Search Results (7,153)

5a-reductase (5a-R) isozymes are essential for androgen metabolism and neurosteroid biosynthesis, linking endocrinology and neuropsychiatry. This systematic review, conducted in accordance with PRISMA 2020 guidelines, aimed to synthesize current evidence on the tissue distribution of SRD5A1, SRD5A2, and SRD5A3 and their implications in mental health. A systematic search of the PubMed, Scopus, and Web of Science databases up to February 2025 identified 257 articles, of which 83 met the inclusion criteria. SRD5A1 is broadly expressed in the liver, skin, and central nervous system, contributing to allopregnanolone synthesis; SRD5A2 is mainly restricted to androgen-dependent tissues, playing a key role in prostate development and alopecia; and SRD5A3 is associated with glycosylation processes and oncogenesis. Converging evidence suggests that impaired neurosteroidogenesis due to 5α-R inhibition may underlie vulnerability to anxiety, depression, and suicidality. While earlier epidemiological findings were heterogeneous, recent pharmacovigilance data have strengthened the evidence supporting this association. Pharmacovigilance and clinical reports show that a subset of patients treated with finasteride or dutasteride may experience persistent psychiatric and sexual adverse effects, known as post-finasteride syndrome. The current findings underscore the need for careful patient counseling, systematic monitoring, and further translational studies integrating genetics, neuroendocrine markers, and standardized psychiatric outcomes to identify individuals at risk and advance personalized medicine in this field. Full article

The rapid digital transformation of healthcare has improved clinical efficiency, patient engagement, and data accessibility, but it has also introduced significant cyber security and data privacy challenges. Healthcare IT systems increasingly rely on interconnected networks, electronic health records (EHRs), tele-medicine platforms, cloud infrastructures, and Internet of Medical Things (IoMT) devices, which collectively expand the attack surface for cyber threats. This scoping review maps and synthesizes recent evidence on cyber security risks in healthcare, including ransomware, data breaches, insider threats, and vulnerabilities in legacy systems, and examines key data privacy concerns related to patient confidentiality, regulatory compliance, and secure data governance. We also review contemporary security strategies, including encryption, multi-factor authentication, zero-trust architecture, blockchain-based approaches, AI-enabled threat detection, and compliance frameworks such as HIPAA and GDPR. Persistent challenges include integrating robust security with clinical usability, protecting resource-limited hospital environments, and managing human factors such as staff awareness and policy adherence. Overall, the findings suggest that effective healthcare cyber security requires a multi-layered defense combining technical controls, continuous monitoring, governance and regulatory alignment, and sustained organizational commitment to security culture. Future research should prioritize adaptive security models, improved standardization, and privacy-preserving analytics to protect patient data in increasingly complex healthcare ecosystems. Full article

The flavor and color profiles of vegetables are crucial in determining their nutritional value, health benefits, taste, and visual appeal. The genomic characteristics of plants control these traits. Components such as sugars, organic acids, amino acids, phenolic compounds, and essential oils, as well as color pigments like anthocyanin, chlorophyll, carotenoid, and betalain, are synthesized in plants based on their genetic structure. Environmental factors like temperature, water, light, and soil can affect the production and intensity of these components. Long-term environmental changes, such as climate change, can significantly alter the dynamics of these components. This comprehensive review focuses on the genetic and environmental interactions underlying the flavor and color profiles of vegetables, with particular emphasis on the analysis of quantitative trait loci (QTL) associated with these traits. The article discusses the identification of genes that regulate taste and color in vegetables and how these genes have been localized in QTL mapping studies. It also discusses the influence of environmental factors on taste and color, as well as gene–environment interactions. Furthermore, it focuses on how this information can be used to improve plant breeding and sustainable agriculture and emphasizes that data from QTL analyses provide valuable insights into the integration of genetic and environmental approaches to improve vegetable quality and meet consumer preferences. In conclusion, the review aims to be a valuable resource for both researchers and professionals interested in the genetic and environmental aspects of taste and color in vegetables. Full article

