Maximum Likelihood Reconstruction Research Articles

The Presence of Two Distinct Lineages of the Foot-And-Mouth Disease Virus Type A in Russia in 2013-2014 Has Significant Implications for the Epidemiology of the Virus in the Region.

Molecular surveillance of FMD epidemiology is a fundamental tool for advancing our understanding of virus biology, monitoring virus evolution, and guiding vaccine design. The accessibility of genetic data will facilitate a more comprehensive delineation of FMDV phylogeny on a global scale. In this study, we investigated the FMDV strains circulating in Russia during the 2013-2014 period in geographically distant regions utilizing whole genome sequencing followed by maximum-likelihood phylogenetic reconstruction of whole genome and VP1 gene sequences. Phylogenetic analysis showed congruence in the topology of the phylogenetic trees constructed using the complete genome and VP1 gene sequence, clearly demonstrating that the isolates analyzed belong to two distinct genetic lineages: A/SEA97 in the Far East and Iran-05 in the North Caucasus. The A/SEA97 isolates exhibited a close genetic identity to those from China and Mongolia, whereas the Iran-05 isolates demonstrated clusterization with those from Turkey. The vaccine-matching studies with isolates from the Far East and North Caucasus revealed no antigenic homology with A/SEA-97 (r1 = 0.015-0.29) and A/Iran 05 (r1 = 0.009-0.17). The close genetic relationship of FMDV in the reported outbreak waves to those from neighboring countries indicates that animal movement could contribute to spillover and virus dispersal. The phylogenetic data reported here provide insight into the molecular epidemiology of FMD in the Eurasia region, elucidating the circulation pattern, molecular evolution, and genetic diversity, which is highly valuable for guiding vaccine designs and improving regional eradication policies.

Deep learning VLBI image reconstruction with closure invariants

ABSTRACT Interferometric closure invariants, constructed from triangular loops of mixed Fourier components, capture calibration-independent information on source morphology. While a complete set of closure invariants is directly obtainable from measured visibilities, the inverse transformation from closure invariants to the source intensity distribution is not established. In this work, we demonstrate a deep learning approach, Deep learning Image Reconstruction with Closure Terms (DIReCT), to directly reconstruct the image from closure invariants. Trained on both well-defined mathematical shapes (two-dimensional Gaussians, discs, ellipses, m-rings) and natural images (CIFAR-10), the results from our specially designed model are insensitive to station-based corruptions and thermal noise. The median fidelity score between the reconstruction and the blurred ground truth achieved is $\gtrsim 0.9$ even for untrained morphologies, where a unit score denotes perfect reconstruction. In our validation tests, DIReCT’s results are comparable to other state-of-the-art deconvolution and regularized maximum-likelihood image reconstruction algorithms, with the advantage that DIR eCT does not require hand-tuned hyperparameters for each individual prediction. This independent approach shows promising results and offers a calibration-independent constraint on source morphology, ultimately complementing and improving the reliability of sparse very long baseline interferometry imaging results.

A phylogenetic assessment of HIV-1 transmission trends among people who inject drugs from Coastal and Nairobi, Kenya.

Although recent modeling suggests that needle-syringe programs (NSPs) have reduced parenteral HIV transmission among people who inject drugs (PWID) in Kenya, the prevalence in this population remains high (∼14-20%, compared to ∼4% in the larger population). Reducing transmission or acquisition requires understanding historic and modern transmission trends, but the relationship between the PWID HIV-1 sub-epidemic and the general epidemic in Kenya is not well understood. We incorporated 303 new (2018-21) HIV-1 pol sequences from PWID and their sexual and injecting partners with 2666 previously published Kenyan HIV-1 sequences to quantify relative rates and direction of HIV-1 transmissions involving PWID from the coast and Nairobi regions of Kenya. We used genetic similarity cluster analysis (thresholds: patristic distance <0.045 and <0.015) and maximum likelihood and Bayesian ancestral state reconstruction to estimate transmission histories at the population group (female sex workers, men who have sex with men, PWID, or general population) and regional (coast or Nairobi) levels. Of 1081 participants living with HIV-1, 274 (25%) were not virally suppressed and 303 (28%) had sequences available. Of new sequences from PWID, 58% were in phylogenetic clusters at distance threshold <0.045. Only 21% of clusters containing sequences from PWID included a second PWID sequence. Sequences from PWID were similarly likely to cluster with sequences from female sex workers, men who have sex with men, and the general population. Ancestral state reconstruction suggested that transmission to PWID from other populations was more common than from PWID to other populations. This study expands our understanding of the HIV-1 sub-epidemic among PWID in Kenya by incorporating four times more HIV-1 sequences from this population than prior studies. Despite recruiting many PWID from local sexual and injecting networks, we found low levels of linked transmission in this population. This may suggest lower relative levels of parenteral transmission in recent years and supports maintaining NSPs among PWID, while also strengthening interventions to reduce HIV-1 sexual acquisition and transmission for this population.

