Effect of ß-lactam antibiotics on the gut microbiota of term neonates.

ß-Lactam antibiotics are a class of antibiotics commonly used to treat bacterial infections. However, the effects of ß-lactam antibiotics on term neonatal intestinal flora have not been fully elucidated. Hospitalized full-term newborns receiving ß-lactam antibiotics formed the antibiotic group (n = 67), while those without antibiotic treatment comprised the non-antibiotic group (n = 47). A healthy group included healthy full-term newborns (n = 16). Stool samples were collected for 16 S rDNA sequencing to analyze gut microbiota variations. Further investigation was carried out within the ß-lactam antibiotic group, exploring the effects of antibiotic use on the newborns' gut microbiota in relation to the duration and type of antibiotic administration, delivery method, and feeding practices. The antibiotic group exhibited significant difference of microbial community composition compared to the other groups. Genera like Klebsiella, Enterococcus, Streptococcus, Alistipes, and Aeromonas were enriched, while Escherichia-Shigella, Clostridium sensu stricto 1, Bifidobacterium, and Parabacteroides were reduced. Klebsiella negatively correlated with Escherichia-Shigella, positively with Enterobacter, while Escherichia-Shigella negatively correlated with Enterococcus and Streptococcus. Regardless of neonatal age, ß-lactam antibiotics induced an elevated abundance of Klebsiella and Enterococcus. The impact on gut microbiota varied with the duration and type of antibiotic (cefotaxime or ampicillin/sulbactam). Compared to vaginal delivery, cesarean delivery after ß-lactam treatment heightened the abundance of Klebsiella, Enterobacteriaceae_Unclassified, Lactobacillales_Unclassified, and Pectobacterium. Feeding patterns minimally influenced ß-lactam-induced alterations. In conclusion, ß-lactam antibiotic treatment for neonatal pneumonia and sepsis markedly disrupted intestinal microbiota, favoring Klebsiella, Enterococcus, Streptococcus, Alistipes, and Aeromonas. The impact of ß-lactam varied by duration, type, and delivery method, emphasizing heightened disruptions post-cesarean delivery.

Tumor-Specific Nano-Herb Delivery System with High L-Arginine Loading for Synergistic Chemo and Gas Therapy against Cervical Cancer.

Cancer metastasis poses significant challenges in current clinical therapy. Osthole (OST) has demonstrated efficacy in treating cervical cancer and inhibiting metastasis. Despite these positive results, its limited solubility, poor oral absorption, low bioavailability, and photosensitivity hinder its clinical application. To address this limitation, a glutathione (GSH)-responded nano-herb delivery system (HA/MOS@OST&L-Arg nanoparticles, HMOA NPs) is devised for the targeted delivery of OST with cascade-activatable nitric oxide (NO) release. The HMOA NPs system is engineered utilizing enhanced permeability and retention (EPR) effects and active targeting mediated by hyaluronic acid (HA) binding to glycoprotein CD44. The cargoes, including OST and L-Arginine (L-Arg), are released rapidly due to the degradation of GSH-responsive mesoporous organic silica (MOS). Then abundant reactive oxygen species (ROS) are produced from OST in the presence of high concentrations of NAD(P)H quinone oxidoreductase 1 (NQO1), resulting in the generation of NO and subsequently highly toxic peroxynitrite (ONOO-) by catalyzing guanidine groups of L-Arg. These ROS, NO, and ONOO- molecules have a direct impact on mitochondrial function by reducing mitochondrial membrane potential and inhibiting adenosine triphosphate (ATP) production, thereby promoting increased apoptosis and inhibiting metastasis. Overall, the results indicated that HMOA NPs has great potential as a promising alternative for the clinical treatment of cervical cancer.

Multi-omics reveals bufadienolide Q-markers of Bufonis Venenum based on antitumor activity and cardiovascular toxicity in zebrafish.

