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Abstract Background Immune checkpoint blockade (ICB) has been improving the patient outcome in multiple cancer types. However, not all patients respond to ICB. Biomarkers are needed for selecting appropriate patients to receive ICB. CD74 is an important chaperone that regulates antigen presentation for immune response. However, the relationship between CD74 expression and ICB response remains elusive. Methods The unified normalized pan-cancer dataset was downloaded from the UCSC database. Wilcoxon Rank Sum Rank Tests were used to analyze the expression differences between normal and tumor samples in each tumor type. Then, the prognostic value of CD74 was determined using univariable Cox proportional hazards regression analysis. The STRING database was utilized to construct the protein-protein interaction (PPI) network of CD74 and the signal pathways were analyzed as well. The correlation of CD74 expression with immune cells and immune regulating genes was investigated in the TIMER database. The TIDE framework was utilized to evaluate the relationship between CD74 expression and the response to immunotherapy. Moreover, the localization of CD74 in the tumor immune microenvironment was verified using multiplex immunohistochemistry. Clinically annotated samples from 38 patients with esophageal cancer treated with neoadjuvant chemotherapy combined with ICB were analyzed for CD74 expression using immunohistochemistry. Results In this study, we investigated the prognostic and predictive value of CD74 in different types of cancer. Compared with normal tissue, the expression of CD74 was higher in tumor tissue in various cancers. High expression of CD74 was associated with improved patient prognosis in the majority of cancers. CD74 and its interacting proteins were mainly enriched in the immune-related pathways. The expression of CD74 was significantly positively correlated with B cells, CD4 T-cells, CD8 T-cells, neutrophils, macrophages and dendritic cells. TIDE analysis showed that tumors with high CD74 expression may have better responses to immunotherapy and improved patient survival. In patients with esophageal cancer who had received ICB, higher intratumoral CD74 expression was associated with improved response to ICB. Conclusions The findings of this study suggest that the high expression of CD74 may be a potential predictive biomarker of response to ICB.

Abstract Background Currently, there are no optimal biomarkers available for distinguishing patients who will respond to immune checkpoint inhibitors (ICIs) therapies. Consequently, the exploration of novel biomarkers that can predict responsiveness to ICIs is crucial in the field of immunotherapy. Methods We estimated the proportions of 22 immune cell components in 10 cancer types (6,128 tumors) using the CIBERSORT algorithm, and further classified patients based on their tumor immune cell proportions in a pan-cancer setting using k-means clustering. Differentially expressed immune genes between the patient subgroups were identified, and potential predictive biomarkers for ICIs were explored. Finally, the predictive value of the identified biomarkers was verified in patients with urothelial carcinoma (UC) and esophageal squamous cell carcinoma (ESCC) who received ICIs. Results Our study identified two subgroups of patients with distinct immune infiltrating phenotypes and differing clinical outcomes. The patient subgroup with improved outcomes displayed tumors enriched with genes related to immune response regulation and pathway activation. Furthermore, CCL5 and CSF2 were identified as immune-related hub-genes and were found to be prognostic in a pan-cancer setting. Importantly, UC and ESCC patients with high expression of CCL5 and low expression of CSF2 responded better to ICIs. Conclusion We demonstrated CCL5 and CSF2 as potential novel biomarkers for predicting the response to ICIs in patients with UC and ESCC. The predictive value of these biomarkers in other cancer types warrants further evaluation in future studies.

Abstract The purpose of this study is to evaluate whether the periprostatic adipose tissue thickness (PPATT) is an independent prognostic factor for prostate cancer patients after laparoscopic radical prostatectomy (LRP). This retrospective cohort study included consecutive prostate cancer patients who underwent LRP treatment at Wuhan Union Hospital from June 2, 2016, to September 7, 2023. PPATT was defined as the thickness of periprostatic fat and was obtained by measuring the shortest vertical distance from the pubic symphysis to the prostate on the midsagittal T2-weighted MR images. Subcutaneous adipose tissue thickness (SATT) was obtained by measuring the shortest vertical distance from the pubic symphysis to the skin at the same slice with PPATT. The primary outcome of the study was biochemical recurrence (BCR), and the secondary outcome was overall survival (OS). Multivariable Cox regression analysis was used to identify independent prognostic factors for prostate cancer survival and prognosis. Based on the optimal cutoff value, 162 patients were divided into a low PPATT/SATT group (n = 82) and a high PPATT/SATT group (n = 80). During the entire follow-up period (median 23.5 months), 26 patients in the high PPATT/SATT group experienced BCR (32.5%), compared to 18 in the low PPATT/SATT group (22.0%). Kaplan–Meier curve analysis indicated that the interval to BCR was significantly shorter in the high PPATT/SATT group (P = 0.037). Multivariable Cox regression analysis revealed that an increase in the PPATT/SATT ratio was associated with BCR (hazard ratio: 1.90, 95% CI, 1.03–3.51; P = 0.040). The PPATT/SATT ratio is a significant independent risk factor for BCR after LRP for prostate cancer patients.

Abstract Antiferromagnets are promising for nano-scale oscillator in a wide frequency range from gigahertz up to terahertz. Experimentally realizing antiferromagnetic moment oscillation via spin-orbit torque, however, remains elusive. Here, we demonstrate that the optical spin-orbit torque induced by circularly polarized laser can be used to drive free decaying oscillations with a frequency of 2 THz in metallic antiferromagnetic Mn2Au thin films. Due to the local inversion symmetry breaking of Mn2Au, ultrafast a.c. current is generated via spin-to-charge conversion, which can be detected through free-space terahertz emission. Both antiferromagnetic moments switching experiments and dynamics analyses unravel the antiferromagnetic moments, driven by optical spin-orbit torque, deviate from its equilibrium position, and oscillate back in 5 ps once optical spin-orbit torque is removed. Besides the fundamental significance, our finding opens a new route towards low-dissipation and controllable antiferromagnet-based spin-torque oscillators.

Abstract Fiddler crabs, as coastal ecosystem engineers, play a crucial role in enhancing biodiversity and accelerating the flow of material and energy. Here we show how widespread crab burrows modify the carbon sequestration capacity of different habitats across a large climatic gradient. The process of crab burrowing results in the reallocation of sediment organic carbon and humus. Crab burrows can increase more greenhouse gases emissions compared to the sediment matrix (CO2: by 17–30%; CH4: by 49–141%). Straightforward calculations indicate that these increased emissions could offset 35–134% of sediment carbon burial in these two ecosystems. This research highlights the complex interactions between crab burrows, habitat type, and climate which reveal a potential lower carbon sink function of blue carbon ecosystems than previously expected without considering crab burrows.

Abstract Intrahepatic accumulation dominates organ distribution for most nanomedicines. However, obscure intrahepatic fate largely hampers regulation on their in vivo performance. Herein, PEGylated liposomal doxorubicin is exploited to clarify the intrahepatic fate of both liposomes and the payload in male mice. Kupffer cells initiate and dominate intrahepatic capture of liposomal doxorubicin, following to deliver released doxorubicin to hepatocytes with zonated distribution along the lobule porto-central axis. Increasing Kupffer cells capture promotes doxorubicin accumulation in hepatocytes, revealing the Kupffer cells capture-payload release-hepatocytes accumulation scheme. In contrast, free doxorubicin is overlooked by Kupffer cells, instead quickly distributing into hepatocytes by directly crossing fenestrated liver sinusoid endothelium. Compared to free doxorubicin, liposomal doxorubicin exhibits sustained metabolism/excretion due to the extra capture-release process. This work unveils the pivotal role of Kupffer cells in intrahepatic traffic of PEGylated liposomal therapeutics, and quantitively describes the intrahepatic transport/distribution/elimination process, providing crucial information for guiding further development of nanomedicines.

