Search Results (9)

Background: Advanced therapy medicinal products (ATMPs) require strict control of critical process parameters (CPPs) to ensure manufacturing efficiency. The relative impact of donor systemic factors, such as vitamin D status, versus technical process parameters on dental pulp-derived stem cell (DPSC) production remains unclear. Methods: In this prospective observational study, 250 adults undergoing extraction of impacted mandibular third molars were included. Dental pulp was processed under a standardized SOP using different preparation methods and enzyme conditions. Primary endpoints were serum 25(OH)D concentration and cell yield; secondary endpoints included number of passages and cryovials. Results: Mean 25(OH)D concentration was 30.1 ± 14.5 ng/mL and was higher in supplemented individuals (38.2 ± 14.0 vs. 25.6 ± 12.7 ng/mL; p < 0.0001) but was not associated with cell yield (ρ = 0.14, p = 0.168) or passages (ρ = 0.07, p = 0.406). In contrast, process parameters showed strong effects: scissor preparation resulted in a substantially higher yield than mechanical methods (median 5.00 vs. 1.00 million cells; p = 3.6 × 10⁻¹³), and type II collagenase was independently associated with a higher yield (+2.04 million cells; p = 0.026). The number of passages was the strongest predictor of yield (β = 2.28 million per passage; p < 10⁻²⁶). Post-thaw viability remained high (mean 90.1% and range 81–98%). Conclusions: Manufacturing efficiency of DPSCs is primarily determined by critical process parameters, particularly preparation method, enzyme selection, and passage control, whereas donor vitamin D status did not significantly influence outcomes under the studied SOP. These findings highlight process standardization as the key driver of reproducible ATMP manufacturing. Full article

Background/Objectives: Achondroplasia is linked to distinctive ear–nose–throat (ENT) morbidity, yet quantitative age-structured profiles and actionable correlates remain incompletely defined. This study mapped ENT phenotypes in a consecutive cohort and examined the achondroplasia subset for prevalence, co-occurrence, age dynamics, and parsimonious risk models. Methods: Retrospective observational analysis (1 February 2023–31 January 2025). Narrative “ENT complications” were dictionary-mapped to five non-exclusive categories: otitis media, adenotonsillar/apnea—obstructive sleep apnea (OSA), audiologic/Eustachian-tube dysfunction (ETD), nasopharyngeal/upper-respiratory (URT), and extra-ENT. Proportions used Wilson 95% confidence intervals (CIs). Pairwise associations used Fisher’s exact tests with Benjamini–Hochberg false discovery rate (BH-FDR). Age was summarized by a four-level age-class schema (AC-4: 0–2, 3–5, 6–12, ≥13 years) and a two-level sensitivity contrast (AC-2: ≤5 vs. >5 years). Results: Of 83 patients, 64 (77.1%) had achondroplasia. In achondroplasia, otitis media occurred in 51.6% and OSA in 28.1%; versus non-achondroplasia, ARDs were +35.8 and +28.1 percentage points (BH-FDR adjusted). Within achondroplasia, otitis media co-occurred with OSA (odds ratio [OR] 4.97; q = 0.012) and with ETD (OR 7.25; q = 0.012). OSA increased across AC-4 to school age (p-trend = 0.0548). In parsimonious models, otitis media independently predicted ETD and OSA. A five-item ENT-burden score discriminated otologic and adeno-tonsillar interventions (AUC 0.83–0.93). Conclusions: Achondroplasia shows a concentrated ENT burden dominated by otitis media and OSA, with large adjusted absolute differences versus non-achondroplasia. Otitis media functions as a practical clinical marker for both OSA and ETD, while a compact burden score may assist intervention triage. Full article

