Abstract : We derive an operator based factorization theorem for the energy-energy correlation (EEC) observable in the back-to-back region, allowing the cross section to be written as a convolution of hard, jet and soft functions. We prove the equivalence of the soft functions for the EEC and color singlet transverse-momentum resummation to all-loop order, and give their analytic result to three-loops. Large logarithms appearing in the perturbative expansion of the EEC can be resummed to all orders using renormalization group evolution. We give analytic results for all required anomalous dimensions to three-loop order, providing the first example of a transverse-momentum (recoil) sensitive e + e − event shape whose anomalous dimensions are known at this order. The EEC can now be computed to next-to-next-to-next-to-leading logarithm matched to next-to-next-to-leading order, making it a prime candidate for precision QCD studies and extractions of the strong coupling constant. We anticipate that our factorization theorem will also be crucial for understanding non-perturbative power corrections for the EEC, and their relationship to those appearing in other observables.

We present an operator-based factorization formula for the transverse energy-energy correlator (TEEC) hadron collider event shape in the back-to-back (dijet) limit. This factorization formula exhibits a remarkably symmetric form, being a projection onto a scattering plane of a more standard transverse momentum dependent factorization. Soft radiation is incorporated through a dijet soft function, which can be elegantly obtained to next-to-next-to-leading order (NNLO) due to the symmetries of the problem. We present numerical results for the TEEC resummed to next-to-next-to-leading logarithm (NNLL) matched to fixed order at the LHC. Our results constitute the first NNLL resummation for a dijet event shape observable at a hadron collider, and the first analytic result for a hadron collider dijet soft function at NNLO. We anticipate that the theoretical simplicity of the TEEC observable will make it indispensable for precision studies of QCD at the LHC, and as a playground for theoretical studies of factorization and its violation.

We present an innovative approach to the linearly polarized gluons confined inside the unpolarized nucleon in lepton-nucleon scattering. Our method analyzes the correlation of energy flows at azimuthal separations φ. The interference of the spinning gluon with both positive and negative helicities translates into a cos(2φ) asymmetry imprinted on the detector. Unlike the conventional transverse momentum dependent probes, the cos(2φ) asymmetry in this approach is preserved by rotational symmetry, holds to all orders, and is free of radiation contamination and is thus expected to provide the exquisite signature of the nucleon linearly polarized gluons.

Abstract : We continue the study of power corrections for N -jettiness subtractions by analytically computing the complete next-to-leading power corrections at $$ \mathcal{O}\left({\alpha}_s\right) $$ O α s for colorsinglet production. This includes all nonlogarithmic terms and all partonic channels for Drell-Yan and gluon-fusion Higgs production. These terms are important to further improve the numerical performance of the subtractions, and to better understand the structure of power corrections beyond their leading logarithms, in particular their universality. We emphasize the importance of computing the power corrections differential in both the invariant mass, Q, and rapidity, Y, of the color-singlet system, which is necessary to account for the rapidity dependence in the subtractions. This also clarifies apparent disagreements in the literature. Performing a detailed numerical study, we find excellent agreement of our analytic results with a previous numerical extraction.

We demonstrate the recently proposed nucleon energy-energy correlator (NEEC) f_{EEC}(x,θ) can unveil the gluon saturation in the small-x regime in eA collisions. The novelty of this probe is that it is fully inclusive just like the deep-inelastic scattering (DIS), with no requirements of jets or hadrons but still provides an evident portal to the small-x dynamics through the shape of the θ distribution. We find that the saturation prediction is significantly different from the expectation of the collinear factorization.

BACKGROUND: In prospective cohorts, biological samples are generally stored over long periods before an adequate number of cases have accrued. We investigated the impact of sample storage at -80°C for 2 years on the stability of the V4 region of the 16S rRNA gene across seven different collection methods (i.e., no additive, 95% ethanol, RNAlater stabilization solution, fecal occult blood test cards, and fecal immunochemical test tubes for feces; OMNIgene ORAL tubes and Scope mouthwash for saliva) among 51 healthy volunteers. METHODS: Intraclass correlation coefficients (ICC) were calculated for the relative abundance of the top three phyla, the 20 most abundant genera, three alpha-diversity metrics, and the first principal coordinates of three beta-diversity matrices. RESULTS: The subject variability was much higher than the variability introduced by the sample collection type, and storage time. For fecal samples, microbial stability over 2 years was high across collection methods (range, ICCs = 0.70-0.99), except for the samples collected with no additive (range, ICCs = 0.23-0.83). For oral samples, most microbiome diversity measures were stable over time with ICCs above 0.74; however, ICCs for the samples collected with Scope mouthwash were lower for two alpha-diversity measures, Faiths phylogenetic diversity (0.23) and the observed number of operational taxonomic units (0.23). CONCLUSIONS: Fecal and oral samples in most used collection methods are stable for microbiome analyses after 2 years at -80°C, except for fecal samples with no additive. IMPACT: This study provides evidence that samples stored for an extended period from prospective studies are useful for microbiome analyses.

