Time-dependent Analysis Research Articles

Effect of Peripheral Interventions in Patients with Peripheral Artery Disease Receiving Rivaroxaban and Aspirin: Analyses from the XATOA Registry

To assess the characteristics and clinical outcomes of patients with lower extremity peripheral artery disease (PAD) in XATOA receiving dual pathway inhibition (DPI) with rivaroxaban 2.5 mg twice daily plus aspirin according to lower extremity revascularisation (LER) history. XATOA is an international, multicentre, prospective, single arm registry study. This subanalysis investigated patients with lower extremity PAD according to LER history. Patients with coronary artery disease, PAD, or both, receiving DPI were followed for 12 or more months. Baseline characteristics and clinical outcomes were assessed according to LER history. A time dependency analysis assessed outcomes by time between the most recent LER procedure and the start of DPI. A multivariate analysis assessed the influence of patient characteristics on clinical outcomes. In XATOA (n = 5 532), 2 820 (51.0%) patients had lower extremity PAD, of whom 1 736 (61.6%) had prior LER and 1 084 (38.4%) had no prior LER. Baseline characteristics were generally similar between patients with or without prior LER. A higher proportion of patients with prior LER experienced any treatment emergent clinical events compared with those without prior LER (15.0% vs. 9.4%, respectively), with greater differences observed between incidence rates of limb events, including major adverse limb events (9.06 vs. 4.09 events per 100 patient years, respectively). Similar rates of myocardial infarction, stroke, and major bleeding were observed in both subgroups. Clinical event rates were generally higher in patients who had previous LER for six months or less compared with patients who had previous LET for more than six months before starting DPI, regardless of LER type. Multivariate analyses showed that prior LER was predictive of limb events. This subanalysis of XATOA found that prior LER was associated with increased rates of limb events, consistent with results of COMPASS and VOYAGER PAD. Rates of bleeding were also low regardless of LER history and consistent with the findings from these trials.

Assessing survival in non-small cell lung cancer brain metastases after stereotactic radiosurgery: before and after the start of the targetable mutation era.

Targeted treatment options for non-small cell lung cancer (NSCLC) brain metastases (BMs) may be combined with stereotactic radiosurgery (SRS) to optimize survival. We assessed patient outcomes after SRS for NSCLC BMs, identifying survival trajectories associated with targetable mutations. In this retrospective time-dependent analysis, we analyzed median overall survival of patients who received ≥ 1 SRS courses for BM from NSCLC from 2001 to 2021. We compared survival of patients with and without targetable mutations based on clinical variables and treatment. Among the 213 patients included, 87 (40.8%) had targetable mutations-primarily EGFR (22.5%)-and 126 (59.2%) did not. Patients with targetable mutations were more often female (63.2%, p <.001) and nonsmokers (58.6%, p <.001); had higher initial lung-molGPA (2.0 vs. 1.5, p <.001) and lower cumulative tumor volume (3.7 vs. 10.6 cm3, p <.001); and received more concurrent (55.2% vs. 36.5%, p =.007) and total (median 3 vs. 2, p <.001) systemic therapies. These patients had lower mortality rates (74.7% vs. 91.3%, p <.001) and risk (HR 0.298 [95%CI 0.190-0.469], p <.001) and longer median overall survival (20.2 vs. 7.4 months, p <.001), including survival ≥ 3 years (p =.001). Survival was best predicted by SRS with tumor resection in patients with non-targetable mutations (HR 0.491 [95%CI 0.318-757], p =.001) and by systemic therapy with SRS for those with targetable mutations (HR 0.124 [95%CI 0.013-1.153], p =.067). The presence of targetable mutations enhances survival in patients receiving SRS for NSCLC BM, particularly when used with systemic therapies. Survival for patients without targetable mutations was longest with SRS and surgical resection. These results inform best practices for managing patients with NSCLC BM based on driver mutation status.

Phosphodiesterase-5 Inhibitors and Dementia Risk: A Real-World Study.

