Search

Microplastics comprise plastic particles that are less than 5 mm in size. Owing to a significant increase in plastic production, micro plastics have become ubiquitous pollutants worldwide. Several studies have reported that microplastics are harmful to living organisms because they can adsorb contaminants from the environment due to their unique physicochemical properties. The adsorbed contaminants on microplastics can be released and accumulated in living organisms, thereby adversely affecting the health of humans and animals. Since existing water treatment technologies as stand-alone processes cannot achieve complete removal of microplastics, reliable methods must be developed. Advanced oxidation processes (AOPs) are a promising approach for the chemical treatment of contaminants such as microplastics. These processes utilize highly reactive oxygen species (e.g., hydroxyl radicals, sulfate radicals, superoxide anions, and singlet oxygen) to decompose microplastics completely. However, at this stage, AOPs can partially degrade and/or alter surface chemistry of microplastics. Therefore, extensive effort must be made to further study AOPs for complete decomposition of microplastics.

Cells respond to a myriad of stressors by senescing, acquiring stable growth arrest, morphologic and metabolic changes, and a senescence-associated-secretory-phenotype (SASP). The heterogeneity of senescent cells (SnCs) and their SASP is vast, yet poorly characterized. SnCs have diverse roles in health and disease and are therapeutically targetable, making characterization of SnCs and harmonization of their nomenclature a priority. The Cellular Senescence Network (SenNet), a NIH Common Fund initiative, will leverage emerging single cell and spatial-omics to identify and map SnCs in numerous organs across the lifespan of humans and mice. A common coordinate framework will integrate the data, using validated, standardized methods, creating public 4-dimensional SnC atlases. Key SenNet deliverables include development of innovative tools/technologies to detect SnCs, biomarker discovery, common annotations to describe SnCs and extensive public data sets. The goal is to comprehensively understand and map SnCs for diagnostic and therapeutic purposes to improve human health.

This paper reviews the currently used pretreatment methods for microplastics (MPs) analysis in soil and freshwater sediments, primarily sample processing, pretreatment, and characterization methods for MPs analysis. In addition, analytical tools (e.g., lab instruments), MPs characteristics, and MPs quantity, are included in this review. Prior to pretreatment, soil and sediment samples are typically processed using sieving and drying methods, and a sample quantity of

Recently, microplastics (MPs) became a big name in the world since their presence in bodies of different species, environmental media, and even in bottled drinking water was frequently reported. Several studies reported MPs’ potential threat to health of humans, animals and the ecosystem. Therefore, it is of great importance to develop reliable technologies for removing MPs in the environment. Advanced oxidation processes (AOPs) are widely studied and applied for the decomposition of different refractory contaminants in the environment. Because reactive oxygen species produced in AOPs could effectively degrade many pollutants, several AOPs were applied for MPs decomposition. Homogeneous and heterogeneous AOPs, including photolysis, UV/H2O2, O3, UV/visible light-induced photocatalysis, and heat activated PS and PMS, could effectively decompose various types of MPs with different sizes. However, the decomposition mostly occurred on the surface of MPs even though several studies reported complete removal of MPs. Interestingly, several studies demonstrated that treated MPs could become pollutant carriers for animals and human beings by adsorbing contaminants in the environment. However, a limited number of studies on MPs removal by AOPs are available and only few types of AOPs are recently studied even though current studies demonstrated the potential of AOPs for complete MPs removal. Therefore, more effort must be put into investigating different AOPs for complete removal of MPs in the environment. AOPs will play a key role for MPs removal in the environment in the near future, definitely.

