Waterborne polyurethane nanoparticles incorporating linoleic acid as a potential strategy for controlling antibiotic resistance spread in the mammalian intestine.

Plasmid-mediated conjugative transfer of antibiotic resistance genes (ARGs) within the human and animal intestine represents a substantial global health concern. linoleic acid (LA) has shown promise in inhibiting conjugation in vitro, but its in vivo effectiveness in the mammalian intestinal tract is constrained by challenges in efficiently reaching the target site. Recent advancements have led to the development of waterborne polyurethane nanoparticles for improved drug delivery. In this study, we synthesized four waterborne polyurethane nanoparticles incorporating LA (WPU@LA) using primary raw materials, including N-methyldiethanolamine, 2,2'-(piperazine-1,4-diyl) diethanol, isophorone diisocyanate, castor oil, and acetic acid. These nanoparticles, identified as WPU0.89@LA, WPU0.99@LA, WPU1.09@LA, and WPU1.19@LA, underwent assessment for their pH-responsive release property and biocompatibility. Among these, WPU0.99@LA displayed superior pH-responsive release properties and biocompatibility towards Caco-2 and IPEC-J2 cells. In a mouse model, a dosage of 10 mg/kg/day WPU0.99@LA effectively reduced the conjugation of IncX4 plasmids carrying the mobile colistin resistance gene (mcr-1) by more than 45.1-fold. In vivo toxicity assessment demonstrated that 10 mg/kg/day WPU0.99@LA maintains desirable biosafety and effectively preserves gut microbiota homeostasis. In conclusion, our study provides crucial proof-of-concept support, demonstrating that WPU0.99@LA holds significant potential in controlling the spread of antibiotic resistance within the mammalian intestine.

Knowledge-based machine learning for predicting and understanding the androgen receptor (AR)-mediated reproductive toxicity in zebrafish.

Traditional methods for identifying endocrine-disrupting chemicals (EDCs) that activate androgen receptors (AR) are costly, time-consuming, and low-throughput. This study developed a knowledge-based deep neural network model (AR-DNN) to predict AR-mediated adverse outcomes on female zebrafish fertility. This model started with chemical fingerprints as the input layer and was implemented through a five-layer virtual AR-induced adverse outcome pathway (AOP). Results indicated that the AR-DNN effectively and accurately screens new reproductive toxicants (AUC = 0.94, accuracy = 0.85), providing potential toxicity pathways. Furthermore, 1477 and 2448 chemicals that could lead to infertility were identified in the plastic additives list (PLASTICMAP, n = 7112) and the Inventory of Existing Chemical Substances in China (IECSC, n = 17741), respectively. Colourants containing steroid-like structures are the major active plastic additives that might lower female zebrafish fertility through AR binding, DNA binding, and transcriptional activation. While active IECSC chemicals primarily have the same fragments, such as benzonitrile, nitrobenzene, and quinolone. The predicted toxicity pathways were consistent with existing fish evidence, demonstrating the model's applicability. This knowledge-based approach offers a promising computational toxicology strategy for predicting and characterising the endocrine-disrupting effects and toxic mechanisms of organic chemicals, potentially leading to more efficient and cost-effective screening of EDCs.

Sequence-Dependent Single-Molecule DNA Sensing Using Covalent Organic Framework Nanopores.

Enzyme-free single-molecule sequencing has the potential to significantly expand the application of nanopore technology to DNA, proteins, and saccharides. Despite their advantages over biological nanopores and natural suitability for enzyme-free single-molecule sequencing, conventional solid-state nanopores have not yet achieved single-molecule DNA sequencing. The biggest challenge for the accuracy of single-molecule sequencing using solid-state nanopores lies in the precise control of the pore size and conformity. In this study, we fabricated nanopore devices by covering the tip of a quartz nanopipette with ultrathin two-dimensional (2D) covalent organic framework (COF) nanosheets (pore size ≈ 1.1 nm). The size of the periodically arranged nanopores in COF is comparable to that of protein nanopores, and the structure of each COF nanopore is consistent at the atomic scale. The COF nanopore device could roughly distinguish dAMP, dCMP, dGMP, and dTMP. Furthermore, a certain percentage of the current blockades originating from 150 nucleotides model DNA molecules (13.5% for dA50dC50dA50 and 11.1% for dC50dA50dC50) show distinct DNA sequence-specific concave and convex resistive current patterns. The finite element simulation confirmed that the current blockade pattern of a DNA molecule passing through a COF nanopore is dependent on the relative location of the nanopore with respect to the wall of the nanopipette. Our study is a significant step toward single-molecule DNA sequencing by solid-state nanopores.

