Search Results (4,110)

Diffuse Large B-cell Lymphoma (DLBCL) is the most common aggressive non-Hodgkin lymphoma (NHL). Despite the use of newer agents, such as polatuzumab vedotin, more than one-third of patients have ultimately relapsed or experienced refractory disease. MiRNAs are single-stranded, ~22-nucleotide-long RNAs that interact with their target RNA. They are significant regulators of post-transcriptional gene expression. One significant miRNA, miR-155, is involved in the pathophysiology of DLBCL and it is a critical modulator of hematopoiesis, inflammation, and immune responses. Targets of miR-155, such as histone deacetylase 4 (HDAC4), suppressor of cytokine signaling-1 (SOCS1) and immune cells, play a crucial role in DLBCL pathogenesis, since miR-155 regulates key pathways, transcription factors and cytokine expression and shapes the tumor microenvironment in DLBCL. In this review, we examine the role of miR-155 in DLBCL and its potential as a future diagnostic, prognostic, or predictive biomarker. Full article

Background/Objectives: Overall survival for patients with Stage 3 pancreatic ductal adenocarcinoma (PDAC) remains limited, with a median survival of 12 to 15 months. Irreversible electroporation (IRE) is a local tumor ablation method that induces cancerous cell death by disrupting cell membrane homeostasis. The DIRECT Registry study was designed to assess the effectiveness and safety of IRE when combined with standard of care (SOC) treatment for Stage 3 PDAC versus SOC alone in a real-world setting after at least 3 months of induction chemotherapy; Methods: Patients with Stage 3 PDAC treated with IRE plus SOC or SOC alone were prospectively enrolled in a multicenter registry study. Enrollment required 3 months of active multi-agent chemotherapy with no progression before enrollment. Endpoints were 30- and 90-day mortality and adverse events (AEs). Results: Eighty-seven IRE and 27 SOC subjects were enrolled in the registry. Mean ages were 64.0 ± 8.4 and 66.4 ± 9.9 years, and mean anterior/posterior tumor diameters were 2.2 ± 0.7 cm and 3.2 ± 1.3 for the IRE and SOC groups respectively (p = 0.0066). All IRE procedures were performed using an open approach. The 90-day all-cause mortality was 5/83 (6.0%) and 2/27 (7.4%) for the IRE and SOC groups, respectively. Two subjects in the IRE group died from treatment-related complications, and one patient in the SOC group died due to chemotherapy-related complications. Conclusions: Initial results from the DIRECT registry study indicate the use of IRE for curative intent tumor ablation in combination with induction chemotherapy has equivalent morbidity and mortality rates when compared to standard-of-care chemotherapy alone. Full article

Soil nutrients are essential for plant survival, especially in karst regions where soil erosion is a significant threat, leading to ecosystem degradation. Rocks exposed in these areas contribute to fragmented soil coverage and the complex spatial distribution of soil nutrients, hindering vegetation recovery. In this study, we collected 60 soil samples (0–30 cm deep) from a typical rocky desertification slope. Classical statistics and geostatistics were used to assess the spatial variability of the following key soil properties: soil organic carbon (SOC), total nitrogen (TN), total phosphorus (TP), and total potassium (TK). The study mapped a continuous surface of soil nutrients using the ordinary kriging method to analyze the spatial variability of the karst slope. The results showed that, except for the bulk density and porosity, which showed little variation, the other soil characteristics had moderate to high levels of variability. The SOC, TN, and TP levels decreased with soil depth, while the TK content increased with soil depth. Each soil layer has strong spatial autocorrelation in its SOC. The variability of TP and TK decreases with soil depth, indicating strong spatial autocorrelation. In the 0–10 cm soil layer, the SOC displays the highest level of continuity, with the TN exhibiting a higher level of variability compared to the other nutrients. Within the 10–20 cm soil layer, the SOC, TN, TP, and TK all exhibit strong spatial autocorrelation. Moving to the 20–30 cm soil layer, the structural variability of SOC is the most pronounced. The correlation between soil nutrients and other soil properties was not strong, with only a cumulative explanatory power of 11.81% in the first two axes of a redundancy analysis (RDA). Among them, the bulk density and silt content had a significant impact on soil nutrients. Studying the spatial variability of soil nutrients in rocky desertification areas is crucial for improving soil quality and promoting vegetation restoration. Full article

