On a productive dialogue between religion and science

Searching for common ground in philosophy, science and theology, it seems to us that it would be reasonable to maintain the position of realistic pragmatism that Charles Sanders Peirce had called pragmaticism. In the pragmaticist manner, we typify the knowledge and select the types of knowledge that might be useful for understanding the problems that are of interest to us. We pose a question of how it would be possible to obtain practically useful information about reality, first from the perspective of natural sciences, and then from that of theology; that is, to diversify the ways of knowledge and just maybe, to move toward a productive dialogue between science and religion

Electrochemical Impedance Spectroscopy Based Biosensors: Mechanistic Principles, Analytical Examples and Challenges towards Commercialization for Assays of Protein Cancer Biomarkers

Impedimetric affinity biosensors are, without any doubt, among the most sensitive analytical devices available, offering low limits of detection and wide linear response ranges. There are, however, only a few papers detailing the application of impedimetric biosensors for the analysis of clinically relevant samples with due clinical performance. The fact that these devices have not found their way to any commercial or clinical use to date might be surprising, since an electrochemical assay platform based on portable potentiostats is a success story for monitoring a range of clinical parameters such as ions, haematological indicators and glucose. This review discusses the reasons behind this discrepancy and addresses the barriers to be overcome in order to achieve the point-of-care diagnostics using such devices for detection of protein oncomarkers approved by FDA. The final part of the review covers the most recent progress in the area.The financial support received from the Slovak Scientific Grant Agency VEGA 2/0137/18 and 2/0090/16 and the Slovak Research and Development Agency APVV 17-0300 and APW-15-0227 is acknowledged. The research received funding from the European Research Council (no. 311532). This publication is the result of the project implementation: Centre for materials, layers and systems for applications and chemical processes under extreme conditions - Stage I, ITMS No.: 26240120007, supported by the ERDF

A graphene-based glycan biosensor for electrochemical label-free detection of a tumor-associated antibody

The study describes development of a glycan biosensor for detection of a tumor-associated antibody. The glycan biosensor is built on an electrochemically activated/oxidized graphene screen-printed electrode (GSPE). Oxygen functionalities were subsequently applied for covalent immobilization of human serum albumin (HSA) as a natural nanoscaffold for covalent immobilization of Thomsen-nouvelle (Tn) antigen (GalNAc-O-Ser/Thr) to be fully available for affinity interaction with its analyte—a tumor-associated antibody. The step by step building process of glycan biosensor development was comprehensively characterized using a battery of techniques (scanning electron microscopy, atomic force microscopy, contact angle measurements, secondary ion mass spectrometry, surface plasmon resonance, Raman and energy-dispersive X-ray spectroscopy). Results suggest that electrochemical oxidation of graphene SPE preferentially oxidizes only the surface of graphene flakes within the graphene SPE. Optimization studies revealed the following optimal parameters: activation potential of +1.5 V vs. Ag/AgCl/3 M KCl, activation time of 60 s and concentration of HSA of 0.1 g L−1. Finally, the glycan biosensor was built up able to selectively and sensitively detect its analyte down to low aM concentration. The binding preference of the glycan biosensor was in an agreement with independent surface plasmon resonance analysis.The financial support received from the Slovak Scientific Grant Agency VEGA 2/0137/18 and 2/0090/16 from the Slovak Research and Development Agency APVV 17-0300 is acknowledged. This publication is the result of the project implementation: Centre for materials, layers and systems for applications and chemical processes under extreme conditions—Stage I, ITMS no.: 26240120007, supported by the ERDF. This publication was supported by Qatar University Collaborative Grant QUCG-CAM-19/20-2. The findings achieved herein are solely the responsibility of the authors.Scopu

Antimicrobial modification of PLA scaffolds with ascorbic and fumaric acids via plasma treatment

