Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Copper and Selenium Supplementation on the Level of Elements in Rats’ Femurs under Neoplastic Conditions

A study was conducted to determine the effect of long-term supplementation with selenium and copper, administered at twice the level used in the standard diet of rats, on the content of selected elements in the femoral bones of healthy rats and rats with implanted LNCaP cancer cells. After an adaptation period, the animals were randomly divided into two experimental groups. The rats in the experimental group were implanted with prostate cancer cells. The rats in the control group were kept in the same conditions as those in the experimental group and fed the same diet, but without implanted cancer cells. The cancer cells (LNCaP) were intraperitoneally implanted in the amount of 1 × 106 (in PBS 0.4 mL) at the age of 90 days. The content of elements in the samples was determined by a quadrupole mass spectrometer with inductively coupled plasma ionization (ICP-MS). In the femoral bones of rats with implanted LNCaP cells, in the case of the standard diet and the copper-enriched diet, there was a marked decreasing trend in the content of the analysed elements relative to the control rats. This may indicate slow osteolysis taking place in the bone tissue. Contrasting results were obtained for the diet enriched with selenium; there was no significant reduction in the level of these elements, and there was even an increase in the concentrations of Fe and K in the bones of rats with implanted LNCaP cells. Particularly, numerous changes in the mineral composition of the bones were generated by enriching the diet with copper. The elements that most often underwent changes (losses) in the bones were cobalt, iron, manganese and molybdenum. The changes observed, most likely induced by the implantation of LNCaP cells, may indicate a disturbance of mineral homeostasis.
Identification of a Steroid Hormone-Associated Gene Signature Predicting the Prognosis of Prostate Cancer through an Integrative Bioinformatics Analysis

Simple Summary Prostate cancer (PC) is the second most common cancer worldwide and steroid hormone plays an important role in prostate carcinogenesis. Most patients with PC are initially sensitive to androgen deprivation therapy (ADT) but eventually become hormone refractory and reflect disease progression. The aim of the study was to investigate the genes which regulate the steroid hormone functional pathways and associate with the disease progression of PC. We identified a panel of eight-gene signatures that modulated steroid-hormone pathways and predicted the prognosis of PC using integrative bioinformatics analysis of multiple datasets validated from external cohorts. This panel could be used for predicting the prognosis of PC patients and might be associated with the drug response of hormonal therapies. Moreover, these genes in the signature could be potential targets to develop a novel treatment for castration-resistant PC therapy. Abstract The importance of anti-androgen therapy for prostate cancer (PC) has been well recognized. However, the mechanisms underlying prostate cancer resistance to anti-androgens are not completely understood. Therefore, identifying pharmacological targets in driving the development of castration-resistant PC is necessary. In the present study, we sought to identify core genes in regulating steroid hormone pathways and associating them with the disease progression of PC. The selection of steroid hormone-associated genes was identified from functional databases, including gene ontology, KEGG, and Reactome. The gene expression profiles and relevant clinical information of patients with PC were obtained from TCGA and used to examine the genes associated with steroid hormone. The machine-learning algorithm was performed for key feature selection and signature construction. With the integrative bioinformatics analysis, an eight-gene signature, including CA2, CYP2E1, HSD17B, SSTR3, SULT1E1, TUBB3, UCN, and UGT2B7 was established. Patients with higher expression of this gene signature had worse progression-free interval in both univariate and multivariate cox models adjusted for clinical variables. The expression of the gene signatures also showed the aggressiveness consistently in two external cohorts, PCS and PAM50. Our findings demonstrated a validated eight-gene signature could successfully predict PC prognosis and regulate the steroid hormone pathway.
Extracellular Vesicles as Signal Carriers in Malignant Thyroid Tumors?

