High Posterior Probability Research Articles

Characterization of Seventeen Complete Mitochondrial Genomes: Structural Features and Phylogenetic Implications of the Lepidopteran Insects.

Lepidoptera (moths and butterflies) are widely distributed in the world, but high-level phylogeny in Lepidoptera remains uncertain. More mitochondrial genome (mitogenome) data can help to conduct comprehensive analysis and construct a robust phylogenetic tree. Here, we sequenced and annotated 17 complete moth mitogenomes and made comparative analysis with other moths. The gene order of trnM-trnI-trnQ in 17 moths was different from trnI-trnQ-trnM of ancestral insects. The number, type, and order of genes were consistent with reported moths. The length of newly sequenced complete mitogenomes ranged from 14,231 bp of Rhagastis albomarginatus to 15,756 bp of Numenes albofascia. These moth mitogenomes were typically with high A+T contents varied from 76.0% to 81.7% and exhibited negative GC skews. Among 13 protein coding genes (PCGs), some unusual initiations and terminations were found in part of newly sequenced moth mitogenomes. Three conserved gene-overlapping regions and one conserved intergenic region were detected among 17 mitogenomes. The phylogenetic relationship of major superfamilies in Macroheterocera was as follows: (Bombycoidea + Lasiocampoidea) + ((Drepanoidea + Geometroidea) + Noctuoidea)), which was different from previous studies. Moreover, the topology of Noctuoidea as (Notodontidae + (Erebidae + Noctuidae)) was supported by high Bayesian posterior probabilities (BPP = 1.0) and bootstrapping values (BSV = 100). This study greatly enriched the mitogenome database of moth and strengthened the high-level phylogenetic relationships of Lepidoptera.

Virtual anthropology: Forensic applications to cranial skeletal remains from the Spanish Civil War

Biological and forensic anthropologists face limitations while studying skeletal remains altered by taphonomic alterations and perimortem trauma, such as in remains from the Spanish Civil War. However, virtual anthropology techniques can optimize the information inferred from fragmented and deformed remains by generating and restoring three-dimensional bone models. We applied a low-cost 3D modelling methodology based on photogrammetry to develop novel forensic applications of virtual 3D skull reconstruction, assembly, restoration and ancestry estimation. Crania and mandible fragments from five Spanish Civil War victims were reconstructed with high accuracy, and only one cranium could not be assembled due to extensive bone loss. Virtual mirroring successfully restored reconstructed crania, producing 3D models with reduced deformation and perimortem trauma. High correlation between traditional and virtual craniofacial measurements confirmed that 3D models are suitable for forensic applications. Craniometric databases of world-wide and Spanish populations were used to assess the potential of discriminant analysis to estimate population ancestry. Our protocol correctly estimated the continental origin of 86.7 % of 15 crania of known origin, and despite low morphological differentiation within European populations, correctly identified 54.5 % as Spanish and 27.3 % of them with high posterior probabilities. Two restored crania from the Civil War were estimated as Spanish, and one as a non-Spanish European. Results were not conclusive for one cranium and did not confirm previous archeological hypotheses. Overall, our research shows the potential to assess the presence of foreign volunteers in the Spanish Civil War and highlights the added value of 3D-virtual techniques in forensic anthropology.

Reference Ranges for Gait Speed and Sit-to-Stand Performance in a Cohort of Mobility-Intact Community-Dwelling Older Adults From Singapore.

