Search Results (25)

Neurorehabilitation has become increasingly data-enabled, yet the conditions that most strongly modulate recovery, sleep consolidation, circadian alignment, medication ecology, and social–environmental context are rarely captured or acted upon. This opinion paper argues that an exposome perspective, defined as the cumulative pattern of external and internal exposures and their biological imprints across the life course, is not ancillary to rehabilitation but foundational to making therapy learnable, timely, and equitable. We propose a pragmatic model that centers on a minimal exposure dataset collected in minutes and interpreted at the point of care. Two clinical exemplars illustrate feasibility and utility. First, sleep and circadian rhythms: brief actigraphy and standardized reporting can make daily alertness windows visible, allowing teams to align high-intensity sessions to receptive states and to justify environmental adjustments as clinical interventions. Second, anticholinergic burden: a simple, trackable index can be integrated with functional goals to guide deprescribing and optimize cognitive availability for training. Implementation hinges less on new infrastructure than on workflow design: a short intake that surfaces high-yield exposures; embedding targets, e.g., sleep efficiency thresholds or anticholinergic load reductions, into plans of care; enabling secure import of device data; and training staff to interpret rhythm metrics and burden scores. We outline a parallel research agenda comprising pragmatic trials of bundled, exposure-informed care; longitudinal cohorts with time-stamped exposure streams; and causal methods suited to time-varying confounding, all under explicit equity and ethics safeguards. By measuring a few modifiable exposures and linking them to routine decisions, neurorehabilitation can convert context from a source of unexplained variance into actionable levers that improve outcomes and narrow unjust gaps in recovery. Full article

Assessing the driver’s state in real time is a critical challenge in modern vehicle safety systems, as human factors account for the vast majority of traffic accidents. Heart rate (HR) is a key physiological indicator of the driver’s condition, yet contactless measurements in dynamic in-vehicle environments remain difficult due to motion artifacts, vibrations, and varying operational conditions. This paper presents a novel two-stage method for HR estimation using a commercial 60 GHz frequency-modulated continuous wave (FMCW) radar sensor, specifically designed and validated for in-vehicle applications. In the first stage, coarse HR estimation is performed using the discrete wavelet transform (DWT) and autoregressive (AR) spectral analysis. The second stage refines the estimate using an inverse application of the relevance vector machine (RVM) approach, leveraging a narrowed frequency window derived from Stage 1. Final HR estimates are stabilized through sequential Kalman filtering (SKF) across time segments. The system was implemented using an Infineon BGT60TR13C radar module installed in the sun visor of a passenger vehicle. Extensive data collection was conducted during real-world driving across diverse traffic scenarios. The results demonstrate robust HR estimations with an accuracy comparable to that of commercial wearable devices, validated against a Polar H10 chest strap. This method offers several advantages over prior work, including short measurement windows (5 s), operation under varying lighting and clothing conditions, and validation in realistic driving environments. In this sense, the method contributes to the field of biomimetics by transferring the biological principles of continuous vital sign perception to technical sensorics in the automotive domain. Future work will explore the fusion of sensors with visual methods and potential extension to heart rate variability (HRV) estimations to enhance driver monitoring systems (DMSs) further. Full article

Background: Genetic variation provides a foundation for understanding evolution. With the rise of artificial intelligence, machine learning has emerged as a powerful tool for identifying genomic footprints of evolutionary processes through simulation-based predictive modeling. However, existing approaches require prior knowledge of the factors shaping genetic variation, whereas uncovering anomalous genomic regions regardless of their causes remains an equally important and complementary endeavor. Methods: To address this problem, we introduce ANDES (ANomaly DEtection using Summary statistics), a suite of algorithms that apply statistical techniques to extract features for unsupervised anomaly detection. A key innovation of ANDES is its ability to account for autocovariation due to linkage disequilibrium by fitting curves to contiguous windows and computing their first and second derivatives, thereby capturing the “velocity” and “acceleration” of genetic variation. These features are then used to train models that flag biologically significant or artifactual regions. Results: Application to human genomic data demonstrates that ANDES successfully detects anomalous regions that colocalize with genes under positive or balancing selection. Moreover, these analyses reveal a non-uniform distribution of anomalies, which are enriched in specific autosomes, intergenic regions, introns, and regions with low GC content, repetitive sequences, and poor mappability. Conclusions: ANDES thus offers a novel, model-agnostic framework for uncovering anomalous genomic regions in both model and non-model organisms. Full article

