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The asymmetric synthesis of 2,2-difluorinated tetrahydrofurans was accomplished via enantioselective formal [3+2] cycloaddition catalyzed by palladium. The asymmetric reaction between gem-difluoroalkenes and racemic vinyl epoxides or vinylethylene carbonates resulted in the formation of enantioenriched 2,2-difluorotetrahydrofurans with an enantioselectivity up to 98 %. Notably, the reaction used the readily available (R)-BINAP as the ligand at a low loading and yielded a wide variety of difluorinated products in moderate to high yields. Both chiral diastereomers could be obtained in a single sequence.

Banana cultivars of agronomic interest have been genetically characterized using two different molecular markers. On the one hand, a panel of 14 trinucleotide single sequence repeats (SSRs or microsatellites) was optimized for homogeneous PCR conditions. It was tested with 50 individuals from seven cultivars, yielding 76 alleles and 5.4 ± 1.8 alleles per locus, while the presence of cultivar-exclusive alleles allowed the discrimination of all cultivars. On the other hand, a retrotransposon-based marker system named inter-primer binding site (iPBS) was implemented for the first time in the Musa genus. A total of 120 bands were detected in eight different Musa cultivars, from which 65.8% were polymorphic and 23.3% were cultivar exclusive. Both techniques allowed a cut-off identification of all cultivars studied, but overall, iPBS analysis was a more straightforward and economical choice. Despite the fact that we were unable to distinguish local banana varieties belonging to the same cultivar, new cultivar-specific molecular markers have been developed for the Musa genus, which could be used to guide new breeding programmes and maintain high quality of Plátano de Canarias., This work has been supported by a contract research (FGULL 17120006) from Fundación General Universidad de La Laguna.

Objectives The Prostate Imaging Quality (PI-QUAL) score assesses the quality of multiparametric MRI (mpMRI). A score of 1 means all sequences are below the minimum standard of diagnostic quality, 3 implies that the scan is of sufficient diagnostic quality, and 5 means that all three sequences are of optimal diagnostic quality. We investigated the inter-reader reproducibility of the PI-QUAL score in patients enrolled in the NeuroSAFE PROOF trial. Methods We analysed the scans of 103 patients on different MR systems and vendors from 12 different hospitals. Two dedicated radiologists highly experienced in prostate mpMRI independently assessed the PI-QUAL score for each scan. Interobserver agreement was assessed using Cohen’s kappa with standard quadratic weighting (κw) and percent agreement. Results The agreement for each single PI-QUAL score was strong (κw = 0.85 and percent agreement = 84%). A similar agreement (κw = 0.82 and percent agreement = 84%) was observed when the scans were clustered into three groups (PI-QUAL 1–2 vs PI-QUAL 3 vs PI-QUAL 4–5). The agreement in terms of diagnostic quality for each single sequence was highest for T2-weighted imaging (92/103 scans; 89%), followed by dynamic contrast-enhanced sequences (91/103; 88%) and diffusion-weighted imaging (80/103; 78%). Conclusion We observed strong reproducibility in the assessment of PI-QUAL between two radiologists with high expertise in prostate mpMRI. At present, PI-QUAL offers clinicians the only available tool for evaluating and reporting the quality of prostate mpMRI in a systematic manner but further refinements of this scoring system are warranted. Key Points • Inter-reader agreement for each single Prostate Imaging Quality (PI-QUAL) score (i.e., PI-QUAL 1 to PI-QUAL 5) was strong, with weighted kappa = 0.85 (95% confidence intervals: 0.51 – 1) and percent agreement = 84%. • Interobserver agreement was strong when the scans were clustered into three groups according to the ability (or not) to rule in and to rule out clinically significant prostate cancer (i.e., PI-QUAL 1-2 vs PI-QUAL 3 vs PI-QUAL 4–5), with weighted kappa = 0.82 (95% confidence intervals: 0.68 – 0.96) and percent agreement = 84%. • T2-weighted acquisitions were the most compliant with the Prostate Imaging Reporting and Data System (PI-RADS) v. 2.0 technical recommendations and were the sequences of highest diagnostic quality for both readers in 95/103 (92%) scans, followed by dynamic contrast enhanced acquisition with 81/103 (79%) scans and lastly by diffusion-weighted imaging with 79/103 (77%) scans.

In solid-phase oligonucleotide synthesis, a single oligonucleotide is generally acquired from a column loaded with a specific solid support. Herein, we have developed new cleavable spacer (CS) derivatives for tandem synthesis of multiple oligonucleotides on a single column­. Four CS analogues were designed, synthesized, and inserted between two oligonucleotide sequences using an automated oligonucleotide synthesizer. The CS derivatives bearing a cyclic cis-1,2-diol exhibited efficient release of the two oligonucleotides under commonly employed basic conditions of aqueous ammonia. Among the CS analogues, it was found that CS with a robust structure can potentially be applied as a spacer molecule in the tandem synthesis of multiple oligonucleotides in a single sequence.

