3C 220.3: a radio galaxy lensing a submillimeter galaxy

Herschel Space Observatory photometry and extensive multiwavelength followup have revealed that the powerful radio galaxy 3C 220.3 at z=0.685 acts as a gravitational lens for a background submillimeter galaxy (SMG) at z=2.221. At an observed wavelength of 1mm, the SMG is lensed into three distinct images. In the observed near infrared, these images are connected by an arc of 1.8" radius forming an Einstein half-ring centered near the radio galaxy. In visible light, only the arc is apparent. 3C 220.3 is the only known instance of strong galaxy-scale lensing by a powerful radio galaxy not located in a galaxy cluster and therefore it offers the potential to probe the dark matter content of the radio galaxy host. Lens modeling rejects a single lens, but two lenses centered on the radio galaxy host A and a companion B, separated by 1.5", provide a fit consistent with all data and reveal faint candidates for the predicted fourth and fifth images. The model does not require an extended common dark matter halo, consistent with the absence of extended bright X-ray emission on our Chandra image. The projected dark matter fractions within the Einstein radii of A (1.02") and B (0.61") are about 0.4 +/- 0.3 and 0.55 +/- 0.3. The mass to i-band light ratios of A and B, M/L ~ 8 +/- 4 Msun/Lsun, appear comparable to those of radio-quiet lensing galaxies at the same redshift in the CASTLES, LSD, and SL2S samples. The lensed SMG is extremely bright with observed f(250um) = 440mJy owing to a magnification factor mu~10. The SMG spectrum shows luminous, narrow CIV 154.9nm emission, revealing that the SMG houses a hidden quasar in addition to a violent starburst. Multicolor image reconstruction of the SMG indicates a bipolar morphology of the emitted ultraviolet (UV) light suggestive of cones through which UV light escapes a dust-enshrouded nucleus.Comment: 17 pages, 14 Figures, accepted for publication in Ap

Long-term viability and function of transplanted islets macroencapsulated at high density are achieved by enhanced oxygen supply

Transplantation of encapsulated islets can cure diabetes without immunosuppression, but oxygen supply limitations can cause failure. We investigated a retrievable macroencapsulation device wherein islets are encapsulated in a planar alginate slab and supplied with exogenous oxygen from a replenishable gas chamber. Translation to clinically-useful devices entails reduction of device size by increasing islet surface density, which requires increased gas chamber pO Here we show that islet surface density can be substantially increased safely by increasing gas chamber pO to a supraphysiological level that maintains all islets viable and functional. These levels were determined from measurements of pO profiles in islet-alginate slabs. Encapsulated islets implanted with surface density as high as 4,800 islet equivalents/cm in diabetic rats maintained normoglycemia for more than 7 months and provided near-normal intravenous glucose tolerance tests. Nearly 90% of the original viable tissue was recovered after device explantation. Damaged islets failed after progressively shorter times. The required values of gas chamber pO were predictable from a mathematical model of oxygen consumption and diffusion in the device. These results demonstrate feasibility of developing retrievable macroencapsulated devices small enough for clinical use and provide a firm basis for design of devices for testing in large animals and humans

Stratification of co-evolving genomic groups using ranked phylogenetic profiles

<p>Abstract</p> <p>Background</p> <p>Previous methods of detecting the taxonomic origins of arbitrary sequence collections, with a significant impact to genome analysis and in particular metagenomics, have primarily focused on compositional features of genomes. The evolutionary patterns of phylogenetic distribution of genes or proteins, represented by phylogenetic profiles, provide an alternative approach for the detection of taxonomic origins, but typically suffer from low accuracy. Herein, we present <it>rank-BLAST</it>, a novel approach for the assignment of protein sequences into genomic groups of the same taxonomic origin, based on the ranking order of phylogenetic profiles of target genes or proteins across the reference database.</p> <p>Results</p> <p>The rank-BLAST approach is validated by computing the phylogenetic profiles of all sequences for five distinct microbial species of varying degrees of phylogenetic proximity, against a reference database of 243 fully sequenced genomes. The approach - a combination of sequence searches, statistical estimation and clustering - analyses the degree of sequence divergence between sets of protein sequences and allows the classification of protein sequences according to the species of origin with high accuracy, allowing taxonomic classification of 64% of the proteins studied. In most cases, a main cluster is detected, representing the corresponding species. Secondary, functionally distinct and species-specific clusters exhibit different patterns of phylogenetic distribution, thus flagging gene groups of interest. Detailed analyses of such cases are provided as examples.</p> <p>Conclusion</p> <p>Our results indicate that the rank-BLAST approach can capture the taxonomic origins of sequence collections in an accurate and efficient manner. The approach can be useful both for the analysis of genome evolution and the detection of species groups in metagenomics samples.</p

