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Combinatory flooding techniques evolved over the years to mitigate various limitations associated with unitary flooding techniques and to enhance their performance as well. This study investigates the potential of a combination of 1-hexadecyl-3-methyl imidazolium bromide (C16mimBr) and monoethanolamine (ETA) as an alkali–surfactant (AS) formulation for enhanced oil recovery. The study is conducted comparative to a conventional combination of cetyltrimethylammonium bromide (CTAB) and sodium metaborate (NaBO2). The study confirmed that C16mimBr and CTAB have similar aggregation behaviors and surface activities. The ETA–C16mimBr system proved to be compatible with brine containing an appreciable concentration of divalent cations. Studies on interfacial properties showed that the ETA–C16mimBr system exhibited an improved IFT reduction capability better than the NaBO2–CTAB system, attaining an ultra-low IFT of 7.6 × 10−3 mN/m. The IFT reduction performance of the ETA–C16mimBr system was improved in the presence of salt, attaining an ultra-low IFT of 2.3 × 10−3 mN/m. The system also maintained an ultra-low IFT even in high salinity conditions of 15 wt% NaCl concentration. Synergism was evident for the ETA–C16mimBr system also in altering the carbonate rock surface, while the wetting power of CTAB was not improved by the addition of NaBO2. Both the ETA–C16mimBr and NaBO2–CTAB systems proved to form stable emulsions even at elevated temperatures. This study, therefore, reveals that a combination of surface-active ionic liquid and organic alkali has excellent potential in enhancing the oil recovery in carbonate reservoirs at high salinity, high-temperature conditions in carbonate formations.

Background Dandy-Walker syndrome (DWS) is an uncommon congenital abnormality characterised by agenesis or hypoplasia of the cerebellar vermis, cystic dilation of the fourth ventricle, and posterior fossa expansion. Neurological defects usually accompany the DWS; however, it has not been documented to coexist with amelia, genu recurvatum, complex congenital cardiac defects, or dyslipidaemia. Case presentation An 18-month-old girl who is a known case of DWS in association with multiple congenital anomalies, including bilateral amelia of the upper limbs, developmental dysplasia of the hip (DDH), bilateral hyperextended knees (genu recurvatum), congenital hypoplastic right ventricle, patent ductus arteriosus (PDA), and a superficial abdominal haemangioma, presented with fever and severe respiratory distress, likely due to recurrent aspiration and infections that required immediate medical intervention. Laboratory work-up revealed severe dyslipidaemia, including extremely high triglyceride (1372 mg/dL), total cholesterol (1254 mg/dL), low-density lipoprotein (975.6 mg/dL), and very low-density lipoprotein (274 mg/dL) levels, as well as significantly raised globulin (10.7 g/dL). The cause of dyslipidaemia is unknown; however, it may indicate an associated undiscovered genetic or metabolic problem that potentially increases the risk of cardiovascular and respiratory complications, which contribute to the severity of her presentation. Unfortunately, the patient died after ten days of critical care, and medical laboratory tests to exclude familial hypercholesterolaemia and pancreatitis, as well as the follow-up levels of dyslipidaemia, were not performed. Conclusion The girl had multiple associations with DWS, necessitating thorough evaluation, including karyotyping and genetic sequencing, to improve long-term outcomes. However, cost barriers and a lack of specialised medical laboratories limited the scope of their request.

The decaying prices and improving efficiency of bifacial solar photovoltaic (PV) technologies make them most promising for harnessing solar radiation. Deserts have a high solar potential, but harsh conditions like high temperatures and dust negatively affect the performance of any proposed solar system. The most attractive aspect of deserts is their long-term sustainability, as they are free from urban and agricultural expansion. In this work, the System Advisor Model (SAM) software version 2023.12.17 was used to model a 100 MW PV plant and evaluate the techno-economic performance of fixed, 1-axis, and 2-axis bifacial systems under the climatic conditions of six deserts from around the world. This study explores technical parameters such as the performance ratio, specific yield, and capacity factor. Additionally, the levelized cost of energy (LCOE) indicator was used to compare the economic performance of the different systems. Results showed high specific yield: the averages for the three systems in six deserts were 2040, 2372, and 2555 kWh/kWp, respectively. Economic analysis found that an LCOE below 4 ¢/kWh is achievable in all deserts, reaching a minimum of 2.45 ¢/kWh under favorable conditions. These results emphasize the high potential of utility-scale PV projects in deserts to advance a green, sustainable energy future.

