biopsy. FNAB is a common type of biopsy and during the examination; a cytological sample is obtained from the tumour and explored under a microscope to determine the occurrence of cancer cells. The main disadvantage of FNAB is that the needle cannot extract sufficient amount of tissue for diagnosis. Detection of cancer cells requires profound knowledge and sufficient experience in the field of histopathology . A visiIn contrast to other CAD systems, fewer studies performed the analysis of breast histopathology images. Issac Niwas et al. (2012) have usMedical image processing requires prior knowledge on the content and nature of image to select appropriate methods to implement the CAD system. In order to achieve a high level of efficiency for automated diagnosis, it is significant to employ efficacious image processing approaches in the main steps of CAD system. Commonly, the CAD systems consists of four stages as shown in Figure 1A brief description of the main stages of a CAD system is provided as follows:Image pre-processing: This step is essential for some modality such as ultrasound for the purpose of enhancing the image and reducing the noise with minimum distortion of image features. Some of the CAD systems do not have a pre-processing stage.Image segmentation: Image segmentation is a vital step towards efficient development of CAD systems. The main purpose of segmentation is the separation of the region of interest (ROI) commensurate with the desired properties . RecentFeature extraction and selection: In this step, different features are extracted according to the characteristics of lesions from the image. These features are used to distinguish benign or malignant lesions. The feature set is usually very large and the selection of the most effective features is very critical for the next step.Classification: According to the selected features, the suspicious areas are classified to benign or malignant based on different classification techniques. The common classification methods used in medical imaging are presented in this section.Performance evaluation: This step evaluates the performance of CAD system.In medical image processing, image pre-processing plays a significant role to achieve the ideal outcomes in other stages of a CAD system such as segmentation and feature extraction. Pre-processing stage is performed to remove noise and defect caused in image acquisition procedure, image resizing, and enhance the image intensity .Image segmentation is a crucial component in computer vision and pattern recognition. Accurate segmentation plays a significant role in the success or failure of the computerised procedure. In medical imaging aspect, the selection of segmentation methods are widely depending on the specific application and imaging modality. With increased dimension and resolution of the image in various modalities, the images cannot be manually examined with regard to the huge amount of image information. Segmentation techniques help to highlight significant regions and extract various structures such as organs or tumours for further examination.Segmentation methods are categorised generally into two groups: semi-automatic and fully automatic. Providing an automatic algorithm in medicine to detect and localise abnormality is highly desirable. In medical application, the low rate of false positive and false negative detection is very important. Therefore, evaluation methods of segmentation algorithms is another dimension of CAD systems in the practical aspect. Segmentation approaches based on image properties are broadly arranged into two groups: discontinuity-based approach and similarity-based approach. Discontinuity-based approach partitions an image based on an abrupt change in intensity , while Edge-based segmentation methods are a structural technique to detect edges or pixels among different regions that have abrupt intensity change . The edOne of the wide methods used for image segmentation is a thresholding-based technique which is an effective way to discriminate foreground from the background image . The fiThe thresholding-based methods have been widely used to develop CAD systems in order to extract significant areas for additional analysis. In the article of Al-Bayati and El-Zaart (2013), variouThe region-based segmentation methods divide an image into homogeneous regions of connected pixels based on predefined criteria such as intensity, colour, or texture. Region-based approaches are broadly classified into two groups: region growing and region split and merging . Seed sIn recent years, region-based segmentation algorithms are widely used to develop CAD systems for breast cancer detection. A region growing approach is applied to the extraction of a region of interests (ROIs) in this article . AnotheClustering-based segmentation methods are popular techniques in medical image segmentation and generally categorised into hierarchal and partitional clustering . HierarClustering methods are potentially very beneficial in clinical image segmentation. Authors have presented adaptive K-means clustering technique  and FuzRecently, imaging modalities such as magnetic resonance imaging (MRI), computed tomography (CT), 3D ultrasound, CTLM and many more modalities are capable of producing images in the form of 3D. Therefore, 3D segmentation methods are desirable for more accurate segmentation in volumetric