Effective prism diopter for strabismus measurement: Conversion from anterior Prentice position to posterior parallel position and from glass prism to acrylic prism.

PURPOSE: In clinical ophthalmology, prisms, commonly made of glass, are labeled based on the prism diopter (PD) value measured in the anterior Prentice position. However, they are often used in the posterior parallel position for practicality, causing a discrepancy between labeled and effective PD. This study proposes a conversion tool to address this issue. METHODS: Geometric optical analysis was employed to calculate the effective PD of glass prisms in the posterior parallel position. A lookup table was created to convert the labeled PD of the anterior Prentice position to the effective PD when the prism is used in the posterior parallel position. Clinical data from 162 patients with horizontal strabismus were collected to validate the method. Glass prism measurements, converted to effective PD, were compared with acrylic prism results. RESULTS: The variations were significant in glass prism PD with rotation in the anterior Prentice position but stability in the posterior parallel position. Clinical deviations were larger with glass prisms, especially exceeding 30 PD, compared with acrylic prisms. Converted PD from glass prisms correlated well with acrylic prisms (R2 = 0.94, P = 0.002). The half-width of the 95% limit of agreement was ±12.32 PD. CONCLUSION: The proposed conversion table is valid, facilitating consistency between clinical and literature-based prism use in different positions and materials.

Combination of Diosmetin With Chrysin Against Hepatocellular Carcinoma Through Inhibiting PI3K/AKT/mTOR/NF-кB Signaling Pathway: TCGA Analysis, Molecular Docking, Molecular Dynamics, In Vitro Experiment.

Hepatocellular carcinoma (HCC) is the sixth most prevalent malignant tumor. Hepatocellular carcinogenesis is closely linked to apoptosis, autophagy, and inflammation. Diosmetin and chrysin, are two flavonoid compounds, exhibit anti-inflammatory and anticancer properties. In this study, the TCGA database was utilized to identify differentially expressed genes between normal subjects and HCC patients. Molecular docking and molecular dynamics analyses were employed to assess the binding affinity of chrysin and diosmetin to key proteins in the PI3K/AKT/mTOR/NF-κB signaling pathway. Western blotting and RT-qPCR were used to measure the protein and gene expression within this pathway. The results indicated that HCC patients had elevated levels of PI3K, AKT, mTOR, and P65 proteins compared to normal subjects, which adversely affected patient survival. Molecular docking and dynamics studies demonstrated that diosmetin and chrysin are effectively bound to these four proteins. In vitro experiments revealed that the combination of diosmetin and chrysin could induce apoptosis, enhance autophagy, reduce inflammatory mediator production, and improve the tumor cell microenvironment by inhibiting the PI3K/AKT/mTOR/NF-κB signaling pathway. Notably, the synergy score for the combination of diosmetin (25 µM) and chrysin (10 µM) was 16. Thus, the diosmetin-chrysin combination shows promise as an effective therapeutic approach for hepatocellular carcinoma due to its strong synergistic effect.

Compromised endothelial Wnt/ß-catenin signaling mediates the blood-brain barrier disruption and leads to neuroinflammation in endotoxemia.

The blood-brain barrier (BBB) is a critical interface that maintains the central nervous system homeostasis by controlling the exchange of substances between the blood and the brain. Disruption of the BBB plays a vital role in the development of neuroinflammation and neurological dysfunction in sepsis, but the mechanisms by which the BBB becomes disrupted during sepsis are not well understood. Here, we induced endotoxemia, a major type of sepsis, in mice by intraperitoneal injection of lipopolysaccharide (LPS). LPS acutely increased BBB permeability, activated microglia, and heightened inflammatory responses in brain endothelium and parenchyma. Concurrently, LPS or proinflammatory cytokines activated the NF-κB pathway, inhibiting Wnt/ß-catenin signaling in brain endothelial cells in vitro and in vivo. Cell culture study revealed that NF-κB p65 directly interacted with ß-catenin to suppress Wnt/ß-catenin signaling. Pharmacological NF-κB pathway inhibition restored brain endothelial Wnt/ß-catenin signaling activity and mitigated BBB disruption and neuroinflammation in septic mice. Furthermore, genetic or pharmacological activation of brain endothelial Wnt/ß-catenin signaling substantially alleviated LPS-induced BBB leakage and neuroinflammation, while endothelial conditional ablation of the Wnt7a/7b co-receptor Gpr124 exacerbated the BBB leakage caused by LPS. Mechanistically, Wnt/ß-catenin signaling activation rectified the reduced expression levels of tight junction protein ZO-1 and transcytosis suppressor Mfsd2a in brain endothelial cells of mice with endotoxemia, inhibiting both paracellular and transcellular permeability of the BBB. Our findings demonstrate that endotoxemia-associated systemic inflammation decreases endothelial Wnt/ß-catenin signaling through activating NF-κB pathway, resulting in acute BBB disruption and neuroinflammation. Targeting the endothelial Wnt/ß-catenin signaling may offer a promising therapeutic strategy for preserving BBB integrity and treating neurological dysfunction in sepsis.

