Molecular Specificity Research Articles

Development and Validation of an RPA Assay for Detecting Xanthomonas citri subsp. citri A, A* and Aw and X. fuscans subsp. aurantifolii B and C

Citrus canker, caused by Xanthomonas citri subsp. citri (Xcc) and X. fuscans subsp. aurantifolii (Xfa), is a destructive disease of citrus. It is sparsely distributed in the Caribbean, and effective biosecurity measures, including accurate pathogen detection systems, are essential to prevent further spread. Current in-field screening methods rely on visual symptom identification and serological tools like Agdia’s X. axonopodis subsp. citri (Xac) ImmunoStrips®. However, they failed to detect the Aw and C pathotypes in this study. Nucleic acid amplification is the gold standard for confirming detection but is resource-intensive and less accessible in Caribbean plant diagnostic laboratories and regulatory services. To address this, a rapid recombinase polymerase amplification (RPA) assay was developed using a portable fluorometer and primers designed to detect all canker-causing pathotypes. The RPA assay accurately detected all five citrus canker pathotypes and was selective against Xanthomonas euvesicatoria pv. citrumelonis, the fastidious citrus greening bacteria Candidatus Liberibacter asiaticus, and the xylem-limited bacterial pathogen Xylella fastidiosa. However, X. perforans, X. citri pv. glycines, and X. citri pv. phaseoli, pathogens unrelated to citrus and unlikely to be present in citrus, were detected. Real-time detection was completed in 25 minutes with high sensitivity levels of 0.001 pg/µl (Xcc A), 0.1 pg/µl (Xfa B), and 1 pg/µl (Xfa C) of DNA. This RPA assay offers a robust, in-field detection method, combining molecular sensitivity and specificity with the field-friendly simplicity of crude extraction and single-tube reactions.

Exploring Innovative Approaches for the Analysis of Micro- and Nanoplastics: Breakthroughs in (Bio)Sensing Techniques

Plastic pollution, particularly from microplastics (MPs) and nanoplastics (NPs), has become a critical environmental and health concern due to their widespread distribution, persistence, and potential toxicity. MPs and NPs originate from primary sources, such as cosmetic microspheres or synthetic fibers, and secondary fragmentation of larger plastics through environmental degradation. These particles, typically less than 5 mm, are found globally, from deep seabeds to human tissues, and are known to adsorb and release harmful pollutants, exacerbating ecological and health risks. Effective detection and quantification of MPs and NPs are essential for understanding and mitigating their impacts. Current analytical methods include physical and chemical techniques. Physical methods, such as optical and electron microscopy, provide morphological details but often lack specificity and are time-intensive. Chemical analyses, such as Fourier transform infrared (FTIR) and Raman spectroscopy, offer molecular specificity but face challenges with smaller particle sizes and complex matrices. Thermal analytical methods, including pyrolysis gas chromatography–mass spectrometry (Py-GC-MS), provide compositional insights but are destructive and limited in morphological analysis. Emerging (bio)sensing technologies show promise in addressing these challenges. Electrochemical biosensors offer cost-effective, portable, and sensitive platforms, leveraging principles such as voltammetry and impedance to detect MPs and their adsorbed pollutants. Plasmonic techniques, including surface plasmon resonance (SPR) and surface-enhanced Raman spectroscopy (SERS), provide high sensitivity and specificity through nanostructure-enhanced detection. Fluorescent biosensors utilizing microbial or enzymatic elements enable the real-time monitoring of plastic degradation products, such as terephthalic acid from polyethylene terephthalate (PET). Advancements in these innovative approaches pave the way for more accurate, scalable, and environmentally compatible detection solutions, contributing to improved monitoring and remediation strategies. This review highlights the potential of biosensors as advanced analytical methods, including a section on prospects that address the challenges that could lead to significant advancements in environmental monitoring, highlighting the necessity of testing the new sensing developments under real conditions (composition/matrix of the samples), which are often overlooked, as well as the study of peptides as a novel recognition element in microplastic sensing.

