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BACKGROUND: The risk of relapse after anti-tumour necrosis factor [TNF] therapy discontinuation in Crohn's disease patients with perianal fistulas [pCD] is unclear. We aimed to assess this risk. METHODS: A systematic literature search was conducted to identify cohort studies on the incidence of relapse following anti-TNF discontinuation in pCD patients. Individual participant data were requested from the original study cohorts. Inclusion criteria were age ≥16 years, pCD as a (co)indication for start of anti-TNF therapy, more than three doses, and remission of luminal and pCD at anti-TNF discontinuation. The primary outcome was the cumulative incidence of CD relapse using Kaplan-Meier estimates. Secondary outcomes included response to re-treatment and risk factors associated with relapse as assessed by Cox regression analysis. RESULTS: In total, 309 patients from 12 studies in ten countries were included. The median duration of anti-TNF treatment was 14 months [interquartile range 5.8-32.5]. Most patients were treated for pCD without active luminal disease [89%], received first-line anti-TNF therapy [87%], and continued immunomodulatory therapy following anti-TNF discontinuation [78%]. The overall cumulative incidence of relapse was 36% (95% confidence interval [CI] 25-48%) and 42% [95% CI 32-53%] at 1 and 2 years after anti-TNF discontinuation, respectively. Risk factors for relapse included smoking (hazard ratio [HR] 1.5 [1.0, 2.1]) and history of proctitis (HR 1.7 [1.1, 2.5]). The overall re-treatment response rate was 82%. CONCLUSIONS: This individual participant data meta-analysis, on predominantly patients with pCD without active luminal disease and first-line anti-TNF therapy, shows that over half of patients remain in remission 2 years after anti-TNF discontinuation. Therefore, anti-TNF discontinuation may be considered in this subgroup.

Given the important role turbulence plays in the settling and growth of dust grains in protoplanetary disks, it is crucial that we determine whether these disks are turbulent and to what extent. Protoplanetary disks are weakly ionized near the mid-plane, which has led to a paradigm in which largely laminar magnetic field structures prevail deeper in the disk, with angular momentum being transported via magnetically launched winds. Yet, there has been little exploration on the precise behavior of the gas within the bulk of the disk. We carry out 3D, local shearing box simulations that include all three low-ionization effects (Ohmic diffusion, ambipolar diffusion, and the Hall effect) to probe the nature of magnetically driven gas dynamics 1-30 AU from the central star. We find that gas turbulence can persist with a generous yet physically motivated ionization prescription (order unity Elsasser numbers). The gas velocity fluctuations range from 0.03-0.09 of the sound speed $c_s$ at the disk mid-plane to $\sim c_s$ near the disk surface, and are dependent on the initial magnetic field strength. However, the turbulent velocities do not appear to be strongly dependent on the field polarity, and thus appear to be insensitive to the Hall effect. The mid-plane turbulence has the potential to drive dust grains to collision velocities exceeding their fragmentation limit, and likely reduces the efficacy of particle clumping in the mid-plane, though it remains to be seen if this level of turbulence persists in disks with lower ionization levels., Comment: 23 pages, 19 figures, 2 tables, submitted to ApJ

Kuiper belt objects show an unexpected trend, whereby large bodies have increasingly higher densities, up to five times greater than their smaller counterparts. Current explanations for this trend assume formation at constant composition, with the increasing density resulting from gravitational compaction. However, this scenario poses a timing problem to avoid early melting by decay of $^{26}$Al. We aim to explain the density trend in the context of streaming instability and pebble accretion. Small pebbles experience lofting into the atmosphere of the disk, being exposed to UV and partially losing their ice via desorption. Conversely, larger pebbles are shielded and remain more icy. We use a shearing box model including gas and solids, the latter split into ices and silicate pebbles. Self-gravity is included, allowing dense clumps to collapse into planetesimals. We find that the streaming instability leads to the formation of mostly icy planetesimals, albeit with an unexpected trend that the lighter ones are more silicate-rich than the heavier ones. We feed the resulting planetesimals into a pebble accretion integrator with a continuous size distribution, finding that they undergo drastic changes in composition as they preferentially accrete silicate pebbles. The density and masses of large KBOs are best reproduced if they form between 15 and 22\,AU. Our solution avoids the timing problem because the first planetesimals are primarily icy, and $^{26}$Al is mostly incorporated in the slow phase of silicate pebble accretion. Our results lend further credibility to the streaming instability and pebble accretion as formation and growth mechanisms., Comment: 24 pages, 13 figures, accepted to The Planetary Science Journal

BACKGROUND AND OBJECTIVES: Intraoperative orientation during microsurgery has a prolonged learning curve among neurosurgical residents. Three-dimensional (3D) understanding of anatomy can be facilitated with realistic 3D anatomic models created from photogrammetry, where a series of 2-dimensional images is converted into a 3D model. This study implements an algorithm that can create photorealistic intraoperative 3D models to exemplify important steps of the operation, operative corridors, and surgical perspectives. METHODS: We implemented photograph-based and video-based scanning algorithms for uptakes using the operating room (OR) microscope, targeted for superficial structures, after surgical exposure, and deep operative corridors, in cranial microsurgery. The algorithm required between 30–45 photographs (superficial scanning), 45–65 photographs (deep scanning), or approximately 1 minute of video recording of the entire operative field to create a 3D model. A multicenter approach in 3 neurosurgical departments was applied to test reproducibility and refine the method. RESULTS: Twenty-five 3D models were created of some of the most common neurosurgical approaches—frontolateral, pterional, retrosigmoid, frontal, and temporal craniotomy. The 3D models present important steps of the surgical approaches and allow rotation, zooming, and panning of the model, enabling visualization from different surgical perspectives. The superficial and medium depth structures were consistently presented through the 3D models, whereas scanning of the deepest structures presented some technical challenges, which were gradually overcome with refinement of the image capturing process. CONCLUSION: Intraoperative photogrammetry is an accessible method to create 3D educational material to show complex anatomy and demonstrate concepts of intraoperative orientation. Detailed interactive 3D models, displaying stepwise surgical case-based anatomy, c, BACKGROUND AND OBJECTIVES:Intraoperative orientation during microsurgery has a prolonged learning curve among neurosurgical residents. Three-dimensional (3D) understanding of anatomy can be facilitated with realistic 3D anatomic models created from photogrammetry, where a series of 2-dimensional images is converted into a 3D model. This study implements an algorithm that can create photorealistic intraoperative 3D models to exemplify important steps of the operation, operative corridors, and surgical perspectives.METHODS:We implemented photograph-based and video-based scanning algorithms for uptakes using the operating room (OR) microscope, targeted for superficial structures, after surgical exposure, and deep operative corridors, in cranial microsurgery. The algorithm required between 30-45 photographs (superficial scanning), 45-65 photographs (deep scanning), or approximately 1 minute of video recording of the entire operative field to create a 3D model. A multicenter approach in 3 neurosurgical departments was applied to test reproducibility and refine the method.RESULTS:Twenty-five 3D models were created of some of the most common neurosurgical approaches-frontolateral, pterional, retrosigmoid, frontal, and temporal craniotomy. The 3D models present important steps of the surgical approaches and allow rotation, zooming, and panning of the model, enabling visualization from different surgical perspectives. The superficial and medium depth structures were consistently presented through the 3D models, whereas scanning of the deepest structures presented some technical challenges, which were gradually overcome with refinement of the image capturing process.CONCLUSION:Intraoperative photogrammetry is an accessible method to create 3D educational material to show complex anatomy and demonstrate concepts of intraoperative orientation. Detailed interactive 3D models, displaying stepwise surgical case-based anatomy, can be used to help understand details of the operat

