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Healthy Volunteers

Healthy Voulnteers: Individuals who participate in research studies and clinical trials without any known medical conditions or diseases.
These participants provide valuable data to help researchers understand normal physiological processes, test new interventions, and advance scientific knowledge.
Healthy volunteers play a crucial role in the development of safe and effective treatments, contributing to the overall progress of biomedical research.

Most cited protocols related to «Healthy Volunteers»

1
16S rRNA Phylometagenomic Analysis of Normal Human Microbiome
Cited 805 times
The 16S rRNA-based phylometagenomic dataset of the normal (healthy) human microbiome was made available through the Human Microbiome Project [13 (link)], and consists of 454 FLX Titanium sequences spanning the V3 to V5 variable regions obtained for 301 samples from 24 healthy subjects (12 male, 12 female) enrolled at a single clinical site in Houston, TX. These samples cover 18 different body sites, including 6 main body site categories: the oral cavity (9 samples), the gut (1 sample), the vagina (3 samples), the retroauricular crease (2 samples), the nasal cavity (1 sample) and the skin (2 samples). Detailed protocols used for enrollment, sampling, DNA extraction, 16S amplification and sequencing are available on the Human Microbiome Project Data Analysis and Coordination Center website [103 ], and are also described elsewhere [55 ,56 (link)]. In brief, genomic DNA was isolated using the Mo Bio PowerSoil kit [104 ] and subjected to 16S amplifications using primers designed incorporating the FLX Titanium adapters and a sample barcode sequence, allowing directional sequencing covering variable regions V5 to partial V3 (primers: 357F 5'-CCTACGGGAGGCAGCAG-3' and 926R 5'-CCGTCAATTCMTTTRAGT-3'). Resulting sequences were processed using a data curation pipeline implemented in mothur [41 (link)], which reduces the sequencing error rate to less than 0.06% as validated on a mock community. As part of the pipeline parameters, to pass the initial quality control step, one unambiguous mismatch to the sample barcode and two mismatches to the PCR amplification primers were allowed. Sequences with an ambiguous base call or a homopolymer longer than eight nucleotides were removed from subsequent analyses, as suggested previously [105 (link)]. Based on the supplied quality scores, all sequences were trimmed when a base call with a score below 20 was encountered. All sequences were aligned using a NAST-based sequence aligner to a custom reference based on the SILVA alignment [106 (link),107 (link)]. Sequences that were shorter than 200 bp or that did not align to the anticipated region of the reference alignment were removed from further analysis. Chimeric sequences were identified using the mothur implementation of the ChimeraSlayer algorithm [108 (link)]. Unique reads were classified with the MSU RDP classifier v2.2 [58 (link)] using the taxonomy proposed by [109 ], maintained at the RDP (RDP 10 database, version 6). The 16S rRNA reads are available in the Sequence Read Archive at [110 ].
Segata N., Izard J., Waldron L., Gevers D., Miropolsky L., Garrett W.S, & Huttenhower C. (2011). Metagenomic biomarker discovery and explanation. Genome Biology, 12(6), R60.
Full text: Click here
Publication 2011
Base Sequence Chimera Females Genome Healthy Volunteers Human Body Human Microbiome Males Nasal Cavity Nucleotides Oligonucleotide Primers Oral Cavity RNA, Ribosomal, 16S Skin Titanium Vagina
2
Developing a 5-Level EQ-5D Version
Cited 514 times
The EuroQol Group task force recommended that English and Spanish versions be developed in parallel, where they could also serve as root languages for further translations and adaptations of the expanded version.
