Complete Linkage Clustering Research Articles

Recovering nested structures in networks: an evaluation of hierarchical clustering techniques

Abstract In this article, we present various algorithms to partition the nodes of a network into groups that show the property of nestedness. Since perfect nestedness is a rare phenomenon, we consider the task from a data mining perspective, and we search for groups having high-level of nestedness. We utilize both agglomerative and divisive hierarchical clustering procedures and compare them on several benchmark and real-life networks. Furthermore, we propose different metrics derived from the results of our algorithms. We show that average-linkage and complete-linkage clustering can recover the largest fully nested clusters, and that the cluster size-weighted mean nestedness was a more stable metric for measuring clustering performance. Our proposed algorithms allow us to create multiple resolution views of nestedness-based clustering of networks, extending the field of graph-based data mining.

Features of the use of adaptive and maladaptive defense mechanisms by a person with various types of sensitivity to justice

Introduction. The concept of sensitivity to justice, in psychological science, is studied in conjunction with personal characteristics. The multiplicity of affective reactions associated with the experience of injustice forces us to raise the question of the features of the use of psychological defense mechanisms from the position of their adaptability for the individual. Thus, there is a need to describe the similarities and differences in the use of different groups of psychological defenses by a person from the position of their adaptive function.Purpose setting. The main objective of the study is to identify differences in the use of adaptive and maladaptive defense mechanisms by individuals with a predominance of various types of sensitivity to justice.Methodology and methods of the study. The empirical study was carried out by testing the following methods: «Questionnaire of sensitivity to justice» (authors A. A. Adamyan, S. K. Nartova-Bochaver, M. Schmitt), and «Method of measuring psychological protection» (authors R. F. Suleymanov, E. R. Pilyugina), then – by methods of mathematical statistics: cluster (the method of complete-linkage and K-means clustering) and comparative analysis (the H criterion of Kruskal-Wallis).Results. Differences in the use of groups of psychological defense mechanisms by persons with various types of sensitivity to justice were identified and described.Conclusions. Based on the results of the study, it is concluded that there are groups of people with a predominance of one particular type of sensitivity to justice. Differences were found in the manifestation of groups of psychological defense mechanisms in individuals with various types of sensitivity to justice, differing in their adaptability for the individual. The most adaptive defenses are used by persons with a predominance of sensitivity to the justice of the offender, the least adaptive – with sensitivity to the justice of the victim; individuals with sensitivity to the justice of the beneficiary and witness tend to use neurotic defenses.

Genetic heterogeneity between paired primary and metastatic solid tumors and implications for neoantigen-based personalized cancer vaccines.

3126 Background: Neoantigen-based personalized cancer vaccines carry significant promise in treating solid malignancies. For the purpose of neoantigen prediction, questions remain on the suitability of the primary versus the metastatic tumor of an individual patient (pt). Here we performed an in-depth analysis of somatic variants of 45 pts with paired primary and metastatic solid tumors. Methods: Pts were enrolled in the Total Cancer Care protocol across the Oncology Research Information Exchange Network (ORIEN). Whole-exome sequencing (WES) of primary and metastatic tumor pairs was performed for 45 pts. These included head and neck (n = 8), renal cell carcinoma (n = 7), non-small cell lung cancer (n = 6), melanoma (n = 5), bladder (n = 3), sarcoma (n = 3), ovary (n = 3), esophageal (n = 2), colorectal (n = 2) and other singletons (n = 5). The data was analyzed through the ORIEN AVATAR Molecular Analysis Pipeline, which consisted of adapter trimming, single sample variant detection, somatic mutation detection and filtering, variant annotation, and filtering of variants from a panel of normal samples. In this analysis, we focused on somatic events that result in an in-frame alteration (such as missense, in-frame insertion/deletion) and out-of-frame protein-altering mutations (such as frameshifts, de novo start and nonstop gain). To assign the clones based on the variant allele frequency, we performed complete linkage clustering. Each cluster was then assigned based on the identified oncogenic driver variant. Results: For in-frame events, we noticed that bladder cancer, melanoma, and gynecological cancers shared close to 75% of the mutations between paired primary and metastatic cases. In contrast, esophageal, brain, and endometrial cancers had a low overlap (< 25%) of variants. For out-of-frame events, we found that these events tend to have a lower proportion of shared somatic variants between primary and metastasis than in-frame variants. Through a closer evaluation of the variant allele frequency in variants shared between primary and metastatic disease, we were able to track several cancer drivers, such as oncogenic drivers of BRAF V600E, RB1 R358*, NRAS G13R, KRAS G12A, and TP53 loss-of-function that were consistently present in paired primary and metastatic tumors. Here, we were able to assign the putative clone based on the driver event in 39 out of 45 pts. Conclusions: Our analysis demonstrates genetic variations that exist when comparing paired primary and metastatic tumors that appear to vary by histology. Variants are potentially undergoing negative selection supported by the preferential loss of out-of-frame events in metastatic tumors. Understanding the clonal structure will be key to neoantigen prediction for effective neoantigen-based vaccines. Additional steps in variant prioritization are ongoing and will be reported at the meeting.

