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Abstract Diabetic retinopathy (DR) is the most common diabetic microvascular complication and cause of blindness in adults under the age of 65. Our results suggest that, when comparing transcriptomes of cultures grown in hypoxic conditions versus room-air, cybrids containing mitochondria from African and Asian diabetic subjects ([Afr + Asi]/DM) have some uniquely different transcriptome profiles compared to European/diabetic (Euro/DM) cybrids (e.g., fatty acid metabolism: EnrichR rank 10 in [Afr + Asi]/DM, rank 85 in Euro/DM; Endocytosis: rank 25 in [Afr + Asi]/DM, rank 5 in Euro/DM; Ubiquitin Mediated Proteolysis: rank 34 in [Afr + Asi]/DM, rank 7 in Euro/DM). As determined by both RNA-seq and qRT-PCR results, transcription of the gene encoding oleoyl-ACP hydrolase (OLAH) was significantly increased in [Afr + Asi]/DM cybrids compared to Euro/DM cybrids in hypoxic conditions. Additionally, our results show that in hypoxic conditions, Euro/DM cybrids and [Afr + Asi]/DM cybrids show similar decreases in ROS production. All cybrids showed decreased ZO1-minus protein levels, but their phagocytic functions were not significantly altered in hypoxic conditions. In conclusion, our findings suggest that the "molecular memory" imparted by [Afr + Asi]/DM mtDNA may act through one of the molecular pathways seen in transcriptome analysis, such as fatty acid metabolism, without significantly changing essential RPE functions.

Abstract This paper develops prototypical communication system (PCS) models to support the analysis of electric distribution systems dependency on communication. Though there exist representative and prototypical distribution test systems, i.e., IEEE test feeders and the taxonomy of prototypical feeders, there are no standard definitions of communication systems appropriate for studies of system interdependence. To accurately represent the impact communication systems have on electric distribution system operations, the paper introduces the design basis for developing PCS models highlighting key characteristics of communication systems architectures and commonly‐deployed technologies. It follows with functional definitions, implementations, and an example of how PCSs can be used for system analysis. The approach leverages existing open‐source modeling and simulation tools. Co‐simulation is achieved with ns‐3 for PCSs, GridLAB‐D extsuperscript{ exttrademark} for distribution systems, and Python extsuperscript{ exttrademark} for distribution system control centers. The Hierarchical Engine for Large‐Scale Infrastructure Co‐simulation (HELICS) environment is used to federate these individual simulators. It allows for different PCSs to be integrated with distribution systems and analyzed in different scenarios. This underlines the importance of correctly identifying network topologies and technologies and their impact on the system control strategies. Though this work uses specific tools development and implementation, the PCS models can be used in other simulation environments.

Abstract Activation of the Simulator of Interferon Genes (STING) system by mitochondrial (mt) DNA can upregulate type 1 interferon genes and enhance immune responses to combat bacterial and viral infections. In cancers, the tumor‐derived DNA activates STING leading to upregulation of IFN‐beta and induction of antitumor T cells. The entire mtDNA from the cell lines was sequenced using next‐generation sequencing (NGS) technology with independent sequencing of both strands in both directions, allowing identification of low‐frequency heteroplasmy SNPs. There were 15 heteroplasmy SNPs showing a range from 3.4% to 40.5% occurrence in the K cybrid cell lines. Three H haplogroup cybrids possessed SNP heteroplasmy that ranged from 4.39% to 30.7%. The present study used qRT‐PCR to determine if cybrids of H and K haplogroups differentially regulate expression levels of five cancer genes (BRAC1, ALK, PD1, EGFR, and HER2) and seven STING subunits genes (CGAS, TBK1, IRF3, IκBa, NFκB, TRAF2, and TNFRSF19). Some cybrids underwent siRNA knockdown of STING followed by qRT‐PCR in order to determine the impact of STING on gene expression. Rho0 (lacking mtDNA) ARPE‐19 cells were used to determine if mtDNA is required for the expression of the cancer genes studied. Our results showed that (a) K cybrids have lower expression levels for BRAC1, ALK, PD1, EGFR, IRF3, and TNFRSF19 genes but increased transcription for IκBa and NFκB compared to H cybrids; (b) STING KD decreases expression of EGFR in both H and K cybrids, and (c) PD1 expression is negligible in Rho0 cells. Our findings suggest that the STING DNA sensing pathway may be a previously unrecognized pathway to target modulation of cancer‐related genes and the PD1 expression requires the presence of mtDNA.