Motivation RNA solvent accessibility, similar to protein solvent accessibility, reflects the structural regions that are accessible to solvents or other functional biomolecules, and plays an important role for structural and functional characterization. Unlike protein solvent accessibility, only a few tools are available for predicting RNA solvent accessibility despite the fact that millions of RNA transcripts have unknown structures and functions. Also, these tools have limited accuracy. Here, we have developed RNAsnap2 that uses a dilated convolutional neural network with a new feature, based on predicted base-pairing probabilities from LinearPartition. Results Using the same training set from the recent predictor RNAsol, RNAsnap2 provides an 11% improvement in median Pearson Correlation Coefficient (PCC) and 9% improvement in mean absolute errors for the same test set of 45 RNA chains. A larger improvement (22% in median PCC) is observed for 31 newly deposited RNA chains that are non-redundant and independent from the training and the test sets. A single-sequence version of RNAsnap2 (i.e. without using sequence profiles generated from homology search by Infernal) has achieved comparable performance to the profile-based RNAsol. In addition, RNAsnap2 has achieved comparable performance for protein-bound and protein-free RNAs. Both RNAsnap2 and RNAsnap2 (SingleSeq) are expected to be useful for searching structural signatures and locating functional regions of non-coding RNAs. Availability and implementation Standalone-versions of RNAsnap2 and RNAsnap2 (SingleSeq) are available at https://github.com/jaswindersingh2/RNAsnap2. Direct prediction can also be made at https://sparks-lab.org/server/rnasnap2. The datasets used in this research can also be downloaded from the GITHUB and the webserver mentioned above. Supplementary information Supplementary data are available at Bioinformatics online.

Purpose To propose a highly time-efficient imaging technique named improved simultaneous noncontrast angiography and intraplaque hemorrhage (iSNAP) for simultaneous assessment of lumen, vessel wall, and blood flow in intracranial arteries. Methods iSNAP consists of pulsed arterial spin labeling preparations and 3D golden angle radial acquisition. Images were reconstructed by k-space weighted image contrast (KWIC) method with optimized data-sharing strategies. Dynamic MRA for blood flow assessment was obtained from iSNAP by reconstruction at multiple inversion times and image subtraction, static MRA by both image subtraction approach and phase-sensitive inversion recovery technique, and vessel wall images by both reconstruction at zero-crossing time-point of blood and phase-sensitive inversion recovery. A T1 -weighted brain MRI was also reconstructed from iSNAP. Preliminary comparison of iSNAP against the dedicated dynamic MRA sequence 4D-TRANCE, MRA/vessel wall imaging sequence SNAP, and vessel wall imaging sequence T1 -weighted VISTA was performed in healthy volunteers and patients. Results iSNAP has whole-brain coverage and takes ~6.5 min. The dedicated reconstruction strategies are feasible for each iSNAP image contrast and beneficial for image SNR. iSNAP-dynamic MRA yields similar dynamic flow information as 4D-TRANCE and allows more flexible temporal resolution. The 2 types of iSNAP static MRA images complement each other in characterizing both proximal large arteries and distal small arteries. Depiction of vessel wall lesions in iSNAP vessel wall images is better than SNAP and may be similar to T1 -weighted VISTA, although the images are slightly blurred. Conclusion iSNAP provides a time-efficient evaluation of intracranial arteries and may have great potential for comprehensive assessment of intracranial vascular conditions using a single sequence.

Measuring genome size across different species can yield important insights into evolution of the genome and allow for more informed decisions when designing next-generation genomic sequencing projects. New techniques for estimating genome size using shallow genomic sequence data have emerged which have the potential to augment our knowledge of genome sizes, yet these methods have only been used in a limited number of empirical studies. In this project, we compare estimation methods using next-generation sequencing (k-mer methods and average read depth of single-copy genes) to measurements from flow cytometry, the gold standard for genome size measures, using ground beetles (Carabidae) and other members of the beetle suborder Adephaga as our test system. We also present a new protocol for using read-depth of single-copy genes to estimate genome size. Additionally, we report flow cytometry measurements for five previously unmeasured carabid species, as well as 21 new draft genomes and six new draft transcriptomes across eight species of adephagan beetles. No single sequence-based method performed well on all species, and all tended to underestimate the genome sizes, although only slightly in most samples. For one species,Bembidion haplogonum, most sequence-based methods yielded estimates half the size suggested by flow cytometry. This discrepancy for k-mer methods can be explained by a large number of repetitive sequences, but we have no explanation for why read-depth methods yielded results that were also strikingly low.

Motivation After the outstanding breakthrough of AlphaFold in predicting protein 3D models, new questions appeared and remain unanswered. The ensemble nature of proteins, for example, challenges the structural prediction methods because the models should represent a set of conformers instead of single structures. The evolutionary and structural features captured by effective deep learning techniques may unveil the information to generate several diverse conformations from a single sequence. Here, we address the performance of AlphaFold2 predictions obtained through ColabFold under this ensemble paradigm. Results Using a curated collection of apo–holo pairs of conformers, we found that AlphaFold2 predicts the holo form of a protein in ∼70% of the cases, being unable to reproduce the observed conformational diversity with the same error for both conformers. More importantly, we found that AlphaFold2's performance worsens with the increasing conformational diversity of the studied protein. This impairment is related to the heterogeneity in the degree of conformational diversity found between different members of the homologous family of the protein under study. Finally, we found that main-chain flexibility associated with apo–holo pairs of conformers negatively correlates with the predicted local model quality score plDDT, indicating that plDDT values in a single 3D model could be used to infer local conformational changes linked to ligand binding transitions. Availability and implementation Data and code used in this manuscript are publicly available at https://gitlab.com/sbgunq/publications/af2confdiv-oct2021. Supplementary information Supplementary data are available at Bioinformatics online.

