Aerobic Oxidative Carboxylation of Styrene Over Cobalt Catalysts: Integrated CO2 Capture and Conversion.

The direct synthesis of cyclic carbonates through oxidative carboxylation of alkenes using CO2 and O2 offers a sustainable and carbon-neutral method for CO2 utilization, which is, however, still a largely unexplored field. Here we develop a single-atom catalyst (SAC) Co-N/O-C as the earth-abundant metal catalyst for the oxidative carboxylation of styrene with CO2 and O2. Remarkably, even using the flue gas as an impure CO2 and O2 source, desired cyclic carbonate could be obtained with moderate productivity, which shows the potential for integrated CO2 capture and conversion, leveraging the high CO2 adsorption capacity of Co-N/O-C. In addition, the catalyst can be reused five times without an obvious decline in activity. Detailed characterizations and theoretical calculations elucidate the crucial role of single Co atoms in activating O2 and CO2, as well as controlling selectivity.

PROTAC Prodrug-Integrated Nanosensitizer for Potentiating Radiation Therapy of Cancer.

Radiation therapy (RT) is one of the primary options for clinical cancer therapy, in particular advanced head and neck squamous cell carcinoma (HNSCC). Herein, the crucial role of bromodomain-containing protein 4 (BRD4)-RAD51 associated protein 1 (RAD51AP1) axis in sensitizing RT of HNSCC is revealed. A versatile nanosensitizer (RPB7H) is thus innovatively engineered by integrating a PROteolysis TArgeting Chimeras (PROTAC) prodrug (BPA771) and hafnium dioxide (HfO2) nanoparticles to downregulate BRD4-RAD51AP1 pathway and sensitize HNSCC tumor to RT. Upon intravenous administration, the RPB7H nanoparticles selectively accumulate at the tumor tissue and internalize into tumor cells by recognizing neuropilin-1 overexpressed in the tumor mass. HfO2 nanoparticles enhance RT effectiveness by amplifying X-ray deposition, intensifying DNA damage, and boosting oxidative stress. Meanwhile, BPA771 can be activated by RT-induced H2O2 secretion to degrade BRD4 and inactivate RAD51AP1, thus impeding RT-induced DNA damage repair. This versatile nanosensitizer, combined with X-ray irradiation, effectively regresses HNSCC tumor growth in a mouse model. The findings introduce a PROTAC prodrug-based radiosensitization strategy by targeting the BRD4-RAD51AP1 axis, may offer a promising avenue to augment RT and more effective HNSCC therapy.

Efficient Alkene Hydroformylation by Co-C Symmetry-Breaking Sites.

Alkene hydroformylation is one of the largest industrial reactions on an industrial scale; however, the development of nonnoble heterogeneous catalysts is usually limited by their low activities and stabilities. Herein, we constructed a 1% Co2C/SiO2 catalyst featuring Co-Cvacancy-Co-C symmetry-breaking sites, which generated a polar surface exhibiting a moderate charge density gradient at the localized Co atoms. Comparatively, this catalyst exhibited notable enhancements in the adsorption and activation of the reactants, as well as in the polarity between intermediates. Significantly, the spatial distance between the adsorption sites of intermediates was reduced, thereby effectively decreasing the energy barrier of reaction processes. As the density of the symmetry-breaking sites increased, the turnover number for propene hydroformylation soared to 18 363, exceeding the activity of heterogeneous Co-based catalysts reported thus far by 1 or 2 orders of magnitude, and the catalyst exhibited high stability during the reaction. This study provides a methodology for constructing atomically active sites, which holds great potential for the design and development of highly efficient catalysts.

Effects of multi-plant harvesting on nitrogen removal and recovery in constructed wetlands.

