Shaping the immune landscape: Multidimensional environmental stimuli refine macrophage polarization and foster revolutionary approaches in tissue regeneration.

In immunology, the role of macrophages extends far beyond their traditional classification as mere phagocytes; they emerge as pivotal architects of the immune response, with their function being significantly influenced by multidimensional environmental stimuli. This review investigates the nuanced mechanisms by which diverse external signals ranging from chemical cues to physical stress orchestrate macrophage polarization, a process that is crucial for the modulation of immune responses. By transitioning between pro-inflammatory (M1) and anti-inflammatory (M2) states, macrophages exhibit remarkable plasticity, enabling them to adapt to and influence their surroundings effectively. The exploration of macrophage polarization provides a compelling narrative on how these cells can be manipulated to foster an immune environment conducive to tissue repair and regeneration. Highlighting cutting-edge research, this review presents innovative strategies that leverage the dynamic interplay between macrophages and their environment, proposing novel therapeutic avenues that harness the potential of macrophages in regenerative medicine. Moreover, this review critically evaluates the current challenges and future prospects of translating macrophage-centered strategies from the laboratory to clinical applications.

Recent advances in sugar-based AIE luminogens and their applications in sensing and imaging.

Most fluorogens with aggregation-induced emission (AIE) characteristics are hydrophobic and most common sugars are hydrophilic and naturally nontoxic. The combination of AIEgens and sugars can construct glycosyl AIEgens with the advantages of good water-solubility, low fluorescent background and satisfactory biocompatibility. Based on the specific reaction or binding with analytes to change the conjugate system or restrict intramolecular motions, glycosyl AIEgens can be used as powerful tools for detecting bioactive molecules or imaging living cells. In this feature article, we summarize recent advances in sugar-based AIE luminogens and their applications in biosensing and imaging. The sugar units could significantly increase the solubility, biocompatibility, target activity, and chemical modifying capacity and often decrease the background fluorescence of the AIE probes. Corresponding studies not only expand the application fields of AIEgens but also provide effective tools for broad carbohydrate research.

Factor structure and measurement invariance of the University Demand-Resource Questionnaire: further evidence from Hungarian university students.

Purpose: The present study aimed to further examine the factor structure and measurement invariance of the UDRQ among a sample of Hungarian university students. Methods: Firstly, the factor structure of the UDRQ was examined among 837 Hungarian university students. Specifically, two measurement models (first-order model and second-order model) were constructed and compared. Secondly, the internal consistency reliability of the UDRQ was examined. Thirdly, measurement invariance of the UDRQ was evaluated across genders. Finally, measurement invariance of the UDRQ was evaluated across two different samples. Results: It was found that the first-order model outperformed the second-order model and better represented the factor structure of the UDRQ subscales. Results of Cronbach's alpha and Composite Reliability suggested that the internal consistency reliabilities of the two UDRQ subscales were satisfactory. Measurement invariance analysis revealed that the UDRQ measurement model was strict invariant across genders and samples. Conclusion: The findings of the present study indicated that the UDRQ displayed satisfactory reliability and validity and could be used to assess demands and resources of Hungarian university students.

1D Anionic Covalent Organic Frameworks With Directed Migration of Alkali Metal Ions for High Ionic Conductivity.

Rational construction of high-performance ionic conductors is a critical challenge in the field of energy storage. In this study, a series of 1D anionic titanium-based covalent organic frameworks (COFs) containing abundant alkali metal ion migration sites, namely, COF-M-R (M = Li, Na, K; R = H, Me, Et), is constructed. The integration of negative TiO6 2- sites on 1D anionic COFs allows alkali metal cations to migrate directly through the channels. Meanwhile, the π-π stacking of 1D chain-to-chain allows the distribution of ion-migration sites in 2D planes. In view of this, multidimensional ionic transport in COFs is realized to achieve high ionic conductivity. COF-M-Rs exhibit an increased ionic conductivity as the counterions change from Li+ to Na+ to K+. Notably, COF-Na-Et has an impressive ionic conductivity as high as 0.81 × 10-3 S cm-1. The different decorated groups (H, Me, and Et) on the skeleton influence the dissociation of the cation from the polyanion. This study offers deep insights into the design of COF-based solid-state electrolytes to achieve high ionic conductivity by increasing the ionic transport dimensions.

