Time-dependent Analysis Research Articles

Time-dependent sequential association rule-based survival analysis: A healthcare application

The analysis of event sequences with temporal dependencies holds substantial importance across various domains, including healthcare. This study introduces a novel approach that combines sequential rule mining and survival analysis to uncover significant associations and temporal patterns within event sequences. By integrating these techniques, we address the limitations linked to the loss of temporal information. The methodology extends traditional sequential rule mining by introducing time-dependent confidence functions, providing a comprehensive understanding of relationships between antecedent and consequent events. The incorporation of the Kaplan-Meier estimator of survival analysis enables the calculation of temporal distributions between events, resulting in time-dependent confidence functions. These confidence functions illuminate the probability of specific event occurrences considering temporal contexts. To present the application of the method, we demonstrated the usage within the healthcare domain. Analyzing the ICD-10 codes and the laboratory events, we successfully identified relevant sequential rules and their time-dependent confidence functions. This empirical validation underscores the potential of methodology to uncover clinically significant associations within intricate medical data.•The study presents a unique methodology that integrates sequential rule mining and survival analysis.•The methodology extends traditional sequential rule mining by introducing time-dependent confidence functions.•The application of the method is demonstrated within the healthcare domain.

Time-Dependent Probabilistic Seismic Hazard Analysis for Seismic Sequences Based on Hybrid Renewal Process Models

ABSTRACT Probabilistic seismic hazard analysis (PSHA) is a methodology with a long history and has been widely implemented. However, in the conventional PSHA and sequence-based probabilistic seismic hazard analysis (SPSHA) approaches, the occurrence of mainshocks is modeled as the homogeneous Poisson process, which is unsuitable for large earthquakes. To account for the stationary occurrence of small-to-moderate (STM) mainshocks and the nonstationary behavior of large mainshocks, we propose a time-dependent sequence-based probabilistic seismic hazard analysis (TD-SPSHA) approach by combining the time-dependent mainshock probabilistic seismic hazard analysis (TD-PSHA) and aftershock probabilistic seismic hazard analysis, consisting of four components: (1) STM mainshocks, (2) aftershocks associated with STM mainshocks, (3) large mainshocks, and (4) aftershocks associated with large mainshocks. The approach incorporates an exponential-magnitude, exponential-time model for STM mainshocks, and a renewal-time, characteristic-magnitude model for large mainshocks to assess the time-dependent hazard for mainshocks. Then nonhomogeneous Poisson process is used to model the occurrence of associated aftershocks, in which the aftershock sequences can be modeled using the Reasenberg and Jones (RJ) model or the epidemic-type aftershock sequence (ETAS) model. To demonstrate the proposed TD-SPSHA approach, a representative site of the San Andreas fault is selected as a benchmark case, for which five time-dependent recurrence models, including normal, lognormal, gamma, Weibull, and Brownian passage time (BPT) distributions, are chosen to determine the occurrence of large mainshocks. Then sensitivity tests are presented to show the effects on TD-SPSHA, including (1) time-dependent recurrence models, (2) mainshock magnitude, (3) rupture distance, (4) aftershock duration, (5) escaped time since the last event, and (6) future time interval. Furthermore, the bimodal hybrid renewal model is utilized by TD-SPSHA for another case site. The comparison results illustrate that the sequence hazard analysis approach ignoring time-varying properties of large earthquakes for long periods and the effects of associated aftershocks will result in a significantly underestimated hazard. The TD-SPSHA-based hazard curves using the ETAS model are larger than those of the RJ model. The proposed TD-SPSHA approach may be of significant interest to the field of earthquake engineering, particularly in the context of structural design or seismic risk analysis for the long term.

Role of Copper as Current Collectors in the Reductive Reactivity of Polymers for Anode-Free Lithium Metal Batteries - Insights from DFT and AIMD Studies

Understanding the role of current collectors (CCs) in the reductive reactivity of polymers on Li metal and the resultant solid electrolyte interphase (SEI) formation is essential for improving the performance of anode-free lithium metal batteries (AFLMBs). In this study, we have examined the reactivity of three polymeric hosts: poly(ethylene oxide) (PEO), poly(ε-caprolactone) (PCL), and poly(trimethylene carbonate) (PTMC) at Li metal supported on Cu surfaces (Li/Cu) using density functional theory (DFT) and ab initio molecular dynamics (AIMD) simulations. In particular, the effect of copper (Cu) CCs on polymer stability, electronic structure, and their reduction reactions is investigated and compared to that of pure Li (100) surface. Through time-dependent Bader charge transfer analysis, electron transfer is identified as the triggering factor for polymer reduction. Based on the simulations, we find that the Cu CCs have a significant influence on the charge distribution of the Li metals, which increases electron transfer to the polymers and thereby accelerates polymers reduction. This thereby leads to different reaction mechanisms as compared to on Li-metal. The findings suggest that utilization of Cu CCs avoid production of CO molecules and improves the quality of the formed SEI layer. Figure 1