Abstract Background Deuterium metabolic imaging (DMI) has emerged as a promising non-invasive technique for studying metabolism in vivo. This review aims to summarize the current developments and discuss the futures in DMI technique in vivo. Methods A systematic literature review was conducted based on the PRISMA 2020 statement by two authors. Specific technical details and potential applications of DMI in vivo were summarized, including strategies of deuterated metabolites detection, deuterium-labeled tracers and corresponding metabolic pathways in vivo, potential clinical applications, routes of tracer administration, quantitative evaluations of metabolisms, and spatial resolution. Results Of the 2,248 articles initially retrieved, 34 were finally included, highlighting 2 strategies for detecting deuterated metabolites: direct and indirect DMI. Various deuterated tracers (e.g., [6,6′-2H2]glucose, [2,2,2′-2H3]acetate) were utilized in DMI to detect and quantify different metabolic pathways such as glycolysis, tricarboxylic acid cycle, and fatty acid oxidation. The quantifications (e.g., lactate level, lactate/glutamine and glutamate ratio) hold promise for diagnosing malignancies and assessing early anti-tumor treatment responses. Tracers can be administered orally, intravenously, or intraperitoneally, either through bolus administration or continuous infusion. For metabolic quantification, both serial time point methods (including kinetic analysis and calculation of area under the curves) and single time point quantifications are viable. However, insufficient spatial resolution remains a major challenge in DMI (e.g., 3.3-mL spatial resolution with 10-min acquisition at 3 T). Conclusions Enhancing spatial resolution can facilitate the clinical translation of DMI. Furthermore, optimizing tracer synthesis, administration protocols, and quantification methodologies will further enhance their clinical applicability. Relevance statement Deuterium metabolic imaging, a promising non-invasive technique, is systematically discussed in this review for its current progression, limitations, and future directions in studying in vivo energetic metabolism, displaying a relevant clinical potential. Key points • Deuterium metabolic imaging (DMI) shows promise for studying in vivo energetic metabolism. • This review explores DMI’s current state, limits, and future research directions comprehensively. • The clinical translation of DMI is mainly impeded by limitations in spatial resolution. Graphical Abstract

IntroductionTai Chi Chuan (TCC) is a traditional Chinese mind–body exercise widely adopted in Chinese communities and colleges. However, the mindful essence of TCC is rarely emphasized during popularization. This makes it difficult for beginners to benefit from it. The present study aimed to examine the effects of a Mindfulness-enhanced Tai Chi Chuan (MTCC) intervention, which enhances mindfulness components embedded within TCC, on mental and physical health among beginners.MethodsA randomized controlled trial was conducted with 119 healthy college students new to Tai Chi Chuan training. Participants were assigned to either the MTCC group or the TCC group. Both interventions consisted of 10 weekly 90-min training sessions, with the MTCC group emphasizing and enhancing mindfulness components. Outcome measures included mindfulness, depression, anxiety, stress, and physical fitness, assessed at baseline and post-intervention.ResultsThe results showed that the MTCC group had significantly greater improvements than the TCC group in mindfulness, anxiety, stress, and health—and skill-related physical fitness. There were no significant differences between the two groups in depression.ConclusionThe findings suggest that compared to TCC, MTCC can effectively promote individuals’ physical fitness and provide additional benefits to mental well-being. MTCC can be recommended as an accessible and beneficial intervention for beginners to improve mental health and strengthen their bodies.Clinical review registrationhttps://www.chictr.org.cn/, identifier ChiCTR2200058175.

Abstract Rearrangements of the mixed lineage leukemia (MLLr) gene are frequently associated with aggressive acute myeloid leukemia (AML). However, the treatment options are limited due to the genomic complexity and dynamics of 3D structure, which regulate oncogene transcription and leukemia development. Here, we carried out an integrative analysis of 3D genome structure, chromatin accessibility, and gene expression in gene-edited MLL-AF9 AML samples. Our data revealed profound MLLr-specific alterations of chromatin accessibility, A/B compartments, topologically associating domains (TAD), and chromatin loops in AML. The local 3D configuration of the AML genome was rewired specifically at loci associated with AML-specific gene expression. Together, we demonstrate that MLL-AF9 fusion disrupts the 3D chromatin landscape, potentially contributing to the dramatic transcriptome remodeling in MLLr AML.

Abstract Néel spin-orbit torque allows a charge current pulse to efficiently manipulate the Néel vector in antiferromagnets, which offers a unique opportunity for ultrahigh density information storage with high speed. However, the reciprocal process of Néel spin-orbit torque, the generation of ultrafast charge current in antiferromagnets has not been demonstrated. Here, we show the experimental observation of charge current generation in antiferromagnetic metallic Mn2Au thin films using ultrafast optical excitation. The ultrafast laser pulse excites antiferromagnetic magnons, resulting in instantaneous non-equilibrium spin polarization at the antiferromagnetic spin sublattices with broken spatial symmetry. Then the charge current is generated directly via spin-orbit fields at the two sublattices, which is termed as the reciprocal phenomenon of Néel spin-orbit torque, and the associated THz emission can be detected at room temperature. Besides the fundamental significance on the Onsager reciprocity, the observed magnonic charge current generation in antiferromagnet would advance the development of antiferromagnetic THz emitter.

Abstract There is no unified planning standard for unstructured roads, and the morphological structures of these roads are complex and varied. It is important to maintain a balance between accuracy and speed for unstructured road extraction models. Unstructured road extraction algorithms based on deep learning have problems such as high model complexity, high computational cost, and the inability to adapt to current edge computing devices. Therefore, it is best to use lightweight network models. Considering the need for lightweight models and the characteristics of unstructured roads with different pattern shapes, such as blocks and strips, a TMB (Triple Multi-Block) feature extraction module is proposed, and the overall structure of the TMBNet network is described. The TMB module was compared with SS-nbt, Non-bottleneck-1D, and other modules via experiments. The feasibility and effectiveness of the TMB module design were proven through experiments and visualizations. The comparison experiment, using multiple convolution kernel categories, proved that the TMB module can improve the segmentation accuracy of the network. The comparison with different semantic segmentation networks demonstrates that the TMBNet network has advantages in terms of unstructured road extraction.

Abstract Acute myeloid leukemia (AML) with mixed-lineage leukemia (MLL) gene rearrangements (MLL-r) is an aggressive subtype of blood cancer with dismal prognosis, underscoring the urgent need for novel therapeutic strategies. E1A-binding protein (EP300) and CREB-binding protein (CREBBP) function as essential transcriptional coactivators and acetyltransferases, governing leukemogenesis through diverse mechanisms. Targeting EP300/CREBBP holds great promise for treating leukemia with some certain cytogenetic abnormalities. Here, we demonstrated that EP300 and CREBBP are core epigenetic regulators in the pathogenesis of MLL-r AML through assaying the transposase-accessible chromatin with high-throughput sequencing (ATAC-seq). Knocking-out EP300/CREBBP and inhibitor (A-485) treatment depressed the MLL-r cells proliferation, while the MLL wild-type cells remained uninfluenced. We found that the CDK4/RB/E2F axis was downregulated specifically in MLL-r AML cell after A-485 treatment by RNA-seq, western blot and cut-tag analyses. EP300/CREBBP inhibitor selectively exerted potent anti-leukemia activity through blocking the MLL-r-BET complex binding to H3K27Ac modification on critical genes loci, distinct from global histone acetylation. Collectively, our study identified EP300/CREBBP as a critical epigenetic driver of MLL-r leukemia and validated their therapeutic potential through targeting inhibition, offering a promising avenue for improving clinical outcomes in this aggressive leukemia.

