Complementary Biological System Journal

Chronic inflammatory and degenerative disorders are driven by interconnected immune dysregulation, metabolic instability, epithelial barrier disruption, and impaired tissue repair, limiting the durability of conventional single-target therapies. The global rise in chronic inflammatory, metabolic, and age-related degenerative diseases underscores an urgent need for multi-dimensional therapeutic strategies that move beyond isolated molecular targets. Despite rapid advances in microbiome science and regenerative medicine, these fields have largely evolved in parallel, with limited integration at the translational level. Emerging evidence identifies the gut microbiome as a central regulator of systemic immunometabolic homeostasis through microbial metabolites, barrier integrity modulation, and immune-cell education. In parallel, mesenchymal stem cell (MSC)–derived peptides, key components of the MSC secretome, function as potent cell-free mediators of immunomodulation, angiogenesis, cytoprotection, and extracellular matrix remodeling. This review advances the concept of a microbiome–peptidome therapeutic axis in which microbiome conditioning enhances the permissiveness of tissues to regenerative peptide signaling. Lactobacillus reuteri DSMZ 17648 is highlighted as a strain-specific probiotic capable of pathogen co-aggregation, ecological modulation, and anti-inflammatory microenvironment stabilization, while MSC-derived peptides act as downstream paracrine effectors driving tissue repair. Integrating mechanistic insights with disease-oriented evidence across gastrointestinal, metabolic, neuroinflammatory, and fibrotic conditions, we propose that upstream microbiome stabilization may potentiate peptide-mediated regeneration. However, translational challenges including microbiome heterogeneity, peptide standardization, regulatory complexity, and limited combination trials must be addressed. Coordinated, biomarker-guided clinical studies are required to validate this multi-tier therapeutic paradigm.

MODFLOW is one of the most commonly used numerical models for simulating groundwater flow. Its structured data design and compatibility with GIS tools make it suitable for groundwater assessment and planning. Groundwater forms an important part of the hydrological cycle and occurs within the pore spaces of sedimentary rocks or within fractures in hard rock terrains. Although its distribution beneath the surface is not always uniform or predictable, it is still considered one of the cleanest, most accessible, and quickly available freshwater sources. Numerical groundwater models help convert complex subsurface processes into simplified relationships that describe flow behavior. Even though such models do not provide a single unique solution, they are useful in representing water level variations and groundwater movement for different hydrogeological settings. With improvements in computational technologies, groundwater models have become important tools for hydro-geologists for resource evaluation, scenario testing, and future prediction. The outcomes of this research will help in supporting better and more sustainable groundwater management in the region

Alzheimer's disease (AD) is increasingly recognized as a multisystem neurodegenerative disorder involving oxidative stress and neuroinflammation beyond classical hippocampal pathology. The hypothalamus, a key regulator of metabolic and neuroendocrine homeostasis, remains comparatively underexplored in experimental AD models. This study investigated the effects of aqueous Annona muricata seed extract (SSE) on hypothalamic oxidative injury in an aluminium chloride (AlCl3)-induced Alzheimer's disease–like model in Wistar rats. Adult Wistar rats of both sexes were randomly assigned to five groups (n = 5): control, AlCl3 (100 mg/kg), SSE alone (200 mg/kg), AlCl3 + SSE, and AlCl3 + donepezil (10 mg/kg). Treatments were administered orally for 28 days with blinded outcome assessment. Spatial learning and memory were assessed using the Morris Water Maze. Hypothalamic tissues were stereotaxically dissected and analyzed for oxidative stress markers (superoxide dismutase, catalase, reduced glutathione, malondialdehyde), pro-inflammatory cytokines (TNF-α , IL-B), and histomorphological integrity using hematoxylin-eosin and Cresyl violet staining with quantitative morphometry. AlCl3 exposure impaired spatial learning, reduced antioxidant defenses, elevated lipid peroxidation and inflammatory cytokines, and induced neuronal degeneration within the hypothalamus. SSE co-administration significantly attenuated these alterations and preserved neuronal architecture, with effects comparable to donepezil. However, classical AD hallmarks such as amyloid-β and tau pathology were not assessed, and findings therefore reflect protection against oxidative and inflammatory neurodegeneration rather than comprehensive AD pathology. These results highlight the hypothalamus as a vulnerable target in experimental Alzheimer-like neurodegeneration and suggest that Annona muricata seed extract warrants further mechanistic and translational investigation.

