NeighborNet: Learning Intra- and Inter-Image Pixel Neighbor Representation for Breast Lesion Segmentation.

Breast lesion segmentation from ultrasound images is essential in computer-aided breast cancer diagnosis. To alleviate the problems of blurry lesion boundaries and irregular morphologies, common practices combine CNN and attention to integrate global and local information. However, previous methods use two independent modules to extract global and local features separately, such feature-wise inflexible integration ignores the semantic gap between them, resulting in representation redundancy/insufficiency and undesirable restrictions in clinic practices. Moreover, medical images are highly similar to each other due to the imaging methods and human tissues, but the captured global information by transformer-based methods in the medical domain is limited within images, the semantic relations and common knowledge across images are largely ignored. To alleviate the above problems, in the neighbor view, this paper develops a pixel neighbor representation learning method (NeighborNet) to flexibly integrate global and local context within and across images for lesion morphology and boundary modeling. Concretely, we design two neighbor layers to investigate two properties (i.e., number and distribution) of neighbors. The neighbor number for each pixel is not fixed but determined by itself. The neighbor distribution is extended from one image to all images in the datasets. With the two properties, for each pixel at each feature level, the proposed NeighborNet can evolve into the transformer or degenerate into the CNN for adaptive context representation learning to cope with the irregular lesion morphologies and blurry boundaries. The state-of-the-art performances on three ultrasound datasets prove the effectiveness of the proposed NeighborNet. The code is available at: https://github.com/fjcaoww/NeighborNet.

Energy-storing DNA-based hydrogel remodels tumor microenvironments for laser-free photodynamic immunotherapy.

Photodynamic therapy (PDT) is a promising modality for cancer treatment. However, limited tissue penetration of external radiation and complicated tumor microenvironments (TMEs) restrict the antitumor efficiency of PDT. Herein, we report an energy-storing DNA-based hydrogel, which enables tumor-selective PDT without external radiation and regulates TMEs to achieve boosted PDT-mediated tumor immunotherapy. The system is constructed with two ultralong single-stranded DNA chains, which programmed partial complementary sequences and repeated G-quadruplex forming AS1411 aptamer for photosensitizer loading via hydrophobic interactions and π-π stacking. Then, energy-storing persistent luminescent nanoparticles are incorporated to sensitize PDT selectively at tumor site without external irradiation, generating tumor antigen to agitate antitumor immune response. The system catalytically generates O2 to alleviate hypoxia and releases inhibitors to reverse the IDO-related immunosuppression, synergistically remodeling the TMEs. In the mouse model of breast cancer, this hydrogel shows a remarkable tumor suppression rate of 78.3 %. Our study represents a new paradigm of photodynamic immunotherapy against cancer by combining laser-free fashion and TMEs remodeling.

Track Irregularity Identification Method of High-Speed Railway Based on CNN-Bi-LSTM.

Track smoothness has become an important factor in the safe operation of high-speed trains. In order to ensure the safety of high-speed operations, studies on track smoothness detection methods are constantly improving. This paper presents a track irregularity identification method based on CNN-Bi-LSTM and predicts track irregularity through car body acceleration detection, which is easy to collect and can be obtained by passenger trains, so the model proposed in this paper provides an idea for the development of track irregularity identification method based on conventional vehicles. The first step is construction of the data set required for model training. The model input is the car body acceleration detection sequence, and the output is the irregularity sequence of the same length. The fluctuation trend of the irregularity data is extracted by the HP filtering (Hodrick Prescott Filter) algorithm as the prediction target. The second is a prediction model based on the CNN-Bi-LSTM network, extracting features from the car body acceleration data and realizing the point-by-point prediction of irregularities. Meanwhile, this paper proposes an exponential weighted mean square error with priority inner fitting (EIF-MSE) as the loss function, improving the accuracy of big value data prediction, and reducing the risk of false alarms. In conclusion, the model is verified based on the simulation data and the real data measured by the high-speed railway comprehensive inspection train.

Synergistic use of photocatalysis and convergent paired electrolysis for nickel-catalyzed arylation of cyclic alcohols.

