MIRAGE syndrome is a multisystemic disorder with a poor prognosis, caused by gain-of-function mutations in the SAMD9 gene. To date, no comprehensive reports on the systemic manifestations and management of MIRAGE syndrome in adult survivors. Here, we present the case of a 22-year-old man long-term survivor of MIRAGE syndrome with a wide range of clinical presentations and complications. From the neonatal period, he exhibited the core features of MIRAGE syndrome: myelodysplasia, recurrent infection, growth retardation, adrenal hypoplasia, atypical external genitalia, and enteropathy. Additionally, brain imaging at 5 years of age revealed new findings, including basal ganglia and white matter lesions, calcification, infarction, and ventricular enlargement. Subsequently, proteinuria was detected at 6 years of age, which gradually progressed to end-stage renal disease. At 21 years of age, he received a living-donor kidney transplant from his father, the first transplant reported for this syndrome. Genetic analysis identified a congenital SAMD9 mutation (p.Gln1286Lys) and three acquired reversion mutations. These revision mutations mitigated his hematologic complications but did not fully restore immune function. In addition to persistent immunological and endocrine dysfunction, the patient has developed progressive neurological and metabolic abnormalities over time. Multidisciplinary management, including prophylactic intravenous immunoglobulin therapy, renal replacement therapy and transplantation, and endocrine support, was provided and may have contributed to his long-term survival. This case highlights the evolving clinical spectrum of MIRAGE syndrome and underscores the importance of careful longitudinal monitoring for patients who survive beyond early childhood.
MIRAGE syndrome, a rare autosomal dominant disorder, is caused by heterozygous gain-of-function mutations in the SAMD9 gene. A key characteristic of MIRAGE syndrome is growth restriction. Although initially thought to stem mainly from prenatal and systemic factors, this growth restriction can also be a consequence of panhypopituitarism, leading to growth hormone deficiency (GHD). The use of recombinant human growth hormone (rhGH) to treat the characteristic severe growth failure is controversial due to an inherent risk of myelodysplastic syndrome (MDS) and acute myeloid leukemia. We report an 11-year-old male diagnosed with MIRAGE syndrome confirmed by a heterozygous de novo SAMD9 variant (c.4615T>A; p.Leu1539Ile) who had previously undergone allogeneic hematopoietic stem cell transplantation for MDS with monosomy 7. Severe pre- and postnatal growth restriction, characterized by short stature and slow growth velocity, marked the clinical course. Comprehensive hormonal testing was performed and ultimately revealed a growth hormone deficiency (GHD). At age 6, growth hormone therapy began after a brain MRI to assess the pituitary gland anatomy. This decision followed a comprehensive risk-benefit analysis and a hematological evaluation that showed no signs of clonal evolution. Over a six-year follow-up period, the patient demonstrated a significant improvement in growth velocity and height standard deviation score, with stable hematological parameters and no adverse events. This case expands the known endocrine phenotype of MIRAGE syndrome, providing the first report, to our knowledge, of a favorable and safe medium-term response to rhGH therapy in this condition. Our observations support systematic GH stimulation testing in MIRAGE patients with marked growth failure who survive beyond early childhood and suggest that, in carefully selected cases with proven GHD, rhGH replacement may be considered in close collaboration with hematology/oncology teams and under strict hematological monitoring.
MIRAGE syndrome is a severe congenital disease affecting multiple systems, caused by functional variants in the SAMD9 gene. It is characterized by myelodysplasia, infections, growth restriction, adrenal hypoplasia, genital phenotypes, and enteropathy. There are few reports of neonatal MIRAGE syndrome. This study presents a rare case of 46,XY karyotype with distinct female external genitalia phenotype and provides a comprehensive literature review of infants under 1 year of age diagnosed with MIRAGE syndrome caused by SAMD9 gene mutations. This article reports a sporadic case of neonatal MIRAGE syndrome confirmed by genetic diagnosis. The patient had a 46, XY karyotype and presented predominantly with female external genitalia, along with preterm birth, respiratory distress, growth restriction, recurrent infections, skin pigmentation, feeding difficulties, thrombocytopenia, anemia, and other manifestations. In clinical practice, when encountering newborns with unexplained premature birth, growth restriction, thrombocytopenia, recurrent infections, and a karyotype of 46, XY but with female or ambiguous external genitalia, clinicians can, based on the experience from this case, differentiate from MIRAGE syndrome and may further perform genetic testing to clarify the etiology.
