Search

Abstract Objectives The simplified endoscopic score of Crohn’s disease (SES-CD) is the gold standard for quantitatively evaluating Crohn’s disease (CD) activity but is invasive. This study aimed to develop and validate a machine learning (ML) model based on dual-energy CT enterography (DECTE) to noninvasively evaluate CD activity. Methods We evaluated the activity in 202 bowel segments of 46 CD patients according to the SES-CD score and divided the segments randomly into training set and testing set at a ratio of 7:3. Least absolute shrinkage and selection operator (LASSO) was used for feature selection, and three models based on significant parameters were established based on logistic regression. Model performance was evaluated using receiver operating characteristic (ROC), calibration, and clinical decision curves. Results There were 110 active and 92 inactive bowel segments. In univariate analysis, the slope of spectral curve in the venous phases (λHU-V) has the best diagnostic performance, with an area under the ROC curve (AUC) of 0.81 and an optimal threshold of 1.975. In the testing set, the AUC of the three models established by the 7 variables to differentiate CD activity was 0.81–0.87 (DeLong test p value was 0.071–0.766, p > 0.05), and the combined model had the highest AUC of 0.87 (95% confidence interval (CI): 0.779–0.959). Conclusions The ML model based the DECTE can feasibly evaluate CD activity, and DECTE parameters provide a quantitative analysis basis for evaluating specific bowel activities in CD patients. Critical relevance statement The machine learning model based on dual-energy computed tomography enterography can be used for evaluating Crohn’s disease activity noninvasively and quantitatively. Key Points Dual-energy CT parameters are related to Crohn’s disease activity. Three machine learning models effectively evaluated Crohn’s disease activity. Combined models based on conventional and dual-energy CT have the best performance. Graphical Abstract

Abstract Background In the aftermath of the COVID-19 pandemic, there has been a surge in human metapneumovirus (HMPV) transmission, surpassing pre-epidemic levels. We aim to elucidate the clinical and epidemiological characteristics of HMPV infections in the post-COVID-19 pandemic era. Methods In this retrospective single-center study, participants diagnosed with laboratory confirmed HMPV infection through Targeted Next Generation Sequencing were included. The study encompassed individuals admitted to Henan Children's Hospital between April 29 and June 5, 2023. Demographic information, clinical records, and laboratory indicators were analyzed. Results Between April 29 and June 5, 2023, 96 pediatric patients were identified as infected with HMPV with a median age of 33.5 months (interquartile range, 12 ~ 48 months). The majority (87.5%) of infected children were under 5 years old. Notably, severe cases were statistically younger. Predominant symptoms included fever (81.3%) and cough (92.7%), with wheezing more prevalent in the severe group (56% vs 21.1%). Coinfection with other viruses was observed in 43 patients, with Epstein–Barr virus (EBV) (15.6%) or human rhinovirus A (HRV type A) (12.5%) being the most common. Human respiratory syncytial virus (HRSV) coinfection rate was significantly higher in the severe group (20% vs 1.4%). Bacterial coinfection occurred in 74 patients, with Haemophilus influenzae (Hin) and Streptococcus pneumoniae (SNP) being the most prevalent (52.1% and 41.7%, respectively). Severe patients demonstrated evidence of multi-organ damage. Noteworthy alterations included lower concentration of IL-12p70, decreased lymphocytes percentages, and elevated B lymphocyte percentages in severe cases, with statistical significance. Moreover, most laboratory indicators exhibited significant changes approximately 4 to 5 days after onset. Conclusions Our data systemically elucidated the clinical and epidemiological characteristics of pediatric patients with HMPV infection, which might be instructive to policy development for the prevention and control of HMPV infection and might provide important clues for future HMPV research endeavors.

Abstract Osteophytes are frequently observed in elderly people and most commonly appear at the anterior edge of the cervical and lumbar vertebrae body. The anterior osteophytes keep developing and will lead to neck/back pain over time. In clinical practice, the accurate measurement of the anterior osteophyte length and the understanding of the temporal progression of anterior osteophyte growth are of vital importance to clinicians for effective treatment planning. This study proposes a new measuring method using the osteophyte ratio index to quantify anterior osteophyte length based on lateral radiographs. Moreover, we develop a continuous stochastic degradation model with time-related functions to characterize the anterior osteophyte formation and growth process on cervical and lumbar vertebrae over time. Follow-up data of anterior osteophytes up to 9 years are obtained for measurement and model validation. The agreement test indicates excellent reproducibility for our measuring method. The proposed model accurately fits the osteophyte growth paths. The model predicts the mean time to onset of pain and obtained survival function of the degenerative vertebrae. This research opens the door to future quantification and mathematical modeling of the anterior osteophyte growth on human cervical and lumbar vertebrae. The measured follow-up data is shared for future studies.

Abstract Head and neck squamous cell carcinoma (HNSCC) is characterized by high recurrence or distant metastases rate and the prognosis is challenging. There is mounting evidence that tumor-infiltrating B cells (TIL-Bs) have a crucial, synergistic role in tumor control. However, little is known about the role TIL-Bs play in immune microenvironment and the way TIL-Bs affect the outcome of immune checkpoint blockade. Using single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database, the study identified distinct gene expression patterns in TIL-Bs. HNSCC samples were categorized into TIL-Bs inhibition and TIL-Bs activation groups using unsupervised clustering. This classification was further validated with TCGA HNSCC data, correlating with patient prognosis, immune cell infiltration, and response to immunotherapy. We found that the B cells activation group exhibited a better prognosis, higher immune cell infiltration, and distinct immune checkpoint levels, including elevated PD-L1. A prognostic model was also developed and validated, highlighting four genes as potential biomarkers for predicting survival outcomes in HNSCC patients. Overall, this study provides a foundational approach for B cells-based tumor classification in HNSCC, offering insights into targeted treatment and immunotherapy strategies.

Abstract Due to the antiquity and difficulty of excavation, the Terracotta Warriors have suffered varying degrees of damage. To restore the cultural relics to their original appearance, utilizing point clouds to repair damaged Terracotta Warriors has always been a hot topic in cultural relic protection. The output results of existing methods in point cloud completion often lack diversity. Probability-based models represented by Denoising Diffusion Probabilistic Models have recently achieved great success in the field of images and point clouds and can output a variety of results. However, one drawback of diffusion models is that too many samples result in slow generation speed. Toward this issue, we propose a new neural network for Terracotta Warriors fragments completion. During the reverse diffusion stage, we initially decrease the number of sampling steps to generate a coarse result. This preliminary outcome undergoes further refinement through a multi-scale refine network. Additionally, we introduce a novel approach called Partition Attention Sampling to enhance the representation capabilities of features. The effectiveness of the proposed model is validated in the experiments on the real Terracotta Warriors dataset and public dataset. The experimental results conclusively demonstrate that our model exhibits competitive performance in comparison to other existing models.

Abstract Background The regulatory role of N6-methyladenosine (m6A) modification in the onset and progression of cancer has garnered increasing attention in recent years. However, the specific role of m6A modification in pulmonary metastasis of colorectal cancer remains unclear. Methods This study identified differential m6A gene expression between primary colorectal cancer and its pulmonary metastases using transcriptome sequencing and immunohistochemistry. We investigated the biological function of METTL3 gene both in vitro and in vivo using assays such as CCK-8, colony formation, wound healing, EDU, transwell, and apoptosis, along with a BALB/c nude mouse model. The regulatory mechanisms of METTL3 in colorectal cancer pulmonary metastasis were studied using methods like methylated RNA immunoprecipitation quantitative reverse transcription PCR, RNA stability analysis, luciferase reporter gene assay, Enzyme-Linked Immunosorbent Assay, and quantitative reverse transcription PCR. Results The study revealed high expression of METTL3 and YTHDF1 in the tumors of patients with pulmonary metastasis of colorectal cancer. METTL3 promotes epithelial-mesenchymal transition in colorectal cancer by m6A modification of SNAIL mRNA, where SNAIL enhances the secretion of CXCL2 through the NF-κB pathway. Additionally, colorectal cancer cells expressing METTL3 recruit M2-type macrophages by secreting CXCL2. Conclusion METTL3 facilitates pulmonary metastasis of colorectal cancer by targeting the m6A-Snail-CXCL2 axis to recruit M2-type immunosuppressive macrophages. This finding offers new research directions and potential therapeutic targets for colorectal cancer treatment.

