Investigation of Breakthrough Curves of Citric Acid Adsorption

In this paper, experimental breakthrough curves for citric acid adsorption from aqueous solution onto ion-exchange resin at 20, 35, 55 °C have been obtained by some weak and strong basic anionic resins, such as IRA-92, IRA-93, IRA-420 and IRA-458. The results show that amberlite IRA-93 has good performance and is one of the best resins in the process of citric acid recovery from aqueous solution. Also, the temperature effect study shows that an increase in temperature causes an increase in diffusion coefficient of particles, but the saturation capacity of resin decreases. To achieve an appropriate model, three mathematical models were analyzed to predict system properties based on statistical tests, and finally, the appropriate model was determined. To examine model capability, mathematical equations have been implemented in various breakthrough curve data obtained by other investigators, and the results show appropriate conformity

Hypermethylation of Tumor Suppressor Genes Involved in Critical Regulatory Pathways for Developing a Blood-Based Test in Breast Cancer

Aberrant DNA methylation patterns might be used as a biomarker for diagnosis and management of cancer patients

Splenic red pulp macrophages provide a niche for CML stem cells and induce therapy resistance.

Disease progression and relapse of chronic myeloid leukemia (CML) are caused by therapy resistant leukemia stem cells (LSCs), and cure relies on their eradication. The microenvironment in the bone marrow (BM) is known to contribute to LSC maintenance and resistance. Although leukemic infiltration of the spleen is a hallmark of CML, it is unknown whether spleen cells form a niche that maintains LSCs. Here, we demonstrate that LSCs preferentially accumulate in the spleen and contribute to disease progression. Spleen LSCs were located in the red pulp close to red pulp macrophages (RPM) in CML patients and in a murine CML model. Pharmacologic and genetic depletion of RPM reduced LSCs and decreased their cell cycling activity in the spleen. Gene expression analysis revealed enriched stemness and decreased myeloid lineage differentiation in spleen leukemic stem and progenitor cells (LSPCs). These results demonstrate that splenic RPM form a niche that maintains CML LSCs in a quiescent state, resulting in disease progression and resistance to therapy

Splenic red pulp macrophages provide a niche for CML stem cells and induce therapy resistance

Disease progression and relapse of chronic myeloid leukemia (CML) are caused by therapy resistant leukemia stem cells (LSCs), and cure relies on their eradication. The microenvironment in the bone marrow (BM) is known to contribute to LSC maintenance and resistance. Although leukemic infiltration of the spleen is a hallmark of CML, it is unknown whether spleen cells form a niche that maintains LSCs. Here, we demonstrate that LSCs preferentially accumulate in the spleen and contribute to disease progression. Spleen LSCs were located in the red pulp close to red pulp macrophages (RPM) in CML patients and in a murine CML model. Pharmacologic and genetic depletion of RPM reduced LSCs and decreased their cell cycling activity in the spleen. Gene expression analysis revealed enriched stemness and decreased myeloid lineage differentiation in spleen leukemic stem and progenitor cells (LSPCs). These results demonstrate that splenic RPM form a niche that maintains CML LSCs in a quiescent state, resulting in disease progression and resistance to therapy

Detector Fabrication Yield for SuperCDMS Soudan

The SuperCDMS collaboration is presently operating a 9 kg Ge payload at the Soudan Underground Laboratory in their direct search for dark matter. The Ge detectors utilize double-sided athermal phonon sensors with an interdigitated electrode structure (iZIPs) to reject near-surface electron-recoil events. These detectors each have a mass of 0.6 kg and were fabricated with photolithographic techniques. The detector fabrication advances required and the production yield encountered are described.United States. Dept. of EnergyNational Science Foundation (U.S.

Do Two Machine-Learning Based Prognostic Signatures for Breast Cancer Capture the Same Biological Processes?

The fact that there is very little if any overlap between the genes of different prognostic signatures for early-discovery breast cancer is well documented. The reasons for this apparent discrepancy have been explained by the limits of simple machine-learning identification and ranking techniques, and the biological relevance and meaning of the prognostic gene lists was questioned. Subsequently, proponents of the prognostic gene lists claimed that different lists do capture similar underlying biological processes and pathways. The present study places under scrutiny the validity of this claim, for two important gene lists that are at the focus of current large-scale validation efforts. We performed careful enrichment analysis, controlling the effects of multiple testing in a manner which takes into account the nested dependent structure of gene ontologies. In contradiction to several previous publications, we find that the only biological process or pathway for which statistically significant concordance can be claimed is cell proliferation, a process whose relevance and prognostic value was well known long before gene expression profiling. We found that the claims reported by others, of wider concordance between the biological processes captured by the two prognostic signatures studied, were found either to be lacking statistical rigor or were in fact based on addressing some other question

