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Meibomian gland dysfunction (MGD) constitutes a highly prevalent ocular surface condition and is a major etiological factor in tear film instability and evaporative dry eye disease. Although MGD can be objectively identified based on structural and functional abnormalities of the meibomian glands, epidemiological studies rarely differentiate between symptomatic and asymptomatic disease. Asymptomatic meibomian gland dysfunction, characterized by structural or functional gland alterations in the absence of self-reported ocular symptoms, may constitute an early and frequently overlooked phase within the disease spectrum. The objective of this systematic review and meta-analysis was to quantify the prevalence of asymptomatic MGD among adult populations. A comprehensive literature search was performed across PubMed, Web of Science, Scopus, ScienceDirect, and Google Scholar in accordance with the PRISMA guidelines. The review protocol was registered in PROSPERO (CRD420261283795). Cross-sectional and observational studies reporting the prevalence of asymptomatic MGD in adult populations were included. Data extraction and study selection were performed independently by two reviewers. A random-effects meta-analysis of proportions with logit transformation was applied using R software. Interstudy heterogeneity was quantified using the I2 statistic, and possible contributors to variability were investigated through sensitivity analyses and meta-regression. Methodological quality and risk of bias were assessed using a modified version of the Newcastle-Ottawa Scale, while the overall certainty of the evidence was evaluated according to the GRADE approach. Eight cross-sectional studies published between 2012 and 2023 were included, comprising a total of 3,637 participants and 1,313 cases of asymptomatic MGD. The combined prevalence of asymptomatic MGD was 72.86% (95% CI: 19.33-96.78%), with substantial heterogeneity across studies (I 2 = 98.8%). Sensitivity analyses identified one influential study; however, the overall finding of a high prevalence remained consistent. Meta-regression showed that sex distribution significantly contributed to between-study heterogeneity, while no association with year of publication was observed. The level of certainty for the pooled prevalence estimate was classified as low. Asymptomatic MGD is highly prevalent among adult populations worldwide. These findings indicate that reliance on symptom-based assessment alone may underestimate the burden of early MGD. Early identification of asymptomatic gland abnormalities may support preventive approaches to reduce progression to symptomatic dry eye disease, although further standardized and prospective studies are required. https://www.crd.york.ac.uk/PROSPERO/view/CRD420261283795, CRD420261283795.

Intracranial atherosclerotic stenosis (ICAS) is a major cause of stroke and cognitive impairment. We evaluated whether nighttime systolic blood pressure (SBP) provides additional information beyond daytime SBP regarding cognition, ICAS burden, and plasma biomarkers in patients with ICAS. In this multicenter cross-sectional study, patients with ICAS underwent 24-hour ambulatory BP monitoring, brain magnetic resonance imaging, plasma biomarker assays, and neuropsychological testing. Multivariable models including both daytime and nighttime SBP assessed associations with ICAS burden, cerebral small vessel disease burden, plasma biomarkers, and cognition. Incremental analyses evaluated additional information from nighttime SBP beyond daytime SBP. Structural equation modeling examined patterns of associations among SBP, ICAS burden, NfL (neurofilament light chain), and cognition. Among 301 patients, higher nighttime SBP was associated with poorer cognition (per 10 mm Hg, β=-0.139 [95% CI, -0.263 to -0.016]; P=0.028), higher plasma NfL (β=0.162 [95% CI, 0.049-0.275]; P=0.005), and greater ICAS burden (odds ratio [OR], 1.365 [95% CI, 1.090-1.716]; P=0.007) independent of daytime SBP. Among biomarkers, only NfL was consistently associated with nighttime SBP. Incremental analyses supported additional information from nighttime SBP beyond daytime SBP for cognition, ICAS burden, and NfL. In structural equation modeling, the association between nighttime SBP and cognition was more closely aligned with NfL than with ICAS burden. In ICAS, nighttime SBP provides additional information beyond daytime SBP for cognition, vascular burden, and neuroaxonal injury. Nighttime SBP and plasma NfL may represent complementary indicators of vascular stress and cognitive vulnerability.

