Search Results (21,156)

Background: Voluntary Assisted Dying (VAD) legislation in Western Australia (WA) introduced new responsibilities for community pharmacists, including the safe disposal of unused VAD substances. Pharmacists may receive VAD-related enquiries; however, their preparedness, including their knowledge of VAD, remains largely unexplored. Aim: To explore Western Australian community pharmacists’ knowledge of VAD and their role as Authorised Disposers under the Voluntary Assisted Dying Act 2019 (WA). Methods: Community pharmacists in WA were invited to participate in an anonymous, online survey consisting of multiple choice and open-ended questions. Results: Of 143 respondents, 76% were aware that VAD is an end-of-life option; despite this, 64% were uncertain about its relevance to their role. Almost one-third had received VAD-related enquiries. Of these, 40% could not provide information, with half attributing this to insufficient knowledge. Among those yet to receive a VAD-related enquiry (n = 115), 75% felt ‘not confident’ to respond, with 76% attributing this to lack of knowledge. A total of 63% of participants were unaware that they may be requested to perform authorised disposal. Uncertainty surrounding the process and the legal and ethical aspects were frequently mentioned. Conclusion: WA Community pharmacists demonstrate awareness of VAD legislation but have gaps in knowledge, particularly regarding authorised disposal. Further training and resources are essential. Full article

Grotto Buddhist Niches are important spatial carriers of Buddhist cave art, containing rich architectural, artistic, and historical information. However, image data of these Buddhist niches are fragmented across multiple scales, including visual features, cultural semantics, and spatial structures, which significantly hinders cross-scale correlative analysis. To address this issue, this paper proposes a multi-scale knowledge representation method based on image semantics and ontology. Specifically, we establish a five-tier semantic description model, comprising the visual feature layer, image data layer, entity layer, cultural semantics layer, and relational layer. Furthermore, using Protégé and the classical Seven-Step Method, we develop a domain ontology named Grotto Buddhist Niche Ontology (GBNOnto) to enable unified semantic modeling of multi-scale information. Based on this ontology, a knowledge graph focusing on cave imagery is constructed, with typical caves such as Cave 38 at the Yungang Grottoes selected as case studies. The resulting graph contains 892 entity nodes and 2621 semantic relations, effectively capturing the complex interconnections among architectural typology, artistic characteristics, and cultural semantics within the selected niche instances. The proposed method enables structured and associative integration of multi-scale information in grotto Buddhist niche images. It thus provides a foundational data infrastructure and modeling framework to support effective management, knowledge retrieval, and semantic reasoning. Full article

Background/Objectives: Medication adherence is a critical determinant of therapeutic outcomes in type 2 diabetes mellitus (T2DM); however, its relationship with glycemic control remains inconsistent, particularly in real-world and socially vulnerable settings. This study aimed to evaluate medication adherence using multiple validated instruments, assess disease-related knowledge, and examine their relationship with glycemic control, with a focus on potential discordance between self-reported adherence and objective metabolic outcomes. Methods: A cross-sectional analytical study was conducted with 237 adults with T2DM receiving care in a primary health care (PHC) unit in the Brazilian Amazon. Medication adherence was assessed using the Almeida Adherence Scale, ARMS-12, and the Haynes–Sackett test, while disease-related knowledge was evaluated using the Batalla–Martínez questionnaire. Glycemic control was determined based on glycated hemoglobin (HbA1c) values obtained from clinical records within the previous three months. Descriptive and comparative analyses were performed. Results: The study population was predominantly female (64.1%) and aged 40–59 years (55.7%), with a high prevalence of socioeconomic vulnerability. Non-adherence was identified in 55.7% of participants using the Almeida Adherence Scale, whereas higher adherence rates were observed with ARMS-12 (91.1%) and the Haynes–Sackett test (72.2%). Inadequate disease-related knowledge was found in 77.2% of participants. Among individuals with available HbA1c data (n = 116), the mean HbA1c was 8.63% (SD = 1.65), and 81.9% presented inadequate glycemic control (HbA1c ≥ 7%). Notably, among participants classified as adherent by the ARMS-12 scale (91.1%), inadequate glycemic control was nonetheless present in 81.9% of those with available HbA1c data, illustrating the magnitude of the observed discordance between self-reported adherence and objective metabolic outcomes. Cross-tabulation of each adherence instrument against glycemic control showed no statistically significant associations (chi-square with Yates correction; ARMS-12: p = 0.631, φ = 0.045; Almeida Adherence Scale: p = 0.301, φ = 0.096; Haynes–Sackett: p = 0.800, φ = 0.024). Multivariable logistic regression (Nagelkerke R² = 0.321; AUC = 0.834) identified older age (aOR = 0.92; 95% CI: 0.87–0.96; p < 0.001) and higher income (aOR = 9.96; 95% CI: 2.05–48.32; p = 0.004) as independent predictors of glycemic outcome, while no adherence measure was independently associated with HbA1c ≥ 7%. A sensitivity analysis using HbA1c ≥ 8.0% revealed poor control in 59.5% of participants (n = 69/116). Conclusions: Despite varying levels of self-reported medication adherence, inadequate glycemic control was highly prevalent. The absence of statistically significant associations between self-reported adherence and HbA1c, combined with the high prevalence of poor glycemic control regardless of adherence status, is consistent with the hypothesis that adherence alone does not fully explain metabolic outcomes in T2DM. Given the cross-sectional design, no causal inferences can be drawn. These findings highlight the need for integrated care strategies in primary health care, including improved health literacy, structured pharmacotherapeutic follow-up, and the use of multiple adherence assessment tools to better inform clinical decision-making. Full article

