Search Results (30,312)

Background and Objectives: Fears of cancer recurrence (FCR) represents one of the most common psychological problems in cancer patients. Therefore, valid and reliable measurement tools are needed to assess FCR in this population. The purpose of this study was to examine the psychometric properties of FCR scales (Fears of Cancer Recurrence-7 Item Version [FCR-7]; FCR-4 Item Version [FCR-4]; FCR-6 Item Version [FCR-6]) in Turkish hematological cancer patients. Materials and Methods: The study sample consisted of 239 hematological cancer patients undergoing treatment at four different state hospitals in Türkiye. Results: Confirmatory factor analysis results showed that all three scales had a single-factor structure (FCR-7: CFI = 0.981, TLI = 0.969, RMSEA = 0.071, SRMR = 0.028; FCR-4: CFI = 1.000, TLI = 1.001, RMSEA = 0.000, SRMR = 0.004; FCR-6: CFI = 0.981, TLI = 0.965, RMSEA = 0.087, SRMR = 0.028). The model allowing for correlated error terms between the first and second items provided the best fit. Research findings also indicated that the scales possessed strict measurement invariance across gender. Convergent and discriminant validity analyses also demonstrated expected associations between FCR scale scores and psychological well-being (r = −0.25 to −0.34) and psychological distress (r = 0.33 to 0.46) variables. The known-groups validity analysis indicated that the scales were effective at differentiating between groups and that they replicated the well-established finding from previous research that women report significantly higher levels of FCR than men (d = 0.42–0.47). Reliability analyses indicated that all three versions of the FCR scales had high internal consistency (Cronbach’s α = 0.91–0.93) and strong test–retest reliability (r = 0.85–0.87). Conclusions: Overall, the findings indicated that FCR-7, FCR-4, and FCR-6 are psychometrically sound, valid, and reliable instruments for assessing FCR in Turkish hematological cancer patients. These instruments can be used in clinical practice and research studies, as well as for evaluating intervention effectiveness in this population. Full article

This study aimed to develop a local dataset of abnormal RBC morphology from confirmed cases of anemia and thalassemia in Thailand, providing a foundation for medical image analysis and future AI-assisted diagnostics. Blood smear samples from six hematological disorders were collected between April and May 2025, with twelve regions of interest segmented into approximately 34,000 single-cell images. To characterize cell variability, a convolutional autoencoder was applied to extract latent features, while ellipse fitting was used to quantify cell geometry. Expert hematologists validated representative clusters to ensure clinical accuracy, and data augmentation was employed to address class imbalance and expand rare morphological types. From the dataset, 14,089 high-quality single-cell images were used to classify RBC morphology into 36 clinically meaningful categories. Unlike existing datasets that rely on limited or curated samples, this dataset reflects population-specific characteristics and morphological diversity relevant to Southeast Asia. The results demonstrate the feasibility of establishing scalable and interpretable datasets that integrate computational methods with expert knowledge. The proposed dataset serves as a robust resource for advancing hematology research and contributes to bridging traditional diagnostics with AI-driven clinical support systems. Full article

Background/Objectives: Cytokines play a fundamental role in the tumor microenvironment, influencing breast cancer progression, metastasis, and therapeutic resistance. The objective of this systematic review and meta-analysis was to evaluate the prognostic impact and therapeutic relevance of key cytokines in breast cancer, based on human studies published between 2015 and 2025. Methods: We systematically searched PubMed, Web of Science, and Scopus for eligible studies reporting on cytokine expression and clinical outcomes in breast cancer. Inclusion criteria were based on the PRISMA framework, focusing on human cohorts and excluding in vitro or animal models. Data were extracted on cytokine types, measurement methods, patient population, and outcomes. Meta-analyses were performed using random-effects models for cytokines with sufficient data, notably IL-6 and TNF-α. Results: Twenty-three studies were included. Elevated IL-6 was consistently associated with poor overall survival (pooled HR = 2.25, 95% CI 1.83–2.76), while high TNF-α levels showed a trend toward worse outcomes but without statistical significance. IL-1β, IL-8, and IL-10 were also linked to increased metastasis and reduced response to therapy. Immunosuppressive cytokines such as IL-10 and TGF-β facilitated tumor immune evasion, while IL-17 promoted inflammation and angiogenesis. Cytokines such as IL-12 and IFN-γ were associated with improved immune responses and a favorable prognosis. Conclusions: Cytokines are central mediators of breast cancer progression and immune regulation. Elevated levels of pro-inflammatory and immunosuppressive cytokines correlate with poor outcomes and may serve as prognostic biomarkers and therapeutic targets. Their integration into personalized treatment strategies holds significant clinical potential but requires further prospective validation and biomarker standardization. Full article

