An electron density clustering based adaptive segmentation method for protein Raman spectrum calculation.

Raman spectroscopy is a powerful technique for protein detection, but the calculation of Raman spectrum is a longstanding challenging problem due to the large sizes and complex structures of protein molecules. Dividing proteins into fragments can greatly accelerate the calculation, but this usually introduces large errors originating from ignored interactions between fragments into obtained spectra. In this paper, we proposed a new adaptive segmentation method based on the strength of interactions and molecular shapes and structures, i.e., electron density clustering, to divide proteins. It can reduce errors of obtained Raman spectra by about 20% compared to the uniform segmentation method without a significant increase in computational cost. This method can facilitate the validation and analysis of detected Raman spectra of proteins and promote the application of Raman spectroscopy in biological detection.

Rapid Detection of SARS-CoV-2 in Clinical and Environmental Samples via a Resonant Cavity SERS Platform within 20 min.

The coronavirus disease 2019 (COVID-19) epidemic has given a warning that it is important to explore the rapid detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in clinical specimens or environmental samples for public health strategies and future variants. The surface-enhanced Raman spectroscopy (SERS) technique was demonstrated to achieve this goal. However, the consistency of signals originating from the poor compatibility of virions with SERS hotspots remains a key scientific challenge for the practical applications of SERS. Herein, we develop a SERS platform for the ultrasensitive and rapid detection of SARS-CoV-2 antigen within 20 min by the combination of a highly consistent SERS substrate and a supervised deep learning algorithm. A V-shaped resonant cavity array (VRC) substrate was fabricated to trap SARS-CoV-2 virions in the periodic V cavity array and stimulate the integral SERS signal of the virus via a resonance coupling effect. Benefiting from the unique architecture of the VRC substrate, we were able to directly detect the SARS-CoV-2 virus with high sensitivity and high consistency. These excellent performances enabled us to identify five different kinds of SARS-CoV-2 variants and detect SARS-CoV-2 from clinical and environmental samples with high accuracies.

Target Density Effects on Charge Transfer of Laser-Accelerated Carbon Ions in Dense Plasma.

We report on charge state measurements of laser-accelerated carbon ions in the energy range of several MeV penetrating a dense partially ionized plasma. The plasma was generated by irradiation of a foam target with laser-induced hohlraum radiation in the soft x-ray regime. We use the tricellulose acetate (C_{9}H_{16}O_{8}) foam of 2 mg/cm^{3} density and 1 mm interaction length as target material. This kind of plasma is advantageous for high-precision measurements, due to good uniformity and long lifetime compared to the ion pulse length and the interaction duration. We diagnose the plasma parameters to be T_{e}=17 eV and n_{e}=4×10^{20} cm^{-3}. We observe the average charge states passing through the plasma to be higher than those predicted by the commonly used semiempirical formula. Through solving the rate equations, we attribute the enhancement to the target density effects, which will increase the ionization rates on one hand and reduce the electron capture rates on the other hand. The underlying physics is actually the balancing of the lifetime of excited states versus the collisional frequency. In previous measurement with partially ionized plasma from gas discharge and z pinch to laser direct irradiation, no target density effects were ever demonstrated. For the first time, we are able to experimentally prove that target density effects start to play a significant role in plasma near the critical density of Nd-glass laser radiation. The finding is important for heavy ion beam driven high-energy-density physics and fast ignitions. The method provides a new approach to precisely address the beam-plasma interaction issues with high-intensity short-pulse lasers in dense plasma regimes.

Classification of Coronavirus Spike Proteins by Deep-Learning-Based Raman Spectroscopy and its Interpretative Analysis.

