Science Progress最新文献

Objective: Serum albumin (ALB) plays a vital role in maintaining oncotic pressure and contributing to hemodynamic stability, with low levels associated with adverse outcomes in critically ill patients. This study aimed to assess the association between serum ALB concentrations and poor outcomes and the possible benefits of ALB supplementation.

Methods: A retrospective study involving 300 intensive care unit (ICU) patients. Albumin levels were recorded upon admission and throughout the stay, and patients were categorized based on a cutoff of 2.49 g/dl. The associations between low ALB levels and mortality were assessed using regression analysis. Additionally, it investigated the association of albumin supplementation with patient outcomes and mortality in specific patient populations.

Results: The mean age was 54.9 years, with 68% having sepsis. Patients with low baseline ALB concentrations exhibited higher overall mortality (71% vs. 52%) and 28-day mortality (50% vs. 39%). Adjusted analyses confirmed associations with mortality. Albumin supplementation was administered to 53% of the patients. Its use demonstrated potential benefits, particularly in reducing mortality, when given to specific groups, such as sepsis and hypoalbuminemia patients.

Discussion: The study confirms that low serum albumin levels are strongly associated with higher mortality rates in ICU patients. Albumin supplementation showed potential benefits, particularly in patients with sepsis and low albumin levels. Further analyses explored the dosage-response relationship and identified potential groups that would benefit from albumin supplementation.

Conclusion: Albumin can play a major role in predicting mortality in critically ill patients. Moreover, ALB supplementation may improve survival, especially in resource-limited settings. Future research should refine protocols through clinical trials for optimal survival in critically ill patients.

When the vehicle is in motion, the elastic deformation of the flexible subframe significantly influences ride comfort. Therefore, it is crucial to investigate the impact of flexible subframes on vehicle ride comfort. In order to enhance the reliability and optimization efficiency of our research, this paper incorporates the concept of elastic deformation in the flexible subframe into the investigation of vehicle ride comfort, and proposes a multi-objective optimization approach to enhance the overall vehicle ride comfort. The vibration mathematical model elucidates how flexible subframes affect vehicle ride comfort and establishes a rigid-flexible coupling model for a specific vehicle with a flexible subframe to analyze the impact of its elastic deformation on vehicle ride comfort through simulation experiments. Subsequently, a radial basis function approximation model is established, and the multi-objective particle swarm optimization and non-dominated sorting genetic algorithm II algorithms are employed to conduct multi-objective optimization of the stiffness of the subframe bushing with the aim of enhancing vehicle ride comfort. The findings indicate that the flexible subframe has a significant impact on vehicle ride comfort. Specifically, on bump roads, peak values of vertical and longitudinal seat accelerations decrease while lateral seat acceleration increases. On random roads, peak values of longitudinal and lateral seat accelerations increase while vertical acceleration decreases. Furthermore, the stiffness of the subframe bushing optimized by the non-dominated sorting genetic algorithm II algorithm further enhances vehicle ride comfort and aligns more closely with the optimization requirements in this study.

In this study, we focus on the analysis and prediction of urban logistics traffic flow, a field that is gaining increasing attention due to the acceleration of global urbanization and heightened environmental awareness. Existing forecasting methods face challenges in processing large and complex datasets, particularly when extracting and analyzing valid information from these data, often hindered by noise and outliers. In this context, time series analysis, as a key technique for predicting future trends, becomes crucial for supporting real-time traffic management and long-term traffic planning. To this end, we propose a composite network model that integrates gated recurrent unit (GRU), autoregressive integrated moving average (ARIMA), and temporal fusion transformer (TFT), namely the GRU-ARIMA-TFT network model, to enhance prediction accuracy and efficiency. Through the analysis of experimental results on different datasets, we demonstrate the significant advantages of this model in improving prediction accuracy and understanding complex traffic patterns. This research not only theoretically expands the boundaries of urban logistics traffic flow prediction but also holds substantial practical significance in real-world applications, especially in optimizing urban traffic planning and logistics distribution strategies during peak periods and under complex traffic conditions. Our study provides a robust tool for addressing real-world issues in the urban logistics domain and offers new perspectives and methodologies for future urban traffic management and logistics system planning.

