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PubMed2026

Efficacy of current approaches to non-invasive diagnosis of skin cancer and the potential impact of artificial intelligence: A systematic review and meta-analysis.

BACKGROUND: Skin cancer is one of the most prevalent malignancies worldwide, particularly within Caucasian populations. This systematic review and meta-analysis aimed to quantitatively review the current literature on non-invasive diagnosis of skin cancer and evaluate the current evidence to support the use of tools in addition to, or in replacement of clinician face-to-face assessment. METHODS: A literature search was conducted for publications in PubMed, Medline and Embase databases. Articles describing accuracy, sensitivity, specificity and outcomes of their mode of assessment were included. A total of 208 articles met the inclusion criteria. RESULTS AND CONCLUSION: This systematic review and meta-analysis showed that the diagnostic performance of artificial intelligence (AI) in the interpretation of dermatoscopic images was high for melanoma diagnosis, basal cell carcinoma or malignancy, in comparison to dermatoscopic assessment alone by clinicians and experts. Although AI interpretation of images demonstrated higher sensitivity for melanoma diagnosis in comparison to clinical assessment combined with dermatoscopic assessment, it is unclear if this is also the case for basal cell carcinoma and squamous cell carcinoma diagnosis. Reflectance confocal microscopy, a non-invasive high resolution imaging technique, is known to have a high sensitivity for diagnosing cutaneous malignancy, and this may have applications within secondary care. Therefore, AI could help reduce resource burden and aid in clinical assessment, particularly within primary care settings.

Humans↗

PubMed2026

Urinary Small Extracellular Vesicle DNA as a Biomarker for the Non-Invasive Diagnosis of Bladder Cancer.

Existing diagnostic technologies for bladder cancer (BC) suffer from low sensitivity, low specificity, or a lack of validation. Therefore, validated, non-invasive diagnostic biomarkers with high sensitivity and specificity for early detection of BC are needed to complement and improve upon the limitations of existing diagnostic methods. We used low-pass whole genome sequencing (LP-WGS) technology to detect copy number variations (CNVs) in small extracellular vesicle (sEV) DNA isolated from urine samples of patients. Based on these results, we constructed and validated a diagnostic model to differentiate between benign and malignant bladder lesions. We conducted a receiver operating characteristic analysis and calculated the area under the curve (AUC) to evaluate the performance of the diagnostic model. The urine sEV-DNA LP-WGS data revealed CNV differences between benign and malignant samples. The diagnostic model achieved an AUC of 0.953, a sensitivity of 86.7%, and a specificity of 100% in the training cohort and an AUC of 0.985, a sensitivity of 90%, and a specificity of 100% in the validation cohort. Even at the lowest coverage depth of 0.01X, the performance of the diagnostic model remained relatively robust. Notably, the performance of this diagnostic model surpassed that of the biomarker neuron-specific enolase (sensitivity: 85.7% vs. 64.3%; specificity: 100% vs. 87.5%) and urinary cytology (sensitivity: 100% vs. 66.7%; specificity: 100% vs. 94.1%). Our study demonstrates that urine sEV-DNA exhibits high discriminatory power in distinguishing between benign and malignant bladder lesions, making it a promising tool for auxiliary diagnosis of BC.

Humans↗

PubMed2026

PRDX1 as a novel urinary biomarker for bladder cancer: Development of an integrated fiber optic sensing platform.

In this study, integrated proteomic and transcriptomic analyses identified peroxiredoxin 1 (PRDX1) as a novel urinary biomarker for bladder cancer (BC). PRDX1 was significantly upregulated in BC tissues and was associated with poorer overall survival. In vitro experiments further demonstrated that PRDX1 promotes malignant phenotypes of BC cells, including proliferation, migration, and invasion. Silencing PRDX1 in BC cells significantly reduced the invasiveness and proliferation ability.To address the clinical need for rapid and non-invasive detection, we developed an innovative optical fiber biosensor based on surface plasmon resonance (SPR) technology for the quantitative detection of urinary PRDX1. The biosensor exhibited excellent analytical performance, including high sensitivity (limit of detection: 0.06 ng/mL), a wide linear range (0-25 ng/mL), rapid response (∼14 s), as well as good stability and selectivity. In clinical validation involving 97 BC patients and 30 healthy controls, the biosensor demonstrated outstanding diagnostic performance, with an area under the receiver operating characteristic curve (AUC) of 0.91 and an overall diagnostic accuracy of 86.6%, outperforming conventional enzyme-linked immunosorbent assay (ELISA). Collectively, this study not only identifies PRDX1 as a promising biomarker for non-invasive diagnosis and prognostic evaluation of BC, but also establishes an efficient SPR-based optical fiber sensing platform, providing new insights into both clinical detection and the functional role of PRDX1 in BC progression.