Purpose: 7-ketocholesterol (7kCh), a natural byproduct of oxidation in lipoprotein deposits is implicated in the pathogenesis of diabetic retinopathy and age-related macular degeneration (AMD). This study was performed to investigate whether several clinical drugs can inhibit 7kCh-induced caspase activation and mitigate its apoptotic effects on retinal cells in vitro. Method: Two populations of retinal cells, human retinal pigment epithelial cells (ARPE-19) and rat neuroretinal cells (R28) were exposed to 7kCh in the presence of the following inhibitors: Z-VAD-FMK (pan-caspase inhibitor), simvastatin, memantine, epicatechin, and Z-IETD-FMK (caspase-8 inhibitor) or Z-ATAD-FMK (caspase-12 inhibitor). Caspase-3/7, -8, and -12 activity levels were measured by fluorochrome caspase assays to quantify cell death. IncuCyte live-cell microscopic images were obtained to quantify cell counts. Results: Exposure to 7kCh for 24 hours significantly increased caspase activities for both ARPE-19 and R28 cells (P < 0.05). In ARPE cells, pretreatment with various drugs had significantly lower caspase-3/7, -8, and -12 activities, reported in % change in mean signal intensity (msi): Z-VAD-FMK (48% decrease, P < 0.01), memantine (decreased 47.8% at 1 µM, P = 0.0039 and 81.9% at 1 mM, P < 0.001), simvastatin (decreased 85.3% at 0.01 µM, P < 0.001 and 84.8% at 0.05 µM, P < 0.001) or epicatechin (83.6% decrease, P < 0.05), Z-IETD-FMK (68.1% decrease, P < 0.01), and Z-ATAD-FMK (47.7% decrease, P = 0.0017). In contrast, R28 cells exposed to 7kCh continued to have elevated caspase-3/7, -8, and -12 activities (between 25.7% decrease and 17.5% increase in msi, P > 0.05) regardless of the pretreatment. Conclusion: Several current drugs protect ARPE-19 cells but not R28 cells from 7kCh-induced apoptosis, suggesting that a multiple-drug approach is needed to protect both cells types in various retinal diseases.

Increasing renewable penetration and grid modernization initiatives are having a significant impact on the operating and fault characteristics of distribution systems. As a result, protection systems need to account for the changing nuances in systems transient response to disturbances and the resulting voltage and/or current to ensure safe and reliable operation. The approaches for modeling and analyzing power systems also need to evolve accordingly, based on the choice of protection system. Therefore, this paper reviews the state-of-the-art and evolving approaches for the protection of future energy systems. The approaches are categorized based on operating principles and variations in the underlying mathematical formulation – to present a comprehensive overview on fault detection and recommendations for future research. The evolving nature of distribution systems, interconnection requirements and standards, and system automation is also discussed in view of the need for higher fidelity models and/or limitations from current approaches. Finally, the protection algorhithms are compared based on their associated challenges with reliability, protection, and communication/design needs.