An activity-based sensing fluorogenic probe for monitoring O-methyltransferase in plants.

Activity-based sensing probes are powerful tools for monitoring enzymatic activities in complex biological samples such as cellular and live animals; however, their application in plants remains challenging. Herein, fourteen activity-based fluorescent probes were assayed against Arabidopsis O-methyltransferases (AtOMTs). One probe, 3-BTD, displayed a high selectivity, reactivity, and fluorescence response toward AtOMTs especially the isoform AtCCoAOMT. We further characterized the features of this probe and explored whether it could be used to detect OMT activities in living plant cells. Our results show that 3-BTD can be used to visualize OMT activity in Arabidopsis, and no fluorescent signal was observed in the comt/ccoaomt double mutant, indicating that it has good specificity. Interestingly, in contrast to the observation that AtCCoAOMT-YFP accumulated in both cytoplasm and nucleus, OMT enzymatic activity tracked by 3-BTD probe was found only in the cytoplasm. This underscores the importance of activity-based sensing in studying protein function. Moreover, 3-BTD can be successfully applied in OMT visualization of different plants. This study indicates that 3-BTD can serve as a potential probe for in situ monitoring the real activity of OMT in multiple plants and provides a strategy for visualizing the activity of other enzymes in plants.

Development of machine learning-based personalized predictive models for risk evaluation of hepatocellular carcinoma in hepatitis B virus-related cirrhosis patients with low levels of serum alpha-fetoprotein.

INTRODUCTION AND OBJECTIVES: The increasing incidence of hepatocellular carcinoma (HCC) in China is an urgent issue, necessitating early diagnosis and treatment. This study aimed to develop personalized predictive models by combining machine learning (ML) technology with a demographic, medical history, and noninvasive biomarker data. These models can enhance the decision-making capabilities of physicians for HCC in hepatitis B virus (HBV)-related cirrhosis patients with low serum alpha-fetoprotein (AFP) levels. PATIENTS AND METHODS: A total of 6,980 patients treated between January 2012 and December 2018 were included. Pre-treatment laboratory tests and clinical data were obtained. The significant risk factors for HCC were identified, and the relative risk of each variable affecting its diagnosis was calculated using ML and univariate regression analysis. The data set was then randomly partitioned into validation (20 %) and training sets (80 %) to develop the ML models. RESULTS: Twelve independent risk factors for HCC were identified using Gaussian naïve Bayes, extreme gradient boosting (XGBoost), random forest, and least absolute shrinkage and selection operation regression models. Multivariate analysis revealed that male sex, age >60 years, alkaline phosphate >150 U/L, AFP >25 ng/mL, carcinoembryonic antigen >5 ng/mL, and fibrinogen >4 g/L were the risk factors, whereas hypertension, calcium <2.25 mmol/L, potassium ≤3.5 mmol/L, direct bilirubin >6.8 µmol/L, hemoglobin <110 g/L, and glutamic-pyruvic transaminase >40 U/L were the protective factors in HCC patients. Based on these factors, a nomogram was constructed, showing an area under the curve (AUC) of 0.746 (sensitivity = 0.710, specificity=0.646), which was significantly higher than AFP AUC of 0.658 (sensitivity = 0.462, specificity=0.766). Compared with several ML algorithms, the XGBoost model had an AUC of 0.832 (sensitivity = 0.745, specificity=0.766) and an independent validation AUC of 0.829 (sensitivity = 0.766, specificity = 0.737), making it the top-performing model in both sets. The external validation results have proven the accuracy of the XGBoost model. CONCLUSIONS: The proposed XGBoost demonstrated a promising ability for individualized prediction of HCC in HBV-related cirrhosis patients with low-level AFP.

Transcriptomic decoding of regional cortical vulnerability to major depressive disorder.

