Two major accretion epochs in M31 from two distinct populations of globular clusters.

Large galaxies grow through the accumulation of dwarf galaxies1,2. In principle it is possible to trace this growth history via the properties of a galaxy's stellar halo3-5. Previous investigations of the galaxy Messier 31 (M31, Andromeda) have shown that outside a galactocentric radius of 25 kiloparsecs the population of halo globular clusters is rotating in alignment with the stellar disk6,7, as are more centrally located clusters8,9. The M31 halo also contains coherent stellar substructures, along with a smoothly distributed stellar component10-12. Many of the globular clusters outside a radius of 25 kiloparsecs are associated with the most prominent substructures, but some are part of the smooth halo13. Here we report an analysis of the kinematics of these globular clusters. We find two distinct populations rotating perpendicular to each other. The rotation axis for the population associated with the smooth halo is aligned with the rotation axis for the plane of dwarf galaxies14 that encircles M31. We interpret these separate cluster populations as arising from two major accretion epochs, probably separated by billions of years. Stellar substructures from the first epoch are gone, but those from the more recent second epoch still remain.

A luminous quasar at a redshift of z = 7.085.

The intergalactic medium was not completely reionized until approximately a billion years after the Big Bang, as revealed by observations of quasars with redshifts of less than 6.5. It has been difficult to probe to higher redshifts, however, because quasars have historically been identified in optical surveys, which are insensitive to sources at redshifts exceeding 6.5. Here we report observations of a quasar (ULAS J112001.48+064124.3) at a redshift of 7.085, which is 0.77 billion years after the Big Bang. ULAS J1120+0641 has a luminosity of 6.3 × 10(13)L(⊙) and hosts a black hole with a mass of 2 × 10(9)M(⊙) (where L(⊙) and M(⊙) are the luminosity and mass of the Sun). The measured radius of the ionized near zone around ULAS J1120+0641 is 1.9 megaparsecs, a factor of three smaller than is typical for quasars at redshifts between 6.0 and 6.4. The near-zone transmission profile is consistent with a Lyα damping wing, suggesting that the neutral fraction of the intergalactic medium in front of ULAS J1120+0641 exceeded 0.1.

Computational pathology of pre-treatment biopsies identifies lymphocyte density as a predictor of response to neoadjuvant chemotherapy in breast cancer.

BACKGROUND: There is a need to improve prediction of response to chemotherapy in breast cancer in order to improve clinical management and this may be achieved by harnessing computational metrics of tissue pathology. We investigated the association between quantitative image metrics derived from computational analysis of digital pathology slides and response to chemotherapy in women with breast cancer who received neoadjuvant chemotherapy. METHODS: We digitised tissue sections of both diagnostic and surgical samples of breast tumours from 768 patients enrolled in the Neo-tAnGo randomized controlled trial. We subjected digital images to systematic analysis optimised for detection of single cells. Machine-learning methods were used to classify cells as cancer, stromal or lymphocyte and we computed estimates of absolute numbers, relative fractions and cell densities using these data. Pathological complete response (pCR), a histological indicator of chemotherapy response, was the primary endpoint. Fifteen image metrics were tested for their association with pCR using univariate and multivariate logistic regression. RESULTS: Median lymphocyte density proved most strongly associated with pCR on univariate analysis (OR 4.46, 95 % CI 2.34-8.50, p < 0.0001; observations = 614) and on multivariate analysis (OR 2.42, 95 % CI 1.08-5.40, p = 0.03; observations = 406) after adjustment for clinical factors. Further exploratory analyses revealed that in approximately one quarter of cases there was an increase in lymphocyte density in the tumour removed at surgery compared to diagnostic biopsies. A reduction in lymphocyte density at surgery was strongly associated with pCR (OR 0.28, 95 % CI 0.17-0.47, p < 0.0001; observations = 553). CONCLUSIONS: A data-driven analysis of computational pathology reveals lymphocyte density as an independent predictor of pCR. Paradoxically an increase in lymphocyte density, following exposure to chemotherapy, is associated with a lack of pCR. Computational pathology can provide objective, quantitative and reproducible tissue metrics and represents a viable means of outcome prediction in breast cancer. TRIAL REGISTRATION: ClinicalTrials.gov NCT00070278 ; 03/10/2003.