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AIM: To investigate the effect of skullcapflavone II (SCF-II) on the epithelial-mesenchymal transition (EMT) induced by transforming growth factor beta (TGF-β) in human corneal epithelial cells (HCECs), as well as to identify the signaling pathways that may be involved. METHODS: HCECs were cultured in vitro. At a SCF-II (5, 10 µmol/L) dose, cell viability was analysed with a cell counting kit-8 (CCK-8) assay, and cell migration was monitored with wound healing and Transwell migration assays. There were 4 groups: SCF-II, TGF-β, SCF-II+TGF-β and Control. Western blotting and immunofluorescence were performed to show the expression of EMT markers and the translocation of nuclear factor kappa-B (NF-κB) into the nucleus in the 4 groups. RESULTS: Treatment with SCF-II decreased HCEC viability in a dose-dependent manner. A concentration below 10 µmol/L did not present obvious cell toxicity, and survival rates were more than 70% at 48h. Treatment with SCF-II (5 and 10 µmol/L) significantly impeded migration in wound healing and Transwell migration assays (P

Understanding the variation patterns of tunnel boring machine (TBM) operational parameters is crucial for assessing engineering geological conditions and quality grades of surrounding rock within tunnels. Studying the multifractal characteristics of the TBM operational parameters can help identify the patterns, but the relevant research has not yet been explored. This paper proposed a novel classification model for quality grades of surrounding rock in TBM tunnels based on multifractal analysis theory. Initially, the statistical characteristics of eight TBM cycle data with different grades of surrounding rock were explored. Subsequently, the method of calculating and analyzing the multifractal characteristic parameters of the TBM operational data was deduced and summarized. The research results showed that the TBM operational parameters of cutterhead torque, total thrust, advance rate, and cutterhead rotation speed have significant multifractal characteristics. Its multifractal dimension, midpoint slope of the generalized fractal spectrum, and singularity strength range can be used to evaluate the surrounding rock grades of the tunnel. Finally, a novel classification model for the tunnel surrounding rocks based on the multifractal characteristic parameters was proposed using the multiple linear regression method, and the model was verified through four TBM cycle data containing different surrounding rock grades. The results showed that the proposed multifractal-based classification model for tunnel surrounding rocks has high accuracy and applicability. This study not only achieves multifractal feature representation and surrounding rock classification for TBM operational parameters but also holds the potential for adaptive adjustment of TBM operational parameters and automated tunneling applications.

Abstract Dual-atom catalysts featuring synergetic dinuclear active sites, have the potential of breaking the linear scaling relationship of the well-established single-atom catalysts for oxygen reduction reaction; however, the design of dual-atom catalysts with rationalized local microenvironment for high activity and selectivity remains a great challenge. Here we design a bisalphen ladder polymer with well-defined densely populated binuclear cobalt sites on Ketjenblack substrates. The strong electron coupling effect between the fully-conjugated ladder structure and carbon substrates enhances the electron transfer between the cobalt center and oxygen intermediates, inducing the low-to-high spin transition for the 3d electron of Co(II). In situ techniques and theoretical calculations reveal the dynamic evolution of Co2N4O2 active sites and reaction intermediates. In alkaline conditions, the catalyst exhibits impressive oxygen reduction reaction activity featuring an onset potential of 1.10 V and a half-wave potential of 1.00 V, insignificant decay after 30,000 cycles, pushing the overpotential boundaries of ORR electrocatalysis to a low level. This work provides a platform for designing efficient dual-atom catalysts with well-defined coordination and electronic structures in energy conversion technologies.

The frequency and spatial extent of cyanobacterial bloom outbreaks have increased in recent years due to climate warming and human activities, causing significant harm to inland water ecosystems. Phycocyanin (PC), a characteristic pigment of cyanobacteria, plays a crucial role in detecting cyanobacterial blooms and providing early warnings. However, accurately estimating PC in turbid waters using remote sensing is challenging due to the optical complexity of most inland waters and the relatively weak optical signal of PC. To address this issue, an enhanced three-band algorithm (ETBA) is proposed for retrieving PC concentration in inland waters. Since the PC absorption feature at 620 nm is prone to interference from non-PC pigments, the algorithm incorporates the quantification of the absorption coefficient of non-PC pigments at 620 nm (${{{\bm{a}}}_{{\bm{ph}} - {\bm{pc}}}}( {620} )$) to improve the accurate of estimating ${{{\bm{a}}}_{{\bm{pc}}}}( {620} )$. Using in situ observation data from Erhai Lake as an example, the results show that ETBA significantly outperforms the original three-band algorithm in mitigating interference from non-PC pigments. Among all the phycocyanin (PC) algorithms considered in this study, the Enhanced Three Band Algorithm (ETBA) achieved the lowest mean relative error (12.76%) and a goodness of fit of (R2 = 0.73), with the second lowest root mean square error of 0.37 μg/L. Therefore, the introduction of the ETBA has a direct positive impact on monitoring harmful algal blooms caused by cyanobacteria in inland and coastal water.

Abstract Mitochondrial dysfunctions are closely associated with different types of disease, including cancer. Carnitine acetyltransferase (CRAT) is a mitochondrial-localized enzyme catalyzing the reversible transfer of acyl groups from an acyl-CoA thioester to carnitine and regulates the ratio of acyl-CoA/CoA. Our bioinformatics analysis using public database revealed a significant decrease of CRAT expression in ovarian cancer (OC). However, the functions of CRAT have rarely been investigated in human cancers, especially in OC. Here, we found a frequent down-regulation of CRAT in OC, which is mainly caused by up-regulation of miR-132-5p. Downregulation of CRAT was significantly associated with shorter survival time for patients with OC. Forced expression of CRAT suppressed OC growth and metastasis by inducing cell cycle arrest and epithelial to mesenchymal transition (EMT). By contrast, CRAT knockdown promoted OC growth and metastasis. Mechanistically, we found that CRAT downregulation promoted OC growth and metastasis by increasing mitochondrial biogenesis to facilitate mitochondrial metabolism through reducing the acetylation of peroxisome proliferator-activated receptor-γ coactivator (PGC-1α). In summary, CRAT functions as a critical tumor suppressor in OC progression by enhancing PGC-1α-mediated mitochondrial biogenesis and metabolism, suggesting CRAT as a potential therapeutic target in treatment of OC.

Abstract Biological ion channels exhibit strong gating effects due to their zero-current closed states. However, the gating capabilities of artificial nanochannels have typically fallen short of biological channels, primarily owing to the larger nanopores that fail to completely block ion transport in the off-states. Here, we demonstrate solid-state hydrogen-bonded organic frameworks-based membranes to achieve high-performance ambient humidity-controlled proton gating, accomplished by switching the proton transport pathway instead of relying on conventional ion blockage/activation effects. Density functional theory calculations reveal that the reversible formation and disruption of humidity-induced water bridges within the frameworks facilitates the switching of proton transport mode from the adsorption site hopping to the Grotthuss mechanism. This transition, coupled with the introduction of bacterial cellulose to enhance desorption/adsorption of water clusters, enables us to achieve a superior proton gating ratio of up to 5740, surpassing state-of-the-art solid-state gating devices. Moreover, the developed membrane operates entirely on solid-state principles, rendering it highly versatile for a myriad of applications from environmental detection to human health monitoring. This study offers perspectives for the design of efficient proton gating systems.

