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Protein probes, including ultrafiltrates from the placenta (UPla) and lung (ULu) of postnatal rabbits, were investigated in premature senescent HEK293 and HepG2 cells to explore whether they could modulate cellular senescence. Tris-Tricine–PAGE, gene ontology (GO), and LC–MS/MS analysis were applied to describe the characteristics of the ultrafiltrates. HEK293 and HepG2 cells (both under 25 passages) exposed to a sub-toxic concentration of hydrogen peroxide (H2O2, 300 μM) became senescent; UPla (10 μg/mL), ULu (10 μg/mL), as well as positive controls lipoic acid (10 μg/mL) and transferrin (10 μg/mL) were added along with H2O2 to the cells. Cell morphology; cellular proliferation; senescence-associated beta-galactosidase (SA-β-X-gal) activity; expression of senescence biomarkers including p16 INK4A (p16), p21 Waf1/Cip1 (p21), HMGB1, MMP-3, TNF-α, IL-6, lamin B1, and phospho-histone H2A.X (γ-H2AX); senescence-related gene expression; reactive oxygen species (ROS) levels; and mitochondrial fission were examined. Tris-Tricine–PAGE revealed prominent detectable bands between 10 and 100 kDa. LC–MS/MS identified 150–180 proteins and peptides in the protein probes, and GO analysis demonstrated a distinct enrichment of proteins associated with “extracellular space” and “proteasome core complex”. UPla and ULu modulated senescent cell morphology, improved cell proliferation, and decreased beta-galactosidase activity, intracellular and mitochondrial ROS production, and mitochondrial fission caused by H2O2. The results from this study demonstrated that UPla and Ulu, as well as lipoic acid and transferrin, could protect HEK293 and HepG2 cells from H2O2-induced oxidative damage via protecting mitochondrial homeostasis and thus have the potential to be explored in anti-aging therapies.

Background The observational, real-world evidence FLIEDER study aimed to describe patient clinical characteristics and investigate clinical outcomes in non-diabetic patients with chronic kidney disease (CKD) using data collected from routine clinical practice in the United States. Methods Between 1 January, 2008–31 December, 2018, individuals aged ≥ 18 years, with non-diabetic, stage 3–4 CKD were indexed in the Optum® Clinformatics® Data Mart US healthcare claims database using International Classification of Diseases-9/10 codes for CKD or by laboratory values (estimated glomerular filtration rate [eGFR] 15–59 mL/min/1.73 m2). The primary outcomes were hospitalization for heart failure, a composite kidney outcome of end-stage kidney disease/kidney failure/need for dialysis and worsening of CKD stage from baseline. The effects of the intercurrent events of a sustained post-baseline decline in eGFR ≥ 30%, ≥ 40%, and ≥ 57% on the subsequent risk of the primary outcomes were also assessed. Results In the main study cohort (N = 504,924), median age was 75.0 years, and 60.5% were female. Most patients (94.7%) had stage 3 CKD at index. Incidence rates for hospitalization for heart failure, the composite kidney outcome, and worsening of CKD stage from baseline were 4.0, 10.3, and 4.4 events/100 patient-years, respectively. The intercurrent event analysis demonstrated that a relative decline in kidney function from baseline significantly increased the risk of cardiorenal events. Conclusions This real-world study highlights that patients with non-diabetic CKD are at high risk of serious adverse clinical outcomes, and that this risk is amplified in patients who experienced greater post-baseline eGFR decline. Graphical abstract

The American Chemical Society, Division of Chemical Education, Examinations Institute has been developing content maps for the undergraduate program based on subdiscipline specifications since 2008. The Anchoring Concepts Content Maps (or ACCM) have been published in four subdisciplines (general, organic, physical, and inorganic chemistry) with the latest work presented here in a fifth subdiscipline: analytical chemistry. As with the development of the other maps, an alignment process of identifying key components of exam items including content, complexity, and other item characteristics was conducted with both analytical chemistry and instrumental analysis items. The results of the alignments as well as an evaluation of the newest ACCM in relation to the other published maps are presented.

Computational drug sensitivity models have the potential to improve therapeutic outcomes by identifying targeted drug components that are likely to achieve the highest efficacy for a cancer cell line at hand at a therapeutic dose. State of the art drug sensitivity models use regression techniques to predict the inhibitory concentration of a drug for a tumor cell line. This regression objective is not directly aligned with either of these principal goals of drug sensitivity models: We argue that drug sensitivity modeling should be seen as a ranking problem with an optimization criterion that quantifies a drug’s inhibitory capacity for the cancer cell line at hand relative to its toxicity for healthy cells. We derive an extension to the well-established drug sensitivity regression model PaccMann that employs a ranking loss and focuses on the ratio of inhibitory concentration and therapeutic dosage range. We find that the ranking extension significantly enhances the model’s capability to identify the most effective anticancer drugs for unseen tumor cell profiles based in on in-vitro data.