There is increasing interest in integrating various forms of Information and Communication technologies (ICT) into education. Well-established theoretical guidelines should guide the integration of these technologies. A flipped classroom is an example of an educational approach that integrates ICT and is guided by an active learning philosophy. The current study aims to evaluate participants’ acceptance of the flipped learning instructional model using six indicators—perceived usefulness, ease of use, hedonic motivation, attitude, self-efficacy, and educational quality—and to assess overall satisfaction. Additionally, it examines how these factors relate to overall satisfaction with this approach. The study utilized a descriptive cross-sectional research design with an exploratory and correlational orientation. The target population for this study included undergraduate students enrolled in the “Computer Applications in Education” course offered by the College of Education over three consecutive semesters: the second semester of the 2023/2024 academic year and the first and second semesters of 2024/2025. All students in this course experienced the flipped learning model as part of their instructional activities. Out of the 180 students, 137 completed the data collection tool, which was a questionnaire. The results showed that participants’ acceptance of the flipped learning approach was generally positive, ranging from moderate to high across all measured dimensions. The majority reported high levels of hedonic motivation, positive attitudes, perceived educational quality, and ease of use of the flipped learning requirements. Students found the flipped learning experience enjoyable, effective, and manageable. They believed it enhanced their learning and reported moderate self-efficacy and perceived usefulness. While satisfaction with flipped learning was moderate overall, it was strongly associated with enjoyment, positive attitudes, self-efficacy, and perceived educational quality, as evident in the results of the correlation analysis. Regression analysis revealed that these four factors were significantly associated with students’ satisfaction, whereas perceived usefulness and ease of use were not significantly associated when considered alongside other variables. These results suggest that emotional engagement, confidence, and perceived educational value are key contributors to students’ satisfaction with flipped learning. Full article

The Atlas cedar Cedrus atlantica is a relict and endemic conifer from Morocco and Algeria, although plantations may be found in several locations aside from its natural range. Recurrent droughts have been widely related to Atlas cedar dieback, growth decline, and mortality, but the genetic basis of potential adaptive capacity is unknown. We used the double digest restriction-site associated DNA sequencing technique (ddRAD-seq) to describe the genetic structure and variability of Atlas cedar along an aridity gradient in Morocco. Furthermore, we investigated the potential genetic origin of three Spanish plantations, also along an aridity gradient. The obtained single nucleotide polymorphisms (SNPs) were used to perform genotype–environment associations (GEAs) to define SNPs related to bioclimatic variables of temperature and precipitation. The vulnerability of this species to environmental variations was also estimated by its risk of non-adaptedness (RONA). Population structure showed a divergence between the Moroccan natural stands and some of the Spanish plantations, with each Moroccan nucleus being genetically distinct. The genetic variability was significantly lower in plantations than in natural populations. The drier Spanish plantations (easternmost) were genetically very similar to the driest Moroccan population (southernmost), suggesting that as its origin. A total of 41 loci under selection were obtained with the Moroccan dataset. In relation to temperature and precipitation variables, isothermality showed the highest number of associated loci (10) in GEA studies, and genotype–phenotype associations (GPAs) showed one locus associated with the Specific Leaf Area. RONA value was higher in the southernmost High Atlas population, where rising temperature was the main driver of expected genetic offset by allele frequency changes under the worst emissions scenario. In contrast, Spanish plantations would need smaller genetic changes to cope with the expected climate change. Likely gene flow from southern to northern areas suggests a latitudinal heading, where Spanish plantations might operate as an assisted migration. Moreover, one locus showed a northern/southern pattern in saplings but not in adults, suggesting a potential latitudinal pattern of selection. Our results are discussed on the basis of their management and conservation. Full article

