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PubMed2026

Prenatal exome sequencing of fetuses with central nervous system anomalies based on prenatal ultrasound and magnetic resonance imaging diagnosis: A retrospective cohort study with a systematic review and meta-analysis.

INTRODUCTION: Fetal central nervous system (CNS) abnormalities have diverse etiologies, with genetic factors as a major contributor. Prenatal exome sequencing (ES) is a powerful tool for precise molecular diagnosis of CNS anomalies, but its diagnostic yield varies among studies. This study aimed to evaluate the additional diagnostic yield of prenatal ES compared with chromosomal microarray analysis (CMA) in fetuses with CNS anomalies detected by prenatal imaging. MATERIAL AND METHODS: We collected ES results from fetuses diagnosed with CNS anomalies by prenatal imaging (2019-2024) who had negative results. Subgroup analyses assessed phenotype-specific ES diagnostic yield for associated genes and variants. A systematic review and meta-analysis incorporating our data and published studies further explored the association between phenotype and diagnostic yield. RESULTS: In the cohort study of 219 cases, ES identified pathogenic/likely pathogenic single nucleotide variations in 36 cases (16%). The highest diagnostic yield of ES was in cases with multisystem malformations (25%, 14/55), followed by multiple CNS anomalies (15%, 2/13) and isolated CNS anomalies (13%, 20/151). The most commonly identified isolated CNS anomaly was agenesis of the corpus callosum (31%, 5/16). Neural tube defects with urogenital anomalies were associated with a positive ES finding in 57% (4/7) of cases. The meta-analysis of 989 cases from 22 studies showed a pooled diagnostic yield of ES of 27% (95% CI, 21%-34%). The highest diagnostic yield of ES was in cases of corpus callosum anomalies with facial abnormalities (75%, 8/11) and neural tube defects with urogenital malformations (80%, 12/15). The diagnostic yield of ES for three or more CNS abnormalities was 43% (95% CI, 31%-58%), significantly higher than that for only two abnormalities (10%, 95% CI, 4%-18%). No significant difference in diagnostic yield was found between cases identified by prenatal MRI combined with ultrasound (27%, 95% CI, 20%-36%) and those identified by ultrasound alone (25%, 95% CI, 17%-35%). CONCLUSIONS: ES provided a significantly higher diagnostic yield than CMA for fetal CNS abnormalities, with diagnostic yields varying by phenotype. The systematic review and meta-analysis confirmed that the complexity and combination of malformations are key factors associated with differences in ES diagnostic yield.

Humans↗

PubMed2026

Enhancing Hemoglobin Bart's hydrops fetalis syndrome prevention: a single-tube multiplex real-time PCR assay for the comprehensive detection of four significant α0-thalassemia deletions (--SEA, --THAI, --CR, and --SA) found in Thailand.

BACKGROUND: Hemoglobin (Hb) Bart's hydrops fetalis is a major public health concern in Southeast Asia, particularly in Thailand. Current screening strategies target the two most common α0 -thalassemia deletions (--SEA and --THAI). METHOD: In this study, we developed a single-tube multiplex real-time PCR assay for the simultaneous detection of four clinically relevant α0-thalassemia deletions (--SEA, --THAI, --CR, and --SA). The assay was validated using 538 clinical samples with diverse thalassemia genotypes and compared against conventional gap-PCR as the reference method. Analytical performance, including sensitivity, specificity, and limit of detection (LOD), was evaluated. In addition, clinical utility was assessed in 22 prenatal diagnosis cases at risk of Hb Bart's hydrops fetalis. RESULTS: The study cohort demonstrated substantial genetic heterogeneity, comprising 43 distinct genotypes. The developed assay achieved 100% sensitivity and specificity for all targeted deletions, with complete concordance with gap-PCR results. No cross-reactivity was observed with α+-thalassemia. The assay demonstrated a high analytical sensitivity with a LOD of 9.76 × 10-3 ng per reaction. Whereas in prenatal diagnosis, all 22 fetal genotypes were accurately identified, including five cases of homozygous --SEA and one rare compound heterozygous --SEA/--CR fetus. CONCLUSIONS: This study presents a rapid, accurate, and cost-effective multiplex real-time PCR assay capable of detecting both common and rare α0-thalassemia deletions in a single reaction. The assay demonstrates strong potential for implementation in routine clinical laboratories and large-scale population screening, contributing to improved prevention and control of severe thalassemia syndromes in high-prevalence regions.

