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Microbes & Immunity Oxidative toxicity and folate in HIV on DTG-ART

Test samples, calibrators, or controls were incubated were communicated privately to each participant during
with the labeled antigen, and the resulting complexes were counseling sessions at the HIV clinic.
magnetically separated from unbound fractions. Following
a wash step, chemiluminescent starter reagents were added 3. Results
to initiate light emission. The relative light units generated 3.1. Baseline characteristics of the study population
were inversely proportional to the folate concentration in
the test sample. 21 Table 1 summarizes the sociodemographic characteristics
of the study population. The distribution of participants
b. Determination of malondialdehyde (MDA) by sex was fairly equitable, with males comprising 48–51%
MDA concentrations were measured using the and females 49–52% across groups, showing no significant
thiobarbituric acid reactive substances (TBARS) assay difference (p=0.816). The mean age of participants was 37.32
with a semi-automated chemistry analyzer (EMP Semi- ± 8.63 years, spanning 19–53 years, representing mostly
Autochemistry Analyzer, Model: 168, Manufactured in young- and middle-aged adults in their physiologically
China), following the method of Gutteridge and Wilkins. 22 active stages.
The assay is based on the reaction of MDA, a However, age distribution differed significantly between
byproduct of lipid peroxidation, with thiobarbituric acid groups (p<0.001). While the majority of HIV-negative
under acidic and high-temperature conditions to form
a stable pink chromogen. Absorbance was measured Table 1. Sociodemographic characteristics of study
spectrophotometrically at 532 nm. The concentration of participants across treatment groups
MDA was calculated using the Beer-Lambert law:
Baseline Subject Control x² p‑value
( A A 10 6 characteristic
MDA M 532 blank) (I) Age group

l
19–28 6 (16.2) 24 (64.9) 20.254 <0.001
Where ε is the molar extinction coefficient and l is the
path length. 29–38 13 (35.1) 8 (21.6)
39–48 14 (37.8) 5 (13.5)
Alternatively, concentration was expressed as: 23 49–58 4 (10.8) 0 (0.00)
[MDA](nmol/mL) = (A -A blank ) × 6.41 (II) Sex
532
2.3. Statistical analysis Male 18 (48.6) 19 (51.4) 0.054 0.816
Female 19 (51.4) 18 (48.6)
Data were analyzed using SPSS version 26.0 (IBM Corp., Educational status
USA). Descriptive statistics (mean ± standard deviation
for continuous variables and frequencies/percentages for Primary 10 (27.0) 10 (27.0) 0.670 0.715
categorical variables) were computed. Secondary 16 (43.2) 13 (35.1)
(i) Comparisons of means across the three groups were Tertiary 11 (29.7) 14 (37.8)
performed using independent sample t-tests and one- Socioeconomic status
way analysis of variance, where appropriate Low 27 (73.0) 26 (70.3) 1.019 0.601
(ii) Chi-square tests were used for categorical variables Middle 10 (27.0) 10 (27.0)
(iii) Effect sizes were calculated using Cohen’s d, allowing
interpretation of the magnitude of observed differences High 0 (0.00) 1 (2.7)
beyond statistical significance Occupation
(iv) A p<0.05 was considered statistically significant Artisan 7 (18.9) 0 (0.00) 20.567 0.001
(v) Results are presented in tables and figures to enhance Business/trader 21 (56.8) 14 (37.8)
clarity. Civil servant 7 (18.9) 17 (45.9)
2.4. Confidentiality and data management Farmer 0 (0.00) 3 (8.1)
Student 0 (0.00) 3 (8.1)
All participants’ personal identifiers—including names, Unemployed 2 (5.4) 0 (0.00)
age, and contact details—were anonymized and coded
before analysis. Laboratory samples were labeled with Marital status
numeric codes rather than participant information. Data Single 14 (37.8) 18 (48.6) 0.881 0.348
were stored on a password-protected computer with access Married 23 (62.2) 19 (51.4)
limited to the research team. Individual laboratory results Note: Data are expressed as n (%).

Volume 2 Issue 4 (2025) 125 doi: 10.36922/MI025310074