The study consisted of two phases. In the first phase, carried out from June to November 2007, a pool of potential labels for the new levels was identified and provisional labels for the 5-level version were chosen from that pool after a response scaling task carried out in face-to-face interviews with convenience samples of lay respondents. In the second phase, carried out from May to July 2008, face and content validity of two alternative 5-level systems were tested in focus group sessions with healthy participants and those with chronic illness. The second phase was also used to test the face validity of a series of health states based on the 5-level versions. Different groups of respondents were used in the two phases of the study.
Participants in both phases were recruited to ensure a wide range of socio-demographic characteristics. For the response scaling phase, the UK participants were recruited via local newspaper advertisements, local community advertisements, and from an existing participant database. The Spanish participants were recruited from among parents from local schools and from patient associations. Patient focus groups included primarily individuals with arthritis, diabetes, or asthma. In all groups, adequate written and oral fluency in English or Spanish was required.
Written informed consent to participate was obtained from all participants in both phases of the study.
Herdman M., Gudex C., Lloyd A., Janssen M., Kind P., Parkin D., Bonsel G, & Badia X. (2011). Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Quality of Life Research, 20(10), 1727-1736.
Publication 2011
Acclimatization Arthritis Asthma Diabetes Mellitus Disease, Chronic Face Healthy Volunteers Hispanic or Latino Parent Patients Plant Roots
3
Evaluating EQ-5D-5L Descriptive Systems
Cited 208 times
The results of the response scaling task led to an intermediary result of two, rather than one, alternative 5-level versions in both UK English and Spanish (for an explanation, see Results). The second part of the study aimed to assess the ease of use, comprehension, interpretation, and acceptability of these two versions and to use these results to decide on a final, definitive version for validation work. A further aim of this part of the study was to evaluate the face validity of some hypothetical health states generated by the 5-level descriptive systems. To this purpose, the two alternative versions were tested in 8 focus groups in each country (total of 16 groups); four of these were composed of healthy participants and four under treatment for a health condition.
Groups were led by an experienced moderator, and sessions were audio-recorded and transcribed for analysis. A previously prepared script was followed in all groups. All participants in each group first completed either Alternative 1 or Alternative 2 of the EQ-5D-5L (depending on the group they were assigned to), followed by the EQ-VAS. Participants were then asked to review their answers and what they had thought about while they completed the survey. Further questions were used to probe their reactions to the questionnaire in more detail, particularly their reactions to the severity labels used. Participants then provided socio-demographic information before being asked to complete the complementary Alternative 2 or Alternative 1, again on their own, after which there was further group discussion on their reactions. At the end, participants were asked their preferences for the alternative descriptive systems. The order of administration of versions 1 and 2 was alternated between the groups to control for possible ordering effects, and groups were assigned randomly to the different orders.
In the final stage of the focus groups, participants discussed a set of hypothetical health states produced by combining different levels from the 5 dimensions using the alternative 5-level versions. Examples of the health states tested are shown in Table 1. Participants reviewed the states and were asked to assess them for face validity, interpretability, and plausibility. The same procedures were used in the remaining groups, though the order in which the alternative versions of the questionnaire were administered was reversed.