Molecular phylogenetic relationships among lineages in the genus Carabus (Coleoptera: Carabidae) and radiation of the subgenus Apotomopterus

Abstract The genus Carabus (Coleoptera: Carabidae: Carabinae) is a group of predacious ground beetles found throughout Holarctic temperate zones. The diversification of this group is attributed not only to allopatric speciation but also to diversification in life-history traits and morphological traits that are involved in ecological adaptation and reproductive isolation. Precise phylogenetic reconstruction of Carabus is important to understanding the factors associated with species’ divergence in relation to such character divergence. Here, we analyse the phylogeny of Carabus among higher taxonomic groups and among species of the subgenus Apotomopterus, a hyper-diverse group endemic to East Asia. We used genome-wide sequence data from ultraconserved elements for phylogenetic reconstruction via maximum-likelihood and species-tree reconstruction methods. With regard to the relationships among higher taxonomic groups, the obtained phylogenetic trees resolved two structures with previously unresolved divergence. The subgenus Apotomopterus contained three lineages, i.e. the Vitalisi, Prodigus, and Sauteri groups. It showed diversification of the spinula, a sclerotized male genital structure, and variation in the female elytral notch (preapical emargination). These morphological traits may be involved in copulatory behaviour and potentially affect reproductive isolation, and their character state divergence may have facilitated species divergence of Apotomopterus.

Semiparametric maximum likelihood reconstruction of stochastic differential equations driven by white and correlated noise.

A semiparametric methodology for reconstructing Markovian and non-Markovian Langevin equations from time series data using unscented Kalman filtering is introduced and explored. The drift function and the logarithm of the diffusion function are expanded into sets of polynomial basis functions. In contrast to the more common state augmentation approach, the Kalman filter is here used only for state estimation and propagation; the model parameters are determined by maximum likelihood based on the predictive distribution generated by the Kalman filter. Model selection regarding the number of included drift and diffusion basis functions is performed with the Bayesian information criterion. The method is successfully validated on various simulated datasets with known system dynamics; it achieves accurate identification of drift and diffusion functions, also outside the prescribed model class, from datasets of moderate length with medium computational cost.

A land plant phylogenetic framework for GLABROUS INFLORESCENCE STEMS (GIS), SUPERMAN, JAGGED and allies plus their TOPLESS co-repressor

Members of the plant specific family of C1-1i zincfinger transcriptionfactors (ZF-TFs), such as SUPERMAN, JAGGED, KNUCKLES or GIS,regulatediversedevelopmental processes including sexual reproduction. C1-1is consist of one zinc-finger and one to two EAR domains, connected by large intrinsically disordered regions (IDR). While the role of C1-i1 ZF-TFs in development processes is well known for some genes in Arabidopsis, rice or tomatoa comprehensive and broadphylogenetic background is lacking, yet knowledge of orthology is a requirement for a better understanding of C1-1i-Zf-TFs diverse roles in plants. Here, we provide a fine-grained and land plant wide classification of C1-1i sub-families and their known co-repressors TOPLESS and TOPLESS RELATED. Our work combines the identification of orthologous groups with Maximum-Likelihood phylogeny reconstructions and digital gene expression analyses mining high quality land plant genomes and transcriptomes to generate a comprehensive framework of C1-1i ZF-TF evolution. We show that C1-1i’s are low to moderate copy genesand that orthologous genesonly partiallyhaveconserved sub-family and life cycle stage dependent expression pattern across land plants while others are highly diverged. Our workprovides the phylogenetic framework for C1-1i ZF-TFs, s and strengthen C1-1 ZF-TFs as a potential model for IDR-research in plants.

