Conditional deletion of HDAC4 from collagen type 2α1-expressing cells increases angiogenesis in vivo.

BACKGROUND: HDAC4 is a key regulator of chondrocyte hypertrophy and skeletal development, but it is not clear whether the increase in vascular invasion at growth plates is related to HDAC4 expression. To determine it, we investigated the relationship between HDAC4 and angiogenesis in both in vivo and in vitro models. METHODS: HDAC4 was deleted in Col2α1-Cre; HDAC4fl/fl mice. Growth of the Col2α1-Cre; HDAC4d/d mice was compared with HDAC4fl/fl mice at postnatal days 2, 4, 6, and 8. X-rays were taken to examine skeletal development. At postnatal days 14 and 21, mice were euthanized for specimen collection. Murine chondrocytes were isolated from the ventral parts of rib cages of 6-day-old mice (C57Bl/6) and transfected with a vector expressing HDAC4 as a fusion protein with green fluorescent protein (GFP). Relative expression levels of HDAC4, VEGF, and Hif1α were measured in these cells by Western blot, RT-qPCR, enzyme-linked immunosorbent, histology, and immunohistochemistry assays. RESULTS: The Col2α1-Cre; HDAC4d/d mice were markedly smaller compared with the control mice. At postnatal days 14 and 21, the Col2α1-Cre; HDAC4d/d mice exhibited a shortened growth plate, a larger secondary ossification center, and stronger staining of CD31 and CD34 compared to control mice. The isolated chondrocyte cells exhibited a high transfection efficiency of HDAC4 which resulted in the detection of a significant decrease in VEGF and Hif1α levels compared with the control chondrocytes. CONCLUSIONS: HDAC4 expression in chondrocytes contributes to angiogenesis in the growth plate, and its absence in vivo negatively affects growth plates.

Irisin counteracts high glucose and fatty acid-induced cytotoxicity by preserving the AMPK-insulin receptor signaling axis in C2C12 myoblasts.

Irisin, a newly identified myokine, is critical to modulating body metabolism and biological homeostasis. However, whether irisin protects the skeletal muscles against metabolic stresses remains unknown. In this study, we determine the effect of irisin on high glucose and fatty acid-induced damages using irisin-overexpressed mouse C2C12 (irisin-C2C12) myoblasts and skeletal muscle from irisin-injected mice. Compared with empty vector-transfected control C2C12 cells, irisin overexpression resulted in a marked increase in cell viability and decrease in apoptosis under high-glucose stress. Progression of the cell cycle into the G2/M phase in the proliferative condition was also observed with irisin overexpression. Furthermore, glucose uptake, glycogen accumulation, and phosphorylation of AMPKα/insulin receptor (IR) ß-subunit/Erk1/2 in response to insulin stimulation were enhanced by irisin overexpression. In irisin-C2C12 myoblasts, these responses of phosphorylation were preserved under palmitate treatment, which induced insulin resistance in the control cells. These effects of irisin were reversed by inhibiting AMPK with compound C. In addition, high glucose-induced suppression of the mitochondrial membrane potential was also prevented by irisin. Moreover, suppression of IR in irisin-C2C12 myoblasts by cotransfection of shRNA against IR also mitigated the effects of irisin while not affecting AMPKα phosphorylation. As an in vivo study, soleus muscles from irisin-injected mice showed elevated phosphorylation of AMPKα and Erk1/2 and glycogen contents. Our results indicate that irisin counteracts the stresses generated by high glucose and fatty acid levels and irisin overexpression serves as a novel approach to elicit cellular protection. Furthermore, AMPK activation is a crucial factor that regulates insulin action as a downstream target.

Confronting data sparsity to identify potential sources of Zika virus spillover infection among primates.

The recent Zika virus (ZIKV) epidemic in the Americas ranks among the largest outbreaks in modern times. Like other mosquito-borne flaviviruses, ZIKV circulates in sylvatic cycles among primates that can serve as reservoirs of spillover infection to humans. Identifying sylvatic reservoirs is critical to mitigating spillover risk, but relevant surveillance and biological data remain limited for this and most other zoonoses. We confronted this data sparsity by combining a machine learning method, Bayesian multi-label learning, with a multiple imputation method on primate traits. The resulting models distinguished flavivirus-positive primates with 82% accuracy and suggest that species posing the greatest spillover risk are also among the best adapted to human habitations. Given pervasive data sparsity describing animal hosts, and the virtual guarantee of data sparsity in scenarios involving novel or emerging zoonoses, we show that computational methods can be useful in extracting actionable inference from available data to support improved epidemiological response and prevention.

The Effects of Indian Hedgehog Deletion on Mesenchyme Cells: Inducing Intermediate Cartilage Scaffold Ossification to Cause Growth Plate and Phalange Joint Absence, Short Limb, and Dwarfish Phenotypes.

