Search Results (618)

The Apple TV+ series Severance (2022–present) offers a dystopian portrayal of workplace life that intensifies real-world dynamics of control, boundary management, and identity regulation. This paper analyzes Severance as a speculative case study in organizational theory, treating the show’s fictional world as a site for conceptual reflection. Drawing on critical management studies and labor process theory, we examine how mechanisms of control, the regulation of work–life boundaries, and the fragmentation of autonomy and subjectivity are depicted in extreme form. We argue that fiction—particularly speculative satire—can serve as a tool of theoretical production, not merely illustration. Rather than restating familiar critiques, Severance allows us to see workplace norms with renewed clarity, surfacing the moral and psychological consequences of surveillance, coercion, and instrumentalized consent. A methodological note outlines our interpretive approach to narrative fiction, and a discussion of implications situates the analysis within broader debates about organizational ethics, resilience, and critique. Full article

Background/Objectives: Treatment of borderline resectable (BRPC) and locally advanced (LAPC) pancreatic cancer involves neoadjuvant chemotherapy followed by complex surgery, posing significant risks of toxicity, complications, and changes in quality of life (QoL). This study aims to investigate the impact of neoadjuvant chemotherapy followed by resection on overall survival (OS) and QoL. Methods: Consecutive patients with BRPC and LAPC included in a population-based study (NORPACT-2) from January 2018 to December 2020 were reviewed. Results: A total of 54 patients (BRPC; n = 43, LAPC; n = 11) underwent neoadjuvant chemotherapy followed by pancreatectomy. The majority (66.7%) received (m)FOLFIRINOX. Forty-six (85.2%) patients underwent pancreatoduodenectomy. Vascular resection was performed in 32 (59.3%) patients. Fourteen (25.9%) patients experienced major complications. The majority of the resected specimens demonstrated T2 (63%), N+ (79.6%), and R1 (85.2%) status. Median OS was 31 (CI 24.7–37.3) months. In multivariate analysis, only CAP 3 (p = 0.035) predicted worse survival. Forty (74.1%) patients experienced recurrence. Global QoL (p = 0.031), social and role functioning (p = 0.024, p = 0.031), improved three months after surgery. Pain (p = 0.042), dyspnea (p = 0.004), appetite loss (p = 0.028), and diarrhea (p = 0.007) improved post-resection. Conclusions: Patients with BRPC and LAPC undergoing neoadjuvant chemotherapy and resection have survival comparable to primary resectable pancreatic cancer. Postoperative morbidity was acceptable, and QoL recovered post-surgery. CAP grade was the only independent negative prognostic factor. Full article

(1) Background: Among the most important authors of spiritual autobiography, Dag Hammarskjöld and Thomas Merton must surely mentioned. The first one, a Swedish Evangelical, and the second one, an American Cistercian monk, provide valuable and interdisciplinary works. Among the topics found, their political theology is also present. Noticing its relevance, we will try there to take into account the way the aforementioned topic is reflected in their work. (2) Results: Aspects such as communism, racism, diplomacy, or love will constitute some of the topics that we will bring into attention in this research in an attempt to present the particularities, common points, and differences of the approaches of the two relevant authors, one from the Protestant space and the other from the Catholic one, both with an ecumenical vocation and openness to dialogue. (3) Methods: As for our methods, we will use the historical inquiry, the analysis of documents, and the deductive and the qualitative method. (4) Conclusions: The work will therefore investigate the aspects of political theology found in their research and will emphasize their vision, the common points, the use of Christian theology in the understanding of political and social realities, but also the differences that may occur between their approaches. At the same time, the role played by the context where they lived, worked, and wrote will be taken into attention in order to provide a more complex perspective on the relationship between their life and work. Full article

