GSDMB interacts with IGF2BP1 to suppress colorectal cancer progression by modulating DUSP6-ERK pathway.

There is growing evidence that the protein family of Gasdermins (GSDMs) play an essential role during the progression of colorectal cancer (CRC). However, it is not completely clear that how GSDMB, abundantly expressed in epithelial cells of gastrointestinal tract, regulates the tumorigenesis of CRC. A wealth of evidence linking GSDMB to the pathogenesis of cancer has come from genome-wide association studies. Here, we provide evidence that aberrantly upregulated GSDMB is responsible for suppressing the CRC progression by using in vitro cell and intestinal organoid, as well as in vivo GSDMB transgenic mice models. Mechanistically, GSDMB interacts with insulin-like growth factor 2 mRNA-binding protein 1 (IGF2BP1), which directly binds to and recognizes the 3'-UTR of dual specificity phosphatase 6 (DUSP6) mRNA, enhances the translation of DUSP6 protein and inhibits downstream ERK phosphorylation, thereby facilitating cell death and restraining cell proliferation. Our results suggest that GSDMB has potential as a novel therapeutic target for CRC treatment.

Machine learning discrimination of Gleason scores below GG3 and above GG4 for HSPC patients diagnosis.

This study aims to develop machine learning (ML)-assisted models for analyzing datasets related to Gleason scores in prostate cancer, conducting statistical analyses on the datasets, and identifying meaningful features. We retrospectively collected data from 717 hormone-sensitive prostate cancer (HSPC) patients at Yunnan Cancer Hospital. Of these, data from 526 patients were used for modeling. Seven auxiliary models were established using Logistic Regression (LR), Support Vector Machine (SVM), Random Forest (RF), Decision Tree (DT), Extreme gradient boosting tree (XGBoost), Adaptive Boosting (Adaboost), and artificial neural network (ANN) based on 21 clinical biochemical indicators and features. Evaluation metrics included accuracy (ACC), precision (PRE), specificity (SPE), sensitivity (SEN) or regression rate(Recall), and f1 score. Evaluation metrics for the models primarily included ACC, PRE, SPE, SEN or Recall, f1 score, and area under the curve(AUC). Evaluation metrics were visualized using confusion matrices and ROC curves. Among the ensemble learning methods, RF, XGBoost, and Adaboost performed the best. RF achieved a training dataset score of 0.769 (95% CI: 0.759-0.835) and a testing dataset score of 0.755 (95% CI: 0.660-0.760) (AUC: 0.786, 95%CI: 0.722-0.803), while XGBoost achieved a training dataset score of 0.755 (95% CI: 95%CI: 0.711-0.809) and a testing dataset score of 0.745 (95% CI: 0.660-0.764) (AUC: 0.777, 95% CI: 0.726-0.798). Adaboost scored 0.789 on the training dataset (95% CI: 0.782-0.857) and 0.774 on the testing dataset (95% CI: 0.651-0.774) (AUC: 0.799, 95% CI: 0.703-0.802). In terms of feature importance (FI) in ensemble learning, Bone metastases at first visit, prostatic volume, age, and T1-T2 have significant proportions in RF's FI. fPSA, TPSA, and tumor burden have significant proportions in Adaboost's FI, while f/TPSA, LDH, and testosterone have the highest proportions in XGBoost. Our findings indicate that ensemble learning methods demonstrate good performance in classifying HSPC patient data, with TNM staging and fPSA being important classification indicators. These discoveries provide valuable references for distinguishing different Gleason scores, facilitating more accurate patient assessments and personalized treatment plans.

Dual-functional probe-based multi-signal immunosensor platform for tropane alkaloids: Verification and evaluation.

This study aims to realise rapid detecting of tropane alkaloids (TAs) in food. For this purpose, a broad-spectrum single-chain fragment variable was fused with horseradish peroxidase to create an antibody-enzyme complex (AEC) with antigen recognition and catalytic activity. A multi-signal immunosensor platform based on AEC in the direct competitive reaction mode was constructed using 3,3',5,5'-tetramethylbenzidine and 10-acetyl-3,7-dihydroxyphenoxazine as substrates. The sensitivity of TAs in the immunosensor platform ranged from 0.25 µg/kg to 7912.46 µg/kg. Honey was selected as a representative food sample, and the limit of detection of TAs in honey ranged from 0.02 µg/kg to 409.11 µg/kg, with a recovery rate of 65.7 %-117.1 % and a coefficient of variation less than 21.4 %. Results showed that the immunosensor platform possesses satisfactory accuracy and precision, which highlights its potential for practical applications and its suitability as an ideal tool for rapid screening of TAs in food.

