Society of Pathological Biochemistry and Hematology
Diabetes Mellitus Overview, Definition, Causes, Statistics in 2025 and 2026: A Review
Diabetes is a group of chronic illnesses that affect how the body uses glucose, or blood sugar, as its primary energy source. The disease is caused by either inadequate insulin synthesis or ineffective insulin use. The hormone insulin, which is secreted by the pancreas, helps cells absorb glucose. Although the causes vary depending on the type, the basic idea of diabetes is a problem with the body's synthesis or use of insulin. Damage is often associated with persistently elevated blood sugar and its impact on blood vessels and neurons. Extremely high blood sugar and the short-term effects of diabetes. The most recent global statistics for 2025 and 2026 show that diabetes is still one of the chronic illnesses with the fastest rate of rise worldwide. Global figures for 2025 are provided by the Diabetes Atlas 2025 edition and the International Diabetes Federation (IDF). Diabetes affects 589 million people worldwide who are between the ages of 20 and 79. This is equivalent to one in nine people on the planet. There are about 252 million people with diabetes who have not been diagnosed. Nearly 3.4 million deaths in 2024 were attributed to diabetes, according to the most recent data published in 2025.
Improving the Genetic Traits of Crops to Cope with Environmental Conditions
The world today faces unprecedented challenges in achieving food security for a continuously growing population amid escalating climate change, from rising temperatures to water scarcity, land degradation, and increasing soil salinity. It has become clear that traditional crops are no longer able to withstand these environmental conditions on their own, and here the role of modern science in improving the genetic traits of crops stands out, with the aim of developing new varieties capable of surviving and producing even in the harshest conditions. Gene modification is not just a technological option but has become an inevitable necessity to ensure the continuity of agricultural production and achieve food security in the future.
The association between Crimean-Congo hemorrhagic fever and COVID-19 outbreaks in Iraq: A review
The 2019 novel coronavirus originated in Wuhan, China, and is rapidly making its way across the rest of the world, causing a worldwide epidemic. The first case of COVID-19 was reported for a traveler entering the city of Najaf and has since spread to all the cities in Iraq. The WHO declared the latest COVID-19 outbreak a worldwide pandemic on March 11, 2020. Crimean-Congo hemorrhagic fever (CCHF) is also one of the issues facing public health that emerged after the COVID-19 outbreak. It has been spread widely in Iraq. Ticks on human or animal tissue or blood are typically the source of infection. The World Health Organization (WHO) has designated CCHFV as a high-priority virus because of its high death rate and lack of viable medical countermeasures. Despite the differences in transmission dynamics and clinical manifestations, there are overlapping epidemiological factors and potential interactions between these two diseases. These two outbreaks cause a serious health issue in Iraq and a high rate of mortality due to the lack of management and control of their spread; furthermore, the absence of health care in hospitals and the lack of medicines and vaccines. Understanding their association is crucial for effective surveillance, diagnosis, and management strategies to mitigate the burden of both diseases in Iraq. This article discusses the two viruses and their emergence in Iraq.
Kinetic and Thermodynamic Investigations of Fuchsin Basic Dye Adsorption onto Graphene Oxide/Polyvinylpyrrolidone/Acrylic Acid Nanocomposite Hydrogel: Equilibrium Modeling, pH Influence, and Ionic Strength Effects
Free-radical polymerization was used to create a nanocomposite hydrogel of graphene oxide, polyvinylpyrrolidone, and acrylic acid (GO/P(PVP-AAc)) to adsorb Fuchsin Basic (FB) dye from aqueous solutions. FTIR, XRD, and FESEM validated the nanocomposite's structural and morphological properties. Batch adsorption experiments assessed the impact of various parameters, such as contact time, initial dye concentration, solution pH (1-10), ionic strength (NaCl, KCl, and CaCO₃ electrolytes), adsorbent dosage, and temperature (288-308K). The kinetic behaviour of the adsorption process was analyzed by applying both pseudo-first-order and pseudo-second-order models, and the results demonstrated that the process conformed more closely to the pseudo-second-order model, with a correlation coefficient (R²) of 0.9985. Equilibrium data were fitted to different isotherm models, among which the Freundlich model provided the best fit, thereby suggesting a heterogeneous multilayer adsorption mechanism. Thermodynamic evaluation through the calculation of ΔG°, ΔH°, and ΔS° indicated that the adsorption was both spontaneous and exothermic in nature. Under optimum conditions—neutral pH and a temperature of 288K, the maximum adsorption capacity reached 172.41mg/g. Furthermore, the swelling behaviour, recyclability, and reusability of the hydrogel were assessed and found satisfactory. Overall, the findings of this study point to the GO/P(PVP-AAc) nanocomposite hydrogel as a viable and cost-effective candidate for the treatment of FB-contaminated wastewater.
