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The genetic cause of 46, XY Disorder of Sex Development(DSD) still cannot be determined in about half of the cases. GATA-4 haploinsufficiency is one of the rare causes of DSD in genetic males (46, XY). Twenty-two cases with 46, XY DSD due to GATA-4 haploinsufficiency (nine missense variant, two copy number variation) have been reported in the literature. In these cases, the phenotype may range from a mild undervirilization to complete female external genitalia. The haploinsufficiency may be caused by a sequence variant or copy number variation (8p23 deletion). The study aimed to present two unrelated patients with DSD due to GATA-4 variants and to review the phenotypic and genotypic characteristics of DSD cases related to GATA-4 deficiency.

In this paper, we introduce the idea of deferred statistical convergence using fractional difference operator of order [Formula: see text] for the sequence of fuzzy numbers. Also, we establish some relations between this idea and the strong deferred-summable fractional difference sequences of fuzzy numbers. As an application, we apply the idea of newly defined statistical convergence for proving fuzzy Korovkin-type approximation theorem.

Background The use of Monoclonal Antibodies (MAbs) as therapeutics has been increasing over the past 30 years due to their high specificity and strong affinity toward the target. One of the major challenges toward their use as drugs is their low thermostability, which impacts both efficacy as well as manufacturing and delivery. Methods To aid the design of thermally more stable mutants, consensus sequence-based method has been widely used. These methods typically have a success rate of about 50% with maximum melting temperature increment ranging from 10 to 32°C. To improve the prediction performance, we have developed a new and fast MAbs specific method by adding a 3D structural layer to the consensus sequence method. This is done by analyzing the close-by residue pairs which are conserved in >800 MAbs’ 3D structures. Results Combining consensus sequence and structural residue pair covariance methods, we developed an in-house application for predicting human MAb thermostability to guide protein engineers to design stable molecules. Major advantage of this structural level assessment is in significantly reducing the false positives by almost half from the consensus sequence method alone. This application has shown success in designing MAb engineering panels in multiple biologics programs. Conclusions Our data science-based method shows impacts in Mab engineering.

Although a generic uniformly distributed sequence has Poissonian pair correlations, only one explicit example has been found up to now. Additionally, it is even known that many classes of uniformly distributed sequences, like van der Corput sequences, Kronecker sequences and LS sequences, do not have Poissonian pair correlations. In this paper, we show that van der Corput sequences and the Kronecker sequence for the golden mean are as close to having Poissonian pair correlations as possible: they both have α-pair correlations for all 0 α 1 but not for α = 1 which corresponds to Poissonian pair correlations.

The 5-methyluridine (m5U)modification plays important roles in a series of biological processes. Accurate identification of m5U sites will be helpful to decode its biological functions. Although experimental techniques have been proposed to detect m5U, they are still expensive and time consuming. In the present work, a support vector machine based method, called iRNA-m5U, was developed to identify the m5U sites in the Saccharomyces cerevisiae transcriptome. The performance of iRNA-m5U was validated based on different datasets. The accuracies obtained by iRNA-m5U is promising, indicating that it holds the potential to become an useful tool for the identification of m5U sites.

Tandem repeats are repetitive structures present in some DNA sequences, consisting of many repeated copies of a single motif. They can serve as important markers for phylogenetic and population genetic studies, due to polymorphism in the number of motif copies as well as variations in the motif. The first step in using tandem repeats for phylogenetic studies is to estimate the evolutionary distance between a pair of tandem repeat sequences with homologous motifs. This problem can be broken into two sub-problems: 1. Construct the most recent common ancestor of the sequences. 2. Calculate the evolutionary distance between each sequence and the hypothesised common ancestor. We present an algorithm that estimates the solution to the second problem. This takes the form of an asymmetric alignment algorithm to estimate the evolutionary distance between two tandem repeat sequences A and D, where D is assumed to have descended from A, under a model that allows block duplication, deletion, and variant substitution. Our model assumes static motif boundaries, meaning that motif duplication and deletion events must respect the motif boundaries. The algorithm may also be applied without modification to more complex repetitive structures with two or more motifs, such as nested tandem repeats.

Bispecific antibodies (BsAbs) represent an emerging class of immunotherapy but inefficiency in the current BsAb discovery paradigm has limited their broad clinical availability. Here we report a high throughput, agnostic, single-cell-based BsAb functional screening pipeline, comprising molecular and cell engineering for efficient generation of BsAb library cells, followed by functional interrogation at the single-cell level to identify and sort positive clones and downstream sequence identification with single-cell PCR and sequencing and functionality characterization. Using a CD19xCD3 bispecific T cell engager (BiTE) as a model system, we demonstrate that our single cell platform possesses a high throughput screening efficiency of up to one and half million variant library cells per run and can isolate rare functional clones at low abundance of 0.008%. Using a complex CD19xCD3 BiTE-expressing cell library with approximately 22,300 unique variants comprising combinatorially varied scFvs, connecting linkers and VL/VH orientations, we have identified 98 unique clones including extremely rare ones (∼ 0.001% abundance). We also discovered BiTEs that exhibit novel properties contradictory to conventional wisdom, including harboring rigid scFv connecting peptide linkers yet with in vitro cytotoxicity comparable to that of clinically approved Blinatumomab. Through sequencing analyses on sorted BiTE clones, we discovered multiple design variable preferences for functionality including the CD19VL-VH– CD3VH-VL and CD19VH-VL–CD3VH-VL arrangements being the most favored orientation. Sequence analysis further interrogated the sequence composition of the CDRH3 domain in scFvs and identified amino acid residues conserved for function. We expect our single cell platform to not only significantly increase the development speed of high quality of new BsAb therapeutics for cancer and other disorders, but also enable identifying generalizable design principles for new BsAbs and other immunotherapeutics based on an in-depth understanding of the inter-relationships between sequence, structure, and function.

