Detection of a pair density wave state in UTe2.

Spin-triplet topological superconductors should exhibit many unprecedented electronic properties, including fractionalized electronic states relevant to quantum information processing. Although UTe2 may embody such bulk topological superconductivity1-11, its superconductive order parameter Δ(k) remains unknown12. Many diverse forms for Δ(k) are physically possible12 in such heavy fermion materials13. Moreover, intertwined14,15 density waves of spin (SDW), charge (CDW) and pair (PDW) may interpose, with the latter exhibiting spatially modulating14,15 superconductive order parameter Δ(r), electron-pair density16-19 and pairing energy gap17,20-23. Hence, the newly discovered CDW state24 in UTe2 motivates the prospect that a PDW state may exist in this material24,25. To search for it, we visualize the pairing energy gap with µeV-scale energy resolution using superconductive scanning tunnelling microscopy (STM) tips26-31. We detect three PDWs, each with peak-to-peak gap modulations of around 10 µeV and at incommensurate wavevectors Pi=1,2,3 that are indistinguishable from the wavevectors Qi=1,2,3 of the prevenient24 CDW. Concurrent visualization of the UTe2 superconductive PDWs and the non-superconductive CDWs shows that every Pi:Qi pair exhibits a relative spatial phase δϕ ≈ π. From these observations, and given UTe2 as a spin-triplet superconductor12, this PDW state should be a spin-triplet PDW24,25. Although such states do exist32 in superfluid 3He, for superconductors, they are unprecedented.

Dichotomous dynamics of magnetic monopole fluids.

A recent advance in the study of emergent magnetic monopoles was the discovery that monopole motion is restricted to dynamical fractal trajectories [J. N. Hallén et al., Science 378, 1218 (2022)], thus explaining the characteristics of magnetic monopole noise spectra [R. Dusad et al., Nature 571, 234 (2019); A. M. Samarakoon et al., Proc. Natl. Acad. Sci. U.S.A. 119, e2117453119 (2022)]. Here, we apply this novel theory to explore the dynamics of field-driven monopole currents, finding them composed of two quite distinct transport processes: initially swift fractal rearrangements of local monopole configurations followed by conventional monopole diffusion. This theory also predicts a characteristic frequency dependence of the dissipative loss angle for AC field-driven currents. To explore these novel perspectives on monopole transport, we introduce simultaneous monopole current control and measurement techniques using SQUID-based monopole current sensors. For the canonical material Dy2Ti2O7, we measure [Formula: see text], the time dependence of magnetic flux threading the sample when a net monopole current [Formula: see text] is generated by applying an external magnetic field [Formula: see text] These experiments find a sharp dichotomy of monopole currents, separated by their distinct relaxation time constants before and after t ~[Formula: see text] from monopole current initiation. Application of sinusoidal magnetic fields [Formula: see text] generates oscillating monopole currents whose loss angle [Formula: see text] exhibits a characteristic transition at frequency [Formula: see text] over the same temperature range. Finally, the magnetic noise power is also dichotomic, diminishing sharply after t ~[Formula: see text]. This complex phenomenology represents an unprecedented form of dynamical heterogeneity generated by the interplay of fractionalization and local spin configurational symmetry.

Imaging the energy gap modulations of the cuprate pair-density-wave state.

The defining characteristic1,2 of Cooper pairs with finite centre-of-mass momentum is a spatially modulating superconducting energy gap Δ(r), where r is a position. Recently, this concept has been generalized to the pair-density-wave (PDW) state predicted to exist in copper oxides (cuprates)3,4. Although the signature of a cuprate PDW has been detected in Cooper-pair tunnelling5, the distinctive signature in single-electron tunnelling of a periodic Δ(r) modulation has not been observed. Here, using a spectroscopic technique based on scanning tunnelling microscopy, we find strong Δ(r) modulations in the canonical cuprate Bi2Sr2CaCu2O8+δ that have eight-unit-cell periodicity or wavevectors Q ≈ (2π/a0)(1/8, 0) and Q ≈ (2π/a0)(0, 1/8) (where a0 is the distance between neighbouring Cu atoms). Simultaneous imaging of the local density of states N(r, E) (where E is the energy) reveals electronic modulations with wavevectors Q and 2Q, as anticipated when the PDW coexists with superconductivity. Finally, by visualizing the topological defects in these N(r, E) density waves at 2Q, we find them to be concentrated in areas where the PDW spatial phase changes by π, as predicted by the theory of half-vortices in a PDW state6,7. Overall, this is a compelling demonstration, from multiple single-electron signatures, of a PDW state coexisting with superconductivity in Bi2Sr2CaCu2O8+δ.

