Emergency department (ED) crowding is increasingly recognized as a global public health issue, while evidences from South-East Europe remain limited. The aim of this study was to characterize daily, annual, weekly, and monthly patterns of ED crowding in a high-volume tertiary hospital. We conducted a retrospective observational study of ED crowding in the largest ED in Serbia over 360 consecutive days (8,640 one-hour intervals). Crowding was measured hourly using the National Emergency Department Overcrowding Score (NEDOCS), derived from routinely collected data from health information system and expressed on a 0-200 scale, later grouped into six standard categories. Descriptive analyses assessed annual distribution, circadian and weekly variation, seasonal trends, and patient age structure. Between-group differences in NEDOCS scores were assessed using the Kruskal-Wallis test. Effect sizes were estimated using eta-squared (η²). The majority of patients in ED (43.14%) were older than 60. Almost 90% of patients (89.5%) waited up to 4 h for the first check up by doctor. The median annual NEDOCS score was 43.87 (IQR 51.92 ), corresponding to a "busy" operational state. Level 2 ("busy") occurred in 39.4% of hourly intervals and level 1 ("not busy") in 29.5%, while overcrowding (levels 4-6) was observed in 5.6% of intervals. Crowding was significantly higher during daytime than nighttime hours (p < 0.001), with a pronounced morning peak. Weekday crowding exceeded weekend levels, peaking on Tuesdays. Seasonal variation showed higher crowding during winter and transitional months. ED crowding demonstrates predictable temporal patterns that mirror broader population health dynamics. Routine high-frequency monitoring may inform strategic staffing, adaptive capacity planning, and governance mechanisms aimed at strengthening emergency care performance and system resilience.
During tumor progression, cells within the solid tumor core experience substantial mechanical crowding (solid stress). Although HDAC6 is a key regulator of cell survival and motility, its spatial regulation under physical crowding remains poorly understood. Here, using HeLa cell monolayers as a model, we show that mechanical crowding promotes the redistribution of HDAC6 from the nucleus to the cytoplasm, whereas fluid shear stress induces the opposite response and favors nuclear accumulation. Expanded immunofluorescence analyses across multiple fields, together with nuclear/cytoplasmic fractionation, support this crowding-associated shift in HDAC6 localization. Transcriptomic profiling further revealed broad remodeling under crowded conditions, including suppression of translation- and cytoskeleton-related programs and enrichment of a candidate export-related signature involving XPO1. Biochemical validation confirmed XPO1 protein expression under crowded conditions, and pharmacological inhibition of XPO1 attenuated the crowding-associated redistribution of HDAC6, supporting a functional role for XPO1 activity in this process. In addition, crowding was accompanied by the upregulation of invasion-associated markers, including MMP9 and Vimentin, suggesting the emergence of a pro-invasive transcriptional state. Together, these findings identify HDAC6 nucleo-cytoplasmic redistribution as a mechanically responsive event under crowding and support the involvement of XPO1 in this adaptation.
The intracellular environment is densely populated with macromolecules, creating crowded conditions. Whether in vitro environments or synthetic crowders like polyethylene glycol (PEG) accurately capture the complexity of RNA interactions in vivo remains unclear. Using all-atom molecular dynamics simulations, we investigated the HIV-1 TAR RNA hairpin in dilute, PEG-crowded, and realistic protein-crowded solutions. We found that PEG primarily exerts excluded-volume effects, maintaining RNA hydration and Na$^{+}$ ion condensation similar to dilute conditions. In contrast, protein crowders significantly altered RNA electrostatics, reducing Na$^{+}$ condensation by nearly 60%, displacing surface hydration water, and forming chemically specific contacts dominated by positively charged residues, notably arginine, and lysine. These interactions led to local RNA expansion and reshaped its conformational landscape without disrupting the global fold. Moreover, protein crowding dramatically slowed RNA translational and rotational dynamics, as well as local water and ion mobility, whereas these effects were minimal with PEG. Our findings emphasize that crowder identity critically determines RNA behavior and challenge the use of PEG as a universal model for intracellular conditions, providing mechanistic predictions for RNA studies in biologically relevant environments.