Background and Objectives: Third-trimester screening is widely used to identify small for gestational age (SGA) and fetal growth restriction (FGR), but optimal models and timing remain under investigation. This study aimed to assess the performance of combined maternal factors and biomarkers, including ultrasound estimated fetal weight (EFW), Doppler indices, mean arterial pressure (MAP), and angiogenic biomarkers, for predicting SGA neonates after a routine 35–36 weeks’ scan in an unselected population. Materials and Methods: We conducted a retrospective cohort study in three Spanish centers offering universal third-trimester ultrasound. Logistic regression analyses were carried out to predict birthweight < 10th and <5th percentile using maternal characteristics and medical history, EFW, MAP, Doppler indices, and the angiogenic biomarkers placental growth factor (PlGF) and soluble fms-like tyrosine kinase-1 (sFlt-1). Using a 10-fold cross-validation, we estimated the area under the receiver operating characteristic curve (AUC), detection rates (DRs), false-positive rates (FPRs), and their corresponding screen-positive rates (SPRs). External validation was performed using an independent cohort. Results: Among 3992 pregnancies, the DR of ultrasound alone for birthweight <10th percentile was 47.9% (95% CI: 44.0 to 51.9), with an FPR of 7.3%. Adding maternal factors increased DR to 57.0% (95% CI: 53.0 to 60.9) at 10% FPR and to 83.0% (95% CI: 79.9 to 85.9) at 30% FPR. Similarly, the DR of ultrasound alone for birthweight < 5th percentile was 48.4% (95% CI: 43.1 to 53.6), with an FPR of 4.5%. Adding maternal factors increased DR to 65.7 (95% CI: 60.5 to 70.5) at 10% FPR and to 88.2 (95% CI: 84.4 to 91.3) at 30% FPR. The inclusion of MAP, Doppler, and biomarkers provided marginal additional gains, particularly for <5th percentile prediction. To achieve a DR > 80%, an SPR of approximately 40% was required. Performance improved when focusing on neonates born before 38 weeks, with a DR of 77.5 (95% CI: 68.6 to 84.9) at 10% FPR for SGA < 10th percentile. However, less than 40% of screen-positive women remained undelivered by 40 weeks, limiting the number requiring further surveillance. Conclusions: A third-trimester screening at 35–36 weeks using maternal characteristics and EFW identifies most SGA neonates, particularly those delivering before 38 weeks. Even including other biomarkers, an SPR of about 40% should be necessary to achieve a high DR. However, less than 40% of the women would remain undelivered before a subsequent follow-up is required. Full article

Background/Objectives: Lung cancer remains the leading cause of cancer-related deaths globally, with non-small-cell lung cancer (NSCLC) accounting for most cases. Although advances in targeted therapies and immunotherapy have improved outcomes, long-term survival remains limited. This review aims to explore current immunotherapeutic strategies, the evolving role of therapeutic cancer vaccines, and the emerging potential of human papillomavirus-targeted interventions in lung cancer, particularly among non-smoker populations. Methods: A comprehensive search of the literature was conducted using PubMed, Scopus, and Web of Science databases to identify relevant articles published between 2015 and 2024. Studies focusing on immune checkpoint inhibitors, vaccine platforms, HPV-associated lung cancer, tumor microenvironment modulation, and novel delivery systems such as bacterial ghosts were included. Relevant clinical trials and preclinical studies were critically evaluated and synthesized. Results: Immune checkpoint inhibitors targeting PD-1, PD-L1, and CTLA-4 have demonstrated clinical efficacy in NSCLC, yet their effectiveness is often limited by resistance mechanisms and lack of robust predictive biomarkers. Cancer vaccines, including peptide-based, mRNA, DNA, dendritic cell, and bacterial ghost platforms are emerging as complementary strategies to enhance antitumor immunity. Moreover, accumulating evidence suggests a potential association between high-risk HPV infection and lung cancer development, supporting the rationale for HPV-targeted vaccine strategies. Conclusions: Immunotherapy and therapeutic vaccination hold significant promise in reshaping lung cancer treatment. Advancements in vaccine design, delivery platforms like bacterial ghosts, and better understanding of HPV’s role in lung oncogenesis could support more effective, personalized immunotherapeutic approaches in the future. Full article

