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A review on planar printed structures that are based on Matryoshka-like geometries is presented. These structures use the well-known principle of Matryoshka dolls that are successively nested inside each other. The well-known advantages of the planar printed technology and of the meandered nested
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A review on planar printed structures that are based on Matryoshka-like geometries is presented. These structures use the well-known principle of Matryoshka dolls that are successively nested inside each other. The well-known advantages of the planar printed technology and of the meandered nested Matryoshka geometries are combined to generate miniaturized, multi-resonance, and/or wideband configurations. Both metal and complementary slot structures are considered. Closed and open configurations were analyzed. The working principles were explored in order to obtain physical insight into their behavior. Low-cost and single-layer applications as frequency-selective surfaces, filters, antennas, and sensors, in the microwave frequency region, were reviewed. Potential future research perspectives and new applications are then discussed.
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We analyze smooth nonlinear mappings for Hilbert and Banach spaces that carry small balls to convex sets, provided that the radii of the balls are small enough. We focus on the study of new and mildly sufficient conditions for the nonlinear mapping of
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We analyze smooth nonlinear mappings for Hilbert and Banach spaces that carry small balls to convex sets, provided that the radii of the balls are small enough. We focus on the study of new and mildly sufficient conditions for the nonlinear mapping of Hilbert and Banach spaces to be locally convex, and address a suitably reformulated local convexity problem analyzed within the Leray–Schauder homotopy method approach for Hilbert spaces, and within the Lipschitz smoothness condition for both Hilbert and Banach spaces. Some of the results presented in this work prove to be interesting and novel, even for finite-dimensional problems. Open problems related to the local convexity property for nonlinear mappings of Banach spaces are also formulated.
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The main focus of this paper is the derivation of the structural properties of the test channels of Wyner’s operational information rate distortion function (RDF), , for arbitrary abstract sources and, subsequently, the derivation of additional properties
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The main focus of this paper is the derivation of the structural properties of the test channels of Wyner’s operational information rate distortion function (RDF), , for arbitrary abstract sources and, subsequently, the derivation of additional properties for a tuple of multivariate correlated, jointly independent, and identically distributed Gaussian random variables, , , , with average mean-square error at the decoder and the side information, , available only at the decoder. For the tuple of multivariate correlated Gaussian sources, we construct optimal test channel realizations which achieve the informational RDF, , where is the set of auxiliary RVs Z such that , , and . We show the following fundamental structural properties: (1) Optimal test channel realizations that achieve the RDF and satisfy conditional independence, (2) Similarly, for the conditional RDF, , when the side information is available to both the encoder and the decoder, we show the equality . (3) We derive the water-filling solution for .
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The medical sciences are facing a major problem with the auto-detection of disease due to the fast growth in population density. Intelligent systems assist medical professionals in early disease detection and also help to provide consistent treatment that reduces the mortality rate. Skin
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The medical sciences are facing a major problem with the auto-detection of disease due to the fast growth in population density. Intelligent systems assist medical professionals in early disease detection and also help to provide consistent treatment that reduces the mortality rate. Skin cancer is considered to be the deadliest and most severe kind of cancer. Medical professionals utilize dermoscopy images to make a manual diagnosis of skin cancer. This method is labor-intensive and time-consuming and demands a considerable level of expertise. Automated detection methods are necessary for the early detection of skin cancer. The occurrence of hair and air bubbles in dermoscopic images affects the diagnosis of skin cancer. This research aims to classify eight different types of skin cancer, namely actinic keratosis (AKs), dermatofibroma (DFa), melanoma (MELa), basal cell carcinoma (BCCa), squamous cell carcinoma (SCCa), melanocytic nevus (MNi), vascular lesion (VASn), and benign keratosis (BKs). In this study, we propose SNC_Net, which integrates features derived from dermoscopic images through deep learning (DL) models and handcrafted (HC) feature extraction methods with the aim of improving the performance of the classifier. A convolutional neural network (CNN) is employed for classification. Dermoscopy images from the publicly accessible ISIC 2019 dataset for skin cancer detection is utilized to train and validate the model. The performance of the proposed model is compared with four baseline models, namely EfficientNetB0 (B1), MobileNetV2 (B2), DenseNet-121 (B3), and ResNet-101 (B4), and six state-of-the-art (SOTA) classifiers. With an accuracy of 97.81%, a precision of 98.31%, a recall of 97.89%, and an F1 score of 98.10%, the proposed model outperformed the SOTA classifiers as well as the four baseline models. Moreover, an Ablation study is also performed on the proposed method to validate its performance. The proposed method therefore assists dermatologists and other medical professionals in early skin cancer detection.
