Multiple Potential Applications Research Articles

Increasing Chemical Diversity of B2N2 Anthracene Derivatives by Introducing Continuous Multiple Boron‐Nitrogen Units

AbstractIncreasing the chemical diversity of organic semiconductors is essential to develop efficient electronic devices. In particular, the replacement of carbon‐carbon (C−C) bonds with isoelectronic boron‐nitrogen (B−N) bonds allows precise modulation of the electronic properties of semiconductors without significant structural changes. Although some researchers have reported the preparation of B2N2 anthracene derivatives with two B−N bonds, no compounds with continuous multiple BN units have been prepared yet. Herein, we report the synthesis and characterization of a B2N2 anthracene derivative with a BNBN unit formed by converting the BOBN unit at the zigzag edge. Compared to the all‐carbon analogue 2‐phenylanthracene, BNBN anthracene exhibits significant variations in the C−C bond length and a larger highest occupied molecular orbital–lowest unoccupied molecular orbital energy gap. The experimentally determined bond lengths and electronic properties of BNBN anthracene are confirmed through theoretical calculations. The BOBN anthracene organic light‐emitting diode, used as a blue host, exhibits a low driving voltage. The findings of this study may facilitate the development of larger acenes with multiple BN units and potential applications in organic electronics.

Protein/Protein and Quantum Dot/Protein Organization in Sequential Monolayer Materials Studied Using Resonance Energy Transfer

Controlled junctions of proteins and nanomaterials offer multiple potential applications in the further construction of nanobiodevices. One of the possible junction types is a set of sequential monolayers of various components deposited on a given substrate. The advantage of such an organization is its high sensitivity, resulting from a huge surface covered by molecules or particles. What is more, the molecules/particles adsorbed on a substrate might be easier to handle than the assay in a cuvette. For further application, there should be crosstalk between monolayers; this is defined by the type of individuals forming a complex system. Here, we are studying, using mainly confocal microscopy and FLIM imaging, crosstalk through resonance energy transfer. The sequential monolayers of fluorescent proteins and CdTe quantum dots were deposited on a convenient substrate, a polyvinylidene difluoride membrane. First, we found that the degree of coverage is lower in the second monolayer. Hence, by manipulating the order of deposition, we obtained a system with a varied yield of resonance energy transfer with a donor excess or an acceptor excess. For a deeper understanding of the energy transfer and its limitations in this system influencing the assay pursuit, we utilized Monte Carlo computation. We found that, indeed, the distance between the monolayers, as well as the degree of coverage, is crucial. With the results of the simulation, we might estimate the relative degree of coverage in our sequential monolayers. We also found that in quantum-dots/protein-composed systems, the yield is stronger than predicted by Monte Carlo simulation. Hence, there should be protein reorientation on the nanoparticle surface, leading to such an effect. Finally, we showed that the yield of resonance energy transfer may be modulated by the external application of poly-L-lysines. These chemicals influenced QD fluorescence but not protein fluorescence and might be used, therefore, as a trigger or a switch in nanobiodevices employing those types of sequential monolayers.

Review of qualification and modeling for radiation-induced polymer degradation

Polymeric materials have multiple potential applications in nuclear power reactors including advanced and small modulus reactors, in addition to their extensive usage in safety electronic cables in the existing light water reactors. Through the qualification programs, knowledge accumulates about the polymer degradation kinetics under gamma-irradiation environment to facilitate the development of service-life predictive models. This paper aims to promote mechanistic-based predictability as a new approach to the qualification of polymeric components. Reviewed in this article are the current qualification standards and procedures, the current understandings of the degradation mechanisms, and kinetic models applicable to accelerated experiments for qualification.

Knowledge Graphs and Their Applications in Drug Discovery.

Knowledge graphs represent information in the form of entities and relationships between those entities. Such a representation has multiple potential applications in drug discovery, including democratizing access to biomedical data, contextualizing or visualizing that data, and generating novel insights through the application of machine learning approaches. Knowledge graphs put data into context and therefore offer the opportunity to generate explainable predictions, which is a key topic in contemporary artificial intelligence. In this chapter, we outline some of the factors that need to be considered when constructing biomedical knowledge graphs, examine recent advances in mining such systems to gain insights for drug discovery, and identify potential future areas for further development.

