Protocol full text hidden due to copyright restrictions
Open the protocol to access the free full text link
>
Anatomy
>
Body System
>
Renin-Angiotensin-Aldosterone System
Renin-Angiotensin-Aldosterone System
The Renin-Angiotensin-Aldosterone System (RAAS) is a critical physiological pathway that regulates blood pressure, fluid and electrolyte balance, and cardiovascular homeostasis.
This complex hormonal system involves the kidneys, adrenal glands, and cardiovascular system.
Key components include the enzymes renin and angiotensin-converting enzyme (ACE), the peptide hormones angiotensin and aldosterone, and their receptors.
Dysregulation of the RAAS has been implicated in the pathogenesis of hypertension, heart failure, kidney disease, and other cardiovascular disorders.
Understading the RAAS is crucial for developing effective therapeutic interventions targeting this system.
PubComapre.ai's AI-driven tools can help researchers quickly locate the best published protocols, pre-prinnts, and patents related to the RAAS, boosting research accuracy and efficiency.
This complex hormonal system involves the kidneys, adrenal glands, and cardiovascular system.
Key components include the enzymes renin and angiotensin-converting enzyme (ACE), the peptide hormones angiotensin and aldosterone, and their receptors.
Dysregulation of the RAAS has been implicated in the pathogenesis of hypertension, heart failure, kidney disease, and other cardiovascular disorders.
Understading the RAAS is crucial for developing effective therapeutic interventions targeting this system.
PubComapre.ai's AI-driven tools can help researchers quickly locate the best published protocols, pre-prinnts, and patents related to the RAAS, boosting research accuracy and efficiency.
Most cited protocols related to «Renin-Angiotensin-Aldosterone System»
Cell Respiration
Coffee
Electrocardiography, Ambulatory
Nervous System, Autonomic
physiology
Pressoreceptors
Rate, Heart
Renin-Angiotensin-Aldosterone System
Twins
A planned 6-year, single-center, randomized, double-blind, placebo-controlled, clinical trial compared the effect of losartan (Cozaar; Merck) versus placebo on development and progression of diabetic nephropathy in type 2 diabetes. Subjects were stratified at baseline by albumin excretion category (normoalbuminuria: albumin/creatinine ratio [ACR] <30 mg/g; microalbuminuria: ACR 30–299 mg/g) based on the geometric mean of three screening measurements and were allocated randomly to receive either losartan or placebo within each category. The prespecified primary study outcome was a decline in GFR to ≤60 mL/min or to half the baseline value in subjects who entered the study with GFR <120 mL/min. Another study outcome was the difference between treatment groups in predefined glomerular structural variables measured on kidney biopsy samples obtained at the end of treatment. Subjects were enrolled between 1996 and 2001, the last biopsy was performed in 2007, and morphometric evaluation was completed in 2012. Progression to macroalbuminuria (ACR ≥300 mg/g) also was examined as an outcome.
Treatment group was assigned by computer-generated random blocks of <10 subjects stratified by albuminuria category. Treatment with losartan began at 50 mg daily, with the dose increasing to 100 mg daily after 1 week if symptomatic hypotension did not develop. A placebo corresponding to each dose of losartan was supplied. Compliance was assessed by pill counts, and subjects were considered compliant if ≥50% of study drug was used. Clinical care was provided outside the study in accordance with existing clinical care guidelines while avoiding the use of ACE inhibitors or ARBs for management of hypertension. In 2000, changes in standards of care and new evidence of cardiovascular protection by treatment with ACE inhibitors in similar patients threatened continuation of the study, because treatment with either an ACE inhibitor or an ARB was recommended for patients with diabetes and microalbuminuria (7 (link),8 (link)). Accordingly, the protocol was modified to suggest that primary care providers consider adding inhibitors of the renin-angiotensin-aldosterone system (RAAS) to the masked treatment regimen of study subjects.
Women were tested quarterly for pregnancy. Each woman with childbearing potential was instructed to stop the study drug if she thought she might be pregnant and to notify the study team for confirmatory testing. If a woman became pregnant while using treatment, then the treatment was withheld. If requested by the woman or her health care provider, then the treatment code was broken and the subject was informed whether she was receiving active drug or placebo. GFR was not measured in women who were pregnant. In those who remained blinded to treatment category, both treatment and GFR measurements were resumed 3 months postpartum or after completion of breastfeeding, whichever was later. In the one patient who was unblinded, unmasked treatment with losartan was reinitiated.