The early diagnosis and prognosis of breast cancer is essential for improving breast cancer survival rates and improving breast cancer clinical outcomes. This study aims to provide breast cancer predictive capabilities through the development and application of a robust hybrid computational prediction methodology that performs testing across multiple whole-genome studies; this research was validated using both TCGA (The Cancer Genome Atlas) and METABRIC (Molecular Taxonomy of Breast Cancer International Consortium). Instead of using traditional methods, where researchers select specific gene sets from the literature, we chose to operate on the highest dimensional input (17,814 genes in TCGA) and the most extensive set of clinical and genomic variables available (503 clinical/genomic features in METABRIC). A multi-stage feature selection process utilizing Random Forest (RF) rankings in conjunction with Association Rule Mining (ARM) was developed to discover important biomarkers. Predictive analysis was performed using a hybrid deep learning model, which contains Convolutional Neural Networks (CNN) in combination with Bidirectional Long Short-Term Memory (BiLSTM) networks, with iterative optimization through the utilization of Bayesian methods. SMOTE and Gaussian noise augmentations were incorporated into the new model to provide additional robustness by addressing class imbalance and minimizing the risk of overfitting (due to the amount of noise present in the training data). The new model outperformed the TCGA-derived model with an accuracy of 97.4% (AUC=0.995), and after validation on the METABRIC dataset, exhibited an even greater accuracy of 99.30% with a 100% recall rate for predicting cancer-related mortality. Through these findings, we have shown that the integration of association-based feature selection with hybrid deep learning architectures has created a tool for breast cancer diagnosis and prognosis that can provide reliable and generalizable results for diverse groups of patients.

Patients diagnosed with breast cancer exhibit a diverse range of prognostic outcomes due to the varied nature of the disease across different patient groups. To address this complexity and enhance prognostic predictions based on gene expression data from breast cancer samples, this study has developed an integrated deep learning method that combines Convolutional Neural Networks (CNN) with Bidirectional Long Short-Term Memory (BiLSTM) networks. This automated pipeline conducts a correlation analysis using Pearson correlation to derive a reliable 236-gene set, ensuring no data contamination from patient samples.Furthermore, patterns of gene–gene interactions based on correlations were examined to provide further evidence of the biological relevance of the gene set that was selected. The training and validation of the proposed model utilized data from The Cancer Genome Atlas-Breast Cancer (TCGA-BRCA) and was assessed using the METABRIC dataset to enhance generalization capabilities. Experimental results indicate that the Full Hybrid (CNN BiLSTM) model significantly outperforms other machine learning and deep learning approaches. Notably, while the BiLSTM-only model achieved an optimal Recall of 0.9319, the hybrid model demonstrated a substantially higher Recall of 0.9943, accompanied by an impressive ROC AUC of 0.9955 and an F1 score of 0.9962. Furthermore, the proposed framework has been statistically validated, achieving a minimal variance of 0.000083 even under conditions of up to 20% noise perturbation. Optimization of this framework was conducted using the Optuna Bayesian Optimization methodology on a dual NVIDIA Tesla T4 array configuration. Overall, this article presents a universal computational tool for precision medicine in breast cancer, designed to yield consistent results across diverse patient scenarios.

The evolution of insect resistance to insecticides is frequently associated with overexpression of one or more cytochrome P450 enzyme genes. Although overexpression of CYP450 genes is a well-known mechanism of insecticide resistance, the underlying regulatory mechanisms are poorly understood. Here we uncovered the mechanisms of overexpression of the P450 gene, CYP321A8 in a major pest insect, Spodoptera exigua that is resistant to multiple insecticides. CYP321A8 confers resistance to organophosphate (chlorpyrifos) and pyrethroid (cypermethrin and deltamethrin) insecticides in this insect. Constitutive upregulation of transcription factors CncC/Maf are partially responsible for upregulated expression of CYP321A8 in the resistant strain. Reporter gene assays and site-directed mutagenesis analyses demonstrated that CncC/Maf enhanced the expression of CYP321A8 by binding to specific sites in the promoter. Additional cis -regulatory elements resulting from a mutation in the CYP321A8 promoter in the resistant strain facilitates the binding of the orphan nuclear receptor, Knirps , and enhances the promoter activity. These results demonstrate that two independent mechanisms; overexpression of transcription factors and mutations in the promoter region resulting in a new cis -regulatory element that facilitates binding of the orphan nuclear receptor are involved in overexpression of CYP321A8 in insecticide-resistant S . exigua .

Polycystic ovary syndrome (PCOS) is a common endocrine disorder in women of reproductive age. Metabolic sequelae associated with PCOS range from insulin resistance to type 2 diabetes mellitus (T2DM) and cardiovascular disease (CVD). Insulin resistance plays a significant role in the pathophysiology of PCOS and it is a reliable marker for cardiometabolic risk. Although insulin sensitising agents such as metformin have been traditionally used for managing metabolic aspects of PCOS, their efficacy is low in terms of weight reduction and cardiovascular risk reduction compared with newer agents such as incretin mimetics and SGLT2 inhibitors. With current pharmaceutical advances, potential therapeutic options have increased, giving patients and clinicians more choices. Incretin mimetics are a promising therapy with a unique metabolic target that could be used widely in the management of PCOS. Likewise, bariatric procedures have become less invasive and result in effective weight loss and the reversal of metabolic morbidities in some patients. Therefore, surgical treatment targeting weight loss becomes increasingly common in the management of obese women with PCOS. Newer emerging therapies, including twincretins, triple GLP-1 agonists, glucagon receptor antagonists and imeglemin, are promising therapeutic options for treating T2DM. Given the similarity of metabolic and pathological features between PCOS and T2DM and the variety of therapeutic options, there is the potential to widen our strategy for treating metabolic disorders in PCOS in parallel with current therapeutic advances. The review was conducted in line with the recommendations from the international evidence-based guideline for the assessment and management of polycystic ovary syndrome 2018.

