PySINDy: A comprehensive Python package for robust sparse system identification

Automated data-driven modeling, the process of directly discovering the governing equations of a system from data, is increasingly being used across the scientific community. PySINDy is a Python package that provides tools for applying the sparse identification of nonlinear dynamics (SINDy) approach to data-driven model discovery. In this major update to PySINDy, we implement several advanced features that enable the discovery of more general differential equations from noisy and limited data. The library of candidate terms is extended for the identification of actuated systems, partial differential equations (PDEs), and implicit differential equations. Robust formulations, including the integral form of SINDy and ensembling techniques, are also implemented to improve performance for real-world data. Finally, we provide a range of new optimization algorithms, including several sparse regression techniques and algorithms to enforce and promote inequality constraints and stability. Together, these updates enable entirely new SINDy model discovery capabilities that have not been reported in the literature, such as constrained PDE identification and ensembling with different sparse regression optimizers

Comparative Genomic Characterization of Francisella tularensis Strains Belonging to Low and High Virulence Subspecies

Tularemia is a geographically widespread, severely debilitating, and occasionally lethal disease in humans. It is caused by infection by a gram-negative bacterium, Francisella tularensis. In order to better understand its potency as an etiological agent as well as its potential as a biological weapon, we have completed draft assemblies and report the first complete genomic characterization of five strains belonging to the following different Francisella subspecies (subsp.): the F. tularensis subsp. tularensis FSC033, F. tularensis subsp. holarctica FSC257 and FSC022, and F. tularensis subsp. novicida GA99-3548 and GA99-3549 strains. Here, we report the sequencing of these strains and comparative genomic analysis with recently available public Francisella sequences, including the rare F. tularensis subsp. mediasiatica FSC147 strain isolate from the Central Asian Region. We report evidence for the occurrence of large-scale rearrangement events in strains of the holarctica subspecies, supporting previous proposals that further phylogenetic subdivisions of the Type B clade are likely. We also find a significant enrichment of disrupted or absent ORFs proximal to predicted breakpoints in the FSC022 strain, including a genetic component of the Type I restriction-modification defense system. Many of the pseudogenes identified are also disrupted in the closely related rarely human pathogenic F. tularensis subsp. mediasiatica FSC147 strain, including modulator of drug activity B (mdaB) (FTT0961), which encodes a known NADPH quinone reductase involved in oxidative stress resistance. We have also identified genes exhibiting sequence similarity to effectors of the Type III (T3SS) and components of the Type IV secretion systems (T4SS). One of the genes, msrA2 (FTT1797c), is disrupted in F. tularensis subsp. mediasiatica and has recently been shown to mediate bacterial pathogen survival in host organisms. Our findings suggest that in addition to the duplication of the Francisella Pathogenicity Island, and acquisition of individual loci, adaptation by gene loss in the more recently emerged tularensis, holarctica, and mediasiatica subspecies occurred and was distinct from evolutionary events that differentiated these subspecies, and the novicida subspecies, from a common ancestor. Our findings are applicable to future studies focused on variations in Francisella subspecies pathogenesis, and of broader interest to studies of genomic pathoadaptation in bacteria

Effectiveness of the Ad26.COV2.S vaccine in health-care workers in South Africa (the Sisonke study) : results from a single-arm, open-label, phase 3B, implementation study