Background/Objectives: High-throughput metabolomics data provide a detailed molecular window into biological processes. We consider the problem of assessing how association of metabolite levels with individual (sample) characteristics, such as sex or treatment, depend on metabolite characteristics such as pathways. Typically, this is done using a two-step process. In the first step, we assess the association of each metabolite with individual characteristics. In the second step, an enrichment analysis is performed by metabolite characteristics. Methods: We combine the two steps using a bilinear model based on the matrix linear model (MLM) framework previously developed for high-throughput genetic screens. Our method can estimate relationships in metabolites sharing known characteristics, whether categorical (such as type of lipid or pathway) or numerical (such as number of double bonds in triglycerides). Results: We demonstrate the flexibility and interoperability of MLMs by applying them to three metabolomic studies. We show that our approach can separate the contribution of the overlapping triglyceride characteristics, such as the number of double bonds and the number of carbon atoms. Conclusion: The matrix linear model offers a flexible, efficient, and interpretable framework for integrating external information and examining complex relationships in metabolomics data. Our method has been implemented in the open-source Julia package, MatrixLM. Data analysis scripts with example data analyses are also available. Full article

Environmental changes, such as applied medication, nutrient depletion, and accumulation of metabolic residues, affect cell culture activity. The combination of these factors reflects on the local temperature distribution and local oxygen concentration towards the cell culture scaffold. However, determining the temporal variation of local temperature, independent of local oxygen concentration changes in biological specimens, remains a significant technological challenge. The process of triplet–triplet annihilation upconversion (TTA-UC), performed in a nanoconfined environment with a continuous aqueous phase, appears to be a possible solution to these severe sensing problems. This process generates two optical signals (delayed emitter fluorescence (dF) and residual sensitizer phosphorescence (rPh)) in response to a single external stimulus (local temperature), allowing the application of the ratiometric-type sensing procedure. The ability to incorporate large amounts of sacrificial singlet oxygen scavenging materials, without altering the temperature sensitivity, allows long-term protection against photo-oxidative damage to the sensing moieties. Translucent agarose/silk fibroin hydrogels embedding non-ionic micellar systems containing energetically optimized annihilation couples simultaneously fulfill two critical functions: first, to serve as mechanical support (for further application as a cell culture scaffold); second, to allow tuning of the material response window to achieve a maximum temperature sensitivity better than 0.5 K for the physiologically important region around 36 °C. Full article

Organic molecular fluorophores have been extensively utilized for biological imaging in the visible and the first near-infrared windows. However, their applications in the second near-infrared (NIR-II) window remain constrained, primarily due to the insufficient fluorescence brightness. Herein, we employ a theoretical protocol combining the thermal vibration correlation function with the time-dependent density functional theory method to investigate the mechanism of the planar-twisted strategy for developing fluorophores with balanced NIR-II emission and fluorescence brightness. Based on a planar donor–acceptor–donor molecular skeleton, various ortho-positioned alkyl side chains with steric hindrances are tactfully incorporated into the backbone to construct a series of twisted fluorophores. Photophysical characterizations of the studied fluorophores demonstrate that the emission spectra located in the NIR-II region exhibited a hypsochromic shift with the structural distortion. Notably, conformational twisting significantly accelerated the radiative decay rate while simultaneously suppressing the nonradiative decay rate, resulting in an improved fluorescence quantum efficiency (FQE). This enhancement can be mainly attributed to both the enlarged adiabatic excitation energy and reduced nonadiabatic electronic coupling between the first excited state and the ground state. Compared with the planar fluorophore, the twisted structures possessed a more than fivefold increase in FQE. In particular, the optimal twisted fluorophore BBTD-4 demonstrated a desirable fluorescence brightness (16.59 M⁻¹ cm⁻¹) on the premise of typical NIR-II emission (980 nm), making it a promising candidate for NIR-II fluorescence imaging in biomedical applications. The findings in this study elucidate the available experimental observations on the analogues, highlighting a feasible approach to modulating the photophysical performances of NIR-II chromophores for developing more highly efficient fluorophores toward optical imaging applications. Full article

