Optics Letters

In previous studies by the author on binocular vision with the asymmetric eye (AE), which models a healthy human eye with misaligned optical components, the results were primarily presented in the Rodrigues vector (RV) framework and supported by simulations and 3D visualizations in GeoGebras dynamic geometry environment. In this paper, the novel geometric kinematics of the human eye, i.e., the eye with misaligned optics, and simplified assumptions about eye rotations (the eyes translational movements are disregarded) are developed within the framework of rigid-body rotations. Despite the eyes misaligned optical components (all eyes axes differ), the geometric formulation, which can only be approximated, yields excellent accuracy as demonstrated by simulations. The originality of the analysis lies in a precise geometric decomposition of the eyes posture changes into torsion-free (geodesic) and torsional (non-geodesic) rotations. This decomposition is extended to the corresponding decomposition of the angular velocity. A novel derivation of the eyes angular velocity from the RV formulation of the eye kinematics is proposed.

The design of the classical fluorescence microscope has undergone few changes since the 1970s-1980s, when Ploemopak modules with filter cubes became widespread. Most of these changes have been in the replacement of mercury and xenon lamps with LED illuminators in the 2010s. However, this does not mean that this stable design cannot be improved upon. New method: The implementation of a vibrating optical fiber, positioned using a micromanipulator and connected to any suitable type of laser, enables a full spectrum of fluorescence research. This work presents an advanced version of the Ellis concept, in which light is delivered directly onto the sample, rather than into the filter cube (technical novelty).To confirm the functionality of the microscope, vibrational slices of mouse brain stained with three fluorescent markers (B3-PPC, DiI and DiD) covering most of the visible spectrum were examined. The fiber-optic illumination system eliminates the need for bulky and obsolete high-voltage plasma arc lamp units without compromising image quality (confirmed by the USAF 1951 test and SDNR assessment on fluorescent beads). Furthermore, the optical fiber mounted on manipulators is convenient and easy to integrate, for example, into stereomicroscopes for scanning large brain tissue samples.

Light-sheet microscopy (LSM) has revolutionized bioimaging by delivering high-contrast volumetric resolution with minimal photodamage. Spatial wavefront shaping, used to gen{-}erate lattice and Airy light-sheets, has been particularly effective in advancing LSM be{-}yond the Rayleigh limit. Despite its broad adoption, most LSM implementations rely on rigid dual-objective geometries that complicate sample handling and impose a trade-off between imaging field of view (FoV) and axial resolution. Here, we introduce space-time light-sheet microscopy (ST-LSM), a single-objective strategy that exploits space-time (ST) correlations for the first time. ST-LSM goes beyond separate spatial or temporal modulation to jointly modulate the spatiotemporal spectral structure of a pulse. This uniquely enabled light-sheets with wavelength-scale thickness over millimeter-scale dis{-}tances. When compared to state-of-the-art approaches, ST-LSM eliminates the dual-objective constraint, expands the sample-accessible volume by 25x, and increases the FoV by 10x without sacrificing sectioning resolution. We demonstrate the versatility of ST-LSM by using a single setup to image specimens across four orders of magnitude in size, from whole roots and developing embryos, down to mammalian cells with sub-cellular axial resolution. These results position ST-LSM as an accessible and high-performance optical microscopy platform at a variety of biological scales, by translating space-time wave-packet physics into a practical imaging modality.

Three-photon microscopy (3PM) has enabled the optical access of neurons [~]500-1500{micro}m below the brain surface but has been limited to slow imaging frame rates or small imaged area due to the combination of a nonlinear peak power requirement and the need to limit average power below the thermal damage threshold. High sensitivity to laser fluctuation and inherently dim signals introduce additional challenges and add error. Combined with the effects of brain motion in behaving animals, 3P imaging of neuronal activity during animal behavior has remained practically unachievable. Herein, we systematically address these limitations by carefully balancing scanning speed with power requirements, using a deeply cooled silicon photomultiplier detector with Bayesian statistics-based processing to reduce excess noise, and through spatiotemporal shaping of excitation pulses. Our improvements enable rapid (20-30Hz) imaging of calcium activity in the dorsal hippocampal dentate gyrus of behaving mice, allowing the identification of spatially tuned neurons and the recapitulation of established functional properties across different cell types in this brain region. PRED-3P imaging provides a new approach to functional characterization of cells deep in the brain that were previously inaccessible to two-photon imaging.