BACKGROUND: Bufonis Venenum (BV) is a traditional animal-based Chinese medicine with therapeutic effects against cancer. However, its clinical use is significantly restricted due to associated cardiovascular risks. BV's value in China's market is typically assessed based on "content priority," focusing on indicator components. However, these components of BV possess both antitumor activity and toxicity, and the correlation between the antitumor activity and toxicity of BV has not yet been elucidated. PURPOSE: This study employs an integrated multi-omics approach to identify bufadienolide Q-markers and explore the correlation between BV's antitumor activity and toxicity. The aim is to establish a more comprehensive method for BV's quality. METHODS: Normal zebrafish and HepG2 xenograft zebrafish were chosen as activity and toxicity evaluation models. Ultra-high performance liquid chromatography (UHPLC) coupled with a linear ion trap orbitrap (LTQ-Orbitrap) mass spectrometry was used to quantify eight batches of BV and key "toxic and effective" components were screened out. Transcriptomic and metabolomic analyses were performed to elucidate the regulatory mechanisms underlying the antitumor activity and cardiovascular toxicity of the key components in BV. RESULTS: Eight key "toxic and effective" compounds were identified: resibufogenin, cinobufagin, arenobufagin, bufotalin, bufalin, gamabufotalin, desacetylcinobufagin, and telocinobufagin. The findings showed that bufalin and cinobufagin interfered with calcium homeostasis through CaV and CaSR, induced cardiotoxicity, and upregulated CASP9 to activate myocardial cell apoptosis. However, desacetylcinobufagin exhibited greater potential in terms of anti-tumor effects. Combining the results of untargeted and targeted metabolomics revealed that desacetylcinobufagin could have a callback effect on differential lipids and correct abnormal energy and amino acid metabolism caused by cancer, similar to cinobufagin and bufalin. Microscale thermophoresis (MST) ligand binding measurements also showed that the binding of desacetylcinobufagin to GPX4 has a more potent ability to induce ferroptosis in tumor cells compared to cinobufagin. CONCLUSION: An innovative evaluation method based on the zebrafish was developed to investigate the relationship between the toxicity and efficacy of BV. This study identified toxicity and activity Q-markers and explored the mechanism between the two effects of BV. The research data could offer valuable insights into the efficacy of BV. Additionally, desacetylcinobufagin, an active ingredient with low toxicity, was found to enhance the quality of BV.

Hot Electrons Induced by Localized Surface Plasmon Resonance in Ag/g-C3N4 Schottky Junction for Photothermal Catalytic CO2 Reduction.

Converting carbon dioxide (CO2) into high-value-added chemicals using solar energy is a promising approach to reducing carbon dioxide emissions; however, single photocatalysts suffer from quick the recombination of photogenerated electron-hole pairs and poor photoredox ability. Herein, silver (Ag) nanoparticles featuring with localized surface plasmon resonance (LSPR) are combined with g-C3N4 to form a Schottky junction for photothermal catalytic CO2 reduction. The Ag/g-C3N4 exhibits higher photocatalytic CO2 reduction activity under UV-vis light; the CH4 and CO evolution rates are 10.44 and 88.79 µmol·h-1·g-1, respectively. Enhanced photocatalytic CO2 reduction performances are attributed to efficient hot electron transfer in the Ag/g-C3N4 Schottky junction. LSPR-induced hot electrons from Ag nanoparticles improve the local reaction temperature and promote the separation and transfer of photogenerated electron-hole pairs. The charge carrier transfer route was investigated by in situ irradiated X-ray photoelectron spectroscopy (XPS). The three-dimensional finite-difference time-domain (3D-FDTD) method verified the strong electromagnetic field at the interface between Ag and g-C3N4. The photothermal catalytic CO2 reduction pathway of Ag/g-C3N4 was investigated using in situ diffuse reflectance infrared Fourier transform spectra (DRIFTS). This study examines hot electron transfer in the Ag/g-C3N4 Schottky junction and provides a feasible way to design a plasmonic metal/polymer semiconductor Schottky junction for photothermal catalytic CO2 reduction.

Antibiotic resistance and epidemiological characteristics of polymyxin-resistant Klebsiella pneumoniae. / è€å¤šé»èŒç´ è‚ºç‚Žå ‹é›·ä¼¯èŒçš„è¯æ•ç‰¹å¾åŠæµè¡Œç— å­¦ç‰¹ç‚¹.

