Pilot-WINGS: An extended MUSE view of the structure of Abell 370

We investigate the strong-lensing cluster Abell 370 (A370) using a wide Integral Field Unit (IFU) spectroscopic mosaic from the Multi-Unit Spectroscopic Explorer (MUSE). IFU spectroscopy provides significant insight into the structure and mass content of galaxy clusters, yet IFU-based cluster studies focus almost exclusively on the central Einstein-radius region. Covering over 14 arcmin2, the new MUSE mosaic extends significantly beyond the A370 Einstein radius, providing, for the first time, a detailed look at the cluster outskirts. Combining these data with wide-field, multi-band Hubble Space Telescope (HST) imaging from the BUFFALO project, we analyse the distribution of objects within the cluster and along the line of sight. Identifying 416 cluster galaxies, we use kinematics to trace the radial mass profile of the halo, providing a mass estimate independent from the lens model. We also measure radially averaged properties of the cluster members, tracking their evolution as a function of infall. Thanks to the high spatial resolution of our data, we identify six cluster members acting as galaxy–galaxy lenses, which constrain localized mass distributions beyond the Einstein radius. Finally, taking advantage of MUSE’s 3D capabilities, we detect and analyse multiple spatially extended overdensities outside of the cluster that influence lensing-derived halo mass estimates. We stress that much of this work is only possible thanks to the robust, extended IFU coverage, highlighting its importance even in less optically dense cluster regions. Overall, this work showcases the power of combining HST + MUSE, and serves as the initial step towards a larger and wider program targeting several clusters

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Glucose metabolism transcriptome clustering identifies subsets of resectable lung adenocarcinoma with different prognosesCentral MessagePerspective

Objectives: Reprogramming of energy metabolism is a well-established hallmark of cancer, with aerobic glycolysis classically considered a prominent feature. We investigate the heterogeneity in glucose metabolism pathways within resectable primary lung adenocarcinoma and its clinical significance. Methods: Using The Cancer Genome Atlas data, RNA expressions were extracted from 489 primary lung adenocarcinoma samples. Prognostic influence of glycolytic, aerobic, and mitochondrial markers (monocarboxylate transporter [MCT]4, MCT1, and translocase of outer mitochondrial membrane 20, respectively) was assessed using Kaplan-Meier analysis. Clustering of 35 genes involved in glucose metabolism was performed using the k-means method. The clusters were then analyzed for associations with demographic, clinical, and pathologic variables. Overall survival was assessed using the Kaplan-Meier estimator. Multivariate analysis was performed to assess the independent prognostic value of cluster membership. Results: Classical statistical approach showed that higher expression of MCT4 was associated with a significantly worse prognosis. Increased expression of translocase of outer mitochondrial membrane 20 was associated with a nonsignificant trend toward better prognosis, and increased expression of MCT1 was associated with a better outcome. Clustering identified 3 major metabolic phenotypes, dominantly hypometabolic, dominantly oxidative, and dominantly mixed oxidative/glycolytic with significantly different pathologic stage distribution and prognosis; mixed oxidative/glycolytic was associated with worse survival. Cluster membership was independently associated with survival. Conclusions: This study demonstrates the existence of distinct glucose metabolism clusters in resectable lung adenocarcinoma, providing valuable prognostic information. The findings highlight the potential relevance of considering metabolic profiles when designing strategies for reprogramming energy metabolism. Further studies are warranted to validate these findings in different cancer types and populations

Total Psoas Area and Total Muscular Parietal Area Affect Long-Term Survival of Patients Undergoing Pneumonectomy for Non-Small Cell Lung Cancer

There is no standardization in methods to assess sarcopenia; in particular the prognostic significance of muscular fatty infiltration in lung cancer patients undergoing surgery has not been evaluated so far. We thus performed several computed tomography (CT)-based morphometric measurements of sarcopenia in 238 consecutive non-small cell lung-cancer patients undergoing pneumonectomy from 1 January 2007 to 31 December 2015. Sarcopenia was assessed by the following CT-based parameters: cross-sectional total psoas area (TPA), cross-sectional total muscle area (TMA), and total parietal muscle area (TPMA), defined as TMA without TPA. Measures were performed at the level of the third lumbar vertebra and were obtained for the entire muscle surface, as well as by excluding fatty infiltration based on CT attenuation. Findings were stratified for gender, and a threshold of the 33rd percentile was set to define sarcopenia. Furthermore, we assessed the possibility of being sarcopenic at both the TPA and TPMA level, or not, by taking into account of not fatty infiltration. Five-year survival was 39.1% for the whole population. Lower TPA, TMA, and TPA were associated with lower survival at univariate analysis; taking into account muscular fatty infiltration did not result in more powerful discrimination. Being sarcopenic at both psoas and parietal muscle level had the optimum discriminating power. At the multivariable analysis, being sarcopenic at both psoas and parietal muscles (considering the whole muscle areas, including muscular fat), male sex, increasing age, and tumor stage, as well as Charlson Comorbidity Index (CCI), were independently associated with worse long-term outcomes. We conclude that sarcopenia is a powerful negative prognostic factor in patients with lung cancer treated by pneumonectomy

