Remote sensing ecological index (RSEI) affects microbial community diversity in ecosystems of different qualities.

Soil microorganisms are key to ecological environment stability, but climate change and human activities exacerbate ecological environment changes. Therefore, assessment of ecological environment quality impacts on microbial diversity is needed. The Tarim River is the largest inland river in China and plays a crucial role in supporting regional biodiversity, maintaining ecological balance, and preventing desertification. In this study, we used the Remote Sensing-based Ecological Index (RSEI) to assess the ecological quality of habitats in the Tarim River Basin and explore the effects of habitat quality (extreme, semi-extreme, and general) on the structural diversity of microbial (bacterial and fungal) communities, biogeographic patterns, co-occurrence networks, and community assembly processes. Study results show that soil physicochemical characteristics varied significantly with habitat quality; highly resilient microorganisms are more abundant in habitats with low ecological quality. RSEI affects changes in microbial communities, and the positive correlation ratio of the network is inversely proportional to RSEI. The interspecific relationships of microbial communities in the Tarim River Basin are dominated by positive correlations, and community assembly is strongly influenced by stochastic processes. RSEI directly affects soil microbial diversity, with its contribution to both bacterial and fungal diversity being 0.27. Total nitrogen (TN) also directly affects microbial diversity, with effects of 0.11 on bacteria and 0.07 on fungi, respectively. This study provides scientific evidence and technical support for understanding microbial diversity in environments and for the development of regional sustainable development policies.

An automated commissioning method based on virtual source models: Customizing Monte Carlo dose verification models for individual accelerators.

BACKGROUND: In pursuit of precise dose calculation and verification, the importance of beam modelling cannot be overstated, as it ensures an accurate distribution of particles incident upon the human body. The virtual source model, as one of the beam modelling methods, offers the advantage of not requiring detailed accelerator information. Although various virtual source models exist, manual adjustment to these models demands a substantial investment of time and computational resources. There has long been a desire to develop an efficient and automated approach for model commissioning. PURPOSE: To develop an automatic commissioning method for the virtual source model to customize the accelerator model for independent Monte Carlo dose verification. METHODS: Initially, the accelerator model is established using the virtual source model and self-developed Jaw and MLC models. Then, a fully automated iteration process is employed to adjust the parameters of the virtual source model. Three types of objective functions are designed to represent differences from water tank measurements. Each objective function is paired with a specific parameter for adjustment, and their effectiveness is demonstrated through physical evidence. In each iteration, parameters with the highest objective function percentage are chosen for adjustment, and step length is determined based on current objective function values. Iteration is terminated when changes in any direction from the optimal solution no longer produce an improvement. Dose verification model for nine accelerators has been accomplished using this method. Additionally, under the same initial conditions, verification models for Versa HD accelerator (FF and FFF modes) are established using this method, Nelder-Mead Simplex optimization method, and the Bayesian optimization method to compare the efficiency and quality of these three iterative approaches. RESULTS: Iterations for all nine accelerators are completed within 30 iterations. The relative dose differences in dose fall-off region compared to water tank measurements are all less than 2%, and the average gamma passing rates (3%/2 mm) for ArcCHECK measurements in QA plans are all higher than 97%. For Versa HD accelerator in FFF and FF modes, the proposed method achieves an average relative dose difference below 1% within 11 and 13 iterations, respectively. In contrast, the Simplex optimization reached 1% within 78 iterations in FFF mode. Furthermore, the Simplex optimization in FF mode and Bayesian optimization in both modes failed to achieve a 1% difference within 100 iterations. CONCLUSIONS: The proposed iterative method achieves fast and automated commissioning of dose verification models, contributing to accurate and reliable clinical dose verification.

Rational design of Ag-doped MnFe2O4/HNTs for peroxidase-mimicking activity and colorimetric sensing of uric acid in human serum.