Abstract Background Several studies have suggested that lung tissue heterogeneity is associated with overall survival (OS) in lung cancer. However, the quantitative relationship between the two remains unknown. The purpose of this study is to investigate the prognostic value of whole lung-based and tumor-based radiomics for OS in LA-NSCLC treated with definitive radiotherapy. Methods A total of 661 patients with LA-NSCLC treated with definitive radiotherapy in combination with chemotherapy were enrolled in this study, with 292 patients in the training set, 57 patients from the same hospital from January to December 2017 as an independent test set (test-set-1), 83 patients from a multi-institutional prospective clinical trial data set (RTOG0617) as test-set-2, and 229 patients from a Dutch radiotherapy center as test-set-3. Tumor-based radiomic features and whole lung-based radiomic features were extracted from primary tumor and whole lungs (excluding the primary tumor) delineations in planning CT images. Feature selection of radiomic features was done by the least absolute shrinkage (LASSO) method embedded with a Cox proportional hazards (CPH) model with 5-fold cross-internal validation, with 1000 bootstrap samples. Radiomics prognostic scores (RS) were calculated by CPH regression based on selected features. Three models based on a tumor RS, and a lung RS separately and their combinations were constructed. The Harrell concordance index (C-index) and calibration curves were used to evaluate the discrimination and calibration performance. Patients were stratified into high and low risk groups based on median RS, and a log-rank test was performed. Results The discrimination ability of lung- and tumor-based radiomics model was similar in terms of C-index, 0.69 vs. 0.68 in training set, 0.68 vs. 0.66 in test-set-1, 0.61 vs. 0.62 in test-set-2, 0.65 vs. 0.64 in test-set-3. The combination of tumor- and lung-based radiomics model performed best, with C-index of 0.71 in training set, 0.70 in test-set-1, 0.69 in test-set-2, and 0.68 in test-set-3. The calibration curve showed good agreement between predicted values and actual values. Patients were well stratified in training set, test-set-1 and test-set-3. In test-set-2, it was only whole lung-based RS that could stratify patients well and tumor-based RS performed bad. Conclusion Lung- and tumor-based radiomic features have the power to predict OS in LA-NSCLC. The combination of tumor- and lung-based radiomic features can achieve optimal performance.

Abstract Background Helicobacter pylori (H. pylori), a specific bacterium capable of surviving in the acidic environment of the stomach, has been recognized as a group of causative agents of gastric cancer. Therefore, the development of mucosal vaccines against H. pylori is expected to provide an important direction for the treatment of chronic gastritis and the prevention of gastric cancer. Methods and results In this study, we used bacteria-like particles (BLPs) obtained by treating Lactic acid bacteria (L. lactis) with hot acid, and successfully displayed the M cell-targeted H. pylori multi-epitope purified antigen SAM-FAdE, with 90% display efficiency. In addition, BLPs-SAM-FAdE can effectively target M ​​cell models and M cells of mouse Peyer’s patches (PPs) through oral immunization, promote the transport of particulate vaccines to dendritic cells (BMDCs) and stimulate their maturation, significantly increased proportion of plasma cells and germinal centers B cells. This indicates that the vaccination can induce notable antigen-specific mucosal immune responses (production of sIgA), CD4+ T cell responses (Th1/Th2/Th17) and humoral immune responses (production of serum IgG). Furthermore, oral BLPs-SAM-FAdE dramatically reduced the H. pylori adhesion and specific 16S rRNA expression of H. pylori in gastric mucosal tissue, protecting gastric tissue from damage. Conclusion BLPs-SAM-FAdE can significantly reduce the adhesion of H. pylori in gastric mucosal tissue and inhibit gastritis and gastric damage caused by H. pylori infection.

Abstract Probiotics as green inputs have been reported to regulate metabolism and immunity of fish. However, the mechanisms by which probiotics improve growth and health of fish are unclear. Therefore, the aim of this study was to investigate the effect of Bacillus subtilis HGCC-1, an indigenous probiotic isolated from fish, on growth performance, host lipid metabolism, liver inflammation and gut microbiota of golden pompano. 160,000 golden pompanos with the initial body weight of 93.6 ± 5.0 g was randomly assigned to two dietary groups: Control and HGCC-1 (control diet supplemented with 0.3 g/kg Bacillus subtilis HGCC-1 fermentation product), and after three weeks of feeding, 26 golden pompanos were randomly collected from each group for gut microbiome and host phenotype analysis. Dietary supplementation with Bacillus subtilis HGCC-1 significantly promoted growth performance (P

Abstract Neural networks are vulnerable to meticulously crafted adversarial examples, leading to high-confidence misclassifications in image classification tasks. Due to their consistency with regular input patterns and the absence of reliance on the target model and its output information, transferable adversarial attacks exhibit a notably high stealthiness and detection difficulty, making them a significant focus of defense. In this work, we propose a deep learning defense known as multi-source adversarial perturbations elimination (MAPE) to counter diverse transferable attacks. MAPE comprises the single-source adversarial perturbation elimination (SAPE) mechanism and the pre-trained models probabilistic scheduling algorithm (PPSA). SAPE utilizes a thoughtfully designed channel-attention U-Net as the defense model and employs adversarial examples generated by a pre-trained model (e.g., ResNet) for its training, thereby enabling the elimination of known adversarial perturbations. PPSA introduces model difference quantification and negative momentum to strategically schedule multiple pre-trained models, thereby maximizing the differences among adversarial examples during the defense model’s training and enhancing its robustness in eliminating adversarial perturbations. MAPE effectively eliminates adversarial perturbations in various adversarial examples, providing a robust defense against attacks from different substitute models. In a black-box attack scenario utilizing ResNet-34 as the target model, our approach achieves average defense rates of over 95.1% on CIFAR-10 and over 71.5% on Mini-ImageNet, demonstrating state-of-the-art performance.

In recent years, significant advances in unmanned aerial vehicle (UAV) technology and hyperspectral remote sensing have spurred rapid and innovative developments in UAV-based hyperspectral image (HSI) classification across a range of fields, including environmental monitoring, precision agriculture, forest health assessment, and disaster management. Compared to spaceborne platforms, the spectra of ground objects observed by UAV platforms exhibit notable variations, presenting more pronounced challenges for accurate classification. This article provides an in-depth and systematic review of UAV HSI classification techniques, systematically examining the evolution from traditional machine learning approaches, such as sparse coding, compressed sensing, and kernel methods, to cutting-edge deep learning frameworks, including convolutional neural networks, Transformer models, recurrent neural networks, graph convolutional networks, generative adversarial networks, and hybrid models. Although traditional methods demonstrate effectiveness in certain scenarios, their limitations become increasingly apparent when dealing with high-dimensional, nonlinear spectral data. In contrast, deep learning-based models excel at capturing intricate relationships between spectral and spatial features, significantly boosting classification accuracy and emerging as the dominant paradigm in the field. The WHU-Hi hyperspectral remote sensing dataset is utilized as a case study to elucidate the advantages and limitations of various deep learning methods through rigorous qualitative and quantitative comparisons. The potential of UAV hyperspectral image classification techniques in addressing high-dimensional data and complex scenarios is also thoroughly described. Furthermore, this article delves into cutting-edge research trends, such as lightweight model development, hyperspectral large models, multisource data fusion, and model interpretability, while also highlighting future trends for UAV hyperspectral remote sensing classification technology, particularly in real-time monitoring and intelligent applications.

