Ultra-high-performance liquid chromatography with tandem mass spectrometry method for cellular toxicity and pharmacokinetic study of PEG1K polymers.

Polyethylene glycol (PEG) is one of the most commonly used polymers in drug delivery systems. The investigation of the pharmacokinetic behavior of PEG is important for revealing the toxicity and efficiency of PEG-related Nano-drug delivery systems. A high through-put and selective ultra-high-performance liquid chromatography with tandem mass spectrometry (UHPLC-MS/MS) method coupled with collision-induced dissociation (CID) in source technique was developed and validated to determine PEG1K polymers in cellular samples in this study. The countless precursor ions of PEG1K are dissociated in the source to generate numerous product ions which have different numbers of subunits. The transition of [M+H]+ precursor ions → product ions at m/z 177.1 (four subunits)→89.1 (two subunits) was selected to determine PEG1K due to its high sensitivity. The UHPLC-MS/MS method coupled with CID in the source showed good linearity over the range of 0.1-10 µg/mL. Intra-day and inter-day accuracies and precisions of the assay were all within ± 12.39%. The assay was successfully applied to a cellular pharmacokinetic study of PEG1K in human breast cancer cells. The cytotoxicity of PEG1K polymers was also studied and the results indicated that the cytotoxicity of PEG1K was not significant in the range of 5-1200 µg/mL.

Mapping Microplastics in Humans: Analysis of Polymer Types, and Shapes in Food and Drinking Water-A Systematic Review.

Microplastics (MPs) pervade the environment, infiltrating food sources and human bodies, raising concerns about their impact on human health. This review is focused on three key questions: (i) What type of polymers are humans most exposed to? (ii) What are the prevalent shapes of MPs found in food and human samples? (iii) Are the data influenced by the detection limit on the size of particles? Through a systematic literature analysis, we have explored data on polymer types and shapes found in food and human samples. The data provide evidence that polyester is the most commonly detected polymer in humans, followed by polyamide, polyurethane, polypropylene, and polyacrylate. Fibres emerge as the predominant shape across all categories, suggesting potential environmental contamination from the textile industry. Studies in humans and drinking water reported data on small particles, in contrast to larger size MPs detected in environmental research, in particular seafood. Discrepancies in size detection methodologies across different reports were identified, which could impact some of the discussed trends. This study highlights the need for more comprehensive research on the interactions between MPs and biological systems and the effects of MPs on toxicity, together with standardised analytical methodologies to accurately assess contamination levels and human exposure. Understanding these dynamics is essential for formulating effective strategies to mitigate the environmental and health implications of MP pollution.

FODMAP Content Like-by-like Comparison in Spanish Gluten-free and Gluten-containing Cereal-based Products.

Gluten-free foods (GF) availability on supermarket shelves is growing and it is expected to continue expanding in the years ahead. These foods have been linked to a lower content of fermentable oligosaccharides, disaccharides, monosaccharides and polyols (FODMAPs), molecules that trigger gastrointestinal symptoms in sensitive persons. In this study, the FODMAP content of 25 cereal-based GF foods in Spain (breakfast cereals, pasta, bread, biscuits, bakery products, and dough and puff pastry) and 25 gluten-containing equivalents (GC) available in the same supermarket were analysed and compared. Lactose, fructose, glucose, sorbitol, mannitol, raffinose, stachyose and fructans were quantified. In a like-by-like analysis, GF foods were found to generally contain fewer FODMAPs than their GC counterparts. The ingredients used in the manufacture of GF cereal-based foods may contribute to this fact. When the individually wrapped size was considered, the proportion of samples classified as high-FODMAPs in GC and GF foods showed a trend towards fewer samples in the GF. However, not all the GF samples were low-FODMAP. Altogether, our findings provide essential information for FODMAP content databases of GF products in Spain.

Single-Standard Quantification Strategy for Lignin Dimers by Supercritical Fluid Chromatography with Charged Aerosol Detection.

