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Large-scale genotyping platforms are currently being developed for several wild species. By querying thousands of polymorphic loci, genomics can be a useful ecological tool for describing and monitoring populations. Genomics is becoming increasingly useful as a forensic tool because of its ability to identify population of origin for purposes of enforcing anti-poaching laws. Our aim was to test the new SNP chip for caribou/reindeer (Rangifer tarandus) (Illumina iSelect caribou 60 K) under recommended and non-optimal sample conditions. Impact on signal detection (call rate) and error rate were assessed using reference samples. The SNP chip was shown to be robust, highly sensitive, reliable, and accurate at more than 10-fold below the recommended DNA input. Biological source of DNA had minor impact, even with fecal pellets given sufficient amount of host DNA. Hybridization of non-Rangifer samples as well as samples bearing DNA from two Rangifer samples both showed a drop in call rate and shifted levels of heterozygosity. Based on a population-targeted subset of SNPs included in the chip design, reassignment of 981 samples to a functional group (here to a caribou ecotype) was highly accurate (99.59 %) and the relative probability of reassignment error was estimated using the logarithm of odds score. Overall, the SNP chip is suitable for analysis of caribou/reindeer genomes even with suboptimal sampling and hence useful for population management and forensics.

Abstract One of the most important steps in conservation of the subterranean life forms is to decipher their distribution and ecology, which is challenging using traditional approaches. Development of an environmental DNA (eDNA) assay provides an efficient means for discovering and monitoring subterranean life forms. In this study, the distribution of three Iranian blind cave fish species (blind Iran cave barb Garra typhlops, blind Lorestan cave barb Garra lorestanensis, and blind cave loach Eidinemacheilus smithi) was assessed using 12S rRNA eDNA metabarcoding performed using MiFish‐U PCR primers and preliminary species distribution modeling (SDM) using bioclimatic data. The majority of sampling localities with positive detection of cave barb eDNA fall within suitable habitats in the Zagros Mountains of Iran. Our results revealed that Lorestan and Iran cave barbs have differential distribution patterns, with some extent of habitat overlap in the vicinity of the originally discovered cave barb locality. According to the observed distribution patterns, the blind Lorestan cave barb and cave loach are mostly distributed in habitats close to the Sezar River (Dez River drainage, Iran), and the blind Iran cave barb is distributed towards the west and probably in a few springs in the Karkheh River drainage. Our data support the previously proposed distribution pattern for the cave barbs, in which the species show partial niche separation and reproductive isolation, with the Lorestan cave barb being a water flow‐dependent species and the Iran cave barb being a generalist species preferring variable flow rates. We showed eDNA metabarcoding to be a useful approach for ecological surveys of subterranean fish biodiversity with implications for conservation.

Abstract Ascidians (Phylum Chordata, Class Ascidiacea) are a large group of invertebrates which occupy a central role in the ecology of marine benthic communities. Many ascidian species have become successfully introduced around the world via anthropogenic vectors. The botryllid ascidians (Order Stolidobranchia, Family Styelidae) are a group of 53 colonial species, several of which are widespread throughout temperate or tropical and subtropical waters. However, the systematics and biology of this group of ascidians is not well-understood. To provide a systematic framework for this group, we have constructed a well-resolved phylogenomic tree using 200 novel loci and 55 specimens. A Principal Components Analysis of all species described in the literature using 31 taxonomic characteristics revealed that some species occupy a unique morphological space and can be easily identified using characteristics of adult colonies. For other species, additional information such as larval or life history characteristics may be required for taxonomic discrimination. Molecular barcodes are critical for guiding the delineation of morphologically similar species in this group.

Induced systemic resistance (ISR) is a mechanism involved in the plant defense response against pathogens. Certain members of the Bacillus genus are able to promote the ISR by maintaining a healthy photosynthetic apparatus, which prepares the plant for future stress situations. The goal of the present study was to analyze the effect of the inoculation of Bacillus on the expression of genes involved in plant responses to pathogens, as a part of the ISR, during the interaction of Capsicum chinense infected with PepGMV. The effects of the inoculation of the Bacillus strains in pepper plants infected with PepGMV were evaluated by observing the accumulation of viral DNA and the visible symptoms of pepper plants during a time-course experiment in greenhouse and in in vitro experiments. The relative expression of the defense genes CcNPR1, CcPR10, and CcCOI1 were also evaluated. The results showed that the plants inoculated with Bacillus subtilis K47, Bacillus cereus K46, and Bacillus sp. M9 had a reduction in the PepGMV viral titer, and the symptoms in these plants were less severe compared to the plants infected with PepGMV and non-inoculated with Bacillus. Additionally, an increase in the transcript levels of CcNPR1, CcPR10, and CcCOI1 was observed in plants inoculated with Bacillus strains. Our results suggest that the inoculation of Bacillus strains interferes with the viral replication, through the increase in the transcription of pathogenesis-related genes, which is reflected in a lowered plant symptomatology and an improved yield in the greenhouse, regardless of PepGMV infection status.

