Miracle-dz/UniFAR-FTUs huggingface dataset:
Clostridioides difficile S-Layer Protein A (SlpA) Serves as a General Phage Receptor

Phage therapy represents an interesting alternative to treat Clostridioides difficile infections because, contrary to antibiotics, most phages are highly species specific, thereby sparing the beneficial gut microbes that protect from infection. However, currently available phages against C. difficile have a narrow host range and target members from only one or a few PCR ribotypes. ABSTRACT Therapeutic bacteriophages (phages) are being considered as alternatives in the fight against Clostridioides difficile infections. To be efficient, phages should have a wide host range, buthe lack of knowledge about the cell receptor used by C. difficile phages hampers the rational design of phage cocktails. Recent reports suggested that the C. difficile surface layer protein A (SlpA) is an important phage receptor, but available data are still limited. Here, using the epidemic R20291 strain and its FM2.5 mutant derivative lacking a functional S-layer, we show that the absence of SlpA renders cells completely resistant to infection by ϕCD38-2, ϕCD111, and ϕCD146, which normally infect the parental strain. Complementation with 12 different S-layer cassette types (SLCTs) expressed from a plasmid revealed that SLCT-6 also allowed infection by ϕCD111 and SLCT-11 enabled infection by ϕCD38-2 and ϕCD146. Of note, the expression of SLCT-1, -6, -8, -9, -10, or -12 conferred susceptibility to infection by 5 myophages that normally do not infect the R20291 strain. Also, deletion of the D2 domain within the low-molecular-weight fragment of SlpA was found to abolish infection by ϕCD38-2 and ϕCD146 but not ϕCD111. Altogether, our data suggest that many phages use SlpA as their receptor and, most importantly, that both siphophages and myophages target SlpA despite major differences in their tail structures. Our study therefore represents an important step in understanding the interactions between C. difficile and its phages. IMPORTANCE Phage therapy represents an interesting alternative to treat Clostridioides difficile infections because, contrary to antibiotics, most phages are highly species specific, thereby sparing the beneficial gut microbes that protect from infection. However, currently available phages against C. difficile have a narrow host range and target members from only one or a few PCR ribotypes. Without a clear comprehension of the factors that define host specificity, and in particular the host receptor recognized by phages, it is hard to develop therapeutic cocktails in a rational manner. In our study, we provide clear and unambiguous experimental evidence that SlpA is a common receptor used by many siphophages and myophages. Although work is still needed to define how a particular phage receptor-binding protein binds to a specific SLCT, the identification of SlpA as a common receptor is a major keystone that will facilitate the rational design of therapeutic phage cocktails against clinically important strains.
origamiFISH allows universal, label-free, single molecule visualization of DNA origami nanodevices across biological samples

Structural DNA nanotechnology enables user-prescribed design of DNA nanostructures (DNs) for biological applications, but how DN design determines their bio-distribution and cellular interactions remain poorly understood. One challenge is that current methods for tracking DN fates in situ, including fluorescent-dye labeling, suffer from low sensitivity and dye-induced artifacts. Here we present origamiFISH, a label-free and universal method for single-molecule fluorescence detection of DNA origami nanostructures in cells and tissues. origamiFISH targets pan-DN scaffold sequences with hybridization chain reaction (HCR) probes to achieve thousand-fold signal amplification. We identify cell-type and shape-specific spatiotemporal uptake patterns within 1 minute of uptake and at picomolar DN concentrations, 10,000x lower than field standards. We additionally optimized compatibility with immunofluorescence and tissue clearing to visualize DN distribution within tissue cryo/vibratome-sections, slice cultures, and whole-mount organoids. Together, origamiFISH enables faithful mapping of DN interactions across subcellular and tissue barriers for guiding the development of DN-based therapeutics.
Effects of Oil Phase on the Inversion of Pickering Emulsions Stabilized by Palmitic Acid Decorated Silica Nanoparticles

Pickering emulsions stabilized by the interaction of palmitic acid (PA) and silica nanoparticles (SiNPs) at the water/oil interface have been studied using different alkane oil phases. The interaction of palmitic acid and SiNPs has a strong synergistic character in relation to the emulsion stabilization, leading to an enhanced emulsion stability in relation to that stabilized only by the fatty acid. This results from the formation of fatty acid-nanoparticle complexes driven by hydrogen bond interactions, which favor particle attachment at the fluid interface, creating a rigid armor that minimizes droplet coalescence. The comparison of emulsions obtained using different alkanes as the oil phase has shown that the hydrophobic mismatch between the length of the alkane chain and the C16 hydrophobic chain of PA determines the nature of the emulsions, with the solubility of the fatty acid in the oil phase being a very important driving force governing the appearance of phase inversion.
Feasibility study for a Cryogenic On-Orbit Liquid Depot-Storage, Acquisition and Transfer (COLD-SAT) satellite