Mimicking enzyme have significantly advanced sensing assays by replicating native enzyme functions, yet achieving both high catalytic activity and easy recyclability remains a challenge. In this study, Ag-doped MnFe2O4/halloysite nanotubes (HNTs) were rationally designed as a novel nanozyme by depositing in-situ Ag and MnFe2O4 nanoparticles onto HNTs. The resulting nanocomposite exhibited excellent peroxidase-like activity along with magnetic properties. Leveraging these features, a highly efficient and sensitive colorimetric system for detecting uric acid (UA) was developed. The Ag-doped MnFe2O4/HNTs catalyzed the oxidation of 3,3',5,5'-tetramethylbenzidine in the presence of H2O2, causing a color change from colorless to blue. The system showed a linear absorbance response to UA concentrations ranging from 1 to 20 µM, with a detection limit of 59 nM. Mechanistic studies revealed that reactive oxygen species intermediates (1O2) were generated through the decomposition of H2O2, leading to peroxidase-like activity in the Ag-doped MnFe2O4/HNTs. The assay was successfully applied to detect UA in human serum with recoveries over 99.68 %. This study indicates the successful application of Ag-doped MnFe2O4/HNTs for colorimetric UA detection in human serum. This research introduces a novel approach for designing recyclable, high-performance mimicking enzyme and establishes an effective colorimetric sensing platform for UA detection in human serum.

Separation and purification of bovine nasal cartilage-derived chondroitin sulfate and evaluation of its binding to bovine serum albumin.

This study employs an optimized and environmentally friendly method to extract and purify chondroitin sulfate (CS) from bovine nasal cartilage using enzymatic hydrolysis, ethanol precipitation, and DEAE Sepharose Fast Flow column chromatography. The extracted CS, representing 44.67 % ± 0.0016 of the cartilage, has a molecular weight of 7.62 kDa. Characterization through UV, FT-IR, NMR spectroscopy, and 2-aminoacridone derivatization HPLC revealed a high content of sulfated disaccharides, particularly ΔDi4S (73.59 %) and ΔDi6S (20.61 %). Interaction studies with bovine serum albumin (BSA) using fluorescence spectroscopy and molecular docking confirmed a high-affinity, static quenching interaction with a single binding site, primarily mediated by van der Waals forces and hydrogen bonding. The interaction did not significantly alter the polarity or hydrophobicity of BSA aromatic amino acids. These findings provide a strong foundation for exploring the application of CS in tissue engineering and drug delivery systems, leveraging its unique interaction with BSA for targeted delivery and enhanced efficacy.

Recent advances in the treatment of gout with NLRP3 inflammasome inhibitors.

Gout is an autoinflammatory disorder characterized by the accumulation of monosodium urate crystals in joints and other tissues, representing the predominant type of inflammatory arthritis with a notable prevalence and propensity for severe outcomes. The NLRP3 inflammasome, a member of the pyrin domain-containing NOD-like receptor family, exerts a substantial impact on both innate and adaptive immune responses and serves as a pivotal factor in the pathogenesis of gout. In recent years, there has been significant academic and industrial interest in the development of NLRP3-targeted small molecule inhibitors as a promising therapeutic approach for gout. To assess the advancements in NLRP3 inflammasome inhibitors for gout treatment, this review offers a comprehensive analysis and evaluation of current clinical candidates and other inhibitors targeting NLRP3 inflammasome from a chemical structure standpoint, with the goal of identifying more efficacious options for clinical management of gout.

Association between cardiovascular health and all-cause mortality risk in patients with osteoarthritis.

