Al-Mustansiriyah Journal of Science

Background: Gastric cancer is a global health issue, and
efforts are being made to discover new compounds that can be used to treat
or prevent this disease. Clove (Syzygium aromaticum) contains eugenol and
other bioactive compounds that have antioxidant and anticancer effects. The
use of nanoemulsion technology can help to improve the solubility, stability, and
bioavailability of these natural compounds, which in turn may enhance their
therapeutic ability. Objective: This study aimed to compare the chemical
composition and anticancer activity of clove oil nanoemulsions and alcoholic
clove extract against human gastric cancer cells. Methods: Both clove oil
nanoemulsion and alcoholic extract were prepared using standardized methods,
with 50% ethanol employed for the extraction of active compounds. The
samples were characterized by dynamic light scattering (DLS) for particle size
analysis and Fourier-transform infrared spectroscopy (FTIR) for identification
of functional groups and structural features. Their anticancer activity was
evaluated using the MTT assay on a gastric cancer cell line by testing multiple
concentrations and assessing effects on cell viability. Results: FTIR analysis
revealed the presence of key functional groups in both the nanoemulsion
and the alcoholic extract, such as phenolic hydroxyl groups (O–H) and aromatic
bonds (C=C), confirming the presence of eugenol as the main active
ingredient in both preparations. However, the nanoemulsion exhibited higher
spectral intensity and a better distribution of nonpolar compounds, indicating
improved solubility and stability of the active compounds. Both samples
demonstrated antioxidant activity and the ability to inhibit the growth of gastric
cancer cells. The nanoemulsion was found to have significantly higher
potency compared to the alcoholic extract, with an IC50 value of 36.30±1.47
μg/mL compared to 41.67±1.53 μg/mL for the extract. Conclusions: This
difference is attributable to enhanced solubility, stability and cellular uptake of
the active compounds in the nanoemulsion. The results suggest that clove oil
nanoemulsions exhibit superior antioxidant properties and anticancer activity
compared to conventional alcoholic extracts indicating that nanotechnology and
traditional methods together present a unique opportunity for improving bioactivity
and bioavailability of natural anticancer agents, which could lead to the
development of effective therapies as treatment options for gastric cancer.

Background: The pathogen “Pseudomonas aeruginosa (P.
aeruginosa)” is extremely hazardous for people with weak immune systems because
it has several virulence factors and can resist antibiotics. Objective: To
isolate and molecularly identify P. aeruginosa from burn and wound infections
and to evaluate its antimicrobial resistance patterns, ESBL production, and
virulence characteristics. Methods: A total of 150 burn and wound samples
were collected from patients at Erbil West Emergency Hospital and processed
immediately. P. aeruginosa was isolated using selective media and confirmed
molecularly by PCR targeting rpoB and oprL genes. Virulence genes (nan1,
plcH, exoT, toxA, aprA) were detected by PCR. Antimicrobial susceptibility
testing was performed against 14 antibiotics using the disk diffusion method.
ESBL production was detected using the Double Disc Synergy Test (DDST).
Hemolytic and proteolytic activities were evaluated using blood agar and skim
milk agar, respectively, while pigment production was assessed on cetrimide
agar. Results: Out of 150 samples, 40 P. aeruginosa isolates were identified.
Imipenem showed the highest efficacy, while complete resistance was observed
against AMP, CTX, P, AMC, and C. Resistance rates were ATM (32.5%),
MEM (42.5%), TOB, AK, and CN (45%), CIP (62.5%), CAZ (67.5%), and
TE (80%). ESBL production was detected in 26 isolates (65%). β-hemolysis
was observed in 25 isolates (62.5%), and strong proteolytic activity was detected
in 35 isolates (87.5%). Typical pigment production was observed on
cetrimide agar. Conclusions: The study reveals a high prevalence of MDR
and ESBL-producing P. aeruginosa with considerable virulence potential in
burns and wounds. Imipenem still holds its position as the most promising
therapeutic agent; this emphasizes the need for continuous surveillance and
proper antibiotic use.

Background: Transformer-based foundation models have
achieved state-of-the-art results in various natural language inference benchmarks,
but their decision-making processes remain largely unexplainable. Addressing
the ’explainability gap’ is crucial for responsible AI adoption in highrisk
industries that require transparency and trustworthiness. Furthermore, the
combination of neural pattern matching with structured symbolic reasoning in
resource-constrained scenarios is an important open problem. Objective: This
study aims to present a memory-optimized probabilistic neuro-symbolic hybrid
architecture that unifies transformer-based neural networks with logic-based
symbolic reasoning systems. Methods: We use the e-SNLI dataset that provides
human-written natural language explanations and reasoning highlights
as training targets, and finetune the BERT transformer-based language model
with an emphasis on gradient checkpointing, mixed-precision (FP16) training,
and layer freezing for optimal resource utilization/reasoning tradeoffs.
All experiments were performed on an NVIDIA GPU with 8–12 GB VRAM
and CUDA-compatible hardware. Results: The proposed framework achieves
80.6% accuracy on 3-way NLI classification (contradiction, entailment, and
neutral) with 0.806 precision, recall, and F1 scores on each class, and detailed
class-level analysis shows high performance on entailment recognition
(F1 = 0.912) and contradiction detection (F1 = 0.902), but slightly lower
performance on neutral cases (F1 = 0.864). Ablation studies and confidence
distributions of the model predictions indicate that memory-optimized models
can maintain competitive performance and be deployed on resource-constrained
devices, reducing GPU memory usage by ≈ 60%. Conclusions: The results
indicate that neuro-symbolic systems within memory-constrained systems can
achieve both explanation needs and foundation models’ performance requirements,
representing an important step in creating more trustworthy AI for
NLP.

Background: Burn and wound infections represent a significant
public health burden in Iraq, contributing to high rates of morbidity
and mortality. Decades of armed conflict, economic instability and deteriorating
healthcare infrastructure have severely compromised the capacity of Iraqi
hospitals to prevent and manage these infections effectively. Objective: This
comprehensive review consolidates scientific literature to evaluate the epidemiology
antimicrobial resistance patterns, pathogenic mechanisms and clinical
outcomes associated with bacterial wound and burn infections across Iraqi
hospitals and healthcare systems. Methods: A systematic search identified
studies on bacterial isolates from wound and burn infections across Iraqi hospitals,
with data drawn primarily from Sulaymaniyah, Baghdad and Misan
provinces as geographically and demographically representative samples rather
than a comprehensive national survey. Results: Pseudomonas aeruginosa,
Staphylococcus aureus and Acinetobacter baumannii collectively account for the
majority of wound and burn infections. Multidrug-resistant (MDR) pathogens
are highly prevalent, including MRSA rates approaching 87%, ESBL-producing
Enterobacteriaceae and carbapenem-resistant Gram-negative organisms. Nosocomial
transmission is the predominant route of spread, driven by overcrowding,
poor infection control and contaminated environments. Burn patient
mortality ranges from 13–28%, with sepsis responsible for 44–65% of burnrelated
deaths. Virulence factors, biofilm formation and bacterial adaptation to
wound environments contribute to treatment failure and infection persistence.
Conclusions: Urgent improvements are required in antibiotic stewardship,
infection prevention, epidemiologic surveillance and evidence-based treatment
protocols across Iraqi healthcare facilities. Inter-hospital collaboration and
investment in regional microbiological diagnostic capacity are essential to addressing
this growing public health crisis.