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Abstract Background Unfavorable social determinants of health (SDoH) are associated with depression. Both depression and SDoH are associated with increased risks of mortality, but their joint impacts on mortality risks remain unclear. This study aims to investigate the joint effects of depression and SDoH on mortality risk. Methods Utilizing data from the National Health and Nutrition Examination Survey (NHANES) 2007–2018, 24,727 adults aged ≥ 20 were included. SDoH was assessed based on the 5 domains outlined in the U.S. Healthy People 2030 initiative. The cumulative number of unfavorable SDoH was calculated and categorized into low and high burden levels. The definition of depression was based on the Patient Health Questionnaire-9 (PHQ-9) scores ≥ 10. The joint associations of depression and SDoH with all-cause, cardiovascular disease (CVD), and cancer mortality were examined using Cox proportional hazard models. Results We identified 2,377 (6.84%) all-cause deaths (CVD, 717; cancer, 606) during a median follow-up of 7.0 years. Depression was associated with increased mortality risks, and SDoH could explain 32.4% and 28.3% of the associations between depression and all-cause and CVD mortality, respectively. No significant interactions were observed between depression and SDoH on mortality. However, a low burden of unfavorable SDoH reduced the risk of all-cause mortality in depressed patients (hazard ratio [HR], 0.58; 95% confidence interval [CI]: 0.36–0.92). In the joint analysis, individuals with both depression and a high burden of unfavorable SDoH had the highest risks of all-cause and CVD mortality. Specifically, compared with individuals with no depression and a low burden of unfavorable SDoH, those with depression and a high burden of unfavorable SDoH had higher risks of all-cause (HR, 2.52; 95% CI: 2.01–3.18) and CVD mortality (HR, 2.79; 95% CI: 1.95–3.99). Conclusion Adults with both depression and a high burden of unfavorable SDoH had the highest risks of all-cause mortality and CVD mortality. The result suggests considering depression and SDoH jointly in developing targeted intervention strategies to improve survival outcomes and calls for larger cohort studies and clinical trials to validate our findings.

BackgroundPituitary tumors (PTs) are common benign intracranial tumors. Investigating the metabolites in serum and cerebrospinal fluid in PTs is essential to understanding the underlying biological mechanisms and identifying new biomarkers and therapeutic strategies.MethodsWe used the GWAS dataset of PTs from the FinnGen database, a dataset of 486 plasma metabolites from the GWAS catalog database, and a dataset of 338 cerebrospinal fluid (CSF) metabolites from the WADRC and WRAP study collections. An inverse variance weighting (IVW) approach was utilized as the mainly method to investigate causality between metabolites and PTs, supplemented by four complementary methods to strengthen our findings. Additionally, we utilized several sensitivity methods to guarantee the robustness of our findings.ResultsThe study identified 17 plasma metabolites and 10 CSF metabolites related to PTs. Among these, 11 metabolites indicated a significant positive causality with PTs, while 16 displayed a remarkable negative causality. Particularly, plasma levels of 3-dehydrocarnitine (OR = 2.73, 95% CI = 1.55–4.83, P = 0.001) and acetylcarnitine (OR = 0.35, 95% CI = 0.19–0.63, P = 0.001) were found to be significant exposure factors for PTs. Multiple sensitivity analyses confirm the robustness of the results. The study found no evidence of a reverse causality between PTs and the plasma levels of 3-dehydrocarnitine and acetylcarnitine.ConclusionsThe present study identified 27 metabolites associated with the incidence of PTs, among which 3-dehydrocarnitine and acetylcarnitine are the most noteworthy.

BackgroundEarlier researches have demonstrated that ischemic stroke, metabolic factors, and associated medications may influence the risk of epilepsy. Nevertheless, the causality between these elements and epilepsy remains inconclusive. This study aims to examine whether ischemic stroke, metabolic factors, and related medications affect the overall risk of epilepsy.MethodsWe used single nucleotide polymorphisms associated with ischemic stroke, hypothyroidism, hypertension, blood glucose levels, high cholesterol, serum 25-Hydroxyvitamin D levels, testosterone, HMG CoA reductase inhibitors, and beta-blocking agents as instrumental variables in a Mendelian randomization technique to investigate causality with epilepsy. Multiple sensitivity methods were performed to evaluate pleiotropy and heterogeneity.ResultsThe IVW analysis revealed positive associations between ischemic stroke (OR = 1.29; p = 0.020), hypothyroidism (OR = 1.05; p = 0.048), high blood pressure (OR = 1.10; p = 0.028), high cholesterol (OR = 1.10; p = 0.024), HMG CoA reductase inhibitors (OR = 1.19; p = 0.003), beta-blocking agents (OR = 1.20; p = 0.006), and the risk of epilepsy. Conversely, blood glucose levels (OR = 0.79; p = 0.009), serum 25-Hydroxyvitamin D levels (OR = 0.75; p = 0.020), and testosterone (OR = 0.62; p = 0.019) exhibited negative associations with the risk of epilepsy. Sensitivity analyses confirmed the robustness of these findings (p > 0.05).ConclusionOur research suggests that ischemic stroke, hypothyroidism, high blood pressure, high cholesterol, HMG CoA reductase inhibitors, and beta-blockers may increase the risk of epilepsy, whereas serum 25-Hydroxyvitamin D levels and blood glucose levels may reduce the risk.

