Traditional Fluorescence Research Articles

Super resolution reconstruction of fluorescence microscopy images by a convolutional network with physical priors

Super-solution fluorescence microscopy, such as single-molecule localization microscopy (SMLM), is effective in observing subcellular structures and achieving excellent enhancement in spatial resolution in contrast to traditional fluorescence microscopy. Recently, deep learning has demonstrated excellent performance in SMLM in solving the trade-offs between spatiotemporal resolution, phototoxicity, and signal intensity. However, most of these researches rely on sufficient and high-quality datasets. Here, we propose a physical priors-based convolutional super-resolution network (PCSR), which incorporates a physical-based loss term and an initial optimization process based on the Wiener filter to create excellent super-resolution images directly using low-resolution images. The experimental results demonstrate that PCSR enables the achievement of a fast reconstruction time of 100 ms and a high spatial resolution of 10 nm by training on a limited dataset, allowing subcellular research with high spatiotemporal resolution, low cell phototoxic illumination, and high accessibility. In addition, the generalizability of PCSR to different live cell structures makes it a practical instrument for diverse cell research.

Use of Proximity Ligation Assay to Study Lymphoid Malignancies.

The advent of high-throughput and unbiased proteogenomic screens promises to rapidly advance our understanding of the molecular mechanisms underpinning pathogenesis of lymphoid malignancies. The wealth of data generated from these studies requires methods to rapidly confirm and extend findings into cell line models and primary patient samples. The proximity ligation assay (PLA) is a method that can visualize protein-protein interactions in situ. PLA can capture transient interactions and characterize constituents of stable biomolecular condensates, both of which pose technical difficulties for traditional biochemical and fluorescence imaging techniques.

Quantitatively characterization of rare earth ore by terahertz time-domain spectroscopy

The Bayan Obo deposit is the world’s largest polymetallic associated minerals deposit of rare earths, iron and niobium, and the rarity of its physical properties restrict the knowledge and understanding of its laws. Taking the high-grade mixed rare earth concentrate of Bayan Obo as the research object, terahertz time-domain spectroscopy (THz-TDS) has been adopted for the systematic investigation of high-grade rare earth concentrate base on the traditional X-ray fluorescence (XRF), X-ray diffraction (XRD), scanning electron microscopy (SEM) and thermogravimetric-differential thermal analysis (TG-DTA). The absorption coefficient and refractive index of high-grade rare earth ores and their associated minerals of fluorite and dolomite, are all investigated by terahertz time-domain spectroscopy. The terahertz spectral response is affected by the type of mineral and its content. The acquired rare earth terahertz spectral data are processed by correlation analysis. Three machine learning algorithms, Partial Least Squares Regression (PLSR), Random forest (RF) and Multilayer Perceptron (MLP), are used to achieve quantitative detection of their concentrations and components with the coefficient of determination R2 of the absorption coefficient of the optical parameter reaching up to 0.975, 0.992 and 0.984, respectively. This work promotes the growing understanding of terahertz transmission spectroscopy of rare earth-bearing minerals, which can be used to help guide the search for minerals, and to detect, identify as well as quantify them in geology. Terahertz time-domain spectroscopy supplies a new method for study of rare earth resources, and the comprehensive development and utilization of resources in the Bayan Obo deposit.

A novel carboxylesterase 2-targeted fluorescent probe with cholic acid as a recognition group for early diagnosis of drug- and environment-related liver diseases