A novel triple-signal biosensor based on ZrFe-MOF@PtNPs for ultrasensitive aflatoxins detection.

The development of more sensitive, stable, and portable biosensors is crucial for meeting the growing demands of diverse and complex detection environments. MOF-based nanozymes have emerged as excellent optical reporters, making them ideal signal donors for constructing multi-signal lateral flow immunoassays (LFIA). In this study, a ZrFe-MOF@PtNPs nanocomposite was synthesized by uniformly depositing platinum nanoparticles (PtNPs) onto the surface of ZrFe-MOFs using an impregnation-reduction method. The ZrFe-MOF@PtNPs exhibited broad absorption spectra, excellent peroxidase-like activity (SA = 21.77 U/mg), high solvent stability, and efficient antibody binding capability. A portable LFIA platform was developed based on ZrFe-MOF@PtNPs and a smartphone for the targeted detection of carcinogenic aflatoxins. This method enabled the readout of colorimetric, fluorescent, and catalytic signals, significantly enhancing detection sensitivity, ensuring result accuracy, and expanding the dynamic detection range. For aflatoxin M1, the calculation of the detection limit of the three signal modes reached as low as 0.0062 ng/mL, which is two orders of magnitude more sensitive than AuNPs-LFIA (0.1839 ng/mL). This study provides effective guidance for multifunctional modification of MOFs and serves as a reference for the application of MOF-based nanozymes in point-of-care biosensors.

Comprehensive scRNA-seq analysis to identify new markers of M2 macrophages for predicting the prognosis of prostate cancer.

BACKGROUND: Prostate cancer (PCa) has become the highest incidence of malignant tumor among men in the world. Tumor microenvironment (TME) is necessary for tumor growth. M2 macrophages play an important role in many solid tumors. This research aimed at the role of M2 macrophages' prognosis value in PCa. METHODS: Single-cell RNA-seq (scRNA-seq) data and mRNA expression data were obtained from the Gene Expression Omnibus database (GEO) and The Cancer Genome Atlas (TCGA). Quality control, normalization, reduction, clustering, and cell annotation of scRNA-seq data were preformed using the Seruat package. The sub-populations of the tumor-associated macrophages (TAMs) were analysis and the marker genes of M2 macrophage were selected. Differentially expressed genes (DEGs) in PCa were identified using limma and the immune infiltration was detected using CIBERSORTx. Then, a weighted correlation network analysis (WGCNA) was constructed to identify the M2 macrophage-related modules and genes. Integration of the marker genes of M2 macrophage from scRNA-seq data analysis and hub genes from WGCNA to select the prognostic gene signature based on Univariate and LASSO regression analysis. The risk score was calculated, and the DEGs, biological function, immune characteristics related to risk score were explored. And a predictive nomogram was constructed. CCK8, Transwell, and wound healing were used to verify cell phenotype changes after co-cultured. RESULTS: A total of 2431 marker genes of M2 macrophage and 650 hub M2 macrophage-related genes were selected based on scRNA-seq data and WGCNA. Then, 113 M2 macrophage-related genes were obtained by overlapping the scRNA-seq data and WGCNA results. Nine M2 macrophage-related genes (SMOC2, PLPP1, HES1, STMN1, GPR160, ABCG1, MAZ, MYC, and EPCAM) were screened as prognostic gene signatures. M2 risk score was calculated, the DEGs, Immune score, stromal score, ESTIMATE score, tumor purity, and immune cell infiltration, immune checkpoint expression, and responses of immunotherapy and chemotherapy were identified. And a predictive nomogram was constructed. CCK8, Transwell invasion, and wound healing further verified that M2 macrophages promoted the proliferation, invasion, and migration of PCa (p < 0.05). CONCLUSIONS: We uncovered that M2 macrophages and relevant genes played key roles in promoting the occurrence, development, and metastases of PCa and played as convincing predictors in PCa.

