Miracle-dz/UniFAR-FTUs huggingface dataset:
The safety and persistence of intravenous iloprost in systemic sclerosis.

INTRODUCTION Vasculopathy is a crucial feature of systemic sclerosis (SSc). It occurs in almost every patient with SSc, with Raynaud's phenomenon (RP) and digital ulcers (DU) having a great impact on the quality of patients' lives. Intravenous (IV) iloprost, a synthetic analogue of prostacyclin, is broadly used to treat RP and DU secondary to SSc. Currently, there is no standard protocol defined for the iloprost treatment of SSc-associated RP and DU, and, consequently, the management of this treatment is largely based on each centre's experience. OBJECTIVE The objective of this study is to evaluate the safety profile of a particular scheme of IV iloprost used in our centre as the standard treatment of SSc-related vascular complications. METHODS We retrospectively evaluated the clinical records of SSc patients, classified according to the 2013 European Alliance of Associations for Rheumatology (EULAR) criteria (31) with SSc-related DU and/or severe RP not responsive to CCB, receiving or who have received IV iloprost infusions from January 1st 2011 to March 31st 2021 Results: Within this time frame, 60 patients (n=44 for DU; n=16 for severe RP) were treated with a monthly 10-hour IV iloprost perfusion with a dosing regimen adapted to individual tolerance. Forty-nine of these 60 patients (81.7%) were on iloprost for more than one year. Within 12 months of therapy, 40 patients have healed the DUs (90.9%), with only 4 patients maintaining active DUs. A significant clinical improvement in RP at 12 months was observed in 87.5% (n=14/16) of SSc patients with severe RP. Eleven AE implying treatment dose/frequency adjustments or suspension were recorded (18.3% of patients): severe headache (n=5), hypotension (n=3), tachycardia (n=1), flushing (n=1) and generalised erythroderma (n=1). In all patients, the perfusion rate was reduced in the following treatment sessions with good tolerance, with the exception of the patient with the generalised erythroderma reaction, who suspended the perfusion and was later switched to bosentan. After a mean follow-up time of 6.9 (+/-) 4.0 years of treatment (range 0.06-22), 24 patients (40%) stopped the therapy, 14 (58.3%) of whom due to clinical improvement. The overall 5-, and 10-year survival rates of IV iloprost were 68.2% and 55.6%, respectively. CONCLUSION SSc patients who received this flexible IV iloprost regimen achieved clinical improvement, reflected in the high persistence rate of the drug, with a good tolerability profile. In addition, most side effects were mild and easily managed.
High Wing-Loading Correlates with Dive Performance in Birds, Suggesting a Strategy to Reduce Buoyancy.

Diving birds are regarded as a classic example of morphological convergence (Darwin 1859). Divers tend to have small wings extending from rotund bodies, requiring many volant species to fly with rapid wingbeats, and rendering others flightless (Darwin 1839; Simpson 1946). The high wing-loading of diving birds is frequently associated with the challenge of using forelimbs adapted for flight for locomotion in a "draggier" fluid, but this does not explain why species that rely exclusively on their feet to dive should have relatively small wings, as well. Therefore, others have hypothesized that ecological factors shared by wing-propelled and foot-propelled diving birds drive the evolution of high wing-loading. Following a reexamination of the aquatic habits of birds, we tested between hypotheses seeking to explain high wing-loading in divers using new comparative data and phylogenetically informed analyses. We found little evidence that wing-propelled diving selects for small wings, as wing-propelled and foot-propelled species share similar wing-loadings. Instead, our results suggest that selection to reduce buoyancy has driven high wing-loading in divers, offering insights for the development of bird-like aquatic robots.
Optimization of Semiautomated Calibration Algorithm of Multichannel Electrotactile Feedback for Myoelectric Hand Prosthesis

