CMR left ventricular strains beyond global longitudinal strain in differentiating light-chain cardiac amyloidosis from hypertrophic cardiomyopathy

BackgroundThe clinical value of left ventricular (LV) global longitudinal strain (GLS) in the differential diagnosis of light-chain cardiac amyloidosis (AL-CA) and hypertrophic cardiomyopathy (HCM) has been previously reported. In this study, we analyzed the potential clinical value of the LV long-axis strain (LAS) to discriminate AL-CA from HCM. Furthermore, we analyzed the association between all the LV global strain parameters derived from cardiac magnetic resonance (CMR) feature tracking and LAS in both the AL-CA and HCM patients to assess the differential diagnostic efficacies of these global peak systolic strains.Materials and methodsThus, this study enrolled 89 participants who underwent cardiac MRI (CMRI), consisting of 30 AL-CA patients, 30 HCM patients, and 29 healthy controls. The intra- and inter-observer reproducibility of the LV strain parameters including GLS, global circumferential strain (GCS), global radial strain (GRS), and LAS were assessed in all the groups and compared. Receiver operating characteristic (ROC) curve analysis was performed to determine the diagnostic performances of the CMR strain parameters in discriminating AL-CA from HCM.ResultsThe intra- and inter-observer reproducibility of the LV global strains and LAS were excellent (range of interclass correlation coefficients: 0.907–0.965). ROC curve analyses showed that the differential diagnostic performances of the global strains in discriminating AL-CA from HCM were good to excellent (GRS, AUC = 0.921; GCS, AUC = 0.914; GLS, AUC = 0.832). Furthermore, among all the strain parameters analyzed, LAS showed the highest diagnostic efficacy in differentiating between AL-CA and HCM (AUC = 0.962).ConclusionCMRI-derived strain parameters such as GLS, LAS, GRS, and GCS are promising diagnostic indicators that distinguish AL-CA from HCM with high accuracy. LAS showed the highest diagnostic accuracy among all the strain parameters

Biogeographic patterns of soil diazotrophic communities across six forests in North America.

Soil diazotrophs play important roles in ecosystem functioning by converting atmospheric N2 into biologically available ammonium. However, the diversity and distribution of soil diazotrophic communities in different forests and whether they follow biogeographic patterns similar to macroorganisms still remain unclear. By sequencing nifH gene amplicons, we surveyed the diversity, structure and biogeographic patterns of soil diazotrophic communities across six North American forests (126 nested samples). Our results showed that each forest harboured markedly different soil diazotrophic communities and that these communities followed traditional biogeographic patterns similar to plant and animal communities, including the taxa-area relationship (TAR) and latitudinal diversity gradient. Significantly higher community diversity and lower microbial spatial turnover rates (i.e. z-values) were found for rainforests (~0.06) than temperate forests (~0.1). The gradient pattern of TARs and community diversity was strongly correlated (r(2)  > 0.5) with latitude, annual mean temperature, plant species richness and precipitation, and weakly correlated (r(2)  < 0.25) with pH and soil moisture. This study suggests that even microbial subcommunities (e.g. soil diazotrophs) follow general biogeographic patterns (e.g. TAR, latitudinal diversity gradient), and indicates that the metabolic theory of ecology and habitat heterogeneity may be the major underlying ecological mechanisms shaping the biogeographic patterns of soil diazotrophic communities

Graft copolymer-based lithium-ion battery for high-temperature operation

The article of record as published may be located at http://dx.doi.org/10.1016/j.jpowsour.2011.03.001The use of conventional lithium-ion batteries in high temperature applications (>50 ◦C) is currently inhibited by the high reactivity and volatility of liquid electrolytes. Solvent-free, solid-state polymer electrolytes allow for safe and stable operation of lithium-ion batteries, even at elevated temperatures. Recent advances in polymer synthesis have led to the development of novel materials that exhibit solidlike mechanical behavior while providing the ionic conductivities approaching that of liquid electrolytes. Here we report the successful charge and discharge cycling of a graft copolymer electrolyte (GCE)-based lithium-ion battery at temperatures up to 120 ◦C. The GCE consists of poly(oxyethylene) methacrylate-gpoly( dimethyl siloxane) (POEM-g-PDMS) doped with lithium triflate. Using electrochemical impedance spectroscopy (EIS), we analyze the temperature stability and cycling behavior of GCE-based lithium-ion batteries comprised of a LiFePO4 cathode, a metallic lithium anode, and an electrolyte consisting of a 20- m-thick layer of lithium triflate-doped POEM-g-PDMS. Our results demonstrate the great potential of GCE-based Li-ion batteries for high-temperature applications

Quantitative Analysis of Industrial Solid Waste Based on Terahertz Spectroscopy

Industrial solid waste refers to the solid waste that is produced in industrial production activities. Without correct treatment and let-off, industrial solid waste may cause environmental pollution due to a variety of pollutants and toxic substances that are contained in it. Conventional detection methods for identifying harmful substances are high performance liquid chromatography (HPLC) and gas chromatography-mass spectrometry (GC-MS), which are complicated, time-consuming, and highly demanding for the testing environment. Here, we propose a method for the quantitative analysis of harmful components in industrial solid waste by using terahertz (THz) spectroscopy combined with chemometrics. Pyrazinamide, benazepril, cefprozil, and bisphenol A are four usual hazardous components in industrial solid waste. By comparing with the Raman method, the THz method shows a much higher accuracy for their concentration analysis (90.3–99.8% vs. 11.7–86.9%). In addition, the quantitative analysis of mixtures was conducted, and the resulting prediction accuracy rate was above 95%. This work has high application value for the rapid, accurate, and low-cost detection of industrial solid waste

