Search Results (2,669)

Comparative studies report inconsistent peptide yields, bioactivities, and sensory outcomes for Alcalase across substrates, creating uncertainty about when it should be favored over other proteases. This study mapped research on hydrolysis of food proteins with Alcalase to quantify scientific output, organize thematic trends, and identify gaps relevant to peptide-based functional foods. A bibliometric analysis of Web of Science records (2004–2024) was performed in R (bibliometrix), using co-occurrence networks, temporal overlays, and conceptual mapping. The dataset comprised 203 documents from 78 sources, exhibiting a 10.3% annual growth rate and a 36.9% international co-authorship rate. Themes clustered around antioxidant and angiotensin-converting enzyme (ACE) inhibitory peptides, particularly in dairy and marine matrices, are supported by workflows combining Alcalase hydrolysis with size-guided ultrafiltration, RP-HPLC (Reverse Phase High-Performance Liquid Chromatography), and, more recently, in silico analyses and encapsulation studies. Recurrent limitations were identified: heterogeneous hydrolysates and uneven reporting that hinder sequence–activity correlations, gastrointestinal degradation and bitterness affecting applicability, and scale-up and purification choices influencing feasibility. The mapping clarified where Alcalase enables bioactive peptide generation and highlighted practical priorities, including protocol standardization and enzyme benchmarking, the integration of peptidomics and machine learning with targeted assays, and formulation-focused validation (encapsulation, stability, and delivery) to bridge in vitro activity to real-world use. These directions support the production of reproducible, application-ready peptide ingredients. Full article

Background: The accelerated convergence of the Internet of Things (IoT) and Blockchain is reconfiguring logistics, yet knowledge regarding their operationalisation for real-time inventory management remains fragmented. Methods: A Bibliometric–Systematic Literature Review (B-SLR) was conducted on peer-reviewed sources from Scopus and Web of Science (2019–2025), utilising science mapping to visualise intellectual and conceptual structures. Results: The analysis reveals a steep rise in publications during 2024–2025, identifying traceability, smart contracts, and integrity mechanisms as central themes. The synthesis supports a layered theoretical model linking transparency (sensing) and trust (ledger validation) to efficiency and supply chain resilience in Industry 5.0. The review highlights unresolved issues, including interoperability and privacy-by-design, alongside emerging directions such as digital twins. Conclusions: While scholarship has expanded rapidly, it remains weighted toward adoption mapping, underscoring the need for empirical, context-aware models that explain socio-technical integration and its measurable impacts on logistics performance. Full article

The automatic detection of foliar nutritional deficiencies through computer vision represents a promising alternative within precision agriculture practices, reducing dependence on laboratory analyses and the subjectivity associated with visual inspection. This systematic review maps and compares the application of machine learning (ML) and deep learning (DL) techniques to nutritional diagnosis across different crops, highlighting methodological trends, barriers to model adoption under field conditions, and existing research gaps. Following the PRISMA guidelines (PRISMA-P and PRISMA-2020), searches were conducted in the Scopus, IEEE Xplore, and Web of Science databases, using a defined time frame and explicit inclusion and exclusion criteria, resulting in 200 articles included (2012–2026; last search on 2 February 2026). The results indicate a predominance of DL-based approaches and RGB imagery, with applications concentrated in crops such as rice and in macronutrients, mainly nitrogen (N), phosphorus (P), and potassium (K), and report a marked increase in publications from 2020 onward. Although many studies report high performance, the evidence is largely derived from controlled environments and proprietary datasets, which limit model comparability, reproducibility, and generalization to real-world scenarios. Accordingly, the main research gaps include limited validation under field conditions, identified as the primary practical barrier; the underrepresentation of micronutrients and multiple-deficiency diagnosis; and the need for lightweight architectures suitable for deployment in mobile and edge-computing applications. It is concluded that ML and DL techniques offer promising alternatives for automated nutritional diagnosis; however, advances in data standardization, open-access datasets, and validation under real field conditions are essential for consolidating these technologies in practical applications. Full article

