WDR1 promotes prostate cancer progression through Wnt/ß-catenin signaling.

Prostate cancer (PCa) is the second most common cancer and the fifth leading cause of cancer-related death among men. A comprehensive understanding of PCa progression is crucial for the development of innovative therapeutic strategies for its treatment. While WDR1 (WD-repeat domain 1) serves as a significant cofactor of actin-depolymerizing factor/cofilin, its role in PCa progression remains unknown. In this study, we demonstrated that knockdown of WDR1 in various PCa cells substantially inhibited cell proliferation, migration, and invasion in vitro, as confirmed at both the cellular and molecular levels. Moreover, the overexpression of WDR1 promoted PCa cell proliferation and metastasis in vitro. Mechanistically, we showed that the application of lithium chloride, an activator of the Wnt/ß-Catenin signaling pathway, restored the suppressive effects of WDR1 deficiency on cell proliferation and migration in PCa cells. Our findings suggest that the WDR1-ß-Catenin axis functions as an activator of the malignant phenotype and represents a promising therapeutic target for PCa treatment.

High-Performance Thin-Layer Chromatography Coupled with Single Quadrupole: Application the Identification and Differentiation of Rehmanniae Radix and Its Different Processing Products from Raw Materials to Commercial Products.

The authentication of ingredients in formulas is crucial yet challenging, particularly for constituents with comparable compositions but vastly divergent efficacy. Rehmanniae Radix and its derivatives are extensively utilized in food supplements, which contain analogous compositions but very distinct effects. Rehmanniae Radix, also a difficult-to-detect herbal ingredient, was chosen as a case to explore a novel HPTLC-QDa MS technique for the identification of herbal ingredients in commercial products. Through systematic condition optimization, including thin layer and mass spectrometry, a stable and reproducible HPTLC-QDa MS method was established, which can simultaneously detect oligosaccharides and iridoids. Rehmannia Radix and its processed products were then analyzed to screen five markers that could distinguish between raw and prepared Rehmannia Radix. An HPTLC-QDa-SIM method was further established for formula detection by using the five markers and validated using homemade prescriptions and negative controls. Finally, this method was applied to detect raw and prepared Rehmannia Radix in 12 commercial functional products and supplements.

Comprehensive HRMS Screening and Risk Assessments of Aristolochic Acid Analogues in Asari Radix et Rhizoma and Related Commercial Health Products.

Aristolochic acid analogues (AAAs) are well-known toxins. We performed the first comprehensive screening on AAAs in Asari Radix et Rhizoma (underground part of Asarum heterotropoides Schmidt), the only Aristolochiaceae plant widely used in clinical practice. LC-HRMS revealed 70 trace AAAs using polygonal mass defect filtering and precursor ion list strategies, 38 of which were newly discovered in A. heterotropoides. UHPLC-QTrap-MS/MS was then utilized for quantitative/semiquantitative analysis of 26 abundant compounds. Seventeen AAAs were detected from 91 batches of A. heterotropoides and 20 AAAs from 166 consumable products. For 141 Asari-containing proprietary products, aristolactam I and aristolactam II-glucoside exhibited the widest distribution, present in 98% products. AA IVa was the most abundant, detected in 91%. Notably, 60% of the products contained AA I (0.03-0.79 ppm). The safety was assessed using linear extrapolation, permitted daily exposure, cumulative amount, and the margin of exposure. It is recommended that AA I content be limited to 3 ppm.

Intelligent chemical profiling of 73 edible flowers by liquid chromatography-high resolution mass spectrometry combined with HRMS database and their authentication based on large-scale fingerprints.

A commercial high-resolution MS database "TCM-PCDL" was innovatively introduced to automatically identify multi-components in 73 edible flowers rapidly and accurately by liquid chromatography-high resolution mass spectrometry, which can be time-consuming and labor-intensive in traditional manual method. The database encompasses over 2565 natural products with various energy levels. Unknown compounds can be identified through direct matching and scoring MS2 spectra with database. A total of 870 compounds were identified from 73 flowers, with polyphenols constituting up to 75%. Focusing on polyphenols, a high performance liquid chromatography (HPLC) method was developed to generate fingerprints from 510 batches, establishing an "HPLC database" that enabled accurate authentication using similarity scores and rankings. This method demonstrated an accuracy rate of 100% when applied to 30 unknown samples. For flowers prone to confusion, additional statistical analysis methods could be employed as aids in authentication. This study provides valuable insights for large-scale sample chemical profiling and authentication.