Abstract Molecular techniques offer sensitive, specific, noninvasive monitoring of target species from a variety of environmental samples. We recently developed a CRISPR‐Cas‐based eDNA assay for rapid single‐species detection as a route to a simple, cost‐effective biosensor device. CRISPR‐Cas‐based diagnostic assays use isothermal conditions in combination with a highly specific sequence recognition system. This CRISPR‐Cas assay was designed to target Salmo salar, and we previously demonstrated its utility in eDNA samples from sites in Ireland. The aim of this study was to validate our assay in two larger sample sets from Canada (n = 16/n = 63) in comparison with an independent S. salar qPCR assay. We demonstrate that overall, the CRISPR‐Cas assay performs similarly to qPCR for assessing the presence or absence of S. salar from eDNA and provides a viable alternative approach where qPCR assay design and application have proven to be challenging.

Network traffic monitoring uses empirical entropy to detect anomalous events such as various types of attacks. However, the exact computation of the entropy in high-speed networks is a difficult process due to the limited memory resources available in the data plane hardware. In this paper, we present a method and hardware accelerator to approximate the empirical entropy of a large data set with high throughput and sublinear memory requirements. Our method uses streaming algorithms that exploit the fine-grained parallelism of existing hardware platforms for data plane processing, such as field-programmable gate arrays (FPGAs). The method uses sketches to compute the cardinality of the stream and the frequencies of the top-K elements on line, and then it estimates the contribution to the entropy of the rest of the stream assuming a simple uniform distribution for these elements. Implemented on a Xilinx UltraScale+ ZCU102 FPGA, the accelerator implements the method using only on-chip memory, with less than 50% resource usage. Tested on real network traces of up to 120 million packets and more than 5 million flows, the accelerator estimates the empirical entropy with less than 1.5% mean relative error and $21~\mu \text{s}$ latency, and supports a minimum throughput of 204 gigabits per second.

The aphid Chaetosiphon fragaefolii Cockerell, 1901 is an agricultural pest and known vector of strawberry viruses. To better understand its biology and systematics, we performed a genomic analysis on C. fragaefolii collected from Quinalt strawberry plants from Pacific Grove, Monterey county, California, USA using Oxford Nanopore and Illumina sequencing. The resulting data were used to assemble the aphids complete mitogenome. The mitogenome of C. fragaefolii is 16,108 bp in length and contains 2 rRNA, 13 protein-coding, and 22 tRNA genes (GenBank accession number LC590896). The mitogenome is similar in content and organization to other Aphididae. Phylogenetic analysis of the C. fragaefolii mitogenome resolved it in a fully supported clade in the tribe Macrosiphini. Analysis of the cox1 barcode sequence of C. fragaefolii from California found exact and nearly identical sequences to C. fragaefolii and Chaetosiphon thomasi Hille Ris Lambers, 1953, suggesting the two species are conspecific.

Abstract Electronic Health (eHealth) is the use of information and communication technologies for health and plays a significant role in improving public health. The rapid expansion and development of eHealth initiatives allow researchers and healthcare providers to connect more effectively with patients. The aim of the CIHLMU Symposium 2020 was to discuss the current challenges facing the field, opportunities in eHealth implementation, to share the experiences from different healthcare systems, and to discuss future trends addressing the use of digital platforms in health. The symposium on eHealth explored how the health and technology sector must increase efforts to reduce the obstacles facing public and private investment, the efficacy in preventing diseases and improving patient quality of life, and the ethical and legal frameworks that influence the proper development of the different platforms and initiatives related to the field. This symposium furthered the sharing of knowledge, networking, and patient/user and practitioner experiences in low- and middle-income countries (LMIC) in both public and private sectors.

