搜索结果：Quantifying

Traumatic brain injury (TBI) is a devastating neurological disorder with long-term functional deficits and limited effective therapies, where secondary injury driven by dysregulated immunity and disrupted signaling is pathogenic; Nao Tan Qing (NTQ), a Chinese herbal formula guided by the traditional principle of "resolving phlegm and inducing resuscitation" for "brain collateral obstruction", shows neuroprotective potential, but its role and mechanism in TBI treatment remain unclear. This study aimed to systematically investigate the neuroprotective effects of NTQ against TBI model mice and elucidate its underlying molecular mechanisms. A controlled cortical impact (CCI) mouse model of TBI was established, and animals received NTQ treatment for 28 consecutive days. NTQ's neuroprotective efficacy was comprehensively evaluated via behavioral tests (functional recovery), cerebral blood flow imaging (vascular integrity), and electromyography (neural activity). Post-treatment inflammatory levels in TBI mice were assessed by quantifying inflammatory cytokine expression using quantitative real-time PCR and detecting microglial activation via immunofluorescence. Mechanistic exploration integrated network pharmacology, transcriptomics and bioinformatics analyses to identify NTQ's active components, potential targets, and associated pathways in TBI. In vivo experiments demonstrated that NTQ significantly improved behavioral outcomes, restored cerebral blood flow, and enhanced neural activity in TBI mice. Concurrent with these functional benefits, NTQ robustly suppressed neuroinflammation, as evidenced by reduced pro-inflammatory cytokine expression and attenuated microglial activation. Integrated network pharmacology and transcriptomic analyses confirmed that NTQ acts primarily through immune regulation after TBI, modifying key immune-related molecules and pathways; Specifically, NTQ intervention elicited pronounced downregulation of immune-inflammatory mediators, including Cd3g, Cd5, Cd8a, Epcam, Slamf7, Il16, Il17r, Il18rap, Cxcl9, Cxcr6, Tnfsf11, and Tnfsf15. Further mechanistic dissection identified six putative bioactive constituents of NTQ, including nicotinamide, curcumin, baicalin, chrysin, daidzein, and apigenin, which may remodel the intracerebral immune microenvironment after TBI through three core pathways: amine ligand-binding receptors, nuclear receptor meta-pathways, and arachidonic acid metabolism. Taken together, our integrated analyses demonstrate that NTQ exerts neuroprotective effects in TBI by modulating immune responses and suppressing neuroinflammation, thereby establishing NTQ as a promising multi-target therapeutic agent for TBI.

The development of polymetallic complexes incorporating N-heterocyclic carbene (NHC) ligands is a promising strategy for achieving enhanced performance that may arise from the presence of multiple metal centers in chemical transformations and/or physicochemical properties. However, quantifying cooperativity in these systems remains a significant challenge. We report a modular synthetic strategy to obtain Ru(II)-Ir(III) heterodinuclear complexes bridged by a bis-bidentate ditopic carbanionic NHC (dc-NHC) ligand (L2). Our synthetic methodology allowed selective metal coordination at the C2 and C4 imidazolium positions. A series of homo- and heterodinuclear complexes were synthesized, fully characterized, and evaluated as catalysts in tandem α-alkylation/transfer hydrogenation of ketones with alcohols under mild, neat, and base-limited conditions. Notably, the heterodinuclear complexes [Ru-L2-Ir]PF6 and [Ir-L2-Ru]PF6 exhibited the highest catalytic activity for tandem products, compared to the corresponding monometallic Ru(II) and Ir(III) analogues under the same metal percentage loadings. Additionally, a possible contribution of the heterodinuclear arrangement was examined by kinetic experiments (Ea), which indicate lowered activation barriers for [Ru-L2-Ir]PF6.