Humans↗

PubMed2026

Characteristics of children with ureteroceles presenting for urological evaluation in the modern medical era.

INTRODUCTION: Historically, children with ureteroceles presented symptomatically and were managed surgically. It is unclear if this changed in the modern medical era of prenatal imaging and shared decision making. We aimed to describe the presentation and management of ureteroceles during initial urological evaluation of children in the era of widespread prenatal ultrasonography. PATIENTS AND METHODS: We retrospectively reviewed records of children (<18 years old [yo]) initially evaluated at our center with a ureterocele (2011-2020). We analyzed demographics, renal anatomy, initial presentation for evaluation, and initial management with non-parametric statistics. Febrile urinary tract infections (fUTIs, ≥ 38 °C) were classified as 1) urosepsis (positive urine culture admitted to pediatric intensive care), 2) documented (positive urine culture) or 3) family-reported. RESULTS: We identified 188 children (65% female). Median age at presentation was 1.2 months old (mo) (IQR 18 days-4.4 mo). Antenatally-detected congenital anomalies of the kidney and urinary tract (aCAKUT) were noted in 143 (76%) children with a confirmed postnatal diagnosis of ureterocele. Overall, 129/188 (69%) children presented without symptoms and 59 (31%) presented with symptoms. fUTI was the most common symptomatic presentation (46/188, 24%): urosepsis (6 children), documented (30), and family-reported (10). Children with aCAKUT presented earlier than those without aCAKUT (27 days vs. 1.6 yo, p < 0.0001). They were also less likely to present with symptoms (11% vs. 96%, p < 0.0001), including fUTIs (7% vs. 78%, p < 0.0001). In total, 108 children (57%) were initially managed with transurethral incision, 73 (39%) were observed, and 7 (4%) had reconstructive surgery. Asymptomatic children with aCAKUT (42%) and symptomatic children without aCAKUT (37%) were more likely to be observed than symptomatic children with aCAKUT (7%, p = 0.02). Among 143 children with aCAKUT, those on antibiotic prophylaxis were less likely to present with a history of a fUTI compared to those not on prophylaxis (4/106 vs. 6/37, 4% vs. 16%, p = 0.02). COMMENT: We present a large observational study describing clinical and anatomical characteristics of children presenting with ureteroceles in a medical era of ubiquitous prenatal ultrasonography. Our retrospective study was limited by incomplete documentation of all antenatal ultrasonography and adherence with antibiotic prophylaxis. Long-term clinical outcomes will be the focus of future work. CONCLUSION: In contrast to historical cohorts, most children presented to urologists with asymptomatic ureteroceles diagnosed with aCAKUT. Most children without aCAKUT presented with a fUTI. Overall, 39% of children were initially observed, indicating an increased use of observation in the modern medical era.

Humans↗

PubMed2026

Association between prenatal exposure to tetrachloroethylene and adverse birth outcomes: Systematic review and meta-analysis.