INFLUENCE OF FUSED DEPOSITION MODELING REGIME PARAMETERS ON MANUFACTURING TIME OF UAV PARTS

Purpose. Investigate the regularities of FDM process parameters influence on the manufacturing time of parts.
 Research methods. The samples for research were produced by the FDM method on a Profi+midi 3D printer. Slic3rPE software were used for CAD model slicing and G-code preparation. The samples were printed using ABS+ filament. The STATISTICA software package was used for statistical processing of the results.
 Results. The influence of different combinations of FDM process parameters (printing speed, layer height, infill geometry, infill density) on the manufacturing time of products was examined. The main factors affecting the manufacturing time were established: printing speed, layer height, infill density and the interaction of these factors
 Scientific novelty. Analysis of the manufacturing time dependence on the layer height and the infill density showed that when selecting a layer height of 0.15 mm and 25 % infill and a layer height of 0.3 mm and 100% infill, the manufacturing time turned out to be nearly identical. It can be concluded that for a lower layer height, increasing the infill density significantly increased the manufacturing time, while setting a higher layer and increasing the infill density led to a small increase in the manufacturing time. It was found that for a layer height of 0.15 mm at a printing speed of 40 mm/s, the manufacturing time significantly increased compared to a printing speed of 80 mm/s, while when selecting a layer height of 0.3 mm, the manufacturing time is less and a decrease in the printing speed led to a small increase of manufacturing time compared to a layer height of 0.15 mm. It was established that an increase in printing speed led to a decrease in manufacturing time and an increase in infill density led to an increase in manufacturing time. Thus, the manufacturing time at a printing speed of 40 mm/s and infill density of 25 % differed slightly from a printing speed of 80 mm/s and infill density of 100 %.
 Practical value. A regression equation was obtained which allowed predicting the influence of the FDM process parameters on the manufacturing time of parts.

Time-dependent and spatio-temporal statistical analysis of seismicity: application on the complete data set of the 2010 Beni–Ilmane earthquake sequence

SUMMARY The Beni–Ilmane (BI) seismic sequence, situated in the north-central region of Algeria, began on 2010 May 14 with a main shock of ML 5.4 followed by two other shocks on May 16 and 23 of ML 5.3 for both. Using the complete data set from May 14 to August 31 and the Epidemic Type Aftershock Sequences (ETAS) model to separate background from aftershocks contribution gave a first insight around the uncertainty that surrounds the causes and mechanisms of the seismicity. According to our findings, two phases have been determined, the first one, beginning from May 14, shows low b- and p-values with most of the seismicity being self-triggered. In contrast, the second phase, beginning from May 23, demonstrates an increase of both the b- and p-values with a high number of background events. In the second phase, the background contribution involves 53 per cent of all seismic activity after May 23’s peak which is high compared to typical main shock–aftershocks sequences. A possible explanation is that the main shocks began or assisted aseismic processes in addition to causing aftershocks. A sealed source at depth may have been broken by the third main shock, opening the way for the following incursion of highly pressurized fluids (hydrocarbures) confirmed by a high Vp/Vs ratios.

Prognostic Value of Nighttime Double Product in Nondialysis Chronic Kidney Disease With Hypertension.

Both nighttime systolic blood pressure and pulse rate are associated with adverse outcomes in patients with chronic kidney disease (CKD). However, nighttime double product (DP), which is the product of nighttime systolic blood pressure and pulse rate, has not yet been investigated in this context. The present study aimed to explore the prognostic value of nighttime DP for adverse outcomes in patients with CKD and hypertension. This retrospective cohort study included a total of 1434 patients with nondialysis CKD complicated by hypertension. The patients were enrolled in Zhuhai and Guangzhou, China, with a median follow-up of 23.8 months. Patient enrollment for the high or low nighttime DP group was performed on the basis of the cutoff value determined by time-dependent receiver operator characteristic curve analysis. The primary end point was a composite of major cardiovascular and cerebrovascular events, and the secondary end point was all-cause death and composite renal end point. The 24-hour circadian DP rhythm was established via multiple-component cosinor analysis. Cox regression was used to explore the association between nighttime DP and adverse outcomes. The DP of nondialysis patients with CKD and hypertension showed a diurnal rhythm, which varied with renal function. After adjustment, high nighttime DP was associated with a higher risk for major cardiovascular and cerebrovascular events (hazard ratio [HR], 5.823 [95% CI, 2.382-14.233]), all-cause death (HR, 4.978 [95% CI, 2.205-11.240]), and composite renal event (HR, 1.661 [95% CI, 1.128-2.447]), compared with low nighttime DP. These associations were independent of nighttime systolic blood pressure and PR. The present cohort study demonstrated that DP had diurnal fluctuations and nighttime DP was an important prognostic factor in nondialysis patients with CKD and hypertension, outperforming traditional risk factors, including systolic blood pressure and pulse rate.