Biological and scarce epidemiological evidence suggested that phosphodiesterase-5 inhibitors (PDE5i) might reduce dementia risk. We aimed to examine the association between PDE5i and dementia using real-world data. Two retrospective cohorts within the database of Clalit, the largest healthcare provider in Israel (2005-2023), were studied. The first cohort included new daily users, older than 50 years of age, of low-dose tadalafil, prescribed for benign prostatic hypertrophy (BPH), propensity-score matched to new-users of alpha-1 blockers, and analyzed using 2-year lag time. The second cohort included patients with erectile dysfunction, with/without any PDE5i treatment, using time-dependent analysis. Individuals in the cohorts were followed through May 2023 for the occurrence of dementia. The first cohort included 5,204 tadalafil initiators propensity-score matched to 18,565 alpha-1 blockers initiators. There was no association between tadalafil use and dementia risk, HR = 0.99 (95% CI: 0.88-1.12), p = 0.927. Similar results were obtained in a competing risk analysis, and in a sensitivity analysis in which we restricted the cohort to patients older than 60 years at cohort entry. The second cohort of 133,336 patients with erectile dysfunction included new users and nonusers of any PDE5i. In a mean follow-up of 7.9 years, 8,631 patients were newly diagnosed with dementia. In a time-dependent multivariable analysis, PDE5i use was not associated with reduced dementia risk, HR = 0.95 (95% CI: 0.86-1.04). Results were not changed in sensitivity analyses (patients older than 60 years or stratification by PDE5i type). This study suggests that the use of PDE5 inhibitors is not associated with decreased risk of dementia.

Ezetimibe use and mortality after myocardial infarction: A nationwide cohort study

BackgroundThe inhibition of intestinal cholesterol absorption by ezetimibe improves outcomes after myocardial infarction (MI), yet real-world data on ezetimibe is scarce. We studied the usage of ezetimibe and association with outcome after MI. MethodsConsecutive MI patients in Finland (2010–2018) were retrospectively studied (N = 57,505; 65 % men; mean age 69 years). The study data were collected from national registries. The median follow-up was 4.5 (IQR 2.8–7.1) years. Between-group differences were adjusted for using multivariable regression. Ezetimibe use was studied with competing risk analyses. ResultsThe cumulative incidence of ezetimibe use was 3.7 % at 90 days, 13.4 % at 5 years, and 19.8 % at 10 years. Younger age was one of the strongest predictors of ezetimibe use (adj.sHR 6.67; CI 5.88–7.69 for patients aged <60 vs ≥80 years). Women were more likely to use ezetimibe during follow-up than men. The average proportion of patients using ezetimibe during follow-up was 6.8 %. (11.7 % at 10 years). Ezetimibe was discontinued by 43.6 % of patients during follow-up. Patients with early ezetimibe therapy after MI had lower all-cause mortality during follow-up (33.6% vs 45.1 %; adj.HR 0.77; CI 0.69–0.86; P < 0.0001). Early ezetimibe use was associated with lower mortality irrespective of sex, age, atrial fibrillation, diabetes, heart failure, malignancy, revascularization, or statin use. Ongoing ezetimibe therapy during follow-up was associated with lower mortality in a time-dependent analysis (adj.HR 0.53; CI 0.48–0.59; P < 0.0001). ConclusionsEzetimibe is associated with a lower risk of death after MI, yet its therapeutic use is limited, and discontinuation is frequent.

Finite Element Method Based Design of a Computer Application Interface for Thermal Analysis of Underground Power Cable System

The aim of thermal analysis of underground power cable studies is to optimize electrical and physical parameters of cable system and to transfer maximum power with minimum losses. For such problems, finite element method is mostly preferred, since they have complex geometry and requires multi-disciplinary (thermal and electrical) study. However, design, calculation and analysis of the problem is quite challenging since it requires advanced knowledge in related areas. Therefore, it becomes difficult particularly for engineers and students to study on thermal analysis of underground cables which has an important role in power system. In this context, it is aimed to design an application to perform thermal analysis of a typical medium voltage underground cable system. The application is designed using Comsol Multiphysics and allows users to perform two-dimensional, time-dependent thermal analyses. It also provides users to set several thermal, electrical and physical parameters as inputs and allows to compare thermal distribution results at desired points and regions. In the study, a series of thermal analyses are performed and results are presented for a sample loading scenario to indicate performance of the application. Besides, the application designed is used as a training material in a seminar in Yildiz Technical University, Electrical Engineering Department. Results showed that the application can be used as a useful tool for engineering education.

