Molecular Mechanisms in Tumorigenesis of Hepatocellular Carcinoma and in Target Treatments-An Overview.

Hepatocellular carcinoma is the most common primary malignancy of the liver, with hepatocellular differentiation. It is ranked sixth among the most common cancers worldwide and is the third leading cause of cancer-related deaths. The most important etiological factors discussed here are viral infection (HBV, HCV), exposure to aflatoxin B1, metabolic syndrome, and obesity (as an independent factor). Directly or indirectly, they induce chromosomal aberrations, mutations, and epigenetic changes in specific genes involved in intracellular signaling pathways, responsible for synthesis of growth factors, cell proliferation, differentiation, survival, the metastasis process (including the epithelial-mesenchymal transition and the expression of adhesion molecules), and angiogenesis. All these disrupted molecular mechanisms contribute to hepatocarcinogenesis. Furthermore, equally important is the interaction between tumor cells and the components of the tumor microenvironment: inflammatory cells and macrophages-predominantly with a pro-tumoral role-hepatic stellate cells, tumor-associated fibroblasts, cancer stem cells, extracellular vesicles, and the extracellular matrix. In this paper, we reviewed the molecular biology of hepatocellular carcinoma and the intricate mechanisms involved in hepatocarcinogenesis, and we highlighted how certain signaling pathways can be pharmacologically influenced at various levels with specific molecules. Additionally, we mentioned several examples of recent clinical trials and briefly described the current treatment protocol according to the NCCN guidelines.

Qatar's FIFA World Cup odyssey: A quest for legacy transforming a small nation into a global destination.

This study delves into the profound impact of mega-events on a destination's perception, focusing notably on Qatar's hosting experience during the FIFA World Cup 2022. Employing a qualitative longitudinal research approach, data is drawn from a variety of sources including Scopus articles, international studies, tourism records, newspapers, and interviews with diverse stakeholders such as visitors, tourism experts, executives, and government officials. Through an inductive content analysis of this extensive dataset, the authors identify key influencing factors. They meticulously examine a decade-long evolution using assessments from independent travel and tourism rating organizations alongside various metrics. The findings reveal a significant uptick in Qatar's allure and inbound tourism. Factors contributing to this surge are systematically categorized, with transportation and events infrastructure, hospitality and accommodation facilities, and media exposure emerging as consistent themes across host nations. Additionally, contextual factors like security/safety, culture/heritage, and diversity are highlighted for their pivotal role in shaping a destination's image. This research underscores how mega-events act as catalysts for reshaping Qatar's destination identity and attracting inbound tourism, as evidenced by a range of indicators contingent upon maintaining both universal and contextual factors. It emphasizes the importance of a strategic vision that nurtures these factors over time, aligning with the destination's life cycle to forge a lasting legacy. Furthermore, the study illuminates how mega-events can bolster soft power for small countries lacking significant natural or historical attractions, providing valuable insights for policymakers and marketers to devise effective strategies.

COVID-Net L2C-ULTRA: An Explainable Linear-Convex Ultrasound Augmentation Learning Framework to Improve COVID-19 Assessment and Monitoring.

While no longer a public health emergency of international concern, COVID-19 remains an established and ongoing global health threat. As the global population continues to face significant negative impacts of the pandemic, there has been an increased usage of point-of-care ultrasound (POCUS) imaging as a low-cost, portable, and effective modality of choice in the COVID-19 clinical workflow. A major barrier to the widespread adoption of POCUS in the COVID-19 clinical workflow is the scarcity of expert clinicians who can interpret POCUS examinations, leading to considerable interest in artificial intelligence-driven clinical decision support systems to tackle this challenge. A major challenge to building deep neural networks for COVID-19 screening using POCUS is the heterogeneity in the types of probes used to capture ultrasound images (e.g., convex vs. linear probes), which can lead to very different visual appearances. In this study, we propose an analytic framework for COVID-19 assessment able to consume ultrasound images captured by linear and convex probes. We analyze the impact of leveraging extended linear-convex ultrasound augmentation learning on producing enhanced deep neural networks for COVID-19 assessment, where we conduct data augmentation on convex probe data alongside linear probe data that have been transformed to better resemble convex probe data. The proposed explainable framework, called COVID-Net L2C-ULTRA, employs an efficient deep columnar anti-aliased convolutional neural network designed via a machine-driven design exploration strategy. Our experimental results confirm that the proposed extended linear-convex ultrasound augmentation learning significantly increases performance, with a gain of 3.9% in test accuracy and 3.2% in AUC, 10.9% in recall, and 4.4% in precision. The proposed method also demonstrates a much more effective utilization of linear probe images through a 5.1% performance improvement in recall when such images are added to the training dataset, while all other methods show a decrease in recall when trained on the combined linear-convex dataset. We further verify the validity of the model by assessing what the network considers to be the critical regions of an image with our contribution clinician.