This feasibility study presents the conceptual design of a spacecraft for performing a series of cryogenic fluid management flight experiments. This spacecraft, the Cryogenic On-Orbit Liquid Depot-Storage, Acquisition, and Transfer (COLD-SAT) satellite, will use liquid hydrogen as the test fluid, be launched on a Delta expendable launch vehicle, and conduct a series of experiments over a two to three month period. These experiments will investigate the physics of subcritical cryogens in the low gravity space environment to characterize their behavior and to correlate the data with analytical and numerical models of in-space cryogenic fluid management systems. Primary technologies addressed by COLD-SAT are: (1) pressure control; (2) chilldown; (3) no-vent fill; (4) liquid acquisition device fill; (5) pressurization; (6) low-g fill and drain; (7) liquid acquisition device expulsion; (8) line chilldown; (9) thermodynamic state control; and (10) fluid dumping.
PopArt: Efficient Sparse Regression and Experimental Design for Optimal Sparse Linear Bandits

In sparse linear bandits, a learning agent sequentially selects an action and receive reward feedback, and the reward function depends linearly on a few coordinates of the covariates of the actions. This has applications in many real-world sequential decision making problems. In this paper, we propose a simple and computationally efficient sparse linear estimation method called PopArt that enjoys a tighter $\ell_1$ recovery guarantee compared to Lasso (Tibshirani, 1996) in many problems. Our bound naturally motivates an experimental design criterion that is convex and thus computationally efficient to solve. Based on our novel estimator and design criterion, we derive sparse linear bandit algorithms that enjoy improved regret upper bounds upon the state of the art (Hao et al., 2020), especially w.r. t. the geometry of the given action set. Finally, we prove a matching lower bound for sparse linear bandits in the data-poor regime, which closes the gap between upper and lower bounds in prior work.
Are Neural Click Models Pointwise IPS Rankers?

Inverse-propensity scoring and neural click models are two popular methods for learning rankers from user clicks affected by position bias. Despite their prevalence, the two methodologies are rarely directly compared on equal footing. In this work, we focus on the pointwise learning setting to compare the theoretical differences of both approaches and present a thorough empirical comparison on the prevalent semi-synthetic evaluation setup in unbiased learning-to-rank. We show theoretically that neural click models, similarly to IPS rankers, optimize for the true document relevance when the position bias is known. However, our work also finds small but significant empirical differences between both approaches indicating that neural click models might be affected by position bias when learning from shared, sometimes conflicting, features instead of treating each document separately.
RRGparbank: A Parallel Role and Reference Grammar Treebank

This paper describes the first release of RRGparbank, a multilingual parallel treebank for Role and Reference Grammar (RRG) containing annotations of George Orwell’s novel 1984 and its translations. The release comprises the entire novel for English and a constructionally diverse and highly parallel sample (“seed”) for German, French and Russian. The paper gives an overview of annotation decisions that have been taken and describes the adopted treebanking methodology. Finally, as a possible application, a multilingual parser is trained on the treebank data. RRGparbank is one of the first resources to apply RRG to large amounts of real-world data. Furthermore, it enables comparative and typological corpus studies in RRG. And, finally, it creates new possibilities of data-driven NLP applications based on RRG.
THE HP-VERSION OF THE FINITE ELEMENT METHOD UNDER NUMERICAL QUADRATURE RULES

we consider the hp-version to solve non-constant coefficients elliptic equations with Dirichlet boundary conditions on a bounded polygonal domain in . In [6], M. Suri obtained an optimal error-estimate for the hp-version: . This optimal result follows under the assumption that all integrations are performed exactly. In practice, the integrals are seldom computed exactly. The numerical quadrature rule scheme is needed to compute the integrals in the variational formulation of the discrete problem. In this paper we consider a family of numerical quadrature rules satisfying certain properties, which can be used for calculating the integrals. Under the numerical quadrature rules we will give the variational form of our non-constant coefficients elliptic problem and derive an error estimate of .
Asteroseismology of DAV white dwarf stars

The author reviews the seismological structural determinations of ZZ Ceti stars done to date, and supplement these with additional preliminary determinations of his own. He compares the constraints on the hydrogen layer mass to see what trends emerge and also determines if the observed hydrogen layer masses are consistent with proposed theories. He then looks ahead to the prospects of further DAV white dwarf seismology.
Masses of globular clusters

