A new role for tissue-type plasminogen activator in liver injury

Chronic liver disease is increasing in prevalence worldwide; however, few medical therapies are available to treat liver cirrhosis and failure. Hepatic stellate cell (HSC) activation and trans-differentiation into myofibroblast-like (MFB-like) cells is a key process in liver injury and fibrogenesis. Greater understanding of the role of matrix regulating proteases, such as the plasminogen activators, in HSC activation could provide new therapeutic targets for treating chronic liver disease. Mice lacking plasminogen activators exhibit delay in liver repair; however, their exact functions after liver injury remain unclear. Recent studies in kidney demonstrate that low density lipoprotein receptor-related protein 1 (LRP1)-dependent signaling by tissue-type plasminogen activator (t-PA) is an essential regulator of the myofibroblast phenotype after injury. This study investigated the role of t-PA and LRP1 in HSC activation and in vivo liver injury. We find that, in contrast to kidney fibroblasts, exogenous t-PA antagonizes activation of primary and immortalized HSCs in vitro. Similar to kidney, these effects are independent of the proteolytic function of t-PA and require phosphorylation of LRP1. Antagonism of LRP1 or PI3K/Akt signaling pathways is able to prevent t-PA-mediated decreases in α-SMA. During recovery following acute liver injury, mice lacking t-PA (globally) or LRP1 (conditionally on HSCs) retain higher densities of the α-SMA+ MFB-like cell population compared to control mice. These differences are seen at time points that correspond to the appearance of co-localization between p-LRP1 and α-SMA, as well as t-PA immunolocalization at sites of α-SMA-positive cells. Additionally, t-PA may regulate macrophage phenotype and drug metabolism, as t-PA null mice exhibit increased macrophage accumulation and lack of normal compensatory down-regulation of a key metabolic enzyme after acute injury. Finally, more collagen I deposition remains in the livers of t-PA null mice up to two weeks after cessation of chronic liver injury, suggesting a decreased rate of matrix turnover. These data reveal that t-PA has multiple functions in liver repair and is able to affect the phenotype of several cell types, in addition to its classical plasminogen activating role. Further preclinical studies are needed to evaluate the clinical potential of using t-PA as a treatment for chronic liver injury and fibrosis

Disruption of thymic central tolerance by infection with murine roseolovirus induces autoimmune gastritis

Infections with herpesviruses, including human roseoloviruses, have been proposed to cause autoimmune disease, but defining a causal relationship and mechanism has been difficult due to the ubiquitous nature of infection and development of autoimmunity long after acute infection. Murine roseolovirus (MRV) is highly related to human roseoloviruses. Herein we show that neonatal MRV infection induced autoimmune gastritis (AIG) in adult mice in the absence of ongoing infection. MRV-induced AIG was dependent on replication during the neonatal period and was CD4+ T cell and IL-17 dependent. Moreover, neonatal MRV infection was associated with development of a wide array of autoantibodies in adult mice. Finally, neonatal MRV infection reduced medullary thymic epithelial cell numbers, thymic dendritic cell numbers, and thymic expression of AIRE and tissue-restricted antigens, in addition to increasing thymocyte apoptosis at the stage of negative selection. These findings strongly suggest that infection with a roseolovirus early in life results in disruption of central tolerance and development of autoimmune disease

Transcriptomic, proteomic and metabolic changes in Arabidopsis thaliana leaves after the onset of illumination

BACKGROUND: Light plays an important role in plant growth and development. In this study, the impact of light on physiology of 20-d-old Arabidopsis leaves was examined through transcriptomic, proteomic and metabolomic analysis. Since the energy-generating electron transport chains in chloroplasts and mitochondria are encoded by both nuclear and organellar genomes, sequencing total RNA after removal of ribosomal RNAs provides essential information on transcription of organellar genomes. The changes in the levels of ADP, ATP, NADP(+), NADPH and 41 metabolites upon illumination were also quantified. RESULTS: Upon illumination, while the transcription of the genes encoded by the plastid genome did not change significantly, the transcription of nuclear genes encoding different functional complexes in the photosystem are differentially regulated whereas members of the same complex are co-regulated with each other. The abundance of mRNAs and proteins encoded by all three genomes are, however, not always positively correlated. One such example is the negative correlation between mRNA and protein abundances of the photosystem components, which reflects the importance of post-transcriptional regulation in plant physiology. CONCLUSION: This study provides systems-wide datasets which allow plant researchers to examine the changes in leaf transcriptomes, proteomes and key metabolites upon illumination and to determine whether there are any correlations between changes in transcript and protein abundances of a particular gene or pathway upon illumination. The integration of data of the organelles and the photosystems, Calvin-Benson cycle, carbohydrate metabolism, glycolysis, the tricarboxylic acid cycle and respiratory chain, thereby provides a more complete picture to the changes in plant physiology upon illumination than has been attained to date.published_or_final_versio