Robots increasingly share spaces with people, supporting delivery services and mobility for the aging populations, yet their ability to share space comfortably lacks understanding and benchmarks for designers and policy-makers. We compared human-robot (HRI) and human-human (HHI) interactions across four real-world crowd datasets spanning Europe, North America, and Asia, using a unified pipeline to detect interactions, stratify by crowd density, and model pedestrian behavior. Local motion patterns (speed, acceleration, and jerk) remained closely matched between HRI and HHI across all densities. In contrast, proxemics diverged, with effects that grew approximately linearly with robot speed and weakened under higher crowding: In the dataset with the faster navigating robot, pedestrians maintained about 0.23 meters more clearance around the robot than around other pedestrians under less crowded conditions and about 0.05 meters more under more crowded conditions, while in the dataset with the predominantly stationary robot, the corresponding differences were small and inconsistent across crowding levels. The main conclusions were robust to parameter variations and remained stable across a broad range of motion-processing and interaction-labeling settings. Our findings provide density- and speed-aware benchmarks for proxemics in social robot navigation and empirically grounded targets for design, evaluation, and modeling across robotics and urban mobility.
Intracellular crowding, a crucial biophysical parameter linked to tumor progression, can serve as a potential marker for phenotyping. Existing sensors rely on transfection, which disrupts the intracellular microenvironment and reduces accuracy. Herein, we design a DNA biosensor with a DNA tetrahedron scaffold and a flexible ssDNA-FRET element, achieving near-physiological crowding sensing via a chemical-driven soft-matter response. Cy3/Cy5-conjugated ssDNA aggregates more tightly with increased crowding, shortening the interfluorophore distance to trigger quantifiable FRET signals, validating the structure-dependent correlation between flexible soft-matter agglomeration and crowding degree via simulations, PEG experiments, and FRET characterization. The tetrahedron enables transfection-agent-free delivery, avoiding reagent drawbacks. We achieved multivariate statistical discrimination of six cell lines based on osmotic-stress-induced FRET fingerprints via osmotic pressure-induced crowding variations, confirming cellular crowding as a hallmark of functional heterogeneity. This work advances soft matter-based biosensing and tumor biophysics.
Intraorbital space-occupying lesions impair visual function, yet whether this stems primarily from optic nerve compression, elongation or orbital apex crowding remains unclear. This study investigated the differential impact of these mechanical factors on visual acuity (VA) and visual field (VF) in patients with intraorbital cavernous haemangiomas. This retrospective cohort study analysed 130 patients with unilateral intraorbital cavernous haemangiomas. Key imaging parameters were measured from CT/MRI and categorised into optic nerve elongation, compression (eg, optic-nerve aspect ratio (ONAR)) and orbital crowding (eg, tumour-to-orbit (TO) ratio, tumour mid-position (TMP)). Univariate and multivariate linear regression models were used to correlate these metrics with visual outcomes. Regression analysis revealed two distinct injury mechanisms. Direct compression, best quantified by ONAR, was the strongest predictor for VA decline (R2=0.15, p<0.0001) but correlated weakly with VF loss (R2=0.09, p=0.0015). Conversely, orbital apex crowding (TO-ratio and TMP) correlated more strongly with VF defects (R2=0.19 and R2=0.20, p<0.0001) than with VA. Optic nerve elongation showed no significant correlation with visual dysfunction. The final multivariate model explained 17.68% of the variance in VA and 36.48% in VF. Visual loss from orbital tumours involves two mechanical pathways: direct compression preferentially impairs central vision (VA), while orbital apex crowding predominantly affects peripheral vision (VF). Imaging metrics like ONAR and TO-ratio can effectively quantify these mechanisms. They may serve as supplementary reference indicators for evaluating visual risk and informing clinical follow-up and surgical consultation, with ONAR indicating risk to central vision and TO-ratio signalling impending field loss.