Antimicrobial Susceptibility of Streptococcus mutans Isolated from Dental Caries Patients: A Laboratory Study Using CLSI M100 Breakpoints
Background: The prevalence of dental caries is one of the most common chronic infections, mostly associated with the cariogenic bacteria Streptococcus Mutans. There is an increase in the number of resistant strains, which poses a significant clinical problem. Objective: Isolation and identification of Streptococcus mutans from patients suffering from dental caries, analysis of resistance to five different clinically important antibiotics, and interpretation based on CLSI M100 criteria. Methods: Plaque specimens were collected from 80 participants. The isolates were then grown on Mitis Salivarius Agar and identified by conventional biochemical methods. Susceptibility to antimicrobials was determined through the Kirby-Bauer disc diffusion technique on Mueller-Hinton Agar containing 5% human blood (CLSI M100). The five antimicrobial agents tested were as follows: Penicillin, Ampicillin, Erythromycin, Tetracycline, and Vancomycin. Results: In 80 bacterial isolates, positive cultures were obtained for 50 samples, where 32 cultures of S. mutans had a frequency of 64%. All isolates were found to be sensitive to Vancomycin (100%) and Penicillin (87.5%). Resistance was observed against Erythromycin (21.9%) and Tetracycline (25%). Conclusion: Vancomycin maintains its effectiveness against S. mutans. Resistance to Erythromycin and Tetracycline needs further surveillance. Standardization of the CLSI method is essential in dental microbiology.
Contemporary Restorative Approaches in Maxillofacial Prosthodontics: Materials, Retention Systems, and Digital Technologies
Background: Particularly after head and neck cancers, maxillofacial prosthodontics is essential to the rehabilitation of patients with facial defects brought on by trauma, congenital abnormalities, or surgical resection. The functional and aesthetic results of facial prosthesis rehabilitation have been greatly enhanced by developments in biomaterials, retention systems, and digital technologies. Objective: The goal of this review is to present a thorough analysis of restorative techniques in maxillofacial prosthodontics, encompassing digital technologies, implant-supported systems, innovative materials, and conventional treatments. Methods: With the use of electronic resources including PubMed, Scopus, and Google Scholar, a narrative literature review was carried out. Using predetermined keywords associated with maxillofacial prosthesis, face rehabilitation, prosthetic materials, retention systems, and digital fabrication technologies, peer-reviewed publications published between 2010 and 2024 were filtered. Included were pertinent papers on intraoral and extraoral prosthesis rehabilitation. Results: According to available data, acrylic resins are still used in some intraoral applications, but silicone elastomers continue to be the preferred material for extraoral prosthesis because of their better biomechanical and aesthetic qualities. When compared to adhesive-based methods, implant-retained prostheses exhibit better retention, stability, and patient satisfaction. Additionally, the combination of digital processes, three-dimensional printing, and CAD/CAM technology has improved customization, decreased manufacturing time, and increased prosthesis precision. Conclusion: Digitally driven, patient-specific rehabilitation techniques that prioritize functional restoration, aesthetics, and quality of life have become the norm in modern maxillofacial prosthodontics. The current level of care is represented by the mix of digital technology, dependable retention methods, and improved materials. It is anticipated that future advancements combining tissue engineering and artificial intelligence would significantly alter clinical judgment and prosthetic results.
The role of nanotechnology in biological applications: Review article
Through the use of unique nano-properties for targeted action and increased sensitivity, such as large surface area and quantum effects. By enabling precise manipulation of matter at the molecular level, nanotechnology revolutionizes biology and leads to advances in tissue engineering (biocompatible implants, 3D bioprinting scaffolds), gene editing, drug delivery (targeted cancer therapy, fewer side effects), and diagnostics (ultra-sensitive biosensors for early disease detection, imaging). Since nanotechnology primarily inhibits and destroys germs, it is a powerful tool against antibiotic resistance. By using nanosensors to enable early detection, enhanced imaging to improve diagnosis, and targeted drug delivery (nanocarriers like liposomes) to improve treatment. Currently, molecular imaging uses a variety of nanoparticles, and in recent decades, the use of nanoparticles for cancer detection and monitoring has attracted a lot of attention. By facilitating targeted drug delivery, painless oral insulin administration, more intelligent glucose monitoring, and regenerative medicine, going beyond injections to offer glucose-responsive systems.