Abstract Conservation of freshwater biodiversity requires being able to track the presence and abundance of entire fish communities. However, studying fish community composition within rivers remains a technical challenge because of high spatial and temporal physico‐chemical variability, anthropic activities and connections with other river catchments, which may all contribute to important variations in local ecology and communities. Here, we used environmental DNA metabarcoding to document spatial variation in fish communities at a small geographic scale in a large river system. The study was conducted in the Contrecoeur sector (5.5 km long and approximately 1–1.5 km wide) of the St. Lawrence River (Québec, Canada), where two water masses with different physico‐chemical properties, known as "brown waters" and "green waters," flow in parallel with limited admixing. Water samples were collected during two consecutive days at 53 stations located in both water masses. Using universal PCR MiFish 12S primers, Illumina MiSeq sequencing, and the Barque (www.github.com/enormandeau/barque) eDNA analysis software developed by our group, a total of 67 fish species were detected. PERMANOVA and redundancy analyses (RDA) performed on relative read abundance revealed that each water mass comprised distinct communities that depended on turbidity, depth, and to a lesser extent on the upstream versus downstream position along the study area. eDNA metabarcoding results were compared with those of traditional surveys conducted previously in the sector and up to 40 km upstream of it. As previously reported, higher species diversity was detected by eDNA and with substantially lower sampling effort. Our results represent one of the few studies documenting the potential of eDNA metabarcoding to investigate small‐scale variation in 2D spatial patterns of distribution of whole fish communities associated with habitat characteristics within a lotic system.

Abstract Background Increased coagulation biomarkers are associated with poor outcomes among people living with HIV (PLHIV). There are few data available from African cohorts demonstrating the effect of antiretroviral therapy (ART) on coagulation biomarkers. Methods From March 2014 to October 2014, ART-naïve PLHIV initiating non-nucleoside reverse transcriptase inhibitor-based ART were recruited from seven clinics in western Kenya and followed for up to 12 months. Demographics, clinical history and blood specimens were collected. Logistic regression models adjusted for intrasite clustering examined associations between HIV viral load and D-Dimer at baseline. Mixed linear effects models were used to estimate mean change from baseline to 6 months overall, and by baseline viral load, sex and TB status at enrollment. Mean change in D-dimer at 6 months is reported on the log10 scale and as percentage change from baseline. Results Among 611 PLHIV enrolled, 66% were female, median age was 34 years (interquartile range (IQR) 29–43 years), 31 (5%) participants had tuberculosis and median viral load was 113,500 copies/mL (IQR: 23,600-399,000). At baseline, 311 (50.9%) PLHIV had elevated D-dimer (> 500 ng/mL) and median D-dimer was 516.4 ng/mL (IQR: 302.7–926.6) (log baseline D-dimer: 2.7, IQR: 2.5–3.0). Higher baseline D-dimer was significantly associated with higher viral load (p 6.0 copies/mL (− 91.1, 95%CI −136.7, − 54.2; p

Abstract Practical applications of environmental DNA (eDNA) are in exponential expansion, especially for the assessment and monitoring of freshwater metazoans. Because eDNA sampling and analysis is noninvasive, it improves the detection of threatened, invasive, and exploited species for which monitoring may be challenging. Species detection efforts using a combination of eDNA and qPCR have been highly successful and, as a result, their use in species monitoring is expanding rapidly. We developed qPCR primers and probes in order to monitor many invasive, threatened, or exploited aquatic species as part of various monitoring eDNA projects in the province of Québec, Canada. Here, we present a total of 60 species‐specific qPCR assays (including PCR protocols, primers, and TaqMan probes sequences) developed for the detection of 45 fishes, six amphibians, five reptiles, two mollusks, and two crustaceans. These comprised nine and 27 species, respectively, listed as invasive and threatened in Eastern Canada. These resources should be of broad usefulness not only for monitoring studies based in Québec but throughout the geographic range of the targeted species in North America.

