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Objective: To validate the predictive performance of the THRIVE, ASTRAL, and iScore scales for clinical functional outcomes following mechanical thrombectomy (MT) for acute ischemic stroke (AIS). Methods: A total of 111 patients meeting the inclusion criteria were included in this study, with 59 (53.2%) having a good prognosis and 52 (46.8%) having a poor prognosis. MedCalc software was applied to plot receiver operating characteristic (ROC) curves, calculate the area under the curve (AUC), and compare the predictive efficacy of the three scales two by two using Delong text. Statistical significance was defined as Pc < 0.05. Results: Logistic binary regression multifactorial analysis revealed that iScore is one of the poor predictors of prognosis in patients with MT. The AUC values for the THRIVE, ASTRAL, and iScore scales in predicting prognosis after MT were found to be 0.713, 0.738, and 0.820, respectively. Conclusion: The iScore is a reliable tool for assessing the poor prognosis of MT in patients with AIS. [ABSTRACT FROM AUTHOR]

Abstract Cancer progression and treatment can be informed by reconstructing its evolutionary history from tumor cells. Although many methods exist to estimate evolutionary trees (called phylogenies) from molecular sequences, traditional approaches assume the input data are error-free and the output tree is fully resolved. These assumptions are challenged in tumor phylogenetics because single-cell sequencing produces sparse, error-ridden data and because tumors evolve clonally. Here, we study the theoretical utility of methods based on quartets (four-leaf, unrooted phylogenetic trees) in light of these barriers. We consider a popular tumor phylogenetics model, in which mutations arise on a (highly unresolved) tree and then (unbiased) errors and missing values are introduced. Quartets are then implied by mutations present in two cells and absent from two cells. Our main result is that the most probable quartet identifies the unrooted model tree on four cells. This motivates seeking a tree such that the number of quartets shared between it and the input mutations is maximized. We prove an optimal solution to this problem is a consistent estimator of the unrooted cell lineage tree; this guarantee includes the case where the model tree is highly unresolved, with error defined as the number of false negative branches. Lastly, we outline how quartet-based methods might be employed when there are copy number aberrations and other challenges specific to tumor phylogenetics.

Abstract Background Species tree estimation is a basic step in many biological research projects, but is complicated by the fact that gene trees can differ from the species tree due to processes such as incomplete lineage sorting (ILS), gene duplication and loss (GDL), and horizontal gene transfer (HGT), which can cause different regions within the genome to have different evolutionary histories (i.e., “gene tree heterogeneity”). One approach to estimating species trees in the presence of gene tree heterogeneity resulting from ILS operates by computing trees on each genomic region (i.e., computing “gene trees”) and then using these gene trees to define a matrix of average internode distances, where the internode distance in a tree T between two species x and y is the number of nodes in T between the leaves corresponding to x and y. Given such a matrix, a tree can then be computed using methods such as neighbor joining. Methods such as ASTRID and NJst (which use this basic approach) are provably statistically consistent, very fast (low degree polynomial time) and have had high accuracy under many conditions that makes them competitive with other popular species tree estimation methods. In this study, inspired by the very recent work of weighted ASTRAL, we present weighted ASTRID, a variant of ASTRID that takes the branch uncertainty on the gene trees into account in the internode distance. Results Our experimental study evaluating weighted ASTRID typically shows improvements in accuracy compared to the original (unweighted) ASTRID, and shows competitive accuracy against weighted ASTRAL, the state of the art. Our re-implementation of ASTRID also improves the runtime, with marked improvements on large datasets. Conclusions Weighted ASTRID is a new and very fast method for species tree estimation that typically improves upon ASTRID and has comparable accuracy to weighted ASTRAL, while remaining much faster. Weighted ASTRID is available at https://github.com/RuneBlaze/internode .

Cancer progression and treatment can be informed by reconstructing its evolutionary history from tumor cells. Although many methods exist to estimate evolutionary trees (called phylogenies) from molecular sequences, traditional approaches assume the input data are error-free and the output tree is fully resolved. These assumptions are challenged in tumor phylogenetics because single-cell sequencing produces sparse, error-ridden data and because tumors evolve clonally. Here, we study the theoretical utility of methods based on quartets (four-leaf, unrooted phylogenetic trees) in light of these barriers. We consider a popular tumor phylogenetics model, in which mutations arise on a (highly unresolved) tree and then (unbiased) errors and missing values are introduced. Quartets are then implied by mutations present in two cells and absent from two cells. Our main result is that the most probable quartet identifies the unrooted model tree on four cells. This motivates seeking a tree such that the number of quartets shared between it and the input mutations is maximized. We prove an optimal solution to this problem is a consistent estimator of the unrooted cell lineage tree; this guarantee includes the case where the model tree is highly unresolved, with error defined as the number of false negative branches. Lastly, we outline how quartet-based methods might be employed when there are copy number aberrations and other challenges specific to tumor phylogenetics. [ABSTRACT FROM AUTHOR]

Background: Species tree estimation is a basic step in many biological research projects, but is complicated by the fact that gene trees can differ from the species tree due to processes such as incomplete lineage sorting (ILS), gene duplication and loss (GDL), and horizontal gene transfer (HGT), which can cause different regions within the genome to have different evolutionary histories (i.e., "gene tree heterogeneity"). One approach to estimating species trees in the presence of gene tree heterogeneity resulting from ILS operates by computing trees on each genomic region (i.e., computing "gene trees") and then using these gene trees to define a matrix of average internode distances, where the internode distance in a tree T between two species x and y is the number of nodes in T between the leaves corresponding to x and y. Given such a matrix, a tree can then be computed using methods such as neighbor joining. Methods such as ASTRID and NJst (which use this basic approach) are provably statistically consistent, very fast (low degree polynomial time) and have had high accuracy under many conditions that makes them competitive with other popular species tree estimation methods. In this study, inspired by the very recent work of weighted ASTRAL, we present weighted ASTRID, a variant of ASTRID that takes the branch uncertainty on the gene trees into account in the internode distance. Results: Our experimental study evaluating weighted ASTRID typically shows improvements in accuracy compared to the original (unweighted) ASTRID, and shows competitive accuracy against weighted ASTRAL, the state of the art. Our re-implementation of ASTRID also improves the runtime, with marked improvements on large datasets. Conclusions: Weighted ASTRID is a new and very fast method for species tree estimation that typically improves upon ASTRID and has comparable accuracy to weighted ASTRAL, while remaining much faster. Weighted ASTRID is available at https://github.com/RuneBlaze/internode. [ABSTRACT FROM AUTHOR]