Comprehensive Overview of Molecular, Imaging, and Therapeutic Challenges in Rectal Mucinous Adenocarcinoma

Rectal cancer is one of the most frequent malignancies worldwide. The most common histological type is adenocarcinoma, followed by mucinous adenocarcinoma. The outcome is less favorable for the mucinous type, yet the treatment course is the same. The aim of this systematic literature review is to assess existing information in order to improve survival in rectal mucinous adenocarcinoma (RMA) and establish a starting point for future research. A systematic search of PubMed, Google Scholar, and Web of Science online libraries was performed in October 2024, evaluating studies regarding clinicopathological and genetic features in connection with targeted treatment and survival outcomes in RMA, using the terms “rectal cancer”, “rectum”, “mucinous adenocarcinoma”, or a combination of the terms. We selected 23 studies, 10 of them regarding the diagnostic implications and 13 discussing the treatment strategies and prognosis of this histological subtype. There were six studies addressing the imaging aspects, highlighting the distinct features of mucinous histology in MRI. The molecular specifics were detailed in four studies, outlining the molecular footprint. The prognosis and treatment course were addressed in 12 studies. The inflammation index prognosis, complete response to neoadjuvant chemotherapy, and surgical aspects were addressed individually in each study. We encapsulated the molecular and clinicopathological characteristics of RMA, as well as diagnostic and treatment approaches, to establish a baseline of references for the benefit of daily practice and further research.

Localized InVivo Prodrug Activation Using Radionuclides.

Radionuclides used for imaging and therapy can show high molecular specificity in the body with appropriate targeting ligands. We hypothesized that local energy delivered by molecularly targeted radionuclides could chemically activate prodrugs at disease sites while avoiding activation in off-target sites of toxicity. As proof of principle, we tested whether this strategy of radionuclide-induced drug engagement for release (RAiDER) could locally deliver combined radiation and chemotherapy to maximize tumor cytotoxicity while minimizing off-target exposure to activated chemotherapy. Methods: We screened the ability of radionuclides to chemically activate a model radiation-activated prodrug consisting of the microtubule-destabilizing monomethyl auristatin E (MMAE) caged by a radiation-responsive phenyl azide, and we interpreted experimental results using the radiobiology computational simulation suite TOPAS-nBio. RAiDER was evaluated in syngeneic mouse models of cancer using the fibroblast activation protein inhibitor (FAPI) agents [99mTc]Tc-FAPI-34 and [177Lu]Lu-FAPI-04 and the prostate-specific membrane antigen (PSMA) agent [177Lu]Lu-PSMA-617, combined with caged MMAE or caged exatecan. Biodistribution in mice, combined with clinical dosimetry, estimated the relationship between radiopharmaceutical uptake in patients and anticipated concentrations of activated prodrug using RAiDER. Results: RAiDER efficiency varied by 70-fold across radionuclides (99mTc > 111In > 177Lu > 64Cu > 32P > 68Ga > 223Ra > 18F), yielding up to 320 nM prodrug activation/Gy of exposure from 99mTc. Computational simulations implicated low-energy electron-mediated free radical formation as driving prodrug activation. Radionuclide-activated caged MMAE restored the prodrug's ability to destabilize microtubules and increased its cytotoxicity by up to 2,600-fold that of the nonactivated prodrug. Mice treated with [99mTc]Tc-FAPI-34 and caged MMAE accumulated concentrations of activated MMAE that were up to 3,000 times greater in tumors than in other tissues. RAiDER with [99mTc]Tc-FAPI-34 or [177Lu]Lu-FAPI-04 delayed tumor growth, whereas monotherapies did not (P < 0.003). Clinically guided dosimetry suggests sufficient radiation doses can be delivered to activate therapeutically meaningful levels of prodrug. Conclusion: This proof-of-concept study shows that RAiDER is compatible with multiple radionuclides commonly used in nuclear medicine and can potentially improve the efficacy of radiopharmaceutical therapies to treat cancer safely. RAiDER thus shows promise as an effective strategy to treat disseminated malignancies and broadens the capability of radiopharmaceuticals to trigger diverse biologic and therapeutic responses.