Abstract Background Immunotherapy based on the application of immune checkpoint inhibitors (ICIs) is one of the standard treatments for advanced non-small cell lung cancer (NSCLC). Non-alcoholic fatty liver Disease (NAFLD) has demonstrated predictive value for response to immunotherapy in non-lung cancer types. Our study investigated the effect of NAFLD on the efficacy of real-life use of ICIs for patients with stage III / IV NSCLC. Methods The clinical and imaging data of patients with stage III / IV NSCLC who were first admitted to Union Hospital, Tongji Medical College, Huazhong University of Science and Technology from March 2020 to July 2022 were retrospectively collected to ensure that they underwent at least one CT scan before treatment. A total of 479 patients were divided into the NAFLD group (Liver/Spleen density ratio ≤ 1) and the non-NAFLD group (Liver/Spleen density ratio > 1) by measuring the baseline liver and spleen CT value. The overall survival (OS), progression-free survival (PFS), objective response rate (ORR) and disease control rate (DCR) of the patients were obtained. Results A total of 118 patients with NAFLD and 361 patients without NAFLD were included in the study. Patients with NAFLD tended to have higher BMI and higher total bilirubin compared to patients without NAFLD. The median duration of follow-up in the study was 22 m (IQR, 17–29 m). Both of 2 groups had a higher DCR (94% vs. 92%, p = 0.199) and ORR (38.1% vs. 44.9%, p = 0.452) respectively. There was no difference in efficacy between the two groups. In univariate analysis, NAFLD had no significant effect on PFS (p = 0.785) and OS (p = 0.851). Surprisingly, the presence of hypertension was observed to be associated with a higher OS (HR 1.471 95%CI 1.018–2.127, p = 0.040). Besides, based on multivariate analysis, lactic dehydrogenase was associated with PFS (HR 1.001 95%CI 1.000,1.002, p = 0.037) and OS (HR 1.002, 95%CI 1.001–1.003, p

Abstract Lithium (Li) metal batteries are regarded as the “holy grail” of next‐generation rechargeable batteries, but the poor redox reversibility of Li anode hinders its practical applications. While extensive studies have been carried out to design lithiophilic substrates for facile Li plating, their effects on Li stripping are often neglected. In this study, by homogeneously loading indium (In) single atoms on N‐doped graphene via In‐N bonds, the affinity between Li and hosting substrates is regulated. In situ observation of Li deposition/stripping processes shows that compared with the N‐doped graphene substrate, the introduction of In effectively promotes its reversibility of Li redox, achieving a dendrite‐free Li anode with much‐improved coulombic efficiency. Interestingly, theoretical calculations demonstrate that In atoms have actually made the substrate less lithophilic via passivating the N sites to avoid the formation of irreversible Li–N bonding. Therefore, a “volcano curve” for reversible Li redox processes is proposed: the affinity of substrates toward Li should be optimized to a moderate value, where the balance for both Li plating and Li stripping processes could be reached. By demonstrating a crucial design principle for Li metal hosting substrates, our finding could trigger the rapid development of related research.

The incorporation of steel reinforcement in cast concrete can effectively enhance the ductility and strength of the concrete. In this paper, the steel wires reinforced 3D printed mortar (3DPM) was utilized as the external restraint for two series of short concrete columns (S-series: square section, C-series: circular section). Three different wire diameters (fine, medium, and thick) were considered as experimental variables. The experimental results indicate that the specimens reinforced with medium steel wires in both series exhibited strengths comparable to or superior to those of the unreinforced specimens. In terms of crack control, the specimens with the appropriate reinforcement ratio exhibited excellent performance, showing the smallest crack widths for both C-M and S-M specimens. It is found that in both S and C series that an appropriate reinforcement ratio positively influences the load-bearing capacity of the restrained columns. Furthermore, a calculated model for the uniaxial compression model of ECC confined concrete was proposed. The findings reveal that the calculated model is conservative and effective in predicting the compressive strength of the short column, with the exception of the C-F specimen.

Existing seed germination detection technologies based on deep learning are typically optimized for hydroponic breeding environments, leading to a decrease in recognition accuracy in complex soil cultivation environments. On the other hand, traditional manual germination detection methods are associated with high labor costs, long processing times, and high error rates, with these issues becoming more pronounced in complex soil–based environments. To address these issues in the germination process of new cucumber varieties, this paper utilized a Seed Germination Phenotyping System to construct a cucumber germination soil–based experimental environment that is more closely aligned with actual production. This system captures images of cucumber germination under salt stress in a soil-based environment, constructs a cucumber germination dataset, and designs a lightweight real-time cucumber germination detection model based on Real-Time DEtection TRansformer (RT-DETR). By introducing online image enhancement, incorporating the Adown downsampling operator, replacing the backbone convolutional block with Generalized Efficient Lightweight Network, introducing the Online Convolutional Re-parameterization mechanism, and adding the Normalized Gaussian Wasserstein Distance loss function, the training effectiveness of the model is enhanced. This enhances the model’s capability to capture profound semantic details, achieves significant lightweighting, and enhances the model’s capability to capture embryonic root targets, ultimately completing the construction of the RT-DETR-SoilCuc model. The results show that, compared to the RT-DETR-R18 model, the RT-DETR-SoilCuc model exhibits a 61.2% reduction in Params, 61% reduction in FLOP, and 56.5% reduction in weight size. Its mAP@0.5, precision, and recall rates are 98.2%, 97.4%, and 96.9%, respectively, demonstrating certain advantages over the You Only Look Once series models of similar size. Germination tests of cucumbers under different concentrations of salt stress in a soil-based environment were conducted, validating the high accuracy of the RT-DETR-SoilCuc model for embryonic root target detection in the presence of soil background interference. This research reduces the manual workload in the monitoring of cucumber germination and provides a method for the selection and breeding of new cucumber varieties.

The high-throughput and full-time acquisition of images of crop growth processes, and the analysis of the morphological parameters of their features, is the foundation for achieving fast breeding technology, thereby accelerating the exploration of germplasm resources and variety selection by crop breeders. The evolution of embryonic soybean radicle characteristics during germination is an important indicator of soybean seed vitality, which directly affects the subsequent growth process and yield of soybeans. In order to address the time-consuming and labor-intensive manual measurement of embryonic radicle characteristics, as well as the issue of large errors, this paper utilizes continuous time-series crop growth vitality monitoring system to collect full-time sequence images of soybean germination. By introducing the attention mechanism SegNext_Attention, improving the Segment module, and adding the CAL module, a YOLOv8-segANDcal model for the segmentation and extraction of soybean embryonic radicle features and radicle length calculation was constructed. Compared to the YOLOv8-seg model, the model respectively improved the detection and segmentation of embryonic radicles by 2% and 1% in mAP50-95, and calculated the contour features and radicle length of the embryonic radicles, obtaining the morphological evolution of the embryonic radicle contour features over germination time. This model provides a rapid and accurate method for crop breeders and agronomists to select crop varieties.

Summary: Retinal ganglion cells (RGCs) summate inputs and forward a spike train code to the brain in the form of either maintained spiking (sustained) or a quickly decaying brief spike burst (transient). We report diverse response transience values across the RGC population and, contrary to the conventional transient/sustained scheme, responses with intermediary characteristics are the most abundant. Pharmacological tests showed that besides GABAergic inhibition, gap junction (GJ)–mediated excitation also plays a pivotal role in shaping response transience and thus visual coding. More precisely GJs connecting RGCs to nearby amacrine and RGCs play a defining role in the process. These GJs equalize kinetic features, including the response transience of transient OFF alpha (tOFFα) RGCs across a coupled array. We propose that GJs in other coupled neuron ensembles in the brain are also critical in the harmonization of response kinetics to enhance the population code and suit a corresponding task.

Abstract This study aimed to assess pulmonary changes at 6-month follow-up CT and predictors of pulmonary residual abnormalities and fibrotic-like changes in COVID-19 pneumonia patients in China following relaxation of COVID restrictions in 2022. A total of 271 hospitalized patients with COVID-19 pneumonia admitted between November 29, 2022 and February 10, 2023 were prospectively evaluated at 6 months. CT characteristics and Chest CT scores of pulmonary abnormalities were compared between the initial and the 6-month CT. The association of demographic and clinical factors with CT residual abnormalities or fibrotic-like changes were assessed using logistic regression. Follow-up CT scans were obtained at a median of 177 days (IQR, 170–185 days) after hospital admission. Pulmonary residual abnormalities and fibrotic-like changes were found in 98 (36.2%) and 39 (14.4%) participants. In multivariable analysis of pulmonary residual abnormalities and fibrotic-like changes, the top three predictive factors were invasive ventilation (OR 13.6; 95% CI 1.9, 45; P 60 years (OR 9.1; 95% CI 2.3, 39; P = .01), paxlovid (OR 0.11; 95% CI 0.04, 0.48; P = .01) and invasive ventilation (OR 10.3; 95% CI 2.9, 33; P = .002), paxlovid (OR 0.1; 95% CI 0.03, 0.48; P = .01), smoker (OR 9.9; 95% CI 2.4, 31; P = .01), respectively. The 6-month follow-up CT of recent COVID-19 pneumonia cases in China showed a considerable proportion of the patients with pulmonary residual abnormalities and fibrotic-like changes. Antivirals against SARS-CoV-2 like paxlovid may be beneficial for long-term regression of COVID-19 pneumonia.