OBJECTIVES: The emergence of polymyxin-resistant Klebsiella pneumoniae (KPN) in clinical settings necessitates an analysis of its antibiotic resistance characteristics, epidemiological features, and risk factors for its development. This study aims to provide insights for the prevention and control of polymyxin-resistant KPN infections. METHODS: Thirty clinical isolates of polymyxin-resistant KPN were collected from the Third Xiangya Hospital of Central South University. Their antibiotic resistance profiles were analyzed. The presence of carbapenemase KPC, OXA-48, VIM, IMP, and NDM was detected using colloidal gold immunochromatography. Hypervirulent KPN was initially screened using the string test. Biofilm formation capacity was assessed using crystal violet staining. Combination drug susceptibility tests (polymyxin B with meropenem, tigecycline, cefoperazone/sulbactam) were conducted using the checkerboard method. Polymyxin-related resistance genes were detected by PCR. Multi-locus sequence typing (MLST) was performed for genotyping and phylogenetic tree construction. The study also involved collecting data from carbapenem-resistant (CR)-KPN polymyxin-resistant strains (23 strains, experimental group) and CR-KPN polymyxin-sensitive strains (57 strains, control group) to analyze potential risk factors for polymyxin-resistant KPN infection through univariate analysis and multivariate Logistic regression. The induction of resistance by continuous exposure to polymyxin B and colistin E was also tested. RESULTS: Among the 30 polymyxin-resistant KPN isolates, 28 were CR-KPN, all producing KPC enzyme. Four isolates were positive in the string test. Most isolates showed strong biofilm formation capabilities. Combination therapy showed additive or synergistic effects. All isolates carried the pmrA and phoP genes, while no mcr-1 or mcr-2 genes were detected. MLST results indicated that ST11 was the predominant type. The phylogenetic tree suggested that polymyxin-resistant KPN had not caused a hospital outbreak in the institution. The use of two or more different classes of antibiotics and the use of polymyxin were identified as independent risk factors for the development of polymyxin-resistant strains. Continuous use of polymyxin induced drug resistance. CONCLUSIONS: Polymyxin-resistant KPN is resistant to nearly all commonly used antibiotics, making polymyxin-based combination therapy a viable option. No plasmid-mediated polymyxin-resistant KPN has been isolated in the hospital. Polymyxin can induce resistance in KPN, highlighting the need for rational antibiotic use in clinical settings to delay the emergence of resistance.

A novel coupling interpretable machine learning framework for water quality prediction and environmental effect understanding in different flow discharge regulations of hydro-projects.

Machine learning models (MLMs) have been increasingly used to forecast water pollution. However, the "black box" characteristic for understanding mechanism processes still limits the applicability of MLMs for water quality management in hydro-projects under complex and frequently artificial regulation. This study proposes an interpretable machine learning framework for water quality prediction coupled with a hydrodynamic (flow discharge) scenario-based Random Forest (RF) model with multiple model-agnostic techniques and quantifies global, local, and joint interpretations (i.e., partial dependence, individual conditional expectation, and accumulated local effects) of environmental factor implications. The framework was applied and verified to predict the permanganate index (CODMn) under different flow discharge regulation scenarios in the Middle Route of the South-to-North Water Diversion Project of China (MRSNWDPC). A total of 4664 sampling cases data matrices, including water quality, meteorological, and hydrological indicators from eight national stations along the main canal of the MRSNWDPC, were collected from May 2019 to December 2020. The results showed that the RF models were effective in forecasting CODMn in all flow discharge scenarios, with a mean square error, coefficient of determination, and mean absolute error of 0.006-0.026, 0.481-0.792, and 0.069-0.104, respectively, in the testing dataset. A global interpretation indicated that dissolved oxygen, flow discharge, and surface pressure are the three most important variables of CODMn. Local and joint interpretations indicated that the RF-based prediction model provides a basic understanding of the physical mechanisms of environmental systems. The proposed framework can effectively learn the fundamental environmental implications of water quality variations and provide reliable prediction performance, highlighting the importance of model interpretability for trustworthy machine learning applications in water management projects. This study provides scientific references for applying advanced data-driven MLMs to water quality forecasting and a reliable methodological framework for water quality management and similar hydro-projects.

Relationships between water quality of a long-distance inter-basin water diversion project and air pollution emissions along the canal: Distributions, lag effects, and nonlinear responses.

