Search Results (733)

To reduce reliability testing time, experiments are often terminated at a predetermined time, producing right-censored lifetime data. Alternatively, when test samples are inspected at fixed intervals, failures are only observed within these intervals, resulting in interval-censored lifetime data. Although quality control methods for right-censored data are well established, relatively little attention has been given to interval-censored observations. Motivated by the success of residual control charts based on convolutional neural network (CNN) for right-censored data, this study extends the chart for monitoring normally distributed interval-censored lifetime data. Simulation results based on average run length (ARL) indicate that the proposed method outperforms the traditional exponentially weighted moving average (EWMA) chart in detecting decreases in mean lifetime. The findings also highlight the practical benefits of employing high- or low-order autoregressive CNN models depending on the magnitude of process shifts. Full article

We develop a unified likelihood-based framework for limited outcomes built on the two-piece normal family. The framework includes a censored specification that accommodates boundary inflation, a doubly truncated specification on $(0,1)$ for rates and proportions, and a survival formulation with a log-two-piece normal baseline and Gamma frailty to account for unobserved heterogeneity. We derive closed-form building blocks (pdf, cdf, survival, hazard, and cumulative hazard), full log-likelihoods with score functions and observed information, and stable reparameterizations that enable routine optimization. Monte Carlo experiments show a small bias and declining RMSE with increasing sample size; censoring primarily inflates the variability of regression coefficients; the scale parameter remains comparatively stable, and the shape parameter is most sensitive under heavy censoring. Applications to HIV-1 RNA with a detection limit, household food expenditure on $(0,1)$, labor-supply hours with a corner solution, and childhood cancer times to hospitalization demonstrate improved fit over Gaussian, skew-normal, and beta benchmarks according to AIC/BIC/CAIC and goodness-of-fit diagnostics, with model-implied censoring closely matching the observed fraction. The proposed formulations are tractable, flexible, and readily implementable with standard software. Full article

The rapid development of autonomous driving systems has increased the demand for scalable frameworks capable of modeling vehicle motion patterns in complex traffic environments. This paper proposes a big data spatio-temporal modeling architecture that integrates Apache Spark version 4.0.1 (SparkML) with Long Short-Term Memory (LSTM) networks to analyze and classify vehicle trajectory patterns. The proposed SparkML–LSTM framework exploits Spark’s distributed processing capabilities and LSTM’s strength in sequential learning to handle large-scale traffic trajectory data efficiently. Experiments were conducted using the DETRAC dataset, which is a large-scale benchmark for vehicle detection and multi-object tracking consisting of more than 10 h of video captured at 24 different locations. The videos were recorded at 25 frames per second with a resolution of 960 × 540 pixels and annotated across more than 140,000 frames, covering 8.250 vehicles and approximately 1.21 million bounding box annotations. The dataset provides detailed annotations, including vehicle categories (Car, Bus, Van, Others), weather conditions (Sunny, Cloudy, Rainy, Night), occlusion ratio, truncation ratio, and vehicle scale. Based on the extracted trajectory features, vehicle motion patterns were categorized into predefined movement classes derived from trajectory dynamics. The experimental results demonstrate strong classification performance. These findings suggest that the proposed SparkML–LSTM architecture is effective for large-scale spatio-temporal trajectory modeling and traffic behavior analysis, and can serve as a foundation for higher-level decision-making modules in intelligent transportation system. Full article

The U94 protein of Human Herpesvirus 6 exerts antiproliferative effects through downregulation of the Src proto-oncogene. We aimed to define the shortest U94 fragment that preserves antiproliferative activity and to explore its structural properties. U94 was truncated into shorter fragments, which were subjected to computational analyses and proliferation assays on MDA-MB-468, BT-549 breast cancer cells. Src phosphorylation levels were scrutinized by Western blot analysis. Data obtained demonstrated that the U94 antiproliferative activity resides in its N-terminal region. Specifically, MT153 (aa 1–153) and MT117 (aa 1–117) fragments exhibited antiproliferative activity, whereas MV85 (aa 1–85) fragment did not. Computational analyses identified MG112 (aa 1–112) and MI108 (aa 1–108) as biologically active and suggested that the β-sheet of the structure is critical. The shortest KI95 fragment (aa 14–108), maintaining a stable β-sheet, demonstrated antiproliferative effects and Src downregulation. The antiproliferative activity of U94 and its active fragments relies on stable tridimensional conformation rather than on linear peptide sequence. KI95 represents the shortest active U94 fragment that preserves biological function, with critical residues likely located within the β-sheet region. These findings highlight the importance of structural integrity in U94 functionality and suggest KI95 as a potential therapeutic agent for cancer treatment. Full article

