Optimal Selection Scheme Research Articles

Abstract TMP73: Endovascular therapy for acute ischemic stroke beyond 24 hours after onset: Japan Stroke Data Bank

Background: The therapeutic time window of endovascular therapy (EVT) for acute ischemic stroke (AIS) has been expanded up to 24 hours of onset. Patients with AIS beyond 24 hours may also benefit from EVT, but the actual status of this clinical issue is unknown. Purpose: To evaluate the real-world status of EVT for AIS beyond 24 hours of onset using a nation-wide stroke registry, Japan Stroke Data Bank (JSDB). JSDB is an ongoing hospital-based multicenter prospective registry of hospitalized patients with acute stroke or transient ischemic attack within 7 days of onset. Methods: From the JSDB dataset, patients with AIS who underwent EVT from 1996 through 2021 were analyzed. Patients were divided into 3 groups according to time from onset to hospital arrival (early: <4.5 hour; late: 4.5–24 hour; and very late: >24 hour). Outcomes included the favorable outcome (mRS 0–2 or return to pre-stroke mRS at discharge) and in-hospital mortality. Results: Among the 256,293 stroke patients, 91,907 AIS patients available for analysis were included in the present study. EVT was implemented in 6.9% (6,356/91,907) (median age 78 years; 41.6% women; median NIHSS score 16). The EVT rate by time window groups was 11.8% (4,258/36,044) for the early, 5.3% (1,676/31,328) for the late, and 1.7% (422/24,535) for the very late group. In the very late group with EVT, baseline NIHSS score was lowest (median 17 points in the early group, 14 points in the late group, and 5 points in the very late group), cardioembolism was least common (67.2%, 53.5%, and 22.0%, respectively), and large artery atherosclerosis was most common (17.9%, 30.8%, and 55.7%, respectively). Favorable outcome was more frequently achieved in the very late group (52.9%) than in the early (41.6%) and late (36.5%) groups. Symptomatic intracranial hemorrhage was more frequently seen in the very late group (6.0%) compared to the early (2.9%) and late (3.8%) groups, but in-hospital mortality was comparable among the time window groups (8.1% in the early group, 7.1% in the late group, and 6.6% in the very late group). Conclusions: Outcomes after EVT for patients with AIS beyond 24 hours were not necessarily worse than for patients with AIS up to 24 hours, but the patient profile in the very late group with EVT differed significantly from that in the early and late groups; developing optimal patient selection strategies for very late AIS may be required.

Review—Recent Progress in Materials Development for Electrochemical Gas Sensors

Abstract Gas sensors are critical in detecting various gases across industrial, environmental, and healthcare applications. Among them, electrochemical gas sensors stand out due to their high sensitivity, selectivity, and portability. However, traditional electrochemical gas sensors have faced limitations regarding long-term stability and the ability to detect gases at low concentrations. This review paper explores the emerging materials and innovative approaches that promise to address these challenges and enhance sensor performance. The unique properties of novel materials, including metal and metal oxides, carbon materials, conducting polymers, their composites, and others, are discussed in detail. These materials exhibit vital features such as high surface area, enhanced conductivity, and improved gas adsorption capabilities, which are crucial for developing advanced electrochemical gas sensors. Our review emphasizes the critical relationship between material properties and sensing mechanisms, offering insights into optimal material selection and design strategies. In addition to the materials aspect, we also cover many advanced electrochemical techniques, including electrode design enhancements, surface functionalization strategies, and innovative electrolytes like ionic liquids and polymer electrolytes. Overall, this comprehensive overview of state-of-the-art developments in electrochemical gas sensing highlights the potential for transformative applications across diverse fields and emphasizes the importance of interdisciplinary collaboration to drive future innovations.

Anti-Tumor Necrosis Factor-α Use in Pediatric Inflammatory Bowel Disease-Reports from a Romanian Center.