ABSTRACT Background The association among coronary heart disease, ischemic stroke, and hydrocephalus remains ambiguous. Objectives There is a need for a Mendelian randomization study to evaluate the underlying causality between coronary heart disease, ischemic stroke, and hydrocephalus. Methods The data source utilized genome‐wide association studies, employing a threshold of p

Abstract Osteoarthritis is a highly prevalent progressive joint disease that still requires an optimal therapeutic approach. Intermittent fasting is an attractive dieting strategy for improving health. Here this study shows that intermittent fasting potently relieves medial meniscus (DMM)‐ or natural aging‐induced osteoarthritic phenotypes. Osteocytes, the most abundant bone cells, secrete excess neuropeptide Y (NPY) during osteoarthritis, and this alteration can be altered by intermittent fasting. Both NPY and the NPY‐abundant culture medium of osteocytes (OCY‐CM) from osteoarthritic mice possess pro‐inflammatory, pro‐osteoclastic, and pro‐neurite outgrowth effects, while OCY‐CM from the intermittent fasting‐treated osteoarthritic mice fails to induce significant stimulatory effects on inflammation, osteoclast formation, and neurite outgrowth. Depletion of osteocyte NPY significantly attenuates DMM‐induced osteoarthritis and abolishes the benefits of intermittent fasting on osteoarthritis. This study suggests that osteocyte NPY is a key contributing factor in the pathogenesis of osteoarthritis and intermittent fasting represents a promising nonpharmacological antiosteoarthritis method by targeting osteocyte NPY.

Aging increases the risks of various diseases and the vulnerability to death. Cellular senescence is a hallmark of aging that contributes greatly to aging and aging-related diseases. This study demonstrates that extracellular vesicles from human urine-derived stem cells (USC-EVs) efficiently inhibit cellular senescence in vitro and in vivo. The intravenous injection of USC-EVs improves cognitive function, increases physical fitness and bone quality, and alleviates aging-related structural changes in different organs of senescence-accelerated mice and natural aging mice. The anti-aging effects of USC-EVs are not obviously affected by the USC donors’ ages, genders, or health status. Proteomic analysis reveals that USC-EVs are enriched with plasminogen activator urokinase (PLAU) and tissue inhibitor of metalloproteinases 1 (TIMP1). These two proteins contribute importantly to the anti-senescent effects of USC-EVs associated with the inhibition of matrix metalloproteinases, cyclin-dependent kinase inhibitor 2A (P16INK4a), and cyclin-dependent kinase inhibitor 1A (P21cip1). These findings suggest a great potential of autologous USC-EVs as a promising anti-aging agent by transferring PLAU and TIMP1 proteins.

The fusion of low-spatial-resolution hyperspectral image and high-spatial-resolution multispectral image provides an effective method to obtain high-spatial-resolution hyperspectral image. However, existing hybrid fusion architectures combining convolutional neural networks (CNNs) and transformers face significant challenges. Sequential approaches struggle with simultaneous local and global modeling, while parallel approaches often result in information redundancy. In this article, to meet diverse information demands at different layers, we propose a novel multiscale inception mixer transformer network (MIMFormer), a multiscale hybrid network based on the Inception structure integrating CNN and transformer. The core of this network is the multiscale spatial transformer (MST) structure, which enhances the detail richness of fused images by integrating local and global information at various scales. The inception spatial–spectral mixer (ISSM) module within the MST leverages an Inception architecture and employs a spectral splitting mechanism to regulate spectral channel counts across different branches. This design allows the ISSM module to efficiently extract local spatial–spectral features through convolution and max pooling, while global features are captured using a self-attention mechanism, ensuring comprehensive feature fusion across spectral groups. Experimental results on three benchmark datasets and one real remote sensing dataset demonstrate that MIMFormer outperforms ten advanced fusion methods.

Abstract Geometric deep learning has been revolutionizing the molecular modeling field. Despite the state-of-the-art neural network models are approaching ab initio accuracy for molecular property prediction, their applications, such as drug discovery and molecular dynamics (MD) simulation, have been hindered by insufficient utilization of geometric information and high computational costs. Here we propose an equivariant geometry-enhanced graph neural network called ViSNet, which elegantly extracts geometric features and efficiently models molecular structures with low computational costs. Our proposed ViSNet outperforms state-of-the-art approaches on multiple MD benchmarks, including MD17, revised MD17 and MD22, and achieves excellent chemical property prediction on QM9 and Molecule3D datasets. Furthermore, through a series of simulations and case studies, ViSNet can efficiently explore the conformational space and provide reasonable interpretability to map geometric representations to molecular structures.

