Iraqi Journal for Applied Science

Diabetes mellitus is a group of metabolic diseases involving carbohydrate,
lipid, and protein metabolism. The present study was carried out to investigate
the Flaxseeds Aqueous Extract effective composition on the Diabetic Mice.
Flaxseeds (Linum Usitatisimum L.) is a rich source of different types of
phenolic such as lignin, phenolic acids, flavonoids, henylpropanoids and
tannins. The Flaxseeds Aqueous Extract composition was determined by UVvis, FT-IR and LC-Mass techniques. FTIR is confirm present Phenols, lignin,
the plant fatty acid alpha-linoleic acid (ALA) and Glycosides Polyphenols
which their act Diabetes mellitus reduced, flaxseeds water extract components
were identified using Gas Chromatography- Mass Spectrometry (LC/MS).
The aqueous extract also showed strong antioxidant capability, which may
help explain its antidiabetic action by lowering oxidative stress in diabetes
tissues. Overall, the results point to the presence of bioactive chemicals in
flaxseed extract that may have therapeutic benefits against diabetes mellitus.

Nine new azo compounds (Y1-Y9) were synthesized in this work by
diazotizing ortho-, meta-, and para-nitroaniline derivatives and then coupling
them with either 2,7-dihydroxynaphthalene, 8-hydroxyquinoline, or αnaphthol. The reactions were carried out in an ice-bath at 0-5 °C under strictly
regulated basic conditions. Using DMSO-d₆ as the solvent, Fourier transform
infrared (FT-IR) and nuclear magnetic resonance (NMR) spectroscopy (¹H
and ¹³C) were used to characterize the structures of all produced compounds
definitively. UV-Vis spectral shifts in DMSO solutions across a wide pH
range (1-14) were examined to measure their effectiveness as acid-base
indicators. Both protonation and deprotonation caused noticeable
bathochromic shifts in the compounds. The cationic form (pH 1-7) exhibited
absorption maxima (λmax) at 391-483 nm, whereas the anionic form (pH 8-
14) absorbed at 448-587 nm. These sharp and reversible color changes, which
correspond to pH ranges of 7-10, demonstrate the effectiveness of the
synthesized azo compounds as effective acid-base indicators in analytical
chemistry, offering potential alternatives to conventional standards

Obesity is a complex condition resulting from a long-term positive energy
balance, in which energy intake exceeds energy expenditure, leading to
excessive accumulation of adipose tissue. This study evaluated the impact of
a six-month healthy lifestyle intervention on anthropometric, metabolic, and
lipid parameters among obese adults. Participants were divided into three
groups: obese individuals pre-intervention, the same group post-intervention,
and normal-weight controls. Body composition was measured, and lipid
profile and metabolic parameters were assessed before and after the
intervention. The study was designed as a quasi-experimental longitudinal
controlled study, done from 2024 to 2025. The intervention included a healthy
lifestyle program was designed for obese group. The results showed
significantly higher body composition and metabolic indices in obese group
compared to normal-weight individuals. Lipid profile were significantly
higher (P<0.05), with the exception of high-density lipoprotein, which was
low in the obese group before the intervention. Post-intervention, a significant
decrease was observed in body compositions indicators, lipid profile, and
metabolic indicators compared to the values recorded before the intervention.
These values, however, remaining higher than the levels of healthy
individuals. High-density lipoprotein increased slightly post-intervention, but
did not reach the level of normal weight individuals. The results reflect the
positive effect of fat loss on reducing chronic inflammation associated with
obesity and improving metabolic and lipid profiles, confirming the
effectiveness of a healthy lifestyle in obesity management

Polycystic ovarian syndrome (PCOS) is an endocrine disorder commonly
affecting women of reproductive age. It is characterized by increased
androgens, metabolic dysfunction and irregular or absent menstrual periods.
The study aimed to estimate the level of adiponectin and lipid profile related
with polycystic ovarian syndrome. The study included 90 women between
September 2024 to September 2025 with a range of ages (15-45years)
(28.666±6.837), divided into two groups: 45 with a mean (31.689±6.842) used
as healthy and 45 with mean of age (24.644±5.390) as patients. The serum
adiponectin, anti-mullerian hormone (AMH), luteinizing hormone (LH),
follicular stimulation hormone (FSH), prolactin, and t.testosterone, were
quantified through Enzyme-Linked Immunosorbent Assay (ELISA)
techniques. lipid profile (Cholesterol, Triglyceride, high-density lipoprotein
(HDL), low-density lipoprotein (LDL), and very-low density lipoprotein
(VLDL) measurement by spectrophotometer. The result found a significant
decrease (p≤0.01) in adiponectin, high density lipoprotein (HDL) and
follicular stimulation hormone (FSH) in the PCOS patient compared to the
healthy group, also in the hormonal level, a significant increase(p≤0.01) in
anti-mullerian hormone (AMH), luteinizing hormone(LH), prolactin,
testosterone, lipid profile demonstrated a statistically significant increase
(p≤0.01) in the LDL, cholesterol, TG, VLDL, adiponectin AUC:95.704%,
with Sensitivity to Specificity 93.333%-97.678%. Low adiponectin and
dyslipidemia are connected to the pathophysiology of PCOS and can be uses
as clinical marker for PCOS.