Abstract Plant extracts, especially herbal extracts, are in line with the cosmetics development trend of natural and safe in today’s world. Dried ginger essential oil (DGEO) is a fragrant oily liquid extracted from the dried roots of Zingiber officinale Rosc. This research investigated DGEO could effectively inhibit Staphylococcus aureus and Propionibacterium acnes. And delay skin aging in mice by down-regulating the expression of TNF-α and the production of MMP-1. These indicates that DGEO has antibacterial and anti-aging effects, and has the potential in beauty and skin care. However, DGEO is easy to volatilize, so it is lack of stability, and the application of DGEO is greatly limited. Therefore, we aim to improve the stability of DGEO and expand its application in facial mask. To achieve this, DGEO was firstly complexed with the β-cyclodextrin (β-CD) to prepare DGEO-β-CD-IC. Then, electrospinning was used to make DGEO-βCD-IC into a nanofiber facial mask. In this process, we found that the thermal stability of DGEO-βCD-IC was significantly improved, and the degradation process was slower than that of physical mixture. During the preparation of the nanofiber mask, DGEO did not undergo a chemical reaction. And the fibers of facial mask were evenly distributed, with smooth surfaces and tight structures. Its diameter was between 90 and 110 nm. And the facial mask had good hydrophilic performance and moisturizing efficacy. It could increase the skin water content by 47.82% on average. What’s more, the safety tests showed that the facial mask was mild and safe. These results show that we improve the stability of DGEO and successfully develop a promising application prospects nanofiber mask. This work may enrich the use of herbal extracts in skincare products.

Abstract Chimeric antigen receptor (CAR) T cell therapy for solid tumors faces significant challenges, including inadequate infiltration, limited proliferation, diminished effector function of CAR T cells, and an immunosuppressive tumor microenvironment (TME). In this study, we utilized The Cancer Genome Atlas database to identify key chemokines (CCL4, CCL5, and CCR5) associated with T cell infiltration across various solid tumor types. The CCL4/CCL5-CCR5 axis emerged as significantly correlated with the presence of T cells within tumors, and enhancing the expression of CCR5 in CAR T cells bolstered their migratory capacity. Furthermore, single-cell immunoprofiling of tumor tissues revealed that macrophages within the TME primarily interact with CD8+ T cells, impeding their tumor response. However, CAR T cells engineered to secrete Interleukin (IL)-12 can counteract macrophage-mediated immunosuppression and augment T cell functionality. To address these obstacles, we employed esophageal carcinoma as a model to develop mesothelin-targeted CAR T cells co-expressing CCR5 and IL-12 (CARTmeso-5-12), subsequently assessing their antitumor capabilities in vitro and in vivo. The CARTmeso-5-12 cells demonstrated enhanced tumor infiltration due to overexpression of CCR5, and IL-12 secretion further amplified CAR T cell efficacy by attenuating the suppressive influence of tumor-infiltrating macrophages, thus improving tumor eradication.

Abstract Chronic neuroinflammation with sustained microglial activation occurs in Parkinson’s disease (PD), yet the mechanisms and exact contribution of these cells to the neurodegeneration remains poorly understood. In this study, we induced progressive dopaminergic neuron loss in mice via rAAV-hSYN injection to cause the neuronal expression of α-synuclein, which produced neuroinflammation and behavioral alterations. We administered PLX5622, a colony-stimulating factor 1 receptor inhibitor, for 3 weeks prior to rAAV-hSYN injection, maintaining it for 8 weeks to eliminate microglia. This chronic treatment paradigm prevented the development of motor deficits and concomitantly preserved dopaminergic neuron cell and weakened α-synuclein phosphorylation. Gene expression profiles related to extracellular matrix (ECM) remodeling were increased after microglia depletion in PD mice, which were further validated on protein level. We demonstrated that microglia exert adverse effects during α-synuclein-overexpression-induced neuronal lesion formation, and their depletion remodels ECM and aids recovery following insult.

Abstract Background Catecholaminergic polymorphic ventricular tachycardia (CPVT) is an inherited ion channelopathy characterized by a structurally normal heart sensitive to catecholamines. It primarily presents as Bidirectional ventricular tachycardia (BiVT) and is a significant cause of sudden cardiac death in children. Case presentation We report our experience with central Extracorporeal Membrane Oxygenation (ECMO) therapy in a 4-year-old boy with CPVT. Despite these measures, his CPVT was refractory to standard medical treatment and mechanical ventilatory support, with symptom progression. Consequently, ECMO support was initiated in addition to existing treatment. The patient was successfully weaned off ECMO on the 10th day of therapy and was discharged in a good condition. Follow-up after discharge showed favorable outcomes. Conclusions The successful outcome in this case was attributed to the application of ECMO, which helped maintain the patient’s circulatory status and address progressively worsening cardiogenic shock and uncontrolled ventricular arrhythmia. In such situations, the early use of ECMO can provide essential circulatory support and stability for patients, as demonstrated in this case.

In response to the registration error problem caused by different degrees of local distortion in different positions of drone orthophoto images during two periods, this article proposes a block-based registration strategy suitable for drone orthophoto images, which is first global and then local. This strategy first uses the Fourier Merlin transform to perform overall registration on the drone orthophoto image, then divides the overall registration result into blocks and uses the scale invariant feature transform (SIFT)-GMS algorithm for local registration. Finally, the Poisson fusion algorithm is used to concatenate the segmented images to obtain the final registration result. The experimental results show that the proposed strategy effectively reduces registration errors caused by local distortions, and is superior to polynomial registration methods and spline function registration methods in terms of registration accuracy and automation.

Abstract Background The ACEF score (age, creatinine, and left ventricular ejection fraction) and the triglyceride-glucose (TyG) index have been identified as robust risk prediction models for adverse outcomes post-percutaneous coronary intervention (PCI) in coronary atherosclerotic heart disease (CHD) patients. This study aimed to assess whether incorporating the TyG index enhances the predictive ability of the ACEF score and enhances risk stratification for CHD patients undergoing PCI. Methods This observational cohort study enrolled 1248 patients diagnosed with CHD who underwent PCI at the Third People’s Hospital of Chengdu, China, between May 2018 and December 2022. Receiver operating characteristic (ROC) curves were employed to establish the optimal cutoff values for the TyG index and ACEF score. The primary endpoint event was defined as major adverse cardiac and cerebrovascular events (MACCEs). Cumulative survival curves were plotted using the Kaplan–Meier method. Univariable and multivariable Cox regression analyses were conducted to identify predictors of MACCEs. The predictive ability of the ACEF score and the TyG index was assessed using the area under the ROC curve, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Results Over a median follow-up period of 30.60 months, 214 patients experienced MACCEs. Kaplan-Meier survival analysis demonstrated a significant association between elevated ACEF score (> 1.27) and TyG index levels (> 8.82) with a heightened incidence of MACCEs (HR = 2.018, 95%CI 1.593–2.789; HR = 2.057, 95%CI 1.572–2.691; Log-Rank test, both P

Abstract Background Rectal cancer patients are potential beneficiaries of adaptive radiotherapy (ART) which demands considerable resources. Currently, there is no definite guidance on what kind of patients and when will benefit from ART. This study aimed to develop and validate a methodology for estimating ART requirements in rectal cancer before treatment course. Methods and materials This study involved 66 rectal cancer patients from center 1 and 27 patients from center 2. The ART requirements were evaluated by comparing 8 dose volume histogram (DVH) metrics of targets and organs at risk (OARs) between planning and treatment fractions. Tolerance ranges of deviation of DVH metrics were derived from 10 patients and applied to assess fractional variability. Eighteen features, encompassing diagnostic, dosimetric, and time-related information, were utilized to formulate a stepwise logistic regression model for fraction-level ART requirement estimation. The super parameters were determined through 5-fold cross-validation with 250 training fractions and the methodology was validated with 109 internal testing fractions and 134 external testing fractions. Results The area under the curve (AUC) of training dataset was 0.74 (95% CI: 0.61 to 0.85), while in the internal and external testing, the AUC achieved 0.76 (95% CI: 0.60–0.90) and 0.68 (95% CI: 0.56–0.81). Using a best (or clinical applicable) cut-off value of 33.4% (11%), the predictive model achieved a sensitivity of 46.2% (69.2%) and specificity of 97.9% (68.7%). During the modeling, 5 features were retained: Homogeneity index (OR = 6.06, 95% CI: 2.93–14.8), planning target volume (OR = 1.77, 95% CI: 1.17–2.69), fraction dose (OR = 45.37, 95% CI: 5.74–469), accumulated dose (OR = 2.29, 95% CI: 1.35–4.14), and whether neoadjuvant chemoradiotherapy (OR > 1000). Conclusion ART requirements are associated with target volume, target dose homogeneity, fraction dose, dose accumulation and whether neoadjuvant radiotherapy. The predictive model exhibited the capability to predict fraction-level ART requirements.

