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Carbohydrates

Carbohydrates are a class of macromolecules composed of carbon, hydrogen, and oxygen atoms.
They serve as a primary source of energy for the body and play crucial roles in various biological processes, such as cell signaling, structure, and immune function.
Carbohydrates can be classified into different types, including monosaccharides (e.g., glucose, fructose), disaccharides (e.g., sucrose, lactose), and polysaccharides (e.g., starch, glycogen).
Thier study is essential for understanding human nutrition, metabolic disorders, and the development of therapeutic interventions.
Reasearchers in this field utilize advanced analytical techniques and bioinformatic tools, such as PubComapre.ai, to optimie research protocols and enhance the reproducibility of carbohydrate studies.

Most cited protocols related to «Carbohydrates»

1
Extraction of High-Quality RNA from Grape Berries
Cited 144 times
The extraction buffer contained 300 mM Tris HCl (pH 8.0), 25 mM EDTA, 2 M NaCl, 2% CTAB, 2% PVPP, 0.05% spermidine trihydrochloride, and just prior to use, 2% β-mercaptoethanol. Tissue was ground to a fine powder in liquid nitrogen using a mortar and pestle. The powder was added to pre-warmed (65°C) extraction buffer at 20 ml/g of tissue and shaken vigorously. Since berries have higher water content than other grape tissues, a lower extraction buffer ratio of 10–15 ml/g weight was sufficient. Tubes were subsequently incubated in a 65°C water bath for 10 min and shaken every couple of min. Mixtures were extracted twice with equal volumes chloroform:isoamyl alcohol (24:1) then centrifuged at 3,500 × g for 15 min at 4°C. The aqueous layer was transferred to a new tube and centrifuged at 30,000 × g for 20 min at 4°C to remove any remaining insoluble material. This step proved more critical for root and flower tissues. To the supernatant, 0.1 vol 3 M NaOAc (pH 5.2) and 0.6 vol isopropanol were added, mixed, and then stored at -80°C for 30 min. Nucleic acid pellets (including any remaining carbohydrates) were collected by centrifugation at 3,500 × g for 30 min at 4°C. The pellet was dissolved in 1 ml TE (pH 7.5) and transferred to a microcentrifuge tube. To selectively precipitate the RNA, 0.3 vol of 8 M LiCl was added and the sample was stored overnight at 4°C. RNA was pelleted by centrifugation at 20,000 × g for 30 min at 4°C then washed with ice cold 70% EtOH, air dried, and dissolved in 50–150 μl DEPC-treated water.
Reid K.E., Olsson N., Schlosser J., Peng F, & Lund S.T. (2006). An optimized grapevine RNA isolation procedure and statistical determination of reference genes for real-time RT-PCR during berry development. BMC Plant Biology, 6, 27.
Full text: Click here
Publication 2006
2-Mercaptoethanol Bath Berries Buffers Carbohydrates Centrifugation Cetrimonium Bromide Chloroform Cold Temperature Edetic Acid Ethanol Grapes isopentyl alcohol Isopropyl Alcohol Nitrogen Nucleic Acids Pellets, Drug Plant Roots polyvinylpolypyrrolidone Powder Sodium Chloride Spermidine Tissues Tromethamine
2
Systematic review of glycaemic index data
Cited 141 times
We conducted a literature search of MEDLINE from January 1981 through December 2007 using the terms “glyc(a)emic index” and “glyc(a)emic load.” We restricted the search to human studies published in English using standardized methodology. We performed a manual search of relevant citations and contacted experts in the field. Unpublished values from our laboratory and elsewhere were included. Values listed in previous tables (6 (link),7 ) were not automatically entered but reviewed first. Final data were divided into two lists. Values derived from groups of eight or more healthy subjects were included in the first list. Data derived from testing individuals with diabetes or impaired glucose metabolism, from studies using too few subjects (n ≤ 5), or showing wide variability (SEM > 15) were included in the second list. Some foods were tested in only six or seven normal subjects but otherwise appeared reliable and were included in the first list. Two columns of GI values were created because both glucose and white bread continue to be used as reference foods. The conversion factor 100/70 or 70/100 was used to convert from one scale to the other. In instances where other reference foods (e.g., rice) were used, this was accepted provided the conversion factor to the glucose scale had been established. To avoid confusion, the glucose scale is recommended for final reporting. GL values were calculated as the product of the amount of available carbohydrate in a specified serving size and the GI value (using glucose as the reference food), divided by 100. Carbohydrate content was obtained from the reference paper or food composition tables (8 ). The relationship between GI values determined in normal subjects versus diabetic subjects was tested by linear regression. Common foods (n = 20), including white bread, cornflakes, rice, oranges, corn, apple juice, sucrose, and milk were used for this analysis.
Atkinson F.S., Foster-Powell K, & Brand-Miller J.C. (2008). International Tables of Glycemic Index and Glycemic Load Values: 2008. Diabetes Care, 31(12), 2281-2283.
Publication 2008
Bread Carbohydrates Corns Diabetes Mellitus Food Glucose Healthy Volunteers Homo sapiens Metabolism Milk, Cow's Oryza sativa Sucrose
3
Beverage Intake Questionnaire (BEVQ-19)
Cited 56 times