The fusion of low-resolution hyperspectral images (LR-HSI) with high-resolution multispectral images (HR-MSI) provides a cost-effective approach to obtaining high-resolution hyperspectral images (HR-HSI). Existing methods primarily based on convolutional neural networks (CNNs) struggle to capture global features and do not adequately address the significant scale and spectral resolution differences between LR-HSI and HR-MSI. To tackle these challenges, our novel FCSwinU network leverages the spectral fast Fourier convolution (SFFC) module for spectral feature extraction and utilizes the Swin Transformer’s self-attention mechanism for multi-scale global feature fusion. FCSwinU employs a UNet-like encoder–decoder framework to effectively merge spatiospectral features. The encoder integrates the Swin Transformer feature abstraction module (SwinTFAM) to encode pixel correlations and perform multi-scale transformations, facilitating the adaptive fusion of hyperspectral and multispectral data. The decoder then employs the Swin Transformer feature reconstruction module (SwinTFRM) to reconstruct the fused features, restoring the original image dimensions and ensuring the precise recovery of spatial and spectral details. Experimental results from three benchmark datasets and a real-world dataset robustly validate the superior performance of our method in both visual representation and quantitative assessment compared to existing fusion methods.

Anthracycline drugs mainly include doxorubicin, epirubicin, pirarubicin, and aclamycin, which are widely used to treat a variety of malignant tumors, such as breast cancer, gastrointestinal tumors, lymphoma, etc. With the accumulation of anthracycline drugs in the body, they can induce serious heart damage, limiting their clinical application. The mechanism by which anthracycline drugs cause cardiotoxicity is not yet clear. This review provides an overview of the different types of cardiac damage induced by anthracycline-class drugs and delves into the molecular mechanisms behind these injuries. Cardiac damage primarily involves alterations in myocardial cell function and pathological cell death, encompassing mitochondrial dysfunction, topoisomerase inhibition, disruptions in iron ion metabolism, myofibril degradation, and oxidative stress. Mechanisms of uptake and transport in anthracycline-induced cardiotoxicity are emphasized, as well as the role and breakthroughs of iPSC in cardiotoxicity studies. Selected novel cardioprotective therapies and mechanisms are updated. Mechanisms and protective strategies associated with anthracycline cardiotoxicity in animal experiments are examined, and the definition of drug damage in humans and animal models is discussed. Understanding these molecular mechanisms is of paramount importance in mitigating anthracycline-induced cardiac toxicity and guiding the development of safer approaches in cancer treatment.

Abstract Endothelial cells (ECs) and bone marrow stromal cells (BMSCs) play crucial roles in supporting hematopoiesis and hematopoietic regeneration. However, whether ECs are a source of BMSCs remains unclear. Here, we evaluate the contribution of endothelial-to-mesenchymal transition to BMSC generation in postnatal mice. Single-cell RNA sequencing identifies ECs expressing BMSC markers Prrx1 and Lepr; however, this could not be validated using Prrx1-Cre and Lepr-Cre transgenic mice. Additionally, only a minority of BMSCs are marked by EC lineage tracing models using Cdh5-rtTA-tetO-Cre or Tek-CreERT2. Moreover, Cdh5 + BMSCs and Tek + BMSCs show distinct spatial distributions and characteristic mesenchymal markers, suggestive of their origination from different progenitors rather than CDH5+ TEK+ ECs. Furthermore, myeloablation induced by 5-fluorouracil treatment does not increase Cdh5 + BMSCs. Our findings indicate that ECs hardly convert to BMSCs during homeostasis and myeloablation-induced hematopoietic regeneration, highlighting the importance of using appropriate genetic models and conducting careful data interpretation in studies concerning endothelial-to-mesenchymal transition.

Objective: Joint stiffness results from the coupling of the nervous system and joint mechanics, and thus stiffness is a comprehensive representation of joint stability. It has been reported that moxibustion can alleviate general weakness and fatigue symptoms and subsequently may influence joint stiffness. This study investigated whether moxibustion could enhance knee joint stiffness in recreational athletes pre- and post-fatigue. Methods: Eighteen participants were randomized into intervention (5 males: 20.6 ± 1.5 yr; 4 females: 20.8 ± 1.5 yr) and control groups (5 males: 19.4 ± 0.9 yr; 4 females: 20.5 ± 0.6 yr). The intervention group received indirect moxibustion applied to acupoints ST36 (bilateral) and CV4 for 30 min every other day for 4 consecutive weeks. The control group maintained regular exercise without moxibustion. Peak torque (PT) of right knee extensor, relaxed and contracted muscle stiffness (MS) of vastus lateralis, and knee extensor musculoarticular stiffness (MAS) was assessed with an isokinetic dynamometer (IsoMed 2000), myometer, and free oscillation technique, respectively. Measurements were taken at three time points: pre-intervention, post-intervention/pre-fatigue, and post-fatigue. Results: MAS (P = 0.006) and PT (P = 0.007) in the intervention group increased more from pre-to post-intervention compared with the control group. Post-fatigue MAS (P = 0.016) and PT (P = 0.031) increased more in the intervention group than in the control group. Conclusion: Moxibustion enhanced PT and knee MAS, suggesting that this intervention could be used in injury prevention and benefit fatigue resistance in young recreational athletes.

