Fe-doped Cu-based bimetallic metal-organic frameworks as nanoscale microwave sensitizers for enhancing microwave thermal and dynamic therapy for hepatocellular carcinoma.

Microwave ablation (MWA) is recognized as a novel treatment modality that can kill tumor cells by heating the ions and polar molecules in these cells through high-speed rotation and friction. However, the size and location of the tumor affect the effective ablation range of microwave hyperthermia, resulting in residual tumor tissue and a high recurrence rate. Due to their tunable porous structure and high specific surface area, metal-organic frameworks (MOFs) can serve as microwave sensitizers, promoting microwave energy conversion owing to ion collisions in the porous structure of the MOFs. Moreover, iron-based compounds are known to possess peroxidase-like catalytic activity. Therefore, Fe-doped Cu bimetallic MOFs (FCMs) were prepared through a hydrothermal process. These FCM nanoparticles not only increased the efficiency of microwave-thermal energy conversion as microwave sensitizers but also promoted the generation of reactive oxygen species (ROS) by consuming glutathione (GSH) and promoted the Fenton reaction to enhance microwave dynamic therapy (MDT). The in vitro and in vivo results showed that the combination of MWA and MDT treatment effectively destroyed tumor tissues via microwave irradiation without inducing significant side effects on normal tissues. This study provides a new approach for the combined application of MOFs and microwave ablation, demonstrating excellent potential for future applications.

A Duplex PCR Assay for Rapid Detection of Klebsiella pneumoniae and Chryseobacterium in Large Yellow Croaker Fish.

Both Klebsiella pneumoniae and Chryseobacterium cause an increasing number of diseases in fish, resulting in great economic losses in aquaculture. In addition, the disease infected with Klebsiella pneumoniae or Chryseobacterium exhibited the similar clinical symptoms in aquatic animals. However, there is no effective means for the simultaneous detection of co-infection and discrimination them for these two pathogens. Here, we developed a duplex polymerase chain reaction (PCR) method based on the outer membrane protein A (ompA) gene of Klebsiella pneumoniae and Chryseobacterium. The specificity and validity of the designed primers were confirmed experimentally using simplex PCR. The expected amplicons for Klebsiella pneumoniae and Chryseobacterium had a size of 663 and 1404 bp, respectively. The optimal condition for duplex PCR were determined to encompass a primer concentration of 0.5 µM and annealing temperature of 57°C. This method was analytical specific with no amplification being observed from the genomic DNA of Escherichia coli, Vibrio harveyi, Pseudomonas plecoglossicida, Aeromonas hydrophila and Acinetobacter johnsonii. The limit of detection was estimated to be 20 fg of genomic DNA for Chryseobacterium and 200 fg for Klebsiella pneumoniae, or 100 colony-forming units (CFU) of bacterial cells in both cases. The duplex PCR was capable of simultaneously amplifying target fragments from genomic DNA extracted from the bacteria and fish liver. For practical validation of the method, 20 diseased fish were collected from farms, among which 4 samples were PCR-positive for Klebsiella pneumoniae and Chryseobacterium. The duplex PCR method developed here is time-saving, specific, convenient, and may prove to be an invaluable tool for molecular detection and epidemiological investigation of Klebsiella pneumoniae and Chryseobacterium in the field of aquaculture.

Integrative analyses of bulk and single-cell transcriptomics reveals the infiltration and crosstalk of cancer-associated fibroblasts as a novel predictor for prognosis and microenvironment remodeling in intrahepatic cholangiocarcinoma.

