Association of proinflammatory cytokines and chemotherapy-associated cognitive impairment in breast cancer patients: a multi-centered, prospective, cohort study.

BackgroundExisting evidence suggests that proinflammatory cytokines play an intermediary role in postchemotherapy cognitive impairment. This is one of the largest multicentered, cohort studies conducted in Singapore to evaluate the prevalence and proinflammatory biomarkers associated with cognitive impairment in breast cancer patients.Patients and methodsChemotherapy-receiving breast cancer patients (stages I-III) were recruited. Proinflammatory plasma cytokines concentrations [interleukin (IL)-1β, IL-2, IL-4, IL-6, IL-8, IL-10, granulocyte-macrophage colony-stimulating factor, interferon-γ and tumor necrosis factor-α] were evaluated at 3 time points (before chemotherapy, 6 and 12 weeks after chemotherapy initiation). The FACT-Cog (version 3) was utilized to evaluate patients' self-perceived cognitive disturbances and a computerized neuropsychological assessment (Headminder) was administered to evaluate patients' memory, attention, response speed and processing speed. Changes of cognition throughout chemotherapy treatment were compared against the baseline. Linear mixed-effects models were applied to test the relationships of clinical variables and cytokine concentrations on self-perceived cognitive disturbances and each objective cognitive domain.ResultsNinety-nine patients were included (age 50.5 ± 8.4 years; 81.8% Chinese; mean duration of education = 10.8 ± 3.3 years). Higher plasma IL-1β was associated with poorer response speed performance (estimate: -0.78; 95% confidence interval (CI) -1.34 to -0.03; P = 0.023), and a higher concentration of IL-4 was associated with better response speed performance (P = 0.022). Higher concentrations of IL-1β and IL-6 were associated with more severe self-perceived cognitive disturbances (P = 0.018 and 0.001, respectively). Patients with higher concentrations of IL-4 also reported less severe cognitive disturbances (P = 0.022).ConclusionsWhile elevated concentrations of IL-6 and IL-1β were observed in patients with poorer response speed performance and perceived cognitive disturbances, IL-4 may be protective against chemotherapy-associated cognitive impairment. This study is important because cytokines would potentially be mechanistic mediators of chemotherapy-associated cognitive changes

Enkephalon - technological platform to support the diagnosis of alzheimer’s disease through the analysis of resonance images using data mining techniques

Dementia can be considered as a decrease in the cognitive function of the person. The main diseases that appear are Alzheimer and vascular dementia. Today, 47 million people live with dementia around the world. The estimated total cost of dementia worldwide is US $ 818 billion, and it will become a trilliondollar disease by 2019 The vast majority of people with dementia not received a diagnosis, so they are unable to access care and treatment. In Colombia, two out of every five people presented a mental disorder at some point in their lives and 90% of these have not accessed a health service. Here it´s proposed a technological platform so early detection of Alzheimer. This tool complements and validates the diagnosis made by the health professional, based on the application of Machine Learning techniques for the analysis of a dataset, constructed from magnetic resonance imaging, neuropsychological test and the result of a radiological test. A comparative analysis of quality metrics was made, evaluating the performance of different classifier methods: Random subspace, Decorate, BFTree, LMT, Ordinal class classifier, ADTree and Random forest. This allowed us to identify the technique with the highest prediction rate, that was implemented in ENKEPHALON platform

Progress on Modified Calcium Oxide Derived Waste-Shell Catalysts for Biodiesel Production

The dwindling of global petroleum deposits and worsening environmental issues have triggered researchers to find an alternative energy such as biodiesel. Biodiesel can be produced via transesterification of vegetable oil or animal fat with alcohol in the presence of a catalyst. A heterogeneous catalyst at an economical price has been studied widely for biodiesel production. It was noted that various types of natural waste shell are a potential calcium resource for generation of bio-based CaO, with comparable chemical characteristics, that greatly enhance the transesterification activity. However, CaO catalyzed transesterification is limited in its stability and studies have shown deterioration of catalytic reactivity when the catalyst is reused for several cycles. For this reason, different approaches are reviewed in the present study, which focuses on modification of waste-shell derived CaO based catalyst with the aim of better transesterification reactivity and high reusability of the catalyst for biodiesel production. The catalyst stability and leaching profile of the modified waste shell derived CaO is discussed. In addition, a critical discussion of the structure, composition of the waste shell, mechanism of CaO catalyzed reaction, recent progress in biodiesel reactor systems and challenges in the industrial sector are also included in this review

Inferring transcriptional compensation interactions in yeast via stepwise structure equation modeling