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With the increasingly strict limitations on emission standards of vehicles, deep desulfurization in fuel is indispensable for social development worldwide. In this study, a series of hybrid materials based on SiO2-supported polyoxometalate ionic liquid were successfully prepared via a facile ball
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With the increasingly strict limitations on emission standards of vehicles, deep desulfurization in fuel is indispensable for social development worldwide. In this study, a series of hybrid materials based on SiO2-supported polyoxometalate ionic liquid were successfully prepared via a facile ball milling method and employed as catalysts in the aerobic oxidative desulfurization process. The composition and structure of prepared samples were studied by various techniques, including FT-IR, UV-vis DRS, wide-angle XRD, BET, XPS, and SEM images. The experimental results indicated that the synthesized polyoxometalate ionic liquids were successfully loaded on SiO2 with a highly uniform dispersion. The prepared catalyst (C16PMoV/10SiO2) exhibited good desulfurization activity on different sulfur compounds. Moreover, the oxidation product and active species in the ODS process were respectively investigated via GC-MS and ESR analysis, indicating that the catalyst can activate oxygen to superoxide radicals during the reaction to convert DBT to its corresponding sulfone in the fuel.
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The incidence and prevalence of cardiac and cerebrovascular diseases are constantly increasing, with chronic coronary syndrome and ischemic stroke as the leading causes of morbidity and mortality worldwide. According to current knowledge, the heart–brain axis is more than a theoretical concept, with many
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The incidence and prevalence of cardiac and cerebrovascular diseases are constantly increasing, with chronic coronary syndrome and ischemic stroke as the leading causes of morbidity and mortality worldwide. According to current knowledge, the heart–brain axis is more than a theoretical concept, with many common pathophysiological mechanisms involved in the onset and evolution of both coronary and cerebral ischemia. Moreover, the focus is on the prevention and early intervention of risk factors in searching for targeted and personalized medical treatment. In this context, this narrative review aims to offer, in a didactic and practice-oriented manner, an up-to-date overview of the role played by lipid-derived biomarkers (from low-density lipoprotein cholesterol to oxylipin and apolipoproteins) in chronic coronary syndrome and ischemic stroke. Firstly, the authors highlight, via relevant epidemiological data, the significant burden of chronic coronary syndrome and ischemic stroke in the general population, thus explaining the need for updated information on this topic. Subsequently, the most important lipid-derived biomarkers and their multiple roles in the pathogenesis of these two disorders are listed. Currently available and experimental targeted therapies based on these lipid-derived biomarkers are presented in the final part of this paper, representing this manuscript’s original and novel input.
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Experience-based methods like reinforcement learning (RL) are often deemed less suitable for the safety field due to concerns about potential safety issues. To bridge this gap, we introduce STPA-RL, a methodology that integrates RL with System-Theoretic Process Analysis (STPA). STPA is a safety
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Experience-based methods like reinforcement learning (RL) are often deemed less suitable for the safety field due to concerns about potential safety issues. To bridge this gap, we introduce STPA-RL, a methodology that integrates RL with System-Theoretic Process Analysis (STPA). STPA is a safety analysis technique that identifies causative factors leading to unsafe control actions and system hazards through loss scenarios. In the context of STPA-RL, we formalize the Markov Decision Process based on STPA analysis results to incorporate control algorithms into the system environment. The agent learns safe actions through reward-based learning, tracking potential hazard paths to validate system safety. Specifically, by analyzing various loss scenarios related to the Platform Screen Door, we assess the applicability of the proposed approach by evaluating hazard trajectory graphs and hazard frequencies in the system. This paper streamlines the RL process for loss scenario identification through STPA, contributing to self-guided loss scenarios and diverse system modeling. Additionally, it offers effective simulations for proactive development to enhance system safety and provide practical assistance in the safety field.