Phylogenetic analysis of Streptococcus cristatus isolated from an infected root canal
Objectives: This research aimed to investigate the identification by molecular and morphological techniques of a new local strain of Streptococcus cristatus. This strain was detected in 30 cases of patients with infected root canals. Methods: In this study, a modification of Schaedler Agar Medium was done to encourage the isolation of this strain. Then tests of ability for slime layer production and Antibiotic sensitivity were done. Results: The results showed that only three out of the thirteen cases gave positive results for S. cristatus, estimating a 10% prevalence. PCR and gel electrophoresis were employed to further verify this outcome. S. cristatus's 16S rRNA gene sequence was ascertained and compared with the present information from the National Center for Biotechnology Information (NCBI) to determine the strain specifically. The accession number PV243282.1 was assigned to the sequence following its submission to GenBank. This strain was registered in GenBank under the name Mosul. Furthermore, the study confirmed that the isolate under study could create a slime layer and the capacity to produce biofilm. Conclusion. The results of this study enhance the knowledge about S. cristatus and its traits in relation to infected root canals, offering insightful information for future studies and Possible approaches to treatment.
new local strain Streptococcus cristatus
The Role of Intelligent Technologies in Advancing Operations Research Models and Statistical Methods: A Review
This article reviews the evolving role of smart technologies in advancing operations research models and statistical methods. The article begins by asserting that operations research and statistics have developed relatively separately despite their natural complementarity, as statistical methods provide the data and standards needed for operations research models. The article identifies three main categories of smart technologies: Artificial Intelligence and Machine Learning (sub-categories: supervised learning, unsupervised learning, and reinforcement learning), data infrastructure and big data analytics (including data processing and feature engineering), and automation, simulation, and digital twining. The article reviews the synergies between these technologies and process research modeling through three main areas: model formulation and solution techniques, by integrating machine learning predictions, surrogate modeling, and designing hybrid structures, data-driven calibration and validation: using data to derive model parameters and estimating uncertainty, instantaneous optimization and adaptive decision-making: through rapid re-optimization and multi-stage optimization. The article also discusses the enhancement of statistical methods through intelligent technologies, especially in AI-powered Bayesian and probabilistic modeling, non-parametric methods, and powerful methods in intelligent data environments, causal reasoning, and experimental design with learning-enhanced tools. The article concludes with applications across multiple sectors, including supply chains and logistics, healthcare and epidemiology, energy systems and sustainability, and finance and risk management, emphasizing that the integration of smart technologies with operations research and statistics opens up new avenues for improving decision-making in complex and data-rich environments.
Functional Foods: Types and Health Benefits
This scientific article examines the concept of functional foods as an important area of research focused on providing health benefits beyond basic nutrition, with the aim of promoting healthy lifestyles and preventing disease. The article reviews the conceptual framework of functional foods and their historical development, as they have been receiving increasing attention since the 1990s, with the emergence of scientific evidence to support the health claims of their ingredients. The article categorizes functional foods into four main types: fortified foods (with added nutrients), whole foods containing bioactive compounds, therapeutic foods that target specific chronic diseases, and nutritional supplements that differ from traditional foods in their form and concentrated doses. The article discusses the different mechanisms by which these foods improve health, such as their impact on the biological pathways associated with lifestyle diseases. It also reviews health benefits across different populations, including: Cardiovascular health: by modulating risks such as plasma lipids and blood pressure. Metabolic health: By improving blood glucose regulation, insulin sensitivity, and weight control. Digestive Health and Microbiome: By promoting the growth of beneficial bacteria via probiotics and prebiotics. Modulation of immunity and inflammation: By reducing signs of chronic inflammation and boosting immunity. Cognitive function and mental health: through the effect of micronutrients and antioxidants.
Potato Peel Pectin as a Valuable Product: A Review
As an organic waste product that is disposed of in large volumes worldwide, potato peels constitute an abundant and imposing environmental predator. This consequently is strategically significant research, which is a fresh perspective to re-examine them as an alternative and sustainable source to extract pectin. The aim of this review is to provide an overview of the use of potato peels as a feedstock for pectin production, which is in agreement with the international trends toward the circular economy and less industrial waste. To this end, the review investigates the chemical and physical strategies available for extracting pectin and converting this environmental liability into a product of enhanced economic value. This section includes the comparison between traditional extraction technologies based on mineral acids and novel technologies such as enzyme-assisted extraction or other extraction methods like ultrasonic extraction, and their effect on the functional properties of the end-product. It also points out the technical difficulties in the structural composition and the degree of esterification of potato pectin, which is unlike conventional sources (citrus) pectin. In light of the scientific evidence they analyzed, the study states that potato skins are a strategic resource with the potential to bridge gaps in the food and pharma additive supply industry. The summary ends with a vision for future research focusing on achieving an optimal economic return while underlining the importance of using industrial processes as efficiently as possible without exceeding the minimal environmental footprint.