Background Synthetic magnetic resonance imaging (MRI), which can generate multiple morphologic MR images as well as quantitative maps from a single sequence, is not widely used in the spine at 3.0 T. Purpose To investigate the feasibility of synthetic MRI of the lumbar spine in clinical practice at 3.0 T. Material and Methods Eighty-four patients with lumbar diseases underwent conventional T1-weighted images, T2-weighted images, short-tau inversion recovery (STIR) images, and synthetic MRI of the lumbar spine at 3.0 T. The quantitative and qualitative image quality and agreement for detection of spinal lesions between conventional and synthetic MRI were compared by two radiologists. Results The signal-to-noise ratios of synthetic MRI showed an inferior image quality in the vertebrae and disc, whereas were higher for spinal canal and fat on the synthetic T1-weighted, T2-weighted, and STIR images. The contrast-to-noise ratios of the synthetic MRI was superior to conventional sequences, except for the vertebrae–disc contrast-to-noise ratio on T1-weighted imaging ( P = 0.005). Image quality assessments showed that synthetic MRI had greater STIR fat suppression ( P < 0.001) and fluid brightness ( P = 0.014), as well as higher degree of artifacts ( P < 0.001) and worse spatial resolution ( P = 0.002). The inter-method agreements for detection of spinal lesions were substantial to perfect (kappa, 0.614–0.925). Conclusion Synthetic MRI is a feasible method for lumbar spine imaging in a clinical setting at 3.0-T MR. It provides morphologic sequences with acceptable image quality, good agreement with conventional MRI for detection of spinal lesions and quantitative image maps with a slightly shorter acquisition time compared with conventional MRI.

A turtle releasing device (TRD) can reduce the mortality of bycatch in setnets. Turtles that have entered the submerged bag net of setnets repeatedly push their heads up against the ceiling net (referred to here as a push‐up) in an effort to ascend to breathe. To aid the successful escape of turtles from the setnet, it is essential to understand the turtle's push‐up behaviour, as they need to reach the TRD and open its flap door. The objectives of this study were to clarify when turtles start to perform push‐ups, how these push‐ups change, and what factors affect push‐ups under the simulated condition of bycatch. A depth, temperature, and tri‐axial acceleration data logger and a video camera were employed to determine vertical movement, ambient temperature, the level of activity, and flipper beat frequency (FBF) of the turtles. Ten trials of 10–30 minutes for five subadult loggerhead turtles (Caretta caretta) were conducted using a submerged bag net (30 × 10 × 10 m) of a setnet in Mie Prefecture, Japan. Turtles started to perform push‐ups 5.1 ± 3.3 minutes after the start of each trial. FBF increased as more time elapsed in 35% of ascent phases recorded, and the level of activity during the following push‐ups was significantly higher than during other push‐ups. The level of activity in each sequence of push‐ups increased as more time elapsed; however, it started to decrease from 9.8 minutes after the first push‐up at the earliest. Therefore, the TRD should be designed to enable turtles to escape within approximately 10 minutes. The number of push‐ups in a single sequence, the activity level, and FBF were affected by water temperature. Therefore, the closing force of the TRD flap door needs to be changed according to the different seasons and regions.

Many methods exist for detecting introgression between non-sister species, but the most commonly used require either a single sequence from four or more taxa or multiple sequences from each of three taxa. Here we present a test for introgression that uses only a single sequence from three taxa. This test, denoted D3, uses similar logic as the standard D-test for introgression, but by using pairwise distances instead of site patterns it is able to detect the same signal of introgression with fewer species. We use simulations to show that D3 has statistical power almost equal to D, demonstrating its use on a dataset of wild bananas (Musa). The new test is easy to apply and easy to interpret, and should find wide use among currently available datasets.

Background: We aimed to investigate whether pre-therapeutic radiomic features based on magnetic resonance imaging (MRI) can predict the clinical response to neoadjuvant chemotherapy (NACT) in patients with locally advanced cervical cancer (LACC). Methods: A total of 275 patients with LACC receiving NACT were enrolled in this study from eight hospitals, and allocated to primary and independent validation cohorts (2:1 ratio). Three radiomic feature sets were extracted from the intratumoural region of T1-weighted images, intratumoural region of T2-weighted images, and peritumoural region of T2-weighted images before NACT for each patient. With a feature selection strategy, three single sequence radiomic models were constructed, and three additional combined models were constructed by combining the features of different regions or sequences. The performance of all models was assessed using receiver operating characteristic curve. Findings: The combined model of the intratumoural zone of T1-weighted images, intratumoural zone of T2-weighted images ,and peritumoural zone of T2-weighted images achieved an AUC of 0.998 in primary cohort and 0.999 in validation cohort, which was significantly better (p

Purpose MR fingerprinting (MRF) sequences permit efficient T1 and T2 estimation in cranial and extracranial regions, but these areas may include substantial fat signals that bias T1 and T2 estimates. MRI fat signal fraction estimation is also a topic of active research in itself, but may be complicated by B0 heterogeneity and blurring during spiral k-space acquisitions, which are commonly used for MRF. An MRF method is proposed that separates fat and water signals, estimates water T1 and T2, and accounts for B0 effects with spiral blurring correction, in a single sequence. Theory and methods A k-space-based fat-water separation method is further extended to unbalanced steady-state free precession MRF with swept echo time. Repeated application of this k-space fat-water separation to demodulated forms of the measured data allows a B0 map and correction to be approximated. The method is compared with MRF without fat separation across a broad range of fat signal fractions (FSFs), water T1s and T2s, and under heterogeneous static fields in simulations, phantoms, and in vivo. Results The proposed method's FSF estimates had a concordance correlation coefficient of 0.990 with conventional measurements, and reduced biases in the T1 and T2 estimates due to fat signal relative to other MRF sequences by several hundred ms. The B0 correction improved the FSF, T1, and T2 estimation compared to those estimates without correction. Conclusion The proposed method improves MRF water T1 and T2 estimation in the presence of fat and provides accurate FSF estimation with inline B0 correction.