Phenomenological models of synaptic plasticity based on spike timing

Synaptic plasticity is considered to be the biological substrate of learning and memory. In this document we review phenomenological models of short-term and long-term synaptic plasticity, in particular spike-timing dependent plasticity (STDP). The aim of the document is to provide a framework for classifying and evaluating different models of plasticity. We focus on phenomenological synaptic models that are compatible with integrate-and-fire type neuron models where each neuron is described by a small number of variables. This implies that synaptic update rules for short-term or long-term plasticity can only depend on spike timing and, potentially, on membrane potential, as well as on the value of the synaptic weight, or on low-pass filtered (temporally averaged) versions of the above variables. We examine the ability of the models to account for experimental data and to fulfill expectations derived from theoretical considerations. We further discuss their relations to teacher-based rules (supervised learning) and reward-based rules (reinforcement learning). All models discussed in this paper are suitable for large-scale network simulations

The potential of antisense oligonucleotide therapies for inherited childhood lung diseases.

Antisense oligonucleotides are an emerging therapeutic option to treat diseases with known genetic origin. In the age of personalised medicines, antisense oligonucleotides can sometimes be designed to target and bypass or overcome a patient's genetic mutation, in particular those lesions that compromise normal pre-mRNA processing. Antisense oligonucleotides can alter gene expression through a variety of mechanisms as determined by the chemistry and antisense oligomer design. Through targeting the pre-mRNA, antisense oligonucleotides can alter splicing and induce a specific spliceoform or disrupt the reading frame, target an RNA transcript for degradation through RNaseH activation, block ribosome initiation of protein translation or disrupt miRNA function. The recent accelerated approval of eteplirsen (renamed Exondys 51™) by the Food and Drug Administration, for the treatment of Duchenne muscular dystrophy, and nusinersen, for the treatment of spinal muscular atrophy, herald a new and exciting era in splice-switching antisense oligonucleotide applications to treat inherited diseases. This review considers the potential of antisense oligonucleotides to treat inherited lung diseases of childhood with a focus on cystic fibrosis and disorders of surfactant protein metabolism

Demonstration of surface electron rejection with interleaved germanium detectors for dark matter searches

The SuperCDMS experiment in the Soudan Underground Laboratory searches for dark matter with a 9-kg array of cryogenic germanium detectors. Symmetric sensors on opposite sides measure both charge and phonons from each particle interaction, providing excellent discrimination between electron and nuclear recoils, and between surface and interior events. Surface event rejection capabilities were tested with two 210 Pb sources producing ∼130 beta decays/hr. In ∼800 live hours, no events leaked into the 8–115 keV signal region, giving upper limit leakage fraction 1.7 × 10−5 at 90% C.L., corresponding to < 0.6 surface event background in the future 200-kg SuperCDMS SNOLAB experiment

The evidence base for circulating tumour DNA blood-based biomarkers for the early detection of cancer: a systematic mapping review

Background: The presence of circulating cell-free DNA from tumours in blood (ctDNA) is of major importance to those interested in early cancer detection, as well as to those wishing to monitor tumour progression or diagnose the presence of activating mutations to guide treatment. In 2014, the UK Early Cancer Detection Consortium undertook a systematic mapping review of the literature to identify blood-based biomarkers with potential for the development of a non-invasive blood test for cancer screening, and which identified this as a major area of interest. This review builds on the mapping review to expand the ctDNA dataset to examine the best options for the detection of multiple cancer types. Methods: The original mapping review was based on comprehensive searches of the electronic databases Medline, Embase, CINAHL, the Cochrane library, and Biosis to obtain relevant literature on blood-based biomarkers for cancer detection in humans (PROSPERO no. CRD42014010827). The abstracts for each paper were reviewed to determine whether validation data were reported, and then examined in full. Publications concentrating on monitoring of disease burden or mutations were excluded. Results: The search identified 94 ctDNA studies meeting the criteria for review. All but 5 studies examined one cancer type, with breast, colorectal and lung cancers representing 60% of studies. The size and design of the studies varied widely. Controls were included in 77% of publications. The largest study included 640 patients, but the median study size was 65 cases and 35 controls, and the bulk of studies (71%) included less than 100 patients. Studies either estimated cfDNA levels non-specifically or tested for cancer-specific mutations or methylation changes (the majority using PCR-based methods). Conclusion: We have systematically reviewed ctDNA blood biomarkers for the early detection of cancer. Pre-analytical, analytical, and post-analytical considerations were identified which need to be addressed before such biomarkers enter clinical practice. The value of small studies with no comparison between methods, or even the inclusion of controls is highly questionable, and larger validation studies will be required before such methods can be considered for early cancer detection