Inflammation, nutrition, and biological aging: The prognostic role of Naples prognostic score in nonalcoholic fatty liver disease outcomes

AimThis study aimed to evaluate the prognostic value of the Naples Prognostic Score (NPS) for predicting mortality in patients with nonalcoholic fatty liver disease (NAFLD) and compare its performance with established non-invasive fibrosis scores, including the fibrosis-4 index (FIB-4) and NAFLD fibrosis score (NFS). MethodsData from 10,035 NAFLD patients identified within the 1999–2018 National Health and Nutrition Examination Survey (NHANES) were analyzed. Cox regression models assessed the association between NPS and all-cause mortality, while time-dependent ROC analysis compared its predictive accuracy with FIB-4 and NFS. Mediation analysis explored the role of phenotypic age acceleration (PhenoAgeAccel). ResultsNPS was significantly associated with all-cause mortality, with each point increase corresponding to a 26 % increased risk (HR = 1.26, 95 % CI: 1.19–1.34). NPS demonstrated comparable predictive performance to FIB-4 and NFS, with further improvement when combined with either score (HRs of 2.03 and 2.11 for NPS + FIB-4 and NPS + NFS, respectively). PhenoAgeAccel mediated 31.5 % of the effect of NPS on mortality. ConclusionsThis study found that NPS has the potential to be an independent, cost-effective, and reliable novel prognostic indicator for NAFLD that may complement existing tools and help improve risk stratification and management strategies for NAFLD, thereby preventing adverse outcomes.

Remotely Controlled Surface Charge Modulation of Magnetoelectric Nanogenerators for Swift and Efficient Drug Delivery.

We have developed a highly efficient technique of magnetically controlled swift loading and release of doxorubicin (DOX) drug using a magnetoelectric nanogenerator (MENG). Core-shell nanostructured MENG with a magnetostrictive core and piezoelectric shell act as field-responsive nanocarriers and possess the capability of field-triggered drug release in a cancerous environment. MENGs generate a surface electric dipole when subjected to a magnetic field due to the strain-mediated magnetoelectric effect. The capability of directional magnetic field-assisted modulation of the surface electrical dipole of MENG provides a mechanism to create/break ionic bonds with DOX molecules, which facilitates efficient drug attachment and on-demand swift detachment of the drug at a targeted site. The magnetic field-assisted drug-loading mechanism was minutely analyzed using spectrophotometry and Raman spectroscopy. The detailed time-dependent analysis of controlled drug release by the MENG under unidirectional and rotating magnetic field excitation was conducted using field-emission scanning electron microscopy, energy-dispersive X-ray, and atomic force microscopic measurements. In vitro, experiments validate the cytocompatibility and magnetically assisted on-demand and swift DOX drug delivery by the MENG near MCF-7 breast cancer cells, which results in a significant enhancement of cancer cell killing efficiency. A state-of-the-art experiment was performed to visualize the nanoscale magnetoelectric effect of MENG using off-axis electron holography under Lorentz conditions.

Time-Dependent Deep Learning Prediction of Multiple Sclerosis Disability.

