Up-conversion luminescence and temperature sensing properties of Ho3+-, Tm3+-, and Yb3+-codoped Bi2WO6 materials in a water environment.

A series of x%Ho3+, 5 %Tm3+, y%Yb3+:Bi2WO6 (x = 0, 0.5, 1, 3, 5; y = 0.5, 1, 3) luminescent materials was prepared using a high-temperature solid-phase method. The microstructure, up-conversion luminescence, and temperature sensing properties of the synthesized powders were analyzed. X-ray diffraction patterns revealed that doping with Ho3+, Tm3+, and Yb3+ ions at certain concentrations did not affect the orthorhombic crystal structure of the Bi2WO6 host. Scanning electron microscopy revealed that the morphology of the sample consisted of lumpy particles with a particle size range of 1-5 µm and agglomeration. SEM mapping and energy-dispersive X-ray spectroscopy analyses revealed that each element was relatively uniformly distributed on the particle surface. Under 980 nm excitation (380 mW), the strongest luminescence of the sample was obtained when both Ho3+ and Yb3+ doping concentrations were 1 %. Compared with the luminescence of the 5 %Tm3+ and 1 %Yb3+:Bi2WO6 sample, with increasing Ho3+ concentrations, the luminescence intensity of Tm3+ was first enhanced and subsequently weakened, whereas the luminescence of Ho3+ was significantly weakened, which indicates the positive energy transfer from Ho3+ â†’ Tm3+. At 980 nm (80-380 mW), for the 1 %Ho3+, 5 %Tm3+, and 1 %Yb3+:Bi2WO6 sample, the 538 nm, 545 nm, 660 nm, and 804 nm emission peaks originated from the two-photon absorption. FIR660 nm/804 nm, FIR545 nm/804 nm, and FIR538 nm/804 nm were used to characterize the temperature and corresponded to temperature sensitivities Sr of 0.0046 K-1, 0.022 K-1 and 0.024 K-1 at 573 K, respectively. At 498 K, the minimum temperature resolution δT values were 0.03384 K, 0.03203 K and 0.04373 K. When the temperature increased from 298 K to 573 K, the powder sample luminescence gradually shifted from the yellow-green region to the red region. The results of environmental discoloration and thermochromic performance tests indicate that this sample has potential application in optical anti-counterfeiting. FIR804 nm /660 nm and FIR804 nm /538 nm were obtained for the 40 NTU turbidity suspension under identical excitation conditions. At 298 K, for the 40 NTU turbidity sample, the maximum Sr values were 0.0197 K-1 and 0.0405 K-1; at 340 K, the minimum temperature resolutions δT values were 0.54037 K and 0.66237 K. When the temperature decreased from 340 K to 298 K, the luminescence of the 40 NTU suspension samples gradually shifted from the yellow region to the green region.

Visible-short wavelength near infrared hyperspectral imaging coupled with multivariate curve resolution-alternating least squares for diagnosis of breast cancer.

This study investigates the application of visible-short wavelength near-infrared hyperspectral imaging (Vis-SWNIR HSI) in the wavelength range of 400-950 nm and advanced chemometric techniques for diagnosing breast cancer (BC). The research involved 56 ex-vivo samples encompassing both cancerous and non-cancerous breast tissue from females. First, HSI images were analyzed using multivariate curve resolution-alternating least squares (MCR-ALS) to exploit pure spatial and spectral profiles of active components. Then, the MCR-ALS resolved spatial profiles were arranged in a new data matrix for exploration and discrimination between benign and cancerous tissue samples using principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). The PLS-DA classification accuracy of 82.1 % showed the potential of HSI and chemometrics for non-invasive detection of BC. Additionally, the resolved spectral profiles by MCR-ALS can be used to track the changes in the breast tissue during cancer and treatment. It is concluded that the proposed strategy in this work can effectively differentiate between cancerous and non-cancerous breast tissue and pave the way for further studies and potential clinical implementation of this innovative approach, offering a promising avenue for improving early detection and treatment outcomes in BC patients.

Modular, Scalable, and Customizable LC-HRMS for Exposomics.