Plant protein-based foods have become dietary preferences worldwide, and the quality of this food group is highly associated with the ingredients used. This study investigated the effects of incorporating caramel, tomato powder, and carrot powder on the product quality of soy protein-based meat patties (SPMPs). The color, total phenolic content (TPC), antioxidant activity, lipid oxidation, and texture profile of uncooked and cooked soy protein meat patties were analyzed. Among the cooked SPMPs, caramel SPMPs exhibited the lowest color difference (ΔE) values, and the ΔE value of tomato SPMPs was lower than that of carrot SPMPs, indicating that caramel has the best color stability, and the tomato experienced less color change than the carrot during cooking. Notably, carrot SPMPs exhibited lower color stability during refrigeration storage than the others. Both carrot and tomato powders increased the total phenolic content (TPC) and antioxidant stability and inhibited lipid oxidation in SPMPs during cooking. However, tomato SPMPs exhibited higher TPC values and greater antioxidant stability compared to carrot SPMPs. The addition of caramel and carrot powders decreased the hardness of raw SPMPs, but tomato powder increased the hardness. The texture profile of tomato SPMPs was more affected by the cooking process compared to caramel and carrot SPMPs. This study showed that incorporating both carrot and tomato powders positively influenced the quality characteristics of SPMPs compared to caramel powder, however, tomato powder exhibited superior efficacy.

Aimed at the problem of human–machine interaction between patients and robots in the process of using rehabilitation robots for rehabilitation training, this paper proposes a human–machine interactive control method based on an independently developed upper limb rehabilitation robot. In this method, the camera is used as a sensor, the human skeleton model is used to analyse the moving image, and the key points of the human body are extracted. Then, the three-dimensional coordinates of the key points of the human arm are extracted by depth estimation and spatial geometry, and then the real-time motion data are obtained, and the control instructions of the robot are generated from it to realise the real-time interactive control of the robot. This method can not only improve the adaptability of the system to individual patient differences, but also improve the robustness of the system, which is less affected by environmental changes. The experimental results show that this method can realise real-time control of the rehabilitation robot, and that the robot assists the patient to complete the action with high accuracy. The results show that this control method is effective and can be applied to the fields of robot control and robot-assisted rehabilitation training.

Abstract The presented paper proposes a photovoltaic module hot spot detection algorithm based on YOLOv8‐BCB. The algorithm addresses issues such as component efficiency degradation and poor contact in long‐term operation of PV systems, with a focus on the hot spot effect’. To achieve rapid detection and localization of small targets in complex scenes, the algorithm incorporates the Weighted Bi‐directional Feature Pyramid Network (BiFPN) into YOLOv8. Additionally, a lightweight upsampling operator called Content‐Aware ReAssembly of FEatures (CARAFE) is used to reduce the detection load on the unmanned aerial vehicle (UAV) detection system. The BiFormer attention mechanism is also integrated into the C2f module to better capture dependencies between sequences and reduce background interference. To highlight the superiority of the authors’ algorithm compared to other high‐quality algorithms, the authors conducted comparative experiments on the same dataset. The YOLOv8‐BCB algorithm surpasses the SSD, faster‐cnn, and RetinaNet algorithms in both accuracy and detection speed. It achieves a precision of 97.1% and a recall rate of 94.9%, with an FPS of 110. The result is a target detection algorithm that is both fast and accurate.

Abstract Background While transcription factor (TF) regulation is known to play an important role in osteoblast development, differentiation, and bone metabolism, the molecular features of TFs in human osteoblasts at the single-cell resolution level have not yet been characterized. Here, we identified modules (regulons) of co-regulated genes by applying single-cell regulatory network inference and clustering to the single-cell RNA sequencing profiles of human osteoblasts. We also performed cell-specific network (CSN) analysis, reconstructed regulon activity-based osteoblast development trajectories, and validated the functions of important regulons both in vivo and in vitro. Results We identified four cell clusters: preosteoblast-S1, preosteoblast-S2, intermediate osteoblasts, and mature osteoblasts. CSN analysis results and regulon activity-based osteoblast development trajectories revealed cell development and functional state changes of osteoblasts. CREM and FOSL2 regulons were mainly active in preosteoblast-S1, FOXC2 regulons were mainly active in intermediate osteoblast, and RUNX2 and CREB3L1 regulons were most active in mature osteoblasts. Conclusions This is the first study to describe the unique features of human osteoblasts in vivo based on cellular regulon active landscapes. Functional state changes of CREM, FOSL2, FOXC2, RUNX2, and CREB3L1 regulons regarding immunity, cell proliferation, and differentiation identified the important cell stages or subtypes that may be predominantly affected by bone metabolism disorders. These findings may lead to a deeper understanding of the mechanisms underlying bone metabolism and associated diseases.

Background Kümmell's disease (KD) is a rare clinical entity characterized by delayed post‐traumatic vertebral body collapse, in which an intravertebral vacuum cleft (IVC) is formed. The patient sustained a minor spinal trauma, and their spine X‐ray examinations were negative. However, after an asymptomatic period of months, they developed recurrent back pain because of the progressive vertebral collapse of the affected spine. However, no imaging examination could confirm the magnetic resonance imaging (MRI)‐negative initial spinal trauma followed by delayed vertebral collapse with IVC. Case Presentation We report a case of KD occurring in a 66‐year‐old postmenopausal patient whose lumbar MRI on sagittal planes were immediately performed following the initial trauma (a ground‐level fall) and revealed that the vertebral integrity or connectivity was not interrupted and the marrow signal was even. After an asymptomatic period of 8 months, the back pain reappeared and progressively exacerbated. The wedge‐shaped change in the T11 vertebra with an IVC was confirmed by lumbar computed tomography and MRI. Finally, KD was diagnosed following extensive routine hematological and biochemical workups. Percutaneous kyphoplasty was performed to relieve her back pain by restoring her vertebral stability. Conclusions We confirmed that the OVF was not the first step in the KD sequence, and the IVC ‐ KD ‐ could from an initial MRI‐negative spine trauma.

