Research on the Effect and Mechanism of Selenium on Colorectal Cancer Through TRIM32.

The intake of selenium (Se) in the human body is negatively correlated with the risk of colorectal cancer (CRC), but its mechanism in the occurrence and development of CRC is not clear. This study aimed to evaluate the therapeutic effect of Se on CRC, and explore the anti-tumor effect of Se supplementation on CRC and its molecular mechanism. In this study, we utilized colony formation assay, cell scratch test, Transwell migration, and flow cytometry to assess cell proliferation, migration, and apoptosis. Our findings demonstrate that Se effectively suppresses the growth and proliferation of CRC cell lines HCT116 and SW480 and promoting cellular apoptosis. In vivo experiments demonstrated a significant inhibitory effect of Se on tumor growth. CRC-related datasets were extracted from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases for differential expression analysis of TRIM32 and survival analysis. We found that TRIM32 was highly expressed in tumor tissues of CRC patients and correlated with a poor prognosis. Furthermore, through RNA sequencing analysis, we identified TRIM32 as a gene that was significantly decreased after Se treatment in HCT116 cells. This finding was subsequently validated by Western blot results. Moreover, TRIM32 knockdown combined with Se treatment significantly inhibited cell growth proliferation and migration and further induced apoptosis of colorectal cancer cells. In conclusion, our findings provided evidence that Se inhibited the growth of colorectal cancer cells by down-regulating TRIM32.

Association between predicted fat mass, predicted lean mass, predicted percent fat and type 2 diabetes mellitus in Japanese adults: a retrospective study.

BACKGROUND: Type 2 diabetes mellitus (T2DM) is known to have obesity as a risk factor. Body mass index cannot distinguish between lean mass and fat mass. We aimed to examine the association between predicted fat mass, predicted lean mass, predicted percent fat and risk of T2DM in Japanese adults. We also explored whether these three new parameters could predict T2DM better than other obesity markers. METHODS: This present study is a secondary data analysis. The study enrolled 20,944 Japanese individuals who participated in the NAGALA medical assessment program between 2004 and 2015. 15,453 participants who are eligible and have complete information were included to our analysis. Through the use of Kaplan-Meier curve, restricted cubic spline and univariate and multivariate Cox regression analysis, the relationship between predicted fat mass, predicted lean mass, predicted percent fat and T2DM risk was examined. The area under the curve method was used to assess the differences between these markers of obesity. RESULTS: A total of 373 cases of T2DM occurred over a median time of 5.4 years. In the male group, we found a U-shaped connection between predicted fat mass, predicted lean mass, and T2DM onset (p value, non-linearity < 0.05). A linear relationship was found between predicted percent fat and T2DM onset. The linear relationship was also found in the female group for predicted fat mass, and predicted percent fat. And for women, predicted lean mass was not an independent predictor. The area under the curve (AUC) for predicted fat mass, predicted lean mass, predicted percent fat in men was 0.673 (95%CI: 0.639 ~ 0.707), 0.598 (95%CI: 0.561 ~ 0.635), 0.715 (95%CI: 0.684 ~ 0.745), respectively. In males, WHtR was the strongest predictor (AUC 0.7151, 95%CI: 0.684 ~ 0.746), followed by predicted percent fat (AUC 0.7150, 95%CI: 0.684 ~ 0.745). In the females, WHtR was also the strongest predictor (AUC 0.758, 95%CI: 0.703 ~ 0.813), followed by body mass index (AUC 0.757, 95%CI: 0.704 ~ 0.811) and predicted percent fat (AUC 0.742, 95%CI: 0.687 ~ 0.798). CONCLUSION: Predicted fat mass, predicted lean mass, predicted percent fat were strongly connected with an increased risk for developing T2DM in Japanese, particularly in males. WHtR and predicted percent fat had a slightly better discrimination than other common obesity indicators in males. In the females, predicted fat mass and predicted percent fat were associated with T2DM risk, WHtR and body mass index had the slightly higher predictive power.

