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The 3D Ising transition, the most celebrated and unsolved critical phenomenon in nature, has long been conjectured to have emergent conformal symmetry, similar to the case of the 2D Ising transition. Yet, the emergence of conformal invariance in the 3D Ising transition has rarely been explored directly, mainly due to unavoidable mathematical or conceptual obstructions. Here, we design an innovative way to study the quantum version of the 3D Ising phase transition on spherical geometry, using the “fuzzy (noncommutative) sphere” regularization. We accurately calculate and analyze the energy spectra at the transition, and explicitly demonstrate the state-operator correspondence (i.e., radial quantization), a fingerprint of conformal field theory. In particular, we identify13 parity-even primary operators within a high accuracy and two parity-odd operators that were not known before. Our result directly elucidates the emergent conformal symmetry of the 3D Ising transition, a conjecture made by Polyakov half a century ago. More importantly, our approach opens a new avenue for studying 3D conformal field theories by making use of the state-operator correspondence and spherical geometry.

Quantum magnets provide the simplest example of strongly interacting quantum matter, yet they continue to resist a comprehensive understanding above one spatial dimension. We explore a promising framework in two dimensions, the Dirac spin liquid (DSL) — quantum electrodynamics (QED 3 ) with 4 Dirac fermions coupled to photons. Importantly, its excitations include magnetic monopoles that drive confinement. We address previously open key questions — the symmetry actions on monopoles on square, honeycomb, triangular and kagome lattices. The stability of the DSL is enhanced on triangular and kagome lattices compared to bipartite (square and honeycomb) lattices. We obtain the universal signatures of the DSL on triangular and kagome lattices, including those of monopole excitations, as a guide to numerics and experiments on existing materials. Even when unstable, the DSL helps unify and organize the plethora of ordered phases in correlated two-dimensional materials. The Dirac spin liquid is a candidate description for the strongly correlated behaviour of some quantum magnets. Song et al. study the symmetry dependence physics of monopole excitations and argue that the lattice-dependent consequences for magnetic ordering may provide a unifying picture for 2D quantum magnetism.

Background Several biomarkers have been proposed to predict the occurrence of acute kidney injury (AKI); however, their efficacy varies between different trials. The aim of this study was to compare the predictive performance of different candidate biomarkers for AKI. Methods In this systematic review, we searched PubMed, Medline, Embase, and the Cochrane Library for papers published up to August 15, 2022. We selected all studies of adults (> 18 years) that reported the predictive performance of damage biomarkers (neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), liver-type fatty acid-binding protein (L-FABP)), inflammatory biomarker (interleukin-18 (IL-18)), and stress biomarker (tissue inhibitor of metalloproteinases-2 × insulin-like growth factor-binding protein-7 (TIMP-2 × IGFBP-7)) for the occurrence of AKI. We performed pairwise meta-analyses to calculate odds ratios (ORs) and 95% confidence intervals (CIs) individually. Hierarchical summary receiver operating characteristic curves (HSROCs) were used to summarize the pooled test performance, and the Grading of Recommendations, Assessment, Development and Evaluations criteria were used to appraise the quality of evidence. Results We identified 242 published relevant studies from 1,803 screened abstracts, of which 110 studies with 38,725 patients were included in this meta-analysis. Urinary NGAL/creatinine (diagnostic odds ratio [DOR] 16.2, 95% CI 10.1–25.9), urinary NGAL (DOR 13.8, 95% CI 10.2–18.8), and serum NGAL (DOR 12.6, 95% CI 9.3–17.3) had the best diagnostic accuracy for the risk of AKI. In subgroup analyses, urinary NGAL, urinary NGAL/creatinine, and serum NGAL had better diagnostic accuracy for AKI than urinary IL-18 in non-critically ill patients. However, all of the biomarkers had similar diagnostic accuracy in critically ill patients. In the setting of medical and non-sepsis patients, urinary NGAL had better predictive performance than urinary IL-18, urinary L-FABP, and urinary TIMP-2 × IGFBP-7: 0.3. In the surgical patients, urinary NGAL/creatinine and urinary KIM-1 had the best diagnostic accuracy. The HSROC values of urinary NGAL/creatinine, urinary NGAL, and serum NGAL were 91.4%, 85.2%, and 84.7%, respectively. Conclusions Biomarkers containing NGAL had the best predictive accuracy for the occurrence of AKI, regardless of whether or not the values were adjusted by urinary creatinine, and especially in medically treated patients. However, the predictive performance of urinary NGAL was limited in surgical patients, and urinary NGAL/creatinine seemed to be the most accurate biomarkers in these patients. All of the biomarkers had similar predictive performance in critically ill patients. Trial registration CRD42020207883 , October 06, 2020.