Previous studies in small samples have identified inconsistent cortical abnormalities in major depressive disorder (MDD). Despite genetic influences on MDD and the brain, it is unclear how genetic risk for MDD is translated into spatially patterned cortical vulnerability. Here, we initially examined voxel-wise differences in cortical function and structure using the largest multi-modal MRI data from 1660 MDD patients and 1341 controls. Combined with the Allen Human Brain Atlas, we then adopted transcription-neuroimaging spatial correlation and the newly developed ensemble-based gene category enrichment analysis to identify gene categories with expression related to cortical changes in MDD. Results showed that patients had relatively circumscribed impairments in local functional properties and broadly distributed disruptions in global functional connectivity, consistently characterized by hyper-function in associative areas and hypo-function in primary regions. Moreover, the local functional alterations were correlated with genes enriched for biological functions related to MDD in general (e.g., endoplasmic reticulum stress, mitogen-activated protein kinase, histone acetylation, and DNA methylation); and the global functional connectivity changes were associated with not only MDD-general, but also brain-relevant genes (e.g., neuron, synapse, axon, glial cell, and neurotransmitters). Our findings may provide important insights into the transcriptomic signatures of regional cortical vulnerability to MDD.

Prediction of non-muscle invasive bladder cancer recurrence using deep learning of pathology image.

We aimed to build a deep learning-based pathomics model to predict the early recurrence of non-muscle-infiltrating bladder cancer (NMIBC) in this work. A total of 147 patients from Xuzhou Central Hospital were enrolled as the training cohort, and 63 patients from Suqian Affiliated Hospital of Xuzhou Medical University were enrolled as the test cohort. Based on two consecutive phases of patch level prediction and WSI-level predictione, we built a pathomics model, with the initial model developed in the training cohort and subjected to transfer learning, and then the test cohort was validated for generalization. The features extracted from the visualization model were used for model interpretation. After migration learning, the area under the receiver operating characteristic curve for the deep learning-based pathomics model in the test cohort was 0.860 (95% CI 0.752-0.969), with good agreement between the migration training cohort and the test cohort in predicting recurrence, and the predicted values matched well with the observed values, with p values of 0.667766 and 0.140233 for the Hosmer-Lemeshow test, respectively. The good clinical application was observed using a decision curve analysis method. We developed a deep learning-based pathomics model showed promising performance in predicting recurrence within one year in NMIBC patients. Including 10 state prediction NMIBC recurrence group pathology features be visualized, which may be used to facilitate personalized management of NMIBC patients to avoid ineffective or unnecessary treatment for the benefit of patients.

Burden of digestive system diseases in China and its provinces during 1990-2019: Results of the 2019 Global Disease Burden Study.

BACKGROUND: Evaluating the impact of digestive system diseases is vital for devising effective prevention strategies. However, comprehensive reports on the burden of digestive system diseases in China are lacking. Our study aimed to provide an overview of the burden and trends of digestive system diseases from 1990 to 2019 in China and its provinces. METHODS: This cross-sectional study utilized the Global Disease Burden Study 2019 to estimate the incidence, mortality rate, disability-adjusted life years (DALYs), years of life disability, years of life lost, and changes in the burden of digestive diseases across 31 Chinese provinces from 1990 to 2019. The analysis of disease burden primarily examines the characteristics of sub-disease distribution, time trends, age distribution, and sex distribution. Additionally, we compared provincial age-standardized DALYs for digestive diseases with the expected rates based on the socio-demographic index (SDI). RESULTS: In 2019, there were 499.2 million cases of digestive system diseases in China, resulting in 1,557,310 deaths. Stomach cancer, colon and rectal cancer, and esophageal cancer are the top three diseases associated with mortality and DALY related to digestive system diseases. Meanwhile, cirrhosis and other chronic liver diseases, gastroesophageal reflux disease, and gallbladder and biliary diseases are the top three kinds of diseases with the highest prevalence among digestive system diseases. The risk of gastric cancer sharply increases among men after the age of 40 years, leading to a significant disparity in burden between men and women. As the SDI increased, the DALYs associated with digestive system diseases in China and its provinces showed a downward trend. CONCLUSION: Our study highlights the inverse correlation between DALYs associated with digestive system diseases and the SDI, providing valuable insights that can assist public health officials in the estimation of the disease burden in this area.

Mechanochemical synthesis of novel metronidazole cocrystal: Structure characterization and pharmaceutical properties study.

