Well-defined N3 C1 -anchored Single-Metal-Sites for Oxygen Reduction Reaction.

N-, C-, O-, S-coordinated single-metal-sites (SMSs) have garnered significant attention due to the potential for significantly enhanced catalytic capabilities resulting from charge redistribution. However, significant challenges persist in the precise design of well-defined such SMSs, and the fundamental comprehension has long been impeded in case-by-case reports using carbon materials as investigation targets. In this work, the well-defined molecular catalysts with N3 C1 -anchored SMSs, i.e., N-confused metalloporphyrins (NCPor-Ms), are calculated for their catalytic oxygen reduction activity. Then, NCPor-Ms with corresponding N4 -anchored SMSs (metalloporphyrins, Por-Ms), are synthesized for catalytic activity evaluation. Among all, NCPor-Co reaches the top in established volcano plots. NCPor-Co also shows the highest half-wave potential of 0.83 V vs. RHE, which is much better than that of Por-Co (0.77 V vs. RHE). Electron-rich, low band gap and regulated d-band center contribute to the high activity of NCPor-Co. This study delves into the examination of well-defined asymmetric SMS molecular catalysts, encompassing both theoretical and experimental facets. It serves as a pioneering step towards enhancing the fundamental comprehension and facilitating the development of high-performance asymmetric SMS catalysts.

Characterizing Powdered Activated Carbon Treatment of Surface Water Samples Using Polarity-Extended Non-Target Screening Analysis.

Advanced wastewater treatment such as powdered activated carbon (PAC) reduces the load of organic micropollutants entering the aquatic environment. Since mobile and persistent compounds accumulate in water cycles, treatment strategies need to be evaluated for the removal of (very) polar compounds. Thereby, non-targeted analysis gives a global picture of the molecular fingerprint (including these very polar molecules) of water samples. Target and non-target screening were conducted using polarity-extended chromatography hyphenated with mass spectrometry. Samples treated with different types and concentrations of PAC were compared to untreated samples. Molecular features were extracted from the analytical data to determine fold changes, perform a principal component analysis and for significance testing. The results suggest that a part of the polar target analytes was adsorbed but also some byproducts might be formed or desorbed from the PAC.

Investigation of the Variability of Alkaloids in Buxus sempervirens L. Using Multivariate Data Analysis of LC/MS Profiles.

Buxus sempervirens L. is a common ornamental plant in southern and central Europe, and has been used ethopharmacologically against a wide variety of diseases due to it containing nor-triterpene alkaloids of the nor-cycloartane type. Recently, we demonstrated the interesting antiprotozoal potential of some of these compounds. To characterize the temporal variability in the alkaloid profile of two different varieties and their leaves and twigs, 30 different extracts of B. sempervirens were evaluated by Ultra High Performance Liquid Chromatography/positive Mode-Electrospray Ionization Quadrupole Time-of-Flight-Tandem Mass Spectrometry (UHPLC/+ESI-QqTOF-MS/MS). The analytical profiles were thoroughly investigated by various methods of multivariate data analysis (MVDA). A principal component analysis (PCA) model elucidates the seasonal variation in the phytochemical composition of B. sempervirens var. arborescens and suffruticosa along with differences between the varieties. Analysis of a volcano plot illustrated the differences between the two organs, the leaf and twig. Eighteen compounds were highlighted by the models as constituents of the plant characteristic for a season, variety or organ. These compounds were dereplicated based on their chromatographic and +ESI-QqTOF-MS and -MS/MS data. In addition, mass spectral fragmentation pathways for already known alkaloids as well as new natural products could be postulated for the first time. In conclusion, the MVDA models give detailed information on the temporal variability in the alkaloid profile of two different varieties and their organs (leaf vs. twig) of B. sempervirens. Thus, the results of this study allow, e.g., the identification of characteristic compounds for the different varieties, plant organs, seasons, and the optimal harvesting time for the isolation of particular Buxus-alkaloids of interest for subsequent studies.

Does a Thermoneutral Electrocatalyst Correspond to the Apex of a Volcano Plot for a Simple Two-Electron Process?