The majority of deep learning models in medical image analysis concentrate on single snapshot timepoint circumstances, such as the identification of current pathology on a given image or volume. This is often in contrast to the diagnostic methodology in radiology where presumed pathologic findings are correlated to prior studies and subsequent changes over time. For multiple sclerosis (MS), the current body of literature describes various forms of lesion segmentation with few studies analyzing disability progression over time. For the purpose of longitudinal time-dependent analysis, we propose a combinatorial analysis of a video vision transformer (ViViT) benchmarked against traditional recurrent neural network of Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) architectures and a hybrid Vision Transformer-LSTM (ViT-LSTM) to predict long-term disability based upon the Extended Disability Severity Score (EDSS). The patient cohort was procured from a two-site institution with 703 patients' multisequence, contrast-enhanced MRIs of the cervical spine between the years 2002 and 2023. Following a competitive performance analysis, a VGG-16-based CNN-LSTM was compared to ViViT with an ablation analysis to determine time-dependency of the models. The VGG16-LSTM predicted trinary classification of EDSS score in 6years with 0.74 AUC versus the ViViT with 0.84 AUC (p-value < 0.001 per 5 × 2 cross-validation F-test) on an 80:20 hold-out testing split. However, the VGG16-LSTM outperformed ViViT when patients with only 2years of MRIs (n = 94) (0.75 AUC versus 0.72 AUC, respectively). Exact EDSS classification was investigated for both models using both classification and regression strategies but showed collectively worse performance. Our experimental results demonstrate the ability of time-dependent deep learning models to predict disability in MS using trinary stratification of disability, mimicking clinical practice. Further work includes external validation and subsequent observational clinical trials.

Incidence of acute kidney injury and attributive mortality in acute respiratory distress syndrome randomized trials.

The development of acute kidney injury (AKI) after the acute respiratory distress syndrome (ARDS) reduces the chance of organ recovery and survival. The purpose of this study was to examine the AKI rate and attributable mortality in ARDS patients. We performed an individual patient-data analysis including 10 multicenter randomized controlled trials conducted over 20years. We employed a Super Learner ensemble technique, including a time-dependent analysis, to estimate the adjusted risk of AKI. We calculated the mortality attributable to AKI using an inverse probability of treatment weighting estimator integrated with the Super Learner. There were 5148 patients included in this study. The overall incidence of AKI was 43.7% (n = 2251). The adjusted risk of AKI ranged from 38.8% (95% confidence interval [CI], 35.7 to 41.9%) in ARMA, to 55.8% in ROSE (95% CI, 51.9 to 59.6%). 37.1% recovered rapidly from AKI, with a significantly lower recovery rate in recent trials (P < 0.001). The 90-day excess in mortality attributable to AKI was 15.4% (95% CI, 12.8 to 17.9%). It decreased from 25.4% in ARMA (95% CI, 18.7 to 32%), to 11.8% in FACTT (95% CI, 5.5 to 18%) and then remained rather stable over time. The 90-dayoverall excess in mortality attributable to acute kidney disease was 28.4% (95% CI, 25.3 to 31.5%). The incidence of AKI appears to be stable over time in patients with ARDS enrolled in randomized trials. The development of AKI remains a significant contributing factor to mortality. These estimates are essential for designing future clinical trials for AKI prevention or treatment.

Effects of ACE inhibitor/ARB therapy and long COVID on kidney disease: a retrospective cohort study using real-world data.

The association between angiotensin-converting enzyme inhibitors (ACEIs) or angiotensin II receptor blockers (ARBs) and severe acute respiratory syndrome coronavirus 2 susceptibility, particularly via ACE-2 receptor upregulation in the kidneys, raises concerns about potential kidney disease risks in long coronavirus disease (COVID) patients. This study explores the association of ACEI/ARB therapy on acute kidney injury (AKI), chronic kidney disease (CKD) and all-cause mortality in patients with and without long COVID. A retrospective cohort study using TriNetX datasets was conducted, with diagnoses of long COVID via International Classification of Diseases, Tenth Revision (ICD-10) codes and prescription for ACEI/ARB as the classification of four cohorts: long COVID ACEI/ARB users (LCAUs), long COVID ACEI/ARB non-users (LCANs), non-long COVID ACEI/ARB users (NLCAUs) and non-long COVID ACEI/ARB non-users (NLCANs). Multivariable stratified Cox proportional hazards regression models assessed the adjusted hazard ratios (aHRs) across groups. Additional analyses were conducted, including time-dependent exposure analysis and comparison with an active comparator, calcium channel blockers. Our study included 18 168 long COVID and 181 680 propensity score-matched non-long COVID patients from October 2021 to October 2023. ACEI/ARB use did not significantly affect the risk of AKI or CKD when comparing LCAUs with LCANs and NLCAUs with NLCANs. However, a protective effect against all-cause mortality was observed {aHR 0.79 [95% confidence interval (CI) 0.65-0.93]} in the NLCAU group compared with the NLCAN group. Conversely, long COVID was associated with increased risks of CKD [aHR 1.49 (95% CI 1.03-2.14)] and all-cause mortality [aHR 1.49 (95% CI 1.00-2.23)] when comparing LCANs with NLCANs. The additional analyses support the primary findings. ACEI/ARB treatment does not increase the incidence of CKD or AKI, regardless of long COVID status. However, long COVID itself is associated with increasing risks of kidney diseases and all-cause mortality.