Agrivoltaics—the co-location of photovoltaic energy production with agriculture—offers a promising pathway to address growing pressures on land, food, and clean energy resources. This study evaluates the first agrivoltaic pilot installation in Jordan, located in Amman (935 m above sea level; hot-summer Mediterranean climate), during its first operational year. Two 11.1 kWp bifacial photovoltaic (PV) systems were compared: (i) a south-facing array tilted at 10°, and (ii) a vertical east–west “fence” configuration. The tilted system achieved an annual specific yield of 1962 kWh/kWp, approximately 35% higher than the 1288 kWh/kWp obtained from the vertical array. Seasonal variation was observed, with the performance gap widening to ~45% during winter and narrowing to ~22% in June. As expected, the vertical system exhibited more uniform diurnal output, enhanced early-morning and late-afternoon generation, and lower soiling losses. The light profiles measured for the year indicate that vertical systems barely impede the light requirements of crops, while the tilted system splits into distinct profiles for the intra-row area (akin to the vertical system) and sub-panel area, which is likely to support only low-light requirement crops. This configuration increases the levelized cost of electricity (LCOE) by roughly 88% compared to a conventional ground-mounted system due to elevated structural costs. In contrast, the vertical east–west system provides an energy yield equivalent to about 33% of the land area at the tested configuration but achieves this without increasing the LCOE. These results highlight a fundamental trade-off: elevated tilted systems offer greater land-use efficiency but at higher cost, whereas vertical systems preserve cost parity at the expense of lower energy density.

The World Health Organization (WHO) declared the current COVID-19 a public health emergency of international concern on January 30, 2020. Countries in the Eastern Mediterranean Region (EMR) have a high vulnerability and variable capacity to respond to outbreaks. Many of these countries addressed the need for increasing capacity in the areas of surveillance and rapid response to public health threats. Moreover, countries addressed the need for communication strategies that direct the public to actions for self- and community protection. This viewpoint article aims to highlight the contribution of the Global Health Development (GHD)/Eastern Mediterranean Public Health Network (EMPHNET) and the EMR’s Field Epidemiology Training Program (FETPs) to prepare for and respond to the current COVID-19 threat. GHD/EMPHNET has the scientific expertise to contribute to elevating the level of country alert and preparedness in the EMR and to provide technical support through health promotion, training and training materials, guidelines, coordination, and communication. The FETPs are currently actively participating in surveillance and screening at the ports of entry, development of communication materials and guidelines, and sharing information to health professionals and the public. However, some countries remain ill-equipped, have poor diagnostic capacity, and are in need of further capacity development in response to public health threats. It is essential that GHD/EMPHNET and FETPs continue building the capacity to respond to COVID-19 and intensify support for preparedness and response to public health emergencies.

Introduction: Polycystic ovary syndrome (PCOS) is a common endocrine disorder that affects women of reproductive age. Metabolic consequences associated with PCOS include, but are not limited to, insulin resistance (IR), type 2 diabetes mellitus (T2DM) and cardiovascular disease (CVD). This narrative review aims to provide a comprehensive overview of the potential therapeutic roles of the incretin-based therapies in the management of PCOS. Methods: We performed a systematic search of databases including PubMed, MEDLINE and EMBASE up to 1 October 2020. We developed a search string of medical subject headings (MeSH) including the terms PCOS, incretin mimetics, glucagon-like peptide-1 (GLP-1), glucagon-like peptide-1 receptor antagonists (GLP-1 RAs), liraglutide, exenatide, semaglutide, dipeptidyl peptidase-4 (DPP-4) inhibitors, combined with IR, testosterone and sex hormone-binding globulin (SHBG). Results: We identified 854 relevant articles and, after the initial screening, eight interventional animal studies, one observational animal study, 14 interventional human studies, two case–control studies and one systematic review were included. These studies showed the potential significant roles of GLP-1 RAs and DPP-4 inhibitors in the management of PCOS, with significant improvements in the metabolic parameters, including substantial weight reduction and improved insulin sensitivity. These agents also improved the hormonal parameters through decreased free androgen and increased SHBG. Moreover, they improved menstrual regularity, increased fertility with enhanced ovulation and pregnancy in obese women with PCOS. Conclusion: GLP-1 RAs and DPP-4 inhibitors have a promising therapeutic role in PCOS; however, larger clinical trials are needed to establish the role of incretin-based therapies in the management of PCOS.