The harvesting of plants is considered an effective method for nutrient recovery in constructed wetlands (CWs). However, excessive plant harvesting can lead to a decrease in plant biomass. It remains unclear what harvesting frequency can optimize plant nutrient uptake and pollutant removal. In this study, CWs planted with Myriophyllum aquaticum were constructed, and three different frequencies of plant harvesting (high: 45 days/time; low: 90 days/time; none: CK) were set to investigate nitrogen removal and its influencing mechanism, as well as the capacity for plant nutrient recovery. The results showed that the average removal efficiencies of ammonia nitrogen (NH4+-N) at 45 days/time, 90 days/time, and CK were 90.3%, 90.8%, and 88.3% respectively, while the corresponding total nitrogen (TN) were 61.2%, 67.4%, and 67.4%. Dissolved oxygen (DO) concentration and water temperature were identified as the main environmental factors affecting nitrogen removal efficiency. Low harvest frequency (90 days/time) increased DO concentration and NH4+-N removal efficiency without impacting TN removal. Additionally, TN recovery from plants under high and low harvest was found to be approximately 9.21-9.32 times higher than that from no harvest conditions. The above studies indicated that a harvest frequency of every 90 days was one appropriate option for M. aquaticum, which not only increased NH4+-N removal efficiencies but also facilitated more efficient nitrogen recovery from the wetland system.

Sono-assembly of ellagic acid into nanostructures significantly enhances aqueous solubility and bioavailability.

INTRODUCTION: Ellagic acid (EA), commonly found in foods, offers significant health benefits in combating chronic diseases. However, its therapeutic potential is hindered by its extremely poor solubility and bioavailability. METHOD: In this study, EA nanoparticles (EA NPs) were produced using a sono-assembly method, without additional agents. RESULTS: EA NPs exhibited stick-like nanoparticle structures with an average size of 147.3 ± 0.73 nm. EA NPs likely adopt a tunnel-type solvate structure, with 4 water participating in disruption of intramolecular hydrogen bonds in EA and establishment of intermolecular hydrogen bonds between EAs. Importantly, EA NPs exhibited remarkable enhancements in water solubility, with 120.7-fold increase in water, and 97.8-fold increase in pH 6.8 buffer. Moreover, ex vivo intestinal permeability studies demonstrated significant improvements (P < 0.5). These findings were further supported by in vivo pharmacokinetic studies, where EA NPs significantly enhanced the relative bioavailability of EA by 4.69 times.

The transcription factor MYB110 regulates plant height, lodging resistance, and grain yield in rice.

The high-yielding Green Revolution varieties of cereal crops are characterized by a semidwarf architecture and lodging resistance. Plant height is tightly regulated by the availability of phosphate (Pi), yet the underlying mechanism remains obscure. Here, we report that rice (Oryza sativa) R2R3-type Myeloblastosis (MYB) transcription factor MYB110 is a Pi-dependent negative regulator of plant height. MYB110 is a direct target of PHOSPHATE STARVATION RESPONSE 2 (OsPHR2) and regulates OsPHR2-mediated inhibition of rice height. Inactivation of MYB110 increased culm diameter and bending resistance, leading to enhanced lodging resistance despite increased plant height. Strikingly, the grain yield of myb110 mutants was elevated under both high- and low-Pi regimes. Two divergent haplotypes based on single nucleotide polymorphisms in the putative promoter of MYB110 corresponded with its transcript levels and plant height in response to Pi availability. Thus, fine-tuning MYB110 expression may be a potent strategy for further increasing the yield of Green Revolution cereal crop varieties.

Mechanisms of total phosphorus removal and reduction of ß-lactam antibiotic resistance genes by exogenous fungal combination activated sludge.