Meningitis, an inflammatory condition that affects the meninges, has reported an increase in cases between 2006 and 2016. While in well-resourced settings, the incidence of acute bacterial meningitis has declined to below 0.5-1.5 cases per 100,000 population. Overall, late excess mortality following meningitis is highest within the first two years after discharge, particularly affecting patients aged 30-60 years. This research seeks to analyse these trends and investigate potential disparities in mortality rates based on demographic variables between 1999 and 2020. By quantifying high-risk populations and regional differences, the findings provide evidence to guide targeted public health interventions and resource allocation. This retrospective observational study used CDC WONDER data (1999-2020) to analyse mortality trends for individuals aged 1-85 + years. Deaths related to meningitis were identified using ICD-10 codes A17.0, A32.1, A39.0, A87.0, A87.1, A87.2, A87.8, A87.9, B00.3, B01.0, B02.1, B05.1, B26.1, B37.5, B38.4, G00.0, G00.1, G00.2, G00.3, G00.8, G00.9, G03.0, G03.1, G03.2, G03.8, G03.9. Crude mortality rates and age-adjusted mortality rates (AAMRs) were calculated. Temporal trends and significant changes in mortality trajectories were assessed using Joinpoint regression analysis, which estimated annual percentage changes (APCs) and identified statistically significant inflection points. Mortality patterns were further stratified by sex, race or ethnicity, census region, state, and urban-rural classification. Between 1999 and 2020, meningitis-related AAMRs in the United States declined from 8.43 to 3.88 per 1,000,000 population, with the steepest decrease between 1999 and 2012 before stabilising thereafter. Males consistently showed higher mortality (AAMR 5.79) compared to females (AAMR 4.53), though both declined substantially over the study period. Non-Hispanic (NH) Black individuals exhibited the highest AAMRs (8.59), followed by Hispanics (4.81), NH Whites (4.64), and NH Asians or Pacific Islanders (3.58). Geographically, the West (5.35) and South (5.33) had the greatest burden, while the Northeast (4.69) and Midwest (4.81) reported lower rates. State-level variation ranged from 8.85 per 1,000,000 in the District of Columbia to 3.52 per 1,000,000 in Delaware, with higher mortality in non-metropolitan areas than metropolitan ones. This study provides a comprehensive analysis of meningitis-related mortality trends in the United States from 1999 to 2020, highlighting significant declines in AAMRs across demographic groups, regions, and urbanisation levels. Despite the overall decline, the stabilisation of AAMRs in the last decade suggests a plateau in progress, necessitating further investigation into the underlying factors. Thus, targeted interventions to enhance the prevention, control, and management of risk factors might be required to achieve lasting change.

Understanding human ageing across multiple organs is essential for characterising individual health trajectories and identifying abnormal ageing processes. Multi-organ imaging provides an opportunity to quantify biological ageing beyond chronological age. The aim of this study is to assess organ-specific and whole-body ageing patterns and their associations with disease and lifestyle factors. In this large-scale study, we evaluate biological ageing patterns using 70,000 MRI scans from the UK Biobank and the German National Cohort. We employ 3D ResNet-18 models to predict chronological age from various body regions (brain, heart, liver, spine, lungs, muscle, and intestine) and the whole body. From these predictions, we derive "age gaps" relative to a strictly healthy reference cohort, which enables the identification of accelerated ageing patterns. We then evaluate associations with chronic diseases and lifestyle factors, and a virtual ageing framework was developed to explore counterfactual scenarios by substituting anatomical regions across subjects, quantifying local impacts on global biological age. Here we show significant associations between detected accelerated ageing and specific chronic diseases, including multiple sclerosis and chronic obstructive pulmonary disease, as well as lifestyle factors such as smoking and physical activity. Virtual substitution of anatomical regions demonstrates that local substitutions can influence global ageing patterns. This study demonstrates that multi-organ imaging enables the detection of abnormal ageing patterns at both local and global levels. The presented framework provides a foundation for improved risk stratification and supports the development of personalised approaches to health assessment and disease prevention. As people age, different organs in the body might not always age at the same pace. Understanding these differences can help to explain a person’s health and why they develop diseases earlier than others. In this study, we measure how ageing varies across the body using medical images. We analysed about 70,000 whole-body scans from large population studies in the United Kingdom and Germany. Using AI models, we estimated a person’s biological age from images of different organs and compared it with their actual age. We found that faster ageing in specific organs is linked to certain diseases (such as multiple sclerosis) and lifestyle factors (like smoking and physical activity). These findings may help improve early disease detection and support more personalised approaches to health and ageing in the future.

Covalent organic frameworks (COFs) have garnered increasing attention in electrochemiluminescence (ECL), but how to improve ECL efficiency is still challenging due to the insufficient charge separation driving forces and non-directional charge transfer. Herein, by rationally modulating the types of building blocks, we synthesize two donor-acceptor (D-A) imine-linked COFs with distinct charge transfer directionality (namely Btt-Tpa-COF and Btt-Tapt-COF). In Btt-Tapt-COF, the D-A orientations of building units align with those of imine bonds (Cδ+=Nδ-), which facilitates the establishment of codirectional charge transfer channels and significantly promotes the intramolecular charge separation/transport for the achievement of exceptional ECL performance. In contrast, Btt-Tpa-COF exhibits the reduced ECL stability and efficiency due to its reversed D-A orientation that impedes the intramolecular charge transfer. As a proof of concept, we construct a target-responsive ECL aptasensor to measure lincomycin (LIN) with Btt-Tapt-COF as an efficient emitter and the three-dimensional DNA hydrogel as an intelligent signal switch. This aptasensor can sensitively measure LIN within a large linear response range of 0.0001-10 ng/mL. Importantly, this research reveals the effect of charge transfer directionality on ECL performance and provides a promising strategy for the construction of efficient ECL sensors to quantify antibiotics in food and the environment.

