Crystalline Phase Engineering to Modulate the Interfacial Interaction of the Ruthenium/Molybdenum Carbide for Acidic Hydrogen Evolution.

Ruthenium (Ru) is an ideal substitute to commercial Pt/C for the acidic hydrogen evolution reaction (HER), but it still suffers from undesirable activity due to the strong adsorption free energy of H* (ΔGH*). Herein, we propose crystalline phase engineering by loading Ru clusters on precisely prepared cubic and hexagonal molybdenum carbide (α-MoC/ß-Mo2C) supports to modulate the interfacial interactions and achieve high HER activity. Advanced spectroscopies demonstrate that Ru on ß-Mo2C shows a lower valence state and withdraws more electrons from the support than that of Ru on α-MoC, indicative of a strong interfacial interaction. Density functional theory reveals that the ΔGH* of Ru/ß-Mo2C approaches 0 eV, illuminating an enhancement mechanism at the Ru/ß-Mo2C interface. The resultant Ru/ß-Mo2C exhibits an encouraging performance in a proton exchange membrane water electrolyzer with a low cell voltage (1.58 V@ 1.0 A cm-2) and long stability (500 h@ 1.0 A cm-2).

Accurate and High-Resolution Particle Mass Measurement Using a Peak Filtering Algorithm.

Charge detection quadrupole ion trap mass spectrometry (CD-QIT MS) is an effective way of achieving the mass analysis of microparticles with ultrahigh mass. However, its mass accuracy and resolution are still poor. To enhance the performance of CD-QIT MS, the resolution Rpeak of each peak in the mass spectra resulting from an individual particle was assessed, and a peak filtering algorithm that can filter out particle adducts and clusters with a lower Rpeak was proposed. By using this strategy, more accurate mass information about the analyzed particles could be obtained, and the mass resolution of CD-QIT MS was improved by nearly 2-fold, which was demonstrated by using the polystyrene (PS) particle size standards and red blood cells (RBCs). Benefiting from these advantages of the peak filtering algorithm, the baseline separation and relative quantification of 3 and 4 µm PS particles were achieved. To prove the application value of this algorithm in a biological system, the mass of yeast cells harvested at different times was measured, and it was found that the mixed unbudded and budded yeast cells, which otherwise would not be differentiable, were distinguished and quantified with the algorithm.

Desorption Separation Ionization Mass Spectrometry (DSI-MS) for Rapid Analysis of COVID-19.

During the coronavirus disease 2019 (COVID-19) pandemic, which has witnessed over 772 million confirmed cases and over 6 million deaths globally, the outbreak of COVID-19 has emerged as a significant medical challenge affecting both affluent and impoverished nations. Therefore, there is an urgent need to explore the disease mechanism and to implement rapid detection methods. To address this, we employed the desorption separation ionization (DSI) device in conjunction with a mass spectrometer for the efficient detection and screening of COVID-19 urine samples. The study encompassed patients with COVID-19, healthy controls (HC), and patients with other types of pneumonia (OP) to evaluate their urine metabolomic profiles. Subsequently, we identified the differentially expressed metabolites in the COVID-19 patients and recognized amino acid metabolism as the predominant metabolic pathway involved. Furthermore, multiple established machine learning algorithms validated the exceptional performance of the metabolites in discriminating the COVID-19 group from healthy subjects, with an area under the curve of 0.932 in the blind test set. This study collectively suggests that the small-molecule metabolites detected from urine using the DSI device allow for rapid screening of COVID-19, taking just three minutes per sample. This approach has the potential to expand our understanding of the pathophysiological mechanisms of COVID-19 and offers a way to rapidly screen patients with COVID-19 through the utilization of machine learning algorithms.

Global synthesis on the response of soil microbial necromass carbon to climate-smart agriculture.

Climate-smart agriculture (CSA) supports the sustainability of crop production and food security, and benefiting soil carbon storage. Despite the critical importance of microorganisms in the carbon cycle, systematic investigations on the influence of CSA on soil microbial necromass carbon and its driving factors are still limited. We evaluated 472 observations from 73 peer-reviewed articles to show that, compared to conventional practice, CSA generally increased soil microbial necromass carbon concentrations by 18.24%. These benefits to soil microbial necromass carbon, as assessed by amino sugar biomarkers, are complex and influenced by a variety of soil, climatic, spatial, and biological factors. Changes in living microbial biomass are the most significant predictor of total, fungal, and bacterial necromass carbon affected by CSA; in 61.9%-67.3% of paired observations, the CSA measures simultaneously increased living microbial biomass and microbial necromass carbon. Land restoration and nutrient management therein largely promoted microbial necromass carbon storage, while cover crop has a minor effect. Additionally, the effects were directly influenced by elevation and mean annual temperature, and indirectly by soil texture and initial organic carbon content. In the optimal scenario, the potential global carbon accrual rate of CSA through microbial necromass is approximately 980 Mt C year-1, assuming organic amendment is included following conservation tillage and appropriate land restoration. In conclusion, our study suggests that increasing soil microbial necromass carbon through CSA provides a vital way of mitigating carbon loss. This emphasizes the invisible yet significant influence of soil microbial anabolic activity on global carbon dynamics.

