Search Results (3,469)

Cervical carcinoma is predominantly driven by high-risk human papillomavirus (HPV) infection, in which functional inactivation of p53 occurs mainly through viral oncoproteins rather than mutations in the TP53 gene. This raises questions concerning the prognostic relevance of TP53 gene status and p53 protein levels in this tumor type. This study aimed to systematically evaluate the prognostic significance of TP53 mutation status, p53 protein abundance, and selected downstream p53-regulated proteins in cervical carcinoma, with particular focus on tumors carrying wild-type TP53. Clinical and proteomic data from 162 cervical carcinoma patients were retrieved from The Cancer Genome Atlas (TCGA). Protein levels (p53, BAX, p21/CDKN1A, and TIGAR) were assessed using reverse-phase protein array (RPPA) data. Survival analyses were performed using Kaplan–Meier estimates with log-rank testing after stratification into quartile-based expression groups. The vast majority of tumors (~93%) harbored wild-type TP53, and the TP53 mutation status showed no association with patient survival. In tumors with wild-type TP53, p53 protein levels did not significantly correlate with overall survival, indicating a limited prognostic value. In contrast, elevated levels of the pro-apoptotic protein BAX showed a clear tendency to be associated with poorer overall and progression-free survival, suggesting BAX as a potential prognostic marker in this specific molecular context. The expression of p21/CDKN1A showed no prognostic relevance, while high TIGAR levels displayed a slight trend toward poorer survival, although without reaching statistical significance. In summary, in HPV-driven cervical carcinoma, neither the TP53 mutation status nor the p53 protein abundance reliably predict patient outcome. Instead, selected downstream effectors of p53 signaling—particularly BAX—may provide more informative prognostic insights in tumors retaining wild-type TP53. These findings highlight the importance of assessing functional outputs of p53 signaling rather than the p53 status alone in this disease context. Full article

Background/Objectives: This study assesses the outcomes of integrating deep learning-augmented zero echo time (ZTE DL) MRI sequences into standard MRI protocols for assessment of the hands and feet. Methods: In this single-center, retrospective study, a standard MRI protocol of hands and feet at 1.5 T was compared with the same protocol with an added ZTE DL sequence. Pathological changes in the bone, including subcortical sclerosis, osteophytes, joint space narrowing and fractures, were rated as present or absent. Indeterminate intraosseous lesions (erosions/ganglia) and indeterminate extraosseous lesions (ossicles/soft tissue calcifications) were additionally assessed on a semi-quantitative 4-point Likert scale. Diagnostic confidence was rated as low, moderate, or high. Standard MRI vs. ZTE-DL-augmented MRI comparisons were evaluated using a mixed-effects model with reader as a random effect, and X-ray vs. ZTE-DL-augmented MRI comparisons using a paired Wilcoxon signed-rank test. Interreader agreement (two readers) was assessed using Kappa statistics. Results: The cohort encompassed 59 datasets (feet = 22, hands = 37) of 40 patients with an average age of 51.79 (SD ± 11.84) years (58% women (n = 34), 42% men (n = 25)). Additional ZTE DL sequences resulted in similar findings, but with higher diagnostic confidence for assessment of bone changes when compared to conventional MR sequences (p-values < 0.05) and, overall, when compared to radiographs in a subgroup (p < 0.05 for five of six pathologic bone changes). Interreader agreement of diagnostic confidence was moderate to substantial (kappa 0.59–0.71). Conclusions: Addition of ZTE DL sequences to standard MRI protocols of hands and feet at 1.5 T demonstrated similar findings in the assessment of pathological bone changes, but with higher diagnostic confidence compared to conventional MR sequences and radiographs. However, further validation against a reference standard is required to determine diagnostic accuracy. Full article

