Physical Processes in Star Formation

© 2020 Springer-Verlag. The final publication is available at Springer via https://doi.org/10.1007/s11214-020-00693-8.Star formation is a complex multi-scale phenomenon that is of significant importance for astrophysics in general. Stars and star formation are key pillars in observational astronomy from local star forming regions in the Milky Way up to high-redshift galaxies. From a theoretical perspective, star formation and feedback processes (radiation, winds, and supernovae) play a pivotal role in advancing our understanding of the physical processes at work, both individually and of their interactions. In this review we will give an overview of the main processes that are important for the understanding of star formation. We start with an observationally motivated view on star formation from a global perspective and outline the general paradigm of the life-cycle of molecular clouds, in which star formation is the key process to close the cycle. After that we focus on the thermal and chemical aspects in star forming regions, discuss turbulence and magnetic fields as well as gravitational forces. Finally, we review the most important stellar feedback mechanisms.Peer reviewedFinal Accepted Versio

The role of environmental factors in search and rescue incidents in Nunavut, Canada

Objectives: Unintentional injury is a leading cause of morbidity and mortality in Nunavut, where the importance of land-based activities and reliance on semi-permanent trails create unique risk profiles. Climate change is believed to be exacerbating these risks, although no studies have quantitatively examined links between environmental conditions and injury and distress in the Canadian Arctic. We examine the correlation between environmental conditions and land-based search and rescue (SAR) incidents across Nunavut. Study design: Case study. Methods: Case data were acquired from the Canadian National Search and Rescue Secretariat. Gasoline sales from across the territory are then used to model land-use and exposure. We compare weather and ice conditions during 202 SAR incidents to conditions during 755 non-SAR days (controls) between 2013 and 2014. Results: We show daily ambient temperature, ice concentration, ice thickness, and variation in types of ice to be correlated with SAR rates across the territory during the study period. Conclusions: These conditions are projected to be affected by future climate change, which could increase demand for SAR and increase injury rates in the absence of targeted efforts aimed at prevention and treatment. This study provides health practitioners and public health communities with clearer understanding to prepare, respond to, and prevent injuries across the Arctic

Mapping and predicting mortality from systemic sclerosis

Objectives To determine the causes of death and risk factors in systemic sclerosis (SSc). Methods Between 2000 and 2011, we examined the death certificates of all French patients with SSc to determine causes of death. Then we examined causes of death and developed a score associated with all-cause mortality from the international European Scleroderma Trials and Research (EUSTAR) database. Candidate prognostic factors were tested by Cox proportional hazards regression model by single variable analysis, followed by a multiple variable model stratified by centres. The bootstrapping technique was used for internal validation. Results We identified 2719 French certificates of deaths related to SSc, mainly from cardiac (31%) and respiratory (18%) causes, and an increase in SSc-specific mortality over time. Over a median follow-up of 2.3 years, 1072 (9.6%) of 11 193 patients from the EUSTAR sample died, from cardiac disease in 27% and respiratory causes in 17%. By multiple variable analysis, a risk score was developed, which accurately predicted the 3-year mortality, with an area under the curve of 0.82. The 3-year survival of patients in the upper quartile was 53%, in contrast with 98% in the first quartile. Conclusion Combining two complementary and detailed databases enabled the collection of an unprecedented 3700 deaths, revealing the major contribution of the cardiopulmonary system to SSc mortality. We also developed a robust score to risk-stratify these patients and estimate their 3-year survival. With the emergence of new therapies, these important observations should help caregivers plan and refine the monitoring and management to prolong these patients' survival. ©Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted

Mapping and predicting mortality from systemic sclerosis

Objectives To determine the causes of death and risk factors in systemic sclerosis (SSc). Methods Between 2000 and 2011, we examined the death certificates of all French patients with SSc to determine causes of death. Then we examined causes of death and developed a score associated with all-cause mortality from the international European Scleroderma Trials and Research (EUSTAR) database. Candidate prognostic factors were tested by Cox proportional hazards regression model by single variable analysis, followed by a multiple variable model stratified by centres. The bootstrapping technique was used for internal validation. Results We identified 2719 French certificates of deaths related to SSc, mainly from cardiac (31%) and respiratory (18%) causes, and an increase in SSc-specific mortality over time. Over a median follow-up of 2.3 years, 1072 (9.6%) of 11 193 patients from the EUSTAR sample died, from cardiac disease in 27% and respiratory causes in 17%. By multiple variable analysis, a risk score was developed, which accurately predicted the 3-year mortality, with an area under the curve of 0.82. The 3-year survival of patients in the upper quartile was 53%, in contrast with 98% in the first quartile. Conclusion Combining two complementary and detailed databases enabled the collection of an unprecedented 3700 deaths, revealing the major contribution of the cardiopulmonary system to SSc mortality. We also developed a robust score to risk-stratify these patients and estimate their 3-year survival. With the emergence of new therapies, these important observations should help caregivers plan and refine the monitoring and management to prolong these patients' survival. ©Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted

Stratification in systemic sclerosis according to autoantibody status versus skin involvement: a study of the prospective EUSTAR cohort

Background The current subclassification of systemic sclerosis into cutaneous subtypes does not fully capture the heterogeneity of the disease. We aimed to compare the performances of stratification into LeRoy's cutaneous subtypes versus stratification by autoantibody status in systemic sclerosis. Methods For this cohort study, we assessed people with systemic sclerosis in the multicentre international European Scleroderma Trials and Research (EUSTAR) database. Individuals positive for systemic-sclerosis autoantibodies of two specificities were excluded, and remaining individuals were classified by cutaneous subtype, according to their systemic sclerosis-specific autoantibodies, or both. We assessed the performance of each model to predict overall survival, progression-free survival, disease progression, and different organ involvement. The three models were compared by use of the area under the curve (AUC) of the receiver operating characteristic and the net reclassification improvement (NRI). Missing data were imputed. Findings We assessed the database on July 26, 2019. Of 16 939 patients assessed for eligibility, 10 711 patients were included: 1647 (15·4%) of 10 709 were male, 9062 (84·6%) were female, mean age was 54·4 (SD 13·8) years, and mean disease duration was 7·9 (SD 8·2) years. Information regarding cutaneous subtype was available for 10 176 participants and antibody data were available for 9643 participants. In the prognostic analysis, there was no difference in AUC for overall survival (0·82, 95% CI 0·81–0·84 for cutaneous only vs 0·84, 0·82–0·85 for antibody only vs 0·84, 0·83–0·86 for combined) or for progression-free survival (0·70, 0·69–0·71 vs 0·71, 0·70–0·72 vs 0·71, 0·70–0·72). However, at 4 years the NRI showed substantial improvement for the antibody-only model compared with the cutaneous-only model in prediction of overall survival (0·57, 0·46–0·71 for antibody only vs 0·29, 0·19–0·39 for cutaneous only) and disease progression (0·36, 0·29–0·46 vs 0·21, 0·14–0·28). The antibody-only model did better than the cutaneous-only model in predicting renal crisis (AUC 0·72, 0·70–0·74 for antibody only vs 0·66, 0·64–0·69 for cutaneous only) and lung fibrosis leading to restrictive lung function (AUC 0·76, 0·75–0·77 vs 0·71, 0·70–0·72). The combined model improved the prediction of digital ulcers and elevated systolic pulmonary artery pressure, but did poorly for cardiac involvement. Interpretation The autoantibody-only model outperforms cutaneous-only subsetting for risk stratifying people with systemic sclerosis in the EUSTAR cohort. Physicians should be aware of these findings at the time of decision making for patient management. Funding World Scleroderma Foundation