Algebraic multigrid (AMG) is known to be an effective solver for many sparse symmetric positive definite (SPD) linear systems. For SPD systems, the convergence theory of AMG is well-understood in terms of the $A$-norm but in a nonsymmetric setting such an energy norm is non-existent. For this reason, convergence of AMG for nonsymmetric systems of equations remains an open area of research. Existing nonsymmetric AMG algorithms in this setting mostly rely on heuristics motivated by SPD convergence theory. In the SPD setting, the classical form of optimal AMG interpolation provides a useful insight in determining the two grid convergence rate of the method. In this work, we discuss a generalization of the optimal AMG convergence theory targeting nonsymmetric problems by constructing a $2\times 2$ block symmetric indefinite system so that the Petrov-Galerkin AMG process for the nonsymmetric matrix $A$ can be recast as a Galerkin AMG process for a symmetric indefinite system. We show that using this generalization of the optimal interpolation theory, one can obtain the same identity for the two-grid convergence rate as that derived in the SPD setting for optimal interpolation. We also provide supporting numerical results for the convergence result and nonsymmetric advection-diffusion problems., Comment: 10 pages, 2 figures, submitted as a student paper for the 18th Copper Mountain Conference on Iterative Methods

Foldy is a cloud-based application that allows non-computational biologists to easily utilize advanced AI-based structural biology tools, including AlphaFold and DiffDock. With many deployment options, it can be employed by individuals, labs, universities, and companies in the cloud without requiring hardware resources, but it can also be configured to utilize locally available computers. Foldy enables scientists to predict the structure of proteins and complexes up to 6000 amino acids with AlphaFold, visualize Pfam annotations, and dock ligands with AutoDock Vina and DiffDock. In our manuscript, we detail Foldy’s interface design, deployment strategies, and optimization for various user scenarios. We demonstrate its application through case studies including rational enzyme design and analyzing proteins with domains of unknown function. Furthermore, we compare Foldy’s interface and management capabilities with other open and closed source tools in the field, illustrating its practicality in managing complex data and computation tasks. Our manuscript underlines the benefits of Foldy as a day-to-day tool for life science researchers, and shows how Foldy can make modern tools more accessible and efficient.

The genus Corydalis, with ca. 530 species, has long been considered taxonomically challenging because of its great variability. Previous molecular analyses, based on a few molecular markers and incomplete taxonomic sampling, were clearly inadequate to delimit sections and subgenera. We have performed phylogenetic analyses of Corydalis and related taxa, using 65 shared protein-coding plastid genes from 313 accessions (including 280 samples of ca. 226 species of Corydalis) and 152 universal low-copy nuclear genes from 296 accessions (including 271 samples of Corydalis) covering all 42 previously recognized sections and five independent “series”. Phylogenetic trees were inferred using Bayesian Inference and Maximum Likelihood. Eight selected morphological characters were estimated using ancestral state reconstructions. Results include: (i) of the three subgenera of Corydalis, two are fully supported by both the plastid and nuclear data; the third, subg. Cremnocapnos, is weakly supported by plastid DNA only, whereas in the nuclear data the two included sections form successive outgroups to the rest of the genus; (ii) among all 42 sections and five “series”, 25 sections and one “series” are resolved as monophyletic in both data sets; (iii) the common ancestor of Corydalis is likely to be a perennial plant with a taproot, yellow flowers with a short saccate spur, linear fruits with recurved fruiting pedicels, and seeds with elaiosomes; (iv) we provide a new classification of Corydalis with four subgenera (of which subg. Bipapillatae is here newly described), 39 sections, 16 of which are consistent with the previous classification, 16 sections have been recircumscribed, one section has been reinstated and six new sections are established. Characters associated with lifespan, underground structures, floral spur, fruit and elaiosomes are important for the recognition of subgenera and sections. These new phylogenetic analyses combined with ancestral character reconstructions

Sea-level projections depend sensitively on the parameterization used for basal slip in glacier flow models. During slip over rock-beds, ice-bed separation increases with slip velocity and basal water pressure. We present a method for using these variables and measured bed topography to estimate the average bed slope in contact with ice, . Three-dimensional numerical modeling of slip over small areas of former beds has shown that changes in with increasing slip velocity and water pressure mimic changes in basal drag. Computed values of can thus provide the form of the slip law that relates drag to velocity and water pressure, avoiding computationally expensive numerical modeling. The method is applied to 618 sections from four former glacier beds. Results generally show an increase in , and hence inferred basal drag, with slip velocity up to a limiting value, consistent with a regularized Coulomb slip law.