Software-Hardware Co-design for Fast and Scalable Training of Deep Learning Recommendation Models

Deep learning recommendation models (DLRMs) are used across many business-critical services at Facebook and are the single largest AI application in terms of infrastructure demand in its data-centers. In this paper we discuss the SW/HW co-designed solution for high-performance distributed training of large-scale DLRMs. We introduce a high-performance scalable software stack based on PyTorch and pair it with the new evolution of Zion platform, namely ZionEX. We demonstrate the capability to train very large DLRMs with up to 12 Trillion parameters and show that we can attain 40X speedup in terms of time to solution over previous systems. We achieve this by (i) designing the ZionEX platform with dedicated scale-out network, provisioned with high bandwidth, optimal topology and efficient transport (ii) implementing an optimized PyTorch-based training stack supporting both model and data parallelism (iii) developing sharding algorithms capable of hierarchical partitioning of the embedding tables along row, column dimensions and load balancing them across multiple workers; (iv) adding high-performance core operators while retaining flexibility to support optimizers with fully deterministic updates (v) leveraging reduced precision communications, multi-level memory hierarchy (HBM+DDR+SSD) and pipelining. Furthermore, we develop and briefly comment on distributed data ingestion and other supporting services that are required for the robust and efficient end-to-end training in production environments

Elective cancer surgery in COVID-19-free surgical pathways during the SARS-CoV-2 pandemic: An international, multicenter, comparative cohort study

PURPOSE As cancer surgery restarts after the first COVID-19 wave, health care providers urgently require data to determine where elective surgery is best performed. This study aimed to determine whether COVID-19–free surgical pathways were associated with lower postoperative pulmonary complication rates compared with hospitals with no defined pathway. PATIENTS AND METHODS This international, multicenter cohort study included patients who underwent elective surgery for 10 solid cancer types without preoperative suspicion of SARS-CoV-2. Participating hospitals included patients from local emergence of SARS-CoV-2 until April 19, 2020. At the time of surgery, hospitals were defined as having a COVID-19–free surgical pathway (complete segregation of the operating theater, critical care, and inpatient ward areas) or no defined pathway (incomplete or no segregation, areas shared with patients with COVID-19). The primary outcome was 30-day postoperative pulmonary complications (pneumonia, acute respiratory distress syndrome, unexpected ventilation). RESULTS Of 9,171 patients from 447 hospitals in 55 countries, 2,481 were operated on in COVID-19–free surgical pathways. Patients who underwent surgery within COVID-19–free surgical pathways were younger with fewer comorbidities than those in hospitals with no defined pathway but with similar proportions of major surgery. After adjustment, pulmonary complication rates were lower with COVID-19–free surgical pathways (2.2% v 4.9%; adjusted odds ratio [aOR], 0.62; 95% CI, 0.44 to 0.86). This was consistent in sensitivity analyses for low-risk patients (American Society of Anesthesiologists grade 1/2), propensity score–matched models, and patients with negative SARS-CoV-2 preoperative tests. The postoperative SARS-CoV-2 infection rate was also lower in COVID-19–free surgical pathways (2.1% v 3.6%; aOR, 0.53; 95% CI, 0.36 to 0.76). CONCLUSION Within available resources, dedicated COVID-19–free surgical pathways should be established to provide safe elective cancer surgery during current and before future SARS-CoV-2 outbreaks

Elective Cancer Surgery in COVID-19-Free Surgical Pathways During the SARS-CoV-2 Pandemic: An International, Multicenter, Comparative Cohort Study.