Extracting discriminative k-mers is an important and challenging problem in DNA sequence analysis with applications in metagenomics and motif discovery. Despite the availability of multiple computational tools designed for this purpose, most discriminative k-mer discovery methods suffer from long execution times and high memory usage when processing large datasets. This paper presents a novel approach for discriminative k-mer discovery in DNA sequences, which leverages streaming and sketch algorithms to reduce space complexity and expose data parallelism, enabling the use of parallel platforms for accelerating the execution of computationally-intensive operations. To assess the performance of our method, we designed and implemented two versions of the algorithm that leverage parallelization at different levels: (i) a software version tailored for multithreading and vector instructions in commodity CPUs, and (ii) a custom architecture implemented on a Field-Programmable Gate Array (FPGA) accelerator that exploits fine-grain parallelism and deep pipelining on reconfigurable logic. Experimental results show that, when mining discriminative k-mers from a set of well-known ChIP-seq sequences, our parallel software implementation executes at least 15% faster than exact-counting tools, and requires at least five times less memory when processing large datasets. More importantly, we designed a custom FPGA-based accelerator for our algorithm on a Xilinx KCU1500 board, which achieves speedups above 78x with the largest datasets, compared to our parallel software implementation. The accelerator uses less than 3% of the logic resources available on the on-board XCKU115 Kintex-7 Ultrascale FPGA, and between 12% and 70% of the memory resources, depending on the size of the dataset.

Objective The present study aimed to identify Mollicutes infection in the reproductive system. We also examined the microbiological, biochemical, and antimicrobial profiles of Mollicutes infection, which are potentially associated with clinical reproductive abnormalities causing infertility in couples. Methods Thirty-seven couples who were attending an infertility clinic were enrolled. Detection of genital mycoplasmas was performed in cervicovaginal samples or male urethral swabs. Microbiological culture and biochemical and antimicrobial profiles were characterized using a Mycoplasma kit. The results were associated with reproductive abnormalities, as assessed by medical specialists from the infertility clinic. Results Up to 28.3% of all biological samples (n = 74) showed positive cultures. Bacterial isolates were Ureaplasma urealyticum (71.4%), Mycoplasma hominis (9.5%), or coinfections (19%). Most Mollicutes showed significant resistance to fluoroquinolones, macrolides, and tetracycline; and showed susceptibility to doxycycline, josamycin, and pristinamycin. The presence of resistant strains to any antibiotic was significantly associated with genital abnormalities (χ 2 test, relative risk = 11.38 [95% confidence interval: 5.8–22.9]), particularly in women. The highest statistical association was found for macrolide-resistant strains. Conclusion The microbiological antibiotic resistance profile is epidemiologically associated with abnormalities of the reproductive system in couples attending an infertility clinic.

Abstract Because significant global changes are currently underway in the Arctic, creating a large‐scale standardized database for Arctic marine biodiversity is particularly pressing. This study evaluates the potential of aquatic environmental DNA (eDNA) metabarcoding to detect Arctic coastal biodiversity changes and characterizes the local spatio‐temporal distribution of eDNA in two locations. We extracted and amplified eDNA using two COI primer pairs from ~80 water samples that were collected across two Canadian Arctic ports, Churchill and Iqaluit, based on optimized sampling and preservation methods for remote regions surveys. Results demonstrate that aquatic eDNA surveys have the potential to document large‐scale Arctic biodiversity change by providing a rapid overview of coastal metazoan biodiversity, detecting nonindigenous species, and allowing sampling in both open water and under the ice cover by local northern‐based communities. We show that DNA sequences of ~50% of known Canadian Arctic species and potential invaders are currently present in public databases. A similar proportion of operational taxonomic units was identified at the species level with eDNA metabarcoding, for a total of 181 species identified at both sites. Despite the cold and well‐mixed coastal environment, species composition was vertically heterogeneous, in part due to river inflow in the estuarine ecosystem, and differed between the water column and tide pools. Thus, COI‐based eDNA metabarcoding may quickly improve large‐scale Arctic biomonitoring using eDNA, but we caution that aquatic eDNA sampling needs to be standardized over space and time to accurately evaluate community structure changes.

