Fragment-based drug design offers multiple routes to advance from fragments. One approach is to build structure-activity relationships (SAR) from analogue series in direct-to-biology workflows. Analogues can be prepared by automated chemistry and tested as crude reaction mixtures (CRMs) without purification, but assay noise often leads to hit resynthesis, potentially discarding false negatives and reducing SAR dataset size. High-throughput (HT) X-ray crystallography has the potential to address these issues by resolving hits directly from 100s-1000s of CRMs. However, no systematic analytics exist for extracting SAR models from HT crystallographic evaluation of CRMs. Here, we demonstrate that crystallographic SAR (xSAR) can be extracted from CRMs evaluated via HT X-ray crystallography. We developed a simple rule-based ligand scoring scheme that identifies conserved chemical features associated with crystallographic binding and non-binding. Applied to a crystallographic dataset of 957 fragment elaborations in CRMs targeting PHIP(2), a therapeutically relevant bromodomain, our xSAR model demonstrated effectiveness in two proof-of-concept experiments. First, it recovered 26 missed binders in the initial dataset (false negatives), doubling the hit rate and denoising the dataset. Second, it enabled a prospective virtual screen that identified novel hits with informative chemistries and measurable binding affinities. This work establishes a proof-of-concept that xSAR models can be directly extracted from large-scale crystallographic readouts of CRMs, offering a valuable methodology to build SAR models and accelerate design-make-test iterations without requiring CRM hit resynthesis and confirmation. This invites future work to utilise advanced analytics and modelling techniques to further strengthen purification-agnostic workflows.
Diffusion MRI is widely used to characterize tissue microstructure, but standardization remains challenging, particularly for advanced models or regions with crossing fibers. Phantoms provide controlled environments to assess measurement repeatability independent of biological variability. This study evaluated the repeatability of higher-order diffusion tensor metrics using a novel anisotropic diffusion phantom designed to mimic white matter tract geometry. The phantom, containing linear, crossing (30°, 45°, 90°), and bifurcating synthetic fiber bundles, was scanned seven times using a GE Healthcare 3.0 T MRI system. Four acquisition protocols were evaluated: 30-direction DTI (b = 1000s/mm2), 60 and 90-direction High Angular Resolution Diffusion Imaging (HARDI; b = 1300s/mm2), and 30-direction Diffusion Kurtosis Imaging (DKI; b = 250, 500, 750, 1000, 1500, 2000, 2500, 3000 s/mm2). Repeatability was quantified using coefficient of variation (CoV) and intraclass correlation coefficient (ICC) for scalar diffusion metrics across six regions of interest. Fiber orientation distribution functions (fODFs) were analyzed to assess crossing fiber resolution accuracy. DTI-derived metrics demonstrated excellent repeatability, with fractional anisotropy (FA) CoV < 10% and mean, axial, and radial diffusivities < 3%. DKI-derived metrics exhibited greater variability, though kurtosis FA remained stable (CoV ∼7%). Generalized FA showed improved reliability with increased angular resolution (ICC = 0.8445 for 90-direction HARDI). fODFs accurately resolved crossing fibers at 90° (RMSE = 3.49°) and 45° (RMSE = 8.92°) but failed at 30° separation. The phantom provides reliable repeatability for standard DTI metrics and demonstrates utility for quality assurance of advanced diffusion models with high angular resolution protocols.