Public debt is widely assumed to constrain social spending by shrinking fiscal space, yet empirical evidence from advanced economies shows little consistent association between debt levels and public health expenditure. This study revisits the debt-health nexus by distinguishing between two analytically separate fiscal constraints: long-term solvency, captured by public debt stock, and short-term liquidity, captured by debt service obligations. Using an unbalanced panel of 26 OECD European countries from 2000 to 2022, the analysis combines data from the World Bank, the International Monetary Fund, and the OECD and employs a dynamic panel framework estimated with bias-corrected least squares dummy variable methods. The empirical strategy explicitly separates stock and flow effects, controls for total government expenditure to identify compositional crowding-out, and tests whether fiscal constraints vary across macroeconomic conditions. The results indicate that public debt stock does not exert a robust negative effect on health expenditure, suggesting a form of "stock neutrality" in mature welfare states. By contrast, interest payments are associated with significantly lower public health expenditure, even conditional on total government expenditure, indicating compositional crowding-out. Moreover, this liquidity-based crowding-out is shaped by macro-fiscal context, with its strength varying across periods of fiscal stress and more stable economic conditions. These findings highlight the importance of debt-service costs, rather than debt accumulation per se, as a key fiscal mechanism shaping health system financing in advanced economies.
Mobile robots operating in human-populated environments must navigate complex, multi-room spaces while ensuring safety, i.e., generating collision-free motion. In this study, we present a sensor-based model predictive control (MPC) scheme designed for safe crowd navigation in such non-convex environments. The proposed framework decomposes the free space into a set of overlapping convex regions to construct a topological graph, enabling a high-level planner to compute optimal sequences of traversable areas. To effectively perceive the crowd, the system employs a robust perception pipeline that fuses 2D LiDAR data with semantic information from an RGB-D camera, utilizing Kalman filters (KFs) to estimate and predict human motion. These predictions are integrated into an MPC controller which generates robot commands by enforcing safety through discrete-time control barrier function (DT-CBF), ensuring that the robot avoids collisions while remaining within navigable regions. The approach is validated through high-fidelity simulations and real-world experiments using the TIAGo mobile manipulator. The results demonstrate that integrating vision-based semantic data with geometric constraints significantly improves collision avoidance and success rates in cluttered, multi-room scenarios.
Collagen self-assembly underlies extracellular matrix architecture, yet how gravitational forces influence collagen fibrillogenesis remains poorly understood. Here, we investigated simulated microgravity as a physical regulator of type I collagen hydrogel formation using a random positioning machine. Rat-tail and bovine type I collagen were assembled under graded simulated gravity conditions and characterized by real-time turbidity monitoring, bright-field and confocal microscopy, Fourier transform infrared spectroscopy, circular dichroism spectroscopy, and fibroblast culture. Simulated microgravity delayed collagen nucleation and prolonged overall assembly while promoting the formation of thicker, more spatially heterogeneous fibril networks in both collagen sources. Despite these architectural changes, post-exposure Fourier transform infrared and circular dichroism analyses indicated preservation of the native triple-helical secondary structure, indicating that gravitational unloading primarily perturbs higher-order assembly rather than molecular integrity. Macromolecular crowding with Ficoll 400 partially restored network uniformity and reduced microgravity-induced fibril thickening, while attenuating architecture-associated fibroblast contractile activation. Together, these findings establish a mechanistic link between gravitational unloading, fibrillogenesis kinetics, and collagen network architecture. This work identifies gravity as a tunable physical parameter for engineering collagen hydrogels and highlights microgravity-enabled control of extracellular matrix organization for biomaterials design and space-based biofabrication.