Digital construction implementation has not yet realized its promised potential after three decades. Across the entire project lifecycle, adoption has encountered difficulties from high-level standard guidance, a lack of strategies, fragmented delivery approaches, and insufficient digital delivery competency. Establishing digital workflows tailored to organizations’ contexts is an essential linkage of the information layer to synthesize the business and technology layers to address these challenges within the ISO 19650 framework. The uneven implementation of building information modelling (BIM) in the Architecture, Engineering, Construction, and Operation (AECO) industry provides a holistic perspective to consider the digitalization workflow dynamics. This report performs a case study through a parallel approach to examining multiple projects’ digital construction implementation of an organization in the Forest City development. Applying an observation research method and real-world data of project records, it analyses its workflows’ digitalization and process digitization, combining with its organization’s structure and overall project strategy. Moreover, it highlights bespoke digital construction ecosystems and relevant stakeholders to streamline workflows. The digital construction implementation results and project benefits as project context indicators verify that fundamental digital workflows of design quality checking, project optimization, asset data collection, and defect management have significant applicability compared with the advanced workflows of integrated 5D cost management and precast design and production. Their adoptability keeps consistency with those of applicability using the extra cost, application complexity, and disruption level indicators from the technology–organization–environment (TOE) framework to measure. These multiple project studies reveal the feasibility for organizations to achieve lifecycle digital construction implementation competency. The feasibility is underpinned by introducing an in-house digital engineering team to organization structure, cultivating applicable digital delivery capabilities through workflows digitalization and process digitization, and synthesizing ISO 19650 with workflows to enable more contextualized digital construction implementation. Full article

Organic fruit and vegetable production in the United States is increasingly popular, driven by consumer interest in foods associated with healthier lifestyles and environmentally friendly practices. This review synthesizes evidence on the production of this subsector from 1960 to 2021, using major literature databases (Agricola, ScienceDirect, and Google Scholar), to summarize health and environmental implications, economic importance, research trends, and persistent challenges. The production of fruits and vegetables is frequently reported to exhibit favorable quality and safety attributes, including higher antioxidant capacity and lower levels of cadmium, pesticides, and other chemical residues, supporting its relevance to nutrition and human health. This type of practice is also described as contributing to environmental restoration and preservation through improved soil conditions, reduced reliance on synthetic inputs, enhanced nutrient cycling, and climate-smart benefits such as increased soil organic matter and lower energy intensity. Nevertheless, it faces constraints that increase costs and limit scalability, including high labor demand, limited effectiveness and availability of some organic pest control tools, perishability, post-harvest losses, certification burdens, and market access regulations. Despite these barriers, data indicate growth: from 2007 to 2021, acreage increased by more than 100%, farm-gate value rose from $685 million to $1913 million, and the number of participating farms increased by more than 100%. Moreover, it accounts for 0.9% of the total value of the agricultural production in the U.S. Overall, the outlook for U.S. organic fruit and vegetables is encouraging, supported by expanding consumer demand, government support, and improved conditions for international trade. Full article

The high peak-to-average power ratio (PAPR) in classical high-speed digital data transmission systems with orthogonal frequency division multiplexing (OFDM) limits energy efficiency and communication range. This paper proposes a method for randomizing OFDM signals via frequency coding using synthesized pseudorandom sequences with improved autocorrelation properties, obtained through machine learning, to minimize PAPR in complex, non-stationary hydroacoustic channels for communicating with underwater robotic systems. A neural network architecture was developed and trained to generate codes of up to 150 elements long based on an analysis of patterns in previously found best short sequences. The obtained class of OFDM signals does not require regular and accurate estimation of channel parameters while remaining resistant to various types of impulse noise, Doppler shifts, and significant multipath interference typical of the underwater environment. The attained spectral efficiency values (up to 0.5 bits/s/Hz) are relatively high for existing hydroacoustic communication systems. It has been shown that the peak power of such multi-frequency information transmission systems can be effectively reduced by an average of 5–10 dB, which allows for an increase in the communication range compared to classical OFDM methods in non-stationary hydrological conditions at acceptable bit error rates (from 10⁻² to 10⁻³ and less). The effectiveness of the proposed methods of randomization with synthesized codes and frequency coding for OFDM signals was confirmed by field experiments at sea on the shelf, over distances of up to 4.2 km, with sea waves of up to 2–3 Beaufort units and mutual movement of the transmitter and receiver. Full article