Losartan and placebo were provided by Merck. The study was approved by the Institutional Review Board of the National Institute of Diabetes and Digestive and Kidney Diseases and was overseen by a safety monitoring board. Each subject gave informed consent at each renal clearance study and before kidney biopsy.
Treatment group was assigned by computer-generated random blocks of <10 subjects stratified by albuminuria category. Treatment with losartan began at 50 mg daily, with the dose increasing to 100 mg daily after 1 week if symptomatic hypotension did not develop. A placebo corresponding to each dose of losartan was supplied. Compliance was assessed by pill counts, and subjects were considered compliant if ≥50% of study drug was used. Clinical care was provided outside the study in accordance with existing clinical care guidelines while avoiding the use of ACE inhibitors or ARBs for management of hypertension. In 2000, changes in standards of care and new evidence of cardiovascular protection by treatment with ACE inhibitors in similar patients threatened continuation of the study, because treatment with either an ACE inhibitor or an ARB was recommended for patients with diabetes and microalbuminuria (7 (link),8 (link)). Accordingly, the protocol was modified to suggest that primary care providers consider adding inhibitors of the renin-angiotensin-aldosterone system (RAAS) to the masked treatment regimen of study subjects.
Women were tested quarterly for pregnancy. Each woman with childbearing potential was instructed to stop the study drug if she thought she might be pregnant and to notify the study team for confirmatory testing. If a woman became pregnant while using treatment, then the treatment was withheld. If requested by the woman or her health care provider, then the treatment code was broken and the subject was informed whether she was receiving active drug or placebo. GFR was not measured in women who were pregnant. In those who remained blinded to treatment category, both treatment and GFR measurements were resumed 3 months postpartum or after completion of breastfeeding, whichever was later. In the one patient who was unblinded, unmasked treatment with losartan was reinitiated.
Losartan and placebo were provided by Merck. The study was approved by the Institutional Review Board of the National Institute of Diabetes and Digestive and Kidney Diseases and was overseen by a safety monitoring board. Each subject gave informed consent at each renal clearance study and before kidney biopsy.
Albumins
Angiotensin-Converting Enzyme Inhibitors
Biopsy
Cardiovascular System
Clinical Trials Data Monitoring Committees
Contraceptives, Oral
Cozaar
Creatinine
Diabetes Mellitus
Diabetes Mellitus, Non-Insulin-Dependent
Diabetic Nephropathy
Digestive System
Disease Progression
Ethics Committees, Research
Health Personnel
High Blood Pressures
inhibitors
Kidney
Kidney Diseases
Kidney Glomerulus
Losartan
Patients
Pharmaceutical Preparations
Placebos
Pregnancy
Primary Health Care
Renin-Angiotensin-Aldosterone System
Treatment Protocols
Woman
Members from a multidisciplinary working group reviewed available phenotype data from NHANES III, performed systematic literature reviews, and identified candidate genes and physiologic pathways thought to be associated with diseases of public health significance at the time of project initiation. The selection of polymorphisms for this study was also based upon input from the SNP500Cancer resource (45 (link)), which had already developed genotyping assays for numerous SNPs in the selected genes based on their potential importance to physiologic processes, epidemiologic studies, and health outcomes.
The selected variants are in genes that encode proteins in 6 major cellular and physiologic pathways: 1) nutrient metabolism (e.g., homocysteine, lipids, glucose, and alcohol); 2) immune and inflammatory responses; 3) xenobiotic metabolism (e.g., of drugs, carcinogens, or environmental contaminants); 4) DNA repair; 5) hemostasis and the renin-angiotensin-aldosterone system; and 6) oxidative stress. The variants are in pathways affecting the development of multiple diseases, including cardiovascular disease, diabetes, cancer, and infectious diseases, as well as modulation of the effects of environmental and occupational exposures.
The selected variants are in genes that encode proteins in 6 major cellular and physiologic pathways: 1) nutrient metabolism (e.g., homocysteine, lipids, glucose, and alcohol); 2) immune and inflammatory responses; 3) xenobiotic metabolism (e.g., of drugs, carcinogens, or environmental contaminants); 4) DNA repair; 5) hemostasis and the renin-angiotensin-aldosterone system; and 6) oxidative stress. The variants are in pathways affecting the development of multiple diseases, including cardiovascular disease, diabetes, cancer, and infectious diseases, as well as modulation of the effects of environmental and occupational exposures.