An optimal medical scaffold should be biocompatible and biodegradable and should have adequate mechanical properties and scaffold architecture porosity, a precise three-dimensional shape, and a reasonable manufacturing method. Polylactic acid (PLA) is a natural biodegradable thermoplastic aliphatic polyester that can be fabricated into nanofiber structures through many techniques, and electrospinning is one of the most widely used methods. Medical fiber mat scaffolds have been associated with inflammation and infection and, in some cases, have resulted in tissue degradation. Therefore, surface modification with antimicrobial agents represents a suitable solution if the mechanical properties of the fiber mats are not affected. In this study, the surfaces of electrospun PLA fiber mats were modified with naturally occurring L-ascorbic acid (ASA) or fumaric acid (FA) via a plasma treatment method. It was found that 30 s of radio-frequency (RF) plasma treatment was effective enough for the wettability enhancement and hydroperoxide formation needed for subsequent grafting reactions with antimicrobial agents upon their decomposition. This modification led to changes in the surface properties of the PLA fiber mats, which were analyzed by various spectroscopic and microscopic techniques. FTIR-ATR confirmed the chemical composition changes after the modification process and the surface morphology/topography changes were proven by SEM and AFM. Moreover, nanomechanical changes of prepared PLA fiber mats were investigated by AFM using amplitude modulation-frequency modulation (AM-FM) technique. A significant enhancement in antimicrobial activity of such modified PLA fiber mats against gram-positive Staphylococcus aureus and gram-negative Escherichia coli are demonstrated herein. © 2020 The AuthorsQatar National Research Fund (a member of The Qatar Foundation) [22-076-1-011]; Qatar University Collaborative Grant [QUCG-CAM-20/21-3]; Czech Science FoundationGrant Agency of the Czech Republic [19-16861S

Electrochemical system design for CO2 conversion: A comprehensive review

This paper reviews the electrochemical reduction of CO2 and the design of CO2 electrolyzer cells using advanced materials and novel configurations to improve efficiency and reduce costs. It examines various system types based on geometry and components, analyzing key performance parameters to offer valuable insights into effective and selective CO2 conversion. Techno-economic analysis is employed to assess the commercial viability of electrochemical CO2 reduction (eCO2R) products. Additionally, the paper discusses the design of eCO2R reactors, addressing challenges, benefits, and developments associated with reactant supply in liquid and gas phases. It also explores knowledge gaps and areas for improvement to facilitate the development of more efficient eCO2R systems. To compete with gas-fed electrolyzers, the paper presents various approaches to enhance the performance of liquid-fed electrolyzers, leveraging their operation simplicity, scalability, low costs, high selectivity, and reasonable energy requirements. Furthermore, recent reports summarizing the performance parameters of reliable and effective electrocatalysts under ideal operating conditions, in conjunction with different electrolyzer configurations, are highlighted. This overview provides insights into the current state of the field and suggests future research directions for producing valuable chemicals with high energy efficiency (low overpotential). Ultimately, this review equips readers with fundamental knowledge and understanding necessary to improve and optimize eCO2R beyond lab-scale applications, fostering advancements in the promising field.This publication was made possible by the Qatar National Research Fund (a member of Qatar Foundation) under NPRP grant ( NPRP13S-0202-200228 ). H.P. is grateful to the National Research Foundation of Korea ( RS-2023-00254645 , 2018R1A6A1A03024962 , and 2021K1A4A7A02102598 ) and the Korea Evaluation Institute of Industrial Technology (Alchemist Project 20018904 , NTIS-1415180111 ) through the Ministry of Trade, Industry, and Energy, Korea.Scopu

Urban stormwater retention capacity of nature-based solutions at different climatic conditions

Climate change and the continuing increase in human population creates a growing need to tackle urban stormwater problems. One promising mitigation option is by using nature-based solutions (NBS) – especially sustainable urban stormwater management technologies that are key elements of NBS action. We used a synthesis approach to compile available information about urban stormwater retention capacity of the most common sustainable urban drainage systems (SUDS) in different climatic conditions. Those SUDS targeting stormwater management through water retention and removal solutions (mainly by infiltration, overland flow and evapotranspiration), were addressed in this study. Selected SUDS were green roofs, bioretention systems (i.e. rain gardens), buffer and filter strips, vegetated swales, constructed wetlands, and water-pervious pavements. We found that despite a vast amount of data available from real-life applications and research results, there is a lack of decisive information about stormwater retention and removal capacity of selected SUDS. The available data show large variability in performance across different climatic conditions. It is therefore a challenge to set conclusive widely applicable guidelines for SUDS implementation based on available water retention data. Adequate data were available only to evaluate the water retention capacity of green roofs (average 56±20%) and we provide a comprehensive review on this function. However, as with other SUDS, still the same problem of high variability in the performance (min 11% and max 99% of retention) remains. This limits our ability to determine the capacity of green roofs to support better planning and wider implementation across climate zones. The further development of SUDS to support urban stormwater retention should be informed by and developed concurrently with the adaptation strategies to cope with climate change, especially with increasing frequency of extreme precipitation events that lead to high volumes of stormwater runoff