The phosphors with persistent luminescence in the NIR (near-infrared) region and the NIR-to-NIR Stokes luminescence properties have received considerable attention owing to their inclusive application prospects in the in vivo imaging field. In this paper, Nd³⁺ doped SrSnO₃ phosphors with remarkable NIR emission performance were prepared using a high temperature solid state reaction method; the phase structure, morphology, and luminescence properties were discussed systematically. The SrSnO₃ host exhibits broadband NIR emission (800–1300 nm) with absorptions in the near ultraviolet region. Nd³⁺ ions emerge excellent NIR-to-NIR Stokes luminescence under 808 nm laser excitation, with maximum emission at around ~1068 nm. The concentration-dependent luminescence properties, temperature dependent emission, and the luminescence decay curves of Nd³⁺ in the SrSnO₃ host were also studied. The Nd³⁺ doped SrSnO₃ phosphors exhibit exceptional thermal stability; the integrated emission intensity can retain approximately 66% at 423 K compared to room temperature. Most importantly, NIR persistent luminescence also can be observed for the SrSnO₃:Nd³⁺ samples, which is in the first and second biological windows. A possible mechanism was proposed for the persistent NIR luminescence of Nd³⁺ based on the thermo-luminescence spectra. Consequently, the exciting results indicate that multifunctional NIR luminescence has been successfully realized in the SrSnO₃:Nd³⁺ phosphors. Full article

Informed species delimitation is crucial in diverse biological fields; however, it can be problematic for species complexes. Showing a peripatric distribution pattern, Stewartia gemmata and S. acutisepala (the S. gemmata complex) provide us with an opportunity to study species boundaries among taxa undergoing nascent speciation. Here, we generated genomic data from representative individuals across the natural distribution ranges of the S. gemmata complex using restriction site-associated DNA sequencing (RAD-seq). Based on the DNA sequence of assembled loci containing 41,436 single-nucleotide polymorphisms (SNPs) and invariant sites, the phylogenetic analysis suggested strong monophyly of both the S. gemmata complex and S. acutisepala, and the latter was nested within the former. Among S. gemmata individuals, the one sampled from Mt. Tianmu (Zhejiang) showed the closest evolutionary affinity with S. acutisepala (which is endemic to southern Zhejiang). Estimated from 2996 high-quality SNPs, the genetic divergence between S. gemmata and S. acutisepala was relatively low (an F_st of 0.073 on a per-site basis). Nevertheless, we observed a proportion of genomic regions showing relatively high genetic differentiation on a windowed basis. Up to 1037 genomic bins showed an F_st value greater than 0.25, accounting for 8.31% of the total. After SNPs subject to linkage disequilibrium were pruned, the principal component analysis (PCA) showed that S. acutisepala diverged from S. gemmata along the first and the second PCs to some extent. By applying phylogenomic analysis, the present study determines that S. acutisepala is a variety of S. gemmata and is diverging from S. gemmata, providing empirical insights into the nascent speciation within a species complex. Full article

For photothermal therapy of cancer, it is necessary to find Ag @TiO₂ core-shell nanoparticles that can freely tune the resonance wavelength within the near-infrared biological window. In this paper, the finite element method and the size-dependent refractive index of metal nanoparticles were used to theoretically investigate the effects of the core material, core length, core aspect ratio, shell thickness, refractive index of the surrounding medium, and the particle orientation on the light absorption properties of Ag@TiO₂ core-shell nanospheroid and nanorod. The calculations show that the position and intensity of the light absorption resonance peaks can be freely tuned within the first and second biological windows by changing the above-mentioned parameters. Two laser wavelengths commonly used in photothermal therapy, 808 nm (first biological window) and 1064 nm (second biological window), were selected to optimize the core length and aspect ratio of Ag@TiO₂ core-shell nanospheroid and nanorod. It was found that the optimized Ag@TiO₂ core-shell nanospheroid has a stronger light absorption capacity at the laser wavelengths of 808 nm and 1064 nm. The optimized Ag@TiO₂ core-shell nanoparticles can be used as ideal therapeutic agents in photothermal therapy. Full article