The increased interest in utilizing lignin as a feedstock to produce various aromatic compounds requires advanced chemical analysis methods to provide qualitative and quantitative characterization of lignin samples along different technology streamlines. However, due to the lack of commercially available chemical standards, routine quantification of industrially relevant lignin oligomers in complex lignin samples remains a challenge. This study presents a novel method for universal quantification of lignin dimers based on supercritical fluid chromatography with charged aerosol detection (CAD). A series of lignin-derived dimeric compounds that have been reported from reductive catalytic fractionation (RCF) were synthesized and used as standards. The applicability of using linear regression instead of quadratic calibration curves was evaluated over a concentration range of 15-125 mg/L, demonstrating that the former calibration method is as appropriate as the latter. The response factors of lignin dimeric compounds were compared to assess the uniformity of the CAD signal, revealing that the CAD response for the tested lignin dimers did not differ substantially. It was also found that the response factors were not dependent on the number of methoxy groups or linkage motifs, ultimately enabling the use of only one calibrant for these compounds. The importance of chromatographic peak resolution in CAD was stressed, and the use of a digital peak sharpening technique was adopted and applied to address this challenge. The developed method was verified and used for the quantification of lignin dimers in an oil obtained by a RCF of birch sawdust.

Rapid Estimation of Size-Based Heterogeneity in Monoclonal Antibodies by Machine Learning-Enhanced Dynamic Light Scattering.

Aggregation of monoclonal antibody therapeutics is a serious concern that is believed to impact product safety and efficacy. There is a need for analytical approaches that enable rapid estimation of mAb aggregates. Dynamic light scattering (DLS) is a well-established technique for estimating the average size of protein aggregates or for evaluating sample stability. It is usually used to measure the size and size distribution over a wide range of nano- to micro-sized particles using time-dependent fluctuations in the intensity of scattered light arising from the Brownian motion of particles. In this study, we present a novel DLS-based approach that allows us to quantify the relative percentage of multimers (monomer, dimer, trimer, and tetramer) in a monoclonal antibody (mAb) therapeutic product. The proposed approach uses a machine learning (ML) algorithm and regression to model the system and predict the amount of relevant species such as monomer, dimer, trimer, and tetramer of a mAb in the size range of 10-100 nm. The proposed DLS-ML technique compares favorably to all potential alternatives with respect to the key method attributes, including per sample cost of analysis, per sample time of data acquisition along with ML-based aggregate prediction (<2 min), sample requirements (<3 µg), and user-friendliness of analysis. The proposed rapid method can serve as an orthogonal tool to size exclusion chromatography, which is the current industry workhorse for aggregate assessment.

The impact of essential oils on the qualitative properties, release profile, and stimuli-responsiveness of active food packaging nanocomposites.

Food industries attempt to introduce a new food packaging by blending essential oils (EOs) into the polymeric matrix as an active packaging, which has great ability to preserve the quality of food and increase its shelf life by releasing active compounds within storage. The main point in designing the active packaging is controlled-release of active substances for their enhanced activity. Biopolymers are functional substances, which suggest structural integrity to sense external stimuli like temperature, pH, or ionic strength. The controlled release of EOs from active packaging and their stimuli-responsive properties can be very important for practical applications of these novel biocomposites. EOs can affect the uniformity of the polymeric matrix and physical and structural characteristics of the composites, such as moisture content, solubility in water, water vapor transmission rate, elongation at break, and tensile strength. To measure the ingredients of EOs and their migration from food packaging, chromatographic methods can be used. A head-space-solid phase micro-extraction coupled to gas chromatography (HS-SPME-GC-MS) technique is as a good process for evaluating the release of Eos. Therefore, the aims of this review were to evaluate the qualitative characteristics, release profile, and stimuli-responsiveness of active and smart food packaging nanocomposites loaded with essential oils and developing such multi-faceted packaging for advanced applications.

Quantitative and qualitative impacts of nitric acid digestion on microplastic identification via FTIR and Raman spectroscopy, implications for environmental samples.

