Search Results (8,004)

Background/Objectives: Persistent human papillomavirus (HPV) infection can lead to malignancies of the cervix, vulva, vagina, penis, anus, and oropharynx. The increasing incidence of HPV-related head and neck cancers has raised concerns regarding potential occupational exposure and transmission risks among healthcare workers. This study aimed to systematically evaluate the evidence on occupational HPV transmission in healthcare settings. Methods: A systematic review of the literature was conducted using three electronic databases (PubMed, Scopus, and Web of Science) from inception to August 2025, following PRISMA 2020 guidelines. A total of 34 studies met the inclusion criteria and were included in the review. Expert opinions and practical recommendations from members of the European Society of Gynaecological Oncology (ESGO) Prevention Committee were included to support interpretation of the results. Results: The available literature on occupational HPV transmission was limited, with a paucity of high-quality studies. Nevertheless, existing data suggest a potential occupational risk, particularly during aerosol or smoke-generating procedures performed for cervical intraepithelial neoplasia or cervical cancer. Several studies reported the detection of HPV DNA in surgical smoke or on instruments used during such procedures, indicating possible exposure among healthcare workers. Conclusions: Although current evidence is insufficient to definitively classify HPV infection as an occupational disease, available data indicate a potential exposure risk for healthcare workers involved in HPV-related procedures. Preventive measures, like personal protective equipment, should be emphasized. HPV vaccination has been recommended by some professional societies for healthcare workers performing gynecological procedures, though further research is needed to evaluate vaccine efficacy beyond the standard age range and its cost-effectiveness in this context. Full article

Residential architectural heritage in Jilin Province, particularly along the Chinese Eastern and South Manchuria Railways, represents the most abundant and widespread form of heritage in the region. This study investigates the distinctive features of these heritage buildings, which are often overlooked due to their technological simplicity, ubiquity, and atypical nature. We analyzed 28 floor plans of residential buildings from the Russian and Japanese colonial periods using GIS technology, space syntax, and Z-score normalization. The findings reveal that (1) Russian elite housing layouts are complex and circular, while Japanese layouts consist of multiple branching combinations; Russian common housing typically has single-node, multi-branch layouts, whereas Japanese housing features multi-node, fewer-branch designs; (2) Russian houses prioritize warmth and privacy, with enclosed layouts that emphasize defensiveness, while Japanese houses focus on space efficiency, rational movement, and multifunctional design, with open layouts highlighting spatial integration and functional differentiation; (3) cultural differences are reflected in factors such as the historical rivalry between Russian and Japanese powers, natural environments, family structures, and standardized construction techniques. This study offers new insights into the cultural characteristics and historical context of Jilin Province’s railway residential heritage and supports its protection and future research. Full article

Artificial intelligence (AI) is rapidly reshaping gastrointestinal (GI) surgery by enhancing decision-making, intraoperative performance, and postoperative management. The integration of AI-driven systems is enabling more precise, data-informed, and personalized surgical interventions. This review provides a state-of-the-art overview of AI applications in GI surgery, organized into four key domains: surgical simulation, surgical computer vision, surgical data science, and surgical robot autonomy. A comprehensive narrative review of the literature was conducted, identifying relevant studies of technological developments in this field. In the domain of surgical simulation, AI enables virtual surgical planning and patient-specific digital twins for training and preoperative strategy. Surgical computer vision leverages AI to improve intraoperative scene understanding, anatomical segmentation, and workflow recognition. Surgical data science translates multimodal surgical data into predictive analytics and real-time decision support, enhancing safety and efficiency. Finally, surgical robot autonomy explores the progressive integration of AI for intelligent assistance and autonomous functions to augment human performance in minimally invasive and robotic procedures. Surgical AI has demonstrated significant potential across different domains, fostering precision, reproducibility, and personalization in GI surgery. Nevertheless, challenges remain in data quality, model generalizability, ethical governance, and clinical validation. Continued interdisciplinary collaboration will be crucial to translating AI from promising prototypes to routine, safe, and equitable surgical practice. Full article