Transcriptomic analysis of spleen-derived macrophages in response to lipopolysaccharide shows dependency on the MyD88-independent pathway in Chinese giant salamanders (Andrias davidianus).

BACKGROUND: Gram-negative bacteria are the main bacterial pathogens infecting Chinese giant salamanders (Andrias davidianus; CGS) in captivity and the wild, causing substantial economic losses in the CGS industry. However, the molecular mechanisms underlying pathogenesis following infection remain unclear. RESULTS: Spleen-derived macrophages from healthy CGS were isolated, cultured, and identified using density gradient centrifugation and immunofluorescence. A macrophage transcriptome database was established 0, 6, and 12 h post lipopolysaccharide stimulation using RNA-sequencing. In the final database 76,743 unigenes and 4,698 differentially expressed genes (DEGs) were functionally annotated. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment results showed that DEGs were concentrated in toll-like receptor-nuclear factor kappa B-related immune pathways. Ten DEGs were validated 12 h after lipopolysaccharide (LPS) stimulation. Although the common LPS recognition receptor toll-like receptor 4 was not activated and the key adaptor protein MyD88 showed no significant response, we observed significant up-regulation of the following adaptors: toll/interleukin-1 receptor domain-containing adaptor inducing interferon-ß, tumour necrosis factor receptor-associated factor 6, and transforming growth factor-ß activated kinase 1, which are located downstream of the non-classical MyD88 pathway. CONCLUSIONS: In contrast to that in other species, macrophage activation in CGS could depend on the non-classical MyD88 pathway in response to bacterial infection. Our study provides insights into the molecular mechanisms regulating CGS antibacterial responses, with implications for disease prevention and understanding immune evolution in amphibians.

[Spatiotemporal Characterization and Driving Factors of Fine Particulate Matter and Its Chemical Components in the Huaihe River Basin].

According to the data sets of fine particulate matter （PM2.5） and its components in 35 cities in the Huaihe River Basin from 2015 to 2021, the temporal and spatial distribution patterns of pollutants were analyzed. The influence of meteorological factors on PM2.5 concentrations was examined using a random forest model. The original series of PM2.5, sulfate （SO42-）, nitrate （NO3-）, ammonium salt （NH4+）, organic matter （OM）, and black carbon （BC） were rebuilt using KZ （Kolmogorov-Zurbenko） filtering and multiple linear regression （MLR） to quantify the effects of meteorological conditions. The results demonstrated that from 2015 to 2021, the declining rates of PM2.5, SO42-, NO3-, NH4+, OM, and BC in the Huaihe River Basin were 4.71, 0.99, 1.05, 0.77, 1.01, and 0.19 µg·ï¼ˆm3·a）-1, respectively. The high mass concentrations of PM2.5 and its components were concentrated in the central and western regions of the HRB, whereas those in coastal and southern cities were lower. The variance contributions of the short-term, seasonal, and long-term components of PM2.5 to the original PM2.5 sequences in 35 cities were 51.6%, 35.9%, and 7.0%, respectively. The PM2.5 in coastal cities were more affected by the short-term components. The meteorological conditions were unfavorable for PM2.5 reduction in the HRB from 2015 to 2018, whereas the meteorological conditions supported the PM2.5 decrease from 2019 to 2021. From 2015 to 2021, the contribution rates of meteorological conditions to the long-term component reductions of PM2.5, SO42-, NO3-, NH4+, OM, and BC were 28.3%, 29.1%, 31.0%, 29.3%, 27.8%, and 28.6%, respectively. The contribution rates of meteorological conditions to the long-term PM2.5 reduction were 43.4%, 25.6%, 25.5%, and 20.6% in the HRB cities in Anhui, Shandong, Jiangsu, and Henan Provinces, respectively. With the decrease in PM2.5 concentration in the HRB, the sulfur oxidation rate （SOR） increased significantly, while the nitrogen oxide oxidation rate （NOR） changed little.