Abstract Background Salmonid fishes are characterised by a very high level of variation in trophic, ecological, physiological, and life history adaptations. Some salmonid taxa show exceptional potential for fast, within-lake diversification into morphologically and ecologically distinct variants, often in parallel; these are the lake-resident charr and whitefish (several species in the genera Salvelinus and Coregonus). To identify selection on genes and gene categories associated with such predictable diversifications, we analysed 2702 orthogroups (4.82 Mbp total; average 4.77 genes/orthogroup; average 1783 bp/orthogroup). We did so in two charr and two whitefish species and compared to five other salmonid lineages, which do not evolve in such ecologically predictable ways, and one non-salmonid outgroup. Results All selection analyses are based on Coregonus and Salvelinus compared to non-diversifying taxa. We found more orthogroups were affected by relaxed selection than intensified selection. Of those, 122 were under significant relaxed selection, with trends of an overrepresentation of serine family amino acid metabolism and transcriptional regulation, and significant enrichment of behaviour-associated gene functions. Seventy-eight orthogroups were under significant intensified selection and were enriched for signalling process and transcriptional regulation gene ontology terms and actin filament and lipid metabolism gene sets. Ninety-two orthogroups were under diversifying/positive selection. These were enriched for signal transduction, transmembrane transport, and pyruvate metabolism gene ontology terms and often contained genes involved in transcriptional regulation and development. Several orthogroups showed signs of multiple types of selection. For example, orthogroups under relaxed and diversifying selection contained genes such as ap1m2, involved in immunity and development, and slc6a8, playing an important role in muscle and brain creatine uptake. Orthogroups under intensified and diversifying selection were also found, such as genes syn3, with a role in neural processes, and ctsk, involved in bone remodelling. Conclusions Our approach pinpointed relevant genomic targets by distinguishing among different kinds of selection. We found that relaxed, intensified, and diversifying selection affect orthogroups and gene functions of ecological relevance in salmonids. Because they were found consistently and robustly across charr and whitefish and not other salmonid lineages, we propose these genes have a potential role in the replicated ecological diversifications.

Differences in technical efficiency across farms are one of the major factors explaining differences in farm survival and growth and changes in farm industry structure. This study employs Data Envelopment Analysis (DEA) to compute technical inefficiency scores for output, energy, materials, pesticides and fertiliser of a sample of Dutch indoor vegetable farms within the period 2006-2016. A bootstrap truncated regression model is used to determine statistical associations between producer-specific characteristics and technical inefficiency scores for the specified inputs. For the sample of indoor growers, the average technical inefficiency was about 14% for energy, 23% for materials, 24% for pesticides and 22% for fertilisers. The bootstrap truncated regression suggested that the degree of specialisation exerts adverse effects on the technical inefficiency of variable inputs. While age, short-term, long-term debt and subsidy were statistically significant, the coefficients were not economically significant. Building the capacity of farmers to reduce input inefficiency will enable farmers to be competitive and reduce the adverse effects of input overuse on the environment.

Purpose. One of the leading causes of irreversible blindness worldwide, age-related macular degeneration (AMD) is a progressive disorder leading to retinal degeneration. While several treatment options exist for the exudative form of AMD, there are currently no FDA-approved treatments for the more common nonexudative (atrophic) form. Mounting evidence suggests that mitochondrial damage and retinal pigment epithelium (RPE) cell death are linked to the pathogenesis of AMD. Human retinal progenitor cells (hRPCs) have been studied as a potential restorative therapy for degenerative conditions of the retina; however, the effects of hRPC treatment on retinal cell survival in AMD have not been elucidated. Methods. In this study, we used a cell coculture system consisting of hRPCs and AMD or age-matched normal cybrid cells to characterize the effects of hRPCs in protecting AMD cybrids from cellular and mitochondrial damage and death. Results. AMD cybrids cocultured with hRPCs showed (1) increased cell viability; (2) decreased gene expression related to apoptosis, autophagy, endoplasmic reticulum (ER) stress, and antioxidant pathways; and (3) downregulation of mitochondrial replication genes compared to AMD cybrids without hRPC treatment. Furthermore, hRPCs cocultured with AMD cybrids showed upregulation of (1) neuronal and glial markers, as well as (2) putative neuroprotective factors, responses not found when hRPCs were cocultured with age-matched normal cybrids. Conclusion. The current study provides the first evidence that therapeutic benefits may be obtainable using a progenitor cell-based approach for atrophic AMD. Our results suggest that bidirectional interactions exist between hRPCs and AMD cybrids such that hRPCs release trophic factors that protect the cybrids against the cellular and mitochondrial changes involved in AMD pathogenesis while, conversely, AMD cybrids upregulate the release of these neuroprotective factors by hRPCs while promoting hRPC differentiation. These in vitro data provide evidence that hRPCs may have therapeutic potential in atrophic AMD.