BACKGROUND: Intrahepatic cholangiocarcinoma (ICC) is a highly malignant neoplasm and characterized by desmoplastic matrix. The heterogeneity and crosstalk of tumor microenvironment remain incompletely understood. METHODS: To address this gap, we performed Weighted Gene Co-expression Network Analysis (WGCNA) to identify and construct a cancer associated fibroblasts (CAFs) infiltration biomarker. We also depicted the intercellular communication network and important receptor-ligand complexes using the single-cell transcriptomics analysis of tumor and Adjacent normal tissue. RESULTS: Through the intersection of TCGA DEGs and WGCNA module genes, 784 differential genes related to CAFs infiltration were obtained. After a series of regression analyses, the CAFs score was generated by integrating the expressions of EVA1A, APBA2, LRRTM4, GOLGA8M, BPIFB2, and their corresponding coefficients. In the TCGA-CHOL, GSE89748, and 107,943 cohorts, the high CAFs score group showed unfavorable survival prognosis (p < 0.001, p = 0.0074, p = 0.028, respectively). Additionally, a series of drugs have been predicted to be more sensitive to the high-risk group (p < 0.05). Subsequent to dimension reduction and clustering, thirteen clusters were identified to construct the single-cell atlas. Cell-cell interaction analysis unveiled significant enhancement of signal transduction in tumor tissues, particularly from fibroblasts to malignant cells via diverse pathways. Moreover, SCENIC analysis indicated that HOXA5, WT1, and LHX2 are fibroblast specific motifs. CONCLUSIONS: This study reveals the key role of fibroblasts - oncocytes interaction in the remodeling of the immunosuppressive microenvironment in intrahepatic cholangiocarcinoma. Subsequently, it may trigger cascade activation of downstream signaling pathways such as PI3K-AKT and Notch in tumor, thus initiating tumorigenesis. Targeted drugs aimed at disrupting fibroblasts-tumor cell interaction, along with associated enrichment pathways, show potential in mitigating the immunosuppressive microenvironment that facilitates tumor progression.

Unraveling the prognostic significance of RGS gene family in gastric cancer and the potential implication of RGS4 in regulating tumor-infiltrating fibroblast.

Regulator of G-protein signaling (RGS) proteins are regulators of signal transduction mediated by G protein-coupled receptors (GPCRs). Current studies have shown that some molecules in the RGS gene family are related to the occurrence, development and poor prognosis of malignant tumors. However, the RGS gene family has been rarely studied in gastric cancer. In this study, we explored the mutation and expression profile of RGS gene family in gastric cancer, and evaluated the prognostic value of RGS expression. Then we established a prognostic model based on RGS gene family and performed functional analysis. Further studies showed that RGS4, as an independent prognostic predictor, may play an important role in regulating fibroblasts in the immune microenvironment. In conclusion, this study explores the value of RGS gene family in gastric cancer, which is of great significance for predicting the prognosis and guiding the treatment of gastric cancer.

Reliable detection of generalized convulsive seizures using an off-the-shelf digital watch: A multisite phase 2 study.

OBJECTIVE: The aim of this study was to develop a machine learning algorithm using an off-the-shelf digital watch, the Samsung watch (SM-R800), and evaluate its effectiveness for the detection of generalized convulsive seizures (GCS) in persons with epilepsy. METHODS: This multisite epilepsy monitoring unit (EMU) phase 2 study included 36 adult patients. Each patient wore a Samsung watch that contained accelerometer, gyroscope, and photoplethysmographic sensors. Sixty-eight time and frequency domain features were extracted from the sensor data and were used to train a random forest algorithm. A testing framework was developed that would better reflect the EMU setting, consisting of (1) leave-one-patient-out cross-validation (LOPO CV) on GCS patients, (2) false alarm rate (FAR) testing on nonseizure patients, and (3) "fixed-and-frozen" prospective testing on a prospective patient cohort. Balanced accuracy, precision, sensitivity, and FAR were used to quantify the performance of the algorithm. Seizure onsets and offsets were determined by using video-electroencephalographic (EEG) monitoring. Feature importance was calculated as the mean decrease in Gini impurity during the LOPO CV testing. RESULTS: LOPO CV results showed balanced accuracy of .93 (95% confidence interval [CI] = .8-.98), precision of .68 (95% CI = .46-.85), sensitivity of .87 (95% CI = .62-.96), and FAR of .21/24 h (interquartile range [IQR] = 0-.90). Testing the algorithm on patients without seizure resulted in an FAR of .28/24 h (IQR = 0-.61). During the "fixed-and-frozen" prospective testing, two patients had three GCS, which were detected by the algorithm, while generating an FAR of .25/24 h (IQR = 0-.89). Feature importance showed that heart rate-based features outperformed accelerometer/gyroscope-based features. SIGNIFICANCE: Commercially available wearable digital watches that reliably detect GCS, with minimum false alarm rates, may overcome usage adoption and other limitations of custom-built devices. Contingent on the outcomes of a prospective phase 3 study, such devices have the potential to provide non-EEG-based seizure surveillance and forecasting in the clinical setting.

