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4,4'-dibenzamido-2,2'-stilbenedisulfonic acid

4,4'-dibenzamido-2,2'-stilbenedisulfonic acid is a chemical compound used in various research applications.
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Most cited protocols related to «4,4'-dibenzamido-2,2'-stilbenedisulfonic acid»

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Publication 2014
4,4'-dibenzamido-2,2'-stilbenedisulfonic acid Amino Acid Sequence Clone Cells Cloning Vectors DNA Replication Escherichia coli Eukaryota Genome Oligonucleotide Primers Plasmids Proteins Proteome
We used a pipeline comprising several packages to annotate identified TFs. Domain structure and GO annotation were predicted by InterProScan (version 4.8) (23 (link)). Cross-links to well-known resources were assigned to the best BLAST hits with maximal e-value 1e-10. Nuclear localization signals were predicted by PredictNLS (24 (link)). Other information such as expert-curated description, expression, regulation, conserved elements and references was collected from corresponding databases. Multiple sequence alignments (MSAs) for DBDs were constructed by HMM-guided method, and MSAs for full-length protein sequences were inferred by T-coffee (version 9.03) (25 (link)). Family trees across 83 species were inferred by FastTree (version 2.1.3) (26 (link)) with 100 resamplings. Family trees within each species were inferred by MrBayes (version 3.2.1) (27 (link)) based on the Dayhoff model for 50 000 generations. The Help page (http://planttfdb.cbi.pku.edu.cn/help_info.php#tfinfo) describes more detailed information on datasets and parameter settings.
Publication 2013
4,4'-dibenzamido-2,2'-stilbenedisulfonic acid Amino Acid Sequence Coffee Nuclear Localization Signals Sequence Alignment
MFG is a 16-week service delivery model that was guided by a manualized protocol. Each group met weekly for approximately a 90- to 120-min/session and included six to eight families, composed of identified youth, their adult caregiver(s), and sibling(s) between the ages of 6 and 18. As a foundation, MFG takes a common elements approach by identifying essential components from the empirical literature from BPT methods (e.g., Chorpita & Daleiden, 2009 (link); Garland et al., 2008 (link)) and family therapy (e.g., Alexander, Pugh, Parsons, & Sexton, 2000 ; Keiley, 2002 (link)) regarding core effective practices for treating DBDs, represented as the “4Rs” (i.e., Rules, Responsibility, Relationships, Respectful Communication) and factors related to family engagement in mental health services, represented as “2Ss” (Stress and Social Support). Core components of BPT included in MFG were positive reinforcement (i.e., labeled praise, positive attending, tangible reinforcement/ rewards), which was incorporated into sessions focused on “relationships”; limit setting (i.e., monitoring, effective commands, response-cost; behavioral contracting/goal setting), which was mainly incorporated into sessions focused on “rules” and “responsibility”; psychoeducation and affect education (i.e., learning about, identifying, and labeling stress-related emotions and behavior; developing methods to address common triggers for stress), which was incorporated into sessions focused on “stress.”
Core components of family therapy included in MFG were role identification (i.e., understanding the unique and integrated role each member plays in a family and supporting how family members can support each other in achieving desired family outcomes), which was incorporated into sessions focused on “relationships”; reframing (i.e., developing new strategies to regulate emotions and interactions between family members), which was incorporated into sessions focused on “relationships” and “respectful communication”; communication training (i.e., identifying behaviors [e.g., eye contact] that demonstrate engaging in a conversation, using “I” statements to express needs/wants, utilizing congruent affect and speech when communicating, etc.), which was incorporated into sessions focused on “relationships” and “respectful communication.” Methods to improve within-family and external sources of emotional, tangible, informational, and companionship social supports (e.g., Chacko et al., 2009 (link)) were incorporated into the session focused on “social support.” Lastly, given the high-risk nature of the population for poor engagement to treatment, core aspects of evidence-based engagement practices (e.g., aligning expectations for treatment with anticipated treatment benefits, reducing stigma related to receipt of mental health services, etc.; McKay & Bannon, 2004 (link)) were also integrated into the MFG program.
Core MFG sessions focused on one of the 4Rs and 2Ss and proceeded with the following processes: (a) creating social networks, (b) information exchange/homework review, (c) group discussion regarding the skill, (d) individual family practice, and (e) homework assignment. MFG content areas (4Rs and 2Ss) were integrated into the program during the first (Sessions 1–8) and the second (Sessions 9–16) halves of MFG to provide opportunities for repeated exposure and practice with content.
Participants in the MFG condition were not prohibited from utilizing any additional services available to them through the outpatient mental health clinic where they were receiving MFG. In this sample, 53% of the participants in the MFG condition did not receive additional interventions. Those 47% of youth who did receive additional services also received outpatient individual services (49%), outpatient medication management (34%), school-based mental health (9%), case management (<1%), and crisis management services (<1%) during the course of the 4-month MFG group. Moreover, for those youth who received additional services beyond receipt of MFG, the majority of youth received one (53%), two (40%), or three (7%) additional services. No youth received more than three additional mental health services.
Publication 2014
4,4'-dibenzamido-2,2'-stilbenedisulfonic acid Adult Case Management Emotions Family Member Health Services, Outpatient Mental Health Mental Health Services Obstetric Delivery Outpatients Pharmaceutical Preparations Population at Risk Positive Reinforcement Precipitating Factors Reinforcement, Psychological Speech Therapies, Family Youth
We refined the TF prediction pipeline by updating the hidden Markov model (HMM) profiles of TF DBDs and adjusting the TF family assignment rules. The latest HMM profiles for most DBDs were downloaded from Pfam version 27.0 (28 (link)). For the remaining domains without available Pfam HMM profiles, we rebuilt the HMM profiles using the sequences in representative species (human, mouse, zebrafish and fly). To predict TFs, we applied the hmmsearch program in HMMER 3.0 (30 (link)) to search all the protein sequences in each species against the HMM profiles with E-value 0.0001 as the cutoff. Then we assigned the TFs into different families according to the above family assignment rules.
Publication 2014
4,4'-dibenzamido-2,2'-stilbenedisulfonic acid Amino Acid Sequence Homo sapiens Mice, House Zebrafish