Humans↗

PubMed2026

Exposome influences: a multi-omics perspective on the combined toxic effects of pharmaceuticals and personal care products in Alzheimer's disease.

According to WHO data, approximately 57 million people worldwide were affected by dementia in 2021, with prevalence projected to rise. Alzheimer's disease (AD), responsible for 60%-80% of dementia cases, continues to be a leading cause of mortality, with current treatments offering limited efficacy and disease-modifying therapies lacking widespread adoption or conclusive safety evidence, shifting the focus toward prevention and risk modification. Risk factors for AD include both non-modifiable elements, such as age, genetics, and gender, and modifiable factors, like environmental pollution, health status, and diet. While age remains the primary non-modifiable risk factor, early-onset dementia represents only up to 9% of cases. Addressing modifiable factors is essential, as it could prevent or delay almost half of dementia cases, with interventions-such as increased physical activity, smoking cessation, alcohol limitation, and overall health management-being significantly associated with a reduced risk. In this context, the exposome approach offers a comprehensive, integrative framework in which both modifiable and non-modifiable risk factors interact to influence individual susceptibility. Within the neural exposome, chronic low-dose exposure to xenobiotics-such as industrial chemicals, pesticides, metals, pharmaceuticals and personal care products (PPCPs), and air pollutants-may induce neurodegeneration via mechanisms including oxidative stress, neuroinflammation, proteinopathies, and epigenetic modifications, although establishing causality remains challenging. Integration of genomics, transcriptomics, proteomics, metabolomics, and lipidomics, combined with artificial intelligence (AI) techniques such as machine learning (ML) and deep learning (DL), provides promising avenues for biomarker discovery, enhanced preventive strategies, early non-invasive diagnosis, and therapeutic target identification by integrating multi-layered biological data with exposure profiles. This review highlights emerging AD risk factors-including PPCPs-underscoring complex, multifactorial nature of AD and exposome, and the requirement for an interdisciplinary research approach, while also addressing several critical research gaps and methodological limitations.

Alzheimer’s disease↗

PubMed2026

cfMethDB: A Comprehensive cfDNA Methylation Data Resource for Cancer Biomarkers.

Cancer is a major global health threat, and early detection is crucial for improving patient outcomes. DNA methylation in circulating cell-free DNA (cfDNA) has emerged as a promising biomarker for non-invasive cancer diagnosis. However, the integration and utilization of existing cfDNA methylation data have been limited, hindering comprehensive research efforts, particularly in the discovery of cfDNA methylation biomarkers. To address this challenge, we introduced cfMethDB, a comprehensive database dedicated to cfDNA methylation in cancer that encompasses 4828 publicly available datasets. Through standardized analysis, we identified 1,048,770 differentially methylated cytosines (DMCs) as candidate biomarkers across seven cancer types. With cfMethDB, we not only identified known cfDNA methylation biomarkers, but also discovered several genes, such as ZIC4, that could be novel biomarkers. Moreover, cfMethDB offers a suite of user-friendly tools, including biomarker evaluation, pan-cancer search, and end motif analysis. We hope that cfMethDB will serve as a valuable platform for the discovery of novel cancer cfDNA methylation biomarkers and facilitate cancer research and clinical applications. cfMethDB is publicly available at https://cfmethdb.hzau.edu.cn/home.

Humans↗

PubMed2025

Serum N-glycomics for non-invasive detection of significant liver pathology across clinical phases of treatment-naïve chronic hepatitis B.