The impact of the COVID-19 surge after the end of China's Zero-COVID policy on the health-related quality of life of IBD patients.

INTRODUCTION: In December 2019, COVID-19 emerged in Wuhan, Hubei Province, China, and rapidly spread worldwide. On December 2022, the Chinese government ended the zero-COVID policy, leading to a surge in cases and significantly impacting daily life. IBD patients face heightened infection risks and substantial effects on their quality of life during the pandemic. METHODS: This cross-sectional study collected demographic, COVID-19-related, and HRQoL data from 224 IBD patients who had previously received treatment at Nanjing BenQ Medical Center. Participants completed an online survey between January 9, 2023, and January 23, 2023. The SIBDQ was used to assess HRQoL. Statistical analysis was performed using SPSS version 26. RESULTS: The study found that UC patients reported higher HRQoL compared to CD patients (p = 0.037). Patients who perceived themselves as less susceptible to COVID-19 had higher scores (p = 0.006 and p = 0.009). Those whose work or study was unaffected also had higher scores (p < 0.001 and p = 0.002). Additionally, irregular medication adherence was associated with lower HRQoL scores (p = 0.014 and p = 0.007). Multivariate linear regression results showed that IBD patients whose work or study was affected during the COVID-19 pandemic scored lower than those who were not affected (p = 0.038; 95% CI, -7.96 to -0.25). Patients who discontinued IBD medication scored higher than those with irregular medication use (p = 0.020; 95% CI, 1.00 to 10.90). CONCLUSIONS: This study highlights the significant impact of the COVID-19 pandemic on the HRQoL of IBD patients. The findings emphasize the need for integrated care addressing both the physical and psychological aspects of IBD.

Construction and validation of a prediction model for inguinal lymph node metastasis of penile malignancy.

Background: Penile squamous cell carcinoma is a relatively rare malignancy among male malignancies, there are more than 30,000 new cases and more than 10,000 deaths of penile cancer annually. In patients with penile malignancy, inguinal lymph node metastasis (ILNM) significantly reduces patient survival. Thus, we identified the risk factors for ILNM in penile malignancies, aiming to develop a precise prediction model. Methods: We retrospectively analyzed 112 male patients with penile cancer. All subjects underwent penile surgery and inguinal lymphadenectomy at the same time, and postoperative pathology confirmed ILNM. Fisher's exact test, t-test, and Wilcoxon rank sum test were used to assess differences in demographic information and clinical features between the two groups, followed by logical least absolute shrinkage and selection operator (LASSO) regression analysis to determine risk factors of ILNM. The prediction model was constructed using nomogram. Results: LASSO regression revealed that age [ß=-0.005, odds ratio (OR) =0.995], smoking history (ß=-0.006, OR =0.994) and interleukin 2 (IL-2) level (ß=-0.0112, OR =0.989) were protective against ILNM. However, lymph node diameter (ß=0.3117, OR =1.366), T-stage (ß=0.1254, OR =1.134), fibrinogen (ß=0.0377, OR =1.038), IL-4 level (ß=0.004, OR =1.001), and neutrophil-to-lymphocyte ratio (ß=0.0355, OR =1.034) were risk factors for developing ILNM. When assessing the risk of metastasis, it is crucial to balance these factors. The aforementioned characteristics were utilized to establish the predictive model, which demonstrated a good predictive ability with an area under the curve (AUC) value of 0.81. Moreover, internal leave-one-way cross-validation was used to construct a nomogram showing consistency, with an AUC of 0.75. Conclusions: The diagnosis of ILNM in penile malignant tumors can be predicted through clinicopathological features, biochemical tests, and prediction models based on tumor markers.

High-throughput prediction of stalk cellulose and hemicellulose content in maize using machine learning and Fourier transform infrared spectroscopy.