Facial aging is not a singular phenomenon but a cascade of anatomical and biological transformations unfolding across the skeleton, fat, ligaments, muscles, dermis, and epidermis. Its clinical expression-volume loss, sagging, wrinkling, and surface irregularities-cannot be adequately explained by simplistic metaphors of “filling” or “lifting.” This article is a narrative review synthesizing current anatomical, physiological, and clinical evidence relevant to multimodal facial rejuvenation. Traditional monotherapies, while sometimes effective in isolation, are increasingly inadequate for contemporary patients who demand outcomes that are natural, harmonious, and durable. Modern esthetic practice has therefore shifted toward multimodal approaches that address aging across multiple planes. Hyaluronic acid (HA) fillers provide volumetric scaffolding and hydration; collagen stimulators such as poly-L-lactic acid (PLLA) and calcium hydroxylapatite (CaHA) induce neocollagenesis and long-term dermal remodeling; botulinum toxin restores balance to muscular vectors and improves expression dynamics; while energy-based devices (EBDs), including fractional lasers, radiofrequency microneedling, and high-intensity focused ultrasound (HIFU), enhance skin texture, tone, and elasticity. When applied in a sequenced and evidence-based manner, these modalities act synergistically to deliver results unattainable by any single intervention. In addition to established modalities, the field has recently witnessed aggressive promotion of “regenerative” therapies-growth factors, exosomes, platelet-rich plasma (PRP), and platelet-rich fibrin (PRF). While biologically plausible, their efficacy and safety remain uncertain due to the absence of robust, randomized clinical trials and the heterogeneity of current data. This raises a critical question: is aesthetic medicine advancing through science, or being driven by novelty and marketing? This review synthesizes current anatomical and physiological knowledge of aging, evaluates the mechanisms, clinical applications, and safety considerations of major treatment modalities, and proposes practical sequencing strategies. It also emphasizes the ethical imperative that aesthetic medicine, while innovative and fast-evolving, must remain anchored in scientific evidence and patient safety—because aesthetic medicine is, fundamentally, still medicine. Full article

The rapid expansion of health big data, encompassing genomic profiles and wearable device telemetry, has significantly escalated personal privacy risks. This systematic literature review (SLR) synthesizes 86 peer-reviewed studies (2014–2025) through the dual lens of the NIST Cybersecurity and Privacy Frameworks to evaluate emerging risks, mitigation technologies, and regulatory landscapes. Our analysis identifies unauthorized access as the predominant threat, while blockchain-based solutions comprise 22.1% of proposed interventions. However, a comparative evaluation reveals critical performance trade-offs: differential privacy mechanisms incur a 15–35% utility loss, whereas blockchain implementations impose a 40–50% computational overhead. Furthermore, an assessment of major regulatory frameworks (GDPR, HIPAA, PIPL, and emerging regional laws in Sub-Saharan Africa) elucidates significant cross-jurisdictional conflicts. To address these challenges, we propose the Bio-inspired Adaptive Healthcare Privacy (BAHP) framework, validated through retrospective case study analysis, offering a dynamic approach to securing sensitive health ecosystems. Full article