Purpose of the study: Long-term graft survival rates after renal transplantation are still poor. We aimed to build an early predictor of an established long-term outcomes marker, the estimated glomerular filtration rate (eGFR) one year post-transplant (eGFR-1y). Materials and Methods: A large cohort of 376 patients was characterized for a multi-level bio-marker panel including gene expression, cytokines, metabolomics and antibody reactivity profiles. Almost one thousand samples from the pre-transplant and early post-transplant period were analysed and employed for machine learning-assisted prediction. Results: Pre-transplant data led to a prediction achieving a Pearson's correlation coefficient of r=0.38 between measured and predicted eGFR-1y. Two weeks post-transplant, the correlation was improved to r=0.63, and at the third month, to r=0.76. eGFR values were stable throughout the first post-transplant year. Several characteristics were predictive for eGFR, including age of donor and recipient, body mass index, HLA mismatch, cytomegalovirus mismatch and valganciclovir prophylaxis. Additionally, a subset of 19 nuclear magnetic resonance bins of the urine metabolome data was shown to have potential applications in non-invasive eGFR monitoring. Importantly, we identified the expression of the genes TMEM176B and HMMR as potential prognostic markers for changes in the eGFR after the second post-transplantation week. Conclusions: Our multi-center, multi-level data set represents a milestone in the efforts to predict transplant outcome. While an acceptable predictive capacity was achieved, we are still far from predicting changes in the eGFR precisely. Additional studies employing further marker panels are needed to establish predictors of eGFR-1y for clinical application; herein, gene expression markers seem to hold the most promise.

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ApoE4, the strongest genetic risk factor for Alzheimer’s disease (AD), has been shown to be associated with both beta-amyloid (Aβ) and tau pathology, with the strongest evidence for effects on Aβ, while the association between ApoE4 and tau pathology remains inconsistent. This study aimed to investigate the associations between ApoE4 with CSF Aβ42, total tau (t-tau), phospho-tau181 (p-tau), and with the progression of decline in a large cohort of MCI subjects, both progressors to AD and other dementias, as well as non-progressors. We analyzed associations of CSF Aβ42, p-tau and t-tau with ApoE4 allele frequency cross-sectionally and longitudinally over 3 years of follow-up in 195 individuals with a diagnosis of MCI-stable, MCI-AD converters and MCI progressing to other dementias from the German Dementia Competence Network. In the total sample, ApoE4 carriers had lower concentrations of CSF Aβ42, and increased concentrations of t-tau and p-tau compared to non-carriers in a gene dose-dependent manner. Comparisons of these associations stratified by MCI-progression groups showed a significant influence of ApoE4 carriership and diagnostic group on all CSF biomarker levels. The effect of ApoE4 was present in MCI-stable individuals but not in the other groups, with ApoE4 + carriers having decreased CSF Aβ 42 levels, and increased concentration of t-tau and p-tau. Longitudinally, individuals with abnormal t-tau and Aβ42 had a more rapid progression of cognitive and clinical decline, independently of ApoE4 genotype. Overall, our results contribute to an emerging framework in which ApoE4 involves mechanisms associated with both CSF amyloid-β burden and tau aggregation at specific time points in AD pathogenesis.

The conventional method of human oocyte maturation in vitro in the presence of gonadotrophins continues to be a relatively low-success procedure in the assisted conception programme owing to suboptimal maturation conditions in the absence of an ovarian 'niche' and poor understanding of this procedure at the molecular level in oocytes. In this study, the gene expression profiles of human oocytes were analysed according to their manner of maturation: in vivo (in the ovaries) or in vitro (matured either by the conventional method or by a new approach - co-cultured with cumulus cells of mature oocytes from the same patient). Our results show that the in-vitro maturation procedure strongly affects the gene expression profile of human oocytes, including several genes involved in transcriptional regulation, embryogenesis, epigenetics, development, and the cell cycle. The in-vitro maturation of oocytes co-cultured with cumulus cells from mature oocytes provides an ovarian 'niche' to some degree, which improves oocyte maturation rates and their gene expression profile to the extent that they are more comparable to oocytes that naturally mature in the ovarian follicle.