BACKGROUND: This study was to explore the relationship between cardiovascular health (CVH) and the risk of all-cause mortality in patients with osteoarthritis (OA). METHODS: This cohort study retrieved the data of 3642 patients with OA aged ≥ 20 years from the 2007-2018 National Health and Nutrition Examination Survey (NHANES). CVH was evaluated based on Life's Essential 8 (LE8) includes diet, physical activity, nicotine exposure, sleep health, body mass index, blood lipids, blood glucose, and blood pressure. The outcome of all-cause mortality was assessed using the death certificate records of participants from the National Death Index. Variables that might affect all-cause mortality were used as covariates. The weighted univariate COX proportional hazards model was used to explore the association between each covariate and all-cause mortality. The weighted univariate and multivariate COX proportional hazards models were used to explore the association between different CVH levels and all-cause mortality. A restricted cubic spline (RCS) curve was plotted to show the association between different CVH levels and all-cause mortality in OA patients. Hazard ratio (HR) and 95% confidence interval (CI) were calculated. RESULTS: Findings show that people with moderate CVH (HR = 0.67, 95% CI = 0.45-0.98) and high CVH (HR = 0.47, 95% CI = 0.26-0.87) were associated with reduced risk of all-cause mortality in patients with OA. The HR of all-cause mortality in patients with OA decreased by 0.12 as per 10 points increase of LE8 score (HR = 0.81, 95% CI = 0.73-0.90). The RCS curve revealed that the HR of all-cause mortality decreased with the increase in LE8 score. The survival probability of patients in the high CVH group was higher than the moderate CVH group and low CVH group (p = 0.002). CONCLUSION: Moderate-to-high CVH is associated with a decreased risk of all-cause mortality in patients with OA. These findings might provide a reference for the formulation of prognosis improvement strategies for the management of patients with OA.

Characteristics and Genesis of Carbonate Weathering Crust Reservoirs: A Case from the Ma5Member of Ordovician in Gaoqiao Area, Ordos Basin, China.

The hydrocarbon reserves in carbonate rocks account for about half of the global hydrocarbon reserves and are an important reservoir type. The Ordovician Majiagou Formation in the central Ordos Basin is a representative weathering crust reservoir. The Caledonian movement uplifted the stratum as a whole, and subsequently, 120 million years of exposed weathering, denudation, and leaching created this unique karst paleomorphology. Dolomite reservoirs have developed dissolved pores and microfractures, which are the best reserved spaces for natural gas and good hydrocarbon migration channels. This paper takes the Ma5Member (hereinafter referred to as Ma51+2) carbonate reservoir in Gaoqiao Gas Field as the research target, based on the core, thin section, cathodoluminescence, logging data, etc., and systematically study the effect of karstification on the reservoir and the genesis of the dolomite reservoir. The results show that the depositional period of the Ordovician Majiagou strata is a regression cycle and the depositional environment is a limited evaporative tidal flat. The reservoir lithology of Ma51+2 is mainly gypsiferous dolomite and micrite dolomite. The reservoir space types consist of intergranular pores, gypsum mold pore, intragranular dissolution pores, intercrystalline pores, and microfractures. The porosity has values from 0.3 to 11.2% (mostly less than 5.0%) with an average of 3.3%, and the permeability ranges from 0.003 to 13.2 mD (mostly less than 1 mD) with an average of 0.36 mD. Karstification is divided into three periods, including syngenetic karst, eogenetic karst, and burial karst. The sedimentary microfacies determine the material basis of the reservoir, and multistage karstification finally modifies the physical properties. By deeply exploring the formation mechanism and influencing factors of the carbonate reservoir in the Ordovician Majiagou Formation, it provides an important theoretical basis and practical guidance for oil and gas exploration and development. At the same time, it also has important reference value for understanding and predicting the development law and distribution characteristics of carbonate reservoirs under similar geological background.

Adaptive assessment based on fractional CBCT images for cervical cancer.

PURPOSE: Anatomical and other changes during radiotherapy will cause inaccuracy of dose distributions, therefore the expectation for online adaptive radiation therapy (ART) is high in effectively reducing uncertainties due to intra-variation. However, ART requires extensive time and effort. This study investigated an adaptive assessment workflow based on fractional cone-beam computed tomography (CBCT) images. METHODS: Image registration, synthetic CT (sCT) generation, auto-segmentation, and dose calculation were implemented and integrated into ArcherQA Adaptive Check. The rigid registration was based on ITK open source. The deformable image registration (DIR) method was based on a 3D multistage registration network, and the sCT generation method was performed based on a 2D cycle-consistent adversarial network (CycleGAN). The auto-segmentation of organs at risk (OARs) on sCT images was finished by a deep learning-based auto-segmentation software, DeepViewer. The contours of targets were obtained by the structure-guided registration. Finally, the dose calculation was based on a GPU-based Monte Carlo (MC) dose code, ArcherQA. RESULTS: The dice similarity coefficient (DSCs) were over 0.86 for target volumes and over 0.79 for OARs. The gamma pass rate of ArcherQA versus Eclipse treatment planning system was more than 99% at the 2%/2 mm criterion with a low-dose threshold of 10%. The time for the whole process was less than 3 min. The dosimetric results of ArcherQA Adaptive Check were consistent with the Ethos scheduled plan, which can effectively identify the fractions that need the implementation of the Ethos adaptive plan. CONCLUSION: This study integrated AI-based technologies and GPU-based MC technology to evaluate the dose distributions using fractional CBCT images, demonstrating remarkably high efficiency and precision to support future ART processes.