Comparative cell viability of dentin-bonding adhesive systems on human dental pulp stem cells: time-dependent analysis

BackgroundRestorative materials are in prolonged contact with living tissues such as oral mucosa, dentin, pulp, periodontal, and periapical tissues. Therefore, the potentially harmful effects of these materials and their components on oral tissues should be evaluated before clinical use. This study aimed to compare the cell viability of different adhesive systems (ASs) on human dental pulp stem cells (hDPSCs).MethodsThree ASs that combining methacryloyloxydecyl dihydrogen phosphate (MDP) monomer with new hydrophilic amide monomers [Clearfil Universal Bond Quick(CUBQ), Kuraray Noritake], self-reinforcing 3D monomer [Bond Force II(BFII), Tokuyama)], and dual-cure property [Futurabond DC(FBDC), VOCO] were used. Three (n = 3) samples were prepared for each group. Dental pulp stem cells were isolated from ten patients’ extracted third molar teeth. Samples were incubated in Dulbecco’s modified Eagle’s medium (DMEM) for 24 h (h), 72 h, and 7 days (d) to obtain extracts. For the control group, cells were cultured without DBA samples. Cell viability of ASs extracts was measured using a cell proliferation detection kit (WST-1, Roche). Statistical analysis was performed using two-way ANOVA and post-hoc (Duncan) tests (p < 0.05).ResultsAt 24 and 72 h statistically significant differences were determined between control and BFII, control and FBDC groups (p < 0.05), while no differences between control and CUBQ groups (p > 0.05). On the 7th d, statistically significant differences were found between the control and experimental groups (p < 0.05), while no differences between experimental groups (p > 0.05). A statistically significant difference was detected for the BFII group over the three-time interval (p < 0.05). The lowest cell viability was observed for the FBDC group at 24 h, and the difference was statistically significant when compared with 72 h and 7th d (p < 0.05).ConclusionAll ASs showed different cell viability values at various exposure times. It should be taken into consideration that pH values, as well as the contents of ASs, have a significant effect on the cell viability.

Comparative Validity of the ALBI Grade and CTP Score in Predicting Overall Survival in Patients Receiving TACE Plus Sorafenib Therapy for Hepatocellular Carcinoma

Background: Hepatocellular carcinoma (HCC) significantly impacts global health, with liver function being a critical factor in patient prognosis. The ALBI grade and Child-Turcotte Pugh (CTP) score are both used to evaluate liver function in HCC patients, but their effectiveness in predicting survival outcomes varies. Objective: This study aimed to evaluate and compare the effectiveness of the ALBI grade and CTP score in predicting overall survival (OS) in HCC patients undergoing combined therapy with sorafenib and transarterial chemoembolization (TACE). Methods: Conducted at Jinnah Hospital Lahore and Hijaz Hospital between January 2019 and June 2023, this study included 103 HCC patients with CTP scores of 5 and 6. We analyzed the predictive values of the ALBI grade and CTP score for OS using multivariate analyses and time-dependent ROC curves. Results: Multivariate analysis indicated significant differences in OS among patients categorized by both scoring systems, with hazard ratios of 2.16 (P&lt;0.001) for the CTP score and 1.49 (P=0.035) for the ALBI grade. Time-dependent ROC analysis showed that the ALBI grade was more effective in discriminating long-term survival. It also remained a significant predictor of OS in a larger number of patient subgroups compared to the CTP score. Conclusion: The ALBI grade demonstrates superior prognostic stratification compared to the CTP score in HCC patients treated with TACE and sorafenib who have stable liver function.