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The concentration of viruses in sewage sludge is significantly higher (10–1000-fold) than that found in natural environments, posing a potential risk for human and animal health. However, the composition of these viruses and their role in the transfer of pathogenic factors, as well
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The concentration of viruses in sewage sludge is significantly higher (10–1000-fold) than that found in natural environments, posing a potential risk for human and animal health. However, the composition of these viruses and their role in the transfer of pathogenic factors, as well as their role in the carbon, nitrogen, and phosphorus cycles remain poorly understood. In this study, we employed a shotgun metagenomic approach to investigate the pathogenic bacteria and viral composition and function in two wastewater treatment plants located on a campus. Our analysis revealed the presence of 1334 amplicon sequence variants (ASVs) across six sludge samples, with 242 ASVs (41.22% of total reads) identified as pathogenic bacteria. Arcobacter was found to be the most dominant pathogen accounting for 6.79% of total reads. The virome analysis identified 613 viral genera with Aorunvirus being the most abundant genus at 41.85%. Approximately 0.66% of these viruses were associated with human and animal diseases. More than 60% of the virome consisted of lytic phages. Host prediction analysis revealed that the phages primarily infected Lactobacillus (37.11%), Streptococcus (21.11%), and Staphylococcus (7.11%). Furthermore, our investigation revealed an abundance of auxiliary metabolic genes (AMGs) involved in carbon, nitrogen, and phosphorus cycling within the virome. We also detected a total of 113 antibiotic resistance genes (ARGs), covering major classes of antibiotics across all samples analyzed. Additionally, our findings indicated the presence of virulence factors including the clpP gene accounting for approximately 4.78%, along with toxin genes such as the RecT gene representing approximately 73.48% of all detected virulence factors and toxin genes among all samples analyzed. This study expands our understanding regarding both pathogenic bacteria and viruses present within sewage sludge while providing valuable insights into their ecological functions.
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The aim of this study was to observe the outcomes of newborn screening (NBS) in a certain population by using next-generation sequencing (NGS) as a first-tier screening test combined with tandem mass spectrometry (MS/MS). We performed a multicenter study of 29,601 newborns from
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The aim of this study was to observe the outcomes of newborn screening (NBS) in a certain population by using next-generation sequencing (NGS) as a first-tier screening test combined with tandem mass spectrometry (MS/MS). We performed a multicenter study of 29,601 newborns from eight screening centers with NBS via NGS combined with MS/MS. A custom-designed panel targeting the coding region of the 142 genes of 128 inborn errors of metabolism (IEMs) was applied as a first-tier screening test, and expanded NBS using MS/MS was executed simultaneously. In total, 52 genes associated with the 38 IEMs screened by MS/MS were analyzed. The NBS performance of these two methods was analyzed and compared respectively. A total of 23 IEMs were diagnosed via NGS combined with MS/MS. The incidence of IEMs was approximately 1 in 1287 patients. Within separate statistical analyses, the positive predictive value (PPV) for MS/MS was 5.29%, and the sensitivity was 91.3%. However, for genetic screening alone, the PPV for NGS was 70.83%, with 73.91% sensitivity. The three most common IEMs were methylmalonic academia (MMA), primary carnitine deficiency (PCD) and phenylketonuria (PKU). The five genes with the most common carrier frequencies were PAH (1:42), PRODH (1:51), MMACHC (1:52), SLC25A13 (1:55) and SLC22A5 (1:63). Our study showed that NBS combined with NGS and MS/MS improves the performance of screening methods, optimizes the process, and provides accurate diagnoses.