Risk of readmission and death after hospitalization for worsening heart failure: Role of post-discharge follow-up visits in a real-world study from the Grand Est Region of France.

Patients who experience hospitalizations due to heart failure (HF) face a significant risk of readmission and mortality. Our objective was to evaluate whether the risk of hospitalization and mortality following discharge from HF hospitalization differed based on adherence to the outpatient follow-up (FU) protocol comprising an appointment with a general practitioner (GP) within 15 days, a cardiologist within 2 months or both (termed combined FU). We studied all adults admitted for a first HF hospitalization from 2016 to 2020 in France's Grand Est region. Association between adherence to outpatient FU and outcomes were assessed with time-dependent survival analysis model. Among 67 476 admitted patients (mean age 80.3 ± 11.3 years, 53% women), 62 156 patients (92.2%) were discharged alive and followed for 723 (317-1276) days. Combined FU within 2 months was used in 21.1% of patients, with lower rates among >85 years, women, and those with higher comorbidity levels (p < 0.0001 for all). Combined FU was associated with a lower 1-year death or rehospitalization (adjusted hazard ratio [HR] 0.91, 95% confidence interval [CI] 0.88-0.94, p < 0.0001) mostly related to lower mortality (adjusted HR 0.65, 95% CI 0.62-0.68, p < 0.0001) whereas HF readmission was higher (adjusted HR 1.19, 95% CI 1.15-1.24, p < 0.0001). When analysing components of combined FU separately, 1-year mortality was more related to cardiologist FU (HR 0.65, 95% CI 0.62-0.67, p < 0.0001), than GP FU (HR 0.87, 95% CI 0.85-0.90, p < 0.0001). Combined FU is carried out in a minority of patients following HF hospitalization, yet it is linked to a substantial reduction in 1-year mortality, albeit at the expense of an increase in HF hospitalizations.

Exploring the immune microenvironment of osteosarcoma through T cell exhaustion-associated gene expression: a study on prognosis prediction.

Osteosarcoma is a highly aggressive type of bone cancer with a poor prognosis. In the tumor immune microenvironment, T-cell exhaustion can occur due to various factors, leading to reduced tumor-killing ability. The purpose of this study was to construct a prognostic model based on T-cell exhaustion-associated genes in osteosarcoma. Patient data for osteosarcoma were retrieved from the TARGET and GEO databases. Consensus clustering was employed to identify two novel molecular subgroups. The dissimilarities in the tumor immune microenvironment between these subgroups were evaluated using the "xCell" algorithm. GO and KEGG analyses were conducted to elucidate the underlying mechanisms of gene expression. Predictive risk models were constructed using the least absolute shrinkage and selection operator algorithm and Cox regression analysis. To validate the prognostic significance of the risk gene expression model at the protein level, immunohistochemistry assays were performed on osteosarcoma patient samples. Subsequently, functional analysis of the key risk gene was carried out through in vitro experimentation. Four gene expression signatures (PLEKHO2, GBP2, MPP1, and VSIG4) linked to osteosarcoma prognosis were identified within the TARGET-osteosarcoma cohort, categorizing patients into two subgroups. The resulting prognostic model showed strong predictive capability, with area under the receiver operating characteristic curve (AUC) values of 0.728/0.740, 0.781/0.658, and 0.788/0.642 for 1, 3, and 5-year survival in both training and validation datasets. Notably, patients in the low-risk group had significantly higher stromal, immune, and ESTIMATE scores compared to high-risk counterparts. Additionally, a nomogram was developed, exhibiting high accuracy in predicting the survival outcome of osteosarcoma patients. Immunohistochemistry, Kaplan-Meier, and time-dependent AUC analyses consistently supported the prognostic value of the risk model within our osteosarcoma patient cohort. In vitro experiments provided additional validation by demonstrating that the downregulation of GBP2 promoted the proliferation, migration, and invasion of osteosarcoma cells while inhibiting apoptosis. The current study established a prognostic signature associated with TEX-related genes and elucidated the impact of the pivotal gene GBP2 on osteosarcoma cells via in vitro experiments. Consequently, it introduces a fresh outlook for clinical prognosis prediction and sets the groundwork for targeted therapy investigations in osteosarcoma.