Protease-Producing Pseudomonas in Cold-Stored Milk: Mechanisms of Quality Deterioration: A Review
This review article addresses a major problem in the dairy industry, namely the role that protease-producing bacteria, Pseudomonas, play in the deterioration of the quality of cold-stored milk. Although cooling slows the growth of most bacteria, it creates an ideal environment for the proliferation of psychrotrophic bacteria, such as Pseudomonas. These bacteria are widespread in dairy environments and can contaminate milk after pasteurization. The main problem is the ability of Pseudomonas to produce heat-resistant protease (proteolytic) and lipase (lipid-lyzing) enzymes, which remain active even after pasteurization. These enzymes target and break down essential milk proteins (such as casein), resulting in: Changes in texture: gelation, increased viscosity and undesirable texture, changes in flavor: release of bitter peptides due to casein degradation, free fatty acids that cause rancid or soapy flavors due to lipolysis, synergistic effects: Proteolysis and lipoprotein work together to accelerate the degradation process and produce unwanted flavor compounds at a faster pace. The article reviews in detail the protease systems in Pseudomonas, which include mineral enzymes (e.g. AprX) and serine enzymes, and how their production is regulated at the genetic and environmental level (e.g., temperature, pH, quorum sensing). It also discusses the impact of storage conditions, especially temperature fluctuations and oxygen availability, on bacterial growth and enzymatic activity. In terms of detection and monitoring, the article points out that traditional methods (microbial transplantation) are slow and impractical for routine monitoring. Therefore, biochemical methods (e.g., enzymatic activity assays) and molecular methods (e.g., PCR and metagenomics techniques) are being used for rapid and accurate diagnosis of degrading potential.
Machine Learning Approaches to Rainfall Forecasting in Nigeria: A Comparative Study of RF, SVR, XGBoost, and DNN Models
Rainfall prediction is critical for agricultural planning, water resource management, and disaster preparedness, particularly in regions vulnerable to climate variability. Traditional forecasting techniques often struggle to capture the non‑linear and complex dynamics of meteorological data. This study developed machine learning models to improve rainfall prediction using historical data obtained from the Nigerian Meteorological Agency, which includes climatic variables such as temperature, wind speed, humidity, and prior rainfall. After preprocessing and normalization, the dataset was divided into training (80%) and testing (20%) subsets. Four algorithms, such as Support Vector Regression (SVR), Extreme Gradient Boosting (XGBoost), Random Forest (RF), and Deep Neural Network (DNN), were implemented and evaluated using regression metrics such as R², Mean Squared Error, and Mean Absolute Error. The results show that RF and XGBoost achieved moderate accuracy, with R² values below 0.87. SVR performed better, reducing error significantly (MAE = 0.6839, MSE = 13.8717, R² = 0.893). The DNN model outperformed all others, achieving very low error (MAE = 0.2334, MSE = 0.1956) and near‑perfect accuracy (R² = 0.9985). These findings demonstrate the superior capacity of deep learning approaches to model complex rainfall patterns compared to traditional ensemble and regression methods, while SVR remains a reliable alternative. The study recommends that stakeholders in meteorology and agriculture adopt advanced machine learning models for improved decision‑making. Future research should incorporate high‑resolution satellite data and ground station records for hybrid modeling and employ techniques such as SHAP and LIME.
Advanced Prediction of Chronic Kidney Failure Using Biostatistical and Machine Learning Models: An Age-Stratified Analytical Study Based on Simulated Iraqi Patient Data
Chronic kidney disease has become one of the major public health issues in Iraq due to the increasing rates of diabetes, high blood pressure, and an ageing population. The aim of this study was to investigate how age influences the creation of predictive models for the various stages of kidney disease. Key attributes were identified, and a synthetic dataset of 1,000 patients from Iraq was generated. To do this, several predictive models were employed, including Logistic Regression, Random Forest, Support Vector Machines (SVM), and Extreme Gradient Boosting (XGBoost). A 10-fold cross-validation was performed on all models to assess their stability and generalizability. The models were assessed, and their performance was measured using accuracy, sensitivity, specificity, receiver operating characteristic (ROC), and area under the curve (AUC), as well as on calibration tests, decision curve analysis, interaction tests, and survival analysis. Of all the models evaluated, Random Forest and XGBoost were found to have the best discriminative ability, with AUCs of 0.88 and 0.89, respectively. From the analyses conducted, individuals aged 60 years and older had a significantly higher likelihood of having kidney disease. The most significant predictors were older age, higher serum creatinine levels, and the presence of diabetes and hypertension. The results underscore the clinical value of predictive models for early risk stratification and emphasize the value of predictive technology for information-based management of chronic kidney disease.
A Scholarly Examination of Cauchy–Riemann Integrals
This article examines an in-depth analytical study of Cauchy-Riemann integrals (CR) and their pivotal role in nodal analysis. The beginning of these integrations is presented with basic definitions of these integrals, which are derived from Cauchy"s theory of integrals and the Cauchy–Riemann equations, with an emphasis on their formulation as linear integrals on closed paths. The article discusses the conditions for the existence and uniqueness of these integrations, the extent to which they depend on the geometry of the field and the choice of the integration path, and shows their analytical properties such as linearity, symmetry, and the possibility of derivation under the integration signal. It also offers important applications, including its use as a criterion for verifying the analytic of nodal functions, and solving complex momentum problems (Hamburger, Stiltis, and Verblinski). The article includes various illustrative examples, such as the integration of polynomials and exponential functions, and the distortion of non-trivial paths. The article concludes by emphasizing the importance of Cauchy-Riemann integrations as a powerful analytical tool and proposes promising prospects for their generalization to higher-dimensional spaces.