Extracellular vesicles (EVs) are small, membranous structures involved in intercellular communication. Here, we analyzed the effects of thyroid cancer-derived EVs on the properties of normal thyroid cells and cells contributing to the tumor microenvironment. EVs isolated from thyroid cancer cell lines (CGTH, FTC-133, 8505c, TPC-1 and BcPAP) were used for treatment of normal thyroid cells (NTHY), as well as monocytes and endothelial cells (HUVEC). EVs’ size/number were analyzed by flow cytometry and confocal microscopy. Gene expression, protein level and localization were investigated by qRT-PCR, WB and ICC/IF, respectively. Proliferation, migration and tube formation were analyzed. When compared with NTHY, CGTH and BcPAP secreted significantly more EVs. Treatment of NTHY with cancer-derived EVs changed the expression of tetraspanin genes, but did not affect proliferation and migration. Cancer-derived EVs suppressed tube formation by endothelial cells and did not affect the phagocytic index of monocytes. The number of 6 μm size fraction of cancer-derived EVs correlated negatively with the CD63 and CD81 expression in NTHY cells, as well as positively with angiogenesis in vitro. Thyroid cancer-derived EVs can affect the expression of tetraspanins in normal thyroid cells. It is possible that 6 μm EVs contribute to the regulation of NTHY gene expression and angiogenesis.
Norovirus Genogroup II Epidemics and the Potential Effect of Climate Change on Norovirus Transmission in Taiwan

The activity of norovirus varies from season to season, and the effect of climate change on the incidence of norovirus outbreaks is a widely recognized yet poorly understood phenomenon. Investigation of the possible association between climatic factors and the incidence of norovirus is key to a better understanding of the epidemiology of norovirus and early prediction of norovirus outbreaks. In this study, clinical stool samples from acute gastroenteritis outbreaks were collected from January 2015 to June 2019 in Taiwan. Data analysis from our study indicated that more than half of the cases were reported in the winter and spring seasons, including those caused by norovirus of genotypes GII (genogroup II). 2, GII.3, GII.6, and GII.17, and 45.1% of the patients who tested positive for norovirus were infected by the GII.4 norovirus in autumn. However, GII.6 norovirus accounted for a higher proportion of the cases reported in summer than any other strain. Temperature is a crucial factor influencing patterns of epidemic outbreaks caused by distinct genotypes of norovirus. The results of this study may help experts predict and issue early public warnings of norovirus transmission and understand the effect of climate change on norovirus outbreaks caused by different genotypes and occurring in different locations.
Simulating mixed land-use change under multi-label concept by integrating a convolutional neural network and cellular automata: a case study of Huizhou, China

ABSTRACT Cellular automata (CA) model is a useful tool for simulating spatiotemporal changes of land-use evolution. However, previous CA models have usually ignored the inhomogeneous and mixed land-use situations and simplified the land grid cell as one single land-use type. This study developed a multi-label (ML) convolutional neural network CA (ML-CNN-CA) model to simulate the complex evolution of mixed land uses. The multi-label learning strategy in the proposed model can formulize mixed land uses by labeling multiple land-use types to each grid cell. The transition rules of CA were modified to accommodate the multi-label learning strategy and mined by coupling a CNN network and three interactive mechanisms, including the neighborhood effect, adaptive inertia coefficient, and random factor. The proposed ML-CNN-CA model was applied and examined in a fast-developing city (Huizhou) in the China’s Pearl River Delta region for the mixed land-use simulation during 2009–2013 and 2013–2020. The ML-CNN-CA model with different CNN architectures and a previous artificial neural network (ANN)-based multi-label CA model were also implemented for comparisons. Results show the capability of the ML-CNN-CA model to simulate fine-scale mixed land-use changes with satisfactory performances. Specifically, the simulated mixed land-use patterns agree well with the actual land uses from the morphological perspective. Furthermore, the quantitative assessments demonstrate the performance of the proposed model, showing an accuracy value of 0.912 for 2009–2013 and 0.896 for 2013–2020, and a hamming loss value of 0.048 for 2009–2013 and 0.055 for 2013–2020. The comparisons also show the best performance of the ML-CNN-CA model with the VGG-based architecture and significant outperformance of the proposed model against the previous ANN-based CA model. Multiple sensitivity analyses were also conducted to investigate the uncertainty of the proposed model. The ML-CNN-CA model proposed in this study can provide a new tool for better simulation of fine-scale mixed land-use changes and is expected to help formulate urban planning guidelines and achieve sustainable urban development.
Detection of TERT Promoter Mutations as a Prognostic Biomarker in Gliomas: Methodology, Prospects, and Advances

