Miracle-dz/UniFAR-FTUs huggingface dataset:
SMAD4 maintains the fluid shear stress set point to protect against arterial-venous malformations

Vascular networks form, remodel, and mature under the influence of both fluid shear stress (FSS) and soluble factors. Physiological FSS promotes and maintains vascular stability via synergy with bone morphogenic proteins 9 and 10 (BMP9 and BMP10). Conversely, mutation of the BMP receptors activin-like kinase 1 (ALK1), endoglin (ENG), or the downstream effector, SMAD family member 4 (SMAD4) leads to hereditary hemorrhagic telangiectasia (HHT), characterized by fragile and leaky arterial-venous malformations (AVMs). How endothelial cells (ECs) integrate FSS and BMP signals in vascular development and homeostasis and how mutations give rise to vascular malformations is not well understood. Here, we aimed to elucidate the mechanism of synergy between FSS and SMAD signaling in vascular stability and how disruption of this synergy leads to AVMs. We found that loss of Smad4 increased the sensitivity of ECs to flow by lowering the FSS set point, with resulting AVMs exhibiting features of excessive flow-mediated morphological responses. Mechanistically, loss of SMAD4 disinhibits flow-mediated KLF4-TIE2-PI3K/Akt signaling, leading to cell cycle progression–mediated loss of arterial identity due to KLF4-mediated repression of cyclin dependent Kinase (CDK) inhibitors CDKN2A and CDKN2B. Thus, AVMs caused by Smad4 deletion are characterized by chronic high flow remodeling with excessive EC proliferation and loss of arterial identity as triggering events.
Practical considerations for individualizing drug dosing in critically ill adults receiving renal replacement therapy

Critically ill patients with sepsis admitted to the intensive care unit (ICU) often present with or develop renal dysfunction requiring renal replacement therapy (RRT) in addition to antimicrobial therapy. While early and appropriate antimicrobials for sepsis have been associated with an increased probability of survival, adequate dosing is also required in these patients. Adequate dosing of antimicrobials refers to dosing strategies that achieve serum drug levels at the site of infection that are able to provide a microbiological and/or clinical response while avoiding toxicity from excessive antibiotic exposure. Therapeutic drug monitoring (TDM) is the recommended strategy to achieve this goal, however, TDM is not routinely available in all ICUs and for all antimicrobials. In the absence of TDM, clinicians are therefore required to make dosing decisions based on the clinical condition of the patient, the causative organism, the characteristics of RRT, and an understanding of the physicochemical properties of the antimicrobial. Pharmacokinetics (PK) of antimicrobials can be highly variable between critically ill patients and also within the same patient over the course of their ICU stay. The initiation of RRT, which can be in the form of intermittent hemodialysis, continuous, or prolonged intermittent therapy, further complicates the predictability of drug disposition. This variability highlights the need for individualized dosing. This review highlights the practical considerations for the clinician for antimicrobial dosing in critically ill patients receiving RRT.
Entropy Generation Analysis of the MHD Flow of Couple Stress Fluid between Two Concentric Rotating Cylinders with Porous Lining

An attempt has been made to study the entropy generation analysis of couple stress fluid flow in an annulus between two concentric rotating vertical cylinders. There is a porous lining attached to the inside of an outer cylinder. The flow is under the influence of a radial magnetic field. The flow in the annular gap is caused by rotation of the cylinders. The Stokes couple stress flow model is employed. The flow in the porous sleeve is governed by Darcy's law. The velocity, temperature, entropy generation number, Bejan number, wall shear stress and heat transfer rate at the inner and outer cylinders are obtained numerically by employing a finite difference scheme with vanishing of couple stresses on the boundary. The effect of relevant parameters on the flow and entropy generation rate are discussed and depicted through graphs.
Underestimated Factors Regarding the Use of Technology in Daily Practice of Long-Term Care: Qualitative Study Among Health Care Professionals