Biological Assay
Carcinogens
Cardiovascular Diseases
Cells
Communicable Diseases
Developmental Disabilities
Diabetes Mellitus
DNA Repair
Ethanol
Genes
Genetic Polymorphism
Glucose
Hemostasis
Homocysteine
Inflammation
Lipids
Malignant Neoplasms
Metabolism
Nutrients
Occupational Exposure
Oxidative Stress
Pharmaceutical Preparations
Phenotype
Physiological Processes
physiology
Proteins
Renin-Angiotensin-Aldosterone System
Single Nucleotide Polymorphism
Xenobiotics
Urine protein excretion per day (i.e. urinary protein–creatinine ratio or 24-h proteinuria, whichever was available), eGFR [calculated using the CKD Epidemiology Collaboration (CKD-EPI) formula] [15 (link)], body mass index, age, gender, presence of hypertension, blood pressure, prior use of medications that block the renin–angiotensin–aldosterone system and prior use of immunosuppressive agents (such as steroids) were determined at time of baseline urine sample collection and during follow-up. Annual eGFR slope after the baseline visit (i.e. during follow-up) was calculated by fitting a straight line through the calculated eGFR using linear regression and the principle of least squares. The total cohort of 209 subjects was divided into tertiles according to the annual eGFR slope. Patients in the lowest eGFR slope tertile (i.e. highest loss of kidney function after baseline) were defined as progressors, patients in the highest eGFR slope tertile (i.e. nearly no loss of kidney function after baseline) were defined as non-progressors, all other were defined as intermediate. When planning the study, we performed a power calculation, which revealed that 29 samples per group were sufficient to detect a 30% change in peptide abundance, with a Type I error of 0.05 and 80% power. We randomly divided the 140 samples from progressors and non-progressors into a training set (n = 94, 47 progressors and 47 non-progressors) for biomarker discovery and a test set (n = 46, 23 progressors and 23 non-progressors) for the validation study (Figure 1A ). Randomization was performed using the Excel randomization (RAND) function (Microsoft, Redmond, WA, USA). There were no significant differences in the clinical characteristics between the subjects from the training set and from the test set (data not shown). The CE-MS data of the training set were used for the definition of peptides being significantly differentially abundant between progressors and non-progressors (Figure 1B ) and for the generation of the classifier. The generated classifier was then validated in the test set.
Biological Markers
Blood Pressure
Cardiac Arrest
Chronic Kidney Diseases
Creatinine
EGFR protein, human
Gender
High Blood Pressures
Immunosuppressive Agents
Index, Body Mass
Patients
Peptides
Pharmaceutical Preparations
Proteins
Renin-Angiotensin-Aldosterone System
Steroids
Synapsin I
Urine
Urine Specimen Collection
Adult
Eligibility Determination
Kidney
Placebos
Polycystic Kidney, Autosomal Dominant
Renin-Angiotensin-Aldosterone System
Most recents protocols related to «Renin-Angiotensin-Aldosterone System»
Statistical analysis was performed with Statistical Package for Social Sciences, version 24.0 (IBM, Armonk, NY). Categorical variables were expressed as percentage, whereas continuous variables were presented as median (interquartile range) (nonnormal distribution) or mean±SD (normal distribution). Descriptive characteristics were compared between the 2 groups using χ2, Kruskal‐Wallis, and independent‐sample t tests for categorical, nonnormally distributed, and normally distributed variables, respectively. Kaplan‐Meier analysis was performed to calculate the incidence of adverse end points, with a log‐rank test assessing the differences. Cox regression analysis was constructed to compare the risks of adverse events. Covariates in the multivariate analysis included age, body weight, systolic blood pressure, heart rate, coronary artery disease, diabetes, hemoglobin, urea, BNP (B‐type natriuretic peptide), high‐sensitivity troponin I, left ventricular end‐diastolic diameter, mitral Doppler early velocity/mitral annular early velocity, time interval between echocardiograms, spironolactone, loop diuretic, aspirin, statins, nitrate, cardiac resynchronization therapy, which were statistically different at baseline between the groups. Additional covariates adjusted for clinically relevant characteristics, including atrial fibrillation, β‐blockers, and renin‐angiotensin‐aldosterone system blockers. For the model comparing the risks of adverse outcomes between the LARR and no‐LAAR groups, covariates included age, sex, BNP, and LVEF. Hazard ratio (HR) with 95% CI were presented. Logistic regression analysis was used to identify the independent factors that predict LA reverse remodeling. A 2‐sided P value <0.05 was considered to be statistically different.