Recent advances in entirely hand-held ionization sources for mass spectrometry.

Ambient ionization mass spectrometry (AIMS) has been developing explosively since its first debut. The ionization process was hence able to be achieved under atmospheric pressure, facilitating on-site field analysis in a variety of areas, such as clinical diagnosis, metabolic phenotyping, and surface analysis. As part of the ambitious goal of making MS a general device that can be used in everyday life, lots of efforts have been paid to miniaturize the ionization source. This review discusses avant-garde sources that could be entirely hand-held without any accessories. The structure and applications of the devices are described in detail as well. They could be expediently used in real-time and on-site analysis, presenting a great future potential for the routinizing of MS.

A rapidly reversible mutation generates subclonal genetic diversity and unstable drug resistance.

Most genetic changes have negligible reversion rates. As most mutations that confer resistance to an adverse condition (e.g., drug treatment) also confer a growth defect in its absence, it is challenging for cells to genetically adapt to transient environmental changes. Here, we identify a set of rapidly reversible drug-resistance mutations in Schizosaccharomyces pombe that are caused by microhomology-mediated tandem duplication (MTD) and reversion back to the wild-type sequence. Using 10,000× coverage whole-genome sequencing, we identify nearly 6,000 subclonal MTDs in a single clonal population and determine, using machine learning, how MTD frequency is encoded in the genome. We find that sequences with the highest-predicted MTD rates tend to generate insertions that maintain the correct reading frame, suggesting that MTD formation has shaped the evolution of coding sequences. Our study reveals a common mechanism of reversible genetic variation that is beneficial for adaptation to environmental fluctuations and facilitates evolutionary divergence.

Epimedium Linn: A Comprehensive Review of Phytochemistry, Pharmacology, Clinical Applications and Quality Control.

Epimedium genus is a traditional Chinese medicine, which has functions of tonifying kidney and yang, strengthening tendons and bones, dispelling wind and emoving dampness. It is mainly used for the treatment of impotence and spermatorrhea, osteoporosis, Parkinson's, Alzheimer's, and cardiovascular diseases. The aim of this review is to provide a systematic summary of the phytochemistry, pharmacology, and clinical applications of the Epimedium Linn. In this paper, the relevant literature on Epimedium Linn. was collected from 1987 to the present day, and more than 274 chemical constituents, including flavonoids, phenylpropanoids, lignans, phenanthrenes, and others, were isolated from this genus. Modern pharmacological studies have shown that Epimedium Linn. has osteoprotective, neuroprotective, cardiovascular protective, and immune enhancing pharmacological effects. In addition, Epimedium Linn. has been commonly used to treat osteoporosis, erectile dysfunction, hypertension and cardiovascular disease. In this paper, the distribution of resources, chemical compositions, pharmacological effects, clinical applications and quality control of Epimedium Linn. are progressed to provide a reference for further research and development of the resources of this genus.

Curcumae Radix: A Review of Traditional Use, Phytochemistry, Pharmacology, Toxicology and Quality Control.

Curcumae Radix (CuR) is a traditional Chinese medicine that has been used in China for more than 1,000 years. It has the traditional efficacy of activating blood and relieving pain, promoting qi and relieving depression, clearing heart and cooling blood, and promoting gallbladder and removing jaundice. Based on this, many domestic and foreign scholars have conducted systematic studies on its chemical composition, pharmacological effects, toxicity and quality control. Currently, 250 compounds, mainly including terpenoids and curcuminoids, have been isolated and identified from CuR, which has pharmacological activities, including antitumor, anti-inflammatory and analgesic, antidepressant, hepatoprotective, hemostatic, hematopoietic, and treatment of diabetes mellitus. In modern clinical practice, CuR is widely used in the treatment of tumors, breast hyperplasia, hepatitis, and stroke. However, the generation of toxicity and clinical application of CuR and Caryophylli Flos, the determination of the concoction process of artifacts, the determination of specific Quality Marker, and the establishment of the quality control system of CuR, are problems that need to be solved urgently at present.