Accurate needle placement is essential for prostate biopsy. Recently, transperineal prostate biopsies are receiving renewed interest due to concern over infection from conventional transrectal biopsies. However, accurate needle placement is more challenging in the transperineal approach than in the transrectal approach due to the long insertion distance leading to a large targeting error and repeated insertion attempts. Improved procedure planning tools that can predict the deviation of the needle can potentially reduce the targeting error and number of insertion attempts. Prediction of deflection magnitude requires a model of biopsy needle deflection, which in turn requires information about tissue material properties. However, material properties of tissue in patients cannot be easily obtained. Accounting for this uncertainty in patient tissue properties requires a model capable of quantifying uncertainty in needle deflection as a function of a distribution of tissue properties. A Monte Carlo uncertainty quantification requires 1000s of samples, but it is not possible to obtain this many samples in a short enough time for intraoperative procedure planning using published needle deflection prediction models. This work seeks to develop a model of needle deflection fast enough for use in intraoperative procedure planning, validate this model against experimental results, and integrate it into a Monte Carlo uncertainty quantification model. This work used a mechanics-based model of biopsy needle deflection to train a Fourier feature neural network (FFNN) model in order to make predictions with a low computational cost. Both models were validated against experimental data. The neural network model was used in a Monte Carlo uncertainty quantification model to quantify uncertainty in needle deflection arising from uncertain tissue mechanical properties. This work (1) implemented a mechanics-based model and a FFNN model. Both models were validated against previously published experiments carried out with tissue phantoms. Both models showed close agreement with the experimental data. (2) We showed that our FFNN model was more accurate than a baseline ordinary least squares model, introducing only about 0.3-mm tip deflection error compared to the mechanics-based model. We also showed that our FFNN model makes unbiased predictions with respect to the amount of deflection. (3) We demonstrated a Monte Carlo uncertainty quantification model of needle deflection with a low computational cost of about 20 CPU s. We used our uncertainty quantification model to show how the depth, stiffness, and magnitude of uncertainty in a layer of tissue affect needle deflection. In addition, we showed a simple clinical example of the use of our model. This work demonstrates a Monte Carlo uncertainty quantification model of needle deflection with a low computational cost. This method shows promise for future applications in procedure planning for prostate biopsies as well as other transperineal procedures conducted with flexible needles such as cryoablation and brachytherapy.
Structure determination by X-ray diffraction is limited by crystal size and can be compromised by radiation damage when using very intense X-ray radiation. X-ray structure determination from partial diffraction data sets combined from multiple crystals is a potential solution, but its exploitation in chemistry and materials science is largely unrealized. Here we report the use of synchrotron radiation for multi-crystal X-ray diffraction (MCXRD) adapted for structure determination of metal-organic framework (MOF) materials with crystal dimensions too small for conventional single-crystal diffraction studies. We further show that radiation-induced chemical changes and degradation of diffraction quality can be alleviated. Our approach encompasses both rotation- and stationary-MCXRD measurements for 10 to 1000s of crystals with software-optimized combination of the multiple data sets. We report the crystal structures of six MOFs: MOF-919(Sc/Cu), MET-2, MIL-88B(Cr)-1,4-NDC, PCN-260(Sc), UiO-66, and UiO-66-MoO4 with unit cell dimensions ranging from 18-114 Å and crystal sizes from 0.5-480 µm3. This approach can address the challenges of structure determination in a regime of particle size and sample radiation sensitivity that lies between existing single-crystal X-ray diffraction and the emerging field of electron diffraction. MCXRD can provide accurate atomic-resolution structure determination for some of the most challenging cases in chemistry and materials science.
RNA synthesis by eukaryotic polymerases requires existing polynucleotides to serve as templates or primers. Here, we describe primer- and template-free RNA generation by human terminal nucleotidyltransferase 4B (TENT4B) via de novo polymerization of free nucleotides. We observed that recombinant TENT4B (rTENT4B) consumes ATP to yield inorganic pyrophosphate in the absence of a primer or template, concurrent with the appearance of oligomeric poly-adenosine RNA products. Remarkably, 5' labels on γ-phosphate-modified ATP or GTP are retained during polymerization in the presence of unlabeled nucleotide triphosphates (NTPs). These polymers are created at a similar efficiency irrespective of the inclusion of a primer, indicating robust RNA synthesis by rTENT4B from free NTPs. While canonical purine NTPs are favored, nucleotide diphosphates can also serve as substrates for rTENT4B-mediated de novo RNA polymerization. rTENT4B-mediated RNA synthesis using free adenosine nucleotides shows high processivity to generate 1000s-mers, whereas guanosine nucleotide polymerization is strongly and uniformly self-limited and yields a 3'-exonuclease-resistant oligonucleotide. Interrogation of other RNA polymerases reveals potential capacity for de novo polymerization using free ATP, albeit at significantly higher substrate concentrations and lower efficiency compared to rTENT4B. Our data provide definitive evidence of efficient template-free de novo RNA synthesis by a eukaryotic polymerase.