This article reviews the existing approaches to determining the TERT promoter mutational status in patients with various tumoral diseases of the central nervous system. The operational characteristics of the most common methods and their transferability in medical practice for the selection or monitoring of personalized treatments based on the TERT status and other related molecular biomarkers in patients with the most common tumors, such as glioblastoma, oligodendroglioma, and astrocytoma, are compared. The inclusion of new molecular markers in the course of CNS clinical management requires their rapid and reliable assessment. Availability of molecular evaluation of gliomas facilitates timely decisions regarding patient follow-up with the selection of the most appropriate treatment protocols. Significant progress in the inclusion of molecular biomarkers for their subsequent clinical application has been made since 2016 when the WHO CNS classification first used molecular markers to classify gliomas. In this review, we consider the methodological approaches used to determine mutations in the promoter region of the TERT gene in tumors of the central nervous system. In addition to classical molecular genetical methods, other methods for determining TERT mutations based on mass spectrometry, magnetic resonance imaging, next-generation sequencing, and nanopore sequencing are reviewed with an assessment of advantages and disadvantages. Beyond that, noninvasive diagnostic methods based on the determination of the mutational status of the TERT promoter are discussed.
Fractional Bandwidth up to 24% and Spurious Free SAW Filters on Bulk 15°YX-LiNbO3 Substrates Using Thickness-Modulated IDT Structures

To cope with ubiquitous wireless connectivity and the increased and faster data delivery in 5G communication, surface acoustic wave (SAW) filters are progressively requiring wider bandwidths. Conventional bulk 15°YX-LiNbO3 substrates with a large coupling coefficient (K2) are attractive for the low-cost mass production of wideband SAW filters, but these generally suffer from spurious responses, limiting their practical application. In this work, a novel and simple SAW configuration is proposed that uses thickness-modulated interdigital transducer (IDT) structures to overcome the limitations set by spurious responses. Different from the conventional design where the thicknesses of the IDT electrodes in the series and parallel resonators generally kept the same, the proposed configuration adopts IDT electrodes of different thicknesses in the series and shunt resonators to suppress or remove unwanted spurious Rayleigh modes from the filter passband. Two different ultra-wideband SAW filter designs employing thickness-modulated IDTs were designed and fabricated to validate the effective suppression of spurious modes. The SAW filters experimentally featured spurious-free responses in the passband as well as a large 3 dB fractional bandwidth (FBW) in the 18.0% and 24.1% ranges and low insertion losses below 1 dB. This work can significantly broaden the range of applications for SAW devices and can open a pathway to commercialize ultra-wideband SAW filters in 5G communication systems.
Growth Performance and Hematological Changes in Growing Sika Deers Fed with Spent Mushroom Substrate of Pleurotus ostreatus

Simple Summary With the rapid development of the mushroom industry, a large number of spent mushroom substrate (SMS) has also been produced. SMS can be easily digested by ruminants and is suitable for feeding animals, such as cows, sheep, as well as deer. The results of this study show that the dietary spent mushroom substrate of Pleurotus ostreatus (SMS-MP) has no obvious effect on the physiological condition of growing sika deer, at the same time it can reduce the cost of feeding and avoid environmental pollution caused by improper disposal of SMS-MP. Abstract The purpose of this experiment is to expand the feed of growing sika deer and to explore the effects on growing sika deer of the spent mushroom substrate of Pleurotus ostreatus (SMS-MP). Twelve immature female growing sika deer were randomly assigned to four groups. The ratios of SMS-MP to replace concentration supplements were 0%, 10%, 20%, and 30%, respectively, and the growth performance, feed intake and apparent digestibility, serum biochemical indexes, blood physiological indexes, serum immune globulin and plasma amino acid of growing sika deer were measured. The results of the current study confirmed the applicability of SMS-MP as a feed ingredient in growing sika deer diets. There was no significant change in growth performance and hematology of growing sika deer when the concentrate supplement was replaced with 10–20% SMS-MP. However, replacing 30% of concentrate supplements with SMS-MP in the growing sika deer diet resulted in significantly decreased Hb and HCT levels. It can be concluded that, as a waste resource, adding a small amount of SMS-MP has no significant effect on the growth of sika deer, and at the same time can reduce the consumption of concentrate supplements, thereby improving the economic benefits of sika deer breeding.
Early activity of the Kerguelen Mantle plume: geochronology, geochemistry and Sr-Nd-Pb isotopes of mafic dykes and sills from the Tethyan Himalaya