Slow gait speed and sit-to-stand performance are associated with adverse clinical outcomes in older adults. Identifying older adults with functional performance "below norms" is the first step toward prevention. We aimed to (1) examine the associations of age, body height, and gender with gait speed and sit-to-stand performance and (2) develop subgroup-specific reference ranges in older adults with no self-reported mobility limitations. Cross-sectional study. This study analyzed data from 775 community-dwelling older adults who reported no difficulty walking 100m, climbing stairs, and rising from the chair. Gait speed and sit-to-stand performance were measured by the 10-m gait speed test and 5-times sit-to-stand test, respectively. Bayesian linear regression was used to derive 95% reference ranges for gait speed and sit-to-stand performance, defined by different levels of age, body height, and gender. Overall, 95% reference range was 0.89-1.79m/s for habitual gait speed and 7.4-27.9 stands/30s for sit-to-stand pace. Age had the highest posterior probability (>99%) of a meaningful association with both functional outcomes. Additionally, height was strongly associated with gait speed: a 10-cm increase in height was associated with 0.07m/s (95% credible interval, 0.05-0.10) faster gait speed. For sit-to-stand test, the lower 95% reference range limits tended to be similar across gender and gender-specific height subgroups, owing to the associations of faster sit-to-stand pace with shorter height and male gender. Because extensive tables of reference ranges are impractical, a web-based application (https://sghpt.shinyapps.io/ippts/) is created to provide subgroup-specific reference ranges. In a large sample of mobile-intact older adults, reference ranges for gait speed and sit-to-stand performance differed meaningfully by age. Furthermore, gait speed was stature dependent. Although requiring validation, our findings may be used to define subgroup-specific "below-range" values and to complement existing universal clinical cut points for gait speed and sit-to-stand performance.

ZELLNER’S G-PRIORS IN BAYESIAN MODEL AVERAGING OF LARGE MODEL SPACE USING MARKOV CHAIN MONTE CARLO MODEL COMPOSITION APPLICABLE UNDER BAYESIAN MODEL SAMPLING

Applied researchers are frequently faced with the issue of model uncertainty in situations where many possible models exist. For large model space in regression analysis, the challenge has always been how to select a single model among competing large model space when making inferences. Bayesian Model Averaging (BMA) is a technique designed to help account for the uncertainty inherent in the model selection process. Informative prior distributions related to a natural conjugate prior specification are investigated under a limited choice of a single scalar hyper parameter called g-prior which corresponds to the degree of prior uncertainty on regression coefficients. This study focuses on situations with extremely large model space made up of large set of regressors generated by a small number of observations, when estimating model parameters. A set of g-prior structures in literature are considered with a view to identify an improved g-prior specification for regression coefficients in Bayesian Model Averaging. The study demonstrates the sensitivity of posterior results to the choice of g-prior on simulated dataand real-life data. Markov Chain Monte Carlo (MCMC) are used to generate a process which moves through large model space to adequately identify the high posterior probability models using the Markov Chain Monte Carlo Model Composition (MC3), a method applicable under Bayesian Model Sampling (BMS). To assess the sensitivity and predictive ability of the g-priors,predictive criteria like Log Predictive Score (LPS) and Log Marginal Likelihood (LML) are employed. The results reveal a g-prior structure that exhibited equally competitive and consistent predictive ability among considered g-prior structures in literature.

Mass-spin reparametrization for a rapid parameter estimation of inspiral gravitational-wave signals

Estimating the source parameters of gravitational waves from compact binary coalescence(CBC) is a key analysis task in gravitational-wave astronomy. To deal with the increasing detection rate of CBC signals, optimizing the parameter estimation analysis is crucial. The analysis typically employs a stochastic sampling technique such as Markov Chain Monte Carlo(MCMC), where the source parameter space is explored and regions of high Bayesian posterior probability density are found. One of the bottlenecks slowing down the analysis is the non-trivial correlation between masses and spins of colliding objects, which makes the exploration of mass$\unicode{x2013}$spin space extremely inefficient. We introduce a new set of mass$\unicode{x2013}$spin sampling parameters which makes the posterior distribution to be simple in the new parameter space, regardless of the true values of the parameters. The new parameter combinations are obtained as the principal components of the Fisher matrix for the restricted 1.5 post-Newtonian waveform. Our re-parameterization improves the efficiency of MCMC by a factor of $\sim10$ for binary neutron star with narrow-spin prior ($|\vec{\chi}|<0.05$) and $\sim100$ with broad-spin prior ($|\vec{\chi}|<0.99$), under the assumption that the binary has spins aligned with its orbital angular momentum.