Quantitative Analysis of Industrial Solid Waste Based on Terahertz Spectroscopy

Industrial solid waste refers to the solid waste that is produced in industrial production activities. Without correct treatment and let-off, industrial solid waste may cause environmental pollution due to a variety of pollutants and toxic substances that are contained in it. Conventional detection methods for identifying harmful substances are high performance liquid chromatography (HPLC) and gas chromatography-mass spectrometry (GC-MS), which are complicated, time-consuming, and highly demanding for the testing environment. Here, we propose a method for the quantitative analysis of harmful components in industrial solid waste by using terahertz (THz) spectroscopy combined with chemometrics. Pyrazinamide, benazepril, cefprozil, and bisphenol A are four usual hazardous components in industrial solid waste. By comparing with the Raman method, the THz method shows a much higher accuracy for their concentration analysis (90.3–99.8% vs. 11.7–86.9%). In addition, the quantitative analysis of mixtures was conducted, and the resulting prediction accuracy rate was above 95%. This work has high application value for the rapid, accurate, and low-cost detection of industrial solid waste

Avrami Kinetic-Based Constitutive Relationship for Armco-Type Pure Iron in Hot Deformation

The work presents a full mathematical description of the stress-strain compression curves in a wide range of strain rates and deformation temperatures for Armco-type pure iron. The constructed models are based on a dislocation structure evolution equation (in the case of dynamic recovery (DRV)) and Avrami kinetic-based model (in the case of dynamic recrystallization (DRX)). The fractional softening model is modified as: X = ( σ 2 − σ r 2 ) / ( σ d s 2 − σ r 2 ) considering the strain hardening of un-recrystallized regions. The Avrami kinetic equation is modified and used to describe the DRX process considering the strain rate and temperature. The relations between the Avrami constant k ∗ , time exponent n ∗ , strain rate ε ˙ , temperature T and Z parameter are discussed. The yield stress σ y , saturation stress σ r s , steady stress σ d s and critical strain ε c are expressed as the functions of the Z parameter. A constitutive model is constructed based on the strain-hardening model, fractional softening model and modified Avrami kinetic equation. The DRV and DRX characters of Armco-type pure iron are clearly presented in these flow stress curves determined by the model

Moderate injury in motor-sensory cortex causes behavioral deficits accompanied by electrophysiological changes in mice adulthood

<div><p>Moderate traumatic brain injury (TBI) in children often happen when there’s a sudden blow to the frontal bone, end with long unconscious which can last for hours and progressive cognitive deficits. However, with regard to the influences of moderate TBI during children adulthood, injury-induced alterations of locomotive ability, long-term memory performance, and hippocampal electrophysiological firing changes have not yet been fully identified. In this study, lateral fluid percussion (LFP) method was used to fabricate moderate TBI in motor and somatosensory cortex of the 6-weeks-old mice. The motor function, learning and memory function, extracellular CA1 neural spikes were assessed during acute and subacute phase. Moreover, histopathology was performed on day post injury (DPI) 16 to evaluate the effect of TBI on tissue and cell morphological changes in cortical and hippocampal CA1 subregions. After moderate LFP injury, the 6-weeks-old mice showed severe motor deficits at the early stage in acute phase but gradually recovered later during adulthood. At the time points in acute and subacute phase after TBI, novel object recognition (NOR) ability and spatial memory functions were consistently impaired in TBI mice; hippocampal firing frequency and burst probability were hampered. Analysis of the altered burst firing shows a clear hippocampal theta rhythm drop. These electrophysiological impacts were associated with substantially lowered NOR preference as compared to the sham group during adulthood. These results suggest that moderate TBI introduced at motorsenory cortex in 6-weeks-old mice causes obvious motor and cognitive deficits during their adulthood. While the locomotive ability progressively recovers, the cognitive deficits persisted while the mice mature as adult mice. The cognitive deficits may be attributed to the general suppressing of whole neural network, which could be labeled by marked reduction of excitability in hippocampal CA1 subregion.</p></div

Results of burst analysis in the CA1 subregion after moderate TBI.

<p>Representative instant firing, autocorrelogram and power spectral density in CA1 pyramidal cell of sham mice on DPI 7 (<b>panel A</b>) and 14 (<b>panel C</b>). Decreases of instant burst firing (<b>left column</b>) in CA1 pyramidal cell of TBI mice on DPI 7 (<b>panel B</b>) and on DPI 14 (<b>panel D</b>) are confirmed by the reductions of frequency in autocorrelogram (1ms bin, <b>middle column</b>) and drops of power spectral density within theta range (<b>right column</b>). Data in three graphs of each panel (A-<b>D</b>) are from the same cell.</p

The Motor function changes after TBI.

<p>Mice motor performance in term of beam-walk latency (A) and foot-fault (B) were significantly impaired due to moderate TBI. Multiple Holm-Sidak <i>t</i> test were used to compare the daily based beam-walk or foot-fault between TBI and sham groups. Data are expressed as mean±SEM (n = 7). * p<0.05, ** p<0.01 and ***, P < 0.001 vs. control.</p