BACKGROUND: Tetrachloroethylene (PCE) is a ubiquitous chlorinated solvent with documented placental transfer. Despite widespread environmental and occupational exposure, no prior systematic review has synthesized evidence on prenatal PCE exposure and adverse birth outcomes. METHODS: We conducted a systematic review and meta-analysis of observational studies. PubMed, Web of Science, PsycINFO, EMBASE, and CINAHL were searched from inception to July 13, 2026. Eligible studies reported associations between prenatal PCE exposure (drinking water or inhalation) and adverse birth outcomes. Study quality was assessed using the Newcastle-Ottawa Scale (NOS) and Agency for Healthcare Research and Quality (AHRQ) criteria. Random-effects meta-analyses were performed using risk ratios (RRs) with 95% confidence intervals (CIs), with Knapp-Hartung adjustments and Paule-Mandel τ2 estimation. RESULTS: Twenty one studies (1987-2023) met inclusion criteria. Prenatal PCE exposure was associated with spontaneous abortion (8 studies; RR = 1.28, 95% CI 1.00-1.63; I2 = 64.2%). Analyses of stillbirth, central nervous system defects, oral clefts, neural tube defects, preterm birth, low birthweight, and small-for-gestational-age (SGA) yielded positive but statistically non-significant pooled estimates. The certainty of evidence ranged from very low to low across outcomes (GRADE). CONCLUSIONS: Prenatal PCE exposure may be associated with spontaneous abortion, particularly at higher exposure levels, and with SGA. Findings support ongoing regulatory efforts to limit PCE in occupational and environmental settings, particularly for pregnant individuals. Future prospective studies with biological monitoring and confounder-adjusted designs are needed.

Tetrachloroethylene↗

PubMed2026

Exploring the dose-response relationship between prenatal exercise and postpartum depression: A systematic review and meta-analysis of randomized controlled trials.

IMPORTANCE: Postpartum depression (PPD) is a hidden and widespread global public health crisis affecting millions of mothers and infants annually. Prenatal exercise is a potentially accessible nonpharmacological strategy for PPD prevention, but its optimal dose remains uncertain. OBJECTIVE: To explore the dose-response relationship between prenatal exercise and the incidence of PPD through meta-analysis of randomized controlled trials (RCTs). DATA SOURCES: Systematic searches were conducted in PubMed, Embase, Web of Science, and Cochrane Library using MeSH terms and keywords related to "pregnant women," "prenatal exercise," and "postpartum depression," up to June 23, 2025. STUDY SELECTION: RCTs included examined prenatal exercise interventions in pregnant women without a history of depression, with PPD incidence reported using validated depression scales (such as EPDS, CES-D). Non-RCT studies, duplicate publications, and studies with insufficient data were excluded. DATA EXTRACTION AND SYNTHESIS: Two researchers independently extracted data according to the PRISMA guidelines. A random-effects model was used to pool odds ratios (OR) and their 95% confidence intervals (CI). Linear and nonlinear dose-response models were employed to analyze and evaluate the relationship between exercise dose (measured in METs-min/week) and the incidence of PPD. MAIN OUTCOME(S) AND MEASURE(S): The primary outcome is the incidence of PPD, analyzing its relationship with prenatal exercise dose. RESULTS: Eight RCTs involving 2231 pregnant women were included. The pooled analysis showed that prenatal exercise was associated with a potential reduction in PPD incidence, although the overall effect did not reach statistical significance (OR=0.58, 95% CI [0.33, 1.02]). In dose-stratified analysis, exercise doses ≥500 METs-min/week were associated with significantly lower PPD incidence (OR=0.44, 95% CI [0.24, 0.78]). Subgroup analyses suggested trends toward greater benefits among women aged ≥30 years and those initiating exercise between 14 and 28 weeks of gestation; however, subgroup differences did not reach statistical significance. The linear dose-response trend did not reach statistical significance (p = 0.0533), and neither the overall spline association (p = 0.1704) nor the test for nonlinearity (p = 0.6361) was statistically significant. CONCLUSIONS AND RELEVANCE: Prenatal exercise may be associated with a lower risk of PPD, but the overall pooled effect did not reach statistical significance. Findings concerning ≥500 METs-min/week and the apparent flattening of the dose-response curve should be considered exploratory and require confirmation in larger trials.

Humans↗

PubMed2026

Prenatal exposure to indoor PM2.5 and children's cognitive performance at 4 years of age: an observational analysis from the UGAAR randomized controlled trial.