Single-cell RNA sequencing and spatial transcriptomics of bladder Ewing sarcoma.

Bladder Ewing sarcoma/primitive neuroectodermal tumor (bladder ES/PNET) is a rare and highly malignant tumor associated with a poor prognosis, yet its underlying mechanisms remain poorly understood. Here, we employed a combination of single-cell RNA sequencing (scRNA-seq), spatial transcriptomics (ST), and functional analyses to delve into the pathogenesis of bladder ES/PNET. The investigation revealed the presence of specialized types of epithelial cells (referred to as bladder ES-Epi) and mast cells (referred to as bladder ES-Mast) within bladder ES/PNET in comparison to urothelial carcinoma. Notably, TNFRSF12A exhibited significant upregulation in bladder ES/PNET. Furthermore, mast cells possessed the ability to activate epithelial cells through the TNFSF12-TNFRSF12A ligand-receptor signaling pattern. In addition, Enavatuzumab can significantly inhibit the migratory ability of the Ewing sarcoma cell line RD-ES. This groundbreaking study provides unprecedented mechanistic insights into the progression of bladder ES/PNET and introduces a potential therapeutic avenue for treating this challenging malignancy.

Postoperative Orbital Morphology Observations Following Fronto-Orbital Advancement and Cranial Vault Remodeling in Patients With Unilateral Coronal Synostosis.

OBJECT: Observations of preoperative and postoperative orbital morphology following fronto-orbital advancement and cranial vault remodeling (FOA and CVR) in patients with unilateral coronal synostosis (UCS). METHODS: This retrospective cohort included patients diagnosed with unilateral coronal synostosis and treated with fronto-orbital advancement and cranial vault remodeling at the Children's Hospital of Fudan University. The orbital height, orbital width, and orbital volume were obtained from head 3-dimensional computed tomography of preoperation and postoperation. The DICOM data of CT were then imported into mimics research version 21.0. The authors measured OH and OW according to the bony landmarks, then reset the parameters of the soft tissue window, and conducted a 3-dimensional reconstruction of the orbital soft tissue to get OV. The preoperative and postoperative measurements of the intact side were compared with the affected side, respectively. Statistical analysis was performed using SPSS version 25.0 (Ρ=0.05). RESULTS: Twelve patients with UCS (5 male, 7 female) meeting criteria were included in the study. There were 4 patients with UCS on the left and 8 on the right. The average age at initial surgery was 19.50 months. Before the operation, the data of the intact side and the affected side were compared, respectively, and the difference was found to be significant in OH (Ρ=0.005) and OW (Ρ=0.005), while the OV (Ρ=0.106) was not statistically significant. After procedures of FOA and CVR, the data of the intact side and the affected side were compared, respectively, the significant difference was found in OV (Ρ=0.002), while not in OH (Ρ=0.060) or OW (Ρ=0.066). CONCLUSION: After undergoing the operation of FOA and CVR, the OH and OW of the ipsilateral and contralateral sides of patients with UCS were basically symmetrical, while the volume of the affected orbit was still relatively smaller.

Fine-Tuning of Optical Resonance Wavelength of Surface-Micromachined Optical Ultrasound Transducer Arrays for Single-Wavelength Light Source Readout.

