Machine Learning-Based Integrated Multiomics Characterization of Colorectal Cancer Reveals Distinctive Metabolic Signatures.

The metabolic signature identification of colorectal cancer is critical for its early diagnosis and therapeutic approaches that will significantly block cancer progression and improve patient survival. Here, we combined an untargeted metabolic analysis strategy based on internal extractive electrospray ionization mass spectrometry and the machine learning approach to analyze metabolites in 173 pairs of cancer samples and matched normal tissue samples to build robust metabolic signature models for diagnostic purposes. Screening and independent validation of metabolic signatures from colorectal cancers via machine learning methods (Logistic Regression_L1 for feature selection and eXtreme Gradient Boosting for classification) was performed to generate a panel of seven signatures with good diagnostic performance (the accuracy of 87.74%, sensitivity of 85.82%, and specificity of 89.66%). Moreover, seven signatures were evaluated according to their ability to distinguish between cancer and normal tissues, with the metabolic molecule PC (30:0) showing good diagnostic performance. In addition, genes associated with PC (30:0) were identified by multiomics analysis (combining metabolic data with transcriptomic data analysis) and our results showed that PC (30:0) could promote the proliferation of colorectal cancer cell SW480, revealing the correlation between genetic changes and metabolic dysregulation in cancer. Overall, our results reveal potential determinants affecting metabolite dysregulation, paving the way for a mechanistic understanding of altered tissue metabolites in colorectal cancer and design interventions for manipulating the levels of circulating metabolites.

Predicting effect of anti-PD-1/PD-L1 inhibitors therapy for hepatocellular carcinoma by detecting plasma metabolite based on UHPLC-MS.

Introduction: Anti-PD-1/PD-L1 inhibitors therapy has become a promising treatment for hepatocellular carcinoma (HCC), while the therapeutic efficacy varies significantly among effects for individual patients are significant difference. Unfortunately, specific predictive biomarkers indicating the degree of benefit for patients and thus guiding the selection of suitable candidates for immune therapy remain elusive.no specific predictive biomarkers are available indicating the degree of benefit for patients and thus screening the preferred population suitable for the immune therapy. Methods: Ultra-high-pressure liquid chromatography-mass spectrometry (UHPLC-MS) considered is an important method for analyzing biological samples, since it has the advantages of high rapid, high sensitivity, and high specificity. Ultra-high-pressure liquid chromatography-mass spectrometry (UHPLC-MS) has emerged as a pivotal method for analyzing biological samples due to its inherent advantages of rapidity, sensitivity, and specificity. In this study, potential metabolite biomarkers that can predict the therapeutic effect of HCC patients receiving immune therapy were identified by UHPLC-MS. Results: A partial least-squares discriminant analysis (PLS-DA) model was established using 14 glycerophospholipid metabolites mentioned above, and good prediction parameters (R2 = 0.823, Q2 = 0.615, prediction accuracy = 0.880 and p < 0.001) were obtained. The relative abundance of glycerophospholipid metabolite ions is closely related to the survival benefit of HCC patients who received immune therapy. Discussion: This study reveals that glycerophospholipid metabolites play a crucial role in predicting the efficacy of immune therapy for HCC.

Single Component Organic Photosensitizer with NIR-I Emission Realizing Type-I Photodynamic and GSH-Depletion Caused Ferroptosis Synergistic Theranostics.

Phototheranostic agents have thrived as prominent tools for tumor luminescence imaging and therapies. Herein, a series of organic photosensitizers (PSs) with donor-acceptors (D-A) are elaborately designed and synthesized. In particular, PPR-2CN exhibits stable near infrared-I (NIR-I) emission, excellent free radicals generation and phototoxicity. Experimental analysis and calculations imply that a small singlet-triplet energy gap (ΔES1-T1 ) and large spin-orbit coupling (SOC) constant boost the intersystem crossing (ISC), leading to type-I photodynamic therapy (PDT). Additionally, the specific glutamate (Glu) and glutathione (GSH) consumption abilities of PPR-2CN inhibit the intracellular biosynthesis of GSH, resulting in redox dyshomeostasis and GSH-depletion causing ferroptosis. This work first realizes that single component organic PS could be simultaneously used as a type-I photodynamic agent and metal-free ferroptosis inducer for NIR-I imaging-guided multimodal synergistic therapy.