Background: Virtual reality (VR) has attracted increasing attention in architectural design education because of its potential to support spatial cognition and embodied understanding of architectural space. Compared with conventional two-dimensional (2D) drawings and screen-based three-dimensional (3D CAD) tools, VR enables learners to experience space at a realistic scale through binocular disparity and motion parallax, which may reduce cognitive load and facilitate experiential learning. However, previous studies have mainly relied on subjective evaluations, such as questionnaires and observations, and have not sufficiently examined differences in educational effectiveness among design tools or among students with different learning levels. Objective and Methods: This study aimed to identify effective teaching tools for facilitating students’ understanding at different learning levels and to propose appropriate methods for applying VR to improve educational effectiveness. To achieve this, we proposed an objective experimental method for evaluating the effectiveness of VR in architectural design education based on students’ ability to identify incorrect content in architectural design plans. The experiment compared the performance of students using 2D drawings, 3D CAD, and VR environments and examined differences according to student grade levels (higher- and lower-year students) objectively. Results: The results revealed that both higher- and lower-year students identified more incorrect content items related to “Fitting” (such as door layouts) when using 2D drawings (finding rates were 43.8%~53.3% higher than those with 3D CAD or VR), whereas more incorrect content items related to “Furniture” size were identified when using VR (finding rates were 18.8%~56.3% higher than those with 2D drawings or 3D CAD). In addition, items related to sectional and elevation design, such as “Opening,” as well as issues concerning the size of “Space,” were identified by higher-year students regardless of the tool used. In contrast, lower-year students identified approximately twice as many of these items when using VR as when using 2D drawings. Conclusions: Based on the above results, the effectiveness of VR varied depending on both the type of design knowledge and the students’ learning levels. VR improved lower-year students’ understanding of spatial dimensions, furniture and fitting compared with conventional tools. Furthermore, VR encouraged more detailed consideration of spatial and design-related issues during architectural design tasks. These findings suggest that VR can reduce the cognitive load associated with learning architectural spatial concepts and promote experiential learning close to real spatial perception. Implications: This study supports the appropriate use of VR in architectural design education. The experimental method proposed in this study can also be used to objectively evaluate the effectiveness of educational tools other than VR before their implementation in architectural design education. Applying this method in architectural education is expected to enhance students’ awareness of architectural spatial issues and promote more comprehensive spatial understanding during the design process. Full article