Abstract Background Mississippi youth are demographically unique compared to that of the nation. The purpose of this study is to determine the prevalence and trend of suicide ideation, suicide plans, suicidal attempts, and suicidal injury among high school students in Mississippi vs. in the United States (U.S.). Method Summary statistics, prevalence ratio (PR), and trend analysis were generated and compared between Mississippi high school students and their U.S. counterparts. Results The 2021 prevalences for suicide plans, suicide attempts, and suicide injury are all significantly higher for Mississippi high school students compared to their national counterparts. From 2001 to 2021, on the national level, none of the four suicide behaviors showed significant change, whereas, in Mississippi, suicide plans, suicide attempts, and suicide injury all had an increasing trend. Conclusions Our study reveals alarming increasing trends and significantly greater severity of suicidal burdens among Mississippi high school students compared to the nation. Left unattended, these trends may continue quicker due to a clustering effect. There is an urgent need for Mississippi to implement more and better intervention and prevention measures to stop and reverse the increasing trend of suicidal behaviors among its 9–12 graders.

Abstract Background Head and neck squamous cell carcinoma (HNSCC) is a very aggressive disease characterized by a heterogeneous tumor immune microenvironment (TIME). Tumor-associated macrophages (TAMs) constitute the major innate immune population in the TIME where they facilitate crucial regulatory processes that participate in malignant tumor progression. SPP1 + macrophages (SPP1 + Macs) are found in many cancers, but their effects on HNSCC remain unknown. This study aimed to identify and validate the role and function of SPP1 + Macs in the malignant progression of HNSCC. Methods In this study, we applied single-cell RNA sequencing (scRNA-seq) analyses of paired tumor and normal tissues from 5 HNSCC patients to identify tumor-specific SPP1 + Macs. RT-qPCR and multiplex immunohistochemical and multiplex immunofluorescence staining were used to verify the presence of SPP1 + Macs in the clinical samples. Gene set variation analysis suggested that SPP1 + Macs were actively involved in cytokine production. Thus, we constructed SPP1-OE macrophages and SPP1-KD macrophages (both differentiated from THP-1 cells), performed a Luminex liquid suspension chip detection assay to detect differential cytokines, and further assessed their biological functions and mechanisms in several HNSCC cell lines and adjacent macrophages. An in vivo experiment was used to verify the function of SPP1 + Macs in HNSCC progression. Results The scRNA-seq results revealed that myeloid cells were heterogeneous and strongly correlated with tumor cells in the TIME in HNSCC and identified tumor-specific SPP1 + Macs, which were positively correlated with poor prognosis of HNSCC patients. Gene set variation analysis (GSVA) suggested that SPP1 + Macs were actively involved in cytokine production. Luminex liquid suspension chip detection assay indicated that SPP1 + Mac-derived TNF-α and IL-1β played important roles. Both in vitro and in vivo experiments and the use of VGX-1027, an inhibitor of macrophage-derived TNF-α and IL-1β, confirmed that SPP1 + Mac-derived TNF-α and IL-1β promoted HNSCC progression by supporting tumor cell proliferation and migration. Mechanistically, we found that TNF-α and IL-1β were upregulated due to NF-kappa B signaling pathway activation in SPP1 + Macs. Moreover, SPP1 + Mac-derived TNF-α and IL-1β promoted the expression of OPN in both tumor cells and other adjacent macrophages through different signaling pathways. Conclusions SPP1 + Macs increase the secretion of TNF-α and IL-1β via the NF-kappa B pathway to promote HNSCC cell proliferation, and TNF-α and IL-1β in turn upregulate the expression of OPN in tumor cells and macrophages; thus, SPP1 + Macs may be a candidate target through which antitumor efficacy can be enhanced.

Abstract Background Research has consistently highlighted the key role of hepatocyte nuclear factor 1β (HNF1B) in organ development and cancer, including its involvement in colon cancer via shifted-code mutations. However, the specific effects of HNF1B on cancer immunotherapy and the immune microenvironment are not fully understood. This study investigated the impact of HNF1B on colon cancer immunotherapy in depth. Methods We analyzed 1,374 colon adenocarcinoma samples from the TCGA and GEO datasets. Our approach involved bioinformatics to uncover how HNF1B influences immunotherapy and the immune microenvironment, with corroboration from external databases and experimental validation. Results HNF1B was expressed at low levels in colon adenocarcinoma and was linked to patient prognosis. CIBERSORT, TIME, and GSVA analyses revealed that HNF1B was associated with macrophage infiltration, immune checkpoints, and signaling pathways. Drug prediction suggested a negative relationship between HNF1B and EGFR-targeted therapies, implying potential resistance. Validation with external cohorts confirmed that patients with low HNF1B expression experienced less benefit from immunotherapy. Conclusion This study clarifies the role of HNF1B in the treatment of colon adenocarcinoma. This study provides a foundation for further in-depth mechanistic studies and proposes new directions for optimizing immunotherapy strategies for colon adenocarcinoma.

Abstract Record breaking atmospheric methane growth rates were observed in 2020 and 2021 (15.2±0.5 and 17.8±0.5 parts per billion per year), the highest since the early 1980s. Here we use an ensemble of atmospheric inversions informed by surface or satellite methane observations to infer emission changes during these two years relative to 2019. Results show global methane emissions increased by 20.3±9.9 and 24.8±3.1 teragrams per year in 2020 and 2021, dominated by heightened emissions from tropical and boreal inundated areas, aligning with rising groundwater storage and regional warming. Current process-based wetland models fail to capture the tropical emission surges revealed by atmospheric inversions, likely due to inaccurate representation of wetland extents and associated methane emissions. Our findings underscore the critical role of tropical inundated areas in the recent methane emission surges and highlight the need to integrate multiple data streams and modeling tools for better constraining tropical wetland emissions.

Abstract Somatic cells can be reprogrammed into pluripotent stem cells (iPSCs) by overexpressing defined transcription factors. Specifically, overexpression of OCT4 alone has been demonstrated to reprogram mouse fibroblasts into iPSCs. However, it remains unclear whether any other single factor can induce iPSCs formation. Here, we report that SALL4 alone, under an optimized reprogramming medium iCD4, is capable of reprogramming mouse fibroblasts into iPSCs. Mechanistically, SALL4 facilitates reprogramming by inhibiting somatic genes and activating pluripotent genes, such as Esrrb and Tfap2c. Furthermore, we demonstrate that co-overexpressing SALL4 and OCT4 synergistically enhances reprogramming efficiency. Specifically, the activation of Rsk1/Esrrb/Tfap2c by SALL4, alongside OCT4’s activation of Sox2 and the suppression of Mndal by SALL4 and Sbsn by OCT4, cooperate to facilitate SALL4+OCT4-mediated reprogramming. Overall, our study not only establishes an efficient method for iPSCs induction using the SALL4 single factor but also provides insights into the synergistic effects of SALL4 and OCT4 in reprogramming.

