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B cells enhance IL-1 beta driven invasiveness in triple negative breast cancer

Finerenone in Heart Failure with Preserved Ejection Fraction

Comparison of management options for spontaneous bleeding into soft tissues in patients with COVID-19

Case 2-2025: A 21-Year-Old Man with Loss of Consciousness and a Fall

High-resolution X-ray phase-contrast tomography of human placenta with different wavefront markers

Abstract Phase-contrast micro-tomography ( $$\upmu$$ CT) with synchrotron radiation can aid in the differentiation of subtle density variations in weakly absorbing soft tissue specimens. Modulation-based imaging (MBI) extracts phase information from the distortion of reference patterns, generated by periodic or randomly structured wavefront markers (e.g., gratings or sandpaper). The two approaches have already found application for the virtual inspection of biological samples. Here, we perform high-resolution $$\upmu$$ CT scans of an unstained human placenta specimen, using MBI with both a 2D grating and sandpaper as modulators, as well as conventional propagation-based imaging (PBI). The 3D virtual representation of placenta offers a valuable tool for analysing its intricate branching villous network and vascular structure, providing new insights into its complex architecture. Within this study, we assess reconstruction quality achieved with all three evaluated phase-contrast methods. Both MBI datasets are processed with the Unified Modulated Pattern Analysis (UMPA) model, a pattern-matching algorithm. In order to evaluate the benefits and suitability of MBI for virtual histology, we discuss how the complexities of the technique influence image quality and correlate the obtained volumes to 2D techniques, such as conventional histology and X-ray fluorescence (XRF) elemental maps.

Centrophilic retrotransposon integration via CENH3 chromatin in Arabidopsis

Fracture Prevention with Infrequent Zoledronate in Women 50 to 60 Years of Age

A hybrid critical channels and optimal feature subset selection framework for EEG fatigue recognition

Publisher Correction: Preliminary investigation on the establishment of a new meibomian gland obstruction model and gene expression

Self-referential belief shares common neural correlates with general belief

Abstract Belief processing and self-referential processing have been consistently associated with cortical midline structures, and cortical regions such as the vmPFC have been implicated in general belief processing. The neural correlates of self-referential belief are yet to be investigated. In this fMRI study, we presented 120 statements with trait adjectives to N = 27 healthy participants, who subsequently judged whether they believed these trait adjectives applied to themselves, a close person, or a public person. Thereafter, participants rated their certainty in this judgment. Expectedly, self-referential processing evoked a large cluster in the vmPFC, ACC, and dmPFC. For belief, we found a cluster in the vmPFC, ACC, and amPFC during statement presentation, partially overlapping with that for self-referential processing. The cluster for self-belief vs. disbelief was similar in location and size to that for general belief processing. For uncertainty, we found dmPFC activation. We replicated vmPFC involvement in belief processing and found a common neural correlate for belief and self-belief in the vmPFC. Furthermore, we replicated the role of the dmPFC in uncertainty, supporting a dual neural process model of belief and certainty.

Multiview attention networks for fine-grained watershed categorization via knowledge distillation

With the rapid development of artificial intelligence technology, an increasing number of village-related modeling problems have been addressed. However, first, the exploration of village-related watershed fine-grained classification problems, particularly the multi-view watershed fine-grained classification problem, has been hindered by dataset collection limitations; Second, village-related modeling networks typically employ convolutional modules for attentional modeling to extract salient features, yet they lack global attentional feature modeling capabilities; Lastly, the extensive number of parameters and significant computational demands render village-related watershed fine-grained classification networks infeasible for end-device deployment. To tackle these challenges, we introduce a multi-view attention mechanism designed for precise watershed classification, leveraging knowledge distillation techniques, abbreviated as MANet-KD. Specifically, first, we have developed the inaugural multi-view watershed classification dataset, termed MVWD.Second, we introduce a cross-view attention module (CVAM), which models salient features from intersecting views with global attention, enhancing the accuracy and precision of watershed classification. This module enhances fine-grained classification accuracy. Based on the above proposed CVAM, we propose a heavyweight MANet-Teacher and a lightweight MANet-Student, and finally, we introduce an Attention Knowledge Distillation (AKD) strategy that effectively transfers critical feature knowledge from the teacher network to the student network, utilizing the AKD approach for enhanced learning outcomes. The experimental results show that the proposed MANet-Teacher achieves state-of-the-art performance with 78.51% accuracy, and the proposed MANet-Student achieves comparable performance to MANet-Teacher with 6.64M parameters and 1.68G computation. The proposed MANet-KD achieves a good balance of performance and efficiency in the multi-view fine-grained watershed classification task. To facilitate further research in multi-view fine-grained watershed classification, all datasets, codes, and benchmark outcomes will be made available to the public. https://github.com/Jack13026212687/MANet-KD.