Protocol full text hidden due to copyright restrictions

Open the protocol to access the free full text link

Publication 2012
Alcoholic Beverages Amniotic Fluid Beer Beverages Black Tea Carbohydrates Coffee Diet Drinks Eating Energy Drinks Fat-Restricted Diet Food Light Macronutrient Milk Soft Drinks Vegetable Juices Water Consumption Wine
4
Optimized Parmbsc1 Force Field Parameters
Cited 47 times
All backbone torsion angles, except the recently corrected α and γ4 (link), were parameterized using representative model compounds (Supplementary Fig. 23), for which torsional profiles were obtained at the MP2/aug-cc-pVDZ level using B3LYP/6-31++G(d,p)-optimized geometries21 -23 . Single-point calculations at crucial points of the conformational space were performed at the CCSD(T)/complete basis set (CBS) level24 -26 . Solvent effects were introduced using our MST28 method as implemented in Gaussian (http://www.gaussian.com). See Supplementary Notes for additional details on QM calculations.
Parameters were fitted using a flexible Monte-Carlo procedure4 (link), which minimizes the error between QM reference profiles (in solution) and classical potentials of mean force calculations in aqueous solution obtained from umbrella sampling calculations29 . By default we used gas phase-fitted values as first guess, and always limited the torsional representation to a three Fourier expansion terms, while reinforcing in the fitting the weight of the points described at the highest level of theory and those geometrical regions that are specially populated in experimental structures. Around 5–10 acceptable solutions of the Monte Carlo refinement were tested on short MD simulations (around 50–100 ns) for one small duplex d(CGATCG)2 rejecting those leading to distorted structures. The optimum parameter set, without additional refinement was extensively tested against experimental results. Additional details (and references) on the parameterization procedure are given in the Supplementary Notes. Note that the way in which the parameters were derived does not guarantee their validity for RNA simulations. The use of others, already validated, RNA force-fields are recommended.
As shown in the Online Methods Table 1, refined parmbsc1 parameters fit very well high-level QM data. The syn-anti equilibrium, which was non-optimal in parmbsc0, is now well reproduced (Supplementary Fig. 24). The fitting to sugar puckering profile was improved by increasing the East barrier, and by displacing the North and South minima to more realistic regions (Online Methods Table 1 and Supplementary Fig. 25). Additionally, parmbsc1 provides ε and ζ conformational map almost indistinguishable from the CCSD(T)/CBS results in solution (Supplementary Fig. 26), with errors in the estimates of relative BI/BII stability and transition barrier equal to 0.2 and 0.0 kcal mol−1 respectively.
Ivani I., Dans P.D., Noy A., Pérez A., Faustino I., Hospital A., Walther J., Andrio P., Goñi R., Balaceanu A., Portella G., Battistini F., Gelpí J.L., González C., Vendruscolo M., Laughton C.A., Harris S.A., Case D.A, & Orozco M. (2015). PARMBSC1: A REFINED FORCE-FIELD FOR DNA SIMULATIONS. Nature methods, 13(1), 55-58.
Publication 2015
Carbohydrates Solvents Vertebral Column
5
Detailed DNA Structural Analysis
Cited 44 times