Examples of two of the health states tested in the phase 2 focus groups

Health state 1
 Slight (mild) problems in walking about
 No problems washing or dressing myself
 Unable to do my usual activities
 Slight pain or discomfort
 Not anxious or depressed
Health state 2
 Severe problems in walking about
 Moderate problems washing or dressing myself
 Slight problems doing my usual activities
 Severe pain or discomfort
 Extremely anxious or depressed
The focus groups were run using a structured ‘script’ or guide, so the analysis was based initially on grouping and contrasting participant statements relating to each of the specific issues addressed. Thematic content analysis [21 ] was used to explore issues in more depth and to examine the transcripts for other, non-scripted statements and expressions.
Herdman M., Gudex C., Lloyd A., Janssen M., Kind P., Parkin D., Bonsel G, & Badia X. (2011). Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Quality of Life Research, 20(10), 1727-1736.
Publication 2011
Healthy Volunteers Hispanic or Latino Pain
4
Aging, Memory, and Neurological Evaluation
Cited 202 times
The Memory and Aging Project is funded by the National Institute on Aging and was approved by the Institutional Review Board of Rush University Medical Center. Older persons without known dementia must agree to an assessment of risk factors, blood donation, and a detailed clinical evaluation each year. Further, all participants also agree to donation of brain, the entire spinal cord, and selected nerve and muscles at the time of death.
Study participants are primarily recruited from retirement communities throughout northeastern Illinois Fig. (1). The study primarily enrolls residents of continuous care retirement communities. Several features of these facilities and the study design enhance the validity and generalizability of the study. Because the only exclusion is the inability to sign the Anatomical Gift Act, and because all clinical evaluations are performed as home visits, co-morbidities common in population-based epidemiologic studies are well represented; this reduces the “healthy volunteer effect” seen in many cohort studies [30 (link)]. The home visits reduce participant burden facilitating high rates of follow-up. Follow-up rates are further enhanced because these facilities provide all levels of care from independent living to unskilled and skilled nursing on campus. This also enhances autopsy rates as many participants die on campus and the Anatomical Gift Act allows us to work directly with facility staff and the funeral home to arrange the autopsy. Residents of continuous care retirement communities are predominantly white and tend to be more affluent. Therefore, the study also recruits from Section 8 and Section 202 housing subsidized by the Department of Housing and Urban Development, retirement homes, and through local churches and other social service agencies serving minorities and low-income elderly.
The study design allows the following types of analyses to be conducted within a single dataset Fig. (2): 1) the relation of risk factors with incident AD, incident MCI, and decline in cognitive and motor function; 2) the relation of neurobiologic indices with AD, MCI, and cognitive and motor function; and 3) modeling neurobiologic pathways linking risk factors to clinical phenotypes.
Bennett D.A., Schneider J.A., Buchman A.S., Barnes L.L., Boyle P.A, & Wilson R.S. (2012). Overview and Findings from the Rush Memory and Aging Project. Current Alzheimer research, 9(6), 646-663.
Publication 2012
Aged Autopsy Blood Donation Brain Cognition Continuity of Patient Care Dementia Disorders, Cognitive Ethics Committees, Research Healthy Volunteers Memory Minority Groups Nervousness Phenotype Spinal Cord Temporal Muscle Urban Development Vision Visit, Home
5
Adipose Distribution Modeling with VAI
Cited 179 times
A total of 315 healthy subjects with BMI between 20 and 30 kg/m2 were further selected from the 1,498 primary-care patients to calculate a model of adipose distribution (MOAD). To correct MOAD for fat function, TG (mmol/l) and HDL (mmol/l) levels were introduced in the formula. This was defined as VAI:


assuming VAI = 1 in healthy nonobese subjects with normal adipose distribution and normal TG and HDL levels (supplemental Appendix 2).
Amato M.C., Giordano C., Galia M., Criscimanna A., Vitabile S., Midiri M, & Galluzzo A. (2010). Visceral Adiposity Index: A reliable indicator of visceral fat function associated with cardiometabolic risk. Diabetes Care, 33(4), 920-922.
Publication 2010
Adiposity Healthy Volunteers

Most recents protocols related to «Healthy Volunteers»

1
Characterization of Oral [14C]Vorasidenib Metabolism in Humans
Not available on PMC !

Example 8

Characterization of Absorption, Distribution, Metabolism, and Excretion of Oral [14C]Vorasidenib with Concomitant Intravenous Microdose Administration of [13C315N3]Vorasidenib in Humans

Metabolite profiling and identification of vorasidenib (AG-881) was performed in plasma, urine, and fecal samples collected from five healthy subjects after a single 50-mg (100 μCi) oral dose of [14C]AG-881 and concomitant intravenous microdose of [13C3 15N3]AG-881.

Plasma samples collected at selected time points from 0 through 336 hour postdose were pooled across subjects to generate 0—to 72 and 96-336-hour area under the concentration-time curve (AUC)-representative samples. Urine and feces samples were pooled by subject to generate individual urine and fecal pools. Plasma, urine, and feces samples were extracted, as appropriate, the extracts were profiled using high performance liquid chromatography (HPLC), and metabolites were identified by liquid chromatography-mass spectrometry (LC-MS and/or LC-MS/MS) analysis and by comparison of retention time with reference standards, when available.

Due to low radioactivity in samples, plasma metabolite profiling was performed by using accelerator mass spectrometry (AMS). In plasma, AG-881 was accounted for 66.24 and 29.47% of the total radioactivity in the pooled AUC0-72 h and AUC96-336 h plasma, respectively. The most abundant radioactive peak (P7; M458) represented 0.10 and 43.92% of total radioactivity for pooled AUC0-72 and AUC96-336 h plasma, respectively. All other radioactive peaks accounted for less than 6% of the total plasma radioactivity and were not identified.