This integrative review synthesizes current knowledge on the physiological responses and adaptive mechanisms of amphibians and reptiles to multiple interacting environmental stressors, with particular emphasis on synergistic effects among temperature, hydric stress, disease, and pollution. Given the stronger empirical basis for amphibians in the existing literature, amphibian responses are covered in greater depth, while reptile-specific physiology, immunology, and emerging infectious diseases are explicitly addressed in dedicated sections throughout the review. Critical thermal tolerance analyses reveal that approximately 7.5% of amphibian species will exceed their physiological limits under a 4 °C warming scenario, with tropical lowland species already operating near their CTmax thresholds. Thermal plasticity is limited, with acclimation responses averaging only 0.13 °C increase in CTmax per 1 °C environmental warming-insufficient to track rapid climate change. Water balance regulation shows dramatic interspecific variation, with cutaneous resistance ranging from 0.05 s/cm in aquatic amphibians to >1000 s/cm in desert-adapted reptiles. Synergistic interactions between thermal and hydric stress significantly amplify vulnerability, particularly in dehydration scenarios that reduce critical thermal limits. Chemical pollutants, including heavy metals and pesticides, cause developmental abnormalities (535% increase in malformation frequency), immunosuppression, and endocrine disruption across multiple life stages. Emerging infectious diseases, particularly chytridiomycosis (Batrachochytrium dendrobatidis and B. salamandrivorans) and ranaviruses, drive mass mortality events globally, with co-infections exacerbating population declines. Climate change intensifies disease susceptibility through stress-mediated immunosuppression and altered pathogen dynamics. Adaptive capacity varies markedly among species. While amphibians exhibit strong phenological responses (2-4× greater than other taxa), genetic adaptation potential remains limited by narrow dispersal abilities and habitat fragmentation. Microhabitat buffering can reduce thermal extremes by several degrees but depends critically on habitat structural integrity. This review demonstrates that the pace of anthropogenic change challenges the adaptive capacity of most species, necessitating integrated conservation strategies including microhabitat preservation, climate corridor establishment, pollution mitigation, disease surveillance, and ex-situ conservation programs.
Lattice structures are the ideal choice for lightweight, high-strength, and energy-absorbing applications. In this study, the mechanical response of Stretching-Bending Synergistic Lattices (SBSLs) fabricated from 316L stainless steel is investigated under dynamic compression at high strain rates using finite element modeling (FEM), which has been experimentally validated. The results show that the strain rate has a significant influence on specific strength and specific energy absorption (SEA). When the strain rate increases from 100 s-1 to 1000 s-1, the specific strength increases by 75.6%. A smaller cell height enhances overall impact resistance. The increase in the diameter of the backbone cell rod can simultaneously enhance the SEA and specific strength. To maximize SEA, optimization models for uniform SBSLs and gradient SBSLs are respectively constructed. When the relative density varies, the SEA of the optimized uniform SBSLs has increased by 275.4% and 368.8% compared with the initial SBSL and uniform lattice (UL) designs, respectively. Similarly, the SEA of the gradient SBSLs is enhanced by 154% and 217% compared to the initial design of SBSLs and ULs, respectively. This work deepens understanding of rate-dependent deformation in multi-layer lattices, guiding their design for dynamic loading.
Platelets bind plasminogen facilitating surface-bound plasmin generation. We previously reported that the plasminogen receptor, Plg-RKT, retains plasminogen on activated platelets. Here, we investigate the significance of the interaction of Plg-RKT on thrombus formation, growth and stability. Whole blood from Plg-RKT-/- or littermate Plg-RKT+/+ mice was flowed over collagen/tissue factor-coated microfluidic biochips at 250 or 1000 s-1 to reflect venous and arterial shear rates. AlexaFluor488-fibrinogen and Dylight633-labelled-plasminogen accumulation was monitored in real-time by fluorescence microscopy in the presence or absence of tissue plasminogen activator (tPA). At 1000 s-1, plasminogen accumulation was reduced in thrombi formed from Plg-RKT-/- mice compared to Plg-RKT+/+ mice. Fibrin(ogen) accumulation in Plg-RKT-/- mice persisted for the duration of the experiment, indicating impaired fibrinolysis compared to Plg-RKT+/+ mice. Mice were subjected to FeCl3 carotid artery model of thrombosis followed by tPA infusion. Initial platelet deposition was faster in Plg-RKT-/- mice compared to Plg-RKT+/+ mice. Fibrin(ogen) accumulation and persistence was enhanced in Plg-RKT-/- mice indicating impaired fibrinolysis. We demonstrate for the first time that under arterial shear, Plg-RKT facilitates plasminogen incorporation and limits both platelet recruitment to the forming thrombus and fibrin accumulation. These data highlight that Plg-RKT and potentially plasmin on the platelet surface regulate arterial thrombus growth.
