Pyrolysis-catalysis upcycling of waste plastic using a multilayer stainless-steel catalyst toward a circular economy.

Current un-sustainable plastic management is exacerbating plastic pollution, an urgent shift is thus needed to create a recycling society. Such recovering carbon (C) and hydrogen (H) from waste plastic has been considered as one practical route to achieve a circular economy. Here, we performed a simple pyrolysis-catalysis deconstruction of waste plastic via a monolithic multilayer stainless-steel mesh catalyst to produce multiwalled carbon nanotubes (MWCNTs) and H2, which are important carbon material and energy carrier to achieve sustainable development. Results revealed that the C and H recovery efficiencies were as high as 86% and 70%, respectively. The unique oxidation-reduction process and improvement of surface roughness led to efficient exposure of active sites, which increased MWCNTs by suppressing macromolecule hydrocarbons. The C recovery efficiency declined by only 5% after 10 cycles, proving the long-term employment of the catalyst. This catalyst can efficiently convert aromatics to MWCNTs by the vapor-solid-solid mechanism and demonstrate good universality in processing different kinds of waste plastics. The produced MWCNTs showed potential in applications of lithium-ion batteries and telecommunication. Owing to the economic profits and environmental benefits of the developed route, we highlighted its potential as a promising alternative to conventional incineration, simultaneously achieving the waste-to-resource strategy and circular economy.

Chandipura viral glycoprotein (CNV-G) promotes Gectosome generation and enables delivery of intracellular therapeutics.

Overexpression of vesicular stomatitis virus G protein (VSV-G) elevates the secretion of EVs known as gectosomes, which contain VSV-G. Such vesicles can be engineered to deliver therapeutic macromolecules. We investigated viral glycoproteins from several viruses for their potential in gectosome production and intracellular cargo delivery. Expression of the viral glycoprotein (viral glycoprotein from the Chandipura virus [CNV-G]) from the human neurotropic pathogen Chandipura virus in 293T cells significantly augments the production of CNV-G-containing gectosomes. In comparison with VSV-G gectosomes, CNV-G gectosomes exhibit heightened selectivity toward specific cell types, including primary cells and tumor cell lines. Consistent with the differential tropism between CNV-G and VSV-G gectosomes, cellular entry of CNV-G gectosome is independent of the Low-density lipoprotein receptor, which is essential for VSV-G entry, and shows varying sensitivity to pharmacological modulators. CNV-G gectosomes efficiently deliver diverse intracellular cargos for genomic modification or responses to stimuli in vitro and in the brain of mice in vivo utilizing a split GFP and chemical-induced dimerization system. Pharmacokinetics and biodistribution analyses support CNV-G gectosomes as a versatile platform for delivering macromolecular therapeutics intracellularly.

Dealkylation of Macromolecules by Eukaryotic α-Ketoglutarate-Dependent Dioxygenases from the AlkB-like Family.

Alkylating modifications induced by either exogenous chemical agents or endogenous metabolites are some of the main types of damage to DNA, RNA, and proteins in the cell. Although research in recent decades has been almost entirely devoted to the repair of alkyl and in particular methyl DNA damage, more and more data lately suggest that the methylation of RNA bases plays an equally important role in normal functioning and in the development of diseases. Among the most prominent participants in the repair of methylation-induced DNA and RNA damage are human homologs of Escherichia coli AlkB, nonheme Fe(II)/α-ketoglutarate-dependent dioxygenases ABH1-8, and FTO. Moreover, some of these enzymes have been found to act on several protein targets. In this review, we present up-to-date data on specific features of protein structure, substrate specificity, known roles in the organism, and consequences of disfunction of each of the nine human homologs of AlkB. Special attention is given to reports about the effects of natural single-nucleotide polymorphisms on the activity of these enzymes and to potential consequences for carriers of such natural variants.

Multiparametric exchange protons using Z-spectrum analysis proton (ZAP) and CEST on phantoms and human abdomen.