Assessment of predicted enzymatic activity of α‐N‐acetylglucosaminidase variants of unknown significance for CAGI 2016

The NAGLU challenge of the fourth edition of the Critical Assessment of Genome Interpretation experiment (CAGI4) in 2016, invited participants to predict the impact of variants of unknown significance (VUS) on the enzymatic activity of the lysosomal hydrolase α‐N‐acetylglucosaminidase (NAGLU). Deficiencies in NAGLU activity lead to a rare, monogenic, recessive lysosomal storage disorder, Sanfilippo syndrome type B (MPS type IIIB). This challenge attracted 17 submissions from 10 groups. We observed that top models were able to predict the impact of missense mutations on enzymatic activity with Pearson's correlation coefficients of up to .61. We also observed that top methods were significantly more correlated with each other than they were with observed enzymatic activity values, which we believe speaks to the importance of sequence conservation across the different methods. Improved functional predictions on the VUS will help population‐scale analysis of disease epidemiology and rare variant association analysis

DNA isolation protocol effects on nuclear DNA analysis by microarrays, droplet digital PCR, and whole genome sequencing, and on mitochondrial DNA copy number estimation.

Potential bias introduced during DNA isolation is inadequately explored, although it could have significant impact on downstream analysis. To investigate this in human brain, we isolated DNA from cerebellum and frontal cortex using spin columns under different conditions, and salting-out. We first analysed DNA using array CGH, which revealed a striking wave pattern suggesting primarily GC-rich cerebellar losses, even against matched frontal cortex DNA, with a similar pattern on a SNP array. The aCGH changes varied with the isolation protocol. Droplet digital PCR of two genes also showed protocol-dependent losses. Whole genome sequencing showed GC-dependent variation in coverage with spin column isolation from cerebellum. We also extracted and sequenced DNA from substantia nigra using salting-out and phenol / chloroform. The mtDNA copy number, assessed by reads mapping to the mitochondrial genome, was higher in substantia nigra when using phenol / chloroform. We thus provide evidence for significant method-dependent bias in DNA isolation from human brain, as reported in rat tissues. This may contribute to array "waves", and could affect copy number determination, particularly if mosaicism is being sought, and sequencing coverage. Variations in isolation protocol may also affect apparent mtDNA abundance

Soluble CD44 Interacts with Intermediate Filament Protein Vimentin on Endothelial Cell Surface

CD44 is a cell surface glycoprotein that functions as hyaluronan receptor. Mouse and human serum contain substantial amounts of soluble CD44, generated either by shedding or alternative splicing. During inflammation and in cancer patients serum levels of soluble CD44 are significantly increased. Experimentally, soluble CD44 overexpression blocks cancer cell adhesion to HA. We have previously found that recombinant CD44 hyaluronan binding domain (CD44HABD) and its non-HA-binding mutant inhibited tumor xenograft growth, angiogenesis, and endothelial cell proliferation. These data suggested an additional target other than HA for CD44HABD. By using non-HA-binding CD44HABD Arg41Ala, Arg78Ser, and Tyr79Ser-triple mutant (CD443MUT) we have identified intermediate filament protein vimentin as a novel interaction partner of CD44. We found that vimentin is expressed on the cell surface of human umbilical vein endothelial cells (HUVEC). Endogenous CD44 and vimentin coprecipitate from HUVECs, and when overexpressed in vimentin-negative MCF-7 cells. By using deletion mutants, we found that CD44HABD and CD443MUT bind vimentin N-terminal head domain. CD443MUT binds vimentin in solution with a Kd in range of 12–37 nM, and immobilised vimentin with Kd of 74 nM. CD443MUT binds to HUVEC and recombinant vimentin displaces CD443MUT from its binding sites. CD44HABD and CD443MUT were internalized by wild-type endothelial cells, but not by lung endothelial cells isolated from vimentin knock-out mice. Together, these data suggest that vimentin provides a specific binding site for soluble CD44 on endothelial cells

Gap-filling eddy covariance methane fluxes:Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an improved baseline of, methane gap-filling models that can be implemented in multi-site syntheses or standardized products from regional and global flux networks (e.g., FLUXNET)