Background: Inflammatory bowel disease (IBD) is a chronic condition characterized by persistent inflammation of the gastrointestinal tract. Sexual dysfunction is a common but often overlooked consequence of IBD, affecting approximately half of women and one-third of men living with the disease. Despite the significant role of sexuality in overall quality of life, discussions about sexuality frequently remain absent from clinical encounters between patients and healthcare providers. Purpose: This study aims to deepen understanding of how individuals with inflammatory bowel disease experience—and wish to approach—conversations about sexuality with healthcare professionals in specialist clinical settings. Method: A descriptive and exploratory qualitative design was employed, using semi-structured interviews with 12 individuals diagnosed with IBD, recruited from two outpatient clinics in Norway. The data were analysed using reflexive thematic analysis. Results: Our analysis generated three main themes: (1) sexuality as an overlooked dimension of IBD care, (2) unmet informational needs related to sexuality, and (3) relational prerequisites for discussing sexuality. Sexuality was seldom addressed in participants’ healthcare encounters. Only a minority had been invited into such discussions, and those experiences were typically brief. Some participants preferred not to engage in conversations about sexuality. Reported barriers included awkwardness, embarrassment, stigma, discomfort, and concerns about privacy. Participants also described limited access to reliable information and perceived some healthcare providers as insufficiently knowledgeable or dismissive when the topic was raised. Feeling safe, trusting the provider, and having an established therapeutic relationship were identified as essential conditions for discussing sexuality. Conclusion: Sexuality remains largely unaddressed in clinical encounters with individuals living with IBD. The findings reveal a gap between patients’ information needs and the support currently provided. Strengthening healthcare providers’ competence and ensuring access to appropriate resources may help create the trust and safety required for meaningful conversations about sexuality. Full article

This manuscript will present an advancement of transformative research that has been conducted at Oak Ridge National Laboratory (ORNL) over a 25-year period (2000–2025) on a variety of environmental and biological matrices. These investigations derived a fundamental understanding of how elemental detection and analysis of these matrices led to the knowledge and discovery of natural processes in plants and the environment. Each project led to the initiation of a new research area which unearthed awesome and novel breakthroughs. Highlights are listed below: 1. The preliminary research at ORNL centered on the detection of aerosols utilizing Laser-induced Breakdown Spectroscopy (LIBS) technology. The Clean Air Act Amendment (CAAA) of 1990 highlighted the importance of identifying hazardous air pollutants (HAPs) due to their impact on environmental and human health, thereby underscoring the need to detect various toxic elements. Research in aerosol chemistry aimed to identify these harmful elements released by factories during periods of increased emissions in their manufacturing processes. LIBS emerged as the most effective method for real-time, in situ measurements of metal species in both gaseous and aerosol phases. 2. An understanding of the presence of total carbon in soils gives perspective on how to develop carbon sequestration strategies. The recognition that carbon sinks can evolve back to carbon sources to emit back to the atmosphere was an important consideration. Also, the concentration of carbon in soil indicates the health of land areas for growing crops successfully. 3. The direct detection of most of the elements in a wood sample in a single emission spectrum, without sample preparation, encouraged the research to use the LIBS technique for preservative treated wood coupled with use of multivariate statistical methodology. Additionally, it encouraged the researchers to try to differentiate natural woods from different parts of the country, and it was successfully demonstrated that LIBS coupled with MVA analysis could differentiate wood of different species from each other and of similar species grown in different environments based on their elemental spectra. This was a breakthrough since it revealed a systematic approach to connect elemental scarcity and abundance to either drought or typical rainfall conditions for the hardwood trees grown in specific areas. 4. Furthermore, the research progressed to reveal physiological and developmental processes contributing to biomass production such that the variation in leaf elemental composition increases our understanding of terrestrial nutrient cycles, as well as tracking the transfer of toxic elements from soils to living organisms. 5. Recently another breakthrough viz., ionomics initiated the correlation of elements to specific genes, uncovering the function that the element performed in the plant. More recently, this has been extended from plants to fungi as well as fungi growing in symbiotic relations with plants. Full article