The w3DNA server reports three sets of rigid-body parameters: (i) the six base-pair parameters describing the spatial arrangements of associated bases—three angles called Buckle, Propeller, and Opening and three displacements called Shear, Stretch, and Stagger; (ii) the six base-pair-step parameters specifying the configurations of spatially adjacent base pairs—two bending angles called Tilt and Roll, the dimeric rotation angle Twist, two in-plane dislocations termed Shift and Slide, and the vertical displacement Rise; and (iii) the six parameters that relate the positions of successive base pairs relative to a local helical frame—the angles Inclination and Tip and the distances x-displacement and y-displacement describing the orientation and translation of the base planes with respect to the helical axis, and the rotation about and displacement along the helical axis, referred to as Helical Twist and Helical Rise (1 (link),10 ). The numerical values describe the deviations of the base pairs in a given structure from the planar Watson–Crick base pairs in an ideal B-DNA helix, where the base-pair parameters, the dimeric bending components, and in-plane dislocations of adjacent base pairs are null (11 (link)). A fourth set of rigid-body variables—the dinucleotide Tilt, Roll, Twist, Shift, Slide, and Rise—specifies the arrangements of adjacent bases along individual strands. The computations of rigid-body parameters use the mathematical definitions of El Hassan and Calladine (5 (link)). The identification of the helical axis between adjacent base pairs follows the methodology introduced by Babcock et al. (13 (link)).
The reported output also includes the areas of overlap of adjacent bases and base pairs and the positioning of phosphorus atoms within each base-pair step. The former values quantify the stacking of neighboring base pairs, and the latter discriminate between A and B double-helical steps (17 (link)). The base-pairing information is complemented by more conventional structural data, such as the identities and lengths of hydrogen bonds, the distances and angles between atoms in hydrogen-bonded and adjacent nucleotides, the torsion angles along the chain backbone, the amplitude and phase angle of sugar pseudorotation (i.e. puckering geometry), the glycosyl torsions orienting the sugars and bases, and the widths of the major and minor grooves.
Zheng G., Lu X.J, & Olson W.K. (2009). Web 3DNA—a web server for the analysis, reconstruction, and visualization of three-dimensional nucleic-acid structures. Nucleic Acids Research, 37(Web Server issue), W240-W246.
Publication 2009
Carbohydrates Dinucleoside Phosphates Epistropheus Helix (Snails) Human Body Hydrogen Hydrogen Bonds Joint Dislocations Muscle Rigidity Nucleotides Phosphorus Reading Frames Sugars Vertebral Column

Most recents protocols related to «Carbohydrates»

1
Targeted siRNA Delivery for Muscle Atrophy
Not available on PMC !

Example 24

For groups 1-12, see study design in FIG. 32, the 21mer Atrogin-1 guide strand was designed. The sequence (5′ to 3′) of the guide/antisense strand was UCGUAGUUAAAUCUUCUGGUU (SEQ ID NO: 14237). The guide and fully complementary RNA passenger strands were assembled on solid phase using standard phospharamidite chemistry and purified over HPLC. Base, sugar and phosphate modifications that are well described in the field of RNAi were used to optimize the potency of the duplex and reduce immunogenicity. Purified single strands were duplexed to get the double stranded siRNA described in figure A. The passenger strand contained two conjugation handles, a C6-NH2 at the 5′ end and a C6-SH at the 3′ end. Both conjugation handles were connected to siRNA passenger strand via phosphodiester-inverted abasic-phosphodiester linkers. Because the free thiol was not being used for conjugation, it was end capped with N-ethylmaleimide.