FvMYB108, a MYB Gene from Fragaria vesca, Positively Regulates Cold and Salt Tolerance of Arabidopsis.

MYB (myoblast) protein comes in large quantities and a wide variety of types and plays a role in most eukaryotes in the form of transcription factors (TFs). One of its important functions is to regulate plant responses to various stresses. However, the role of MYB TFs in regulating stress tolerance in strawberries is not yet well understood. Therefore, in order to investigate the response of MYB family members to abiotic stress in strawberries, a new MYB TF gene was cloned from Fragaria vesca (a diploid strawberry) and named FvMYB108 based on its structural characteristics and evolutionary relationships. After a bioinformatics analysis, it was determined that the gene belongs to the R2R3-MYB subfamily, and its conserved domain, phylogenetic relationships, predicted protein structure and physicochemical properties, subcellular localization, etc. were analyzed. After qPCR analysis of the expression level of FvMYB108 in organs, such as the roots, stems, and leaves of strawberries, it was found that this gene is more easily expressed in young leaves and roots. After multiple stress treatments, it was found that the target gene in young leaves and roots is more sensitive to low temperatures and salt stimulation. After these two stress treatments, various physiological and biochemical indicators related to stress in transgenic Arabidopsis showed corresponding changes, indicating that FvMYB108 may be involved in regulating the plant's ability to cope with cold and high-salt stress. Further research has found that the overexpression of this gene can upregulate the expression of AtCBF1, AtCOR47, AtERD10, and AtDREB1A related to low-temperature stress, as well as AtCCA1, AtRD29a, AtP5CS1, and AtSnRK2.4 related to salt stress, enhancing the ability of overexpressed plants to cope with stress.

Effects of soil physicochemical environment on the plasticity of root growth and land productivity in maize soybean relay strip intercropping system.

BACKGROUND: Soil is a key foundation of crop root growth. There are interactions between root system and soil in multiple ways. The present study aimed to further explore the response of root distribution and morphology to soil physical and chemical environment under maize (Zea mays L.) soybean (Glycine Max L. Merr.) relay strip intercropping (MS) An experiment was carried out aiming to examine the effects of nitrogen (N) applications and interspecific distances on root system and soil environment in MS. The two N application levels, referred to as no N application (NN) and conventional N application (CN), were paired with different interspecific distances: 30, 45 and 60 cm (MS30, MS45 and MS60) and 100 cm of monoculture maize and soybean (MM/SS100). RESULTS: The results demonstrated that MS45 increased the distribution of soil aggregates (> 2 mm) near the crop roots and maize soil nutrients status, which increased by 20.3% and 15.6%. Meanwhile, MS reduced soil bulk density, increased soil porosity and improved soil oxygen content. Optimization of the soil environment facilitated root growth. The MS45 achieved a better result on root distribution and morphology than the other configuration and also increased land productivity. CONCLUSION: Relay intercropped soybean with maize in interspecific row spacing of 45 cm, improved soil physicochemical environment, reshaped root architecture and optimized root spatial distribution of crops to achieve greater land productivity. © 2024 Society of Chemical Industry.

Pocket-Size Wireless Nanoelectrospray Ionization Mass Spectrometry for Metabolic Analysis of Salty Biofluids and Single Cells.

Analysis of volume-limited biological samples such as single cells and biofluids not only benefits clinical purposes but also promotes fundamental research in life sciences. Detection of these samples, however, imposes strict requirements on measurement performance because of the minimal volume and concentrated salts of the samples. Herein, we developed a self-cleaning nanoelectrospray ionization device powered by a pocket-size "MasSpec Pointer" (MSP-nanoESI) for metabolic analysis of salty biological samples with limited volume. The self-cleaning effect induced by Maxwell-Wagner electric stress helps with keeping the borosilicate glass capillary tip free from clogging and thus increasing salt tolerance. This device possesses a high sample economy (about 0.1 µL per test) due to its pulsed high voltage supply, sampling method (dipping the nanoESI tip into analyte solution), and contact-free electrospray ionization (ESI) (the electrode does not touch the analyte solution during ESI). High repeatable results could be acquired by the device with a relative standard deviation (RSD) of 1.02% for voltage output and 12.94% for MS signals of caffeine standard. Single MCF-7 cells were metabolically analyzed directly from phosphate buffered saline, and two types of untreated cerebrospinal fluid from hydrocephalus patients were distinguished with 84% accuracy. MSP-nanoESI gets rid of the bulky apparatus and could be held in hand or put into one's pocket for transportation, and it could operate for more than 4 h without recharge. We believe this device will boost scientific research and clinical usage of volume-limited biological samples with high-concentration salts in a low-cost, convenient, and rapid manner.