Abstract Utrophin (UTRN), known as a tumor suppressor, potentially regulates tumor development and the immune microenvironment. However, its impact on breast cancer’s development and treatment remains unstudied. We conducted a thorough examination of UTRN using both bioinformatic and in vitro experiments in this study. We discovered UTRN expression decreased in breast cancer compared to standard samples. High UTRN expression correlated with better prognosis. Drug sensitivity tests and RT-qPCR assays revealed UTRN’s pivotal role in tamoxifen resistance. Furthermore, the Kruskal–Wallis rank test indicated UTRN’s potential as a valuable diagnostic biomarker for breast cancer and its utility in detecting T stage of breast cancer. Additionally, our results demonstrated UTRN’s close association with immune cells, inhibitors, stimulators, receptors, and chemokines in breast cancer (BRCA). This research provides a novel perspective on UTRN’s role in breast cancer’s prognostic and therapeutic value. Low UTRN expression may contribute to tamoxifen resistance and a poor prognosis. Specifically, UTRN can improve clinical decision-making and raise the diagnosis accuracy of breast cancer.

Abstract Interplay between innate and adaptive immune cells is important for the antitumor immune response. However, the tumor microenvironment may turn immune suppressive, and tumor associated macrophages are playing a role in this transition. Here, we show that CD276, expressed on tumor-associated macrophages (TAM), play a role in diminishing the immune response against tumors. Using a model of tumors induced by N-butyl-N-(4-hydroxybutyl) nitrosamine in BLCA male mice we show that genetic ablation of CD276 in TAMs blocks efferocytosis and enhances the expression of the major histocompatibility complex class II (MHCII) of TAMs. This in turn increases CD4 + and cytotoxic CD8 + T cell infiltration of the tumor. Combined single cell RNA sequencing and functional experiments reveal that CD276 activates the lysosomal signaling pathway and the transcription factor JUN to regulate the expression of AXL and MerTK, resulting in enhanced efferocytosis in TAMs. Proving the principle, we show that simultaneous blockade of CD276 and PD-1 restrain tumor growth better than any of the components as a single intervention. Taken together, our study supports a role for CD276 in efferocytosis by TAMs, which is potentially targetable for combination immune therapy.

Abstract Creating microenvironments that mimic an enzyme’s active site is a critical aspect of supramolecular confined catalysis. In this study, we employ the commonly used chiral 1,1’-bi-2-naphthol (BINOL) phosphates as subcomponents to construct supramolecular hollow nanotube in an aqueous medium through non-covalent intermolecular recognition and arrangement. The hexagonal nanotubular structure is characterized by various techniques, including X-ray, NMR, ESI-MS, AFM, and TEM, and is confirmed to exist in a homogeneous aqueous solution stably. The nanotube’s length in solution depends on the concentration of chiral BINOL-phosphate as a monomer. Additionally, the assembled nanotube can accelerate the rate of the 3-aza-Cope rearrangement reaction by up to 85-fold due to the interior confinement effect. Based on the detailed kinetic and thermodynamic analyses, we propose that the chain-like substrates are constrained and pre-organized into a reactive chair-like conformation, which stabilizes the transition state of the reaction in the confined nanospace of the nanotube. Notably, due to the restricted conformer with less degrees of freedom, the entropic barrier is significantly reduced compared to the enthalpic barrier, resulting in a more pronounced acceleration effect.

Abstract It is very challenging to accurately segment smoke images because smoke has some adverse vision characteristics, such as anomalous shapes, blurred edges, and translucency. Existing methods cannot fully focus on the texture details of anomalous shapes and blurred edges simultaneously. To solve these problems, a Dense Multi‐scale context and Asymmetric pooling Embedding Network (DMAENet) is proposed to model the smoke edge details and anomalous shapes for smoke segmentation. To capture the feature information from different scales, a Dense Multi‐scale Context Module (DMCM) is proposed to further enhance the feature representation capability of our network under the help of asymmetric convolutions. To efficiently extract features for long‐shaped objects, the authors use asymmetric pooling to propose an Asymmetric Pooling Enhancement Module (APEM). The vertical and horizontal pooling methods are responsible for enhancing features of irregular objects. Finally, a Feature Fusion Module (FFM) is designed, which accepts three inputs for improving performance. Low and high‐level features are fused by pixel‐wise summing, and then the summed feature maps are further enhanced in an attention manner. Experimental results on synthetic and real smoke datasets validate that all these modules can improve performance, and the proposed DMAENet obviously outperforms existing state‐of‐the‐art methods.

Abstract Symbiodinium are the photosynthetic endosymbionts for corals and play a vital role in supplying their coral hosts with photosynthetic products, forming the nutritional foundation for high-yield coral reef ecosystems. Here, we determine the cryo-electron microscopy structure of Symbiodinium photosystem I (PSI) supercomplex with a PSI core composed of 13 subunits including 2 previously unidentified subunits, PsaT and PsaU, as well as 13 peridinin-Chl a/c-binding light-harvesting antenna proteins (AcpPCIs). The PSI–AcpPCI supercomplex exhibits distinctive structural features compared to their red lineage counterparts, including extended termini of PsaD/E/I/J/L/M/R and AcpPCI-1/3/5/7/8/11 subunits, conformational changes in the surface loops of PsaA and PsaB subunits, facilitating the association between the PSI core and peripheral antennae. Structural analysis and computational calculation of excitation energy transfer rates unravel specific pigment networks in Symbiodinium PSI–AcpPCI for efficient excitation energy transfer. Overall, this study provides a structural basis for deciphering the mechanisms governing light harvesting and energy transfer in Symbiodinium PSI–AcpPCI supercomplexes adapted to their symbiotic ecosystem, as well as insights into the evolutionary diversity of PSI–LHCI among various photosynthetic organisms.

Abstract Background Currently, noninvasive imaging techniques and circulating biomarkers are still insufficient to accurately assess carotid plaque stability, and an in-depth understanding of the molecular mechanisms that contribute to plaque instability is still lacking. Methods We established a clinical study cohort containing 182 patients with carotid artery stenosis. After screening, 39 stable and 49 unstable plaques were included in the discovery group, and quantitative proteomics analysis based on data independent acquisition was performed for these plaque samples. Additionally, 35 plaques were included in the validation group to validate the proteomics results by immunohistochemistry analysis. Results A total of 397 differentially expressed proteins were identified in stable and unstable plaques. These proteins are primarily involved in ferroptosis and lipid metabolism-related functions and pathways. Plaque validation results showed that ferroptosis- and lipid metabolism-related proteins had different expression trends in stable plaques versus unstable fibrous cap regions and lipid core regions. Ferroptosis- and lipid metabolism-related mechanisms in plaque stability were discussed. Conclusions Our results may provide a valuable strategy for revealing the mechanisms affecting plaque stability and will facilitate the discovery of specific biomarkers to broaden the therapeutic scope.

Ground penetrating radar (GPR) is a vital non-destructive testing (NDT) technology that can be employed for detecting the backfill grouting of shield tunnels. To achieve intelligent analysis of GPR data and overcome the subjectivity of traditional data processing methods, the CatBoost & BO-TPE model was constructed for regressing the grouting thickness based on GPR waveforms. A full-scale model test and corresponding numerical simulations were carried out to collect GPR data at 400 and 900 MHz, with known backfill grouting thickness. The model test helps address the limitation of not knowing the grout body condition in actual field detection. The data were then used to create machine learning datasets. The method of feature selection was proposed based on the analysis of feature importance and the electromagnetic (EM) propagation law in mediums. The research shows that: (1) the CatBoost & BO-TPE model exhibited outstanding performance in both experimental and numerical data, achieving R2 values of 0.9760, 0.8971, 0.8808, and 0.5437 for numerical data and test data at 400 and 900 MHz. It outperformed extreme gradient boosting (XGBoost) and random forest (RF) in terms of performance in the backfill grouting thickness regression; (2) compared with the full-waveform GPR data, the feature selection method proposed in this paper can promote the performance of the model. The selected features within the 5–30 ns of the A-scan can yield the best performance for the model; (3) compared to GPR data at 900 MHz, GPR data at 400 MHz exhibited better performance in the CatBoost & BO-TPE model. This indicates that the results of the machine learning model can provide feedback for the selection of GPR parameters; (4) the application results of the trained CatBoost & BO-TPE model in engineering are in line with the patterns observed through traditional processing methods, yet they demonstrate a more quantitative and objective nature compared to the traditional method.