Depletion of CPNE7 sensitizes colorectal cancer to 5-fluorouracil by downregulating ATG9B expression.

We aimed to explore the biological function of CPNE7 and determine the impact of CPNE7 on chemotherapy resistance in colorectal cancer (CRC) patients. According to the Gene Expression Profiling Interactive Analysis database and previously published data, CPNE7 was identified as a potential oncogene in CRC. RT-qPCR and Western blotting were performed to verify the expression of CPNE7. Chi-square test was used to evaluate the associations between CPNE7 and clinical features. Cell proliferation, colony formation, cell migration and invasion, cell cycle and apoptosis were assessed to determine the effects of CPNE7. Transcriptome sequencing was used to identify potential downstream regulatory genes, and gene set enrichment analysis was performed to investigate downstream pathways. The effect of CPNE7 on 5-fluorouracil chemosensitivity was verified by half maximal inhibitory concentration (IC50). Subcutaneous tumorigenesis assay was used to examine the role of CPNE7 in sensitivity of CRC to chemotherapy in vivo. Transmission electron microscopy was used to detect autophagosomes. CPNE7 was highly expressed in CRC tissues, and its expression was correlated with T stage and tumour site. Knockdown of CPNE7 inhibited the proliferation and colony formation of CRC cells and promoted apoptosis. Knockdown of CPNE7 suppressed the expression of ATG9B and enhanced the sensitivity of CRC cells to 5-fluorouracil in vitro and in vivo. Knockdown of CPNE7 reversed the induction of the autophagy pathway by rapamycin and reduced the number of autophagosomes. Depletion of CPNE7 attenuated the malignant proliferation of CRC cells and enhanced the chemosensitivity of CRC cells to 5-fluorouracil.

Sophoricoside ameliorates cerebral ischemia-reperfusion injury dependent on activating AMPK.

AIMS: Ischemic stroke accounts for 87% of all strokes, and its death and disability bring a huge burden to society. Brain injury caused by ischemia-reperfusion (I/R) is also a major difficulty in clinical treatment and prognosis. Sophoricoside (SOP) is an isoflavone glycoside isolated from the seed of medical herb Sophora japonica L. Previously, SOP was found to be effective in anti-inflammation and glucose-lipid metabolism-related diseases. In order to investigate whether SOP has a regulatory effect on cerebral I/R injury, we conducted this study. METHODS: Here, by application of SOP into MCAO (transient middle cerebral artery occlusion)-induced mice and OGD/R (oxygen glucose deprivation/reperfusion)-induced primary neurons, the regulation effects of SOP was analyzed by detecting neurological score of post-stroke mice, phenotypes of brains and brain sections, cell viabilities, and apoptosis- and inflammation-regulation. RNA sequencing and molecular biology experiments were performed to explore the mechanism of SOP regulating cerebral I/R injury. RESULTS: SOP administration decreased the infarct size, neurological deficit score, neuronal cell injury, inflammation and apoptosis. Mechanistically, SOP exerted its protective effect by activating the AMP-activated protein kinase (AMPK) signaling pathway. CONCLUSION: SOP inhibits cerebral I/R injury by promoting the phosphorylation of AMPK.

Integrated UPLC/Q-TOF-MS/MS Analysis and Network Pharmacology to Reveal the Neuroprotective Mechanisms and Potential Pharmacological Ingredients of Aurantii Fructus Immaturus and Aurantii Fructus.