Understanding and quantifying the influences and contributions of air pollution emissions on water quality variations is critically important for surface water quality protection and management. To address this, we created a five-year daily data matrix of six water quality indicators-permanganate index (CODMn), NH3-N, pH, turbidity, conductivity, and dissolved organic matter (DOM)-and six air pollution indicators-O3, CO, NO2, SO2, 2.5 µm particulate matter (PM2.5), and inhalable particles (PM10)-using data from seven national monitoring stations along the world's longest water-diversion project, the Middle Route of the South-to-North Water Diversion Project in China (MR-SNWD). Multivariate techniques (Mann-Kendall, Spearman's correlation, lag correlation, and Generalized Additive Models [GAMs]) were applied to examine the nonlinear relationships and lag effects of air pollution on water quality. Air pollution and water quality exhibited marked spatial heterogeneity along the MR-SNWD, with all water quality parameters meeting Class I or II national standards and the air pollution indicators exceeding those thresholds. Except for CODMn and DOM, the other water quality and air pollution indicators exhibited significant seasonal differences. Air pollution exhibited significant lag effects on water quality at the northern stations, with NO2, SO2, PM2.5, and PM10 being highly correlated with changes in pH, with an average lag of 17 d. Based on the GAMs, lag effects enhanced the significant nonlinear relationships between air pollution and water quality, increasing the average deviance explained for CODMn, NH3-N, and pH by 93%, 24%, and 41%, respectively. These findings provide a scientific basis for protecting water quality along the long-distance inter-basin water-diversion project under anthropogenic air pollution.

A Visualized Nomogram for Predicting Prognosis in Elderly Patients after Percutaneous Coronary Intervention.

Background: Revascularized patients still experience adverse cardiovascular events. This is particularly true for elderly patients over the age of 65, as they often have more co-morbid vascular conditions. It is important to develop a tool to assist clinicians in comprehensively assessing these patients' prognosis. The objective of this study is to create a comprehensive visual nomogram model combining clinical and physiological assessments to predict outcomes in elderly patients undergoing percutaneous coronary intervention (PCI). Methods: This study is a retrospective investigation of patients who underwent PCI between January 2016 and December 2017. A total of 691 patients with 1461 vessels were randomly divided into a training (n = 483) and a validation set (n = 208). A multivariate Cox regression model was employed using the training set to select variables for constructing a nomogram. The performance of the nomogram was assessed through the receiver operating characteristic curve (ROC) and calibration curves to evaluate its discrimination and predictive accuracy. To further assess the clinical usefulness, Kaplan-Meier curve analysis and landmark analysis were conducted. Results: Independent risk factors, including diabetes mellitus (DM), post-PCI quantitative flow ratio (QFR), previous myocardial infarction (MI), and previous PCI, were contained in the nomogram. The nomogram exhibited a good area under the curve (AUC) ranging from 0.742 to 0.789 in the training set, 0.783 to 0.837 in the validation set, and 0.764 to 0.786 in the entire population. Calibration curves demonstrated a well-fitted curve in all three sets. The Kaplan-Meier curves showed clear separation and the patients with higher scores in the nomogram model exhibited a higher incidence of target vessel revascularization (TVR) (7.99% vs. 1.24% for 2-year, p < 0.001 and 13.54% vs. 2.23% for 5-years, p < 0.001, respectively). Conclusions: This study has developed the visually intuitive nomogram to predict the 2-year and 5-year TVR rates for elderly patients who underwent PCI. This tool provides more accurate and comprehensive healthcare guidance for patients and their physicians.

Multi-parametric MRI-based machine learning model for prediction of pathological grade of renal injury in a rat kidney cold ischemia-reperfusion injury model.