Anatomically Guided PET Image Reconstruction Using Conditional Weakly-Supervised Multi-Task Learning Integrating Self-Attention.

To address the lack of high-quality training labels in positron emission tomography (PET) imaging, weakly-supervised reconstruction methods that generate network-based mappings between prior images and noisy targets have been developed. However, the learned model has an intrinsic variance proportional to the average variance of the target image. To suppress noise and improve the accuracy and generalizability of the learned model, we propose a conditional weakly-supervised multi-task learning (MTL) strategy, in which an auxiliary task is introduced serving as an anatomical regularizer for the PET reconstruction main task. In the proposed MTL approach, we devise a novel multi-channel self-attention (MCSA) module that helps learn an optimal combination of shared and task-specific features by capturing both local and global channel-spatial dependencies. The proposed reconstruction method was evaluated on NEMA phantom PET datasets acquired at different positions in a PET/CT scanner and 26 clinical whole-body PET datasets. The phantom results demonstrate that our method outperforms state-of-the-art learning-free and weakly-supervised approaches obtaining the best noise/contrast tradeoff with a significant noise reduction of approximately 50.0% relative to the maximum likelihood (ML) reconstruction. The patient study results demonstrate that our method achieves the largest noise reductions of 67.3% and 35.5% in the liver and lung, respectively, as well as consistently small biases in 8 tumors with various volumes and intensities. In addition, network visualization reveals that adding the auxiliary task introduces more anatomical information into PET reconstruction than adding only the anatomical loss, and the developed MCSA can abstract features and retain PET image details.

In silico analysis of a heme-thiolate peroxidase gene discovered in an ectomycorrhizal fungus of Carpathian primeval forest: implications for biotechnological applications

In this work, we focus on the identification of novel fungal peroxygenase gene belonging to the peroxidase-peroxygenase superfamily. We applied a metagenomic approach on soil samples from primeval forest and appropriate bioinformatics tools for analysis of obtained genomic DNA sequence. Peroxidases are ubiquitous metalloenzymes that are able to reduce reactive peroxides, mainly hydrogen peroxide, into water, whereas several substrates can be concomitantly oxidized during their catalytic reaction. Our purpose was to collect unique peroxygenase sequence data originating from a preserved biotope for a robust phylogenetic reconstruction of a particular gene family coding for highly versatile heme-thiolate peroxidases that has peculiar yet undiscovered representatives among ectomycorrhizal fungi. We identified unique DNA sequence, 812 bp long, from ectomycorrhizal Suillus species coding for a heme-thiolate peroxidase with 1 typical intron that appears distinctive for Carpathian forests. After translation in corresponding protein sequence 251 amino acids long we could identify typical signatures of this peroxygenase. On the proximal side of heme we found the conserved P-C-P triad responsible for efficient ligation of heme iron thus influencing the reactivity of this peroxidase. On the distal side we recognized the E-H-D-X-S-L motif for interaction with a stabilizing magnesium ion. Maximum likelihood reconstruction of protein phylogeny revealed with a high bootstrap support the presence of a monophyletic HTP4 clade originating in numerous Suillus representatives. Together with sister clades of edible Boletus and poisonous Paxillus containing diverse peroxygenases these newly discovered heme catalyst can be considered for application of oxyfunctionalization of organic molecules.

First Report of Isolation and Characterization of Acanthamoeba spp. from the Milk Used for Calf Feeding.

