Exocytosis is a dynamic physiological process that enables the release of biomolecules to the surrounding environment via the fusion of membrane compartments to the plasma membrane. Understanding its mechanisms is crucial, as defects can compromise essential biological functions. The development of pH-sensitive optical reporters alongside fluorescence microscopy enables the assessment of individual vesicle exocytosis events at the cellular level. Manual annotation represents, however, a time-consuming task, prone to selection biases and human operational errors. Here, we introduce ExoJ, an automated plugin based on ImageJ2/Fiji. ExoJ identifies user-defined genuine populations of exocytosis events, recording quantitative features including intensity, apparent size and duration. We designed ExoJ to be fully user-configurable, making it suitable to study distinct forms of vesicle exocytosis regardless of the imaging quality. Our plugin demonstrates its capabilities by showcasing distinct exocytic dynamics among tetraspanins and vesicular SNAREs protein reporters. Assessment of performance on synthetic data showed ExoJ is a robust tool, capable to correctly identify exocytosis events independently of signal-to-noise ratio conditions. We propose ExoJ as a standard solution for future comparative and quantitative studies of exocytosis.

OBJECTIVE: Serum caffeine concentration is an indicator of caffeine intoxication; however, it is difficult to measure it in most emergency departments. We developed a simple estimation method using a point-of-care test kit for urinary caffeine.
METHODS: Caffeine-spiked human serum (100, 50, 25, and 10 µg/mL) was diluted 10-, 20-, 50-, and 100-fold with phosphate-buffered saline and applied to the kit. After 5 min incubation, the kit was scanned by a flatbed scanner and the membrane image was processed with ImageJ.
RESULTS: When the 20-fold diluted serum was applied, serum samples with initial caffeine concentration ≤ 25 and ≥ 50 µg/mL were caffeine-negative and -positive, respectively. When the 100-fold diluted serum was applied, none of the caffeine-spiked serum samples gave positive results. Therefore, we proposed the following test procedure: (i) 20-fold diluted serum was initially tested and (ii) 100-fold diluted serum was additionally tested when the initial result was caffeine positive. Using this procedure, caffeine concentration is expected to be classified into three levels: ≤ 25, > 25- ≤ 100, and > 100 µg/mL, which almost correspond to no or mild, severe, and potentially fatal intoxication, respectively. The test procedure was validated using postmortem heart blood from two cases of fatal caffeine intoxication (caffeine concentration: 276 and 175 µg/mL) and two cases of other intoxication.
CONCLUSIONS: Our developed method using point-of-care urinary caffeine test kits enabled simple estimation of serum caffeine concentration.

OBJECTIVE: The aim was to compare the use of different tools within the ImageJ program (polygon vs. segmented line) and their impact on the calculation of muscle area and echo intensity (EI) values in ultrasound imaging of the vastus lateralis muscle.
METHODS: Thirteen volunteers participated in this study. Ultrasound images of the vastus lateralis muscle were acquired using 2D B-mode ultrasonography and analyzed using both the polygon and segmented line tools by the same evaluator. The intraclass correlation coefficient (ICC) and coefficient of variation (CV) assessed the tools\' reliability. Bland-Altman plots were employed to verify the agreement between measurements, and linear regression analysis determined proportional bias. A paired t-test was conducted to analyze differences between the tools.
RESULTS: The reliability between tools for muscle area calculation was weak (r = 0.000; CV = 138.03 ± 0.34%), while it was excellent for EI (r = 0.871; CV = 15.19 ± 2.96%). The Bland-Altman plots indicated a large bias for muscle area (d = 195.2%) with a proportional bias (p < 0.001). For EI, the bias was (d = 15.2) with proportional bias (p = 0.028). The paired t-test revealed significant differences between the tools for area (p < 0.001) but not for EI (p = 0.060).
CONCLUSIONS: The study found significant differences in measurements obtained with the polygon and segmented line tools in ImageJ, with the polygon tool showing higher values for muscle area and lower values for EI.

