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Background: The effectiveness of a concomitant intra-aortic balloon pump (IABP) with veno-arterial extracorporeal membrane oxygenation (VA-ECMO) intervention in acute myocardial infarction with cardiogenic shock (AMICS) patients is contested in the literature. This study sought to compare short-term mortality weaning rate from VA-ECMOin AMICS cases. Methods: We conducted a literature review and compared the primary and secondary endpoints in the following treatment groups of AMICS patients: (1) VA-ECMO plus IABP vs. IABP alone and (2) VA-ECMO plus IABP vs. VA-ECMO alone. The primary endpoint was in-hospital all-cause mortality; while 30-days mortality, weaning from VA-ECMO, and vascular complications comprised secondary endpoints. Results: VA-ECMO concomitant with IABP was administered to 3,580 (76.4%) patients, while IABP alone and VA-ECMO alone treatments accounted for 1.7% and 21.9% of the patients, respectively. We found that in-hospital mortality was significantly lower in patients treated with VA-ECMO plus IABP vs. VA-ECMO alone (odds ratio (OR) = 0.52; 95% Confidence Interval (CI) = 0.21–1.31; I-squared statistic (I 2 = 30%) or IABP alone (OR = 0.20; 95% CI = 0.08–0.55; I 2 = 0%). Additionally, 30-days mortality was significantly lower in patients treated with VA-ECMO plus IABP vs. VA-ECMO alone (OR = 0.31; 95% CI = 0.25–0.40; I 2 = 0%) or IABP alone (OR = 0.24; 95% CI = 0.11–0.50; I 2 = 0%). A significant difference was observed in weaning from VA-ECMO in patients treated with VA-ECMO plus IABP vs. VA-ECMO alone (OR = 1.91; 95% CI = 1.09–3.33; I 2 = 0%). Conclusion: In-hospital and 30-days mortality were significantly lower in AMICS patients treated with VA-ECMO plus IABP vs. VA-ECMO alone or IABP alone. VA-ECMO with concomitant IABP could increase the proportion of patients weaned from VA-ECMO, significantly reducing in-hospital mortality, without increasing complications. [ABSTRACT FROM AUTHOR]

Background: White matter network alterations have increasingly been implicated in major depressive disorder, bipolar disorder and schizophrenia. The aim of this study was to identify shared and distinct white matter network alterations among the 3 disorders. Methods: We used analysis of covariance, with age and gender as covariates, to investigate white matter network alterations in 123 patients with schizophrenia, 123 with bipolar disorder, 124 with major depressive disorder and 209 healthy controls. Results: We found significant group differences in global network efficiency (F = 3.386, p = 0.018), nodal efficiency (F = 8.015, p < 0.001 corrected for false discovery rate [FDR]) and nodal degree (F = 5.971, [p.sub.FDR] < 0.001) in the left middle occipital gyrus, as well as nodal efficiency (F = 6.930, [p.sub.FDR] < 0.001) and nodal degree (F = 5.884, [p.sub.FDR] < 0.001) in the left postcentral gyrus. We found no significant alterations in patients with major depressive disorder. Post hoc analyses revealed that compared with healthy controls, patients in the schizophrenia and bipolar disorder groups showed decreased global network efficiency, nodal efficiency and nodal degree in the left middle occipital gyrus. Furthermore, patients in the schizophrenia group showed decreased nodal efficiency and nodal degree in the left postcentral gyrus compared with healthy controls. Limitations: Our findings could have been confounded in part by treatment differences. Conclusion: Our findings implicate graded white matter network alterations across the 3 disorders, enhancing our understanding of shared and distinct pathophysiological mechanisms across diagnoses and providing vital insights into neuroimaging-based methods for diagnosis and research., Introduction Schizophrenia, bipolar disorder and major depressive disorder (MDD) are among the most common diseases in psychiatric nosology. There is increasing evidence for shared features among these disorders with respect [...]

Rechargeable batteries, typically represented by lithium-ion batteries, have taken a huge leap in energy density over the last two decades. However, they still face material/chemical challenges in ensuring safety and long service life at temperatures beyond the optimum range, primarily due to the chemical/electrochemical instabilities of conventional liquid electrolytes against aggressive electrode reactions and temperature variation. In this regard, a gel polymer electrolyte (GPE) with its liquid components immobilized and stabilized by a solid matrix, capable of retaining almost all the advantageous natures of the liquid electrolytes and circumventing the interfacial issues that exist in the all-solid-state electrolytes, is of great significance to realize rechargeable batteries with extended working temperature range. We begin this review with the main challenges faced in the development of GPEs, based on extensive literature research and our practical experience. Then, a significant section is dedicated to the requirements and design principles of GPEs for wide-temperature applications, with special attention paid to the feasibility, cost, and environmental impact. Next, the research progress of GPEs is thoroughly reviewed according to the strategies applied. In the end, we outline some prospects of GPEs related to innovations in material sciences, advanced characterizations, artificial intelligence, and environmental impact analysis, hoping to spark new research activities that ultimately bring us a step closer to realizing wide-temperature rechargeable batteries. [ABSTRACT FROM AUTHOR]