In this chapter, we describe a multi-purpose, reversed-phase liquid chromatography-high-resolution mass spectrometry (LC-HRMS) workflow for acquiring high-quality, non-targeted exposomics data utilizing data-dependent acquisition (DDA) combined with the use of toxicant inclusion lists for semi-targeted analysis. In addition, we describe expected retention times for >160 highly diverse xenobiotics in human plasma and serum samples. The method described is intended to serve as a generic LC-HRMS exposomics workflow for research and educational purposes. Moreover, it may be employed as a primer, allowing for further adaptations according to specialized research needs, e.g., by including reference and/or internal standards, by expanding to data-independent acquisition (DIA), or by modifying the list of compounds prioritized in fragmentation experiments (MS2).

Recommendations for Accurate Lipid Annotation and Semi-absolute Quantification from LC-MS/MS Datasets.

Recent developments in LC-MS instrumentation and analytical technologies together with bioinformatics tools supporting high-throughput processing of large omics datasets significantly enhanced our capabilities and efficiency of identification and quantification of lipids in diverse biological materials. However, each biological matrix is characterized by its unique lipid composition, thus requiring optimization of analytical and bioinformatics workflows for each studied lipidome. Here, we describe an integrated workflow for deep lipidome profiling, accurate annotation, and semi-absolute quantification of complex lipidomes based on reversed phase chromatography and high resolution mass spectrometry. This chapter provides details on selection of the optimal extraction protocol, acquisition of LC-MS/MS data for accurate annotation of lipid molecular species, and design of lipidome-specific mixtures of internal standards to assist quantitative analysis of complex, native lipidomes.

Projected changes in heatwaves over Central and South America using high-resolution regional climate simulations.

Heatwaves (HWs) pose a severe threat to human and ecological systems. Here we assess the projected changes in heatwaves over Latin America using bias corrected high-resolution regional climate simulations under two Representative Concentration Pathway scenarios (RCPs). Heatwaves are projected to be more frequent, long-lasting, and intense in the mid-century under both RCP2.6 and RCP8.5 scenarios, with severe increases under the RCP8.5 scenario. Even under the low emissions scenario of RCP2.6, the frequency of heatwaves doubles over most of the region. A three- to tenfold rise in population exposure to heatwave days is projected over Central and South America, with climate change playing a dominant role in driving these changes. Results show that following the low emission pathway would reduce 57% and 50% of heatwave exposure for Central and South American regions respectively, highlighting the need to control anthropogenic emissions and implement sustainable practices.

Copper-Catalyzed Enantioselective Hydrophosphorylation of Unactivated Alkynes.

P-stereogenic phosphorus compounds are essential across various fields, yet their synthesis via enantioselective P-C bond formation remains both challenging and underdeveloped. We report the first copper-catalyzed enantioselective hydrophosphorylation of alkynes, facilitated by a newly designed chiral 1,2-diamine ligand. Unlike previous methods that rely on kinetic resolution with less than 50% conversion, our approach employs a distinct dynamic kinetic asymmetric transformation mechanism, achieving complete conversion of racemic starting materials. This reaction is compatible with a broad range of aromatic and aliphatic terminal alkynes, producing products with high yields (up to 95%), exclusive cis selectivity, and exceptional regio- and enantioselectivity (> 20:1 r.r. and up to 96% ee). The resulting products were further transformed into a diverse array of enantioenriched P-stereogenic scaffolds. Preliminary mechanistic studies were conducted to elucidate the reaction details.

A novel GAN-based three-axis mutually supervised super-resolution reconstruction method for rectal cancer MR image.