Due to the detrimental effects of various harmful substances—such as carcinogens, drug toxicity, and environmental pollutants—on the liver, which can trigger or exacerbate conditions like hepatocellular carcinoma (HCC), drug-induced liver injury (DILI), and non-alcoholic fatty liver disease (NAFLD), accurate detection and monitoring of these diseases are crucial for effective treatment. Carboxylesterase 2 (CES2) is primarily found in the liver and, as a potential biomarker, its accurate detection can enhance the early diagnosis and treatment efficacy of liver diseases. Traditional fluorescence probes for CES2 detection suffer from non-specific recognition groups, leading to poor targeting specificity. To address this limitation, we propose a novel CES2-responsive fluorescent probe utilizing cholic acid (CA) as a recognition group. The probe, LAN-CA, was synthesized by esterifying CA with a near-infrared fluorophore, LAN-OH. This novel fluorescent probe leverages the unique affinity of CA for hepatocytes, ensuring that LAN-CA remains and accumulates specifically within the hepatoenteric circulation. In vitro experiments showed that the probe exhibits superior optical performance compared to traditional benzoate-based probe (LAN-PH), with a detection limit of 0.015 μg/mL. Examination of 56 common biological interferents demonstrated that using CA as a recognition group offers high selectivity. Cell experiments confirmed that LAN-CA is an effective tool for monitoring endogenous CES2 in live cells. Comprehensive evaluations of fluorescence imaging in various mouse models of liver diseases, such as HCC, DILI, and NAFLD, demonstrated that LAN-CA provides exceptional imaging accuracy and therapeutic monitoring capabilities. In conclusion, this probe not only can be a promising tool for accurate liver disease diagnosis, but also can provide valuable insights into treatment efficacy.

Fluorescent aptasensor based on competitive recognition strategies and point-of-care testing system for brain natriuretic peptide detection

Brain natriuretic peptide (BNP) is the preferred biomarker for clinical analysis, widely used in early screening and prognostic monitoring of cardiovascular and neurological diseases. Due to the low concentration and short half-life of BNP in the blood, its sensitive detection remains a challenge that must be overcome. With the rapid development of molecular diagnosis and point-of-care testing (POCT), developing a BNP biosensor with high sensitivity, good stability, accuracy, speed, and low-cost is of great significance for clinical applications and emergency diagnosis. However, BNP in human blood exists in various forms, and traditional fluorescence sensors may lead to overestimation of the concentration. In this work, we constructed an “on” fluorescent aptasensor based on competitive recognition strategy for quantitative detection of BNP, and built a fluorescence sensing detection system based on smartphone to achieve rapid on-site detection. We designed a specific aptamer labeled with carboxyfluorescein (FAM) with a simple structure and high biological affinity for selective capture of BNP, and utilized the large specific surface area and excellent fluorescence quenching effect of carboxylated graphene oxide (GO-COOH) as a carrier and quencher for the aptasensor. By optimizing experimental parameters such as aptamer and GO-COOH concentrations, as well as quenching/recovery time, linear sensitive detection of BNP was achieved in the concentration range of 0.01 ng/mL–10 ng/mL, with a detection limit as low as 10 pg/mL, good specificity, and excellent application potential in artificial serum spiking experiments. Additionally, a stable and sensitive fluorescence signal collection system has been developed to meet the needs of portable detection, breaking through the usage environment of traditional fluorescence detection equipment and filling the gap of portable fluorescence biosensing. In summary, we have creatively proposed a fluorescent aptasensor that enables rapid and sensitive detection of BNP and the development of low-cost fluorescent biosensors. The combination with POCT has shown broad application prospects and also provides some ideas for the fluorescence detection of other protein biomarkers.

Evaluation of Postoperative Anastomotic Patency in Lymphaticovenular Anastomosis Using Photoacoustic Imaging.