Background/Objectives: Acute health events in institutionalized older adults often lead to avoidable hospital referrals, requiring rapid, accurate remote decision-making. Telemedicine has become a key tool to improve assessment and care continuity in nursing homes. This study aimed to evaluate outcomes associated with telemedicine-supported management of acute events in residential care facilities for older adults and to develop a deep learning model to classify episodes and predict hospital referrals. Methods: A quasi-experimental study analyzed 5202 acute events managed via a 24/7 telemedicine system in Vitalia nursing homes (January–October 2024). The dataset included demographics, comorbidities, vital signs, event characteristics, and outcomes. Data preprocessing involved imputation, normalization, encoding, and dimensionality reduction via Truncated SVD (200 components). Given the imbalance in referral outcomes (~10%), several resampling techniques (SMOTE, SMOTEENN, SMOTETomek) were applied. A deep feedforward neural network (256–128–64 units with Batch Normalization, LeakyReLU, Dropout, AdamW) was trained using stratified splits (70/10/20) and optimized via cross-validation. Results: Telemedicine enabled the resolution of approximately 90% of acute events within the residential setting, reducing reliance on emergency services. The deep learning model outperformed traditional algorithms, achieving its best performance with SMOTEENN preprocessing (AUC = 0.91, accuracy = 0.88). The proposed model achieved higher overall performance than baseline classifiers, providing a more balanced precision–specificity trade-off for hospital referral prediction, with an F1-score of 0.63. Conclusions: Telemedicine-enabled acute care, strengthened by a robust deep learning classifier, offers a reliable strategy to enhance triage accuracy, reduce unnecessary transfers, and optimize clinical decision-making in nursing homes. These findings support the integration of AI-assisted telemedicine systems into long-term care workflows. Full article

Background: Coffin–Siris syndrome 12 (CSS12) is a recently described neurodevelopmental disorder caused by heterozygous pathogenic variants in BICRA, a gene encoding a core subunit of the non-canonical BAF (ncBAF) chromatin-remodeling complex. The condition is characterized by developmental delay, hypotonia, hypertrichosis, and joint laxity. However, long-term data remain limited, and systemic manifestations are incompletely defined. Case Description: We report a 22-year-old male with a de novo BICRA frameshift variant, c.2479_2480delinsA (p.Ala827Thrfs*15), previously included in the original cohort reported by Barish et al. Longitudinal follow-up revealed an expanded phenotype extending beyond neurodevelopmental features. Early findings included global developmental delay, growth hormone deficiency, short stature, and joint hypermobility. In adolescence and adulthood, he developed severe intestinal dysmotility requiring total colectomy, recurrent spontaneous pneumothoraces from bilateral apical bullous disease, and portal-vein thrombosis, representing visceral and vascular complications not previously emphasized in BICRA-related disorders. The identified BICRA variant truncates the coiled-coil domain critical for BRD9/BRD4 interaction, consistent with a loss-of-function mechanism. The patient’s systemic features suggest that BICRA haploinsufficiency affects not only neurodevelopmental pathways but also smooth-muscle and connective-tissue integrity. Conclusions: This case expands the phenotypic spectrum of BICRA-related CSS12, demonstrating that visceral and vascular involvement can occur alongside neurodevelopmental and connective-tissue features. Recognition of these broader manifestations underscores the need for lifelong multidisciplinary surveillance and contributes to understanding the diverse biological roles of the ncBAF complex in human development. Full article