A new strategy for searching determinants in colorectal cancer progression through whole-part relationship combined with multi-omics.

The high incidence and mortality of colorectal cancer (CRC) and the lack of adequate diagnostic molecules have led to poor treatment outcomes for colorectal cancer, making it particularly important to develop methods to obtain molecular with significant diagnostic effects. Here, we proposed a whole and part study strategy (early-stage colorectal cancer as "part" and colorectal cancer as "whole") to identify specific and co-pathways of change in early-stage and colorectal cancers and to discover the determinants of colorectal cancer development. Metabolite biomarkers discovered in plasma may not necessarily reflect the pathological status of tumor tissue. To explore the determinant biomarkers associated with plasma and tumor tissue in the CRC progression, multi-omics were performed on three phases of biomarker discovery studies (discovery, identification and validation) including 128 plasma metabolomes and 84 tissue transcriptomes. Importantly, we observe that the metabolic levels of oleic acid and FA (18:2) in patients with colorectal cancer were much higher than in healthy people. Finally, biofunctional verification confirmed that oleic acid and FA (18:2) can promote the growth of colorectal cancer tumor cells and be used as plasma biomarkers for early-stage colorectal cancer. We propose a novel research strategy to discover co-pathways and important biomarkers that may be targeted for a potential role in early colorectal cancer, and our work provides a promising tool for the clinical diagnosis of colorectal cancer.

Comparative proteomic analysis of the mitochondria of menstrual stem cells and ovarian cancer cells.

Mitochondrial transplantation is a popular field of research in cell-free therapy. Menstrual stem cells (MenSCs) are potential donor cells for provision of foreign mitochondria. The present study aimed to investigate the potential effects of MenSC-derived mitochondria on ovarian cancer from the perspective of protein expression profiling. MenSCs were harvested from menstrual blood. The mitochondria were isolated from MenSCs and ovarian cancer cell line SKOV3. A label-free mitochondria proteomics and analysis were performed by comparing the protein expression in mitochondria of MenSCs and SKOV3 cells. The differentially expressed proteins with fold-change >2 were analyzed by Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathway and protein domain enrichment, protein interaction networks and parallel reaction monitoring (PRM) analysis. In total, 592 proteins that were found to have increased expression in the mitochondria of MenSCs were analyzed. Functional enrichment analysis revealed these proteins were enriched in metabolism-associated pathway entries including 'oxidative phosphorylation' (OXPHOS) pathway. PRM analysis confirmed that four of 6 candidate proteins in the OXPHOS pathway showed similar increasing trends. The protein domain enrichment analysis showed that domains such as 'thioredoxin domain' were significantly enriched. Based on these findings, it was hypothesized that mitochondria from MenSCs have the potential to enhance progression of ovarian cancer likely mediated by the enrichment of OXPHOS-associated metabolic pathways.

Preparation of Carbon Dots from PET Waste by One-step Hydrothermal Method and its Application in Light Blocking Films and LEDs.

An environmentally friendly PET-based Carbon Dots (PET-CDs) with excellent fluorescence properties were prepared with waste PET bottle, pyromellitic acid and ammonia water as raw materials by one-step hydrothermal method. The preparation mechanism of PET-CDs was as follows: PET first underwent ammonolysis reaction to produce terephthalic acid diamide and ethylene glycol, and then dehydrated and carbonized with pyromellitic acid to form PET-CDs. The as-prepared PET-CDs exhibit excitation-independent emission properties in the range from 340 to 440 nm, and the fluorescence quantum yield is as high as 87.36%. In terms of structure, PET-CDs is a spherical structure with an average particle size of 2.0 nm, and its surface contains carboxyl and amino groups. The PET-CDs were dispersed in a PVA matrix to obtain an light blocking films(LBFs) for 250-450 nm light with excellent properties, and its transparency for 450-700 nm light is good. In addition, PET-CDs was used in the fields of LED, and it was found that the color coordinate for the LED assembled with PET-CDs and 395 nm LED chips is (0.55, 0.44) and the correlated color temperature is 2018 K.

