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Continuous monitoring of arterial blood pressure (BP) in non-clinical (ambulatory) settings is essential for understanding numerous health conditions, including cardiovascular diseases. Besides their importance in medical diagnosis, ambulatory BP monitoring platforms can advance disease correlation with individual behaviour, daily habits and lifestyle, potentially enabling analysis of root causes, prognosis and disease prevention. Although conventional ambulatory BP devices exist, they are uncomfortable, bulky and intrusive. Here we introduce a wearable continuous BP monitoring platform that is based on electrical bioimpedance and leverages atomically thin, self-adhesive, lightweight and unobtrusive graphene electronic tattoos as human bioelectronic interfaces. The graphene electronic tattoos are used to monitor arterial BP for >300 min, a period tenfold longer than reported in previous studies. The BP is recorded continuously and non-invasively, with an accuracy of 0.2 ± 4.5 mm Hg for diastolic pressures and 0.2 ± 5.8 mm Hg for systolic pressures, a performance equivalent to Grade A classification. Self-adhesive bioimpedance graphene electronic tattoos enable accurate continuous blood pressure monitoring.

Background The outbreak of a new virus known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has now become the main health concern all over the world. Since effective antiviral treatments have not been developed until now, SARS-CoV-2 is severely affecting countries and territories around the world. Methods At the present review, articles in PubMed were searched with the following terms: mesenchymal stem cells, exosomes, coronavirus, and SARS-CoV-2, either alone or in a combination form. The most relevant selected functions were mesenchymal stem cell-derived exosomes and SARS-CoV-2 virus infection. Results SARS-CoV-2 could damage pulmonary cells and induce secretion of different types of inflammatory cytokines. In the following, these cytokines trigger inflammation that damages the lungs and results in lethal acute respiratory distress syndrome (ARDS). The main characteristic of ARDS is the onset of inflammation in pulmonary, hyaline formation, pulmonary fibrosis, and edema. Mesenchymal stem cell-derived exosomes (MSC-Exo) are believed to have anti-inflammatory effects and immune-modulating capacity as well as the ability to induce tissue regeneration, suggesting a significant therapeutic opportunity that could be used to SARS-CoV-2 pneumonia treatment. Besides, exosomes may serve as a biomarker, drug delivery system, and vaccine for the management of the patient with SARS-CoV-2. Conclusion MSC-Exo may serve as a promising tool in the treatment of SARS-CoV-2 pneumonia. However, further work needs to be carried out to confirm the efficacy of exosomes in the treatment of SARS-CoV-2 pneumonia.

This study is based on a new approach to the development of the adsorption process from two perspectives, including the possibility of using the adsorbent in a wide range of pH (increasing chemical resistance) and also its easy separation from solution (mechanical strength), or in other words the possibility of preparing a simple fixed bed for the adsorbent during adsorption process. According to this view, chitosan/activated carbon composite was synthesized and used to remove of methylene blue as a cationic pollutant from water. The structural properties of the synthesized adsorbent were analyzed using FE-SEM, FTIR, BET and zeta potential analyses, which showed significant improvement in chemical and physical stability. The influence of main parameters such as adsorbent dose, contact time, initial concentration and pH value of the solution in the adsorption process was investigated. The results showed that if chitosan is used more than half amount of carbon, the performance of the adsorbent decreases, which may be related to the filling of carbon pores by chitosan. According to the zeta potential analysis, the pH of point zero charge of the adsorbent was found to be 4.4. Also, the adsorption mechanism followed the Langmuir model and pseudo-second-order kinetics, and the maximum adsorption capacity of a single layer for methylene blue dye was measured 22.52 mg/g.

In this study, hollow Fe3O4-SiO2-chitosan adsorbent with an optimal chitosan concentration of 2% (w/v) was synthesized to enhance arsenic (V) adsorption performance from low-concentration aqueous solutions. The hollowing process was used to enhance the surface area of the adsorbent and compensate for the surface area reduction of Fe3O4 nanoparticles induced by SiO2 and chitosan coating layers. Furthermore, the adsorption properties of organic pollutants were evaluated using methyl orange as the adsorbate. The microspheres underwent systematic characterization, and their arsenic (V) and methyl orange adsorption capacities were evaluated under various influencing factors. The results indicated improved surface area (202.174 m2/g) compared to non-hollow magnetic adsorbents (110 m2/g) reported in previous studies. Complete arsenic (V) removal (100%) was achieved within 60 minutes at a concentration of 0.2 mg/L, using an adsorbent dose of 0.012 g at pH 5. The optimal adsorbent doses for methyl orange (0.1 g/L) and arsenic (V) (0.5 g/L) were notably lower than those reported in previous studies. The electrostatic attraction was likely the dominant mechanism for arsenic (V) adsorption, whereas methyl orange adsorption may involve n-π interactions, hydrogen bonding, and electrostatic forces. The adsorption process followed the pseudo-second-order kinetics model and the Langmuir isotherm, with maximum adsorption capacities of 175.086 mg/g for arsenic (V) at pH 5 and 2399.910 mg/g for methyl orange at pH 3. The adsorbent showed significant potential for removing arsenic (V) and methyl orange, particularly from acidic wastewater. Moreover, the adsorbent maintained significant portion of its initial adsorption capacity for As(V) and methyl orange even in the presence of competing anions such as phosphate, sulfate, chloride, and nitrate. After four adsorption-desorption cycles, it retained over 90% of its adsorption capacity, demonstrating excellent selectivity, stability, and strong potential for the effective removal of both As(V) and methyl orange from aqueous solutions.