Chloroquine often causes serious eye and vision problems, which are mainly mediated by lysosomotropic alteration. In this study, we investigated whether the ginsenoside protopanaxadiol relieves chloroquine-induced retinopathy by restoring lysosomotropic abnormalities in human adult retinal pigment epithelial-19 cells. Cytotoxicity was assessed using a 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay. Morphological alterations in autophagosomes of adult retinal pigment epithelial-19 cells was detected using confocal microscopy. Apoptosis was examined using flow cytometry, whereas cellular reactive oxygen species levels were determined by measuring the fluorescence intensity of 5-(and-6)-carboxy-2’-7’-dichlorohydrofluorescein diacetate. Lysosomal function was assessed by measuring lysosomal pH and enzyme activity. Immunoprecipitation and western blotting analyses were performed. Adult retinal pigment epithelial-19 cells accumulated autophagosomes with fusion defects in lysosomes and reactive oxygen species formation following exposure to chloroquine. This effect trapped Beclin-1 and B-cell lymphoma 2 interfering with autophagy initiation and autophagosome development. Protopanaxadiol alleviated chloroquine-induced toxicity by modulating the interaction between Beclin-1 and Bcl-2, which was mediated by the AMP-activated protein kinase-mammalian target of rapamycin signal axis. Furthermore, autophagy and apoptosis were simultaneously controlled by protopanaxadiol via upregulation of autophagy flux and decreased reactive oxygen species formation and apoptotic protein expression. These findings suggest that protopanaxadiol is a promising treatment strategy for chloroquine-mediated retinopathy.

We consider a locally uniformly strictly elliptic second order partial differential operator in $\mathbb{R}^d$, $d\ge 2$, with low regularity assumptions on its coefficients, as well as an associated Hunt process and semigroup. The Hunt process is known to solve a corresponding stochastic differential equation that is pathwise unique. In this situation, we study the relation of invariance, infinitesimal invariance, recurrence, transience, conservativeness and $L^r$-uniqueness, and present sufficient conditions for non-existence of finite infinitesimally invariant measures as well as finite invariant measures. Our main result is that recurrence implies uniqueness of infinitesimally invariant measures, as well as existence and uniqueness of invariant measures, both in subclasses of locally finite measures. We can hence make in particular use of various explicit analytic criteria for recurrence that have been previously developed in the context of (generalized) Dirichlet forms and present diverse examples and counterexamples for uniqueness of infinitesimally invariant, as well as invariant measures and an example where $L^1$-uniqueness fails for one infinitesimally invariant measure but holds for another and pathwise uniqueness holds. Furthermore, we illustrate how our results can be applied to related work and vice versa., Comment: revision

We present conservativeness criteria for sub-Markovian semigroups generated by divergence type operators with specified infinitesimally invariant measures. The conservativeness criteria in this article are derived by $L^1$-uniqueness and imply that a given infinitesimally invariant measure becomes an invariant measure. We explore further conditions on the coefficients of the partial differential operators that ensure the uniqueness of the invariant measure beyond the case where the corresponding semigroups are recurrent. A main observation is that for conservativeness and uniqueness of invariant measures in this article, no growth conditions are required for the partial derivatives related to the anti-symmetric matrix of functions $C=(c_{ij})_{1 \leq i,j \leq d}$ that determine a part of the drift coefficient. As stochastic counterparts, our results can be applied to show not only the existence of a pathwise unique and strong solution up to infinity to a corresponding It\^{o}-SDE, but also the existence and uniqueness of invariant measures for the family of strong solutions., Comment: 23 pages. typo corrected, some content added

We show the $L^r(\mathbb{R}^d, \mu)$-uniqueness for any $r \in (1, 2]$ and the essential self-adjointness of a Dirichlet operator $Lf = \Delta f +\langle \frac{1}{\rho}\nabla \rho , \nabla f \rangle$, $f \in C_0^{\infty}(\mathbb{R}^d)$ with $d \geq 3$ and $\mu=\rho dx$. In particular, $\nabla \rho$ is allowed to be in $L^d_{loc}(\mathbb{R}^d, \mathbb{R}^d)$ or in $L^{2+\varepsilon}_{loc}(\mathbb{R}^d, \mathbb{R}^d)$ for some $\varepsilon>0$, while $\rho$ is required to be locally bounded below and above by strictly positive constants. The main tools in this paper are elliptic regularity results for divergence and non-divergence type operators and basic properties of Dirichlet forms and their resolvents., Comment: 15 pages, minor corrections on typos and omissions