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Microorganisms carrying antimicrobial resistance genes are often found in greywater. As the reuse of greywater becomes increasingly needed, it is imperative to determine how greywater treatment impacts antimicrobial resistance genes (ARGs). Using qPCR and SmartChip™ qPCR, we characterized ARG patterns in greywater microbial
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Microorganisms carrying antimicrobial resistance genes are often found in greywater. As the reuse of greywater becomes increasingly needed, it is imperative to determine how greywater treatment impacts antimicrobial resistance genes (ARGs). Using qPCR and SmartChip™ qPCR, we characterized ARG patterns in greywater microbial communities before, during, and after treatment by a recirculating vertical flow constructed wetland. In parallel, we examined the impact of greywater-treated irrigation on soil, including the occurrence of emerging micropollutants and the taxonomic and ARG compositions of microbial communities. Most ARGs in raw greywater are removed efficiently during the winter season, while some ARGs in the effluents increase in summer. SmartChip™ qPCR revealed the presence of ARGs, such as tetracycline and beta-lactam resistance genes, in both raw and treated greywater, but most abundantly in the filter bed. It also showed that aminoglycoside and vancomycin gene abundances significantly increased after treatment. In the irrigated soil, the type of water (potable or treated greywater) had no specific impact on the total bacterial abundance (16S rRNA gene). No overlapping ARGs were found between treated greywater and greywater-irrigated soil. This study indicates ARG abundance and richness increased after treatment, possibly due to the concentration effects of the filter beds.
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In recent decades, advancements in medical imaging technologies have revolutionized diagnostic and therapeutic approaches, enhancing the precision and efficacy of healthcare interventions [...]
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In this review, an overview was given of the mutual interactions between nematodes and fungi of the genus Trichoderma sp. due to the potential of these fungi to protect plant roots from plant-parasitic nematodes on the one hand and the influence of nematodes
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In this review, an overview was given of the mutual interactions between nematodes and fungi of the genus Trichoderma sp. due to the potential of these fungi to protect plant roots from plant-parasitic nematodes on the one hand and the influence of nematodes (fungivores) on the efficacy of the fungus on the other. In addition, an overview of the advantages of Trichoderma sp. for agricultural production was given. The basis of sustainable agricultural production is the healthy functioning of the soil ecosystem. The diversity of organisms—bacteria, protozoa, algae, metazoans (nematodes) and fungi—improves the quality and performance of the soil by maintaining biological productivity. Root exudates in the rhizosphere support microbial communities that play a key role in regulating the dynamics of organic matter decomposition and the availability of plant nutrients. The microbial activity of organisms in the soil is interconnected and interacts to form a soil food web that reflects the condition, function and health of the soil. The energy in food webs flows through trophic chains of consumers, which are divided into energy channels. Root, bacterial and fungal channels increase soil biomass, carbon (C) and energy flow through the soil food web. The structure of the nematode community is an effective tool for the biological assessment of soil quality. This is due to a number of characteristics that nematodes have, including the following: a great diversity of species, the possibility of subdivision according to different criteria such as trophic groups and c-p groups, the duration of reproduction, the ease of sampling, the identification of genera and preservation, etc. Nematodes are involved in various ecological functions in the soil, of which the interaction between them and fungi is based on antagonism or mutualism, which is the basis for a better understanding of their impact on the ecosystem. Fungi of the genus Trichoderma sp. are successful colonizers of all habitats, secondary opportunists and fast growing.
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Xiao Y. Tong, Hussain Hussain, Nagarajarao Shamaladevi, Michael D. Norenberg, Aya Fadel, Omar El Hiba, El got Abdeljalil, El-Mansoury Bilal, Deepak Kempuraj, Sampath Natarajan, Andrew V. Schally, Miklos Jaszberenyi, Luis Salgueiro, Michael J. Paidas and Arumugam R. Jayakumar
Biology2024, 13(4), 228; https://doi.org/10.3390/biology13040228 (registering DOI) - 29 Mar 2024
Hepatic encephalopathy (HE) is a neurological condition linked to liver failure. Acute HE (Type A) occurs with acute liver failure, while chronic HE (Type C) is tied to cirrhosis and portal hypertension. HE treatments lag due to gaps in understanding its development by
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Hepatic encephalopathy (HE) is a neurological condition linked to liver failure. Acute HE (Type A) occurs with acute liver failure, while chronic HE (Type C) is tied to cirrhosis and portal hypertension. HE treatments lag due to gaps in understanding its development by gender and age. We studied how sex and age impact HE and its severity with combined liver toxins. Our findings indicate that drug-induced (thioacetamide, TAA) brain edema was more severe in aged males than in young males or young/aged female rats. However, adding alcohol (ethanol, EtOH) worsens TAA’s brain edema in both young and aged females, with females experiencing a more severe effect than males. These patterns also apply to Type A HE induced by azoxymethane (AZO) in mice. Similarly, TAA-induced behavioral deficits in Type C HE were milder in young and aged females than in males. Conversely, EtOH and TAA in young/aged males led to severe brain edema and fatality without noticeable behavioral changes. TAA metabolism was slower in aged males than in young or middle-aged rats. When TAA-treated aged male rats received EtOH, there was a slow and sustained plasma level of thioacetamide sulfoxide (TASO). This suggests that with EtOH, TAA-induced HE is more severe in aged males. TAA metabolism was similar in young, middle-aged, and aged female rats. However, with EtOH, young and aged females experience more severe drug-induced HE as compared to middle-aged adult rats. These findings strongly suggest that gender and age play a role in the severity of HE development and that the presence of one or more liver toxins may aggravate the severity of the disease progression.