Carbon satellites, as the most direct means of observing carbon dioxide globally, offer credible and scientifically robust methods for estimating carbon emissions. To enhance the accuracy and timeliness of urban-scale carbon emission estimates, this study proposes an innovative model that integrates top-down carbon satellite data with high-resolution spatial proxies, including points of interest, road networks, and population distribution. The K-means clustering method was employed to study the relationship between carbon emissions and XCO₂ anomalies. Based on this, the local adaptive carbon emission estimation model was constructed. Further, by integrating the spatial distribution and weights of proxy data, carbon emissions were reallocated to generate a high-resolution urban carbon emission map at a 1 km × 1 km resolution. Taking Urumqi, the XCO₂ background concentration ranged from approximately 408 ppm to 415 ppm in 2020, and the corresponding ${∆XCO}_2$ ranged from −1.58 ppm to 1.13 ppm. The total carbon emission estimated by the local adaptive model amounted to approximately 58.26718 million tons in 2020, close to the EDGAR dataset, with most monthly relative error within ±10%. The Pearson correlation coefficient between the ODIAC dataset and spatially redistributed carbon emission was 0.192, and their comparison showed that high carbon emission areas in the spatially redistributed carbon emission aligned closely with urban industrial parks and commercial centers, offering a more detailed representation of urban carbon emission spatial characteristics. This method contributed to exploring the potential of carbon satellites for quantitatively measuring anthropogenic emissions and offers improved insights into monitoring urban-scale carbon dioxide emissions. Full article

As apex predators, felids (Felidae) face unresolved phylogenetic controversies due to their recent rapid speciation and remarkable morphological conservatism. Previous studies, often relying on a limited number of genetic markers, were constrained by insufficient data and conflicting phylogenetic signals, leaving these disputes unresolved. Therefore, establishing a robust phylogenetic framework based on larger-scale genomic data is crucial. This study integrated complete mitogenomes from 37 species representing all major felid genera to characterize genomic diversity, selection pressures, and phylogenetic relationships. Results revealed conserved gene content and arrangement patterns but significant intergenic variation in nucleotide composition, with the light-strand encoded ND6 exhibiting pronounced strand-specific bias. Nucleotide diversity was highest in ND4L (Pi = 0.132) and ATP6 (Pi = 0.131), suggesting their utility as novel markers for species delimitation and population studies. Selection pressure analysis indicated strong purifying selection on cytochrome oxidase subunits (e.g., COX1 Ka/Ks = 0.00327) but relaxed constraints on ATP8 (Ka/Ks = 0.12304). Phylogenies reconstructed from the complete 13PCGs + 2rRNAs dataset (showing high congruence between maximum likelihood and Bayesian methods) clearly delineated Felidae into two primary clades (Pantherinae and Felinae), confirming monophyly of all genera and positioning Neofelis nebulosa as the basal lineage within Pantherinae. Crucially, exclusion of ND6 (12PCGs + 2rRNAs) yielded topologies congruent with the complete 13PCGs + 2rRNAs dataset, whereas single-gene or limited multi-gene datasets produced inconsistent trees (particularly at genus-level nodes). This demonstrates that near-complete mitogenomic data (≥12PCGs + 2rRNAs) are essential for reconstructing robust felid phylogenetic frameworks. Our study provides insights into carnivoran mitogenome evolution. Full article

Zelkova schneideriana (Ulmaceae), an endemic relict species of the Tertiary in China, has experienced a sharp decline in population due to habitat fragmentation, poor natural regeneration, and anthropogenic disturbances. It is currently listed as a category II national key protected wild plant and categorized as Vulnerable by the International Union for Conservation of Nature (IUCN). To explore its response mechanisms to climate change, this study integrates 11 species distribution models (SDMs) to comprehensively predict its suitable habitat distribution patterns. Key environmental variables were identified as Bio06 (minimum temperature of the coldest month, 21.57%), Bio02 (mean diurnal range, 19.81%), Bio17 (precipitation of the driest quarter, 13.52%), Bio15 (precipitation seasonality, 8.32%), Bio07 (temperature annual range, 8.15%), Bio12 (annual precipitation, 6.58%), and elevation (6.57%), collectively contributing approximately 85%. Spatiotemporal analysis revealed that during historical glacial periods, suitable habitats were significantly restricted, and highly suitable zones were absent under extreme climatic conditions, suggesting the presence of potential glacial refugia. Under current climatic conditions, highly suitable habitats have expanded notably. However, under the high-emission scenario (SSP585) in the future, the suitable range is projected to shrink considerably, with a drastic reduction in highly suitable areas. Moreover, the suitability centroid is expected to shift markedly toward higher elevations in the northeast, indicating a potential adaptation strategy of Z. schneideriana toward mountainous regions in Hunan, Hubei, and Chongqing. These findings provide quantitative guidance for the formulation of targeted conservation strategies for Z. schneideriana and offer methodological insights for predicting suitable habitats and managing related relict plant species under the threat of climate change. Full article