Habitat conversion is a major driver of tropical biodiversity loss, but its effects are poorly understood in montane environments. While community-level responses to habitat loss display strong elevational dependencies, it is unclear whether these arise via elevational turnover in community composition and interspecific differences in sensitivity, or elevational variation in environmental conditions and proximity to thermal thresholds. Here, we assess the relative importance of inter and intraspecific variation across the elevational gradient by quantifying how 243 forest-dependent bird species vary in sensitivity to landscape-scale forest loss across a 3000 m elevational gradient in the Colombian Andes. We find that species that live at lower elevations are strongly affected by loss of forest in the nearby landscape, while those at higher elevations appear relatively unperturbed, an effect that is independent of phylogeny. Conversely, we find limited evidence of intraspecific elevational gradients in sensitivity, with populations displaying similar sensitivities to forest loss, regardless of where they exist in a species’ elevational range. Gradients in biodiversity response to habitat loss thus appear to arise via interspecific gradients in sensitivity rather than proximity to climatically limiting conditions.

Background: Gut microbiota have been implicated in atherosclerotic disease, but their relation with subclinical coronary atherosclerosis is unclear. This study aimed to identify associations between the gut microbiome and computed tomography-based measures of coronary atherosclerosis and to explore relevant clinical correlates. Methods: We conducted a cross-sectional study of 8973 participants (50 to 65 years of age) without overt atherosclerotic disease from the population-based SCAPIS (Swedish Cardiopulmonary Bioimage Study). Coronary atherosclerosis was measured using coronary artery calcium score and coronary computed tomography angiography. Gut microbiota species abundance and functional potential were assessed with shotgun metagenomics sequencing of stool, and associations with coronary atherosclerosis were evaluated with multivariable regression models adjusted for cardiovascular risk factors. Associated species were evaluated for association with inflammatory markers, metabolites, and corresponding species in saliva. Results: The mean age of the study sample was 57.4 years, and 53.7% were female. Coronary artery calcification was detected in 40.3%, and 5.4% had at least 1 stenosis with >50% occlusion. Sixty-four species were associated with coronary artery calcium score independent of cardiovascular risk factors, with the strongest associations observed for Streptococcus anginosus and Streptococcus oralis subsp oralis (P<1×10-5). Associations were largely similar across coronary computed tomography angiography-based measurements. Out of the 64 species, 19 species, including streptococci and other species commonly found in the oral cavity, were associated with high-sensitivity C-reactive protein plasma concentrations, and 16 with neutrophil counts. Gut microbial species that are commonly found in the oral cavity were negatively associated with plasma indole propionate and positively associated with plasma secondary bile acids and imidazole propionate. F

Type I polyketide synthases (T1PKSs) hold enormous potential as a rational production platform for the biosynthesis of specialty chemicals. However, despite great progress in this field, the heterologous expression of PKSs remains a major challenge. One of the first measures to improve heterologous gene expression can be codon optimization. Although controversial, choosing the wrong codon optimization strategy can have detrimental effects on the protein and product levels. In this study, we analyzed 11 different codon variants of an engineered T1PKS and investigated in a systematic approach their influence on heterologous expression in Corynebacterium glutamicum, Escherichia coli, and Pseudomonas putida. Our best performing codon variants exhibited a minimum 50-fold increase in PKS protein levels, which also enabled the production of an unnatural polyketide in each of these hosts. Furthermore, we developed a free online tool (https://basebuddy.lbl.gov) that offers transparent and highly customizable codon optimization with up-to-date codon usage tables. In this work, we not only highlight the significance of codon optimization but also establish the groundwork for the high-throughput assembly and characterization of PKS pathways in alternative hosts.

For parallel-in-time integration methods, the multigrid-reduction-in-time (MGRIT) method has shown promising results in both improved convergence and increased computational speeds when solving evolution problems. However, one problem the MGRIT algorithm currently faces is it struggles solving hyperbolic problems efficiently. In particular, hyperbolic problems are generally solved using explicit methods and this causes issues on the coarser multigrid levels, where larger (coarser) time step sizes can violate the stability condition. In this thesis, physics-informed neural networks (PINNs) are used to evaluate the coarse grid equations in the MGRIT algorithm with the goal to improve convergence for problems with hyperbolic behavior, as well as improve stability for the time-stepping on coarser levels.

Objective Drugs targeting the glucose-dependent insulinotropic polypeptide (GIP) receptor (GIPR) are emerging as treatments for type-2 diabetes and obesity. GIP acutely decreases serum markers of bone resorption and transiently increases bone formation markers in short-term clinical investigations. However, it is unknown whether GIP acts directly on bone cells to mediate these effects. Using a GIPR-specific antagonist, we aimed to assess whether GIP acts directly on primary human osteoclasts and osteoblasts.Methods Osteoclasts were differentiated from human CD14(+) monocytes and osteoblasts from human bone. GIPR expression was determined using RNA-seq in primary human osteoclasts and in situ hybridization in human femoral bone. Osteoclastic resorptive activity was assessed using microscopy. GIPR signaling pathways in osteoclasts and osteoblasts were assessed using LANCE cAMP and AlphaLISA phosphorylation assays, intracellular calcium imaging and confocal microscopy. The bioenergetic profile of osteoclasts was evaluated using Seahorse XF-96.Results GIPR is robustly expressed in mature human osteoclasts. GIP inhibits osteoclastogenesis, delays bone resorption, and increases osteoclast apoptosis by acting upon multiple signaling pathways (Src, cAMP, Akt, p38, Akt, NF?B) to impair nuclear translocation of nuclear factor of activated T cells-1 (NFATc1) and nuclear factor-?B (NF?B). Osteoblasts also expressed GIPR, and GIP improved osteoblast survival. Decreased bone resorption and improved osteoblast survival were also observed after GIP treatment of osteoclast-osteoblast co-cultures. Antagonizing GIPR with GIP(3-30)NH2 abolished the effects of GIP on osteoclasts and osteoblasts.Conclusions GIP inhibits bone resorption and improves survival of human osteoblasts, indicating that drugs targeting GIPR may impair bone resorption, whilst preserving bone formation.