Background/Objectives: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused the global COVID-19 pandemic, which led to hundreds of millions of human infections and more than seven million deaths worldwide. Major variants of concern, particularly the Omicron variant and its associated subvariants, can escape the vaccines developed so far to target previous strains/subvariants. Therefore, effective vaccines that broadly neutralize different Omicron subvariants and show good protective efficacy are needed to prevent further spread of Omicron. The spike (S) protein, including its receptor-binding domain (RBD), is a key vaccine target. Methods: Here, we designed a unique mRNA vaccine encoding Omicron-KP.3 RBD based on RBD-truncated S protein backbone of an earlier Omicron subvariant EG.5 (KP3 mRNA), and evaluated its stability, immunogenicity, neutralizing activity, and protective efficacy in a mouse model. Results: Our data showed that the nucleoside-modified, lipid nanoparticle-encapsulated mRNA vaccine was stable at various temperatures during the period of detection. In addition, the vaccine elicited potent antibody responses with broadly neutralizing activity against multiple Omicron subvariants, including KP.2, KP.3, XEC, and NB.1.8.1. This mRNA vaccine protected immunized transgenic mice from challenge with SARS-CoV-2 Omicron-KP.3. Immune serum also protected against subsequent virus challenge, with the level of protection associating positively with the serum neutralizing antibody titer. Conclusions: Taken together, the data presented herein suggest that this newly designed mRNA vaccine has potential against current and future Omicron subvariants. Full article

This review integrates molecular, clinical, and translational data to provide an updated understanding of GJB2-related deafness and its emerging treatment landscape. Truncating mutations in GJB2 typically cause severe-profound hearing loss (HL) phenotypes, whereas non-truncating alleles are often associated with milder or progressive phenotypes. Geographic variation in variant prevalence contributes to regional differences in disease burden. Beyond the coding region, deletions and cis-regulatory mutations within the DFNB1 locus, including GJB6 and CRYL1, can influence HL severity when compounded with other pathogenic GJB2 variants. DFNB1 hearing loss generally presents as symmetric, bilateral, and flat to gently sloping across frequencies, with preserved cochlear neurons that support excellent cochlear implant (CI) outcomes. Early implantation CI in GJB2-positive children yields superior speech and language development compared with non-GJB2 etiologies. Emerging therapies include dual-AAV (AAV1 + AAV-ie/ScPro) delivery, achieving cell-specific Cx26 restoration, adenine base-editing for dominant-negative variants, and allele-specific suppression using RNA interference or antisense oligonucleotides. Concurrent progress in human iPSC-derived cochlear organoids provides a physiologic model to advance toward clinical trials. By integrating genotype-phenotype correlations, natural history insights, and advances in molecular therapeutics, this review presents a comprehensive update on GJB2-related HL and highlights how gene-based strategies are poised to change the treatment of this condition. Full article

Background: Germline alterations in DNA damage repair (DDR) genes represent a clinically important subset of prostate cancer (PCa), but real-world data from Middle Eastern and Turkish populations remain limited. We evaluated the prevalence and clinicopathologic associations of germline DDR variants in a single-center Turkish cohort. Methods: We retrospectively analyzed 122 men with histologically confirmed PCa who underwent germline multigene panel testing. Variants were classified according to ACMG/ClinVar criteria. Patients were grouped as pathogenic/likely pathogenic (P/LP), variants of uncertain significance (VUS), or variant-negative. Patients were grouped as variant-positive (P/LP or VUS/uncategorized) or clinically actionable variant–negative (benign/likely benign or no variant detected). Group comparisons used t-tests, chi-square or Fisher’s exact tests as appropriate. Results: The median age at diagnosis was 65.2 years (mean 64.6 ± 8.78). Overall, 37 patients (30.3%) carried at least one germline variant, including 12 (9.8%) with P/LP alterations and 24 (19.7%) with VUS; one patient (0.8%) harbored an uncategorized variant. The most frequently affected genes were CHEK2 (n = 8), BRCA1 (n = 6), BRCA2 (n = 6), ATM (n = 5), and APC (n = 4). Variant-positive status increased from 10.8% in ISUP 1–2 to 21.6% in ISUP 3 and 76.0% in ISUP 4–5, although this trend was not statistically significant (p = 0.391). Mean age at diagnosis and the prevalence of metastatic disease did not differ between variant-positive and clinically actionable variant–negative patients (64.2 vs. 65.7 years, p = 0.390; 66.7% vs. 64.6%, p = 0.842). Truncating DDR variants (RAD50, BRCA2, MSH3, NBN, CHEK2, ATM) occurred predominantly in ISUP 4–5 tumors. Conclusions: Germline DDR alterations—most notably in BRCA2, CHEK2, and ATM—were present in a substantial subset of Turkish men with PCa and showed a non-significant trend toward clustering in higher-grade disease. The high prevalence of VUS reflects limited genomic annotation in under-represented populations and underscores the need for longitudinal reinterpretation. These data support the clinical value of incorporating germline DDR testing into risk assessment and familial counseling, while larger cohorts integrating somatic profiling are needed to refine genotype–phenotype associations. Full article