Normalized Pulmonary Artery Diameter Predicts Occurrence of Postpneumonectomy Respiratory Failure, ARDS, and Mortality

Hypothesizing that pulmonary artery diameter is a marker of subclinical pulmonary hypertension, we assessed its impact on postoperative outcome in patients requiring pneumonectomy. Morphometric, clinical, and laboratory data were retrospectively retrieved from files of 294 consecutive patients treated by pneumonectomy for malignancy (289 NSCLC). Pulmonary artery was measured at bifurcation level on CT scan and normalized by body surface area. Median normalized pulmonary artery diameter (cut-off for analyses) was 14 mm/m2. Postoperatively, 46 patients required re-do intubation and 30 had acute respiratory distress syndrome (ARDS). Multivariate analysis showed that Charlson Comorbidity Index >5 (p = 0.0009, OR 3.8 [1.76–8.22]), right side of pneumonectomy (p = 0.013, OR 2.37 [1.20–4.71]), and higher normalized pulmonary artery diameter (p = 0.029, OR 2.16 [1.08–4.33]) were independent predictors of re-do intubation, while Charlson Comorbidity Index >5 (p = 0.018, OR 2.55 [1.17–5.59]) and higher normalized pulmonary artery diameter (p = 0.028, OR = 2.52 [1.10–5.77]) were independently associated with occurrence of ARDS. Post-operative mortality was 8.5%. Higher normalized pulmonary artery diameter, (p = 0.026, OR 3.39 [1.15–9.95]), right side of pneumonectomy (p = 0.0074, OR 4.11 [1.46–11.56]), and Charlson Comorbidity Index >5 (p = 0.0011, OR 5.56 [1.99–15.54]) were independent predictors of postoperative death. We conclude that pre-operative normalized pulmonary artery diameter predicts the risk of re-do intubation, ARDS and mortality in patients undergoing pneumonectomy for cancer

Normalized Pulmonary Artery Diameter Predicts Occurrence of Postpneumonectomy Respiratory Failure, ARDS, and Mortality

Hypothesizing that pulmonary artery diameter is a marker of subclinical pulmonary hypertension, we assessed its impact on postoperative outcome in patients requiring pneumonectomy. Morphometric, clinical, and laboratory data were retrospectively retrieved from files of 294 consecutive patients treated by pneumonectomy for malignancy (289 NSCLC). Pulmonary artery was measured at bifurcation level on CT scan and normalized by body surface area. Median normalized pulmonary artery diameter (cut-off for analyses) was 14 mm/m2. Postoperatively, 46 patients required re-do intubation and 30 had acute respiratory distress syndrome (ARDS). Multivariate analysis showed that Charlson Comorbidity Index &gt;5 (p = 0.0009, OR 3.8 [1.76–8.22]), right side of pneumonectomy (p = 0.013, OR 2.37 [1.20–4.71]), and higher normalized pulmonary artery diameter (p = 0.029, OR 2.16 [1.08–4.33]) were independent predictors of re-do intubation, while Charlson Comorbidity Index &gt;5 (p = 0.018, OR 2.55 [1.17–5.59]) and higher normalized pulmonary artery diameter (p = 0.028, OR = 2.52 [1.10–5.77]) were independently associated with occurrence of ARDS. Post-operative mortality was 8.5%. Higher normalized pulmonary artery diameter, (p = 0.026, OR 3.39 [1.15–9.95]), right side of pneumonectomy (p = 0.0074, OR 4.11 [1.46–11.56]), and Charlson Comorbidity Index &gt;5 (p = 0.0011, OR 5.56 [1.99–15.54]) were independent predictors of postoperative death. We conclude that pre-operative normalized pulmonary artery diameter predicts the risk of re-do intubation, ARDS and mortality in patients undergoing pneumonectomy for cancer.</jats:p