Systematic dissection of sequence features affecting binding specificity of a pioneer factor reveals binding synergy between FOXA1 and AP-1.

Despite the unique ability of pioneer factors (PFs) to target nucleosomal sites in closed chromatin, they only bind a small fraction of their genomic motifs. The underlying mechanism of this selectivity is not well understood. Here, we design a high-throughput assay called chromatin immunoprecipitation with integrated synthetic oligonucleotides (ChIP-ISO) to systematically dissect sequence features affecting the binding specificity of a classic PF, FOXA1, in human A549 cells. Combining ChIP-ISO with in vitro and neural network analyses, we find that (1) FOXA1 binding is strongly affected by co-binding transcription factors (TFs) AP-1 and CEBPB; (2) FOXA1 and AP-1 show binding cooperativity in vitro; (3) FOXA1's binding is determined more by local sequences than chromatin context, including eu-/heterochromatin; and (4) AP-1 is partially responsible for differential binding of FOXA1 in different cell types. Our study presents a framework for elucidating genetic rules underlying PF binding specificity and reveals a mechanism for context-specific regulation of its binding.

Size-based expectation maximization for characterizing nucleosome positions and subtypes.

Genome-wide nucleosome profiles are predominantly characterized using MNase-seq, which involves extensive MNase digestion and size selection to enrich for mono-nucleosome-sized fragments. Most available MNase-seq analysis packages assume that nucleosomes uniformly protect 147-bp DNA fragments. However, some nucleosomes with atypical histone or chemical compositions protect shorter lengths of DNA. The rigid assumptions imposed by current nucleosome analysis packages potentially prevent investigators from understanding the regulatory roles played by atypical nucleosomes. To enable the characterization of different nucleosome types from MNase-seq data, we introduce the Size-based Expectation Maximization (SEM) nucleosome-calling package. SEM employs a hierarchical Gaussian mixture model to estimate nucleosome positions and subtypes. Nucleosome subtypes are automatically identified based on the distribution of protected DNA fragments. Benchmark analysis indicates that SEM is on par with existing packages in terms of standard nucleosome-calling accuracy metrics, while uniquely providing the ability to characterize nucleosome subtype identities. Applying SEM to a low-dose MNase-H2B-ChIP-seq dataset from mouse embryonic stem cells, we identified three nucleosome types: short-fragment nucleosomes; canonical nucleosomes; and di-nucleosomes. Short-fragment nucleosomes can be divided further into two subtypes based on their chromatin accessibility. Interestingly, short-fragment nucleosomes in accessible regions exhibit high MNase sensitivity and are enriched at transcription start sites (TSSs) and CTCF peaks, similar to previously reported 'fragile nucleosomes'. These SEM-defined accessible short-fragment nucleosomes are found not just in promoters, but also in distal regulatory regions. Additional analyses reveal their colocalization with the chromatin remodelers Chd6, Chd8, and Ep400. In summary, SEM provides an effective platform for exploration of nonstandard nucleosome subtypes.

Chemical Nose Strategy with Metabolic Labeling and "Antibiotic-Responsive Spectrum" Enables Accurate and Rapid Pathogen Identification.

The worldwide antimicrobial resistance (AMR) dilemma urgently requires rapid and accurate pathogen phenotype discrimination and antibiotic resistance identification. The conventional protocols are either time-consuming or depend on expensive instrumentations. Herein, we demonstrate a metabolic-labeling-assisted chemical nose strategy for phenotyping classification and antibiotic resistance identification of pathogens based on the "antibiotic-responsive spectrum" of different pathogens. d-Amino acids with click handles were metabolically incorporated into the cell wall of pathogens for further clicking with dibenzocyclooctyne-functionalized upconversion nanoparticles (DBCO-UCNPs) in the presence/absence of six types of antibiotics, which generates seven-channel sensing responses. With the assistance of machine learning algorithms, eight types of pathogens, including three types of antibiotic-resistant bacteria, can be well classified and discriminated in terms of microbial taxonomies, Gram phenotypes, and antibiotic resistance. The present metabolic-labeling-assisted strategy exhibits good anti-interference capability and improved discrimination ability rooted in the unique sensing mechanism. Sensitive identification of pathogens with 100% accuracy from artificial urinary tract infection samples at a concentration as low as 105 CFU/mL was achieved. Pathogens outside of the training set can also be discriminated well. This clearly demonstrated the potential of the present strategy in the identification of unknown pathogens in clinical samples.