The aim of this study was to analyze long-term trends and spatial variability of PM10 concentrations in Poland during the period 2019–2024, based on data from the European Air Quality Monitoring System (EAQ). The analysis covered nine locations representing three types of areas: large agglomerations (Warsaw, Kraków, Katowice), medium-sized cities (Wrocław, Poznań), and spa towns (Ciechocinek, Lądek-Zdrój, Świnoujście). An integrated statistical approach was applied, including Welch’s ANOVA, Linear Mixed Models (LMM), Generalized Additive Models (GAM), and Quantile Regression (FDR–BH). Mean PM10 concentrations in the analyzed period ranged from 17.43 µg/m³ in Świnoujście to 31.16 µg/m³ in Kraków, with 30.17 µg/m³ in Katowice and 27.90 µg/m³ in Warsaw. The largest differences between locations were observed during smog episodes —the 90th percentile values reached 56.61 µg/m³ in Kraków, 49.99 µg/m³ in Katowice, and 29.19 µg/m³ in Świnoujście. In most locations, a downward trend in PM10 levels was recorded over time; however, regional differences persist. The GAMs confirmed strong seasonality (winter maximum, summer minimum), while quantile regression indicated that the highest risk of smog episodes occurs in southern Poland. The novelty of this study lies in the integration of three complementary modeling approaches (LMM, GAM, and Quantile Regression) in the analysis of the spatio-temporal variability of PM10, as well as in the innovative comparison-unique in the literature-of agglomerations, medium-sized cities, and spa towns in Poland based on a uniform, reference EAQ dataset. This approach made it possible to reveal persistent environmental disparities of significant relevance to the national anti-smog policy and enables a more realistic assessment of environmental risk within the European research context. Full article

Statistical inference in spatiotemporal trend analysis often involves testing separate hypotheses for each pixel in datasets containing thousands of observations. A pixel is considered significant if its p-value falls below a rejection threshold (α). However, this uncorrected approach ignores the large number of simultaneous tests and greatly increases the risk of false positives. This issue, known as multiple testing or multiplicity, can be addressed by controlling the false discovery rate (FDR), defined as the expected proportion of false positives (i.e., false discoveries) among all rejected hypotheses, at a pre-specified control level q. This study implements the linear adaptive two-stage Benjamini–Krieger–Yekutieli (BKY) procedure for FDR control in spatiotemporal trend testing and compares it with two alternatives: the uncorrected significance approach and the original non-adaptive Benjamini–Hochberg (BH) procedure. The BKY method empirically estimates the number of true null hypotheses (m₀) and adaptively relaxes the rejection threshold when many true alternatives are present, thereby increasing statistical power without compromising FDR control. Results indicate that the BKY procedure is a recommended approach for large-scale trend testing using spatiotemporal environmental data, particularly in gridded-data-intensive fields such as environmental remote sensing, climatology, and hydrology. To foster reproducibility, R code is provided to apply the BKY procedure and compare it with the uncorrected raw p-values and the BH approach on any gridded dataset. Full article

MicroRNAs (miRNAs) are key regulators of gene expression with critical roles in oncogenic signaling. Endometrial cancer (EC) has been redefined with the identification of POLE-ultramutated tumors which, despite their hypermutated phenotype, show more favorable prognosis. We profiled miRNA expression in tumor tissues from forty (40) EC patients and twenty (20) healthy controls using qPCR panels. POLE exonuclease domain mutations (P286R, V411L) were genotyped, and subgroup analyses were conducted between POLE-mutated (n = 7) and POLE-wild-type (n = 33) tumors. Bioinformatic analyses included validated miRNA–mRNA interactions, target enrichment, and Gene Ontology (GO) pathway mapping. Comparison of EC versus healthy endometrium revealed 50 significantly dysregulated (∣log₂ (FoldReg)∣ > 1 and BH FDR < 0.05) miRNAs, including up-regulation of the oncogenic hsa-miR-181a-5p, hsa-miR-23a-3p, hsa-miR-200c-3p, and down-regulation of tumor-suppressive let-7 family members. Target enrichment implicated canonical oncogenic regulators such as MYC, TP53, and VEGFA. POLE-mutated tumor analysis demonstrated a miRNA signature, with 19 miRNAs significantly down-regulated, including let-7f-5p and hsa-miR-200b-3p. Findings for the EC versus healthy endometrium comparison were validated against TCGA-UCEC sequencing data which confirmed concordant dysregulation of key miRNAs across platforms. Our findings reveal that EC is characterized by widespread miRNA deregulation, with a unique global down-regulation signature in POLE-mutated tumors. These results highlight the potential of miRNAs as complementary biomarkers for classification and potential targets in EC. Full article