Retracted: A nomogram for predicting in-hospital overall survival of hypertriglyceridemia-induced severe acute pancreatitis: A single center, cross-sectional study

BackgroundHypertriglyceridemia-induced severe acute pancreatitis (HTG-SAP) is a type of pancreatitis characterized by an abnormal elevation of plasma triglyceride. HTG-SAP has been associated with various complications and a high mortality rate. In this study, we established a nomogram for predicting the overall survival (OS) of HTG-SAP patients during hospitalization. Methods128 HTG-SAP cases hospitalized at the Affiliated Huadu Hospital, Southern Medical University, from 2019 to 2022 were analyzed retrospectively. A nomogram including prognostic factors correlated with OS during hospitalization was established by multivariate Cox regression analysis. We internally validated the nomogram using time-dependent (at 1-, 2-, and 3- months) survival receiver operating characteristic (SROC) and calibration curve with 500 iterations of bootstrap resampling. Time-dependent decision curve analysis (DCA) was employed to validate the clinical value of the nomogram. ResultsMultivariate Cox regression indicated that serum triglyceride, red blood cell distribution width (RDW), lactic acid, and interleukin-6 (IL6) were independent prognostic factors for OS of HTG-SAP patients during hospitalization and were used to construct a nomogram. The time-dependent area under the curve (AUC) values at 1-, 2-, and 3- months were 0.946, 0.913, and 0.929, respectively, and the Concordance index (C-index) of the nomogram was 0.916 (95%CI 0.871–0.961). The time-dependent calibration curves indicated good consistency between the observed and predicted outcomes. The time-dependent DCAs also revealed that the nomogram yielded a high clinical net benefit. After stratifying the included cases into two risk groups based on the risk score obtained from the nomogram, the high-risk group exhibited a significantly inferior overall survival (OS) compared to the low-risk group (p < 0.0001). ConclusionsOur nomogram exhibited good performance in predicting the overall survival of HTG-SAP patients during hospitalization.

Time-Dependent Unavailability Exploration of Interconnected Urban Power Grid and Communication Network

This paper presents a time-dependent reliability analysis created for a critical energy infrastructure use case, which consists of an interconnected urban power grid and a communication network. By utilizing expert knowledge from the energy and communication sectors and integrating the renewal theory of multi-component systems, a representative reliability model of this interconnected energy infrastructure, based on real network located in the Czech Republic, is established. This model assumes reparable and non-reparable components and captures the topology of the interconnected infrastructure and reliability characteristics of both the power grid and the communication network. Moreover, a time-dependent reliability assessment of the interconnected system is provided. One of the significant outputs of this research is the identification of the critical components of the interconnected network and their interdependencies by the directed acyclic graph. Numerical results indicate that the original design has an unacceptable large unavailability. Thus, to improve the reliability of the interconnected system, a slightly modified design, in which only a limited number of components in the system are modified to keep the additional costs of the improved design limited, is proposed. Consequently, numerical results indicate reducing the unavailability of the improved interconnected system in comparison with the initial reliability design. The proposed unavailability exploration strategy is general and can bring a valuable reliability improvement in the power and communication sectors.

Time-dependent association between STOPP and START criteria and gastrointestinal bleeding in older patients using routinely collected primary care data

Purpose Only few studies have assessed the preventive effect of the STOPP/START criteria on adverse events. We aim to quantify 1) the association between nonadherence to STOPP/START criteria and gastrointestinal bleedings, and 2) the association between exposure to the potentially harmful START-medications and gastrointestinal bleedings. Design A retrospective cohort study using routinely collected data of patients aged ≥ 65 years from the electronic health records (EHR) of 49 general practitioners (GPs) in 6 GP practices, from 2007 to 2014. The database is maintained in the academic research network database (AHA) of Amsterdam UMC, the Netherlands. Methods Gastrointestinal bleedings were identified using ICPC codes and free text inspections. Three STOPP and six START criteria pertaining to gastrointestinal bleedings were selected. Cox proportional hazards regression with time-dependent covariate analysis was performed to assess the independent association between nonadherence to the STOPP/START criteria and gastrointestinal bleedings. The analysis was performed with all criteria as a composite outcome, as well as separately for the individual criteria. Results Out of 26,576 participants, we identified 19,070 Potential Inappropriate Medications (PIM)/Potential Prescribing Omission (PPO) instances for 3,193 participants and 146 gastrointestinal bleedings in 143 participants. The hazard ratio for gastrointestinal bleedings of STOPP/STARTs, taken as composite outcome, was 5.45 (95% CI 3.62–8.21). When analysed separately, two out of nine STOPP/STARTs showed significant associations. Conclusion This study demonstrates a significant positive association between nonadherence to the STOPP/START criteria and gastrointestinal bleeding. We emphasize the importance of adherence to the relevant criteria for gastrointestinal bleeding, which may be endorsed by decision support systems.