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Introduction: Hyperbaric oxygen therapy (HBOT) is one of the treatment methods in patients with sudden sensorineural hearing loss (SSNHL). It is recommended as an elective treatment in patients undergoing steroid therapy. According to current scientific reports, HBOT should be implemented within two weeks
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Introduction: Hyperbaric oxygen therapy (HBOT) is one of the treatment methods in patients with sudden sensorineural hearing loss (SSNHL). It is recommended as an elective treatment in patients undergoing steroid therapy. According to current scientific reports, HBOT should be implemented within two weeks after the first symptoms. However, as far as the profile of HBOT is concerned, there are no straightforward recommendations. Methods: The data obtained from the medical records of 218 patients undergoing HBOT for SSNHL at the Military Institute of Medicine—National Research Institute were analyzed statistically for the impact of the duration and the delay in implementing HBOT on the end results of pure-tone audiometry (PTA). Results: A statistically significant hearing improvement in patients undergoing more than 15 cycles of HBOT was detected at all frequencies except for 1500 Hz; in the group reporting for treatment with a delay of more than 10 days, hearing improvement was statistically unsignificant at frequencies of 1500, 3000, and 4000 Hz. Conclusions: The statistical analysis showed that the urgent onset of HBOT could be a significant factor in the therapy of SSNHL.
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Many methods have been developed to detect and predict the fracture properties of fractured rocks. The standard data sources for fracture evaluations are image logs and core samples. However, many wells do not have these data, especially for old wells. Furthermore, operating both
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Many methods have been developed to detect and predict the fracture properties of fractured rocks. The standard data sources for fracture evaluations are image logs and core samples. However, many wells do not have these data, especially for old wells. Furthermore, operating both methods can be costly, and, sometimes, the data gathered are of bad quality. Therefore, previous research attempted to evaluate fractures indirectly using the widely available conventional well-logs. Sedimentary rocks are widespread and have been studied in the literature. However, fractured reservoirs, like igneous and metamorphic rock bodies, may also be vital since they provide fluid migration pathways and can store some hydrocarbons. Hence, two fractured metamorphic rock bodies are studied in this study to evaluate any difference in fracture responses on well-log properties. Also, a quick and reliable prediction method is studied to predict fracture density (FD) in the case of the unavailability of image logs and core samples. Gene expression programming (GEP) was chosen for this study to predict FD, and ten conventional well-log data were used as input variables. The model produced by GEP was good, with R2 values at least above 0.84 for all studied wells, and the model was then applied to wells without image logs. Both selected metamorphic rocks showed similar results in which the significant parameters to predict FD were the spectral gamma ray, resistivity, and porosity logs. This study also proposed a validation method to ensure that the FD value predictions were consistent using discriminant function analysis. In conclusion, the GEP method is reliable and could be used for FD predictions for basement metamorphic rocks.
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Classifying the flow subsequences of sensor networks is an effective way for fault detection in the Industrial Internet of Things (IIoT). Traditional fault detection algorithms identify exceptions by a single abnormal dataset and do not pay attention to the factors such as electromagnetic
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Classifying the flow subsequences of sensor networks is an effective way for fault detection in the Industrial Internet of Things (IIoT). Traditional fault detection algorithms identify exceptions by a single abnormal dataset and do not pay attention to the factors such as electromagnetic interference, network delay, sensor sample delay, and so on. This paper focuses on fault detection by continuous abnormal points. We proposed a fault detection algorithm within the module of sequence state generated by unsupervised learning (SSGBUL) and the module of integrated encoding sequence classification (IESC). Firstly, we built a network module based on unsupervised learning to encode the flow sequence of the different network cards in the IIoT gateway, and then combined the multiple code sequences into one integrated sequence. Next, we classified the integrated sequence by comparing the integrated sequence with the encoding fault type. The results obtained from the three IIoT datasets of a sewage treatment plant show that the accuracy of the SSGBUL–IESC algorithm exceeds 90% with subsequence length 10, which is significantly higher than the accuracies of the dynamic time warping (DTW) algorithm and the time series forest (TSF) algorithm. The proposed algorithm reaches the classification requirements for fault detection for the IIoT.
