Minia University

Identifying the baseline status and the timing of ecosystem disturbances are essential for restoration programs. The historical bioaccumulation of heavy metals was assessed from an 80-cm-long core from the Manzala Lagoon (Nile Delta). The heavy metal concentrations increased slightly upward and peaked around 1964, after the completion of Aswan High Dam. The metal concentrations of shells are 2-3 times less than those of bulk sediment. The topmost sediments are enriched in Cd, Cu, and Pb above USEPA. Sediment type and sediment grain size have a minor effect on the heavy metal concentration in mollusk shells, suggesting a priority over bulk sediments. Although correlated, the shells of the grazer gastropod Melanoides tuberculata have the highest concentration of all metals relative to the suspension-feeder bivalves Cerastoderma glaucum and Saccostrea cuculata. This was attributed to the influences of the eco-physiological traits, which exert a similar influence on the bioaccumulation process of all metals.

Background Papillary thyroid carcinoma (PTC) is the most common type of thyroid carcinoma, representing the majority of thyroid cancer cases. Most patients with PTC have an excellent prognosis following treatment, yet approximately 10% face mortality within ten years, primarily due to lymph node metastasis (LNM) or local recurrence. The SIX1 gene, a member of the SIX gene superfamily, encodes a transcription factor integral to the development of certain tissues during embryogenesis. The impact of SIX1 in different subtypes of PTC has not been studied previously. Objective The purpose of this study was to investigate the expression of SIX1 protein in PTC and to explore its relationship with clinical behavior in two subtypes of PTC: classic PTC (C-PTC) and follicular variant PTC (FV-PTC). Materials and methods Using immunohistochemistry, the study analyzed 125 primary PTC cases, including 85 cases of C-PTC and 40 cases of FV-PTC. Results The study found significant positive associations between high SIX1 expression and several adverse clinical features across the PTC samples. High SIX1 expression was linked with increased tumor size, multifocal tumors, LNM, high-grade tumor features, advanced tumor stage, lymphovascular invasion, perineural invasion, and extrathyroidal extension (ETE). Within the classic PTC subgroup, high SIX1 expression showed significant positive correlations with Tumor size (P = 0.04), Multifocality (P = 0.02) and High-grade features (P = 0.03). In the follicular variant subgroup, high SIX1 expression was significantly associated with Lymph node metastasis (LNM) (P = 0.001), Lymphovascular invasion (P = 0.03), ETE (P = 0.003) and tumor stage (P = 0.007). Conclusions The findings of this study indicate that SIX1 expression is a marker of poor prognosis in PTC, suggesting that its high expression is linked with more aggressive tumor characteristics and advanced disease stages. Importantly, the impact of SIX1 expression varies between C-PTC and FV-PTC, predicting distinct prognostic factors in each subtype. This suggests that SIX1 could be utilized not only as a prognostic biomarker but also in developing subtype-specific therapeutic strategies for PTC patients.

This comprehensive review delves into the medicinal chemistry of amidoxime and 1,2,4- oxadiazole scaffolds. These scaffolds have been modified to address bacterial infections, malaria, inflammation, Alzheimer's disease, and cancer, yielding novel lead compounds with significant therapeutic potential. The review scrutinizes recently developed bioactive candidates, highlighting their antibacterial and anti-biofilm properties through the targeting of essential bacterial replication and virulence factors. In oncology, these derivatives exhibit promise by interacting with critical macromolecules, presenting diverse mechanisms of action. Notably, amidoxime hybrids have shown potential in inhibiting indoleamine 2,3-dioxygenase 1 (IDO1), whereas oxadiazole hybrids demonstrate anti-proliferative effects by targeting the epidermal growth factor receptor (EGFR). These hybrids also display dual inhibition of cyclooxygenase-2 (COX-2) and 15-lipoxygenase (15-LOX), indicating significant anti-inflammatory potential. In the context of Alzheimer's disease, oxadiazoles are emerging as promising agents targeting human carbonic anhydrase (hCA) I and II enzymes. Additionally, they exhibit anti-malarial activity by targeting the Plasmodium parasite. The review further examines marketed drugs such as Ximelagatran, Upamostat, and Naldemedine, underscoring their versatile and targeted therapeutic approaches. The aim of this review is to guide medicinal chemists in synthesizing amidoximes and oxadiazoles with enhanced efficacy and reduced side effects. These scaffolds hold promising potential for future development and clinical trials.