Volcano analyses have been established as a standard tool in the field of electrocatalysis for assessing the performance of electrodes in a class of materials. The apex of the volcano curve, where the most active electrocatalysts are situated, is commonly defined by a hypothetical ideal material that binds its reaction intermediates thermoneutrally at zero overpotential, in accordance with Sabatier's principle. However, recent studies report a right shift of the apex in a volcano curve, in which the most active electrocatalysts bind their reaction intermediates endergonically rather than thermoneutrally at zero overpotential. Focusing on two-electron process, this Viewpoint addresses the question of how the definition of an optimum catalyst needs to be modified with respect to the requirements of Sabatier's principle when kinetic effects and the applied overpotential are included in the analysis.

Robust volcano plot: identification of differential metabolites in the presence of outliers.

BACKGROUND: The identification of differential metabolites in metabolomics is still a big challenge and plays a prominent role in metabolomics data analyses. Metabolomics datasets often contain outliers because of analytical, experimental, and biological ambiguity, but the currently available differential metabolite identification techniques are sensitive to outliers. RESULTS: We propose a kernel weight based outlier-robust volcano plot for identifying differential metabolites from noisy metabolomics datasets. Two numerical experiments are used to evaluate the performance of the proposed technique against nine existing techniques, including the t-test and the Kruskal-Wallis test. Artificially generated data with outliers reveal that the proposed method results in a lower misclassification error rate and a greater area under the receiver operating characteristic curve compared with existing methods. An experimentally measured breast cancer dataset to which outliers were artificially added reveals that our proposed method produces only two non-overlapping differential metabolites whereas the other nine methods produced between seven and 57 non-overlapping differential metabolites. CONCLUSION: Our data analyses show that the performance of the proposed differential metabolite identification technique is better than that of existing methods. Thus, the proposed method can contribute to analysis of metabolomics data with outliers. The R package and user manual of the proposed method are available at https://github.com/nishithkumarpaul/Rvolcano .

Altered eicosanoid production and phospholipid remodeling during cell culture.

The remodeling of PUFAs by the Lands cycle is responsible for the diversity of phospholipid molecular species found in cells. There have not been detailed studies of the alteration of phospholipid molecular species as a result of serum starvation or depletion of PUFAs that typically occurs during tissue culture. The time-dependent effect of cell culture on phospholipid molecular species in RAW 264.7 cells cultured for 24, 48, or 72 h was examined by lipidomic strategies. These cells were then stimulated to produce arachidonate metabolites derived from the cyclooxygenase pathway, thromboxane B2, PGE2, and PGD2, and the 5-lipoxygenase pathway, leukotriene (LT)B4, LTC4, and 5-HETE, which decreased with increasing time in culture. However, the 5-lipoxygenase metabolites of a 20:3 fatty acid, LTB3, all trans-LTB3, LTC3, and 5-hydroxyeicosatrienoic acid, time-dependently increased. Molecular species of arachidonate containing phospholipids were drastically remodeled during cell culture, with a new 20:3 acyl group being populated into phospholipids to replace increasingly scarce arachidonate. In addition, the amount of TNFα induced by lipopolysaccharide stimulation was significantly increased in the cells cultured for 72 h compared with 24 h, suggesting that the remodeling of PUFAs enhanced inflammatory response. These studies supported the rapid operation of the Lands cycle to maintain cell growth and viability by populating PUFA species; however, without sufficient n-6 fatty acids, 20:3 n-9 accumulated, resulting in altered lipid mediator biosynthesis and inflammatory response.

Dysfunction of dendritic cells in aged C57BL/6 mice leads to failure of natural killer cell activation and of tumor eradication.