A practical approach to quantitative analytical surface-enhanced Raman spectroscopy.

Many of the features of SERS, such as its high sensitivity, molecular specificity and speed of analysis make it attractive as an analytical technique. However, SERS currently remains a specialist technique which has not yet entered the mainstream of analytical chemistry. Therefore, this review draws out the underlying principles for analytical SERS and provides practical tips and tricks for SERS quantitation. The aim is to show the readers how to rationally design their SERS experiments to improve quantitation performance. We begin by introducing the three core components in SERS analysis: (1) the enhancing substrate material, (2) the Raman instrument and (3) the processed data that is used to establish a calibration curve. This is followed by discussion of the analytical figures of merit relevant to SERS. In the following sections each of the three essential components in SERS quantitation and how they affect the quality of the analysis are described in more detail using examples from the literature. Finally, we highlight the current challenges in applying SERS to the analysis of complex real-life samples and briefly introduce the state-of-the-art developments on multifunctional substrates, digital SERS and AI-assisted data processing, which will help SERS rise to the challenge of moving out into routine real-world analysis.

Hierarchical structures of surface-accessible plasmonic gold and silver nanoparticles for SERS detection.

Surface-enhanced Raman spectroscopy (SERS) is a highly sensitive analytical technique with excellent molecular specificity. However, separate pristine nanoparticles produce relatively weak Raman signals. It is necessary to focus on increasing the "hot-spot" density generated at the nanogaps between the adjacent nanoparticles (second-generation SERS hotspot), thus significantly boosting the Raman signal by creating an electromagnetic field. This study employed a self-assembly method without using modifiers based on promoter-induced self-assembly to synthesize stable and plasmonically active surfaces from citrate-reduced Ag and Au nanoparticles. Hierarchical structures like Pickering emulsions (PEs) and stable plasmonic aggregates (SPAs) were studied, focusing on controlling their sizes using "promoters" (TBANO3). The sizes of the SPAs were also adjusted from 85.5 nm to 136 nm by regulating the ratio of the water to the oil phase. Furthermore, to understand the distribution of "hot-spots" on these Au or Ag hierarchical structures, the electric field was simulated using the finite difference time domain (FDTD) software. Third-generation hotspots were also created using hybrid structures of plasmonic nanomaterials and surfaces to significantly improve SERS detection by depositing the colloidosome structure on Cu foil (AgSPAs/Cu substrate). The SERS signal was amplified by achieving an enhancement factor of 7 × 107, compared to an enhancement factor of 2 × 106 when using the AgSPA/glass substrate. Significantly, the limits of detection (LOD) and quantification (LOQ) for the colloidosome substrate to detect crystal violet were found to be 4.51 ppb and 13.66 ppb, respectively. The reproducibility of the prepared substrates was demonstrated to be commendably high, characterized by relative standard deviations (RSDs) of 8.00% for the 1177 cm-1 peak, 7.61% for the 1588 cm-1 peak, and 9.35% for the 1619 cm-1 peak. The AgSPAs/Cu substrate's demonstrated reliability made it suitable for detecting and quantifying analytes, potentially for determining trace amounts of pesticide residues. The LOD and LOQ for thiram detection were calculated to be 0.1 ppm and 0.3 ppm, respectively. These findings highlight the effectiveness of increasing electromagnetic field density for SERS enhancement.