Impact of Pulmonary Ventilation Dysfunction on Prognosis of Patients with Coronary Artery Disease: A Single-Center, Observational Study.

Background: Patients with coronary artery disease (CAD) often experience pulmonary ventilation dysfunction following their initial event. However, there is insufficient research exploring the relationship between this dysfunction and CAD prognosis. Methods: To address this gap, a retrospective observational study was conducted involving 3800 CAD patients without prior pulmonary ventilation disease who underwent cardiopulmonary exercise testing (CPET) during hospitalization between November 2015 and September 2021. The primary endpoint was a composite of major adverse cardiovascular events (MACE), such as death, myocardial infarction (MI), repeat revascularization, and stroke. Propensity score matching (PSM) was used to minimize selection bias between the two groups, with a subgroup analysis stratified by smoking status. Results: The results showed that patients were divided into normal (n = 2159) and abnormal (n = 1641) groups based on their pulmonary ventilation function detected by CPET, with 1469 smokers and 2331 non-smokers. The median follow-up duration was 1237 (25-75% interquartile range 695-1596) days. The primary endpoint occurred in 390 patients (10.26%). 1472 patients in each of the two groups were enrolled in the current analysis after PSM, respectively. However, pulmonary function was not associated with MACE before (hazard ratio (HR) 1.20, 95% confidence interval (95% CI) 0.99-1.47; Log-rank p = 0.069) or after PSM (HR 1.07, 95% CI 0.86-1.34; Log-rank p = 0.545) among the entire population. Nonetheless, pulmonary ventilation dysfunction was significantly associated with an increased risk of MACE in smoking patients (HR 1.65, 95% CI 1.25-2.18; p < 0.001) but not in non-smoking patients (HR 0.81, 95% CI 0.60-1.09; p = 0.159). In addition, there was a significant interaction between current smoking status and pulmonary ventilation dysfunction on MACE (p for interaction < 0.001). Conclusions: Pulmonary ventilation dysfunction identified through CPET was independently associated with long-term poor prognosis in smoking patients with CAD but not in the overall population.

Development and optimization of the Glabridin-loaded dissolving microneedle for enhanced treatment of keloid.

Glabridin (Gla) has been reported to have significant effects in scar treatment, and however, the water insolubility of Gla leads to its poor transdermal absorption ability, which affects its bioactivities. Therefore, we attempted to prepare the Gla dissolving microneedles (Gla-MN) to improve the absorbtion of Gla. After investigation of the 3 factors including the needle tip matrix concentration, the prescription concentration of backing material, and the dissolution method of Gla, we finally determined the process parameters of 10% hyaluronic acid (HA) as the needle tip and 5% polyvinyl alcohol (PVA) as the backing, according to which the Gla-MN was prepared with the good characteristics of high hardness, complete appearance and good in vitro dissolution ability. We then loaded Gla onto the microneedles and measured that the average drug loading of Gla-MN was 2.26 ± 0.11 µg/mg and the cumulative transdermal release of Gla-MN was up to 76.9% after 24 h. In addition, Gla-MN had good skin penetration properties, with Gla-MN penetrating at least 4 to 5 layers of parafilm. And the skin basically could return to normal after 4 h of piercing. Importantly, our results showed that Gla-MN had higher transdermal delivery and therapeutic effects against keloid than that of Gla at the same dosage.

Clinical application of a GPU-accelerated monte carlo dose verification for cyberknife M6 with Iris collimator.

