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BLOOD

Blood is a vital fluid that circulates throughout the body, transporting oxygen, nutrients, hormones, and waste products.
It is composed of plasma, red blood cells, white blood cells, and platelets, each playing a crucial role in maintaining the body's health and function.
Blood is essential for delivering oxygen to tissues, fighting infection, clotting wounds, and regulating temperature.
Imbalances or disorders in the composition or function of blood can lead to a wide range of medical conditions, including anemia, leukemia, and thrombosis.
Understanding the complex nature of blood and its components is crucial for effective disease diagnosis, treatment, and prevention.
Reasearch into blood's mechanisms and applications continues to evolve, with new insights and technologies, such as PubCompare.ai, driving advancements in this critical field of medecine.

Most cited protocols related to «BLOOD»

We performed two in silico experiments to assess the detection limits of different deconvolution algorithms. In the first experiment (Supplementary Fig. 6), we used the same cell line GEPs described above to compare CIBERSORT and RLR with five other GEP deconvolution methods4 (link)–8 (link). We evaluated detection limit using Jurkat cells (spike-in concentrations of 0.5%, 1%, 2.5%, 5%, 7.5%, and 10%), whose reference GEP (median of three replicates in GSE11103) was added into randomly created background mixtures of the other three blood cell lines. Five mixtures were created for each spike-in concentration. Predicted Jurkat fractions were assessed in the presence of differential tumor content, which we simulated by adding HCT116 (described above) in ten even increments, from 0% to 90%. Of note, we also used the same marker or signature genes described for simulated tumors (above). In a second experiment (Supplementary Fig. 7a), we compared CIBERSORT with QP5 (link), LLSR4 (link), PERT6 (link), and RLR. We spiked naïve B cell GEPs from the leukocyte signature matrix into four random background mixtures of the remaining 21 leukocyte subsets in the signature matrix. The same background mixtures were used for each spike-in. We also tested the addition of unknown content by adding defined proportions (0 to 90%) of randomly permuted expression values from a naïve B cell reference transcriptome (median expression profile from samples used to build LM22, Supplementary Table 1). We then repeated this analysis for each of the remaining leukocyte subsets in LM22 (Supplementary Fig. 7b).
Publication 2015
B-Lymphocytes BLOOD Cell Lines Cytosol Genes Jurkat Cells Leukocyte Count Leukocytes Neoplasms Transcriptome
A detailed description of materials and methods is given in Methods. The work-flow and organization of the project are given in Supplementary Fig. 16. Case series came from previously established collections with nationally representative recruitment: 2,000 samples were genotyped for each. The control samples came from two sources: half from the 1958 Birth Cohort and the remainder from a new UK Blood Service sample. The latter collection was established specifically for this study and is a UK national repository of anonymized DNA samples from 3,622 consenting blood donors. The vast majority of subjects were self-reported as of European Caucasian ancestry. All DNA samples were requantified and tested for degradation and PCR amplification. Genotyping was performed using GeneChip 500K arrays at the Affymetrix Services Lab (California): arrays not passing the 93% call rate threshold at P=0.33 with the Dynamic Model algorithm were repeated. CEL (cell intensity) files were transferred to WTCCC for quantile normalization, and genotypes called using a new genotyping algorithm, CHIAMO, developed for this project. QC/QA measures included sample call rate, overall heterozygosity and evidence of non-European ancestry (809 samples excluded; 16,179 retained for analysis). SNPs were excluded from analysis because of missing data rates, departures from Hardy-Weinberg equilibrium and other metrics (31,011 excluded; 469,557 retained). Standard 1-d.f. and 2-d.f. tests of case-control association were supplemented with bayesian approaches, multilocus methods (data imputation) and analyses with combined data sets, either as additional cases (to detect variants influencing multiple phenotypes) or as an expanded reference group (to increase power). Results for each SNP for all analyses reported will be available from http://www.wtccc.org.uk, as will details allowing other researchers to apply for access to WTCCC genotype data. Software packages developed within the WTCCC are available on request (see Methods for details).
Publication 2007
Birth Cohort BLOOD Caucasoid Races Cells DNA, A-Form Donor, Blood Europeans Gene Chips Genotype Heterozygote Phenotype
In the following two sections, we describe how to create a custom leukocyte signature matrix and apply it to study cellular heterogeneity and TIL survival associations in melanoma tumors profiled by The Cancer Genome Atlas (TCGA). Readers can follow along by creating ‘LM6’, a leukocyte RNA-Seq signature matrix comprised of six peripheral blood immune subsets (B cells, CD8 T cells, CD4 T cells, NK cells, monocytes/macrophages, neutrophils; GSE60424 [20 ]). Key input files are provided on the CIBERSORT website (‘Menu>Download’).
A custom signature file can be created by uploading the Reference sample file and the Phenotype classes file (section 3.3.2) to the online CIBERSORT application (SeeFigure 2) or can be created using the downloadable Java package. To build a custom gene signature matrix with the latter, the user should download the Java package from the CIBERSORT website and place all relevant files under the package folder. To link Java with R, run the following in R:
Within R:

> library(Rserve)

> Rserve(args=“–no-save”)

Command line:

> java -Xmx3g -Xms3g -jar CIBERSORT.jar -M Mixture_file -P Reference_sample_file -c phenotype_class_file -f

The last argument (-f) will eliminate non-hematopoietic genes from the signature matrix and is generally recommended for signature matrices tailored to leukocyte deconvolution. The user can also run this step on the website by choosing the corresponding reference sample file and phenotype class file (seeFigure 2). The CIBERSORT website will generate a gene signature matrix located under ‘Uploaded Files’ for future download.
Following signature matrix creation, quality control measures should be taken to ensure robust performance (see ‘Calibration of in silico TIL profiling methods’ in Newman et al.) [17 (link)]. Factors that can adversely affect signature matrix performance include poor input data quality, significant deviations in gene expression between cell types that reside in different tissue compartments (e.g., blood versus tissue), and cell populations with statistically indistinguishable expression patterns. Manual filtering of poorly performing genes in the signature matrix (e.g., genes expressed highly in the tumor of interest) may improve performance.
To benchmark our custom leukocyte matrix (LM6), we compared it to LM22 using a set of TCGA lung squamous cell carcinoma tumors profiled by RNA-Seq and microarray (n = 130 pairs). Deconvolution results were significantly correlated for all cell subsets shared between the two signature matrices (P < 0.0001). Notably, since LM6 was derived from leukocytes isolated from peripheral blood [20 ,21 (link)], we restricted the CD4 T cell comparison to naïve and resting memory CD4 T cells in LM22. Once validation is complete, a CIBERSORT signature matrix can be broadly applied to mixture samples as described in section 3.3 (e.g., SeeFigure 4).
Publication 2018
B-Lymphocytes BLOOD CD4 Positive T Lymphocytes CD8-Positive T-Lymphocytes cDNA Library Cells Genes, vif Genetic Diversity Genetic Heterogeneity Hematopoietic System Leukocytes Lung Neoplasms Macrophage Malignant Neoplasms Melanoma Memory Microarray Analysis Monocytes Natural Killer Cells Neoplasms Neutrophil Phenotype Population Group RNA-Seq RNA Motifs Squamous Cell Carcinoma Strains Tissues
Ethics approval for the UK Biobank study was obtained from the North West Centre for Research Ethics Committee (11/NW/0382). Blood samples were collected from participants on their visit to a UK Biobank assessment centre and the samples are stored at the UK Biobank facility in Stockport, UK7 (link). Over a period of 18 months samples were retrieved, DNA was extracted, and 96-well plates of 94 × 50-μl aliquots were shipped to Affymetrix Research Services Laboratory for genotyping. Special attention was paid in the automated sample retrieval process at UK Biobank to ensure that experimental units such as plates or timing of extraction did not correlate systematically with baseline phenotypes such as age, sex, and ethnic background, or the time and location of sample collection. Full details of the UK Biobank sample retrieval and DNA extraction process were described previously34 (link).
On receipt of DNA samples, Affymetrix processed samples on the GeneTitan Multi-Channel (MC) Instrument in 96-well plates containing 94 UK Biobank samples and two control samples from the 1000 Genomes Project25 (link). Genotypes were then called from the array intensity data, in units called ‘batches’ which consist of multiple plates. Across the entire cohort, there were 106 batches of 4,700 UK Biobank samples each (Supplementary Information, Supplementary Table 12). Following the earlier interim data release, Affymetrix developed a custom genotype calling pipeline that is optimized for biobank-scale genotyping experiments, which takes advantage of the multiple-batch design35 . This pipeline was applied to all samples, including the 150,000 samples that were part of the interim data release. Consequently, some of the genotype calls for these samples may differ between the interim data release and this final data release (see below).
Routine quality checks were carried out during the process of sample retrieval, DNA extraction36 , and genotype calling37 . Any sample that did not pass these checks was excluded from the resulting genotype calls. The custom-designed arrays contain a number of markers that had not been previously typed using Affymetrix genotype array technology. As such, Affymetrix also applied a series of checks to determine whether the genotyping assay for a given marker was successful, either within a single batch, or across all samples. Where these newly attempted assays were not successful, Affymetrix excluded the markers from the data delivery (see Supplementary Information for details).
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Publication 2018
Attention Biological Assay BLOOD Ethics Committees, Research Ethnicity Genome Obstetric Delivery Phenotype Specimen Collection
We applied LM22 to a publicly available dataset (GSE298325 (link)) to measure stability of deconvolution results over defined levels of blood admixed with breast tissue. To confirm reported fractions of blood admixed with breast tissue, we compared these proportions with an ‘LM22 normalized immune index’, defined for each sample as the median gene expression value of all genes in LM22 (Supplementary Table 1) divided by the median expression level of the transcriptome, and normalized into the range of known leukocyte content across the datasets (Fig. 2e). As a consistency metric, we compared deconvolution results for each sample with results from the sample with highest immune purity (Fig. 2e).
Publication 2015
BLOOD Breast Gene Expression Genes Leukocytes Tissues Transcriptome