The main drawback of the commercially available myoelectric hand prostheses is the absence of somatosensory feedback. We recently developed a feedback interface for multiple degrees of freedom myoelectric prosthesis that allows proprioceptive and sensory information (i.e., grasping force) to be transmitted to the wearer instantaneously. High information bandwidth is achieved through intelligent control of spatiotemporal distribution of electrical pulses over a custom-designed electrode array. As electrotactile sensations are location-dependent and the developed interface requires that electrical stimuli are perceived to be of the same intensity on all locations, a calibration procedure is of high importance. The aim of this study was to gain more insight into the calibration procedure and optimize this process by leveraging a priori knowledge. For this purpose, we conducted a study with 9 able-bodied subjects performing 10 sessions of the array electrode calibration. Based on the collected data, we optimized and simplified the calibration procedure by adapting the initial (baseline) amplitude values in the calibration algorithm. The results suggest there is an individual pattern of stimulation amplitudes across 16 electrode pads for each subject, which is not affected by the initial amplitudes. Moreover, the number of user actions performed and the time needed for the calibration procedure are significantly reduced by the proposed methodology.
Sex-specific and social experience-dependent oxytocin–endocannabinoid interactions in the nucleus accumbens: implications for social behaviour

Oxytocin modulates social behaviour across diverse vertebrate taxa, but the precise nature of its effects varies across species, individuals and lifetimes. Contributing to this variation is the fact that oxytocin's physiological effects are mediated through interaction with diverse neuromodulatory systems and can depend on the specifics of the local circuits it acts on. Furthermore, those effects can be influenced by both genetics and experience. Here we discuss this complexity through the lens of a specific neuromodulatory system, endocannabinoids, interacting with oxytocin in the nucleus accumbens to modulate prosocial behaviours in prairie voles. We provide a survey of current knowledge of oxytocin–endocannabinoid interactions in relation to social behaviour. We review in detail recent research in monogamous female prairie voles demonstrating that social experience, such as mating and pair bonding, can change how oxytocin modulates nucleus accumbens glutamatergic signalling through the recruitment of endocannabinoids to modulate prosocial behaviour toward the partner. We then discuss potential sex differences in experience-dependent modulation of the nucleus accumbens by oxytocin in voles based on new data in males. Finally, we propose that future oxytocin-based precision medicine therapies should consider how prior social experience interacts with sex and genetics to influence oxytocin actions. This article is part of the theme issue ‘Interplays between oxytocin and other neuromodulators in shaping complex social behaviours’.
Analysis of Stator Slots and Rotor Pole Pairs Combinations of Rotor-Permanent Magnet Flux-Switching Machines

This paper investigates the influence of stator slots and rotor pole pairs combinations on torque performances in rotor permanent magnet flux switching (RPM-FS) machines. Based on a magnetomotive force (MMF) permeance model, the candidates of stator slots and rotor pole pairs combinations with higher torque capability can be determined by analyzing the PM-MMF and winding factor. Meanwhile, the candidates with a lower torque ripple can be obtained by referring to the cogging torque, which is related to the greatest common divisor of stator slots and rotor pole pairs. In addition, from the field modulation principle, the RPM-FS machines with the same fundamental magnetic loadings and winding factors exhibit identical fundamental harmonic torque, but different modulation harmonic components. Finally, four candidates with attractive torque performance are chosen, and the characteristics are verified by finite-element analysis and experiments.
Quantum trajectories under frequent measurements in a non-Markovian environment

In this work we generalize the quantum trajectory (QT) theory from Markovian to non-Markovian environments. We model the non-Markovian environment by using a Lorentzian spectral density function with bandwidth $(\mathrm{\ensuremath{\Lambda}})$, and find a perfect ``scaling'' property with the measurement frequency $({\ensuremath{\tau}}^{\ensuremath{-}1})$ in terms of the scaling variable $x=\mathrm{\ensuremath{\Lambda}}\ensuremath{\tau}$. Our result bridges the gap between the existing QT theory and the Zeno effect, by rendering them as two extremes corresponding to $x\ensuremath{\rightarrow}\ensuremath{\infty}$ and $x\ensuremath{\rightarrow}0$, respectively. This $x$-dependent criterion improves the idea of using $\ensuremath{\tau}$ alone and quantitatively identifies the validity condition of the conventional QT theory.
Phronesis: Efficient Performance Modeling for High-dimensional Configuration Tuning