Lymphaticovenular anastomosis (LVA) is a surgical technique used to alleviate lymphedema by bypassing the lymphatic and venous vessels and facilitating lymphatic fluid drainage. Accurate evaluation of anastomotic patency is crucial for assessing LVA outcomes. Traditional near-infrared fluorescence lymphography has limitations, including fluorescence diffusion in subcutaneous fat and difficulty evaluating areas beneath the dermal backflow. Photoacoustic imaging (PAI) is a potential alternative for high-resolution visualization of lymphatic and blood vessels. We aimed to evaluate the utility of PAI for assessing LVA patency. Using the LUB0 PAI system, we examined patients who underwent LVA. Imaging was conducted using subcutaneously injected indocyanine green (ICG) to visualize lymphatic vessels. Results showed clear patency in some cases, inability to evaluate it in others, and confirmed occlusion in certain instances. While PAI provides valuable insights, challenges remain, including the potential for ambiguous results from the intermittent nature of lymphatic flow and difficulty visualizing low-ICG-concentration lymphatic vessels. Nonetheless, PAI offers a promising method for detailed 3D evaluation of anastomoses. It may improve surgical outcomes and contribute to future evidence in the field. Further advancements, including real-time video assessment, may enhance the accuracy and reliability of LVA patency evaluation.

Dual-Modality Imaging with a Zwitterionic Fluorescent Probe for Reversible Monitoring of Mitochondrial Membrane Potential Dynamics.

Traditional fluorescence intensity-based probes face challenges in accurately measuring mitochondrial membrane potential (MMP) due to intramolecular fluorescence quenching. In this work, we introduce a novel approach by incorporating quenching moieties within the zwitterionic probe to eliminate self-quenching interference, thus, enabling real-time and precise visualization of reversible MMP changes. We synthesized a zwitterionic fluorescent probe consisting of silicon-rhodamine (SiR) that was hydroxyl-substituted on the bay position of perylene diimides (PDIs) connected via a polyethylene glycol (PEG) linker. The lipophilic cationic SiR facilitates the entry of the PDI into the mitochondria, where the alkaline pH environment (pH = 8.0) ionizes the hydroxyl to a negatively charged species, affecting the quenching efficiency of SiR depending on the distance between the PDI and SiR moieties regulated by the MMP. The rigid aromatic ring of the PDI and strong hydrophobic interactions with the lipid bilayer, along with the inhibitory effect of the negatively charged hydroxyl on internalization, ensure the retention of PDI within the mitochondria. As the MMP decreases, SiR shifts outward, reducing quenching by phenolic anions and restoring fluorescence. Conversely, as the MMP increases, SiR moves inward, intensifying quenching by phenolic ions and reducing fluorescence, enabling reversible visualization monitoring of the MMP. This strategy overcomes the limitations of traditional intensity-based probes, providing a new avenue for reversible monitoring of the MMP.

Modeling of a Single-Band-Ratiometric Sensor Based on Lattice Positive Thermal Expansion in Eu3+-Activated Halide Perovskite Cs2NaEuCl6.

Recently, single-band ratiometric (SBR) thermometry has emerged as an innovative approach to traditional fluorescence thermometry, overcoming uncertainties associated with emission spectrum overlap or scattering while maintaining high spatial resolution and remote monitoring. This paper presents a novel Cs2NaEuCl6 perovskite prepared through a slow-cooling solution method. Additionally, it proposes a temperature sensor model that relies on the thermal quenching of charge-transfer state absorption. Mechanical studies highlight the role of lattice positive thermal expansion in affecting Eu3+ emission. Conversely, a significant emission enhancement is observed upon excitation corresponding to both the ground state and excited state absorption. The distinct luminescent behavior of this Eu3+-activated halide perovskite model makes it suitable for developing a highly sensitive SBR-type sensor with a relative sensitivity (Sr) exceeding 1.5% K-1 and temperature resolution (𝛿T) below 1 K at room temperature. Furthermore, it demonstrates the thermal stability during multiple heating-cooling cycles. Finally, the practical applicability of the proposed SBR model is demonstrated by employing a self-manufactured film sensor that enables precise real-time temperature detection for electronic components. The work is regarded as a significant stride toward the development of cutting-edge and exquisitely sensitive thermometers based on lanthanide-based halide double perovskites.

