African American
This population often faces unique health challenges and may require specialized research protocols to address disparities.
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Most cited protocols related to «African American»
Dataset 1. This study included 40 individual interviews with African American men in the Southeast US about their health seeking behaviors [29 (link)]. The interview guide contained 13 main questions, each with scripted sub-questions. Inductive probing was employed throughout all interviews. The inductive thematic analysis included 11 of the 13 questions and generated 93 unique codes. The study sample was highly homogenous.
Dataset 2. The second dataset consists of 48 individual interviews conducted with (mostly white) mothers in the Southeast US about medical risk and research during pregnancy [30 (link)]. The interview guide contained 13 main questions, each with scripted sub-questions. Inductive probing was employed throughout all interviews. Of note, the 48 interviews were conducted, 12 each, using different modes of data collection: in-person, by video (Skype-like platform), email (asynchronous), or text chat (synchronous). The qualitative thematic analysis included 10 of these questions and generated 85 unique codes.
Dataset 3. This study included 60 interviews with women at higher risk of HIV acquisition—30 participants in Kenya and 30 in South Africa [31 (link)]. The interview was a follow-up qualitative inquiry into women’s responses on a quantitative survey. Though there were 14 questions on the guide, only data from three questions were included in the thematic analysis referenced here. Those three questions generated 55 codes. Participants from the two sites were similar demographically with the exceptions of education and marital status. Substantially more women from the Kenya sample were married and living with their partners (63% versus 3%) and were less likely to have completed at least some secondary education. All interviews were conducted in a local language.
Data from all three studies were digitally recorded and transcribed using a transcription protocol [32 ]; transcripts were translated to English for Dataset 3. Transcripts were imported into NVivo [33 ] to facilitate coding and analysis. All three datasets were analyzed using a systematic inductive thematic approach [2 ], and all codes were explicitly defined in a codebook following a standard template [34 ]. For Datasets 1 & 2, two analysts coded each transcript independently and compared code application after each transcript. Discrepancies in code application were resolved through discussion, resulting in consensus-coded documents. For Dataset 3, two coders conducted this type of inter-coder reliability assessment on 20% of the interviews (a standard, more efficient approach than double-coding all interviews [2 ]). All three studies were reviewed and approved by the FHI 360 Protection of Human Subjects Committee; the study which produced Dataset 3 was also reviewed and approved by local IRBs in Kenya and South Africa.
Most recents protocols related to «African American»
Example 2
As shown in
Example 5
ECE-1 converts biologically inactive big ET-1 into the biologically active ET-1 peptide. Thus, over-expression of ECE-1 can lead to increased production of ET-1. Peripheral blood derived macrophages from the above described ethnic groups were treated as described above. ECE-1 mRNA was detected using real time quantitative PCR and normalized against 18s rRNA. Differences in macrophage ECE-1 mRNA expression between ethnic and treatment groups are shown in
HIV Nef induced the greatest amount of ECE-1 mRNA in African American HIV positive macrophages, which was significantly higher than all the other groups (P<0.02). Macrophages from African American HIV positive and HIVAN patients had significantly increased ECE-1 mRNA expression when cultured in media only or treated with HIV Nef (P<0.02 and P<0.001, respectively) compared to the healthy controls and Caucasian HIV positive patients. LPS treatment did not significantly increase ECE-1 mRNA in any groups when compared to the other treatments. No significant differences were found between the Caucasian HIV positive patients responses and the healthy group. HIV gp120 did not induce any detectable ECE-1 mRNA from any of the macrophages (data not shown).
Example 4
Preproendothelin-1 (ppET-1) is the precursor polypeptide processed to big ET-1 and then cleaved by ECE-1 to produce the active ET-1 peptide. Peripheral blood derived macrophage were cultured with media only (control), 100 ng/ml LPS, 10 ng/ml HIV Nef or 10 ng/ml HIV gp120 for 4 hours. PpET-1 mRNA was detected using real time quantitative PCR and normalized against 18s rRNA. All other significant differences are denoted by the brackets. As shown in
The eGFR was calculated using the following equations, utilizing the preoperative sCr taken closest to the time before surgery:
MDRD II equation [11 (link)]: eGFR = 186 × sCr − 1.154 × Age − 0.203 × (0.742 if female) × (1.210 if African − American)
Re-expressed MDRD II equation [12 (link)]: eGFR = 175 × sCr − 1.154 × Age − 0.203 × (0.742 if female) × (1.210 if African − American)
CG equation [13 (link)]: eGFR = [(140 − Age) × Weight/(72 × sCr)] × (0.85 if female)
This equation is adjusted for body surface area: (1.73 m2 × CG)/BSA,where BSA = 0.007184 × weight 0.425 × height 0.725
Mayo equation [14 (link)]: eGFR = exp [1.911 + 5.249/sCr − 2.114/sCr2 − 0.00686 × Age − (0.205 if female)], if sCr < 0.8 mg/dL then sCr = 0.8
CKD-EPI Equation [15 (link)]: eGFR = 141 × min (sCr/κ, 1)α × max (sCr/κ, 1) − 1.209 × 0.993Age × 1.018 [if female] × 1.159 [if African − American], where κ is 0.9 for males and 0.7 for females, α is –0.411 for males and –0.329 for females, min demonstrates the minimum of sCr/κ or 1, and max demonstrates the maximum of sCR/κ or 1 [15 (link)].
Top products related to «African American»
More about "African American"
This community often faces unique health challenges and requires specialized research protocols to address disparities.
PubCompare.ai, a powerful AI-driven platform, helps researchers optimize their African American health investigations by identifying the most effective study designs and products.
Leveraging advanced artificial intelligence, PubCompare.ai streamlines the discovery process, enabling researchers to easily locate the best protocols and products from literature, pre-prints, and patents.
The platform provides cutting-edge insights to help investigators uncover the most effective research strategies for their African American studies.
Researchers can utilize PubCompare.ai to explore a wide range of relevant topics, including the use of statistical software like SAS 9.4, Stata 15, and Stata 14 for data analysis.
Additionally, the platform can assist with the selection of appropriate genetic analysis tools, such as the Genome-Wide Human SNP Array 6.0 and TaqMan SNP Genotyping Assays, to uncover genetic factors that may contribute to health disparities in the African American community.
Furhter, PubCompare.ai can guide researchers in the use of common cell culture reagents, like Penicillin/streptomycin and FBS, to ensure their African American health studies are conducted with the utmost rigor and precision.
By leveraging the power of PubCompare.ai, researchers can optimize their investigations and make significant strides in addressing the unique health challenges faced by the African American population.