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[This corrects the article DOI: 10.1016/j.mex.2026.103985.].
The cellular thermal shift assay (CETSA) is a tool for target identification and validation in drug discovery. It relies on thermal melting curves to indicate drug binding and is performed in cells, cell lysates, or purified protein. These approaches can disrupt the structural integrity of membrane proteins, hindering drug-target engagement. We describe the first application of CETSA in isolated mitochondria and show the effects of this approach on the analysis of the compound UK5099 and its known binding target, the mitochondrial pyruvate carrier (MPC), a mitochondrial inner membrane-localized protein complex. Our analysis supports a model in which the MPC must remain structurally intact for UK5099 binding. We demonstrate that the binding of UK5099 to the MPC is disrupted in cells and cell lysates, whereas isolating mitochondria maintains the binding interaction between drug and target observable using CETSA. These data suggest that isolating membrane-bound organelles through subcellular CETSA stabilizes membrane-bound proteins in their native conformation, allowing the identification of membrane-localized drug binding targets that might otherwise be missed.•CETSA on subcellular isolates preserves membrane target in native conformation.•UK5099-MPC binding is preserved in mitochondrial isolates but not cells or lysates.•This approach validates direct-binding interaction of membrane proteins.
Glyphosate is one of the most widely used herbicides in the world, whose potential effects on human health are still the subject of debate today. To assess the associated risks, reliable biomonitoring data are required using validated robust and sensitive analytical methods. In this context, an ion chromatography coupled with tandem mass spectrometry (IC-MS/MS) method was developed to quantify glyphosate in human urine. The method is based on direct injection of diluted urine samples. A labeled internal standard (13C2 15N1 glyphosate) is added prior to injection to correct for losses or matrix effects during the analysis. The method limit of quantification (LOQ) is 0.1 ng/mL in urine. The working range was validated between 0.1 and 20 ng/mL. Method trueness was assessed at three concentration levels (LOQ, 2 and 20 ng/mL), and a full validation of the method was performed to characterize the analytical performance in terms of precision and measurement uncertainty.•Direct injection ion chromatography coupled with tandem mass spectrometry•Validation of the method according to international standards.
Rheumatoid arthritis causes persistent synovial inflammation, pain, and progressive joint damage that limits the range of motion. Although ROM is clinically relevant, in routine practice it is often assessed incompletely or only qualitatively. The technologies available to quantify it, such as digital inclinometers, electrogoniometers, and motion capture systems, are frequently limited by their cost, the infrastructure they require, and the difficulty of measuring impaired or deformed joints. This protocol describes a standardized manual goniometry procedure to quantify the ROM in six joint regions (hip, knee, ankle, shoulder, elbow, and wrist) in women with established RA, using an accessible, portable, and inexpensive instrument. It covers participant recruitment and selection, preparation before the assessment, evaluator standardization, general measurement principles, and measurement of each joint, complemented by the calculation of the expected ROM percentage. The protocol allows joint impairment to be characterized by anatomical region and movement pattern, which supports clinical evaluation and the design of targeted interventions.•A standardized and reproducible manual goniometry protocol to quantify joint ROM in women with rheumatoid arthritis.•It covers six major joint regions (hip, knee, ankle, shoulder, elbow, and wrist) using an inexpensive and portable universal goniometer.•It includes standardization of the evaluator and calculation of the expected ROM percentage, which allows comparison between joints and between individuals.
This article offers a practice-oriented reflection on conducting Grounded Theory (GT) in midwifery research. Building on a constructivist GT study on Italian midwifery care, it does not restate standard GT procedures; instead, it focuses on the methodological decision points that most strongly shaped analytic quality, coherence, and feasibility. Rather than providing a generic overview, it traces the concrete steps, trade-offs, and adaptations involved in implementing GT in a real world, applied setting. The paper discusses the importance of explicit paradigmatic positioning, the central interpretive role of the researcher, and the need to preserve continuity between data collection and analysis. It also examines practical issues that are often underreported, including the organisation of episodes, early and ongoing memoing, data management, the limits of automation, and the time-intensive nature of analytic consolidation. By making these aspects explicit, the article aims to support researchers in planning and conducting GT studies with greater methodological awareness and rigour, especially in applied healthcare contexts. In doing so, it offers a transferable methodological template for designing and reporting constructivist GT studies in midwifery and related fields.
