As Phase III trial costs and durations rise, pharmaceutical companies increasingly use quantitative methods to decide if a drug should progress beyond Phase II. A key method is the probability of success (PoS) for Phase III, calculated using the power function averaged across a treatment effect distribution estimated from Phase II. This paper explores PoS's role, particularly in moving from Phase II trials with putative surrogate endpoints to Phase III trials with clinical endpoints. Since the relationship between these endpoints is often unknown, expert input is necessary (prior elicitation). We propose the bivariate meta-analysis and a copula-based extension to characterize their relationship, using visual tools to simplify parameter elicitation. Specifically, we begin by eliciting the marginal distributions of the two quantities of interest. Then, to assist in eliciting the concordance parameter, we use the distribution of the treatment effect on the clinical endpoint conditional on the treatment effect on the putative surrogate. Our approach is illustrated in prophylactic vaccine development, linking immunological and clinical endpoints.
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Metabolic dysfunction-associated steatotic liver disease is increasingly recognized as a precursor to secondary hyperuricemia, significantly exacerbating metabolic burden. However, reliable tools for early risk stratification in MASLD patients remain limited. This study aimed to develop and validate a robust machine learning-based model to identify factors associated with concurrent hyperuricemia and develop a diagnostic nomogram for MASLD patients. A multicenter retrospective study was conducted involving 530 participants from two independent hospitals. The Least Absolute Shrinkage and Selection Operator regression was employed to screen characteristic variables. Seven machine learning algorithms, including Logistic Regression, Random Forest, and XGBoost, were constructed and compared. A quantitative nomogram was subsequently developed based on the optimal model. Six independent risk factors were identified: gender, body mass index, gamma-glutamyl transferase, serum creatinine concentration, serum triglycerides concentration, and the TyG index. Among the evaluated algorithms, the logistic regression model exhibited the superior balance of robustness and interpretability, achieving an area under the curve of 0.93 in the internal validation set and 0.67 in the external validation cohort. The constructed nomogram demonstrated satisfactory calibration and significant clinical utility, as confirmed by decision curve analysis, effectively distinguishing high-risk individuals across diverse populations. The novel logistic regression-based nomogram provides a practical, accurate, and cost-effective tool for the personalized risk assessment of concurrent hyperuricemia in MASLD patients, facilitating informed clinical decision-making and management.
To investigate the characteristics, surgery incidence, and outcomes of pigmentary glaucoma (PG), compared with primary open-angle glaucoma (POAG). Retrospective cohort study SUBJECTS: Eyes with PG and POAG defined by diagnosis codes (2013-2025) in the IRIS® Registry (Intelligent Research in Sight). Cumulative incidence of procedures (trabeculectomy, tube shunt surgery, minimally invasive glaucoma surgery (MIGS), laser trabeculoplasty (LTP), and cyclophotocoagulation) was estimated using the Kaplan-Meier method. Cumulative failure probability was estimated for matched eyes. Cumulative incidence of procedures in each diagnosis group. We identified 49,171 eyes with PG and 2,546,775 eyes with POAG. Compared to the POAG group, the PG group had more non-Hispanic White patients (89.2% vs 69.0%, P < 0.001). In the PG group, the percentage of severe stage was the highest in non-Hispanic Black patients (25.1%), followed by Asian (20.2%), Hispanic (19.7%), and non-Hispanic White patients (14.6%). The 4-year cumulative incidence of procedures, including LTP, was 22.2% (95% confidence interval: 21.8-22.6%) in PG and 19.5% (19.4-19.5%) in POAG (log-rank test, P < 0.001), with the highest incidence observed in the severe stage. Filtering or cyclodestructive procedures accounted for 12.8% and 10.3% of procedures in PG and POAG, respectively (P < 0.001). The cumulative probability of failure following LTP and MIGS was statistically higher in PG than in POAG (60.7% vs 58.2% and 66.7% vs 60.8% at 1 year, both P < 0.001). Combined trabeculectomy-cataract surgery had higher 1-year failure rates than standalone trabeculectomy in both PG (56.4% vs. 33.5%) and POAG (49.1% vs. 34.9%, both P < 0.001). Eyes with PG underwent glaucoma-related procedures more frequently than those with POAG, including filtering and cyclodestructive procedures. Although the proportion of Black or Asian patients among PG is relatively small compared to White patients, they are more frequently categorized as having severe disease, underscoring the need for closer monitoring and tailored management in these populations. Surgical failure was more frequent after LTP and MIGS in PG than in POAG. Combined trabeculectomy and cataract surgery had higher failure probability than standalone trabeculectomy in both the PG and POAG groups.
