The agricultural sector in Saudi Arabia has witnessed rapid growth in both production and area under cultivation over the last few decades. This has prompted some concern over the state and
future ...availability of fossil groundwater resources, which have been used to drive this
expansion. Large-scale studies using satellite gravimetric data show a declining trend over this
region. However, water management agencies require much more detailed information on both the
spatial distribution of agricultural fields and their varying levels of water exploitation through time than coarse gravimetric data can provide. Relying on self-reporting from farm
operators or sporadic data collection campaigns to obtain needed information are not feasible
options, nor do they allow for retrospective assessments. In this work, a water accounting
framework that combines satellite data, meteorological output from weather prediction models, and
a modified land surface hydrology model was developed to provide information on both irrigated crop water use and groundwater abstraction rates. Results from the local scale, comprising several thousand individual center-pivot fields, were then used to quantify the regional-scale response. To do this, a semi-automated approach for the delineation of center-pivot fields using a
multi-temporal statistical analysis of Landsat 8 data was developed. Next, actual crop evaporation
rates were estimated using a two-source energy balance (TSEB) model driven by leaf area index,
land surface temperature, and albedo, all of which were derived from Landsat 8. The
Community Atmosphere Biosphere Land Exchange (CABLE) model was then adapted to use satellite-based
vegetation and related surface variables and forced with a 3 km reanalysis dataset from the Weather Research and Forecasting (WRF) model. Groundwater abstraction rates were then inferred
by estimating the irrigation supplied to each individual center pivot, which was determined via an optimization approach that considered CABLE-based estimates of evaporation and TSEB-based satellite estimates. The framework was applied over two study regions in Saudi Arabia: a
small-scale experimental facility of around 40 center pivots in Al Kharj that was used for an initial evaluation and a much larger agricultural region in Al Jawf province comprising more than 5000 individual fields across an area exceeding 2500 km2. Total groundwater abstraction
for the year 2015 in Al Jawf was estimated at approximately 5.5 billion cubic meters, far exceeding any recharge to the groundwater system and further highlighting the need for a
comprehensive water management strategy. Overall, this novel data–model fusion approach facilitates the compilation of national-scale groundwater abstractions while also detailing field-scale information that allows both farmers and water management agencies to make informed
water accounting decisions across multiple spatial and temporal scales.
Metastatic breast cancer (MBC) is an extremely recalcitrant disease capable of bypassing current targeted therapies via engagement of several growth promoting pathways. SH2 containing protein ...tyrosine phosphatase-2 (SHP2) is an oncogenic phosphatase known to facilitate growth and survival signaling downstream of numerous receptor inputs. Herein, we used inducible genetic depletion and two distinct pharmacological inhibitors to investigate the therapeutic potential of targeting SHP2 in MBC. Cells that acquired resistance to the ErbB kinase inhibitor, neratinib, displayed increased phosphorylation of SHP2 at the Y542 activation site. In addition, higher levels of SHP2 phosphorylation, but not expression, were associated with decreased survival of breast cancer patients. Pharmacological inhibition of SHP2 activity blocked ERK1/2 and AKT signaling generated from exogenous stimulation with FGF2, PDGF, and hGF and readily prevented MBC cell growth induced by these factors. SHP2 was also phosphorylated upon engagement of the extracellular matrix (ECM) via focal adhesion kinase. Consistent with the potential of SHP2-targeted compounds as therapeutic agents, the growth inhibitory property of SHP2 blockade was enhanced in ECM-rich 3D culture environments. In vivo blockade of SHP2 in the adjuvant setting decreased pulmonary metastasis and extended the survival of systemic tumor-bearing mice. Finally, inhibition of SHP2 in combination with FGFR-targeted kinase inhibitors synergistically blocked the growth of MBC cells. Overall, our findings support the conclusion that SHP2 constitutes a shared signaling node allowing MBC cells to simultaneously engage a diversity of growth and survival pathways, including those derived from the ECM.
In breast cancer (BC), tissue stiffening via fibronectin (FN) and collagen accumulation is associated with advanced disease progression at both the primary tumor and metastatic sites. Here, we ...evaluate FN production in 15 BC cell lines, representing a variety of subtypes, phenotypes, metastatic potentials, and chemotherapeutic sensitivities. We demonstrate that intracellular and soluble FN is initially lost during tumorigenic transformation but is rescued in all lines with epithelial-mesenchymal plasticity (EMP). Importantly, we establish that no BC cell line was able to independently organize a robust FN matrix. Non-transformed mammary epithelial cells were also unable to deposit FN matrices unless transglutaminase 2, a FN crosslinking enzyme, was overexpressed. Instead, BC cells manipulated the FN matrix production of fibroblasts in a phenotypic-dependent manner. In addition, varied accumulation levels were seen depending if the fibroblasts were conditioned to model paracrine signaling or endocrine signaling of the metastatic niche. In the former, fibroblasts conditioned by BC cultures with high EMP resulted in the largest FN matrix accumulation. In contrast, mesenchymal BC cells produced extracellular vesicles (EV) that resulted in the highest levels of matrix formation by conditioned fibroblasts. Overall, we demonstrate a dynamic relationship between tumor and stromal cells within the tumor microenvironment, in which the levels and fibrillarization of FN in the extracellular matrix are modulated during the particular stages of disease progression.