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Publication 2014
2',5'-oligoadenylate 4,4'-dibenzamido-2,2'-stilbenedisulfonic acid Amber Biological Evolution Cell Lines Centrifugation Chromatography, Affinity Circular Dichroism Crystallography DNA, Complementary DNA, Double-Stranded DNA Replication Escherichia coli Fluorescence Polarization Genes Hydrochloride, Guanidine Luciferases Luciferases, Firefly Mutagenesis Mutation Peptides Protein Dimerization Proteins RELA protein, human Steroids

Most recents protocols related to «4,4'-dibenzamido-2,2'-stilbenedisulfonic acid»

To probe the large-scale functional motions of the modeled hRPA and its dynamics and flexibility, we performed the Normal Mode Analysis (NMA). For NMA analysis, the initial structure of the protein was selected after discarding the initial few steps at ϵinter value of 0.3 kcal/mol and 1.0 kcal/mol. Here, we used the coarse-grained structure of ssDNA binding core domains only (domains A-E). To perform the NMA analysis and produce the visualizations of the data, the Bio3D package in R was used [74 (link)]. A variety of functions from the Bio3D package were employed. Some of them are nma.pdbs(), dccm.nma(), and pymol(). The function nma.pdbs() was used to calculate the normal modes and produce an NMA object for visualization. dccm.nma() function was used to calculate the cross-correlation between DBDs. This function utilizes the normal mode analysis of a protein structure to calculate a cross-correlation matrix with elements Cij. Graphically, it is represented by dynamic cross-correlation map (DCCM). The Cij value corresponds to the fluctuations of residues i and j and denotes if they are correlated, anti-correlated or uncorrelated. For example, Cij = 1 signifies their fluctuations are completely correlated, whereas, a completely anti-correlated fluctuations of two interacting beads is represented by Cij = -1. Cij = 0 indicates that the fluctuations of two beads are not correlated. The Bio3D package also allows the visualization of the normal modes either through a vector field representation or trajectory file in PyMol using the Bio3D inbuilt function, pymol(). With this function, three-dimensional visualization of the protein is obtained and it highlights the domain dynamics in the hRPA molecule. The total number of modes generated were 2055 including the first 6 modes with zero frequency (trivial modes). These trivial modes correspond to the rotational and translational modes. For comparison between the normal modes of the protein in apo hRPA and bound hRPA conformations obtained from MD simulation trajectory (where binding is complete), we calculated the root-mean-square inner product (RMSIP) of the normal modes obtained from normal mode analysis of both conformations. These calculations were performed to facilitate a direct comparison of the flexibility patterns between protein structures. To determine which normal modes contribute to the observed conformational changes in hRPA protein from our MD simulation trajectory, the squared overlap analysis was carried out. Here, the squared overlap of the first 20 modes was calculated, with the conformational difference vector between the first (after discarding the initial 104 steps) and last frames (the bound hRPA-ssDNA conformation) of our MD trajectories. The trajectory of MD simulation consists of the unbiased binding simulation of hRPA and ssDNA to achieve the final bound complex of ssDNA and hRPA (bound state) starting from both molecules in solution (unbound state). All these calculations were performed using the Bio3D package in R [74 (link)–76 (link)].
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Publication 2023
4,4'-dibenzamido-2,2'-stilbenedisulfonic acid Cloning Vectors DNA, Single-Stranded Molecular Dynamics Plant Roots Protein Biosynthesis Proteins Reading Frames Staphylococcal Protein A