Cellulose and hemicellulose are key cross-linked carbohydrates affecting bioethanol production in maize stalks. Traditional wet chemical methods for their detection are labor-intensive, highlighting the need for high-throughput techniques. This study used Fourier transform infrared (FTIR) spectroscopy combined with machine learning (ML) algorithms on 200 large-scale maize germplasms to develop robust predictive models for stalk cellulose, hemicellulose and holocellulose content. We identified several peak height features correlated with three contents, used them as input data for model building. Four ML algorithms demonstrated higher predictive accuracy, achieving coefficient of determination (R2) ranging from 0.83 to 0.97. Notably, the Categorical Boosting algorithm yielded optimal models with coefficient of determination (R2) exceeding 0.91 for the training set and over 0.81 for the test set. The approach combined FTIR spectroscopy with ML algorithms offers a precise and high-throughput tool for predicting stalk cellulose, hemicellulose and holocellulose contents, benefiting maize genetic breeding for bioenergy and biofuels.

Machine learning prediction of stalk lignin content using Fourier transform infrared spectroscopy in large scale maize germplasm.

Lignin has been recognized as a major factor contributing to lignocellulosic recalcitrance in biofuel production and attracted attentions as a high-value product in the biorefinery field. As the traditional wet chemical methods for detecting lignin content are labor-intensive, time-consuming and environment-toxic, it is an urgent need to develop high-throughput and environment-friendly techniques for large-scale crop germplasms screening. In this study, we conducted a Fourier transform infrared (FTIR) assay on 150 maize germplasms with a diverse lignin composition to build predictive models for lignin content in maize stalk. Principal component analysis (PCA) was applied to the FTIR spectra for use as model inputs. Classification and advanced gradient boosting machine (GBM) algorithms demonstrated higher predictive accuracy (0.82-0.96) compared to traditional linear and regularization algorithms (0.03-0.04) in the training set. Notably, two optimal models, built using the extreme gradient boosting (XGBoost) and light gradient boosting machine (LightGBM) algorithms, achieved R2 values of over 0.91 in the training set and over 0.82 in the test set. Overall, the combination of FTIR and machine learning (ML) algorithms offers a high-throughput and efficient method for predicting lignin content. This approach holds significant potential for genetic breeding and the effective utilization of maize in industrial production.

Aquaporin 1 confers apoptosis resistance in pulmonary arterial smooth muscle cells from the SU5416 hypoxia rat model.

Pulmonary hypertension (PH) arises from increased pulmonary vascular resistance due to contraction and remodeling of the pulmonary arteries. The structural changes include thickening of the smooth muscle layer from increased proliferation and resistance to apoptosis. The mechanisms underlying apoptosis resistance in PH are not fully understood. In cancer cells, high expression of aquaporin 1 (AQP1), a water channel, is associated with apoptosis resistance. We showed AQP1 protein was expressed in pulmonary arterial smooth muscle cells (PASMCs) and upregulated in preclinical PH models. In this study, we used PASMCs isolated from control male rats and the SU5416 plus hypoxia (SuHx) model to test the role of AQP1 in modulating susceptibility to apoptosis. We found the elevated level of AQP1 in PASMCs from SuHx rats was necessary for resistance to apoptosis and that apoptosis resistance could be conferred by increasing AQP1 in control PASMCs. In exploring the downstream pathways involved, we found AQP1 levels influence the expression of Bcl-2, with enhanced AQP1 levels corresponding to increased Bcl-2 expression, reducing the ratio of BAX to Bcl-2, consistent with apoptosis resistance. These results provide a mechanism by which AQP1 can regulate PASMC fate.

Identification of prostate cancer bone metastasis related genes and potential therapy targets by bioinformatics and in vitro experiments.

The aetiology of bone metastasis in prostate cancer (PCa) remains unclear. This study aims to identify hub genes involved in this process. We utilized machine learning, GO, KEGG, GSEA, Single-cell analysis, ROC methods to identify hub genes for bone metastasis in PCa using the TCGA and GEO databases. Potential drugs targeting these genes were identified. We validated these results using 16 specimens from patients with PCa and analysed the relationship between the hub genes and clinical features. The impact of APOC1 on PCa was assessed through in vitro experiments. Seven hub genes with AUC values of 0.727-0.926 were identified. APOC1, CFH, NUSAP1 and LGALS1 were highly expressed in bone metastasis tissues, while NR4A2, ADRB2 and ZNF331 exhibited an opposite trend. Immunohistochemistry further confirmed these results. The oxidative phosphorylation pathway was significantly enriched by the identified genes. Aflatoxin B1, benzo(a)pyrene, cyclosporine were identified as potential drugs. APOC1 expression was correlated with clinical features of PCa metastasis. Silencing APOC1 significantly inhibited PCa cell proliferation, clonality, and migration in vitro. This study identified 7 hub genes that potentially facilitate bone metastasis in PCa through mitochondrial metabolic reprogramming. APOC1 emerged as a promising therapeutic target and prognostic marker for PCa with bone metastasis.