A new cocrystalline form of metronidazole (MET) with propyl gallate (PRO), referred to as MET-PRO, has been successfully synthesized and characterized. Structural characterization reveals that MET and PRO are present in a 1:1 ratio within the cocrystal lattice, with one water molecule equivalent incorporated into the structure. This arrangement facilitates the formation of MET-PRO heterodimers and multiple stable units, collectively constructing a three-dimensional supramolecular network. The solubility and permeability of the current cocrystal, along with the parent drug MET, are evaluated under physiological pH conditions. Experimental findings reveal that MET within the cocrystal exhibits a 1.54-2.37 folds increase in solubility and approximately a threefold improvement in permeability compared to its standalone form. Intriguingly, these concurrent enhancements in the physicochemical properties of MET lead to augmented antibacterial activity in vitro, evidenced by a reduction in minimum inhibitory concentration. Even more intriguingly, the enhanced physicochemical properties observed in vitro for the current cocrystal translate into tangible pharmacokinetic benefits in vivo, characterized by prolonged half-life and enhanced bioavailability. Consequently, this research not only introduces a fresh crystal structure for antibacterial medication but also presents approach for optimizing drug properties across in vitro and in vivo settings, while concurrently bolstering the antibacterial effectiveness of MET through pharmaceutical cocrystallization techniques.

Development and Validation of a Comprehensive Analysis of the Competing Endogenous circRNA/miRNA/mRNA Network for the Identification of Immune-Related Targets in Esophageal Squamous Cell Carcinoma.

Immunotherapy for esophageal squamous cell carcinoma (ESCC) exhibits notable variability in efficacy. Concurrently, recent research emphasizes circRNAs' impact on the ESCC tumor microenvironment. To further explore the relationship, we leveraged circRNA, microRNA, and mRNA sequence datasets to construct a comprehensive immune-related circRNA-microRNA-mRNA network, revealing competing endogenous RNA (ceRNA) roles in ESCC. The network comprises 16 circular RNAs, 13 microRNAs, and 1,560 mRNAs. Weighted gene co-expression analysis identified immune-related modules, notably cancer-associated fibroblast (CAF) and myeloid-derived suppressor cell modules, correlating significantly with immune and stemness scores. Among them, the CAF module plays a crucial role in extracellular matrix function and effectively discriminates ESCC patients. Four hub collagen family genes within CAF correlated robustly with CAF, macrophage infiltration, and T-cell exclusion. In-house sequencing and RT-qPCR validated their elevated expression. We also identified CAF module-targeting drugs as potential ESCC treatments. In summary, we established an immune-related circRNA-miRNA-mRNA network that not only illuminates ceRNA functionality but also highlights circRNAs' involvement in the CAF through collagen gene targeting. These findings hold promise to predict ESCC immune landscapes and therapy responses, ultimately aiding in more personalized and effective clinical decision-making.

Risk and pathologic factors of recurrence after endoscopic resection for superficial esophageal squamous cell carcinoma: a systematic review and meta-analysis.

BACKGROUND AND AIMS: The risk and pathologic factors of recurrence after endoscopic resection (ER) for superficial esophageal squamous cell carcinoma (ESCC) are inconsistent across studies. We evaluated this in a systematic review and meta-analysis. METHODS: The data of recurrence in such patients were extracted from all studies. Risk ratios (RRs) were combined using random-effects meta-analysis to assess pooled recurrence rate and pathologic risk factors. Relapse-free survival was combined using the Kaplan-Meier method to estimate the relationship between various pathologic factors and recurrence time. RESULTS: We identified 26 studies, with a total of 5100 patients and 321 with recurrences (pooled rate, 6.2%). The risk of recurrence was significantly higher in positive vertical margin (RR, 4.51; 95% confidence interval [CI], 2.16-9.44), positive horizontal margin (RR, 2.54; 95% CI, 1.57-4.13), lymphovascular invasion (LVI) (RR, 2.33; 95% CI, 1.75-3.11; P < .001), lymphatic invasion (LI) (RR, 2.24; 95% CI, 1.24-4.06), and tumor invading submucosa of ≤200 µm (SM1) (RR, 1.71; 95% CI, 1.32-2.21, compared to muscularis mucosa). Patients with LI (hazard ratio, 2.47; 95% CI, 1.24-4.90; P = .02) and LVI (HR, 2.36; 95% CI, 2.22-4.59; P = .0006) tended to have earlier recurrence after ER. CONCLUSIONS: The recurrence rate of superficial esophageal squamous cell carcinoma after ER is acceptable. Patients with positive margins, LVI, LI, and SM1 need to pay significant attention to the risk of recurrence. LI and VI should be evaluated separately. (PROSPERO CRD42023406309.).