PURPOSE: This study aims to investigate a multiparametric exchange proton approach using CEST and Z-spectrum analysis protons (ZAP) in human abdominal organs, focusing on tissue differentiation for a potential early biomarker of abnormality. Prior to human studies, CEST and ZAP effects were studied in phantoms containing exchange protons. METHODS: Phantoms composed of iopamidol and iohexol solutions with varying pH levels, along with 12 human subjects, were scanned on a clinical 3T MR scanner. Subsequent ZAP analyses employed a two-Lorentzian pool model to provide free and restricted apparent T 2 f , r ex $$ {\mathrm{T}}_{2\ \mathrm{f},\mathrm{r}}^{\mathrm{ex}} $$ , and their fractions for data acquired across a wide range of offset frequencies (±100 kHz or ± 800 ppm), while a narrower range (±7 ppm or ± 900 Hz) was used for CEST analysis to estimate magnetization transfer ratio asymmetry (MTRAsym) for exchange protons like hydroxyl (-OH), amine (-NH2), and amide (-NH), resonating ˜1, 2, and 3.5 ppm, respectively. Differences in ZAP metrics across various organs were statistically analyzed using one-way analysis of variance (ANOVA). RESULTS: The phantom study differentiated contrast agents based on resonance peaks detected from CEST analysis, while ZAP metrics showed sensitivity to pH variations. In human, ZAP metrics revealed significant differences in abdominal organs, with a subgroup study indicating changes in ZAP metrics due to the presence of gallstones. CONCLUSION: CEST and ZAP techniques demonstrated promise in specific CEST protons and wide range ZAP protons and identifying tissue-specific characteristics. The preliminary findings underscore the necessity for more extensive study involving a broader subject pool to potentially establish biomarkers for diseased states.

Macromolecular Nano-Assemblies for Enhancing the Effect of Oxygen-Dependent Photodynamic Therapy Against Hypoxic Tumors.

In oxygen (O2)-dependent photodynamic therapy (PDT), photosensitizers absorb light energy, which is then transferred to ambient O2 and subsequently generates cytotoxic singlet oxygen (1O2). Therefore, the availability of O2 and the utilization efficiency of generated 1O2 are two significant factors that influence the effectiveness of PDT. However, tumor microenvironments (TMEs) characterized by hypoxia and limited utilization efficiency of 1O2 resulting from its short half-life and short diffusion distance significantly restrict the applicability of PDT for hypoxic tumors. To address these challenges, numerous macromolecular nano-assemblies (MNAs) have been designed to relieve hypoxia, utilize hypoxia or enhance the utilization efficiency of 1O2. Herein, we provide a comprehensive review on recent advancements achieved with MNAs in enhancing the effectiveness of O2-dependent PDT against hypoxic tumors.

Validation of the Absorption-Enhancing Ability of Oligoarginines Grafted onto a Backbone of Hyaluronic Acid through Animal Studies from Rodents to Primates.

The purpose of our research is to develop functional additives that enhance mucosal absorption of biologics, such as peptide/protein and antibody drugs, to provide their non-to-poor invasive dosage forms self-managed by patients. Our previous in vivo and in vitro studies demonstrated that the intranasal absorption of biologics in mice was significantly improved when coadministered with oligoarginines anchored chemically to hyaluronic acid via a glycine spacer, presumably through syndecan-4-mediated macropinocytosis under activation by oligoarginines. The present mouse experiments first revealed that diglycine-L-tetraarginine-linked hyaluronic acid significantly enhanced the intranasal absorption of sulpiride, which is a poor-absorptive organic compound with a low molecular weight. However, similar enhancement was not observed for levofloxacin, which has a similarly low molecular weight but is a well-absorptive organic compound, probably because its absorption was mostly dominated by passive diffusion. The subsequent monkey experiments revealed that there was no species difference in the absorption-enhancing ability of diglycine-L-tetraarginine-linked hyaluronic acid for not only organic compounds but also biologics. This was presumably because the expression levels of endocytosis-associated membrane proteins on the nasal mucosa in monkeys were almost equivalent to those in mice, and poorly membrane-permeable/membrane-impermeable drugs were mainly absorbed via syndecan-4-mediated macropinocytosis, regardless of animal species. Drug concentrations in the brain assessed in mice and monkeys and those in the cerebral spinal fluids (CSFs) assessed in monkeys indicated that drugs would be delivered from the systemic circulation to the central nervous system by crossing the blood-brain and the blood-CSF barriers under coadministration with the hyaluronic acid derivative. In line with our original hypothesis, this new set of data supported that our oligoarginine-linked hyaluronic acid would locally perform on the mucosal surface and enhance the membrane permeation of drugs under its colocalization.