COVID-19-Associated Rhino-Orbital Mucormycosis: Histological and Electron Microscopy Characteristics.

COVID-19-associated rhino-orbital mucormycosis has become a new clinical entity. This study's aim was to evaluate the histopathological and ultramicroscopic morphological aspects of this fungal infection. This was an observational retrospective study on eight patients from three tertiary centers in Romania. The tissue samples collected during functional endoscopic sinus surgery were studied through histopathological examination, scanning electron microscopy, and transmission electron microscopy. In the histopathological examination, the morphological aspects characteristic of mucormycosis in all cases were identified: wide aseptate hyphae with right-angle ramifications, which invade blood vessels. One case presented perineural invasion into the perineural lymphatics. And in another case, mucormycosis-aspergillosis fungal coinfection was identified. Through scanning electron microscopy, long hyphae on the surface of the mucosa surrounded by cells belonging to the local immune system were identified in all samples, and bacterial biofilms were identified in half of the samples. Through transmission electron microscopy, aseptate hyphae and bacterial elements were identified in the majority of the samples. Rhino-orbital-cerebral mucormycosis associated with COVID-19 produces nasal sinus dysbiosis, which favors the appearance of bacterial biofilms. The way in which the infection develops depends on the interaction of the fungi with cells of the immune system.

COVID-Net Biochem: an explainability-driven framework to building machine learning models for predicting survival and kidney injury of COVID-19 patients from clinical and biochemistry data.

Since the World Health Organization declared COVID-19 a pandemic in 2020, the global community has faced ongoing challenges in controlling and mitigating the transmission of the SARS-CoV-2 virus, as well as its evolving subvariants and recombinants. A significant challenge during the pandemic has not only been the accurate detection of positive cases but also the efficient prediction of risks associated with complications and patient survival probabilities. These tasks entail considerable clinical resource allocation and attention. In this study, we introduce COVID-Net Biochem, a versatile and explainable framework for constructing machine learning models. We apply this framework to predict COVID-19 patient survival and the likelihood of developing Acute Kidney Injury during hospitalization, utilizing clinical and biochemical data in a transparent, systematic approach. The proposed approach advances machine learning model design by seamlessly integrating domain expertise with explainability tools, enabling model decisions to be based on key biomarkers. This fosters a more transparent and interpretable decision-making process made by machines specifically for medical applications. More specifically, the framework comprises two phases: In the first phase, referred to as the "clinician-guided design" phase, the dataset is preprocessed using explainable AI and domain expert input. To better demonstrate this phase, we prepared a benchmark dataset of carefully curated clinical and biochemical markers based on clinician assessments for survival and kidney injury prediction in COVID-19 patients. This dataset was selected from a patient cohort of 1366 individuals at Stony Brook University. Moreover, we designed and trained a diverse collection of machine learning models, encompassing gradient-based boosting tree architectures and deep transformer architectures, specifically for survival and kidney injury prediction based on the selected markers. In the second phase, called the "explainability-driven design refinement" phase, the proposed framework employs explainability methods to not only gain a deeper understanding of each model's decision-making process but also to identify the overall impact of individual clinical and biochemical markers for bias identification. In this context, we used the models constructed in the previous phase for the prediction task and analyzed the explainability outcomes alongside a clinician with over 8 years of experience to gain a deeper understanding of the clinical validity of the decisions made. The explainability-driven insights obtained, in conjunction with the associated clinical feedback, are then utilized to guide and refine the training policies and architectural design iteratively. This process aims to enhance not only the prediction performance but also the clinical validity and trustworthiness of the final machine learning models. Employing the proposed explainability-driven framework, we attained 93.55% accuracy in survival prediction and 88.05% accuracy in predicting kidney injury complications. The models have been made available through an open-source platform. Although not a production-ready solution, this study aims to serve as a catalyst for clinical scientists, machine learning researchers, and citizen scientists to develop innovative and trustworthy clinical decision support solutions, ultimately assisting clinicians worldwide in managing pandemic outcomes.