Cerebral edema and contusion expansion are major determinants of morbidity and mortality after TBI. Current treatment options are reactive, suboptimal and associated with significant side effects. First discovered in models of focal cerebral ischemia, there is increasing evidence that the sulfonylurea receptor 1 (SUR1)-Transient receptor potential melastatin 4 (TRPM4) channel plays a key role in these critical secondary injury processes after TBI. Targeted SUR1-TRPM4 channel inhibition with glibenclamide has been shown to reduce edema and progression of hemorrhage, particularly in preclinical models of contusional TBI. Results from small clinical trials evaluating glibenclamide in TBI have been encouraging. A Phase-2 study evaluating the safety and efficacy of intravenous glibenclamide (BIIB093) in brain contusion is actively enrolling subjects. In this comprehensive narrative review, we summarize the molecular basis of SUR1-TRPM4 related pathology and discuss TBI-specific expression patterns, biomarker potential, genetic variation, preclinical experiments, and clinical studies evaluating the utility of treatment with glibenclamide in this disease.

Phylogenomic analyses routinely estimate species trees using methods that account for gene tree discordance. However, the most scalable species tree inference methods, which summarize independently inferred gene trees to obtain a species tree, are sensitive to hard-to-avoid errors introduced in the gene tree estimation step. This dilemma has created much debate on the merits of concatenation versus summary methods and practical obstacles to using summary methods more widely and to the exclusion of concatenation. The most successful attempt at making summary methods resilient to noisy gene trees has been contracting low support branches from the gene trees. Unfortunately, this approach requires arbitrary thresholds and poses new challenges. Here, we introduce threshold-free weighting schemes for the quartet-based species tree inference, the metric used in the popular method ASTRAL. By reducing the impact of quartets with low support or long terminal branches (or both), weighting provides stronger theoretical guarantees and better empirical performance than the unweighted ASTRAL. Our simulations show that weighting improves accuracy across many conditions and reduces the gap with concatenation in conditions with low gene tree discordance and high noise. On empirical data, weighting improves congruence with concatenation and increases support. Together, our results show that weighting, enabled by a new optimization algorithm we introduce, improves the utility of summary methods and can reduce the incongruence often observed across analytical pipelines. [ABSTRACT FROM AUTHOR]

Mass spectrometry-based sample multiplexing with isobaric tags permits the development of high-throughput and precise quantitative biological assays with proteome-wide coverage and minimal missing values. Here, we nearly doubled the multiplexing capability of the TMTpro reagent set to a 35-plex through the incorporation of one deuterium isotope into the reporter group. Substituting deuterium frequently results in suboptimal peak coelution, which can compromise the accuracy of reporter ion-based quantification. To counteract the deuterium effect on quantitation, we implemented a strategy that necessitated the segregation of nondeuterium and deuterium-containing channels into distinct subplexes during normalization procedures, with reassembly through a common bridge channel. This multiplexing strategy of "design independent sub-plexes but acquire together" (DISAT) was used to compare protein expression differences between human cell lines and in a cysteine-profiling (i.e., chemoproteomics) experiment to identify compounds binding to cysteine-113 of Pin1.

Objective: This study aimed to validate the iScore, ASTRAL score, DRAGON score, and THRIVE score for assessing large vessel occlusion-acute ischemic stroke (AIS-LVO) and establish a predictive model for AIS-LVO patients that has better performance to guide clinical practice., Methods: We retrospectively included 439 patients with AIS-LVO and collected baseline data from all of them. External validation of the iScore, ASTRAL score, DRAGON score, and THRIVE score was performed. All variables were compared between groups via univariate analysis, and the results are expressed as ORs and 95 % CIs. Independent variables with P < 0.25 were included in the multivariate logistic analysis, and statistically significant differences (P < 0.05) were identified as risk factors for prognosis in AIS-LVO patients. Receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA) were used to evaluate the predictive value of our model., Results: Our external validation resulted in an iScore under the curve (AUC) of 0.8475, an ASTRAL AUC of 0.8324, a DRAGON AUC of 0.8196, and a THRIVE AUC of 0.8039. In our research, multivariate Cox regression revealed 8 independent predictors. We used a nomogram to visualize the results of the data analysis. The AUC for the training cohort was 0.8855 (95 % CI, 0.8487-0.9222), and that in the validation cohort was 0.8992 (95 % CI, 0.8496-0. 9488)., Conclusions: In this study, we verified that the above scores have excellent efficacy in predicting the prognosis of AIS-LVO patients. The nomogram we developed was able to predict the prognosis of AIS-LVO more accurately and may contribute to personalized clinical decision-making and treatment for future clinical work., Competing Interests: Declaration of competing interest The authors declare that they have no competing interests., (Copyright © 2024 Elsevier Inc. All rights reserved.)