ABSTRACT The remnant Comei igneous province in SE Tibet has been recognized as a product of early Kerguelen mantle plume activity. In this paper, we investigate mafic dykes and sills intruded into Lakang Formation in the southeastern Tethyan Himalaya. Based on new whole-rock geochemical, Sr-Nd-Pb isotopic and SHRIMP zircon U-Pb geochronological data, these rocks can be divided into three groups. Group 1 is composed of OIB-like mafic dykes and sills with lower εNd(t) (+1.78-+2.55) and dated at 124.8 ± 1.7 and 133.3 ± 1.5 Ma. Group 2 consists of N-MORB-like mafic dykes and sills with lower TiO2 and P2O5 contents. Group 3 has geochemical compositions transitional between Group 1 and Group 2, with εNd(t) ranging from +1.98 to +2.24 and an age of 125.1 ± 2.1 Ma. We interpret Group 1 as being derived from an OIB-like source related to a mantle plume. Groups 2 and 3 are considered to have been generated from melts of the asthenosphere and the lower crust, with some involvement of melts from the upper crust. Considering the oldest (ca. 147 Ma) and the youngest (ca. 125 Ma) ages of the OIB-like mafic dykes and sills related to the Kerguelen mantle plume and their palaeogeographic location, we suggest that the Kerguelen mantle plume head had reached the lithosphere during the late Jurassic and was later directly underneath the Cona area. We propose a new model to describe the early activity of Kerguelen mantle plume, which put the mantle plume below the mid-ocean ridge and can well explain the long-lived magmatism related to Kerguelen mantle plume.
Robust Reinforcement Learning: A Review of Foundations and Recent Advances

Reinforcement learning (RL) has become a highly successful framework for learning in Markov decision processes (MDP). Due to the adoption of RL in realistic and complex environments, solution robustness becomes an increasingly important aspect of RL deployment. Nevertheless, current RL algorithms struggle with robustness to uncertainty, disturbances, or structural changes in the environment. We survey the literature on robust approaches to reinforcement learning and categorize these methods in four different ways: (i) Transition robust designs account for uncertainties in the system dynamics by manipulating the transition probabilities between states; (ii) Disturbance robust designs leverage external forces to model uncertainty in the system behavior; (iii) Action robust designs redirect transitions of the system by corrupting an agent’s output; (iv) Observation robust designs exploit or distort the perceived system state of the policy. Each of these robust designs alters a different aspect of the MDP. Additionally, we address the connection of robustness to the risk-based and entropy-regularized RL formulations. The resulting survey covers all fundamental concepts underlying the approaches to robust reinforcement learning and their recent advances.
Calculation of Thermal Expansion Coefficient of Rare Earth Zirconate System at High Temperature by First Principles

Compounds of rare earth zirconates with pyrochlore structure are candidates for the application of thermal barrier coatings of next generation. In order to modify the mechanic properties and maintain the low thermal conductivity, other trivalent rare-earth element substitution is commonly used. Presently, investigation on the evaluation of the property of thermal expansion is attracting more attention. In this paper, a feature parameter of thermal expansion coefficient at high temperature (α∞) was proposed by combining Grüneisen’s equation and the Debye heat capacity model. Using α∞ model, the thermal expansion property of different compounds can be easily figured out by first principles. Firstly, α∞ of ZrO2, HfO2, were calculated, and results are in good agreement with the experimental data from the literature. Moreover, α∞ of La2Zr2O7, Pr2Zr2O7, Gd2Zr2O7, and Dy2Zr2O7 were calculated, and results demonstrated that the model of α∞ is a useful tool to predict the thermal expansion coefficient at high temperature. Finally, Gd2Zr2O7 with 4 different Yb dopant concentrations (Gd1-xYbx)2Zr2O7 (x = 0, 0.125, 0.3125, 0.5) were calculated. Comparing with the experimental data from the literature, the calculation results showed the same tendency with the increasing of Yb concentration.
CNN-Based Dense Monocular Visual SLAM for Real-Time UAV Exploration in Emergency Conditions