Background Post-burn scars are one of the most common consequences that influence patients’ quality of life following burns. Many treatments have been demonstrated to be helpful in the treatment of post-burn scars, including ablative fractional CO2 laser (AFCL) and lipofilling. However, few research has been conducted to determine the effect of combining these measures. The present study aimed to assess the effects of AFCL when it’s combined with lipofilling for post burn scars management. Methods This was a prospective study of 20 patients with post burn scars, they were managed by scar splitting, all the scar was treated by lipofilling then scar was split into 2 equal segments. Segment A remained as a control and Segment B received AFCL session after one week of lipofilling. The evaluation was conducted 3 months after the final treatment session by clincal, histopathological and Immunohistochemistry (IHC) evaluation. Results Both scar segments showed statistically significant improvements according to the Patient and Observer Scar Assessment Scale (POSAS). However, the degree of improvement was not significantly different between the two scar segments. Histological and Immunohistochemical analysis revealed similar skin regeneration, improving in collagen density and arrangement, and increase in vessels density in both segments. Conclusions This study demonstrated that lipofilling enhances the clinical outcomes of post-burn scars. However, the addition of AFCL to lipofilling did not yield greater effectiveness compared to lipofilling alone. Level of evidence Level III, therapeutic study.

The kinetics of the pyrolysis process is a key parameter for the design, optimization, and operation of industrial applications of polymer pyrolysis systems. Determining the kinetic triplet of activation energy, kinetic reaction mechanism, and pre-exponential (frequency) factor is the key of understanding of pyrolysis process. The objective of this study is to determine the kinetic triplet and the heat release rate of polystyrene (PS), high-density polyethylene (HDPE), and their blend using a micro combustion calorimeter (MCC). Estimation of the activation energy for each polymer was investigated using four iso-conversional methods: the Friedman, Kissinger–Akahira–Sunose, and Flynn–Wall–Ozawa methods and an advanced iso-conversional method. Comparative and detailed analyses of the reliability of these methods were conducted at heating rates from 0.25 to 1.5 K/s. The reaction mechanism f(α) was determined using a master plot and compared with commonly used reaction functions. The heat release rate increased with increasing heating rate for the pure polymers and their blend. The peak heat release rates of HDPE, PS, and the blend at a heating rate of 1.5 K/s were 1880, 466, and 860 W/g, respectively. The activation energies of HDPE, PS, and the blend were 225.4, 186.86, and 249.93 kJ/mol, respectively. The obtained results provide essential data for calculating the heat release and kinetic triplet and selecting a suitable model for HDPE, PS, and the HDPE/PS blend in potential pyrolysis reactors.

Objective The objectives of this study are to evaluate the effects of the educational intervention on mothers’ knowledge, awareness, and communication difficulties experienced with their children and mothers’ capacity to successfully interact with their affected child before and after the intervention. Materials and Methods A quasi-experimental research design was used. A total of 30 mothers and their children complaining of attention-deficit hyperactivity disorder from four Dawadmi primary schools were included. Data were collected through a self-developed questionnaire from September 2023 to January 2024 after study acceptance by Shaqra University’s scientific deanship. Intervention prepared according to subjects’ needs and current scientific base and demonstrated in 10 sessions in schools. Results Regarding mothers’ age, more than one-fourth of them (26.7%) ranged from 31 to 35 year old, and about a third (36.7%) had secondary education. Regarding mother’s job, about 76.7% do not work, and the majority of affected children (66.6%) were male, there were significant improvements in mothers’ knowledge pre- and postintervention also a significant improvement in mothers’ awareness about symptoms of poor attention, hyperactivity, and impulsivity pre- and postintervention was found. Significant differences were found before and after the intervention regarding the impact of the intervention in decreasing mothers’ challenges. Conclusion The study hypothesis was accepted, and the intervention improved mothers; knowledge, awareness, and communication challenges. The intervention should be conducted and followed up for a long period of time to manage all mother’s and children’s daily challenges, improve children’s daily activities, and stabilize effective communication patterns between children and their family members.