TXNIP knockdown protects rats against bupivacaine-induced spinal neurotoxicity via the inhibition of oxidative stress and apoptosis.

Bupivacaine (BUP) is an anesthetic commonly used in clinical practice that when used for spinal anesthesia, might exert neurotoxic effects. Thioredoxin-interacting protein (TXNIP) is a member of the α-arrestin protein superfamily that binds covalently to thioredoxin (TRX) to inhibit its function, leading to increased oxidative stress and activation of apoptosis. The role of TXNIP in BUP-induced oxidative stress and apoptosis remains to be elucidated. In this context, the present study aimed to explore the effects of TXNIP knockdown on BUP-induced oxidative stress and apoptosis in the spinal cord of rats and in PC12 cells through the transfection of adeno-associated virus-TXNIP short hairpin RNA (AAV-TXNIP shRNA) and siRNA-TXNIP, respectively. In vivo, a rat model of spinal neurotoxicity was established by intrathecally injecting rats with BUP. The BUP + TXNIP shRNA and the BUP + Control shRNA groups of rats were injected with an AAV carrying the TXNIP shRNA and the Control shRNA, respectively, into the subarachnoid space four weeks prior to BUP treatment. The Basso, Beattie & Bresnahan (BBB) locomotor rating score, % MPE of TFL, H&E staining, and Nissl staining analyses were conducted. In vitro, 0.8 mM BUP was determined by CCK-8 assay to establish a cytotoxicity model in PC12 cells. Transfection with siRNA-TXNIP was carried out to suppress TXNIP expression prior to exposing PC12 cells to BUP. The results revealed that BUP effectively induced neurological behavioral dysfunction and neuronal damage and death in the spinal cord of the rats. Similarly, BUP triggered cytotoxicity and apoptosis in PC12 cells. In addition, treated with BUP both in vitro and in vivo exhibited upregulated TXNIP expression and increased oxidative stress and apoptosis. Interestingly, TXNIP knockdown in the spinal cord of rats through transfection of AAV-TXNIP shRNA exerted a protective effect against BUP-induced spinal neurotoxicity by ameliorating behavioral and histological outcomes and promoting the survival of spinal cord neurons. Similarly, transfection with siRNA-TXNIP mitigated BUP-induced cytotoxicity in PC12 cells. In addition, TXNIP knockdown mitigated the upregulation of ROS, MDA, Bax, and cleaved caspase-3 and restored the downregulation of GSH, SOD, CAT, GPX4, and Bcl2 induced upon BUP exposure. These findings suggested that TXNIP knockdown protected against BUP-induced spinal neurotoxicity by suppressing oxidative stress and apoptosis. In summary, TXNIP could be a central signaling hub that positively regulates oxidative stress and apoptosis during neuronal damage, which renders TXNIP a promising target for treatment strategies against BUP-induced spinal neurotoxicity.

Gut symbionts alleviate MASH through a secondary bile acid biosynthetic pathway.