Purpose: Pineal region tumors are rare tumors in the pediatric population, typically managed with surgical resection or biopsy, and often with radiation therapy and chemotherapy. This study aims to examine the clinical and neurocognitive outcomes of pediatric patients with pineal tumors. Methods: A retrospective analysis was conducted on pediatric patients with pineal region tumors treated at Istituto Giannina Gaslini, Genoa, from January 1998 to July 2023. Data on medical history, surgical approaches, histological findings, administered therapies, long-term outcomes using the Glasgow Outcome Scale (GOS), education level, and employment status were collected. Statistical analysis was performed using SPSS software. Results: We identified 38 patients, with germinoma being the most prevalent tumor (47.4%). Surgical interventions included endoscopic biopsy (20 patients), stereotactic biopsy (5 patients), and excisional surgery (5 patients). Thirty-three patients received chemotherapy, and 35 underwent adjuvant radiotherapy. The mean follow-up duration was 8.79 ± 5.71 years. Significant correlations were found between tumor dissemination at diagnosis and patient outcomes (p-value = 0.03). Notably, patients in GOS classes 5–6 did not significantly differ from those in classes 7–8 regarding the frequency of intervention. School dropout rates significantly differed between GOS classes 5–6 and 7–8. Conclusions: This study highlights that prognosis is strongly associated with tumor aggressiveness, and particularly dissemination at diagnosis. The findings also suggest potential cognitive impairments, possibly linked to melatonin dysfunction induced by tumor-related treatments, as indicated by school dropout and employment data. Implications for Cancer Survivors: Our results underscore the need for further investigation into the impact of pineal involvement and potential therapeutic strategies. Full article

The performances of two autosegmentation algorithms were evaluated on 28 anonymized pelvic CT scans as a pilot study for the clinical implementation of a semi-automatic workflow. Four organs at risk (OARs), namely the rectum, bladder, and femoral heads, were contoured manually by an expert radiation oncologist (RO)—considered as the ground truth (GT)—and by model-based segmentation (MBS) and deep learning (DL) algorithms. Autocontouring performances were evaluated using a qualitative scoring system, contouring time analysis, and five geometrical indices: the 95^th percentile Hausdorff Distance (95HD), Dice Similarity Coefficient (DSC), Surface Dice Similarity Coefficient (SDSC), Added Path Length (APL), and Relative Added Path Length (RAPL). Considering total median value for the four OARs, both MBS and DL showed clinically acceptable results with differences between the two algorithms being not statistically significant for almost all indices. The DL autocontouring algorithm achieved high geometric accuracy, high scores from the ROs, and consistent performances with all validation indices for every OAR. The MBS algorithm achieved high geometric accuracy for the femoral heads and bladder. The DL algorithm required 30 s to contour all the OARs, and the MBS algorithm required 90 s, showing a time gain compared with the manual contours, which took 20 min for each case. The DL autocontouring algorithm obtained promising but preliminary results with every evaluation metric and for every analyzed OAR. The application of the MBS algorithm as the only contouring tool still presents challenges. Full article

Non-contact monitoring of human vital signs using microwave radar has attracted increasing attention due to its capability to operate unobtrusively and through clothing or light obstacles. In vector network analyzer (VNA)-based radar systems, vital signs can be extracted from phase variations in the forward transmission coefficient $S_{21}$, whose sensitivity strongly depends on the electromagnetic performance of the antenna system. This work presents the design, optimization, fabrication, and experimental validation of a high-gain 12 GHz 4 × 4 microstrip patch antenna array specifically developed for phase-based vital signs monitoring. The antenna array was progressively optimized through coaxial feeding, slot-based impedance control, stepped transmission line matching, and mitered bends, achieving a simulated gain of 17.8 dBi, a measured gain of 17.06 dBi, a reflection coefficient of −26 dB at 12 GHz, and a total efficiency close to 74%. The antenna performance was experimentally validated in an anechoic chamber and subsequently integrated into a continuous-wave VNA-based radar system. Comparative measurements were conducted against a commercial biconical antenna, a single patch radiator, and an MIMO antenna under identical conditions. Results demonstrate that while respiration can be detected with moderate-gain antennas, reliable heartbeat detection requires high-gain, narrow-beam antennas to enhance phase sensitivity and suppress environmental clutter. The proposed array significantly improves pulse detectability in the (1–1.5) Hz band without relying on advanced signal processing. These findings highlight the critical role of antenna design in $S_{21}$-based biomedical radar systems and provide practical design guidelines for high-sensitivity non-contact vital signs monitoring. Full article

Severe COVID-19 and bacterial sepsis share clinical manifestations of systemic inflammation and organ dysfunction. Yet, early differentiation between these conditions and timely identification of patients at risk of deterioration remain major clinical challenges. Extracellular vesicle (EV)-associated microRNAs (miRNAs) have emerged as promising biomarkers of host immune dysregulation. In our study, we have characterized circulating EV-miRNAs in patients with COVID-19, bacterial sepsis, localized bacterial infections, and healthy subjects to assess their diagnostic and prognostic utility. After EV isolation from plasma and characterization by nanoparticle tracking analysis and flow cytometry, a panel of 12 inflammation-related miRNAs were individually quantified by qRT-PCR. Four EV-miRNAs—miR-28-5p, miR-199a-5p, miR-200a-3p, and miR-369-3p—were significantly elevated in COVID-19 patients, with higher levels in those with poor prognosis. miR-199a-5p and miR-200a-3p were increased in bacterial sepsis compared with COVID-19, enabling discrimination between viral and bacterial sepsis. Three EV-miRNAs—miR-28-5p, miR-199a-5p, and miR-200a-3p—were markedly higher in bacterial sepsis than localized infections, and ROC analysis showed a strong diagnostic performance, particularly for miR-199a-5p, alone or in combination with other EV-miRNAs. The increased expression of selected EV-miRNAs was associated with higher SOFA scores and in-hospital mortality. These findings indicate that EV-miRNAs reflect pathogen-specific and severity-related immune responses, supporting their potential as minimally invasive biomarkers for early diagnosis and risk stratification in severe infections. Full article