to enhance the measurement performance of satellite laser ranging (SLR) on an active satellite, we suggest utilizing a high-data-rate free-space laser communication (lasercom) link for time/distance measurement. As a demonstrator, a new laser ranging technique based on a 10 Gbps lasercom link is implemented to measure the propagation delay over a folded 2.5 km free-space path. In this document, we describe the measurement principle and the experimental setup to achieve a sensitivity of a few tens of fs from a 10 Gbps on-off keying (OOK) telecom signal generated by commercial telecom components. The high speed and high sensitivity of the ranging system make it possible to precisely characterize the timing jitter/drift caused by the atmosphere over 5.0 km. The sensitivity of the ranging system is validated through independent estimates obtained from turbulence monitoring instruments, including GDIMM (generalized differential image motion monitor) and a SHWFS (Shack-Hartmann wavefront sensor). For short time scales, fluctuations exceeding 350 fs rms were observed over integration times between 5 ms and 5 s, consistent with theoretical predictions derived from the turbulence structure parameter Cn2 and outer scale L0 measured by GDIMM and the SHWFS. For long time ranges, > 1000 s, the variation of the propagation delay is dominated by the slow drift of the air refractive index and is in agreement with estimates based on the metrological parameters (temperature, humidity, pressure, CO2 content) measured by two stations at two sites.
Poor sedimentation stability remains a critical bottleneck hindering the widespread application of magnetorheological fluids (MRFs). To address this challenge, we propose a synergistic strategy that combines plasma surface engineering with micro-nano dual-dispersed particles to simultaneously tailor interfacial properties and suspension microstructure. Graphite-coated Fe/FeN core-shell magnetic nanoparticles (Fe/FeN@G) were synthesized through the pyrolysis of ferrocene in high-temperature plasma and subsequently fluorinated in a low-temperature CF4 plasma to obtain Fe/FeN@PFG. Unlike previous studies that individually employed plasma-treated carbonyl iron particles or bidisperse micro-nano systems, the present work integrates fluorinated Fe/FeN@PFG nanoparticles as a nanosized secondary phase with micron-sized carbonyl iron (CI) at a fixed solid loading of 50 wt % without additional stabilizing additives, thereby constructing an additive-free, plasma-engineered bidisperse MRF. Plasma fluorination introduces a fluorine-containing organic layer (C-F/C-F2 bonds), reduces the contact angle with silicone oil from 65.7° to 40.3°, and promotes the formation of a shear-sensitive three-dimensional thixotropic network. The resulting Fe/FeN@PFG-CI MRF exhibits a high zero-field viscosity of 73.2 Pa·s at 0.01 s-1, providing structural antisedimentation support, while maintaining a low viscosity of 0.111 Pa·s at 1000 s-1 to ensure good flowability. Despite the enhanced off-state viscosity and elasticity, the system retains reversible magnetorheological responses and fast thixotropic recovery. Sedimentation stability is markedly improved, as reflected by a turbiscan stability index of only 0.51 after 5.3 h and a sedimentation ratio of 85% after 72 h. These findings demonstrate that coupling core-shell nanoparticle design with CF4 plasma fluorination offers a cost-effective and scalable route to high-stability, high-performance MRFs that complement and extend existing stabilization strategies.
