Enhanced ovarian cancer survival prediction using temporal analysis and graph neural networks.

Ovarian cancer is a formidable health challenge that demands accurate and timely survival predictions to guide clinical interventions. Existing methods, while commendable, suffer from limitations in harnessing the temporal evolution of patient data and capturing intricate interdependencies among different data elements. In this paper, we present a novel methodology which combines Temporal Analysis and Graph Neural Networks (GNNs) to significantly enhance ovarian cancer survival rate predictions. The shortcomings of current processes originate from their disability to correctly seize the complex interactions amongst diverse scientific information units in addition to the dynamic modifications that arise in a affected person`s nation over time. By combining temporal information evaluation and GNNs, our cautioned approach overcomes those drawbacks and, whilst as compared to preceding methods, yields a noteworthy 8.3% benefit in precision, 4.9% more accuracy, 5.5% more advantageous recall, and a considerable 2.9% reduction in prediction latency. Our method's Temporal Analysis factor uses longitudinal affected person information to perceive good-sized styles and tendencies that offer precious insights into the direction of ovarian cancer. Through the combination of GNNs, we offer a robust framework able to shoot complicated interactions among exclusive capabilities of scientific data, permitting the version to realize diffused dependencies that would affect survival results. Our paintings have tremendous implications for scientific practice. Prompt and correct estimation of the survival price of ovarian most cancers allows scientific experts to customize remedy regimens, manipulate assets efficiently, and provide individualized care to patients. Additionally, the interpretability of our version`s predictions promotes a collaborative method for affected person care via way of means of strengthening agreement among scientific employees and the AI-driven selection help system. The proposed approach not only outperforms existing methods but also has the possible to develop ovarian cancer treatment by providing clinicians through a reliable tool for informed decision-making. Through a fusion of Temporal Analysis and Graph Neural Networks, we conduit the gap among data-driven insights and clinical practice, proposing a capable opportunity for refining patient outcomes in ovarian cancer management operations.

Can serum 17-hydroxy progesterone predict an improvement in semen parameters following micro-varicocelectomy? A prospective study.

BACKGROUND & OBJECTIVES: Notably, 17-hydroxy progesterone (17-OHP) (17-OHP) is a precursor for testosterone (T) synthesis, and intratesticular testosterone (ITT) is essential for spermatogenesis. Varicocele (Vx) has an estimated prevalence of 15% in the general population and 35% in those with primary infertility. We aimed to evaluate the correlation between changes of serum 17-OHP after sub-inguinal micro-varicocelectomy and improvement of semen parameters. PATIENTS AND METHODS: The current prospective study included 45 infertile men attending the andrology clinic form February 2021 to August 2021. Two semen analyses and hormonal profile were evaluated. Colored duplex ultasonography (CDUS) was done in standing and supine position for accurate measurements of testicular volumes and confirmation of Vx. Patients underwent sub-inguinal micro-varicocelectomy using a surgical microscope HB surgitech. We followed them prospectively up for three months following micro-varicocelectomy with serum TT and 17-OHP. RESULTS: Sperm concentration improved significantly from 8.36 ± 5.04 million/ml to 12.52 ± 8.42 million/ml after 3 months following sub-inguinal micro-varicocelectomy (p= 0.001), with normalization of concentration in 15/45 (33%) patients. Total motility did not improve significantly but progressive motility improved significantly from 8.62 ± 8.74% to 16.24 ± 14.45% (p=0.001). Abnormal forms significantly declined from 96.67 ± 2.03% to 95.75 ± 2.47% (p=0.009).  Serum 17 OHP and 17 OHP/total testosterone (TT) improved significantly from 1.21 ± 0.45 ng/ml and 0.26 ± 0.09 to 1.42 ± 0.76 ng/ml and 0.3 ± 0.16 (p= 0.013, p= 0.004), respectively, while serum TT did not improve significantly. A significant correlation was found between improvement in sperm concentration and both serum 17 OHP and 17 OHP/TT ratio (p=0.001, p=004). Furthermore, change in abnormal sperm forms showed significant correlations with changes in both 17-OHP and 17-OHP/TT. CONCLUSION: 17 OHP and 17OHP/ TT ratio can be used as biomarkers to detect improvement in semen parameters following sub-inguinal micro-varicocelectomy.

Silicon mediated heavy metal stress amelioration in fruit crops.