Background/Objectives: Exposure to high and sustained levels of non-esterified fatty acids (NEFA) in the peripartal period is the main cause of fatty liver disease in dairy cows. Rumen-protected choline is often fed as part of the nutritional management of peripartal cows, with in vivo and in vitro data indicating positive effects of this nutrient on alleviating liver lipid accumulation. Although hepatic molecular mechanisms associated with choline supply have been studied using a target gene, protein, or metabolite approach, application of high-throughput technologies could vastly enhance fundamental knowledge on the functional role of choline. The main objective was to challenge isolated hepatocytes with a mixture of NEFA and determine proteome- and metabolome-wide effects in response to choline supply. Methods: Three healthy female calves (1 d old, 30–45 kg) were sacrificed to harvest hepatocytes. During a 12 h incubation, isolated hepatocytes were challenged without NEFA (control), 1.2 mM NEFA (c9-18:1, 18:2, 16:0, 18:0, and c9-16:1 at 43.5%, 4.9%, 31.9%, 14.4%, and 5.3% of total NEFA, respectively), or NEFA for 6 h followed by 10 μM choline chloride for another 6 h (NEFA + Chol). iTRAQ labeling-based protein profiling and GC/MS-based metabolomics profiling were used to determine changes in proteins and metabolites. Differentially abundant proteins for each group comparison were determined at a threshold of 1.4-fold change. Differences in metabolite profiles were assessed via pairwise comparisons. A subset of differentially abundant proteins was validated via qRT-PCR and Western blotting. Results: Compared with the control, there were 90 proteins and 22 metabolites in the NEFA group, and 83 proteins and 29 metabolites in the NEFA + Chol. Compared with NEFA, there were 49 proteins and 17 metabolites in the NEFA + Chol group. Greater abundance of hexokinase-1 (HK1), fructose-bisphosphate aldolase (ALDOA), mitochondrial pyruvate carrier 1 (MPC1), and increased concentrations of lactate with high NEFA treatment alone suggested greater glycolytic and TCA cycle activity. Accumulation of triacylglycerol in the NEFA group was associated with lipotoxicity and markers of inflammation, such as greater abundance of prostaglandin reductase 1 (PTGR1), serious cell autophagy processes, such as greater abundance of cell division cycle 42 (CDC42), and NFκB-related proteins. Choline supplementation reduced TAG partly due to greater VLDL secretion driven by greater abundance of diacylglycerol acyltransferase (DGAT1), perilipin 3 (PLIN3), and apolipoprotein C-III (APOC3). In addition, a greater abundance of carnitine O-palmitoyltransferase 1b (CPT1B) with choline suggested enhanced mitochondrial β-oxidation. Activation of the CDC42/JNK pathway and ROS/NFκB axis-related proteins, along with depressed PI3K/AKT/RAC-related proteins, indicated enhanced mitochondrial autophagy in response to NEFA. Conclusions: Overall, data confirmed published effects of choline on TAG accumulation, VLDL secretion, and fatty acid oxidation, while highlighting negative effects of NEFA on the respiratory electron transport chain, autophagy, and inflammatory processes. Full article

Fire safety in high-rise residential buildings depends on active fire protection systems subject to technical, human, and organisational risks. Prior probabilistic models incorporating human and organisational errors (HOEs) raise expected risk-to-life by 20 to 37%, yet remain inaccessible to the owners, managers, qualified persons, and regulators who must act on them. This paper applies SHAP (SHapley Additive exPlanations) to a reconstructed Bayesian network fire risk model with Markov Chain Monte Carlo uncertainty propagation, extending the T-H-O-Risk methodology across sixteen system configurations and seven buildings in five jurisdictions (Singapore, Australia, Hong Kong, New Zealand, the UK) plus a generic reference case. Global SHAP analysis attributes 89.8% of total HOE attribution to maintenance-related factors (H7, insufficient technical handover; H8, insufficient safety check; H9, inadequate periodic inspection), reframing the primary intervention from behavioural to structural. The reconstruction reproduces 112 published ERL values with a mean absolute percentage error of 1.8% on total ERL (13.7% on the HOE increment, the layer carrying the paper’s claims) and 96% interval coverage. Attribution outputs are translated into graded, risk-informed maintenance conditions for SCDF waiver assessment. To the authors’ knowledge, this is the first Shapley values attribution of HOE factors in a building system-level Bayesian network fire risk model. Full article

Objectives: Temporomandibular disorders (TMD) are common musculoskeletal conditions in adults. The repetitive neuromusculoskeletal demands of operatic singing, together with suboptimal technique, intensive training, and psychological strain, may be associated with TMD-related symptoms. Knowledge of TMD and awareness of warning signs may support appropriate health-seeking behaviours. This study aimed to assess self-reported TMD-related symptoms and selected aspects of TMD-related knowledge among Polish opera singers. Methods: An online cross-sectional survey was conducted in 2024 among 241 adult Polish classically trained singers, including professional opera singers and vocal students (90 men and 151 women; age range, 20–73 years). Data were collected using an author-developed questionnaire and the Fonseca Anamnestic Index (FAI), a self-report screening instrument for TMD-related symptoms and symptom severity. Results: FAI scores were within the lowest symptom category in 21.6% of participants, within the mild category in 50.6%, within the moderate category in 24.5%, and within the severe category in 3.3%. Overall, 87.1% rated their TMD-related knowledge as poor or sufficient, although 89.6% recognised that TMD may adversely affect vocal technique. Conclusions: Self-reported TMD-related symptoms were frequently observed in this study sample, and responses to individual questionnaire items indicated gaps in selected areas of TMD-related knowledge. A self-reported previous diagnosis of TMD was associated with greater FAI-assessed symptom severity, whereas self-assessed TMD knowledge was not. These findings may support further evaluation of targeted education and access to appropriate clinical assessment for classically trained singers. Full article