Background: Cervical intraepithelial neoplasia (CIN) represents a precancerous condition whose effective management is crucial for preventing invasive cervical cancer, a disease that remains a leading cause of cancer-related mortality among women worldwide. The long pre-invasive phase of cervical carcinogenesis and the availability of effective screening and treatment procedures make CIN a largely preventable and curable entity. Objectives: This review aimed to analyze therapeutic options applied in CIN, correlating interventions with lesion grade and guideline recommendations, in order to outline a management model adapted to the Romanian clinical setting. Materials and Methods: A structured narrative review of 20 published articles addressing cervical intraepithelial neoplasia (CIN 1–3) published between 2021 and 2023 was performed. Relevant studies were identified through a targeted literature search and analyzed descriptively. This study synthesized data from the recent literature and international clinical guidelines to identify management trends and context-specific adaptations. Results: Extracted variables included lesion grade, reported therapeutic approach (surveillance, excisional, or ablative treatment), reproductive considerations, and patient compliance, with international guidelines used as reference standards. Across the reviewed studies, excisional procedures (conization and LEEP) were predominantly reported for high-grade neoplasia (CIN 2–3), while low-grade lesions (CIN 1) were managed either conservatively or through close surveillance. Treatment decisions described in the literature were strongly influenced by patient age, fertility preservation needs, and obstetric history. Overall, management approaches reported in Romanian and international studies were broadly aligned with current guideline recommendations, although variations were observed in the expectant management of younger patients. Conclusions: The findings emphasize the importance of individualized management in cervical dysplasia, integrating lesion characteristics with patient-specific factors. While international guidelines provide a robust framework, their adaptation to the Romanian healthcare context should prioritize patient education, compliance, and structured post-treatment follow-up strategies. Full article

Municipal smart city programs remain hampered by conceptual fragmentation and the absence of validated, context-specific maturity assessments. We develop the Smart Municipality Maturity Model (SMMM) via a design-science process, synthesizing 183 publications and adapting a practitioner-oriented self-assessment with 99 binary items across ten dimensions. Validation proceeded in four stages: expert review, industry validation, a pilot with 24 municipalities, and a large-scale rollout to 1136 municipalities. The five-level model yields comparable maturity scores and reveals a structural capability gap—governance and strategy outpace foundational technical capacities, especially digital infrastructure and data management. Maturity rises with municipality size, yet leadership, partnerships, and innovation culture act as moderators. The SMMM represents one of the first empirically validated, large-scale maturity assessments tailored to municipal administrations, providing a robust analytical basis for diagnosing capability gaps at scale. Its architecture directly supports municipal policy by translating conceptual smart city ambitions into measurable, comparable operational capacities and by enabling more targeted, evidence-driven interventions. The SMMM provides a low-burden instrument for self-assessment, peer benchmarking, and evidence-based policy design. Closing the identified capability gap requires capability-first investment and more explicit integration of cybersecurity and data privacy in future models and municipal practice. Full article

Autonomous Underwater Vehicles (AUVs) play a central role in marine observation, inspection, and monitoring missions, where effective trajectory planning is essential for ensuring safe operation, reliable sensing, and efficient data transfer. In realistic underwater environments, uneven seafloor geometry, limited acoustic communication, navigation uncertainty, and sensing visibility constraints significantly influence mission performance and challenge classical planar planning formulations. This survey reviews trajectory planning methods for AUVs operating in uneven environments, with a focus on two major classes of underwater sensing missions: underwater area coverage using onboard sensors and underwater sensor data collection within underwater acoustic sensor networks (UASNs) supporting the Internet of Underwater Things (IoUT). For area coverage, the survey examines the progression from classical planar coverage strategies to terrain-aware, occlusion-aware, multi-AUV, and online planning frameworks designed to address uneven terrain and sensing visibility. For underwater sensor data collection, it reviews mobile sink-based trajectory planning strategies, including energy-aware, channel-aware, and information-based formulations based on metrics such as Age of Information (AoI) and Value of Information (VoI), as well as cooperative architectures involving unmanned surface vehicles (USVs). By synthesizing these two bodies of literature, the survey clarifies current capabilities and limitations of trajectory planning methods for AUVs operating in uneven underwater environments. Full article