<p>Abstract</p> <p>Background</p> <p>With the abundant information produced by microarray technology, various approaches have been proposed to infer transcriptional regulatory networks. However, few approaches have studied subtle and indirect interaction such as genetic compensation, the existence of which is widely recognized although its mechanism has yet to be clarified. Furthermore, when inferring gene networks most models include only observed variables whereas latent factors, such as proteins and mRNA degradation that are not measured by microarrays, do participate in networks in reality.</p> <p>Results</p> <p>Motivated by inferring transcriptional compensation (TC) interactions in yeast, a stepwise structural equation modeling algorithm (SSEM) is developed. In addition to observed variables, SSEM also incorporates hidden variables to capture interactions (or regulations) from latent factors. Simulated gene networks are used to determine with which of six possible model selection criteria (MSC) SSEM works best. SSEM with Bayesian information criterion (BIC) results in the highest true positive rates, the largest percentage of correctly predicted interactions from all existing interactions, and the highest true negative (non-existing interactions) rates. Next, we apply SSEM using real microarray data to infer TC interactions among (1) small groups of genes that are synthetic sick or lethal (SSL) to SGS1, and (2) a group of SSL pairs of 51 yeast genes involved in DNA synthesis and repair that are of interest. For (1), SSEM with BIC is shown to outperform three Bayesian network algorithms and a multivariate autoregressive model, checked against the results of qRT-PCR experiments. The predictions for (2) are shown to coincide with several known pathways of Sgs1 and its partners that are involved in DNA replication, recombination and repair. In addition, experimentally testable interactions of Rad27 are predicted.</p> <p>Conclusion</p> <p>SSEM is a useful tool for inferring genetic networks, and the results reinforce the possibility of predicting pathways of protein complexes via genetic interactions.</p

Plasma miRNA as Biomarkers for Assessment of Total-Body Radiation Exposure Dosimetry

The risk of radiation exposure, due to accidental or malicious release of ionizing radiation, is a major public health concern. Biomarkers that can rapidly identify severely-irradiated individuals requiring prompt medical treatment in mass-casualty incidents are urgently needed. Stable blood or plasma-based biomarkers are attractive because of the ease for sample collection. We tested the hypothesis that plasma miRNA expression profiles can accurately reflect prior radiation exposure. We demonstrated using a murine model that plasma miRNA expression signatures could distinguish mice that received total body irradiation doses of 0.5 Gy, 2 Gy, and 10 Gy (at 6 h or 24 h post radiation) with accuracy, sensitivity, and specificity of above 90%. Taken together, these data demonstrate that plasma miRNA profiles can be highly predictive of different levels of radiation exposure. Thus, plasma-based biomarkers can be used to assess radiation exposure after mass-casualty incidents, and it may provide a valuable tool in developing and implementing effective countermeasures

Clear Genetic Distinctiveness between Human- and Pig-Derived Trichuris Based on Analyses of Mitochondrial Datasets

The whipworm, Trichuris trichiura, causes trichuriasis in ∼600 million people worldwide, mainly in developing countries. Whipworms also infect other animal hosts, including pigs (T. suis), dogs (T. vulpis) and non-human primates, and cause disease in these hosts, which is similar to trichuriasis of humans. Although Trichuris species are considered to be host specific, there has been considerable controversy, over the years, as to whether T. trichiura and T. suis are the same or distinct species. Here, we characterised the entire mitochondrial genomes of human-derived Trichuris and pig-derived Trichuris, compared them and then tested the hypothesis that the parasites from these two host species are genetically distinct in a phylogenetic analysis of the sequence data. Taken together, the findings support the proposal that T. trichiura and T. suis are separate species, consistent with previous data for nuclear ribosomal DNA. Using molecular analytical tools, employing genetic markers defined herein, future work should conduct large-scale studies to establish whether T. trichiura is found in pigs and T. suis in humans in endemic regions

Landscape Composition and Spatial Prediction of Alveolar Echinococcosis in Southern Ningxia, China

In humans, larvae of the fox tapeworm Echinococcus multilocularis typically infect the liver where metastasis, calcification and necrosis cause the zoonotic disease alveolar echinococcosis (AE). Treatment is difficult. Early detection greatly increases patient life expectancy but under-detection is a problem. Understanding the ecological conditions that elevate AE risk would help identify at-risk communities. Voles and lemmings of the subfamily Arvicolinae are important intermediate hosts in most AE endemic areas, and arvicoline habitat has been proposed as a predictor of AE risk. Using a model of spatial autocorrelation with land cover identified from satellite remote sensing imagery, we identified AE hotspots in southern Ningxia Hui Autonomous Region (NHAR), China. Hotspots were not located near optimal arvicoline habitats. Thus, non-arvicolines provide principal reservoirs in NHAR and the range of ecological conditions sustaining E. multilocularis transmission in China is greater than previously thought. We also show: social factors explain higher prevalence in females than males; dogs increase infection risk; and we argue that water source quality is important via interaction with other environmental variables. Our map of AE prevalence represents the current state-of-the-art regarding the spatial distribution of AE in southern NHAR and provides an important baseline for future monitoring programs there

TET family dioxygenases and DNA demethylation in stem cells and cancers

The methylation of cytosine and subsequent oxidation constitutes a fundamental epigenetic modification in mammalian genomes, and its abnormalities are intimately coupled to various pathogenic processes including cancer development. Enzymes of the Ten-eleven translocation (TET) family catalyze the stepwise oxidation of 5-methylcytosine in DNA to 5-hydroxymethylcytosine and further oxidation products. These oxidized 5-methylcytosine derivatives represent intermediates in the reversal of cytosine methylation, and also serve as stable epigenetic modifications that exert distinctive regulatory roles. It is becoming increasingly obvious that TET proteins and their catalytic products are key regulators of embryonic development, stem cell functions and lineage specification. Over the past several years, the function of TET proteins as a barrier between normal and malignant states has been extensively investigated. Dysregulation of TET protein expression or function is commonly observed in a wide range of cancers. Notably, TET loss-of-function is causally related to the onset and progression of hematologic malignancy in vivo. In this review, we focus on recent advances in the mechanistic understanding of DNA methylation-demethylation dynamics, and their potential regulatory functions in cellular differentiation and oncogenic transformation