Acanthamoeba spp. can be found in natural and artificial environments, which reflects their high adaptability to different conditions. Based on the available data, there is scarce information about the isolation of amoeba from milk. This study aimed to investigate the probable presence of Acanthamoeba in milk used for calf feeding. 200 milk samples from 50 industrial and traditional farms were collected. The samples were filtered and cultured on the 1.5% Non-nutrient agar medium. The amoebic growth was examined with an inverted microscope daily. DNA was extracted from the positive plates, and a PCR reaction was undertaken using the primers amplifying the Acanthamoeba 18S rRNA gene. Five samples were purified and sequenced using specific primers. Maximum likelihood reconstructions were performed using the phylogenetic program MEGA software. The osmo and thermotolerance of isolated trophozoites were examined as well. Out of 200 milk samples, Acanthamoeba was isolated from 27 (13.5%). The phylogenetic tree represents that all the isolates belonged to the genotype T4. Results of thermo and osmotolerance tests showed that isolates could develop at 37 and 43 ◦C. Besides, trophozoites survived at 0.5M mannitol and 1M. For the first time, Acanthamoeba spp. were isolated from milk used to feed dairy calves. Due to Acanthamoeba's neglected role in pathogen persistence and survival, hygiene instructions should be reconsidered.

Supplemental Transmission Aided Attenuation Correction for Quantitative Cardiac PET.

Quantitative PET attenuation correction (AC) for cardiac PET/CT and PET/MR is a challenging problem. We propose and evaluate an AC approach that uses coincidences from a relatively weak and physically fixed sparse external source, in combination with that from the patient, to reconstruct μ -maps based on physics principles alone. The low 30 cm3 volume of the source makes it easy to fill and place, and the method does not use prior image data or attenuation map assumptions. Our supplemental transmission aided maximum likelihood reconstruction of attenuation and activity (sTX-MLAA) algorithm contains an attenuation map update that maximizes the likelihood of terms representing coincidences originating from tracer in the patient and a weighted expression of counts segmented from the external source alone. Both external source and patient scatter and randoms are fully corrected. We evaluated performance of sTX-MLAA compared to reference standard CT-based AC with FDG PET/CT phantom studies; including modeling a patient with myocardial inflammation. Through an ROI analysis we measured ≤ 5 % bias in activity concentrations for PET images generated with sTX-MLAA and a TX source strength ≥ 12.7 MBq, relative to CT-AC. PET background variability (from noise and sparse sampling) was substantially reduced with sTX-MLAA compared to using counts segmented from the transmission source alone for AC. Results suggest that sTX-MLAA will enable quantitative PET during cardiac PET/CT and PET/MR of human patients.

Characterization of the Complete Mitochondrial Genome of the Elongate Loach and Its Phylogenetic Implications in Cobitidae.

The elongate loach is an endemic fish in China. Previous studies have provided some insights into the mitochondrial genome composition and the phylogenetic relationships of the elongate loach inferred using protein-coding genes (PCGs), yet detailed information about it remains limited. Therefore, in this study we sequenced the complete mitochondrial genome of the elongate loach and analyzed its structural characteristics. The PCGs and mitochondrial genome were used for selective stress analysis and genomic comparative analysis. The complete mitochondrial genome of the elongate loach, together with those of 35 Cyprinidae species, was used to infer the phylogenetic relationships of the Cobitidae family through maximum likelihood (ML) reconstruction. The results showed that the genome sequence has a full length of 16,591 bp, which includes 13 PCGs, 22 transfer RNA genes (tRNA), 2 ribosomal RNA genes (rRNA), and 2 non-coding regions (CR D-loop and light chain sub-chain replication origin OL). Overall, the elongate loach shared the same gene arrangement and composition of the mitochondrial genes with other teleost fishes. The Ka/Ks ratios of all mitochondrial PCGs were less than 1, indicating that all of the PCGs were evolving under purifying selection. Genome comparison analyses showed a significant sequence homology of species of Leptobotia. A significant identity between L. elongata and the other five Leptobotia species was observed in the visualization result, except for L. mantschurica, which lacked the tRNA-Arg gene and had a shorter tRNA-Asp gene. The phylogenetic tree revealed that the Cobitidae species examined here can be grouped into two clades, with the elongate loach forming a sister relationship with L. microphthalma. This study could provide additional inferences for a better understanding of the phylogenetic relationships among Cobitidae species.