Paracapoeta, a new genus of the Cyprinidae from Mesopotamia, Cilicia and Levant (Teleostei, Cypriniformes)

The molecular and morphological studies carried out within the scope of this study revealed that the scrapers, known as the Mesopotamian group, belong to a different genus. The Paracapoetagen. nov., from the Mesopotomia and Levant, is distinguished from Capoeta and Luciobarbus species by the presence of a strong ligament between the base of the last simple and the first branched rays of the dorsal-fin (vs. no or a very weak ligament). The Paracapoeta further differs from Capoeta by the last simple dorsal-fin ray strongly ossified in adult specimens (more than 75%, vs. less than 75%). The Paracapoeta further differs from Luciobarbus by the lower lip with horny layer (vs. fleshy lips). The molecular phylogeny based on the combined dataset (COI + Cytb, 1312 bp.) showed that the genus Paracapoeta was recovered from the other groups in the subfamily Barbinae with high bootstrap and posterior probability values (BP: 94%, PP: 0.96). Also, Paracapoeta and Capoeta are well differentiated by an average genetic distance of 8.02±0.78%. The morphological and molecular findings have largely overlapped each other. Besides, Capoeta turani is treated as a synonym of Capoeta erhani.

Entropic Out-of-Distribution Detection: Seamless Detection of Unknown Examples

In this article, we argue that the unsatisfactory out-of-distribution (OOD) detection performance of neural networks is mainly due to the SoftMax loss anisotropy and propensity to produce low entropy probability distributions in disagreement with the principle of maximum entropy. On the one hand, current OOD detection approaches usually do not directly fix the SoftMax loss drawbacks, but rather build techniques to circumvent it. Unfortunately, those methods usually produce undesired side effects (e.g., classification accuracy drop, additional hyperparameters, slower inferences, and collecting extra data). On the other hand, we propose replacing SoftMax loss with a novel loss function that does not suffer from the mentioned weaknesses. The proposed IsoMax loss is isotropic (exclusively distance-based) and provides high entropy posterior probability distributions. Replacing the SoftMax loss by IsoMax loss requires no model or training changes. Additionally, the models trained with IsoMax loss produce as fast and energy-efficient inferences as those trained using SoftMax loss. Moreover, no classification accuracy drop is observed. The proposed method does not rely on outlier/background data, hyperparameter tuning, temperature calibration, feature extraction, metric learning, adversarial training, ensemble procedures, or generative models. Our experiments showed that IsoMax loss works as a seamless SoftMax loss drop-in replacement that significantly improves neural networks' OOD detection performance. Hence, it may be used as a baseline OOD detection approach to be combined with current or future OOD detection techniques to achieve even higher results.

Model Based Screening Embedded Bayesian Variable Selection for Ultra-high Dimensional Settings

We develop a Bayesian variable selection method, called SVEN, based on a hierarchical Gaussian linear model with priors placed on the regression coefficients as well as on the model space. Sparsity is achieved by using degenerate spike priors on inactive variables, whereas Gaussian slab priors are placed on the coefficients for the important predictors making the posterior probability of a model available in explicit form (up to a normalizing constant). Embedding a unique model based screening and using fast Cholesky updates, SVEN produces a highly scalable computational framework to explore gigantic model spaces, rapidly identify the regions of high posterior probabilities and make fast inference and prediction. A temperature schedule is used to further mitigate multimodal posterior distributions. The temperature value is guided by our model selection consistency results which hold even when the norm of mean effects solely due to the unimportant variables diverges. An appealing byproduct of SVEN is the construction of novel model weight adjusted prediction intervals. The performance of SVEN is demonstrated through a number of simulation experiments and a real data example from a genome wide association study with over half a million markers. Supplementary materials for this article are available online.