The primary objective of this article is to examine the organizational, economic, and sustainability-related implications of implementing artificial intelligence (AI) systems in small and medium-sized enterprises (SMEs) in Poland. The study combines a survey of 112 SMEs in the Kuyavian–Pomeranian region, including 70 AI-using firms, with 13 in-depth interviews with managers. The quantitative analysis applies logit models to identify determinants of perceived AI effects on internal processes: working time and workload reduction, automation, cost effects, and creativity. The qualitative component explains how AI is adopted and embedded in business practice. The results show that AI adoption in SMEs is increasingly common but remains uneven and mostly operational. The strongest effects concern workload reduction and time efficiency, particularly in service firms and where AI is used intensively. Advanced AI adoption increases the probability of perceiving workload and cost-related effects. However, these effects should not be interpreted simply as direct cost reduction. Rather, AI improves productivity and work capacity while creating new costs related to paid tools, data preparation, integration, output verification, and governance. The interviews show that AI implementation follows a staged path: from curiosity-driven experimentation, through cognitive work augmentation, to workflow integration and, in selected cases, AI-enabled business model innovation. The transition from ad hoc use to strategic implementation depends less on firm size alone and more on process maturity, capabilities, and data readiness. Barriers also change with maturity: early-stage firms face a lack of knowledge, time, and clear use cases, whereas advanced users encounter data quality, hallucinations, security, integration, and governance problems. The study finds that sustainability considerations, particularly environmental impacts and ESG-related implications of AI, remain largely unperceived in SME decision-making. Entrepreneurs primarily interpret sustainability through the lenses of organizational resilience, long-term competitiveness, adaptability, and responsible digital transformation rather than through formal environmental metrics. The findings suggest that SME managers should implement AI gradually, link adoption to measurable process-level outcomes, and invest in AI literacy and governance. They should also integrate responsible AI principles into organizational strategy to support sustainable digital transformation. The study contributes to the literature by showing that AI adoption in SMEs should be understood not only as a productivity-enhancing process but also as a broader organizational transition shaping long-term sustainability and resilience. Full article

The rapid advancement of internet technology has transformed the tourism industry from traditional offline services to digital networked, and intelligent platforms. WebGIS has become critical infrastructure for tourism information retrieval and spatial decision-making. However, the growing volume and heterogeneity of multi-source tourism data expose fundamental limitations in conventional relational database architectures, particularly in handling complex spatial semantic queries. To address this, the present study proposes a WebGIS design methodology that integrates knowledge graphs with relational databases through a dual-database collaborative architecture. Using tourist attraction data from China’s Xinjiang Uyghur Autonomous Region as a case study, a prototype Xinjiang Smart Tourism WebGIS system was constructed, which consists of an asynchronous synchronization mechanism based on Change Data Capture (CDC) to ensure data consistency across heterogeneous databases. Subsequently, tourism semantic queries of varying depths were constructed and comprehensively tested across different data scales. The experimental results indicate that the proposed methodology effectively decouples business transactions and supports complex relationship computations, achieving shorter cross-domain semantic query times and higher latency stability. These findings offer practical guidance for designing high-performance regional tourism information services. Full article

Reactive oxygen species (ROS) and reactive nitrogen species (RNS) are critical modulators of male reproductive health, influencing sperm function, hormonal regulation, and overall fertility. While physiological levels of ROS and RNS are essential for processes such as sperm capacitation and acrosome reaction, their overproduction leads to oxidative and nitrosative stress, contributing to male infertility. Excessive ROS and RNS can damage sperm DNA, proteins, and lipids, impairing motility, viability, and fertilizing capacity. Moreover, these reactive species disrupt the hypothalamic-pituitary-gonadal (HPG) axis, leading to hormonal imbalances that further compromise reproductive function. Environmental factors, lifestyle choices, and underlying health conditions exacerbate the production of ROS and RNS, highlighting the need for preventive and therapeutic strategies. Clinically, ROS- and RNS-mediated redox imbalance has been implicated in several male reproductive disorders, including varicocele, genital tract infection and inflammation, obesity, diabetes and other metabolic disorders, and toxicant-related reproductive dysfunction. Antioxidant supplementation has shown promise in mitigating oxidative stress; however, its efficacy varies, and further research is necessary to establish standardized treatment protocols. These findings underscore the clinical relevance of integrating oxidative stress assessment with conventional semen analysis to improve risk stratification and guide targeted interventions in male infertility. This review synthesizes current knowledge on the molecular mechanisms by which ROS and RNS affect male reproduction and discusses potential clinical interventions to address oxidative and nitrosative stress in male infertility. Full article