For groups 13-18 see study design in FIG. 32, a 21mer negative control siRNA sequence (scramble) (published by Burke et al. (2014) Pharm. Res., 31(12):3445-60) with 19 bases of complementarity and 3′ dinucleotide overhangs was used. The sequence (5′ to 3′) of the guide/antisense strand was UAUCGACGUGUCCAGCUAGUU (SEQ ID NO: 14228). The same base, sugar and phosphate modifications that were used for the active MSTN siRNA duplex were used in the negative control siRNA. All siRNA single strands were fully assembled on solid phase using standard phospharamidite chemistry and purified over HPLC. Purified single strands were duplexed to get the double stranded siRNA. The passenger strand contained two conjugation handles, a C6-NH2 at the 5′ end and a C6-SH at the 3′ end. Both conjugation handles were connected to siRNA passenger strand via phosphodiester-inverted abasic-phosphodiester linker. Because the free thiol was not being used for conjugation, it was end capped with N-ethylmaleimide.

Antibody siRNA Conjugate Synthesis Using Bis-Maleimide (BisMal) Linker

Step 1: Antibody Reduction with TCEP

Antibody was buffer exchanged with 25 mM borate buffer (pH 8) with 1 mM DTPA and made up to 10 mg/ml concentration. To this solution, 4 equivalents of TCEP in the same borate buffer were added and incubated for 2 hours at 37° C. The resultant reaction mixture was combined with a solution of BisMal-siRNA (1.25 equivalents) in pH 6.0 10 mM acetate buffer at RT and kept at 4° C. overnight. Analysis of the reaction mixture by analytical SAX column chromatography showed antibody siRNA conjugate along with unreacted antibody and siRNA. The reaction mixture was treated with 10 EQ of N-ethylmaleimide (in DMSO at 10 mg/mL) to cap any remaining free cysteine residues.

Step 2: Purification

The crude reaction mixture was purified by AKTA Pure FPLC using anion exchange chromatography (SAX) method-1. Fractions containing DAR1 and DAR2 antibody-siRNA conjugates were isolated, concentrated and buffer exchanged with pH 7.4 PBS.

Anion Exchange Chromatography Method (SAX)-1.

Column: Tosoh Bioscience, TSKGel SuperQ-5PW, 21.5 mm ID×15 cm, 13 um

Solvent A: 20 mM TRIS buffer, pH 8.0; Solvent B: 20 mM TRIS, 1.5 M NaCl, pH 8.0; Flow Rate: 6.0 ml/min

Gradient:

a.% A% BColumn Volume
b.10001
c.81190.5
d.505013
e .40600.5
f.01000.5
g.10002

Anion Exchange Chromatography (SAX) Method-2

Column: Thermo Scientific, ProPac™ SAX-10, Bio LC™, 4×250 mm

Solvent A: 80% 10 mM TRIS pH 8, 20% ethanol; Solvent B: 80% 10 mM TRIS pH 8, 20% ethanol, 1.5 M NaCl; Flow Rate: 0.75 ml/min

Gradient:

a.Time% A% B
b.0.09010
c.3.009010
d.11.004060
e.14.004060
f.15.002080
g.16.009010
h.20.009010

Step-3: Analysis of the Purified Conjugate

The purity of the conjugate was assessed by analytical HPLC using anion exchange chromatography method-2 (Table 22).

TABLE 22
SAX retention% purity
Conjugatetime (min)(by peak area)
TfR1-Atrogin-1 DAR19.299
TfR1-Scramble DAR18.993