OA30 Identification of causal genes and mechanisms by which genetic variation mediates juvenile idiopathic arthritis susceptibility using functional genomics and CRISPR-Cas9

Abstract Background/Aims We recently performed the largest juvenile idiopathic arthritis (JIA) genome-wide association study (GWAS) to date. Disease-associated loci contain multiple single nucleotide polymorphism (SNPs), and the majority map to non-coding enhancers, making it challenging to define causal variants and genes. Functional genomics datasets in disease-relevant tissues have been shown to be essential for the functional interpretation of GWAS loci. In particular, capture Hi-C (CHi-C) has been successful in detecting chromosomal interactions linking GWAS loci to their target genes. However, such datasets are lacking in JIA. The aim of this study is to bridge this gap and advance the knowledge of the biological mechanisms that underpin susceptibility to JIA, by integrating GWAS with public epigenomics datasets and in-house generated CHi-C from JIA patients. We focus on CD4+ T-cells, which have been shown to be one of the most relevant cell types in JIA. In addition, we use CRISPR-Cas9 to validate the regulatory effect of prioritised variants on their predicted target genes. Methods Credible SNP sets for the top JIA risk loci (P &amp;lt; 5x10-6) were annotated using EpiMap data. Low input whole genome promoter CHi-C (PCHi-C) was performed on CD4+ T-cells isolated from blood from 3 JIA oligoarthritis patients, and data was analysed using CHiCAGO. We employed CRISPR activation (CRISPRa) and CRISPR interference (CRISPRi) in Jurkats to assess whether prioritized JIA variants are capable of regulating the expression of the interacting genes. Results 614 SNPs (out of 735) were found to overlap active enhancers in CD4+ T-cells, and were prioritized for further analysis. We identified numerous significant chromatin interactions in 19 out of 44 non-MHC JIA associated loci, linking JIA SNPs mapping to T-cell enhancers to a total of 61 target genes and revealing potential novel disease pathways. A JIA-associated locus on chromosome 3 contains 39 SNPs. It maps to an intergenic region and the causal gene/s are unclear. Our PCHi-C data revealed that this JIA locus presents chromatin interactions with the promoters of several genes, such as CCRL2, CCR2, CCR3 and CCR5. Two variants were selected for further analysis: rs79815064, which had the highest posterior probability, and rs8005404, the only variant within a CD4+ T-cell enhancer linked to surrounding gene activity. When both SNPs were targeted with CRISPRa and CRISPRi, we observed an increased and decreased expression, respectively, of CCRL2, CCR2, CCR3 and CCR5, confirming their role in disease. These genes belong to the chemokine receptor family and are important regulators of the inflammatory response. Conclusion Our work shows how functional genomics can help identify biological mechanisms by which GWAS variants increase risk of JIA, which in turn will benefit patients through personalised medicine and the identification of therapeutic targets. Disclosure A. Frantzeskos: None. V. Malysheva: None. C. Shi: None. J. Ding: None. J. Bowes: None. W. Thomson: None. S. Eyre: None. M. Spivakov: Shareholder/stock ownership; M.S. is co-founder and shareholder of Enhanc3D Genomics Ltd. G. Orozco: None.

Four new Parasterope (Ostracoda, Myodocopina) from the Northwest Pacific and their phylogeny based on 16S rRNA

Parasterope Kornicker, 1975 is a marine ostracod genus with 49 species described so far, which makes it the most diverse representative of the subfamily Cylindroleberidinae, as well as the entire family Cylindroleberididae. Despite its global distribution no species are reported from South Korea. Three new species collected from the Korean coast of the Sea of Japan (Parasteropebusanensissp. nov., P.singulasp. nov., and P.sohisp. nov.), and one from the Japanese coast of the Pacific Ocean (P.sagamisp. nov.) are described. A taxonomic key to all named species from East Asia is provided. A phylogenetic tree is reconstructed based on partial 16S rRNA sequences of the four new species and other Cylindroleberidinae available from GenBank. Monophyly of Parasterope is supported by high posterior probabilities, but the phylogenetic analyses also indicate that some of the GenBank data attributed to this genus are probably misidentifications. A map of distribution and a checklist of all described Parasterope species are also provided.