Obesity and related metabolic disorders are closely linked to dysregulated lipid metabolism, where the metabolic balance of diacylglycerol (DAG) played a pivotal role. Although cis-palmitoleic acid (cPOA) exhibits anti-obesity effects, its efficacy varies across dietary conditions, and its molecular mechanisms remains unclear. In this study, we investigated the dose-dependent regulatory effects of cPOA on DAG metabolic shunting in db/db mice, employing lipidomics, pathway analysis, and gene/protein expression assays. Under a basal diet, low-dose cPOA (75 mg/kg) inhibited DAG-to-triglyceride (TAG) conversion, reducing hepatic lipid accumulation, while medium-to-high doses (150–300 mg/kg) redirected DAG flux toward phospholipid metabolism pathways (e.g., phosphatidylcholine [PC] and phosphatidylethanolamine [PE]), significantly lowering body weight and adiposity index. In high-fat diet (HFD)-fed mice, cPOA failed to reduce body weight but alleviated HFD-induced hepatic pathological damage by suppressing DAG-to-TAG conversion and remodeling phospholipid metabolism (e.g., inhibiting PE-to-PC conversion). Genetic and protein analyses revealed that cPOA downregulated lipogenic genes (SREBP-1c, SCD-1, FAS) and upregulated fatty acid β-oxidation enzymes (CPT1A, ACOX1), while dose-dependently modulating DGAT1, CHPT1, and PEMT expression to drive DAG metabolic shunting. Notably, DAG(36:3, 18:1–18:2) emerged as a potential biomarker for HFD-aggravated metabolic dysregulation. This study elucidated cPOA as a bidirectional regulator of lipid synthesis and oxidation, improving lipid homeostasis through dose-dependent DAG metabolic reprogramming. These findings provide novel insights and strategies for precision intervention in obesity and related metabolic diseases. Full article

Ginseng rusty root symptoms (GRSs) compromise the yield and quality of Panax ginseng. While transcriptomic analyses have demonstrated extensive remodeling of stress signaling networks, the post-transcriptional defense circuitry remains obscure. We profiled alternative splicing (AS) in three phloem tissues, the healthy phloem (AG), the non-reddened phloem neighboring lesions (BG), and the reddened lesion core (CG), to delineate AS reprogramming during GRS progression. The frequency of AS was sharply elevated in CG, with intron retention predominating. Extensive gains and losses of splice events indicate large-scale rewiring of the splice network. Overlapping differentially alternative spliced genes (DAGs) identified in both CG vs AG and CG vs BG contrasts were significantly enriched for RNA–spliceosome assembly and stress–response pathways, revealing a conserved post-transcriptional response associated with lesion formation. Integrative analysis of differentially expressed genes uncovered 671 loci under dual regulation; functional classification categorized these genes in receptor-like kinase signaling and chromatin-remodeling modules, underscoring the synergy between AS and transcriptional control. Moreover, the B subgenome disproportionately contributed stress-responsive transcripts in diseased tissue, suggesting an adaptive, subgenome-biased strategy. These findings demonstrate that dynamic AS remodeling and subgenome expression bias jointly orchestrate ginseng defense against GRS and provide a framework for breeding disease-resilient crops. Full article

Background: Diabetic retinopathy (DR) is a leading cause of visual impairment worldwide. Manual grading of fundus images is the gold standard in DR screening, although it is time-consuming. Artificial intelligence (AI)-based algorithms offer a faster alternative, though concerns remain about their diagnostic reliability. Methods: A cross-sectional pilot study among patients (≥18 years) with diabetes was established for DR and diabetic macular edema (DME) screening at the Oslo University Hospital (OUH), Department of Ophthalmology, and the Norwegian Association of the Blind and Partially Sighted (NABP). The aim of the study was to evaluate the validity (accuracy, sensitivity, specificity) and reliability (inter-rater agreement) of automated AI-based compared to manual consensus (MC) grading of DR and DME, performed by a multidisciplinary team of healthcare professionals. Grading of DR and DME was performed manually and by EyeArt (Eyenuk) software version v2.1.0, based on the International Clinical Disease Severity Scale (ICDR) for DR. Agreement was measured by Quadratic Weighted Kappa (QWK) and Cohen’s Kappa (κ). Sensitivity, specificity, and diagnostic test accuracy (Area Under the Curve (AUC)) were also calculated. Results: A total of 128 individuals (247 eyes) (51 women, 77 men) were included, with a median age of 52.5 years. Prevalence of any vs. referable DR (RDR) was 20.2% vs. 11.7%, while sensitivity was 94.0% vs. 89.7%, specificity was 72.6% was 83.0%, and AUC was 83.5% vs. 86.3%, respectively. DME was detected only in one eye by both methods. Conclusions: AI-based grading offered high sensitivity and acceptable specificity for detecting DR, showing moderate agreement with manual assessments. Such grading may serve as an effective screening tool to support clinical evaluation, while ongoing training of human graders remains essential to ensure high-quality reference standards for accurate diagnostic accuracy and the development of AI algorithms. Full article