This article reports the fine-tuning of the optical resonance wavelength (ORW) of surface-micromachined optical ultrasound transducer (SMOUT) arrays to enable ultrasound data readout with non-tunable interrogation light sources for photoacoustic computed tomography (PACT). Permanent ORW tuning is achieved by material deposition onto or subtraction from the top diaphragm of each element with sub-nanometer resolution. For demonstration, a SMOUT array is first fabricated, and its ORW is tuned for readout with an 808 nm laser diode (LD). Experiments are conducted to characterize the optical and acoustic performances of the elements within the center region of the SMOUT array. Two-dimensional and three-dimensional PACT (photoacoustic computed tomography) is also performed to evaluate the imaging performance of the ORW-tuned SMOUT array. The results show that the ORW tuning does not degrade the optical, acoustic, and overall imaging performances of the SMOUT elements. As a result, the fine-tuning method enables new SMOUT-based PACT systems that are low cost, compact, powerful, and even higher speed, with parallel readout capability.

A review of multiparametric ultrasound imaging in the clinical setting: scrotal contents.

The innovative techniques in ultrasound have added a new dimension to investigating superficially located areas such as the contents of the scrotal sac. High frequency transducers, improved technology with the addition of elastography, contrast enhanced ultrasound and microvascular imaging has resulted in a further improvement in diagnostic capabilities. The ability to clearly demonstrate the presence or absence of vascularity within the area under investigation adds an additional dimension to operator confidence in establishing the presence of infarction, global or segmental, or the walls and cavity of an abscess in the testis or epididymis. Increased vascularity of a tumor aids the differential diagnosis based on the flow dynamics of the microbubble contrast, benign lesions likely to retain contrast. Elastography has the ability to ascertain the stiffness of tissue, and when used in conjunction with other ultrasound methods adds to the understanding of the likelihood of a malignant abnormality being present. All the different techniques come under the umbrella term 'multiparametric ultrasound', with the application in the scrotal sac detailed in this article.

Mutation of KAP, which encodes a keratin-associated protein, affects grain size and yield production in rice.

Grain size and shape are critical agronomic traits that directly impact rice grain yield. Identifying genes that control these traits can provide new strategies for yield improvement. In this study, we characterized a rice mutant, reduced grain length (rgl), which exhibited decreased grain length due to reduced cell proliferation. Map-based cloning identified a base deletion in OsRGL2, a gene encoding a keratin-associated protein (KAP), as the cause of the mutant phenotype. CRISPR-Cas9-generated OsRGL2 knockout mutants also displayed reduced grain length, confirming its role. OsRGL2 transcripts were detected in various tissues, with relative higher gene expression in young panicles, and OsRGL2 was localized to the plasma membrane. Overexpression of OsRGL2 increased grain size by promoting cell proliferation in the spikelet hull and significantly enhanced grain yield per plant. Importantly, OsRGL2 was found to interact with RGB1, indicating that OsRGL2 positively regulates grain size and yield through its interaction with RGB1. Additionally, OsRGL2 regulated the expression of cell cycle-related genes, further elucidating its role in grain development. These findings demonstrate that OsRGL2 is a positive regulator of grain size in rice, and manipulating its expression may offer a novel strategy for enhancing rice grain yield.

Quantitative Ultrasound and Ultrasound-Based Elastography for Chronic Liver Disease: Practical Guidance, From the AJR Special Series on Quantitative Imaging.

Quantitative ultrasound (QUS) and ultrasound-based elastography techniques are emerging as non-invasive effective methods for assessing chronic liver disease. They are more accurate than B-mode imaging alone and more accessible than MRI as alternatives to liver biopsy. Early detection and monitoring of diffuse liver processes such as steatosis, inflammation, and fibrosis play an important role in guiding patient management. The most widely available and validated techniques are attenuation-based QUS techniques and shear-wave elastography techniques that measure shear-wave speed. Other techniques are supported by a growing body of evidence and are increasingly commercialized. This review explains general physical concepts of QUS and ultrasound-based elastography techniques for evaluating chronic liver disease. The first section describes QUS techniques relying on attenuation, backscatter, and speed of sound. The second section discusses ultrasound-based elastography techniques analyzing shear-wave speed, shear-wave dispersion, and shear-wave attenuation. With an emphasis on clinical implementation, each technique's diagnostic performance along with thresholds for various clinical applications are summarized, to provide guidance on analysis and reporting for radiologists. Measurement methods, advantages, and limitations are also discussed. The third section explores developments in quantitative contrast-enhanced and vascular ultrasound that are relevant to chronic liver disease evaluation.