The antiferromagnetic spin-1/2 Heisenberg model on a kagome lattice is one of the most paradigmatic models in the context of spin liquids, yet the precise nature of its ground state is not understood. We use large-scale density matrix renormalization group simulations (DMRG) on infinitely long cylinders and find indications for the formation of a gapless Dirac spin liquid. First, we use adiabatic flux insertion to demonstrate that the spin gap is much smaller than estimated from previous DMRG simulation. Second, we find that the momentum-dependent excitation spectrum, as extracted from the DMRG transfer matrix, exhibits Dirac cones that match those of a π -flux free-fermion model [the parton mean-field ansatz of a U(1) Dirac spin liquid].

Genomic changes in Mycoplasma pneumoniae caused by adaptation to environmental or ecologic pressures are poorly understood. We collected M. pneumoniae from children who had confirmed pneumonia in Taiwan during 2017-2020. We used whole-genome sequencing to compare these isolates with a worldwide collection of current and historical clinical strains for characterizing population structures. A phylogenetic tree for 284 strains showed that all sequenced strains consisted of 5 clades: T1-1 (sequence type [ST]1), T1-2 (mainly ST3), T1-3 (ST17), T2-1 (mainly ST2), and T2-2 (mainly ST14). We identified a putative recombination block containing 6 genes (MPN366‒371). Macrolide resistance involving 23S rRNA mutations was detected for each clade. Clonal expansion of macrolide resistance occurred mostly within subtype 1 strains, of which clade T1-2 showed the highest recombination rate and genome diversity. Functional characterization of recombined regions provided clarification of the biologic role of these recombination events in the evolution of M. pneumoniae.

Defects in conformal field theory (CFT) are of significant theoretical and experimental importance. The presence of defects theoretically enriches the structure of the CFT, but at the same time, it makes it more challenging to study, especially in dimensions higher than two. Here, we demonstrate that the recently-developed theoretical scheme, fuzzy (non-commutative) sphere regularization , provides a powerful lens through which one can dissect the defect of 3D CFTs in a transparent way. As a notable example, we study the magnetic line defect of 3D Ising CFT and clearly demonstrate that it flows to a conformal defect fixed point. We have identified 6 low-lying defect primary operators, including the displacement operator, and accurately extract their scaling dimensions through the state-operator correspondence. Moreover, we also compute one-point bulk correlators and two-point bulk-defect correlators, which show great agreement with predictions of defect conformal symmetry, and from which we extract various bulk-defect operator product expansion coefficients. Our work demonstrates that the fuzzy sphere offers a powerful tool for exploring the rich physics in 3D defect CFTs. The study of defects and boundaries in the context of conformal field theory is important but challenging in dimensions higher than two. Here the authors use the recently developed fuzzy sphere regularization approach to perform non-perturbative analysis of defect conformal field theory in 3D

A bstract In CFTs, the partition function of a line defect with a cusp depends logarithmically on the size of the line with an angle-dependent coefficient: the cusp anomalous dimension. In the first part of this work, we study the general properties of the cusp anomalous dimension. We relate the small cusp angle limit to the effective field theory of defect fusion, making predictions for the first couple of terms in the expansion. Using a concavity property of the cusp anomalous dimension we argue that the Casimir energy between a line defect and its orientation reversal is always negative (“opposites attract”). We use these results to determine the fusion algebra of Wilson lines in N = 4 SYM as well as pinning field defects in the Wilson-Fisher fixed points. In the second part of the paper we obtain nonperturbative numerical results for the cusp anomalous dimension of pinning field defects in the Ising model in d = 3, using the recently developed fuzzy-sphere regularization. We also compute the pinning field cusp anomalous dimension in the O ( N ) model at one-loop in the ε -expansion. Our results are in agreement with the general theory developed in the first part of the work, and we make several predictions for impurities in magnets.