BACKGROUND: Renal cold ischemia-reperfusion injury (CIRI), a pathological process during kidney transplantation, may result in delayed graft function and negatively impact graft survival and function. There is a lack of an accurate and non-invasive tool for evaluating the degree of CIRI. Multi-parametric MRI has been widely used to detect and evaluate kidney injury. The machine learning algorithms introduced the opportunity to combine biomarkers from different MRI metrics into a single classifier. OBJECTIVE: To evaluate the performance of multi-parametric magnetic resonance imaging for grading renal injury in a rat model of renal cold ischemia-reperfusion injury using a machine learning approach. METHODS: Eighty male SD rats were selected to establish a renal cold ischemia -reperfusion model, and all performed multiparametric MRI scans (DWI, IVIM, DKI, BOLD, T1mapping and ASL), followed by pathological analysis. A total of 25 parameters of renal cortex and medulla were analyzed as features. The pathology scores were divided into 3 groups using K-means clustering method. Lasso regression was applied for the initial selecting of features. The optimal features and the best techniques for pathological grading were obtained. Multiple classifiers were used to construct models to evaluate the predictive value for pathology grading. RESULTS: All rats were categorized into mild, moderate, and severe injury group according the pathologic scores. The 8 features that correlated better with the pathologic classification were medullary and cortical Dp, cortical T2*, cortical Fp, medullary T2*, ∆T1, cortical RBF, medullary T1. The accuracy(0.83, 0.850, 0.81, respectively) and AUC (0.95, 0.93, 0.90, respectively) for pathologic classification of the logistic regression, SVM, and RF are significantly higher than other classifiers. For the logistic model and combining logistic, RF and SVM model of different techniques for pathology grading, the stable and perform are both well. Based on logistic regression, IVIM has the highest AUC (0.93) for pathological grading, followed by BOLD(0.90). CONCLUSION: The multi-parametric MRI-based machine learning model could be valuable for noninvasive assessment of the degree of renal injury.

Biomechanical effects of deltoid muscle atrophy on rotator cuff tissue: a finite element study.

The deltoid muscle and rotator cuff tissue are structural components that maintain the dynamic stability of the shoulder joint. However, atrophy of the deltoid muscle may affect the stability of the shoulder joint, which in turn alters the mechanical distribution of rotator cuff tissue. Currently, the effect of muscle volume changes in the deltoid muscle on reducing the load on the rotator cuff tissue is still unknown. Therefore, this paper intends to analyze the mechanical changes of rotator cuff tissue by deltoid muscle atrophy through finite elements. Based on previously published finite element shoulder models, the deltoid muscle was modeled by constructing deltoid muscle models with different degrees of atrophy as, 100% deltoid muscle (Group 1), 80% deltoid muscle (Group 2), and 50% deltoid muscle (Group 3), respectively. The three models were given the same external load to simulate glenohumeral joint abduction, and the stress changes in the rotator cuff tissue were analyzed and recorded. In all three models, the stress in the rotator cuff tissue showed different degrees of increase with the increase of abduction angle, especially in the supraspinatus muscle. At 90° of glenohumeral abduction, supraspinatus stress increased by 58% and 118% in Group 2 and Group 3, respectively, compared with Group 1; In the subscapularis, the stress in Group 3 increased by 59% and 25% compared with Group 1 and Group 2, respectively. In addition, the stress of the infraspinatus muscle and teres minor muscle in Group 2 and Group 3 were higher than that in Group 1 during the abduction angle from 30° to 90°. Deltoid atrophy alters the abduction movement pattern of the glenohumeral joint. During glenohumeral abduction activity, deltoid atrophy significantly increases the stress on the rotator cuff tissue, whereas normal deltoid volume helps maintain the mechanical balance of the rotator cuff tissue.

Clinicopathological and molecular characterization of extra-appendix goblet cell adenocarcinomas.

Goblet cell adenocarcinoma (GCA) is a distinctive type of endocrine-exocrine mixed tumor, exhibiting intermediate morphological features between neuroendocrine tumor and adenocarcinoma. It predominantly arises in the appendix, but primary extra-appendiceal GCA is extremely rare. Here, we presented six cases of primary extra-appendiceal GCA from 2016 to 2022. Notably, one case was originating in the bladder which was the first report of primary GCA to occur outside the digestive tract. The tumors frequently displayed variable goblet cell morphology, characterized by cytoplasmic mucin accumulation and basally located nucleus. Low-grade components typically exhibited glandular or clustered patterns without prominent fibrotic responses. High-grade components demonstrated cribriform, cluster and single-file arrangement accompanied by marked fibrous reactions. Immunohistochemically, the tumors showed positivity for both neuroendocrine markers（synaptophysin, chromogranin A, CD56 ）and adenoids markers（CDX-2, CK20）. Next-generation sequencing revealed the most prevalent mutated genes within GCAs were TP53. Due to their morphological and immunohistochemical similarities to primary appendiceal GCA counterparts, we propose a distinct category for extra-appendiceal Goblet cell adenocarcinoma.

Novel post-translational modifications of protein by metabolites with immune responses and immune-related molecules in cancer immunotherapy.