The evaluation of photovoltaic (PV) model parameters has gained importance considering emerging new energy power systems. Because weather patterns are unpredictable, variations in PV output power are nonlinear and periodic. It is impractical to rely on a time series because traditional power forecast techniques are based on linearity. As a result, meta-heuristic algorithms have drawn significant attention for their exceptional performance in extracting characteristics from solar cell models. This study analyzes a new modification in the double-diode solar cell model (NMDDSCM) to evaluate its performance compared with the traditional double-diode solar cell model (TDDSCM). Modified Fire Hawk Optimizer (mFHO) is applied to identify the photovoltaic parameters (PV) of the TDDSCM and NMDDSCM models. The Modified Fire Hawks Optimizer (mFHO) algorithm, which incorporates two enhancement strategies to address the shortcomings of FHO. The experimental performance is evaluated by investigating the scores achieved by the method on the CEC-2022 standard test suite. The parameter extraction of the TDDSCM and NMDDSCM is an optimization problem treated with an objective function to minimize the root mean square error (RMSE) between the calculated and the measured data. Real data of the R.T.C France solar cell is used to verify the performance of NMDDSCM. The effectiveness of the mFHO algorithm is compared with other algorithms such as Teaching Learning-Based Optimization (TLBO), Grey Wolf Optimizer (GWO), Fire Hawk Optimizer (FHO), Moth Flame Optimization (MFO), Heap Based optimization (HBO), and Chimp Optimization Algorithm (ChOA). The best objective function for the TDDSCM equal to 0.000983634 and its value for NMDDSCM equal to 0.000982485 that is achieved by the mFHO algorithm. The obtained results have proved the NMDDSCM’s superiority over TDDSCM for all competitor techniques.

Accurately assessing power systems’ ability to accommodate wind power is an important basis for systems to participate in the day-ahead wind power market and make reasonable trading plans. However, existing assessment methods do not consider frequency security of systems, which leads to frequency security issues during the execution process of trading results. This paper proposes an assessment method for day-ahead wind power admissibility (DWPA) of power systems considering frequency constraints (FCs). First, a FCs model is established through the oscillation equation of frequency deviation dynamics after system disturbances, and embedded in the assessment of day-ahead DWPA. Then, a robust feasible region definition for wind power output is proposed, and a system operation risk model is developed based on it. Finally, based on the two-stage robust optimization theory, an overall assessment model for the DWPA of power systems considering FCs is proposed, and the column-and-constraint generation algorithm is used to solve the problem. The effectiveness of the proposed method was verified through simulations conducted on the IEEE 9-bus and 118-bus power systems. The results emphasized the importance of taking FCs into account and the enthusiasm of wind farms to provide virtual inertia.

The escalating resistance to traditional antibiotics causes a significant hazard to public health, demanding innovative antimicrobial strategies. This study introduces cefixime‐infused green‐synthesized zinc oxide nanoplatelets (ZnO NPts) highlighting their enhanced biological potential. The successful formation of ZnO NPts and their subsequent infusion with cefixime were confirmed using various characterization techniques: UV–visible spectroscopy, Fourier transform infrared spectroscopy, x‐ray diffraction, scanning electron microscopy, transmission electron microscopy, energy dispersive spectroscopy, and dynamic light scattering. Comparing cefixime‐functionalized ZnO NPts with pure ZnO and cefixime alone, biological assessments revealed that the former exhibited stronger antifungal activity against the tested strains. Moreover, these NPts demonstrated the highest cytotoxicity in tests with Artemia salina larvae and pronounced antioxidant activity in TAC, TRP, and DPPH assays. These findings emphasize the significant potential of cefixime‐infused ZnO NPts for various biomedical applications, offering enhanced antifungal, cytotoxic, and antioxidant properties.