Background Drug therapy yields different results depending on its recipient population. Cisplatin, a commonly used chemotherapeutic agent, causes different levels of resistance and side effects for different patients, but the mechanism(s) are presently unknown. It has been assumed that this variation is a consequence of differences in nuclear (n) DNA, epigenetics, or some external factor(s). There is accumulating evidence that an individual’s mitochondrial (mt) DNA may play a role in their response to medications. Variations within mtDNA can be observed, and an individual’s mtDNA can be categorized into haplogroups that are defined by accumulations of single nucleotide polymorphisms (SNPs) representing different ethnic populations. Methods The present study was conducted on transmitochondrial cytoplasmic hybrids (cybrids) that possess different maternal-origin haplogroup mtDNA from African (L), Hispanic [A+B], or Asian (D) backgrounds. Cybrids were created by fusing Rho0 ARPE-19 cells (lacking mtDNA) with platelets, which contain numerous mitochondria but no nuclei. These cybrid cells were cultured to passage five, treated with cisplatin, incubated for 48 h, then analyzed for cell metabolic activity (tetrazolium dye (MTT) assay), mitochondrial membrane potential (JC-1 assay), cytotoxicity (lactate dehydrogenase (LDH) assay), and gene expression levels for ALK, BRCA1, EGFR, and ERBB2/HER2. Results Results indicated that untreated cybrids with varying mtDNA haplogroups had similar relative metabolic activity before cisplatin treatment. When treated with cisplatin, (1) the decline in metabolic activity was greatest in L (27.4%, p [A+B], p = 0.0270). (4) The expression levels decreased for ALK in L (p

Background We aim to determine the possible adverse effects of ciprofloxacin (CPFX) and tetracycline (TETRA), as examples of bactericidal and bacteriostatic agents, respectively, on cultured human retinal pigment epithelial cells (ARPE-19).Methods Cells were treated with 30, 60 and 120 µg/mL of CPFX and TETRA. Cell metabolism was measured by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. JC-1 dye (5′,6,6′-tetrachloro-1,1′,3,3′-tetraethylbenzimidazolylcarbocyanine iodide) assay was conducted to measure the mitochondrial membrane potential (MMP). The level of reactive oxygen species (ROS) was measured using the -2’,7’-dichlorodihydrofluorescein diacetate assay (H2DCFDA). Quantitative real-time PCR was performed to analyse the gene expression levels associated with apoptosis (BAX, BCL2-L13, BCL2, Caspase 3, Caspase 7 and Caspase 9), inflammatory (interleukin-1β (IL-1β), IL-6, IL-33, transforming growth factor-α (TGF-α), TGF-β1 and TGF-β2) and antioxidant pathways (SOD2, SOD3, GPX3 and NOX4), along with the mitochondrial DNA (mtDNA) copy numbers.Results Results illustrated that while all three concentrations of CPFX decreased cellular viability of ARPE-19 during all incubation periods, the 120 µg/mL TETRA resulted in increased cellular viability. At 48 and 72 hours, levels of MMP and ROS decreased significantly with each antibiotic. BAX, BCL2-L13, CASP-7, CASP-9, SOD2 and GPX3 genes overexpressed by either antibiotics. There was higher expression of IL-6 and IL-1B with TETRA treatment. The level of mtDNA decreased using both treatments.Conclusions Clinically relevant concentrations of CPFX and TETRA have detrimental impacts on ARPE-19 cell lines in vitro, including upregulation of genes related to apoptosis, inflammation and antioxidant pathways. Additional studies are warranted to investigate if these harmful effects might be seen in retinal degeneration models in vivo.

Summary: Plant metabolism is broadly reprogrammed during acclimation to abiotic changes. Most previous studies have focused on transitions from standard to single stressful conditions. Here, we systematically analyze acclimation processes to levels of light, heat, and cold stress that subtly alter physiological parameters and assess their reversibility during de-acclimation. Metabolome and transcriptome changes were monitored at 11 different time points. Unlike transcriptome changes, most alterations in metabolite levels did not readily return to baseline values, except in the case of cold acclimation. Similar regulatory networks operate during (de-)acclimation to high light and cold, whereas heat and high-light responses exhibit similar dynamics, as determined by surprisal and conditional network analyses. In all acclimation models tested here, super-hubs in conditional transcriptome networks are enriched for components involved in translation, particularly ribosomes. Hence, we suggest that the ribosome serves as a common central hub for the control of three different (de-)acclimation responses.