Background/Objectives: Clinical and scientific professionalization in orthodontics requires a comprehensive understanding of the biomechanical principles governing force generation and distribution produced by orthodontic appliances, beyond purely esthetic considerations. In this context, finite element analysis (FEA) has emerged as a fundamental computational tool for the detailed evaluation of the biomechanical behavior of the dentoalveolar system. The aim of this study was to map and synthesize the available scientific evidence on the application of FEA in the assessment of force distribution, tooth movement, and the mechanical response of periodontal tissues during orthodontic treatment. Methods: Original studies published between 2020 and 2025 that relied exclusively on computational simulations using FEA were included. Eligible studies addressed orthodontic biomechanics, including tooth movement, appliance–tooth–periodontium interactions, or the mechanical evaluation of orthodontic attachments. Clinical studies, narrative reviews, and articles without finite element modeling were excluded. A systematic literature search was conducted in the PubMed and ScienceDirect databases to answer the following question: Which FEA methodologies have been used to evaluate the biomechanical behavior of orthodontic appliances? Results: Data were categorized according to key biomechanical variables. The findings indicate an increasing use of FEA as a supportive tool in orthodontic research. However, significant limitations were identified, including lack of methodological standardization, limited model validation, and insufficient correlation between computational outcomes and clinical evidence. Conclusions: Currently, FEA in orthodontics is used predominantly for descriptive purposes, particularly for visualizing stress and strain distributions. Greater standardization and validation are required to enhance its translational applicability in clinical relevance. Full article

Background/Objectives: Anesthesia for intracranial neurosurgery presents unique challenges because of the sensitivity of the brain to perioperative physiological disturbances, yet neuroanesthetic practice remains highly variable and supported by a limited high-level evidence base. We conducted a scoping review to map and characterize multicenter randomized controlled trials (RCTs) evaluating perioperative management strategies in adults undergoing intracranial neurosurgery. Methods: This scoping review was reported in accordance with the PRISMA extension for Scoping Reviews. MEDLINE, PubMed, EMBASE, Cochrane Central, and Web of Science were searched from inception to 25 June 2025. Multicenter RCTs enrolling adults undergoing intracranial neurosurgery and evaluating anesthetic, hemodynamic, ventilatory, or perioperative interventions were included. We prioritized mapping multicenter designs for their greater external validity and implementation potential. Data were extracted in duplicate and summarized descriptively. Results: Of 417 records identified, 13 multicenter trials (≥2 recruiting sites) involving 2765 participants across nine countries from 1997–2025 were included. Most trials evaluated anesthetic maintenance or opioid regimens (7/13), followed by post-craniotomy pain control (3/13), ventilation/brain relaxation strategies (1/13), antiemetic prophylaxis (1/13), and temperature management (1/13). Outcomes were predominantly short-term and process-based (hemodynamics 7/13, opioid use 7/13, emergence metrics 5/13). Patient-centered outcomes were rarely measured (mortality 1/13, functional neurological outcome 1/13, cognitive outcome 1/13; quality of life 0/13). Only one trial assessed outcomes at ≥72 h postoperatively. Over half of the included trials were judged at high risk of bias. Conclusions: Multicenter RCT activity in neuroanesthesia remains sparse and narrowly focused, highlighting the need for larger, methodologically robust trials targeting patient-centered and long-term outcomes. Full article