Currently, implantation of electroencephalogram (EEG) electrodes in laboratory animals is time-consuming and requires specialized equipment. We present a novel method for EEG recordings in mice that utilizes thin needle electrodes. These electrodes are inserted into the skull at predetermined locations by gently pressing them against the bone surface. To ensure stable fixation of the implant, hook-shaped needles are positioned along the lateral aspects of the skull. The electrodes are connected to a multipin connector and secured to the skull using dental composite, after which the animal is allowed to recover from anesthesia. Importantly, procedures such as skull drilling and screw placement are not required, allowing the entire surgery to be completed in <15 min. Consequently, this EEG implantation approach is rapid and minimally invasive. Results of our studies indicate that EEG recordings obtained with needle electrodes are not inferior to those obtained with screw electrodes. Overall, the method is designed to enhance the accuracy and efficiency of EEG recording studies while improving animal welfare. • Simplifies the placement of EEG electrodes. • Reduces the time required for electrode implantation.
Precise prediction of agricultural commodity prices is key to assisting farmers, traders, policymakers and supply chain stakeholders to alleviate the uncertainty, and enable them to make sound decisions. The fluctuation in the price of soybean is very unpredictable because of the interplay of market forces, weather unpredictability, trade, output and farming methods. This paper suggests a multi-source machine learning model that is capable of forecasting the accurate price of soy beans using past market prices, arrivals, trade as well as weather forecasting, crop supply and area under cultivation. The dataset of a complete prediction of the prices of soybean between Jan 2015 to March 2026 was built by using the data provided in AGMARKNET, NCDEX, government trade portals, meteorological agencies and state agricultural databases. Exploratory data analysis was done to learn price distributions and regional differences, then systematic data preprocessing, normalization and feature engineering such as rainfall deviation, price range and arrivals per cultivation area was done. Several machine learning and deep learning models were implemented, such as Random Forest, Gradient Boosting, XGBoost, ensemble methods, dense neural network, attention-based models, and a proposed Wide and Deep Network (AgroWDN) was tested. RMSE, MAE, MSE and R2 measures were used to evaluate model performance on training, validation and test datasets. Experimental outcomes depict that AgroWDN model is, by all means, more efficient than the traditional machine learning and deep learning methods, making the least prediction errors and R2 at 98.97; it implies a high predictive performance. These results prove that the method of multi-source data fusion and hybrid deep learning structures are effective in price prediction in agriculture. The suggested framework provides a scalable and useful solution to the profitable prediction of soybean prices and may be applied to other crops and markets.
Finite element (FE) programs such as Plaxis and Abaqus allow so-called user-defined constitutive models. However, each FE code requires the user-defined constitutive equations to be implemented in a different internal solver-specific format. This limits the reusability of the user-defined implementations within different FE codes, even when the theoretical formulation of the constitutive model is identical. This paper presents an interface that couples a constitutive formulation originally implemented as a Plaxis user-defined soil model (UDSM) with an implementation in Abaqus through a user material subroutine (UMAT). Thus, a given UDSM can easily be used as a UMAT in Abaqus. The interface preserves the original constitutive implementation and therefore the parameter and state variable structure, enabling direct execution of the Plaxis-style UDSM within an Abaqus UMAT. The proposed method is demonstrated and validated using a UDSM that describes the Hardening Soil model (HSM) through element tests and a boundary-value problem solved in Abaqus and Plaxis, confirming its accuracy and numerical stability.•UMAT interface for Abaqus that executes an external Plaxis-specific UDSM.•Generic interface that enables the plug-in of other UDSM subroutines in Abaqus with minimal modification.•Validation using the Hardening Soil model (HSM) via element tests and boundary value problem.