Exploring the analytical potential of total reflection X-ray fluorescence (TXRF) combined with partial least square (PLS) for simple determination of ash content in various coal types

Ash content, as a crucial indicator of coal quality, its rapid and accurate determination is pivotal to improve the energy utilization of coal and reduce environmental pollution. Traditional spectroscopic methods face significant challenges in acquiring accurate information from coal samples due to the notorious matrix effects arising from their complex composition, vast molecular structure, and diverse coal types. In this study, the feasibility of total reflection X-ray fluorescence (TXRF) combined with partial least squares (PLS) for the determination of coal ash was firstly investigated based on the TXRF being unaffected by matrix effects. Firstly, coal samples were prepared as suspensions, and the effects of sample particle size and different dispersants on the results of TXRF analyses were evaluated. The accuracy and applicability of the chosen sample preparation strategies were further validated using inductively coupled plasma mass spectrometry (ICP-MS) and two certified reference materials (CRMs). Subsequently, based on the analysis of 19 coal samples, the impact of three different predictive variables on the performance of the PLS model was investigated: (a) TXRF full spectrum normalized by the net intensity of the internal standard; (b) net intensity of characteristic peaks for 12 elements (Al, Si, K, Ca, Ti, Fe, Cr, Mn, Cu, Ni, and Sr) normalized by the net intensity of the internal standard; (c) concentrations of the aforementioned 12 elements. The results demonstrate that the PLS model constructed usingthe TXRF full spectrum normalized by the net intensity of the internal standard exhibits the best predictive capabilities, with the determination coefficient of calibration set (R2) and mean square error (MSE) of the prediction set reaching 0.9736 and 0.99 %, respectively. Moreover, the measurement accuracy of this model was six times greater than that obtained with traditional X-ray fluorescence (XRF). Presented analytical results display the possibilities of combining TXRF with PLS for coal quality evaluation.

Self-ratiometric fluorescence approach based on room-temperature instantaneously synthesized carbon dots from Folin's reagent and ethanolamine for determination of nitroxinil in water, milk, and food samples

BackgroundNitroxinil has been used extensively to treat parasitic worms, mainly Fasciola, in food-producing cattle and sheep. The reported methods for nitroxinil analysis included expensive instrumentation, the need for skilled operators, and tedious procedures. Fluorimetry is one of the fastest and simplest methods widely used; hence, we aimed to develop a simple, cost-effective, and convenient fluorometric approach for the estimation of nitroxinil in various matrices. Compared with other detection methods, self-ratiometric fluorescent probes are considered a promising approach for the detection of analytes as their detection accuracy overcomes traditional fluorescence sensing probe in that it is not affected by the probe concentration, solution polarity, instrument parameters, and other factors. In this research, room temperature instantaneously synthesized carbon dots were used as a sensitive and selective self-ratiometric probe for the determination of the veterinary medicine nitroxinil in various matrices. ResultsA room-temperature synthesized quinone-ethanolamine carbon dots (RTQECDs) was fabricated using the instantaneous reaction of sodium 1,2-naphthoquinone-4-sulfonate (Folin's) with ethanolamine, without any energy/catalyzing reagents, for the first time. The prepared carbon dots show green-blue fluorescence at 450 nm upon exposure to UV light at 365 nm with a quantum yield of 26.6 %. Upon interaction with nitroxinil, the fluorescence intensity of RTQECDs at 450 nm is quenched and shifted to a longer wavelength at 475 nm. Meanwhile, the fluorescence of RTQECDs at 400 nm (absorbance maxima of nitroxinil) was more extremely quenched under the same conditions. Taking this in hand, a new RTQECDs self-ratiometric probe was developed for the determination of nitroxinil using the decrease in peaks at 450 nm and 400 nm and the shift of the fluorescence maxima to 475 nm as built-in reference peaks. The probe showed a quantitative increase in signal output of F475/F400 in the range of 0.10–30.0 μg/mL nitroxinil with a limit of detection of 30.0 ppb. The nitroxinil-sensing mechanism using RTQECDs is mainly ascribed to the partial secondary blue-type inner filter effect (IFE). The designed study was applied for the estimation of nitroxinil in veterinary dosage forms (recoveries; 99.78 %–100.35 %), river water (recoveries; 98.55 %–101.53 %), and food products, including meat, liver, kidney, and milk (recoveries; 97.60 %–104.25 %). SignificanceThe novelty of our work includes the immediate synthesis of the sensing probe at room temperature, as well as its use as a self-ratiometric fluorescence probe for the determination of nitroxinil in veterinary samples, river water, and food products with excellent sensitivity down to 30.0 ppb. RTQECDs own the highest response and selectivity to nitroxinil compared with cations, anions, as well as other co-administered drugs, including cefotaxime and ivermectin.