Pine wilt disease (PWD) can spread rapidly after the disease occurs and often causes large-scale death of the pine. Therefore, the timely identification of infected trees is critical for forest conservation and effective disease management. However, early infected trees are difficult to distinguish in satellite remote sensing images. Their visual differences from healthy trees and complex background features are often subtle, and existing image-processing methods do not fully exploit heterogeneous information. To address this problem, we constructed the Naro dataset for satellite-based PWD detection and proposed SGM-RTDETR based on Real-Time Detection Transformer (RT-DETR). The proposed model consists of a Semantic–Visual Fusion Module (SVFM) and a Disease Feature Refinement Module (DFRM). In SVFM, ExG, VARI, and GLI are concatenated with RGB imagery to form a six-channel visual input, which enhances the spectral differences between diseased and non-diseased targets. In addition, textual prior knowledge is introduced into the decoder input through a Stackelberg game-based visual–text fusion strategy. This strategy helps the encoded memory features maintain clearer disease-related semantics in complex backgrounds. DFRM then performs channel recalibration, feature refinement, and residual enhancement on the fused memory features to better extract fine-grained disease cues in remote sensing scenes. Experiments on the Naro dataset show that SGM-RTDETR achieves 80.75% mAP@0.5 and 35.43% mAP@0.5:0.95, which is 2.74 percentage points higher than RT-DETR-L on mAP@0.5:0.95. Overall, the results indicate that the dual-module structure improves the precision and robustness of PWD detection in satellite remote sensing images. Full article

Toxoplasmosis remains one of the most common parasitic infections affecting humans, with significant implications for pregnancy and fetal health. Maternal primary infection during gestation can result in transplacental transmission of Toxoplasma gondii, leading to a wide spectrum of congenital disease. The risk of vertical transmission increases with gestational age, whereas disease severity is inversely related—early infections causing severe neurological and ocular damage, and late infections often resulting in subclinical forms. Advances in serological testing, including IgG avidity assays and molecular diagnostics such as PCR on amniotic fluid, have improved early detection and management. Prenatal treatment with spiramycin or pyrimethamine–sulfadiazine–folinic acid combinations has been associated with reduced transmission and less severe fetal disease in several studies, although the magnitude of benefit remains debated. Long-term follow-up is essential, as late-onset manifestations, particularly chorioretinitis and neurodevelopmental impairment, are common. This narrative review was based on a comprehensive literature search of major medical databases and summarizes current knowledge on the epidemiology, pathophysiology, diagnosis, treatment, and outcomes of toxoplasmosis in pregnancy. Particular emphasis is placed on high-prevalence countries, where greater parasite genetic diversity, distinct epidemiological patterns, and a higher burden of congenital disease pose unique clinical and public health challenges. Despite progress in understanding parasite biology, pathogenesis, and treatment efficacy, congenital toxoplasmosis continues to be underdiagnosed and underreported, especially in low-resource settings. Ongoing challenges include optimizing screening strategies, ensuring access to standardized therapies, and strengthening surveillance systems. Full article

The pathogenesis of interstitial lung diseases (ILDs) is significantly influenced by genetic factors, yet lack of consensus on the optimal timing for genetic testing and precise patient selection could hinder clinical practice. Position papers currently suggest testing patients presenting with a suspect of Familial Pulmonary Fibrosis (FPF) and with extra-pulmonary syndromic features (i.e., premature graying, cytopenias, liver cirrhosis) for genetic screening. Diagnostics rely on next-generation sequencing (NGS) to identify pathogenic/likely pathogenic variants in telomere-related and surfactant-related genes. A specialized genetic consultation is essential in the correct interpretation of test results, especially when variants of uncertain significance (VUS) are detected. Adoption of other tests, such as polygenic risk scores, could further support precision medicine in ILD care. Future research might address the knowledge gap regarding early test prescription and the role of therapy, including lung transplant stratification and antifibrotic therapy, in FPF. Full article