TGFβ/BMP immune signaling affects abundance and function of C. elegans gut commensals.

The gut microbiota contributes to host health and fitness, and imbalances in its composition are associated with pathology. However, what shapes microbiota composition is not clear, in particular the role of genetic factors. Previous work in Caenorhabditis elegans defined a characteristic worm gut microbiota significantly influenced by host genetics. The current work explores the role of central regulators of host immunity and stress resistance, employing qPCR and CFU counts to measure abundance of core microbiota taxa in mutants raised on synthetic communities of previously-isolated worm gut commensals. This revealed a bloom, specifically of Enterobacter species, in immune-compromised TGFβ/BMP mutants. Imaging of fluorescently labeled Enterobacter showed that TGFβ/BMP-exerted control operated primarily in the anterior gut and depended on multi-tissue contributions. Enterobacter commensals are common in the worm gut, contributing to infection resistance. However, disruption of TGFβ/BMP signaling turned a normally beneficial Enterobacter commensal to pathogenic. These results demonstrate specificity in gene-microbe interactions underlying gut microbial homeostasis and highlight the pathogenic potential of their disruption

A New Bound for the Brown--Erd\H{o}s--S\'os Problem

Let $f(n,v,e)$ denote the maximum number of edges in a $3$-uniform hypergraph not containing $e$ edges spanned by at most $v$ vertices. One of the most influential open problems in extremal combinatorics then asks, for a given number of edges $e \geq 3$, what is the smallest integer $d=d(e)$ so that $f(n,e+d,e) = o(n^2)$? This question has its origins in work of Brown, Erd\H{o}s and S\'os from the early 70's and the standard conjecture is that $d(e)=3$ for every $e \geq 3$. The state of the art result regarding this problem was obtained in 2004 by S\'{a}rk\"{o}zy and Selkow, who showed that $f(n,e + 2 + \lfloor \log_2 e \rfloor,e) = o(n^2)$. The only improvement over this result was a recent breakthrough of Solymosi and Solymosi, who improved the bound for $d(10)$ from 5 to 4. We obtain the first asymptotic improvement over the S\'{a}rk\"{o}zy--Selkow bound, showing that $$ f(n, e + O(\log e/ \log\log e), e) = o(n^2). $

A New Bound for the Brown-Erdős-Sós Problem

Let f(n,v,e) denote the maximum number of edges in a 3-uniform hypergraph not containing e edges spanned by at most v vertices. One of the most influential open problems in extremal combinatorics then asks, for a given number of edges e≥3, what is the smallest integer d=d(e) so that f(n,e+d,e)=o(n²)? This question has its origins in work of Brown, Erdős and Sós from the early 70's and the standard conjecture is that d(e)=3 for every e≥3. The state of the art result regarding this problem was obtained in 2004 by Sárközy and Selkow, who showed that f(n,e+2+⌊log₂e⌋,e)=o(n²). The only improvement over this result was a recent breakthrough of Solymosi and Solymosi, who improved the bound for d(10) from 5 to 4. We obtain the first asymptotic improvement over the Sárközy--Selkow bound, showing that f(n,e+O(loge/logloge),e)=o(n²)

Return to Sport and Athletic Function in an Active Population After Primary Arthroscopic Labral Reconstruction of the Hip

Background: Labral reconstruction has been advocated as an alternative to debridement for the treatment of irreparable labral tears, showing favorable short-term results. However, literature is scarce regarding outcomes and return to sport in the nonelite athletic population. Purpose: To report minimum 1-year clinical outcomes and the rate of return to sport in athletic patients who underwent primary hip arthroscopy with labral reconstruction in the setting of femoroacetabular impingement syndrome and irreparable labral tears. Study Design: Case series; Level of evidence, 4. Methods: Data were prospectively collected and retrospectively analyzed for patients who underwent an arthroscopic labral reconstruction between August 2012 and December 2017. Patients were included if they identified as an athlete (high school, college, recreational, or amateur); had follow-up on the following patient-reported outcomes (PROs): modified Harris Hip Score (mHHS), Nonarthritic Hip Score (NAHS), Hip Outcome Score–Sport Specific Subscale (HOS-SSS), and visual analog scale (VAS); and completed a return-to-sport survey at 1 year postoperatively. Patients were excluded if they underwent any previous ipsilateral hip surgery, had dysplasia, or had prior hip conditions. The proportions of patients who achieved the minimal clinically important difference (MCID) and patient acceptable symptomatic state (PASS) for mHHS and HOS-SSS were calculated. Statistical significance was set at P =.05. Results: There were 32 (14 females) athletes who underwent primary arthroscopic labral reconstruction during the study period. The mean age and body mass index of the group were 40.3 years (range, 15.5-58.7 years) and 27.9 kg/m2 (range, 19.6-40.1 kg/m2), respectively. The mean follow-up was 26.4 months (range, 12-64.2 months). All patients demonstrated significant improvement in mHHS, NAHS, HOS-SSS, and VAS (P \u3c.001) at latest follow-up. Additionally, 84.4% achieved MCID and 81.3% achieved PASS for mHHS, and 87.5% achieved MCID and 75% achieved PASS for HOS-SSS. VAS pain scores decreased from 4.4 to 1.8, and the satisfaction with surgery was 7.9 out of 10. The rate of return to sport was 78%. Conclusion: At minimum 1-year follow-up, primary arthroscopic labral reconstruction, in the setting of femoroacetabular impingement syndrome and irreparable labral tears, was associated with significant improvement in PROs in athletic populations. Return to sport within 1 year of surgery was 78%

Generative Social Choice

Traditionally, social choice theory has only been applicable to choices among a few predetermined alternatives but not to more complex decisions such as collectively selecting a textual statement. We introduce generative social choice, a framework that combines the mathematical rigor of social choice theory with large language models' capability to generate text and extrapolate preferences. This framework divides the design of AI-augmented democratic processes into two components: first, proving that the process satisfies rigorous representation guarantees when given access to oracle queries; second, empirically validating that these queries can be approximately implemented using a large language model. We illustrate this framework by applying it to the problem of generating a slate of statements that is representative of opinions expressed as free-form text, for instance in an online deliberative process