Isolation of three MiDi19-4 genes from mango, the ectopic expression of which confers early flowering and enhances stress tolerance in transgenic Arabidopsis.

MAIN CONCLUSION: Three Di19-4 genes were identified in mango. Overexpression of MiDi19-4B in A. thaliana promoted earlier flowering and enhanced drought, salt, and ABA resistance. Drought-induced protein 19 (Di19) is a drought-induced protein that is mainly involved in multiple stress responses. Here, three Di19-4 genes (MiDi19-4A/B/C) in mango (Mangifera indica L.) were identified, and the coding sequences (CDS) had lengths of 684, 666, and 672 bp and encoded proteins with 228, 222, and 224 amino acids, respectively. The promoters of the MiDi19-4 genes contained phytohormone-, light-, and abiotic stress-responsive elements. The MiDi19-4 genes were expressed in every tissue and highly expressed in leaves. Moreover, MiDi19-4 genes were highly correlated with the vegetative growth period and induced by polyethylene glycol (PEG) or salt stress. MiDi19-4B displayed the highest expression during the vegetative growth period and then showed decreased expression, and MiDi19-4B was highly expressed at both the late stage of the vegetative growth period and the initial stage of the flowering induction period. The 35S::GFP-MiDi19-4B fusion protein was located in the cell nucleus. The transgenic plants ectopically expressing MiDi19-4B exhibited earlier flowering and increased expression patterns of FRUITFULL (AtFUL), APETALA1 (AtAP1), and FLOWERING LOCUS T (AtFT). The drought and salt tolerance of MiDi19-4B transgenic plants was significantly increased, and these plants showed decreased sensitivity to abscisic acid (ABA) and considerably increased expression levels of drought- and salt-related genes and ABA signalling pathway genes. Additionally, bimolecular fluorescence complementation (BiFC) experiments revealed that the MiDi19-4B protein interacted with CAULIFLOWER (MiCAL1), MiCAL2, MiAP1-1, and MiAP1-2. Taken together, these results highlighted the important regulatory roles of MiDi19-4B in tolerance to multiple abiotic stresses and in flowering.

A meta-analysis on morphological, physiological and biochemical responses of plants with PGPR inoculation under drought stress.

Plant growth-promoting rhizobacteria (PGPR) can help plants to resist drought stress. However, the mechanisms of how PGPR inoculation affect plant status under drought remain incompletely understood. We performed a meta-analysis of plant response to PGPR inoculation by compiling data from 57 PGPR-inoculation studies, including 2, 387 paired observations on morphological, physiological and biochemical parameters under drought and well-watered conditions. We compare the PGPR effect on plants performances among different groups of controls and treatments. Our results reveal that PGPR enables plants to restore themselves from drought-stressed to near a well-watered state, and that C4 plants recover better from drought stress than C3 plants. Furthermore, PGPR is more effective underdrought than well-watered conditions in increasing plant biomass, enhancing photosynthesis and inhibiting oxidant damage, and the responses of C4 plants to the PGPR effect was stronger than that of C3 plants under drought conditions. Additionally, PGPR belonging to different taxa and PGPR with different functional traits have varying degrees of drought-resistance effects on plants. These results are important to improve our understanding of the PGPR beneficial effects on enhanced drought-resistance of plants.

Automatic prediction of hepatic arterial infusion chemotherapy response in advanced hepatocellular carcinoma with deep learning radiomic nomogram.