The reciprocal activation of dendritic cells (DCs) and natural killer cells (NKs) plays a key role in both innate and adaptive immunity. The effect of aging on this cross-talk, a critical step in virus disease control and tumor immunology, has not been reported. Splenic DCs and NKs were purified from both young and old C57BL/6 mice and cocultured in the presence of polyinosinic:polycytidylic acid (poly I:C). The resulting activation of NKs was measured as expression of CD69 and secretion of IFN-γ. However, DCs from old mice could not activate NKs from either young or old mice in vitro or in vivo. In contrast, DCs from young mice efficiently activated NKs from both young and old mice. DCs from old mice were deficient in poly I:C-stimulated secretion of IL-15, IL-18, and IFN-α. Gene expression analysis revealed many other differences between DCs of old and young mice. Young mice strongly eradicated MHC class I-negative NK-sensitive RMA-S lymphoma mutant tumor cells, but old mice did not, in concert with the previous report that mousepox kills aged, but not young, C57BL/6 mice. Furthermore, a similar dysfunction of DC and its key role in NK activation was found in 27 out of 55 healthy human donors.

A High-Entropy Single-Atom Catalyst Toward Oxygen Reduction Reaction in Acidic and Alkaline Conditions.

The design of high-entropy single-atom catalysts (HESAC) with 5.2 times higher entropy compared to single-atom catalysts (SAC) is proposed, by using four different metals (FeCoNiRu-HESAC) for oxygen reduction reaction (ORR). Fe active sites with intermetallic distances of 6.1 Å exhibit a low ORR overpotential of 0.44 V, which originates from weakening the adsorption of OH intermediates. Based on density functional theory (DFT) findings, the FeCoNiRu-HESAC with a nitrogen-doped sample were synthesized. The atomic structures are confirmed with X-ray photoelectron spectroscopy (XPS), X-ray absorption (XAS), and scanning transmission electron microscopy (STEM). The predicted high catalytic activity is experimentally verified, finding that FeCoNiRu-HESAC has overpotentials of 0.41 and 0.37 V with Tafel slopes of 101 and 210 mVdec-1 at the current density of 1 mA cm-2 and the kinetic current densities of 8.2 and 5.3 mA cm-2, respectively, in acidic and alkaline electrolytes. These results are comparable with Pt/C. The FeCoNiRu-HESAC is used for Zinc-air battery applications with an open circuit potential of 1.39 V and power density of 0.16 W cm-2. Therefore, a strategy guided by DFT is provided for the rational design of HESAC which can be replaced with high-cost Pt catalysts toward ORR and beyond.

Electrochemical production of hydroxylamine from nitrate on metal electrodes: A comparative study of selectivity and efficiency.

Despite the great potential of electrochemical nitrate reduction as a hydroxylamine production method, this strategy has not been sufficiently examined, and the effects of electrode material type on the selectivity and efficiency of this reduction remain underexplored. To bridge this gap, the present study evaluated six metals (Ag, Cu, Ni, Sn, Ti, and Zn) as cathode materials for the electrochemical reduction of nitrate to hydroxylamine, showing that the selectivity of hydroxylamine production was maximal for Sn, while the corresponding faradaic and energy utilization efficiencies were maximal for Ti. Although all tested materials favored nitrate reduction over hydrogen evolution, the disparity in the onset potentials of these reactions did not adequately explain the variations in nitrate removal efficiency, which was found to be influenced by material resistance and charge-transfer properties. The rate constants of elementary nitrate reduction steps determined from the time-dependent concentrations of nitrate and its reduction products (nitrous acid, hydroxylamine, and ammonium) were used to calculate the selectivity and efficiency of hydroxylamine production for each electrode. In turn, these selectivities and efficiencies were correlated with the density functional theory-computed adsorption energies of a key hydroxylamine precursor on different electrodes to afford a volcano-type plot with Ti and Sn at its pinnacle. Thus, this study introduces valuable descriptors and methods for the further screening of electrocatalysts for hydroxylamine generation and the establishment of more environmentally friendly hydroxylamine production techniques utilizing sustainable electricity.

Temperature-dependent mycotoxins production investigation in Alternaria infected cherry by ultra-high performance liquid chromatography and Orbitrap high resolution mass spectrometry.