Predicting distant metastasis in nasopharyngeal carcinoma using gradient boosting tree model based on detailed magnetic resonance imaging reports.

BACKGROUND: Development of distant metastasis (DM) is a major concern during treatment of nasopharyngeal carcinoma (NPC). However, studies have demonstrated improved distant control and survival in patients with advanced NPC with the addition of chemotherapy to concomitant chemoradiotherapy. Therefore, precise prediction of metastasis in patients with NPC is crucial. AIM: To develop a predictive model for metastasis in NPC using detailed magnetic resonance imaging (MRI) reports. METHODS: This retrospective study included 792 patients with non-distant metastatic NPC. A total of 469 imaging variables were obtained from detailed MRI reports. Data were stratified and randomly split into training (50%) and testing sets. Gradient boosting tree (GBT) models were built and used to select variables for predicting DM. A full model comprising all variables and a reduced model with the top-five variables were built. Model performance was assessed by area under the curve (AUC). RESULTS: Among the 792 patients, 94 developed DM during follow-up. The number of metastatic cervical nodes (30.9%), tumor invasion in the posterior half of the nasal cavity (9.7%), two sides of the pharyngeal recess (6.2%), tubal torus (3.3%), and single side of the parapharyngeal space (2.7%) were the top-five contributors for predicting DM, based on their relative importance in GBT models. The testing AUC of the full model was 0.75 (95% confidence interval [CI]: 0.69-0.82). The testing AUC of the reduced model was 0.75 (95%CI: 0.68-0.82). For the whole dataset, the full (AUC = 0.76, 95%CI: 0.72-0.82) and reduced models (AUC = 0.76, 95%CI: 0.71-0.81) outperformed the tumor node-staging system (AUC = 0.67, 95%CI: 0.61-0.73). CONCLUSION: The GBT model outperformed the tumor node-staging system in predicting metastasis in NPC. The number of metastatic cervical nodes was identified as the principal contributing variable.

AI-based digital pathology provides newer insights into lifestyle intervention-induced fibrosis regression in MASLD: An exploratory study.

BACKGROUND AND AIMS: Lifestyle intervention is the mainstay of therapy for metabolic dysfunction-associated steatohepatitis (MASH), and liver fibrosis is a key consequence of MASH that predicts adverse clinical outcomes. The placebo response plays a pivotal role in the outcome of MASH clinical trials. Second harmonic generation/two-photon excitation fluorescence (SHG/TPEF) microscopy with artificial intelligence analyses can provide an automated quantitative assessment of fibrosis features on a continuous scale called qFibrosis. In this exploratory study, we used this approach to gain insight into the effect of lifestyle intervention-induced fibrosis changes in MASH. METHODS: We examined unstained sections from paired liver biopsies (baseline and end-of-intervention) from MASH individuals who had received either routine lifestyle intervention (RLI) (n = 35) or strengthened lifestyle intervention (SLI) (n = 17). We quantified liver fibrosis with qFibrosis in the portal tract, periportal, transitional, pericentral, and central vein regions. RESULTS: About 20% (7/35) and 65% (11/17) of patients had fibrosis regression in the RLI and SLI groups, respectively. Liver fibrosis tended towards no change or regression after each lifestyle intervention, and this phenomenon was more prominent in the SLI group. SLI-induced liver fibrosis regression was concentrated in the periportal region. CONCLUSION: Using digital pathology, we could detect a more pronounced fibrosis regression with SLI, mainly in the periportal region. With changes in fibrosis area in the periportal region, we could differentiate RLI and SLI patients in the placebo group in the MASH clinical trial. Digital pathology provides new insight into lifestyle-induced fibrosis regression and placebo responses, which is not captured by conventional histological staging.

Roles of Two-Dimensional Materials in Antibiofilm Applications: Recent Developments and Prospects.