Background Increasing life expectancy is resulting in a growing demand for long-term care; however, there is a shortage of qualified health care professionals (HCPs) to deliver it. If used optimally, technology can provide a solution to this challenge. HCPs play an important role in the use of technology in long-term care. However, technology influences several core aspects of the work that HCPs do, and it is therefore important to have a good understanding of their viewpoint regarding the use of technology in daily practice of long-term care. Objective The aim of this study was to identify the factors that HCPs consider as relevant for using technology in daily practice of long-term care. Methods In this qualitative study, 11 focus groups were organized with 73 HCPs. The focus group discussions were guided by an innovative game, which was specifically developed for this study. The content of the game was categorized into 4 categories: health care technology and me; health care technology, the patient, and me; health care technology, the organization, and me; and facilitating conditions. The perspectives of HCPs about working with technology were discussed based on this game. The focus groups were recorded and transcribed, followed by an inductive thematic analysis using ATLAS.ti 9x (ATLAS.ti Scientific Software Development GmbH). Results Overall, 2 main domain summaries were developed from the data: technology should improve the quality of care and acceptance and use of technology in care. The first factor indicates the need for tailored and personalized care and balance between human contact and technology. The second factor addresses several aspects regarding working with technology such as trusting technology, learning to work with technology, and collaboration with colleagues. Conclusions HCPs are motivated to use technology in daily practice of long-term care when it adds value to the quality of care and there is sufficient trust, expertise, and collaboration with colleagues. Their perspectives need to be considered as they play a crucial part in the successful use of technology, transcending their role as an actor in implementation. On the basis of the findings from this study, we recommend focusing on developing technology for situations where both efficiency and quality of care can be improved; redefining the roles of HCPs and the impact of technology hereon; involving HCPs in the design process of technology to enable them to link it to their daily practice; and creating ambassadors in care teams who are enthusiastic about working with technology and can support and train their colleagues.
The core genome evolution of Lactobacillus crispatus as a driving force for niche competition in the human vaginal tract

The lower female reproductive tract is notoriously dominated by Lactobacillus species, among which Lactobacillus crispatus emerges for its protective and health‐promoting activities. Although previous comparative genome analyses highlighted genetic and phenotypic diversity within the L. crispatus species, most studies have focused on the presence/absence of accessory genes. Here, we investigated the variation at the single nucleotide level within protein‐encoding genes shared across a human‐derived L. crispatus strain selection, which includes 200 currently available human‐derived L. crispatus genomes as well as 41 chromosome sequences of such taxon that have been decoded in the framework of this study. Such data clearly pointed out the presence of intra‐species micro‐diversities that could have evolutionary significance contributing to phenotypical diversification by affecting protein domains. Specifically, two single nucleotide variations in the type II pullulanase gene sequence led to specific amino acid substitutions, possibly explaining the substantial differences in the growth performances and competition abilities observed in a multi‐strain bioreactor culture simulating the vaginal environment. Accordingly, L. crispatus strains display different growth performances, suggesting that the colonisation and stable persistence in the female reproductive tract between the members of this taxon is highly variable.
Right-dislocated pronouns in British English: the form and functions of ProTag constructions

Tags are widely acknowledged as being an important feature of colloquial British English. In this article, I examine a type of tag that has to date received little attention in the literature beyond sociolinguistic research into its interpersonal functions: right-dislocated lone pronouns, or ProTags. Biber et al. (1999) acknowledge that the demonstrative pronoun that can be used as a right-dislocated tag in conversational British English, but corpus data reveal that other pronouns can also be used as ProTags. Based on a range of examples, primarily taken from large-scale corpora, I examine the form of the ProTag construction and its functions, comparing it with other tags used in British English, particularly question tags. In common with other tags, ProTags are a classic case of language conveying more than straightforward propositional content. I consider to what extent proposed analyses of the functions of tag questions carry over to ProTags, and briefly whether this construction has been a feature of British English for longer than might at first be assumed.
Pediatric Short Bowel Syndrome: Real-World Evidence on Incidence and Hospital Resource Use From a Finnish Data Lake

