Contra-Analysis: Prioritizing Meaningful Effect Size in Scientific Research

At every phase of scientific research, scientists must decide how to allocate limited resources to pursue the research inquiries with the greatest potential. This prioritization dictates which controlled interventions are studied, awarded funding, published, reproduced with repeated experiments, investigated in related contexts, and translated for societal use. There are many factors that influence this decision-making, but interventions with larger effect size are often favored because they exert the greatest influence on the system studied. To inform these decisions, scientists must compare effect size across studies with dissimilar experiment designs to identify the interventions with the largest effect. These studies are often only loosely related in nature, using experiments with a combination of different populations, conditions, timepoints, measurement techniques, and experiment models that measure the same phenomenon with a continuous variable. We name this assessment contra-analysis and propose to use credible intervals of the relative difference in means to compare effect size across studies in a meritocracy between competing interventions. We propose a data visualization, the contra plot, that allows scientists to score and rank effect size between studies that measure the same phenomenon, aid in determining an appropriate threshold for meaningful effect, and perform hypothesis tests to determine which interventions have meaningful effect size. We illustrate the use of contra plots with real biomedical research data. Contra-analysis promotes a practical interpretation of effect size and facilitates the prioritization of scientific research.Comment: 4 figures, 8000 word

A novel semisupervised support vector machine classifier based on active learning and context information

This paper proposes a novel semisupervised support vector machine classifier (Formula presented.) based on active learning (AL) and context information to solve the problem where the number of labeled samples is insufficient. Firstly, a new semisupervised learning method is designed using AL to select unlabeled samples as the semilabled samples, then the context information is exploited to further expand the selected samples and relabel them, along with the labeled samples train (Formula presented.) classifier. Next, a new query function is designed to enhance the reliability of the classification results by using the Euclidean distance between the samples. Finally, in order to enhance the robustness of the proposed algorithm, a fusion method is designed. Several experiments on change detection are performed by considering some real remote sensing images. The results show that the proposed algorithm in comparison with other algorithms can significantly improve the detection accuracy and achieve a fast convergence in addition to verify the effectiveness of the fusion method developed in this paper

Resibufogenin Targets the ATP1A1 Signaling Cascade to Induce G2/M Phase Arrest and Inhibit Invasion in Glioma

Resibufogenin (RB) is a major active ingredient in the traditional Chinese medicine Chansu and has garnered considerable attention for its efficacy in the treatment of cancer. However, the anticancer effects and underlying mechanisms of RB on glioblastoma (GBM) remain unknown. Here, we found that RB induced G2/M phase arrest and inhibited invasion in a primary GBM cell line, P3#GBM, and two GBM cell lines, U251 and A172. Subsequently, we demonstrated that RB-induced G2/M phase arrest occurred through downregulation of CDC25C and upregulation of p21, which was caused by activation of the MAPK/ERK pathway, and that RB inhibited GBM invasion by elevating intercellular Ca2+ to suppress the Src/FAK/Paxillin focal adhesion pathway. Intriguingly, we confirmed that upon RB binding to ATP1A1, Na+-K+-ATPase was activated as a receptor and then triggered the intracellular MAPK/ERK pathway and Ca2+-mediated Src/FAK/Paxillin focal adhesion pathway, which led to G2/M phase arrest and inhibited the invasion of GBM cells. Taken together, our findings reveal the antitumor mechanism of RB by targeting the ATP1A1 signaling cascade and two key signaling pathways and highlight the potential of RB as a new class of promising anticancer agents.publishedVersio

Valtrate, an iridoid compound in Valeriana, elicits anti-glioblastoma activity through inhibition of the PDGFRA/MEK/ERK signaling pathway

Background Valtrate, a natural compound isolated from the root of Valeriana, exhibits antitumor activity in many cancers through different mechanisms. However, its efficacy for the treatment of glioblastoma (GBM), a tumor type with a poor prognosis, has not yet been rigorously investigated. Methods GBM cell lines were treated with valtrate and CCK-8, colony formation and EdU assays, flow cytometry, and transwell, 3D tumor spheroid invasion and GBM-brain organoid co-culture invasion assays were performed to assess properties of proliferation, viability, apoptosis and invasion/migration. RNA sequencing analysis on valtrate-treated cells was performed to identify putative target genes underlying the antitumor activity of the drug in GBM cells. Western blot analysis, immunofluorescence and immunohistochemistry were performed to evaluate protein levels in valtrate-treated cell lines and in samples obtained from orthotopic xenografts. A specific activator of extracellular signal-regulated kinase (ERK) was used to identify the pathways mediating the effect. Results Valtrate significantly inhibited the proliferation of GBM cells in vitro by inducing mitochondrial apoptosis and suppressed invasion and migration of GBM cells by inhibiting levels of proteins associated with epithelial mesenchymal transition (EMT). RNA sequencing analysis of valtrate-treated GBM cells revealed platelet-derived growth factor receptor A (PDGFRA) as a potential target downregulated by the drug. Analysis of PDGFRA protein and downstream mediators demonstrated that valtrate inhibited PDGFRA/MEK/ERK signaling. Finally, treatment of tumor-bearing nude mice with valtrate led to decreased tumor volume (fivefold difference at day 28) and enhanced survival (day 27 vs day 36, control vs valtrate-treated) relative to controls. Conclusions Taken together, our study demonstrated that the natural product valtrate elicits antitumor activity in GBM cells through targeting PDGFRA and thus provides a candidate therapeutic compound for the treatment of GBM.publishedVersio

TRIM56 promotes malignant progression of glioblastoma by stabilizing cIAP1 protein