Most recents protocols related to «BLOOD»

Example 12

As a proof of concept, the patient population of this study is patients that (1) have moderate to severe ulcerative colitis, regardless of extent, and (2) have had an insufficient response to a previous treatment, e.g., a conventional therapy (e.g., 5-ASA, corticosteroid, and/or immunosuppressant) or a FDA-approved treatment. In this placebo-controlled eight-week study, patients are randomized. All patient undergo a colonoscopy at the start of the study (baseline) and at week 8. Patients enrolled in the study are assessed for clinical status of disease by stool frequency, rectal bleeding, abdominal pain, physician's global assessment, and biomarker levels such as fecal calprotectin and hsCRP. The primary endpoint is a shift in endoscopy scores from Baseline to Week 8. Secondary and exploratory endpoints include safety and tolerability, change in rectal bleeding score, change in abdominal pain score, change in stool frequency, change in partial Mayo score, change in Mayo score, proportion of subjects achieving endoscopy remission, proportion of subjects achieving clinical remission, change in histology score, change in biomarkers of disease such as fecal calprotectin and hsCRP, level of adalimumab in the blood/tissue/stool, change in cytokine levels (e.g., TNFα, IL-6) in the blood and tissue.

FIG. 72 describes an exemplary process of what would occur in clinical practice, and when, where, and how the ingestible device will be used. Briefly, a patient displays symptoms of ulcerative colitis, including but not limited to: diarrhea, bloody stool, abdominal pain, high c-reactive protein (CRP), and/or high fecal calprotectin. A patient may or may not have undergone a colonoscopy with diagnosis of ulcerative colitis at this time. The patient's primary care physician refers the patient. The patient undergoes a colonoscopy with a biopsy, CT scan, and/or MRI. Based on this testing, the patient is diagnosed with ulcerative colitis. Most patients are diagnosed with ulcerative colitis by colonoscopy with biopsy. The severity based on clinical symptoms and endoscopic appearance, and the extent, based on the area of involvement on colonoscopy with or without CT/MRI is documented. Treatment is determined based on diagnosis, severity and extent.

For example, treatment for a patient that is diagnosed with ulcerative colitis is an ingestible device programmed to release a single bolus of a therapeutic agent, e.g., 40 mg adalimumab, in the cecum or proximal to the cecum. Prior to administration of the treatment, the patient is fasted overnight and is allowed to drink clear fluids. Four hours after swallowing the ingestible device, the patient can resume a normal diet. An ingestible device is swallowed at the same time each day. The ingestible device is not recovered.

In some embodiments, there may be two different ingestible devices: one including an induction dose (first 8 to 12 weeks) and a different ingestible device including a different dose or a different dosing interval.

In some examples, the ingestible device can include a mapping tool, which can be used after 8 to 12 weeks of induction therapy, to assess the response status (e.g., based on one or more of the following: drug level, drug antibody level, biomarker level, and mucosal healing status). Depending on the response status determined by the mapping tool, a subject may continue to receive an induction regimen or maintenance regimen of adalimumab.

In different clinical studies, the patients may be diagnosed with Crohn's disease and the ingestible devices (including adalimumab) can be programmed to release adalimumab in the cecum, or in both the cecum and transverse colon.

In different clinical studies, the patients may be diagnosed with illeocolonic Crohn's disease and the ingestible devices (including adalimumab) can be programmed to release adalimumab in the late jejunum or in the jejunum and transverse colon.

