A susceptible-infected model of early detection of respiratory infection outbreaks on a background of influenza

The threat of biological warfare and the emergence of new infectious agents spreading at a global scale have highlighted the need for major enhancements to the public health infrastructure. Early detection of epidemics of infectious diseases requires both real-time data and real-time interpretation of data. Despite moderate advancements in data acquisition, the state of the practice for real-time analysis of data remains inadequate. We present a nonlinear mathematical framework for modeling the transient dynamics of influenza, applied to historical data sets of patients with influenza-like illness. We estimate the vital time-varying epidemiological parameters of infections from historical data, representing normal epidemiological trends. We then introduce simulated outbreaks of different shapes and magnitudes into the historical data, and estimate the parameters representing the infection rates of anomalous deviations from normal trends. Finally, a dynamic threshold-based detection algorithm is devised to assess the timeliness and sensitivity of detecting the irregularities in the data, under a fixed low false-positive rate. We find that the detection algorithm can identify such designated abnormalities in the data with high sensitivity with specificity held at 97%, but more importantly, early during an outbreak. The proposed methodology can be applied to a broad range of influenza-like infectious diseases, whether naturally occurring or a result of bioterrorism, and thus can be an integral component of a real-time surveillance system.     

Retinal proteomics of experimental glaucoma model reveal intraocular pressure-induced mediators of neurodegenerative changes

Current evidence suggests that exposure to chronically induced intraocular pressure (IOP) leads to neurodegenerative changes in the inner retina. This study aimed to determine retinal proteomic alterations in a rat model of glaucoma and compared findings with human retinal proteomics changes in glaucoma reported previously. We developed an experimental glaucoma rat model by subjecting the rats to increased IOP (9.3 ± 0.1 vs 20.8 ± 1.6 mm Hg) by weekly microbead injections into the eye (8 weeks). The retinal tissues were harvested from control and glaucomatous eyes and protein expression changes analysed using a multiplexed quantitative proteomics approach (TMT-MS3). Immunofluorescence was performed for selected protein markers for data validation. Our study identified 4304 proteins in the rat retinas. Out of these, 139 proteins were downregulated (≤0.83) while the expression of 109 proteins was upregulated (≥1.2-fold change) under glaucoma conditions (P ≤ .05). Computational analysis revealed reduced expression of proteins associated with glutathione metabolism, mitochondrial dysfunction/oxidative phosphorylation, cytoskeleton, and actin filament organisation, along with increased expression of proteins in coagulation cascade, apoptosis, oxidative stress, and RNA processing. Further functional network analysis highlighted the differential modulation of nuclear receptor signalling, cellular survival, protein synthesis, transport, and cellular assembly pathways. Alterations in crystallin family, glutathione metabolism, and mitochondrial dysfunction associated proteins shared similarities between the animal model of glaucoma and the human disease condition. In contrast, the activation of the classical complement pathway and upregulation of cholesterol transport proteins were exclusive to human glaucoma. These findings provide insights into the neurodegenerative mechanisms that are specifically affected in the retina in response to chronically elevated IOP.     

Study of the Alzheimer's Aβ40 peptide in SDS micelles using molecular dynamics simulations

The interaction of the Alzheimer's amyloid beta peptide, Aβ40, with sodium dodecyl sulfate (SDS) micelles, together with the self-assembly of SDS molecules around the peptide from an initial random distribution were studied using atomistic and coarse-grained (CG) molecular dynamics simulations. In atomistic simulations, the peptide structure in the micelle was characterized by two helical regions connected through a short hinge. The initial structure of the system was shown to affect the simulation results. The atomistic self-assembly of SDS molecules resulted in a 38-molecule micelle around the peptide, along with some globules and individual molecules. Coarse-grained simulation results, however, did not show such a difference, and at the end of all CG simulations, a complete 60-molecule micelle was obtained, with the peptide located at the interface of the micelle with water. The obtained CG radial density profiles and SDS micelle size and shape properties were identical for all CG simulations.     

Surrogating and redirection of pyrazolo[1,5-a]pyrimidin-7(4H)-one core,a novel class of potent and selective DPP-4 inhibitors

The initial focus on characterizing novel pyrazolo[1,5-a]pyrimidin-7(4H)-one derivatives as DPP-4 inhibitors, led to a potent and selective inhibitor compound b2. This ligand exhibits potent in vitro DPP-4 inhibitory activity (IC₅₀: 80?nM), while maintaining other key cellular parameters such as high selectivity, low cytotoxicity and good cell viability. Subsequent optimization of b2 based on docking analysis and structure-based drug design knowledge resulted in d1. Compound d1 has nearly 2-fold increase of inhibitory activity (IC₅₀: 49?nM) and over 1000-fold selectivity against DPP-8 and DPP-9. Further in vivo IPGTT assays showed that compound b2 effectively reduce glucose excursion by 34% at the dose of 10?mg/kg in diabetic mice. Herein we report the optimization and design of a potent and highly selective series of pyrazolo[1,5-a]pyrimidin-7(4H)-one DPP-4 inhibitors.     