Fruit crops are essential for human nutrition and health, yet high level of heavy metal levels in soils can degrade fruit quality. These metals accumulate in plant roots and tissues due to factors like excessive fertilizer and pesticide use, poor waste management, and unscientific agricultural practices. Such accumulation can adversely affect plant growth, physiology, and yield. Consuming fruits contaminated with toxic metals poses significant health risks, including nervous system disorders and cancer. Various strategies, such as organic manuring, biomaterials, and modified cultivation practices have been widely researched to reduce heavy metal accumulation. Recently, silicon (Si) application has emerged as a promising and cost-effective solution for addressing biological and environmental challenges in food crops. Si, which can be applied to the soil, through foliar application or a combination of both, helps reduce toxic metal concentrations in soil and plants. Despite its potential, there is currently no comprehensive review that details Si's role in mitigating heavy metal stress in fruit crops. This review aims to explore the potential of Si in reducing heavy metal-induced damage in fruit crops while enhancing growth by alleviating heavy metal toxicity.

Tackling exosome and nuclear receptor interaction: an emerging paradigm in the treatment of chronic diseases.

Nuclear receptors (NRs) function as crucial transcription factors in orchestrating essential functions within the realms of development, host defense, and homeostasis of body. NRs have garnered increased attention due to their potential as therapeutic targets, with drugs directed at NRs demonstrating significant efficacy in impeding chronic disease progression. Consequently, these pharmacological agents hold promise for the treatment and management of various diseases. Accumulating evidence emphasizes the regulatory role of exosome-derived microRNAs (miRNAs) in chronic inflammation, disease progression, and therapy resistance, primarily by modulating transcription factors, particularly NRs. By exploiting inflammatory pathways such as protein kinase B (Akt)/mammalian target of rapamycin (mTOR), nuclear factor kappa-B (NF-κB), signal transducer and activator of transcription 3 (STAT3), and Wnt/ß-catenin signaling, exosomes and NRs play a pivotal role in the panorama of development, physiology, and pathology. The internalization of exosomes modulates NRs and initiates diverse autocrine or paracrine signaling cascades, influencing various processes in recipient cells such as survival, proliferation, differentiation, metabolism, and cellular defense mechanisms. This comprehensive review meticulously examines the involvement of exosome-mediated NR regulation in the pathogenesis of chronic ailments, including atherosclerosis, cancer, diabetes, liver diseases, and respiratory conditions. Additionally, it elucidates the molecular intricacies of exosome-mediated communication between host and recipient cells via NRs, leading to immunomodulation. Furthermore, it outlines the implications of exosome-modulated NR pathways in the prophylaxis of chronic inflammation, delineates current limitations, and provides insights into future perspectives. This review also presents existing evidence on the role of exosomes and their components in the emergence of therapeutic resistance.

Impact of Partial Replacement of Clover by Anise, Basil, Mint and Fennel Remnants in Rabbits Diet on Blood Constituents.

<b>Background and Objective:</b> The clover plant (alfalfa) is considered the primary fiber source in the rabbit diet in Mediterranean Sea countries like Egypt, so researchers are always trying to find alternatives and aromatic and medicinal plant remnants could be one of them. So, this study was designed to determine the effects of some aromatic and medicinal plant remnants on New Zealand white rabbits' blood hematological and biochemical aspects. <b>Materials and Methods:</b> A total of 108 weaned white New Zealand rabbits at five weeks of age were used to consider the effect of using remnants of mint, fennel, basil and anise with or without probiotics to replace 50% from alfalfa hay in rabbits' diets. Four remnants were obtained after etheric oil distillation and were incorporated in rabbit diets at level 17.5% without probiotics and with probiotics (replacement 50% of alfalfa hay). Rabbits were randomly assigned into nine experimental groups; the experimental period lasted eight weeks. Rabbit blood hematological and blood biochemical were analyzed. <b>Results:</b> The highest values of RBC 6.03 µL, HCT 37.13%, WBC 12.70 µL and lymph percentage were found in the basil+probiotics group. In contrast, the highest value of hemoglobin (HGB 10,50 g/dL), MCV 64.13 fl, MCH 23.27pg, MCHC 36.40 g/dL, PLT 463 µL, urea 50.33 mg/dL and creatinine 1.30 mg/dL were found in anise+probiotic group. In contrast, RDW-CV 33.17%, Mid 13.17 µL, granulocytes (Gran 7.13 µL) and PDW 16.73 in the mint group. Furthermore, RDW-SD (34.40 fl) and procalcitonin (PCT 0.35%) were found in the control group and the highest values ALT 142 IU/L and AST 77.33 IU/L were found in the fennel group. The highest albumin value (3.10 g/dL) was found in the anise group and the highest total protein (TP 5.23 g/dL) was found in the mint+probiotic group. <b>Conclusion:</b> The results proved that using these medicinal plant remnants and probiotics as substitutes for half the amount of alfalfa used in the diet of New Zealand white rabbits did not have a negative effect and improved their health condition.