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Patent 2024
Abdominal Pain Adalimumab Adrenal Cortex Hormones Biological Markers Biopsy BLOOD Cecum Colonoscopy C Reactive Protein Crohn Disease Cytokine Diarrhea Diet Endoscopy Endoscopy, Gastrointestinal Feces Homo sapiens Immunoglobulins Immunosuppressive Agents Jejunum Leukocyte L1 Antigen Complex Medical Devices Mesalamine Mucous Membrane Neoadjuvant Therapy Patient Care Management Patients Pharmaceutical Preparations Placebos Primary Care Physicians Safety Therapeutics Tissues Transverse Colon Treatment Protocols Tumor Necrosis Factor-alpha Ulcerative Colitis X-Ray Computed Tomography

Example 1

The sequence coding for the light chain variable region of the antibody was inserted into vector pFUSE2ss-CLIg-hK (Invivogen, Catalog Number: pfuse2ss-hclk) using EcoRI and BsiWI restriction sites to construct a light chain expression vector. The sequence coding for the heavy chain variable region of the antibody was inserted into vector pFUSEss-CHIg-hG2 (Invivogen, Catalog Number: pfusess-hchg2) or vector pFUSEss-CHIg-hG4 (Invivogen, Catalog Number: pfusess-hchg4) using EcoRI and NheI restriction sites to construct a heavy chain expression vector.

The culture and transfection of Expi293 cells were performed in accordance with the handbook of Expi293™ Expression System Kit from Invitrogen (Catalog Number: A14635). The density of the cells was adjusted to 2×106 cells/ml for transfection, and 0.6 μg of the light chain expression vector as described above and 0.4 μg of the heavy chain expression vector as described above were added to each ml of cell culture, and the supernatant of the culture was collected four days later.

The culture supernatant was subjected to non-reduced SDS-PAGE gel electrophoresis in accordance with the protocol described in Appendix 8, the Third edition of the “Molecular Cloning: A Laboratory Manual”.

Pictures were taken with a gel scanning imaging system from BEIJING JUNYI Electrophoresis Co., LTD and in-gel quantification was performed using Gel-PRO ANALYZER software to determine the expression levels of the antibodies after transient transfection. Results were expressed relative to the expression level of control antibody 1 (control antibody 1 was constructed according to U.S. Pat. No. 7,186,809, which comprises a light chain variable region as set forth in SEQ ID NO: 10 of U.S. Pat. No. 7,186,809 and a heavy chain variable region as set forth in SEQ ID NO: 12 of U.S. Pat. No. 7,186,809, the same below) (control antibody 2 was constructed according to U.S. Pat. No. 7,638,606, which comprises a light chain variable region as set forth in SEQ ID NO: 6 of U.S. Pat. No. 7,638,606 and a variable region as set forth in SEQ ID NO: 42 of U.S. Pat. No. 7,638,606, the same below). See Tables 2a-2c below for the results.

TABLE 2a
Expression levels of the antibodies of the present
invention after transient transfection (antibodies whose
expression levels are significantly higher than that of control antibody 1):
Number ofExpression level vsNumber of Expression level vs
the antibodycontrol antibody 1the antibodycontrol antibody 1
L1021H10002.08L1000H10281.27
L1020H10001.58L1000H10151.19
L1000H10271.56L1000H10321.18
L1000H10241.51L1000H10261.15
L1000H10251.48L1021H10291.12
L1001H10001.48L1000H10301.1
L1021H10161.43L1024H10311.08
L1000H10141.35L1000H10161.05

TABLE 2b
Expression levels of the antibodies of the present
invention after transient transfection (antibodies whose
expression levels are slightly lower than that of control antibody 1):
Number of Expression level vsNumber of Expression level vs
the antibodycontrol antibody 1the antibodycontrol antibody 1
L1000H10310.99L1017H10000.85
L1021H10310.99L1020H10160.84
L1020H10290.96L1000H10090.81
control anti-0.93L1000H10070.8
body 2
L1012H10000.89L1000H10230.8
L1019H10000.87L1020H10270.78
L1020H10310.87L1024H10070.77
L1021H10200.87L1000H10130.75
L1000H10290.86L1020H10070.74
L1008H10000.86L1021H10070.74
L1000H10010.85L1000H10210.71

TABLE 2c
Expression levels of the antibodies of the present
invention after transient transfection (antibodies whose
expression levels are significantly lower than that of control antibody 1):
Number ofExpression level vsNumber of Expression level vs
the antibodycontrol antibody 1the antibodycontrol antibody 1
L1000H10200.69L1024H10000.52
L1010H10000.69L1000H10080.51
L1000H10220.67L1000H10370.5
L1000H10120.64L1007H10000.49
L1022H10000.64L1016H10000.49
L1011H10000.63L1000H10170.47
L1000H10110.62L1000H10350.46
L1000H10330.62L1012H10270.46
L1020H10200.61L1018H10000.44
L1000H10360.6L1023H10000.43
L1021H10270.6L1012H10160.42
L1012H10070.59L1013H10000.41
L1009H10000.57L1000H10340.4
L1012H10200.57L1000H10180.35
L1012H10310.56L1000H10190.34
L1000H10380.54L1015H10000.27
L1012H10290.54L1014H10000.17
L1000H10100.53