Discovery of orbital ordering in Bi2Sr2CaCu2O8+x.

The primordial ingredient of cuprate superconductivity is the CuO2 unit cell. Theories usually concentrate on the intra-atom Coulombic interactions dominating the 3d9 and 3d10 configurations of each copper ion. However, if Coulombic interactions also occur between electrons of the 2p6 orbitals of each planar oxygen atom, spontaneous orbital ordering may split their energy levels. This long-predicted intra-unit-cell symmetry breaking should generate an orbitally ordered phase, for which the charge transfer energy ε separating the 2p6 and 3d10 orbitals is distinct for the two oxygen atoms. Here we introduce sublattice-resolved ε(r) imaging to CuO2 studies and discover intra-unit-cell rotational symmetry breaking of ε(r). Spatially, this state is arranged in disordered Ising domains of orthogonally oriented orbital order bounded by dopant ions, and within whose domain walls low-energy electronic quadrupolar two-level systems occur. Overall, these data reveal a Q = 0 orbitally ordered state that splits the oxygen energy levels by ~50 meV, in underdoped CuO2.

Magnetic monopole noise.

Magnetic monopoles1-3 are hypothetical elementary particles with quantized magnetic charge. In principle, a magnetic monopole can be detected by the quantized jump in magnetic flux that it generates upon passage through a superconducting quantum interference device (SQUID)4. Following the theoretical prediction that emergent magnetic monopoles should exist in several lanthanide pyrochlore magnetic insulators5,6, including Dy2Ti2O7, the SQUID technique has been proposed for their direct detection6. However, this approach has been hindered by the high number density and the generation-recombination fluctuations expected of such thermally generated monopoles. Recently, theoretical advances have enabled the prediction of the spectral density of magnetic-flux noise from monopole generation-recombination fluctuations in these materials7,8. Here we report the development of a SQUID-based flux noise spectrometer and measurements of the frequency and temperature dependence of magnetic-flux noise generated by Dy2Ti2O7 crystals. We detect almost all of the features of magnetic-flux noise predicted for magnetic monopole plasmas7,8, including the existence of intense magnetization noise and its characteristic frequency and temperature dependence. Moreover, comparisons of simulated and measured correlation functions of the magnetic-flux noise indicate that the motions of magnetic charges are strongly correlated. Intriguingly, because the generation-recombination time constant for Dy2Ti2O7 is in the millisecond range, magnetic monopole flux noise amplified by SQUID is audible to humans.

Machine learning in electronic-quantum-matter imaging experiments.

For centuries, the scientific discovery process has been based on systematic human observation and analysis of natural phenomena1. Today, however, automated instrumentation and large-scale data acquisition are generating datasets of such large volume and complexity as to defy conventional scientific methodology. Radically different scientific approaches are needed, and machine learning (ML) shows great promise for research fields such as materials science2-5. Given the success of ML in the analysis of synthetic data representing electronic quantum matter (EQM)6-16, the next challenge is to apply this approach to experimental data-for example, to the arrays of complex electronic-structure images17 obtained from atomic-scale visualization of EQM. Here we report the development and training of a suite of artificial neural networks (ANNs) designed to recognize different types of order hidden in such EQM image arrays. These ANNs are used to analyse an archive of experimentally derived EQM image arrays from carrier-doped copper oxide Mott insulators. In these noisy and complex data, the ANNs discover the existence of a lattice-commensurate, four-unit-cell periodic, translational-symmetry-breaking EQM state. Further, the ANNs determine that this state is unidirectional, revealing a coincident nematic EQM state. Strong-coupling theories of electronic liquid crystals18,19 are consistent with these observations.

Identification of a nematic pair density wave state in Bi2Sr2CaCu2O8+x.