AAV-aMTD-Parkin, a therapeutic gene delivery cargo, enhances motor and cognitive functions in Parkinson's and Alzheimer's diseases.

Neurodegenerative disorders, such as Parkinson's disease (PD) and Alzheimer's disease (AD), have a global prevalence and profoundly impact both motor and cognitive functions. Although adeno-associated virus (AAV)-based gene therapy has shown promise, its application for treating central nervous system (CNS) diseases faces several challenges, including effective delivery of AAV vectors across the blood-brain barrier, determining optimal dosages, and achieving targeted distribution. To address these challenges, we have developed a fusion delivery therapeutic cargo called AAV-aMTD-Parkin, which combines a hydrophobic cell-penetrating peptide sequence with the DNA sequences of AAV and Parkin. By employing this fusion delivery platform at lower dosages compared to zolgensma, we have achieved significant enhancements in cell and tissue permeability, while reducing the occurrence of common pathological protein aggregates. Consequently, motor and cognitive functions were restored in animal models of PD and AD. With its dual functionality in addressing PD and AD, AAV-aMTD-Parkin holds immense potential as a novel class of therapeutic biologics for prevalent CNS diseases.

Cellular junction dynamics and Alzheimer's disease: a comprehensive review.

Alzheimer's disease (AD) is a prevalent neurodegenerative disorder characterized by progressive neuronal damage and cognitive decline. Recent studies have shed light on the involvement of not only the blood-brain barrier (BBB) dysfunction but also significant alterations in cellular junctions in AD pathogenesis. In this review article, we explore the role of the BBB and cellular junctions in AD pathology, with a specific focus on the hippocampus. The BBB acts as a crucial protective barrier between the bloodstream and the brain, maintaining brain homeostasis and regulating molecular transport. Preservation of BBB integrity relies on various junctions, including gap junctions formed by connexins, tight junctions composed of proteins such as claudins, occludin, and ZO-1, as well as adherence junctions involving molecules like vascular endothelial (VE) cadherin, Nectins, and Nectin-like molecules (Necls). Abnormalities in these junctions and junctional components contribute to impaired neuronal signaling and increased cerebrovascular permeability, which are closely associated with AD advancement. By elucidating the underlying molecular mechanisms governing BBB and cellular junction dysfunctions within the context of AD, this review offers valuable insights into the pathogenesis of AD and identifies potential therapeutic targets for intervention.

MaDDOSY (Mass Determination Diffusion Ordered Spectroscopy) using an 80 MHz Bench Top NMR for the Rapid Determination of Polymer and Macromolecular Molecular Weight.

Measurement of molecular weight is an integral part of macromolecular and polymer characterization which usually has limitations. Herein, this article presents the use of a bench-top 80 MHz Nuclear Magnetic Resonance (NMR) spectrometer for diffusion-ordered spectroscopy as a practical and rapid approach for the determination of molecular weight/size using a novel solvent and polymer-independent universal calibration.

Substituted Maleimides: Self-Reportable Linkers and Tags in Bioconjugation, Materials Science, and Nanotechnology.

Substituted maleimides are customisable fluorescent linkers and probes with adaptable reactivity and optical properties. Their compact nature and tunability has led to their use in various applications. For example, their solvatochromic properties offer real-time feedback on linking chemistry and environmental changes, essential for applications in material labelling, drug delivery, and nanoparticle functionalisation. This review focusses on developing, synthesising, and modifying substituted maleimides as environment-sensitive fluorescent linkers and probes. It delves into their photophysical dynamics and strategic applications, highlighting their significant contributions to macromolecule conjugation and the development of self-reporting materials.