imagery. Some approaches have been proposed on different modalities such as breast MRI  and autThe development of reconstruction algorithms has been the attention of many researchers in latest work since the reconstruction of 3D images for consecutive images, due to its various applications in surgery, teaching anatomy, and diagnosis . In theComputing feature descriptors from an image to reduce the volume of data ordinarily signifies feature extraction. Features are characteristics of the whole image or region of interests. The proper selection of features has an important influence on (1) memory size, (2) accuracy of classification, (3) computational cost of classification and (4) robustness. Feature descriptors and metrics widely depend on the specific application. Generally, image descriptors are divided into the three dimensions. Figure 3According to the literature . A brieColour-based descriptors are the significant visual cue for image retrieval and object recognition . The coShape feature extraction plays a significant role in various application such as shape retrieval, shape recognition, and classification, and shape alignment and registration . A hierThe shape is one of the main visual cues in medical image processing, thus shape descriptors are widely used to design the feature extractors in CAD systems. In recent years, shape feature extraction has been receiving more attention in the case of breast cancer detection. In order to classify malignant or benign calcifications in mammograms, Shen et al. (1994) have prZhang et al. (2012), have dAz) of 0.79 under the receiver operating characteristics  for theal., 2001) curve. In Gc et al. 2015), three , three 1Texture features also are another expression of visual characteristics that is convenient for various domain of computer vision and pattern recognition. A hierarchical view of different texture description approaches is collected in Figure 6Texture or pattern is another visual clue in medical image processing, which are widely applied to design the feature extractors in CAD systems. Recently, several researchers have used textural features for the development of breast CAD system. The co-occurrence texture feature is one of the significant features that are widely used in the design of CAD system. A fuzzy support vector machine is presented to classify mass using ultrasound images .Az) in this work were 94.25 %, 91.67 % and 0.964, respectively. Textural features consist of co-occurrence matrix based on spatial grey level dependence (SGLD), fractal features, and histogram-based features extracted and transferred into fuzzy support vector machine classifier (FSVM). The obtained accuracy, sensitivity and area  have emTo conduct an analysis of the 3D morphology between benign and malignant tumours in breast MRI images, a set of texture features are used: GLCM features, Energy, Entropy, Correlation, Difference Moment, Inertia, Cluster Shade, Cluster Prominence, Horlick's Correlation . The reA particle swarm that optimised wavelet neural network (PSOWNN) is presented based on texture features for breast cancer detection in mammogram images . Laws tClassification is the last stage in CAD systems that differentiates and labels of the abnormality. Classification methods play an important role in the diagnosis and educational purposes in medicine. Classification approaches are categorised into two groups as shown in Figure 7Supervised classification examines a large number of unknown data and assigns them into related classes based on their characteristics. The main difference between unsupervised and supervised methods is that the unsupervised do not require pre-determined class. In a successfully supervised classification, all classes should be defined and the spectral properties of these classes have to be extracted during the training phase. However, in unsupervised classification, classes may be discovered but not known in advance. A brief description of the most popular supervised classification techniques along with their advantages and disadvantages are proposed in Table 3The imbalance dataset is a crucial issue in various pattern recognition applications. In binary classification, this problem occurs when the number of instances from one class is significantly less than the other class. In this situation, the overall predictive accuracy is achieved by the majority class while the minority class has a greater impact on the classifier performance. The impact of the imbalanced data in the real-world applications is the irreversible effect on classification performance, specifically in medical diagnosis. Due to delays in diagnosis and treatment, the patient may lose their lives. To deal with the imbalanced dataset, several approaches have been presented in functional level and data level . Some sThe cost-sensitive learning offers another way to address the imbalanced dataset issue. In cost-sensitive classification approaches, the sensibility of a classifier for a specific class can be increased by assigning a higher cost of misclassification to this class . The miAt the data level, these solutions contain multitude variant forms of re-sampling such as random over-sampling, random under-sampling, directed over-sampling, directed under-sampling, and combinations of the above techniques. The rise of the likelihood for overfitting is the main drawback of random over-sampling techniques