A group of nine lithic pieces from Banao is presented as part of the pre-Columbian mobile art in this area of Sancti Spíritus, Cuba, considered as cupular petroglyphs executed in flagstones and boulders. The first references to these artifacts in Banao come from Dr. Luis Montané during his visit to the Purial cave in 1888, later several similar specimens were located by the Guamá group from Havana in 1946 and Samá group from Sancti Spíritus from 1960 on. The objective of the investigation focused on the anthropic authenticity of the depressions by studying the traces produced in their execution and the symbolic interpretation that they could have had for their authors. The meticulous study of the available specimens included an extensive bibliographical review, laboratory work, visits to the sites of origin and the exploration of others that provided new evidence. As a result, the symbolic nature of the engravings was corroborated, three presumably associated with astral representations. [ABSTRACT FROM AUTHOR]

Species tree inference is a basic step in biological discovery, but discordance between gene trees creates analytical challenges and large data sets create computational challenges. Although there is generally some information available about the species trees that could be used to speed up the estimation, only one species tree estimation method that addresses gene tree discordance—ASTRAL-J, a recent development in the ASTRAL family of methods—is able to use this information. Here we describe two new methods, NJst-J and FASTRAL-J, that can estimate the species tree, given a partial knowledge of the species tree in the form of a nonbinary unrooted constraint tree. We show that both NJst-J and FASTRAL-J are much faster than ASTRAL-J and we prove that all three methods are statistically consistent under the multispecies coalescent model subject to this constraint. Our extensive simulation study shows that both FASTRAL-J and NJst-J provide advantages over ASTRAL-J: both are faster (and NJst-J is particularly fast), and FASTRAL-J is generally at least as accurate as ASTRAL-J. An analysis of the Avian Phylogenomics Project data set with 48 species and 14,446 genes presents additional evidence of the value of FASTRAL-J over ASTRAL-J (and both over ASTRAL), with dramatic reductions in running time (20 hours for default ASTRAL, and minutes or seconds for ASTRAL-J and FASTRAL-J, respectively). [ABSTRACT FROM AUTHOR]

This article provides a glimpse into the story and meaning of the Bebegig Sukamantri Mask which is used in the art of a sustainable and fast-growing folk carnival in West Java, Indonesia. The masks used in the carnival are unique and are an expression of the cultural heritage left by the ancestors of the ancient Sundanese people in West Java. Each mask creation, in various colors and shapes, derives from the face of Batarakala, who is a very well-known figure in Hindu culture and represents the god of anger. Based on the various shapes and colors of the masks, there are three groups, which are believed to relate to the mythology of the existence of astral creatures that protected ancient Sundanese people, namely Rakshasa for the nobility, Detya for the common people and Denawa for the clergy. The existence of these astral beings is found in the 15th-century ancient manuscript entitled Sanghyang Siksa Kanda ing Karesian (a clue to Reshi). Preserving the Bebegig Sukamantri mask as part of ancient Sundanese cultural heritage is a worthwhile goal because of its uniqueness and its significance for future generations. It is, moreover, greatly appreciated as a cultural carnival event at both national and international level.

Lichens collected worldwide for centuries have resulted in millions of specimens deposited in herbaria that offer the potential to assess species boundaries, phenotypic diversification, ecology, and distribution. The application of molecular approaches to historical collections has been limited due to DNA fragmentation, but high-throughput sequencing offers an opportunity to overcome this barrier. Here, we combined a large dataset of ITS sequences from recently collected material and historical collections, obtained through Sanger, 454, or Illumina Sequencing, to test the performance of ITS barcoding in two genera of lichenized Basidiomycota: Cora and Corella. We attempted to generate new sequence data for 62 fresh specimens (from 2016) and 274 historical collections (collected between 1888 and 1998), for a final dataset of 1325 sequences. We compared various quantitative approaches to delimit species (GMYC, bPTP, ASAP, ABGD) and tested the resolution and accuracy of the ITS fungal barcoding marker by comparison with a six-marker dataset. Finally, we quantitatively compared phylogenetic and phenotypic species delimitation for 87 selected Cora species that have been formally described. Our HTS approach successfully generated ITS sequences for 76% of the historical collections, and our results show that an integrative approach is the gold-standard for understanding diversity in this group. [ABSTRACT FROM AUTHOR]

Introduction. Accurately predicting outcomes after acute ischaemic stroke (AIS) is a major clinical goal. The aim of this pilot study was to evaluate the prognostic validity and accuracy of the Acute Stroke Registry and Analysis of Lausanne (ASTRAL) score in predicting symptomatic haemorrhagic transformation (sHT) in patients with AIS who have undergone revascularisation. Material and methods. Consecutive patients hospitalised for AIS who underwent treatment with intravenous thrombolysis (IVT) and/or mechanical thrombectomy (MT) were identified, and their ASTRAL scores at hospital admission were estimated. The study endpoint was sHT within 24 hours of stroke onset. The predictive performance of the ASTRAL score was investigated through logistic regression analysis and discrimination and calibration tests. Results. Sixty-eight AIS patients, with a median age of 69 (58-79) years, were included. sHT occurred in 20 (29.4%) of the 68 patients. The ASTRAL score was significantly higher in patients who developed sHT compared to non-sHT patients [36 (34-38) versus 24 (17-32); p<0.001]. The ASTRAL score was an independent predictor of sHT, and showed good discriminative power (area under the curve 0.88; 95% confidence interval, 0.789-0.965). Conclusions and clinical implications. ASTRAL score is an independent predictor of sHT and shows high predictive accuracy in patients with AIS. Future studies are warranted to confirm these results. [ABSTRACT FROM AUTHOR]