End-stage liver disease (ESLD) is one of the leading causes of death worldwide. Currently, the only curative option for patients with ESLD is liver transplantation. However, the demand for donor livers far exceeds the available supply, partly because many potentially viable livers are discarded following biopsy evaluation. While biopsy is the gold standard for assessing liver histological features related to graft quality and transplant suitability, it often leads to high discard rates due to its susceptibility to sampling errors and limited spatial coverage. Besides, biopsy is invasive, time-consuming, and unavailable in clinical facilities with limited resources. Here, we present an AI-assisted photoacoustic/ultrasound (PA/US) imaging framework for quantitative assessment of human donor liver graft quality and transplant suitablity at the whole-organ scale. With multimodal volumetric PA/US images as the input, our deep-learning (DL) model accurately predicted the risk level of fibrosis and steatosis, which indicate the graft quality and transplant suitability, when comparing with true pathological scores. DL also identified the imaging modes (PAI wavelength and B-mode USI) that correlated the most with prediction accuracy, without relying on ill-posed spectral unmixing. Our method was evaluated in six discarded human donor livers comprising sixty spatially matched regions of interest. Our study will pave the way for a new standard of care in organ graft quality and transplant suitability that is fast, noninvasive, and spatially thorough to prevent unnecessary organ discards in liver transplantation.

Saccadic eye movements are established biomarkers in neuroscience and clinical neurology, where video-oculography (VOG) remains the gold standard. However, VOG's high cost, bulky equipment, and poor portability restrict its clinical utility. Electrooculography (EOG) offers a promising alternative by detecting cornea-retinal potential changes during eye movements. To enable quantitative saccadic analysis using EOG as a VOG alternative, this study develops and validates a mathematical transformation model converting EOG data into VOG-equivalent values. A prospective observational study was conducted on 4 healthy adults without neurological or sleep disorders. Horizontal saccades were recorded simultaneously using EOG and VOG during controlled gaze shifts. EOG peak saccadic velocity was derived from voltage change rate, whereas VOG was calculated from angular displacement over time. A derivation dataset of fixed horizontal saccades ({+/-}20{degrees}) formulated the transformation model, achieving a strong correlation coefficient (r = 0.95 rightward, r = 0.93 leftward, p < 0.0001). Multiple filter settings were evaluated, and 0.3 Hz high-pass and 35 Hz low-pass filtering were identified as optimal. The fixed horizontal saccades derived model was applied to a validation dataset of random horizontal saccades, confirming robustness across saccades without significant differences from VOG measurements. These findings establish EOG's feasibility for quantitative analysis of horizontal saccades and provide a validated transformation model. By systematically optimizing filtering parameters, this approach enables EOG as a cost-effective VOG alternative while maintaining high-precision measurement accuracy.

PurposeThe optic nerve head (ONH) is a central feature of the retina, affected in many human ocular pathologies, yet it has remained underexplored in most mouse models of disease. We hypothesize that the analysis of the ONH can yield valuable insight into the phenotype of retinal diseases and that pathological changes can be detected using state-of-the-art optical coherence tomography (OCT). MethodsFour mouse models - the 5xFAD, PS19 and APP/PS1 models of Alzheimers disease (AD) as well as the SOD1 knockout mouse model - were imaged using a polarization-sensitive OCT system to investigate potential disease related changes of the ONH. 5xFAD and SOD1 animals were investigated longitudinally to study disease progression. Additionally, aging effects in wild type mice were studied. ResultsTwo different analysis methods for the segmentation of the ONH were implemented and evaluated. Longitudinal changes to the ONH in 5xFAD animals were observed, specifically an increase of ONH volume from 3 to 5 months of age followed by a strong decrease until 9 months of age. Significant differences between transgenic (tg) and non-transgenic (ntg) animals, as well as sex dependent distinctions were found. Also, for the APP/PS1 model disease related differences between ntg and tg APP/PS1 were significant. ConclusionsWe demonstrated a simple segmentation of the ONH structure based on OCT intensity images and show its potential as a preclinical biomarker in amyloid mouse models of AD.