Aurantii Fructus (AF) and Aurantii Fructus Immaturus (AFI) have been used for thousands of years as traditional Chinese medicine (TCM) with sedative effects. Modern studies have shown that Citrus plants also have protective effects on the nervous system. However, the effective substances and mechanisms of action in Citrus TCMs still remain unclear. In order to explore the pharmacodynamic profiles of identified substances and the action mechanism of these herbs, a comprehensive approach combining ultra-high-performance liquid chromatography with quadrupole time-of-flight mass spectrometry (UPLC/Q-TOF-MS/MS) analysis and network pharmacology was employed. Firstly, UNIFI 2.1.1 software was used to identify the chemical characteristics of AF and AFI. Secondly, the SwissTargetPrediction database was used to predict the targets of chemical components in AF and AFI. Targets for neuroprotection were also collected from GeneCards: The Human Gene Database (GeneCards-Human Genes|Gene Database|Gene Search). The networks between targets and compounds or diseases were then constructed using Cytoscape 3.9.1. Finally, the Annotation, Visualization and Integrated Discovery Database (DAVID) (DAVID Functional Annotation Bioinformatics Microarray Analysis) was used for GO and pathway enrichment analysis. The results showed that 50 of 188 compounds in AF and AFI may have neuroprotective biological activities. These activities are associated with the regulatory effects of related components on 146 important signaling pathways, derived from the KEGG (KEGG: Kyoto Encyclopedia of Genes and Genomes), such as neurodegeneration (hsa05022), the Alzheimer's disease pathway (hsa05010), the NF-kappa B signaling pathway (hsa04064), the hypoxia-inducible factor (HIF)-1 signaling pathway (hsa04066), apoptosis (hsa04210), the epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor resistance signaling pathway (hsa01521), and others, by targeting 108 proteins, including xanthine dehydrogenase (XDH), glutamate ionotropic receptor NMDA type subunit 2B (GRIN2B), and glucose-6-phosphate dehydrogenase (G6PD), among others. These targets are thought to be related to inflammation, neural function and cell growth.

Diastereomers of Steroidal Alkaloids with Cytotoxic Activities against Non-Small-Cell Lung Cancer from the Bulbs of Fritillaria sinica.

Eleven new steroidal alkaloids, along with nine known related compounds, were isolated from the bulbs of Fritillaria sinica. Seven pairs of diastereomers were identified, including six and four 20-deoxy cevanine-type steroidal alkaloid diastereomers with molecular weights of 413 and 415, respectively. Structures were elucidated based on spectroscopic data analysis, chemical derivatization, and single-crystal X-ray diffraction analysis. Compounds 5, 9, 11, 12, 16, and 20 exhibited significant in vitro cytotoxic activity against non-small-cell lung cancer with CC50 values from 6.8 ± 3.9 to 12 ± 5 µM.

MI-DenseCFNet: deep learning-based multimodal diagnosis models for Aureus and Aspergillus pneumonia.

OBJECTIVE: To build and merge a diagnostic model called multi-input DenseNet fused with clinical features (MI-DenseCFNet) for discriminating between Staphylococcus aureus pneumonia (SAP) and Aspergillus pneumonia (ASP) and to evaluate the significant correlation of each clinical feature in determining these two types of pneumonia using a random forest dichotomous diagnosis model. This will enhance diagnostic accuracy and efficiency in distinguishing between SAP and ASP. METHODS: In this study, 60 patients with clinically confirmed SAP and ASP, who were admitted to four large tertiary hospitals in Kunming, China, were included. Thoracic high-resolution CT lung windows of all patients were extracted from the picture archiving and communication system, and the corresponding clinical data of each patient were collected. RESULTS: The MI-DenseCFNet diagnosis model demonstrates an internal validation set with an area under the curve (AUC) of 0.92. Its external validation set demonstrates an AUC of 0.83. The model requires only 10.24s to generate a categorical diagnosis and produce results from 20 cases of data. Compared with high-, mid-, and low-ranking radiologists, the model achieves accuracies of 78% vs. 75% vs. 60% vs. 40%. Eleven significant clinical features were screened by the random forest dichotomous diagnosis model. CONCLUSION: The MI-DenseCFNet multimodal diagnosis model can effectively diagnose SAP and ASP, and its diagnostic performance significantly exceeds that of junior radiologists. The 11 important clinical features were screened in the constructed random forest dichotomous diagnostic model, providing a reference for clinicians. CLINICAL RELEVANCE STATEMENT: MI-DenseCFNet could provide diagnostic assistance for primary hospitals that do not have advanced radiologists, enabling patients with suspected infections like Staphylococcus aureus pneumonia or Aspergillus pneumonia to receive a quicker diagnosis and cut down on the abuse of antibiotics. KEY POINTS: • MI-DenseCFNet combines deep learning neural networks with crucial clinical features to discern between Staphylococcus aureus pneumonia and Aspergillus pneumonia. • The comprehensive group had an area under the curve of 0.92, surpassing the proficiency of junior radiologists. • This model can enhance a primary radiologist's diagnostic capacity.