Microfluidic devices enable the study of cellular properties in a highly controlled environment while allowing close observation. One important aspect of a plant cell's environment is the influence of neighboring cells on cell growth through chemical signals and mechanical forces. However, while the use of microfluidics in plant cell biology has expanded in recent years, very few systems provide cell-cell contact together with long-term growth and imaging. Here, we develop a microfluidic device that uses arrays of cylindrical cups to gently capture and confine multiple protoplasts into stable aggregates, generating a constrained microenvironment with cell-to-cell contact. The device addresses a key challenge wherein aggregating cells can create hypoxic, media-starved environments that rapidly lead to cell death. The porous micro-post design supported sustained media flux through confined aggregates, reducing limitations typically associated with dense cell clustering. The platform maintained sterile culture conditions and enabled convenient media switching, as demonstrated by hormone treatment and salt-stress assays. Protoplasts from Arabidopsis thaliana and Zea mays remained viable for more than two weeks. Over this period, cells showed growth, cell wall formation, and cell divisions, with divisions occurring significantly more frequently in crowded aggregates than in isolated cells. This aggregates-on-chip platform provides a controlled and live-imaging system for studying how cell-cell contact and microenvironmental cues influence plant protoplast behavior. By integrating physical confinement, continuous perfusion, and chemical perturbation, the device offers a technical advance for long-term studies of plant cell growth, regeneration, division, and stress responses.
Clopidogrel is widely used after structural heart interventions, but symptomatic intraocular pressure (IOP) abnormalities without clinically evident hemorrhage are rarely reported. We describe a 52-year-old woman who developed recurrent ocular discomfort, eye pain, and blurred vision after percutaneous patent foramen ovale closure followed by clopidogrel-containing antiplatelet therapy. Baseline pre-exposure assessment showed ocular hypertension with angle crowding features but no definite glaucomatous structural or functional damage. Symptoms improved after clopidogrel withdrawal and recurred after re-administration. During recurrent symptomatic exposure, 24-h IOP monitoring showed marked peak elevation and diurnal fluctuation in both eyes. Baseline pre-exposure IOP measurements were available, but baseline 24-h IOP monitoring was not performed; therefore, worsening relative to the patient's baseline diurnal pattern could not be confirmed. Formal gonioscopy and symptomatic-phase angle reassessment were unavailable, and intermittent angle closure could not be excluded. This case represents a dechallenge-rechallenge-supported temporal association and hypothesis-generating pharmacovigilance signal rather than definitive evidence of a clopidogrel-induced effect.
Deep learning has shown promising performance in cervical cytology; however, many studies have relied on presegmented single-cell images rather than the more complex morphologic patterns encountered in routine practice. Here, scattered cells were defined as isolated or dissociated, nonoverlapping single cells. This study quantified the performance loss when artificial intelligence (AI) models trained on these cells were applied to hyperchromatic crowded cell groups (HCGs). Binary convolutional neural network models were developed to differentiate between negative for intraepithelial lesion or malignancy cases and high-grade squamous intraepithelial lesion cases via a scattered cell data set composed of institutional and public liquid-based cytology images. The scattered cell data set comprised 101 cases, with 1062 images; the independent HCG data set comprised 48 cases, with 330 images. ResNet-50, ResNeXt-50, ConvNeXt-Tiny, EfficientNet-B3, VGG-19, and GoogLeNet were trained on scattered cell images, and then directly applied to HCGs without retraining or threshold recalibration. All models showed high performance on the scattered cell data set, with the area under the receiver operating characteristic curve (AUC) ranging from 0.950 to 0.996. When directly applied to HCGs, performance declined across all architectures, with the AUC ranging from 0.385 to 0.683. ConvNeXt-Tiny showed the highest AUC on HCGs (0.683); however, this remained substantially lower than its performance on scattered cells (0.996). For all architectures, the AUC was significantly lower on HCGs than on the scattered cell data set. Binary AI models trained on scattered cell images achieved excellent discrimination in the original setting but their performance was not preserved when directly applied to HCGs. These findings underscore the need for direct validation and HCG-aware model design in cervical cytology AI.