This study utilized Trichoderma and activated sludge to construct combined activated sludge (TAS). The metagenomic approach was employed to examine the shifts in microbial community structure and function of TAS under amoxicillin stress and investigate the mechanism underlying the reduction of ß-lactam antibiotic resistance genes (ß-ARGs). The findings demonstrated that the elevated aundance of glpa, glpd, ugpq, glpq, and glpb were primarily responsible for the reduction in total phosphorus (TP) removal by TAS. The increased abundance of Proteobacteria and Verrucomicrobia led to enhanced expression of ugpb, phnd, and phne, thereby improving the TP removal of TAS. Furthermore, antibiotic inactivation has gradually become the primary antibiotic resistance mechanism in TAS. Specifically, an increase in the abundance of OXA-309 in TAS will decrease the probability of amoxicillin accumulation in TAS. A decrease in ß-ARGs diversity confirmed this. This study presents a novel approach to reducing antibiotic and ARG accumulation in sludge.

Global burden of neck pain in 204 countries from 1990-2019.

Introduction: The estimation of global burden of neck pain is lacking. To estimate the trends and burden of neck pain by sex, age, region, and sociodemographic index (SDI). Material and methods: The incidence and disability-adjusted life years (DALY) data for neck pain were extracted from the Global Burden of Disease 2019 database. The estimated annual percent change (EAPC) and 95% confidence intervals (CIs) were used to assess the trends in age-standardized incidence and DALY rates from 1990 to 2019. Results: From 1990 to 2019, the global age-standardized incidence rate and age-standardized DALY rate indicated downward trends, with EAPCs of -0.06 and -0.09, respectively. The EAPCs of the age-standardized incidence rate and age-standardized DALY rate were negatively correlated with the SDI in 2019, respectively. The age-standardized incidence rates and age-standardized DALY rates in regions with a high SDI indicated a downward trend, including in high-income North America, Australia, and New Zealand. In 2019, the Philippines and high-income North America had the highest age-standardized incidence and age-standardized DALY rates. From 1990 to 2019, the areas which increased most rapidly in the age-standardized incidence rate and age-standardized DALY rate were in tropical Latin America (EAPCs of 0.53 and 0.60, respectively). Brazil had the most rapid increase in the age-standardized incidence rate and age-standardized DALY rate (EAPCs of 0.55 and 0.61, respectively). Conclusions: The age-standardized incidence rate and age-standardized DALY rate of neck pain decreased globally from 1990 to 2019. However, there were significant differences concerning sex, age, and regional distributions. Therefore, targeted prevention interventions and risk factor control measures should be reasonably allocated.

Efficacy and safety of Chinese medicine injections in combination with docetaxel and cisplatin for non-small cell lung cancer: a network meta-analysis.

Background: Non-small cell lung cancer (NSCLC) poses a serious threat to human health. Several clinical studies have reported the benefits of Chinese herbal injections (CHIs) in combination with docetaxel and cisplatin (DP). This multidimensional network meta-analysis aimed to investigate the preferred regimen of CHIs in combination with DP for the treatment of NSCLC. Methods: Multiple databases were searched to identify randomized controlled trials (RCTs) of CHIs for NSCLC from the database inception to 30 April 2023. Studies that met the inclusion criteria and exhibited good methodological quality were included. Data analysis was conducted using Stata 15.0 and R 4.2.1 software. An odds ratio (OR) was used as the effect size, and the surface under the cumulative ranking curve (SCURA) was employed to rank the evaluated treatments. Results: The network meta-analysis included 85 eligible RCTs, encompassing 6,580 patients and 11 CHIs. Astragalus Injection combined with DP was identified as the most effective regimen for improving the response rate (SUCRAs: 90.25%). Brucea Javanica Oil Milk Injection combined with DP proved most effective in ameliorating the quality of life (SUCRAs: 76.89%). Shenfu Injection combined with DP emerged as the most effective for enhancing CD3+ and CD4+ (SUCRAs: 93.75%, 88.50%). Kanglaite Injection combined with DP exhibited the best efficacy in improving CD8+ (SUCRAs: 88.96%). Brucea Javanica Oil Milk Injection combined with DP was the most potent regimen for enhancing CD4+/CD8+ (SUCRAs: 93.13%). Conclusion: CHIs in combination with DP outperformed DP alone in NSCLC patients. Astragalus Injection plus DP, Brucea Javanica Oil Milk Injection plus DP, Shenfu Injection plus DP, Kanglaite Injection plus DP, and Brucea Javanica Oil Milk Injection plus DP were significantly effective. However, further multicenter and well-designed RCTs are required to validate our findings.