Outdoor fine particulate matter (PM2.5) concentrations during pregnancy are linked to reduced cognitive performance in children. We previously reported that portable HEPA filter air cleaners use during pregnancy improved children's mean full-scale IQ (FSIQ), but no previous studies have evaluated the relationship between indoor PM2.5 during pregnancy and FSIQ in childhood. We conducted an observational analysis using data from the Ulaanbaatar Gestation and Air Pollution Research (UGAAR) randomized controlled trial. Using a previously developed model of weekly indoor PM2.5 concentrations, we estimated the average concentrations in participants' homes over the full pregnancy and in each trimester. When the children were four years old, we measured FSIQ using the Wechsler Preschool and Primary Scale of Intelligence (WPPSI-IV). We used multiple linear regression to assess the adjusted relationships between interquartile range (IQR) contrasts in indoor PM2.5 during pregnancy and FSIQ among 475 mother-child dyads. An 8.8 μg/m3 increase in indoor PM2.5 concentration over the full pregnancy was associated with a reduction of 1.4 points (95% CI: -3.4, 0.6) in mean FSIQ. The strongest association between PM2.5 concentrations and FSIQ was in the first trimester, when a 19.1 μg/m3 contrast was associated with a 2.8-point reduction (95% CI: -5.7, 0.2) in mean FSIQ. Indoor PM2.5, particularly during early pregnancy, may impair brain development, leading to lower mean FSIQ scores in four-year old children. These results, combined with our previous analysis of HEPA filter air cleaners, indicate that reducing PM2.5 exposure during pregnancy has beneficial effects on children's cognitive performance.

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PubMed2026

The association between prenatal PM2.5 constituent exposure and gestational diabetes mellitus: Exploratory analysis of the potential modifying role of thyroid hormones.

The associations of PM2.5 constituents with blood glucose and GDM remain unclear, and the interplay between PM2.5 exposure and thyroid hormone levels in relation to GDM has not been well characterized. This retrospective cohort study included 1314 pregnant women with data collected through multiple methods. A generalized linear model analyzed PM2.5-glucose links, logistic regression assessed pollutant-GDM associations, and stratified analyses explored these relationships at different thyroid hormone levels. In the study population, first-trimester exposure to SO42- and BC correlated positively with FBG, as did PM2.5 and its components in the second trimester. First-trimester SO4²⁻ exposure (OR=1.26, 95% CI: 1.06, 1.51) and second-trimester exposures to PM2.5 (OR=1.67, 95% CI: 1.19, 2.35), NO3⁻ (OR=1.34, 95% CI: 1.06, 1.68), and NH4⁺ (OR=1.33, 95% CI: 1.06, 1.65) were associated with increased GDM risk. Stratified analyses showed that second-trimester BC and OM were positively correlated with FBG in the high-TSH and low-FT4 strata, respectively. In addition, first-trimester exposure to SO42- (high TSH: OR = 1.42, 95% CI: 1.10, 1.84; low FT4: OR = 1.35, 95% CI: 1.05, 1.74) and to PM2.5 (high TSH: OR = 1.93, 95% CI: 1.14, 3.27; low FT4: OR = 1.82, 95% CI: 1.46, 2.25) in the second trimester were associated with higher odds of GDM. These findings show that PM2.5 exposure was associated with glucose dysregulation and GDM in pregnant women differently by trimester and component. Across the separate TSH- and FT4-stratified analyses, women in the high-TSH and low-FT4 strata, respectively, appeared to show greater susceptibility to air pollution-related GDM. These subgroup findings should therefore be interpreted as exploratory and require validation in future studies.

Effect modification↗

PubMed2026

Perinatal depression, maternal thyroid status and fetus/infant health and development: A systematic review.