Quality Evaluation of Wind Energy Data with Complete Linkage Clustering

Quality Evaluation of Wind Energy Data with Complete Linkage Clustering

Parameterization in the Analysis of Changes in the Rural Landscape on the Example of Agritourism Farms in Kłodzko District (Poland)

The European Landscape Convention (2006) indicates that landscape conservation is as important as the protection of the overall environment. Although the boundaries between urban and rural areas in many countries are blurring, the rural landscape is still perceived as a valuable landscape artefact. Traditional rural landscapes have undergone significant transformations over the past few decades. The authors attempt to analyze factors causing apparent changes in the rural landscape, based on the example of agritourism farms in Kłodzko District, Lower Silesia. The changes taking place in Poland after 1989 resulted in reduced profitability of agricultural production. This was why small farms stopped using land for agricultural production. Agritourism has become one of the forms of business activity. Therefore, it became necessary to adapt farms to a new function. The 37 agritourism farms registered in rural and rural-urban municipalities of Kłodzko District have been randomly selected for the survey. The research has shown the extent of changes related to the transformation of agricultural farms into agritourism ones. Six areas (categories) where changes took place have been identified based on the analysis of collected data. The authors have included the collected data in the parameterization of surveyed agritourism farms, taking into account: the condition of the agricultural farm before introducing its new role (0) and the present condition, with an agritourism function (1). The complete linkage clustering (the maximum distance) known as cluster analysis was used to examine the variables in terms of farm change. The aim was to select outstanding units from the research sample for further research as case studies.

Las políticas de integridad corporativa como política económica en la OCDE

Durante el siglo XX, la doctrina económica tradicional se ha centrado en estudiar, desde distintas perspectivas, la relación entre la corrupción y los delitos económicos afines y el crecimiento y el desarrollo económico. Sin embargo, las nuevas políticas económicas y recomendaciones de la Organización para la Cooperación y el Desarrollo Económicos (OCDE) apuestan claramente por un mayor protagonismo de los factores institucionales en la prevención del daño social inherente a los delitos de corrupción. En la metodología de este trabajo se aplica, por un lado, el modelo econométrico de regresión probit y, por otro, el método estadístico de análisis de conglomerados por vinculación completa, para ilustrar la importancia creciente del cumplimiento corporativo en la OCDE, especialmente a partir de la regulación legal de la responsabilidad de las personas jurídicas y de la designación de un oficial de cumplimiento. Los resultados de investigación sugieren que ha existido una expansión geográfica de esta política de integridad desde los países de tradición anglosajona hacia el resto de los países miembro de la OCDE; asimismo, que los aspectos institucionales e historicistas están recuperando importancia en el funcionamiento de la economía mundial como palanca de cambio para la integridad en las corporaciones.