Comprehensive analysis of bulk and single-cell RNA sequencing data reveals Schlafen-5 (SLFN5) as a novel prognosis and immunity.

Recent advancements have elucidated the multifaceted roles of the Schlafen (SLFN) family, including SLFN5, SLFN11, SLFN12, SLFN13, and SLFN14, which are implicated in immunological responses. However, little is known about the roles of this gene family in relation to malignancy development. The current study aimed to explore the diagnostic and prognostic potential of Schlafen family genes in colorectal adenocarcinoma (COAD) through bioinformatics analysis. Leveraging advanced bioinformatics tools of bulk RNA-sequencing and single-cell sequencing, we conducted in-depth analyses of gene expressions, functional enrichment, and survival patterns of patients with colorectal cancer compared to normal tissue. Among Schlafen family genes, the transcription levels of SLFN5 in COAD tissues were significantly elevated and correlated with poor survival outcomes. Furthermore, SLFN5 regulated the immune response via Janus kinase (JAK)/signal transduction and activator of transcription (STAT)/interferon (IFN)-alpha/beta signaling. These chemokines in inflammation are associated with diabetes and metabolism, suggesting their involvement in altered cellular energetics for COAD progress. In addition, an immune cell deconvolution analysis indicated a correlation between SLFN5 expression and immune-related cell populations, such as regulatory T cells (Tregs). These findings highlighted the potential clinical significance of SLFN5 in COAD and provided insights into its involvement in the tumor microenvironment and immune regulation. Meanwhile, the drug discovery data of SFLN5 with potential targeted small molecules suggested its therapeutic potential for COAD. Collectively, the current research demonstrated that SFLN5 play crucial roles in tumor development and serve as a prospective biomarker for COAD.

Development of a System for Predicting Hospitalization Time for Patients With Traumatic Brain Injury Based on Machine Learning Algorithms: User-Centered Design Case Study.

Background: Currently, the treatment and care of patients with traumatic brain injury (TBI) are intractable health problems worldwide and greatly increase the medical burden in society. However, machine learning-based algorithms and the use of a large amount of data accumulated in the clinic in the past can predict the hospitalization time of patients with brain injury in advance, so as to design a reasonable arrangement of resources and effectively reduce the medical burden of society. Especially in China, where medical resources are so tight, this method has important application value. Objective: We aimed to develop a system based on a machine learning model for predicting the length of hospitalization of patients with TBI, which is available to patients, nurses, and physicians. Methods: We collected information on 1128 patients who received treatment at the Neurosurgery Center of the Second Affiliated Hospital of Anhui Medical University from May 2017 to May 2022, and we trained and tested the machine learning model using 5 cross-validations to avoid overfitting; 28 types of independent variables were used as input variables in the machine learning model, and the length of hospitalization was used as the output variables. Once the models were trained, we obtained the error and goodness of fit (R2) of each machine learning model from the 5 rounds of cross-validation and compared them to select the best predictive model to be encapsulated in the developed system. In addition, we externally tested the models using clinical data related to patients treated at the First Affiliated Hospital of Anhui Medical University from June 2021 to February 2022. Results: Six machine learning models were built, including support vector regression machine, convolutional neural network, back propagation neural network, random forest, logistic regression, and multilayer perceptron. Among them, the support vector regression has the smallest error of 10.22% on the test set, the highest goodness of fit of 90.4%, and all performances are the best among the 6 models. In addition, we used external datasets to verify the experimental results of these 6 models in order to avoid experimental chance, and the support vector regression machine eventually performed the best in the external datasets. Therefore, we chose to encapsulate the support vector regression machine into our system for predicting the length of stay of patients with traumatic brain trauma. Finally, we made the developed system available to patients, nurses, and physicians, and the satisfaction questionnaire showed that patients, nurses, and physicians agreed that the system was effective in providing clinical decisions to help patients, nurses, and physicians. Conclusions: This study shows that the support vector regression machine model developed using machine learning methods can accurately predict the length of hospitalization of patients with TBI, and the developed prediction system has strong clinical use.

Combining Clinical-Radiomics Features With Machine Learning Methods for Building Models to Predict Postoperative Recurrence in Patients With Chronic Subdural Hematoma: Retrospective Cohort Study.