Advancements in total knee arthroplasty kinematics: 3D implant computer aided design model creation through X-ray or fluoroscopic images

Background3D-to-2D fluoroscopic registration is a popular and important step for analyzing total-knee-arthroplasty weight-bearing kinematics. Unfortunately, in vivo analyses using these techniques cannot be completed if the associated computer-aided design implant models are not available. This study introduces a novel method that enables the accessible computation of knee replacement patients' kinematics from fluoroscopy, achieved through the reconstruction of 3-dimensional knee component models using a limited set of 2-dimensional X-ray or fluoroscopic images. MethodsThe proposed non-rigid morphing algorithm, based on the coherent point drift algorithm, scales and transforms the shape of the template model to fit with the silhouette of the corresponding fluoroscopic images without changing the structure of the knee implant. While a greater number of fluoroscopic images can lead to higher accuracy, our study utilizes only 4 images. FindingsThe morphed models show excellent results in comparison with known models with a 0.52 mm average root-mean-square error and a 2.82 mm largest source error for 17 tested knee models of various implant types. The proposed algorithm also enables direct output of patient kinematics using fluoroscopy, with an average error of only 0.54 ± 0.42 mm for femorotibial contact and 0.86 ± 0.34 degrees for axial rotation. InterpretationA novel methodology was introduced to overcome common 3-dimentional to 2-dimensional registration limitations by recreating entire families of 3 dimensional models from a limited number of fluoroscopic images for both cruciate-retaining and posterior-stabilized knee replacement implants. Our algorithm has demonstrated high levels of accuracy with multiple potential extended applications.

Visible Light-Activated Ultralong-Lived Triplet Excitons of Carbon Dots for White-Light Manipulated Anti-Counterfeiting.

Room temperature phosphorescence (RTP) has emerged as an interesting but rare phenomenon with multiple potential applications in anti-counterfeiting, optoelectronic devices, and biosensing. Nevertheless, the pursuit of ultralong lifetimes of RTP under visible light excitation presents a significant challenge. Here, new phosphorescent materials that can be excited by visible light with record-long lifetimes are demonstrated, realized through embedding nitrogen doped carbon dots (N-CDs) into a poly(vinyl alcohol) (PVA) film. The RTP lifetime of the N-CDs@PVA film is remarkably extended to 2.1s excited by 420nm, representing the highest recorded value for visible light-excited phosphorescent materials. Theoretical and experimental studies reveal that the robust hydrogen bonding interactions can effectively reduce the non-radiative decay rate and radiative transition rate of triplet excitons, thus dramatically prolong the phosphorescence lifetime. Notably, the RTP emission of N-CDs@PVA film can also be activated by easily accessible low-power white-light-emitting diode. More significantly, the practical applications of the N-CDs@PVA film in state-of-the-art anti-counterfeiting security and optical information storage domains are further demonstrated. This research offers exciting opportunities for utilizing visible light-activated ultralong-lived RTP systems in a wide range of promising applications.

Cortisol in deciduous tooth tissues: A potential metric for assessing stress exposure in archaeological and living populations

ObjectiveCortisol is a glucocorticoid hormone produced by the hypothalamic-pituitary-adrenal axis that is regularly assessed in modern human and non-human populations in saliva, blood, and hair as a measure of stress exposure and stress reactivity. While recent research has detected cortisol concentrations in modern and archaeological permanent dental tissues, the present study assessed human primary (deciduous) teeth for cortisol concentrations. Materials and MethodsFifty-one dentine and enamel samples from nine modern and 10 archaeological deciduous teeth were analyzed for cortisol concentrations via enzyme-linked immunosorbent assay (ELISA). ResultsDetectable concentrations of cortisol were identified in 15 (of 32) dentine and 8 (of 19) enamel samples coming from modern and archaeological deciduous teeth. ConclusionsThis study is the first known analysis of cortisol from deciduous dental tissues, demonstrating the potential to identify measurable concentrations. SignificanceThe ability to analyze deciduous teeth is integral to developing dental cortisol methods with multiple potential future applications, including research on the biological embedding of stress in the skeleton. This study marks a key step in a larger research program to study stress in primary dentition from living and archaeological populations. LimitationsMultiple samples generated cortisol values that were not detectable with ELISA. Minimum quantities of tissue may be required to generate detectable levels of cortisol. Suggestions for Further ResearchFuture research should include larger sample sizes and consideration of intrinsic biological and extrinsic preservation factors on dental cortisol. Further method validation and alternative methods for assessing dental cortisol are needed.