Risk-adapted treatment in multiple myeloma: Does more make it merrier?

Kaiser etal. offer management recommendations for transplant-eligible, high-risk multiple myeloma (HRMM), derived from recent trials exploring treatment intensification in the various phases of front-line therapy. The definition of HRMM continues to evolve with emergence of novel genomic insights and impact of modern therapies, underscoring the need to expand beyond traditional interphase fluorescence insitu hybridization cytogenetics and International Staging System staging for a precise risk assessment. Despite progress, ongoing challenges in treatment delivery and tolerability underscore the urgency for exploring novel approaches like T-cell redirecting bispecific antibodies and chimeric antigen receptor T-cell to enhance outcomes in this complex patient population. Commentary on: Kaiser etal. Diagnosis and initial treatment of transplant-eligible high-risk myeloma patients: A British Society for Haematology/UK Myeloma Society Good Practice Paper. Br J Haematol 2024 (Online ahead of print). doi: 10.1111/bjh.19623.

Diagnostic Accuracy of IgA Anti-Transglutaminase Assessed by Chemiluminescence: A Systematic Review and Meta-Analysis.

A new chemiluminescence immunoassay method (CLIA) for detecting IgA anti-transglutaminase (atTG IgA) in celiac disease (CD) has prompted inquiries into its diagnostic performance. We conducted a systematic review and meta-analysis comparing CLIA with traditional enzyme-linked immunosorbent assay (ELISA) and fluorescence enzyme immunoassay (FEIA). We searched PubMed, Medline, and Embase databases up to March 2024. The diagnostic references were intestinal biopsy and ESPGHAN guidelines. We calculated the sensitivity and specificity of atTG IgA assessed by CLIA and the odds ratio (OR) between the assays. Eleven articles were eligible for the systematic review and seven for the meta-analysis. Sensitivity and specificity of atTG IgA CLIA-assay were 0.98 (95% CI, 0.95-0.99) and 0.97 (95% CI, 0.94-0.99), respectively. The sensitivity of atTG IgA antibody detection did not significantly vary across the three assay modalities examined (CLIA vs. ELISA OR: 1.08 (95% CI, 0.56-2.11; p = 0.8); CLIA vs. FEIA OR: 6.97 (95% CI, 0.60-81.03; p = 0.1). The specificity of atTG IgA assessed by FEIA was higher than for CLIA (OR 0.17 (95% CI, 0.05-0.62); p < 0.007). According to the systematic review, normalization of atTG IgA levels in CD patients following a gluten-free diet was delayed when using CLIA compared to ELISA and FEIA methods. Conflicting findings were reported on the antibody threshold to use in order to avoid biopsy confirmation.

In situ imaging of intracellular miRNAs in tumour cells by branched hybridisation chain reaction.

