Comment on "Research on values of GDF-15 level in the diagnosis of primary liver cancer and evaluation of chemotherapeutic effect"

Comment on research on values of GDF-15 level in the diagnosis of primary liver cancer and evaluation of chemotherapeutic effec

Unveiling Clusters of RNA Transcript Pairs Associated with Markers of Alzheimer's Disease Progression

Background: One primary goal of transcriptomic studies is identifying gene expression patterns correlating with disease progression. This is usually achieved by considering transcripts that independently pass an arbitrary threshold (e.g. p<0.05). In diseases involving severe perturbations of multiple molecular systems, such as Alzheimer's disease (AD), this univariate approach often results in a large list of seemingly unrelated transcripts. We utilised a powerful multivariate clustering approach to identify clusters of RNA biomarkers strongly associated with markers of AD progression. We discuss the value of considering pairs of transcripts which, in contrast to individual transcripts, helps avoid natural human transcriptome variation that can overshadow disease-related changes. Methodology/Principal Findings: We re-analysed a dataset of hippocampal transcript levels in nine controls and 22 patients with varying degrees of AD. A large-scale clustering approach determined groups of transcript probe sets that correlate strongly with measures of AD progression, including both clinical and neuropathological measures and quantifiers of the characteristic transcriptome shift from control to severe AD. This enabled identification of restricted groups of highly correlated probe sets from an initial list of 1,372 previously published by our group. We repeated this analysis on an expanded dataset that included all pair-wise combinations of the 1,372 probe sets. As clustering of this massive dataset is unfeasible using standard computational tools, we adapted and re-implemented a clustering algorithm that uses external memory algorithmic approach. This identified various pairs that strongly correlated with markers of AD progression and highlighted important biological pathways potentially involved in AD pathogenesis. Conclusions/Significance: Our analyses demonstrate that, although there exists a relatively large molecular signature of AD progression, only a small number of transcripts recurrently cluster with different markers of AD progression. Furthermore, considering the relationship between two transcripts can highlight important biological relationships that are missed when considering either transcript in isolation. © 2012 Arefin et al

Modeling storm water control operated by green roofs at the urban catchment scale

The urban catchment of Colle Ometti, in the town of Genoa, Italy, where storm water runoff is monitored for both quantity and quality, was selected as a test site for the hydrologic modelling of greening scenarios. Although no green roof installations are now present in the area, this study modelled \u2013 using extensive green roof details \u2013 the hydrologic effects of three hypothetical roof greenin scenarios at the catchment scale (conversion of 10%, 20%, and 100% impervious to green roofs). The modelling of green roof performances was undertaken using the EPA SWMM and was calibrated and validated on a small size green roof system completed in September 2007 in the laboratory of the Department of Civil, Environmental and Architectural Engineering (DICAT \u2013 University of Genoa). Precipitation scenarios were developed based on eighteen years of high resolution (one minute) rain gauge data in Genoa (1990-2007).Hydrologic modelling demonstrated that widespread green roof implementation can significantly reduce peak runoff rates and the lag time (7min and 15 min) runoff volume (detention effect) while after introducing the drying process operated by evapo-traspiration during the inter-event period the runoff volume reduction at the event scale (retention effect) can also be appreciated

Experiment K-6-03. Gravity and skeletal growth, part 1. Part 2: Morphology and histochemistry of bone cells and vasculature of the tibia; Part 3: Nuclear volume analysis of osteoblast histogenesis in periodontal ligament cells; Part 4: Intervertebral disc swelling pressure associated with microgravity

Bone area, bone electrophysiology, bone vascularity, osteoblast morphology, and osteoblast histogenesis were studied in rats associated with Cosmos 1887. The results suggest that the synchronous animals were the only group with a significantly larger bone area than the basal group, that the bone electrical potential was more negative in flight than in the synchronous rats, that the endosteal osteoblasts from flight rats had greater numbers of transitional Golgi vesicles but no difference in the large Golgi saccules or the alkaline phosphatase activity, that the perioteal vasculature in the shaft of flight rats often showed very dense intraluminal deposits with adjacent degenerating osteocytes as well as lipid accumulations within the lumen of the vessels and sometimes degeneration of the vascular wall (this change was not present in the metaphyseal region of flight animals), and that the progenitor cells decreased in flight rats while the preosteoblasts increased compared to controls. Many of the results suggest that the animals were beginning to recover from the effects of spaceflight during the two day interval between landing and euthanasia; flight effects, such as the vascular changes, did not appear to recover

Integrative medicine in the cancer setting: a new challenge for physicians and patients

In 2019, World Cancer Research Journal launched a new topic, dedicated to Complementary and alternative medicine (CAM), enjoying good scientific interest. The articles, published on this topic, highlights the concept and the importance of a new integrative medicine approach. According to the National Center Institute of USA for Complementary and Integrative Health (NCCIH), integrative medicine is an approach to medical care that combines traditional medicine (TM) with CAM practices, which have demonstrated safety and benefits as adjuncts to mainstream cancer care