Abstract Unsupervised clustering method has shown strong capabilities in automatically categorizing the ARPES (ARPES: angle-resolved photoemission spectroscopy) spatial mapping dataset. However, there is still room for improvement in distinguishing subtle differences caused by different layers and substrates. Here, we propose a method called Multi-Stage Clustering Algorithm (MSCA). Using the K-means clustering results/metrics for real space in different energy-momentum windows as the input of the second round K-means clustering for momentum space, the energy-momentum windows that exhibit subtle inhomogeneity in real space will be highlighted. It recognizes different types of electronic structures both in real space and momentum space in spatially resolved ARPES dataset. This method can be used to capture the areas of interest, and is especially suitable for samples with complex band dispersions, and can be a practical tool to any high dimensional scientific data analysis.

Abstract We investigated changes in physiology and mechanical properties of diatoms exposed to chemical cues released by copepods Pseudodiaptomus annandalei. Our results showed that the diatoms Phaeodactylum tricornutum, Cylindrotheca closterium, Thalassiosira weissflogii, and Amphora coffeaeformis exhibited elevated growth rates and a substantial 2‐ to 50‐fold increase in biogenic silica (BSi) content increase when exposed to the chemical cues except for Cyclotella sp. Atomic force microscopy and X‐ray photoelectron spectroscopy analyses revealed that diatom frustules exhibited a remarkable 3‐ to 10‐fold increase in modulus and a substantial 2‐ to 5‐fold increase in hardness when they received grazing signals. The increase in the proportion of condensed silicon in the frustules could be the major reason for the more mechanically robust cells. Our results indicate that diatoms simultaneously increase their growth rate and robustness when exposed to copepod chemical cues. This study at the nanoscale enhanced our understanding of how diatoms respond to zooplankton predation in marine ecosystems.

By integrating an established rock damage model into the LS-DYNA computer code and using a widely used method for equivalently simulating multiple blastholes detonation, the damage processes of surrounding rock with different properties under the bench blasting of a large cross-section tunnel are comparatively studied. The damage distribution across the excavation cross-section is characterized by greater damage at the upper and lower ends, with lesser damage in the middle (junction between adjacent benches). For grade III surrounding rock excavated with two-bench blasting, the maximum damage depth of 3.6 m occurs in the middle floor. For grades IV and V surrounding rock excavated with three-bench blasting, the maximum damage depths both occur at the vault, with 3.6 m and 2.5 m, respectively. In bench blasting, the blasting of breaking holes closest to the excavation boundary significantly impacts surrounding rock, whereas the damage caused by smooth holes blasting is minor. The surrounding rock with poorer mechanical properties tends to exhibit greater damage under the same blasting operations. According to the proposed method, the critical Peak Particle Velocity (PPV) for cumulative damage in grades III, IV, and V surrounding rock of the Longnan tunnel is 16.8 cm/s, 13.7 cm/s, and 11.5 cm/s, respectively.

The global COVID-19 pandemic has severely impacted human health and socioeconomic development, posing an enormous public health challenge. Extensive research has been conducted into the relationship between environmental factors and the transmission of COVID-19. However, numerous factors influence the development of pandemic outbreaks, and the presence of confounding effects on the mechanism of action complicates the assessment of the role of environmental factors in the spread of COVID-19. Direct estimation of the role of environmental factors without removing the confounding effects will be biased. To overcome this critical problem, we developed a Double Machine Learning (DML) causal model to estimate the debiased causal effects of the influencing factors in the COVID-19 outbreaks in Chinese cities. Comparative experiments revealed that the traditional multiple linear regression model overestimated the impact of environmental factors. Environmental factors are not the dominant cause of widespread outbreaks in China in 2022. In addition, by further analyzing the causal effects of environmental factors, it was verified that there is significant heterogeneity in the role of environmental factors. The causal effect of environmental factors on COVID-19 changes with the regional environment. It is therefore recommended that when exploring the mechanisms by which environmental factors influence the spread of epidemics, confounding factors must be handled carefully in order to obtain clean quantitative results. This study offers a more precise representation of the impact of environmental factors on the spread of the COVID-19 pandemic, as well as a framework for more accurately quantifying the factors influencing the outbreak.

Thrombosis and infection are pivotal clinical complications associated with interventional blood-contacting devices, leading to significant morbidity and mortality. To address these issues, we present a stepwise metal-catechol-(amine) (MCA) surface engineering strategy that efficiently integrates therapeutic nitric oxide (NO) gas and antibacterial peptide (ABP) onto catheters, ensuring balanced anti-thrombotic and anti-infective properties. First, copper ions were controllably incorporated with norepinephrine and hexanediamine through a one-step molecular/ion co-assembly process, creating a NO-generating and amine-rich MCA surface coating. Subsequently, azide-polyethylene glycol 4-N-hydroxysuccinimidyl and dibenzylcyclooctyne modified ABP were sequentially immobilized on the surface via amide coupling and bioorthogonal click chemistry, ensuring the dense grafting of ABP while maintaining the catalytic efficacy for NO. This efficient integration of ABP and NO-generating ability on the catheter surface provides potent antibacterial properties and ability to resist adhesion and activation of platelets, thus synergistically preventing infection and thrombosis. We anticipate that this synergistic modification strategy will offer an effective solution for advancing surface engineering and enhancing the clinical performance of biomedical devices.

Mesenchymal stem cells (MSCs) have demonstrated significant therapeutic potential in heart failure (HF) treatment. However, their clinical application is impeded by low retention rate and low cellular activity of MSCs caused by high inflammatory and reactive oxygen species (ROS) microenvironment. In this study, monascus pigment (MP) nanoparticle (PPM) was proposed for improving adverse microenvironment and assisting in transplantation of bone marrow-derived MSCs (BMSCs). Meanwhile, in order to load PPM and reduce the mechanical damage of BMSCs, injectable hydrogels based on Schiff base cross-linking were prepared. The PPM displays ROS-scavenging and macrophage phenotype-regulating capabilities, significantly enhancing BMSCs survival and activity in HF microenvironment. This hydrogel demonstrates superior biocompatibility, injectability, and tissue adhesion. With the synergistic effects of injectable, adhesive hydrogel and the microenvironment-modulating properties of MP, cardiac function was effectively improved in the pericardial sac of rats. Our results offer insights into advancing BMSCs-based HF therapies and their clinical applications.

Abstract Background With the extensive utilization of immune checkpoint inhibitors (ICIs) across various cancers, ICIs-related thyroid dysfunction (ICI-TD) has become a growing concern in clinical practice. This study aimed to devise an individualized management strategy for ICI-TD to enhance the early identification and proactive management in cancer patients. Methods We designed and conducted a three-phase study. Initially, we analyzed the influencing factors through a systematic review and meta-analysis, which adhered to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. Moreover, the study protocol was registered with PROSPERO (CRD42019131133). Subsequently, prediction models for ICI-TD were developed utilizing 11 algorithms based on the real-world cohort data from July 20, 2018 (the approval date of the first ICIs, Pembrolizumab in China), to October 31, 2022. Considering discrimination, calibration, and clinical utility, we selected the model with the best performance for web calculator development. Finally, individualized management strategies for ICI-TD were proposed by combining evidence-based analysis with practical considerations. Results The systematic review encompassed 21 observational studies involving 4,145 patients, revealing associations between ICI-TD and factors such as female gender, age, receipt of Pembrolizumab (versus other ICIs), and baseline levels of thyroid-stimulating hormone, free thyroxine, and antithyroid antibodies. In the prediction model development phase, 621 participants were enrolled, with 36 patients developing ICI-TD. The model based on the LightGBM algorithm demonstrated superior performance, leading to the development of a web calculator. Based on these findings and existing guidelines, individualized monitoring and treatment pathways for pharmacists were devised. Conclusion This study offers comprehensive insights into managing ICI-TD, potentially enhancing tailored cancer immunotherapy management.