Towards Building a Trustworthy Deep Learning Framework for Medical Image Analysis.

Computer vision and deep learning have the potential to improve medical artificial intelligence (AI) by assisting in diagnosis, prediction, and prognosis. However, the application of deep learning to medical image analysis is challenging due to limited data availability and imbalanced data. While model performance is undoubtedly essential for medical image analysis, model trust is equally important. To address these challenges, we propose TRUDLMIA, a trustworthy deep learning framework for medical image analysis, which leverages image features learned through self-supervised learning and utilizes a novel surrogate loss function to build trustworthy models with optimal performance. The framework is validated on three benchmark data sets for detecting pneumonia, COVID-19, and melanoma, and the created models prove to be highly competitive, even outperforming those designed specifically for the tasks. Furthermore, we conduct ablation studies, cross-validation, and result visualization and demonstrate the contribution of proposed modules to both model performance (up to 21%) and model trust (up to 5%). We expect that the proposed framework will support researchers and clinicians in advancing the use of deep learning for dealing with public health crises, improving patient outcomes, increasing diagnostic accuracy, and enhancing the overall quality of healthcare delivery.

Effects of Phytochemicals from Fermented Food Sources in Alzheimer's Disease In Vivo Experimental Models: A Systematic Review.

The socioeconomic burden of Alzheimer's Disease (AD) stems from its characteristic multifactorial etiology and, implicitly, the difficulties associated with its treatment. With the increase in life expectancy and health awareness, nutraceuticals and functional foods are filling in the gaps left by the limitation of classical medical treatment in chronic conditions associated with lifestyle factors, such as neurological disorders. Processes, such as fermentation that enhance food phytochemical content are garnering increased attention due to their functional and health-related properties. This systematic review aims to provide an overview of the evidence of phytochemicals from fermented food sources inducing therapeutic outcomes and cognitive benefits from in vivo experimental models of Alzheimer's Disease. The present systematic review was conducted in accordance with PRISMA guidelines. Searches were performed in the following databases: MEDLINE, Embase, Cochrane, Scopus, Google Scholar, and Science Citation Index Expanded (Web of Science) by two independent reviewers. Titles and abstracts yielded by the search were screened for eligibility against the inclusion criteria. The search strategy yielded 1899 titles, encompassing studies from 1948 to 2022. After the removal of duplicates, and screening of titles, abstracts, and full texts, thirty three studies obtained from the original search strategy and seven studies from references satisfied the inclusion criteria and were included in the present systematic review. Several studies have emphasized the potential of fermentation to yield small-molecule phytochemicals that are not present in raw products. When these phytochemicals are combined, their collective strength has demonstrated the ability to exceed the antioxidant, anti-inflammatory, and neuroprotective benefits of individual phytochemicals when given in their pure form. Among the various fermented foods that have been studied, soy isoflavones obtained through fermentation have shown the most substantial evidence of altering phytochemical content and improving outcomes in animal models of AD. While promising in initial results, other fermented foods and traditional medicines require more detailed research in order to establish their effectiveness and proper utilization. As is, many of the experimental designs lacked phytochemical analysis of the used fermented product or comparison with the non-fermented counterpart. This, coupled with proper reporting in animal studies, will significantly raise the quality of performed studies as well as the weight of obtained results.

Albumin nanoparticles with tunable ultraviolet-to-red autofluorescence for label-free cell imaging and selective biosensing of copper ion.