Clinical impact of Academic Research Consortium for High Bleeding-Risk scores on clinical outcomes in patients with stable coronary artery disease undergoing percutaneous coronary intervention.

High bleeding risk (HBR), as defined by the Academic Research Consortium for High Bleeding Risk (ARC-HBR) criteria, has been recently reported to be associated with an increased risk of major bleeding events and cardiovascular events. We investigated the association between the ARC-HBR score and clinical outcomes in patients with stable coronary artery disease (CAD) who underwent percutaneous coronary intervention (PCI). We assessed 328 consecutive patients with stable CAD who underwent PCI between January 2017 and December 2020. We scored the ARC-HBR criteria by assigning 1 point to each major criterion and 0.5 points to each minor criterion. Patients were stratified into low (ARC-HBR score < 1), intermediate (1 ≤ ARC-HBR score < 2), and high (ARC-HBR score ≥ 2) bleeding-risk groups. The primary outcome measure was major adverse cardiovascular events (MACE), defined as a composite of all-cause death, nonfatal myocardial infarction, and nonfatal stroke. We compared the discriminative abilities of the ARC-HBR score with the Thrombolysis in Myocardial Infarction Risk Score for Secondary Prevention (TRS2°P) and ARC-HBR score with Coronary Revascularization Demonstrating Outcome Study in Kyoto (CREDO-Kyoto) thrombotic risk score. The mean patient age was 70.1 ± 10.2years (males, 76.8%). During the median follow-up period of 983 (618-1338) days, 44 patients developed MACE. Kaplan-Meier curves showed that a stepwise significant increase in the cumulative incidence of MACE as the ARC-HBR score increased (log-rank p < 0.001). In the time-dependent receiver-operating characteristic curve analysis for predicting MACE within 2years, the area under the curve (AUC) of the ARC-HBR score was significantly higher than that of the TRS2°P (AUC: 0.825 vs. 0.725, p value for the difference = 0.023) and similar to that of CREDO-Kyoto thrombotic risk score (AUC: 0.825 vs. 0.813, p value for the difference = 0.627). Conclusions: The ARC-HBR score adequately stratified future risk of MACE in patients with stable CAD who underwent PCI. The ARC-HBR score showed a higher discriminative ability for predicting mid-term MACE than the TRS2°P.

Time-dependent efficacy analysis of first-line immunotherapies for advanced non–small cell lung cancer

BackgroundMany randomized controlled trials (RCTs) and network meta-analyses have demonstrated that the progression-free survival (PFS) and overall survival (OS) of advanced non-small cell lung cancer (NSCLC) patients can be improved through combination immunotherapy or monotherapies. However, time-dependent analysis of the treatment effect is currently lacking. Thus, we aimed to evaluate the efficacy of first-line immunotherapy, and establish a hazard ratio function to reflect the time-varying progression or mortality risk of patients with NSCLC.MethodsSeventeen clinical trials were selected based on search strategy. Baseline characteristics, including the age, sex, smoking status, geographical region, and Eastern Cooperative Oncology Group (ECOG) performance status of patients, were balanced, resulting in ten immunotherapies from nine appropriate clinical trials to conduct treatment effect comparison.ResultsWe found that nivolumab plus ipilimumab (nivo + ipi) improved the PFS and OS over time. The hazard ratio of nivo + ipi, relative to that of pembrolizumab, decreased from 1.11 to 0.36 for PFS, and from 0.93 to 0.49 for OS over a 10-year period. In terms of the response to immunotherapy in patients with different PD-L1 expression levels, patients with PD-L1 > = 50% experienced lower rates of progression and a reduced mortality risk over time. The hazard ratio of patients with PD-L1 > = 50% relative to all of the patients decreased from 0.73 to 0.69 for PFS, and from 0.78 to 0.67 for OS.ConclusionsBased on the fact that time-dependent progression and mortality risk existed during the treatment duration, physicians should select a suitable treatment regimen for patients based on the hazard ratio.