ω-5 gliadin is a major causative allergen associated with various types of wheat allergy, including wheat-dependent exercise-induced anaphylaxis. Recently, ω-5 gliadin-deficient wheat has been developed. However, several wheat protein studies do not use standard ω-5 gliadin because its naturally derived form is expensive, and purifying it in-house is time-consuming. Therefore, we sought to develop an inexpensive, simple method for purifying ω-5 gliadin on a small scale.▪We compared ω-5 gliadin-deficient wheat with normal wheat and screened for ω-5 gliadin bands using acid-polyacrylamide gel electrophoresis (A-PAGE) on a mini-slab electrophoresis apparatus.▪The ω-5 gliadin band was excised and sealed in dialysis tubing, and the protein was electroeluted using agarose gel electrophoresis. After electroelution, the eluted solution was filtered, dialyzed, and then freeze-dried.▪The main band of collected proteins migrated at approximately 55 kDa in SDS-PAGE, and the most intense band was identified as ω-5 gliadin using nano-LC-MS/MS.
Ambrosia beetles have become major threats to forest ecosystems, often vectoring pathogenic fungi and causing severe tree mortality. Early infestations produce only a few frass-filled pinholes, making species identification difficult without destructive sampling, which may further attract beetles. We developed a non-destructive detection method based on the specific fungal symbionts of Platypus quercivorus (Dryadomyces quercivorus) and Euwallacea interjectus (Fusarium kuroshium). Plastic inoculating needles inserted into beetle pinholes allowed sampling without injuring trees. Fungal detection was achieved through either fungal isolation, or direct DNA analysis using species-specific primers for both symbionts. This approach enables reliable, non-destructive identification of ambrosia beetles through their associated fungi.•We developed a non-destructive method that detects species-specific fungal tree pathogens of wood‑boring ambrosia beetles using plastic inoculating needles, enabling indirect identification of the associated beetle species.•For fungal detection, we confirmed the utility of species-specific primers for Fusarium kuroshium and developed a species-specific probe for Dryadomyces quercivorus.•This study provides the first report of non-destructive detection and identification of ambrosia beetles through their associated tree pathogens.
An augmented virtuality framework is presented in which the physical scene is admitted only through developer-defined geometric apertures, while all other pixels are rendered virtually. The scene initialises as a black field and uses surface-projected, overlay-style compositing so that the camera stream is visible only on circular or square meshes registered as projection surfaces. Tracking origin is configured to minimise unintended recentring, and the same method can operate either as a minimal black scene or within an optional three-dimensional environment. Main features of the framework are as follows: deterministic compositing that binds real imagery to user-defined meshes and prevents leakage outside apertures. stable alignment between virtual geometry and the physical workspace during head motion achieved through standard XR configuration. a flexible scene recipe that supports circular or square apertures and optional contextual environments without altering projection logic. The framework is intended for sensory and consumer studies that require real product interaction under controlled context and generalises to training, human factors, and rehabilitation scenarios requiring constrained visibility of the real world.
We describe a time-integrated platform based on sorbent-coated metal discs, formalized as a configurable architecture for VOC enrichment prior to gas chromatography/mass spectrometry (GC/MS) via secondary re-adsorption onto a solid-phase microextraction (SPME) fiber. A reproducible fabrication, conditioning, sampling, desorption, and re-adsorption protocol is specified, with a sorbent loading of approximately 0.2 g per 3.6 cm disc and sampling durations of 60 min. Across standard analysis replicates, the disc workflow produced higher GC/MS peak areas than direct SPME for most of the analytes, with reduced response for highly volatile compounds such as acetone. To explain this volatility-dependent behavior, we introduce a mass-transport competition framework in which the measurable signal is governed by the product of accumulated analyte mass and transfer efficiency, S = M_ads × η_transfer. The framework distinguishes the capacity-driven platform from equilibrium-based SPME. The described workflow is solvent-free, low-waste, reusable, and compatible with routine GC/MS instrumentation. Method overview:•Sorbent discs are prepared by covering a metal plate with a layer of sorbent material using a silicon adhesive.•Conditioned sorbent discs can be exposed to any gaseous samples.•Sorbent discs are heated to desorb the enriched VOCs that are subsequently re-adsorbed onto an SPME fiber to enable GC/MS analysis.