This study aimed to investigate the feasibility of MR diffusion imaging of fresh prostate needle biopsy cores in a 14 Tesla vertical bore NMR system. Biopsies sampled from the index tumor and a presumed tumor-free area of eight prostatectomy specimens underwent diffusion-weighted imaging using conventional pulsed gradient spin echoes (PGSE) and stimulated echo acquisition mode (STEAM) with different gradient separation times between 10 and 400 ms at nominal b values ranging from 0 up to 5000 s/mm2. The apparent diffusion coefficient (ADC) was determined over the b-value range 0-1000 s/mm2. Kurtosis and biexponential models were fitted to measured signals at effective b values within the range 0-2000 and 0-5000 s/mm2, respectively. Moreover, monoexponential models were fitted over the same b-value ranges. After imaging, all biopsies underwent histopathological evaluation. For all diffusion gradient separation times evaluated, the ADC of histopathologically confirmed tumor and normal tissue was not significantly different (p = 0.140 at 10 ms gradient separation time). Irrespective of the investigated tissue type, for an increasing gradient separation time up to 150 ms ADC decreased. For longer times up to 400 ms no further change was evident. For short diffusion gradient separation times, the Akaike information criterion (AIC) favored the biexponential model in almost all voxels, but for longer diffusion gradient separation times, in a majority of voxels the AIC favored the monoexponential model over either the kurtosis or biexponential model. Imaging of fresh prostate biopsies is feasible. At short diffusion times, in agreement with the presence of at least two distinct compartments, the signal decay is well described by a biexponential model. At long diffusion times, the ADC is lower, and a monoexponential model tends to be more appropriate, indicating the presence of exchange between compartments.
Electronic devices operating in extreme cold environments, such as outdoor base stations and polar unmanned aerial vehicles, require not only electromagnetic interference (EMI) shielding but also effective anti-icing and deicing capabilities to prevent ice formation and accretion. Protective materials that integrate anti-icing/deicing and EMI shielding functions are critically in demand. The multifunctional superhydrophobic Ti3C2Tx MXene/poly(methyl methacrylate) (PMMA) thin film presented herein accomplishes this goal through rational material selection and structural design. A continuous MXene-flakes-constructed conductive network is embedded with radially diameter-arranged PMMA microspheres driven by electrostatic force. Tightly packed nanospheres generate abundant hierarchical wrinkles on the surface, establishing the structural foundation for light absorptivity (89.56%) and hydrophobicity, which reaches a water contact angle of 155.6° after further hydrophobic modification. The existence of PMMA also prevents supercooled droplet penetration into the composite structure under high-humidity environments and prolongs icing time by retarding heat transfer simultaneously. Due to the excellent photothermal and electrothermal properties of MXene, the film surface can remain ice-free for extended periods (>1000 s) under low-temperature and high-humidity conditions with minimal external energy input, while also enabling rapid removal of any accumulated ice. The film remains superior EMI shielding performance, showing an EMI SE of 54.2 dB at 35 ± 7 μm thickness at X-band. This work supplies a promising approach for efficiently integrating anti/deicing and EMI shielding functions.
Background/Objectives: Whole-blood viscosity (WBV) is increasingly used in cardiovascular risk assessment; however, inter-device comparability may depend on shear-rate definition. We performed a paired comparison of two scanning capillary viscometers to evaluate shear-dependent analytical agreement and its impact on clinical classification. Methods: In 300 identical blood samples, WBV was measured using Rheovis 2000A and Hemovister. Systolic WBV was defined at 300 s-1 for both devices (shear-matched), whereas clinically defined diastolic WBV corresponded to 1 s-1 for Rheovis 2000A and 5 s-1 for Hemovister. Agreement was assessed using linear regression and Bland-Altman analysis. Hematocrit tertiles were examined as effect modifiers. Clinical agreement was evaluated using quadratic weighted Cohen's κ. Results: Across matched shear rates (1000 to 1 s-1), Hemovister yielded consistently higher WBV values than Rheovis 2000A, with statistically significant inter-device differences at all shear levels except 1000 s-1. The magnitude of bias increased progressively as shear rate decreased, reaching -8.34 mPa·s at 1 s-1. Under shear-matched systolic conditions (300 s-1), the mean difference was -0.25 mPa·s (limits of agreement -1.72 to 1.22). In contrast, under clinically defined diastolic conditions (1 vs. 5 s-1), the mean difference was 14.54 mPa·s (3.93 to 25.15), increasing across hematocrit tertiles. Clinical agreement was fair for systolic (κ = 0.31; 95% CI 0.24 to 0.39) and moderate for diastolic WBV (κ = 0.44; 95% CI 0.37 to 0.51). Notably, among samples classified as high by Hemovister, 72.8% (systolic) and 54.0% (diastolic) were reclassified as normal by Rheovis 2000A. Conclusions: Inter-device agreement in WBV measurement is strongly shear-dependent. Although numerical divergence increases at low shear, categorical concordance may remain moderate when device-specific reference thresholds are applied. Harmonization of shear definitions and reference frameworks may therefore be essential for consistent cross-platform interpretation.
