CD105
- Known as:
- CD105
- Catalog number:
- 11-298-C025
- Product Quantity:
- 0.025 mg
- Category:
- -
- Supplier:
- Exbio
- Gene target:
- CD105
Related genes to: CD105
- Gene:
- ENG NIH gene
- Name:
- endoglin
- Previous symbol:
- ORW1, ORW
- Synonyms:
- END, HHT1, CD105
- Chromosome:
- 9q34.11
- Locus Type:
- gene with protein product
- Date approved:
- 1993-03-03
- Date modifiied:
- 2019-04-23
Related products to: CD105
Related articles to: CD105
- High protein concentrations often lead to high viscosity, necessitating reduced solution viscosity. We investigated the effects of eight anionic excipients commonly used in biopharmaceutical formulations on the solution viscosity of high-concentration monoclonal antibodies using three antibodies with different isoelectric points. The three antibodies exhibited attractive or repulsive protein-protein interaction tendencies in histidine buffer without anionic excipients. The effect of adding anionic excipients on solution viscosity differed by interaction tendencies. Preferential interaction coefficients revealed differences in the extent of interaction between individual anionic excipients and antibodies. Comparison with chloride, positioned in the middle of the Hofmeister series, suggested that the observed viscosity behavior could only be partially explained by the previously reported Hofmeister anion effects on solution viscosity. We examined the effects of combining L-arginine with each anionic excipient as a counter anion. Formulations containing L-arginine and other anionic excipients contributed more strongly to reducing solution viscosity than L-arginine hydrochloride. The effects of anionic excipients on viscosity can be understood in terms of protein-protein interactions of an antibody in the presence of anionic excipients; whether anionic excipients strengthen or weaken the intrinsic protein-protein interactions is important, underscoring the key indicator for selecting the optimal anionic excipients when designing high-concentration formulations with lower viscosities. - Source: PubMed
Publication date: 2026/09/19
Maruyama SouheiShibuya RisaTorisu TetsuoUchiyama Susumu - Pretreatment is a crucial stage in obtaining cellulose pulp from coconut residue. It helps in extracting lignin and hemicellulose, increasing the efficiency of the further process. This study proposed and developed a sequential pretreatment combining autohydrolysis, organosolv, and chemical bleaching to maximize the efficiency of extractive, hemicelluloses, and lignin removal. The aim was to explore and enhance the extraction of high-quality cellulose pulp derived from coconut residues for the production of carboxymethyl cellulose (CMC). Chemical and structural analysis was performed to confirm the efficiency of the proposed process. Chemical analysis confirmed the removal of lignin and hemicellulose, resulting in an enhancement of cellulose content from 40.01% to 78.92% FT-IR analyses confirmed modifications in the chemical structure of cellulose, while TGA revealed a significant mass loss in the cellulose-specific temperature range, demonstrating the efficient removal of other components. SEM images, in turn, provided microscopic visualizations that proved the successful preparation of CMC. The process resulted in a CMC yield of 30.75%, demonstrating its effectiveness in preparing cellulosic pulp suitable for CMC production, which stands out as a promising method for using coconut fibers in industry. - Source: PubMed
Publication date: 2026/09/19
Vieira FabríciaSantana Hortência E PBrazil Osiris Ashton VitalSilva Isabelly PereiraSilva Daniel PereiraRuzene Denise Santos - Chemotaxis, the capacity of cells and microorganisms to detect and respond to chemical gradients, is integral to various biological processes, including biofilm formation, environmental decontamination, pathogen identification, and targeted drug delivery. This study involved the fabrication of a Y-shaped microfluidic device to examine the chemotactic migration of Escherichia coli K12 DH5α toward gradient concentrations of alanine, an amino acid that serves as a potent chemoattractant for E. coli. The microfluidic device was designed and fabricated using standard photolithography and soft lithography techniques, and computational fluid dynamics (CFD) simulations were conducted using ANSYS Fluent to analyze the laminar flow behavior within the device. CFD simulations of phosphate-buffered saline (PBS) co-flow with 2 μm bacterial-sized particles predicted creeping, low-Reynolds-number laminar flow characterized by parallel, non-mixing streams, stable velocity profiles, and a smooth pressure drop of approximately 1.45 Pa toward the outlet. These results confirm the formation of a sharp interfacial boundary suitable for gradient-based chemotaxis assays. The chemotactic response of green fluorescent protein (GFP)-tagged E. coli was quantified by measuring fluorescence intensity in the central channel of the device. The results demonstrated that bacterial migration was dependent on alanine concentration, with maximum cell migration observed at 10 mM alanine. The bacteria exhibited motility perpendicular to the direction of streamlined laminar flow, migrating toward regions of higher alanine concentration. This study introduces a gradient-based Y-shaped microfluidic platform, validated through computational fluid dynamics (CFD), which integrates fluorescence-based quantification of GFP-tagged E. coli K12 DH5α chemotaxis. This platform facilitates real-time, reproducible, and concentration-dependent analysis of bacterial migration towards alanine under controlled laminar flow conditions. In contrast to traditional chemotaxis assays, it allows for precise chemical gradient generation, direct visualization of bacterial movement, and quantitative assessment of chemotactic responses within a single microfluidic system. The study provides both qualitative and quantitative insights into bacterial chemotaxis and highlights the potential of microfluidic platforms for real-time analysis of cellular behavior. The findings contribute to the advancement of rapid biosensing technologies and enhance the understanding of bacterial responses to chemical stimuli, with promising applications in biotechnology, microbiology, and environmental science. - Source: PubMed
Publication date: 2026/09/19
Yadav SnehlataKumari PoojaYadav VibhutiPaulraj SushmithaKumar AmiteshMahto Sanjeev Kumar - The existing kinetic models for autotrophic denitrification have limitations in explaining the reaction mechanism of composite filler systems and quantifying the dynamic effects of environmental factors. Therefore, the kinetic model, which explicitly couples the S hydrolysis, two-step denitrification process with environmental factor correction functions, was developed for the sulfur-boron mud autotrophic denitrification (SBMAD) system through batch experiments with varied filler ratios and environmental factors (pH, temperature) in this study. And the highest NO-N removal rate of 27.13 mg/(L·d) was achieved under optimal conditions. On this basis, the key parameters in the model were calibrated using batch experimental data of four groups with different initial NO-N concentrations and sulfur nitrogen ratios (20 and 200 mg/L NO-N with 2.8 S/NO-N, 50 and 150 mg/L NO-N with 2.2 S/NO-N), obtaining µ = 0.065 ± 0.017 d, and µ = 0.052 ± 0.113 d. The model was further validated using four independent experimental data. The results showed that it had reliable predictive performance under different conditions (TIC < 0.25, IoA > 0.91). Therefore, the kinetic model demonstrated reliable predictive performance for simulating the SBMAD process under the investigated batch conditions. - Source: PubMed
Publication date: 2026/09/19
Shao LixinFan LihuaBai YunSun YuZhao HangWang Dexi - Coronary diagnostic indices-fractional flow reserve (FFR) and coronary flow reserve (CFR)-disagree in up to 30% of cases, complicating diagnosis and revascularization decisions. Microvascular health likely drives this discordance, but its isolated effect is challenging to quantify in vivo and is often confounded by anatomical factors in computational studies. - Source: PubMed
Publication date: 2026/09/19
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