Insights into the Unusual Activity of a Novel Homospermidine Synthase with a Promising Application to Produce Spermidine.

Spermidine is a naturally occurring polyamine with multiple biological activities and potential food and agricultural applications. However, sustainable and scalable spermidine production has not yet been attained. In this study, a homospermidine synthase (HSS) from Pseudomonas frederiksbergensis (PfHSS) capable of catalyzing the synthesis of spermidine from 1,3-diaminopropane and putrescine was identified based on multiple sequence alignment using Blastochloris viridis HSS (BvHSS) as a template. The optimal reaction pH and temperature for purified PfHSS were determined to be 8.5 and 45 °C, respectively, and K+ was able to promote the enzyme activity. Further analysis of the structural and functional relationships through molecular docking and molecular dynamics simulation indicates that glutamic acid at position 359 is the essential residue for the enzyme-catalyzed synthesis of spermidine. The whole-cell catalytic reaction yielded 1321.4 mg/L spermidine and 678.2 mg/L of homospermidine. This study presents a novel, promising, and sustainable biological method for producing spermidine.

Circulating Osteoprogenitor Cells Have a Mixed Immune and Mesenchymal Progenitor Function in Humans.

Circulating osteoprogenitors (COP) are a population of cells in the peripheral circulation that possess functional and phenotypical characteristics of multipotent stromal cells (MSCs). This population has a solid potential to become an abundant, accessible, and replenishable source of MSCs with multiple potential clinical applications. However, a comprehensive functional characterization of COP cells is still required to test and fully develop their use in clinical settings. This study characterized COP cells by comparing them to bone marrow-derived MSCs (BM-MSCs) and adipose-derived MSCs (ASCs) through detailed transcriptomic and proteomic analyses. We demonstrate that COP cells have a distinct gene and protein expression pattern with a significantly stronger immune footprint, likely owing to their hematopoietic lineage. In addition, regarding progenitor cell differentiation and proliferation pathways, COP cells have a similar expression pattern to BM-MSCs and ASCs. COP cells are a unique but functionally similar population to BM-MSCs and ASCs, sharing their proliferation and differentiation capacity, thus presenting an accessible source of MSCs with strong potential for translational regenerative medicine strategies.

Medium-Range Order Structure Controls Thermal Stability of Pores in Zeolitic Imidazolate Frameworks.

Metal-organic framework (MOF) glasses have multiple potential applications, as they combine advantages of traditional glasses with those of MOFs. The melt-quenching process used to form MOF glasses typically leads to a significant decrease in porosity, but the structural origin of this thermally induced pore collapse remains largely unknown. Here, we study the melting process of three zeolitic imidazolate frameworks (ZIFs), namely ZIF-4, ZIF-62, and ZIF-76, using ab initio molecular dynamics (MD) simulations. By analyzing the MD data using topological data analysis, we show that while the three ZIF systems exhibit similar short-range order structural changes upon heating, they exhibit significant differences in their medium-range order structure. Specifically, ZIF-76 retains more of its medium-range order structures in the liquid state compared to the other glass-forming ZIF systems, which allows it to remain more porous than ZIF-4 and ZIF-62. As such, our results may aid in understanding the structural features that govern the ability to maintain porosity in the melt-quenched glassy state.