Background : Warm acupuncture (WA) has analgesic and anti-inflammatory effects. However, the underlying mechanism of these effects remain unclear. Objectives: To explore the analgesic and anti-inflammatory effects of WA and the potential underlying mechanism in male Sprague-Dawley rats with non-compressive lumbar disk herniation (LDH) caused by autologous nucleus pulposus (NP) transplantation. Methods : We used low-frequency (2 Hz) electrical stimulation and WA (40℃) to treat GB30 and BL54 acupoints in rats for 30 mins per day. We monitored the paw withdrawal threshold of rats during the experiment and measured serum cytokine levels using commercial kits. Dorsal root ganglion (DRG) tissue pathology was analyzed via H&E staining. We used qRT-PCR to measure the mRNA expression levels of IL-1β, IL-6, and TNF-α genes in DRG. Western blot was used to analyze the expression levels of IL-1β, IL-6, TNFα, P-p38MAPK, p38MAPK, P-IκBα, IκB α, and NF-κB p65 proteins. Results : WA treatment significantly increased the pain threshold of rats, reduced serum IL-6, PEG2, NO, SP, NP-Y, and MMP-3 levels, and effected histopathological improvements in the DRG in rats. Moreover, WA treatment significantly downregulated the expression levels of inflammation-associated genes (Il-1β, Il-6, and Tnf-α) and proteins (IL-1β, IL-6, TNF-α, P-p38MAPK, P-IκBα, and NF-κB p65) in the DRG of non-compressive LDH rats. Conclusion : WA can alleviate pain and inhibit inflammatory response in rats with non-compressive LDH caused by autologous NP transplantation, and these effects are likely associated with the inhibition of the p38MAPK/NF-κB pathway.

Abstract Despite the recent achievements in urea electrosynthesis from co-reduction of nitrogen wastes (such as NO3 −) and CO2, the product selectivity remains fairly mediocre due to the competing nature of the two parallel reduction reactions. Here we report a catalyst design that affords high selectivity to urea by sequentially reducing NO3 − and CO2 at a dynamic catalytic centre, which not only alleviates the competition issue but also facilitates C−N coupling. We exemplify this strategy on a nitrogen-doped carbon catalyst, where a spontaneous switch between NO3 − and CO2 reduction paths is enabled by reversible hydrogenation on the nitrogen functional groups. A high urea yield rate of 596.1 µg mg−1 h−1 with a promising Faradaic efficiency of 62% is obtained. These findings, rationalized by in situ spectroscopic techniques and theoretical calculations, are rooted in the proton-involved dynamic catalyst evolution that mitigates overwhelming reduction of reactants and thereby minimizes the formation of side products.

Abstract Background Immune checkpoint inhibitors (ICIs) have contributed to a significant advancement in the treatment of cancer, leading to improved clinical outcomes in many individuals with advanced disease. Both preclinical and clinical investigations have shown that ICIs are associated with atherosclerosis and other cardiovascular events; however, the exact mechanism underlying this relationship has not been clarified. Methods Patients diagnosed with stages III or IV non-small cell lung cancer (NSCLC) at the Wuhan Union Hospital from March 1, 2020, to April 30, 2022, were included in this retrospective study. Coronary artery calcium (CAC) volume and score were assessed in a subset of patients during non-ECG-gated chest CT scans at baseline and 3, 6, and 12 months after treatment. Propensity score matching (PSM) was performed in a 1:1 ratio to balance the baseline characteristics between the two groups. Results Overall, 1458 patients (487 with ICI therapy and 971 without ICI therapy) were enrolled in this cardiovascular cohort study. After PSM, 446 patients were included in each group. During the entire period of follow-up (median follow-up 23.1 months), 24 atherosclerotic cardiovascular disease (ASCVD) events (4.9%) occurred in the ICI group, and 14 ASCVD events (1.4%) in the non-ICI group, before PSM; 24 ASCVD events (5.4%) occurred in the ICI group and 5 ASCVD events (1.1%) in the non-ICI group after PSM. The CAC imaging study group comprised 113 patients with ICI therapy and 133 patients without ICI therapy. After PSM, each group consisted of 75 patients. In the ICI group, the CAC volume/score increased from 93.4 mm3/96.9 (baseline) to 125.1 mm3/132.8 (at 12 months). In the non-ICI group, the CAC volume/score was increased from 70.1 mm3/68.8 (baseline) to 84.4 mm3/87.9 (at 12 months). After PSM, the CAC volume/score was increased from 85.1 mm3/76.4 (baseline) to 111.8 mm3/121.1 (12 months) in the ICI group and was increased from 74.9 mm3/76.8 (baseline) to 109.3 mm3/98.7 (12 months) in the non-ICI group. Both cardiovascular events and CAC progression were increased after the initiation of ICIs. Conclusions Treatment with ICIs was associated with a higher rate of ASCVD events and a noticeable increase in CAC progression.

Rapid urbanization has exerted immense pressure on urban environments, severely constraining the growth of ancient trees. The growth of ancient trees is closely linked to the microbial communities in their rhizospheres, and studying their community characteristics may provide new insights into promoting the growth and rejuvenation of ancient trees. In this study, the rhizosphere soil and root systems of ancient Ginkgo biloba trees (approximately 200 years old) and adult G. biloba trees (approximately 50 years old) in Shanghai were selected as research subjects. Phospholipid fatty acid (PLFA) analysis and high-throughput sequencing were employed to investigate the diversity of microbial communities in the G. biloba rhizosphere. The results indicated that the 19 PLFA species selected to characterize the soil microbial community structure and biomass were present in the rhizosphere soil of both ancient and adult G. biloba trees. However, the total microbial biomass and the microbial biomass in the rhizosphere soil of ancient G. biloba were lower than the microbial biomass in the rhizosphere soil of adult G. biloba. The biomasses of Gram-negative bacteria (G−), arbuscular mycorrhizal fungi (AMF), and protozoans (P) were significantly different. Total phosphorus, organic matter, and pH may be the key factors influencing the soil microbial community in the rhizosphere zone of ancient G. biloba. An in-depth study of AMF showed that the roots and rhizosphere soil of G. biloba contained abundant AMF resources, which were assigned to 224 virtual taxa using the MaarjAM reference database, belonging to four orders, ten families, and nineteen genera. The first and second most dominant genera were Glomus and Paraglomus, respectively. Archaeospora and Ambispora were more dominant in the rhizosphere than the roots. Furthermore, the abundance of live AMF was significantly higher in ancient G. biloba than in adult G. biloba. Therefore, future research should focus on the improvement of soil environmental characteristics and the identification and cultivation of indigenous dominant AMF in the rhizosphere of ancient G. biloba, aiming for their effective application in the rejuvenation of ancient trees.

Dynamic mutations in some human genes containing trinucleotide repeats are associated with severe neurodegenerative and neuromuscular disorders—known as Trinucleotide (or Triplet) Repeat Expansion Diseases (TREDs)—which arise when the repeat number of triplets expands beyond a critical threshold. While the mechanisms causing the DNA triplet expansion are complex and remain largely unknown, it is now recognized that the expandable repeats lead to the formation of nucleotide configurations with atypical structural characteristics that play a crucial role in TREDs. These nonstandard nucleic acid forms include single-stranded hairpins, Z-DNA, triplex structures, G-quartets and slipped-stranded duplexes. Of these, hairpin structures are the most prolific and are associated with the largest number of TREDs and have therefore been the focus of recent single-molecule FRET experiments and molecular dynamics investigations. Here, we review the structural and dynamical properties of nucleic acid hairpins that have emerged from these studies and the implications for repeat expansion mechanisms. The focus will be on CAG, GAC, CTG and GTC hairpins and their stems, their atomistic structures, their stability, and the important role played by structural interrupts.