Satellite–terrestrial integrated communication systems (STICSs) are envisioned to provide ubiquitous, seamless connectivity in next-generation (6G) wireless communication networks for massive-scale Internet of Things (IoT) deployments. This global coverage extends beyond densely populated areas to remote regions (e.g., polar zones, open oceans, deserts) and disaster-prone areas, supporting diverse IoT applications, including remote sensing, smart cities, intelligent agriculture/forestry, environmental monitoring, and emergency reporting. Random access signals, which constitute the initial transmission from access IoT devices to base station for unscheduled transmissions or network entry in terrestrial networks (TNs), encounter significant challenges in STICSs due to inherent satellite characteristics: wide coverage, large-scale access, substantial round-trip delay, and high carrier frequency offset (CFO). Consequently, conventional TN preamble designs based on Zadoff–Chu (ZC) sequences, as used in 4G LTE and 5G NR systems, are unsuitable for direct deployment in 6G STICSs. This paper first analyzes the challenges in adapting terrestrial designs to STICSs. It then proposes a CFO-resistant preamble design specifically tailored for STICSs and details its detection procedure. Furthermore, a dedicated root set selection algorithm for the proposed preambles is presented, generating an expanded pool of random access signals to meet the demands of increasing IoT device access. The developed analytical framework provides a foundation for performance analysis of random access signals in 6G STICSs. Full article

Background/Objectives: Dülmen wild horses are kept in a fenced wooden and marsh area around Dülmen in Westphalia, Germany, since 1856. Previous analyses supported early genetic divergence from other domesticated horse populations and the Przewalski horse. Therefore, the objective of this study was to evaluate genetic diversity using high-density genomic data. Methods: We collected 337 one-year-old male Dülmen wild horses, captured at 12 annual auctions, for genotyping on the Illumina GGP Equine Plus Beadchip. All analyses were performed for 63,123 autosomal SNPs. Results: On average, each horse had 27.96 ROH with an average length of 8.237 Mb, resulting in an average genomic inbreeding coefficient F_ROH of 0.107. ROH with a length of 2–4 Mb were most frequent, and the next frequent ROH fall into the length categories of 4–8 and 8–16 Mb. The effective population size (N_e) steadily decreased in the last 100 generations by 4.57 individuals per generation from 498 to 41. We identified 10 ROH islands on equine chromosomes 1, 4, 5, 7, 9, and 10. Only one ROH island on ECA 1 was shared by 45% of the horses. Overrepresented genes of ROH islands were associated with glycerophospholipid catabolism through phospholipase A2 genes, skeletal muscle contraction (TNNI3, TNNT1), synapse activity and structure (CTTNBP2), regulation of inflammatory response (NLRP genes), and zinc finger protein genes, which are involved in many cellular processes and may also act as tumor suppressors and oncogenes. Conclusions: This study highlights the development of genomic inbreeding and shows the importance of the stallions selected for breeding on the genetic diversity of the Dülmen wild horses. The results of this study should be used to develop strategies to slow down increase in inbreeding and prevent transmitting unfavorable alleles from the stallions to the next generation. Full article

The Pottiaceae family represents one of the most diverse and ecologically adaptable bryophytes; however, its chloroplast genome diversity remains largely unexplored. This study aimed to investigate plastome variation and identify evolutionary informative loci within the moss genus Tortula. We performed a comprehensive comparative plastome analysis of nine species within the genus Tortula, using Syntrichia princeps as an outgroup within the family Pottiaceae. High-quality chloroplast genomes were assembled and annotated based on next-generation sequencing (NGS) data. All plastomes exhibited conserved quadripartite structures with genome size ranging from 121,889 to 122,697 bp. Adenine–thymine (AT)-rich dinucleotide repeats were the most abundant simple sequence repeats (SSRs), and several genes contained unique higher-order SSRs, suggesting potential utility as population-level markers. Codon usage analysis revealed species-specific biases, particularly in leucine, serine, and threonine codons, with Tortula acaulon exhibiting the most pronounced deviation. Phyloplastomic analysis based on maximum likelihood identified two major clades, indicating that Tortula section Tortula is not monophyletic. Several highly informative loci were found to replicate the full plastome phylogenetic signal. Additionally, a subset of genes, including atpE and matK, exhibited nonsynonymous-to-synonymous substitution (dN/dS) ratios that suggest possible positive selection. These findings provide new insights into chloroplast genome evolution within Tortula, while identifying candidate loci for future phylogenetic and evolutionary studies. This study contributes to a more robust understanding of plastome-based studies in Pottiaceae and highlights efficient molecular markers for broader bryophyte phylogenomics. Full article