Abstract Background Pneumocystis pneumonia (PCP) is a life-threatening opportunistic fungal infection with a high mortality rate in immunocompromised patients, ranging from 20 to 80%. However, current understanding of the variation in host immune response against Pneumocystis across different timepoints is limited. Methods In this study, we conducted a time-resolved single-cell RNA sequencing analysis of CD45+ cells sorted from lung tissues of mice infected with Pneumocystis. The dynamically changes of the number, transcriptome and interaction of multiply immune cell subsets in the process of Pneumocystis pneumonia were identified according to bioinformatic analysis. Then, the accumulation of Trem2hi interstitial macrophages after Pneumocystis infection was verified by flow cytometry and immunofluorescence. We also investigate the role of Trem2 in resolving the Pneumocystis infection by depletion of Trem2 in mouse models. Results Our results characterized the CD45+ cell composition of lung in mice infected with Pneumocystis from 0 to 5 weeks, which revealed a dramatic reconstitution of myeloid compartments and an emergence of PCP-associated macrophage (PAM) following Pneumocystis infection. PAM was marked by the high expression of Trem2. We also predicted that PAMs were differentiated from Ly6C+ monocytes and interacted with effector CD4+ T cell subsets via multiple ligand and receptor pairs. Furthermore, we determine the surface markers of PAMs and validated the presence and expansion of Trem2hi interstitial macrophages in PCP by flow cytometry. PAMs secreted abundant pro-inflammation cytokines, including IL-6, TNF-α, GM-CSF, and IP-10. Moreover, PAMs inhibited the proliferation of T cells, and depletion of Trem2 in mouse lead to reduced fungal burden and decreased lung injury in PCP. Conclusion Our study delineated the dynamic transcriptional changes in immune cells and suggests a role for PAMs in PCP, providing a framework for further investigation into PCP’s cellular and molecular basis, which could provide a resource for further discovery of novel therapeutic targets.

The occurrence of coal mine accidents is mostly caused by the instability and failure of the coal pillar and its overlying roof rock layer. To study the influence of different coal-rock height ratios on the deformation failure and energy evolution mechanism of the coal pillar-roof system, uniaxial loading and cyclic loading and unloading tests are conducted on coal-rock structural body with coal-rock height ratios of 1∶3, 1∶2, 1∶1, 2∶1, and 3∶1, respectively. The relationship between deformation and energy evolution of coal-rock structural body are analyzed, and the stability of coal-rock structural body are quantitatively evaluated through the load-unload response ratio. The test results show that the peak strength of coal-rock structural body under uniaxial loading and cyclic loading gradually decreases with the increase of coal-rock height ratio. The peak strength of coal-rock structural body under cyclic loading test is lower than that in uniaxial loading test. The higher the coal-rock height ratio, the smaller the reduction rate of the peak strength of the structural body under cyclic loading; the input energy, elastic energy and dissipative energy of the composite increase nonlinearly with the increase of stress. The coal-rock height ratio is positively proportional to the average elastic strain, average elastic energy, average residual strain, average dissipative energy, total residual strain and loading and unloading response, and inversely proportional to the total elastic strain, total elastic energy and total dissipative energy of the composite during cyclic loading.

Frequency scanning interferometry (FSI) has become a popular method for long-range, targetbased, distance measurements. However, the cost of developing such systems, particularly the electronic components required for high-speed data acquisition (DAQ), remains a significant concern. In this article, we present a cost-effective, FPGA-based real-time DAQ system specifically designed for FSI, with a focus on long absolute distance measurements. Our design minimizes the use of third-party intellectual property (IP) and is fully compatible with the Xilinx FPGA 7 series families. The hardware employs a 160-MS/s, 16-bit dual-channel ADC interfaced to the FPGA via a low-voltage differential signaling (LVDS). The proposed system incorporates an external sampling clock, referred to as the K-clock, which linearizes the laser’s tuning rate, enabling optical measurements to be sampled at equal optical frequency intervals rather than equal time intervals. Additionally, we present the design of a high-speed, 160-MS/s ADC module for the front-end analog signal interface and the LVDS connection to the chosen FPGA. We demonstrate that the digitized data samples can be efficiently transmitted to a polarization controller (PC) application via a USB interface for further processing.

Inrush current is high-magnitude current drawn by power transformers upon energization. The severity of inrush current depends on factors such as the transformer’s residual flux and the voltage phase angle at the energization instant. This paper proposes a flux matching method for the energization of V/V traction transformers to mitigate inrush current. This is achieved by adjusting the residual flux of the core to an appropriate reference value and then obtaining the proper energization instant. To this end, the method only requires knowledge of nominal voltage and excitation current, eliminating the need to acquire transformer’s parameters/design information. The railway power conditioner, typically present at the low voltage side of the V/V transformer, is used as a current source to inject sinusoidal current into the transformer windings before its energization. The reference residual flux is calculated based on the circuit breaker operating characteristics. The energization instant is determined such that the adjusted flux density matches the steady-state flux expected with respect to the applied voltage. The proposed method is validated by conducting over 14,000 simulations under different conditions using PSCAD/EMTDC. The method is also implemented and successfully tested on a laboratory-scale test rig, which verifies its effectiveness in more realistic conditions.

Abstract Cancer immunotherapies have achieved unprecedented success in clinic, but they remain largely ineffective in some major types of cancer, such as colorectal cancer with microsatellite stability (MSS CRC). It is therefore important to study tumor microenvironment of resistant cancers for developing new intervention strategies. In this study, we identify a metabolic cue that determines the unique immune landscape of MSS CRC. Through secretion of distal cholesterol precursors, which directly activate RORγt, MSS CRC cells can polarize T cells toward Th17 cells that have well-characterized pro-tumor functions in colorectal cancer. Analysis of large human cancer cohorts revealed an asynchronous pattern of the cholesterol biosynthesis in MSS CRC, which is responsible for the abnormal accumulation of distal cholesterol precursors. Inhibiting the cholesterol biosynthesis enzyme Cyp51, by pharmacological or genetic interventions, reduced the levels of intratumoral distal cholesterol precursors and suppressed tumor progression through a Th17-modulation mechanism in preclinical MSS CRC models. Our study therefore reveals a novel mechanism of cancer–immune interaction and an intervention strategy for the difficult-to-treat MSS CRC.

As the electric vehicle industry continues to grow on a large scale, the challenges related to the locating and sizing of charging stations are becoming more apparent. This paper utilizes floating car data from Urumqi, considering factors such as battery SoC, usage time, and the diverse preferences of electric vehicle drivers when making charging decisions. Through this approach, this paper predicts the charging demands of electric vehicles and formulates a model for optimal locating and sizing based on these predicted needs. The research findings indicate that by simulating charging decisions made by electric vehicle drivers, a total of 10,766 charging demands were identified. In comparison, there were 14,759 parking events extracted from the floating car data. This approach reduced redundancy in charging demand predictions compared to directly using the floating car data for extracting parking events. When considering the locating of charging stations, the strategy of exclusively installing fast-charging stations showed better results than the approach involving a mix of fast and slow charging stations. When the decision of locating prioritized minimizing unmet charging demands, it successfully addressed a minimum of 130 additional charging demands. Similarly, when minimizing the idle time for electric taxi drivers was the primary concern, this approach led to a reduction of at least 109 hours in idle time; through a reallocating and sizing adjustment of charging piles within the charging station based on the locating plan, it was possible to meet an additional 83 charging demands. This modification also significantly reduced the average idle time for users, decreasing from an average of 4.26 minutes to 2.63 minutes. Moreover, the charging piles’ average usage time increased, going up from 10.31 hours to 10.42 hours, thus improving the overall efficiency of the charging piles. These findings provide valuable insights for the locating and sizing of charging stations tailored to urban electric taxis.

Graph convolutional networks (GCN) have been widely utilized in Alzheimer's disease (AD) classification research due to its ability to automatically learn robust and powerful feature representations. Inter-patient relationships are effectively captured by constructing patients magnetic resonance imaging (MRI) data as graph data, where nodes represent individuals and edges denote the relationships between them. However, the performance of GCNs might be constrained by the construction of the graph adjacency matrix, thereby leading to learned features potentially overlooking intrinsic correlations among patients, which ultimately causes inaccurate disease classifications. To address this issue, we propose an Alzheimer's disease Classification network based on MRI utilizing diffusion maps for multi-scale feature fusion in graph convolution. This method aims to tackle the problem of features neglecting intrinsic relationships among patients while integrating features from diffusion mapping with different neighbor counts to better represent patients and achieve an accurate AD classification. Initially, the diffusion maps method conducts diffusion information in the feature space, thus breaking free from the constraints of diffusion based on the adjacency matrix. Subsequently, the diffusion features with different neighbor counts are merged, and a self-attention mechanism is employed to adaptively adjust the weights of diffusion features at different scales, thereby comprehensively and accurately capturing patient characteristics. Finally, metric learning techniques enhance the similarity of node features within the same category in the graph structure and bring node features of different categories more distant from each other. This study aims to enhance the classification accuracy of AD, by providing an effective tool for early diagnosis and intervention. It offers valuable information for clinical decisions and personalized treatment. Experimentation on the publicly accessible Alzheimer's disease neuroimaging initiative (ADNI) dataset validated our method's competitive performance across various AD-related classification tasks. Compared to existing methodologies, our approach captures patient characteristics more effectively and demonstrates superior generalization capabilities.

