A Liver Stiffness-Based Etiology-Independent Machine Learning Algorithm to Predict Hepatocellular Carcinoma.

BACKGROUND & AIMS: The existing hepatocellular carcinoma (HCC) risk scores have modest accuracy, and most are specific to chronic hepatitis B infection. In this study, we developed and validated a liver stiffness-based machine learning algorithm (ML) for prediction and risk stratification of HCC in various chronic liver diseases (CLDs). METHODS: MLs were trained for prediction of HCC in 5155 adult patients with various CLDs in Korea and further tested in 2 prospective cohorts from Hong Kong (HK) (N = 2732) and Europe (N = 2384). Model performance was assessed according to Harrell's C-index and time-dependent receiver operating characteristic (ROC) curve. RESULTS: We developed the SMART-HCC score, a liver stiffness-based ML HCC risk score, with liver stiffness measurement ranked as the most important among 9 clinical features. The Harrell's C-index of the SMART-HCC score in HK and Europe validation cohorts were 0.89 (95% confidence interval, 0.85-0.92) and 0.91 (95% confidence interval, 0.87-0.95), respectively. The area under ROC curves of the SMART-HCC score for HCC in 5 years was ≥0.89 in both validation cohorts. The performance of SMART-HCC score was significantly better than existing HCC risk scores including aMAP score, Toronto HCC risk index, and 7 hepatitis B-related risk scores. Using dual cutoffs of 0.043 and 0.080, the annual HCC incidence was 0.09%-0.11% for low-risk group and 2.54%-4.64% for high-risk group in the HK and Europe validation cohorts. CONCLUSIONS: The SMART-HCC score is a useful machine learning-based tool for clinicians to stratify HCC risk in patients with CLDs.

Single-Cell Unsaturated Lipid Profiling for Studying Chemoresistance Heterogeneity of Triple-Negative Breast Cancer Cells.

Chemoresistance to triple-negative breast cancer (TNBC) is a critical issue in clinical practice. Lipid metabolism takes a unique role in breast cancer cells; especially, unsaturated lipids involving cell membrane fluidity and peroxidation are highly remarked. At present, for the lack of a high-resolution molecular recognition platform at the single-cell level, it is still hard to systematically study chemoresistance heterogeneity based on lipid unsaturation proportion. By designing a single-cell mass spectrometry workflow based on CyESI-MS, we profiled the unsaturated lipids of TNBC cells to evaluate lipidomic remodeling under platinum stress. Profiling revealed the heterogeneity of the polyunsaturated lipid proportion of TNBC cells under cisplatin treatment. A cluster of cells identified by polyunsaturated lipid accumulation was found to be involved in platinum sensitivity. Furthermore, we found that the chemoresistance of TNBC cells could be regulated by fatty acid supplementation, which determinates the composition of unsaturated lipids. These discoveries provide insights for monitoring and controlling cellular unsaturated lipid proportions to overcome chemoresistance in breast cancer.

SEAM is a spatial single nuclear metabolomics method for dissecting tissue microenvironment.

Spatial metabolomics can reveal intercellular heterogeneity and tissue organization. Here we report on the spatial single nuclear metabolomics (SEAM) method, a flexible platform combining high-spatial-resolution imaging mass spectrometry and a set of computational algorithms that can display multiscale and multicolor tissue tomography together with identification and clustering of single nuclei by their in situ metabolic fingerprints. We first applied SEAM to a range of wild-type mouse tissues, then delineated a consistent pattern of metabolic zonation in mouse liver. We further studied the spatial metabolic profile in the human fibrotic liver. We discovered subpopulations of hepatocytes with special metabolic features associated with their proximity to the fibrotic niche, and validated this finding by spatial transcriptomics with Geo-seq. These demonstrations highlighted SEAM's ability to explore the spatial metabolic profile and tissue histology at the single-cell level, leading to a deeper understanding of tissue metabolic organization.

Age and the relative importance of liver-related deaths in nonalcoholic fatty liver disease.