Background: Duchenne muscular dystrophy (DMD) results from pathogenic variants in the DMD gene, one of the most significant and most mutation-prone genes in the human genome. Although global mutation registries are well developed, genetic data from Central Asian populations remain extremely limited, leaving essential gaps in regional epidemiology and in the understanding of genotype–phenotype patterns. Methods: We conducted a retrospective analysis of patients with genetically confirmed dystrophinopathy in Kazakhstan. Variants were identified using multiplex ligation-dependent probe amplification (MLPA) for exon-level copy number alterations and next-generation sequencing (NGS) with Sanger confirmation for sequence-level changes. All variants were classified under ACMG guidelines. Statistical modelling incorporated mutation-class grouping, exon-hotspot mapping, reading-frame status, CPK stratification, chi-squared association testing, Spearman correlations, Kaplan–Meier ambulation survival curves, and multivariable logistic and Cox regression. Results: multi-exon deletions were the predominant mutation class, with a marked concentration within the canonical hotspot spanning exons 44–55. Recurrent deletions affecting exons 46–50 and 45–50 appeared in several unrelated patients. NGS confirmed severe protein-truncating variants, including p. Lys1049* and p. Ser861Ilefs*7. Phenotypic severity followed a consistent hierarchy: hotspot-associated deletions and early truncating variants showed the earliest loss of ambulation, whereas splice-site variants and duplications demonstrated the mildest courses. CPK levels correlated with the extent of genomic involvement, though extreme elevations did not consistently predict early functional decline. Regression models identified hotspot localization and out-of-frame effect as independent predictors of ambulation loss. Conclusions: This study provides the first statistically modelled characterisation of DMD gene mutations in Kazakhstan. While the mutational landscape largely mirrors global patterns, notable variability in clinical severity suggests the presence of population-specific modifiers. Integrating comprehensive molecular diagnostics with statistical-genetics approaches enhances prognostic accuracy and supports the development of mutation-targeted therapeutic strategies in Central Asia. Full article

Accurate estimation of the open-circuit voltage (OCV) as a function of state of charge (SOC) is critical for reliable battery-management system (BMS) design in lithium-ion battery applications. However, at low temperatures, polarization effects distort the measured OCV–SOC profile due to premature voltage cutoffs during low-rate testing. This paper presents an offsetting-based correction method that reconstructs the truncated portions of the OCV curve by extrapolating the charge/discharge data beyond the cutoff points using simple voltage offsets. The approach is applied entirely in post-processing, requiring no modification to standard test protocols. Experimental validation using Samsung EB575152 Li-ion cells across a wide temperature range (−25 °C to 50 °C) demonstrates that the method restores the full OCV span, reduces apparent capacity loss, and improves consistency across cells and temperatures. The proposed technique offers a practical and effective enhancement to standard OCV testing procedures for temperature-aware SOC modeling. Full article