We present Phronesis, a learning framework for efficiently modeling the performance of data analytic workloads as a function of their high-dimensional software configuration parameters. Accurate performance models are useful for efficiently optimizing data analytic performance. Phronesis explicitly considers the error decomposition in statistical learning and implications for efficient data acquisition and model growth strategies in performance modeling. We demonstrate Phronesis with three popular machine learning models commonly used in performance tuning: neural network, random forest, and regression spline. We implement and evaluate it for Spark configuration parameters. We show that Phronesis significantly reduces data collection time for training predictive models by up to 57% and 37%, on average, compared to state-of-the-art techniques in building Spark performance models. Furthermore, we construct a configuration autotuning pipeline based on Phronesis. Our results indicate up to 30% gains in performance for Spark workloads over previous, state-of-the-art tuning strategies that use high-dimensional models.
Brief Announcement: The (Limited) Power of Multiple Identities: Asynchronous Byzantine Reliable Broadcast with Improved Resilience through Collusion

We present a new model for (asynchronous) byzantine reliable broadcast to investigate the potential of secret collusion between honest players. To model the collusion, we assume that each honest player has k > 1 distinct communication identities over which they can send and receive messages. A player can obtain these identities - for example - by joining a distributed system under several aliases.
Achieving Sublinear Complexity under Constant T in T-interval Dynamic Networks

This paper considers standard T-interval dynamic networks, where the N nodes in the network proceed in lock-step rounds, and where the topology of the network can change arbitrarily from round to round, as determined by an adversary. The adversary promises that in every T consecutive rounds, the T (potentially different) topologies in those T rounds contain a common connected subgraph that spans all nodes. Within such a context, we propose novel algorithms for solving some fundamental distributed computing problems such as Count/Consensus/Max. Our algorithms are the first algorithms whose complexities do not contain an Ømega(N) term, under constant T values. Previous sublinear algorithms require significantly larger T values.
Dynamic System Diversification for Securing Cloud-based IoT Subnetworks

Remote exploitation attacks use software vulnerabilities to penetrate through a network of Internet of Things (IoT) devices. This work addresses defending against remote exploitation attacks on vulnerable IoT devices. As an attack mitigation strategy, we assume it is not possible to fix all the vulnerabilities and propose to diversify the open-source software used to manage IoT devices. Our approach is to deploy dynamic cloud-based virtual machine proxies for physical IoT devices. Our architecture leverages virtual machine proxies with diverse software configurations to mitigate vulnerable and static software configurations on physical devices. We develop an algorithm for selecting new configurations based on network anomaly detection signals to learn vulnerable software configurations on IoT devices, automatically shifting towards more secure configurations. Cloud-based proxy machines mediate requests between application clients and vulnerable IoT devices, facilitating a dynamic diversification system. We report on simulation experiments to evaluate the dynamic system. Two models of powerful adversaries are introduced and simulated against the diversified defense strategy. Our experiments show that a dynamically diversified IoT architecture can be invulnerable to large classes of attacks that would succeed against a static architecture.
Review article: Follow‐up of coeliac disease