The merging of transition metal catalysis with electrochemistry has become a powerful tool for organic synthesis because catalysts can govern the reactivity and selectivity. However, coupling catalysts with alkyl radical species generated by anodic oxidation remains challenging because of electrode passivation, dimerization, and overoxidation. In this study, we developed convergent paired electrolysis for the coupling of nickel catalysts with alkyl radicals derived from photoinduced ligand-to-metal charge-transfer of cyclic alcohols and iron catalysts, providing a practical method for site-specific and remote arylation of ketones. The synergistic use of photocatalysis with convergent paired electrolysis can provide alternative avenues for metal-catalyzed radical coupling reactions.

Early prediction of sepsis-induced respiratory tract infection using a biomarker-based machine-learning algorithm.

Early and differential diagnosis of sepsis is essential to avoid unnecessary antibiotic use and further reduce patient morbidity and mortality. Here, we aimed to identify predictors of sepsis and advance a machine-learning strategy to predict sepsis-induced respiratory tract infection (RTI). Patients with sepsis and RTI were selected via retrospective analysis, and essential population characteristics and laboratory parameters were recorded. To improve the performance of the primary model and avoid over-fitting, a recursive feature elimination with cross-validation (RFECV) strategy was used to screen the optimal subset of biomarkers and construct nine machine-learning models based on this subset; the average accuracy, precision, recall, and F1-score were used for evaluation of the models. We identified 430 patients with sepsis and 686 patients with RTI. A total of 39 features were collected, with 23 features identified for initial model construction. Using the RFECV algorithm, we found that the XGBoost classifier, which only needed to include seven biomarkers, demonstrated the best performance among all prediction models, with an average accuracy of 89.24 ± 2.28, while the Ridge classifier, which included 11 biomarkers, had an average accuracy of only 83.87 ± 4.69. The remaining models had prediction accuracies greater than 88%. We developed nine models for predicting sepsis using a strategy that combined RFECV with machine learning. Among these models, the XGBoost classifier, which included seven biomarkers, showed the best performance and highest accuracy for predicting sepsis and may be a promising tool for the timely identification of sepsis.

NIR-enhanced Pt single atom/g-C3N4 nanozymes as SOD/CAT mimics to rescue ATP energy crisis by regulating oxidative phosphorylation pathway for delaying osteoarthritis progression.

Osteoarthritis (OA) progresses due to the excessive generation of reactive oxygen and nitrogen species (ROS/RNS) and abnormal ATP energy metabolism related to the oxidative phosphorylation pathway in the mitochondria. Highly active single-atom nanozymes (SAzymes) can help regulate the redox balance and have shown their potential in the treatment of inflammatory diseases. In this study, we innovatively utilised ligand-mediated strategies to chelate Pt4+ with modified g-C3N4 by π-π interaction to prepare g-C3N4-loaded Pt single-atom (Pt SA/C3N4) nanozymes that serve as superoxide dismutase (SOD)/catalase (CAT) mimics to scavenge ROS/RNS and regulate mitochondrial ATP production, ultimately delaying the progression of OA. Pt SA/C3N4 exhibited a high loading of Pt single atoms (2.45 wt%), with an excellent photothermal conversion efficiency (54.71%), resulting in tunable catalytic activities under near-infrared light (NIR) irradiation. Interestingly, the Pt-N6 active centres in Pt SA/C3N4 formed electron capture sites for electron holes, in which g-C3N4 regulated the d-band centre of Pt, and the N-rich sites transferred electrons to Pt, leading to the enhanced adsorption of free radicals and thus higher SOD- and CAT-like activities compared with pure g-C3N4 and g-C3N4-loaded Pt nanoparticles (Pt NPs/C3N4). Based on the use of H2O2-induced chondrocytes to simulate ROS-injured cartilage invitro and an OA joint model invivo, the results showed that Pt SA/C3N4 could reduce oxidative stress-induced damage, protect mitochondrial function, inhibit inflammation progression, and rebuild the OA microenvironment, thereby delaying the progression of OA. In particular, under NIR light irradiation, Pt SA/C3N4 could help reverse the oxidative stress-induced joint cartilage damage, bringing it closer to the state of the normal cartilage. Mechanistically, Pt SA/C3N4 regulated the expression of mitochondrial respiratory chain complexes, mainly NDUFV2 of complex 1 and MT-ATP6 of ATP synthase, to reduce ROS/RNS and promote ATP production. This study provides novel insights into the design of artificial nanozymes for treating oxidative stress-induced inflammatory diseases.