Electron-pair density wave (PDW) states are now an intense focus of research in the field of cuprate correlated superconductivity. PDWs exhibit periodically modulating superconductive electron pairing that can be visualized directly using scanned Josephson tunneling microscopy (SJTM). Although from theory, intertwining the d-wave superconducting (DSC) and PDW order parameters allows a plethora of global electron-pair orders to appear, which one actually occurs in the various cuprates is unknown. Here, we use SJTM to visualize the interplay of PDW and DSC states in Bi2Sr2CaCu2O8+x at a carrier density where the charge density wave modulations are virtually nonexistent. Simultaneous visualization of their amplitudes reveals that the intertwined PDW and DSC are mutually attractive states. Then, by separately imaging the electron-pair density modulations of the two orthogonal PDWs, we discover a robust nematic PDW state. Its spatial arrangement entails Ising domains of opposite nematicity, each consisting primarily of unidirectional and lattice commensurate electron-pair density modulations. Further, we demonstrate by direct imaging that the scattering resonances identifying Zn impurity atom sites occur predominantly within boundaries between these domains. This implies that the nematic PDW state is pinned by Zn atoms, as was recently proposed [Lozano et al., Phys. Rev. B 103, L020502 (2021)]. Taken in combination, these data indicate that the PDW in Bi2Sr2CaCu2O8+x is a vestigial nematic pair density wave state [Agterberg et al. Phys. Rev. B 91, 054502 (2015); Wardh and Granath arXiv:2203.08250].

On the electron pairing mechanism of copper-oxide high temperature superconductivity.

The elementary CuO2 plane sustaining cuprate high-temperature superconductivity occurs typically at the base of a periodic array of edge-sharing CuO5 pyramids. Virtual transitions of electrons between adjacent planar Cu and O atoms, occurring at a rate t/ℏ and across the charge-transfer energy gap [Formula: see text], generate "superexchange" spin-spin interactions of energy [Formula: see text] in an antiferromagnetic correlated-insulator state. However, hole doping this CuO2 plane converts this into a very-high-temperature superconducting state whose electron pairing is exceptional. A leading proposal for the mechanism of this intense electron pairing is that, while hole doping destroys magnetic order, it preserves pair-forming superexchange interactions governed by the charge-transfer energy scale [Formula: see text]. To explore this hypothesis directly at atomic scale, we combine single-electron and electron-pair (Josephson) scanning tunneling microscopy to visualize the interplay of [Formula: see text] and the electron-pair density nP in Bi2Sr2CaCu2O8+x. The responses of both [Formula: see text] and nP to alterations in the distance δ between planar Cu and apical O atoms are then determined. These data reveal the empirical crux of strongly correlated superconductivity in CuO2, the response of the electron-pair condensate to varying the charge-transfer energy. Concurrence of predictions from strong-correlation theory for hole-doped charge-transfer insulators with these observations indicates that charge-transfer superexchange is the electron-pairing mechanism of superconductive Bi2Sr2CaCu2O8+x.

Multicomponent Strategy with Decentralized Molecular Testing for Tuberculosis.

BACKGROUND: Effective strategies are needed to facilitate the prompt diagnosis and treatment of tuberculosis in countries with a high burden of the disease. METHODS: We conducted a cluster-randomized trial in which Ugandan community health centers were assigned to a multicomponent diagnostic strategy (on-site molecular testing for tuberculosis, guided restructuring of clinic workflows, and monthly feedback of quality metrics) or routine care (on-site sputum-smear microscopy and referral-based molecular testing). The primary outcome was the number of adults treated for confirmed tuberculosis within 14 days after presenting to the health center for evaluation during the 16-month intervention period. Secondary outcomes included completion of tuberculosis testing, same-day diagnosis, and same-day treatment. Outcomes were also assessed on the basis of proportions. RESULTS: A total of 20 health centers underwent randomization, with 10 assigned to each group. Of 10,644 eligible adults (median age, 40 years) whose data were evaluated, 60.1% were women and 43.8% had human immunodeficiency virus infection. The intervention strategy led to a greater number of patients being treated for confirmed tuberculosis within 14 days after presentation (342 patients across 10 intervention health centers vs. 220 across 10 control health centers; adjusted rate ratio, 1.56; 95% confidence interval [CI], 1.21 to 2.01). More patients at intervention centers than at control centers completed tuberculosis testing (adjusted rate ratio, 1.85; 95% CI, 1.21 to 2.82), received a same-day diagnosis (adjusted rate ratio, 1.89; 95% CI, 1.39 to 2.56), and received same-day treatment for confirmed tuberculosis (adjusted rate ratio, 2.38; 95% CI, 1.57 to 3.61). Among 706 patients with confirmed tuberculosis, a higher proportion in the intervention group than in the control group were treated on the same day (adjusted rate ratio, 2.29; 95% CI, 1.23 to 4.25) or within 14 days after presentation (adjusted rate ratio, 1.22; 95% CI, 1.06 to 1.40). CONCLUSIONS: A multicomponent diagnostic strategy that included on-site molecular testing plus implementation supports to address barriers to delivery of high-quality tuberculosis evaluation services led to greater numbers of patients being tested, receiving a diagnosis, and being treated for confirmed tuberculosis. (Funded by the National Heart, Lung, and Blood Institute; XPEL-TB ClinicalTrials.gov number, NCT03044158.).