The antimalarial drug chloroquine (CQ) induces retinopathy, a disorder characterized by lysosomotropic alteration. In this study, we examined whether D4476 (4-(4-(2,3-dihydrobenzo [1,4] dioxin-6-yl)-5-pyridin-2-yl-1H-imidazole-2-yl) benzamide), a specific casein kinase 1 inhibitor, alleviate CQ-induced retinopathy in adult retinal pigment epithelial (ARPE-19) cells. Cultured ARPE-19 cells were exposed to CQ with or without D4476 and cell death was quantified using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. To examine autophagy flux, ARPE-19 cells were transfected with green fluorescence protein light chain 3 (GFP-LC3)-red fluorescence protein (RFP)-LC3ΔG plasmid DNA and co-stained with the lysosomal-associated membrane protein (LAMP)-1 antibody. Western blotting and fluorescence-activated cell sorting (FACS) showed apoptosis, whereas the fluorescence intensity of 2'-7'-dichlorofluorescein diacetate revealed levels of cellular oxidative stress. We then confirmed the effect of D4476 on the interaction between Beclin 1 and B-cell lymphoma-2 (Bcl-2) through immunoprecipitation with an anti-Bcl-2 antibody. Following CQ exposure, ARPE-19 cells accumulated autophagosomes because of defective lysosomal degradation. Furthermore, CQ trapped Beclin 1 with Bcl-2, disturbing autophagy initiation and autolysosome formation. However, D4476 alleviated CQ-induced effects by rescuing ARPE-19 cells from CQ-induced toxicity by modulating the association between Beclin 1 and Bcl-2. Therefore, D4476 controls autophagy and apoptosis simultaneously by upregulating autophagy flux, decreasing ROS formation, and triggering the expression of anti-apoptotic proteins through inhibition of mTOR, JNK, and p38 MAPK signals. We conclude that D4476 is a promising treatment strategy for CQ-mediated retinopathy.

Billions of electric equipment are connected to Internet of Things (IoT)-based sensor networks, where they continuously generate a large volume of status information of assets. So, there is a need for state-aware information retrieval technology that can automatically recognize the status of each electric asset and provide the user with timely information suitable for the asset management of electric equipment. In this paper, we investigate state-aware information modeling that specializes in the asset management of electric equipment. With this state-aware information model, we invent a new asset state-aware ranking technique for effective information retrieval for electric power and energy systems. We also derive an information retrieval scenario for IoT in power and energy systems and develop a mobile application prototype. A comparative performance evaluation proves that the proposed technique outperforms the existing information retrieval technique.

// Hardik R. Mody 2, 3, * , Sau Wai Hung 3, * , Kineta Naidu 4 , Haesung Lee 4 , Caitlin A. Gilbert 4 , Toan Thanh Hoang 4 , Rakesh K. Pathak 2 , Radhika Manoharan 2 , Shanmugam Muruganandan 2 and Rajgopal Govindarajan 1, 2, 3 1 The Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA 2 Division of Pharmaceutics and Pharmaceutical Chemistry, The Ohio State University, Columbus, OH, USA 3 Department of Pharmaceutical and Biomedical Sciences, The University of Georgia, Athens, GA, USA 4 Department of Biochemistry and Molecular Biology, The University of Georgia, Athens, GA, USA * These authors have contributed equally to this work Correspondence to: Rajgopal Govindarajan, email: govindarajan.21@osu.edu Keywords: SET, EMT, pancreatic cancer, N-cadherin, signaling Received: December 20, 2016 Accepted: May 22, 2017 Published: July 07, 2017 ABSTRACT Pancreatic cancer has a devastating prognosis due to 80-90% of diagnostic cases occurring when metastasis has already presented. Activation of the epithelial-mesenchymal transition (EMT) is a prerequisite for metastasis because it allows for the dissemination of tumor cells to blood stream and secondary organs. Here, we sought to determine the role of SET oncoprotein, an endogenous inhibitor of PP2A, in EMT and pancreatic tumor progression. Among the two major isoforms of SET (isoform 1 and isoform 2), higher protein levels of SET isoform 2 were identified in aggressive pancreatic cancer cell lines. Overexpressing SET isoform 2, and to a lesser extent SET isoform 1, in epithelial cell lines promoted EMT-like features by inducing mesenchymal characteristics and promoting cellular proliferation, migration, invasion, and colony formation. Consistently, knockdown of SET isoforms in the mesenchymal cell line partially resisted these characteristics and promoted epithelial features. SET-induced EMT was likely facilitated by increased N-cadherin overexpression, decreased PP2A activity and/or increased expression of key EMT-driving transcription factors. Additionally, SET overexpression activated the Rac1/JNK/c-Jun signaling pathway that induced transcriptional activation of N-cadherin expression. In vivo , SET isoform 2 overexpression significantly correlated with increased N-cadherin in human PDAC and to tumor burden and metastatic ability in an orthotopic mouse tumor model. These findings identify a new role for SET in cancer and have implications for the design and targeting of SET for intervening pancreatic tumor progression.