Biofilm-associated infections pose a significant challenge in healthcare, constituting 80% of bacterial infections and often leading to persistent, chronic conditions. Conventional antibiotics struggle with efficacy against these infections due to the high tolerance and resistance induced by bacterial biofilm barriers. Two-dimensional nanomaterials, such as those from the graphene family, boron nitride, molybdenum disulfide (MoS2), MXene, and black phosphorus, hold immense potential for combating biofilms. These nanomaterial-based antimicrobial strategies are novel tools that show promise in overcoming resistant bacteria and stubborn biofilms, with the ability to circumvent existing drug resistance mechanisms. This review comprehensively summarizes recent developments in two-dimensional nanomaterials, as both therapeutics and nanocarriers for precision antibiotic delivery, with a specific focus on nanoplatforms coupled with photothermal/photodynamic therapy in the elimination of bacteria and penetrating and/or ablating biofilm. This review offers important insight into recent advances and current limitations of current antibacterial nanotherapeutic approaches, together with a discussion on future developments in the field, for the overall benefit of public health.

Closed Bipolar Nanoelectrode Array for Ultra-Sensitive Detection of Alkaline Phosphatase and Two-Dimensional Imaging of Epidermal Growth Factor Receptors.

The combination of closed bipolar electrodes (cBPE) with electrochemiluminescence (ECL) imaging has demonstrated remarkable capabilities in the field of bioanalysis. Here, we established a cBPE-ECL platform for ultrasensitive detection of alkaline phosphatase (ALP) and two-dimensional imaging of epidermal growth factor receptor (EGFR). This cBPE-ECL system consists of a high-density gold nanowire array in anodic aluminum oxide (AAO) membrane as the cBPE coupled with ECL of highly luminescent cadmium selenide quantum dots (CdSe QDs) luminophores to achieve cathodic electro-optical conversion. When an enzyme-catalyzed amplification effect of ALP with 4-aminophenyl phosphate monosodium salt hydrate (p-APP) as the substrate and 4-aminophenol (p-AP) as the electroactive probe is introduced, a significant improvement of sensing sensitivity with a detection limit as low as 0.5 fM for ALP on the cBPE-ECL platform can be obtained. In addition, the cBPE-ECL sensing system can also be used to detect cancer cells with an impressive detection limit of 50 cells/mL by labeling ALP onto the EGFR protein on A431 human epidermal cancer cell membranes. Thus, two-dimensional (2D) imaging of the EGFR proteins on the cell surface can be achieved, demonstrating that the established cBPE-ECL sensing system is of high resolution for spatiotemporal cell imaging.

High-Throughput Single-Molecule Surface-Enhanced Raman Spectroscopic Profiling of Single-Amino Acid Substitutions in Peptides by a Gold Plasmonic Nanopore.

Simultaneous detection and structural characterization of protein variants on a single platform are highly desirable but technically challenging. Herein, we present a single-molecule spectral system based on a gold plasmonic nanopore for analyzing two peptides and their single-point mutated variants. The gold plasmonic nanopore enabled the high-throughput acquisition of surface-enhanced Raman scattering (SERS) spectra at the single-molecule level by electrically driving analytes into hot spots. Furthermore, a statistical method based on Boolean operations was developed to extract prominent features from fluctuated single-molecule SERS spectra. The effects of the single-amino acid substitutions on both the intramolecular interactions and the peptide conformations were directly characterized by the nanopore system, and the results agreed with the predictions by AlphaFold2. This study highlights the mutual benefits of spectroscopy and nanopore technology, whereby the gold plasmonic nanopore offers a powerful tool for the structural analysis of single-molecule proteins.

Co-delivery of Siape1 and Melatonin by 125I-loaded PSMA-targeted Nanoparticles for the Treatment of Prostate Cancer.

BACKGROUND: Both apurinic/apyrimidinic endodeoxyribonuclease 1 (APE1) inhibition and melatonin suppress prostate cancer (PCa) growth. OBJECTIVE: This study evaluated the therapeutic efficiency of self-assembled and prostate-specific membrane antigen (PSMA)-targeted nanocarrier loading 125I radioactive particles and encapsulating siRNA targeting APE1 (siAPE1) and melatonin for PCa. METHODS: The linear polyarginine R12 polypeptide was prepared using Fmoc-Arg-Pbf-OH. The PSMA-targeted polymer was synthesized by conjugating azide-modified R12 peptide to PSMA monoclonal antibody (mAb). Before experiments, the PSMA-R12 nanocarrier was installed with melatonin and siAPE1, which were subsequently labeled by 125I radioactive particles. In vitro biocompatibility and cytotoxicity of nanocomposites were examined in LNCaP cells and in vivo biodistribution and pharmacokinetics were determined using PCa tumor-bearing mice. RESULTS: PSMA-R12 nanocarrier was ~120 nm in size and was increased to ~150 nm by melatonin encapsulation. PSMA-R12 nanoparticles had efficient loading capacities of siAPE1, melatonin, and 125I particles. The co-delivery of melatonin and siAPE1 by PSMA-R12-125I showed synergistic effects on suppressing LNCaP cell proliferation and Bcl-2 expression and promoting cell apoptosis and caspase-3 expression. Pharmacokinetics analysis showed that Mel@PSMA-R12-125I particles had high uptake activity in the liver, spleen, kidney, intestine, and tumor, and were accumulated in the tumor sites within the first 8 h p.i., but was rapidly cleared from all the tested organs at 24 h p.i. Administration of nanoparticles to PCa tumors in vivo showed that Mel@PSMA-R12- 125I/siAPE1 had high efficiency in suppressing PCa tumor growth. CONCLUSION: The PSMA-targeted nanocarrier encapsulating siAPE1 and melatonin is a promising therapeutic strategy for PCa and can provide a theoretical basis for patent applications.