Background/Objectives: The introduction of anti-tumor necrosis factor-α (anti-TNF-α) agents, particularly infliximab (IFX) and adalimumab (ADA), has significantly expanded the therapeutic arsenal for inflammatory bowel disease (IBD). While these biologics have demonstrated substantial efficacy, they are associated with a spectrum of potential adverse events (AEs). This study aims to evaluate and document these AEs to facilitate optimal patient selection and monitoring strategies of patients undergoing these therapies. Methods: This retrospective, single-center study examined pediatric IBD patients receiving anti-TNF-α therapy at the "Grigore Alexandrescu" Emergency Hospital for Children in Bucharest, Romania, from January 2015 to October 2024. AEs were categorized into non-infectious complications (acute infusion reactions, anti-drug antibody formation), dermatological effects (erythema nodosum, vasculitis), neurological effects (Guillain-Barré syndrome), and infections. AEs were analyzed in relation to the specific anti-TNF-α agent administered and comprehensively characterized. Results: Of 40 patients enrolled, 22 (55%) had Crohn's disease (CD). The median (IQR) age at diagnosis was 14.8 years [10.8-15.9]. IFX was used in 34 (85%) patients while 6 (15%) patients received either ADA or IFX/ADA sequential therapy. Twenty-seven AEs were documented in 19 (47.5%) patients, the most prevalent being antidrug antibody formation (44.4%), infections (22.2%), and acute infusion reactions (22.2%). All ADA-exposed patients experienced at least one AE, compared to 41.2% (n = 14) patients treated with IFX, p = 0.01. Conclusions: AEs were observed in approximately half of the study cohort, with anti-drug antibody formation emerging as the most frequent complication. ADA therapy was associated with a significantly higher rate of AEs compared to IFX. These findings underscore the critical importance of vigilant monitoring for patients undergoing anti-TNF-α therapy in pediatric IBD management.

CARES Framework: A Circularity Assessment Method for Residential Building Structures

The construction industry contributes to global waste through its “take-make-dispose” model. In response, the European Commission has developed Action Plans to promote a Circular Economy (CE). However, there is currently no standardised Circularity Indicator (CI). The main barrier thereof is the lack of consensus on assessment criteria, stemming from the dispersity of advancements among the methodologies available. The CARES Framework (CARES-F) has been designed to address this issue by integrating ISO standards, Level(s), and Life Cycle Assessment (LCA) criteria into the traditional MCI framework. This innovative framework also introduces further variables from the CE perspective, such as transport impact, biomaterials, and quantitative Key Performance Indicators (KPIs) for Design for Disassembly (DfD) and Design for Adaptability (DfA). The validation is carried out on a typical Spanish residential building structure by applying the CARES-F and two micro-CIs based on the MCI. The results exhibit the low circularity of resource-intensive systems and highlight the need for secondary raw material in flow, as well as DfA criteria. These findings underscore the significance of the introduced quantitative KPIs in the CIs accuracy and demonstrate the feasibility of the CARES-F in the identification of circularity gaps and selection of optimal circular design strategies from early project stages.

Double kissing crush versus culotte for bifurcation percutaneous coronary interventions: insights from the PROGRESS-BIFURCATION registry.

Upfront 2-stent techniques are often used in bifurcation percutaneous coronary interventions (PCI), but there is controversy about optimal strategy selection. The authors examined the clinical and angiographic characteristics and long-term outcomes of 232 bifurcation PCIs that were performed using the double kissing (DK) crush or culotte technique in 216 patients between 2014 and 2023 using data from the Prospective Global Registry for the Study of Bifurcation Lesion Interventions (NCT05100992). The inverse probability of treatment weighted (IPTW) Cox proportional hazards model was used to assess long-term outcomes. DK crush was more commonly used (69.0%). Patients in the DK-crush group had similar baseline characteristics to those in the culotte group. Lesions treated with DK crush were more likely to be in the left main coronary artery (42.9% vs 15.5%, P less than .001), had larger proximal (3.50 [3.50-4.00] vs 3.50 [3.21-3.79] mm, P = .027) and distal (3.00 [3.00-3.50] vs 3.00 [2.75-3.25] mm, P = .047) main vessel diameter, and were more likely to have severe calcification (29.8% vs 5.6%, P less than .001). Technical (98.8% vs 97.2%, P = .588), procedural success (96.5% vs 95.1%, P = .698), and in-hospital major adverse cardiovascular events (MACE) (6.1% vs 3.0%, P = .509) were similar in both groups. During a median follow-up of 43 months, 60 (33.9%) patients experienced MACE. On IPTW adjusted Cox analysis, DK crush was associated with lower follow-up MACE (hazard ratio 0.28; 95% CI, 0.13-0.60; P = .001) compared with culotte driven by lower target vessel revascularization (TVR) (14.3% vs 29.3%, P = .029). Compared with culotte, DK crush is associated with similar periprocedural outcomes but lower TVR and MACE during follow-up.