Citrus yield estimation using deep learning and unmanned aerial vehicles (UAVs) is an effective method that can potentially achieve high accuracy and labor savings. However, many citrus varieties with different fruit shapes and colors require varietal-specific fruit detection models, making it challenging to acquire a substantial number of images for each variety. Understanding the performance of models on constrained or biased image datasets is crucial for determining methods for improving model performance. In this study, we evaluated the accuracy of the You Only Look Once (YOLO) v8m, YOLOv9c, and YOLOv5mu models using constrained or biased image datasets to obtain fundamental knowledge for estimating the yield from UAV images of yellow maturing citrus (Citrus junos) trees. Our results demonstrate that the YOLOv5mu model performed better than the others based on the constrained 25-image datasets, achieving a higher average precision at an intersection over union of 0.50 (AP@50) (85.1%) than the YOLOv8m (80.3%) and YOLOv9c (81.6%) models in the training dataset. On the other hand, it was revealed that the performance improvement due to data augmentation was high for the YOLOv8m and YOLOv9c models. Moreover, the impact of the bias in the training dataset, such as the light condition and the coloring of the fruit, on the performance of the fruit detection model is demonstrated. These findings provide critical insights for selecting models based on the quantity and quality of the image data collected under actual field conditions.

Abstract Background Pathological scars (PS) are one of the most common complications in patients with trauma and burns, leading to functional impairments and aesthetic concerns. Mechanical tension at injury sites is a crucial factor in PS formation. However, the precise mechanisms remain unclear due to the lack of reliable animal models. Results We developed a novel mouse model, the Retroflex Scar Model (RSM), which induces PS by applying controlled tension to wounds in vivo. RNA sequencing identified significant transcriptome changes in RSM-induced scars. Elevated expression of E-Selectin (Sele) was observed in endothelial cells from both the RSM model and human PS (Keloid) samples. In vitro studies demonstrated that cyclic mechanical stretching (CMS) increased Sele expression, promoting monocyte adhesion and the release of pro-inflammatory factors. Single-cell sequencing analysis from the GEO database, complemented by Western blotting, immunofluorescence, and co-immunoprecipitation, confirmed the role of Sele-mediated monocyte adhesion in PS formation. Additionally, we developed Sele-targeted siRNA liposome nanoparticles (LNPs) to inhibit monocyte adhesion. Intradermal administration of these LNPs effectively reduced PS formation in both in vivo and in vitro studies. Conclusions This study successfully established a reliable mouse model for PS, highlighting the significant roles of mechanical tension and chronic inflammation in PS formation. We identified Sele as a key therapeutic target and developed Sele-targeted siRNA LNPs, which demonstrated potential as a preventive strategy for PS. These findings provide valuable insights into PS pathogenesis and open new avenues for developing effective treatments for pathological scars. Graphical Abstract

Magnesium and its alloys show strong mechanical anisotropy due to their hexagonal close-packed structure. This paper processed ambient extrusion and subsequent annealing on AZ31 magnesium alloy bars to investigate the effect of working hardening and texture weakening on yield anisotropy of magnesium alloy. After ambient extrusion, yield strength on different loading direction are improved due to working hardening. ED-yield strength has the highest increment because work hardening has a higher effect on prismatic slip. Then, yield anisotropy becomes stronger with the increase of extrusion train. During annealing, static recrystallization occurs firstly in {101‾1} twinning zones and producing recrystallized grains with random orientation. With the growth of recrystallized grains, basal fiber texture is weakened gradually. Such weak basal texture can promote the activation of basal slip when loading along ED, so ED-yield strength shows a high decrement. On this way, the yield anisotropy in AZ31 magnesium alloy bars is weakened through ambient extrusion and subsequent annealing.

Abstract Deep brain stimulation (DBS) can ameliorate motor symptoms in Parkinson’s disease (PD), but its mechanism remains unclear. This work constructs a multi-scale brain model using the fMRI data from 27 PD patients with subthalamic DBS and 30 healthy controls. The model fits microscopic coupling parameters in the cortico-basal ganglia-thalamic neural loop to match individual connectivity, finding the “push-pull” effect of basal ganglia network. Specifically, increased GABAergic projection into the thalamus from basal ganglia worsens rigidity, while reduced GABAergic projection within the cortex exacerbates bradykinesia, suggesting that the dopamine deficiency induces the chain coupling variations to “push” the network to an abnormal state. Conversely, DBS can alleviate rigidity by enhancing GABAergic projections within the basal ganglia, and improve bradykinesia by reducing cortical projections to basal ganglia, exhibiting that DBS “pulls” the network to a healthy state. This work combines the microscopic and macroscopic neural information for understanding PD and its treatment.

Abstract This study presents an innovative scraper pump design. The design utilizes the synchronized movement of the upper and lower scrapers of the rotor to adjust the cavity volumes on either side, facilitating efficient fluid transfer. Unlike previous studies, scraper pumps face the challenge of dynamic contact between the scraper and the rotor due to their unique structure. A viscous wall strategy was employed to address hydrodynamic challenges at the point of contact, significantly improving performance prediction accuracy. The experimental data verified the accuracy of the simulation model, and the mass flow rate deviation between the simulation results and the experimental results was maintained within 10% when the viscosity at the contact point was set to 40 times the original medium viscosity. In addition, the study examined the effect of different operating speeds and load pressures on the pump performance. The results indicated that the outlet flow rate decreased by 22% when the pressure was increased from 2 MPa to 10 MPa and increased by 88.24% when the speed was increased from 900 r/min to 2200 r/min. These quantitative analyses provided valuable insights into optimizing scraper pump design and offered clear guidance for improving hydraulic performance and operational efficiency.

Abstract Background Evidence has accumulated to demonstrate that intestinal microbiome can inhibit viral infection. However, our knowledge of the signaling pathways and identity of specific commensal microbes that mediate the antiviral response is limited. Zebrafish have emerged as a powerful animal model for study of vertebrate-microbiota interactions. Here, a rhabdoviral infection model in zebrafish allows us to investigate the modes of action of microbiome-mediated antiviral effect. Results We observed that oral antibiotics-treated and germ-free zebrafish exhibited greater spring viremia of carp virus (SVCV) infection. Mechanistically, depletion of the intestinal microbiome alters TLR2-Myd88 signaling and blunts neutrophil response and type I interferon (IFN) antiviral innate immunity. Through 16S rRNA sequencing of the intestinal contents from control and antibiotic(s)-treated fish, we identified a single commensal bacterial species, Cetobacterium somerae, that can restore the TLR2- and neutrophil-dependent type I IFN response to restrict SVCV infection in gnotobiotic zebrafish. Furthermore, we found that C. somerae exopolysaccharides (CsEPS) was the effector molecule that engaged TLR2 to mediate the type I IFN-dependent antiviral function. Conclusions Together, our results suggest a conserved role of intestinal microbiome in regulating type I IFN antiviral response among vertebrates and reveal that the intestinal microbiome inhibits viral infection through a CsEPS-TLR2-type I IFN signaling axis in zebrafish. Video Abstract

Highlights Wafer-scale integration of Ag2S-based memristive crossbar arrays was demonstrated using complementary metal–oxide–semiconductor (CMOS) compatible processes below 160 °C. A record-low threshold voltage for filament formation and an ultra-low switching-energy reaching that of biological synapses in wafer-scale CMOS-compatible memristive units were achieved. The energy-efficient resistance switching was enabled by self-supply of mobile Ag+ ions in Ag2S electrolytes and low silver-nucleation barrier at Ag/Ag2S interface.