Early and simple detection of aberrant cooper metabolism in diseases with neurological-manifestations and several other conditions, including cancer, becomes an urgent necessity. Instrumental methods used today are limited to high-cost equipment and reagents and demand highly qualified personnel. In this work, we report easy-to-use and cost-effective nano-sized sensors for the selective and quantitative detection of copper ion based on fluorescence quenching. Glutaraldehyde cross-linked albumin nanoparticles with tunable ultraviolet-to-red autofluorescence emissions are developed as dual-agents for sensing and imaging. These albumin nanoparticles show great selectivity towards copper ion when tested against a selection of biochemical components and other metal ions, and a limit of detection as low as 1.9 µM, relevant for sensing in clinical diagnosis, was determined. In addition, a lack of toxicity and good cellular uptake were observed and the ultraviolet-to-red intrinsic fluorescence of the albumin nanoparticles was preserved when tested in vitro on NIH:OVCAR3 cell line. Preliminary studies confirm the albumin nanoparticles' ability to detect Cu2+in vitro and establishes their potential for future practical use.

Experimental envenomation with honeybee venom melittin and phospholipase A2 induced multiple ultrastructural changes in adrenocortical mitochondria.

Bee stings represent a public health subject, but the mechanisms involved in bee venom toxicity are not yet fully understood. To evaluate the reactions of adrenocortical cells, through which organisms respond to stress, two honeybee venom components: melittin (Mlt) and phospholipase A2 (PLA2) were tested as potential chemical stressors. Modifications were investigated with transmission electron microscopy and microanalysis. A single dose of Mlt (31 mg/kg) or PLA2 (9.3 mg/kg) was injected in rats of groups ML and PL; daily doses of Mlt (350 µg/kg) or PLA2 (105 µg/kg) were injected 30 days in rats of groups M30 and P30. Adrenocortical cells in ML group showed ultrastructural degenerative alterations of nuclei, endoplasmic reticulum, and mitochondria that exhibited lipid inclusions and mitochondrial cristae (MC) re-organized into mono- or multimembrane large vesicles, and whorls of membranes. Many MC were degenerated. In the M30 group, similar ultrastructural changes, but of lower amplitude were noted; lipid cytosolic droplets were heterogenous. MC diameters in Mlt groups (melittin treated groups) were significantly higher than in control (C) group. In PL group, mitochondria contained large lipid inclusions, vesicular MC of different sizes and multiple membranes, and debris, or whorl structures. In P30 group MC were tubular with increased diameters. In both PLA2 groups (PLA2 treated groups) MC were significantly larger than in C group. We concluded that Mlt and PLA2 were powerful stressors, toxic at the tested doses, cellular reactions concerning in all groups mainly mitochondria, but also other cellular compartments. Apart from degenerative regression of MC, the rearrangement of tubular MC occurred into one or multiple large multimembrane vesicular MC. Reactions to the high doses were more pronounced, with the highest amplitude in ML group, and the lowest in P30 group.

Effects of Gold Nanoparticles Functionalized with Cornus mas L. Fruit Extract on the Aorta Wall in Rats with a High-Fat Diet and Experimental-Induced Diabetes Mellitus-An Imaging Study.

Diabetes mellitus and high-fat diets trigger the mechanisms that alter the walls of blood vessels. Gold nanoparticles, as new pharmaceutical drug delivery systems, may be used in the treatment of different diseases. In our study, the aorta was investigated via imaging after the oral administration of gold nanoparticles functionalized with bioactive compounds derived from Cornus mas fruit extract (AuNPsCM) in rats with a high-fat diet and diabetes mellitus. Sprague Dawley female rats that received a high-fat diet (HFD) for 8 months were injected with streptozotocin to develop diabetes mellitus (DM). The rats were randomly allocated into five groups and were treated, for one additional month with HFD, with carboxymethylcellulose (CMC), insulin, pioglitazone, AuNPsCM solution or with Cornus mas L. extract solution. The aorta imaging investigation consisted of echography, magnetic resonance imaging and transmission electron microscopy (TEM). Compared to the rats that received only CMC, the oral administration of AuNPsCM produced significant increases in aorta volume and significant decreases in blood flow velocity, with ultrastructural disorganization of the aorta wall. The oral administration of AuNPsCM altered the aorta wall with effects on the blood flow.

Magnetic Nanoclusters Stabilized with Poly[3,4-Dihydroxybenzhydrazide] as Efficient Therapeutic Agents for Cancer Cells Destruction.