According to previously reported procedures by our group (Luo et al. 2021 (link)), we prepared the ethanol extract. The air-dried and finely powdered roots (10 kg) of D. trilobus were macerated in 95% ethanol (3 × 60 L) for 48 h at room temperature. After filtering and evaporating the extract to remove ethanol, the remaining dark brown residue was retained (1.15 kg). DB (33.4 g, yield: 2.9%, m.p. 252–253 °C) was isolated from the D. trilobus extract by recrystallization (methanol). DB (20 g) was dissolved in methanol at room temperature followed by addition of 2 equiv. of NaOH for the production of DBDS. After NaOH was dissolved completely, the solution was concentrated under reduced pressure to provide the desired product DBDS (20.1 g, yield: 94.3%). The 1H and 13C NMR spectra of DB and DBDS were shown in Supplementary material.
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Publication 2023
4,4'-dibenzamido-2,2'-stilbenedisulfonic acid Carbon-13 Magnetic Resonance Spectroscopy Ethanol Methanol Plant Roots Pressure
The test was performed as described by Ayumi et al. (2020 (link)). Female mice were randomly divided into twelve groups (n = 6), each group was pretreated with vehicle (distilled water), MOP (1 mg/kg, positive control), IND (10 mg/kg, positive control), ASA (100 mg/kg, positive control), DB (2.5, 5, 10, and 20 mg/kg), and DBDS (2.5, 5, 10, and 20 mg/kg) by oral or intraperitoneal administration, respectively, 1 h before the formalin injection. 2.5% Formalin (20 μL) was injected in the plantar surface of the right hind paw. The indicator of pain was evaluated as the time spent licking paw. It was recorded from 0 to 5 min (early phase) and from 15 to 30 min (late phase) after the injection of formalin. Among the tests in the absence and presence of NAL, i.p. injection of NAL (5 mg/kg) was performed 10 min before administration of testing compounds.
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Publication 2023
4,4'-dibenzamido-2,2'-stilbenedisulfonic acid Females Formalin Injections, Intraperitoneal Mice, House Pain
A modified method, according to previous report by Banskota et al. (2003 (link)), was employed for the evaluation of inhibitory effect of test compounds on nitric oxide (NO) production in RAW264.7 cells. Briefly, the logarithmic phase cells were seeded in 96-well plates with 1 × 105 cells/well (volume of the well is 100 μL). Under a humidified atmosphere (5% CO2, 37 °C), the cells were cultured for 24 h. Subsequently, 50 μL of lipopolysaccharide (LPS, 1 μg/L) was added to each well and continued to culture these cells under the same environment for an additional 1 h. Next, 50 μL of different concentrations of DBDS (0.63, 2.5, 10, and 40 µmol/L) and L-NMMA (positive control, 25 µmol/L) were added to each well and cells were continued to be cultured under the same environment for an additional 24 h, and three repeated wells were set at each concentration. NO production was determined by measuring the accumulation of nitrite in the supernatant of culture medium using the Griess reagent. Inhibition (%) was calculated using the following equation:
inhibition (%)= A  BA  C ×100
A: NO concentration of LPS-treated group; B: NO concentration of sample-treated group; C: NO concentration of control group.
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Publication 2023
4,4'-dibenzamido-2,2'-stilbenedisulfonic acid Atmosphere Cells Culture Media Griess reagent Nitrites omega-N-Methylarginine Oxide, Nitric Psychological Inhibition RAW 264.7 Cells
The MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) colorimetric method was used to determine cytotoxicity of DBDS. The logarithmic phase cells were seeded in 96-well plates with 1 × 105 cells/well (volume of the well is 100 μL). Under a humidified atmosphere (5% CO2, 37 °C), the cells were cultured for 24 h following treatment with vehicle and DBDS (12.5, 25, 50, 100, and 200 µmol/L). After 24 h, 20 μL of MTT solution was added to each well and kept under the same environment for 4 h again. Subsequently, 150 μL of DMSO was added to each well after removing the culture supernatant, vibrated and kept under a darkroom at room temperature for 15 min. The optical density (OD) of the solution was measured with a microplate reader at 490 nm. The survival rate was calculated using the formula, survival rate (%) = OD of the sample-treated group/OD of the control group × 100%.
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Publication 2023
4,4'-dibenzamido-2,2'-stilbenedisulfonic acid Atmosphere Bromides Cells Colorimetry Cytotoxin Sulfoxide, Dimethyl Vision