Background. High blood pressure (BP) is common in acute stroke and a predictor of poor outcomes. Treatment of acute stroke, before a distinction can be made between ischemic and hemorrhagic types, is challenging. We aimed to assess whether patients with presumed acute stroke benefit from pre-hospital BP lowering. Methods. We conducted a comprehensive systematic review and meta-analysis of randomized controlled trials from PubMed, Web of Science, Scopus, and Cochrane searches until June 2024. Dichotomous data were pooled using risk ratio (RR), and continuous data were pooled using mean difference (MD), both with a 95% confidence interval (CI), using (R version 4.3). PROSPERO ID: CRD42024560200. Results. Our analysis included five RCTs encompassing 3,933 patients. There was no difference between early BP control and usual care regarding the National Institutes of Health Stroke Scale (NIHSS) after 24 hours (MD: 0.65 with 95% CI [0.01, 1.29], P = 0.05), excellent neurological recovery (Modified Rankin Score (mRS) 0–1) (RR: 1.00 with 95% CI [0.91, 1.11], P= 0.98), functional independence (mRS 0–2) (RR: 1.04 with 95% CI [0.96, 1.13], P= 0.30), and independent Ambulation (mRS 0–3) (RR: 1.01 with 95% CI [0.95, 1.06], P= 0.84). Also, there was no difference between both groups in poor neurological recovery (mRS 4–6) (RR: 0.98 with 95% CI [0.91, 1.07], P= 0.68), all-cause mortality (RR: 1.02 with 95% CI [0.90, 1.15], P= 0.79), and any serious adverse events (RR: 1.04 with 95% CI [0.95, 1.15], P= 0.40). However, early BP control significantly increased the incidence of hypotension (RR: 2.24 with 95% CI [1.14, 4.38], P= 0.02) and headache (RR: 1.51 with 95% CI [1.01, 2.26], P= 0.04). Conclusion. In patients with presumed hyperacute stroke and elevated blood pressure, the rapid initiation of blood pressure reduction in the ambulance very early after symptom onset had no significant benefit regarding functional outcomes in patients with undifferentiated stroke but with an increased incidence of hypotension and headaches.

Background The use of electronic nicotine delivery systems (ENDS), including e-cigarettes, vape pens, hookah pens, e-cigars, and e-pipes, has grown in popularity worldwide, particularly among young individuals. However, these products are not without risks, as their emissions may contain harmful substances such as diacetyl (a flavoring agent linked to specific pulmonary problems in high concentrations), tobacco-specific nitrosamines, and volatile organic compounds with unknown long-term effects on lung health. Objective This systematic review and meta-analysis aimed to assess the prevalence of ENDS use among school and college students on a global scale. Methods A comprehensive search was conducted in PubMed, Scopus, Cochrane Library, and Web of Science databases. Two researchers independently selected and extracted data from the identified studies. The pooled prevalence of ENDS use among school or college students was calculated using a random-effect meta-analysis. Results The systematic review encompassed 146 studies with 4,189,145 subjects from 53 countries and six continents. The overall current prevalence of ENDS use was 10.2%, indicating a significant presence of this behavior among students. Moreover, ENDS current use was higher among males (10.2%) than females (7.5%). In comparison, the lifetime prevalence was 22.0%, indicating that a substantial portion of students have tried these products but do not continue to use them regularly. Conclusion Our meta-analysis reveals a significant prevalence of ENDS use among school and college students globally, with higher rates observed among males than females. The lifetime prevalence of ENDS indicates that many students have tried or are currently using these products. The current prevalence of ENDS use was 10.2%, with notable variations across different continents.