Comparative Analysis of Hierarchical Clustering with Improve Feature for Herbs Leaves

Plants have different leaf morphological characteristics starting from the leaf surface, leaf bone, leaf tips, leaf edges, leaf base, and even leaf color. The study of plants has been progressing rapidly. One of them is the branch of science in plant morphology. Morphological characteristics of leaves are one of the properties possessed by leaves and can be seen clearly. This morphological study learns about the structure of the plant body, especially about the edge leaf shape. This study will be done based on leaf shape. Leaf shape can be used as a reference in the classification process. The classification process requires a good data extraction feature, so it is necessary to improve the feature process at the pre-processing level. Combining the median filter and image erosion is used to improve the feature process. As for feature extraction, the seven moment invariant method is used. The classification method used for grouping is the Hierarchical Clustering. This method consists of four kinds. There are complete link clustering, single link clustering, average link clustering, and centroid linked clustering. Based on the results of experiments conducted, the use of Average Linkage Clustering method obtained clustering accuracy of 87%. It proves that the average method successfully optimizes the result by calculating any distance between points of the cluster. While the smallest accuracy results using complete linkage clustering of 81%.

Complete-Linkage Clustering Analysis of Surrogate Measures for Road Safety Assessment in Roundabouts

This paper presents the findings of a comparative road safety assessment between an existing two-lane roundabout and proposed basic turboroundabout, both designed for the same intersection, to determine which one is safer, based on traffic conflicts and surrogate safety measures. We performed microsimulation models in VISSIM to replicate the fieldobserved traffic operation, and the SSAM to determinate six surrogate measures. We validated the consistency of values obtained by several statistical analyzes. The number of conflicts was 72% lower at the turboroundabout. Through a complete-linkage clustering analysis and Euclidean distances of the surrogate measures, we found that traffic conflicts at the turbo-roundabout tend to cluster in a group, whereas conflicts at the roundabout are scattered, suggesting better organization of traffic flows at the turbo-roundabout. Three-dimensional graphical analysis of clusters and its centroids allowed verifying that surrogate measures point out a safer operation at the turbo-roundabout, even though it presented higher operating speeds. Reducing the dimensionality by principal components analysis, the cumulative variance for the first two components (87.72%) allowed observing results on a two-dimensional graph and their clusters. To endorse conflicts classification, resulting of clusters, we used discriminant analysis. Results validate the methodology and the safety benefits of the turbo-roundabout.

WILD SUGARCANE - SACCHARUM SP. GERMPLASM COLLECTION IN THE STATES OF PUNJAB AND HARYANA, INDIA

The Indian sub-continent harbours a great wealth of diversity of Saccharum and its related genera. Several targeted expeditions were conducted to collect the range of diversity present in Saccharum complex from diverse parts of the country. But the north western states of Punjab and Haryana were hitherto unexplored. A targeted exploration was conducted during 2016 to collect the entire range of variability present in Saccharum complex. Collections were made from a wide range of habitats and altitudes. The Saccharum spontaneum was present mostly along the river banks and river beds and showed considerable variability for morphological characteristics. S. spontaneum was distributed throughout both the states and collections could be made from all the districts and union territory of Chandigarh. A total of 104 accessions comprising of 100 Saccharum spontaneum and four Erinathus sp. have been collected. They were occurring mostly as small population except in the canal bunds where larger population was noticed. Plant height ranged from 0.46 m to 4.5 m. Variation for leaf and stem characters were observed from the collections. Statistical analysis of altitude of the collection sites with plant characters showed no significant association. Correlation analysis among plant characters showed the highest correlation coefficient between plant height and internode thickness. Clustering of Haryana, Chandigarh and Punjab Saccharum spontaneum collections through complete linkage clustering resulted in five clear clusters among the collections. Geographic distance and environmental factors including local climates interplay in the formation of the genetic structure and geographic patterns of the native S. spontaneum populations. Haryana and Punjab state were not much explored during earlier period and hence the collection would add more diversity to the germplasm maintained. In addition to the 100 S. spontaneum, four Erianthus sp. were collected during the exploration which will enrich the gene pool.

Universal whole-sequence-based plasmid typing and its utility to prediction of host range and epidemiological surveillance.