The outbreak of COVID-19 has spread worldwide, causing great damage to the global economy. Raman spectroscopy is expected to become a rapid and accurate method for the detection of coronavirus. A classification method of coronavirus spike proteins by Raman spectroscopy based on deep learning was implemented. A Raman spectra dataset of the spike proteins of five coronaviruses (including MERS-CoV, SARS-CoV, SARS-CoV-2, HCoVHKU1, and HCoV-OC43) was generated to establish the neural network model for classification. Even for rapidly acquired spectra with a low signal-to-noise ratio, the average accuracy exceeded 97%. An interpretive analysis of the classification results of the neural network was performed, which indicated that the differences in spectral characteristics captured by the neural network were consistent with the experimental analysis. The interpretative analysis method provided a valuable reference for identifying complex Raman spectra using deep-learning techniques. Our approach exhibited the potential to be applied in clinical practice to identify COVID-19 and other coronaviruses, and it can also be applied to other identification problems such as the identification of viruses or chemical agents, as well as in industrial areas such as oil and gas exploration.

Combined Morphological and Spectroscopic Diagnostic of HER2 Expression in Breast Cancer Tissues Based on Label-Free Surface-Enhanced Raman Scattering.

Breast cancer is the most commonly diagnosed cancer type worldwide. Overexpression of human epidermal growth factor receptor 2 (HER2) is an important subtype of breast cancer and results in an increased risk of recurrence and metastasis in patients. At present, immunohistochemistry (IHC) is used to detect the expression of HER2 in breast cancer tissues as the golden standard. However, IHC has some shortcomings, such as large subjective impact, long time consumption, expensive reagents, etc. In this paper, a combined morphological and spectroscopic diagnostic method based on label-free surface-enhanced Raman scattering (SERS) for HER2 expression in breast cancer is proposed. It can not only quantitively detect HER2 expression in breast cancer tissues by spectroscopic measurements but also give morphological images reflecting the distribution of HER2 in tissues. The results show that the consistency between this method and IHC is 95% and achieves the annotation of tumor regions on tissue sections. This method is time-consuming, quantifiable, intuitive, scalable, and easy to understand. Combined with deep learning approaches, it is expected to promote the development of clinical detection and diagnosis technology for breast cancer and other cancers.

Cyclin-dependent kinase subunit2 (CKS2) promotes malignant phenotypes and epithelial-mesenchymal transition-like process in glioma by activating TGFß/SMAD signaling.

BACKGROUND: Gliomas are a group of primary intracranial tumors with high morbidity and mortality. The previous researches indicated a crucial role of CKS2 (cyclin-dependent kinases regulatory subunit 2) in hepatocellular carcinoma and breast cancer; however, little is known about the molecular mechanism of CKS2 in the tumorigenesis and epithelial-mesenchymal transition-like (EMT) process in glioma. METHODS: Datasets for bioinformatics analysis were obtained from the GEO, TCGA and CGGA databases. qRT-PCR, western blotting (WB), and immunohistochemistry (IHC) assays were used to investigate the expression patterns of CKS2 among glioma and brain tissues. Glioma cells were transfected with small interfering RNA/overexpression plasmid against CKS2, then clone formation assay, CCK-8, wound healing, Transwell assay, and flow cytometry were performed to detect changes in cell viability, invasiveness, and the apoptosis rate. Markers of cell invasion, apoptosis, EMT and TGFß/SMAD signaling were evaluated by WB and immunofluorescence (IF) assays. RESULTS: We found that CKS2 overexpression correlates with poor prognosis in human glioma and knockdown of CKS2 could inhibit cell proliferation, migration, invasion, and induced apoptosis in glioma cells. Besides, we also found that knockdown of CKS2 could reverse the EMT process via modulating EMT-related molecules. Glioma cells with overexpression of CKS2 were constructed to confirmed the fact that CKS2 induced nucleocytoplasmic translocation of SMAD2/3 and activated TGFß/SMAD pathway, then upregulated its downstream targets expression, while inhibition of TGFß/SMAD (by TGFß inhibitor LY2157299 or SMAD4 siRNA) could reverse the tumor-promoting effects and malignant phenotype caused by CKS2 overexpression. CONCLUSIONS: We identified CKS2 as a critical contributor to the gliomagenesis, which might provide a novel therapeutic target for inhibiting the spread and infiltration of glioma.

CUX1 Facilitates the Development of Oncogenic Properties Via Activating Wnt/ß-Catenin Signaling Pathway in Glioma.