Tumour immunotherapy is an effective and essential treatment for cancer. However, the heterogeneity of tumours and the complex and changeable tumour immune microenvironment (TME) creates many uncertainties in the clinical application of immunotherapy, such as different responses to tumour immunotherapy and significant differences in individual efficacy. It makes anti-tumour immunotherapy face many challenges. Immunometabolism is a critical determinant of immune cell response to specific immune effector molecules, significantly affecting the effects of tumour immunotherapy. It is attributed mainly to the fact that metabolites can regulate the function of immune cells and immune-related molecules through the protein post-translational modifications (PTMs) pathway. This study systematically summarizes a variety of novel protein PTMs including acetylation, propionylation, butyrylation, succinylation, crotonylation, malonylation, glutarylation, 2-hydroxyisobutyrylation, ß-hydroxybutyrylation, benzoylation, lactylation and isonicotinylation in the field of tumour immune regulation and immunotherapy. In particular, we elaborate on how different PTMs in the TME can affect the function of immune cells and lead to immune evasion in cancer. Lastly, we highlight the potential treatment with the combined application of target-inhibited protein modification and immune checkpoint inhibitors (ICIs) for improved immunotherapeutic outcomes.

Optimizing UAV spray parameters to improve precise control of tobacco pests at different growth stages.

BACKGROUND: Unmanned aerial vehicles (UAVs) for pesticide application show promising potential in tobacco pest management. However, the impact of flight parameters on spray efficacy requires further investigation. Three field experiments were conducted from the rosette to the maturation stage of tobacco to systematically assess spray efficacy under varying flight heights, speeds, and application volumes. Using a multi-index weight analysis method, optimal operational parameter combinations for different tobacco growth stages were evaluated and compared with backpack electric sprayers. RESULTS: For the rosette stage, the recommended parameter is a flight speed of 5 m s-1, a flight height of 2 m, and a liquid application volume of 30 L hm-2; during the vigorous growth stage, the suggested parameter includes a flight speed of 3 m s-1, a flight height of 2 m, and a liquid application volume of 22.5 L hm-2. In the maturing stage, optimal parameter consists of a flight speed of 3 m s-1, a flight height of 3.5 m, and a liquid application volume of 30 L hm-2. Furthermore, UAV spraying achieves higher droplet deposition on both sides of tobacco leaves compared to traditional electric backpack sprayers. CONCLUSIONS: Adjusting UAV spraying parameters for different tobacco growth stages is crucial. These results can provide the methods for the precise control technology of tobacco pests at different growth stages. © 2024 Society of Chemical Industry.

NSUN6-mediated 5-methylcytosine modification of NDRG1 mRNA promotes radioresistance in cervical cancer.

BACKGROUND: Radioresistance is the leading cause of death in advanced cervical cancer (CC). Dysregulation of RNA modification has recently emerged as a regulatory mechanism in radiation and drug resistance. We aimed to explore the biological function and clinical significance of 5-methylcytosine (m5C) in cervical cancer radiosensitivity. METHODS: The abundance of RNA modification in radiotherapy-resistant and sensitive CC specimens was quantified by liquid chromatography-tandem mass spectrometry. The essential RNA modification-related genes involved in CC radiosensitivity were screened via RNA sequencing. The effect of NSUN6 on radiosensitivity was verified in CC cell lines, cell-derived xenograft (CDX), and 3D bioprinted patient-derived organoid (PDO). The mechanisms of NSUN6 in regulating CC radiosensitivity were investigated by integrative m5C sequencing, mRNA sequencing, and RNA immunoprecipitation. RESULTS: We found a higher abundance of m5C modification in resistant CC samples, and NSUN6 was the essential m5C-regulating gene concerning radiosensitivity. NSUN6 overexpression was clinically correlated with radioresistance and poor prognosis in cervical cancer. Functionally, higher NSUN6 expression was associated with radioresistance in the 3D PDO model of cervical cancer. Moreover, silencing NSUN6 increased CC radiosensitivity in vivo and in vitro. Mechanistically, NDRG1 was one of the downstream target genes of NSUN6 identified by integrated m5C-seq, mRNA-seq, and functional validation. NSUN6 promoted the m5C modification of NDRG1 mRNA, and the m5C reader ALYREF bound explicitly to the m5C-labeled NDRG1 mRNA and enhanced NDRG1 mRNA stability. NDRG1 overexpression promoted homologous recombination-mediated DNA repair, which in turn led to radioresistance in cervical cancer. CONCLUSIONS: Aberrant m5C hypermethylation and NSUN6 overexpression drive resistance to radiotherapy in cervical cancer. Elevated NSUN6 expression promotes radioresistance in cervical cancer by activating the NSUN6/ALYREF-m5C-NDRG1 pathway. The low expression of NSUN6 in cervical cancer indicates sensitivity to radiotherapy and a better prognosis.