Aspirin
Atrial Fibrillation
Body Weight
Cardiac Resynchronization Therapy
Coronary Artery Disease
Diabetes Mellitus
Diastole
Echocardiography
Hemoglobin
Hydroxymethylglutaryl-CoA Reductase Inhibitors
Hypersensitivity
Left Ventricles
Loop Diuretics
Nitrates
Rate, Heart
Renin-Angiotensin-Aldosterone System
Spironolactone
Systolic Pressure
Troponin I
Urea
Sex was derived from the municipality registry and classified as man or woman.
Ethnicity was defined by registered country of birth, combined with the registered parental countries of birth. Participants of Dutch, Surinamese, Ghanaian, Moroccan, and Turkish origin were included. A participant was defined as belonging to one of the included ethnic minority groups if he/she fulfilled one of two criteria: (1) he/she was born outside the Netherlands and has at least one parent born outside the Netherlands (first generation) or (2) he/she was born in the Netherlands but both parents were born outside the Netherlands (second generation). For the Dutch sample, we invited people who were born in the Netherlands and whose parents were born in the Netherlands. After data collection, Surinamese participants were further classified according to self-reported ethnic origin into “African”, “South-Asian”, “Javanese”, or “other”.
Smoking status was based on self-report (‘Do you smoke?’) and classified as current (‘Yes, daily’), former (‘No, but I used to’), and never smoker (‘No, I never smoked’).
Educational level (as domain of socioeconomic status) was based on the self-reported highest qualification attained in the Netherlands or in the country of origin and categorized into four groups: 1) no or elementary, 2) lower vocational or lower secondary, 3) intermediate vocational or intermediate or higher secondary, and 4) higher vocational or university. Family history of CVD was defined by a self-reported CVD diagnosis among first degree family members aged <60 years. Participants were asked to bring their prescribed medications to the research location, which were categorized using the Anatomical Therapeutic Chemical (ATC) classification system. Blood pressure-lowering medication included centrally acting antihypertensives (ATC code C02), diuretics (C03), beta-blockers (C07), calcium channel blockers (C08) and agents acting on the renin–angiotensin–aldosterone system (C09). Glucose-lowering medication was classified as ATC code A10. Lipid-lowering medication was classified as ATC code C10.
Ethnicity was defined by registered country of birth, combined with the registered parental countries of birth. Participants of Dutch, Surinamese, Ghanaian, Moroccan, and Turkish origin were included. A participant was defined as belonging to one of the included ethnic minority groups if he/she fulfilled one of two criteria: (1) he/she was born outside the Netherlands and has at least one parent born outside the Netherlands (first generation) or (2) he/she was born in the Netherlands but both parents were born outside the Netherlands (second generation). For the Dutch sample, we invited people who were born in the Netherlands and whose parents were born in the Netherlands. After data collection, Surinamese participants were further classified according to self-reported ethnic origin into “African”, “South-Asian”, “Javanese”, or “other”.
Smoking status was based on self-report (‘Do you smoke?’) and classified as current (‘Yes, daily’), former (‘No, but I used to’), and never smoker (‘No, I never smoked’).
Educational level (as domain of socioeconomic status) was based on the self-reported highest qualification attained in the Netherlands or in the country of origin and categorized into four groups: 1) no or elementary, 2) lower vocational or lower secondary, 3) intermediate vocational or intermediate or higher secondary, and 4) higher vocational or university. Family history of CVD was defined by a self-reported CVD diagnosis among first degree family members aged <60 years. Participants were asked to bring their prescribed medications to the research location, which were categorized using the Anatomical Therapeutic Chemical (ATC) classification system. Blood pressure-lowering medication included centrally acting antihypertensives (ATC code C02), diuretics (C03), beta-blockers (C07), calcium channel blockers (C08) and agents acting on the renin–angiotensin–aldosterone system (C09). Glucose-lowering medication was classified as ATC code A10. Lipid-lowering medication was classified as ATC code C10.