The streaming instability (SI) is a leading candidate for planetesimal formation, which can concentrate solids through two-way aerodynamic interactions with the gas. The resulting concentrations can become sufficiently dense to collapse under particle self-gravity, forming planetesimals. Previous studies have carried out large parameter surveys to establish the critical particle to gas surface density ratio ($Z$), above which SI-induced concentration triggers planetesimal formation. The threshold $Z$ depends on the dimensionless stopping time ($\tau_s$, a proxy for dust size). However, these studies neglected both particle self-gravity and external turbulence. Here, we perform 3D stratified shearing box simulations with both particle self-gravity and turbulent forcing, which we characterize via $\alpha_D$ that measures turbulent diffusion. We find that forced turbulence, at amplitudes plausibly present in some protoplanetary disks, can increase the threshold $Z$ by up to an order of magnitude. For example, for $\tau_s = 0.01$, planetesimal formation occurs when $Z \gtrsim 0.06$, $\gtrsim 0.1$, and $\gtrsim 0.2$ at $\alpha_D = 10^{-4}$, $10^{-3.5}$, and $10^{-3}$, respectively. We provide a single fit to the critical $Z$ as a function of $\alpha_D$ and $\tau_s$ required for the SI to work (though limited to the range $\tau_s = 0.01$--0.1). Our simulations also show that planetesimal formation requires a mid-plane particle-to-gas density ratio that exceeds unity, with the critical value being independent of $\alpha_D$. Finally, we provide the estimation of particle scale height that accounts for both particle feedback and external turbulence., Comment: 27 pages, 13 figures, submitted to The Astrophysical Journal

This work develops a novel all-at-once space-time preconditioning approach for resistive magnetohydrodynamics (MHD), with a focus on model problems targeting fusion reactor design. We consider parallel-in-time due to the long time domains required to capture the physics of interest, as well as the complexity of the underlying system and thereby computational cost of long-time integration. To ameliorate this cost by using many processors, we thus develop a novel approach to solving the whole space-time system that is parallelizable in both space and time. We develop a space-time block preconditioning for resistive MHD, following the space-time block preconditioning concept first introduced by Danieli et al. in 2022 for incompressible flow, where an effective preconditioner for classic sequential time-stepping is extended to the space-time setting. The starting point for our derivation is the continuous Schur complement preconditioner by Cyr et al. in 2021, which we proceed to generalise in order to produce, to our knowledge, the first space-time block preconditioning approach for the challenging equations governing incompressible resistive MHD. The numerical results are promising for the model problems of island coalescence and tearing mode, with the overhead computational cost associated with space-time preconditioning versus sequential time-stepping being modest and primarily in the range of 2x-5x, which is low for parallel-in-time schemes in general. Additionally, the scaling results for inner (linear) and outer (nonlinear) iterations are flat in the case of fixed time-step size and only grow very slowly in the case of time-step refinement., Comment: 25 pages, 4 figures, 3 tables

Fully CMOS-compatible photonic memory holding devices hold a potential in a development of ultrafast artificial neural networks. Leveraging the benefits of photonics such as high-bandwidth, low latencies, low-energy interconnect and high speed they can overcome the existing limits of the electronic processing. To satisfy all these requirements a new photonic platform is proposed that combines low-loss nitride-rich silicon as a guide and low-loss transparent conductive oxides as an active material that can provide high nonlinearity and bistability under both electrical and optical signals., Comment: 13 pages, 8 figures

Photonics integrated circuits have a huge potential to serve as a framework for a new class of information processing machines and can enable ultrafast artificial neural networks. They can overcome the existing speed and power limits of the electronic processing elements and provide additional benefits of photonics such as high-bandwidth, sub-nanosecond latencies and low-energy interconnect credentials leading to a new paradigm called neuromorphic photonics. The main obstacle to realize such a task is a lack of proper material platform that imposes serious requirements on the architecture of the network. Here we suggest and justify that transparent conductive oxides can be an excellent candidate for such a task as they provide a nonlinearity and bistability under both optical and electrical inputs., Comment: 13 pages, 7 figures

This paper focuses on developing a reduction-based algebraic multigrid method that is suitable for solving general (non)symmetric linear systems and is naturally robust from pure advection to pure diffusion. Initial motivation comes from a new reduction-based algebraic multigrid (AMG) approach, $\ell$AIR (local approximate ideal restriction), that was developed for solving advection-dominated problems. Though this new solver is very effective in the advection dominated regime, its performance degrades in cases where diffusion becomes dominant. This is consistent with the fact that in general, reduction-based AMG methods tend to suffer from growth in complexity and/or convergence rates as the problem size is increased, especially for diffusion dominated problems in two or three dimensions. Motivated by the success of $\ell$AIR in the advective regime, our aim in this paper is to generalize the AIR framework with the goal of improving the performance of the solver in diffusion dominated regimes. To do so, we propose a novel way to combine mode constraints as used commonly in energy minimization AMG methods with the local approximation of ideal operators used in $\ell$AIR. The resulting constrained $\ell$AIR (C$\ell$AIR) algorithm is able to achieve fast scalable convergence on advective and diffusive problems. In addition, it is able to achieve standard low complexity hierarchies in the diffusive regime through aggressive coarsening, something that has been previously difficult for reduction-based methods., Comment: Revised form published in the SIAM Journal on Scientific computing (SPECIAL SECTION Copper Mountain 2023), 22 pages, 7 Figures

In this work, we achieve propellantless control of both cross-track and along-track separation of a satellite formation by manipulating atmospheric drag. Increasing the differential drag of one satellite with respect to another directly introduces along-track separation, while cross-track separation can be achieved by taking advantage of higher-order terms in the Earth's gravitational field that are functions of altitude. We present an algorithm for solving an n-satellite formation flying problem based on linear programming. We demonstrate this algorithm in a receeding-horizon control scheme in the presence of disturbances and modeling errors in a high-fidelity closed-loop orbital dynamics simulation. Our results show that separation distances of hundreds of kilometers can be achieved by a small-satellite formation in low-Earth orbit over a few months.

Evolutionary dynamics at the population level play a central role in creating the diversity of life on our planet. In this study, we sought to understand the origins of such population-level variation in mating systems and defensive acylsugar chemistry in Solanum habrochaites-a wild tomato species found in diverse Andean habitats in Ecuador and Peru. Using Restriction-site-Associated-DNA-Sequencing (RAD-seq) of 50 S. habrochaites accessions, we identified eight population clusters generated via isolation and hybridization dynamics of 4-6 ancestral populations. Detailed characterization of mating systems of these clusters revealed emergence of multiple self-compatible (SC) groups from progenitor self-incompatible populations in the northern part of the species range. Emergence of these SC groups was also associated with fixation of deleterious alleles inactivating acylsugar acetylation. The Amotape-Huancabamba Zone-a geographical landmark in the Andes with high endemism and isolated microhabitats-was identified as a major driver of differentiation in the northern species range, whereas large geographical distances contributed to population structure and evolution of a novel SC group in the central and southern parts of the range, where the species was also inferred to have originated. Findings presented here highlight the role of the diverse ecogeography of Peru and Ecuador in generating population differentiation, and enhance our understanding of the microevolutionary processes that create biological diversity.