In very low birth weight (VLBW) infants, hypothermia immediately following birth is common even in countries rich in medical resources. The purpose of this study is to design a standard prevention bundle that decreases the rate of hypothermia among infants after birth and to investigate efficacy of the bundle and short-term outcomes for VLBW infants. This quality improvement project was conducted from February 2017 to July 2018 on all VLBW preterm infants admitted at a single referral level III neonatal intensive care unit. The infants were classified into the pre-intervention (February to September 2017) and post-intervention (October 2017 to July 2018) groups according to the time periods when they were recruited. During the pre-intervention period, we analyzed the primary causes of hypothermia, developed solutions corresponding to each cause, integrated all solutions into a prevention bundle, and applied the bundle during the post-intervention period. Afterwards, the incidence of neonatal hypothermia and short-term outcomes, such as intraventricular hemorrhage (IVH), acidosis, and shock requiring inotropic agents, in each group were compared. A total of 95 VLBW infants were enrolled in the study, including 37 pre-intervention, and 58 post-intervention cases. The incidence of hypothermia in preterm infants decreased significantly upon the implementation of our prevention bundle, both in the delivery room (from 45.9% to 8.6%) and on admission (59.5% to 15.5%). In addition, the short-term outcomes of VLBW infants improved significantly, especially with the decreased incidence of IVH (from 21.6% to 5.2%, P = 0.015). Our standardized prevention bundle for preventing hypothermia in VLBW infants is effective and decreased the IVH rate in VLBW infants. We strongly believe that this prevention bundle is a simple, low-cost, replicable, and effective tool that hospitals can adopt to improve VLBW infant outcomes.

Background Microbial infection is the main cause of increased morbidity and mortality in burn patients, especially infections caused by multiple drug-resistant organisms (MDRO). The purpose of this study was to explore major microbial trends in burn patients . Methods This retrospective study was conducted at burn wards and intensive care units, where burn patients were admitted following an event of dust explosion. Data were collected for a number of variables including severity of burns, demographic and clinical characteristics, laboratory data, and therapeutic devices. Results A total of 1132 specimens were collected from 37 hospitalized burn patients with mean TBSA of 46.1%.The most commonly isolated species were Staphylococcus spp. (22.4%). The highest rate of antibiotic resistance was observed in carbapenem–resistant A. baumannii (14.6%), followed by methicillin-resistant S. aureus (11.3%). For each additional 10% TBSA, the isolation of MDRO increased 2.58–17.57 times ( p  < 0.05); for each additional 10% of the third-degree burn severity, the risk of MDRO significantly decreased by 47% (95% CI, 0.38–0.73, p  < 0.001) by Cox model. Conclusions The proportion of overall microbial isolates increased with the increase in TBSA and duration of time after burns. The extent of TBSA was the most important factor affecting MDRO.

Plants dedicate a high amount of energy and resources to the production of ribosomes. Historically, these multi-protein ribosome complexes have been considered static protein synthesis machines that are not subject to extensive regulation but only read mRNA and produce polypeptides accordingly. New and increasing evidence across various model organisms demonstrated the heterogeneous nature of ribosomes. This heterogeneity can constitute specialized ribosomes that regulate mRNA translation and control protein synthesis. A prominent example of ribosome heterogeneity is seen in the model plant, Arabidopsis thaliana , which, due to genome duplications, has multiple paralogs of each ribosomal protein (RP) gene. We support the notion of plant evolution directing high RP paralog divergence toward functional heterogeneity, underpinned in part by a vast resource of ribosome mutants that suggest specialization extends beyond the pleiotropic effects of single structural RPs or RP paralogs. Thus, Arabidopsis is a highly suitable model to study this phenomenon. Arabidopsis enables reverse genetics approaches that could provide evidence of ribosome specialization. In this review, we critically assess evidence of plant ribosome specialization and highlight steps along ribosome biogenesis in which heterogeneity may arise, filling the knowledge gaps in plant science by providing advanced insights from the human or yeast fields. We propose a data analysis pipeline that infers the heterogeneity of ribosome complexes and deviations from canonical structural compositions linked to stress events. This analysis pipeline can be extrapolated and enhanced by combination with other high-throughput methodologies, such as proteomics. Technologies, such as kinetic mass spectrometry and ribosome profiling, will be necessary to resolve the temporal and spatial aspects of translational regulation while the functional features of ribosomal subpopulations will become clear with the combination of reverse genetics and systems biology approaches.