Direct and indirect lactate oxidation in trained and untrained men.

Lactate has been shown to be an important oxidative fuel. We aimed to quantify the total lactate oxidation rate (Rox) and its direct vs. indirect (glucose that is gluconeogenically derived from lactate and subsequently oxidized) components (mg·kg(-1)·min(-1)) during rest and exercise in humans. We also investigated the effects of endurance training, exercise intensity, and blood lactate concentration ([lactate]b) on direct and indirect lactate oxidation. Six untrained (UT) and six trained (T) men completed 60 min of constant load exercise at power outputs corresponding to their lactate threshold (LT). T subjects completed two additional 60-min sessions of constant load exercise at 10% below the LT workload (LT-10%), one of which included a lactate clamp (LC; LT-10%+LC). Rox was higher at LT in T [22.7 ± 2.9, 75% peak oxygen consumption (Vo2peak)] compared with UT (13.4 ± 2.5, 68% Vo2peak, P < 0.05). Increasing [lactate]b (LT-10%+LC, 67% Vo2peak) significantly increased lactate Rox (27.9 ± 3.0) compared with its corresponding LT-10% control (15.9 ± 2.2, P < 0.05). Direct and indirect Rox increased significantly from rest to exercise, and their relative partitioning remained constant in all trials but differed between T and UT: direct oxidation comprised 75% of total lactate oxidation in UT and 90% in T, suggesting the presence of training-induced adaptations. Partitioning of total carbohydrate (CHO) use showed that subjects derived one-third of CHO energy from blood lactate, and exogenous lactate infusion increased lactate oxidation significantly, causing a glycogen-sparing effect in exercising muscle

Local seismicity of the Rainbow massif on the Mid‐Atlantic Ridge

Author Posting. © American Geophysical Union, 2018. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Solid Earth 123 (2018): 1615-1630, doi:10.1002/2017JB015288.The Rainbow massif, an oceanic core complex located in a nontransform discontinuity on the Mid‐Atlantic Ridge (36°N), is notable for hosting high‐temperature hydrothermal discharge through ultramafic rocks. Here we report results from a 9 month microearthquake survey conducted with a network of 13 ocean bottom seismometers deployed on and around the Rainbow massif as part of the MARINER experiment in 2013–2014. High rates (~300 per day) of low‐magnitude (average ML ~ 0.5) microearthquakes were detected beneath the massif. The hypocenters do not cluster along deeply penetrating fault surfaces and do not exhibit mainshock/aftershock sequences, supporting the hypothesis that the faulting associated with the exhumation of the massif is currently inactive. Instead, the hypocenters demarcate a diffuse zone of continuous, low‐magnitude deformation at relatively shallow (< ~3 km) depths beneath the massif, sandwiched in between the seafloor and seismic reflectors interpreted to be magmatic sills driving hydrothermal convection. Most of the seismicity is located in regions where seismic refraction data indicate serpentinized ultramafic host rock, and although the seismic network we deployed was not capable of constraining the focal mechanism of most events, our analysis suggests that serpentinization may play an important role in microearthquake generation at the Rainbow massif.NSF Grant Numbers: OCE‐0961680, OCE‐09611512018-07-2

The Potential for Student Performance Prediction in Small Cohorts with Minimal Available Attributes

The measurement of student performance during their progress through university study provides academic leadership with critical information on each student’s likelihood of success. Academics have traditionally used their interactions with individual students through class activities and interim assessments to identify those “at risk” of failure/withdrawal. However, modern university environments, offering easy on-line availability of course material, may see reduced lecture/tutorial attendance, making such identification more challenging. Modern data mining and machine learning techniques provide increasingly accurate predictions of student examination assessment marks, although these approaches have focussed upon large student populations and wide ranges of data attributes per student. However, many university modules comprise relatively small student cohorts, with institutional protocols limiting the student attributes available for analysis. It appears that very little research attention has been devoted to this area of analysis and prediction. We describe an experiment conducted on a final-year university module student cohort of 23, where individual student data are limited to lecture/tutorial attendance, virtual learning environment accesses and intermediate assessments. We found potential for predicting individual student interim and final assessment marks in small student cohorts with very limited attributes and that these predictions could be useful to support module leaders in identifying students potentially “at risk.”.Peer reviewe