Mesenchymal stem cell (MSC)-derived extracellular vesicles (EVs), which cover both microvesicles (MV) and exosomes, are increasingly in focus for immune-modulatory application as an alternative or substitute in MSC cellular therapy. Experimentally it has been documented that EVs take part in cell-to-cell communication, cell signaling, and changing cell or tissue physiological functions over short or long distances in the organism. It has been observed that MVs and exosomes influence the tissue responses to injury, infection, and disease. MSC-derived EVs contain cytokines, growth factors, signaling lipids, mRNAs, and regulatory miRNAs being able to modify the innate and adaptive immune response. The MSC EVs materials are not static but rather a product of the MSC tissue conditions and can be primed to an anti-inflammatory state.

SummaryAcute cellular rejection (ACR) is associated with complications after kidney transplantation, such as graft dysfunction and graft loss. Early risk assessment is therefore critical for the improvement of transplantation outcomes. In this work, we retrospectively analyzed a pre-transplant HLA antigen bead assay data set that was acquired by the e:KID consortium as part of a systems medicine approach. The data set included single antigen bead (SAB) reactivity profiles of 52 low-risk graft recipients (negative complement dependent cytotoxicity crossmatch, PRA

Oxidation catalysts in emissions control systems generally contain Pd/Pt and require exhaust temperatures above 200 °C to operate, but under low-temperature conditions, oxidation of CO and hydrocarbons are challenging. As engine efficiency improves and exhaust temperature decreases, there is an increasing demand for high emissions control performance at low temperatures. Therefore, it becomes imperative to design new catalysts that are active at low operating temperatures. Au–CuOx catalysts, made through the oxidation of AuCu alloy nanoparticles, have been found to be highly active for the oxidation of CO at low reaction temperatures. The catalytic activity for the conversion of CO using Au–CuOx/SiO2 was evaluated under simulated lean exhaust conditions (CO, C3H6, NO, H2O, O2 and Ar). It was found that the oxidation of CO over the Au–CuOx/SiO2 catalyst was inhibited when C3H6 or NO was introduced into the reaction stream. Interestingly, a physical mixture of Au–CuOx/SiO2 and Pt/Al2O3 worked in synergy to enhance the oxidation of NO to NO2 with 90% conversion near 300 °C in the presence of CO. This reactivity is on par with Pt/Al2O3 NO oxidation activity in the absence of CO. The Au–CuOx/SiO2 catalysts were also found to be thermally stable after being aged up to 700 °C for 10 h. The resistance to particle sintering can be attributed to the CuOx “anchoring” the Au particles to the silica support.

Supported AuCu and AuCuPd catalysts were synthesized through the diffusion of Pd and Cu into Au nanoparticle seeds. When supported on SiO2, the AuCuPd nanoparticles were found to be the most active for the oxidation of CO after being exposed to reductive pretreatment conditions as opposed to oxidative pretreatment conditions. In contrast, AuCu/SiO2 was found to be more active for CO oxidation after the alloy phase was segregated into a Au–CuO x heterostructure. In situ XRD and EXAFS were used to monitor the structural changes of AuCu and AuCuPd catalysts as they were subjected to different pretreatment conditions.

The selective oxidation of ethanol with molecular O2 is increasingly becoming an important process to develop fine chemicals because it can be obtained from renewable biomass feedstock while reducing the demand on fossil fuels. We have synthesized silica-supported Au–Cu alloy nanoparticles, and through an oxidative dealloying process, we have developed Au–CuOx hybrid catalysts for the selective oxidation of ethanol into acetaldehyde. Using a combination of XRD, XPS, and HR-STEM experiments, we have confirmed that the active catalyst is a Au core with a thin CuOx shell. Oxidation of the AuCu/SiO2 alloy catalyst at 300 °C was found to produce the most active and stable catalyst for ethanol conversion (∼90%) with the highest selectivity (∼80–90%) at a reaction temperature of 200 °C for 50 h on-stream. TEM and XRD results show that Au–CuOx/SiO2 catalysts calcined at 300 and 500 °C are also more resistant to sintering during pretreatment and catalytic conditions than pure gold supported on silica. Furthermore,...

In an effort to determine the active state of supported palladium for the direct formation of H2O2 from H2 and O2, the catalytic behavior of Pd0/SiO2, PdO/SiO2 and partially reduced PdO/SiO2 was determined. The results obtained in an ethanol slurry, with chloride ions and H2SO4 being present, showed that the PdO/SiO2 catalyst was almost completely inactive for the formation of H2O2 at 10 °C. The Pd0/SiO2 catalyst exhibited the highest activity for H2O2 formation, and the PdO/SiO2 material, reduced under very mild conditions, exhibited an intermediate activity. The state of Pd on the three catalysts was characterized by XRD, TEM and XPS methods. Only Pd0 (the metal phase) and PdO were observed on Pd0/SiO2 and PdO/SiO2, respectively. As expected, with the partially reduced PdO/SiO2 catalyst, both Pd0 and PdO phases were evident. The TEM results revealed that the Pd0 particles decorated the larger PdO particles. The results reported here support the role of metallic palladium, rather than the oxide, as the active phase for the direct formation of H2O2.