Background: Postpartum depression (PPD) is a common mental health condition, and women with elevated prenatal anxiety are at increased risk. Evidence from Kazakhstan remains limited. This study aimed to describe postpartum depressive symptoms and associated factors among women with elevated prenatal anxiety who received routine perinatal care and participated in the PRISM prenatal psychoeducational program. Methods: This prospective single-arm cohort study with postpartum follow-up was conducted in Astana, Kazakhstan. Of 1232 pregnant women screened, 234 women with elevated prenatal anxiety participated in the PRISM program, and 226 completed the postpartum assessment. Because no control group was included, the study was not designed to evaluate the effectiveness of PRISM or establish causal effects. Postpartum depressive symptoms were assessed using the Postpartum Depression Screening Scale–Short Form (PDSS-SF). Descriptive statistics were calculated, and associations with age, parity, and postpartum assessment period were examined using Spearman’s rank correlation and non-parametric tests. Results: The mean PDSS-SF score was 20.65 ± 6.00. Using a cut-off score of ≥17, 158 of 226 participants screened positive for clinically significant depressive symptoms, corresponding to 69.9% (95% confidence interval (CI): 63.6–75.5%). Scores were highest among women assessed between 6 weeks and 6 months postpartum (p < 0.001). Age showed a weak negative correlation with depressive symptoms, whereas parity was not significantly associated. The most frequently reported symptoms were sleep disturbance, loneliness, and depressed mood. Conclusions: A substantial burden of postpartum depressive symptoms was observed in this high-risk cohort. The findings support early identification of prenatal anxiety, continued postpartum screening, and access to appropriate psychological and psychiatric care. Controlled studies are needed to evaluate PRISM and similar preventive programs. Full article

Wearable and intelligent bioelectronic systems are emerging as a key enabling technology for continuous, non-invasive health monitoring, coupling physiological sensing with data-driven inference. Within this paradigm, electroencephalography (EEG) provides a wearable-compatible biosensing modality for capturing the pre-sleep neurophysiological dynamics linked to emotional regulation and sleep onset. Insomnia affects approximately 10–15% of adults worldwide and is often associated with dysregulated emotions and pre-sleep hyperarousal. Existing EEG-based affective and sleep-onset processing pipelines often rely either on deep-learning architectures with limited interpretability or on hand-crafted spectral descriptors with weak theoretical motivation. This study presents an exploratory proof-of-principle bioelectronic processing framework in which EEG sensing features are organized according to ANT-7 (artificial neurotransmitter seven-dimensional model), a neurotransmitter-inspired computational taxonomy introduced as a heuristic feature-design prior rather than as a validated neurochemical theory. The proposed feature set includes the alpha/theta power ratio, sample entropy, Higuchi fractal dimension, and phase-locking value extracted from the public DREAMER and DEAP datasets (23 and 32 subjects, respectively). SVM, Random Forest, and 1D-CNN classifiers are trained under subject-independent leave-one-subject-out cross-validation with strict within-fold normalization to prevent data leakage, and interpretability is assessed through SHAP values and permutation importance (PI). To stress-test whether this feature organization transfers beyond the affective benchmarks on which it is trained, classifier outputs are then related to sleep-onset latency in Sleep-EDF Expanded through a deliberately cautious cross-dataset transfer analysis. Within this protocol, the best model reaches 88.4% accuracy in three-class affective-state recognition (stress/neutral/relaxed; AUC-ROC = 0.93). As an exploratory secondary analysis, classifier-derived relaxation estimates show a statistically significant negative association with polysomnographic sleep-onset latency and improve over a single alpha/theta-ratio baseline; this cross-dataset result is reported as a proof of concept, not as a validated sleep-onset predictor. Interpretability analyses (SHAP and permutation importance) indicate that the learned feature rankings are internally consistent with the neurotransmitter-inspired feature design, a property we interpret as internal coherence rather than as independent confirmation of the taxonomy. Together, these elements outline a complete sensor-to-AI processing chain—from EEG biosensing, through neurotransmitter-inspired signal-feature extraction, to interpretable and computationally lightweight inference—designed for compatibility with low-density wearable EEG devices and edge deployment. However, EEG does not measure neurotransmitter concentrations, the study does not benchmark ANT-7 directly against competing taxonomies such as valence-arousal/circumplex or RDoC-inspired feature organizations, and the Sleep-EDF analysis should not be interpreted as evidence that the model measures a validated latent construct of sleep readiness. Accordingly, the manuscript should be read as a framework-validation study of one interpretable feature taxonomy, not as a theory-validation study of ANT-7 or as a clinical validation study. Full article

