Enigmatic origin of massive Late Cretaceous‐to‐Neogene coprolite‐like deposits in North America: a novel palaeobiological alternative to inorganic morphogenesis

Innumerable coprolite specimens, alternatively pseudo‐coprolites, are distributed in several Late Cretaceous‐to‐Neogene continental deposits hosted by the Whitemud Formation (Maastrichtian) in southern Saskatchewan, Canada, Golden Valley Formation (Paleocene) in western North Dakota and the Wilkes Formation (Miocene) in Washington State, USA. These massive accumulations of excrement‐shaped specimens also include multi‐decimetre‐long specimens previously interpreted as casts of intestinal organs by an unknown zoology, possibly reptilian. The possible vertebrate zoology origin of these has been widely disputed because of the lack of any skeletal remains or any other definitive evidence of palaeobiology. Alternative originations suggest non‐zoological processes, such as sideritic muds extruded by biogenic gas‐driven flows during diagenesis. Multi‐decimetre‐long intestine‐like casts recovered from the three deposits differ from the more widely distributed faeces‐like specimens because their elongated forms have bilateral symmetry in cross‐section and surface textures consisting of sub‐mm‐wide longitudinal parallel striations extending without interruption along the looped and coiled surfaces. These possible impressions of musculature are not present on smaller specimens having coprolite‐like shapes. A novel interpretation proposes that these multi‐decimetre‐long specimens may be gut casts of a previously unrecognized giant terrestrial earthworm (Oligochaeta) that existed from the Late Cretaceous to the Neogene. The possibility of this Annelida zoology provides palaeobiological resolution for the lack of any evidence of vertebrate skeletal remains or other evidence of origination and further suggests that the innumerable excrement‐like specimens may also have palaeobiological affinity.     

Spatially Dependent Polya Tree Modeling for Survival Data

Summary With the proliferation of spatially oriented time‐to‐event data, spatial modeling in the survival context has received increased recent attention. A traditional way to capture a spatial pattern is to introduce frailty terms in the linear predictor of a semiparametric model, such as proportional hazards or accelerated failure time. We propose a new methodology to capture the spatial pattern by assuming a prior based on a mixture of spatially dependent Polya trees for the baseline survival in the proportional hazards model. Thanks to modern Markov chain Monte Carlo (MCMC) methods, this approach remains computationally feasible in a fully hierarchical Bayesian framework. We compare the spatially dependent mixture of Polya trees (MPT) approach to the traditional spatial frailty approach, and illustrate the usefulness of this method with an analysis of Iowan breast cancer survival data from the Surveillance, Epidemiology, and End Results (SEER) program of the National Cancer Institute. Our method provides better goodness of fit over the traditional alternatives as measured by log pseudo marginal likelihood (LPML), the deviance information criterion (DIC), and full sample score (FSS) statistics.     

A note on pseudo‐observations and left‐truncation

Pseudo‐observations have been introduced as a way to perform regression analysis of a mean value parameter related to a right‐censored time‐to‐event outcome, such as the survival probability or the restricted mean survival time. Since the introduction of the approach there have been several extensions from the original setting. However, the proper definition and performance of pseudo‐observations under left‐truncation has not yet been addressed. Here, we look at two types of pseudo‐observations under right‐censoring and left‐truncation. We explored their performance in a simulation study and applied them to data on diabetes patients with left‐truncation.     

The internal anatomy of Stiliger fuscatus (A. Gould, 1870) (Opisthobranchia: Sacoglossa)

The central nervous system of Stiliger fuscatus has two ganglia on the visceral loop. The superficial buccal musculature includes an ascus muscle; its contraction drives the lower limb of the radula in the action of piercing an algal wall. The reproductive system is described in functional terms and related to those of other species of the family Stiligeridae. The vagina does not open to the exterior and the penial style is of the penetrant type; fertilization is by hypodermic impregnation. The system could be called pseudo-diaulic and this term is explained in the additional notes.     

Ultrastructure of the haustorium of Trenomyces histophthorus and adjacent host cells

The haustorium of Trenomyces histophthorus (Ascomycetes, Laboulbeniales) appears to be enucleate and aseptate; its bulbs, isthmuses, and tubules contain abundant mitochondria and are often vacuolate. Although host cells around some bulbs appear to be unaffected, most host cells in contact with the haustorial tubules are in various stages of degeneration. In some instances deterioration of the tissues of the mallophagan host apparently occurs in advance of the haustorial tips.     

Joint regression analysis for survival data in the presence of two sets of semi‐competing risks

In many clinical trials, multiple time‐to‐event endpoints including the primary endpoint (e.g., time to death) and secondary endpoints (e.g., progression‐related endpoints) are commonly used to determine treatment efficacy. These endpoints are often biologically related. This work is motivated by a study of bone marrow transplant (BMT) for leukemia patients, who may experience the acute graft‐versus‐host disease (GVHD), relapse of leukemia, and death after an allogeneic BMT. The acute GVHD is associated with the relapse free survival, and both the acute GVHD and relapse of leukemia are intermediate nonterminal events subject to dependent censoring by the informative terminal event death, but not vice versa, giving rise to survival data that are subject to two sets of semi‐competing risks. It is important to assess the impacts of prognostic factors on these three time‐to‐event endpoints. We propose a novel statistical approach that jointly models such data via a pair of copulas to account for multiple dependence structures, while the marginal distribution of each endpoint is formulated by a Cox proportional hazards model. We develop an estimation procedure based on pseudo‐likelihood and carry out simulation studies to examine the performance of the proposed method in finite samples. The practical utility of the proposed method is further illustrated with data from the motivating example.