Background: Periodontitis is a highly prevalent chronic inflammatory disease characterized by a complex host–microbe interaction and modulated by systemic regulatory pathways, including stress-related neuroendocrine and immunological mechanisms. Mind–body movement-based interventions such as yoga, tai chi, and qigong have demonstrated beneficial effects on stress and inflammation in general medicine, yet their relevance for periodontal health has not been systematically mapped. Methods: A scoping review was conducted in accordance with the Joanna Briggs Institute methodology and the PRISMA-ScR guidelines. Eligibility criteria included studies conducted in adult human participants examining mind–body movement-based interventions in relation to periodontal health. Sources of evidence comprised peer-reviewed studies identified through systematic searches in CINAHL, BIOSIS, Embase, PubMed/MEDLINE, the Cochrane Library, Web of Science, and LIVIVO. Data were charted using a standardized extraction form capturing key study characteristics and outcomes. Eligible studies reported clinical periodontal parameters and/or biological or psychosocial outcomes related to stress or inflammation. Results: Eleven studies investigating mind–body movement-based interventions and periodontal health were included. Interventions comprised yoga, pranayama, tai chi, and qigong, with study designs ranging from one randomized controlled trial to non-randomized interventional and observational studies. Most studies reported clinical periodontal parameters and/or periodontal-related biological markers, including inflammatory, oxidative, and immune markers, and several also assessed stress-related outcomes. The interventions were applied both as adjuncts to conventional periodontal therapy and as stand-alone approaches. Overall, the included studies reported short-term changes in periodontal parameters and stress-related measures that were generally directed towards associated with improvement; however, long-term periodontal outcomes were rarely assessed. Conclusions: Mind–body movement-based interventions, such as yoga and pranayama, have been examined in relation to periodontal health, with studies reporting periodontal clinical parameters, biological markers, and stress-related outcomes. The available evidence is heterogeneous and largely limited to short-term observations. Further methodologically rigorous studies with standardized outcome measures and longer follow-up periods are needed to better characterize the relationship between mind–body interventions and their potential adjunctive relevance in periodontal care, as current evidence does not allow conclusions regarding their routine adjunctive use. Full article

This paper presents a bibliometric analysis and literature review of methodologies for optimal capital structure decision making, focusing on research published between 2000 and 2024. This study reviews current research, identifies gaps, and outlines a plan to support with financial decisions. A mixed-methods approach was employed, combining data from the Web of Science and Scopus databases using the search string “capital structure” AND (“decision making” OR “optimal structure”). The study used Bibliometrix(R), VOSviewer, and NVivo tools, and followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flowchart for choosing studies. The findings show that this field is well-developed but still changing. The intellectual structure is organized around two main clusters: one focused on testing classical theories and another oriented toward optimization and managerial applications, revealing a clear theory–practice divide. The mapping also highlights the dominance of Chinese and U.S. scholarship and the central role of practitioner-oriented journals such as Managerial Finance, indicating both a shift toward emerging markets and a strong demand for applicable research. The study provides three key contributions. First, it identifies important countries, authors, outlets, and themes. Second, it uses a method that combines bibliometric and text-mining tools. Third, it introduces a new decision-support framework that is thorough, context-sensitive, and flexible. There are some limitations. These include relying on Scopus and Web of Science, language limits, and the fact that bibliometrics cannot judge the quality of methods. Future research should empirically validate the proposed framework in different contexts, expand studies in emerging markets, test emerging theories such as Brusov–Filatova–Orekhova (BFO) theory, and develop more dynamic and stochastic models to better capture financial uncertainty. Full article

Agri-food supply chains (AFSCs) lose approximately 1.3 billion tons of food annually, posing a major challenge to environmental sustainability. Logistics deficiencies are widely recognized as key drivers of postharvest losses. However, most studies examine isolated practices, with limited attention to their interactive effects across AFSCs stages, or to the mechanism linking operation practices, theories, and empirical research framework. This study conducts a systematic literature review following the PRISMA guidelines. Using Web of Science and Scopus, 90 empirical studies published between 2001 and August 2025 were analyzed to examine how food loss occurs and is mitigated across AFSCs. The review defines the operational boundaries of AFSCs, identifies six categories of food loss drivers, and systematically maps corresponding mitigation strategies across logistics stages. Findings indicate that logistics practices alone are insufficient to achieve effective food loss reduction. The effectiveness of logistics practices depends on organizational capabilities such as digital technology for monitoring and forecasting, collaboration for coordinated decision-making, and institutional pressures that encourage sustainable operations. Drawing on Natural Resource-based View, Dynamic Capability View, and institutional theory, this study proposes an integrated research framework to guide future empirical studies. The framework also provides practical guidance for managers and policymakers seeking to advance food loss reduction and contribute to achieving SDG 12.3. Full article