Example 4

6-8 week-old SPF Balb/c mice were selected and injected subcutaneously with antibodies (the antibodies of the present invention or control antibody 2) in a dose of 5 mg/kg (weight of the mouse). Blood samples were collected at the time points before administration (0 h) and at 2, 8, 24, 48, 72, 120, 168, 216, 264, 336 h after administration. For blood sampling, the animals were anesthetized by inhaling isoflurane, blood samples were taken from the orbital venous plexus, and the sampling volume for each animal was about 0.1 ml; 336 h after administration, the animals were anesthetized by inhaling isoflurane and then euthanized after taking blood in the inferior vena cava.

No anticoagulant was added to the blood samples, and serum was isolated from each sample by centrifugation at 1500 g for 10 min at room temperature within 2 h after blood sampling. The collected supernatants were immediately transferred to new labeled centrifuge tubes and then stored at −70° C. for temporary storage. The concentrations of the antibodies in the mice were determined by ELISA:

1. Preparation of Reagents

sIL-4Rα (PEPRO TECH, Catalog Number: 200-04R) solution: sIL-4Rα was taken and 1 ml ddH2O was added therein, mixed up and down, and then a solution of 100 μg/ml was obtained. The solution was stored in a refrigerator at −20° C. after being subpacked.

Sample to be tested: 1 μl of serum collected at different time points was added to 999 μl of PBS containing 1% BSA to prepare a serum sample to be tested of 1:1000 dilution.

Standard sample: The antibody to be tested was diluted to 0.1 μg/ml with PBS containing 1% BSA and 0.1% normal animal serum (Beyotime, Catalog Number: ST023). Afterwards, 200, 400, 600, 800, 900, 950, 990 and 1000 μl of PBS containing 1% BSA and 0.1% normal animal serum were respectively added to 800, 600, 400, 200, 100, 50, 10 and 0 μl of 0.1 μg/ml antibodies to be tested, and thus standard samples of the antibodies of the present invention were prepared with a final concentration of 80, 60, 40, 20, 10, 5, 1, or 0 ng/ml respectively.

2. Detection by ELISA

250 μl of 100 μg/ml sIL-4Rα solution was added to 9.75 ml of PBS, mixed up and down, and then an antigen coating buffer of 2.5 μg/ml was obtained. The prepared antigen coating buffer was added to a 96-well ELISA plate (Corning) with a volume of 100 μl per well. The 96-well ELISA plate was incubated overnight in a refrigerator at 4° C. after being wrapped with preservative film (or covered). On the next day, the 96-well ELISA plate was taken out and the solution therein was discarded, and PBS containing 2% BSA was added thereto with a volume of 300 μl per well. The 96-well ELISA plate was incubated for 2 hours in a refrigerator at 4° C. after being wrapped with preservative film (or covered). Then the 96-well ELISA plate was taken out and the solution therein was discarded, and the plate was washed 3 times with PBST. The diluted standard antibodies and the sera to be detected were sequentially added to the corresponding wells, and three duplicate wells were made for each sample with a volume of 100 μl per well. The ELISA plate was wrapped with preservative film (or covered) and incubated for 1 h at room temperature. Subsequently, the solution in the 96-well ELISA plate was discarded and then the plate was washed with PBST for 3 times. Later, TMB solution (Solarbio, Catalog Number: PR1200) was added to the 96-well ELISA plate row by row with a volume of 100 μl per well. The 96-well ELISA plate was placed at room temperature for 5 minutes, and 2 M H2SO4 solution was added in immediately to terminate the reaction. The 96-well ELISA plate was then placed in flexstation 3 (Molecular Devices), the values of OD450 were read, the data were collected and the results were calculated with Winnonlin software. The pharmacokinetic results were shown in FIG. 1 and Table 6 below.