Many proteins work together with others in groups called complexes in order to achieve a specific function. Discovering protein complexes is important for understanding biological processes and predict protein functions in living organisms. Large-scale and throughput techniques have made possible to compile protein-protein interaction networks (PPI networks), which have been used in several computational approaches for detecting protein complexes. Those predictions might guide future biologic experimental research. Some approaches are topology-based, where highly connected proteins are predicted to be complexes; some propose different clustering algorithms using partitioning, overlaps among clusters for networks modeled with unweighted or weighted graphs; and others use density of clusters and information based on protein functionality. However, some schemes still require much processing time or the quality of their results can be improved. Furthermore, most of the results obtained with computational tools are not accompanied by an analysis of false positives. We propose an effective and efficient mining algorithm for discovering highly connected subgraphs, which is our base for defining protein complexes. Our representation is based on transforming the PPI network into a directed acyclic graph that reduces the number of represented edges and the search space for discovering subgraphs. Our approach considers weighted and unweighted PPI networks. We compare our best alternative using PPI networks from Saccharomyces cerevisiae (yeast) and Homo sapiens (human) with state-of-the-art approaches in terms of clustering, biological metrics and execution times, as well as three gold standards for yeast and two for human. Furthermore, we analyze false positive predicted complexes searching the PDBe (Protein Data Bank in Europe) database in order to identify matching protein complexes that have been purified and structurally characterized. Our analysis shows that more than 50 yeast protein complexes and more than 300 human protein complexes found to be false positives according to our prediction method, i.e., not described in the gold standard complex databases, in fact contain protein complexes that have been characterized structurally and documented in PDBe. We also found that some of these protein complexes have recently been classified as part of a Periodic Table of Protein Complexes. The latest version of our software is publicly available at http://doi.org/10.6084/m9.figshare.5297314.v1.

La inyección intracitoplasmática del espermatozoide (ICSI) ha permitido resolver problemas masculinos severos con excelentes resultados. Sin embargo, la difusión de su técnica llevó a la aplicación en casos donde no existe una indicación clara, desplazando muchas veces a la fertilización in vitro (FIV) sin suficientes argumentos. Esta revisión pretende, partiendo de conceptos fisiológicos de fecundación, llamar la atención sobre los eventos involucrados en el ICSI que transgreden dicha fisiología y constituyen grandes enigmas en cuanto a sus implicaciones en el desarrollo futuro. Las diversas observaciones descritas por los grupos de investigación básica dedicados a estos análisis, si bien no establecen un efecto indeseable inherente a la técnica, dejan abierta la investigación y permiten concluir que el ICSI es una técnica con claras indicaciones que no debe utilizarse indiscriminadamente.The intracytoplasmic sperm injection (ICSI) from its introduction in humans has let to treat severe male infertility with great results. However, the diffusion of this technology has led to its application in several cases without a clear indication, displacing in many cases the in vitro fertilization (FIV), without enough reasons. This review looks for calling the attention in the physiology of fertilization, recalls the events involved in ICSI which transgress the principles of this physiology and are great enigmas about future development implications. The different findings described by the basic research groups in this area, if they do not give a relation between the ICSI technology and any undesirable effect, they leave the investigation open and let us conclude that ICSI is an assisted reproductive technology with clear indications and should not be used so widely.

This article describes a collaborative, distance-delivered, teacher preparation program for rural, culturally and linguistically diverse (CLD) teacher candidates. Multiple institutions partnered with one university in order to diversify the teaching force in the region and meet the needs of CLD students living there. In describing the program’s design and implementation phases, a focus on cultural responsiveness to the candidates’ needs, their rural settings, and high populations of Latino/a students in the rural areas in which they were trained is presented. Assessment of each implementation phase guided program practice for the participants’ training as effective teachers. Relevant discussion indicates that even with responses to the pre-service teachers’ academic, social, and financial needs, issues of communication and barriers imposed by distances emerged. Additionally, while collaborative bonds among the partner institutions facilitated the candidates’ training as effective teachers, the building of multi-institutional partnerships concurrently with the implementation phases caused participants and implementers stress.

Abstract Karst represents approximately 15% of the planet’s surface, hundreds of millions of people live on and rely on these aquifers for water supply and agricultural irrigation. In karstic landscapes, groundwater is exposed in sinkholes, inundated caves, and artesian wells, which are two-way communication spots. When the phreatic level is exposed, the groundwater can change substantially as a result of anthropogenic impacts, modifying the water quality and the environmental integrity by incoming excess nutrients, contaminants, pathogens, and other hazardous substances such as metals and microplastics. In this paper, we develop and test a multimetric index to evaluate the condition status of dolines located within urban areas, including seven indicators: trophic index, fecal bacteria, fecal viruses, microplastics, heavy metals, zooplankton biodiversity, and fish biodiversity. Lastly, we made a proof of concept for the index in the dolines on the island of Cozumel (Mexico), resulting in evaluations from fair to good. The index is powerful due to its sensitivity to pathogens and exotic invasive species. This additive weighted index allows to assess the condition status of dolines in urban areas anywhere in the world; if required, modifications are possible.