Development and initial validation of the Engagement in Athletic Training Scale.

The current study presents the development process and initial validation of the Engagement in Athletic Training Scale (EATS), which was designed to evaluate athletes' engagement in athletic training. In study 1, item generation and initial content validity of the EATS were achieved. In study 2, the factor structure of the EATS was examined using exploratory factor analysis (EFA) and exploratory structural equation modeling (ESEM). Internal consistency reliabilities of the subscales were examined (N = 460). In study 3, factor structure, discriminant validity, internal consistency reliability, and nomological validity of the EATS were further examined in an independent sample (N = 513). Meanwhile, measurement invariance of the EATS across samples (study 2 and study 3) and genders was evaluated. Overall, results from the 3 rigorous studies provided initial psychometric evidence for the 19-item EATS and suggested that the EATS could be used as a valid and reliable measure to evaluate athletes' engagement in athletic training.

Three-Dimensional Covalent Organic Frameworks Based on Linear and Trigonal Linkers for High-Performance H2O2 Photosynthesis.

The design of three-dimensional covalent organic frameworks (3D COFs) using linear and trigonal linkers remains challenging due to the difficulty in achieving a specific non-planar spatial arrangement with low-connectivity building units. Here, we report the novel 3D COFs with linear and trigonal linkers, termed TMB-COFs, exhibiting srs topology. The steric hindrance provides an additional force to alter the torsion angles of peripheral triangular units, guiding the linear unit to connect with the trigonal unit into 3D srs frameworks, rather than the more commonly observed two-dimensional (2D) hcb structures. Furthermore, we comprehensively examined the hydrogen peroxide photocatalytic production capacity of the TMB-COFs in comparison with analogous 2D COFs. The experimental results and DFT calculations demonstrate a significant enhancement in photocatalytic hydrogen peroxide production efficacy through framework regulation. This work emphasizes the steric configuration using low connectivity building units, offering a fresh perspective on the design and application of 3D COFs.

Thermal facial image analyses reveal quantitative hallmarks of aging and metabolic diseases.

Although human core body temperature is known to decrease with age, the age dependency of facial temperature and its potential to indicate aging rate or aging-related diseases remains uncertain. Here, we collected thermal facial images of 2,811 Han Chinese individuals 20-90 years old, developed the ThermoFace method to automatically process and analyze images, and then generated thermal age and disease prediction models. The ThermoFace deep learning model for thermal facial age has a mean absolute deviation of about 5 years in cross-validation and 5.18 years in an independent cohort. The difference between predicted and chronological age is highly associated with metabolic parameters, sleep time, and gene expression pathways like DNA repair, lipolysis, and ATPase in the blood transcriptome, and it is modifiable by exercise. Consistently, ThermoFace disease predictors forecast metabolic diseases like fatty liver with high accuracy (AUC > 0.80), with predicted disease probability correlated with metabolic parameters.

The Buerger's rabbit model: a closer step to unravelling thromboangiitis obliterans?