Convolutional Neural Networks Facilitate Process Understanding of Megacity Ozone Temporal Variability.

Ozone pollution is profoundly modulated by meteorological features such as temperature, air pressure, wind, and humidity. While many studies have developed empirical models to elucidate the effects of meteorology on ozone variability, they predominantly focus on local weather conditions, overlooking the influences from high-altitude and broader regional meteorological patterns. Here, we employ convolutional neural networks (CNNs), a technique typically applied to image recognition, to investigate the influence of three-dimensional spatial variations in meteorological fields on the daily, seasonal, and interannual dynamics of ozone in Shenzhen, a major coastal urban center in China. Our optimized CNNs model, covering a 13° × 13° spatial domain, effectively explains over 70% of daily ozone variability, outperforming alternative empirical approaches by 7 to 62%. Model interpretations reveal the crucial roles of 2-m temperature and humidity as primary drivers, contributing 16% and 15% to daily ozone fluctuations, respectively. Regional wind fields account for up to 40% of ozone changes during the episodes. CNNs successfully replicate observed ozone temporal patterns, attributing -5-6 µg·m-3 of interannual ozone variability to weather anomalies. Our interpretable CNNs framework enables quantitative attribution of historical ozone fluctuations to nonlinear meteorological effects across spatiotemporal scales, offering vital process-based insights for managing megacity air quality amidst changing climate regimes.

Intra- and Interimage Reliability of Inter-Rectus Distance Measurements Determined via Ultrasound Imaging by the Same or Different Testers in Women in the Early Postpartum Period.

OBJECTIVES: No consensus regarding the optimal position and location for the measurement of the inter-rectus distance (IRD) via ultrasound (US) has been reached. By investigating the intra- and interimage reliability of IRD measurements taken in different positions and at different locations within and between testers, this study provides a theoretical basis for the current situation. METHODS: The IRD was measured via US in 46 women at 42-60 days after delivery at the superior margin of the umbilicus and 3 cm above, 5 cm above and 3 cm below the umbilicus while the women were in the supine, crunch and standing positions. In the interimage test, every participant was tested 2 times by Physician X and 1 time by Physician Y; in the intraimage test, the images collected by Physician X during the first test were saved in the machines, and two measurements were performed by Physician X and one measurement was performed by Physician Y. Paired t tests and intraclass correlation coefficients (ICCs) were calculated. RESULTS: Only the first IRD measurements by tester X and tester Y at 3 cm below the umbilicus in the crunch position were significantly different (9.56 ± 6.00 versus 11.00 ± 5.55) (P < .05). All the ICCs were greater than .75, and the intratester ICCs were greater than or equal to the corresponding intertester ICCs. The ICCs at 3 cm below the umbilicus were the smallest in the supine and crunch positions and the largest in the standing position due to the increased frequency of IRD values of 0. The ICCs for the crunch position were greatest according to the intraimage test but smallest according to the interimage test. The interimage ICCs between the two testers in the supine position at the superior margin, 3 cm above, 5 cm above, and 3 cm below the umbilicus were .972, .974, .975, and .956, respectively. CONCLUSIONS: Ultrasound imaging (USI) is a reliable method for measuring the IRD in women in the early postpartum period. The dynamic measurement of the IRD at or above the umbilicus in the supine position by different testers in real time showed the highest reliability.

Single-Cell Transcriptome Reveals Cell Type-Specific Molecular Pathology in a 2VO Cerebral Ischemic Mouse Model.