BACKGROUND: Archaeobotanists and palaeoecologists extensively use geometric morphometrics to identify plant opal phytoliths. Particularly when applied to assemblages of phytoliths from concentrations retrieved from closed contexts, morphometric data from archaeological phytoliths compared with similar data from reference material may allow taxonomic attribution. Observer variation is one aspect of phytolith morphometry that has received little attention but may be an important source of error, and hence cause of potential misidentification of plant remains.
METHODS: To investigate inter- and intra-observer variation in phytolith morphometry, eight researchers (observers) from different laboratories measured 50 samples each from three phytolith morphotypes, Bilobate, Bulliform flabellate and Elongate dendritic, three times, under the auspices of the International Committee for Phytolith Morphometrics (ICPM).
METHODS: Data for 17 size and shape variables were collected for each phytolith by manually digitising a phytolith outline (mask) from a photograph, followed by measurement of the mask with open-source morphometric software.
RESULTS: Inter-observer variation ranged from 0 to 23% difference from the mean of all observers. Intra-observer variation ranged from 0 to 9% difference from the mean of individual observers per week. Inter- and intra-observer variation was generally higher among inexperienced researchers.
CONCLUSIONS: Scaling errors were a major cause of variation and occurred more with less experienced researchers, which is likely related to familiarity with data collection. The results indicate that inter- and intra-observer variation can be substantially reduced by providing clear instructions for and training with the equipment, photo capturing, software, data collection and data cleaning. In this paper, the ICPM provides recommendations to minimise variation.Advances in automatic data collection may eventually reduce inter- and intra-observer variation, but until this is common practice, the ICPM recommends that phytolith morphometric analyses adhere to standardised guidelines to assure that measured phytolith variables are accurate, consistent and comparable between different researchers and laboratories.

As rapid responders to their environments, microglia engage in functions that are mirrored by their cellular morphology. Microglia are classically thought to exhibit a ramified morphology under homeostatic conditions which switches to an ameboid form during inflammatory conditions. However, microglia display a wide spectrum of morphologies outside of this dichotomy, including rod-like, ramified, ameboid, and hypertrophic states, which have been observed across brain regions, neurodevelopmental timepoints, and various pathological contexts. We applied dimensionality reduction and clustering to consider contributions of multiple morphology measures together to define a spectrum of microglial morphological states in a mouse dataset that we used to demonstrate the utility of our toolset. Using ImageJ, we first developed a semiautomated approach to characterize 27 morphology features from hundreds to thousands of individual microglial cells in a brain region-specific manner. Within this pool of features, we defined distinct sets of highly correlated features that describe different aspects of morphology, including branch length, branching complexity, territory span, and circularity. When considered together, these sets of features drove different morphological clusters. Our tools captured morphological states similarly and robustly when applied to independent datasets and using different immunofluorescent markers for microglia. We have compiled our morphology analysis pipeline into an accessible, easy-to-use, and fully open-source ImageJ macro and R package that the neuroscience community can expand upon and directly apply to their own analyses. Outcomes from this work will supply the field with new tools to systematically evaluate the heterogeneity of microglia morphological states across various experimental models and research questions.

Animal and plant colouration presents a striking dimension of phenotypic variation, the study of which has driven general advances in ecology, evolution, and animal behaviour. Quantitative Colour Pattern Analysis (QCPA) is a dynamic framework for analysing colour patterns through the eyes of non-human observers. However, its extensive array of user-defined image processing and analysis tools means image analysis is often time-consuming. This hinders the full use of analytical power provided by QCPA and its application to large datasets. Here, we offer a robust and comprehensive batch script, allowing users to automate many QCPA workflows. We also provide a complimentary set of useful R scripts for downstream data extraction and analysis. The presented batch processing extension will empower users to further utilise the analytical power of QCPA and facilitate the development of customised semi-automated workflows. Such quantitatively scaled workflows are crucial for exploring colour pattern spaces and developing ever-richer frameworks for analysing organismal colouration accounting for visual perception in animals other than humans. These advances will, in turn, facilitate testing hypotheses on the function and evolution of vision and signals at quantitative and qualitative scales, which are otherwise computationally unfeasible.
UNASSIGNED: The online version contains supplementary material available at 10.1007/s10682-024-10291-7.