Objective: We aimed to investigate the feasibility of multi-acquisition with variable resonance image combination slab selectivity inversion recovery (MAVRIC SL IR) sequence on 3.0 T MRI in patients with anterior cervical discectomy and fusion (ACDF) surgery compared to bandwidth-optimized short tau inversion recovery (STIR) sequence. Methods: Paired sagittal MR images of MAVRIC SL IR and bandwidth-optimized STIR sequences were acquired and analyzed for 21 patients after ACDF surgery with PEEK cage-plate construct. Quantitative comparisons were made on the metal artifact areas of paired mid-sagittal images. In qualitative analysis, the consistency of fat suppression and visibility of anatomic structures (bonemetal interface, surrounding soft tissues, and spinal cord) were independently assessed, based on a five-point scale by two musculoskeletal radiologists, who were blind to the images and patient details. Results: The application of the MAVRIC SL IR sequence resulted in a significant reduction of 48% in the mean area of metal artifacts (t = -7.141, p < 0.001). Based on the comments received from both the reviewers, the MAVRIC SL IR sequence showed greater visibility of the bone-metal interface (p < 0.001), considerable visibility of the surrounding soft tissues (p > 0.05) but worse visibility of the spinal cord (p < 0.001), including the consistency of fat suppression (p < 0.001) relative to the bandwidth-optimized STIR sequence. Conclusion: With significantly reduced metal artifacts, the MAVRIC SL IR sequence can be implemented in patients undergoing ACDF surgery with PEEK cage-plate construct for 3.0 T MRI, despite the poor visibility of the spinal cord.

Asparagines in proteins deamidate spontaneously, which changes the chemical structure of a protein and often affects its function. Current prediction algorithms for asparagine deamidation require a structure as an input or are too slow to be applied at a proteomic scale. We present NGOME-Lite, a new version of our sequence-based predictor for spontaneous asparagine deamidation that is faster by over two orders of magnitude at a similar degree of accuracy. The algorithm takes into account intrinsic sequence propensities and slowing down of deamidation by local structure. NGOME-Lite can run in a proteomic analysis mode that provides the half-time of the intact form of each protein, predicted by taking into account sequence propensities and structural protection or sequence propensities only, and a structure protection factor. The detailed analysis mode also provides graphical output for all Asn residues in the query sequence. We applied NGOME-Lite to over 257,000 sequences in 38 proteomes and found that different taxa differ in their predicted deamidation dynamics. Spontaneous protein deamidation is faster in Eukarya than in Bacteria because of a higher degree of structural protection in the latter. Predicted protein deamidation half-lifes correlate with protein turnover in human, mouse, rat, C. elegans and budding yeast but not in two plants and two bacteria. NGOME-Lite is implemented in a docker container available at https://ngome.proteinphysiologylab.org.

Automatic landing of aircraft is a challenging guidance and control task that requires multiple feedback loops and a precise sequence of actions. Increasing operational flexibility and reducing the...

Anti-CRISPRs are molecules typically encoded in mobile elements and capable of blocking CRISPR-Cas systems. Since their discovery, numerous anti-CRISPR families have been identified. However, the spread and sequence diversity of members within a family, and the implications of the underlying patterns of dissemination and genetic variation for the evolution and function of the anti-CRISPR, have not been investigated. Here, we use AcrIF7 as a model to explore the distribution and molecular evolution of an anti-CRISPR family. Our comparative analyses uncovered five sub-clusters and prevalent sequence variants within the group. AcrIF7 homologs display high similarity, particularly within sub-clusters, and are mainly associated with Pseudomonas aeruginosa. Still, acrIF7 genes were identified in distinct genetic backgrounds, indicating horizontal dissemination, primarily by phages. Using random mutagenesis, we recreated variation observed in databases and extended the sequence diversity of the group considerably. Characterisation of the generated variants revealed that the anti-CRISPR is tolerant to the introduction of diverse mutations, but also identified residues essential for its function predicted to impact the stability of the protein. Our analysis of the genome data publicly available and variants generated in this study suggest that the dominant AcrIF7 type corresponds to both the optimal and minimal functional unit, possibly explaining the conservation versus mutational tolerance paradox. Our study provides a blueprint to investigate molecular evolution in other anti-CRISPR families.