Nonrecombining sex chromosomes, like the mammalian Y, often lose genes and accumulate transposable ele ments, a process termed degeneration. The correlation between suppressed recombination and degeneration is clear in animal XY systems, but the absence of recombination is confounded with other asymmetries between the X and Y. In contrast, UV sex chromosomes, like those found in bryophytes, experience symmetrical population genetic conditions. Here, we generate nearly gapless female and male chromosome-scale reference genomes of the moss Ceratodon purpureus to test for degeneration in the bryophyte UV sex chromosomes. We show that the moss sex chromosomes evolved over 300 million years ago and expanded via two chromosomal fusions. Although the sex chromosomes exhibit weaker purifying selection than autosomes, we find that suppressed recombination alone is insufficient to drive degeneration. Instead, the U and V sex chromosomes harbor thousands of broadly expressed genes, including numerous key regulators of sexual development across land plants.

Planet induced sub-structures, like annular gaps, observed in dust emission from protoplanetary disks provide a unique probe to characterize unseen young planets. While deep learning based model has an edge in characterizing the planet's properties over traditional methods, like customized simulations and empirical relations, it lacks in its ability to quantify the uncertainty associated with its predictions. In this paper, we introduce a Bayesian deep learning network "DPNNet-Bayesian" that can predict planet mass from disk gaps and provides uncertainties associated with the prediction. A unique feature of our approach is that it can distinguish between the uncertainty associated with the deep learning architecture and uncertainty inherent in the input data due to measurement noise. The model is trained on a data set generated from disk-planet simulations using the \textsc{fargo3d} hydrodynamics code with a newly implemented fixed grain size module and improved initial conditions. The Bayesian framework enables estimating a gauge/confidence interval over the validity of the prediction when applied to unknown observations. As a proof-of-concept, we apply DPNNet-Bayesian to dust gaps observed in HL Tau. The network predicts masses of $ 86.0 \pm 5.5 M_{\Earth} $, $ 43.8 \pm 3.3 M_{\Earth} $, and $ 92.2 \pm 5.1 M_{\Earth} $ respectively, which are comparable to other studies based on specialized simulations., Comment: 14 pages, 6 figures, submitted to ApJ

Additive manufacturing technology is an emerging method for rapid prototyping, which enables the creation of complex geometries by one-step fabrication processes through a layer-by-layer approach. The simplified fabrication achieved with this methodology opens the way towards a more efficient industrial production, with applications in a great number of fields such as biomedical devices. In biomedicine, blood is the gold-standard biofluid for clinical analysis. However, blood cells generate analytical interferences in many test procedures; hence, it is important to separate plasma from blood cells before analytical testing of blood samples. In this research, a custom-made resin formulation combined with a high-resolution 3D printing methodology were used to achieve a methodology for the fast prototype optimization of an operative plasma separation modular device. Through an iterative process, 17 different prototypes were designed and fabricated with printing times ranging from 5 to 12 min. The final device was evaluated through colorimetric analysis, validating this fabrication approach for the qualitative assessment of plasma separation from whole blood. The 3D printing method used here demonstrates the great contribution that this microfluidic technology will bring to the plasma separation biomedical devices market.

Habitat conversion is a major driver of tropical biodiversity loss, but its effects are poorly understood in montane environments. While community-level responses to habitat loss display strong elevational dependencies, it is unclear whether these arise via elevational turnover in community composition and interspecific differences in sensitivity, or elevational variation in environmental conditions and proximity to thermal thresholds. Here, we assess the relative importance of inter and intraspecific variation across the elevational gradient by quantifying how 243 forest-dependent bird species vary in sensitivity to landscape-scale forest loss across a 3000 m elevational gradient in the Colombian Andes. We find that species that live at lower elevations are strongly affected by loss of forest in the nearby landscape, while those at higher elevations appear relatively unperturbed, an effect that is independent of phylogeny. Conversely, we find limited evidence of intraspecific elevational gradients in sensitivity, with populations displaying similar sensitivities to forest loss, regardless of where they exist in a species’ elevational range. Gradients in biodiversity response to habitat loss thus appear to arise via interspecific gradients in sensitivity rather than proximity to climatically limiting conditions.

To capture the full spectrum of genetic risk for autism, we performed a two-stage analysis of rare de novo and inherited coding variants in 42,607 autism cases, including 35,130 new cases recruited online by SPARK. We identified 60 genes with exome-wide significance (P < 2.5 × 10-6), including five new risk genes (NAV3, ITSN1, MARK2, SCAF1 and HNRNPUL2). The association of NAV3 with autism risk is primarily driven by rare inherited loss-of-function (LoF) variants, with an estimated relative risk of 4, consistent with moderate effect. Autistic individuals with LoF variants in the four moderate-risk genes (NAV3, ITSN1, SCAF1 and HNRNPUL2; n = 95) have less cognitive impairment than 129 autistic individuals with LoF variants in highly penetrant genes (CHD8, SCN2A, ADNP, FOXP1 and SHANK3) (59% vs 88%, P = 1.9 × 10-6). Power calculations suggest that much larger numbers of autism cases are needed to identify additional moderate-risk genes.

Despite advances in understanding the metabolism of Pseudomonas putida KT2440, a promising bacterial host for producing valuable chemicals from plant-derived feedstocks, a strain capable of producing free fatty acid-derived chemicals has not been developed. Guided by functional genomics, we engineered P. putida to produce medium- and long-chain free fatty acids (FFAs) to titers of up to 670 mg/L. Additionally, by taking advantage of the varying substrate preferences of paralogous native fatty acyl-CoA ligases, we employed a strategy to control FFA chain length that resulted in a P. putida strain specialized in producing medium-chain FFAs. Finally, we demonstrate the production of oleochemicals in these strains by synthesizing medium-chain fatty acid methyl esters, compounds useful as biodiesel blending agents, in various media including sorghum hydrolysate at titers greater than 300 mg/L. This work paves the road to produce high-value oleochemicals and biofuels from cheap feedstocks, such as plant biomass, using this host.