Multi-omic analyses reveal the unique properties of chia (Salvia hispanica) seed metabolism

Chia (Salvia hispanica) is an emerging crop considered a functional food containing important substances with multiple potential applications. However, the molecular basis of some relevant chia traits, such as seed mucilage and polyphenol content, remains to be discovered. This study generates an improved chromosome-level reference of the chia genome, resolving some highly repetitive regions, describing methylation patterns, and refining genome annotation. Transcriptomic analysis shows that seeds exhibit a unique expression pattern compared to other organs and tissues. Thus, a metabolic and proteomic approach is implemented to study seed composition and seed-produced mucilage. The chia genome exhibits a significant expansion in mucilage synthesis genes (compared to Arabidopsis), and gene network analysis reveals potential regulators controlling seed mucilage production. Rosmarinic acid, a compound with enormous therapeutic potential, was classified as the most abundant polyphenol in seeds, and candidate genes for its complex pathway are described. Overall, this study provides important insights into the molecular basis for the unique characteristics of chia seeds.

Applications of the levelized cost concept

Levelized cost is a life-cycle cost measure that aggregates investment expenditures and operating costs into a unit cost figure. So far, most applications of this concept have originated in relation to energy technologies. This paper describes the role of the levelized cost concept in cost accounting and synthesizes multiple research streams in connection with electricity, energy storage, hydrogen and carbon capture. Finally, we sketch multiple potential future applications of the levelized cost concept.

Recent Advances and Perspectives Regarding Paper-Based Sensors for Salivary Biomarker Detection

Paper-based sensors overcome the drawbacks of conventional sensors in terms of their flexibility, portability, and stability compared to conventional sensors. Moreover, as a noninvasive bodily fluid, saliva contains various biomarkers related to physical status, which makes it perfectly matched with to use of paper-based sensors to manufacture a convenient and inexpensive disposable sensing device. This review focuses on the recent advances and progress in the design of paper-based salivary sensors and their applications. The first part mainly discusses various paper-based sensors and their advanced compositions, including dipstick assay, lateral flow assay, and microfluidic analytical device. Different detection methods in salivary biomarker detection are specially introduced in the secondary section, then their multiple potential applications and prospects are summarized. The sensor has excellent advantages for saliva detection, provides a reliable platform for point-of-care tests and telemedicine, and epically promotes the development of the medical Internet of Things.

Structural Transitions of Papain-like Cysteine Proteases: Implications for Sensor Development.

The significant role of papain-like cysteine proteases, including papain, cathepsin L and SARS-CoV-2 PLpro, in biomedicine and biotechnology makes them interesting model systems for sensor development. These enzymes have a free thiol group that is suitable for many sensor designs including strong binding to gold nanoparticles or low-molecular-weight inhibitors. Focusing on the importance of the preservation of native protein structure for inhibitor-binding and molecular-imprinting, which has been applied in some efficient examples of sensor development, the aim of this work was to examine the effects of the free-thiol-group's reversible blocking on papain denaturation that is the basis of its activity loss and aggregation. To utilize biophysical methods common in protein structural transitions characterization, such as fluorimetry and high-resolution infrared spectroscopy, low-molecular-weight electrophilic thiol blocking reagent S-Methyl methanethiosulfonate (MMTS) was used in solution. MMTS binding led to a two-fold increase in 8-Anilinonaphthalene-1-sulfonic acid fluorescence, indicating increased hydrophobic residue exposure. A more in-depth analysis showed significant transitions on the secondary structure level upon MMTS binding, mostly characterized by the lowered content of α-helices and unordered structures (either for approximately one third), and the increase in aggregation-specific β-sheets (from 25 to 52%) in a dose-dependant manner. The recovery of this inhibited protein showed that reversibility of inhibition is accompanied by reversibility of protein denaturation. Nevertheless, a 100-fold molar excess of the inhibitor led to the incomplete recovery of proteolytic activity, which can be explained by irreversible denaturation. The structural stability of the C-terminal β-sheet rich domain of the papain-like cysteine protease family opens up an interesting possibility to use its foldamers as a strategy for sensor development and other multiple potential applications that rely on the great commercial value of papain-like cysteine proteases.