Computer vision and deep learning techniques, including convolutional neural networks (CNNs) and transformers, have increased the performance of medical image classification systems. However, training deep learning models using medical images is a challenging task that necessitates a substantial amount of annotated data. In this paper, we implement data augmentation strategies to tackle dataset imbalance in the VinDr-SpineXR dataset, which has a lower number of spine abnormality X-ray images compared to normal spine X-ray images. Geometric transformations and synthetic image generation using Generative Adversarial Networks are explored and applied to the abnormal classes of the dataset, and classifier performance is validated using VGG-16 and InceptionNet to identify the most effective augmentation technique. Additionally, we introduce a hybrid augmentation technique that addresses class imbalance, reduces computational overhead relative to a GAN-only approach, and achieves ~99% validation accuracy with both classifiers across all three case studies. Keywords: Data augmentation, Generative Adversarial Network, VGG-16, InceptionNet, Class imbalance, Computer vision, Spine X-ray, Radiology.

Neuronal migration is a vital process that positions billions of neurons to create a functional brain. To navigate the constrained microenvironments within the cortex, precise control over the nuclear mechanics in migrating neurons is indispensable. Here, we show that Lamin B1 (LB1) regulates neuronal migration by modulating nuclear deformability. Excess LB1 in neurons halted migration without altering laminar identity or overall gene expressions in vivo, while in vitro, it elevated nuclear stiffness and impaired neuronal motility in confined spaces. Moreover, mispositioned neurons resulted in electrophysiological defects in the brain. Computational modeling predicted a temporal relationship between nuclear deformation and enhanced migration velocity, which was validated experimentally through live imaging. Notably, cerebral organoid assays using iPS cells established from patients with LMNB1 duplication exhibited impaired neuronal migration in a human model. Collectively, these findings demonstrate that LB1 is a critical regulator of nuclear mechanics, ensuring the accurate spatiotemporal positioning of neurons.

Understanding how cells migrate through confined environments is crucial for elucidating fundamental biological processes, including cancer invasion, immune surveillance, and tissue morphogenesis. The nucleus, as the largest and stiffest cellular organelle, often limits cellular deformability, making it a key factor in migration through narrow pores or highly constrained spaces. In this work, we introduce a geometric surface partial differential equation (GS-PDE) model in which the cell plasma membrane and nuclear envelope are described as evolving energetic closed surfaces governed by force-balance equations. We replicate the results of a biophysical experiment, where a microfluidic device is used to impose compressive stresses on cells by driving them through narrow microchannels under a controlled pressure gradient. The model is validated by reproducing cell entry into the microchannels. A parametric sensitivity analysis highlights the dominant influence of specific parameters, whose accurate estimation is essential for faithfully capturing the experimental setup. We found that surface tension and confinement geometry emerge as key determinants of translocation efficiency. Although tailored to this specific setup for validation purposes, the framework is sufficiently general to be applied to a broad range of cell mechanics scenarios, providing a robust and flexible tool for investigating the interplay between cell mechanics and confinement. It also offers a solid foundation for future extensions integrating more complex biochemical processes such as active confined migration.