Background: Lipoprotein(a) (Lp(a)) is a genetically determined lipoprotein that plays an independent role in the development of atherosclerotic cardiovascular disease (ASCVD). Ethnic differences in Lp(a) levels are well-documented, yet regional data from Central Asia, particularly Kazakhstan, remain scarce. Methods: We conducted a retrospective, single-center study involving 3727 patients aged ≥ 18 years who underwent Lp(a) testing between January 2023 and June 2024. Participants were stratified by self-reported ethnicity and atherosclerosis status confirmed via coronary angiography. Lp(a) levels were analyzed using immunoturbidimetric assays. Results: Elevated Lp(a) levels (≥50 mg/dL) were identified in 19.6% of the total population. While Kazakhs exhibited a slightly higher prevalence of elevated Lp(a) compared to Russians, there were no statistically significant differences in Lp(a) levels across ethnic groups. ROC analysis revealed limited discriminatory power of Lp(a) for diagnosing atherosclerosis (AUC = 0.5464), although PRC analysis showed high sensitivity and precision in both Kazakh and Russian subgroups at lower thresholds. Conclusions: Despite modest ethnic variation in Lp(a) distribution, its predictive value for atherosclerosis remains limited as a standalone marker. These findings highlight the need for population-specific thresholds and support incorporating Lp(a) testing in broader cardiovascular risk assessment strategies in Central Asia. Full article

Screening for diabetes-specific distress should be considered a standard component of diabetes management. This study aimed to evaluate the psychometric properties of the Serbian adaptation of the Problem Areas in Diabetes—Teen Version (PAID-T). Methods: A multicentre, validation, cross-sectional study was conducted with 374 adolescents (aged 13–18 years) diagnosed with type 1 diabetes (T1D), all of whom completed the Serbian version of the PAID-T. The psychometric evaluation included assessments of construct validity through exploratory (EFA, first subsample, n = 140) and confirmatory (CFA, second subsample, n = 234) factor analyses, as well as examinations of concurrent and convergent validity. Reliability was evaluated using measures of internal consistency and test–retest stability (n = 289). Results: Factor analyses indicated some multidimensionality; however, the high correlations between factors in the three-factor model and the optimal fit of the hierarchical three-factor model with a single second-order factor supported the interpretation that the PAID-T measures a unified construct, with satisfactory fit indices (CFI = 0.95; TLI = 0.93; RMSEA = 0.08; SRMR = 0.05). Concurrent validity testing demonstrated gender-based differences in adolescents’ perceptions of the emotional burden of diabetes (W = 19.718, p = 0.03, small effect size = 0.11). Convergent validity analyses showed that adolescents who were non-adherent to treatment (W = 11.390, p = 0.01, small effect size = 0.13) or experienced difficulties managing diabetes at school (W = 16.333, p < 0.001, small effect size = 0.16) reported significantly higher levels of diabetes-specific distress. A significant negative correlation was also observed between PAID-T scores and perceived social support (ρ = −0.24, p < 0.001). Importantly, Serbian adolescents with T1D reported mean PAID-T scores close to the cutoff point of 44, indicating clinically relevant levels of distress. The Serbian version demonstrated strong internal consistency (Cronbach’s α = 0.92; McDonald’s ω = 0.93) and excellent test–retest reliability (ICC = 0.99, 95% CI), confirming stability over time. Conclusions: The Serbian adaptation of the PAID-T demonstrated strong validity and reliability, supporting its use as a robust tool for assessing self-reported diabetes-specific distress in adolescents. Notably, the mean PAID-T scores in Serbian adolescents with T1D were close to the established cutoff point of 44, underscoring the clinical relevance of routine screening in this population. The early identification of diabetes distress can enable nurses and other members of the multidisciplinary healthcare team to deliver tailored interventions, ultimately improving psychological well-being and health outcomes. Full article