BACKGROUND AND AIMS: It is unclear if the leading causes of death in patients with NAFLD differ by age. We aimed to investigate if the relative importance of liver-related deaths is lower and overshadowed by cardiovascular and cancer-related deaths in the elderly population. APPROACH AND RESULTS: We conducted a territory-wide retrospective cohort study of adult patients with NAFLD between 2000 and 2021 in Hong Kong. The outcomes of interest were all-cause and cause-specific mortality. Age groups at death were studied at 10-year intervals. During 662,471 person-years of follow-up of 30,943 patients with NAFLD, there were 2097 deaths. The top three causes of death were pneumonia, extrahepatic cancer, and cardiovascular diseases. Liver disease was the sixth leading cause of death in patients aged 70-79 and 80-89 years, accounting for 5.1% and 5.9% of deaths, respectively, but only accounted for 3% or fewer of the deaths in the other age groups. Nonetheless, liver disease was the leading cause of death in patients with NAFLD-related cirrhosis, accounting for 36.8% of all deaths. The incidence of liver-related death was higher in men younger than age 70 but higher in women afterwards. The incidence of liver-related death in women increased from 0.62 to 7.14 per 10,000 person-years from age 60-69 to 70-79 years. CONCLUSION: The relative importance of liver-related death increases with age in patients with NAFLD, especially among women. In patients with cirrhosis, liver disease is the leading cause of death.

Duration of type 2 diabetes and liver-related events in nonalcoholic fatty liver disease: A landmark analysis.

BACKGROUND AND AIMS: We aimed to determine the impact of the duration of type 2 diabetes (T2D) on the risk of liver-related events and all-cause mortality in patients with NAFLD. APPROACH AND RESULTS: We conducted a territory-wide cohort study of adult patients with NAFLD diagnosed between January 1, 2000, and July 31, 2021, in Hong Kong. T2D was defined by the use of any antidiabetic agents, laboratory tests, and/or diagnosis codes. The primary endpoint was liver-related events, defined as a composite endpoint of HCC and cirrhotic complications. To conduct a more granular assessment of the duration of T2D, we employed landmark analysis in four different ages of interest (biological age of 40, 50, 60, and 70 years). By multivariable analysis with adjustment of non-liver-related deaths, compared with patients without diabetes at age 60 (incidence rate of liver-related events: 0.70 per 1,000 person-years), the adjusted subdistribution HR (SHR) of liver-related events was 2.51 (95% CI: 1.32-4.77; incidence rate: 2.26 per 1,000 person-years) in patients with T2D duration < 5 years, 3.16 (95% CI: 1.59-6.31; incidence rate: 2.54 per 1,000 person-years) in those with T2D duration of 6-10 years, and 6.20 (95% CI: 2.62-14.65; incidence rate: 4.17 per 1000 person-years) in those with T2D duration more than 10 years. A similar association between the duration of T2D and all-cause mortality was also observed. CONCLUSIONS: Longer duration of T2D is significantly associated with a higher risk of liver-related events and all-cause mortality in patients with NAFLD.

Diagnostic and prognostic performance of the SAFE score in non-alcoholic fatty liver disease.

BACKGROUND & AIMS: The steatosis-associated fibrosis estimator (SAFE) score was developed to detect clinically significant liver fibrosis in patients with NAFLD in the United States. We compare the performance of the SAFE score and other non-invasive tests to diagnose liver fibrosis and to correlate the scores with liver-related outcomes in patients with NAFLD in Hong Kong. METHODS: This was a retrospective cohort study involving two data sets. The first cohort was a biopsy cohort of NAFLD patients (n = 279), and the second was a territory-wide cohort of NAFLD patients (n = 4603) retrieved from a territory-wide electronic healthcare database in Hong Kong. RESULTS: In detecting significant fibrosis, liver stiffness measured by transient elastography had the highest area under the receiver operating characteristic curve (AUROC) (.844), followed by SAFE score (.773). SAFE score had the highest AUROC among blood-based algorithms (.773 vs. .746 for FIB-4, .697 for APRI). Based on cut-off values of SAFE score (0 and 100 points), 854 (18.6%), 1596 (34.6%) and 2153 (46.8%) were in the low-, intermediate- and high-risk groups, respectively, in the territory-wide cohort. Six (.7%), 15 (.9%) and 59 (2.7%) developed liver-related events in those three groups respectively. Among patients who had liver-related events at 5 years, using the high cut-off, SAFE score could predict 84.9% of patients accurately, compared to 40.9% for FIB-4 and 27.2% for APRI. CONCLUSION: The SAFE score performed well and better than other blood-based markers in diagnosing significant fibrosis and predicting liver-related events in Asian patients with NAFLD.

