Search Results (84)

Background and Clinical Significance: Withdrawal symptoms from an abrupt discontinuation or rapid dose reduction in amantadine has been documented as early as 1987. Symptoms can align with several diagnoses, including but not limited to infection, fever, worsening of Parkinson’s disease, seizures, and an altered mental status. In the case described, the timely diagnosis of amantadine withdrawal was delayed due to its nonspecific presentation. Case Presentation: A man in his 60s presented with lethargy, confusion, and delayed responses. His past medical history included parkinsonism, a seizure, type 2 diabetes, and schizoaffective disorder. Outpatient medications included amantadine, benztropine, divalproex, levetiracetam, paliperidone, risperidone, and semaglutide. He was admitted for an altered mental status, and home medications were held when he became NPO. A nasogastric tube was placed, and amantadine was restarted. Following the amantadine reinitiation, the patient returned to baseline and, after ruling out other causes, was diagnosed with amantadine withdrawal. He ultimately completed a 20-day admission and was discharged to a nursing home. Conclusions: The timely diagnosis of amantadine withdrawal was delayed due to its nonspecific presentation. For patients taking amantadine, clinicians should include amantadine withdrawal in their list of differential diagnoses, and in cases of altered mentation, a careful review of the medication list is essential. Full article

Global cerebral hypoxia triggers (mal-)adaptive responses that can lead to neuronal damage. This study evaluated edaravone’s neuroprotective effects in a rat hypoxia model, focusing on sex differences, treatment durations, and behavioral outcomes. Male and female rats underwent global cerebral hypoxia induced by rocuronium, with post-hypoxia edaravone treatment. Motor coordination and activity were assessed through exploratory behavior tests. Histological analyses evaluated neuronal integrity and apoptosis, while microglial activity and gene expression were analyzed via immunofluorescence and qPCR. Edaravone showed transient neuroprotective effects on motor behavior and early immune responses, particularly in the cerebellum and hippocampus. No gross morphological damage was observed, though functional impairments occurred despite preserved cytoarchitecture. Microglial activity was initially suppressed in treated and later activated in untreated hypoxic brains, suggesting modulating immune responses. Gene expression analysis revealed region-specific, time-dependent, and sex-specific changes, including early upregulation of CCR7, S100B, and NSE in treated animals. Males were more susceptible to hypoxic damage, while females showed higher baseline resistance and better functional recovery. Seven-day edaravone treatment increased apoptotic markers in male cerebellum, indicating sex-specific differences in cell death mechanisms. These findings highlight the potential for personalized therapy and underscore the importance of considering sex differences in both research and clinical practice. Full article

Communities in the Dominican Republic (DR) face increased natural disasters, poor air quality, food insecurity, and health impacts related to climate change. We evaluated the success of a train-the-trainer program to empower community leaders, women, and at-risk youth with the knowledge and skills to increase individual and community resilience in Cristo Rey, Dominican Republic. Three in-person two-day courses were conducted between July and August 2024 at the Universidad Iberoamericana. Each session included eight lectures and collaborative learning activities on climate change science, adaptation, resilience, and health impacts. Intra-group analyses comparing pre- and post-course surveys assessed participants’ climate change awareness, literacy, and communication and response skills. One hundred and four attendees participated in the survey study. Of the 100 participants with demographic data, 55% (n = 55) were 35 years old or younger, 70% (n = 70) identified as female, and 45% (n = 45) lived in Cristo Rey. The participants reported high baseline climate change awareness. Compared to before the course, the participants reported increased literacy regarding the environmental impacts of climate change relevant to the DR and the specific health impacts (p-value < 0.05) and increased climate change-related communication and response skills (p-value < 0.001). This study suggests competency-based, regional-specific courses deployed in a train-the-trainer model, have the potential to equip community members with knowledge to protect their health. Full article

The complexity of large-scale group decision-making (LSGDM) in the digital society is becoming increasingly prominent. How to achieve efficient consensus through social networks (SNs) has become a core challenge in improving the decision quality. First, conventional clustering methods often rely on a single-distance metric, neglecting both numerical assessments and preference rankings. Second, ensuring the decision authenticity requires considering diverse behaviors, such as trust propagations, risk preferences, and minority opinion expressions, for scientific decision-making in SNs. To address these challenges, a consensus-reaching process (CRP) method based on an enhanced K-means++ clustering is proposed. The above method not only focuses on minority opinion handling (MOH), but also incorporates decision indicator sets (DISs) to analyze the degree of opinion divergences within groups. First, the Hamacher aggregation operator with a decay factor completes trust matrices, improving the trust representation. Second, a personalized distance metric that combines cardinal distances with ordinal distances is incorporated into the enhanced K-means++ clustering, enabling more precise clustering. Third, weights for decision-makers (DMs) and subgroups are determined based on trust levels and degree centrality indices. Fourth, minority opinions are appropriately handled via considering the diverse backgrounds and expertise of DMs, leveraging a difference-oriented DIS to detect and adjust these opinions via weight modifications until a consensus is reached. Fifth, the alternative ranking is objectively generated via DIS scores derived from multigranulation rough approximations. Finally, the feasibility of the proposed method is validated via a case study on unmanned aerial vehicle (UAV) selection using online reviews, supported by a sensitivity analysis and comparative experiments demonstrating superior performances over existing methods. The result shows that the proposed model can enhance clustering accuracies with hybrid distances, objectively measure the consensus via DISs, handle minority opinions effectively, and improve LSGDM’s overall efficiencies. Full article