A novel member of miR169 family negatively regulates maize resistance against Bipolaris maydis.

MicroRNAs (miRNAs) have been confirmed to play important roles in plant defense response. However, the key maize miRNAs involved in the defense response against Bipolaris maydis are very limited. In this study, a novel member of the miR169 family in response to B. maydis, named zma-miR169s, was discovered and investigated. The expression levels of pre-miR169s and zma-miR169s were significantly repressed during B. maydis infection. CRISPR/Cas9-induced zma-miR169s mutant exhibited more resistance against B. maydis, whereas overexpression zma-miR169s enhanced susceptibility, supporting that zma-miR169s might play a negative role in maize resistance. Moreover, RNA-seq and GO analysis showed that differentially expressed genes were highly enriched in the oxidation-reduction process and plant hormone pathway. Hence, reactive oxygen species (ROS) and plant hormone levels were further investigated. ROS detection confirmed that zma-miR169s mutant accumulated more ROS, while less ROS was detected in transgenic maize OE-miR169s. Furthermore, more remarkable changes in PR-1 expression levels and salicylic acid (SA) contents were detected in zma-miR169s mutant compared to wild-type and transgenic maize during B. maydis infection. Additionally, nuclear transcription factors (NF-YA1 and NF-YA13) were identified as targets regulated by zma-miR169s through the agrobacterium-mediated transient expression method. Overexpression of ZmNF-YA13 enhanced Arabidopsis resistance to Pseudomonas syringae pv. tomato DC3000. Taken together, our results suggest that zma-miR169s negatively regulate maize defense responses by influencing ROS accumulation and the SA-dependent signaling pathway.

Osteopontin regulation of MerTK+ macrophages promotes Crohn's disease intestinal fibrosis.

The pathogenesis of intestinal fibrosis in Crohn's disease (CD) remains unclear. Mer receptor tyrosine kinase (MerTK) is an immunosuppressive protein specifically expressed in macrophages. Osteopontin (OPN), also known as secreted phosphoprotein 1, contributes to inflammation and wound repair. This study investigates the potential profibrotic pathway in MerTK+ macrophages in order to provide a possible therapeutic target for intestinal fibrosis. MerTK expression in the inflamed and stenotic bowels was evaluated. The MerTK/ERK/TGF-ß1 pathway was overactivated in the fibrotic intestinal tissues of patients with CD. This pathway was induced by epithelial cell apoptosis, resulting in activated fibroblasts with increased TGF-ß1 secretion. OPN upregulated TGF production by altering ERK1/2 phosphorylation, as evidenced by OPN or MerTK knockdown and OPN overexpression in vitro. MerTK inhibitor UNC2025 alleviated intestinal fibrosis in mouse colitis models, suggesting a potential therapeutic target for intestinal fibrosis in patients with CD.

FASN regulates STING palmitoylation via malonyl-CoA in macrophages to alleviate sepsis-induced liver injury.

STING (stimulator of interferon genes) is a critical immunoregulatory protein in sepsis and is regulated by various mechanisms, especially palmitoylation. FASN (fatty acid synthase) is the rate-limiting enzyme to generate cellular palmitic acid (PA) via acetyl-CoA and malonyl-CoA and participates in protein palmitoylation. However, the mechanisms underlying the interaction between STING and FASN have not been completely understood. In this study, STING-knockout mice were used to confirm the pivotal role of STING in sepsis-induced liver injury. Metabolomics confirmed the dyslipidemia in septic mice and patients. The compounds library was screened, revealing that FASN inhibitors exerted a significant inhibitory effect on the STING pathway. Mechanically, the regulatory effect of FASN on the STING pathway was dependent on palmitoylation. Further experiments indicated that the upstream of FASN, malonyl-CoA inhibited STING pathway possibly due to C91 (palmitoylated residue) of STING. Overall, this study reveals a novel paradigm of STING regulation and provides a new perspective on immunity and metabolism.