Background: Wolfram syndrome (WS) is an ultrarare neuroendocrine disorder caused by pathogenic variants in WFS1, frequently leading to progressive neurological, autonomic, and cognitive impairment. Anticipating neurological trajectories remains challenging due to marked phenotypic variability and limited genotype–phenotype data. Methods: Forty-five genetically confirmed patients with WS were evaluated between 1998 and 2024 in Spain. All WFS1 variants were systematically classified by exon, zygosity, protein-level functional impact, and predicted wolframin production (Classes 0–3). Machine learning models (Random Forests with engineered gene–gene interaction terms) were applied to predict neurological manifestations and identify the strongest genetic determinants of symptom severity. Results: Neurological involvement was present in 93% of patients. The most prevalent manifestations were absence of gag reflex (67%), gait instability (64%), dysphagia (60%), and sialorrhea (60%), followed by dysmetria (56%), impaired tandem gait (53%), anosmia (44%), dysarthria (44%), and adiadochokinesia (42%). Most symptoms emerged in early adulthood (23–26 years), whereas cognitive decline occurred later (29.9 ± 12.2 years). Homozygosity for truncating variants—particularly c.409_424dup16 (Val142fsX110)—and complete loss of wolframin production (Class 0; 67–83% across symptoms) were the strongest predictors of early and severe neurological involvement. Machine learning models achieved high discrimination for ataxia, gait instability, and absent gag reflex (AUC 0.63–0.86; calibrated AUC up to 0.97), identifying Mut1_Protein_Class and Mut2_Protein_Class as dominant predictors across all phenotypes, followed by coherent secondary effects from zygosity × exon interaction terms (Prod_mgm). Conclusions: Integrating detailed genetic classification with machine learning methods enables accurate prediction of neurological outcomes in WS. Protein-level dysfunction and allele interaction structure are the principal drivers of neurological vulnerability. This framework enhances precision diagnosis and offers a foundation for individualized surveillance, clinical risk stratification, and future therapeutic trial design in WFS1-related disorders. Full article

Background: Pathogenic variants in interphotoreceptor matrix proteoglycan 1 (IMPG1) have been associated with autosomal dominant and recessive retinitis pigmentosa (RP) and autosomal dominant adult vitelliform macular dystrophy (AVMD). Monoallelic pathogenic variants in IMPG2 have been linked to maculopathy and biallelic variants to RP with early onset macular atrophy. Herein we characterise the phenotypic and genotypic features of patients with IMPG1/IMPG2 retinopathy and report novel variants. Methods: Patients with IMPG1 and IMPG2 variants and compatible phenotypes were retrospectively identified. Clinical data were obtained from reviewing the medical records. Phenotypic data included visual acuity, imaging included ultra-widefield pseudo-colour, fundus autofluorescence, and optical coherence tomography (OCT). Genetic testing was performed using next generation sequencing (NGS). Variant pathogenicity was investigated using in silico analysis (SIFT, PolyPhen-2, mutation taster, SpliceAI). The evolutionary conservation of novel missense variants was also investigated. Results: A total of 13 unrelated patients were identified: 2 (1 male; 1 female) with IMPG1 retinopathy and 11 (7 male; 4 female) with IMPG2 retinopathy. Both IMPG1 retinopathy patients were monoallelic: one patient had adult vitelliform macular dystrophy (AVMD) with drusenoid changes while the other had pattern dystrophy (PD), and they presented to clinic at age 81 and 72 years, respectively. There were 5 monoallelic IMPG2 retinopathy patients with a maculopathy phenotype, of whom 1 had PD and 4 had AVMD. The mean age of symptom onset of this group was 54.2 ± 11.8 years, mean age at presentation was 54.8 ± 11.5 years, and mean BCVAs were 0.15 ± 0.12 logMAR OD and −0.01 ± 0.12 logMAR OS. Six biallelic IMPG2 patients had RP with maculopathy, where the mean age of onset symptom onset was 18.4 years, mean age at examination was 68.7 years, and mean BCVAs were 1.90 logMAR OD and 1.82 logMAR OS. Variants in IMPG1 included one missense and one exon deletion. A total of 11 different IMPG2 variants were identified (4 missense, 7 truncating). A splicing defect was predicted for the c.871C>A p.(Arg291Ser) missense IMPG2 variant. One IMPG1 and five IMPG2 variants were novel. Conclusions: This study describes the phenotypic spectrum of IMPG1/IMPG2 retinopathy and six novel variants are reported. The phenotypes of PD and AVMD in monoallelic IMPG2 patients may result from haploinsufficiency, supported by the presence of truncating variants in both monoallelic and biallelic cases. The identification of novel variants expands the known genetic landscape of IMPG1 and IMPG2 retinopathies. These findings contribute to diagnostic accuracy, informed patient counselling regarding inheritance pattern, and may help guide recruitment for future therapeutic interventions. Full article