Accurate trajectory tracking is a key requirement in unmanned ground vehicles (UGVs) operating in autonomous driving, mobile robotics, and industrial automation. In wireless Time-Sensitive Networking (WTSN) scenarios, trajectory accuracy strongly depends on deterministic packet delivery, precise traffic scheduling, and time synchronization among distributed devices. This paper quantifies the impact of IEEE 802.1Qbv time-aware traffic scheduling on trajectory tracking accuracy in UGVs operating over Wi-Fi-enabled TSN networks. The analysis focuses on how misconfigured real-time (RT) and best-effort (BE) transmission windows, as well as clock misalignment between devices, affect packet reception and control performance. A mathematical framework is introduced to predict the number of correctly received RT packets based on cycle time, packet periodicity, scheduling window lengths, and synchronization offsets, enabling the a priori dimensioning of RT and BE windows. The proposed model is validated through extensive simulations conducted in an ROS–Gazebo environment, utilising Linux-based traffic shaping and scheduling tools. Results show that improper traffic scheduling and synchronization offsets can significantly degrade trajectory tracking accuracy, while correctly dimensioned scheduling windows ensure reliable packet delivery and stable control, even under imperfect synchronization. The proposed approach provides practical design guidelines for configuring wireless TSN networks supporting real-time trajectory tracking in mobile robotic systems. Full article

The organic fraction of municipal solid waste (OFMSW) compost has the potential to be an effective soil improver, and agriculture is the industry with the largest potential market for its adoption, followed by landscaping and gardening hobbyist uses. Understanding which factors foster the intention to adopt OFMSW compost among users engaged in agricultural activities is, therefore, crucial for its diffusion. A paper-and-pencil questionnaire was administered to 119 visitors involved in farming activities at an exhibition focused on the green and circular economy. The PROCESS macro for SPSS model 8 was applied to test a moderated mediated model to investigate the relationship between being a professional or hobby farmer, perceived drivers and the intention to adopt compost, with the moderation of the frequency of exposure to different information sources. The results showed that hobbyists perceived more drivers for compost adoption. In turn, the perceived drivers had a positive impact on users’ intention to adopt. Moreover, with a low frequency of use of information sources, professionals perceived fewer advantages of compost adoption. The present study highlighted the need to enhance discussions about compost properties and benefits, especially for professional farmers. Full article

This paper addresses the opportunities and risks of integrating Large Language Models (LLMs) into structural engineering. Exclusive reliance on LLMs is inadequate in this field, because their probabilistic nature can lead to hallucinations and inaccuracies that are unacceptable in safety-critical domains which require rigorous calculations. To resolve this dilemma, we propose adopting Neuro-Symbolic Artificial Intelligence (NSAI), a hybrid approach that balances neural intuition with symbolic rigor. The NSAI architecture employs an intelligent query system to enrich user requests and delegate critical operations to deterministic external algorithms. This system is designed to enhance reliability and support regulatory compliance, as exemplified by the 3Muri chatbot case study, an NSAI (gemini-2.5-flash)-based intelligent assistant for structural analysis software. We developed 3Muri chatbot implementing AI processes. Our experimental results, based on over 200 questions submitted to the chatbot, show that this hybrid approach achieves 94% accuracy while keeping response times below 2 s. These results validate the feasibility of deploying AI systems in safety-critical engineering domains. Full article

The construction industry’s heavy reliance on Ordinary Portland Cement (OPC) significantly contributes to global CO₂ emissions, prompting the search for sustainable alternatives. This study investigates the partial substitution of Portland cement with construction and demolition waste (CDW) powder and concrete waste (CON) powder in mortar mixes. Replacement levels of 5%, 10%, 15%, and 20% by weight were tested following EN 196-1 standards to evaluate the mechanical performance of the resulting materials. X-ray diffraction (XRD), X-ray fluorescence (XRF), and thermo-gravimetric analyses confirmed that CDW and CON powders consist mainly of quartz and calcite, with chemical compositions compatible with cementitious systems. Mechanical testing revealed that compressive strength was maintained or slightly improved at replacement levels up to 10%, while higher substitutions led to moderate reductions due to dilution effects. The use of CDW and CON powders effectively transformed a 52.5 R Type I cement into a 42.5 R Type II equivalent, demonstrating the feasibility of producing sustainable binders with acceptable performance. Full article

