One of the significant aromatic plants applied in food and pharma is cumin. Despite its massive trading in Egypt, there are no comprehensive reports on cumin landraces profile screening. This study ...aimed to investigate the variation in seeds' physical and biochemical profiles and genetic diversity as well as assess the efficiency of seeds' germination under salinity stress. Consequently, during the 2020/2021 growing season, four common cumin seed landraces were gathered from various agro-climatic regions: El Gharbia, El Menia, Assiut, and Qena. Results showed a significant variation in physical profile among the four seeds of landraces. In addition, Assiut had the highest percentage of essential oil at 8.04%, whilst Qena had the largest amount of cumin aldehyde, the primary essential oil component, at 25.19%. Lauric acid was found to be the predominant fatty acid (54.78 to 62.73%). According to ISSR amplification, El Menia presented a negative unique band, whereas other landraces offered a positive band. Additionally, the cumin genotypes were separated into two clusters by the dendrogram, with El Gharbia being located in an entirely separate cluster. There were two sub-clusters within the other cluster: El Menia in one and Assiut and Qena in the other. Moreover, the germination sensitivity to the diverse salinity concentrations (control, 4, 8, 12, and 16 dS/m) findings showed that landraces exhibited varying responses to increased salinity when El Gharbia and El Menia showed a moderate response at four dS/m. Whilst, Qena landraces showed supreme values among other landraces under 12 and 16 dS/m. The majority of the examined features had strong positive associations over a range of salinity levels, according to phenotypic correlation coefficient analysis. To accomplish the aims of sustainable agriculture in Egypt, it would be imperative that the potential breeding program for cumin landraces consider this screening study.
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In metastatic breast cancer (MBC), the conventional doxorubicin (DOX) has various problems due to lack of selectivity with subsequent therapeutic failure and adverse effects. DOX- ...induced cardiotoxicity is a major problem that necessitates the presence of new forms to decrease the risk of associated morbidity.
Nanoparticles (NPs) are considered an important approach to selectively increase drug accumulation inside tumor cells and thus decreasing the associated side effects. Tumor cells develop resistance to chemotherapeutic agents through multiple mechanisms, one of which is over expression of efflux transporters. Various NPs have been investigated to overcome efflux mediated resistance.
To date, only liposomal doxorubicin (LD) and pegylated liposomal doxorubicin (PLD) have entered phase II and III clinical trials and FDA- approved for clinical use in MBC. This review addresses the effects of LD and PLD on the hematological and palmar-plantar erythrodysesthesia (PPE) in anthracycline naïve and pretreated MBC patients. For evidence, studies to be included in this review were identified through PubMed, Cochrane and Google scholar databases. The results derived from: four phase III clinical trials that compared LD with the conventional DOX in naïve MBC patients, and ten non-comparative clinical trials investigated LD and PLD as monotherapy or combination in pretreated MBC. This work confirmed the cardiac tolerability profile of LD and PLD versus DOX, while hematological and skin toxicities were more common.
Other DOX-NPs in preclinical trials were discussed in a chronological order. Finally, the modern preclinical development framework for DOX includes exosomal DOX (exo-DOX). Exosomal NPs are non-toxic, non-immunogenic, and can be engineered to have high cargo loading capacity and targeting specificity. These NPs have not been investigated clinically. Our study shows that the full clinical potentiality of DOX-NPs remains to be addressed to move the field forward.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Diabetic retinopathy (DR) is a serious retinal disease and is considered as a leading cause of blindness in the world. Ophthalmologists use optical coherence tomography (OCT) and fundus photography ...for the purpose of assessing the retinal thickness, and structure, in addition to detecting edema, hemorrhage, and scars. Deep learning models are mainly used to analyze OCT or fundus images, extract unique features for each stage of DR and therefore classify images and stage the disease. Throughout this paper, a deep Convolutional Neural Network (CNN) with 18 convolutional layers and 3 fully connected layers is proposed to analyze fundus images and automatically distinguish between controls (i.e. no DR), moderate DR (i.e. a combination of mild and moderate Non Proliferative DR (NPDR)) and severe DR (i.e. a group of severe NPDR, and Proliferative DR (PDR)) with a validation accuracy of 88%-89%, a sensitivity of 87%-89%, a specificity of 94%-95%, and a Quadratic Weighted Kappa Score of 0.91-0.92 when both 5-fold, and 10-fold cross validation methods were used respectively. A prior pre-processing stage was deployed where image resizing and a class-specific data augmentation were used. The proposed approach is considerably accurate in objectively diagnosing and grading diabetic retinopathy, which obviates the need for a retina specialist and expands access to retinal care. This technology enables both early diagnosis and objective tracking of disease progression which may help optimize medical therapy to minimize vision loss.
