Factors impacting the behavior of phytoremediation in pesticide-contaminated environment: A meta-analysis.

Phytoremediation provides substantial advantages, including eco-friendliness, cost-effectiveness, efficiency, and visual appeal. However, the current knowledge of the factors influencing phytoremediation in pesticide-contaminated environments remains limited. It is critical to understand phytoremediation and the factors affecting the variation in removal efficiency. In this study, we compiled 72 previous research articles to quantify plant-induced improvements in removal efficiency and identify factors that influence variations in phytoremediation behavior through meta-analysis. We observed a significant increase in the removal efficiency of phytoremediation compared to the control group which did not involve phytoremediation. Pesticides significantly affect removal efficiency in terms of their modes of action, substance group, and properties. Plants demonstrated higher efficiency in remediating environments contaminated with pesticides possessing lower molecular masses and log Kow values. Plant species emerged as a crucial determinant of variations in removal efficiency. Annual plants exhibited a 1.45-fold higher removal efficiency than perennial plants. The removal efficiencies of different plant types decreased in the following order: agri-food crops > aquatic macrophytes > turfgrasses > medicinal plants > forage crops > woody trees. The Gramineae family, which was the most prevalent, demonstrated a robust and consistent phytoremediation ability. This study offers a more comprehensive triangular relationship between removal efficiency, pesticides, and plants, expanding the traditional linear model. Our findings offer valuable insights into the behavior of phytoremediation in pesticide-contaminated environments and the factors determining its success, ultimately guiding further research toward developing strategies for higher removal efficiency in phytoremediation.

Proteomic investigation and biomarker identification of lung and spleen deficiency syndrome in HIV/AIDS immunological nonresponders.

Background: Human immunodeficiency virus (HIV) and acquired immune deficiency syndrome (AIDS) immunological nonresponders (HIV/AIDS-INRs) whose CD4+ cell counts do not rebound after highly active antiretroviral therapy (HAART) treatment usually experience severely impaired immune function and high mortality. Traditional Chinese medicine (TCM) has many advantages in the field of AIDS, especially its promotion of patients' immune reconstitution. Accurate differentiation of TCM syndromes is a prerequisite for guiding an effective TCM prescription. However, the objective and biological evidence for identification of the TCM syndromes in HIV/AIDS-INRs remains lacking. Lung and spleen deficiency (LSD) syndrome, a typical HIV/AIDS-INR syndrome, was examined on in this study. Methods: We first performed a proteomic study of LSD syndrome in INRs (INRs-LSD) using tandem mass tag combined with liquid chromatography-tandem mass spectrometry (TMT-LC-MS/MS) and screened them against the healthy and undocumented identifiable groups. The TCM syndrome-specific proteins were subsequently validated based on bioinformatics analysis and enzyme-linked immunosorbent assay (ELISA). Results: A total of 22 differentially expressed proteins (DEPs) were screened in INRs-LSD compared to the healthy group. Based on bioinformatic analysis, these DEPs were found to be mainly associated with the immunoglobin A (IgA)-generated intestinal immune network. In addition, we examined the TCM syndrome-specific proteins alpha-2-macroglobulin (A2M) and human selectin L (SELL) with ELISA and found that they were both upregulated, which was consistent with the proteomic screening results. Conclusions: A2M and SELL were finally identified as potential biomarkers for INRs-LSD, providing a scientific and biological basis for identifying typical TCM syndromes in HIV/AIDS-INRs and an opportunity to build a more effective TCM treatment system for HIV/AIDS-INRs.

Epidemiological investigation and proteomic profiling of typical TCM syndrome in HIV/AIDS immunological nonresponders.

HIV/AIDS pandemic remains the world's most severe public health challenge, especially for HIV/AIDS immunological nonresponders (HIV/AIDS-INRs), who tend to have higher mortality. Due to the advantages in promoting patients' immune reconstitution, Traditional Chinese medicine (TCM) has become one of the mainstays of complementary treatments for HIV/AIDS-INRs. Given that effective TCM treatments largely depend on precise syndrome differentiation, there is an increasing interest in exploring biological evidence for the classification of TCM syndromes in HIV/AIDS-INRs. In our study, to identify the typical HIV/AIDS-INRs syndrome, an epidemiological survey was first conducted in the Liangshan prefecture (China), a high HIV/AIDS prevalence region. The key TCM syndrome, Yang deficiency of spleen and kidney (YDSK), was evaluated by using a tandem mass tag combined with liquid chromatography-tandem mass spectrometry (TMT-LC-MS/MS). A total of 62 differentially expressed proteins (DEPs) of YDSK syndrome compared with healthy people were screened out. Comparative bioinformatics analyses showed that DEPs in YDSK syndrome were mainly associated with response to wounding and acute inflammatory response in the biological process. The pathway annotation is mainly enriched in complement and coagulation cascades. Finally, the YDSK syndrome-specific DEPs such as HP and S100A9 were verified by ELISA, and confirmed as potential biomarkers for YDSK syndrome. Our study may lay the biological and scientific basis for the specificity of TCM syndromes in HIV/AIDs-INRs, and may provide more opportunities for the deep understanding of TCM syndromes and the developing more effective and stable TCM treatment for HIV/AIDS-INRs.

Genome-scale screening of drug-target associations relevant to Ki using a chemogenomics approach.

The identification of interactions between drugs and target proteins plays a key role in genomic drug discovery. In the present study, the quantitative binding affinities of drug-target pairs are differentiated as a measurement to define whether a drug interacts with a protein or not, and then a chemogenomics framework using an unbiased set of general integrated features and random forest (RF) is employed to construct a predictive model which can accurately classify drug-target pairs. The predictability of the model is further investigated and validated by several independent validation sets. The built model is used to predict drug-target associations, some of which were confirmed by comparing experimental data from public biological resources. A drug-target interaction network with high confidence drug-target pairs was also reconstructed. This network provides further insight for the action of drugs and targets. Finally, a web-based server called PreDPI-Ki was developed to predict drug-target interactions for drug discovery. In addition to providing a high-confidence list of drug-target associations for subsequent experimental investigation guidance, these results also contribute to the understanding of drug-target interactions. We can also see that quantitative information of drug-target associations could greatly promote the development of more accurate models. The PreDPI-Ki server is freely available via: http://sdd.whu.edu.cn/dpiki.

LC-DAD-APCI-MS-based screening and analysis of the absorption and metabolite components in plasma from a rabbit administered an oral solution of danggui.

A valid chromatographic fingerprint method using liquid chromatography-diode array detection-atmospheric pressure chemical ionization mass spectrometry in negative mode (LC-DAD-APCI-MS) is proposed for studying the absorption and metabolites of a traditional Chinese medicine (TCM) Angelica sinensis (danggui) in rabbit plasma, after the rabbit is administered with danggui oral solution (DOS). More than thirty-two common components were detected in both DOS and rabbit plasma, which shows that the components in the DOS were absorbed into the body of the rabbit. Of these, senkyunolide I, senkyunolide H, Z-6,7-epoxyligustilide, 3-butylidene-7-hydroxyphthalide, Z-ligustilide, Z-butylidenephthalide, Diels-Alder dimers of ligustilide, linolenic acid, linoleic acid and falcarindiol were tentatively identified from their MS, UV spectra and retention behavior by comparing the results with the published literature. At least ten components were found in rabbit plasma but not in DOS, indicating that these components must be metabolites of some of the components in the original extract. The results prove that the proposed method can be used to rapidly analyze multiple constituents in TCMs, and to screen for bioactive compounds by comparing and contrasting the chromatographic fingerprints of DOS and plasma samples.