Highly efficient overexpression and purification of multisubunit tethering complexes in Saccharomyces cerevisiae.

Vesicle trafficking is a fundamental cellular process that ensures proper material exchange between organelles in eukaryotic cells, and multisubunit tethering complexes (MTCs) are essential in this process. The heterohexameric homotypic fusion and protein sorting (HOPS) complex, which functions in the endolysosomal pathway, is a member of MTCs. Despite its critical role, the complex composition and low-expression level of HOPS have made its expression and purification extremely challenging. In this study, we present a highly efficient strategy for overexpressing and purifying HOPS from Saccharomyces cerevisiae. We achieved HOPS overexpression by integrating a strong promoter TEF1 before each subunit using the gRNA-tRNA array for CRISPR-Cas9 (GTR-CRISPR) system. The HOPS complex was subsequently purified using Staphylococcus aureus protein A (ProtA) affinity purification and size-exclusion chromatography, resulting in high purity and homogeneity. We obtained two-fold more HOPS using this method than that obtained using the commonly used GAL1 promoter-controlled HOPS overexpression. Negative staining electron microscopy analysis confirmed the correct assembly of HOPS. Notably, we also successfully purified two other MTCs, class C core vacuole/endosome tethering (CORVET) and Golgi-associated retrograde protein (GARP) using this approach. Our findings facilitate further in vitro biochemical characterization and functional studies of MTCs and provide a useful guide for the preparation of other heterogenic multisubunit complexes.

3D microscopy in industrial measurements.

Quality control is essential to ensure the performance and yield of microdevices in industrial processing and manufacturing. In particular, 3D microscopy can be considered as a separate branch of microscopic instruments and plays a pivotal role in monitoring processing quality. For industrial measurements, 3D microscopy is mainly used for both the inspection of critical dimensions to ensure the design performance and detection of defects for improving the yield of microdevices. However, with the progress of advanced manufacturing technology and the increasing demand for high-performance microdevices, 3D microscopy has ushered in new challenges and development opportunities, such as breakthroughs in diffraction limit, 3D characterisation and calibrations of critical dimensions, high-precision detection and physical property determination of defects, and application of artificial intelligence. In this review, we provide a comprehensive survey about the state of the art and challenges in 3D microscopy for industrial measurements, and provide development ideas for future research. By describing techniques and methods with their advantages and limitations, we provide guidance to researchers and developers about the most suitable technique available for their intended industrial measurements.

A New Vision Measurement Technique with Large Field of View and High Resolution.

The three-dimensional (3D) displacement resolution of conventional visual measurement systems can only reach tens of microns in cases involving long measuring distances (2.5 m) and large fields of view (1.5 m × 1.5 m). Therefore, a stereo vision measurement technology based on confocal scanning is proposed herein. This technology combines macroscopic visual measurement technology with confocal microscopic measurement technology to achieve a long measuring distance, a large field of view, and micron-level measuring resolution. First, we analyzed the factors affecting the 3D resolution of the visual system and developed a 3D resolution model of the visual system. Subsequently, we fabricated a prototype based on the resolution model and the proposed stereo vision measurement technology. The 3D displacement resolution measurement results in the full field of view show that the displacement resolutions of the developed equipment in the x-, y-, and z-directions can reach 2.5, 2.5, and 6 µm, respectively.

A Single-Image Noise Estimation Algorithm Based on Pixel-Level Low-Rank Low-Texture Patch and Principal Component Analysis.

Noise level is an important parameter for image denoising in many image-processing applications. We propose a noise estimation algorithm based on pixel-level low-rank, low-texture subblocks and principal component analysis for white Gaussian noise. First, an adaptive clustering algorithm, based on a dichotomy merge, adaptive pixel-level low-rank matrix construction method and a gradient covariance low-texture subblock selection method, is proposed to construct a pixel-level low-rank, low-texture subblock matrix. The adaptive clustering algorithm can improve the low-rank property of the constructed matrix and reduce the content of the image information in the eigenvalues of the matrix. Then, an eigenvalue selection method is proposed to eliminate matrix eigenvalues representing the image to avoid an inaccurate estimation of the noise level caused by using the minimum eigenvalue. The experimental results show that, compared with existing state-of-the-art methods, our proposed algorithm has, in most cases, the highest accuracy and robustness of noise level estimation for various scenarios with different noise levels, especially when the noise is high.

Learning-based self-calibration for correcting lateral and axial field distortions in 3D surface topography measurement.

A learning-based self-calibration method is demonstrated to achieve simultaneous corrections for both lateral and axial field distortions in three-dimensional (3D) surface topography measurements. In this method, the back propagation neural network is introduced into the self-calibration technology to learn the mapping relationship between the distorted space and the undistorted space for realizing the separation of systematic errors and calibration sample topography. The rigid body feature of the artifact is used to construct the loss function to achieve the optimization of network parameters. This method not only retains the advantages of the self-calibration method but also characterizes a complex distortion model. Simulation results show that the accuracy of nanometers is achieved for the correction of lateral and axial field distortions. In the experiment, the root-mean-square (RMS) values of lateral correction residual errors are less than 30 nm, and the axial RMS values are less than 2 nm. Simulation and experimental results prove that this method can correct both lateral and axial field distortions to the level of nanometer by one calibration. It indicates that the learning-based self-calibration method might be the future development trend for lateral and axial field distortions corrections of measuring instruments in 3D surface topography measurement.