Quantification of short echo time MRS signals with improved version of QUantitation based on quantum ESTimation algorithm.

Magnetic resonance spectroscopy offers information about metabolite changes in the organism, which can be used in diagnosis. While short echo time proton spectra exhibit more distinguishable metabolites compared with proton spectra acquired with long echo times, their quantification (and providing estimates of metabolite concentrations) is more challenging. They are hampered by a background signal, which originates mainly from macromolecules (MM) and mobile lipids. An improved version of the quantification algorithm QUantitation based on quantum ESTimation (QUEST), with MM prior knowledge (QUEST-MM), dedicated to proton signals and invoking appropriate prior knowledge on MM, is proposed and tested. From a single acquisition, it enables better metabolite quantification, automatic estimation of the background, and additional automatic quantification of MM components, thus improving its applicability in the clinic. The proposed algorithm may facilitate studies that involve patients with pathological MM in the brain. QUEST-MM and three QUEST-based strategies for quantifying short echo time signals are compared in terms of bias-variance trade-off and Cramér-Rao lower bound estimates. The performances of the methods are evaluated through extensive Monte Carlo studies. In particular, the histograms of the metabolite and MM amplitude distributions demonstrate the performances of the estimators. They showed that QUEST-MM works better than QUEST (Subtract approach) and is a good alternative to QUEST when measured MM signal is unavailable or unsuitable. Quantification with QUEST-MM is shown for 1 H in vivo rat brain signals obtained with the SPECIAL pulse sequence at 9.4 T, and human brain signals obtained, respectively, with STEAM at 4 T and PRESS at 3 T. QUEST-MM is implemented in jMRUI and will be available for public use from version 7.1.

The Combination of a Human Biomimetic Liver Microphysiology System with BIOLOGXsym, a Quantitative Systems Toxicology (QST) Modeling Platform for Macromolecules, Provides Mechanistic Understanding of Tocilizumab- and GGF2-Induced Liver Injury.

Biologics address a range of unmet clinical needs, but the occurrence of biologics-induced liver injury remains a major challenge. Development of cimaglermin alfa (GGF2) was terminated due to transient elevations in serum aminotransferases and total bilirubin. Tocilizumab has been reported to induce transient aminotransferase elevations, requiring frequent monitoring. To evaluate the clinical risk of biologics-induced liver injury, a novel quantitative systems toxicology modeling platform, BIOLOGXsym™, representing relevant liver biochemistry and the mechanistic effects of biologics on liver pathophysiology, was developed in conjunction with clinically relevant data from a human biomimetic liver microphysiology system. Phenotypic and mechanistic toxicity data and metabolomics analysis from the Liver Acinus Microphysiology System showed that tocilizumab and GGF2 increased high mobility group box 1, indicating hepatic injury and stress. Tocilizumab exposure was associated with increased oxidative stress and extracellular/tissue remodeling, and GGF2 decreased bile acid secretion. BIOLOGXsym simulations, leveraging the in vivo exposure predicted by physiologically-based pharmacokinetic modeling and mechanistic toxicity data from the Liver Acinus Microphysiology System, reproduced the clinically observed liver signals of tocilizumab and GGF2, demonstrating that mechanistic toxicity data from microphysiology systems can be successfully integrated into a quantitative systems toxicology model to identify liabilities of biologics-induced liver injury and provide mechanistic insights into observed liver safety signals.

Characterization of Different Types of Epiretinal Proliferations by Synchrotron Radiation-Based Fourier Transform Infrared Micro-Spectroscopy.