Biochemical Roles of Bile Acids in Intrahepatic Cholestasis of Pregnancy: A Review
This article reviews the biochemical role of bile acids in intrahepatic cholestasis of pregnancy (ICP), one of the most common pregnancy-related liver diseases. ICP is associated with pruritus and elevated blood bile acid concentrations, and increases the risk of fetal mortality and preterm delivery. Bile acids, which are synthesized from cholesterol, play a central role in the pathophysiology of ICP, as changes in their synthesis and metabolism lead to their toxic accumulation in the liver. The article explains the mechanism of action of this accumulation through the activation of cellular and inflammatory signaling pathways, specifically through receptors such as FXR and TGR5, leading to oxidative stress, mitochondrial dysfunction, and liver cell damage. Elevated bile acids also cross the placenta, negatively affecting its function and fetal health. Bile acid levels and ratios can be used as biomarkers for diagnosis and assessment, and understanding these mechanisms opens up possibilities for targeted therapies.
Intrahepatic cholestasis of pregnancy (ICP)
Endocrine and Hormonal Effects of Medicinal Plant Extracts in Experimental Animal Models: A Review
The endocrine and hormonal effects of medicinal plant extracts in experimental animal models are reviewed in this article. Excluding research on people or cell cultures, the systematic review concentrated on studies that directly or indirectly assessed hormone levels or functioning in animals. Numerous plant extracts have shown significant effects on a number of hormonal axis, including: Hormones (LH, FSH, testosterone, estrogen, and progesterone) in a number of animal species were impacted by extracts from the hypothalamic-pituitary-gonadal (HPG) axis. Hypothalamic-pituitary-adrenal (HPA) axis: By influencing hormones like corticosterone, some extracts have demonstrated the capacity to regulate the reaction to stress. Thyroid-pancreatic axis: Certain extracts have an impact on insulin and glucagon release, thyroid hormones (T3, T4), and glucose management. Certain phytochemical classes are linked to these effects, most notably: Sex and thyroid hormone receptors are impacted by flavonoids, such as quercetin and genistein. Terpenes, polyphenols, and alkaloids all have different roles in regulating endocrine processes. Conclusion: This review highlights the need for more research to fully comprehend the mechanisms, improve the chemical makeup of the extracts, and carry out thorough toxicity studies to better evaluate their therapeutic potential and potential risks. However, it also confirms the promising potential of medicinal plant extracts in modulating the endocrine system.
Applications for Artificial Intelligence in Food and Dairy Science: Advancing Food Quality and Safety: A Review
Artificial intelligence (AI) has become a key tool in food science that significantly raises the safety and quality of food. AI methods like computer vision, machine learning, and artificial neural networks enable effective analysis of complex food data. These technologies are widely used in sensory evaluation, spoilage prediction, and quality assessment of food products. Because AI can detect chemical and microbiological contaminants early on, it is also crucial for human health. AI-powered solutions also enhance food manufacturing procedures and reduce waste. All things considered, applying AI to food science improves consumer protection and encourages more reliable decision-making.
Sustainable Horticulture: Assessing the Efficacy of Organic and Bio-Fertilizers in Supporting Tree Health and Production-Review
Chemical fertilizers and pesticides have greatly enhanced agricultural productivity over the last half-century, but their unselective application has been responsible for environmental pollution, soil degradation, pest resistance, and human health issues. Hence, there has been increasing interest in environment-friendly methods like Integrated Pest Management (IPM), biofertilizers, and organic farming. Biofertilizers—consisting of beneficial microorganisms like bacteria, fungi, and algae—increase nutrient availability due to nitrogen fixation and mineral dissolution, and provide a sustainable source of chemicals. Organic farming and organic amendments enhance soil fertility, microbial diversity, and ecosystem services, and sustain or enhance crop quality. Organic systems, in earlier research, were shown to have yields equal to conventional systems under favorable conditions, but it requires more labor and higher input costs. Recent research has highlighted the application of biofertilizers and microbial inoculants in tree crops, namely citrus, apricot, olive, pomegranate, and apple, and has noted improved growth, yield, fruit quality, nutrient uptake, and disease resistance. A combination of synergistic inputs like amino acids, humic substances, PGPR, mycorrhizal fungi, and organic amendments further increases crop productivity and stress tolerance. Emerging technologies such as nanomaterials, microbial endophytes, and controlled environment agriculture hold further promise for sustainable productivity. Long-term experiments reaffirm that mixed and organic fertilization methods equal or surpass the nutritional and yield capacity of inorganic fertilizers, but these have lower environmental effects. It indicates the potential of organic and biological inputs in sustainable horticultural production, especially for perennial tree crops, and stresses their role in addressing future food demand against altered climatic and demographic scenarios.