OBJECTIVES: Hepatic arterial infusion chemotherapy (HAIC) using the FOLFOX regimen (oxaliplatin plus fluorouracil and leucovorin) is a promising option for advanced hepatocellular carcinoma (Ad-HCC). As identifying patients with Ad-HCC who would obtain objective response (OR) to HAIC preoperatively remains a challenge, we aimed to develop an automatic and non-invasive model for predicting HAIC response. METHODS: A total of 458 patients with Ad-HCC who underwent HAIC were retrospectively included from three hospitals (310 for training, 77 for internal validation, and 71 for external validation). The deep learning and radiomic features were extracted from the automatically segmented liver region on contrast-enhanced computed tomography images. Then, a deep learning radiomic nomogram (DLRN) was constructed by integrating deep learning scores, radiomic scores, and significant clinical variables with multivariate logistic regression. Model performance was assessed by AUC and Kaplan-Meier estimator. RESULTS: After automatic segmentation, only a few modifications were needed (less than 30 min for 458 patients). The DLRN achieved an AUC of 0.988 in the training cohort, 0.915 in the internal validation cohort, and 0.896 in the external validation cohort, respectively, outperforming other models in HAIC response prediction. Moreover, survival risk stratification was also successfully performed by the DLRN. The overall survival (OS) of the predictive OR group was significantly longer than that of the predictive non-OR group (median OS: 26.0 vs. 12.3 months, p < 0.001). CONCLUSIONS: The DLRN provided a satisfactory performance for predicting HAIC response, which is essential to identify Ad-HCC patients for HAIC and may potentially benefit personalized pre-treatment decision-making. CLINICAL RELEVANCE STATEMENT: This study presents an accurate and automatic method for predicting response to hepatic arterial infusion chemotherapy in patients with advanced hepatocellular carcinoma, and therefore help in defining the best candidates for this treatment. KEY POINTS: • Deep learning radiomic nomogram (DLRN) based on automatic segmentation of CECT can accurately predict hepatic arterial infusion chemotherapy (HAIC) response of advanced HCC patients. • The proposed prediction model can perform survival risk stratification and is an easy-to-use tool for personalized pre-treatment decision-making for advanced HCC patients.

Screening of hepatocellular carcinoma via machine learning based on atmospheric pressure glow discharge mass spectrometry.

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors with a high mortality rate. The diagnosis of HCC is currently based on alpha-fetoprotein detection, imaging examinations, and liver biopsy, which are expensive or invasive. Here, we developed a cost-effective, time-saving, and painless method for the screening of HCC via machine learning based on atmospheric pressure glow discharge mass spectrometry (APGD-MS). Ninety urine samples from HCC patients and healthy control (HC) participants were analyzed. The relative quantification data were utilized to train machine learning models. Neural network was chosen as the best classifier with a classification accuracy of 94%. Besides, the levels of eleven urinary carbonyl metabolites were found to be significantly different between HCC and HC, including glycolic acid, pyroglutamic acid, acetic acid, etc. The possible reasons for the regulation were tentatively proposed. This method realizes the screening of HCC via potential urine metabolic biomarkers based on APGD-MS, bringing a hopeful point-of-care diagnosis of HCC in a patient-friendly manner.

A Review of Extraction and Purification, Biological Properties, Structure-Activity Relationships and Future Prospects of Schisandrin C: A Major Active Constituent of Schisandra Chinensis.

Since ancient times, China has used natural medicine as the primary way to combat diseases and has a rich arsenal of natural medicines. With the progress of the times, the extraction of bioactive molecules from natural drugs has become the new development direction for natural medicines. Among the numerous natural drugs, Schisandrin C (Sch C), derived from Schisandra Chinensis (Turcz.) Baill. It has excellent potential for development and has been shown to possess various pharmacological properties, including hepatoprotective, antitumor and anti-inflammatory activities. Based on the biological properties of hepatoprotection, scholars have explored Sch C and its synthetic products in depth; some studies have shown that pentosidine has the effect of improving the symptoms of liver fibrosis and reducing the concentration of alanine transaminase (ALT) and aspartate aminotransferase (AST) in the serum of rats, which is an essential inspiration for the development of anti-liver fibrosis drugs. But more in vivo and ex vivo studies still need to be included. This paper focuses on Sch C's extraction and synthesis, biological activities and drug development progress. The future application prospects of Sch C are discussed to perfect its development work further.

[Phenolic derivatives from root bark of Schisandra sphenanthera].

This paper aimed to study the chemical constituents from the root bark of Schisandra sphenanthera. Silica, Sephadex LH-20 and RP-HPLC were used to separate and purify the 80% ethanol extract of S. sphenanthera. Eleven compounds were identified by ~1H-NMR, ~(13)C-NMR, ESI-MS, etc., which were 2-[2-hydroxy-5-(3-hydroxypropyl)-3-methoxyphenyl]-propane-1,3-diol(1), threo-7-methoxyguaiacylglycerol(2),4-O-(2-hydroxy-1-hydroxymethylethyl)-dihydroconiferylalcohol(3), morusin(4), sanggenol A(5), sanggenon I(6), sanggenon N(7), leachianone G(8),(+)-catechin(9), epicatechin(10), and 7,4'-dimethoxyisoflavone(11). Among them, compound 1 was a new compound, and compounds 2-9 were isolated from S. sphenanthera for the first time. Compounds 2-11 were subjected to cell viability assay, and the results revealed that compounds 4 and 5 had potential cytotoxicity, and compound 4 also had potential antiviral activity.