Nemtabrutinib is a Bruton's tyrosine kinase (BTK) inhibitor under clinical investigation in patients with hematologic malignancies, including chronic lymphocytic leukemia and small lymphocytic lymphoma (CLL/SLL). Nemtabrutinib plasma concentration data from 578 patients enrolled in phase 1 and 2 clinical studies, treated with doses from 5 to 80 mg daily were used to develop a preliminary population pharmacokinetic (PK) model. A two-compartment model with first-order absorption with time delay, and first-order elimination described the data accurately. A full covariate modeling approach was adopted to evaluate prespecified clinically meaningful covariates. The final model included the impact of body weight, sex, race, and disease indication on clearance (CL) and central volume of distribution; age, albumin, moderate CYP3A4 inducers, strong CYP3A4 inhibitors, mild hepatic and moderate renal impairment on CL; and acid reducing agents (ARAs) (i.e., proton pump inhibitors, H2 antagonists, and antacids) on bioavailability. The effect of CYP3A4 modulators and ARAs was estimated to be very low (< 4%) and none of the intrinsic factors were found to have a clinically significant impact on nemtabrutinib PK. Preliminary exposure-efficacy analysis in patients with CLL/SLL showed a significant trend of increased probability of best overall response with increased exposure to nemtabrutinib, while preliminary exposure-safety in patients with hematologic malignancies showed a significant trend between increased exposure and increased probability of any-grade drug-related adverse events (as assessed by investigator) and any-grade hypertension events. Taken together, these exposure-response analyses suggest that 65 mg daily is an appropriate dose for nemtabrutinib monotherapy treatment of patients with CLL/SLL.
We performed a systematic review and meta-analysis of randomised controlled trials (RCTs) to determine whether individualised intraoperative blood pressure (BP) management improves postoperative outcomes in patients having noncardiac surgery compared with routine BP management. A comprehensive literature search was performed across PubMed, Scopus, Web of Science, and Embase for relevant RCTs. The primary outcome was the incidence of postoperative acute kidney injury (AKI). We performed frequentist (random-effects model with Knapp-Hartung adjustment) and Bayesian meta-analyses. Ten RCTs (n=5842 patients) were included. Although individualised, compared with routine, intraoperative BP management resulted in significantly higher intraoperative BP (reflected by a reduction in the area under a mean arterial pressure (MAP) of 65 mm Hg; mean difference -44.5 mm Hg × min, 95% confidence interval [CI] -58.5 to -30.4, P=0.0005), it did not reduce the incidence of AKI (risk ratio [RR] 0.83, 95% CI 0.65-1.07, P=0.13), 30-day mortality (RR 0.78, 95% CI 0.35-1.75, P=0.44), or myocardial injury (RR 1.11, 95% CI 0.92-1.35, P=0.14). A significant reduction in postoperative delirium was observed (RR 0.46, 95% CI 0.25-0.83, P=0.02). Bayesian analysis indicated a 91% probability of any degree of AKI protection (RR<1); however, the probability of this benefit reaching a clinically meaningful threshold (RR<0.8) was low (39%). Compared with routine intraoperative BP management (typically targeting MAP ≥60-65 mm Hg), individualised intraoperative BP management resulted in higher intraoperative BP but did not significantly reduce postoperative AKI. Individualised intraoperative BP management might decrease the risk of postoperative delirium. CRD420251186093.