We show existence of an infinitesimally invariant measure $m$ for a large class of divergence and non-divergence form elliptic second order partial differential operators with locally Sobolev regular diffusion coefficient and drift of some local integrability order. Subsequently, we derive regularity properties of the corresponding semigroup which is defined in $L^s(\mathbb{R}^d,m)$, $s\in [1,\infty]$, including the classical strong Feller property and classical irreducibility. This leads to a transition function of a Hunt process that is explicitly identified as a solution to an SDE. Further properties of this Hunt process, like non-explosion, moment inequalities, recurrence and transience, as well as ergodicity, including invariance and uniqueness of $m$, and uniqueness in law, can then be studied using the derived analytical tools and tools from generalized Dirichlet form theory., Comment: Revised version, slightly modified title

Tetrazonium gold(III) salts of syn-(cis) and anti-(trans) geometry of 4,4′-(1,3-phenylenediisopropylidene)bisaniline and 4,4′-(1,4-phenylenediisopropylidene)bisaniline were synthesized. HAuCl4 was used as a metal-based counter anion precursor. The gold-carbon nanoparticles (AuNPs) were constructed using the mild reducing agent organoborane 9-borabicyclo[3.3.1]nonane (9-BBN). The nanoparticles dispersed in acetonitrile showed a plasmon peak at 540 nm. Dynamic light scattering measurements showed the size of cis-AuNPs is smaller than the trans-AuNPs. Transmission electron microscopy images showed the formation of spherical shaped AuNPs. X-ray diffraction, energy dispersive spectroscopy, and X-ray photoelectron spectroscopy results supported the presence of metallic gold in both the cis and trans AuNPs. Electrochemical studies of the tetrazonium salts showed the facile reduction and the blocking effect of the films formed on glassy carbon electrodes. The photothermal mirror method was used to study the thermal diffusivity of gold thin films deposited over a glassy carbon substrate. The values of the thermal diffusivity coefficient were determined for the cis and trans isomers of the film.

INTRODUCTION: Amongst COVID19 patients in the intensive care unit (ICU), acute kidney injury (AKI) occurs in 40-60% with 10-30% requiring renal replacement therapy (RRT) During any ICU surge situation, an increase in the total number of patients that will require RRT should be expected as the number of ICU patients increases This surge in RRT needs can quickly exhaust RRT machine availability During the pandemic, hospitals developed RRT surge contingency plans to maximize the number of patients who can receive RRT on a given day This may involve mixing modalities of therapy to include using CRRT machines to provide prolonged intermittent RRT (PIRRT) in a shift-based model However, implementing a machine allocation system to deploy RRT machines in the most efficient manner is a vexing challenge Automated strategies for machine allocation could aid staff in quickly developing daily RRT operational plans METHODS: Efficient routing of CRRT machines is analogous to an optimization routing problem, traditionally formulated with multiple vehicles picking up varying loads at each stop We reformulate the problem with CRRT machines as vehicles and patient needs as varying loads, with a maximum load of 24 patient-hours per day per machine, including transition time between patients RESULTS: Our solution, designed to be run daily, was written in Python 3 6 In conjunction with the primary team, nephrologists determine RRT durations based on patient need (6-12 hours vs 24 hours), generating a list of needs in the upcoming 24h period on a shared server If there is more RRT demand than capacity, nephrologists will be asked to reallocate required hours Next, we process CRRT machine locations with patient needs and locations The distance matrix preferentially routes machines between patients within units, then between closeby units, with preference given towards patients and units of similar COVID status to support cohorting The system then generates a sequence of patients that each machine should serve within minutes CONCLUSIONS: We report this as the first known implementation of automated scheduling for optimizing CRRT machine utilization given scarcity constraints from COVIDrelated surges Further characterization is necessary to quantify workload benefit and machine utilization

Platinum (Pt) is an easily moldable, anti-corrosive and also good catalyst in a variety of chemical reactions. Platinum can be used in many fields, however, however, the low wettability of platinum substrate in many platinum-based devices has been made a problem when they contact with liquid state environment. In this study, we report a simple and effective self-assembled monolayer coating method which provides tremendously increased wettability on platinum substrate device by using Sodium 3-mercapto-1-propanesulfonic acid solution. After surface modifications, water contact angle of the surfaces displayed less than , representing that surfaces are successfully coated to be super-hydrophilic surface by simple dip coating method.