PURPOSE: To apply an independent GPU-accelerated Monte Carlo (MC) dose verification for CyberKnife M6 with Iris collimator and evaluate the dose calculation accuracy of RayTracing (TPS-RT) algorithm and Monte Carlo (TPS-MC) algorithm in the Precision treatment planning system (TPS). METHODS: GPU-accelerated MC algorithm (ArcherQA-CK) was integrated into a commercial dose verification system, ArcherQA, to implement the patient-specific quality assurance in the CyberKnife M6 system. 30 clinical cases (10 cases in head, and 10 cases in chest, and 10 cases in abdomen) were collected in this study. For each case, three different dose calculation methods (TPS-MC, TPS-RT and ArcherQA-CK) were implemented based on the same treatment plan and compared with each other. For evaluation, the 3D global gamma analysis and dose parameters of the target volume and organs at risk (OARs) were analyzed comparatively. RESULTS: For gamma pass rates at the criterion of 2%/2 mm, the results were over 98.0% for TPS-MC vs.TPS-RT, TPS-MC vs. ArcherQA-CK and TPS-RT vs. ArcherQA-CK in head cases, 84.9% for TPS-MC vs.TPS-RT, 98.0% for TPS-MC vs. ArcherQA-CK and 83.3% for TPS-RT vs. ArcherQA-CK in chest cases, 98.2% for TPS-MC vs.TPS-RT, 99.4% for TPS-MC vs. ArcherQA-CK and 94.5% for TPS-RT vs. ArcherQA-CK in abdomen cases. For dose parameters of planning target volume (PTV) in chest cases, the deviations of TPS-RT vs. TPS-MC and ArcherQA-CK vs. TPS-MC had significant difference (P < 0.01), and the deviations of TPS-RT vs. TPS-MC and TPS-RT vs. ArcherQA-CK were similar (P > 0.05). ArcherQA-CK had less calculation time compared with TPS-MC (1.66 min vs. 65.11 min). CONCLUSIONS: Our proposed MC dose engine (ArcherQA-CK) has a high degree of consistency with the Precision TPS-MC algorithm, which can quickly identify the calculation errors of TPS-RT algorithm for some chest cases. ArcherQA-CK can provide accurate patient-specific quality assurance in clinical practice.

The association between triglyceride glucose-body mass index and all-cause and cardiovascular mortality in diabetes patients: a retrospective study from NHANES database.

The triglyceride glucose body mass index (TyG-BMI) is a potential indicator for insulin resistance, but its association with mortality in diabetic patients is unclear. This study investigates the relationship between TyG-BMI and all-cause and cardiovascular mortality in diabetics. The study included 3109 diabetic patients from the National Health and Nutrition Examination Survey (2001-2018). Mortality data were obtained from National Death Index records until 31 December 2019. Multivariate Cox models analyzed the association between TyG-BMI and mortality. Non-linear correlations were assessed using restricted cubic splines, and a two-piecewise Cox model evaluated the relationship on both sides of the inflection point. Over a median 7.25-year follow-up, 795 total and 238 cardiovascular deaths occurred. A U-shaped link was found between initial TyG-BMI and mortality in diabetic patients. Low TyG-BMI (< 279.67 for all-cause, < 270.19 for CVD) reduced death risks (all-cause: HR 0.77, 95% CI 0.69-0.86; CVD: HR 0.64, 95% CI 0.48-0.86). High TyG-BMI (> 279.67 for all-cause, > 270.19 for CVD) increased these risks (all-cause: HR 1.26, 95% CI 1.10-1.44; CVD: HR 1.33, 95% CI 1.06-1.68). In the NHANES study population, a U-shaped association was observed between the baseline TyG-BMI index and all-cause mortality or CVD in diabetic patients.

Development of Peptide Paratope Mimics Derived from the Anti-ROR1 Antibody and Long-Acting Peptide-Drug Conjugates for Targeted Cancer Therapy.