Expanding the use of mathematical modeling in healthcare epidemiology and infection prevention and control.

During the coronavirus disease 2019 pandemic, mathematical modeling has been widely used to understand epidemiological burden, trends, and transmission dynamics, to facilitate policy decisions, and, to a lesser extent, to evaluate infection prevention and control (IPC) measures. This review highlights the added value of using conventional epidemiology and modeling approaches to address the complexity of healthcare-associated infections (HAI) and antimicrobial resistance. It demonstrates how epidemiological surveillance data and modeling can be used to infer transmission dynamics in healthcare settings and to forecast healthcare impact, how modeling can be used to improve the validity of interpretation of epidemiological surveillance data, how modeling can be used to estimate the impact of IPC interventions, and how modeling can be used to guide IPC and antimicrobial treatment and stewardship decision-making. There are several priority areas for expanding the use of modeling in healthcare epidemiology and IPC. Importantly, modeling should be viewed as complementary to conventional healthcare epidemiological approaches, and this requires collaboration and active coordination between IPC, healthcare epidemiology, and mathematical modeling groups.

Exergy, exergoeconomic optimization and exergoenvironmental analysis of a hybrid solar, wind, and marine energy power system: A strategy for carbon-free electrical production.

In this research, aligned with global policies aimed at reducing CO2 emissions from traditional power plants, we developed a holistic energy system utilizing solar, wind, and ocean thermal energy sources, tailored to regions optimal for ocean thermal energy conversion (OTEC). The selected site, characterized by favorable wind and solar conditions close to areas with high OTEC potential, is designed to meet the electricity needs of a coastal community. The system's core components include an Organic Rankine Cycle, turbines, thermoelectric elements, pumps, a heat exchanger, a wind turbine, and a solar collector. A detailed system analysis and thermodynamic evaluation based on thermodynamic principles were carried out using the Engineering Equation Solver (EES) software. Key factors such as wind speed, solar radiation, and collector area were critical in determining system performance. To enhance the system's effectiveness, we conducted a comprehensive comparison of optimization algorithms, incorporating the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and utilizing a Pareto front for value optimization. This approach significantly outperformed other algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Simulated Annealing (SA) in terms of system efficiency and cost-effectiveness. The developed system achieved an exergy efficiency of 14.46 % and a cost rate of $74.98 per hour, demonstrating its suitability for its intended functions. Moreover, exergoenvironmental evaluation was conducted for the proposed plant. The findings revealed that key component HEX has a high exergoenvironmental factor due to their use of hot water, which has zero unit exergoenvironmental impact. Additionally, pumps demonstrated a zero exergoenvironmental impact factor, indicating negligible component-related environmental impacts. Sensitivity analysis further evaluated critical performance parameters, revealing that increases in solar irradiation lead to decreased total system cost rates, while higher turbine temperatures resulted in a remarkable 14.08 % reduction in the system's cost rate. These results underscore the economic viability of operating the system at higher temperatures and strengthen the argument for its adoption from a financial perspective.

Radiative flow of cross ternary hybrid nanofluid (MoS 2, TiO 2 , Ag/CMC-water) in a Darcy Forchheimer porous medium over a stretching cylinder with entropy minimization.