: Various tools are currently available to quantify the risks of adverse clinical outcomes after an ischemic stroke. This study aimed to validate and compare prognostic scales among Chinese patients with ischemic stroke. : We compared three stroke prognostic scales (Stroke Prognostication using Age and the National Institutes of Health Stroke Scale-100 [SPAN-100], Totaled Health Risks in Vascular Events [THRIVE], and Acute Stroke Registry and Analysis of Lausanne [ASTRAL]) in 3870 Chinese patients with ischemic stroke from the China Antihypertensive Trial in Acute Ischemic Stroke (CATIS). The 2-year primary outcome was a combination of death and major disability (modified Rankin Scale score ≥3). : Among all the scales, the ASTRAL score had the best accuracy for predicting 2-year prognosis in Chinese patients with ischemic stroke. The C-statistic of the ASTRAL score for the 2-year primary outcome was 0.79 (95% confidence interval [CI]: 0.78–0.80), and the Hosmer–Lemeshow goodness-of-fit test showed that the ASTRAL score fitted Chinese patients with ischemic stroke well (χ2 = 9.83, P = 0.277). The incidences of the primary outcome in the <5%, 5%–9.9%, 10%–19.9%, and ≥20% risk groups based on the ASTRAL scores were 3.93%, 7.55%, 14.29%, and 41.81%, respectively (odds ratio: 1.23; 95% CI: 1.21–1.26; P < 0.001). : The ASTRAL score had higher efficacy than the SPAN-100 and THRIVE scores in predicting 2-year adverse outcomes among Chinese patients with ischemic stroke, suggesting that it could be a valuable risk assessment tool for the 2-year prognosis of such patients. [ABSTRACT FROM AUTHOR]

Abstract Background To account for genome-wide discordance among gene trees, several widely-used methods seek to find a species tree with the minimum distance to input gene trees. To efficiently explore the large space of species trees, some of these methods, including ASTRAL, use dynamic programming (DP). The DP paradigm can restrict the search space, and thus, ASTRAL and similar methods use heuristic methods to define a restricted search space. However, arbitrary constraints provided by the user on the output tree cannot be trivially incorporated into such restrictions. The ability to infer trees that honor user-defined constraints is needed for many phylogenetic analyses, but no solution currently exists for constraining the output of ASTRAL. Results We introduce methods that enable the ASTRAL dynamic programming to infer constrained trees in an effective and scalable manner. To do so, we adopt a recently developed tree completion algorithm and extend it to allow multifurcating input and output trees. In simulation studies, we show that the approach for honoring constraints is both effective and fast. On real data, we show that constrained searches can help interrogate branches not recovered in the optimal ASTRAL tree to reveal support for alternative hypotheses. Conclusions The new algorithm is added ASTRAL to all user-provided constraints on the species tree.

Phylogenomics—the estimation of species trees from multilocus data sets—is a common step in many biological studies. However, this estimation is challenged by the fact that genes can evolve under processes, including incomplete lineage sorting (ILS) and gene duplication and loss (GDL), that make their trees different from the species tree. In this article, we address the challenge of estimating the species tree under GDL. We show that species trees are identifiable under a standard stochastic model for GDL, and that the polynomial-time algorithm ASTRAL-multi, a recent development in the ASTRAL suite of methods, is statistically consistent under this GDL model. We also provide a simulation study evaluating ASTRAL-multi for species tree estimation under GDL. [ABSTRACT FROM AUTHOR]

Lichens collected worldwide for centuries have resulted in millions of specimens deposited in herbaria that offer the potential to assess species boundaries, phenotypic diversification, ecology, and distribution. The application of molecular approaches to historical collections has been limited due to DNA fragmentation, but high-throughput sequencing offers an opportunity to overcome this barrier. Here, we combined a large dataset of ITS sequences from recently collected material and historical collections, obtained through Sanger, 454, or Illumina Sequencing, to test the performance of ITS barcoding in two genera of lichenized Basidiomycota: Cora and Corella. We attempted to generate new sequence data for 62 fresh specimens (from 2016) and 274 historical collections (collected between 1888 and 1998), for a final dataset of 1325 sequences. We compared various quantitative approaches to delimit species (GMYC, bPTP, ASAP, ABGD) and tested the resolution and accuracy of the ITS fungal barcoding marker by comparison with a six-marker dataset. Finally, we quantitatively compared phylogenetic and phenotypic species delimitation for 87 selected Cora species that have been formally described. Our HTS approach successfully generated ITS sequences for 76% of the historical collections, and our results show that an integrative approach is the gold-standard for understanding diversity in this group.

Incongruence among phylogenetic results has become a common occurrence in analyses of genome-scale data sets. Incongruence originates from uncertainty in underlying evolutionary processes (e.g. incomplete lineage sorting) and from difficulties in determining the best analytical approaches for each situation. To overcome these difficulties, more studies are needed that identify incongruences and demonstrate practical ways to confidently resolve them. Here, we present results of a phylogenomic study based on the analysis 197 taxa and 2,526 ultraconserved element (UCE) loci. We investigate evolutionary relationships of Eucerinae, a diverse subfamily of apid bees (relatives of honey bees and bumble bees) with >1,200 species. We sampled representatives of all tribes within the group and >80% of genera, including two mysterious South American genera, Chilimalopsis and Teratognatha. Initial analysis of the UCE data revealed two conflicting hypotheses for relationships among tribes. To resolve the incongruence, we tested concatenation and species tree approaches and used a variety of additional strategies including locus filtering, partitioned gene-trees searches, and gene-based topological tests. We show that within-locus partitioning improves gene tree and subsequent species-tree estimation, and that this approach, confidently resolves the incongruence observed in our data set. After exploring our proposed analytical strategy on eucerine bees, we validated its efficacy to resolve hard phylogenetic problems by implementing it on a published UCE data set of Adephaga (Insecta: Coleoptera). Our results provide a robust phylogenetic hypothesis for Eucerinae and demonstrate a practical strategy for resolving incongruence in other phylogenomic data sets. [ABSTRACT FROM AUTHOR]

Parmeliaceae is the largest family of lichen-forming fungi with a worldwide distribution. We used a target enrichment data set and a qualitative selection method for 250 out of 350 genes to infer the phylogeny of the major clades in this family including 81 taxa, with both subfamilies and all seven major clades previously recognized in the subfamily Parmelioideae. The reduced genome-scale data set was analyzed using concatenated-based Bayesian inference and two different Maximum Likelihood analyses, and a coalescent-based species tree method. The resulting topology was strongly supported with the majority of nodes being fully supported in all three concatenated-based analyses. The two subfamilies and each of the seven major clades in Parmelioideae were strongly supported as monophyletic. In addition, most backbone relationships in the topology were recovered with high nodal support. The genus Parmotrema was found to be polyphyletic and consequently, it is suggested to accept the genus Crespoa to accommodate the species previously placed in Parmotrema subgen. Crespoa. This study demonstrates the power of reduced genome-scale data sets to resolve phylogenetic relationships with high support. Due to lower costs, target enrichment methods provide a promising avenue for phylogenetic studies including larger taxonomic/specimen sampling than whole genome data would allow. [ABSTRACT FROM AUTHOR]