The low carbon park islanded microgrid faces operational challenges due to the high variability and uncertainty of distributed renewable energy sources. These sources cause severe random disturbances that impair the frequency control performance and increase the regulation cost of the islanded microgrid, jeopardizing its safety and stability. This paper presents a data-driven intelligent load frequency control (DDI-LFC) method to address this problem. The method replaces the conventional LFC controller with an intelligent agent based on a deep reinforcement learning algorithm. To adapt to the complex islanded microgrid environment and achieve adaptive multi-objective optimal frequency control, this paper proposes the quantum-inspired maximum entropy actor-critic (QIS-MEAC) algorithm, which incorporates the quantum-inspired principle and the maximum entropy exploration strategy into the actor-critic algorithm. The algorithm transforms the experience into a quantum state and leverages the quantum features to improve the deep reinforcement learning’s experience replay mechanism, enhancing the data efficiency and robustness of the algorithm and thus the quality of DDI-LFC. The validation on the Yongxing Island isolated microgrid model of China Southern Grid (CSG) demonstrates that the proposed method utilizes the frequency regulation potential of distributed generation, and reduces the frequency deviation and generation cost.

Student dropout prediction (SDP) in educational research has gained prominence for its role in analyzing student learning behaviors through time series models. Traditional methods often focus singularly on either prediction accuracy or earliness, leading to sub-optimal interventions for at-risk students. This issue underlines the necessity for methods that effectively manage the trade-off between accuracy and earliness. Recognizing the limitations of existing methods, this study introduces a novel approach leveraging multi-objective reinforcement learning (MORL) to optimize the trade-off between prediction accuracy and earliness in SDP tasks. By framing SDP as a partial sequence classification problem, we model it through a multiple-objective Markov decision process (MOMDP), incorporating a vectorized reward function that maintains the distinctiveness of each objective, thereby preventing information loss and enabling more nuanced optimization strategies. Furthermore, we introduce an advanced envelope Q-learning technique to foster a comprehensive exploration of the solution space, aiming to identify Pareto-optimal strategies that accommodate a broader spectrum of preferences. The efficacy of our model has been rigorously validated through comprehensive evaluations on real-world MOOC datasets. These evaluations have demonstrated our model’s superiority, outperforming existing methods in achieving optimal trade-off between accuracy and earliness, thus marking a significant advancement in the field of SDP.

BackgroundImmune checkpoint inhibitors (ICIs) have left a deep impression in the treatment of non-small cell lung cancer (NSCLC), however, not all patients benefit from it. The purpose of this study was to investigate the prognostic value of baseline bone mineral density (BMD) derived from chest computed tomography (CT) scans in NSCLC patients treated with ICIs.MethodsThis study included patients with advanced NSCLC who underwent ICI treatment at the Wuhan Union Hospital from March 2020 to October 2022. Baseline BMD was evaluated at non-contrast chest CT at the level of first lumbar vertebra. Patients were divided into BMD-lower group and BMD-higher group according to the optimal cutoff value calculated by X-tile software. Baseline characteristics of the two groups were compared and variables between the two groups were balanced by propensity score matching (PSM) analysis. We calculated the objective response rate (ORR) and disease control rate (DCR) of the two groups and analyzed overall survival (OS) and progression-free survival (PFS) using BMD and other clinical indexes through Cox regression models and Kaplan-Meier survival curves.ResultsA total of 479 patients were included in this study, and all patients were divided into BMD-lower group (n=270) and BMD-higher group (n=209). After PSM analysis, each group consisted of 150 patients. ORR (43.3% vs. 43.5% before PSM, P = 0.964; 44.7% vs. 44.7% after PSM, P = 1.000) and DCR (91.1% vs. 94.3% before PSM, P = 0.195; 93.3% vs. 96.7% after PSM, P =0.190) were similar in two groups. There was no statistically significant relationship between BMD degree and PFS before (16.0 months vs. 18.0 months, P = 0.067) and after PSM analysis (17.0 months vs. 19.0 months, P = 0.095). However, lower BMD was associated with shorter OS both before (20.5 months vs. 23.0 months, P< 0.001) and after PSM analysis (20.0 months vs. 23.0 months, P = 0.008).ConclusionLower baseline BMD is associated with worse clinical outcomes in NSCLC patients treated with ICIs. As a reliable and easily obtained individual prognostic biomarker, BMD can become a routine detection indicator before immunotherapy.

With the increasing complexity of power systems and the proliferation of renewable energy sources, the task of calculating carbon emissions has become increasingly challenging. To address these challenges, we developed a new method for predicting carbon emission factors. Bayesian optimization technique graphical convolutional networks with long- and short-term network (BO-TGNN) is used to predict the carbon emissions of the power system. The method aims to quickly predict the day-ahead carbon emissions of power system nodes with enhanced feature extraction and optimized network training hyperparameters. The effectiveness of the proposed method is demonstrated through simulation tests on three different power systems using four deep learning algorithms. The method provides a tailored solution to the evolving needs of carbon reduction efforts and is a significant step forward in addressing the complexity of carbon emission calculations for modern power systems.

In light of the escalating concerns surrounding climate change and air quality degradation, the imperative for energy conservation and emission reduction has garnered widespread attention. Given that factories represent a significant portion of electricity consumption within the power network, a comprehensive analysis of the electricity consumption behavior of energy-intensive enterprises becomes paramount. To meticulously dissect the electricity consumption patterns of energy-intensive enterprises, this paper categorizes them into four distinct production modes: 24-hour all-day production factories, pure daytime production factories, pure nighttime production factories, and environmentally friendly peaking production factories. Employing the dynamic electricity–carbon factor as a guiding force, the analysis encompasses electricity consumption, tariff expenditure, peaking costs, carbon emissions, and comfort levels associated with each production method throughout the year. A delicate equilibrium is sought among multiple objectives, aiming to optimize the user experience while simultaneously mitigating costs and carbon emissions. Furthermore, this paper conducts a comparative analysis of each objective, employing single-objective genetic algorithms and the interior point method. The resultant findings serve as invaluable insights for business users, aiding in informed decision-making processes.

Background: Huachansu injection (HCS) is an aqueous extract preparation of Traditional Chinese Medicine (TCM) toad skin (Bufo melanosticus or B. bufo gargarizans). As a national second-class and self-developed TCM preparation, it is widely used to treat human colorectal cancer (CRC), yet its substantial toxic side effects, such as vascular irritation reaction, drug fever, and allergic reactions, pose a considerable challenge during clinical use. In-depth research on the material basis of HCS' traditional efficacy is essential for developing more effective and less toxic medicine. Identifying the main components responsible for the efficacy of HCS is crucial in determining its material basis and explaining any adverse reactions. Purpose: The purpose of this study is to clarify the main active components of HCS as a growth inhibitory agent against CRC HCT116 cells and to further understand the material basis of its anti-CRC properties. Methods: Sulforhodamine B (SRB) assay was used to screen the compound with strong inhibitory activity against HCT116 cells from 44 compounds isolated from aqueous extracts of toad skin (B. melanosticus). The screened compounds as standard and MeOH extracts from HCS were determined by HPLC coupled with triple quadrupole mass spectrometry. The partial MeOH extract was subjected to HPLC system using solvents in a gradient of increasing polarity, yielding 12 fractions in total (HCS1 to HCS12). Besides, the screened active compounds were knocked out from HCS to obtain a fraction as a negative control, and the knocked-out components were collected as one fraction using semi-preparative HPLC. Those fractions were submitted to HPLC-MS/MS or HPLC-DAD system to determine the presence or absence of the screened compounds. In addition, cytotoxicity of those prepared fractions against CRC HCT116 cells was evaluated to determine the effect of the screened compounds in the anti-CRC of HCS. Results: Six compounds, namely arenobufagin, telocinobufagin, gamabufalin, hellebrigenin, 19-hydroxylbufagin and argentinogenin, were screened for their inhibitory activity (with an IC50 value of less than 400 nM), and were present in HCS at a total-mass-percentage of 1.35×10−3 % in HCS MeOH extract. In addition, those 6 compounds were mainly distributed in HCS8, which also showed the strongest inhibitory activity against HCT116 cells. And the results of multicomponent knockout assay indicated the negative control lost its anti-CRC activity significantly, while the activity can be restored after those 6 compounds were added to the negative control. Conclusions: Those six bufadienolides derivatives are responsible for the anti-CRC HCT116 cells activity of HCS, and are the main components of HCS on anti-CRC. Through this research, we can more clearly understand the main anti-CRC active components in HCS, and the work also lays the foundation for the development of more effective and less toxic medicine from HCS.