To solve the heat diffusion problem in electronic packaging, a novel kind of irregularly shaped hybrid filler, boron nitride@copper (BN@Cu), was successfully assembled via reduction of Cu2+. BN@Cu hybrid fillers composed of different mass ratios between BN and Cu have been prepared and characterized. A specific BN@Cu hybrid filler (mBN:mCu = 100:2), labeled as BN@2Cu, exhibited remarkable ability in enhancing the thermal conductivity of polybenzoxazine (PBz) composites fabricated through ball milling followed by hot pressing. With 25 wt% of BN@2Cu hybrid fillers, the thermal conductivity of PBz composites reaches 1.049 W m−1 K−1. Dielectric properties, electrical conductivity, and curing behavior of the composites were also investigated. In addition, Foygel's thermal conduction model was employed to demonstrate the mechanism of BN@2Cu hybrid filler in improving thermal conductivity.

We present a system capable of providing visual feedback for ergometer training, allowing detailed analysis and gamification. The presented solution can easily upgrade any existing ergometer device. The system consists of a set of pedals with embedded sensors, readout electronics and wireless communication modules and a tablet device for interaction with the users, which can be mounted on any ergometer, transforming it into a full analytical assessment tool with interactive training capabilities. The methods to capture the forces and moments applied to the pedal, as well as the pedal’s angular position, were validated using reference sensors and high-speed video capture systems. The mean-absolute error (MAE) for load is found to be 18.82 N, 25.35 N, 0.153 Nm for Fx, Fz and Mx respectively and the MAE for the pedal angle is 13.2°. A fully gamified experience of ergometer training has been demonstrated with the presented system to enhance the rehabilitation experience with audio visual feedback, based on measured cycling parameters.

Our study assesses the effects of anti-VEGF (Vascular Endothelial Growth Factor) drugs and Trichostatin A (TSA), an inhibitor of histone deacetylase (HDAC) activity, on cultured ARPE-19 (Adult Retinal Pigment Epithelial-19) cells that are immortalized human retinal pigment epithelial cells. ARPE-19 cells were treated with the following anti-VEGF drugs: aflibercept, ranibizumab, or bevacizumab at 1× and 2× concentrations of the clinical intravitreal dose (12.5 μL/mL and 25 μL/mL, respectively) and analyzed for transcription profiles of genes associated with the pathogenesis age-related macular degeneration (AMD). HDAC activity was measured using the Fluorometric Histone Deacetylase assay. TSA downregulated HIF-1α and IL-1β genes, and upregulated BCL2L13, CASPASE-9, and IL-18 genes. TSA alone or bevacizumab plus TSA showed a significant reduction of HDAC activity compared to untreated ARPE-19 cells. Bevacizumab alone did not significantly alter HDAC activity, but increased gene expression of SOD2, BCL2L13, CASPASE-3, and IL-18 and caused downregulation of HIF-1α and IL-18. Combination of bevacizumab plus TSA increased gene expression of SOD2, HIF-1α, GPX3A, BCL2L13, and CASPASE-3, and reduced CASPASE-9 and IL-β. In conclusion, we demonstrated that anti-VEGF drugs can: (1) alter expression of genes involved in oxidative stress (GPX3A and SOD2), inflammation (IL-18 and IL-1β) and apoptosis (BCL2L13, CASPASE-3, and CASPASE-9), and (2) TSA-induced deacetylation altered transcription for angiogenesis (HIF-1α), apoptosis, and inflammation genes.

Plant pest invasions cost billions of Euros each year in Europe. Prediction of likely places of pest introduction could greatly help focus efforts on prevention and control and thus reduce societal costs of pest invasions. Here, we test whether generic data-driven risk maps of pest introduction, valid for multiple species and produced by machine learning methods, could supplement the costly species-specific risk analyses currently conducted by governmental agencies. An elastic-net algorithm was trained on a dataset covering 243 invasive species to map risk of new introductions in Europe as a function of climate, soils, water, and anthropogenic factors. Results revealed that the BeNeLux states, Northern Italy, the Northern Balkans, and the United Kingdom, and areas around container ports such as Antwerp, London, Rijeka, and Saint Petersburg were at higher risk of introductions. Our analysis shows that machine learning can produce hotspot maps for pest introductions with a high predictive accuracy, but that systematically collected data on species’ presences and absences are required to further validate and improve these maps.