We evaluated the effects of supplementing 1,3-diacylglycerol (1,3-DAG) in diets with different energy levels on the growth performance, nutrient digestibility, excreta scores, rectal temperature, meat quality, and blood parameters of broilers. A total of 576 one-day-old Ross 308 broilers (initial BW: 47.65 ± 0.51 g) were used in a 35-day feeding trial. The broilers were randomly assigned to four treatment groups (144 birds per group), with eight cages per group and 18 birds per cage, consisting of 9 males and 9 females. A 2 × 2 factorial design was employed, with two dietary energy levels (normal and reduced by 100 kcal/kg) with or without 0.075% 1,3-DAG supplementation. The results showed that compared with the diets without 1,3-DAG, the broilers receiving 1,3-DAG supplementation exhibited significantly greater body weight gain (BWG) and overall body weights (BWs) from days 10 to 35, along with a lower feed conversion ratio (FCR) (p < 0.05). In contrast, the low-energy diets without 1,3-DAG supplementation resulted in reduced growth performance, an increased FCR, higher drip loss, and lower total cholesterol levels. Notably, the rectal temperature and excreta scores were not affected by dietary energy levels or 1,3-DAG supplementation. In conclusion, while low-energy diets negatively impact growth and meat quality, 1,3-DAG supplementation enhances energy digestibility and growth performance, partially alleviating the adverse effects of reduced-energy diets and potentially lowering feed costs without compromising growth. Full article

Fatty acids (FAs) play a crucial role in human physiology, including energy production and serving as signaling molecules. However, a dysregulation in their balance can lead to multiple disorders, such as obesity and metabolic syndrome. These pathological conditions alter the balance between the heart’s energetic substrates, promoting an increased reliance on FAs and decreased cardiac efficiency. A therapeutic application of a non-psychotropic phytocannabinoid, cannabigerol (CBG), seems to be a promising target since it interacts with different receptors and ion channels, including cannabinoid receptors—CB₁ and CB₂, α2 adrenoceptor, or 5-hydroxytryptamine receptor. Therefore, in the current study, we evaluated a concentration-dependent effect of CBG (2.5 µM, 5 µM, and 10 µM) on H9c2 cardiomyocytes in lipid overload conditions. Gas–liquid chromatography and Western blotting techniques were used to determine the cellular lipid content and the level of selected proteins involved in FA metabolism, glucose transport, and the insulin signaling pathway. The glucose uptake assay was performed using a colorimetric method. Eighteen-hour CBG treatment in the highest concentration (10 µM) significantly diminished the accumulation of diacylglycerols (DAGs) and the saturation status of this lipid fraction. Moreover, the same concentration of CBG markedly decreased the level of FA transporters, namely fatty acid translocase (CD36) and plasma membrane fatty acid-binding protein (FABPpm), in the presence of palmitate (PA) in the culture medium. The results of our experiment suggest that CBG can significantly modulate lipid storage and composition in cardiomyocytes, thereby protecting against lipid-induced cellular dysfunction. Full article

ChatGPT, a prominent large language model developed by OpenAI, has rapidly become embedded in digital infrastructures across various sectors. This narrative review examines its evolving role and societal implications in three key domains: healthcare, education, and the economy. Drawing on recent literature and examples, the review explores ChatGPT’s applications, limitations, and ethical challenges in each context. In healthcare, the model is used to support patient communication and mental health services, while raising concerns about misinformation and privacy. In education, it offers new forms of personalized learning and feedback, but also complicates assessment and equity. In the economy, ChatGPT augments business operations and knowledge work, yet introduces risks related to job displacement, data governance, and automation bias. The review synthesizes these developments to highlight how ChatGPT is driving digital transformation while generating new demands for oversight, regulation, and critical inquiry. It concludes by outlining priorities for future research and policy, emphasizing the need for interdisciplinary collaboration, transparency, and inclusive access as generative AI continues to evolve. Full article