The ability to visualise microRNA in situ is crucial for studying microRNAs, their microRNA-associated biological functions and disease diagnosis. Traditional fluorescence in situ hybridisation methods based on paraformaldehyde fixation of microRNAs suffer from release of microRNAs from cells, which limits the sensitivity of in situ hybridisation, making them unsuitable for the detection of small, low-abundance microRNAs. To reduce the loss, microRNAs were covalently cross-linked to proteins within cells by combining EDC and paraformaldehyde, and the target microRNA was used as the initiator chain for a branched hybridisation chain reaction to detect microRNA expression levels in situ. A simplified branched hybridisation chain reaction can be realised by coupling two hybridisation chain reaction circuits with a hairpin linker. Upon forming the primary hybridisation chain reaction product with extended sequence, this sequence reacts with the linker hairpin H3 to release the initiator sequence, resulting in the formation of numerous dendritic branched hybridisation chain reaction products. Imaging results show that this technique can detect microRNAs with high sensitivity and selectivity at both the single-cell and single-molecule levels. Compared with the traditional fluorescence in situ hybridisation technique, this method greatly improves the sensitivity and image resolution of in situ imaging detection. Therefore, we believe that the target-initiated branched hybridisation chain reaction based in situ detection method provides a reliable assay platform for analysing disease-related microRNA expression.

Dye‐based recombinase‐aided amplification assay with enhanced sensitivity and specificity

AbstractObjectiveFluorescent recombinase‐aided amplification (RAA) assays are increasingly being used in the detection of a variety of pathogens and have the advantages of rapidity and simplicity and similar sensitivity and specificity, compared with real‐time PCR (qPCR) assays, but they require a complex probe design. To eliminate the addition of fluorescent probes for RAA, an EvaGreen dye‐based recombinase‐aided amplification (EvaGreen‐RAA) assay using self‐avoiding molecular recognition system (SAMRS) primers was developed.MethodsThe SAMRS primers effectively avoided the production of primer dimers, thus improving the detection sensitivity, while EvaGreen dye was used to quantitatively measure the amplified products in real time. Using Staphylococcus aureus (SA) and Listeria monocytogenes (LM) as examples, EvaGreen‐RAA with SAMRS primers was developed. As a reference and comparison, a traditional fluorescence probe RAA method and a RAA with SAMRS primers (SAMRS‐RAA) for detecting SA and LM were also investigated. Serial dilutions of recombinant plasmids were used to evaluate the sensitivity of the assays. Unenriched and enriched simulated milk samples were used to evaluate the limits of detection (LOD) of these methods. Using high‐resolution melting (HRM) was used to explore the sensitivity of the dual EvaGreen‐RAA assay.ResultsThe sensitivity of the fluorescent RAA method for detecting SA and LM was 10 copies/μL using plasmids and the sensitivity of the SAMRS‐RAA and EvaGreen‐RAA for detecting SA and LM plasmids was 1 copies/μL. The LOD values of the EvaGreen‐RAA for SA and LM in unenriched simulated milk samples were 100 and 50 CFU/mL, respectively, and the LOD value for both SA and LM using enriched simulated milk samples was 10 CFU/mL. EvaGreen‐RAA had linear amplification in real time in the range of 1–105 copies/μL of the plasmids of SA and LM. The sensitivity of the dual EvaGreen‐RAA assay for SA and LM was estimated to be 102 CFU/mL.ConclusionA real‐time quantitative EvaGreen‐RAA method for detecting SA and LM was developed, which eliminates the need to design complex RAA probes. This dye‐based RAA with SARMS primers provides a new strategy for simplifying fluorescence probe RAA and allowing the detection of multiple pathogens, which has many potential applications.

Unlocking a New Path: An Autophagometer that Measures Flux Using a Non-Fluorescent Immunohistochemistry Method.

Macroautophagy/autophagy, a crucial cellular process, is typically measured using fluorescence-based techniques, which can be costly, complex, and impractical for clinical settings. In this paper, we introduce a novel, cost-effective, non-fluorescent immunohistochemistry (IHC) method for evaluating autophagy flux. This technique, based on antigen-antibody reactions and chromogenic detection, provides clear, quantifiable results under standard light microscopy, eliminating the need for expensive equipment and specialized reagents. Our method simplifies technical requirements, making it accessible to routine clinical laboratories and research settings with limited resources. By comparing our approach with traditional fluorescence methods, we demonstrate its superior effectiveness, cost-efficiency, and applicability to patient samples. This innovative technique has the potential to significantly advance autophagy research and improve clinical diagnostics, offering a practical and robust tool for studying autophagy mechanisms in diseases such as cancer and neurodegenerative disorders. Our non-fluorescent IHC method represents a significant step forward in evaluating autophagy flux, making it more accessible and reliable, with the promise of enhancing our understanding and treatment of autophagy-related diseases.