In Vivo Study Design

The conjugates were assessed for their ability to mediate mRNA downregulation of Atrogin-1 in muscle (gastroc) in the presence and absence of muscle atrophy, in an in vivo experiment (C57BL6 mice). Mice were dosed via intravenous (iv) injection with PBS vehicle control and the indicated ASCs and doses, see FIG. 32. Seven days post conjugate delivery, for groups 3, 6, 9, 12, and 15, muscle atrophy was induced by the daily administration via intraperitoneal injection (10 mg/kg) of dexamethasone for 3 days. For the control groups 2, 5, 8, 11, and 14 (no induction of muscle atrophy) PBS was administered by the daily intraperitoneal injection. Groups 1, 4, 7, 10, and 13 were harvested at day 7 to establish the baseline measurements of mRNA expression and muscle weighted, prior to induction of muscle atrophy. At three days post-atrophy induction (or 10 days post conjugate delivery), gastrocnemius (gastroc) muscle tissues were harvested, weighed and snap-frozen in liquid nitrogen. mRNA knockdown in target tissue was determined using a comparative qPCR assay as described in the methods section. Total RNA was extracted from the tissue, reverse transcribed and mRNA levels were quantified using TaqMan qPCR, using the appropriately designed primers and probes. PPIB (housekeeping gene) was used as an internal RNA loading control, results were calculated by the comparative Ct method, where the difference between the target gene Ct value and the PPIB Ct value (ΔCt) is calculated and then further normalized relative to the PBS control group by taking a second difference (ΔΔCt).

Quantitation of tissue siRNA concentrations was determined using a stem-loop qPCR assay as described in the methods section. The antisense strand of the siRNA was reverse transcribed using a TaqMan MicroRNA reverse transcription kit using a sequence-specific stem-loop RT primer. The cDNA from the RT step was then utilized for real-time PCR and Ct values were transformed into plasma or tissue concentrations using the linear equations derived from the standard curves.

Results

The data are summarized in FIG. 33-FIG. 35. The Atrogin-1 siRNA guide strands were able to mediate downregulation of the target gene in gastroc muscle when conjugated to an anti-TfR mAb targeting the transferrin receptor, see FIG. 33. Increasing the dose from 3 to 9 mg/kg reduced atrophy-induced Atrogin-1 mRNA levels 2-3 fold. The maximal KD achievable with this siRNA was 80% and a tissue concentration of 40 nM was needed to achieve maximal KD in atrophic muscles. This highlights the conjugate delivery approach is able to change disease induce mRNA expression levels of Atrogin-1 (see FIG. 34), by increasing the increasing the dose. FIG. 35 highlights that mRNA down regulation is mediated by RISC loading of the Atrogin-1 guide strands and is concentration dependent.

Conclusions

In this example, it was demonstrated that a TfR1-Atrogin-1 conjugates, after in vivo delivery, mediated specific down regulation of the target gene in gastroc muscle in a dose dependent manner. After induction of atrophy the conjugate was able to mediate disease induce mRNA expression levels of Atrogin-1 at the higher doses. Higher RISC loading of the Atrogin-1 guide strand correlated with increased mRNA downregulation.

US11872287B2. Compositions and methods of treating muscle atrophy and myotonic dystrophy (2024-01-16). Avidity Biosciences, Inc. [US]. Inventors: Andrew John Geall [US], Venkata Doppalapudi [US], David Sai-Ho Chu [US], Michael Caramian Cochran [US], Michael Hood [US], Beatrice Diana Darimont [US], Rob Burke [US], Yunyu Shi [US], Gulin Erdogan Marelius [US], Barbora Malecova [US].
Full text: Click here
Patent 2024
Acetate Anions Antibody Formation Antigens Atrophy Biological Assay Borates Buffers Carbohydrates Chromatography Complementary RNA Complement System Proteins Cysteine Dexamethasone Dinucleoside Phosphates DNA, Complementary Down-Regulation Ethanol Ethylmaleimide Freezing Genes Genes, Housekeeping High-Performance Liquid Chromatographies Immunoglobulins Injections, Intraperitoneal maleimide MicroRNAs Mus Muscle, Gastrocnemius Muscle Tissue Muscular Atrophy Nitrogen Obstetric Delivery Oligonucleotide Primers Pentetic Acid Phosphates Plasma PPIB protein, human Prospective Payment Assessment Commission Real-Time Polymerase Chain Reaction Retention (Psychology) Reverse Transcription RNA, Messenger RNA, Small Interfering RNA-Induced Silencing Complex RNA Interference Sodium Chloride Solvents Stem, Plant STS protein, human Sulfhydryl Compounds Sulfoxide, Dimethyl TFRC protein, human Tissues Transferrin tris(2-carboxyethyl)phosphine Tromethamine
2
Enhancing Aerobic Performance Recovery
Not available on PMC !