With the development of system-on-chip (SoC) and chiplet technology in the post-Moore era, an increasing number of chiplets are being integrated into a single chip. Consequently, the functions and complexity that can be realized are growing daily. Simultaneously, the volume of test data required for ultra-large-scale integrated circuits (ULSIs) has risen significantly. However, traditional automatic test equipment (ATE) is constrained by its data storage and bandwidth limitations, and its long technology iteration cycle. These cannot keep pace with the rapid development of design technology. This discrepancy leads to challenges in ULSI testing, such as excessively long test time and difficulties in completing the tests. Test compression technology can effectively address these issues by reducing the performance requirements of the test equipment, which in turn can lower test costs. This paper summarizes the classifications of chip test compression technology and, based on their current development, provides a detailed analysis of key technologies. It includes test compression-oriented coding methods, optimization of scan chain structures, and enhancements in coding for compression efficiency. Finally, a forward-looking perspective on the development of chip test compression technology is presented. The aim is to offer a reference for subsequent research in this field and related areas, as well as to provide technical support for the advancement of ULSI testing in the post-Moore era. Full article

Background: Numerous studies have evaluated the effect that mindfulness-based interventions (MBIs) have on multiple health outcomes. For its part, stress is a natural response to environmental disturbances and within the associated metabolic responses, alterations in cortisol levels and their measurement in different tissues are a way to determine the stress state of an individual. Therefore, it has been proposed that MBIs can modify cortisol levels. Methods and results: The objective of this systematic review was to analyze and summarize the different studies that have evaluated the effect of MBIs on cortisol levels. The following databases were consulted: MEDLINE, AMED, CINAHL, Web of Science, Science Direct, PsycINFO, SocINDEX, PubMed, the Cochrane Library and Scopus. The search terms “mindfulness”, “mindfulness-based interventions” and “cortisol” were used (and the search was limited to studies from January 1990 to May 2024). In order to reduce selection bias, each article was scrutinized using the JBI Critical Appraisal Checklist independently by two authors. We included those studies with specified intervention groups with at least one control group and excluded duplicate studies or those in which the intervention or control group was not adequately specified. Significant changes in cortisol following MBIs were found in 25 studies, while 10 found no changes. The small sample size, lack of randomization, blinding, and probable confounding and interaction variables stand out in these studies. Conclusion: MBIs have biological plausibility as a means of explaining a positive effect on cortisol levels; however, the weakness of the studies and the absence of robust designs makes it difficult to establish a causal association between both variables. Registration number: INPLASY2024110017. Full article

Soil organic carbon (SOC) sequestration in cropland is not only instrumental in combating climate change, but it also significantly enhances soil fertility. It is imperative to precisely and accurately quantify the SOC sequestration potential and assess the relative significance of various multiple explanatory factors in a timely manner. We studied 555 soil samples from the cropland topsoil (0–15 cm) across the black soil region in Northeast China between the years 2021 and 2022, and we identified 16 significant impact factors using one-way ANOVA and Pearson correlation coefficient analysis. In addition, the Random Forest (RF) model outperformed the Cubist model in predicting the spatial distribution of SOC contents. The predicted ranges of SOC contents span from 5.24 to 43.93 g/kg, with the average SOC content using the RF model standing at 17.24 g/kg in Northeast China. Stepwise regression and structural equation modeling revealed climate and topography as key factors affecting SOC distribution. The SOC density in the study area varied from 0.51 to 9.11 kg/m², averaging 3.30 kg/m², with a total SOC stock of 1226.64 Tg. The SOC sequestration potential in the study area was estimated at 3057.65 Tg by the categorical maximum method, with a remaining sequestration capacity of 1831.01 Tg. The study area has great potential for SOC sequestration. We hope to transform the theoretical value of SOC sequestration potential into actual SOC sequestration capacity by promoting sustainable agriculture and additional strategies. Our findings provide insights into the global soil conditions, SOC storage capacities, and effective SOC management strategies. Full article

Due to its improved capacity compared to graphite, silicon is a promising candidate to handle the demands of high-energy batteries. With the introduction of new materials, further aspects of the battery system must be reconsidered. One of those aspects is the heat generation during the charging and discharging of a cell, which delivers important information for the development of cooling systems, the battery management system and the overall performance of the cell. Since the reversible heat presents an important contribution to the overall heat generation during cycling, the entropy coefficient is the main value that needs to be determined. This study evaluates the entropy coefficient of custom-produced 2032 coin half-cells with lithium counter electrodes, containing 45 wt% nanosilicon and 45 wt% carbon black. The potentiometric method, utilizing VR and self-discharge curves, produced reliable results, yielding entropy coefficient values between 95% SoC and 10% SoC during delithiation. These values of the entropy coefficient are consistently negative. Furthermore, ICA measurements identified two phase transitions during delithiation, with these transitions shifting to lower SoC as SoH decreases, impacting the slope of the entropy coefficient. Full article