Objectives To construct MRI-based radiomics logistic model in differentiating solid pseudopapillary neoplasm (SPN) from three differential diseases containing adenocarcinoma, neuroendocrine tumor (NET), and cystadenoma of pancreas. Materials and methods A total of 21 SPNs and 140 differential diseases were enrolled. The MRI images of T1WI, T2WI, DWI, and contrast-enhanced (CE) sequences were taken to delineate the volume of interest, and the corresponding radiomics features were calculated. After the preprocess of data balance and image standardize, the data was divided into training set (6 SPNs and 42 differential diseases) and validation set (15 SPNs and 98 differential diseases) with a proportion of 7:3, randomly. Then after feature selection, four MRI-based logistic models included T1WI, T2WI, DWI, CE, and sum logistic models (Log-T1WI, Log-T2WI, Log-DWI, Log-CE, and Log-sum) were established. The receiver operation curve (ROC) was depicted to evaluate the efficacy of each model. Results To the single MRI sequence, the AUCs of Log-T1WI, Log-T2WI, Log-DWI, and Log-CE were similar. Seemingly the AUCs of Log-T2WI were slightly higher with 0. 876 (95%CI, 0.797-0.956) in the training set and 0.853 (95%CI, 0.708-0.998) in the validation set. The Log-sum of four MRI sequences displayed better differentiating efficiency, with AUCs of 0.929 (95%CI, 0.877-0.980) in the training set and 0.925 (95%CI, 0.845-1.000) in the validation set. The Log-Ra/Clin model combined clinical information and radiomics showed the highest AUC of 0.962 (95%CI, 0.919-0.985). Conclusions MRI-based radiomics analysis helped to discern SPNs from radiologically misdiagnosed adenocarcinoma, neuroendocrine tumor, and cystadenoma of pancreas. The efficacy of single sequence logistic model was similar. The Log-sum combined four sequences and Log-Ra/Clin combined clinical information and radiomics demonstrated the better performance in distinction.

MotivationAccurate prediction of protein contact-map is essential for accurate protein structure and function prediction. As a result, many methods have been developed for protein contact map prediction. However, most methods rely on protein-sequence-evolutionary information, which may not exist for many proteins due to lack of naturally occurring homologous sequences. Moreover, generating evolutionary profiles is computationally intensive. Here, we developed a contact-map predictor utilizing the output of a pre-trained language model ESM-1b as an input along with a large training set and an ensemble of residual neural networks.ResultsWe showed that the proposed method makes a significant improvement over a single-sequence-based predictor SSCpred with 15% improvement in the F1-score for the independent CASP14-FM test set. It also outperforms evolutionary-profile-based methods TrRosetta and SPOT-Contact with 48.7% and 48.5% respective improvement in the F1-score on the proteins without homologs (Neff=1) in the independent SPOT-2018 set. The new method provides a much faster and reasonably accurate alternative to evolution-based methods, useful for large-scale prediction.AvailabilityStand-alone-version of SPOT-Contact-Single is available at https://github.com/jas-preet/SPOT-Contact-Single. Direct prediction can also be made at https://sparks-lab.org/server/spot-contact-single. The datasets used in this research can also be downloaded from the GitHub.Contactjaspreetsingh2@griffithuni.edu.au, k.paliwal@griffith.edu.au, and zhouyq@szbl.ac.cnSupplementary informationSupplementary data are available at Bioinformatics online.

Inertial navigation is a crucial part of vehicle navigation systems in complex and covert surroundings. To address the low accuracy of vehicle inertial navigation in multifaced and covert surroundings, in this study, we proposed an inertial navigation error estimation based on an adaptive neuro fuzzy inference system (ANFIS) which can quickly and accurately output the position error of a vehicle end-to-end. The new system was tested using both single-sequence and multi-sequence data collected from a vehicle by the KITTI dataset. The results were compared with an inertial navigation system (INS) position solution method, artificial neural networks (ANNs) method, and a long short-term memory (LSTM) method. Test results indicated that the accumulative position errors in single sequence and multi-sequences experiments decreased from 9.83% and 4.14% to 0.45% and 0.61% by using ANFIS, respectively, which were significantly less than those of the other three approaches. This result suggests that the ANFIS can considerably improve the positioning accuracy of inertial navigation, which has significance for vehicle inertial navigation in complex and covert surroundings.