As CPU clock speeds have stagnated and high performance computers continue to have ever higher core counts, increased parallelism is needed to take advantage of these new architectures. Traditional serial time-marching schemes can be a significant bottleneck, as many types of simulations require large numbers of time-steps which must be computed sequentially. Parallel in Time schemes, such as the Multigrid Reduction in Time (MGRIT) method, remedy this by parallelizing across time-steps, and have shown promising results for parabolic problems. However, chaotic problems have proved more difficult, since chaotic initial value problems (IVPs) are inherently ill-conditioned. MGRIT relies on a hierarchy of successively coarser time-grids to iteratively correct the solution on the finest time-grid, but due to the nature of chaotic systems, small inaccuracies on the coarser levels can be greatly magnified and lead to poor coarse-grid corrections. Here we introduce a modified MGRIT algorithm based on an existing quadratically converging nonlinear extension to the multigrid Full Approximation Scheme (FAS), as well as a novel time-coarsening scheme. Together, these approaches better capture long-term chaotic behavior on coarse-grids and greatly improve convergence of MGRIT for chaotic IVPs. Further, we introduce a novel low memory variant of the algorithm for solving chaotic PDEs with MGRIT which not only solves the IVP, but also provides estimates for the unstable Lyapunov vectors of the system. We provide supporting numerical results for the Lorenz system and demonstrate parallel speedup for the chaotic Kuramoto- Sivashinsky partial differential equation over a significantly longer time-domain than in previous works., Comment: 24 pages, 10 figures. arXiv admin note: text overlap with arXiv:2201.10441

Algebraic multigrid (AMG) is one of the most widely used solution techniques for linear systems of equations arising from discretized partial differential equations. The popularity of AMG stems from its potential to solve linear systems in almost linear time, that is with an O(n) complexity, where n is the problem size. This capability is crucial at the present, where the increasing availability of massive HPC platforms pushes for the solution of very large problems. The key for a rapidly converging AMG method is a good interplay between the smoother and the coarse-grid correction, which in turn requires the use of an effective prolongation. From a theoretical viewpoint, the prolongation must accurately represent near kernel components and, at the same time, be bounded in the energy norm. For challenging problems, however, ensuring both these requirements is not easy and is exactly the goal of this work. We propose a constrained minimization procedure aimed at reducing prolongation energy while preserving the near kernel components in the span of interpolation. The proposed algorithm is based on previous energy minimization approaches utilizing a preconditioned restricted conjugate gradients method, but has new features and a specific focus on parallel performance and implementation. It is shown that the resulting solver, when used for large real-world problems from various application fields, exhibits excellent convergence rates and scalability and outperforms at least some more traditional AMG approaches., Comment: 24 pages, 4 figures

Background: Biologic disease-modifying drugs have revolutionised the treatment of a number of chronic inflammatory diseases (CID). However, up to 60% of the patients do not have a sufficient response to treatment and there is a need for optimization of treatment strategies. Objective: To investigate if the treatment outcome of biological therapy is associated with the habitual dietary intake of fibre and red/processed meat in patients with a CID. Methods: In this multicentre prospective cohort study, we consecutively enrolled 233 adult patients with a diagnosis of Crohn's Disease, Ulcerative Colitis, Rheumatoid Arthritis (RA), Axial Spondyloarthritis, Psoriatic Arthritis and Psoriasis, for whom biologic therapy was planned, over a 3 year period. Patients with completed baseline food frequency questionnaires were stratified into a high fibre/low red and processed meat exposed group (HFLM) and an unexposed group (low fibre/high red and processed meat intake = LFHM). The primary outcome was the proportion of patients with a clinical response to biologic therapy after 14–16 weeks of treatment. Results: Of the 193 patients included in our primary analysis, 114 (59%) had a clinical response to biologic therapy. In the HFLM group (N = 64), 41 (64%) patients responded to treatment compared to 73 (56%) in the LFHM group (N = 129), but the difference was not statistically significant (OR: 1.48, 0.72–3.05). For RA patients however, HFLM diet was associated with a more likely clinical response (82% vs. 35%; OR: 9.84, 1.35–71.56). Conclusion: Habitual HFLM intake did not affect the clinical response to biological treatment across CIDs. HFLM diet in RA patients might be associated with better odds for responding to biological treatment, but this would need confirmation in a randomised trial. Trial registration: (clinicaltrials.gov), identifier [NCT03173144].

lncRAP2 is a conserved cytoplasmic lncRNA enriched in adipose tissue and required for adipogenesis. Using purification and in vivo interactome analyses, we show that lncRAP2 forms complexes with proteins that stabilize mRNAs and modulate translation, among them Igf2bp2. Surveying transcriptome-wide Igf2bp2 client mRNAs in white adipocytes reveals selective binding to mRNAs encoding adipogenic regulators and energy expenditure effectors, including adiponectin. These same target proteins are downregulated when either Igf2bp2 or lncRAP2 is downregulated, hindering adipocyte lipolysis. Proteomics and ribosome profiling show this occurs predominantly through mRNA accumulation, as lncRAP2-Igf2bp2 complex binding does not impact translation efficiency. Phenome-wide association studies reveal specific associations of genetic variants within both lncRAP2 and Igf2bp2 with body mass and type 2 diabetes, and both lncRAP2 and Igf2bp2 are suppressed in adipose depots of obese and diabetic individuals. Thus, the lncRAP2-Igf2bp2 complex potentiates adipose development and energy expenditure and is associated with susceptibility to obesity-linked diabetes.