The limited physical and mechanical properties of polymethyl methacrylate (PMMA), the current gold standard, necessitates exploring improved denture base materials. While three-dimensional (3D) printing offers accuracy, efficiency, and patient comfort advantages, achieving superior mechanics in 3D-printed denture resins remains challenging despite good biocompatibility and esthetics. This review investigates the potential of innovative materials to address the limitations of 3D-printed denture base materials. Thus, this article is organized to provide a comprehensive overview of recent efforts to enhance 3D-printed denture base materials, highlighting advancements. It critically examines the impact of incorporating various nanoparticles (zirconia, titania, etc.) on these materials' physical and mechanical properties. Additionally, it delves into recent strategies for nanofiller surface treatment and biocompatibility evaluation and explores potential future directions for polymeric composites in denture applications. The review finds that adding nanoparticles significantly improves performance compared to unmodified resins, and properties can be extensively enhanced through specific modifications, particularly silanized nanoparticles. Optimizing 3D-printed denture acrylics requires a multifaceted approach, with future research prioritizing novel nanomaterials and surface modification techniques for a novel generation of superior performance, esthetically pleasing, and long-lasting dentures.

Background: Inflammatory processes are key factors in pathological events associated with severe traumatic brain injury (STBI). The aim of this trial was to determine the effect of probiotics on anthropometric measures, disease severity, inflammatory markers, and T cells in patients with STBI.

Methods: Forty adult patients with STBI were enrolled in this parallel randomized, double-blind, placebo-controlled trial. Energy and protein status, Acute Physiology and Chronic Health Evaluation (APACHE II) score, Sequential Organ Failure Assessment (SOFA), interleukin 10 (IL-10), interleukin 1β (IL-1β), tumor necrosis factor-alpha (TNF-α), transforming growth factor beta (TGF-β), T-helper 17 (Th17), and T- Regulator (T-reg) cells were assessed at baseline (day 1), and week 2 (day 14) for each patient.

Results: Probiotic supplementation led to a substantial reduction in the serum levels of TNF-α (from 10.15 ± 6.52 to 5.05 ± 3.27) (P = 0.034), IL-1β (from 11.84 ± 7.74 to 5.87 ± 3.77) (P < 0.001), and Th17 cells (from 5.19 ± 1.69 to 2.67 ± 1.89) (P < 0.001) and a substantial increase in the serum levels of IL-10 (from 3.35 ± 1.45 to 6.17 ± 2.04) (P = 0.038), TGF-β (from 30.5 ± 15.27 to 46.25 ± 21.05) (P < 0.001), and T-reg cells (from 2.83 ± 1.43 to 4.29 ± 1.89) (P < 0.001) compared with the placebo group. Furthermore, no notable changes were observed in energy and protein intake and also, terms of SOFA and APACHE II scores following probiotic treatment compared with the placebo.

Conclusions: Probiotics could reduce inflammation and improve cellular immunity and may be considered as an adjunctive therapy in STBI patients.

Perclose ProGlide were created as preferred for puncture site closure of femoral artery. Femoral artery occlusion is one of the serious device-related complications. This report presents a continuous endovascular technique combined with peripheral cutting balloon (PCB) treatment for a case of a 32s woman diagnosed with lower extremity ischaemia caused by right superficial femoral artery (SFA) occlusion following the use of the Perclose ProGlide system in minimally invasive cardiac surgery. During the primary operation, limb ischaemia symptoms were relieved with vessel perfusion and reconstruction after regular balloon dilatation. A secondary operation was conducted 6 weeks later, and the obstructive lesions were recanalised without residual stenosis after PCB dilatation. No vessel-related adverse events such as dissection, rupture or distal embolisation occurred during the perioperative period. The patient recovered uneventfully after the operation, with complete alleviation of symptoms. Follow-up computed tomography angiography 3 month post-operatively revealed an undeformed shape and excellent patency of the right SFA.