The majority of the radioactivity recovered in feces was associated with unchanged AG-881 (55.5% of the dose), while no AG-881 was detected in urine. In comparison, metabolites in excreta accounted for approximately 18% of dose in feces and for approximately 4% of dose in urine. M515, M460-1, M499, M516/M460-2, and M472/M476 were the most abundant metabolites in feces, and each accounted for approximately 2 to 5% of the radioactive dose, while M266 was the most abundant metabolite identified in urine and accounted for a mean of 2.54% of the dose. The remaining radioactive components in urine and feces each accounted for <1% of the dose.

Overall, the data presented indicate [14C]AG-881 underwent moderate metabolism after a single oral dose of 50-mg (100 μCi) and was eliminated in humans via a combination of metabolism and excretion of unchanged parent. AG-881 metabolism involved the oxidation and conjugation with glutathione (GSH) by displacement of the chlorine at the chloropyridine moiety. Subsequent biotransformation of GSH intermediates resulted in elimination of both glutamic acid and glycine to form the cysteinyl conjugates (M515 and M499). The cysteinyl conjugates were further converted by a series of biotransformation reactions such as oxidation, S-dealkylation, S-methylation, S-oxidation, S-acetylation and N-dealkylation resulting in the formation multiple metabolites.

A summary of the metabolites observed is included in Table 2

TABLE 2
Retention
ComponentTimeMatrix
designation(Minutes)[M + H]+Type of BiotransformationPlasmaUrineFeces
Unidentified 17.00UnknownX
M2667.67a267N-dealkylationX
Unidentified 2UnknownX
Unidentified 3UnknownX
Unidentified 4UnknownX
Unidentified 5UnknownX
M51519.79b516OxidationX
M460-120.76b461OxidationX
M49921.22b500Dechloro-glutathioneXX
conjugation + hydrolysis
M51621.89b517Oxidative-deaminationX
M460-221.98b461OxidationX
M47222.76b473S-dealkylation + S-X
acetylation + reduction
M47622.76b477OxidationX
Unidentified 6UnknownX
M47423.63b475OxidationX
Unidentified 7UnknownX
M43025.88b431AG-881-oxidationX
M42630.62b427S-dealkylation + methylationX
M45831.03c459AG-69460X*
AG-88139.41b415AG-881XX
M42847.40b429S-dealkylation + oxidationX
Table 3 contains a summary of protonated molecular ions and characteristic product ions for AG-881 and identified metabolites

TABLE 3
RetentionCharacteristic
MetaboliteTimeProposed MetaboliteProduct Ions
designation(Minutes)[M + H]+Identification(m/z)Matrix
M266 7.88a267[Figure (not displayed)]
188, 187Urine
M51519.79b516[Figure (not displayed)]
429, 260, 164, 153Feces
M460-120.76b461[Figure (not displayed)]
379, 260, 164Feces
M49921.22b500[Figure (not displayed)]
437, 413, 260, 164, 137Urine Feces
M51621.89b517[Figure (not displayed)]
427, 260, 164, 153Feces
M460-221.98b461[Figure (not displayed)]
369, 260, 164, 139, 121, 93Feces
M47222.76b473[Figure (not displayed)]
429, 260, 179, 164, 153Feces
M47622.76b477[Figure (not displayed)]
395, 260, 164, 139, 119Feces
M47423.63b475[Figure (not displayed)]
260, 164, 68Feces
M43025.88b431[Figure (not displayed)]
260, 164, 155, 68Feces
M42630.62b427[Figure (not displayed)]
260, 164, 151Feces
M45831.03b459[Figure (not displayed)]
380, 311, 260, 183, 164, 130Plasma Fecesd
AG-88139.41b415[Figure (not displayed)]
319, 277, 260, 240, 164, 139, 119, 68Plasma Fecesd
M42847.40b429[Figure (not displayed)]
260, 164, 153Feces
Notes
aRetention time from analysis of a urine sample
bRetention time from analysis of a feces sample
cRetention time from analysis of a plasma sample
dM458 was only detected in feces by mass spectrometry, not by radioprofiling.
The proposed (theoretical) biotransformation pathways leading to the observed metabolites are shown in FIG. 1.