As the penetration of electric vehicles (EVs) accelerates according to eco-friendly policies, the impact of electric vehicle charging demand on a power distribution network is becoming significant for reliable power system operation. In this regard, accurate power demand or load forecasting is of great help not only for unit commitment problem considering demand response but also for long-term power system operation and planning. In this paper, we present a forecasting model of EV charging station load based on long short-term memory (LSTM). Besides, to improve the forecasting accuracy, we devise an imputation method for handling missing values in EV charging data. For the verification of the forecasting model and our imputation approach, performance comparison with several imputation techniques is conducted. The experimental results show that our imputation approach achieves significant improvements in forecasting accuracy on data with a high missing rate. In particular, compared to a strategy without applying imputation, the proposed imputation method results in reduced forecasting errors of up to 9.8%.

Overexpression of the MYC oncogene is a key feature of many human malignancies including Burkitt lymphoma. While MYC is widely regarded to be a promising therapeutic target, a clinically effective MYC inhibitor is still elusive. Here, we report an alternative strategy, targeting MYC indirectly through inhibition of the HSP90 machinery. We found that inhibition of HSP90 function reduces MYC expression in human Burkitt lymphoma through suppression of MYC transcription and destabilization of MYC protein, thereby diminishing the proliferation of tumor cells. Consistently, treatment of Burkitt lymphoma cell lines with HSP90 inhibitors (17-AAG or 17-DMAG) was accompanied by downregulation of canonical MYC target genes. Combination treatment with 17-DMAG and the proteasome inhibitor, MG-132, led to accumulation of MYC protein, indicating that upon HSP90 inhibition, MYC is degraded by the proteasome. Using co-immunoprecipitation, we furthermore demonstrated a direct interaction between MYC and HSP90, indicating that MYC is an HSP90 client protein in Burkitt lymphoma. Together, we report here the use of HSP90 inhibitors as an alternative approach to target the MYC oncogene and its network in Burkitt lymphoma.

Object detection in a road scene has received a significant attention from research fields of developing autonomous vehicle and automatic road monitoring systems. However, object occlusion problems frequently occur in generic road scenes. Due to such occlusion problems, previous object detection methods have limitations of not being able to detect objects accurately. In this paper, we propose a novel object detection network which is robust in occlusions. For effective object detection even with occlusion, the proposed network mainly consists of two parts; 1) Object detection framework, 2) Multiple object bounding box (OBB)-Critic network for predicting a BB map which estimates both ob-j ect region and occlusion region. Comprehensive experimental results on a KITTI Vision Benchmark Suite dataset showed that the proposed object detection network outperformed the state-of-the-art methods.

The K-means clustering algorithm is a popular and widely used method for clustering. For covariance matrices, we consider a geodesic clustering algorithm based on the K-means clustering framework in consideration of symmetric positive definite matrices as a Riemannian (non-Euclidean) manifold. This paper considers a geodesic clustering algorithm for data consisting of symmetric positive definite (SPD) matrices, utilizing the Riemannian geometric structure for SPD matrices and the idea of a K-means clustering algorithm. A K-means clustering algorithm is divided into two main steps for which we need a dissimilarity measure between two matrix data points and a way of computing centroids for observations in clusters. In order to use the Riemannian structure, we adopt the geodesic distance and the intrinsic mean for symmetric positive definite matrices. We demonstrate our proposed method through simulations as well as application to real financial data.

