Search Results (6,389)

The continuous-flow technologies in organic synthesis for the production of active pharmaceutical ingredients (APIs) are nowadays more and more applied. In-silico process design is a powerful tool able to support organic synthesis in the field of scale-up and process development. Process design feasibility and reliability depend on the availability of a well-defined chemical reaction kinetic scheme, information which is usually derived from experimental datasets collected on purpose. The latter approach is time-consuming and demanding in terms of resources. Different possibilities are here proposed to valorize widely available experimental data from explorative works with different approaches, depending on the nature, richness, and structure of the datasets. The kinetic parameters (i.e., reaction order, kinetic constant, and activation energy) of some interesting organic reactions have been approximately estimated by applying different computational methodologies, thanks to built-in experimental databases. The numerical algebra approach dealing with linear and non-linear regression analysis for the kinetic parameters has been initially considered and related to the database information for oseltamivir synthesis. The Bayesian statistic was applied to the ibuprofen case through the application of the Markov Chain Monte Carlo (MCMC) method for reaction order estimation. At last, a Machine Learning (ML) approach has been applied to the Rolipram and Pregabalin case study. The in-house developed T-ReX experimental kinetic constant database was exploited, with application of the k-Nearest neighbor algorithm for classification and regular expression pattern recognition. Advantages and limitations of the three approaches are discussed. Full article

The use of artificial intelligence (AI) to recognize postures is a promising approach for the prevention of work-related musculoskeletal disorders (WMSDs). The aim was to conduct a systematic review with meta-analysis to assess the performance of work posture recognition systems during occupational activity. The results were reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The Google Scholar, IEEE Xplore, PubMed/MedLine, and ScienceDirect databases were screened without date restrictions. Two authors independently selected articles and extracted data. Studies were included if they presented a performance analysis of an AI deep learning (DL) or machine learning (ML) method that assessed the WMSD risk associated with working postures. Only peer-reviewed studies written in English including accuracy, precision, specificity, sensitivity, or F1-score values were included. The risk of bias was assessed using the Prediction Model Study Risk of Bias Assessment Tool. Of the 157 unique records, 58 studies were selected. The five performance parameters were investigated and averaged for seven occupational activities, eight posture categories, and the AI methods (ML vs. DL). Statistical analyses showed that DL methods produced better results. The reported systems detected sitting and standing postures with high accuracy. The solutions proposed in Manufacturing and Construction were the most numerous and the most effective on average. The major limitation lies in the wide variety of methods used. This analysis is a valuable source of information for designing new detection systems that are effective, ergonomic, easy to use, and acceptable so that humans remain at the center of the production process as defined by Industry 5.0. Full article

Contagious bovine pleuropneumonia (CBPP) is a significant respiratory disease in cattle caused by Mycoplasma mycoides subsp. mycoides (Mmm). A better understanding of the pathogenesis of CBPP and the immune response of the host to infection will assist in the development of novel interventions to prevent disease progression. In this study, bovine lung explants (BLEs) were exposed to Mmm to investigate the upregulation and release of early inflammatory cytokines, mediators and receptors following tissue infection. Immunomodulatory molecules indicative of cell activation were investigated by immunoblotting on the BLEs and the tissue culture supernatants, and quantitative real-time PCR (RTq-PCR) was performed on the BLEs to determine the fold change in the expression of the respective mRNA. Immunoblotting indicated the production of inflammatory cytokines, mediators and receptors in Mmm-infected BLEs; however, this contrasted strongly with the mRNA expression profile, which did not show any significant fold increase. Infection of the BLEs with Mmm stimulated the production of some pro-inflammatory cytokines and mediators, including IL-1β, COX-2, 5-LOX and iNOS. Toll-like receptor proteins TLR2 and TLR4 were detected solely in the tissue culture supernatant of Mmm-infected BLEs. These receptors are considered to be involved in the recognition of Mmm by BLE tissue cells, thus triggering intracellular pathways that produce specific inflammatory cytokines and mediators, initiating the inflammatory response. Full article