Regular spatial patterns are ubiquitous forms of organization in nature. In animals, regular patterns can be found from the cellular scale to the tissue scale, and from early stages of development to adulthood. To understand the formation of these patterns, how they assemble and mature, and how they are affected by perturbations, a precise quantitative description of the patterns is essential. However, accessible tools that offer in-depth analysis without the need for computational skills are lacking for biologists. Here, we present PatternJ, a novel toolset to analyze regular one-dimensional patterns precisely and automatically. This toolset, to be used with the popular imaging processing program ImageJ/Fiji, facilitates the extraction of key geometric features within and between pattern repeats in static images and time-lapse series. We validate PatternJ with simulated data and test it on images of sarcomeres from insect muscles and contracting cardiomyocytes, actin rings in neurons, and somites from zebrafish embryos obtained using confocal fluorescence microscopy, STORM, electron microscopy, and brightfield imaging. We show that the toolset delivers subpixel feature extraction reliably even with images of low signal-to-noise ratio. PatternJ\'s straightforward use and functionalities make it valuable for various scientific fields requiring quantitative one-dimensional pattern analysis, including the sarcomere biology of muscles or the patterning of mammalian axons, speeding up discoveries with the bonus of high reproducibility.

Proteins often show alterations in their subcellular localization with changing environmental conditions; transcription factors enter the nucleus or are actively removed from the nucleus; some even bind to endo-membranes by conditional membrane anchors; and other proteins and mRNA arrange in RNA granules. These are some examples of the complex regulation of subcellular localization, which often depends on posttranslational modifications and is triggered by environmental stressors. The challenge is the precise identification of the compartments, the quantitative analysis of proteins, which reside in multiple compartments, and their transport dynamics. Therefore, appropriate compartment markers and routines for a reproducible quantitative workflow are required.

In this paper we present OLEAtool, a new software tool for palynological research to facilitate morphological analysis and measurements of Olea pollen. OLEAtool is a macro extension for use with ImageJ, an open-access and freely available image analysis software, and was developed as a component of the OLEA-project. This larger project examines olive tree expansion and mosaic landscape formation on the Balearic Islands. Pollen analysis of both fossil and modern grains has been proven useful for characterizing cultivars and therefore an important method for studying olive tree cultivation in the Mediterranean. However, these methods still struggle with distinguishing between wild and cultivated varieties. Traditional morphological analysis of pollen grains can be a difficult and time-consuming task. However, OLEAtool dramatically increases the speed of collecting data on pollen grains, expands the number of variables an analyst can measure, and greatly enhances the replicability of morphological analysis.
Pollen plays a key role in reproduction for seed plants. Palynology is the study of pollen and spores with a wide variety of applications, such as the study of past landscapes or the characterization of agronomic cultivars. The onset of the olive tree management and the origin of its domestication in the Mediterranean still remains unclear, despite great advances in methods and interpretation over the last decades. Pollen analysis may help in identifying the distribution and historical trends of this species, but it is still difficult to distinguish between cultivated and wild varieties through pollen analysis. To shed some light into this issue, we have developed OLEAtool, a new extension for the open-source image analysis software, ImageJ. OLEAtool uses image analysis and replicable measurements to standardize and improve pollen morphology studies.

UNASSIGNED: To investigate the long-term efficacy and safety of adalimumab(ADA) in the treatment of patients with serpiginous choroiditis (SC) refractory to conventional therapy through quantitative parameters.
UNASSIGNED: A retrospective analysis was conducted on patients diagnosed with SC clinically and through fundus autofluorescence(FAF). Patients receiving ADA treatment were included. Demographic and clinical characteristics of the patients, association with tuberculosis (TB) infection, number of immunosuppressive therapies, recurrences, best corrected visual acuity (BCVA) change, and ADA-related side effects were recorded. The progression rate before and after ADA was calculated based on the area involved by FAF.
UNASSIGNED: Sixteen eyes of 8 patients (3 female/5 male) were enrolled to the study. The median (IQR) age was 53.5 (16.5) years. Diagnosis was SC in 4, ampiginous choroiditis in 3, and TB-related serpiginous-like choroiditis in 1 patient. Peripapillary involvement was present in 10 of 16 eyes. The area involved by FAF continued to progress under ADA treatment, however the progression rate was decreased (p = 0.143).The BCVA was preserved (p = 0.772). The number of systemic and local treatments decreased with ADA (p = 0.025 and 0.019, respectively). Additionally, the number of recurrences was reduced with ADA (p = 0.002). Median (IQR) follow-up was 45(28.75) months. Two patients experienced ADA-related side effects (pulmonary TBand rash).
UNASSIGNED: Our findings suggest a promising role for ADA in halting the progression of SC and have implications for improving outcomes. Despite the evidence in the literature at the level of case reports, ADA can be used effectively with close monitoring for potential risks.