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A series of new complexes derived from Pd(II), Cu(II) and Fe(III) ions reacted with thiazole derivative (HL, CPTP) was prepared. Structures of all new compounds were characterized and confirmed using ...analytical and spectroscopic (IR, UV–Vis and
13
C&
1
H NMR) techniques. All complexes have non-electrolytic nature based on molar conductance measurements. TGA was executed to confirm the presence of water molecules inside or outside the coordination sphere as well as the mono-nuclear feature of isolated complexes. Accordingly, thermo kinetic parameters were calculated for all decomposition steps. The obtained analytical data regarding complexation in solution, molar ratio and continuous variation methods suggest 1 M:1 L molar ratio. The oriented structures using advanced program assert on best distribution for coordinating sites (NH& NH
2
). Moreover, electrostatic potential map as well as iso-surface with array plot of ligand reflects high nucleophilic feature with reduced outer contour on two coordinating sites. In vitro antimicrobial, anticancer and antioxidant activities of ligand and its complexes were checked. All complexes exhibited superiority on free ligand in successful treatment, specifically CPTPPd complex. Drug-likeness as well as MOE-docking simulation outcomes indicates promising inhibitory feature of CPTPPd and CPTPCu complexes, in agreement with in vitro results.
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DOBA, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, IZUM, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, SIK, UILJ, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Autism spectrum disorder (ASD) is a combination of developmental anomalies that causes social and behavioral impairments, affecting around 2% of US children. Common symptoms include difficulties in ...communications, interactions, and behavioral disabilities. The onset of symptoms can start in early childhood, yet repeated visits to a pediatric specialist are needed before reaching a diagnosis. Still, this diagnosis is usually subjective, and scores can vary from one specialist to another. Previous literature suggests differences in brain development, environmental, and/or genetic factors play a role in developing autism, yet scientists still do not know exactly the pathology of this disorder. Currently, the gold standard diagnosis of ASD is a set of diagnostic evaluations, such as the Autism Diagnostic Observation Schedule (ADOS) or Autism Diagnostic Interview-Revised (ADI-R) report. These gold standard diagnostic instruments are an intensive, lengthy, and subjective process that involves a set of behavioral and communications tests and clinical history information conducted by a team of qualified clinicians. Emerging advancements in neuroimaging and machine learning techniques can provide a fast and objective alternative to conventional repetitive observational assessments. This paper provides a thorough study of implementing feature engineering tools to find discriminant insights from brain imaging of white matter connectivity and using a machine learning framework for an accurate classification of autistic individuals. This work highlights important findings of impacted brain areas that contribute to an autism diagnosis and presents promising accuracy results. We verified our proposed framework on a large publicly available DTI dataset of 225 subjects from the Autism Brain Imaging Data Exchange-II (ABIDE-II) initiative, achieving a high global balanced accuracy over the 5 sites of up to 99% with 5-fold cross validation. The data used was slightly unbalanced, including 125 autistic subjects and 100 typically developed (TD) ones. The achieved balanced accuracy of the proposed technique is the highest in the literature, which elucidates the importance of feature engineering steps involved in extracting useful knowledge and the promising potentials of adopting neuroimaging for the diagnosis of autism.
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Diabetic retinopathy (DR) is a devastating condition caused by progressive changes in the retinal microvasculature. It is a leading cause of retinal blindness in people with diabetes. Long periods of ...uncontrolled blood sugar levels result in endothelial damage, leading to macular edema, altered retinal permeability, retinal ischemia, and neovascularization. In order to facilitate rapid screening and diagnosing, as well as grading of DR, different retinal modalities are utilized. Typically, a computer-aided diagnostic system (CAD) uses retinal images to aid the ophthalmologists in the diagnosis process. These CAD systems use a combination of machine learning (ML) models (e.g., deep learning (DL) approaches) to speed up the diagnosis and grading of DR. In this way, this survey provides a comprehensive overview of different imaging modalities used with ML/DL approaches in the DR diagnosis process. The four imaging modalities that we focused on are fluorescein angiography, fundus photographs, optical coherence tomography (OCT), and OCT angiography (OCTA). In addition, we discuss limitations of the literature that utilizes such modalities for DR diagnosis. In addition, we introduce research gaps and provide suggested solutions for the researchers to resolve. Lastly, we provide a thorough discussion about the challenges and future directions of the current state-of-the-art DL/ML approaches. We also elaborate on how integrating different imaging modalities with the clinical information and demographic data will lead to promising results for the scientists when diagnosing and grading DR. As a result of this article's comparative analysis and discussion, it remains necessary to use DL methods over existing ML models to detect DR in multiple modalities.
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Zinc linked amino acid complex, Zn(l‐proline)2, is considered as a green catalyst for the synthesis of novel series of pyrimidine derivatives 5a–q. The pyrimidines 5a–q were prepared via two ...pathways: the first is a one‐pot reaction of guanidines 3a–c with aromatic aldehyde 1 and acetophenones 2; and the second one is the reaction of guanidines 3a–c with different chalcones 4a–j in aqueous medium. The simplicity of the operation, the short reaction time, and the high efficiency (97%) are the main advantages of this protocol. Furthermore, the green aspects of this synthetic protocol were further investigated by examining the reusability of Zn(l‐proline)2 complex throughout five consecutive cycles without a significant loss of catalytic activity. This new procedure has presented remarkable advantages in terms of safety, simplicity, stability, mild conditions, a short reaction time, excellent yields, and high purities without using any organic solvents.