BACKGROUND: Chronic subdural hematoma (CSDH) represents a prevalent medical condition, posing substantial challenges in postoperative management due to risks of recurrence. Such recurrences not only cause physical suffering to the patient but also add to the financial burden on the family and the health care system. Currently, prognosis determination largely depends on clinician expertise, revealing a dearth of precise prediction models in clinical settings. OBJECTIVE: This study aims to use machine learning (ML) techniques for the construction of predictive models to assess the likelihood of CSDH recurrence after surgery, which leads to greater benefits for patients and the health care system. METHODS: Data from 133 patients were amassed and partitioned into a training set (n=93) and a test set (n=40). Radiomics features were extracted from preoperative cranial computed tomography scans using 3D Slicer software. These features, in conjunction with clinical data and composite clinical-radiomics features, served as input variables for model development. Four distinct ML algorithms were used to build predictive models, and their performance was rigorously evaluated via accuracy, area under the curve (AUC), and recall metrics. The optimal model was identified, followed by recursive feature elimination for feature selection, leading to enhanced predictive efficacy. External validation was conducted using data sets from additional health care facilities. RESULTS: Following rigorous experimental analysis, the support vector machine model, predicated on clinical-radiomics features, emerged as the most efficacious for predicting postoperative recurrence in patients with CSDH. Subsequent to feature selection, key variables exerting significant impact on the model were incorporated as the input set, thereby augmenting its predictive accuracy. The model demonstrated robust performance, with metrics including accuracy of 92.72%, AUC of 91.34%, and recall of 93.16%. External validation further substantiated its effectiveness, yielding an accuracy of 90.32%, AUC of 91.32%, and recall of 88.37%, affirming its clinical applicability. CONCLUSIONS: This study substantiates the feasibility and clinical relevance of an ML-based predictive model, using clinical-radiomics features, for relatively accurate prognostication of postoperative recurrence in patients with CSDH. If the model is integrated into clinical practice, it will be of great significance in enhancing the quality and efficiency of clinical decision-making processes, which can improve the accuracy of diagnosis and treatment, reduce unnecessary tests and surgeries, and reduce the waste of medical resources.

Revealing and reconstructing the 3D Li-ion transportation network for superionic poly(ethylene) oxide conductor.

Understanding the Li-ions conduction network and transport dynamics in polymer electrolyte is crucial for developing reliable all-solid-state batteries. In this work, advanced nano- X-ray computed tomography combined with Raman spectroscopy and solid state nuclear magnetic resonance are used to multi-scale qualitatively and quantitatively reveal ion conduction network of poly(ethylene) oxide (PEO)-based electrolyte (from atomic, nano to macroscopic level). With the clear mapping of the microstructural heterogeneities of the polymer segments, aluminium-oxo molecular clusters (AlOC) are used to reconstruct a high-efficient conducting network with high available Li-ions (76.7%) and continuous amorphous domains via the strong supramolecular interactions. Such superionic PEO conductor (PEO-LiTFSI-AlOC) exhibites a molten-like Li-ion conduction behaviour among the whole temperature range and delivers an ionic conductivity of 1.87 × 10-4 S cm-1 at 35 °Ï¹. This further endows Li electrochemical plating/stripping stability under 50 µA cm-2 and 50 µAh cm-2 over 2000 h. The as-built Li|PEO-LiTFSI-AlOC|LiFePO4 full batteries show a high rate performance and a capacity retention more than 90% over 200 cycling at 250 µA cm-2, even enabling a high-loading LiFePO4 cathode of 16.8 mg cm-2 with a specific capacity of 150 mAh g-1 at 50 °Ï¹.

[Estimation of Regional Background Ozone in Henan Province from 2019 to 2021].