Two dimensional alkaline earth metal sensors (2D-AEMS) of fluorescent strontium sulfide nanosheets for neurotransmitter drug detection via photo induced electron transfer (PIET)

A new sensing platform has been introduced that provides a powerful solution for fluorescence-based biosensors using photoluminescent nanosheets (NS) using the novel two dimensional alkaline earth metal sensors (2D-AEMS). We have synthesized two-dimensional (2D) fluorescent strontium sulfide (SrS) NS using deep eutectic solvent (DES) as green solvent media by a hydrothermal method. The resulting product of 2D SrS NS to enhance the fluorescence intensity was achieved successfully followed by probe ultrasonication. The optical properties of SrS NS were studied by UV–visible and photoluminescence (PL) spectroscopy. The 2D SrS NS showed a blueish-green fluorescence optimized at λex320 nm/λem390 nm and a quantum yield of 38.6% was calculated. Under optimal conditions, the fluorescent SrS NS effectively detected noradrenaline (NA) by PIET-based fluorescence quenching and wavelength shifts were observed. Our proposed 2D-AEMS of 2D SrS NS fluorescence intensity was quenched in a wide linear range from 1 to 300 µM, with a limit of detection (LOD = 3*3SD/S) of 0.047 µM. The 2D-AEMS (fluorescent SrS NS) was applied to the determination of NA in human urine samples, with good recovery ranging from 98.7-100.08%. Also, the SrS NS fluorescence quenching mechanism in the detection of NA was investigated by zeta potential analysis, UV analysis, and dynamic light scattering (DLS). Our proposed 2D SrS NS fluorescence nanomaterials stand as an innovative platform for generating fluorescence sensors, with extensive potential applications in medical, biological, and life science fields, designed to replace traditional dye fluorescence in the near future.

Rapid detection of salmon louse larvae in seawater based on machine learning

The proliferation of salmon lice is one of the most challenging problems in salmon farming, seriously affecting the welfare of both farmed and wild salmonids. The detection of salmon lice in seawater, especially in the (pre-) infectious stage, supports the accurate management of salmon lice proliferation. Methods for detecting salmon lice in seawater to date involve traditional light and fluorescence microscopy and Polymerase Chain Reaction (PCR) methods. However, these methods require sample pre-processing and are laborious and time-consuming, rendering them difficult to apply for the task of continuous, rapid salmon lice detection in large water volumes. This study aims to develop a rapid and easy-to-use method for the detection of salmon lice in seawater. A novel approach was introduced for the detection of salmon lice at different larval stages in seawater by leveraging machine learning. A setup for the rapid acquisition of images of salmon lice in seawater was developed, and a dataset comprising 8316 images encompassing salmon lice “Nauplius Live,” “Nauplius Shell” and “Copepodite” was created. Then 16 object detection models including one- and two-stage Convolutional Neural Network (CNN-) based models and Transformer-based models were trained, tested, and compared on this comprehensive dataset. RT-DETR showed the best performance among all models tested with a precision of 0.972 and a recall of 0.978. The YOLO series models, except for YOLOv3, showcased remarkable inference speeds (ranging from 152 to 416 frames per second) while maintaining high precision (ranging from 0.968 to 0.977) and recall (ranging from 0.964 to 0.970). To our knowledge, this is the first time machine learning has been applied to the task of rapidly detecting salmon louse larvae at different stages in seawater samples. The results demonstrate that the machine learning approaches can achieve rapid easy-to-use and cost-effective detection of salmon lice in seawater. In the future, this study has the potential for application in measuring salmon louse larvae numbers in aquatic environments, supporting the enhancement of the welfare of both farmed and wild salmon.