For communities on the margins of hostile or indifferent power structures, the political order can be experienced as a force whose acts are not motivated by reasons in accord with recognizable norms. Power, then, as a social phenomenon, is naturalized in the sense that it is dehumanized. Derrida explored some of this territory in his final seminar, the Beast and the Sovereign. Power becomes a latent animality, structuring social life as it removes itself from mechanisms of accountability. At the same time, the Black church ritual, in the United States and elsewhere, provides an experience of a self-sustaining power, whose invisibility is taken as coextensive with its omnipresence. The act of worship becomes a project of counter-habituation whereby power can be constituted as just and life-affirming. Simone Weil’s spiritual writings on the necessity of God’s love can be of some assistance here, but her concern with “decreation” is on its face a self-erasing theological enterprise, the sociopolitical implications of which would seem to put it at odds with a movement, among marginalized people, toward increased recognition. A look at the relation between Weil’s writing method—which I analyze as a kind of endophrasis—and Edmund Husserl’s transcendental understanding of the self provides a way to reorganize our understanding of the sociocultural project supported by the ritual. To grasp the counter-habituating project of the ritual, we must see it as founded in non-linguistic thinking and post-linguistic acts. These acts are, in part, improvisational, which is a key to habituating the recognition of higher-order necessity through free activity. They bring the worshiper “through” culturally determined linguistic acts to another kind of experience, in which the freedom to worship an invisible God is manifest. Full article

Background: Dieulafoy’s disease is a rare vascular anomaly of the gastrointestinal tract and an uncommon cause of acute upper gastrointestinal bleeding. Its occurrence during pregnancy is exceptionally rare, and the available literature is limited to isolated case reports that almost invariably describe acute and overt hemorrhagic presentations. As a result, atypical or clinically silent forms of the disease during pregnancy remain poorly characterized. Objective: To report an atypical case of Dieulafoy’s disease during pregnancy, presenting exclusively with severe progressive anemia in the absence of gastrointestinal symptoms and to contextualize this observation through a focused narrative review of the literature. Methods: An illustrative clinical case is presented, followed by a narrative review of the available literature on Dieulafoy’s disease in pregnancy. Particular attention was given to pregnancy-related physiological and hormonal adaptations, diagnostic challenges, therapeutic strategies, and reported maternal–fetal outcomes. All published cases identified in the literature were reviewed and summarized. Results: In the general population, Dieulafoy’s disease typically presents with sudden and overt gastrointestinal bleeding and is most commonly localized in the proximal stomach. In pregnancy, reported cases are rare and have almost exclusively involved acute hemorrhage occurring in the second or third trimester, frequently requiring urgent endoscopic intervention. Mechanical endoscopic hemostasis represents the treatment of choice and is generally associated with favorable maternal and fetal outcomes. In contrast, the illustrative case described herein demonstrates a clinically silent presentation, characterized by severe and progressive anemia without hematemesis, melena, or hematochezia, resulting in delayed diagnosis until upper gastrointestinal endoscopy identified multiple actively bleeding gastric Dieulafoy’s lesions. Conclusions: Dieulafoy’s disease should be considered in the differential diagnosis of severe, unexplained, or transfusion-dependent anemia during pregnancy, even in the absence of overt gastrointestinal bleeding. Pregnancy-related physiological adaptations may mask classic symptoms and complicate timely diagnosis. When clinically indicated, upper gastrointestinal endoscopy is safe and effective during pregnancy and remains central to both diagnosis and management. Increased awareness of atypical presentations may facilitate earlier recognition and improve maternal and fetal outcomes. Full article

Therapeutics based on RNA are commonly produced via biocatalytic approaches using RNA polymerases. The most frequently applied enzyme is the RNA polymerase of Enterobacteria phage T7. However, this enzyme has unfavorable properties, like the formation of double-stranded RNA (dsRNA). This undesired by-product can activate the innate immune system via pattern recognition receptors and cause inflammation. Removal of the contaminant is time-consuming and expensive. In this work, we applied a genome mining approach to identify unidentified single-subunit RNA polymerases with minimal dsRNA generation. A large meta database was screened, and 74 sequences were selected. Two RNA polymerases generating barely detectable amounts of dsRNA were identified from the initial sequence portfolio. Their promoters were detected via a fluorescent RNA aptamer screening, and slightly acidic transcription conditions were established. Further activity characterization showed a significant reduction of dsRNA to 0.001% and 0.02%. Due to these beneficial attributes, these RNA polymerases generate mRNA with enhanced stability, which most likely lowers the immune response towards the desired mRNA. This could be especially useful for producing long RNAs, such as self-amplifying RNA, as these typically require improved stability and low dsRNA content. Full article