Mammalian fertilization is triggered by a series of calcium (Ca²⁺) oscillations that are essential for egg activation and successful embryo development. It is widely accepted that Phospholipase C zeta (PLCζ) is the sperm-derived factor that triggers these oscillations, initiating egg activation through the hydrolysis of phosphatidylinositol 4,5-bisphosphate (PIP₂) into inositol 1,4,5-trisphosphate (IP₃) and diacylglycerol (DAG), leading to Ca²⁺ release. Several studies have reported a number of PLCζ mutations associated with polyspermy, egg activation failure and early embryonic arrest. Herein, six infertility-linked PLCζ mutations (I120M, L246F, L277P, S350P, A384V and M578T) spanning different domains of PLCζ were selected for characterization through in vivo assessment of their Ca²⁺-oscillation-inducing activities and complementary in silico analysis. Our data revealed that five of the investigated PLCζ mutants exhibited reduced or complete loss of in vivo Ca²⁺-oscillation-inducing activity, with the exception of the L277P, which resulted in increased frequency and duration of Ca²⁺ oscillations. Molecular modeling of PLCζ mutants was consistent with the in vivo characterization, revealing that most mutations have a deleterious effect on the structural stability. For the first time, we provide evidence that a gain-of-function PLCζ mutation may be a cause of fertilization failure in humans. Our findings suggest that PLCζ enzymatic activity must operate within an optimal range to ensure successful egg activation and early embryonic development. Additionally, we demonstrate the essential role of all PLCζ domains in maintaining the Ca²⁺ oscillation-inducing activity in eggs and the importance of PLCζ functionality in human fertilization. Full article

Cortisol, the main glucocorticoid in teleost, plays a central role in mediating the physiological response to stress by regulating metabolism, immune function, and growth. While its transcriptional effects are well known, its role in modulating chromatin accessibility in fish skeletal muscle remains poorly understood. In this study, we investigated the epigenomic and transcriptomic changes induced by cortisol in a juvenile rainbow trout’s (Oncorhynchus mykiss) skeletal muscle using ATAC-seq and RNA-seq. Fish were treated with a single intraperitoneal dose of cortisol (10 mg/kg) or vehicle, and muscle samples were collected 3 h post-treatment. ATAC-seq analysis revealed a total of 163,802 differentially accessible regions (DARs), with an important enrichment of open regions near transcription start sites and promoters. A total of 1612 and 1746 differentially accessible genes (DAGs) were identified in the cortisol and control groups, respectively. Motif enrichment analysis identified 89 transcription factors to be significantly enriched, among which key stress-responsive regulators such as Fos, AP-1, FoxO1/3, Mef2a/b/c, Klf5/10, and ATF4 were prominently represented. RNA-seq analysis identified 4050 differentially expressed genes (DEGs), with 2204 upregulated genes involved in autophagy, mitophagy, and FoxO signaling, while 1864 downregulated genes were enriched in spliceosome and chromatin remodeling pathways. Integrative analysis revealed 174 overlapping genes between ATAC-seq and RNA-seq datasets, highlighting pathways linked to autophagy and ATP-dependent chromatin remodeling. Four selected DEGs (sesn1, sesn2, cullin3, samtor) were validated by qPCR, showing high concordance with transcriptomic data. These findings provide new insights into cortisol-mediated regulation of chromatin dynamics and gene expression in teleost skeletal muscle and underscore the importance of epigenetic mechanisms in fish stress responses. Full article