Despite advances in understanding the metabolism of Pseudomonas putida KT2440, a promising bacterial host for producing valuable chemicals from plant-derived feedstocks, a strain capable of producing free fatty acid-derived chemicals has not been developed. Guided by functional genomics, we engineered P. putida to produce medium- and long-chain free fatty acids (FFAs) to titers of up to 670 mg/L. Additionally, by taking advantage of the varying substrate preferences of paralogous native fatty acyl-CoA ligases, we employed a strategy to control FFA chain length that resulted in a P. putida strain specialized in producing medium-chain FFAs. Finally, we demonstrate the production of oleochemicals in these strains by synthesizing medium-chain fatty acid methyl esters, compounds useful as biodiesel blending agents, in various media including sorghum hydrolysate at titers greater than 300 mg/L. This work paves the road to produce high-value oleochemicals and biofuels from cheap feedstocks, such as plant biomass, using this host.

As CPU clock speeds have stagnated, and high performance computers continue to have ever higher core counts, increased parallelism is needed to take advantage of these new architectures. Traditional serial time-marching schemes are a significant bottleneck, as many types of simulations require large numbers of time-steps which must be computed sequentially. Parallel in Time schemes, such as the Multigrid Reduction in Time (MGRIT) method, remedy this by parallelizing across time-steps, and have shown promising results for parabolic problems. However, chaotic problems have proved more difficult, since chaotic initial value problems are inherently ill-conditioned. MGRIT relies on a hierarchy of successively coarser time-grids to iteratively correct the solution on the finest time-grid, but due to the nature of chaotic systems, subtle inaccuracies on the coarser levels can lead to poor coarse-grid corrections. Here we propose a modification to nonlinear FAS multigrid, as well as a novel time-coarsening scheme, which together better capture long term behavior on coarse grids and greatly improve convergence of MGRIT for chaotic initial value problems. We provide supporting numerical results for the Lorenz system model problem.

In this chapter, we review the processes involved in the formation of planetesimals and comets. We will start with a description of the physics of dust grain growth and how this is mediated by gas-dust interactions in planet-forming disks. We will then delve into the various models of planetesimal formation, describing how these planetesimals form as well as their resulting structure. In doing so, we focus on and compare two paradigms for planetesimal formation: the gravitational collapse of particle over-densities (which can be produced by a variety of mechanisms) and the growth of particles into planetesimals via collisional and gravitational coagulation. Finally, we compare the predictions from these models with data collected by the Rosetta and New Horizons missions and that obtained via observations of distant Kuiper Belt Objects., Comment: Planetesimal Formation Review accepted for publication in Comets III

We present evidence that it is unlikely that the streaming instability (SI) can form planetesimals from mm grains inside axisymmetric pressure bumps. We conducted the largest simulation of the SI so far (7 million CPU hours), consisting of a large slice of the disk with mm grains, a solar-like dust-to-gas ratio ($Z = 0.01$), and the largest pressure bump that does not cause gravitational instability (GI) in the particle layer. We used a high resolution of $1000/H$ to resolve as many SI unstable modes as possible. The simulation produced a long-lived particle over-density far exceeding the SI criteria (i.e., a critical solid abundance to headwind parameter ratio $Z/\Pi$) where strong clumping would occur if these conditions were present over an extended region of the disk; yet we observed none. The likely reason is that the time it takes particles to cross the high-$Z/\Pi$ region ($t_{\rm cross}$) is shorter than the growth timescale of the SI ($t_{\rm grow}$). We propose an added criterion for planetesimal formation by the SI -- that $t_{\rm cross} > t_{\rm grow}$. We show that any bump larger than the one in this run would form planetesimals by the GI instead of the SI. Our results significantly restrict the pathways to planet formation: Either protoplanetary disks regularly form grains larger than 1~mm, or planetesimals do not form by the SI in axisymmetric pressure bumps. Since bumps large enough to induce the GI are likely Rossby-wave unstable, we propose that mm grains may only form planetesimals in vortices., Comment: 13 pages, 8 figures, accepted to ApJL. Updated with minor changes to improve clarity with respect to prior works

lncRAP2 is a conserved cytoplasmic lncRNA enriched in adipose tissue and required for adipogenesis. Using purification and in vivo interactome analyses, we show that lncRAP2 forms complexes with proteins that stabilize mRNAs and modulate translation, among them Igf2bp2. Surveying transcriptome-wide Igf2bp2 client mRNAs in white adipocytes reveals selective binding to mRNAs encoding adipogenic regulators and energy expenditure effectors, including adiponectin. These same target proteins are downregulated when either Igf2bp2 or lncRAP2 is downregulated, hindering adipocyte lipolysis. Proteomics and ribosome profiling show this occurs predominantly through mRNA accumulation, as lncRAP2-Igf2bp2 complex binding does not impact translation efficiency. Phenome-wide association studies reveal specific associations of genetic variants within both lncRAP2 and Igf2bp2 with body mass and type 2 diabetes, and both lncRAP2 and Igf2bp2 are suppressed in adipose depots of obese and diabetic individuals. Thus, the lncRAP2-Igf2bp2 complex potentiates adipose development and energy expenditure and is associated with susceptibility to obesity-linked diabetes.

Chondrichthyans are now widely adopted as models for examining the development and evolution of the stem gnathostome body plan. The fins of some cartilaginous fish are recognized for their plesiomorphic form and mode of muscular development, i.e., epithelial extension. Despite detailed molecular and descriptive examinations of these developmental mechanisms, there has been little contemporary examination of the ontogeny and morphology of the musculature in chondrichthyans including that of the paired fins. This gap represents a need for further examination of the developmental morphology of these appendicular musculatures to gain insight into their evolution in gnathostomes. The elephant shark is a Holocephalan, the sister group of all other chondrichthyans (Holocephali: Callorhinchus milii). Here, we use nano-CT imaging and 3D reconstructions to describe the development of the pelvic musculature of a growth series of elephant shark embryos. We also use historical descriptions from the nineteenth century and traditional dissection methods to describe the adult anatomy. This combined approach, using traditional methods and historical knowledge with modern imaging techniques, has enabled a more thorough examination of the anatomy and development of the pelvic musculature revealing that chimaeroid musculatures are more complex than previously thought. These data, when compared to extant and extinct sister taxa, are essential for interpreting and reconstructing fossil musculatures as well as understanding the evolution of paired fins.