TABLE 6
Pharmacokinetic results of the antibodies of the present invention in mouse
Area
TimeUnder the
HalftoPeakdrug-timeVolume ofClearance
lifepeakconcentrationCurvedistributionrate
Numberhhμg/mlh*μg/mlml/kgml/h/kg
L1020H1031Mean269.347233.797679.28138.920.38
value
Standard105.730.000.42163.9122.480.09
deviation
L1012H1031Mean167.274845.59852.391.30.38
value
Standard8.520.001.86448.345.580.00
deviation
ControlMean56.67367.881132.68288.923.79
antibody 2value
Standard25.8416.970.2594.4249.451.12
deviation

Example 5

A series of pharmacokinetic experiments were carried out in Macaca fascicularises to further screen antibodies.

3-5 year-old Macaca fascicularises each weighting 2-5 Kg were selected and injected subcutaneously with antibodies (the antibodies of the present invention or control antibody 2) in a dose of 5 mg/kg (weight of the Macaca fascicularis). The antibody or control antibody 2 to be administered was accurately extracted with a disposable aseptic injector, and multi-point injections were made subcutaneously on the inner side of the thigh of the animal, and the injection volume per point was not more than 2 ml. Whole blood samples were collected from the subcutaneous vein of the hind limb of the animal at the time points before administration (0 h) and at 0.5, 2, 4, 8, 24, 48, 72, 120, 168, 240, 336 h, 432 h, 504 h, 600 h, 672 h after administration. The blood volume collected from each animal was about 0.1 ml each time.

No anticoagulant was added to the blood samples, and serum was isolated from each sample by centrifugation at 1500 g for 10 min at room temperature within 2 h after blood sampling. The collected supernatants were immediately transferred to new labeled centrifuge tubes and then stored at −70° C. for temporary storage. The concentrations of the antibodies in the Macaca fascicularises were determined according the method as described in Example 4. The pharmacokinetic results are shown in FIG. 2 and Table 7 below.

TABLE 7
Pharmacokinetic results of the antibodies of the present invention in macaca fascicularis
Area
TimeUnder the
HalftoPeakdrug-timeVolume ofClearance
lifepeakconcentrationCurvedistributionrate
Numberhhμg/mlh*μg/mlml/kgml/h/kg
L1020H1031Mean254.9548.0089.6522189.9175.940.22
value
Standard44.5733.9444.298557.1522.950.10
deviation
L1012H1031Mean185.75486516185.7373.410.28
value
Standard42.5433.944.52506.980.810.06
deviation
ControlMean37.031637.822773.2193.971.78
antibody 2value
Standard18.0311.316.75155.8442.470.07
deviation

Example 10

In vivo pharmacokinetics of the antibodies of the invention are further detected and compared in this Example, in order to investigate the possible effects of specific amino acids at specific positions on the pharmacokinetics of the antibodies in animals. The specific experimental method was the same as that described in Example 4, and the results are shown in Table 9 below.

TABLE 9
Detection results of in vivo pharmacokinetics of the antibodies of the present invention
Area
TimeUnder the
HalftoPeakdrug-timeVolume ofClearance
lifepeakconcentrationCurvedistributionrate
hhug/mlh*ug/mlml/kgml/h/kg
L1020H1031Mean185.494038.948188.8114.280.43
value
Standard18.5213.862.33510.476.50.05
deviation
L1012H1001Mean161.2648.0012.362491.19332.791.47
value
Standard54.300.002.26165.1676.910.20
deviation
L1001H1031Mean171.4156.0042.749273.7399.170.40
value
Standard6.1213.867.381868.6618.690.07
deviation
L1020H1001Mean89.0064.0020.113481.40164.141.30
value
Standard16.7013.862.14268.3922.860.20
deviation

From the specific sequence, the amino acid at position 103 in the sequence of the heavy chain H1031 (SEQ ID NO. 91) of the antibody (in CDR3) is Asp (103Asp), and the amino acid at position 104 is Tyr (104Tyr). Compared with antibodies that have no 103Asp and 104Tyr in heavy chain, the present antibodies which have 103Asp and 104Tyr have a 2- to 4-fold higher area under the drug-time curve and an about 70% reduced clearance rate.

The expression levels of the antibodies of the present invention are also detected and compared, in order to investigate the possible effects of specific amino acids at specific positions on the expression of the antibodies. Culture and transfection of Expi293 cells were conducted according to Example 1, and the collected culture supernatant was then passed through a 0.22 μm filter and then purified by GE MabSelect Sure (Catalog Number: 11003494) Protein A affinity chromatography column in the purification system GE AKTA purifier 10. The purified antibody was collected and concentrated using Amicon ultrafiltration concentrating tube (Catalog Number: UFC903096) and then quantified. The quantitative results are shown in Table 10 below.