Longitudinal on-treatment circulating tumor DNA as a biomarker for real-time dynamic risk monitoring in cancer patients: The EP-SEASON study.

Recurrence risks of cancer patient can change during treatment as a result of treatment-related tumor evolution. However, biomarkers that can monitor these changes are lacking. Here, we investigated whether tracking circulating tumor DNA (ctDNA) dynamics through liquid biopsy can inform real-time recurrence risk. Nasopharyngeal carcinoma (NPC) provides an ideal model where cell-free Epstein-Barr virus (EBV) DNA (cfEBV DNA), a ctDNA, can be sensitively detected. We conducted the EP-SEASON study (NCT03855020) and prospectively recruited 1,000 NPC patients undergoing per-protocol cfEBV DNA assessments at 11 time points and receiving sequential chemo-radiotherapy. Longitudinal cfEBV DNA displayed distinct patterns during neoadjuvant chemotherapy and radiotherapy. Despite the prognostic significance of cfEBV DNA at each time point, real-time recurrence risks changed in sync with cfEBV DNA dynamics. Furthermore, we identified phenotypes of whole-course ctDNA changing dynamics associated with different survival outcomes. In conclusion, tracking longitudinal on-treatment ctDNA can forecast real-time recurrence risk, facilitating risk-adapted, individualized patient management.

4.4 kW Nd:YAG slab amplifier with a high repetition frequency and high beam quality.

Using the self-developed fused indium wetting technology and planar waveguide, the uniform heat dissipation of the slab crystal and uniform pumping of the pump light were achieved, respectively. Based on the master oscillator power amplification (MOPA) scheme, the power was then amplified when the seed light source passed through the Nd:YAG slab crystal three times. Additionally, the image transfer system that we added to the amplified optical path achieved high beam quality. Finally, we obtained a rectangular pulsed laser with an output average power of 4461 W, a repetition frequency of 20 kHz, a pulse width of 62 ns, an optical-to-optical conversion efficiency of 26.8%, and a beam quality of ß x=7.0 and ß y=7.7.

Daily occupational exposure in swine farm alters human skin microbiota and antibiotic resistome.

Antimicrobial resistance (AMR) is a major threat to global public health, and antibiotic resistance genes (ARGs) are widely distributed across humans, animals, and environment. Farming environments are emerging as a key research area for ARGs and antibiotic resistant bacteria (ARB). While the skin is an important reservoir of ARGs and ARB, transmission mechanisms between farming environments and human skin remain unclear. Previous studies confirmed that swine farm environmental exposures alter skin microbiome, but the timeline of these changes is ill defined. To improve understanding of these changes and to determine the specific time, we designed a cohort study of swine farm workers and students through collected skin and environmental samples to explore the impact of daily occupational exposure in swine farm on human skin microbiome. Results indicated that exposure to livestock-associated environments where microorganisms are richer than school environment can reshape the human skin microbiome and antibiotic resistome. Exposure of 5 h was sufficient to modify the microbiome and ARG structure in workers' skin by enriching microorganisms and ARGs. These changes were preserved once formed. Further analysis indicated that ARGs carried by host microorganisms may transfer between the environment with workers' skin and have the potential to expand to the general population using farm workers as an ARG vector. These results raised concerns about potential transmission of ARGs to the broader community. Therefore, it is necessary to take corresponding intervention measures in the production process to reduce the possibility of ARGs and ARB transmission.