Extraction of coronary thrombus-derived exosomes from patients with acute myocardial infarction and its effect on the function of adventitial cells

Background Type I acute myocardial infarction (T1MI) has a very high morbidity and mortality rate. The role of thrombus-derived exosomes (TEs) in T1MI is unclear. Methods The objective of this study was to identify the optimal thrombolytic drug and concentration for extracting TEs. To this end, a series of time and concentration combinations were tested. Subsequently, the effect of TEs on thrombus-adjacent cells was investigated. Finally, we conducted lncRNA microarray analysis on the extracted TEs (GSE213115). Results TEs has been demonstrated to promote necrosis, autophagy, and ferroptosis of human cardiomyocytes, while inhibiting the proliferation and migration of human umbilical vein endothelial cells (HUVECs). Furthermore, TEs can stimulate the proliferation and migration of smooth muscle cells, and induce a transformation from a contractile to a secretory phenotype. Bioinformatics analysis revealed that five lncRNAs, AC068418.2, AC010186.3, AL031430.1, AC121333.1, and AL136526.1, exhibited significant differential expression in TE and regulated cell autophagy and ferroptosis by directly binding to TP53, TP63, and RELA, respectively. Conclusions We demonstrate that TEs as a potential target and research direction for the treatment of heart failure after T1MI. TEs may regulate ferroptosis and autophagy in thrombus-adjacent cells through the enrichment of certain lncRNAs.

UAV target tracking method based on global feature interaction and anchor-frame-free perceptual feature modulation

Target tracking techniques in the UAV perspective utilize UAV cameras to capture video streams and identify and track specific targets in real-time. Deep learning UAV target tracking methods based on the Siamese family have achieved significant results but still face challenges regarding accuracy and speed compatibility. In this study, in order to refine the feature representation and reduce the computational effort to improve the efficiency of the tracker, we perform feature fusion in deep inter-correlation operations and introduce a global attention mechanism to enhance the model’s field of view range and feature refinement capability to improve the tracking performance for small targets. In addition, we design an anchor-free frame-aware feature modulation mechanism to reduce computation and generate high-quality anchors while optimizing the target frame refinement computation to improve the adaptability to target deformation motion. Comparison experiments with several popular algorithms on UAV tracking datasets, such as UAV123@10fps, UAV20L, and DTB70, show that the algorithm balances speed and accuracy. In order to verify the reliability of the algorithm, we built a physical experimental environment on the Jetson Orin Nano platform. We realized a real-time processing speed of 30 frames per second.

Metastatic melanoma: An integrated analysis to identify critical regulators associated with prognosis, pathogenesis and targeted therapies