Land use carbon emissions (LUCE) is crucial for achieving carbon neutrality and sustainable development goals. How to coordinate ecological and economic benefits and formulate targeted regional carbon balance strategies based on local conditions remains to be explored. Therefore, Shaanxi Province in China was selected as the case for this study due to its rich ecological and energy resources and its significant differences. LUCE was calculated for each county in the region from 2000 to 2020. The contribution of carbon ecological capacity was quantified by calculating the carbon ecological support coefficient (ESC). The economic output per unit of carbon emission was measured using the carbon economic contribution coefficient (ECC). Based on the above, an optimized functional zoning for LUCE and carbon balance was constructed. Results showed that LUCE in Shaanxi Province increased from 2,088.18&#x2009;&#xd7;&#x2009;104 tonnes in 2000 to 19,330.99&#x2009;&#xd7;&#x2009;104 tonnes in 2020, with central region accounting for 64.81% of the total, northern region 22.92%, and southern region 12.27%. About 53.27% of counties maintained ecological deficits (ESC&#x2009;<&#x2009;1) in the Northern Shaanxi Energy Zone and the Guanzhong Belt, while 56.07% exhibited an imbalance between economic output and carbon emissions (ECC&#x2009;<&#x2009;1) in the Northern periphery and the Southern Ecological Zone. Economic growth was positively correlated with LUCE and negatively with ESC, but had a relatively small relationship with ECC and carbon absorption. Subsequently, all counties in Shaanxi Province were classified into five functional types: Carbon Sink Zones, Low-Carbon Economic Zones, Economic Development Zones, Carbon Intensity Control Zones and High-Carbon Optimization Zones, and a targeted strategy was proposed for each functional type. These results could provide a practical and transferable framework for supporting carbon neutrality planning and sustainable land use management in ecologically sensitive regions.

Patients with severe peripartum cardiomyopathy (PPCM) often receive mechanical circulatory support with good outcomes. However, mechanisms underlying the functional improvements are poorly understood for patients with different PPCM characteristics. This study investigated effects of partial, continuous-flow left ventricular assist device (LVAD) support on cardiac function and mechanics in patients with different PPCM severity. Patient-specific biventricular finite element models of six patients with different PPCM severity were developed from magnetic resonance images and combined with a circulatory system model, including variable LVAD support. Ventricular function and myocardial mechanics were predicted and changes due to LVAD support were quantified. The LVAD support decreased LV myofiber stress and increased ejection fraction (EF). EF increased steadily (two patients), fluctuated (two patients), or peaked before a steady decrease (two patients) with increasing LVAD speed. Improvement due to LVAD support was greater for PPCM patients with higher disease severity than those with lower disease severity. The LVAD and native LV jointly generated stroke volume (SV) in four patients, and the LV contribution diminished with increasing LVAD speed. In the two patients with the lowest EF, the LVAD was the sole source of SV. The improvement of cardiac function and mechanics due to LVAD support in PPCM exceeds that reported for chronic heart failure due to ischaemia. However, the predicted variability of the LVAD benefits with PPCM severity and mechanical support level suggests the need and potential for further studies to guide clinicians in selecting personalised treatment parameters required for optimised LVAD therapy for each PPCM patient.

Refugees often experience disruptions in social networks after resettlement. This study examined associations between bonding (within-group) and bridging (across-group) social capital and self-rated health among resettled U.S. refugees and evaluated potential psychosocial pathways. We analyzed pooled cross-sectional data from the 2020-2022 Annual Survey of Refugees (N&#x2009;=&#x2009;4,530). Structural equation modeling was used to estimate total effects of bonding and bridging social capital on self-rated physical and mental health and to quantify indirect effects operating through sense of belonging, perceived discrimination, and receipt of public benefits. All models adjusted for sociodemographic and resettlement-related covariates. Total effects showed that bonding and bridging social capital were both positively associated with physical health (&#x3b2;&#x2009;=&#x2009;0.0382, 95% CI: 0.0110, 0.0655 and &#x3b2;&#x2009;=&#x2009;0.0402, 95% CI: 0.0132, 0.0672 respectively), while only bonding social capital was associated with mental health (&#x3b2;&#x2009;=&#x2009;0.0877, 95% CI: 0.0571, 0.1183). Indirect effects indicated that sense of belonging mediated positive associations for both types of social capital (for bonding: &#x3b2;physical health=0.0075, 95% CI: 0.0041, 0.0109 and &#x3b2;mental health=0.0126, 95% CI: 0.0076, 0.0177; for bridging: &#x3b2;physical health=0.0046, 95% CI: 0.0015, 0.0078 and &#x3b2;mental health=0.0081, 95% CI: 0.0031, 0.0137), whereas discrimination only mediated the effects of bonding social capital (&#x3b2;physical health=0.0026, 95% CI: 0.0002, 0.0050 and &#x3b2;mental health=0.0064, 95% CI: 0.0023, 0.0105). Receipt of public benefits did not significantly mediate either relationship. Sense of belonging and discriminatory experiences may represent key pathways linking social capital and refugee health. Longitudinal research is needed to clarify causal mechanisms.