Polysaccharides derived from Angelica dahurica exhibit potent wound healing activity, yet the pronounced structural heterogeneity of natural extracts has obscured the identity of the active motif and hindered clinical translation. Here we report a convergent, one-pot [22+22+22] glycosylation strategy based on glycosyl donor preactivation that enables the precise chemical synthesis of a 66-unit A. dahurica polysaccharide. This approach facilitates the efficient assembly of a comprehensive glycan library spanning tetrasaccharides to the full-length 66-mer polysaccharide, allowing for systematic biological evaluation. Functional screening identifies the reducing end hexasaccharide as the minimal active motif responsible for wound healing activity. Mechanistic analyses reveal that the synthetic hexa- and dodecasaccharides promote fibroblast and keratinocyte proliferation and migration, while concurrently reprogramming macrophage polarization. Crucially, gram-scale synthesis of both glycans enables definitive in vivo evaluation, demonstrating significantly accelerated wound closure through attenuation of excessive inflammation and promotion of organized collagen deposition. Collectively, these findings establish a general paradigm for deconvoluting heterogeneous natural polysaccharide extracts through de novo synthesis of structurally well-defined glycans as precision-engineered wound healing therapeutics.

Decellularized extracellular matrix (dECM) preserves native biochemical and biophysical cues and serves as a functional biomaterial for engineered tissue development. While tissue-specific extracellular matrix (ECM) has been widely studied, regional variation within the same organ remains poorly understood. Here, we investigate chamber-specific roles of ventricular (vtdECM) and atrial (atdECM) dECMs in engineered heart tissue (EHT) formation using induced pluripotent stem cell-derived cardiomyocyte (CM) subtypes. Proteomic analysis revealed distinct compositional profiles, with vtdECM enriched in ventricular development-related proteins and atdECM enriched in structural organization-related proteins. Ventricular CMs exhibited enhanced maturation and function in vtdECM, whereas atrial CMs showed limited responsiveness to ECM composition despite transcriptome-level differences. Encapsulation timing further modulated these effects, with early encapsulation promoting structural maturation and late encapsulation enhancing calcium handling. These findings demonstrate that chamber-specific ECM composition and developmental timing cooperatively regulate subtype-specific CM maturation, providing a framework for designing physiologically relevant EHTs.

Human erythrocytes serve as an ideal model for cellular aging, a process where longevity relies on membrane scaffold integrity. The oxidative deterioration of Band 3, a major integral membrane protein, is a central driver of this senescence. This study investigated whether methyl eugenol (ME) stabilizes Band 3 against age-associated oxidative fragility. Erythrocytes were challenged with H2O2 to simulate age-associated oxidative injury. Damage was evaluated via hemolysis assays, SEM, and flow cytometry. Sulfate (SO4 2-) uptake kinetics and Western blotting were employed to assess Band 3 anion exchange function and structural stability. In silico docking simulated interactions between ME metabolites and the Band 3 structure. Physiological relevance was validated in a human cohort (n = 81; 20-90 years) via regression and stratified analyses of glutathione (GSH) and malondialdehyde (MDA) levels. ME exhibited an optimal protective concentration at 2 µM, effectively preserving biconcave morphology and attenuating hemolysis. Treatment significantly mitigated intracellular oxidative stress and rescued cell viability. Mechanistically, ME suppressed the pathological increase in intracellular Ca2+ concentration and inhibited calpain activity. Functionally, ME significantly restored sulfate transport rates. Western blotting confirmed that ME specifically preserved the full-length (100 kDa) and cytoplasmic (43 kDa) domains of Band 3, whereas the 55 kDa transmembrane domain remained largely unaffected. Docking simulations predicted a specific interaction with residue ARG292 within the cytoplasmic domain, suggesting a structural basis for this stabilization. In the donor cohort, ME extended the projected GSH half-life (from 47.14 to 64.14 years) and reduced maximal lipid peroxidation by ~40%. ME mitigates oxidative eryptosis by coupling Ca2+-calpain inhibition with site-specific Band 3 stabilization, offering a rationale for using ME to standardize erythrocyte quality and reduce age-associated fragility.