Proton Shell Gaps in N=28 Nuclei from the First Complete Spectroscopy Study with FRIB Decay Station Initiator.

The first complete measurement of the ß-decay strength distribution of _{17}^{45}Cl_{28} was performed at the Facility for Rare Isotope Beams (FRIB) with the FRIB Decay Station Initiator during the second FRIB experiment. The measurement involved the detection of neutrons and γ rays in two focal planes of the FRIB Decay Station Initiator in a single experiment for the first time. This enabled an analytical consistency in extracting the ß-decay strength distribution over the large range of excitation energies, including neutron unbound states. We observe a rapid increase in the ß-decay strength distribution above the neutron separation energy in _{18}^{45}Ar_{27}. This was interpreted to be caused by the transitioning of neutrons into protons excited across the Z=20 shell gap. The SDPF-MU interaction with reduced shell gap best reproduced the data. The measurement demonstrates a new approach that is sensitive to the proton shell gap in neutron rich nuclei according to SDPF-MU calculations.

The role of the granuloma in expansion and dissemination of early tuberculous infection.

Granulomas, organized aggregates of immune cells, form in response to persistent stimuli and are hallmarks of tuberculosis. Tuberculous granulomas have long been considered host-protective structures formed to contain infection. However, work in zebrafish infected with Mycobacterium marinum suggests that granulomas contribute to early bacterial growth. Here we use quantitative intravital microscopy to reveal distinct steps of granuloma formation and assess their consequence for infection. Intracellular mycobacteria use the ESX-1/RD1 virulence locus to induce recruitment of new macrophages to, and their rapid movement within, nascent granulomas. This motility enables multiple arriving macrophages to efficiently find and phagocytose infected macrophages undergoing apoptosis, leading to rapid, iterative expansion of infected macrophages and thereby bacterial numbers. The primary granuloma then seeds secondary granulomas via egress of infected macrophages. Our direct observations provide insight into how pathogenic mycobacteria exploit the granuloma during the innate immune phase for local expansion and systemic dissemination.

sgcocaller and comapr: personalised haplotype assembly and comparative crossover map analysis using single-gamete sequencing data.

Profiling gametes of an individual enables the construction of personalised haplotypes and meiotic crossover landscapes, now achievable at larger scale than ever through the availability of high-throughput single-cell sequencing technologies. However, high-throughput single-gamete data commonly have low depth of coverage per gamete, which challenges existing gamete-based haplotype phasing methods. In addition, haplotyping a large number of single gametes from high-throughput single-cell DNA sequencing data and constructing meiotic crossover profiles using existing methods requires intensive processing. Here, we introduce efficient software tools for the essential tasks of generating personalised haplotypes and calling crossovers in gametes from single-gamete DNA sequencing data (sgcocaller), and constructing, visualising, and comparing individualised crossover landscapes from single gametes (comapr). With additional data pre-possessing, the tools can also be applied to bulk-sequenced samples. We demonstrate that sgcocaller is able to generate impeccable phasing results for high-coverage datasets, on which it is more accurate and stable than existing methods, and also performs well on low-coverage single-gamete sequencing datasets for which current methods fail. Our tools achieve highly accurate results with user-friendly installation, comprehensive documentation, efficient computation times and minimal memory usage.