BACKGROUND: Thyroid hormones are known to influence both maternal depression and child developmental outcomes, while maternal depression independently affects child outcomes. The potential interaction between thyroid dysfunction and depression in shaping child development remains insufficiently explored. The present study addresses such interplay. METHODS: Following PRISMA 2020 and JBI guidelines, three databases were searched through December 2025 for primary studies on maternal thyroid status, perinatal depression, and child development. Risk of bias (RoB) was assessed using validated tools. Due to clinical and methodological heterogeneity, data were synthesized narratively following SWiM guidelines. RESULTS: Eleven studies were included. Beyond independent risks for preterm birth and behavioral problems, limited evidence supports a synergistic model, while most studies likely reflect the simple co-occurrence of risks. Maternal thyroid peroxidase antibodies (TPO-Ab) were associated with child externalizing problems exclusively in the presence of clinical depression. High depressive symptoms also attenuated the cognitive benefits of prenatal iodine supplementation. Thyroid status appears to function as a risk moderator rather than a mediator. However, 50% of observational studies presented high RoB, primarily due to participant attrition. CONCLUSION: Findings are still scarce to support a synergistic risk model where specific maternal thyroid parameters (i.e. thyroid autoimmunity and iodine status) may moderate the impact of depressive symptoms on child development. Despite the high RoB in half of the studies, results highlight the need for integrated screening protocols. Simultaneously assessing mental health and thyroid status may optimize risk stratification for high-risk mother-infant dyads.

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PubMed2026

Integrated multi-omics profiling of amniotic fluid identifies predictive biomarkers for fetal growth restriction trajectories.

BACKGROUND: Fetal growth restriction (FGR) is a complex condition with highly heterogeneous clinical outcomes, making prenatal distinction between transient and persistent growth failure challenging. This study aims to identify amniotic fluid (AF) biomarkers capable of differentiating distinct FGR trajectories and characterizing persistent growth failure mechanisms. METHODS: Integrated proteomic and metabolomic profiling was performed on AF samples from transient FGR (n = 11), persistent FGR (n = 9), and healthy controls (n = 13). Diagnostic and prognostic models were developed using multivariate analysis. Selected protein candidates were validated via ELISA in an independent cohort (n = 69). RESULTS: Multi-omics analysis revealed distinct molecular signatures for FGR stratification. A two-protein diagnostic panel (PDGFA and phospho-STAT5A) achieved an AUC of 1.000 in the discovery stage and 0.780 in the external validation cohort. For prognostic assessment, a molecular signature including IREB2, HLA-C, and PLXNB2 accurately predicted persistent growth failure from transient recovery (AUC = 0.966). Cross-platform integration highlighted the mass spectrometry-derived WASHC2C as a central hub protein with a significant progressive increase across the control, transient, and persistent groups (p < 0.001). CONCLUSIONS: This study establishes a multi-omics framework for prenatal FGR stratification. Our findings identify distinct molecular signatures reflecting the intrauterine environment and provide high-performance molecular tools for predicting divergent fetal growth trajectories to guide personalized clinical decision-making.

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PubMed2026

The Childhood Cancer and Leukemia International Consortium (CLIC): Expanding global collaboration in pediatric cancer etiology research.

Childhood cancers are rare, but incidence has risen modestly in countries with robust registration, partly reflecting improved diagnosis. In high-income countries, cancer is the leading cause of disease-related death in children. Marked inequities in incidence, survival, and research capacity underscore the need for large-scale collaboration to identify environmental, genetic, and contextual determinants of risk. The Childhood Cancer and Leukemia International Consortium (CLIC) was established in 2007 to study the etiology of childhood leukemia and later expanded in 2019 to include other childhood cancers, principally solid tumors. CLIC pools harmonized, individual-level data from case-control and cohort studies, obtained through interviews, record linkage (insurance claims, registries), or geographic information systems, and integrates germline genomic data where available. Membership has grown from 13 studies in 9 countries to 57 studies in 21 countries; recruitment spans the early 1960s to the present and encompasses approximately 150,000 cases across all tumor types and 300,000 controls with clinical, demographic, and exposure data, centralized via harmonized data dictionaries at the Data Coordination Center, established in 2014 at the International Agency for Research on Cancer, and supported by a secure analysis platform. Pooled analyses across diverse populations have implicated parental age, prenatal vitamin or folic acid use, mode of delivery, fetal growth, selected congenital anomalies, occupational or household exposures (e.g., pesticides), paternal smoking, and markers of early-life immune modulation (e.g., breastfeeding, daycare attendance) in leukemia risk, informing carcinogen evaluation and prevention. The integration of genetic ancestry and germline susceptibility data is clarifying ancestry-related differences in leukemia biology and outcomes, while confirming risk loci with population-specific effects. CLIC is now adding polygenic risk scores and exposomic data to refine etiologic subtyping and identify modifiable pathways, while broadening representation from underserved regions through partnership-building and capacity-strengthening.