Compact, low-loss, and high-polarized-extinction ratio terahertz TM-pass polarizer based on a hybrid plasmonic waveguide with a graphene ridge.

A compact, low-loss, and high-polarized-extinction ratio TM-pass polarizer based on a graphene hybrid plasmonic waveguide (GHPW) has been demonstrated for the terahertz band. A ridge coated by a graphene layer and the hollow HPW with a semiround arch (SRA) Si core is introduced to improve structural compactness and suppress the loss. Based on this, a TM-pass polarizer has been designed that can effectively cut off the unwanted TE mode, and the TM mode passes with negligible loss. By optimizing the angle of the ridge, the height of the ridge, air gap height, and the length of the tapered mode converter, an optimum performance with a high polarization extinction ratio of 30.28 dB and a low insert loss of 0.4 dB is achieved in the 3 THz band. This work provides a scheme for the design and optimization of polarizers in the THz band, which has potential application value in integrated terahertz systems.

Clinical care pathway to detect advanced liver disease in patients with type 2 diabetes through automated fibrosis score calculation and electronic reminder messages: a randomised controlled trial.

OBJECTIVE: We aimed to test the hypothesis that automated fibrosis score calculation and electronic reminder messages could increase the detection of advanced liver disease in patients with type 2 diabetes. DESIGN: In this pragmatic randomised controlled trial at five general medical or diabetes clinics in Hong Kong and Malaysia, we randomly assigned patients in a 1:1 ratio to the intervention group with Fibrosis-4 index and aspartate aminotransferase-to-platelet ratio index automatically calculated based on routine blood tests, followed by electronic reminder messages to alert clinicians of abnormal results, or the control group with usual care. The primary outcome was the proportion of patients with increased fibrosis scores who received appropriate care (referred for hepatology care or specific fibrosis assessment) within 1 year. RESULTS: Between May 2020 and Oct 2021, 1379 patients were screened, of whom 533 and 528 were assigned to the intervention and control groups, respectively. A total of 55 out of 165 (33.3%) patients with increased fibrosis scores in the intervention group received appropriate care, compared with 4 of 131 (3.1%) patients in the control group (difference 30.2% (95% CI 22.4% to 38%); p<0.001). Overall, 11 out of 533 (2.1%) patients in the intervention group and 1 out of 528 (0.2%) patients in the control group were confirmed to have advanced liver disease (difference 1.9% (95% CI 0.61% to 3.5%); p=0.006). CONCLUSION: Automated fibrosis score calculation and electronic reminders can increase referral of patients with type 2 diabetes and abnormal fibrosis scores at non-hepatology settings. TRIAL REGISTRATION NUMBER: NCT04241575.

Efficient Sample Preparation System for Multi-Omics Analysis via Single Cell Mass Spectrometry.