This study aimed to develop a dual-domain radiomics framework integrating probability-driven high-risk habitats and peritumoral microenvironmental features to accurately predict the aggressiveness of pheochromocytomas and paragangliomas (PPGLs). This retrospective study included 356 patients with abdominal PPGLs from four institutions, who were divided into a training set (n = 182) and two external test sets (n = 70, n = 104). Radiomic features were extracted from the whole-tumor and 1-mm peritumoral regions on contrast-enhanced CT images. Probability-driven habitat analysis utilizing a Support Vector Machine and K-means clustering was implemented to segment high-risk subregions. Following rigorous cascaded feature selection, a Random Forest-based fusion model was constructed to integrate key habitat and peritumoral features for predicting aggressiveness. Additionally, SHapley Additive exPlanations (SHAP) analysis was employed to evaluate feature importance and model interpretability. The habitat-peritumoral fusion model demonstrated superior predictive performance and robustness compared to traditional single-modality models, achieving area under the receiver operating characteristic curve values of 0.884 and 0.854 in external test sets 1 and 2, respectively. The model maintained excellent diagnostic efficacy across both >6 cm and ≤6 cm tumor subgroups. Furthermore, the model-derived risk score successfully stratified metastasis-free survival in the overall cohort (P < 0.001) and the clinically ambiguous ≤6 cm subgroup (P = 0.003), serving as an independent prognostic factor (HR = 10.73, P = 0.028). The fusion model is a robust, non-invasive tool for preoperatively identifying high-risk PPGLs. Particularly for tumors ≤6 cm where decision-making is challenging, it provides objective evidence to individualize surgical strategies and stratify postoperative surveillance.
Artificial intelligence (AI) offers a potential solution to radiologist shortages in breast cancer screening while maintaining diagnostic accuracy. Retrospective studies suggest AI performs comparably to human readers in detecting cancers, but no economic evaluations have yet used prospective trial data. We developed a de novo discrete-event simulation model to estimate the cost-effectiveness of integrating AI into the NHS screening pathway using evidence from a large prospective trial. The AI-only strategy generated a small incremental QALY gain of 0.00009 and reduced lifetime costs by £159.55 per woman invited, and had a 100% probability of being most cost-effective at the £20,000/QALY threshold. Replacing one human reader with AI also increased QALYs, by 0.00019, and reduced costs by £31.07. Triple reading (two humans plus AI) produced the largest QALY gain (0.00023) but increased costs by £72.79. All AI-based pathways reduced cancer deaths, shifted cancers from advanced (TNM stage 4) to earlier stages at detection, and increased the proportion of cancers detected by screening. Using AI in place of human readers is likely to be cost-effective, marginally improving health outcomes while reducing overall costs, with full replacement of both human readers being the most cost-effective screening strategy.
The diagnostic accuracy of computed tomography angiography (CTA) and its appropriate clinical indications remain unclear. We aimed to assess the diagnostic performance of CTA and identify clinical predictors to determine the optimal clinical indications for its use in patients with acute gastrointestinal (GI) bleeding. This large cohort study included patients who underwent CTA for suspected acute GI bleeding in Korea between October 2011 and December 2023. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of CTA were assessed. Multivariate analysis was conducted to identify the predictors of positive CTA findings, and a predictive nomogram was developed and validated. Of the 5,525 patients identified, 1,770 were included in the final analysis. CTA demonstrated low sensitivity (44.9%) and PPV (52.4%), with relatively high specificity (88.3%) and NPV (84.9%). Multivariate analysis identified male sex, use of antithrombotic agents, low hemoglobin level (<9.6 g/dL), elevated blood urea nitrogen level (≥29.9 mg/dL), hemodynamic instability, and presentation with hematemesis or hematochezia as independent predictors of positive CTA findings. A nomogram incorporating these variables showed good discrimination. The selective application of CTA based on clinical risk factors improved diagnostic sensitivity (47.3% at predicted probability ≥0.1, 56.5% at ≥0.2, and 69.5% at ≥0.3; all P < 0.001). Although CTA may be unsuitable as an initial diagnostic modality for acute GI bleeding, its selective use-guided by a clinical prediction model-can help identify patients most likely to benefit, thereby reducing inappropriate use and improving the diagnostic yield of CTA.