Danshensu inhibits SARS-CoV-2 by targeting its main protease as a specific covalent inhibitor and discovery of bifunctional compounds eliciting antiviral and anti-inflammatory activity

The coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has posed a serious threat to human. Since there are still no effective treatment options against the new emerging variants of SARS-CoV-2, it is necessary to devote a continuous endeavor for more targeted drugs and the preparation for the next pandemic. Salvia miltiorrhiza and its active ingredients possess wide antiviral activities, including against SARS-CoV-2. Danshensu, as one of the most important active ingredients in Salvia miltiorrhiza, has been reported to inhibit the entry of SARS-CoV-2 into ACE2 (angiotensin-converting enzyme 2)-overexpressed HEK-293T cells and Vero-E6 cells. However, there is a paucity of information regarding its detailed target and mechanism against SARS-CoV-2. Here, we present Danshensu as a covalent inhibitor of 3-chymotrypsin-like protease (3CLpro) against SARS-CoV-2 by the time-dependent inhibition assay (TDI) and mass spectrometry analysis. Further molecular docking, site-directed mutagenesis, circular dichroism (CD) and fluorescence spectra revealed that Danshensu covalently binds to C145 of SARS-CoV-2 3CLpro, meanwhile forming the hydrogen bonds with S144, H163 and E166 in the S1 site. Structure-based optimization of Danshensu led to the discovery of the promising compounds with good inhibitory activity and microsomal stability in vitro. Due to Danshensu inhibiting lung inflammation in the mouse model, we found that Danshensu derivatives also showed better anti-inflammatory activity than Danshensu in lipopolysaccharide (LPS)-stimulated RAW264.7 macrophage cells. Thus, our study provides not only the clue of the efficacy of Salvia miltiorrhiza against SARS-CoV-2, but also a detailed mechanistic insight into the covalent mode of action of Danshensu for design of covalent inhibitors against SARS-CoV-2 3CLpro, highlighting its potential as a bifunctional molecule with antivirus and anti-inflammation.

Venetoclax–based low intensity therapy in molecular failure of NPM1-mutated AML

AbstractMolecular failure in NPM1-mutated acute myeloid leukemia (AML) inevitably progresses to frank relapse if untreated. Recently published small case series show that venetoclax combined with low-dose cytarabine or azacitidine can reduce or eliminate measurable residual disease (MRD). Here, we report on an international multicenter cohort of 79 patients treated for molecular failure with venetoclax combinations and report an overall molecular response (≥1-log reduction in MRD) in 66 patients (84%) and MRD negativity in 56 (71%). Eighteen of 79 patients (23%) required hospitalization, and no deaths were reported during treatment. Forty-one patients were bridged to allogeneic transplant with no further therapy, and 25 of 41 were MRD negative assessed by reverse transcription quantitative polymerase chain reaction before transplant. Overall survival (OS) for the whole cohort at 2 years was 67%, event-free survival (EFS) was 45%, and in responding patients, there was no difference in survival in those who received a transplant using time-dependent analysis. Presence of FLT3-ITD mutation was associated with a lower response rate (64 vs 91%; P < .01), worse OS (hazard ratio [HR], 2.50; 95% confidence interval [CI], 1.06-5.86; P = .036), and EFS (HR, 1.87; 95% CI, 1.06-3.28; P = .03). Eighteen of 35 patients who did not undergo transplant became MRD negative and stopped treatment after a median of 10 months, with 2-year molecular relapse free survival of 62% from the end of treatment. Venetoclax–based low intensive chemotherapy is a potentially effective treatment for molecular relapse in NPM1-mutated AML, either as a bridge to transplant or as definitive therapy.

Impact of sex on antidepressant discontinuation in groups of similar cytochrome P450 phenotypes.