Eco‐Labels and Sales Mode Selection Strategies for E‐Commerce Platform Supply Chain

ABSTRACTThe E‐commerce platform supply chain (EPSC) is maturing as a result of the platform economy's growth, and an increasing number of eco‐friendly producers are joining E‐commerce platforms to increase the sales of their eco‐friendly goods. However, without an information disclosure mechanism, customers find it challenging to completely comprehend or grasp the green information on items. Eco‐labels, as a green declaration symbol, can effectively reduce the information asymmetry between consumers and manufacturers. This paper establishes four game models for the EPSC under industry and government labels, considering the reselling and agency selling modes. The effects of consumers' green perceptions, eco‐label credibility, and R&D cost coefficient on the operation of EPSC, consumer surplus, environmental quality improvement, and social welfare were analyzed. We find that the enhancement of consumers' green perceptions and eco‐label credibility are beneficial for improving the product's greenness, increasing the profit of the E‐commerce platform, consumer surplus, environmental quality improvement, and social welfare, but it may not necessarily be beneficial for the manufacturer and the overall profitability of EPSC. Additionally, the profitability of the E‐commerce platform, consumer surplus, environmental quality improvement, and social welfare are more susceptible to shifts in consumers' green perceptions, whereas increasing the eco‐label credibility is more beneficial to the revenues of the manufacturer and EPSC. From the perspective of pursuing profits, the industry label is often chosen by the manufacturer, whereas the E‐commerce platform tends to choose the government label. Whether the optimal sales mode selection strategy of the manufacturer under the eco‐label is beneficial to the E‐commerce platform also depends on the size of unit production cost, commission rate, and consumers' green perceptions (eco‐label credibility). Moreover, EPSC benefits most from the reselling mode under the industry label, whereas consumer surplus, environmental quality, and social welfare are better served by the reselling mode under the government label. Conversely, the manufacturer is more likely to decide to resell the product under the government label when the R&D for green products is highly challenging.

An Approach for Detecting Parkinson’s Disease by Integrating Optimal Feature Selection Strategies with Dense Multiscale Sample Entropy

Parkinson’s disease (PD) is a neurological disorder that severely affects motor function, especially gait, requiring accurate diagnosis and assessment instruments. This study presents Dense Multiscale Sample Entropy (DM-SamEn) as an innovative method for diminishing feature dimensions while maintaining the uniqueness of signal features. DM-SamEn employs a weighting mechanism that considers the dynamic properties of the signal, thereby reducing redundancy and improving the distinctiveness of features extracted from vertical ground reaction force (VGRF) signals in patients with Parkinson’s disease. Subsequent to the extraction process, correlation-based feature selection (CFS) and sequential backward selection (SBS) refine feature sets, improving algorithmic accuracy. To validate the feature extraction and selection stage, three classifiers—Adaptive Weighted K-Nearest Neighbors (AW-KNN), Radial Basis Function Support Vector Machine (RBF-SVM), and Multilayer Perceptron (MLP)—were employed to evaluate classification efficacy and ascertain optimal performance across selection strategies, including CFS, SBS, and the hybrid SBS-CFS approach. K-fold cross-validation was employed to provide improved evaluation of model performance by assessing the model on various data subsets, thereby mitigating the risk of overfitting and augmenting the robustness of the results. As a result, the model demonstrated a significant ability to differentiate between PD patients and healthy controls, with classification accuracy reported as ACC [CI 95%: 97.82–98.5%] for disease identification and ACC [CI 95%: 96.3–97.3%] for severity assessment. Optimal performance was primarily achieved through feature sets chosen using SBS and the integrated SBS-CFS methods. The findings highlight the model’s potential as an effective instrument for diagnosing PD and assessing its severity, contributing to advancements in clinical management of the condition.