Objective: The objective of this study was to investigate the correlation between metformin exposure and the incidence of lactic acidosis in critically ill patients.

Methods: The patients with type 2 diabetes mellitus (T2DM) were included from Medical Information Mart for Intensive Care IV database (MIMIC-IV). The primary outcome was the incidence of lactic acidosis. The secondary outcomes were lactate level and in-hospital mortality. Propensity score matching (PSM) method was adopted to reduce bias of the confounders. The multivariate logistic regression was used to explore the correlation between metformin exposure and the incidence of lactic acidosis. Subgroup analysis and sensitivity analysis were used to test the stability of the conclusion.

Results: We included 4939 patients. There were 2070 patients in the metformin group, and 2869 patients in the nonmetformin group. The frequency of lactic acidosis was 5.7% (118/2070) in the metformin group and it was 4.3% (122/2869) in the nonmetformin group. There was a statistically significant difference between the two groups (P < 0.05). The lactate level in the metformin group was higher than in the nonmetformin group (2.78 ± 2.23 vs. 2.45 ± 2.24, P < 0.001). After PSM, the frequency of lactic acidosis (6.3% vs. 3.7%, P < 0.001) and lactate level (2.85 ± 2.38 vs. 2.40 ± 2.14, P < 0.001) were significantly higher in the metformin group compared with the nonmetformin group. In multivariate logistic models, the frequency of lactic acidosis was obviously increased in metformin group, and the adjusted odds ratio (OR) of metformin exposure was 1.852 (95% confidence interval (CI) = 1.298-2.643, P < 0.001). The results were consistent with subgroup analysis except for respiratory failure subgroup. Metformin exposure increased lactate level but did not affect the frequency of lactic acidosis in patients of respiratory failure with hypercapnia. However, the in-hospital mortality between metformin and nonmetformin group had no obvious difference (P = 0.215). In sensitivity analysis, metformin exposure showed similar effect as the original cohort.

Conclusions: In critically ill patients with T2DM, metformin exposure elevated the incidence of lactic acidosis except for patients of respiratory failure with hypercapnia, but did not affect the in-hospital mortality.

One of the best ways to improve new learning and increase memory strength is by reprocessing the recently acquired information, for example, by thinking of it again. Synaptic plasticity, the process by which neurons change the strength of their connections with each other, is fundamental for learning and memory formation. Yet, at present, it is unclear how reprocessing information drives synaptic plasticity to support memory improvement. A new study suggests that reprocessing enhances memory formation by recruiting more synapses to represent the new memory, thus increasing its strength.

Background: The pressure fluctuation in the volute can be effectively reduced when the impeller of the double-suction pump is staggered, but the mechanism of this reduction is still unclear. At the same time, the traditional analysis method cannot realize the visualization of pressure fluctuation.

Objective: The purpose of this article is to explore the spatial distribution, propagation, and attenuation law of pressure fluctuation, and on this basis, to research the reason why staggered impeller reduce pressure fluctuation.

Methods: A new method called Pulse tracking network (PTN) was used in this article. Compared with the traditional method, which only analyzes the pressure fluctuation at scattered points, this method greatly improves the spatial resolution of the pressure fluctuation. In particular, the phase analysis is a major highlight of the method.

Results: Staggered impeller significantly reduced the pressure fluctuation intensity dominated by blade passing frequency. At the same time, the propagation of the pressure fluctuation in the volute changed from radial to circumferential in the volute cross-section.

Conclusions: Staggered impeller can effectively reduce pressure fluctuation, and the circumferential propagation caused by it is considered to be the main reason for it.