MIRAGE syndrome is an autosomal-dominant genetic disease primarily caused by a de novo mutation in the gene SAMD9 gene. This study is aimed at investigating the pathogenesis of MIRAGE syndrome through a Chinese case exhibiting intrauterine growth retardation and renal hypoplasia. We performed clinical exome sequencing to identify the pathogenic loci in the family. Further functional studies were conducted to understand the impact of the identified mutation. We identified a de novo mutation in SAMD9 that causes MIRAGE syndrome: c.2423A>G p.(Tyr808Cys). This mutation was associated with a novel phenotypic combination of intrauterine growth retardation and renal hypoplasia in a fetus. In vitro functional experiments demonstrated that the SAMD9 mutation reduced its levels of mRNA and protein. This study expands the pathogenic mutation spectrum of MIRAGE syndrome and provides new insights into its pathogenic mechanism. The identified mutation in SAMD9 provides a potential target for understanding and treating this complex disease.
High myopia (HM) is a complex condition influenced by both genetic and environmental factors, yet its early prediction and clinical intervention remain challenging due to heterogeneous progression patterns. To support early identification of individuals at risk for HM, we developed MIRAGE, a deep learning framework combining exome-wide genotypes with fundus images for personalized prediction. The model combines DeepExGRS for genetic risk modeling and a convolutional network for imaging, fused via a gating attention mechanism. Applied to a cohort of 1991 individuals, MIRAGE achieved high predictive accuracy (AUC = 0.963), outperforming unimodal models. Interpretation using Integrated Gradients and Shapley values identified key genes (e.g. GJD2, FGF1) and image regions (optic disc, macula) contributing to predictions. Further, deep learning-based genetic risk models (DeepcvGRS and DeeprvGRS) outperformed traditional polygenic risk scores, capturing nonlinear interactions and improving HM prediction. Interaction analysis using Shapley interaction scores revealed 314 significant gene-gene interactions, including biologically relevant pairs such as PRSS56-GLI3 and SEMA4D-FRY. Overall, MIRAGE offers a scalable, interpretable, and accurate approach for HM risk stratification, paving the way to early intervention guided by both genetics and retinal imaging.
To be useful for downstream applications, vision decoding models that are trained to reconstruct seen images from human brain activity must be able to generalize to internally generated visual representations, i.e., mental images. In an analysis of the recently released NSD-Imagery dataset, we demonstrated that while some modern vision decoders can perform quite well on mental image reconstruction, some fail, and that state-of-the-art (SOTA) performance on seen image reconstruction is no guarantee of SOTA performance on mental image reconstruction. Motivated by these findings, we developed MIRAGE, a method explicitly designed to train on vision datasets and cross-decode mental images from brain activity. MIRAGE employs a linear backbone and multi-modal text and image features as input to a diffusion model. Feature metrics and human raters establish MIRAGE as SOTA for mental image reconstruction on the NSD-Imagery benchmark. With ablation analysis we show that mental image reconstruction works best when decoders use image features with relatively few dimensions and include guidance from text-based and both high- and low-level image-based features. Our work indicates that-given the right architecture-existing large-scale datasets using external stimuli are viable training data for decoding mental images, and warrant optimism about the future success and utility of mental image reconstruction.
To characterize the immune and molecular abnormalities underlying MIRAGE syndrome by profiling peripheral blood transcriptomes and assessing immune cell composition and function in affected patients. We performed RNA sequencing on peripheral whole-blood samples collected from identical twins diagnosed with MIRAGE syndrome and their healthy parents. Bulk RNA-seq data were subsequently deconvoluted to assess the composition, state, and functional characteristics of immune cell populations. Differentially expressed genes between patients and healthy parents were significantly enriched in the PI3K-Akt signaling pathway, B-cell receptor signaling pathway, and primary immunodeficiency-related pathways. Patients exhibited reduced proportions of memory and naïve B cells, accompanied by increased proportions of CD8 T cells and M2 macrophages. We further identified the top 10 hub genes, which showed moderate to strong correlations with B-cell differentiation, proliferation, and activation. Immune cell dysregulation is evident in patients with MIRAGE syndrome, with B-cell abnormalities representing a prominent immunological feature.