To explore patients' fundamental care needs, to which extent they are met and to assess how the care activities of Registered Nurses and assistant nurses are accomplished. A further aim is to investigate their associations with contextual factors in an emergency department setting. Quantitative exploratory observational study with data collected through structured observations. Seventy-five patients, 30 registered nurses, and 20 assistant nurses were recruited from one emergency department. Structured observation protocols, spot checks, and follow-up dialogues were used. Descriptive and analytical statistics were calculated. A total of 812 fundamental care needs were observed: physical (45%), psychosocial (38%), and relational (14%). The prevalence of missed nursing care was 20% and was more prevalent among older patients, those receiving care in shared spaces, and during crowding. In total, 3797 care activities were observed. Medical/technical activities were implemented at a higher rate than integration of care activities; unlike the latter, higher rates were significantly associated with crowding, the surgical section, and registered nurses compared to assistant nurses. Missed nursing care was more prevalent among older patients and those in shared spaces or during crowding. The increased rate of medical/technical care activities was associated with crowding, whereas the integration of care activities remained unchanged. Fast-track solutions robust to crowding could reduce missed nursing care among older patients. Staff and management should critically assess physical layout in relation to crowding and missed nursing care. Crowding is a system-level phenomenon representing a significant driver of missed nursing care in the emergency department, and responsibility for addressing this decline in care quality must be acknowledged at system and policy levels. This study provides evidence of how organizational conditions shape nursing care delivery in emergency departments and will inform interventions to improve care quality and safety. None.
Outbreaks of acute infectious conjunctivitis can spread rapidly in overcrowded communities and healthcare settings. Sudan's armed conflict has increased displacement, crowding, water insecurity, and barriers to healthcare access. A facility- and camp-based cross-sectional study included 417 consecutive patients with acute conjunctivitis or keratoconjunctivitis who presented to participating ophthalmic services and internally displaced persons' settings in Kassala State, Sudan, from 15 August 2024 to 15 December 2024. Demographic, environmental, behavioural, clinical, treatment, and follow-up data were collected using a structured form. Diagnosis was clinical; laboratory viral typing was not performed. Descriptive statistics, Spearman correlations, Mann-Whitney U tests, Kruskal-Wallis tests, and multivariable regression models were used as appropriate. Among 417 patients, 231 (55.4%) were female, and 353 (84.7%) lived in urban areas. Inadequate water/sanitation access was recorded in 125 (30.0%), a dusty environment in 224 (53.7%), a dirty environment in 317 (76.0%), a crowded environment in 223 (53.5%), and contact with a symptomatic person in 353 (84.7%). The most frequent symptoms were itching or burning (94.2%), redness (89.4%), foreign-body sensation (81.1%), eye pain (63.1%), and lid oedema (60.0%). The most frequent signs were conjunctival injection (38.8%), subconjunctival injection (35.7%), follicles/papillae (31.2%), periauricular lymphadenopathy (18.0%), punctate keratitis (11.0%), and membranes (3.8%). Clinicians recorded suspected bacterial superinfection complicating viral keratoconjunctivitis (43.9%), suspected adenoviral keratoconjunctivitis (29.3%), and suspected bacterial keratoconjunctivitis (21.3%) as the most frequent categories. Recovery data were available for 238/417 patients (57.1%); in this sub-cohort, complete recovery was associated with urban residence (OR 3.51; 95% CI 1.47-8.42), inadequate water/sanitation access (OR 9.87; 95% CI 2.46-39.62), a crowded environment (OR 2.41; 95% CI 1.12-5.14), and a lower symptom score (OR 0.78; 95% CI 0.63-0.97). All estimates are observational and are not interpreted as causal. This outbreak occurred in a war-affected setting characterized by displacement, overcrowding, and limited access to water and sanitation. The clinical pattern is consistent with acute infectious keratoconjunctivitis, but the lack of laboratory testing prevents definitive classification as adenoviral epidemic keratoconjunctivitis or as enterovirus- or coxsackievirus-associated acute hemorrhagic conjunctivitis. Future outbreak response in similar settings should include laboratory confirmation and viral typing, access to clean water, hand hygiene, separation of cases in eye-care services, and avoidance of shared personal items.