Although there are studies assessing reasons for antidepressant discontinuation, little is known about the impact of sex differences or cytochrome P450 phenotypes. Our objective is to assess discontinuation rates between males and females and whether CYP450 phenotype influences discontinuation. This is a retrospective review of patients previously enrolled in the Right Drug, Right Dose, Right Time: Using Genomic Data to Individualize Treatment database with major depressive disorder. Patients were evaluated for antidepressants trialed between January 1, 2009, and September 30, 2019. Survival analyses with competing risks were used to analyze discontinuation reasons. A Kaplan-Meier estimation method was used to assess the time to discontinuation and discontinuation rates. Analyses were also completed to assess discontinuation between men and women by phenotypic groups. All tests were two-sided, and p-values ≤ .05 were considered statistically significant. There were 620 antidepressant discontinuation events discovered from 1015 antidepressant trials included. Overall, the median time to discontinuation for males was 2.6 years and 1.9 years for females (hazard ratio [HR] 0.97 [95% confidence interval (CI): 0.80, 1.19], p = .77). The risk of discontinuation was not different between males and females in any of the phenotype groups, which was consistent in the multivariable analyses. Concomitant use of medications that inhibited or induced antidepressant metabolism increased the overall risk of discontinuation (HR 1.45, 95% CI [1.06, 1.99], p = .020) in a time-dependent analysis. We did not detect a significant difference in risk of antidepressant discontinuation rates between males and females even when accounting for cytochrome P450 phenotype. Future studies should account for whether medications that inhibit or induce antidepressant metabolism may be a crucial factor in antidepressant discontinuation.

Synergistic effects of immune checkpoint inhibitors in combination with stereotactic radiosurgery for patients with lung cancer and brain metastases: a propensity score-matched analysis.

Stereotactic radiosurgery (SRS) is the mainstay treatment for brain metastases (BMs) from lung cancer. In recent years, immune checkpoint inhibitors (ICIs) have been applied to metastatic lung cancer and have contributed to improved outcomes. The authors investigated whether SRS with concurrent ICIs for lung cancer BMs prolongs overall survival (OS), improves intracranial disease control, and raises safety concerns. Patients who underwent SRS for lung cancer BMs at Aizawa Hospital between January 2015 and December 2021 were included. Concurrent use of ICIs was defined as no more than 3 months between SRS and ICI administration. The two treatment groups, which had a similar likelihood of receiving concurrent ICIs, were generated by propensity score matching (PSM; match ratio 1:1) based on 11 potential prognostic covariates. Patient survival and intracranial disease control were compared between the groups with and without concurrent ICIs (ICI + SRS vs SRS) by time-dependent analyses, taking into account competing events. Five hundred eighty-five patients with lung cancer BM (494 with non-small cell lung cancer and 91 with small cell lung cancer) were eligible. Of those patients, 93 (16%) received concurrent ICIs. Two groups, each with 89 patients (ICI + SRS group and SRS group), were generated by PSM. The 1-year survival rates of the ICI + SRS and SRS groups after the initial SRS were 65% and 50% and the median survival times were 16.9 and 12.0 months, respectively (HR 0.62, 95% CI 0.44-0.87, p = 0.006). The 2-year cumulative neurological mortality rates were 12% and 16%, respectively (HR 0.55, 95% CI 0.28-1.10, p = 0.091). The 1-year intracranial progression-free survival rates were 35% and 26% (HR 0.73, 95% CI 0.53-0.99, p = 0.047). The 2-year local failure rates were 12% and 18% (HR 0.72, 95% CI 0.32-1.61, p = 0.43) and the 2-year distant recurrence rates were 51% and 60% (HR 0.82, 95% CI 0.55-1.23, p = 0.34). Severe adverse radiation events (Common Terminology Criteria for Adverse Events [CTCAE] grade 4) occurred in 1 patient in each group, and CTCAE grade 3 toxicities were observed in 3 patients in the ICI + SRS group and in 5 in the SRS group (OR 1.53, 95% CI 0.35-7.7, p = 0.75). The present study found that SRS with concurrent ICIs for patients with lung cancer BMs was associated with longer survival and durable intracranial disease control, with no apparent increase in treatment-related adverse events.

Stress Analysis and Life Prediction of a Ceramic Matrix Composite Vane Using a Micromechanics-Based Approach

The results of stress analysis of a ceramic matrix composite (CMC) vane using a physics-based model developed for two-dimensional woven CMCs are presented. The model considers the inherent defects and micromechanical damage in woven CMCs along with time-dependent deformation of the constituents. Predictions include damage state under general load conditions and the global deformation response of the vane. Strain-gage data from burst tests are compared to strain predictions obtained using the model. Results from time-dependent analysis and life prediction of the vane under constant loads and cyclic loads at elevated temperatures are presented. Effect of fatigue frequency on the deformation and long-term life of the vane are also discussed.