Background and Objectives: The COVID-19 pandemic has led to an unprecedented mental health crisis among workers in the healthcare field, with average burnout rates increasing from about 32% before the pandemic to 46–52% during peak times and post-traumatic stress disorder (PTSD) affecting 24–34% of frontline staff. The primary objective of this article is to synthesize evidence on the prevalence of burnout and PTSD among healthcare workers before and during the COVID-19 pandemic. The secondary objectives are: (a) to examine the mechanisms and empirical evidence linking clinician mental health to medical errors and patient safety outcomes and (b) to analyze the medico-legal implications of this relationship, including malpractice liability, institutional responsibility, and opportunities for policy reform. Materials and Methods: We conducted a narrative review searching PubMed (November 2025–January 2026) using predefined keyword combinations. Inclusion criteria comprised original research, systematic reviews, and meta-analyses examining mental health outcomes or patient safety among clinical staff. Data were synthesized narratively across five thematic domains. Results: Burnout prevalence increased from approximately 32% pre-pandemic to 46–52% during peak periods, with emotional exhaustion reaching 67.5% in some settings. PTSD rates rose to 24–34% among frontline staff, exceeding pre-pandemic levels of 15–20%, with ICU staff particularly affected (27–40%). Substantial overlap exists between conditions (86–98% comorbidity). Physician burnout is associated with 2.72 times higher odds of self-reported errors (95% CI: 2.19–3.37), with each point increase in emotional exhaustion raising the error risk by 5–11%. Mechanisms include cognitive impairment (reduced executive function, g = −0.39; impaired working memory, g = −0.36) and sleep disturbance. Malpractice litigation compounds psychological harm, increasing depression and suicidal ideation. Conclusions: This review, synthesizing data from over 500,000 healthcare workers, demonstrates bidirectional relationships among burnout, PTSD, and medical errors with significant medico-legal ramifications. Addressing this crisis requires systemic interventions including workload management, psychological support, blame-free reporting cultures, and policy reforms balancing accountability with recognition of system-level contributors to error. Full article

Background: Radiomics has emerged as a promising approach to non-invasively characterize the molecular landscape of gliomas, providing quantitative, high-dimensional data derived from routine MRI. Given the recent shift toward molecularly driven classification, radiomics may support precision oncology by predicting key genomic, epigenetic, and phenotypic alterations without the need for invasive tissue sampling. This systematic review aimed to synthesize current radiomics applications for the non-invasive prediction of molecular biomarkers in gliomas, evaluating methodological trends, performance metrics, and translational readiness. Methods: This review followed the PRISMA 2020 guidelines. A systematic search was conducted in PubMed, Ovid MEDLINE, and Scopus on 10 January 2025, and updated on 1 February 2025, using predefined MeSH terms and keywords related to glioma, radiomics, machine learning, deep learning, and molecular biomarkers. Eligible studies included original research using MRI-based radiomics to predict molecular alterations in human gliomas, with reported performance metrics. Data extraction covered study design, cohort size, MRI sequences, segmentation approaches, feature extraction software, computational methods, biomarkers assessed, and diagnostic performance. Methodological quality was evaluated using the Radiomics Quality Score (RQS), Image Biomarker Standardization Initiative (IBSI) criteria, and Newcastle–Ottawa Scale (NOS). Due to heterogeneity, no meta-analysis was performed. Results: Of 744 screened records, 70 studies met the inclusion criteria. A total of 10,324 patients were included across all studies (mean 140 patients/study, range 23–628). The most frequently employed MRI sequences were T2-weighted (59 studies, 84.3%), contrast-enhanced T1WI (53 studies, 75.7%), T1WI (50 studies, 71.4%), and FLAIR (48 studies, 68.6%); diffusion-weighted imaging was used in only 7 studies (12.8%). Manual segmentation predominated (52 studies, 74.3%), whereas automated approaches were used in 13 studies (18.6%). Common feature extraction platforms included 3D Slicer (20 studies, 28.6%) and MATLAB-based tools (17 studies, 24.3%). Machine learning methods were applied in 47 studies (67.1%), with support vector machines used in 29 studies (41.4%); deep learning models were implemented in 27 studies (38.6%), primarily convolutional neural networks (20 studies, 28.6%). IDH mutation was the most frequently predicted biomarker (49 studies, 70%), followed by ATRX (27 studies, 38.6%), MGMT methylation (8 studies, 11,4%), and 1p/19q codeletion (7 studies, 10%). Reported AUC values ranged from 0.80 to 0.99 for IDH, approximately 0.71–0.953 for 1p/19q, 0.72–0.93 for MGMT, and 0.76–0.97 for ATRX, with deep learning or hybrid pipelines generally achieving the highest performance. RQS values highlighted substantial methodological variability, and IBSI adherence was inconsistent. NOS scores indicated high-quality methodology in a limited subset of studies. Conclusions: Radiomics demonstrates strong potential for the non-invasive prediction of key glioma molecular biomarkers, achieving high diagnostic performance across diverse computational approaches. However, widespread clinical translation remains hindered by heterogeneous imaging protocols, limited standardization, insufficient external validation, and variable methodological rigor. Full article