The gut microbiota has been found to play an important role in the progression of metabolic dysfunction-associated steatohepatitis (MASH), but the mechanisms have not been established. Here, by developing a click-chemistry-based enrichment strategy, we identified several microbial-derived bile acids, including the previously uncharacterized 3-succinylated cholic acid (3-sucCA), which is negatively correlated with liver damage in patients with liver-tissue-biopsy-proven metabolic dysfunction-associated fatty liver disease (MAFLD). By screening human bacterial isolates, we identified Bacteroides uniformis strains as effective producers of 3-sucCA both in vitro and in vivo. By activity-based protein purification and identification, we identified an enzyme annotated as ß-lactamase in B. uniformis responsible for 3-sucCA biosynthesis. Furthermore, we found that 3-sucCA is a lumen-restricted metabolite and alleviates MASH by promoting the growth of Akkermansia muciniphila. Together, our data offer new insights into the gut microbiota-liver axis that may be leveraged to augment the management of MASH.

An n-Type Open-Shell Conjugated Polymer with High-Spin Ground-State and High Intrinsic Electrical Conductivity.

Open-shell conjugated polymers with a high intrinsic conductivity and high-spin ground state hold considerable promise for applications in organic electronics and spintronics. Herein, two novel acceptor-acceptor (A-A) conjugated polymers based on a highly electron-deficient quinoidal benzodifurandione unit have been developed, namely DPP-BFDO-Th and DPP-BFDO. The incorporation of the quinoidal moiety into the polymers backbones enables deeply aligned lower-lying lowest unoccupied molecular orbital (LUMO) levels of below -4.0 eV. Notably, DPP-BFDO exhibits an exceptionally low LUMO (-4.63 eV) and a high-spin ground state characterized by strong diradical characters. Moreover, a self-doping through intermolecular charge-transfer is observed for DPP-BFDO, as evidenced by X-ray photoelectron spectroscopy (XPS) studies. The high carrier concentration in combination with a planar and linear conjugated backbone yields a remarkable electrical conductivity (σ) of 1.04 S cm-1 in the "undoped" native form, ranking among the highest values reported for n-type radical-based conjugated polymers. When employed as an n-type thermoelectric material, DPP-BFDO achieves a power factor of 12.59 µW m-1 K-2. Furthermore, upon n-doping, the σ could be improved to 65.68 S cm-1. This study underscores the great potential of electron-deficient quinoidal units in constructing dopant-free n-type conductive polymers with a high-spin ground state and exceptional intrinsic conductivity.

CAPN2 correlates with insulin resistance states in PCOS as evidenced by multi-dataset analysis.

OBJECTIVE: IR emerges as a feature in the pathophysiology of PCOS, precipitating ovulatory anomalies and endometrial dysfunctions that contribute to the infertility challenges characteristic of this condition. Despite its clinical significance, a consensus on the precise mechanisms by which IR exacerbates PCOS is still lacking. This study aims to harness bioinformatics tools to unearth key IR-associated genes in PCOS patients, providing a platform for future therapeutic research and potential intervention strategies. METHODS: We retrieved 4 datasets detailing PCOS from the GEO, and sourced IRGs from the MSigDB. We applied WGCNA to identify gene modules linked to insulin resistance, utilizing IR scores as a phenotypic marker. Gene refinement was executed through the LASSO, SVM, and Boruta feature selection algorithms. qPCR was carried out on selected samples to confirm findings. We predicted both miRNA and lncRNA targets using the ENCORI database, which facilitated the construction of a ceRNA network. Lastly, a drug-target network was derived from the CTD. RESULTS: Thirteen genes related to insulin resistance in PCOS were identified via WGCNA analysis. LASSO, SVM, and Boruta algorithms further isolated CAPN2 as a notably upregulated gene, corroborated by biological verification. The ceRNA network involving lncRNA XIST and hsa-miR-433-3p indicated a possible regulatory link with CAPN2, supported by ENCORI database. Drug prediction analysis uncovered seven pharmacological agents, most being significant regulators of the endocrine system, as potential candidates for addressing insulin resistance in PCOS. CONCLUSIONS: This study highlights the pivotal role of CAPN2 in insulin resistance within the context of PCOS, emphasizing its importance as both a critical biomarker and a potential therapeutic target. By identifying CAPN2, our research contributes to the expanding evidence surrounding the CAPN family, particularly CAPN10, in insulin resistance studies beyond PCOS. This work enriches our understanding of the mechanisms underlying insulin resistance, offering insights that bridge gaps in the current scientific landscape.