Mass spectrometry (MS) has become a powerful tool for metabolome, lipidome, and proteome analyses. The efficient analysis of multi-omics in single cells, however, is still challenging in the manipulation of single cells and lack of in-fly cellular digestion and extraction approaches. Here, we present a streamlined strategy for highly efficient and automatic single-cell multi-omics analysis by MS. We developed a 10-pL-level microwell chip for housing individual single cells, whose proteins were found to be digested in 5 min, which is 144 times shorter than traditional bulk digestion. Besides, an automated picoliter extraction system was developed for sampling of metabolites, phospholipids, and proteins in tandem from the same single cell. Also, 2 min MS2 spectra were obtained from 700 pL solution of a single cell sample. In addition, 1391 proteins, phospholipids, and metabolites were detected from one single cell within 10 min. We further analyzed cells digested from cancer tissue samples, achieving up to 40% increase in cell classification accuracy using multi-omics analysis in comparison with single-omics analysis. This automated single-cell MS strategy is highly efficient in analyzing multi-omics information for investigation of cell heterogeneity and phenotyping for biomedical applications.

Risk of liver-related events by age and diabetes duration in patients with diabetes and nonalcoholic fatty liver disease.

BACKGROUND AND AIMS: Several guidelines recommend screening for NAFLD in patients with type 2 diabetes (T2D). We aimed to determine if there is a threshold of age and duration of T2D for liver-related event development to guide screening strategies. APPROACH AND RESULTS: We conducted a territory-wide retrospective cohort study of adult patients with NAFLD and T2D diagnosed between 2000 and 2014 in Hong Kong to allow for at least 5 years of follow-up. The primary endpoint was liver-related events, defined as a composite of HCC and cirrhotic complications. This study included 7028 patients with NAFLD with T2D (mean age, 56.1 ± 13.3 years; 3363 male [47.9%]). During a follow-up of 77,308 person-years, there was a threshold effect with 1.1%, 4.9%, and 94.0% of patients developing liver-related events at the age of <40, 40-50, and ≥50 years, respectively. Similarly, 3.1%, 5.1%, and 91.8% of patients developed cirrhosis at the age of <40, 40-50, and ≥50 years, respectively. In contrast, liver-related events increased linearly with diabetes duration, with no difference in the annual incidence rate between the first 10 years of T2D diagnosis and subsequent years (0.06% vs. 0.10%; p = 0.136). On multivariable analysis, baseline age ≥50 years (adjusted HR [aHR] 2.01) and cirrhosis (aHR 3.12) were the strongest risk factors associated with liver-related events. Substitution of cirrhosis with the aspartate aminotransferase-to-platelet ratio index or the Fibrosis-4 index yielded similar results. CONCLUSIONS: Age rather than duration of T2D predicts liver-related events in patients with NAFLD and T2D. It is reasonable to screen patients with NAFLD and T2D for advanced liver disease starting at 50 years of age.

Angiotensin-converting enzyme inhibitors prevent liver-related events in nonalcoholic fatty liver disease.

BACKGROUND AND AIMS: Angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) can inhibit liver fibrogenesis in animal models. We aimed to evaluate the impact of ACEI/ARB use on the risk of liver cancer and cirrhosis complications in patients with NAFLD. APPROACH AND RESULTS: We conducted a retrospective, territory-wide cohort study of adult patients with NAFLD diagnosed between January 2000 and December 2014 to allow for at least 5 years of follow-up. ACEI or ARB users were defined as patients who had received ACEI or ARB treatment for at least 6 months. The primary endpoint was liver-related events (LREs), defined as a composite endpoint of liver cancer and cirrhosis complications. We analyzed data from 12,327 NAFLD patients (mean age, 54.2 ± 14.7 years; 6163 men [50.0%]); 6805 received ACEIs, and 2877 received ARBs. After propensity score weighting, ACEI treatment was associated with a lower risk of LREs (weighted subdistribution hazard ratio [SHR], 0.48; 95% CI, 0.35-0.66; p < 0.001), liver cancer (weighted SHR, 0.46; 95% CI, 0.28-0.75; p = 0.002), and cirrhosis complications (weighted SHR, 0.42; 95% CI, 0.27-0.66; p < 0.001), but ARB was not. In subgroup analysis, ACEI treatment was associated with greater reduction in LREs in patients with chronic kidney diseases (CKDs) than those without (CKD-weighted SHR, 0.74; 95% CI, 0.52-0.96; p = 0.036; non-CKD-weighted SHR, 0.15; 95% CI, 0.07-0.33; p < 0.001). CONCLUSIONS: ACEI, rather than ARB, treatment is associated with a lower risk of LREs in NAFLD patients, especially among those with CKD.