Using elliptic and parabolic regularity results in $L^p$-spaces and generalized Dirichlet form theory, we construct for every starting point weak solutions to SDEs in $\mathbb{R}^d$ up to their explosion times including the following conditions. For arbitrary but fixed $p>d$ the diffusion coefficient $A=(a_{ij})_{1\le i,j\le d}$ is locally uniformly strictly elliptic with functions $a_{ij}\in H^{1,p}_{loc}(\mathbb{R}^d)$ and the drift coefficient $\mathbf{G}=(g_1,\dots, g_d)$ consists of functions $g_i\in L^p_{loc}(\mathbb{R}^d)$. The solution originates by construction from a Hunt process with continuous sample paths on the one-point compactification of $\mathbb{R}^d$ and the corresponding SDE is by a known local well-posedness result pathwise unique up to an explosion time. Just under the given assumptions we show irreducibility and the strong Feller property on $L^{1}(\mathbb{R}^d,m)+L^{\infty}(\mathbb{R}^d,m)$ of its transition function, and the strong Feller property on $L^{q}(\mathbb{R}^d,m)+L^{\infty}(\mathbb{R}^d,m)$, $q=\frac{dp}{d+p}\in (d/2,p/2)$, of its resolvent, which both include the classical strong Feller property. We present moment inequalities and classical-like non-explosion criteria for the solution which lead to pathwise uniqueness results up to infinity under presumably optimal general non-explosion conditions. We further present explicit conditions for recurrence and ergodicity, including existence as well as uniqueness of invariant probability measures., Comment: Further revised version improved explanations and expressions, correction of typos

The tremendous growth of data in recent years poses some key challenges for recommender systems. Theses keys are related with producing high quality recommendations and fast performing the composition recommended items. In this paper, we propose social clustering-based similar user index to not only improve the prediction of recommendations, but also compose personalized recommendations in fast. Through the experimental result, we show that proposed clustering method is more accurate than k-means which is prevalent clustering techniques. And, we reduce computation time needed for composing recommendation. That is, proposed clustering-based indexing method improves the performance of recommender systems which deals with a very large data.

Increasing amounts of TV contents are being disseminated through advanced broadcast, satellite and smart TV technologies leading to an information overload. Despite the excessive increase of TV contents, there are few considerations in the development of novel methods for personalized smart TV content recommender services. Most existing personalized TV content services are mainly focus on using individual profiles and require user’s immediate participation in rating their experienced contents. In this paper, we propose the context tagging-based user’s preference prediction mechanism by extending the widely known recommender algorithm, collaborative filtering (CF) in order to increase the user’s satisfaction about the recommender service. The development of the prototype system shows the usefulness of proposed mechanism. And the experiment confirms that the proposed mechanisms improve the recommender system.

With the brilliant advance of ubiquitous technologies, it is possible to provide more smart and pervasive healthcare services in a smart home environment. Despite of these remarkable advances of technologies, there are few smart home-based personalized healthcare services which fully consider not only user’s current situation but also user’s social relationship. In this paper, we try to model contexts which are generally distributed in smart home environment using the ontology technology. The set of modeled contexts includes home domain-based contexts and social relationship-based contexts. Based on these context models, we can provide fully personalized healthcare service to a specific user in a smart home environment. For verifying the usefulness of the proposed smart home service, we implemented a prototype of healthcare services. Through the demonstration of the developed prototype, we know that using ontology-based context awareness model can provide situation and social-aware health care services in much pervasive way.

Emerging Health Information Technologies (HIT), such as Electronic Health Records (EHR) and Personal Health Records (PHR) systems, facilitate access to and sharing of patients’ medical data in a distributed environment. The privacy protection of medical information is a pressing issue with the use of these medical technologies. In this paper, the authors present a Patient-controlled Privacy Protection Framework, which allows a patient to specify his or her own privacy policies on their own medical data no matter where they are stored. In addition, the authors extend this basic framework to medical emergency situations, where roles and users may not be limited to an organizational boundary. To enforce patient’s privacy policies even in emergency situations, the authors propose the Situation Role-based Privacy Control model and a social network-based user credential discovery method to recommend a situation role to candidate users. The authors present a mobile prototype system and two experiments to show the feasibility of our approach.

People use more and more electronic devices at home, in their car or in the office and with the proliferation of smart connected devices. The internet of things (IoT) is a vision of interconnected everyday objects and self-configuration wireless networks of sensors. In this paper, we describe a new concept of the social IoT as a pervasive interaction paradigm for the information sharing in the Web of devices. And we propose the architecture of the system for information sharing in the environment of IoT.