Self-Adaptive Nanoregulator to Mitigate Dynamic Immune Evasion of Pancreatic Cancer.

The advance of immunotherapy has shifted the paradigm of cancer management in clinics. Nevertheless, a considerable subset of pancreatic ductal adenocarcinoma (PDAC) patients marginally respond to current immunotherapy due to the occurrence of dynamic immune evasion arising from intrinsic and therapeutic stress. In this investigation, the pivotal role of pancreatic cancer-associated fibroblast (CAF)-induced fibrosis and tumor cell-mediated T-cell exhaustion in driving the dynamic immune evasion is identified. Building upon this discovery, the authors herein engineer a novel peptide-drug conjugate (PDC)-based self-adaptive nanoregulator for mitigating dynamic immune evasion of PDAC. The resulting nanoregulator can perform a two-stage morphology transformation from spherical micelle to nanofiber, and subsequently from nanofiber to spherical nanoparticles. Such kind of nanostructure design can facilitate differentialized delivery of CAF inhibitor in the extracellular matrix for intervening CAF-mediated tumor fibrosis, and indoleamine 2,3-dioxygenase 1 inhibitor to tumor cells for relieving IDO1-kynurenine axis-induced T-cell exhaustion. Antitumor study with the self-adaptive nanoregulator elicited persistent antitumor immunity and remarkable antitumor performance in both Panc02 and KPC tumor models in vivo. Taken together, the PDC-based self-adaptive nanoregulator may provide a novel avenue for enhanced PDAC immunotherapy.

Associations between environmental heavy metals exposure and preserved ratio impaired spirometry in the U.S. adults.

We examined 9556 individuals aged 18 to 79 years who had information on spirometry testing and heavy metals and used multivariable logistic or linear regression to evaluate associations between serum levels of cadmium, lead, and mercury and PRISm and lung function in U.S. adults, which were conducted first in all participants, and then separately in never/former smokers and current smokers. The overall prevalence of PRISm was 7.02%. High levels of serum cadmium were significantly associated with PRISm in all individuals, no matter in never/former smokers (quartile 4 vs 1, the OR = 2.517, 95% CI = 1.376-4.604, p-trend = 0.0077) and current smokers (quartile 4 vs 1, the OR = 2.201, 95% CI = 1.265-3.830, p-trend = 0.0020). Serum lead and mercury were not significantly correlated with PRISm, regardless of smoking status. Serum cadmium was strongly correlated with lower FEV1/FVC, regardless of smoking status. Besides, serum cadmium was also significantly related to lower FVC % predicted in never/former smokers and lower FEV1% predicted in current smokers. Serum lead was strongly correlated with lower FVC % predicted and FEV1/FVC in all individuals and never/former smokers. And serum mercury was significantly associated with decrements in FVC % predicted in all individuals and current smokers. These findings demonstrate that serum cadmium is associated with a higher risk of PRISm and lower lung function, with the most significant effect on FEV1/FVC in particular. Our results also indicate that exposure to lead and mercury negatively affects lung function in never/former smokers and current smokers, respectively.

Improving rice eating and cooking quality by enhancing endogenous expression of a nitrogen-dependent floral regulator.