Harnessing Raman spectroscopy and multimodal imaging of cartilage for osteoarthritis diagnosis

Osteoarthritis (OA) is a complex disease of cartilage characterised by joint pain, functional limitation, and reduced quality of life with affected joint movement leading to pain and limited mobility. Current methods to diagnose OA are predominantly limited to X-ray, MRI and invasive joint fluid analysis, all of which lack chemical or molecular specificity and are limited to detection of the disease at later stages. A rapid minimally invasive and non-destructive approach to disease diagnosis is a critical unmet need. Label-free techniques such as Raman Spectroscopy (RS), Coherent anti-Stokes Raman scattering (CARS), Second Harmonic Generation (SHG) and Two Photon Fluorescence (TPF) are increasingly being used to characterise cartilage tissue. However, current studies are based on whole tissue analysis and do not consider the different and structurally distinct layers in cartilage. In this work, we use Raman spectroscopy to obtain signatures from the superficial (top) and deep (bottom) layer of healthy and osteoarthritic cartilage samples from 64 patients (19 control and 45 OA). Spectra were acquired both in the ‘fingerprint’ region from 700 to 1720 cm− 1 and high-frequency stretching region from 2500 to 3300 cm− 1. Principal component and linear discriminant analysis was used to identify the peaks that contributed significantly to classification accuracy of the different samples. The most pronounced differences were observed at the proline (855 cm− 1 and 921 cm− 1) and hydroxyproline (877 cm− 1 and 938 cm− 1), sulphated glycosaminoglycan (sGAG) (1064 cm− 1 and 1380 cm− 1) frequencies for both control and OA as well as the 1245 cm− 1 and 1272 cm− 1, 1320 cm− 1 and 1345 cm− 1, 1451 cm− 1 collagen modes were altered in OA samples, consistent with expected collagen structural changes. Classification accuracy based on Raman fingerprint spectral analysis of superficial and deep layer cartilage for controls was found to be 97% and 93% on using individual/all spectra and, 100% and 95% on using mean spectra per patient, respectively. OA diseased cartilage was classified with an accuracy of 88% and 84% for individual/all spectra, and 96% and 95% for mean spectra per patient based on analysis of the superficial and the deep layers, respectively. Raman spectra from the C-H stretching region (2500–3300 cm− 1) resulted in high classification accuracy for identification of different layers and OA diseased cartilage but low accuracy for controls. Differential changes in superficial and deep layer cartilage signatures were observed with age (under 60 and over 60 years), in contrast, less significant differences were observed with gender. Prominent chemical changes in the different layers of cartilage were preliminarily imaged using CARS, SHG and TPF. Cell clustering was observed in OA together with differences in pericellular matrix and collagen structure in the superficial and the deep layers correlating with the Raman spectral analysis. The current study demonstrates the potential of Raman Spectroscopy and multimodal imaging to interrogate cartilage tissue and provides insight into the chemical and structural composition of its different layers with significant implications for OA diagnosis for an increasing aging demographic.

Initial regional cytoarchitectonic differences in dorsal and orbitobasal human developing frontal cortex revealed by spatial transcriptomics.

Early development of the human fetal cerebral cortex involves a set of precisely coordinated molecular processes that remains rather underexplored. Previous studies indicate that the laminar identity and the molecular specification of cortical neurons driven by genetic programming, as well as associated histogenetic events begin during early fetal development. Our recent study discovered unique regional cytoarchitectonic features in the developing human frontal lobe, including migratory waves of postmitotic neurons in the dorsal frontal cortex and the "double plate" feature in orbitobasal cortex (Kopić et al. in Cells 12:231, 2023). Notably, neurons of these two cytoarchitectonic features typically express deep projection neuron (DPN) markers (TBR1, TLE4, SOX5). This paper aims to conduct an in-depth investigation of these cytoarchitectonic features at the transcriptomic level, whilst preserving spatial information. Here, we employed NanoString GeoMx™ Digital Spatial Profiler (DSP) technology to examine gene expression differences in the transient cortical compartments of the dorsal and ventral regions of the developing frontal lobe, focusing specifically on 15 post-conceptional weeks (PCW), that is a critical period for subplate formation. We identified multiple differentially expressed genes between the transient cellular compartments of the dorsal and orbitobasal regions of the developing human frontal cortex. These new findings additionally confirm that regional patterning and specification of the prospectivehigher-order association prefrontal cortex emerges early in fetal development, contributing to the highly organized cortical architecture of the human brain.