This study investigates age-related changes in diffusion-relaxation coupling within basal ganglia nuclei using a novel single-scan multi-TE diffusion-weighted imaging (SMT-DWI) approach, with a focus on microstructural alterations associated with regional iron deposition patterns during normal brain aging. Fifty-seven healthy participants (10-73 years) underwent optimized SMT-DWI at 3T, simultaneously acquiring multi-b-value (0/500/1000 s/mm²) and multi-TE (53/71/89 ms) data in 7:58 minutes (1.5 × 1.5 × 4 mm³ resolution). Apparent diffusion coefficient (ADC) and R2 maps were generated through mono-exponential fitting, with coupling quantified via TE-dependent ADC (kADC/TE) and b-value-dependent R2 (kR2/b) metrics. Iron-related tissue properties were assessed using R2 at b = 0 (R2b = 0) as a surrogate. The SMT-DWI method achieved excellent image quality (e.g., SNR = 63.8 under the most unfavorable conditions of b = 1000 s/mm² and TE = 89 ms) with good anatomical delineation. Young subjects exhibited positive coupling (ADC increasing with TE, R2 rising with b-value) across basal ganglia, while older adults showed progressive inversion to negative coupling that correlated strongly with age after accounting for sex as a covariant (sex was not a significant predictor; all p > 0.05). This transition was the most pronounced in iron-rich putamen (p < 0.001, R2b = 0 = 0.0208 ± 0.0027 ms-¹), globus pallidus (p < 0.001, R2b = 0 = 0.0276 ± 0.0030 ms-¹), and substantia nigra (p < 0.001, R2b = 0 = 0.0241 ± 0.0023 ms-¹), while the caudate maintained stable coupling (p > 0.05) with lower iron levels (R2b = 0 = 0.0169 ± 0.0012 ms-¹). All four regions demonstrated significant negative correlations between coupling metrics and R2b = 0 (r = -0.38 to -0.75, all p < 0.01), consistent with a role for iron-mediated microstructural changes in driving the observed coupling shifts. The age-dependent inversion from positive to negative diffusion-relaxation coupling reflects regionally heterogeneous microstructural alterations in basal ganglia. Our method provides sensitive detection of compartment-sensitive microstructural alterations, offering new insights into normal brain aging and a potential biomarker for neurodegenerative risk assessment.
To determine whether a new deep learning (DL) based phase corrected (DLPC) reconstruction model can enhance image quality of diffusion weighted images of the prostate acquired at 1.5 T compared to a commercially available DL based product. A retrospective study of 30 consecutive patients undergoing conventional multiparametric MRI (mpMRI) of the prostate on a single 1.5 T scanner was performed. Diffusion image datasets reconstructed with a commercially available DL product and a new DLPC model were assessed. Qualitative image assessment was performed by three board certified radiologists using a 5-point Likert scale across four features and inter-rater agreement was estimated using Gwet's AC2 statistic. Quantitative image comparison was performed by assessing SNR of acquired intermediate b-value (b = 1000 s/mm2) diffusion images. The Wilcoxon matched-pairs signed rank test was used to assess differences between techniques. Image noise was assessed using the edge function. Median patient age was 70 years (interquartile range: 66.0-75.3). All radiologists perceived less noise and better image quality for all DLPC image sets compared to commercial DL images (p < 0.05). Significantly higher SNR was observed for the acquired intermediate b-value diffusion images reconstructed with DLPC (median SNR: 49.4 vs 27.5; p < 0.001), and mean ADC values did not significantly differ between DLPC and DL images (p = 0.63). Edge analyses demonstrated significantly reduced noise for DLPC images (p < 0.001). DLPC image reconstruction of diffusion weighted prostate image datasets reduces image noise and improves SNR over a commercial DL product at 1.5 T.