Systematical targeted multicomponent characterization and comparison of Arnebiae Radix and its three confusing species by offline two-dimensional liquid chromatography/LTQ-Orbitrap mass spectrometry.

Arnebiae Radix, commonly known as "Zicao," can be easily confused with other compounding species, posing challenges for its clinical use. Here, we developed a comprehensive strategy to systematically characterize the diverse components across Arnebiae Radix and its three confusing species. First, an offline two-dimensional liquid chromatography (2D-LC) system integrating hydrophilic interaction chromatography (HILIC) and reverse phase (RP) separations was established, enabling effective separation and detection of more trace constituents. Second, a polygonal mass defect filtering (MDF) workflow was implemented to screen target ions and generate a precursor ion list (PIL) to guide multistage mass (MSn) data acquisition. Third, a three-step characterization strategy utilizing diagnostic ions and neutral losses was developed for rapid determination of molecular formulas, structure classes, and compound identification. This approach enabled systematic characterization of Arnebiae Radix and its three confusing species, with 437 components characterized including 112 shikonins, 22 shikonfurans, 144 phenolic acids, 131 glycosides, 18 flavonoids, and 10 other compounds. Additionally, 361, 230, 340, and 328 components were identified from RZC, YZC, DZC, and ZZC, respectively, with 142 common components and 30 characteristic components that may serve as potential markers for distinguishing the four species. In summary, this is the first comprehensive characterization and comparison of the phytochemical profiles of Arnebiae Radix and its three confusing species, advancing our understanding of this herbal medicine for quality control.

Species discrimination of multiple botanical origins of Fritillaria species based on infrared spectroscopy, thin layer chromatography-image analysis and untargeted metabolomics.

BACKGROUND: Fritillaria Bulbus (FB), a precious medicinal herb renowned for its heat-clearing, lung-moistening, cough-relieving and phlegm-eliminating effects. In pursuit of profits, unscrupulous merchants have engaged in the substitution or adulteration of valuable varieties with cheaper alternatives. It is, therefore, urgent to develop effective technical approaches to identify FBs from adulterants. METHODS: This paper employed infrared spectroscopy (IR), thin layer chromatography-image analysis (TLC-IA), and untargeted metabolomics techniques to discriminate ten species of FBs. RESULTS: Five species of FBs were successfully differentiated using mid-infrared spectroscopy. Furthermore, the power of TLC-IA technology allowed the differentiation of five species of FBs and two origins of FCBs (Fritillariae Cirrhosae Bulbus). Remarkably, through the application of untargeted metabolomics technique, the precise discrimination of five species of FBs, as well as three origins of FCBs were accomplished. Moreover, a comprehensive identification of 101 markers that reliably distinguished diverse FBs was achieved through the employment of untargeted metabolomics technique. CONCLUSION: The investigation presented powerful means of detection for assuring the quality control of Fritillaria herbs.

MATLAB language assisted data acquisition and processing in liquid chromatography Orbitrap mass spectrometry: Application to the identification and differentiation of Radix Bupleuri from its adulterants.

Comprehensive and rapid analysis of secondary metabolites like saponins remains challenging. This study aimed to establish a semi-automated workflow for filtration, identification, and characterization of saikosaponins in six Bupleurum species. Radix Bupleuri, a high-sales herbal medicine, is often adulterated, restricting its quality control and applications. Two authentic Radix Bupleuri species and four major adulterants were analyzed through UHPLC-LTQ-Orbitrap-MS for targeted saikosaponin analysis. To reveal trace saikosaponins and obtain quality fragment data, a MATLAB-based process automatically enumerating "sugar chain + aglycone + side chain" combinations and deduplicating generated a predicted saikosaponin database covering all possible saikosaponins as a precursor ion list for comprehensive targeted acquisition. To focus on informative ions and reduce MS analysis workload, we utilized MATLAB to automatically filtrate the false positive ions by MS1 and MS2 spectrometry. The newly established MATLAB-assisted data acquisition approach exhibited 50 % improvement in characterization of targeted saikosaponins. Furthermore, positive and negative ionization workflows were designed for accurate saikosaponins characterization based on fragmentation rules. In total, 707 saikosaponins were characterized, including over 500 potential new compounds and previously unreported C29 aglycones. We identified 25 saikosaponins present in both authentic species but absent in adulterants as potential markers. This unprecedented comprehensive multi-origin species differentiation demonstrates the promise of MATLAB-assisted acquisition and processing to advance saponin identification and standardize the Radix Bupleuri market.