Photothermal biomodulation is used to precondition platelet-rich plasma, but standardized laboratory workflows for monitoring associated physicochemical changes remain limited. This article describes a paired ex vivo protocol for assessing selected physicochemical parameters of platelet-rich plasma before and after photothermal preconditioning.•Platelet-rich plasma is prepared from donor blood, pooled per donor, and divided into paired control and photothermally preconditioned aliquots.•The protocol enables time-course monitoring of density/turbidity, pH, and temperature from baseline to 60 min.•Application in samples from three healthy donors showed that the workflow can detect small time-dependent differences between paired aliquots.
This study presents a simple and inexpensive surfactant-free method for the synthesis of polystyrene (PS) nanoparticles that are suitable for use as model nanoplastics in environmental research. PS nanoparticles were prepared using a two-step process: polystyrene was dissolved in acetone and rapidly injected into heated deionised water (the Ouzo effect). An injection rate of 1 mL of the PS solution per 1.7 s led to the formation of the smallest nanoparticles with the average size of 40 nm. The temporal stability of the resulting nanosuspensions was also investigated. The average hydrodynamic sizes of the PS nanoparticles ranged from 40 to 44 nm over the period from 1 h to 265 d, and the corresponding zeta potentials ranged from -19.6 to -22.8 mV. The PS nanoparticles prepared using this procedure are free of stabilisers, easily reproducible, and scalable, making them a suitable reference material for further studies on the behaviour of nanoplastics.•PS nanoprecipitation is driven by solvent polarity change.•Ouzo-effect-induces nucleation and growth of nanoparticles tuneable by injection speed.•Stabiliser-free, reproducible, and stable nanoplastic particles were obtained.
Immunohistochemistry (IHC) is a widely used technique for detecting proteins in tissue sections; however, its performance is significantly influenced by the quality of antibodies and detection strategies. Conventional IgG or IgM-based antibodies often come with high production costs, variability between batches, and limited penetration into tissues, which can compromise the uniformity and reproducibility of staining. Recombinant single-chain variable fragments (scFvs) offer an attractive alternative due to their smaller size, defined molecular composition, and renewable production capabilities. In this work, we focus on optimizing IHC by chemically biotinylating scFvs, allowing for direct coupling to streptavidin-based detection systems. This method enhances signal sensitivity while eliminating the need for secondary antibodies or additional labeling steps. Biotinylated scFvs can diffuse more easily into tissue sections, streamline the staining workflow, and reduce both assay time and cost. Overall, integrating biotinylated scFvs into IHC protocols presents a robust, scalable, and reproducible strategy that addresses key limitations of conventional antibody-based methods, thus supporting more consistent and efficient protein detection in histological analyses.This protocol allowed the optimization of conventional IHC conditions by using biotinylating scFv to achieve precise, time and cost-efficient antigen visualization.
Plaque reduction neutralization tests (PRNTs) are the gold standard for measuring neutralizing antibodies but are labor-intensive, low-throughput, and subject to variability from manual plaque counting. We developed a NanoLuc-based microneutralization (mNT) assay using rMP12-NanoLuc that quantifies luminescence in culture supernatants as a surrogate for infection. The assay runs in 96-well plates without overlay, fixation, or staining, using 35 focus-forming unit (FFU) per well and a 40 hour readout with back-titration to ensure accuracy. mNT titers from vaccinated animal sera showed strong correlation with conventional PRNTs. This approach enables rapid, reproducible, high-throughput detection of RVFV neutralizing antibodies, with the main limitations being substrate cost and the requirement for a luminometer.•The assay enables high-throughput, objective neutralization testing in 96-well plates.•Optimized conditions yield mNT titers that strongly correlate with conventional PRNTs.•Limitations include NanoLuc substrate cost and the need for a luminometer.