Magnetic structures exhibiting large magnetic moments are sought after in theranostic approaches that combine magnetic hyperthermia treatment (MH) and diagnostic magnetic resonance imaging in oncology, since they offer an enhanced magnetic response to an external magnetic field. We report on the synthesized production of a core-shell magnetic structure using two types of magnetite nanoclusters (MNC) based on a magnetite core and polymer shell. This was achieved through an in situ solvothermal process, using, for the first time, 3,4-dihydroxybenzhydrazide (DHBH) and poly[3,4-dihydroxybenzhydrazide] (PDHBH) as stabilizers. Transmission electron microscopy (TEM) analysis showed the formation of spherical MNC, X-ray photoelectronic spectroscopy (XPS) and Fourier transformed infrared (FT-IR) analysis proved the existence of the polymer shell. Magnetization measurement showed saturation magnetization values of 50 emu/g for PDHBH@MNC and 60 emu/g for DHBH@MNC with very low coercive field and remanence, indicating that the MNC are in a superparamagnetic state at room temperature and are thus suitable for biomedical applications. MNCs were investigated in vitro, on human normal (dermal fibroblasts-BJ) and tumor (colon adenocarcinoma-CACO2, and melanoma-A375) cell lines, in view of toxicity, antitumor effectiveness and selectivity upon magnetic hyperthermia. MNCs exhibited good biocompatibility and were internalized by all cell lines (TEM), with minimal ultrastructural changes. By means of flowcytometry apoptosis detection, fluorimetry, spectrophotometry for mitochondrial membrane potential, oxidative stress, ELISA-caspases, and Western blot-p53 pathway, we show that MH efficiently induced apoptosis mostly via the membrane pathway and to a lower extent by the mitochondrial pathway, the latter mainly observed in melanoma. Contrarily, the apoptosis rate was above the toxicity limit in fibroblasts. Due to its coating, PDHBH@MNC showed selective antitumor efficacy and can be further used in theranostics since the PDHBH polymer provides multiple reaction sites for the attachment of therapeutic molecules.

COVID-Net USPro: An Explainable Few-Shot Deep Prototypical Network for COVID-19 Screening Using Point-of-Care Ultrasound.

As the Coronavirus Disease 2019 (COVID-19) continues to impact many aspects of life and the global healthcare systems, the adoption of rapid and effective screening methods to prevent the further spread of the virus and lessen the burden on healthcare providers is a necessity. As a cheap and widely accessible medical image modality, point-of-care ultrasound (POCUS) imaging allows radiologists to identify symptoms and assess severity through visual inspection of the chest ultrasound images. Combined with the recent advancements in computer science, applications of deep learning techniques in medical image analysis have shown promising results, demonstrating that artificial intelligence-based solutions can accelerate the diagnosis of COVID-19 and lower the burden on healthcare professionals. However, the lack of large, well annotated datasets poses a challenge in developing effective deep neural networks, especially in the case of rare diseases and new pandemics. To address this issue, we present COVID-Net USPro, an explainable few-shot deep prototypical network that is designed to detect COVID-19 cases from very few ultrasound images. Through intensive quantitative and qualitative assessments, the network not only demonstrates high performance in identifying COVID-19 positive cases, using an explainability component, but it is also shown that the network makes decisions based on the actual representative patterns of the disease. Specifically, COVID-Net USPro achieves 99.55% overall accuracy, 99.93% recall, and 99.83% precision for COVID-19-positive cases when trained with only five shots. In addition to the quantitative performance assessment, our contributing clinician with extensive experience in POCUS interpretation verified the analytic pipeline and results, ensuring that the network's decisions are based on clinically relevant image patterns integral to COVID-19 diagnosis. We believe that network explainability and clinical validation are integral components for the successful adoption of deep learning in the medical field. As part of the COVID-Net initiative, and to promote reproducibility and foster further innovation, the network is open-sourced and available to the public.

Iron chelation alleviates multiple pathophysiological pathways in a rat model of cardiac pressure overload.

