Toward an internally consistent astronomical distance scale

Accurate astronomical distance determination is crucial for all fields in astrophysics, from Galactic to cosmological scales. Despite, or perhaps because of, significant efforts to determine accurate distances, using a wide range of methods, tracers, and techniques, an internally consistent astronomical distance framework has not yet been established. We review current efforts to homogenize the Local Group's distance framework, with particular emphasis on the potential of RR Lyrae stars as distance indicators, and attempt to extend this in an internally consistent manner to cosmological distances. Calibration based on Type Ia supernovae and distance determinations based on gravitational lensing represent particularly promising approaches. We provide a positive outlook to improvements to the status quo expected from future surveys, missions, and facilities. Astronomical distance determination has clearly reached maturity and near-consistency.Comment: Review article, 59 pages (4 figures); Space Science Reviews, in press (chapter 8 of a special collection resulting from the May 2016 ISSI-BJ workshop on Astronomical Distance Determination in the Space Age

Allan Sandage and the Cosmic Expansion

This is an account of Allan Sandage's work on (1) The character of the expansion field. For many years he has been the strongest defender of an expanding Universe. He later explained the CMB dipole by a local velocity of 220 +/- 50 km/s toward the Virgo cluster and by a bulk motion of the Local supercluster (extending out to ~3500 km/s) of 450-500 km/s toward an apex at l=275, b=12. Allowing for these streaming velocities he found linear expansion to hold down to local scales (~300 km/s). (2) The calibration of the Hubble constant. Probing different methods he finally adopted - from Cepheid-calibrated SNe Ia and from independent RR Lyr-calibrated TRGBs - H_0 = 62.3 +/- 1.3 +/- 5.0 km/s/Mpc.Comment: 12 pages, 11 figures, 1 table, Submitted to Astrophysics and Space Science, Special Issue on the Fundamental Cosmic Distance Scale in the Gaia Er

In-vitro venous prostacyclin production, plasma 6-keto-prostaglandin F1 alpha concentrations, and diabetic retinopathy.

Previous studies have shown that vessels from diabetics produce less prostacyclin in vitro than those from normal controls. To determine whether this decreased production is related to complications elective biopsy of a superficial forearm vein was performed on 12 insulin-dependent male diabetics, six with nil or minimal and six with proliferative retinopathy, and seven male controls. Vein segments from the diabetics and controls produced similar amounts of prostacyclin in vitro (medians 0.11 and 0.19 ng/mg tissue respectively), but the segments from the diabetics with nil or minimal retinopathy produced less than those from the diabetics with proliferative retinopathy (medians 0.09 and 0.18 ng/mg respectively). Preoperative plasma immunoreactive concentrations of 6-keto-prostaglandin F1 alpha were not significantly different between the controls and the diabetics (medians 101 and 116 pg/ml respectively). In a separate study, however, 11 diabetics with duration of disease of over 10 years and nil or minimal retinopathy had significantly lower concentrations than a matched group of 16 with background or proliferative retinopathy (medians 79 and 121 pg/ml respectively). These results do not support an association between reduced prostacyclin production and diabetic retinopathy

Effects of complete androgen blockade for 12 and 24 weeks on the pathological stage and resection margin status of prostate cancer.

AIMS: To compare the pathological stage and surgical margin status in patients undergoing either immediate radical prostatectomy or 12 and 24 weeks of neoadjuvant hormonal treatment (NHT) in a prospective, randomised study. METHODS: Whole mount sections of 393 radical prostatectomy specimens were evaluated: 128 patients had immediate surgery, 143 were treated for 12 weeks and 122 for 24 weeks with complete androgen blockade. RESULTS: Histopathology revealed organ confined tumours in 40.4% of patients with clinical stage B disease in the immediate surgery group, whereas 12 and 24 weeks of NHT increased the number of organ confined tumours to 54.6% and 64.8%, respectively. Among patients with clinical stage C tumours, pathological staging found organ confined disease in 10.4%, 31.4%, and 61.2% in the immediate surgery, 12 weeks of NHT, and 24 weeks of NHT groups, respectively. Preoperative NHT caused a significant decrease in positive margins both in patients with clinical stage B and C disease. The extent of margin involvement was not influenced by preoperative treatment. CONCLUSIONS: Neoadjuvant androgenic suppression is effective in reducing both the pathological stage and the positive margin rate in patients with stage B and C prostatic cancer undergoing radical surgery. Some beneficial effects are evident in those patients treated for 24 weeks, and it is reasonable to assume that the optimal duration of NHT is longer than three months

A Machine Learning Algorithm to Identify Patients at Risk of Unplanned Subsequent Surgery After Intramedullary Nailing for Tibial Shaft Fractures

Objectives: In the SPRINT trial, 18% of patients with a tibial shaft fracture (TSF) treated with intramedullary nailing (IMN) had one or more unplanned subsequent surgical procedures. It is clinically relevant for surgeon and patient to anticipate unplanned secondary procedures, other than operations that can be readily expected such as reconstructive procedures for soft tissue defects. Therefore, the objective of this study was to develop a machine learning (ML) prediction model using the SPRINT data that can give individual patients and their care team an estimate of their particular probability of an unplanned second surgery. Methods: Patients from the SPRINT trial with unilateral TSFs were randomly divided into a training set (80%) and test set (20%). Five ML algorithms were trained in recognizing patterns associated with subsequent surgery in the training set based on a subset of variables identified by random forest algorithms. Performance of each ML algorithm was evaluated and compared based on (1) area under the ROC curve, (2) calibration slope and intercept, and (3) the Brier score. Results: Total data set comprised 1198 patients, of whom 214 patients (18%) underwent subsequent surgery. Seven variables were used to train ML algorithms: (1) Gustilo-Anderson classification, (2) Tscherne classification, (3) fracture location, (4) fracture gap, (5) polytrauma, (6) injury mechanism, and (7) OTA/AO classification. The best-performing ML algorithm had an area under the ROC curve, calibration slope, calibration intercept, and the Brier score of 0.766, 0.954, -0.002, and 0.120 in the training set and 0.773, 0.922, 0, and 0.119 in the test set, respectively. Conclusions: An ML algorithm was developed to predict the probability of subsequent surgery after IMN for TSFs. This ML algorithm may assist surgeons to inform patients about the probability of subsequent surgery and might help to identify patients who need a different perioperative plan or a more intensive approach.Orthopaedics, Trauma Surgery and Rehabilitatio