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More about "4,4'-dibenzamido-2,2'-stilbenedisulfonic acid"

4,4'-dibenzamido-2,2'-stilbenedisulfonic acid (DBSS) is a chemical compound that has a wide range of research applications.
It is also known as 4,4'-dibenzoyl-2,2'-stilbenedisulfonic acid or 4,4'-bis(benzamido)-2,2'-stilbenedisulfonic acid.
DBSS is commonly used as a fluorescent dye, a pH indicator, and a protein labeling agent in various biomedical and analytical techniques.
In research, DBSS is often employed in the PURExpress In Vitro Protein Synthesis Kit, which is used for the synthesis of recombinant proteins.
It is also utilized in the preparation of FAM-labeled nucleic acid duplexes, which are important tools for studying DNA and RNA interactions.
The Avance III 600 MHz NMR spectrometer is one of the analytical instruments that can be used to characterize DBSS and its related compounds.
The ChemiDoc Touch imaging system is another useful tool for visualizing and quantifying DBSS-labeled proteins or nucleic acids.
The PGEX-2T vector, which is commonly used for the expression of recombinant proteins, may also incorporate DBSS-based labeling strategies.
The QIAamp DNA Maxi Kit, which is used for the purification of genomic DNA, could potentially utilize DBSS-based detection methods.
In the field of data analysis, the SAS statistical software suite and the Synergy plate reader can be employed to process and analyze data generated from DBSS-based experiments.
Additionally, the HiTrap Desalting column can be used to purify DBSS-labeled biomolecules, ensuring high-quality samples for further analysis.
Overall, 4,4'-dibenzamido-2,2'-stilbenedisulfonic acid is a versatile and important chemical compound that plays a crucial role in a variety of research applications, from protein synthesis to nucleic acid analysis.
By leveraging the power of AI-driven platforms like PubCompare.ai, researchers can streamline their DBSS-related studies, improving reproducibility, accuracy, and efficiency.