Artificial Intelligence Applications in Breast Imaging: Current Status and Future Directions.

Attempts to use computers to aid in the detection of breast malignancies date back more than 20 years. Despite significant interest and investment, this has historically led to minimal or no significant improvement in performance and outcomes with traditional computer-aided detection. However, recent advances in artificial intelligence and machine learning are now starting to deliver on the promise of improved performance. There are at present more than 20 FDA-approved AI applications for breast imaging, but adoption and utilization are widely variable and low overall. Breast imaging is unique and has aspects that create both opportunities and challenges for AI development and implementation. Breast cancer screening programs worldwide rely on screening mammography to reduce the morbidity and mortality of breast cancer, and many of the most exciting research projects and available AI applications focus on cancer detection for mammography. There are, however, multiple additional potential applications for AI in breast imaging, including decision support, risk assessment, breast density quantitation, workflow and triage, quality evaluation, response to neoadjuvant chemotherapy assessment, and image enhancement. In this review the current status, availability, and future directions of investigation of these applications are discussed, as well as the opportunities and barriers to more widespread utilization.

Computing Surface Reaction Rates by Adaptive Multilevel Splitting Combined with Machine Learning and Ab Initio Molecular Dynamics.

Computing accurate rate constants for catalytic events occurring at the surface of a given material represents a challenging task with multiple potential applications in chemistry. To address this question, we propose an approach based on a combination of the rare event sampling method called adaptive multilevel splitting (AMS) and ab initio molecular dynamics. The AMS method requires a one-dimensional reaction coordinate to index the progress of the transition. Identifying a good reaction coordinate is difficult, especially for high dimensional problems such as those encountered in catalysis. We probe various approaches to build reaction coordinates such as support vector machine and path collective variables. The AMS is implemented so as to communicate with a density functional theory-plane wave code. A relevant case study in catalysis, the change of conformation and the dissociation of a water molecule chemisorbed on the (100) γ-alumina surface, is used to evaluate our approach. The calculated rate constants and transition mechanisms are discussed and compared to those obtained by a conventional static approach based on the Eyring-Polanyi equation with harmonic approximation. It is revealed that the AMS method may provide rate constants that are smaller than those provided by the static approach by up to 2 orders of magnitude due to entropic effects involved in the chemisorbed water molecule.

Laser-induced tuning of carbon nanosensitizers to maximize nitrogen doping and reactive oxygen species production in the visible range

Carbon nanodots (CNDs) have emerged as novel fluorescent nanosensitizers able to expand the photocatalytic response of conventional semiconductors beyond the ultraviolet spectral window. Key aspects of CNDs related with their high photostability, resistance to photobleaching and optical properties (including downconversion and upconversion luminescence) are often associated with the capacity to dope the carbogenic network with light heteroatoms, especially nitrogen. In this work, we present the use of laser pyrolysis as a versatile and convenient synthesis technique to generate different N-doped CNDs. The level of N doping can be tuned through the selection of a single liquid solvent containing N as carbon precursor. This liquid precursor can be alternatively enriched with additional N sources co-fed in the form of gas (i.e. NH3) or disolved solid precursors (i.e. phtalocyanine-Ph). We demonstrate that the N-CNDs retrieved after the additional N cofeeding treatments improve their photoactivity when assembled to P25 nanoparticles towards the conversion of methyl orange (MO) under white LED illumination. All the N-CNDs act as photosensitizers expanding the response of P25 beyond the UV region and exhibit an active role generating different types of Reactive Oxygen Species (ROS) via singlet oxygen, superoxide and hydroxyl radicals that can pave the way for multiple potential applications in environmental and green processes.