In view of the challenges such as feature redundancy and insufficient small sample risk prediction accuracy caused by the proliferation of multi-source heterogeneous data in the distribution network in the ubiquitous power Internet of Things environment, this study proposes a distribution network risk prediction method based on data mining and improved swarm intelligence algorithm fusion support vector machine, namely the DM-IS model. First, this study uses kernel principal component analysis technology to map high-dimensional nonlinear data to low-dimensional space to eliminate redundant feature. Then, the nonlinear adaptive weights and chaotic mutation strategy of the improved particle swarm optimization algorithm based on logistic mapping are introduced. A hybrid model that can accurately optimize the penalty factors and kernel parameters of support vector machines globally is constructed. The results revealed that this model not only effectively overcome the premature convergence defect in the parameter optimization process, but also achieved high-precision fitting with a median error of only 0.022 in 92.0 s under extreme small-sample constraints, outperforming baseline models by significantly narrowing the error distribution bandwidth. In actual engineering scenarios, its average detection time for typical faults such as transformer overload was shortened by 77.90%, and monthly operation and maintenance costs were reduced by 42.65%. In addition to confirming the efficacy of multi-source heterogeneous data fusion in enhancing forecast robustness, this study offers quantitative algorithm reference and decision support for conversing power systems from passive repair to active defense by continuously quantifying risk probability indices and dynamic early-warning time margins to drive predictive parameter adjustments and early equipment replacements prior to critical systemic failures.
Pregnancy-associated venous thromboembolism is a leading cause of maternal mortality, particularly in the postpartum period. Thrombotic risk is heightened by physiological adaptations of pregnancy, including hypercoagulability, venous stasis, and vascular compression. Clinical signs and symptoms of pregnancy-associated venous thromboembolism such as edema and shortness of breath are frequently normal findings in pregnancy. Given the overlap of pathology and physiology, there is a low threshold for evaluation in the emergency department. Computed tomography is the gold standard for diagnosing pulmonary embolism. Noninvasive testing strategies use ultrasound and D-dimer testing to avoid chest imaging in patients with a low pretest probability for pregnancy-associated pulmonary embolism. Advanced emergency clinicians can influence maternal and fetal outcomes through evidence-based test selection and treatment. Management of pregnancy-associated pulmonary embolism is guided by hemodynamic status. Patients with a low risk of short-term mortality are typically managed with anticoagulation for a minimum of 3 months and through 6 weeks postpartum. Hemorrhagic complications occur in less than one-third of patients treated with anticoagulation. The presence of hypotension, hypoxemia, and/or right ventricular dysfunction may necessitate urgent reperfusion. Reperfusion strategies include catheter-directed thrombolysis, mechanical or surgical thrombectomy, or, less frequently, systemic thrombolysis or extracorporeal membrane oxygenation. Early nonpharmacologic reperfusion should be considered for those who are at a higher risk of hemorrhagic complications.