BACKGROUND AND OBJECTIVE: This study aims to enhance the resolution in the axial direction of rectal cancer magnetic resonance (MR) imaging scans to improve the accuracy of visual interpretation and quantitative analysis. MR imaging is a critical technique for the diagnosis and treatment planning of rectal cancer. However, obtaining high-resolution MR images is both time-consuming and costly. As a result, many hospitals store only a limited number of slices, often leading to low-resolution MR images, particularly in the axial plane. Given the importance of image resolution in accurate assessment, these low-resolution images frequently lack the necessary detail, posing substantial challenges for both human experts and computer-aided diagnostic systems. Image super-resolution (SR), a technique developed to enhance image resolution, was originally applied to natural images. Its success has since led to its application in various other tasks, especially in the reconstruction of low-resolution MR images. However, most existing SR methods fail to account for all anatomical planes during reconstruction, leading to unsatisfactory results when applied to rectal cancer MR images. METHODS: In this paper, we propose a GAN-based three-axis mutually supervised super-resolution reconstruction method tailored for low-resolution rectal cancer MR images. Our approach involves performing one-dimensional (1D) intra-slice SR reconstruction along the axial direction for both the sagittal and coronal planes, coupled with inter-slice SR reconstruction based on slice synthesis in the axial direction. To further enhance the accuracy of super-resolution reconstruction, we introduce a consistency supervision mechanism across the reconstruction results of different axes, promoting mutual learning between each axis. A key innovation of our method is the introduction of Depth-GAN for synthesize intermediate slices in the axial plane, incorporating depth information and leveraging Generative Adversarial Networks (GANs) for this purpose. Additionally, we enhance the accuracy of intermediate slice synthesis by employing a combination of supervised and unsupervised interactive learning techniques throughout the process. RESULTS: We conducted extensive ablation studies and comparative analyses with existing methods to validate the effectiveness of our approach. On the test set from Shanxi Cancer Hospital, our method achieved a Peak Signal-to-Noise Ratio (PSNR) of 34.62 and a Structural Similarity Index (SSIM) of 96.34 %. These promising results demonstrate the superiority of our method.

The Quantification of Bone Mineral Density Using Photon Counting Computed Tomography and its Implications for Detecting Bone Remodelling.

High-Resolution peripheral quantitative CT (HR-pQCT) has become standard practice when quantifying volumetric bone mineral density (vBMD) in vivo. Yet, it is only accessible to peripheral sites, with small fields of view and lengthy scanning times. This limits general applicability in clinical workflows. The goal of this study was to assess the potential of Photon Counting CT (PCCT) in quantitative bone imaging. Using the European Forearm Phantom, PCCT was calibrated to hydroxy-apatite (HA) density. Eight cadaveric forearms were scanned twice with PCCT, and once with HR-pQCT. The dominant forearm of two volunteers was scanned twice with PCCT. In each scan the carpals were delineated. At bone-level, accuracy was assessed with a paired measurement of total vBMD (Tt.vBMD) calculated with PCCT and HR-pQCT. At voxel-level, repeatability was assessed by image registration and voxel-wise subtraction of the ex vivo PCCT scans. In an ideal scenario, this difference would be zero; any deviation was interpreted as falsely detected remodelling. For clinical usage, the least detectable remodelling was determined by finding a threshold in the PCCT difference image that resulted in a classification of bone formation and resorption below acceptable noise levels (<0.5%). The paired measurement of Tt.vBMD had a Pearson correlation of 0.986. Compared to HR-pQCT, PCCT showed a bias of 7.46 mgHA/cm3. At voxel-level, the repeated PCCT scans showed a bias of 17.66 mgHA/cm3 and standard error of 96.23 mgHA/cm3. Least detectable remodelling was found to be 250 mgHA/cm3, for which 0.37% of the voxels was incorrectly classified as newly added or resorbed bone. In vivo, this volume increased to 0.97%. Based on the cadaver data we conclude that PCCT can be used to quantify vBMD and bone turnover. We provided proof of principle that this technique is also accurate in vivo, hence, that it has high potential for clinical applications.

In quantitative computed tomography (QCT) , bone images have grey values that reflect the local bone mineral content within each voxel. Aggregated over large bone regions, a total bone mineral density can be calculated, which helps in identifying weak bones and fracture risk. At small scales, QCT can detect where bone is being formed, and thus the bone mineral content increases, and where bone is being removed, and thus the bone mineral content decreases. These measurements are typically done with high-resolution peripheral QCT (HR-pQCT). However, HR-pQCT can only scan small regions of the arms and legs, for which a long scanning time is needed. This makes it challenging to use HR-pQCT in a clinical context. Photon Counting CT (PCCT) is a new CT device that can scan bone with an image quality similar to HR-pQCT, yet it can scan faster and cover a larger area. Used at the large scale, our results indicate that PCCT and HR-pQCT can be used interchangeably for the quantification of bone mineral density in large bone regions. Used at small scales, our results indicate that both technologies can detect changes in bone mineral content with similar sensitivity. These results demonstrate that PCCT enables the use of these QCT analyses in a clinical context.

