A diabody that dissociates to monomer forms at low concentration: effects on binding activity and tumor targeting

2005 ◽  
Vol 327 (4) ◽  
pp. 999-1005 ◽  
Author(s):  
Bao-cheng Huang ◽  
Linda J. Foote ◽  
Trish K. Lankford ◽  
Sandra M. Davern ◽  
Cathy K. McKeown ◽  
...  
Keyword(s):  
Tumor Targeting ◽  
Binding Activity ◽  
Concentration Effects ◽  
Low Concentration

scholarly journals Identification of a New Peptide for Fibrosarcoma Tumor Targeting and Imaging In Vivo

2010 ◽  
Vol 2010 ◽  
pp. 1-10 ◽  
Author(s):  
Chia-Che Wu ◽  
Erh-Hsuan Lin ◽  
Yu-Ching Lee ◽  
Cheng-Jeng Tai ◽  
Tsu-Hsiang Kuo ◽  
...  
Keyword(s):  
Tumor Targeting ◽  
Therapeutic Agent ◽  
Phage Display Library ◽  
Binding Activity ◽  
Competition Assay ◽  
Lead Structure ◽  
Amino Acid Peptide ◽  
Normal Tissues ◽  
In Vivo Biodistribution

A 12-mer amino acid peptide SATTHYRLQAAN, denominated TK4, was isolated from a phage-display library with fibrosarcoma tumor-binding activity. In vivo biodistribution analysis of TK4-displaying phage showed a significant increased phage titer in implanted tumor up to 10-fold in comparison with normal tissues after systemic administration in mouse. Competition assay confirmed that the binding of TK4-phage to tumor cells depends on the TK4 peptide. Intravenous injection of131I-labeled synthetic TK4 peptide in mice showed a tumor retention of 3.3% and 2.7% ID/g at 1- and 4-hour postinjection, respectively. Tumor-to-muscle ratio was 1.1, 5.7, and 3.2 at 1-, 4-, and 24-hour, respectively, and tumors were imaged on a digital γ-camera at 4-hour postinjection. The present data suggest that TK4 holds promise as a lead structure for tumor targeting, and it could be further applied in the development of diagnostic or therapeutic agent.

scholarly journals Predicting low-concentration effects of pesticides

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Matthias Liess ◽  
Sebastian Henz ◽  
Saskia Knillmann
Keyword(s):  
Risk Assessment ◽  
Response Curve ◽  
Concentration Effect ◽  
Concentration Effects ◽  
Low Concentration ◽  
Effect Relationship ◽  
Human Risk ◽  
Low Concentrations ◽  
Random Variability ◽  
High Concentrations

Abstract We present a model to identify the effects of low toxicant concentrations. Due to inadequate models, such effects have so far often been misinterpreted as random variability. Instead, a tri-phasic relationship describes the effects of a toxicant when a broad range of concentrations is assessed: i) at high concentrations where substantial mortality occurs (LC50), we confirmed the traditional sigmoidal response curve (ii) at low concentrations about 10 times below the LC50, we identified higher survival than previously modelled, and (iii) at ultra-low concentrations starting at around 100 times below the LC50, higher mortality than previously modelled. This suggests that individuals benefit from low toxicant stress. Accordingly, we postulate that in the absence of external toxicant stress individuals are affected by an internal “System Stress” (SyS) and that SyS is reduced with increasing strength of toxicant stress. We show that the observed tri-phasic concentration-effect relationship can be modelled on the basis of this approach. Here we revealed that toxicant-related effects (LC5) occurred at remarkably low concentrations, 3 to 4 orders of magnitude below those concentrations inducing strong effects (LC50). Thus, the ECx-SyS model presented allows us to attribute ultra-low toxicant concentrations to their effects on individuals. This information will contribute to performing a more realistic environmental and human risk assessment.

Genomic analysis of C-type lectins

2002 ◽  
Vol 69 ◽  
pp. 59-72 ◽  
Author(s):  
Kurt Drickamer ◽  
Andrew J. Fadden
Keyword(s):  
Biological Effects ◽  
Cell Signalling ◽  
Genomic Analysis ◽  
Binding Activity ◽  
Immunoglobulin Superfamily ◽  
Carbohydrate Binding ◽  
Carbohydrate Recognition ◽  
Calcium Dependent ◽  
Binding Domains ◽  
Carbohydrate Recognition Domains

Many biological effects of complex carbohydrates are mediated by lectins that contain discrete carbohydrate-recognition domains. At least seven structurally distinct families of carbohydrate-recognition domains are found in lectins that are involved in intracellular trafficking, cell adhesion, cell–cell signalling, glycoprotein turnover and innate immunity. Genome-wide analysis of potential carbohydrate-binding domains is now possible. Two classes of intracellular lectins involved in glycoprotein trafficking are present in yeast, model invertebrates and vertebrates, and two other classes are present in vertebrates only. At the cell surface, calcium-dependent (C-type) lectins and galectins are found in model invertebrates and vertebrates, but not in yeast; immunoglobulin superfamily (I-type) lectins are only found in vertebrates. The evolutionary appearance of different classes of sugar-binding protein modules parallels a development towards more complex oligosaccharides that provide increased opportunities for specific recognition phenomena. An overall picture of the lectins present in humans can now be proposed. Based on our knowledge of the structures of several of the C-type carbohydrate-recognition domains, it is possible to suggest ligand-binding activity that may be associated with novel C-type lectin-like domains identified in a systematic screen of the human genome. Further analysis of the sequences of proteins containing these domains can be used as a basis for proposing potential biological functions.

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