The study objective was to evaluate human faecal contamination impacts in the Yal-ku lagoon in the Mexican Caribbean and to estimate adenovirus infection and illness risks associated with recreational exposure during water activities. A total of 20 water samples (10 from each site × two sites) (50 L) were collected monthly over a period of 12 months from two selected sampling sites in the swimming area of the Yal-ku lagoon. The occurrence of faecal-associated viruses was explored, and human adenovirus (HAdV) and pepper mild mottle virus (PMMoV) concentrations were quantified. A quantitative microbial risk assessment (QMRA) model was used to estimate exposure and subsequent adenovirus infection and illness risk for 1 h of swimming or snorkelling. Somatic and F + -specific coliphages occurred in 100% of the samples. Both HAdV and PMMoV were detected at a 60% frequency thereby indicating persistent faecal inputs. PMMoV concentrations (44–370 GC/L) were relatively lower than the concentrations of HAdV (64–1,000 GC/L). Estimated mean adenovirus risks were greater for snorkelling than for swimming by roughly one to two orders of magnitude and estimated mean illness risks for snorkelling were >32/1,000. Human faecal contamination is frequent in the Yal-ku lagoon, which is associated with human gastrointestinal illness. HIGHLIGHTS Human faecal contamination detected in a Mexican Caribbean lagoon.; The rainfall seasons posed the greatest risk.; Estimated risks were greater for snorkelling than for swimming by one to two orders of magnitude.; Estimated mean illness risks for snorkelling were >32/1,000.;

Diffusion Magnetic Resonance Imaging tractography is a non-invasive technique that produces a collection of streamlines representing the main white matter bundle trajectories. Methods, such as fiber clustering algorithms, are important in computational neuroscience and have been the basis of several white matter analysis methods and studies. Nevertheless, these clustering methods face the challenge of the absence of ground truth of white matter fibers, making their evaluation difficult. As an alternative solution, we present an innovative brain fiber bundle simulator that uses spline curves for fiber representation. The methodology uses a tubular model for the bundle simulation based on a bundle centroid and five radii along the bundle. The algorithm was tested by simulating 28 Deep White Matter atlas bundles, leading to low inter-bundle distances and high intersection percentages between the original and simulated bundles. To prove the utility of the simulator, we created three whole-brain datasets containing different numbers of fiber bundles to assess the quality performance of QuickBundles and Fast Fiber Clustering algorithms using five clustering metrics. Our results indicate that QuickBundles tends to split less and Fast Fiber Clustering tends to merge less, which is consistent with their expected behavior. The performance of both algorithms decreases when the number of bundles is increased due to higher bundle crossings. Additionally, the two algorithms exhibit robust behavior with input data permutation. To our knowledge, this is the first whole-brain fiber bundle simulator capable of assessing fiber clustering algorithms with realistic data.

In recent years, there has been a growing interest in studying the Superficial White Matter (SWM). The SWM consists of short association fibers connecting near giry of the cortex, with a complex organization due to their close relationship with the cortical folding patterns. Therefore, their segmentation from dMRI tractography datasets requires dedicated methodologies to identify the main fiber bundle shape and deal with spurious fibers. This paper presents an enhanced short fiber bundle segmentation based on a SWM bundle atlas and the filtering of noisy fibers. The method was tuned and evaluated over HCP test-retest probabilistic tractography datasets (44 subjects). We propose four fiber bundle filters to remove spurious fibers. Furthermore, we include the identification of the main fiber fascicle to obtain well-defined fiber bundles. First, we identified four main bundle shapes in the SWM atlas, and performed a filter tuning in a subset of 28 subjects. The filter based on the Convex Hull provided the highest similarity between corresponding test-retest fiber bundles. Subsequently, we applied the best filter in the 16 remaining subjects for all atlas bundles, showing that filtered fiber bundles significantly improve test-retest reproducibility indices when removing between ten and twenty percent of the fibers. Additionally, we applied the bundle segmentation with and without filtering to the ABIDE-II database. The fiber bundle filtering allowed us to obtain a higher number of bundles with significant differences in fractional anisotropy, mean diffusivity, and radial diffusivity of Autism Spectrum Disorder patients relative to controls.