Quantification and characterization of microplastics, synthetic polymers less than 5 mm in diameter, requires extraction methods that can reduce non-plastic debris without loss or alteration of the polymers. Nitric acid has been used to extract plastic particles from zooplankton and other biota because it completely digests tissue and exoskeletons, thus reducing interferences. While the impact of acid digestion protocols on several polymers has been demonstrated, advice for quantifying microplastic and interpreting their spectra following nitric acid digestion is lacking. Fourier transform infrared (FTIR) and/or Raman spectroscopy was performed on plastics from > 50 common consumer products (including a variety of textiles) pre- and post-nitric acid treatment. The percent match and assigned polymer were tabulated to compare the accuracy of spectral identification before and after nitric acid digestion via two open spectral analysis software. Nylon-66, polyoxymethylene, polyurethane, polyisoprene, nitrile rubber, and polymethyl methacrylate had ≥ 90% mass loss in nitric acid. Other less-impacted polymers changed color, morphology, and/or size following digestion. Thus, using nitric acid digestion for microplastic extraction can impact our understanding of the particle sizes and morphologies ingested in situ. Spectral analysis results were compiled to understand how often (1) the best-hit matches were correct (30-60% of spectra), (2) the best-hit matches exceeding the (arbitrary) threshold of 65% match were correct (53-78% of spectra), and (3) the best-hit matches for anthropogenic polymers were incorrectly identified as natural polymers (12-15% of spectra). Based on these results, advice is provided on how nitric acid digestion can impact microplastics as well as spectral interpretation.

Multifilament Collagen Fiber Bundles with Tendon-like Structure and Mechanical Performance.

Collagen multifilament bundles comprised of thousands of monofilaments are prepared by multipin contact drawing of an entangled polymer solution consisting of collagen and poly(ethylene oxide) (PEO). The multifilament bundles are hydrated in graded concentrations of PEO and phosphate buffered saline (PBS) to promote assembly of collagen fibrils within each monofilament while preserving the structure of the multifilament bundle. Multiscale structural characterization reveals that the hydrated multifilament bundle contains properly folded collagen molecules packed in collagen fibrils containing microfibrils, staggered by exactly one-sixth of the microfibril D-band spacing to produce a periodicity of 11 nm. Sequence analysis predicts that in this structure, phenylalanine residues are close enough within and between microfibrils to become ultraviolet C (UVC) crosslinked. In agreement with this analysis, the ultimate tensile strength (UTS) and Young's modulus of the hydrated collagen multifilament bundles crosslinked by UVC radiation increase nonlinearly with total UVC energy to reach values in the range of native tendons without damage to the collagen molecules. This fabrication method recapitulates the structure of a tendon across multiple length scales and offers tunability in tensile properties using only collagen molecules and no other chemical additives in addition to PEO, which is almost entirely removed during the hydration process.

Development of a three-point cantilever bending technique to study the mechanical properties of hair styling ingredients.

BACKGROUND: The mechanical properties of hair treated with styling ingredients is an important aspect to determine if products will be efficacious when used by the consumer. Measurement techniques have been proposed in earlier work; however, these are mostly aimed at hairspray systems and not the myriad of styling products available to the modern-day consumer. AIM: In this article, experimental and data analysis guidelines are proposed for the evaluation of styling ingredients using a three-point cantilever bending technique. Most of the experiments were carried out on polysaccharide-based ingredients-guar hydroxypropyltrimonium chloride (Guar HPTC) and cassia hydroxypropyltrimonium chloride (Cassia HPTC)-to establish basic characterization concepts of the polymer-fiber assemblies. METHODS: A three-point cantilever bending technique was developed using a texture analyzer housed in a temperature and humidity-controlled chamber. Scanning electron microscopy (SEM) studies were conducted to monitor the fracture mechanics of polymer-fiber assemblies. RESULTS: Fundamental studies were carried out to determine the effect of concentration, molecular weight (MW), and chemistry of the polysaccharides on the calculated indices, which characterize the stiffness, flexibility, elasticity, and plasticity of the treated hair. Experiments were conducted in a controlled temperature and humidity environment, which allowed us to monitor the behavior of the polymer-treated hair from 40-90% RH. Studies were also conducted on polymer blends and conventional styling polymers to provide guidance of the performance of naturally-derived polymers to their synthetic counterparts. CONCLUSIONS: A detailed description is provided for a user-friendly, quick method to measure the mechanical properties of styling ingredients on hair. We provide guidelines for three-point cantilever bending tests of straight hair tresses treated with conventional and naturally-derived styling polymers. Indices were developed to characterize the force-distance curves and were designated as E1, F1, position of F1, post-fracture gradient, toughness, E10/E1, and F10/F1. These indices provide an overall characterization of the stiffness, flexibility, elasticity, and plasticity of polymer-treated hair.