Maximum likelihood bolometry for ASDEX upgrade experiments

Bolometry is an essential diagnostic for calculating the power balances and for the understanding of different physical aspects of tokamak experiments. The reconstruction method based on the Maximum Likelihood (ML) principle, developed initially for JET, has been implemented for ASDEX Upgrade. Due to the availability of a limited number of views, the reconstruction problem is mathematically ill-posed. A regularizing procedure, based on the assumption of smoothness along the magnetic surfaces, given by plasma equilibrium, must also be implemented. A new anisotropic smoothing technique, which acts along locally oriented kernels, has been implemented. The performances of the method have been evaluated, in terms of shapes, resolution and of the derived radiated power, and compared with the bolometry method used routinely on ASDEX Upgrade. The specific advantage of the ML reconstruction algorithm consists of the possibility to assess the uncertainties of the reconstruction and to derive confidence intervals in the emitted radiation levels. The importance of this capability is illustrated.

The Ga1 locus of the genus Zea is associated with novel genome structures derived from multiple, independent non-homologous recombination events.

The Ga1 locus controls cross incompatibility between field corn and popcorn. The Ga1-S haplotype contains two types of pectin methylesterase (PME) genes, ZmPme3 and several copies of ZmGa1P, that are expressed in silk and pollen, respectively. The ga1 haplotype contains non-functional tandem repeat sequences related to ZmPme3 and ZmGa1P. This haplotype can cross pollinate freely and is widely present in field corn. The primary objective of this study is to characterize the repeat sequences from a diverse collection of maize and teosinte lines and use this information to understand the evolution of the Ga1 locus. First, we characterized the complexity of the Ga1 genome region in high quality maize genome assemblies which led to their categorization into five groups based on the number and type of PME-like sequences found at this region. Second, we studied duplication events that led to the ga1 and Ga1-S repeats using maximum-likelihood phylogenetic reconstruction. Divergence estimates of the ga1 haplotype suggest that the duplication events occurred more than 600 kya whereas those in Ga1-S occurred at three time points i.e., > 600 kya, ∼ 260 kya and ∼ 100 kya. These estimates suggest that the ga1 and Ga1-S tandem duplication events occurred independently. Finally, analysis of ZmPme3 and ZmGa1P homologs in Zea and Tripsacum genomes suggests that ga1 and Ga1-S repeats originated from an ancestral pair of PME genes that duplicated and diverged through two evolutionary branches prior to the domestication of maize.

Novel B2 mitogenomes from Continental southern Patagonia's Late Holocene: New insights into the peopling of the Southern Cone.

The main aim of this study is to discuss the migratory processes and peopling dynamics that shaped the genetic variability of populations during the settlement of the Southern Cone, through the analysis of complete mitogenomes of individuals from southern Patagonia. Complete mitogenomes were sequenced through massively parallel sequencing from two late Holocene individuals (SAC 1-1-3 and SAC 1-1-4) buried in the same chenque at Salitroso Lake Basin (Santa Cruz province, Argentina). To evaluate matrilineal phylogenetic affinities with other haplotypes, maximum likelihood and Bayesian phylogenetic reconstructions were performed, as well as a haplotype median-joining network. The mitogenomes were assigned to haplogroups B2 and B2b, exhibiting an average depth of 54X and 89X (≥1X coverage of 98.6% and 100%), and a high number of nucleotide differences among them. The phylogenetic analyses showed a relatively close relationship between the haplotype found in SAC 1-1-4 and those retrieved from a Middle Holocene individual from Laguna Chica (Buenos Aires province), and from a group of individuals from the Peruvian coast. For the SAC 1-1-3, no clear affiliations to any other haplotype were established. The large divergence between the haplotypes presented in this study suggests either a highly variable founder gene pool, or a later enrichment by frequent biological contact with other populations. Our results underline the persistence of genetic signals related to the first waves of peopling in South America, suggesting that the regional settlement of the southern end of the continent has been much more complex than initially thought.

Ancient mitochondrial genome diversity in South America: Contributions from Quebrada del Toro, Northwestern Argentina.