Coeliac disease is a lifelong immune‐mediated enteropathy with systemic features associated with increased morbidity and modestly increased mortality. Treatment with a strict gluten‐free diet improves symptoms and mucosal damage but is not curative and low‐level gluten intake is common despite strict attempts at adherence. Regular follow‐up after diagnosis is considered best‐practice however this is executed poorly in the community with the problem compounded by the paucity of data informing optimal approaches. The aim of dietary treatment is to resolve symptoms, reduce complication risk and improve quality of life. It follows that the goals of monitoring are to assess dietary adherence, monitor disease activity, assess symptoms and screen for complications. Mucosal disease remission is regarded a key measure of treatment success as healing is associated with positive health outcomes. However, persistent villous atrophy is common, even after many years of a gluten‐free diet. As the clinical significance of asymptomatic enteropathy is uncertain the role for routine follow‐up biopsies remains contentious. Symptomatic non‐responsive coeliac disease is common and with systematic follow‐up a cause is usually found. Effective models of care involving the gastroenterologist, dietitian and primary care doctor will improve the consistency of long‐term management and likely translate into better patient outcomes. Identifying suitable treatment targets linked to long‐term health is an important goal.
Single-cell reference mapping to construct and extend cell-type hierarchies

Single-cell genomics is now producing an ever-increasing amount of datasets that, when integrated, could provide large-scale reference atlases of tissue in health and disease. Such atlases increase the scale and generalizability of analyses and enable combining knowledge generated by individual studies. Specifically, individual studies often differ regarding cell annotation terminology and depth, with different groups often using distinct terminology. Understanding how annotations are related and complement each other would mark a major step towards a consensus-based cell-type annotation reflecting the latest knowledge. Whereas recent computational techniques, referred to as “reference mapping” methods, facilitate the usage and expansion of existing reference atlases by mapping new datasets (i.e., queries) onto an atlas; a systematic approach towards harmonizing dataset-specific cell-type terminology and annotation depth is still lacking. Here, we present “treeArches”, a framework to automatically build and extend reference atlases while enriching them with an updatable hierarchy of cell-type annotations across different datasets. We demonstrate various use cases, from automatically resolving relations between reference and query cell types to identifying unseen cell types absent in the reference, such as disease-associated cell states. We envision treeArches enabling data-driven construction of consensus atlas-level cell-type hierarchies and facilitating efficient usage of reference atlases.
Associative nitrogen fixation could be common in South African mesic grassland

Non-symbiotic nitrogen-fixing bacterial diazotrophs closely associated with the roots of grasses probably contribute most of the new nitrogen acquired to sustain productive natural grasslands, yet their ecology is poorly understood, especially in southern Africa. We looked for genetic evidence, using qPCR and gel electrophoresis, for the presence of the bacterial nifH gene associated with the roots of four grass species (20 plants each) in a mesic grassland in South Arica, which would indicate the potential for N fixation by diazotrophs. Grasses most tolerant of low N (Aristida junciformis) were predicted to harbour the most diazotrophs, especially compared to those most responsive to fertiliser N (Eragrostis curvula). However, the nifH gene was found in all 80 root samples and did not differ in copy number between species. Sequencing of a representative sample confirmed the identity of the nifH gene. The recently burned half of the grassland had 60% more nifH genes than the area burned 15 months previously, suggesting that grass growth stimulated by fire could recruit diazotrophs. Given their ubiquity and importance in the N economy of grasslands, research is required to characterise root-associated diazotroph communities, quantify their N fixation rates, and understand their environmental controls.
Competition between endogenous and exogenous attention delays the selection of task-relevant working memory content.

Working memory (WM) is a capacity- and duration-limited system that forms a temporal bridge between sensory phenomena and action. Capacity limits in WM necessitate the existence of external selection mechanisms that control access to this system (i.e., input gating), while changing behavioral demands necessitate the existence of internal selection mechanisms that prioritize existing WM representations for action (i.e., output gating). Whether similar mechanisms mediate WM input and output gating is unclear. We examined this possibility by exploiting a well-known distinction between top-down (endogenous) and bottom-up (exogenous) selection. Specifically, we examined how endogenous and exogenous factors compete to control the selection of WM content by examining their effects on EEG decoding performance. We found no evidence for a reflexive selection of task-irrelevant WM content when endogenous and exogenous factors conflicted. Instead, the selection of task-relevant WM content was delayed when these factors conflicted compared to when they were aligned. Thus, unlike external attention where the real-time balance of competition between endogenous and exogenous factors determines what information is selected, the selection of task-relevant WM content is delayed until competition between endogenous and exogenous factors is resolved.
The contraction-expansion behaviour in the demosponge Tethya wilhelma is diurnal and light-controlled