Advancing municipal solid waste (MSW) management from disposal-oriented practices toward circular, value-driven systems requires standardized methodologies capable of identifying material composition and resource recoverable potential at the point of generation. Despite extensive research, MSW characterization remains fragmented due to inconsistences in sampling methodologies, waste sorting categories, and temporal coverage across previous studies which limit cross-site comparability, reproducibility, and constrain the reliable evaluation of potential resource recovery pathways. This lack of consistency has hindered the development of a unified framework for MSW characterization and resource assessment. This study introduces a standardized, field-validated protocol for MSW sampling and composition analysis that ensures consistent, traceable data across diverse waste sources. The protocol integrates randomized spatial sampling, systematic material sorting, and controlled subsampling for multi-site and multi-season field campaigns. Validation included MSW collection from residential, grocery, restaurant, and school MSW streams across five U.S. states, including Maryland, Idaho, Virginia, Ohio, and Mississippi, to demonstrate the protocol's ability to identify source-based composition patterns relevant to resource recovery applications. Grocery and restaurant streams were dominated by food waste and high-moisture organics, while school waste contained higher paper content and residential waste showed greater heterogeneity. Aggregation into energy-relevant fractions highlighted practical recovery pathways via anaerobic digestion or gasification, supporting data-driven planning, policy, and circular economy strategies for sustainable waste management across waste sources.
Validated techniques for androgen replacement in swine research models are limited, particularly for studies requiring controlled hormone delivery in males during early development. We adapted a silicone-based androgen implant methodology originally developed for adult female pigs to establish an androgen replacement model in castrated juvenile male pigs.•Castrated male pigs were surgically implanted with low (0.5 g), medium (1.0 g), or high (2.0 g) doses of testosterone propionate (TP), and compared with castrated controls.•Intact male pigs were included as a physiologically relevant reference group to benchmark implant-derived testosterone concentrations against endogenous androgen production during juvenile development.•Circulating testosterone was monitored weekly for 49 days to evaluate the concentration and duration of testosterone release.•Body weights were recorded weekly to assess body weight gain.Testosterone propionate implants produced a dose-dependent elevation in circulating testosterone that peaked between 7 and ​14 days post-implantation and reached or exceeded concentrations of intact males. Following peak release, testosterone levels gradually declined across all implant groups but remained elevated relative to castrated controls throughout the 49-day study period, with the medium- and high-dose groups maintaining the highest concentrations. Growth rates of animals were similar across experimental groups, indicating that TP implantation did not adversely affect overall growth during the study. These findings validate silicone-based TP surgical implants as a reliable method for sustained androgen delivery in juvenile, prepubertal pigs, establishing a tractable model for mechanistic studies of androgen action with translational relevance to human and animal health.
Automated rice seed vigor classification provides a non-invasive and scalable solution for improving agricultural decision-making. This study proposed an image-based framework to compare traditional machine learning and deep learning approaches for classifying individual rice seed vigor using standard RGB images. Machine learning models were developed using hand-crafted morphological and color features, while convolutional neural networks were employed to automatically extract visual patterns related to seed quality. Both single-time-point and multi-time-point image analysis strategies were investigated. Models trained on images captured at individual growth stages were compared with a multi-time-point ensemble approach that integrated visual information across multiple developmental stages. The ensemble approach achieved superior performance, highlighting the importance of incorporating temporal growth dynamics into vigor classification. Notably, traditional machine learning models performed comparably to deep learning models when informative features were carefully engineered. To improve transparency and reliability, interpretability techniques were applied to better understand model decisions. Overall, the findings demonstrate the practical potential of data-driven, image-based seed vigor assessment.
Assigning area-level socioeconomic measures to street addresses across historical and contemporary census years requires harmonising address, geography and deprivation datasets that change over time. This methods article describes a reproducible workflow and online implementation for assigning New Zealand Index of Socioeconomic Deprivation (NZDep) measures to street addresses for census years 1991-2023. The method integrates public Land Information New Zealand address data, openly licensed postcode boundary polygons, Stats NZ census geographies and University of Otago NZDep datasets into an indexed SQLite lookup database and Shiny address-lookup tool (https://bit.ly/nzdep). Address labels are standardised, address points are spatially linked to year-specific census geographies, and geography identifiers are joined to corresponding NZDep values. Raw NZDep scores are converted to census-year-specific national percentile ranks, allowing relative deprivation position to be expressed on a consistent 1-100 scale across census periods. The workflow supports unit-level address lookup where available and base street-address lookup only where deprivation assignment is unambiguous. The final database contained 2405,589 address records and achieved 99.65% completeness across 16,839,123 potential address-year NZDep assignments.