OBJECTIVE: Thromboangiitis obliterans (TAO) remains clinical challenging due to its rarity and underwhelming management outcomes. This study aimed to describe a novel TAO rabbit model that demonstrates a closer resemblance to TAO. METHODS: Thirty-six New Zealand rabbits underwent the surgical implantation of calibrated gelatin sponge particles (CGSPs) into their right femoral artery. The CGSPs were soaked in different solutions to simulate different types of thrombi: normal (NT; normal saline); inflammatory TAO thrombus (TAO; dimethylsulfoxide [DMSO]), and DMSO with methotrexate (MTX). All groups underwent clinical assessment, digital subtraction angiography (DSA) and histopathological analysis at time points day 0 (immediate), week 1 (acute), week 2 (subacute), and week 4 (chronic). RESULTS: The TAO rabbit presented with signs of ischemia of the right digit at week 4. On DSA, the TAO rabbits exhibited formation of corkscrew collaterals starting week 1. On H&E staining, gradual CGSP degradation was observed along with increased red blood cell aggregation and inflammatory cells migration in week 1. On week 2, disorganization of the tunica media layer and vascular smooth muscle cell (VSMC) proliferation was observed. In the TAO rabbit, migrated VSMCs, inflammatory cells, and extracellular matrix with collagen-like substances gradually occluded the lumen. On week 4, the arterial lumen of the TAO rabbit was filled with relatively-organized VSMC and endothelial cell clusters with less inflammatory cells. Neorevascularization was found in the MTX-treated group. CONCLUSION: The novel TAO rabbit model shows a closer resemblance to human TAO clinically, radiographically, and histopathologically. Histological analysis of the IT progression in the TAO model suggests that it is of VSMC origin.

Single-cell omics: experimental workflow, data analyses and applications.

Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular features. Our exploration of how the genomes orchestrate the formation and maintenance of each cell, and control the cellular phenotypes of various organismsis, is both captivating and intricate. Since the inception of the first single-cell RNA technology, technologies related to single-cell sequencing have experienced rapid advancements in recent years. These technologies have expanded horizontally to include single-cell genome, epigenome, proteome, and metabolome, while vertically, they have progressed to integrate multiple omics data and incorporate additional information such as spatial scRNA-seq and CRISPR screening. Single-cell omics represent a groundbreaking advancement in the biomedical field, offering profound insights into the understanding of complex diseases, including cancers. Here, we comprehensively summarize recent advances in single-cell omics technologies, with a specific focus on the methodology section. This overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.

A case of Ph+ acute lymphoblastic leukemia and EGFR mutant lung adenocarcinoma synchronous overlap: may one TKI drug solve two diseases?

BACKGROUND: Philadelphia chromosome positive (Ph+) acute lymphoblastic leukemia (ALL) refers to ALL patients with t(9;22) cytogenetic abnormalities, accounting for about 25% of ALL. Lung adenocarcinoma (LUAD) is the most common pathological type of non-small-cell lung cancer, which has a frequency of approximately 45% cases with mutations in EGFR. Both Ph+ ALL and EGFR mutant LUAD are involved in the pathogenesis of the abnormal activation of the tyrosine kinase pathway. Although the second primary hematological malignancy after the treatment of solid tumors is common in clinics, the synchronous multiple primary malignant tumors of hematological malignancy overlap solid tumors are uncommon, even both tumors involved in the pathogenesis of the abnormal activation of the tyrosine kinase pathway are extremely rare. CASE PRESENTATION: An 84-year-old man with fatigue and dizziness was diagnosed with Ph+ ALL. Meanwhile, a chest CT indicated a space-occupying lesions, characterized by the presence of void, in the right lower lope with the enlargement of mediastinal lymph node and right pleural effusion. After a few weeks, the patient was diagnosed with LUAD with EGFR exon 19 mutation. Both tyrosine kinase inhibitors (TKI) (Flumatinib) and EGFR-TKI (Oxertinib) was used for the patients, and finally have controlled both diseases. CONCLUSION: As far as we know, we for the first time reported a case of Ph+ ALL and EGFR mutant LUAD synchronous overlap, of which pathogenesis is related to abnormal tyrosine kinase activation. This patient was successfully treated with two different TKIs without serious adverse events.

Optimizing anterior urethral stricture assessment: leveraging AI-assisted three-dimensional sonourethrography in clinical practice.