Abstract Streptococcus suis infection represents a major challenge in pig farming and public health due to its zoonotic potential and diverse serotypes, while existing vaccines lack effective cross-protection. This study employed reverse vaccinology and immunoinformatics to identify 8 conserved proteins across 11 prevalent serotypes of S. suis. 16 candidate epitopes were selected to design three multi-epitope antigens against S. suis (designated as MEASs), which fused with a dendritic cell-targeting peptide to improve antigen presentation in host. Purified MEASs displayed favorable cross-reactogenicity against 29 serotype-specific antiserums. Robust humoral and cellular immune responses can be induced by MEAS 1 and MEAS 3 in a mouse model, which provided substantial protection against virulent strains from two different serotypes. In particular, their immune serums exhibited positive opsonization effects within bloodstream and macrophage phagocytosis. Taken together, we identified two promising MEASs with excellent cross-protection, offering potential in preventing S. suis infections in a mouse model.

Abstract Bioinformatics software tools are essential to identify informative molecular features that define different phenotypic sample groups. Among the most fundamental and interrelated tasks are missing value imputation, signature gene detection, and differential pattern visualization. However, many commonly used analytics tools can be problematic when handling biologically diverse samples if either informative missingness possess high missing rates with mixed missing mechanisms, or multiple sample groups are compared and visualized in parallel. We developed the ABDS tool suite specifically for analyzing biologically diverse samples. Collectively, a mechanism-integrated group-wise pre-imputation scheme is proposed to retain informative missingness associated with signature genes, a cosine-based one-sample test is extended to detect group-silenced signature genes, and a unified heatmap is designed to display multiple sample groups. We describe the methodological principles and demonstrate the effectiveness of three analytics tools under targeted scenarios, supported by comparative evaluations and biomedical showcases. As an open-source R package, ABDS tool suite complements rather than replaces existing tools and will allow biologists to more accurately detect interpretable molecular signals among phenotypically diverse sample groups.

Abstract As a critical technology, anomaly detection ensures the smooth operation of cloud systems while maintaining the market competitiveness of cloud service providers. However, the resource data in real-world cloud systems is predominantly unannotated, leading to insufficient supervised signals for anomaly detection. Moreover, complicated topological associations existed between cloud servers (e.g., computation, storage, and communication). While acquiring resource information, correlating the system topology is challenging. To this end, we propose the GCAD for cloud system anomaly detection, which integrates data augmentation, GraphGRU, contrastive learning, and reconstruction. First, GCAD constructs positive and negative sample pairs through the masking and Gaussian noise data augmentation. Then, the GraphGRU processes extended temporal graph data, extracting and fusing spatiotemporal features from resource status and system topology. In addition, GCAD introduces linear attention for encoding spatiotemporal representations to capture their global correlation information. The weight parameters of the encoder are optimized using a contrastive learning mechanism. Finally, GCAD utilizes a reconstruction technique to calculate anomaly scores, facilitating the evaluation of the state of the cloud system at each time point. Experimental results indicate that GCAD outperforms state-of-the-art compared methods on two real-world datasets that contain topology information.

The accurate description of anisotropic plastic deformation is key to accurately predicting the stamping forming of metal sheets. The anisotropic yield criterion, when based on the assumption of isotropic hardening, often leads to significant inaccuracies. To address this issue, this paper observes the anisotropic hardening phenomenon through non-associated flow rules and evaluates the anisotropy of 7075-O aluminum alloy. Through a series of tensile tests, we determined the mechanical properties of 7075-O aluminum alloy in three distinct orientations. To describe the metal hardening behavior, we employed the Swift-Voce hardening criterion. From the hardening curves in three different directions, it was found that AA7075-O exhibits plastic anisotropy. Based on the VUMAT subroutine, finite element simulation of AA7075-O tensile tests was conducted through Abaqus. Compared with the Hill48 model, it was found that the simulated values of the S–Y2009 anisotropic hardening model have a higher degree of agreement with the experimental curves. The S–Y2009 anisotropic hardening model was adopted to predict the earing behavior of AA7075-O during circular cup deep drawing. The root mean square error between the predicted values of the S–Y2009 model and the experimental values was only 0.1795, which is far smaller than that of the Hill48 yield model. Therefore, the SY2009 model has important guiding significance for the stamping forming of metal sheets.

In this study, we investigated the evolution of grain structures and second phases of a Mg-9.5Gd-4Y–2Zn-0.3Zr alloy during two-stage deformation that took place in the metal during hot extrusion, as well as their effects on its mechanical properties. We found that the alloy exhibited a bimodal grain structure consisting of equiaxed dynamic recrystallized (DRXed) grains and elongated unDRXed grains. As the extrusion process progressed, DRX occurred on a large scale, resulting in an increase in the proportion of DRXed grains from 17.8% to 93.2%, and a reduction in average grain size from 80.3 μm to 9.41 μm. The grain orientation also underwent a transition from a single orientation of an extrusion direction (ED) parallel to (i.e. ED//) to mixed orientations of ED// and ED//. The primary mechanism of dynamic recrystallization (DRX) during extrusion involved particle-stimulated nucleation (PSN) accompanied by both continuous and discontinuous DRX. The Mg-9.5Gd-4Y–2Zn-0.3Zr alloy mainly contained intergranular 18R-long period stacking order (LPSO) phases and intragranular 14H-LPSO. As the extrusion process progressed, 18R-LPSO changed from blocky to lamellar to accommodate deformation, and β-Mg5(Gd,Y) phase particles dynamically precipitated along DRXed grain boundaries. The 14H-LPSO phase was found to be primarily distributed within coarse unDRXed grains. As deformation via extrusion progressed, the quantity of 14H-LPSO gradually decreased. Ultimately, with the gradual dissolution of Mg5(Gd,Y), 14H-LPSO reprecipitated within the recrystallized grain boundaries. As the extrusion process progressed, both the yield strength (YS) and elongation (EL) increased from 132.6 MPa to 287.6 MPa and from 10.8% to 15.5%, respectively. This was mainly attributed to the significant reduction in grain size and second phase size.

The sink strength of developing ovaries in wheat determines the grain weight potential. The period from booting to the grain setting stage is critical for ovary growth and development and potential sink capacity determination. However, the underlying regulatory mechanism during this period by which the wheat plant balances and coordinates the floret number and ovary/grain weight under water stress has not been clarified. Therefore, we designed two irrigation treatments of W0 (no seasonal irrigation) and W1 (additional 75 mm of irrigation at the jointing stage) and analyzed the responses of the ovary/grain weight to water stress at the phenotypic, metabolomic, and transcriptomic levels. The results showed that the W0 irrigation treatment reduced the soil water content, plant height, and green area of the flag leaf, thus reducing grain number, especially for the inferior grains. However, it improved the grain weight of the superior and inferior grains as well as average grain weight at maturity, while the average ovary/grain weight and volume during –3 to 10 days after anthesis (DAA) also increased. Transcriptomic analysis indicated that the genes involved in both sucrose metabolism and phytohormone signal transduction were prominently accelerated by the W0 treatment, accompanied by greater enzymatic activities of soluble acid invertase (SAI) and sucrose synthase (Sus) and elevated abscisic acid (ABA) and indole-3-acetic acid (IAA) levels. Thus, the sucrose content decreased, while the glucose and fructose contents increased. In addition, several TaTPP genes (especially TaTPP-6) were down-regulated and the IAA biosynthesis genes TaTAR1 and TaTAR2 were up-regulated under the W0 treatment before anthesis, which further increased the IAA level. Collectively, water stress reduced the growth of vegetative organs and eliminated most of the inferior grains, but increased the ABA and IAA levels of the surviving ovaries/grains, promoting the enzymatic activity of Sus and degrading sucrose into glucose and fructose. As a result, the strong sucrose utilization ability, the enhanced enzymatic activity of SAI and the ABA- and IAA-mediated signaling jointly increased the weight and volume of the surviving ovaries/grains, and ultimately achieved the trade-off between ovary/grain weight and number in wheat under water stress.