The endochondral ossification plays a critical role in vertebrate limb development and skeletal homeostasis, where limb mesenchyme cells form an intermediate cartilage scaffold that develops into growth plates and then replaced by bone. Although Indian hedgehog (Ihh) is known to control the hypertrophic differentiation process of chondrocytes, its role from the mesenchyme cells to the early stages of chondrogenesis is unclear. To define the function of Ihh in the mesenchymal cell's early stages of chondrogenesis, we specifically delete Ihh in Prx1-expressed mesenchyme cells at E9.5 using Prx1-Cre;Ihhfl/fl;Rosa26-ZsGreen1 mice. We found that deleting Ihh in the mesenchyme cells results in an early and quick ossification of the intermediate cartilage scaffold, causing the growth plate and phalange joint absence, short limbs, and dwarfishness. The green fluorescent protein (GFP)-positive cells derived from deleted Ihh mesenchyme cells overlap with von Kossa- and osteocalcin-positive staining area. These deleted Ihh/GFP-positive cells isolated from Prx1-Cre;Ihhfl/fl;Rosa26-ZsGreen1 newborn mice had osteogenic differentiation by showing a positive Alizarin red and von Kossa staining, as well as an enhanced Col1a1, osteocalcin, and Runx2 expression. Our findings demonstrate that deleting Ihh in mesenchyme cells during early limb development promotes intermediate cartilage scaffold ossification, which prevents growth plate formation that causes phalange joint absence, short limb, and dwarfish phenotype.

Suicide intervention training for college staff: Program evaluation and intervention skill measurement.

OBJECTIVE: Suicide remains a pressing issue for college communities. Consequently, gatekeeper trainings are often provided for staff. This study examines the effect of one such program, Applied Suicide Intervention Skills Training (ASIST). PARTICIPANTS: 51 college employees received ASIST in August of 2014 and were compared to 30 wait-list control participants. METHODS: Repeated Measures ANOVA were used to analyze pre- and post-training: (a) skills at responding to students-at-risk; (b) attitudes toward suicide; (c) knowledge about suicide; and (d) comfort/competence/confidence at helping a student-at-risk. RESULTS: Significant positive training effects were observed for ASIST on self-report measures and also for objectively assessed skill at responding, after adjusting for a potential scoring limitation of the Suicide Intervention Response Inventory, Revised (SIRI-2). CONCLUSIONS: ASIST improved the self-perception of college staff at working with students-at-risk of suicide and also their skills at performing an intervention. Further, analysis of SIRI-2 data provides support for a potential instrument revision.

A Dictionary Approach to Electron Backscatter Diffraction Indexing.

We propose a framework for indexing of grain and subgrain structures in electron backscatter diffraction patterns of polycrystalline materials. We discretize the domain of a dynamical forward model onto a dense grid of orientations, producing a dictionary of patterns. For each measured pattern, we identify the most similar patterns in the dictionary, and identify boundaries, detect anomalies, and index crystal orientations. The statistical distribution of these closest matches is used in an unsupervised binary decision tree (DT) classifier to identify grain boundaries and anomalous regions. The DT classifies a pattern as an anomaly if it has an abnormally low similarity to any pattern in the dictionary. It classifies a pixel as being near a grain boundary if the highly ranked patterns in the dictionary differ significantly over the pixel's neighborhood. Indexing is accomplished by computing the mean orientation of the closest matches to each pattern. The mean orientation is estimated using a maximum likelihood approach that models the orientation distribution as a mixture of Von Mises-Fisher distributions over the quaternionic three sphere. The proposed dictionary matching approach permits segmentation, anomaly detection, and indexing to be performed in a unified manner with the additional benefit of uncertainty quantification.

Ensemble estimators for multivariate entropy estimation.

The problem of estimation of density functionals like entropy and mutual information has received much attention in the statistics and information theory communities. A large class of estimators of functionals of the probability density suffer from the curse of dimensionality, wherein the mean squared error (MSE) decays increasingly slowly as a function of the sample size T as the dimension d of the samples increases. In particular, the rate is often glacially slow of order O(T-γ/d ), where γ > 0 is a rate parameter. Examples of such estimators include kernel density estimators, k-nearest neighbor (k-NN) density estimators, k-NN entropy estimators, intrinsic dimension estimators and other examples. In this paper, we propose a weighted affine combination of an ensemble of such estimators, where optimal weights can be chosen such that the weighted estimator converges at a much faster dimension invariant rate of O(T-1). Furthermore, we show that these optimal weights can be determined by solving a convex optimization problem which can be performed offline and does not require training data. We illustrate the superior performance of our weighted estimator for two important applications: (i) estimating the Panter-Dite distortion-rate factor and (ii) estimating the Shannon entropy for testing the probability distribution of a random sample.