Colloidal science provides predictive frameworks for particle stability and interactions, yet applying these classical models to biological systems requires extending them to account for the complex and dynamic conditions present in physiological environments. Theories such as Derjaguin-Landau-Verwey-Overbeek (DLVO) were developed to describe interactions in carefully defined colloidal systems. When applied to biological environments, additional factors, including soft interfaces, evolving protein adsorption layers, and macromolecular crowding, must be incorporated to capture the full interaction landscape. Consequently, nanoparticles designed under traditional assumptions often behave unpredictably in vivo. This Perspective reframes colloidal science through a biological lens, emphasizing that particle behavior in physiological media is governed by protein corona formation and interactions with soft, charged, and crowded interfaces such as tumors and mucus. Integrating these disciplines requires integrating colloids and biomedical engineering, standardizing nanoparticle characterization techniques in biological media, and prioritizing interface-driven research to enable predictive, clinically relevant nanomaterial design.
Urban areas often act as early epicentres of pandemics, yet transmission dynamics across regions with different demographic profiles remains poorly understood. We aimed to characterise COVID-19 transmission in Norway and assess how it interacted with infection control measures across urban and rural settings. We analysed daily COVID-19 cases across three pandemic waves (Alpha, Delta, Omicron). For local trends, 36 sites in the Greater Oslo Region were grouped by infection trajectories using group-based trajectory modelling. For national trends, we examined the cities of Oslo, Bergen, Trondheim, Stavanger, Tromsø, and Akershus county. Infection trends were analysed using linear mixed models and lagged regression analyses and related to demographic characteristics. In the Greater Oslo Region, three distinct site groups-high, moderate, and low infection-were identified. The high infection group had the highest population density, largest proportion of crowded housing and immigrant population and preceded the moderate and low groups by 5-13 days during the Alpha wave. Nationally, Oslo's infection rates peaked 11-24 days before other cities during the Alpha wave, with shorter lags during the Delta and Omicron waves. Despite similar control measures, infection rates differed substantially, with the high infection group and Oslo city consistently bearing the greatest burden. Densely populated areas with crowded housing act as early warning signals, with infection growth preceding that in other areas by days to weeks. Systematic monitoring of such high-burden urban areas could provide valuable lead time for policymakers and support more targeted, timely responses in future pandemics.
Contralateral gate cannulation of the distal bifurcated component during thoracoabdominal branched endovascular repair can be challenging in patients with previous endovascular aneurysm repair (EVAR) because multiple indwelling and newly implanted stent graft components may crowd the distal aortic field and obscure wire behavior. We describe a trilumen catheter-assisted contralateral gate precannulation (TRIP) technique for distal bifurcated component during thoracoabdominal branched endovascular repair. A 81-year-old man presented 7 years after infrarenal EVAR with a type IA endoleak from a previous suprarenal fixation stent graft. Because of his operative risk, off the shelf endovascular thoracoabdominal branched endovascular repair was selected. After establishment of through-and-through access, placement of the aortic component, and completion of visceral branch stenting, attention was turned to distal bifurcated component deployment using the TRIP technique. Before deployment of the distal bifurcated component, a trilumen catheter was advanced from the upper-extremity sheath to the ipsilateral femoral sheath over the existing through-and-through wire. A 0.014-inch wire was introduced through the trilumen catheter and passed through the removable guidewire tube of the distal bifurcated component to precannulate the contralateral gate. After deployment of the distal bifurcated component, a 7F, 75-cm-long sheath was advanced over the precannulated wire through the contralateral gate. A 0.035-inch buddy wire was then introduced, snared from the contralateral femoral access, and exchanged to establish secure through-and-through access for contralateral limb delivery. The TRIP technique enabled confident contralateral gate access despite a crowded distal aortic configuration and may be useful during thoracoabdominal branched endovascular repair for type IA endoleak after previous EVAR when conventional gate cannulation is expected to be difficult.
