Miracle-dz/UniFAR-FTUs huggingface dataset:
Graphene-Based Sensors for the Detection of Microorganisms in Food: A Review

There is a constant need to maintain the quality of consumed food. In retrospect to the recent pandemic and other food-related problems, scientists have focused on the numbers of microorganisms that are present in different food items. As a result of changes in certain environmental factors such as temperature and humidity, there is a constant risk for the growth of harmful microorganisms, such as bacteria and fungi, in consumed food. This questions the edibility of the food items, and constant monitoring to avoid food poisoning-related diseases is required. Among the different nanomaterials used to develop sensors to detect microorganisms, graphene has been one of the primary materials due to its exceptional electromechanical properties. Graphene sensors are able to detect microorganisms in both a composite and non-composite manner, due to their excellent electrochemical characteristics such as their high aspect ratios, excellent charge transfer capacity and high electron mobility. The paper depicts the fabrication of some of these graphene-based sensors, and their utilization to detect bacteria, fungi and other microorganisms that are present in very small amounts in different food items. In addition to the classified manner of the graphene-based sensors, this paper also depicts some of the challenges that exist in current scenarios, and their possible remedies.
Biosensors Based on Inorganic Composite Fluorescent Hydrogels

Fluorescent hydrogels are promising candidate materials for portable biosensors to be used in point-of-care diagnosis because (1) they have a greater capacity for binding organic molecules than immunochromatographic test systems, determined by the immobilization of affinity labels within the three-dimensional hydrogel structure; (2) fluorescent detection is more sensitive than the colorimetric detection of gold nanoparticles or stained latex microparticles; (3) the properties of the gel matrix can be finely tuned for better compatibility and detection of different analytes; and (4) hydrogel biosensors can be made to be reusable and suitable for studying dynamic processes in real time. Water-soluble fluorescent nanocrystals are widely used for in vitro and in vivo biological imaging due to their unique optical properties, and hydrogels based on these allow the preservation of these properties in bulk composite macrostructures. Here we review the techniques for obtaining analyte-sensitive fluorescent hydrogels based on nanocrystals, the main methods used for detecting the fluorescent signal changes, and the approaches to the formation of inorganic fluorescent hydrogels via sol–gel phase transition using surface ligands of the nanocrystals.
Composition of Sugars, Organic Acids, Phenolic Compounds, and Volatile Organic Compounds in Lingonberries (Vaccinium vitis-idaea L.) at Five Ripening Stages

Wild lingonberries are a traditional source of food in the Nordic countries and an important contributor to economic activity of non-wood forest products in the region. Lingonberries are a rich source of bioactive compounds and can be a valuable contributor to a healthy diet. However, there are few studies available on how the bioactive compounds in lingonberries develop as they ripen. In this investigation, we examined the content of 27 phenolic compounds, three sugars, four organic acids, and 71 volatile organic compounds at five ripening stages. The study showed that, while the highest content of phenolic compounds was found early in the development, the organoleptic quality of the fruits improved as they ripened. From the first to the last stage of development, anthocyanins went from being nearly absent to 100 mg/100 g fw, and there was an increased content of sugars from 2.7 to 7.2 g/100 g fw, whereas the content of organic acids decreased from 4.9 to 2.7 g/100 g fw, and there were several changes in the profile of volatiles. The contents of flavonols, cinnamic acid derivatives, flavan-3-ols, and the total concentration of phenolic compounds were significantly lower in the fully ripe berries compared to berries in the early green stage. In addition to the changes occurring due to ripening, there was observed variation in the profile of both phenolic compounds and volatiles, depending on the growth location of the berries. The present data are useful for the assessment of harvest time to obtain the desired quality of lingonberries.
Fast Incremental SVM Learning Algorithm Based on Active Set Iterations

A new support vector machine (SVM) was introduced. What is unusual for the SVM is that the dual problem for the constrained optimization of the SVM is a convex quadratic problem with simple bound constraints. The active set iteration method for this quadratic problem was applied as a learning algorithm for the SVM, and the selection of the initial active set was discussed. For incremental learning and large-scale learning problems, a fast incremental learning algorithm for the SVM was proposed. Some experiments show the efficiency of the proposed algorithm.
Systematic Review on S-ICD Lead Extraction