Over time, human beings have built increasingly large astronomical observatories to increase the number of discoveries related to celestial objects. However, the amount of collected elements far ...exceeds the human capacity to analyze findings without help. For this reason, researchers must now turn to machine learning to analyze such data, identifying and classifying transient objects or events within extensive observations of the firmament. Algorithms from the family of random forests (an ensemble of decision trees) have become a powerful tool that can be used to classify astronomical events and objects. This work aims to illustrate the versatility of machine learning algorithms, such as decision trees, to facilitate the identification and classification of celestial bodies by manipulating hyperparameters and studying the attributes of celestial body datasets. By applying a random forest algorithm to a well-known dataset that includes three types of celestial bodies, its effectiveness was compared against some supervised classifiers of the most important approaches (Bayes, nearest neighbors, support vector machines, and neural networks). The results show that random forests are a good alternative for data analysis and classification in astronomical observations.
Worldwide, there are currently around 18.1 million new cancer cases and 9.6 million cancer deaths yearly. Although cancer diagnosis and treatment has improved greatly in the past several decades, a ...complete understanding of the complex interactions between cancer cells and the tumor microenvironment during primary tumor growth and metastatic expansion is still lacking. Several aspects of the metastatic cascade require in vitro investigation. This is because in vitro work allows for a reduced number of variables and an ability to gather real-time data of cell responses to precise stimuli, decoupling the complex environment surrounding in vivo experimentation. Breakthroughs in our understanding of cancer biology and mechanics through in vitro assays can lead to better-designed ex vivo precision medicine platforms and clinical therapeutics. Multiple techniques have been developed to imitate cancer cells in their primary or metastatic environments, such as spheroids in suspension, microfluidic systems, 3D bioprinting, and hydrogel embedding. Recently, magnetic-based in vitro platforms have been developed to improve the reproducibility of the cell geometries created, precisely move magnetized cell aggregates or fabricated scaffolding, and incorporate static or dynamic loading into the cell or its culture environment. Here, we will review the latest magnetic techniques utilized in these in vitro environments to improve our understanding of cancer cell interactions throughout the various stages of the metastatic cascade.
Purpose
To analyze the differential transcriptome expression in hypertrophic ligaments flavum (HLF) compared to normal ligaments.
Methods
A case–control study was conducted that included 15 patients ...with hypertrophy of LF and 15 controls. Samples of LF were obtained through a lumbar laminectomy and analyzed by DNA microarrays and histology. The dysregulated biological processes, signaling pathways, and pathological markers in the HLF were identified using bioinformatics tools.
Results
The HLF had notable histological alterations, including hyalinosis, leukocyte infiltration, and disarrangement of collagen fibers. Transcriptomic analysis showed that up-regulated genes were associated with the signaling pathways of Rho GTPases, receptor tyrosine kinases (RTK), fibroblast growth factors (FGF), WNT, vascular endothelial growth factor, phosphoinositide 3-kinase (PIK3), mitogen-activated protein kinases, and immune system. The genes PIK3R1, RHOA, RPS27A, CDC42, VAV1, and FGF5, 9, 18, and 19 were highlighted as crucial markers in HLF. The down-expressed genes in the HLF had associations with the metabolism of RNA and proteins.
Conclusion
Our results suggest that abnormal processes in hypertrophied LF are mediated by the interaction of the Rho GTPase, RTK, and PI3K pathways, which have not been previously described in the HLF, but for which there are currently therapeutic proposals. More studies are required to confirm the therapeutic potential of the pathways and mediators described in our results.