PURPOSE: As cancer surgery restarts after the first COVID-19 wave, health care providers urgently require data to determine where elective surgery is best performed. This study aimed to determine whether COVID-19-free surgical pathways were associated with lower postoperative pulmonary complication rates compared with hospitals with no defined pathway. PATIENTS AND METHODS: This international, multicenter cohort study included patients who underwent elective surgery for 10 solid cancer types without preoperative suspicion of SARS-CoV-2. Participating hospitals included patients from local emergence of SARS-CoV-2 until April 19, 2020. At the time of surgery, hospitals were defined as having a COVID-19-free surgical pathway (complete segregation of the operating theater, critical care, and inpatient ward areas) or no defined pathway (incomplete or no segregation, areas shared with patients with COVID-19). The primary outcome was 30-day postoperative pulmonary complications (pneumonia, acute respiratory distress syndrome, unexpected ventilation). RESULTS: Of 9,171 patients from 447 hospitals in 55 countries, 2,481 were operated on in COVID-19-free surgical pathways. Patients who underwent surgery within COVID-19-free surgical pathways were younger with fewer comorbidities than those in hospitals with no defined pathway but with similar proportions of major surgery. After adjustment, pulmonary complication rates were lower with COVID-19-free surgical pathways (2.2% v 4.9%; adjusted odds ratio [aOR], 0.62; 95% CI, 0.44 to 0.86). This was consistent in sensitivity analyses for low-risk patients (American Society of Anesthesiologists grade 1/2), propensity score-matched models, and patients with negative SARS-CoV-2 preoperative tests. The postoperative SARS-CoV-2 infection rate was also lower in COVID-19-free surgical pathways (2.1% v 3.6%; aOR, 0.53; 95% CI, 0.36 to 0.76). CONCLUSION: Within available resources, dedicated COVID-19-free surgical pathways should be established to provide safe elective cancer surgery during current and before future SARS-CoV-2 outbreaks

Effects of total fat intake on body fatness in adults

Background: The ideal proportion of energy from fat in our food and its relation to body weight is not clear. In order to prevent overweight and obesity in the general population, we need to understand the relationship between the proportion of energy from fat and resulting weight and body fatness in the general population. Objectives: To assess the effects of proportion of energy intake from fat on measures of body fatness (including body weight, waist circumference, percentage body fat and body mass index) in people not aiming to lose weight, using all appropriate randomised controlled trials (RCTs) of at least six months duration. Search methods: We searched CENTRAL, MEDLINE, Embase, Clinicaltrials.gov and the WHO International Clinical Trials Registry Platform (ICTRP) to October 2019. We did not limit the search by language. Selection criteria: Trials fulfilled the following criteria: 1) randomised intervention trial, 2) included adults aged at least 18 years, 3) randomised to a lower fat versus higher fat diet, without the intention to reduce weight in any participants, 4) not multifactorial and 5) assessed a measure of weight or body fatness after at least six months. We duplicated inclusion decisions and resolved disagreement by discussion or referral to a third party. Data collection and analysis: We extracted data on the population, intervention, control and outcome measures in duplicate. We extracted measures of body fatness (body weight, BMI, percentage body fat and waist circumference) independently in duplicate at all available time points. We performed random-effects meta-analyses, meta-regression, subgrouping, sensitivity, funnel plot analyses and GRADE assessment. Main results: We included 37 RCTs (57,079 participants). There is consistent high-quality evidence from RCTs that reducing total fat intake results in small reductions in body fatness; this was seen in almost all included studies and was highly resistant to sensitivity analyses (GRADE high-consistency evidence, not downgraded). The effect of eating less fat (compared with higher fat intake) is a mean body weight reduction of 1.4 kg (95% confidence interval (CI) -1.7 to -1.1 kg, in 53,875 participants from 26 RCTs, I2 = 75%). The heterogeneity was explained in subgrouping and meta-regression. These suggested that greater weight loss results from greater fat reductions in people with lower fat intake at baseline, and people with higher body mass index (BMI) at baseline. The size of the effect on weight does not alter over time and is mirrored by reductions in BMI (MD -0.5 kg/m2, 95% CI -0.6 to -0.3, 46,539 participants in 14 trials, I2 = 21%), waist circumference (MD -0.5 cm, 95% CI -0.7 to -0.2, 16,620 participants in 3 trials; I2 = 21%), and percentage body fat (MD -0.3% body fat, 95% CI -0.6 to 0.00, P = 0.05, in 2350 participants in 2 trials; I2 = 0%). There was no suggestion of harms associated with low fat diets that might mitigate any benefits on body fatness. The reduction in body weight was reflected in small reductions in LDL (-0.13 mmol/L, 95% CI -0.21 to -0.05), and total cholesterol (-0.23 mmol/L, 95% CI -0.32 to -0.14), with little or no effect on HDL cholesterol (-0.02 mmol/L, 95% CI -0.03 to 0.00), triglycerides (0.01 mmol/L, 95% CI -0.05 to 0.07), systolic (-0.75 mmHg, 95% CI -1.42 to -0.07) or diastolic blood pressure(-0.52 mmHg, 95% CI -0.95 to -0.09), all GRADE high-consistency evidence or quality of life (0.04, 95% CI 0.01 to 0.07, on a scale of 0 to 10, GRADE low-consistency evidence). Authors' conclusions: Trials where participants were randomised to a lower fat intake versus a higher fat intake, but with no intention to reduce weight, showed a consistent, stable but small effect of low fat intake on body fatness: slightly lower weight, BMI, waist circumference and percentage body fat compared with higher fat arms. Greater fat reduction, lower baseline fat intake and higher baseline BMI were all associated with greater reductions in weight. There was no evidence of harm to serum lipids, blood pressure or quality of life, but rather of small benefits or no effect