The application of improved densenet algorithm in accurate image recognition.

Image recognition technology belongs to an important research field of artificial intelligence. In order to enhance the application value of image recognition technology in the field of computer vision and improve the technical dilemma of image recognition, the research improves the feature reuse method of dense convolutional network. Based on gradient quantization, traditional parallel algorithms have been improved. This improvement allows for independent parameter updates layer by layer, reducing communication time and data volume. The introduction of quantization error reduces the impact of gradient loss on model convergence. The test results show that the improvement strategy designed by the research improves the model parameter efficiency while ensuring the recognition effect. Narrowing the learning rate is conducive to refining the updating granularity of model parameters, and deepening the number of network layers can effectively improve the final recognition accuracy and convergence effect of the model. It is better than the existing state-of-the-art image recognition models, visual geometry group and EfficientNet. The parallel acceleration algorithm, which is improved by the gradient quantization, performs better than the traditional synchronous data parallel algorithm, and the improvement of the acceleration ratio is obvious. Compared with the traditional synchronous data parallel algorithm and stale synchronous parallel algorithm, the optimized parallel acceleration algorithm of the study ensures the image data training speed and solves the bottleneck problem of communication data. The model designed by the research improves the accuracy and training speed of image recognition technology and expands the use of image recognition technology in the field of computer vision.Please confirm the affiliation details of [1] is correct.The relevant detailed information in reference [1] has been confirmed to be correct.

Schiff base functionalized dialdehyde starch for enhanced removal of Cu (II): Preparation, performances, DFT calculations.

Dialdehyde starch modified by 2-hydrazinopyridine (HYD-DAS) based on the reaction of dialdehyde starch (DAS) and 2-hydrazinopyridine was synthesized and characterized by FT-IR spectra, element analysis and SEM. HYD-DAS can efficiently adsorb Cu (II) ion to demonstrate visual color changes from yellow to dark brown in aqueous solutions. The influence on HYD-DAS to Cu (II) adsorption including pH value of solution, isotherm, kinetics, thermodynamics and possible mechanism had also been examined. Batch experiments indicate that HYD-DAS's to Cu (II) adsorption reaches equilibrium within 250 min, and its adsorption capacity and rate are 195.75 mg/g and 98.63 %, respectively. Moreover, HYD-DAS to Cu (II) adsorption remains robust and underscoring after five cycles to exhibit good selectivity and reusability. Kinetics studies suggest the absorption process follows a quasi-second-order with isotherms aligning to the Langmuir monolayer model, and thermodynamics reveals that it is a spontaneous endothermic nature of adsorption. Based on the analyses of XPS and DFT calculations, a possible mechanism for HYD-DAS to Cu (II) adsorption is that Cu (II) combined with nitrogen atoms from Schiff base and hydrazine pyridine ring in HYD-DAS.

The Examination of Peroxidase-Positive Leukocytes in Semen.

Leukocytospermia can lead to decreased spermatozoa motility, increased spermatozoa morphological abnormalities, elevated spermatozoa DNA fragmentation index, impairment of the spermatozoa acrosome function, and even affected embryonic development. It is a common andrological disease in clinical practice and one of the important causes of male infertility. When determining whether male reproductive tract inflammation exists, andrologists often choose to examine round cells or seminal plasma elastase in the semen as a clinical diagnostic basis. However, the examination of round cells is easily influenced by sloughed spermatogenic cells and reproductive tract epithelial cells, which do not contribute to reducing the indiscriminate and unnecessary use of antibiotics. At the same time, the detection process of elastase is relatively complicated, time-consuming, and slow in reporting results, which is not beneficial for early diagnosis and treatment of diseases such as male genital tract infections (MGTIs). We have innovatively applied the examination of peroxidase-positive leukocytes in semen assisted by a computer-assisted semen analysis (CASA) system as a diagnostic criterion for leukocytospermia, successfully solving these problems. This examination only requires the addition of the operating fluid consisting of four reagents into the specimen, and the total reaction time at room temperature can be controlled within 20-30 min. With the subsequent smear and microscopic examination, the concentration of peroxidase-positive leukocytes in semen can be obtained within a total of 60 min, which can be used to diagnose whether the inflammation of the male reproductive tract existed.