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Understanding the structure and function of intermediate filaments (IFs) is necessary in order to explain why more than 70 related IF genes have evolved in vertebrates while maintaining such dramatically tissue-specific expression. Desmin is a member of the large multigene family of IF
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Understanding the structure and function of intermediate filaments (IFs) is necessary in order to explain why more than 70 related IF genes have evolved in vertebrates while maintaining such dramatically tissue-specific expression. Desmin is a member of the large multigene family of IF proteins and is specifically expressed in myocytes. In an effort to elucidate its muscle-specific behavior, we have used a yeast two-hybrid system in order to identify desmin’s head binding partners. We described a mitochondrial and a lysosomal protein, NADH ubiquinone oxidoreductase core subunit S2 (NDUFS2), and saposin D, respectively, as direct desmin binding partners. In silico analysis indicated that both interactions at the atomic level occur in a very similar way, by the formation of a three-helix bundle with hydrophobic interactions in the interdomain space and hydrogen bonds at R16 and S32 of the desmin head domain. The interactions, confirmed also by GST pull-down assays, indicating the necessity of the desmin head domain and, furthermore, point out its role in function of mitochondria and lysosomes, organelles which are disrupted in myopathies due to desmin head domain mutations.
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Roberto Caruana, Maria Grazia Zizzo, Gaetano Felice Caldara, Francesco Montalbano, Silvia Fasciano, Dora Arena, Marida Salamone, Gaetano Di Fazio, Alessandro Bottino and Mariano Licciardi
Int. J. Mol. Sci.2024, 25(7), 3852; https://doi.org/10.3390/ijms25073852 (registering DOI) - 29 Mar 2024
In this study, a new micro delivery system based on an anionic methacrylate copolymer, able to improve the biological response of myo-inositol by daily oral administration, was manufactured by spray-drying. It has an ideal dose form for oral administration, with an experimental drug
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In this study, a new micro delivery system based on an anionic methacrylate copolymer, able to improve the biological response of myo-inositol by daily oral administration, was manufactured by spray-drying. It has an ideal dose form for oral administration, with an experimental drug loading (DL)% of 14% and a regulated particle size of less than 15 µm. The new formulation features an improvement on traditional formulations used as a chronic therapy for the treatment of polycystic ovary syndrome. The microparticles’ release profile was studied and ex vivo porcine intestinal mucosa permeation experiments were performed to predict potential improvements in oral absorption. Batch n. 3, with the higher Eudragit/MI weight ratio (ratio = 6), showed the best-modified release profiles of the active ingredient, ensuring the lowest myo-inositol loss in an acidic environment. The in vivo evaluation of the myo-inositol micro delivery system was carried out in a rat animal model to demonstrate that the bioavailability of myo-inositol was increased when compared to the administration of the same dosage of the pure active ingredient. The AUC and Cmax of the loaded active molecule in the micro delivery system was improved by a minimum of 1.5 times when compared with the pure substance, administered with same dosage and route. Finally, the increase of myo-inositol levels in the ovary follicles was assessed to confirm that a daily administration of the new formulation improves myo-inositol concentration at the site of action, resulting in an improvement of about 1.25 times for the single administration and 1.66 times after 7 days of repeated administration when compared to pure MI.