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised controlled, open-label, platform trial

SummaryBackground Azithromycin has been proposed as a treatment for COVID-19 on the basis of its immunomodulatoryactions. We aimed to evaluate the safety and efficacy of azithromycin in patients admitted to hospital with COVID-19.Methods In this randomised, controlled, open-label, adaptive platform trial (Randomised Evaluation of COVID-19Therapy [RECOVERY]), several possible treatments were compared with usual care in patients admitted to hospitalwith COVID-19 in the UK. The trial is underway at 176 hospitals in the UK. Eligible and consenting patients wererandomly allocated to either usual standard of care alone or usual standard of care plus azithromycin 500 mg once perday by mouth or intravenously for 10 days or until discharge (or allocation to one of the other RECOVERY treatmentgroups). Patients were assigned via web-based simple (unstratified) randomisation with allocation concealment andwere twice as likely to be randomly assigned to usual care than to any of the active treatment groups. Participants andlocal study staff were not masked to the allocated treatment, but all others involved in the trial were masked to theoutcome data during the trial. The primary outcome was 28-day all-cause mortality, assessed in the intention-to-treatpopulation. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936.Findings Between April 7 and Nov 27, 2020, of 16 442 patients enrolled in the RECOVERY trial, 9433 (57%) wereeligible and 7763 were included in the assessment of azithromycin. The mean age of these study participants was65·3 years (SD 15·7) and approximately a third were women (2944 [38%] of 7763). 2582 patients were randomlyallocated to receive azithromycin and 5181 patients were randomly allocated to usual care alone. Overall,561 (22%) patients allocated to azithromycin and 1162 (22%) patients allocated to usual care died within 28 days(rate ratio 0·97, 95% CI 0·87–1·07; p=0·50). No significant difference was seen in duration of hospital stay (median10 days [IQR 5 to >28] vs 11 days [5 to >28]) or the proportion of patients discharged from hospital alive within 28 days(rate ratio 1·04, 95% CI 0·98–1·10; p=0·19). Among those not on invasive mechanical ventilation at baseline, nosignificant difference was seen in the proportion meeting the composite endpoint of invasive mechanical ventilationor death (risk ratio 0·95, 95% CI 0·87–1·03; p=0·24).Interpretation In patients admitted to hospital with COVID-19, azithromycin did not improve survival or otherprespecified clinical outcomes. Azithromycin use in patients admitted to hospital with COVID-19 should be restrictedto patients in whom there is a clear antimicrobial indication

S117_EEG

EEG data fil