Purpose: Optimizing CT protocols is challenging in the presence of automatic dose modulation because the CT dose index (CTDIvol) at different patient sizes is unknown to the operator. The task is more difficult when both the image quality index and iterative reconstruction prospectively affect the dose determination. It is of interest in practice to be informed of the CTDIvol during the protocol initialization and evaluation. It was our objective to obtain a predictive relationship between CTDIvol, the image quality index, and iterative reconstruction strength at various patient sizes. Methods: Dose modulation data were collected on a GE Revolution 256‐slice scanner utilizing a Mercury phantom and selections of the noise index (NI) from 8 to 17, the third generation iterative reconstruction (ASIR‐V) from 0% to 80%, and phantom diameters from 16 to 36 cm. The fixed parameters were 120 kVp, a pitch of.984, and a collimation of 40 mm with a primary slice width of 2.5 mm. The CTDIvol per diameter was based on the average tube current over three adjacent slices (same or similar diameter) multiplied by a conversion factor between the average mA of the series and the reported CTDIvol. The relationship between CTDIvol, NI, and ASIR‐V for each diameter was fitted with a 2nd order polynomial of ASIR‐V multiplied by a power law of NI. Results: The ASIR‐V fit parameters versus diameter followed a Lorentz function while the NI exponent versus diameter followed an exponential growth function. The CTDIvol predictions were accurate within 15% compared to phantom results on a separate GE Revolution. For clinical relevance, the phantom diameter was converted to an abdomen or chest equivalent diameter and was well matched to patient data. Conclusion: The fitted relationship for CTDIvol. for given values of NI and ASIR‐V blending for a range of phantom sizes was a good match to phantom and patient data. The results can be of direct help for selecting adequate parameters in CT protocol development. [ABSTRACT FROM AUTHOR]

Background: Growing evidence indicates both shared and distinct features of emotional perception in schizophrenia, bipolar disorder and major depressive disorder. In these disorders, alterations in spontaneous low-frequency fluctuations have been reported in the neural system for emotional perception, but the similarities and differences in the amplitude of low-frequency fluctuation (ALFF) across the 3 disorders are unknown. Methods: We compared ALFF and its signal balance in the neural system for emotional perception at 2 frequency bands (slow-5 and slow-4) in 119 participants with schizophrenia, 100 with bipolar disorder, 123 with major depressive disorder and 183 healthy controls. We performed exploratory Pearson partial correlation analyses to determine the relationship between ALFF signal balance and clinical variables. Results: We observed commonalities in ALFF change patterns across the 3 disorders for emotional perception neural substrates, such as increased ALFF in the anterior cerebrum (including subcortical, limbic, paralimbic and heteromodal cortical regions) and decreased ALFF in the posterior visual cortices. Schizophrenia, bipolar disorder and major depressive disorder showed significantly decreased ALFF signal balance in the neural system for emotional perception at both slow-5 and slow-4 frequency bands, with the greatest alterations for schizophrenia, followed by bipolar disorder and major depressive disorder. We found a negative correlation between ALFF signal balance and negative/disorganized symptoms in slow-4 across the 3 disorders. Limitations: The relatively broad age range in our sample and the cross-sectional study design may not account for our findings. Conclusion: The extent of the commonalities we observed further support the concept of core neurobiological disruptions shared among the 3 disorders; ALFF signal balance could be an important neuroimaging marker for the diagnosis and treatment of schizophrenia, bipolar disorder and major depressive disorder., Introduction Psychiatric nosology arose in central Europe toward the end of the 19th century. In particular, Kraepelin made the foundational distinction between dementia praecox (schizophrenia) and manic depression. (1) The [...]

Developing high-precision vehicle longitudinal control technology guided by ecological driving represents a highly promising yet challenging endeavor. It necessitates the fulfillment of the driver's operational intentions, precise speed control, and reduced fuel consumption. In light of this challenge, this study presents a novel vehicle longitudinal control model that integrates real-time driving style analysis and road slope prediction. First, it utilizes spectral clustering based on Bi-LSTM automatic encoders to identify driver driving styles. Next, it examines the driving environment and predicts the current slope of the vehicle. Additionally, a fuzzy controller is designed to optimize control performance, adapt to various driving styles and slopes, and achieve better fuel efficiency. The research results indicate that the DS-MPC control model developed in this paper can effectively distinguish various driving modes and has high speed control accuracy while saving 3.27% of fuel. [ABSTRACT FROM AUTHOR]