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Deoxynivalenol (DON), primarily generated by Fusarium species, often exists in agricultural products. It can be transformed to 3-epi-deoxynivalenol (3-epi-DON), with a relatively low toxicity, via two steps. DDH in Pelagibacterium halotolerans ANSP101 was proved to convert DON to 3-keto-deoxynivalenol
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Deoxynivalenol (DON), primarily generated by Fusarium species, often exists in agricultural products. It can be transformed to 3-epi-deoxynivalenol (3-epi-DON), with a relatively low toxicity, via two steps. DDH in Pelagibacterium halotolerans ANSP101 was proved to convert DON to 3-keto-deoxynivalenol (3-keto-DON). In the present research, AKR4, a NADPH-dependent aldo/keto reductase from P. halotolerans ANSP101, was identified to be capable of converting 3-keto-DON into 3-epi-DON. Our results demonstrated that AKR4 is clearly a NADPH-dependent enzyme, for its utilization of NADPH is higher than that of NADH. AKR4 functions at a range of pH 5–10 and temperatures of 20–60 °C. AKR4 is able to degrade 89% of 3-keto-DON in 90 min at pH 7 and 50 °C with NADPH as the cofactor. The discovery of AKR4, serving as an enzyme involved in the final step in DON degradation, might provide an option for the final detoxification of DON in food and feed.
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In the past 30 years, there have been numerous positive body image and eating disorder prevention programs targeting youth developed for school-based settings. Frequently, teachers are used as interventionists to increase dissemination, decrease costs relative to researchers, and increase scalability. However, little is
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In the past 30 years, there have been numerous positive body image and eating disorder prevention programs targeting youth developed for school-based settings. Frequently, teachers are used as interventionists to increase dissemination, decrease costs relative to researchers, and increase scalability. However, little is known about teacher concerns and barriers that may hinder successful uptake and implementation. The current study recruited a total of 269 teachers who consented to implement a universal body image and appearance-related bullying and teasing prevention program in their classrooms as part of a randomized controlled trial. Teachers expressed some worry that they may say the wrong thing, and concern about feeling uncomfortable teaching the program due to their own body dissatisfaction. Teacher’s ethnicity, gender, years teaching, dieting behaviors and other weight control behaviors, and self-efficacy were not associated with concerns related to teaching the curriculum. Teachers with lower body esteem reported higher concerns and anxiety related to teaching a body image curriculum. In free response items, teachers worried about handling student comments that were beyond the scope of the curriculum. Teacher self-efficacy was the only variable associated with the number of program sessions implemented. Findings suggest avenues to increase implementation.
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Long-term variations in population structure, growth, mortality, exploitation rate, and recruitment pattern of two major commercial small pelagic fishes (CSPFs) (Decapterus maruadsi and Trachurus japonicus) are reported based on bottom trawl survey data collected during 2006–2020 in the Beibu Gulf, South
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Long-term variations in population structure, growth, mortality, exploitation rate, and recruitment pattern of two major commercial small pelagic fishes (CSPFs) (Decapterus maruadsi and Trachurus japonicus) are reported based on bottom trawl survey data collected during 2006–2020 in the Beibu Gulf, South China Sea. All individuals collected during each sampling quarter over a period of 15 years were subjected to laboratory-based analysis. In this study, the stock of D. maruadsi and T. japonicus inhabiting the Beibu Gulf was assessed using length-based methods (bootstrapped electronic length frequency analysis (ELEFAN)) to complete stock assessment in different fishery management periods (the division of fisheries management periods was based on China’s input and output in the South China Sea offshore fisheries over 15 years, specifically divided into period I (2006–2010), period II (2011–2015), and period III (2016–2020)). The results showed that the mean body length, dominant body size, and estimated asymptotic length of two CSPFs decreased, whereas their growth coefficient decreased, indicating miniaturization and slower growth, respectively. Estimated exploitation rates and catching body length for two CSPFs indicated that both stocks in the Beibu Gulf were overexploited in period I and moderately exploited after 2011. These stocks were taking a good turn in status in period III, with the exploitation rate much lower than the initial period and reversing the downward trend in catching body length. Furthermore, the variations in the spawning season of the two CSPF stocks and their barely satisfactory expected yield indicated the complexity of the current fishery management in the Beibu Gulf. These results suggest that management measures to reduce fishing pressure may have a positive influence on the biological characteristics of those CSPFs in the Beibu Gulf; however, the stock structure already affected by overfishing will be a huge challenge for the conservation and restoration of fisheries resources in the future. Given that the current stocks of D. maruadsi and T. japonicus in the Beibu Gulf still have low first-capture body length (Lc) and high fishing mortality (F) (compared to F0.1), we identify a need to refine population structure by controlling fishing efforts and increasing catchable size, and more consideration should be given to the local fishery resource status in fisheries management.
