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PubMed2026

Health-Related quality of life (HRQoL) and health state utility values (HSUV) in patients with head and neck Cancer: A systematic review and Meta-Analysis.

BACKGROUND: Head and neck cancer (HNC) and its treatment can substantially impair speech, swallowing, eating, appearance, and social functioning, resulting in persistent reductions in health-related quality of life (HRQoL). Although the EuroQol 5-Dimensions questionnaire (EQ-5D) is widely used to assess generic HRQoL and derive health state utility values (HSUVs), EQ-5D-based evidence in HNC has not been comprehensively synthesized. This study aimed to summarize EQ-5D-based HRQoL and HSUVs in HNC, estimate pooled utility and EQ-VAS scores, explore subgroup differences, and identify predictors of poorer HRQoL. METHODS: A systematic review and meta-analysis was conducted according to PRISMA guidelines and registered in PROSPERO (CRD420261307907). PubMed, EMBASE, Web of Science, Cochrane Library, and Scopus were searched from inception to February 10, 2026. Studies reporting baseline EQ-5D utility values and/or EQ-VAS scores in patients with HNC were included. Random-effects meta-analyses using the DerSimonian-Laird (DL) estimator with the Hartung-Knapp-Sidik-Jonkman (HKSJ) adjustment were performed to pool mean scores. Between-study variance (τ2) and 95 % prediction intervals (PI) were calculated to capture parameter dispersion. Subgroup analyses were conducted across clinical and methodological vectors. RESULTS: Twenty studies involving 7,403 patients were included. The pooled mean EQ-5D utility score was 0.79 (95 % CI: 0.75-0.83; τ2 = 0.0011; 95 % PI: 0.72-0.86). The pooled mean EQ-VAS score was 69.36 (95 % CI: 65.71-73.01; τ2 = 38.4586; 95 % PI: 55.11-83.61). Extreme heterogeneity was observed (I2 = 96.4 % and 97.1 %, respectively). Utility values were significantly higher in studies utilizing the EQ-5D-5 L than the EQ-5D-3 L version (0.82 vs. 0.76). By tumor subsite, nasopharyngeal cancer showed the highest utility value (0.85, exploratory), whereas oral cancer demonstrated the lowest (0.73). Adjusted multivariable models revealed that advanced stage, high treatment intensity, severe pharyngolaryngeal pain, dysphagia, malnutrition, and older age were robust predictors of poorer HRQoL. CONCLUSIONS: Patients with HNC experience substantial and persistent HRQoL impairment, with meaningful variations driven by tumor subsites and instrument versions. In light of the extreme heterogeneity, these pooled findings establish a macro-level, broad reference estimate rather than a fixed target. These parameters directly inform localized survivorship care planning, health technology evaluations, and cost-utility decision-making modeling in head and neck oncology.

Humans↗
PubMed2026

Addressing lignin composition and content via Arabidopsis arogenate dehydratase knockout and over-expression genotypes.

Following the down-selection of 14 Arabidopsis thaliana arogenate dehydratase (ADT) knockout and over-expression (OE) genotypes, the most highly contrasting quadruple knockout adt3/4/5/6 and ADT OE genotypes were subjected to proteomics, metabolomics, and scanning electron microscopy (SEM) analyses as needed, with results compared to Columbia wild-type (WT). The basal adt3/4/5/6 stem cross-sections, ∼70% lignin content reduced, exhibited buckled vessel cell walls and partially detached xylary fibers, in contrast to WT and ADT4m/5 m OE genotypes that did not. Anatomical defects primarily resulted from guaiacyl lignin level reductions in vessels with concomitant increased stem syringyl:guaiacyl (S/G) ratios. Phenylpropanoid and various upstream shikimate-chorismate pathway enzyme abundances, as well as specific monolignol oxidases (laccases/peroxidases), generally increased in adt3/4/5/6 at different stem and rosette leaf growth/development stages, relative to WT. Opposite effects were largely observed with the ADT5m OE genotype. By contrast, flavonoid and glucosinolate pathway enzyme amounts varied. Such enzyme abundance increases were overall unproductive as adt3/4/5/6 was unable to restore WT, ADT4 OE, ADT5 OE, ADT5m OE, and ADT4m/5 m OE secondary metabolite (lignin, phenylpropanoid, lignan, flavonoid, phenolic acid, and glucosinolate) levels. Conversely, ADT OE genotypes did not significantly increase programmed lignin levels or alter S/G compositions. In sum, proteomics analyses of adt3/4/5/6 and adt5 'perceived' that lignin and low molecular weight secondary metabolite amounts were not at 'programmed' levels as for WT and ADT OE genotypes but observed increases in relevant pathway protein abundances were futile. Notably though, proteomics analyses did not lead to predicting that lignin and associated biochemical pathways would have reduced metabolite levels, relative to WT and ADT OE genotypes. Genotype adt3/4/5/6, possibly the highest lignin level reduced genotype reported, did not utilize other phenolics to compensate. By contrast, the differential temporal and spatial deposition of cell wall oxidases again indicate the exquisite control over lignin deposition, and our lack of knowledge of precise lignin structure and assembly in subcellular regions of the lignified cell walls.

