Spatial omics technologies decipher functional components of complex organs at cellular and subcellular resolutions. We introduce Spatial Graph Fourier Transform (SpaGFT) and apply graph signal processing to a wide range of spatial omics profiling platforms to generate their interpretable representations. This representation supports spatially variable gene identification and improves gene expression imputation, outperforming existing tools in analyzing human and mouse spatial transcriptomics data. SpaGFT can identify immunological regions for B cell maturation in human lymph nodes Visium data and characterize variations in secondary follicles using in-house human tonsil CODEX data. Furthermore, it can be integrated seamlessly into other machine learning frameworks, enhancing accuracy in spatial domain identification, cell type annotation, and subcellular feature inference by up to 40%. Notably, SpaGFT detects rare subcellular organelles, such as Cajal bodies and Set1/COMPASS complexes, in high-resolution spatial proteomics data. This approach provides an explainable graph representation method for exploring tissue biology and function.

Objective. Ultrafast ultrasound imaging using planar or diverging waves for transmission is a promising approach for efficient 3D imaging with matrix arrays. This technique has advantages for B-mode imaging and advanced techniques, such as 3D vector flow imaging (VFI). The computation load of the cross-beam technique is associated with the number of transmit anglesmand receive anglesn. The full velocity vector is obtained using the least square fashion. However, the beamforming is repeatedm × ntimes using a conventional time-domain delay-and-sum (DAS) beamformer. In the 3D case, the collection and processing of data from different beams increase the amount of data that must be processed, requiring more storage capacity and processing power. Furthermore, the large computation complexity of DAS is another major concern. These challenges translate into longer computational times, increased complexity in data processing, and difficulty in real-time applications.Approach. In response to this issue, this study proposes a novel Fourier domain beamformer for 3D plane wave imaging, which significantly increases the computational speed. Additionally, a selective compounding strategy is proposed for VFI, which reduces the beamforming process fromm × ntom(wheremandnrepresent the number of transmission and reception, respectively), effectively shortening the processing time. The underlying principle is to decompose the receive wavefront into a series of plane waves with different slant angles. Each slant angle can produce a sub-volume for coherent or selective compounding. This method does not rely on the assumption that the plane wave is perfect and the results show that our proposed beamformer is better than DAS in terms of resolution and image contrast. In the case of velocity estimation, for the Fourier-based method, only Tx angles are assigned in the beamformer and the selective compounding method produces the final image with a specialized Rx angle.Main results. Simulation studies andin vitroexperiments confirm the efficacy of this new method. The proposed beamformer shows improved resolution and contrast performance compared to the DAS beamformer for B-mode imaging, with a suppressed sidelobe level. Furthermore, the proposed technique outperforms the conventional DAS method, as evidenced by lower mean bias and standard deviation in velocity estimation for VFI. Notably, the computation time has been shortened by 40 times, thus promoting the real-time application of this technique. The efficacy of this new method is verified through simulation studies andin vitroexperiments and evaluated by mean bias and standard deviation. Thein vitroresults reveal a better velocity estimation: the mean bias is 2.3%, 3.4%, and 5.0% forvx,vy, andvz, respectively. The mean standard deviation is 1.8%, 1.7%, and 3.4%. With DAS, the evaluated mean bias is 9.8%, 4.6%, and 6.7% and the measured mean standard deviation is 7.5%, 2.5%, and 3.9%.Significance. In this work, we propose a novel Fourier-based method for both B-mode imaging and functional VFI. The new beamformer is shown to produce better image quality and improved velocity estimation. Moreover, the new VFI computation time is reduced by 40 times compared to conventional methods. This new method may pave a new way for real-time 3D VFI applications.

Over the past few decades, early osteoporosis detection using ultrasonic bone quality evaluation has gained prominence. Specifically, various studies focused on axial transmission using ultrasonic guided waves and have highlighted this technique\'s sensitivity to intrinsic properties of long cortical bones. This work aims to demonstrate the potential of low-frequency ultrasonic guided waves to infer the properties of the bone inside which they are propagating. A proprietary ultrasonic transducer, tailored to transmit ultrasonic guided waves under 500 kHz, was used for the data collection. The gathered data underwent two-dimensional fast Fourier transform processing to extract experimental dispersion curves. The proposed inversion scheme compares experimental dispersion curves with simulated dispersion curves calculated through the semi-analytical iso-geometric analysis (SAIGA) method. The numerical model integrates a bone phantom plate coupled with a soft tissue layer on its top surface, mimicking the experimental bone phantom plates. Subsequently, the mechanical properties of the bone phantom plates were estimated by reducing the misfit between the experimental and simulated dispersion curves. This inversion leaned heavily on the dispersive trajectories and amplitudes of ultrasonic guided wave modes. Results indicate a marginal discrepancy under 5% between the mechanical properties ascertained using the SAIGA-based inversion and those measured using bulk wave pulse-echo measurements.