Abstract We investigate obstacles of superluminal “warp drive” travels from interactions with interstellar matter and from curvature effects. The effect of collision of interstellar dust particles and photons with the spacecraft will all lead to a pressure proportional to the apparent velocity of the spaceship $$v_s$$ v s . The force exerted on the spacecraft from the curvature effect has two non-trivial components. The radial and longitudinal components scales as $$v_s^2$$ v s 2 and $$v_s^4$$ v s 4 respectively. The above obstacles become increasingly important when the spaceship travels at high superluminal speeds.

Abstract With many frameworks based on message passing neural networks proposed to predict molecular and bulk properties, machine learning methods have tremendously shifted the paradigms of computational sciences underpinning physics, material science, chemistry, and biology. While existing machine learning models have yielded superior performances in many occasions, most of them model and process molecular systems in terms of homogeneous graph, which severely limits the expressive power for representing diverse interactions. In practice, graph data with multiple node and edge types is ubiquitous and more appropriate for molecular systems. Thus, we propose the heterogeneous relational message passing network (HermNet), an end-to-end heterogeneous graph neural networks, to efficiently express multiple interactions in a single model with ab initio accuracy. HermNet performs impressively against many top-performing models on both molecular and extended systems. Specifically, HermNet outperforms other tested models in nearly 75%, 83% and 69% of tasks on revised Molecular Dynamics 17 (rMD17), Quantum Machines 9 (QM9) and extended systems datasets, respectively. In addition, molecular dynamics simulations and material property calculations are performed with HermNet to demonstrate its performance. Finally, we elucidate how the design of HermNet is compatible with quantum mechanics from the perspective of the density functional theory. Besides, HermNet is a universal framework, whose sub-networks could be replaced by other advanced models.

BackgroundWhile osteoimmunology interactions between the immune and skeletal systems are known to play an important role in osteoblast development, differentiation and bone metabolism related disease like osteoporosis, such interactions in either bone microenvironment or peripheral circulation in vivo at the single-cell resolution have not yet been characterized.MethodsWe explored the osteoimmunology communications between immune cells and osteoblastic lineage cells (OBCs) by performing CellphoneDB and CellChat analyses with single-cell RNA sequencing (scRNA-seq) data from human femoral head. We also explored the osteoimmunology effects of immune cells in peripheral circulation on skeletal phenotypes. We used a scRNA-seq dataset of peripheral blood monocytes (PBMs) to perform deconvolution analysis. Then weighted gene co-expression network analysis (WGCNA) was used to identify monocyte subtype-specific subnetworks. We next used cell-specific network (CSN) and the least absolute shrinkage and selection operator (LASSO) to analyze the correlation of a gene subnetwork identified by WGCNA with bone mineral density (BMD).ResultsWe constructed immune cell and OBC communication networks and further identified L-R genes, such as JAG1 and NOTCH1/2, with ossification related functions. We also found a Mono4 related subnetwork that may relate to BMD variation in both older males and postmenopausal female subjects.ConclusionsThis is the first study to identify numerous ligand-receptor pairs that likely mediate signals between immune cells and osteoblastic lineage cells. This establishes a foundation to reveal advanced and in-depth osteoimmunology interactions to better understand the relationship between local bone microenvironment and immune cells in peripheral blood and the impact on bone phenotypes.

Abstract Tamoxifen resistance (TamR) prevents ER-positive breast cancer patients from benefitting from endocrine therapy, and miR-221 or miR-222 plays vital roles in inducing TamR. In this study, we designed synthetic sponges to reverse TamR by targeting these two miRs. First, we established a tamoxifen resistant breast cancer cell line (MCF-7TamR), we verified the high expressing level of these two miRs in TamR cells. miR-221 or miR-222 inhibitors rendered MCF-7TamR cells responsive to tamoxifen. Next, we designed a miR-221/222 sponge, which contains total 8 multi-antisense binding sites (MBSs) for these two onco-miRs, and inserted it into CMV promoter- or hTERT promoter-driven expressing vectors. After transfected miR-221/222 sponge expressing vectors into MCF-7TamR cells, we identified a strong interaction between miR-221/222 sponge and endogenous miR-221 or miR-222 by RNA pulldown assay. We also found that miR-221/222 sponge restored the expression of ERα and PTEN, arrested cells in G1 phase, and finally resulted in reduced cell growth and cell migration. Notably, miR-221/222 sponge expressing cells abrogates tamoxifen resistance through restoring the expression of ERα, suggesting that miR-221/222 sponge gene therapy especially driven by tumor specific promoter could provide an effective therapeutic approach against TamR in breast cancer.