BACKGROUND: Early identification of significant liver pathology is crucial for timely antiviral intervention in individuals with chronic hepatitis B (CHB) infection. Current non-invasive methods show limited accuracy in detecting occult liver damage, particularly in those with normal ALT. This study evaluated serum N-glycan profiles for diagnosing significant liver pathology in treatment-naïve CHB patients across clinical phases. METHODS: This cross-sectional study analyzed 626 treatment-naïve CHB patients confirmed by liver biopsy, classified according to 2025 EASL guidelines. Serum N-glycan profiles were determined using DNA sequencer-assisted fluorophore-assisted carbohydrate electrophoresis. Significant liver pathology was defined as inflammation grade ≥ G2 and/or fibrosis stage ≥ S2 (per Scheuer scoring system). Multivariate logistic regression models were developed and compared with traditional non-invasive markers. RESULTS: Among 626 CHB patients, 66.0% had significant inflammation and 58.9% had significant fibrosis. Patients with significant pathology showed characteristic alterations, with elevated P1, P3, P6, P7, P11 peaks and decreased P0, P5, P8, P10 peaks (all p < 0.0001). Compared to respective infection phases, hepatitis phases showed P1 increases of 19.6% and 36% in HBeAg(+) and HBeAg(-) patients, with P11 increases of 82.4% and 73.4%, while P0 decreased by 20.3% and 27.6%, and P10 by 21.6% and 20.3%. Relative to mild pathology (G and S < 2), P1 increased by 27% in significant pathology (G and/or S ≥ 2), reaching 58.7%/48.7% in G4/S4 stages (vs. G0/S0). In ALT-normal HBeAg(+) infection phase, P1 increased by 80.2%/65.8% in G4/S4 stages (vs. G0/S0), with P2 also increasing by 54.1%/45.2%. Multivariate analysis identified P11 as strongest risk factor (OR = 3.84, 95%CI: 1.74-8.45, p = 0.0008), followed by P1 (OR = 2.04, 95%CI: 1.57-2.64, p < 0.0001) and P7 (OR = 1.75, 95%CI: 1.31-2.34, p = 0.0002), while P2 (OR = 0.07, 95%CI: 0.02-0.26, p < 0.0001) and P0 (OR = 0.30, 95%CI: 0.12-0.79, p = 0.0140) served as protective factors. The glycomics combined model (AUC = 0.876 (0.844-0.908)) achieved superior performance and outperformed the clinical model (AUC = 0.818 (0.779-0.857)), LSM (AUC = 0.817 (0.775-0.858)), APRI (AUC = 0.830 (0.792-0.867)), and FIB-4 (AUC = 0.672 (0.621-0.723)) (all p < 0.001), with 78.7% sensitivity and 83.2% specificity. The optimized model reached AUC = 0.917 (0.891-0.942) with accuracy 84.2%, with 78.7% sensitivity and 94.6% specificity. Both glycomics-based models maintained diagnostic capability in ALT-normal patients particularly in HBeAg(+) infection. CONCLUSIONS: Serum N-glycomics demonstrates promising potential for non-invasive identification of significant liver pathology in treatment-naïve CHB patients, providing an alternative approach for early treatment decisions, especially in ALT-normal patients with occult liver damage.

Humans↗

PubMed2026

Lesion-specific oral microbiome signatures and predicted carcinogenic pathways in oral squamous cell carcinoma: a paired-site study in Pakistan.

BACKGROUND: Oral squamous cell carcinoma accounts for over 90% of oral neoplasms. Despite therapeutic advances, the lack of reliable, non-invasive biomarkers and delayed diagnosis continues to impede effective clinical management. By combining paired lesion and non-lesion sampling with predictive metagenomics analysis, our study addresses this gap and advances the current understanding of microbiome‒tumor interactions. METHODS: We analyzed 92 buccal swab samples from 39 OSCC patients and 14 healthy controls using 16S rRNA gene (V3-V4) sequencing. Taxonomic profiling was conducted using QIIME2 and SILVA/eHOMD databases, functional pathways were predicted using PICRUSt2, and hub taxa were identified through co-abundance network analysis. RESULTS: Microbial community structure differed significantly across lesion, non-lesion, and healthy sites (PERMANOVA, p = 0.001). Lesions were enriched with Selenomonas infelix and Treponema vincentii, while healthy controls harbored Streptococcus oralis and Gemella haemolysans. Co-abundance network analysis revealed lesion-specific hub species, notably T. vincentii, strongly correlated with predicted activation of pyrimidine biosynthesis pathways (r = 0.69, q < 1E-6), suggesting predicted metabolic alterations in the tumor microenvironment. Non-lesion sites were also characterized by two hub species, Prevotella melaninogenica and Segatella oulorum. CONCLUSION: Our findings define a lesion-specific microbial signature of OSCC characterized by the depletion of health-associated taxa, enrichment of pro-inflammatory pathobionts, and predicted associations with metabolic pathways implicated in carcinogenesis. These alterations reflect a predicted functionally altered tumor microenvironment.