With the electrification of automotive powertrains, aerodynamic noise has emerged as the primary factor affecting vehicle comfort. This systematic review, adhering to PRISMA 2020 guidelines, bridges the gap between biological fluid mechanics and automotive engineering by synthesizing recent advances in aerodynamic mechanisms and bionic control strategies. Based on a comprehensive search of Web of Science, ScienceDirect, SAE Mobilus, and Google Scholar for the literature published between 2016 and 2025, 90 eligible studies were analyzed to provide a rigorous evidence-based synthesis. The review details complex flow phenomena, such as turbulent separation and vortex shedding across key regions like A-pillars and mirrors, drawing parallels to bio-inspired fluid–structure interactions. Numerical prediction methods, including large eddy simulation (LES), detached eddy simulation (DES), and lattice boltzmann method (LBM), are critically examined for their efficacy in resolving both conventional and bionic flow structures. A significant focus is placed on bio-inspired mitigation technologies, where quantitative findings demonstrate substantial noise suppression: specifically, the reviewed data shows that bionic riblet surfaces on tires can reduce noise levels by up to 5.18 dB, while beetle-head-inspired protuberances on exterior mirrors can achieve reductions of up to 10 dB. Finally, this work suggests future research directions in integrated fluid–acoustic–structural simulation frameworks and self-adaptive bionic systems, providing a robust reference for developing high-performance, low-noise vehicles inspired by natural organisms. Full article

Background: Salt-sensitive blood pressure (SSBP) represents a prevalent yet underrecognized hypertensive phenotype, in which blood pressure (BP) and volume status are disproportionately influenced by dietary sodium intake. Beyond BP elevation alone, salt sensitivity reflects a convergence of renal sodium handling abnormalities, neurohormonal activation, vascular dysfunction, and inflammatory pathways that link excessive sodium exposure to progressive kidney injury and adverse cardiac remodeling. Given its association with chronic kidney disease (CKD) and the association of heart failure with preserved ejection fraction (HFpEF), improved recognition of SSBP has direct clinical relevance. Objective: This narrative review aims to synthesize current mechanistic and clinical evidence on SSBP, focusing on pathophysiology, cardiorenal interactions, diagnostic challenges, and phenotype-guided therapeutic strategies with practical applicability. Methods: A narrative literature review was conducted using PubMed, Scopus, and Web of Science from inception through January 2026. Experimental, translational, and clinical studies, along with relevant guideline documents, were integrated to provide conceptual and clinical interpretation rather than quantitative analysis. Key Findings: Impaired renal sodium excretion, intrarenal RAAS activation, sympathetic overactivity, endothelial dysfunction, and immune-mediated inflammation contribute to sodium retention, microvascular dysfunction, and fibrotic remodeling across the kidney–heart axis. These pathways are strongly supported by experimental and translational data, but direct interventional clinical validation remains limited for several mechanisms. Clinically, salt-sensitive individuals often exhibit non-dipping BP patterns, albuminuria, salt-induced edema, and a predisposition to HFpEF. Dynamic BP monitoring combined with targeted laboratory assessment improves identification of this phenotype and supports individualized management. Conclusions: Early recognition of SSBP enables targeted interventions beyond uniform sodium restriction. Phenotype-guided strategies integrating lifestyle modification, RAAS blockade, thiazide-like diuretics, mineralocorticoid receptor antagonists, and sodium-glucose co-transporters 2 inhibitors (SGLT2i) may improve cardiorenal outcomes. Emerging precision tools (e.g., wearable blood-pressure sensors, digital sodium tracking technologies, etc.) remain exploratory but may further refine individualized management. Full article