Inducing Probabilistic Grammars by Bayesian Model Merging

We describe a framework for inducing probabilistic grammars from corpora of positive samples. First, samples are {\em incorporated} by adding ad-hoc rules to a working grammar; subsequently, elements of the model (such as states or nonterminals) are {\em merged} to achieve generalization and a more compact representation. The choice of what to merge and when to stop is governed by the Bayesian posterior probability of the grammar given the data, which formalizes a trade-off between a close fit to the data and a default preference for simpler models (`Occam's Razor'). The general scheme is illustrated using three types of probabilistic grammars: Hidden Markov models, class-based $n$-grams, and stochastic context-free grammars.Comment: To appear in Grammatical Inference and Applications, Second International Colloquium on Grammatical Inference; Springer Verlag, 1994. 13 page

Predicting distributions of known and unknown reptile species in Madagascar

Despite the importance of tropical biodiversity(1), informative species distributional data are seldom available for biogeographical study or setting conservation priorities(2,3). Modelling ecological niche distributions of species offers a potential soluion(4-7); however, the utility of old locality data from museums, and of more recent remotely sensed satellite data, remains poorly explored, especially for rapidly changing tropical landscapes. Using 29 modern data sets of environmental land coverage and 621 chameleon occurrence localities from Madagascar ( historical and recent), here we demonstrate a significant ability of our niche models in predicting species distribution. At 11 recently inventoried sites, highest predictive success (85.1%) was obtained for models based only on modern occurrence data (74.7% and 82.8% predictive success, respectively, for pre-1978 and all data combined). Notably, these models also identified three intersecting areas of over-prediction that recently yielded seven chameleon species new to science. We conclude that ecological niche modelling using recent locality records and readily available environmental coverage data provides informative biogeographical data for poorly known tropical landscapes, and offers innovative potential for the discovery of unknown distributional areas and unknown species.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62843/1/nature02205.pd

Mol. Cell. Proteomics

The term “proteomics” encompasses the large-scale detection and analysis of proteins and their post-translational modifications. Driven by major improvements in mass spectrometric instrumentation, methodology, and data analysis, the proteomics field has burgeoned in recent years. It now provides a range of sensitive and quantitative approaches for measuring protein structures and dynamics that promise to revolutionize our understanding of cell biology and molecular mechanisms in both human cells and model organisms. The Proteomics Specification in Time and Space (PROSPECTS) Network is a unique EU-funded project that brings together leading European research groups, spanning from instrumentation to biomedicine, in a collaborative five year initiative to develop new methods and applications for the functional analysis of cellular proteins. This special issue of Molecular and Cellular Proteomics presents 16 research papers reporting major recent progress by the PROSPECTS groups, including improvements to the resolution and sensitivity of the Orbitrap family of mass spectrometers, systematic detection of proteins using highly characterized antibody collections, and new methods for absolute as well as relative quantification of protein levels. Manuscripts in this issue exemplify approaches for performing quantitative measurements of cell proteomes and for studying their dynamic responses to perturbation, both during normal cellular responses and in disease mechanisms. Here we present a perspective on how the proteomics field is moving beyond simply identifying proteins with high sensitivity toward providing a powerful and versatile set of assay systems for characterizing proteome dynamics and thereby creating a new “third generation” proteomics strategy that offers an indispensible tool for cell biology and molecular medicine

High-Dose Carmustine, Etoposide, and Cyclophosphamide Followed by Allogeneic Hematopoietic Cell Transplantation for Non-Hodgkin Lymphoma