Accurate land cover mapping is a fundamental tool for environmental management and ecosystem monitoring. This study presents a comparative evaluation of four deep learning architectures, namely a Convolutional Neural Network (CNN), UNet++, ConvNeXt and Vision Transformer (ViT), for land cover classification into five primary classes: water, cropland, forest, low/natural vegetation and built-up. The broader Lake Kerkini basin was selected as the primary training and evaluation area. The multispectral input data were generated through Google Earth Engine and consisted of multi-seasonal Sentinel-2 composite mosaics for the 2021 mapping year, covering winter, spring, summer and autumn. To obtain a more reliable performance estimate and mitigate the effects of spatial autocorrelation, a four-fold spatial cross-validation approach was implemented. Under this spatial validation framework, the convolution-based architectures achieved the strongest performance. CNN obtained the highest numerical fold-mean performance, with an overall accuracy of 81.53% and a macro-averaged F1 score (Macro-F1) of 80.09%, followed closely by UNet++ and ConvNeXt. Non-parametric repeated-measures statistical testing indicated a significant overall architecture effect, with CNN, UNet++ and ConvNeXt showing broadly comparable fold-level Macro-F1 performance, while the tested ViT configuration trained from scratch ranked last across all spatial folds. Regional transferability was further evaluated in the nearby independent Lake Doirani region, where the convolutional architectures, particularly CNN and UNet++, showed strong agreement with the WorldCover-derived reference labels without fine-tuning. Finally, feature-importance analysis indicated that specific spectral-seasonal channels, especially the Blue band (B2) in winter and the Short-Wave Infrared band (B12) in summer, were consistently influential in the models’ predictions. Overall, under the tested 2021 Mediterranean case-study conditions, the results highlight the importance of spatially rigorous validation and show that the evaluated convolution-based configurations achieved stronger performance than the tested ViT configuration trained from scratch. Full article

Asymmetric dental expansion is a preliminary goal in the treatment of a true unilateral crossbite (CB). The aim of this study was to investigate transverse dental changes following modified asymmetric rapid palatal expansion (ARPE) based on cone-beam computed tomography (CBCT) records. The dataset consisted of CBCT records obtained before and after treatment with a modified ARPE appliance in patients presenting with unilateral skeletal posterior CB and class I skeletal relationship. Eighteen linear and four angular measurements were analyzed based on CBCT images. The Shapiro–Wilk test, paired-samples t-test and Wilcoxon signed-rank test were used for statistical analyses. Maxillary interdental widths showed significant increments on both sides (p < 0.05). Maxillary posterior dental expansion was greater on the CB side compared to the non-crossbite (NCB) side. A significant increase was detected in the mandibular inter-first premolar width (p < 0.05). In addition, the inter-side difference in maxillary first molar inclination between the NCB and CB sides was also significant (p < 0.05). Modified ARPE may be beneficial for treatment of a unilateral CB. Full article

Historical document collections are increasingly available as digitised images and PDFs, but their conversion into reliable text remains affected by optical character recognition (OCR) errors, degraded pages, heterogeneous layouts, and domain-specific terminology. This study proposes a pathway-level framework for documenting and comparing conventional OCR, OCR followed by large language model (LLM)-assisted correction, and direct multimodal transcription. The framework is demonstrated using the Portuguese Agricultural and Forestry Surveys (1950–1958). A stratified validation sample of 45 pages was selected by visual quality, page type, and geographic coverage. Outputs were evaluated against manually verified reference transcriptions using content-normalised character error rate (CER) and word error rate (WER), document-condition analysis, paired statistical tests, and an entity-level semantic preservation assessment focused on place names, agricultural terms, and measurement expressions. Under the evaluated model and interface conditions, both LLM-based pathways produced lower mean CER and WER than the conventional OCR baseline, with the lowest values observed for direct multimodal transcription. Semantic preservation was also higher for the LLM-based pathways, although measurement expressions remained the most persistent risk, particularly in table-based pages. Downstream tasks were not directly evaluated. The findings support the framework as a method for validating text-extraction pathways before reuse, rather than establishing a universal ranking of tools. Full article