Abstract Background Many supertree estimation and multi-locus species tree estimation methods compute trees by combining trees on subsets of the species set based on some NP-hard optimization criterion. A recent approach to computing large trees has been to constrain the search space by defining a set of “allowed bipartitions”, and then use dynamic programming to find provably optimal solutions in polynomial time. Several phylogenomic estimation methods, such as ASTRAL, the MDC algorithm in PhyloNet, FastRFS, and ALE, use this approach. Results We present SIESTA, a method that can be combined with these dynamic programming algorithms to return a data structure that compactly represents all the optimal trees in the search space. As a result, SIESTA provides multiple capabilities, including: (1) counting the number of optimal trees, (2) calculating consensus trees, (3) generating a random optimal tree, and (4) annotating branches in a given optimal tree by the proportion of optimal trees it appears in. Conclusions SIESTA improves the accuracy of FastRFS and ASTRAL, and is a general technique for enhancing dynamic programming methods for constrained optimization.

Abstract Background Estimation of species trees from multiple genes is complicated by processes such as incomplete lineage sorting, gene duplication and loss, and horizontal gene transfer, that result in gene trees that differ from each other and from the species phylogeny. Methods to estimate species trees in the presence of gene tree discord due to incomplete lineage sorting have been developed and proved to be statistically consistent when gene tree discord is due only to incomplete lineage sorting and every gene tree includes the full set of species. Results We establish statistical consistency of certain coalescent-based species tree estimation methods under some models of taxon deletion from genes. We also evaluate the impact of missing data on four species tree estimation methods (ASTRAL-II, ASTRID, MP-EST, and SVDquartets) using simulated datasets with varying levels of incomplete lineage sorting, gene tree estimation error, and degrees/patterns of missing data. Conclusions All the species tree estimation methods improved in accuracy as the number of genes increased and often produced highly accurate species trees even when the amount of missing data was large. These results together indicate that accurate species tree estimation is possible under a variety of conditions, even when there are substantial amounts of missing data.

Abstract Background Evolutionary histories can be discordant across the genome, and such discordances need to be considered in reconstructing the species phylogeny. ASTRAL is one of the leading methods for inferring species trees from gene trees while accounting for gene tree discordance. ASTRAL uses dynamic programming to search for the tree that shares the maximum number of quartet topologies with input gene trees, restricting itself to a predefined set of bipartitions. Results We introduce ASTRAL-III, which substantially improves the running time of ASTRAL-II and guarantees polynomial running time as a function of both the number of species (n) and the number of genes (k). ASTRAL-III limits the bipartition constraint set (X) to grow at most linearly with n and k. Moreover, it handles polytomies more efficiently than ASTRAL-II, exploits similarities between gene trees better, and uses several techniques to avoid searching parts of the search space that are mathematically guaranteed not to include the optimal tree. The asymptotic running time of ASTRAL-III in the presence of polytomies is O(nk)1.726D $O\left ((nk)^{1.726} D \right)$ where D=O(nk) is the sum of degrees of all unique nodes in input trees. The running time improvements enable us to test whether contracting low support branches in gene trees improves the accuracy by reducing noise. In extensive simulations, we show that removing branches with very low support (e.g., below 10%) improves accuracy while overly aggressive filtering is harmful. We observe on a biological avian phylogenomic dataset of 14K genes that contracting low support branches greatly improve results. Conclusions ASTRAL-III is a faster version of the ASTRAL method for phylogenetic reconstruction and can scale up to 10,000 species. With ASTRAL-III, low support branches can be removed, resulting in improved accuracy.

Parmeliaceae is the largest family of lichen-forming fungi with a worldwide distribution. We used a target enrichment data set and a qualitative selection method for 250 out of 350 genes to infer the phylogeny of the major clades in this family including 81 taxa, with both subfamilies and all seven major clades previously recognized in the subfamily Parmelioideae. The reduced genome-scale data set was analyzed using concatenated-based Bayesian inference and two different Maximum Likelihood analyses, and a coalescent-based species tree method. The resulting topology was strongly supported with the majority of nodes being fully supported in all three concatenated-based analyses. The two subfamilies and each of the seven major clades in Parmelioideae were strongly supported as monophyletic. In addition, most backbone relationships in the topology were recovered with high nodal support. The genus Parmotrema was found to be polyphyletic and consequently, it is suggested to accept the genus Crespoa to accommodate the species previously placed in Parmotrema subgen. Crespoa. This study demonstrates the power of reduced genome-scale data sets to resolve phylogenetic relationships with high support. Due to lower costs, target enrichment methods provide a promising avenue for phylogenetic studies including larger taxonomic/specimen sampling than whole genome data would allow. [ABSTRACT FROM AUTHOR]

Background: To account for genome-wide discordance among gene trees, several widely-used methods seek to find a species tree with the minimum distance to input gene trees. To efficiently explore the large space of species trees, some of these methods, including ASTRAL, use dynamic programming (DP). The DP paradigm can restrict the search space, and thus, ASTRAL and similar methods use heuristic methods to define a restricted search space. However, arbitrary constraints provided by the user on the output tree cannot be trivially incorporated into such restrictions. The ability to infer trees that honor user-defined constraints is needed for many phylogenetic analyses, but no solution currently exists for constraining the output of ASTRAL. Results: We introduce methods that enable the ASTRAL dynamic programming to infer constrained trees in an effective and scalable manner. To do so, we adopt a recently developed tree completion algorithm and extend it to allow multifurcating input and output trees. In simulation studies, we show that the approach for honoring constraints is both effective and fast. On real data, we show that constrained searches can help interrogate branches not recovered in the optimal ASTRAL tree to reveal support for alternative hypotheses. Conclusions: The new algorithm is added ASTRAL to all user-provided constraints on the species tree. [ABSTRACT FROM AUTHOR]