Full text: Click here
Adrenergic beta-Antagonists
Antihypertensive Agents
Blood Pressure
Calcium Channel Blockers
Diagnosis
Diuretics
Ethnicity
Family Member
Glucose
Lipids
Minority Groups
Negroid Races
Parent
Pharmaceutical Preparations
Renin-Angiotensin-Aldosterone System
South Asian People
Therapeutics
Woman
The variables were CKD-related factors and medications in the EMR data [4 ,25 –28 ]. They were selected for global use on the basis of their being common measurements used at outpatient clinics and ease of data input by users at implementation. The variables with more than 20% of their time-series data missing were not included in the analysis, because these variables were considered not to be usually measured at clinical settings.
The following variables were used in the analysis as follows (S7 Table ): age; gender; DM; hypertension; history of CVD; eGFR; serum albumin, sodium, potassium, calcium, phosphorus, low-density lipoprotein, and uric acid levels; white blood cell count; hemoglobin level; urinary protein-to-creatinine ratio (UPCR); and use of renin-angiotensin-aldosterone system inhibitors, phosphorus absorbents, vitamin D, statins, uric-acid-lowering medicines, and erythropoietin-stimulating agents. The primary outcome was ESKD or death. If no outcomes were observed within the follow-up period, the observation data were treated as censored data. The onset of ESKD was defined as the initiation of renal replacement therapy. None of the patients in this study had received a kidney transplantation.
eGFR was calculated using the equation for the Japanese population on the basis of the serum creatinine level measured using the enzymatic method [29 (link)]. The baseline data were defined as the first measurements within 30 days of the initial eGFR. KFRE was calculated using eGFR, age, gender, and natural logarithm (urine albumin-to-creatinine ratio, UACR) [14 (link)]. Negative values of KFRE were treated as zero. Because the Japanese national health insurance covers UACR measurement only for DM patients, UACR was estimated from the UPCR using Weaver et al.’s estimation formulae [30 (link)]. The last observation data carried forward were input in place of all missing time-series data.
The following variables were used in the analysis as follows (
eGFR was calculated using the equation for the Japanese population on the basis of the serum creatinine level measured using the enzymatic method [29 (link)]. The baseline data were defined as the first measurements within 30 days of the initial eGFR. KFRE was calculated using eGFR, age, gender, and natural logarithm (urine albumin-to-creatinine ratio, UACR) [14 (link)]. Negative values of KFRE were treated as zero. Because the Japanese national health insurance covers UACR measurement only for DM patients, UACR was estimated from the UPCR using Weaver et al.’s estimation formulae [30 (link)]. The last observation data carried forward were input in place of all missing time-series data.
Full text: Click here
Albumins
Calcium
Creatinine
EGFR protein, human
Enzymes
Erythropoietin
Gender
Hemoglobin
High Blood Pressures
Hydroxymethylglutaryl-CoA Reductase Inhibitors
inhibitors
Japanese
Kidney Transplantation
Leukocyte Count
Low-Density Lipoproteins
National Health Insurance
Patients
Pharmaceutical Preparations
Phosphorus
Potassium
Proteins
Renal Replacement Therapy
Renin-Angiotensin-Aldosterone System
Serum
Serum Albumin
Sodium
Uric Acid
Urine
Vitamin D
Among the baseline characteristics, categorical variables such as sex, underlying comorbidities, and medications were compared between groups using chi-squared tests. Continuous variables were compared using Student’s t test for normally distributed variables and the Mann–Whitney U test for non-normally distributed variables. We performed multivariate imputation by chained equations to impute missing values with five imputed data sets and 50 iterations [28 (link), 29 (link)]. For matched cohort analysis, we used 1:2 propensity score matching of individuals from the low and high TCO2 groups [30 (link), 31 (link)]. The covariates used in the propensity score were as follows: age, sex, eGFR, respiratory infection, bacteremia, endocarditis, central nervous system infection, skin infection, pelvic inflammatory disease, genitourinary tract infection, intra-abdominal infection, septic shock, intensive care unit admission, use of mechanical ventilation, inotropes use, hypertension, coronary artery disease, diabetes mellitus, congestive heart failure, autoimmune disease, chronic obstructive pulmonary disease, obstructive sleep apnea syndrome, malignancy, CCI score, calcium channel blockers, alpha blockers, beta blockers, renin–angiotensin–aldosterone system inhibitors, diuretics, statins, nonsteroidal anti-inflammatory drugs, proton-pump inhibitors, antiplatelets, anticoagulants, and follow-up period. In addition, we calculated propensity scores for the likelihood of sepsis survivors with high and low TCO2 by including clinical covariates in a multivariate logistic regression model (Table S1 in the supplementary material). The standardized mean difference was calculated to assess the balance between sepsis survivors with high and low TCO2 after matching, and a difference of less than 0.1 in the score was considered to be well balanced [32 (link), 33 (link)]. Cox regression was used to obtain hazard ratios (HRs) for the evaluation of relative risks of outcomes in the two study groups. All analyses were performed using the SAS statistical software (version 9.4; SAS Institute, Cary, NC, USA) and R software (version 3.5.2 for Windows; R Foundation for Statistical Computing, Vienna, Austria. The significance level was set to p < 0.05.