Triglyceride mixtures: Cold-bursting and double emulsion formation

It was shown recently that a solid-to-solid phase transitions (α-to-β, gel-to-crystal), typical for many lipid substances, can lead to formation of nanoporous network inside lipid micro-particles dispersed in aqueous surfactant solutions (Cholakova et al. ACS Nano2020, 14, 8594). These nanopores are spontaneously infused by the aqueous phase when appropriate combination of water-soluble and oil-soluble surfactants is applied. As a result, the initial lipid micro-particles can spontaneously burst into much smaller nanoparticles, just by cooling and heating of the initial dispersion. Under certain conditions, the infused aqueous phase is entrapped in the moment of lipid particle melting and double emulsion of type water-in-oil-in-water (W/O/W) is formed. The current study aims to clarify how the composition of the lipid micro-drops and surfactants affect the observed phenomena. Selected mixtures of monoacid triglycerides are studied systematically. The results show that the bursting efficiency usually decreases when the complexity of the lipid mixture increases, due to the expanded temperature interval for lipid melting. Nevertheless, complete particle bursting and lipid nanoparticles with diameters down to 20 nm are formed even for the most complex lipid compositions under appropriate conditions. The key mechanisms leading to efficient fragmentation and double emulsion formation are clarified, and the main governing factors are explored. On this basis, we reveal that the system behavior can be switched between complete particle bursting and W/O/W emulsion formation by: (1) Change in the cooling and heating rates without any changes in the chemical composition, (2) Change in the concentration of oil-soluble surfactant, and/or (3) Change in the phase in which the oil-soluble surfactant is introduced initially. Thus, we have formulated guiding rules to control the formation of lipid nanoparticles and W/O/W emulsions with triglyceride mixtures promising multiple potential applications.

Bifunctional reduced graphene oxide/polyelectrolyte/NiFe layered double hydroxide composites for efficient catalyzed dephosphorylation and 4-nitrophenol reduction

Dephosphorylation that separates phosphate groups from substrates is a significant reaction for both living organisms and environmental protection. Meanwhile, 4-nitrophenol (4-NP) is known to be a popular organic compound used for pesticides production, which is genotoxic and carcinogenic to humans and animals. Herein, we have developed a bifunctional catalyst that can be used for simultaneous dephosphorylation and 4-nitrophenol (4-NP) reduction when para-nitrophenyl phosphate (p-NPP) serves as the model compound. This bifunctional catalyst was obtained by in-situ growth of NiFe layered double hydroxide on the reduced graphene oxide/polyelectrolytes assembly nanolayers (denoted as rGP3.5/NiFe LDH). The results demonstrate that the rGP3.5/NiFe LDH can activate dephosphorylation of p-NPP at 20 °C and the catalytic efficiency increases significantly with increasing temperature in the range of 20 °C to 90 °C. Moreover, by-product 4-NP formed through p-NPP dephosphorylation is further fully converted to 4-aminophenol by the rGP3.5/NiFe LDH within 15 min. As far as we know, this is the first example for both dephosphorylation and 4-NP reduction through NiFe LDH as bifunctional catalysts, which paves the way for the development of multiple potential applications for NiFe LDH.

Green synthesis and multifunctional applications of nitrogen-doped carbon quantum dots via one-step hydrothermal carbonization of Curcuma zedoaria.

Low-dimensional (<10 nm) semiconductor carbon quantum dots (CQDs) have been widely used in metal ion sensing and bioimaging. Here, we used the renewable resource Curcuma zedoaria as a carbon source and prepared green carbon quantum dots with good water solubility by a hydrothermal method without any chemical reagent. At different pH values (4-6) and high NaCl concentrations, the photoluminescence of the CQDs was very stable, which indicated that they were suitable for a wide range of applications even under harsh conditions. The CQDs exhibited fluorescence quenching in the presence of Fe3+ ions, indicating their application potential as fluorescence probes for the sensitive and selective detection of Fe3+ ions. The CQDs showed high photostability, low cytotoxicity, and good hemolytic activity, and were successfully applied to bioimaging experiments, i.e. multicolor cell imaging in L-02 (human normal hepatocytes) and CHL (Chinese hamster lung) cells with and without Fe3+, as well as wash-free labeling imaging of Staphylococcus aureus and Escherichia coli. The CQDs also showed good free radical scavenging activity and demonstrated a protective effect against photooxidative damage to L-02 cells. These results indicate that CQDs obtained from medicinal herb sources have multiple potential applications in the fields of sensing, bioimaging, and even disease diagnosis.