Respiratory epidemics often place substantial pressure on intensive care units (ICU), which are continuously challenged to managing acute and life-threatening conditions under unpredictable workloads. During these periods, ICUs usually exhibit inefficient patient flows, treatment delays, and critical resource shortages. Proactive decision-making and precise interventions are therefore pivotal for patient survival and minimizing long-term sequelae. This paper proposes a robust approach combining Artificial Intelligence (AI), Bayesian Optimization, and Digital Twin (DT) to support ICU patient flow management. An eXtreme Gradient Boosting (XGBoost) algorithm is used to predict the patient transfer probability from the emergency department (ED) to the ICU within the next 24 h. Bayesian optimization is employed for efficient hyperparameter tuning of the XGBoost model. Then, the transfer predictions are inserted into a DT to verify ICU capacity for timely care and design interventions for process mismatches. A case study from a European healthcare group validates the proposed approach. The specificity of the prediction XGBoost model was 94.90% (CI 95% 91.72% - 97.11%), whereas the sensitivity was 81.55% (CI 95% 72.70% - 88.51%). Finally, the median ICU bed waiting time decreased to between 66.74 and 69.38 h after implementing a patient transfer policy with a partner hospital having available ICU beds. This study demonstrates the effectiveness of AI-DT in predicting the probability of ICU transfers, assessing the operational response of emergency wards and intensive care units, and crafting practical scenarios for enhancing patient flow management.
Cue-induced seeking engages neuronal ensembles within the nucleus accumbens core (NAcore), with neuronal ensembles defined here as neurons coactivated during specific behavioral experiences that have been implicated in cued-reinstatement. Although transient synaptic plasticity has been widely observed in unidentified ensemble and non-ensemble neuronal populations in the NAcore during reinstatement, its expression within behaviorally relevant ensembles remains unclear. Here, we used c-Fos-TRAP2-based tagging to characterize structural and functional synaptic plasticity within ensembles during cocaine-seeking in mice following cocaine intravenous self-administration, extinction, and cue-induced reinstatement. Structural plasticity was measured via spine confocal imaging, and functional changes were evaluated by AMPA/NMDA ratios using whole-cell electrophysiology across reinstatement time points. Ensemble neurons exhibited increased dendritic spine head diameter during cue-induced reinstatement and were functionally potentiated relative to non-ensemble neurons. Spine classification showed reduced mature spines during reinstatement in both ensemble and non-ensemble cells, suggesting morphological remodeling rather than new spine formation. Non-ensemble neurons showed no change in spine head diameter during reinstatement but did exhibit an increased AMPA/NMDA ratio during cued-reinstatement. Paired-pulse ratio analysis suggested that yoked-cocaine exposure decreased presynaptic vesicle release probability, while operant cocaine exposure had no effect. Ensemble neurons showed an elevated AMPA/NMDA ratio following cocaine exposure, regardless of whether intake was yoked or contingent. Together, these findings suggest that ensemble and non-ensemble neurons undergo distinct forms of synaptic plasticity during cue-induced reinstatement. By distinguishing ensemble-specific structural plasticity from non-ensemble functional plasticity, this study refines the current understanding of mechanisms underlying cue-induced relapse. SIGNIFICANCE STATEMENT: In preclinical models of substance use disorder drug seeking is associated with cue-induced reactivation of neuronal ensembles in the nucleus accumbens core. While transient synaptic plasticity has been extensively described in non-selective neuronal populations pooling recordings of both ensemble and non-ensemble neurons of the nucleus accumbens core, ensemble-specific plasticity remains unclear. Here, we combined c-Fos-TRAP2 tagging, confocal imaging, and slice electrophysiology to show that structural synaptic plasticity is selectively expressed in behaviorally relevant ensembles. By linking ensemble identity with structural and functional plasticity during cue-induced cocaine seeking, these findings refine current models of relapse and identify plasticity within the ensemble as a potential target for therapeutic intervention.