Impact of a 6-12-h delay between ileocolic intussusception diagnostic US and fluoroscopic reduction on patients' outcomes.

BACKGROUND: Image-guided reduction of intussusception is considered a radiologic urgency requiring 24-h radiologist and technologist availability. OBJECTIVE: To assess whether a delay of 6-12 h between US diagnosis and fluoroscopic reduction of ileocolic intussusception affects the success frequency of fluoroscopic reduction. MATERIALS AND METHODS: Retrospective review of 0-5-year-olds undergoing fluoroscopic reduction for ileocolic intussusception from 2013 to 2023. Exclusions were small bowel intussusception, self-reduced intussusception, first fluoroscopic reduction attempt>12 h after US, prior bowel surgery, inpatient status, and patient transferred for recurrent intussusception. Data collected included demographics, symptoms, air/contrast enema selection, radiation dose, reduction failure, 48-h recurrence, surgery, length of stay, and complications. Comparisons between<6-h and 6-12-h delays after ultrasound diagnosis were made using chi-square, Fisher's exact test, and Mann-Whitney U tests (P< 0.05 considered significant). RESULTS: Of 438 included patients, 387 (88.4%) were reduced in <6 h (median age 1.4 years) and 51 (11.7%) were reduced between 6 and 12 h (median age 2.05 years), with median reduction times of 1:42 and 7:07 h, respectively. There were no significant differences between the groups for reduction success (<6 h 87.3% vs. 6-12 h 94.1%; P-value = 0.16), need for surgery (<6 h 11.1% vs. 6-12 h 3.9%; P-value=0.112), recurrence of intussusception within 48 h after reduction (<6 h 9.3% vs. 6-12 h 15.7%; P-value=0.154), or length of hospitalization (<6 h 21:07 h vs. 6-12 h 20:03 h; P-value=0.662). CONCLUSION: A delay of 6-12 h between diagnosis and fluoroscopic reduction of ileocolic intussusception is not associated with reduced fluoroscopic reduction success, need for surgical intervention after attempted reduction, recurrence of intussusception following successful reduction, or hospitalization duration after reduction.

Cognitive tasks affect the relationship between representational pattern similarity and subsequent item memory in the hippocampus.

Episodic memories are records of personally experienced events, coded neurally via the hippocampus and surrounding medial temporal lobe cortex. Information about the neural signal corresponding to a memory representation can be measured in fMRI data when the pattern across voxels is examined. Prior studies have found that similarity in the voxel patterns across repetition of a to-be-remembered stimulus predicts later memory retrieval, but the results are inconsistent across studies. The current study investigates the possibility that cognitive goals (defined here via the task instructions given to participants) during encoding affect the voxel pattern that will later support memory retrieval, and therefore that neural representations cannot be interpreted based on the stimulus alone. The behavioral results showed that exposure to variable cognitive tasks across repetition of events benefited subsequent memory retrieval. Voxel patterns in the hippocampus indicated a significant interaction between cognitive tasks (variable vs. consistent) and memory (remembered vs. forgotten) such that reduced voxel pattern similarity for repeated events with variable cognitive tasks, but not consistent cognitive tasks, supported later memory success. There was no significant interaction in neural pattern similarity between cognitive tasks and memory success in medial temporal cortices or lateral occipital cortex. Instead, higher similarity in voxel patterns in right medial temporal cortices was associated with later memory retrieval, regardless of cognitive task. In conclusion, we found that the relationship between pattern similarity across repeated encoding and memory success in the hippocampus (but not medial temporal lobe cortex) changes when the cognitive task during encoding does or does not vary across repetitions of the event.

Cardelino: computational integration of somatic clonal substructure and single-cell transcriptomes.