The brewing-dependent molecular diversity, properties, and formation mechanism of Moutai (a typical sauce-flavor Baijiu) base Baijiu, were explored using FT-ICR MS combined with various visualization methods. Seven-round Moutai base Baijiu exhibited significant diversity and heterogeneity, containing more unsaturated/saturated reduced molecules. The increased brewing round increased the molecular unsaturation/aromaticity and enhanced the transformation between saturated/oxidized and unsaturated/reduced molecules. Moreover, lignin-/aliphatic-/peptide-/lipid-like molecules dominated the molecular characteristics of Moutai base Baijiu. The basic and acidic components contained more reduced carbohydrate-/lipid-like molecules and oxidized tannin-like/condensed aromatic molecules, respectively, contributing to the molecular stability and diversity, respectively. More unique lipid-like and lignin-like molecules newly formed in the early and late brewing rounds, respectively, and the increased brewing shifted the chemical reaction from a single dominant to a multi-dimensional balance. More unique N-containing molecules (>450 Da) significantly contributed the specific brewing characteristics. These new findings help to understand the molecular-level formation mechanism of Moutai base Baijiu.

Brain hypoperfusion is associated with cognitive impairment. Higher cerebrovascular impedance modulus (Z) may contribute to brain hypoperfusion. We tested hypotheses that patients with amnestic mild cognitive impairment (aMCI) (i.e., those who have high risk of developing Alzheimer\'s disease) have higher Z than age-matched cognitively normal individuals, and that high Z is correlated with brain hypoperfusion. Fifty-eight patients with aMCI (67±7 years) and 25 cognitively normal subjects (CN, 65±6 years) underwent simultaneous measurements of carotid artery pressure (CAP, via applanation tonometry) and middle cerebral arterial blood velocity (CBV, via transcranial Doppler). Z was quantified using cross-spectral and transfer function analyses between dynamic changes in CBV and CAP. Patients with aMCI exhibited higher Z than NC (1.18±0.34 vs. 1.01±0.35 mmHg/cm/s, P=0.044) in the frequency range from 0.78 to 4.29 Hz. The averaged Z in the frequency range (0.78-3.13 Hz) of high coherence (>0.9) was inversely correlated with total cerebral blood flow measured with 2D Doppler ultrasonography normalized by the brain tissue mass (via structural MRI) across both patients with aMCI and NC (r=-0.311, P=0.007), and in patients with aMCI alone (r=-0.306, P=0.007). Our findings suggest that patients with aMCI have higher cerebrovascular impedance than cognitively normal older adults and that increased cerebrovascular impedance is associated with brain hypoperfusion.

The accurate prediction of chlorophyll-a (chl-a) concentration in coastal waters is essential to coastal economies and ecosystems as it serves as the key indicator of harmful algal blooms. Although powerful machine learning methods have made strides in forecasting chl-a concentrations, there remains a gap in effectively modeling the dynamic temporal patterns and dealing with data noise and unreliability. To wiggle out of quagmires, we introduce an innovative deep learning prediction model (termed ChloroFormer) by integrating Transformer networks with Fourier analysis within a decomposition architecture, utilizing coastal in-situ data from two distinct study areas. Our proposed model exhibits superior capabilities in capturing both short-term and middle-term dependency patterns in chl-a concentrations, surpassing the performance of six other deep learning models in multistep-ahead predictive accuracy. Particularly in scenarios involving extreme and frequent blooms, our proposed model shows exceptional predictive performance, especially in accurately forecasting peak chl-a concentrations. Further validation through Kolmogorov-Smirnov tests attests that our model not only replicates the actual dynamics of chl-a concentrations but also preserves the distribution of observation data, showcasing its robustness and reliability. The presented deep learning model addresses the critical need for accurate prediction on chl-a concentrations, facilitating the exploration of marine observations with complex dynamic temporal patterns, thereby supporting marine conservation and policy-making in coastal areas.

