Breast milk-derived human milk oligosaccharides promote Bifidobacterium interactions within a single ecosystem

Diet-microbe interactions play an important role in modulating the early-life microbiota, with Bifidobacterium strains and species dominating the gut of breast-fed infants. Here, we sought to explore how infant diet drives distinct bifidobacterial community composition and dynamics within individual infant ecosystems. Genomic characterisation of 19 strains isolated from breast-fed infants revealed a diverse genomic architecture enriched in carbohydrate metabolism genes, which was distinct to each strain, but collectively formed a pangenome across infants. Presence of gene clusters implicated in digestion of human milk oligosaccharides (HMOs) varied between species, with growth studies indicating that within single infants there were differences in the ability to utilise 2'FL and LNnT HMOs between strains. Cross-feeding experiments were performed with HMO degraders and non-HMO users (using spent or 'conditioned' media and direct co-culture). Further H-NMR analysis identified fucose, galactose, acetate, and N-acetylglucosamine as key by-products of HMO metabolism; as demonstrated by modest growth of non-HMO users on spend media from HMO metabolism. These experiments indicate how HMO metabolism permits the sharing of resources to maximise nutrient consumption from the diet and highlights the cooperative nature of bifidobacterial strains and their role as 'foundation' species in the infant ecosystem. The intra- and inter-infant bifidobacterial community behaviour may contribute to the diversity and dominance of Bifidobacterium in early life and suggests avenues for future development of new diet and microbiota-based therapies to promote infant health

Three cachexia phenotypes and the impact of fat-only loss on survival in FOLFIRINOX therapy for pancreatic cancer

BACKGROUND: By the traditional definition of unintended weight loss, cachexia develops in ~80% of patients with pancreatic ductal adenocarcinoma (PDAC). Here, we measure the longitudinal body composition changes in patients with advanced PDAC undergoing 5-fluorouracil, leucovorin, irinotecan, and oxaliplatin therapy. METHODS: We performed a retrospective review of 53 patients with advanced PDAC on 5-fluorouracil, leucovorin, irinotecan, and oxaliplatin as first line therapy at Indiana University Hospital from July 2010 to August 2015. Demographic, clinical, and survival data were collected. Body composition measurement by computed tomography (CT), trend, univariate, and multivariate analysis were performed. RESULTS: Among all patients, three cachexia phenotypes were identified. The majority of patients, 64%, had Muscle and Fat Wasting (MFW), while 17% had Fat-Only Wasting (FW) and 19% had No Wasting (NW). NW had significantly improved overall median survival (OMS) of 22.6 months vs. 13.0 months for FW and 12.2 months for MFW (P = 0.02). FW (HR = 5.2; 95% confidence interval = 1.5-17.3) and MFW (HR = 1.8; 95% confidence interval = 1.1-2.9) were associated with an increased risk of mortality compared with NW. OMS and risk of mortality did not differ between FW and MFW. Progression of disease, sarcopenic obesity at diagnosis, and primary tail tumours were also associated with decreased OMS. On multivariate analysis, cachexia phenotype and chemotherapy response were independently associated with survival. Notably, CT-based body composition analysis detected tissue loss of >5% in 81% of patients, while the traditional definition of >5% body weight loss identified 56.6%. CONCLUSIONS: Distinct cachexia phenotypes were observed in this homogeneous population of patients with equivalent stage, diagnosis, and first-line treatment. This suggests cellular, molecular, or genetic heterogeneity of host or tumour. Survival among patients with FW was as poor as for MFW, indicating adipose tissue plays a crucial role in cachexia and PDAC mortality. Adipose tissue should be studied for its mechanistic contributions to cachexia

Randomness Concerns When Deploying Differential Privacy

The U.S. Census Bureau is using differential privacy (DP) to protect confidential respondent data collected for the 2020 Decennial Census of Population & Housing. The Census Bureau's DP system is implemented in the Disclosure Avoidance System (DAS) and requires a source of random numbers. We estimate that the 2020 Census will require roughly 90TB of random bytes to protect the person and household tables. Although there are critical differences between cryptography and DP, they have similar requirements for randomness. We review the history of random number generation on deterministic computers, including von Neumann's "middle-square" method, Mersenne Twister (MT19937) (previously the default NumPy random number generator, which we conclude is unacceptable for use in production privacy-preserving systems), and the Linux /dev/urandom device. We also review hardware random number generator schemes, including the use of so-called "Lava Lamps" and the Intel Secure Key RDRAND instruction. We finally present our plan for generating random bits in the Amazon Web Services (AWS) environment using AES-CTR-DRBG seeded by mixing bits from /dev/urandom and the Intel Secure Key RDSEED instruction, a compromise of our desire to rely on a trusted hardware implementation, the unease of our external reviewers in trusting a hardware-only implementation, and the need to generate so many random bits.Comment: 12 pages plus 2 pages bibliograph

Revealing the progenitor of SN 2021zby through analysis of the TESSTESS shock-cooling light curve

We present early observations and analysis of the double-peaked Type IIb supernova (SN IIb) 2021zby. $TESS$ captured the prominent early shock cooling peak of SN 2021zby within the first $\sim$10 days after explosion with a 30-minute cadence. We present optical and near-infrared spectral series of SN 2021zby, including three spectra during the shock cooling phase. Using a multi-band model fit, we find that the inferred properties of its progenitor are consistent with a red supergiant or yellow supergiant, with an envelope mass of $\sim$0.3-3.0 M$_\odot$ and an envelope radius of $\sim$50-350$R_\odot$. These inferred progenitor properties are similar to those of other SNe IIb with double-peak feature, such as SNe 1993J, 2011dh, 2016gkg and 2017jgh. This study further validates the importance of the high cadence and early coverage in resolving the shape of the shock cooling light curve, while the multi-band observations, especially UV, is also necessary to fully constrain the progenitor properties.Comment: 12 pages, 5 figures, 2 tables, submitted to ApJ

Factors affecting residency rank-listing: A Maxdiff survey of graduating Canadian medical students

<p>Abstract</p> <p>Background</p> <p>In Canada, graduating medical students consider many factors, including geographic, social, and academic, when ranking residency programs through the Canadian Residency Matching Service (CaRMS). The relative significance of these factors is poorly studied in Canada. It is also unknown how students differentiate between their top program choices. This survey study addresses the influence of various factors on applicant decision making.</p> <p>Methods</p> <p>Graduating medical students from all six Ontario medical schools were invited to participate in an online survey available for three weeks prior to the CaRMS match day in 2010. Max-Diff discrete choice scaling, multiple choice, and drop-list style questions were employed. The Max-Diff data was analyzed using a scaled simple count method. Data for how students distinguish between top programs was analyzed as percentages. Comparisons were made between male and female applicants as well as between family medicine and specialist applicants; statistical significance was determined by the Mann-Whitney test.</p> <p>Results</p> <p>In total, 339 of 819 (41.4%) eligible students responded. The variety of clinical experiences and resident morale were weighed heavily in choosing a residency program; whereas financial incentives and parental leave attitudes had low influence. Major reasons that applicants selected their first choice program over their second choice included the distance to relatives and desirability of the city. Both genders had similar priorities when selecting programs. Family medicine applicants rated the variety of clinical experiences more importantly; whereas specialty applicants emphasized academic factors more.</p> <p>Conclusions</p> <p>Graduating medical students consider program characteristics such as the variety of clinical experiences and resident morale heavily in terms of overall priority. However, differentiation between their top two choice programs is often dependent on social/geographic factors. The results of this survey will contribute to a better understanding of the CaRMS decision making process for both junior medical students and residency program directors.</p

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment