Individualized assignments, group work and discussions. How they interact with class size, low socioeconomic status, and second language learners

Varied teaching techniques are an important aspect of a successful classroom. Student and classroom factors such as ability level, lower socioeconomic status, and/or native language can interact with teaching techniques. Previous work suggests that each teaching technique may be more effective for different students or in different classroom situations, but few studies have directly examined which factors relate to effective teaching techniques. This study uses data for early secondary school students in Germany from the National Education Panel Study (NEPS) to examine the effects of group work, discussions, and individualized assignments on reading and math competency change between 7th and 9th grade. Additionally, we model the interactions of effects of class size, second language learners background, and lower socioeconomic status with these teaching techniques. We conclude that group work relates to more competency growth in math for second language learners, while classroom discussions relate to less growth for second language learners. Discussions relate to less growth in math competency for smaller classes and more growth in larger classes. Group work was also related to slower reading competency growth for children with a higher prior ability level. Findings are discussed in relation to existing theories of teaching techniques

Salmonella typhimurium Suppresses Tumor Growth via the Pro-Inflammatory Cytokine Interleukin-1 beta

Although strains of attenuated Salmonella typhimurium and wild-type Escherichia coli show similar tumor-targeting capacities, only S. typhimurium significantly suppresses tumor growth in mice. The aim of the present study was to examine bacteria-mediated immune responses by conducting comparative analyses of the cytokine profiles and immune cell populations within tumor tissues colonized by E. coli or attenuated Salmonellae. CT26 tumor-bearing mice were treated with two different bacterial strains: S. typhimurium defective in ppGpp synthesis (Delta ppGpp Salmonellae) or wild-type E. coli MG1655. Cytokine profiles and immune cell populations in tumor tissue colonized by these two bacterial strains were examined at two time points based on the pattern of tumor growth after Delta ppGpp Salmonellae treatment: 1) when tumor growth was suppressed ('suppression stage') and 2) when they began to re-grow ('re-growing stage'). The levels of IL-1 beta and TNF-alpha were markedly increased in tumors colonized by Delta ppGpp Salmonellae. This increase was associated with tumor regression; the levels of both IL-1 beta and TNF-alpha returned to normal level when the tumors started to re-grow. To identify the immune cells primarily responsible for Salmonellae-mediated tumor suppression, we examined the major cell types that produce IL-1 beta and TNF-alpha. We found that macrophages and dendritic cells were the main producers of TNF-alpha and IL-1 beta. Inhibiting IL-1 beta production in Salmonellae-treated mice restored tumor growth, whereas tumor growth was suppressed for longer by local administration of recombinant IL-1 beta or TNF-alpha in conjunction with Salmonella therapy. These findings suggested that IL-1 beta and TNF-alpha play important roles in Salmonella-mediated cancer therapy. A better understanding of host immune responses in Salmonella therapy may increase the success of a given drug, particularly when various strategies are combined with bacteriotherapy.111715Ysciescopu

Phage Displayed Short Peptides against Cells of Candida albicans Demonstrate Presence of Species, Morphology and Region Specific Carbohydrate Epitopes

Candida albicans is a commensal opportunistic pathogen, which can cause superficial infections as well as systemic infections in immuocompromised hosts. Among nosocomial fungal infections, infections by C. albicans are associated with highest mortality rates even though incidence of infections by other related species is on the rise world over. Since C. albicans and other Candida species differ in their susceptibility to antifungal drug treatment, it is crucial to accurately identify the species for effective drug treatment. Most diagnostic tests that differentiate between C. albicans and other Candida species are time consuming, as they necessarily involve laboratory culturing. Others, which employ highly sensitive PCR based technologies often, yield false positives which is equally dangerous since that leads to unnecessary antifungal treatment. This is the first report of phage display technology based identification of short peptide sequences that can distinguish C. albicans from other closely related species. The peptides also show high degree of specificity towards its different morphological forms. Using fluorescence microscopy, we show that the peptides bind on the surface of these cells and obtained clones that could even specifically bind to only specific regions of cells indicating restricted distribution of the epitopes. What was peculiar and interesting was that the epitopes were carbohydrate in nature. This gives insight into the complexity of the carbohydrate composition of fungal cell walls. In an ELISA format these peptides allow specific detection of relatively small numbers of C. albicans cells. Hence, if used in combination, such a test could help accurate diagnosis and allow physicians to initiate appropriate drug therapy on time

DNA Display Selection of Peptide Ligands for a Full-Length Human G Protein-Coupled Receptor on CHO-K1 Cells

The G protein-coupled receptors (GPCRs), which form the largest group of transmembrane proteins involved in signal transduction, are major targets of currently available drugs. Thus, the search for cognate and surrogate peptide ligands for GPCRs is of both basic and therapeutic interest. Here we describe the application of an in vitro DNA display technology to screening libraries of peptide ligands for full-length GPCRs expressed on whole cells. We used human angiotensin II (Ang II) type-1 receptor (hAT1R) as a model GPCR. Under improved selection conditions using hAT1R-expressing Chinese hamster ovary (CHO)-K1 cells as bait, we confirmed that Ang II gene could be enriched more than 10,000-fold after four rounds of selection. Further, we successfully selected diverse Ang II-like peptides from randomized peptide libraries. The results provide more precise information on the sequence-function relationships of hAT1R ligands than can be obtained by conventional alanine-scanning mutagenesis. Completely in vitro DNA display can overcome the limitations of current display technologies and is expected to prove widely useful for screening diverse libraries of mutant peptide and protein ligands for receptors that can be expressed functionally on the surface of CHO-K1 cells

Identifying Drug Effects via Pathway Alterations using an Integer Linear Programming Optimization Formulation on Phosphoproteomic Data

Understanding the mechanisms of cell function and drug action is a major endeavor in the pharmaceutical industry. Drug effects are governed by the intrinsic properties of the drug (i.e., selectivity and potency) and the specific signaling transduction network of the host (i.e., normal vs. diseased cells). Here, we describe an unbiased, phosphoproteomicbased approach to identify drug effects by monitoring drug-induced topology alterations. With the proposed method, drug effects are investigated under several conditions on a cell-type specific signaling network. First, starting with a generic pathway made of logical gates, we build a cell-type specific map by constraining it to fit 13 key phopshoprotein signals under 55 experimental cases. Fitting is performed via a formulation as an Integer Linear Program (ILP) and solution by standard ILP solvers; a procedure that drastically outperforms previous fitting schemes. Then, knowing the cell topology, we monitor the same key phopshoprotein signals under the presence of drug and cytokines and we re-optimize the specific map to reveal the drug-induced topology alterations. To prove our case, we make a pathway map for the hepatocytic cell line HepG2 and we evaluate the effects of 4 drugs: 3 selective inhibitors for the Epidermal Growth Factor Receptor (EGFR) and a non selective drug. We confirm effects easily predictable from the drugs’ main target (i.e. EGFR inhibitors blocks the EGFR pathway) but we also uncover unanticipated effects due to either drug promiscuity or the cell’s specific topology. An interesting finding is that the selective EGFR inhibitor Gefitinib is able to inhibit signaling downstream the Interleukin-1alpha (IL-1α) pathway; an effect that cannot be extracted from binding affinity based approaches. Our method represents an unbiased approach to identify drug effects on a small to medium size pathways and is scalable to larger topologies with any type of signaling perturbations (small molecules, 3 RNAi etc). The method is a step towards a better picture of drug effects in pathways, the cornerstone in identifying the mechanisms of drug efficacy and toxicity

The Use of Phage-Displayed Peptide Libraries to Develop Tumor-Targeting Drugs

Monoclonal antibodies have been successfully utilized as cancer-targeting therapeutics and diagnostics, but the efficacies of these treatments are limited in part by the size of the molecules and non-specific uptake by the reticuloendothelial system. Peptides are much smaller molecules that can specifically target cancer cells and as such may alleviate complications with antibody therapy. Although many endogenous and exogenous peptides have been developed into clinical therapeutics, only a subset of these consists of cancer-targeting peptides. Combinatorial biological libraries such as bacteriophage-displayed peptide libraries are a resource of potential ligands for various cancer-related molecular targets. Target-binding peptides can be affinity selected from complex mixtures of billions of displayed peptides on phage and further enriched through the biopanning process. Various cancer-specific ligands have been isolated by in vitro, in vivo, and ex vivo screening methods. As several peptides derived from phage-displayed peptide library screenings have been developed into therapeutics in current clinical trials, which validates peptide-targeting potential, the use of phage display to identify cancer-targeting therapeutics should be further exploited

A comprehensive analysis of filamentous phage display vectors for cytoplasmic proteins: an analysis with different fluorescent proteins

Filamentous phage display has been extensively used to select proteins with binding properties of specific interest. Although many different display platforms using filamentous phage have been described, no comprehensive comparison of their abilities to display similar proteins has been conducted. This is particularly important for the display of cytoplasmic proteins, which are often poorly displayed with standard filamentous phage vectors. In this article, we have analyzed the ability of filamentous phage to display a stable form of green fluorescent protein and modified variants in nine different display vectors, a number of which have been previously proposed as being suitable for cytoplasmic protein display. Correct folding and display were assessed by phagemid particle fluorescence, and with anti-GFP antibodies. The poor correlation between phagemid particle fluorescence and recognition of GFP by antibodies, indicates that proteins may fold correctly without being accessible for display. The best vector used a twin arginine transporter leader to transport the displayed protein to the periplasm, and a coil-coil arrangement to link the displayed protein to g3p. This vector was able to display less robust forms of GFP, including ones with inserted epitopes, as well as fluorescent proteins of the Azami green series. It was also functional in mock selection experiments

PERSONALIZED IMMUNE DIAGNOSTICS: EPITOPE MAPPING OF THE IMMUNOME

Statistical phage display is a highly complex, but rapid and efficient way to identify “binding peptides” from a unique and specially designed library. It avoids repeated selection rounds and can therefore provide much more complex data than just a few sequences usually obtained with repeated peptide library selection. The complexity of the data analyzed is sufficient to cover hundreds of potential binder/target combinations in parallel.Applying this novel way to generate and analyze data from peptide phage display with antibodies allows to predict potential epitopes at amino acid resolution. Fingerprinting of monoclonal antibodies reveals the large variety of peptides binding to any given antibody. Independent of such laborious and failure prone methods like peptide arrays or phage display with antigen gene fragments. Surprisingly easy this can explain the specificity of antibodies and it is a valuable tool for antibody quality control.Beyond the application to individual antibodies we are able to analyze the immunome of patient sera. Theoretically, there are hundreds of antibody molecules for each recently encountered antigen epitope in a few µl. This is enough to define individual antibody epitopes. Since a single patient sample allows to record the entire immunome data, there is a tremendous amount of information hidden in the data sets we obtain. Nevertheless, all patients show different epitope patterns and for the generation of diagnostic tools we must compare many different sera. Results from examples will be given for allergic disease, viral infection diagnostics and the vaccine imprint on the immunome of one individual patient history.In infectious disease diagnostics (e.g. EBV, COVID-19, influenza) epitope-based kits can provide a robust analysis of existing and past disease as well as effective monitoring of vaccine efficacy. The aspect that the immune system carries the memories of antigens at least for many months allows a complex analysis even identifying different viral strains in a single experiment.In allergic disease we carried out epitope mapping with hundreds of sera from patients with sensibilization to allergenic food ingredients. Predicted epitopes were validated by binding IgE and IgG from many more patient sera for the main food allergy agents. Since peptide epitope diagnostics do not suffer from the undefined cross reactivities of present methods, we are gathering now a rather different understanding of what food allergies really are. In particular, we can also use IgG measurement based on immunoassays with epitopes, which has been regarded as impossible.Presently we are extending our work also in auto-immune diseases connected to long-COVID and psychiatric diseases