Evaluation of Kunkur Fines for Utilization in the Production of Ternary Blended Cements

Ternary blended cements, such as limestone calcined clay cement (LC3), represent a type of strategic binder for the mitigation of environmental impacts associated with cement production. These are estimated to reduce CO2 emissions by about 40% compared to ordinary Portland cement (OPC). In this paper, we explore the possibility of producing such ternary blends by utilizing secondary raw materials that may be locally available. Specifically, the primary limestone that is commonly used in LC3 is herein substituted with quarry dust obtained by sourcing “kunkur”, a carbonate-rich sedimentary rock (also known as caliche) that can be locally utilized for the production of ordinary OPC clinker. To optimize the blending proportions of ternary cement consisting of OPC, calcined clay, and kunkur fines, a “design of experiment” (DoE) approach was implemented with the goal of exploring the possibility of reducing the amount of the OPC fraction to values lower than 50%. The properties of the formulated blends were assessed by a combination of techniques that comprise mechanical strength testing, XRD time-dependent quantitative phase analysis, and SEM–EDS microstructural and microchemical analyses. The results suggest that ternary blended cement based on kunkur fines forms hydration products, such as hemicarboaluminates, which are also observed in LC3. This shows that such waste materials can potentially be used in sustainable cement blends; however, the presence of kaolinite in the kunkur fines seems to affect their strength development when compared to both OPC and conventional LC3.

Validation and Retraining of the Stellae-123 Gene Expression Signature Improved Risk Stratification in Taiwanese Acute Myeloid Leukemia Patients

The European Leukemia Net (ELN) recommendations provide valuable guidance in treatment decisions of patients with acute myeloid leukemia (AML). However, the genetic complexity and heterogeneity of AML are not fully covered, despite the critical role of gene expression analysis in risk stratification. Addressing this gap, the Stellae-123 score, an AI-based model that captures gene expression patterns, has demonstrated promising results in predicting survival of AML patients in four western cohorts. This study aims to assess the applicability of Stellae-123 in a Taiwanese cohort. Our cohort included 233 de novo AML patients, who were diagnosed and treated at the National Taiwan University Hospital and received standard induction therapy with 7+3 chemotherapy (or 5+2 in elder fit patients). All patients had sufficient bone marrow samples for DNA and RNA sequencing at diagnosis. The median age of the cohort was 41 years. Among the patients, ELN-2022 risk groups were distributed as follows: favorable (53.4%), intermediate (27.6%), and adverse (19%). Appling the original Stellae-123 model, which derived gene expression signatures from the BeatAML cohort RNA-seq data, our patients were categorized into low-, intermediate-, and high-risk groups, each representing 33% of the cohort. Overall, there were no differences in clinical features among these risk groups. The Stellae-123 risk groups partially aligned with the ELN risk groups, with more ELN low-risk patients in the Stellae-123 low-risk group and a higher proportion of ELN-high risk patients in the Stellae-123 high-risk group. Intriguingly, aside from mutations listed in ELN-2022, the Stellae-123 high-risk group had significantly less NRAS mutations than others. Cumulative hazards predicted by Stellae-123 model yielded a c-index of 0.612 for overall survival (OS), and the three risk groups had significantly different OS (p&amp;lt;0.001). We next postulated that since Stellae-123 relies on molecular features derived from the leukemic cells, it might serve as a biomarker of biological risk to predict relapse-free survival (RFS). The c-index calculated by Stellae-123 to predict RFS was 0.607, suggesting a reasonable ability to discriminate between different risk levels for RFS. Recognizing the potential variation between the original training cohort and the Taiwanese population, we addressed this concern by retraining the Stellae-123 model using Taiwanese RNAseq data. As a result, the model retraining led to significant improvements in the cross-validated c-indexes, with values of 0.656 (OS) and 0.636 (RFS), leading to an even more robust risk stratification (p&amp;lt;0.001, Figure 1A). As we noticed overlapping grouping between Stellae-123 and ELN-2022 in both pretrained and retrained models, we explored if Stellae-123's prognostic power was independent of ELN risk status by conducting a multivariable analysis. Remarkably, in both the pretrained and retrained Stellae-123 models, whether calculated as continuous values or categorized into three groups, they consistently demonstrated discriminative power in predicting OS and RFS, irrespective of age and ELN-2022 risk, suggesting that Stellae-123 could offer additional valuable information in predicting patient outcomes. Considering recent data showing that incorporating age helped improve the prognostication performance of ELN-2022 and that age was an independent risk factor for inferior outcome in our cohort, we examined how age could complement current risk stratification. Serial model testing revealed significant improvement of the prognostic models when age and transcriptomic data, especially the locally retrained Stellae-123 model, were combined with ELN-2022, evident by drastically declined Akaike Information Criterion (AIC) values. Time-dependent ROC curve analysis confirmed the potential of incorporating Stellae-123 and age to complement current risk stratification system (Figure 1B). In summary, we showed that the Stellae-123 predicted both OS and relapse risk in AML patients from Taiwan. Furthermore, we demonstrated that model retraining could improve prognostication by adapting the Stellae-123 to the particularities of Taiwanese patients. Given the remarkable extrapolation of the signature, it's suggested gene expression profile be incorporated in the risk stratification of AML patients who are candidates to intensive therapy.