This study applies integrated LCA–LCC to 1 L of bottled beer at a representative small Japanese brewery using 2024 operational data. Following ISO 14040/44, the cradle-to-gate boundary covers raw materials (excluding agricultural cultivation while including transport and preprocessing), brewing, packaging, and thermal sterilization. The baseline global warming impact is 0.52 kg CO₂e/L and the cost is JPY 487/L, with single-use glass and labor identified as dominant hotspots. As beer is produced from malt, hops, yeast, and water, this study focuses on how alternative production strategies mitigate sustainability hotspots within this process. Three alternative production scenarios were evaluated within this integrated LCA–LCC model. Scenario 1 (local rice substitution) replaces 30% of the fermentable extract from imported malt with domestically grown rice, changing only ingredient transport and preprocessing within the truncated cradle-to-gate boundary (crop cultivation remains excluded), and yields 0.55 kg CO₂e/L and JPY 492/L, i.e., a slightly higher global warming impact and cost than the baseline. Scenario 2 (direct sales expansion) assumes that 50% of the beer is sold on site via draft, thereby reducing single-use glass bottles and fuel for pasteurization and achieving 0.29 kg CO₂e/L (−44%) and JPY 435/L (−11%) in the deterministic model, the best combined environmental and economic performance among the modeled options. Scenario 3 (joint logistics) models cooperative brewing and shared distribution, which improve labor efficiency and modestly reduce transport intensity, delivering 399 JPY/L in the deterministic model; however, Monte Carlo analysis yields a higher expected cost and indicates that these cost savings are not robust. One-way sensitivity analysis identified packaging and labor as the dominant drivers of both environmental and economic performance, while Monte Carlo simulation confirmed the relative insignificance of electricity-related parameters and reinforced the comparative robustness of Scenario 2. Together, these results highlight the most effective leverage points for a sustainable transition in Japan’s craft beer sector, offering the greatest leverage for a more sustainable transition in Japan’s craft brewing sector. Full article

Efficient spatial indexing is critical for processing large-scale remote sensing datasets (e.g., LiDAR point clouds, orthophotos, hyperspectral imagery). We present a bidirectional, hierarchical index based on the Polish PL-2000 coordinate reference system for (1) direct computation of a map-sheet identifier from metric coordinates (forward encoder) and (2) reconstruction of the sheet extent from the identifier alone (inverse decoder). By replacing geometric point-in-polygon tests with closed-form arithmetic, the method achieves constant-time assignment O(1), eliminates boundary-geometry loading, and enables multi-scale aggregation via simple code truncation. Unlike global spatial indices (e.g., H3, S2), a CRS-native, aligned with cartographic map sheets in PL-2000 implementation, removes reprojection overhead and preserves the legal sheet semantics, enabling the direct use of deterministic O(1) numeric keys for remote-sensing data and Polish archives. We detail the algorithms, formalize their complexity and boundary rules across all PL-2000 zones, and analyze memory trade-offs, including a compact 26-bit packing of numeric keys for nationwide single-table indexing. We also discuss integration patterns with the OGC Tile Matrix Set (TMS), ETL pipelines, and GeoAI workflows, showing how bidirectional indexing accelerates ingest, training and inference, and national-scale visualization. Although demonstrated for PL-2000, the approach is transferable to other national coordinate reference systems, illustrating how statutory map-sheet identification schemes can be transformed into high-performance indices for modern remote sensing and AI data pipelines. Full article