To identify risk factors associated with poor prognosis in patients with severe fever with thrombocytopenia syndrome (SFTS) and develop a prognostic model based on these factors. A retrospective analysis was conducted on 207 patients with SFTS admitted to Tongji Hospital from April 1, 2023, to July 18, 2024. Patients were categorized into survival (n = 133) and death (n = 74) groups based on their prognosis. Univariate and multivariate logistic regression analyses were performed to identify independent predictors of mortality, incorporating demographic characteristics and inflammatory biomarkers measured within 24 h of hospital admission. A nomogram model was constructed using R software based on the regression coefficients of the identified predictors. The model's discriminative ability was evaluated using the receiver operating characteristic (ROC) curve, with the area under the curve (AUC) and concordance index (C-index) calculated. Internal validation was performed using the Bootstrap resampling method (1,000 iterations).Furthermore, an external validation cohort comprising 55 patients with SFTS admitted to our hospital between August 2024 and February 2025 was retrospectively collected to evaluate the model's generalizability and stability. Age, viral load, procalcitonin (PCT), and interleukin-10 (IL-10) were identified as independent risk factors for poor prognosis. A nomogram model incorporating these four factors demonstrated robust predictive performance, yielding an AUC of 0.905 (95% CI, 0.862-0.949; P < 0.001).Internal and external validations confirmed the model's stability and strong prognostic performance in patients with SFTS. Decision curve analysis (DCA) showed that the nomogram yielded a higher net benefit over a wider threshold probability range than previous models in predicting SFTS mortality. This study provides a novel prognostic model for SFTS patients, which may aid in early risk stratification. However, its clinical utility and generalizability need to be further validated in larger cohorts. Not applicable.
The increasing penetration of photovoltaic distributed generation (PV-DG) in Radial Distribution Systems (RDSs) plays a vital role in achieving sustainable energy transition objectives; however, the inherent uncertainty associated with solar irradiance and load demand poses significant challenges to optimal planning and operation. This paper presents a stochastic optimization framework for PV-DG allocation in RDSs using the Barrel Theory-Based Optimizer (BTO). Uncertainties in solar irradiance and load demand are explicitly modeled using appropriate probability density functions and efficiently represented through a higher-order Point Estimate Method (PEM), which captures the essential statistical characteristics with a limited number of representative scenarios. The proposed framework simultaneously optimizes the location and capacity of PV-DG units to minimize real power losses and enhance voltage profile performance while ensuring system operational constraints are satisfied. The effectiveness of the proposed approach is validated on the 85-bus and the IEEE 118-bus RDSs, where the BTO exhibits superior convergence characteristics and enhanced solution robustness when compared with several benchmark optimization techniques, including the well-established Differential Evolution Algorithm (DEA), the recent Crocodile Ambush Optimization (CAO, 2025), and the Schrödinger Optimizer Algorithm (SOA, 2025). For the 85-bus RDS, the impact of integrating different numbers of PV units is systematically investigated. Simulation results confirm that the proposed BTO-based stochastic planning strategy significantly improves energy efficiency, voltage regulation, and loss reduction, thereby enhancing the overall sustainability of the RDS. For the 85-node RDS, the BTO achieves a noticeable reduction in average real power losses, outperforming DEA, CAO, and SOA by 2.55%, 4.10%, and 6.74%, respectively, when three PV units are installed. Additionally, for the case of four PV units, the proposed BTO yields even greater improvements, with loss reductions of 5.12%, 7.50%, and 14.12%, respectively, compared with the same benchmark algorithms. Furthermore, for five PV units, the BTO achieves much greater reduction, outperforming DEA, CAO, and SOA by 13.05%, 6.45%, and 32.31%, respectively, when three PV units are installed.