Objectives: Little is known about the epidemiology and healthcare burden of pediatric intestinal failure (IF). We aimed to assess the incidence, prevalence, healthcare resource utilization (HCRU), and related costs of pediatric short bowel syndrome (SBS) using follow-up data from the largest hospital district in Finland. Methods: This retrospective registry study utilized electronic healthcare data covering all pediatric patients with SBS-IF born between 2010 and 2019 at the Hospital District of Helsinki and Uusimaa in Finland. Patients were followed from birth until the end of 2020 and compared to control patients, all from the same hospital system. Results: In total, 38 patients with SBS-IF and 1:5 matched controls were included, with median follow-up time of almost 6 years from birth. Over half of the patients were born early preterm (gestational age ≤30 weeks). The incidence of pediatric SBS-IF was 24 per 100,000 live births. The HCRU was higher compared to controls and most of the inpatient days incurred during the first year of the SBS-IF patients’ life. The average hospital-based HCRU costs were €221,000 for the first year and €57,000 for whole follow-up annually. The costs were higher for the early preterm patients and accumulated mainly from inpatient days. Conclusions: SBS-IF is a rare disease with a relatively low number of patients treated at each hospital district. The burden on the hospital system, as well as the patient’s family, is especially high at the onset as the newborns with SBS-IF spend a significant part of their first year of life in the hospital.
Alterations in the gut microbiome implicate key taxa and metabolic pathways across inflammatory arthritis phenotypes

Musculoskeletal diseases affect up to 20% of adults worldwide. The gut microbiome has been implicated in inflammatory conditions, but large-scale metagenomic evaluations have not yet traced the routes by which immunity in the gut affects inflammatory arthritis. To characterize the community structure and associated functional processes driving gut microbial involvement in arthritis, the Inflammatory Arthritis Microbiome Consortium investigated 440 stool shotgun metagenomes comprising 221 adults diagnosed with rheumatoid arthritis, ankylosing spondylitis, or psoriatic arthritis and 219 healthy controls and individuals with joint pain without an underlying inflammatory cause. Diagnosis explained about 2% of gut taxonomic variability, which is comparable in magnitude to inflammatory bowel disease. We identified several candidate microbes with differential carriage patterns in patients with elevated blood markers for inflammation. Our results confirm and extend previous findings of increased carriage of typically oral and inflammatory taxa and decreased abundance and prevalence of typical gut clades, indicating that distal inflammatory conditions, as well as local conditions, correspond to alterations to the gut microbial composition. We identified several differentially encoded pathways in the gut microbiome of patients with inflammatory arthritis, including changes in vitamin B salvage and biosynthesis and enrichment of iron sequestration. Although several of these changes characteristic of inflammation could have causal roles, we hypothesize that they are mainly positive feedback responses to changes in host physiology and immune homeostasis. By connecting taxonomic alternations to functional alterations, this work expands our understanding of the shifts in the gut ecosystem that occur in response to systemic inflammation during arthritis. Description Gut microbiome configurations and activity exhibit similarities across distinct types of inflammatory arthritis. Editor’s summary The gut microbiome has been implicated in inflammatory conditions such as inflammatory arthritis, but a head-to-head analysis of which microbes are associated with which types of inflammatory arthritis remains to be shown. Here, Thompson et al. analyzed the microbiome of 221 individuals with rheumatoid arthritis, ankylosing spondylitis, and psoriatic arthritis, as well as 219 healthy controls. The authors found taxa-level alterations that were shared across the inflammatory arthritis phenotypes and further identified microbiome-driven functional pathways that associated with inflammatory disease. Together, these data expand our understanding of how the functions of the gut microbiome may influence inflammation in humans. —Courtney Malo
Event-Based Stereo Visual Odometry With Native Temporal Resolution via Continuous-Time Gaussian Process Regression