Emergency department (ED) crowding and inpatient boarding delay care and increase the risk of patients leaving without being seen (LWBS). We implemented a combined physician waterfall schedule (PWS) and modified physician-in-triage (PIT) model to expand front-end capacity, accelerate early physician assessment, and reduce LWBS. We conducted a single-center, retrospective pre-post study of adult ED encounters (≥20 years) over consecutive 12-month pre- and post-intervention periods (January 3, 2023-December 31, 2024). The intervention paired a staggered PWS (increasing attending coverage from 54 to 62 h/day) with a modified PIT model requiring full initial evaluation and clinical ownership through disposition. We used statistical process control (P-chart) to assess monthly LWBS trends and logistic regression with inverse probability of treatment weighting (IPTW) plus covariate adjustment to compare the primary outcome between periods; univariable tests were used for secondary outcomes (throughput, ED returns, and patient experience) and balancing measures (left-before-treatment-complete, ED return within 72-h resulting in hospital admission). Among 79,898 adult encounters, LWBS decreased from 6.5% to 4.7%. IPTW analysis showed lower odds of LWBS (OR 0.71; 95% CI 0.66-0.76), corresponding to a 28.1% relative reduction and exceeding the 25% target. ED return within 72 h decreased (5.5% to 5.1%, p = 0.004), as did returns with admission (0.8% to 0.7%, p = 0.027). Other secondary outcomes were largely unchanged. Improvements occurred despite increased boarding. A combined PWS plus modified PIT model was associated with reduced LWBS while maintaining safety and patient experience, offering a pragmatic strategy to mitigate ED crowding.
The size of the nucleus scales with cell size, suggesting a universal scaling rule. Yet the biophysical determinants of nuclear size and the significance and consequences of altered nuclear-to-cell (N/C) ratios, which are observed across diverse pathological states and cell-fate transitions, remain poorly understood. Recent theoretical models propose that nuclear size arises from a balance of colloid osmotic pressures generated by macromolecules in the nucleoplasm and cytoplasm. Here we demonstrate that altering this osmotic balance through massive overexpression of an exogenous protein targeted to either the nucleoplasm or cytoplasm produces predictable changes in the N/C ratio in S. pombe. These quantitative perturbations show that nuclear size is set primarily by the number of proteins in the nucleus and cytoplasm, providing strong support for a pure osmotic pressure mechanism. Furthermore, cells with altered N/C ratios display tunable changes in nucleoplasmic crowding, nuclear condensate formation, nucleolar scaling and heterochromatin organization, establishing a causal link between nuclear size and gene regulatory processes. These findings reveal how cells exploit osmotic forces to set organelle dimensions, with broad implications for understanding how nuclear size shapes gene expression and cell identity in health and disease.
Boarding occurs when a patient is admitted to the hospital but remains in the emergency department until an inpatient bed is available. No previous evidence establishes a relationship between hospital nurse staffing and emergency department boarding times. This study fills this gap. This was a cross-sectional study of 335 hospitals in Florida, New Jersey, and Pennsylvania. Using staffing data from 1367 medical-surgical nurses in the RN4CAST-US 2016 survey, hospitals were categorized as having worse (≥5:1) than better (<5:1) patient-to-nurse staffing ratios. The American Hospital Association provided data on hospital characteristics. Hospital emergency department patient boarding times were derived from the Centers for Medicare and Medicaid Services Compare timely and effective care files. Hospital-level linear regression models using a doubly robust propensity score weighting approach were used to evaluate the relationship between nurse staffing and boarding times. Most study hospitals had worse (n = 286) than better (n = 49) patient-to-nurse staffing ratios. Mean boarding times were longer in the worse-staffed hospitals than the better-staffed hospitals (128 vs 108 minutes; P = .01). These findings persisted in the propensity score weighted models (127 vs 108 minutes; P = .03) and the doubly robust models (128 vs 108 minutes; P = .009). This study establishes a baseline understanding of the relationship between hospital nurse staffing levels and patient boarding times, providing a foundation for evaluating changes over time. Safe nurse staffing levels are a modifiable lever to reduce emergency department crowding through decreasing patient boarding times.