Bacterial plasmids play a large role in allowing bacteria to adapt to changing environments and can pose a significant risk to human health if they confer virulence and antimicrobial resistance (AMR). Plasmids differ significantly in the taxonomic breadth of host bacteria in which they can successfully replicate, this is commonly referred to as ‘host range’ and is usually described in qualitative terms of ‘narrow’ or ‘broad’. Understanding the host range potential of plasmids is of great interest due to their ability to disseminate traits such as AMR through bacterial populations and into human pathogens. We developed the MOB-suite to facilitate characterization of plasmids and introduced a whole-sequence-based classification system based on clustering complete plasmid sequences using Mash distances (https://github.com/phac-nml/mob-suite). We updated the MOB-suite database from 12 091 to 23 671 complete sequences, representing 17 779 unique plasmids. With advances in new algorithms for rapidly calculating average nucleotide identity (ANI), we compared clustering characteristics using two different distance measures – Mash and ANI – and three clustering algorithms on the unique set of plasmids. The plasmid nomenclature is designed to group highly similar plasmids together that are unlikely to have multiple representatives within a single cell. Based on our results, we determined that clusters generated using Mash and complete-linkage clustering at a Mash distance of 0.06 resulted in highly homogeneous clusters while maintaining cluster size. The taxonomic distribution of plasmid biomarker sequences for replication and relaxase typing, in combination with MOB-suite whole-sequence-based clusters have been examined in detail for all high-quality publicly available plasmid sequences. We have incorporated prediction of plasmid replication host range into the MOB-suite based on observed distributions of these sequence features in combination with known plasmid hosts from the literature. Host range is reported as the highest taxonomic rank that covers all of the plasmids which share replicon or relaxase biomarkers or belong to the same MOB-suite cluster code. Reporting host range based on these criteria allows for comparisons of host range between studies and provides information for plasmid surveillance.

Assessment of genetic diversity of cultivated and wild Iranian grape germplasm using retrotransposon-microsatellite amplified polymorphism (REMAP) markers and pomological traits.

Understanding the genetic diversity and relationships between genotypes is an effective step in designing effective breeding programs. Insertional polymorphisms of retrotransposons were studied in 75 cultivated and wild grape genotypes using retrotransposon-microsatellite amplified polymorphism (REMAP) technique. In the morphological part of work, seven pomological traits with a high breeding interest were also analyzed in the cultivated genotypes. A total of 328 markers were produced by 42 primer pairs, out of which 313 markers (95.43%) were polymorphic. Number of markers ranged from 4 in loci Tvv1Fa-873, Vine1-811, Gret1Ra-855 and Tvv1Fa-890 to 12 in locus Vine1Ra-841 with an average value of 7.45. Similarity values based on Dice's coefficient among all 75 grapevine genotypes varied from 0.41 to 0.77. Classification of genotypes using unweighted pair-group method using complete-linkage clustering led to six distinct groups. Some wild and cultivated varieties placed in the same groups. It seems there are close relationship between wild and cultivated genotypes and maybe wild genotypes are ancestor of native grapevines. Grouping of grapevine genotypes based on molecular marker data was not in agreement with clustering by agro-morphological data indicating that the most of multiplied sequences are confined to the non-coding regions of transposon elements. Results showed a substantial level of genetic diversity at molecular and pomological level and the potential of this diversity for future grape breeding programs.

Robust Mean-Variance Portfolio Selection with Ward and Complete Linkage Clustering Algorithm

Robust Mean-Variance Portfolio Selection with Ward and Complete Linkage Clustering Algorithm

A generic hierarchical clustering approach for detecting bottlenecks in manufacturing