Fused deposition modeling (FDM) of polylactic acid (PLA) is widely used, yet most parameter studies tune one mechanical property at a time and leave the conflicts between properties unresolved. This work treats three responses of FDM PLA together: ultimate tensile strength, flexural strength, and Shore D hardness. A Taguchi L9 orthogonal array varied infill density, raster angle, and layer thickness; signal-to-noise ratios and analysis of variance ranked the factors, linear regression linked the parameters to each response, and the NSGA-II algorithm mapped the trade-off surface between them. Layer thickness proved the leading factor for tensile and flexural strength, while hardness answered mainly to infill density; raster angle stayed weak for every response. The Pareto front showed that low infill favors tensile strength while high infill favors flexural strength and hardness, all at the finest layer setting, and these trends were converted into parameter guidelines for tensile-led, flexure-led, and balanced parts. The statistical limits of the screening design are stated openly, the flexural and hardness campaigns are flagged as provisional, and a replicated, standard-compliant confirmation study is set out as the next step. Full article

Waterlogging stress severely restricts the growth and stable yield of Carthamus tinctorius L., an important medicinal and oilseed crop. At present, systematic phenotypic evaluation of safflower seedling waterlogging tolerance across diverse germplasm resources remains insufficient. In this study, 15 seedling agronomic indicators of 51 safflower accessions under waterlogging treatment and normal control conditions were measured. Descriptive statistics, correlation analysis, principal component analysis, fuzzy membership function transformation and hierarchical cluster analysis were combined to conduct phenotypic evaluation of waterlogging response. Obvious phenotypic differentiation was detected among tested germplasms; the coefficient of variation in most traits under waterlogging ranged from 18.84% to 63.48%, far higher than the 2.44–4.83% observed under normal growth conditions. Four principal components with eigenvalues greater than 1 were retained, collectively explaining 79.64% of total phenotypic variation. Comprehensive waterlogging tolerance D-values were calculated by weighting principal component contribution rates, and the 51 germplasms were statistically divided into five tolerance grades based on D-value intervals, with six materials exhibiting superior seedling waterlogging performance screened out. Correlation analysis showed shoot fresh weight (SFW), stem diameter (SD), root diameter (RD) and leaf area (LA) had strong positive correlations with D-value. Nine agronomic traits with close correlation to overall waterlogging performance were identified as candidate indicators for preliminary phenotypic screening. It should be noted that the D-value only provides statistical ranking based on measured seedling phenotypes and cannot directly interpret the physiological regulatory mechanisms of waterlogging tolerance. This study adopted a well-established multi-index statistical pipeline to characterize phenotypic responses of safflower seedlings under 7-day waterlogging stress at the six-leaf stage. Notably, all phenotypic data were derived from a single greenhouse trial under controlled waterlogging conditions; multi-environment field validation is required to confirm the broader applicability of the identified indicators and germplasms. Full article

Rooftop bifacial photovoltaic (PV) performance depends on both the optical properties of the roof surface and the installation geometry. This simulation-based study assessed a planned rooftop PV installation on a school building in Brno, Czech Republic, using PV*SOL simulations and statistical post-processing in R. The principal dataset comprised 238 bifacial scenarios combining seven spatially distinct roof zones assigned nominal albedo values from 8% to 80%, 17 module tilts from 0° to 80°, and row spacings of 1.00 and 2.10 m. Because each nominal albedo was associated with a different physical roof zone, the results represent combined roof-zone, reflectance and geometry responses rather than the isolated causal effect of albedo. The highest annual specific yield was obtained in the roof-zone scenario assigned 70% nominal albedo. The maximum was 1296.60 kWh/kWp at 1.00 m spacing and 35° tilt and 1359.34 kWh/kWp at 2.10 m spacing and 50° tilt. Under the fixed 25° reference configuration, the bifacial system outperformed the matched monofacial reference in all seven scenarios, with bifacial gain ranging from 7.57% to 11.23%. An empirical response-surface model reproduced the complete simulation grid with adjusted $R^2=0.980$ and RMSE of 13.94 kWh/kWp. For the representative 6.0 kWp subarray, the maximum lifetime incremental avoided-emission difference relative to the matched 8% reference was 10.35 t CO₂. Within the predefined Monte Carlo ranges, the highest-ranked scenarios produced positive incremental net present value in all 5000 sampled combinations. The findings show that roof reflectance should be evaluated together with tilt, spacing and spatial roof context. They do not establish a universally optimal albedo or rooftop configuration. Full article