Antibody-based targeted therapy in cancer faces a challenge due to uneven antibody distribution in solid tumors, hindering effective drug delivery. We addressed this by developing peptide mimetics with nanomolar-range affinity for Receptor Tyrosine Kinase-Like Orphan Receptor 1 (ROR1) using computational methods. These peptides showed both specific targeting and deep penetration in vitro and in vivo. Additionally, we created peptide-drug conjugates (PDCs) by linking targeting peptides to toxin drugs via various linkers and enhancing their in vivo half-life with fatty side chains for albumin binding. The antitumor candidate II-3 displayed exceptional affinity (KD = 1.72 × 10-9 M), internalization efficiency, anticancer potency (IC50 = 0.015 ± 0.002 µM), and pharmacokinetics (t1/2 = 2.6 h), showcasing a rational approach for designing PDCs with favorable tissue distribution and strong tumor penetration.

Dual effects on vegetation from urban expansion in the drylands of northern China: A multiscale investigation using the vegetation disturbance index.

Drylands contribute roughly 40 % of the global net primary productivity and are essential for achieving sustainable development. Investigating the effects on vegetation from urban expansion in drylands within the context of rapid urbanization could help enhance the sustainability of dryland cities. With the use of the drylands of northern China (DNC) as an example, we applied the vegetation disturbance index to investigate the negative and positive effects on vegetation from urban expansion in drylands. The results revealed that the DNC experienced massive and rapid urban expansion from 2000 to 2020. Urban land in the entire DNC increased by 19,646 km2 from 8141 to 27,787 km2, with an annual growth rate of 6.3 %. Urban expansion in the DNC imposed both negative and positive effects on regional vegetation. The area with negative effects reached 7736 km2 and was mainly concentrated in the dry subhumid zones. The area with positive effects amounted to 5011 km2 and was comparable among the dry subhumid, semiarid, and arid zones. Land use/cover change induced by population growth significantly contributed to these negative effects, while the positive effects were largely caused by economic growth. Therefore, it is recommended to strike a balance between urban growth and vegetation conservation to mitigate the adverse effects on vegetation from urban expansion in drylands. Simultaneously, it is imperative to expand urban green spaces and build sustainable and livable ecological cities to facilitate sustainable urban development.

Effects of Leukocyte-rich platelet-rich plasma and Leukocyte-poor platelet-rich plasma on cartilage in a rabbit osteoarthritis model.

Osteoarthritis is a prevalent chronic disease. One of its primary pathological processes involves the degeneration of articular cartilage. Platelet-rich plasma (PRP) contains cytokines and growth factors that can stimulate the repair and regeneration of articular cartilage tissues. PRP may also slow the progression of osteoarthritis. The purpose of this experiment is to compare the efficacy of Leukocyte poor (LP) - PRP and Leukocyte rich (LR) - PRP in treating rabbit osteoarthritis and to investigate their mechanisms of action. Analyzing the impact of leukocytes on PRP therapeutic effectiveness will provide a valuable clinical reference for the choice of which PRP is better for the treatment of osteoarthritis. A rabbit osteoarthritis model was established by injecting papain into the knee joint cavity, and LP-PRP and LR-PRP were prepared through different centrifugation methods for injection into the knee joint cavity. Eight weeks after injection, rabbit knee cartilage specimens were observed for gross changes, HE staining, senna O-solid green staining, and immunohistochemistry of type II collagen and were quantitatively compared using Pelletier's score, Mankin's pathology score, and ImageJ image processing software. Injection of papain into the knee joint cavity successfully established a rabbit model of osteoarthritis. All three evaluation indexes differed significantly from those of the blank group (P<0.05). LP-PRP and LR-PRP exhibited therapeutic effects when compared with the model group. The two PRP groups had similar gross tissue appearance and pathology (P>0.05). The LR-PRP group had higher collagen type-II expression (P < 0.05) than the LP-PRP group. Both LP-PRP and LR-PRP proved therapeutic for the rabbit papain osteoarthritis model. The difference in leukocyte content between the two groups did not yield different cartilage morphology or other factors by 8 weeks posttreatment. LR-PRP displayed the ability to release more factors relevant to the metabolism of type II collagen than LP-PRP, enabling the preservation of into cartilage collagen content of type II collagen and delaying osteoarthritis progression.

BCL6 attenuates hyperoxia-induced lung injury by inhibiting NLRP3-mediated inflammation in fetal mouse.