In this study, the pure Al and binary Al–Ni alloys with Ni addition of 1, 3, 6, and 10 wt % were coated via micro arc oxidation (MAO) in a tetraborate and phosphate based electrolyte for 60 min. With increased Ni content, the color of MAO coating became darker due to increased Ni-containing compounds on the surface. The Ni played a negative effect on the coating growth, decreasing both the coating thickness and surface roughness. The coatings on the Al–Ni alloys were mainly composed of γ-Al2O3 and α-Al2O3, and the Ni facilitated the formation of α-Al2O3 in the coating. Nanoparticles of NiO were generated around the edge of discharge channels for Al–6Ni and Al–10Ni alloys after a certain oxidation time. All coatings exhibited a uniform and dense surface structure, with the outer layer being more compact than the inner layer. Many tiny pores were found in the inner layer. Despite the corrosion resistance was decreased, the anti-wear performance of MAO treated samples was improved with the increased Ni content in the matrix. While, the corrosion resistance of the coated samples decreased with the adding of Ni content in the matrix.

Objective Syringomyelia is a common central nervous system disease characterized by the dilation of the central canal (CC). Regarding the pathogenesis of syringomyelia, cerebrospinal fluid (CSF) circulation obstruction in the subarachnoid space (SAS) of the spinal cord has been widely accepted. However, clinical and animal studies on obstructing the CSF in SAS failed to form syringomyelia, challenging the theory of SAS obstruction. The precise pathogenesis remains unknown. Methods We utilized an extradural compression rat model to investigate the pathogenesis underlying syringomyelia. Magnetic resonance imaging enabled detection of syringomyelia formation. To assess CSF flow within the SAS, Evans blue was infused into the cisterna magna. Histological analysis allowed morphological examination of the CC. Furthermore, CSF flow through the CC was traced using Ovalbumin Alexa-Flour 647 conjugate (OAF-647). Scanning electron microscopy (SEM) enabled visualization of ependymal cilia. Results The findings showed that the dura mater below the compression segment exhibited lighter coloration relative to the region above the compression, indicative of partial obstruction within the SAS. However, the degree of SAS occlusion did not significantly differ between syringomyelia (SM-Y group) and those without (SM-N group). Intriguingly, hematoxylin and eosin staining and CSF tracing revealed occlusion of the CC accompanied by reduced CSF flow in the SM-Y group compared to SM-N and control groups. SEM images uncovered impairment of ependymal cilia inside the syringomyelia. Conclusion CC occlusion may represent a physiological prerequisite for syringomyelia formation, while SAS obstruction serves to initiate disease onset. The impairment of ependymal cilia appears to facilitate progression of syringomyelia.

The skin, being the largest organ in the human body, plays a vital role in shielding internal organs from external physical and chemical factors. However, skin damage caused by various factors such as injuries, surgeries, diabetes, or burns can lead to wounds that diminish the skin's protective function. Monitoring essential physiological parameters like temperature, moisture, and pH is crucial to facilitate antibiotic treatment, remote physician monitoring, patient comfort, cost reduction, and prevention of hospital-acquired infections. To this end, innovative wound coverings made of biological materials like gelatin, carboxymethyl chitosan, and titanium nanoparticles have been developed, mainly for hospital and pediatric applications. These wound coverings come equipped with sensors to monitor temperature, pH, and moisture and are suitable for pediatric hospitals where children experience difficulty in wound healing due to their sensitive skin. The temperature monitoring feature allows physicians to accurately assess the wound's temperature, detect potential infections, and take prompt actions. These wound coverings can significantly enhance wound treatment for patients, as real-time monitoring of physiological parameters enables informed decision-making by physicians, leading to better therapeutic outcomes. Furthermore, the use of these wound coverings can minimize the risk of hospital-acquired infections. Their adaptability and flexibility make them ideal for various wound types and sizes, ensuring patient comfort and compliance with the treatment plan. In conclusion, the development of innovative and flexible wound coverings using biological materials and equipped with sensors represents a significant breakthrough in wound management. The use of these wound coverings has the potential to revolutionize wound care and improve patient outcomes, particularly in pediatric hospitals where wound healing is often challenging.

ObjectiveThe study aimed to build and validate a competitive risk nomogram to predict the cumulative incidence of hepatocellular carcinoma (HCC) for patients with hepatitis B virus (HBV)-related cirrhosis.MethodsA total of 1401 HBV-related cirrhosis patients were retrospectively enrolled from January 1, 2011 to December 31, 2014. Application of 20 times imputation dealt with missing data using multiple imputation by chained equations (MICE). The patients were randomly divided into a training set (n = 1017) and a validation set (n = 384) at a ratio of 3:1. A prediction study was carried out using a competing risk model, where the event of interest was HCC and the competing events were death and liver transplantation, and subdistribution hazard ratios (sHRs) with 95% CIs were reported. The multivariate competing risk model was constructed and validated.ResultsThere was a negligible difference between the original database and the 20 imputed datasets. At the end of follow-up, the median follow-up time was 69.9 months (interquartile range: 43.8–86.6). There were 31.5% (442/1401) of the patients who developed HCC, with a 5-year cumulative incidence of 22.9 (95%CI, 20.8%–25.2%). The univariate and multivariate competing risk regression and construction of the nomogram were performed in 20 imputed training datasets. Age, sex, antiviral therapy history, hepatitis B e antigen, alcohol drinking history, and alpha-fetoprotein levels were included in the nomogram. The area under receiver operating characteristic curve values at 12, 24, 36, 60, and 96 months were 0.68, 0.69, 0.70, 0.68, and 0.80, and the Brier scores were 0.30, 0.25, 0.23, 0.21, and 0.20 in the validation set. According to the cumulative incidence function, the nomogram effectively screened out high-risk HCC patients from low-risk patients in the presence of competing events (Fine–Gray test p < 0.001).ConclusionThe competitive risk nomogram was allowed to be used for predicting HCC risk in individual patients with liver cirrhosis, taking into account both the association between risk factors and HCC and the modifying effect of competition events on this association.

Conger eel (Conger myriaster) is an economically important species in China. Due to the complex life history of the conger eel, achieving artificial reproduction has remained elusive. This study aimed to explore the effect of water stimulation on hormonal regulation during the artificial reproduction of conger eel. The experiment was divided into four groups: A1 (no hormone injection, still water), A2 (no hormone injection, flowing water), B1 (hormone injection, still water), and B2 (hormone injection, flowing water). The flowing water group maintained a flow velocity of 0.4 ± 0.05 m/s for 12 h daily throughout the 60-day period. Steroid hormone levels in the serum and ovaries of conger eels were analyzed using UPLC-MS/MS and ELISA on the 30th and 60th days of the experiment. The relative expression levels of follicle-stimulating hormone (FSHβ) and luteinizing hormone (LHβ) in the pituitary were determined by quantitative PCR. The results showed a significantly lower gonadosomatic index (GSI) in B2 compared to B1 (p < 0.05) on the 30th day. FSH was found to act only in the early stages of ovarian development, with water stimulation significantly enhancing FSH synthesis (p < 0.05), while FSHβ gene was not expressed after hormone injection. Conversely, LH was highly expressed in late ovarian development, with flowing water stimulation significantly promoting LH synthesis (p < 0.05). Serum cortisol (COR) levels were significantly higher in the flowing water group than in the still water group (p < 0.05). Furthermore, estradiol (E2) content of B2 was significantly lower than that of B1 on the 30th and 60th day. Overall, flowing water stimulation enhanced the synthesis of FSH in early ovarian development and LH in late ovarian development, while reducing E2 accumulation in the ovaries. In this study, the effect of flowing water stimulation on hormone regulation during the artificial reproduction of conger eel was initially investigated to provide a theoretical basis for optimizing artificial reproduction techniques.