Super-resolution microscopy unveils the nanoscale organization and self-limiting clustering of CD47 in human erythrocytes.

The transmembrane protein CD47, an innate immune checkpoint protein, plays a pivotal role in preventing healthy erythrocytes from immune clearance. Our study utilized stochastic optical-reconstruction microscopy (STORM) and single-molecule analysis to investigate the distribution of CD47 on the human erythrocyte membrane. Contrary to previous findings in mouse erythrocytes, we discovered that CD47 exists in randomly distributed monomers rather than in clusters across the human erythrocyte membrane. Using 2nd antibody-induced crosslinking, we found that CD47 aggregates into stable clusters within minutes. By comparing these STORM results with those of the fully mobile protein CD59 and the cytoskeleton-bound membrane protein glycophorin C under similar conditions, as well as devising two-color STORM co-labeling and co-clustering experiments, we further quantitatively revealed an intermediate, self-limiting clustering behavior of CD47, elucidating its fractional (∼14%) attachment to the cytoskeleton. Moreover, we report reductions in both the amount of CD47 and its clustering capability in aged erythrocytes, providing new insight into erythrocyte senescence. Together, the combination of STORM and 2nd antibody-based crosslinking unveils the unique self-limiting clustering behavior of CD47 due to its fractional cytoskeleton attachment.

Fourier Ptychographic Coherent Anti-Stokes Raman Scattering Microscopy with Point-Scanning for Super-Resolution Imaging.

Fourier ptychography (FP) is a high resolution wide-field imaging method based on the extended aperture in the Fourier space, which is synthesized from raw images with varying illumination angles. If FP is extended to coherent nonlinear optical imaging, the resolution could be further improved due to the increase of the cutoff frequency of the synthesized coherent optical transfer function (C-OTF) with respect to the order of nonlinear optical processes. However, there is a fundamental conflict between wide-field FP and nonlinear optical imaging, whereby the nonlinear optical imaging typically requires a focused excitation laser beam with high power density. To tackle the problem, in this work, a unique point-scanning FP (PS-FP) method is presented for super-resolution nonlinear optical imaging, in which the nonlinear optical signal is obtained by using focused laser beam, while the conventional FP algorithm can still be used to retrieve the super-resolution image. PS-FP coherent anti-Stokes Raman scattering (PS-FP-CARS) imaging on a variety of samples, where a 1.8-fold expansion of the OTF is achieved experimentally for enhancing vibrational imaging. Further theoretical calculation shows that the C-OTF of PS-FP higher-order CARS (PS-FP-HO-CARS) can be expanded up to ≈4.9-fold, thereby improving the spatial resolution by ≈3-fold in comparison with conventional point-scanning CARS with under tightly focused beams. The generality of PS-FP method developed in this work can be adapted to other coherent nonlinear optical imaging modalities for super-resolution imaging in tissue and cells.

Neural network-assisted localization of clustered point spread functions in single-molecule localization microscopy.

Single-molecule localization microscopy (SMLM), which has revolutionized nanoscale imaging, faces challenges in densely labelled samples due to fluorophore clustering, leading to compromised localization accuracy. In this paper, we propose a novel convolutional neural network (CNN)-assisted approach to address the issue of locating the clustered fluorophores. Our CNN is trained on a diverse data set of simulated SMLM images where it learns to predict point spread function (PSF) locations by generating Gaussian blobs as output. Through rigorous evaluation, we demonstrate significant improvements in PSF localization accuracy, especially in densely labelled samples where traditional methods struggle. In addition, we employ blob detection as a post-processing technique to refine the predicted PSF locations and enhance localization precision. Our study underscores the efficacy of CNN in addressing clustering challenges in SMLM, thereby advancing spatial resolution and enabling deeper insights into complex biological structures.