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Linda Skibsted Kornerup, Mikkel Andreassen, Ulrich Knigge, Anne Kirstine Arveschoug, Per Løgstup Poulsen, Andreas Kjær, Peter Sandor Oturai, Henning Grønbæk and Gitte Dam
Cancers2024, 16(7), 1349; https://doi.org/10.3390/cancers16071349 (registering DOI) - 29 Mar 2024
Introduction: Pheochromocytomas and paragangliomas are rare neuroendocrine tumours that originate from chromaffin cells within the adrenal medulla or extra-adrenal sympathetic ganglia. Management of disseminated or metastatic pheochromocytomas and paragangliomas continues to pose challenges and relies on limited evidence. Method: In this study, we
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Introduction: Pheochromocytomas and paragangliomas are rare neuroendocrine tumours that originate from chromaffin cells within the adrenal medulla or extra-adrenal sympathetic ganglia. Management of disseminated or metastatic pheochromocytomas and paragangliomas continues to pose challenges and relies on limited evidence. Method: In this study, we report retrospective data on median overall survival (OS) and median progression-free survival (PFS) for all Danish patients treated with peptide receptor radionuclide therapy (PRRT) with 177Lu-Dotatate or 90Y-Dotatate over the past 15 years. One standard treatment of PRRT consisted of 4 consecutive cycles with 8–14-week intervals. Results: We included 28 patients; 10 were diagnosed with pheochromocytoma and 18 with paraganglioma. Median age at first PRRT was 47 (IQR 15–76) years. The median follow-up time was 31 (IQR 17–37) months. Eight patients died during follow-up. Median OS was 72 months, and 5-year survival was 65% with no difference between pheochromocytoma and paraganglioma. Patients with germline mutations had better survival than patients without mutations (p = 0.041). Median PFS after the first cycle of PRRT was 30 months. For patients who previously received systemic treatment, the median PFS was 19 months, compared with 32 months for patients with no previous systemic treatment (p = 0.083). Conclusions: The median OS of around 6 years and median PFS of around 2.5 years found in this study are comparable to those reported in previous studies employing PRRT. Based on historical data, the efficacy of PRRT may be superior to 131I-MIBG therapy, and targeted therapy with sunitinib and PRRT might therefore be considered as first-line treatment in this patient group.
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The thermal protection system (TPS) represents one of the most critical subsystems for vehicle re-entry. However, due to uncertainties in thermal loads, material properties, and manufacturing deviations, the thermal response of the TPS exhibits significant randomness, posing considerable challenges in engineering design and
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The thermal protection system (TPS) represents one of the most critical subsystems for vehicle re-entry. However, due to uncertainties in thermal loads, material properties, and manufacturing deviations, the thermal response of the TPS exhibits significant randomness, posing considerable challenges in engineering design and reliability assessment. Given that uncertain aerodynamic heating loads manifest as a stochastic field over time, conventional surrogate models, typically accepting scalar random variables as inputs, face limitations in modeling them. Consequently, this paper introduces an effective characterization approach utilizing proper orthogonal decomposition (POD) to represent the uncertainties of aerodynamic heating. The augmented snapshots matrix is used to reduce the dimension of the random field by the decoupling method of independently spatial and temporal bases. The random variables describing material properties and geometric thickness are also employed as inputs for probabilistic analyses. An uncoupled POD Gaussian process regression (UPOD-GPR) model is then established to achieve highly accurate solutions for transient heat conduction. The model takes random heat flux fields as inputs and thermal response fields as outputs. Using a typical multi-layer TPS and thermal structure as two examples, probabilistic analyses are conducted. The mean square relative error of a typical multi-layer TPS is less than 4%. For the thermal structure, the averaged absolute error of the radiation and insulation layer is less than 25 C and 6 C when the maximum reaches 1200 C and 150 C, respectively. This approach can provide accurate and rapid predictions of thermal responses for TPS and thermal structures throughout their entire operating time when furnished with input heat flux fields and structural parameters.
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