Spatial and temporal variation of hydraulic conductivity and vegetation growth in green infrastructures using infiltrometer and visual technique

Hydraulic conductivity of a vegetated soil (i.e., mixed grass cover) is an important parameter governing the hydrological performance of green infrastructure (GI). This paper focuses on GI with mixed grass cover in the presence of trees. Due to shading effects (interception of radiant energy) of tree canopy, mixed grass cover in the vicinity of trees may not receive direct photosynthetically active radiation (PAR). This can hinder the growth rates resulting in the low grass cover (i.e., in density). The hydraulic conductivity and the performance of GI can be further affected. Several field studies were conducted to investigate hydraulic conductivity in different types of vegetated covers. However, any variation in growth and hydraulic conductivity of mixed grass cover in the vicinity of trees was rarely investigated. The objective of this study is to quantify spatial and temporal variation of vegetation growth and hydraulic conductivity in a mixed grass cover in the vicinity of a tree. Field monitoring of a mixed grass cover in the vicinity of a tree in a GI was conducted for about six months. Hydraulic conductivity tests were carried out using mini disk infiltrometer (MDI) at 149 locations in a selected site once every month. Vegetation density was quantified using image analysis and the images were captured by a DJI Phantom drone. The growth of mixed grass cover around tree vicinity (within 5 m radial distance) was found to be more uniform during months characterized by high rainfall depth. Spatial heterogeneity in both vegetation density and hydraulic conductivity is found to be more significant during a dry period than wet period. Variation of hydraulic conductivity with respect to the change in vegetation density is found to be significant in a wet period than dry period. It is also found that hydraulic conductivity is higher at the portions where shredded leaves are present. The obtained dynamic spatio-temporal relationship of soil, vegetation and atmospheric parameters can support the design of green infrastructures and contribute to a better understanding of the maintenance practices

Identification of a 5-Protein Biomarker Molecular Signature for Predicting Alzheimer's Disease

Background: Alzheimer’s disease (AD) is a progressive brain disease with a huge cost to human lives. The impact of the disease is also a growing concern for the governments of developing countries, in particular due to the increasingly high number of elderly citizens at risk. Alzheimer’s is the most common form of dementia, a common term for memory loss and other cognitive impairments. There is no current cure for AD, but there are drug and non-drug based approaches for its treatment. In general the drug-treatments are directed at slowing the progression of symptoms. They have proved to be effective in a large group of patients but success is directly correlated with identifying the disease carriers at its early stages. This justifies the need for timely and accurate forms of diagnosis via molecular means. We report here a 5-protein biomarker molecular signature that achieves, on average, a 96% total accuracy in predicting clinical AD. The signature is composed of the abundances of IL-1α, IL-3, EGF, TNF-α and G-CSF. Methodology/Principal Findings: Our results are based on a recent molecular dataset that has attracted worldwide attention. Our paper illustrates that improved results can be obtained with the abundance of only five proteins. Our methodology consisted of the application of an integrative data analysis method. This four step process included: a) abundance quantization, b) feature selection, c) literature analysis, d) selection of a classifier algorithm which is independent of the feature selection process. These steps were performed without using any sample of the test datasets. For the first two steps, we used the application of Fayyad and Irani’s discretization algorithm for selection and quantization, which in turn creates an instance of the (alpha-beta)-k-Feature Set problem; a numerical solution of this problem led to the selection of only 10 proteins. Conclusions/Significance: the previous study has provided an extremely useful dataset for the identification of A biomarkers. However, our subsequent analysis also revealed several important facts worth reporting: 1. A 5-protein signature (which is a subset of the 18-protein signature of Ray et al.) has the same overall performance (when using the same classifier). 2. Using more than 20 different classifiers available in the widely-used Weka software package, our 5- protein signature has, on average, a smaller prediction error indicating the independence of the classifier and the robustness of this set of biomarkers (i.e. 96% accuracy when predicting AD against non-demented control). 3. Using very simple classifiers, like Simple Logistic or Logistic Model Trees, we have achieved the following results on 92 samples: 100 percent success to predict Alzheimer’s Disease and 92 percent to predict Non Demented Control on the AD dataset

Toward a personalized therapy in soft-tissue sarcomas: State of the art and future directions

Soft-tissue sarcomas are rare tumors characterized by pathogenetic, morphological, and clinical intrinsic variability. Median survival of patients with advanced tumors are usually chemo-and radio-resistant, and standard treatments yield low response rates and poor survival results. The identification of defined genomic alterations in sarcoma could represent the premise for targeted treatments. Summarizing, soft-tissue sarcomas can be differentiated into histotypes with reciprocal chromosomal translocations, with defined oncogenic mutations and complex karyotypes. If the latter are improbably approached with targeted treatments, many suggest that innovative therapies interfering with the identified fusion oncoproteins and altered pathways could be potentially resolu-tive. In most cases, the characteristic genetic signature is discouragingly defined as “undruggable”, which poses a challenge for the development of novel pharmacological approaches. In this review, a summary of genomic alterations recognized in most common soft-tissue sarcoma is reported together with current and future therapeutic opportunities