The lncRNA LINC01605 promotes the progression of pancreatic ductal adenocarcinoma by activating the mTOR signaling pathway.

BACKGROUND: This study investigated the molecular mechanism of long intergenic non-protein coding RNA 1605 (LINC01605) in the process of tumor growth and liver metastasis of pancreatic ductal adenocarcinoma (PDAC). METHODS: LINC01605 was filtered out with specificity through TCGA datasets (related to DFS) and our RNA-sequencing data of PDAC tissue samples from Renji Hospital. The expression level and clinical relevance of LINC01605 were then verified in clinical cohorts and samples by immunohistochemical staining assay and survival analysis. Loss- and gain-of-function experiments were performed to estimate the regulatory effects of LINC01605 in vitro. RNA-seq of LINC01605-knockdown PDAC cells and subsequent inhibitor-based cellular function, western blotting, immunofluorescence and rescue experiments were conducted to explore the mechanisms by which LINC01605 regulates the behaviors of PDAC tumor cells. Subcutaneous xenograft models and intrasplenic liver metastasis models were employed to study its role in PDAC tumor growth and liver metastasis in vivo. RESULTS: LINC01605 expression is upregulated in both PDAC primary tumor and liver metastasis tissues and correlates with poor clinical prognosis. Loss and gain of function experiments in cells demonstrated that LINC01605 promotes the proliferation and migration of PDAC cells in vitro. In subsequent verification experiments, we found that LINC01605 contributes to PDAC progression through cholesterol metabolism regulation in a LIN28B-interacting manner by activating the mTOR signaling pathway. Furthermore, the animal models showed that LINC01605 facilitates the proliferation and metastatic invasion of PDAC cells in vivo. CONCLUSIONS: Our results indicate that the upregulated lncRNA LINC01605 promotes PDAC tumor cell proliferation and migration by regulating cholesterol metabolism via activation of the mTOR signaling pathway in a LIN28B-interacting manner. These findings provide new insight into the role of LINC01605 in PDAC tumor growth and liver metastasis as well as its value for clinical approaches as a metabolic therapeutic target in PDAC.

Cu(II)-Loaded Polydopamine-Coated Urchin-like Titanate Microspheres as a High-Performance IMAC Adsorbent for Hemoglobin Separation.

Immobilized metal ion affinity chromatography (IMAC) adsorbents generally have excellent affinity for histidine-rich proteins. However, the leaching of metal ions from the adsorbent usually affects its adsorption performance, which greatly affects the reusable performance of the adsorbent, resulting in many limitations in practical applications. Herein, a novel IMAC adsorbent, i.e., Cu(II)-loaded polydopamine-coated urchin-like titanate microspheres (Cu-PDA-UTMS), was prepared via metal coordination to make Cu ions uniformly decorate polydopamine-coated titanate microspheres. The as-synthesized microspheres exhibit an urchin-like structure, providing more binding sites for hemoglobin. Cu-PDA-UTMS exhibit favorable selectivity for hemoglobin adsorption and have a desirable adsorption capacity towards hemoglobin up to 2704.6 mg g-1. Using 0.1% CTAB as eluent, the adsorbed hemoglobin was easily eluted with a recovery rate of 86.8%. In addition, Cu-PDA-UTMS shows good reusability up to six cycles. In the end, the adsorption properties by Cu-PDA-UTMS towards hemoglobin from human blood samples were analyzed by SDS-PAGE. The results showed that Cu-PDA-UTMS are a high-performance IMAC adsorbent for hemoglobin separation, which provides a new method for the effective separation and purification of hemoglobin from complex biological samples.

Analysis of cuproptosis-related lncRNA signature for predicting prognosis and tumor immune microenvironment in pancreatic cancer.