In order to study genetic diversity and the origin of wild Rosa roxburghii in Southwest China and provide some bases for its utilization and protection. A survey was based on the splicing sequences of two single-copy nuclear genes (GAPDH and ncpGS) and three chloroplast genes (atpF-trnH, trnL-trnF and trnG-trnS). The individuals of 320 wild R. roxburghii from 27 wild populations in China were amplified, sequenced by PCR. After that, the sequencing results were analyzed with relevant software. The results were as follows: (1) Low genetic diversity levels were found in R. roxburghii of single-copy nuclear gene (Hd=0.469 2, π=0.000 49) and chloroplast gene (Hd=0.653 4, π=0.000 65). But there were significant differences among different populations. (2) Analysis of molecular variance (AMOVA) showed that the genetic variation almost occured within populations, which indicated that population variation was the main source of genetic variation in wild R. roxburghii. It existed obvious genetic differentiation among populations (cpDNA: FST=0.336 47, GST=0.273, NST=0.308; scnDNA: FST=0.094 87, NST=0.076, GST=0.056). The distribution of R. roxburghii did not have obvious phylogeographical structure (P>0.05). (3) Tajima’s D value of neutral test was insignificantly negative value, indicating that R. roxburghii populations conformed to neutral evolution model. Fu's Fs value was significantly negative, combining the result of mismatch analysis curve, deducing that R. roxburghii populations had an expansion within a small range before. But generally, they remained stable. (4) According to the haplotype network, the populations of the Bijie region not only presented higher genetic diversity, but also had a lot of haplotypes. Therefore, the Bijie region was speculated to be one of the refuges of ice age. Therefore, they were supposed to be carried out the strategy of local protection, and the populations with special traits and unique haplotypes shall be protected to adopt a priority protection approach. The study provides a reference for wild R. roxburghii of the resource protection and genetic breeding.

Abstract Introduction This study aimed to investigate the associations of comorbidities with knee symptoms and radiographic abnormalities of osteoarthritis (OA). Methods Participants were from the Osteoarthritis Initiative. Comorbidities were identified at baseline using the modified Charlson Comorbidity Index. For both knees, symptoms were assessed annually from baseline to 48 months using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain and function scores (rescaled range 0–100), and radiographic abnormalities using the Kellgren–Lawrence (KL, 0–4) grades. The presence of significant pain and functional disability was defined as a WOMAC score of ≥ 25 and ≥ 22, respectively, and radiographic OA (ROA) as KL ≥ 2. An increase of ≥ 9 in WOMAC scores and ≥ 1 in KL grades were defined as symptomatic and radiographic progression, respectively. Results Of 3337 participants, 28% and 9% had one and ≥ 2 comorbidities, respectively. The number of comorbidities was associated with the presence of significant functional disability (odds ratios [ORs] 1.15; 1.46) and predicted the progression of both knee pain and functional disability (ORs 1.11; 1.51). For the type of comorbidities, non-OA musculoskeletal diseases were associated with the presence of ROA and significant functional disability (ORs 1.63; 1.82) and showed a trend to predict incident ROA (OR 1.84, 95% confidence interval 1.00–3.38 p = 0.051). Diabetes and kidney diseases were associated with symptomatic progression of OA (ORs 1.38; 2.72). Conclusions Having more comorbidities, especially diabetes and kidney diseases, is associated with symptomatic progression of knee OA. Moreover, non-OA musculoskeletal diseases may be associated with the presence and onset of ROA.

Abstract As one of the most promising alternatives to graphite negative electrodes, silicon oxide (SiO x ) has been hindered by its fast capacity fading. Solid electrolyte interphase (SEI) aging on silicon SiO x has been recognized as the most critical yet least understood facet. Herein, leveraging 3D focused ion beam-scanning electron microscopy (FIB-SEM) tomographic imaging, we reveal an exceptionally characteristic SEI microstructure with an incompact inner region and a dense outer region, which overturns the prevailing belief that SEIs are homogeneous structure and reveals the SEI evolution process. Through combining nanoprobe and electron energy loss spectroscopy (EELS), it is also discovered that the electronic conductivity of thick SEI relies on the percolation network within composed of conductive agents (e.g., carbon black particles), which are embedded into the SEI upon its growth. Therefore, the free growth of SEI will gradually attenuate this electron percolation network, thereby causing capacity decay of SiO x . Based on these findings, a proof-of-concept strategy is adopted to mechanically restrict the SEI growth via applying a confining layer on top of the electrode. Through shedding light on the fundamental understanding of SEI aging for SiO x anodes, this work could potentially inspire viable improving strategies in the future.

Abstract Objectives This study aimed to investigate the long-term effect of vitamin D supplementation compared to placebo over 5 years in participants with knee osteoarthritis (OA). We also aimed to describe the effect of maintaining sufficient serum vitamin D levels over five years in knee OA. Methods Participants (n = 173) from the Hobart centre of the Vitamin D Effects on Osteoarthritis (VIDEO) trial were extensively followed up 3 years after the cessation of 2-year investigational treatment. Participants were classified as maintaining sufficient vitamin D (n = 79) and not maintaining sufficient vitamin D (n = 61) groups. Results There was no significant difference in change in the knee symptoms, depression, and serum levels of IL6 and hs-CRP between both comparisons after 3 years of cessation of the clinical trial. However, among participants who reported no knee surgery (KS), there was a significant improvement in WOMAC function (β: − 83.7, 95% CI: − 167.3, 0) and depression scores (β: − 1.3, 95% CI: − 2.3, − 0.2) in vitamin D group compared to the placebo group. Similarly, those who maintained adequate vitamin D levels over 5 years had significantly less WOMAC knee pain (β: − 33.9, 95% CI: − 65.7, − 2) and physical dysfunction (β: − 105.5, 95% CI: − 198.2, − 12.8) than participants with vitamin D deficiency over 5 years. Conclusion Vitamin D supplementation over 2 years or maintaining vitamin D sufficiency for 5 years was not associated with statistically significant differences in change in knee symptom scores over 5 years. However, among participants who did not report KS, 2-year vitamin D supplementation and maintaining sufficient vitamin D was linked to modest improvements in knee symptoms and depression scores in knee OA.

Consumer-feeder relationship is an important basis for the fault location, outage management, load adjustment and power quality management in low-voltage distribution station area (LVDSA). The current identification method of the consumer-feeder relationship based on electrical characteristics analysis is single and lack of reliability. Besides, the consumers of different feeders which locate near the bus at the low voltage side of distribution transformer have high voltage variation similarity, which makes it difficult to distinguish reliably. The spatial distribution of consumers can directly reflects the feeder trend. Therefore, a consumer-feeder relationship identification method for LVDSA considering feature fusion of voltage variation and spatial distribution is proposed in this paper. Firstly, the electrical characteristics based on voltage variation and spatial distribution characteristics based on geographical location are analyzed, and the correlation between the characteristics above and consumer-feeder relationship is explained. Secondly, a semi-supervised spectral clustering (SSC) algorithm based on the feature of voltage variation and spatial distribution is proposed to identify the consumer-feeder relationship. Finally, the proposed method is tested with the real data of LVDSAs in China. The results indicate that the feature fusion of voltage variation and spatial distribution can effectively improve the identification accuracy of consumer-feeder relationship.