Background and purpose: Subcutaneous implantable cardioverter defibrillators (S-ICDs) have emerged in recent years as a valid alternative to traditional transvenous ICDs (TV-ICDs). Therefore, the number of S-ICD implantations is rising, leading to a consequent increase in S-ICD-related complications sometimes requiring complete device removal. Thus, the aim of this systematic review is to gather all the available literature on S-ICD lead extraction (SLE), with particular reference to the type of indication, techniques, complications and success rate. Methods: Studies were identified by searching electronic databases (Medline via PubMed, Scopus and Web of Science) from inception to 21 November 2022. The search strategy adopted was developed using the following key words: subcutaneous, S-ICD, defibrillator, ICD, extraction, explantation. Studies were included if they met both of the following criteria: (1) inclusion of patients with S-ICD; (2) inclusion of patients who underwent SLE. Results: Our literature search identified 238 references. Based on the abstract evaluation, 38 of these citations were considered potentially eligible for inclusion, and their full texts were analyzed. We excluded 8 of these studies because no SLE was performed. Eventually, 30 studies were included, with 207 patients who underwent SLE. Overall, the majority of SLEs were performed for non-infective causes (59.90%). Infection of the device (affecting either the lead or the pocket) was the cause of SLE in 38.65% of cases. Indication data were not available in 3/207 cases. The mean dwelling time was 14 months. SLEs were performed using manual traction or with the aid of a tool designed for transvenous lead extraction (TLE), including either a rotational or non-powered mechanical dilator sheath. Conclusions: SLE is performed mainly for non-infective causes. Techniques vary greatly across different studies. Dedicated tools for SLE might be developed in the future and standard approaches should be defined. In the meantime, authors are encouraged to share their experience and data to further refine the existing variegated approaches.
Proton Plasma Asymmetries Between Venus' Quasi‐Perpendicular and Quasi‐Parallel Magnetosheaths

Proton plasma asymmetries between the hemispheres of Venus' dayside magnetosheath lying downstream of the quasi‐perpendicular (q⊥) and quasi‐parallel (q‖) sides of the bow shock are characterized using measurements taken by a mass‐energy spectrometer. This characterization enables comparison to analogous Earth studies, thereby providing insight as to which plasma phenomena, such as turbulent particle heating, contribute in creating the observed plasma asymmetries in planetary magnetosheaths. A database of dayside bow‐shock crossings along with magnetosheath proton densities, bulk speeds, temperatures, and magnetic‐field strengths is manually constructed by selecting measurements taken during stable solar‐wind conditions. Ratios of these magnetosheath proton parameters are calculated as functions of distance from the central meridian and the upstream Alfvén Mach number to quantify the q⊥/‖ asymmetries. The density and bulk‐speed exhibit q‖‐favored asymmetries, mirroring those observed at Earth, whereas the magnetic‐field strength reveals no significant asymmetry despite expectations based on simulations. The temperatures perpendicular (T⊥) and parallel (T‖) to the background magnetic field have q⊥‐favored asymmetries while the temperature anisotropy T⊥/T‖ exhibits a q‖‐favored asymmetry. This trend is opposite to that seen at Earth, suggesting that the different spatial scales of the two planets' magnetosheaths may affect the impact of turbulent processes on global plasma properties.
Histochemical and surface microstructural analyses of floral cuticles provide evidence for differential behaviors in scent volatiles emission in two tuberoses (Agave amica (Medik.) Theide and Govaerts) cultivars from Asparagaceae