Adapting SynSin for Enhanced Video Frame Interpolation via Temporal Feature Fusion and Depth Consistency
Frame interpolation seeks to synthesize temporally consistent in-between frames that enhance video smoothness and visual continuity. We revisit SynSin—originally designed for single-image novel view synthesis—and reformulate it for interpolation by introducing (i) dual-frame input handling, (ii) temporal feature fusion and explicit temporal encoding, (iii) a dedicated interpolation module, (iv) depth-consistency constraints across inputs and the synthesized frame, and (v) a refinement stage to suppress artifacts. Training uses reconstruction-oriented loss while evaluation reports MSE, SSIM, and PSNR. We assess the approach on the indoor 7Scenes benchmark. The modified model yields validation MSE = 0.0011 and SSIM = 0.943, improving over an unmodified baseline (MSE = 0.0033, SSIM = 0.9327), a 66.7 % error reduction, and a +0.0103 absolute SSIM gain. These results indicate that a view-synthesis backbone can be effectively adapted to temporal synthesis, offering a simple, data-efficient route to competitive interpolation quality useful for video editing, animation, and streaming. Beyond performance, our study highlights a practical pathway for repurposing view-synthesis architectures to broader video tasks, encouraging unified designs that share geometry-aware depth reasoning and temporal modeling.
Phylogenetic and antibiotic resistance analysis of Escherichia coli isolates from septicemia patients
Escherichia coli is a major bacterium impacting human health, widely present in the environment and the human body. Its persistence challenges the immune system and facilitates opportunistic infections across all age groups. A critical strategy of E. coli is EMDR, which exacerbates chronic diseases and complicates treatment, contributing to the global crisis of antibiotic-resistant epidemics. This study investigated bacteremia caused by E. coli. A total of 100 blood samples were collected from patients exhibiting clinical symptoms such as fever, chills, and weakness. Samples were cultured anaerobically at 37°C for 24–72 hours, then subcultured on selective media. Identification use Vitek ID system, antibiotic sensitivity testing with the Vitek AST card, and 16S rRNA sequencing. Phylogenetic analysis revealed evolutionary relationships between E. coli isolates and members of the Enterobacteriaceae family. Results: showed that 75 isolates (75%) were identified as E. coli, confirming its significant role in bloodstream infections (BSI). The evolutionary tree highlighted close genetic links with resistant Enterobacteriaceae strains. To explore alternative therapies, the antibacterial activity of green tea extracts was assessed using agar well diffusion. The aqueous extract exhibited dose-dependent inhibition zones of 25, 20, 15, and 10 mm at concentrations of 40, 30, 20, and 10 mg/mL, respectively. Ethanol extracts showed stronger activity, with inhibition zones of 35, 30, 25, and 22 mm at the same concentrations.
The main mycotoxins in nuts: (Aflatoxins): The most toxic and widespread, produced by the fungi Aspergillus flavus and A. parasiticus, and considered to be highly carcinogenic. Found in high levels in walnuts, pistachios, almonds, and hazelnuts. Ochratoxins: These pose a risk to the kidneys, nervous system, and immune system, and are found in almonds, Brazil nuts, and hazelnuts. Fumonisins: These are relatively rare in nuts, but their chronic toxicity is under study. Patulin: Its presence in nuts is limited, but it is the subject of regulatory discussions. The most important sources and routes of contamination are: Pre-harvest: Climatic conditions (humidity, temperature) and genetic factors in the crop play a major role in fungal infection and toxin production. Post-harvest: Inadequate drying and storage in warm, humid conditions (relative humidity >50%) are critical factors that stimulate fungal growth and toxin production. Processing: Common roasting, baking, and frying processes do not significantly reduce aflatoxin levels or may be ineffective. Several methods are used for detection and analysis: Traditional analytical methods include (HPLC), (LC-MS/MS), and (ELISA). Emerging technologies such as biosensors and hyperspectral imaging supported by artificial intelligence show great potential for rapid, field-based detection. The review emphasizes that mycotoxin contamination of nuts is an ongoing global challenge that requires an integrated “farm-to-table” approach. Successfully controlling this problem depends on combining good agricultural practices, appropriate storage conditions, accurate detection methods, and effective mitigation strategies, all within a strict regulatory framework to ensure the safety of these highly nutritious foods.