Abstract Background In May 2024, a chickenpox outbreak was reported at Xiasha Primary School located in Nanshan District, Shenzhen City, China, with a total of 12 cases identified. Despite thorough on-site investigations, the source of infection remained undetected. The purpose of our study was to infer the timing and duration of the infectious period of the initial case using modeling techniques, thereby deducing the identity of the source. Methods We conducted an individual contact survey within the class affected by the epidemic and utilized an agent-based model (ABM) to estimate the key parameters related to the timing of the infectious source’s emergence and the duration of its infectiousness. The point estimates derived from the ABM served as prior information for a subsequent Bayesian analysis, which in turn provided the posterior distribution for these parameters. Results Our models suggested the infection source entered the classroom around April 24th (95% credible interval: April 22nd to April 26th), with an infectious period of approximately two days. Based on these findings, we should aim to detect students who may have been absent due to atypical chickenpox symptoms during this period and closely examine teachers who were present for two consecutive days for any indication of potential infection. Conclusion This study demonstrates the efficacy of combining contact surveys with mathematical modeling for outbreak source tracing, offering a novel approach to supplement field epidemiological surveys. Clinical trial number Not applicable.

Abstract In the financial field, constructing efficient investment portfolios is a focal point of research, encompassing asset selection and optimization of asset allocation. With the advancements in Large Language Models (LLMs), generative Artificial Intelligence (AI) tools have showcased capabilities never seen before. However, the black-box nature of these tools renders their outputs difficult to interpret directly, often necessitating iterative fine-tuning to align with users’ expected outcomes. This study presents a structured prompt framework specifically designed for stock selection, aiming to provide direct and interpretable stock-selecting tools for investors of various levels. By creating representative scenarios and combining them into different cases for experimentation, we can explore how the construction of prompts influences the responses generated by generative AI tools. Additionally, this paper proposes a novel algorithm that combines the Nonlinear-Activated Beetle Antennae Search strategy with the Egret Swarm Optimization Algorithm (NBESOA) to address the Mean-Variance Portfolio Selection problem with Transaction Costs and Cardinality Constraints (MVPS-TCCC), utilizing real stock market data to construct portfolios based on generative AI tools recommendations. Simulation results indicate that, compared to other algorithms, NBESOA prefers optimizing portfolio configurations to achieve the highest Sharpe Ratio with the strictest constraints, bringing the outcomes closer to the portfolio’s efficient frontier.

Abstract Background and aims Diabetic peripheral neuropathy (DPN) and diabetic nephropathy (DN) both have microcirculation dysfunction. Urinary albumin-to-creatinine ratio (UACR) is a biomarker for DN. We aimed to explore the links between DPN and UACR in patients with type 2 diabetes mellitus (T2DM). Methods A total of 195 T2DM patients were defined as Control or DPN group. Clinical parameters were compared, and the association between HbA1c (or UACR) and DPN was analyzed. Risk factors for DPN were observed, and the diagnostic values of HbA1c and UACR were assessed. Results Compared with 104 participants without DPN, 91 individuals with DPN exhibited higher HbA1c and UACR levels. In all patients, increased HbA1c and UACR were identified as risk factors for DPN in individuals with T2DM. Moreover, increased HbA1c was a risk factor for DPN in volunteers without DN, whereas elevated UACR was determined as a risk factor for DPN in participants with DN. The cut-off point for HbA1c (7.65%) in patients without DN had a sensitivity of 86.0% and specificity of 44.6%, while the cut-off point for UACR (196.081 mg/g) in patients with DN had a sensitivity of 52.9% and specificity of 76.2%. Conclusion Elevated HbA1c and UACR levels are risk factors for DPN and may serve as potential biomarkers for DPN in T2DM patients.

Abstract High-grade serous ovarian carcinoma (HGSOC) is one of the most lethal gynecological cancer. Genetic studies have revealed gene copy number alterations (CNAs) frequently occurred in HGSOC pathogenesis, however the function and mechanism of CNAs for microRNAs are still not fully understood. Here, we show the dependence on gene copy number amplification of MIR937 that enhances cell autophagy and dictates HGSOC proliferative activity. Data mining of TCGA database revealed MIR937 amplification is correlated with increased MIR937 expression and cell proliferation of HGSOC. Deletion of MIR937 in HGSOC cells led to impaired autophagy and retarded cell proliferation, and the extent for its inhibitory effects scaled with the degree of MIR937 copy loss. Rescue assay confirmed miR-937-5p, a mature product of MIR937, was sufficient to restore its oncogenic function. Mechanistically, MIR937 amplification raised the expression of miR-937-5p, enhanced its binding to 3′ UTR of FBXO16 transcript, and thereby restricting FBXO16 degradative effects on ULK1. Our results demonstrate that MIR937 amplification augments cell autophagy and proliferation, and suggest an alternative strategy of MIR937/FBXO16/ULK1 targeting for HGSOC treatment.

Abstract Background Increased awareness of the factors contributing to the diagnostic disparities seen in bipolar disorder between individuals of different heritage is needed to achieve equity in diagnosis and treatment. One such inequity is the provision of earlier treatment. Earlier treatment of patients diagnosed with bipolar disorder may prolong time to recurrence of mood episodes and reduce functional impairment and other poor outcomes associated with disease progression. The aim of this post hoc analysis was to study the efficacy and safety of long-acting injectable aripiprazole once-monthly 400 mg (AOM 400) in patients with earlier-stage bipolar I disorder (BP-I). Data from a 52-week multicenter, double-blind, placebo-controlled, randomized withdrawal trial of AOM 400 versus placebo in patients with BP‑I (NCT01567527) were analyzed. Those patients in the lowest quartiles for age (18–≤32 years; n = 70) or disease duration (0.13–≤4.6 years; n = 67) at baseline were categorized with earlier-stage BP-I. The primary endpoint was time from randomization to recurrence of any mood episode. Other endpoints included proportion of patients with recurrence of any mood episode, and change from baseline in Young Mania Rating Scale (YMRS) and Montgomery–Åsberg Depression Rating Scale (MADRS) total scores. Results Maintenance treatment with AOM 400 significantly delayed time to recurrence of any mood episode versus placebo in patients aged 18–≤32 years (hazard ratio [HR]: 2.46 [95% confidence interval (CI) 1.09, 5.55]; p = 0.0251) or with disease duration 0.13–≤4.6 years (HR: 3.21 [95% CI 1.35, 7.65]; p = 0.005). This was largely driven by a lower proportion of patients in the AOM 400 group with YMRS total score ≥15 or clinical worsening. Changes from baseline in MADRS total score in both earlier-stage groups indicated AOM 400 did not worsen depression versus placebo. The safety profile of AOM 400 was consistent with the original study. Note that the original study included patients who had previously been stabilized on AOM 400 monotherapy, which may have enriched the population with patients who respond to and tolerate AOM 400. Conclusions In this post hoc analysis, AOM 400 prolonged time to recurrence of any mood episode versus placebo in earlier-stage BP-I. These findings support early initiation of maintenance treatment with AOM 400.

This is an article in the field of materials science. Magnetic LSX molecular sieves were prepared by colloidal directing agent and Fe3O4. After silver ion exchange and hydrazine hydrate reduction, magnetic LSX molecular sieves containing silver atoms were prepared, the surface morphology, magnetic properties, phase structure, elemental composition and specific surface area of the samples were characterized by scanning electron microscopy, vibrating sample magnetometer, X-ray diffraction analyzer, photoelectron spectroscopy and specific surface adsorption instrument. The results showed that magnetic LSX molecular sieve is the composite material of LSX molecular sieve and Fe3O4. The micropore specific surface area was 679.38 m2/g. The optimum dosage of colloidal guide agent was 0.5%. The magnetic properties increased with the increase of Fe3O4 content. The specific surface area of magnetic LSX molecular sieve reduced after silver exchange with hydrazine hydrate.