(1) Background: Bioactive peptides from marine and plant sources show neuroprotective potential, yet how their combination ratios affect memory regulation via the gut–brain axis remains unclear. This study investigated the effects of different ratios of marine peptide QMDDQ (Glutamine-Methionine-Aspartate-Aspartate-Glutamine) and plant peptide AGLPM (Alanine-Glycine-Leucine-Proline-Methionine) on scopolamine-induced memory impairment in mice. (2) Methods: Cognitive function was assessed using the Morris water maze and novel object recognition tests. Nissl staining, microplate-based assays for acetylcholine (ACh) content and acetylcholinesterase (AChE) activity, Western blotting for neurotrophic factors, LC-MS/MS-based intestinal peptide profiling, and HPLC-based brain amino acid analysis were performed. (3) Results: The 1:1 ratio most effectively restored learning and memory, regulated hippocampal cholinergic function, mitigated neuronal damage, and elevated BDNF, NGF, and NTF-3 expression. In the gut, peptides were hydrolyzed into glutamate- and proline-rich fragments, which influenced brain amino acid balance by elevating glutamate and proline levels while reducing NH₃-related signaling. (4) Conclusions: These results highlight the ratio-dependent efficacy of QMDDQ-AGLPM combinations and provide evidence for a gut peptide remodeling-brain metabolic link relevant to cognitive impairment. Full article

This study examines how a voice-recognition project may support vocational secondary students’ AI literacy. In this applied scenario, students used Arduino hardware and an AI tools platform to collect data, train models, and deploy a basic voice-recognition device, linking introductory AI concepts with practical engineering applications. A mixed-methods design combined pre–post self-report assessment using the AI Literacy Questionnaire (AILQ) with post semi-structured interviews. Emerging gains were associated with the maker-learning pathway, particularly in the affective, behavioral, and cognitive AI literacy domains, whereas ethical outcomes were limited within this intervention window. Qualitative insights provided complementary interpretive context, suggesting that learning through making was experienced as more engaging and personally relevant, while hands-on linked with emerging understanding of AI model behavior and limitations. Overall, the study extends AI-literacy research to a vocational classroom setting, where evidence remains limited. It also highlights a domain-level AI literacy analysis for identifying which components strengthen through making and which may require more explicit instructional scaffolding in this specific vocational context. The exploratory nature of the study offers evidence that maker activities can provide a feasible approach for engaging vocational learners with multidimensional AI literacy. Full article

Carbapenemase-producing bacteria, particularly those expressing the KPC-3 variant, pose a critical global health threat due to their resistance to nearly all β-lactam antibiotics, including carbapenems. Rapid and reliable detection tools are urgently needed to improve infection control and guide patient management. Nanobodies (VHHs) present a promising alternative to conventional antibodies thanks to their high stability, small size, and capacity to access cryptic epitopes. Here, we report the generation and characterization of a nanobody specifically targeting KPC-3. An immune VHH phage display library was constructed, with over 90% of clones containing correctly sized inserts. After three rounds of biopanning, high-specificity binders were identified by ELISA screening. Sequencing identified a nanobody with hallmark VHH features, which was expressed and validated by ELISA and Western blot. Although kinetic assays showed no inhibition of KPC-3 enzymatic activity, interestingly, the nanobody demonstrated high-binding recognition of both KPC-2 and KPC-3 in periplasmic extracts from clinical strains. Structural modeling further supported these results, highlighting favorable interaction surfaces. This study provides the first evidence of a nanobody raised against KPC-3 that recognizes a conserved epitope shared by KPC-3 and KPC-2, underscoring its promising use as a molecular tool for detecting KPC variants and establishing a basis for future affinity maturation toward therapeutic applications. Full article