Lignin↗
PubMed2026

Spinal meningiomas: histopathological grading using a benchmark radiomics model with notes on disease control.

OBJECTIVE: Spinal meningiomas (SMs) are common primary spinal tumors for which surgery is considered the first-line treatment when safe and feasible. The ability to extrapolate the tumor grade from preoperative imaging may significantly inform early patient expectation-setting regarding recurrence. Building on radiomics studies in cranial meningiomas, the authors aimed to construct a benchmark radiomics model to preoperatively identify the histological grade of SMs. METHODS: Institutional surgical records from May 2012 to November 2025 were queried for pathology-confirmed meningiomas below the foramen magnum, with preoperative contrast-enhanced imaging available for segmentation. SMs were classified as low-grade (WHO grade 1) and high-grade (WHO grade 2 tumors and grade 1 tumors with atypia). Tumors were manually segmented, and features were extracted using the PyRadiomics software package. An ensemble model of k-nearest neighbors, random forest, and support vector machine classifiers was trained using nested cross-validation on a subset of 10 features to differentiate tumor grades. Clinical data for the cohort were also extracted, and disease control in an adjunctive clinical series was assessed. RESULTS: Seventy-four patients were included in radiomics analysis, with an area under the receiver operating characteristic curve of 0.879 and a mean F1 score of 0.748. The model's top 5 features were all texture features that differed significantly (p < 0.05) across low- and high-grade SMs. These included measures of tumor textural and contrast-enhancement heterogeneity, with overlap with features reported in radiomics models for histological grading of intracranial meningiomas. Fifty-five patients with a median radiographic follow-up of 22.2 (range 1.9-86.4) months remained for clinical analysis after exclusion of patients with less than 1 month of follow-up and syndromic meningiomas. Four recurrences occurred at a median of 20.8 (range 1.8-41.8) months. High-grade tumor pathology did not significantly impact progression-free survival (p = 0.682, log-rank test; Cox regression high vs low grade hazard ratio [HR] 0.62, 95% CI 0.06-6.11, p = 0.685). Subtotal resection was associated with poorer progression-free survival than gross-total resection (p = 0.004, log-rank test; Cox regression subtotal vs gross-total resection HR 10.62, 95% CI 1.46-77.05, p = 0.019). These findings remain contextualized within a relatively limited follow-up window and small recurrence event count, suggesting a need to characterize the interplay between tumor grade and extent of resection as drivers of local disease control in SMs. CONCLUSIONS: A preoperative radiomics model can stratify high-grade SMs using open-source tools applied to single-institution data.

Humans↗
PubMed2026

Artificial intelligence (AI) uses in stereotactic radiosurgery (SRS): diagnosis with brain metastasis (BM) - A systematic review.