The simultaneous quantitative detection of multiple hormones based on PS-MS: affinity capture by a single antibody.

Steroid hormones play important roles in metabolism and metabolic diseases. Currently, various detection methods are employed in clinical labs, mainly immunoassays and LC-MS/MS, but these methods suffer from antibody cross-reactivity or the need for complex LC processes, respectively. Here, we utilized single antibody to capture and separate multiple hormones from samples to avoid LC procedures and used MS/MS to analyze multiple molecules in a single run. In our strategy, testosterone (T), androstenedione (4-AD), and androsterone (ADT) were affinity-captured simultaneously using only T antibody. The qualitative and quantitative analysis of three androgens was realized through MS/MS spectra using testosterone-D3 (T-D3) as an internal standard. Standard curves for standard solution or spiked serum samples were realized in the range of 0.01-2 µg L-1. The LODs for the three androgens were 2.3 × 10-3 µg L-1 for testosterone, 4.6 × 10-3 µg L-1 for androstenedione, and 2.8 × 10-3 µg L-1 for androsterone. The recovery results verified the reliability and stability of our method. This strategy has widespread potential for advancing the combination of immunoassay and MS methods in the analysis of small molecules, with high through-put and low cost.

The heterogeneity of oxidized lipids in individual tumor cells reveals NK cell-mediated cytotoxicity by label-free mass cytometry.

NK cell-mediated immunotherapy has received increasing attention in the past decade due to its efficacy and bio-safety. The composition and content of lipids in individual cells are closely related to NK cell-mediated cytotoxicity, especially polyunsaturated fatty acids (PUFA) which are oxidized during NK cell-mediated apoptosis. Here we investigated the changes of lipids in single HepG2 cells by label-free mass cytometry and obtained information on 53 lipids and 13 oxidized lipids after the interaction with NK92 MI cells. We found that the contents of lipids and oxidized lipids of HepG2 cells changed obviously during the NK cell-mediated apoptosis. The HepG2 cells could be classified into two phenotypes after co-culturing with NK92 MI cells based on the ratio of PC(38:6-2OH)/PC(38:6) in individual cells, which may serve as a feature to evaluate NK cell-mediated cytotoxicity. The present work used the lipids and oxidized lipids of individual cells to reveal the heterogeneity in NK cell-mediated apoptosis which would be a powerful method for evaluating the cytotoxicity of NK cells at the single-cell level.

Trimethylamine-N-Oxide Aggravates Kidney Injury via Activation of p38/MAPK Signaling and Upregulation of HuR.

BACKGROUND: Trimethylamine-N-oxide (TMAO) is an intestinal metabolic toxin, which is produced by gut flora via metabolizing high-choline foods. TMAO is known to increase the risk of atherosclerosis and cardiovascular events in chronic kidney disease (CKD) patients. OBJECTIVES: The objective of this study was to explore the role and mechanism of TMAO aggravating kidney injury. METHOD: We used the five-sixths nephrectomy (5/6 Nx)-induced CKD rats to investigate whether TMAO could aggravate kidney damage and its possible mechanisms. Six weeks after the operation, the two groups of 5/6 Nx rats were subjected to intraperitoneal injection with 2.5% glucose peritoneal dialysis fluid (2.5% PDF) and 2.5% PDF plus TMAO 20 mg/kg/day. RESULTS: In this study, we provided evidence showing TMAO significantly aggravated renal failure as well as inflammatory cell infiltration and in five-sixths nephrectomy-induced CKD rats. We found that TMAO could upregulate inflammatory factors including MCP-1, TNF-α, IL-6, IL-1ß, and IL-18 by activating p38 phosphorylation and upregulation of human antigen R. TMAO could aggravate oxidative stress by upregulating NOX4 and downregulating SOD. The result also confirmed that TMAO promoted NLRP3 inflammasome formation as well as cleaved caspase-1 and IL-1ß activation in the kidney tissue. CONCLUSIONS: Taken together, the present study validates TMAO as a pro-inflammatory factor that causes renal inflammatory injury and renal function impairment. Inhibition of TMAO synthesis or promoting its clearance may be a potential therapeutic approach of CKD in the future.