Event-based cameras asynchronously capture individual visual changes in a scene. This makes them more robust than traditional frame-based cameras to highly dynamic motions and poor illumination. It also means that every measurement in a scene can occur at a unique time. Handling these different measurement times is a major challenge of using event-based cameras. It is often addressed in visual odometry (VO) pipelines by approximating temporally close measurements as occurring at one common time. This grouping simplifies the estimation problem but, absent additional sensors, sacrifices the inherent temporal resolution of event-based cameras. This paper instead presents a complete stereo VO pipeline that estimates directly with individual event-measurement times without requiring any grouping or approximation in the estimation state. It uses continuous-time trajectory estimation to maintain the temporal fidelity and asynchronous nature of event-based cameras through Gaussian process regression with a physically motivated prior. Its performance is evaluated on the MVSEC dataset, where it achieves $7.9\cdot 10^{-3}$ and $5.9\cdot 10^{-3}$ RMS relative error on two independent sequences, outperforming the existing publicly available event-based stereo VO pipeline by two and four times, respectively.
Multimodal Manoeuvre and Trajectory Prediction for Automated Driving on Highways Using Transformer Networks

Predicting the behaviour (i.e., manoeuvre/trajectory) of other road users, including vehicles, is critical for the safe and efficient operation of autonomous vehicles (AVs), a.k. a. , automated driving systems (ADSs). Due to the uncertain future behaviour of vehicles, multiple future behaviour modes are often plausible for a vehicle in a given driving scene. Therefore, multimodal prediction can provide richer information than single-mode prediction, enabling AVs to perform a better risk assessment. To this end, we propose a novel multimodal prediction framework that can predict multiple plausible behaviour modes and their likelihoods. The proposed framework includes a bespoke problem formulation for manoeuvre prediction, a novel transformer-based prediction model, and a tailored training method for multimodal manoeuvre and trajectory prediction. The performance of the framework is evaluated using three public highway driving datasets, namely NGSIM, highD, and exiD. The results show that our framework outperforms the state-of-the-art multimodal methods in terms of prediction error and is capable of predicting plausible manoeuvre and trajectory modes.
BayesDAG: Gradient-Based Posterior Inference for Causal Discovery

Bayesian causal discovery aims to infer the posterior distribution over causal models from observed data, quantifying epistemic uncertainty and benefiting downstream tasks. However, computational challenges arise due to joint inference over combinatorial space of Directed Acyclic Graphs (DAGs) and nonlinear functions. Despite recent progress towards efficient posterior inference over DAGs, existing methods are either limited to variational inference on node permutation matrices for linear causal models, leading to compromised inference accuracy, or continuous relaxation of adjacency matrices constrained by a DAG regularizer, which cannot ensure resulting graphs are DAGs. In this work, we introduce a scalable Bayesian causal discovery framework based on a combination of stochastic gradient Markov Chain Monte Carlo (SG-MCMC) and Variational Inference (VI) that overcomes these limitations. Our approach directly samples DAGs from the posterior without requiring any DAG regularization, simultaneously draws function parameter samples and is applicable to both linear and nonlinear causal models. To enable our approach, we derive a novel equivalence to the permutation-based DAG learning, which opens up possibilities of using any relaxed gradient estimator defined over permutations. To our knowledge, this is the first framework applying gradient-based MCMC sampling for causal discovery. Empirical evaluation on synthetic and real-world datasets demonstrate our approach's effectiveness compared to state-of-the-art baselines.
ADAPT: Efficient Multi-Agent Trajectory Prediction with Adaptation

Forecasting future trajectories of agents in complex traffic scenes requires reliable and efficient predictions for all agents in the scene. However, existing methods for trajectory prediction are either inefficient or sacrifice accuracy. To address this challenge, we propose ADAPT, a novel approach for jointly predicting the trajectories of all agents in the scene with dynamic weight learning. Our approach outperforms state-of-the-art methods in both single-agent and multi-agent settings on the Argoverse and Interaction datasets, with a fraction of their computational overhead. We attribute the improvement in our performance: first, to the adaptive head augmenting the model capacity without increasing the model size; second, to our design choices in the endpoint-conditioned prediction, reinforced by gradient stopping. Our analyses show that ADAPT can focus on each agent with adaptive prediction, allowing for accurate predictions efficiently. https://KUIS-AI.github. io/adapt
Phase Transitions in Long-Range Random Field Ising Models in Higher Dimensions