Egg White and Eggshell Mortar Reinforcing a Masonry Stone Bridge: Experiments on Mortar and 3D Full-Scale Bridge Discrete Simulations

In this study, experimental and numerical investigations were conducted to examine the time-dependent creep and earthquake performance of the historical Plaka stone bridge, which was constructed in 1866 in Arta, Greece. During the original construction of the bridge in 1866, Khorasan mortar with an egg white additive was used between the stone elements. Furthermore, when the bridge underwent restoration in 2015, Khorasan mortar with an eggshell additive was employed between the stone elements. Consequently, two distinct 3D finite-difference models were developed for this study. In the first bridge model, egg white was used in the Khorasan mortar, replacing water at various proportions of 0%, 25%, 50%, 75%, and 100%. In contrast, for the second model, eggshell was incorporated into the Khorasan mixture at percentages of 25%, 50%, 75%, and 100%, relative to the lime amount. Subsequently, the mortars were subjected to curing periods of 1 day, 7 days, and 28 days, and their mechanical properties were determined through unconfined compression strength experiments. Taking into account the determined strengths of the mortars, the kn and ks stiffness values of the interface elements between the stone elements and Khorasan mortar were calculated. In the 3D model, each stone element was individually represented, resulting in a total of 1,849,274 stone elements being utilized. Non-reflecting boundary conditions were applied to the edge boundaries of the bridge model, and the Burger creep and Mohr–Coulomb material models was employed for time-dependent creep and seismic analyses, respectively. Subsequently, time-dependent creep analyses were conducted on the bridge, and seismic events that occurred in the region where the bridge was located were simulated to assess their impact. Based on the results of the time-dependent creep and seismic analyses, we observed that the use of 50% eggshell-mixed Khorasan mortar between the stone elements had a positive influence on the earthquake and creep behaviors of both restored and yet-to-be-restored historical bridges.

Ab Initio Characterization of the CO2-Water Interface Using Unsupervised Machine Learning for Dimensionality Reduction.

Precise characterization of the supercritical CO2-water interface under high pressure and temperature conditions is crucial for the geological storage of carbon dioxide (CO2) in deep saline aquifers. Molecular dynamics (MD) simulations offer a valuable approach to gaining insight into the CO2-water interface at a microscopic level. However, no attempt has been made to characterize the CO2-water interface with the accuracy afforded by ab initio calculations. In this study, we performed ab initio MD (AIMD) simulations to investigate the structural and dynamical properties of the CO2-water interface, comparing the results with those obtained from classical force-field MD (FF-MD) simulations. Molecular orientation at the interface was well reproduced in both AIMD and FF-MD simulations. Characteristic structural fluctuations of water at the interface were unveiled by applying multidimensional scaling and time-dependent principal component analysis to the AIMD trajectories; however, they were not prominent in the FF-MD simulations. Furthermore, our study demonstrated a marked difference in the residence time of molecules in the interface region between AIMD and FF-MD simulations, indicating that time-dependent properties of the CO2-water interface strongly depend on the description of the intermolecular forces.

Prediction of electronic density of states in guanine-TiO2 adsorption model based on machine learning

The electronic density of states is a property of the material that is extensively used in quantum systems in condensed matter physics. It refers to the energy level of the electrons in a solid crystal. One of the most current ways to compute it is by Density Functional Tight Binding (DFTB), given the geometry of the material. Nevertheless, this computation could be very computationally demanding, although applied to some materials with a very reduced number of atoms. This paper presents a method to deduce the electronic density of states, which is based on a neural network, thus, almost linear with respect to the number of atoms in the material. Specifically, we have applied our method to a metal oxide structure interacting with a nucleic base guanine. We have focused on stoichiometric and O-defective anatase TiO2 (101) surfaces. The data set of the electronic density of states needed to train the neural network has been obtained by a DFTB+ numerical solver given an initial molecular geometry model, which computed a track of time-dependent geometry and their associated electronic density of states. We validated that the predicted electronic density of states deduced by our method and by DFTB tends to be very similar, thus, opening the door to other computations such that introducing our method in the process of generating the time-dependent geometry analysis.