Width determination for deep grooves based on a variable point spread function imaging model.

In three-dimensional confocal microscopy, two-dimensional width measurement can be significantly influenced by the groove height. The groove height not only results in deformation of the input light field due to the effect of edge occlusions, but also introduces a defocus error to the detection plane. This paper proposes a new, to the best of our knowledge, edge-setting method to determine groove width, which engineers the point spread function to correct for the groove edge obstruction effect and develops an edge obstruction imaging model (EOIM) based on the variable point spread function. This model gives a relationship between the groove height and the normalized intensity at the groove edge and can use this relationship to determine the groove edge position that would result from focusing at the groove's lower surface. Experimental results show that an EOIM-based width determination method is more accurate than the traditional 1/4 edge-setting method. Compared to the 1/4 edge-setting method, the deviation from a reference width measured with traceable scanning electron microscopy is reduced by a factor of 2.1 with a 1.3 times smaller standard deviation.

Correction of phase-delay distortion for α-ß circular scanning.

α-ß circular scanning with a large scanning field of view and high reliability can be widely applied in laser scanning imaging systems and laser processing. However, mechanical inertia of the galvanometers introduces phase delay and ultimately leads to scanning distortions in α-ß circular scanning in both constant angular velocity scanning (CAVS) and constant line velocity scanning (CLVS). To compensate for the phase-delay distortions, two correction models are respectively proposed for CAVS and CLVS, which utilize phase-frequency relationships based on the galvanometer's transfer function. Experimental results show that the presented models can effectively correct rotation distortion in CAVS and tortuosity distortion in CLVS. The correction of phase-delay distortion can improve the image quality and refine positioning accuracy in laser scanning systems.

Interference Confocal Microscope Integrated with Spatial Phase Shifter.

We present an interference confocal microscope (ICM) with a new single-body four-step simultaneous phase-shifter device designed to obtain high immunity to vibration. The proposed ICM combines the respective advantages of simultaneous phase shifting interferometry and bipolar differential confocal microscopy to obtain high axis resolution, large dynamic range, and reduce the sensitivity to vibration and reflectance disturbance seamlessly. A compact single body spatial phase shifter is added to capture four phase-shifted interference signals simultaneously without time delay and construct a stable and space-saving simplified interference confocal microscope system. The test result can be obtained by combining the interference phase response and the bipolar property of differential confocal microscopy without phase unwrapping. Experiments prove that the proposed microscope is capable of providing stable measurements with 1 nm of axial depth resolution for either low- or high-numerical aperture objective lenses.

A promising solution to the limits of microscopes for smooth surfaces: fluorophore-aided scattering microscopy.

Reflected light escape and mesoscopic penetration are two serious problems for optical characterization using microscopes. For specular samples with steep slopes, the detector does not receive enough light and the detection algorithm is not be able to detect the peak position, and would generate non-measured points. Moreover, the mesoscopic penetration phenomenon has been ignored when measuring and observing the shapes of samples with multi-layer structures. But this phenomenon, due to the transparency of materials to certain wavelengths of light, may result in serious errors in the measurements of the heights of samples, as well as errors in the descriptions of their shapes. Here we describe the use of fluorophore-aided scattering microscopy to significantly extend the magnitudes of slopes that can be detected, and to essentially eliminate errors in measurements of height caused by mesoscopic penetration.

Environmentally friendly and non-polluting solvent pretreatment of palm samples for polyphenol analysis using choline chloride deep eutectic solvents.

In this work, choline chloride (ChCl) deep eutectic solvents (DESs) were evaluated for the pretreatment of palm samples in the analysis of polyphenols, such as protocatechuic acid, catechins, epicatechin, and caffeic acid. During the enrichment step of the pretreatment, eight DESs comprising ChCl with ethylene glycol (EG), glycerol (Gly), xylitol (Xyl), phenol (Ph), formic acid (FA), citric acid (CiA), oxalic acid (OA), or malonic acid (MA), were prepared and applied to the reflux extraction of polyphenols from palm samples. All the DESs exhibited higher polyphenol extraction efficiency than methanol, and the highest extraction efficiency was obtained using ChCl-FA (1:1, mole ratio). For the purification step of the pretreatment, eight ChCl DES-modified adsorbents were prepared by hydrothermal polymerization and packed into solid-phase extraction (SPE) cartridges, and ChCl-Urea, ChCl-Gly, ChCl-FA, and water, were used as eluents. The ChCl DES-modified adsorbents were characterized by Fourier transform infrared spectroscopy, thermal gravimetric analysis, scanning electron microscopy, and Brunauer-Emmett-Teller surface analysis, and the polyphenols were analyzed by mass spectrometry and high-performance liquid chromatograph-ultraviolet detection. The highest purification efficiency was obtained using the ChCl-Ph DES-modified adsorbent as the SPE packing material and ChCl-Urea-H2O (1:1:5, mole ratio), ChCl-Gly (1:1, mole ratio), ChCl-FA-H2O (1:1:5, mole ratio), and H2O as the eluents. Compared to conventional purification processes that employ commercial C18 or C8 SPE columns with organic solvents as eluents, the ChCl DES-based SPE purification process successfully avoided the use of expensive commercial SPE columns and organic solvents. Furthermore, it isolated a larger amount of the target compounds under the same experimental conditions, and could be applied over five cycles with good reversibility. This work indicates that DESs as green solvents have great potential for the totally green pretreatment of samples during the enrichment and purification processes.