A Bayesian network (BN) is an uncertainty processing model that simulates human cognitive thinking on the basis of probability theory and graph theory. Its network topology is a directed acyclic graph (DAG) that can be manually constructed through expert knowledge or automatically generated through data learning. However, the acquisition of expert knowledge faces problems such as excessively high labor costs, limited expert experience, and the inability to solve large-scale and highly complex DAGs. Moreover, the current data learning methods also face the problems of low computational efficiency or decreased accuracy when dealing with large-scale and highly complex DAGs. Therefore, we consider mining fragmented knowledge from the data to alleviate the bottleneck problem of expert knowledge acquisition. This generated fragmented knowledge can compensate for the limitations of data learning methods. In our work, we propose a new binary stochastic fractal search (SFS) algorithm to learn DAGs. Moreover, a new feature selection (FS) method is proposed to mine fragmented knowledge. This fragmented prior knowledge serves as a soft constraint, and the acquired expert knowledge serves as a hard constraint. The combination of the two serves as guidance and constraints to enhance the performance of the proposed SFS algorithm. Extensive experimental analysis reveals that our proposed method is more robust and accurate than other algorithms. Full article

With the demand for workflow processing driven by edge computing in the Internet of Things (IoT) and cloud computing growing at an exponential rate, task scheduling in heterogeneous distributed systems has become a key challenge to meet real-time constraints in resource-constrained environments. Existing studies now attempt to achieve the best balance in terms of time constraints, energy efficiency, and system reliability in Dynamic Voltage and Frequency Scaling environments. This study proposes a two-stage collaborative optimization strategy. With the help of an innovative algorithm design and theoretical analysis, the multi-objective optimization challenges mentioned above are systematically solved. First, based on a reliability-constrained model, we propose a topology-aware dynamic priority scheduling algorithm (EAWRS). This algorithm constructs a node priority function by incorporating in-degree/out-degree weighting factors and critical path analysis to enable multi-objective optimization. Second, to address the time-varying reliability characteristics introduced by DVFS, we propose a Fibonacci search-based dynamic frequency scaling algorithm (SEFFA). This algorithm effectively reduces energy consumption while ensuring task reliability, achieving sub-optimal processor energy adjustment. The collaborative mechanism of EAWRS and SEFFA has well solved the dynamic scheduling challenge based on DAG in heterogeneous multi-core processor systems in the Internet of Things environment. Experimental evaluations conducted at various scales show that, compared with the three most advanced scheduling algorithms, the proposed strategy reduces energy consumption by an average of 14.56% (up to 58.44% under high-reliability constraints) and shortens the makespan by 2.58–56.44% while strictly meeting reliability requirements. Full article

In fractional routing, the flows are distributed through different paths; this allows the maximum efficiency to be achieved by using several partial capacities to balance flow. However, the mathematical formalism for dynamic and scalable implementation is yet to be developed. This paper proposes the aforementioned hybrid framework of edge-linear transformations, AIs, and QCs for fractional routing optimizations. The system encodes flows by means of vector linear transformations over finite fields, supports real-time reconfiguration via deep reinforcement learning, and employs quantum algorithms such as QAOA and HHL for efficient minimization of path costs. The Python 3-based implementations of the model were utilized to test DAGs of a small- and medium-scale, showing a 30% increase in computational efficiency and a 25% drop in runtime compared to classical implementations. The evidence states that the practical-scalability results can be used for the real-time applications of emerging IoT and 6G networks. Full article

The need to prevent crossing planetary boundaries has accelerated sustainable product development and production research. This resulted in the introduction of tools and methods to support the development of sustainable products. However, practice is still challenged by changing requirements, regulations, guidelines, and a plethora of tools. This study aims to identify different tools and methods that support transferring sustainability aspects into technical requirements during product and production development through a systematic literature review in Scopus. The search was limited to articles in the engineering, manufacturing sector, and journal or conference publications in the period between 2014 and 2024. Multiple authors were involved in the selection process to avoid bias. 56 articles were selected and analyzed based on purpose, user, production support, and utilization of the requirements management process. Results indicated that good support for product development and design engineers exists, but not for production, product production co-development, and other stakeholders. A need for a requirements management-based method to support the integration of sustainability aspects during product production co-development is identified. A research framework and three research strands are proposed based on this identified need, which will be developed as future work. Exclusion criteria can introduce some limitations, but the review provides an extensive overview of existing methods and gaps. Full article