Thinning, a core forest management measure, is implemented to adjust stand density and affect soil biogeochemical processes by changing biotic and abiotic properties. However, the responses of soil organic carbon (SOC), soil enzyme activity (EEA), and stoichiometry (EES) in plantations in hilly zones to thinning have received little attention. To test the hypothesis that thinning has regulatory effects on the SOC pool, EEA, and EES characteristics, field sampling and indoor analysis were conducted 9 years after thinning. Thinning significantly influenced the soil properties, especially in the topsoil, and significantly greater SOC and mineral-associated organic carbon (MAOC) contents were observed in the high-density treatment. The EEAs in the topsoil tended to increase with increasing density. SOC, MAOC, and C to phosphorus (C:P) had the greatest influence on the soil EEAs and EESs. Microbial metabolic limitations tended to change from nitrogen to phosphorus with increasing density. The soil properties, SOC fractions, available nutrients, and elemental stoichiometry drove microbial metabolic limitations and were significantly positively correlated with β-glucosidase, elemental stoichiometry, and EES. This study deepens our understanding of EEAs, SOC, and nutrient dynamics under thinning practices and elucidates how forest tending measures affect soil biogeochemical processes, thereby providing ideas for developing strategies to mitigate the adverse impacts of human interventions. Full article

Congenital heart defects (CHDs) are one of the most common congenital malformations and often require heart surgery with cardiopulmonary bypass (CPB). Children undergoing cardiac surgery with CPB are especially at greater risk of post-operative complications due to a systemic inflammatory response caused by innate inflammatory mediators. However, the pathophysiological response is not fully understood and warrants further investigation. Therefore, we investigated the inflammatory response in macrophages initiated by peri-operative serum samples obtained from patients with CHD undergoing CPB cardiac surgery. Human differentiated THP-1 macrophages were pretreated with Stattic, a STAT3 (Tyr705) inhibitor, before stimulation with serum samples. STAT3 and NF-κB activation were investigated via a Western blot, IL-1β, TNFα, IL-10, mediators for vascular permeability (VEGF-A, ICAM), and SOCS3 gene expressions via RT-qPCR. CPB induced an inflammatory response in macrophages via the activation of the STAT3 but not NF-κB signaling pathway. Longer duration on the CPB correlated with increased cytokine, VEGF, and ICAM expressions, relative to individual pre-operation levels. Patients that did not require CPB showed no significant immune response. Pretreatment with Stattic significantly attenuated all inflammatory mediators investigated except for TNFα in the macrophages. CPB induces an increased expression of cytokines and mediators of vascular permeability via the activation of STAT3 by IL-6 and IL-8 in the serum samples. Stattic attenuates all mediators investigated but promotes TNFα expression. Full article

Precise modeling and state of charge (SoC) estimation of a lithium-ion battery (LIB) are crucial for the safety and longevity of battery systems in electric vehicles. Traditional methods often fail to adapt to the dynamic, nonlinear, and time-varying behavior of LIBs under different operating conditions. In this paper, an advanced joint estimation approach of the model parameters and SoC is proposed utilizing an enhanced Sigma Point Kalman Filter (SPKF). Based on the second-order equivalent circuit model (2RC-ECM), the proposed approach was compared to the two most widely used methods for simultaneously estimating the model parameters and SoC, including a hybrid recursive least square (RLS)-extended Kalman filter (EKF) method, and simple joint SPKF. The proposed adaptive joint SPKF (ASPKF) method addresses the limitations of both the RLS+EKF and simple joint SPKF, especially under dynamic operating conditions. By dynamically adjusting to changes in the battery’s characteristics, the method significantly enhances model accuracy and performance. The results demonstrate the robustness, computational efficiency, and reliability of the proposed ASPKF approach compared to traditional methods, making it an ideal solution for battery management systems (BMS) in modern EVs. Full article

The state of charge (SoC) is a critical parameter in lithium-ion batteries and their alternatives. It determines the battery’s remaining energy capacity and influences its performance longevity. Accurate SoC estimation is essential for making informed charging and discharging decisions, mitigating the risks of overcharging or deep discharge, and ensuring safety. Battery management systems rely on SoC estimation, utilising both hardware and software components to maintain safe and efficient battery operation. Existing SoC estimation methods are broadly classified into direct and indirect approaches. Direct methods (e.g., Coulumb counting) rely on current measurements. In contrast, indirect methods (often based on a filter or observer) utilise a model of a battery to incorporate voltage measurements besides the current. While the latter is more accurate, it faces challenges related to sensor drift, computational complexity, and model inaccuracies. The need for more precise and robust SoC estimation without increasing complexity is critical, particularly for real-time applications. Recently, sliding mode observers (SMOs) have gained prominence in this field for their robustness against model uncertainties and external disturbances, offering fast convergence and superior accuracy. Due to increased interest, this review focuses on various SMO approaches for SoC estimation, including first-order, adaptive, high-order, terminal, fractional-order, and advanced SMOs, along with hybrid methods integrating intelligent techniques. By evaluating these methodologies, their strengths, weaknesses, and modelling frameworks in the literature, this paper highlights the ongoing challenges and future directions in SoC estimation research. Unlike common review papers, this work also compares the performance of various existing methods via a comprehensive simulation study in MATLAB 2024b to quantify the difference and guide the users in selecting a suitable version for the applications. Full article