Stepwise molecular specification of excitatory synapse diversity onto cerebellar Purkinje cells.

Brain function relies on the generation of a large variety of morphologically and functionally diverse, but specific, neuronal synapses. Here we show that, in mice, the initial formation of synapses on cerebellar Purkinje cells involves a presynaptic protein-CBLN1, a member of the C1q protein family-that is secreted by all types of excitatory inputs. The molecular program then evolves only in one of the Purkinje cell inputs, the inferior olivary neurons, with the additional expression of the presynaptic secreted proteins C1QL1, CRTAC1 and LGI2. These molecules work in concert to specify the mature connectivity pattern on the Purkinje cell target. These results show that some inputs actively and gradually specify their synaptic molecular identity, while others rely on the 'original molecular code'. Thus, the molecular specification of excitatory synapses, crucial for proper circuit function, is acquired in a stepwise manner during mouse postnatal development and obeys input-specific rules.

Simple and low-cost thrombin activity assay using screen-printed electrodes with portable electrochemiluminescence device

Real-time monitoring of thrombin activity is essential for preventing, diagnosing, and treating coagulation-related diseases. Herein, we present a simple, disposable electrochemiluminescence (ECL) biosensor for thrombin activity assay based on screen-printed electrodes (SPE). The thrombin-specific peptide substrate Mpr (4-Methoxybenzyl group)-GGRK-Fc (ferrocene) was identified from four candidates using molecular docking and specificity constant experiments. Mpr-GGRK-Fc exhibited the highest apparent specificity constant (kcat/KM) of 2.09 × 1012 M−1 s−1, indicating superior affinity and specificity for thrombin. Thrombin catalyzes the cleavage of Mpr-GGRK-Fc, resulting in the detachment of Fc from the electrode surface, which leads to an increase in ECL intensity. Under optimal conditions, the biosensor exhibits a wide linear range from 1.0 × 10−4 U/mL to 1.0 U/mL, with a low detection limit of 4.02 × 10−5 U/mL. The biosensor shows high specificity for thrombin among a range of proteins. Compared to commercial fluorescence kits, our biosensor offers superior sensitivity, selectivity, and stability in detecting thrombin activity in whole blood, making it a promising tool for bedside clinical applications.

Assessing the effect of model specification and prior sensitivity on Bayesian tests of temporal signal.

Our understanding of the evolution of many microbes has been revolutionised by the molecular clock, a statistical tool to infer evolutionary rates and timescales from analyses of biomolecular sequences. In all molecular clock models, evolutionary rates and times are jointly unidentifiable and 'calibration' information must therefore be used. For many organisms, sequences sampled at different time points can be employed for such calibration. Before attempting to do so, it is recommended to verify that the data carry sufficient information for molecular dating, a practice referred to as evaluation of temporal signal. Recently, a fully Bayesian approach, BETS (Bayesian Evaluation of Temporal Signal), was proposed to overcome known limitations of other commonly used techniques such as root-to-tip regression or date randomisation tests. BETS requires the specification of a full Bayesian phylogenetic model, posing several considerations for untangling the impact of model choice on the detection of temporal signal. Here, we aimed to (i) explore the effect of molecular clock model and tree prior specification on the results of BETS and (ii) provide guidelines for improving our confidence in molecular clock estimates. Using microbial molecular sequence data sets and simulation experiments, we assess the impact of the tree prior and its hyperparameters on the accuracy of temporal signal detection. In particular, highly informative priors that are inconsistent with the data can result in the incorrect detection of temporal signal. In consequence, we recommend: (i) using prior predictive simulations to determine whether the prior generates a reasonable expectation of parameters of interest, such as the evolutionary rate and age of the root node, (ii) conducting prior sensitivity analyses to assess the robustness of the posterior to the choice of prior, and (iii) selecting a molecular clock model that reasonably describes the evolutionary process.