This study examines the long-term variations in the water-level time series of Lake Uluabat, located in western Türkiye, over the past six decades. Despite the decline in lake water level in recent years, the scarcity of reliable information remains a major problem in understanding this phenomenon. To overcome this limitation, monthly water-level observations spanning from October 1960 to September 2019 (708 months) were analyzed to explore temporal dynamics in trend, homogeneity, stationarity, frequency, persistence, entropy, and the reconstructed phase-space geometry. The analyses were conducted for the entire period (1960-2019) and six decadal intervals (i.e., 1960-1969, 1970-1979, 1980-1989, 1990-1999, 2000-2009, and 2010-2019) to identify regime shifts and decade-scale variability. The so-called autocorrelation function, mutual information, probability distributions, return period, and dimensional analysis were performed. Also, the teleconnections between lake-level fluctuations and 19 large-scale atmospheric-oceanic oscillation indices were investigated. Results indicated a persistent but gradually descending downward trend, accompanied by a rise in system entropy and short-term dependencies. This indicates increased complexity and dependence on external factors. So in a nutshell, the recent lake water-level properties indicate reduced degree of functionality and self-dependency of the hydrological regime. Yet, the temporal teleconnection between lake water level and the climatic oscillations showed stability. This indicates that the climate and the anthropogenic factors have a direct effect on the lake water level states, although in this case, the latter seems to have the upper hand.
The chemical composition, antioxidant activity and authenticity of commercially available rosemary (REO) and laurel (LEO) essential oils from the Slovenian market were investigated. In both EOs, 1,8-cineole was identified as the most abundant compound. It was determined that VOCs in lower concentrations contribute more to antioxidant activity compared to more abundant compounds. Key isotopic markers for adulteration detection were determined using compound-specific isotope analysis (CSIA). The sensitivity of the developed method was evaluated, demonstrating the best sensitivity for linalool in REO and for α-pinene in LEO, which means if the sample contains more than 19% of linalool (47% for α-pinene) synthetic fraction, it is almost certain (95% probability) that falsification will be suspected. When analysing commercial EOs declared as natural, the δ13CVPDB values indicated possible falsification of several VOCs in EOs. The developed methodology has shown great promise in the quality control of EOs, verifying labelling claims and detecting adulteration.
Traditional aptamer screening methods often prove ineffective for small molecule targets, primarily due to the inherent structural limitations of such compounds. Their simple architecture, limited functional groups, and restricted spatial complexity drastically reduce the probability of identifying nucleic acid sequences that bind with both high affinity and specificity. Consequently, the screening process becomes inefficient and labor-intensive, frequently failing to yield aptamers of satisfactory performance for practical applications. This represents a significant technical hurdle in expanding the use of aptamers in small-molecule detection and therapeutics. Based on this, this study innovatively proposes an aptamer design method based on single-nucleotide docking assembly, using the small molecule temicloxacin as an example. Through molecular dynamics simulations (50 ns, RMSD convergence threshold of 0.15 nm), the dynamic conformational characteristics of tilmicosin were analyzed. Subsequently, saturated docking was performed on four classes of mononucleotides, screening out 32 high-affinity mononucleotides (atomic contact distance ≤4 Å). Methods such as depth-first search algorithm (DFS) and weighted graph theory model were introduced to obtain the representative single nucleotides of eight classes of functional modules and linkage assembly, and finally 63 non-redundant candidate sequences were screened. Molecular docking results indicate that the optimal aptamer Til-14 exhibits high binding affinity with tilmicosin. with an affinity of 298.16 ± 95.588 nM measured via SYBR Green I fluorescence assay. Colloidal gold colorimetric analysis confirmed its high affinity (Kd = 279.323 ± 87.234 nM) and excellent specificity. This innovative method successfully addresses the key limitations of the traditional SELEX process in screening aptamers for small molecule targets. By enhancing the efficiency and specificity of selection, it not only facilitates the discovery of high-performance aptamers but also establishes a novel, generalizable framework for the construction of nucleic acid aptamers targeting other small molecules.