Central velocity dispersions have been derived for 10 globular clusters from high dispersion (6.7A mm-1) coude spectra of the integrated light. Two methods were used. The first involved the comparison of the cluster spectra with star spectra convolved with an appropriate velocity distribution function. This is the method used often for velocity dispersion determinations from spectra of the integrated light of galaxies (e.g. Morton and Chevalier 1972). Fourier techniques were used in the second method. Power spectra were obtained from the Fourier transformed spectral-intensity data of both the stars and the clusters. The star power spectra were multiplied by the transformed velocity distribution function and compared with the cluster power spectra. The advantages accruing from use of the Fourier method over the direct comparison method are (1) use of much more of the information contained in the original spectra; (2) greater accuracy arising from the increased sensitivity to changes in the velocity dispersion and (J) lessening of the necessity for critical local matching in the star - cluster line strengths. Surface density distributions have been derived from photoelectric surface photometry (using centered apertures and small aperture drifts across the cluster) and from star counts. These surface density distributions were then compared with the theoretical distributions given by King (1966a). These theoretical surface density distributions are derived from self-consistent single mass models using a realistic velocity distribution function. Two characteristic lengths, the core radius rc and the tidal cutoff rt, obtained from the comparison of the theoretical and observed surface density distributions are then usBd, along with the velocity dispersion, to derive masses for the 10 clusters. For comparison, masses are also derived by the r 1/4 law/virial theorem method. The mass-to-light ratio is obtained and the form of the luminosity function in globular clusters is discussed.
Towards Evaluation of Cross-document Coreference Resolution Models Using Datasets with Diverse Annotation Schemes

Established cross-document coreference resolution (CDCR) datasets contain event-centric coreference chains of events and entities with identity relations. These datasets establish strict definitions of the coreference relations across related tests but typically ignore anaphora with more vague context-dependent loose coreference relations. In this paper, we qualitatively and quantitatively compare the annotation schemes of ECB+, a CDCR dataset with identity coreference relations, and NewsWCL50, a CDCR dataset with a mix of loose context-dependent and strict coreference relations. We propose a phrasing diversity metric (PD) that encounters for the diversity of full phrases unlike the previously proposed metrics and allows to evaluate lexical diversity of the CDCR datasets in a higher precision. The analysis shows that coreference chains of NewsWCL50 are more lexically diverse than those of ECB+ but annotating of NewsWCL50 leads to the lower inter-coder reliability. We discuss the different tasks that both CDCR datasets create for the CDCR models, i.e., lexical disambiguation and lexical diversity. Finally, to ensure generalizability of the CDCR models, we propose a direction for CDCR evaluation that combines CDCR datasets with multiple annotation schemes that focus of various properties of the coreference chains.
stoichiometry of a neglected trophic level

biomass, we applied a standardised model averaging approach investigating the effects of basal resource stoichiometry, litter mass, plant species richness, and soil pH on both consumer community characteristics. This standardised approach enabled us to identify differences and similarities in the magnitude and importance of such effects on consumer species richness and biomass. 4. Across consumer groups, we found litter mass to be the most important predictor of both species richness and biomass. Resource stoichiometry had a more pronounced impact on consumer species richness than on their biomass. As expected, taxonomic groups differed in which resource and habitat parameters (basal resource stoichiometry, litter mass, plant species richness, and pH) were most important for modulating their community characteristics. 5. The importance of litter mass for both species richness and biomass indicates that these tropical consumers strongly depend on habitat space and resource availability. Our study supports previous theoretical work indicating that consumer species richness is jointly influenced by resource availability and the balanced supply of multiple chemical elements in their resources.
Effect of compressive therapy on sensorimotor function of the more affected upper extremity in chronic stroke patients: A randomized clinical trial

Background: Common upper extremity (UE) physical impairments after stroke include paresis, abnormal muscle tone, and somatosensory affection. This study evaluated the effect of passive somatosensory stimulation using compressive therapy on sensorimotor function of the more affected UE in chronic stroke patients. Methods: Forty chronic stroke patients were enrolled in this study. They were randomized into 2 groups: Gr1 and Gr2. Three patients dropped out leaving us with a total of 37 patients completing the study. Gr1 received UE motor program for the more affected UE along with sham electrical stimulation while Gr2 had the same UE motor program along with passive somatosensory stimulation. The session duration in both groups was 85 min. Gr1 and Gr2 received a total of 36 sessions for 6 successive weeks. UE function in Gr1 and Gr2 was examined, before and after treatment using Box and Block test (BBT) and Perdue Pegboard test (PPBT) as measures of motor of both the more affected and less affected UE while the Nottingham sensory assessment (NSA) scale was used as a measure of sensory function of the more affected UE. Results: There were significant improvements in motor and sensory function of the more affected UE compared to the less affected UE in both groups, measured by the BBT, PPBT, and NSA scales post-treatment (P < .05). However, the comparison between both groups regarding improvement revealed no significant change (P > .05). Conclusion: Upper extremity motor and passive somatosensory stimulation techniques are effective in improving sensorimotor function of the more affected UE, but none of them had the advantage over the other, in terms of improving motor and sensory function in chronic stroke patients.
Rotating boson stars in five-dimensional Einstein-Gauss-Bonnet gravity