Human rhinovirus (HRV) is one of the common respiratory viral infection agents that triggers airway obstruction and asthma exacerbations, especially during childhood. This project aimed at evaluating the mechanism of ultraviolet (UV) and infrared (IR) radiations to inactivate HRV infection and replication inside and outside infected airway epithelial cells and the resulting impact on interferon responses and epithelial barrier integrity. Hereby, airway epithelial cells were infected with different RV concentrations. Later these cells are exposed to UV and IR light to analyze their impact on the viral immune response of the host by real-time PCR. It was found that RV1B disrupted cell junctions of airway epithelial cell barriers. Moreover, high doses of RV1B activated pattern recognition receptor (TLR3), induced interferon (IFN-β) response and reduced SOCS1, which is a negative regulator of IFN-β. Further, IR lights inhibited rhinovirus post infection in primary nasal epithelial cells (NECs). Finally, UVC exposure significantly inhibited the antiviral effects of the host via SOCS1 inhibition and decreased RV1B within 72 h. Collectively, these findings support the role of UV light as an effective therapeutic approach for acutely eliminating RV but resulting in barrier and antiviral damage, which can have a drawback effect for asthma. Full article

Durable responses to cancer immunotherapy remain restricted to a subset of patients, highlighting persistent gaps in understanding immune failure mechanisms. Dendritic cells (DCs) serve as the critical bridge between antigen recognition and adaptive immune activation, yet conventional molecular models centered on discrete components fail to fully explain heterogeneous therapeutic outcomes. This integrative mechanistic synthesis proposes that DC-mediated antitumor immunity is governed by higher-order structural determinants, including membrane microdomain organization, spatial compartmentalization of signaling, and temporal integration of antigenic and co-stimulatory cues. These features determine whether antigen presentation leads to effective T-cell priming or dysfunctional states such as exhaustion or anergy within the tumor microenvironment. By reanalyzing our validated 2025 experimental pipeline alongside high-impact contextual literature, we identify emergent properties of immune competence that transcend linear molecular interactions. The resulting framework distinguishes structurally mediated failure modes from classical resistance paradigms, providing a coherent non-reductionist explanation for variability in immunotherapy efficacy. Membrane raft repair is positioned as a key promising structural condition for effective immune integration, with direct relevance to translational and regulatory contexts involving non-pharmacodynamic platforms and New Approach Methodologies (NAM)-aligned evaluation strategies. This work proposes an integrative mechanistic framework to guide future hypothesis-driven studies and clinical advancement of DC-based approaches. Full article

Background/Objectives: Immune-mediated thrombotic thrombocytopenic purpura (iTTP) is a rare but life-threatening thrombotic microangiopathy in children. Secondary forms, occurring in association with immune dysregulation, autoimmune disease, or other triggers, are particularly challenging to diagnose and manage, and pediatric-specific data remain limited. This study aimed to describe the clinical characteristics, diagnostic pathways, and management of pediatric iTTP and to contextualize these findings within the recent literature. Methods: We conducted a retrospective case series of pediatric patients diagnosed with iTTP at a tertiary referral center, between November 2021 and January 2026. Clinical presentation, laboratory findings, including ADAMTS13 activity and ADAMTS13 inhibitors, associated conditions, treatment strategies, and outcomes were reviewed. In parallel, a narrative literature review was performed focusing on pediatric immune-mediated secondary TTP published over the past five years. Results: Four pediatric patients (three females, one male; median age 14 years) met inclusion criteria. All presented with severe thrombocytopenia and microangiopathic hemolytic anemia, accompanied by prominent neurologic manifestations in three cases. Severe ADAMTS13 activity deficiency (≤10%) with positive inhibitors was documented in all patients. Secondary iTTP occurred in association with evolving systemic autoimmunity, systemic lupus erythematosus, common variable immunodeficiency, or without an identifiable trigger at presentation. High clinical probability scores facilitated early diagnosis. Management required plasma exchange, corticosteroids, and targeted and immunomodulatory therapy. Conclusions: Pediatric secondary iTTP is a heterogeneous condition that frequently presents with diagnostic ambiguity and severe neurologic involvement. Early recognition, prompt initiation of TTP-directed therapy, and comprehensive immunologic evaluation are critical for favorable outcomes. Case series combined with narrative reviews remain valuable for advancing understanding and optimizing individualized care in this rare pediatric disorder. Full article