: Two popular cultivars of tuberose ( Agave amica (Medik.) Theide and Govaerts syn. Polianthes tuberosa L. ) from the family Asparagaceae, widely cultivated for floricultural purposes are ‘Calcutta Single’ (CS) and ‘Calcutta Double’ (CD). It was evidenced that CS flowers emit intense scent volatiles as compared to CD flowers, while CD flowers retained higher contents of internal pool of scent volatiles than CS flowers. Such contrasting observations between the flowers of two cultivars suggest the role of possible barriers such as cuticles that prevent the emission of scent volatiles. The cuticular structure of both cultivars was studied using different histochemical approaches, including light and epi-fluorescence microscopies. Scanning electron microscopy (SEM) was used to understand the cuticular deposition in the cultivars. Our observations confirmed relatively higher cuticular thickness in CD flowers than in CS. SEM results showed the accumulation of wax crystalloids in CS flower and the formation of cuticular nanoridges in CD flowers over the surfaces of the tepals. In addition, accumulation of lipid droplets was also noticed on the tepal peels of the cultivars showing a denser deposition in CD. Our observations suggest that the presence of wax crystalloids in CS flowers enhances the emission of volatiles, while in CD flowers, the presence of thick cuticular nanoridges possibly deters the scent emission and accumulated as an internal pool in higher amounts. The stomatal behavior also indicates a proportional relationship between cuticular deposition and scent emission; low cuticular deposition corresponds to higher emission of floral volatiles emission and vice versa as observed in CS and CD flowers, respectively.
Giza 183 Egyptian rice variety: a step to confront climate change challenges

Climate change is one of the biggest threats to plant species around the world. As one of the most important crops worldwide, rice is an awfully climate-sensitive agro-ecosystem. Therefore, Giza 183 will be released in 2023 as a high-yielding variety that has been adapted to mitigate climate change. This new variety is the product of cross-breeding between Giza 178 and SKC 23893 in 2010. The first generation, "F1,” of this cross was evaluated in 2011 and planted as the F2 generation in 2012. Sequentially, the next generations from F3 to F6 were evaluated in the pedigree trails from 2013 to 2016, under cross number “GZ 10848. " Five promising sister lines of GZ 10848 were selected and evaluated in the preliminary yield trail (GZ 10848-1-2-2-1, GZ 10848-1-2-2-2, GZ 10848-1-2-4-5, GZ 10848-1-2-5-3, and GZ 10848-1-2-5-6). The results revealed that the promising line GZ 10848-1-2-2-1 “Giza 183” surpassed all selected lines. Accordingly, Giza 183 was evaluated from 2017 to 2022 in multi -location yield trails at Sakha, Gemmiza, and Zarzoura as normal conditions and El-Sirw as saline conditions, as well as in regional, final, and verification yield trails. The evaluation resulted in a significant superiority of the yield of Giza 183 over Giza 178, with shorter growth duration and blast resistance. The new variety grain yield recorded 10.88, 10.47, 11.30, 10.60, and 10.70 t/ha during the 2017 to 2022 seasons under normal conditions, respectively, with a total duration of 122 days. while the grain yield for Giza 178 was recoded at 10.50, 10.54, 9.90, 10.00, 9.80, and 10.30 t/ha during the same seasons and conditions, with a total duration of 135 days. Furthermore, Giza 183 exhibited a higher yield than Giza 178 as a salt tolerance check variety at a rate of 0.800 – 0.160 t/ha under saline conditions at El-Sirw Agricultural Research Station in different years of evaluation. Giza 183 showed a high level of blast resistance in blast nursery and trap varieties in the field and artificial inoculation under greenhouse conditions. Finally, the new rice variety Giza 183 is resistant to stem borer and has high grain quality traits
Pro-Apoptotic Activity and Cell Cycle Arrest of Caulerpa sertularioides against SKLU-1 Cancer Cell in 2D and 3D Cultures