BACKGROUND: The transcriptional repressor B-cell lymphoma 6 (BCL6) has been reported to inhibit inflammation. So far, experimental evidence for the role of BCL6 in bronchopulmonary dysplasia (BPD) is lacking. Our study investigated the roles of BCL6 in the progression of BPD and its downstream mechanisms. METHODS: Hyperoxia or lipopolysaccharide (LPS) was used to mimic the BPD mouse model. To investigate the effects of BCL6 on BPD, recombination adeno-associated virus serotype 9 expressing BCL6 (rAAV9-BCL6) and BCL6 inhibitor FX1 were administered in mice. The pulmonary pathological changes, inflammatory chemokines and NLRP3-related protein were observed. Meanwhile, BCL6 overexpression plasmid was used in human pulmonary microvascular endothelial cells (HPMECs). Cell proliferation, apoptosis, and NLRP3-related protein were detected. RESULTS: Either hyperoxia or LPS suppressed pulmonary BCL6 mRNA expression. rAAV9-BCL6 administration significantly inhibited hyperoxia-induced NLRP3 upregulation and inflammation, attenuated alveolar simplification and dysregulated angiogenesis in BPD mice, which were characterized by decreased mean linear intercept, increased radical alveolar count and alveoli numbers, and the upregulated CD31 expression. Meanwhile, BCL6 overexpression promoted proliferation and angiogenesis, inhibited apoptosis and inflammation in hyperoxia-stimulated HPMECs. Moreover, administration of BCL6 inhibitor FX1 arrested growth and development. FX1-treated BPD mice exhibited exacerbation of alveolar pathological changes and pulmonary vessel permeability, with upregulated mRNA levels of pro-inflammatory cytokines and pro-fibrogenic factors. Furthermore, both rAAV9-BCL6 and FX1 administration exerted a long-lasting effect on hyperoxia-induced lung injury (≥4 wk). CONCLUSIONS: BCL6 inhibits NLRP3-mediated inflammation, attenuates alveolar simplification and dysregulated pulmonary vessel development in hyperoxia-induced BPD mice. Hence, BCL6 may be a target in treating BPD and neonatal diseases.

The long rod-shaped Sr2 MgSi2 O7 :Eu2+ ,Dy3+ with ultrahigh afterglow performance.

The afterglow properties of long afterglow luminescent materials are greatly affected by their defects, which are distributed on the grain surface. Increasing the exposed surface area is an important method to improve the afterglow performance. In this research, long rod-shaped long afterglow materials Sr2 MgSi2 O7 :Eu2+ ,Dy3+ were prepared using the hydrothermal-coprecipitation method. When the reaction time reached 96 h, the length of the afterglow materials could grow to 2 mm, and the sintering temperature was just 1150°C. The emission spectra of all obtained samples upon excitation at 397 nm had a maximum of 465 nm, which belonged to the representative transition of Eu2+ . The initial brightness was 1.35 cd/m2 . The afterglow time could reach 19 h, giving a good afterglow performance. The research on this kind of material has essential significance in the exploration of luminescence mechanisms and their applications.

Expressway traffic flow prediction based on MF-TAN and STSA.

Highly accurate traffic flow prediction is essential for effectively managing traffic congestion, providing real-time travel advice, and reducing travel costs. However, traditional traffic flow prediction models often fail to fully consider the correlation and periodicity among traffic state data and rely on static network topology graphs. To solve this problem, this paper proposes a expressway traffic flow prediction model based on multi-feature spatial-temporal adaptive periodic fused graph convolutional network (MFSTAPFGCN). First, we make fine preprocessing of the raw data to construct a complete and accurate dataset. Second, by deeply investigating the correlation properties among section speed, traffic flow, and section saturation rate, we incorporate these features into a multi-feature temporal attention mechanism in order to dynamically model the correlation of traffic flow in different time periods. Next, we adopt a spatial-temporal adaptive fusion graph convolutional network to capture the daily cycle similarity and potential spatial-temporal dependence of traffic flow data. Finally, the superiority of the proposed MFSTAPFGCN model over the traditional baseline model is verified through comparative experiments on real Electronic Toll Collection (ETC) gantry transaction data, and the effectiveness of each module is demonstrated through ablation experiments.