Iron dysmetabolism affects a great proportion of heart failure patients, while chronic hypertension is one of the most common risk factors for heart failure and death in industrialized countries. Serum data from reduced ejection fraction heart failure patients show a relative or absolute iron deficiency, whereas cellular myocardial analyses field equivocal data. An observed increase in organellar iron deposits was incriminated to cause reactive oxygen species formation, lipid peroxidation, and cell death. Therefore, we studied the effects of iron chelation on a rat model of cardiac hypertrophy. Suprarenal abdominal aortic constriction was achieved surgically, with a period of nine weeks to accommodate the development of chronic pressure overload. Next, deferiprone (100 mg/kg/day), a lipid-permeable iron chelator, was administered for two weeks. Pressure overload resulted in increased inflammation, fibrotic remodeling, lipid peroxidation, left ventricular hypertrophy and mitochondrial iron derangements. Deferiprone reduced cardiac inflammation, lipid peroxidation, mitochondrial iron levels, and hypertrophy, without affecting circulating iron levels or ejection fraction. In conclusion, metallic molecules may pose ambivalent effects within the cardiovascular system, with beneficial effects of iron redistribution, chiefly in the mitochondria.

Changes in Organ Weight, Sperm Quality and Testosterone Levels After Aluminum (Al) and Indium (In) Administration to Wistar Rats.

BACKGROUND: Aluminum and indium are widely used in industrial manufacturing, in pharmaceutical products, in medical treatments, and in food packaging, so they could reach organisms by different way. In order to clarify whether these elements are dangerous, we already demonstrated the ultrastructural modifications observed in the testicles, the epididymides, and the seminal vesicles of rat. Their pro-oxidative effect was also confirmed concomitantly to a decrease in anti-oxidant defenses in the blood, the testicles, and the liver. Thus, it seemed very logic to evaluate damages in the reproductive organs, especially on the exocrine and endocrine functions of the testicles. METHODS: Aluminum and indium were intraperitoneally administered to male Wistar rats. Sperm solution was obtained from cauda epididymides. Motility, viability, density, and malformation of spermatozoa solution were assessed. Serum total unconjugated testosterone concentrations were measured using RIA technique. RESULTS: Our results showed a decrease in weight of the testicles, epididymides, and seminal vesicles of indium-treated rats and an increase in the weight of their kidneys. A decrease in motility, viability, and density of epididymides stored sperm as well as generation of many spermatozoa malformations was also observed especially in indium-treated rats. Testosterone levels were increased in indium but were enhanced in aluminum group. This confirmed our previous studies showing that aluminum and indium are toxic for the testicular tissues. This could be explained by the generation of reactive oxygen species (ROS) affecting strongly the exocrine and the endocrine functions of the testicles. CONCLUSION: Aluminum and indium are disturbing elements for the exocrine and endocrine functions of rat testicles.

Low Doses of Celecoxib Might Promote Phenotype Switching in Cutaneous Melanoma Treated with Dabrafenib-Preliminary Study.

Background: Cutaneous melanoma is a heterogeneous tumor with a rapidly switching molecular and cellular phenotype. The invasive phenotype switching characterized by MITFlow/AXLhigh predicts early resistance to multiple targeted drugs in melanoma. Celecoxib proved to be a valuable adjuvant in cutaneous melanoma in preclinical studies. Our in vitro study evaluated for the first time whether celecoxib could prevent phenotype switching in two human melanoma cell lines treated with dabrafenib. Methods: All in vitro experiments were carried out on BRAF-V600E-positive A375 and SK-MEL-28 human melanoma cell lines, and subjected to a celecoxib and dabrafenib drug combination for 72 h. Melanoma cells were already in the MITFlow/AXLhigh end of the spectrum. Of main interest was the evaluation of the key proteins expressed in phenotype switching (TGF-ß, MITF, AXL, YAP, TAZ), as well as cell death mechanisms correlated with oxidative stress production. Results: Celecoxib significantly enhanced the apoptotic effect of dabrafenib in each melanoma cell line compared to the dabrafenib group (p < 0.0001). Even though celecoxib promoted low MITF expression, this was correlated with high receptor tyrosine kinase AXL levels in A375 and SK-MEL-28 cell lines (p < 0.0001), a positive marker for the phenotype switch to an invasive state. Conclusion: This preliminary study highlighted that celecoxib might promote MITFlow/AXLhigh expression in cutaneous melanoma treated with dabrafenib, facilitating phenotype switching in vitro. Our results need further confirmation, as this finding could represent an important limitation of celecoxib as an antineoplastic drug.