Metastatic melanoma causes a high rate of mortality. We conducted an integrated analysis to identify critical regulators associated with the prognosis, pathogenesis, and targeted therapies of metastatic-melanoma. A microarray dataset, GSE15605, including 12 metastatic-melanoma and sixteen normal skin (NS) samples, were obtained from the GEO database. After exploration of DEGs of NS and metastatic-melanoma, identification of relevant transcription factors (TFs) and kinases, the Gene Ontology (GO), and pathways analyses of DEGs were performed. Protein-protein interaction (PPI) networks were evaluated by the STRING and Cytoscape. Subsequently, the hub genes were selected using GEPIA. Survival analysis was performed using the TCGA. To identify microRNA and lncRNA DEGs of the melanoma-associated genes miRwalk and FANTOM6 were employed. In metastatic-melanoma samples 285 and 1173 genes were up and down-regulated, respectively. The upregulated genes were mostly involved in granulocyte chemotaxis, positive regulation of calcium ion transmembrane transport, and melanin biosynthetic process. Five hub genes including CXCL11, ICAM1, LEF1, MITF, and STAT1 were identified, SUZ12, SOX2, TCF3, NANOG, and SMAD4 were determined as the most significant TFs in metastatic-melanoma. Furthermore, CDK2, GSK3B, CSNK2A1, and CDK1 target the highest amounts of genes associated with disease. The DGIdb analysis results show the match drugs for five hub genes. MiRNAs analysis revealed hsa-miR-181c-5p, hsa-miR-30b-3p, hsa-miR-3680-3P, hsa-miR-4659a-3p, hsa-miR-4687-3P, and hsa-miR-6808-3P could regulate the hub genes, whereas RP11-553K8.5 and SRP14-AS1 were identified as the top significant lncRNA. The items recognized in the current study can be used as potential biomarkers for diagnostic, predictive, and might helpful to develop targeted combined therapies.

Achieving universal sanitation in Ghana: An analysis of key drivers of toilet ownership among property owners in Urban areas

Access to safe sanitation facilities remains a critical public health concern, especially in rapidly urbanizing countries like Ghana. This study investigates the determinants of household toilet ownership among property owners in three urban districts in Ghana. Using a cross-sectional survey design, data were collected from 1,256 property owners selected through a multi-stage stratified sampling procedure. Logistic regression analysis revealed that toilet ownership is significantly associated with the age and education level of property owners, community classification, building characteristics, and household income. Older property owners were more likely to own toilets (OR = 1.014 per year increase), as were those with higher education levels (OR = 1.752 for secondary, OR = 4.489 for tertiary education). Medium-class communities (OR = 2.013) completed buildings (OR = 2.625), and those constructed with sandcrete (OR = 12.755) were more likely to have toilets. Higher household income (OR = 1.00) correlated positively with toilet ownership. We conclude that enforcing building regulations requiring toilet facilities in all properties is crucial for improving sanitation in urban Ghana. Additionally, innovative sanitation financing interventions that subsidize the costs of sanitation facilities can be effective in addressing financial barriers and increasing household toilet ownership.

Development of a broad-spectrum epitope-based vaccine against Streptococcus pneumoniae

Streptococcus pneumoniae (SPN) is a significant pathogen causing pneumonia and meningitis, particularly in vulnerable populations like children and the elderly. Available pneumonia vaccines have limitations since they only cover particular serotypes and have high production costs. The emergence of antibiotic-resistant SPN strains further underscores the need for a new, cost-effective, broad-spectrum vaccine. Two potential vaccine candidates, CbpA and PspA, were identified, and their B-cell, CTL, and HTL epitopes were predicted and connected with suitable linkers, adjivant and PADRE sequence. The vaccine construct was found to be antigenic, non-toxic, non-allergenic, and soluble. The three-dimensional structure of the vaccine candidate was built and validated. Docking analysis of the vaccine candidate by ClusPro demonstrated robust and stable binding interactions between the MEV and toll-like receptor 4 in both humans and animals. The iMOD server and Amber v.22 tool has verified the stability of the docking complexes. GenScript server confirmed the high efficiency of cloning for the construct and in-silico cloning into the pET28a (+) vector using SnapGene, demonstrating successful translation of the epitope region. Immunological responses were shown to be enhanced by the C-IMMSIM server. This study introduced a strong peptide vaccine candidate that has the potential to contribute to the development of a rapid and cost-effective solution for combating SPN. However, experimental verification is necessary to evaluate the vaccine’s effectiveness.