The objective of this study was to enhance our understanding of the population history in South America, specifically Northwestern Argentina, by analyzing complete ancient mitogenomes of individuals from the Ojo de Agua archeological site (970 BP) in Quebrada del Toro (Salta, Argentina). We analyzed teeth from four individuals from the site Ojo de Agua (970 ± 60 BP), located in Quebrada del Toro (Andean region of Northwestern Argentina). DNA extracts were converted to double-stranded DNA libraries and indexed using unique dual-indexing primer combinations. DNA libraries were then enriched for the complete mitochondrial genome, pooled at equimolar concentrations, and sequenced on an Illumina® MiSeq™ platform. Reads from high quality libraries were trimmed, merged, and then mapped to the revised Cambridge Reference Sequence. The aDNA damage patterns were assessed and contamination estimated. Finally, variants were called, filtered, and the consensus mitogenome was constructed and used for haplogroup assignment. We also compiled available mitogenome sequences from ancient and present-day populations from the Southcentral Andes and other surrounding regions in Argentina. Maximum Likelihood and Bayesian phylogenetic reconstructions were obtained using the generated dataset. We successfully obtained the complete mitogenome sequence from one individual with an average depth coverage of 102X. We discovered a novel haplotype that was assigned to haplogroup D1. Phylogenetic reconstructions suggests that this haplotype falls within the sister branches of the D1j lineage, forming a well-supported clade. The estimate TMRCA of this clade that includes D1j and its sister branches ranged between 12,535 and 18,669 ya. The sequence analyzed in this study represents the first ancient mitogenome from within the valley region in Northwestern Argentina. We found that a representative of a lineage highly associated with D1j was already present approximately 1000 BP in the region. Our results agree with the proposed origin of D1j in other regions north of Patagonia and independent of the Pacific coast fast migratory route, contrary to what was originally hypothesized. This study highlights the lack of information regarding pre-Hispanic genetic diversity and contributes to the knowledge about the peopling process in South America.

Neural KEM: A Kernel Method With Deep Coefficient Prior for PET Image Reconstruction.

Image reconstruction of low-count positron emission tomography (PET) data is challenging. Kernel methods address the challenge by incorporating image prior information in the forward model of iterative PET image reconstruction. The kernelized expectation-maximization (KEM) algorithm has been developed and demonstrated to be effective and easy to implement. A common approach for a further improvement of the kernel method would be adding an explicit regularization, which however leads to a complex optimization problem. In this paper, we propose an implicit regularization for the kernel method by using a deep coefficient prior, which represents the kernel coefficient image in the PET forward model using a convolutional neural-network. To solve the maximum-likelihood neural network-based reconstruction problem, we apply the principle of optimization transfer to derive a neural KEM algorithm. Each iteration of the algorithm consists of two separate steps: a KEM step for image update from the projection data and a deep-learning step in the image domain for updating the kernel coefficient image using the neural network. This optimization algorithm is guaranteed to monotonically increase the data likelihood. The results from computer simulations and real patient data have demonstrated that the neural KEM can outperform existing KEM and deep image prior methods.

Evolutionary Optimization of Multiple Machine-Learned Objectives for PET Image Reconstruction

This article proposes optimizing machine-learned objective functions to estimate a set of images optimal for multiple tasks. Tomographic image reconstruction commonly relies on optimizing an objective function that dictates the goodness of an image estimate. We propose a novel use of deep learning in which we train models to perform blind estimation of the goodness of an image. The trained model that maps an image to a target figure of merit serves as the objective function. Using simulated PET images, we train convolutional neural networks (CNNs) to estimate for a single image the root mean square error (RMSE), signal-to-noise ratio, and full width half maximum (FWHM) of a point source. These figures of merit serve as surrogates for the common medical task performance in terms of quantitation, detection, and spatial resolution, respectively. These multiple objective functions are optimized using our recently proposed multiobjective evolutionary algorithm for PET image reconstruction. The evolutionary algorithm seeks to identify the Pareto-optimal front of image solutions, optimal for multiple objectives. Additionally, we propose a reference point method to focus the evolutionary optimization on regions of the multiobjective space to reduce computation. Likewise, we integrate optimality conditions to estimate how close a solution is to optimal without any prior knowledge about the Pareto-optimal front in an effort to guide termination conditions. The multiobjective approach is compared with conventional maximum-likelihood reconstruction with increasing explicit regularization and maximum a posteriori reconstruction with varying penalty strength. The approaches are tested with simulated PET data from a digital phantom and patient data. Results suggest that the proposed machine-learned objectives can estimate quantification, detection, and spatial resolution performance and that the evolutionary algorithm estimates a set of solutions with a good balance for convergence and diversity across different multiobjective combinations. In general, the evolutionary algorithm estimates images with superior performance compared to conventional techniques. Future work is needed to ensure and improve generalizability of the machine-learned objectives for different imaging conditions and to explore other target figures of merit for training machine-learned objectives. This proof-of-concept effort demonstrates a new use of deep learning for tomographic image reconstruction.