Adrenergic alpha-Antagonists
Adrenergic beta-Antagonists
Anti-Inflammatory Agents, Non-Steroidal
Anticoagulants
Autoimmune Diseases
Bacteremia
Calcium Channel Blockers
Cellulitis
Central Nervous System Infection
Chronic Obstructive Airway Disease
Congestive Heart Failure
Coronary Artery Disease
Diabetes Mellitus
dioxotechnetium
Diuretics
EGFR protein, human
Endocarditis
High Blood Pressures
Hydroxymethylglutaryl-CoA Reductase Inhibitors
Infection
inhibitors
Inotropism
Intraabdominal Infections
Malignant Neoplasms
Mechanical Ventilation
Pelvic Inflammatory Disease
Pharmaceutical Preparations
Proton Pump Inhibitors
Renin-Angiotensin-Aldosterone System
Respiratory Tract Infections
Sepsis
Septic Shock
Sleep Apnea, Obstructive
Student
Survivors
Urinary Tract
On the basis of their post-discharge TCO2 levels, the sepsis survivors were divided into high TCO2 (≥ 18 mmol/L) and low TCO2 (< 18 mmol/L) groups. The following baseline variables were recorded: age, sex, eGFR, sources of infection, septic shock, intensive care unit admission, use of mechanical ventilation, use of inotropes, hypertension, coronary artery disease, diabetes mellitus, congestive heart failure, autoimmune disease, chronic obstructive pulmonary disease, obstructive sleep apnea syndrome, malignancy, Charlson comorbidity index (CCI) score, use of calcium channel blockers, alpha blockers, beta blockers, renin–angiotensin–aldosterone system inhibitors, diuretics, statins, non-steroidal anti-inflammatory drugs, proton pump inhibitors, antiplatelets, and anticoagulants.
Adrenergic alpha-Antagonists
Adrenergic beta-Antagonists
Anti-Inflammatory Agents, Non-Steroidal
Anticoagulants
Autoimmune Diseases
Calcium Channel Blockers
Chronic Obstructive Airway Disease
Congestive Heart Failure
Coronary Arteriosclerosis
Diabetes Mellitus
dioxotechnetium
Diuretics
EGFR protein, human
High Blood Pressures
Hydroxymethylglutaryl-CoA Reductase Inhibitors
Infection
inhibitors
Inotropism
Malignant Neoplasms
Mechanical Ventilation
Patient Discharge
Proton Pump Inhibitors
Renin-Angiotensin-Aldosterone System
Septicemia
Septic Shock
Sleep Apnea, Obstructive
Survivors
Top products related to «Renin-Angiotensin-Aldosterone System»
Sourced in United States, Japan, Austria
JMP version 13 is a data analysis software developed by SAS Institute. It provides tools for data exploration, visualization, and statistical analysis. JMP 13 allows users to import, manipulate, and analyze data from various sources.
Sourced in United States
The Free Fatty Acid Fluorometric Assay is a laboratory tool used to measure the concentration of free fatty acids in a sample. It provides a quantitative analysis of free fatty acid levels without interpretation or extrapolation of the intended use.
Sourced in Germany, Switzerland, United Kingdom, Japan, France, Sweden
The Cobas analyzer is a laboratory instrument manufactured by Roche. It is designed for the automated analysis of various clinical chemistry and immunoassay parameters. The Cobas analyzer provides accurate and reliable results, enabling healthcare professionals to make informed decisions in patient care.