Effect of crude canine pituitary extract (cCPE) on the in vitro production of progesterone and nuclear maturation of canine oocytes

We examined the effect of crude canine pituitary extract (cCPE) on the in vitro nuclear maturation of canine oocytes and production of progesterone by cumulus cells. cCPE was extracted from canine pituitaries and the concentrations of canine follicle stimulating hormone (FSH) and luteinizing hormone (LH) were determined. Cumulus oocyte complexes (COCs) were harvested from anestrus cycle ovaries and matured in NCSU-37 supplemented with 10% estrus bitch serum, 50 μg/ml gentamycin and 0, 40 or 400 μg/ml cCPE at 38°C in a humidified atmosphere of 5% CO2 for 72 h. The nuclear maturation of the oocytes and the level of progesterone in the culture medium were evaluated. Development to metaphase I (MI) - metaphase II (MII) of canine oocytes in 400 μg/ml cCPE (15.4%) was significantly higher than in 0 and 40 μg/ml cCPE (4.3 and 8.7%), respectively. Treatment with 40 and 400 μg/ml cCPE also generated 0.33 and 0.65 ng/ml progesterone in the culture medium, respectively. Thus, the addition of cCPE to the culture medium promotes the nuclear maturation of canine oocytes and elevates the production of progesterone by cumulus cells.Key words: In vitro maturation, pituitary extract, canine oocyte

Automated Classification Model With OTSU and CNN Method for Premature Ventricular Contraction Detection

Premature ventricular contraction (PVC) is one of the most common arrhythmias which can cause palpitation, cardiac arrest, and other symptoms affecting the work and rest activities of a patient. However, patients hardly decipher their own feelings to determine the severity of the disease thus, requiring a professional medical diagnosis. This study proposes a novel method based on image processing and convolutional neural network (CNN) to extract electrocardiography (ECG) curves from scanned ECG images derived from clinical ECG reports, and segment and classify heartbeats in the absence of a digital ECG data. The ECG curve is extracted using a comprehensive algorithm that combines the OTSU algorithm with erosion and dilation. This algorithm can efficiently and accurately separate the ECG curve from the ECG background grid. The performance of the classification model was evaluated and optimized using hundreds of clinical ECG data collected from Fujian Provincial Hospital. Additionally, thousands of clinical ECG reports were scanned to digital images as the test set to confirm the accuracy of the algorithm for practical application. Results showed that the average sensitivity, specificity, positive predictive value, and accuracy of the proposed model on the MIT-BIH dataset were 95.47%, 97.72%, 98.75%, and 98.25%, respectively. The classification average sensitivity, specificity, positive predictive value, and accuracy based on clinical scanned ECG images can reach to 97.24%, 81.6%, 83.8%, and 89.33%, respectively, and the clinical feasibility is high. Overall, the proposed method can extract ECG curves from scanned ECG images efficiently and accurately. Furthermore, it performs well on heartbeat classification of normal (N) and ventricular premature heartbeat

Three-Heartbeat Multilead ECG Recognition Method for Arrhythmia Classification

Electrocardiogram (ECG) is the primary basis for the diagnosis of cardiovascular diseases. However, the amount of ECG data of patients makes manual interpretation time-consuming and onerous. Therefore, the intelligent ECG recognition technology is an important means to decrease the shortage of medical resources. This study proposes a novel classification method for arrhythmia that uses for the very first time a three-heartbeat multi-lead (THML) ECG data in which each fragment contains three complete heartbeat processes of multiple ECG leads. The THML ECG data pre-processing method is formulated which makes use of the MIT-BIH arrhythmia database as training samples. Four arrhythmia classification models are constructed based on one-dimensional convolutional neural network (1D-CNN) combined with a priority model integrated voting method to optimize the integrated classification effect. The experiments followed the recommended inter-patient scheme of the Association for the Advancement of Medical Instrumentation (AAMI) recommendations, and the practicability and effectiveness of THML ECG data are proved with ablation experiments. Results show that the average accuracy of the N, V, S, F, and Q classes is 94.82%, 98.10%, 97.28%, 98.70%, and 99.97%, respectively, with the positive predictive value of the N, V, S, and F classes being 97.0%, 90.5%, 71.9%, and 80.4%, respectively. Compared with current studies, the THML ECG data can effectively improve the morphological integrity and time continuity of ECG information and the 1D-CNN model of ECG sequence has a higher accuracy for arrhythmia classification. The proposed method alleviates the problem of insufficient samples, meets the needs of medical ECG interpretation and contributes to the intelligent dynamic research of cardiac disease