Example 3

Aerobic Exercise Recovery: Nine male, endurance-trained cyclists perform an interval workout followed by 4 hr. of recovery, and a subsequent endurance trial to exhaustion at 70% VO2 max, on three separate days.

Immediately following the first exercise bout and 2 hr. of recovery, subjects drink iso-volumic amounts of WCAP, protein and fluid replacement drink (FR), or carbohydrate replacement drink (CR), in a single-blind, randomized design. Carbohydrate content is equivalent for WCAP and CR and protein content is equivalent for WCAP and FR. Time to exhaustion (TTE), average heart rate (HR), rating of perceived exertion (RPE), and total work (WT) for the endurance exercise were compared between trials. TTE and WT are significantly greater for the WCAP group compared to the FR and CR groups. This suggests that WCAP is an effective recovery aid between two exhausting aerobic exercise bouts, and that WCAP increases exercise stamina.

US11857553B2. Chromium containing compositions for improving health and fitness (2024-01-02). NUTRITION 21, LLC [US]. Inventors: James R. Komorowski [US].
Full text: Click here
Patent 2024
Carbohydrates Chromium Exercise, Aerobic Males Proteins Rate, Heart Visually Impaired Persons
3
Biochemical Markers for Alcohol Use
Not available on PMC !

Example 22

Clinicians can use several biochemical measurements to objectively assess patients' current or past alcohol use. Several more experimental markers hold promise for measuring acute alcohol consumption and relapse. These include certain alcohol byproducts, such as acetaldehyde, ethyl glucuronide (EtG), and fatty acid ethyl esters (FAEE), as well as two measures of sialic acid, a carbohydrate that appears to be altered in alcoholics (Peterson K, Alcohol Research and Health, 2005). Clinicians have had access to a group of biomarkers that indicate a person's alcohol intake. Several of these reflect the activity of certain liver enzymes: serum gamma-glutamyltransferase (GGT), aspartate aminotransferase (AST), alanine aminotransferase (ALT), and carbohydrate-deficient transferrin (CDT), a protein that has received much attention in recent years. Another marker, N-acetyl-β-hexosaminidase (beta-Hex), indicates that liver cells, as well as other cells, have been breaking down carbohydrates, which are found in great numbers in alcohol (Javors and Johnson 2003).

In some embodiments the disclosed device focuses on detecting markers associated with alcohol abuse from menstrual blood or cervicovaginal fluid.

US11864740B2. Sample collection and preservation devices, systems and methods (2024-01-09). NextGen Jane, Inc. [US]. Inventors: Ridhi Tariyal [US], Stephen K. Gire [US].
Full text: Click here
Patent 2024
Abuse, Alcohol Acetaldehyde Alcoholics Aspartate Transaminase Attention beta-N-Acetylhexosaminidase Biological Markers BLOOD carbohydrate-deficient transferrin Carbohydrates Cells D-Alanine Transaminase enzyme activity Esters Ethanol ethyl glucuronide Fatty Acids gamma-Glutamyl Transpeptidase Hepatocyte Liver Medical Devices Menstruation N-Acetylneuraminic Acid Patients Relapse Serum Staphylococcal Protein A
4
Reduced Gluten and Carb Composite Flours
Not available on PMC !

Example 10

Reduced gluten and reduced carbohydrate composite plant-MCT flour is made by replacing 5-50% of the gluten flour in Examples 1-7 with one or more gluten-free and low carbohydrate flours selected from coconut flour, almond flour, peanut flour, sesame flour, sunflower seed flower, hazelnut flour, walnut flour, soy flour, chickpea flour, flaxseed (linseed) flour, fava bean flour, pumpkin seed flour, lupine flour, red lentil flour, or white bran flour.