Sourced in Switzerland, Germany, United States, Japan, France, Italy, China, United Kingdom, Sweden
The Cobas 8000 is a modular, automated in-vitro diagnostic system designed for high-throughput clinical chemistry and immunochemistry testing. It is used to perform a wide range of laboratory tests, including those for chemistry, immunoassay, and electrolyte analysis. The Cobas 8000 is capable of processing a large volume of samples efficiently and accurately.
Sourced in Taiwan, Province of China, China
KA3836 is a high-performance liquid chromatography (HPLC) system designed for precise and efficient separation and analysis of various chemical compounds. Its core function is to provide consistent and reliable chromatographic separation, enabling accurate quantitative and qualitative analysis of samples.
Sourced in United States
Ab-100573 is a protein-based lab equipment product. It functions as a core component for various laboratory procedures.
Sourced in United States
Ab-100756 is a laboratory instrument used for sample preparation and analysis. Its core function is to perform high-throughput sample processing. This product is suitable for a variety of applications in research and clinical settings.
Sourced in United States
Ab65356 is a laboratory equipment product. It is designed for a specific core function, but a detailed description cannot be provided while maintaining an unbiased and factual approach without extrapolation. Therefore, a detailed description is not available.
Sourced in United States, United Kingdom, Japan, Thailand, China, Italy, Germany
SPSS version 18.0 is a statistical software package developed by IBM. It provides data management, analysis, and reporting capabilities. The core function of SPSS is to assist in the analysis of data and presentation of results.
More about "Renin-Angiotensin-Aldosterone System"
The Renin-Angiotensin-Aldosterone System (RAAS) is a crucial physiological pathway that plays a vital role in regulating blood pressure, fluid and electrolyte balance, and cardiovascular homeostasis.
This complex hormonal system involves the kidneys, adrenal glands, and cardiovascular system, and its key components include the enzymes renin and angiotensin-converting enzyme (ACE), the peptide hormones angiotensin and aldosterone, and their receptors.
Dysregulation of the RAAS has been implicated in the pathogenesis of various cardiovascular disorders, such as hypertension, heart failure, and kidney disease.
Understanding the intricate workings of the RAAS is crucial for developing effective therapeutic interventions targeting this system.
PubCompare.ai's AI-driven tools can help researchers quickly locate the best published protocols, pre-prints, and patents related to the RAAS, boosting research accuracy and efficiency.
These tools can be particularly useful in analyzing data from JMP version 13, Free Fatty Acid Fluorometric Assay, Cobas analyzer, Cobas 8000, KA3836, Ab-100573, Ab-100756, and Ab65356, as well as SPSS version 18.0, to gain deeper insights into the RAAS and its implications in various health conditions.
By leveraging the power of AI-driven search and comparison tools, researchers can accelerate their understanding of the Renin-Angiotensin-Aldosterone System and its role in maintaining cardiovascular homeostasis, ultimately leading to more effective treatment strategies and improved patient outcomes.
This complex hormonal system involves the kidneys, adrenal glands, and cardiovascular system, and its key components include the enzymes renin and angiotensin-converting enzyme (ACE), the peptide hormones angiotensin and aldosterone, and their receptors.
Dysregulation of the RAAS has been implicated in the pathogenesis of various cardiovascular disorders, such as hypertension, heart failure, and kidney disease.
Understanding the intricate workings of the RAAS is crucial for developing effective therapeutic interventions targeting this system.
PubCompare.ai's AI-driven tools can help researchers quickly locate the best published protocols, pre-prints, and patents related to the RAAS, boosting research accuracy and efficiency.
These tools can be particularly useful in analyzing data from JMP version 13, Free Fatty Acid Fluorometric Assay, Cobas analyzer, Cobas 8000, KA3836, Ab-100573, Ab-100756, and Ab65356, as well as SPSS version 18.0, to gain deeper insights into the RAAS and its implications in various health conditions.
By leveraging the power of AI-driven search and comparison tools, researchers can accelerate their understanding of the Renin-Angiotensin-Aldosterone System and its role in maintaining cardiovascular homeostasis, ultimately leading to more effective treatment strategies and improved patient outcomes.