6,6'-Diheptyl-3,3'-bis-[(pyridin-3-yl)ethyn-yl]-5H,5'H-di-pyrrolo-[1,2-b:1',2'-g][2,6]naphthyridine-5,5'-dione.

The complete mol-ecule of the title compound, C42H42N4O2, is generated by a crystallographic centre of symmetry. The pendant heptyl chains adopt extended conformations and the dihedral angle between the pyrrole and pyridine rings is 8.18 (15)°. In the crystal, the mol-ecules are arranged in columnar stacks propagating in the [010] direction via slipped aromatic π-π stacking inter-actions.

Codelivery of Que and BCL-2 siRNA with Lipid-Copolymer Hybrid Nanocomplexes for Efficient Tumor Regression.

The efficacy of chemotherapy is often reduced due to the chemotherapy resistance of tumor cells, which is usually caused by abnormal gene overexpression. Herein, multifunctional nanocomplexes (Que/siBCL2@BioMICs) were developed to deliver quercetin (Que) and BCL-2 siRNA (siBCL2) to synergistically inhibit tumor growth. The nanocomplexes were composed of an amphiphilic triblock copolymer of poly(ethylene glycol) methyl ether methacrylate-poly[2-(dimethylamino) ethyl acrylate]-polycaprolactone (PEGMA-PDMAEA-PCL) and 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-poly(ethylene glycol)-biotin (DSPE-PEG-biotin). Que was encapsulated into the cores through hydrophobic interactions, while negatively charged siBCL2 was loaded through electrostatic interactions. The nanocomplexes could effectively facilitate cellular uptake via biotin-mediated active targeting and cytosolic release of cargos by the "proton sponge effect" of PDMAEA. Que/siBCL2@BioMICs achieved enhanced cytotoxicity and anti-metastasis activity due to a synergistic effect of Que and siBCL2 in vitro. More importantly, superior anti-tumor efficacy was observed in orthotopic 4T1 tumor-bearing mice with reduced primary tumor burden and lung metastatic nodules, while no obvious side effects to major organs were observed. In conclusion, the biotin-targeted nanocomplexes with chemotherapeutic and nucleotide agent entrapment provide a promising strategy for efficient triple-negative breast cancer (TNBC) therapy.

System to screen and purify active ingredients from herbal medicines using hydrogel-modified human umbilical vein endothelial cell membrane chromatography coupled with semi-preparative high-performance liquid chromatography-offline-high-performance liquid chromatography-mass spectrometry.

Analytical screening and validation systems based on a combination of cell membrane chromatography and two-dimensional chromatography-tandem mass spectrometry are incapable of providing prepared samples containing the active ingredients found in traditional Chinese medicine; therefore, these samples cannot be directly used in subsequent studies. In this study, a semi-preparative cell membrane chromatography column was developed using a hydrogel-modified carrier and human umbilical vein endothelial cells to optimize prepared conditions, such as hydrogel polymerization, cell fragmentation, and cell membrane volume. This increased the binding ratio of membrane protein and carrier to 15.79 mg/g. The column was systematically evaluated using multitarget tyrosine kinase inhibitors that displayed good specificity and reproducibility. Subsequently, using the column coupled with a semi-preparative high-performance liquid chromatography-offline-high-performance liquid chromatography-mass spectrometry system, 15 active ingredients were screened and purified from Indigo naturalis, and five main components were identified: l-lysine, oxyresveratrol, tryptanthrin, isorhamnetin, and indirubin. Furthermore, the pharmacological effects of the ingredients were confirmed using cell proliferation and apoptosis assays. Results revealed potent proliferation-inhibiting and apoptosis-promoting abilities on human chronic myelogenous leukemic cells and human promyelocytic leukemic cells (p < 0.001). Overall, the system presented screening and purification functions that could be used to prepare I. naturalis samples acting on the epidermal growth factor receptor and vascular endothelial cell growth factor.