BACKGROUND: During a robot-assisted minimally invasive surgery, hand tremors in a surgeon\'s manipulation of the master manipulator can cause vibrations of the slave surgical instruments.
METHODS: This letter addresses this problem by proposing an improved Enhanced Band-Limited Multiple Linear Fourier Combiner (E-BMFLC) algorithm for filtering the physiological tremor signals of a surgeon\'s hand. The proposed method uses the amplitude of the input signal to adapt the learning rate and a dense division of the combiner bands for the higher amplitude bands of the tremor signals.
RESULTS: By using the proposed improved E-BMFLC algorithm, the compensation accuracy can be improved by 4.5%-8.9%, as well as a spatial position error of less than 1 mm.
CONCLUSIONS: The results show that among all filtering methods, the improved E-BMFLC filtering method has the highest number of successful experiments and the lowest experimental time.

In electrokinetic remediation (EKR), the sedimentary dissolved organic matter (DOM) could impede remediation by scavenging reactive species and generating unintended byproducts. Yet its transformation and mechanisms remained largely unknown. This study conducted molecular-level characterization of the water-extractable DOM (WEOM) in EKR using negative-ion electrospray ionization coupled to 21 tesla Fourier transform ion cyclotron resonance mass spectrometry (21 T FT-ICR MS). The results suggested that ∼55 % of the ∼7,000 WEOM compounds identified were reactive, and EKR lowered their diversity, molecular weight distribution, and double-bond equivalent (DBE) through a combination of electrochemical and microbial redox reactions. Heteroatom-containing WEOM (CHON and CHOS) were abundant (∼ 35% of the total WEOM), with CHOS generally being more reactive than CHON. Low electric potential (1 V/cm) promoted the growth of dealkylation and desulfurization bacteria, and led to anodic CO2 mineralization, anodic cleavage of -SO and -SO3, and cathodic cleavage of -SH2; high electric potential (2 V/cm) only enriched desulfurization bacteria, and differently, led to anodic oxygenation and cathodic hydrogenation of unsaturated and phenolic compounds, in addition to cathodic cleavage of -SH2. The long-term impact of these changes on soil quality and nitrogen-sulfur-carbon flux may be need to studied to identify unknown risks and new applications of EKR.

In this study, we proposed a multiplexed color illumination strategy to improve the data acquisition efficiency of Fourier ptychography microscopy (FPM). Instead of sequentially lighting up one single channel LED, our method turns on multiple white light LEDs for each image acquisition via a color camera. Thus, each raw image contains multiplexed spectral information. An FPM prototype was developed, which was equipped with a 4×/0.13 NA objective lens to achieve a spatial resolution equivalent to that of a 20×/0.4 NA objective lens. Both two- and four-LED illumination patterns were designed and applied during the experiments. A USAF 1951 resolution target was first imaged under these illumination conditions, based on which MTF curves were generated to assess the corresponding imaging performance. Next, H&E tissue samples and analyzable metaphase chromosome cells were used to evaluate the clinical utility of our strategy. The results show that the single and multiplexed (two- or four-LED) illumination results achieved comparable imaging performance on all the three channels of the MTF curves. Meanwhile, the reconstructed tissue or cell images successfully retain the definition of cell nuclei and cytoplasm and can better preserve the cell edges as compared to the results from the conventional microscopes. This study initially validates the feasibility of multiplexed color illumination for the future development of high-throughput FPM scanning systems.

Reconstruction maps of cryo-electron microscopy (cryo-EM) exhibit distortion when the cryo-EM dataset is incomplete, usually caused by unevenly distributed orientations. Prior efforts had been attempted to address this preferred orientation problem using tilt-collection strategy and modifications to grids or to air-water interfaces. However, these approaches often require time-consuming experiments, and the effect was always protein dependent. Here, we developed a procedure containing removing misaligned particles and an iterative reconstruction method based on signal-to-noise ratio of Fourier component to correct this distortion by recovering missing data using a purely computational algorithm. This procedure called signal-to-noise ratio iterative reconstruction method (SIRM) was applied on incomplete datasets of various proteins to fix distortion in cryo-EM maps and to a more isotropic resolution. In addition, SIRM provides a better reference map for further reconstruction refinements, resulting in an improved alignment, which ultimately improves map quality and benefits model building.