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Background: Many supertree estimation and multi-locus species tree estimation methods compute trees by combining trees on subsets of the species set based on some NP-hard optimization criterion. A recent approach to computing large trees has been to constrain the search space by defining a set of "allowed bipartitions", and then use dynamic programming to find provably optimal solutions in polynomial time. Several phylogenomic estimation methods, such as ASTRAL, the MDC algorithm in PhyloNet, FastRFS, and ALE, use this approach. Results: We present SIESTA, a method that can be combined with these dynamic programming algorithms to return a data structure that compactly represents all the optimal trees in the search space. As a result, SIESTA provides multiple capabilities, including: (1) counting the number of optimal trees, (2) calculating consensus trees, (3) generating a random optimal tree, and (4) annotating branches in a given optimal tree by the proportion of optimal trees it appears in. Conclusions: SIESTA improves the accuracy of FastRFS and ASTRAL, and is a general technique for enhancing dynamic programming methods for constrained optimization. [ABSTRACT FROM AUTHOR]

Background: Estimation of species trees from multiple genes is complicated by processes such as incomplete lineage sorting, gene duplication and loss, and horizontal gene transfer, that result in gene trees that differ from each other and from the species phylogeny. Methods to estimate species trees in the presence of gene tree discord due to incomplete lineage sorting have been developed and proved to be statistically consistent when gene tree discord is due only to incomplete lineage sorting and every gene tree includes the full set of species. Results: We establish statistical consistency of certain coalescent-based species tree estimation methods under some models of taxon deletion from genes. We also evaluate the impact of missing data on four species tree estimation methods (ASTRAL-II, ASTRID, MP-EST, and SVDquartets) using simulated datasets with varying levels of incomplete lineage sorting, gene tree estimation error, and degrees/patterns of missing data. Conclusions: All the species tree estimation methods improved in accuracy as the number of genes increased and often produced highly accurate species trees even when the amount of missing data was large. These results together indicate that accurate species tree estimation is possible under a variety of conditions, even when there are substantial amounts of missing data. [ABSTRACT FROM AUTHOR]

Background: Evolutionary histories can be discordant across the genome, and such discordances need to be considered in reconstructing the species phylogeny. ASTRAL is one of the leading methods for inferring species trees from gene trees while accounting for gene tree discordance. ASTRAL uses dynamic programming to search for the tree that shares the maximum number of quartet topologies with input gene trees, restricting itself to a predefined set of bipartitions. Results: We introduce ASTRAL-III, which substantially improves the running time of ASTRAL-II and guarantees polynomial running time as a function of both the number of species (n) and the number of genes (k). ASTRAL-III limits the bipartition constraint set (X) to grow at most linearly with n and k. Moreover, it handles polytomies more efficiently than ASTRAL-II, exploits similarities between gene trees better, and uses several techniques to avoid searching parts of the search space that are mathematically guaranteed not to include the optimal tree. The asymptotic running time of ASTRAL-III in the presence of polytomies is O ( nk ) 1.726 D \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$O\left ((nk)^{1.726} D \right)$\end{document} where D=O(nk) is the sum of degrees of all unique nodes in input trees. The running time improvements enable us to test whether contracting low support branches in gene trees improves the accuracy by reducing noise. In extensive simulations, we show that removing branches with very low support (e.g., below 10%) improves accuracy while overly aggressive filtering is harmful. We observe on a biological avian phylogenomic dataset of 14K genes that contracting low support branches greatly improve results. Conclusions: ASTRAL-III is a faster version of the ASTRAL method for phylogenetic reconstruction and can scale up to 10,000 species. With ASTRAL-III, low support branches can be removed, resulting in improved accuracy. [ABSTRACT FROM AUTHOR]

The phylogenetic relationships among extant gibbon species remain unresolved despite numerous efforts using morphological, behavorial, and genetic data and the sequencing of whole genomes. Amajor challenge in reconstructing the gibbon phylogeny is the radiative speciation process, which resulted in extremely short internal branches in the species phylogeny and extensive incomplete lineage sorting with extensive gene-tree heterogeneity across the genome. Here, we analyze two genomic-scale data sets, with ~10,000 putative noncoding and exonic loci, respectively, to estimate the species tree for the major groups of gibbons. We used the Bayesian full-likelihood method BPP under themultispecies coalescentmodel, which naturally accommodates incomplete lineage sorting and uncertainties in the gene trees. For comparison, we included three heuristic coalescent-based methods (MP-EST, SVDQUARTETS, and ASTRAL) as well as concatenation. From both data sets, we infer the phylogeny for the four extant gibbon genera to be (Hylobates, (Nomascus, (Hoolock, Symphalangus))). We used simulation guided by the real data to evaluate the accuracy of the methods used. ASTRAL, while not as efficient as BPP, performed well in estimation of the species tree even in presence of excessive incomplete lineage sorting. Concatenation, MP-EST and SVDQUARTETS were unreliable when the species tree contains very short internal branches. Likelihood ratio test of gene flow suggests a small amount of migration from Hylobates moloch to H. pileatus, while cross-genera migration is absent or rare. Our results highlight the utility of coalescent-based methods in addressing challenging species tree problems characterized by short internal branches and rampant gene tree-species tree discordance. [ABSTRACT FROM AUTHOR]

The early radiation of Neoaves has been hypothesized to be an intractable “hard polytomy”. We explore the fundamental properties of insertion/deletion alleles (indels), an under-utilized form of genomic data with the potential to help solve this. We scored >5 million indels from >7000 pan-genomic intronic and ultraconserved element (UCE) loci in 48 representatives of all neoavian orders. We found that intronic and UCE indels exhibited less homoplasy than nucleotide (nt) data. Gene trees estimated using indel data were less resolved than those estimated using nt data. Nevertheless, Accurate Species TRee Algorithm (ASTRAL) species trees estimated using indels were generally similar to nt-based ASTRAL trees, albeit with lower support. However, the power of indel gene trees became clear when we combined them with nt gene trees, including a striking result for UCEs. The individual UCE indel and nt ASTRAL trees were incongruent with each other and with the intron ASTRAL trees; however, the combined indel+nt ASTRAL tree was much more congruent with the intronic trees. Finally, combining indel and nt data for both introns and UCEs provided sufficient power to reduce the scope of the polytomy that was previously proposed for several supraordinal lineages of Neoaves.