Improving rice eating and cooking quality (ECQ) is one of the primary tasks in rice production to meet the rising demands of consumers. However, improving grain ECQ without compromising yield faces a great challenge under varied nitrogen (N) supplies. Here, we report the approach to upgrade rice ECQ by native promoter-controlled high expression of a key N-dependent floral and circadian clock regulator Nhd1. The amplification of endogenous Nhd1 abundance alters rice heading date but does not affect the entire length of growth duration, N use efficiency and grain yield under both low and sufficient N conditions. Enhanced expression of Nhd1 reduces amylose content, pasting temperature and protein content while increasing gel consistence in grains. Metabolome and transcriptome analyses revealed that increased expression of Nhd1 mainly regulates the metabolism of carbohydrates and amino acids in the grain filling stage. Moreover, expression level of Nhd1 shows a positive relationship with grain ECQ in some local main cultivars. Thus, intensifying endogenous abundance of Nhd1 is a promising strategy to upgrade grain ECQ in rice production.

Two-stage generative adversarial networks for metal artifact reduction and visualization in ablation therapy of liver tumors.

PURPOSE: The strong metal artifacts produced by the electrode needle cause poor image quality, thus preventing physicians from observing the surgical situation during the puncture process. To address this issue, we propose a metal artifact reduction and visualization framework for CT-guided ablation therapy of liver tumors. METHODS: Our framework contains a metal artifact reduction model and an ablation therapy visualization model. A two-stage generative adversarial network is proposed to reduce the metal artifacts of intraoperative CT images and avoid image blurring. To visualize the puncture process, the axis and tip of the needle are localized, and then the needle is rebuilt in 3D space intraoperatively. RESULTS: Experiments show that our proposed metal artifact reduction method achieves higher SSIM (0.891) and PSNR (26.920) values than the state-of-the-art methods. The accuracy of ablation needle reconstruction is 2.76 mm average in needle tip localization and 1.64° average in needle axis localization. CONCLUSION: We propose a novel metal artifact reduction and an ablation therapy visualization framework for CT-guided ablation therapy of liver cancer. The experiment results indicate that our approach can reduce metal artifacts and improve image quality. Furthermore, our proposed method demonstrates the potential for displaying the relative position of the tumor and the needle intraoperatively.

I know my teammates: the role of Group Member Familiarity in Computer-Supported and face-to-face collaborative learning.

Considering the importance of group member familiarity in collaborative learning in classroom learning environments, this study examined the impact of group member familiarity on CSCL (computer-supported collaborative learning) in a networked setting. Also, the differences between CSCL in the online environments and FtF (face-to-face) collaborative learning were also compared. An analysis using structural equation modeling revealed that group member familiarity increased teamwork satisfaction, which in turn increased student engagement and perceived knowledge construction. A multi-group analysis revealed that while FtF collaborative learning exhibits higher levels of group member familiarity, teamwork satisfaction, student engagement, and perceived knowledge construction, the mediating effect of teamwork satisfaction was more pronounced in online settings. The study findings provided insights for teachers to improve collaborative learning experiences and adapt different teaching strategies.

Automatic vertebral fracture and three-column injury diagnosis with fracture visualization by a multi-scale attention-guided network.

Deep learning methods have the potential to improve the efficiency of diagnosis for vertebral fractures with computed tomography (CT) images. Most existing intelligent vertebral fracture diagnosis methods only provide dichotomized results at a patient level. However, a fine-grained and more nuanced outcome is clinically needed. This study proposed a novel network, a multi-scale attention-guided network (MAGNet), to diagnose vertebral fractures and three-column injuries with fracture visualization at a vertebra level. By imposing attention constraints through a disease attention map (DAM), a fusion of multi-scale spatial attention maps, the MAGNet can get task highly relevant features and localize fractures. A total of 989 vertebrae were studied here. After four-fold cross-validation, the area under the ROC curve (AUC) of our model for vertebral fracture dichotomized diagnosis and three-column injury diagnosis was 0.884 ± 0.015 and 0.920 ± 0.104, respectively. The overall performance of our model outperformed classical classification models, attention models, visual explanation methods, and attention-guided methods based on class activation mapping. Our work can promote the clinical application of deep learning to diagnose vertebral fractures and provide a way to visualize and improve the diagnosis results with attention constraints.