The effect of adding Pt to a Pd/SiO 2 catalyst for the direct formation of H 2 O 2 in ethanol that contains H 2 SO 4 and halide ions (Cl − or Br − ) has been investigated. The addition of only 5 atom% Pt to a catalyst that contained 0.5 wt.% Pd resulted in a 2.5-fold increase in the rate of peroxide formation with only a small decrease in selectivity. The addition of substantially more Pt caused a decrease in the selectivity; whereas, the peroxide formation rate depended on the amount of Pt, as well as the type and amount of the halide. The Pt had no significant effect on the particle size distribution of the supported bimetallic catalysts. The positive role of Pt on the rate of H 2 O 2 formation can be understood in terms of an electronic modification through which Pt partially reverses the negative influence that the halides have on hydrogen activation.

Multi-metal nanoparticles, particularly alloys and intermetallic compounds, are useful catalysts for a variety of chemical transformations. Supported intermetallic nanoparticle catalysts are usually prepared by depositing precursors onto a support followed by high-temperature annealing, which is necessary to generate the intermetallic compound but causes sintering and minimizes surface area. Here we show that solution chemistry methods for converting metal nanoparticles into intermetallic compounds are applicable to supported nanoparticle catalyst systems. Unsupported nanocrystalline Pt can be converted to nanocrystalline PtSn, PtPb, PtBi, and FePt3 by reaction with appropriate metal salt solutions under reducing conditions. Similar reactions convert Al2O3, CeO2, and carbon-supported Pt nanoparticles into PtSn, PtPb, PtSb, Pt3Sn, and Cu3Pt. These reactions generate supported alloy and intermetallic nanoparticles directly in solution without the need for high temperature annealing or additional surface stabilizers. These supported intermetallic nanoparticles are catalytically active for chemical transformations such as formic acid oxidation (PtPb/Vulcan) and CO oxidation (Pt3Sn/graphite). Notably, PtPb/Vulcan XC-72 was found to electrocatalytically oxidize formic acid at a lower onset potential (0.1 V) than commercial PtRu/Vulcan XC-72 (0.4 V).

Ternary and quaternary transition metal oxides, which offer a wide variety of important physical properties, are traditionally synthesized using high-temperature reactions that often require several days of heating. A new nanoparticle-directed approach for the rapid low-temperature synthesis of nanocrystalline bulk-scale ternary and quaternary transition metal oxides has been developed. Readily available metal oxide nanoparticles can serve as a robust toolkit of highly reactive reagents, which can be mixed in solution in known ratios to form nanomodulated precursors and rapidly transformed, at relatively low temperatures, into more complex oxides. This approach is initially demonstrated for pyrochlore-type Y2Ti2O7 and Eu2Ti2O7 using XRD, DSC, and TEM to monitor the reaction. A nanocomposite of Y2O3 and TiO2 nanoparticles transforms into nanocrystalline Y2Ti2O7 within 2 h of heating to 700 °C, and Eu2Ti2O7 forms within 2 h of heating a nanocomposite of Eu2O3 and TiO2 nanoparticles to 800 °C. NiTiO3, CoTiO3...

The Mathematics and Science Collaborative Project is an action research effort between the University of New Hampshire and four middle- and junior high schools in the Durham, NH area designed to develop integrated mathematics and science curriculum materials. The original goals of the project focused on school-university collaboration and team effectiveness among mathematics and science teachers at each site, in order to produce long-term sustained reform in mathematics and science teaching. In this paper, we describe the transformation of the original description of the Mathematics and Science Collaborative Project as its participants and leaders tried to balance the demands of an externally funded project with the practitioners' need to control the project's content and process. The story is told as four “fables” from the perspectives of the four university collaborators who found that they had to significantly adjust their thinking and actions as the project progressed.