Seismic design of long-period reinforced concrete tall buildings is drift-dominated, and yet closed-form tuned mass damper (TMD) calibration lacks a rank-oriented robustness framework and a deterministic treatment of inelastic period drift. First, a two-layer closed-form calibration procedure is verified on 30-, 48- and 60-storey RC towers with periods of 3.80 to 8.45 s on a rock-like Istanbul site under eleven spectrum-matched records. The first layer, a Robust Tuning Index built on four design requirements, weighs nominal suppression against detuning robustness through a closed-form dominance condition and a unique crossover at the ±13% band. The second layer, a period-elongation-aware anchor, sets the calibration period to the mean of the elastic and DD-2 secant first-mode periods, capping the worst-case offset at ±9.0% to ±12.1% against +19.7% to +27.6% under elastic anchoring. Response-history analyses give mean peak roof-drift reductions of 2.8% to 4.6% with statistically inseparable formulation means at exact tuning, while the Sadek calibration cuts dispersion by more than a third and stroke by roughly a third, carries 2.3 to 2.5 times less frequency-response loss at the anchor offsets, and ranks first in 122 of 144 envelope scenarios. The framework replaces numerical retuning with a transparent closed-form route within the linear verification tier. Full article

Material Extrusion (MEX) additive manufacturing (AM) of ABS polymer components often requires post-process machining to achieve the necessary dimensional precision and surface quality. However, the influence of printing parameters and tool–material interaction in hybrid manufacturing remains insufficiently explored. This study investigates the impact of initial hole size (D_start), build orientation, and cutting parameters (cutting speed and feed rate) on the dimensional accuracy and surface roughness of machined holes in ABS-M30 specimens. Samples were fabricated in vertical and horizontal orientations and subjected to drilling in solid material and enlargement of printed pilot holes using a twist drill on a 5-axis machining center. Dimensional deviation and surface roughness (Ra, Rz) were evaluated using coordinate metrology and profilometry. The results showed that the smallest machining allowance (0.062 mm per side) was insufficient to completely remove the printing-induced surface texture, resulting in significantly higher and more variable Ra and Rz values. This distinct low-machining-allowance regime was confirmed by statistical analysis and representative optical observations. Conversely, a machining allowance of 0.565 mm per side (corresponding to D_start = 9 mm) resulted in substantially lower surface roughness (Ra ≈ 1.6 µm). Vertical build orientation generally provided better surface quality than the horizontal orientation, which was consistent with fewer visible surface features in the selected optical fields of view. All machining conditions resulted in negative dimensional deviations, indicating elastic recovery of the ABS material after machining. An exploratory multi-response ranking showed that the lowest composite quality scores for overall final hole quality were associated with D_start = 10 mm (machining allowance of 0.062 mm per side). When the analysis was limited to the machining-dominated regime, the lowest score was obtained for the vertical build orientation, D_start = 9 mm, a cutting speed of 40 m/min, and a feed rate of 0.2 mm/rev. These findings provide preliminary guidelines for selecting hybrid manufacturing conditions for MEX-manufactured ABS-M30 components. Full article