BAYES AĞLARI KULLANARAK HATA TEMELLİ BAKIM PLANLAMASI: HİDROLİK TÜRBİNDE BİR VAKA ÇALIŞMASI

The assessment of existing infrastructures in the energy sector is of great economic importance for the world. The extension of the power generation life of hydroelectric power plants depends on logical decisions regarding the maintenance and renewal of the equipment. For this purpose, a Bayesian network (BN) has been applied to evaluate the failures in the hydraulic turbine to calculate the failure of the turbine. Forty-six nodes have been identified that will affect the operation of the system. Preventive measures have been established for failures with the highest posterior probability. By creating four different cases, failure probabilities and the change of the main fault have been calculated. How much savings could be made in each case is determined with the maintenance. This proposed framework will be guided in determining the maintenance strategies for hydroelectric power plant operators.

ICA1L Is Associated with Small Vessel Disease: A Proteome-Wide Association Study in Small Vessel Stroke and Intracerebral Haemorrhage.

Small vessel strokes (SVS) and intracerebral haemorrhages (ICH) are acute outcomes of cerebral small vessel disease (SVD). Genetic studies combining both phenotypes have identified three loci associated with both traits. However, the genetic cis-regulation at the protein level associated with SVD has not been studied before. We performed a proteome-wide association study (PWAS) using FUSION to integrate a genome-wide association study (GWAS) and brain proteomic data to discover the common mechanisms regulating both SVS and ICH. Dorsolateral prefrontal cortex (dPFC) brain proteomes from the ROS/MAP study (N = 376 subjects and 1443 proteins) and the summary statistics for the SVS GWAS from the MEGASTROKE study (N = 237,511) and multi-trait analysis of GWAS (MTAG)-ICH–SVS from Chung et al. (N = 240,269) were selected. We performed PWAS and then a co-localization analysis with COLOC. The significant and nominal results were validated using a replication dPFC proteome (N = 152). The replicated results (q-value < 0.05) were further investigated for the causality relationship using summary data-based Mendelian randomization (SMR). One protein (ICA1L) was significantly associated with SVS (z-score = −4.42 and p-value = 9.6 × 10−6) and non-lobar ICH (z-score = −4.8 and p-value = 1.58 × 10−6) in the discovery PWAS, with a high co-localization posterior probability of 4. In the validation PWAS, ICA1L remained significantly associated with both traits. The SMR results for ICA1L indicated a causal association of protein expression levels in the brain with SVS (p-value = 3.66 × 10−5) and non-lobar ICH (p-value = 1.81 × 10−5). Our results show that the association of ICA1L with SVS and non-lobar ICH is conditioned by the cis-regulation of its protein levels in the brain.

HAMdetector: a Bayesian regression model that integrates information to detect HLA-associated mutations.

A key process in anti-viral adaptive immunity is that the human leukocyte antigen (HLA) system presents epitopes as major histocompatibility complex I (MHC I) protein-peptide complexes on cell surfaces and in this way alerts CD8+ cytotoxic T-lymphocytes (CTLs). This pathway exerts strong selection pressure on viruses, favoring viral mutants that escape recognition by the HLA/CTL system. Naturally, such immune escape mutations often emerge in highly variable viruses, e.g. HIV or HBV, as HLA-associated mutations (HAMs), specific to the hosts MHC I proteins. The reliable identification of HAMs is not only important for understanding viral genomes and their evolution, but it also impacts the development of broadly effective anti-viral treatments and vaccines against variable viruses. By their very nature, HAMs are amenable to detection by statistical methods in paired sequence/HLA data. However, HLA alleles are very polymorphic in the human host population which makes the available data relatively sparse and noisy. Under these circumstances, one way to optimize HAM detection is to integrate all relevant information in a coherent model. Bayesian inference offers a principled approach to achieve this. We present a new Bayesian regression model for the detection of HAMs that integrates a sparsity-inducing prior, epitope predictions and phylogenetic bias assessment, and that yields easily interpretable quantitative information on HAM candidates. The model predicts experimentally confirmed HAMs as having high posterior probabilities, and it performs well in comparison to state-of-the-art models for several datasets from individuals infected with HBV, HDV and HIV. The source code of this software is available at https://github.com/HAMdetector/Escape.jl under a permissive MIT license. The data underlying this article were provided by permission. Data will be shared on request to the corresponding author with permission of the respective co-authors. Supplementary data are available at Bioinformatics online.