Site-Specific Scissors Based on Myeloperoxidase for Phosphorothioate DNA.

The tool box of site-specific cleavage for nucleic acid has been an increasingly attractive subject. Especially, the recent emergence of the orthogonally activatable DNA device is closely related to the site-specific scission. However, most of these cleavage strategies are based on exogenous assistance, such as laser irradiation. Endogenous strategies are highly desirable for the orthogonally regulatable DNA machine to explore the crucial intracellular biological process and cell signal network. Here, we found that the accurate site-specific cleavage reaction of phosphorothioate (PT) modified DNA by using myeloperoxidase (MPO). A scissors-like mechanism by which MPO breaks PT modification through chloride oxidation has been revealed. Furthermore, we have successfully applied the scissors to activate PT-modified hairpin-DNA machines to produce horseradish peroxidase (HRP)-mimicking DNAzyme or initiate hybridization chain reaction (HCR) amplification. Since MPO plays an important role in the pathway related to oxidative stress in cells, through the HCR amplification activated by this tool box, the oxidative stress in living cells has been robustly imaged. This work proposes an accurate and endogenous site-specific cleavage tool for the research of biostimuli and the construction of DNA molecular devices.

Rapid Disulfide Mapping in Peptides and Proteins by meta-Chloroperoxybenzoic Acid (mCPBA) Oxidation and Tandem Mass Spectrometry.

Disulfide bonds are a class of important post-translational modifications that play important roles in modulating the structures and functions of proteins. Therefore, the mapping of disulfide linkages in peptides and proteins is indispensable for complete structure characterization and functional studies. As disulfide bonds in protonated ions do not dissociate readily under low-energy collision-induced dissociation (CID), they are usually chemically cleaved or activated prior to mass spectrometry (MS) or tandem MS (MS/MS) analysis. In this study, we report a new method that allows the mapping of disulfide linkages in peptides and proteins through meta-chloroperoxybenzoic acid (mCPBA)-based disulfide oxidation and MS/MS. Upon oxidation, the disulfide bond is converted to a thiosulfinate group, i.e., S(═O)-S, in a rapid (>60% yield in 1 min) and highly specific approach in an aqueous phase. The thiosulfinate group is then preferentially cleaved by MS/MS. For interchain disulfide linkages, this leads to a facile peptide chain separation and the identification of disulfide-linked peptides. For intrachain disulfide linkages, collisional activation of the thiosulfinate leads to disulfide cleavage and fragmentation of the peptide backbone constrained by the disulfide loop, enabling a near-complete peptide sequencing. The mCPBA oxidation-based disulfide mapping strategy can be readily integrated with bottom-up or top-down protein analysis for comprehensive protein structure elucidation, e.g., digested lysozyme and intact human insulin.

Discriminating Leukemia Cellular Heterogeneity and Screening Metabolite Biomarker Candidates using Label-Free Mass Cytometry.