Chordoma is a rare bone cancer with variable clinical outcomes. Here, we recruited 184 sporadic chordoma patients from the US and Canada and collected their clinical and treatment data. The average age at diagnosis was 45.5 years (Range 5-78) and the chordoma site distribution was 49.2% clivus, 26.2% spinal, and 24.0% sacral. Most patients (97.5%) received surgery as the primary treatment, among whom 85.3% also received additional treatment. Except for the most prevalent cancers like prostate, lung, breast, and skin cancer, there was no discernible enrichment for any specific cancer type among patients or their family members. Among a subset of patients (N = 70) with tumor materials, we conducted omics analyses and obtained targeted panel sequencing and SNP array genotyping data for 51 and 49 patients, respectively. The most recurrent somatic driver mutations included PIK3CA (12%), followed by chromatin remodeling genes PBRM1 and SETD2. Amplification of the 6q27 region, containing the chordoma susceptibility gene TBXT, was detected in eight patients (16.3%). Clival patients appeared to be less likely to carry driver gene mutations, chromosome arm level deletion events (e.g., 5p, 5p, and 9p), or 6q27 amplification compared to sacral patients. After adjusting for age, sex, tumor site, and additional treatment, patients with somatic deletions of 14q (OR = 13.73, 95% CI 1.96-96.02, P = 0.008) and 18p (OR = 13.68, 95% CI 1.77-105.89, P = 0.012) were more likely to have persistent chordoma. The study highlights genomic heterogeneity in chordoma, potentially linked to location and clinical progression.

The gut microbiota may play a role in breast cancer etiology by regulating hormonal, metabolic and immunologic pathways. We investigated associations of fecal bacteria with breast cancer and nonmalignant breast disease in a case-control study conducted in Ghana, a country with rising breast cancer incidence and mortality. To do this, we sequenced the V4 region of the 16S rRNA gene to characterize bacteria in fecal samples collected at the time of breast biopsy (N = 379 breast cancer cases, N = 102 nonmalignant breast disease cases, N = 414 population-based controls). We estimated associations of alpha diversity (observed amplicon sequence variants [ASVs], Shannon index, and Faith's phylogenetic diversity), beta diversity (Bray-Curtis and unweighted/weighted UniFrac distance), and the presence and relative abundance of select taxa with breast cancer and nonmalignant breast disease using multivariable unconditional polytomous logistic regression. All alpha diversity metrics were strongly, inversely associated with odds of breast cancer and for those in the highest relative to lowest tertile of observed ASVs, the odds ratio (95% confidence interval) was 0.21 (0.13-0.36; P_trend < .001). Alpha diversity associations were similar for nonmalignant breast disease and breast cancer grade/molecular subtype. All beta diversity distance matrices and multiple taxa with possible estrogen-conjugating and immune-related functions were strongly associated with breast cancer (all Ps < .001). There were no statistically significant differences between breast cancer and nonmalignant breast disease cases in any microbiota metric. In conclusion, fecal bacterial characteristics were strongly and similarly associated with breast cancer and nonmalignant breast disease. Our findings provide novel insight into potential microbially-mediated mechanisms of breast disease.

Background

One mechanism that can explain the link between processed meat consumption and colorectal cancer (CRC) is the production of carcinogenic N-nitroso compounds (NOCs) in the gastrointestinal tract. Oral and gut microbes metabolize ingested proteins (a source of secondary and tertiary amines and amides) and can reduce nitrate to nitrite, generating potentially carcinogenic NOCs.

Objective

We evaluated whether nitrate/nitrite in processed meat or water influences the fecal or salivary microbiota.

Design

In this dietary intervention study, 63 volunteers consumed diets high in conventional processed meats for two weeks, switched to diets high in poultry for two weeks, and then consumed phytochemical-enriched conventional processed or low-nitrite processed meat diets for two weeks. During the intervention, they drank water with low nitrate concentrations and consumed a healthy diet with low antioxidants. Then the volunteers drank nitrate-enriched water for 1 week, in combination with one of the four different diets. We measured creatinine-adjusted urinary nitrate levels and characterized the oral and fecal microbiota using 16S rRNA amplicon sequencing.

Results

Using linear mixed models, we found that, compared to baseline, urinary nitrate levels were reduced during the phytochemical-enriched low-nitrite meat diet (p-value = 0.009) and modestly during the poultry diet (p-value = 0.048). In contrast, urinary nitrate increased after 1-week of drinking nitrate-enriched water (p-value<10^-5). Nitrate-enriched water, but not processed meats with or without phytochemicals, altered the saliva microbial population (p-value ≤0.001), and significantly increased abundance of 8 bacterial taxa, especially genus Neisseria and other nitrate-reducing taxa. Meats, phytochemicals and nitrate-enriched water had no significant effects on saliva alpha diversity or any diversity parameter measured for the fecal microbiota.

Conclusion

These findings support the hypothesis that drinking high nitrate water increases oral nitrate-reducing bacteria, which likely results in increased NOC. However, meat nitrate/nitrite at the levels tested had no effect on either the gut or oral bacteria. CLINICALTRIALS.

Gov identifier

NCT04138654.