Advanced-stage ovarian cancers exhibit significant variability in responses to standard chemotherapy ranging from platinum-refractory to platinum-sensitive cancers. While genomic testing reveals tissue heterogeneity, it rarely provides actionable data for guiding therapy. To evaluate the heterogeneity of ex&#xa0;vivo drug responses in primary ovarian cancer tissues using a functional profiling platform, and to assess the platform's potential for guiding personalized therapy selection within current clinical practice. A functional profiling platform that creates 3D microtumors from fresh biopsies was used to enable ex&#xa0;vivo assessment of drug efficacy in a physiologically relevant model. Interpatient heterogeneity was quantified as the statistical variability of the EC50 values, calculated using the ratio of upper and lower interdecile values. Seventeen ovarian cancer tissues were processed and exposed to NCCN-recommended drugs and drug combinations. Drug efficacy demonstrated significant interpatient heterogeneity (p&#x2009;<&#x2009;0.001). Carboplatin and paclitaxel alone exhibited moderate heterogeneity (54-fold and 42-fold difference), while their combination showed higher heterogeneity (3880-fold difference), suggesting synergy in certain samples but not in others. Gemcitabine exhibited the highest single-agent heterogeneity across the cohort (1504-fold difference), whereas doxorubicin and olaparib demonstrated more consistent responses but limited efficacy in many samples (20-fold and 16-fold difference). These findings align with the clinically observed variability in patient responses, highlighting the platform's potential to optimize therapy selection and support patient-centric care within the standard of care for ovarian cancer patients.

Federated Learning (FL) in surgical video AI enables collaborative model training without sharing sensitive data. However, standard evaluation practices-selecting the "best" global model based only on validation data from participating hospitals-can lead to suboptimal deployment choices. We identify this critical failure mode as performance leakage, where the selected model overfits internal federation data and fails to generalize to unseen institutions, thereby undermining the core goal of FL: robust real-world generalization. We propose GEN-Guard, a practical post-hoc framework to detect and correct generalization failures in federated surgical AI. It integrates Generalization Detection via Client-Blocked Evaluation (CBE), which validates performance on isolated client distributions to prevent performance leakage, and Generalization Correction through Disagreement-Aware Distillation (DAD), which learns adaptive feature-level corrections for cross-institutional robustness. Both components operate after standard FL convergence while providing robust support for zero-shot adaptation to unseen clinical environments. We first quantify the severity of performance leakage, observing Model Selection Failures (MSFs) exceeding 80% under standard evaluation. GEN-Guard is evaluated on two multi-center clinical challenges: surgical phase recognition in laparoscopic cholecystectomy and polyp segmentation in colonoscopy. Across both datasets, GEN-Guard consistently corrects these failures, improving in-federation F1 scores by up to 2 points, unseen-institution performance by up to 3 points, and worst-case institutional performance by 3-9 points. Performance leakage represents a systematic and previously under-recognized risk in federated surgical AI. GEN-Guard provides a practical, privacy-preserving solution for detecting and correcting such failures without modifying the core federated training procedures. By improving cross-institutional robustness and zero-shot generalization, it strengthens the reliability of FL for real-world surgical deployment.