Pathological tissue on the surface of the retina that can be of different etiology and pathogenesis can cause changes in the retina that have a direct consequence on vision. Tissues of different etiology and pathogenesis have different morphological structures and also different macromolecule compositions usually characteristic of specific diseases. In this study, we evaluated and compared biochemical differences among samples of three different types of epiretinal proliferations: idiopathic epiretinal membrane (ERMi), membranes in proliferative vitreoretinopathy (PVRm), and proliferative diabetic retinopathy (PDRm). The membranes were analyzed by using synchrotron radiation-based Fourier transform infrared micro-spectroscopy (SR-FTIR). We used the SR-FTIR micro-spectroscopy setup, where measurements were set to achieve a high resolution that was capable of showing clear biochemical spectra in biological tissue. We were able to identify differences between PVRm, PDRm, and ERMi in protein and lipid structure; collagen content and collagen maturity; differences in proteoglycan presence; protein phosphorylation; and DNA expression. Collagen showed the strongest expression in PDRm, lower expression in ERMi, and very low expression in PVRm. We also demonstrated the presence of silicone oil (SO) or polydimethylsiloxane in the structure of PVRm after SO endotamponade. This finding suggests that SO, in addition to its many benefits as an important tool in vitreoretinal surgery, could be involved in PVRm formation.

Volumetric macromolecule identification in cryo-electron tomograms using capsule networks.

BACKGROUND: Despite recent advances in cellular cryo-electron tomography (CET), developing automated tools for macromolecule identification in submolecular resolution remains challenging due to the lack of annotated data and high structural complexities. To date, the extent of the deep learning methods constructed for this problem is limited to conventional Convolutional Neural Networks (CNNs). Identifying macromolecules of different types and sizes is a tedious and time-consuming task. In this paper, we employ a capsule-based architecture to automate the task of macromolecule identification, that we refer to as 3D-UCaps. In particular, the architecture is composed of three components: feature extractor, capsule encoder, and CNN decoder. The feature extractor converts voxel intensities of input sub-tomograms to activities of local features. The encoder is a 3D Capsule Network (CapsNet) that takes local features to generate a low-dimensional representation of the input. Then, a 3D CNN decoder reconstructs the sub-tomograms from the given representation by upsampling. RESULTS: We performed binary and multi-class localization and identification tasks on synthetic and experimental data. We observed that the 3D-UNet and the 3D-UCaps had an [Formula: see text]score mostly above 60% and 70%, respectively, on the test data. In both network architectures, we observed degradation of at least 40% in the [Formula: see text]-score when identifying very small particles (PDB entry 3GL1) compared to a large particle (PDB entry 4D8Q). In the multi-class identification task of experimental data, 3D-UCaps had an [Formula: see text]-score of 91% on the test data in contrast to 64% of the 3D-UNet. The better [Formula: see text]-score of 3D-UCaps compared to 3D-UNet is obtained by a higher precision score. We speculate this to be due to the capsule network employed in the encoder. To study the effect of the CapsNet-based encoder architecture further, we performed an ablation study and perceived that the [Formula: see text]-score is boosted as network depth is increased which is in contrast to the previously reported results for the 3D-UNet. To present a reproducible work, source code, trained models, data as well as visualization results are made publicly available. CONCLUSION: Quantitative and qualitative results show that 3D-UCaps successfully perform various downstream tasks including identification and localization of macromolecules and can at least compete with CNN architectures for this task. Given that the capsule layers extract both the existence probability and the orientation of the molecules, this architecture has the potential to lead to representations of the data that are better interpretable than those of 3D-UNet.

Harmonization of multi-site MRS data with ComBat.