The shape of corn seeds not being spherical affects their mobility. This study focuses on modeling the typically shaped corn seeds and calibrating the coefficient of rolling friction for different shape types to improve simulation reliability. By analyzing the corn seed shape characteristics and size statistics, this study establishes a classification system that enables the determination of the average value and quantity of different types of corn seed using the spherical granule cluster method. The discrete element method is used to model simplified corn models, and contact parameters are validated through two types of repose angle and a seed metering experiment. In the collapse repose experiment, the relative error between the simulation and the experiment was only 0.72%, while the relative error in another repose experiment was 0.2%. The verification experiment for the metering of seeds showed that the relative error between the simulation and the experiment was below 15% at both low and high speeds, and the multi-grain rate error was less than 10%. This shows that the method proposed in this paper is somewhat accurate.

Abstract Axillary reverse mapping (ARM) is a technique to identify arm lymphatic drainage during axillary lymph node dissection (ALND). This study compared the feasibility of ARM using indocyanine green (ICG) or methylene blue (MB), and accessed the oncologic safety of the procedure. Overall, 158 patients qualified for ALND were enrolled. The characteristics of ARM‐identified nodes were recorded with ICG (n = 78) or MB (n = 80) visualization. Fine‐needle aspiration cytology (FNAC) of the nodes were performed and validated by histologic analysis. The nodal identification rate in the ICG group significantly surpassed that of the MB group (87.2% vs 52.5%, P

Objective The present study explored the effects of grape seed procyanidin extract (GSPE) on rumen fermentation, methane production and archaeal communities in vitro. Methods A completely randomized experiment was conducted with in vitro incubation in a control group (CON, no GSPE addition; n = 9) and the treatment group (GSPE, 1 mg/bottle GSPE, 2 g/kg dry matter; n = 9). The methane and volatile fatty acid concentrations were determined using gas chromatography. To explore methane inhibition after fermentation and the response of the ruminal microbiota to GSPE, archaeal 16S rRNA genes were sequenced by MiSeq high-throughput sequencing. Results The results showed that supplementation with GSPE could significantly inhibit gas production and methane production. In addition, GSPE treatment significantly increased the proportion of propionate, while the acetate/propionate ratio was significantly decreased. At the genus level, the relative abundance of Methanomassiliicoccus was significantly increased, while the relative abundance of Methanobrevibacter decreased significantly in the GSPE group. Conclusion In conclusion, GSPE is a plant extract that can reduce methane production by affecting the structures of archaeal communities, which was achieved by a substitution of Methanobrevibacter with Methanomassiliicoccus.

An experimental study was carried out on the ignition characteristics of the HAN/(Emim)(EtSO4) (hydroxylammonium nitrate and 1-ethyl-3-methyl-imidazolium ethyl sulfate) dual-mode ionic liquid monopropellant in chemical propulsion mode in model thrusters. Firstly, a model thruster with a detachable convergent nozzle was designed and fabricated. Secondly, catalytic ignition experiments at different flow rates were carried out in atmosphere and in high chamber pressure environment, respectively, using a model thruster, with and without the convergent nozzle. During the catalytic ignition process, measurement methods such as thermocouple, pressure sensor, and flue gas analyzer were employed to obtain the temperature at different depths of the catalytic bed, the pressure of the combustion chamber, and the concentration variations of gaseous products CO, CO2, CH4, SO2, NO, and NO2. Then the three characteristic stages of water evaporation, HAN decomposition, and (Emim)(EtSO4) combustion were analyzed at the initiation time, and the reaction characteristics in the process of the catalytic ignition were analyzed. In addition, the composition and concentration of the combustion products at equilibrium were theoretically calculated. The effects of temperature and pressure on the concentrations of five main gaseous products were studied. Finally, the exhaust gas of the three groups of catalytic ignition experiments under different pressure environments was separately collected and measured with gas chromatography (GC) when the experiments approached equilibrium, the result of which roughly agrees with the theoretical calculations. These results are of great significance for exploring the chemical propulsion of the dual-mode ionic liquid propellant and understanding its physical catalytic combustion mechanisms.

Background: Recently, single-cell RNA sequencing (scRNA-seq) technology was increasingly used to study transcriptomics at a single-cell resolution, scRNA-seq analysis was complicated by the “dropout”, where the data only captures a small fraction of the transcriptome. This phenomenon can lead to the fact that the actual expressed transcript may not be detected. We previously performed osteoblast subtypes classification and dissection on freshly isolated human osteoblasts. Materials and Methods: Here, we used the scImpute method to impute the missing values of dropout genes from a scRNA-seq dataset generated on freshly isolated human osteoblasts. Results: Based on the imputed gene expression patterns, we discovered three new osteoblast subtypes. Specifically, these newfound osteoblast subtypes are osteoblast progenitors, and two undetermined osteoblasts. Osteoblast progenitors showed significantly high expression of proliferation related genes (FOS, JUN, JUNB and JUND). Analysis of each subtype showed that in addition to bone formation, these undetermined osteoblasts may involve osteoclast and adipocyte differentiation and have the potential function of regulate immune activation. Conclusions: Our findings provided a new perspective for studying the osteoblast heterogeneity and potential biological functions of these freshly isolated human osteoblasts at the single-cell level, which provides further insight into osteoblasts subtypes under various (pathological) physiological conditions.