Cortical transcriptional dysregulation is widespread in Huntington’s disease (HD). We re-examined prefrontal Brodmann Area 9 (BA9) RNA-seq (GSE64810; 20 HD, 49 controls) using BH-FDR and GEO2R to obtain differential-expression statistics for downstream in silico integration. A compact, direction-aware 80-gene panel was assembled for visualization/ranking only, while inference relied on validated target sets and full-universe testing. At FDR < 0.05, we detected Up = 2923 and Down = 2448 genes (ratio 1.19), indicating a mild predominance of up-regulation. MIR219A2 was strongly down-regulated, and four experimentally validated targets (FOXC1, NFKBIA, SLC38A2, SLC6A20) overlapped the up-regulated core; as expected for n = 4, no GO/KEGG/Reactome term met FDR < 0.05, and STRING returned no high-confidence edges. Beyond the curated panel, we tested MIR219A2 (hsa-miR-219a-5p; hsa-miR-219a-1-3p; hsa-miR-219a-2-3p) targets against the full FDR-significant BA9 up-regulated universe. Two orthogonal, experimentally supported resources—miRTarBase functional assays and ENCORI/starBase CLIP—showed direction-consistent, FDR-controlled enrichment, with effect sizes and uncertainty reported in the main text, supporting a BA9-specific, MIR219A2-aligned association signal. On the TF axis, MSigDB C3:TFT (gene symbols) revealed significant over-representation of TF target sets among BA9-Up under the same BA9 expressed-gene background after BH-FDR (e.g., NFAT motifs, C/EBP, FOXA/HNF3), while TRRUST v2 applied to the MIR219A2 CLIP–BA9-Up subset provided target-level transparency. MIR219A2 enrichments were robust to composition sensitivity analyses (marker-excluded and neuron/glia-stratified backgrounds). Exploratory GO–Biological Process bubbles are shown for trend summarization only; no term met FDR < 0.05 in the primary analysis. All conclusions are analysis-only; no wet-lab or biofluid/peripheral assays were performed, and findings are BA9-specific—generalization to other regions remains hypothesis-generating. Full article

Ankylosing spondylitis (AS) displays wide inter-patient variability that is not accounted for by HLA-B27 alone, suggesting that additional immune and metabolic modifiers contribute to disease severity. Using a genetically matched design, we profiled peripheral blood mononuclear cells from two brother pairs discordant for AS severity and one healthy brother pair. Strand-specific RNA-seq was analyzed with a family-blocked DESeq2 model, while untargeted metabolites were quantified using gas chromatography–mass spectrometry (GC-MS) and liquid chromatography–mass spectrometry (LC-MS). Differential features were defined as follows: differentially expressed genes (DEGs) (|log₂FC| ≥ 1 and FDR < 0.05) and metabolites (VIP > 1, FC ≥ 1.2, and BH-adjusted p < 0.05). Pathway enrichment was performed with KEGG and Gene Ontology (GO). A total of 325 genes were differentially expressed. Type I interferon and neutrophil granule transcripts (e.g., IFI44L, ISG15, S100A8/A9) were markedly up-regulated, whereas mitochondrial β-oxidation genes (ACADM, CPT1A, ACOT12) were repressed. Metabolomics revealed 110 discriminant features, including 25 MS/MS-annotated metabolites. Primary bile acid intermediates were depleted, whereas oxidized fatty acid derivatives such as 12-Z-octadecadienal and palmitic amide accumulated. Spearman correlation identified two antagonistic modules (i) interferon/neutrophil genes linked to pro-oxidative lipids and (ii) lipid catabolism genes linked to bile acid species that persisted when severe and mild siblings were compared directly. Enrichment mapping associated these modules with viral defense, neutrophil degranulation, fatty acid β-oxidation, and bile acid biosynthesis pathways. This sibling-paired peripheral blood mononuclear cell (PBMC) dual-omics study delineates an interferon-driven lipid–bile acid axis that tracks AS severity, supporting composite PBMC-based biomarkers for future prospective validation and highlighting mitochondrial lipid clearance and bile acid homeostasis as potential therapeutic targets. Full article