Post-ischemia memory impairment is a major sequela in cerebral ischemia patients. However, cell type-specific molecular pathology in the hippocampus after ischemia is poorly understood. In this study, we adopted a mouse two-vessel occlusion ischemia model (2VO model) to mimic cerebral ischemia-induced memory impairment and investigated the single-cell transcriptome in the hippocampi in 2VO mice. A total of 27,069 cells were corresponding 14 cell types with neuronal, glial, and vascular lineages. We next analyzed cell-specific gene alterations in 2VO mice and the function of these cell-specific genes. Differential expression analysis identified cell type-specific genes with altered expression in neurons, astrocytes, microglia, and oligodendrocytes in 2VO mice. Notably, four subtypes of oligodendrocyte precursor cells with distinct differentiation pathways were suggested. Taken together, this is the first single-cell transcriptome analysis of gene expression in a 2VO model. Furthermore, we suggested new types of oligodendrocyte precursor cells with angiogenesis and neuroprotective potential, which might offer opportunities to identify new avenues of research and novel targets for ischemia treatment.

Nanoformulations of chemotherapeutic activators of the cGAS-STING pathway in tumor chemoimmunotherapy.

Chemotherapeutic drugs to activate the cyclic guanosine monophosphate-adenosine monophosphate synthase (cGAS)-stimulator of interferon genes (STING) pathway have been exploited for tumor chemoimmunotherapy. The clinical translation of chemotherapeutic cGAS-STING activators is hindered by the lack of safe, efficient, and specific delivery strategies. Nanodrug delivery systems (NDDS) designed for reducing toxic effects and improving transport effectiveness potentiate in vivo delivery of chemotherapeutic cGAS-STING activators. cGAS-STING monotherapy often encounters tumor resistance without providing satisfactory therapeutic benefit; therefore combination therapy is desirable. This review describes NDDS strategies for surmounting delivery obstacles of chemotherapeutic cGAS-STING activators and highlights combinatorial regimens, which utilize therapeutics that work by different mechanisms, for optimal therapy.

Anti-stromal nanotherapeutics for hepatocellular carcinoma.

Hepatocellular carcinoma (HCC), the most commonly diagnosed primary liver cancer, has become a leading cause of cancer-related death worldwide. Accumulating evidence confirms that the stromal constituents within the tumor microenvironment (TME) exacerbate HCC malignancy and set the barriers to current anti-HCC treatments. Recent developments of nano drug delivery system (NDDS) have facilitated the application of stroma-targeting therapeutics, disrupting the stromal TME in HCC. This review discusses the stromal activities in HCC development and therapy resistance. In addition, it addresses the delivery challenges of NDDS for stroma-targeting therapeutics (termed anti-stromal nanotherapeutics in this review), and provides recent advances in anti-stromal nanotherapeutics for safe, effective, and specific HCC therapy.

Sacubitril/Valsartan Cannot Improve Cardiac Function Compared with Valsartan in Patients Suffering Nonvalvular Atrial Fibrillation without Systolic Heart Failure.

This study investigates the effect of sacubitril/valsartan (Sac/Val) in patients diagnosed with nonvalvular atrial fibrillation (AF) without systolic heart failure (SHF).Nonvalvular AF patients without SHF admitted to the People's Hospital of Bortala Mongol Autonomous Prefecture from December 2020 to December 2021 were enrolled and randomly divided into Sac/Val treatment group (group T) and valsartan treatment group (group C, control). For subgroup analysis, patients were divided into subgroups with and without diastolic heart failure (DHF). After 1-month adaptive phase and subsequent 3-month treatment period, patients were followed up in the cardiology clinic. Plasma levels of biochemical markers and echocardiographic parameters before and after treatment were evaluated, and DHF scores were computed to assess diastolic function.Of 61 enrolled patients, 46 patients completed follow-up. Sac/Val treatment did not increase the percentage of sinus rhythm. Although N-terminal pro-B-type natriuretic peptide (NT-proBNP) expression tended to be reduced in both groups after 3 months of treatment, the differences compared with respective baseline levels and between groups were not significant. According to subgroup analysis, although NT-proBNP expression in the subgroup with DHF was lower at follow-up compared to baseline, the difference was not statistically significant. Similarly, no marked differences in echocardiographic parameters or tissue Doppler parameters related to DHF were detected between the groups (P > 0.05). Additionally, a subgroup analysis found no significant variations in the echocardiographic measures (P > 0.05).Sac/Val is not superior to valsartan for the short-term treatment of patients suffering with AF without SHF in improving NT-proBNP level and cardiac function.