At present, most fuel cell engines are single-stack systems, and high-power single-stack systems have bottlenecks in meeting the power requirements of heavy-duty trucks, mainly because the increase in the single active area and the excessive number of cells will lead to poor distribution uniformity of water, gas and heat in the stack, which will cause local attenuation and reduce the performance of the stack. This paper introduces the design concept of internal combustion engine, takes three-stack fuel cell engine as an example, designs multi-stack fuel cell system scheme and serialized high-voltage scheme. Through Intelligent control technology of independent hydrogen injection based on multi-stack coupling, the hydrogen injection inflow of each stack is controlled online according to the real-time anode pressure to achieve accurate fuel injection of a single stack and ensure the consistency between multiple stacks. proves the performance advantage of multi-stack fuel cell engine through theoretical design, intelligent control and test verification, and focuses on analyzing the key technical problems that may exist in multi-stack consistency. The research results provide a reference for the design of multi-stack fuel cell engines, and have important reference value for the powertrain design of long-distance heavy-duty and high-power fuel cell trucks.

Multi-energy synergy systems integrating high-penetration large-scale plug-in electric vehicles, distributed renewable energy generations, and battery energy storage systems have great potential to reduce the reliance of the grid on traditional fossil fuels. However, the random charging characteristics of plug-in electric vehicles and the uncertainty of photovoltaics may impose an additional burden on the grid and affect the supply–demand equilibrium. To address this issue, judicious scheduling optimization offers an effective solution. In this study, considering charge and discharge management of plug-in electric vehicles and intermittent photovoltaics, a novel Multi-energy synergy systems scheduling framework is developed for solving grid instability and unreliability issues. This formulates a large-scale mixed-integer problem, which calls for a powerful and effective optimizer. The new binary level-based learning optimization algorithm is proposed to address nonlinear large-scale high-coupling unit commitment problems. To investigate the feasibility of the proposed scheme, numerical experiments have been carried out considering multiple scales of unit numbers and various scenarios. Finally, the results confirm that the proposed scheduling framework is reasonable and effective in solving unit commitment problems, can achieve 3.3% cost reduction and demonstrates superior performance in handling large-scale energy optimization problems. The integration of plug-in electric vehicles, distributed renewable energy generations, and battery energy storage systems is verified to reduce the output power of 192.72 MW units during peak periods to improve grid stability. Therefore, optimizing energy utilization and distribution will become an indispensable part of future power systems.

IntroductionThe gut microbiota, T cell subsets, and cytokines participate in tuberculosis (TB) pathogenesis. To date, the mechanisms by which these factors interactively promote TB development at different time points remain largely unclear. In the context of this study, We looked into the microorganisms in the digestive tract, T cell types, and cytokines related to tuberculosis.MethodsAccording to QIIME2, we analyzed 16SrDNA sequencing of the gut microbiome on the Illumina MiSeq. Enzyme-linked immunosorbent assay was used to measure the concentrations of cytokines.ResultsWe showed the presence of 26 identifiable differential microbiomes in the gut and 44 metabolic pathways between healthy controls and the different time points in the development of TB in patients. Five bacterial genera (Bacteroides, Bifidobacterium, Faecalibacterium, Collinsella, and Clostridium) were most closely associated with CD4/CD8, whereas three bacterial taxa (Faecalibacterium, Collinsella, and Clostridium) were most closely associated with CD4. Three bacterial taxa (Faecalibacterium, Ruminococcus, and Dorea) were most closely associated with IL-4. Ruminococcus was most closely associated with IL-2 and IL-10.ConclusionDiverse microorganisms, subsets of T cells, and cytokines, exhibiting varying relative abundances and structural compositions, were observed in both healthy controls and patients throughout distinct phases of tuberculosis. Gaining insight into the function of the gut microbiome, T cell subsets, and cytokines may help modulate therapeutic strategies for TB.

Previous studies have shown that early-life exposure to fine particulate matter (PM2.5) is associated with an increasing risk of autism spectrum disorder (ASD), however, the specific sensitive period of ASD is unknown. Here, a model of dynamic whole-body concentrated PM2.5 exposure in pre- and early-postnatal male offspring rats (MORs) was established. And we found that early postnatal PM2.5 exposed rats showed more typical ASD behavioral characteristics than maternal pregnancy exposure rats, including poor social interaction, novelty avoidance and anxiety disorder. And more severe oxidative stress and inflammatory responses were observed in early postnatal PM2.5 exposed rats. Moreover, the expression level of phosphatase and tensin homolog deleted on chromosome ten (PTEN) was down-regulated and the ratios of p-PI3K/PI3K and p-AKT/AKT were up-regulated in early postnatal PM2.5 exposed rats. This study suggests that early postnatal exposure to PM2.5 is more susceptible to ASD-like phenotype in offspring than maternal pregnancy exposure and the activation of PI3K-AKT signaling pathway may represent underlying mechanisms.

Objective: Deltamethrin (DLM) is a commonly used insecticide, which is harmful to many organs. Here, we explored the effects of chronic low-dose DLM residues on colon tissue and its potential mechanism. Methods: The mice were given long-term low-dose DLM by intragastric administration, and the body weights and disease activity index (DAI) scores of the mice were regularly recorded. The colon tissues were then collected for hematoxylin-eosin, immunofluorescence and immunohistochemistry staining. Besides, the RNA sequencing was performed to explore the potential mechanism. Results: Our results showed that long-term exposure to low-dose DLM could cause inflammation in mice colon tissue, manifested as weight loss, increased DAI score, increased apoptosis of colonic epithelial cells, and increased infiltration of inflammatory cells. However, we observed that after long-term exposure to DLM and withdrawal for a period of time, although apoptosis was restored, the recovery of colon inflammation was not ideal. Subsequently, we performed RNA sequencing and found that long-term DLM exposure could lead to the senescence of some cells in mice colon tissue. The results of staining of cellular senescence markers in colon tissue showed that the level of cellular senescence in the DLM group was significantly increased, and the p53 signalling related to senescence was also significantly activated, indicating that cellular senescence played a key role in DLM-induced colitis. We further treated mice with quercetin (QUE) after long-term DLM exposure, and found that QUE could indeed alleviate DLM-induced colitis. In addition, we observed that long-term accumulation of DLM could aggravate DSS-induced colitis in mice, and QUE treatment could reverse this scenario. Conclusion: Continuous intake of DLM caused chronic colitis in mice, and the inflammation persisted even after discontinuation of DLM intake. This was attributed to the induction of cellular senescence in colon tissue. Treatment with QUE alleviated DLM-induced colitis by reducing cellular senescence. Long-term DLM exposure also aggravated DSS-induced colitis, which could be mitigated by QUE treatment.

BackgroundHepatitis B surface antigen (HBsAg) clearance is associated with improved long-term outcomes and reduced risk of complications. The aim of our study was to identify the effects of levels of HBsAg in HCC patients undergoing TACE and sequential ablation. In addition, we created a nomogram to predict the prognosis of HCC patients with high levels of HBsAg (≥1000U/L) after local treatment.MethodThis study retrospectively evaluated 1008 HBV-HCC patients who underwent TACE combined with ablation at Beijing Youan Hospital and Beijing Ditan Hospital from January 2014 to December 2021, including 334 patients with low HBsAg levels and 674 patients with high HBsAg levels. The high HBsAg group was divided into the training cohort (N=385), internal validation cohort (N=168), and external validation cohort (N=121). The clinical and pathological features of patients were collected, and independent risk factors were identified using Lasso-Cox regression analysis for developing a nomogram. The performance of the nomogram was evaluated by C-index, receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) curves in the training and validation cohorts. Patients were classified into high-risk and low-risk groups based on the risk scores of the nomogram.ResultAfter PSM, mRFS was 28.4 months (22.1-34.7 months) and 21.9 months (18.5-25.4 months) in the low HBsAg level and high HBsAg level groups (P

IntroductionThere are three main types of culture in human society, namely, individual-oriented, relationship-oriented and social-oriented cultures. In history, there are two main positions on the relationship between culture and self-construal: the cultural determinist position and the interaction position. After analyzing literature critically, we propose that the interaction position is more persuasive than the cultural determinist position. A self-construal model was constructed from an interactionist and polycultural perspective, pointing out the relationship between three cultures and self-construal. We argue that individuals interacting with cultures in the context of globalization can develop a more integrated self-construal. The present study proposes the existence of polycultural self-construal, and aimed to explore how self-construal factors relate to cultures.MethodsThree approaches—psychological tests, priming with cultural icons and content analysis—were used to explore mechanisms between cultures (individual-oriented, relationship-oriented, and social-oriented cultures) and self-construal. In Study 1, we recruited 460 undergraduate students as participants through campus advertising to complete three psychological tests, namely, the Cultural Identity Scale (CIS), the Marlowe-Crowne Social Approval Scale (MC-SDS), and the Polycultural Self-construal Scale (PSCS). In Study 2, we created icon materials that could prime the three cultures. The experimental process was divided into two stages: priming and measurement. First, 165 participants were presented with icon materials on the computer screen to activate the corresponding culture, and then they were asked to complete the PSCS. In Study 3, the experimental procedures were followed as for Study 2. Then the Ten Statements Test (TST) was used. Each of the 178 participants gave 10 different responses to the question of “Who am I?.” Each participant’s “I am …” narratives were qualitatively processed using content analysis.ResultsThe individual-oriented culture mainly affects the individuality and equality factor of self-construal. The relationship-oriented culture mainly impacts the relationality factor of self-construal, while the social-oriented culture mainly affects the collectivity and equality factors of self-construal. There were no significant differences in the effects of the three cultures on the autonomy factor of self-construal. The multi-components of the polycultural self-construal are difficult to interpret based on one culture type. All three cultures have specific and shared effects on human self-construal.