Molecular Lineages and Spatial Distributions of Subplate Neurons in the Human Fetal Cerebral Cortex.

The expansion of neural progenitors and production of distinct neurons are crucial for architectural assembly and formation of connectivity in human brains. Subplate neurons (SPNs) are among the firstborn neurons in the human fetal cerebral cortex, and play a critical role in establishing intra- and extracortical connections. However, little is known about SPN origin and developmental lineages. In this study, spatial landscapes and molecular trajectories of SPNs in the human fetal cortices from gestational weeks (GW) 10 to 25 are created by performing spatial transcriptomics and single-cell RNA sequencing. Genes known to be evolutionarily human-specific and genes associated with extracellular matrices (ECMs) are found to maintain stable proportions of subplate neurons among other neuronal types. Enriched ECM gene expression in SPNs varies in distinct cortical regions, with the highest level in the frontal lobe of human fetal brains. This study reveals molecular origin and lineage specification of subplate neurons in the human fetal cerebral cortices, and highlights underpinnings of SPNs to cortical neurogenesis and early structural folding.

Molecular profiling of invertebrate glia.

Caenorhabditis elegans and Drosophila melanogaster are powerful experimental models for uncovering fundamental tenets of nervous system organization and function. Findings over the last two decades show that molecular and cellular features are broadly conserved between invertebrates and vertebrates, indicating that insights derived from invertebrate models can broadly inform our understanding of glial operating principles across diverse species. In recent years, these model systems have led to exciting discoveries in glial biology and mechanisms of glia-neuron interactions. Here, we summarize studies that have applied current state-of-the-art "-omics" techniques to C. elegans and D. melanogaster glia. Coupled with the remarkable acceleration in the pace of mechanistic studies of glia biology in recent years, these indicate that invertebrate glia also exhibit striking molecular complexity, specificity, and heterogeneity. We provide an overview of these studies and discuss their implications as well as emerging questions where C. elegans and D. melanogaster are well-poised to fill critical knowledge gaps in our understanding of glial biology.

ExoSloNano: Multi-Modal Nanogold Tags for identification of Macromolecules in Live Cells & Cryo-Electron Tomograms.

In situ cryo-Electron Microscopy (cryo-EM) enables the direct interrogation of structure-function relationships by resolving macromolecular structures in their native cellular environment. Tremendous progress in sample preparation, imaging and data processing over the past decade has contributed to the identification and determination of large biomolecular complexes. However, the majority of proteins are of a size that still eludes identification in cellular cryo-EM data, and most proteins exist in low copy numbers. Therefore, novel tools are needed for cryo-EM to identify the vast majority of macromolecules across multiple size scales (from microns to nanometers). Here, we introduce and validate novel nanogold probes that enable the detection of specific proteins using cryo-ET (cryo-Electron Tomography) and resin-embedded correlated light and electron microscopy (CLEM). We demonstrate that these nanogold probes can be introduced into live cells, in a manner that preserves intact molecular networks and cell viability. We use this system to identify both cytoplasmic and nuclear proteins by room temperature EM, and resolve associated structures by cryo-ET. We further employ gold particles of different sizes to enable future multiplexed labeling and structural analysis. By providing high efficiency protein labeling in live cells and molecular specificity within cryo-ET tomograms, we establish a broadly enabling tool that significantly expands the proteome available to electron microscopy.

Molecular imaging supports the development of multispecific cancer antibodies.