The Impact of Vitamin D Deficiency on Susceptibility to Parasitic Infections: A Review
Vitamin D is one of the most important vital elements in regulating the immune system in the human body. This vitamin can support the body in confronting pathogenic agents. On the other hand, a deficiency of this vitamin makes the immune response to pathogenic agents low, and the incidence of parasitic diseases increases, especially in areas whose population suffers from malnutrition and poor health services. Vitamin D increases immune activity by regulating the work of immune system cells, lymphocytes such as macrophages and dendritic cells, where immune defense mechanisms depend mainly on these cells against pathogens. Many recent studies have indicated that there is a relationship between low vitamin D and infection with some parasites, including the Toxoplasma gondii parasite, which causes toxoplasmosis, and the leishmaniasis parasite, which causes cutaneous leishmaniasis. This review indicates, through its presentation of sources, that vitamin D deficiency affects the immune response and weakens the body’s ability to defend and get rid of parasites, which leads to their development within it. Understanding the relationship between low levels of vitamin D and susceptibility to parasitic infection in a deeper way is an important step in scientific research because it can help devise new methods of prevention and treatment, aiming to strengthen immunity and reduce the spread of parasitic diseases.
Bacterial and Viral Sexually Transmitted Infections
There are two terms often used interchangeably, Sexually Transmitted Infection (STI) and Sexually Transmitted Disease (STD), but in fact, they are different. STI is infection that can lead to STDs, so every STD is preceded by an STI but not every STI leads to STD severe reproductive complications can result from STDs, including congenital infection, infertility, and ectopic pregnancy. In addition, STDs can increase the chance of acquiring and transmitting Human Immunodeficiency Virus (HIV) infection. STIs or STDs typically result from sexual contact, and the causative agents can be bacteria, parasites, or viruses. The most prevalent STDs are viral infections, as they are treatable but not curable. Symptoms vary according to the viral type and range from skin lesions and warts to immune deficiency and cancer. The treatment of infections that are transmitted sexually relies on the infection type. It is important for sexually active members at higher risk to undergo regular screenings. Neglecting the use of condoms represents a significant risk of infection.
Sexually transmitted diseases, sexually transmitted infections, Vaccination, Human immunodeficiency virus.
The Relationship Between Obesity and Pregnancy
Pregnancy outcomes for both the mother and the foetus are greatly impacted by obesity, a growing global health concern. With an emphasis on the physiological, metabolic, and obstetric ramifications, this study examines the intricate relationship between obesity and pregnancy. Preeclampsia, hypertensive disorders, gestational diabetes, and caesarean delivery are all linked to maternal obesity. Additionally, it can have a detrimental effect on foetal development, resulting in complications like preterm birth, macrosomia, and long-term metabolic disorders in the offspring. The study also emphasises the difficulties in controlling obesity during pregnancy and the significance of weight-loss plans, dietary advice, and preconception counselling. It is essential to comprehend this relationship to enhance prenatal care and lessen unfavourable outcomes for both mother and child.
Obesity, pregnancy, maternal health, fetal outcomes, gestational diabetes, preeclampsia.
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Creating and Analysing Electronic Well-Log Patterns for Identifying Environmental Facies in Abu-Roash ‘G’ Member, West Qaroun field, and Northern Western Desert, Egypt
This study highlights the challenges of exploring oil in the Abu Roash ‘G’ Member, within Egypt’s Abu Gharadig Basin. The reservoir is formed in a near-shore depositional environment and is highly heterogeneous, with rock properties varying dramatically over short distances. Analysing the provided logs is essential in providing correlations, and visualizing those correlations is crucial for understanding the environmental characteristics and spatial changes between the wells. Creating patterns using electronic well-logs helps with identifying facies, and that, in turn, can be used while correlating.
Abu Gharadig Basin, Abu Roash ‘G’, Facies, Environment, Well-Logs Patterns
Modeling Photobleaching and Absorption in Skin Tissue Using Nonlinear Optics: Applications in Laser Techniques and Dosimetry for Photodynamic Therapy
Photodynamic therapy (PDT) efficacy arises from the interplay of photosensitizer photobleaching, evolving tissue optics, and nonlinear light–tissue interactions. Conventional dosimetry assumes exponential decay and constant optical properties, overlooking depth-dependent bleaching and scattering drift. Here, we present a nonlinear dosimetry framework that integrates first-order bleaching kinetics with Monte Carlo (MC) photon transport, extending the optical penetration depth through a nonlinear expansion. A new metric, the Fluorescence Curvature Index (FCI), classifies regimes as bleaching-dominated (FCI > 0) or surface-confined, multiphoton-dominated (FCI < 0). Using high-resolution MC simulations (10⁶ photons, 0.005 mm steps), bleaching constants ( ), nonlinear coefficients (C, Q), and multiphoton orders ( ), with dose–response sweeps across 10–300 J/cm² ensuring reproducibility. were extracted, including thermal scattering drift terms. Results identified three characteristic regimes: 405 nm and 630 nm with bleaching-dominated clearing, 595 nm with inversion-prone vascular confinement, and multiphoton-driven confinement at high fluence. The consolidated protocol table links penetration depth, bleaching thresholds, and disease targets, providing quantitative guidance for wavelength-specific PDT optimization.