We show that there is a measure-preserving system $(X,\mathscr{B}, \mu, T)$ together with functions $F_0, F_1, F_2 \in L^{\infty}(\mu)$ such that the correlation sequence $C_{F_0, F_1, F_2}(n) = \int_X F_0 \cdot T^n F_1 \cdot T^{2n} F_2 d\mu$ is not an approximate integral combination of $2$-step nilsequences., Comment: 14 pages

Background Structural variation (SV), which ranges from 50 bp to $$\sim$$ ∼ 3 Mb in size, is an important type of genetic variations. Deletion is a type of SV in which a part of a chromosome or a sequence of DNA is lost during DNA replication. Three types of signals, including discordant read-pairs, reads depth and split reads, are commonly used for SV detection from high-throughput sequence data. Many tools have been developed for detecting SVs by using one or multiple of these signals. Results In this paper, we develop a new method called EigenDel for detecting the germline submicroscopic genomic deletions. EigenDel first takes advantage of discordant read-pairs and clipped reads to get initial deletion candidates, and then it clusters similar candidates by using unsupervised learning methods. After that, EigenDel uses a carefully designed approach for calling true deletions from each cluster. We conduct various experiments to evaluate the performance of EigenDel on low coverage sequence data. Conclusions Our results show that EigenDel outperforms other major methods in terms of improving capability of balancing accuracy and sensitivity as well as reducing bias. EigenDel can be downloaded from https://github.com/lxwgcool/EigenDel.

We present single molecule experimental and computational modeling studies investigating the accessibility of human telomeric overhangs of physiologically relevant lengths. We studied 25 different overhangs that contain 4-28 repeats of GGGTTA (G-Tract) sequence and accommodate 1-7 tandem G-quadruplex (GQ) structures. Using FRET-PAINT method, we probed the distribution of accessible sites via a short imager strand, which is complementary to a G-Tract and transiently binds to available sites. We report accessibility patterns that periodically change with overhang length and interpret these patterns in terms of the underlying folding landscape and folding frustration. Overhangs that have [4n]G-Tracts, (12, 16, 20…), demonstrate the broadest accessibility patterns where the PNA probe accesses G-Tracts throughout the overhang. On the other hand, constructs with [4n+2]G-Tracts, (14, 18, 22…), have narrower patterns where the neighborhood of the junction between single and double stranded telomere is most accessible. We interpret these results as the folding frustration being higher in [4n]G-Tract constructs compared to [4n+2]G-Tract constructs. We also developed a computational model that tests the consistency of different folding stabilities and cooperativities between neighboring GQs with the observed accessibility patterns. Our experimental and computational studies suggest the neighborhood of the junction between single and double stranded telomere is least stable and most accessible, which is significant as this is a potential site where the connection between POT1/TPP1 (bound to single stranded telomere) and other shelterin proteins (localized on double stranded telomere) is established.Significance StatementThe ends of eukaryotic linear chromosomes are capped by telomeres which terminate with a single-stranded overhang. Telomeric overhangs fold into compact structures, called G-quadruplex, that inhibit access to these critical genomic sites. We report single molecule measurements and computational modeling studies probing the accessibility of a set of human telomeric overhangs that covers a significant portion of the physiologically relevant length scale. We observe novel accessibility patterns which have a well-defined periodicity and show that certain regions are significantly more accessible than others. These accessibility patterns also suggest the underlying folding frustration of G-quadruplexes depends on telomere length. These patterns have significant implications for regulating the access of DNA processing enzymes and DNA binding proteins that can target telomeric overhangs.

Thalassemia is a common monogenic autosomal disorder prevalent in India. HbE beta thalassemia is a compound heterozygous state of two different beta globin mutations (HBB), predominant in the Eastern India. In HbE-beta thalassemia (β+/β°) patients, one HBB mutation does not produce any functional protein (β°); another mutation produces a structural altered haemoglobin, variant E (β+). It has been observed that in HbE-beta thalassemia patients with same type of HBB mutations, there exist diverse phenotypic presentation ranging from very severe, with regular transfusion-dependence to clinically non severe requiring very less transfusion or no transfusion. To explore this phenotypic mystery, we performed trio based expanded whole exome sequencing (WES) of two extreme phenotypes of HbE beta thalassemia subjects with similar HBB genotype and their parents. For WES library preparation, Agilent Sure select V6+UTR kit was used and sequencing was done through the Illumina HiSeq 2500 platform. This study aimed to search for de novo or inherited variants associated with the clinical severity. Six significant inherited variants were found in the genes, ATOH8, TTLL4, P2RX7, PRSS54, SLC9C2 and VRK2 in severe subject, however only one significant inherited variant in MTRR gene was found in non-severe subject. Bioinformatic analysis also confirms that each variant significantly changes in respective protein structure. The identified genes were either associated with iron absorption, oxidative stress, hematopoietic stem cell differentiation, structural organization of RBC cytoskeleton or regulating anemia. No significant de novo variant were identified associated with clinical severity. The finding of this study indicates that the combined effect of mutation load in major pathways may responsible for severe phenotype.