For temperature-dependent Alternaria mycotoxins production analysis, cherry samples were inoculated with Alternaria sp. and incubated at two different temperatures (4 °C and 25 °C). Six Alternaria mycotoxins, including altenuene (ALT), alternariol monomethyl ether (AME), alternariol (AOH), altertoxin-I (ATX-I), tenuazonic acid (TeA), and tentoxin (TEN), in cherries were detected with integrated visible data-processing tools. Maximum concentration of these mycotoxins reached 71,862.2 µg/kg at 25 °C. Notably, considerable amount of TeA (290.4 µg/kg) was detected at 4 °C, which indicated that low temperature is not a safe storage condition for fruits. A total of 102 compounds were detected with a neutral loss of 162.0528 Da, and TeA-glucose was identified in this work. Based on MS/MS cosine similarity, products were verified and annotated with feature based molecular networking (FBMN) in global natural products social networking (GNPS). The results showed Alternaria mycotoxins in cherry samples were mainly demethylation, hydrogenation, and dehydration. This work revealed the production of Alternaria mycotoxins in cherries under different storage temperature, which will provide theoretical basis for the control of mycotoxin contamination in food commodities.

Importance of the Walden Inversion for the Activity Volcano Plot of Oxygen Evolution.

Since the birth of the computational hydrogen electrode approach, it is considered that activity trends of electrocatalysts in a homologous series can be quantified by the construction of volcano plots. This method aims to steer materials discovery by the identification of catalysts with an improved reaction kinetics, though evaluated by means of thermodynamic descriptors. The conventional approach for the volcano plot of the oxygen evolution reaction (OER) relies on the assumption of the mononuclear mechanism, comprising the * OH, * O, and * OOH intermediates. In the present manuscript, two new mechanistic pathways, comprising the idea of the Walden inversion in that bond-breaking and bond-making occurs simultaneously, are factored into a potential-dependent OER activity volcano plot. Surprisingly, it turns out that the Walden inversion plays an important role since the activity volcano is governed by mechanistic pathways comprising Walden steps rather than by the traditionally assumed reaction mechanisms under typical OER conditions.

Statistical plots in oncologic imaging, a primer for neuroradiologists.

The simplest approach to convey the results of scientific analysis, which can include complex comparisons, is typically through the use of visual items, including figures and plots. These statistical plots play a critical role in scientific studies, making data more accessible, engaging, and informative. A growing number of visual representations have been utilized recently to graphically display the results of oncologic imaging, including radiomic and radiogenomic studies. Here, we review the applications, distinct properties, benefits, and drawbacks of various statistical plots. Furthermore, we provide neuroradiologists with a comprehensive understanding of how to use these plots to effectively communicate analytical results based on imaging data.

Analysis of Corticosteroid-Induced Glaucoma Using the Japanese Adverse Drug Event Reporting Database.

Glaucoma is the most common cause of blindness, which significantly reduces quality of life. Most glaucoma cases are primary glaucoma; nevertheless, many patients suffer from glaucoma caused by drugs, such as corticosteroids. A comprehensive review of the risks associated with corticosteroid-induced glaucoma is limited. Therefore, we used the Japanese Adverse Drug Event Reporting Database (JADER) published by the Pharmaceuticals and Medical Devices Agency (PMDA) to analyze the risk factors associated with glaucoma and the trends and characteristics of corticosteroid-induced glaucoma. We did not find sex or age differences associated with the onset of glaucoma. Hierarchical clustering and principal component analysis revealed that triamcinolone acetonide and betamethasone sodium phosphate, which are used around the eyes in Japan, are more likely to induce intraocular pressure (IOP) elevation compared with other corticosteroids. Increased IOP is a direct cause of glaucoma. Based on these findings, it may be necessary to limit or avoid the use of these corticosteroids.

Identifying Crude Drugs in Kampo Medicines Associated with Drug-Induced Liver Injury Using the Japanese Adverse Drug Event Report Database: A Comprehensive Survey.