Cardiovascular diseases (CVD) are among the leading causes of mortality worldwide due to genetic predisposition and lifestyle factors. Proper diagnosis of cardiovascular diseases is crucial to provide early-stage treatments. Conventional diagnostic methods such as stress tests, electrocardiograms, and echocardiography detect valuable insights into rhythm abnormalities, structural anomalies, or other cardiovascular conditions. However, their reliability heavily depends on human expertise, and they may not always detect early-stage signs of disease. In recent years, Machine Learning (ML) models have emerged as alternative diagnosis tools, capable of identifying CVD with higher accuracy. ML enables automated and precise detection based on data relationships, capturing hidden, complex patterns that are not apparent through traditional diagnostics. Most ML approaches employ supervised learning, which requires labeled data that are not always available in medical records. Under such circumstances, unsupervised learning has been explored as a suitable alternative. In this paper, a hybrid unsupervised approach combines the neural network structure of Self-Organizing Maps (SOM) with the dimensionality reduction technique of Principal Component Analysis (PCA) for unsupervised analysis for clustering CVD across different severity levels. Considering a data compression mechanism, the synergy among these methods leverages the ability to map unsupervised complex, high-dimensional data into lower-dimensional space. The proposed approach significantly improves the detection of hidden structures within large, high-dimensional medical cardiovascular datasets, providing insights into cardiovascular risk factors and improving the overall diagnostic process. Experimental evaluation on the UCI Cleveland Heart Disease dataset shows that the proposed PCA-SOM model achieves a Silhouette score of 0.94 (train) and 0.79 (test), and a Davies-Bouldin index of 0.08 (train) and 0.16 (test), outperforming baseline clustering methods such as K-means, hierarchical clustering, Gaussian Mixture and Spectral clustering highlighting its potential for supporting CVD detection.

Clear cell renal cell carcinoma (ccRCC) can transition from indolent, low-grade lesions to high-grade, lethal disease through a layered cascade of genomic, epigenomic, metabolic, and immune remodeling. The initiating event in ∼90% of ccRCC is loss of chromosome 3p, enabling biallelic inactivation of VHL and frequent co-loss of chromatin regulators PBRM1, BAP1, and SETD2. The order and combination of genetic alterations shape distinct evolutionary trajectories in ccRCC. PBRM1 loss, observed in approximately 55% of cases, is linked to angiogenic, initially low-grade tumors that may later progress to higher-grade disease. In contrast, BAP1 loss (∼15%) drives early high-grade, inflammatory, immune-enriched phenotypes associated with aggressive behavior and worse prognosis. Progression is further shaped by structural and copy-number events including, chromothripsis coupling 3p loss with 5q gain, and recurrent 9p and 14q losses and 8q gain further promote cell-cycle dysregulation, genomic instability, and metastatic competence. Functionally, VHL loss stabilizes HIF-2α, driving VEGF signaling and Carbonic Anhydrase IX (CA9) expression and coupling pseudohypoxia to metabolic reprogramming and redox protection (glutathione/SLC7A11). Proteogenomic and metabolomic studies further highlight nutrient addiction with GLUT1/ASCT2 upregulation and a stress-resistant metabolic shield linked to grade and therapy resistance. Single-cell and spatial atlases place these programs in anatomic setting. They show that invasive fronts with high epithelial-mesenchymal transition (EMT) activity co-localize with myeloid and regulatory T-cell niches dominated by IL-1β, NF-κB, IL-10, STAT3, and TGF-β, along with exhausted CD8+ T cells, thereby promoting immune escape and invasion. Integrating these layers yields mechanism-based biomarkers and therapeutic nodes for risk-adapted precision treatment.

There is broad consensus that successful repair of severe peripheral nerve injuries requires recreating key structural and cellular features of the natural regenerative process, particularly the action of Bands of Büngner (BoB), longitudinal Schwann cell (SC) structures that guide regenerating axons. Current biomaterial-based strategies have shown limited efficacy, in part because they do not sufficiently reproduce the anisotropic and cellular microenvironment established by BoB, resulting in disorganized axonal growth and reduced regenerative efficiency across long gaps. To address this limitation, a biohybrid scaffold designed to promote Schwann cell self-organization into Büngner-like structures through defined physical cues. Rather than relying solely on biochemical supplementation is developed, this system leverages anisotropic fiber architecture to induce SC alignment and early activation-associated phenotypic modulation. In this study, a self-organizing biohybrid BoB (BBoB) construct formed by Schwann cells within an aligned fiber-based scaffold is presented. It is demonstrated that these engineered structures recapitulate key morphological features of native BoB in vitro and promote enhanced axonal regeneration across a 11 mm sciatic nerve defect in vivo. Together, these findings support the concept that physically programmed Schwann cell organization within biomaterial conduits can enhance peripheral nerve regeneration, using clinically accessible biomaterials and autologous Schwann cells.