Ballistic Composite Fermions in Semiconductor Nanostructures

We report the results of two fundamental transport measurements at a Landau level filling factor $\nu$ of 1/2. The well known ballistic electron transport phenomena of quenching of the Hall effect in a mesoscopic cross-junction and negative magnetoresistance of a constriction are observed close to B~=~0 and $\nu~=~ 1/2$. The experimental results demonstrate semi-classical charge transport by composite fermions, which consist of electrons bound to an even number of flux quanta.Comment: 9 pages TeX 3.1415 C version 6.1, 3 PostScript figure

Kondo effect in systems with dynamical symmetries

This paper is devoted to a systematic exposure of the Kondo physics in quantum dots for which the low energy spin excitations consist of a few different spin multiplets $|S_{i}M_{i}>$. Under certain conditions (to be explained below) some of the lowest energy levels $E_{S_{i}}$ are nearly degenerate. The dot in its ground state cannot then be regarded as a simple quantum top in the sense that beside its spin operator other dot (vector) operators ${\bf R}_{n}$ are needed (in order to fully determine its quantum states), which have non-zero matrix elements between states of different spin multiplets $\ne 0$. These "Runge-Lenz" operators do not appear in the isolated dot-Hamiltonian (so in some sense they are "hidden"). Yet, they are exposed when tunneling between dot and leads is switched on. The effective spin Hamiltonian which couples the metallic electron spin ${\bf s}$ with the operators of the dot then contains new exchange terms, $J_{n} {\bf s} \cdot {\bf R}_{n}$ beside the ubiquitous ones $J_{i} {\bf s}\cdot {\bf S}_{i}$. The operators ${\bf S}_{i}$ and ${\bf R}_{n}$ generate a dynamical group (usually SO(n)). Remarkably, the value of $n$ can be controlled by gate voltages, indicating that abstract concepts such as dynamical symmetry groups are experimentally realizable. Moreover, when an external magnetic field is applied then, under favorable circumstances, the exchange interaction involves solely the Runge-Lenz operators ${\bf R}_{n}$ and the corresponding dynamical symmetry group is SU(n). For example, the celebrated group SU(3) is realized in triple quantum dot with four electrons.Comment: 24 two-column page

Analysis of human immune responses in quasi-experimental settings: tutorial in biostatistics

<p>Abstract</p> <p>Background</p> <p>Human immunology is a growing field of research in which experimental, clinical, and analytical methods of many life science disciplines are utilized. Classic epidemiological study designs, including observational longitudinal birth cohort studies, offer strong potential for gaining new knowledge and insights into immune response to pathogens in humans. However, rigorous discussion of methodological issues related to designs and statistical analysis that are appropriate for longitudinal studies is lacking.</p> <p>Methods</p> <p>In this communication we address key questions of quality and validity of traditional and recently developed statistical tools applied to measures of immune responses. For this purpose we use data on humoral immune response (IR) associated with the first cryptosporidial diarrhea in a birth cohort of children residing in an urban slum in south India. The main objective is to detect the difference and derive inferences for a change in IR measured at two time points, before (pre) and after (post) an event of interest. We illustrate the use and interpretation of analytical and data visualization techniques including generalized linear and additive models, data-driven smoothing, and combinations of box-, scatter-, and needle-plots.</p> <p>Results</p> <p>We provide step-by-step instructions for conducting a thorough and relatively simple analytical investigation, describe the challenges and pitfalls, and offer practical solutions for comprehensive examination of data. We illustrate how the assumption of time irrelevance can be handled in a study with a pre-post design. We demonstrate how one can study the dynamics of IR in humans by considering the timing of response following an event of interest and seasonal fluctuation of exposure by proper alignment of time of measurements. This alignment of calendar time of measurements and a child's age at the event of interest allows us to explore interactions between IR, seasonal exposures and age at first infection.</p> <p>Conclusions</p> <p>The use of traditional statistical techniques to analyze immunological data derived from observational human studies can result in loss of important information. Detailed analysis using well-tailored techniques allows the depiction of new features of immune response to a pathogen in longitudinal studies in humans. The proposed staged approach has prominent implications for future study designs and analyses.</p