Pancreatic cancer (PC) is a highly malignant digestive tract tumor, with a dismal 5-year survival rate. Recently, cuproptosis was found to be copper-dependent cell death. This work aims to establish a cuproptosis-related lncRNA signature which could predict the prognosis of PC patients and help clinical decision-making. Firstly, cuproptosis-related lncRNAs were identified in the TCGA-PAAD database. Next, a cuproptosis-related lncRNA signature based on five lncRNAs was established. Besides, the ICGC cohort and our samples from 30 PC patients served as external validation groups to verify the predictive power of the risk signature. Then, the expression of CASC8 was verified in PC samples, scRNA-seq dataset CRA001160, and PC cell lines. The correlation between CASC8 and cuproptosis-related genes was validated by Real-Time PCR. Additionally, the roles of CASC8 in PC progression and immune microenvironment characterization were explored by loss-of-function assay. As showed in the results, the prognosis of patients with higher risk scores was prominently worse than that with lower risk scores. Real-Time PCR and single cell analysis suggested that CASC8 was highly expressed in pancreatic cancer and related to cuproptosis. Additionally, gene inhibition of CASC8 impacted the proliferation, apoptosis and migration of PC cells. Furthermore, CASC8 was demonstrated to impact the expression of CD274 and several chemokines, and serve as a key indicator in tumor immune microenvironment characterization. In conclusion, the cuproptosis-related lncRNA signature could provide valuable indications for the prognosis of PC patients, and CASC8 was a candidate biomarker for not only predicting the progression of PC patients but also their antitumor immune responses.

Boosting Photo-Electro-Fenton Process Via Atomically Dispersed Iron Sites on Graphdiyne for InVitro Hydrogen Peroxide Detection.

Hydrogen peroxide (H2 O2 ) is essential in oxidative stress and signal regulation of organs of animal body. Realizing in vitro quantification of H2 O2 released from organs is significant, but faces challenges due to short lifetime of H2 O2 and complex bio-environment. Herein, rationally designed and constructed a photoelectrochemical (PEC) sensor for in vitro sensing of H2 O2 , in which atomically dispersed iron active sites (Hemin) modified graphdiyne (Fe-GDY) serves as photoelectrode and catalyzes photo-electro-Fenton process. Sensitivity of Fe-GDY electrode is enhanced 8 times under illumination compared with dark condition. The PEC H2 O2 sensor under illumination delivers a wide linear range from 0.1 to 48 160 µm and a low detection limit of 33 nm, while demonstrating excellent selectivity and stability. The high performance of Fe-GDY is attributed to, first, energy levels matching of GDY and Hemin that effectively promotes the injection of photo-generated electrons from GDY to Fe3+ for reduced Fe2+ , which facilitates the Fe3+ /Fe2+ cycle. Second, the Fe2+ actively catalyzes H2 O2 to OH- through the Fenton process, thereby improving the sensitivity. The PEC sensor demonstrates in vitro quantification of H2 O2 released from different organs, providing a promising approach for molecular sensing and disease diagnosis in organ levels.

Multi-Scale Feature Fusion of Covariance Pooling Networks for Fine-Grained Visual Recognition.

Multi-scale feature fusion techniques and covariance pooling have been shown to have positive implications for completing computer vision tasks, including fine-grained image classification. However, existing algorithms that use multi-scale feature fusion techniques for fine-grained classification tend to consider only the first-order information of the features, failing to capture more discriminative features. Likewise, existing fine-grained classification algorithms using covariance pooling tend to focus only on the correlation between feature channels without considering how to better capture the global and local features of the image. Therefore, this paper proposes a multi-scale covariance pooling network (MSCPN) that can capture and better fuse features at different scales to generate more representative features. Experimental results on the CUB200 and MIT indoor67 datasets achieve state-of-the-art performance (CUB200: 94.31% and MIT indoor67: 92.11%).

Research on a fiber Bragg grating hydrostatic level based on elliptical ring for settlement deformation monitoring.

The hydrostatic leveling system based on the connecting pipe principle has important application value in the field of settlement monitoring. In this paper, a novel fiber Bragg grating (FBG) hydrostatic level based on elliptical ring is proposed. In this study, the vertical and lateral deformations of elliptical ring under concentrated force is analyzed using force method and Mohr integral. Thereby, the deformation-coordination equation of the elliptical ring and the diaphragm is constructed. The temperature self-compensation model for the elliptical ring is established from the three levels of material, structure, and device. A complete set of theories and methods for the designed FBG hydrostatic level is proposed. Furthermore, the tests of the sensitivity, resolution, and temperature self-compensation for the encapsulated sensors are carried out by multi-point loading experiment. The experimental results show that in the range of 0∼100 mm, the sensitivity of the sensor is close to the theoretical analysis, which is about 12 pm/mm. The effective resolution can reach 0.025∼0.05 mm, with the sensitivity coefficient to temperature as low as only 1.46 pm/°C.

