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Natural photosynthesis proceeded by sequential water splitting and CO 2 reduction reactions is an efficient strategy for CO 2 conversion. Here, mimicking photosynthesis to boost CO 2 -to-CO conversion is achieved by using plasmonic Bi as an electron-proton-transfer mediator. Electroreduction of H 2 O with a Bi electrode simultaneously produces O 2 and hydrogen-stored Bi (Bi-H x ). The obtained Bi-H x is subsequently used to generate electron-proton pairs under light irradiation to reduce CO 2 to CO; meanwhile, Bi-H x recovers to Bi, completing the catalytic cycle. This two-step strategy avoids O 2 separation and enables a CO production efficiency of 283.8 μmol g −1 h −1 without sacrificial reagents and cocatalysts, which is 9 times that on pristine Bi in H 2 gas. Theoretical/experimental studies confirm that such excellent activity is attributed to the formed Bi-H x intermediate that improves charge separation and reduces reaction barriers in CO 2 reduction. Using a single catalyst to mimic the two-step photosynthesis for CO 2 conversion remains a challenge. Here, the authors report a simple Bi catalyst that can act as an electron-proton-transfer mediator to spatially and temporally separate H2 O splitting and CO 2 reduction reactions in CO 2 -to-CO conversion process.

In recent years, text sentiment analysis has attracted wide attention, and promoted the rise and development of stance detection research. The purpose of stance detection is to determine the author’s stance (favor or against) towards a specific target or proposition in the text. Pre-trained language models like BERT have been proven to perform well in this task. However, in many reality scenes, they are usually very expensive in computation, because such heavy models are difficult to implement with limited resources. To improve the efficiency while ensuring the performance, we propose a knowledge distillation model BERTtoCNN, which combines the classic distillation loss and similarity-preserving loss in a joint knowledge distillation framework. On the one hand, BERTtoCNN provides an efficient distillation process to train a novel ‘student’ CNN structure from a much larger ‘teacher’ language model BERT. On the other hand, based on the similarity-preserving loss function, BERTtoCNN guides the training of a student network, so that input pairs with similar (dissimilar) activation in the teacher network have similar (dissimilar) activation in the student network. We conduct experiments and test the proposed model on the open Chinese and English stance detection datasets. The experimental results show that our model outperforms the competitive baseline methods obviously.

Previous observational studies have indicated associations between various immune cells and diabetic nephropathy (DN). However, the causality remains unclear. We aimed to further evaluate the causal association between immune cells and DN using bidirectional two-sample Mendelian randomization (MR) analysis. The DN data were retrieved from the IEU OpenGWAS Project database, while the data for 731 immune cells were sourced from GWAS summary statistics by Orru ̀ et al. The investigation into the causal relationship between immune cells and DN employed the inverse variance weighted (IVW), weighted median (WME), and MR-Egger methods. The stability and reliability of the findings underwent evaluation through Cochran's Q test, MR-Egger intercept's -value, MR-PRESSO, and Leave-One-Out (LOO) method. The IVW estimates suggested a positive causal effect of CD25 on IgD-CD38dim B cell, CD25 on naive-mature B cell, CD127 on granulocyte, SSC-A on HLA DR + Natural Killer, HLA DR on plasmacytoid Dendritic Cell, and HLA DR on Dendritic Cell on DN. Conversely, the abundance of Myeloid Dendritic Cell, CD62L- Dendritic Cell %Dendritic Cell, CD86+ myeloid Dendritic Cell %Dendritic Cell, CD14- CD16-, CX3CR1 on CD14- CD16-, and SSC-A on CD4+ T cell had negative causal effects on DN. However, after correcting the value for significant causality results using the FDR method, it was concluded that only Myeloid Dendritic Cells had a causal relationship with DN (FDR-  = 0.041), while the other immune cells showed no significant association with DN, so their relationship was suggestive. The results were stable with no observed horizontal pleiotropy and heterogeneity. Reverse MR analysis indicated no causal relationship between DN and the increased risk of positively identified immune cells. This study provides an initial insight into the genetic perspective of the causal relationship between immune cells and DN. It establishes a crucial theoretical foundation for future endeavors in precision medicine and individualized treatment.