Line loss is directly responsible for the management profitability of the grid company. The traditional method of calculating the theoretical line loss for Low Voltage Distribution Networks (LVDN) necessitates more electrical parameters. which cannot be obtained easily. Besides, due to the backward communication conditions of LVDN, the problem of smart meter data missing is significant, which poses a challenge to an exact theoretical line loss calculation. In an attempt to solve the issues above, a theoretical line loss computation approach via matrix completion and ReliefF-convolutional neural network (CNN) for LVDN is proposed. Firstly, a feature weighting algorithm based on ReliefF is presented to analyze the relevance of the electrical parameters, which can be obtained easily. Secondly, a theoretical line loss calculation method is proposed for CNN-based. In the view of the data missing problem, a matrix completion method based on singular value thresholding (SVT) is introduced to obtain the high-precision data, in order to enhance the calculation accuracy of the theoretical line loss calculation. Finally, the proposed method is tested on the data sample of 789 LVDNs. The results show that comparing with CNN, back-propagation and other methods, the mean absolute percentage error (MAPE) of the presented method can reduce by more than 90%. When data missing, the MAPE of the proposed method can reduce by more than 95% compared with the method without considering the data completion.

This paper addresses task allocation to multi-UAV systems in time- and communication-constrained environments by presenting an extension to the novel heuristic performance impact (PI) algorithm. The presented algorithm, termed local reassignment performance impact (LR-PI), consists of an improved task inclusion phase, a novel communication and conflict resolution phase, and a systematic method of reassignment for unallocated tasks. Considering the cooperation in accomplishing tasks that may require multiple UAVs or an individual UAV, the task inclusion phase can build the ordered task list on each UAV with a greedy approach, and the significance value of tasks can be further decreased and conflict-free assignments can be reached eventually. Furthermore, the local reassignment for unallocated tasks focuses on maximizing the number of allocated tasks without conflicts. In particular, the non-ideal communication factors, such as bit error, time delay, and package loss, are integrated with task allocation in the conflict resolution phase, which inevitably exist and can degrade task allocation performance in realistic communication environments. Finally, we show the performance of the proposed algorithm under different communication parameters and verify the superiority in comparison with the PI-MaxAsses and the baseline PI algorithm.

In view of the challenges faced by cotton dibbler in Xinjiang under high-speed operation, a novel crawler-type delayed hole-forming device has been designed to address the seed throwing and floating issues in high-speed cotton dibbling in Xinjiang, enhancing the duck bill’s performance. This mechanism increases the sowing speed to 6 km/h by extending the duck bill horizontally. Utilizing agronomic principles, the mechanism’s layout and key components were optimized for efficient hole-forming. DEM and multi-body dynamics simulations were employed to analyze the motion, focusing on the fixed the tilt angle of the duck bill (A), the depth of the duck bill hole-forming into the soil (B), and the angle of rotation of the moving duck bill (C) as factors affecting hole dimensions (longitudinal length of hole Y1 and hole-forming depth of cotton seed hole Y2). Quadratic regression test using RecurDyn-EDEM coupling identified optimal parameter settings for maximum hole-forming performance. When A was 2.4°, B was 42.4 mm, and C was 30.5°, the performance of the hole-forming was the best. Under the optimal parameter combination, the bench verification test was carried out. The error between the bench verification results and the simulation results is small, indicating that the model has high accuracy. The average opening time of the duck bill at a speed of 6 km/h is 0.45 s, which is much longer than the time required for cotton seeds to fall from the duck bill (0.11 s). It meets the requirements of high-speed cotton planting in China and facilitating advancements high-speed planter technology.

To solve the limitation of speed in the operation of air-suction cotton precision seeding devices, a new crawler-type precision on-film seeding device was designed using an extended duckbill hole-forming device to produce hole-forming belts and lateral seed collection. Coupling simulation of seeding, and analysis of drag force and movement speed of cotton seeds were conducted on EDEM-CFD. A mechanical model of the operation was established, and the effects of the suction hole diameter, pressure relief block length, and wind pressure on seeding performance were analyzed. Regression models between influencing factors and seeding performance indices were established using response surface methodology. The test data were analyzed using Design Expert 10.0.3. The influence rules for each factor on seeding performance were established. The factors affecting the seeding qualified index exhibited the following order: air pressure > pressure relief block length > suction hole diameter. The optimization goals included defining the maximum value of a qualified single-seed index and the minimum value of the missing index, and the best parameter combination was obtained based on a suction hole diameter of 3.624 mm, pressure relief block length of 63.369 mm, and wind pressure of 3.797 kPa. According to the actual test conditions, the parameters were revised to include a suction hole diameter of 3.6 mm, a relief block length of 63.4 mm, and wind (air) pressure of 3.8 kPa for verification tests. The actual qualified single-seed index is 94.87% ± 0.98 %, the missing index is 1.45% ± 0.32%, and the multiple index is 3.68% ± 0.62%. The difference from the predicted value is within 5%, indicating that this study can provide a reference for the structural design and optimization of crawler-type on-film precision cotton seeding devices.

Abstract Background Amyloid-related imaging abnormalities (ARIA) have been identified as the most common and serious adverse events resulting from pathological changes in the cerebral vasculature during several recent anti-amyloid-β (Aβ) immunotherapy trials. However, the precise cellular and molecular mechanisms underlying how amyloid immunotherapy enhances cerebral amyloid angiopathy (CAA)-mediated alterations in vascular permeability and microhemorrhages are not currently understood. Interestingly, brain perivascular macrophages have been implicated in regulating CAA deposition and cerebrovascular function however, further investigations are required to understand how perivascular macrophages play a role in enhancing CAA-related vascular permeability and microhemorrhages associated with amyloid immunotherapy. Methods In this study, we examined immune responses induced by amyloid-targeting antibodies and CAA-induced microhemorrhages using histology and gene expression analyses in Alzheimer’s disease (AD) mouse models and primary culture systems. Results In the present study, we demonstrate that anti-Aβ (3D6) immunotherapy leads to the formation of an antibody immune complex with vascular amyloid deposits and induces the activation of CD169+ perivascular macrophages. We show that macrophages activated by antibody mediated Fc receptor signaling have increased expression of inflammatory signaling and extracellular matrix remodeling genes such as Timp1 and MMP9 in vitro and confirm these key findings in vivo. Finally, we demonstrate enhanced vascular permeability of plasma proteins and recruitment of inflammatory monocytes around vascular amyloid deposits, which are associated with hemosiderin deposits from cerebral microhemorrhages, suggesting the multidimensional roles of activated perivascular macrophages in response to Aβ immunotherapy. Conclusions In summary, our study establishes a connection between Aβ antibodies engaged at CAA deposits, the activation of perivascular macrophages, and the upregulation of genes involved in vascular permeability. However, the implications of this phenomenon on the susceptibility to microhemorrhages remain to be fully elucidated. Further investigations are warranted to determine the precise role of CD169 + perivascular macrophages in enhancing CAA-mediated vascular permeability, extravasation of plasma proteins, and infiltration of immune cells associated with microhemorrhages.

Abstract Magnetic skyrmions with a well-defined spin texture have shown unprecedented potential for various spintronic applications owning to their topologically non-trivial and quasiparticle properties. To put skyrmions into practical technology, efficient manipulation, especially the inhibition of skyrmion Hall effect (SkHE) has been intensively pursued. In spite of the recent progress made on reducing SkHE in several substituted systems, such as ferrimagnets and synthetic antiferromagnets, the organized creation and current driven motion of skyrmions with negligible SkHE in ferromagnets remain challenging. Here, by embedding the [Co/Pd] multilayer into a surface acoustic wave (SAW) delay line where the longitudinal leaky SAW is excited to provide both the strain and thermal effect, we experimentally realized the ordered generation of magnetic skyrmions. The resultant current-induced skyrmions movement with negligible SkHE was observed, which can be attributed to the energy redistribution of the system during the excitation of SAW. Our findings open up an unprecedentedly new perspective for manipulating topological solitons, which could possibly trigger the future discoveries in skyrmionics and spin acousto-electronics.