Predicting marine habitat for marbled murrelets during breeding and nonbreeding seasons in the Salish Sea, British Columbia, Canada

The marbled murrelet (Brachyramphus marmoratus) is a small seabird inhabiting coastal regions along the Pacific coast of North America, and nests in old-growth forests usually within 80 km from shore. The Canadian population of marbled murrelets is listed as Threatened under the federal Species at Risk Act. To investigate the species’ marine distribution, we conducted analyses of the occurrence of marbled murrelets at-sea between 2000 and 2022, utilizing at-sea and marine shoreline surveys in the Canadian portion of the Salish Sea. The data were divided into breeding season (April to August) and non-breeding season (September to March) to examine the relationship between environmental covariates and the species’ distribution. We considered terrestrial covariates related to potential nesting habitat, as well as marine covariates related to Pacific sand lance (Ammodytes personatus) quality habitat, slope, depth, streams, tidal currents, shorelines and climate indices (NPGO). We compared marine distribution between breeding and nonbreeding seasons and predicted variations in covariate relationships. Our study focuses on identifying averaged relationships and key spatial areas to gauge habitat quality at a landscape scale. Using a Generalized Additive Modelling approach, we found that both marine and terrestrial covariates contributed to predicting murrelet distribution during both seasons. Notably, Pacific sand lance habitat played a significant role in both the breeding and nonbreeding season, while the overall amount of nesting habitat within an 80 km radius influenced occurrence probability in the nonbreeding season. Our analysis accurately predicted distribution patterns at a resolution of 3 x 3 km with an AUC of 0.89 and AUPRC of 0.52 for the breeding season, and AUC of 0.88 and a AUPRC of 0.28 for non-breeding season. Overall, our study highlights both terrestrial and marine drivers that influence the marine distribution of this threatened species and informs Canadian conservation efforts.

Comparative evaluation of TNM staging systems (eighth vs. ninth edition) for the non-surgical treatment of localized and locally advanced anal squamous cell carcinoma: Prognostic significance of T classification and lymph node status

This study aims to compare the survival discrimination of the Tumor-Node-Metastasis (TNM) eighth and ninth editions for patients with localized and locally advanced (LLA) anal squamous cell carcinoma (ASCC) treated non-surgically and to evaluate the prognostic impact of T classification and lymph node (LN) status with data from the Surveillance, Epidemiology, and End Results database. We retrospectively included 6,876 patients in the comparison. We observed the inversion of survival outcomes for stages IIB and IIIA diseases in the TNM eighth edition [median overall survival (OS): 112 months for stage IIB vs. not reached for stage IIIA]. By contrast, it demonstrated improvement in the TNM ninth edition (median OS: not reached for IIB disease vs. 120 months for IIIA disease, P<0.001). In the correlation analysis, we observed an increased correlation between T classification and TNM staging systems (r value increased from 0.78 to 0.93) and a decreased correlation for the LN status (r value decreased from 0.83 to 0.59). For OS, variable importance analysis demonstrated more weight of importance for the T classification than the LN status (0.0871 vs. 0.0048). Additionally, decision curve analysis and time-dependent receiver operating characteristic analysis confirmed the prognostic accuracy of T classification rather than the LN status. In conclusion, TNM ninth edition is a better prognostic indicator than the eighth edition for patients with LLA ASCC treated non-surgically. T classification plays a more important prognostic role than the LN status and warrants further validation.

Correction: Diversity and sex differences in rectal gland volatiles of Queensland fruit fly, Bactrocera tryoni (Diptera: Tephritidae)

Representation models and processing operators for quantum informational multi-media

To enhance the efficacy of multimedia quantum processing and diminish processing overhead, an advanced multimedia quantum representation model and quantum video display framework are devised. A range of framework processing operators are also developed, including an image color compensation operator, a bit plane inversion operator, and a frame displacement operator. In addition, to address image security issues, two quantum image operations have been proposed: color transformation operation and pixel blending operation. The research results indicated that the grayscale cost of the framework designed in this study was 33.8, the color cost was 40.5, and the total cost was 574 δ. In terms of color, the distribution of image elements in the red, green, and blue (RGB) channels was more balanced. In summary, the quantum video display framework has significant advantages in processing efficiency and image security. Compared to previous studies, the model proposed in this study exhibits higher processing speed and better processing quality in the face of complex image and video data. It effectively addresses the limitations of existing processing techniques while addressing emerging image security issues.