Over time, a myriad of applications have been generated for pattern classification algorithms. Several case studies include parametric classifiers such as the Multi-Layer Perceptron (MLP) classifier, ...which is one of the most widely used today. Others use non-parametric classifiers, Support Vector Machine (SVM), K-Nearest Neighbors (K-NN), Naïve Bayes (NB), Adaboost, and Random Forest (RF). However, there is still little work directed toward a new trend in Artificial Intelligence (AI), which is known as eXplainable Artificial Intelligence (X-AI). This new trend seeks to make Machine Learning (ML) algorithms increasingly simple and easy to understand for users. Therefore, following this new wave of knowledge, in this work, the authors develop a new pattern classification methodology, based on the implementation of the novel Minimalist Machine Learning (MML) paradigm and a higher relevance attribute selection algorithm, which we call
. We examine and compare the performance of this methodology with MLP, NB, KNN, SVM, Adaboost, and RF classifiers to perform the task of classification of Computed Tomography (CT) brain images. These grayscale images have an area of 128 × 128 pixels, and there are two classes available in the dataset: CT without Hemorrhage and CT with Intra-Ventricular Hemorrhage (IVH), which were classified using the Leave-One-Out Cross-Validation method. Most of the models tested by Leave-One-Out Cross-Validation performed between 50% and 75% accuracy, while sensitivity and sensitivity ranged between 58% and 86%. The experiments performed using our methodology matched the best classifier observed with 86.50% accuracy, and they outperformed all state-of-the-art algorithms in specificity with 91.60%. This performance is achieved hand in hand with simple and practical methods, which go hand in hand with this trend of generating easily explainable algorithms.
The advent of microbubble contrast agents has enhanced the capabilities of ultrasound as a medical imaging modality and stimulated innovative strategies for ultrasound-mediated drug and gene ...delivery. While the utilization of microbubbles as carrier vehicles has shown encouraging results in cancer therapy, their applicability has been limited by a large size which typically confines them to the vasculature. To enhance their multifunctional contrast and delivery capacity, it is critical to reduce bubble size to the nanometer range without reducing echogenicity. In this work, we present a novel strategy for formulation of nanosized, echogenic lipid bubbles by incorporating the surfactant Pluronic, a triblock copolymer of ethylene oxide copropylene oxide coethylene oxide into the formulation. Five Pluronics (L31, L61, L81, L64 and P85) with a range of molecular weights (M w: 1100 to 4600 Da) were incorporated into the lipid shell either before or after lipid film hydration and before addition of perfluorocarbon gas. Results demonstrate that Pluronic−lipid interactions lead to a significantly reduced bubble size. Among the tested formulations, bubbles made with Pluronic L61 were the smallest with a mean hydrodynamic diameter of 207.9 ± 74.7 nm compared to the 880.9 ± 127.6 nm control bubbles. Pluronic L81 also significantly reduced bubble size to 406.8 ± 21.0 nm. We conclude that Pluronic is effective in lipid bubble size control, and Pluronic M w, hydrophilic−lipophilic balance (HLB), and Pluronic/lipid ratio are critical determinants of the bubble size. Most importantly, our results have shown that although the bubbles are nanosized, their stability and in vitro and in vivo echogenicity are not compromised. The resulting nanobubbles may be better suited for contrast enhanced tumor imaging and subsequent therapeutic delivery.
OBJECTIVES/GOALS: Annually, 1.5 million global patients receive maxillofacial reconstruction. The gold standard, involving bone particulate, lacks reproducibility. To improve this, we have developed ...a custom 3D-printable, porous cover-core design. This study optimizes the hydrogel core properties and growth factor (GF) release for enhanced bone regeneration. METHODS/STUDY POPULATION: Different ratios of Methacrylated Gelatin (GelMa), Methacrylated Alginate (AlgMa) and tricalcium phosphate (α²-TCP) were combined to optimize cell viability, GF sequestration and mechanical stability. Material characterization was performed using a rheometer to determine the viscoelastic properties of the blends. Release from disks loaded with FGF-containing PLGA microparticles was quantified with an ELISA kit. Furthermore, scanning electron microscopy (SEM) was conducted to quantify hydrogel porosity. In vitro studies were performed using NIH 3T3 murine fibroblasts in Corning Transwells while immunofluorescent, metabolic and osteogenic studies were performed in 96 well plates to investigate cell infiltration, cell adhesion, viability and differentiation, respectively. RESULTS/ANTICIPATED RESULTS: By adjusting the AlgGelMa ratio, we manipulated matrix properties. GelMa possesses excellent durability and cell adhesion due to intrinsic RGD-binding motifs. AlgMa enhanced swelling by 30%, growth factor sequestration by 50% in 24hrs, and matrix storage modulus without increasing the loss modulus which could cause cell migration away from the hydrogel. Varying the AlgGelMa ratio lowered pH, promoted cell infiltration, and reduced fibronectin accumulation. The addition of β-TCP is anticipated to improve cell differentiation towards an osteogenic lineage due to improved elastic modulus, calcium and phosphate ion concentration improving mineral deposition. DISCUSSION/SIGNIFICANCE: These findings suggest through the use of this composite, early cell infiltration can be increased and promoted due to FGF release, leading to increased osteointegration. Our porous cover-core design ensures efficient clot integration and early cell infiltration, enhancing osteointegration through FGF release.
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