Continuous flow biocatalysis: synthesis of purine nucleoside esters catalyzed by lipase TL IM from Thermomyces lanuginosus.

Purine nucleoside ester is one of the derivatives of purine nucleoside, which has antiviral and anticancer activities. In this work, a continuous flow synthesis of purine nucleoside esters catalyzed by lipase TL IM from Thermomyces lanuginosus was successfully achieved. Various parameters including solvent, reaction temperature, reaction time/flow rate and substrate ratio were investigated. The best yields were obtained with a continuous flow microreactor for 35 min at 50 °C with the substrate ratio of 1 : 5 (nucleosides to vinyl esters) in the solvent of tert-amyl alcohol. 12 products were efficiently synthesized with yields of 78-93%. Here we reported for the first time the use of lipase TL IM from Thermomyces lanuginosus in the synthesis of purine nucleoside esters. The significant advantages of this methodology are a green solvent and mild conditions, a simple work-up procedure and the highly reusable biocatalyst. This research provides a new technique for rapid synthesis of anticancer and antiviral nucleoside drugs and is helpful for further screening of drug activity.

Environmental magnesium ion affects global gene expression, motility, biofilm formation and virulence of Vibrio parahaemolyticus.

Vibrio parahaemolyticus is widely distributed in marine ecosystems. Magnesium ion (Mg2+) is the second most abundant metal cation in seawater, and plays important roles in the growth and gene expression of V. parahaemolyticus, but lacks the detailed mechanisms. In this study, the RNA sequencing data demonstrated that a total of 1494 genes was significantly regulated by Mg2+. The majority of the genes associated with lateral flagella, exopolysaccharide, type III secretion system 2, type VI secretion system (T6SS) 1, T6SS2, and thermostable direct hemolysin were downregulated. A total of 18 genes that may be involved in c-di-GMP metabolism and more than 80 genes encoding putative regulators were also significantly and differentially expressed in response to Mg2+, indicating that the adaptation process to Mg2+ stress may be strictly regulated by complex regulatory networks. In addition, Mg2+ promoted the proliferative speed, swimming motility and cell adhesion of V. parahaemolyticus, but inhibited the swarming motility, biofilm formation, and c-di-GMP production. However, Mg2+ had no effect on the production of capsular polysaccharide and cytoxicity against HeLa cells. Therefore, Mg2+ had a comprehensive impact on the physiology and gene expression of V. parahaemolyticus.

Impact of Empathic Concern on Prosocial Behavior in Gain and Loss Contexts: Evidence from Event-Related Potential.

This study employs event-related potential (ERP) to examine the impact of empathic concern on prosocial decision-making with costs in both gain and loss contexts. In this experiment, participants can choose between two types of lottery tickets and pay lottery money to help the target person gain more money or lose less money. The behavioral results showed that regardless of the context of the decision (financial loss or gain), participants tended to help individuals who had induced high empathic concern. ERP results show that compared to the low-empathic-concern condition, the high-empathic-concern condition induced greater P3 amplitude in the gain context. However, this change in P3 amplitude caused by empathic concern did not occur in the context of loss. These findings indicate that empathic concern has different psychological mechanisms that moderate prosocial behavior in gain and loss contexts.

C-terminal binding protein 2 is a novel tumor suppressor targeting the MYC-IRF4 axis in multiple myeloma.