In this paper, a novel ensemble learning model named EWT-EnsemLSTM-SSA, which assembles long short-term memory (LSTM), support vector regression (SVR), and sparrow search algorithm (SSA), is a proposed to deal with long term metro passenger flow volume prediction, which is an essential content of traffic flow prediction problems. Firstly, the empirical wavelet transform (EWT) method is introduced to decompose the original dataset into five wavelet time-sequence data for further prediction. Then, a cluster of LSTMs with diverse hidden layers and neuron counts are employed to explore and exploit the implicit information of the EWT-decomposed signals. Next, the output of LSTMs is aggregated into a nonlinear regression method SVR. Lastly, SSA is utilized to optimize the SVR automatically. The proposed EWT-EnsemLSTM-SSA model is applied in three case studies, using the data collected from the passengers' amount in the Minneapolis, America metro, divided into one hour in one day. Experiment results, which compare the proposed EnsemLSTM-SSA model with five conventional time series forecasting models, show that the proposed model can achieve a better performance than the traditional prediction algorithms.

Introduction: Cordyceps militaris , which has many potential medicinal properties, has rarely been reported to alleviate type 2 diabetes mellitus (T2DM). Methods: The effects of C. militaris extracts (CE) and cordycepin (CCS) on high-fat diet and streptozotocin (STZ) induced T2DM mice were analysed by gut microbiome and metabolomics methods in this study. Results: The results demonstrated that glucose and lipid metabolism parameters, oxidative stress biomarkers and inflammation cytokines were down-regulated in the CCS and CE groups. A comparative analysis of the fecal samples from mice in the model and experimental groups showed that experimental groups resulted in a higher abundance of Firmicutes/Bacteroidetes. Conclusion: This study provides evidence that C. militaris can be used as a food supplement to relieve T2DM, which provides a promising prospect for new functional food in it.

Background To compare standalone oblique lateral interbody fusion (OLIF) vs. OLIF combined with posterior bilateral percutaneous pedicle screw fixation (OLIF combined) for the treatment of lumbar spondylolisthesis. Methods This was a retrospective study of patients who underwent standalone OLIF or combined OLIF between 07/2014 and 08/2017 at two hospitals in China. Direct decompressions were not performed. Visual analog scale (VAS), Oswestry Disability Index (ODI), satisfaction rate, anterior/posterior disc heights (DH), foraminal height (FH), foraminal width (FW), cage subsidence, cage retropulsion, fusion rate, and complications were analyzed. All imaging examinations were read independently by two physicians and the mean measurements were used for analysis. Results A total of 73 patients were included: 32 with standalone OLIF and 41 with combined OLIF. The total complication rate was 25.0% with standalone OLIF and 26.8% with combined OLIF. There were no differences in VAS and ODI scores by 2 years of follow-up, but the scores were better with standalone OLIF at 1 week and 3 months ( P  < 0.05). PDH and FW was smaller in the combined OLIF group compared with the standalone OLIF group before and after surgery (all P  < 0.05). There were significant differences in FH before surgery and at 1 week and 3 months between the two groups (all P  < 0.05), but the difference disappeared by 2 years ( P  = 0.111). Cage subsidence occurred in 7.3% (3/41) and 7.3% (3/41) of the patients at 3 and 24 months, respectively, in the combined OLIF group, compared with 6.3% (2/32) and 15.6% (5/32), respectively, in the standalone OLIF group at the same time points ( P  = 0.287). There was no cage retropulsion in both groups at 2 years. The fusion rate was 85.4%(35/41) in the combined OLIF group and 84.4% (27/32) in the standalone OLIF group at 3 months( P  = 0.669). At 24 months, the fusion rate was 100.0% in the combined OLIF group and 93.8% (30/32) in the standalone OLIF group ( P  = 0.066). Conclusion Standalone OLIF may achieve equivalent clinical and radiological outcomes than OLIF combined with fixation for spondylolisthesis. The rate of complications was similar between the two groups. Patients who are osteoporotic might be better undergoing combined rather than standalone OLIF. The possibilty of proof lies within a future prospective study, preferably an RCT.

This work aimed to automate the current manual inspection process of orthopedic joint reconstruction loaner trays, which contain multiple components securely placed in designated slots, by developing an end-to-end pipeline, including an object detection model followed by a tray layout verification algorithm. We collected video training data from 74 trays comprising 1039 unique components. We trained a single You Only Look Once (YOLOv7) model capable of detecting 1039 classes, where we customized the loss and non-max suppression (NMS) functions. For layout verification, we implemented an in-house algorithm based on a pretrained Local Feature Matching with Transformer (LoFTR) model to verify each component’s presence and correct placement within a tray. We evaluated our end-to-end pipeline on 139 testing inspection images and achieved an overall mean average precision (mAP@0.5) and false-positive rate of 0.94 ± 0.10 and 0.05 ± 0.08, respectively, across 12 test scenarios. Our enhanced YOLOv7-X architecture outperformed the Region-based Convolutional Neural Network (Faster-RCNN-ResNet101) baseline model by 24%. Remarkably, in 7 out of 12 scenarios, we achieved an mAP exceeding 0.99. Our proposed solution substantially reduces the inspection time by 47.3% and is highly scalable, allowing straightforward integration into broad industrial applications.