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PubMed2026

Analysis of deep learning techniques in computer-aided diagnosis for meniscus injuries: a systematic literature review.

Meniscus informatics is a growing subject of study in the healthcare industry. One of the major hindrances to the healthcare system's transformation is obtaining knowledge and meaningful information from complicated, high-dimensional and diverse sources. Modern biomedical research, for instance, has seen an increase in the use of complex, dissimilar, poorly documented, and generally unstructured electronic health records, imaging, sensor data and text, even after many current techniques have been used to extract more robust and useful elements from the data for analysis. New efficient standards for building end-to-end learning models from complex data are therefore needed. Therefore, the current study aims to examine the most recent research on the use of deep learning techniques for diagnosing meniscus tears and recommend creating comprehensive and meaningful interpretable structures that might benefit the healthcare industry. We also draw attention to shortcomings and the need for better technique development, and we provide new perspectives about this exciting new development in the field.

Humans↗

PubMed2026

Sitosterolemia: evolving strategies for earlier diagnosis.

PURPOSE OF REVIEW: Sitosterolemia is a rare autosomal recessive lipid disorder caused by biallelic pathogenic variants in ABCG5 or ABCG8 , resulting in excessive intestinal absorption and impaired biliary excretion of plant sterols. Although historically considered exceptionally rare, recent genetic studies suggest the disorder is substantially underdiagnosed, with marked phenotypic heterogeneity ranging from xanthomas and premature atherosclerosis to hematologic abnormalities, and frequently mimics familial hypercholesterolemia. This review summarizes recent advances in the clinical, biological, and genetic diagnosis of sitosterolemia, with a focus on strategies that may facilitate earlier detection. RECENT FINDINGS: Phytosterol quantification, particularly sitosterol, campesterol, and stigmasterol, remains indispensable for accurate diagnosis. Hematologic abnormalities, including hemolytic anemia, stomatocytosis, and macrothrombocytopenia, are increasingly recognized as valuable diagnostic clues complementing the biochemical approach. Expanded variant catalogs for ABCG5/ABCG8 and genome-wide association studies have revealed potentially polygenic contributions to phytosterol metabolism extending beyond these two genes. However, no specific guidelines have yet been established for cascade screening. SUMMARY: Earlier diagnosis requires integration of clinical, biochemical, hematologic, and genetic data. Plasma phytosterol measurement remains the diagnostic cornerstone. Improved disease awareness, broader access to sterol testing, and expanded genetic screening may reduce diagnostic delays and enable timely management, including ezetimibe and dietary phytosterol restriction.

Humans↗

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

Combining neuromelanin-sensitive MRI and quantitative susceptibility mapping for enhanced diagnosis and differentiation of parkinson's disease: A systematic review.

BACKGROUND: Loss of dopaminergic neurones and iron deposition in the substantia nigra pars compacta (SNpc) are two major pathological hallmarks of Parkinson's disease (PD). Such changes can be visualised by advanced techniques including neuromelanin-sensitive MRI (NM-MRI) and quantitative susceptibility mapping (QSM). This systematic review investigates the diagnostic performance and methodological development of the integrated use of NM-MRI and QSM in PD. METHODS: The systematic search was performed in four databases (Scopus, PubMed, ScienceDirect, and Web of Science) according to the PRISMA 2020 guidelines until July 2026. Bias was assessed using QUADAS-2 and certainty of evidence was assessed using GRADE. RESULTS: Seventeen studies with 2228 participants were included. Combined NM-MRI and QSM consistently showed reduced neuromelanin volume/contrast and increased iron deposition in the SNpc of PD patients compared to healthy controls. Multimodal integration yielded a significant improvement in diagnostic accuracy (AUC values 0.86-0.99), and was able to successfully differentiate PD. Recent methodological advances included simultaneous acquisition sequences (e.g. MTC-GRE, STAGE, setMag) and AI-driven automated segmentation, which led to significantly reduced scan times and improved reproducibility. CONCLUSION: The combination of NM-MRI and QSM has a synergistic effect and provides powerful complementary biomarkers for the diagnosis and differential diagnosis of PD.