COVIDx-US: An Open-Access Benchmark Dataset of Ultrasound Imaging Data for AI-Driven COVID-19 Analytics.

BACKGROUND: The Coronavirus Disease 2019 (COVID-19) pandemic continues to have a devastating effect on the health and well-being of the global population. Apart from the global health crises, the pandemic has also caused significant economic and financial difficulties and socio-physiological implications. Effective screening, triage, treatment planning, and prognostication of outcome play a key role in controlling the pandemic. Recent studies have highlighted the role of point-of-care ultrasound imaging for COVID-19 screening and prognosis, particularly given that it is non-invasive, globally available, and easy-to-sanitize. COVIDx-US Dataset: Motivated by these attributes and the promise of artificial intelligence tools to aid clinicians, we introduce COVIDx-US, an open-access benchmark dataset of COVID-19 related ultrasound imaging data. The COVIDx-US dataset was curated from multiple data sources and its current version, i.e., v1.5., consists of 173 ultrasound videos and 21,570 processed images across 147 patients with COVID-19 infection, non-COVID-19 infection, other lung diseases/conditions, as well as normal control cases. CONCLUSIONS: The COVIDx-US dataset was released as part of a large open-source initiative, the COVID-Net initiative, and will be continuously growing, as more data sources become available. To the best of the authors' knowledge, COVIDx-US is the first and largest open-access fully-curated benchmark lung ultrasound imaging dataset that contains a standardized and unified lung ultrasound score per video file, providing better interpretation while enabling other research avenues such as severity assessment. In addition, the dataset is reproducible, easy-to-use, and easy-to-scale thanks to the well-documented modular design.

Effects of Gold Nanoparticles Functionalized with Bioactive Compounds from Cornus mas Fruit on Aorta Ultrastructural and Biochemical Changes in Rats on a Hyperlipid Diet-A Preliminary Study.

Cornus mas L. extract (CM) presents hypolipidemic, antioxidant and anti-inflammatory activity. Gold nanoparticles (AuNPs) are considered potent delivery systems and may be used to release pharmaceutical compounds at the level of injury. In our study, we used gold nanoparticles functionalized with bioactive compounds from Cornus mas L. (AuNPsCM) in an experimental model of a high-fat diet (HFD), and we assessed their effects on aorta wall but also in the serum, as compared to Cornus mas (CM) administration. Sprague Dawley female rats were fed for 9 months with an HFD. During the last month of the experiment, we randomly allocated the animals into three groups that received, by oral gavage: saline solution, CM solution (0.158 mg/mL polyphenols) or AuNPsCM solution (260 µg Au/kg/day), while a Control group received a standard diet and saline solution. At the end of the experiment, we performed an ultrasonography of the aorta and left ventricle and a histology and transmission electron microscopy of the aorta walls; we investigated the oxidative stress and inflammation in aorta homogenates and in serum and, in addition, the lipid profile. AuNPsCM presented better effects in comparison with the natural extract (CM) on lipid peroxidation (p < 0.01) and TNF-alpha (p < 0.001) in aorta homogenates. In serum, both CM and AuNPsCM decreased the triglycerides (p < 0.001) and C-reactive protein (CM, p < 0.01; AuNPsCM, p < 0.001) and increased the antioxidant protection (p < 0.001), in comparison with the HFD group. In intima, AuNPsCM produced ultrastructural lesions, with the disorganization of intima and subendothelial connective layer, whereas CM administration preserved the intima normal aspect, but with a thinned subendothelial connective layer. AuNPsCM oral administration presented certain antioxidant, anti-inflammatory and hypolipidemic effects in an experimental model of HFD, but with a negative impact on the ultrastructure of aorta walls, highlighted by the intima disorganization.

Histological and ultrastructural changes observed in testicles, epididymides, seminal vesicles and liver of rat after intraperitoneal administration of aluminum and indium.