US11865079B2. Therapeutically active compounds and their methods of use (2024-01-09). Servier Pharmaceuticals LLC [US]. Inventors: Chandra Agarwal Prakash [US].
Full text: Click here
Patent 2024
Acetylation AG 30 Biotransformation Chlorine Dealkylation Deamination Elements, Radioactive Feces Glutamic Acid Glutathione Glycine Healthy Volunteers High-Performance Liquid Chromatographies Homo sapiens Hydrolysis Intravenous Infusion Ions Liquid Chromatography Mass Spectrometry Metabolism Methylation Parent Plasma Radioactivity Retention (Psychology) Tandem Mass Spectrometry Urinalysis Urine vorasidenib
2
Flow Cytometry Profiling of CAR T Cells
Not available on PMC !

Example 3

FIGS. 6 and 7 provide the results of the flow cytometry assay which show the expression intensity and expression level of ligands in various CAR T cells. On day 0, peripheral blood of healthy volunteers was taken, CD3+ T cells were sorted, and CD3/CD28 Dynabeads were added in a 1:1 ratio. On Day 2, T cells were transfected with lentivirus including various following vectors: CD19CAR infected according to the infection ratio of MOI=10:1, while hCD19CAR, hCD19CAR-CD86, hCD19CAR-GITRUhCD19CAR-41BBL, hCD19CAR-CD80 infected according to the infection ratio of MOI=60:1. On Day 3, the media were changed, the lentivirus was removed, and the cells were resuspended in fresh medium. On Day 7, flow cytometry assays were used to detect CAR and ligand expression. The data shows that each ligand is expressed and detected. Flow cytometry was performed using human CD80/86/41BBL/GITRL antibodies to detect the expression intensity and expression level of ligands.

US11866494B2. CAR T therapy through uses of co-stimulation (2024-01-09). Innovative Cellular Therapeutics Co., Ltd. [KY]. Inventors: Zhiyuan Cao [CN], Chengfei Pu [CN], Lei Xiao [CN], Zhao Wu [CN].
Full text: Click here
Patent 2024
Antibodies Biological Assay BLOOD Cells Cloning Vectors Figs Flow Cytometry Healthy Volunteers Homo sapiens Infection Lentivirus Ligands T-Lymphocyte Therapies, CAR T-Cell
3
Detecting Pancreatic Cancer via Exosomes
Not available on PMC !

Example 2

Comparison in Number of ABA/ACA-Specific Exosomes Between Pancreatic Cancer and Other Cancer Types

It was studied whether there was a difference in the amount of ABA/ACA-specific exosomes between cancer types from healthy subjects' sera and sera from each of pancreatic cancer patients, esophageal cancer patients, and colorectal cancer patients. The quantitative determination of ABA/ACA-specific exosomes was performed through the method described in (Method for Measuring Exosomes Binding to Lectins) described above.

The results are shown in FIG. 7. In the pancreatic cancer patients' sera (PC), both ABA-specific exosomes and ACA-specific exosomes were higher than those in the esophageal cancer patients' sera (Esophageal Cancer) and the colorectal cancer patients' sera (Colorectal Cancer). It was shown from the results that the ABA-specific exosomes and the ACA-specific exosomes are effective for specifically detecting pancreatic cancer.

US11867697B2. Pancreatic cancer detection method and pancreatic cancer detection kit (2024-01-09). JVCKENWOOD Corporation [JP], KEIO UNIVERSITY [JP]. Inventors: Makoto Itonaga [JP], Masayuki Ono [JP], Takahiro Yokose [JP], Atsushi Matsuda [JP], Yasuaki Kabe [JP], Sachiko Matsuda [JP], Miwa Hirai [JP], Minoru Kitago [JP].
Full text: Click here
Patent 2024
Colorectal Carcinoma Esophageal Cancer Exosomes Healthy Volunteers Lectin Malignant Neoplasms Pancreatic Cancer Patients Serum
4
Gut Microbiome Diversity in Pediatric Crohn's Disease
Not available on PMC !