Humans↗

PubMed2026

Non-motor symptoms and healthcare utilization before diagnosis of myasthenia gravis: a nationwide cohort study.

BACKGROUND: Non-motor symptoms have been reported prior to myasthenia gravis (MG) diagnosis. However, the temporal patterns of non-motor symptoms and healthcare utilization before MG diagnosis remain unclear. METHODS: We conducted a retrospective, population-based cohort study using the Korean National Health Insurance Service (KNHIS) database from 2011 to 2021. Incident MG cases were identified using the International Classification of Diseases, Tenth and Rare Intractable Disease codes. Individuals younger than 20  years or with missing health screening data were excluded. Each MG case was matched 1:10 by age, sex, and index date to controls. Non-motor symptoms and healthcare utilization were defined using operational criteria derived from KNHIS claims data. Rate ratios (RRs) and 95 % confidence intervals (CIs) were estimated across four prespecified intervals (0-1, 1-2, 2-5, and 5-10  years) before MG diagnosis. RESULTS: We included 8,355 MG patients and 83,550 controls (mean age, 53.7  years; male, 44 %). MG patients had higher rates of any non-motor symptoms over 10  years(RR 1.34; 95 % CI 1.30-1.39), with the sharpest increase in the year before diagnosis. Depression, anxiety, migraine, constipation, and insomnia consistently showed higher RRs across all intervals. Hospitalizations (RR 1.66; 95 % CI 1.61-1.71) and outpatient clinic visits (RR 1.10; 95 % CI 1.04-1.17) were consistently higher across 10  years, peaking during the 0-1 year before MG diagnosis. CONCLUSION: Non-motor symptoms and healthcare utilization increased years before MG diagnosis. Earlier recognition of these symptom patterns may facilitate timelier evaluation for MG and improve diagnostic pathways.

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PubMed2026

Applications of quantum AI in brain disorder diagnosis: A systematic review.

BACKGROUND AND OBJECTIVE: Brain disorder diagnosis and prediction remain challenging because neuroimaging, electrophysiological, behavioral, and multimodal data are high-dimensional, noisy, heterogeneous, and limited by small clinical cohorts. This systematic review synthesised applications of quantum artificial intelligence (QAI) for brain disorder diagnosis, prediction, detection, and monitoring. METHODS: Following PRISMA guidelines, studies published from 2016 to 13 January 2026 were retrieved from Scopus, Web of Science, and IEEE Xplore. After screening, 36 studies met the eligibility criteria and were qualitatively analysed according to disorder category, data modality, QAI method, implementation setting, validation strategy, and performance. RESULTS: At the broader disease-group level, neurodegenerative disorders were the most frequently investigated, followed by mental health and psychiatric disorders. At the individual level, Parkinson's disease and schizophrenia were the leading applications, followed by depression, anxiety, Alzheimer's disease, and stress-related tasks. MRI-based modalities were the most frequently used data source, followed by multimodal data and EEG. Methodologically, primary QAI approaches were dominated by quantum neural and QDL architectures, followed by quantum-inspired optimization or feature-selection methods and quantum-kernel/conventional QML classifiers. Qiskit/IBM Quantum and PennyLane were the most frequently reported quantum software frameworks. However, most studies relied on simulators, classical quantum-inspired implementations, or unclear implementation settings, with limited real-hardware evaluation. CONCLUSIONS: QAI shows emerging potential for brain disorder analysis, particularly through hybrid quantum-classical learning, quantum neural architectures, quantum-kernel methods, and quantum-inspired optimization. Nevertheless, current evidence remains preliminary and requires larger datasets, subject-level and external validation, fair classical benchmarking, noise-resilient circuits, real quantum hardware evaluation, explainability, and clinical validation.