Our objectives were to evaluate general and specific combining ability (SCA) and genetic divergence among tropical maize inbred lines using single sequence repeat (SSR) markers. Thirteen inbred lines were crossed based on a complete diallel scheme. Hybrids and three checks were evaluated in a lattice experimental design. Silk and anthesis flowering, average plant height, average ear height, white spot (Pantoea ananatis) and gray leaf spot (Cercospora zeae-maydis) severity, and grain yield were evaluated. Significant differences (p < 0.05) for general and specific combining abilities were observed for all traits. Based on additive effects, inbred lines 1 (Flash) and 12 (SG 6015) were selected to reduce the flowering period and plant and ear height. Inbred lines 2 (CD 303) and 3 (AG 8080) were selected to reduce disease severity. For the simultaneous increase in grain yield and reduced severity of diseases, line 11 (AG 9090) as a parent or tester in topcross schemes is recommended. According to non-additive effects, crosses 2 (CD 303) × 13 (DKB 747) and 11 (AG 9090) × 12 (SG 6015) were selected for grain yield and future breeding programs. Six groups were identified using SSR markers; a major group contained six inbred lines. Because of the minor relationship between genetic divergence and SCA effects on grain yield limits, the use of the groups for future divergent crosses is recommended. Our objectives were to evaluate general and specific combining ability (SCA) and genetic divergence among tropical maize inbred lines using single sequence repeat (SSR) markers. Thirteen inbred lines were crossed based on a complete diallel scheme. Hybrids and three checks were evaluated in a lattice experimental design. Silk and anthesis flowering, average plant height, average ear height, white spot (Pantoea ananatis) and gray leaf spot (Cercospora zeae-maydis) severity, and grain yield were evaluated. Significant differences (p < 0.05) for general and specific combining abilities were observed for all traits. Based on additive effects, inbred lines 1 (Flash) and 12 (SG 6015) were selected to reduce the flowering period and plant and ear height. Inbred lines 2 (CD 303) and 3 (AG 8080) were selected to reduce disease severity. For the simultaneous increase in grain yield and reduced severity of diseases, line 11 (AG 9090) as a parent or tester in topcross schemes is recommended. According to non-additive effects, crosses 2 (CD 303) × 13 (DKB 747) and 11 (AG 9090) × 12 (SG 6015) were selected for grain yield and future breeding programs. Six groups were identified using SSR markers; a major group contained six inbred lines. Because of the minor relationship between genetic divergence and SCA effects on grain yield limits, the use of the groups for future divergent crosses is recommended.

Prior radiomics studies have focused on two-class brain tumor classification, which limits generalizability. The performance of radiomics in differentiating the three most common malignant brain tumors (glioblastoma (GBM), primary central nervous system lymphoma (PCNSL), and metastatic disease) is assessed, factors affecting the model performance and usefulness of a single sequence versus multiparametric MRI (MP-MRI) remain largely unaddressed. This retrospective study included 253 patients (120 metastatic (lung and brain), 40 PCNSL, and 93 GBM). Radiomic features were extracted for whole a tumor mask (enhancing plus necrotic) and an edema mask (first pipeline), as well as for separate enhancing and necrotic and edema masks (second pipeline). Model performance was evaluated using MP-MRI, individual sequences, and the T1 contrast enhanced (T1-CE) sequence without the edema mask across 45 model/feature selection combinations. The second pipeline showed significantly high performance across all combinations (Brier score: 0.311–0.325). GBRM fit using the full feature set from the T1-CE sequence was the best model. The majority of the top models were built using a full feature set and inbuilt feature selection. No significant difference was seen between the top-performing models for MP-MRI (AUC 0.910) and T1-CE sequence with (AUC 0.908) and without edema masks (AUC 0.894). T1-CE is the single best sequence with comparable performance to that of multiparametric MRI (MP-MRI). Model performance varies based on tumor subregion and the combination of model/feature selection methods.

Red clover (Trifolium pratense L.) is a globally significant legume having economic value as a forage and green manure crop in temperate agricultural zones. Based on the gametophytic self-incompatibility system, and analysis of seed set rates between self and cross pollination, the clover has long been considered an outcrossing species. However, the outcrossing rates of red clover under open-pollination conditions are not definitive. Development of a reliable, timesaving, and easily usable marker system is needed to quantify and characterize rates of red clover crossing and selfing. Here, genome-wide screening of 209 mapped simple sequence repeat (SSR) markers was conducted, and 185 produced clear scorable bands on a pooled DNA sample of 20 red clover accessions. Seventy markers were selected based on polymerase chain reaction (PCR) amplification quality on 24 genotypes and their relatively even distribution in red clover genome. Mean polymorphic information content for the 70 markers was 0.490, ranging from 0.117 to 0.878. From the markers, a core set of 24 loci, which had been mapped on six linkage groups, was further tested to develop 12 sets of duplex markers. Using the established duplex PCR protocol, 10 out of 12 sets of duplex SSR markers were used to genotype 60 maternal parents and their respective 22 half-sib progenies. Eight plants among the 1,320 progenies were identified to be selfed, indicating that the outcrossing rate was 99.4% in a natural environment. The protocol and the finding of this rare selfing strategy under open-pollinating conditions contribute to red clover breeding efforts.

Motivation Over the past 50 years, our ability to model protein sequences with evolutionary information has progressed in leaps and bounds. However, even with the latest deep learning methods, the modelling of a critically important class of proteins, single orphan sequences, remains unsolved. Results By taking a bioinformatics approach to semi-supervised machine learning, we develop Profile Augmentation of Single Sequences (PASS), a simple but powerful framework for building accurate single-sequence methods. To demonstrate the effectiveness of PASS we apply it to the mature field of secondary structure prediction. In doing so we develop S4PRED, the successor to the open-source PSIPRED-Single method, which achieves an unprecedented Q3 score of 75.3% on the standard CB513 test. PASS provides a blueprint for the development of a new generation of predictive methods, advancing our ability to model individual protein sequences. Availability and implementation The S4PRED model is available as open source software on the PSIPRED GitHub repository (https://github.com/psipred/s4pred), along with documentation. It will also be provided as a part of the PSIPRED web service (http://bioinf.cs.ucl.ac.uk/psipred/). Supplementary information Supplementary data are available at Bioinformatics online.