Unmanned Aerial Vehicles (UAVs) for 3D indoor mapping applications are often equipped with bulky and expensive sensors, such as LIDAR (Light Detection and Ranging) or depth cameras. The same task could be also performed by inexpensive RGB cameras installed on light and small platforms that are more agile to move in confined spaces, such as during emergencies. However, this task is still challenging because of the absence of a GNSS (Global Navigation Satellite System) signal that limits the localization (and scaling) of the UAV. The reduced density of points in feature-based monocular SLAM (Simultaneous Localization and Mapping) then limits the completeness of the delivered maps. In this paper, the real-time capabilities of a commercial, inexpensive UAV (DJI Tello) for indoor mapping are investigated. The work aims to assess its suitability for quick mapping in emergency conditions to support First Responders (FR) during rescue operations in collapsed buildings. The proposed solution only uses images in input and integrates SLAM and CNN-based (Convolutional Neural Networks) Single Image Depth Estimation (SIDE) algorithms to densify and scale the data and to deliver a map of the environment suitable for real-time exploration. The implemented algorithms, the training strategy of the network, and the first tests on the main elements of the proposed methodology are reported in detail. The results achieved in real indoor environments are also presented, demonstrating performances that are compatible with FRs’ requirements to explore indoor volumes before entering the building.
Implantation of Hypoxia-Induced Mesenchymal Stem Cell Advances Therapeutic Angiogenesis

Hypoxia preconditioning enhances the paracrine abilities of mesenchymal stem cells (MSCs) for vascular regeneration and tissue healing. Implantation of hypoxia-induced mesenchymal stem cells (hi-MSCs) may further improve limb perfusion in a murine model of hindlimb ischemia. This study is aimed at determining whether implantation of hi-MSCs is an effective modality for improving outcomes of treatment of ischemic artery diseases. We evaluated the effects of human bone marrow-derived MSC implantation on limb blood flow in an ischemic hindlimb model. hi-MSCs were prepared by cell culture under 1% oxygen for 24 hours prior to implantation. A total of 1 × 105 MSCs and hi-MSCs and phosphate-buffered saline (PBS) were intramuscularly implanted into ischemic muscles at 36 hours after surgery. Restoration of blood flow and muscle perfusion was evaluated by laser Doppler perfusion imaging. Blood perfusion recovery, enhanced vessel densities, and improvement of function of the ischemia limb were significantly greater in the hi-MSC group than in the MSC or PBS group. Immunochemistry revealed that hi-MSCs had higher expression levels of hypoxia-inducible factor-1 alpha and vascular endothelial growth factor A than those in MSCs. In addition, an endothelial cell-inducing medium showed high expression levels of vascular endothelial growth factor, platelet endothelial cell adhesion molecule-1, and von Willebrand factor in hi-MSCs compared to those in MSCs. These findings suggest that pretreatment of MSCs with a hypoxia condition and implantation of hi-MSCs advances neovascularization capability with enhanced therapeutic angiogenic effects in a murine hindlimb ischemia model.
Orally Administered, Biodegradable and Biocompatible Hydroxypropyl–β–Cyclodextrin Grafted Poly(methacrylic acid) Hydrogel for pH Sensitive Sustained Anticancer Drug Delivery

In the current study, a pH sensitive intelligent hydroxypropyl–β–cyclodextrin-based polymeric network (HP-β-CD-g-MAA) was developed through a solution polymerization technique for site specific delivery of cytarabine in the colonic region. Prepared hydrogel formulations were characterized through cytarabine loading (%), ingredient’s compatibility, structural evaluation, thermal integrity, swelling pattern, release behavior and toxicological profiling in rabbits. Moreover, the pharmacokinetic profile of cytarabine was also determined in rabbits. New polymer formation was evident from FTIR findings. The percentage loaded into the hydrogels was in the range of 37.17–79.3%. Optimum swelling ratio of 44.56 was obtained at pH 7.4. Cytarabine release was persistent and in a controlled manner up to 24 h. In vitro degradation of hydrogels was more pronounced at intestinal pH as compared to acidic pH. Toxicity studies proved absence of any ocular, skin and oral toxicity, thus proving biocompatibility of the fabricated network. Hydrogels exhibited longer plasma half-life (8.75 h) and AUC (45.35 μg.h/mL) with respect to oral cytarabine solution. Thus, the developed hydrogel networks proved to be excellent and biocompatible cargo for prolonged and site-specific delivery of cytarabine in the management of colon cancer.