Bulk and single-cell DNA sequencing has enabled reconstructing clonal substructures of somatic tissues from frequency and cooccurrence patterns of somatic variants. However, approaches to characterize phenotypic variations between clones are not established. Here we present cardelino (https://github.com/single-cell-genetics/cardelino), a computational method for inferring the clonal tree configuration and the clone of origin of individual cells assayed using single-cell RNA-seq (scRNA-seq). Cardelino flexibly integrates information from imperfect clonal trees inferred based on bulk exome-seq data, and sparse variant alleles expressed in scRNA-seq data. We apply cardelino to a published cancer dataset and to newly generated matched scRNA-seq and exome-seq data from 32 human dermal fibroblast lines, identifying hundreds of differentially expressed genes between cells from different somatic clones. These genes are frequently enriched for cell cycle and proliferation pathways, indicating a role for cell division genes in somatic evolution in healthy skin.

Effectiveness of adjunctive rifampicin for treatment of Staphylococcus aureus bacteraemia: a systematic review and meta-analysis of randomized controlled trials.

OBJECTIVES: To assess whether the addition of rifampicin to conventional treatment of Staphylococcus aureus bacteraemia (SAB) reduces bacteriological or clinical failure or death. DATA SOURCES: PubMed, Embase and Cochrane CENTRAL databases were searched from inception to 31 December 2022. Reference lists and PubMed citations of eligible studies were checked. REVIEW METHODS: Two study authors independently identified randomized controlled trials (RCTs) involving adult participants with SAB, in which an intervention group received adjunctive rifampicin and the control group received usual care with or without a placebo. Dichotomous data (bacteriological and clinical failure and deaths) were analysed and pooled across studies using risk ratio (RR) with 95% confidence intervals (CI) using a Mantel-Haenszel random-effect model. The key variable of interest being whether rifampicin was used. RESULTS: Six RCTs including 894 participants-of which 758 (85%) were from one trial-met the inclusion criteria. The addition of rifampicin to conventional treatment of SAB significantly reduced bacteriological failure by 59% (RR 0.41, 95% CI 0.21-0.81, I2 = 0%, number need to treat 27). However, it did not reduce clinical failure (RR 0.70, 95% CI 0.47-1.03, I2 = 0%) or deaths (RR 0.96, 95% CI 0.70-1.32, I2 = 0%). Further, it did not reduce the duration of bacteraemia, or the length of hospital stay. Adjunctive rifampicin reduced SAB recurrences (1% versus 4%, P = 0.01). Emergence of rifampicin resistance during treatment was uncommon (<1%). CONCLUSION: Although adjunctive rifampicin reduced the risk of bacteriological failure and recurrences, we found no mortality benefit to support its use in SAB.

The granuloma in cryptococcal disease.

Although we have recognized cryptococcosis as a disease entity for well over 100 years, there are many details about its pathogenesis which remain unknown. A major barrier to better understanding is the very broad range of clinical and pathological forms cryptococcal infections can take. One such form has been historically called the cryptococcal granuloma, or the cryptococcoma. These words have been used to describe essentially any mass lesion associated with infection, due to their presumed similarity to the quintessential granuloma, the tubercle in tuberculosis. Although clear distinctions between tuberculosis and cryptococcal disease have been discovered, cellular and molecular studies still confirm some important parallels between these 2 diseases and what we now call granulomatous inflammation. In this review, we shall sketch out some of the history behind the term "granuloma" as it pertains to cryptococcal disease, explore our current understanding of the biology of granuloma formation, and try to place that understanding in the context of the myriad pathological presentations of this infection. Finally, we shall summarize the role of the granuloma in cryptococcal latency and present opportunities for future investigations.

Prognostic Discussion for Infants with Neurologic Conditions: Qualitative Analysis of Family Conferences.