Standard in vitro antimicrobial susceptibility testing (AST) using Mueller-Hinton broth (MHB) does not reflect infection-site conditions, and its results often do not correlate with therapeutic outcomes. Here, we compared the antibiotic susceptibility of methicillin-resistant Staphylococcus aureus (MRSA), a common chronic wound pathogen, in simulated wound fluid (SWF) resembling wound exudate versus MHB, revealing discordant AST results across six of nine tested antibiotic classes. The most significant were 128-fold increased resistance to tetracyclines and 256-fold sensitization to {beta}-lactams in SWF. Tetracycline resistance was mediated by MntC, an extracellular manganese-binding protein, whereas {beta}-lactam sensitization was driven by cell envelope remodelling in SWF. Galleria mellonella wound infection results matched the SWF susceptibility phenotypes, suggesting SWF better predicts in vivo wound infection therapeutic outcomes. These comprehensive phenotypic and mechanistic insights into MRSA antibiotic responses under wound-infection-mimetic conditions with direct in vivo validation identify a potential new antibiotic adjuvant target and may guide improved antibiotic therapy for MRSA wound infections.

Objectives: Among surgically resected non-small cell lung cancer (NSCLC) patients with similar stage and histopathological characteristics, there is variability in patient outcomes which highlights urgency of identifying biomarkers to predict recurrence. The goal of this study was to systematically develop a pre-surgical CT-based habitat-based radiomics classifier to predict recurrence-of-risk in NSCLC. Methods: This study included 293 NSCLC patients with surgically resected stage IA-IIIA disease that were randomly divided into a training (n = 195) and test cohorts (n = 98). From pre-surgical CT images, tumor habitats were generated using two-level unsupervised clustering and then radiomic features were calculated from the intratumoral region and habitat-defined subregions. Using ridge-regularized logistic regression, separate classifiers were developed to predict 3-year recurrence using intratumoral radiomics, habitat-based radiomics, and a combined model (intratumoral and habitat) which was generated using a stacked learning framework. For each classifier, probability of recurrence was calculated for each patient then numerous statistical and machine learning approaches were utilized to stratify patients for recurrence-free survival. Results: The combined radiomics classifier yielded a superior AUC (0.82) compared to the intratumoral (AUC = 0.75) and habitat radiomics (AUC = 0.81) models. When the classifiers were used to stratify high- versus low-risk patients utilizing a cut-point identified by decision tree analysis, high-risk patients were yielded the largest risk estimate (HR = 8.43; 95% CI 2.47 - 28.81) compared to the habitat (HR = 5.41; 95% CI 2.08 - 14.09) and intratumoral radiomics (HR = 3.54; 95% CI 1.45 - 8.66) models. SHAP analyses indicated that habitat-derived information contributed most strongly to recurrence prediction. Conclusions: This study revealed that habitat-based radiomics provided superior statistical performance than intratumoral radiomics for predicting recurrence in NSCLC.

Objective To evaluate the Cartilage Thickness Score (CTh-Score) as a quantitative measure of cartilage damage severity by assessing its association with three osteoarthritis (OA) milestones and comparing its performance with conventional morphometric measures (radiographic minimum joint space width (JSW) and regional average cartilage thickness). Methods Data were obtained from the Osteoarthritis Initiative (OAI) and the publicly available OAI CTh-Maps and CTh-Score dataset. Three matched case-control designs were used to represent major OA milestones: (i) incident radiographic OA onset, (ii) combined pain and structural progression, and (iii) knee replacement (KR) in the coming 2 years. Progression subjects were extracted from the FNIH Biomarkers Consortium cohort. Cases and controls were compared at 4 years (T-4Y), 2 years (T-2Y), and 0 years (T0) before the milestone. MRI-based CTh-Score and regional average cartilage thickness, as well as JSW, were analyzed cross-sectionally and longitudinally. Associations with case status were assessed using adjusted logistic regression models, and responsiveness was evaluated using longitudinal change and standardized response means. Results The onset cohort included 307 matched case-control pairs, the progression cohort 164 cases and 369 controls, and the KR cohort 81 cases and 324 controls. Across all three study designs, the CTh-Score significantly differentiated cases from controls at all timepoints. In the onset cohort, the CTh-Score was higher in future cases than controls at T-4Y (16.2 vs 12.6, p=0.007), T-2Y (23.5 vs 16.7, p<0.001), and T0 (39.8 vs 18.6, p<0.001), whereas JSW and regional thickness measures showed limited or later discrimination. Similar findings were observed for progression (43.2 vs 33.0 at T-4Y; p<0.001) and KR (55.4 vs 46.1 at T-4Y; p=0.02) cohorts. Longitudinally, CTh-Score changes differentiated cases from controls earlier and more consistently than JSW or regional average thickness, and its responsiveness was consistently the highest across OA milestones and time intervals. In adjusted models, the CTh-Score was independently associated with all outcomes at T-4Y and T-2Y, with odds ratios per standard deviation increase ranging from 1.3 to 2.2. Conclusion The CTh-Score captures high-resolution cartilage thickness patterns associated with OA onset, progression, and future knee replacement, outperforming conventional morphometric measures in early discrimination, responsiveness, and predictive association. These findings support CTh-Score as a sensitive quantitative marker of cartilage damage severity across the OA continuum.