Urine stem cells are equipped to provide B cell survival signals.

The interplay between mesenchymal stem cells (MSCs) and immune cells has been studied for MSCs isolated from different tissues. However, the immunomodulatory capacity of urine stem cells (USCs) has not been adequately researched. The present study reports on the effect of USCs on peripheral blood lymphocytes. USCs were isolated and characterized before coculture with resting and with anti-CD3/CD28 bead stimulated lymphocytes. Similarly to bone marrow mesenchymal stem cells (BM-MSCs), USCs inhibited the proliferation of activated T lymphocytes and induced their apoptosis. However, they also induced strong activation, proliferation, and cytokine and antibody production by B lymphocytes. Molecular phenotype and supernatant analysis revealed that USCs secrete a range of cytokines and effector molecules, known to play a central role in B cell biology. These included B cell-activating factor (BAFF), interleukin 6 (IL-6) and CD40L. These findings raise the possibility of an unrecognized active role for kidney stem cells in modulating local immune cells.

Domain Adaptive Hand Pose Estimation Based on Self-Looping Adversarial Training Strategy.

In recent years, with the development of deep learning methods, hand pose estimation based on monocular RGB images has made great progress. However, insufficient labeled training datasets remain an important bottleneck for hand pose estimation. Because synthetic datasets can acquire a large number of images with precise annotations, existing methods address this problem by using data from easily accessible synthetic datasets. Domain adaptation is a method for transferring knowledge from a labeled source domain to an unlabeled target domain. However, many domain adaptation methods fail to achieve good results in realistic datasets due to the domain gap. In this paper, we design a self-looping adversarial training strategy to reduce the domain gap between synthetic and realistic domains. Specifically, we use a multi-branch structure. Then, a new adversarial training strategy we designed for the regression task is introduced to reduce the size of the output space. As such, our model can reduce the domain gap and thus improve the prediction performance of the model. The experiments using H3D and STB datasets show that our method significantly outperforms state-of-the-art domain adaptive methods.

WPL-Based Constraint for 3D Human Pose Estimation from a Single Depth Image.

Three-dimensional human pose estimation from depth maps is a fast-growing research area in computer vision. The distal joints of the human body are more flexible than the proximal joints, making it more difficult to estimate the distal joints. However, most existing methods ignore the difference between the distal joints and proximal joints. Moreover, the distal joint can be constrained by the proximal joint on the same kinematic chain. In our work, we model the human skeleton as the tree structure called the human-tree. Then, motivated by the WPL (weighted path length) in the data structure, we propose a WPL-based loss function to constrain the distal joints with the proximal joints in a global-to-local manner. Extensive experiments on benchmarks demonstrate that our method can effectively improve the performance of the distal joints.

Vision-Sensor-Assisted Probabilistic Localization Method for Indoor Environment.

Among the numerous indoor localization methods, Light-Detection-and-Ranging (LiDAR)-based probabilistic algorithms have been extensively applied to indoor localization due to their real-time performance and high accuracy. Nevertheless, these methods are challenged in symmetrical environments when tackling global localization and the robot kidnapping problem. In this paper, a novel hybrid method that combines visual and probabilistic localization results is proposed. Augmented Monte Carlo Localization (AMCL) is improved for position tracking continually. LiDAR-based measurements' uncertainty is evaluated to incorporate discrete visual-based results; therefore, a better diversity of the particle can be maintained. The robot kidnapping problem can be detected and solved by preventing premature convergence of the particle filter. Extensive experiments were implemented to validate the robustness and accuracy performance. Meanwhile, the localization error was reduced from 30 mm to 9 mm during a 600 m tour.

Polyamine Oxidase Triggers H2O2-Mediated Spermidine Improved Oxidative Stress Tolerance of Tomato Seedlings Subjected to Saline-Alkaline Stress.