Stretching cylinders play a crucial role in the plastic and metal extrusion processes. This current investigation is to examine the Darcy Forchheimer flow of Carboxymethyl cellulose ( C M C ) /water-based tri-hybrid nanofluid through a stretching cylinder. A composite of ternary hybrid nanofluid containing M o S 2 , T i O 2 and A g with CMC-water-based fluid has been added to the Crossflow model. The equations regulating motion and the equation for entropy generation are both formulated using cylindrical coordinates. The governing partial differential equations (PDEs) equations have been transformed into an ordinary differential equations (ODEs) system using a similar scaling operation. Afterward, the B V P 4 c function employs the finite difference method and then implements the Lobatto IIIa formula. To fully understand how the flow behaves close to the cylinder's surface, the effects of these various factors on the number of entropy generation, Bejan number, the speed of the flow, the temperature and concentration distributions have been carefully studied. The result reveals that enhancing the values of Weissenberg number W e and the porosity parameter declines the velocity profile. An increment in the curvature parameter ß declines the velocity gradient and temperature distribution. In addition, enhancement in the radiation parameter escalates the entropy minimization and Bejan number. Furthermore, the impact of drag friction, heat, and mass are displayed in tabular form and elaborated suitably. The outcomes are authenticated with previously published literature for accuracy and authenticity.

Assessment of the unwanted tooth movement associated with an extended maxillary fixed retainer (3D analysis).

BACKGROUND: Posttreatment changes after orthodontic treatment are challenging. One of the main reasons for such a phenomenon is the lack of patient compliance with removable retainers especially in the maxillary arch, due to palatal coverage, deterioration of speech, decreased masticatory efficiency, and loss of retainers. Fixed retainers have been introduced to overcome patient compliance and provide longer stable results. However, teeth still show movements when a six-unit fixed retainer is in place. Thus, in this study, an eight-unit fixed retainer was evaluated in an attempt to eliminate unwanted movements. THE AIM OF THIS RESEARCH: was to assess short-term positional changes associated with an eight-unit extended maxillary fixed retainer. MATERIALS AND METHODS: A single-arm clinical trial was conducted to address the aim of the study. This research was approved by the institutional review board of the Faculty of Dentistry, Alexandria University (IORG:0008839, No-0479-8/2022). The registration date of this study was 5/06/2023. Twenty-eight patients (19.8 ± 4.5 years) who had finished the active orthodontic phase and started retention had an eight-unit extended maxillary fixed retainer that was bonded to the palatal surface of the maxillary incisors, canines, and the first premolars or the second premolars. Pre-retention and one-year post-retention intra-oral scans were made to produce STL files that were superimposed to determine the amount of tooth change. Additionally, analysis of digital casts and lateral cephalometric radiographs was performed. RESULTS: Statistically significant changes in all planes and the rotation of teeth after one year of retention were found. The upper right lateral incisor exhibited the most evident change in the vertical plane, while the upper right central incisor exhibited the greatest change overall. Minimal changes in the cast measurements were observed. Lateral cephalometric measurements showed minimal changes after one year of retention, and these changes were not statistically significant except in the interincisal angle and the angle between the upper incisor and the line connecting the A-point to the pogonion. CONCLUSION: Increasing the extension of maxillary fixed retainers did not eliminate unwanted tooth movement in the first year of retention.

Impact of non-covalent interactions on the solvation of ovalbumin in an aqueous environment of different pHs: Thermodynamic and diffusion studies.

The solvation behavior of protein is an important factor in protein-based food products. In the present study, the xylitol (XY) - ovalbumin (OVN) interaction in an aqueous solution of different pH conditions is analyzed in two methods. In one method, the thermodynamic parameters Gibbs free energy, free volume, and internal pressure are calculated by using ultrasonic velocity, density, and viscosity in addition the refractive index is also measured. The second method is a theoretical method in which using the Laplace transform technique the diffused amount of protein have been calculated for OVN with and without XY in different pH environment. The addition of XY with OVN makes the system with more free energy and free volume as the internal pressure decreases. This trend shows that preferential interaction occurs between solvent-solute molecules. The diffusivity of OVN is reduced after the addition of XY representing the strength of protein-protein interaction. The effect of pH changes is well reflected in both experimental and theoretical results. The results confirm that acidic pH extremity offers more solvation of OVN compared to alkaline pH extremity.

Innovative optimization for enhancing Pb2+ biosorption from aqueous solutions using Bacillus subtilis.