ABSTRACTCRF01_AE strains have been shown to form multiple transmission clusters in China, and some clusters have disparate pathogenicity in Chinese men who have sex with men. This study focused on other CRF01_AE clusters prevalent in heterosexual populations. The CD4+ T-cell counts from both cross-section data in National HIV Molecular Epidemiology Survey and seropositive cohort data were used to evaluate the pathogenicity of the CRF01_AE clusters and other HIV-1 sub-types. Their mechanisms of pathogenicity were evaluated by co-receptor tropisms, predicted by genotyping and confirmed with virus isolate phenotyping, as well as inflammation parameters. Our research elucidated that individuals infected with CRF01_AE clusters 1 and 2 exhibited significantly lower baseline CD4+ T-cell counts and greater CD4+ T-cell loss in cohort follow-up, compared with other HIV-1 sub-types and CRF01_AE clusters. The increased pathogenesis of cluster 1 or 2 was associated with higher CXCR4 tropisms, higher inflammation/immune activation, and increased pyroptosis. The protein structure modeling analysis revealed that the envelope V3 loop of clusters 1 and 2 viruses is favorable for CXCR4 co-receptor usage. Imbedded with the most mutating reverse transcriptase, HIV-1 is one of the most variable viruses. CRF01_AE clusters 1 and 2 have been found to have evolved into more virulent strains in regions with predominant heterosexual infections. The virulent strains increased the pressure for early diagnosis and treatment in HIV patients. To save more lives, HIV-1 surveillance systems should be upgraded from serology and genotyping to phenotyping, which could support precision interventions for those infected by virulent viruses.IMPORTANCERetroviruses swiftly adapt, employing error-prone enzymes for genetic and phenotypic evolution, optimizing survival strategies, and enhancing virulence levels. HIV-1 CRF01_AE has persistently undergone adaptive selection, and cluster 1 and 2 infections display lower counts and fast loss of CD4+ T cells than other HIV-1 sub-types and CRF01_AE clusters. Its mechanisms are associated with increased CXCR4 tropism due to an envelope structure change favoring a tropism shift from CCR5 to CXCR4, thereby shaping viral phenotype features and impacting pathogenicity. This underscores the significance of consistently monitoring HIV-1 genetic evolution and phenotypic transfer to see whether selection bias across risk groups alters the delicate balance of transmissible versus toxic trade-offs, since virulent strains such as CRF01_AE clusters 1 and 2 could seriously compromise the efficacy of antiviral treatment. Only through such early warning and diagnostic services can precise antiviral treatments be administered to those infected with more virulent HIV-1 strains.

Abstract Injection-production operation parameters, the minimum injection gas pressure (IGP: operation pressure), IGP interval, minimum IGP residence time, and injection-production cycle of the underground salt rock gas storage under long-term operation, affect not only the capacity and working ability of a salt cavern but also be crucial to the safety and stability of the surrounding rock. A 3D geo-mechanical model of the salt cavern is established to study the stability of the storage in the operation period. The deformation, expansion safety factor, volume shrinkage, and plastic zone are comprehensively considered for predicting the feasibility and stability of the salt cavern. The stability of the surrounding rock of the cavern with different injection-production parameters and the impact of each parameter on the stability of the cavern during operating are systematically investigated. The results indicate that the displacement, the expansion coefficient of the surrounding rock, and the volume shrinkage rate of the salt cavern reduces significantly with the increment of IGP interval and minimum IGP, while they increases with raising the minimum IGP residence time and injection-production cycle. With the continuous operation of the cavity, the displacement and the volume shrinkage rate enhances significantly year by year with the augment of operation parameters, moreover, their value show a fluctuating upward trend with the alternation of the gas injection and the production. The volume of the plastic zone is enlarged with the increment of the IGP interval, minimum IGP, and injection-production cycle, while it reduces with the extension of the minimum IGP residence time. The variation becomes remarkably with the augment of parameters. The sensitivity coefficients of each injection-production operation parameter are ranked, from large to small, as follows: IGP interval, minimum IGP, minimum IGP residence time, injection-production cycle. The results can offer beneficial reference for effectively optimize the injection-production parameters, so as to provide technical guidance for ensuring the stability of the storage and meeting requirements for the storage capacity.

Abstract Objective The aim of the present study was to explore the prognostic role of γδ T cells in colorectal cancer, and establish a nomogram for predicting the survival of the patients. Methods Immunohistochemistry was performed to analyze the infiltration degree of γδ T cells in tumor and normal tissues of colorectal cancer. The relationship between γδ T cells infiltration in tumor tissues and the prognosis of patients with colorectal cancer were determined by Cox regression analysis and survival analysis. R software was used to establish and verify a nomogram for predicting the prognosis of patients with colorectal cancer. Results The degree of γδ T cell infiltration in tumor tissues and normal tissues of CRC was not different (t = 0.35, P = 0.73). However, the infiltration of γδ T cell was related to the survival status of the patients (x 2 = 4.88, P = 0.03). Besides, the infiltrating degree of γδ T cells in tumor tissue was obviously related to the prognostic improvement of the patients with colorectal cancer (log-rank P = 0.02) and could reflect the benefit of adjuvant chemotherapy. The nomogram based on tumor diameter, tumor location, AJCC stage, chemotherapy, serum CEA level and γδ T cell infiltration was established and could provide a reference for predicting the survival of colorectal cancer patients. Conclusion γδ T cell infiltration degree in tumor tissue was an important factor to improve the outcome of patients with colorectal cancer, and can predict the benefit of adjuvant chemotherapy.

Abstract Background About 10% of non-small cell lung cancer (NSCLC) patients with epidermal growth factor receptor (EGFR) mutations are harbored as uncommon mutations. This study aimed to explore the efficacy and safety of dacomitinib, a second-generation EGFR tyrosine kinase inhibitor (EGFR-TKIs), in treating uncommon EGFR-mutated advanced NSCLC. Methods Treatment-naïve advanced NSCLC patients treated with dacomitinib at Hunan Cancer Hospital with uncommon EGFR mutations were evaluated. The primary endpoint was progression-free survival (PFS). Secondary end points included overall survival (OS), objective response rate (ORR), disease control rate (DCR) and safety. Result Between December 2019 and December 2021, a total of 16 patients was included. Median PFS was 14.0 (95% CI 4.32–23.7) months, and median OS was not reached. ORR was 68.8% (95% CI 41.3 to 89.0%) and DCR was 93.8% (95%CI 69.8 to 99.8%), including three achieving complete remission (CR) and eight achieving partial remission (PR). Median PFS for patients with brain metastasis was 9.0 (95%CI 6.9 to 11.1) months. Intracranial ORR was 100%, including 2 CR and 4 PR. Major treatment-related adverse events (TRAEs) included rash (87.5%), paronychia (62.5%), oral ulcers (50.0%), and diarrhea (50.0%), none of which were ≥ grade 3 TRAEs. Conclusions Dacomitinib showed good activity and manageable toxicity in NSCLC patients with uncommon EGFR mutations.

Abstract Foundation models, often pre-trained with large-scale data, have achieved paramount success in jump-starting various vision and language applications. Recent advances further enable adapting foundation models in downstream tasks efficiently using only a few training samples, e.g., in-context learning. Yet, the application of such learning paradigms in medical image analysis remains scarce due to the shortage of publicly accessible data and benchmarks. In this paper, we aim at approaches adapting the foundation models for medical image classification and present a novel dataset and benchmark for the evaluation, i.e., examining the overall performance of accommodating the large-scale foundation models downstream on a set of diverse real-world clinical tasks. We collect five sets of medical imaging data from multiple institutes targeting a variety of real-world clinical tasks (22,349 images in total), i.e., thoracic diseases screening in X-rays, pathological lesion tissue screening, lesion detection in endoscopy images, neonatal jaundice evaluation, and diabetic retinopathy grading. Results of multiple baseline methods are demonstrated using the proposed dataset from both accuracy and cost-effective perspectives.

