Raman cell sorting for single-cell research.

Cells constitute the fundamental units of living organisms. Investigating individual differences at the single-cell level facilitates an understanding of cell differentiation, development, gene expression, and cellular characteristics, unveiling the underlying laws governing life activities in depth. In recent years, the integration of single-cell manipulation and recognition technologies into detection and sorting systems has emerged as a powerful tool for advancing single-cell research.

Precision isolation and cultivation of single cells by vortex and flat-top laser ejection.

Single-cell isolation stands as a critical step in single-cell studies, and single-cell ejection technology based on laser induced forward transfer technology (LIFT) is considered one of the most promising methods in this regard for its ability of visible isolating single cell from complex samples. In this study, we improve the LIFT technology and introduce optical vortex laser-induced forward transfer (OV-LIFT) and flat-top laser-induced forward transfer (FT-LIFT) by utilizing spatial light modulator (SLM), aiming to enhance the precision of single-cell sorting and the cell's viability after ejection. Experimental results demonstrate that applying vortex and flat-top beams during the sorting and collection process enables precise retrieval of single cells within diameter ranges of 50 μm and 100 μm, respectively.

Stable SERS Detection of Lactobacillus fermentum Using Optical Tweezers in a Microfluidic Environment.

Rapid identification of fermented lactic acid bacteria has long been a challenge in the brewing industry. This study combined label-free surface-enhanced Raman scattering (SERS) and optical tweezer technology to construct a test platform within a microfluidic environment. Six kinds of lactic acid bacteria common in industry were tested to prove the stability of the SERS spectra.

Evaluation of Raman spectroscopy combined with the gated recurrent unit serum detection method in early screening of gastrointestinal cancer.

Gastric and colorectal cancers are significant causes of human mortality. Conventionally, the diagnosis of gastrointestinal tumors has been accomplished through image-based techniques, including endoscopic and biopsy procedures coupled with tissue staining. Most of these methods are invasive.

Deep learning-based ultra-fast identification of Raman spectra with low signal-to-noise ratio.

Ensuring the correct use of cell lines is crucial to obtaining reliable experimental results and avoiding unnecessary waste of resources. Raman spectroscopy has been confirmed to be able to identify cell lines, but the collection time is usually 10-30 s. In this study, we acquired Raman spectra of five cell lines with integration times of 0.

Genetically predicted vitamin C levels significantly affect patient survival and immunotypes in multiple cancer types.

Background: Recent observational studies and meta-analyses have shown that vitamin C reduces cancer incidence and mortality, but the underlying mechanisms remain unclear. We conducted a comprehensive pan-cancer analysis and biological validation in clinical samples and animal tumor xenografts to understand its prognostic value and association with immune characteristics in various cancers.

Methods: We used the Cancer Genome Atlas gene expression data involving 5769 patients and 20 cancer types.

Classification of deep-sea cold seep bacteria by transformer combined with Raman spectroscopy.

Raman spectroscopy is a rapid analysis method of biological samples without labeling and destruction. At present, the commonly used Raman spectrum classification models include CNN, RNN, etc. The transformer has not been used for Raman spectrum identification.

Building an ensemble learning model for gastric cancer cell line classification via rapid raman spectroscopy.

Cell misuse and cross-contamination can affect the accuracy of cell research results and result in wasted time, manpower and material resources. Thus, cell line identification is important and necessary. At present, the commonly used cell line identification methods need cell staining and culturing.

Classification of pathogenic bacteria by Raman spectroscopy combined with variational auto-encoder and deep learning.

Rapid and early identification of pathogens is critical to guide antibiotic therapy. Raman spectroscopy as a noninvasive diagnostic technique provides rapid and accurate detection of pathogens. Raman spectrum of single cells serves as the "fingerprint" of the cell, revealing its metabolic characteristics.

Multi-point scanning confocal Raman spectroscopy for accurate identification of microorganisms at the single-cell level.

Raman spectroscopy has been widely used for microbial analysis due to its exceptional qualities as a rapid, simple, non-invasive, reproducible, and real-time monitoring tool. The Raman spectrum of a cell is a superposition of the spectral information of all biochemical components in the laser focus. In the case where the microbial size is larger than the laser spot size, the Raman spectrum measured from a single-point within a cell cannot capture all biochemical information due to the spatial heterogeneity of microorganisms.

Rapid detection of beer spoilage bacteria based on label-free SERS technology.

Beer spoilage bacteria have been a headache for major breweries. In order to rapidly identify spoilage bacteria and improve the sensitivity and signal-to-noise ratio of bacterial SERS detection, the label-free SERS technique was used as a starting point, and we found eight bacteria species that led to beer spoilage. The impact of AgNP concentration and AgNP and bacterial binding time on the final results were thoroughly investigated.