16S rRNA gene↗

PubMed2026

Diagnostic value of plasma cell-free DNA metagenomic next-generation sequencing in patients with suspected infections and exploration of clinical scenarios-a retrospective study from a single center.

BACKGROUND: Plasma cell-free DNA metagenomic next-generation sequencing (mNGS) is a non-invasive comprehensive method for the etiological diagnosis of various infectious diseases. However, research on the early diagnosis and real-world clinical impact of plasma mNGS in patients with suspected infection are still limited. MATERIALS AND METHODS: This study retrospectively included 140 patients with suspected infections who underwent early plasma mNGS and conventional culture testing. Referring to the clinical diagnosis of infectious diseases, the diagnostic performance of plasma mNGS and culture tests was compared, and the application scenarios and clinical effects of plasma mNGS were evaluated. RESULTS: The positive rate of plasma mNGS was significantly higher than that of culture methods (55.71% vs 25.10%, p < 0.001) and blood cultures (55.71% vs 12.86%, p < 0.001). Regarding clinical diagnosis, the sensitivity of plasma mNGS was significantly higher than that of culture (58.27% vs 37.80%, p = 0.002). The combination of mNGS and culture achieved a higher detection sensitivity (69.29%), especially in patients with multi-site co-infections (73.68%) and blood infections (73.17%). Plasma mNGS demonstrated higher sensitivity in patients with procalcitonin (PCT) index > 5 ng/ml or human neutrophil lipocalin (HNL) index > 200 ng/ml. In terms of treatment, a total of 69 patients (54.33%) benefited from plasma mNGS. CONCLUSION: This study highlights the significant improvement in pathogen detection performance by combining conventional culture with plasma mNGS detection, especially in patients with multi-site co-infections and blood infections. Early use of plasma mNGS as an adjunct to culture can better guide clinicians to initiate appropriate anti-infective therapy.

Humans↗

PubMed2026

Prenatal SNP-array chromosomal microarray analysis in 3,549 pregnancies: indication-specific yields and clinical implications.

BACKGROUND: SNP-based chromosomal microarray analysis (CMA) is widely used in invasive prenatal diagnosis, yet real-world performance across contemporary referral pathways, especially in the NIPT era, remains incompletely characterized. METHODS: We retrospectively analyzed 3,549 prenatal invasive samples tested by SNP array, and evaluated diagnostic yield overall and by referral indication and ultrasound phenotype. RESULTS: In total, we identified 398 pathogenic or likely pathogenic (P/LP) variants across 386 fetuses, resulting in an overall diagnostic yield of 10.9% (386/3,549). These findings comprised 223 aneuploidies and 175 pathogenic CNVs. In contrast, variants of uncertain significance (VOUS) were detected in 12.0% (426/3,549) of cases. Diagnostic yields were heavily stratified by indication: yields peaked in NIPT high-risk referrals (38.9%) and were intermediate in ultrasound-based cases (~ 11%), but dropped significantly in the advanced maternal age (AMA; 4.2%) and serum screening (~ 5-6%) groups. Conversely, VOUS rates remained remarkably stable across all referral categories. Sub-analysis of ultrasound abnormalities revealed that multisystem anomalies conferred the highest risk (27.3%), driven predominantly by aneuploidies; among soft markers, increased nuchal translucency (NT) emerged as the strongest predictor of chromosomal pathology. CONCLUSIONS: In our cohort, SNP-array identified clinically actionable findings in 10.9% of cases. NIPT enriched diagnostic yields, particularly for aneuploidies, and NT thickness was strongly associated with pathogenic findings. These results support an indication-based approach to genomic testing, with NIPT as a triage tool for aneuploidy and CMA for high-risk populations, while improving VOUS counseling.

Humans↗

PubMed2026

Presentation, management, and outcomes of anterior inferior cerebellar artery dissecting and fusiform aneurysms: a systematic review and institutional case series.