Background/Objectives: Individuals with childhood obesity exhibit significant metabolic heterogeneity, necessitating precise biomarkers for risk stratification and assessment. This multi-omics investigation characterizes metabolic and microbial signatures underlying divergent metabolic phenotypes in the context of pediatric obesity. Methods: We analyzed 285 Chinese children (5–7 years) stratified into five groups: wasting (WAS, n = 55), metabolically healthy/unhealthy and normal weight (MHWH, n = 54; MUWH, n = 67), and metabolically healthy/unhealthy obesity (MHO, n = 36; MUO, n = 73). Untargeted metabolomics (Orbitrap ID-X Tribrid™) and 16S rRNA sequencing were integrated with multivariate analyses (OPLS-DA with VIP > 1, FDR < 0.05; Maaslin 2 with TSS normalization and BH correction, FDR < 0.10). Results: Analysis identified 225 differential metabolites and 12 bacterial genera. The proportion of steroids and their derivatives among differential metabolites in the MUO/MHO group was significantly lower than that in the OVOB/NOR and OVOB/WAS groups (2.12% vs. 7.9–14.1%). MUO displayed elevated C17 sphinganine and LysoPC (O-18:0) levels but reduced PI (16:0/14:1) levels. In contrast, OVOB showed upregulated glycerol phospholipids (LPCs and PSs) and downregulated PE species (e.g., PE(16:0/16:0)) as well as gut microbiota dysbiosis characterized by a higher Firmicutes/Bacteroidetes (F/B) ratio (2.07 vs. 1.24 in controls, p = 0.009) and reduced α diversity (Ace index, Chao1 index, and Shannon index values were lower in the OVOB group, Shannon index: 2.96 vs. 3.45, p = 0.03). SCFA-producing genera were negatively correlated with the OVOB group, while positively associated with PE(16:0/16:0). Internal validation showed differential metabolites had potential predictive efficacy for MUO/MHO (AUC = 0.967) and OVOB/NOR (AUC = 0.888). Conclusions: We identified distinct lipid disruptions characterizing obesity subtypes, including steroid/terpene deficits and sphingolipid/ether lipid dysregulation in the MUO/MHO groups as well as phospholipid imbalance (↑LPC/PS↓PE) in the OVOB/NOR groups. The gut microbiota exhibited a profile characterized by low diversity, an increased F/B ratio, and a reduced abundance of SCFA-producing genera. These findings suggest potential biomarkers for childhood obesity stratification, though further validation is warranted. Full article

In high-dimensional gene expression data analysis, the accuracy and reliability of cancer classification and selection of important genes play a very crucial role. To identify these important genes and predict future outcomes (tumor vs. non-tumor), various methods have been proposed in the literature. But only few of them take into account correlation patterns and grouping effects among the genes. In this article, we propose a rank-based modification of the popular penalized logistic regression procedure based on a combination of ${\ell }_1$ and ${\ell }_2$ penalties capable of handling possible correlation among genes in different groups. While the ${\ell }_1$ penalty maintains sparsity, the ${\ell }_2$ penalty induces smoothness based on the information from the Laplacian matrix, which represents the correlation pattern among genes. We combined logistic regression with the BH-FDR (Benjamini and Hochberg false discovery rate) screening procedure and a newly developed rank-based selection method to come up with an optimal model retaining the important genes. Through simulation studies and real-world application to high-dimensional colon cancer gene expression data, we demonstrated that the proposed rank-based method outperforms such currently popular methods as lasso, adaptive lasso and elastic net when applied both to gene selection and classification. Full article