Multispecific antibodies are engineered antibody derivatives that can bind to two or more distinct epitopes or antigens. Unlike mixtures of monospecific antibodies, the binding properties of multispecific antibodies enable two specific molecules to be physically linked, a characteristic with important applications in cancer therapy. The field of multispecific antibodies is highly dynamic and expanding rapidly; to date, 15 multispecific antibodies have been approved for clinical use, of which 11 were approved for oncological indications, and more than 100 new antibodies are currently in clinical development. Nevertheless, substantial challenges limit the applications of multispecific antibodies in cancer therapy, particularly inefficient targeting of solid tumours and substantial adverse effects. Both PET and single photon emission CT imaging can reveal the biodistribution and complex pharmacology of radiolabelled multispecific antibodies. This Review summarizes the insights obtained from preclinical and clinical molecular imaging studies of multispecific antibodies, focusing on their structural properties, such as molecular weight, shape, target specificity, affinity and avidity. The opportunities associated with use of molecular imaging studies to support the clinical development of multispecific antibody therapies are also highlighted.

Manipulating the molecular specificity of transcriptional biosensors for tryptophan metabolites and analogs

Tryptophan and its metabolites, produced by the gut microbiota, are pivotal for human physiological and mental health. Yet, quantifying these structurally similar compounds with high specificity remains a challenge, hindering point-of-care diagnostics and targeted therapeutic interventions. Leveraging the innate specificity and adaptability of biological systems, we present a biosensing approach capable of identifying specific metabolites in complex contexts with minimal cross-activity. This study introduces a generalizable strategy that combines evolutionary analysis, key ligand-binding residue identification, and mutagenesis scanning to pinpoint ligand-specific transcription factor variants. Furthermore, we uncover regulatory mechanisms within uncharacterized ligand-binding domains, whether in homodimer interfaces or monomers, through structural prediction and ligand docking. Notably, our "plug-and-play" strategy broadens the detection spectrum, enabling the exclusive biosensing of indole-3-acetic acid (an auxin), tryptamine, indole-3-pyruvic acid, and other tryptophan derivatives in engineered probiotics. This groundwork paves the way to create highly specific transcriptional biosensors for potential clinical, agricultural, and industrial use.

Single-Shot Ultra-Widefield Polarization-Diversity Optical Coherence Tomography for Assessing Retinal and Choroidal Pathologies.

Background: Optical coherence tomography (OCT) is a leading ocular imaging modality, known for delivering high-resolution volumetric morphological images. However, conventional OCT systems are limited by their narrow field-of-view (FOV) and their reliance on scattering contrast, lacking molecular specificity. Methods: To address these limitations, we developed a custom-built 105∘ ultra-widefield polarization-diversity OCT (UWF PD-OCT) system for assessing various retinal and choroidal conditions, which is particularly advantageous for visualizing peripheral retinal abnormalities. Patients with peripheral lesions or pigmentary changes were imaged using the UWF PD-OCT to evaluate the system's diagnostic capabilities. Comparisons were made with conventional swept-source OCT and other standard clinical imaging modalities to highlight the benefits of depolarization contrast for identifying pathological changes. Results: The molecular-specific contrast offered by UWF PD-OCT enhanced the detection of disease-specific features, particularly in the peripheral retina, by capturing melanin distribution and pigmentary changes in a single shot. This detailed visualization allows clinicians to monitor disease progression with greater precision, offering more accurate insights into retinal and choroidal pathologies. Conclusions: Integrating UWF PD-OCT into clinical practice represents a major advancement in ocular imaging, enabling comprehensive views of retinal pathologies that are difficult to capture with current modalities. This technology holds great potential to transform the diagnosis and management of retinal and choroidal diseases by providing unique insights into peripheral retinal abnormalities and melanin-specific changes, critical for early detection and timely intervention.

Leveraging ultra-high field (7T) MRI in psychiatric research.