Directed differentiation of pancreatic δ cells from human pluripotent stem cells.

Dysfunction of pancreatic δ cells contributes to the etiology of diabetes. Despite their important role, human δ cells are scarce, limiting physiological studies and drug discovery targeting δ cells. To date, no directed δ-cell differentiation method has been established. Here, we demonstrate that fibroblast growth factor (FGF) 7 promotes pancreatic endoderm/progenitor differentiation, whereas FGF2 biases cells towards the pancreatic δ-cell lineage via FGF receptor 1. We develop a differentiation method to generate δ cells from human stem cells by combining FGF2 with FGF7, which synergistically directs pancreatic lineage differentiation and modulates the expression of transcription factors and SST activators during endoderm/endocrine precursor induction. These δ cells display mature RNA profiles and fine secretory granules, secrete somatostatin in response to various stimuli, and suppress insulin secretion from in vitro co-cultured ß cells and mouse ß cells upon transplantation. The generation of human pancreatic δ cells from stem cells in vitro would provide an unprecedented cell source for drug discovery and cell transplantation studies in diabetes.

Fast and non-invasive identification of Baijiu based on Tyndall effect and chemometrics.

The value of Baijiu is affected by its flavor, age, and adulteration. Therefore, a simple and rapid identification method is crucial for the market. In this study, we present a rapid, non-intrusive identification technique for Baijiu utilizing the Tyndall effect combined with chemometrics analysis. Our experiment begins illuminating Baijiu with a 405 nm wavelength laser and recording the resulting bright light path due to the Tyndall effect. To further analyze the color and brightness information, Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Hierarchical Cluster Analysis (HCA), and Multilayer Perceptron (MLP) were employed. This study establishes correlations between the brightness of the Tyndall light path and seven trace flavor compounds in Baijiu. The findings demonstrate that this method effectively identifies the flavor, age cellar, and adulteration of Baijiu and also quantitatively detects the concentrations of flavor compounds. Additionally, an analysis platform was developed to enable the rapid identification of Baijiu.

Bone injury imaging in knee and ankle joints using fast-field-echo resembling a CT using restricted echo-spacing MRI: a feasibility study.

Purpose: To explore the consistency of FRACTURE (Fast-field-echo Resembling A CT Using Restricted Echo-spacing) MRI and X-Ray/computerized tomography (CT) in the evaluation of bone injuries in knee and ankle joints. Methods: From Nov. 2020 to Jul. 2023, 42 patients with knee joint or ankle joint injuries who underwent FRACTURE MRI examinations were retrospectively collected. 11 patients were examined by both X-Ray and FRACTURE examinations. 31 patients were examined by both CT and FRACTURE examinations. The fracture, osteophyte, and bone destruction of the joints were evaluated by two radiologists using X-Ray/CT and FRACTURE images, respectively. Kappa test was used for consistency analysis. Results: The evaluation consistency of fracture, osteophyte and bone destruction via X-Ray and FRACTURE images by radiologist 1 were 0.879, 0.867 and 0.847 respectively, and for radiologist 2 were 0.899, 0.930, and 0.879, respectively. The evaluation consistency of fracture, osteophyte and bone destruction via CT and FRACTURE images by radiologist 1 were 0.938, 0.937 and 0.868 respectively, and for radiologist 2 were 0.961, 0.930, and 0.818, respectively. Conclusion: For fracture, osteophyte, and bone destruction of knee and ankle joints. FRACTURE MRI showed a high consistency with X-Ray/CT examinations.

High Young's Modulus Li6.4La3Zr1.4Ta0.6O12-Based Solid Electrolyte Interphase Regulating Lithium Deposition for Dendrite-Free Lithium Metal Anode.