Channel-Hopping Using Reinforcement Learning for Rendezvous in Asymmetric Cognitive Radio Networks

This paper addresses the rendezvous problem in asymmetric cognitive radio networks (CRNs) by proposing a novel reinforcement learning (RL)-based channel-hopping algorithm. Traditional methods like the jump-stay (JS) algorithm, while effective, often struggle with high time-to-rendezvous (TTR) in asymmetric scenarios where secondary users (SUs) have varying channel availability. Our proposed RL-based algorithm leverages the actor-critic policy gradient method to learn optimal channel selection strategies by dynamically adapting to the environment and minimizing TTR. Extensive simulations demonstrate that the RL-based algorithm significantly reduces the expected TTR (ETTR) compared to the JS algorithm, particularly in asymmetric scenarios where M-sequence-based approaches are less effective. This suggests that RL-based approaches not only offer robustness in asymmetric environments but also provide a promising alternative in more predictable settings.

Butyrate Metabolism-Related Gene Signature in Tumor Immune Microenvironment in Lung Adenocarcinoma: A Comprehensive Bioinformatics Study.

Experimental results have verified the suppressive impact of butyrate on tumor formation. Nevertheless, there is a limited understanding of the hidden function of butyrate metabolism within the tumor immune microenvironment (TIME) of lung adenocarcinoma (LUAD). This research aimed at digging the association between genes related to butyrate metabolism (butyrate metabolism-related genes [BMRGs) and immune infiltrates in LUAD patients. Through analyzing The Cancer Genome Atlas dataset (TCGA), the identification of 38 differentially expressed BMRGs was made between LUAD and normal samples. Later, a prognostic signature made up of nine BMRGs was made to evaluate the risk score of LUAD subjects. Notably, high-risk scores emerged as negative prognostic indicators for overall survival in LUAD subjects. Additionally, BMRGs displayed associations with immunocyte infiltration levels, immune pathway activities, and pivotal prognostic hub BMRGs. One key prognostic BMRG, PTGDS, exhibited a robust correlation with T cells, the chemokine-related pathway, and the TCR signaling pathway. This study suggests that investigating the interplay between butyrate metabolism and T cells could present a promising novel approach to cancer treatment. OncoPredict analysis further unveiled distinct sensitivities of nine medicine in high- and low-risk groups, facilitating the selection of optimal treatment strategies for individual LUAD patients. The study establishes that the BMRG signature serves as a sensitive predictive biomarker, providing profound insights into the crucial effect of butyrate metabolism in the context of LUAD TIME.

Sustainable pavement maintenance and rehabilitation planning using the quantum cognitive trust network

Selecting appropriate pavement maintenance strategies can enhance resource efficiency, reduce environmental pollution, prolong road lifespan, and improve societal sustainability. Currently, most models, which selecting pavement maintenance options, exhibit high subjectivity and low reliability. This study employs an innovative probabilistic linguistic multi-attribute decision-making model basing on the quantum cognitive theory. Therefore, the model focuses on expert decision-making groups for pavement maintenance strategies. It considers the trust networks within the decision-making process, as well as the sequential and interference effects arising from experts' belief biases and behavioral interactions. By doing so, it facilitates a more scientific selection of optimal strategies among multiple maintenance options. The proposed method has been validated through practical case studies of road segments, and its scientific validity and effectiveness have been further corroborated through sensitivity analysis.

Online fountain code with an improved caching mechanism

AbstractThe original online fountain codes discard a large number of symbols that do not meet the requirements at the decoder. To improve channel utilization, this article proposes a new online fountain code. In the completion phase, the proposed code improves the receiving rules of encoded symbols, that is, the encoded symbols discarded in the original online fountain codes are selectively cached. Moreover, an optimal degree selection strategy of encoded symbols is obtained in the proposed scheme. The valid degree range of the proposed strategy is also analyzed, leading to an upper bound of cached events which eventually limits the number of feedbacks. The theoretical analysis and simulation results reveal that the proposed scheme outperforms two state‐of‐the‐art online fountain codes in terms of overhead factors, number of feedback transmissions, and encoding/decoding efficiency.

Breast cancer cell resistance to hormonal and targeted therapeutics is correlated with the inactivation of the NR6A1 axis.