Purpose: The glycoprotein molecule known as megalin is present on the proximal renal tubular epithelial cells. With an emphasis on megalin and cubilin levels in T2DM and IR patients, an area that obviously needs more research, this study attempts to give an outline of current knowledge of megalin function in relation to vitamin D and its metabolite (vitamin D receptor and vitamin D binding protein). Materials and Methods: This was a case control comparative study conducted at a endocrine and diabetes center in AL-Imamain Kadumain teaching hospital in Baghdad-Iraq. Study subjects were divided into three groups: 25 with T2DM with age range 42–45 years, 25 with IR with age range 45–47 years, and 28 as healthy controls with age range 42–44 years. The enzyme-linked immunosorbent assay technique used to estimate serum megalin, cubilin, vitamin D status, and insulin while lipid profile and fasting blood sugar measured by using colorimetric enzymatic method. Results: serum megalin and cubilin levels were higher in the diabetic and insulin resistance subjects compared to healthy control. No correlation was found between serum megalin and cubilin with the biochemical parameters measured in this study. Conclusion: we conclude that megalin and cubilin develop vitamin D deficiency. Lack of presence or malfunction of either receptor is linked to their action by binding and a reduction vitamin D, VDR, and VDBP. The distribution of lipids, vitamins, and other nutrients depends on this interaction. Tubular proteinuria and complications with vitamin metabolism can result from defects in either receptor because they interfere with the reabsorption of carrier proteins.

it is very important to find reliable biomarkers for early detection and monitoring of treatment response because breast cancer is still one of the most common cancers in women around the world. The goal of this study was to find out how clinically important different biochemical markers are in Iraqi women with breast cancer. Some of these signs are progesterone (PG), oestrogen (E2), cancer antigen 15-3 (CA15-3), and circulating progastrin (hPG80). There were 100 women in this study, and they were all between the ages of 20 and 70. There were three groups of people who took part: a healthy control group (n = 25), a group of newly diagnosed breast cancer patients who weren't getting treatment (Group 1, n = 27), and a group of breast cancer patients who were getting chemotherapy and radiation (Group 2, n = 48). After taking blood, ELISA was used to measure the levels of hPG80, CA15-3, oestrogen, and progesterone in the serum. Statistical analysis was performed using GraphPad Prism version 9.3. A p-value of less than 0.05 was considered statistically significant. The participants were categorized into three groups: healthy controls, newly diagnosed untreated breast cancer patients, and patients undergoing chemotherapy and/or radiotherapy. Both treated and untreated breast cancer patients showed significantly elevated hPG80 levels compared to the control group (p < 0.0001), with no significant difference between the two patient groups. Serum CA15-3 levels were markedly higher in breast cancer patients, particularly in untreated individuals. Estrogen levels were substantially reduced during chemotherapy and radiotherapy, indicating suppression of ovarian function, whereas newly diagnosed patients exhibited significantly higher estrogen levels. Progesterone levels were elevated in untreated patients compared to controls, but significantly decreased in treated patients. These results show that CA15-3 is still useful for tracking the progress of a disease and the effectiveness of treatment. hPG80, on the other hand, may be a good biomarker for diagnosing breast cancer. Changes in oestrogen and progesterone levels are another way to see how different treatment methods and hormonal pathways change the biology of breast cancer. This study highlights the potential of circulating hPG80 as a novel diagnostic biomarker in breast cancer, alongside the established role of CA15-3 in disease monitoring, and provides new insights into hormone profile changes in Iraqi patients.

Curcuma zedoaria Rosc. (white turmeric) is a rhizomatous medicinal plant in the Zingiberaceae family, widely used in traditional Asian medicine. In recent years, increasing scientific attention has focused on its diverse pharmacological properties and bioactive constituents. This mini review summarises current knowledge of the phytochemical composition and biological activities of C. zedoaria, with particular emphasis on its antimicrobial, antioxidant, anti-inflammatory, and anticancer effects. Phytochemical investigations using analytical techniques such as GC–MS and HPLC have revealed the presence of numerous bioactive compounds, including sesquiterpenes (example, germacrone, curzerenone, and curdione) and curcuminoids, which contribute to its therapeutic potential. Experimental studies demonstrate that extracts and essential oils of C. zedoaria exhibit inhibitory effects against various bacterial pathogens, strong radical-scavenging capacity in multiple antioxidant assays, and notable anti-inflammatory activity in animal models. Furthermore, several studies report antiproliferative and apoptosis-inducing effects against different cancer cell lines. Despite these promising findings, limitations remain due to variations in extraction methods, insufficient mechanistic investigations, and the low bioavailability of certain phytochemicals. Therefore, further research focusing on standardised phytochemical characterisation, detailed mechanistic studies, and improved formulation strategies is required to support the development of C. zedoaria-derived therapeutic agents.