Treatment for chronic hepatitis C virus (HCV) has evolved rapidly from an interferon based regimen of modest efficacy with significant adverse events to a well-tolerated, highly effective all-oral directly acting antiviral (DAA) therapy. Although significant improvement in sustained virologic responses (SVR) has been reported with new DAAs for genotypes 1 and 4, effective treatments for genotype 3 have been lacking, and a single pill that can yield high SVR rates against HCV genotypes 1-6 has not been available until now. Sofosbuvir (a pangenotypic NS5B inhibitor) and velpatasvir (a pangenotypic NS5A inhibitor) were recently approved in a fixed-dose combination pill. The availability of this pangenotypic pill holds promise for providing highly effective treatment with minimal laboratory testing for chronic HCV worldwide. [ABSTRACT FROM AUTHOR]

Background and purpose Multimodal computed tomography ( CT) based imaging ( MCTI) is widely used in acute ischaemic stroke. It was postulated that the use of MCTI is associated with improved patient outcome without causing harm. Methods All patients with an acute ischaemic stroke and CT-based imaging within 24 h from the ASTRAL (Acute Stroke Registry and Analysis of Lausanne) registry were included. Preceding demographic, clinical, biological, radiological and follow-up data were collected. Significant predictors of MCTI use were identified retrospectively to go on to fit a multivariable analysis. Then, patients undergoing additional CT angiography ( CTA) or CTA and perfusion CT ( CTP) were compared with non-contrast CT only patients with regard to 3-month favourable outcome (modified Rankin Scale score ≤2), 12-month mortality, stroke mechanism, short-term renal failure, use of ancillary diagnostic tests, duration of hospitalization and 12-month stroke recurrence. Results Of the 1994 included patients, 273 had only non-contrast CT, 411 had both non-contrast CT and CTA and 1310 had all three examinations. Factors independently associated with MCTI were younger age, low pre-stroke modified Rankin Scale score, low creatinine value, known stroke onset, anterior circulation stroke, anticoagulation or antihypertensive therapy ( CTA only) and higher National Institutes of Health Stroke Scale scores ( CTP only). After adjustment, MCTI was associated with a 50% reduction of 12-month mortality and a lower likelihood of unknown stroke mechanism. No association was found between MCTI and 3-month outcome, contrast-induced nephropathy, hospitalization duration, number of ancillary diagnostic tests or with stroke recurrence. Conclusion Our study shows an association of MCTI use with lower adjusted 12-month mortality, better identification of the stroke mechanism and no signs of harm. [ABSTRACT FROM AUTHOR]

Background and purpose ASTRAL, SEDAN and DRAGON scores are three well-validated scores for stroke outcome prediction. Whether these scores predict stroke outcome more accurately compared with physicians interested in stroke was investigated. Methods Physicians interested in stroke were invited to an online anonymous survey to provide outcome estimates in randomly allocated structured scenarios of recent real-life stroke patients. Their estimates were compared to scores' predictions in the same scenarios. An estimate was considered accurate if it was within 95% confidence intervals of actual outcome. Results In all, 244 participants from 32 different countries responded assessing 720 real scenarios and 2636 outcomes. The majority of physicians' estimates were inaccurate (1422/2636, 53.9%). 400 (56.8%) of physicians' estimates about the percentage probability of 3-month modified Rankin score ( mRS) > 2 were accurate compared with 609 (86.5%) of ASTRAL score estimates ( P < 0.0001). 394 (61.2%) of physicians' estimates about the percentage probability of post-thrombolysis symptomatic intracranial haemorrhage were accurate compared with 583 (90.5%) of SEDAN score estimates ( P < 0.0001). 160 (24.8%) of physicians' estimates about post-thrombolysis 3-month percentage probability of mRS 0-2 were accurate compared with 240 (37.3%) DRAGON score estimates ( P < 0.0001). 260 (40.4%) of physicians' estimates about the percentage probability of post-thrombolysis mRS 5-6 were accurate compared with 518 (80.4%) DRAGON score estimates ( P < 0.0001). Conclusions ASTRAL, DRAGON and SEDAN scores predict outcome of acute ischaemic stroke patients with higher accuracy compared to physicians interested in stroke. [ABSTRACT FROM AUTHOR]

Coalescent-based methods are nowbroadly used to infer evolutionary relationships between groups of organisms under the assumption that incomplete lineage sorting (ILS) is the only source of gene tree discordance. Many of these methods are known to consistently estimate the species tree when all their assumptions are met. Nonetheless, little work has been done to test the robustness of such methods to violations of their assumptions. Here, we study the performance of two of the most efficient coalescent-based methods, ASTRAL and NJst, in the presence of gene flow. Gene flow violates the assumption that ILS is the sole source of gene tree conflict. We find anomalous gene trees on three-taxon rooted trees and on four-taxon unrooted trees. These anomalous trees do not exist under ILS only, but appear because of gene flow. Our simulations show that species tree methods (and concatenation) may reconstruct the wrong evolutionary history, even from a very large number of well-reconstructed gene trees. In other words, species tree methods can be inconsistent under gene flow. Our results underline the need for methods like PhyloNet, to account simultaneously for ILS and gene flow in a unified framework. Although much slower, PhyloNet had better accuracy and remained consistent at high levels of gene flow. [ABSTRACT FROM AUTHOR]