Increased radiosensitivity can cause adverse radiotherapy effects. Heterozygote variants in breast cancer risk genes increase cancer risk and may affect radiosensitivity. This study assessed their impact on individual radiosensitivity to determine the radiation risk for gene carriers. Radiosensitivity was analyzed in 273 patients with breast cancer risk gene variants. Using fluorescence in situ hybridization (FiSH), chromosomal aberrations were quantified as breaks per metaphase (B/M) after ex vivo irradiation of blood lymphocytes. Results were compared with healthy controls and breast cancer cases, both without confirmed non-carrier status, limiting gene-specific conclusions. Gene carriers showed slightly increased radiosensitivity (mean 0.488 B/M&#x2009;&#xb1;&#x2009;0.134) compared with healthy controls (0.411 B/M&#x2009;&#xb1;&#x2009;0.088; p&#x2009;<&#x2009;0.0001) but similar to breast cancer control group (0.498 B/M&#x2009;&#xb1;&#x2009;0.192; p&#x2009;=&#x2009;0.563). In BRCA1/2 carriers, radiosensitivity was slightly increased, while single cases in BARD1, RAD51, and MSH variants suggested a possible increase (p&#x2009;<&#x2009;0.003). Radiosensitivity was influenced by gene locus, variant type, age, and cancer history. 24.5% of carriers exceeded a cutoff of &#x2265;&#x2009;0.55 B/M, where dose reduction could be considered. Radiosensitivity of breast cancer risk gene carriers varies and is slightly increased. Individuals with increased radiosensitivity risk should consider testing.

Trauma-induced coagulopathy (TIC) is a leading cause of preventable mortality following severe injury, yet prehospital recognition is fundamentally constrained by the limited sensitivity of static vital-sign metrics. Although fifth-generation (5G) wireless technology theoretically enables continuous biosignal transmission, robust computational frameworks for streaming risk prediction remain underdeveloped and largely unvalidated. To address this methodological gap, this study presents Trauma-Former, an inverted Transformer (iTransformer) architecture for real-time TIC prediction, trained and validated on high-fidelity synthetic physiological data within a rigorous in-silico engineering assessment framework. An Ornstein-Uhlenbeck (OU) process generated 1&#xa0;Hz vital-sign waveforms (heart rate [HR], systolic and diastolic blood pressure [SBP/DBP], SpO&#x2082;) for 1,240 simulated 30-minute transport episodes (50% TIC prevalence), structured according to the ADEMP framework. Trauma-Former embeds 60-second histories as independent variable tokens, applying self-attention across physiological streams to model inter-variable coupling. Models were benchmarked against an expanded set including a linear trend-based logistic regression (LR-trend), a 1D convolutional neural network (1D-CNN), a bidirectional gated recurrent unit (GRU), LSTM, XGBoost, PatchTST, Informer, and the shock index. An independent test set with 25% TIC prevalence assessed performance under clinically representative event rates. A sensitivity analysis incorporating binary missingness indicators probed the missing-completely-at-random (MCAR) assumption. Monte Carlo standard errors (MCSE) quantified simulation uncertainty throughout. On the balanced development set, Trauma-Former achieved an AUROC of 0.939 (95% CI 0.92-0.95; MCSE&#x2009;=&#x2009;0.003) and an AUPRC of 0.88. Critically, the LR-trend model achieved an AUROC of 0.917 (95% CI 0.89-0.94), confirming that the synthetic task is predominantly solvable by detecting monotonic vital-sign drifts; the incremental contribution of iTransformer's cross-variable attention is consequently modest (AUROC gap: 0.022). Under a realistic 25% prevalence setting, AUROC remained 0.931 but positive predictive value (PPV) collapsed from 0.89 to 0.48-a 46% relative reduction-indicating that fewer than half of all model-generated alerts would correspond to true TIC events in a representative prehospital cohort. Adding binary missingness indicators yielded only a marginal PPV improvement of 0.02 under 30% MCAR data loss. The model demonstrated resilience to 30% packet loss and 4G-equivalent latency jitter with less than 5% AUROC degradation. Trauma-Former provides a reproducible, open-source synthetic testbed for prehospital AI development. All reported metrics represent upper-bound estimates derived under deliberately simplified linear conditions. The severe PPV collapse under realistic prevalence identifies alarm fatigue as the paramount translational barrier and underscores that rigorous external validation on real-world prehospital data is the absolute prerequisite for any clinical application.