due to the replicating of minority instances . ChawlaHe et al. (2008) presentRandom majority under-sampling is a common technique for under-sampling imbalance data . The maThe selection of a reliable classifier is critical to succeed in distinguishing benign breast tumours from malignant ones. Different classification approaches have been developed for breast cancer detection in different modalities. Artificial intelligent techniques and support vector machines have been widely investigated to develop classification frame work in the diagnosis of breast cancer in recent years. A comparison of SVM, K-means cluster, and neural network have been presented in Liu et al. 2003) to diag003 to diEvaluating the true performance of the classifier is the last stage in CAD system. The outcome of binary classification  is presented in a 2×2 confusion matrix in Figure 8Receiver operative characteristics  is a twIn recent years, CAD systems are developed to automate breast cancer detections and classification of benign and malignant lesions in different modalities such as ultrasound, mammography, and MRI. The CAD systems improve radiologists' performance in finding and discriminating between normal and abnormal tissues.The main stages of implementation of CAD system and different techniques for each specific step were categorised and presented in this chapter. The region-based segmentation and clustering-based algorithms are wildly used to develop CAD systems for breast cancer detection. Extract suitable features for the detection of normal and abnormal lesions in breast depends on the nature of mass and imaging modalities, in which various features were introduced in this chapter. Artificial intelligent techniques and support vector machines have been widely investigated to develop classification frame-work in the diagnosis of breast cancer in recent years. The imbalance dataset is a crucial issue in various pattern recognition applications. To deal with the imbalanced dataset several approaches have been presented in functional level and data level . Kernel


Polyamines (PAs) are natural compounds involved in many growth and developmental processes in plants, and, specifically in fruits, play a vital role regulating its development, ripening and senescence processes. Putrescine (PUT), spermine (SPE), and spermidine (SPD) are prominent PAs applied exogenously to extend shelf life of fruits. They also originate endogenously during developmental phases of horticultural crops and simultaneously affect the quality attributes and shelf life. Their anti-ethylene nature is being exploited to enhance the shelf life when exogenously applied on fruits. In growth and development of fruits, PA levels generally fall, which marks the beginning of senescence at postharvest phase. PUT, SPE and SPD treatments are being applied during postharvest phase to prolong the shelf life. They enhance the shelf life of fruits by reducing respiration rate, ethylene release and enhance firmness and quality attributes in fruits. PAs have a mitigating impact on biotic and abiotic stresses including chilling injury (CI) in tropical and sub-tropical fruits. PAs are environment friendly in nature and are biodegradable without showing any negative effect on environment. Biotechnological interventions by using chimeric gene constructs of PA encoding genes has boosted the research to develop transgenic fruits and vegetables which would possess inherent or in situ mechanism of enhanced biosynthesis of PAs at different stages of development and thereby will enhance the shelf life and quality in fruits. Internal and external quality attributes of fruits are improved by modulation of antioxidant system and by strengthening biophysical morphology of fruits by electrostatic interaction between PAs and phospholipids in the cell wall. Polyamines (PAs) are the aliphatic, cationic organic compounds participating in the growth and development of living organisms. Naturally found PAs include putrescine (PUT), spermine (SPE) and spermidine (SPD). PAs exist both in free and conjugated forms in plants . The amiThe appearance of senescence in the fruits after the harvest devalues market potential. Ethylene production remains at peak after the harvest which causes shrivelling in the outer peel of fruit and diminishes its flavour and other quality attributes and ultimately the shelf life. PAs restricts the transcriptional synthesis of ethylene and 1-aminocyclopropane-1-carboxylic acid (ACC)-synthase and thereby blocks the activity of ACC oxidase by removal of free superoxide radicals which are essentially required for the conversion of ACC to ethylene . It is al-arginine and l-ornithine act as primary precursors for biosynthesis of PUT and indirectly for SPE and SPD as well. Decarboxylation of l-ornithine by ornithine decarboxylase (ODC) synthesises PUT, whereas the decarboxylation of l-arginine by arginine decarboxylase synthesises an intermediate PA called agmatine which in turn is acted upon by agmatimeiminohydrolase (AIH) to form N-carbamoyl putrescine. N-carbamoyl putrescine is acted upon by N-carbamoyl putrescine aminohydrolase to form PUT. The conversion of PUT by spermidine synthase (SpdS) directly synthesises SPD and consequentially the SPD is acted upon by spermine synthase (SpeS) to synthesise SPE. Besides this, S-adenosyl methionine (SAM) whose precursor is methionine acts as a balancing