PURPOSE: This investigation sought to validate the clinical precision and practical applicability of AI-enhanced three-dimensional sonographic imaging for the identification of anterior urethral stricture. METHODS: The study enrolled 63 male patients with diagnosed anterior urethral strictures alongside 10 healthy volunteers to serve as controls. The imaging protocol utilized a high-frequency 3D ultrasound system combined with a linear stepper motor, which enabled precise and rapid image acquisition. For image analysis, an advanced AI-based segmentation process using a modified U-net algorithm was implemented to perform real-time, high-resolution segmentation and three-dimensional reconstruction of the urethra. A comparative analysis was performed against the surgically measured stricture lengths. Spearman's correlation analysis was executed to assess the findings. RESULTS: The AI model completed the entire processing sequence, encompassing recognition, segmentation, and reconstruction, within approximately 5 min. The mean intraoperative length of urethral stricture was determined to be 14.4 ± 8.4 mm. Notably, the mean lengths of the urethral strictures reconstructed by manual and AI models were 13.1 ± 7.5 mm and 13.4 ± 7.2 mm, respectively. Interestingly, no statistically significant disparity in urethral stricture length between manually reconstructed and AI-reconstructed images was observed. Spearman's correlation analysis underscored a more robust association of AI-reconstructed images with intraoperative urethral stricture length than manually reconstructed 3D images (0.870 vs. 0.820). Furthermore, AI-reconstructed images provided detailed views of the corpus spongiosum fibrosis from multiple perspectives. CONCLUSIONS: The research heralds the inception of an innovative, efficient AI-driven sonographic approach for three-dimensional visualization of urethral strictures, substantiating its viability and superiority in clinical application.

Covalent Organic Frameworks for Electrocatalysis: Design, Applications, and Perspectives.

Covalent organic frameworks (COFs) are an innovative class of crystalline porous polymers composed of light elements such as C, N, O, etc., linked by covalent bonds. The distinctive properties of COFs, including designable building blocks, large specific surface area, tunable pore size, abundant active sites, and remarkable stability, have led their widespread applications in electrocatalysis. In recent years, COF-based electrocatalysts have made remarkable progress in various electrocatalytic fields, including the hydrogen evolution reaction, oxygen evolution reaction, oxygen reduction reaction, nitrogen reduction reaction, nitrate reduction reaction, and carbon dioxide reduction reaction. This review begins with an introduction to the design and synthesis strategies employed for COF-based electrocatalysts. These strategies include heteroatom doping, metalation of COF and building monomers, encapsulation of active sites within COF pores, and the development of COF-based derived materials. Subsequently, a systematic overview of the recent advancements in the application of COF-based catalysts in electrocatalysis is presented. Finally, the review discusses the main challenges and outlines possible avenues for the future development of COF-based electrocatalysts.

Prediagnosis recognition of acute ischemic stroke by artificial intelligence from facial images.

Stroke is a major threat to life and health in modern society, especially in the aging population. Stroke may cause sudden death or severe sequela-like hemiplegia. Although computed tomography (CT) and magnetic resonance imaging (MRI) are standard diagnosis methods, and artificial intelligence models have been built based on these images, shortage in medical resources and the time and cost of CT/MRI imaging hamper fast detection, thus increasing the severity of stroke. Here, we developed a convolutional neural network model by integrating four networks, Xception, ResNet50, VGG19, and EfficientNetb1, to recognize stroke based on 2D facial images with a cross-validation area under curve (AUC) of 0.91 within the training set of 185 acute ischemic stroke patients and 551 age- and sex-matched controls, and AUC of 0.82 in an independent data set regardless of age and sex. The model computed stroke probability was quantitatively associated with facial features, various clinical parameters of blood clotting indicators and leukocyte counts, and, more importantly, stroke incidence in the near future. Our real-time facial image artificial intelligence model can be used to rapidly screen and prediagnose stroke before CT scanning, thus meeting the urgent need in emergency clinics, potentially translatable to routine monitoring.

The Correlation of Centromere Protein Q with Diagnosis and Prognosis in Hepatocellular Carcinoma.