Cerebral amyloid angiopathy (CAA), a cerebral small vessel disease characterized by vascular amyloid deposition, presents with heterogeneous imaging features, but the biological mechanisms underlying hemorrhagic markers remain unclear. We assessed hemorrhage patterns in CAA to determine their associations with amyloid burden and related imaging markers. Sixty-two patients with probable CAA underwent Pittsburgh compound B-positron emission tomography and structural magnetic resonance imaging. Participants were classified by dominant hemorrhagic pattern: lobar cerebral microbleed-dominant (n=31), cortical superficial siderosis-dominant (n=17), and nondominant (n=14). Global cortical amyloid burden was quantified as Pittsburgh compound B distribution volume ratio. White matter hyperintensity volume and high-degree centrum semiovale-enlarged perivascular spaces were assessed. Associations were tested using age- and sex-adjusted regression models. Global Pittsburgh compound B distribution volume ratio was significantly higher in the cerebral microbleed-dominant (1.40±0.23) and cortical superficial siderosis-dominant (1.45±0.27) groups than nondominant group (1.20±0.17; P=0.007 and P=0.006, respectively), and these associations remained independent after adjustment (odds ratio [OR], 1.8 [95% CI, 1.1-2.8]; P=0.009 and OR, 1.6 [95% CI, 1.1-2.5]; P=0.020). Compared with the nondominant group, high-degree centrum semiovale-enlarged perivascular spaces were independently associated with both cerebral microbleed-dominant (OR, 9.3 [95% CI, 1.6-52]; P=0.011) and cortical superficial siderosis-dominant (OR, 10 [95% CI, 1.6-62]; P=0.013). In the full cohort, Pittsburgh compound B distribution volume ratio was independently associated with high-degree centrum semiovale-enlarged perivascular spaces (P=0.016) and white matter hyperintensity volume (P=0.049). Findings were unchanged in sensitivity analyses, adjusting for intracerebral hemorrhage. Amyloid burden in CAA is associated with hemorrhage-dominant patterns, high-degree centrum semiovale-enlarged perivascular spaces, and greater WMH volume. These findings support a close link between vascular amyloid deposition and downstream vascular brain injury, underscoring its relevance as a therapeutic target in CAA.

The clinical deployment of antibiotics is undermined by antimicrobial resistance. Without new agents to treat antibiotic-resistant bacterial infections, mortality rates are predicted to reach 10 million people per year by 2050. Most antibiotics are derived from natural products (NPs) produced by bacteria; however, this resource was abandoned by industry because of high rediscovery rates. We are amid a natural product renaissance fuelled by inexpensive access to genome sequencing and sophisticated bioinformatic tools, which have highlighted that most of the biosynthetic pathways for NPs are not expressed in the laboratory. Here, we engineered the expression of a silent biosynthetic gene cluster harboured by an environmental isolate of Streptomyces albidoflavus. Using a bioinformatics-guided approach, we isolated and structurally characterised a novel glycopeptide antibiotic (GPA) named biffamycin A, which is the smallest GPA known and harbours unprecedented 5-chloro-4-methoxy tryptophan and 3-hydroxy(α-D-mannoysl)-D-lysine moieties. Biffamycin A possesses antimycobacterial and antistaphylococcal bioactivity, including against methicillin- and vancomycin-resistant Staphylococcus aureus.