The short and similar sized chromosomes of Acropora pose a challenge for karyotyping. Conventional methods, such as staining of heterochromatic regions, provide unclear banding patterns that hamper identification of such chromosomes. In this study, we used short single-sequence probes for tandemly repetitive 5S ribosomal RNA (rRNA) and core histone genes to identify specific chromosomes of Acropora pruinosa. Both the probes produced intense signals in fluorescence in situ hybridization, which distinguished chromosome pairs. The locus of the core histone gene was on chromosome 8, whereas that of 5S rRNA gene was on chromosome 5. The sequence of the 5S rRNA probe was composed largely of U1 and U2 spliceosomal small nuclear RNA (snRNA) genes and their interspacers, flanked by short sequences of the 5S rRNA gene. This is the first report of a tandemly repetitive linkage of snRNA and 5S rRNA genes in Cnidaria. Based on the constructed tentative karyogram and whole genome hybridization, the longest chromosome pair (chromosome 1) was heteromorphic. The probes also hybridized effectively with chromosomes of other Acropora species and population, revealing an additional core histone gene locus. We demonstrated the applicability of short-sequence probes as chromosomal markers with potential for use across populations and species of Acropora.

Previous work on dialogue-specific ellipsis and coreference resolution usually concatenates all dialogue history utterances into a single sequence. It may mislead the model to attend to inappropriate parts and to copy from wrong utterances when the dialogue history is long. In this paper, we aim to model dialogue history from multiple granularities and take a deep look into the semantic connection between the dialogue history and the omitted or coreferred expressions. To achieve this, we propose a speaker highlight dialogue history encoder and a top-down hierarchical copy mechanism to generate the complete utterances. We conduct dozens of experiments on the CamRest676 dataset, and the experimental results show that our methods are expert in long-distance dialogue history modeling and can significantly improve the performance of ellipsis and coreference resolution in the dialogue task.

Comparative studies of the complete genome sequences of the phages of the Caudovirales revealed that the genomes are collections of genes with independent evolutionary histories; i.e., they are mosaics. Moreover, all phages have unequal access to a vast global pool of diverse viral genes, such that phage genomes share no single sequence or gene in common, and newly sequenced phages contain many genes with no discernable function or similarity to other genes in the global databases. Otherwise unrelated genomes may exhibit similar genome architectures, synteny of gene content, and rates of gene flux, these are influenced by virion morphology and lifestyle.

Purpose Fluid collections due to anastomotic leakage are a common complication after hepatopancreaticobiliary (HPB) surgery and are usually treated with drainage. We conducted a study to evaluate imaging work-up with a postoperative single-sequence (PoSSe) MRI for the detection of collections and indication of drainage. Material and methods Forty-six patients who developed signs of leakage (fever, pain, laboratory findings) after HPB surgery were prospectively enrolled. Each patient was examined by abdominal sonography and our PoSSe MRI protocol (axial T2-weighted HASTE only). PoSSe MRI examination time (from entering to leaving the MR scanner room) was measured. Sonography and MRI were evaluated regarding the detection and localization of fluid collections. Each examination was classified for diagnostic sufficiency and an imaging-based recommendation if CT-guided or endoscopic drainage is reasonable or not was proposed. Imaging work-up was evaluated in terms of feasibility and the possibility of drainage indication. Results Sonography, as first-line modality, detected 21 focal fluid collections and allowed to decide about the need for drainage in 41% of patients. The average time in the scanning room for PoSSe MRI was 9:23 min [7:50–13:32 min]. PoSSe MRI detected 46 focal collections and allowed therapeutic decisions in all patients. Drainage was suggested based on PoSSe MRI in 25 patients (54%) and subsequently indicated and performed in 21 patients (100% sensitivity and 84% specificity). No patient needed further imaging to optimize the treatment. Conclusions The PoSSe MRI approach is feasible in the early and intermediate postoperative setting after HPB surgery and shows a higher detection rate than sonography. Imaging work-up regarding drainage of collections was successful in all patients and our proposed PoSSe MRI algorithm provides an alternative to the standard work-up.

The nonstationary Poisson process (NSPP) is a workhorse tool for modeling and simulating arrival processes with time-dependent rates. In many applications only a single sequence of arrival times are observed. While one sample path is sufficient for estimating the arrival rate or integrated rate function of the process—as we illustrate in this paper—we show that testing for Poissonness, in the general case, is futile. In other words, when only a single sequence of arrival data are observed then one can fit an NSPP to it, but the choice of "NSPP" can only be justified by an understanding of the underlying process physics, or a leap of faith, not by testing the data. This result suggests the need for sensitivity analysis when such a model is used to generate arrivals in a simulation.

Wild relatives of domesticated Capsicum represent substantial genetic diversity and thus sources of traits of potential interest. Furthermore, the hybridization compatibility between members of Capsicum species complexes remains unresolved. Improving our understanding of the relationship between Capsicum species relatedness and their ability to form hybrids is a highly pertinent issue. Through the development of novel interspecific hybrids in this study, we demonstrate interspecies compatibility is not necessarily reflected in relatedness according to established Capsicum genepool complexes. Based on a phylogeny constructed by genotyping using single sequence repeat (SSR) markers and with a portion of the waxy locus, and through principal component analysis (PCA) of phenotypic data, we clarify the relationships among wild and domesticated Capsicum species. Together, the phylogeny and hybridization studies provide evidence for the misidentification of a number of species from the World Vegetable Center genebank included in this study. The World Vegetable Center holds the largest collection of Capsicum genetic material globally, therefore this may reflect a wider issue in the misidentification of Capsicum wild relatives. The findings presented here provide insight into an apparent disconnect between compatibility and relatedness in the Capsicum genus, which will be valuable in identifying candidates for future breeding programs.