Introduction: Toxic heavy metal pollution has been considered a major ecosystem pollution source. Unceasing or rare performance of Pb2+ to the surrounding environment causes damage to the kidney, nervous, and liver systems. Microbial remediation has acquired prominence in recent decades due to its high efficiency, environment-friendliness, and cost-effectiveness. Methods: The lead biosorption by Bacillus subtilis was optimized by two successive paradigms, namely, a definitive screening design (DSD) and an artificial neural network (ANN), to maximize the sorption process. Results: Five physicochemical variables showed a significant influence (p < 0.05) on the Pb2+ biosorption with optimal levels of pH 6.1, temperature 30°C, glucose 1.5%, yeast extract 1.7%, and MgSO4.7H2O 0.2, resulting in a 96.12% removal rate. The Pb2+ biosorption mechanism using B. subtilis biomass was investigated by performing several analyses before and after Pb2+ biosorption. The maximum Pb2+ biosorption capacity of B. subtilis was 61.8 mg/g at a 0.3 g biosorbent dose, pH 6.0, temperature 30°C, and contact time 60 min. Langmuir's isotherm and pseudo-second-order model with R2 of 0.991 and 0.999 were suitable for the biosorption data, predicting a monolayer adsorption and chemisorption mechanism, respectively. Discussion: The outcome of the present research seems to be a first attempt to apply intelligence paradigms in the optimization of low-cost Pb2+ biosorption using B. subtilis biomass, justifying their promising application for enhancing the removal efficiency of heavy metal ions using biosorbents from contaminated aqueous systems.

Synergistic enhancement: Exploring the potential of piperine in cancer therapeutics through chemosensitization and combination therapies.

Despite significant advancements in chemotherapy, effective treatments for advanced cancer stages remain largely elusive due to chemoresistance. Resistance to anticancer agents in cancer cells can arise through various mechanisms, including multi-drug resistance, inhibition of apoptosis, modification of drug targets, and enhancement of DNA repair capabilities. Consequently, there is a critical need for agents that can suppress the molecular signatures responsible for drug resistance. Piperine, an active alkaloid extracted from Piper nigrum L. (black pepper), is one such agent that has been extensively studied for its potential in addressing chronic diseases, including cancer. Piperine's antineoplastic properties are mediated through the regulation of numerous key cellular signaling pathways and the modulation of various biological processes. Its capability to enhance drug bioavailability and counteract mechanisms of drug resistance, such as the inhibition of P-glycoprotein (P-gp) and multidrug resistance-associated protein 1 (MRP-1), emphasizes its potential as an adjunct in cancer therapy. Research across various cancer types has demonstrated piperine's role in chemosensitization by targeting P-gp and MRP-1 and altering drug-metabolizing enzymes. This review provides a comprehensive analysis of piperine's pharmacological characteristics and its capacity to modulate several cellular signaling pathways involved in drug resistance. Furthermore, the review emphasizes how piperine, when used in conjunction with other chemotherapeutic agents or natural compounds, can enhance therapeutic effects, leading to improved outcomes in cancer treatment.

Development of hybrid polyvinylpyrrolidone/carboxymethyl cellulose/collagen incorporated oregano scaffolds via direct ink write printing for potential wound healing applications.

Additive manufacturing can develop regenerative scaffolds for wound healing. 3D printing offers meticulous porosity, mechanical integrity, cell adhesion and cost-effectiveness. Herein, we prepared ink composed of carboxymethyl cellulose (CMC), polyvinylpyrrolidone (PVP), collagen, and oregano extract for the fabrication of tissue constructs. The blend was optimized to form a homogeneous ink and rheological characterization demonstrated shear thinning behavior. The scaffolds were printed using Direct Ink Write (DIW) at a flow speed of 4 mm3/s and a layer height of 0.18 mm. The fabricated scaffolds demonstrated an ultimate tensile strength (UTS) and toughness of 730 KPa and 2.72 MJ/m3, respectively. Scanning Electron Microscopy (SEM) revealed an average pore size of 300 ± 30 µm. Fourier transform infrared spectroscopy (FTIR) analysis confirmed that all materials were present. The contact angle of the composite scaffold was 68° ± 1°. Moreover, the scaffolds presented 82 % mass loss (degradation) in phosphate buffer saline (PBS) over 14 days. The composite scaffold exhibited inhibition zones of 9 mm and 12 mm against Staphylococcus aureus and Escherichia coli, respectively. The PVP/CMC/collagen/oregano 3D printed scaffolds exhibited excellent biocompatibility with the mesenchymal stem cells and humman dermal fibroblast cells, confirmed by water-soluble tetrazolium - 8 (WST-8) assay (test conducted for 7 days). The enhanced angiogenic potential of said scaffold was assesed by release of vascular endothelial growth factor followed by further validation through in-vivo CAM assay. Thus, confirming suitability for the potential wound healing application.