Van der Waals Schottky Junction Photodetector with Ultrahigh Rectifying Ratio and Switchable Photocurrent Generation.

Metal-semiconductor junctions play an important role in the development of electronic and optoelectronic devices. A Schottky junction photodetector based on two-dimensional (2D) materials is promising for self-powered photodetection with fast response speed and large signal-to-noise ratio. However, it usually suffers from an uncontrolled Schottky barrier due to the Fermi level pinning effect arising from the interface states. In this work, all-2D Schottky junctions with near-ideal Fermi level depinning are realized, attributed to the high-quality interface between 2D semimetals and semiconductors. We further demonstrate asymmetric diodes based on multilayer graphene/MoS2/PtSe2 with a current rectification ratio exceeding 105 and an ideality factor of 1.2. Scanning photocurrent mapping shows that the photocurrent generation mechanism in the heterostructure switches from photovoltaic effect to photogating effect at varying drain biases, indicating both energy conversion and optical sensing are realized in a single device. In the photovoltaic mode, the photodetector is self-powered with a response time smaller than 100 µs under the illumination of a 405 nm laser. In the photogating mode, the photodetector exhibits a high responsivity up to 460 A/W originating from a high photogain. Finally, the photodetector is employed for single-pixel imaging, demonstrating its high-contrast photodetection ability. This work provides insight into the development of high-performance self-powered photodetectors based on 2D Schottky junctions.

Distinct Gut Microbiota and Arachidonic Acid Metabolism in Obesity-Prone and Obesity-Resistant Mice with a High-Fat Diet.

An imbalance of energy intake and expenditure is commonly considered as the fundamental cause of obesity. However, individual variations in susceptibility to obesity do indeed exist in both humans and animals, even among those with the same living environments and dietary intakes. To further explore the potential influencing factors of these individual variations, male C57BL/6J mice were used for the development of obesity-prone and obesity-resistant mice models and were fed high-fat diets for 16 weeks. Compared to the obesity-prone mice, the obesity-resistant group showed a lower body weight, liver weight, adipose accumulation and pro-inflammatory cytokine levels. 16S rRNA sequencing, which was conducted for fecal microbiota analysis, found that the fecal microbiome's structural composition and biodiversity had changed in the two groups. The genera Allobaculumbiota, SMB53, Desulfovibrio and Clostridium increased in the obesity-prone mice, and the genera Streptococcus, Odoribacter and Leuconostoc were enriched in the obesity-resistant mice. Using widely targeted metabolomics analysis, 166 differential metabolites were found, especially those products involved in arachidonic acid (AA) metabolism, which were significantly reduced in the obesity-resistant mice. Moreover, KEGG pathway analysis exhibited that AA metabolism was the most enriched pathway. Significantly altered bacteria and obesity-related parameters, as well as AA metabolites, exhibited strong correlations. Overall, the phenotypes of the obesity-prone and obesity-resistant mice were linked to gut microbiota and AA metabolism, providing new insight for developing an in-depth understanding of the driving force of obesity resistance and a scientific reference for the targeted prevention and treatment of obesity.

Benefits of adjuvant treatment with the Pingxiao capsule in patients with early breast cancer: A single­center retrospective cohort study.