Amidst the centenary reflections on Franz Kafka’s legacy, this article explores his work’s ongoing resonance with the digital age, particularly through the lens of generative AI and cloud computation. Anchored in a close reading of Kafka’s “Beim Bau der chinesischen Mauer”, this study interrogates how the spatial and temporal codes embedded in the narrative parallel the architectures of contemporary diffusion systems at the heart of AI models. Engaging with critical theory, media archaeology, and AI discourse, this article argues that the rise of large language models not only commodifies language but also recasts Kafka’s allegorical critiques of bureaucratic opacity and imperial command structures within a digital framework. The analysis leverages concepts like Kittler’s code, Benjamin’s figural cloud, and Hamacher’s linguistic dissemblance to position Kafka’s parables as proto-critical tools for examining AI’s black-box nature. Ultimately, the piece contends that Kafka’s text is less a metaphor for our technological present than a mirror reflecting the epistemological crises engendered by the collapse of semantic transparency in the era of algorithmic communication. This reframing invites a rethinking of how narrative, code, and digital architectures intersect, complicating our assumptions about clarity, control, and the digital regimes shaping contemporary culture. Full article

For many genetic disorders, there are no specific metabolic biomarkers nor analytical methods suitable for newborn population screening, even where highly effective preemptive treatments are available. The direct measurement of signature peptides as a surrogate marker for the protein in dried blood spots (DBSs) has been shown to successfully identify patients with Wilson Disease (WD) and three life-threatening inborn errors of immunity, X-linked agammaglobulinemia (XLA), Wiskott–Aldrich syndrome (WAS), and adenosine deaminase deficiency (ADAD). A novel proteomic-based multiplex assay to detect these four conditions from DBS using high-throughput LC-MS/MS was developed and validated. The clinical validation results showed that the assay can accurately identify patients of targeted disorders from controls. Additionally, 30,024 newborn DBS samples from the Washington State Department of Health Newborn Screening Laboratory have been screened from 2022 to 2024. One true presumptive positive case of WD was found along with three false positive cases. Five false positives for WAS were detected, but all of them were premature and/or low-birth-weight babies and four of them had insufficient DNA for confirmation. The pilot study demonstrates the feasibility and effectiveness of utilizing this multiplexed proteomic assay for newborn screening. Full article

The symmetrical linear Diophantine fuzzy Hamacher aggregation operators play a fundamental role in many decision-making applications. The selection of a cyber security system is of paramount importance for maintaining digital assets. It necessitates a comprehensive review of threat landscapes, vulnerability assessments, and the specific needs of the organization in order to ensure the implementation of effective security measures. Smart grid (SG) technology uses modern communication and monitoring technologies to enhance the management and regulation of electricity production and transmission. However, greater dependence on technology and connection creates new vulnerabilities, exposing SG communication networks to large-scale attacks. Unlike previous surveys, which often give broad overviews of SG design, our research goes a step further, giving a full architectural layout that includes major SG components and communication linkages. This in-depth review improves comprehension of possible cyber threats and allows SGs to analyze cyber risks more systematically. To determine the best cybersecurity strategies, this study introduces a multi-criteria group decision-making (MCGDM) approach using the linear Diophantine fuzzy Hamacher prioritized aggregation operator (LDFHPAO). In real-world applications, aggregation operators (AOs) are essential for information fusion. This research presents innovative prioritized AOs designed to address MCGDM problems in uncertain environments. We developed the LDF Hamacher prioritized weighted average (LDFHPWA) and LDF Hamacher prioritized weighted geometric (LDFHPWG) operators, which address the shortcomings of traditional operators and provide a more robust modeling approach for MCGDM challenges. This study also outlines key characteristics of these new prioritized AOs. An MCGDM approach incorporating these operators is proposed and demonstrated to be effective through an example that compares and selects the optimal cybersecurity. Full article