M2pep-Modified Cyclodextrin-siRNA Nanoparticles Modulate the Immunosuppressive Tumor Microenvironment for Prostate Cancer Therapy.

Prostate cancer (PCa) is the most prevalent cause of cancer deaths in men. Conventional strategies, such as surgery, radiation, or chemotherapy, face challenges including poor prognosis and resistance. Therefore, the development of new improved strategies is vital to enhance patient outcomes. Recently, immunotherapy has shown potential in the treatment of a range of cancers, including PCa. Tumor-associated macrophages (TAMs) play an important role in the tumor microenvironment (TME) and reprogramming of TAMs is associated with remodeling the TME. The colony-stimulating factor-1/colony stimulating factor-1 receptor (CSF-1/CSF-1R) signaling pathway is closely related to the polarization of TAMs. The downregulation of CSF-1R, using small interfering RNA (siRNA), has been shown to achieve the reprogramming of TAMs, from the immunosuppressive M2 phenotype to the immunostimulatory M1 one. To maximize specific cellular delivery an M2 macrophage-targeting peptide, M2pep, was formulated with an amphiphilic cationic ß-Cyclodextrin (CD) incorporating CSF-1R siRNA. The resulting nanoparticles (NPs) increased M2 macrophage targeting both in vitro and in vivo, promoting the release of M1 factors and simultaneously downregulating the levels of M2 factors through TAM reprogramming. The subsequent remodeling of the TME resulted in a reduction in tumor growth in a subcutaneous PCa mouse model mainly mediated through the recruitment of cytotoxic T cells. In summary, this M2pep-targeted CD-based delivery system demonstrated significant antitumor efficacy, thus presenting an alternative immunotherapeutic strategy for PCa treatment.

Analysis of influencing factors on vibration characteristics of electro-hydraulic vibration cutting system.

The cutting process of the cantilever tunneling machine mainly generates excitation through the cutting motor or the hydraulic cylinder driven by the hydraulic system. Regardless of the driving method, the frequency width of the excitation system is limited, difficult to control, and the excitation effect is poor. Therefore, in order to improve excavation efficiency, the excitation system parallel to the original cutting and rotating system is designed. Based on the excitation characteristics caused by alternating fluid flow, the core component of the excitation system, hydraulic exciter, is designed, and the dynamics and dynamic characteristics of the excitation system are analyzed. Based on AMESim software, analyze the impact of factors such as pump displacement, excitation frequency, and pipeline parameters on the operational performance of the electro-hydraulic vibration cutting system, and conduct experimental verification by building a cutting test bench. The experimental results show that as the inner diameter of the pipeline increases, the fluctuation at the acceleration turning point decreases in each cycle and approaches the peak faster. As the excitation frequency increases, the cutting acceleration of the electro-hydraulic excitation cutting system decreases first and then increases, verifying the accuracy of the simulation results. In the experiment, it was found that the acceleration transformation range of the cutting head of the excitation system is the smallest and most stable when the excitation frequency is 30 Hz. In order to verify that the excitation frequency of 30 Hz is the optimal frequency, further contact force tests were conducted on the cutting teeth. It was found that when the hydraulic excitation system adds a 30 Hz excitation frequency, the contact force on the cutting teeth is the smallest. It is more conducive to reducing the damage and wear of the cutting head, and the cutting effect of the cutting head is more obvious. The research results are beneficial for improving the cutting performance of the electro-hydraulic excitation cutting system, providing theoretical support for the selection of cutting parameters for excavation machinery and hydraulic excitation, and improving the existing theoretical system for active excitation cutting vibration analysis of excavation machines.

Killing tumor-associated bacteria with a liposomal antibiotic generates neoantigens that induce anti-tumor immune responses.