Background: Different immunotherapy approaches for the treatment of cancer and autoimmune diseases are being developed and tested in clinical studies worldwide. Their resulting complex experimental data should be properly evaluated, therefore reliable normal healthy control baseline values are indispensable. Methodology/Principal Findings: To assess intra- and inter-individual variability of various biomarkers, peripheral blood of 16 age and gender equilibrated healthy volunteers was sampled on 3 different days within a period of one month. Complex "crossomics'' analyses of plasma metabolite profiles, antibody concentrations and lymphocyte subset counts as well as whole genome expression profiling in CD4(+)T and NK cells were performed. Some of the observed age, gender and BMI dependences are in agreement with the existing knowledge, like negative correlation between sex hormone levels and age or BMI related increase in lipids and soluble sugars. Thus we can assume that the distribution of all 39.743 analysed markers is well representing the normal Caucasoid population. All lymphocyte subsets, 20% of metabolites and less than 10% of genes, were identified as highly variable in our dataset. Conclusions/Significance: Our study shows that the intra- individual variability was at least two-fold lower compared to the inter-individual one at all investigated levels, showing the importance of personalised medicine approach from yet another perspective.

Background Diabetes like many diseases and biological processes is not mono-causal. On the one hand multi-factorial studies with complex experimental design are required for its comprehensive analysis. On the other hand, the data from these studies often include a substantial amount of redundancy such as proteins that are typically represented by a multitude of peptides. Coping simultaneously with both complexities (experimental and technological) makes data analysis a challenge for Bioinformatics. Results We present a comprehensive work-flow tailored for analyzing complex data including data from multi-factorial studies. The developed approach aims at revealing effects caused by a distinct combination of experimental factors, in our case genotype and diet. Applying the developed work-flow to the analysis of an established polygenic mouse model for diet-induced type 2 diabetes, we found peptides with significant fold changes exclusively for the combination of a particular strain and diet. Exploitation of redundancy enables the visualization of peptide correlation and provides a natural way of feature selection for classification and prediction. Classification based on the features selected using our approach performs similar to classifications based on more complex feature selection methods. Conclusions The combination of ANOVA and redundancy exploitation allows for identification of biomarker candidates in multi-dimensional MALDI-TOF MS profiling studies with complex experimental design. With respect to feature selection our method provides a fast and intuitive alternative to global optimization strategies with comparable performance. The method is implemented in R and the scripts are available by contacting the corresponding author.

Peak picking is an early key step in MS data analysis. We compare three commonly used approaches to peak picking and discuss their merits by means of statistical analysis. Methods investigated encompass signal-to-noise ratio, continuous wavelet transform, and a correlation-based approach using a Gaussian template. \ud Functionality of the three methods is illustrated and discussed in a practical context using a mass spectral data set created with MALDI-TOF technology. Sensitivity and specificity are investigated using a manually defined reference set of peaks. As an additional criterion, the robustness of the three methods is assessed by a perturbation analysis and illustrated using ROC curves.

Peak picking is an early key step in MS data analysis. We compare three commonly used approaches to peak picking and discuss their merits by means of statistical analysis. Methods investigated encompass signal-to-noise ratio, continuous wavelet transform, and a correlation-based approach using a Gaussian template. Functionality of the three methods is illustrated and discussed in a practical context using a mass spectral data set created with MALDI-TOF technology. Sensitivity and specificity are investigated using a manually defined reference set of peaks. As an additional criterion, the robustness of the three methods is assessed by a perturbation analysis and illustrated using ROC curves.

POGIL implementation strategies organized around issues associated with the large classroom lecture have been compiled by instructors at various institutions and are presented. Issues such as physical space, group and individual accountability, establishing groups, and stakeholder buy-in are addressed.

Pre-operative planning and intra-operative computer interfaces for minimally invasive interventions were investigated with an active robot integrated with a CT scanner. To test the robotic system, a biopsy study was performed using a pig. For pre-operative planning, a virtual needle was superimposed on axial slices and multiplanar reformatted views in correlation with the interventional field. The path of the virtual needle was sent to the robot's controller, and the robot's needle gripper moved into a position congruent with the planned path. Intra-operative controls were then used to drive the needle while keeping the interventionalist's hands out of the direct X-ray beam during CT fluoroscopy. After needle insertion, the imaged and virtual needles were shown to be sufficiently congruent.

Solution chemistry methods have been used to synthesize bimetallic CuPt alloy nanoparticle catalysts with controllable sizes and shapes. By variation of the relative ratios of the oleylamine and oleic acid stabilizers, solvent, and reduction rate, the nanoparticles could be tuned from approximately 2 nm spherical particles to nanorods with diameters of approximately 2.5 nm and aspect ratios tunable from 5:1 to 25:1. These mixed-metal nanoparticles show excellent catalytic properties for CO oxidation, with light-off temperatures that are nearly 200 K below those of conventional supported Pt catalysts.