Comparative effectiveness of combined biologic agents versus standard therapies in the treatment of plaque psoriasis: a retrospective analysis.

Introduction: Plaque psoriasis is a persistent skin disorder that necessitates efficient management. This study investigates the therapeutic effectiveness and timeline for skin lesion resolution in plaque psoriasis patients treated with combined biologic agents compared to standard therapies. Methods: Conducted retrospectively between March 2020 and March 2023, the study included 162 patients with moderate to severe plaque psoriasis. Participants were divided into two groups: the Control Group, which received standard treatments, and the Combined Biologic Agent Group, which received additional biologic therapy with secukinumab. Participants in the Control Group received standard treatments, while those in the Combined Biologic Agent Group received standard treatments plus secukinumab. Results: The results showed that the Combined Biologic Agent Group experienced a significantly faster onset of therapeutic effects, with an average time of 3.04 ± 2.25 days compared to 6.12 ± 2.06 days in the Control Group. Additionally, skin lesion resolution occurred more rapidly in the biologic agent group (7.04 ± 2.13 days) than in the control group (14.56 ± 4.73 days). By week 24, the Psoriasis Area and Severity Index (PASI) scores demonstrated a more substantial reduction in the biologic agent group, decreasing from 26.98 ± 11.28 to 2.48 ± 3.01, whereas the control group showed a reduction from 25.82 ± 10.47 to 10.40 ± 7.63. The overall effectiveness rate was higher in the biologic agent group, with no cases of ineffectiveness, compared to a 20.99% ineffectiveness rate in the control group. Furthermore, there was no recurrence of the disease in the biologic agent group, while the control group experienced an 11.11% recurrence rate. Both groups had a similar incidence of adverse reactions, indicating that the addition of biologic agents does not significantly increase the risk of adverse events. Discussion: These findings suggest that combined biologic agent therapy offers a more effective and faster treatment option for plaque psoriasis without compromising safety. However, larger-scale clinical trials are necessary to validate these results and establish the long-term benefits and safety of this treatment approach in diverse patient populations.

Optimization of 3D imaging time reduction by assessing spatial resolution in the slice selective direction using the ladder method.

PURPOSE: Assessing spatial resolution in MRI is challenging due to non-linearity. Despite the widespread use of 3D imaging in clinical practice for lesion detection and multi-planar reconstruction (MPR), the extended acquisition time poses a shortcoming. To address this, the "Slice resolution" parameter is utilized; however, its impact on MPR images is unclear. This study aims to assess spatial resolution using the ladder method, investigate the effects of diverse slice resolution settings in various imaging sequences, and propose optimal conditions. METHODS: Images were acquired using various 3D imaging sequences-SPACE T1WI, SPACE T2WI, and VIBE T1WI-with different slice resolutions. Axial cross-section images were acquired and reconstructed into coronal cross-sections. The ladder method was employed for objective evaluation, including spatial frequency analysis. Additionally, visual evaluation was conducted and compared with ladder method results. RESULTS: For three imaging sequences, the evaluated value of ladder method remained relatively constant from 100 % to 80 % slice resolution. However, the evaluated value decreased in low-spatial frequency for slice resolution below 70 %. CONCLUSIONS: Results from both ladder method and visual evaluations indicated image quality remained stable when the slice resolution was decreased to 80 %, potentially enabling a 20 % reduction in imaging time while preserving resolution in other cross-sections reconstructed by MPR.

Interpretation of river water quality data is strongly controlled by measurement time and frequency.