Aim: Resistance to hormonal and targeted therapies in breast cancer limits treatment efficacy. Epigenetic alterations, including changes mediated by DNA methyltransferases, play a key role in this process. Previously, we identified that resistance to tamoxifen and rapamycin is associated with the suppression of DNMT3A. This study aims to further explore the mechanisms underlying this suppression, with a focus on identifying NR6A1 as a novel regulatory factor. Methods: Acquisition of resistant breast cancer cell sublines, MTT-test, immunoblotting, transient transfection and reporter analysis, lentiviral infection, qRT-PCR, and analysis of methylation using bisulfite pyrosequencing. Results: Our findings indicate that the development of cross-resistance in breast cancer cells to hormonal and targeted therapies involves a shift in cell signaling to alternative AKT pathways, marked by a localized suppression of the NR6A1/DNMT3A axis and associated DNA methylation changes. We demonstrated the critical role of NR6A1 downregulation in resistance development. Additionally, we observed activation of Snail - a key regulator in the epithelial-mesenchymal transition - as a mediator of the effects of NR6A1 depletion, establishing a direct link between Snail expression and resistance formation. Conclusion: The coordinated suppression of NR6A1 and DNMT3A may contribute to sustaining the resistant phenotype in breast cancer cells. This pathway could serve as a predictive marker, helping guide the selection of optimal therapeutic strategies for breast cancer treatment in the future.

Abstract 4141481: Outcomes of the upfront two stent strategies for bifurcation percutaneous coronary interventions: Insights from PROGRESS-BIFURCATION registry

Background: Upfront two-stent techniques are often used in bifurcation percutaneous coronary interventions (PCI), but there is controversy about optimal strategy selection. Methods: We examined the clinical, angiographic characteristics, and long-term outcomes of 206 bifurcation PCIs using the double kissing (DK) crush or the culotte techniques in 192 patients between 2014-2023 from the Prospective Global Registry for the Study of Bifurcation Lesion Interventions (NCT05100992). For the long-term outcomes adjusted hazard ratios (aHR) and 95% confidence intervals (CI) were calculated using the mixed effects Cox proportional hazards model. Results: DK crush was more commonly used (70.4%). Patients in the culotte group had similar baseline characteristics with the DK crush group. Lesions treated with culotte were more likely to be in the left anterior descending (54.1% vs. 35.9%, p<0.001) and circumflex arteries (21.3% vs. 9.0%, p<0.001), had smaller proximal (3.50 [3.00, 3.75] vs. 3.50 [3.30, 4.00] mm, p=0.032) and distal (3.00 [2.75, 3.00] vs. 3.00 [3.00, 3.50] mm, p=0.047) main vessel diameters, and were less likely to have severe calcification (6.6% vs. 32.4%, p<0.001). Technical success (96.7% vs. 98.6%, p=0.583), procedural success (93.1% vs. 93.9%, p=0.758), and in-hospital major adverse cardiovascular events (MACE) (3.4% vs. 6.1%, p=0.726) were similar in both groups. During a mean follow-up of 38-month, 32 (28.3%) patients experienced MACE. On multivariable analysis, culotte was associated with similar MACE (aHR 1.19; 95%CI 0.78-1.80; p=0.680), mortality (aHR 1.11; 95%CI 0.68-1.79; p=0.810), and target vessel PCI revascularization (aHR 0.58; 95%CI 0.30-1.13; p=0.460) compared with DK crush (Figure). Conclusions: Bifurcation PCI with DK crush and culotte had similarly high technical and procedural success, low in-hospital MACE, and long-term outcomes.

Development and Validation of a Novel Classification System and Prognostic Model for Open Traumatic Brain Injury: A Multicenter Retrospective Study.

Open traumatic brain injury (OTBI) is associated with high mortality and morbidity; however, the classification of these injuries and the determination of patient prognosis remain uncertain, hindering the selection of optimal treatment strategies. This study aimed to develop and validate a novel OTBI classification system and a prognostic model for poor prognosis. This retrospective study included patients with isolated OTBI who received treatment at three large medical centersin China between January 2020 and June 2022 as the training set. Data on patients with OTBI collected at the Fuzong Clinical Medical College of Fujian Medical University between July 2022 and June 2023 were used as the validation set. Clinical parameters, including clinical data at admission, radiological and laboratory findings, details of surgical methods, and prognosis were collected. Prognosis was assessed through a dichotomized Glasgow Outcome Scale (GOS). A novel OTBI classification was proposed, categorizing patients based on a combination of intracranial hematoma and midline shift observed on imaging, and logistic regression analyses were performed to identify risk factors associated with poor prognosis and to investigate the association between the novel OTBI classification and prognosis. Finally, a nomogram suitable for clinical application was established and validated. Multivariable logistic regression analysis identified OTBI classification type C (p<0.001), a Glasgow Coma Scale score (GCS)≤8 (p<0.001), subarachnoid hemorrhage (SAH) (p=0.004), subdural hematoma (SDH) (p=0.011), and coagulopathy (p=0.020) as independent risk factors for poor prognosis. The addition of the OTBI classification to a model containing all the other identified prognostic factors improved the predictive ability of the model (Z=1.983; p=0.047). In the validation set, the model achieved an area under the curve (AUC) of 0.917 [95% confidence interval (CI)=0.864-0.970]. The calibration curve closely approximated the ideal curve, indicating strong predictive performance of the model. The implementation of our proposed OTBI classification system and its use alongside the other prognostic factors identified here may improve the prediction of patient prognosis and aid in the selection of the most suitable treatment strategies.