Background: Healthcare supply chains (HSCs) are critical socio-technical systems that ensure the timely delivery of pharmaceuticals, medical devices, and electromedical equipment, yet they face increasing complexity due to regulatory constraints, demand uncertainty, and the growing digitalization of healthcare systems. This study aims to systematically map the HSC literature and identify its main thematic structures and research gaps. Methods: A systematic literature review was conducted following PRISMA guidelines, analyzing 705 peer-reviewed articles retrieved from the Web of Science database (PROSPERO registration: CRD42024605761). Natural language processing techniques were applied to support the analysis, including topic modeling, term frequency–inverse document frequency for keyword relevance, and Keyword in Context analysis for semantic interpretation. Results: The analysis identified six main thematic clusters and revealed a fragmented research landscape, characterized by limited integration across supply chain tiers, uneven attention to technological innovations, and marginal consideration of sustainability and implementation issues. The findings also highlight a gap between conceptual developments and real-world applications. Conclusions: This study provides a data-driven overview of the HSC research domain, highlighting key gaps and opportunities for more integrated, resilient, and efficient supply chain management. Full article

Over the years, the impact of music on the prenatal and neonatal stages of human life has gained significant scientific attention. This study provides a comprehensive bibliometric review of research investigating how music influences fetal and newborn development. Using the Scopus and Web of Science databases, a search of relevant studies published in English between January 2006 and July 2025 was conducted, whose basic criterion was the use of the following keywords: “music” and “fetus” or “fetal”. Additional terms such as “fetus development”, “fetus heart rate”, “fetus movement”, “mother–fetus relationship”, “newborn”, etc., were also utilized. In result, 75 publications were selected, and their bibliographic data and full sources were retrieved. The included studies were grouped according to two perspectives that consider the impact of music (1) on the development of the fetus and the newborn, and (2) on maternal health and mother–fetus bonding. Using VOSviewer, bibliometric mapping was performed, which allowed to obtain keyword co-occurrence network and co-authorship network. The chosen literature was then quantitatively and qualitatively analyzed. The analysis revealed a sharp upward trend in publications starting in 2015, with a temporary decline in 2020 due to the COVID-19 pandemic. The highest number of publications were from Iran. The most investigated topics were related to the fetus heart and maternal health. The most common publication type and research methodology were, respectively, article and experiment. While the key authors Lordier, L., Filippa, M., Grandjean, D., and Monaci, M.G. lead the field, the co-authorship network remains fragmented into isolated and relatively small research groups. The Journal of Maternal–Fetal and Neonatal Medicine emerged as the leading publication outlet, while the study by Graven et al. entitled “Auditory Development in the Fetus and Infant” remains the most cited work. The keyword co-occurrence network allowed the identification of three main thematic clusters indicating the physiological, clinical, and therapeutic aspects of the impact of music on fetal and neonatal development. A qualitative analysis revealed that music plays a vital role in early human development and maternal well-being, demonstrating positive effects of auditory stimuli on fetal and newborn physiology, as well as on the mother–fetus relationship, while being a non-invasive and non-pharmacological method of intervention. However, the lack of a fully connected global research community and standardized protocols for, e.g., choosing the musical repertoire, sound administration, and the duration of exposure suggests the need for increased international collaboration to further integrate music therapy into standard clinical practices for prenatal and neonatal care. Full article

The convergence of Robotics and artificial intelligence (AI) has transformed engineering by enabling the design of intelligent systems capable of learning, adapting, and performing complex tasks. These synergies are driving innovation across multiple engineering disciplines, including mechanical, materials, electrical, industrial, civil, and aerospace engineering. This review provides a comprehensive overview of the knowledge structure and emerging research directions of Robotics and AI in engineering, with the aim of identifying research trends, influential authors, leading institutions, and emerging thematic areas. Data were collected from the Web of Science and Scopus databases, covering the period from 2020 to 2025, and analyzed using bibliometric mapping techniques and performance indicators. The results reveal a sustained growth in research on autonomous systems, collaborative robots, and human–robot interaction within engineering contexts, with a strong emphasis on AI-driven optimization. Bibliometric analyses show that deep learning, reinforcement learning, and computer vision constitute the core enabling technologies structuring the field. In addition, the results highlight a high degree of international collaboration and a concentration of scientific output and impact in a limited number of leading countries, institutions, and journals. Full article