Volume 63, no. 6, e02282-18, 2019, [https://doi.org/10.1128/AAC.02282-18][1]. In the originally published article, one institutional affiliation was missing for the first author. The corrected affiliation line is shown above. [1]: /lookup/doi/10.1128/AAC.02282-18

Purpose: Developing an MRI-based radiomics model to effectively and accurately predict the predominant histopathologic growth patterns (HGPs) of colorectal liver metastases (CRLMs). Materials and Methods: In this study, 182 resected and histopathological proven CRLMs of chemotherapy-naive patients from two institutions, including 123 replacement CRLMs and 59 desmoplastic CRLMs, were retrospectively analyzed. Radiomics analysis was performed on two regions of interest (ROI), the tumor zone and the tumor-liver interface (TLI) zone. Decision tree (DT) algorithm was used for radiomics modeling on each MR sequence, and fused radiomics model was constructed by combining the radiomics signature of each sequence. The clinical and combination models were developed through multivariate logistic regression method. The performance of the developed models was assessed by receiver operating characteristic (ROC) curves with indicators of area under curve (AUC), accuracy, sensitivity, and specificity. A nomogram was constructed to evaluate the discrimination, calibration, and usefulness. Results: The fused radiomicstumor and radiomicsTLI models showed better performance than any single sequence and clinical model. In addition, the radiomicsTLI model exhibited better performance than radiomicstumor model (AUC of 0.912 vs. 0.879) in internal validation cohort. The combination model showed good discrimination, and the AUC of nomogram was 0.971, 0.909, and 0.905 in the training, internal validation, and external validation cohorts, respectively. Conclusion: MRI-based radiomics method has high potential in predicting the predominant HGPs of CRLM. Preoperative non-invasive identification of predominant HGPs could further explore the ability of HGPs as a potential biomarker for clinical treatment strategy, reflecting different biological pathways.

There has been a significant improvement in protein residue contact prediction in recent years. Nevertheless, state-of-the-art methods still show deficiencies in the contact prediction of proteins with low-homology information. These top methods depend largely on statistical features that derived from homologous sequences, but previous studies, along with our analyses, show that they are insufficient for inferencing an accurate contact map for nonhomology protein targets. To compensate, we proposed a brand new single-sequence-based contact predictor (SSCpred) that performs prediction through the deep fully convolutional network (Deep FCN) with only the target sequence itself, i.e., without additional homology information. The proposed pipeline makes good use of the target sequence by utilizing the pair-wise encoding technique and Deep FCN. Experimental results demonstrated that SSCpred can produce accurate predictions based on the efficient pipeline. Compared with several most recent methods, SSCpred achieves completive performance on nonhomology targets. Overall, we explored the possibilities of single-sequence-based contact prediction and designed a novel pipeline without using a complex and redundant feature set. The proposed SSCpred can compensate for current methods' disadvantages and achieves better performance on the nonhomology targets. The web server of SSCpred is freely available at http://csbio.njust.edu.cn/bioinf/sscpred/.

Background Notwithstanding the efforts of direct-acting antivirals (DAAs) for the treatment of chronically infected hepatitis C virus (HCV) patients, concerns exist regarding the emergence of resistance-associated substitutions (RAS) related to therapy failure. Sanger sequencing is still the reference technique used for the detection of RAS and it detects viral variants present up to 15%, meaning that minority variants are undetectable, using this technique. To date, many studies are focused on the analysis of the impact of HCV low variants using next-generation sequencing (NGS) techniques, but the importance of these minority variants is still debated, and importantly, a common data analysis method is still not defined. Methods Serum samples from four patients failing DAAs therapy were collected at baseline and failure, and amplification of NS3, NS5A and NS5B genes was performed on each sample. The genes amplified were sequenced using Sanger and NGS Illumina sequencing and the data generated were analyzed with different approaches. Three different NGS data analysis methods, two homemade in silico pipeline and one commercially available certified user-friendly software, were used to detect low-level variants. Results The NGS approach allowed to infer also very-low level virus variants. Moreover, data processing allowed to generate high accuracy data which results in reduction in the error rates for each single sequence polymorphism. The results improved the detection of low-level viral variants in the HCV quasispecies of the analyzed patients, and in one patient a low-level RAS related to treatment failure was identified. Importantly, the results obtained from only two out of the three data analysis strategies were in complete agreement in terms of both detection and frequency of RAS. Conclusions These results highlight the need to find a robust NGS data analysis method to standardize NGS results for a better comprehension of the clinical role of low-level HCV variants. Based on the extreme importance of data analysis approaches for wet-data interpretation, a detailed description of the used pipelines and further standardization of the in silico analysis could allow increasing diagnostic laboratory networking to unleash true potentials of NGS.