Dynamics of soluble salts in cooling systems of circulating water supply

A model of the dynamics of soluble salts in the water of cooling systems of circulating water supply was developed based on mass balance principles. The proposed model is expressed in a general form under the assumption of a constant volume of circulating water and non-stationary input and output flows. The model accounts for scenarios where the concentration of soluble salts exceeds their concentration in the circulating water, thereby considering the technological necessity to change the system's power source in the event of an emergency at the feedwater treatment facilities. The developed model enables accurate prediction of the water-chemical regime in both existing and new recirculating cooling systems, sufficient for engineering calculations. It also facilitates the selection of optimal management strategies for such systems, including stabilization methods for recirculating water, feedwater preparation, blowdown volumes, etc. The model was validated under laboratory conditions for cases of concentration and dilution of highly soluble NaCl salt, with an observed error margin not exceeding 2%, attributed to experimental and instrumental factors. The variation in the concentration factor was analyzed for different blowdown rates, assuming initial equality of soluble salt concentrations in feedwater and circulation water. It was shown that establishing dynamic equilibrium between the circulation and feed waters can require dozens or even hundreds of circulation cycles for blowdown rates of 1–4%, and this system inertia must be considered during operation and when forecasting the performance of cooling systems with circulating water supply.

Novel scoring system for predicting stone-free rate after flexible ureteroscopy lithotripsy.

This study aims to investigate the factors affecting the stone-free rate (SFR) of flexible ureteroscopy and laser lithotripsy (fURSL) for renal stones and establish predictive models by identifying their prognostic factors. We retrospectively examined 252 patients with renal stones who were treated with fURSL between July 2020 and April 2022. We analyzed the relationship between the patient's clinical data (sex, age, and body mass index), stone status (side, size, location, stone/transverse process pixel ratio [STPR], and the CT value of stone [SCTV]), and SFR to determine the relevant factors and analyze their influence. Additionally, a nomogram was constructed based on these prediction results. A total of 252 patients were enrolled based on the inclusion and exclusion criteria. They were reviewed 7, 30, and 90 days postoperatively, with 46, 23, and 10 patients failing to discharge stones, respectively. Univariate Cox proportional hazard regression results revealed that the SFR was correlated with stone location, diameter (D1, diameter of stone measured by computed tomography [CT]; D2, diameter of stone measured by kidney-ureter-bladder abdominal radiography), SCTV, STPR, and operation time. Multivariate Cox proportional hazard regression was used to develop 2 predictive models for the SFR. The influencing factors of model 1 included D1, location, and SCTV, whereas those of model 2 were D2, location, and STPR. The results are shown in the nomogram. Receiver operating characteristic curves showed no significant difference between models 1 and 2 (P = .498), indicating that the nomogram was highly predictive. After 1000 resamples and internal self-validation, the C-indices of models 1 and 2 were 0.924 and 0.895, respectively, showing that the stone clearance predicted by the nomogram matched the actual situation. Stone location, size, and density (SCTV and STPR) were significant predictors of SFR after fURSL. The scoring system based on these factors may be used to guide optimal treatment strategy selection.