Background/Objectives: Reverse total shoulder arthroplasty (RTSA), a commonly performed procedure in elderly patients with osteoarthritis, is frequently complicated by postoperative infections—primarily caused by Cutibacterium acnes and coagulase-negative staphylococci (CoNS)—which remain a major clinical challenge. While standard antiseptic skin protocols can reduce the bacterial load at the surgical site, they often fail to achieve complete eradication, particularly with C. acnes, a resident species of the shoulder microbiome. Recent evidence indicates that intraoperative povidone–iodine irrigation is effective in significantly decreasing microbial burden; however, a thorough characterization of the virulence factors of the isolated strains remains essential. Methods: A total of 187 clinical strains isolated immediately after RTSA were characterized with respect to their antibiotic resistance profiles and biofilm-forming capacity, and the impact of intraoperative povidone–iodine irrigation on the reduction in bacteria that express these virulence traits was evaluated. Results: Of the 120 C. acnes isolates, 97.67% were susceptible to the tested antimicrobial agents, while only 3.33% exhibited resistance, specifically to clindamycin. In contrast, 53% of CoNS isolates were classified as susceptible, whereas the remaining 47% demonstrated multidrug resistance. Biofilm production was detected in 24% (29/120) of C. acnes and 39% (25/64) of CoNS isolates, with a statistically significant reduction observed after irrigation only for C. acnes. No association was found between biofilm formation and clindamycin resistance in C. acnes, likely due to the low number of resistant isolates. Conversely, among CoNS, a correlation was observed, with the 17.2% of biofilm-producing strains also exhibiting resistance to antimicrobial agents. Conclusions: Notwithstanding the presence of these virulence factors, povidone–iodine irrigation proved effective in substantially reducing the number of bacterial isolates recovered at the surgical site without selecting for strains with enhanced pathogenicity. Notably, the majority of resistant bacteria were detected prior to intraoperative irrigation. This intraoperative procedure may be a key approach to reducing prosthetic joint infections frequently caused by more virulent pathogens, which are unlikely to be selected following this disinfection strategy. Full article

Molting is an important biological and physiological stage in penguins, influenced by environmental and nutritional factors. Feather composition analysis before and after molting can consequently place boundaries on element bioaccumulation and excretion. We quantified and compared elemental concentrations in African penguin (Spheniscus demersus) feathers collected pre- and post-molt across three zoos to evaluate how molt stage and zoo-specific conditions influence feather elemental composition. Feathers were retrieved from individual penguins at Zoom Torino (Italy), Overloon ZooParc (Netherlands), and Zoo Magdeburg (Germany). Quantification of elemental concentrations were performed by analytical methods, with both ICP-OES and HR-ICP-MS techniques. A statistical approach involving MANOVA and factorial analysis helped identify important trends. Pre-molt features had more variability than post-molt, with both showing significant differences in elemental concentrations. Factorial analysis showed geogenic trends in Mg, Sr, and Ni trends as well as anthropogenic trends in Pb. While Na and K differed among all treatment groups, this likely points to physiological adaptations in response to increased demand during feather regrowth. Additionally, inter-zoo comparisons highlighted distinct elemental profiles linked to local environmental and dietary conditions, particularly in Zoo Magdeburg, where Na levels were markedly elevated. This study highlights the influence of environmental and dietary conditions on feather composition during molt, offering insights for improving captive penguin welfare and broader ecological implications related to climate change and pollution. Full article

Urban populations are exposed to elevated local temperatures compared to surrounding rural areas due to the urban heat island (UHI) effect, which increases health risks and energy demand. The literature highlights that accurately quantifying UHIs at broader territorial scales remains challenging because of limited microscale climate data availability and, at the same time, the difficulty of increasing the spatial coverage of the outcomes. Within the PRIN2022-PNRR CRiStAll (Climate Resilient Strategies by Archetype-based Urban Energy Modeling) project, this work addresses these limitations by coupling Urban Building Energy Modeling with archetype-based representation of urban form and high-resolution climatic data. Urban archetypes are defined as representative microscale configurations derived from combinations of urban canyon geometries and building typologies, accounting for different climatic zones, use categories, and construction periods. The proposed methodology was applied to the city of Turin (Italy), where representative urban blocks were identified and modeled to evaluate key urban context metrics under short-, medium-, and long-term climate scenarios. The UHI effect was assessed using Urban Weather Generator, while energy simulations were performed with CitySim. The urban archetype approach enables both fine spatial resolution and extensive spatial coverage, supporting urban-scale mapping. Full article