Effect of daily new cases of COVID-19 on public sentiment and concern: Deep learning-based sentiment classification and semantic network analysis.

Aim: This study explored the influence of daily new case videos posted by public health agencies (PHAs) on TikTok in the context of COVID-19 normalization, as well as public sentiment and concerns. Five different stages were used, based on the Crisis and Emergency Risk Communication model, amidst the 2022 Shanghai lockdown. Subject and Methods: After dividing the duration of the 2022 Shanghai lockdown into stages, we crawled all the user comments of videos posted by Healthy China on TikTok with the theme of daily new cases based on these five stages. Third, we constructed the pre-training model, ERNIE, to classify the sentiment of user comments. Finally, we performed semantic network analyses based on the sentiment classification results. Results: First, the high cost of fighting the epidemic during the 2022 Shanghai lockdown was why ordinary people were reluctant to cooperate with the anti-epidemic policy in the pre-crisis stage. Second, Shanghai unilaterally revised the definition of asymptomatic patients led to an escalation of risk levels and control conditions in other regions, ultimately affecting the lives and work of ordinary people in the area during the initial event stage. Third, the public reported specific details that affected their lives due to the long-term resistance to the epidemic in the maintenance stage. Fourth, the public became bored with videos regarding daily new cases in the resolution stage. Finally, the main reason for the negative public sentiment was that the local government did not follow the central government's anti-epidemic policy. Conclusion: Our results suggest that the methodology used in this study is feasible. Furthermore, our findings will help the Chinese government or PHAs improve the possible behaviors that displease the public in the anti-epidemic process.

How does online social interaction promote students' continuous learning intentions?

Learning from online videos using synchronized Danmu comments provides a co-learning experience. To explore the factors influencing learning with or without Danmu videos, an initial set of reasons and impediments was compiled based on a pilot study of 24 Chinese university students with learning experience using Danmu videos. Three hundred such students were surveyed to determine the factors that influence their motivations and hindrances with regard to using Danmu videos. The potential predictors of users' continuance intentions were also examined. The results showed that the frequency of using Danmu videos is related to the continuous learning intention. Seeking information, social presence, and perceived entertainment motivate learners and positively impact their intention to continue learning using Danmu videos. Hindrances such as information pollution, attention failure, and visual obstacle were found to be negatively associated with learners' continuance intention in the long run. Our findings provided constructive suggestions for addressing the issue of dropout rates, and novel ideas for future studies were proposed.

Correction to: Effect of daily new cases of COVID-19 on public sentiment and concern: Deep learning-based sentiment classification and semantic network analysis.

[This corrects the article DOI: 10.1007/s10389-023-01833-4.].

Hierarchical multimodal fusion framework based on noisy label learning and attention mechanism for cancer classification with pathology and genomic features.

Classification of subtype and grade is imperative in the clinical diagnosis and prognosis of cancer. Many deep learning-based studies related to cancer classification are based on pathology and genomics. However, most of them are late fusion-based and require full supervision in pathology image analysis. To address these problems, we present an integrated framework for cancer classification with pathology and genomics data. This framework consists of two major parts, a weakly supervised model for extracting patch features from whole slide images (WSIs), and a hierarchical multimodal fusion model. The weakly supervised model can make full use of WSI labels, and mitigate the effects of label noises by the self-training strategy. The generic multimodal fusion model is capable of capturing deep interaction information through multi-level attention mechanisms and controlling the expressiveness of each modal representation. We validate our approach on glioma and lung cancer datasets from The Cancer Genome Atlas (TCGA). The results demonstrate that the proposed method achieves superior performance compared to state-of-the-art methods, with the competitive AUC of 0.872 and 0.977 on these two datasets respectively. This paper establishes insight on how to build deep networks on multimodal biomedical data and proposes a more general framework for pathology image analysis without pixel-level annotation.