The concept of passenger-centric design has become increasingly significant in the intelligent automotive industry. Enhancing in-cabin thermal comfort while maintaining energy efficiency is crucial, and to this end, we leverage real-time passenger thermal sensation as a basis for HVAC control strategies. This study introduces a non-invasive, dual-phase prediction model that evaluates passenger thermal comfort by utilizing facial thermal imaging and environmental factors. The proposed model employs a deep learning neural network to extract pertinent features from the facial thermal images for an initial prediction. Then this prediction is refined by integrating it with environmental data through a machine learning algorithm, facilitating real-time personal thermal comfort assessment. Data collection for the model was performed across two distinct seasons, with 22 participants in summer and 18 in winter, gathering facial thermal images, environmental parameters, and thermal sensation votes to construct a comprehensive dataset. Analysis revealed a set of critical environmental factors that correlate strongly with thermal sensation votes, which were used as auxiliary features in the model. The performance of the proposed dual-phase approach, combining deep learning and machine learning techniques, demonstrated robust effectiveness on both summer and winter datasets. This substantiates the method's practicality for real-world application within vehicle environments.

Purpose: To investigate whether erythropoietin (EPO) can treat pulmonary arterial hypertension (PAH) in rats by regulating the differentiation and homing of bone marrow mesenchymal stem cells (BMSCs) through Notch1/Jagged signaling pathway. Materials & methods: BMSCs were isolated from the bone marrow of 6-week-old male SD rats by whole bone marrow method and identified. BMSCs were treated with 500 IU/mL EPO, and the proliferation, migration, invasion and differentiation ability, and the expression of MMP-2 and MMP-9 protein of BMSCs were detected in vitro. After the establishment of the pulmonary hypertension model in rats, BMSCs were intervened with different concentrations of EPO and injected into the rats through intravenous injection. The levels of TNF-α, IL-1β and IL-6 in lung tissue, the expression of SRY CXCR4, CCR2, Notch1 and Jagged protein in lung tissue, and the levels of TGF-α, vascular endothelial factor (VEGF), IGF-1 and HGF in serum were detected. Immunofluorescence (IF) staining was used to detect the co-localization of CD34. Results: EPO promoted the proliferation, migration, and invasion of BMSCs by inhibiting Notch1/Jagged pathway in vitro, and induced BMSCs to differentiate into vascular smooth muscle cells and vascular endothelial cells. EPO inhibited Notch1/Jagged pathway in PAH rats, induced BMSCs homing and differentiation, increased the levels of TGF-α, VEGF, IGF-1 and HGF, and decreased the levels of TNF-α, IL-1β and IL-6. Discussion & conclusion: EPO can inhibit the Notch1/Jagged pathway and promote the proliferation, migration, invasion, homing and differentiation of BMSCs to treat pulmonary hypertension in rats in vitro and in vivo.

The performance of on-orbit GaAs-based solar cells is susceptible to the displacement damage effect. The proton-induced primary displacement damage in GaAs on a geosynchronous equatorial orbit (GEO) was simulated and analyzed by combining the Monte Carlo (MC) and molecular dynamics (MD) methods. The MC simulation provided the distribution of primary knock-on atoms (PKAs) in GaAs induced by GEO-related protons to the MD simulation. In MD simulations, the effects of radiation fluence and ambient temperature on the displacement damage were considered. The simulation results showed that GEO-related protons generated a significant number of PKAs within an energy range of below 10 keV in GaAs. The high-fluence radiation emulated by the binary PKA could generate more point defects and cluster defects in GaAs than the low-fluence radiation emulated by single PKAs. As compared to room temperature (300 K), both a low (100 K) and high (500 K) ambient temperature could deteriorate the displacement damage. In addition, a high ambient temperature of 500 K could induce widespread thermal spikes in GaAs as compared to 100 and 300 K. This work can provide useful insight into the proton-induced displacement damage in GaAs and the radiation hardening of GaAs-based photoelectric devices in space.

BackgroundCrohn’s disease (CD) is a non-specific chronic inflammatory disease of the gastrointestinal tract and is a phenotype of inflammatory bowel disease (IBD). The current study sought to compile the resting-state functional differences in the brain between CD patients and healthy controls.MethodsThe online databases PubMed, Web of Science Core, and EMBASE were used to find the published neuroimage studies. The search period was from the beginning through December 15, 2023. The predetermined inclusion and exclusion criteria allowed for the identification of the studies. The studies were assembled by two impartial reviewers, who also assessed their quality and bias.ResultsThis review comprised 16 resting-state fMRI studies in total. The included studies generally had modest levels of bias. According to the research, emotional processing and pain processing were largely linked to increased or decreased brain activity in patients with CD. The DMN, CEN, and limbic systems may have abnormalities in patients with CD, according to research on brain networks. Several brain regions showed functional changes in the active CD group compared to the inactive CD group and the healthy control group, respectively. The abnormalities in brain areas were linked to changes in mood fluctuations (anxiety, melancholy) in patients with CD.ConclusionFunctional neuroimaging helps provide a better understanding of the underlying neuropathological processes in patients with CD. In this review, we summarize as follows: First, these findings indicate alterations in brain function in patients with CD, specifically affecting brain regions associated with pain, emotion, cognition, and visceral sensation; second, disease activity may have an impact on brain functions in patients with CD; and third, psychological factors may be associated with altered brain functions in patients with CD.

PurposeTo evaluate the characteristic of blood supply of liver portal vein tumor thrombus (PVTT) using perfusion indexes and spectral parameters.MethodsBetween July 2020 and December 2022, the study enrolled 25 liver cancer patients completed with PVTT (male=20, female=5; age 41-74 years (59.48 ± 9.12)) from the Interventional Department of Jiangsu Cancer Hospital. There were 11 cases of type III PVTT, 12 of type II PVTT, and 2 of type I PVTT (Cheng’s classification). All patients underwent spectral perfusion scans through dual-layer spectral detector computed tomography. The PVTTs were divided into proximal and distal groups based on the distance between the tumor thrombus and the main portal vein. The perfusion analysis was performed on the 120-kVp conventional images to generate hepatic perfusion index (HPI). The spectral based images (SBIs) during the artery and venous peak phases were extracted from the perfusion data. The iodine map and 40&100-keV virtual monoenergetic image (VMI) were generated from SBI data. HPI, iodine concentration (IC), CT value at 40 and 100-keV, and spectral slope (40-100keV) of the primary lesion, proximal and distal PVTT, and liver parenchyma were measured and compared. The correlation between the primary lesion and proximal and distal PVTT was analyzed.ResultsThe IC and spectral slope during the arterial and venous peak phases and HPI of the primary lesion, proximal PVTT, and distal PVTT were highly correlated (P

Summary: Background: Platinum-doublet chemotherapy plus immunotherapy has been the standard of care for the first-line treatment of advanced non-small cell lung cancer lacking actional driver mutations. However, optimization of drug combinations is still needed to find a better balance between therapeutic efficacy and safety in the immunotherapy era. We aimed to investigate the efficacy and safety of platinum-free albumin bound paclitaxel (nab-paclitaxel) combined with camrelizumab and apatinib as first-line treatment for patients with advanced lung adenocarcinoma. Methods: In this multicenter open-label, single-arm phase II trial, patients with systemic treatment-naïve advanced lung adenocarcinoma without epidermal growth factor receptor (EGFR) or anaplastic lymphoma kinase (ALK) mutations received a rational-based combination of camrelizumab (200 mg intravenously, day one), apatinib (250 mg, q.d., five continuous days per week), and nab-paclitaxel (135 mg/m2 intravenously, days one and eight) every three weeks for four to six cycles in China. Patients with controlled disease were maintained with camrelizumab and apatinib. The primary end point was progression-free survival (PFS). This trial is registered with ClinicalTrials.gov (No. NCT04459078). Findings: Between August 26, 2020 and May 20, 2022, 64 patients were enrolled. The median PFS was 14.3 (95% CI: 9.9, not reached) months. The confirmed objective response rate was 64.1% (95% CI: 51.1, 75.7). The grade 3–4 hematologic treatment-related adverse events (TRAEs) were decreased neutrophil count (14.1%), decreased white blood cell count (7.8%), and anemia (3.1%). The most common non-hematologic TRAEs of grade 3–4 were increased alanine transaminase (18.8%) and aspartate transaminase (15.6%). No treatment-related death occurred. The quality of life was on average not clinically meaningful worse through treatment cycle 14. Interpretation: Nab-paclitaxel plus camrelizumab and apatinib showed clinically meaningful anti-tumor activity and manageable safety, with few hematologic toxicities, and might be a potential treatment option in patients with advanced lung adenocarcinoma lacking EGFR/ALK mutations. Funding: Heath Research Foundation of Chinese Society of Clinical Oncology, Hunan Provincial Natural Science Foundation of China, Hunan Cancer Hospital Climb Plan, Sister Institution Network Fund of The University of Texas MD Anderson Cancer Center, The Science and Technology Innovation Program of Hunan Province, and Suzhou Sheng Diya Biomedical Co., Ltd, a subsidiary of Jiangsu Hengrui Pharmaceuticals Co., Ltd. (Shanghai, China).