MotivationThe assembly of contiguous sequence from metagenomic samples presents a particular challenge, due to the presence of multiple species, often closely related, at varying levels of abundance. Capturing diversity within species, for example viral haplotypes, or bacterial strain-level diversity, is even more challenging.ResultsWe present MetaCortex, a metagenome assembler that captures intra-species diversity by searching for signatures of local variation along assembled sequences in the underlying assembly graph and outputting these sequences in sequence graph format. We show that MetaCortex produces accurate assemblies with higher genome coverage and contiguity than other popular metagenomic assemblers on mock viral communities with high levels of strain level diversity, and on simulated communities containing simulated strains.Availability and ImplementationSource code is freely available to download fromhttps://github.com/SR-Martin/metacortex, is implemented in C and supported on MacOS and Linux.Contactrichard.leggett@earlham.ac.ukSupplementary informationSupplementary materials are available at the journal’s website. All assemblies, simulated reads, and simulated genomes used in this paper have been deposited online on Zenodo and can be found at DOI 10.5281/zenodo.6616437.

Clusterbean is an obligatory self-pollinating and inbreeding species and therefore, little variation in DNA polymorphism is expected among the cultivars. It has triploid endosperm and has more vegetative growth as compared to diploid counterparts. The endosperm tissue often shows a high degree of chromosomal variations, polyploidy, miotic irregularities, chromosome bridges and laggards. A brief detail of various techniques, viz. RAPD—random amplified polymorphic DNA; ISSR—inter simple sequence repeats; EST—expressed sequence tag markers; SCAR—sequence characterized amplified regions for amplification of specific band; CAPs—cleaved amplified polymorphic sequences; ITS—internal transcribed spacer; SSRs—Simple sequence repeats used for various purposes in clusterbean is summarized in this chapter.

Surgical practice administrators need to determine the sequence of surgeries and reserved operating room (OR) time for each surgery in the surgery scheduling process. Both decisions require coordination among multiple ORs and the recovery resource in the postanesthesia care unit (PACU) in a surgical suite. Although existing studies have addressed OR time reservation, surgery sequencing coordination is an open challenge in the stochastic surgical environment. In this paper, we propose an algorithmic solution to this problem based on stochastic optimization. The proposed methodology involves the development of a surrogate objective function that is highly correlated with the original one. The resulting surrogate model has network-structured subproblems after Lagrangian relaxation and decomposition, which makes it easier to solve than the impractically difficult original problem. We show that our proposed approach finds near-optimal solutions in small instances and outperforms benchmark methods by 13%–51% or equivalently an estimated saving of $760–$7,420 per day in surgical suites with 4–10 ORs. Our results illustrate a mechanism to alleviate congestion in the PACU. We also recommend that practice administrators prioritize sequencing coordination over the optimization of OR time reservation in an effort for performance improvement. Furthermore, we demonstrate how administrators should consider the impact of sequencing decisions when making strategic capacity adjustments for the PACU. Summary of Contribution: Our work provides an algorithmic solution to an open question in the field of healthcare operations management. This solution approach involves formulating a surrogate optimization model and exploiting its decomposability and network-structure. In computational experiments, we quantitatively benchmark its performance and assess its benefits. Our numerical results provide unique managerial insights for healthcare leadership.

Potyviral coat protein (CP) is involved in the replication and movement of potyviruses. However, little information is available on the roles of CP-coding sequence in potyviral infection. Here, we introduced synonymous substitutions to the codon C574G575C576 coding conserved residue arginine at position 192 (R192) of tobacco vein banding mosaic virus (TVBMV) CP. Substitution of the codon C574G575C576 to A574G575A576 or A574G575G576, but not C574G575A576, C574G575T576, or C574G575G576, reduced the replication, cell-to-cell movement, and accumulation of TVBMV in Nicotiana benthamiana plants, suggesting that C574 was critical for replication of TVBMV. Nucleotides 531 to 576 of the TVBMV CP-coding sequence were predicted to form a stem-loop structure, in which four consecutive C-G base pairs (C576-G531, C532-G575, C574-G533, and C534-G573) were located at the stem. Synonymous substitutions of R178-codon C532G533C534 to A532G533A534 and A532G533G534, but not C532G533A534, C532G533T534, or C532G533G534, reduced the replication levels, cell-to-cell, and systemic movement of TVBMV, suggesting that C532 was critical for TVBMV replication. Synonymous substitutions disrupting base pairs C576-G531 and C534-G573 did not affect viral accumulation. After three serial-passage inoculations, the accumulation of spontaneous mutant viruses was restored, and codons A532G533A534, A532G533G534, A574G575A576, or A574G575G576 of mutants were each separately changed to C532G533A534, C532G533G534, C574G575A576, or C574G575G576. Synonymous mutation of R178 and R192 also reduced viral accumulation in N. tabacum plants. Therefore, we concluded that the two consecutive C532-G575 and C574-G533 base pairs played critical roles in TVBMV replication via maintaining the stability of the stem-loop structures formed by nucleotides 531 to 576 of the CP-coding sequence.