In the dry areas of Northwest China, cavity planters with vertical insertions are used for seeding on film. Due to the uncertain mechanism between cavity planters and maize seeds and soil, research on the cavity planter has been slow. Several theoretical and experimental methods have been developed to investigate the interaction between the cavity planter and maize seeds in soil. These methods enable exploration of the mechanism to reduce soil disturbance and improve seeding performance. However, these methods are unable to predict the dynamic force of tools and soil behavior because of non-linear soil properties. A simulation experiment was conducted using the DEM-MBD coupling method to explore soil disturbance caused by cavity seeders and the resistance to entry. Additionally, the effect of the maize shape and the cavity planter motion on the seed number qualification and the empty cavity rate was investigated. It was proposed that the inverted hook be used to prevent the movement of maize seeds up and down in cavity seeders, thereby improving seed filling performance. Simulations and experiments were conducted, and the results showed that the average empty cavity rate and the seed number qualification were 2.0% and 91.3%, respectively, which met the requirements of the maize sowing standards.

ObjectiveAchieving negative resection margin is critical but challenging in breast-conserving surgery. Fluorescence-guided surgery allows the surgeon to visualize the tumor bed in real-time and to facilitate complete resection. We envisioned that intraoperative real-time fluorescence imaging with a human serum albumin decorated indocyanine green probe could enable complete surgical removal of breast cancer in a mouse model.MethodsWe prepared the probe by conjugating indocyanine green (ICG) with human serum albumin (HSA). In vitro uptake of the HSA-ICG probe was compared between human breast cancer cell line MDA-MB-231 and normal breast epithelial cell line MCF 10A. In vivo probe selectivity for tumors was examined in nude mice bearing MDA-MB-231-luc xenografts and the FVB/N-Tg (MMTV-PyMT) 634Mul/J mice model with spontaneous breast cancer. A positive-margin resection mice model bearing MDA-MB-231-luc xenograft was established and the performance of the probe in assisting surgical resection of residual lesions was examined.ResultsA significantly stronger fluorescence intensity was detected in MDA-MB-231 cells than MCF 10A cells incubated with HSA-ICG. In vivo fluorescence imaging showed that HSA-ICG had an obvious accumulation at tumor site at 24 h with tumor-to-normal tissue ratio of 8.19 ± 1.30. The same was true in the transgenic mice model. The fluorescence intensity of cancer tissues was higher than that of non-cancer tissues (58.53 ± 18.15 vs 32.88 ± 11.34). During the surgical scenarios, the residual tumors on the surgical bed were invisible with the naked eye, but were detected and resected with negative margin under HSA-ICG guidance in all the mice (8/8). Recurrence rate among mice that underwent resection with HSA-ICG (0/8) was significantly lower than the rates among mice with ICG (4/8), as well as the control group under white light (7/7).ConclusionsThis study suggests that real-time in vivo visualization of breast cancer with an HSA-ICG fluorescent probe facilitates complete surgical resection of breast cancer in a mouse xenograft model.

Summary: Osteoporosis is characterized by low bone mineral density (BMD). The advancement of high-throughput technologies and integrative approaches provided an opportunity for deciphering the mechanisms underlying osteoporosis. Here, we generated genomic, transcriptomic, methylomic, and metabolomic datasets from 119 subjects with high (n = 61) and low (n = 58) BMDs. By adopting sparse multiple discriminative canonical correlation analysis, we identified an optimal multi-omics biomarker panel with 74 differentially expressed genes (DEGs), 75 differentially methylated CpG sites (DMCs), and 23 differential metabolic products (DMPs). By linking genetic data, we identified 199 targeted BMD-associated expression/methylation/metabolite quantitative trait loci (eQTLs/meQTLs/metaQTLs). The reconstructed networks/pathways showed extensive biomarker interactions, and a substantial proportion of these biomarkers were enriched in RANK/RANKL, MAPK/TGF-β, and WNT/β-catenin pathways and G-protein-coupled receptor, GTP-binding/GTPase, telomere/mitochondrial activities that are essential for bone metabolism. Five biomarkers (FADS2, ADRA2A, FMN1, RABL2A, SPRY1) revealed causal effects on BMD variation. Our study provided an innovative framework and insights into the pathogenesis of osteoporosis. : Disease; Genomics; Metabolomics; Transcriptomics Subject Areas: Disease, Genomics, Metabolomics, Transcriptomics

Idiopathic pulmonary fibrosis (IPF) can severely disrupt lung function, leading to fatal consequences, and there is currently a lack of specific therapeutic drugs. Bergenin is an isocoumarin compound with lots of biological functions including antioxidant activity. This study evaluated the potential beneficial effects of bergenin on pulmonary fibrosis and investigated the possible mechanisms. We found that bergenin alleviated bleomycin-induced pulmonary fibrosis by relieving oxidative stress, reducing the deposition of the extracellular matrix (ECM) and inhibiting the formation of myofibroblasts. Furthermore, we showed that bergenin could induce phosphorylation and expression of p62 and activation of Nrf2, Nrf2 was required for bergenin-induced p62 upregulation, and p62 knockdown reduced bergenin-induced Nrf2 activity. More importantly, knockdown of Nrf2 or p62 could abrogate the antioxidant activity of bergenin and the inhibition effect of bergenin on TGF-β-induced ECM deposition and myofibroblast differentiation. Thereby, a regulatory loop is formed between p62 and Nrf2, which is an important target for bergenin aimed at treating pulmonary fibrosis.