The COVID-19 pandemic is a novel, fast-spreading, deadly virus. It has spread around the world in an extremely short time. Due to its rapid spread and negative effects on all aspects of our lives (health, finances, stress, etc.), scientists are seeking to find accurate and fast solutions to this crisis. In our paper, we present a systematic literature review (SLR) of the different machine learning (ML) and deep learning (DL) techniques used for the detection, classification, and segmentation of COVID-19. We depend on our review of reliable databases such as IEEE Explore, Google Scholar, MDPI, Springer, PubMed, and Science Direct. By surveying approximately 978 papers, we found that 160 were more authorized, 77 of which were selected for review and met the criteria. A taxonomy is introduced to describe the sequence of our paper. Subsequently, a deep analysis and critical review of the academic literature were conducted to highlight the challenges and significant gaps identified in the introduced subject. The results revealed a shortage of research that assessed and established standards for the methods utilized for identifying and categorizing COVID-19 chest imaging techniques. As we continue the assessment and standardization process, three main difficulties are anticipated: the existence of various evaluation criteria for each task, the conflicts between these criteria, and the importance of these criteria. Moreover, we present a review of different systems used from the beginning of this crisis based on ML and DL by using different medical image modalities, such as chest X-ray, chest computed tomography (CT), magnetic resonance imaging (MRI), and ultrasound imaging. We also highlight the datasets used and the different results of performance measures that have been developed by different researchers in this medical field. Finally, we discuss the limitations and lessons learned that are associated with the use of ML and DL techniques for diagnosing COVID-19. To support our work, we developed a new algorithm based on using transfer learning for several deep learning models and applied it to our own dataset. The aim of our paper is to collect various authorized data to help experts and specialists understand the importance of ML and DL systems in this respect, represent a new algorithm, and benefit them in future work toward fighting COVID-19.

Numerous chemotherapeutic medications can have hazardous effects on the lungs, which can result in severe lung diseases. Methotrexate (MTX) is prescribed for cancer and inflammation-related disorders; nevertheless, it is exceptionally highly toxic and has multiple kinds of adverse reactions, including pulmonary injury. Our work was designed to demonstrate the ability of etoricoxib (ETO) to mitigate MTX-induced lung injury in experimental animals. Adult male Wistar rats were separated into four groups. The first group consisted of healthy controls that received carboxymethyl cellulose (1 ml/day, p.o.), the second group received a single dose of MTX (20 mg/kg/day, i.p.), the third group received ETO (10 mg/kg/day, p.o.) for three weeks, and the fourth group first received a single MTX (20 mg/kg, i.p.) and then was treated with ETO for three weeks. Concomitant treatment with ETO and MTX improved the histological structure of the lung tissue. It significantly altered the levels of oxidant/antioxidant markers, such as malondialdehyde (MDA), heme oxygenase-1 (HO-1), reduced glutathione (GSH), and nuclear factor erythroid 2-related factor 2 (Nrf-2), in favor of antioxidants. Moreover, ETO can normalize the proinflammatory cascade, which includes tumor necrosis factor-alpha (TNF-α) and interleukin-1 beta (IL-1β). At the molecular level, ETO downregulated the protein expression of toll-like receptor 4 (TLR4), nuclear factor kappa-B (NF-κB), and p38 mitogen-activated protein kinase (p38 MAPK) in inflamed rat lungs. In conclusion, our findings indicate that oral administration of ETO ameliorates MTX-induced lung injury by inhibiting oxidative stress and suppressing the TLR4/NF-κB and TLR4/p38-MAPK inflammatory signaling pathways.