Background: Homeobox cut like 1 (CUX1), which often presents aberrated expression in many cancer cells, exerts a crucial role in tumorigenesis. Evidence describing CUX1 in gliomagenesis is scarce, and the effects of CUX1 on the Wnt/ß-catenin pathway have not been reported. Our study aimed to explore the biological functions and molecular mechanisms involved in CUX1 activity in glioma. Methods: Datasets for bioinformatics analysis were obtained from the GEO, TCGA, CGGA, GTEX and CCLE databases. qRT-PCR, western blotting (WB), and immunohistochemistry (IHC) assays were used to investigate the expression patterns of CUX1 among glioma and brain tissues. CUX1 knockdown and overexpression vectors were transfected into glioma cell lines, the CCK-8, clone formation assay, wound healing, Transwell assay, and flow cytometry were performed to detect changes in cell viability, invasiveness, and the cell cycle. WB and immunofluorescence (IF) assays were used to explore changes in cell cycle-related and Wnt/ß-catenin signaling protein levels. Results: Overexpression of CUX1 was identified in glioma tissues, and especially in glioblastoma (GBM), when compared to normal controls and correlated with poor prognosis. In comparison with untreated cells, TJ905 glioma cells overexpressing CUX1 showed higher proliferation and invasion abilities and S phase cell-cycle arrest, while the knockdown of CUX1 suppressed cell invasive ability and induced G1 phase arrest. Active Wnt/ß-catenin signaling was enriched and clustered in a CUX1-associated GSEA/GSVA analysis. IF and WB assays indicated that CUX1 regulated the distribution of Axin2/ß-catenin in glioma cells and regulated the expression of proteins downstream of the Wnt/ß-catenin signaling pathway, suggesting that CUX1 served as an upstream positive regulator of the Wnt/ß-catenin pathway. Finally, the knockdown of Axin2 or ß-catenin could reverse the tumor-promoting effects caused by CUX1 overexpression, suggesting that CUX1 induced gliomagenesis and malignant phenotype by activating the Wnt/ß-catenin signaling pathway. Conclusion: Our data suggested that the transcription factor CUX1 could be a novel therapeutic target for glioma with gene therapy.

On-Site Detection of SARS-CoV-2 Antigen by Deep Learning-Based Surface-Enhanced Raman Spectroscopy and Its Biochemical Foundations.

A rapid, on-site, and accurate SARS-CoV-2 detection method is crucial for the prevention and control of the COVID-19 epidemic. However, such an ideal screening technology has not yet been developed for the diagnosis of SARS-CoV-2. Here, we have developed a deep learning-based surface-enhanced Raman spectroscopy technique for the sensitive, rapid, and on-site detection of the SARS-CoV-2 antigen in the throat swabs or sputum from 30 confirmed COVID-19 patients. A Raman database based on the spike protein of SARS-CoV-2 was established from experiments and theoretical calculations. The corresponding biochemical foundation for this method is also discussed. The deep learning model could predict the SARS-CoV-2 antigen with an identification accuracy of 87.7%. These results suggested that this method has great potential for the diagnosis, monitoring, and control of SARS-CoV-2 worldwide.

TROAP regulates cell cycle and promotes tumor progression through Wnt/ß-Catenin signaling pathway in glioma cells.