Reactive jet impingement is a 3D bioprinting process which forms cell filled hydrogels through reacting droplets of polymer and crosslinker solutions. This study evaluates for the first time the relationship between the droplet volumes of the hydrogels with the viscosity and surface tension of the starting solutions. Calcium chloride, sodium alginate, thrombin, and fibrinogen solutions are characterised together with two blended solutions: collagen-alginate-fibrin and thrombin-calcium chloride, which combine to create a collagen-alginate-fibrin hydrogel. The influence of cells on bio-ink behaviour has been assessed through suspending TC28a chondrocytes within the thrombin-calcium chloride solution. Viscosity was a greater differentiator in defining print volumes than surface tension, and there is a clear relationship between droplet volume and kinematic viscosity measured at high strain rates (1000 s-1). The addition of cells had a minimal effect on the kinematic viscosity of solutions at high strain rates and, therefore, on processing of cell filled hydrogels, meaning that processing high cell densities is possible without significant adjustments to processing parameters. Reactive jet impingement is a reliable and accurate process for creating high cell density hydrogels, and the kinematic viscosity at high strain rates is the key mechanical property in defining the relative print volumes of different inks.
Objective.Heart rate variability (HRV) is widely used to assess autonomic function, but the minimum data length required for reliable ultra-short-term (UST) frequency-domain analysis remains without consensus. This study aimed to (1) identify factors determining the minimum required length and (2) determine minimum length for reliable estimation.Approach.Simulated relatively stationary inter-beat intervals (IBIs) were used to examine spectral factors influencing minimum data length. Relatively stationary IBIs from 20 min resting electrocardiogram (ECG) recordings in eight healthy subjects were analyzed to determine practical requirements. High frequency (HF) and low frequency (LF) estimates were compared against 5 min references, and very low frequency (VLF) against 20 min references, using limits of agreement (LoA) and intraclass correlation coefficient (ICC).Results.Both signal properties (spectral distribution proximity to defined band edges) and spectral analysis parameters (window and segment length) are critical factors determining the minimum required length. Data lengths of ∼60 s, 100 s, and 1000 s provided coarse estimates for HF, LF, and VLF, respectively, with ICC > 0.9. More reliable estimates were achieved at ∼90 s, 250 s, and 1080 s, where the LoA remained within ±20%. Even stricter reliability was obtained at ∼200 s, 290 s, and 1180 s, where the LoA further narrowed to within ±10%. Although LF achieved ICC > 0.90 at ∼100 s, the LoA remained wide (> ± 50%), reliable LF estimation required⩾220 s, where both absolute values and ICC stabilized.Significance.These findings offer methodological insights into the selection of recording durations and parameters for UST frequency-domain HRV analysis in clinical, wearable, and research applications.
Cervical cancer is the fourth most common cause of cancer and cancer related mortality among women worldwide. MRI is standard of care for cervical cancer staging. The objective of this project is to evaluate the feasibility and performance of an advanced diffusion-weighted imaging (DWI) MRI technique for cervical cancer. Forty-four patients with cervical cancer and 22 healthy volunteers underwent 3 T pelvic MRI with reduced field-of-view (FOV) multi-shell diffusion-weighted imaging (DWI; b = 0-3000 s/mm2). Patients were divided into model development and independent testing cohorts. Healthy volunteers provided reference distributions for Z-score mapping. RSI models with multi-exponential components were fitted to tumor signals. For each model, the outputs were voxel-wise compartmental signal contributions (Ci,N) from each water component within tissue. Model performance was assessed using the Bayesian Information Criterion (BIC), tumor contrast-to-noise ratio (CNR), and Z-scores. Conventional apparent diffusion coefficient (ADC) was estimated from full-FOV DWI (b = 50-1000 s/mm2). The tetra-exponential model achieved the highest CNR, with only a 6% BIC increase relative to the bi-exponential model. In an independent cohort, CNR was significantly higher in restricted compartments C1,3 (median 14.3) and C1,4 (median 26.2) compared with ADC. Tumor Z-scores were elevated in C1,3 (median 3.8) and C1,4 (median 8.0), whereas other compartments remained near zero. RSI with Z-score mapping improved cervical cancer conspicuity compared with ADC, producing interpretable maps that localized tumor signal to restricted diffusion compartments. Based on BIC and CNR, the tetra-exponential RSI model was optimal, supporting RSI as a feasible non-contrast imaging strategy for cervical cancer evaluation.