Enhancing enzymatic catalysis efficiency: Immobilizing laccase on HHSS for synergistic bisphenol A adsorption and biodegradation through optimized external surface utilization.

Laccase, a prominent enzyme biomacromolecule, exhibits promising catalytic efficiency in degrading phenolic compounds like bisphenol A (BPA). The laccase immobilized on conventional materials frequently demonstrates restricted loading and suboptimal catalytic performance. Hence, there is a pressing need to optimized external surface utilization to enhance catalytic performance. Herein, we synthesized amino-functionalized modified silica particles with a hierarchical hollow silica spherical (HHSS) structure for laccase immobilization via crosslinking, resulting in HHSS-LE biocatalysts. Through Box-Behnken design (BBD) and response surface methodology (RSM), we achieved a remarkably high enzyme loading of up to 213.102 mg/g. The synergistic effect of adsorption by HHSS and degradation by laccase facilitated efficient removal of BPA. The HHSS-LE demonstrated superior BPA removal capabilities, with efficiencies exceeding 100 % in the 50-200 mg/L BPA concentration range. Compared to MCM-41 and solid silica spheres (SSS), HHSS showed the highest enzyme loading capacity and catalytic activity, underscoring its superior external surface utilization rate per unit mass. Remarkably, the HHSS-LE biocatalyst exhibited remarkable recyclability even after 11 successive cycles of reuse. By preparing high immobilization rate with efficient external surface utilization, this study lays the foundation for the design of universally applicable and efficient enzyme immobilization catalysts.

Nanoparticles in cancer theragnostic and drug delivery: A comprehensive review.

This comprehensive review provides an in-depth analysis of how nanotechnology has revolutionized cancer theragnostic, which combines diagnostic and therapeutic methods to customize cancer treatment. The study examines the unique attributes, uses, and difficulties linked to different types of nanoparticles, including gold, iron oxide, silica, Quantum dots, Carbon nanotubes, and liposomes, in the context of cancer treatment. In addition, the paper examines the progression of nanotheranostics, emphasizing its uses in precise medication administration, photothermal therapy, and sophisticated diagnostic methods such as MRI, CT, and fluorescence imaging. Moreover, the article highlights the capacity of nanoparticles to improve the effectiveness of drugs, reduce the overall toxicity in the body, and open up new possibilities for treating cancer by releasing drugs in a controlled manner and targeting specific areas. Furthermore, it tackles concerns regarding the compatibility of nanoparticles and their potential harmful effects, emphasizing the significance of continuous study to improve nanotherapeutic methods for use in medical treatments. The review finishes by outlining potential future applications of nanotechnology in predictive oncology and customized medicine.

Potential magnetic drug targeting with magnetite nanoparticles in cancer treatment by enhancer-modifier natural herb and loaded drug.

In the present study, we prepared magnetite nanoparticles (MNPs) loaded with natural Moringa oleifera (M. olf) herb and Epilim (Ep) drug to evaluate the anti-cancerous activity against brain cancer cells. All the samples were prepared via co-precipitation approach modified with different concentrations of M. olf and Ep drug at room temperature. The MNPs loaded with drug and natural herb were studied in terms of crystal structure, morphology, colloidal stability, size distribution, and magnetic properties. Field emission scanning electron microscopy (FESEM) images exhibited the morphologies of samples with spherical shape as well as the particles size of 9 nm for MNPs and up to 23 nm for its composites. The results of vibrating sample magnetometer (VSM) indicated the magnetization saturation (Ms) of 42.510 emu/g for MNPs. This value reduced to 16-35 emu/g upon loading MNPs with different concentrations of M. olf and Ep. Fourier transform infrared spectroscopy (FTIR) indicated the chemical interaction between the Ep, M.olf and MNPs. Brunauer-Emmett-Teller (BET) analysis confirmed the largest surface area for MNPs (422.61 m2/g) which gradually reduced on addition of M. olf and Ep indicating the successful loading. The zeta potential measurements indicated that the MNPs and MNPs loaded with M. olf and Ep are negatively charged and can be dispersed in the suspension. Furthermore, U87 human glioblastoma cell line was used for the in vitro cellular studies to determine the efficacy of synthesized MNPs against cancer cells. The results confirmed the anti-proliferative activity of the MNPs loaded with M. olf and Ep.