The effect of metformin on senescence of T lymphocytes.

BACKGROUND: Immunosenescence occurs as people age, leading to an increased incidence of age-related diseases. The number of senescent T cells also rises with age. T cell senescence and immune response dysfunction can result in a decline in immune function, especially in anti-tumor immune responses. Metformin has been shown to have various beneficial effects on health, such as lowering blood sugar levels, reducing the risk of cancer development, and slowing down the aging process. However, the immunomodulatory effects of metformin on senescent T cells still need to be investigated. METHODS: PBMCs isolation from different age population (n = 88); Flow Cytometry is applied to determine the phenotypic characterization of senescent T lymphocytes; intracellular staining is applied to determine the function of senescent T cells; Enzyme-Linked Immunosorbent Assay (ELISA) is employed to test the telomerase concentration. The RNA-seq analysis of gene expression associated with T cell senescence. RESULTS: The middle-aged group had the highest proportion of senescent T cells. We found that metformin could decrease the number of CD8 + senescent T cells. Metformin affects the secretion of SASP, inhibiting the secretion of IFN-γ in CD8 + senescent T cells. Furthermore, metformin treatment restrained the production of the proinflammatory cytokine IL-6 in lymphocytes. Metformin had minimal effects on Granzyme B secretion in senescent T cells, but it promoted the production of TNF-α in senescent T cells. Additionally, metformin increased the concentration of telomerase and the frequency of undifferentiated T cells. The results of RNA-seq showed that metformin promoted the expression of genes related to stemness and telomerase activity, while inhibiting the expression of DNA damage-associated genes. CONCLUSION: Our findings reveal that metformin could inhibit T cell senescence in terms of cell number, effector function, telomerase content and gene expression in middle-aged individuals, which may serve as a promising approach for preventing age-related diseases in this population.

Characterization of natural peptides in Pheretima by integrating proteogenomics and label-free peptidomics.

Pheretima, also called "earthworms", is a well-known animal-derived traditional Chinese medicine that is extensively used in over 50 Chinese patent medicines (CPMs) in Chinese Pharmacopoeia (2020 edition). However, its zoological origin is unclear, both in the herbal market and CPMs. In this study, a strategy for integrating in-house annotated protein databases constructed from close evolutionary relationship-sourced RNA sequencing data from public archival resources and various sequencing algorithms (restricted search, open search, and de novo) was developed to characterize the phenotype of natural peptides of three major commercial species of Pheretima, including Pheretima aspergillum (PA), Pheretima vulgaris (PV), and Metaphire magna (MM). We identified 10,477 natural peptides in the PA, 7,451 in PV, and 5,896 in MM samples. Five specific signature peptides were screened and then validated using synthetic peptides; these demonstrated robust specificity for the authentication of PA, PV, and MM. Finally, all marker peptides were successfully applied to identify the zoological origins of Brain Heart capsules and Xiaohuoluo pills, revealing the inconsistent Pheretima species used in these CPMs. In conclusion, our integrated strategy could be used for the in-depth characterization of natural peptides of other animal-derived traditional Chinese medicines, especially non-model species with poorly annotated protein databases.

New easily recycled carrier based polyurethane foam by loading Al-MOF and biochar for selective removal of fluoride ion from aqueous solutions.