Exploring the target and molecular mechanism of Astragalus membranaceus in the treatment of vascular cognitive impairment based on network pharmacology and molecular docking.

Astragalus membranaceus (AM) is a traditional Chinese herbal medicine extensively utilized in vascular cognitive impairment (VCI) treatment. However, due to the complex components of AM, its exact molecular mechanism remains unclear. Therefore, this study investigated the target and molecular mechanism of AM to treat VCI based on network pharmacology and molecular docking. Firstly, the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, STITCH, and SwissTargetPrediction were utilized to gather the primary active ingredients of AM. The potential therapeutic targets of VCI were collected through GeneCards, OMIM, and DisGeNET databases. Secondly, the protein-protein interaction network was built using the STRING database. The enrichment analysis of gene ontology and the Kyoto Encyclopedia of Genes and Genome pathways was carried out in the R language. Finally, The network topology calculation of Cytoscape software was combined with module analysis to predict the binding properties of its active ingredients and targets. Twenty effective compounds and 733 targets were screened from AM, among which 158 targets were seen as possible targets of AM to treat VCI. MAPK3 and MMP9 were the critical targets of AM intervention in VCI. The crucial pathways include PI3K/Akt, MAPK, Rap1, and Ras signaling pathways. Besides, calycosin and quercetin might be the potential active compounds of AM for VCI treatment. AM intervenes in VCI through a multi-ingredient, multi-target, and multi-pathway coordination mechanism. These findings provide a foundation for a deeper understanding of the molecular mechanisms by which AM is effective in treating VCI.

Characteristics and health risk assessment of volatile N-nitrosamines in the plasma of adults in Guangdong Province, China.

N-nitrosamines are strong carcinogens that are widely present in the environment. This study developed a method, and analyzed the concentrations of volatile N-nitrosamines (VNAs) in the plasma of adults in Guangdong Province, China. Finally, the health risks to adults in Guangdong Province, China, with dietary exposure to VNAs were assessed. Gas chromatography/mass spectrometry (GC/MS) in electron impact (EI) ionization source mode was used to quantitatively analyze VNAs, and to perform accurate mass determination. The lower limit of detection (LOD) of nine nitrosamines are ranged from 0.01 to 2.14 ng/mL. The recovery rate ranged from 83 % to 116 %, and the relative standard deviation (RSD) was < 10 %. The method developed is simple, rapid, and provides good reproducibility and high sensitivity. N-nitrosodimethylamine (NDMA), N-nitrosomethylethylamine (NMEA), N-nitrosodinbutylamine (NDBA), N-nitrosopiperidine (NPIP), N-nitrosopyrrolidine (NPYR), N-nitrosomorpholine (NMOR) and N-nitrosodiphenylamine (NDPhA) were detected in 92 adult plasma samples. NDMA and NMEA were detected in 56.5 % and 44.6 % of the samples, followed by NPIP (34.8 %). NDMA had the highest median concentration (43.7 ng/mL) in the total samples. There were gender-related differences found in the concentrations of NDBA and NDPhA. The exposure risk assessment results showed that the two highest daily dietary intakes of VNAs were N-nitrosodi-n-propylamine (NDPA) and NDMA, and aquatic products and pickled vegetables contributed the most total nitrosamine intake. The lifetime cancer risk of adults ranged from 2.88 × 10-10 to 7.46 × 10-5, and the risk associated with NDMA, NDPA, N-nitrosodiethylamine (NDEA), NMEA and NPIP are important and should attract more attention. This study aimed to explore the exposure levels of VNAs in the plasma of adults in Guangdong Province, China, and to assess the health risks of dietary intake of VNAs, which provides a basis of the effect of VNAs exposure on human health.

Oil pollutant identification based on excitation-emission matrix of UV-induced fluorescence and deep convolutional neural network.