Saline-alkaline stress is one of several major abiotic stresses in crop production. Exogenous spermidine (Spd) can effectively increase tomato saline-alkaline stress resistance by relieving membrane lipid peroxidation damage. However, the mechanism through which exogenous Spd pre-treatment triggers the tomato antioxidant system to resist saline-alkaline stress remains unclear. Whether H2O2 and polyamine oxidase (PAO) are involved in Spd-induced tomato saline-alkaline stress tolerance needs to be determined. Here, we investigated the role of PAO and H2O2 in exogenous Spd-induced tolerance of tomato to saline-alkaline stress. Results showed that Spd application increased the expression and activities of superoxide dismutase (SOD), catalase (CAT), ascorbate peroxidase (APX), glutathione reductase (GR), and the ratio of reduced ascorbate (AsA) and glutathione (GSH) contents under saline-alkaline stress condition. Exogenous Spd treatment triggered endogenous H2O2 levels, SlPAO4 gene expression, as well as PAO activity under normal conditions. Inhibiting endogenous PAO activity by 1,8-diaminooctane (1,8-DO, an inhibitor of polyamine oxidase) significantly reduced H2O2 levels in the later stage. Moreover, inhibiting endogenous PAO or silencing the SlPAO4 gene increased the peroxidation damage of tomato leaves under saline-alkaline stress. These findings indicated that exogenous Spd treatment stimulated SlPAO4 gene expression and increased PAO activity, which mediated the elevation of H2O2 level under normal conditions. Consequently, the downstream antioxidant system was activated to eliminate excessive ROS accumulation and relieve membrane lipid peroxidation damage and growth inhibition under saline-alkaline stress. In conclusion, PAO triggered H2O2-mediated Spd-induced increase in the tolerance of tomato to saline-alkaline stress.

Revolution of a trapped particle in counter-propagating dual-beam optical tweezers under low pressure.

We presented faster and more accurate simulations and experiments describing the revolution of a suspended particle in optical tweezers under a low pressure. Instead of the state-of-the-art offline method of pinhole alignment, we proposed an in situ method of revolution suppression by adjusting the laser beam while observing the power spectral density and time-domain plot of the particle centroid displacement. The experimental results under different air pressures show that our method is more effective at low pressures. We observed that "revolution occurs when radial alignment error is below the threshold" and uncovered the mechanism behind this phenomenon. The rapidly growing Q value of the revolution indicates a high-precision resonance measurement method under lower air pressure compared with random translation measurements.

Research on Joint-Angle Prediction Based on Artificial Neural Network for Above-Knee Amputees.

In the current study, our research group proposed an asymmetric lower extremity exoskeleton to enable above-knee amputees to walk with a load. Due to the absence of shank and foot, the knee and ankle joint at the amputation side of the exoskeleton lack tracking targets, so it is difficult to realize the function of assisted walking when going up and downstairs. Currently, the use of lower-limb electromyography to predict the angles of lower limb joints has achieved remarkable results. However, the prediction effect was poor when only using electromyography from the thigh. Therefore, this paper introduces hip-angle and plantar pressure signals for improving prediction effect and puts forward a joint prediction method of knee- and ankle-joint angles by electromyography of the thigh, hip-joint angle, and plantar pressure signals. The generalized regression neural network optimized by the golden section method is used to predict the joint angles. Finally, the parameters (the maximum error, the Root-Mean-Square error (RMSE), and correlation coefficient (γ)) were calculated to verify the feasibility of the prediction method.

A Superfast Super-Resolution Method for Radar Forward-Looking Imaging.

The super-resolution method has been widely used for improving azimuth resolution for radar forward-looking imaging. Typically, it can be achieved by solving an undifferentiable L1 regularization problem. The split Bregman algorithm (SBA) is a great tool for solving this undifferentiable problem. However, its real-time imaging ability is limited to matrix inversion and iterations. Although previous studies have used the special structure of the coefficient matrix to reduce the computational complexity of each iteration, the real-time performance is still limited due to the need for hundreds of iterations. In this paper, a superfast SBA (SFSBA) is proposed to overcome this shortcoming. Firstly, the super-resolution problem is transmitted into an L1 regularization problem in the framework of regularization. Then, the proposed SFSBA is used to solve the nondifferentiable L1 regularization problem. Different from the traditional SBA, the proposed SFSBA utilizes the low displacement rank features of Toplitz matrix, along with the Gohberg-Semencul (GS) representation to realize fast inversion of the coefficient matrix, reducing the computational complexity of each iteration from O(N3) to O(N2). It uses a two-order vector extrapolation strategy to reduce the number of iterations. The convergence speed is increased by about 8 times. Finally, the simulation and real data processing results demonstrate that the proposed SFSBA can effectively improve the azimuth resolution of radar forward-looking imaging, and its performance is only slightly lower compared to traditional SBA. The hardware test shows that the computational efficiency of the proposed SFSBA is much higher than that of other traditional super-resolution methods, which would meet the real-time requirements in practice.