Background/Objectives. Cisplatin is part of the first-line treatment of advanced urothelial carcinoma. Cisplatin resistance is a major problem but may be overcome by combination treatments such as targeting epigenetic aberrances. Here, we investigated the effect of the class I HDACi entinostat and bromodomain inhibitors (BETis) on the potency of cisplatin in two pairs of sensitive and cisplatin-resistant bladder cancer cell lines. Cisplatin-resistant J82cisR and T24 LTT were 3.8- and 24-fold more resistant to cisplatin compared to the native cell lines J82 and T24. In addition, a hybrid compound (compound 20) comprising structural features of an HDACi and a BETi was investigated. Results. We found complete (J82cisR) or partial (T24 LTT) reversal of chemoresistance upon combination of entinostat, JQ1, and cisplatin. The same was found for the BETis JQ35 and OTX015, both in clinical trials, and for compound 20. The combinations were highly synergistic (Chou Talalay analysis) and increased caspase-mediated apoptosis accompanied by enhanced expression of p21, Bim, and FOXO1. Notably, the combinations were at least 4-fold less toxic in non-cancer cell lines HBLAK and HEK293. Conclusions. The triple combination of entinostat, a BETi, and cisplatin is highly synergistic, reverses cisplatin resistance, and may thus serve as a novel therapeutic approach for bladder cancer. Full article

Pancreatic ductal adenocarcinoma (PDAC) is the most lethal form of pancreatic cancer characterized by therapy resistance and early metastasis, resulting in a low survival rate. Histone deacetylase (HDAC) inhibitors showed potential for the treatment of hematological malignancies. In PDAC, the overexpression of HDAC 2 is associated with the epithelial–mesenchymal transition (EMT), principally accompanied by the downregulation of the epithelial marker E-cadherin and increased metastatic capacity. The effector cytokine transforming growth factor-β (TGF β) is known to be a major inducer of the EMT in PDAC, leading to high metastatic and invasive potential. In addition, the overexpression of HDAC 6 in PDAC is associated with reduced apoptosis. Here, we have demonstrated that a novel HDAC 2/6 inhibitor not only significantly increased E-cadherin expression in PANC-1 cells (5.5-fold) and in 3D PDAC co-culture spheroids (2.5-fold) but was also able to reverse the TGF-β-induced downregulation of E-cadherin expression. Moreover, our study indicates that the HDAC inhibitor mediated re-differentiation resulting in a significant inhibition of tumor cell invasion by approximately 60% compared to control. In particular, we have shown that the HDAC inhibitor induces both apoptosis (2-fold) and cell cycle arrest. In conclusion, the HDAC 2/6 inhibitor acts by suppressing invasion via upregulating E-cadherin mediated by HDAC 2 blockade and by inducing cell cycle arrest leading to apoptosis via HDAC 6 inhibition. These results suggest that the HDAC 2/6 inhibitor might represent a novel therapeutic strategy for the treatment of PDAC tumorigenesis and metastasis. Full article

About 20% of the world’s CO₂ emissions originate from transport. Many countries are committed to decarbonizing their transport sector. Singapore pledged to electrify a whole host of its land transportation fleet, which includes private cars, public buses, ride-hail vehicles, and motorcycles. This paper proposes a simple empirical framework to estimate the future energy demand after 100% electrification has been realized for nine selected road transport vehicle sub-classes and to calculate the carbon emission reduction potential based on various scenarios. The present energy demand for each vehicle sub-class is first calculated based on parameters like petrol and diesel consumption, heat value and density of petrol and diesel, population of vehicle type, and average mileage per vehicle sub-class. Several scenarios are presented, and an analysis is carried out to derive a range of emission factors which are used to estimate the carbon emission reduction potential. Relative to the present day, the future energy demand estimates reveal an overall reduction of 73.60%. Full electrification and a “clean” power generation mix could lead to an emission reduction as high as 93.64% across all vehicles sub-classes, with private cars having the highest reduction potential. Full article

This essay explores the notion of Mitsprechen or “with-speaking” in Paul Celan’s poetry. “With-speaking” supposes that voices in the poems actively participate and engage in a dialogue that goes beyond traditional hermeneutic frameworks. Celan’s notion of col-loquy, distinct from the conventional sense of dialogue, challenges the separation between author and interpreter, rendering the traditional concept of intertextuality inadequate. The poems, according to Celan, give voice to human destinies, making texts audible as the voices of others. This vocal dimension of Celan’s poetry has prompted extensive discussion among philosophers, particularly in France. Levinas, Blanchot, and Derrida, influenced by German phenomenology and hermeneutics, critically examine the ethical implications of speaking “about” the other. They challenge traditional hermeneutical practices, emphasizing the responsibility of interpreters to respect the unique and untranslatable character of individual voices. This critique extends to Protestant categories of interpretation, drawing on alternative Jewish perspectives on being-in-the-world and alterity. The text explores the tensions inherent in speaking “for” or “in the name of” others, especially in the context of interpreting Celan’s work, raising questions about maintaining the fundamental difference and distance that otherness implies. The discussion concludes by highlighting Werner Hamacher’s formulation of a new philology that disrupts hermeneutical violence, influenced by the critiques of Blanchot, Levinas, and Derrida, and offering an alternative way of addressing the particular challenges posed by Celan’s poetry. Full article