Dissecting and fusiform aneurysms of the anterior inferior cerebellar artery (AICA) are rare and poorly characterized lesions. This study provides a comprehensive patient-level synthesis to date, combining a systematic review with institutional data to describe their clinical presentation, diagnostic workup, management strategies, and outcomes. A systematic review was conducted according to PRISMA guidelines. Studies were included if they reported on dissecting or fusiform AICA aneurysms. Individual patient data were extracted and supplemented with a single-institution case series. Outcomes, complications, and radiological evolution were analyzed descriptively. Forty-nine patients from 36 studies and 6 patients from our institution were included in this study. In the systematic review cohort, most aneurysms presented with subarachnoid hemorrhage (n = 38/49, 77.6%). Compressive cranial neuropathies, particularly including the vestibulocochlear system, were common in patients with unruptured aneurysms. Diagnosis often required digital subtraction angiography after the initial non-invasive imaging. Endovascular treatment, most commonly parent artery occlusion, was employed in 61.2% (n = 30/49) of cases. However, ischemic complications occurred in 23.3% (n = 7/30), especially in proximal (A1-A2) lesions. Bypass surgery was reported selectively for proximal aneurysms with inadequate collateral flow. As an alternative surgical approach, decompression or trapping was pursued based on aneurysm morphology or clinical context. Conservative management was typically reserved for select patients with poor-grade SAH, high procedural risk, or patient refusal of intervention. Overall, 81.4% (n = 35/43) of patients with available follow-up achieved good functional outcomes. Management of AICA dissecting and fusiform aneurysms is highly individualized. Endovascular approaches were frequently used to secure ruptured lesions or lesions considered at high risk, but periprocedural ischemic risk in perforator-rich segments remains a notable concern. Bypass procedures were reported in selected proximal aneurysms with limited collateralization. Conservative management was reserved for highly selected high-risk or anatomically inaccessible cases. Clinical trial registration: This study is not a clinical trial.

Humans↗

PubMed2026

Promises and Pitfalls of ctDNA testing in the Management of Cholangiocarcinoma.

Diagnosis and treatment of cholangiocarcinoma is often limited by the availability of tissue biopsies for genomic analysis. Liquid biopsies using blood circulating tumor DNA (ctDNA) have emerged as a valuable and non-invasive alternative to conventional testing. ctDNA analysis has advanced the treatment paradigm for cholangiocarcinoma (CCA) by identifying targetable mutations and molecular mechanisms of treatment resistance. Additionally, it has shown preliminary promise in stratifying patients for adjuvant systemic therapy and enabling earlier detection of relapse. However, current ctDNA platforms face biological and technical challenges that limit their sensitivity for certain mutation types (i.e. gene fusions and amplifications), which are commonly found in CCA. To overcome these hurdles, new sequencing techniques and analytic methods involving artificial intelligence, epigenetic profiling, and diverse reference genomes are being developed. These advanced technologies underscore the promise of ctDNA testing as an indispensable tool in the management and study of CCAs.

Cholangiocarcinoma↗

PubMed2026

Integrated salivary proteomic and metabolomic analyses reveal molecular characterization and novel biomarker panels of chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD) is a respiratory disorder characterized by chronic inflammation, oxidative stress, and metabolic dysregulation. The lack of convenient and easily-accessible non-invasive diagnostic approaches remains a major clinical challenge. This study applied an integrated saliva-based proteomic and untargeted metabolomic strategy to identify potential biomarkers for COPD classification. Comprehensive multi-omics analyses identified 225 differentially abundant proteins and 60 differentially abundant metabolites between patients with COPD and healthy controls, including 24 biologically relevant endogenous metabolites. Functional enrichment analyses revealed pronounced dysregulation of mitochondrial energy metabolism, redox homeostasis, lipid remodeling, and inflammatory-related pathways in COPD. By integrating salivary proteomic and metabolomic biomarkers, a stepwise feature selection combined with LASSO logistic regression was used to construct diagnostic models, yielding an optimized biomarker panel consisting of 11 proteins and 2 endogenous metabolites. This integrated model achieved excellent diagnostic performance, with an area under the ROC curve of 0.96. Collectively, these findings demonstrate that integrated salivary proteomic and metabolomic profiling provides a robust, non-invasive approach for COPD classification and offers a promising foundation for the development of biosensor-based diagnostic platforms and early disease detection. SIGNIFICANCE: Chronic obstructive pulmonary disease (COPD) remains a major global health burden. Current diagnostic approaches rely largely on spirometry and clinical assessment, which are limited in sensitivity for early-stage disease and unsuitable for large-scale screening. This study employs an integrated saliva-based proteomic and metabolomic strategy to identify non-invasive biomarkers for COPD classification. Our findings reveal coordinated dysregulation of mitochondrial energy metabolism, redox homeostasis, and lipid remodeling in COPD, highlighting the interconnected roles of metabolic reprogramming, oxidative stress, and inflammation in disease pathophysiology. Notably, a robust diagnostic panel comprising 11 proteins and 2 endogenous metabolites was established, achieving excellent classification performance (AUC of 0.96). To our knowledge, the integrated application of salivary proteomics and metabolomics for COPD diagnosis remains largely unexplored, underscoring the significance and translational potential of our findings.