Preparation of COPs Mixed Matrix Membrane for Sensitive Determination of Six Sulfonamides in Human Urine.

In this study, TpDMB-COPs, a specific class of covalent organic polymers (COPs), was synthesized using Schiff-base chemistry and incorporated into a polyvinylidene fluoride (PVDF) polymer for the first time to prepare COPs mixed matrix membranes (TpDMB-COPs-MMM). A membrane solid-phase extraction (ME) method based on the TpDMB-COPs-MMM was developed to extract trace levels of six sulfonamides from human urine identified by high-performance liquid chromatography (HPLC). The key factors affecting the extraction efficiency were investigated. Under the optimum conditions, the proposed method demonstrated an excellent linear relationship in the range of 3.5-25 ng/mL (r2 ≥ 0.9991), with the low limits of detection (LOD) between 1.25 ng/mL and 2.50 ng/mL and the limit of quantification (LOQ) between 3.50 ng/mL and 7.00 ng/mL. Intra-day and inter-day accuracies were below 5.0%. The method's accuracy was assessed by recovery experiments using human urine spiked at three levels (7-14 ng/mL, 10-15 ng/mL, and 16-20 ng/mL). The recoveries ranged from 87.4 to 112.2% with relative standard deviations (RSD) ≤ 8.7%, confirming the applicability of the proposed method. The developed ME method based on TpDMB-COPs-MMM offered advantages, including simple operation, superior extraction affinity, excellent recycling performance, and easy removal and separation from the solution. The prepared TpDMB-COPs-MMM was demonstrated to be a promising adsorbent for ME in the pre-concentration of trace organic compounds from complex matrices, expanding the application of COPs and providing references for other porous materials in sample pre-treatment.

Programmable DNA Hydrogels as Artificial Extracellular Matrix.

The cell microenvironment plays a crucial role in regulating cell behavior and fate in physiological and pathological processes. As the fundamental component of the cell microenvironment, extracellular matrix (ECM) typically possesses complex ordered structures and provides essential physical and chemical cues to the cells. Hydrogels have attracted much attention in recapitulating the ECM. Compared to natural and synthetic polymer hydrogels, DNA hydrogels have unique programmable capability, which endows the material precise structural customization and tunable properties. This review focuses on recent advances in programmable DNA hydrogels as artificial extracellular matrix, particularly the pure DNA hydrogels. It introduces the classification, design, and assembly of DNA hydrogels, and then summarizes the state-of-the-art achievements in cell encapsulation, cell culture, and tissue engineering with DNA hydrogels. Ultimately, the challenges and prospects for cellular applications of DNA hydrogels are delivered.

Modeling microtubule dynamic instability: Microtubule growth, shortening and pause.

Microtubules (MTs) are protein polymers found in all eukaryotic cells. They are crucial for normal cell development, providing structural support for the cell and aiding in the transportation of proteins and organelles. In order to perform these functions, MTs go through periods of relatively slow polymerization (growth) and very fast depolymerization (shortening), where the switch from growth to shortening is called a catastrophe and the switch from shortening to growth is called a rescue. Although MT dynamic instability has traditionally been described solely in terms of growth and shortening, MTs have been shown to pause for extended periods of time, however the reason for pausing is not well understood. Here, we present a new mathematical model to describe MT dynamics in terms of growth, shortening, and pausing. Typically, MT dynamics are defined by four key parameters which include the MT growth rate, shortening rate, frequency of catastrophe, and the frequency of rescue. We derive a mathematical expression for the catastrophe frequency in the presence of pausing, as well as expressions to describe the total time that MTs spend in a state of growth and pause. In addition to exploring MT dynamics in a control-like setting, we explore the implicit effect of stabilizing MT associated proteins (MAPs) and stabilizing and destabilizing chemotherapeutic drugs that target MTs on MT dynamics through variations in model parameters.