AIMS: Experimental evidence demonstrated a crucial role of TROAP (Trophinin-associated protein) in regulating the cell proliferation of multiple tumors, while TROAP expression and function were largely unknown in glioma. We aimed to investigate the oncogenic role of TROAP and its potential mechanisms in gliomagenesis. METHODS: Four gene expression databases (GEO, TCGA, GTEx and CCLE) were enrolled in our study and used for TROAP expression and survival analysis. TROAP expression was quantified by qRT-PCR, western blot and immunohistochemistry assays in glioma tissues and cell lines. TROAP knockdown and overexpression vector were constructed and transfected into glioma cells. CCK-8, colony formation, transwell, and wound healing assays were used to evaluate cell viability, migration and invasion, flow cytometry to determine cell cycle arrest. Gene set enrichment analysis (GSEA) was conducted to screen the pathway involved in TROAP-high phenotype. The expression of cell cycle and Wnt/ß-Catenin signaling proteins were analyzed by immunofluorescence and western blot. RESULTS: Based on the bioinformatic analysis and a series of functional assays, we found the TROAP was enriched in glioma tissues and cell lines, its overexpression was correlated with the clinicopathologic characteristics and poor prognosis. TROAP knockdown inhibited cell proliferation, migration, invasion, and G1/S cell cycle arrest compared with control group in glioma. Mechanism analysis revealed that TROAP activated Wnt/ß-Catenin pathway and upregulated its downstream targets expression, while silencing ß-Catenin or Axin2 could reverse the tumor-promoting effects caused by TROAP, confirming that TROAP-induced malignant phenotype and tumorigenesis via Wnt/ß-Catenin signaling pathway. CONCLUSION: The present study found that TROAP accelerated the progression of gliomagenesis through Wnt/ß-Catenin pathway, and TROAP might be considered as a novel target for glioma therapy.

Observation of a high degree of stopping for laser-accelerated intense proton beams in dense ionized matter.

Intense particle beams generated from the interaction of ultrahigh intensity lasers with sample foils provide options in radiography, high-yield neutron sources, high-energy-density-matter generation, and ion fast ignition. An accurate understanding of beam transportation behavior in dense matter is crucial for all these applications. Here we report the experimental evidence on one order of magnitude enhancement of intense laser-accelerated proton beam stopping in dense ionized matter, in comparison with the current-widely used models describing individual ion stopping in matter. Supported by particle-in-cell (PIC) simulations, we attribute the enhancement to the strong decelerating electric field approaching 1 GV/m that can be created by the beam-driven return current. This collective effect plays the dominant role in the stopping of laser-accelerated intense proton beams in dense ionized matter. This finding is essential for the optimum design of ion driven fast ignition and inertial confinement fusion.

Blind deconvolution for spatial distribution of Kα emission from ultraintense laser-plasma interaction.

The spatial distributions of the Kα emission from foil targets irradiated with ultra-intensity laser pulses have been studied using the x-ray coded imaging technique. Due to the effect of hard x-ray background contamination, noise as well as imperfection of imaging system, it is hard to determine the PSF analytically or measure it experimentally. Therefore, we propose a blind deconvolution method to restore both the spatial distributions of the Kα emission and the system's PSF from the coded images based on the maximum-likelihood scheme. Experimental restoration results from penumbral imaging and ring coded imaging demonstrated that both the structure integrity and the rich detail information can be well preserved.

Measurement of the chirp characteristics of linearly chirped pulses by a frequency domain interference method.

A linear optical technique for chirp characteristics measurement based on frequency domain interference is developed. This technique can be applied to measure the temporal structure of linearly chirped pulses which have become increasingly important in ultrafast optics. To confirm this technique, an experiment is carried out to measure the chirp rate and duration of a picosecond chirped pulse with an imaging spectrometer.

Fractional spiral zone plates.

In this paper, we generalize the concept of classical spiral zone plates (SZPs) to fractional spiral zone plates (FSZPs). By using an SZP with a fractional topological charge and controlling the starting orientation, we can break down the symmetry of the focusing process to give orientation-selective anisotropic vortex foci. Numerical results show that its binary structure gives additional high-order foci on the optical axis and the intensities in the foci can be controlled by properly choosing the fractional topological charge. Our study reveals the feasibility to control the intensity in the foci by means of FSZPs.

Realizing a Gabor zone plate with quasi-random distributed hexagon dots.

We propose a quasi-random-dot-array binary Gabor zone plate (QBGZP) with focusing properties of single order foci only. These features are verified with simulations and experiments in the visible light region. Moreover, we find that the performance of QBGZP, which is composed of hexagon patterns, is determined by the ratio of hexagon circumcircle diameter to the outermost zone width. The QBGZP offers a potential alternative for focusing and imaging in the soft x-ray and extreme ultraviolet region.