The advancements in machine learning (ML) techniques open new opportunities for analysing production system dynamics and augmenting the domain expert's decision-making. A common problem for domain experts on the shop floor is detecting throughput bottlenecks, as they constrain the system throughput. Detecting throughput bottlenecks is necessary to prioritise maintenance and improvement actions and obtain greater system throughput. The existing literature provides many ways to detect bottlenecks from machine data, using statistical-based approaches. These statistical-based approaches can be best applied in environments where the statistical descriptors of machine data (such as distribution of machine data, correlations and stationarity) are known beforehand. Computing statistical descriptors involves statistical assumptions. When the machine data doesn't comply with these assumptions, there is a risk of the results being disconnected from actual production system dynamics. An alternative approach to detecting throughput bottlenecks is to use ML- based techniques. These techniques, particularly unsupervised ML techniques, require no prior statistical information on machine data. This paper proposes a generic, unsupervised ML-based hierarchical clustering approach to detect throughput bottlenecks. The proposed approach is the outcome of systematic and careful selection of ML techniques. It begins by generating a time series of the chosen bottleneck detection metric and then clustering the time series using a dynamic time-wrapping measure and a complete-linkage agglomerative hierarchical clustering technique. The results are clusters of machines with similar production dynamic profiles, revealed from the historical data and enabling the detection of bottlenecks. The proposed approach is demonstrated in two real-world production systems. The approach integrates the concept of humans in-loop by using the domain expert's knowledge.

Concordance of SNP- and allele-based typing workflows in the context of a large-scale international Salmonella Enteritidis outbreak investigation.

A large European multi-country Salmonella enterica serovar Enteritidis outbreak associated with Polish eggs was characterized by whole-genome sequencing (WGS)-based analysis, with various European institutes using different analysis workflows to identify isolates potentially related to the outbreak. The objective of our study was to compare the output of six of these different typing workflows (distance matrices of either SNP-based or allele-based workflows) in terms of cluster detection and concordance. To this end, we analysed a set of 180 isolates coming from confirmed and probable outbreak cases, which were representative of the genetic variation within the outbreak, supplemented with 22 unrelated contemporaneous S . enterica serovar Enteritidis isolates. Since the definition of a cluster cut-off based on genetic distance requires prior knowledge on the evolutionary processes that govern the bacterial populations in question, we used a variety of hierarchical clustering methods (single, average and complete) and selected the optimal number of clusters based on the consensus of the silhouette, Dunn2, and McClain–Rao internal validation indices. External validation was done by calculating the concordance with the WGS-based case definition (SNP-address) for this outbreak using the Fowlkes–Mallows index. Our analysis indicates that with complete-linkage hierarchical clustering combined with the optimal number of clusters, as defined by three internal validity indices, the six different allele- and SNP-based typing workflows generate clusters with similar compositions. Furthermore, we show that even in the absence of coordinated typing procedures, but by using an unsupervised machine learning methodology for cluster delineation, the various workflows that are currently in use by six European public-health authorities can identify concordant clusters of genetically related S . enterica serovar Enteritidis isolates; thus, providing public-health researchers with comparable tools for detection of infectious-disease outbreaks.

Tools used to assess the quality of peer review reports: a methodological systematic review

BackgroundA strong need exists for a validated tool that clearly defines peer review report quality in biomedical research, as it will allow evaluating interventions aimed at improving the peer review process in well-performed trials. We aim to identify and describe existing tools for assessing the quality of peer review reports in biomedical research.MethodsWe conducted a methodological systematic review by searching PubMed, EMBASE (via Ovid) and The Cochrane Methodology Register (via The Cochrane Library) as well as Google® for all reports in English describing a tool for assessing the quality of a peer review report in biomedical research. Data extraction was performed in duplicate using a standardized data extraction form. We extracted information on the structure, development and validation of each tool. We also identified quality components across tools using a systematic multi-step approach and we investigated quality domain similarities among tools by performing hierarchical, complete-linkage clustering analysis.ResultsWe identified a total number of 24 tools: 23 scales and 1 checklist. Six tools consisted of a single item and 18 had several items ranging from 4 to 26. None of the tools reported a definition of ‘quality’. Only 1 tool described the scale development and 10 provided measures of validity and reliability. Five tools were used as an outcome in a randomized controlled trial (RCT). Moreover, we classified the quality components of the 18 tools with more than one item into 9 main quality domains and 11 subdomains. The tools contained from two to seven quality domains. Some domains and subdomains were considered in most tools such as the detailed/thorough (11/18) nature of reviewer’s comments. Others were rarely considered, such as whether or not the reviewer made comments on the statistical methods (1/18).ConclusionSeveral tools are available to assess the quality of peer review reports; however, the development and validation process is questionable and the concepts evaluated by these tools vary widely. The results from this study and from further investigations will inform the development of a new tool for assessing the quality of peer review reports in biomedical research.