Metabolic-Dysregulation-Based iEESI-MS Reveals Potential Biomarkers Associated with Early-Stage and Progressive Colorectal Cancer.

The application of rapid and accurate diagnostic methods can improve colorectal cancer (CRC) survival rates dramatically. Here, we used a non-targeted metabolic analysis strategy based on internal extractive electrospray ionization mass spectrometry (iEESI-MS) to detect metabolite ions associated with the progression of CRC from 172 tissues (45 stage I/II CRC, 41 stage III/IV CRC, and 86 well-matched normal tissues). A support vector machine (SVM) model based on 10 differential metabolite ions for differentiating early-stage CRC from normal tissues was built with a good prediction accuracy of 92.6%. The biomarker panel consisting of lysophosphatidylcholine (LPC) (18:0) has good diagnostic potential in differentiating early-stage CRC from advanced-stage CRC. We showed that the down-regulation of LPC (18:0) in tumor tissues is associated with CRC progression and related to the regulation of the epidermal growth factor receptor. Pathway analysis showed that metabolic pathways in CRC are related to glycerophospholipid metabolism and purine metabolism. In conclusion, we built an SVM model with good performance to distinguish between early-stage CRC and normal groups based on iEESI-MS and found that LPC (18:0) is associated with the progression of CRC.

Effect of Bletilla striata on the Prevention of Postoperative Peritoneal Adhesions in Abrasion-Induced Rat Model.

Postoperative peritoneal adhesions (PPAs) constitute a common complication of abdominal surgery with a high incidence. Bletilla striata (BS) is an important hemostatic drug used in China for nearly 2000 years. The purpose of this study was to investigate the effect of Bletilla striata on postoperative intestinal adhesion in rats. PPA was induced by cecal wall abrasion, and Bletilla striata was injected to observe its effect on adhesion in rats. The adhesion and inflammation score were assessed through visual observation and histopathologic evaluation. The levels of interleukin-1 (IL-1ß), tumor necrosis factor (TNF-α), and interleukin-17F (IL-17F) in abdominal cavity and interleukin-6 (IL-6) in plasma were measured by enzyme-linked immunosorbent assay (ELISA) at 6 hours, 12 hours, 24 hours, and 1 week after operation. The tissue level of transforming growth factor beta-1 (TGF-ß1) was also determined by ELISA on the seventh day after surgery. The expressions of collagen and TNF-α were, respectively, detected by Masson trichrome staining and immunohistochemical staining. The expression of TGF-ß1 and alpha smooth muscle actin (α-SMA) was detected by Western blot. The result showed that Bletilla striata has obvious preventive effect on PPAs and celiac inflammation of PPAs. Bletilla striata could significantly reduce the level of IL-17F abdominal cavity and IL-6 in plasma. Masson trichrome staining and immunohistochemical staining results showed that Bletilla striata also decreased the expression of TNF-α and collagen. Western blot results showed that Bletilla striata decreased the expression of α-SMA and TGF-ß1. Our results suggest that Bletilla striata decreased the development of abdominal adhesion in abrasion-induced model of rats and reduced the expression of the important substance which increased in PPAs. Bletilla striata can be further studied as a new and cheaper antiadhesive substance.

Dissociative Ionization and Coulomb Explosion of Molecular Bromocyclopropane in an Intense Femtosecond Laser Field.

The dissociative ionization and Coulomb explosion of molecular bromocyclopropane (BCP) has been experimentally investigated by time-of-flight mass spectrum and dc-slice imaging technology. The sliced 2D images, kinetic energy releases and angular distributions of the fragment ions are obtained under the intense femtosecond laser fields (8.0 × 1013⁻2.0 × 1014 W/cm²). The results indicated that the low kinetic energy release (KER) components come from dissociative ionization of BCP⁺, while the high KER components come from Coulomb explosion of BCP2+. The chemical reaction path of BCP⁺ has been calculated by ab initio calculation, furthermore, the C-Br bond cleavage involved Coulomb explosion channels have been revealed, and the corresponding dehydrogenation mechanism has been confirmed.