The objective of this study was to assess the use of pMDI alone and pMDI with different spacers in asthmatic patients and to identify any associations between errors in handling the device for the first time and the sessions needed to reach the correct handling method, considering patient demographics and clinical characteristics. A total of 150 Asthmatic patients were crossed over to handle pMDI alone and with add-on inhalable devices (Aerochamber plus, Tips Haler, Able, Dispoz-able and Aer-8) randomly, without receiving verbal or demonstrative instruction (baseline assessment). The assessment of the inhaler technique was performed using checklists that had been set beforehand. Subsequently, the proper utilization of the inhaler was exhibited, and the patient's inhaler usage was reassessed. The demonstration was repeated until an optimal technique was attained. The number of counselling attempts required to achieve successful management, together with patient demographics and clinical factors, were documented. The mean percentage of total errors at baseline shows that pMDI alone is significantly higher than pMDI attached to add-on devices (53.90 ± 9.71, 32.54 ± 13.93, 24.53 ± 14.93, 21.6 ± 14.48, 25.14 ± 10.99, 27.47 ± 10.28) for pMDI alone, Aerochamber plus, Tips Haler, Able, Dispozable and Aer-8 respectively at p < 0.01. Able and Tips Haler spacers are significantly lower than other spacers with pMDI and pMDI alone in terms of total sessions needed to attain the complete optimal handling technique at p < 0.01. Weak and very weak correlations were observed between the percentage of total errors at baseline and the total sessions with education years, Montreal Cognitive Assessment, and age as well as some demographics and clinical variables. Handling pMDI can be challenging however the introduction of spacers simplifies this procedure. Different spacers cannot be treated as a homogeneous group due to variations in handling techniques and ease of use. the Able spacer requires the fewest handling steps of any spacer and has the highest percentage of patients who can use it without assistance.

Emotion recognition, a burgeoning field with applications in healthcare, human-computer interaction, and affective computing, has seen significant advances by integrating physiological signals and environmental factors. With the increasing development of Artificial Intelligence (AI), the precision and efficiency of machine learning (ML) algorithms are becoming increasingly crucial to a growing number of businesses. However, the mystery and black-box effect of ML methods limits our ability to comprehend the underlying applied logic and merely allow us to obtain results. Consequently, understanding the intricate models created for emotion recognition is still vital. ML techniques, such as Random Forest (RF) and Decision Tree (DT) classifiers, were used to predict emotional labels on a dataset collected from an actual study that includes environmental and physiological sensors. In this paper, four performance indicators were used to evaluate the results: precision, recall, precision, and F1 score. Based on the findings, the RF and DT algorithms demonstrated impressive performance with an average accuracy of 98%, precision of 97.8%, recall of 97.8%, and F-measure of 98.2%. Furthermore, this paper discusses the use of Explainable Artificial Intelligence (XAI) techniques, such as Shapley additive explanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME) that were implemented and applied to the results obtained from these ML methods, to improve the interpretability and transparency of emotion recognition systems that integrate physiological signals and environmental factors. This article investigates the significance of these methods in providing insights into the relationships between human emotions and external stimuli and their potential to advance personalized and context-based applications in various domains.

Background Claudin-5 is a vital constituent of tight junctions, which are critical elements of the blood-brain barrier. In people with neuropsychiatric disorders, peripheral inflammation is often found, although it is less common in healthy populations. The objective of this study was to examine the relationship between Claudin-5, peripheral immune cells, and the severity of symptoms in children with attention deficit hyperactivity disorder (ADHD). Methods The study included a cohort of 33 children diagnosed with ADHD and 29 control subjects, all aged between 5 and 12 years. The intensity of ADHD symptoms was evaluated using Conner’s questionnaire, which the parents completed. Each kid had serum level measurements of Claudin-5 and a complete blood count in order to establish a correlation with symptoms of ADHD. Results Serum Claudin-5 levels are lower in the ADHD group compared to the control group; median (IQR) = 30.94 (4-137) and 44.12 (4–223.3) respectively (p = 0.69). The levels of neutrophils and neutrophil/lymphocyte ratio are significantly higher in ADHD than in controls (p = 0.011 and 0.015, respectively). Lymphocytes have a significant positive correlation with ADHD symptoms severity, namely, total Conner’s scale and inattention (p = 0.021 and 0.004 respectively), while NLR has a significant negative correlation with total Conner’s score and impulsivity (p = 0.046, p = 0.038), also a negative correlation yet not significant between serum Claudin-5 level and total Conner’s score, hyperactivity, impulsivity, and inattention. Neutrophils were found to have a significant positive linear regression with Claudin-5 (p = 0.023). Conclusion These results revealed that BBB integrity is affected in ADHD children, as claudin-5 levels were found to be lower in children with ADHD, lymphocytes were found to be associated with increased ADHD symptoms severity, and NLR was associated with decreased symptoms severity, which may be via the positive effects of increased neutrophils on Claudin-5 levels.