In this study, we investigate the effect of K 2 FeO 4 , as a new and soluble Fe salt at alkaline conditions, on oxygen-evolution reaction (OER) of Ni oxide. Both oxidation and reduction peaks for Ni in the presence and absence of Fe are linearly changed by (scan rate) 1/2 . Immediately after the interaction of [FeO 4 ] 2- with the surface of the electrode, a significant increase in OER is observed. This could be indicative of the fact that either the [FeO 4 ] 2- on the surface of Ni oxide is directly involved in OER, or, it is important to activate Ni oxide toward OER. Due to the change in the Ni(II)/(III) peak, it is hypothesized that Fe impurity in KOH or electrochemical cell has different effects at the potential range. At low potential, [FeO 4 ] 2− is reduced on the surface of the electrode, and thus, is significantly adsorbed on the electrode. Finally, oxygen-evolution measurements of K 2 FeO 4 and Ni 2 O 3 are investigated under chemical conditions. K 2 FeO 4 is not stable in the presence of Ni(II) oxide, and OER is observed in a KOH solution (pH ≈ 13).

The increasing use of artificial intelligence (AI) systems in our daily lives through various applications, services, and products highlights the significance of trust and distrust in AI from a user perspective. AI-driven systems have significantly diffused into various aspects of our lives, serving as beneficial “tools” used by human agents. These systems are also evolving to act as co-assistants or semi-agents in specific domains, potentially influencing human thought, decision-making, and agency. Trust and distrust in AI serve as regulators and could significantly control the level of this diffusion, as trust can increase, and distrust may reduce the rate of adoption of AI. Recently, a variety of studies focused on the different dimensions of trust and distrust in AI and its relevant considerations. In this systematic literature review, after conceptualizing trust in the current AI literature, we will investigate trust in different types of human–machine interaction and its impact on technology acceptance in different domains. Additionally, we propose a taxonomy of technical (i.e., safety, accuracy, robustness) and non-technical axiological (i.e., ethical, legal, and mixed) trustworthiness metrics, along with some trustworthy measurements. Moreover, we examine major trust-breakers in AI (e.g., autonomy and dignity threats) and trustmakers; and propose some future directions and probable solutions for the transition to a trustworthy AI.

Hydraulic fracturing (HF) is a pivotal technique in the oil and gas industry, aimed at enhancing hydrocarbon recovery by increasing reservoir permeability through high-pressure fluid injection. Despite its effectiveness, traditional methods used to evaluate HF performance often struggle to capture the complex, nonlinear interactions among operational and geological parameters. This study presents a comprehensive machine learning (ML)-based framework to address this challenge by predicting HF efficiency using three widely used algorithms: Random Forest (RF), Support Vector Machine (SVM), and Neural Networks (NN). The novelty of this research lies in the combined application of advanced statistical characterization and comparative ML modeling over a large-scale dataset comprising 16,000 records. Key statistical metrics, including mean, median, variance, skewness, and quartiles, were used to explore data distribution and inform model training. Additionally, the study uniquely evaluates model robustness across varying train/test data ratios (from 0.1 to 0.9), providing deeper insights into algorithm performance stability. Among the tested models, RF outperformed others by achieving the highest coefficient of determination (R 2  = 0.9804), alongside the lowest Mean Absolute Deviation (MAD) and Root Mean Square Error (RMSE) for both training and testing phases. These results demonstrate RF’s capability in handling complex subsurface data with high accuracy and low computational cost. The proposed framework not only enhances predictive accuracy in HF evaluation but also serves as a practical tool for optimizing fracturing design and decision-making in field operations. This integrated approach represents a step forward in applying artificial intelligence for data-driven reservoir engineering and contributes to the advancement of intelligent hydraulic fracturing practices in heterogeneous and data-rich environments.