Lung cancer resection is curative but associated with postoperative morbidity and mortality. This study evaluated whether elevated blood eosinophil count (BEC) was associated with postoperative outcomes in early-stage lung cancer. This was a retrospective cohort study of consecutive adult patients undergoing lung resection for stage I and II non-small cell lung cancer in a large tertiary referral center from September 2017 to June 2021. Data were drawn from the institution's Data Warehouse. The primary outcome was 90-day healthcare utilization defined as emergency department visit or hospital readmission. Secondary outcomes were postoperative complications, index hospitalization length of stay, and 1-year survival. Preoperative 90-day BEC was categorized by a threshold of 200 cells/µL. Covariates were age, sex, smoking status, Charlson Comorbidity Index, chronic obstructive pulmonary disease (COPD), asthma, tumor size, nodal status, surgical approach, and blood results (white blood cells, hemoglobin, and creatinine). The main analyses were validated by a second international cohort. Log-Poisson with robust variance estimation and Cox proportional hazards regression models were fit for primary and secondary outcomes. Analyses were replicated for BEC thresholds of 150 and 300 cells/µL. Among 715 patients undergoing lung resection (median age = 69 years, 42% male, 29% with COPD), 146 patients (20%) had high preoperative BEC ≥ 200 cells/µL. BEC ≥ 200 cells/µL was associated with a higher rate of 90-day healthcare utilization:19% vs. 14% for BEC < 200 cells/µL. This association remained after adjustment (Risk Ratio [RR], 1.52; 95% Confidence Interval [CI], 1.02-2.25) and the validation cohort (RR, 2.23; 95% CI, 1.06-4.69). BEC as a continuous measure was also associated with the primary outcome in both cohorts: RR, 2.15 (95% CI, 1.49-3.12) and RR, 1.42 (95% CI, 1.10-1.94), respectively. BEC ≥ 200 cells/µL was associated with higher probability of death 1 year post-surgery (adjusted Hazard Ratio, 2.41; 95% CI, 1.08-5.35). There was no difference in the risk of postoperative pulmonary complications between high and low BEC (RR, 0.86; 95% CI, 0.58-1.27). Elevated preoperative BEC was associated with higher risk of postoperative healthcare utilization and lower 1-year survival after lung cancer resection among patients with or without respiratory disease.
Sm3+-doped antimony-tungsten-phosphate glasses (designated SWNSm) with the composition (40 - x) Sb2O3-10WO3-50NaPO3-xSm2O3 (x = 0.15, 0.30, 0.45, 0.60, and 0.75 mol%) were prepared by the conventional melt-quenching-annealing technique. Differential scanning calorimetry (DSC) and X-ray diffraction (XRD) analyses confirmed the amorphous nature and excellent thermal stability of the prepared glasses. Both experimental and theoretical elastic parameters, including Young's modulus (E) and Poisson's ratio (ν), were evaluated to verify that the incorporation of Sm3+ ions does not compromise the mechanical stiffness of the host glass. The measured density increased with increasing Sm2O3 content. Vibrational modes were identified using IR and FTIR spectroscopy. The optical bandgap values for all glass compositions were determined to lie in the range of 2.84-2.87 eV, confirming the insulating character of these glasses. Under 402 nm excitation, the down-conversion emission spectra exhibited characteristic transitions: 4G5/2 → 6H5/2 (560 nm), 4G5/2 → 6H7/2 (596 nm), 4G5/2 → 6H9/2 (643 nm), and 4G5/2 → 6H11/2 (707 nm). The observed up-conversion luminescence was interpreted in terms of excited-state absorption (ESA), energy transfer (ET), and cross-relaxation (CR) mechanisms. IR analysis revealed that the low phonon energy of the antimony-based glass host-evidenced by the dominant Sb-O-Sb stretching band at 602 cm-1-results in a reduced multiphonon relaxation rate, thereby facilitating efficient up-conversion processes. With increasing Sm3+ content, the measured fluorescence lifetime decreased from 1.815 to 1.710 ms, which is attributed to the increased concentration of OH- groups and the enhanced probability of ET among Sm3+ ions. The CIE chromaticity coordinates (x, y) fall within the orange-red region, indicating that these glasses are promising candidates for orange-red LED and solid-state laser applications.