The aim was to evaluate bias and precision for 177Lu-activity-quantification using window-based scatter compensation in a ring-configured CZT gamma camera (StarGuide&#x2122;, GE HealthCare). This paper extends a previous study by applying modified scatter compensation (MSC) methods introduced with the StarGuidePlus upgrade. The modified methods account for contamination of scatter windows by primary photons due to tailing. Whilst the original compensation addressed tailing in the 208&#xa0;keV peak only, the upgrade extends the concept to the 113&#xa0;keV peak and enables the estimated primary signal in the scatter windows to be included to the measured projections (MSC&#x2009;+&#x2009;P). Listmode-data for a NEMA phantom and anthropomorphic phantom were reframed to accommodate the updated settings for MSC and MSC&#x2009;+&#x2009;P. Reconstruction was performed using OS-EM (two to 30 iterations, 10 subsets) with compensation for attenuation, scatter (DEW/TEW, MSC and MSC&#x2009;+&#x2009;P), spatial resolution, and penetration at 208&#xa0;keV. Volumes-of-interest following the manufacturer-specified sphere sizes were defined and activity-concentration was quantified for each sphere and the total phantom activity across six (10&#xa0;min) time-frames. Bias was evaluated with mean relative error and precision with coefficient of variation (CV). Imaging at 208&#xa0;keV generally results in similar activity concentrations and total activity estimates for MSC and MSC&#x2009;+&#x2009;P (mean relative error: -&#x2009;24.8 to -&#x2009;23.4%, CV: 0.6 and 0.7% for the larges sphere). For 113&#xa0;keV, a slightly better precision is obtained for MSC and MSC&#x2009;+&#x2009;P (mean relative error: -&#x2009;15.4 and -&#x2009;21.5%, CV: 0.6 and 0.7% for the largest sphere in the NEMA phantom) but a larger bias compared with TEW (mean relative error&#x2009;-&#x2009;7.1%, CV 0.8%). The major difference is for total activity where the MSC and MSC&#x2009;+&#x2009;P decrease bias compared to TEW (5 and 4% versus 21% for 113&#xa0;keV in the NEMA phantom). The improvement in activity-concentration accuracy in regard to bias and precision is modest in small-volume high activity-concentration regions. However, the findings suggest potential value in preservation of total activity for both MSC and MSC&#x2009;+&#x2009;P.

Adolescent idiopathic scoliosis (AIS) is a heterogeneous three-dimensional spinal deformity associated with neuromuscular imbalance and chronic asymmetric loading, which may induce adaptive changes in lumbar paraspinal and trunk muscles. Although magnetic resonance imaging allows in vivo assessment of muscle morphology, most studies have focused on muscle size, with limited evaluation of muscle composition and few analyses across Lenke curve types. This study aimed to characterize lumbar muscle morphology and composition in AIS and to assess curve-type-specific and concave-convex asymmetry patterns. This retrospective cohort study included AIS patients undergoing posterior spinal fusion January 2019 and December 2023 with available preoperative T1-weighted axial MRI. Lumbar muscle morphology of the psoas, paraspinal (erector spinae and multifidus), and quadratus lumborum muscles was assessed bilaterally at the inferior endplate of L3. Patients were stratified by Lenke classification into non-structural lumbar curves (Group 1, Lenke 1-2) and structural lumbar curves (Group 2, Lenke 3-6) and compared with age-matched controls (Group 3). Muscle size and composition were quantified using threshold-based methods, with measurements independently performed by two pediatric radiologists and interobserver reliability assessed using intraclass correlation coefficients. Non-parametric analyses were performed using Wilcoxon tests for group comparisons and univariate Spearman correlations for associations between lumbar muscle metrics and radiographic parameters, with statistical significance set at p&#x2009;<&#x2009;0.05. Eighty-three AIS patients (Group 1, n&#x2009;=&#x2009;31; Group 2, n&#x2009;=&#x2009;52) and 20 controls were included. Demographic characteristics were comparable between groups. Lumbar muscle bulk was largely preserved across AIS subtypes and controls, with minimal cross-sectional area asymmetry. In contrast, muscle composition showed distinct curve-type-specific patterns. Group 1 demonstrated marked concave-sided fatty infiltration of the psoas muscle, whereas Group 2 exhibited greater degeneration of paraspinal muscles, particularly the multifidus (p&#x2009;>&#x2009;0.05). Controls showed lower fatty infiltration and no side-to-side asymmetry. Quadratus lumborum morphology was relatively preserved, with modest concave-sided alterations in AIS. Associations between AIS muscle parameters, curve severity, flexibility, and spinal alignment were weak and not statistically significant after correction (p&#x2009;>&#x2009;0.05). Lumbar muscle alterations in AIS predominantly involve muscle composition rather than muscle bulk and follow curve-type-specific patterns consistent with localized adaptations to asymmetric loading. These findings support further longitudinal and multimodal studies to clarify the role of muscle composition in the pathophysiology and progression of spinal deformity.

