Research Progress of Novel Inorganic Nanomaterials in the Diagnosis and Treatment of Alzheimer's Disease.

The global increase in the number of Alzheimer's disease (AD) patients has posed numerous treatment challenges. Six Food and Drug Administration-approved medications (e.g.

The role of SIRT1 in kidney diseases.

SIRT1, a nicotinamide adenine dinucleotide (NAD +)-dependent class III histone deacetylase, exhibits a high level of expression within renal tissues. It has garnered considerable recognition for its pivotal role in modulating signaling pathways intricately linked with the aging process; however, it extends beyond this in the organism. The literature reports that SIRT1 regulates biological processes such as glucose metabolism, lipid metabolism, oxidative stress, inflammation, autophagy, endoplasmic reticulum stress, and apoptosis.

Establishment of an Efficient -Mediated Genetic Transformation System to Enhance the Tolerance of the Paraquat Stress in Engineering Goosegrass ( L.).

(goosegrass) is a problematic weed worldwide known for its multi-herbicide tolerance/resistance biotype. However, a genetic transformation method in goosegrass has not been successfully established, making a bottleneck for functional genomics studies in this species. Here, we report a successful -mediated transformation method for goosegrass.

Role of household waste, governance quality, and greener energy for public health: Evidence from developed economies.

In the current times, the global economies and international organizations declared that pollution is one of the prominent causes of declined human health. Still, most literature is biased toward economic sustainability and ignores such vital issues. The current study tends to identify the factors affecting public health in the Group of Seven economies except for Italy (G6).

Role of Environmental Degradation, Institutional Quality, and Government Health Expenditures for Human Health: Evidence From Emerging Seven Countries.

The current study investigates the association of various economic, non-economic, governance, and environmental indicators on human health for seven emerging economies. Covering the period from 2000Q1 to 2018Q1, this study uses various panel data approaches for empirical estimations. The data is found first-order stationary.

Differences of endogenous polyamines and putative genes associated with paraquat resistance in goosegrass (Eleusine indica L.).

Background: Paraquat is one of the most effective herbicides used to control weeds in agricultural management, while the pernicious weed goosegrass (Eleusine indica) has evolved resistance to herbicides, including paraquat. Polyamines provide high-level paraquat resistance in many plants. In the present study, we selected three polyamines, namely, putrescine, spermidine, and spermine, as putative genes to investigate their correlation with paraquat resistance by using paraquat-resistant (R) and paraquat-susceptible (S) goosegrass populations.

A Multi-year Beneficial Effect of Seed Priming with Gibberellic Acid-3 (GA) on Plant Growth and Production in a Perennial Grass, Leymus chinensis.

Seed priming is a widely used technique in crops to obtain uniform germination and high-quality seedlings. In this study, we found a long-term effect of seed priming with gibberellic acid-3 (GA) on plant growth and production in Leymus chinensis. Seeds were germinated on agar plates containing 0-200 μM GA, and the germinated seedlings were transplanted to clay planting pots and grown for about one year.

Enrichment of serum biomarkers by magnetic metal-organic framework composites.

Highly efficient extraction of peptides from serum is critical for finding serum biomarkers using mass spectrometry, which still remains a great challenge. Currently, a bottom-up proteomics approach has been applied to discover serum biomarkers. However, the approach was labor intensive, time and cost consuming, and cannot meet the requirements for clinical application.

Rapid Isolation of Phenol Degrading Bacteria by Fourier Transform Infrared (FTIR) Spectroscopy.

Phenol is an important chemical engineering material and ubiquitous in industry wastewater, its existence has become a thorny issue in many developed and developing country. More and more stringent standards for effluent all over the world with human realizing the toxicity of phenol have been announced. Many advanced biological methods are applied to industrial wastewater treatment with low cost, high efficiency and no secondary pollution, but the screening of function microorganisms is certain cumbersome process.

Biocompatible chiral monolithic stationary phase synthesized via atom transfer radical polymerization for high performance liquid chromatographic analysis.

Novel biocompatible chiral monolithic stationary phase was prepared by reverse and direct atom transfer radical polymerization (ATRP) methods. By taking advantages of the controlled/living property of ATRP method, the chiral monolith was prepared by reverse ATRP (RATRP) firstly. An attractive feature of RATRP is the prepared polymer containing a terminal radically transferable atom that can initiate another post-polymerization reaction by direct ATRP.

Emerging enantiomeric resolution materials with homochiral nano-fabrications.

The major scientific challenge of enantiomeric separation is to develop simple, rapid, and sensitive routine analytical methods. Generally, enantio-resolution is still based on "three-point interaction" theory, which indicates that homochiral sites are needed for enantio-selective interaction. However, in recent years, advanced materials with precise homochiral fabrication at the nanoscale have been synthesized, and have shown great potential in development of high-throughput enantio-resolution methods.