DATA SHARING : Individual participant data will not be made available. Study protocol, statistical analysis plan, and analytical code will be available from the time of publication in response to any reasonable request to the corresponding author.BACKGROUND : We aimed to assess the effectiveness of a single dose of the Ad26.COV2.S vaccine (Johnson & Johnson) in health-care workers in South Africa during two waves of the South African COVID-19 epidemic. METHODS : In the single-arm, open-label, phase 3B implementation Sisonke study, health-care workers aged 18 years and older were invited for vaccination at one of 122 vaccination sites nationally. Participants received a single dose of 5 x 10¹⁰ viral particles of the Ad26.COV2.S vaccine. Vaccinated participants were linked with their person-level data from one of two national medical insurance schemes (scheme A and scheme B) and matched for COVID-19 risk with an unvaccinated member of the general population. The primary outcome was vaccine effectiveness against severe COVID-19, defined as COVID-19-related admission to hospital, hospitalisation requiring critical or intensive care, or death, in health-care workers compared with the general population, ascertained 28 days or more after vaccination or matching, up to data cutoff. This study is registered with the South African National Clinical Trial Registry, DOH-27-022021-6844, ClinicalTrials.gov, NCT04838795, and the Pan African Clinical Trials Registry, PACTR202102855526180, and is closed to accrual. FINDINGS : Between Feb 17 and May 17, 2021, 477 102 health-care workers were enrolled and vaccinated, of whom 357 401 (74·9%) were female and 119 701 (25·1%) were male, with a median age of 42·0 years (33·0–51·0). 215 813 vaccinated individuals were matched with 215 813 unvaccinated individuals. As of data cutoff (July 17, 2021), vaccine effectiveness derived from the total matched cohort was 83% (95% CI 75–89) to prevent COVID-19-related deaths, 75% (69–82) to prevent COVID-19-related hospital admissions requiring critical or intensive care, and 67% (62–71) to prevent COVID-19-related hospitalisations. The vaccine effectiveness for all three outcomes were consistent across scheme A and scheme B. The vaccine effectiveness was maintained in older health-care workers and those with comorbidities including HIV infection. During the course of the study, the beta (B.1.351) and then the delta (B.1.617.2) SARS-CoV-2 variants of concerns were dominant, and vaccine effectiveness remained consistent (for scheme A plus B vaccine effectiveness against COVID-19-related hospital admission during beta wave was 62% [95% CI 42–76] and during delta wave was 67% [62–71], and vaccine effectiveness against COVID-19-related death during beta wave was 86% [57–100] and during delta wave was 82% [74–89]). INTERPRETATION : The single-dose Ad26.COV2.S vaccine shows effectiveness against severe COVID-19 disease and COVID-19-related death after vaccination, and against both beta and delta variants, providing real-world evidence for its use globally.National Treasury of South Africa, the National Department of Health, Solidarity Response Fund NPC, The Michael & Susan Dell Foundation, The Elma Vaccines and Immunization Foundation, and the Bill & Melinda Gates Foundation.http;//thelancet.comam2023Paediatrics and Child HealthSchool of Health Systems and Public Health (SHSPH

Search for gravitational-lensing signatures in the full third observing run of the LIGO-Virgo network

Gravitational lensing by massive objects along the line of sight to the source causes distortions of gravitational wave-signals; such distortions may reveal information about fundamental physics, cosmology and astrophysics. In this work, we have extended the search for lensing signatures to all binary black hole events from the third observing run of the LIGO--Virgo network. We search for repeated signals from strong lensing by 1) performing targeted searches for subthreshold signals, 2) calculating the degree of overlap amongst the intrinsic parameters and sky location of pairs of signals, 3) comparing the similarities of the spectrograms amongst pairs of signals, and 4) performing dual-signal Bayesian analysis that takes into account selection effects and astrophysical knowledge. We also search for distortions to the gravitational waveform caused by 1) frequency-independent phase shifts in strongly lensed images, and 2) frequency-dependent modulation of the amplitude and phase due to point masses. None of these searches yields significant evidence for lensing. Finally, we use the non-detection of gravitational-wave lensing to constrain the lensing rate based on the latest merger-rate estimates and the fraction of dark matter composed of compact objects

Biolink Model: A universal schema for knowledge graphs in clinical, biomedical, and translational science

<h2>What's Changed</h2> <ul> <li>Documentation and repo hierarchy refactoring by @sierra-moxon in https://github.com/biolink/biolink-model/pull/1418</li> </ul> <p>Summary: 4.0.0 is a major release that includes many changes to the documentation for Biolink Model as well as the reorganization of the repository to support the new documentation structure and comply with LinkML best practices. The model itself has not changed significantly, but the documentation has been updated to reflect the current state of the model, and includes new visualizations of the model, additional text-based documentation, and a new gh-pages documentation layout.</p> <p><strong>Full Changelog</strong>: https://github.com/biolink/biolink-model/compare/v3.6.0...v4.0.0</p>Please cite the following works when using this software