Water quality monitoring at high temporal frequency provides a detailed picture of environmental stressors and ecosystem response, which is essential to protect and restore lake and river health. An effective monitoring network requires knowledge on optimal monitoring frequency and data variability. Here, high-frequency hydrochemical datasets (dissolved oxygen, pH, electrical conductivity, turbidity, water temperature, total reactive phosphorus, total phosphorus and nitrate) from six UK catchments were analysed to 1) understand the lowest measurement frequency needed to fully capture the variation in the datasets; and 2) investigate bias caused by sampling at different times of the day. The study found that reducing the measurement frequency increasingly changed the interpretation of the data by altering the calculated median and data range. From 45 individual parameter-catchment combinations (six to eight parameters in six catchments), four-hourly data captured most of the hourly range (>90 %) for 37 combinations, whilst 41 had limited impact on the median (<0.5 % change). Twelve-hourly and daily data captured >90 % of the range with limited impact on the median in approximately half of the combinations, whereas weekly and monthly data captured this in <6 combinations. Generally, reducing sampling frequency had most impact on the median for parameters showing strong diurnal cycles, whilst parameters showing rapid responses to extreme flow conditions had most impact on the range. Diurnal cycles resulted in year-round intra-daily variation in most of the parameters, apart from nutrient concentrations, where daily variation depended on both seasonal flow patterns and anthropogenic influences. To design an optimised monitoring programme, key catchment characteristics and required data resolution for the monitoring purpose should be considered. Ideally a pilot study with high-frequency monitoring, at least four-hourly, should be used to determine the minimum frequency regime needed to capture temporal behaviours in the intended focus water quality parameters by revealing their biogeochemical response patterns.

Graphene Bilayer as a Template for Manufacturing Novel Encapsulated 2D Materials.

Bilayer graphene (BLG) has recently been used as a tool to stabilize encapsulated single sheets of various layered materials and tune their properties. It was also discovered that the protecting action of graphene sheets makes it possible to synthesize completely new two-dimensional materials (2DMs) inside the BLG by intercalating various atoms and molecules. In comparison to the bulk graphite, BLG allows for easier intercalation and a much larger increase in the interlayer separation of the sheets. Moreover, it enables studying the atomic structure of the intercalated 2DM by using high-resolution transmission electron microscopy. In this review, we summarize the recent progress in this area, with a special focus on new materials created inside BLG. We compare the experimental findings with the theoretical predictions, pay special attention to the discrepancies, and outline the challenges in the field. Finally, we discuss unique opportunities offered by intercalation into 2DMs beyond graphene and their heterostructures.

An alternative filament fabrication method as the basis for 3D-printing personalized implants from elastic ethylene vinyl acetate copolymer.

In this work, a novel tool for small-scale filament production is presented. Unlike traditional methods such as hot melt extrusion (HME), the device (i) allows filament manufacturing from small material amounts as low as three grams, (ii) ensures high diameter stability almost independent of the viscoelastic behavior of the polymer melt, and (iii) enables processing of materials with rheological profiles specifically tailored toward fused filament fabrication (FFF). Hence, novel materials, previously difficult to process due to HME limitations, become easily accessible for FFF for the first time. Here, we showcase the production of highly flexible drug-free, and drug-loaded filaments based on ethylene-vinyl acetate polymers with a vinyl acetate content of 28 w% (EVA28) and unprecedented high melt flow rates of up to 400 g/10 min. Owing to their low viscosity, FFF with low print nozzle sizes of 250 µm was achieved for the first time for EVA28. These small nozzle diameters facilitate 3D-printing of high-resolution structures in small-dimensional dosage forms such as subcutaneous implantable drug delivery systems, which can later be used for personalization. Consequently, the material portfolio for FFF is tremendously broadened, allowing material and formulation optimization toward FFF, independent of a preliminary extrusion process.

Coronary artery disease detection using deep learning and ultrahigh-resolution photon-counting coronary CT angiography.