This paper presents an optimal sizing strategy for a hybrid generation system combining photovoltaic (PV) and energy storage systems. To achieve this, the optimization problem is solved using the simplex method for linear programming, implemented through Python. The model considers test data on electrical energy demand and solar irradiation, alongside battery operating conditions such as state of charge (SOC) and upper and lower charge limits as key decision variables. Conventional PV system sizing serves as a benchmark to assess the effectiveness of the optimization, with particular attention given to the computational resources required for problem solving.The results obtained from the optimization method demonstrate a substantial improvement in the utilization of energy resources, both from the photovoltaic system and the energy storage system. This approach enabled the design of an optimized system based on the proposed model, which was further refined using Matlab/Simulink. Full article

Forests play a crucial role in climate change mitigation by acting as a carbon sink. Understanding the influence of soil properties on carbon stocks in forests is essential for developing effective forest management strategies. The aim of the study was to assess the impact of soil texture on carbon stocks in the biomass of deciduous and coniferous tree stands of a forest-steppe ecotone. Soil samples were collected from 55 soil pits, and forest inventory data were obtained from eight permanent sample plots. The results showed that the distribution of mechanical particles in soils, particularly the stocks of silt and clay, significantly influenced the accumulation of carbon in tree stands. The stock of silt and clay was shown to increase with an increase in the diversity of tree species in forests and carbon stocks in forest stands. While soil organic carbon stocks did not exhibit a clear relationship with tree stand carbon stocks, a strong positive correlation (r = 0.802, p < 0.05) was found between the stocks of fine particles in the 2 m root-inhabited soil layer and the carbon stocks in tree biomass. The study provides a classification of forest types based on soil texture, which can facilitate differentiated forest management strategies for enhancing the carbon sequestration potential of forest ecosystems in the forest-steppe zone. Full article

Effective health management and accurate state of charge (SOC) estimation are crucial for the safety and longevity of lithium-ion batteries (LIBs), particularly in electric vehicles. This paper presents a health management system (HMS) that continuously monitors a 4s2p LIB pack’s parameters—current, voltage, and temperature—to mitigate risks such as overcurrent and thermal runaway while ensuring balanced charge distribution between cells. An improved online battery model (IOBM) is developed to enhance SOC estimation accuracy. The system utilises forgetting factor recursive least squares (FFRLS) for real-time parameter updates, an adaptive nonlinear sliding mode observer (ANSMO) for SOC estimation, and a long short-term memory (LSTM) network to dynamically adjust capacity based on operating conditions. Validation using the urban dynamometer driving schedule (UDDS) test demonstrated high accuracy, with the proposed battery model achieving a root mean square error (RMSE) of 12.13 mV and the LSTM achieving an RMSE of 0.0118 Ah. Regular updates to the battery’s current capacity, along with the proposed IOBM, significantly improved SOC estimation performance, maintaining estimation errors within 1.08%. Full article

Many agreements and protocols in the global framework call on industries and businesses to respond to threats related to climate change. New terminologies such as environmental, social, and governance (ESG) scores address this issue and responsibility. This study investigates the impact of sustainability (environment (ENV), social (SOC), governance (GOV), and ESG) on the financial performance of firms in the fast-moving consumer goods industry from 2013 to 2020, the second commitment period of the Kyoto Protocol (SCKP). The study sample covers 113 firms in the North American region (the USA and Canada did not participate in SCKP). The results showed that ESG is not an influencer of financial performance, while ENV and SOC components negatively affect financial performance. On the other hand, GOV is the most significant influencer that positively impacts financial performance. Based on these findings, ESG and its components are not conducive to promoting financial performance during the SCKP period. However, fast-moving consumer goods are ahead of other sectors in terms of sustainability disclosure. Moreover, the highest positive impact of GOV is attributed to the advanced system with rules, standards, and regulations that foster the better and more efficient governance of firms from developed countries. Full article