Super-Hydrophilic Zwitterionic Polymer Surface Modification Facilitates Liquid Transportation of Microfluidic Sweat Sensors.

The transportation of sweat in an epidermal sweat sensor is critical for the monitoring of biochemical compositions of human sweat. However, it is still a challenge to engineer microfluidic devices with super-wetting channels for such epidermal sweat sensors. Herein, a zwitterionic poly (2-methacryloyloxyethyl phosphorylcholine) (PMPC) modified microfluidic device with super-wetting and good liquid transport ability via an azo coupling reaction of PMPC onto the surface of polydimethylsiloxane microfluidic devices is reported. The obtained PMPC-modified microfluidic device can be integrated with flexible electrochemical sensor to measure the ion compositions of human sweat in real-time. The super-hydrophilic zwitterionic polymer surface modification can greatly facilitate the transportation of body fluids in microfluidic sensors for the detection of various biomarkers. Such microfluidic sensors have great potential for next-generation personalized healthcare.

One-pot synthesis of brewer's spent grain-supported superabsorbent polymer for highly efficient uranium adsorption from wastewater.

High-efficient and fast adsorption of uranium is important to reduce the hazards caused by the uranium contamination of water environment due to the increased human activities. Herein, brewer's spent grain (BSG)-supported superabsorbent polymers (SAP) with different cross-linking densities are prepared as cheap and eco-friendly adsorbents for the first time via one-pot swelling and graft polymerization. A 7 wt% NaOH solution is used to swell BSG before grafting and subsequently neutralize the acrylic acid to control the reaction rate without producing alkaline wastewater. Compared with the traditional methods, swelling improves the grafting density and the utilization of raw materials due to the increased disorder degree of the BSG fibers. This results in the grafting of abundant carboxyl and amide groups onto the BSG backbone, forming a strongly hydrophilic polymer network of the BSG-SAP. Compared with the reference polymers without BSG, BSG-SAP presents higher adsorption capacity and enhanced reusability. The highly cross-linked BSG-SAP (BSG-SAP-H) shows an outstanding adsorption capacity of U(VI) (1465 mg/g at pH0 = 4.6), a fast adsorption rate (81% of equilibrium adsorption capacity in 15 min), and a high selectivity in the presence of competing ions. Adsorption mechanism studies reveal the involvement of amide groups, a bidentate binding structure between UO22+ and the carboxyl groups, and a cation exchange between Na+ and UO22+. More importantly, the adsorption capacity of BSG-SAP-H reaches 254.4 mg/g in the fixed-bed column experiment at a low initial concentration (c0(U) = 30 mg/L) and keeps 80% of the adsorption capacity after four cycles, indicating a great potential for uranium removal from wastewater. This work shows a suitable approach to explore the untreated biomass to prepare SAP with enhanced adsorption performance via a general and low-cost strategy.

Optimization of non-equilibrium self-assembly protocols using Markov state models.

The promise of self-assembly to enable the bottom-up formation of materials with prescribed architectures and functions has driven intensive efforts to uncover rational design principles for maximizing the yield of a target structure. Yet, despite many successful examples of self-assembly, ensuring kinetic accessibility of the target structure remains an unsolved problem in many systems. In particular, long-lived kinetic traps can result in assembly times that vastly exceed experimentally accessible timescales. One proposed solution is to design non-equilibrium assembly protocols in which system parameters change over time to avoid such kinetic traps. Here, we develop a framework to combine Markov state model (MSM) analysis with optimal control theory to compute a time-dependent protocol that maximizes the yield of the target structure at a finite time. We present an adjoint-based gradient descent method that, in conjunction with MSMs for a system as a function of its control parameters, enables efficiently optimizing the assembly protocol. We also describe an interpolation approach to significantly reduce the number of simulations required to construct the MSMs. We demonstrate our approach with two examples; a simple semi-analytic model for the folding of a polymer of colloidal particles, and a more complex model for capsid assembly. Our results show that optimizing time-dependent protocols can achieve significant improvements in the yields of selected structures, including equilibrium free energy minima, long-lived metastable structures, and transient states.