OBJECTIVE: We characterize the content and role of prognostic discussion for infants with neurologic conditions. METHODS: In this descriptive qualitative study, we prospectively enrolled infants (age < 1 year) in the intensive care unit with a neurologic condition anticipated to have ≥1 family conference about prognosis or goals of care. We audiorecorded family conferences as they occurred. We used a rapid-cycle qualitative approach to identify and refine themes. RESULTS: Forty infants and 61 parents were enrolled; 68 family conferences occurred for 24 infants. The majority of infant cases (n = 23/24, 96%) and conferences (n = 64/68, 94%) included discussion of neurologic prognosis. Common infant diagnoses included prematurity (n = 12, 52%), genetic conditions (n = 9, 35%), and brain malformations (n = 7, 30%). We identified 2 themes relating to the characterization of the infant's prognosis: (1) predictions of impairment and (2) rationale for prognostic predictions. We identified 3 themes characterizing the role of prognostic discussion: (1) aligning parent and clinician understanding of infant outcome, (2) influencing decision-making, and (3) preparing for life at home. We identified 2 themes characterizing discussion of prognostic uncertainty: (1) multilayered types of uncertainty and (2) holding space for hope alongside uncertainty. INTERPRETATION: In this cohort of infants with neurologic conditions and their parents, we identified salient themes characterizing the content and role of discussion about neurologic outcome. Our findings highlight that prognostic discussion focuses on anticipated impairments, informs decision-making, and helps families prepare for home life. Future work should characterize whether these findings align with parent preferences for prognostic disclosure. ANN NEUROL 2022;92:699-709.

Deep learning prediction of hospital readmissions for asthma and COPD.

QUESTION: Severe asthma and COPD exacerbations requiring hospitalization are linked to increased disease morbidity and healthcare costs. We sought to identify Electronic Health Record (EHR) features of severe asthma and COPD exacerbations and evaluate the performance of four machine learning (ML) and one deep learning (DL) model in predicting readmissions using EHR data. STUDY DESIGN AND METHODS: Observational study between September 30, 2012, and December 31, 2017, of patients hospitalized with asthma and COPD exacerbations. RESULTS: This study included 5,794 patients, 1,893 with asthma and 3,901 with COPD. Patients with asthma were predominantly female (n = 1288 [68%]), 35% were Black (n = 669), and 25% (n = 479) were Hispanic. Black (44 vs. 33%, p = 0.01) and Hispanic patients (30 vs. 24%, p = 0.02) were more likely to be readmitted for asthma. Similarly, patients with COPD readmissions included a large percentage of Blacks (18 vs. 10%, p < 0.01) and Hispanics (8 vs. 5%, p < 0.01). To identify patients at high risk of readmission index hospitalization data of a subset of 2,682 patients, 777 with asthma and 1,905 with COPD, was analyzed with four ML models, and one DL model. We found that multilayer perceptron, the DL method, had the best sensitivity and specificity compared to the four ML methods implemented in the same dataset. INTERPRETATION: Multilayer perceptron, a deep learning method, had the best performance in predicting asthma and COPD readmissions, demonstrating that EHR and deep learning integration can improve high-risk patient detection.

A systematic review of gut microbiota composition in observational studies of major depressive disorder, bipolar disorder and schizophrenia.

The emerging understanding of gut microbiota as 'metabolic machinery' influencing many aspects of physiology has gained substantial attention in the field of psychiatry. This is largely due to the many overlapping pathophysiological mechanisms associated with both the potential functionality of the gut microbiota and the biological mechanisms thought to be underpinning mental disorders. In this systematic review, we synthesised the current literature investigating differences in gut microbiota composition in people with the major psychiatric disorders, major depressive disorder (MDD), bipolar disorder (BD) and schizophrenia (SZ), compared to 'healthy' controls. We also explored gut microbiota composition across disorders in an attempt to elucidate potential commonalities in the microbial signatures associated with these mental disorders. Following the PRISMA guidelines, databases were searched from inception through to December 2021. We identified 44 studies (including a total of 2510 psychiatric cases and 2407 controls) that met inclusion criteria, of which 24 investigated gut microbiota composition in MDD, seven investigated gut microbiota composition in BD, and 15 investigated gut microbiota composition in SZ. Our syntheses provide no strong evidence for a difference in the number or distribution (α-diversity) of bacteria in those with a mental disorder compared to controls. However, studies were relatively consistent in reporting differences in overall community composition (ß-diversity) in people with and without mental disorders. Our syntheses also identified specific bacterial taxa commonly associated with mental disorders, including lower levels of bacterial genera that produce short-chain fatty acids (e.g. butyrate), higher levels of lactic acid-producing bacteria, and higher levels of bacteria associated with glutamate and GABA metabolism. We also observed substantial heterogeneity across studies with regards to methodologies and reporting. Further prospective and experimental research using new tools and robust guidelines hold promise for improving our understanding of the role of the gut microbiota in mental and brain health and the development of interventions based on modification of gut microbiota.