Example 3

16S rRNA sequencing of ileal biopsies showed that the mucosally-associated bacteria from pediatric CD patients had reduced alpha diversity (Faith's phylogenetic diversity) compared to non-IBD patients (FIG. 2A and FIG. 2B). In addition, by examining the beta diversity, we found that microbial communities were more dissimilar among CD patients than a separately recruited, slightly younger non-IBD patient cohort (FIG. 2C and FIG. 2D). In the pediatric population, healthy volunteers are not available. The non-IBD controls were culled from pediatric patients with abdominal pain, who had no evidence of intestinal inflammation by histology, and were primarily comprised of individuals with functional abdominal pain and irritable bowel syndrome. Analysis of the bacterial composition of CD and non-IBD patients revealed distinguishing taxa between non-IBD and CD patients (FIG. 9A, FIG. 9B and FIG. 9C). These results suggested that the non-IBD controls in this study, while slightly younger on average and exhibiting GI complaints without evidence of inflammation were nevertheless more homogeneous and maintained an overall diverse microbial community.

US11867701B2. Methods for prognosing crohn's disease comprising human defensin 5 (HD5) (2024-01-09). None [US], None [US], None [US]. Inventors: Thaddeus Stappenbeck [US], Ta-Chiang Liu [US], Kelli VanDussen [US].
Full text: Click here
Patent 2024
Abdominal Pain Bacteria Biopsy Healthy Volunteers Ileum Inflammation Intestines Irritable Bowel Syndrome Microbial Community Microbiome Mucous Membrane Patients RNA, Ribosomal, 16S Youth
5
Pancreatic Cancer Exosome Biomarkers
Not available on PMC !

Example 1

Comparison in Number of ABA/ACA-Specific Exosomes Between Healthy Subject and Pancreatic Cancer Patient

It was studied whether there was a difference in the amount of ABA/ACA-specific exosomes between healthy subjects' sera and preoperative and postoperative sera from pancreatic cancer patients. The quantitative determination of ABA/ACA-specific exosomes was performed through the method described in (Method for Measuring Exosomes Binding to Lectins) described above. The sera were diluted 4 times with PBS-T before use.

The results are shown in FIG. 6. In the preoperative serum (PC/Preoperative) of the pancreatic cancer patient, both the ABA-specific exosomes and ACA-specific exosomes were statistically significantly higher than those in the healthy subjects' sera (NC). On the other hand, the exosomes in both cases decreased in the postoperative sera (PC/Postoperative) of the pancreatic cancer patients with respect to the preoperative sera, and the difference therebetween was statistically significant. It was shown from the results that the ABA-specific exosomes and the ACA-specific exosomes can be used for detecting pancreatic cancer and monitoring recurrence of pancreatic cancer after surgery.

US11867697B2. Pancreatic cancer detection method and pancreatic cancer detection kit (2024-01-09). JVCKENWOOD Corporation [JP], KEIO UNIVERSITY [JP]. Inventors: Makoto Itonaga [JP], Masayuki Ono [JP], Takahiro Yokose [JP], Atsushi Matsuda [JP], Yasuaki Kabe [JP], Sachiko Matsuda [JP], Miwa Hirai [JP], Minoru Kitago [JP].
Full text: Click here
Patent 2024
Exosomes Healthy Volunteers Lectin Operative Surgical Procedures Pancreatic Cancer Patients Recurrence Serum

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More about "Healthy Volunteers"

Healthy volunteers play a crucial role in biomedical research by providing valuable data to help researchers understand normal physiological processes, test new interventions, and advance scientific knowledge.
These individuals participate in research studies and clinical trials without any known medical conditions or diseases.
Healthy volunteers are often recruited to serve as control groups in studies, allowing researchers to compare the effects of new treatments or interventions against a baseline of normal, healthy physiology.
By leveraging the participation of healthy volunteers, researchers can gain important insights into the safety and efficacy of new drugs, medical devices, and other healthcare products.
The recruitment and management of healthy volunteers involves several key considerations, such as the use of appropriate cell isolation and culture media, like Ficoll-Paque PLUS, Histopaque-1077, and RPMI 1640 medium, as well as the administration of necessary supplements, such as Penicillin and Streptomycin.
Careful sample collection and processing, using tools like BD Vacutainer, also play a crucial role in ensuring the quality and integrity of the data collected from healthy volunteer studies.
Optimizing the recruitment and management of healthy volunteers is essential for enhancing the reproducibility and reliability of biomedical research.
Platforms like PubCompare.ai can help researchers identify the best protocols and products for their healthy volunteer studies, leveraging AI-driven comparisons and data-driven decision making to streamline the research process and advance scientific progress.