Adolescent idiopathic scoliosis (AIS) is a three-dimensional deformity, yet the direction of controlling force applied in orthotic treatment remains largely empirical. Whether this force direction is aligned with patient-specific structural orientation has not been adequately evaluated in clinical cohorts. This retrospective study investigated the alignment between controlling force direction (CFD) and the plane of maximum curvature (PMC) and explored its relationship with first in-orthosis correction. A cohort of 265 patients with AIS treated with CAD/CAM-manufactured thoracolumbosacral orthoses was analyzed. CFD was estimated from digital orthosis models using transverse-plane analysis, and PMC orientation was derived from biplanar radiographs. Force-structure alignment was quantified as the angular difference between CFD and PMC. The study outcomes were changes in coronal Cobb angle and PMC-Cobb angle from baseline to the first in-orthosis radiograph. The mean CFD was 41.1&#xb0;&#xa0;&#xb1; 11.3&#xb0;, the mean PMC orientation was 66.0&#xb0;&#xa0;&#xb1; 14.9&#xb0;, the mean signed CFD-PMC difference was -24.9&#xb0;&#xa0;&#xb1; 17.6&#xb0;, and the mean absolute difference was 26.1&#xb0;&#xa0;&#xb1; 15.8&#xb0;, indicating a systematic posterior offset of CFD relative to PMC. In the analyses, absolute misalignment was not associated with first in-orthosis coronal Cobb change (r = -0.071, p = 0.248) but was associated with less favorable first in-orthosis PMC-Cobb change (r = 0.124, p = 0.045). The signed difference showed a similar association with the first in-orthosis PMC-Cobb change (r = -0.137, p = 0.026), whereas the corresponding coronal association was also non-significant. In an exploratory &#x2264;20&#xb0;&#xa0;grouping, aligned and misaligned cases showed similar coronal correction (-12.7&#xb0;&#xa0;vs. -13.3&#xb0;, p = 0.448), while the aligned group demonstrated numerically better PMC-Cobb correction (-14.0&#xb0;&#xa0;vs. -12.5&#xb0;, p = 0.112). These preliminary findings suggest that the force-structure alignment may be more obvious at the deformity-plane than the coronal plane in the first in-orthosis correction, although the early signal appears modest and exploratory.

Step-length asymmetry is a prevalent, energy-inefficient gait deviation in children with unilateral cerebral palsy (CP). While neuromotor impairments and energy efficiency factors are implicated in gait deviations, their combined predictive power on step-length asymmetry remains poorly understood. This study aimed to quantify the independent and synergistic predictive roles of specific neuromotor constraints and energetic efficiency variables in explaining step-length asymmetry in this population. Fifty-two children with unilateral CP (aged 8-18&#x2009;years; Gross Motor Function Classification System levels I - II) participated. Step-length asymmetry was defined as the absolute percentage difference between affected and less-affected limb step lengths, normalized to their mean. Neuromotor function was assessed through dorsiflexor strength, plantarflexor dynamic spasticity slope, passive dorsiflexion range, and ankle proprioceptive acuity. Energetic efficiency was evaluated using the metabolic cost of walking and self-selected walking speed. Hierarchical multiple linear regression demonstrated that the final model, incorporating neuromotor impairments and energy efficiency factors, accounted for 70% of the total variance in step-length asymmetry (R2&#x2009;=&#x2009;0.70, p&#x2009;<&#x2009;.001). Neuromotor impairments were primary drivers, explaining 58.8% of the variance (R2&#x2009;=&#x2009;0.588, p&#x2009;<&#x2009;.001), but adding energy efficiency factors provided a unique, statistically significant predictive contribution of 11.2% (&#x394;R2 = 0.112, p = .0008). The strongest individual predictors of step-length asymmetry were dorsiflexor weakness, dynamic spasticity slope, metabolic cost of walking, and self-selected walking speed. Step-length asymmetry in unilateral CP is a multifactorial phenomenon significantly predicted by specific neuromotor and energy efficiency factors. Importantly, the statistical dominance of dorsiflexor strength in our specific model should not be misconstrued as a clinical directive to deprioritize plantarflexor strengthening, given the undeniable biomechanical role of the plantarflexors in forward propulsion and contralateral step length. Nonetheless, these findings underscore the need for integrated rehabilitation strategies that simultaneously target dorsiflexor strength, dynamic spasticity, and gait efficiency (including walking speed and metabolic economy) to optimize gait symmetry and function in this population.