The clinical genomics knowledgebase is dynamic with variant classifications changing as newly identified cases, additional population data, and other evidence become available. This is a challenge for the clinical laboratory because of limited resource availability for variant reassessment.Throughout the Electronic Medical Records and Genomics phase III program, clinical sites associated with the Mass General Brigham/Broad sequencing center received automated, real-time notifications when reported variants were reclassified. In this study, we summarized the nature of these reclassifications and described the proactive reassessment framework we used for the Electronic Medical Records and Genomics program data set to identify variants most likely to undergo reclassification.Reanalysis of 1855 variants led to the reclassification of 2% (n = 45) of variants, affecting 0.6% (n = 67) of participants. Of these reclassifications, 78% (n = 35) were high-impact changes affecting reportability, with 8 variants downgraded from likely pathogenic/pathogenic to variants of uncertain significance (VUS) and 27 variants upgraded from VUS to likely pathogenic/pathogenic. Most upgraded variants (67%) were initially classified as VUS-Favor Pathogenic, highlighting the benefit of VUS subcategorization. The most common reason for reclassification was new published case data and/or functional evidence.Our results highlight the importance of periodic sequence variant reevaluation and the need for automated approaches to advance routine implementation of variant reevaluations in clinical practice.

Prestressed hollowcore slabs are potentially critical segments in the construction sequence of a precast concrete structure, in which very early age strength is vital for ensuring factory productivity. Importantly, the construction industry is striving to reduce concrete's carbon footprint by using Portland cement substitutes, particularly using ground granulated blastfurnace slag (GGBS) in Ireland. This paper investigates the early age strength enhancement methods for slag-concrete mixes, in order to address the well-known retarding effects arising from slag's inclusion. The strength enhancement methods, including temperature curing and a novel accelerating admixture, are used to activate the slag in the concrete mixes, with replacement rates up to 50% GGBS. The efficacy of these methods is investigated in relation to establishing the development of compressive strength and modulus of elasticity over time (being relevant to stress transfer), particularly at very early and at later ages for strength compliance. The study demonstrates the potential for using up to 50% GGBS mixes for slab production while still maintaining the strengths sufficient to achieve existing productivity targets in precast concrete production.

Public sequence data represents a major opportunity for viral discovery, but its exploration has been inhibited by a lack of efficient methods for searching this corpus, which is currently at the petabase scale and growing exponentially. To address the ongoing pandemic caused by Severe Acute Respiratory Syndrome Coronavirus 2 and expand the known sequence diversity of viruses, we aligned pangenomes for coronaviruses (CoV) and other viral families to 5.6 petabases of public sequencing data from 3.8 million biologically diverse samples. To implement this strategy, we developed a cloud computing architecture, Serratus, tailored for ultra-high throughput sequence alignment at the petabase scale. From this search, we identified and assembled thousands of CoV and CoV-like genomes and genome fragments ranging from known strains to putatively novel genera. We generalise this strategy to other viral families, identifying several novel deltaviruses and huge bacteriophages. To catalyse a new era of viral discovery we made millions of viral alignments and family identifications freely available to the research community. Expanding the known diversity and zoonotic reservoirs of CoV and other emerging pathogens can accelerate vaccine and therapeutic developments for the current pandemic, and help us anticipate and mitigate future ones.

Development of a pattern recognition system is comprised from a number of subtasks: formalization of the subject area, formation of a training sample, training of the recognition system, reduction of the dimensionality of the feature space, the problem of pattern recognition itself (based on the degree of similarity of the detected object with the training sample), recognition quality control, adaptation, inverse problem recognition, cluster and structural analysis, cognitive analysis. The article considers the formalization one of the subtasks (formation of the training sample). The conclusion about the "almost linear dependence" of the length of the training sequences and the dimensionality of the feature space is made using the proposed probabilistic model. Evaluation of the length of the training sequences for realistic values of model parameters is performed.

The conformation of three amyloidogenic peptides; amyloid beta 1–40 (Aβ1−40), alpha synuclein (α-syn), and beta-2-microglobulin (β2m) are closely associated with the process of causing neurodegenerative diseases. Use of a peptide adsorbed gold nano-particle system allowed us to investigate the interactive segment of each peptide responsible for peptide-peptide networking, which is crucial to initiate the formation of an oligomer and leads to fibrillogenesis. The adsorption orientationof theamyloidogenic peptides onthe nano-goldcolloid spherical surface wasexplainedbysimulatinghowmuchareaofthemetalsurfacewascoveredbythepeptides,i.e.,coverageratio,Θ. The empirically extracted Θ was explained by the summation of the 1st layer and the 2nd layer with a spikingout orientation of the prolate. Of note, the involvement of the 2nd layer was peptide type dependent. The nanosize dependence of Θ was linearly correlated with available spacing between adjacent peptides, Sd, which were approximated as prolates, For Aβ1−40 and α-syn, the 2nd layer was more included as Sd increased. In contrast, β2m was found to gyrate over the gold surface as Sd increased, creating a partially positive (δ+) region and repelling the extra β2m from the surface. Thus, as Sd decreased, it prohibited the gyration of β2m resulting in less δ+ region, and more β2m monomers were adsorbed with δ+ segment as the 2nd layer than the case where β2m gyrates more under relatively larger Sd. Based on the trend found in an experimentally extracted Θ as a function of Sd, optimized charge distribution of Aβ1−40 and α-syn were concluded to be negative partial charge (δ−) region that was covered by the positive partial charge (δ+) region. However, β2m may have a relatively large and/or distributed δ+ region with a small portion of δ− at the one end of a prolate. The characterization made in this work confirmed current understandings on the formation of the protein corona over nano-particles.