Humans↗

PubMed2026

Clinical performance of the urine-based TERT promoter AbsoluteQ Digital PCR for non-invasive detection of bladder cancer.

Bladder cancer (BC) is the ninth most common cancer worldwide, with urothelial carcinoma accounting for approximately 90% of all cases and presenting predominantly as non-muscle-invasive disease. Due to its high recurrence rate and the need for long-term surveillance, BC is associated with the highest lifetime treatment costs per patient among all cancers, making its effective management a significant clinical and economic challenge. The most frequently identified variants in the TERT gene promoter are c.-124C>T (C228T) and c.-146C>T (C250T), located within a region characterized by high guanine-cytosine (GC) content, which makes amplification challenging. We aimed to validate the AbsoluteQ Digital PCR assay for the detection of urine-based TERT promoter variants for the diagnosis of urothelial bladder cancer and to assess its diagnostic performance in comparison with standard methods. Urine samples were collected from patients with histopathologically confirmed bladder cancer (n = 58) and compared with a control group (n = 55). The C228T and C250T variants were tested using the AbsoluteQ Digital PCR assay. Sensitivity, specificity, and predictive values were calculated to evaluate the performance of the assessed method. The AbsoluteQ Digital PCR demonstrated superior diagnostic performance compared to conventional Sanger sequencing for detecting TERT promoter variants, achieving a sensitivity of 89.65% (95% CI: 78.16-95.72) and a specificity of 100% (95% CI: 91.87-100), with no false positives observed. Given its robustness and clinical relevance, AbsoluteQ Digital PCR is emerging as a promising tool for non-invasive molecular diagnostics targeting TERT promoter variants.

Humans↗

PubMed2026

Quantitative susceptibility mapping in neurodegenerative diseases: An umbrella review of iron-related biomarkers and mechanisms.

Pathological iron accumulation is a common pathophysiological hallmark across multiple neurodegenerative diseases (NDDs), motivating the need for accurate, non-invasive quantification methods. Quantitative susceptibility mapping (QSM) is an advanced magnetic resonance imaging (MRI) technique that enables in vivo measurement of tissue magnetic susceptibility (χ), providing a sensitive proxy for iron content. This umbrella review systematically evaluates the diagnostic accuracy, clinical correlations, and distinct iron distribution patterns of QSM in major NDDs, such as Parkinson's disease (PD), Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), and atypical Parkinsonism. We included 15 (13/15 were rated Low or Critically Low on AMSTAR 2) systematic reviews and meta-analyses (through July 15, 2026); however, the findings should be interpreted cautiously because of heterogeneity and the low methodological quality. A Corrected Covered Area (CCA) analysis demonstrated only slight overlap of primary studies across the included reviews (CCA = 5.42%). Collectively, the evidence indicates that QSM provides comparable or higher diagnostic sensitivity and reliability than conventional R2* and SWI techniques, particularly for deep gray matter structures. The findings support significant iron overload in the substantia nigra, particularly in the pars compacta, as a robust biomarker for PD that correlates with motor severity and disease duration. Furthermore, regional iron profiling in the basal ganglia is critical for differential diagnosis; specifically, elevated χ in the putamen and globus pallidus effectively distinguishes multiple system atrophy and progressive supranuclear palsy from idiopathic PD. Distinctively, AD and ALS exhibit specific χ alterations in the thalamus, motor cortex, and hippocampus, reflecting divergent iron-related pathophysiological mechanisms, which correlate with cognitive impairment and upper motor neuron signs. Overall, QSM shows diagnostic promise and offers mechanistic insights into iron-related neurodegenerative processes.