Cluster Based Energy Efficient Optimal Relay Selection Strategy for Multi Hop Reliable Cooperative Communication in Vehicular Communication

Cluster Based Energy Efficient Optimal Relay Selection Strategy for Multi Hop Reliable Cooperative Communication in Vehicular Communication

Direct comparison of mechanical circulatory support devices in porcine model of acute myocardial infarction complicated by ventricular septal defect and cardiogenic shock

Abstract Introduction Despite urgent clinical need, until now optimal strategy for mechanical circulatory support in acute myocardial infarction (AMI) complicated by ventricular septal defect (VSD) and cardiogenic shock has not been determined. Purpose The aim of our study was to compare hemodynamic effects of intra-aortic balloon pump (IABP), extracorporeal membrane oxygenation (ECMO) and Impella CP in the animal model of AMI complicated by VSD and cardiogenic shock. Methods Under general anesthesia and mechanical ventilation in pigs (sus scrofa domestica), using partial sternotomy, AMI was induced by ligation of left anterior descending. VSD was simulated by insertion of 25F cannulas into the left and right ventricles and their extracorporeal connection by 3/8 tubes generating left-to-right shunt. The hemodynamic effect of ECMO (2 L/min), IABP, and Impella CP (2 L/min) was evaluated by the measurement of the left ventricular end-diastolic pressure (LVEDP), mean arterial pressure (MAP), carotid flow (CAR) as a surrogate of total circulatory output, and VSD flow. Data are presented as mean (SD), P &amp;lt; 0.05 was considered statistically significant. Results Eleven animals were used, one died after induction of AMI, ten pigs completed all study procedures. Baseline (no mechanical support) LVEDP was 13.8 (3.0) mmHg, MAP 54.5 (11.0) mmHg, CAR 290.9 (37.3) mL/min, and VSD 1174.0 (499.3) mL/min (Table 1). IABP significantly improved all parameters in comparison to Baseline (Table 1). ECMO significantly improved MAP and CAR not only in comparison to Baseline but also in comparison to IABP and Impella; on the other hand, ECMO increased VSD flow (Table 1). Impella significantly improved all parameters with the largest effect on LVEDP and VSD flow (Table 1). Conclusions All tested devices improved the key hemodynamic parameters of MAP and CAR, however each to different extent. Individual devices influenced differently LVEDP and VSD flow. The results of this study may help in selection of optimal therapeutic strategy in AMI complicated by VSD and cardiogenic shock.Table 1.Hemodynamic outcomes.

Enhancing EDM Productivity for Plastic Injection Mold Manufacturing: An Experimental Optimization Study.

Electrical erosion molding (EDM) is an unconventional machining technology widely used in the manufacture of injection molds for plastics injection molding for the creation of complex cavities and geometries. However, EDM productivity can be challenging, directly influencing mold manufacturing time and cost. This work aims to improve EDM productivity in the context of mold manufacturing for plastics injection molding. The research focuses on the optimization of processing parameters and strategies to reduce manufacturing time and increase process efficiency. Through a rigorous experimental approach, this work demonstrates that the optimization of EDM parameters and strategies can lead to significant productivity gains in the manufacture of plastic injection molds without compromising part quality and accuracy. This research involved a series of controlled experiments on a Mitsubishi EA28V Advance die-sinking EDM machine. Different combinations of pre-cutting parameters and processing strategies were investigated using copper electrodes on a heat-treated steel plate. Productivity was evaluated by measuring the volume of material removed, and geometrical accuracy was checked on a coordinate measuring machine. The experimental results showed a significant increase in productivity (up to 61%) by using the "processing speed priority" function of the EDM machine, with minimal impact on geometric accuracy. Furthermore, the optimized parameters led to an average reduction of 12% in dimensional deviations, indicating improved geometric accuracy of the machined parts. This paper also provides practical recommendations on the selection of optimal EDM processing parameters and strategies, depending on the specific requirements of plastic injection mold manufacturing.

Optimizing Pricing Strategies for Product Lines and Value‐Added Services: Accounting for Reference Prices and Network Effects

ABSTRACTCustomer choice behavior is increasingly influenced by the reference price effect and negative network effect as customers become more rational and personalized. This study, considering customers as pivotal stakeholders for enterprise development, employs the multinomial logit (MNL) model and develops pricing and strategy optimization models for pure bundling and mixed bundling strategies of an enterprise's product line. The main focus is to analyze how these effects impact optimal pricing and strategy selection. The results indicate that stronger effects lead to lower enterprise profits, and ignoring them can cause substantial losses. Generally, mixed bundling strategies yield higher profits.