Clinical Practice Points • Selpercatinib and pralsetinib both have high extracranial efficacy in RET fusion-positive non-small cell lung cancer (NSCLC). • We present a case of a patient with RET fusion-positive NSCLC who had a durable extracranial response to pralsetinib, but had leptomeningeal progression. She subsequently had both a clinical and radiographic CNS response to selpercatinib. • Future studies should compare the intracranial efficacy with these 2 RET inhibitors, with implications on choice and sequence of their use.

To disclose the antimicrobial susceptibility and wide adaptability of commonly occurring genotypes of Salmonella enterica serovar Typhimurium, the antimicrobial resistance and multilocus sequence t...

Societal Impact Statement The international conservation of biological diversity is addressed under the Convention on Biological Diversity (CBD) and goals for the next decade will be discussed at the next Conference of the Parties. One issue under negotiation in the CBD is Digital Sequence Information (DSI), which has created tension between parties calling for preserving open access to DSI who also note its importance in addressing biodiversity and the UN Sustainable Development Goals and those parties calling for fair and equitable benefit sharing from DSI. This article introduces scientists to the current debate and political process on DSI within the CBD. Summary Most biologists take open access to sequence data for granted. This open system, while a hallmark of innovation and collaboration for the scientific community, is being called into question as some parties to the Convention on Biological Diversity (CBD) assert that this access undermines their sovereign rights over their genetic resources and corresponding benefit sharing. The governance of sequence data and potentially other types of biological data, known in international policy circles as “Digital Sequence Information” (DSI), a placeholder term invented by negotiators, could be dramatically altered and ultimately change the way scientific research and publishing on sequence data is conducted. Many sequence‐using scientists are unfamiliar with the international political processes around DSI even though it could lead to irreversible decisions that might have significant impacts on research. This paper bridges that gap by providing an overview of the ongoing political process with a focus on the most recent studies on DSI commissioned by the Secretariat of the Convention on Biological Diversity (SCBD) and what these studies forecast about the political debate. With this information in hand, the scientific community can hopefully better engage with the political process and proactively promote evidence‐based decisions or even solutions that can bridge the demand for benefit sharing with the scientific need for open access to DSI.

AQX-1125 is an indane based SHIP1 agonist that has been evaluated in the clinic for the treatment of bladder pain syndrome/interstitial cystitis. To support our own studies on SHIP1 agonists as potential treatments for IBD and Crohn's disease, a new synthetic route to the SHIP1 agonist AQX-1125 has been developed. This sequence utilizes a hydroxy-acid intermediate which allows for ready differentiation of the C6 and C7 positions. The role of the C17 alkene in the biological activity of the system is also investigated, and this functional group is not required for SHIP1 agonist activity. While AQX-1125 shows SHIP1 agonist activity in enzyme assays, it does not show activity in cell based assays similar to other SHIP1 agonists, which limits the utility of this molecule.

Problem definition: We consider the intraday scheduling problem in a group of orthopaedic clinics where the planner schedules appointment times, given a sequence of appointments. We consider patient re-entry—where patients may be required to go for an x-ray examination, returning to the same doctor they have seen—and variability in patient behaviours such as walk-ins, earliness, and no-shows, which leads to inefficiency such as long patient waiting time and physician overtime. Academic/practical relevance: In our data set, 25% of the patients are required to go for x-ray examination. We also found significant variability in patient behaviours. Hence, patient re-entry and variability in behaviours are common, but we found little in the literature that could handle them. Methodology: We formulate the problem as a two-stage optimization problem, where scheduling decisions are made in the first stage. Queue dynamics in the second stage are modeled under a P-Queue paradigm, which minimizes a risk index representing the chance of violating performance targets, such as patient waiting times. The model reduces to a sequence of mixed-integer linear-optimization problems. Results: Our model achieves significant reductions, in comparative studies against a sample average approximation (SAA) model, on patient waiting times, while keeping server overtime constant. Our simulations further characterize the types of uncertainties under which SAA performs poorly. Managerial insights: We present an optimization model that is easy to implement in practice and tractable to compute. Our simulations indicate that not accounting for patient re-entry or variability in patient behaviours will lead to suboptimal policies, especially when they have specific structure that should be considered.

Polyploidy plays an important role in the evolution of eukaryotes, especially for flowering plants. Many of ecologically or agronomically important plant or crop species are polyploids, including sycamore maple (tetraploid), the world second and third largest food crops wheat (hexaploid) and potato (tetraploid) as well as economically important aquaculture animals such as Atlantic salmon and trout. The next generation sequencing data enables to allocate genotype at a sequence variant site, known as genotyping by sequencing (GBS). GBS has stimulated enormous interests in population based genomics studies in almost all diploid and many polyploid organisms. DNA sequence polymorphisms are codominant and thus fully informative about the underlying genotype at the polymorphic site, making GBS a straightforward task in diploids. However, sequence data may usually be uninformative in polyploid species, making GBS a far more challenging task in polyploids. This paper presents novel and rigorous statistical methods for predicting the number of sequence reads needed to ensure accurate GBS at a polymorphic site bared by the reads in polyploids and shows that a dozen of reads can ensure a probability of 95% to recover all constituent alleles of any tetraploid genotype but several hundreds of reads are needed to accurately uncover the genotype with probability confidence of 90%, subverting the proposition of GBS using low coverage sequence data in the literature. The theoretical prediction was tested by use of RAD-seq data from tetraploid potato cultivars. The paper provides polyploid experimentalists with theoretical guides and methods for designing and conducting their sequence-based studies.