From Graphite to Graphene Oxide and Graphene Oxide Quantum Dots.

Many methods have been reported for synthesizing graphene oxide (GO) and graphene oxide quantum dots (GOQDs) where a tedious operational procedure and long reaction time are generally required. Herein, a facile one-pot solvothermal method that allows selective synthesis of pure GO and pure GOQDs, respectively is demonstrated. What is more, the final product of either GO or differently sized GOQDs can be easily controlled by adjusting the reaction temperatures or reactant ratios, which is also feasible when enlarged to gram scale. The 2.5 nm GOQDs show excellent photoluminescence that can be utilized for bioimaging or distinctive detection of Eu3+ and Tb3+ from their respective mixtures with other rare earth and/or transition metal ions, at sub-ppm level.

Near infrared spectroscopy coupled with radial basis function neural network for at-line monitoring of Lactococcus lactis subsp. fermentation.

In our previous work, partial least squares (PLSs) were employed to develop the near infrared spectroscopy (NIRs) models for at-line (fast off-line) monitoring key parameters of Lactococcus lactis subsp. fermentation. In this study, radial basis function neural network (RBFNN) as a non-linear modeling method was investigated to develop NIRs models instead of PLS. A method named moving window radial basis function neural network (MWRBFNN) was applied to select the characteristic wavelength variables by using the degree approximation (Da) as criterion. Next, the RBFNN models with selected wavelength variables were optimized by selecting a suitable constant spread. Finally, the effective spectra pretreatment methods were selected by comparing the robustness of the optimum RBFNN models developed with pretreated spectra. The results demonstrated that the robustness of the optimal RBFNN models were better than the PLS models for at-line monitoring of glucose and pH of L. lactis subsp. fermentation.

Design and implementation of an intelligent belt system using accelerometer.

Activity monitor systems are increasing used recently. They are important for athletes and casual users to manage physical activity during daily exercises. In this paper, we use a triaxial accelerometer to design and implement an intelligent belt system, which can detect the user's step and flapping motion. In our system, a wearable intelligent belt is worn on the user's waist to collect activity acceleration signals. We present a step detection algorithm to detect real-time human step, which has high accuracy and low complexity. In our system, an Android App is developed to manage the intelligent belt. We also propose a protocol, which can guarantee data transmission between smartphones and wearable belt effectively and efficiently. In addition, when users flap the belt in emergency, the smartphone will receive alarm signal sending by the belt, and then notifies the emergency contact person, which can be really helpful for users in danger. Our experiment results show our system can detect physical activities with high accuracy (overall accuracy of our algorithm is above 95%) and has an effective alarm subsystem, which is significant for the practical use.

Bi2MoO6 nanobelts for crystal facet-enhanced photocatalysis.

γ-Bi2MoO6 single-crystal nanobelts with dominant {010} facets exhibit facet-enhanced photocatalytic property for the photodegradation of dye pollutants under visible light irradiation. The charge carriers are more efficiently separated on the low-index facets due to the exposure of more photoactive sites to the reacting substrates.

Rare Earth Ion-Doped Upconversion Nanocrystals: Synthesis and Surface Modification.

The unique luminescent properties exhibited by rare earth ion-doped upconversion nanocrystals (UCNPs), such as long lifetime, narrow emission line, high color purity, and high resistance to photobleaching, have made them widely used in many areas, including but not limited to high-resolution displays, new-generation information technology, optical communication, bioimaging, and therapy. However, the inherent upconversion luminescent properties of UCNPs are influenced by various parameters, including the size, shape, crystal structure, and chemical composition of the UCNPs, and even the chosen synthesis process and the surfactant molecules used. This review will provide a complete summary on the synthesis methods and the surface modification strategies of UCNPs reported so far. Firstly, we summarize the synthesis methodologies developed in the past decades, such as thermal decomposition, thermal coprecipitation, hydro/solvothermal, sol-gel, combustion, and microwave synthesis. In the second part, five main streams of surface modification strategies for converting hydrophobic UCNPs into hydrophilic ones are elaborated. Finally, we consider the likely directions of the future development and challenges of the synthesis and surface modification, such as the large-scale production and actual applications, stability, and so on, of the UCNPs.