Increasing evidence implicates the tumor microbiota as a factor that can influence cancer progression. In patients with colorectal cancer (CRC), we found that pre-resection antibiotics targeting anaerobic bacteria substantially improved disease-free survival by 25.5%. For mouse studies, we designed an antibiotic silver-tinidazole complex encapsulated in liposomes (LipoAgTNZ) to eliminate tumor-associated bacteria in the primary tumor and liver metastases without causing gut microbiome dysbiosis. Mouse CRC models colonized by tumor-promoting bacteria (Fusobacterium nucleatum spp.) or probiotics (Escherichia coli Nissle spp.) responded to LipoAgTNZ therapy, which enabled more than 70% long-term survival in two F. nucleatum-infected CRC models. The antibiotic treatment generated microbial neoantigens that elicited anti-tumor CD8+ T cells. Heterologous and homologous bacterial epitopes contributed to the immunogenicity, priming T cells to recognize both infected and uninfected tumors. Our strategy targets tumor-associated bacteria to elicit anti-tumoral immunity, paving the way for microbiome-immunotherapy interventions.

d-lactate modulates M2 tumor-associated macrophages and remodels immunosuppressive tumor microenvironment for hepatocellular carcinoma.

The polarization of tumor-associated macrophages (TAMs) from M2 to M1 phenotype demonstrates great potential for remodeling the immunosuppressive tumor microenvironment (TME) of hepatocellular carcinoma (HCC). d-lactate (DL; a gut microbiome metabolite) acts as an endogenous immunomodulatory agent that enhances Kupffer cells for clearance of pathogens. In this study, the potential of DL for transformation of M2 TAMs to M1 was confirmed, and the mechanisms underlying such polarization were mainly due to the modulation of phosphatidylinositol 3-kinase/protein kinase B pathway. A poly(lactide-co-glycolide) nanoparticle (NP) was used to load DL, and the DL-loaded NP was modified with HCC membrane and M2 macrophage-binding peptide (M2pep), forming a nanoformulation (DL@NP-M-M2pep). DL@NP-M-M2pep transformed M2 TAMs to M1 and remodeled the immunosuppressive TME in HCC mice, promoting the efficacy of anti-CD47 antibody for long-term animal survival. These findings reveal a potential TAM modulatory function of DL and provide a combinatorial strategy for HCC immunotherapy.

Direct yaw-moment control of electric vehicles based on adaptive sliding mode.

The direct yaw-moment control (DYC) system consisting of an upper controller and a lower controller is developed on the basis of sliding mode theory and adaptive control technique. First, the two-degree of freedom (2-DOF) model is utilized to calculate the ideal yaw rate. Then, the seven-degree of freedom (7-DOF) electric vehicle model is given to design the upper controller by employing first-order sliding mode (FOSM) method, which is constructed to guarantee the actual yaw rate to approach the ideal value and gain the additional yaw moment. On this basis, an adaptive first-order sliding mode (AFOSM) controller is designed to enhance the system robustness against probable modelling error and parametric uncertainties. In order to mitigate the chattering issue present in the FOSM controller, a novel adaptive super-twisting sliding mode (ASTSM) controller is proposed for the design of DYC. Furthermore, the lower controller converting the additional yaw moment into driving or braking torque acting on each wheel is also developed. Finally, The simulation results indicate that the proposed DYC system can improve the electric vehicle driving stability effectively.

[Characteristics of VOCs and Assessment of Emission Reduction Effect During the Epidemic Lockdown Period in Shenzhen Urban Area].