Human skeletal development is continuous and staged, and different stages have various morphological characteristics. Therefore, bone age assessment (BAA) can accurately reflect the individual’s growth and development level and maturity. Clinical BAA is time consuming, highly subjective, and lacks consistency. Deep learning has made considerable progress in BAA in recent years by effectively extracting deep features. Most studies use neural networks to extract global information from input images. However, clinical radiologists are highly concerned about the ossification degree in some specific regions of the hand bones. This paper proposes a two-stage convolutional transformer network to improve the accuracy of BAA. Combined with object detection and transformer, the first stage mimics the bone age reading process of the pediatrician, extracts the hand bone region of interest (ROI) in real time using YOLOv5, and proposes hand bone posture alignment. In addition, the previous information encoding of biological sex is integrated into the feature map to replace the position token in the transformer. The second stage extracts features within the ROI by window attention, interacts between different ROIs by shifting the window attention to extract hidden feature information, and penalizes the evaluation results using a hybrid loss function to ensure its stability and accuracy. The proposed method is evaluated on the data from the Pediatric Bone Age Challenge organized by the Radiological Society of North America (RSNA). The experimental results show that the proposed method achieves a mean absolute error (MAE) of 6.22 and 4.585 months on the validation and testing sets, respectively, and the cumulative accuracy within 6 and 12 months reach 71% and 96%, respectively, which is comparable to the state of the art, markedly reducing the clinical workload and realizing rapid, automatic, and high-precision assessment. Full article

Nanophosphors are widely used, especially in biological applications in the first and second biological windows. Currently, nanophosphors doped with lanthanide ions (Ln³⁺) are attracting much attention. However, doping the matrix with lanthanide ions is associated with a narrow luminescence bandwidth. This paper describes the structural and luminescence properties of co-doped LaPO₄ nanophosphors, fabricated by the co-precipitation method. X-ray structural analysis, scanning electron microscope measurements with EDS analysis, and luminescence measurements (excitation 395 nm) of LaPO₄:Eu³⁺/Nd³⁺ and LaPO₄:Eu³⁺/Nd³⁺/Yb³⁺ nanophosphors were made and energy transfer between rare-earth ions was investigated. Tests performed confirmed the crystal structure of the produced phosphors and deposition of rare-earth ions in the structure of LaPO₄ nanocrystals. In the range of the first biological window (650–950 nm), strong luminescence bands at the wavelengths of 687 nm and 698 nm (⁵D₀ → ⁷F₄:Eu³⁺) and 867 nm, 873 nm, 889 nm, 896 nm, and 907 nm (⁴F_3/2 → ⁴I_9/2:Nd³⁺) were observed. At 980 nm, 991 nm, 1033 nm (²F_5/2 → ²F_7/2:Yb³⁺) and 1048 nm, 1060 nm, 1073 nm, and 1080 nm (⁴F_3/2 → ⁴I_9/2:Nd³⁺), strong bands of luminescence were visible in the 950 nm–1100 nm range, demonstrating that energy transfer took place. Full article