Atropine is a commonly used anticholinergic agent in anesthetic practice, administered primarily to counteract bradycardia. Rapid treatment of intraoperative bradycardia is clinically critical, as delays may lead to hemodynamic compromise. This study aimed to compare the onset, magnitude, and duration of the chronotropic response to atropine administered via the intravenous (IV) versus intratracheal (IT) route in anesthetized adult patients. A prospective, single-blind, randomized controlled study was conducted on 60 adult patients classified as American Society of Anesthesiologists (ASA) physical status I-II, scheduled for elective peripheral surgery under general anesthesia. Patients were randomly allocated into three equal groups (n = 20 each). Group A received 0.6 mg atropine intratracheally; Group B received 0.6 mg atropine intravenously with 1 mL saline instilled intratracheally; Group C (control) received 1 mL of 0.9% saline intratracheally. The primary outcome was onset of chronotropic effect (time to 10% increase in heart rate from baseline). Heart rate (HR) was recorded at 15-second intervals for the first minute, then every minute for 15 minutes. Both Groups A and B showed a statistically significant increase in heart rate (p < 0.01). The maximum HR increase was comparable between groups (Group A: +28.15 bpm; Group B: +29.15 bpm; p > 0.05), confirming equivalent efficacy. Onset of action was significantly faster in Group A (21 sec vs. 46.5 sec; p < 0.01), as was time to peak effect (49.5 sec vs. 267 sec; p < 0.01). Group C showed no significant chronotropic change. Intratracheal atropine produces a chronotropic response equivalent in magnitude but significantly faster in onset than the intravenous route, and may be considered as an effective alternative route, particularly when intravenous access is unavailable or delayed.

The aim of this work was to investigating the effect of foliar application of potassium (K) and the growth regulator Cycocel (CCC) on the physiological traits of maize (Zea mays L). The experiment was designed using a split-plot arrangement within a randomized complete block design (RCBD) with three replicates. The treatments included foliar application of potassium at concentrations of 500, 1000, and 1500 mg.L–1, as well as three concentrations of the growth regulator Cycocel (0, 150, and 200 mg.L–1). The results indicated a significant increase in Protein (P), phosphorus, and carbohydrate contents at the concentration of 200 mg.L–1 of Cycocel, reaching 8.22%, 0.71%, and 199.46 mg g–1, respectively. Biological reason for the observed decrease in leaf nitrogen percentage with increasing Cycocel concentrations by spry ratio. A significant decrease in nitrogen percentage in the leaves was observed with increasing concentrations. The results also showed no significant differences due to potassium application in all physiological traits except for carbohydrate content, which significantly increased at the concentration of 1500 mg.L–1, reaching 214.35 mg.L–1. For future work use different concentrations of K and the growth regulator CCC, depend on the spry ration, apply both to soil and as foliar sprays on different maize cultivars, investigate the effects of potassium and CCC on other cereal crops.

Diabetes mellitus (DM) constitutes one of the most consequential comorbidities shaping the clinical trajectory of Coronavirus Disease 2019 (COVID-19), operating through intersecting mechanisms of chronic inflammation, endothelial injury, and immunosuppression that collectively amplify viral pathogenicity. This study investigated the impact of diabetes type on COVID-19 symptom severity, hospitalization duration, and recovery time among patients in Nasiriyah City, southern Iraq — a region substantially underrepresented in the global DM–COVID-19 literature. A descriptive cross-sectional study was conducted across healthcare facilities in Nasiriyah City from 2023 to 2024. A total of 150 hospitalized adult patients carrying confirmed diagnoses of both COVID-19 and type 1 or type 2 diabetes were enrolled through convenience sampling. Structured questionnaires and verified hospital medical records captured demographic data, symptom profiles, glycemic management, hospitalization duration, and recovery outcomes. Chi-square and independent t-tests examined between-group associations; significance was set at p < 0.05. Type 2 diabetes predominated (66.7%). Fatigue (86.7%), fever (80.0%), and cough (73.3%) were the most prevalent symptoms. Diabetes type was significantly associated with COVID-19 severity (χ² = 12.45, p = 0.002), hospitalization duration (χ² = 7.89, p = 0.006), and recovery time (χ² = 4.67, p = 0.035). Over half (53.3%) of participants reported subjectively worsened COVID-19 symptoms attributable to their diabetes. Diabetes — particularly type 2 — significantly worsens COVID-19 outcomes in this southern Iraqi cohort. Optimized glycemic control upon admission and targeted care protocols for diabetic COVID-19 patients represent urgent clinical priorities for resource-limited healthcare settings.

This study compares several deep learning models including DenseNet20, CNN, ResNet50, VGG19, EfficientNet-B3, MobileNetV2, NASNetMobile, Xception to automatically classify brain meningiomas from MRI scans. A public dataset was used to evaluate the proposed model. All models were trained, validated, and tested on this dataset. Because meningiomas are common and manual reads, the goal is to speed and standardize diagnosis. Our main contribution is pairing a high-accuracy classifier with deep learning models. Among all models, DenseNet201 performed best, reaching 0.991% accuracy and reliably separating tumorous from non-tumorous MRIs. Future work will expand the dataset and incorporate stronger segmentation to further boost performance and robustness.