A self-interacting SU(2)-doublet of complex scalar fields, minimally coupled to Einstein-Gauss-Bonnet gravity is considered in five space-time dimensions. The classical equations admit two families of solitons corresponding to spinning and non-spinning bosons stars. The generic solutions are constructed numerically and agree with exact results that are available in special limits of the parameters. The pattern of the boson stars is shown to be qualitatively affected by the Gauss-Bonnet coupling constant.
Lactate dehydrogenase/albumin ratio as a prognostic factor in severe acute respiratory distress syndrome cases associated with COVID-19

Background: Patients with severe acute respiratory distress syndrome (ARDS) have high mortality rates; therefore, new biomarkers are necessary to predict the prognosis in the early stages. Serum lactate dehydrogenase (LDH) level is a specific marker of lung damage, but it is not sensitive because it is affected by several factors. This study aimed to determine whether the LDH/albumin ratio could be used as a prognostic biomarker in patients with severe ARDS due to COVID 19. Methods: Tertiary intensive care unit (ICU) patients with severe ARDS and confirmed COVID-19 diagnosis between August 1, 2020, and October 31, 2021, were included. The demographic and clinical characteristics of the patients were recorded from the hospital databases, together with laboratory results on the day of admission to the ICU and the length of stay in the ICU and hospital. LDH/albumin, lactate/albumin, C-reactive protein (CRP)/albumin, and BUN/albumin ratios were calculated. Logistic regression analysis was performed to determine independent risk factors affecting mortality. Results: Nine hundred and five patients hospitalized in a tertiary ICU were evaluated. Three hundred fifty-one patients with severe ARDS were included in this study. The mortality rate of the included patients was 61.8% (of 217/351). LDH/albumin, lactate/albumin, and BUN/albumin ratios were higher in the nonsurvivor group (P < .001). The area under the curve (AUC) from the receiver operating characteristic analysis that predicted in-hospital mortality was 0.627 (95% confidence intervals (CI): 0.574–0.678, P < . 001) for the LDH/albumin ratio, 0.605 (95% CI: 0.551–0.656, P < .001) for lactate/albumin, and 0.638 (95% CI: 0.585–0.688, P < .001) for BUN/albumin. However, LDH/albumin ratio was independently associated with mortality in multivariate logistic regression analysis. Conclusion: LDH/albumin ratio can be used as an independent prognostic factor for mortality in patients with severe ARDS caused by COVID-19.
DA-EPOCH-R improves the prognosis of patients with double-expressor lymphoma: A single-center retrospective study and meta-analysis

Purpose: Double-expressor lymphoma (DEL) is associated with a poor prognosis. The standard treatment for patients with DEL remains controversial. A comparison of the safety and feasibility of R-CHOP and DA-EPOCH-R as the first-line therapy for patients with DEL is urgently needed. Methods: The clinical and treatment outcomes of 75 DEL patients were retrospectively analyzed. The role of DA-EPOCH-R was determined and compared to that of R-CHOP in DEL patients. PubMed, Embase, the Cochrane Central Library, and ClinicalTrials.gov were systematically searched up to November 1, 2021 and were evaluated by Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines. Articles comparing DA-EPOCH-R versus R-CHOP in patients with DEL were included. Results: Overall, 49 and 26 DEL patients received R-CHOP and DA-EPOCH-R, respectively. Although the difference in response for patients who received R-CHOP and DA-EPOCH-R was not significant (P = .347), DA-EPOCH-R may improve the prognosis compared to R-CHOP (P = .056 for progression-free survival [PFS], P = .009 for overall survival [OS]). A systematic review and meta-analysis including 412 DEL patients in six articles were conducted. The event rate for 3-year PFS was significantly lower in patients receiving DA-EPOCH-R treatment than in those undergoing R-CHOP treatment (OR = 0.63, 95% CI = 0.42–0.94, P = .02), whereas no statistically significant difference was found in the HRs for both PFS and OS or the event rate for 3-year OS. Conclusion: The results of this study indicated that DA-EPOCH-R might improve the prognosis of DEL patients compared with R-CHOP.
Assessing the Semantic Difficulty of Queries

Traditional Information Retrieval (IR) models, also known as lexical models, are hindered by the semantic gap, which refers to the mismatch between different representations of the same underlying concept. To address this gap, semantic models have been developed. Semantic and lexical models exploit complementary signals that are best suited for different types of queries. For this reason, these model categories should not be used interchangeably, but should rather be properly alternated depending on the query. Therefore, it is important to identify queries where the semantic gap is prominent and thus semantic models prove effective. In this work, we quantify the impact of using semantic or lexical models on different queries, and we show that the interaction between queries and model categories is large. Then, we propose a labeling strategy to classify queries into semantically hard or easy, and we deploy a prototype classifier to discriminate between them.