Interactions between host and gut microbial communities are modulated by diets and play pivotal roles in immunological homeostasis and health. We show that exchanging the protein source in a high fat, high sugar, westernized diet from casein to whole-cell lysates of the non-commensal bacterium Methylococcus capsulatus Bath is sufficient to reverse western diet-induced changes in the gut microbiota to a state resembling that of lean, low fat diet-fed mice, both under mild thermal stress (T22 °C) and at thermoneutrality (T30 °C). Concomitant with microbiota changes, mice fed the Methylococcus-based western diet exhibit improved glucose regulation, reduced body and liver fat, and diminished hepatic immune infiltration. Intake of the Methylococcu-based diet markedly boosts Parabacteroides abundances in a manner depending on adaptive immunity, and upregulates triple positive (Foxp3+RORγt+IL-17+) regulatory T cells in the small and large intestine. Collectively, these data point to the potential for leveraging the use of McB lysates to improve immunometabolic homeostasis.

A common mechanism of multidrug resistance is the upregulation of efflux pumps in the cancer cells that can more rapidly export unwanted materials (e.g. cancer drugs) out of the cell, compared to sensitive cancer cells. This research seeks to overcome this mechanism by vaporizing a perfluoropentane emulsion droplet inside of a drug-containing liposome (eLiposome) that was endocytosed into a cancer cell. Folate attached to the eLiposome facilitates uptake into the cell as observed by confocal microscopy. Ultrasound was examined as a trigger to initiate the vaporization of the perfluoropentane droplet and release doxorubicin from folated eLiposomes (feLD). Two seconds of ultrasound released 78% of encapsulated doxorubicin from feLD. Doxorubicin-sensitive KB-3-1 cells and doxorubicin-resistant KB-V1 cells treated with feLD (without ultrasound) had cell viabilities of 33% and 60%, respectively. Ultrasound had negligible additional effect on the cell viability of KB-3-1 and KB-V1 cells treated with feLD (33% and 53%, respectively). We hypothesized that the doxorubicin sulfate fibers that were formed during the loading of doxorubicin into the eLiposome present a site for heterogeneous nucleation once the feLD is endocytosed by the cell, and thus droplet vaporization occurs with or without ultrasound.

Numerous nanocarriers are currently being investigated as drug delivery vehicles for transporting chemotherapeutics to cancer cells. Our research group has recently synthesized a new generation of echogenic liposomes based on the concept of encapsulating one or more nanoemulsion droplets inside a liposome (called an “eLiposome”). The concept is to use a nanoemulsion droplet with a low boiling point near body temperature, thus requiring only a small acoustic nudge to vaporize the droplet from liquid to gas and break open the eLiposome, thus releasing its contents. The purpose of this note is twofold. First, we wanted to show experimentally that eLiposomes remained stable at body temperature and retained their potential to deliver drugs through the ultrasonically-activated expansion of the emulsion nanodroplet. Additionally, we examined the physical mechanism potentially involved in the release of calcein at higher temperatures. Experimental results using calcein as a model drug confirmed the eLiposome stability at physiological temperatures and suggested that heterogeneous nucleation theory was capable of capturing the general release characteristics observed in this study. Heterogeneous nucleation of gas is possibly the main mechanism at play in passive release from eLiposomes at temperatures above body temperature. More research is needed to confirm the definitive physics of the model drug’s release from these novel nanovehicles.

Obesity and type 2 diabetes are strongly associated with adipose tissue dysfunction and impaired adipogenesis. Understanding the molecular underpinnings that control adipogenesis is thus of fundamental importance for the development of novel therapeutics against metabolic disorders. However, translational approaches are hampered as current models do not accurately recapitulate adipogenesis. Here, a scaffold-free versatile 3D adipocyte culture platform with chemically defined conditions is presented in which primary human preadipocytes accurately recapitulate adipogenesis. Following differentiation, multi-omics profiling and functional tests demonstrate that 3D adipocyte cultures feature mature molecular and cellular phenotypes similar to freshly isolated mature adipocytes. Spheroids exhibit physiologically relevant gene expression signatures with 4704 differentially expressed genes compared to conventional 2D cultures (false discovery rate < 0.05), including the concerted expression of factors shaping the adipogenic niche. Furthermore, lipid profiles of >1000 lipid species closely resemble patterns of the corresponding isogenic mature adipocytes in vivo (R2 = 0.97). Integration of multi-omics signatures with analyses of the activity profiles of 503 transcription factors using global promoter motif inference reveals a complex signaling network, involving YAP, Hedgehog, and TGFβ signaling, that links the organotypic microenvironment in 3D culture to the activation and reinforcement of PPARγ and CEBP activity resulting in improved adipogenesis.

Uveal melanoma is a rare form of melanoma with particularly poor outcomes in the metastatic setting. In contrast with cutaneous melanoma, uveal melanoma lacks BRAF mutations and demonstrates very low response rates to immune-checkpoint blockade. Our objectives were to study the transcriptomics of metastatic uveal melanoma with the intent of assessing gene pathways and potential molecular characteristics that might be nominated for further exploration as therapeutic targets. We initially analyzed transcriptional data from The Cancer Genome Atlas suggesting PI3K/mTOR and glycolysis as well as IL6 associating with poor survival. From tumor samples collected in a prospective phase II trial (A091201), we performed a transcriptional analysis of human metastatic uveal melanoma observing a novel role for epithelial-mesenchymal transition associating with survival. Specifically, we nominate and describe initial functional validation of neuropillin-1 from uveal melanoma cells as associated with poor survival and as a mediator of proliferation and migration for uveal melanoma in vitro. These results immediately nominate potential next steps in clinical research for patients with metastatic uveal melanoma.

Nonrecombining sex chromosomes, like the mammalian Y, often lose genes and accumulate transposable elements, a process termed degeneration. The correlation between suppressed recombination and degeneration is clear in animal XY systems, but the absence of recombination is confounded with other asymmetries between the X and Y. In contrast, UV sex chromosomes, like those found in bryophytes, experience symmetrical population genetic conditions. Here, we generate nearly gapless female and male chromosome-scale reference genomes of the moss Ceratodon purpureus to test for degeneration in the bryophyte UV sex chromosomes. We show that the moss sex chromosomes evolved over 300 million years ago and expanded via two chromosomal fusions. Although the sex chromosomes exhibit weaker purifying selection than autosomes, we find that suppressed recombination alone is insufficient to drive degeneration. Instead, the U and V sex chromosomes harbor thousands of broadly expressed genes, including numerous key regulators of sexual development across land plants.