The production of Integrated circuits (ICs) generates wastewater with a high concentration of residual fluoride ions, necessitating highly efficient fluorine removal methods. In this study, a novel composite carrier was developed using a hydrothermal synthesis method to load Al-MOF and biochar (BC) onto polyurethane foam (PUF), resulting in the composite foam of Al-MOF-PUF@BC. The results showed that the composite carrier exhibited a stable fluoride removal effect, with a maximum adsorption capacity of 16.52 mg/g at room temperature. The adsorption isotherm curves were consistent with the Langmuir isotherm model, and the adsorption kinetics were well-described by the pseudo-first-order model. The mechanism of fluorine adsorption on Al-MOF-PUF@BC was ligand exchange with hydroxyl groups and the formation of FAl bonds. Density functional theory (DFT) calculations revealed that the adsorption energy reached -246.7 eV, indicating stable adsorption for fluoride ions. The composite foam demonstrated excellent regenerative properties and was effective for fluoride removal in actual IC wastewater.

Prevalence of and risk factors for chlamydia in female outpatients with genital tract infections: a nationwide multi-center, cross-sectional study in China.

Introduction: Chlamydia trachomatis is the etiological agent of the commonest sexually transmitted bacterial infection. This study aimed to examine the prevalence of genital chlamydia and associated risk factors in Chinese female outpatients with genital tract infections. Methods: A prospective, multicenter epidemiological study of genital chlamydia prevalence in 3008 patients with genital tract infections in 13 hospitals in 12 provinces of China was performed between May 2017 and November 2018. Vaginal secretion specimens were collected for the clinical diagnosis of vaginitis, whereas cervical secretion specimens were tested for Chlamydia trachomatis and Neisseria gonorrhoeae. All patients participated in a one-on-one cross-sectional questionnaire interview. Results: Totally 2,908 participants were included. The prevalence rates of chlamydia and gonococcal infections in women with genital tract infections were 6.33% (184/2908) and 0.01% (20/2908), respectively. Multivariate analysis showed high risk factors for chlamydia were premarital sex behavior, first sexual intercourse before the age of 20 and bacterial vaginosis. Discussion: Given that most chlamydia cases are asymptomatic and no vaccine is currently available, chlamydia prevention strategies should include behavioral interventions as well as early screening programs to identify and treat individuals with genital tract infections, especially those with the above identified risk factors.

Machine learning-aided metallomic profiling in serum and urine of thyroid cancer patients and its environmental implications.

The incidence rate of thyroid cancer has been growing worldwide. Thyroid health is closely related with multiple trace metals, and the nutrients are essential in maintaining thyroid function while the contaminants can disturb thyroid morphology and homeostasis. In this study, we conducted metallomic analysis in thyroid cancer patients (n = 40) and control subjects (n = 40) recruited in Shenzhen, China with a high incidence of thyroid cancer. We found significant alterations in serumal and urinary metallomic profiling (including Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Sr, Cd, I, Ba, Tl, and Pb) and elemental correlative patterns between thyroid cancer patients and controls. Additionally, we also measured the serum Cu isotopic composition and found a multifaceted disturbance in Cu metabolism in thyroid disease patients. Based on the metallome variations, we built and assessed the thyroid cancer-predictive performance of seven machine learning algorithms. Among them, the Random Forest model performed the best with the accuracy of 1.000, 0.858, and 0.813 on the training, 5-fold cross-validation, and test set, respectively. The high performance of machine learning has demonstrated the great promise of metallomic analysis in the identification of thyroid cancer. Then, the Shapley Additive exPlanations approach was used to further interpret the variable contributions of the model and it showed that serum Pb contributed the most in the identification process. To the best of our knowledge, this is the first study that combines machine learning and metallome data for cancer identification, and it supports the indication of environmental heavy metal-related thyroid cancer etiology.

Undescribed steroidal alkaloids from the bulbs of Fritillaria sinica.

Eight undescribed steroidal alkaloid derivatives, including three cevanine-type isosteroidal alkaloids (two N-oxide glycosides and one D-ring aromatization) (1-3), one verazine-type steroidal alkaloid derivative (4), three solanidine-type steroidal alkaloid glycosides (5-7), and one veratramine-type analogue (8), along with three known compounds (9-11) were isolated from the bulbs of Fritillaria sinica. Their structures were elucidated by comprehensive analysis of spectroscopic data, acidic hydrolysis, and X-ray crystal diffractions. In the in vitro bioassay, the anti-cancer effect, anti-oxidation and anti-inflammatory activities for the isolates were evaluated at a concentration of 10 µM.