A novel technique for leaf disease classification using Legion Kernels with parallel support vector machine (LK-PSVM) and fuzzy C means image segmentation.

Detection of plant disease and classificationare being investigated in many parts of the worldto save precious medical plants from becoming extinct.Major problem in this task, include the lack of advanced and technology driven solution. Manual identification is often time-consuming and prone to inaccuracies. Therefore, there is an urgent need for an automated and efficient method that can accurately identify and classify plant diseases. This article focuses on detecting the disease through classificationthrough a new technique using leaf images for automatic classification. This paper proposes a novel segmentation technique using Fuzzy C means and Particle Swarm Optimization for effective segmentation of leaf images and feature extraction that can help in classification of disease.The approach emphasizes on the integration of techniques such as image processing, segmentation and feature extraction and finally the classification, which offers a comprehensive solution for the disease detection. The work leverages on the advantages of Legion Kernels and Parallal support vector Machine (LK-PSVM) clubbed with fuzzy C means Image segmentation to offer a framework that can handle diverse leaf images and which can effectively differentiate the type of the disease.The proposed method LK-PSVM combined with Fuzzy C means presents a novel approach that is significantly deviated from the conventional methods of leaf disease classification.The proposed wok brings an integrated framework which can synergistically combine the Legion Kernels with the PSVM technique coupled with Fuzzy C Means Image segmentation which can handle the issue of overlapped data sets and support vector machines are used to handle the situation where the number of dimensions are more than the number of samples, which is more probable in the classification problem under consideration.By integrating these components, the proposed method achieves more accuracy and robustness when compared to the existing methods in the literature. The segmentation is carried out using PSO after pre-processing of images. The Gaussian functions are used to eliminate the background subtraction. Different features of the images are then computed. A total of 55,400 images were used for the experiment consisting of various plants' leaves spreading across 38 labels. A classifier is then proposed using Machine learning methods for the detection of disease in apple fruit leaves. The experiments prove that the proposed method have high degree of classification accuracy when compared to existing methods. The proposed method not only cater to the need in terms of accuracy but also making it scalable for different types of leaves.

Using PyCaret to model Chlorella vulgaris's growth response to salinity and oil contamination for crude oil bioremediation.

Crude oil spills significantly impact aquatic ecosystems, necessitating innovative remediation strategies. Microalgae-based bioremediation, particularly with Chlorella vulgaris, offers a promising solution. This study introduces a novel framework that evaluates the combined effects of selected environmental stressors on microalgal adaptability, advancing beyond traditional isolated factor analyses. By integrating a factorial experimental design with a machine learning approach using PyCaret AutoML and SHAP values, we provide a detailed examination of how crude oil concentration, salinity, and exposure duration affect C. vulgaris growth. The Extra Trees Regressor model emerged as highly accurate in predicting biomass concentration, a crucial adaptability indicator, achieving an MAE of 0.0202, RMSE of 0.029, and an R² of 0.8875. SHAP analysis highlighted salinity and crude oil as significant growth influencers, with exposure duration playing a minor role. Notably, C. vulgaris exhibited more sensitivity to salinity than to crude oil, indicating potential high-salinity challenges but also a strong tolerance to oil pollutants. These findings enhance our understanding of microalgal responses in polluted environments and suggest improved bioremediation approaches for saline waters affected by oil spills, leveraging the synergy of environmental factors and machine learning insights.

Feasibility of a new 'balanced binocular viewing' treatment for unilateral amblyopia in children aged 3-8 years (BALANCE): results of a phase 2a randomised controlled feasibility trial.