ABSTRACT: Multiple myeloma (MM) cells are addicted to MYC and its direct transactivation targets IRF4 for proliferation and survival. MYC and IRF4 are still considered "undruggable," as most small-molecule inhibitors suffer from low potency, suboptimal pharmacokinetic properties, and undesirable off-target effects. Indirect inhibition of MYC/IRF4 emerges as a therapeutic vulnerability in MM. Here, we uncovered an unappreciated tumor-suppressive role of C-terminal binding protein 2 (CTBP2) in MM via strong inhibition of the MYC-IRF4 axis. In contrast to epithelial cancers, CTBP2 is frequently downregulated in MM, in association with shortened survival, hyperproliferative features, and adverse clinical outcomes. Restoration of CTBP2 exhibited potent antitumor effects against MM in vitro and in vivo, with marked repression of the MYC-IRF4 network genes. Mechanistically, CTBP2 impeded the transcription of MYC and IRF4 by histone H3 lysine 27 deacetylation (H3K27ac) and indirectly via activation of the MYC repressor IFIT3. In addition, activation of the interferon gene signature by CTBP2 suggested its concomitant immunomodulatory role in MM. Epigenetic studies have revealed the contribution of polycomb-mediated silencing and DNA methylation to CTBP2 inactivation in MM. Notably, inhibitors of Enhance of zeste homolog 2, histone deacetylase, and DNA methyltransferase, currently under evaluation in clinical trials, were effective in restoring CTBP2 expression in MM. Our findings indicated that the loss of CTBP2 plays an essential role in myelomagenesis and deciphers an additional mechanistic link to MYC-IRF4 dysregulation in MM. We envision that the identification of novel critical regulators will facilitate the development of selective and effective approaches for treating this MYC/IRF4-addicted malignancy.

Dual-Region Computed Tomography Radiomics-Based Machine Learning Predicts Subcarinal Lymph Node Metastasis in Patients with Non-small Cell Lung Cancer.

BACKGROUND: Noninvasively and accurately predicting subcarinal lymph node metastasis (SLNM) for patients with non-small cell lung cancer (NSCLC) remains challenging. This study was designed to develop and validate a tumor and subcarinal lymph nodes (tumor-SLNs) dual-region computed tomography (CT) radiomics model for predicting SLNM in NSCLC. METHODS: This retrospective study included NSCLC patients who underwent lung resection and SLNs dissection between January 2017 and December 2020. The radiomic features of the tumor and SLNs were extracted from preoperative CT, respectively. Ninety machine learning (ML) models were developed based on tumor region, SLNs region, and tumor-SLNs dual-region. The model performance was assessed by the area under the curve (AUC) and validated internally by fivefold cross-validation. RESULTS: In total, 202 patients were included in this study. ML models based on dual-region radiomics showed good performance for SLNM prediction, with a median AUC of 0.794 (range, 0.686-0.880), which was superior to those of models based on tumor region (median AUC, 0.746; range, 0.630-0.811) and SLNs region (median AUC, 0.700; range, 0.610-0.842). The ML model, which is developed by using the naive Bayes algorithm and dual-region features, had the highest AUC of 0.880 (range of cross-validation, 0.825-0.937) among all ML models. The optimal logistic regression model was inferior to the optimal ML model for predicting SLNM, with an AUC of 0.727. CONCLUSIONS: The CT radiomics showed the potential for accurately predicting SLNM in NSCLC patients. The ML model with dual-region radiomic features has better performance than the logistic regression or single-region models.

Association of cardiometabolic multimorbidity with all-cause and cardiovascular disease mortality among Chinese hypertensive patients.