[Chemical constituents of Helleborus thibetanus].

The chemical constituents of Helleborus thibetanus were isolated and purified by silica gel column chromatography, Sephadex LH-20 gel column chromatography, and semi-preparative RP-HPLC, and the structures of all compounds were identified by modern spectrographic technology(MS, NMR). The MTT method was used to measure the cytotoxicity of compounds 1-8. Twelve compounds were isolated from the roots and rhizomes of H. thibetanus and were identified as(25R)-22ß,25-expoxy-26-[(O-ß-D-glucopyranosyl)oxy]-1ß,3ß-dihydroxyfurosta-5-en(1), ß-sitosterol myristate(2), ß-sitosterol lactate(3), ß-sitosterol 3-O-ß-D-glucopyrannoside(4), 4,6,8-trihydroxy-3,4-dihydronaphthalen-1(2H)-one(5), 1,3,5-trimethoxybenzene(6), 7,8-dimethylbenzo pteridine-2,4(1H,3H)-dione(7), 1H-indole-3-carboxylic acid(8), p-hydroxy cinnamic acid(9), lauric acid(10), n-butyl α-L-arabinofuranoside(11) and methyl-α-D-fructofuranoside(12), respectively. Among them, compound 1 is a new compound and named thibetanoside L; compounds 2, 5-8, 11 are first isolated from the family Ranunculaceae; compound 12 is isolated from the genus Helleborus for the first time. The results of MTT assay showed that the IC_(50) values of compounds 1-8 against HepG2 and HCT116 cells were greater than 100 µmol·L~(-1).

High Speed Mass Measurement of a Single Metal-Organic Framework Nanocrystal in a Paul Trap.

Mass spectrometry (MS) has emerged as an excellent tool for the characterization of metal-organic frameworks (MOFs) based on the characteristic metal ions and organic ligands. Mass measurement of intact MOF nanocrystals, however, remains a challenge for MS technology. Here, we reported the development of a probe particles based charge detection-quadrupole ion trap mass spectrometry (probe CD-QIT MS) method, where charge detection and mass measurement of a single MOF nanocrystal were achieved under the assistance of probe particles of micrometer size. As a validation of the method, the masses of a series of polystyrene (PS) size standards from 493 nm to 1.6 µm were measured with 3 µm PS particles as probes, and the measured masses were found to match well with their certified masses. Then, charge detections and mass analysis of single ZIF-8 and GOx@ZIF-8 with a size around 600 nm were achieved successfully. The method presented here demonstrates simplicity, high speed, and accuracy. Notably, it allows quantitative measurement of the amount of immobilized GOx enzyme by using the mass difference between ZIF-8 and GOx@ZIF-8. In addition, based on the determined mass, the size analysis of these MOF particles with irregular shape was carried out and demonstrated to be complementary to transmission electron microscopy (TEM).

Biofluids Metabolic Profiling Based on PS@Fe3O4-NH2 Magnetic Beads-Assisted LDI-MS for Liver Cancer Screening.

Liver cancer (LC) is the third frequent cause of death worldwide, so early diagnosis of liver cancer patients is crucial for disease management. Herein, we applied NH2-coated polystyrene@Fe3O4 magnetic beads (PS@Fe3O4-NH2 MBs) as a matrix material in laser desorption/ionization mass spectrometry (LDI-MS). Rapid, sensitive, and selective metabolic profiling of the native biofluids was achieved without any inconvenient enrichment or purification. Then, based on the selected m/z features, LC patients were discriminated from healthy controls (HCs) by machine learning, with the high area under the curve (AUC) values for urine and serum assessments (0.962 and 0.935). Moreover, initial-diagnosed and subsequent-visited LC patients were also differentiated, which indicates potential applications of this method in early diagnosis. Furthermore, among these identified compounds by FT-ICR MS, the expression level of some metabolites changed from HCs to LCs, including 29 and 12 characteristic metabolites in human urine and serum samples, respectively. These results suggest that PS@Fe3O4-NH2 MBs-assisted LDI-MS coupled with machine learning is feasible for LC clinical diagnosis.