Diversity Assessment of Some Sesame (Sesamum indicumL.) Genotypes Cultivated in Northern Ghana Using Morphological and Simple Sequence Repeat (SSR) Markers

In Ghana, sesame is cultivated in some districts of northern Ghana. Genotypes cultivated are land races that are low yielding leading to decline in production. There is the need for improvement of these land races to generate high yielding cultivars. Characterization of genetic diversity of the sesame land races will be of great value in assisting in parental lines selection for sesame breeding programmes in Ghana. Twenty-five sesame land races were collected from five districts in northern Ghana noted for sesame cultivation. Seeds collected were planted in three replicates in randomized complete block design and were evaluated for a number of morphological characters. Data collected were subjected to Principal Component Analysis (PCA) and a dendrogram showing similarity between the accessions were drawn. Data on number of capsules per plant, number of seeds per capsule, and plant height at flowering were subjected to analysis of variance using GenStat Discovery Edition 4. Molecular genetic diversity was assessed by using thirty eight SSR markers widely distributed across sesame genome to characterize the materials. Twenty-one out of the 38 primers were polymorphic. Cluster analyses using the Euclidean similarity test and a complete link clustering method were used to make a dendrogram out of the morphological data. Analysis of variance showed that capsule number was significantly different; a range of 54.9 and 146.7 was produced. The number of seeds per capsule varied significantly and the variation between highest and lowest accession in seed production was 33%. Plant height was also significantly different ranging from 60.6 to 94.1 cm. Using morphological traits the accessions clustered into two major groups and two minor groups and variation among accessions were 10-61%. On the other hand, SSR marker-based dendrogram revealed five major and two minor groups. It showed that variation among the accessions was low, 10-20%. Heterozygosity was 0.52, total alleles produced were 410, and average allele per locus was 19.52. Six accessions, C3, C4, S5, W1, W3, and W5 fell in five different clusters in the SSR dendrogram and in six clusters in the morphomolecular based dendrogram. These accessions were noted for high capsule number per plant and seeds number per capsule and are recommended for consideration as potential parental lines for breeding programme for high yield.

Generating similarity cluster of Indonesian languages with semi-supervised clustering

<p>Lexicostatistic and language similarity clusters are useful for computational linguistic researches that depends on language similarity or cognate recognition. Nevertheless, there are no published lexicostatistic/language similarity cluster of Indonesian ethnic languages available. We formulate an approach of creating language similarity clusters by utilizing ASJP database to generate the language similarity matrix, then generate the hierarchical clusters with complete linkage and mean linkage clustering, and further extract two stable clusters with high language similarities. We introduced an extended k-means clustering semi-supervised learning to evaluate the stability level of the hierarchical stable clusters being grouped together despite of changing the number of cluster. The higher the number of the trial, the more likely we can distinctly find the two hierarchical stable clusters in the generated k-clusters. However, for all five experiments, the stability level of the two hierarchical stable clusters is the highest on 5 clusters. Therefore, we take the 5 clusters as the best clusters of Indonesian ethnic languages. Finally, we plot the generated 5 clusters to a geographical map.</p>

Accommodation of a dimer in an Ar-like lattice: exploring the generic structural motifs.

A global optimization strategy is applied to Lennard-Jones models describing the stable trapping sites of a dimer in the face-centered cubic Ar-like lattice. Effective volumes of the trapping sites, quantified as the number of host atoms dislodged from the lattice, are mapped onto the parameter space defined by the strength and range of the dimer interaction potentials. The two models considered differ in the host-guest interaction and give very different maps that reflect the effect of local lattice relaxation. A hierarchical complete-linkage clustering technique is applied to identify generic structural types of the dimer accommodations. The dominant types found and enlisted maintain the symmetry of the isolated dimer and possess high tetrahedral and octahedral symmetry of the host environment with respect to the dimer atoms or center and can be roughly classified as the "whole" or "per atom" dimer accommodations. The results are compared to the analysis of the analogous model for trapped atoms and realistic model for trapped alkaline-earth metal dimers. Implications for matrix isolation spectroscopy are discussed.