Species tree reconstruction is complicated by effects of incomplete lineage sorting, commonly modeled by the multispecies coalescentmodel (MSC). While there has been substantial progress in developingmethods that estimate a species tree given a collection of gene trees, less attention has been paid to fast and accurate methods of quantifying support. In this article, we propose a fast algorithm to compute quartet-based support for each branch of a given species tree with regard to a given set of gene trees. We then show how the quartet support can be used in the context of the MSC to compute (1) the local posterior probability (PP) that the branch is in the species tree and (2) the length of the branch in coalescent units. We evaluate the precision and recall of the local PP on a wide set of simulated and biological datasets, and show that it has very high precision and improved recall compared with multi-locus bootstrapping. The estimated branch lengths are highly accurate when gene tree estimation error is low, but are underestimated when gene tree estimation error increases. Computation of both the branch length and local PP is implemented as new features in ASTRAL. [ABSTRACT FROM AUTHOR]

Background: BLOSUM matrices belong to the most commonly used substitution matrix series for protein homology search and sequence alignments since their publication in 1992. In 2008, Styczynski et al. discovered miscalculations in the clustering step of the matrix computation. Still, the RBLOSUM64 matrix based on the corrected BLOSUM code was reported to perform worse at a statistically significant level than the BLOSUM62. Here, we present a further correction of the (R)BLOSUM code and provide a thorough performance analysis of BLOSUM-, RBLOSUM- and the newly derived CorBLOSUM-type matrices. Thereby, we assess homology search performance of these matrix-types derived from three different BLOCKS databases on all versions of the ASTRAL20, ASTRAL40 and ASTRAL70 subsets resulting in 51 different benchmarks in total. Our analysis is focused on two of the most popular BLOSUM matrices—BLOSUM50 and BLOSUM62. Results: Our study shows that fixing small errors in the BLOSUM code results in substantially different substitution matrices with a beneficial influence on homology search performance when compared to the original matrices. The CorBLOSUM matrices introduced here performed at least as good as their BLOSUM counterparts in ∼ 75 % of all test cases. On up-to-date ASTRAL databases BLOSUM matrices were even outperformed by CorBLOSUM matrices in more than 86 % of the times. In contrast to the study by Styczynski et al., the tested RBLOSUM matrices also outperformed the corresponding BLOSUM matrices in most of the cases. Comparing the CorBLOSUM with the RBLOSUM matrices revealed no general performance advantages for either on older ASTRAL releases. On up-to-date ASTRAL databases however CorBLOSUM matrices performed better than their RBLOSUM counterparts in ∼ 74 % of the test cases. Conclusions: Our results imply that CorBLOSUM type matrices outperform the BLOSUM matrices on a statistically significant level in most of the cases, especially on up-to-date databases such as ASTRAL ⩾ 2.01. Additionally, CorBLOSUM matrices are closer to those originally intended by Henikoff and Henikoff on a conceptual level. Hence, we encourage the usage of CorBLOSUM over (R)BLOSUM matrices for the task of homology search. [ABSTRACT FROM AUTHOR]

Gene-tree-estimation error is a major concern for coalescent methods of phylogenetic inference. We sampled eight empirical studies of ancient lineages with diverse numbers of taxa and genes for which the original authors applied one or more coalescent methods. We found that the average pairwise congruence among gene trees varied greatly both between studies and also often within a study. We recommend that presenting plots of pairwise congruence among gene trees in a dataset be treated as a standard practice for empirical coalescent studies so that readers can readily assess the extent and distribution of incongruence among gene trees. ASTRAL-based coalescent analyses generally outperformed MP-EST and STAR with respect to both internal consistency (congruence between analyses of subsamples of genes with the complete dataset of all genes) and congruence with the concatenation-based topology. We evaluated the approach of subsampling gene trees that are, on average, more congruent with other gene trees as a method to reduce artifacts caused by gene-tree-estimation errors on coalescent analyses. We suggest that this method is well suited to testing whether gene-tree-estimation error is a primary cause of incongruence between concatenation- and coalescent-based results, to reconciling conflicting phylogenetic results based on different coalescent methods, and to identifying genes affected by artifacts that may then be targeted for reciprocal illumination. We provide scripts that automate the process of calculating pairwise gene-tree incongruence and subsampling trees while accounting for differential taxon sampling among genes. Finally, we assert that multiple tree-search replicates should be implemented as a standard practice for empirical coalescent studies that apply MP-EST. [ABSTRACT FROM AUTHOR]

It has recently been concluded that phylogenomic data from 310 nuclear genes support the clade of (Amborellales, Nymphaeales) as sister to the remaining angiosperms and that shortcut coalescent phylogenetic methods outperformed concatenation for these data. We falsify both of those conclusions here by demonstrating that discrepant results between the coalescent and concatenation analyses are primarily caused by the coalescent methods applied (MP-EST and STAR) not being robust to the highly divergent and often mis-rooted gene trees that were used. This result reinforces the expectation that low amounts of phylogenetic signal and methodological artifacts in gene-tree reconstruction can be more problematic for shortcut coalescent methods than is the assumption of a single hierarchy for all genes by concatenation methods when these approaches are applied to ancient divergences in empirical studies. We also demonstrate that a third coalescent method, ASTRAL, is more robust to mis-rooted gene trees than MP-EST or STAR, and that both Observed Variability (OV) and Tree Independent Generation of Evolutionary Rates (TIGER), which are two character subsampling procedures, are biased in favor of characters with highly asymmetrical distributions of character states when applied to this dataset. We conclude that enthusiastic application of novel tools is not a substitute for rigorous application of first principles, and that trending methods (e.g., shortcut coalescent methods applied to ancient divergences, tree-independent character subsampling), may be novel sources of previously under-appreciated, systematic errors. [ABSTRACT FROM AUTHOR]