intermediate to facilitate the synthesis of ethylene and at the same time facilitates the biosynthesis of natural PAs, SPE and SPD. In general, the activity of S-adenosyl methionine decarboxylase is one of the steps which facilitates the synthesis of SPE and SPD. The particular characteristics of S-adenosyl methionine decarboxylase encoding gene has made it to be widely applied in the transgenic crops for facilitating the in situ biosynthesis of PAs which ultimately controls the ethylene biosynthesis in coherence with synthesis of PAs particularly SPE and SPD to improve the quality attributes of fruits.PAs make links with pectin and cell wall components  with aniThe anti-ethylene nature of the PAs led them to act as shelf life enhancing amines by affecting the diverse physiological processes under the storage conditions and enhancing the shelf life of fruits . PAs appWeight loss after harvest is a common phenomenon which ultimately deteriorates fruit quality. PAs have potential to reduce weight loss during postharvest . ApplicaMaximum 17% weight loss was observed in control pomegranate fruits, whereas pre-storage treatment of PAs has led to 13–15% reduction in weight . CombinaPectic substances play an important role in providing firmness to fruits, which is one of the most important fruit quality parameters. The diverse set of enzymes plays a vital role in reducing or degrading the firmness during the ripening and thereby affecting postharvest quality of fruits. These degrading enzymes include polygalacturonase (PG), pectin methyl esterase (PME), pectin esterase (PE) and cellulase. They play an important role in softening the fruit. PG is the principal enzyme involved in the hydrolytic cleavage in pear, avocado and apples . ActivitMechanical damage is one important aspect which affects the physico-chemical quality attributes of fruits in postharvest handling and makes them prone to the attack of microbes, insects and pests and therefore ultimately spoils the produce under storage. Apricots when treated with PUT (1 mM) after 24 h by pressure infiltration led to retention in firmness and when subjected to a force of 25 N equatorially on fruit zones and were stored  for six days enhanced the resistance towards the mechanical damage and were evaluated in terms of low deformation percentage, followed by lowered bruising volume . It was Ethylene evolution is one of the important event during postharvest phase. Ethylene evolution is inversely proportional to shelf life of fruits. The metabolic processes are driven by enzymes and most of the biochemical processes involves the active participation of enzymes. The arginine decarboxylase (ADC) activity is influenced by the exogenous application of SPD and also affects the enzymes involved in the biosynthesis of ethylene, lead to delay in senescence of fruit . PAs areRespiration plays an important role in diverse physiological processes till the senescence phase and is vitally involved in diverse postharvest losses. Postharvest application of PAs has led to the reduction in respiration rate in different kind of fruits . ApplicaIranian apricots namely “Lasgerdi” and “Shahrodi” were treated with PUT 1.0, 2.0, 3.0 or 4.0 mM followed by packaging in containers with covers made of polyethylene and stored at 4°C, 95% RH for 20 days. A decrease in TSS was reported in fruits treated with PUT in comparison to control . When beFruit pericarp browning in postharvest is one of the critical problems affecting the marketability of fruits. Mostly the mechanically damaged fruits are highly prone towards browning due to the intervention of diverse enzymatic reactions and due to enhanced metabolism in fruit. The physiological effects that take place in the damaged fruits are juice leakage, browning of flesh and loss in weight . Anti-brAA oxidation takes place under the storage conditions of fruits and therefore the levels of AA decreases under storage conditions. This reduction could be due to the oxidative conversion of dehydroascorbic acid to diketogluconic acid . PAs plaPAs play an important role in maintaining the total phenolic content (TPC) in fruits under storage conditions . BreakdoAntioxidant activity in fruits is the expression of diverse class of secondary metabolites. Antioxidant property of fruits is biochemically facilitated by the presence of compounds such as flavanoids, TPC, and AA. These antioxidants are nutritional from the health point of view and ensuring their bioavailability under storage conditions is a challenge. It is sine qua non to maintain the levels of antioxidants in fruits under storage by up keeping the overall attributes required for fruit quality. The decline in the contents of antioxidants under colder temperatures leads to the suppression of active oxygen species (AOS) content . Under cFruit ripening is considered as an oxidative phenomenon and follows an increase in the levels of AOS, hydrogen peroxide and superoxide anions . The natActivity of enzymes involved in fruit ripening was greatly suppressed by exogenous application of PAs in “Kensington Pride” mangoes . TreatmeCI is the most common physiological disorder occurred in tropical and subtropical fruits postharvest storage. Postharvest CI in tropical and subtropical fruits could be mitigated by the exogenous application of PAs. Subtropical and tropical fruits are highly prone to CI when exposed to temperature range