Theoretical approach on Hg2+, Pb2+ and Cd2+ ions adsorption via phographene

Due to widespread concerns regarding health and environmental risks associated with heavy metal ions, wastewater must be cleaned of them. As part of this study, phographene (PG) is investigated for removing Pb2+, Hg2+, and Cd2 + ions from wastewater. It has been proven that PG can be effective in removing heavy metals from watery media. The present study utilizes density functional theory (DFT). By the absorption of Pb2+, Hg2+, and Cd2 + ions, the pure PG gap (HOMO-LUMO) is significantly narrowed. Research shows that faster electron transport rates result in larger charge transfers between cations and PGs and higher binding energies. In the studied complexes, time-dependent DFT analysis indicates a charge transfer between the ligand and the metal. Based on the theory analysis conducted in this paper, experimental studies can be conducted to find PG-based materials that effectively remove contaminants from wastewater.

Dynamic Thrombocytopenia Has a Negative Impact with Distinctive Genetic and Immunologic Features in Patients with Myelofibrosis

Background: Myelofibrosis (MF) is a distinct subtype of the Philadelphia-negative myeloproliferative neoplasms (MPNs) characterized by an overproduction of differentiated hematopoietic cells. MF consisted of primary myelofibrosis (PMF) and secondary myelofibrosis (SMF) progressed from polycythemia vera and essential thrombocythemia. The pathologic and clinical features of MF include myeloproliferation, bone marrow fibrosis, anemia, splenomegaly, and MF-associated symptoms. But, some cases of MF shows cytopenic features, which were known to effect on inferior outcomes. The previous studies evaluating the prognostic impact of cytopenia at diagnosis have a limitation because the progression of cytopenia through disease course cannot be reflected. Therefore, the study by a time-dependent model is required. In the present study, we evaluated prognostic implication of dynamic thrombocytopenia as a time-dependent variable in patients with myelofibrosis. And, we attempt to determine the genetic and immunologic factors associated with dynamic thrombocytopenia. Methods: A total of 226 patients diagnosed with myelofibrosis and treated at Seoul St. Mary's Hematology Hospital from December 2001 to August 2021, who were performed DNA samples for next-generation sequencing (NGS) analysis were included in this study. To evaluated the correlation of various immune subsets and dynamic thrombocytopenia, immunophenotypic analysis by multiparameter flow cytometry was performed. Results: The patients with myelofibrosis were composed of SMF (n=66, 29.2%), PMF (n=160, 70.8%). Among the patients, 100 × 10 9/L or more platelet count group (PLT≥100) was the most common (n = 131, 60%), followed by progression to thrombocytopenia (defined as a PROG) (n = 64, 28.3%), and less than 100 × 10 9/L platelet count group (PLT&amp;lt;100) (n = 31, 13.7%). We observed that the 4-year overall survival of patients was 57.7%, 89.4%, and 93.9% in the PLT&amp;lt;100, PROG, and PLT≥100 groups ( p&amp;lt;0.001), respectively. In the PLT≥100 groups, patients with PMF were fewer than SMF. Next, we performed a time-dependent covariate analysis between the PLT≥100 group and PROG group. The progression of thrombocytopenia showed an inferior overall survival (P=0.004). In the multivariate analysis, the progression of thrombocytopenia ( p = 0.042, HR =7.7 [95% CI 1.04-7.70]), ASXL1 mutation ( p= 0.041, HR = 9.91 [95% CI 1.05-9.91]), and IDH1 mutation ( p =0.002, HR = 1103 [95% CI 5.19-1103]) were associated with poor OS. The frequency of CD45RA +CD4 + T cells was lower in PROG group compared to the PLT&amp;gt;100 group ( p = 0.015). Among the patients in the PROG group, detection of ASXL1 mutation was higher than the other groups ( p=0.021). Genemic alteration of ASXL1 showed a trend for a decreased CD45RA +CD4 + T cells than counterpart ( p=0.01). Conclusion: Our study demonstrated that dynamic thrombocytopenia, as a time-dependent variable has a prognostic value for the patients with MF, and low frequency of CD45RA +CD4 + T cells and genetic alteration of ASXL1 correlated with the progression to thrombocytopenia. Further investigation is warranted to determine the crucial clones and immune microenvironment signature associated with cytopenic features in patients with MF.