BACKGROUND: Brain metastases (BM) are the most common intracranial tumors in adults, and stereotactic radiosurgery (SRS) has become a mainstay of management. However, several diagnostic challenges persist in the SRS pathway, particularly the differentiation of radiation necrosis (RN) from true tumor progression, which conventional MRI and even advanced imaging techniques often cannot reliably resolve. Recent advances in artificial intelligence (AI) offer the potential to address these diagnostic limitations. This systematic review synthesizes current literature on AI applications for MRI-based diagnostic decision support in BM patients undergoing SRS, with a focus on radiomics and deep learning tools for distinguishing RN from progression, classifying molecular and histologic subtypes, and predicting treatment response. METHODS: A systematic review was performed in accordance with PRISMA guidelines. PubMed, Web of Science, and Scopus were searched using a targeted query combining terms related to AI, brain metastasis, diagnosis or imaging, and SRS. After screening 483 records and applying strict inclusion and exclusion criteria, 18 studies published between 2015 and 2025 were included. Data were extracted on study design, cohort characteristics, imaging modality, AI methodology, validation strategy, and reported diagnostic performance. RESULTS: Among the 18 included studies, AI models demonstrated strong performance across diagnostic tasks in the BM-SRS pathway. The differentiation of RN from true tumor progression was the most extensively studied application, addressed by 14 of 18 studies, with reported AUCs ranging from 0.71 to 0.94. Support vector machines, random-forest ensembles, convolutional neural networks, and transformer-based multimodal architectures were widely used. The literature evolved from single-sequence radiomic classifiers in 2018 to multimodal deep learning frameworks fusing imaging with clinical and genomic data in 2025. Contrast-enhanced T1-weighted MRI was the dominant imaging input, and texture-based radiomic features (GLCM, GLSZM, GLDM, and wavelet-derived features) were the most consistently predictive. The highest-performing models reached AUCs of 0.85-0.91 through multimodal integration of imaging with clinical and genomic features, and consistently outperformed expert neuroradiologist read on matched cases. Remaining studies addressed longitudinal segmentation-based detection of local failure and adverse radiation effects, BRAF mutation status in melanoma BM, early Gamma Knife treatment response, and primary tumor histology classification, with more variable performance. CONCLUSION: AI models, particularly those integrating MRI-derived radiomic features with clinical and genomic data, show high accuracy in supporting diagnostic decisions for BM patients treated with SRS. The post-SRS differentiation of radiation necrosis from true tumor progression has reached the greatest level of maturity and is closest to clinical translation, with potential to reduce unnecessary biopsies, personalize surveillance intervals, and rationalize treatment-pathway decisions. Other diagnostic applications, including molecular subtyping and primary tumor histology classification, remain exploratory and require further multicenter validation. Integration of AI tools into multidisciplinary tumor-board workflows, combined with prospective validation and standardized reporting, will be essential to realize the full clinical benefits of AI in SRS for brain metastases.

Humans↗
PubMed2026

[Pathogenicity analysis and prenatal genetic counseling for five Chinese pedigrees harboring a hemizygous c.-32C>G variant of FGF13 gene].

OBJECTIVE: To explore the pathogenicity and prenatal counseling strategies for five Chinese pedigrees harboring a hemizygous c.-32C>G (NM_001139500.2) variant of fibroblast growth factor 13 (FGF13) gene. METHODS: Five Chinese pedigrees found to carry a hemizygous c.-32C>G variant of the FGF13 gene at the Prenatal Diagnosis Center of Henan Provincial People's Hospital between January 2024 and January 2025 were selected as study subjects. The pedigrees had undergone prenatal diagnosis for a family history of genetic disorders, abnormal fetal ultrasound findings, or advanced maternal age. A retrospective analysis was carried out, wherein clinical data for all members of the pedigrees were obtained through the medical records system and outpatient visit system. Peripheral blood samples were collected from all pedigree members, and amniotic fluid samples were obtained from the probands. Following extraction of genomic DNA, prenatal diagnosis was performed using chromosomal microarray analysis (CMA) and trio whole-exome sequencing (trio-WES). Sanger sequencing was used to determine the carrier status for the candidate variant, and Mini-Mental State Examination (MMSE) was used to assess the cognitive function of hemizygous individuals carrying the FGF13 gene c.-32C>G variant. Pathogenicity of candidate variant was assessed based on guidelines from the American College of Medical Genetics and Genomics (ACMG). This study was approved by the Medical Ethics Committee of the hospital (Ethics No.: 2021-171). RESULTS: CMA and trio-WES revealed no pathogenic variants in all probands, whilst trio-WES and Sanger sequencing had identified 11 male individuals carrying a hemizygous c.-32C>G variant of the FGF13 gene from the five pedigrees, which included six adult males, a young boy, and four fetuses. One fetus had undergone termination of pregnancy due to hydrocephalus, one was born pre-term at 34+1 weeks of gestation owing to maternal hypertension, and other two were delivered at full term. Follow-up of the survived males revealed no phenotypic manifestations related to language or intellectual impairment. Among these, three adult males underwent the MMSE assessment, all of whom showed normal cognitive function. Search of the gnomAD database suggested the carrier frequency of FGF13 c.-32C>G variant in the East Asian population to be 0.125%, with 11 hemizygous males documented. Three male patients harboring the variant showed severe intellectual disability. Both in vitro and in vivo studies suggested that it could reduce the translation levels of FGF13 protein. Based on the ACMG guidelines, it was classified as variant of uncertain significance (BS4+PS3_Supporting). CONCLUSION: There is insufficient evidence to classify the FGF13 c.-32C>G as a pathogenic variant in clinical practice, and its presence should not be considered an indication for pregnancy termination due to major birth defects.

Adult↗