High-throughput sequencing confirms the boundary between traditionally considered species pairs in a group of lichenized fungi (Peltigeraceae, Pseudocyphellaria)

Abstract Accurate species delimitations are fundamental to our understanding of the genetic diversity on Earth and a vital part in evolutionary and conservation biology research. In lichenized fungi, species pairs have the same morphology and chemistry. They only differ in how they reproduce with one species using sexual reproductive structures and the other using asexual propagules. To classify these as one species or two has been a point of contention, and conclusions based on Sanger sequencing, where sequence data are limited and species boundaries are usually not observed, have been refuted after analysis with genome-scale data such as restriction site-associated DNA sequencing that tends to find fixed genetic differences between the two morphs. Pseudocyphellaria glabra and P. homoeophylla have long been considered a species pair that differ in geographical ranges but co-occur in New Zealand. We used restriction site-associated DNA sequencing data and generated thousands of genetic loci across 53 individuals. The RADseq data provided high-resolution phylogenetic and population genomic information. A maximum-likelihood phylogenetic reconstruction recovered both species as separate lineages, whereas population genetics indicated some evidence for admixture among P. glabra and P. homoeophylla from New Zealand. It is not clear whether the latter is due to ancient polymorphism or recent gene flow. Our study represents another example of the usefulness of RADseq to test species boundaries that segregate closely related species in lichenized fungi.

Horizontal convergence reconstruction in the longitudinal direction for shield tunnels based on conditional random field

Tunnel horizontal convergence monitoring is essential to ensure the operation safety. However, only a few representative tunnel sections are chosen for monitoring due to the cost limitation. It is difficult to capture the horizontal convergence of each tunnel ring with limited measurements. Confronted with this difficulty, the paper proposes a horizontal convergence reconstruction method based on the measurements of deployed sensors. The tunnel horizontal convergence along the longitudinal direction is seen as a one-dimensional stationary and ergodic random field. The reconstruction problem is then transformed into the generation of conditional random fields. Monte Carlo simulation is adopted to generate possible realizations and the mean of realizations is considered as the maximum likelihood reconstruction. Error analysis proves the effectiveness of the proposed reconstruction method. The proposed method is proved to be applicable in reconstructing the time-variant horizontal convergence and is verified by the monitoring results of the shield tunnel of Shanghai Metro Line 2. The effect of sensor numbers is parametrically studied, and an optimal sensor placement scheme is decided. Additional sensors placed at the deformation drastically changed location can significantly improve the performance of the proposed method.

Pushing the performance of image scanning microscopy to its limits with maximum likelihood reconstruction

Fast and sensitive detector arrays make Image Scanning Microscopy (ISM) the natural successor of confocal microscopy. Indeed, ISM enables super-resolution at an excellent signal-to-noise ratio. Optimizing photon collection requires large detectors and so more out-of-focus light is collected. Nonetheless, the ISM dataset inherently contains information on the axial position of the fluorescence emitters. We exploit such information to directly invert the cmresponding physical model with a maximum-likelihood approach and reassign the signal in the thr ee dimensions, improving the signal-to-background ratio and resolution. We validated our method on synthetic and experimental images; these latter acquired with a custom setup equipped with a single photon avalanche diode array detector. Moreover, our method is compatible with recent developments in ISM data processing and requires minimal knowledge of physical parameters.