Magnetic resonance spectroscopy (MRS) is a non-invasive neuroimaging technique used to measure brain chemistry in vivo and has been used to study the healthy brain as well as neuropathology in numerous neurological disorders. The number of multi-site studies using MRS are increasing; however, non-biological variability introduced during data collection across multiple sites, such as differences in scanner vendors and site-specific acquisition implementations for MRS, can obscure detection of biological effects of interest. ComBat is a data harmonization technique that can remove non-biological sources of variance in multisite studies. It has been validated for use with structural and functional MRI metrics but not for MRS measured metabolites. This study investigated the validity of using ComBat to harmonize MRS metabolites for vendor and site differences. Analyses were performed using data acquired across 20 sites and included edited MRS for GABA+ (N = 218) and macromolecule-suppressed GABA data (N = 209), as well as standard PRESS data to quantify NAA, creatine, choline, and glutamate (N = 190). ComBat harmonization successfully mitigated vendor and site differences for all metabolites of interest. Moreover, significant associations were detected between sex and choline levels and between age and glutamate and GABA+ levels that were not detectable prior to harmonization, confirming the importance of removing site and vendor effects in multi-site data. In conclusion, ComBat harmonization can be successfully applied to MRS data in multi-site MRS studies.

The macromolecular MR spectrum does not change with healthy aging.

PURPOSE: To acquire the mobile macromolecule (MM) spectrum from healthy participants, and to investigate changes in the signals with age and sex. METHODS: 102 volunteers (49 M/53 F) between 20 and 69 years were recruited for in vivo data acquisition in the centrum semiovale (CSO) and posterior cingulate cortex (PCC). Spectral data were acquired at 3T using PRESS localization with a voxel size of 30 × 26 × 26 mm3 , pre-inversion (TR/TI 2000/600 ms) and CHESS water suppression. Metabolite-nulled spectra were modeled to eliminate residual metabolite signals, which were then subtracted out to yield a "clean" MM spectrum using the Osprey software. Pearson's correlation coefficient was calculated between integrals and age for the 14 MM signals. One-way ANOVA was performed to determine differences between age groups. An independent t-test was carried out to determine differences between sexes. RESULTS: MM spectra were successfully acquired in 99 (CSO) and 96 (PCC) of 102 subjects. No significant correlations were seen between age and MM signals. One-way ANOVA also suggested no age-group differences for any MM peak (all p > .004). No differences were observed between sex groups. WM and GM voxel fractions showed a significant (p < .05) negative linear association with age in the WM-predominant CSO (R = -0.29) and GM-predominant PCC regions (R = -0.57) respectively while CSF increased significantly with age in both regions. CONCLUSION: Our findings suggest that a pre-defined MM basis function can be used for linear combination modeling of metabolite data from different age and sex groups.

Comparison of seven modelling algorithms for γ-aminobutyric acid-edited proton magnetic resonance spectroscopy.

Edited MRS sequences are widely used for studying γ-aminobutyric acid (GABA) in the human brain. Several algorithms are available for modelling these data, deriving metabolite concentration estimates through peak fitting or a linear combination of basis spectra. The present study compares seven such algorithms, using data obtained in a large multisite study. GABA-edited (GABA+, TE = 68 ms MEGA-PRESS) data from 222 subjects at 20 sites were processed via a standardised pipeline, before modelling with FSL-MRS, Gannet, AMARES, QUEST, LCModel, Osprey and Tarquin, using standardised vendor-specific basis sets (for GE, Philips and Siemens) where appropriate. After referencing metabolite estimates (to water or creatine), systematic differences in scale were observed between datasets acquired on different vendors' hardware, presenting across algorithms. Scale differences across algorithms were also observed. Using the correlation between metabolite estimates and voxel tissue fraction as a benchmark, most algorithms were found to be similarly effective in detecting differences in GABA+. An interclass correlation across all algorithms showed single-rater consistency for GABA+ estimates of around 0.38, indicating moderate agreement. Upon inclusion of a basis set component explicitly modelling the macromolecule signal underlying the observed 3.0 ppm GABA peaks, single-rater consistency improved to 0.44. Correlation between discrete pairs of algorithms varied, and was concerningly weak in some cases. Our findings highlight the need for consensus on appropriate modelling parameters across different algorithms, and for detailed reporting of the parameters adopted in individual studies to ensure reproducibility and meaningful comparison of outcomes between different studies.

Quantitative pharmacokinetic analyses of anterior and posterior elimination routes of intravitreal anti-VEGF macromolecules using published human and rabbit data.