Magnetic polymer particles as a highly efficient and facile cleanup adsorbent for multi-pesticide residues analysis in aquatic products.

A novel and efficient sample pretreatment procedure using magnetic particles was exploited for the determination of multi-pesticide residues in aquatic products. The magnetic adsorbent was prepared using divinyl benzene and N-vinyl pyrrolidone as functional monomers modified on the Fe3O4 @SiO2. The obtained magnetic adsorbent, octadecylsilane sorbents, and graphitized carbon black were employed as effective adsorbents to remove matrix interferences in aquatic products, and their dosages were optimized. Satisfactory levels of accuracy and precision were procured under optimum conditions. The method limits of quantification ranged from 0.1 to 2.0 µg/kg. The analytical accuracy of the developed method for the analysis of multi-pesticide residues in freshwater and seafood products was validated. It was found to be suitable for the analysis of multi-pesticide residues in different types of aquatic products. Additionally, the method was successfully applied for the analysis of pesticide residues in fish samples obtained from aquaculture plants located in Zhejiang Province, China. The detected concentrations of pesticides ranged from 0.14 to 0.95 µg/kg. In general, this method shows promising application prospects for the rapid determination of multi-pesticide residues in aquatic products.

Simultaneous Determination of Active Pharmaceutical Ingredients and Water-Soluble Polymers: Analysis of Dissolution Profiles from Sustained-Release Formulations and Mechanisms Involved.

The dissolution behaviors of base excipients from sustained-release formulations have been investigated using various methodologies. However, the dissolution of polymers has not been fully evaluated because differences between formulations are still verified only by the release of active pharmaceutical ingredients (APIs). In our previous study, we proposed a quick and simultaneous analysis of dissolved APIs and water-soluble polymers by ultra HPLC using charged aerosol and photodiode array detectors. The purpose of this study was to verify whether the analysis system could be adapted to other water-soluble polymers. Dissolution tests were conducted using matrix model tablets prepared from three polymers and three APIs (propranolol, ranitidine, and cilostazol) with different solubilities. The dissolution profiles of the polymers and APIs were determined using the proposed analysis system and compared. The results clarified differences in the dissolution behaviors of the APIs and polymers. The polymers, especially hydroxypropyl cellulose, exhibited the dissolution properties characteristic of each model formulation. Propranolol and ranitidine showed the diffusion type, while cilostazol showed the erosion type release mechanism due to their different solubilities. The release of cilostazol was delayed in all models compared to the polymer, which may be due to the aggregation of cilostazol in the gel layer. This analytical method can be used to study the dissolution behavior (diffusion or erosion) of APIs from matrix tablets containing various polymers. This method will provide useful information on release control, which will make it easier and more efficient to design appropriate formulations and analyze the release mechanisms.

Structural Investigation of DHICA Eumelanin Using Density Functional Theory and Classical Molecular Dynamics Simulations.

Eumelanin is an important pigment, for example, in skin, hair, eyes, and the inner ear. It is a highly heterogeneous polymer with 5,6-dihydroxyindole-2-carboxylic acid (DHICA) and 5,6-dihydroxyindole (DHI) building blocks, of which DHICA is reported as the more abundant in natural eumelanin. The DHICA-eumelanin protomolecule consists of three building blocks, indole-2-carboxylic acid-5,6-quinone (ICAQ), DHICA and pyrrole-2,3,5-tricarboxylic acid (PTCA). Here, we focus on the self-assembly of DHICA-eumelanin using multi-microsecond molecular dynamics (MD) simulations at various concentrations in aqueous solutions. The molecule was first parameterized using density functional theory (DFT) calculations. Three types of systems were studied: (1) uncharged DHICA-eumelanin, (2) charged DHICA-eumelanin corresponding to physiological pH, and (3) a binary mixture of both of the above protomolecules. In the case of uncharged DHICA-eumelanin, spontaneous aggregation occurred and water molecules were present inside the aggregates. In the systems corresponding to physiological pH, all the carboxyl groups are negatively charged and the DHICA-eumelanin model has a net charge of -4. The effect of K+ ions as counterions was investigated. The results show high probability of binding to the deprotonated oxygens of the carboxylate anions in the PTCA moiety. Furthermore, the K+ counterions increased the solubility of DHICA-eumelanin in its charged form. A possible explanation is that the charged protomolecules favor binding to the K+ ions rather than aggregating and binding to other protomolecules. The binary mixtures show aggregation of uncharged DHICA-eumelanins; unlike the charged systems with no aggregation, a few charged DHICA-eumelanins are present on the surface of the uncharged aggregation, binding to the K+ ions.