Cancer is a disease with the highest mortality and morbidity rate worldwide. First-line drugs induce several side effects that drastically reduce the quality of life of people with this disease. Finding molecules to prevent it or generate less aggressiveness or no side effects is significant to counteract this problem. Therefore, this work searched for bioactive compounds of marine macroalgae as an alternative treatment. An 80% ethanol extract of dried Caulerpa sertularioides (CSE) was analyzed by HPLS-MS to identify the chemical components. CSE was utilized through a comparative 2D versus 3D culture model. Cisplatin (Cis) was used as a standard drug. The effects on cell viability, apoptosis, cell cycle, and tumor invasion were evaluated. The IC50 of CSE for the 2D model was 80.28 μg/mL versus 530 μg/mL for the 3D model after 24 h of treatment exposure. These results confirmed that the 3D model is more resistant to treatments and complex than the 2D model. CSE generated a loss of mitochondrial membrane potential, induced apoptosis by extrinsic and intrinsic pathways, upregulated caspases-3 and -7, and significantly decreased tumor invasion of a 3D SKLU-1 lung adenocarcinoma cell line. CSE generates biochemical and morphological changes in the plasma membrane and causes cell cycle arrest at the S and G2/M phases. These findings conclude that C. sertularioides is a potential candidate for alternative treatment against lung cancer. This work reinforced the use of complex models for drug screening and suggested using CSE’s primary component, caulerpin, to determine its effect and mechanism of action on SKLU-1 in the future. A multi-approach with molecular and histological analysis and combination with first-line drugs must be included.
An LC–MS/MS Analytical Method for Quantifying Tepotinib in Human Liver Microsomes: Application to In Vitro and In Silico Metabolic Stability Estimation

Tepotinib (MSC2156119) is a potent mesenchymal–epithelial transition (MET) factor inhibitor, a receptor tyrosine kinase that plays a crucial role in promoting cancer cell malignant progression. Adverse effects of tepotinib (TEP), such as peripheral edema, interstitial lung disease, nausea and diarrhea, occur due to drug accumulation and lead to termination of therapy. Therefore, the in silico and experimental metabolic susceptibility of TEP was investigated. In the current work, an LC-MS/MS analytical method was developed for TEP estimation with metabolic stability assessment. TEP and lapatinib (LTP) used as internal standards (ISs) were separated on a reversed-phase C18 column using the isocratic mobile phase. Protein precipitation steps were used to extract TEP from the human liver microsome (HLM) matrix. An electrospray ionization multi-reaction monitoring (MRM) acquisition was conducted at m/z 493→112 for TEP, at m/z 581→350, and 581→365 for the IS. Calibration was in the range of 5 to 500 ng/mL (R2 = 0.999). The limit of detection (LOD) was 0.4759 ng/mL, whereas the limit of quantification (LOQ) was 1.4421 ng/mL. The reproducibility of the developed analytical method (inter- and intra-day precision and accuracy) was within 4.39%. The metabolic stability of TEP in HLM was successfully assessed using the LC-MS/MS method. The metabolic stability assessment of TEP showed intermediate Clint (35.79 mL/min/kg) and a moderate in vitro t1/2 (22.65 min), proposing the good bioavailability and moderate extraction ratio of TEP. The in silico results revealed that the N-methyl piperidine group is the main reason of TEP metabolic lability. The in silico Star Drop software program could be used in an effective protocol to confirm and propose the practical in vitro metabolic experiments to spare resources and time, especially during the first stages for designing new drugs. The established analytical method is considered the first LC-MS/MS method for TEP estimation in the HLM matrix with its application to metabolic stability assessment.
Numerical Study of Velocity and Mixture Fraction Fields in a Turbulent Non-Reacting Propane Jet Flow Issuing into Parallel Co-Flowing Air in Isothermal Condition through OpenFOAM