The purpose of this study was to evaluate the contribution of the anterior elimination route for four anti-vascular endothelial growth factor (anti-VEGF) macromolecules (aflibercept, bevacizumab, pegaptanib and ranibizumab) after intravitreal injection using published human and rabbit data and three previously described pharmacokinetic (PK) modeling methods. A PubMed search was used to identify published studies with concentration-time data. The data were utilized only if the intravitreally injected drugs were used as plain solutions and several criteria for a well-performed PK study were fulfilled. The three methods to analyze rabbit data were (1) the equation for vitreal elimination half-life based molecular size assuming anterior elimination, (2) Maurice equation and plot for the ratio of aqueous humor (AH) to vitreal concentration assuming anterior elimination, and (3) the equation for amount of macromolecule eliminated anteriorly based on the area under the curve in AH. The first and third methods were used for human data. In the second and third methods, AH flow rate is a key model parameter, and it was varied between 2 and 3 µl/min. The methods were applied to data from 9 rabbit studies (1 for aflibercept, 5 for bevacizumab, and 3 for ranibizumab) and 5 human studies (1 for aflibercept, 3 for bevacizumab, and 1 for ranibizumab). Experimental half-lives of anti-VEGF macromolecules in both vitreous and aqueous humor were close to those calculated with the equations for vitreal elimination half-life in humans and rabbits. Rabbit data analyzed with Maurice plot indicated that the contribution of anterior elimination was usually at least 75%. In most human and rabbit studies, the calculated percentage of anterior elimination was at least 51%. Variability between studies was extensive for bevacizumab and ranibizumab. The results suggest that the anterior elimination route dominates after intravitreal injection of anti-VEGF macromolecules. However, the clinical data are sparse and variability is extensive, the latter emphasizing the need of proper experimental design.

Size and macromolecule stabilizer-dependent performance of gold colloids in immuno-PCR.

Gold nanoparticles (GNPs) are well-documented for their size and surface chemistry-dependent electronic and optical properties that are extensively utilized to develop highly sensitive immunoassays. GNP-based immuno-polymerase chain reaction (immuno-PCR) is especially interesting due to the facile loading of biomolecules on the surface of GNP probes and has been utilized to develop analyte-specific assays. In this study, the role of size and surface chemistry of GNPs is explored in detail to develop a highly sensitive and reproducible immuno-PCR assay for specific detection of biotinylated analytes. Our results indicate that smaller-sized gold nanoparticles outperform the larger ones in terms of their sensitivity in immuno-PCR assay and show superior loading of proteins and oligonucleotides on the surface of nanoparticles. Furthermore, the role of different macromolecular stabilizers (such as polyethylene glycol (PEG), bovine serum albumin (BSA), and PEGylated BSA) was compared to optimize the loading of biomolecules and to improve the signal-to-noise ratio of GNP probes. mPEG-BSA-functionalized GNP probes of 15 nm were found to be highly sensitive at low concentrations of analytes and significantly (~ 30 fold) improve the limit of detection of analytes in comparison with ELISA assay.

The Use of the Statistical Entropy in Some New Approaches for the Description of Biosystems.

Some problems of describing biological systems with the use of entropy as a measure of the complexity of these systems are considered. Entropy is studied both for the organism as a whole and for its parts down to the molecular level. Correlation of actions of various parts of the whole organism, intercellular interactions and control, as well as cooperativity on the microlevel lead to a more complex structure and lower statistical entropy. For a multicellular organism, entropy is much lower than entropy for the same mass of a colony of unicellular organisms. Cooperativity always reduces the entropy of the system; a simple example of ligand binding to a macromolecule carrying two reaction centers shows how entropy is consistent with the ambiguity of the result in the Bernoulli test scheme. Particular attention is paid to the qualitative and quantitative relationship between the entropy of the system and the cooperativity of ligand binding to macromolecules. A kinetic model of metabolism. corresponding to Schrödinger's concept of the maintenance biosystems by "negentropy feeding", is proposed. This model allows calculating the nonequilibrium local entropy and comparing it with the local equilibrium entropy inherent in non-living matter.