OBJECTIVES: This study aimed to evaluate the safety of dichoptic balanced binocular viewing (BBV) for amblyopia in children, plus feasibility, adherence, acceptability, trial methodology and clinical measures of visual function. DESIGN: We carried out an observer-masked parallel-group phase 2a feasibility randomised controlled trial. SETTING: Two study sites, a secondary/tertiary and a community site. PARTICIPANTS: We enrolled 32 children aged 3-8 years with unilateral amblyopia who had completed optical adaptation where indicated. 20 children attended the 16-week exit visit (retention 63%). INTERVENTIONS: Children were randomised to BBV (movies customised to interocular acuity difference at baseline) for 1 hour a day (active intervention) or standard management as per parental choice (part-time occlusion or atropine blurring, control). All interventions were used at home, daily for 16 weeks. PRIMARY OUTCOME MEASURE: 'VacMan suppression test' of interocular balance at 16 weeks from randomisation. SECONDARY OUTCOME MEASURES: feasibility outcomes (recruitment and retention ratios, adherence with the allocated intervention); safety outcomes at other time points (changes in prevalence of diplopia, manifest strabismus, suppression/interocular balance on a range of tests); efficacy outcomes (clinical measures of visual function, such as best-corrected visual acuity, BCVA). Outcome measures were identical to those planned in the protocol. RESULTS: Primary outcome: At baseline, values for the interocular balance point were higher (indicating greater suppression of the amblyopic eye) in the occlusion group than in the BBV group. These values shifted downwards on average for the occlusion group, significantly decreasing from baseline to week 16 (t8=4.49, p=0.002). Balance values did not change between baseline and week 16 for the BBV group (t9=-0.82, p=0.435). At 16 weeks, there was no statistical difference in interocular balance/suppression change over time between the two arms. The difference at follow-up between the arms, adjusted for baseline, was -0.02 (95% CI -0.28 to 0.23, p=0.87). FEASIBILITY: We prescreened 144 records of potentially eligible children. Between 28 October 2019 and 31 July 2021, including an interruption due to the COVID-19 pandemic, 32 children were screened and randomised (recruitment rate 22%), 16 to BBV and 16 to standard treatment. 20 children attended the 16-week exit visit (retention 63%). Mean adherence with BBV as proportion of viewing time prescribed was 56.1% (SD36) at 8 and 57.9% (SD 30.2) at 16 weeks. Mean adherence with prescribed occlusion time was 90.1% (SD 19.7) at 8 and 59.2% (SD 24.8) at 16 weeks. SECONDARY SAFETY/EFFICACY OUTCOMES: One child in the BBV arm reported transient double vision, which resolved; two reported headaches, which led to withdrawal. BCVA improved from mean 0.47 (SD0.18) logMAR at randomisation to 0.26 (0.14) with standard treatment, and from 0.55 (0.28) to 0.32 (0.26) with BBV. Outcomes at 16 weeks did not differ between treatments. PARTICIPANT EXPERIENCE: Families were generally positive about BBV, but families found both patching and BBV difficult to integrate into family routines. CONCLUSIONS: Recruitment rates indicate that a future phase 3 trial will require multiple sites or a longer enrolment period. Retention and adherence rates were lower than anticipated, which will influence future study designs. Dichoptic treatment may be equal to occlusion treatment in safety and efficacy; headaches may lead to discontinuation. Integration into family routines may constitute a barrier to implementation. TRIAL REGISTRATION NUMBER: NCT03754153.

Sex differences in long-term outcomes following transvenous lead extraction.

INTRODUCTION: Transvenous lead extraction (TLE) is generally considered a safe procedure, albeit not without risks. While gender-based disparities have been noted in short-term outcomes following TLE, a notable gap exists in understanding the long-term consequences of this procedure. The objective of this analysis was to investigate sex differences in both acute and long-term outcomes among patients who underwent TLE at a tertiary referral center. METHODS: In this retrospective cohort study, consecutive patients who underwent TLE between January 2014 and January 2016 were enrolled. The primary outcome comprised a composite of all-cause mortality and need for repeated TLE procedures. Secondary outcomes included fluoroscopy time, lead extraction techniques, success rates, and major and minor complications. Results were compared between female and male cohorts. RESULTS: The study population comprised 191 patients (median age, 70 years), 29 (15.2%) being women and 162 men (84.8%). Study groups had similar baseline characteristics. Complete procedural success was achieved in 189 out of 191 patients (99.0%), with no significant difference observed between the two groups (p = .17). No major complications were reported in the total cohort. However, there was a significantly higher incidence of minor complications in women compared to men (17.2% vs. 2.5%, p < .01). Following a median follow-up of 6.5 years, the incidence of the primary composite outcome occurred similarly between the study groups (log-rank p = .68). CONCLUSION: Women who underwent TLE exhibited a significantly higher incidence of minor acute intra- and peri-procedural complications than men. However, no differences in long-term outcomes between genders were observed.