Abstract Introduction Extrapolating long-term overall survival (OS) from shorter-term clinical trial data is key to health technology assessment in oncology. However, extrapolation using conventional methods is often subject to uncertainty. Using ciltacabtagene autoleucel (cilta-cel), a chimeric antigen receptor T-cell therapy for multiple myeloma, we used a flexible Bayesian approach to demonstrate use of external longer-term data to reduce the uncertainty in long-term extrapolation. Methods The pivotal CARTITUDE-1 trial (NCT03548207) provided the primary efficacy data for cilta-cel, including a 12-month median follow-up snapshot of OS. Longer-term (48-month median follow-up) survival data from the phase I LEGEND-2 study (NCT03090659) were also available. Twelve-month CARTITUDE-1 OS data were extrapolated in two ways: (1) conventional survival models with standard parametric distributions (uninformed), and (2) Bayesian survival models whose shape prior was informed from 48-month LEGEND-2 data. For validation, extrapolations from 12-month CARTITUDE-1 data were compared with observed 28-month CARTITUDE-1 data. Results Extrapolations of the 12-month CARTITUDE-1 data using conventional uninformed parametric models were highly variable. Using informative priors from the 48-month LEGEND-2 dataset, the ranges of projected OS at different timepoints were consistently narrower. Area differences between the extrapolation curves and the 28-month CARTITUDE-1 data were generally lower in informed Bayesian models, except for the uninformed log-normal model, which had the lowest difference. Conclusions Informed Bayesian survival models reduced variation of long-term projections and provided similar projections as the uninformed log-normal model. Bayesian models generated a narrower and more plausible range of OS projections from 12-month data that aligned with observed 28-month data. Trial Registration CARTITUDE-1 ClinicalTrials.gov identifier, NCT03548207. LEGEND-2 ClinicalTrials.gov identifier, NCT03090659, registered retrospectively on 27 March 2017, and ChiCTR-ONH-17012285.

BackgroundImmunotherapy, represented by immune checkpoint inhibitors (ICIs), is a major breakthrough in cancer treatment. Studies have reported that the use of ICIs is associated with an increase in the pulmonary artery to ascending aorta diameter (PAD/AoD) ratio. However, the impact of PAD/AoD ratio progression on the prognosis of patients is unclear.MethodsThis retrospective cohort study included patients with stage III or IV non-small cell lung cancer (NSCLC) treated with ICIs at the Wuhan Union Hospital between March 1, 2020, and September 1, 2022. The baseline and post-treatment PAD/AoD ratios of patients were evaluated through chest CT scans. The primary outcome of this study was overall survival (OS), while the secondary outcomes included progression-free survival (PFS), objective response rate (ORR) and disease control rate (DCR).ResultsThe PAD/AoD ratio increased after the initiation of ICIs (from 0.75 to 0.78; P < 0.001). A total of 441 patients were divided into severe group (n=221) and non-severe group (n=220) according to the median increase of PAD/AoD ratio (1.06). Compared with the non-severe group, the severe group had a lower DCR (87.8% vs. 96.0%, P = 0.005) and ORR (87.5% vs. 96.0%, P = 0.063). Over the entire duration of follow-up (median 22.0 months), 85 (38.5%) patients in the severe group and 30 (7.3%) patients in the non-severe group died. An increased PAD/AoD ratio was associated with shorter PFS (Hazard ratio (HR): 1.48 [95% CI, 1.14 to 1.93]; P = 0.003) and OS (HR: 3.50 [95% CI, 2.30 to 5.30]; P < 0.001). Similar results were obtained across subgroups.ConclusionsICI treatment exacerbates an increase in the PAD/AoD ratio in patients with cancer, and greater increase in the PAD/AoD ratio was associated with a worse prognosis. PAD/AoD ratio could be a biomarker to stratify prognosis of NSCLC patients treated with ICIs.

A multi-shell extension of the simplest formulation of the interacting boson model that appends parity-conserving (2ħω) energy excitations to the non-extended theory is proffered. From a physical perspective this extension links the system's low-lying configurations to higher-lying multiple one-particle-one-hole (1p-1h) excitation modes that are in part tethered to the system's isoscalar giant monopole and quadrupole resonances. An application of the theory to low-lying energy levels and known B(E0) and B(E2) values of 152Sm shows that the results obtained with the extension are better than those without the extension.

Microangiopathy is the most basic pathological manifestation of lupus nephritis (LN), and glomerular endothelial cells (GECs) injury is an important pathological mechanism. LN patients with microangiopathy are prone to steroid resistance (SR). Our previous studies confirmed that Panax notoginseng saponins (PNS) could reverse SR by downregulating the expression of P-gp in SR lymphocytes of LN mice (SLCsL/S). However, the mechanism of how circulating lymphocytes transmit SR information to GECs and thus affect the efficacy of kidney treatment is not clear. Recent studies have found that exosomes (exos) are an important carrier for intercellular bioactive substance communication. But whether exosomes derived from SLCsL/S mediate SR in GECs and PNS interventions. To solve this problem, Exosomes isolated from SLCsL/S were characterized, and in vitro cell coculture was further conducted to investigate the effect of SLCsL/S-derived exosomes in the SR of GECs and PNS intervention. Sequencing was used to define the exosomal miRNA expression profiling of SR GECs. Moreover, the in vivo experiments were performed through the injection of exosomes extracted from SLCsL/S into the tail vein of mice.Our research results indicate that exosomes derived from SLCsL/S could transmit SR information to GECs and lead to the aggravation of inflammatory injury through conferring P-gp, which were negated by a P-gp inhibitor. Further, we identified higher levels of exosomal miR-125b-5p from SR GECs were associated with SR in LN and could serve as biomarker for the risk of developing SR. PNS could reverse the SR of GECs and alleviate inflammatory injury by suppressing exosomal P-gp levels from lymphocytes to GECs in vitro and in vivo. However, the specific molecular mechanism by which PNS regulates exosomes has not yet been elucidated, and we need to conduct more in-depth research in the future. Overall, Our findings suggest that exosomal transfer of SLCsL/S derived P-gp confer SR to GECs, and PNS can target exosome communication to reverse SR in LN, which provides new ideas and a scientific basis for improving the clinical efficacy of traditional Chinese medicine in the treatment of refractory LN.

Two-dimensional ferromagnetic (2DFM) semiconductors (metals, half-metals, and so on) are important materials for next-generation nano-electronic and nano-spintronic devices. However, these kinds of materials remain scarce, “trial and error” experiments and calculations are both time-consuming and expensive. In the present work, in order to obtain the optimal 2DFM materials with strong magnetization, a machine learning (ML) framework was established to search the 2D material space containing over 2417 samples and identified 615 compounds whose magnetic orders were then determined via high-throughput first-principles calculations. With the adoption of ML algorithms, two classification models and a regression model were trained. The interpretability of the regression model was evaluated through Shapley Additive exPlanations (SHAP) analysis. Unexpectedly, it is found that Cr2NF2 is a potential antiferromagnetic ferroelectric 2D multiferroic material. More importantly, 60 novel 2DFM candidates were predicted, and among them, 13 candidates have magnetic moments of > 7μB. Os2Cl8, Fe3GeSe2, and Mn4N3S2 were predicted to be novel 2DFM semiconductors, metals, and half-metals, respectively. With the adoption of the ML approach in the current work, the prediction of 2DFM materials with strong magnetization can be accelerated, and the computation time can be drastically reduced by more than one order of magnitude.

The monoclinic CuO has a natural tendency to grow into sheet-like structures from alkaline solutions without the need for any specialized reaction conditions or structural directing agents. We demonstrate this growth habit of CuO by heterogeneously nucleating it onto Ni foam substrate from just the ammonical solutions of Cu salts. The growth kinetics were found to be fast and, dense, interlaced thin films with an average sheet width of 20 nm can be grown by simply controlling the degree of supersaturation of the solution. Strongly adhered films with thicknesses up-to 5 μm were deposited from three different Cu salt solutions. Due to faster growth kinetics, growth time has little effect on both the film and nanosheet thickness. Detailed structural and compositional characterizations of the CuO nanosheets were made using FESEM, HRTEM, SAED, XRD and, XPS. The utility of the grown CuO nanosheets is demonstrated as a ready to use electrode for electrochemical supercapacitors. Specific capacitance in excess of 498 F/g was calculated from the Galvanostatic charge–discharge measurements collected at a current density of 0.5 A/g.