Gelatin methacryloyl (GelMA) is one of the most widely used photo-crosslinkable biopolymers in tissue engineering. In in presence of an appropriate photoinitiator, the light activation triggers the crosslinking process, which provides shape fidelity and stability at physiological temperature. Although ultraviolet (UV) has been extensively explored for photo-crosslinking, its application has been linked to numerous biosafety concerns, originated from UV phototoxicity. Eosin Y, in combination with TEOA and VC, is a biosafe photoinitiation system that can be activated via visible light instead of UV and bypasses those biosafety concerns; however, the crosslinking system needs fine-tuning and optimization. In order to systematically optimize the crosslinking conditions, we herein independently varied the concentrations of Eosin Y [(EY)], triethanolamine (TEOA), vinyl caprolactam (VC), GelMA precursor, and crosslinking times and assessed the effect of those parameters on the properties the hydrogel. Our data showed that except EY, which exhibited an optimal concentration (~ 0.05 mM), increasing [TEOA], [VA], [GelMA], or crosslinking time improved mechanical (tensile strength/modulus and compressive modulus), adhesion (lap shear strength), swelling, biodegradation properties of the hydrogel. However, increasing the concentrations of crosslinking reagents ([TEOA], [VA], [GelMA]) reduced cell viability in 3-dimensional (3D) cell culture. This study enabled us to optimize the crosslinking conditions to improve the properties of the GelMA hydrogel and to generate a library of hydrogels with defined properties essential for different biomedical applications.

Background: On March 11, 2020, the World Health Organization (WHO) declared the novel coronavirus disease (COVID-19) a global pandemic. Starting in December 2019 from China, the first cases were officially announced on February 19 in Qom city, Iran. As of April 3, 2020, 206 countries have reported a total of 932166 cases with 46764 deaths. Along with China, USA, Italy, Spain, and Germany, Iran has been suffering the hardest burden of COVID-19 outbreak. Worse still, countries like Iran are struggling with the double burden of political sanctions to provide lifesaving medical equipment and medicines to combat the emergency. Methods: Using systematic document content analysis and through the lenses of health policy triangle, this article aims to compare the policies and strategies that Iran is adopting, with the experience and recommendations of China and WHO to combat COVID-19. Results: Iran has formulated contextual-based policies to combat COVID-19 outbreak before and after virus entrance. Insufficient whole-government, whole-society approach in managing the outbreak, inadequate lifesaving and protective equipment, and delayed decisive governance are the biggest challenges in policy making to combat COVID-19. COVID-19 policies are a public health concern and require professional advocacy attempts through appropriate inter-sectoral collaboration and whole-government coalitions. Conclusion: COVID-19 is an unfolding outbreak; hence, policy learning is crucial to formulate appropriate policies and implement them accordingly. Iran has made many efforts to defeat the outbreak, but more coherent, timely and efficient action is required, now, more than ever, to save lives and slow the spread of this pandemic.

Fabrication of well-ordered and bio-mimetic scaffolds is one of the most important research lines in tissue engineering. Different techniques have been utilized to achieve this goal, however, each method has its own disadvantages. Recently, melt electrowriting (MEW) as a technique for fabrication of well-organized scaffolds has attracted the researchers’ attention due to simultaneous use of principles of additive manufacturing and electrohydrodynamic phenomena. In previous research studies, polycaprolactone (PCL) has been mostly used in MEW process. PCL is a biocompatible polymer with characteristics that make it easy to fabricate well-arranged structures using MEW device. However, the mechanical properties of PCL are not favorable for applications like bone tissue engineering. Furthermore, it is of vital importance to demonstrate the capability of MEW technique for processing a broad range of polymers. To address aforementioned problems, in this study, three ten-layered box-structured well-ordered scaffolds, including neat PLA, neat PCL, and PLA/PCL composite are fabricated using an MEW device. Printing of the composite PLA/PCL scaffold using the MEW device is conducted in this study for the first time. The MEW device used in this study is a commercial fused deposition modeling (FDM) 3D printer which with some changes in its setup and configuration becomes prepared for being used as an MEW device. Since in most of previous studies, a setup has been designed and built for MEW process, the use of the FDM device can be considered as one of the novelties of this research. The printing parameters are adjusted in a way that scaffolds with nearly equal pore sizes in the range of 140 µm to 150 µm are fabricated. However, PCL fibers are mostly narrower (diameters in the range of 5 µm to 15 µm) than PLA fibers with diameters between 15 and 25 µm. Unlike the MEW process of PCL, accurate positioning of PLA fibers is difficult which can be due to higher viscosity of PLA melt compared to PCL melt. The printed composite PLA/PCL scaffold possesses a well-ordered box structure with improved mechanical properties and cell-scaffold interactions compared to both neat PLA and PCL scaffolds. Besides, the composite scaffold exhibits a higher swelling ratio than the neat PCL scaffold which can be related to the presence of less hydrophobic PLA fibers. This scaffold demonstrates an anisotropic behavior during uniaxial tensile test in which its Young’s modulus, ultimate tensile stress, and strain to failure all depend on the direction of the applied tensile force. This anisotropy makes the composite PLA/PCL scaffold an exciting candidate for applications in heart tissue engineering. The results of in-vitro cell viability test using L929 mouse murine fibroblast and human umbilical vein endothelial (HUVEC) cells demonstrate that all of the printed scaffolds are biocompatible. In particular, the composite scaffold presents the highest cell viability value among the fabricated scaffolds. All in all, the composite PLA/PCL scaffold shows that it can be a promising substitution for neat PCL scaffold used in previous MEW studies.