Genetic associations at regulatory phenotypes improve fine-mapping of causal variants for 12 immune-mediated diseases.

The resolution of causal genetic variants informs understanding of disease biology. We used regulatory quantitative trait loci (QTLs) from the BLUEPRINT, GTEx and eQTLGen projects to fine-map putative causal variants for 12 immune-mediated diseases. We identify 340 unique loci that colocalize with high posterior probability (≥98%) with regulatory QTLs and apply Bayesian frameworks to fine-map associations at each locus. We show that fine-mapping credible sets derived from regulatory QTLs are smaller compared to disease summary statistics. Further, they are enriched for more functionally interpretable candidate causal variants and for putatively causal insertion/deletion (INDEL) polymorphisms. Finally, we use massively parallel reporter assays to evaluate candidate causal variants at the ITGA4 locus associated with inflammatory bowel disease. Overall, our findings suggest that fine-mapping applied to disease-colocalizing regulatory QTLs can enhance the discovery of putative causal disease variants and enhance insights into the underlying causal genes and molecular mechanisms.

Molecular phylogenetic analysis resolving the taxonomic discrepancies among Salix L. species naturally found in Turkey

Detailed phylogenetic relationships and molecular dating are still quite rare for the complex and diverse genus Salix L. Here we focus on the taxonomic status and phylogeny of twenty-six Salix taxa natu­rally found in Turkey using the chloroplast DNA regions (trn T-F, matK, and rbcL) to unravel the relationship among them. The status of Salix species was also checked in the phylogenetic tree constructed with the data from Internal Transcribed Spacer (ITS) region of nuclear gene, including 158 accessions from the GenBank and 126 newly generated sequences of 26 Salix taxa (24 species) naturally found in Turkey. The phyloge­netic analysis of the sequence data from both the chloroplast (cpDNA) and nuclear (nrDNA) DNA regions enabled a reliable classification of the genus at the subgeneric level (Salix and Vetrix) with high posterior probability/ bootstrap values as 1/100. The study provides important information on the Salix phylogenetic placements and diverging times of S. pentandroides, S.apoda, S. armenorossica, S. pseudomedemii, S. pedicellata subsp. pedicellata, S. pseudodepressa, S. amplexicaulis, two subspecies of S.triandra, and two endemic species of Turkey (S. purpurea subsp. leucodermis and S. rizeensis) for the first time. Taxonomically, S. amplexicaulis and S. rizeensis previously classified under the subgenus Vetrix were clustered phylogenetically under the subgenus Salix. Subgenera Salix species appears to be diverged from the subg. Vetrix in Eocene (ca. 45.1 Mya) while the estimated divergence times of subg. Salix and subg. Vetrix dated back to 23.1 and 21.65 Mya, respective­ly. However, divergence times among species within Salix and Vetrix subgenera of Turkey seem to be around the Pliocene period. Molecular phylogenetic relationship between Salix species native to Turkey and Salix species from the world were mainly associated with taxonomic hierarchy, rather than geographic proximity.

Bayesian two-stage design for phase II oncology trials with binary endpoint.

In phase II oncology trials, two-stage design allowing early stopping for futility and/or efficacy is frequently used. However, this design based on frequentist statistical approaches could not guarantee a high posterior probability of attending the pre-specified clinically interesting rate from a Bayesian perspective. Here, we proposed a new Bayesian design enabling early terminating for efficacy as well as futility. In addition to the clinically uninteresting and interesting response rate, a prior distribution of response rate, the minimum posterior threshold probabilities and the lengths of the highest posterior density intervals were specified in the design. Finally, we defined the feasible design with the highest total effective predictive probability. We studied the properties of the proposed design and applied it to an oncology trial as an example. The proposed design ensured that the observed response rate fell within prespecified levels of posterior probability. The proposed design provides an alternative design to single-arm two-stage trials.

Ecomorphology of the tarsometatarsus of waterfowl (Anseriformes) based on geometric morphometrics and its application to fossils.