BACKGROUND: Hypertension usually clusters with multiple comorbidities. However, the association between cardiometabolic multimorbidity (CMM) and mortality in hypertensive patients is unclear. This study aimed to investigate the association between CMM and all-cause and cardiovascular disease (CVD) mortality in Chinese patients with hypertension. METHODS: The data used in this study were from the China National Survey for Determinants of Detection and Treatment Status of Hypertensive Patients with Multiple Risk Factors (CONSIDER), which comprised 5006 participants aged 19-91 years. CMM was defined as the presence of one or more of the following morbidities: diabetes mellitus, dyslipidemia, chronic kidney disease, coronary heart disease, and stroke. Cox proportional hazard models were used to calculate the hazard ratios (HR) with 95% CI to determine the association between the number of CMMs and both all-cause and CVD mortality. RESULTS: Among 5006 participants [mean age: 58.6 ± 10.4 years, 50% women (2509 participants)], 76.4% of participants had at least one comorbidity. The mortality rate was 4.57, 4.76, 8.48, and 16.04 deaths per 1000 person-years in hypertensive patients without any comorbidity and with one, two, and three or more morbidities, respectively. In the fully adjusted model, hypertensive participants with two cardiometabolic diseases (HR = 1.52, 95% CI: 1.09-2.13) and those with three or more cardiometabolic diseases (HR = 2.44, 95% CI: 1.71-3.48) had a significantly elevated risk of all-cause mortality. The findings were similar for CVD mortality but with a greater increase in risk magnitude. CONCLUSIONS: In this study, three-fourths of hypertensive patients had CMM. Clustering with two or more comorbidities was associated with a significant increase in the risk of all-cause and cardiovascular mortality among hypertensive patients, suggesting more intensive treatment and control in this high-risk patient group.

Microplastics in drinking water: A review on methods, occurrence, sources, and potential risks assessment.

Microplastics in drinking water captured widespread attention following reports of widespread detection around the world. Concerns have been raised about the potential adverse effects of microplastics in drinking water on human health. Given the widespread interest in this research topic, there is an urgent need to compile existing data and assess current knowledge. This paper provides a systematic review of studies on microplastics in drinking water, their evidence, key findings, knowledge gaps, and research needs. The data collected show that microplastics are widespread in drinking water, with large variations in reported concentrations. Standardized methodologies of sampling and analysis are urgently needed. There were more fibrous and fragmented microplastics, with the majority being <10 µm in size and composed of polyester, polyethylene, polypropylene, and polystyrene. Little attention has been paid to the color of microplastics. More research is needed to understand the occurrence and transfer of microplastics throughout the water supply chain and the treatment efficiency of drinking water treatment plants (DWTPs). Methods capable of analyzing microplastics <10 µm and nanoplastics are urgently needed. Potential ecological assessment models for microplastics currently in use need to be improved to take into account the complexity and specificity of microplastics.

Characteristics of number concentration, size distribution and components of particulate matter emitted from a typical large civil airport.

Civil airports are recognized as significant contributors to fine particulate matter, especially ultra-fine particulate matter (UFP). The pollutants from airport activities have a notable adverse impact on global climate, urban air quality, and public health. However, there is a lack of practical observational studies on the characterization of integrated pollutant emissions from large civil airports. This study aims to focus on the combined emission characteristics of particulate number concentration (PNC), size distribution, and components at a large civil airport, especially UFP. The findings reveal that airport activities significantly contribute to elevated PNC levels during aircraft activity in downwind conditions (four times higher than background levels) and upwind conditions (7.5 times higher). UFP dominates the PNC around the airport. The particle size distribution shows two peaks occurring around 10-30 nm and 60-80 nm. Notably, particles within the ranges of 17-29 nm and 57-101 nm account for 65.9 % and 12.0 % of the total PNC respectively. Aircraft landing has the greatest impact on particles sized between 6 and 17 nm while takeoff affects particles sized between 29 and 57 nm resulting in a respective increase in PNC by factors of approximately 3.27 and 35.4-fold increase compared to background levels. Different aircraft types exhibit varying effects on PNC with A320 and A321 showing more pronounced effects during takeoff and landing.The presence of airports leads to roughly five-fold rise in elemental component concentrations with Si being highest followed by OC, Ca, Al, Fe, Ca2+, EC, and Mg2+. The OC/EC ratio under high aircraft activity in downwind conditions falls within range of approximately 2.5-3.5. These characteristic components and ratio can be considered as identifying species for civil airports. PMF model show about 75 % of the particulate emissions at the airport boundary were related to airport activities.