Inferring Patterns for Taint-Style Vulnerabilities With Security Patches

Taint-style vulnerabilities can damage the service provided by mobile seriously. The pattern-based method is a practical way to detect taint-style vulnerabilities. Most of the methods extract the vulnerability patterns from the code base, however, sometimes missing the vulnerability patterns and resulting in some vulnerabilities undiscovered. The security patches contain valuable information about the vulnerabilities. To compensate for the inherent incompleteness of pattern matching, in this paper, we propose an approach to infer patterns with the security information carried on the security patches. The taint-style vulnerability is described as a 3-tuples (S src , S san , S sink ) here, which consist of sources(S src ), sanitization (S san ), and sinks(Ssink). For each pair of vulnerable and patched programs, we extract the sanitizations from the changes between the vulnerable code and corresponding patches, infer the sinks with the impact analysis, and determine the sources through the backward traversal on the control flow graph. Finally, the complete-linkage clustering method is applied to the extracted triples to summary the patterns. We evaluate our method with open source projects. The results show our method is effective: 1) our method infers vulnerability patterns for taint-style vulnerabilities; 2) compared with the method inferring patterns from the code base, new patterns are discovered; and 3) the inferred patterns are applied to search the similar vulnerabilities successfully.

Gut Microbiome in Survivors of Childhood Acute Lymphoblastic Leukemia

PurposeAcute lymphoblastic leukemia (ALL) is the most common cancer in childhood and has a high treatment success rate. However, survivors of childhood ALL have a high prevalence of chronic medical illnesses, such as metabolic syndrome. Dysbiosis in the gut microbiome is associated with metabolic derangement and disease risk. Chemotherapy and antibiotics increase gut microbiome dysbiosis. We tested the hypothesis that ALL treatment can cause alterations in the gut microbiome that persist in survivorship.MethodStool samples were collected on fecal occult blood test cards from 38 survivors between 2-18 years of age who were >1 year off therapy for ALL. 16 stool samples from healthy siblings age 2-18 years were collected from 14 families as controls. Clinical data including anthropometrics, antibiotic use, and probiotic use were collected. DNA was extracted and sequenced using a modified Illumina 16S Metagenomics Sequencing Library Preparation protocol for analysis of hypervariable region V4. A single rarefaction was performed at 4,897 removing 2 samples with low mapped read counts. Alpha and beta (Bray) diversities were calculated; Wilcoxon rank-sum test was used to compare the alpha diversities between groups, as well as the beta diversities within and between groups. Wilcoxon signed-rank test was used to compare the alpha diversity between survivors and their matched siblings. Finally, read counts for each Operational Taxonomic Unit (OTU) was normalized and tested for differential abundance using edgeR, assuming a negative binomial model.ResultsSignificant differences in the abundance of taxa were found, with the most notable being the depletion of Faecalibacterium in survivors (FDR= 0.0004). Figure 1 shows a heatmap with the complete linkage clustering method on the Euclidean distance using the 13 OTUs with statistically significant (FDR<0.05) differences between survivors and siblings (Table 1). When compared to their respective siblings, survivors exhibited decreased alpha diversity using four metrics (Observed, Shannon, Simpson, Fisher), but these results did not meet statistical significance. Significant differences were not observed in alpha diversity within survivors between different clinical categories (antibiotic usage, probiotic usage, disease risk, age at diagnosis and time off treatment). Stool microbiome was more similar within a family than between families (P = 0.00079).ConclusionDifferences in the relative abundance of certain taxa were found between survivors and siblings. Specifically, Fecalibacterium was depleted in survivors, which has also been previously observed in older populations of childhood ALL survivors. This study shows that these microbiome changes are present in ALL survivors during childhood, and should be evaluated longitudinally for association with the chronic medical illnesses seen in ALL survivors in adulthood. Early interventions to restore the gut microbiome in ALL patients may potentially ameliorate the risk of long-term adverse health outcomes. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.