The study involved the synthesis and characterization of the new compound
4-methoxy-N-(2-(phenylcarbamothioyl) hydrazine-1-carbonothioyl)
benzamide (L). By combining the title ligand with metal ions of manganese
(II), cobalt (II), and nickel (II), three transition metal complexes were
synthesized. This reaction occurred through the combination of metal and
ligand in a mole ratio of one-to-one utilizing ethanol as the solvent. The
complexes generated have a chemical formula as follows: [LMnCl₂.H₂O],
[LCoCl₂H₂O], and [LNiCl₂.H₂O]. A variety of physicochemical techniques
have been utilized to demonstrate the entity of the predicted structure of the
ligand and its metal complexes. including Fourier transform infrared
spectroscopy, UV-Vis spectroscopy, (1H and 13C)-NMR, elemental analysis
(C, H, N, S), content of chloride, content of metal, m.p., the molar
conductivity measurements, and also magnetic susceptibility. Based on
spectral and analytical data, the isolation complexes for the manganese (II),
cobalt (II), and nickel (II) exhibit a six-coordinate with a distorted octahedral
geometry. The antibacterial activity of the complexes was investigated against
(G+) and (G-) bacteria.

Lipase, a versatile biocatalyst, has many biotechnological applications. A
lipolytic fungal strain BTSS 1005 was isolated from a marine sediment in the
eastern coast of Visakhapatnam, after sequencing studies of my previous
work, it was identified as a novel strain of Aspergillus sydowii. It was found
to produce a thermostable lipase by submerged fermentation during my
research and hence was selected for bioprocess development. In the present
work, media composition was optimized for the enhancement of lipase
activity using statistical techniques. The major ingredients were chosen
through Plackett-Burman experimental design and optimum ingredient level
was investigated through Central Composite Design, of Response Surface
Methodology, for best lipase yield. The activity of lipase produced by
submerged fermentation studies, initially determined as 28.64 U/ml before
optimization, was predicted 63.94 U/ml by using RSM. This study was useful
for paving way for usage of different statistical models in optimization of
cultural parameters in industrial productions of bioactive compounds

This study investigates the structural characteristics of the idempotent graph
???????????? (????) associated with a commutative ring ????. The graph is defined as a
simple, undirected graph in which the vertices correspond to the elements of
????, and two distinct vertices ???? and ???? are considered adjacent precisely when
the condition (???? + ????)
2 = ???? + ???? holds, meaning their sum is an idempotent
element. The research specifically examines the idempotent graph constructed
over the ring of integers modulo n, denoted ????????, where ???? = ???????? and ???? and ????
are distinct prime numbers satisfying ???? < ????. Within this framework, the work
provides a detailed analysis of several fundamental graph-theoretic properties
of ???????????? (????), including its radius, diameter, vertex degree, and chromatic
number. The findings offer insight into how the algebraic structure of ????????????
influences the resulting graph, contributing to a deeper understanding of the
interaction between ring theory and graph theory

Dermatology is considered one of the most challenging medical specialties
studied in medical schools due to the considerable similarity among various
skin diseases, such as psoriasis, seborrheic dermatitis, chronic dermatitis,
lichen planus, pityriasis rubra, and pityriasis rosea. With the rapid
advancement of technology, computers have become deeply integrated into
medicine, and many decision-support systems have been developed to assist
physicians in making accurate diagnoses. Medical data obtained from
laboratory analyses can play a decisive role in determining disease type. The
application of classification algorithms and feature selection techniques has
significantly improved the efficiency of diagnostic systems, particularly
through the use of metaheuristic algorithms. In this research, a classification
methodology for skin diseases is proposed by introducing a novel hybrid
feature selection (FS) technique. The sine cosine algorithm (SCA) was
employed within a wrapper model framework to select the optimal subset of
features for classification. To enhance exploration and maintain diversity, a
mutation factor was incorporated as an internal function, evolving the SCA
into the enhanced sine cosine algorithm (ESCA). Consequently, the system
generates two outputs for each algorithm. Experimental results demonstrated
that the SCA achieved a diagnostic accuracy of 96% with 79% of selected
features, whereas the ESCA achieved a remarkable diagnostic accuracy of
98% while reducing the selected features to 63%.

The Internet of Things (IoT) is a promising technology used for several
connectivity applications to enable technologies. IoT includes connectivity
protocols, sensors, communication technologies, and data processing methods
that will allow IoT devices to collect, process, and analyze large amounts of
data. Many types of foot distortion, such as bunions, hammer toe, flatfoot, and
others, can either be congenital or acquired. These deformities are considered
significant contributors to body imbalance, leading to fatigue and discomfort
during everyday activities. Timely identification of flatfeet and the
development of treatment plans are very important to mitigate or eliminate
complications. Thus, IoT technology can enhance patient care, improve
diagnostic accuracy, increase efficiency, and support connected doctors and
clinical staff in caring for their patients. Therefore, the objective of the present
manuscript is to design and implement an IoT application that can detect and
diagnose the flatfeet types. It is a user-friendly application that can be
managed by both patients and physicians to record the stages of flatfeet and
perform a preliminary check for possible gait problems in daily life. The
proposed work uses a segmentation method that partitions and analyzes a
digital image into discrete clusters of pixels. This method assigns a label to
each segment based on shared characteristics (i.e., colors). Thus, all segments
that belong to the same cluster are treated as identical. The proposed method
classifies foot distortion types into flatfeet, concave, and normal, and finds
hidden patterns in the dataset. The finding of this study is to enable early
disease detection, enable real-time patient monitoring, and thus personalized
treatment plans.