This research employs computational methods to analyze the velocity and mixture fraction distributions of a non-reacting Propane jet flow that is discharged into parallel co-flowing air under iso-thermal conditions. This study includes a comparison between the numerical results and experimental results obtained from the Sandia Laboratory (USA). The objective is to improve the understanding of flow structure and mixing mechanisms in situations where there is no involvement of chemical reactions or heat transfer. In this experiment, the Realizable k-ε eddy viscosity turbulence model with two equations was utilized to simulate turbulent flow on a nearly 2D plane (specifically, a 5-degree partition of the experimental cylinder domain). This was achieved using OpenFOAM open-source software and swak4Foam utility, with the reactingFoam solver being manipulated carefully. The selection of this turbulence model was based on its superior predictive capability for the spreading rate of both planar and round jets, as compared to other variants of the k-ε models. Numerical axial and radial profiles of different parameters were obtained for a mesh that is independent of the grid (mesh B). These profiles were then compared with experimental data to assess the accuracy of the numerical model. The parameters that are being referred to are mean velocities, turbulence kinetic energy, mean mixture fraction, mixture fraction half radius (Lf), and the mass flux diagram. The validity of the assumption that w߰ = v߰ for the determination of turbulence kinetic energy, k, seems to hold true in situations where experimental data is deficient in w߰. The simulations have successfully obtained the mean mixture fraction and its half radius, Lf, which is a measure of the jet’s width. These values were determined from radial profiles taken at specific locations along the X-axis, including x/D = 0, 4, 15, 30, and 50. The accuracy of the mean vertical velocity fields in the X-direction (Umean) is noticeable, despite being less well-captured. The resolution of mean vertical velocity fields in the Y-direction (Vmean) is comparatively lower. The accuracy of turbulence kinetic energy (k) is moderate when it is within the range of Umean and Vmean. The absence of empirical data for absolute pressure (p) is compensated by the provision of numerical pressure contours.
Role of Bovine Serum Albumin Addition in Micellization and Gel Formation of Poloxamer 407

The combination of the thermoresponsive polymer and protein has demonstrated great promise in its applications in drug delivery and tissue engineering fields. This study described the impact of bovine serum albumin (BSA) on the micellization and sol–gel transition behaviors of poloxamer 407 (PX). The micellization of aqueous PX solutions with and without BSA was examined using isothermal titration calorimetry. In the calorimetric titration curves, the pre-micellar region, the transition concentration region, and the post-micellar region were observed. The presence of BSA had no noticeable impact on critical micellization concentration, but the inclusion of BSA caused the pre-micellar region to expand. In addition to studying the self-organization of PX at a particular temperature, the temperature-induced micellization and gelation of PX were also explored using differential scanning calorimetry and rheology. The incorporation of BSA had no discernible effect on critical micellization temperature (CMT), but it did affect gelation temperature (Tgel) and gel integrity of PX-based systems. The response surface approach illustrated the linear relation between the compositions and the CMT. The major factor affecting the CMT of the mixtures was the concentration of PX. The alteration of the Tgel and the gel integrity were discovered to be a consequence of the intricate interaction between PX and BSA. BSA mitigated the inter-micellar entanglements. Hence, the addition of BSA demonstrated a modulating influence on Tgel and a softening effect on gel integrity. Understanding the influence of serum albumin on the self-assembly and gelation of PX will enable the creation of thermoresponsive drug delivery and tissue engineering systems with controlled gelation temperatures and gel strength.
Deep Learning for Human Activity Recognition on 3D Human Skeleton: Survey and Comparative Study

Human activity recognition (HAR) is an important research problem in computer vision. This problem is widely applied to building applications in human–machine interactions, monitoring, etc. Especially, HAR based on the human skeleton creates intuitive applications. Therefore, determining the current results of these studies is very important in selecting solutions and developing commercial products. In this paper, we perform a full survey on using deep learning to recognize human activity based on three-dimensional (3D) human skeleton data as input. Our research is based on four types of deep learning networks for activity recognition based on extracted feature vectors: Recurrent Neural Network (RNN) using extracted activity sequence features; Convolutional Neural Network (CNN) uses feature vectors extracted based on the projection of the skeleton into the image space; Graph Convolution Network (GCN) uses features extracted from the skeleton graph and the temporal–spatial function of the skeleton; Hybrid Deep Neural Network (Hybrid–DNN) uses many other types of features in combination. Our survey research is fully implemented from models, databases, metrics, and results from 2019 to March 2023, and they are presented in ascending order of time. In particular, we also carried out a comparative study on HAR based on a 3D human skeleton on the KLHA3D 102 and KLYOGA3D datasets. At the same time, we performed analysis and discussed the obtained results when applying CNN-based, GCN-based, and Hybrid–DNN-based deep learning networks.