TABLE 10
Detection results of the expression
levels of the antibodies of the present invention
Expression level
Antibody(×10−2 mg/ml culture medium)
L1020H10318.39
L1001H10311.79
L1020H10014.04
L1012H10015.00
L1023H10014.63
L1001H10011.75

From the specific sequence, the amino acid at position 31 in the sequence of the light chain L1012 (SEQ ID NO. 44), L1020 (SEQ ID NO. 55) or L1023 (SEQ ID NO. 51) of the antibody (in CDR1) is Ser (31Ser). Compared with antibodies that have no 31Ser in light chain, the present antibodies which have 31Ser have a 2- to 5-fold higher expression level.

The above description for the embodiments of the present invention is not intended to limit the present invention, and those skilled in the art can make various changes and variations according to the present invention, which are within the protection scope of the claims of the present invention without departing from the spirit of the same.

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Patent 2024
Amino Acids Animals Antibodies Anticoagulants Antigens Asepsis BLOOD Blood Volume Buffers Cell Culture Techniques Cells Centrifugation Chromatography Chromatography, Affinity Cloning Vectors Culture Media Deoxyribonuclease EcoRI Drug Kinetics Electrophoresis Enzyme-Linked Immunosorbent Assay Hindlimb Human Body Immunoglobulin Heavy Chains Immunoglobulin Light Chains Immunoglobulins Interleukin-1 Isoflurane Light Macaca Macaca fascicularis Medical Devices Metabolic Clearance Rate Mice, Inbred BALB C Mus Open Reading Frames Pharmaceutical Preparations Pharmaceutical Preservatives SDS-PAGE Serum Staphylococcal Protein A Technique, Dilution Thigh Transfection Transients Ultrafiltration Veins Vena Cavas, Inferior

Example 66

The activity of SYN-PKU-2002 was assessed in vivo. To prepare the cells for the study, SYN-PKU901 and SYN-PKU-2002 overnight cultures were each used to inoculate 4 2 L flasks containing 500 mL of LB with DAP100 ug/mL. These cultures were grown for 1 hr and 45 min and then moved to the anaerobic chamber supplying 90% N2, 5% CO2, and 5% H2 for 4 hours. Cells were then spun down at 4600×G for 12 min and resuspended in 10 mL of formulation buffer (Glycerol: 15% (v/v), Sucrose: 10% (w/v) (100 g/L), MOPS: 10 mM (2.1 g/L), NaCl: 25 mM (1.46 g/L)). Several 40 ul aliquots were removed to be used for cell counting and activity determination. The viability as determined by cellometer count (in quadruplicate) 6.94e10 cfu/ml (+/−5.78e9).

Activity was determined using a plate based assay. Briefly, 1×108 cfu as determined by cellometer were added to 1 ml of prewarmed assay buffer (1× M9 minimal media containing 0.5% glucose, 50 mM MOPS, and 50 mM phenylalanine) in a microfuge tube, vortexed briefly, and immediately placed in a heat block or water bath at 37 degrees Celsius for static incubation (t=0). Supernatant samples from cells re-suspended in assay buffer were analyzed for the abundance of TCA over several time points using spectrophotometer at an absorbance of 290 nm. The accurate OD290 window for TCA detection occurs in a relatively narrow concentration range. For this reason, supernatant samples were diluted to ensure that the absorbance measurement fell into the linear range for detection. Measurements were compared to a TCA standard curve. Activity was determined to be 2.72 umol/hr/le9 cfu (+/−0.15 umol/hr/le9 cfu).

Beginning 4 days prior to the study (i.e., Days −4-1), Pah ENU2/2 mice (˜11-15 weeks of age) were maintained on phenylalanine-free chow and water that was supplemented with 0.5 grams/L phenylalanine. On the day of the study, mice were randomized into treatment groups according to weight as follows: Group 1: SYN-PKU901 (n=9); Group 2: Group 2: SYN-PKU-2002 (n=9). Blood samples were collected by sub-mandibular skin puncture to determine baseline phenylalanine levels. Mice were then administered single dose of phenylalanine by subcutaneous injection at 0.1 mg per gram body weight, according to the average group weight. At 1, 2 and 3 h post Phe challenge, the bacteria (or water) were administered to mice by oral gavage (3×250 ul). Whole blood was collected via submandibular bleed at each time point. Urine collection in metabolic caging commenced immediately after the 1st bacterial dose and continued to be collected for the duration of the study (4 hours).

Blood samples were kept on ice until processing for plasma in a centrifuge (2000 g for 10 min at 4 C) within 20 min of collection. Plasma was then transferred into a 96-well plate for MS analysis. Urine was collected in 5 mL tubes and volumes were recorded before transferring samples to MS for analysis. Results are shown in FIG. 17A and FIG. 17B and show that SYN-PKU-2002 causes decreased changes in phenylalanine post-Phe injection and produces hippurate, in a similar manner as SYN-PKU-710.