Impact of Graft-Versus-Host Disease on Relapse and Nonrelapse Mortality Following Posttransplant Cyclophosphamide-Based Transplantation

Following conventional graft-versus-host disease (GVHD) prophylaxis, the development of acute and/or chronic GVHD is associated with lower relapse rates. However, the effects of GVHD on relapse and non-relapse mortality following post-transplant cyclophosphamide (PTCy)-based GVHD prophylaxis have not been well studied. To this end, we analyzed the impact of acute and chronic GVHD following PTCy-based haploidentical donor transplantation (HIDT). The analysis included 335 consecutive HIDT recipients transplanted at a single institution between 2005 and 2021. Landmark analysis (LA) and time-dependent multivariable analysis (MVA) were utilized to study the impact of GVHD development on transplant outcome. Landmarks were defined as Day +100 for acute GVHD and one-year for chronic GVHD. Recipient characteristics included a median age of 50 (19-80) years, most commonly transplanted for acute leukemia[/MDS [242]. PBSC was the graft source in 81%, and regimen intensity was myeloablative in 49%. Median follow-up was 65 (23-207) months. In landmark analysis, development of grade 3 to 4 acute GVHD (versus 0-1) was associated with inferior 3-year overall survival (OS 47% versus 64%, P = .041), due to higher NRM (25% versus 10%, P = .013). In contrast, development of grade 2 acute GVHD had no significant effect on NRM or survival. When restricted to acute leukemia/MDS patients, development of grade II acute GVHD was associated with improved OS (79% versus 58%, P = .027) and a trend towards lower relapse (24% versus 36%, P = .08). Development of moderate-to-severe chronic GVHD resulted in significantly higher NRM (15% versus 4%, P = .010), but had no impact on relapse, DFS or OS. In Cox multivariate analysis (MVA), grade 3 to 4 acute GVHD and moderate-to-severe chronic GVHD were both associated with significantly higher NRM (HR 3.38, P < .001 and HR3.35, P < .001, respectively). In addition, grade 3 to 4 acute GVHD predicted worse OS (HR 1.80, P = .007) and DFS (HR 1.55, P = .041). In contrast, relapse was not impacted by acute or chronic GVHD in MVA. Grade 2 acute GVHD was not associated with transplant outcome in MVA. In summary, both grade 3 to 4 acute and moderate-to-severe chronic GVHD were associated with higher NRM after PTCy-based HIDT, without an effect on relapse risk. Methods of early identification of such patients in order to augment GVHD prophylaxis are clearly needed.

Efficient time-dependent reliability analysis for a railway bridge model

Efficient time-dependent reliability analysis for a railway bridge model

Design of a UWB patch antenna and performance evaluation in detecting brain tumors

In this study, a patch antenna is designed for easy fabrication and effective operation across a wide frequency range, making it particularly valuable for detecting brain tumors within a human head phantom using the monostatic technique. The study presents the proposed antenna's modeling in four stages, analyzing all essential parameters where a substrate material consisting of FR 4 is used. The antenna has a patch area of 0.27 λ × 0.21 λ and operates at 7.5 (free space), 7.48, and 7.47 GHz with a wide bandwidth of 3.188 GHz (free space), whereas in measurement, it operates in free space at 6.79 GHz with a bandwidth of 3.24 GHz, which is also categorized as an ultra-wide band. A comparative analysis is carried out between the proposed patch antenna and previous studies utilizing FR4 and similar substrate materials to enhance understanding. In this research, the analysis includes a human head phantom model, assessing key performance criteria such as SAR, return loss, and VSWR. The time-dependent analysis provides in this study insights into the dynamic behavior of the system in detecting brain tumor. The proposed antenna has been evaluated and yielded a maximum specific absorption rate (SAR) of 0.420985 W/kg for 1 gram of tissue in the head phantom. The performance of the patch antenna is evaluated using CST software, while the fabricated PCB antenna is tested in real-world conditions to ensure dependable operation in practical applications. The main challenge addressed in this work is achieving accurate brain tumor detection within a human head phantom model in a CST environment and using a UWB patch antenna fabricated via PCB technology.