The current study aimed to identify the crude drugs associated with drug-induced liver injury (DILI) in 148 Kampo medicines prescribed throughout Japan using the Japanese Adverse Drug Event Report (JADER) database, a large-scale spontaneous reporting system in Japan. First, we tabulated the number of DILI reports from the report-based dataset and the background information from the patient-based dataset. Thereafter, we combined the 126 crude drugs into 104 crude drug groups to examine multicollinearity. Finally, the reporting odds ratios (RORs), 95% confidence intervals, p values for Fisher's exact test, and number of reports were calculated for each crude group to identify those associated with DILI. Notably, the number of adverse event reports for DILI (63,955) exceeded that for interstitial lung disease (51,347), the most common adverse event. In total, 78 crude drug groups (90 crude drugs) were reported to have an ROR > 1, a p < 0.05, and ≥10 reported cases. Our results highlight DILI as an essential issue, given that it was among the most frequently reported adverse drug reactions. We were able to clearly identify the crude drugs associated with DILI, which could help manage adverse drug reactions attributed to Kampo medicines and crude drugs.

Uneven Stripping Behavior, an Unheeded Killer of Mg Anodes.

Uniform magnesium (Mg) plating/stripping under high areal capacity utilization is critical for the practical application of Mg-metal anodes in rechargeable Mg batteries. However, the failure of the Mg-metal anode when cycling under a practical areal capacity (>4 mA h cm-2 ), is of rising concern. The mechanism behind these failures remains controversial. In this work, it is illustrated that the initial plating Mg can be undoubtedly uniform in a wide range of current densities (≤5 mA cm-2 ) and under a practical areal capacity (6 mA h cm-2 ). However, an unusual self-accelerating pit growth is observed in the Mg stripping side under moderate current densities (0.1-1 mA cm-2 ), which severely deteriorates the anode integrity and subsequent Mg plating uniformity, causing failure of the Mg-metal anode or short circuit of the battery. The stripping morphology depends on the applied current density, as non-uniformity versus the current density displays a volcano plot during the stripping process. Through in situ spectroscopy, it is illustrated that this current-dependent behavior is determined by the evolution of chlorine-containing complex ions near the interface. This research reminds that the plating/stripping process of the Mg-metal anode must be considered comprehensively for practical Mg-metal batteries.

Computational Analysis of Structure - Activity Relationships in Highly Active Homogeneous Ruthenium-based Water Oxidation Catalysts.

Linear free energy scaling relationships (LFESRs) and regression analysis may predict the catalytic performance of heterogeneous and recently, homogenous water oxidation catalysts (WOCs). This study analyses twelve homogeneous Ru-based catalysts - some, the most active catalysts studied: the Ru(tpy-R)(QC) and Ru(tpy-R)(4-pic)2 catalysts, where tpy is 2,2:6,2-terpyridine, QC is 8-quinolinecarboxylate and 4-pic is 4-picoline. Typical relationships studied among heterogenous and solid-state catalysts cannot be broadly applied to homogeneous catalysts. This subset of structurally similar catalysts with impressive catalytic activity deserves closer computational and statistical analysis of energetics correlating with measured catalytic activity. We report general methods of LFESR analysis yield insufficiently robust relationships between descriptor variables. However, volcano plot-based analysis grounded in Sabatier's principle reveals ranges of ideal relative energies of the RuIV=O and RuIV-OH intermediates and optimal changes in free energies of water nucleophilic attack on RuV=O. A narrow range of RuIV-OH to RuV=O redox potentials corresponding with the highest catalytic activities suggests facile access to the catalytically competent high-valent RuV=O state, often inaccessible from RuIV=O. Our work introduces experimental oxygen evolution rates into approaches of LFESR and Sabatier principle-based analysis, identifying a narrow yet fertile energetic landscape to bountiful oxygen-evolution activity, leading future rational design.

Metal Effect Meets Volcano Plots: A DFT Study on Tris(phosphino)borane-Transition Metal Complexes Catalyzed H2 Activation.