MIRAGE syndrome, an acronym for myelodysplasia, infections, restriction of growth, adrenal hypoplasia, genital abnormalities, and enteropathy, is a multisystem genetic condition due to variants in sterile alpha motif domain-containing protein 9. Neurodevelopmental features are infrequently documented with this condition. Informed consent was obtained from families. A retrospective chart review was done to document the phenotype. A literature review was done to identify neurodevelopmental features and causes of death that have been documented. Three individuals with MIRAGE syndrome were included. A spectrum of neurological features were seen including hypotonia, seizures, cerebral and cerebellar hypoplasia, lenticulostriate vasculopathy, and ventriculomegaly, as well as early death from noninfectious processes. Additionally, we report a case of malignant hyperthermia. This report expands on the neurological phenotype and supports the need for further research to understand the neuropathologic process to provide more informed prognostic information to families.
The etiology of the improved long-term sexual function seen following MRI-guided stereotactic body radiotherapy (SBRT) with aggressive margin reduction for prostate cancer remains unknown. To investigate potential explanatory mechanisms for this finding, we conducted a secondary analysis of data collected for the prospective, randomized phase III MIRAGE trial. Dosimetric data for the structures hypothesized to drive sexual function decline (neurovascular bundles (NVB) and internal pudendal arteries (IPA)) were retrospectively collected and analyzed for correlations with treatment arm or clinically significant sexual function decline as measured by patient reported outcome (PRO) surveys focused on sexual function, namely the EPIC26-SF and SHIM scores. One-hundred-and-seventeen participants from the MIRAGE trial (CT-arm: 58, MRI-arm: 59), corresponding to 75 % of the overall cohort, had complete sexual function PRO survey responses at 24 months. Baseline SHIM score was slightly higher in the MRI arm although EPIC26-SF was the same. No significant differences were noted in treatment characteristics (such as hydrogel spacer, GTV boost, or ADT use) between the study arms. Patients in the MRI group were noted to have significantly lower V36Gy and V20Gy for the NVBs and IPAs. Maximum dose to the right NVB was associated with increased likelihood of sexual function decline (p < 0.05). Although this analysis is limited in its exploratory nature, the data suggest that the unintentional sparing effect of aggressive margin reduction may be associated with a reduction in volume of the NVBs and IPAs receiving intermediate- or low-dose radiation. This, in turn, could explain the reduced rates of sexual function decline experienced by patients receiving MRgSBRT.
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Cystic nephroma (CN) is an uncommon benign pediatric renal neoplasm composed of multiloculated cysts separated by fibrous septa, lacking solid or blastemal elements. It occurs primarily in toddlers, often presenting as an asymptomatic abdominal mass. CN lies at the benign end of the spectrum that includes cystic partially differentiated nephroblastoma (CPDN) and Wilms tumor. We report a case of pediatric CN with detailed imaging and clinical correlation to highlight its distinguishing features. In this report, we present a case of a one-year-old boy who presented with a three-month history of a left-sided abdominal mass. Ultrasound showed a well-circumscribed multicystic lesion at the left kidney's lower pole, composed of anechoic loculi with thin septa (no solid component or vascularity). Contrast-enhanced CT confirmed a large (≈11 × 9 × 8 cm) encapsulated multiloculated cystic mass arising from the left kidney's lower pole, with enhancing thin septa and herniation of cysts into the pelvicalyceal system; no enhancing nodules or calcifications were seen. The patient underwent left nephroureterectomy; grossly, the specimen showed numerous clear-fluid cysts separated by fibrous septa. Microscopically, cysts were lined by flattened-cuboidal epithelium with focal hobnail change, and fibrous septa contained only mature stroma and inflammation, with no blastema or immature elements - consistent with CN (resection margins and sampled lymph nodes were free of tumor).