The prognostic relevance of IDH1 mutations remains unclear in acute myeloid leukemia (AML). This study, representing the first Turkish AML cohort characterized for IDH1 mutations, aimed to determine the frequency of IDH1, FLT3 and NPM1 mutations and to describe the associated clinical characteristics. We retrospectively analyzed clinical, cytogenetic, and molecular data for 57 AML patients. Bone marrow aspirates were evaluated cytogenetically using G-banding, and molecular mutations were assessed by PCR or NGS (MiSeq-Illumina). IDH1 mutations were detected in 7% of patients; FLT3 and NPM1 mutations were detected in 38.6% and 19.3% of patients, respectively. A significant positive correlation existed between IDH1 and NPM1 mutations (r = 0.388, p = 0.003). Overall mortality was 56.1% and remission was achieved in 43.9%. Older age (p = 0.029) and comorbidities (p = 0.009) were significantly linked to mortality. Mortality was 100% in the four IDH1-mutant patients and significantly higher in NPM1-mutant patients. Overall survival was shorter in IDH1-mutants, although the difference did not reach statistical significance (log-rank p = 0.057). Relapse occurred in 26.3%, rising to 50% in the IDH1-mutated subgroup. In this limited cohort, IDH1-mutant cases were associated with shorter overall survival and higher mortality; however, the small number of IDH1-mutant patients (n = 4) precludes definitive prognostic conclusions. Outcomes in NPM1-mutated patients were also less favorable than typically expected, possibly related to co-occurring IDH1 mutations. These descriptive findings characterize the molecular landscape of AML in an underrepresented Turkish population and may provide a foundation for larger, multicenter studies rather than confirming a prognostic role for these mutations. Full article

This study examines correlates of preferred future work arrangements among adult residents of the Roanoke Metropolitan Statistical Area, Virginia, a mid-sized U.S. metropolitan region. It focuses on whether remote-work preference varies by sociodemographic characteristics, pandemic-era work-from-home experience, occupational perceptions, and attitudes toward physical interaction. Data were collected through a cross-sectional online survey administered in 2023, during the post-acute pandemic period. After excluding incomplete responses, duplicates, respondents younger than 18 years, cases without verifiable adult eligibility, and cases without verified residence in the study area, the final analytical sample included 636 respondents. Analyses included chi-square tests, Spearman rank correlations, a Stuart–Maxwell test of marginal homogeneity, and an adjusted multinomial logistic regression model. Among respondents with valid preference data in this nonprobability analytical sample, 63.8% preferred fully remote work. Among paired current–preferred cases, preferred arrangements differed significantly from current arrangements, with 87.0% of respondents reporting a directional change preferring movement toward a more remote arrangement. Preferred future work arrangement was significantly associated with age, education, earnings, marital status, housing tenure, perceived work-from-home efficiency, occupational remote-work perceptions, and physical-interaction importance; gender was not significant. Findings indicate substantial but socially differentiated remote-work preference, with implications for workforce planning in mid-sized metropolitan regions. Full article

Background: The most accurate intraocular lens power calculation formula for highly myopic eyes remains uncertain. The objective of this study was to perform a systematic review and network meta-analysis to compare and rank IOL power calculation formulas in eyes with an axial length greater than 26 mm. Methods: A literature search was conducted in PubMed, the Cochrane Library, Scopus, and Web of Science. The main outcome for comparison was the percentage of eyes with a refractive prediction error <0.25 diopters, <0.50 diopters, and <1.00 diopter. A network meta-analysis was performed, and Surface Under the Cumulative Ranking Curve values were calculated to rank formulas across the three prediction error thresholds. Forest plots were generated comparing all formulas with Barrett Universal II as the reference. Results: Ten studies were finally included. Based on Surface Under the Cumulative Ranking Curve values, Kane and Holladay 1 (with the original Wang–Koch axial length adjustment) ranked among the top three formulas across all prediction error thresholds. Hill-RBF 3.0, EVO, and Barrett Universal II ranked among the top three for the <0.25 diopters, <0.50 diopters, and <1.00 diopter thresholds, respectively. The Kane and Holladay 1 (with the original Wang–Koch axial length adjustment) formulas were the only ones showing odds ratios favouring their accuracy over Barrett Universal II across all prediction error thresholds in the forest plots, although differences were not statistically significant. Conclusions: The Kane and Holladay 1 (with the original Wang–Koch axial length adjustment) formulas showed the most consistent performance in highly myopic eyes. Hill-RBF 3.0, EVO, and Barrett Universal II also demonstrated high precision and may be considered reliable alternatives. Full article