Maize is seriously affected by different viruses like Maize Dwarf Mosaic Virus (MDMV) and Maize Chlorotic Dwarf Virus (MCDV) throughout the world. In Bangladesh, no genotype has been identified yet as a source of resistant gene against MDMV and MCDV. The study was carried out with the objective to screen nine maize genotypes carrying Wsm gene using three sets of Single Sequence Repeat (SSR) marker. Maize plants were inoculated with viruses. Symptoms were scored at 7, 10 and 14 dpi (days post inoculation) to calculate infection percentage and Area Under Disease Progress Curve (AUDPC). The molecular result indicated that BHM-7, BHM-5, V-92, Uttaran and Duranta carried Wsm gene, but according to pathological test, functional resistance was observed for only BHM-7, V-92 and Uttaran on the basis of infection percentage and AUDPC score. BHM-7 (BARI Hybrid Maize 7) was noticed as the best one for showing resistance against MDMV and carrying Wsm gene. No genotype was found to govern resistance against MCDV.J. Bangladesh Agril. Univ. 16(2): 208-214, August 2018

Massively parallel sequencing is transforming forensic work by allowing various useful forensic markers, such as STRPs and SNPs, to be multiplexed providing information on ancestry, individual and familial identification, phenotypes for eye/hair/skin pigmentation, and the deconvolution of mixtures. Microhaplotypes also become feasible with massively parallel sequencing, these are DNA segments (smaller than 300 nucleotides) that are selected to contain multiple SNPs unambiguously defining three or more haplotype alleles occurring at common frequencies. The physical extent of a microhaplotype can thus be covered by a single sequence read making these loci phase-known codominant genetic systems. Such microhaplotypes supply significantly more information than a single SNP can. Our efforts to develop useful sets of microhaplotypes have already identified 182 such loci that we have studied on a large number of human populations from around the world. We present various analyses on 83 populations in our ongoing study for a subset of the best microhaplotypes currently available illustrating their characteristics and potential utility for ancestry, identification, and mixture deconvolution.

Next-generation sequencing (NGS) is the method of choice when large numbers of sequences have to be obtained. While the technique is widely applied, varying error rates have been observed. We analysed millions of reads obtained after sequencing of one single sequence on an Illumina sequencer. According to our analysis, the index-PCR for sample preparation has no effect on the observed error rate, even though PCR is traditionally seen as one of the major contributors to enhanced error rates in NGS. In addition, we observed very persistent pre-phasing effects although the base calling software corrects for these. Removal of shortened sequences abolished these effects and allowed analysis of the actual mutations. The average error rate determined was 0.24 ± 0.06% per base and the percentage of mutated sequences was found to be 6.4 ± 1.24%. Constant regions at the 5′- and 3′-end, e.g., primer binding sites used in in vitro selection procedures seem to have no effect on mutation rates and re-sequencing of samples obtains very reproducible results. As phasing effects and other sequencing problems vary between equipment and individual setups, we recommend evaluation of error rates and types to all NGS-users to improve the quality and analysis of NGS data.

We highlight new evolutionary insights enabled by recent genome-wide studies on protein-protein interaction (PPI) networks ('interactomes'). While most PPIs are mediated by a single sequence region promoting or inhibiting interactions, many PPIs are mediated by multiple sequence regions acting cooperatively. Most PPIs perform important functions maintained by negative selection: we estimate that less than ∼10% of the human interactome is effectively neutral upon perturbation (i.e. 'junk' PPIs), and the rest are deleterious upon perturbation; interfacial sites evolve more slowly than other sites; many conserved PPIs show signatures of co-evolution at the interface; PPIs evolve more slowly than protein sequence. At the same time, many PPIs undergo rewiring during evolution for lineage-specific adaptation. Finally, chaperone-protein and host-pathogen interactomes are governed by distinct evolutionary principles.

Background The use of intraprostatic gold fiducial markers (FMs) ensures highly accurate and precise image-guided radiation therapy for patients diagnosed with prostate cancer thanks to the ease of localising FMs on photon-based imaging, like Computed Tomography (CT) images. Recently, Magnetic Resonance (MR)-only radiotherapy has been proposed to simplify the workflow and reduce possible systematic uncertainties. A critical, determining factor in the accuracy of such an MR-only simulation will be accurate FM localisation using solely MR images. Purpose The aim of this study is to evaluate the performances of manual MR-based FM localisation within a clinical environment. Methods We designed a study in which 5 clinically involved radiation therapy technicians (RTTs) independently localised the gold FMs implanted in 16 prostate cancer patients in two scenarios: employing a single MR sequence or a combination of sequences. Inter-observer precision and accuracy were assessed for the two scenarios for localisation in terms of 95% limit of agreement on single FMs (LoA)/ centre of mass (LoA CM) and inter-marker distances (IDs), respectively. Results The number of precisely located FMs (LoA

The Hebb repetition effect (i.e., the enhanced recall performance for a sequence of items that is repeated during a serial recall experiment) is considered an experimental analogue to language learning. However, although language learning occurs in a context in which multiple verbal sequences are repeated concurrently, the effect of increasing the number of repeated sequences in the Hebb repetition paradigm has received little attention, and previous studies have used tasks that depart considerably from the natural language learning experience. In the present study, we manipulated the number of repeated sequences in a Hebb repetition paradigm that is a close experimental analogue of language learning. Participants were asked to orally recall sequences of 7 nonsense syllables that were aurally presented. The paradigm included 1 or 3 sequences that were repeated every 4th trial. The results showed that participants could learn 3 sequences simultaneously and they could do so as easily as they would learn a single sequence. The results provide additional evidence to models relating the Hebb repetition effect to word-form learning. (PsycINFO Database Record

This publisher’s note contains corrections to Appl. Opt. 60, 8915 (2021).APOPAI0003-693510.1364/AO.435321