The effects of intravenous thrombolytic agents on fibrinogen differ due to structural differences among the agents. Using data from the RAISE (Reteplase Versus Alteplase for Acute Ischemic Stroke) trial, we aimed to investigate the impact of differences in baseline plasma fibrinogen levels on the efficacy and safety of reteplase versus alteplase within 4.5&#x2009;hours of acute ischemic stroke symptom onset. This post hoc subgroup analysis of the multicenter RAISE trial categorized participants by baseline fibrinogen levels: low (<2&#x2009;g/L), normal (2-4&#x2009;g/L), and high (>4&#x2009;g/L). The primary efficacy outcome was excellent functional outcome at 90&#x2009;days (modified Rankin scale score of 0 or 1). The primary safety outcome was symptomatic intracranial hemorrhage within 36&#x2009;hours. A total of 1373 patients with acute ischemic stroke were included. Ninety-two in the low fibrinogen group (<2&#x2009;g/L), 1178 in the normal fibrinogen group (2-4&#x2009;g/L), and 103 in the high fibrinogen group (>4&#x2009;g/L). Adjusted risk ratios of primary efficacy outcome were 1.13 (95% CI, 0.97-1.32) for the low fibrinogen group, 1.13 (95% CI, 1.04-1.23) for the normal fibrinogen group, and 1.09 (95% CI, 0.84-1.42) for the high fibrinogen group. The primary safety outcome showed no difference between reteplase and alteplase in the 3 fibrinogen subgroups. Among patients with acute ischemic stroke who were treated with either reteplase or alteplase within 4.5&#x2009;hours after symptom onset, there was no difference observed in the relative efficacy and safety between the 2 groups across the 3 fibrinogen subgroups. However, these findings should be interpreted cautiously and require validation in larger, adequately powered prospective studies. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT05295173.

Quantum technologies-quantum computing, quantum sensing, and quantum-enabled materials-are increasingly proposed as tools to accelerate drug discovery. Yet "quantum advantage" is frequently asserted without standardized benchmarks, clinically meaningful endpoints, or controlled comparisons against modern classical workflows. This review separates (i) quantum computing for molecular simulation and optimization, (ii) quantum sensing for structural/biophysical characterization and diagnostics, and (iii) quantum nanotechnologies for imaging and sensing, and then extends the framework to include device-led and physical therapies that increasingly co-evolve with drug development: photobiomodulation (red/NIR), focused ultrasound for blood-brain barrier opening and delivery enhancement, noninvasive neuromodulation devices (tDCS/TMS), and optogenetic therapies. We summarize demonstrated capabilities and constraints of NISQ-era computing, outline algorithmic classes for quantum chemistry and hybrid variational methods, evaluate quantum error-mitigation strategies and their limits, and contrast claimed performance with classical baselines in computational chemistry and machine learning. We conclude that near-term translational value is most substantial for quantum sensing and for device/physical platforms with established clinical evidence. In contrast, quantum computing remains principally hypothesis-generating until fault tolerance and reproducible advantage are established. Device-based modalities-including transcranial photobiomodulation for neuropsychiatric indications, focused ultrasound enabling CNS drug delivery, and home-supervised neuromodulation-are already reshaping therapeutic landscapes and clinical trial design. For drug discovery, the central requirement is not quantum novelty but validated decision impact, demonstrated under controlled benchmarks aligned with reproducibility expectations comparable to those evolving for AI/ML-driven methods in regulated contexts.

Filamentous supramolecular polymers provide a modular synthetic platform that can emulate various extracellular matrix biopolymers in their structure and function. However, hydrogels based on their entangled one-dimensional nanostructures are mechanically weak and challenged in replicating the properties of native tissues that surmount cyclic compressive loads. Inspired by the structural features of load-bearing tissues such as cartilage that consist of water-rich and interconnected biopolymer networks with distinct features, we explore the in situ photopolymerization of a secondary covalent network within a filamentous supramolecular material. The resulting connectable hybrid double network hydrogels show biomimetic cartilage-like mechanical properties under dynamic loads, such as hydrostatic pressure generation and stress relaxation. We further exploit the biocompatible dithiolane-ene light-mediated crosslinking reaction to culture human primary articular chondrocytes in 3D within the materials under cyclic compressive loads. Their loading leads to significantly increased production of cartilaginous matrix proteins, sulfated-glycosaminoglycans, fibronectin I and collagen II, particularly in the photocrosslinked domains. The enclosed&#xa0;hybrid supramolecular and covalent double network strategy with biocompatible light-mediated crosslinking paves the way to expand the application space of filamentous supramolecular materials in 3D cell culture, providing facile access to compressive mechanical features such as hydrostatic pressure and stress relaxation essential for load-bearing cell types.