This review describes the development of the bioassay as a means of quantifying plant viruses, with particular attention to tobamovirus. It delves into various models used to establish a correlation between virus particle concentration and the number of induced local lesions (the infectivity dilution curve), including the Poisson, Furumoto and Mickey, Kleczkowski, Growth curve, and modified Poisson models. The parameters of each model are described, and their application or performance in the context of the tobacco mosaic virus is explored. This overview highlights the enduring value of the infectivity dilution curve in tobamovirus quantification, providing valuable insights for researchers or practitioners of bioassays and theoreticians of modeling. Full article

In this paper, based on the advantages of q-rung orthopair fuzzy sets (q-ROFSs), complex fuzzy sets (CFSs) and cubic sets (CSs), the concept of complex cubic q-rung orthopair fuzzy sets (CCuq-ROFSs) is introduced and their operation rules and properties are discussed. The objective of this paper was to develop some novel Maclaurin symmetric mean (MSM) operators for any complex cubic q-rung orthopair fuzzy numbers (CCuq-ROFNs) using Hamacher t-norm and t-conorm inspired arithmetic operations. The advantage of employing Hamacher t-norm and t-conorm based arithmetic operations with the MSM operator lies in their ability to take into account not only the interrelationships among multiple attributes but also to provide flexibility in the aggregation process due to the involvement of additional parameters. Also, the prominent characteristic of the MSM is that it can capture the interrelationship among the multi-input arguments and can provide more flexible and robust information fusion. Thus, based on the CCuq-ROF environment, we develop some new Hamacher operations for CCuq-ROFSs, such as the complex cubic q-rung orthopair fuzzy Hamacher average (CCuq-ROFHA) operator, the weighted complex cubic q-rung orthopair fuzzy Hamacher average (WCCuq-ROFHA) operator, the complex cubic q-rung orthopair fuzzy Hamacher Maclaurin symmetric mean (CCuq-ROFHMSM) operator and the weighted complex cubic q-rung orthopair fuzzy Hamacher Maclaurin symmetric mean (WCCuq-ROFHMSM) operator. Further, we develop a novel multi-attribute group decision-making (MAGDM) approach based on the proposed operators in a complex cubic q-rung orthopair fuzzy environment. Finally, a numerical example is provided to demonstrate the effectiveness and superiority of the proposed method through a detailed comparison with existing methods. Full article

The topic of the article is the status of translation and homophony in philosophy, psychoanalysis and philology. The article focuses on the question of how translation is carried out using the basic principle of equivalence of meaning by homophony and what effects this can produce. The analysis of two case studies by Freud and Lacan shows that homophonic transfer from one language to another can be extremely productive for the subjective traversal of a phantasm. It is then shown that this is not, however, of purely subjective interest. Werner Hamacher has sketched the future of philology starting from such homophonic translations; Lacan has tried to advance to another theory of language through homophonic formations. Full article

It is difficult to describe the hesitation and uncertainty of experts by single-valued information, and the differences in the importance of attributes are often ignored during the decision-making process. This paper introduces the probability and interval values into Fermatean hesitant fuzzy set (FHFS) and creatively proposes the probabilistic interval-valued Fermatean hesitant fuzzy set (PIVFHFS) to deal with information loss. This new fuzzy set allows decision makers to use interval-valued information with probability to express their quantitative evaluation, which broadens the range of information expression, effectively reflects the important degree of different membership degrees, and can describe uncertain information more completely and accurately. Under the probabilistic interval-valued Fermatean hesitant fuzzy environment, several new aggregation operators based on Hamacher operation are proposed, including the probabilistic interval-valued Fermatean hesitant fuzzy Hamacher weighted averaging (PIVFHFHWA) operator and geometric (PIVFHFHWG) operator, and their basic properties and particular forms are studied. Then, considering the general correlation between different attributes, this paper defines the probabilistic interval-valued Fermatean hesitant fuzzy Hamacher Choquet integral averaging (PIVFHFHCIA) operator and geometric (PIVFHFHCIG) operator and discusses related properties. Finally, a multi-attribute decision-making (MADM) method is presented and applied to the decision-making problem of reducing carbon emissions of manufacturers in the supply chain. The stability and feasibility of this method are demonstrated by sensitivity analysis and comparative analysis. The proposed new operators can not only consider the correlation between various factors but also express the preference information of decision makers more effectively by using probability, thus avoiding information loss in decision-making progress to some extent. Full article