Generating single-cell gene expression profiles for high-resolution spatial transcriptomics based on cell boundary images.

In spatially resolved transcriptomics, Stereo-seq facilitates the analysis of large tissues at the single-cell level, offering subcellular resolution and centimeter-level field-of-view. Our previous work on StereoCell introduced a one-stop software using cell nuclei staining images and statistical methods to generate high-confidence single-cell spatial gene expression profiles for Stereo-seq data. With advancements allowing the acquisition of cell boundary information, such as cell membrane/wall staining images, we updated our software to a new version, STCellbin. Using cell nuclei staining images, STCellbin aligns cell membrane/wall staining images with spatial gene expression maps. Advanced cell segmentation ensures the detection of accurate cell boundaries, leading to more reliable single-cell spatial gene expression profiles. We verified that STCellbin can be applied to mouse liver (cell membranes) and Arabidopsis seed (cell walls) datasets, outperforming other methods. The improved capability of capturing single-cell gene expression profiles results in a deeper understanding of the contribution of single-cell phenotypes to tissue biology. Availability & Implementation: The source code of STCellbin is available at https://github.com/STOmics/STCellbin.

Identification of Time-Varying External Force Using Group Sparse Regularization and Redundant Dictionary.

How to accurately identify unknown time-varying external force from measured structural responses is an important engineering problem, which is critical for assessing the safety condition of the structure. In the context of a few available accelerometers, this paper proposes a novel time-varying external force identification method using group sparse regularization based on the prior knowledge in the redundant dictionary. Firstly, the relationship between time-varying external force and acceleration responses is established, and a redundant dictionary is designed to create a sparse expression of external force. Then, the relevance of atoms in the redundant dictionary is revealed, and this prior knowledge is used to determine the group structures of atoms. As a result, a force identification governing equation is formulated, and the group sparse regularization is reasonably introduced to ensure the accuracy of the identified results. The contribution of this paper is that the group structures of atoms are reasonably determined based on prior knowledge, and the complexity in the process for identifying external force from measured acceleration responses is reduced. Finally, the effectiveness of the proposed method is demonstrated by numerical simulations and an experimental structure. The illustrated results show that, compared with the force identification method based on the standard l1-norm regularization, the proposed method can further improve the identified accuracy of unknown external force and greatly enhance the computational efficiency for the force identification problem.

Effect of Ropivacaine-Loaded Magnetic Nanoparticles on Ankle Nerve Block in Rats.

AIM: Our study is to determine the influence of ropivacaine-loaded magnetic nanoparticles (MNP/Rop) on ankle nerve block in rats. MATERIALS AND METHODS: MNP/Rop was prepared and then injected intravenously into rats to evaluate its anesthetic effect on rat limbs. Mechanical pain thresholds paw withdrawal threshold (PWT) and paw withdrawal thermal latency (PWL) were employed for the assessment of ankle nerve block in rats. RESULTS: PWT increased from T1 to T4 in each group (P < 0.05). The intergroup comparison determined no distinct difference in the PWT value among the three series at T1 (P > 0.05); however, PWT values at T2-T4 were higher in nerve block control group (NBCG) and MNP/Rop group than in blank group (BG), and they remained slightly higher in MNP/Rop group than in NBCG. The intragroup comparison revealed that from T1 to T4, PWL in each group showed a rising trend. The PWL at T1 showed no evident difference among the three series (P > 0.05); however, PWL values at T2-T4 were higher in NBCG and MNP/Rop group than in BG, and they remained slightly higher in MNP/Rop group than in NBCG. In MNP/Rop group, both PWT and PWL increased with the increase of Fe3O4 load in MNP/Rop (P < 0.05), while PWT and PWL remained unchanged when the load was 2.189%; moreover, PWT and PWL elevated as Rop concentration increased in MNP/Rop (P < 0.05), while they kept unaltered under 40 µL 1% Rop. CONCLUSION: Intravenous injection of MNP/Rop into rats and inhalation of MNP into the ankle joint can effectively block ankle nerve conduction in rats.

[Processing FBG Sensing Signals with Exponent Modified Gaussian Curve Fitting Peak Detection Method].

The system based on Fiber Bragg Grating (FBG) sensor is used in various fields, because of its advantages of high detection accuracy, good repeatability and adaptability. While the FBG sensor is a wavelength modulation type sensor, so the outside parameter detection is the center wavelength of FBG detection. At the same time, the FBG center wavelength corresponding to the peak value of the FBG reflection spectrum. Therefore, the core of demodulation system is the demodulation of FBG reflection spectrum during peak-seeking, and the high-precision peak detecting algorithm is the key technology of the system demodulation. The current peak detecting algorithms has a precondition for peak detection on FBG reflective spectrum, that the FBG reflective spectrum was a standard Gaussian model. But FBG reflective spectrum is not a standard Gaussian spectrum owing to the practical manufacture process and the individual environment; actually, it is an asymmetrical Gaussian spectrum. The experiment would achieve a lower accuracy because of this asymmetric property during peak-seeking. Based on the defect of the existing algorithm, an Exponent Modified Gaussian (EMG) Curve Fitting peak detecting algorithm is proposed in this paper. In the proposed algorithm, the coarse location was first determined by three times judgments and it can remove the false peak and peak invalid at the same time. Based on this, as the center of the coarse localization point to reconstruct the spectrum, and using the integral to judge the peak bias; then according to different peak bias, it revised the peak by the prepared exponential modified function. Simulation results show that at normal temperature or under variable temperature conditions, by comparing with direct peak searching algorithm, Gaussian fitting algorithm and the algorithm proposed by literature, the error of EMG peak detection algorithm is the minimum and high peak detecting precision. The algorithm proposed in this paper considers the FBG reflection spectrum characteristic of asymmetric effect. From its spectrum character, the EMG algorithm solves the problem of the limits of traditional peak detecting algorithm, meanwhile also guarantees a high-precision peak search results.