The present review article explores the emerging evidence on the use of autologous platelet concentrates (APCs) as sustained release vehicles for a variety of drugs, including antibiotics, antifungals, antidiabetic drugs, exosomes, and vitamins for localized delivery approaches. The incorporation of such bioactive agents into APCs could enhance their therapeutic efficacy, support antimicrobial effects, wound healing and regeneration, and potentially reduce the need for systemic therapy. Although platelet-rich plasma (PRP) has also been studied as a carrier of bioactive agents, the rapid degranulation of platelets and lack of a cohesive fibrin network in PRP lead to a short-lived burst-type release profile. On the other hand, platelet-rich fibrin (PRF) has a three-dimensional scaffold of fibrin in which the growth factors and drug agents are retained, characteristics which make PRF-based APCs advantageous over PRP in the field of drug-delivery systems. However, a major challenge remains to be the absence of standardized drug-loaded APCs preparation protocols, with variations in centrifugation parameters, tube composition, and biomolecules' loading techniques, thereby influencing the APCs' structural integrity and release kinetics. The present review further highlights key findings on optimal loading strategies and the interactions between incorporated agents and the carrying APCs. It further highlights the level of current evidence for each of these drug-loaded APCs under investigation, their strength of recommendation, and possible knowledge gaps. Future work should focus on further developing and standardizing preparation protocols, advancing controlled release technologies, and validating efficacy through large scale clinical trials. Overall, bioactive drug-loaded APCs could represent a promising platform for targeted antimicrobial, antifungal, and regenerative therapies, bridging infection management with precision-guided tissue healing.

Peptide self-assembly represents a versatile and programmable strategy for generating functional nanomaterials with broad biomedical relevance. This review outlines the physicochemical principles governing assembly, highlighting cooperative noncovalent interactions, hydrogen bonding, &#x3c0;-&#x3c0; stacking, electrostatics and hydrophobic forces that drive hierarchical organisation into supramolecular structures. Key analytical techniques for characterising peptide assemblies and nanostructures are also summarised. The contribution of secondary structural motifs, particularly &#x3b1;-helices and &#x3b2;-sheets, is explored in relation to morphology, stability and biological function. &#x3b1;-Helical coiled-coil peptides form well-defined nanotubular architectures suitable for cargo encapsulation, whereas &#x3b2;-sheet peptides assemble into nanofibrillar networks and hydrogels with tuneable mechanical properties and sustained release profiles, as illustrated by systems such as RQDL10. Beyond peptides, protein and DNA self-assembly further expand the biomolecular design space. Protein-based systems leverage hydrophobic and Debye-H&#xfc;ckel electrostatic interactions to build hierarchical, functional architectures. DNA platforms enable programmable, stimulus-responsive assembly, including enzyme- and logic-controlled activation and hybridisation-driven formation of reversible higher-order nanostructures. Applications in drug delivery, tissue engineering and regenerative medicine are discussed alongside challenges such as limited in&#xa0;vivo stability, proteolytic degradation and scalability. Emerging approaches-including rational design, sequence engineering and advanced fabrication-aim to improve predictability and reproducibility, positioning biomolecular self-assembly as a unified platform for next-generation biomaterials.

Autonomic painful diabetic gastropathy is an uncommon and often overlooked cause of recurrent abdominal pain in individuals with diabetes. We describe a young man with type 1 diabetes who developed repeated episodes of severe epigastric pain and vomiting after a traumatic event, with all routine investigations failing to identify a structural, metabolic, or functional cause. His symptoms were resistant to standard therapies but showed rapid and sustained improvement with centrally acting sympatholytic treatment, and autonomic testing later supported underlying dysautonomia. This case highlights the importance of considering autonomic gastrointestinal involvement in unexplained, recurrent abdominal pain in diabetic patients, as early recognition can guide targeted therapy and help avoid unnecessary investigations and hospitalizations.