BACKGROUND: Aluminum (Al) and indium (In) have been largely used in medicine, pharmacy, dentistry, manufacturing, engineering, clothing as well as food processing and packaging. Our previous study showed that In was accumulated as electron-dense materials in lysosomes of Sertoli and Leydig testicular cells and the liver ones, when administered to male rats as soluble form. For this reason, we have undertaken to confirm whether Al have the same behavior as In and to enlarge this behavior to other organs of the male reproductive system: epididymis and seminal vesicle. METHODS: Experiments were performed on 24 adult male Wistar rat weighing approximately 250 g. Animals were divided to 3 groups, received Al, In or saline solution as 7 chronic intraperitoneal injections over a period of two weeks and were sacrificed 24 h after the last injection. For ultrastructure study we used The Transmission Electron Microscopy (TEM). RESULTS: The TEM showed the presence of electron-dense granules in lysosomes of testicular cells (Sertoli and Leydig cells), and in the principal epididymal and seminal vesicle cells of Al and In treated rats. Impairments were observed in the endoplasmic reticulum and mitochondria and many vacuoles were identified in the cells cytoplasm. Our results concluded that lysosomes of Leydig and Sertoli cells, principal epididymis, and seminal vesicle cells as well as liver cells, played a central role in the extraction and concentration of Al and In under insoluble form after their introduction into the body as a soluble route. This mechanism intended to protect the organism against exogenous toxic and non-recognized mineral elements after their intrusion into the body. CONCLUSION: It looks important to proceed with the study of Al and In impact on the endocrine and exocrine functions of the male rat reproductive system.

A zero-valent iron and zeolite filter for nitrate recycling from agricultural drainage water.

Nitrate reduction to ammonium followed by ammonium capture and reuse, represent a new pathway to recycle nitrogen, prevent eutrophication, and to save energy used for industrial ammonium production. The present study investigates the principle of nitrogen recycling to agricultural drainage water using a coupled zero-valent iron (ZVI) and zeolite-based filter column system tested in laboratory and field continuous-flow experiments. A 40-day laboratory test showed 82% nitrate removal, of which 70% was converted to ammonium. In the following pilot scale field test, a total of 59.2 m3 (1700 pore volumes) drainage water with a nitrate concentration of 2-8 mg L-1 NO3--N was filtrated. An oxidizing unit inserted after the ZVI unit removed iron(II) and optimized ammonium retention in the zeolite unit. Nitrate removal efficiency was 94% for the entire 56-day period with a slight pH increase (pH 8.9). All ammonium produced was retained by the zeolite unit. Formation of green rust carbonate (layered FeII-FeIII-hydroxide) was observed on ZVI particle surfaces, which may increase the redox capacity of the filter system by up to 50% and contribute to its cost-efficiency. Moreover, all phosphate in the influent waters with concentrations between 0.1 and 0.5 mg L-1 was retained due to sorption by iron oxides in the system. Corrosion products formed cause partial filter clogging and should be removed by regular cleaning and backflushing. In conclusion, the ZVI - zeolite coupled filter system serves as a promising and cost-effective technology for nutrient removal and ammonium retention from agricultural drainage water.

Silica Coating of Ferromagnetic Iron Oxide Magnetic Nanoparticles Significantly Enhances Their Hyperthermia Performances for Efficiently Inducing Cancer Cells Death In Vitro.

Increasing the biocompatibility, cellular uptake, and magnetic heating performance of ferromagnetic iron-oxide magnetic nanoparticles (F-MNPs) is clearly required to efficiently induce apoptosis of cancer cells by magnetic hyperthermia (MH). Thus, F-MNPs were coated with silica layers of different thicknesses via a reverse microemulsion method, and their morphological, structural, and magnetic properties were evaluated by multiple techniques. The presence of a SiO2 layer significantly increased the colloidal stability of F-MNPs, which also enhanced their heating performance in water with almost 1000 W/gFe as compared to bare F-MNPs. The silica-coated F-MNPs exhibited biocompatibility of up to 250 µg/cm2 as assessed by Alamar Blues and Neutral Red assays on two cancer cell lines and one normal cell line. The cancer cells were found to internalize a higher quantity of silica-coated F-MNPs, in large endosomes, dispersed in the cytoplasm or inside lysosomes, and hence were more sensitive to in vitro MH treatment compared to the normal ones. Cellular death of more than 50% of the malignant cells was reached starting at a dose of 31.25 µg/cm2 and an amplitude of alternating magnetic field of 30 kA/m at 355 kHz.