Photodynamic Therapy; Photobleaching Kinetics; Photosensitizer Concentration; Multiphoton Absorption; Nonlinear Scattering; Optical Penetration Depth
Breast Cancer Epidemiology and Risk Factors: A Comprehensive Review
Breast cancer remains the most commonly diagnosed malignancy among women worldwide and a leading cause of cancer-related mortality. Despite advances in screening and therapy, its global burden continues to rise, particularly in low- and middle-income countries, highlighting rising incidence in Asia and persistently high mortality in sub-Saharan Africa. The disease’s incidence reflects a complex interplay between genetic, hormonal, environmental, and lifestyle determinants. Established risk factors include age, family history, reproductive behavior, hormonal exposure, obesity, alcohol consumption, and radiation exposure. Strong evidence supports associations between breast cancer risk and high mammographic breast density, hormonal exposures (hormone replacement therapy and oral contraceptives), early menarche, late menopause, delayed first childbirth, and limited breastfeeding duration. Genetic factors, notably BRCA1 and BRCA2 mutations, contribute to 5–10% of cases, predominantly in younger women and those with family history. Emerging evidence implicates atrial fibrillation, metabolic syndrome, and microbiome alterations in modulating breast cancer susceptibility. Meanwhile, protective factors such as physical activity, breastfeeding, and healthy dietary patterns have shown potential to mitigate risk. This review synthesizes current epidemiological trends and evidence-based risk factors contributing to breast cancer development, highlighting regional disparities, modifiable exposures, and emerging genetic insights. Understanding these determinants is essential to guide preventive strategies, early detection, and tailored public health interventions.
breast cancer, epidemiology, risk factors, genetics, prevention, global health
Acacia nilotica: A Natural Antimicrobial Agent Compared to Standard Antibiotics
This study evaluated the antibacterial efficacy of Acacia nilotica extracts against six bacterial strains: P. mirabilis, S. aureus ATCC 6538, E. faecium ATCC 14936, E. faecalis ATCC 29212, E. coli ATCC 8739, and Serratia spp. The extracts were tested in varying concentrations (1/10, 1/100, and 1/1000) and compared to standard antibiotics, including Amoxicillin, Cefotaxime, Amikacin, and Ciprofloxacin. The results revealed that alcohol-based extracts exhibited superior antibacterial activity compared to aqueous extracts, with the hot alcohol extract at a (1/10) concentration showing the most significant effects. P. mirabilis and S. aureus were the most susceptible strains, demonstrating inhibition zones up to 30 mm with alcohol extracts. In contrast, Serratia spp. and E. coli were largely resistant across all extract types and concentrations. E. faecium and E. faecalis showed moderate sensitivity, particularly to hot alcohol extract. High-concentration extracts (1/10) consistently produced measurable inhibition zones, while diluted extracts (1/100 and 1/1000) showed reduced or no activity, highlighting the importance of extract concentration for antimicrobial efficacy. Cold alcohol extract showed the highest activity against S. aureus, while hot alcohol extract was most effective against P. mirabilis. When compared with antibiotics, Amoxicillin and Ciprofloxacin demonstrated the highest antibacterial activity, with inhibition zones reaching up to 48 mm against E. faecium. A. nilotica extracts showed significant antibacterial activity, even against resistant strains, though they were less potent. The results emphasize A. nilotica's promise as a natural antibacterial, with its effectiveness influenced by the extraction method and concentration.
Hayfa Amhimmid Masoud Hayfa Amhimmid Masoud
The effect of organic and chemical fertilization on the growth and yield of cucumbers (Cucumis sativus L.) under protected cultivation conditions: Comprehensive review.
The cultivation of cucumbers (Cucumis sativus L.) in protected greenhouses requires careful nutrient management to maintain rapid plant growth, high fruiting rates, and continuous harvesting. This review compiles evidence on organic and chemical fertilization strategies and their effects on growth, yield, fruit quality, soil health, and sustainability. Chemical fertilizers (especially N–P–K via top dressing) promote early activity, leaf area, and marketable yield through readily available nutrients and controllable doses. However, exclusive reliance on them can exacerbate soil salinity, nutrient imbalance, and environmental pollution, especially under intensive year-round production. Organic amendments (compost, manure, digestate, biochar, and plant extracts) improve cation exchange capacity, water retention, and microbial activity, often leading to improved fruit quality (dry matter, firmness, soluble solids, vitamin C) and reduced physiological disorders. Crop responses to organic fertilizers alone vary, reflecting the quality of amendments, mineralization rates, and temperature-dependent decomposition common in protected systems. In all studies, integrated nutrient management — combining basic organic amendments and soluble mineral fertilization — provides the most reliable results: higher nutrient use efficiency, stable yields, improved storage life, and partial (20–50%) replacement of synthetic nitrogen without affecting yield. Economic analyses generally favor integrated programs when organic inputs are locally available and fertigation is optimized. Future priorities include standardizing organic input characterization, modeling N mineralization under protected microclimates, and long-term trials that jointly track yield, quality, and soil biological indicators to define fertilizer substitution thresholds for resilient cucumber production.