To demonstrate improved image quality and lesion conspicuity in prostate diffusion-weighted imaging (DWI) using an inside-out nonlinear gradient coil that provides locally strong gradients (200-500 500 mT/m) at typical prostate positions. Before applying the nonlinear gradient coil to DWI with Echo Planar Imaging (EPI) readout, we investigated geometric distortion and eddy currents, and proposed necessary corrections. We then developed two DWI protocols (bmax = 1000 and 3000 s/mm2) with minimized echo time (TE) and tested them on volunteers and patients. We validated apparent diffusion coefficient (ADC) maps from the nonlinear gradient acquisition against the reference (linear gradients only). We quantified improvements in signal-to-noise ratio (SNR), lesion contrast-to-noise ratio (CNR), and lesion-to-normal-tissue contrast ratio in the compartmental map of restricted diffusion. Corrections effectively reduced nonlinear-gradient DWI artifacts. ADC maps from linear- and nonlinear-gradient-encoded studies agreed well, with a normalized root-mean-square-error of ∼10%, a common level of ADC variation. TE was significantly reduced from 57 to 42-47 ms for moderate b-values (≤ 1000 s/mm2) and from 72 to 42-54 ms for high b-values (≤ 3000 s/mm2). Consequently, SNR increased by 3%-38% (median 16%, p < 0.01) and 7%-38% (median 26%, p < 0.01), respectively. Lesion CNR improved by a median of 133% at b = 2000 s/mm2 and 217% at b = 3000 s/mm2. The restricted diffusion component in lesions was more conspicuous at short TE, with a median 23% increase in lesion-to-normal-tissue contrast ratio (p = 0.02). The inside-out nonlinear gradient coil enhances prostate DWI.
Urea is a common nitrogenous pollutant in agricultural and industrial wastewaters, and its electrochemical oxidation in alkaline media enables simultaneous detoxification and energy recovery. Herein, we report an interface-engineering strategy based on P,N-modified nickel-carbon nanofibers prepared via a scalable electrospinning-carbonization process using ammonium phosphate as a multifunctional precursor. During thermal treatment, phosphorus and nitrogen heteroatoms are incorporated into the carbon framework while regulating the surface chemistry of embedded nickel nanoparticles, promoting the formation of a NiOOH-ready interfacial layer. Structural analyses (XRD, SEM/TEM) confirm the formation of metallic Ni domains uniformly dispersed within turbostratic carbon nanofibers. XPS reveals the coexistence of Ni0/Ni+2/Ni+3 species along with phosphate- and nitrogen-derived functionalities that enhance electronic modulation and redox reversibility. In 1.0 M KOH, the optimized composition exhibits a Ni+2/Ni+3 redox charge of ~12.5 mC.cm-2. For urea electrooxidation (0.5 M urea), the catalyst delivers a maximum current density of ~115 mA.cm-2 with a low onset potential of 0.37 V (vs Ag/AgCl). The apparent activation energy is 9.82 kJ.mol-1, indicating a kinetically favorable NiOOH-mediated pathway. Chronoamperometry shows stable operation with ~70-80% current retention over 1000 s. When implemented as an anode in a membrane-less direct urea fuel cell, the material achieves a peak power density of ~1.1 W.m-2 at 35 °C, demonstrating practical wastewater-to-energy feasibility. This work highlights how dual heteroatom modification of carbon nanofibers can regulate nickel interfacial chemistry, enabling efficient urea remediation coupled with renewable power generation.