US11871773B1. Composite plant-MCT flour, method of manufacture, and food products made therefrom (2024-01-16). INNOVATIVE FLOURS, LLC [US]. Inventors: Gary Millet [US], Kylin Liao [CN].
Full text: Click here
Patent 2024
Almond Flour Arachis hypogaea Carbohydrates Chickpea Coconut Flour Food Gluten Gluten-Free Diet Hazelnuts Helianthus annuus Juglans Lentils Lupinus Plants Pumpkins Sesame Vicia faba
5
Optimizing siRNA Potency and Conjugation
Not available on PMC !

Example 20

All siRNA single strands were fully assembled on solid phase using standard phospharamidite chemistry and purified using HPLC. Base, sugar and phosphate modifications that are well described in the field of RNAi were used to optimize the potency of the duplex and reduce immunogenicity. All the siRNA passenger strands contained a C6-NH2 conjugation handle on the 5′ end, see FIG. 20A-FIG. 21B. For the 21mer duplex with 19 bases of complementarity and 3′ dinucleotide overhangs, the conjugation handle was connected to siRNA passenger strand via an inverted abasic phosphodiester, see FIG. 20A-FIG. 20B for the structures. For the blunt ended duplex with 19 bases of complementarity and one 3′ dinucleotide overhang the conjugation handle was connected to siRNA passenger strand via a phosphodiester on the terminal base, see FIG. 21A-FIG. 21B for the structures.

Purified single strands were duplexed to get the double stranded siRNA.

US11872287B2. Compositions and methods of treating muscle atrophy and myotonic dystrophy (2024-01-16). Avidity Biosciences, Inc. [US]. Inventors: Andrew John Geall [US], Venkata Doppalapudi [US], David Sai-Ho Chu [US], Michael Caramian Cochran [US], Michael Hood [US], Beatrice Diana Darimont [US], Rob Burke [US], Yunyu Shi [US], Gulin Erdogan Marelius [US], Barbora Malecova [US].
Full text: Click here
Patent 2024
Anabolism Antigens Carbohydrates Complement System Proteins Dinucleoside Phosphates High-Performance Liquid Chromatographies Phosphates RNA, Small Interfering RNA Interference

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1
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2
Fetal bovine serum (fbs) by Thermo Fisher Scientific
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3
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8
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More about "Carbohydrates"

Carbohydrates are a class of macromolecules consisting of carbon, hydrogen, and oxygen atoms.
These organic compounds serve as a primary energy source for the body and play crucial roles in various biological processes, such as cell signaling, structure, and immune function.
Carbohydrates can be classified into different types, including monosaccharides (e.g., glucose, fructose), disaccharides (e.g., sucrose, lactose), and polysaccharides (e.g., starch, glycogen).
The study of carbohydrates is essential for understanding human nutrition, metabolic disorders, and the development of therapeutic interventions.
Researchers in this field utilize advanced analytical techniques and bioinformatic tools, such as PubCompare.ai, to optimize research protocols and enhance the reproducibility of carbohydrate studies.
PubCompare.ai is an AI-driven platform that helps researchers in the carbohydrate field to easily locate and compare protocols from literature, pre-prints, and patents, allowing them to identify the best methodologies and products.
The cutting-edge AI algorithms used by PubCompare.ai take the guesswork out of research, helping researchers achieve more reliable and reproducible results.
Key topics related to carbohydrates include monosaccharides (e.g., glucose, fructose), disaccharides (e.g., sucrose, lactose), polysaccharides (e.g., starch, glycogen), cell signaling, immune function, metabolic disorders (e.g., diabetes), and nutritional studies.
Researchers may also utilize related terms and concepts, such as FBS (fetal bovine serum), STZ (streptozotocin), D12451 (high-fat diet), C57BL/6J mice, HFD (high-fat diet), and MacConkey agar.
By leveraging the insights and tools provided by PubCompare.ai, researchers can elevate their carbohydrate studies, achieving more reliable and reproducible results that advance our understanding of these essential biomolecules.