We extend the recent argument by Ding and Zhuang from nearest-neighbor to long-range interactions and prove the phase transition in the class of ferromagnetic random field Ising models. Our proof combines a generalization of Fr\"ohlich-Spencer contours to the multidimensional setting, proposed by two of us, with the coarse-graining procedure introduced by Fisher, Fr\"ohlich and Spencer. The result shows that the Ding-Zhuang strategy is also useful for interactions $J_{xy}=|x-y|^{- \alpha}$ when $\alpha>d$ in dimension $d\geq 3$ if we have a suitable system of contours. We can consider i.i. d. random fields with Gaussian or Bernoulli distributions. Our main result is an alternative proof that does not use the Renormalization Group Method (RGM), since Bricmont and Kupiainen claimed that the RGM should also work on this generality.
Formulation and Implementation of Frequency-Dependent Linear Response Properties with Relativistic Coupled Cluster Theory for GPU-Accelerated Computer Architectures.

We present the development and implementation of relativistic coupled cluster linear response theory (CC-LR), which allows the determination of molecular properties arising from time-dependent or time-independent electric, magnetic, or mixed electric-magnetic perturbations (within a common gauge origin for the magnetic properties) as well as taking into account the finite lifetime of excited states in the framework of damped response theory. We showcase our implementation, which is capable to offload the computationally intensive tensor contractions characteristic of coupled cluster theory onto graphical processing units, in the calculation of (a) frequency-(in)dependent dipole-dipole polarizabilities of IIB atoms and selected diatomic molecules, with a particular emphasis on the calculation of valence absorption cross sections for the I2 molecule; (b) indirect spin-spin coupling constants for benchmark systems such as the hydrogen halides (HX, X = F-I) as well the H2Se-H2O dimer as a prototypical system containing hydrogen bonds; and (c) optical rotations at the sodium D line for hydrogen peroxide analogues (H2Y2, Y = O, S, Se, Te). Thanks to this implementation, we are able to show the similarities in performance, but often the significant discrepancies, between CC-LR and approximate methods such as density functional theory. Comparing standard CC response theory with the flavor based upon the equation of motion formalism, we find that for valence properties such as polarizabilities, the two frameworks yield very similar results across the periodic table as found elsewhere in the literature; for properties that probe the core region, such as spin-spin couplings, on the other hand, we show a progressive differentiation between the two as relativistic effects become more important. Our results also suggest that as one goes down the periodic table, it may become increasingly difficult to measure pure optical rotation at the sodium D line due to the appearance of absorbing states.
Dwarf (Twin) Neutron Stars I: Did GW170817 Involve One?

Dwarf neutron stars are stable twins of neutron stars but with a maximum mass less than that of neutron stars. Their existence brings into concordance the seemingly conflicting information on the size of neutron stars inferred from gravitational waves from GW170817, from the NICER mission, and from the PREX-II experiment. Their distinctive characteristics lead to rich and falsifiable predictions that are expected to be tested in the near future. If corroborated, the existence of dwarf neutron stars would substantially improve our understanding of the QCD phase diagram and offer valuable insights into the dark sector.
On the dynamics of endomorphisms of the direct product of two free groups

We prove that Brinkmann's problems are decidable for endomorphisms of $F_n\times F_m$: given $(x,y),(z,w)\in F_n\times F_m$ and $\Phi\in \text{End}(F_n\times F_m)$, it is decidable whether there is some $k\in \mathbb N$ such that $(x,y)\Phi^k=(z,w)$ (or $(x,y)\Phi^k\sim(z,w)$). We also prove decidability of a two-sided version of Brinkmann's conjugacy problem for injective endomorphisms which, from the work of Logan, yields a solution to the conjugacy problem in ascending HNN-extensions of $F_n\times F_m$. Finally, we study the dynamics of automorphisms of $F_n\times F_m$ at the infinity, proving that every point in a continuous extension of an automorphism to the completion is either periodic or wandering, implying that the dynamics is asymptotically periodic, as occurs in the free and free-abelian times free cases.