Background: Artificial Intelligence as a Medical Device (AIaMD) introduces regulatory, methodological, ethical, and clinical challenges that are not fully addressed by traditional device trial frameworks. Given rapidly evolving and jurisdiction-specific guidance, a consolidated mapping of trial design expectations and regulatory requirements is needed. Objective: To map regulatory requirements and clinical trial design approaches for AIaMD across major jurisdictions and to identify key methodological and implementation gaps relevant to adaptive/continuously learning systems. Methods: A scoping review was conducted in accordance with the PRISMA-ScR reporting guideline. Peer-reviewed literature (2017–2025) was searched in PubMed, Embase, Web of Science, and the Cochrane Library. Gray literature was identified from major regulators and policy bodies (FDA, EMA, MHRA, PMDA, WHO, CDSCO). Eligible records addressed AIaMD clinical evaluation, trial design, regulatory pathways, post-market surveillance, or reporting standards. Data were charted using a predefined extraction framework and synthesized descriptively with thematic analysis across regulatory, methodological, ethical, and clinical implementation domains. Results: Included sources demonstrate substantial heterogeneity in evidence expectations and AI-specific pathways across jurisdictions. Recurrent themes include the need for predefined change management, performance monitoring and drift controls, dataset representativeness and bias evaluation, transparency and versioning, cybersecurity, and real-world evidence integration. Reporting frameworks (SPIRIT-AI, CONSORT-AI, MI-CLAIM) are frequently cited as mechanisms to improve reproducibility and regulatory readiness. Conclusions: Evidence and regulatory expectations for AIaMD remain fragmented. Harmonization of terminology, trial design principles, and post-market governance—supported by standardized reporting—would improve clinical validity, safety assurance, and scalability across regions. This review has several limitations. As a scoping synthesis, it prioritizes breadth of coverage rather than quantitative meta-analysis. Included sources vary in methodological rigor and reporting detail, and evolving regulatory guidance may change rapidly over time. Nevertheless, integrating peer-reviewed and regulatory evidence provides a comprehensive overview of current expectations and emerging gaps. In conclusion, effective evaluation of AIaMD requires a shift from static, one-time validation toward continuous lifecycle oversight that integrates adaptive trial designs, transparent reporting standards, bias surveillance, and structured post-market monitoring. Regulatory heterogeneity currently poses significant barriers to multinational development; however, coordinated adoption of standardized evidence frameworks and collaborative governance mechanisms may reduce duplication while preserving patient safety. By translating methodological principles into operational guidance, this review aims to support regulators, sponsors, and clinical investigators in designing trials that are both scientifically rigorous and practically implementable for continuously learning systems. Full article

Handgrip strength (HGS) has been considered as an indicator of muscle strength and overall physical fitness, with increasing relevance in sports science for talent identification and performance monitoring. However, no bibliometric study has been conducted to map the HGS research landscape in athletic contexts. A bibliometric analysis was conducted in the Web of Science Core Collection database, retrieving 229 publications. Typical bibliometric laws (i.e., Price’s, Bradford’s, Lotka’s, and Zipf’s) were employed to analyze publication trends, core journals, influential authors, country contributions, and keyword co-occurrences. Annual publications increased exponentially, especially after 2019, reaching 37 documents in 2024. The Journal of Strength and Conditioning Research and Journal of Sports Medicine and Physical Fitness were the most prominent journals. The United States and Spain led in productivity and impact. Key research themes included strength, performance, body composition, and physical fitness, with HGS demonstrating significant associations with sport tasks such as throwing, racquet sports, and weightlifting. HGS constitutes an accessible and valuable tool for assessing and predicting athletic performance, especially in sports requiring upper body strength and coordination. Future research should aim to expand database inclusion and address identified gaps, such as the relationship between HGS training and sport-specific outcomes. Full article