Introduction: Hepatocellular carcinoma (HCC) is one of the major types of liver cancer. Previous studies have shown that the centromere protein family is associated with malignant biological behaviors such as HCC proliferation. As a member of the centromere protein family, centromere protein Q (CENPQ) is closely associated with immunotherapy and immune cell infiltration in various tumors. However, the role and mechanism of CENPQ in HCC remain unclear. Methods: Multiple public databases and RT-qPCR were used to study the expression of CENPQ in HCC. Based on TCGA data, the correlation between CENPQ and clinicopathological characteristics and prognosis of HCC patients was analyzed, and its diagnostic value was evaluated. The potential biological functions of CENPQ in HCC were explored by functional enrichment analysis of differentially expressed genes. The distribution of tumor-infiltrating immune cell types was assessed using single-sample GSEA, and immune checkpoint gene expression was analyzed using Spearman correlation. Subsequently, loss-of-function experiments were performed to determine the function of CENPQ on the cell cycle and proliferation of HCC cells in vitro. Results: CENPQ was found highly expressed in HCC and correlated with weight, BMI, age, AFP, T stage, pathologic stage, histologic grade, and prothrombin time (all p < 0.05). ROC and Kaplan-Meier analyses indicated that CENPQ may be potentially used as a diagnostic marker for HCC (AUC = 0.881), and its upregulation is associated with decreased OS (p = 0.002), DSS (p < 0.001), and PFI (p = 0.002). Functional enrichment analysis revealed an association of CENPQ with biological processes such as immune cell infiltration, cell cycle, and hippo-merlin signaling deregulation in HCC. Furthermore, knockdown of CENPQ manifested in HCC cells with G0/1 phase cycle arrest and decreased proliferative capacity. Conclusion: CENPQ expression was higher in HCC tissues than in normal liver tissues. It was significantly associated with poor prognosis, immune cell infiltration, cell cycle, and proliferation. Therefore, CENPQ may become a promising prognostic biomarker for HCC patients.

Mental health literacy, mental health experiences and help-seeking behaviours of Chinese elite athletes: a qualitative study.

Introduction: Elite athletes' help-seeking on mental health might be influenced by their mental health literacy (MHL) and mental health experiences. The current study aimed to explore the MHL, experiences and help-seeking behaviours among elite athletes using a qualitative approach. Methods: Face-to-face semi-structured interviews were conducted among 20 Chinese elite athletes, 12 coaches, and 5 team officials. Interview data was analyzed using content analysis. Results: Seven main themes emerged from the analysis. The current study revealed that Chinese elite athletes suffered from various mental health issues and athletes' MHL levels, help-seeking attitudes and intentions, Chinese sports environments, and Chinese cultural background could impact their help-seeking behaviours. Conclusion: Support for Chinese elite athletes' mental health and help-seeking requires improvement.

Coordinate-wise monotonic transformations enable privacy-preserving age estimation with 3D face point cloud.

The human face is a valuable biomarker of aging, but the collection and use of its image raise significant privacy concerns. Here we present an approach for facial data masking that preserves age-related features using coordinate-wise monotonic transformations. We first develop a deep learning model that estimates age directly from non-registered face point clouds with high accuracy and generalizability. We show that the model learns a highly indistinguishable mapping using faces treated with coordinate-wise monotonic transformations, indicating that the relative positioning of facial information is a low-level biomarker of facial aging. Through visual perception tests and computational 3D face verification experiments, we demonstrate that transformed faces are significantly more difficult to perceive for human but not for machines, except when only the face shape information is accessible. Our study leads to a facial data protection guideline that has the potential to broaden public access to face datasets with minimized privacy risks.

Single-cell senescence identification reveals senescence heterogeneity, trajectory, and modulators.

Cellular senescence underlies many aging-related pathologies, but its heterogeneity poses challenges for studying and targeting senescent cells. We present here a machine learning program senescent cell identification (SenCID), which accurately identifies senescent cells in both bulk and single-cell transcriptome. Trained on 602 samples from 52 senescence transcriptome datasets spanning 30 cell types, SenCID identifies six major senescence identities (SIDs). Different SIDs exhibit different senescence baselines, stemness, gene functions, and responses to senolytics. SenCID enables the reconstruction of senescent trajectories under normal aging, chronic diseases, and COVID-19. Additionally, when applied to single-cell Perturb-seq data, SenCID helps reveal a hierarchy of senescence modulators. Overall, SenCID is an essential tool for precise single-cell analysis of cellular senescence, enabling targeted interventions against senescent cells.