Quantification of NOx sources contribution to ambient nitrate aerosol, uncertainty analysis and sensitivity analysis in a megacity.

Dual isotopes of nitrogen and oxygen of NO3- are crucial tools for quantifying the formation pathways and precursor NOx sources contributing to atmospheric nitrate. However, further research is needed to reduce the uncertainty associated with NOx proportional contributions. The acquisition of nitrogen isotopic composition from NOx emission sources lacks regulation, and its impact on the accuracy of contribution results remains unexplored. This study identifies key influencing factors of source isotopic composition through statistical methods, based on a detailed summary of δ15N-NOx values from various sources. NOx emission sources are classified considering these factors, and representative means, standard deviations, and 95 % confidence intervals are determined using the bootstrap method. During the sampling period in Tianjin in 2022, the proportional nitrate formation pathways varied between sites. For suburban and coastal sites, the ranking was [Formula: see text] (NO2 + OH radical) > [Formula: see text] (N2O5 + H2O) > [Formula: see text] (NO3 + DMS/HC), while the rural site exhibited similar fractional contributions from all three formation pathways. Fossil fuel NOx sources consistently contributed more than non-fossil NOx sources in each season among three sites. The uncertainties in proportional contributions varied among different sources, with coal combustion and biogenic soil emission showing lower uncertainties, suggesting more stable proportional contributions than other sources. The sensitivity analysis clearly identifies that the isotopic composition of 15N-enriched and 15N-reduced sources significantly influences source contribution results, emphasizing the importance of accurately characterizing the localized and time-efficient nitrogen isotopic composition of NOx emission sources. In conclusion, this research sheds light on the importance of addressing uncertainties in NOx proportional contributions and emphasizes the need for further exploration of nitrogen isotopic composition from NOx emission sources for accurate atmospheric nitrate studies.

Dual immunotherapy in advanced or metastatic non-small cell lung cancer: A network meta-analysis.

Objectives: Recently, there has been extensive research on dual immunotherapy for advanced or metastatic non-small cell lung cancer (NSCLC), yet a comprehensive evaluation is lacking. This study aimed to rank the available treatment options and assess the efficacy and safety of dual immunotherapy regimens through the implementation of a Bayesian network meta-analysis (NMA). Materials and methods: A thorough search was conducted to recognize eligible randomized controlled trials (RCTs) on March 20, 2023. Overall survival (OS), progression-free survival (PFS), treatment-related adverse events (TRAEs) and grade ≥3 TRAEs were evaluated to identify the efficacy and safety of dual immunotherapy regimens. The surface under the cumulative ranking curve (SUCRA) and P score were employed to rank the treatments. Results: Eleven clinical trials involving six different regimens were included in this study. The combination of anti-programmed cell death protein 1/programmed cell death ligand 1 (PD-1/PD-L1) antibodies with anti-T-cell immunoglobulin and ITIM domain (TIGIT) antibodies emerged as the most promising regimen for improving OS and PFS, followed by anti-PD-1/PD-L1 + anti-cytotoxic T lymphocyte antigen 4 (CTLA-4) + chemotherapy treatment and anti-PD-1/PD-L1 + anti-CTLA-4 treatment. The forest plots demonstrated that these three regimens were all superior to chemotherapy. The above results were observed in both unselected treatment line and first-line settings. The least likely to be associated with TRAEs and grade ≥3 TRAEs were respectively anti-CTLA-4 treatment and anti-PD-1/PD-L1 + anti-TIGIT treatment, with anti-PD-1/PD-L1 + anti-CTLA-4 + chemotherapy treatment to be the worst. Conclusions: This NMA validated the promising efficacy and safety of dual immunotherapy in advanced or metastatic NSCLC. Among them, anti-PD-1/PD-L1 + anti-TIGIT regimen emerges as a highly potential therapeutic approach. Ongoing research efforts should focus on improving treatment regimens, identifying biomarkers, and managing TRAEs to optimize the patient benefits of dual immunotherapy.