Background The tripartite motif (TRIM) family of proteins plays a key role in the developmental growth and therapeutic resistance of many tumors. However, the regulatory mechanisms and biological functions of TRIM proteins in human glioblastoma (GBM) are not yet fully understood. In this study, we focused on TRIM56, which emerged as the most differentially expressed TRIM family member with increased expression in GBM. Methods Western blot, real-time quantitative PCR (qRT-PCR), immunofluorescence (IF) and immunohistochemistry (IHC) were used to study the expression levels of TRIM56 and cIAP1 in GBM cell lines. Co-immunoprecipitation (co-IP) was used to explore the specific binding between target proteins and TRIM56. A xenograft animal model was used to verify the tumor promoting effect of TRIM56 on glioma in vivo. Results We observed elevated expression of TRIM56 in malignant gliomas and revealed that TRIM56 promoted glioma progression in vitro and in a GBM xenograft model in nude mice. Analysis of the Human Ubiquitin Array and co-IPs showed that cIAP1 is a protein downstream of TRIM56. TRIM56 deubiquitinated cIAP1, mainly through the zinc finger domain (amino acids 21–205) of TRIM56, thereby reducing the degradation of cIAP1 and thus increasing its expression. TRIM56 also showed prognostic significance in overall survival of glioma patients. Conclusions TRIM56-regulated post-translational modifications may contribute to glioma development through stabilization of cIAP1. Furthermore, TRIM56 may serve as a novel prognostic indicator and therapeutic molecular target for GBM.publishedVersio

Thiabendazole Inhibits Glioblastoma Cell Proliferation and Invasion Targeting Mini-chromosome Maintenance Protein 2

Thiabendazole (TBZ), approved by the US Food and Drug Administration (FDA) for human oral use, elicits a potential anticancer activity on cancer cells in vitro and in animal models. Here, we evaluated the efficacy of TBZ in the treatment of human glioblastoma multiforme (GBM). TBZ reduced the viability of GBM cells (P3, U251, LN229, A172, and U118MG) relative to controls in a dose- and time-dependent manner. However, normal human astrocytes (NHA) exhibited a greater IC50 than tumor cell lines and were thus more resistant to its cytotoxic effects. 5-Ethynyl-2′-deoxyuridine (EdU)-positive cells and the number of colonies formed were decreased in TBZ-treated cells (at 150 μM, P < 0.05 and at 150 μM, P < 0.001, respectively). This decrease in proliferation was associated with a G2/M arrest as assessed with flow cytometry, and the downregulation of G2/M check point proteins. In addition, TBZ suppressed GBM cell invasion. Analysis of RNA sequencing data comparing TBZ-treated cells with controls yielded a group of differentially expressed genes, the functions of which were associated with the cell cycle and DNA replication. The most significantly downregulated gene in TBZ-treated cells was mini-chromosome maintenance protein 2 (MCM2). SiRNA knockdown of MCM2 inhibited proliferation, causing a G2/M arrest in GBM cell lines and suppressed invasion. Taken together, our results demonstrated that TBZ inhibited proliferation and invasion in GBM cells through targeting of MCM2.publishedVersio

Loss of COPZ1 induces NCOA4 mediated autophagy and ferroptosis in glioblastoma cell lines

Dysregulated iron metabolism is a hallmark of many cancers, including glioblastoma (GBM). However, its role in tumor progression remains unclear. Herein, we identified coatomer protein complex subunit zeta 1 (COPZ1) as a therapeutic target candidate which significantly dysregulated iron metabolism in GBM cells. Overexpression of COPZ1 was associated with increasing tumor grade and poor prognosis in glioma patients based on analysis of expression data from the publicly available database The Cancer Genome Atlas (P < 0.001). Protein levels of COPZ1 were significantly increased in GBM compared to non-neoplastic brain tissue samples in immunohistochemistry and western blot analysis. SiRNA knockdown of COPZ1 suppressed proliferation of U87MG, U251 and P3#GBM in vitro. Stable expression of a COPZ1 shRNA construct in U87MG inhibited tumor growth in vivo by ~60% relative to controls at day 21 after implantation (P < 0.001). Kaplan–Meier analysis of the survival data demonstrated that the overall survival of tumor bearing animals increased from 20.8 days (control) to 27.8 days (knockdown, P < 0.05). COPZ1 knockdown also led to the increase in nuclear receptor coactivator 4 (NCOA4), resulting in the degradation of ferritin, and a subsequent increase in the intracellular levels of ferrous iron and ultimately ferroptosis. These data demonstrate that COPZ1 is a critical mediator in iron metabolism. The COPZ1/NCOA4/FTH1 axis is therefore a novel therapeutic target for the treatment of human GBM.publishedVersio

In Materia Neuron Spiking Plasticity for Sequential Event Processing Based on Dual-Mode Memristor

Artificial neurons are the fundamental elements in neuromorphic computing systems. Studies have revealed neuronal spike‐rate adaptation owing to intrinsic plasticity that neurons will adapt to the spiking patterns and store the events in the background spiking through clustered neuronal spiking. The event can be reactivated by specific retrieval clues instead of solely relying on synaptic plasticity. However, the neural adaptation, as well as the interactive adaptations of neuronal activity for information processing, have not been implemented. Herein, an artificial adaptive neuron via in materia modulation of the VO2/HfO2 based dual‐mode memristor is demonstrated. By changing the conductance of the HfO2 layer, the firing threshold can be modulated, thus the excitability and inhibition can be adjusted according to the previous stimuli without any complex peripherals, showing an adaptive firing rate even under the same stimuli. The artificial neuron clusters can emulate the concept of neuronal memory and neural adaptation, demonstrating spatiotemporal encoding capabilities via the correlated neural firing patterns. This conceptual work provides an alternative way to expand the computation power of spiking neural networks by exploiting the neural adaptation and could be enlightenment to maximize the synergy across both synapse and neuron in neuromorphic computing systems