Doxorubicin entrapped carbon dots (DOX-CDs) were prepared for bioimaging and enhanced intracellular drug delivery. The CDs were synthesized via the hydrothermal method using citrate and urea under 200 °C for 1 h. Then, DOX was successfully conjugated on the CDs via physicochemical interactions. The DOX-CDs exhibited good crystal structure, remarkable aqueous stability, excellent photoluminescence property, and a high quantum yield of 93%. The fluorescent images revealed that the DOX-CDs could be readily taken up by the cancer cells for cell labeling. Furthermore, endo-lysosomal pH-assisted DOX release behavior was observed from DOX-CDs, and the cytotoxicity of DOX-CDs was confirmed by the MTS assay against H0-8910 ovarian cancer cells. In addition, the CDs indicated bright fluorescent signal in the animal imaging test and demonstrated low toxicity after administration for 7 and 21 days. Therefore, the prepared CDs could be a promising imaging probe for biomedical imaging and intracellular drug delivery.

Background Oblique lumbar interbody fusion (OLIF) procedures have the potential to increase the segmental lordosis by inserting lordotic cages, however, the amount of segmental lordosis (SL) changes can vary and is likely influenced by several factors, such as patient characteristics, radiographic parameters, and surgical techniques. The objective of this study was to analyze the impact of related factors on the amount of SL changes in OLIF procedures and to build up predictive model for SL changes. Methods This is a retrospective study involving prospectively enrolled patients. A total of 119 patients with 174 segments undergoing OLIF procedure were included and analyzed. The lordotic cages used in all cases had 6-degree angle. Radiographic parameters including preoperative and postoperative segmental disc angle (SDA, preSDA and postSDA), SDA changes on flexion-extension views (ΔSDA-FE), CageLocation and CageInclination were measured by two observers. Interobserver reliability of measurements were ensured by analysis of interclass correlation coefficient (ICC > 0.75). Pearson correlation coefficient analysis and multivariate linear regression were employed to identify factors related to SDA changes and to build up predictive model for SDA changes. Results The average change of segmental disc angle (ΔSDA, postSDA-preSDA) was 3.9° ± 4.8° (95% confidence interval [CI]: 3.1°-4.6°) with preSDA 5.3° ± 5.0°. ΔSDA was 10.8° ± 3.2° with negative preSDA (kyphotic), 5.0° ± 3.7° with preSDA ranging from 0° to 6°, and 1.0° ± 4.1° with preSDA> 6°. Correlation analysis revealed a significant negative correlation between ΔSDA and preSDA ( r  = − 0.713, P  < 0.001), CageLocation ( r  = − 0.183, P  = 0.016) and ΔSDA-FE ( r  = − 0.153, P  = 0.044). In the multivariate linear regression, preSDA and CageLocation were included in the predictive model, resulting in minimal adjusted R 2 change (0.017) by including CageLocation. Therefore, the recommended predictive model was ΔSDA = 7.9–0.8 × preSDA with acceptable fit. (adjusted R 2  = 0.508, n  = 174, P  < 0.001). Conclusions The restoration of segmental lordosis through OLIF largely depends on the preoperative segmental lordosis. The predictive model, which utilized preoperative segmental lordosis, facilitates preoperative planning for corrective surgery using the OLIF procedure.

The sequential deposition method assists the vertical phase distribution in the photoactive layer of organic solar cells, enhancing power conversion efficiencies. With this film coating approach, the morphology of both layers can be fine‐tuned with high boiling solvent additives, as frequently applied in one‐step casting films. However, introducing liquid additives can compromise the morphological stability of the devices due to the solvent residuals. Herein, 1,3,5‐tribromobenzene (TBB) with high volatility and low cost, is used as a solid additive in the acceptor solution and combined thermal annealing to regulate the vertical phase in organic solar cells composed of D18‐Cl/L8‐BO. Compared to the control cells, the devices treated with TBB and those that underwent additional thermal processing exhibit increased exciton generation rate, charge carrier mobility, charge carrier lifetime, and reduced bimolecular charge recombination. As a result, the TBB‐treated organic solar cells achieve a champion power conversion efficiency of 18.5% (18.1% averaged), one of the highest efficiencies in binary organic solar cells with open circuit voltage exceeding 900 mV. This study ascribes the advanced device performance to the gradient‐distributed donor‐acceptor concentrations in the vertical direction. The findings provide guidelines for optimizing the morphology of the sequentially deposited top layer to achieve high‐performance organic solar cells.