Early breast cancer (EBC) is cancer that has not spread beyond the breast or the axillary lymph nodes. The present retrospective cohort study investigated the efficacy and safety of the Pingxiao capsule (PXC), which contains a formula of traditional Chinese herbs, as adjuvant therapy in patients with EBC in a single Chinese academic medical center. Patients with EBC who had received surgery and chemotherapy were analyzed and divided into the PXC and non-PXC groups. Disease-free survival (DFS) time, overall survival (OS) time, demographic characteristics and adverse events were examined. Kaplan-Meier survival curves were used to compare the differences in DFS and OS. A total of 371 participants with a median age of 54 years were included in this study. The median DFS time of all patients was 101 months. The overall DFS rate was 72.1% in the PXC group compared with 63.6% in the non-PXC group. For women with hormone receptor-negative tumors, the DFS rate in the PXC group was significantly higher than that in the non-PXC group, irrespective of node status. Adjuvant treatment with PXC for ≥3 months was associated with significantly longer median DFS time compared with that in the non-PXC group. In addition, the incidence of neutropenia rated to be grade 2 or higher was significantly lower in the PXC group compared with that in the control group, and a markedly, but non-significantly, lower prevalence of nausea was observed in PXC group (0 vs. 4.1%). In conclusion, PXC as an adjuvant therapy along with chemotherapy is associated with prolonged DFS times in patients with EBC when compared with chemotherapy alone. The therapeutic value of combined PXC and systemic chemotherapy should be further elucidated by rigorous prospective clinical trials.

Label-free direct detection of melamine using functionalized gold nanoparticles-based dual-fluorescence colorimetric nanoswitch sensing platform.

Developing a simple, economical, sensitive, and selective method for label-free direct detection analytes is attractive, especially the strategies that could achieve signal amplification without complicated operations. Herein, a dual-fluorescence colorimetric nanoswitch sensing platform for label-free direct melamine (MEL) detection was established. We first explored the relationship between MEL-induced aggregation of gold nanoparticles (AuNPs) and size and determined the optimal size to be 37 nm. Using surfactant Triton X-100 to modify AuNPs and clarify possible interaction mechanisms to improve detection performance. The dynamic changes of surface plasmon resonance absorption peaks in the dispersed and aggregated states of AuNPs were skillfully utilized to match the emission of multicolor gold nanoclusters to trigger the multi-inner filter effect. Accompanied by the addition of MEL-induced AuNPs to change from dispersed to aggregated state, the fluorescence of green-emitting and red-emitting gradually turned on and turned off, respectively. The fluorescence turn-on mode detection limit was 10 times higher than the colorimetric method and as low as 5.5 ng/mL; the detection took only 10 min. The sensor detected MEL in spiked milk samples with a good recovery in the range of 81.2-111.0 % with a coefficient of variation less than 11.4 % and achieved a good correlation with commercial kits. The proposed sensor integrates numerous merits of label-free, multi-signal readout, self-calibration, simple operations, and economical, which provides a promising tool for convenient on-site detection of MEL.

Fate of florfenicol and linezolid resistance genes and their bacterial hosts during two waste treatment models in swine feedlots.

Florfenicol resistance genes (FRGs) are widely present in livestock farms. The aim of this study was to evaluate the removal efficiencies of FRGs as well as the relationships between FRGs, mobile genetic elements (MGEs) and bacterial communities during the natural drying (ND) and anaerobic digestion (AD) processes of manure treatment in swine farms by combining bacterial isolation, quantitative PCR and metagenomic approaches. Solid manure showed a higher abundance of FRGs than fresh manure and was the main contamination source of fexA and fexB in ND farms, whilst biogas slurry displayed a lower abundance of FRGs than the wastewater in AD farms. Moreover, fresh manure and wastewater showed a high abundance of optrA, and wastewater was the main contamination source of cfr in both ND and AD farms. Both optrA/fexA-positive enterococci and cfr/fexA-positive staphylococci were mainly isolated along the farms' treatment processes. The cfr-positive staphylococci were highly prevalent in wastewater (57.14 % - 100 %) and may be associated with nasal-derived cfr-positive porcine staphylococci. An increased abundance of Enterococcus, Jeotgalibaca and Vagococcus in the bacterial community structures may account for the high optrA abundance in wastewater and Jeotgalibaca may be another potential host of optrA. Furthermore, the abundance of FRG-related MGEs increased by 22.63 % after the ND process and decreased by 66.96 % in AD farms. A significant correlation was observed between cfr and ISEnfa4, whereas no significance was found between optrA and IS1216E, although IS1216E is the predominant insertion sequence involved in the transfer of optrA. In conclusion, manure and wastewater represented independent pollution sources of FRGs in swine farms. Associated MGEs might play a key role in the transfer and persistence of FRGs. The AD process was more efficient in the removal of FRGs than the ND method, nevertheless a longer storage of slurry may be required for a complete removal.