Identifying the types of oil pollutants in a spill event can help determine the source of spill and formulate the plan of emergency responses. Excitation-emission matrix (EEM), which is also called three-dimensional fluorometric spectra, includes abundant spectral information in the domain of excitation wavelength and can be potentially applied to identify oil types. UV-induced fluorometric experiments were conducted in this study to collect EEMs for five types of oil that are commonly used in maritime transportation. A deep convolutional neural network (CNN) model for oil types identification was built based on the classic VGG-16 model. According to the identification results, the model was able to provide a reasonable classification on the five types of oil used in the experiments. Additionally, a biased classification result was observed in the experiment: the model was able to provide the most accurate classification on 0W40 lubricant but encounters difficulty distinguishing between - 10# diesel and 92# gasoline. The potential reasons for this result and the approaches to improve the model were also discussed.

Prediction Method of Soft Fault and Service Life of DC-DC-Converter Circuit Based on Improved Support Vector Machine.

A data-driven prediction method is proposed to predict the soft fault and estimate the service life of a DC-DC-converter circuit. First, based on adaptive online non-bias least-square support-vector machine (AONBLSSVM) and the double-population particle-swarm optimization (DP-PSO), the prediction model of the soft fault is established. After analyzing the degradation-failure mechanisms of multiple key components and considering the influence of the co-degradation of these components over time on the performance of the circuit, the output ripple voltage is chosen as the fault-characteristic parameter. Finally, relying on historical output ripple voltages, the prediction model is utilized to gradually deduce the predicted values of the fault-characteristic parameter; further, in conjunction with the circuit-failure threshold, the soft fault and the service life of the circuit can be predicted. In the simulation experiment, (1) a time-series prediction is made for the output ripple voltage using the model proposed herein and the online least-square support-vector machine (OLS-SVM). Comparative analyses of fitting-assessment indicators of the predicted and experimental curves confirm that our model is superior to OLS-SVM in both modeling efficiency and prediction accuracy. (2) The effectiveness of the service life prediction method of the circuit is verified.

Experimental Analysis on the Optimal Excitation Wavelength for Fine-Grained Identification of Refined Oil Pollutants on Water Surface Based on Laser-Induced Fluorescence.

Laser-induced fluorescence (LIF) is an effective and all-weather oil spill identification method that has been widely applied for oil spill monitoring. However, the distinguishability on oil types was seldom considered while selecting the excitation wavelengths. This study is intended to find the optimal excitation wavelength for fine-grained classification of refined oil pollutants using LIF by comparing the distinguishability of fluorometric spectra under various excitation wavelengths on some typical types of refined oil samples. The results show that the fluorometric spectra of oil samples significantly vary under different excitation wavelengths, and the four types of oil applied in this study are most likely to be distinguished under the excitation wavelengths of 395 nm and 420 nm. This study is expected to improve the ability of oil types identification using LIF method without increasing time or other cost, and also provide theoretical basis for the development of portable LIF devices for oil spill types identification.

Matrine-Family Alkaloids: Versatile Precursors for Bioactive Modifications.

Matrine-family alkaloids as tetracycloquinolizindine analogues from Traditional Chinese Medicine Sophora flavescens Ait, Sophora subprostrata and Sophora alopecuroides L possess various pharmacological activities and have aroused great interests over the past decades. Especially, a lot of matrine derivatives have been designed and synthesized and their biological activities investigated, and encouraging results have continuously been achieved in recent several years. These studies are helpful to develop more potent candidates or therapeutic agents and disclose their molecular targets and mechanisms. This paper reviews recent advances in the bioactive modifications of matrine-family alkaloids from derivatization of the C-13, C-14 or C-15 position, opening D ring, fusing D ring and structural simplification.

Preparation of immobilized lipase on magnetic nanoparticles dialdehyde starch.