Intercellular Bridge Mediates Ca2+ Signals between Micropatterned Cells via IP3 and Ca2+ Diffusion.

Intercellular bridges are plasma continuities formed at the end of the cytokinesis process that facilitate intercellular mass transport between the two daughter cells. However, it remains largely unknown how the intercellular bridge mediates Ca2+ communication between postmitotic cells. In this work, we utilize BV-2 microglial cells planted on dumbbell-shaped micropatterned assemblies to resolve spatiotemporal characteristics of Ca2+ signal transfer over the intercellular bridges. With the use of such micropatterns, considerably longer and more regular intercellular bridges can be obtained than in conventional cell cultures. The initial Ca2+ signal is evoked by mechanical stimulation of one of the daughter cells. A considerable time delay is observed between the arrivals of passive Ca2+ diffusion and endogenous Ca2+ response in the intercellular-bridge-connected cell, indicating two different pathways of the Ca2+ communication. Extracellular Ca2+ and the paracrine pathway have practically no effect on the endogenous Ca2+ response, demonstrated by application of Ca2+-free medium, exogenous ATP, and P2Y13 receptor antagonist. In contrast, the endoplasmic reticulum Ca2+-ATPase inhibitor thapsigargin and inositol trisphosphate (IP3) receptor blocker 2-aminoethyl diphenylborate significantly inhibit the endogenous Ca2+ increase, which signifies involvement of IP3-sensitive calcium store release. Notably, passive Ca2+ diffusion into the connected cell can clearly be detected when IP3-sensitive calcium store release is abolished by 2-aminoethyl diphenylborate. Those observations prove that both passive Ca2+ diffusion and IP3-mediated endogenous Ca2+ response contribute to the Ca2+ increase in intercellular-bridge-connected cells. Moreover, a simulation model agreed well with the experimental observations.

Mercury speciation based on mercury-stimulated peroxidase mimetic activity of gold nanoparticles.

Mercury speciation is of significant importance in environmental and biological analysis because its toxicity and metabolic behavior in the human body differ among species. Nanomaterial-assisted optical sensors are widely used for mercury ion detection but rarely applied in mercury speciation analysis. In this work, we develop a novel colorimetric sensing strategy for mercury speciation based on mercury-stimulated peroxidase mimetic activity of gold nanoparticles with the assistance of different reductants. In the presence of a weak reductant, only inorganic mercury can be reduced to Hg0, whereas both inorganic mercury and organic mercury can be reduced to Hg0 in the presence of a strong reductant. Due to the high affinity between Hg and Au, Hg0 deposits on the AuNP surface in the form of a Au-Hg amalgam, leading to a remarkable enhancement of peroxidase mimetic activity of gold nanoparticles. On the basis of this effect, inorganic mercury and total mercury can be detected by using 3,3',5,5'-tetramethylbenzidine (TMB) as the substrate. The limits of detection for inorganic mercury and total mercury are 1.9 and 0.9 nM within 5-100 nM, respectively. The selectivity of this sensing system is high due to the specificity of Au-Hg interaction. Its practical applications are further demonstrated by organic mercury analysis in a fish sample and mercury speciation in a human hair sample.

Displacement Detection Decoupling in Counter-Propagating Dual-Beams Optical Tweezers with Large-Sized Particle.

As a kind of ultra-sensitive acceleration sensing platform, optical tweezers show a minimum measurable value inversely proportional to the square of the diameter of the levitated spherical particle. However, with increasing diameter, the coupling of the displacement measurement between the axes becomes noticeable. This paper analyzes the source of coupling in a forward-scattering far-field detection regime and proposes a novel method of suppression. We theoretically and experimentally demonstrated that when three variable irises are added into the detection optics without changing other parts of optical structures, the decoupling of triaxial displacement signals mixed with each other show significant improvement. A coupling detection ratio reduction of 49.1 dB and 22.9 dB was realized in radial and axial directions, respectively, which is principally in accord with the simulations. This low-cost and robust approach makes it possible to accurately measure three-dimensional mechanical quantities simultaneously and may be helpful to actively cool the particle motion in optical tweezers even to the quantum ground state in the future.