Zinc linked amino acid complex, Zn(l‐proline)2, is considered a green protocol catalyst for synthesis of novel series of pyrimidine derivatives 5a–q. The pyrimidines 5a–q were prepared via two pathways. The first is one‐pot reaction of guanidines 3a–c with aromatic aldehyde 1 and acetophenones 2, and the second is the reaction of guanidines 3a–c with different chalcones 4a–j in aqueous medium. The advantages result of this catalyst safety, simplicity, stability
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
The advent of the nanotechnology era offers a unique opportunity for sustainable agriculture, and the contribution of nanoparticles (NPs) to ameliorate abiotic stresses became the new area of ...interest for researchers due to their special physiochemical characteristics in the biological system. Salinity is a key devastating abiotic factor that hinders the development and yield of rapeseed. On the flip side, the impact of nanoparticles on plant hormones upon salt stress during seed imbibition and germination has been poorly understood. Hence, we aimed to study the influence of nanopriming on plant hormones and germination processes using selenium and zinc oxide nanoparticles (SeNPs and ZnONPs) during seed imbibition and the early seedling stage upon salinity stress. Nanopriming showed a positive effect on final germination percentage, germination rate, seed microstructure, and antioxidant enzyme activity of two rapeseed cultivars under salt stress. Moreover, nano-treatment decreased the expression of abscisic acid related genes BnCYP707A1, 3, and 4 during the priming time and after sowing, where the levels of BnCYP707A1, and 3 genes showed a slightly significant difference between the nanopriming and hydropriming, which gave an evidence that the nanopriming influenced the ABA levels then elevated the seed germination with SeNPs and ZnONPs. Likewise, nanoparticles significantly elevated the expression levels of BnGA20ox, BnGA3ox and BnCPS genes during the germination stage, especially at 24 h after being sown in salt stress. That confirms the positive role of SeNPs and ZnONPs in regulating gibberellic acid level, which increases the germination in primed seeds as compared to unprimed seeds and hydroprimed seeds. Additionally, our results demonstrated that nanopriming regulated the expression level of BnCAM and BnPER during priming time and after sowing, along with the various levels of expression remarkably in BnEXP4 and BnRAB28, especially at 24 h of being sown under salt stress, which promoted seed germination and early seedling growth. Overall, this work provides new insights into mechanisms underlying the interactions of SeNPs and ZnONPs with plant hormones during the seed imbibition and early seedling stage, consequently enhanced plant growth and development. Additionally, these findings portrayed that the application of SeNPs and ZnONPs could be a new strategy and useful approach to enhance tolerance against salinity in rapeseed plants.
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•Nano-Se and -ZnO modulated the expression of ABA and GA genes during the germination stage.•NPs enhanced the germination attributes and seed microstructure and reduced the oxidative damage under salt stress.•Nanomaterials increased salinity tolerance during the early seedling stage in B. napus.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Diabetic retinopathy (DR) is a disease that forms as a complication of diabetes. It is particularly dangerous since it often goes unnoticed and can lead to blindness if not detected early. Despite ...the clear importance and urgency of such an illness, there is no precise system for the early detection of DR so far. Fortunately, such system could be achieved using deep learning including convolutional neural networks (CNNs), which gained momentum in the field of medical imaging due to its capability of being effectively integrated into various systems in a manner that significantly improves the performance. This paper proposes a computer aided diagnostic (CAD) system for the early detection of non-proliferative DR (NPDR) using CNNs. The proposed system is developed for the optical coherence tomography (OCT) imaging modality. Throughout this paper, all aspects of deployment of the proposed system are studied starting from the preprocessing stage required to extract input retina patches to train the CNN without resizing the image, to the use of transfer learning principals and how to effectively combine features in order to optimize performance. This is done through investigating several scenarios for the system setup and then selecting the best one, which from the results revealed to be a two pre-trained CNNs based system, in which one of these CNNs is independently fed by nasal retina patches and the other one by temporal retina patches. The proposed transfer learning based CAD system achieves a promising accuracy of 94%.
Oil leaks onto water surfaces from big tankers, ships, and pipeline cracks cause considerable damage and harm to the marine environment. Synthetic Aperture Radar (SAR) images provide an approximate ...representation for target scenes, including sea and land surfaces, ships, oil spills, and look-alikes. Detection and segmentation of oil spills from SAR images are crucial to aid in leak cleanups and protecting the environment. This paper introduces a two-stage deep-learning framework for the identification of oil spill occurrences based on a highly unbalanced dataset. The first stage classifies patches based on the percentage of oil spill pixels using a novel 23-layer Convolutional Neural Network. In contrast, the second stage performs semantic segmentation using a five-stage U-Net structure. The generalized Dice loss is minimized to account for the reduced oil spill representation in the patches. The results of this study are very promising and provide a comparable improved precision and Dice score compared to related work.
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