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Four variable-exponent taper equations and their modified forms were evaluated for lodgepole pine (Pinus contorta var. latifolia Engelm.) trees in Alberta, Canada. A nonlinear mixed-effects modeling approach was applied to account for within-and between-tree variations in stem form. Even though a direct modeling of within-tree autocorrelation by a variance-covariance structure failed to achieve convergence, most of the autocorrelation was accounted for when random-effects parameters were included in the models. Using an independent data set, the best taper equation with two random-effects parameters was chosen based on its ability to predict diameter inside bark, whole tree volume, and sectioned log volume. Diameter measurements from various stem locations were evaluated for tree-specific calibrations by predicting random-effects parameters using an approximate Bayesian estimator. It was found that an upper stem diameter at 5.3 m above ground was best suited for calibrating treespecific predictions of diameter inside bark, whole tree volume, and sectioned log volume.

Human hereditary tumor syndromes serve as an ideal model for studying molecular pathways regulating tumorigenesis. Multiple endocrine neoplasia type 1 (MEN1), a human familial tumor syndrome, results from mutations in the Men1 gene. Men1 encodes a novel tumor suppressor, menin, of unknown biochemical function. Recently, significant progress has been made in identifying menin as a regulator of gene transcription, cell proliferation, apoptosis, and genome stability, leading to a new model of understanding menin's tumor-suppressing function. These findings suggest that menin's diverse functions depend on its association with chromatin and its control over gene transcription. This knowledge will likely be translated into new strategies to improve therapeutic interventions against MEN1 and other related cancers.

Model validation is an important part of model development. It is performed to increase the credibility and gain sufficient confidence about a model. This paper evaluated the usefulness of 10 statistical tests, five parametric and five nonparametric, in validating forest biometric models. The five parametric tests are the paired t test, the Χ2 test, the separate t test, the simultaneous F test, and the novel test. The five nonparametric tests are the Brown-Mood test, the Kolmogorov–Smirnov test, the modified Kolmogorov–Smirnov test, the sign test, and the Wilcoxon signed-rank test. Nine benchmark data sets were selected to evaluate the behavior of these tests in model validation; three were collected from Alberta and six were published elsewhere. It was shown that the usefulness of statistical tests in model validation is very limited. None of the tests seems to be generic enough to work well across a wide range of models and data. Each model passed one or more tests, but not all of them. Because of this, caution should be exercised when choosing a statistical test or several tests together to try to validate a model. It is important to reduce and remove any potential personal bias in selecting a favorite test, which can influence the outcome of the results.

Malignant ovarian tumors bear the highest mortality rate among all gynecological cancers. Both late tumor diagnosis and tolerance to available chemical therapy increase patient mortality. Therefore, it is both urgent and important to identify biomarkers facilitating early identification and novel agents preventing recurrence. Accumulating evidence demonstrates that epigenetic aberrations (particularly histone modifications) are crucial in tumor initiation and development. Histone acetylation and methylation are respectively regulated by acetyltransferases-deacetylases and methyltransferases-demethylases, both of which are implicated in ovarian cancer pathogenesis. In this review, we summarize the most recent discoveries pertaining to ovarian cancer development arising from the imbalance of histone acetylation and methylation, and provide insight into novel therapeutic interventions for the treatment of ovarian carcinoma.

Hematopoietic stem cells (HSCs) are conventionally thought to be at the apex of a hierarchy that produces all mature cells of the blood. The quintessential property of these cells is their ability to reconstitute the entire hematopoietic system of hemoablated recipients. This characteristic has enabled HSCs to be used to replenish the hematopoietic system of patients after chemotherapy or radiotherapy. Here, we use deletion of the monocytic leukemia zinc finger gene to examine the effects of removing HSCs. Loss of MOZ in adult mice leads to the rapid loss of HSCs as defined by transplantation. This is accompanied by a reduction of the LSK-CD48CD150 and LSK-CD34Flt3 populations in the bone marrow and a reduction in quiescent cells in G Surprisingly, the loss of classically defined HSCs did not affect mouse viability, and there was no recovery of the LSK-CD48CD150 and LSK-CD34Flt3 populations 15 to 18 months after deletion. Clonal analysis of myeloid progenitors, which produce short-lived granulocytes, demonstrate that these are derived from cells that had undergone recombination at the locus up to 2 years earlier, suggesting that early progenitors have acquired extended self-renewal. Our results establish that there are essential differences in HSC requirement for steady-state blood cell production compared with the artificial situation of reconstitution after transplantation into a hemoablated host. A better understanding of steady-state hematopoiesis may facilitate the development of novel therapies engaging hematopoietic cell populations with previously unrecognized traits, as well as characterizing potential vulnerability to oncogenic transformation.