of less than 10 °C . As a reS-adenosylmethionine decarboxylase (ySAMdc) gene from yeast fused with E8 promoter, which is ripening inducible, led to rise in PA levels particularly SPE and SPD in tomato fruit [The expression of to fruit . Conversto fruit . Developto fruit .Transcriptomic analysis followed by metabolite profile study in genetically engineered tomato with ySAMdc to produce SPE and SPD showed that PAs act as anabolic growth regulators . TransgeIntrogression of genes encoding higher level PAs traits when incorporated in tomato using the transgenic technology led to suppression of ethylene release ultimately reported to combat the negative impacts of ethylene. The investigation of the effect of transgenes encoding PA production metabolic profiling which proved that changes related to ripening in fruit were both ethylene dependent and independent. The metabolome of fruit was found to be controlled by regulators such as ethylene and PAs . ySpdSynPAs, being biodegradable and environment friendly organic compounds, will promote sustainability by mitigating the postharvest losses of fruits. Stage of application and optimisation of concentrations of these compounds are of utmost importance and of great consideration when exogenously applied. Their application at pre- and post-harvest phases will make a difference by mitigating the biotic and abiotic stress in horticultural crops as well. However, during the beginning of postharvest phase, sudden decline in PAs shortens shelf life of fruit due to diverse biotic and abiotic stress under storage environment. Besides this, PAs could be produced in situ by the application of emerging technologies such as genetic engineering by incorporating the genes encoding PAs. These genes must be incorporated with suitable promoters to facilitate in situ biosynthesis of PAs at higher levels. Such a biotechnological interventions will pave the path for developing an inherent mechanism for in situ endogenous production of PAs in fruits and vegetables and will improve the fruit quality and shelf life under storage. Besides this, for exogenous applications, nanotechnology based carriers could be developed for the targeted assimilation of the PAs when used for the shelf life enhancement in perishable horticultural crops.


Trauma of anterior teeth is quite a common occurrence in both children and adults. Various degrees of trauma leading to fracture may affect teeth in different ways depending on the age of the patient and extent of fracture and other factors that will be discussed. Guidelines have been given as to how each of these situations should be treated. In the past, often more aggressive restorations were performed to restore fractured teeth. However improved and more efficient adhesion may affect the type of treatment we decide to carry out, leading to more conservative therapies through an increased preservation of tooth structures. Traumatic injuries to teeth and their supporting tissues usually occur in young people aged 6–13 years, and damage may vary from enamel fracture to avulsion, with or without pulpal involvement or bone fracture . Most ofAnterior teeth fractures as a result of traumatic injury are frequently seen in dental practice. A high prevalence is noted in children between 7 and 12 years of age , 15. OftThe position and the circumferential extent of the fracture are of considerable importance in treatment planning. However, the severity of the fracture in a subgingival direction is probably the most important factor influencing the treatment plan. With this respect, teeth with subgingival fractures may be classified into four categories  Figure .The first step in the process of determining if the teeth should be saved or extracted is to locate the most apical extent of the fracture. Traumatically fractured maxillary anterior teeth generally have an oblique fracture angle with the most apical portion located on the palatal or on the labial depending on the impact direction. For a palatal fracture the cause is usually the external direct force resulting from the impact on the maxillary central, whereas for a labial fracture the cause is the lower incisor impacting on the palatal of the upper incisor . Often tEndotreatment + fragment reattachmentEndotreatment + periodontal surgery + fragment reattachmentEndotreatment + orthodontic extrusion + restoration of the teethFragment removal and direct or indirect restorationEndotreatment + post and core + periodontal surgery + prosthetic restorationExtraction + implantTreatments of fractures are often interdisciplinary . In factAn 11-year-old patient presented following a complicated CRF trauma to tooth 2.2 . The treA 28-year-old man presented following a complicated CRF trauma of the 11 and less severe dentin-enamel fracture of the 21 Figures  and 13. Conventional approaches to rehabilitating fractured anterior teeth include composite restorations and post-core-supported prosthetic restorations when the tooth has had pulpal exposure and extensive fracture of the crown , 3, 4. TThe authors consider the immediate reattachment of the tooth fragment not a temporary or transitory alternative but a reliable and long-term treatment alternative, considering the efficacy of current adhesive systems. This type of treatment is immediate, uses the ideal restorative material, and eliminates the need for aggressive and complex restorations , 31.