Background: The open and accessible regions of the chromosome are more likely to be bound by transcription factors which are important for nuclear processes and biological functions. Studying the change of chromosome flexibility can help to discover and analyze disease markers and improve the efficiency of clinical diagnosis. Current methods for predicting chromosome flexibility based on Hi-C data include the Flexibility-Rigidity Index (FRI) and the Gaussian Network Model (GNM), which have been proposed to characterize chromosome flexibility. However, these methods require the chromosome structure data based on 3D biological experiments, which is time-consuming and expensive. Objective: Generally, the folding and curling of the double helix sequence of DNA have a great impact on chromosome flexibility and function. Motivated by the success of genomic sequence analysis in biomolecular function analysis, we hope to propose a method to predict chromosome flexibility only based on genomic sequence data. Methods: We propose a new method (named "DeepCFP") using deep learning models to predict chromosome flexibility based on only genomic sequence features. The model has been tested in the GM12878 cell line. Results: The maximum accuracy of our model has reached 91%. The performance of DeepCFP is close to FRI and GNM. Conclusion: The DeepCFP can achieve high performance only based on genomic sequence.

As early as the 1950s the Zagros range in western Iran has been one of the main arenas for seeking the earliest villages and domestication of plants and animals in the eastern wing of the Fertile C...

Background: Group B streptococcus (GBS) is a leading cause of serious infection in infants. Understanding its regional molecular epidemiology is helpful for regulating efficient prevention practice. Methods: A retrospective study was conducted to collected data from infants and pregnant women with culture-proven GBS disease in the largest women and children's medical center in Shanxi between January 2017 and September 2019. All GBS isolates were analyzed by multi-locus sequence typing (MLST) as well as distribution of pilus island (PI) genes. Results: A total of 54 GBS isolates were obtained from 36 (66.7%) pregnant women and 18 (33.3%) infants with invasive disease. Among invasive GBS strains, the most common sequence type was ST10 (72.2%, P

Background: Roberton’s movement components are used to assess fundamental motor skills as segmental developmental sequences. In 1991, Haywood, Williams and VanSant determined that original developmental sequences proposed for the backswing levels of the overarm throw did not encompass all ages. Their study of older throwers identified two new qualitatively different levels, with half the participants categorized at two new levels. This investigation extended the initial validation across a wider age range. Method: Two hundred and twenty-eight primary, high school, university students, and adults were instructed to make five throws for maximum force using their dominant hand. Throws were recorded with side and rear cameras synchronized for analysis. Prelongitudinal screening was used to analyze the Haywood et al. revisions of the Langendorfer developmental sequence. Results: Five of the six levels of Haywood’s sequence were suitable for assessing throwers 8 years of age through to adulthood. More study is needed of one less advanced pattern. Lower level throws corresponded to lower velocities; higher level throws were faster, suggesting the sequence was properly ordered. More males than females were classified at higher levels, demonstrating typical gender differences. Discussion: The categories hypothesized for the backswing action of the overarm throw were valid descriptors of differences observed across ages, from childhood to adulthood. Additional study of Levels 3 and 4 is warranted to clarify their order.

Nowadays, most research conducted in the field of abstractive text summarization focuses on neural-based models alone, without considering their combination with knowledge-based approaches that could further enhance their efficiency. In this direction, this work presents a novel framework that combines sequence-to-sequence neural-based text summarization along with structure and semantic-based methodologies. The proposed framework is capable of dealing with the problem of out-of-vocabulary or rare words, improving the performance of the deep learning models. The overall methodology is based on a well-defined theoretical model of knowledge-based content generalization and deep learning predictions for generating abstractive summaries. The framework is composed of three key elements: (i) a pre-processing task, (ii) a machine learning methodology, and (iii) a post-processing task. The pre-processing task is a knowledge-based approach, based on ontological knowledge resources, word sense disambiguation, and named entity recognition, along with content generalization, that transforms ordinary text into a generalized form. A deep learning model of attentive encoder-decoder architecture, which is expanded to enable a coping and coverage mechanism, as well as reinforcement learning and transformer-based architectures, is trained on a generalized version of text-summary pairs, learning to predict summaries in a generalized form. The post-processing task utilizes knowledge resources, word embeddings, word sense disambiguation, and heuristic algorithms based on text similarity methods in order to transform the generalized version of a predicted summary to a final, human-readable form. An extensive experimental procedure on three popular data sets evaluates key aspects of the proposed framework, while the obtained results exhibit promising performance, validating the robustness of the proposed approach.