Humans↗

PubMed2025

Identification of maternal Gγ(Aγδβ)0 thalassemia through retrospective reanalysis of prenatal cfDNA sequencing data.

OBJECTIVE: Non-invasive prenatal screening (NIPS) is widely used to detect chromosomal abnormalities such as trisomies 21, 13, and 18 and is also effective in screening for copy number variations (CNVs). However, the routine application of NIPS to detect smaller CNVs within the HBB gene, specifically Gγ(Aγδβ)0 thalassemia, has yet to be well documented. This study aims to evaluate the efficacy of cfDNA-based maternal carrier screening in routine screening for Gγ(Aγδβ)0 thalassemia. METHODS: We performed a retrospective analysis of 107,300 pregnant women who underwent NIPS at Longgang Maternal and Child Healthcare Hospital in Shenzhen from December 2017 to May 2022. Using an improved algorithm, we reanalyzed NIPS data to identify maternal Gγ(Aγδβ)0 thalassemia. Positive cases were confirmed by multiplex ligation-dependent probe amplification (MLPA) using peripheral blood leukocytes. RESULTS: Among the 107,300 NIPS analyses, 38 maternal deletion CNVs within the HBB gene were identified using the improved algorithm, with a prevalence of 0.035% (38/107,300). MLPA confirmed that all detected deletions were consistent with Gγ(Aγδβ)0 thalassemia. The positive predictive value (PPV) for detecting Gγ(Aγδβ)0 thalassemia by cfDNA-based maternal carrier screening was 100%. Among the 38 Gγ(Aγδβ)0 cases, 9 were also associated with α-thalassemia deletions, including 4 cases with -SEA/αα, 4 with -α3.7/αα, and 1 with -α4.2/αα. No cases of homozygosity or compound HBB gene variants were observed. CONCLUSIONS: Gγ(Aγδβ)0 thalassemia is not uncommon in China, and repurposed NIPS methodology for maternal genomic analysis in detecting HBB gene deletions is a reliable method for identifying maternal carriers of this disease.

Humans↗

PubMed2026

Lower urinary tract evaluation in children with cerebral palsy: A crossectional study.

INTRODUCTION: Cerebral palsy (CP) is a chronic, non-progressive motor disorder affecting voluntary movement and posture. Lower urinary tract (LUT) dysfunction is highly prevalent in children with CP. This study aims to evaluate LUT function in children with CP. MATERIAL AND METHODS: This cross-sectional study was conducted at a tertiary care hospital. Patients aged 5-18 years with established CP diagnosis were included. Evaluation included clinical history, physical examination, urinary ultrasonography with post-void residual (PVR) measurement, and urodynamic studies when indicated. Patients were categorized into three groups; group-1 (LUT dysfunction), group-2 (symptomatic), and group-3 (asymptomatic) for analysis. RESULTS: The study included 97 children with CP (41 girls, 56 boys; median age 8 years). Of the patients, 61.8% were ambulatory (GMFCS I-III) and 38.2% were non-ambulatory (GMFCS IV-V). At least one LUT symptom was detected in 75.3% of patients. Incontinence was the most common symptom at 69.1%. Incontinence prevalence was significantly higher in non-ambulatory patients (81.1% vs 61.7%, p = 0.044). Invasive urodynamics was performed in 19 patients, and LUT dysfunction was diagnosed in 89.5% of them (19.3% of the entire population). Prematurity rate was significantly higher in patients with LUT dysfunction (94.1% vs 64.8%, p = 0.017). Binary logistic regression analysis identified elevated PVR as the strongest independent risk factor for LUT dysfunction (OR = 108, p < 0.001). Abnormal urinary frequency (OR = 14.9, p = 0.022) and quadriplegia (OR = 10.3, p = 0.016) were other independent risk factors. ROC analysis determined the optimal cut-off value for PVR as 19 mL (sensitivity 58.82%, specificity 94.92%). In the intergroup analysis, multinomial logistic regression identified elevated PVR as the strongest predictor (Group-1 vs Group-2: OR = 101; Group-1 vs Group-3: OR = 24, both p < 0.003). Lower gestational age was also an independent risk factor in both comparisons (OR = 1.25-1.26, p < 0.020). DISCUSSION: This study demonstrates LUT dysfunction affects 19.3% of children with CP, strongly correlating with motor impairment severity. Elevated PVR emerged as the strongest independent predictor (OR = 108), offering a practical non-invasive screening tool. Our proposed urodynamic criteria achieved 94.7% diagnostic yield, enabling selective evaluation. Limitations include single-center design and cross-sectional methodology without longitudinal follow-up. These findings support integrating systematic urological assessment into standard CP care for early intervention. CONCLUSION: LUT dysfunction prevalence is high in children with CP, and symptom frequency increases with higher GMFCS levels. Elevated PVR is the strongest predictor, with a clinically applicable cut-off value of 19 mL. Particularly in quadriplegic, non-ambulatory, and premature patients, close follow-up and urodynamic evaluation when necessary should be performed with a multidisciplinary approach.