Raman Spectroscopy: A Novel Technology for Gastric Cancer Diagnosis.

Gastric cancer is usually diagnosed at late stage and has a high mortality rate, whereas early detection of gastric cancer could bring a better prognosis. Conventional gastric cancer diagnostic methods suffer from long diagnostic times, severe trauma, and a high rate of misdiagnosis and rely heavily on doctors' subjective experience. Raman spectroscopy is a label-free molecular vibrational spectroscopy technique that identifies the molecular fingerprint of various samples based on the inelastic scattering of monochromatic light.

Laser tweezers Raman spectroscopy combined with deep learning to classify marine bacteria.

Rapid identification of marine microorganisms is critical in marine ecology, and Raman spectroscopy is a promising means to achieve this. Single cell Raman spectra contain the biochemical profile of a cell, which can be used to identify cell phenotype through classification models. However, traditional classification methods require a substantial reference database, which is highly challenging when sampling at difficult-to-access locations.

Isolation and Culture of Single Microbial Cells by Laser Ejection Sorting Technology.

Single-cell isolation and cultivation play an important role in studying physiology, gene expression, and functions of microorganisms. A series of single-cell isolation technologies have been developed, among which single-cell ejection technology is one of the most promising. Single-cell ejection technology has applied laser-induced forward transfer (LIFT) techniques to isolate bacteria, but the viability (or recovery rate) of cells after sorting has not been clarified in current research.

MicroRNA‑192 acts as a tumor suppressor in colon cancer and simvastatin activates miR‑192 to inhibit cancer cell growth.

Colon cancer is one of the most common malignant tumors worldwide. Understanding the underlying molecular mechanisms is crucial for the development of therapeutic strategies for the treatment of patients with colon cancer. In the present study, a novel tumor suppressive microRNA, miR‑192, was demonstrated to be markedly downregulated in colon cancer cells compared with normal colon cells.

[Association between polymorphisms of HIF-1alpha C1772T and G1790A and hypoxic acclimation in high altitude in Tibetans].

In this study the blood sample was collected from eighty-six athletes in Tibetan mountaining team and Tibetan mountaining sports school and ninety healthy Han nationality people in Guangdong province, and genomic DNA was extracted from peripheral leukocyte. The allele frequency distribution and the genotypes combination distribution of hypoxia-inducible factor-la gene (HIF-1alpha)exonl2 C1772T and G1790A were examined by restriction fragment length polymorphism PCR (PCR-RFLP) in order to evaluate the association of single nucleotide polymorphisms (SNPs) of HIF-1alpha C1772T and G1790A with hypoxic acclimation in high altitude in Tibetans. The results indicated that the genotype frequency of HIF-1alpha C1772T in Tibetan and in Han nationality was 13.

[Relationship between adaptation to high altitude hypoxia environment and glucose transport 1 gene polymorphism].

This investigation was conducted to explore the relationship between the polymorphism of gene of glucose transport 1(GLUT1) and the human body adaptation to high altitude hypoxia environment. The data on glucose transport 1 gene polymorphism in Tibetan mountaineers (high altitude group) were analyzed and compared with the data from the level-land Guangdong Hans (control group). The genotype of 86 Tibetan mountaineers and 90 level-land Hans as controls were tested with polymerase chain reaction followed by restriction fragment length polymorphism analysis for GLUT1 gene.

[Association of polymorphisms of 1772 (C-->T) and 1790 (G-->A) in HIF1A gene with hypoxia adaptation in high altitude in Sherpas].

Objective: To investigate the association of single nucleotide polymorphisms (SNPs) of 1772 (C-->T) and 1790 (G-->A) in exon 12 of hypoxia-inducible factor 1, alpha subunit gene (HIF1A) with hypoxia adaptation in high altitude in Sherpas.

Methods: The blood samples were chosen from 148 Sherpas in Tibet high altitude and 90 Han nationality healthy people in Guangdong province, and from which genomic DNA was extracted. The single nucleotide polymorphisms of 1772(C-->T) and 1790(G-->A) in exon 12 of HIF1A gene were examined by restriction fragment length polymorphism-polymerase chain reaction (RFLP-PCR).

[Single nucleotide polymorphisms study of surfactant protein A gene between Tibet Sherpas and Guangdong Chinese Hans].

Aim: To investigate the relationship between single nucleotide polymorphisms(SNPs) of surfactant protein A(SP-A) gene of Chinese Han and Sherpas and their adaptation to high altitude hypoxia.

Methods: The genotypes of 90 Chinese Han in Guangdong and 104 Sherpas in Tibet were analyzed by sequence special primer polymerase chain reaction(SSP-PCR) sequencing the surfactant protein A gene.

Results: The frequencies of genotypes and alleles at SP-A1 1544 locus showed no difference between the Sherpas and the Chinese Han (P>0.