Artificial solid electrolyte interphase (SEI) layers have been widely regarded as an effective protection for lithium (Li) metal anodes. In this work, an artificial SEI film consisting of dense Li6.4La3Zr1.4Ta0.6O12 (LLZTO) nanoparticles and polymerized styrene butadiene rubber is designed, which has good mechanical and chemical stability to effectively prevent Li anode corrosion by the electrolyte. The LLZTO-based SEI film can not only guide Li to uniformly deposit at the interface but also accelerate the electrochemical reaction kinetics due to its high Li+ conductivity. In particular, the high Young's modulus of the LLZTO-based SEI will regulate e- distribution in the continuous Li plating/stripping process and achieve uniform deposition of Li. As a consequence, the Li anode with LLZTO-based SEI (Li@LLZTO) enables symmetric cells to demonstrate a stable overpotential of 25 mV for 600 h at a current density of 1 mA cm-2 for 1 mA h cm-2. The Li@LLZTO||LFP (LiFePO4) full cell exhibits a capacity of 106 mA h g-1 after 800 cycles at 5 C with retention as high as 90%. Our strategy here suggests that the artificial SEI with high Young's modulus effectively inhibits the formation of Li dendrites and provides some guidance for the design of higher performance Li metal batteries.

Acceleration of uterine 3D T2-weighted imaging by compressed SENSE-a multicentre study.

OBJECTIVES: To find the optimal acceleration factor (AF) of the compressed SENSE (CS) technique for uterine isotropic high-resolution 3D T2-weighted imaging (3D-ISO-T2WI). METHODS: A total of 91 female volunteers from the First Affiliated Hospital of Dalian Medical University, Chu Hsien-I Memorial Hospital and Tianjin Institute of Endocrinology, and The Fourth Hospital of Harbin were recruited. A total of 44 volunteers received uterus sagittal 3D-ISO-T2WI scans on 3.0T MRI device with different CS AFs (including SENSE3, CS3, CS4, CS5, CS6, and CS7), 51 received 3D-ISO-T2WI scans with different degrees of fat suppression (none, light, moderate, and severe), while 4 volunteers received both series of scans. Image quality was subjectively evaluated with a 3-point scoring system. Junction zone signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and myometrial SNR were also calculated. Intraclass correlation coefficients were used to analyse the consistency of the measurement results by 2 observers. Analysis of variance test or Friedman rank sum test was used to compare the differences in subjective scores, SNR, and CNR under different AFs/different degrees of fat suppression. RESULTS: Images by AFs of CS3, CS4, and CS5 had the highest SNR and CNR. Among them, CS5 had the shortest scan time. CS5 also had one of the highest subjective scores. There was no significant difference in SNR and CNR among images acquired with different degrees of fat suppression. Also, images with moderate fat suppression had the highest subjective scores. CONCLUSION: The CS5 combined with moderate fat suppression is recommended for routine female pelvic 3D-ISO-T2WI scan. ADVANCES IN KNOWLEDGE: The CS5 has the highest image quality and has the shortest scan time, which is the best AF. Moderate fat suppression has the highest subjective scores. The CS5 and moderate fat suppression are the best combination for a female pelvic 3D-ISO-T2WI scan.

GOLPH3 inhibits erastin-induced ferroptosis in colorectal cancer cells.

Ferroptosis is a novel form of programmed cell death and is considered to be a druggable target for colorectal cancer (CRC) therapy. However, the role of ferroptosis in CRC and its underlying mechanism are not fully understood. In the present study we found that a protein enriched in the Golgi apparatus, Golgi phosphoprotein 3 (GOLPH3), was overexpressed in human CRC tissue and in several CRC cell lines. The expression of GOLPH3 was significantly correlated with the expression of ferroptosis-related genes in CRC. The overexpression of GOLPH3 in Erastin-induced Caco-2 CRC cells reduced ferroptotic phenotypes, whereas the knockdown of GOLPH3 potentiated ferroptosis in HT-29 CRC cells. GOLPH3 induced the expression of prohibitin-1 (PHB1) and prohibitin-2 (PHB2), which also inhibited ferroptosis in Erastin-treated CRC cells. Moreover, GOLPH3 interacted with PHB2 and nuclear factor erythroid 2-related factor 2 (NRF2) in Caco-2 cells. These observations indicate that GOLPH3 is a negative regulator of ferroptosis in CRC cells. GOLPH3 protects these cells from ferroptosis by inducing the expression of PHB1 and PHB2, and by interacting with PHB2 and NRF2.