Background/Objectives: Lower urinary tract symptoms (LUTSs), particularly nocturia and urgency, often intensify during the menopause transition and may worsen with caffeine intake and cold exposure. This review aims to synthesize evidence relevant to a hypothesized caffeine–cold interaction in transitional menopause, focusing on water homeostasis and the estrogen–transient receptor potential melastatin 8 (TRPM8) cold-sensory axis, and to propose potentially actionable, nutrition-centered intervention candidates for future testing. Methods: Structured narrative review of PubMed, Embase, Web of Science, and citation tracking (inception–January 2026). Evidence was mapped into a mechanistic framework distinguishing established from hypothesis-generating links; no formal systematic-review study selection or meta-analysis was performed. Results: Caffeine can increase urine output via renal mechanisms (adenosine receptor antagonism and natriuresis) and may lower bladder sensory thresholds. Because half-life is long and variable, afternoon intake can extend into sleep, potentially increasing awakenings and nocturnal voids. Human studies link colder indoor environments to nocturia/overactive bladder, and passive pre-bedtime heating is associated with fewer nocturnal voids. We propose that repeated nighttime cold may amplify caffeine-related diuresis and may shift urine production toward the night, while estradiol decline may heighten TRPM8-mediated cold sensory gain, potentially contributing to urgency/frequency flares. A testable 2 × 2 cold × caffeine framework can operationalize dose, timing, and metabolism, pairing voiding diaries and bedroom temperature sensing with copeptin profiling. Conclusions: Transitional menopause may represent a susceptibility window in which endocrine instability and estradiol decline could plausibly increase sensitivity to indoor cold exposure and caffeine intake, potentially contributing to nocturia and urgency. The hypothesis label ‘dual hormone suppression’ (attenuated nocturnal AVP signal plus estradiol decline) may provide a mechanistic substrate for cold-exacerbated nocturnal polyuria, while an estrogen–TRPM8 axis may amplify cold-evoked urgency. Potentially actionable candidates include chronobiological caffeine timing/management and low-burden thermal strategies; nevertheless, menopause-stage-specific epidemiologic and clinical evidence for a caffeine × cold interaction remains limited and several mechanistic links are extrapolated, so prospective diary- and biomarker-enabled studies and controlled trials are needed to validate mechanisms and refine cold-sensitive endotypes. Full article

HER2-positive/hormone-receptor-positive breast cancer represents approximately 10% of all breast cancer cases and constitutes a distinct biological entity with unique therapeutic challenges. The complex crosstalk between HER2 and estrogen receptor signaling pathways contributes to both primary and acquired resistance to anti-HER2 therapies, and the convergence of these pathways on cell cycle regulation, particularly through the cyclin D1-CDK4/6-Rb axis, has provided a compelling rationale for combining CDK4/6 inhibitors with anti-HER2 therapy. This scoping review aimed to map preclinical and clinical evidence evaluating combinations of CDK4/6 inhibitors with HER2-targeted therapy in HER2+/HR+ disease. Eligible sources included preclinical models and clinical studies assessing CDK4/6 inhibitor-based combinations with anti-HER2 therapy, identified through searches of PubMed, Embase, Cochrane Library, Web of Science and ClinicalTrials.gov. Data were charted and synthesized descriptively according to PRISMA-ScR guidelines. Preclinical studies have demonstrated synergistic antitumor activity when CDK4/6 inhibitors are combined with trastuzumab, pertuzumab, or newer HER2-targeted agents across multiple HER2+ breast cancer models. In the metastatic setting, phase II trials including MonarcHER and PATRICIA II have shown encouraging efficacy signals, while the phase III PATINA trial demonstrated a clinically meaningful 15.2-month progression-free survival benefit with palbociclib plus anti-HER2 therapy and endocrine therapy. In the neoadjuvant setting, trials including NA-PHER2 and MUKDEN-01 demonstrated marked Ki67 suppression and promising pathologic responses, supporting the exploration of chemotherapy de-escalation strategies. Despite these advances, key challenges remain including the identification of predictive biomarkers, optimal treatment sequencing, and the integration of emerging HER2-targeted agents such as trastuzumab deruxtecan. Novel CDK4/6 inhibitors including dalpiciclib and next-generation agents are expanding therapeutic options, while combination strategies incorporating CDK7 inhibition represent future therapeutic frontiers. The evolving landscape of HER2+/HR+ breast cancer treatment increasingly emphasizes precision medicine approaches that leverage cell cycle control mechanisms to overcome resistance and improve patient outcomes across all disease stages. Full article