PURPOSE: The purpose of this study was to evaluate the diagnostic performance of automated deep learning in the detection of coronary artery disease (CAD) on photon-counting coronary CT angiography (PC-CCTA). MATERIALS AND METHODS: Consecutive patients with suspected CAD who underwent PC-CCTA between January 2022 and December 2023 were included in this retrospective, single-center study. Non-ultra-high resolution (UHR) PC-CCTA images were analyzed by artificial intelligence using two deep learning models (CorEx, Spimed-AI), and compared to human expert reader assessment using UHR PC-CCTA images. Diagnostic performance for global CAD assessment (at least one significant stenosis ≥ 50 %) was estimated at patient and vessel levels. RESULTS: A total of 140 patients (96 men, 44 women) with a median age of 60 years (first quartile, 51; third quartile, 68) were evaluated. Significant CAD on UHR PC-CCTA was present in 36/140 patients (25.7 %). The sensitivity, specificity, accuracy, positive predictive value), and negative predictive value of deep learning-based CAD were 97.2 %, 81.7 %, 85.7 %, 64.8 %, and 98.9 %, respectively, at the patient level and 96.6 %, 86.7 %, 88.1 %, 53.8 %, and 99.4 %, respectively, at the vessel level. The area under the receiver operating characteristic curve was 0.90 (95 % CI: 0.83-0.94) at the patient level and 0.92 (95 % CI: 0.89-0.94) at the vessel level. CONCLUSION: Automated deep learning shows remarkable performance for the diagnosis of significant CAD on non-UHR PC-CCTA images. AI pre-reading may be of supportive value to the human reader in daily clinical practice to target and validate coronary artery stenosis using UHR PC-CCTA.

East Victoria long term hydrodynamic modelling: Dataset and methodology.

This dataset is the output of a long term multi-resolution calibrated hydrodynamic model of Bass Strait waters in south-eastern Australia. The model is 3 dimensional with 16 sigma layers. It is forced by tides, wind, non-tidal sea level variability as well as salinity and temperature through a nudging scheme. The model was calibrated against existing data from previous fixed location instrument deployments and hull mounted ADCP data. While the model has limitations, it performs well against measured data and provides a useful tool for describing spatially varying currents throughout East Victorian waters.

SpLitteR: diploid genome assembly using TELL-Seq linked-reads and assembly graphs.

Background: Recent advances in long-read sequencing technologies enabled accurate and contiguous de novo assemblies of large genomes and metagenomes. However, even long and accurate high-fidelity (HiFi) reads do not resolve repeats that are longer than the read lengths. This limitation negatively affects the contiguity of diploid genome assemblies since two haplomes share many long identical regions. To generate the telomere-to-telomere assemblies of diploid genomes, biologists now construct their HiFi-based phased assemblies and use additional experimental technologies to transform them into more contiguous diploid assemblies. The barcoded linked-reads, generated using an inexpensive TELL-Seq technology, provide an attractive way to bridge unresolved repeats in phased assemblies of diploid genomes. Results: We developed the SpLitteR tool for diploid genome assembly using linked-reads and assembly graphs and benchmarked it against state-of-the-art linked-read scaffolders ARKS and SLR-superscaffolder using human HG002 genome and sheep gut microbiome datasets. The benchmark showed that SpLitteR scaffolding results in 1.5-fold increase in NGA50 compared to the baseline LJA assembly and other scaffolders while introducing no additional misassemblies on the human dataset. Conclusion: We developed the SpLitteR tool for assembly graph phasing and scaffolding using barcoded linked-reads. We benchmarked SpLitteR on assembly graphs produced by various long-read assemblers and have demonstrated that TELL-Seq reads facilitate phasing and scaffolding in these graphs. This benchmarking demonstrates that SpLitteR improves upon the state-of-the-art linked-read scaffolders in the accuracy and contiguity metrics. SpLitteR is implemented in C++ as a part of the freely available SPAdes package and is available at https://github.com/ablab/spades/releases/tag/splitter-preprint.

Super-Resolution Surface-Enhanced Raman Scattering: Perspectives on the Past, Present, and Future.

Super-resolution surface-enhanced Raman scattering (SERS) allows researchers to overcome the resolution limit of far field optical microscopy and peer into electromagnetic hot spots with nanoscale resolution. By localizing the signal from single (or few) molecules on the surface of plasmonic nanoparticle aggregates, relationships between the spatial origin of the SERS signal, local electromagnetic field enhancements, and SERS intensity can be determined. This Perspective describes the successes and challenges of super-resolution SERS, from the earliest mapping of single-molecule SERS hot spots to the current state-of-the-art, while highlighting open questions and future opportunities to advance the field. Comparisons with fluorescence-based super-resolution imaging are discussed to help frame the unique challenges associated with performing SERS in the super-resolution regime.