Bifunctional transition metal complexes are of particular interest in metal-ligand cooperative activation of small molecules. As a novel type of bifunctional catalyst, Lewis acid transition metal (LA-TM) complexes have attracted increasing interest in hydrogen activation and storage. To advance the catalyst design, herein the metal effect of LA-TM complexes on the hydrogen activation has been systematically studied with a series of tris(phosphino)borane (TPB) complexes with V, Cr, Mn, Fe, Co, and Ni as metal centers. The metal effect not only influences the mechanism of hydrogen activation, but also notably casts a volcano plot for the activity. TPB complexes of V, Cr, Mn, Fe, and Co tend to activate H2 through a stepwise mechanism, while TPB-Ni prefers a synergetic mechanism for H2 activation. More importantly, the metal effect significantly influences the activity of H2 activation and the formation of the LA-H-TM bridging hydride. The trend of changes in the LA-H-TM structures, the second-order perturbation stabilization energies, and the Laplacian bond orders, along with different metals (from V to Ni), are all interestingly constitute volcano plots for the performance of TPB-TM complexes catalyzed H2 activation. TPB-Mn and TPB-Fe are found to be the optimal catalysts among the discussed TPB-TM complexes. The volcano plots disclosed for the metal effects should be informative and instructive for homogeneous and heterogeneous LA-TM catalysts development.

ggVolcanoR: A Shiny app for customizable visualization of differential expression datasets.

Volcano and other analytical plots (e.g., correlation plots, upset plots, and heatmaps) serve as important data visualization methods for transcriptomic and proteomic analyses. Customizable generation of these plots is fundamentally important for a better understanding of dysregulated expression data and is therefore instrumental for the ensuing pathway analysis and biomarker identification. Here, we present an R-based Shiny application, termed ggVolcanoR, to allow for customizable generation and visualization of volcano plots, correlation plots, upset plots, and heatmaps for differential expression datasets, via a user-friendly interactive interface in both local executable version and web-based application without requiring programming expertise. Compared to currently existing packages, ggVolcanoR offers more practical options to optimize the generation of publication-quality volcano and other analytical plots for analyzing and comparing dysregulated genes/proteins across multiple differential expression datasets. In addition, ggVolcanoR provides an option to download the customized list of the filtered dysregulated expression data, which can be directly used as input for downstream pathway analysis. The source code of ggVolcanoR is available at https://github.com/KerryAM-R/ggVolcanoR and the webserver of ggVolcanoR 1.0 has been deployed and is freely available for academic purposes at https://ggvolcanor.erc.monash.edu/.

Important Issues in Planning a Proteomics Experiment: Statistical Considerations of Quantitative Proteomic Data.

Mass spectrometry is frequently used in quantitative proteomics to detect differentially regulated proteins. A very important but unfortunately oftentimes neglected part in detecting differential proteins is the statistical analysis. Data from proteomics experiments are usually high-dimensional and hence require profound statistical methods. It is especially important to already correctly design a proteomic experiment before it is conducted in the laboratory. Only this can ensure that the statistical analysis is capable of detecting truly differential proteins afterward. This chapter thus covers aspects of both statistical planning as well as the actual analysis of quantitative proteomic experiments.

Identification of critical chemical modifications and paratope mapping by size exclusion chromatography of stressed antibody-target complexes.

Therapeutic proteins including antibodies and Fc-fusion proteins undergo a large number of chemical modifications during cell culture, purification, storage and in human circulation. They are also exposed to harsh conditions during stress studies, including elevated temperature, extremes of pH, forced oxidation, physiological pH, UV light to assess the possible degradation pathways and suitability of methods for detecting them. Some of these modifications are located on residues in binding regions, leading to loss of binding and potency and classified as critical quality attributes. Currently, criticality of modifications is assessed by a laborious process of collecting antibody fractions from the soft chromatography techniques ion exchange and hydrophobic interaction chromatography and characterizing the fractions one-by-one for potency and chemical modifications. Here, we describe a method for large-scale, parallel identification of all critical chemical modifications in one experiment. In the first step, the antibody is stressed by one or several stress methods. It is then mixed with target protein and separated by size-exclusion chromatography (SEC) on bound antibody-target complex and unbound antibody. Peptide mapping of fractions and statistical analysis are performed to identify modifications on amino acid residues that affect binding. To identify the modifications leading to slight decreases in binding, competitive SEC of antibody and antigen mixtures was developed and described in a companion study by Shi et al, where target protein is provided at lower level, below the stoichiometry. The newly described method was successfully correlated to crystallography for assessing criticality of chemical modifications and paratope mapping. It is more sensitive to low-level modifications, better streamlined and platform ready.