AbstractAllogeneic hematopoietic cell transplantation (HCT) has been shown to be curative in a group of patients with aggressive non-Hodgkin lymphoma (NHL). A previous study has demonstrated equivalent outcomes with a conditioning regimen based on total body irradiation and another not based on total body irradiation with preparative therapy using cyclophosphamide, carmustine, and etoposide (CBV) in autologous HCT. We investigated the safety and efficacy of using CBV in an allogeneic setting. Patients were required to have relapsed or be at high risk for subsequent relapse of NHL. All patients had a fully HLA-matched sibling donor. Patients received carmustine (15 mg/kg), etoposide (60 mg/kg), and cyclophosphamide (100 mg/kg) on days −6, −4, and −2, respectively, followed by allogeneic HCT. All patients were treated with cyclosporine and methylprednisolone as prophylaxis for graft-versus-host disease (GVHD). Thirty-one patients (median age, 46 years) who were felt to be inappropriate candidates for autologous transplantation were enrolled. Each subject had a median of 3 previous chemotherapy regimens. All patients engrafted. Fifteen of 31 patients are alive. Median follow-up time was 11.5 months (range, .4-126). There were 8 deaths due to relapse. Nonrelapse mortality (n = 8) included infection (n = 3), GVHD (n = 2), diffuse alveolar hemorrhage (n = 1), veno-occlusive disease in the setting of concurrent acute GVHD of the liver (n = 1), and leukoencephalopathy (n = 1). Probabilities of event-free survival and overall survival were, respectively, 44% (95% confidence interval, 26%-62%) and 51% (33%-69%) at 1 year and 44% (26%-62%) and 47% (29%-65%) at 5 years. Probability of relapse was 33% (15%-51%) at 1 year and 5 years. Probability of nonrelapse mortality was 31% (13%-49%) at 1 year and 5 years. Incidences were 29% for acute GVHD and 39% for chronic GVHD. None of the 12 patients who developed chronic GVHD has disease recurrence. Patients who had required >3 previous chemotherapy regimens before HCT had an increased probability of relapse. CBV is an effective preparative regimen for patients with aggressive NHL who undergo allogeneic HCT

Mitogen- and Stress-Activated Protein Kinase 1 Regulates Status Epilepticus-Evoked Cell Death in the Hippocampus

Mitogen-activated protein kinase (MAPK) signaling has been implicated in a wide range of neuronal processes, including development, plasticity, and viability. One of the principal downstream targets of both the extracellular signal-regulated kinase/MAPK pathway and the p38 MAPK pathway is M itogen- and S tress-activated protein K inase 1 (MSK1). Here, we sought to understand the role that MSK1 plays in neuroprotection against excitotoxic stimulation in the hippocampus. To this end, we utilized immunohistochemical labeling, a MSK1 null mouse line, cell viability assays, and array-based profiling approaches. Initially, we show that MSK1 is broadly expressed within the major neuronal cell layers of the hippocampus and that status epilepticus drives acute induction of MSK1 activation. In response to the status epilepticus paradigm, MSK1 KO mice exhibited a striking increase in vulnerability to pilocarpine-evoked cell death within the CA1 and CA3 cell layers. Further, cultured MSK1 null neurons exhibited a heighted level of N-methyl-D-aspartate-evoked excitotoxicity relative to wild-type neurons, as assessed using the lactate dehydrogenase assay. Given these findings, we examined the hippocampal transcriptional profile of MSK1 null mice. Affymetrix array profiling revealed that MSK1 deletion led to the significant (>1.25-fold) downregulation of 130 genes and an upregulation of 145 genes. Notably, functional analysis indicated that a subset of these genes contribute to neuroprotective signaling networks. Together, these data provide important new insights into the mechanism by which the MAPK/MSK1 signaling cassette confers neuroprotection against excitotoxic insults. Approaches designed to upregulate or mimic the functional effects of MSK1 may prove beneficial against an array of degenerative processes resulting from excitotoxic insults