Walking speed is widely used to assess gait recovery following stroke, yet it provides limited insight into how walking performance is mechanically organized. This study examined how center of mass (COM) work organization and propulsion-support coupling vary across walking speeds in individuals with post stroke hemiparesis to distinguish recovery of gait organization from recovery of limb level mechanical function. Eleven individuals with post stroke hemiparesis performed treadmill walking across speeds ranging from 0.2 to 0.7 m/s while ground reaction forces were recorded. Limb specific COM power and work were computed using an individual limbs framework, and interlimb asymmetry in net and positive work, along with the propulsion-support ratio (PSR), were quantified. A qualitative transition in gait organization was observed: at lower walking speeds, COM power exhibited a simplified two phase pattern, whereas at higher walking speeds (approximately >=0.5 m/s), a structured four phase COM power pattern emerged, including identifiable push off and preload phases. Despite this recovery of gait organization, interlimb work asymmetry remained elevated and paretic PSR remained reduced across all speeds, indicating persistent limb level mechanical deficits. These findings demonstrate that increases in walking speed and the emergence of typical COM power structure reflect recovery of gait organization rather than restoration of underlying limb level mechanical capacity. Consequently, walking speed alone is insufficient to characterize gait recovery after stroke, and biomechanically informed measures of COM work organization and propulsion-support coupling provide complementary insight by distinguishing organizational recovery from limb-level mechanical recovery.

IntroductionIndividuals with COPD can be classified according to their levels of physical activity (PA) and physical capacity (PC). The relationship between nutrition and body composition within these classifications remains unclear. ObjectivesTo compare the body composition and food intake of people with COPD and verify the associations. MethodsCross-sectional exploratory analysis study in which body composition and food intake were assessed in individuals with COPD. Classification was based on six-minute walk test (PC) and accelerometry(PA): Quadrant "can do, dont do" (I-preserved PC, low PA); quadrant "can do, do do" (II-preserved PC, preserved PA). Results72 individuals with COPD, 39 in quadrant I and 33 in quadrant II, with mean ages of (69 {+/-} 6) (67 {+/-} 7), respectively. Group I had a higher proportion of males, whereas group II had a higher proportion of females. A positive trend in skeletal muscle mass (p=0.011) (B= 2.883) and a negative trend in basal metabolic rate (p=0.010) (B=-0.092) for group I. ConclusionBrazilians with COPD classified in quadrants I and II showed similar results in terms of body composition and food intake. A positive trend in skeletal muscle mass was observed for the group I. These findings align with the pathophysiological model of COPD, in which the preservation of muscle mass and adequate protein intake support functional capacity and the maintenance of higher physical activity levels.