Development of a Solid-Phase Extraction Method Based on Biocompatible Starch Polyurethane Polymers for GC-MS Analysis of Polybrominated Diphenyl Ethers in Ambient Water Samples.

A new solid-phase extraction (SPE) method for the extraction, enrichment, and analysis of eight polybrominated diphenyl ethers (PBDEs) in water was developed. The current approach involves using a cross-linked starch-based polymer as an extraction adsorbent and determining the PBDE analytes of interest using gas chromatography-mass spectrometry in negative chemical ionization mode (GC-NCI-MS). The starch-based polymer was synthesized by the reaction of soluble starch with 4,4'-methylene-bis-phenyldiisocyanate as a cross-linking agent in dry dimethylformamide. Various parameters impacting extraction efficiencies, such as adsorbent quantity, sample volumes, elution solvents and volumes, and methanol content, were carefully optimized. The 500 mg of starch-based polymer as an adsorbent used to extract 1000 mL of spiked water, presented high extraction recoveries of eight PBDEs. The linearity of the extraction process was investigated in the range of 1-200 ng L-1 for BDE-28, 47, 99, 100, and 5-200 ng L-1 for BDE-153, 154, 183, and 209, with coefficients of determination (r2) exceeding 0.990 for all PBDEs. The limits of detection (LODs) ranged from 0.06 to 1.42 ng L-1 (S/N = 3) and the relative standard deviation values (RSD) were between 3.6 and 9.5 percent (n = 5) under optimum conditions. The method was successfully used to analyze river and lake water samples, where it exhibited acceptable recovery values of 71.3 to 104.2%. Considering the excellent analytical performance and comparative cost advantage, we recommend the developed starch-based SPE method for routine extraction and analysis of PBDEs in water media.

Using machine learning to study protein-protein interactions: From the uromodulin polymer to egg zona pellucida filaments.

Neural network-based models for protein structure prediction have recently reached near-experimental accuracy and are fast becoming a powerful tool in the arsenal of biologists. As suggested by initial studies using RoseTTAFold or the ColabFold implementation of AlphaFold2, a particularly interesting future development will be the optimization of these computational methods to also routinely yield high-confidence predictions of protein-protein interactions. Here I use AlphaFold2 and ColabFold to investigate the activation and polymerization of uromodulin (UMOD)/Tamm-Horsfall protein, a zona pellucida (ZP) module-containing protein whose precursor and filamentous structures have been previously determined experimentally by X-ray crystallography and cryo-EM, respectively. Despite having no knowledge of the UMOD polymer structure (coordinates for which were neither used for model training nor as template), AlphaFold2/ColabFold are able to recapitulate a crucial conformational change underlying UMOD polymerization, as well as the general organization of protein subunits within the resulting filament. This surprising result is achieved by simply deleting from the input sequence a stretch of residues that correspond to a polymerization-inhibiting C-terminal propeptide. By mimicking in silico the activating effect of propeptide dissociation triggered by site-specific proteolysis of the protein precursor, this example has implications for the assembly of egg coat proteins and the many other molecules that also contain a ZP module. Most importantly, it shows the potential of exploiting machine learning not only to accurately predict the structures of individual proteins or complexes, but also to carry out computational experiments replicating specific molecular events.