Clarifying the regional transmission and local generation contributions of ozone （O3） is important for controlling O3 pollution. To quantify the regional background and spatial-temporal variations of O3, a comprehensive study was conducted using multiple methods including principal component analysis （PCA） and TCEQ, with Henan Province as a case study. Based on monitoring data from 59 national sites in Henan Province during 2019-2021, four methods were employed to estimate the regional background of O3. Method 1 was the traditional method, performing O3 univariate-multisite PCA analysis. Method 2 was a multivariate-single-site PCA analysis considering nitrogen dioxide and meteorological conditions as constraints. Method 3 combined PCA and multiple linear regression （MLR） to determine regional background contributions, drawing on the idea of source apportionment. Method 4 was the TCEQ method that used the lowest measured O3-8h concentration as the regional background. The estimation results showed that Methods 1 and 2 were basically equal, and Methods 3 and 4 were approximately 37-60 µg·m-3 lower than Method 1. From 2019 to 2021, the changes in regional background ρ（O3-8h） estimated by Methods 1-4 were 1.6, -13.4, 5.9, and -3.5 µg·m-3, respectively. The average estimations derived from multiple methods showed that the regional background ρ（O3-8h） in Henan Province from 2019 to 2021 concentrations were 82.0, 79.0, and 79.7 µg·m-3, accounting for 75.9%, 76.4%, and 78.7% of the total regional O3-8h, respectively. The regional background O3-8h estimated by the four methods showed obvious seasonal changes, characterized by summer > spring > fall > winter.

[Regional Difference and Spatial Convergence of Land Use Carbon Emissions in Three Urban Agglomerations of Yangtze River Economic Belt].

It is of great significance to explore the regional differences of land use carbon emission （LUCE） in the Yangtze River Economic Belt and the path of coordinated emission reduction for regional sustainable development. Based on the LUCE estimation method, this study scientifically calculated the LUCE of the three major urban agglomerations of the Yangtze River Economic Belt （Yangtze River Delta, middle reaches of the Yangtze River, and Chengdu-Chongqing urban agglomeration） from 2010 to 2020. Kernel density estimation and the spatial convergence model were used to study the dynamic evolution, regional differences, and convergence characteristics of LUCE. The results showed that： ① The carbon absorption of forest land, water areas, grassland, and unused land were relatively small in terms of carbon emissions from cultivated land and construction land. The carbon emission of construction land increased gradually, whereas the carbon absorption of four carbon sinks fluctuated little during the study period. ② The core density curves of different urban agglomerations showed different distribution patterns, extensibility, and polarization characteristics but generally tended to be balanced. ③ From 2010 to 2020, the LUCE of the Yangtze River Economic Belt as a whole showed the spatio-temporal characteristics of increasing first and then decreasing and high in the east and low in the west. The LUCE of the central cities of the three urban agglomerations were at the highest level steadily, and stable coupling mechanisms had not been established between the economic development level and the ecological environment. ④ The LUCE of the three urban agglomerations in the Yangtze River Economic Belt all had absolute ß convergence and also had conditional ß convergence under the model control variables such as economic development level, urbanization level, industrial structure, population density, and environmental regulation, etc., and the conditional convergence speed was greater than the absolute convergence speed in each region. The convergence speed of the Yangtze River Delta urban agglomeration was the slowest. The above conclusions provide support for the coordinated emission reduction path of the three urban agglomerations in the Yangtze River Economic Belt and are also conducive to actively and steadily promoting the realization of the goals of carbon peak and carbon neutralization.

Connectomic insights into the impact of 1p/19q co-deletion in dominant hemisphere insular glioma patients.

Objectives: This study aimed to elucidate the influences of 1p/19q co-deletion on structural connectivity alterations in patients with dominant hemisphere insular diffuse gliomas. Methods: We incorporated 32 cases of left insular gliomas and 20 healthy controls for this study. Using diffusion MRI, we applied correlational tractography, differential tractography, and graph theoretical analysis to explore the potential connectivity associated with 1p/19q co-deletion. Results: The study revealed that the quantitative anisotropy (QA) of key deep medial fiber tracts, including the anterior thalamic radiation, superior thalamic radiation, fornix, and cingulum, had significant negative associations with 1p/19q co-deletion (FDR = 4.72 × 10-5). These tracts are crucial in maintaining the integrity of brain networks. Differential analysis further supported these findings (FWER-corrected p < 0.05). The 1p/19q non-co-deletion group exhibited significantly higher clustering coefficients (FDR-corrected p < 0.05) and reduced betweenness centrality (FDR-corrected p < 0.05) in regions around the tumor compared to HC group. Graph theoretical analysis indicated that non-co-deletion patients had increased local clustering and decreased betweenness centrality in peritumoral brain regions compared to co-deletion patients and healthy controls (FDR-corrected p < 0.05). Additionally, despite not being significant through correction, patients with 1p/19q co-deletion exhibited lower trends in weighted average clustering coefficient, transitivity, small worldness, and global efficiency, while showing higher tendencies in weighted path length compared to patients without the co-deletion. Conclusion: The findings of this study underline the significant role of 1p/19q co-deletion in altering structural connectivity in insular glioma patients. These alterations in brain networks could have profound implications for the neural functionality in patients with dominant hemisphere insular gliomas.