BackgroundGastroesophageal reflux disease (GERD) is highly prevalent in systemic sclerosis (SSc) and frequently persists despite proton pump inhibitor (PPI) therapy. However, the mechanisms underlying PPI-refractory GERD in SSc remain incompletely understood. MethodsWe conducted a singlel7lcentre, retrospective study of adults with SSc who underwent ambulatory pH-multichannel intraluminal impedance (pH/MII) monitoring while receiving twicel7ldaily PPI therapy (2021-2025). Esophageal motility (highl7lresolution manometry, HREM) and gastric emptying scintigraphy were integrated to examine associations between gastro-esophageal dysmotility and reflux phenotypes. ResultsThirty patients were included, of whom 67% had PPI-refractory reflux symptoms and 33% were undergoing pre-lung transplantation evaluation. Refractory GERD was present in 29/30 patients (97%) based on Lyon 2.0 classification, with conclusive evidence in 53% and borderline evidence in 43%. Esophageal dysmotility was identified in 80%, most commonly absent contractility (67%), and was associated with impaired reflux clearance, reflected by longer acid clearance times (2.20 [1.15-3.75] vs 1.15 [0.43-1.90] min) and prolonged reflux episode duration (16.60 [4.38-40.63] vs 1.95 [0.53-20.43] min). Gastric dysmotility was identified in 60.7% and was associated with an increased reflux episode burden (51.00 [30.00-81.50] vs 25.00 [21.00-54.00] episodes/24h). ConclusionsPPIl7lrefractory GERD is nearly universal in this SSc cohort and reflects heterogeneous, quantifiable abnormalities across the foregut, including impaired esophageal clearance and increased reflux burden related to gastric retention. These findings support integrated physiologic evaluation to define reflux mechanisms, inform risk stratification (including lung transplantation), and guide targeted, mechanism-based therapies beyond acid suppression.

Altered iron homeostasis has long been implicated in Parkinson's Disease (PD), although the mechanisms have not been clear. Given the critical role of PD-related activating mutations in LRRK2 (leucine-rich repeat protein kinase 2) within membrane trafficking pathways we examined the impact of a homozygous mutant LRRK2G2019S on iron homeostasis within the RAW macrophage cell line with high iron capacity. Proteomics analysis revealed a dysregulation of iron-related proteins in steady state with highly elevated levels of ferritin light chain and a reduction of ferritin heavy chain. LRRK2G2019S mutant cells showed efficient ferritinophagy upon iron chelation, but upon iron overload there was a near complete block in the degradation of the ferritinophagy adaptor NCOA4. These conditions lead to an accumulation of phosphorylated Rab8 at the plasma membrane, which is selectively inhibited by LRRK type II kinase inhibitors. Iron overload then leads to increased oxidative stress and ferroptotic cell death. These data implicate LRRK2 as a key regulator of iron homeostasis and point to the need for an increased focus on the mechanisms of iron dysregulation in PD.

Physical inactivity is common in chronic kidney disease (CKD) and is associated with poor neuromuscular and functional outcomes. Whether habitual physical activity (PA) influences adaptations to structured exercise in CKD remains unclear. This study examined if adaptations to combined flywheel resistance and aerobic exercise (FRE+AE) differed based on self-reported PA in Veterans with CKD stages 3 and 4. Twenty older male Veterans with CKD stages 3-4 (mean eGFR 37.9 +/- 10.2 mL/min/1.73 m2) were randomized to six weeks of FRE+AE (n=11) or health education (EDU; n=9). Participants were classified as meeting (Meets PA) or below (Low PA) weekly moderate intensity PA recommendations using the 7-day Physical Activity Recall. Outcomes included vastus lateralis muscle thickness (VL MT), knee extensor power output (60/s and 180/s), gait speed (GS), and five-repetition sit-to-stand (STS). FRE+AE increased VL MT (p=0.030), power output at 180/s (p=0.021), GS (p=0.001), and reduced STS time (p=0.012), with significant between-group differences versus EDU for VL MT (p=0.009) and GS (p=0.028). Low PA experienced greater increases in power output at 60/s (Hedges g; Low PA=0.44, Meets PA=0.25) and 180/s (Hedges g; Low PA=1.38, Meets PA=0.38) compared to Meets PA after FRE+AE. Conversely, Meets PA had greater improvements in GS (Hedges g; Low PA=0.93, Meets PA=1.29) and STS (Hedges g; Low PA=-0.72, Meets PA=-2.20) compared to Low PA. Six weeks of FRE+AE produced clinically meaningful neuromuscular and functional improvements in Veterans with CKD stages 3 and 4 irrespective of PA level, supporting FRE+AE as a feasible intervention in this population.