Prediction of Blood miRNA-mRNA Regulatory Network in Gastric Cancer

Background:The aim of the study was to suggest a high specific and sensitive blood biomarker for early GC diagnosis.Methods:the expression data of miRNAs and mRNAs were collected from the blood samples of the GC patients based on literature mining. Bioinformatics tools and databases (PANTHER, TargetScan, miRTarBase, miRDB, STRING, and Cytoscape) were used to predict the regulatory relationship. Subsequently, expression level of the selected miRNA was evaluated in the blood samples of gastritis patients to recognize the common miRNA between the GC and gastritis patients.Results:Analysis of 40 target genes by MCODE (installed in Cytoscape software) indicated 4 hub genes (WWP1, SKP2, KLHL42, and FBXO11) as a significant cluster in the PPI network related to miR-21, with Node Score Cutoff: 0.2, Degree Cutoff: 2 and K-Core: 2. In addition, the miRNA RT-qPCR results showed that, the expression level of miR-21 was significantly higher in gastritis group compared to the healthy group (p< 0.05).Conclusion:the present study clearly demonstrated the increasing level of blood miR-21 among the gastritis patients infected by H. pylori. Therefore, the altered miRNAs, especially overexpression of onco-miRs, may identify a potential link between miRNAs and pathogenesis of the H. pylori–related complications.Key Words: Blood Profiling, Gastric Cancer, H. pylori, Mir-21, Regulatory Network     

An overview of the role of cancer stem cells in spine tumors with a special focus on chordoma简

Primary malignant tumors of the spine are relatively rare, less than 5% of all spinal column tumors. However, these lesions are often among the most difficult to treat and encompass challenging pathologies such as chordoma and a variety of invasive sarcomas. The mechanisms of tumor recurrence after surgical intervention, as well as resistance to radiation and chemotherapy, remain a pervasive and costly problem. Recent evidence has emerged supporting the hypothesis that solid tumors contain a sub-population of cancer cells that possess characteristics normally associated with stem cells. Particularly, the potential for long-term proliferation appears to be restricted to subpopulations of cancer stem cells (CSCs) functionally defined by their capacity to self-renew and give rise to differentiated cells that phenotypically recapitulate the original tumor, thereby causing relapse and patient death. These cancer stem cells present a unique opportunity to better understand the biology of solid tumors in general, as well as targets for future therapeutics. The general objective of the current study is to discuss the fundamental concepts for understanding the role of CSCs with respect to chemoresistance, radioresistance, special cell surface markers, cancer recurrence and metastasis in tumors of the osseous spine. This discussion is followed by a specific review of what is known about the role of CSCs in chordoma, the most common primary malignant osseous tumor of the spine.     

Transient dynamics and early diagnostics in infectious disease

To date, mathematical models of the dynamics of infectious disease have consistently focused on understanding the long-term behavior of the interacting components, where the steady state solutions are paramount. However for most acute infections, the long-term behavior of the pathogen population is of little importance to the host and population health. We introduce the notion of transient pathology, where the short-term dynamics of interaction between the immune system and pathogens is the principal focus. We identify the amplifying effect of the absence of a fully operative immune system on the pathogenesis of the initial inoculum, and its implication for the acute severity of the infection. We then formalize the underlying dynamics, and derive two measures of transient pathogenicity: the peak of infection (maximum pathogenic load) and the time to peak of infection, both crucial to understanding the early dynamics of infection and its consequences for early intervention. Received: 25 January 2000 / Revised version: 30 November 2000 / Published online: 12 October 2001     

An insight into the distribution,genetic diversity,and mycotoxin production of <Emphasis Type="Italic">Aspergillus</Emphasis> section <Emphasis Type="Italic">Flavi</Emphasis> in soils of pistachio orchards

In the present study, 193 Aspergillus strains were isolated from a total of 100 soil samples of pistachio orchards, which all of them were identified as Aspergillus flavus as the most abundant species of Aspergillus section Flavi existing in the environment. Approximately 59%, 81%, and 61% of the isolates were capable of producing aflatoxins (AFs), cyclopiazonic acid (CPA), and sclerotia, respectively. The isolates were classified into four chemotypes (I to IV) based on the ability to produce AFs and CPA. The resulting dendrogram of random amplified polymorphic DNA (RAPD) analysis of 24 selected A. flavus isolates demonstrated the formation of two separate clusters. Cluster 1 contained both aflatoxigenic and non-aflatoxigenic isolates (17 isolates), whereas cluster 2 comprised only aflatoxigenic isolates (7 isolates). All the isolates of cluster 2 produced significantly higher levels of AFs than those of cluster 1 and the isolates that produced both AFB₁ and AFB₂ were found only in cluster 2. RAPD genotyping allowed the differentiation of A. flavus from Aspergillus parasiticus as a closely related species within section Flavi. The present study has provided for the first time the relevant information on distribution and genetic diversity of different A. flavus populations from nontoxigenic to highly toxigenic enable to produce hazardous amounts of AFB₁ and CPA in soils of pistachio orchards. These fungi, either toxigenic or not-toxigenic, should be considered as potential threats for agriculture and public health.