Background: Sport climbing, encompassing lead, bouldering, and speed disciplines, has transformed from a niche activity to a widely popular trend, notably after its Olympic debut at the Tokyo Games 2021. This recognition spurred an increase in publications. Despite the emerging scientific interest, terminology in climbing textbooks often relies on experiential rather than scientific understanding, leading to inconsistencies. This paper aims to standardize terminology by applying sports science frameworks, including biomechanics, training science, and sports medicine. Methods: The study reinterprets general sports science concepts for climbing-specific applications, proposing a structure of climbing skill that covers physical fitness components, biomechanical principles and techniques (body positioning), and specific components (hand and foot positioning). This integrated approach seeks to establish a coherent nomenclature, facilitating research, training, prevention, and rehabilitation within the climbing discipline. Results: Five primary climbing principles are proposed: optimal wall contact, maintained stability, center of mass shift, movement initiation from the legs and optimal climbing speed. Two technique categories—frontal and rotational—are defined in consideration of the spatial position of the pelvic frontal plane in relation to the wall surface. Each climbing technique can be described by applying the three-phase model of acyclic movements. Principles and techniques both aim to maximize efficiency in moving and resting on the climbing wall. Conclusions: A unified understanding of climbing principles and techniques is vital for progressing research, training programs, prevention strategies, and rehabilitation efforts in sport climbing. Adopting a comprehensive sports science framework promises enhanced clarity and efficacy in climbing practices, benefiting both theoretical analyses and practical applications. Full article

Human activity recognition (HAR) is essential in many applications, such as smart homes, assisted living, healthcare monitoring, rehabilitation, physiotherapy, and geriatric care. Conventional methods of HAR use wearable sensors, e.g., acceleration sensors and gyroscopes. However, they are limited by issues such as sensitivity to position, user inconvenience, and potential health risks with long-term use. Optical camera systems that are vision-based provide an alternative that is not intrusive; however, they are susceptible to variations in lighting, intrusions, and privacy issues. The paper uses an optical method of recognizing human domestic activities based on pose estimation and deep learning ensemble models. The skeletal keypoint features proposed in the current methodology are extracted from video data using PoseNet to generate a privacy-preserving representation that captures key motion dynamics without being sensitive to changes in appearance. A total of 30 subjects (15 male and 15 female) were sampled across 2734 activity samples, including nine daily domestic activities. There were six deep learning architectures, namely, the Transformer (Transformer), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), Multilayer Perceptron (MLP), One-Dimensional Convolutional Neural Network (1D CNN), and a hybrid Convolutional Neural Network–Long Short-Term Memory (CNN–LSTM) architecture. The results on the hold-out test set show that the CNN–LSTM architecture achieves an accuracy of 98.78% within our experimental setting. Leave-One-Subject-Out cross-validation further confirms robust generalization across unseen individuals, with CNN–LSTM achieving a mean accuracy of 97.21% ± 1.84% across 30 subjects. The results demonstrate that vision-based pose estimation with deep learning is a useful, precise, and non-intrusive approach to HAR in smart healthcare and home automation systems. Full article

To support ambient assisted living for the elderly living alone, we investigate a method for recognizing daily activities from household sounds. To reduce the cost of building an activity-recognition model, we adopt an unsupervised learning approach based on a Dirichlet multinomial mixture model. The model represents the generative process of neural audio codec codes conditioned on latent activities. We further extend the model to handle multiple streams of codes corresponding to different sound directions. This extension enables the formation of more accurate activity clusters, partly because code occurrence patterns exhibit burstiness. The proposed approach is expected to serve as a key component for constructing an activity recognition system that requires minimal labeled data and a small number of user inquiries. Full article