Dialdehyde starch (DAS) is a kind of modified starch which contains many active aldehyde groups and has good biocompatibility. In this study, magnetic dialdehyde starch nanoparticles were successfully used to immobilize lipase. The lipase was immobilized onto magnetic nanoparticles by using DAS instead of glutaraldehyde as a crosslinker. The parameters like DAS dosage, enzyme concentration and immobilization time were optimized. Enzymatic properties studies exhibited that after DAS cross-linking, the storage stability of the immobilized enzyme reached 82.5%, and the recycling rate reached 53.6%, whereas in case of glutaraldehyde cross linker, it was 79.4% and 46.8%, the former also exhibited better stability and durability. Compared with the free enzyme, the immobilized enzyme indicated higher acid-base tolerance and thermal stability, and had good enzymatic properties. Magnetic dialdehyde starch nanoparticles may have application prospects as an excellent enzyme carrier, which provides a reference for the preparation of other immobilized enzymes with excellent performance.

Tertiary Enamides: Versatile and Available Substrates in Synthetic Chemistry.

BACKGROUND: Enamines and their variant enamides as powerful and versatile synthons have attracted great attention in synthetic chemistry. Enamides display unique stability and reduce enaminic reactivity in view of the electron-withdrawing effect of N-acyl group. A great deal of satisfactory achievements in the synthesis and application of enamides has been made in recent years. Especially, tertiary enamides without N-H bond regarded as low reactivity of compounds in the past can act as excellent nucleophiles to react with electrophiles for the construction of various nitrous molecules. OBJECTIVE: This review focuses on recent advances on tertiary enamides in the synthetic strategies and applications including addition, coupling reaction, functionalization and electro- or photo-chemical reaction. CONCLUSION: Tertiary enamides as electron-deficient nucleophiles display a satisfactory balance between stability and reactivity to offer multiple opportunities for the construction of various functionalized nitrogencontaining compounds. Further exploration of the reactive mechanisms involved tertiary enamides and the development of novel and efficient transformations to generate ever more complex building blocks starting from tertiary enamides are particularly worth pursuing.

Structural Modifications of Matrine-Type Alkaloids.

Matrine-type alkaloids belong to quinolizidine analogues from Sophora flavescens Ait, Sophora subprostrata and Sophora alopecuroides L. possess numerous therapeutic properties and have attracted continuous attention over the past few decades. In order to improve the activities and amplify their applicants, many matrine-type derivatives have synthesized and evaluated for their biological activities in recent years. These structural modifications have resulted in stronger activities and improvement of the pharmacokinetic properties. The structure and activity relation studies based on matrine- type semi-synthetic derivatives have immensely contributed to the understanding of their mechanism of actions and molecular targets. This review mainly summarizes recent progress in the structural modifications of matrine-type alkaloids based on the alteration of C-13 or C-14 position, opening D ring, fusing D ring and structural simplification.

Oxidatively rearranged cycloartane triterpenoids from the seeds of Pseudolarix amabilis.

One novel and eight known oxidatively rearranged cycloartane triterpenoids were isolated from the seeds of Pseudolarix amabilis. The structure of the new isolate was elucidated on extensive spectroscopic analyses. Results indicated that pseudolarolide Q (4) exhibited strong antimicrobial activity against Gram-positive Staphylococcus aureus and Candida albicans at the MICs of 6.08 and 24.32 µM, respectively. Pseudolarolide I (2) showed the 11ß-HSD1 inhibitory property at the IC50 value of 34.5 nM.

Rhein functionalized magnetic chitosan as a selective solid phase extraction for determination isoflavones in soymilk.

A new solid-phase extraction mode was developed for separation some flavones from the complex interference system. In the experiment, rhein anchored on magnetic chitosan microparticles, prepared facilely without removal of the template molecule, was used as sorbents for the extraction of target analytes; after completion of the extraction process, Fe3O4 particles acted as carrier to retrieve rhein functionalized magnetic chitosan microparticles (RMCMPs) from the sample solution. RMCMPs showed excellent selective adsorption capacity of isoflavones. The result suggested that the method was useful for fast determination and quantification of isoflavones in soymilk. The RMCMPs were characterized by scanning electron microscope (SEM), X-ray diffraction (XRD) and Fourier transforms infrared spectrometer (FTIR).