Both venous excess ultrasound (VExUS) and central venous pressure (CVP) can assess venous congestion from different perspectives. CVP provides continuous and simple monitoring of the risk of congestion and is easily repeatable in patients with a central venous catheter. In contrast, VExUS offers an intermittent, organ-level evaluation of established congestion and may help identify the venous waterfall phenomenon. Furthermore, assessment of pulmonary congestion should not be overlooked.
As the most important equipment in the power system, the operation state of the transformer directly affects the stability and safety of the power grid. Once the transformer has a DC magnetic bias fault, it will lead to problems such as excessive temperature, increased vibration, and excitation current distortion. To quantitatively classify the DC magnetic bias degree of power transformers, this paper proposes a classification method based on a probabilistic neural network optimized by the Mirage Search Optimization algorithm. First, a three-phase two-winding transformer simulation model is established in PSCAD to generate samples under different DC magnetic bias conditions, and the bias degree is divided into four categories: normal, slight, middle, and heavy. Neutral-point DC current and excitation-current total harmonic distortion are selected as excitation-response input features, and their sufficiency is verified through feature relevance analysis and ablation experiments. The MSO algorithm is used to optimize the smoothing factor of PNN, thereby improving the classification boundary and generalization ability of the model. Experimental results show that the proposed MSO-PNN model achieves a mean accuracy of 98.15% over 30 independent runs, with the best accuracy reaching 99.01%, outperforming other optimized PNN models. Under simulated Gaussian-noise conditions, the model maintains an accuracy of 96.4% at SNR = 15 dB and 91.0% at SNR = 10 dB. These results indicate that the proposed method provides an accurate and robust diagnostic framework for transformer DC magnetic bias degree classification.
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The reliability of deep learning models in neonatal seizure detection depends on rigorous experimental design and transparent reporting of performance. In this systematic review, 48 peer-reviewed studies and 145 distinct study observations of EEG-based neonatal seizure detection were examined to assess how data partitioning (validation) strategies, open data (code), and data leakage influence reported performance. We analyzed the extracted data using Fisher’s exact test, chi-square test, and partial least squares structural equation modeling (PLS-SEM). Of the 48 studies included, public datasets were used in 87.69% of papers, but only 22.9% reported code availability. While studies with low risk of data leakage are common, we found that 16.7% of papers or 31.7% of study observations exhibited a high risk of data leakage. The PLS-SEM results and chi-square test align well, supporting that rigorous data partitioning reduces leakage and that leakage adversely affects performance. Data Partitioning (Validation) strategy emerged as a strong and statistically significant predictor of data leakage (p < 0.001, R2 = 0.598), explaining 59.8% of its variance. Data leakage has a statistically significant effect on reported model performance (p = 0.005, R2 = 0.202). Still, they account for only about 20.2% of the variation in performance, indicating other factors might play a substantial role, such as dataset size, class balance, model architecture, and preprocessing. Overall, the evidence suggests a generalizable relationship between leakage and performance, though caution is warranted due to variability in accuracy outcomes across studies. These findings highlight the importance of methodological standards to reduce data leakage and promote transparency in neonatal EEG seizure detection models. The online version contains supplementary material available at 10.1186/s13040-025-00516-y.
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Strong electron-lattice coupling in 1T-MX2 (M = Nb, Ta; X = S, Se) enables diverse quantum phenomena. Using first-principles calculations, we reveal temperature-dependent orbital textures of midgap states in monolayer 1T-NbSe2 with a star-of-David charge-density-wave superstructure. A mere 0.1% thermal lattice expansion drives a sharp nonmagnetic-to-ferromagnetic transition. In the ferromagnetic phase, midgap states localize at the supercell center, while in the nonmagnetic phase, high-energy Rydberg-like states generate weak in-gap signals and characteristic six-petal orbital patterns. These findings resolve long-standing theory-experiment discrepancies and establish Rydberg fingerprinting as a method to probe high-energy electronic structures via low-bias scanning tunneling spectroscopy, offering new insights into coupled electronic and magnetic degrees of freedom in two-dimensional transition metal dichalcogenides.