Humans↗

PubMed2026

Novel insights into retinoblastoma: From oncogenic circuitry to precision diagnosis and eye-preserving therapies.

Retinoblastoma (RB) represents the most common primary intraocular malignancy in childhood and stands as a paradigm for translating molecular oncology into precision clinical management. This review synthesizes the comprehensive evolution in the understanding and treatment of RB. First, we deconstruct the intricate oncogenic circuitry that extends far beyond Knudson's classic "two-hit" RB1 inactivation model, describing non-classical MYCN-driven pathogenesis, multi-layered epigenetic reprogramming (including chromatin, RNA and histone changes), and distinct histological subtypes with defined clinical correlates, such as the favorable-prognosis cavitary RB. Single-cell genomics has elucidated the cellular origin from cone precursor cells and intratumoral heterogeneity. Risk stratification has been refined through well-defined classification systems, from the therapy-guiding International Intraocular Retinoblastoma Classification (IIRC) to the comprehensive American Joint Committee on Cancer Tumor-Node-metastasis (AJCC TNM) staging. Furthermore, the diagnostic paradigm has advanced from conventional anatomical imaging to liquid biopsies, enabling non-invasive molecular staging and monitoring via tumor-derived cell-free DNA analysis. Concurrently, the therapeutic landscape has undergone a radical shift, moving from enucleation and external-beam radiotherapy to an era dominated by local sight-preserving strategies. We provide a critical synthesis of the evidence for intravenous chemotherapy and the transformative role of super-selective intra-arterial chemotherapy (IAC), and describe essential randomized controlled trials, technical innovations, and optimized drug regimens. Finally, we explore emerging targeted molecular therapies and future directions. By integrating cutting-edge molecular insights with robust, high-level clinical evidence, this review offers the framework for achieving patient and eye survival as well as vision preservation in children with Retinoblastoma.

Intra-arterial chemotherapy↗

PubMed2026

Machine learning approaches for cancer prognosis and diagnosis via non-coding RNA: a comprehensive review.

Non-coding RNAs (ncRNAs), once considered genomic dark matter, are now established as key regulators of gene expression with widespread roles in cellular homeostasis and disease. In cancer, ncRNA expression is frequently and systematically dysregulated, and many of these molecules circulate in stable, protected form within biofluids, offering a compelling basis for non-invasive or minimally invasive diagnostic strategies. However, their clinical translation remains substantially hindered to date due to biological complexity, technical noise, and high dimensionality inherent to ncRNA expression datasets. In this context, machine learning (ML) has emerged as a powerful analytical tool to address these challenges, enabling the identification of subtle, reproducible ncRNA signatures predictive of diverse malignancies. This review critically evaluates ML-driven frameworks for cancer diagnosis and prognosis across four ncRNA subclasses, namely miRNAs, lncRNAs, circRNAs, and piRNAs, while also acknowledging the biophysical and thermodynamic models that reinforce ncRNA bioinformatics. Despite substantial methodological progress in ML-based cancer diagnosis and prognosis, key challenges persist, including tumor biological heterogeneity, limited multicenter validation, and the lack of widely adopted standardized protocols for preprocessing, normalization, and reporting workflows. Furthermore, many current ML models lack interpretability in biological or clinical context, constraining their translational utility. By synthesizing recent advances and identifying unresolved barriers, this review charts a roadmap for developing a robust, clinically actionable ncRNA biomarker platform for cancer detection. With global cancer incidence projected to exceed 35 million annual cases by 2050, validated ncRNA-ML-driven frameworks hold potential to revolutionize early-stage detection and personalized therapeutic strategies, thereby reducing the escalating socio-economic burden of cancer worldwide.

Humans↗