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Patent 2024
Bacteria Bath Biological Assay BLOOD Buffers Cells Glucose Glycerin hippurate Mandible morpholinopropane sulfonic acid Mus Plasma Punctures Serum Skin Sodium Chloride Subcutaneous Injections Sucrose Tube Feeding Urine Urine Specimen Collection

Example 19

To confirm bioactivity of 3 and 7, experiments were performed with the HH cell line, a mature T cell line derived from peripheral blood of a patient with aggressive cutaneous T cell leukemia/lymphoma (ATCC® CRL-2105™) which been demonstrated to only express the IL-2Rβ/γ. One of the earliest events in cytokine mediated activation of lymphocytes such as CD8+ T cells and NK cells is Janus Associated Kinase mediated phosphorylation and activation of Signal transducer and activator of transcription (pSTAT5). Thus, pSTAT5 was used to measure biological activity of 3 and 7 alongside 12. 3 demonstrated clear bioactivity in IL-2Rβ/γ expressing HH cells (EC50: 773 ng/ml) that was approximately 3.5 fold lower than 12 (EC50: 233 ng/ml). Additionally, 7 induced bioactivity (EC50: 756 ng/ml) very similar to 3, demonstrating that 7 retains bioactivity after being released from prodrug 5 even after accelerated (stress) conditions.

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Patent 2024
Biopharmaceuticals BLOOD CD8-Positive T-Lymphocytes Cell Lines Cells Cytokine IL19 protein, human Kinase, Janus Leukemia Lymphocyte Activation Lymphoma, T-Cell, Cutaneous Natural Killer Cells Patients Phosphorylation Prodrugs Transcription, Genetic Transducers

Example 5

The effects of AST on P. falciparum transmission to Anopheles gambiae mosquitoes was analyzed. AST was added to 15-day cultured P. falciparum-infected blood at concentrations from 0.1 to 3 μM and fed to An. gambiae using a standard membrane feeding assay (SMFA). The number of oocysts in mosquito midguts was counted on day 7 post-infection. AST completely inhibited malaria transmission at 3 μM (FIG. 4A) suggesting that AST effectively blocks transmission. Most of currently available antimalarial drugs and candidate drugs in clinical development require 5 μM or higher for complete inhibition of P. falciparum transmission in SMFAs. These results demonstrate that AST is at least as effective as current drugs. In contrast, no dead mosquitoes were observed, suggesting that AST has no or little insecticidal activity. The EC50 of AST in blocking the transmission of the sexual-stage P. falciparum to mosquitos, defined as the concentration of a compound that inhibits 50% of infection intensity (the number of oocysts per mosquito) compared to that of the compound-free control, was 0.34 μM.

Advantageously, AST significantly inhibits Plasmodium falciparum transmission to Anopheles gambiae mosquitoes compared to that of PT and MSO (FIG. 4B).

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Patent 2024
Anopheles gambiae Antimalarials Biological Assay BLOOD Cardiac Arrest Culicidae Infection Insecticides Malaria Oocysts Pharmaceutical Preparations Plasmodium falciparum Psychological Inhibition Tissue, Membrane Transmission, Communicable Disease

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More about "BLOOD"

Discover the essential role of blood in the human body.
Blood is a vital fluid that circulates throughout the body, transporting oxygen, nutrients, hormones, and waste products.
It is composed of plasma, red blood cells (erythrocytes), white blood cells (leukocytes), and platelets (thrombocytes), each playing a crucial part in maintaining health and function.
Blood delivers oxygen to tissues, fights infection, clots wounds, and regulates temperature.
Imbalances or disorders in the composition or function of blood can lead to a wide range of medical conditions, including anemia, leukemia, and thrombosis.
Understanding the complex nature of blood and its components is crucial for effective disease diagnosis, treatment, and prevention.
Researchers use various methods and kits to study blood, such as the DNeasy Blood and Tissue Kit, QIAamp DNA Blood Mini Kit, BD Vacutainer, Ficoll-Paque PLUS, and TRIzol reagent.
These tools help extract, purify, and analyze DNA, RNA, and other blood components.
Fetal bovine serum (FBS) and Histopaque-1077 are also commonly used in blood research.
New technologies, like PubCompare.ai, are driving advancements in blood research by providing AI-driven protocols for reproducibility and accuracy.
These innovations help locate the best research protocols from literature, preprints, and patents, ensuring reliable and effective blood studies.
Experience the future of blood research today with PubCompare.ai.