Synthesis of magnetic framework composites for the discrimination of Escherichia coli at the strain level.

Rapid and efficient characterization and identification of pathogens at the strain level is of key importance for epidemiologic investigations, which still remains a challenge. In this work, solvothermically Fe3O4-COOH@MIL-101 composites were fabricated by in situ crystallization approach. The composites combine the excellent properties of both chromium (III) terephthalate (MIL-101) and carboxylic-functionalized magnetite (Fe3O4-COOH) particles and possess the efficient peptides/proteins enrichment properties and magnetic responsiveness.

Restricted access chiral stationary phase synthesized via reversible addition-fragmentation chain-transfer polymerization for direct analysis of biological samples by high performance liquid chromatography.

Novel hydrophilic microparticles containing β-cyclodextrin (β-CD) were prepared via one-pot synthesis using reversible addition-fragmentation chain-transfer (RAFT) precipitation polymerization, a "controlled/living" radical polymerization technique. The polymerization was initiated by hydrophilic macromolecular chain-transfer agent [poly(2-hydroxyethyl methacrylate), PHEMA]. The hydrophilic PHEMA on the surface of microparticles can well improve their surface hydrophilicity and lead to their biological compatibility.

[Application of SVR in quantitative analysis of wines].

Fourier transform infrared spectroscopy has been widely used in some related fields, thus induces the rapid development of quantitative analysis method based on Lambert-Beer's Law and chemometrics in recent years. The selection of appropriate pre-processing method and calibration model is extremely crucial to the quantitative analysis. The present paper selected 30 wine samples and used infrared spectroscopy combined with vector regression algorithm SVR quantitative analysis model with standard normal variate, baseline correction and outliers elimination to analyze four representative components of wine.

An improved ensemble partial least squares for analysis of near-infrared spectra.

Traditional ensemble regression algorithms such as BAgging Partial Least Squares (BAPLS) and BOosting Partial Least Squares (BOPLS) do not perform very well in the data set that is relatively small or contaminated by random noise. To make the method robust and improve its prediction ability, inspired from bias-variance-covariance decomposition, we propose an improved ensemble partial least squares method based on the diversity. The new method is applied to quantitative analysis of Near InfraRed (NIR) data sets.

Baseline correction combined partial least squares algorithm and its application in on-line Fourier transform infrared quantitative analysis.

In order to eliminate the lower order polynomial interferences, a new quantitative calibration algorithm "Baseline Correction Combined Partial Least Squares (BCC-PLS)", which combines baseline correction and conventional PLS, is proposed. By embedding baseline correction constraints into PLS weights selection, the proposed calibration algorithm overcomes the uncertainty in baseline correction and can meet the requirement of on-line attenuated total reflectance Fourier transform infrared (ATR-FTIR) quantitative analysis. The effectiveness of the algorithm is evaluated by the analysis of glucose and marzipan ATR-FTIR spectra.

[SVM-based qualitative analysis of Muscat Hamburg wine produced in Tianjin region].

The purpose was to achieve the identification of Muscat Hamburg wines produced in Tianjin region through scanning and analyzing dry white wine samples of different grape varieties and regions by infrared spectroscopy technology. A support vector machine (SVM) based method was introduced to analyze infrared spectra of dry white wines. The pretreatment processes of the IR spectra were also elaborated, including baseline adjustment, noise Elimination, standard normalization and eliminating the main component of abnormal sample points.

Asymmetric least squares for multiple spectra baseline correction.

In this paper, based on asymmetric least squares smoothing, a new algorithm for multiple spectra baseline correction is proposed. By means of the similarity among the multiple spectra, the algorithm estimates the baselines by penalizing the differences in the baseline corrected signals, which makes the algorithm possible to eliminate scatter effects on the spectra. In addition, a relaxation factor which measures the similarity of the baseline corrected spectra is incorporated into the optimization model and an alternate iteration strategy is used to solve the optimization problem.

[Analysis of liquor flavor spectra and pattern recognition computation].

Chinese liquor is a complex mixture and contains a large amount of microconstituents, which affects the quality and flavor of liquor. In order to discriminate liquor flavors rapidly, the spectra of liquors were obtained by FTIR and employed as the input patterns of pattern classification algorithms, then liquor flavor discrimination models were built. This paper introduces liquor flavor pattern recognition algorithms comprehensively and systematically for the first time, and the algorithms contain statistical classifications (linear discriminant function, quadratic discriminant function, regularized discriminant analysis, and K nearest neighbor), prototype learning algorithm (learning vector quantization), support vector machine and adaboost algorithm.