Humans↗

PubMed2026

Early infantile developmental and epileptic encephalopathy: clinical spectrum, diagnosis, outcomes, and evolving treatment strategies.

Early infantile developmental and epileptic encephalopathy (EIDEE) is among the most severe epilepsy syndromes, with onset before three months of age and an estimated incidence of approximately 10 per 100,000 live births. The 2022 International League Against Epilepsy classification unified the historically distinct Ohtahara syndrome and early myoclonic encephalopathy under a single diagnostic framework defined by frequent drug-resistant tonic and/or myoclonic seizures, an abnormal neurological examination, and an abnormal interictal electroencephalogram-most characteristically a burst-suppression pattern. This narrative review synthesizes the clinical, electrophysiological, neuroimaging, genetic, and therapeutic literature within the EIDEE framework. The clinical phenotype is characterized by central hypotonia, postnatal microcephaly, cortical visual impairment, and age-dependent syndromic evolution toward infantile epileptic spasms syndrome or Lennox-Gastaut syndrome in the majority of patients. Electroencephalography remains essential for syndromic classification, while systematic metabolic screening and early trio whole-exome or whole-genome sequencing are central to the etiologic workup, achieving diagnostic yields of 60-65%. The most commonly identified genetic causes include STXBP1, KCNQ2, and SCN2A variants. Outcomes are poor overall and strongly etiology-dependent: vitamin-responsive disorders carry a substantially more favorable prognosis, whereas mortality reaches 25% in genetic cohorts. Genotype-guided pharmacotherapy is now applicable to a clinically meaningful subset of patients, with sodium channel blockers, potassium channel openers, and emerging antisense oligonucleotide therapies representing important therapeutic advances. Gene therapy trials are underway but have encountered early safety signals, underscoring the vulnerability of this population. Critical unmet needs include earlier molecular diagnosis, precision therapies targeting developmental outcomes beyond seizure control, and prospective international registries to characterize the long-term natural history of EIDEE.

Humans↗

PubMed2026

Journey Mapping of the Patient Experience from Diagnosis to End of Life in Lung Cancer: A Qualitative Meta-Synthesis.

OBJECTIVES: This study aimed to systematically synthesize the lived experiences and journey narratives of lung cancer patients across disease stages, and identify key tasks and pain points during the disease course through patient journey mapping, providing evidence for comprehensive disease management throughout the patient journey. METHODS: Ten databases, including PubMed, Embase, Web of Science, Scopus, PsycINFO, CINAHL, Cochrane Library, CNKI, Wanfang, and SinoMed, were systematically searched, with a search period from database inception to August 15, 2025. The JBI Critical Appraisal Tool for qualitative studies was used to evaluate the quality of studies, and the results were integrated using a meta-aggregative approach. RESULTS: Thirteen studies were included. Based on the patient journey mapping, the lung cancer patient journey comprises four potential stages: evaluation and diagnosis, initial treatment, maintenance therapy, and end-of-life. A total of 30 themes emerged within three dimensions: tasks, emotions, and pain points. Each dimension of each stage consists of 2-3 themes. CONCLUSION: The journey of lung cancer patients is protracted and complex, characterized by stage-specific needs and challenges. Future management strategies should be tailored to these distinct phases, providing precision supportive care to optimize treatment outcomes and enhance patients' quality of life. IMPLICATIONS FOR NURSING PRACTICE: This Patient Journey Map integrates routine clinical pathways with patients' lived experiences across each stage, revealing stage-specific challenges and providing targets for tailored nursing interventions. The framework promotes multidisciplinary, digitally enabled supportive care and indicates the importance of including patients' social circles to enhance patient-centered outcomes.

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