Background Venous thromboembolism (VTE) remains a major cause of perioperative morbidity in cranial neurosurgery, yet clinical practice varies widely, and formal guidelines are inconsistent. Understanding internationally sampled neurosurgical practice is essential for informing consensus and future trials. Methods An international, 2-stage cross-sectional, internet-based survey was conducted. Practising neurosurgeons performing elective adult cranial surgery were eligible. Descriptive statistics were used to summarise practice. Responses covered patterns of pre-operative haemostasis decision making, use and timing of mechanical and/or chemical prophylaxis, use of perioperative imaging prior to anticoagulation, and frequency of clinical assessment for VTE. Associations with geographical income status, subspecialty, and years post-certification were statistically tested. Practice heterogeneity was quantified and contextual influence was summarised using mean effect sizes across stratifying variables in order to determine domains of true equipoise. Results Of 585 responses, 456 (78%) met criteria for inclusion: representing 322 units across 78 countries (71% high-income). Thirteen per cent reported no departmental VTE plan; 23% followed no guidelines and 12% used multiple. Routine pre-operative testing almost universally included haemoglobin/platelets/haematocrit, with fibrinogen more common in high-income settings. Compared with high-income country respondents, low- and middle-income respondents reported higher haemoglobin transfusion thresholds (>90 g/dL; p<0.001) and shorter antiplatelet interruption (p[&le;]0.03), and less frequent outpatient VTE assessment (p<0.001). Mechanical prophylaxis was common (TEDs 81%, IPC 62%), typically started pre- or intra-operatively. Among those completing the chemoprophylaxis section (n=310), 57% required a CT or MRI scan before LMWH which was then initiated on average 31.4 hours after surgery. 1% of respondents did not routinely use LMWH. Many clinical decisions demonstrated statistical equipoise ie. high heterogeneity with low contextual influence. Conclusion Peri-operative haemostasis and VTE prophylaxis practices in adult elective cranial neurosurgery vary substantially worldwide, with some decisions reflecting geographical or socioeconomic differences and many others reflecting true clinical equipoise rather than contextual determinants. By mapping contemporary real-world practice across diverse health-system contexts, this study provides a necessary empirical foundation for rational trial design and future guideline development.

Background: To investigate the safety and efficacy of CTguided lung nodule localization needles for the preoperative localization of small pulmonary nodules. Methods: A retrospective study was conducted on 102 patients with a total of 113 small pulmonary nodules who underwent preoperative localization at Jinan Fourth People's Hospital from January 2024 to December 2025. Nodule diameter and depth, localization time, the number of pleural punctures, the localization success rate, and postoperative complications (hook dislodgement, hemorrhage, and pneumothorax) were recorded. All patients underwent video assisted thoracoscopic surgery (VATS) after localization. Results: The mean nodule diameter was 0.97{+/-}0.36 cm, the mean depth was 1.26{+/-}0.48 cm, and the mean localization time was 9.8{+/-}3.65 minutes. The hook dislodgement rate was 0.98% (1/102), the intrapulmonary hemorrhage rate was 14.71% (15/102), and the pneumothorax rate was 16.67% (17/102). All pulmonary nodules were successfully resected by VATS at 73.82{+/-}13.83 minutes after localization, and no severe complications occurred. Conclusions: The use of a CTguided lung nodule localization needle for the preoperative localization of small pulmonary nodules decreases the time needed for intraoperative nodule detection and operation time. This strategy is a simple, safe, and accurate preoperative localization method that is worthy of increased clinical use.