Early conception failure is a major contributor to infertility in dairy cows. Fatty acids (FAs) play critical roles in maintaining normal reproductive function. This study aimed to determine Long Chain Fatty Acids (LCFAs) and their derivatives in plasma and to explore their association with early pregnancy outcome in high producing dairy cows. Blood samples were collected from 36 inseminated cows at 30 days post-insemination (dpi). Pregnancy was diagnosed at both 30 dpi and 45 dpi. Plasma LCFA levels were quantified via gas chromatography-mass spectrometry (GC-MS). Cows that experienced conception failure or early embryonic death (before 45 dpi; n&#x2009;=&#x2009;25) had significantly higher concentrations (P&#x2009;<&#x2009;0.05) of oleic acid (OA), palmitic acid (PA), stearic acid (SA), and linoleic acid (LA) than cows carrying viable embryos at 45 dpi (n&#x2009;=&#x2009;11). Methylated LCFAs were detected only in the plasma of cows with healthy embryos at 45 dpi. The plasma OA: PA and LA: PA ratios exceeded 1 in cows with conception failure. Principal component analysis indicated that a component including LA and methylated FAs differed between cows that failed to conceive from those with viable embryos at 45 dpi. These findings reveal the composition of LCFAs and their derivatives in the cattle plasma and suggest an association between LCFAs and their methylated derivatives with early conception outcomes in dairy cows.

Measurement of soluble ligand targets of biotherapeutics can be challenging, especially when non-competing reagents are unavailable. This study aimed to develop a simple assay to quantify total soluble B-cell Maturation Antigen (sBCMA), including antibody-bound sBCMA, in serum when anti-BCMA antibody is present. A sample predilution strategy was coupled with a ligand-binding assay (LBA) to dissociate sBCMA from anti-BCMA antibody complexes and enable measurement of total sBCMA. A lower limit of quantitation (LLOQ) of 3&#x2009;ng/mL in neat serum was achieved in the presence of clinically relevant concentrations of anti-BCMA antibody less than 30&#x2009;&#xb5;g/mL. sBCMA serum levels were elevated in patients with multiple myeloma (MM) (mean 198.3&#x2009;ng/mL; range 3.3-2035.7&#x2009;ng/mL) compared with healthy subjects (mean 12.4&#x2009;ng/mL; range 2.9-18.4&#x2009;ng/mL). This dilution-based approach enabled accurate measurement of total sBCMA despite circulating anti-BCMA antibody. However, this sample predilution approach may or may not have general applicability for similar bioanalytical purposes, when candidate biotherapeutic levels are moderate, assay is highly sensitive, and the target protein levels are substantially elevated, as described in this case. Measuring soluble ligand targets of biotherapeutics can be difficult, especially when non-competing antibody reagents are unavailable. Herein, we report a simple sample dilution-based scheme coupled with a ligand-binding assay (LBA) to dissociate soluble B-cell maturation antigen (sBCMA) from anti-BCMA antibody complexes, and enable accurate measurement of total sBCMA, unbound or in complex with anti-BCMA antibody. Such a procedure was otherwise impossible due to the lack of non-competing reagents. A lower limit of quantitation (LLOQ) of 3ng/mL in neat serum was achieved in the presence of clinically relevant concentrations of anti-BCMA antibody. sBCMA levels in multiple myeloma (MM) patients&#x2019; serum were elevated (mean 198.3, range 3.3 to 2035.7ng/mL) compared to healthy subjects (mean 12.4, range 2.9 to 18.4ng/mL). This sample predilution approach may or may not have general applicability for similar bioanalytical purposes, when candidate biotherapeutic levels are moderate, assay is highly sensitive, and the target protein levels are substantially elevated, as described in this case.

Interatrial connections (IACs) may act as pathways sustaining atrial fibrillation, yet their role as ablation targets remains uncertain due to challenges in identifying IAC-dependent reentrant circuits. This study tracks reentrant activity along IACs, characterizes IAC-dependent reentries, and assesses the impact of in silico IAC ablation on reentry maintenance. Six patient-specific biatrial bilayer models were reconstructed from CT and MRI-derived geometries, each incorporating four IACs: Bachmann's bundle, fossa ovalis, upper posterior, and coronary sinus. The Courtemanche ionic model was used to simulate mild (M) and severe (S) AF-related electrical remodeling, with fibrosis burden ranging from 9.0% (M) to 27.6% (S). Across the 12 models, 110 sustained reentries were induced, followed by circumferential pulmonary vein isolation. Fifteen IAC ablation strategies were tested at three different timings. Critical pathways along the six possible interatrial loops were quantified. Tachycardia cycle length (TCL) and phase singularity (PS) clusters were analyzed before and after IAC ablation. Overall, 11.8% of reentries were IAC-dependent. Larger interatrial loops were the major contributors to critical pathway formation. IAC-dependent reentries exhibited more critical pathways, shorter TCL (194.2 vs 201.9 ms; &#x394;TCL=7.65 ms, p = 0.006), and more PS clusters in the RA body (8 [5-10] vs. 4 [2-6], p = 0.006). Ablation timing did not influence termination rates. We present the first framework to track reentrant activity along IACs. We identified IAC-dependent reentry characteristics that may guide patient stratification and targeted ablation strategies in clinical practice.