Anseriformes is a diverse group of birds that comprises screamers, the Magpie Goose, and swans ducks and geese, with a relatively rich fossil record. Waterfowl live in close relation to water bodies, but show a diversity of locomotory habits, being typically categorized as walkers, dabblers, and divers. Owing to its functional significance and high preservation potential, the tarsometatarsus has been considered to be a "key" element upon which to base ecomorphological inferences in fossil waterfowl. For instance, based on features of the tarsometatarsus the Miocene flightless duck Cayaoa bruneti and the Oligocene-Miocene large waterfowl Paranyroca have been inferred as divers. Herein, we use a geometric morphometric approach and comparative methods to assess the phylogenetic and ecomorphological signals in the shape and size of waterfowl tarsometatarsi in relation to their locomotory habits. We also apply phylogenetic flexible discriminant analysis (pFDA) to test the inferred diving habits in the extinct waterfowl Cayaoa and Paranyroca. Extant waterfowl species are largely distributed according to their locomotory habit along the main axis of variation in the shape space, a pattern mirrored by the phylogenetic generalized least squares model, which shows that a third of the shape variation is significantly explained by the habit. The pFDA reclassifies correctly almost all extant species and classified with high posterior probabilities the fossil Cayaoa and Paranyroca as a diver and as a dabbler, respectively. Our quantitative multivariate approach confirms the tarsometatarsus as a useful source of data upon which reliably assesses locomotory habits of fossil waterfowl.

Should angiogenic markers be included in diagnostic criteria of superimposed pre-eclampsia in women with chronic hypertension?

Although the most recent guidance from the International Society for the Study of Hypertension in Pregnancy (ISSHP) has highlighted the role of angiogenic marker assessment in the diagnosis of pre-eclampsia (PE) in women with chronic hypertension, the ISSHP has withheld recommending its implementation due to the limited available evidence in this group of women. Therefore, we aimed to investigate the value of soluble fms-like tyrosine kinase-1 (sFlt-1) and placental growth factor (PlGF) assessment in women with chronic hypertension and suspected superimposed PE. This was a retrospective analysis of prospectively collected data recorded in an electronic database between January 2013 and October 2019. Women with chronic hypertension and singleton pregnancy who had suspected superimposed PE were included. Superimposed PE was suspected in women presenting with worsening hypertension, epigastric pain, new-onset edema, dyspnea or neurological symptoms. The exclusion criteria were delivery within 1 week after assessment for reasons other than PE, chronic kidney disease, history of cardiac disease, fetal aneuploidy, genetic syndrome or major structural anomaly and missing pregnancy outcome. Maternal serum angiogenic markers (sFlt-1, PlGF and sFlt-1/PlGF ratio) were measured. The primary outcome was the utility of angiogenic markers in the prediction of superimposed PE. Predictive accuracy was assessed for superimposed PE diagnosed at different timepoints, including within 1 week after assessment and any time before birth. The secondary outcome was comparison of adverse maternal and perinatal outcomes between women with superimposed PE diagnosed according to the traditional ISSHP criteria and those diagnosed according to extended criteria including angiogenic markers. The predictive accuracy of each angiogenic marker was assessed using receiver-operating-characteristics-curve analysis. Area under the curve (AUC) values were compared using De Long's test. A sensitivity analysis was planned for gestational age at assessment. The association of various variables with composite adverse maternal and perinatal outcomes was assessed using binomial regression. The study included 142 pregnant women with chronic hypertension and suspected superimposed PE, of whom 25 (17.6%) developed PE within 1 week after assessment, 52 (36.6%) developed PE at any timepoint before birth and 90 (63.4%) delivered without PE. Maternal serum angiogenic imbalance was associated significantly with superimposed PE diagnosed according to the ISSHP criteria within 1 week or at any time after assessment (P < 0.001 for both). The predictive accuracy of maternal serum sFlt-1/PlGF ratio for superimposed PE diagnosed within 1 week after assessment was superior to that of maternal serum PlGF level (AUC, 0.91 vs 0.86; P = 0.032). The addition of angiogenic imbalance to the traditional ISSHP diagnostic criteria was associated with an increase in the detection rate (35.1% increase; 95% credible interval (CrI), 16.6-53.6%) and positive (9.6% increase; 95% CrI, 0.0-20.6%) and negative (3.1% increase; 95% CrI, 1.3-4.9%) predictive values for composite adverse maternal outcome, with high posterior probabilities of an increase in each predictive accuracy parameter (> 99.9%, 95.6% and > 99.9%, respectively), without a meaningful decrease in specificity. The addition of angiogenic imbalance improved the detection rate for composite adverse perinatal outcome (20.6% increase; 95% CrI, 0.0-42.2%), with a high posterior probability (96.9%). There was a corresponding drop in specificity (5.7% decrease; 95% CrI, -2.3% to 13.6%), with a posterior probability of 91.8%. In women with chronic hypertension and suspected superimposed PE, addition of maternal serum angiogenic markers to the traditional diagnostic criteria for superimposed PE improved significantly the sensitivity for the prediction of both maternal and perinatal adverse outcomes. Implementation of angiogenic marker assessment in the evaluation of pregnant women with chronic hypertension should therefore be considered. © 2021 International Society of Ultrasound in Obstetrics and Gynecology.