Persistent Luminescence Nanoplatform for Autofluorescence-Free Tracking of Submicrometer Plastic Particles in Plant.

The uptake of plastic particles by plants and their transport through the food chain make great risks to biota and human health. Therefore, it is important to trace plastic particles in the plant. Traditional fluorescence imaging in plants usually suffers significant autofluorescence background. Here, we report a persistent luminescence nanoplatform for autofluorescence-free imaging and quantitation of submicrometer plastic particles in plant. The nanoplatform was fabricated by doping persistent luminescence nanoparticles (PLNPs) onto polystyrene (PS) nanoparticles. Cr3+-doped zinc gallate PLNP was employed as the dopant for autofluorescence-free imaging due to its persistent luminescence nature. In addition, the Ga element in PLNP was used as a proxy to quantify the PS in the plant by inductively coupled plasma mass spectrometry (ICP-MS). Thus, the developed nanoplatform allows not only dual-mode autofluorescence-free imaging (persistent luminescence and laser-ablation ICP-MS) but also ICP-MS quantitation for tracking PS in plant. Application of this nanoplatform in a typical plant model Arabidopsis thaliana revealed that PS mainly distributed in the root (>99.45%) and translocated very limited (<0.55%) to the shoot. The developed nanoplatform has great potential for quantitative tracing of submicrometer plastic particles to investigate the environmental process and impact of plastic particles.

Wide-field, high-resolution reconstruction in computational multi-aperture miniscope using a Fourier neural network

Traditional fluorescence microscopy is constrained by inherent trade-offs among resolution, field of view, and system complexity. To navigate these challenges, we introduce a simple and low-cost computational multi-aperture miniature microscope, utilizing a microlens array for single-shot wide-field, high-resolution imaging. Addressing the challenges posed by extensive view multiplexing and non-local, shift-variant aberrations in this device, we present SV-FourierNet, a multi-channel Fourier neural network. SV-FourierNet facilitates high-resolution image reconstruction across the entire imaging field through its learned global receptive field. We establish a close relationship between the physical spatially varying point-spread functions and the network’s learned effective receptive field. This ensures that SV-FourierNet has effectively encapsulated the spatially varying aberrations in our system and learned a physically meaningful function for image reconstruction. Training of SV-FourierNet is conducted entirely on a physics-based simulator. We showcase wide-field, high-resolution video reconstructions on colonies of freely moving C. elegans and imaging of a mouse brain section. Our computational multi-aperture miniature microscope, augmented with SV-FourierNet, represents a major advancement in computational microscopy and may find broad applications in biomedical research and other fields requiring compact microscopy solutions.

EnderScope: a low-cost 3D printer-based scanning microscope for microplastic detection.

Low-cost and scalable technologies that allow people to measure microplastics in their local environment could facilitate a greater understanding of the global problem of marine microplastic pollution. A typical way to measure marine microplastic pollution involves imaging filtered seawater samples stained with a fluorescent dye to aid in the detection of microplastics. Although traditional fluorescence microscopy allows these particles to be manually counted and detected, this is a resource- and labour-intensive task. Here, we describe a novel, low-cost microscope for automated scanning and detection of microplastics in filtered seawater samples-the EnderScope. This microscope is based on the mechanics of a low-cost 3D printer (Creality Ender 3). The hotend of the printer is replaced with an optics module, allowing for the reliable and calibrated motion system of the 3D printer to be used for automated scanning over a large area (>20 × 20 cm). The EnderScope is capable of both reflected light and fluorescence imaging. In both configurations, we aimed to make the design as simple and cost-effective as possible, for example, by using low-cost LEDs for illumination and lighting gels as emission filters. We believe this tool is a cost-effective solution for microplastic measurement. This article is part of the Theo Murphy meeting issue 'Open, reproducible hardware for microscopy'.