To prevent disease spreading during the COVID-19 epidemic, Shenzhen adopted lockdown measures in March of 2022. This provided an opportunity to study the response of changes in anthropogenic volatile organic compounds (AVOCs) in Shenzhen to emission reduction and to evaluate the effectiveness of current emission reduction measures. This study analyzed the variety of AVOCs before, during, and after the epidemic lockdown based on the online observation data of pollutants at Lianhua Station in Shenzhen from March 7, 2022 to March 27, 2022. Additionally, the sensitivity of ozone formation and the assessment of the reduction effect of precursors was conducted by an observation based model(OBM). The results showed that:affected by regional influences and the interference of meteorological conditions, the average value of AVOCs in Shenzhen urban areas did not drop significantly during the lockdown period compared to that before the lockdown. However, the peak of AVOCs at the morning peak time under the influence of "sea and land wind" during the epidemic lockdown period dropped by 46% on average compared with that during the non-lockdown period, and the aromatic hydrocarbon component dropped the most by 59%. Additionally, under the influence of continuous easterly wind, or during the accumulation and increase of AVOCs affected by regional transmission, aromatic components also decreased by an average of 25% and 21%, respectively. During the lockdown period of the epidemic in Shenzhen, the O3 formation in urban areas was still AVOCs-limited. Increasing the emission reduction ratio of AVOCs was the most effective measure to reduce O3 in the short term. In order to ensure the effectiveness of emission reduction, it was recommended that the coordinated emission reduction ratio of AVOCs and NOx should be greater than 1:2. It was only possible to enter the downward channel of O3 if the deep emission reduction was more than 60%. This study revealed that the emission reduction of AVOCs during the morning traffic peak during the epidemic lockdown period was conducive to inhibiting the formation of O3, whereas the control of NOx would promote it. Strengthening the control of local aromatic hydrocarbon components during the regional impact process could also significantly reduce O3 production. At this stage, Shenzhen should strengthen the management and control of industrial solvents, especially to reduce the aromatic hydrocarbon components in the solvent source that have a greater impact on the generation of O3. Further, Shenzhen should continue to promote the reform of the energy structure of motor vehicles to reduce the emission of VOCs in fuel combustion.

EZH2 Contributes to Anoikis Resistance and Promotes Epithelial Ovarian Cancer Peritoneal Metastasis by Regulating m6A.

OBJECTIVE: Histone modification has a significant effect on gene expression. Enhancer of zeste homolog 2 (EZH2) contributes to the epigenetic silencing of target chromatin through its roles as a histone-lysine N-methyltransferase enzyme. The development of anoikis resistance in tumor cells is considered to be a critical step in the metastatic process of primary malignant tumors. The purpose of this study was to investigate the effect and mechanism of anoikis resistance in ovarian adenocarcinoma peritoneal metastasis. METHODS: In addition to examining EZH2 protein expression in ovarian cancer omental metastatic tissues, we established a model of ovarian cancer cell anoikis and a xenograft tumor model in nude mice. Anoikis resistance and ovarian cancer progression were tested after EZH2 and N6-methyladenosine (m6A) levels were modified. RESULTS: EZH2 expression was significantly higher in ovarian cancer omental metastatic tissues than in normal ovarian tissues. Reducing the level of EZH2 decreased the level of m6A and ovarian cancer cell anoikis resistance in vitro and inhibited ovarian cancer progression in vivo. M6a regulation altered the effect of EZH2 on anoikis resistance. CONCLUSION: Our results indicate that EZH2 contributes to anoikis resistance and promotes ovarian adenocarcinoma abdominal metastasis by m6A modification. Our findings imply the potential of the clinical application of m6A and EZH2 for patients with ovarian cancer.

Observation on the aerosol and ozone precursors in suburban areas of Shenzhen and analysis of potential source based on MAX-DOAS.

Long-term stereoscopic observations of aerosol, NO2, and HCHO were carried out at the Yangmeikeng (YMK) site in Shenzhen. Aerosol optical depths and NO2 vertical column concentration (NO2 VCD) derived from MAX-DOAS were found to be consistent with other datasets. The total NO2 VCD values of the site remained low, varying from 2 × 1015 to 8 × 1015 mol/cm2, while the HCHO VCD was higher than NO2 VCD, varying from 7 × 1015 to 11 × 1015 mol/cm2. HCHO VCD was higher from September to early November than that was from mid-late November to December and during February 2021, in contrast, NO2 VCD did not change much during the same period. In January, NO2 VCD and HCHO VCD were both fluctuating drastically. High temperature and HCHO level in the YMK site is not only driving the ozone production up but also may be driving up the ozone concentration as well, and the O3 production regime in the YMK site tends to be NOx-limited. At various altitudes, backward trajectory clustering analysis and Potential Source Contribution Function (PSCF) were utilized to identify possible NO2 and HCHO source locations. The results suggested that the Huizhou-Shanwei border and the Daya Bay Sea area were the key potential source locations in the lower (200 m) and middle (500 m) atmosphere (WPSCF > 0.6). The WPSCF value was high at the 1000 m altitude which was closer to the YMK site than the near ground, indicating that the pollution transport capability in the upper atmosphere was limited.