The complete mitochondrial genome of an endemic cichlid Etroplus canarensis from Western Ghats, India (Perciformes: Cichlidae) and molecular phylogenetic analysis.

The Indian endemic cichlid Etroplus canarensis (Canara pearl spot) is an endangered fish and is one among the three Indian cichlids (Etroplinae) that had a restricted distribution in the South Canara region of Karnataka, India. Despite considerable investigations, the phylogeny of Indian Cichlids and its biogeographical origin is still ambiguous and remains a question under discussion which is scrutinized based on whole mitogenomes in the present study. We report the 16,339bp complete mitochondrial genome of E. canarensis for the first time using the next-generation sequencing methods. Comparison of gene arrangement and genome characterization was found to commensurate with the previous reports on two Indian cichlid fishes, E. suratensis and E. maculatus. ND6 has been identified as a gene with the highest evolutionary rate and COI and COII is the most conserved gene based on p-genetic distance calculation. Substitution rate (ka/ks) was found to be very low indicating a reduced rate of evolution among subfamily Etroplinae accounting for its subsided species divergence of Indian cichlids. Phylogenetic analysis of Indian cichlids based on a combined dataset of 12 protein-coding genes representing cichlids generated high posterior probability values pillaring paraphyletic nature of Indian Malagasy lineage and monophyletic Indian genus Etroplus. The mitogenome sequence of E. canarensis may provide fundamental molecular data useful for further researches on genetic diversity, endemicity and the conservation of this endangered freshwater fish.

Hidden Diversity in a Narrow Valley: Description of New Endemic Palearctic Rock Lizard Darevskia (Squamata: Lacertidae) Species from Northeastern Turkey.

Darevskia is a particularly species-rich radiation of Palearctic rock lizards from the Caucasus region. Thanks to intense systematic and taxonomic research, the knowledge of species-level diversity within this genus has increased over the last quarter century. Here, we described a new species, Darevskia salihae sp. nov. from northeastern Turkey. The new taxon is differentiated from other nearby taxon by the low number of dorsal scales in the middle of the body, the shorter body length, and the absence of blue dots both on the lateral region above the forelimbs and on the margin of the ventral plates. In addition to their morphological differences, the new taxon is phylogenetically different from close groups. It is located in a separate subclade from the rudis-valentini-portschinskii subclade. This distinction is supported by both a high bootstrap value (100) and a high posterior probability value (1.00). These two subclades are separated from each other by a genetic distance of almost 4%. This separation is supported not only genetically and morphologically, but also geographically. Since the habitat of the new taxon is limited to a high mountain and a narrow valley, it does not provide an opportunity for a different Darevskia species to shelter because it creates geographical isolation. However, Darevskia parvula that live closest to the habitat of the new taxon live only at the habitat boundaries and do not enter areas where the new taxon is found. Therefore, it might be possible that while it was separated from the rudis-valentini-portschinskii group during the evolutionary transformation, it remained as a refuge and relict in a narrow area as a result of the collapse of the valleys and the partial uplift of the Kaçkar Mountains.