Background: Obesity is now a common risk factor for non-alcoholic fatty liver disease (NAFLD). Thus, it is important to explore its underlying mechanisms. Methods: Total RNA was extracted from peripheral whole blood samples from 50 NAFLD patients and 50 healthy controls. In addition, human liver specimens were obtained through liver biopsies from NAFLD patients and healthy controls. The level of miRNA was studied using real-time PCR. The expression of lipogenic genes was analyzed using western blot, and a dual luciferase reporter assay was conducted to identify the possible target gene. Adenovirus vectors were injected into the tail vein of the high fat diet (HFD)-fed mice to study the role of miR-155 on lipid accumulation in vivo. Results: The level of miR-155 was markedly reduced in the livers and peripheral blood of NAFLD patients compared with healthy controls. Upregulation of miR-155 decreased intracellular lipid content and the SREBP1 and FAS protein levels, while inhibition of miR-155 enhanced the intracellular lipid content. The dual luciferase reporter assay showed that Liver X receptor (LXR)α was the target gene of miR-155, and silencing miR-155 reduced the expression of SREBP1 and FAS. An in vivo study showed that upregulation of miR-155 decreased the hepatic lipid accumulation mainly by suppressing the LXRα-dependent lipogenic signaling pathway. Conclusions: In summary, decreased expression of miR-155 in the peripheral blood may be utilized as a potential novel biomarker for NAFLD screening mainly by targeting LXRα.

Background: Type 2 diabetes afflicts 95% of diabetes patients. Recent data suggest that miRNAs play a key role in insulin production, secretion and function. This study aims to explore the specific role of miR-499-5p in hepatic insulin resistance. Methods: The miRNA expression levels in the livers of db/db mice were analyzed using miRNA chips and were verified by real-time PCR. miR-499-5p mimics and an inhibitor were transfected into NCTC1469 cells. Then, the PI3K/AKT signaling pathway and glycogen level were determined. The target genes of miR-499-5p were predicted by bioinformatics and then confirmed by dual luciferase reporter assay and Western blot. To establish an insulin resistance (IR) animal model, C57BL/6 mice were fed a high-fat diet (HFD). The level of miR-499-5p in the livers of HFD-fed mice was upregulated through tail vein injection of adenovirus vectors (ad) containing miR-499-5p mimics. The glucose tolerance test (GTT) and insulin tolerance test (ITT) were used to determine glucose tolerance and insulin tolerance, respectively. Results: MicroRNA chips and qPCR showed that miR-499-5p was significantly decreased in the livers of db/db mice. Downregulation of miR-499-5p impaired the insulin signaling pathway and glycogen synthesis, whereas upregulation of miR-499-5p promoted the insulin signaling pathway and glycogen synthesis in NCTC1469 cells. The dual luciferase reporter assay and Western blot demonstrated that PTEN was the target gene of miR-499-5p. Compared with the control group, miR-499-5p was increased 2.1-fold in the livers of HFD-fed mice. By tail vein injection of adenovirus vector containing miR-499-5p mimics, GTT and ITT were improved in HFD-fed mice. Conclusion: Downregulation of the miR-499-5p level impaired the PI3K/AKT/GSK signaling pathway and glycogen synthesis by targeting PTEN.

Predicting truck (heavy vehicle) travel time is a principal component of freight project prioritization and planning. However, most existing travel time prediction models are designed for passenger vehicles and fail to make truck specific forecasts or use truck specific data. Little is known about the impact of this limitation, or how truck travel time prediction could be improved in response to freight investments with an improved methodology. In light of this, this paper proposes a pragmatic multi-regime speed-density relationship based approach to predict freeway truck travel time using empirical truck probe GPS data (which is increasingly available in North American and Europe) and loop detector data. Traffic regimes are segmented using a cluster analysis approach. Two case studies are presented to illustrate the approach. The travel time estimates are compared with the Bureau of Public Roads (BPR) model and the Akçelik model outputs. It is found that the proposed method is able to estimate more accurate travel times than traditional methods. The predicted travel time can support freight prioritization and planning.

This paper introduces a novel quay crane design, double girder bridge crane (DGBC). DGBC is capable of handling containers of two adjacent bays simultaneously, avoiding crane collisions, saving travelling and reposition cost, and eventually improving terminal efficiency. This problem is formulated as a resource-constrained project scheduling with objective to minimize the maximum completion time. A two-stage heuristic algorithm is proposed in which an operating sequences on each bay is obtained by double cycling, and the integrated timetable for both bays is constructed by solving resource conflicts using the proposed minimum cost strategy. We examine effectiveness and performance of applying DGBC with double cycling. A case study is presented to illustrate how DGBC works with the two-stage method. Three extreme cases with respective conflict types are investigated to develop the performance bounds of DGBC with double cycling. The results show that DGBC can significantly improve terminal productivity, and outperforms single girder crane in both makespan and the lift operation percentage. The highest DGBC efficiency does not require maximum double cycles in two bay schedules; rather the integrated timetable for two bays is the main contribution to the DGBC performance as it yields better cooperation between two spreaders and the driver.