Changes in the Aggregation Behaviour of Zinc Oxide Nanoparticles Influenced by Perfluorooctanoic Acid, Salts, and Humic Acid in Simulated Waters.

The increasing utilization of zinc oxide nanoparticles (ZnO-NPs) in many consumer products is of concern due to their eventual release into the natural environment and induction of potentially adverse impacts. The behaviour and environmental impacts of ZnO-NPs could be altered through their interactions with environmentally coexisting substances. This study investigated the changes in the behaviour of ZnO-NPs in the presence of coexisting organic pollutants (such as perfluorooctanoic acid [PFOA]), natural organic substances (i.e., humic acid [HA]), and electrolytes (i.e., NaCl and CaCl2) in simulated waters. The size, shape, purity, crystallinity, and surface charge of the ZnO-NPs in simulated water after different interaction intervals (such as 1 day, 1 week, 2 weeks, and 3 weeks) at a controlled pH of 7 were examined using various characterization techniques. The results indicated alterations in the size (such as 162.4 nm, 1 day interaction to >10 µm, 3 weeks interaction) and zeta potential (such as -47.2 mV, 1 day interaction to -0.2 mV, 3 weeks interaction) of the ZnO-NPs alone and when PFOA, electrolytes, and HA were present in the suspension. Different influences on the size and surface charge of the nanoparticles were observed for fixed concentrations (5 mM) of the different electrolytes. The presence of HA-dispersed ZnO-NPs affected the zeta potential. Such dispersal effects were also observed in the presence of both PFOA and salts due to their large aliphatic carbon content and complex structure. Cation bridging effects, hydrophobic interactions, hydrogen bonding, electrostatic interactions, and van der Waals forces could be potential interaction forces responsible for the adsorption of PFOA. The presence of organic pollutants (PFOA) and natural organic substances (HA) can transform the surface characteristics and fate of ZnO-NPs in natural and sea waters.

Integrated Transcriptomic-Metabolomic Analysis Reveals the Effect of Different Light Intensities on Ovarian Development in Chickens.

Light is a key environmental factor regulating reproduction in avians. However, the mechanism of light intensity regulating ovarian development is still unclear. In this study, 5-week-old (5 wk) partridge broiler breeders were randomly divided into a low-light-intensity group (LL group) and a natural-light-intensity group (NL group) (n = 100). In the rearing period (5 wk to 22 wk), the light intensity of the LL group and NL group were 0.41 ± 0.05 lux and 45.39 ± 1.09 lux, and in the laying period (23 wk to 32 wk) they were 23.92 ± 0.06 lux and 66.93 ± 0.76 lux, respectively. Samples were collected on 22 wk and 32 wk. The results showed that the LL group had a later age at first egg and a longer laying period than the NL group. Serum P4 and LH levels in the LL group were higher than in the NL group on 22 wk (p < 0.05). On 32 wk, P4, E2, LH and FSH levels in the LL group were lower than in the NL group (p < 0.05). Ovarian transcriptomics and metabolomics identified 128 differentially expressed genes (DEGs) and 467 differential metabolites (DMs) on 22 wk; 155 DEGs and 531 DMs on 32 wk between two groups. An enrichment analysis of these DEGs and DMs identified key signaling pathways, including steroid hormone biosynthesis, neuroactive ligand-receptor interaction. In these pathways, genes such as CYP21A1, SSTR2, and NPY may regulate the synthesis of metabolites, including tryptamine, triglycerides, and phenylalanine. These genes and metabolites may play a dominant role in the light-intensity regulation of ovarian development and laying performance in broiler breeders.