Insights into growth stages and genotypes in airborne Pb accumulation in Oryza sativa L. grains: Utilizing isotope fingerprinting alongside a model study.

Atmospheric exposure is an important pathway of accumulation of lead (Pb) in Oryza sativa L. grains. In this study, source contributions of soil, early atmospheric exposure, and late atmospheric exposure, along with their bioaccumulation ratios were examined both in the pot and field experiments using stable Pb isotope fingerprinting technology combined with a three-compartment accumulation model. Furthermore, genotype differences in airborne Pb accumulation among four field-grown rice cultivars were investigated using the partial least squares path model (PLS-PM) linking rice Pb accumulation to agronomic traits. The findings revealed that during the late growth period, the air-foliar-grain transfer of Pb was crucial for rice Pb accumulation. Approximately 69-82% of the Pb found in polished rice was contributed by atmospheric source, with more than 80% accumulating during the late growth stage. The air accumulation ratios of rice grains were genotype-specific and estimated to be 0.364-1.062 m3/g during the late growth. Notably, grain size exhibited the highest standardized total effects on the airborne Pb concentrations in the polished rice, followed by leaf Pb and the upward translocation efficiency of Pb. The present study indicates that mitigating the health risks associated with Pb in rice can be achieved by controlling atmospheric Pb levels during the late growth stage and choosing Japonica inbred varieties characterized by large grain size.

Cell-free DNA methylation reveals cell-specific tissue injury and correlates with disease severity and patient outcomes in COVID-19.

BACKGROUND: The recently identified methylation patterns specific to cell type allows the tracing of cell death dynamics at the cellular level in health and diseases. This study used COVID-19 as a disease model to investigate the efficacy of cell-specific cell-free DNA (cfDNA) methylation markers in reflecting or predicting disease severity or outcome. METHODS: Whole genome methylation sequencing of cfDNA was performed for 20 healthy individuals, 20 cases with non-hospitalized COVID-19 and 12 cases with severe COVID-19 admitted to intensive care unit (ICU). Differentially methylated regions (DMRs) and gene ontology pathway enrichment analyses were performed to explore the locus-specific methylation difference between cohorts. The proportion of cfDNA derived from lung and immune cells to a given sample (i.e. tissue fraction) at cell-type resolution was estimated using a novel algorithm, which reflects lung injuries and immune response in COVID-19 patients and was further used to evaluate clinical severity and patient outcome. RESULTS: COVID­19 patients had globally reduced cfDNA methylation level compared with healthy controls. Compared with non-hospitalized COVID-19 patients, the cfDNA methylation pattern was significantly altered in severe patients with the identification of 11,156 DMRs, which were mainly enriched in pathways related to immune response. Markedly elevated levels of cfDNA derived from lung and more specifically alveolar epithelial cells, bronchial epithelial cells, and lung endothelial cells were observed in COVID-19 patients compared with healthy controls. Compared with non-hospitalized patients or healthy controls, severe COVID-19 had significantly higher cfDNA derived from B cells, T cells and granulocytes and lower cfDNA from natural killer cells. Moreover, cfDNA derived from alveolar epithelial cells had the optimal performance to differentiate COVID-19 with different severities, lung injury levels, SOFA scores and in-hospital deaths, with the area under the receiver operating characteristic curve of 0.958, 0.941, 0.919 and 0.955, respectively. CONCLUSION: Severe COVID-19 has a distinct cfDNA methylation signature compared with non-hospitalized COVID-19 and healthy controls. Cell type-specific cfDNA methylation signature enables the tracing of COVID-19 related cell deaths in lung and immune cells at cell-type resolution, which is correlated with clinical severities and outcomes, and has extensive application prospects to evaluate tissue injuries in diseases with multi-organ dysfunction.