Little is known about cardiac troponin T (cTnT) release during transvenous lead extraction (TLE). The aim of the study was to identify factors influencing the intensity of cTnT release during TLE and to investigate whether the increase in cTnT levels after TLE has any prognostic significance for medium-term survival. Retrospective analysis of a TLE database. In 166 consecutive patients who underwent the TLE procedure, an elevated hs cTnT level > 0.014 &#xb5;g/l was present in almost 100%. The increase in troponin level 8 h after TLE (DcTnT8) was 900% of average and 400% of the median initial concentration. The factors most strongly associated with cTnT release during TLE were the age of the oldest extracted leads and the number of points on the Complex Indicator of Difficulty (CID) score. Additional procedural factors included the occurrence of technical problems, the need for second-line tools, hypotension > 1 min appearance, and traction on cardiac structures visible on transoesophageal echocardiography. Elevated cTnT levels are observed following nearly all TLE procedures; however, they do not impact the incidence of major complications, perioperative mortality, or long-term survival rates. Longer dwelling time of the extracted leads and the procedural complexity of TLE are the primary determinants of the magnitude of cardiac troponin release.

Spatial organization plays a critical role in shaping microbial community structure and function, influencing ecological stability, resource utilization, and evolutionary dynamics. Microbial interactions such as competition and cooperation are key drivers of spatial patterning, yet the environmental factors modulating these interactions remain incompletely understood. Here, we investigated how toxic substrates influence the spatial organization of synthetic microbial communities engaged in metabolic cross-feeding. Using a synthetic Pseudomonas stutzeri consortium consisting of the detoxifier and consumer that cooperatively degrade the toxic compound salicylate, we found that increasing the substrate concentration leads to a distinct shift in spatial organization: the detoxifier increasingly dominates the outer periphery of the expanding colony, forming a "detoxifier-first" succession pattern. Mathematical modeling further revealed that this spatial arrangement emerges from substrate toxicity, which selectively favors the detoxifier. Substrate toxicity inhibits consumer proliferation. However, the detoxifier, capable of degrading the substrate, locally reduces toxicity and creates a protective microenvironment that enables nearby consumer cells to survive and grow. In return, the consumer provides essential final products that support the growth and expansion of the detoxifier. This reciprocal interaction establishes a directional dynamic in which the detoxifier, favored by its detoxification capability, colonizes first, paving the way for subsequent consumer proliferation. Our findings demonstrate that substrate toxicity is a crucial environmental factor shaping spatial organization and diversity in microbial communities. This study highlights the importance of considering both metabolic interactions and substrate properties in understanding microbial ecology.

Inhaled therapy is critical for treating chronic airway diseases, yet the competency of respiratory nurses in providing guidance remains inconsistent. Few studies have explored the systemic competency disparities that are driven by a hierarchical distribution of healthcare resources. The aim of this study is to assess self-reported inhaled therapy guidance (ITG) competency among respiratory nurses across multiple-tier healthcare institutions, as well as to explore factors that affected such competency. A total of 962 respiratory nurses at multilevel hospitals in Jiangsu Province, Eastern China were investigated. We developed an ITG competency scale and evaluated its reliability and validity. Nurses rated themselves on a structured questionnaire that was designed to collect data on ITG competency in this population. The associated factors were determined using a descriptive statistical analysis, a correlation analysis, and a hierarchical multiple regression analysis. We followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist for cross-sectional studies. The ITG competency average score for respiratory nurses was (73.90&#x202f;&#xb1;&#x202f;9.42). Significant competency disparities were observed across all hospital tiers (p&#x202f;<&#x202f;0.001), with the primary hospitals demonstrating higher rates of poor and lower proportions of good ratings than secondary/tertiary hospitals. For the knowledge dimension, tertiary hospitals had the fewest poor ratings, while primary hospitals exhibited the highest prevalence of poor ratings, although the proportion of good skill ratings remained comparable across all tiers (p&#x202f;>&#x202f;0.05). Educational attainment, hospital grade, and training methodologies were associated with respiratory nurses' competency at ITG. The respiratory nurses exhibited moderate levels of ITG competency, with a notable gap between their knowledge and skills. This gap was more pronounced in primary hospitals, suggesting an association with institutional resource contexts. These results highlight the need for training strategies tailored to each hospital tier, as well as enhanced resource support from tertiary centers to primary care. This would help promote more standardized training programs and reduce competency disparities across hospital tiers.