Introduction: Coronaviruses comprise a group of enveloped, positive-sense single-stranded RNA viruses that infect humans as well as a wide range of animals. The study was performed on a set of 573 sequences belonging to SARS, MERS and SARS-CoV-2 (CoVID-19) viruses. The sequences were represented with alignment-free sequence descriptors and analyzed with different chemometric methods: Euclidean/Mahalanobis distances, principal component analysis and self-organizing maps (Kohonen networks). We report the cluster structures of the data. The sequences are well-clustered regarding the type of virus; however, some of them show the tendency to belong to more than one virus type. Background: This is a study of 573 genome sequences belonging to SARS, MERS and SARS-CoV-2 (CoVID-19) coronaviruses. Objective: The aim was to compare the virus sequences, which originate from different places around the world. Methods: The study used alignment free sequence descriptors for the representation of sequences and chemometric methods for analyzing clusters. Results: Majority of genome sequences are clustered with respect to the virus type, but some of them are outliers. Conclusion: We indicate 71 sequences, which tend to belong to more than one cluster.

Background: Mutation processes leave different signatures in genes. For single-base substitutions, previous studies have suggested that mutation signatures are not only reflected in mutation bases but also in neighboring bases. However, because of the lack of a method to identify features of long sequences next to mutation bases, the understanding of how flanking sequences influence mutation signatures is limited.Methods: We constructed a long short-term memory – self organizing map (LSTM-SOM) unsupervised neural network. By extracting mutated sequence features via LSTM and clustering similar features with the SOM, single-base substitutions in The Cancer Genome Atlas database were clustered according to both their mutation site and flanking sequences. The relationship between mutation sequence signatures and clinical features was then analyzed. Finally, we clustered patients into different classes according to the composition of the mutation sequence signatures by the K-means method and then studied the differences in clinical features and survival between classes.Results: Ten classes of mutant sequence signatures (mutation blots, MBs) were obtained from 2,141,527 single-base substitutions via LSTM-SOM machine learning approach. Different features in mutation bases and flanking sequences were revealed among MBs. MBs reflect both the site and pathological features of cancers. MBs were related to clinical features, including age, gender, and cancer stage. The class of an MB in a given gene was associated with survival. Finally, patients were clustered into 7 classes according to the MB composition. Significant differences in survival and clinical features were observed among different patient classes.Conclusions: We provided a method for analyzing the characteristics of mutant sequences. Result of this study showed that flanking sequences, together with mutation bases, shape the signatures of SBSs. MBs were shown related to clinical features and survival of cancer patients. Composition of MBs is a feasible predictive factor of clinical prognosis. Further study of the mechanism of MBs related to cancer characteristics is suggested.

Synonymous single nucleotide variants (sSNVs) are common in the human genome but are often overlooked. However, sSNVs can have significant biological impact and may lead to disease. Existing computational methods for evaluating the effect of sSNVs suffer from the lack of gold-standard training/evaluation data and exhibit over-reliance on sequence conservation signals. We developed synVep (synonymous Variant effect predictor), a machine learning-based method that overcomes both of these limitations. Our training data was a combination of variants reported by gnomAD (observed) and those unreported, but possible in the human genome (generated). We used positive-unlabeled learning to purify the generated variant set of any likely unobservable variants. We then trained two sequential extreme gradient boosting models to identify subsets of the remaining variants putatively enriched and depleted in effect. Our method attained 90% precision/recall on a previously unseen set of variants. Furthermore, although synVep does not explicitly use conservation, its scores correlated with evolutionary distances between orthologs in cross-species variation analysis. synVep was also able to differentiate pathogenic vs. benign variants, as well as splice-site disrupting variants (SDV) vs. non-SDVs. Thus, synVep provides an important improvement in annotation of sSNVs, allowing users to focus on variants that most likely harbor effects. Availability synVep webserver for online query: https://services.bromberglab.org/synvep; For local runs Python script (https://bitbucket.org/bromberglab/synvep_local) and prediction database (https://zenodo.org/record/4763256) are also available.

The high transmission and mortality rates associated with SARS-CoV-2 have led to tragic consequences worldwide. Large-scale whole-genome sequencing of the SARS-CoV-2 genome since its identification in late 2019 has identified many sequence changes and the emergence of novel strains, each described by co-segregation of a particular set of sequence variations. Variants designated G, alpha (B.1.1.7), beta (B.1.351), gamma (P.1), and delta (B.1.617.2) are important lineages that emerged sequentially and are considered variants of concern. A notable feature of the last four, each of which ultimately evolved from clade G, is the large number (≥ 20) of co-segregating sequence variations associated with them. Several variations are in the spike gene, and some variations are shared among or between strains. Meanwhile, observation of recurrent infections with the same or different SARS-CoV-2 lineages has raised concerns about the duration of the immune responses induced by the initial infection or the vaccine that was administered. While the alpha strain is sensitive to immune responses induced by earlier strains, the beta, gamma, and delta strains can escape antibody neutralization. Apart from random replication errors, intra-host RNA editing, chronic infections, and recombination are processes that may promote the accumulation of sequence changes in the SARS-CoV-2 genome. The known contribution of recombination to coronavirus evolution and recent data pertaining to SARS-CoV-2 suggest that recombination may be particularly important. Continued surveillance of the SARS-CoV-2 genome is imperative. Supplementary Information The online version contains supplementary material available at 10.1007/s00705-021-05295-5.