This article describes the synthesis and characterization of two nanocarriers consisting of β-cyclodextrin-based nanosponges (NSs) inclusion compounds (ICs) and gold nanorods (AuNRs) for potential near-infrared II (NIR-II) drug-delivery systems. These nanosystems sought to improve the stability of two drugs, namely melphalan (MPH) and curcumin (CUR), and to trigger their photothermal release after a laser irradiation stimulus (1064 nm). The inclusion of MPH and CUR inside each NS was confirmed by field emission scanning electron microscopy (FE-SEM), Raman spectroscopy, Fourier transform infrared spectroscopy, (FT-IR) differential scanning calorimetry (DSC), transmission electron microscopy (TEM), and proton nuclear magnetic resonance (¹H-NMR). Furthermore, the association of AuNRs with both ICs was confirmed by FE-SEM, energy-dispersive spectroscopy (EDS), TEM, dynamic light scattering (DLS), ζ-potential, and UV–Vis. Moreover, the irradiation assays demonstrated the feasibility of the controlled-photothermal drug release of both MPH and CUR in the second biological window (1000–1300 nm). Finally, MTS assays depicted that the inclusion of MPH and CUR inside the cavities of NSs reduces the effects on mitochondrial activity, as compared to that observed in the free drugs. Overall, these results suggest the use of NSs associated with AuNRs as a potential technology of controlled drug delivery in tumor therapy, since they are efficient and non-toxic materials. Full article

We report a computed tomography (CT) technique for mapping near-infrared fluorescence (NIRF) lifetime as a multiplex three-dimensional (3D) imaging method, using a conventional NIR camera. This method is achieved by using a time-gated system composed of a pulsed laser and an NIR camera synchronized with a rotatable sample stage for NIRF-CT imaging. The fluorescence lifetimes in microsecond-order of lanthanides were mapped on reconstructed cross-sectional and 3D images, via back-projection of two-dimensional projected images acquired from multiple angles at each time point showing fluorescence decay. A method to select slopes (the observed decay rates in time-gated imaging) used for the lifetime calculation, termed as the slope comparison method, was developed for the accurate calculation of each pixel, resulting in reduction of image acquisition time. Time-gated NIRF-CT provides a novel choice for multiplex 3D observation of deep tissues in biology. Full article

Development of nanotheranostic agents with near-infrared (NIR) absorption offers an effective tool for fighting malignant diseases. Lanthanide ion neodymium (Nd³⁺)-based nanomaterials, due to the maximum absorption at around 800 nm and unique optical properties, have caught great attention as potential agents for simultaneous cancer diagnosis and therapy. Herein, we employed an active nanoplatform based on gadolinium-ion-doped NdVO₄ nanoplates (NdVO₄:Gd³⁺ NPs) for multiple-imaging-assisted photothermal therapy. These NPs exhibited enhanced NIR absorption and excellent biocompatibility after being grafted with polydopamine (pDA) and bovine serum albumin (BSA) layers on their surface. Upon expose to an 808 nm laser, these resulting NPs were able to trigger hyperthermia rapidly and cause photo-destruction of cancer cells. In a xenograft tumor model, tumor growth was also significantly inhibited by these photothermal agents under NIR laser irradiation. Owing to the multicomponent nanostructures, we demonstrated these nanoagents as being novel contrast agents for in vivo magnetic resonance (MR) imaging, X-ray computed tomography (CT), photoacoustic (PA) imaging, and second biological window fluorescent imaging of tumor models. Thus, we believe that this new kind of nanotherapeutic will benefit the development of emerging nanosystems for biological imaging and cancer therapy. Full article

In terms of synergistic cancer therapy, biological nanomaterials with a second near-infrared (NIR-II) window response can greatly increase photothermal effects and photoacoustic imaging performance. Herein, we report a novel stimuli-responsive multifunctional drug-loading system which was constructed by integrating miniature gold nanorods (GNR) as the NIR-II photothermal nanorods and cyclic ternary aptamer (CTA) composition as a carrier for chemotherapy drugs. In this system, doxorubicin hydrochloride (DOX, a chemotherapy drug) binds to the G-C base pairs of the CTA, which exhibited a controlled release behavior based on the instability of G-C base pairs in the slightly acidic tumor microenvironment. Upon the 1064 nm (NIR-II biowindow) laser irradiation, the strong photothermal and promoted cargo release properties endow gold nanorods@CTA (GNR@CTA) nanoparticles displaying excellent synergistic anti-cancer effect. Moreover, the GNR@CTA of NIR also possesses thermal imaging and photoacoustic (PA) imaging properties due to the strong NIR region absorbance. This work enables to obtaining a stimuli-responsive “all-in-one” nanocarrier, which are promising candidate for bimodal imaging diagnosis and chemo-photothermal synergistic therapy. Full article