Non-invasive brain imaging has played a critical role in establishing our understanding of the neural properties that contribute to the emergence of psychiatric disorders. However, characterizing core neurobiological mechanisms of psychiatric symptomatology requires greater structural, functional, and neurochemical specificity than is typically obtainable with standard field strength MRI acquisitions (e.g., 3T). Ultra-high field (UHF) imaging at 7 Tesla (7T) provides the opportunity to identify neurobiological systems that confer risk, determine etiology, and characterize disease progression and treatment outcomes of major mental illnesses. Increases in scanner availability, regulatory approval, and sequence availability have made the application of UHF to clinical cohorts more feasible than ever before, yet the application of UHF approaches to the study of mental health remains nascent. In this technical review, we describe core neuroimaging methodologies which benefit from UHF acquisition, including high resolution structural and functional imaging, single (1H) and multi-nuclear (e.g., 31P) MR spectroscopy, and quantitative MR techniques for assessing brain tissue iron and myelin. We discuss advantages provided by 7T MRI, including higher signal- and contrast-to-noise ratio, enhanced spatial resolution, increased test-retest reliability, and molecular and neurochemical specificity, and how these have begun to uncover mechanisms of psychiatric disorders. Finally, we consider current limitations of UHF in its application to clinical cohorts, and point to ongoing work that aims to overcome technical hurdles through the continued development of UHF hardware, software, and protocols.

MSIGen: An Open-Source Python Package for Processing and Visualizing Mass Spectrometry Imaging Data.

Mass spectrometry imaging (MSI) provides information about the spatial localization of molecules in complex samples with high sensitivity and molecular selectivity. Although point-wise data acquisition, in which mass spectra are acquired at predefined points in a grid pattern, is common in MSI, several MSI techniques use line-wise data acquisition. In line-wise mode, the imaged surface is continuously sampled along consecutive parallel lines and MSI data are acquired as a collection of line scans across the sample. Furthermore, aside from the standard imaging mode in which full mass spectra are acquired, other acquisition modes have been developed to enhance molecular specificity, enable separation of isobaric and isomeric species, and improve sensitivity to facilitate the imaging of low abundance species. These methods, including MS/MS-MSI in both MS2 and MS3 modes, multiple-reaction monitoring (MRM)-MSI, and ion mobility spectrometry (IMS)-MSI have all demonstrated their capabilities, but their broader implementation is limited by the existing MSI analysis software. Here, we present MSIGen, an open-source Python package for the visualization of MSI experiments performed in line-wise acquisition mode containing MS1, MS2, MRM, and IMS data, which is available at https://github.com/LabLaskin/MSIGen. The package supports multiple vendor-specific and open-source data formats and contains tools for targeted extraction of ion images, normalization, and exportation as images, arrays, or publication-style images. MSIGen offers multiple interfaces, allowing for accessibility and easy integration with other workflows. Considering its support for a wide variety of MSI imaging modes and vendor formats, MSIGen is a valuable tool for the visualization and analysis of MSI data.

A first-in-kind MAPK13 inhibitor that can correct stem cell reprogramming and post-injury disease.

The stress kinase MAPK13 (aka p38δ-MAPK) is an attractive entry point for therapeutic intervention because it regulates the structural remodeling that can develop after epithelial barrier injury in the lung and likely other tissue sites. However, a selective, safe, and effective MAPK13 inhibitor is not yet available for experimental or clinical application. Here we identify a first-in-kind MAPK13 inhibitor using structure-based drug design combined with a screening funnel for cell safety and molecular specificity. This inhibitor (designated NuP-4) down-regulates basal-epithelial stem cell reprogramming, structural remodeling, and pathophysiology equivalently to Mapk13 gene-knockout in mouse and mouse organoid models of post-viral lung disease. This therapeutic benefit persists after stopping treatment as a sign of disease modification and attenuates key aspects of inflammation and remodeling as an indication of disease reversal. Similarly, NuP-4 treatment can directly control cytokine-stimulated growth, immune activation, and mucinous differentiation in human basal-cell organoids. The data thereby provide a new tool and potential fix for long-term stem cell reprogramming after viral injury and related conditions that require MAPK13 induction-activation.