The objective of gene set enrichment analysis (GSEA) in modern biological studies is to identify functional profiles in huge sets of biomolecules generated by high-throughput measurements of genes, transcripts, metabolites, and proteins. GSEA is based on a two-stage process using classical statistical analysis to score the input data and subsequent testing for overrepresentation of the enrichment score within a given functional coherent set. However, enrichment scores computed by different methods are merely statistically motivated and often elusive to direct biological interpretation. Here, we propose a novel approach, called Thermodynamically Motivated Enrichment Analysis (TMEA), to account for the energy investment in biological relevant processes. Therefore, TMEA is based on surprisal analysis, which offers a thermodynamic-free energy-based representation of the biological steady state and of the biological change. The contribution of each biomolecule underlying the changes in free energy is used in a Monte Carlo resampling procedure resulting in a functional characterization directly coupled to the thermodynamic characterization of biological responses to system perturbations. To illustrate the utility of our method on real experimental data, we benchmark our approach on plant acclimation to high light and compare the performance of TMEA with the most frequently used method for GSEA.

Targeted mass spectrometry has become the method of choice to gain absolute quantification information of high quality, which is essential for a quantitative understanding of biological systems. However, the design of absolute protein quantification assays remains challenging due to variations in peptide observability and incomplete knowledge about factors influencing peptide detectability. Here, we present a deep learning algorithm for peptide detectability prediction, d::pPop, which allows the informed selection of synthetic proteotypic peptides for the successful design of targeted proteomics quantification assays. The deep neural network is able to learn a regression model that relates the physicochemical properties of a peptide to its ion intensity detected by mass spectrometry. The approach makes use of experimentally detected deviations from the assumed equimolar abundance of all peptides derived from a given protein. Trained on extensive proteomics datasets, d::pPop's plant and non-plant specific models can predict the quality of proteotypic peptides for not yet experimentally identified proteins. Interrogating the deep neural network after learning from ~76,000 peptides per model organism allows to investigate the impact of different physicochemical properties on the observability of a peptide, thus providing insights into peptide observability as a multifaceted process. Empirical evaluation with rank accuracy metrics showed that our prediction approach outperforms existing algorithms. We circumvent the delicate step of selecting positive and negative training sets and at the same time also more closely reflect the need for selecting the top most promising peptides for targeting a protein of interest. Further, we used an artificial QconCAT protein to experimentally validate the observability prediction. Our proteotypic peptide prediction approach not only facilitates the design of absolute protein quantification assays via a user-friendly web interface but also enables the selection of proteotypic peptides for not yet observed proteins, hence rendering the tool especially useful for plant research.

Developing tendency of increasing integration in electronic components filed led to the demand for thermally conductive polymer materials. Forming a segregated structure with thermally conductive fillers in the matrix has been proven to be a promising technique. However, the mechanical properties of the material prepared via this technique are commonly sacrificed because the interaction between fillers and matrix are weak. We present a simple method to improve the mechanical properties while maintaining the segregated structure via the collaboration of epoxy and polybenzoxazine(PBz). The fillers, epoxy resin, and benzoxazine(BOZ) were mixed and then hot pressed under 12 MPa of pressure with a certain heating strategy. The thermal conductivity, density, mechanical properties, morphology, and thermal stability of the composites were investigated. With 25 wt% filler, the value of thermal conductivity coefficient of EP/PBz composites reached 0.811 W mK ^−1 , while that of PBz composites was 0.762 W mK ^−1 . The tensile strength of the matrix improved from 58.3 MPa to 99.7 MPa.

Data visualization is integral for exploratory data analysis and data presentation. Consequently, every programming environment suitable for data analysis needs a feature-rich visualization library. In this paper, we present Plotly.NET - a fully featured charting library for the .NET ecosystem. Plotly.NET requires little ceremony to use, provides multiple API (application programming interface) layers for both low-code and maximum customizability, and can be used in many different visualization workflows - from interactive scripting and notebooks to user interface applications. Plotly.NET brings the charting capabilities of plotly.js to the .NET ecosystem, successfully combining the flexibility of the plotly grammar with the type-safety and expressiveness of .NET.