Geosmin is an environmental pollutant that causes off-flavor in water and aquatic products. The high occurrence of geosmin contamination in aquatic systems and aquaculture raises public awareness, however, few studies have investigated the response pathways of geosmin stress on freshwater fish. In this research, grass carp were exposed to 50 μg/L geosmin for 96 h, liver tissue was sequenced and validated using real-time qPCR. In total of 528 up-regulated genes and 488 down-regulated genes were observed, includes cytochrome P450 and uridine diphosphate (UDP)-glucuronosyltransferase related genes. KEGG analysis showed that chemical carcinogenesis-DNA adducts, metabolism of xenobiotics by cytochrome P450, drug metabolism-cytochrome P450 pathway was enriched. Common genes from the target genes of microRNAs and differential expression genes are enriched in metabolism of xenobiotics cytochrome P450 pathway. Two miRNAs (dre-miR-146a and miR-212–3p) down regulated their target genes (LOC127510138 and adh5, respectively) which are enriched cytochrome P450 related pathway. The results present that geosmin is genetoxic to grass carp and indicate that cytochrome P450 system and UDP-glucuronosyltransferase play essential roles in biotransformation of geosmin. MicroRNAs regulate the biotransformation of geosmin by targeting specific genes, which contributes to the development of strategies to manage its negative impacts in both natural and artificial environments.

In this study, we explored the impact of ionic liquid gating on YBa2Cu3O7−x superconductivity. We observed that direct contact of YBa2Cu3O7−x and the ionic liquid N-diethyl-N-methyl-N-(2methoxyethyl)ammonium bis(trifluoromethanesulfonyl)imide (DEME-TFSI) results in irreversible electrochemical reactions, despite the application of a relatively low gate voltage at 220 K. Capping a thin layer of boron nitride (BN) on YBa2Cu3O7−x enabled a reversible modulation of carrier density at 300 K. Benefiting from the higher ion mobility of ionic liquid at 300 K, this modification led to more than a one-time increase in carrier density, a 3-time improvement in voltage modulation efficiency, and a reversible tuning of the superconducting temperature. These findings suggest that using a BN capping layer holds promise for enhancing the stability and efficiency of devices using ionic liquid gating.

Strigolactone (SL) plays essential roles in plant development and the metabolism of rice leaves. However, the impact of SL on the accumulation of nutritional metabolites in polished rice, as well as the transcription factors directly involved in SL synthesis, remains elusive. In this study, we performed a metabolome analysis on polished rice samples from mutants of an SL biosynthetic gene, OsDWARF10 (OsD10). Compared with those in the wild type plants, primary and secondary metabolites exhibited a series of alterations in the d10 mutants. Notably, the d10 mutants showed a substantial increase in the amino acids and vitamins content. Through a yeast one-hybridization screening assay, we identified OsSPL3 as a transcription factor that binds to the OsD10 promoter, thereby inhibiting OsD10 transcription in vivo and in vitro. Furthermore, we conducted a metabolic profiling analysis in polished rice from plants that overexpressed OsSPL3 and observed enhanced levels of amino acids and vitamins. This study identified a novel transcriptional repressor of the SL biosynthetic gene and elucidated the regulatory roles of OsSPL3 and OsD10 on the accumulation of nutritional metabolites in polished rice.

ABSTRACTBackground: N6-methyladenosine (m6A) is the most abundant modification in eukaryotic mRNA. However, its role in non-small cell lung cancer (NSCLC) has not been completely elucidated.Objective: To explore whether methyltransferase like 3 (METTL3) in cancer associated fibroblasts (CAFs) affects the secretion of IL-18, which drives NSCLC cells to regulate PD-L1-mediated immunosuppression via the nuclear factor kappa B (NF-κB) pathway.Methods: Histopathological features of NSCLC tissues were identified by H&E and IHC staining. The levels of m6A writers (METTL3), IL-18 and NF-κB pathway related genes were assessed. The quantity of CD8+ T cells was evaluated by flow cytometry (FCM). The direct binding relationship between METTL3 and IL-18 mRNA was detected by RIP assay and RNA pulldown and confirmed by dual – luciferase reporter assay. The level of RNA m6A was detected by RNA m6A dot blot and meRIP assays. A heterotopic implantation model of NSCLC was established in NOD-SCID mice for further explore the effect of CAF derived METTL3 on immunosuppression of NSCLC in vivo.Results: Our results illustrated that METTL3 was down-regulated in CAFs, and CAF derived METTL3 alleviated PD-L1-mediated immunosuppression of NSCLC through IL-18. Subsequently, we found that IL-18 was main effector of CAF-derived METTL3 against immunosuppression of NSCLC, and IL-18 accelerated immunosuppression of NSCLC by driving NF-κB pathway. In vivo, METTL3 knockdown-derived CAFs accelerated immunosuppression of NSCLC.Conclusion: IL-18 served as a main effector of CAF-derived METTL3 against immunosuppression of NSCLC via driving NF-κB pathway.

As a pleiotropic cytokine in the interleukin (IL)-12 family, IL-27β plays a significant role in regulating immune cell responses, eliminating invading pathogens, and maintaining immune homeostasis. Although non-mammalian IL-27β homologs have been identified, the mechanism of whether and how it is involved in adaptive immunity in early vertebrates remains unclear. In this study, we identified an evolutionarily conserved IL-27β (defined as OnIL-27β) from Nile tilapia (Oreochromis niloticus), and explored its conserved status through gene collinearity, gene structure, functional domain, tertiary structure, multiple sequence alignment, and phylogeny analysis. IL-27β was widely expressed in the immune-related tissues/organ of tilapia. The expression of OnIL-27β in spleen lymphocytes increased significantly at the adaptive immune phase after Edwardsiella piscicida infection. OnIL-27β can bind to precursor cells, T cells, and other lymphocytes to varying degrees. Additionally, IL-27β may be involved in lymphocyte-mediated immune responses through activation of Erk and JNK pathways. More importantly, we found that IL-27β enhanced the mRNA expression of the Th1 cell-associated cytokine IFN-γ and the transcription factor T-bet. This potential enhancement of the Th1 response may be attributed to the activation of the JAK1/STAT1/T-bet axis by IL-27β, as it induced increased transcript levels of JAK1, STAT1 but not TYK2 and STAT4. This study provides a new perspective for understanding the origin, evolution and function of the adaptive immune system in teleost.

ABSTRACTHIV-1 infection is mediated by a viral envelope subsequently binding to CD4 receptor and two main coreceptors, CCR5 (R5) for primary infection and CXCR4 (X4) in chronic infection. Switching from R5 to X4 tropism in HIV-1 infection is associated with increased viral pathogenesis and disease progression. The coreceptor switching is mainly due to variations in the V3 loop, while the mechanism needs to be further elucidated. We systematically studied the determinant for HIV-1 coreceptor switching by substitution of the genes from one R5 and one X4 pseudoviruses. The study results in successfully constructing two panels of chimeric viruses of R5 to X4 forward and X4 to R5 reverse switching. The determinants for tropism switching are the combined substitution of the V3 loop and C4 region of the HIV-1 envelope. The possible mechanism of the tropism switching includes two components, the V3 loop to enable the viral envelope binding to the newly switched coreceptor and the C4 region, to compensate for the loss of fitness caused by deleterious V3 loop mutations to maintain the overall viral viability. The combined C4 and V3 substitution showed at least an eightfold increase in replication activity compared with the pseudovirus with only V3 loop substitution. The site-directed mutations of N425R and S440-I442 with charged amino acids could especially increase viral activity. This study could facilitate HIV-1 phenotype surveillance and select right entry inhibitor, CCR5 or CXCR4 antagonists, for antiviral therapy.