Sponges (phylum Porifera) are metazoans without muscles and nervous system. Still, they perform coordinated behaviours, such as whole body contrations. Previous studies have indicated diurnal variability in number of contractions, and in expression of circadian clock genes. Here we show that diurnal patterns are present in the contraction-expansion behaviour of the demosponge Tethya wilhelma using infrared videography and a simulated night/day-cycle including sunset and sunrise mimic. In addition, we show that this behaviour is at least strongly influenced by the ambient light intensity and therefore implicates light-sensing capabilities in this sponge species. This is backed by our finding that T. wilhelma consistently contracts at sunrise, and that this pattern disappears both when the sponge is kept in constant darkness and when in constant light.
svCapture: efficient and specific detection of very low frequency structural variant junctions by error-minimized capture sequencing

Error-corrected sequencing of genomic targets enriched by probe-based capture has become a standard approach for detecting single-nucleotide variants (SNVs) and small insertion/deletions (indels) present at very low variant allele frequencies. Less attention has been given to strategies for comparable detection of rare structural variant (SV) junctions, where different error mechanisms must be addressed. Working from cell samples with known SV properties, we demonstrate that Duplex Sequencing (DuplexSeq), which demands confirmation of variants on both strands of a source DNA molecule, eliminates false SV junctions arising from chimeric PCR. DuplexSeq could not address frequent intermolecular ligation artifacts that arise during Y-adapter addition prior to strand denaturation without requiring multiple source molecules. In contrast, tagmentation libraries coupled with data filtering based on strand family size greatly reduced both artifact classes and enabled efficient and specific detection of even single-molecule SV junctions. The throughput of SV capture sequencing (svCapture) and the high base-level accuracy of DuplexSeq provided detailed views of the microhomology profile and limited occurrence of de novo SNVs near the junctions of hundreds of sub-clonal and newly created SVs, suggesting end joining as a predominant formation mechanism. The open source svCapture pipeline enables rare SV detection as a routine addition to SNVs/indels in properly prepared capture sequencing libraries.
Using colony size to measure fitness in Saccharomyces cerevisiae

Competitive fitness assays in liquid culture have been a mainstay for characterizing experimental evolution of microbial populations. Growth of microbial strains has also been extensively characterized by colony size and could serve as a useful alternative if translated to per generation measurements of relative fitness. To examine fitness based on colony size, we established a relationship between cell number and colony size for strains of Saccharomyces cerevisiae robotically pinned onto solid agar plates in a high-density format. This was used to measure growth rates and estimate relative fitness differences between evolved strains and their ancestors. After controlling for edge effects through both normalization and agar-trimming, we found that fitness based on colony size is as sensitive as competitive fitness assays grown in liquid medium. While fitnesses determined from liquid and solid mediums were not equivalent, our results demonstrate that colony size provides a sensitive means of measuring fitness that is particularly well suited to measurements across many environments.
Transformation of acoustic information to sensory decision variables in the parietal cortex

The process by which sensory evidence contributes to perceptual choices requires an understanding of its transformation into decision variables. Here, we address this issue by evaluating the neural representation of acoustic information in auditory cortex-recipient parietal cortex while gerbils either performed an auditory discrimination task or while they passively listened to identical acoustic stimuli. During task performance, decoding performance of simultaneously recorded parietal neurons reflected psychometric sensitivity. In contrast, decoding performance during passive listening was significantly reduced. Principal component and geometric analyses each revealed the emergence of decision-relevant, linearly separable manifolds, but only during task engagement. Finally, using a clustering analysis, we found subpopulations of neurons that may reflect the encoding of separate segments during task performance: stimulus integration and motor preparation or execution. Taken together, our findings demonstrate how parietal cortex neurons integrate and transform encoded auditory information to guide sound-driven perceptual decisions.