Discriminating various leukocyte subsets with specific functions is critical due to their important roles in the development of many diseases. Here, we proposed a general strategy to unravel leukocytes heterogeneity and screen differentiated metabolites as biomarker candidates for leukocyte subtypes using the label-free mass cytometry (CyESI-MS) combined with a homemade data processing workflow. Taking leukemia cells as an example, metabolic fingerprints of single leukemia cells were obtained from 472 HL-60, 416 THP-1, 313 U937, 356 Jurkat, and 366 Ramos cells, with throughput up to 40 cells/min. Five leukemia subtypes were clearly distinguished by unsupervised learning t-SNE analysis of the single-cell metabolic fingerprints. Cell discrimination in the mixed leukemia cell samples was also realized by supervised learning of the single-cell metabolic fingerprints with high recovery and good repetition (98.31 ± 0.24%, -102.35 ± 4.82%). Statistical analysis and metabolite assignment were carried out to screen characteristic metabolites for discrimination and 36 metabolites with significant differences were annotated. Then, differentiated metabolites for pairwise discrimination of five leukemia subtypes were further selected as biomarker candidates. Furthermore, discriminating cultured leukemia cells from human normal leukocytes, separated from fresh human peripheral blood, was performed based on single-cell metabolic fingerprints as well as the proposed biomarker candidates, unveiling the potential of this strategy in clinical research. This work makes efforts to realize high-throughput single-leukocyte metabolic analysis and metabolite-based discrimination of leukocytes. It is expected to be a powerful means for the clinical molecular diagnosis of hematological diseases.

Combination of Structured Illumination Microscopy with Hyperspectral Imaging for Cell Analysis.

Existing structured illumination microscopy (SIM) allows super-resolution live-cell imaging in few color channels that provide merely morphological information but cannot acquire the sample spectrum that is strongly relevant to the underlying physicochemical property. We develop hyperspectral SIM which enables high-speed spectral super-resolution imaging in SIM for the first time. Through optically mapping the three-dimensional (x, y, and λ) datacube of the sample to the detector plane, hyperspectral SIM allows snapshot spectral imaging of the SIM raw image, detecting the sample spectrum while retaining the high-speed and super-resolution characteristics of SIM. We demonstrate hyperspectral SIM imaging and reconstruct a datacube containing 31 super-resolution images of different wavelengths from only 9 exposures, achieving a 15 nm spectral resolution. We show time-lapse hyperspectral SIM imaging that achieves an imaging speed of 2.7 s per datacube-31-fold faster than the existing wavelength scanning strategy. To demonstrate the great prospects for further combining hyperspectral SIM with various spectral analysis methods, we also perform spectral unmixing of the hyperspectral SIM result while imaging the spectrally overlapped sample.

Dynamic Monitoring of Phase-Separated Biomolecular Condensates by Photoluminescence Lifetime Imaging.

The formation of biomolecular condensates is driven by liquid-liquid phase separation, which is prevalent in cells to govern crucial cellular functions. However, understanding the properties of phase-separated condensates remains very challenging for the lack of suitable techniques. Here, we report a photoluminescence lifetime imaging method for real-time monitoring of phase-separated condensates, both in vitro and in living cells, using a microsecond-scale photoluminescence lifetime probe based on iridium complex. The probe has a large Stokes shift, excellent cell permeability, and minimal cell autofluorescence interference. With this method, the dynamic process of phase separation of fused in sarcoma protein has been well explored, showing high spatiotemporal resolution and high throughput. Beginning with initial formation, the protein droplets get bigger and more viscous, and then a final maturation to solidified aggregates has been characterized. This study paves the path for a deeper understanding of the properties of phase-separated biomolecular condensates.

Mannose Promotes Metabolic Discrimination of Osteosarcoma Cells at Single-Cell Level by Mass Spectrometry.

Discrimination of cancer cells at the single-cell metabolic level is crucial for early diagnosis. However, some cancer cells share similar metabolic information with normal cells, making them difficult to be distinguished using mass spectrometry. Herein, we propose a method by treating osteosarcoma cells and normal human osteoblasts with mannose as a stimulant, which greatly promotes the metabolic discrimination of osteosarcoma cells at the single-cell level. The low PMI (mannose 6-phosphate isomerase) level of both osteosarcoma cell lines compared to normal human osteoblasts is the reason for the abnormal metabolic pathway of two osteosarcoma cell lines with mannose treatment. We also found that the level of hexoses-6P in osteosarcoma cells significantly increased after mannose treatment, while no such increase was found in normal human osteoblasts. The proposed method is very meaningful for early diagnosis of cancer.