Taxonomy, biostratigraphy, and phylogeny of Oligocene and lower Miocene Dentoglobigerina and Globoquadrina

The taxonomy, phylogeny, and biostratigraphy of Oligocene and lower Miocene Dentoglobigerina and Globoquadrina are reviewed. Because of the discovery of spine holes in various species assigned to these genera, the entire group is now considered to have been fully or sparsely spinose in life and hence part of Family Globigerinidae. One new species, Dentoglobigerina eotripartita Pearson, Wade, and Olsson n. sp., is named. Dentoglobigerina includes forms with and without umbilical teeth and species for which the presence or absence of a tooth is a variable feature. A significant finding has been the triple synonymy of Globigerina tripartita Koch, Globigerina rohri Bolli, and Globoquadrina dehiscens praedehiscens Blow, which greatly simplifies part of the taxonomy. The genus Globoquadrina is restricted to its type species, Globigerina dehiscens Chapman and others. The following species from the time interval of interest are regarded as valid: Dentoglobigerina altispira (Cushman and Jarvis), Dentoglobigerina baroemoenensis (LeRoy), Dentoglobigerina binaiensis (Koch), Dentoglobigerina eotripartita Pearson, Wade, and Olsson n. sp., Dentoglobigerina galavisi (Bermúdez), Dentoglobigerina globosa (Bolli), Dentoglobigerina globularis (Bermúdez), Dentoglobigerina juxtabinaiensis Fox and Wade, Dentoglobigerina larmeui (Akers), Dentoglobigerina prasaepis (Blow), Dentoglobigerina pseudovenezuelana (Blow and Banner), Dentoglobigerina sellii (Borsetti), Dentoglobigerina taci Pearson and Wade, Dentoglobigerina tapuriensis (Blow and Banner), Dentoglobigerina tripartita (Koch), Dentoglobigerina venezuelana (Hedberg), and Globoquadrina dehiscens (Chapman, Parr, and Collins). The genus Dentoglobigerina also comprises other Neogene/Quaternary species not listed, including the living species Dentoglobigerina cf. conglomerata (Schwager)

Taxonomy, biostratigraphy, and phylogeny of Oligocene and early Miocene Paragloborotalia and Parasubbotina

The taxonomy, phylogeny, and biostratigraphy of Oligocene and early Miocene Paragloborotalia and Parasubbotina are reviewed. The two genera are closely related; Paragloborotalia was derived from Parasubbotina in the early Eocene. Parasubbotina was more diverse during the middle Eocene, while Paragloborotalia experienced considerable diversification during the mid-Oligocene and in the latest Oligocene-earliest Miocene. A significant finding has been the synonymization of Globorotalia (Tuborotalia) mendacis Blow, and Turborotalia primitiva Brӧnnimann and Resig with Globorotalia birnageae Blow. The following species from the time interval of interest are regarded as valid: Paragloborotalia acrostoma (Wezel), Paragloborotalia birnageae (Blow), Paragloborotalia continuosa (Blow), Paragloborotalia incognita (Walters) Paragloborotalia kugleri (Bolli), Paragloborotalia mayeri (Cushman and Ellisor), Paragloborotalia nana (Bolli), Paragloborotalia opima (Bolli), Paragloborotalia pseudocontinuosa (Jenkins), Paragloborotalia pseudokugleri (Blow), Paragloborotalia semivera (Hornibrook), Paragloborotalia siakensis (LeRoy), Parasubbotina hagni (Gohrbandt), and Parasubbotina varianta (Subbotina). Paragloborotalia is a long-lived group of planktonic foraminifera that spanned the early Eocene to late Miocene and provided the root stock for the evolution of multiple smooth, nonspinose, and keeled globorotaliid lineages during the Neogene. The early Oligocene forms of Paragloborotalia (nana, opima, siakensis, pseudocontinuosa) have 4 or 5 globular chambers in the final whorl with radial spiral sutures and a broadly rounded periphery. A trend from radial to curved spiral sutures is observed in late Oligocene and earliest Miocene lineages. Most species of Paragloborotalia had wide distributions, but some were more common in tropical to warm subtropical waters (e.g., siakensis, kugleri) and were especially dominant in the equatorial Pacific divergence zone (e.g., nana, opima, and pseudocontinuosa) analogous to modern tropical upwelling Neogloboquadrina. Other species thrived in cool subtropical and temperate waters (e.g., acrostoma, incognita)

Growth of breast cancer recurrences assessed by consecutive MRI

<p>Abstract</p> <p>Background</p> <p>Women with a personal history of breast cancer have a high risk of developing an ipsi- or contralateral recurrence. We aimed to compare the growth rate of primary breast cancer and recurrences in women who had undergone prior breast magnetic resonance imaging (MRI).</p> <p>Methods</p> <p>Three hundred and sixty-two women were diagnosed with breast cancer and had undergone breast MRI at the time of diagnosis in our institution (2005 - 2009). Among them, 37 had at least one prior breast MRI with the lesion being visible but not diagnosed as cancer. A linear regression of tumour volume measured on MRI scans and time data was performed using a generalized logistic model to calculate growth rates. The primary objective was to compare the tumour growth rate of patients with either primary breast cancer (no history of breast cancer) or ipsi- or contralateral recurrences of breast cancer.</p> <p>Results</p> <p>Twenty women had no history of breast cancer and 17 patients were diagnosed as recurrences (7 and 10 were ipsi- and contralateral, respectively). The tumour growth rate was higher in contralateral recurrences than in ipsilateral recurrences (growth rate [10^-3days^-1] 3.56 vs 1.38, p < .001) or primary cancer (3.56 vs 2.09, p = 0.01). Differences in tumour growth were not significant for other patient-, tumour- or treatment-related characteristics.</p> <p>Conclusions</p> <p>These findings suggest that contralateral breast cancer presents accelerated growth compared to ipsilateral recurrences or primary breast events.</p

Predicting outcomes in radiation oncology-multifactorial decision support systems

With the emergence of individualized medicine and the increasing amount and complexity of available medical data, a growing need exists for the development of clinical decision-support systems based on prediction models of treatment outcome. In radiation oncology, these models combine both predictive and prognostic data factors from clinical, imaging, molecular and other sources to achieve the highest accuracy to predict tumour response and follow-up event rates. In this Review, we provide an overview of the factors that are correlated with outcome-including survival, recurrence patterns and toxicity-in radiation oncology and discuss the methodology behind the development of prediction models, which is a multistage process. Even after initial development and clinical introduction, a truly useful predictive model will be continuously re-evaluated on different patient datasets from different regions to ensure its population-specific strength. In the future, validated decision-support systems will be fully integrated in the clinic, with data and knowledge being shared in a standardized, instant and global manner